Daily rainfall estimate by emissivity temporal variation from 10 satellites
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Daily rainfall estimate by emissivity temporal variation from 10 satellites

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  • Journal Title:
    Journal of Hydrometeorology
  • Personal Author:
  • NOAA Program & Office:
    CISESS (Cooperative Institute for Satellite Earth System Studies)
  • Description:
    Rainfall retrieval algorithms for passive microwave radiometers often exploit the brightness temperature depression due to ice scattering at high-frequency channels ($85 GHz) over land. This study presents an alternate method to estimate the daily rainfall amount using the emissivity temporal variation (i.e., De) under rain-free conditions at lowfrequency channels (19, 24, and 37 GHz). Emissivity is derived from 10 passive microwave radiometers, including the Global Precipitation Measurement (GPM) Microwave Imager (GMI), the Advanced Microwave Scanning Radiometer 2 (AMSR2), three Special Sensor Microwave Imager/Sounders (SSMIS), the Advanced Technology Microwave Sounder (ATMS), and four Advanced Microwave Sounding Units-A (AMSU-A). Four different satellite combination schemes are used to derive the De for daily rainfall estimates. They are all 10 satellites, 5 imagers, 6 satellites with very different equator crossing times, and GMI only. Results show that De from all 10 satellites has the best performance with a correlation of 0.60 and RMSE of 6.52 mm, compared with the Integrated Multisatellite Retrievals for GPM (IMERG) Final run product. The 6-satellites scheme has comparable performance with the all-10-satellites scheme. The 5-imagers scheme performs noticeably worse with a correlation of 0.49 and RMSE of 7.28 mm, while the GMI-only scheme performs the worst with a correlation of 0.25 and RMSE of 11.36 mm. The inferior performance from the 5-imagers and GMI-only schemes can be explained by the much longer revisit time, which cannot accurately capture the emissivity temporal variation.
  • Keywords:
  • Source:
    Journal of Hydrometeorology, 22(3), 623-637
  • DOI:
  • Document Type:
    Journal Article
  • Funding:
    Grant no. ​NA19NES4320002
  • Rights Information:
    Other
  • Compliance:
    Submitted
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