Climate doi: 10.3390/cli12040047
Authors: Todd A. Eisenstadt Sk Tawfique M. Haque Michael A. Toman Matthew Wright
After decades of presuming that climate adaptation is a private good benefitting only those receiving resources to reduce individual climate risks, respondents in a survey experiment among the climate-vulnerable in Bangladesh chose less-particularistic adaptation projects than “electoral connection” disaster relief theories predict and more “short-sighted” projects than international diplomats anticipate. This article reports on the experiment, which asked a representative national sample of Bangladeshis whether they favor spending funds on short-term particularistic solutions (disaster relief stockpiles), medium-term inclusionary and non-excludable solutions (ocean embankments), or long-term, public goods solutions (the development of flood-resistant rice seeds). More respondents chose “middle ground” embankment spending, and a statistically significant change in respondent propensities was tied to their lived experience with climate vulnerability rather than electoral incentives. The logic of their choices contradicts existing explanations, implying that a reconsideration of vulnerable community preferences, and how to address them, may be needed.
]]>Climate doi: 10.3390/cli12030046
Authors: Mokhele E. Moeletsi Mitsuru Tsubo
Dryland farming is at the center of increasing pressure to produce more food for the growing population in an environment that is highly variable and with high expectations for the standard of their production systems. While there is mounting pressure for increased productivity, the responsibility to protect the environment and diminish the agricultural sector’s carbon footprint is receiving growing emphasis. Achieving these two goals calls for a consolidated effort to ensure that the scientific community and service providers partner with farmers to create a sustainable food production system that does not harm the environment. In this paper, we studied the nature of the services present in the market and identified ways that could be used to improve the climate services available to the agricultural sector. Important factors that could increase the usability of climate services include coproduction, context-specific information, innovation, demand-driven services, timeliness of services, highly applicable information, provision of services in the correct format, services that increase user experience, specificity of services to a locale, and services that are easily accessible.
]]>Climate doi: 10.3390/cli12030045
Authors: Eldar Kurbanov Oleg Vorobev Sergei Lezhnin Denis Dergunov Jinliang Wang Jinming Sha Aleksandr Gubaev Ludmila Tarasova Yibo Wang
Wildfires are important natural drivers of forest stands dynamics, strongly affecting their natural regeneration and providing important ecosystem services. This paper presents a comprehensive analysis of spatiotemporal burnt area (BA) patterns in the Middle Volga region of the Russian Federation from 2000 to 2022, using remote sensing time series data and considering the influence of climatic factors on forest fires. To assess the temporal trends, the Mann–Kendall nonparametric statistical test and Theil–Sen’s slope estimator were applied using the LandTrendr algorithm on the Google Earth Platform (GEE). The accuracy assessment revealed a high overall accuracy (>84%) and F-score value (>82%) for forest burnt area detection, evaluated against 581 reference test sites. The results indicate that fire occurrences in the region were predominantly irregular, with the highest frequency recorded as 7.3 over the 22-year period. The total forest BA was estimated to be around 280 thousand hectares, accounting for 1.7% of the land surface area or 4.0% of the total forested area in the Middle Volga region. Coniferous forest stands were found to be the most fire-prone ecosystems, contributing to 59.0% of the total BA, while deciduous stands accounted for 25.1%. Insignificant fire occurrences were observed in young forests and shrub lands. On a seasonal scale, temperature was found to have a greater impact on BA compared with precipitation and wind speed.
]]>Climate doi: 10.3390/cli12030044
Authors: Sehouevi Mawuton David Agoungbome Marie-Claire ten Veldhuis Nick van de Giesen
Climate variability poses great challenges to food security in West Africa, a region heavily dependent on rainfall for farming. Identifying sowing strategies that minimize yield losses for farmers in the region is crucial to securing their livelihood. In this paper, we investigate three sowing strategies to assess their ability to identify safe sowing windows for smallholder farmers in the Sudanian region of West Africa (WA) in the context of a changing climate. The GIS version of the FAO crop model, AquaCrop-GIS, is used to simulate the yield response of maize (Zea mays L.) to varying sowing dates throughout the rainy season across WA. Based on an average of 38 years of data per grid cell, we identify safe sowing windows across the Sudanian region that secure at least 90% of maximal yield. We find that current sowing strategies, based on minimum thresholds for rainfall accumulated over a period that are widely applied in the region, carry a higher risk of yield failure, especially at the beginning of the rainy season. This analysis shows that delaying sowing for a month to mid-June in the central region (east of Lon 8.5°W), and to early August in the semi-arid areas is a safer strategy that ensures optimal yields. A comparison between the periods 1982–1991 and 1992–2019 shows a negative shift for LO10 mm and LO20 mm, suggesting a wetter regime compared to the dry periods of the 1970s and 1980s. On the contrary, we observe a positive shift in the safe window strategy, highlighting the need for precautions due to erratic rainfall at the beginning of the season. The precipitation-based strategies hold a high risk, while the safe sowing window strategy, easily accessible to smallholder farmers, is more fitting, given the current climate.
]]>Climate doi: 10.3390/cli12030043
Authors: Ana Letícia Melo dos Santos Weber Andrade Gonçalves Lara de Melo Barbosa Andrade Daniele Tôrres Rodrigues Flávia Ferreira Batista Gizelly Cardoso Lima Cláudio Moisés Santos e Silva
Various indices of climate variability and extremes are extensively employed to characterize potential effects of climate change. Particularly, the semiarid region of Brazil is influenced by adverse effects of these changes, especially in terms of precipitation. In this context, the main objective of the present study was to characterize the regional trends of extreme precipitation indices in the semiarid region of Brazil (SAB), using daily precipitation data from the IMERG V06 product, spanning the period from 1 January 2001 to 31 December 2020. Twelve extreme precipitation indices were considered, which were estimated annually, and their spatial and temporal trends were subsequently analyzed using the nonparametric Mann–Kendall test and Sen’s slope. The analysis revealed that the peripheral areas of the SAB, especially in the northwest and extreme south regions, exhibited higher intensity and frequency of extreme precipitation events compared to the central portion of the area. However, a negative trend in event intensity was noted in the north, while positive trends were identified in the south. The frequency of extreme events showed a predominance of negative trends across most of the region, with an increase in consecutive dry days particularly throughout the western SAB. The average total precipitation index was above 1000 mm in the north of the SAB, whereas in the central region, the precipitation averages were predominantly below 600 mm, with rainfall intensity values ranging between 6 and 10 mm/day. Over the span of 20 years, the region underwent an average of 40 consecutive dry days in certain localities. A negative trend was observed in most of the indices, indicating a reduction in precipitation intensity in future decades, with variations in some indices. The dry years observed towards the end of the analyzed period likely contributed to the observed negative trends in the majority of extreme precipitation indices. Such trends directly impact the intensity and frequency of extreme weather events in the SAB. The study is important for highlighting and considering the impacts of changes in precipitation extremes in the semiarid region of Brazil. Based on the obtained results, we advocate the implementation of public policies to address future challenges, such as incorporating adaptations in water resource management, sustainable agricultural practices, and planning for urban and rural areas.
]]>Climate doi: 10.3390/cli12030042
Authors: Tiago Bigolin Edson Talamini
Brazil is one of the main producing and exporting countries of corn and soybean and a continental country with climatic diversity that allows the cultivation of these crops in various agricultural systems. Double cropping is a widely adopted system throughout the national territory, where it is possible to cultivate soybeans at the beginning of the growing season, followed by corn in succession, in the same growing season. The present study aims to systematize the scientific knowledge about the impacts of future climate change scenarios on yield and on the double-cropping system of soybean + corn in Brazil. Systematic review procedures were adopted. The soybean yield is projected to increase in all regions of Brazil under all climate scenarios. Corn yields under future climate scenarios are projected to decline, with the subtropical climate region being less affected than the northern regions. The double-cropping systems of soybean + corn tend to present increasing climate risks in tropical climate regions. Climate change scenarios point to a delay in the start of the rainy season that will delay the sowing of soybeans, consequently delaying the sowing of corn in succession, resulting in fewer rainy days to complete its cycle.
]]>Climate doi: 10.3390/cli12030041
Authors: Rohit Mondal Sabrina Bresciani Francesca Rizzo
Cities are taking action to respond to climate change by designing and implementing sustainable solutions which provide benefits and challenges to citizens. Measuring the progress and effects of such actions at the urban level, beyond mere greenhouse gas (GHG) emissions quantification, is still an emerging research area. Based on data from the 40 European cities belonging to 20 pilot city programmes within the EU-funded NetZeroCities (NZC) project, cities’ selections and preferences for indicators for assessing their climate actions are analysed in relation to the Sustainable Development Goals (SDGs). This study provides bottom-up evidence of cities’ selection of non-GHG indicators through different levers of change, including participatory governance and social innovation, for assessing progress and the co-benefits of actions toward climate neutrality taken at the urban level. The resulting list of indicators, classified according to the SDGs, provides evidence of cities’ priorities and can be utilised by cities’ climate transition teams and also by researchers, as it highlights gaps and opportunities compared to extant literature.
]]>Climate doi: 10.3390/cli12030040
Authors: Mobin Hossain Shohan Mohammad Abu Baker Siddique Balaram Mahalder Mohammad Mahfujul Haque Chayon Goswami Md. Borhan Uddin Ahmed Mohammad Ashraful Alam Md. Abul Bashar Yahia Mahmud Mahamudul Alam Chowdhury Md. Mahmudul Hasan A. K. Shakur Ahammad
An integrated multivariate approach was applied to gain a deeper understanding of the feeding biology of hilsa shad, Tenualosa ilisha, collected from six different aquatic habitats across Bangladesh. This approach involved linking climatic factors, ecological factors, plankton abundance in water, reproductive traits, and plankton ingestion data. Climatic data were obtained from the National Oceanic and Atmospheric Administration (NOAA) and Climate Data Online (CDO) databases on a monthly basis. Water quality parameters were observed on-site at various sampling sites. Plankton data from water bodies and hilsa guts were collected monthly from the study areas and analyzed in the laboratory. The results obtained were averaged for each month. The correlation tests, multivariate approaches, cluster analyses, and regression analyses revealed that the gonadosomatic index was primarily influenced by climatic factors, the abundance of ingested gut plankton, and heir compositions. The analysis of selectivity indices confirmed that plankton preferentially ingested selective taxa. Thirteen plankton groups were identified in the water column of six different hilsa habitats. The dominant phytoplankton groups were Bacillariophyceae (34–53%), Chlorophyceae (31–50%), Cyanophyceae (4–8%), and Euglenophyceae (1–3%). Additionally, Copepoda, Rotifera, and Cladocera were the most numerous zooplankton groups. Hilsa shad primarily consumed Bacillariophyceae (38–57%), Chlorophyceae (35–53%), and Cyanophyceae (4–6%). However, they also exhibited selective ingestion of higher quantities of Bacillariophyceae and Chlorophyceae to fulfill specific and unique metabolic needs. Cluster analysis revealed the variability of phytoplankton and zooplankton abundance in water and gut in relation to diverse locations. Combining all the datasets, a principal component analysis (PCA) was applied. The first two principal components explained more than 54% of the variability. The first component explained the association between the gonadosomatic index and eco-climatic factors, while the second component extracted the cluster of ingested gut plankton in relation to salinity and pH. Pearson’s correlations and linear regression analyses showed that the number of gut plankton had a positive influence on the gonadosomatic index (GSI). Finally, the outcomes from these extensive datasets have provided a better understanding of the selective feeding behavior and the influence of feeding biology on the gonadal maturation of T. ilisha. This understanding is likely to be useful for maintaining and improving the growth and productivity of the existing production systems for this transboundary species.
]]>Climate doi: 10.3390/cli12030039
Authors: Jürg Luterbacher Rob Allan Clive Wilkinson Ed Hawkins Praveen Teleti Andrew Lorrey Stefan Brönnimann Peer Hechler Kondylia Velikou Elena Xoplaki
The rescue, digitization, quality control, preservation, and utilization of long and high quality meteorological and climate records, particularly related to historical marine data, are crucial for advancing our understanding of the Earth’s climate system. In combination with land and air measurements, historical marine records serve as foundational pillars in linking present and past weather and climate information, offering essential insights into natural climate variability, extreme events in marine areas, baseline data for assessing current changes, and inputs for enhancing predictive climate models and reanalyses. This paper provides an overview of rescue activities covering marine weather data over the past centuries and presents and highlights several ongoing projects across the world and how the data are used in an integrative and international framework. Current and future continuous efforts in data rescue, digitization, quality control, and the development of temporally high-resolution meteorological and climatological observations from oceans, will greatly help to further complete our understanding and knowledge of the Earth’s climate system, including extremes, as well as improve the quality of reanalysis.
]]>Climate doi: 10.3390/cli12030038
Authors: Hadi Allafta Christian Opp
Carbon dioxide (CO2) emissions are a major cause of climate change. However, CO2 emissions data for 178 countries from 1960 to 2018 revealed inequality in global CO2 emissions. For example, we found that 50% of the world’s population (ca. 3.75 billion people) was responsible for just 8.9% of the global cumulative carbon emissions. These people are concentrated in low- and middle-income countries. Conversely, 10% of the world’s population (ca. 757 million people), concentrated in high-income countries, were responsible for 46.8% of the global emissions. Furthermore, the literature review disclosed evolution of CO2 emission inequalities within countries. A significant (p < 0.001) negative (r2 = −0.52) correlation was detected between carbon emissions and climate change impacts on national incomes. Such correlation indicated that countries most likely to experience the greatest effects of climate change are also those who make the smallest contributions to its underlying causes. Similar disparities were observed within countries where low-income groups who make the smallest contributions to climate change are subjected to its worst implications. Evaluations of the data from the literature showed that migration could be the result of climate change, though such migration does not happen in isolation. In other words, this kind of migration is frequently linked to other issues such as the fragility and lack of adaptability of the communities. Furthermore, reviews showed that climate change catalyzes instability and conflict. On the other hand, conflict damages the environment and climate in multiple ways. Therefore, it is necessary to collaborate to resolve these two issues concurrently.
]]>Climate doi: 10.3390/cli12030037
Authors: Laksmita Dwi Hersaputri Rudolf Yeganyan Carla Cannone Fernando Plazas-Niño Simone Osei-Owusu Yiannis Kountouris Mark Howells
Indonesia’s commitment to the Paris Agreement and its Nationally Determined Contribution (NDC) is not adequately reflected in the significant CO2 emissions from fossil-fuel-intensive energy sectors, despite the enormous potential of renewable energy sources in the country. The ongoing coal regime has led to electricity oversupply and air pollution problems. Despite the huge challenges for Indonesia, a just energy transition away from fossil fuel is crucial. This study aims to explore the ideal energy mix and key emission reduction pathway in Indonesia in achieving a just energy transition using the least-cost optimisation energy modelling tool OSeMOSYS. Six scenarios are modelled over the period 2015–2050 including coal phase-out, NDC, the Just Energy Transition Partnership (JETP), and carbon tax implementation. The results highlight that solar power, geothermal power, and hydropower are the alternatives for coal decommissioning. Despite the large-scale investment in renewable energy under the NDC and JETP scenarios, emissions could be reduced by 55% and 52%, respectively, by 2050. Moreover, Indonesia’s current carbon tax rate will not lead to a significant emission reduction. Three recommended policies include (1) accelerating CFPP retirement; (2) imposing an aggressive carbon tax rate; (3) prioritising investment in solar technologies.
]]>Climate doi: 10.3390/cli12030036
Authors: Ioannis Moisoglou Aglaia Katsiroumpa Antigoni Kolisiati Evangelia Meimeti Ioanna Prasini Maria Tsiachri Olympia Konstantakopoulou Parisis Gallos Petros Galanis
Heat waves are a significant consequence of climate change, threatening public health by increasing morbidity and mortality. The aim of this study was to estimate individuals’ knowledge, attitudes and practice related to heat waves. We conducted an exploratory cross-sectional study in Greece during September 2023. We employed a convenience sample of 1055 participants. We used the heat wave knowledge, awareness, practice and behavior scale (HWKAPBS) to measure our outcome. We measured several socio-demographic variables, such as gender, age and educational level, as potential determinants. Mean scores for the knowledge, awareness, practice and behavior factors were 12.5, 22.7, 22.2 and 12.1, respectively. Females had higher scores for the four factors compared with males. We found a positive relationship between self-perceived health status and awareness, practice and behavior concerning heat waves. Similarly, we identified a positive relationship between self-perceived financial status, and awareness and behavior concerning heat waves. Increased age was associated with an increased practice score, while increased educational level was associated with an increased knowledge score. Additionally, the behavior score was higher among participants in urban areas than those in rural areas. We found statistically significant positive correlations between the four factors. Levels of knowledge, awareness, practice and behavior concerning heat waves were high in our sample. Several socio-demographic variables affect participants’ knowledge, awareness, practice and behavior concerning heat waves.
