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Remote Sensing
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Satellite Microwave Remote Sensing for Severe Storms Detection
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Satellite Microwave Remote Sensing for Severe Storms Detection

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 9747

Special Issue Editors

Dr. Sante Laviola

E-Mail Website
Guest Editor
National Research Council of Italy (CNR), Institute of Atmospheric Sciences and Climate (ISAC), Bologna, Italy
Interests: algorithm development; satellite remote sensing of severe storms; climate studies of extreme weather; atmospheric rivers
Special Issues, Collections and Topics in MDPI journals
Dr. Yalei You

E-Mail Website
Guest Editor
Earth System Science Interdisciplinary Center/Cooperative Institute for Climate and Satellites, University of Maryland, College Park, MD, USA
Interests: passive microwave precipitation retrieval; precipitation dataset validation

Special Issue Information

Dear Colleagues,

The last two decades have seen significant increasing precipitation products from satellite microwaves. Since the launch of the Tropical Rainfall Measuring Mission (TRMM) and the Advanced Microwave Sounding Unit (AMSU) aboard NOAA 15 in 1997–98, the advancement of sensor technology equipped in new satellite missions strongly improved the sampling of the atmosphere, allowing the retrieval of several hydrological parameters. New architectures of passive and active satellite sensors provided accurate measurements of precipitation by improving the retrieval of frozen hydrometeors. Currently, a wide range of microwave sensors orbiting around the Earth offers an unprecedented opportunity to investigate precipitating systems by identifying cloud-scale details useful to better classify cloud types and evaluate the severity degree of storms.

This Special Issue will publish contributions from research, operational products, and data assimilation capabilities of microwave satellites used in support of the investigation of severe storms. Studies that address connections with essential climate variables are particularly welcome. Contributions from CubeSat applications and theoretical studies with new microwave sensors onboard future satellite missions are also strongly encouraged.

Dr. Sante Laviola
Dr. Yalei You
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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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

  • Passive and active satellite microwaves
  • Precipitation and heavy rain
  • Hail and snowfall
  • Extreme weather
  • Climatology
  • Water Cycle
  • Algorithms, theoretical methods, and operational products
  • Precipitation dataset validation

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Published Papers (3 papers)

