Environmental Footprints of Drought: Focusing on Emerging Issues and Their Underlying Mechanisms (2nd Edition)

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

Deadline for manuscript submissions: closed (6 February 2024) | Viewed by 1591

Special Issue Editors


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Guest Editor
1. College of Surveying and Geo-informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
2. Hydraulics and Geotechnics Section, KU Leuven, Kasteelpark Arenberg 40, BE-3001 Leuven, Belgium
Interests: extreme climatic events; climate change and human health impacts; hydrology modeling; water resources; vegetation remote sensing
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Guest Editor
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, University of Chinese Academy of Sciences, Beijing 100094, China
Interests: heat waves; climate models; remote sensing; vegetation dynamics
Special Issues, Collections and Topics in MDPI journals
College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
Interests: hydrology modeling; impacts of climate change on hydrologic research

Special Issue Information

Dear Colleagues,

Following the successful publication of our first volume, which focused on the dynamics of droughts and their impacts, we are excited to announce the call for papers for the second volume of our Special Issue. In this volume, we aim to continue exploring the same primary theme of “Environmental Footprints of Drought: Focusing on Emerging Issues and Their Underlying Mechanisms” while encouraging the application of artificial intelligence (AI) techniques and methods, as well as give a platform to research on the interplay between droughts and heatwave events.

In recent years, AI has emerged as a powerful tool across various scientific domains, offering new insights and innovative solutions to complex problems. As we delve deeper into the study of droughts, we recognize the potential of AI in enhancing our understanding of drought patterns, improving prediction accuracy, and developing effective adaptation strategies. Therefore, we encourage researchers to incorporate AI methodologies and explore their application in studying droughts. Additionally, the interplay between droughts and heatwave events is of great importance, as these climate phenomena often reinforce each other, leading to amplified impacts on ecosystems, agriculture, water resources, and human well-being. Therefore, studies investigating the intertwined dynamics, feedback mechanisms, and potential adaptation measures between droughts and heatwaves are highly encouraged.

Therefore, we invite original research papers, reviews, and case studies that align with the primary focus of the first volume while also highlighting the application of AI techniques and methods. Contributions may cover various local–regional scales and utilize diverse data sources, including observational data, modeling studies, and remote sensing data. Our goal is to foster interdisciplinary research and advance our understanding of the complex dynamics of drought (events), ultimately contributing to effective decision-making and risk reduction in the face of these climatic challenges.

Dr. Jinping Liu
Dr. Quoc Bao Pham
Dr. Arfan Arshad
Dr. Masoud Jafari Shalamzari
Dr. Yanqun Ren
Guest Editors

Manuscript Submission Information

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Keywords

  • roles of atmospheric circulation pattens in the development of droughts
  • natural and anthropogenic influences
  • climate extremes
  • hydrological extremes
  • land–atmosphere interactions (emergent risks associated with droughts)
  • drought vulnerability, risk, and impact assessments
  • sensitivity and adaptive capacity of environmental systems
  • weather hazards and warning systems
  • compound droughts
  • drought increases CO2 footprints
  • drought increases water scarcity
  • effects on agricultural systems
  • downscaling of climate projections to inform drought conditions over local scale
  • numerical simulation models, resilience strategies, and decision-making tools
  • interplay between droughts and heatwaves
  • artificial intelligence (AI) techniques and methods

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Published Papers (1 paper)

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Research

25 pages, 24760 KiB  
Article
Investigating Whether the Ensemble Average of Multi-Global-Climate-Models Can Necessarily Better Project Seasonal Drought Conditions in China
by Jinping Liu, Yanqun Ren, Patrick Willems, Tie Liu, Bin Yong, Masoud Jafari Shalamzari and Huiran Gao
Atmosphere 2023, 14(9), 1408; https://doi.org/10.3390/atmos14091408 - 06 Sep 2023
Viewed by 1130
Abstract
Global drought patterns are substantially impacted by climate change, with far-reaching implications for socioeconomic and ecological systems. Existing global climate models (GCMs) are unable to accurately project precipitation and drought characteristics, particularly in countries or regions with complex topography and significant seasonal variability, [...] Read more.
Global drought patterns are substantially impacted by climate change, with far-reaching implications for socioeconomic and ecological systems. Existing global climate models (GCMs) are unable to accurately project precipitation and drought characteristics, particularly in countries or regions with complex topography and significant seasonal variability, such as China. Consequently, the purpose of this study is to assess the efficacy of GCMs, and their multi-model ensemble mean, as well as to investigate the seasonal drought characteristics in China using precipitation data from CMIP6 under various “possible future” scenarios. This study selected five GCMs with historical (1961–2014) and future (2015–2100) periods, namely CNRM-CM6-1, GFDL-ESM4, MPI-ESM1-2-HR, MPI-ESM1-2-LR, and NorESM2-MM, as well as their ensemble mean ENS-CGMMN. Based on the China Daily Precipitation Analysis Product (CPAP) as the reference precipitation, the performance of these models is evaluated using the DISO index and the quantile mapping (QM) method for calibration, as well as seasonal-scale drought using the standardized precipitation index (SPI) and spatiotemporal variability analysis methods. In comparison to other climate models and the ensemble mean, the calibrated MPI-ESM1-2-HR model can more precisely describe the actual precipitation conditions at the seasonal scale. Under four scenarios, China’s climate will shift from arid to moist in the future period (2015–2100) (SSP126, SSP245, SSP370, and SSP585). Autumn and summer will see a considerable increase in China’s moisture levels. During the autumn, winter, and spring, the moisture will generally increase in the northern subregions of China, including the Qinghai-Tibet Plateau (QTP), Xinjiang (XJ), Northwest (NW), Northeast (NE), and North China (NC). Dryness will decrease in southern subregions, such as the Southwest (SW) and South China (SC). In contrast to these three seasons, summer in XJ exhibits a distinct trend of aridity, especially in the SSP245 scenario, whereas the NE, NC, and SC exhibit a distinct trend of moisture. To be more specific, the aridity changes in subregions during various seasons under different future climate scenarios vary significantly. This study’s findings can provide significant support for future research on climate change and drought, which can help improve the accuracy of future climate projections and serve as a reference for drought risk management and policy formulation. Full article
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