]]>Climate doi: 10.3390/cli12030035
Authors: Jianhui Bai Xiaowei Wan Erhan Arslan Xuemei Zong
On the analysis of solar radiation and meteorological variables measured in Ankara province in Türkiye from 2017 to 2018, an empirical model of global solar radiation was developed. The global solar radiation at the ground and at the top of the atmosphere (TOA) was calculated and in good agreement with the observations. This model was applied to compute the losses of global solar radiation in the atmosphere and the contributions by atmospheric absorbing and scattering substances. The loss of global solar radiation in the atmosphere was dominated by the absorbing substances. The sensitivity test showed that global solar radiation was more sensitive to changes in scattering (described by a scattering factor S/G, S and G are diffuse and global solar radiation, respectively) than to changes in absorption. This empirical model was applied to calculate the albedos at the TOA and the surface. In 2017, 2018, and 2019, the computed albedos were 28.8%, 27.8%, and 28.2% at the TOA and 21.6%, 22.1%, and 21.9% at the surface, which were in reasonable agreement with satellite retrievals. The empirical model is a useful tool for studying global solar radiation and the multiple interactions between solar energy and atmospheric substances. The comparisons of global solar radiation and its loss in the atmosphere, as well as meteorological parameters, were made at some representative sites on the Earth. Some internal relationships (between G and the absorbing and scattering substances, air temperature and atmospheric substances, air temperature increase and latitude, etc.) were found. Thus, it is suggested to thoroughly study solar radiation, atmospheric substances, and climate change as a whole system and reduce the direct emissions of all atmospheric substances and, subsequently, secondary products (e.g., CO2 and non-CO2) in the atmosphere for the achievement of slowing down climate warming.
]]>Climate doi: 10.3390/cli12030034
Authors: Alina Bărbulescu
In recent decades, an increase in the earth’s atmospheric temperature has been noticed due to the augmentation of the volume of gases with the greenhouse effect (GHG) released into the atmosphere. To reduce this effect, the European Union’s directives indicate the action directions for reducing these emissions, among which carbon dioxide (CO2) recorded the highest amount. In this context, the article analyzes the CO2 series reported in 1990–2021 by 30 European countries. The Kruskal-Wallis test rejected the hypothesis that the series comes from the same underlying distribution. The Anderson-Darling test rejected the normality hypothesis for seven series out of thirty, and Sen’s procedure found a decreasing trend slope only for 17 series. ARIMA models have been built for all individual series. Grouping the series (by the k-means and hierarchical clustering) provided the base for building the Regional series (RegS), which describes the CO2 pollution evolution over Europe. The advantage of this approach is to provide the synthetic image of the regional evolution of the CO2 emission volume (mt), incorporating information from 30 series (one for each country) in only one—RegS. It is also shown that selecting the number of clusters involved in building RegS and assessing their stability is essential for the model’s goodness of fit.
]]>Climate doi: 10.3390/cli12030033
Authors: Mashford Zenda Michael Rudolph
This systematic review identified the prevalence, effectiveness, and potential benefits of agroecology strategies in promoting sustainable agriculture practices implemented by smallholder crop farmers in South Africa. The review carried out a comprehensive literature search across various academic databases, including PubMed, Scopus, and Web of science. The relevant studies were screened and selected based on predetermined inclusion criteria where a total of 262 articles were extracted and reduced to 30 articles for this systematic review. Data were extracted and synthesised to classify patterns and trends in the adoption of agroecology elements. The results obtained from the review of this study highlights the identification of specific strategies such as indigenous crop varieties, conservation agriculture, intercropping, agroforestry, drought-tolerant crop varieties, and water management strategies. These outcomes demonstrated insights into the prevalence of different strategies applied by smallholder crop farmers in South Africa. Furthermore, the review determined the reported benefits, such as increased crop resilience, improved soil fertility, and enhanced water use efficiency. These benefits were assessed on the available evidence from the selected studies. This review contributes to a better understanding of agroecology practices in South African. The results can inform policymakers, researchers, and farmers in developing appropriate strategies to enhance sustainable agricultural practices.
]]>Climate doi: 10.3390/cli12030032
Authors: Sameeha Malikah Stephanie Avila Gabriella Garcia Tarendra Lakhankar
This study analyzes daily temperature and precipitation data collected from 44 weather stations throughout New York, New Jersey, and Connecticut to assess and quantify the historical climatic changes within these states. The study conducts a detailed examination of spatial and temporal trends, focusing on specific stations that best represent the climatic diversity of each area. A critical analysis aspect involves comparing temperature trends in urban and suburban areas, mainly focusing on New York City. The findings reveal a significant upward increasing trend in average temperatures across all seasons, with urban areas, especially NYC, exhibiting the most marked increases. This trend is notably sharp in the spring, reflecting climate change’s escalating influence. The study also observes an increase in the annual average temperatures and a concurrent decrease in the variability of temperature ranges, suggesting a stabilization of temperature fluctuations over time. Also, we identified a notable increase in heat wave frequency, more so in urban locales than in their suburban counterparts. Analysis of precipitation patterns, particularly in NYC, reveals a decline in snowfall days, consistent with the general warming trend. The results demonstrate significant trends in seasonal average temperatures, a decrease in the variability of temperatures, and a rise in heat wave occurrences, with urban areas typically experiencing warmer conditions. This comprehensive study highlights the need for a more in-depth analysis of spatial precipitation trends. It underscores the importance of continued research in understanding the multifaceted impacts of climate change, particularly in differentiating urban and rural experiences.
]]>Climate doi: 10.3390/cli12030031
Authors: Roberto Ariel Abeldaño Zuñiga Gabriela Narcizo de Lima José Carlos Suarez-Herrera
Background: During 2020 and 2021, over 50.2 million individuals were forced to leave their homes to escape the impacts of climate-related disasters, unable to practice social isolation or self-quarantine. A considerable proportion of them reside in densely populated areas with a lack of basic services such as water and sanitation and limited access to essential healthcare. This study aimed to estimate the internal displacements during 2020 and 2021 due to climate-related events, and review the evidence for proposing policy recommendations. Methods: Data from the Internal Displacement Monitoring Centre were used for assessing internal displacement by disasters during 2020 and 2021. In addition, the authors conducted a bibliographic review to analyse the responses to internal displacements in climate-related disasters. Results: There were 883 severe storms and 1567 flood events resulting in 50.2 million internal displacements globally. Through the documents reviewed, the legal framework, the vulnerabilities and current challenges of internally displaced persons, and the response policy recommendations were analysed. Conclusions: The increased awareness of displacement and migration, particularly driven by climate-related factors, aligns with international agreements emphasising coordinated action. This recognition becomes even more critical in the context of the convergence of climate-related displacements and the potential for future pandemics.
]]>Climate doi: 10.3390/cli12030030
Authors: Iago Turba Costa Cassio Arthur Wollmann Luana Writzl Amanda Comassetto Iensse Aline Nunes da Silva Otavio de Freitas Baumhardt João Paulo Assis Gobo Salman Shooshtarian Andreas Matzarakis
The exponential growth of urban populations and city infrastructure globally presents distinct patterns, impacting climate change forecasts and urban climates. This study conducts a systematic review of the literature focusing on human thermal comfort (HTC) in outdoor urban environments. The findings indicate a significant surge in studies exploring HTC in open urban spaces in recent decades. While historically centered on Northern Hemisphere cities, there is a recent shift, with discussions extending to various metropolitan contexts in the Southern Hemisphere. Commonly employed urban categorization systems include Sky View Factor (SVF), Height × Width (H/W) ratio, and the emerging Local Climate Zones (LCZs), facilitating the characterization of urban areas and their usage. Various thermal indices, like Physiological Equivalent Temperature (PET), Predicted Mean Vote (PMV), Universal Thermal Climate Index (UTCI), and Standard Effective Temperature (SET), are frequently utilized in evaluating external HTC in metropolitan areas. These indices have undergone validation in the literature, establishing their reliability and applicability.
]]>Climate doi: 10.3390/cli12030029
Authors: Marcely Sondermann Sin Chan Chou Renata Genova Martins Lucas Costa Amaro Rafael de Oliveira Gomes
Southern Brazil is a region strongly influenced by the occurrence of extratropical cyclones. Some of them go through a rapid and intense deepening and are known as explosive cyclones. These cyclones are associated with severe weather conditions such as heavy rainfall, strong winds, and lightning, leading to various natural disasters and causing socioeconomic losses. This study investigated the interaction between atmospheric and oceanic conditions that contributed to the rapid intensification of the cyclone that occurred near the coast of South Brazil from 29 June to 3 July 2020, causing significant havoc. Hourly atmospheric and oceanic data from the ERA5 reanalysis were employed in this analysis. The results showed that warm air and moisture transportation were key contributors to these phenomena. In addition, the interaction between the jet stream and the cyclone’s movement played a crucial role in cyclone formation and intensification. Positive sea surface temperature anomalies also fueled the cyclone’s intensification. These anomalies increased the surface heat fluxes, making the atmosphere more unstable and promoting a strong upward motion. Due to the strong winds and the heavy rainfall, the explosive cyclone caused substantial impacts on the power services, resulting in widespread power outages, damaged infrastructure, and interruptions in energy distribution. This work describes in detail the cyclone development and intensification and aims at the understanding of these storms, which is crucial for minimizing their aftermaths, especially on energy distribution.
]]>Climate doi: 10.3390/cli12030028
Authors: Graziela T. Tejas Dorisvalder D. Nunes Reginaldo M. S. Souza Carlos A. S. Querino Marlon R. Faria Daiana C. B. Floresta Emerson Galvani Michel Watanabe João P. A. Gobo
This paper aims to analyze the weather conditions in Porto Velho (Rondonia, Brazil, Western Amazon) and the influence of air masses on the climatic elements between 2017 and 2018, using rhythmic analysis. Climatic data were obtained through the official weather station, tabulated and statistically organized, and processed in R Studio programming language. The monitoring of air masses occurred through the synoptic charts of the Navy Hydrography Center. The results were analyzed by dry–rainy transition season, rainy season, wet–dry transition season, and dry season. Thus, the results point out that the Tropical Continental mass (mTc) acted up to 62.9%, responsible for the low precipitation index in October 2017. Although the mass has characteristics of warm and unstable weather, it is even lower than the action of the mEc. In January 2018, there was an 85.5% prevalence of the Continental Equatorial Mass (mEc), added to the action of the South Atlantic Convergence Zone (ZCAS), which contributed to an accumulated rainfall of 443 mm/month. In April 2018, the mEC acted with 56.7%, reaching 35.5% in August. Another highlight was the performance of the Tropical Atlantic mass (mTa) (27.4%) and mTc (19.4%), both of which had a crucial role in the dry season, followed by the Polar Atlantic mass (mPa) (17.7%), that contributed to the phenomenon of “coldness” in the region. Therefore, the mEc is extremely important in the control of the relative humidity of the air and the precipitations, while the mTc is a dissipator of winds that, at times, inhibits the performance of the mEc.
]]>Climate doi: 10.3390/cli12020027
Authors: Renalda El-Samra Abeer Haddad Ibrahim Alameddine Elie Bou-Zeid Mutasem El-Fadel
Climatic statistical downscaling in arid and topographically complex river basins remains relatively lacking. To address this gap, climatic variables derived from a global climate model (GCM) ensemble were downscaled from a grid resolution of 2.5° × 2.5° down to the station level. For this purpose, a combination of multiple linear and logistic regressions was developed, calibrated and validated with regard to their predictions of monthly precipitation and daily temperature in the Jordan River Basin. Seasonal standardized predictors were selected using a backward stepwise regression. The validated models were used to examine future scenarios based on GCM simulations under two Representative Concentration Pathways (RCP4.5 and RCP8.5) for the period 2006–2050. The results showed a cumulative near-surface air temperature increase of 1.54 °C and 2.11 °C and a cumulative precipitation decrease of 100 mm and 135 mm under the RCP4.5 and RCP8.5, respectively, by 2050. This pattern will inevitably add stress to water resources, increasing management challenges in the semi-arid to arid regions of the basin. Moreover, the current application highlights the potential of adopting regression-based models to downscale GCM predictions and inform future water resources management in poorly monitored arid regions at the river basin scale.
]]>Climate doi: 10.3390/cli12020026
Authors: Alec Feinberg
Solar geoengineering (SG) solutions have many advantages compared to the difficulty of carbon dioxide removal (CDR): SG produces fast results, is shown here to have much higher efficiency than CDR, is not related to fossil fuel legislation, reduces the GHG effect including water vapor, and is something we all can participate in by brightening the Earth with cool roofs and roads. SG requirements detailed previously to mitigate global warming (GW) have been concerning primarily because of overwhelming goals and climate circulation issues. In this paper, annual solar geoengineering (ASG) equations and estimated requirements for yearly solar radiation modification (SRM) of areas are provided along with the advantages of annual solar geoengineering (ASG) to mitigate yearly global warming temperature increases. The ASG albedo area modification requirements found here are generally 50 to potentially more than 150 times less compared to the challenge of full SG GW albedo mitigation, reducing circulation concerns and increasing feasibility. These reductions are applied to L1 space sunshading, Earth brightening, and stratosphere aerosol injection (SAI) SRM annual area requirements. However, SAI coverage compared to other methods will have higher yearly increasing maintenance costs in the annual approach. Results also show that because ASG Earth albedo brightening area requirements are much smaller than those needed for full mitigation, there are concerns that worldwide negative SG would interfere with making positive advances for several reasons. That is, negative SG currently dominates yearly practices with the application of dark asphalt roads, roofs, and building sides. This issue is discussed.
]]>Climate doi: 10.3390/cli12020025
Authors: Jong-Gyu Kim
This study aimed to investigate the outbreaks and characteristics of Vibrio parahaemolyticus food poisoning in the Republic of Korea and the impact of climatic factors on the food poisoning occurrence. All data were obtained from the official statistics of the Republic of Korea (2002 to 2017). A trend analysis, Pearson’s correlation analysis, and regression analysis were used to determine the relationship between the outbreaks of V. parahaemolyticus food poisoning and climatic factors. During the study period, the number of outbreaks of V. parahaemolyticus food poisoning ranked third among bacterial food poisoning. The food poisoning incidences of V. parahaemolyticus occurred mostly from July to September. The average temperature, maximum and minimum temperatures, precipitation, number of days with rainfall, and humidity showed a significant positive correlation with the number of outbreaks of V. parahaemolyticus food poisoning (p < 0.001), but daytime hours showed a negative correlation (p < 0.01). The data further indicated that minimum temperature was the most influential variable on the outbreaks of food poisoning (p < 0.01). These results indicate that the outbreaks of V. parahaemolyticus food poisoning in the Republic of Korea are associated with climatic factors, suggesting that these incidences may have been impacted by climate change, especially due to warming around the Korean peninsula.
]]>Climate doi: 10.3390/cli12020024
Authors: Ishfaq Hussain Malik James D. Ford
Climate change adaptation is a critical response to the challenges posed by climate change and is important for building resilience. Progress in adaptation efforts has been made globally, nationally, and locally through international agreements, national plans, and community-based initiatives. However, significant gaps exist in knowledge, capacity, and finance. The Adaptation Gap Report 2023, published by the United Nations Environment Programme (UNEP), examines the status of climate change adaptation efforts globally. The report highlights the widening adaptation finance gap and the deepening climate crisis. We analyse the key themes of the report and incorporate an analysis of the wider literature and insights from COP28 to substantiate key points and identify gaps where more work is needed to develop an understanding of climate change adaptation. This paper focuses on the underfinanced and underprepared state of global climate change adaptation efforts, the widening adaptation finance gap, slow progress in adaptation, gender equality and social inclusion issues, and challenges in addressing loss and damage. We provide a way forward for climate change adaptation and offer recommendations for future actions.
]]>Climate doi: 10.3390/cli12020023
Authors: Mohamed Saad Suliman Hooman Farzaneh Eric Zusman Alphonce Ngila Mulumba Puji Lestari Didin Agustian Permadi Nandakumar Janardhanan
Quantifying the co-benefits of renewable energy investments can aid policymakers in identifying technologies capable of generating significant social, economic, and environmental benefits to effectively offset mitigation costs. Although there has been a growing body of work evaluating co-benefits, few studies have compared the potential co-benefits of several technologies across different regions in key countries. This study fills this gap by formulating a new modeling structure to assess the environmental–health–economic co-benefits of hybrid renewable energy systems (HRESs) in different parts of Indonesia. The proposed model is unique in that it incorporates various techno-economic activities to assess air quality, health, and economic benefits and then presents results as part of a cost–benefit analysis. From the intervention scenario, the modeling results show that installing 0.5 GW grid-connected solar PV, 100 MW of wind turbines, and a 100 MW biomass generator to cover a total of 1.64 million residential load units in the Bali province can avoid GHGs, PM2.5, disability-adjusted life years (DALYs), and provide health savings of 1.73 Mt/y, 289.02 t/y, 1648, and 6.16 million USD/y, respectively. In addition, it shows that the payback period is enhanced by one year, while the net present value is increased by 28%. In Jakarta, a 3 GW solar PV plant and a 100 MW biomass generator that supply 5.8 million residential load units can deliver 32,490 averted DALYs and 652.81 million USD/y of health care savings. Nationally, the contribution of renewable energy to the electricity supply mix could grow from the 2020 baseline of 18.85% to 26.93%, reducing dependence on oil and coal contribution by 5.32%.
