Remote Sensing of Precipitation Extremes

Dear Colleagues,

Extreme rainfall and snowfall are key parameters for studying and monitoring hydro-meteorological events also from a climatological perspective. Extreme events are likely to increase in frequency and severity in the near future due to climate change. Therefore, extreme rainfall monitoring through remote- sensing sensors (satellite and radar) is of paramount importance. Although some countries have established dense rain gauge and/or operational radar networks, extensive areas remain ungauged. Therefore, there is a growing necessity to strengthen our ability to monitor precipitation intensity, duration, frequency, phase, etc. and analyze its spatial characteristics in a timely manner, and consequently to enhance our capacity to manage water resources. Recent developments in satellite-based precipitation products (i.e., high spatio-temporal resolution, quasi-global coverage, and free near-real-time data availability) open new doors for further development in water-related applications. The use of satellite-based precipitation data offers an efficient and effective tool to cope with some of the known challenges of in situ observations, particularly for monitoring extreme events.

The aim of this Special Issue is to present advances and new findings in satellite-based precipitation products for extreme rainfall monitoring and analysis. We solicit contributions focusing on various aspects, including, but not limited to:

• Development of new observation strategies and algorithms for precipitation monitoring;
• Characterization of extreme precipitation events;
• Use of satellite-based precipitation estimates to predict floods and droughts;
• Near-real-time and post-real-time rainfall monitoring;
• Downscaling and bias correction of satellite-based precipitation products;
• Assessment and analysis of extreme rainfall events at different time scales (e.g., sub-daily, daily, monthly) and spatial scales (local, regional and global);
• Development and implementation of machine learning techniques for monitoring extreme precipitation events.

Dr. Ehsan Sharifi
Prof. Dr. Silas Michaelides
Prof. Dr. Vincenzo Levizzani
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 250 words) can be sent to the Editorial Office for assessment.

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.