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Atmosphere
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Climate and Weather Extremes and Their Impacts on Water Resources...
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Climate and Weather Extremes and Their Impacts on Water Resources and Agriculture in Asia

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

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 12167

Special Issue Editors

Dr. Safi Ullah

E-Mail Website
Guest Editor
Department of Atmospheric and Oceanic Sciences, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
Interests: climate change; climate extremes; climate modeling; climate change adaptation; disaster risk management; disaster risk assessment; hazard assessment; vulnerability analysis; disaster resilience assessment
Dr. Waheed Ullah

E-Mail Website
Guest Editor
School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
Interests: remote sensing; land-atmosphere interactions; atmospheric dynamics; climate modeling; regional climate modeling; monsoon; atmosphere; meteorology; atmospheric physics; soil moisture
Dr. Adnan Abbas

E-Mail Website
Guest Editor
Land Science Research Center, Nanjing University of Information Science and Technology, Nanjing 210044, China
Interests: impact assessment; regional climate modeling; atmosphere; extreme events; climate change adaptation; drought; agricultural resources and energy efficiency
Dr. Asher Samuel Bhatti

E-Mail Website
Guest Editor
Department of Geology, Bacha Khan University Charsadda, Khyber Pakhtunkhwa Pakistan, Charsadda 24420, Pakistan
Interests: remote sensing; geophysics; land-atmosphere interactions; atmospheric dynamics; climate modeling; hydrology

Special Issue Information

Dear Colleagues,

The socioeconomic and environmental impact assessment of climate variability and climate change is necessary to develop relevant policies for adaption and mitigation strategies toward the sustainable planning of water resource management, food security, and disaster risk management. Information regarding climate variability and climate change is vital not only at the national level but also at regional and global scales. The reliable assessment of climate change and its extremes is a hot topic in the global debate. The Asian region is more vulnerable to climate change risks due to its dependence on natural resources, agriculture sectors, densely populated coastal areas, weak institutions, and poverty among a considerable proportion of the population. Therefore, adaptation—making adjustments in natural and/or human systems in response to actual or expected climatic stimuli or their effects that moderate negative or exploit beneficial opportunities—becomes a key strategy for sustainable socio-economic development. Failure to adapt could stall development, particularly in Asian countries. Thus, understanding the pattern of climate change and climate variability has been the focus of many researchers, and many efforts are being made to better frame the consequences of their future impacts.

This Special Issue (SI) focuses on the assessment and projection of climate change and its extremes over Asia, where the erratic, scant, and unstable climatic situations exacerbate the risks to food and water security. The region has experienced frequent heat and cold waves, flooding, and drought that recede regional water tables and crop failures in different parts of Asia. The overall changes in temperature and precipitation have led to alterations in water availability in Asia. Therefore, to help solve this problem, this Special Issue seeks contributions of historical trends and future projections of climate change and its extremes to enhance the understanding of the regional climate patterns and variations over Asia.

This Issue encourages articles that discuss regional (Asia) analysis of climate-change-induced extreme weather events and their impacts on the socio-economic sectors—particularly on water resources and agriculture. Contributions to model simulations and evaluations to advance the understanding of physics and dynamics associated with climate-change-related weather hazards will also be considered. Submissions in, but not limited to, the following research areas are invited: climate variability and climate change, climate modeling, global and regional climate models, climate extremes (heat waves, cold waves, flood, drought, aridity, etc.), trend analysis, statistical downscaling techniques, spatiotemporal mapping of hydrometeorological parameters, climate dynamics, climate change impacts, water resources, food security.

Dr. Safi Ullah
Dr. Waheed Ullah
Dr. Adnan Abbas
Dr. Asher Samuel Bhatti
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

  • climate variability and climate change
  • climate modeling
  • global and regional climate models
  • climate extremes (heat waves, cold waves, floods, drought, aridity, etc.)
  • trend analysis
  • statistical downscaling techniques
  • spatiotemporal mapping of hydrometeorological parameters
  • climate dynamics
  • climate change impacts
  • water resources
  • food security

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Published Papers (4 papers)

