Climate, Volume 9, Issue 11 (November 2021) – 14 articles

Diversification of production to strengthen resilience is a key tenet of climate-smart agriculture (CSA), which can help to address the complex vulnerabilities of agriculture-dependent rural communities. In this study, we investigated the relationship between the promotion of different CSA practices across four climate-smart villages (CSVs) in Myanmar. To determine the impact of the CSA practices on livelihoods and health, survey data were collected from agricultural households (n = 527) over three years. Within the time period studied, the results indicate that some the CSA practices and technologies adopted were significantly associated with changes in household dietary diversity scores (HDDS), but, in the short-term, these were not associated with improvements in the households’ food insecurity scores (HFIAS). Based on the survey responses, we examined how pathways of CSA practice adoption tailored to different contexts of Myanmar’s four agroecologies could contribute to the observed changes, including possible resulting trade-offs. We highlight that understanding the impacts of CSA adoption on household food security in CSVs will require longer-term monitoring, as most CSA options are medium- to long-cycle interventions. Our further analysis of knowledge, attitudes and practices (KAPs) amongst the households indicated a poor understanding of the household knowledge, attitudes and practices in relation to nutrition, food choices, food preparation, sanitation and hygiene. Our KAP findings indicate that current nutrition education interventions in the Myanmar CSVs are inadequate and will need further improvement for health and nutrition outcomes from the portfolio of CSA interventions. Full article

This study evaluated changes in climatic variable impacts on hydrology and water quality in Big Sunflower River Watershed (BSRW), Mississippi. Site-specific future time-series precipitation, temperature, and solar radiation data were generated using a stochastic weather generator LARS-WG model. For the generation of climate scenarios, Representative Concentration Pathways (RCPs), 4.5 and 8.5 of Global Circulation Models (GCMs): Hadley Center Global Environmental Model (HadGEM) and EC-EARTH, for three (2021–2040, 2041–2060 and 2061–2080) future climate periods. Analysis of future climate data based on six ground weather stations located within BSRW showed that the minimum temperature ranged from 11.9 °C to 15.9 °C and the maximum temperature ranged from 23.2 °C to 28.3 °C. Similarly, the average daily rainfall ranged from 3.6 mm to 4.3 mm. Analysis of changes in monthly average maximum/minimum temperature showed that January had the maximum increment and July/August had a minimum increment in monthly average temperature. Similarly, maximum increase in monthly average rainfall was observed during May and maximum decrease was observed during September. The average monthly streamflow, sediment, TN, and TP loads under different climate scenarios varied significantly. The change in average TN and TP loads due to climate change were observed to be very high compared to the change in streamflow and sediment load. The monthly average nutrient load under two different RCP scenarios varied greatly from as low as 63% to as high as 184%, compared to the current monthly nutrient load. The change in hydrology and water quality was mainly attributed to changes in surface temperature, precipitation, and stream flow. This study can be useful in the development and implementation of climate change smart management of agricultural watersheds. Full article

Life cycle impact assessment (LCA) provides a better understanding of the energy, water, and material input and evaluates any production system’s output impacts. LCA has been carried out on various crops and products across the world. Some countries, however, have none or only a few studies. Here, we present the results of a literature review, following the PRISMA protocol, of what has been done in LCA to help stakeholders in these regions to understand the environmental impact at different stages of a product. The published literature was examined using the Google Scholar database to synthesize LCA research on agricultural activities, and 74 studies were analyzed. The evaluated papers are extensively studied in order to comprehend the various impact categories involved in LCA. The study reveals that tomatoes and wheat were the major crops considered in LCA. The major environmental impacts, namely, human toxicity potential and terrestrial ecotoxicity potential, were the major focus. Furthermore, the most used impact methods were CML, ISO, and IPCC. It was also found that studies were most often conducted in the European sector since most models and databases are suited for European agri-food products. The literature review did not focus on a specific region or a crop. Consequently, many studies appeared while searching using the keywords. Notwithstanding such limitations, this review provides a valuable reference point for those practicing LCA. Full article

The paper aims to quantify solar and anthropogenic influences on climate change, and to make some tentative predictions for the next hundred years. By means of double regression, we evaluate linear combinations of the logarithm of the carbon dioxide concentration and the geomagnetic aa index as a proxy for solar activity. Thereby, we reproduce the sea surface temperature (HadSST) since the middle of the 19th century with an adjusted $R^2$ value of around 87 percent for a climate sensitivity (of TCR type) in the range of 0.6 K until 1.6 K per doubling of CO${}_2$. The solution of the double regression is quite sensitive: when including data from the last decade, the simultaneous occurrence of a strong El Niño and of low aa values leads to a preponderance of solutions with relatively high climate sensitivities around 1.6 K. If these later data are excluded, the regression delivers a significantly higher weight of the aa index and, correspondingly, a lower climate sensitivity going down to 0.6 K. The plausibility of such low values is discussed in view of recent experimental and satellite-borne measurements. We argue that a further decade of data collection will be needed to allow for a reliable distinction between low and high sensitivity values. In the second part, which builds on recent ideas about a quasi-deterministic planetary synchronization of the solar dynamo, we make a first attempt to predict the aa index and the resulting temperature anomaly for various typical CO${}_2$ scenarios. Even for the highest climate sensitivities, and an unabated linear CO${}_2$ increase, we predict only a mild additional temperature rise of around 1 K until the end of the century, while for the lower values an imminent temperature drop in the near future, followed by a rather flat temperature curve, is prognosticated. Full article

