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Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales

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A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 38015

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Special Issue Editors

Dr. Ankit Agarwal

E-Mail Website1 Website2
Guest Editor

1. Department of Hydrology, Indian Institute of Technology (IIT) Roorkee, Uttarakhand 247667, India
2. Visiting Scientist at Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, section 4.4 Hydrology, 14473 Potsdam, Germany
Interests: data-driven analysis of complex systems; unraveling multiscale dynamics of the Earth system; hydroclimatology; hydroclimatic patterns; teleconnections; extreme events; soft computing skills; big data; wavelets and complex network

Dr. Naiming Yuan

E-Mail Website
Guest Editor

Institute of Atmospheric Physics, Chinese Academy of Sciences, Hua Yan Li #40, Beijing 100029, China
Interests: climate prediction; predictability; climate network; extreme events; nonlinear processes in geoscience; multiscale interactions in climate system; stochastic processes

Dr. Kevin K.W. Cheung

E-Mail Website
Guest Editor

E3-Complexity Consultant, Sydney NSW 2000, Australia
Interests: tropical meteorology; severe weather; climate dynamics; nonlinear science; numerical analysis and prediction
Special Issues, Collections and Topics in MDPI journals

Dr. Roopam Shukla

E-Mail Website
Guest Editor

Adaptation in Agriculture Systems, RD2: Climate Resilience, Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Telegrafenberg, 14476 Potsdam, Germany
Interests: climate vulnerability; adaptation planning; extreme events; climate change and climate resilience

Special Issue Information

Dear Colleagues,

Unraveling spatiotemporal patterns and interactions among climate variables, especially those related to hydroclimate, has always been an important task for geoscientists in general, and for climatologists in particular, mostly because it contributes significantly to better prediction and forecasting. However, complexities are intrinsic to natural systems, and for this reason, the task of identifying patterns and interactions has always been challenging. Coupled with the existing challenges of global-warming-induced climate change, these patterns and interactions become further unusual, unexpected, and unpredictable. With these challenging realities, climate science studies globally recognize that climatic and other geophysical processes are intrinsically nonlinear and carry multiscale features along with influences that are in general of time-varying nature. This Special Issue is largely prompted by these realizations and an implied aspiration to develop a collection of advanced studies addressing aforementioned issues.

This Special Issue is expected to advance our understanding of these emerging patterns, teleconnections, and extreme events in a changing world for more accurate prediction or projection of their changes especially on different spatial–time scales. We invite authors to submit original and review articles that aim to study new patterns, interaction and its variability, including its impact to climate extremes, such as drought, flooding, heat waves, and so on. Submissions of recent progress in observational, modeling, and theoretical studies in relation to new connections interactions, especially those that apply advanced techniques to analyze the nonlinearity and multiscale nature of processes, are welcome.

Dr. Ankit Agarwal
Dr. Naiming Yuan
Dr. Kevin Cheung
Dr. Roopam Shukla
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Spatiotemporal patterns
Teleconnections
Climatic variables
Climate change and variability
Climate dynamics
Extreme climate/weather
Large-scale interactions
Nonlinear and multiscale approach

Published Papers (14 papers)

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Editorial

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3 pages, 167 KiB

Open AccessEditorial

Emerging Hydro-Climatic Patterns, Teleconnections, and Extreme Events in Changing World at Different Timescales

by Ankit Agarwal, Naiming Yuan, Kevin K. W. Cheung and Roopam Shukla

Atmosphere 2022, 13(1), 56; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13010056 - 30 Dec 2021

Cited by 1 | Viewed by 1333

Abstract

The Atmosphere Special Issue, entitled “Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales”, comprises thirteen original papers [...] Full article

(This article belongs to the Special Issue Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales)

Research

Jump to: Editorial

12 pages, 639 KiB

Open AccessArticle

Train Performance Analysis Using Heterogeneous Statistical Models

by Jianfeng Wang and Jun Yu

Atmosphere 2021, 12(9), 1115; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12091115 - 30 Aug 2021

Cited by 4 | Viewed by 1613

Abstract

This study investigated the effect of a harsh winter climate on the performance of high-speed passenger trains in northern Sweden. Novel approaches based on heterogeneous statistical models were introduced to analyse the train performance to take time-varying risks of train delays into consideration. Specifically, the stratified Cox model and heterogeneous Markov chain model were used to model primary delays and arrival delays, respectively. Our results showed that weather variables including temperature, humidity, snow depth, and ice/snow precipitation have a significant impact on train performance. Full article