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Research

18 pages, 4992 KiB  
Article
Evaluation of the Performance of CMIP6 Climate Models in Simulating Rainfall over the Philippines
by Shelly Jo Igpuara Ignacio-Reardon and Jing-jia Luo
Atmosphere 2023, 14(9), 1459; https://doi.org/10.3390/atmos14091459 - 20 Sep 2023
Cited by 3 | Viewed by 2067
Abstract
The Philippines is highly vulnerable to multiple climate-related hazards due to its geographical location and weak adaptation measures. Floods are the most catastrophic hazards that impact lives, livelihoods, and, consequently, the economy at large. Understanding the ability of the general circulation models to [...] Read more.
The Philippines is highly vulnerable to multiple climate-related hazards due to its geographical location and weak adaptation measures. Floods are the most catastrophic hazards that impact lives, livelihoods, and, consequently, the economy at large. Understanding the ability of the general circulation models to simulate the observed rainfall using the latest state-of-the-art model is essential for reliable forecasting. Based on this background, this paper objectively aims at assessing and ranking the capabilities of the recent Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating the observed rainfall over the Philippines. The Global Precipitation Climatology Project (GPCP) v2.3 was used as a proxy to gauge the performance of 11 CMIP6 models in simulating the annual and rainy-season rainfall during 1980–2014. Several statistical metrics (mean, standard deviation, normalized root means square error, percentage bias, Pearson correlation coefficient, Mann–Kendall test, Theil–Sen slope estimator, and skill score) and geospatial measures were assessed. The results show that that CMIP6 historical simulations exhibit satisfactory effectiveness in simulating the annual cycle, though some models display wet/dry biases. The CMIP6 models generally underestimate rainfall on the land but overestimate it over the ocean. The trend analysis shows that rainfall over the country is insignificantly increasing both annually and during the rainy seasons. Notably, most of the models could correctly simulate the trend sign but over/underestimate the magnitude. The CMIP6 historical rainfall simulating models significantly agree on simulating the mean annual cycle but diverge in temporal ability simulation. The performance of the models remarkably differs from one metric to another and among different time scales. Nevertheless, the models may be ranked from the best to the least best at simulating the Philippines’ rainfall in the order GFDL, NOR, ACCESS, ENS, MRI, CMCC, NESM, FIO, MIROC, CESM, TAI, and CAN. The findings of this study form a good basis for the selection of models to be used in robust future climate projection and impact studies regarding the Philippines. The climate model developers may use the documented shortcoming of these models and improve their physical parametrization for better performance in the future. Full article
(This article belongs to the Special Issue Climate and Weather Extremes and Their Impacts on Water Resources and Agriculture in Asia)
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19 pages, 4684 KiB  
Article
Spatiotemporal Precipitation Trends and Associated Large-Scale Teleconnections in Northern Pakistan
by Ansa Rebi, Azfar Hussain, Ishtiaq Hussain, Jianhua Cao, Waheed Ullah, Haider Abbas, Safi Ullah and Jinxing Zhou
Atmosphere 2023, 14(5), 871; https://doi.org/10.3390/atmos14050871 - 15 May 2023
Cited by 17 | Viewed by 2595
Abstract
The effects of climate change are unparalleled in magnitude, ranging from changing weather patterns that endanger food production to increasing sea levels that increase the likelihood of catastrophic flooding. Therefore, determining the extent of such variations on regional and local scales is imperative. [...] Read more.
The effects of climate change are unparalleled in magnitude, ranging from changing weather patterns that endanger food production to increasing sea levels that increase the likelihood of catastrophic flooding. Therefore, determining the extent of such variations on regional and local scales is imperative. We used monthly precipitation data from 25 meteorological stations in northern Pakistan (NP) to document the observed changes in seasonal and annual precipitation. The station density in the NP is small and unevenly distributed; therefore, ERA-5 reanalysis data were used to supplement the observed dataset to assess the spatial trends in NP. The non-parametric Mann–Kendall (MK), Sen’s Slope estimator (SSE), and Sequential Mann–Kendall (SQMK) tests were performed to assess the trends. In addition, the wavelet analysis technique was used to determine the association of precipitation with various oceanic indices from 1960 to 2016. Results indicate that maximum precipitation was shown in the annual and summer seasons. In NP, annual, winter, spring, and summer precipitation declined, while an increase in autumn was observed at a rate of 0.43 mm/decade between 1989 and 2016. The spatial trends for observed and ERA-5 reanalysis datasets were almost similar in winter, spring, and autumn; however, some disagreement was observed in both datasets in the summer and annual precipitation trends in NP during 1960–2016. Between 1989 and 2016, summer and annual precipitation increased significantly in Region III. However, seasonal and annual precipitation decreased in NP between 1960 and 2016. Moreover, there were no prominent trends in annual precipitation until the mid-1980s, but an apparent increase from 1985 onwards. Annual precipitation increased in all elevations except at the 500–1000 m zone. The ENSO (El Niño–Southern Oscillation) shared notable interannual coherences among all indices above 16–64 months. Inter-decadal coherence with the ENSO, AO (Arctic Oscillation), and PDO (Pacific Decadal Oscillation) in NP for 128 months and above. Generally, AO, AMO (Atlantic Multidecadal Oscillation), and NAO (North Atlantic Oscillation) exhibited less coherence with precipitation in NP. The regression of seasonal and annual precipitation revealed that winter and spring precipitation levels had higher linear regression with the AO and ENSO, respectively, while both the AO and ENSO also dominated at the annual scale. Similarly, the IOD and PDO indices had a higher influence in summer precipitation. The findings may help water resource managers and climate researchers develop a contingency plan for better water resource management policies in the face of changing climate change in Pakistan, particularly in NP. Full article
