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

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.

Satellite-Based Precipitation Estimation and Its Application for Streamflow Prediction over Mountainous Western U.S. Basins

“…Moreover, MW sensors can capture hydrometeor signals from the entire atmosphere using a combination of lowand high-frequency channels. An additional source of useful precipitation data, particularly in higher latitudes and winter seasons, are short-term forecasts from numerical weather prediction models (Kidd et al 2013;Zhang et al 2013). So far, MW retrieval techniques rely mainly on indirect-scattering-based schemes over land (Wilheit et al 2003;Ferraro et al 2005;Gopalan et al 2010) to mitigate the surface contamination of signals.…”

Assessment of Satellite and Radar Quantitative Precipitation Estimates for Real Time Monitoring of Meteorological Extremes Over the Southeast of the Iberian Peninsula

“…Similar patterns have been identified in other mountain areas using the TRMM (Tropical Rainfall Measuring Mission) Multi-Satellite Precipitation Analysis (TMPA) 3B42b6 [40]. In Europe, other satellite-based QPEs have been evaluated, such as the CMORPH (Climate Center Morphing technique) of NOAA,a satellite QPE similar to PERSIANN-CCS, with a spatial resolution of 8 × 8 km 2 and a temporal resolution of 30 min [41]. In this case, the data were temporarily aggregated to one hour and five heavy rainfall events were analyzed in three European mountain areas located in the Italian Alps and the Massif Central mountain range.…”

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

“…The technique of model-based satellite adjustment was first introduced by Zhang et al [29] and demonstrated on five heavy precipitation events over the European Alps and Massif Central. The raw CMORPH product largely underestimated high rain rates, while the WRF simulations provided reasonable overall rainfall magnitudes.…”

“…To address the aforementioned disadvantages of gauge-based adjustment, Zhang et al [29] developed a numerical model-based technique for satellite precipitation adjustment. This technique is designed specifically for heavy precipitation events over topographically-complex regions, where the raw satellite products considerably underestimate heavy precipitation [20,30] and can remedy the negative bias without gauge data input.…”

“…In this paper, we apply the evaluation of Zhang et al's [29] model-adjustment technique to the latest near-real-time satellite precipitation product (IMERG) by incorporating an ensemble precipitation forecast dataset produced by NCAR [34]. The study focuses on a large number of flood-inducing storms that occurred in mountainous areas over the conterminous United States (CONUS) and is unique relative to past studies in that it contrasts model-adjustment performance characteristics across different complex terrain domains (coastal vs. inland) and uses model precipitation forecasts for near-real-time adjustment of satellite precipitation datasets.…”