(This article belongs to the Special Issue Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales)

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23 pages, 12362 KiB

Open AccessArticle

Spatio-Temporal Variability in North Atlantic Oscillation Monthly Rainfall Signatures in Great Britain

by Harry West, Nevil Quinn and Michael Horswell

Atmosphere 2021, 12(6), 763; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12060763 - 13 Jun 2021

Cited by 8 | Viewed by 2264

Abstract

The North Atlantic Oscillation (NAO) is the primary atmospheric-oceanic circulation/teleconnection influencing regional climate in Great Britain. As our ability to predict the NAO several months in advance increases, it is important that we improve our spatio-temporal understanding of the rainfall signatures that the circulation produces. We undertake a high resolution spatio-temporal analysis quantifying variability in rainfall response to the NAO across Great Britain. We analyse and map monthly NAO-rainfall response variability, revealing the spatial influence of the NAO on rainfall distributions, and particularly the probability of wet and dry conditions/extremes. During the winter months, we identify spatial differences in the rainfall response to the NAO between the NW and SE areas of Britain. The NW area shows a strong and more consistent NAO-rainfall response, with greater probability of more extreme wet/dry conditions. However, greater NAO-rainfall variability during winter was found in the SE. The summer months are marked by a more spatially consistent rainfall response; however, we find that there is variability in both wet/dry magnitude and directionality. We note the implications of these spatially and temporally variable NAO-rainfall responses for regional hydrometeorological predictions and highlight the potential explanatory role of other atmospheric-oceanic circulations. Full article

(This article belongs to the Special Issue Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales)

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17 pages, 5637 KiB

Open AccessArticle

Subseasonal Forecasts of the Northern Queensland Floods of February 2019: Causes and Forecast Evaluation

by Wayne Yuan-Huai Tsai, Mong-Ming Lu, Chung-Hsiung Sui and Yin-Min Cho

Atmosphere 2021, 12(6), 758; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12060758 - 10 Jun 2021

Cited by 6 | Viewed by 2127

Abstract

During the austral summer 2018/19, devastating floods occurred over northeast Australia that killed approximately 625,000 head of cattle and inundated over 3000 homes in Townsville. In this paper, the disastrous event was identified as a record-breaking subseasonal peak rainfall event (SPRE). The SPRE was mainly induced by an anomalously strong monsoon depression that was modulated by the convective phases of an MJO and an equatorial Rossby (ER) wave. The ER wave originated from an active equatorial deep convection associated with the El Niño warm sea surface temperatures near the dateline over the central Pacific. Based on the S2S Project Database, we analyzed the extended-range forecast skill of the SPRE from two different perspectives, the monsoon depression represented by an 850-hPa wind shear index and the 15-day accumulated precipitation characterized by the percentile rank (PR) and the ratio to the three-month seasonal (DJF) totals. The results of four S2S models of this study suggest that the monsoon depression can maintain the same level of skill as the short-range (3 days) forecast up to 8–10 days. For precipitation parameters, the conclusions are similar to the monsoon depression. For the 2019 northern Queensland SPRE, the model forecast was, in general, worse than the expectation derived from the hindcast analysis. The clear modulation of the ER wave that enhanced the SPRE monsoon depression circulation and precipitation is suspected as the main cause for the lower forecast skill. The analysis procedure proposed in this study can be applied to analyze the SPREs and their associated large-scale drivers in other regions. Full article

(This article belongs to the Special Issue Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales)

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21 pages, 11462 KiB

Open AccessArticle

The Evolution Characteristics of Daily-Scale Silk Road Pattern and Its Relationship with Summer Temperature in the Yangtze River Valley

