Evaluation of GPM-era Global Satellite Precipitation Products over Multiple Complex Terrain Regions

Abstract

The great success of the Tropical Rainfall Measuring Mission (TRMM) and its successor Global Precipitation Measurement (GPM) has accelerated the development of global high-resolution satellite-based precipitation products (SPP). However, the quantitative accuracy of SPPs has to be evaluated before using these datasets in water resource applications. This study evaluates the following GPM-era and TRMM-era SPPs based on two years (2014–2015) of reference daily precipitation data from rain gauge networks in ten mountainous regions: Integrated Multi-SatellitE Retrievals for GPM (IMERG, version 05B and version 06B), National Oceanic and Atmospheric Administration (NOAA)/Climate Prediction Center Morphing Method (CMORPH), Global Satellite Mapping of Precipitation (GSMaP), and Multi-Source Weighted-Ensemble Precipitation (MSWEP), which represents a global precipitation data-blending product. The evaluation is performed at daily and annual temporal scales, and at 0.1 deg grid resolution. It is shown that GSMaPV07 surpass the performance of IMERGV06B Final for almost all regions in terms of systematic and random error metrics. The new orographic rainfall classification in the GSMaPV07 algorithm is able to improve the detection of orographic rainfall, the rainfall amounts, and error metrics. Moreover, IMERGV05B showed significantly better performance, capturing the lighter and heavier precipitation values compared to IMERGV06B for almost all regions due to changes conducted to the morphing, where motion vectors are derived using total column water vapor for IMERGV06B.

Evaluation and Application of Satellite Precipitation Products in Studying the Summer Precipitation Variations over Taiwan

“…After the GPM mission was launched, a new algorithm was developed for the GSMaP project which included the GPM satellite data, producing GSMaP-Gauge data from March 2014 [4]. Recently, Derin et al [15] pointed out that GSMaP-Gauge v7 (hereafter GSMaP7) and IMERG5 performed better than IMERG6 in depicting the precipitation formation over multiple complex terrain regions, including western Taiwan, during the period 2014-2015. However, only 34 gauges in western Taiwan and only two years of data from 2014-2015 were used by Derin et al [15] as the reference base for comparison.…”

“…Recently, Derin et al [15] pointed out that GSMaP-Gauge v7 (hereafter GSMaP7) and IMERG5 performed better than IMERG6 in depicting the precipitation formation over multiple complex terrain regions, including western Taiwan, during the period 2014-2015. However, only 34 gauges in western Taiwan and only two years of data from 2014-2015 were used by Derin et al [15] as the reference base for comparison. It should be noted that there are more than 400 rain gauges across the entirety of Taiwan [24] that can be used for a more detailed comparison of SPPs starting from 2000.…”

“…The main objective of this study was to evaluate the performance of multiple SPPs (including TRMM7, IMERG5, IMERG6, and GSMaP7) in depicting the spatial-temporal variations of summer (June, July, and August; JJA) precipitation over whole Taiwan, using more than 400 local rain gauges as the reference base for comparison. The selection of GPM SPPs followed Derin et al [15]. However, in contrast to Derin et al [15], who only performed the evaluation at daily and annual timescales, we perform the evaluation of summer precipitation at mean status, daily, interannual and diurnal timescales.…”

“…The selection of GPM SPPs followed Derin et al [15]. However, in contrast to Derin et al [15], who only performed the evaluation at daily and annual timescales, we perform the evaluation of summer precipitation at mean status, daily, interannual and diurnal timescales. In addition, we examine the capabilities to apply SPPs in studying the activities of summer connective afternoon rainfall (CAR) event ( Figure 7, explained later), which is the most frequently observed weather pattern in Taiwan [30].…”

“…Recall, Derin et al [15] indicated that IMERG6 performed worse than GSMaP7 and IMERG5 in capturing the daily precipitation formation over western Taiwan during 2014-2015. Consistent with Derin et al [15], one can note from Figure 2c that GSMaP7 and IMERG5 did perform better than IMERG6 in some coastal regions of southwest Taiwan, even though the time periods used for the Additionally, as noted from Figure 2c, which shows the spatial distribution of grid-to-grid Tcorr for the comparison between the SPPs and the CWB data, IMERG6 has more areas with larger values of Tcorr (e.g., >0.8). Moreover, even though the related spatial distributions of grid-to-grid RMSE in Figure 2d do not show too much difference among the performance of the four SPPs, IMERG6 is still the one having more areas with smaller values of RMSE (e.g., <7.5 mm•d −1 ).…”