Application of Satellite-Based Precipitation Estimates Using Machine Learning and Numerical Modeling
A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".
Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 2549
Special Issue Editors
Interests: hydrology; hydro-meteorological extremes; climate change; satellite-based precipitation estimates; citizen science in water resources engineering
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; climate variability; weather and climate extremes; natural hazard vulnerability assessments; flood forecasting; statistical and dynamical downscaling
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The precipitation information is generally derived from ground-based rain gauges, meteorological radars, and satellite-based estimates. With the advancement in satellite technology, different missions are successfully being operated to observe climatic variables, including precipitation. Around the world, the availability of high resolution (spatial and temporal) has been recognized as a crucial achievement, and satellite-based products have been applied in many disciplines. However, these satellite-based estimates might contain systematic as well as random biases. Assessing the accuracy and performance is a prerequisite for any satellite-based estimates before using them for hydrologic and water resources planning or decision-making. Blending satellite-based estimates, ground-based rain gauges, and reanalysis data could augment our understanding of the spatiotemporal characteristics of precipitation, particularly in data-scarce regions. Similarly, downscaling and bias-correcting the satellite-based estimates are equally crucial to get information on a local scale. Several techniques, including artificial intelligence (AI) and machine learning (ML), play an instrumental role while using these satellite-based precipitation estimates. This Special Issue aims to collect the state-of-the-art contributions appraising the use of satellite-based precipitation estimates. In particular, it is quite challenging to understand the spatiotemporal distribution of weather variables and their atmospheric mechanisms during extreme weather events. Moreover, these satellite-based products still have uncertainties when focusing on extreme weather events, such as cloudbursts or flash floods. Therefore, this special issue encourages the contributors to explore the opportunities and challenges in using satellite-based precipitation products during extreme events. Topics of specific interest also include:
- Review of various satellite-based products
- Opportunities and challenges in the use of satellite-based products in data-scarce regions
- Bias correction and spatial downscaling of satellite-based products
- Comparison of different satellite-based products with high-resolution weather observations
- Development of high space-time resolution datasets of meteorological variables
- Use of numerical models (i.e., atmospheric, hydrologic) using satellite-based products
Dr. Rocky Talchabhadel
Dr. Md Abul Ehsan Bhuiyan
Guest Editors
Manuscript Submission Information
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Keywords
- satellite-based precipitation
- extreme precipitation
- weather monitoring
- numerical modeling
- bias correction and spatial downscaling
- cloud