by Chao Wang, Ying Wen, Lijuan Wang, Xianbiao Kang and Yunfeng Liu

Atmosphere 2021, 12(6), 747; https://doi.org/10.3390/atmos12060747 - 09 Jun 2021

Cited by 2 | Viewed by 2207

Abstract

By employing multi-reanalysis daily datasets and station data, this study focuses on the evolution characteristics of the daily-scale Silk Road pattern (SRP) and its effect on summer temperatures in the Yangtze River Valley (YRV). The results manifest that the evolution characteristics of positive- and negative-phase SRP (referred to SRP+ and SRP−) exhibit marked distinctions. The anomaly centers of SRP+ over West Central Asia (WCA) and Mongolia emerge firstly, vanishing simultaneously one week after peak date; however, the Far East (FE) anomaly centers can persist for a longer period. The SRP− starts with the WCA and FE centers, with a rapid decline in the strength of the WCA center and preservation of other anomaly centers after its peak. In the vertical direction, daily-scale SRP mainly concentrates in the mid-to-upper troposphere. Baroclinicity accounts for its early development and barotropic instability process favors the maintenance. Moreover, the SRP+ (SRP−) is inextricably linked to heat wave (cool summer) processes in the YRV. Concretely, before the onset of SRP+ events, an anomalous anticyclone and significant negative vorticities over East Asia related to SRP+ favor the zonal advance between the South Asia high (SAH) and western Pacific subtropical high (WPSH), inducing local descents over YRV area. The sinking adiabatic warming and clear-sky radiation warming can be considered as the possible causes for the YRV heat waves. The adiabatic cooling with the local ascents leads to more total cloud cover (positive precipitation anomalies) and less solar radiation incident to surface of the YRV, inducing the cool summer process during SRP−. Full article

(This article belongs to the Special Issue Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales)

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19 pages, 4125 KiB

Open AccessArticle

Spatial Characteristics of Precipitation in the Greater Sydney Metropolitan Area as Revealed by the Daily Precipitation Concentration Index

by Kevin K. W. Cheung, Aliakbar A. Rasuly, Fei Ji and Lisa T.-C. Chang

Atmosphere 2021, 12(5), 627; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12050627 - 13 May 2021

Cited by 4 | Viewed by 2602

Abstract

In this study; the spatial distribution of the Daily Precipitation Concentration Index (DPCI) has been analyzed inside the Greater Sydney Metropolitan Area (GSMA). Accordingly, the rainfall database from the Australian Bureau of Meteorology archive was utilized after comprehensive quality control. The compiled data contains a set of 41 rainfall stations indicating consistent daily precipitation series from 1950 to 2015. In the analysis of the DPCI across GSMA the techniques of Moran’s Spatial Autocorrelation has been applied. In addition, a cross-covariance method was applied to assess the spatial interdependency between vector-based datasets after performing an Ordinary Kriging interpolation. The results identify four well-recognized intense rainfall development zones: the south coast and topographic areas of the Illawarra district characterized by Tasman Sea coastal regions with DPCI values ranging from 0.61 to 0.63, the western highlands of the Blue Mountains, with values between 0.60 and 0.62, the inland regions, with lowest rainfall concentrations between 0.55 and 0.59, and lastly the districts located inside the GSMA with DPCI ranging 0.60 to 0.61. Such spatial distribution has revealed the rainstorm and severe thunderstorm activity in the area. This study applies the present models to identify the nature and mechanisms underlying the distribution of torrential rains over space within the metropolis of Sydney, and to monitor any changes in the spatial pattern under the warming climate. Full article

(This article belongs to the Special Issue Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales)

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23 pages, 11230 KiB

Open AccessArticle

Multiscale Spatiotemporal Analysis of Extreme Events in the Gomati River Basin, India

by AVS Kalyan, Dillip Kumar Ghose, Rahul Thalagapu, Ravi Kumar Guntu, Ankit Agarwal, Jürgen Kurths and Maheswaran Rathinasamy

Atmosphere 2021, 12(4), 480; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12040480 - 09 Apr 2021

Cited by 12 | Viewed by 3347

Abstract

Accelerating climate change is causing considerable changes in extreme events, leading to immense socioeconomic loss of life and property. In this study, we investigate the characteristics of extreme climate events at a regional scale to -understand these events’ propagation in the near future. We have considered sixteen extreme climate indices defined by the World Meteorological Organization’s Expert Team on Climate Change Detection and Indices from a long-term dataset (1951–2018) of 53 locations in Gomati River Basin, North India. We computed the present and future spatial variation of theses indices using the Sen’s slope estimator and Hurst exponent analysis. The periodicities and non-stationary features were estimated using the continuous wavelet transform. Bivariate copulas were fitted to estimate the joint probabilities and return periods for certain combinations of indices. The study results show different variation in the patterns of the extreme climate indices: D95P, R95TOT, RX5D, and RX showed negative trends for all stations over the basin. The number of dry days (DD) showed positive trends over the basin at 36 stations out of those 17 stations are statistically significant. A sustainable decreasing trend is observed for D95P at all stations, indicating a reduction in precipitation in the future. DD exhibits a sustainable decreasing trend at almost all the stations over the basin barring a few exceptions highlight that the basin is turning drier. The wavelet power spectrum for D95P showed significant power distributed across the 2–16-year bands, and the two-year period was dominant in the global power spectrum around 1970–1990. One interesting finding is that a dominant two-year period in D95P has changed to the four years after 1984 and remains in the past two decades. The joint return period’s resulting values are more significant than values resulting from univariate analysis (R95TOT with 44% and RTWD of 1450 mm). The difference in values highlights that ignoring the mutual dependence can lead to an underestimation of extremes. Full article

