Estimating Uncertainty of PMW‐Based Convective Fraction Product

Details

• Journal Title:
  Journal of Geophysical Research: Atmospheres
• Personal Author:
  Ji, Lei ; Petković, Veljko ; Orescanin, Marko
• NOAA Program & Office:
  NESDIS (National Environmental Satellite, Data, and Information Service) ; CISESS (Cooperative Institute for Satellite Earth System Studies)
• Description:
  Convective precipitation plays a crucial role in the Earth's hydrological cycle, vertical thermodynamic transport, and natural weather hazards. While satellite passive microwave (PMW) observations offer broad spatial coverage essential for global precipitation monitoring, uncertainties in PMW‐derived precipitation class (i.e., regime) remain poorly quantified across varying environmental conditions. This study systematically characterizes Convective Volume Fraction (CVF) uncertainty using 8 years (2015-2023) of collocated observations from the Global Precipitation Measurement (GPM) mission Core Observatory Microwave Imager (GMI) and Ku‐band Precipitation Radar (KuPR), following their widely used retrieval framework. Results reveal distinct CVF bias patterns between ocean and land surfaces: GMI generally underestimates CVF over oceans except under high moisture conditions (TCWV >60 mm) or elevated surface temperatures (T2m > 304 K), while systematically overestimating over land except in cool, dry environments. Convective volume fraction uncertainties are found to be the highest in tropical regions dominated by deep convection and within an oceanic "transition zone" (T2m: 290-300 K; TCWV: 10-60 mm) characterized by mixed precipitation regimes. Uncertainty patterns correlate strongly with ice‐phase hydrometeor presence, evidenced by brightness temperature depressions at 89 and 166 GHz. Temporal stability analysis across two independent 4‐year periods confirms the robustness of the derived uncertainties. These environment‐dependent uncertainty estimates offer upper bounds directly applicable to operational PMW algorithm refinement and uncertainty propagation in precipitation‐dependent applications.
• Source:
  Journal of Geophysical Research: Atmospheres, 131(14)
• DOI:
  https://doi.org/10.1029/2026JD046377
• ISSN:
  2169-897X ; 2169-8996
• Format:
  PDF
• Publisher:
  American Geophysical Union (AGU)
• Document Type:
  Journal Article
• Funding:
  Grant no. NA24NESX4320001
• License:
  https://creativecommons.org/licenses/by/4.0/
• Rights Information:
  CC BY
• Compliance:
  Submitted
• Download URL:
  https://repository.library.noaa.gov/view/noaa/76520/noaa_76520_DS1.pdf
• File Type:
  [PDF - 8.24 MB]
• Collection(s):
  NOAA Cooperative Institutes ; National Environmental Satellite and Data Information Service (NESDIS)
• Main Document Checksum:
  urn:sha-512:f62f533123e955cf39e811c1340b410ab3dde644a4c544663d52ea5c7e8b1a25d75c3248cfbfc252406f72bc2cb9842ef735776d3dfbc6dcfb8174870ec00f81