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Observations and Modeling of Precipitation Extremes and Tropical Cyclones (2nd...
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Observations and Modeling of Precipitation Extremes and Tropical Cyclones (2nd Edition)

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: 6 June 2025 | Viewed by 3040

Special Issue Editors

Dr. Muhammad Jehanzaib

E-Mail Website
Guest Editor
School of the Natural and Built Environment, Queen’s University Belfast, Belfast, UK
Interests: spatial drought analysis; machine learning; SPI; drought forecasting; climate change and drought; remote sensing of drought; regional drought indicators
Special Issues, Collections and Topics in MDPI journals
Dr. Shoaib Ali

E-Mail Website
Guest Editor
Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen 518005, China
Interests: terrestrial and groundwater storage assessment; hydrological and groundwater drought events; climate extremes; machine learning

Special Issue Information

Dear Colleagues,

This Special Issue is a sequel to the first Special Issue entitled “Observations and Modeling of Precipitation Extremes and Tropical Cyclones” (https://www.mdpi.com/journal/atmosphere/special_issues/34ATGG3JZ7), published in Atmosphere in 2024.

Extreme precipitation events have increased in frequency and intensity across many regions of the world due to climate variations. The simulations of climate models has also evidenced that precipitation extremes will intensify in the future in response to a warming climate. Various natural disasters, such as tropical cyclones, flooding, droughts, soil erosion, and landslides, are associated with extreme precipitation events. Anthropogenic forcing has been shown to have contributed to the intensification of precipitation extremes over northern hemisphere land. Therefore, research on extreme precipitation has become a hot topic. Different approaches have been used to model extreme precipitations, such as index analysis, frequency analysis, and spatial trend analysis. These methods use statistical technology to disperse the climatic factors into the related indices to examine the time interval of the recurrence of an extreme event for many years; thus, these methods are very significant to engineering design and planning. Further, the challenge of modeling dynamics needs to be addressed in extreme precipitation analysis. The core aim of this Special Issue is to contribute novel modeling frameworks as well as innovative approaches for extreme precipitation modeling in the field of meteorology and safeguarding water resources under climate change.

Dr. Muhammad Jehanzaib
Dr. Shoaib Ali
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. Atmosphere 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 2400 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 extremes
  • droughts
  • floods
  • non-stationarity
  • climate change
  • anthropocene
  • typhoon
  • extreme events
  • forecasting
  • machine learning
  • frequency analysis
  • statistical modeling

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Published Papers (3 papers)

