Journal article
STREAM-Sat: A Novel Near-Realtime Quasi-Global Satellite-Only Ensemble Precipitation Dataset
Water resources research, Vol.61(3), p.n/a
03/01/2025
DOI: 10.1029/2023WR036756
Abstract
Satellite-based precipitation observations can provide near-global coverage with high spatiotemporal resolution in near-realtime. Their utility, however, is hindered by oftentimes large uncertainties that vary substantially in space and time. This problem is particularly pronounced in regions which lack dense ground-based measurements to quantify or reduce such uncertainty. Since this uncertainty is, by definition, a random process, probabilistic representations are needed to advance their operational application. Ensemble methods, in which uncertainty is depicted via multiple realizations of precipitation fields, have been widely used in numerical weather and climate prediction, but rarely in satellite contexts. Creating such an ensemble dataset is challenging due to the complexity of observational uncertainties and the scarcity of "ground truth" to characterize them. In this study, we attempt to resolve these two challenges and propose the first quasi-global (covering all continental land masses within 50 degrees N-50 degrees S) satellite-only ensemble precipitation dataset (STREAM-Sat), derived entirely from NASA's Integrated Multi-SatellitE Retrievals for Global Precipitation Measurement (IMERG) and GPM's radar-radiometer combined precipitation product (2B-CMB). No ground-based measurements are used to generate STREAM-Sat, and it is suitable for near-realtime use without extending the 4-hr latency and 0.1 degrees, 30-min spatiotemporal resolution of IMERG Early. We compare STREAM-Sat against several precipitation datasets, including global satellite-based, rain gage-based, atmospheric reanalysis, and merged products. While our proposed approach faces some limitations and is not universally superior to the comparison datasets in all respects, it does hold relative advantages due to its unique combination of accuracy, resolution, rainfall spatiotemporal structure, latency, and utility in hydrologic and hazard applications.
Details
- Title: Subtitle
- STREAM-Sat: A Novel Near-Realtime Quasi-Global Satellite-Only Ensemble Precipitation Dataset
- Creators
- Kaidi Peng - University of Wisconsin–MadisonDaniel B. Wright - University of Wisconsin–MadisonYagmur Derin - University of Wisconsin–MadisonSamantha H. Hartke - NSF National Center for Atmospheric ResearchZhe Li - Colorado State UniversityJackson Tan - Goddard Space Flight Center
- Resource Type
- Journal article
- Publication Details
- Water resources research, Vol.61(3), p.n/a
- DOI
- 10.1029/2023WR036756
- ISSN
- 0043-1397
- eISSN
- 1944-7973
- Publisher
- Amer Geophysical Union
- Number of pages
- 24
- Grant note
- NNX16AL23G / NASA Precipitation Measurement Mission 80NSSC22K0600 / National Aeronautics and Space Administration; National Aeronautics & Space Administration (NASA) NASA Global Precipitation Measurement Ground Validation program
- Language
- English
- Date published
- 03/01/2025
- Academic Unit
- Civil and Environmental Engineering
- Record Identifier
- 9984944741302771
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