]]>Climate doi: 10.3390/cli12020022
Authors: Jakeline Baratto Paulo Miguel de Bodas Terassi Nádia Gilma de Beserra de Lima Emerson Galvani
The objective of this research is to select the best orbital sensor for rainfall estimates (monthly and annual scales) and to analyze the frequency and magnitude of extreme rainfall events and their trends and disruptions based on the use of satellite rainfall product data for the Cananeia–Iguape Coastal System (CICS). Data from four satellite rainfall products were used to identify the correspondence with seven points on the surface of the study area. Statistical metrics were used to identify the best satellite rainfall product. After identifying the sensor with the best performance in estimating orbital precipitation, extreme events were identified by the Standardized Precipitation Index (SPI) on a one-month (SPI-1), three-month (SPI-3), and twelve-month (SPI-12) scale. Trend and rupture detection in the time series were performed using different statistical techniques (Mann–Kendall, Pettitt, Standard Normal Homogeneity Test, or Buishand test). Among the satellite rainfall products, CHIRPS had the best measurements for the analyzed points on the surface. The year 1983 was characterized as very rainy, also marked by the occurrence of El Niño, and was marked by the rupture of the rains at all points (IDs 1, 2, 3, 4, 5, 6, and 7) analyzed in the month of June. The decrease in monthly rainfall was more significant in the months of February (at points IDs 1, 2, 3, 5, and 7) and April (IDs 1, 3, 5, and 7). Decreased rainfall may cause CICS mangrove shrinkage. These results showed the importance of studying rainfall in an area with mangroves in order to understand the dynamics of vegetation in the face of climate change.
]]>Climate doi: 10.3390/cli12020021
Authors: Neil Macdonald Robert Dietz
A monthly composite rainfall record for the period 1786–present representative of Manchester, northwest England is presented. The 235-year record ranks as the second-longest instrumental rainfall record available for northern England, and the fifth-longest for the UK, and contributes to a growing network of long homogenous rainfall series. A composite record is constructed, extended, and homogenised, and the record is analysed in terms of annual and seasonal variability, with a focus on extreme wet/dry events. Three primary meteorological stations in Manchester, located within 2 km of one another, form the basis of the reconstruction, with other records identified for infilling and extension based on their longevity, continuity, and proximity to the primary stations. A linear regression analysis is applied to produce a continuous record, and adjustment factors are applied to ensure homogeneity. Record homogeneity is assessed via cross-comparison with long-term records from the region (Carlisle, Chatsworth House and HadNWEP), and the methods are applied to assess relative homogeneity include the double-mass curve and Standard Normal Homogeneity tests. The Manchester record is deemed to be homogenous overall but includes two periods of increased uncertainty: 1786–1819, comprising the earliest observations and greatest number of different stations, and 1883–1911, which encompasses multi-year and multi-decadal drought events of (1883–1885 and 1890–1910) as identified by other long-term meteorological studies. The analysis of the entire record reflects long-term rainfall variability with an increasing, although not significant, trend in annual rainfall observed. Seasonally, a significant increase in winter rainfall is exhibited, in keeping with patterns observed in other regional studies. Seasonal rainfall totals are found to be highly variable at the decadal timescale. Several well-documented extreme wet (e.g., autumn 2000) and dry (e.g., summer 1976) seasons are identified, including historic events (e.g., the floods of summer 1872 and drought of summer 1887) from the less-well documented eighteenth and nineteenth centuries.
]]>Climate doi: 10.3390/cli12020020
Authors: Elena A. Grigorieva John E. Walsh Vladimir A. Alexeev
Cold exposure remains a significant public health concern, particularly in the Arctic regions prone to extremely cold weather. While the physical health impacts of cold exposure are well documented, understanding the social vulnerability aspects is crucial for effective mitigation and policy development. This study investigates the multifaceted dimensions of social vulnerability in the face of cold temperatures across various communities in Alaska. Alaska, renowned for its extreme cold temperatures and harsh environmental conditions, poses unique challenges to its residents, particularly in the context of social vulnerability. Drawing on a combination of quantitative data analysis and qualitative insights, we examine the factors contributing to social vulnerability, including demographic, economic, geographic, and infrastructural elements, in terms of the Extremely Cold Social Vulnerability Index, for seven Public Health Regions in Alaska. The Universal Thermal Climate Index in two very cold categories (<−27 °C) was used to identify cold exposure. Factors such as income, housing quality, health status, and resilience of the population play crucial roles in determining an individual or community’s sensitivity to, and ability to cope with, cold temperatures. Our analysis reveals that social vulnerability in Alaska is not uniform but varies significantly among regions. The research findings highlight the importance of considering factors of both sensitivity and adaptivity in understanding and addressing social vulnerability, thereby informing the development of targeted strategies and policies to enhance the resilience of Alaskan communities. As cold temperatures are projected to continue to challenge the region, addressing social vulnerability is essential for ensuring the well-being and safety of Alaska’s diverse populations.
]]>Climate doi: 10.3390/cli12020019
Authors: Oye Ideki Anthony R. Lupo
This study used an ERA5 reanalysis SST dataset re-gridded to a common grid with a 0.25° × 0.25° spatial resolution (latitude × longitude) for the historical (1940–2014) and projected (2015–2100) periods. The SST simulation under the SSP5-8.5 scenario was carried out with outputs from eight General Circulation Models (GCMs). The bias-corrected dataset was developed using Empirical Quantile Mapping (EQM) for the historical (1940–2015) and future (2030–2100) periods while the CMIP6 model simulation was evaluated against the ERA5 monthly observed reanalysis data for temperatures over the Gulf of Guinea. Overall, the CMIP6 models’ future simulations in 2030–20100 based on the SSP5-8.5 scenario indicate that SSTs are projected, for the Gulf of Guinea, to increase by 4.61 °C, from 31 °C in the coast in 2030 to 35 °C in 2100, and 2.6 °C in the Western GOG (Sahel). The Linux-based Ncview, Ferret, and the CDO (Climate Data Operator) software packages were used to perform further data re-gridding and assess statistical functions concerning the data. In addition, ArcGIS was used to develop output maps for visualizing the spatial trends of the historical and future outputs of the GCM. The correlation coefficient (r) was used to evaluate the performance of the CMIP6 models, and the analysis showed ACCESS 0.1, CAMS CSM 0.2, CAN ESM 0.3, CMCC 0.3, and MCM 0.4, indicating that all models performed well in capturing the climatological patterns of the SSTs. The CMIP6 bias-corrected model simulations showed that increased SST warming over the GOG will be higher in the far period than the near-term climate scenario. This study affirms that the CMIP6 projections can be used for multiple assessments related to climate and hydrological impact studies and for the development of mitigation measures under a warming climate.
]]>Climate doi: 10.3390/cli12020018
Authors: Ioannis Charalampopoulos Fotoula Droulia
Climate change is already having a negative impact on many areas of human activity, affecting life globally. It is more urgent than ever to increase our adaptive capacity to respond to current and future climate change risks. Climate services refer to a specialized sector that encompasses both research and operational activities. This sector is primarily focused on interpreting and communicating knowledge and information about climate risks in a manner that is tailored to meet the specific needs of diverse user communities. Climate services offer a range of specialized outputs, including forecasts, assessments, and advisories, which enable users to make decisions that are based on an understanding of the potential impacts of climate change. The outputs of climate services are designed to help diverse user communities effectively manage risks and capitalize on opportunities arising from climate variability and change. An attempt is made to outline the fundamental elements of climate services and point out their contribution to various aspects of human activity, focusing on their essential role in the adaptability of the priority for action agricultural sector, which appears as considerably vulnerable to the change of considerably susceptible to climate conditions. This article is structured to answer basic questions about climate services in general and to show the specificities of climate services in the agricultural sector.
]]>Climate doi: 10.3390/cli12020017
Authors: Raquel de Rivas Amparo Vilches Olga Mayoral
This research is framed in Education for Sustainability, aimed at promoting the inclusion of the principles and values of Sustainability in education from a holistic perspective. The study focuses on finding out the concerns and knowledge of secondary school students from Valencia (Spain), who were surveyed during the academic years 2019–2020, 2020–2021 and 2021–2022 about Sustainability and Climate Change. Examining their conceptions, initial ideas, possible shortcomings, and conceptual errors is necessary to build a teaching itinerary with the purpose of adapting and reorienting educational practice to changing situations and different social contexts. The analysis, which is part of a broader research project, focuses on studying what secondary school students know (or rather, what they do not know or are unaware of) about Sustainability and Climate Change, examining their interests and concerns. Our experimental design is based on a wide-ranging questionnaire addressed to students that also promotes initial reflections. The results show that the participating students are concerned about socio-environmental problems, particularly about Climate Change. Nevertheless, they show a limited knowledge of Sustainability. This situation must encourage the involvement of the whole educational community to achieve a greater understanding of the planetary crisis through Education for Sustainability with the final goal of ensuring an effective involvement of the younger generations who are beginning to make their own decisions.
]]>Climate doi: 10.3390/cli12020016
Authors: Quang Chi Truong Thao Hong Nguyen Vu Thanh Pham Trung Hieu Nguyen
Land-use planning plays an important role in agricultural development. However, the tools used to support planners in proposing land-use planning solutions are lacking, especially when considering saltwater intrusion conditions in coastal regions. In this study, optimization is applied by analyzing land use in developing solutions for agricultural land-use planning, wherein a multi-objective optimization model is developed to optimize land-use area, including land-use allocation, and taking into account socioeconomic and environmental factors. The model was applied to three districts of Soc Trang province, Vietnam (Long Phu, My Xuyen, and Tran De), representing three ecological regions of salt water, brackish water, and fresh water in the Mekong Delta of Vietnam. The results are shown for the implementation of two multi-objective optimization scenarios (in terms of profit, labor, environment benefits, and risk reduction) as follows: (i) multi-objective optimization of agricultural land use until 2030 under normal conditions; (ii) optimizing agricultural land use until 2030 under climate change conditions similar to the 2016 drought and saltwater intrusion phenomenon in the Mekong Delta. The results demonstrate that the second scenario is the preferred option for implementing land-use planning thanks to the balance between good profits and minimizing economic and environmental risk. Land allocation was carried out by taking into account the factors of household economics, the influence of adjacent production types, local traffic, and canal systems to allocate areas toward ensuring optimal land use. This process, involving a combination of land-use optimization and spatial allocation, can help planners to improve the quality of agricultural land-use planning.
]]>Climate doi: 10.3390/cli12020015
Authors: Suresh Neethirajan
This paper explores the transformative potential of Big Data and Artificial Intelligence (AI) in propelling the dairy industry toward net zero emissions, a critical objective in the global fight against climate change. Employing the Canadian dairy sector as a case study, the study extrapolates its findings to demonstrate the global applicability of these technologies in enhancing environmental sustainability across the agricultural spectrum. We begin by delineating the environmental challenges confronting the dairy industry worldwide, with an emphasis on greenhouse gas (GHG) emissions, including methane from enteric fermentation and nitrous oxide from manure management. The pressing need for innovative approaches in light of the accelerating climate crisis forms the crux of our argument. Our analysis delves into the role of Big Data and AI in revolutionizing emission management in dairy farming. This includes applications in optimizing feed efficiency, refining manure management, and improving energy utilization. Technological solutions such as predictive analytics for feed optimization, AI in herd health management, and sensor networks for real-time monitoring are thoroughly examined. Crucially, the paper addresses the wider implications of integrating these technologies in dairy farming. We discuss the development of benchmarking standards for emissions, the importance of data privacy, and the essential role of policy in promoting sustainable practices. These aspects are vital in supporting the adoption of technology, ensuring ethical use, and aligning with international climate commitments. Concluding, our comprehensive study not only suggests a pathway for the dairy industry towards environmental sustainability but also provides insights into the role of digital technologies in broader agricultural practices, aligning with global environmental sustainability efforts.
]]>Climate doi: 10.3390/cli12020014
Authors: Marilina Hernandez Garcia María Cristina Garza-Lagler Tereza Cavazos Ileana Espejel
We analyzed climate change scenarios and their possible impacts on winegrape yield in Baja California, the leading wine producer in Mexico. Linear regression models were used to predict the current yield based on climate and economic variables. Using future projections of the climate variables from two regional climate models (RegCM and RCA4), we evaluated the possible changes in yield for the Near Future (NF: 2021−2040) and Intermediate Future (IF: 2041−2060) periods under low (RCP2.6) and high (RCP8.5) greenhouse gas emissions scenarios. One regression model includes maximum and minimum temperatures (Tx and Tn) of the winegrape growing season and accumulated winter precipitation (Pre), and the other model also includes the real minimum wage and winegrape price to evaluate the operating cost paid by producers. The results show that the linear regression model with the climatic and economic variables explains 28% of the winegrape yield, and Tx and Tn had the greatest influence. The climate change scenarios show that during the winegrape growing season, these variables could increase more than 1 °C in the NF and more than 2 °C in the IF under the RCP8.5 scenario. These latter temperature changes could reduce the yield between 18% and 35% relative to the reference observed climate dataset (Livneh). However, winegrape yield is sensitive to economic factors, as the yield reduction increases at least 3% in all cases. Thus, adaptation strategies need to be implemented in the viticulture sector to reduce future impacts.
]]>Climate doi: 10.3390/cli12020013
Authors: Augusto G. C. Pereira Rafael Palácios Paula C. R. Santos Raimundo Vitor S. Pereira Glauber Cirino Breno Imbiriba
The El Niño-Southern Oscillation (ENSO) stands out as the most significant tropical phenomenon in terms of climatic magnitude resulting from ocean–atmosphere interaction. Due to its atmospheric teleconnection mechanism, ENSO influences various environmental variables across distinct atmospheric scales, potentially impacting the spatiotemporal distribution of atmospheric aerosols. Within this context, this study aims to evaluate the relationship between ENSO and atmospheric aerosols across the entire Legal Amazon during the period from 2006 to 2011. Over this five-year span, four ENSO events were identified. Concurrently, an analysis of the spatiotemporal variability of aerosol optical depth (AOD) and Black Carbon radiation extinction (EAOD-BC) was conducted alongside these ENSO events, utilizing data derived from the Aerosol Robotic Network (AERONET), MERRA-2 model, and ERSSTV5. Employing the Windowed Cross-Correlation (WCC) approach, statistically significant phase lags of up to 4 to 6 months between ENSO indicators and atmospheric aerosols were observed. There was an approximate 100% increase in AOD immediately after El Niño periods, particularly during intervals encompassing the La Niña phase. The analysis of specific humidity anomaly (QA) revealed that, contrary to expectations, positive values were observed throughout most of the El Niño period. This result suggests that while there is a suppression of precipitation events during El Niño due to the subsidence of drier air masses in the Amazon, the region still exhibits positive specific humidity (Q) conditions. The interaction between aerosols and humidity is intricate. However, Q can exert influence over the microphysical and optical properties of aerosols, in addition to affecting their chemical composition and aerosol load. This influence primarily occurs through water absorption, leading to substantial alterations in radiation scattering characteristics, and thus affecting the extinction of solar radiation.
]]>Climate doi: 10.3390/cli12010012
Authors: Simran Bharti Adyan Ul Haq L. T. Sasang Guite Shruti Kanga Fayma Mushtaq Majid Farooq Suraj Kumar Singh Pankaj Kumar Gowhar Meraj
Evaluating inherent vulnerability, an intrinsic characteristic becomes imperative for the formulation of adaptation strategies, particularly in highly complex and vulnerable regions of Himalayas. Jammu City, situated in the north-western Himalayas within a transitional zone between the Himalayan range and the plains, is not only susceptible to intense seismic activities but also faces multiple hazards, including floods, earthquakes, avalanches, and landslides. In recent years, the region has experienced growth in population with rapid progress in infrastructure development, encompassing the construction of highways, dams, and tunnels as integral components of urban development initiatives. Therefore, this study has been conducted to assess the inherent vulnerability index (VI) in Jammu City at ward level as a function of sensitivity, adaptive capacity, and exposure, using ecological and social indicators in GIS environment. The primary objective was to identify the most vulnerable area and ascertain the corresponding municipal ward, aiming to formulate a comprehensive ranking. The 22 indicators analysed were from four major components, namely social, infrastructure, technological, and ecological. The ecological indicators like Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), and Land use/Land cover were derived from Landsat 8 OLI satellite data. The results show that the majority of the area of the city falls into the moderate (20%), high (25.49%), and very high (25.17%) vulnerability categories, respectively, clustered in north-western and south-western transects with densely populated residential areas. The results can assist policymakers in identification of components of inherent vulnerability for focused resource management and formulating adaptation strategies to address the current stressors in the region.
