New Perspectives in Climate Modelling and Forecasting

A special issue of Climate (ISSN 2225-1154).

Deadline for manuscript submissions: closed (15 July 2023) | Viewed by 4055

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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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Department of Meteorology and Climatology, School of Geology, Aristotle University of Thessaloniki, University Campus, 54124 Thessaloniki, Greece
Interests: climate variability; artificial neural networks; atmosphere; regional climate modeling; extreme events
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Department of Mathematical and Computer Sciences, Physical and Earth Sciences, University of Messina, Viale Ferdinando Stagno D’Alcontres 31, 98166 Messina, Italy
Interests: complementary spectroscopic techniques; infrared spectroscopy; Raman spectroscopic; neutron scattering; polymers; peo; peg; disaccharides; trehalose; maltose; sucrose
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1. Department of Atmospheric & Environmental Sciences, College of Natural Sciences, Gangneung-Wonju National University (GWNU), Jukheongil 7, Gangneung 25457, Republic of Korea
2. Atmospheric & Oceanic Disaster Research Institute, Dalim Apartment 209 ho, Songjungdong 940-23, Gangneung 25563, Republic of Korea
Interests: numerical modeling of air pollution; air pollutant measurement and assessment; coastal and oceanic atmospheric boundary layer modeling; physical oceanographic modeling (waves and typhoons); statistical modeling (artificial neuron network modeling, multiple regression modeling)
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Special Issue Information

Dear Colleagues,

Climate models are widely used to understand and predict the evolution of the climate system. They use quantitative methods to simulate the interactions of the important drivers of climate, including astronomical conditions as well as atmosphere, oceans, land surface and ice.

Although climate models have been improving in accuracy and efficiency over the past few decades, they still represent a complex endeavor and, due to the large number of involved processes and the interactions among them, spread across climate projections for given future scenarios persist. For these reasons, there is an urgent need to improve their accuracy to provide more confident assessments of the future risks associated with both natural climate variability and human-induced climate change.

Therefore, we welcome the submission of papers covering any aspects of the application of climate models and achievements in accuracy improvement in climate modelling.

Prof. Dr. Salvatore Magazù
Dr. Konstantia Tolika
Dr. Maria Teresa Caccamo
Prof. Dr. Hyo Choi
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.

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Keywords

  • climate model
  • forecasting
  • climate dynamics
  • weather prediction
  • disaster risk prediction

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Published Papers (1 paper)

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Research

17 pages, 2823 KiB  
Article
Assessment of the Spatial Variation in the Occurrence and Intensity of Major Hurricanes in the Western Hemisphere
by Luis-Carlos Martinez, David Romero and Eric J. Alfaro
Climate 2023, 11(1), 15; https://doi.org/10.3390/cli11010015 - 4 Jan 2023
Cited by 5 | Viewed by 3195
Abstract
Major hurricanes are a critical hazard for North and Central America. The present study investigated the trends of occurrence, affectation, and intensity of major hurricanes in the North Atlantic and Northeast Pacific Oceans using GIS applications to the IBTrACS database. The study period [...] Read more.
Major hurricanes are a critical hazard for North and Central America. The present study investigated the trends of occurrence, affectation, and intensity of major hurricanes in the North Atlantic and Northeast Pacific Oceans using GIS applications to the IBTrACS database. The study period ranged from 1970 to 2021. Tropical cyclones were sampled using a grid composed of 3.5° hexagonal cells; in addition, trends were obtained to assess the effect of long-term variability from natural phenomena and climate change. Critical factors influencing these trends at the oceanic scale and for each hexagon were determined using multivariate and multiscale analysis by the application of stepwise analysis and the related ANOVA. The integrated variables related to atmospheric and oceanographic oscillations and patterns, i.e., spatial variables resampled with the same analysis unit and climate indices. Our results indicated marked spatial areas with significant trends in occurrence and intensity. Additionally, there was evidence of linear changes in the number of major hurricanes and an increase in the maximum annual speed of +1.61 m s−1 in the North Atlantic basin and +1.75 m·s−1 in the Northeast Pacific, reported for a 10-year period. In terms of occurrence, there were increases of 19% and 5%, respectively, which may be related to ocean warming and natural variability associated with oceanic and atmospheric circulation. Full article
(This article belongs to the Special Issue New Perspectives in Climate Modelling and Forecasting)
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