Compilation, Integration, and Organization of Interdisciplinary Approaches to Climate Change Impacts

A special issue of Climate (ISSN 2225-1154). This special issue belongs to the section "Climate Dynamics and Modelling".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 2238

Special Issue Editors


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Guest Editor
Department of Economics, Sapporo Gakuin University, Ebetsu 069-8555, Japan
Interests: statistics of climate variability; nonlinear phenomena in physics; solitons and solitary waves; information theory; complex systems

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Guest Editor
Department of Mathematical and Informatics Sciences, Physical Sciences and Earth Sciences (MIFT), University of Messina, Viale F. Stagno D’Alcontres 31, 98166 Messina, Italy
Interests: structural and dynamical characterization of material systems; spectral characterization technology
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Guest Editor
Meteoceanics Institute for Complex System Science, Washington, DC 20004, USA
Interests: physics of complex systems; information theory; nonlinear statistical physics; nonlinear dynamics; nonlinear statistics; fluid dynamical systems; climate dynamics; earth system dynamics; nonlinear geophysics; atmospheric physics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Appreciating, identifying, and predicting the signatures of climate change impacts have beyond doubt been regarded as one of the most urgent topics in contemporary climatic studies. To date, a number of attempts have been reported to apply existing quantitative methods for elucidating the underlying mechanism of the impacts. Typical examples are given as detrended fluctuation analysis, variationally optimized Markov analysis, Monte Carlo, wavelet transformations, multifractals, information-theoretic analysis, multiscale entropy, statistical linguistics, convergent cross mapping, Mahalanobis distance metrics, singular spectral analysis, Lyapunov method, Minkowski distance functions, vectorial rotations, and stochastic resonances. With this trend in mind, we are now in the best position to integrate interdisciplinary efforts as an organic whole.

The present Special Issue aims at compiling, integrating, and organizing statistical approaches to the time-series climatic data that are represented not only with temperatures and precipitations, but also with humidities, air pressures, wind velocities, sea levels, and ice thicknesses.  

Both original and review articles, which deal with such transdisciplinary attempts as sharing a methodology with physiologists and economists as well as with electronics, information, and communication engineers, are welcome but approaches in which one can find a special novelty for the analysis of time-dependent climatic data are welcome as well.

Prof. Dr. Kazuya Hayata
Prof. Dr. Salvatore Magazù
Prof. Dr. Rui A. P. Perdigão
Guest Editors

Manuscript Submission Information

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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. Climate 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 1800 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

  • predicting global and/or regional climate anomalies
  • statistical physics applied to climate studies
  • symbolic dynamics
  • permutation entropy
  • detrended fluctuation analysis
  • distinguishing chaotic and stochastic dynamics
  • comparative studies between Fisher’s and Bayes’ statistics
  • complex networks of world stations

Published Papers (1 paper)

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Research

11 pages, 7314 KiB  
Article
Changing Climatic Conditions in Czechia Require Adaptation Measures in Agriculture
by Martin Mozny, Lenka Hajkova, Vojtech Vlach, Veronika Ouskova and Adela Musilova
Climate 2023, 11(10), 210; https://doi.org/10.3390/cli11100210 - 20 Oct 2023
Cited by 1 | Viewed by 1751
Abstract
Changes in climatic conditions increase risks associated with crop production in certain regions. Early detection of these changes enables the implementation of suitable adaptation measures in the local area, thereby stabilising agricultural production. Our analysis shows a significant shift in climatic conditions in [...] Read more.
Changes in climatic conditions increase risks associated with crop production in certain regions. Early detection of these changes enables the implementation of suitable adaptation measures in the local area, thereby stabilising agricultural production. Our analysis shows a significant shift in climatic conditions in Czechia between 1961 and 2020. We examined the changes in observed temperature conditions, precipitation distribution, drought occurrences, and frost incidents at a high resolution (0.5 × 0.5 km). The outputs show a significant increase in air temperatures and drought occurrence. Temperature totals above 5 °C in 1991–2020 were 15% higher than in 1961–1990. Furthermore, the relative change in totals above 10 °C was 26% after 1991. Over the last 30 years, drought incidence was four times more frequent than in 1961–1990, particularly in spring. In contrast, no significant changes in the distribution of precipitation occurred, and there was a slight decrease in the probability of frost during the growing season. Ongoing climate change brings warmer and drier conditions to higher-altitude regions in Czechia. Assessing climatic conditions on a global scale is less precise for relatively small and topographically diverse countries like Czechia due to coarse resolution. Therefore, a high-resolution analysis is more appropriate for these countries. Full article
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