]]>Climate doi: 10.3390/cli12010011
Authors: Rita Kamalova Ekaterina Bogdan Larisa Belan Iren Tuktarova Alexey Firstov Ildar Vildanov Irik Saifullin
The process of climate warming significantly affects agroclimatic resources and agricultural production. We study the agroclimatic resources and their variability on the territory of the Republic of Bashkortostan (Russia). The Bashkortostan has a high agricultural potential and holds a leading position in the country in the production of grain crops, potatoes, milk, and honey. Currently, no detailed studies have been conducted for this area to assess the effects of global climate change on agro-climatic resources. World experience shows such research becomes strategically important for regions with powerful agricultural production. We used the sums of average daily air temperatures above 0 and 10 °C, the G.T. Selyaninov hydrothermal coefficient, and the Ped aridity (humidification) index as agroclimatic indicators. We used data of long-term meteorological observations of 30 meteorological stations for the period of 1961–2020. We revealed the long-term dynamics of the agroclimatic indicators and the spatial and temporal regularities in their distribution on the territory of Bashkortostan. There is a steady increase in the sums of average daily air temperatures above 0 and 10 °C. Against this background, aridity increases, which is especially manifested in the southern parts of the Republic of Bashkortostan. We assessed the impact of agroclimatic indicators on the main types of agricultural crops in the republic. We revealed that the greatest positive impact on the yield of oilseeds, cereals, and industrial crops is made by precipitation at the beginning (r = 0.50, r = 0.44, and r = 0.52, respectively) and in the middle of the growing season (r = 0.55, r = 0.76, and r = 0.51, respectively). Temperature and precipitation during the growing season have a complex effect on cereals. This is proven by correlations with HCS and the Ped index (r = 0.45 and r = −0.56, respectively). Aridity at the beginning of the growing season affects the yield of oilseeds and potatoes. This is confirmed by correlations with the Ped index (r = −0.49 and r = −0.52, respectively). In general, the aridity of the growing season has a significant impact on the yield of cereals (r = −0.57). Negative relationships have been found between the air temperature growing season and the yield of potatoes (r = −0.50) and cereals (r = −0.53). The results of the study were compared with data from the Copernicus Climate Change Service database. We identified climate trends under RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5 scenarios. These scenarios should be taken into account when developing plans for the adaptation of agriculture in the Republic of Bashkortostan to changes in the regional climate. Maximum decrease in precipitation is established for the RCP 6.0 scenario. This can have an extremely negative impact on crop yields. This problem is especially relevant for the southern part of the Republic of Bashkortostan. The information presented in the study will allow for a more effective adaptation of the agricultural sector to current and future climate changes.
]]>Climate doi: 10.3390/cli12010010
Authors: David Mfitumukiza Gordon Y. Mwesigwa Ellen J. Kayendeke Vincent B. Muwanika
Climate change impacts threaten sustainable development efforts. The magnitude of the impacts, however, varies with the socio-ecological characteristics of locations. This is the reason there is consensus on the necessity for climate change adaptive capacity building that is country driven, and based on, and responsive to, local needs. However, information on context specific capacity building needs in developing countries is not readily available. The objective of this study was to establish location specific awareness, training, educational research and technology capacity building needs for climate change adaptation among smallholder farmers in Uganda. Semi-structured questionnaires were used with 465 households from five agro-ecological zones, selected based on the level of vulnerability of agricultural systems to the main climate variation and change hazards. Results reveal substantial capacity building needs in all the zones. The majority of the farmers needed capacity building for interventions on soil-water conservation practices for adapting to drought and unpredictable rainfall. For all zones, education, research, and technology were perceived as key needs. However, the needs varied among zones. These results demonstrate the importance of context specificity in adaptation efforts. The study provides agro-ecological and social system specific information for climate change adaptation planning and policy interventions for effective capacity building.
]]>Climate doi: 10.3390/cli12010009
Authors: Gamil Gamal Pavol Nejedlik Ahmed M. El Kenawy
Understanding long-term variations in precipitation is crucial for identifying the effects of climate change and addressing hydrological and water management issues. This study examined the trends of the mean and four extreme precipitation indices, which are the max 1-day precipitation amount, the max 5-day precipitation amount, the consecutive wet days, and the consecutive dry days, for historical observations (1971–2000) and two future periods (2041–2060/2081–2100) under RCP2.6 and RCP8.5 emission scenarios over the Nile River Basin (NRB) at 11 major stations. Firstly, the empirical quantile mapping procedure significantly improved the performance of all RCMs, particularly those with lower performance, decreasing inter-model variability and enhanced seasonal precipitation variability. The Mann–Kendall test was used to detect the trends in climate extreme indices. This study reveals that precipitation changes vary across stations, scenarios, and time periods. Addis Ababa and Kigali anticipated a significant increase in precipitation across all periods and scenarios, ranging between 8–15% and 13–27%, respectively, while Cairo and Kinshasa exhibited a significant decrease in precipitation at around 90% and 38%, respectively. Wet (dry) spells were expected to significantly decrease (increase) over most parts of the NRB, especially during the second period (2081–2100). Thereby, the increase (decrease) in dry (wet) spells could have a direct impact on water resource availability in the NRB. This study also highlights that increased greenhouse gas emissions have a greater impact on precipitation patterns. This study’s findings might be useful to decision makers as they create NRB-wide mitigation and adaptation strategies to deal with the effects of climate change.
]]>Climate doi: 10.3390/cli12010008
Authors: Sergey Loginov Evgeniia Moraru Elena Kharyutkina Ivan Sudakow
The analysis of spatial and temporal variability in the number of non-Gaussian extreme anomalies of climatic parameters was carried out for both the initial time series and synoptic variability in the troposphere of the Northern Hemisphere over the period 1979–2018, based on ERA-Interim reanalysis data. There are predominantly three types of empirical distribution densities at 850 hPa, each characterizing the processes of advective and convective heat transfer. At the beginning of the 21st century, compared to the end of the 20th century, there was an increase in the number of anomalies in vertical wind speed and specific humidity for the Northern Hemisphere. Additionally, there is an increase in the number of zonal wind speed anomalies in the low and middle latitudes. Regions with the maximum number of anomalies are primarily located over the continents, while for vertical wind speed anomalies, they are predominantly over the oceans. The application of R/S analysis and multifractal analysis has established that the identified tendencies (which are persistent processes) will continue in the identified regions. The time series of non-Gaussian anomalies (both initial and synoptic scales) exhibit a long-term memory of approximately four years, and synoptic extreme anomalies were found to be more predictable.
]]>Climate doi: 10.3390/cli12010007
Authors: Zolisanani Mpanyaro Ahmed Mukalazi Kalumba Leocadia Zhou Gbenga Abayomi Afuye
The increasing drought frequency poses a significant threat to global and regional river systems and ecosystem functioning, especially in the complex topographical Buffalo River catchment area of the Eastern Cape Province, South Africa. This study explored the impact of drought on riparian vegetation dynamics using the Normalize Difference Vegetation Index (NDVI), Transformed Difference Vegetation Index (TDVI) and Modified Normalized Difference Water Index (MNDWI) from satellite-derived Landsat data from 1990 to 2020. The least-squares linear regression and Pearson’s correlation coefficient were used to evaluate the long-term drought in riparian vegetation cover and the role of precipitation and streamflow. The correlation results revealed a moderate positive correlation (r = 0.77) between precipitation and streamflow with a significant p-value of 0.04 suggesting consequences on riparian vegetation health. Concurrent with the precipitation, the vegetation trends showed that precipitation increased insignificantly with less of an influence while the reverse was the case with the streamflow in the long term. The results show that the NDVI and TDVI were significant indices for detecting water-stressed vegetation in river catchment dynamics. Much of these changes were reflected for MNDWI in dry areas with a higher accuracy (87.47%) and dense vegetation in the upper catchment areas. The standardized precipitation index (SPI) revealed the inter-annual and inter-seasonal variations in drought-stressed years between 1991–1996, 2000–2004, 2009–2010, 2015, and 2018–2019, while 2020 exhibited slight sensitivity to drought. The findings of this study underscore the need for heightened efforts on catchment-scale drought awareness for policy development, programs, and practices towards ecosystem-based adaptation.
]]>Climate doi: 10.3390/cli12010006
Authors: Dario Camuffo Antonio della Valle Roberta Giorio Francesco Rizzi Patrizia Barucco Marivita Suma Jalal Ahmed Amel Chabbi Ola Shaker Peter Sheehan
Al Ain, near Abu Dhabi, United Arab Emirates, is characterized by hot desert climate with high temperatures, aridity, and almost no rain. Several truncated earthen walls were discovered at the historic house of Sheikh Mohammed Bin Khalifa, a component of the World Heritage Cultural Sites. These remains are preserved in situ, outdoors, protected in glass showcases for public display. As this situation is not documented in the literature, the local Authority has requested to study the showcase environment to optimize conservation. The solar radiation and the projected shades have been modeled over one year; the temperature and humidity inside and outside the showcases, as well as the moisture content, have been measured to assess the potential preservation risks. The paper presents the results, i.e., the direct solar radiation generates extreme conditions of greenhouse effect with extremely high temperatures and forces evaporation from the remains. During the night, the excess moisture condenses on the inner surface of the glass panes, forming large drops that affect viewing and are dangerous for conservation. The repetition of evaporation–condensation cycles accumulates soluble salts on the remains. The paper discusses mitigation strategies (e.g., shading, ventilation, and cooling, to reduce the greenhouse effect) to improve conservation and fruition.
]]>Climate doi: 10.3390/cli12010005
Authors: Ndonaye Allarané Assouhan Jonas Atchadé Vidjinnagni Vinasse Ametooyona Azagoun Adanvo Isaac Houngnigbe Romain Gouataine Seingue Tob-Ro N’Dilbé Follygan Hetcheli
Climate variability and change are already having a negative impact on the health of tens of millions of Africans through exposure to sub-optimal temperatures and extreme weather conditions as well as increasing the range and transmission of infectious diseases. This study aims to identify climate risks and the vulnerability of health systems as well as individual coping strategies in the city of N’Djaména. To achieve this, we adopted a methodology combining both quantitative and qualitative approaches. Meteorological data on wind, temperature, and rainfall were collected at daily and monthly intervals from the National Meteorological Agency in N’Djaména. Qualitative data were collected via focus group discussions with targets of the city’s health system and quantitative data were collected from the population on the basis of oriented questionnaires. The results show that rising temperatures with heat waves, regular flooding, and strong winds are the major climate risks identified. These have numerous impacts and effects on the city’s health system due to the following vulnerability factors most recognized by city dwellers: insufficient medical equipment in health facilities (IEME), the fragile nature of people’s physiological state in the face of climatic risks (CFEP), and the failure of city sanitation strategies and policies (DSPA). This study proposes a set of recommendations for transformational adaptation of the healthcare sector, which remains vulnerable to climate risks.
]]>Climate doi: 10.3390/cli12010004
Authors: Karina Angélica García-Pardo David Moreno-Rangel Samuel Domínguez-Amarillo José Roberto García-Chávez
The validated influence of urban biophysical structure on environmental processes within urban areas has heightened the emphasis on studies examining morphological patterns to determine precise locations and underlying causes of urban climate conditions. The present study aims to characterise morphological patterns describing the distribution of Land Surface Temperature (LST) based on a prior classification of biophysical variables, including urban density (building intensity and average height), surface characteristics, shortwave solar radiation (broadband albedo), and seasonal variations in vegetation cover (high, medium, and low levels), retrieved from multisource datasets. To describe the distribution of LST, the variables were calculated, classified, and subsequently, analysed individually and collectively concerning winter and summer LST values applied in an urban neighbourhood in Madrid, Spain. The results from the analytical approaches (observation, correlations, and multiple regressions) were compared to define the morphological patterns. The selection of areas resulting from the morphological patterns with the most unfavourable LST values showed agreement of up to 89% in summer and up to 70% for winter, demonstrating the feasibility of the methods applied to identify priority areas for intervention by season. Notably, low and high vegetation levels emerged as pivotal biophysical characteristics influencing LST distribution compared to the other characteristics, emphasising the significance of integrating detailed seasonal vegetation variations in urban analyses.
]]>Climate doi: 10.3390/cli12010003
Authors: Israel Edem Agbehadji Stefanie Schütte Muthoni Masinde Joel Botai Tafadzwanashe Mabhaudhi
Early warning systems (EWS) facilitate societies’ preparedness and effective response capabilities to climate risks. Climate risks embody hazards, exposure, and vulnerability associated with a particular geographical area. Building an effective EWS requires consideration of the factors above to help people with coping mechanisms. The objective of this paper is to propose an approach that can enhance EWSs and ensure an effective climate risk resilience development. The paper focuses on the Southern African Development Community (SADC) region and highlights the issues with EWS, identifying weaknesses and characteristics of EWS to help in climate risk adaptation strategies. The SADC region was chosen as the context because it is a climate variability and change hotspot with many vulnerable populations residing in rural communities. Trending themes on building climate risk resilience were uncovered through scientific mapping and network analysis of published articles from 2008 to 2022. This paper contributes to on-going research on building climate risks resilience through early warning systems to identify hidden trends and emerging technologies from articles in order to enhance the operationalization and design of EWS. This review provides insight into technological interventions for assessing climate risks to build preparedness and resilience. From the review analysis, it is determined that there exists a plethora of evidence to support the argument that involving communities in the co-designing of EWS would improve risk knowledge, anticipation, and preparedness. Additionally, Fourth Industrial Revolution (4IR) technologies provide effective tools to address existing EWS’ weaknesses, such as lack of real-time data collection and automation. However, 4IR technology is still at a nascent stage in EWS applications in Africa. Furthermore, policy across societies, institutions, and technology industries ought to be coordinated and integrated to develop a strategy toward implementing climate resilient-based EWS to facilitate the operations of disaster risk managers. The Social, Institutional, and Technology model can potentially increase communities’ resilience; therefore, it is recommended to develop EWS.
]]>Climate doi: 10.3390/cli12010002
Authors: Phumzile Maluleke Mokhele E. Moeletsi Mitsuru Tsubo
In recent decades, southern Africa has experienced a shift towards hotter and drier climate conditions, affecting vital sectors like agriculture, health, water, and energy. Scientific research has shown that the combination of high temperatures and unreliable rainfall can have detrimental effects on agricultural production. Thus, this study focused on assessing climate variability, with implications on rangelands in the Limpopo Province of South Africa over 38 years. Historical climate data from 15 stations, including rainfall and minimum and maximum temperatures from 1980 to 2018, were analysed. To achieve the main objective, various statistics including mean, standard deviation, and coefficient of variation (CV) were computed for all variables across four seasons. The results highlighted significant variability in rainfall, with Musina (71.2%) and Tshiombo (88.3%) stations displaying the highest variability during the September-to-April season. Both minimum and maximum temperatures displayed low variability. The Mann–Kendall test revealed both increasing and decreasing trends in minimum temperatures and rainfall across different stations. Notably, there was a significant increase in maximum temperatures. This study provides valuable climate information for decision makers, aiding in the planning and management of agricultural activities, particularly in understanding how climate variations affect forage availability in rangelands.
]]>Climate doi: 10.3390/cli12010001
Authors: Nazario Tartaglione Thomas Toniazzo Odd Helge Otterå Yvan Orsolini
In this study, we use the Whole Atmosphere Community Climate Model, forced by present-day atmospheric composition and coupled to a Slab Ocean Model, to simulate the state of the climate under grand solar minimum forcing scenarios. Idealized experiments prescribe time-invariant solar irradiance reductions that are either uniform (percentage-wise) across the total solar radiation spectrum (TOTC) or spectrally localized in the ultraviolet (UV) band (SCUV). We compare the equilibrium condition of these experiments with the equilibrium condition of a control simulation, forced by perpetual solar maximum conditions. In SCUV, we observe large stratospheric cooling due to ozone reduction. In both the Northern Hemisphere (NH) and the Southern Hemisphere (SH), this is accompanied by a weakening of the polar night jet during the cold season. In TOTC, dynamically induced polar stratospheric cooling is observed in the transition seasons over the NH, without any ozone deficit. The global temperature cooling values, compared with the control climate, are 0.55±0.03 K in TOTC and 0.39±0.03 K in SCUV. The reductions in total meridional heat transport outside of the subtropics are similar in the two experiments, especially in the SH. Despite substantial differences in stratospheric forcing, similarities exist between the two experiments, such as cloudiness; meridional heating transport in the SH; and strong cooling in the NH during wintertime, although this cooling affects two different regions, namely, North America in TOTC and the Euro–Asian continent in SCUV.
]]>Climate doi: 10.3390/cli11120246
Authors: Manoj Bhatta Emma Field Max Cass Kerstin Zander Steven Guthridge Matt Brearley Sonia Hines Gavin Pereira Darfiana Nur Anne Chang Gurmeet Singh Stefan Trueck Chi Truong John Wakerman Supriya Mathew
Extreme heat has been linked to increased mortality and morbidity across the globe. Increasing temperatures due to climatic change will place immense stress on healthcare systems. This review synthesises Australian literature that has examined the effect of hot weather and heatwaves on various health outcomes. Databases including Web of Science, PubMed and CINAHL were systematically searched for articles that quantitatively examined heat health effects for the Australian population. Relevant, peer-reviewed articles published between 2010 and 2023 were included. Two authors screened the abstracts. One researcher conducted the full article review and data extraction, while another researcher randomly reviewed 10% of the articles to validate decisions. Our rapid review found abundant literature indicating increased mortality and morbidity risks due to extreme temperature exposures. The effect of heat on mortality was found to be mostly immediate, with peaks in the risk of death observed on the day of exposure or the next day. Most studies in this review were concentrated on cities and mainly included health outcome data from temperate and subtropical climate zones. There was a dearth of studies that focused on tropical or arid climates and at-risk populations, including children, pregnant women, Indigenous people and rural and remote residents. The review highlights the need for more context-specific studies targeting vulnerable population groups, particularly residents of rural and remote Australia, as these regions substantially vary climatically and socio-demographically from urban Australia, and the heat health impacts are likely to be even more substantial.
