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NWP-Based Adjustment of IMERG Precipitation for Flood-Inducing Complex Terrain Storms: Evaluation over CONUS

1
Department of Civil and Environmental Engineering, University of Connecticut, Storrs, CT 06269, USA
2
National Center for Atmospheric Research, Boulder, CO 80301, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(4), 642; https://doi.org/10.3390/rs10040642
Received: 20 February 2018 / Revised: 12 April 2018 / Accepted: 15 April 2018 / Published: 21 April 2018
(This article belongs to the Special Issue Remote Sensing of Precipitation)
This paper evaluates the use of precipitation forecasts from a numerical weather prediction (NWP) model for near-real-time satellite precipitation adjustment based on 81 flood-inducing heavy precipitation events in seven mountainous regions over the conterminous United States. The study is facilitated by the National Center for Atmospheric Research (NCAR) real-time ensemble forecasts (called model), the Integrated Multi-satellitE Retrievals for GPM (IMERG) near-real-time precipitation product (called raw IMERG) and the Stage IV multi-radar/multi-sensor precipitation product (called Stage IV) used as a reference. We evaluated four precipitation datasets (the model forecasts, raw IMERG, gauge-adjusted IMERG and model-adjusted IMERG) through comparisons against Stage IV at six-hourly and event length scales. The raw IMERG product consistently underestimated heavy precipitation in all study regions, while the domain average rainfall magnitudes exhibited by the model were fairly accurate. The model exhibited error in the locations of intense precipitation over inland regions, however, while the IMERG product generally showed correct spatial precipitation patterns. Overall, the model-adjusted IMERG product performed best over inland regions by taking advantage of the more accurate rainfall magnitude from NWP and the spatial distribution from IMERG. In coastal regions, although model-based adjustment effectively improved the performance of the raw IMERG product, the model forecast performed even better. The IMERG product could benefit from gauge-based adjustment, as well, but the improvement from model-based adjustment was consistently more significant. View Full-Text
Keywords: GPM; IMERG; satellite precipitation adjustment; numerical weather prediction; heavy precipitation; flood-inducing storm; complex terrain GPM; IMERG; satellite precipitation adjustment; numerical weather prediction; heavy precipitation; flood-inducing storm; complex terrain
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Zhang, X.; Anagnostou, E.N.; Schwartz, C.S. NWP-Based Adjustment of IMERG Precipitation for Flood-Inducing Complex Terrain Storms: Evaluation over CONUS. Remote Sens. 2018, 10, 642.

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