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Earth
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Modelling and Forecasting Extreme Climate Events
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Modelling and Forecasting Extreme Climate Events

A special issue of Earth (ISSN 2673-4834).

Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 3471

Special Issue Editors

Prof. Dr. Christina Anagnostopoulou

E-Mail Website
Guest Editor
Department of Meteorology Climatology, School of Geology, Aristotle University of Thessaloniki, GR54124 Thessaloniki, Greece
Interests: climatology; synoptic climatology; weather types; dynamic climatology; teleconnection patterns; climate change; regional climate models; dynamical downscaling extremes—climate hazards—statistical climatology
Special Issues, Collections and Topics in MDPI journals
Dr. Georgia Lazoglou

E-Mail Website
Guest Editor
The Cyprus Institute, Climate and Atmosphere Research Center (CARE-C), 2121 Aglantzia, Cyprus
Interests: climatology; climate change; extremes; climate hazards; statistical climatology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As the world’s climate changes, extreme events are becoming more frequent and intense. Nowadays, the current state-of-the-art climate models consist of fundamental tools for analyzing and predicting climate and weather extremes. The accuracy of climate models’ simulations is high for long-duration extremes (mainly monthly or seasonal scales). In contrast, there is great insufficiency due to uncertainty around high-resolution and short-timescale extreme events. Hence, understanding the mechanisms leading to the occurrence of climate and weather extremes will be the basis for assessing their predictability and enabling their prediction.

This Special Issue of Climate is devoted to promoting advances in understanding, modeling, and predicting climate extremes. Pertinent examples of topics for this Special Issue include types of extreme; the frequency, intensity and duration of climate extremes; observed and projected climate extremes; short- and medium-range forecasts of weather extremes; modeling impacts of weather and climate extremes; statistical aspects of extremes; case studies of extreme events; and sensitivity experiments for extremes prediction.

The Special Issue “Modelling and Forecasting Extreme Climate Events” is jointly organized between “Climate” and “Earth” journals. Contributors are required to check the website below and follow the specific instructions for authors:
https://www.mdpi.com/journal/climate/instructions
https://www.mdpi.com/journal/earth/instructions

You may choose our Joint Special Issue in Climate.

Dr. Christina Anagnostopoulou
Dr. Georgia Lazoglou
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. Earth is an international peer-reviewed open access quarterly 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 1200 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

  • extreme weather
  • climate change
  • extreme climate indices
  • extreme temperature
  • extreme precipitation
  • storms
  • heatwaves
  • drought
  • floods
  • hurricanes
  • extreme value theory

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Published Papers (1 paper)

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Research

15 pages, 5430 KiB  
Article
Estimating the Statistical Significance of Cross–Correlations between Hydroclimatic Processes in the Presence of Long–Range Dependence
by Aristotelis Koskinas, Eleni Zaharopoulou, George Pouliasis, Ilias Deligiannis, Panayiotis Dimitriadis, Theano Iliopoulou, Nikos Mamassis and Demetris Koutsoyiannis
Earth 2022, 3(3), 1027-1041; https://doi.org/10.3390/earth3030059 - 15 Sep 2022
Cited by 4 | Viewed by 2526
Abstract
Hydroclimatic processes such as precipitation, temperature, wind speed and dew point are usually considered to be independent of each other. In this study, the cross–correlations between key hydrological-cycle processes are examined, initially by conducting statistical tests, then adding the impact of long-range dependence, [...] Read more.
Hydroclimatic processes such as precipitation, temperature, wind speed and dew point are usually considered to be independent of each other. In this study, the cross–correlations between key hydrological-cycle processes are examined, initially by conducting statistical tests, then adding the impact of long-range dependence, which is shown to govern all these processes. Subsequently, an innovative stochastic test that can validate the significance of the cross–correlation among these processes is introduced based on Monte-Carlo simulations. The test works as follows: observations obtained from numerous global-scale timeseries were used for application to, and a comparison of, the traditional methods of validation of statistical significance, such as the t-test, after filtering the data based on length and quality, and then by estimating the cross–correlations on an annual-scale. The proposed method has two main benefits: it negates the need of the pre-whitening data series which could disrupt the stochastic properties of hydroclimatic processes, and indicates tighter limits for upper and lower boundaries of statistical significance when analyzing cross–correlations of processes that exhibit long-range dependence, compared to classical statistical tests. The results of this analysis highlight the need to acquire cross–correlations between processes, which may be significant in the case of long-range dependence behavior. Full article
(This article belongs to the Special Issue Modelling and Forecasting Extreme Climate Events)
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