]]>Climate doi: 10.3390/cli11120245
Authors: Seyhakreaksmey Duong Layheang Song Rattana Chhin
The consequences of climate change are arising in the form of many types of natural disasters, such as flooding, drought, and tropical cyclones. Responding to climate change is a long horizontal run action that requires adaptation and mitigation strategies. Hence, future climate information is essential for developing effective strategies. This study explored the applicability of a statistical downscaling method, Bias-Corrected Spatial Disaggregation (BCSD), in downscaling climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and then applied the downscaled data to project the future condition of precipitation pattern and extreme events in Cambodia. We calculated four climate change indicators, namely mean precipitation changes, consecutive dry days (CDD), consecutive wet days (CWD), and maximum one-day precipitation (rx1day) under two shared socioeconomic pathways (SSPs) scenarios, which are SSP245 and SSP585. The results indicated the satisfactory performance of the BCSD method in capturing the spatial feature of orographic precipitation in Cambodia. The analysis of downscaled CMIP6 models shows that the mean precipitation in Cambodia increases during the wet season and slightly decreases in the dry season, and thus, there is a slight increase in annual rainfall. The projection of extreme climate indices shows that the CDD would likely increase under both climate change scenarios, indicating the potential threat of dry spells or drought events in Cambodia. In addition, CWD would likely increase under the SSP245 scenario and strongly decrease in the eastern part of the country under the SSP585 scenario, which inferred that the wet spell would have happened under the moderate scenario of climate change, but it would be the opposite under the SSP585 scenario. Moreover, rx1day would likely increase over most parts of Cambodia, especially under the SSP585 scenario at the end of the century. This can be inferred as a potential threat to extreme rainfall triggering flood events in the country due to climate change.
]]>Climate doi: 10.3390/cli11120244
Authors: Claudio Stefanini Francesca Becherini Antonio della Valle Francesco Rech Fabio Zecchini Dario Camuffo
Meteorological observations over the last four decades are of paramount importance to investigating ongoing climate change. An important issue is the quality and reliability of the climatic series, which are fundamental prerequisites to drawing the correct conclusions. Homogeneity tests are used to detect discontinuities whose interpretation is facilitated by metadata availability. In this work, daily minimum and maximum temperature measurements collected in Padua, Italy, between 1980 and 2022 are examined. During this period, the weather station of Padua center underwent many changes in location or instruments; therefore, some tests have been used to identify and remove their effects and obtain homogeneous series. Some well-known absolute tests have been applied to investigate the shift in the mean value: Standard Normal Homogeneity test (SNH), Buishand U and range tests, Pettitt test, F-test, and STARS. Relative tests have been applied too, using several stations nearby Padua and two reanalysis datasets (ERA5 and MERIDA) as reference series to enhance the picture of the local situation and provide more robust conclusions. The applied tests identify change-points in the years in which a change in instrument or the location of the station has occurred, confirming that these changes have compromised the homogeneity of the series. The sub-series obtained, splitting the observations in correspondence with these change-points, have been homogenized with respect to a selected period. The corrected series of the minimum and maximum temperatures are more coherent with the modern warming trend. The transfer functions to be applied to future measurements of minimum temperature have been calculated, while the series of maximum temperature measurements can be directly extended.
]]>Climate doi: 10.3390/cli11120243
Authors: Gashaw Bimrew Tarekegn Addis A. Alaminie Sisay E. Debele
In Ethiopia, the impacts of climate change are expected to have significant consequences for agriculture and food security. This study investigates both past (1981–2010) and future (2041–2070) climate trends and their influence on the length of the growing season (LGS) in the North-Western Ethiopian highlands. Climate observations were obtained from the National Meteorological Agency of Ethiopia, while the best performing and highest resolution models from the CMIP5 experiment and RCP6 (Coupled Models Intercomparison Project and representative concentration pathway 6) were used for the analysis. Standard statistical methods were applied to compute soil water content, evaluate climate variability and trends, and assess their impact on the length of the growing season. Maximum temperature (tasmax) and minimum temperature (tasmin) inter-annual variability anomalies show that the region has experienced cooler years than hotter years in the past. However, in the future, the coolest years are expected to decrease by −1.2 °C, while the hottest years will increase by +1.3 °C. During the major rainfall season (JJAS), the area has received an adequate amount of rainfall in the past and is very likely to receive similar rainfall in the future. On the other hand, the rainfall amount in the season February to May (FMAM) is expected to assist only with early planting. For the season October to January (ONDJ), the rainfall amount may help lengthen the growing season of JJAS if properly utilized; otherwise, the season has the potential to destroy crops before and during the harvesting time. The soil water content changes in the future remain close to those of the past period. The length of growing seasons has less variable onset and cessation dates, while in the future, the length of the growing period (LGP) of 174 to 177 days will be suitable for short- and long-cycle crops, as well as double cropping, benefiting crop production yield in the North-Western Ethiopian highlands in the future.
]]>Climate doi: 10.3390/cli11120242
Authors: Athanasios Sfetsos Nadia Politi Diamando Vlachogiannis
Many modern frameworks for community resilience and emergency management in the face of extreme hydrometeorological and climate events rely on scenario building. These scenarios typically cover multiple hazards and assess the likelihood of their occurrence. They are quantified by their main characteristics, including likelihood of occurrence, intensity, duration, and spatial extent. However, most studies in the literature focus only on the first two characteristics, neglecting to incorporate the internal hazard dynamics and their persistence over time. In this study, we propose a multidimensional approach to construct extreme event scenarios for multiple hazards, such as heat waves, cold spells, extreme precipitation and snowfall, and wind speed. We consider the intensity, duration, and return period (IDRP) triptych for a specific location. We demonstrate the effectiveness of this approach by developing pertinent scenarios for eight locations in Greece with diverse geographical characteristics and dominant extreme hazards. We also address how climate change impacts the scenario characteristics.
]]>Climate doi: 10.3390/cli11120241
Authors: Fabrício Daniel dos Santos Silva Claudia Priscila Wanzeler da Costa Vânia dos Santos Franco Helber Barros Gomes Maria Cristina Lemos da Silva Mário Henrique Guilherme dos Santos Vanderlei Rafaela Lisboa Costa Rodrigo Lins da Rocha Júnior Jório Bezerra Cabral Júnior Jean Souza dos Reis Rosane Barbosa Lopes Cavalcante Renata Gonçalves Tedeschi Naurinete de Jesus da Costa Barreto Antônio Vasconcelos Nogueira Neto Edmir dos Santos Jesus Douglas Batista da Silva Ferreira
Monitoring rainfall in the Brazilian Legal Amazon (BLA), which comprises most of the largest tropical rainforest and largest river basin on the planet, is extremely important but challenging. The size of the area and land cover alone impose difficulties on the operation of a rain gauge network. Given this, we aimed to evaluate the performance of nine databases that estimate rainfall in the BLA, four from gridded analyses based on pluviometry (Xavier, CPC, GPCC and CRU), four based on remote sensing (CHIRPS, IMERG, CMORPH and PERSIANN-CDR), and one from reanalysis (ERA5Land). We found that all the bases are efficient in characterizing the average annual cycle of accumulated precipitation in the BLA, but with a predominantly negative bias. Parameters such as Pearson’s correlation (r), root-mean-square error (RMSE) and Taylor diagrams (SDE), applied in a spatial analysis for the entire BLA as well as for six pluviometrically homogeneous regions, showed that, based on a skill ranking, the data from Xavier’s grid analysis, CHIRPS, GPCC and ERA5Land best represent precipitation in the BLA at monthly, seasonal and annual levels. The PERSIANN-CDR data showed intermediate performance, while the IMERG, CMORPH, CRU and CPC data showed the lowest correlations and highest errors, characteristics also captured in the Taylor diagrams. It is hoped that this demonstration of hierarchy based on skill will subsidize climate studies in this region of great relevance in terms of biodiversity, water resources and as an important climate regulator.
]]>Climate doi: 10.3390/cli11120240
Authors: Farshad Amiraslani Deirdre Dragovich
Climate change impacts occur at varying spatial scales requiring appropriately scaled responses. In impoverished rural areas, adapting to or mitigating the effects of climate change is challenging, with any short-term impairment to precarious livelihoods likely triggering negative community responses even if people are aware of long-term benefits. The paper will discuss a community-based carbon sequestration project in eastern Iran. It started in 2003 and since then has been expanded widely. It was nominated by UNDP as one of 10 transformative projects in Asia/Pacific in 2016. Over the past 20 years, the project has targeted improving the livelihood of the local communities while addressing local measures to adapt to/mitigate climate change. The paper elaborates on the formation of village development groups as pivotal drivers of success by highlighting local income-generating schemes and project documentation. Key lessons for climate change adaptation can be learnt and are applicable to other developing countries. Extreme poverty in rural areas facing climate change could be tackled through implementing bottom-up approaches in which local communities can be respected and engaged in co-leadership and planning.
]]>Climate doi: 10.3390/cli11120239
Authors: Reneilwe Maake Johan Malherbe Teboho Masupha George Chirima Philip Beukes Sarah Roffe Mark Thompson Mokhele Moeletsi
The Umlindi newsletter was developed to provide information towards climate advisories, considering, for instance, drought conditions, presented in a relevant manner for the agricultural and disaster sectors in South Africa. This newsletter, which is disseminated on a monthly basis, provides information derived from climate-related monitoring products obtained from an integration of remote sensing and in situ data from weather stations. It contains useful indicators, such as rainfall, vegetation, and fire conditions, that provide an overview of conditions across the country. The present study demonstrates how these natural resource indices are integrated and consolidated for utilization by farmers, policy-makers, private organizations, and the general public to make day-to-day decisions on the management and mitigation of natural disasters. However, there is a need to expand these baseline observation initiatives, including the following: (1) forecasting future conditions to strengthen coping mechanisms of government, farmers, and communities at large; and (2) incorporating information on other natural disasters such as floods and extreme heat. In the context of South Africa, this information is important to improve disaster preparedness and management for agricultural productivity. In a global context, the Umlindi newsletter can be insightful for developing and disseminating natural resources information on adaptation to and mitigation of climate change and variability impacts to other regions facing similar risks. Furthermore, while international organizations also provide natural resource information, the Umlindi newsletter may be distinguished by its regional focus and linkages to individual communities. It bridges the gap between global environmental data and local decision-making by illustrating how global scientific knowledge may be applied locally.
]]>Climate doi: 10.3390/cli11120238
Authors: Fernanda Silva Carvalho Maria Gabriela Meirelles Diamantino Henriques João Porteiro Patrícia Navarro Helena Cristina Vasconcelos
In small island regions, the influence of climate change assumes particular relevance. In the Azores archipelago, made up of nine islands, the geographical circumstances, oceanic condition, territorial dispersion, land use model and other physiographic constraints reinforce and enhance the vulnerability of the islands to changes in current weather patterns. Coupled Model Intercomparison Phase 6 (CMIP6) projections are used for the northeast Atlantic region to evaluate daily extreme climate events in large scale for the Azores region. Results shows changes in the annual maximum number of consecutive dry days, the annual number of wet days, and especially in the annual number of tropical nights. Despite limitations due to the lack of spatial detail, the large-scale framework suggests changes that may be enhanced by topography, particularly with respect to precipitation. The conclusions point to the need to establish standard rules in the processes of design, reviewing and/or amending territorial management instruments at the municipal scale in the Autonomous Region of the Azores, with the goal of adapting to a different climate from the recent past.
]]>Climate doi: 10.3390/cli11120237
Authors: Aneurin Grant Christopher L. Atkinson
This study analyzes insurance claim data from an 11-county area in the Florida Panhandle following the landfall of Hurricane Michael. The data includes 1467 non-mobile home structures, with 902 (61.5%) storm-damaged structures in Bay County. The analysis focuses on Wind Mitigation form 1802. Specifically, building design variables were analyzed via linear regression as to their influence on the percent claim loss. The building design variables included total square footage, dwelling construction type, age of the building, roof type, roof cover type, roof deck attachment type, roof to wall attachment, the presence of secondary water resistance (or sealed roof deck), opening protection type, and roof shape. Results show that building design variables for insurance claims have a high predictive value relative to a Category 5 hurricane event. However, the predictive values of building design variables are also dependent on the dwelling’s proximity to the coast, its location relative to the strong or weak side of the storm, the diameter of the storm, and other wind field variables.
]]>Climate doi: 10.3390/cli11120236
Authors: Kartheek Mamidi Vincent Mathew
An attempt has been made to explore the relative contributions of moisture feedback processes on tropical intraseasonal oscillation or Madden–Julian Oscillation (MJO). We focused on moisture feedback processes, including evaporation wind feedback (EWF) and moisture convergence feedback (MCF), which integrate the mechanisms of convective interactions into the tropical atmosphere. The dynamical framework considered here is a moisture-coupled, single-layer linear shallow-water model on an equatorial beta-plane with zonal momentum damping. With this approach, we aimed to recognize the minimal physical mechanisms responsible for the existence of the essential dispersive characteristics of the MJO, including its eastward propagation (k>0), the planetary-scale (small zonal wavenumbers) instability, and the slow phase speed of about ≈5 m/s. Furthermore, we extended our study to determine each feedback mechanism’s influence on the simulated eastward dispersive mode. Our model emphasized that the MJO-like eastward mode is a possible outcome of the combined effect of moisture feedback processes without requiring additional complex mechanisms such as cloud radiative feedback and boundary layer dynamics. The results substantiate the importance of EWF as a primary energy source for developing an eastward moisture mode with a planter-scale instability. The eastward moisture mode exhibits the highest growth rate at the largest wavelengths and is also sensitive to the strength of the EWF, showing a significant increase in the growth rate with the increasing strength of the EWF; however, the eastward moisture mode remains unstable at planetary-scale wavelengths. Moreover, our model endorses that the MCF alone could not produce instability without surface fluxes, although it has a significant role in developing deep convection. It was found that the MCF exhibits a damping mechanism by regulating the frequency and growth rate of the eastward moisture mode at shorter wavelengths.
]]>Climate doi: 10.3390/cli11120235
Authors: Kade Berman Yuriy Kuleshov
Tropical cyclones (TCs) are one of the most destructive natural hazards to impact on Australia’s population, infrastructure, and the environment. To examine potential TC impacts, it is important to understand which assets are exposed to the hazard and of these, which are vulnerable to damage. The aim of this study is to improve TC risk assessments through developing an exposure–vulnerability index, utilising a case study for the six Local Government Areas (LGAs) impacted by the landfall of TC Debbie in 2017: Burdekin Shire, Charters Towers Region, Isaac Region, Mackay Region, City of Townsville, and Whitsunday Region. This study utilised a natural hazard risk assessment methodology, linking exposure and vulnerability indicators related to social factors, infrastructure, and the environment. The two LGAs with the most extreme exposure–vulnerability values were the coastal regions of Mackay Region and the City of Townsville. This is consistent with urbanisation and city development trends, with these LGAs having more people (social) and infrastructure exposed, while the environmental domain was more exposed and vulnerable to TC impacts in rural LGAs. Therefore, further resilience protocols and mitigation strategies are required, particularly for Mackay Region and the City of Townsville, to reduce the damage and ultimate loss of lives and livelihoods from TC impacts. This study serves as a framework for developing a TC risk index based on hazard, exposure, and vulnerability indices, and insight into the improved mitigation strategies for communities to implement in order to build resilience to the impacts of future TCs.
]]>Climate doi: 10.3390/cli11120234
Authors: Qianyi Cai Eric Zusman Guobi Meng
China has long sought to address climate change in line with other development goals. However, research supporting this alignment often employs data-driven models that downplay the policies and institutions needed to achieve the multiple benefits that studies feature in their analyses. This oversight is troubling because it neglects gaps between goals and the actual integration of climate and development or co-control of air pollution and greenhouse gases (GHGs). Additionally, this oversight may overlook growing implementation challenges as China pursues synergies between net-zero emissions, biodiversity, and circularity. This article illustrates these challenges by tracing the goals and policies/institutions in China over three phases: (1) integration (1979–2010), (2) co-control (2011–2019), and (3) synergies (2020–present). This article argues that China needs to strengthen the science–policy interface and ensure that new market-based policy instruments (such as emissions trading programs) as well as the leadership responsibility system incentivize reductions in overall GHG emissions while shrinking ecological footprints in the shifts to synergies.
]]>Climate doi: 10.3390/cli11120233
Authors: Christo Odeyemi Takashi Sekiyama
This study answers four research questions by contextualising the background to Japan’s “carbon neutrality and net-zero” (CNN) policy, which was announced in October 2020, and identifying important changes in Japanese climate policy between 1990 and 2020. What is the link between the problem of fairness under the Kyoto targets and the Japanese government’s initial reluctance towards ambitious carbon emission reductions? Why did the Japanese business sector initially resist the possibility of ambitious carbon emission reductions? How has the term “climate crisis” contributed to the need for CNN policy? Why did the Japanese government change its reluctant stance and announce the CNN policy in October 2020? Four main findings were extracted from a narrative technique-based analysis of Japan’s policy documents related to CNN. The following are the findings: [i] the framing of climate change as a “climate crisis” by influential Japanese climate stakeholders was a key motivation for Japan to formally announce its CNN policy in October 2020; [ii] pressure from the international community and the political leadership of the Yoshihide Suga administration are essential factors that led the Japanese government to change its stance and announced this policy; [iii] it is possible that the policy could have been announced sooner, but concern among Japanese climate stakeholders about the problem of fairness in the Kyoto Protocol’s emission reduction targets likely impeded such an announcement; and [iv] this concern underpinned Keidanren’s (or the business sector’s) consistent opposition to the introduction of regulatory schemes. These results emerge for the first time in a study of Japan’s carbon neutrality, particularly in terms of the broader context of climate politics. Finally, we offer a possible explanation for Suga’s deliberate announcement of the CNN policy. This opens up space for future research to complement our study by providing important indicators on the trajectory of this important policy.
