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Feature Papers for Section "Climate Dynamics and Modelling"
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Feature Papers for Section "Climate Dynamics and Modelling"

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

Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 17790

Special Issue Editor

Prof. Dr. Salvatore Magazù

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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
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As Section Editor-in-Chief of Climate Dynamics and Modelling in Climate, I am pleased to announce the Special Issue "Feature Papers of Section“Climate Dynamics and Modelling”". This Special Issue is designed to publish high-quality papers in Climate. We welcome submissions from Editorial Board Members and outstanding scholars invited by the Editorial Board and by the Editorial Office. The scope of this Special Issue includes, but is not limited to, all the aspects of the dynamics and modeling governing the global climate system.

You are welcome to send short proposals for submissions to our Editorial Office ([email protected]). They will first be evaluated by academic editors, and then selected papers will be thoroughly and rigorously peer reviewed. The fees for all the selected papers will be fully waived.

Prof. Dr. Salvatore Magazù
Guest Editor

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. 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

  • climate dynamics
  • climate modeling
  • physical and mathematical approaches
  • analogic modeling
  • climate and complex systems dynamics
  • case studies
  • big data
  • machine learning approach
  • climate and meteorology correlations
  • numerical climate and weather predictions
  • dynamics and modeling of volcanic ash emissions
  • climate dynamics and modeling by satellite images investigations
  • data assimilation techniques
  • transdisciplinary approach to climate dynamics and modeling
  • climate dynamics and modeling in education.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (6 papers)

