Editorial Type:
Article
Article Type:
Research Article

Using NWP Simulations in Satellite Rainfall Estimation of Heavy Precipitation Events over Mountainous Areas

Xinxuan Zhang Department of Civil and Environmental Engineering, University of Connecticut, Storrs, Connecticut

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Emmanouil N. Anagnostou Department of Civil and Environmental Engineering, University of Connecticut, Storrs, Connecticut

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Maria Frediani Department of Civil and Environmental Engineering, University of Connecticut, Storrs, Connecticut

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Stavros Solomos School of Physics, University of Athens, Athens, Greece

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George Kallos School of Physics, University of Athens, Athens, Greece

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Print Publication:
01 Dec 2013
DOI:
https://doi.org/10.1175/JHM-D-12-0174.1
Page(s):
1844–1858
Restricted access

Abstract

In this study, the authors investigate the use of high-resolution simulations from the Weather Research and Forecasting Model (WRF) for evaluating satellite rainfall biases of flood-inducing storms in mountainous areas. A probability matching approach is applied to evaluate a power-law relationship between satellite-retrieved and WRF-simulated rain rates over the storm domain. Satellite rainfall in this study is from the NOAA Climate Prediction Center morphing technique (CMORPH). Results are presented based on analyses of five heavy precipitation events that induced flash floods in northern Italy and southern France complex terrain basins. The WRF-based adjusted CMORPH rain rates exhibited improved error statistics against independent radar rainfall estimates. The authors show that the adjustment procedure reduces the underestimation of high rain rates, thus moderating the magnitude dependence of CMORPH rainfall bias. The Heidke skill score for the WRF-based adjusted CMORPH was consistently higher for a range of rain rate thresholds. This is an indication that the adjustment procedure ameliorates the satellite rain rates to provide a better estimation. Results also indicate that the low rain detection of CMORPH technique is also identifiable in the WRF–CMORPH comparison; however, the adjustment procedure herein does not incorporate this effect on the satellite rainfall bias adjustment.

Corresponding author address: Emmanouil Anagnostou, Civil and Environmental Engineering, University of Connecticut, Storrs, CT 06269. E-mail: manos@engr.uconn.edu

Abstract

In this study, the authors investigate the use of high-resolution simulations from the Weather Research and Forecasting Model (WRF) for evaluating satellite rainfall biases of flood-inducing storms in mountainous areas. A probability matching approach is applied to evaluate a power-law relationship between satellite-retrieved and WRF-simulated rain rates over the storm domain. Satellite rainfall in this study is from the NOAA Climate Prediction Center morphing technique (CMORPH). Results are presented based on analyses of five heavy precipitation events that induced flash floods in northern Italy and southern France complex terrain basins. The WRF-based adjusted CMORPH rain rates exhibited improved error statistics against independent radar rainfall estimates. The authors show that the adjustment procedure reduces the underestimation of high rain rates, thus moderating the magnitude dependence of CMORPH rainfall bias. The Heidke skill score for the WRF-based adjusted CMORPH was consistently higher for a range of rain rate thresholds. This is an indication that the adjustment procedure ameliorates the satellite rain rates to provide a better estimation. Results also indicate that the low rain detection of CMORPH technique is also identifiable in the WRF–CMORPH comparison; however, the adjustment procedure herein does not incorporate this effect on the satellite rainfall bias adjustment.

Corresponding author address: Emmanouil Anagnostou, Civil and Environmental Engineering, University of Connecticut, Storrs, CT 06269. E-mail: manos@engr.uconn.edu
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Journal of Hydrometeorology

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