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Research

24 pages, 6847 KiB  
Article
Comparing Reflectivity from Space-Based and Ground-Based Radars During Detection of Rainbands in Two Tropical Cyclones
by Corene J. Matyas, Stephanie E. Zick and Kimberly M. Wood
Atmosphere 2025, 16(3), 307; https://doi.org/10.3390/atmos16030307 - 6 Mar 2025
Viewed by 528
Abstract
With varying tangential winds and combinations of stratiform and convective clouds, tropical cyclones (TCs) can be difficult to accurately portray when mosaicking data from ground-based radars. This study utilizes the Dual-frequency Precipitation Radar (DPR) from the Global Precipitation Measurement Mission (GPM) satellite to [...] Read more.
With varying tangential winds and combinations of stratiform and convective clouds, tropical cyclones (TCs) can be difficult to accurately portray when mosaicking data from ground-based radars. This study utilizes the Dual-frequency Precipitation Radar (DPR) from the Global Precipitation Measurement Mission (GPM) satellite to evaluate reflectivity obtained using four sampling methods of Weather Surveillance Radar 1988-Doppler data, including ground radars (GRs) in the GPM ground validation network and three mosaics, specifically the Multi-Radar/Multi-Sensor System plus two we created by retaining the maximum value in each grid cell (MAX) and using a distance-weighted function (DW). We analyzed Hurricane Laura (2020), with a strong gradient in tangential winds, and Tropical Storm Isaias (2020), where more stratiform precipitation was present. Differences between DPR and GR reflectivity were larger compared to previous studies that did not focus on TCs. Retaining the maximum value produced higher values than other sampling methods, and these values were closest to DPR. However, some MAX values were too high when DPR time offsets were greater than 120 s. The MAX method produces a more consistent match to DPR than the other mosaics when reflectivity is <35 dBZ. However, even MAX values are 3–4 dBZ lower than DPR in higher-reflectivity regions where gradients are stronger and features change quickly. The DW and MRMS mosaics produced values that were similar to one another but lower than DPR and MAX values. Full article
(This article belongs to the Special Issue Observations and Modeling of Precipitation Extremes and Tropical Cyclones (2nd Edition))
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12 pages, 3011 KiB  
Article
Geo-Statistical Characterization of Annual Maximum Daily Rainfall Variability in Semi-Arid Regions
by Mohammed Achite, Tommaso Caloiero, Muhammad Jehanzaib, Andrzej Wałęga, Alban Kuriqi and Gaetano Pellicone
Atmosphere 2024, 15(12), 1519; https://doi.org/10.3390/atmos15121519 - 19 Dec 2024
Cited by 1 | Viewed by 776
Abstract
In the Wadi Cheliff basin (Algeria), a 48-year (1971–2018) time series of annual maximum daily rainfall was studied to identify and quantify trends observed at 150 rain gauges. Initial trends in annual maximum daily rainfall were determined using the Mann–Kendall test, with a [...] Read more.
In the Wadi Cheliff basin (Algeria), a 48-year (1971–2018) time series of annual maximum daily rainfall was studied to identify and quantify trends observed at 150 rain gauges. Initial trends in annual maximum daily rainfall were determined using the Mann–Kendall test, with a significance level of 95%. The slope or increase/decrease in the annual maximum daily precipitation was assessed using the Theil–Sen estimator. A running trend analysis was then performed to quantify the effects of different time windows on trend detection. Finally, to assess the different spatial distribution of annual maximum daily precipitation during the observation period, spatial analysis was performed using a geo-statistical approach for the whole observation period and at different decades. The results showed a predominant negative trend in annual maximum daily rainfall (about 11% of rain gauges at a 95% significance level), mainly affecting the north-eastern area of the catchment. The spatial distribution of annual maximum daily rainfall showed high rainfall variability in the period of 1970–1980, with a decrease in the decades of 1980–1990 and 2010–2017 when the maximum values were more evenly distributed across the region. Full article
(This article belongs to the Special Issue Observations and Modeling of Precipitation Extremes and Tropical Cyclones (2nd Edition))
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16 pages, 31264 KiB  
Article
Spatiotemporal Variation Characteristics of Extreme Precipitation in Henan Province Based on RClimDex Model
by Zhijia Gu, Yuemei Li, Mengchen Qin, Keke Ji, Qiang Yi, Panying Li and Detai Feng
Atmosphere 2024, 15(11), 1399; https://doi.org/10.3390/atmos15111399 - 20 Nov 2024
Viewed by 1101
Abstract
Global warming has led to an increasing frequency and intensity of extreme precipitation events worldwide. The extreme precipitation of Henan Province in central China usually occurs in summer, with the climate transition from the northern subtropical to the warm temperate climate. Compared with [...] Read more.
Global warming has led to an increasing frequency and intensity of extreme precipitation events worldwide. The extreme precipitation of Henan Province in central China usually occurs in summer, with the climate transition from the northern subtropical to the warm temperate climate. Compared with the study of extreme precipitation events in other regions, the study of Henan Province pays less attention. In order to systematically understand the spatial and temporal characteristics of extreme precipitation in Henan Province, this study applied RClimDex model to obtain nine extreme precipitation indices based on daily precipitation data from 90 meteorological stations from 1981 to 2020. Linear propensity estimation, M-K mutation test, Morlet wavelet analysis, and geostatistical analysis were used to investigate the spatial and temporal variation characteristics of the extreme precipitation indices in the region. The results indicated that continuous dry days (CDD), number of heavy rain days (R20mm), maximum daily precipitation (Rx1day), maximum precipitation for 5 consecutive days (Rx5day), and precipitation intensity (SDII) showed an overall increasing trend, but none passed the significance test (p > 0.01). Extremely strong precipitation (R99p) and Rx5day changed abruptly in 1994, and Rx1day and SDII changed abruptly in 2004. The seven extreme precipitation indices, except CDD and continuous wet days (CWD), had a 30-year cyclical pattern. The multi-year average of extreme precipitation indices showed that the CDD gradually decreased from north to south, CWD and R20mm gradually increased from north to south. Rx1day and Rx5day gradually increased from northwest to southeast, and SDII increased from west to east. The results can contribute valuable insights to extreme precipitation trends and future climate predictions in Henan Province and provide scientific support for coping with extreme precipitation changes and disaster prevention. Full article
(This article belongs to the Special Issue Observations and Modeling of Precipitation Extremes and Tropical Cyclones (2nd Edition))
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