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Research

18 pages, 2249 KiB  
Article
The Role of Instability Indices in Forecasting Thunderstorm and Non-Thunderstorm Days across Six Cities in India
by Kopal Arora, Kamaljit Ray, Suresh Ram and Rajeev Mehajan
Climate 2023, 11(1), 14; https://doi.org/10.3390/cli11010014 - 4 Jan 2023
Cited by 9 | Viewed by 2942
Abstract
Thunderstorms are one of the most damaging natural hazards demanding in-depth understanding and prediction. These convective systems form in an unstable environment which is quantitatively expressed in terms of instability indices. These indices are studied over six locations across the Indian landmass in [...] Read more.
Thunderstorms are one of the most damaging natural hazards demanding in-depth understanding and prediction. These convective systems form in an unstable environment which is quantitatively expressed in terms of instability indices. These indices are studied over six locations across the Indian landmass in an attempt to predict thunderstorm activity on any given day. A combination of multiple regression, logistic regression, and range analysis provides new insight into the prediction of these storms. A supervised machine learning-based logistic regression model is developed in this study for thunderstorm prediction over Patna and can be further extended for operational forecasting of Thunderstorms over the region. Critical thresholds for the instability indices are determined over the considered locations providing valuable insight into the domain of Thunderstorm prediction Full article
(This article belongs to the Special Issue Feature Papers for Section "Climate Dynamics and Modelling")
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22 pages, 4868 KiB  
Article
Revealing a Tipping Point in the Climate System: Application of Symbolic Analysis to the World Precipitations and Temperatures
by Kazuya Hayata
Climate 2022, 10(12), 195; https://doi.org/10.3390/cli10120195 - 5 Dec 2022
Viewed by 2804
Abstract
Climate variabilities over the period of 80 years (1930–2010) are analyzed by the combined use of divergence measures and rank correlation. First, on the basis of a statistical linguistics procedure, the m-th order differences of the monthly mean precipitations and temperatures on [...] Read more.
Climate variabilities over the period of 80 years (1930–2010) are analyzed by the combined use of divergence measures and rank correlation. First, on the basis of a statistical linguistics procedure, the m-th order differences of the monthly mean precipitations and temperatures on the globe are symbolized according to a binary coding rule. Subsequently, the annual 12-bit binary sequence for a station is divided into twelve 6-bit sequences by scanning it over a year. Computed results indicate that there is an optimal order of differences with which one can reveal the variabilities most distinctly. Specifically, it is found that for the analysis of precipitations, the second differences (m = 2) are most useful, whereas, for the temperatures, the third differences (m = 3) are preferable. A detailed comparison between the information-theoretic and the ranking methods suggests that along with the stability and coherence, owing to its ability to make an appeal to the eyes, the latter is superior to the former. Full article
(This article belongs to the Special Issue Feature Papers for Section "Climate Dynamics and Modelling")
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15 pages, 5958 KiB  
Article
Temporal and Spatial Distribution of Lightning Activity over Bulgaria during the Period 2012–2021 Based on ATDnet Lightning Data
by Boryana Dimitrova Tsenova and Ilian Gospodinov
Climate 2022, 10(11), 184; https://doi.org/10.3390/cli10110184 - 21 Nov 2022
Cited by 3 | Viewed by 2194
Abstract
In the present study, lightning activity based on data from ATDnet over the territory of Bulgaria for the 10-year period between 2012 and 2021 is evaluated. This analysis shows the highest lightning activity with the greatest number of thunderstorm days in June. December [...] Read more.
In the present study, lightning activity based on data from ATDnet over the territory of Bulgaria for the 10-year period between 2012 and 2021 is evaluated. This analysis shows the highest lightning activity with the greatest number of thunderstorm days in June. December is the month with the lowest number of flashes and thunderstorm days. It was found that more than 30% of thunderstorm days annually are in the cold half of the year over the southern part of the considered domain. The average diurnal distribution showed a maximum of lightning activity between 12 and 15 UTC, while over some mountainous and sea regions it is between 03 and 06 UTC. The spatial distribution of flash density (fl km−2 y−1) reveals that the number of flashes and the number of thunderstorm days increase with altitude up to 1800 m and then decrease for higher altitudes. Full article
(This article belongs to the Special Issue Feature Papers for Section "Climate Dynamics and Modelling")
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20 pages, 20966 KiB  
Article
A Comparative Study on the Performances of Spectral Nudging and Scale-Selective Data Assimilation Techniques for Hurricane Track and Intensity Simulations
by Xia Sun and Lian Xie
Climate 2022, 10(11), 168; https://doi.org/10.3390/cli10110168 - 3 Nov 2022
Viewed by 2416
Abstract
It is a common practice to use a buffer zone to damp out spurious wave growth due to computational error along the lateral boundary of limited-area weather and climate models. Although it is an effective technique to maintain model stability, an unintended side [...] Read more.
