4.5 Article

Validation of GPM IMERG V05 and V06 Precipitation Products over Iran

Journal

JOURNAL OF HYDROMETEOROLOGY
Volume 21, Issue 5, Pages 1011-1037

Publisher

AMER METEOROLOGICAL SOC
DOI: 10.1175/JHM-D-19-0269.1

Keywords

Atmosphere; Precipitation; Satellite observations; Climate services

Funding

  1. National Natural Science Foundation of China [41790424]
  2. International Partnership Program of Chinese Academy of Sciences [131A11KYSB20170113]
  3. Chinese Academy of Sciences President's International Fellowship Initiative [2019VEA0019]
  4. Newton Advanced Fellowships

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This study attempts to assess the validity of the Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) products across Iran. Six IMERG precipitation products (IPPs) including early, late, and final runs for versions 05 and 06 were compared with precipitation data from 76 synoptic stations on a daily scale for the period from June 2014 to June 2018. According to the results, V05 performed better than V06, particularly in early and late runs. The IPPs overestimate precipitation ranging from 5% to 32%; however, IPPs tended to underestimate (overestimate) the amount of precipitation for wet (dry) areas and precipitation classes higher than 5 mm day(-1) (less than 5 mm day(-1)). The probability of detection (POD) in IPPs was almost similar (with a median equal to 0.60), whereas other categorical validation metrics like false alarm ratio (FAR) improved in the final run. Our assessments revealed that the dependency of IPPs to the elevation was low, while the error characteristics of IPPs were strongly dependent on the climate and precipitation intensity. For instance, the systematic error varied between less than 12% in dry regions to more than 60% in wet regions. Also, according to modified Kling-Gupta efficiency (KGE) and relative bias (RBias), the performance of IPPs in winter with the highest KGE (ranging from 0.47 to 0.63) and lowest RBias (ranging from 0% to 16%) was better than other seasons. Further improvement is recommended in the satellite sensors and the precipitation retrieval algorithms to achieve a reliable precipitation source.

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