U.S. flag An official website of the United States government.
Official websites use .gov

A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS

A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

i

Estimating Near Real-Time Hourly Evapotranspiration Using Numerical Weather Prediction Model Output and GOES Remote Sensing Data in Iowa



Details

  • Journal Title:
    Remote Sensing
  • Personal Author:
  • NOAA Program & Office:
    CIMSS (Cooperative Institute for Meteorological Satellite Studies)
  • Description:
    This study evaluates the applicability of numerical weather prediction output supplemented with remote sensing data for near real-time operational estimation of hourly evapotranspiration (ET). Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR) systems were selected to provide forcing data for a Penman-Monteith model to calculate the Actual Evapotranspiration (AET) over Iowa. To investigate how the satellite-based remotely sensed net radiation ( R n ) estimates might potentially improve AET estimates, Geostationary Operational Environmental Satellite derived R n (GOES- R n ) data were incorporated into each dataset for comparison with the RAP and HRRR R n -based AET evaluations. The authors formulated a total of four AET models—RAP, HRRR, RAP-GOES, HRRR-GOES, and validated the respective ET estimates against two eddy covariance tower measurements from central Iowa. The implementation of HRRR-GOES for AET estimates showed the best results among the four models. The HRRR-GOES model improved statistical results, yielding a correlation coefficient of 0.8, a root mean square error (mm hr−1) of 0.08, and a mean bias (mm hr−1) of 0.02 while the HRRR only model results were 0.64, 0.09, and 0.04, respectively. Despite limited in situ observational data to fully test a proposed AET estimation, the HRRR-GOES model clearly showed potential utility as a tool to predict AET at a regional scale with high spatio-temporal resolution.
  • Source:
    Remote Sensing, 12(14), 2337
  • DOI:
  • ISSN:
    2072-4292
  • Format:
    pdf
  • Publisher:
    MDPI AG
  • Document Type:
    Journal Article
  • License:
  • Rights Information:
    CC BY
  • Compliance:
    Library
  • Main Document Checksum:
    urn:sha-512:217211b2b7fe1aff70ec9bb485f1aee8701e58bdc9540e52c92b9770f0bbcaaf66c1efa53252c48f5f9f1f66b380ab144126ceedb8d8e593dca092b8a4b87606
  • Download URL:
  • File Type:
    Filetype[PDF - 4.83 MB ]
PREVIOUS
ON THIS PAGE
Details
The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners. As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.
BACK TO TOP