]]>Climate doi: 10.3390/cli11120232
Authors: Debanjana Das Sen Chiao Chayan Roychoudhury Fatema Khan Sutapa Chaudhuri Sayantika Mukherjee
Tropical cyclones (TC) are one of the deadliest natural meteorological hazards with destructive winds and heavy rains, resulting losses often reach billions of dollars, imposing a substantial and long-lasting burden on both local and national economies. The El-Niño Southern Oscillation (ENSO), a tropical ocean–atmosphere interaction, is known to significantly impact cyclonic systems over global ocean basins. This study investigates the variability of TC activity in the presence of ENSO over the North Indian Ocean (NIO), comprising the Arabian Sea (ARB) and the Bay of Bengal (BOB) basins during the pre- and post-monsoon season, using accumulated cyclone energy (ACE) over the last 29 years. Our analysis reveals a significant rise in tropical cyclone energy intensity over the past two decades, with eight of the ten most active years occurring since the 2000s. Total ACE over the NIO is found to be higher in La-Niña. Higher ACE observed over ARB is strongly associated with a combination of elevated sea surface height (SSH) anomaly and low vertical wind shear during the El-Niño episodes, with higher sea surface temperatures (SST) during the post-monsoon season. Whereas in the BOB, El Niño not only reduces ACE, but also decreases basin-wide variability, and more pronounced effects during the post-monsoon season, coinciding with warmer SST and higher SSH along the coast during La-Niña.
]]>Climate doi: 10.3390/cli11120231
Authors: Liliana Proskuryakova
The UN vision of climate resilience contains three independent outcomes: resilient people and livelihoods, resilient business and economies, and resilient environmental systems. This article analyzes the positive contributions of low-carbon energy technologies to climate resilience by reviewing and critically assessing the existing pool of studies published by researchers and international organizations that offer comparable data (quantitative indicators). Compilation, critical analysis, and literature review methods are used to develop a methodological framework that is in line with the UN vision of climate resilience and makes it possible to compare the input of low-carbon energy technologies climate resilience by unit of output or during their lifecycle. The framework is supported by the three relevant concepts—energy trilemma, sharing economy/material footprint, and Planetary Pressures-Adjusted Human Development Index. The study identifies indicators that fit the suggested framework and for which the data are available: total material requirement (TMR), present and future levelized cost of electricity (LCOE) without subsidies, CO2 emissions by fuel or industry, lifecycle CO2-equivalent emissions, and mortality rates from accidents and air pollution. They are discussed in the paper with a focus on multi-country and global studies that allow comparisons across different geographies. The findings may be used by decision-makers when prioritizing the support of low-carbon technologies and planning the designs of energy systems.
]]>Climate doi: 10.3390/cli11110230
Authors: David Espín-Sánchez Jorge Olcina-Cantos Carmelo Conesa-García
In the context of climate change, where the average temperature has risen in recent decades on the Mediterranean coast of the Iberian Peninsula, bioclimatic indicators show an increase in thermal discomfort. This is especially relevant in regions with a clear focus on mass and seasonal sun and beach tourism, with a large number of tourists experiencing discomfort in hot and humid summer environments. The research analyses the temporal evolution (1967–2022) of the coasts of the provinces of Alicante and Murcia (Spain) using the Climate Comfort Index (CCI), divided into four different regions. Used are 14 coastal meteorological observatories divided into four regions. Trend analysis was performed using the Mann–Kendall (MKT) and Theil–Sen (TSE) tests. The results revealed a loss of climate comfort during the summer season (−0.3 to −0.4/decade), as well as an expansion of the warm period toward June and early September, with an increase of 38.7 days in “hot” thermal comfort. The increase in thermal discomfort in the summer is influenced by an increase in average temperature (0.5 to 0.7 °C/decade) and a reduction in the average relative humidity (−1.0 to −2.1%/decade) and wind speed (−0.2 to −0.9 km/h/decade). In the last 22 years (2000–2022), decreases (p  ≤ 0.05) have been recorded in July and September (−0.2 to −0.4/decade), reaching “excessive heat” climatic comfort thresholds for the first time. Finally, there has been an increase in thermal comfort in winter, especially during December in recent years (2000–2022).
]]>Climate doi: 10.3390/cli11110229
Authors: Michael Kaspi Yuriy Kuleshov
This study investigated tropical cyclone (TC)-induced flooding in coastal regions of Australia due to the impact of TC Debbie in 2017 utilising a differential evolution-optimised random forest to model flood susceptibility in the region of Bowen, Airlie Beach, and Mackay in North Queensland. Model performance was evaluated using a receiver operating characteristic curve, which showed an area under the curve of 0.925 and an overall accuracy score of 80%. The important flood-influencing factors (FIFs) were investigated using both feature importance scores and the SHapely Additive exPlanations method (SHAP), creating a flood hazard map of the region and a map of SHAP contributions. It was found that the elevation, slope, and normalised difference vegetation index were the most important FIFs overall. However, in some regions, the distance to the river and the stream power index dominated for a similar flood hazard susceptibility outcome. Validation using SHAP to test the physical reasoning of the model confirmed the reliability of the flood hazard map. This study shows that explainable artificial intelligence allows for improved interpretation of model predictions, assisting decision-makers in better understanding machine learning-based flood hazard assessments and ultimately aiding in mitigating adverse impacts of flooding in coastal regions affected by TCs.
]]>Climate doi: 10.3390/cli11110228
Authors: Xiaofan Zhao Huimin Li Qin Cai Ye Pan Ye Qi
On 20 July 2021, an extreme rainstorm battered Zhengzhou in China’s Henan Province, killing 302 people, including 14 individuals who drowned in a subway tunnel and 6 who drowned in a road tunnel. As the global climate warms, extreme weather events similar to the Zhengzhou flood will become more frequent, with increasingly catastrophic consequences for society. Taking a case study-based approach by focusing on the record-breaking Zhengzhou flood, this paper examines the governance capacity of inland cities in North China for managing extreme precipitation and flooding events from the perspective of the flood risk management process. Based on in-depth case analysis, our paper hypothesizes that inland cities in North China still have low risk perceptions of extreme weather events, which was manifested in insufficient pre-disaster preparation and prevention, poor risk communication, and slow emergency response. Accordingly, it is recommended that inland cities update their risk perceptions of extreme rainfall and flooding events, which are no longer low-probability, high-impact “black swans”, but turning into high-probability, high-impact “gray rhinos.” In particular, cities must make sufficient preparation for extreme weather events by revising contingency plans and strengthening their implementation, improving risk communication of meteorological warnings, and synchronizing emergency response with meteorological warnings.
]]>Climate doi: 10.3390/cli11110227
Authors: Simon Kamwele Awala Kudakwashe Hove Johanna Shekupe Valombola Helena Nalitende Nafuka Evans Kamwi Simasiku Barthlomew Chataika Lydia Ndinelao Horn Simon Angombe Levi S. M. Akundabweni Osmund D. Mwandemele
In semi-arid regions, climate change has affected crop growing season length and sowing time, potentially causing low yield of the rainfed staple crop pearl millet (Pennisetum glaucum L.) and food insecurity among smallholder farmers. In this study, we used 1994–2023 rainfall data from Namibia’s semi-arid North-Central Region (NCR), receiving November–April summer rainfall, to analyze rainfall patterns and trends and their implications on the growing season to propose climate adaptation options for the region. The results revealed high annual and monthly rainfall variabilities, with nonsignificant negative trends for November–February rainfalls, implying a shortening growing season. Furthermore, we determined the effects of sowing date on grain yields of the early-maturing Okashana-2 and local landrace Kantana pearl millet varieties and the optimal sowing window for the region, using data from a two-year split-plot field experiment conducted at the University of Namibia—Ogongo Campus, NCR, during the rainy season. Cubic polynomial regression models were applied to grain-yield data sets to predict grain production for any sowing date between January and March. Both varieties produced the highest grain yields under January sowings, with Kantana exhibiting a higher yield potential than Okashana-2. Kantana, sown by 14 January, had a yield advantage of up to 36% over Okashana-2, but its yield gradually reduced with delays in sowing. Okashana-2 exhibited higher yield stability across January sowings, surpassing Kantana’s yields by up to 9.4% following the 14 January sowing. We determined the pearl millet optimal sowing window for the NCR to be from 1–7 and 1–21 January for Kantana and Okashana-2, respectively. These results suggest that co-cultivation of early and late pearl millet varieties and growing early-maturing varieties under delayed seasons could stabilize grain production in northern Namibia and enhance farmers’ climate adaptation. Policymakers for semi-arid agricultural regions could utilize this information to adjust local seed systems and extension strategies.
]]>Climate doi: 10.3390/cli11110226
Authors: Niki Evelpidou Constantinos Cartalis Anna Karkani Giannis Saitis Kostas Philippopoulos Evangelos Spyrou
This paper addresses the riverine flood events that have occurred in Greece over the last 136 years (i.e., during the 1886–2022 period), focusing, amongst others, on the case of urban floods. The flood record of various sites of the country has been collected and analyzed to determine their spatial and temporal distribution. Greece is a country where flood data and records are very scarce. Therefore, as there is not an integrated catalog of Greek floods spanning from the 19th century to recently, this is the first attempt to create an integrated catalog for Greece. The sources used include published papers, local and regional newspapers and public bodies (mainly the Ministry of Environment and Energy and the official websites of Greek municipalities). Additionally, the main factors responsible for their occurrence have been issued, regarding the country’s climatic, geological and geomorphological setting, as well as human interventions. In addition, the atmospheric circulation driving factors of floods are assessed via an unsupervised neural network approach (i.e., Self-Organizing Maps). Based on the results of this research, an online GIS-based database has been created, depicting the areas that have been struck by riverine floods in Greece. By clicking a flood event in the online database, one can view several characteristics, depending on data availability, such as duration and height of the rainfall that caused them and number of fatalities. Long-term trends of mean and extremes seasonal precipitation also linked to the spatial distribution of floods. Our analysis shows that urban floods are a very large portion of the overall flood record, and they mainly occur in the two large urban centers, Athens and Thessaloniki, as well as near large rivers such as Pineios. Autumn months and mainly November are the periods with higher flood hazards, based on past records and cyclonic atmospheric circulation constitutes the principal driving factor. Our results indicate that a flood catalog at national level is of fundamental importance, as it can provide valuable statistical insights regarding seasonality, spatial distribution of floods, etc., while it can also be used by stakeholders and researchers for flood management and flood risk analysis and modelling.
]]>Climate doi: 10.3390/cli11110225
Authors: José Javier Hernández Ayala Rafael Méndez Tejeda
This study explores spatial and temporal changes in the rainfall climatology of Puerto Rico in order to identify areas where annual, seasonal or daily precipitation is increasing, decreasing, or remaining normal. Total annual, seasonal, and daily rainfall were retrieved from 23 historical rain gauges with consistent data for the 1956–2021 period. Mann–Kendall trend tests were done on the annual and seasonal rainfall series, and percentage change differences between two different climatologies (1956–1987 and 1988–2021) were calculated. Most of the stations did not exhibit statistically significant annual or seasonal trends in average rainfall. However, of the sites that did experience changes, most of them had statistically significant decreasing trends in mean precipitation. The annual, dry, and early wet season had more sites with negative trends when compared with positive trends, especially in the northwestern and southeastern region of the island. The late wet season was the only period with more sites showing statistically significant trends when compared with negative trends, specifically in the northern region of the island. Results for daily events show that extreme rainfall occurrences have generally decreased, especially in the western region of the island. When the 1955–1987 and 1988–2022 climatologies are compared, the results for annual average rainfall show two main regions with mean precipitation reductions, and those are the northwestern and southeastern areas of the island. The dry season was the only period with more areas exhibiting percentage increases in mean rainfall when the two climatologies were analyzed. The early and late wet season months exhibited similar patterns, with more areas on the island showing negative percentage decreases in average seasonal precipitation. The best predictor for the decreasing annual and seasonal trend in the northwest was a higher sea level pressure, and the variable that best explained the increasing trend in the northeast was total precipitable water.
]]>Climate doi: 10.3390/cli11110224
Authors: Peter Domonkos
Homogenization of climatic time series aims to remove non-climatic biases which come from the technical changes in climate observations. The method comparison tests of the Spanish MULTITEST project (2015–2017) showed that ACMANT was likely the most accurate homogenization method available at that time, although the tested ACMANTv4 version gave suboptimal results when the test data included synchronous breaks for several time series. The technique of combined time series comparison was introduced to ACMANTv5 to better treat this specific problem. Recently performed tests confirm that ACMANTv5 adequately treats synchronous inhomogeneities, but the accuracy has slightly worsened in some other cases. The results for a known daily temperature test dataset for four U.S. regions show that the residual errors after homogenization may be larger with ACMANTv5 than with ACMANTv4. Further tests were performed to learn more about the efficiencies of ACMANTv4 and ACMANTv5 and to find solutions for the problems occurring with the new version. Planned changes in ACMANTv5 are presented in the paper along with related test results. The overall results indicate that the combined time series comparison can be kept in ACMANT, but smaller networks should be generated in the automatic networking process of the method. To improve further the homogenization methods and to obtain more reliable and more solid knowledge about their accuracies, more synthetic test datasets mimicking the true spatio-temporal structures of real climatic data are needed.
]]>Climate doi: 10.3390/cli11110223
Authors: Cooper P. Corey Jason C. Senkbeil
Tornadoes present an undisputable danger to communities throughout the United States. Despite this known risk, there is a limited understanding of how tornado frequency varies spatially at the mesoscale across county or city area domains. Furthermore, while previous studies have examined the relationships between various climate indices and continental or regional tornado frequency, little research has examined their influence at a smaller scale. This study examines the relationships between various climate indices and regional tornado frequency alongside the same relationships at the mesoscale in seven cities with anomalous tornado patterns. The results of a correlation analysis and generalized linear modeling show common trends between the regions and cities. The strength of the relationships varied by region, but, overall, the ENSO had the greatest influence on tornado frequency, followed in order by the PNA, AO, NAO, MJO, and PDO. However, future research is critical for understanding how the effects of climate indices on tornado frequency vary at different spatial scales, or whether other factors are responsible for the atypical tornado rates in certain cities.
]]>Climate doi: 10.3390/cli11110222
Authors: Aashutosh Aryal Rieks Bosch Venkataraman Lakshmi
The Climate Risk and Vulnerability Assessment (CRVA) is a systematic process used to identify gaps in regional climate adaptation strategies. The CRVA method assesses regional vulnerability, adaptation capacity, exposure, and sensitivity to climate change to support improved adaptation policies. This CRVA study assesses Georgia’s climate exposure, geographic sensitivity, and socio-economic sensitivity by focusing on the impacts of climate change on regional hydrology. The projected change in climate extreme indices, defined by the Expert Team on Climate Change Detection and Indices (ETCCDI), is assessed against the 1961–1990 baseline under future Representative Concentration Pathway (RCP) scenarios. These indices encompass various climate factors such as the maximum daily temperature, warmth duration, total precipitation, heavy and extreme precipitation, maximum 5-day precipitation, and consecutive drought duration. This evaluation helps us understand the potential climate exposure impacts on Georgia. The climate-induced geographic sensitivity is examined based on water stress, drought risk, and changes in soil productivity using the Normalized Difference Vegetation Index (NDVI). The climate-induced socio-economic sensitivity is determined using the Gross Domestic Product per capita (GDP), Human Development Index, Education Index, and population density. The highest vulnerability to climate change was found in the Kakheti and Kvemo Kartli regions, with the vulnerability index values ranging from 6 to 15, followed by Mtskheta-Mtianeti, Samtskhe–Javakheti, and Shida Kartli with vulnerability index values ranging from 2 to 8. The location of these regions upstream of the Alazani-Iori, Khrami-Debeda, and Mktvari river basins indicates that the country’s water resources are vulnerable to climate change impacts in the future under the RCP 4.5 and 8.5 scenarios.
]]>Climate doi: 10.3390/cli11110221
Authors: Dilshani Sarathchandra Kristin Haltinner
Resistance to clean energy policy in the United States stems partly from public hesitancy and skepticism toward anthropogenic climate change. This article examines self-declared climate change skeptics’ views of clean energy policy along a continuum of skeptical thought, spanning from epistemic denial to attribution doubt. To perform this, we use data from an online survey administered in the US Pacific Northwest and a series of pilot interviews conducted with skeptics in the same region. Results reveal that skeptics’ support for clean energy policy is consistently linked with their environmental concern across the skepticism continuum. Conspiracy ideation and distrust in science lead to a reduction in support. However, the positive effect of environmental concern trumps the effects of these beliefs. Important and hopeful implications of these findings for climate change communication and policy are discussed.
]]>Climate doi: 10.3390/cli11110220
Authors: Anirban Mahata Rajendra Mohan Panda Padmanava Dash Ayusmita Naik Alok Kumar Naik Sharat Kumar Palita
Understanding the factors that influence the diversity and distribution of butterfly species is crucial for prioritizing conservation. The Eastern Ghats of India is an ideal site for such a study, where butterfly diversity studies have yet to receive much attention. This study emphasized the butterfly assemblages of three prominent habitats in the region: open forests, riparian forests, and dense forests. We hypothesized that riparian forests would be the most preferred habitat for the butterflies, as they provide suitable microclimatic conditions for butterflies. The study collected samples for 35 grids of 2 × 2 km2 for each habitat during the dry months (December–June). We considered the relative humidity, temperature, light intensity, elevation, and canopy cover to assess their influences on butterfly richness and abundance. We also considered the impact of disturbances on their distribution. We used structural equation modeling and canonical correspondence analysis to quantify the correlation and causation between the butterflies and their environment. The study recorded 1614 individual butterflies of 79 species from 57 genera and 6 families. During the study, we found that temperature was the most significant factor influencing butterfly richness. Relative humidity was also important and had a positive impact on butterfly richness. Riparian forests, where daytime temperatures are relatively low, were the most preferred microhabitat for butterflies. Open forests had greater species diversity, indicating the critical significance of an open canopy for butterflies. Though riparian forests need greater attention concerning butterfly distribution, maintaining open and dense forests are crucial for preserving butterfly diversity.