(This article belongs to the Special Issue Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales)

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13 pages, 6608 KiB

Open AccessArticle

Refined Characteristics of Moisture Cycling over the Inland River Basin Using the WRF Model and the Finer Box Model: A Case Study of the Heihe River Basin

by Xiaoduo Pan, Weiqiang Ma, Ying Zhang and Hu Li

Atmosphere 2021, 12(3), 399; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12030399 - 20 Mar 2021

Cited by 5 | Viewed by 2015

Abstract

The Heihe River Basin (HRB), located on the northeastern edge of the Tibetan Plateau, is the second-largest inland river basin in China, with an area of 140,000 km². The HRB is a coupling area of the westerlies, the Qinghai–Tibet Plateau monsoon and the Southeast monsoon circulation system, and is a relatively independent land-surface water-circulating system. The refined characteristics of moisture recycling over the HRB was described by using the Weather Research and Forecasting (WRF) model for a long-term simulation, and the “finer box model” for calculating the net water-vapor flux. The following conclusions were drawn from the results of this study: (1) The water vapor of the HRB was dominantly transported by the wind from the west and from the north, and the west one was much larger than the north one. The net vapor transported by the west wind was positive, and by the north wind was negative. (2) The precipitation over the HRB was triggered mainly by the vapor from the west, which arose from the lower vertical layer to higher one during transporting from west to east. The vapor from the north sank from a higher layer to a lower one, and crossed the south edge of the HRB. (3) The moisture-recycling ratio of evapotranspiration to precipitation over the HRB was much higher than the other regions, which may be due to the strong land–atmosphere interaction in the arid inland river basin. Full article

(This article belongs to the Special Issue Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales)

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14 pages, 9183 KiB

Open AccessArticle

Recognizing the Aggregation Characteristics of Extreme Precipitation Events Using Spatio-Temporal Scanning and the Local Spatial Autocorrelation Model

by Changjun Wan, Changxiu Cheng, Sijing Ye, Shi Shen and Ting Zhang

Atmosphere 2021, 12(2), 218; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12020218 - 05 Feb 2021

Cited by 6 | Viewed by 2283

Abstract

Precipitation is an essential climate variable in the hydrologic cycle. Its abnormal change would have a serious impact on the social economy, ecological development and life safety. In recent decades, many studies about extreme precipitation have been performed on spatio-temporal variation patterns under global changes; little research has been conducted on the regionality and persistence, which tend to be more destructive. This study defines extreme precipitation events by percentile method, then applies the spatio-temporal scanning model (STSM) and the local spatial autocorrelation model (LSAM) to explore the spatio-temporal aggregation characteristics of extreme precipitation, taking China in July as a case. The study result showed that the STSM with the LSAM can effectively detect the spatio-temporal accumulation areas. The extreme precipitation events of China in July 2016 have a significant spatio-temporal aggregation characteristic. From the spatial perspective, China’s summer extreme precipitation spatio-temporal clusters are mainly distributed in eastern China and northern China, such as Dongting Lake plain, the Circum-Bohai Sea region, Gansu, and Xinjiang. From the temporal perspective, the spatio-temporal clusters of extreme precipitation are mainly distributed in July, and its occurrence was delayed with an increase in latitude, except for in Xinjiang, where extreme precipitation events often take place earlier and persist longer. Full article

(This article belongs to the Special Issue Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales)

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12 pages, 1758 KiB

Open AccessArticle

Characteristic of the Regional Rainy Season Onset over Vietnam: Tailoring to Agricultural Application

by Nachiketa Acharya and Elva Bennett

Atmosphere 2021, 12(2), 198; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12020198 - 02 Feb 2021

