Details

Autor(en) / Beteiligte

• Jiang, Le
• Kogan, Felix N.
• Guo, Wei
• Tarpley, J. Dan
• Mitchell, Kenneth E.
• Ek, Michael B.
• Tian, Yuhong
• Zheng, Weizhong
• Zou, Cheng-Zhi
• Ramsay, Bruce H.

Titel

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

Ist Teil von

• Journal of Geophysical Research. D. Atmospheres, 2010-06, Vol.115 (D11), p.n/a

Ort / Verlag

Washington, DC: Blackwell Publishing Ltd

Erscheinungsjahr

2010

Quelle

Wiley Online Library Journals Frontfile Complete

Beschreibungen/Notizen

• 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.