Analysis of new chronological data, including 55 radiocarbon, 1 OSL, and 8 dendrochronological dates, obtained in the upper reaches of trough valleys within the Katun, North Chuya, South Chuya, and Chikhachev ranges, together with the 55 previously published ones, specifies climatically driven glacier dynamic in the Russian Altai. Available data refute the traditional concept of the Russian Altai Holocene glaciations as a consecutive retreat of the Late Pleistocene glaciation. Considerable and prolonged warming in the Early Holocene started no later than 11.3–11.4 cal kBP. It caused significant shrinking or even complete degradation of alpine glaciers and regeneration of forest vegetation 300–400 m above the modern upper timber limit. Stadial advances occurred in the middle of the Holocene (4.9–4.2 cal kBP), during the Historical (2.3–1.7 cal kBP), and the Aktru (LIA thirteenth–nineteenth century) stages. New radiocarbon ages of fossil soils limited glaciers expansion in the Middle Holocene by the size of the Historical moraine. Lesser glacial activity between 5 and 4 cal kBP is also supported by rapid reforestation in the heads of trough valleys. Glaciers advance within the Russian Altai, accompanied by accumulation of the Akkem moraine, could have occurred at the end of the Late Pleistocene. Full article

The last-generation CMIP6 global circulation models (GCMs) are currently used to interpret past and future climatic changes and to guide policymakers, but they are very different from each other; for example, their equilibrium climate sensitivity (ECS) varies from 1.83 to 5.67 °C (IPCC AR6, 2021). Even assuming that some of them are sufficiently reliable for scenario forecasts, such a large ECS uncertainty requires a pre-selection of the most reliable models. Herein the performance of 38 CMIP6 models are tested in reproducing the surface temperature changes observed from 1980–1990 to 2011–2021 in three temperature records: ERA5-T2m, ERA5-850mb, and UAH MSU v6.0 Tlt. Alternative temperature records are briefly discussed but found to be not appropriate for the present analysis because they miss data over large regions. Significant issues emerge: (1) most GCMs overestimate the warming observed during the last 40 years; (2) there is great variability among the models in reconstructing the climatic changes observed in the Arctic; (3) the ocean temperature is usually overestimated more than the land one; (4) in the latitude bands 40° N–70° N and 50° S–70° S (which lay at the intersection between the Ferrel and the polar atmospheric cells) the CMIP6 GCMs overestimate the warming; (5) similar discrepancies are present in the east-equatorial pacific region (which regulates the ENSO) and in other regions where cooling trends are observed. Finally, the percentage of the world surface where the (positive or negative) model-data discrepancy exceeds 0.2, 0.5 and 1.0 °C is evaluated. The results indicate that the models with low ECS values (for example, 3 °C or less) perform significantly better than those with larger ECS. Therefore, the low ECS models should be preferred for climate change scenario forecasts while the other models should be dismissed and not used by policymakers. In any case, significant model-data discrepancies are still observed over extended world regions for all models: on average, the GCM predictions disagree from the data by more than 0.2 °C (on a total mean warming of about 0.5 °C from 1980–1990 to 2011–2021) over more than 50% of the global surface. This result suggests that climate change and its natural variability remain poorly modeled by the CMIP6 GCMs. Finally, the ECS uncertainty problem is discussed, and it is argued (also using semi-empirical climate models that implement natural oscillations not predicted by the GCMs) that the real ECS could be between 1 and 2 °C, which implies moderate warming for the next decades. Full article

Observed rainfall data (1961–2016) were used to analyze variability, trends and changes of extreme precipitation indices over Benin. Nine indices out of the ones developed by the Expert Team on Climate Change Detection and Indices (ETCCDI) were used. The results indicate a mix of downward and upward trends for maximum 1-day precipitation (RX1day) and maximum 5-days precipitation (RX5day). Decrease trends are observed for annual total precipitation of wet days (P), while significant increases are found for the simple daily intensity index (SDII). The number of wet days (RR1) and maximum consecutive dry days (CDD) show a mix of increase/decrease trends. However, the number of heavy (R10) and very heavy (R20) wet days and maximum consecutive wet days (CWD) show decreased trends. All wet indices increased over 1991–2010 in relation to 1971–1990. The increase in all wet indices over Benin could explain the intensification of hydrology, and the increase in the frequency and the intensity of floods. It caused damages such as soil erosion, crop destruction, livestock destruction, displacement of populations, proliferation of waterborne diseases and loss of human life. Some adaptive strategies are suggested to mitigate the impacts of changes in extreme rainfall. Full article

