Ground validation of GPM DPR algorithms by hydrometeor measurements and polarimetric radar observations of winter snow clouds: A case study on 4 February 2018

Rimpei Kamamoto, Kenji Suzuki, Tetsuya Kawano, Hiroshi Hanado, Katsuhiro Nakagawa, Yuki Kaneko

Research output: Contribution to journalArticle

Abstract

Two products from the Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) algorithms, a flag of intense solid precipitation above the-10°C height ("flagHeavyIcePrecip") and a classification of precipitation type ("typePrecip") were validated by ground-based hydrometeor measurements and X-band multi-parameter (X-MP) radar observations of snow clouds on 4 February 2018. Contoured frequency by altitude diagrams of the X-MP radar reflectivity exhibited a significant difference between footprints flagged and unflagged by the "flagHeavyIcePrecip" algorithm, which indicated that the algorithm is reasonable. The hydrometeor classification (HC) by the X-MP radar, which was confirmed by microphysical evidence from ground-based hydrometeor measurements, suggested the existence of graupel in the footprints with "flagHeavyIcePrecip". In addition, according to the information of the GPM DPR, the "flagHeavyIcePrecip" footprints were characterized by not only graupel but also large snowflakes. According to the information of X-MP radar HC, the "typePrecip" algorithm by the detection of "flagHeavyIcePrecip" was effective in classifying precipitation types of snow clouds, whereas it seems that there is room for improvement in the "typePrecip" algorithms based on the extended-DPRm-method and H-method.

Original languageEnglish
Pages (from-to)115-119
Number of pages5
JournalScientific Online Letters on the Atmosphere
Volume16
DOIs
Publication statusPublished - 2020

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

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