Cited by 5 | Viewed by 3139

Abstract

Owing to its unique position within multiple monsoon regimes, latitudinal extent, and complex topography, Vietnam is divided into seven agroclimatic zones, each with distinct rainy season characteristics. Variation in the dominant rainfall system across zones affects the rainfall climatology, the primary water resource for regional crops. This study explores the creation of an agronomic rainy season onset based on high-resolution rainfall data for each agroclimatic zone for applications in an agricultural context. Onset information has huge practical importance for both agriculture and the economy. The spatiotemporal characteristics of zonal onset date are analyzed using integrated approaches of spatial and interannual variability, temporal changes, and estimation of predictability using teleconnection with Niño 3.4 sea surface temperature anomalies (SSTA) for 1980 to 2010. Results suggest that northern and southern zones experience regional onset dates in May, while the central zones experience rainy season onset in late August. The regional variability of rainy season onset is lower in the northern and southern zones and higher in the central zones which are latitudinally extended. The interannual variation in rainy season onset date is found to be approximately two weeks across all agroclimatic zones. The significant negative trend in rainy season onset date is found for Central Coast and South Central Coast zones, suggesting that the onset date shifted earlier for the entire period. In the decadal scale, the zonal mean onset date shifted later in the Northwest zone and earlier in the Central Highlands. Out of the seven climate zones, a significant positive correlation is only noticed in the Central Highlands and South zones between zonal mean onset date and Niño 3.4 SSTA for Dec–Jan–Feb, suggesting the potential of seasonal scale predictability of rainy season onset date with respect to preceding El Niño-Southern Oscillation (ENSO) events. Full article

(This article belongs to the Special Issue Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales)

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17 pages, 4871 KiB

Open AccessArticle

Sensitivity of Microphysical Schemes on the Simulation of Post-Monsoon Tropical Cyclones over the North Indian Ocean

by Gundapuneni Venkata Rao, Keesara Venkata Reddy and Venkataramana Sridhar

Atmosphere 2020, 11(12), 1297; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos11121297 - 30 Nov 2020

Cited by 11 | Viewed by 2242

Abstract

Tropical Cyclones (TCs) are the most disastrous natural weather phenomenon, that have a significant impact on the socioeconomic development of the country. In the past two decades, Numerical Weather Prediction (NWP) models (e.g., Advanced Research WRF (ARW)) have been used for the prediction of TCs. Extensive studies were carried out on the prediction of TCs using the ARW model. However, these studies are limited to a single cyclone with varying physics schemes, or single physics schemes to more than one cyclone. Hence, there is a need to compare different physics schemes on multiple TCs to understand their effectiveness. In the present study, a total of 56 sensitivity experiments are conducted to investigate the impact of seven microphysical parameterization schemes on eight post-monsoon TCs formed over the North Indian Ocean (NIO) using the ARW model. The performance of the Ferrier, Lin, Morrison, Thompson, WSM3, WSM5, and WSM6 are evaluated using error metrics, namely Mean Absolute Error (MAE), Mean Square Error (MSE), Skill Score (SS), and average track error. The results are compared with Indian Meteorological Department (IMD) observations. From the sensitivity experiments, it is observed that the WSM3 scheme simulated the cyclones Nilofar, Kyant, Daye, and Phethai well, whereas the cyclones Hudhud, Titli, and Ockhi are best simulated by WSM6. The present study suggests that the WSM3 scheme can be used as the first best scheme for the prediction of post-monsoon tropical cyclones over the NIO. Full article

(This article belongs to the Special Issue Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales)

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16 pages, 3246 KiB

Open AccessArticle

Future Changes in the Free Tropospheric Freezing Level and Rain–Snow Limit: The Case of Central Chile

by Piero Mardones and René D. Garreaud

Atmosphere 2020, 11(11), 1259; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos11111259 - 23 Nov 2020

Cited by 11 | Viewed by 3374

Abstract

The freezing level in the free troposphere often intercepts the terrain of the world’s major mountain ranges, creating a rain–snow limit. In this work, we use the free tropospheric height of the 0

^{°}

C isotherm (

H_{0}

) as a proxy [...] Read more.

