HR: 0830h
AN: GC31B-0190    [PDF]
TI: Global Climatological and Real-Time Green Vegetation Fraction from AVHRR
AU: * Jiang, L
EM: jiangl@imsg.com
AF: Le Jiang, IMSG at NOAA/NESDIS, NOAA Science Center, 5200 Auth Rd., Rm 810, Station 8216, Camp Springs, MD 20746 United States
AU: Ramsay, B H
EM: Bruce.H.Ramsay@noaa.gov
AF: Bruce H. Ramsay, Cooperative Institute for Climate Studies, Earth System Science Interdisciplinary Center, 2207 Computer and Space Sciences Building (#224), Rm 4115F University of Maryland at College Park, College Park, MD 20742 United States
AU: Mitchell, K
EM: Kenneth.Mitchell@noaa.gov
AF: Kenneth Mitchell, NOAA/NCEP/EMC, NOAA Science Center, 5200 Auth Rd., Rm. 206, Camp Springs, MD 20746 United States
AU: Kogan, F
EM: Felix.Kogan@noaa.gov
AF: Felix Kogan, NOAA/NESDIS/ORA, NOAA Science Center, 5200 Auth Rd., Rm 710, Camp Springs, MD 20746
AU: Tarpley, D
EM: Dan.Tarpley@noaa.gov
AF: Dan Tarpley, NOAA/NESDIS/ORA, NOAA Science Center, 5200 Auth Rd., 7th Floor, Camp Springs, MD 20746 United States
AU: Guo, W
EM: Wei.Guo@noaa.gov
AF: Wei Guo, IMSG at NOAA/NESDIS, NOAA Science Center, 5200 Auth Rd., Rm 705, Camp Springs, MD 20746
AB: The global coverage, 0.144-degree resolution green vegetation fraction (GVF) climatological fields have been derived at weekly temporal resolution using 12-year weekly smoothed NDVI datasets, while such smoothed NDVI datasets were obtained by post-launch calibrated AVHRR visible and near infrared radiances that span over the operational period of NOAA-9, NOAA-11 and NOAA-14 satellites. A comprehensive statistical approach was further developed to utilize both the weekly GVF climatology and the real time vegetation anomaly magnitude indicated by vegetation condition index (VCI) to produce high quality near real-time meso-scale grid resolution global GVF fields that are suitable to use by numerical weather, climate and hydrological models. This approach considers different scenarios of the relationship between GVF anomaly and VCI for each week, land surface class and hemisphere. The case studies show that the resulting GVF fields are capable of capturing real-time moderate to strong land surface vegetation anomaly signals while preserving general trend in the climatological datasets. The data products summarized in this study appear be superior to previously derived GVF climatology.
DE: 0315 Biosphere/atmosphere interactions
DE: 1600 GLOBAL CHANGE (New category)
DE: 1640 Remote sensing
DE: 1812 Drought
DE: 1833 Hydroclimatology
SC: Global Climate Change [GC]
MN: 2003 Fall Meeting