Evaluation of the CMORPH high-resolution precipitation product for hydrological applications over South Korea

Details

• Journal Title:
  Atmospheric Research
• Personal Author:
  Kim, Jungho ; Han, Heechan
• NOAA Program & Office:
  OAR (Oceanic and Atmospheric Research) ; PSL (Physical Sciences Laboratory) ; CIRA (Cooperative Institute for Research in the Atmosphere)
• Description:
  The use of a high-resolution satellite-based precipitation product on a global-scale is attractive to hydrological applications. However, it should be systematically evaluated from various perspectives as the quality property is dependent on the geographical and topographical features of a region. This study aims to comprehensively assess the Climate Prediction Center morphing technique (CMORPH) precipitation product over South Korea. Two evaluation approaches, the general evaluation using statistical metrics and the detection evaluation (to measure skill in detecting precipitation and non-precipitation) using categorical metrics, are employed based on an 18-year long-term period of record. As a result, the CMORPH product tended to underestimate precipitation over South Korea, and the level of the underestimation varied with the seasons and regions. The overall quality was adequate for hydrological applications that require precipitation data at the annual-to-daily resolution but not at hourly resolution. Skill in detecting hourly precipitation in a storm event was 60% of the rain-gauge data, and the accuracies of total volume and peak value were 45% and 40%, respectively. The quality in the coastal regions and islands was not as good as in inland areas at low altitudes. The accuracy in a wet season was better than that in a dry/winter season. Notably, the CMORPH precipitation product was not suitable for snowfall data. Ultimately, the CMORPH product at hourly resolution needs a correction process using the local measurement systems for enhancing the quality property over South Korea.
• Keywords:
  Hydrology Numerical Weather Forecasting Rain And Rainfall Numerical Weather Forecasting Rain And Rainfall
• Source:
  Atmospheric Research 258, 105650, 2021
• DOI:
  https://doi.org/10.1016/j.atmosres.2021.105650
• Document Type:
  Journal Article
• Place as Subject:
  Korea (South)
• Rights Information:
  Accepted Manuscript
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha256:3e0253943021b5dfe02335f3766310793b38d5e83941bf8c50a9148315215cf2
• Download URL:
  https://repository.library.noaa.gov/view/noaa/33266/noaa_33266_DS1.pdf
• File Type:
  [PDF - 6.21 MB ]