It is a common practice to use a buffer zone to damp out spurious wave growth due to computational error along the lateral boundary of limited-area weather and climate models. Although it is an effective technique to maintain model stability, an unintended side effect of using such buffer zones is the distortion of the data passing through the buffer zone. Various techniques are introduced to enhance the communication between the limited-area model’s inner domain and the outer domain, which provides lateral boundary values for the inner domain. Among them, scale-selective data assimilation (SSDA) and the spectral nudging (SPNU) techniques share similar philosophy, i.e., directly injecting the large-scale components of the atmospheric circulation from the outer model domain into the interior grids of the inner model domain by-passing the lateral boundary and the buffer zone, but the two methods are taking different implementation approaches. SSDA utilizes a 3-dimensional variational data assimilation procedure to accomplish the data injection objective, whereas SPNU uses a nudging process. In the present study, the two approaches are evaluated comparatively for simulating hurricane track and intensity in a pair of cases: Jeanne (2004) and Irma (2017) using the Weather Research and Forecasting (WRF) model. The results indicate that both techniques are effective in improving tropical cyclone intensity and track simulations by reducing the errors of the large-scale circulation in the inner model domain. The SSDA runs produced better simulations of temperature and humidity fields which are not directly nudged. The SSDA runs also produced more accurate storm intensities in both cases and more realistic structure in Hurricane Jeanne’s case than those produced by the SPNU runs. It should be noted, however, that extending these case study results to more general situations requires additional studies covering a large number of additional cases. Full article
(This article belongs to the Special Issue Feature Papers for Section "Climate Dynamics and Modelling")
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17 pages, 7959 KiB  
Article
New Air Temperature- and Wind Speed-Based Clothing Thermal Resistance Scheme—Estimations for the Carpathian Region
by Ferenc Ács, Erzsébet Kristóf, Amanda Imola Szabó, Hajnalka Breuer, Zsófia Szalkai and Annamária Zsákai
Climate 2022, 10(9), 131; https://doi.org/10.3390/cli10090131 - 1 Sep 2022
Cited by 1 | Viewed by 2539
Abstract
A new clothing thermal resistance scheme is presented and verified for the Carpathian region and for the time period 1971–2000. The scheme is as simple as possible by connecting operative temperature to air temperature, which allows for it to only use air temperature [...] Read more.
A new clothing thermal resistance scheme is presented and verified for the Carpathian region and for the time period 1971–2000. The scheme is as simple as possible by connecting operative temperature to air temperature, which allows for it to only use air temperature and wind speed data as meteorological inputs. Another strength of the scheme is that a walking person’s metabolic heat flux density is also simply simulated without having to regard any thermoregulation processes. Human thermal load in the above region is characterised by a representative adult Hungarian male and female with a body mass index of 23–27 kgm−2. Our most important findings are as follows: (1) human thermal load in the Carpathian region is relief dependent; (2) the scheme cannot be applied in the lowland areas of the region in the month of July since the energy balance is not met; (3) in the same areas but during the course of the year, clothing thermal resistance values are between 0.4 and 1 clo; (4) clothing thermal resistance can reach 1–1.2 clo in the mountains in the month of July, but during the course of the year this value is 1.8 clo; and (5) the highest clothing thermal resistance values can be found in January reaching about 2.5 clo. The scheme may be easily applied to any another region by determining new, region-specific, operative temperature–air temperature relationships. Full article
(This article belongs to the Special Issue Feature Papers for Section "Climate Dynamics and Modelling")
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19 pages, 6821 KiB  
Article
Regional Responses of the Northern Hemisphere Subtropical Jet Stream to Reduced Arctic Sea Ice Extent
by José Luis Rodriguez Solis, Cuauhtémoc Turrent and Markus Gross
Climate 2022, 10(7), 108; https://doi.org/10.3390/cli10070108 - 16 Jul 2022
Cited by 2 | Viewed by 3649
Abstract
The effect of Arctic sea ice loss on the boreal winter regional trends of wind speed and latitudinal position of the Northern Hemisphere subtropical jet stream (STJ) in 1980–2012 is investigated. Two sets of global simulations with reduced Arctic sea ice extent are [...] Read more.
The effect of Arctic sea ice loss on the boreal winter regional trends of wind speed and latitudinal position of the Northern Hemisphere subtropical jet stream (STJ) in 1980–2012 is investigated. Two sets of global simulations with reduced Arctic sea ice extent are analyzed: simulations that, south of 70 N, use a climatological annual cycle of the sea surface temperature (SST) and a second set that uses full SST variability. Results with the climatological SST have a significant but weak response of the STJ wind speed and latitudinal position to the warmer Arctic: the wind speed generally decreases and the jet core is displaced equatorward. However, in the realistic SST simulations, the effect of Arctic warming is only slightly evident in a small equatorward shift of the jet over the Atlantic basin. Over the Pacific basin the STJ is mostly driven by tropical and mid-latitude SST variability, with little influence from the Arctic region. A weakening and poleward shift of the STJ that is observed in the realistic SST simulations over the Pacific basin is attributed to negative SST trends in the tropical Pacific and the consequent weakening of the mid-latitude meridional gradient of geopotential height in the upper troposphere. Full article
(This article belongs to the Special Issue Feature Papers for Section "Climate Dynamics and Modelling")
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