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Research

27 pages, 3155 KiB  
Article
Rainfall Consistency, Variability, and Concentration over the UAE: Satellite Precipitation Products vs. Rain Gauge Observations
by Faisal Baig, Muhammad Abrar, Haonan Chen and Mohsen Sherif
Remote Sens. 2022, 14(22), 5827; https://doi.org/10.3390/rs14225827 - 17 Nov 2022
Cited by 4 | Viewed by 2705
Abstract
Recent advancements in remote sensing have led to the development of several useful technologies that would significantly improve our understanding of atmospheric sciences. The ability to identify atmospheric conditions and determine the possibility and intensity of rainfall over a specific location represents one [...] Read more.
Recent advancements in remote sensing have led to the development of several useful technologies that would significantly improve our understanding of atmospheric sciences. The ability to identify atmospheric conditions and determine the possibility and intensity of rainfall over a specific location represents one of the most important advantages. However, the use of remote sensing to measure precipitation in arid regions has revealed significant disparities due to a mixture of climatic and terrestrial factors. The objective of this study is to assess the precipitation consistency, variability, and concentration over the UAE using four multi-satellite remote sensing products, namely CHIRPS, CMORPH, GPM-IMERG, and the PERSIANN-CDR, considering daily rainfall data from 50 rain gauges for the period from 2004 through 2020. The study area is divided into various geomorphological regions to assess the accuracy of the products in different regions. Results reveal that the products with a finer spatial resolution such as CHIRPS and CMORPH are better in terms of annual and daily average values. CHIRPS and GPM-IMERG demonstrated better POD values of 0.80 and 0.78, respectively, while CMORPH and the PERSIANN-CDR showed POD values of 0.72 and 0.44, respectively. The correlation and error estimate analysis showed that the performance of different products varies in each region. The PERSIANN-CDR registered the highest correlation of 0.8 for the East Coast, while for other regions it could not correlate well. IMERG and CHIRPS were able to exhibit a good correlation value (up to 0.8) with the gauge observations. Precipitation concentration and variability analysis revealed that GPM-IMERG represents a better alternative to gauge data. It is concluded that multiple hydro-climatological measures should be utilized to assess the effectiveness of satellite products and select the best product for specific studies. Full article
(This article belongs to the Special Issue Satellite Microwave Remote Sensing for Severe Storms Detection)
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22 pages, 3982 KiB  
Article
Clouds’ Microphysical Properties and Their Relationship with Lightning Activity in Northeast Brazil
by Lizandro Pereira de Abreu, Weber Andrade Gonçalves, Enrique Vieira Mattos, Pedro Rodrigues Mutti, Daniele Torres Rodrigues and Marcos Paulo Araújo da Silva
Remote Sens. 2021, 13(21), 4491; https://doi.org/10.3390/rs13214491 - 8 Nov 2021
Cited by 2 | Viewed by 3068
Abstract
The Northeast region of Brazil (NEB) has a high rate of deaths from lightning strikes (18% of the country’s total). The region has states, such as Piauí, with high mortality rates (1.8 deaths per million), much higher than the national rate (0.8) and [...] Read more.
The Northeast region of Brazil (NEB) has a high rate of deaths from lightning strikes (18% of the country’s total). The region has states, such as Piauí, with high mortality rates (1.8 deaths per million), much higher than the national rate (0.8) and the NEB rate (0.5). In this sense, the present work analyzes the microphysical characteristics of clouds with and without the occurrence of total lightning. For this purpose, data from the Lightning Imaging Sensor (LIS), TRMM Microwave Imager (TMI) and Precipitation Radar (PR), aboard the Tropical Rainfall Measuring Mission (TRMM) satellite from 1998 to 2013 were used. The TRMM data were analyzed to establish a relationship between the occurrence of lightning and the clouds’ microphysical characteristics, comparing them as a function of lightning occurrence classes, spatial location and atmospheric profiles. A higher lightning occurrence is associated with higher values of ice water path (>38.9 kg m−2), rain water path (>2 kg m−2), convective precipitation (>5 mm h−1) and surface precipitation (>7 mm h−1), in addition to slightly higher freezing level height values. Reflectivity observations (>36 dBZ) demonstrated typical convective profile curves, with higher values associated with classes with higher lightning densities (class with more than 6.8 flash km−2 year−1). Full article
(This article belongs to the Special Issue Satellite Microwave Remote Sensing for Severe Storms Detection)
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21 pages, 7315 KiB  
Article
A 4-Year Climatological Analysis Based on GPM Observations of Deep Convective Events in the Mediterranean Region
by Dario Hourngir, Giulia Panegrossi, Daniele Casella, Paolo Sanò, Leo Pio D’Adderio and Chuntao Liu
Remote Sens. 2021, 13(9), 1685; https://doi.org/10.3390/rs13091685 - 27 Apr 2021
Cited by 8 | Viewed by 2498
Abstract
Since early March 2014, the NASA/JAXA Global Precipitation Measurement Core- Observatory (GPM-CO) satellite has allowed analysis of precipitation systems around the globe, thanks to the capabilities of the GPM Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR). In this work, we demonstrate how [...] Read more.
Since early March 2014, the NASA/JAXA Global Precipitation Measurement Core- Observatory (GPM-CO) satellite has allowed analysis of precipitation systems around the globe, thanks to the capabilities of the GPM Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR). In this work, we demonstrate how GPM-CO measurements obtained from 4 years of observations over the Mediterranean area can be used as an extremely effective tool to study the main climatological characteristics of the most intense Mediterranean storm structures. DPR and GMI-based Precipitation Features (PFs) parameters are used as proxies of the vertical structure and microphysical properties of these events, and their statistical distribution is analyzed to identify extremes. The analysis of annual, seasonal and geographical distribution of the identified deep convective systems highlights substantial differences in their diurnal cycle and in the distribution between land-sea and summer-winter. There is a general shift of the convective systems from the south (mostly over the sea) in the cold season, to the north (mostly over land) in the warm season. The analysis shows also that the inferred convective intensity is not always related to heavy precipitation. Known DPR and GMI-based criteria were adopted to identify overshooting top events and potential hailstorms, identify extreme deep convection signatures, like those observed for tropical and subtropical systems, and the most intense occur mostly over the sea. Although the analysis is limited to four years, the results show that the GPM-CO offers unprecedented measurements to identify and characterize extreme weather events in the Mediterranean region, with unique potentials for future long-term climatology and interannual variability analysis. Full article
(This article belongs to the Special Issue Satellite Microwave Remote Sensing for Severe Storms Detection)
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