]]>Climate doi: 10.3390/cli11110219
Authors: Han Ling Guangyu Wang Wanli Wu Anil Shrestha John L. Innes
The grasslands of North America are threatened by woody encroachment. Restoring historical fire regimes has been used to manage brush encroachment. However, fire management may be insufficient due to the nonlinear and hysteretic responses of vegetation recovery following encroachment and the social–political constraints affecting fire management. We synthesized the fire thresholds required to control woody encroachment by typical encroaching species in North America, especially the Great Plains region, and identified the social–political constraints facing fire management in selected grassland national parks. Our synthesis revealed the resistance, hysteresis, and irreversibility of encroached grasslands using fire and emphasized the need for a combination of brush management methods if the impacts of climate change are to be addressed. Frequent fires alone may maintain grassland states, reflecting resistance. However, high-intensity fires exceeding fire-mortality thresholds are required to exclude non-resprouting shrubs and trees, indicating hysteresis. Fire alone may be insufficient to reverse encroachment by resprouting species, exhibiting reversibility. In practice, appropriate fire management may restore resistant grassland states. However, social–political constraints have restricted the use of frequent and high-intensity fires, thereby reducing the effectiveness of management actions to control woody encroachment of grasslands in national parks. This research proposes a resilience-based framework to manage woody encroachment in grassland national parks and similar protected areas.
]]>Climate doi: 10.3390/cli11110218
Authors: Kenneth D. Lightburn
There were errors in the original publication [...]
]]>Climate doi: 10.3390/cli11110217
Authors: Evelyn G. Shu Mariah Pope Bradley Wilson Mark Bauer Mike Amodeo Neil Freeman Jeremy R. Porter
Properties in the United States face increasing exposure to tropical storm-level winds due to climate change. Driving this increasing risk are severe hurricanes that are more likely to occur when hurricanes form in the future and the northward shift of Atlantic-formed hurricanes, increasing the estimated exposure of buildings and infrastructure to damaging winds. The wind model presented here combines open data and science by utilizing high-resolution topography, computer-modeled hurricane tracks, and property data to create hyper-local tropical cyclone wind exposure information for the Contiguous United States (CONUS) from current time to 2053 under RCP 4.5. This allows for a detailed evaluation of probable wind speeds by several return periods, probabilities of cyclonic thresholds being reached or surpassed, and a comparison of this cyclone-level wind exposure between the current year and 30 years into the future under climatic changes. The results of this research reveal extensive exposure along the Gulf and Southeastern Atlantic Coasts, with significant growing exposure in the Mid-Atlantic and Northeastern regions of the country.
]]>Climate doi: 10.3390/cli11110216
Authors: John Narh Stefanie Wehner Christian Ungruhe Andreas Eberth
People-centred reforestation is one of the ways to achieve natural climate solutions. Ghana has established a people-centred reforestation programme known as the Modified Taunya System (MTS) where local people are assigned degraded forest reserves to practice agroforestry. Given that the MTS is a people-centred initiative, socioeconomic factors are likely to have impact on the reforestation drive. This study aims to understand the role of translocal practices of remittances and visits by migrants on the MTS. Using multi-sited, sequential explanatory mixed methods and the lens of socioecological systems, the study shows that social capital and socioeconomic obligations of cash remittances from, as well as visits by migrants to their communities of origin play positive roles on reforestation under the MTS. Specifically, translocal households have access to, and use remittances to engage relatively better in the MTS than households that do not receive remittances. This shows that translocal practices can have a positive impact on the environment at the area of origin of migrants where there are people-centred environmental policies in place.
]]>Climate doi: 10.3390/cli11110215
Authors: David Dentelski Ran Damari Yanir Marmor Avner Niv Mor Roses Yonatan Dubi
Anthropogenic activity is considered a central driver of current climate change. A recent paper, studying the consensus regarding the hypothesis that the recent increase in global temperature is predominantly human-made via the emission of greenhouse gasses (see text for reference), argued that the scientific consensus in the peer-reviewed scientific literature pertaining to this hypothesis exceeds 99%. This conclusion was reached after the authors scanned the abstracts and titles of some 3000 papers and mapped them according to their (abstract) statements regarding the above hypothesis. Here, we point out some major flaws in the methodology, analysis, and conclusions of the study. Using the data provided in the study, we show that the 99% consensus, as defined by the authors, is actually an upper limit evaluation because of the large number of “neutral” papers which were counted as pro-consensus in the paper and probably does not reflect the true situation. We further analyze these results by evaluating how so-called “skeptic” papers fit the consensus and find that biases in the literature, which were not accounted for in the aforementioned study, may place the consensus on the low side. Finally, we show that the rating method used in the study suffers from a subjective bias which is reflected in large variations between ratings of the same paper by different raters. All these lead to the conclusion that the conclusions of the study does not follow from the data.
]]>Climate doi: 10.3390/cli11110214
Authors: William L. Baker
Temperate conifer forests stressed by climate change could be lost through tree regeneration decline in the interior of high-severity fires, resulting in type conversion to non-forest vegetation from seed-dispersal limitation, competition, drought stress, and reburns. However, is fire triggering this global change syndrome at a high rate? To find out, I analyzed a worst-case scenario. I calculated fire rotations (FRs, expected period to burn once across an area) across ~56 million ha of forests (~80% of total forest area) in 11 western USA states from 2000 to 2020 for total high-severity fire area, interior area (>90 m inward), and reburned area. Unexpectedly, there was no trend in area burned at high severity from 2000 to 2020 across the four forest types studied. The vulnerable interior area averaged only 21.9% of total high-severity fire area, as 78.1% of burned area was within 90 m of live seed sources where successful tree regeneration is likely. FRs averaged 453 years overall, 2089 years in interiors, and 19,514 years in reburns. Creation of vulnerable interior area in a particular location is thus, on average, a 2000+ year event, like a very rare natural disaster, and reburns that may favor type conversion to non-forest have almost no effect. This means that, from 2021 to 2050 at most, only 3.0–4.2% of total forest area may become a vulnerable interior area, based on a likely high aridity-based climate projection of future fire and a higher scenario, where rates in the exceptional 2020 fire year have become the norm. These findings show that increased management to reduce high-severity fires is not currently needed, as the risk to forests from this global change syndrome is likely quite low up to 2050. Faster and larger disturbances (e.g., severe droughts) are more likely to cause most tree mortality or forest loss that occurs by 2050.
]]>Climate doi: 10.3390/cli11110213
Authors: Nicole C. R. Ferreira Sin C. Chou Claudine Dereczynski
Water conflicts have been a significant issue in Brazil, especially in the Sao Francisco River basin. Subseasonal forecasts, up to a 60-day forecast range, can provide information to support decision-makers in managing water resources in the river basin, especially before drought events. This report aims to evaluate 5-year mean subseasonal simulations generated by the Eta regional model for the period from 2011 to 2016 and assess the usefulness of this information to support decision-making in water resource conflicts in the Sao Francisco River basin. The capability of the Eta model to reproduce the drought events that occurred between the years 2011 and 2016 was compared against the Climate Prediction Center Morphing (CMORPH) precipitation data. Two sets of 60-day simulations were produced: one started in September (SO) and the other in January (JF) of each year. These months were chosen to evaluate the model’s capability to reproduce the onset and the middle of the rainy seasons in central Brazil, where the upper Sao Francisco River is located. The SO simulations reproduced the observed spatial distribution of precipitation but underestimated the amounts. Precipitation errors exhibited large variability across the subbasins. The JF simulations also reproduced the observed precipitation distribution but overestimated it in the upper and lower subbasins. The JF simulations better captured the interannual variability in precipitation. The 60-day simulations were discretized into six 10-day accumulations to assess the intramonthly variability. They showed that the simulations captured the onset of the rainy season and the small periods of rainy months that occurred in these severe drought years. This research is a critical step to indicate subbasins where the model simulation needs to be improved and provide initial information to support water allocation in the region.
]]>Climate doi: 10.3390/cli11100212
Authors: Degefie Tibebe Mekonnen Adnew Degefu Woldeamlak Bewket Ermias Teferi Greg O’Donnell Claire Walsh
Spatiotemporal climate variability is a leading environmental constraint to the rain-fed agricultural productivity and food security of communities in the Abbay basin and elsewhere in Ethiopia. The previous one-size-fits-all approach to soil and water management technology targeting did not effectively address climate-induced risks to rain-fed agriculture. This study, therefore, delineates homogenous climatic regions and identifies climate-induced risks to rain-fed agriculture that are important to guide decisions and the selection of site-specific technologies for green water management in the Abbay basin. The k-means spatial clustering method was employed to identify homogenous climatic regions in the study area, while the Elbow method was used to determine an optimal number of climate clusters. The k-means clustering used the Enhancing National Climate Services (ENACTS) daily rainfall, minimum and maximum temperatures, and other derived climate variables that include daily rainfall amount, length of growing period (LGP), rainfall onset and cessation dates, rainfall intensity, temperature, potential evapotranspiration (PET), soil moisture, and AsterDEM to define climate regions. Accordingly, 12 climate clusters or regions were identified and mapped for the basin. Clustering a given geographic region into homogenous climate classes is useful to accurately identify and target locally relevant green water management technologies to effectively address local-scale climate-induced risks. This study also provided a methodological framework that can be used in the other river basins of Ethiopia and, indeed, elsewhere.
]]>Climate doi: 10.3390/cli11100210
Authors: Martin Mozny Lenka Hajkova Vojtech Vlach Veronika Ouskova Adela Musilova
Changes in climatic conditions increase risks associated with crop production in certain regions. Early detection of these changes enables the implementation of suitable adaptation measures in the local area, thereby stabilising agricultural production. Our analysis shows a significant shift in climatic conditions in Czechia between 1961 and 2020. We examined the changes in observed temperature conditions, precipitation distribution, drought occurrences, and frost incidents at a high resolution (0.5 × 0.5 km). The outputs show a significant increase in air temperatures and drought occurrence. Temperature totals above 5 °C in 1991–2020 were 15% higher than in 1961–1990. Furthermore, the relative change in totals above 10 °C was 26% after 1991. Over the last 30 years, drought incidence was four times more frequent than in 1961–1990, particularly in spring. In contrast, no significant changes in the distribution of precipitation occurred, and there was a slight decrease in the probability of frost during the growing season. Ongoing climate change brings warmer and drier conditions to higher-altitude regions in Czechia. Assessing climatic conditions on a global scale is less precise for relatively small and topographically diverse countries like Czechia due to coarse resolution. Therefore, a high-resolution analysis is more appropriate for these countries.
]]>Climate doi: 10.3390/cli11100211
Authors: Bruce Kelly da Nóbrega Silva Rafaela Lisboa Costa Fabrício Daniel dos Santos Silva Mário Henrique Guilherme dos Santos Vanderlei Helder José Farias da Silva Jório Bezerra Cabral Júnior Djailson Silva da Costa Júnior George Ulguim Pedra Aldrin Martin Pérez-Marin Cláudio Moisés Santos e Silva
Agriculture is the world’s main economic activity. According to the Intergovernmental Panel on Climate Change, this activity is expected to be impacted by drought. In the Northeast region of Brazil (NEB), most agricultural activity is carried out by small rural communities. Local socio-economic data were analyzed using multivariate statistical techniques in this study to determine agricultural sensitivity to drought events (SeA) and agricultural vulnerability to drought extremes (VaED). The climate data used to develop the risk factor (Rdrought) were the drought indicator with the Standard Precipitation Index (SPI) and the average number of drought disasters from 1991 to 2012. Conditional probability theory was applied to determine agricultural vulnerability to drought extremes (VaED). Characterization of the risk of agricultural drought using the proposed methodology showed that the rainy season presents high risk values in the central region, covering areas of the states of Ceará, Piauí, Pernambuco and Rio Grande do Norte, as well as all areas of the semi-arid region. The risk ranged from high to medium. The results also indicated that part of the south of Bahia and the west of Pernambuco have areas of extreme agro-climatic sensitivity. Consequently, these states have an extreme degree of climate vulnerability during the region’s rainy season.
]]>Climate doi: 10.3390/cli11100209
Authors: Tahimy Fuentes-Alvarez Pedro M. González-Jardines José C. Fernández-Alvarez Laura de la Torre Juan A. Añel
The Gálvez–Davison Index (GDI) is an atmospheric stability index recently developed to improve the prediction of thunderstorms and shallower types of moist convection in the tropics. Because of its novelty, its use for tropical regions remains largely unexplored. Cuba is a region that suffers extreme weather events, such as tropical storms and hurricanes, some of them worsened by climate change. This research analyzes the effectiveness of the GDI in detecting the potential for convective cloud development, using forecast data from the Weather Research and Forecasting (WRF) model for Western Cuba. To accomplish this, here, we evaluated the performance of the GDI in ten study cases from the dry and wet seasons. As part of our study, we researched how GDI correlates with brightness temperatures (BTs) measured using GOES-16. In addition, the GDI results with the WRF model are compared with results using the Global Forecast System (GFS). Our results show a high correlation between the GDI and BT, concluding that the GDI is a robust tool for forecasting both synoptic and mesoscale convective phenomena over the region studied. In addition, the GDI is able to adequately forecast stability conditions. Finally, the GDI values computed from the WRF model perform much better than those from the GFS, probably because of the greater horizontal resolution in the WRF model.
]]>Climate doi: 10.3390/cli11100208
Authors: Eliseu Oliveira Afonso Sin Chan Chou
The objective of this work was to study climate variability and its impacts on the temperature of Sobradinho Lake in Northeast Brazil. Surface weather station data and lake measurements were used in this study. The model applied in this work is FLake, which is a one-dimensional model used to simulate the vertical temperature profile of freshwater lakes. First, the climate variability around Sobradinho Lake was analyzed. Observations showed a reduction in precipitation during 1991–2020 compared to 1981–2010. To study climate variability impacts on Sobradinho Lake, the years 2013, 2015, and 2020 were selected to characterize normal, dry, and rainy years, respectively. In addition, the months of January, April, July, and October were analyzed for rainy months, rainy–dry transitions, dry months, and dry–rainy transitions. Dry years showed higher incoming solar radiation at the surface and, consequently, higher 2 m air temperatures. A characteristic of the normal years was more intense surface winds. October presented the highest incoming solar radiation, the highest air temperature, and the most intense winds at the surface. The lowest incoming solar radiation at the surface was observed in January, and the lightest wind was observed in April. To assess the effects of these atmospheric conditions on the thermodynamics of Sobradinho Lake, the FLake model was forced using station observation data. The thermal amplitude of the lake surface temperature (LST) varied by less than 1 °C during the four months. This result was validated against surface lake observations. FLake was able to accurately reproduce the diurnal cycle variation in sensible heat fluxes (H), latent heat fluxes, and momentum fluxes. The sensible heat flux depends directly on the difference between the LST and the air temperature. During daytime, however, Flake simulated negative values of H, and during nighttime, positive values. The highest values of latent heat flux were simulated during the day, with the maximum value was simulated at 12:00 noon. The momentum flux simulated a similar pattern, with the maximum values simulated during the day and the minimum values during the night. The FLake model also simulated the deepest mixing layer in the months of July and October. However, our results have limitations due to the lack of observed data to validate the simulations.
]]>Climate doi: 10.3390/cli11100207
Authors: Callum F. Thompson Charles Jones Leila Carvalho Anna T. Trugman Donald D. Lucas Daisuke Seto Kevin Varga
Surface winds over California can compound fire risk during autumn, yet their long-term trends in the face of decadal warming are less clear compared to other climate variables like temperature, drought, and snowmelt. To determine where and how surface winds are changing most, this article uses multiple reanalyses and Remote Automated Weather Stations (RAWS) to calculate autumn 10 m wind speed trends during 1979–2020. Reanalysis trends show statistically significant increases in autumn night-time easterlies on the western slopes of the Sierra Nevada. Although downslope windstorms are frequent to this region, trends instead appear to result from elevated gradients in warming between California and the interior continent. The result is a sharper horizontal temperature gradient over the Sierra crest and adjacent free atmosphere above the foothills, strengthening the climatological nocturnal katabatic wind. While RAWS records show broad agreement, their trend is likely influenced by year-to-year changes in the number of observations.
