The global parameter fields used in the revised Simple Biosphere Model (SiB2) of Sellers et al. are reviewed. The most important innovation over the earlier SiB1 parameter set of Dorman and Sellers is the use of satellite data to specify the time-varying phonological properties of FPAR, leaf area index. and canopy greenness fraction. This was done by processing a monthly 1° by 1° normalized difference vegetation index (NDVI) dataset obtained farm Advanced Very High Resolution Radiometer red and near-infrared data. Corrections were applied to the source NDVI dataset to account for (i) obvious anomalies in the data time series, (ii) the effect of variations in solar zenith angle, (iii) data dropouts in cold regions where a temperature threshold procedure designed to screen for clouds also eliminated cold land surface points, and (iv) persistent cloud cover in the Tropics. An outline of the procedures for calculating the land surface parameters from the corrected NDVI dataset is given, and a brief d... Abstract The global parameter fields used in the revised Simple Biosphere Model (SiB2) of Sellers et al. are reviewed. The most important innovation over the earlier SiB1 parameter set of Dorman and Sellers is the use of satellite data to specify the time-varying phonological properties of FPAR, leaf area index. and canopy greenness fraction. This was done by processing a monthly 1° by 1° normalized difference vegetation index (NDVI) dataset obtained farm Advanced Very High Resolution Radiometer red and near-infrared data. Corrections were applied to the source NDVI dataset to account for (i) obvious anomalies in the data time series, (ii) the effect of variations in solar zenith angle, (iii) data dropouts in cold regions where a temperature threshold procedure designed to screen for clouds also eliminated cold land surface points, and (iv) persistent cloud cover in the Tropics. An outline of the procedures for calculating the land surface parameters from the corrected NDVI dataset is given, and a brief d...

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) provides global monthly measurements of both oceanic phytoplankton chlorophyll biomass and light harvesting by land plants. These measurements allowed the comparison of simultaneous ocean and land net primary production (NPP) responses to a major El Niño to La Niña transition. Between September 1997 and August 2000, biospheric NPP varied by 6 petagrams of carbon per year (from 111 to 117 petagrams of carbon per year). Increases in ocean NPP were pronounced in tropical regions where El Niño–Southern Oscillation (ENSO) impacts on upwelling and nutrient availability were greatest. Globally, land NPP did not exhibit a clear ENSO response, although regional changes were substantial.

The physiological response of terrestrial vegetation when directly exposed to an increase in atmospheric carbon dioxide (CO ₂ ) concentration could result in warming over the continents in addition to that due to the conventional CO ₂ “greenhouse effect.” Results from a coupled biosphere-atmosphere model (SiB2-GCM) indicate that, for doubled CO ₂ conditions, evapotranspiration will drop and air temperature will increase over the tropical continents, amplifying the changes resulting from atmospheric radiative effects. The range of responses in surface air temperature and terrestrial carbon uptake due to increased CO ₂ are projected to be inversely related in the tropics year-round and inversely related during the growing season elsewhere.

Global, monthly, 1° by 1° biophysical land surface datasets for 1982–90 were derived from data collected by the Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA-7, -9, and -11 satellites. The AVHRR data are adjusted for sensor degradation, volcanic aerosol effects, cloud contamination, short-term atmospheric effects (e.g., water vapor and aerosol effects ⩽2 months), solar zenith angle variations, and missing data. Interannual variation in the data is more realistic as a result. The following biophysical parameters are estimated: fraction of photosynthetically active radiation absorbed by vegetation, vegetation cover fraction, leaf area index, and fraction of green leaves. Biophysical retrieval algorithms are tested and updated with data from intensive remote sensing experiments. The multiyear vegetation datasets are consistent spatially and temporally and are useful for studying spatial, seasonal, and interannual variability in the biosphere related to the hydrological cycle, th... Abstract Global, monthly, 1° by 1° biophysical land surface datasets for 1982–90 were derived from data collected by the Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA-7, -9, and -11 satellites. The AVHRR data are adjusted for sensor degradation, volcanic aerosol effects, cloud contamination, short-term atmospheric effects (e.g., water vapor and aerosol effects ⩽2 months), solar zenith angle variations, and missing data. Interannual variation in the data is more realistic as a result. The following biophysical parameters are estimated: fraction of photosynthetically active radiation absorbed by vegetation, vegetation cover fraction, leaf area index, and fraction of green leaves. Biophysical retrieval algorithms are tested and updated with data from intensive remote sensing experiments. The multiyear vegetation datasets are consistent spatially and temporally and are useful for studying spatial, seasonal, and interannual variability in the biosphere related to the hydrological cycle, th...