Vesicular stomatitis (VS) is the most common vesicular livestock disease in North America. Transmitted by direct contact and by several biting insect species, this disease results in quarantines and animal movement restrictions in horses, cattle and swine. As changes in climate drive shifts in geographic distributions of vectors and the viruses they transmit, there is considerable need to improve understanding of relationships among environmental drivers and patterns of disease occurrence. Multidisciplinary approaches integrating pathology, ecology, climatology, and biogeophysics are increasingly relied upon to disentangle complex relationships governing disease. We used a big data model integration approach combined with machine learning to estimate the potential geographic range of VS across the continental United States (CONUS) under long-term mean climate conditions over the past 30 years. The current extent of VS is confined to the western portion of the US and is related to summer and winter precipitation, winter maximum temperature, elevation, fall vegetation biomass, horse density, and proximity to water. Comparison with a climate-only model illustrates the importance of current processes-based parameters and identifies regions where uncertainty is likely to be greatest if mechanistic processes change. We then forecast shifts in the range of VS using climate change projections selected from CMIP5 climate models that most realistically simulate seasonal temperature and precipitation. Climate change scenarios that altered climatic conditions resulted in greater changes to potential range of VS, generally had non-uniform impacts in core areas of the current potential range of VS and expanded the range north and east. We expect that the heterogeneous impacts of climate change across the CONUS will be exacerbated with additional changes in land use and land cover affecting biodiversity and hydrological cycles that are connected to the ecology of insect vectors involved in VS transmission. Full article

Accurate long-term daily maximum and minimum air temperature series are needed to assess the frequency, intensity, distribution, and duration of extreme climatic events. However, quality control and homogenisation procedures are required to minimise errors and inhomogeneities in climate series before the commencement of climate data analysis. A semi-automatic quality control procedure consisting of climate consistency, internal consistency, day-to-day step-change, and persistency tests was applied for 12 long-term series registered in Ireland from 1831–1968, Armagh Observatory (Northern Ireland) from 1844–2018, and for 21 short-term series dating to the mid-19th century. There were 976,786 observations quality-controlled, and 27,854 (2.9%) values flagged. Of the flagged records, 98.5% (n = 27,446) were validated, 1.4% (n = 380) corrected and 0.1% (n = 28) deleted. The historical long-term quality-controlled series were merged with the modern series quality-controlled by Met Éireann and homogenised using the software MASHv3.03 in combination with station metadata for 1885–2018. The series presented better homogenisation outcomes when homogenised as part of smaller regional networks rather than as a national network. The homogenisation of daily, monthly, seasonal, and annual series improved for all stations, and the homogenised records showed stronger correlations with the Central England long-term temperature series. Full article

All cities globally are growing considerably as they are experiencing an intensive urbanization process that leads to high soil consumption and pollution of environmental components. For this reason, cities are required to adopt measures to reduce these impacts and tree planting has been suggested as a cost-effective strategy. In our study, we implemented for the first time in a Southern Caucasus city the i-Tree Eco model to quantify the main ecosystem services provided by urban forests. Trees in two parks in Tbilisi, EXPO Park (694 trees) and RED Park (1030 trees), have been measured, and a model simulation was performed for the year 2018. These green infrastructures store large amounts of carbon in their woody tissues (198.4 t for EXPO Park and 126.5 t for RED Park) and each year they sequester 4.6 and 4.7 t of CO₂ for EXPO Park and RED Park. They also remove 119.6 and 90.3 kg of pollutants (CO, NO₂, O₃, PM_2.5, SO₂), and reduce water runoff of 269.5 and 200.5 m³, respectively. This analysis highlights the key role of urban forests in improving the environmental sustainability of the city of Tbilisi and provides important decision support for tree species selection in this geographic area. Full article

Climate variability can be the source of several multiple hazards and damaging phenomena, such as flash floods, debris flows, landslides, forest fires, etc. In this study the response in the frequency of landslides, floods and forest fires to a set of climate indices is studied, referring to a region of southern Italy (Calabria) located in the center of the Mediterranean basin, a hot-spot for climate change. For these comparisons, 5022 landslides and 1584 flood occurrences for a 29-year period (1990–2018) have been selected for the whole Calabria; the burnt areas have been analyzed for the same territory from 2008 to 2018. The climate indices have been calculated by means of daily rainfall and temperature data registered in 93 stations. The results showed that landslide occurrences are more linked with climate indices describing not very intense rainfall. Conversely, floods show best matches with climate indices representative of more extreme precipitation. Regarding the burnt areas, the results confirmed that very dry climate conditions, modifying the moisture content of the soil, can change the intensity and the extension of fires. Full article

