Evaluation of GPM Dual-Frequency Precipitation Radar (DPR) Rainfall Products Using the Rain Gauge Network over China

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  • 1 National Satellite Meteorological Center, China Meteorological Administration, Beijing, 100081, China
  • 2 Beijing Climate Center, China Meteorological Administration, Beijing, 100081, China
  • 3 Department of Chemical and Biochemical Engineering, the University of Iowa, Iowa City, IA 52242, USA
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Abstract

The Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement (GPM) mission core satellite provides the new-generation global observation of rain since 2014. The main objective of this paper is to evaluate the suitability and limitation of GPM-DPR level-2 products over China. The DPR rain rate products are compared with rain gauge data during the summers of five years (2014-2018). The ground observation network is composed of more than 50000 rain gauges. The DPR precipitation products for all scans (DPR_NS, DPR_MS and DPR_HS) generally underestimate rain rates. However, DPR_MS agrees better with gauge estimates than DPR_NS and DPR_HS, yielding the lowest mean error, systematic deviation, and the highest Pearson correlation coefficient. In addition, all three swath types show obvious overestimation over gauge estimates between 0.5 to 1 mm/h and underestimation when gauge estimates are larger than 1 mm/h. The DPR_HS and DPR_MS agree better with gauge estimates below and above 2.5 mm/h, respectively. A deeper investigation was carried out to analyze the variation of DPR_MS’s performance with respect to terrains over China. An obvious underestimation, relative to gauge estimates, occurs in Tibetan Plateau while a slight overestimation occurs in North China Plain. Furthermore, our comprehensive analysis suggests that in Sichuan Basin, the DPR_MS exhibit the best agreement with gauge estimates.

Correspondence to: Tongwen Wu (twwu@cma.gov.cn)

Abstract

The Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement (GPM) mission core satellite provides the new-generation global observation of rain since 2014. The main objective of this paper is to evaluate the suitability and limitation of GPM-DPR level-2 products over China. The DPR rain rate products are compared with rain gauge data during the summers of five years (2014-2018). The ground observation network is composed of more than 50000 rain gauges. The DPR precipitation products for all scans (DPR_NS, DPR_MS and DPR_HS) generally underestimate rain rates. However, DPR_MS agrees better with gauge estimates than DPR_NS and DPR_HS, yielding the lowest mean error, systematic deviation, and the highest Pearson correlation coefficient. In addition, all three swath types show obvious overestimation over gauge estimates between 0.5 to 1 mm/h and underestimation when gauge estimates are larger than 1 mm/h. The DPR_HS and DPR_MS agree better with gauge estimates below and above 2.5 mm/h, respectively. A deeper investigation was carried out to analyze the variation of DPR_MS’s performance with respect to terrains over China. An obvious underestimation, relative to gauge estimates, occurs in Tibetan Plateau while a slight overestimation occurs in North China Plain. Furthermore, our comprehensive analysis suggests that in Sichuan Basin, the DPR_MS exhibit the best agreement with gauge estimates.

Correspondence to: Tongwen Wu (twwu@cma.gov.cn)
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