]]>Climate doi: 10.3390/cli11100206
Authors: Daria Gushchina Maria Tarasova Elizaveta Satosina Irina Zheleznova Ekaterina Emelianova Ravil Gibadullin Alexander Osipov Alexander Olchev
Forest ecosystems in the mid-latitudes of the Northern Hemisphere are significantly affected by frequent extreme weather events. How different forest ecosystems respond to these changes is a major challenge. This study aims to assess differences in the response of daily net ecosystem exchange (NEE) of CO2 and latent heat flux (LE) between different boreal and temperate ecosystems and the atmosphere to extreme weather events (e.g., anomalous temperature and precipitation). In order to achieve the main objective of our study, we used available reanalysis data and existing information on turbulent atmospheric fluxes and meteorological parameters from the global and regional FLUXNET databases. The analysis of NEE and LE responses to high/low temperature and precipitation revealed a large diversity of flux responses in temperate and boreal forests, mainly related to forest type, geographic location, regional climate conditions, and plant species composition. During the warm and cold seasons, the extremely high temperatures usually lead to increased CO2 release in all forest types, with the largest response in coniferous forests. The decreasing air temperatures that occur during the warm season mostly lead to higher CO2 uptake, indicating more favorable conditions for photosynthesis at relatively low summer temperatures. The extremely low temperatures in the cold season are not accompanied by significant NEE anomalies. The response of LE to temperature variations does not change significantly throughout the year, with higher temperatures leading to LE increases and lower temperatures leading to LE reductions. The immediate response to heavy precipitation is an increase in CO2 release and a decrease in evaporation. The cumulative effect of heavy precipitations is opposite to the immediate effect in the warm season and results in increased CO2 uptake due to intensified photosynthesis in living plants under sufficient soil moisture conditions.
]]>Climate doi: 10.3390/cli11100205
Authors: Zili Xiong Wei Shangguan Vahid Nourani Qingliang Li Xingjie Lu Lu Li Feini Huang Ye Zhang Wenye Sun Hua Yuan Xueyan Li
Land carbon fluxes play a critical role in ecosystems, and acquiring a comprehensive global database of carbon fluxes is essential for understanding the Earth’s carbon cycle. The primary methods of obtaining the spatial distribution of land carbon fluxes include utilizing machine learning models based on in situ measurements, estimating through satellite remote sensing, and simulating ecosystem models. Recently, an innovative machine learning product known as the Global Carbon Flux Dataset (GCFD) has been released. In this study, we assessed the reliability of the GCFD by comparing it with existing data products, including two machine learning products (FLUXCOM and NIES (National Institute for Environmental Studies)), two ecosystem model products (TRENDY and EC-LUE (eddy covariance–light use efficiency model)), and one remote sensing product (Global Land Surface Satellite), on both site and global scales. Our findings indicate that, in terms of average absolute difference, the spatial distribution of the GCFD is most similar to the NIES product, albeit with slightly larger discrepancies compared to the other two types of products. When using site observations as the benchmark, gross primary production (GPP), respiration of ecosystem (RECO), and net ecosystem exchange of machine learning products exhibit higher R2 (ranging from 0.57 to 0.85, 0.53–0.79, and 0.31–0.70, respectively) compared to model products and remote sensing products. Furthermore, we analyzed the spatial and temporal distribution characteristics of carbon fluxes in various regions. The results demonstrate an upward trend in both GPP and RECO over the past two decades, while NEE exhibits an opposite trend. This trend is particularly pronounced in tropical regions, where higher GPP is observed in tropical, subtropical, and oceanic climate zones. Additionally, two remote sensing variables that influence changes in carbon fluxes, i.e., fraction absorbed photosynthetically active radiation and leaf area index, exhibit relatively consistent spatial and temporal characteristics. Overall, our study can provide valuable insights into different types of carbon flux products and contribute to understanding the general features of global carbon fluxes.
]]>Climate doi: 10.3390/cli11100204
Authors: Yadanar Kyaw Thi Phuoc Lai Nguyen Ekbordin Winijkul Wenchao Xue Salvatore G. P. Virdis
Agriculture, entwined with climatic conditions, plays a pivotal role in Thailand’s sustenance and economy. This study aimed to examine the trends of climate variability and its correlation with crop yields and social and farm factors affecting farm net income in Chiang Mai province, Thailand. Time series climate data (2002–2020) on temperature and rainfall and yields were analyzed using the Mann–Kendall trend test and Sen’s slope estimation to investigate the trends and their changes. The Pearson correlation was used to assess the association between climate variability and cultivated crop yields, and multiple linear regression was used to detect the factors influencing the farm net income. The findings show that the total annual rainfall showed an unchanged trend, but the annual temperature increased over time. Higher temperature negatively impacted longan yield but positively affected maize, with no significant impact on rice yield. The rainfall trend had no effect on crop yields. Despite declining trends in some cultivated crops’ yield, farm net income was unaffected by individual crop types. Farm income relied on cumulative output and geographic location. This research emphasizes the need for integrating climate data and forecasting models considering agronomic and socio-economic factors and crop suitability assessments for specific regions into adaptation policies and practice.
]]>Climate doi: 10.3390/cli11100203
Authors: Ilaria Perissi Davide Natalini Aled Jones
The European Green Deal comprises various policy initiatives with the goal of reaching carbon neutrality by 2050. The “Fit for 55 packages” include the Social Climate Fund, which aims to help, among others, vulnerable households and transport users meet the costs of the green energy transition. Thus, analyzing households’ expenditures and the associated carbon emissions is crucial to achieving a net-zero society. In the present study, we combine scenarios of households’ expenditures according to the Classification of Individual Consumption According to Purpose with economic decoupling scenarios to assess, for the first time, the European carbon budget allocation on a consumption basis. Expenditure projections based on socioeconomic scenarios were calculated using the Bayesian structural time series, and the associated emissions were estimated through the greenhouse gas intensity of the Gross Domestic Product. The model can be used to report the carbon budget of households and monitor the effectiveness of the measures funded by the Social Climate Fund. However, the emissions burden obtained by means of averaged greenhouse gas intensity of Gross Domestic Product results in a rough approximation of outcomes, and more accurate indicators should be developed across the member states.
]]>Climate doi: 10.3390/cli11100202
Authors: Elena Grigorieva Alexandra Livenets Elena Stelmakh
Since agricultural productivity is weather and climate-related and fundamentally depends on climate stability, climate change poses many diverse challenges to agricultural activities. The objective of this study is to review adaptation strategies and interventions in countries around the world proposed for implementation to reduce the impact of climate change on agricultural development and production at various spatial scales. A literature search was conducted in June–August 2023 using electronic databases Google Scholar and Scientific Electronic Library eLibrary.RU, seeking the key words “climate”, “climate change”, and “agriculture adaptation”. Sixty-five studies were identified and selected for the review. The negative impacts of climate change are expressed in terms of reduced crop yields and crop area, impacts on biotic and abiotic factors, economic losses, increased labor, and equipment costs. Strategies and actions for agricultural adaptation that can be emphasized at local and regional levels are: crop varieties and management, including land use change and innovative breeding techniques; water and soil management, including agronomic practices; farmer training and knowledge transfer; at regional and national levels: financial schemes, insurance, migration, and culture; agricultural and meteorological services; and R&D, including the development of early warning systems. Adaptation strategies depend on the local context, region, or country; limiting the discussion of options and measures to only one type of approach—"top-down” or “bottom-up”—may lead to unsatisfactory solutions for those areas most affected by climate change but with few resources to adapt to it. Biodiversity-based, or “ecologically intensive” agriculture, and climate-smart agriculture are low-impact strategies with strong ecological modernization of agriculture, aiming to sustainably increase agricultural productivity and incomes while addressing the interrelated challenges of climate change and food security. Some adaptation measures taken in response to climate change may not be sufficient and may even increase vulnerability to climate change. Future research should focus on adaptation options to explore the readiness of farmers and society to adopt new adaptation strategies and the constraints they face, as well as the main factors affecting them, in order to detect maladaptation before it occurs.
]]>Climate doi: 10.3390/cli11100201
Authors: Benedito Cláudio da Silva Rebeca Meloni Virgílio Luiz Augusto Horta Nogueira Paola do Nascimento Silva Filipe Otávio Passos Camila Coelho Welerson
Study region: The Três Marias 396 MW power plant located on the São Francisco River in Brazil. Study focus: Hydropower generation is directly and indirectly affected by climate change. It is also a relevant source of energy for electricity generation in many countries. Thus, methodologies need to be developed to assess the impacts of future climate scenarios. This is essential for effective planning in the energy sector. Energy generation at the Três Marias power plant was estimated using the water balance of the reservoir and the future stream flow projections to the power plant, for three analysis periods: FUT1 (2011–2040); FUT2 (2041–2070); and FUT3 (2071–2100). The MGB-IPH hydrological model was used to assimilate precipitation and other climatic variables from the regional Eta climatic model, via global models HadGEM2-ES and MIROC5 for scenarios RCP4.5 and RCP8.5. New hydrological insights for the region: The results show considerable reductions in stream flows and consequently, energy generation simulations for the hydropower plant were also reduced. The average power variations for the Eta-MIROC5 model were the mildest, around 7% and 20%, while minimum variations for the Eta-HadGEM2-ES model were approximately 35%, and almost 65% in the worst-case scenario. These results reinforce the urgent need to consider climate change in strategic Brazilian energy planning.
]]>Climate doi: 10.3390/cli11100200
Authors: Mikhail Varentsov Mikhail Krinitskiy Victor Stepanenko
This study considers the problem of approximating the temporal dynamics of the urban-rural temperature difference (ΔT) in Moscow megacity using machine learning (ML) models and predictors characterizing large-scale weather conditions. We compare several ML models, including random forests, gradient boosting, support vectors, and multi-layer perceptrons. These models, trained on a 21-year (2001–2021) dataset, successfully capture the diurnal, synoptic-scale, and seasonal variations of the observed ΔT based on predictors derived from rural weather observations or ERA5 reanalysis. Evaluation scores are further improved when using both sources of predictors simultaneously and involving additional features characterizing their temporal dynamics (tendencies and moving averages). Boosting models and support vectors demonstrate the best quality, with RMSE of 0.7 K and R2 > 0.8 on average over 21 years. For three selected summer and winter months, the best ML models forced only by reanalysis outperform the comprehensive hydrodynamic mesoscale model COSMO, supplied by an urban canopy scheme with detailed city-descriptive parameters and forced by the same reanalysis. However, for a longer period (1977–2023), the ML models are not able to fully reproduce the observed trend of ΔT increase, confirming that this trend is largely (by 60–70%) driven by megacity growth. Feature importance assessment indicates the atmospheric boundary layer height as the most important control factor for the ΔT and highlights the relevance of temperature tendencies as additional predictors.
]]>Climate doi: 10.3390/cli11100199
Authors: Yuo-Hsien Shiau Su-Fen Yang Rishan Adha Giia-Sheun Peng Syamsiyatul Muzayyanah
The diurnal temperature range (DTR) is a significant indicator of climate change, and a previous study has shown its impact on human health. However, research investigating the influence of DTR on road traffic accidents is scarce. Thus, this study aims to evaluate the impact of changes in DTR on road traffic accidents. The present study employs two methods to address the complexities of road accidents. Firstly, panel data from 20 cities and counties in Taiwan are utilized, and the autoregressive distributed lag (ARDL) model is employed for estimation. Secondly, distributed lag non-linear models (DLNMs) are used with quasi-Poisson regression analysis to assess the DTR’s lagged and non-linear relationships with road accidents using time series data from six Taiwanese metropolitan cities. The study results indicate that a decrease of 1 °C in DTR raises long-term road traffic accidents by 17.1%. In the short term, the impact of declining DTR on road accidents is around 4%. Moreover, the effect of low DTR values differs in each city in Taiwan. Three cities had high levels of road accidents, as evidenced by an increase in the relative risk value; two cities had moderate responses; and one city had a relatively lower response compared to high DTR values. Finally, based on the cumulative relative risk estimations, the study found that a low diurnal temperature range is linked to a high road traffic accident rate, especially during the lag-specific 0–5 months. The findings of this study offer fresh evidence of the negative impact of climate factor on road traffic accidents.
]]>Climate doi: 10.3390/cli11100198
Authors: Andrew Ezra Kai Zhu Lóránt Dénes Dávid Barnabas Nuhu Yakubu Krisztian Ritter
The impact of climate change on river systems is a multifaceted threat to the environment, affecting various aspects of ecosystems. The Upper Benue River Basin (UBRB) in Nigeria is an area of concern, as river flow and water levels are crucial for irrigation and transportation. In this study, we investigate the impact of climate change on the hydrology of the UBRB using data on rainfall, temperature, relative humidity, wind speed, river discharge, and water level. Trend, correlation, and stepwise regression analyses were conducted using Excel and SPSS 20 to analyze the data. The results indicate that the UBRB is experiencing climate change, as evidenced by annual decreases in rainfall and relative humidity and increases in maximum and minimum temperatures. Specifically, mean annual rainfall and relative humidity exhibit a negative trend, while the maximum and minimum temperature exhibit a positive trend. Furthermore, we found that rainfall and relative humidity have a significant positive relationship with river discharge and level (p < 0.01), whereas maximum temperature and wind speed have a significant negative relationship with water discharge and level. We also identified wind speed and rainfall as the critical climatic indices influencing river discharge, accounting for 21.7% of the variation in river discharge within the basin (R2 = 21.7). Based on these findings, we conclude that increases in rainfall and relative humidity will lead to significant increases in river discharge and level, while increases in wind speed and maximum temperature will decrease river discharge and level. Moreover, wind speed and rainfall are the critical climatic indices influencing river discharge, whereas relative humidity, wind speed, and rainfall are the critical climatic indices influencing water level. Thus, we recommend constructing more reservoirs (dams) to mitigate the negative trend in rainfall and encourage climate change control, such as afforestation among the population of the region. These findings have important implications for understanding the impact of climate change on river systems and developing effective strategies to mitigate its effects.
]]>Climate doi: 10.3390/cli11100197
Authors: Bethune Carmichael Cathy Daly Sandra Fatorić Mark Macklin Sue McIntyre-Tamwoy Witiya Pittungnapoo
Significant riverine archaeological sites around the world are vulnerable to flooding associated with climate change. However, identifying sites most at risk is not straightforward. We critically review the parameters used in 22 published analyses of risk to riverine archaeology from climate change (ARRACC). Covering 17 countries globally, the ARRACC’s risk parameters are highly variable. Proximity to rivers and projected changes to extreme flood frequency are the most commonly employed. However, to be robust, future ARRACC should select from a wider range of hazard parameters, including channel mobility/type, erosion/sedimentation patterns, land use and engineering works, as well as parameters for site sensitivity to flooding and heritage significance. To assist in this, we propose a basic field survey for ARRACC, to be treated primarily as a conceptual checklist or as a starting point for a bespoke ARRACC method adapted for a particular river and the objectives of local stakeholders. The framework proposes a pathway to optimal prioritisation of sites most in need of adaptation so that scarce management resources can be targeted.
]]>Climate doi: 10.3390/cli11090196
Authors: Samuel Chukwujindu Nwokolo Edson L. Meyer Chinedu Christian Ahia
This paper seeks to address Nigeria’s challenges in meeting its climate objectives by investigating feasible pathways that can be implemented to accelerate progress and ensure credibility in meeting these targets. By examining the current policies and practices in place as well as successful strategies employed by other countries, this paper aims to provide strategies and policy implications recommendations for Nigeria to enhance its climate action efforts. The potential scenarios developed in this study ranged from increasing renewable energy capacity to implementing stricter regulations and standards for industries to reduce their carbon footprint, promote sustainable production processes, and strengthen climate governance and policy frameworks. The authors further investigated these measures and discovered that implementing stricter regulations and standards for industries would reduce their carbon footprint, promote sustainable production processes, and strengthen climate governance and policy frameworks. As such, Nigeria will be able to meet its climate goals more quickly as a result of the following factors: preventing environmental degradation, funding environmentally friendly infrastructure, and improving public transportation systems that can reduce vehicle-related greenhouse gas emissions. The authors developed policy measures based on the proposed twelve credible pathways to catching up with climate goals in Nigeria, thereby promoting faster progress by the Nigerian government in achieving climate goals. By adopting these measures, Nigeria’s progress toward the proposed zero net by 2060 will be significantly accelerated. It will position Nigeria as a continental leader in sustainable development and contribute to the overall global efforts to mitigate climate change. This will not only benefit the environment but also lead to financial development and an improved standard of living for its citizens.
]]>Climate doi: 10.3390/cli11090195
Authors: Masaharu Tsuji
The Antarctica and High Arctic regions are extreme environments, with average maximum temperatures below 0 °C for most days of the year. Interestingly, fungi inhabit these regions. This review describes the history of fungal surveys near the Syowa Station and the fungal diversity in this region. In the High Arctic region, I summarize the changes in the fungal communities of the glacial retreat areas of Ny-Ålesund, Norway and Ellesmere Island, Canada, in response to climate change. In addition, the ability of Antarctic and Arctic fungi to secrete enzymes at sub-zero temperatures is presented. Finally, the future directions of Antarctic and Arctic fungal research are provided.
]]>Climate doi: 10.3390/cli11090194
Authors: Petri P. Kärenlampi
The nitrogen fertilization of boreal forests is investigated in terms of microeconomics as a tool for carbon sequestration. The effects of nitrogen fertilization’s timing on the return rate on capital and the expected value of the timber stock are investigated within a set of semi-fertile, spruce-dominated boreal stands using an inventory-based growth model. Early fertilization tends to shorten rotations, reducing timber stock and carbon storage. The same applies to fertilization after the second thinning. Fertilization applied ten years before stand maturity is profitable and increases the timber stock, but the latter effect is small. The fertilization of mature stands, extending any rotation by ten years, effectively increases the carbon stock. Profitability varies but is increased by fertilization instead of merely extending the rotation.
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