Drought and Extreme Events Caused by Climate Changes

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water and Climate Change".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 3708

Special Issue Editor


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Guest Editor
1) ENEA, SSPT-MET-CLIM, Climate & Impact Modeling Laboratory, Rome, Italy
2) EURAC, Institute for Earth Observation, Bozen, Italy
Interests: extreme events; drought; climate dynamics; climate change; remote sensing

Special Issue Information

Dear Colleagues

Extreme meteorological events deeply impact economies and societies. Weather-related disasters are already increasingly undermining economic growth and threatening human lives in populations around the world. Moreover, due to the variations of climate conditions, droughts are expected to increase in frequency and intensity globally because of climate change. It is hence fundamental for climate change adaptation plans to define new approaches for the attribution, localization and identification of extreme events.

The major difficulty arises from the intrinsic variability of the climate system. In fact, a change in the frequency and magnitude of extremes can be detected only over a large enough sample, i.e., a sample that represents the climatology. The climatological conditions are generally calculated over 30 years; over a shorter time-scale, a fluctuation of the climate system might be confused with a systematic change in the frequency of extremes. It is indeed necessary to develop theoretical methods to spot statistically significant changes in extreme events.

Within this framework, the definition of new methodologies for extreme event detection, location, attribution and assessment is necessary. At the same time, the development of new indexes for identification of droughts and other climate extremes is essential in order to take into consideration the effects due to the combination of contemporaneous events which can results in extremes.

In the water sector, as in others, the application of novel theories and approaches founded on mathematical analysis and new artificial intelligence techniques are strongly encouraged for extreme event detection and localization.

Therefore, the present Special Issue entitled “Drought and Extreme Events Caused by Climate Changes” aims to publish original research or review papers on identification, localization, attribution and measurement of extreme events caused by climate change and associated methodologies and techniques.

The overall scope includes up-to-date developments on the current state of knowledge of theoretical, applied, observational and methodological studies in which novel approaches and strong results are presented and discussed. Specifically, the topics of this Special Issue include, but are not restricted to, the following:

  • Drought and its relationship to climate change;
  • Extreme event identification, localization and attribution;
  • Artificial intelligence techniques applied to drought and extreme events;
  • Extreme events in climate change and water cycle dynamics;
  • Theoretical approaches for extreme event statistics in climate science.

Looking forward to receiving your contribution.

Dr. Marcello Petitta
Guest Editor

Manuscript Submission Information

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Keywords

  • extreme events
  • drought
  • water
  • tipping points
  • machine learning
  • mathematical modelling of extremes
  • water cycle
  • precipitation extremes
  • extreme events statistical methods

Published Papers (1 paper)

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Research

19 pages, 7064 KiB  
Article
Prediction of Droughts in the Mongolian Plateau Based on the CMIP5 Model
by Yongzhen Li, Siqin Tong, Yongbin Bao, Enliang Guo and Yuhai Bao
Water 2020, 12(10), 2774; https://doi.org/10.3390/w12102774 - 05 Oct 2020
Cited by 9 | Viewed by 2959
Abstract
Understanding the variations of future drought under climate warming can provide the basis for mitigation efforts. This study utilized the standardized precipitation evapotranspiration index (SPEI), empirical mode decomposition (EMD) and empirical orthogonal function analysis (EOF) to predict the spatiotemporal variation of future drought [...] Read more.
Understanding the variations of future drought under climate warming can provide the basis for mitigation efforts. This study utilized the standardized precipitation evapotranspiration index (SPEI), empirical mode decomposition (EMD) and empirical orthogonal function analysis (EOF) to predict the spatiotemporal variation of future drought under the representative concentration pathway RCP4.5 and RCP8.5 scenarios within the Mongolian Plateau over the period 2020–2100. The SPEI was computed using temperature and precipitation data generated by the fifth stage of the Coupled Model Intercomparison Project (CMIP5). The results under both the RCP4.5 and RCP8.5 scenarios showed increasing changes in temperature and precipitation. Both scenarios indicated increases in drought, with those under RCP8.5 much more extreme than that under RCP4.5. Under both scenarios, the climate showed an abrupt change to become drier, with the change occurring in 2041 and 2054 for the RCP4.5 and RCP8.5 scenarios, respectively. The results also indicated future drought to be more extreme in Mongolia than in Inner Mongolia. The simulated drought pattern showed an east–west antiphase and a north–south antiphase distribution based on EOF. The frequency of drought was higher under RCP8.5 compared to that under RCP4.5, with the highest frequencies under both scenarios occurring by the end of the 21st century, followed by the mid-21st century and early 21st century. The findings of this research can provide a solid foundation for the prevention, early warning and mitigation of drought disasters within the context of climate change in the Mongolian Plateau. Full article
(This article belongs to the Special Issue Drought and Extreme Events Caused by Climate Changes)
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