^{°}

C isotherm (

H_{0}

) as a proxy of both levels and study its distribution along the western slope of the subtropical Andes (30

^{°}

–38

^{°}

S) in present climate and during the rest of the 21st century. This portion of the Andes corresponds to central Chile, a highly populated region where warm winter storms have produced devastating landslides and widespread flooding in the recent past. Our analysis is based on the frequency distribution of

H_{0}

derived from radiosonde and surface observations, atmospheric reanalysis and climate simulations. The future projections primarily employ a scenario of heavy greenhouse gasses emissions (RCP8.5), but we also examine the more benign RCP4.5 scenario. The current

H_{0}

distribution along the central Chile coast shows a gradual decrease southward, with mean heights close to 2600 m ASL (above sea level) at 30

^{°}

C S to 2000 m ASL at 38

^{°}

S for days with precipitation, about 800 m lower than during dry days. The mean value under wet conditions toward the end of the century (under RCP8.5) is close to, or higher than, the upper quartile of the

H_{0}

distribution in the current climate. More worrisome,

H_{0}

values that currently occur only 5% of the time will be exceeded in about a quarter of the rainy days by the end of the century. Under RCP8.5, even moderate daily precipitation can increase river flow to levels that are considered hazardous for central Chile. Full article

(This article belongs to the Special Issue Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales)

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26 pages, 5562 KiB

Open AccessArticle

Inter-Comparison of Gauge-Based Gridded Data, Reanalysis and Satellite Precipitation Product with an Emphasis on Hydrological Modeling

by Sridhara Setti, Rathinasamy Maheswaran, Venkataramana Sridhar, Kamal Kumar Barik, Bruno Merz and Ankit Agarwal

Atmosphere 2020, 11(11), 1252; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos11111252 - 20 Nov 2020

Cited by 27 | Viewed by 3875

Abstract

Precipitation is essential for modeling the hydrologic behavior of watersheds. There exist multiple precipitation products of different sources and precision. We evaluate the influence of different precipitation product on model parameters and streamflow predictive uncertainty using a soil water assessment tool (SWAT) model for a forest dominated catchment in India. We used IMD (gridded rainfall dataset), TRMM (satellite product), bias-corrected TRMM (corrected satellite product) and NCEP-CFSR (reanalysis dataset) over a period from 1998–2012 for simulating streamflow. The precipitation analysis using statistical measures revealed that the TRMM and CFSR data slightly overestimate rainfall compared to the ground-based IMD data. However, the TRMM estimates improved, applying a bias correction. The Nash–Sutcliffe (and

R^{2}

) values for TRMM, TRMMbias and CFSR, are 0.58 (0.62), 0.62 (0.63) and 0.52 (0.54), respectively at model calibrated with IMD data (Scenario A). The models of each precipitation product (Scenario B) yielded Nash–Sutcliffe (and

R^{2}

) values 0.71 (0.76), 0.74 (0.78) and 0.76 (0.77) for TRMM, TRMMbias and CFSR datasets, respectively. Thus, the hydrological model-based evaluation revealed that the model calibration with individual rainfall data as input showed increased accuracy in the streamflow simulation. IMD and TRMM forced models to perform better in capturing the streamflow simulations than the CFSR reanalysis-driven model. Overall, our results showed that TRMM data after proper correction could be a good alternative for ground observations for driving hydrological models. Full article

(This article belongs to the Special Issue Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales)

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14 pages, 43696 KiB

Open AccessArticle

Trends and Variabilities of Thunderstorm Days over Bangladesh on the ENSO and IOD Timescales

by Md Wahiduzzaman, Abu Reza Md. Towfiqul Islam, Jing–Jia Luo, Shamsuddin Shahid, Md. Jalal Uddin, Sayed Majadin Shimul and Md Abdus Sattar

Atmosphere 2020, 11(11), 1176; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos11111176 - 30 Oct 2020

Cited by 15 | Viewed by 3576

Abstract

Thunderstorms (TS) are one of the most devastating atmospheric phenomena, which causes massive damage and adverse losses in various sectors, including agriculture and infrastructure. This study investigates the spatiotemporal variabilities of TS days over Bangladesh and their connection with El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). The TS, ENSO and IOD years’ data for 42 years (1975–2016) are used. The trend in TS days at the spatiotemporal scale is calculated using Mann Kendall and Spearman’s rho test. Results suggest that the trend in TS days is positive for all months except December and January. The significant trends are found for May and June, particularly in the northern and northeastern regions of Bangladesh. In the decadal scale, most of the regions show a significant upward trend in TS days. Results from the Weibull probability distribution model show the highest TS days in the northeastern region. The connection between TS days and ENSO/IOD indicates a decrease in TS activities in Bangladesh during the El Niño and positive IOD years. Full article

(This article belongs to the Special Issue Emerging Hydro-Climatic Patterns, Teleconnections and Extreme Events in Changing World at Different Timescales)

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