Special Issue "Remote Sensing for Precipitation Retrievals"

A special issue of Geomatics (ISSN 2673-7418).

Deadline for manuscript submissions: 31 July 2022.

Special Issue Editors

Prof. Dr. Atsushi Hamada
E-Mail Website
Guest Editor
Faculty of Sustainable Design, University of Toyama, Toyama 930-8555, Japan
Interests: precipitation system climatology; tropical meteorology
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Kenji Nakamura
E-Mail Website
Guest Editor
Department of International Environmental Economics, Faculty of Economics, Dokkyo University, Soka-shi, Saitama 340-0042, Japan
Interests: satellite remote sensing; precipitation; radar
Special Issues, Collections and Topics in MDPI journals
Dr. Mikiko Fujita
E-Mail Website
Guest Editor
Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Kanagawa 236-0001, Japan
Interests: precipitation system; water vapor climatology; GPS/GNSS meteorology
Special Issues, Collections and Topics in MDPI journals
Dr. Jungho Kim
E-Mail Website
Guest Editor
Hydrometeorology Modeling and Applications (HMA) Team, Physical Sciences Laboratory (PSL), National Onceanic and Atmospheric Administration (NOAA), Boulder, CO 80521, USA
Interests: remote sensing in hydrology; physical sciences and modeling in hydrology; weather radar hydrology; data sciences in hydrology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent extremes in precipitation are thought to be due to changes in the global environment. Many disastrous events occur due to extreme precipitation. Monitoring and prediction are essential for water disaster prevention. Precipitation data are also essential for studies of current climate change. While many countries have established excellent rain gauge or operational radar networks, many ungauged regions still exist. For the local precipitation observations, many techniques for precipitation retrievals using rain gauge or radar networks have been proposed and applied for obtaining precise rain rate or snow rate. The techniques include not only rain rate or snow rate estimates but also temporal and spatial interpolations. Covering large areas including oceans and satellite observations is essential. The satellite observations use remote sensing techniques. Here, retrieval techniques take important roles.

This Special Issue aims to provide novel techniques of precipitation retrievals and new findings so as to contribute to advancement of precipitation observation techniques. This Special Issue accepts papers related to studies on precipitation retrieval using observations by space-borne or ground-based sensors. This Special Issue also accepts papers on algorithm developments as well as observational studies, data analyses, and numerical simulations aiming to improve precipitation retrievals.

The Special Issue "Remote Sensing for Precipitation Retrievals" is jointly organized between “Remote Sensing” and “Geomatics” journals. Contributors are required to check the website below and follow the specific instructions for authors:
https://0-www-mdpi-com.brum.beds.ac.uk/journal/remotesensing/instructions
https://0-www-mdpi-com.brum.beds.ac.uk/journal/geomatics/instructions

You may choose our Joint Special Issue in Remote Sensing.

Prof. Dr. Atsushi Hamada
Prof. Dr. Kenji Nakamura
Dr. Mikiko Fujita
Dr. Jungho Kim
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 papers will be 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. Geomatics is an international peer-reviewed open access quarterly 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 1000 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

  • precipitation
  • radar
  • rain gauge
  • microwave radiometer
  • mesoscale model

Published Papers (1 paper)

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Technical Note
Precipitation Data Retrieval and Quality Assurance from Different Data Sources for the Namoi Catchment in Australia
Geomatics 2021, 1(4), 417-428; https://0-doi-org.brum.beds.ac.uk/10.3390/geomatics1040024 - 28 Oct 2021
Viewed by 599
Abstract
Within the Horizon 2020 Project WaterSENSE a modular approach was developed to provide different stakeholders with the required precipitation information. An operational high-quality rainfall grid was set up for the Namoi catchment in Australia based on rain gauge adjusted radar data. Data availability [...] Read more.
Within the Horizon 2020 Project WaterSENSE a modular approach was developed to provide different stakeholders with the required precipitation information. An operational high-quality rainfall grid was set up for the Namoi catchment in Australia based on rain gauge adjusted radar data. Data availability and processing considerations make it necessary to explore alternative precipitation approaches. The gauge adjusted radar data will serve as a benchmark for the alternative precipitation data. The two well established satellite-based precipitation datasets IMERG and GSMaP will be analyzed with the temporal and spatial requirements of the applications envisioned in WaterSENSE in mind. While first results appear promising, these datasets will need further refinements to meet the criteria of WaterSENSE, especially with respect to the spatial resolution. Inferring information from soil moisture-derived from EO observations to increase the spatial detail of the existing satellite-based datasets is a promising approach that will be investigated along with other alternatives. Full article
(This article belongs to the Special Issue Remote Sensing for Precipitation Retrievals)
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