(This article belongs to the Special Issue Climate and Weather Extremes and Their Impacts on Water Resources and Agriculture in Asia)
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24 pages, 37262 KiB  
Article
Assessing the Impact of Long-Term ENSO, SST, and IOD Dynamics on Extreme Hydrological Events (EHEs) in the Kelani River Basin (KRB), Sri Lanka
by Vithana P. I. S. Wijeratne, Gang Li, Muhammad Sajid Mehmood and Adnan Abbas
Atmosphere 2023, 14(1), 79; https://doi.org/10.3390/atmos14010079 - 30 Dec 2022
Cited by 19 | Viewed by 3093
Abstract
Hydrological extremes are common throughout the world and can be considered a globally significant phenomenon with severe environmental and social consequences. In recent decades, especially in the second half of the 20th century, Extreme Hydrological Events (EHEs) have attracted extensive attention. Physiological and [...] Read more.
Hydrological extremes are common throughout the world and can be considered a globally significant phenomenon with severe environmental and social consequences. In recent decades, especially in the second half of the 20th century, Extreme Hydrological Events (EHEs) have attracted extensive attention. Physiological and anthropogenic factors have increased the frequency and severity of hydrological extremes worldwide in the last few decades. Recently, it has become a significant environmental issue in Sri Lanka. Both floods and droughts are widespread throughout the country, and the influence of floods is becoming more common every year. Currently, the frequency and severity of EHEs in the Kelani River Basin (KRB), Sri Lanka, are very common and have increased due to climate variations. Therefore, this study focused mainly on evaluating the EHEs and the impact of long-term El Niño Southern Oscillation (ENSO), Sea Surface Temperature (SST), and Indian Ocean Dipole (IOD) dynamics on extreme events. Rainfall Anomaly Index (RAI) and Extreme Precipitation Indices (EPIs) were calculated to examine the EHEs and their spatial variability. In addition, the relationships between EHEs and ENSO were investigated using several climate indices based on SST anomalies. Both observed and satellite-derived daily precipitation from 1951 to 2019 were used to assess the EHEs in the KRB. The trend of EHEs and the change points were evaluated using the Pettitt test, and teleconnection with global indices was examined using the correlation coefficient in the R application. The result of the study revealed that the pattern of EHEs varied spatially from 1951 to 2019. The strong La Niña years showed a high degree of teleconnection with EHEs in April (r = 0.622 at 0.05 significance level) and August (r = −0.732 at 0.05 significance level). NINO3.4 and the Southern Oscillation Index (SOI) have shown a significant positive impact on EHEs in the Northeast Monsoon (NEM) period. This research on KRB will be a popular scientific measure that can provide scientific results and solutions for the comprehensive decision-making process in the future. Investigating the global physical changes that influence EHEs is critical to taking the necessary steps to reduce the severity of hydrological extremes in Sri Lanka. Full article
(This article belongs to the Special Issue Climate and Weather Extremes and Their Impacts on Water Resources and Agriculture in Asia)
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14 pages, 2482 KiB  
Article
Predicting the Environmental Change of Carbon Emission Patterns in South Asia: A Deep Learning Approach Using BiLSTM
by Muhammad Aamir, Mughair Aslam Bhatti, Sibghat Ullah Bazai, Shah Marjan, Aamir Mehmood Mirza, Abdul Wahid, Ahmad Hasnain and Uzair Aslam Bhatti
Atmosphere 2022, 13(12), 2011; https://doi.org/10.3390/atmos13122011 - 30 Nov 2022
Cited by 22 | Viewed by 2897
Abstract
China’s economy has made significant strides in the past three decades. As a direct result of China’s “one belt, one road” (OBOR) initiative, the country’s rate of industrialization and urbanization is currently the fastest in the entire world. This rapid development is largely [...] Read more.
China’s economy has made significant strides in the past three decades. As a direct result of China’s “one belt, one road” (OBOR) initiative, the country’s rate of industrialization and urbanization is currently the fastest in the entire world. This rapid development is largely dependent on the enormous amounts of energy currently being consumed and forms the foundation of the world’s high levels of carbon emissions. It is generally agreed that the production of greenhouse gases, particularly carbon dioxide, is the primary contributor to the current state of climate change. In this paper, a CO2 emission prediction model based on Bi-LSTM is constructed. In order to conduct empirical tests on the model, this study uses data from South Asian countries and China from 2001 to 2020. China’s CO2 emissions from 2022 to 2030 were predicted along with those of other countries in order to study the combined effects of the scientific and technological progress, industrial structures, and energy structure factors affecting CO2 emissions. When compared with the LSTM and GRU methods, the Bi-LSTM model’s results produced lower MAE, MSE, and MAPE values, indicating that it performs better. According to the findings, carbon emissions represent a significant problem that will become much worse in the future due to China and India’s high emissions, particularly in the next 10 years, if the government does not implement policies that help reduce those emissions. Full article
(This article belongs to the Special Issue Climate and Weather Extremes and Their Impacts on Water Resources and Agriculture in Asia)
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