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Real-time weekly global green vegetation fraction derived from advanced very high resolution radiometer-based NOAA operational global vegetation index (GVI) system

  • Le Jiang
  • , Felix N. Kogan
  • , Wei Guo
  • , J. Dan Tarpley
  • , Kenneth E. Mitchell
  • , Michael B. Ek
  • , Yuhong Tian
  • , Weizhong Zheng
  • , Cheng Zhi Zou
  • , Bruce H. Ramsay
    • National Oceanic and Atmospheric Administration
    • National Environmental Satellite, Data, and Information Service, Center for Satellite Applications and Research, World Weather Building

    Research output: Contribution to journalArticlepeer-review

    67 Scopus citations

    Abstract

    To provide quality-improved and consistent real-time global green vegetation fraction (GVF) data products that are suitable for use in operational numerical weather, climate, and hydrological models, necessary processing steps are applied to the output data stream from the advanced very high resolution radiometer (AVHRR)-based NOAA operational global vegetation index (GVI) system. This paper reviewed the NOAA GVI data and described the algorithm to derive weekly updated real-time GVF from the normalized difference vegetation index (NDVI). The methodology description focuses on algorithm justification in an operational production context. The described algorithm was implemented in the global vegetation processing system (GVPS). The new global GVF data sets include the multiyear GVF weekly climatology and the real-time weekly GVF. Compared to the old 5 year GVF monthly climatology currently used in the operational National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) weather and climate models, the new data sets provide an overall higher vegetation value, real-time surface vegetation information, and numerous other improvements. The new GVF data set quality was partially assured by validation against Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI at a few EOS land validation core sites and comparison with another independently processed NDVI data set. Impact of the new GVF data sets in numerical weather prediction (NWP) model was investigated using EMC mesoscale model simulations and concluded overall positive.

    Original languageEnglish
    Article numberD11114
    JournalJournal of Geophysical Research
    Volume115
    Issue number11
    DOIs
    StatePublished - Jun 2010

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