The 29–30 June 2012 “super” derecho was, up until the 10 August 2020 “Iowa Derecho”, the most prolific derecho of modern times. While many of the synoptic-scale precursors to derecho events are understood, the multi-scale dynamics which likely distinguish derecho-producing events versus non-derecho events remain much more elusive. Using both observations and high-resolution WRF-ARW simulations, the sequence of adjustments that ultimately set up the pre-29 June derecho environment are examined. Planetary scale Rossby wave breaking occurred almost exactly two weeks before the super derecho on 15–16 June 2012 resulting in the development and intensification of a strong high-pressure system and mixed layer over the complex terrain of the western United States. A week after the initial Rossby wave break (~23 June), daily record-breaking temperatures began to dominate much of the central U.S. as the mixed layer/high pressure continued to strengthen. A second Rossby wave break on 26 June was crucial for detaching the mixed layer from the western U.S. elevated plateau, creating an elevated mixed layer that was rapidly deformed and propagated downstream to set up the derecho environment between 27–29 June. On 28 June, flow imbalance at the elevated mixed layer front resulted in highly ageostrophic circulations in the mid-levels, generating an along-stream mid-level jetlet which ultimately moved the elevated mixed layer and associated mesoscale front downstream across the Midwest and Mid-Atlantic. On the morning of 29 June, a well-defined corridor of both potential static instability and lowered inertial stability was set up across the Midwest and Mid-Atlantic states. This along with strong capping, a divergent polar jet entrance region to the north, and the highly imbalanced mid-level jetlet set the stage for this prolific severe convective event. Full article

Fluctuations of the weather conditions, due to global climate change, greatly influence plant growth and development, eventually affecting crop yield and quality, but also plant survival. Since water shortage is one of the key risks for the future of agriculture, exploring the capability of crop species to grow with limited water is therefore fundamental. By using chlorophyll fluorescence analysis, we evaluated the responses of wild tomato accession Solanum pennellii LA0716, Solanum lycopersicum cv. Μ82, the introgression line IL12-4 (from cv. M82 Χ LA0716), and the Greek tomato cultivars cv. Santorini and cv. Zakinthos, to moderate drought stress (MoDS) and severe drought stress (SDS), in order to identify the minimum irrigation level for efficient photosynthetic performance. Agronomic traits (plant height, number of leaves and root/shoot biomass), relative water content (RWC), and lipid peroxidation, were also measured. Under almost 50% deficit irrigation, S. pennellii exhibited an enhanced photosynthetic function by displaying a hormetic response of electron transport rate (ETR), due to an increased fraction of open reaction centers, it is suggested to be activated by the low increase of reactive oxygen species (ROS). A low increase of ROS is regarded to be beneficial by stimulating defense responses and also triggering a more oxidized redox state of quinone A (Q_A), corresponding in S. pennellii under 50% deficit irrigation, to the lowest stomatal opening, resulting in reduction of water loss. Solanumpennellii was the most tolerant to drought, as it was expected, and could manage to have an adequate photochemical function with almost 30% water regime of well-watered plants. With 50% deficit irrigation, cv. Μ82 and cv. Santorini did not show any difference in photochemical efficiency to control plants and are recommended to be cultivated under deficit irrigation as an effective strategy to enhance agricultural sustainability under a global climate change. We conclude that instead of the previously used Fv/Fm ratio, the redox state of Q_A, as it can be estimated by the chlorophyll fluorescence parameter 1 - q_L, is a better indicator to evaluate photosynthetic efficiency and select drought tolerant cultivars under deficit irrigation. Full article

Climate change impact assessment is crucial for strategic planning in many areas, including water management, agriculture and forestry. Water planning has a long tradition in the Czech Republic, who has implemented the requirements of the Water Framework Directive since 2000. Following the expected impacts of climate change on the hydrological regime, adaptation measures in the water sector are being prepared as part of strategic plans. This contribution studies the uncertainty propagation of climate scenarios in hydrological data, which are then used to assess the reliability of water resources and to design appropriate adaptation measures. The results are being discussed for a case study in the deficit area of Rakovnický stream and Blšanska river basins, which are among the driest areas in the Czech Republic. Research of the impact of climate change on the reliability of water resources has been prepared using ensembles of selected regional climate models. This approach has allowed a probabilistic assessment of the impact on the hydrology regime and the reliability of water supply from reservoirs for various time horizons of climate change. In view of the relatively large variance of potential impacts on water resources, options for further strategic planning in the water management area are being discussed. Full article