An algorithm based on the physics of radiative transfer in vegetation canopies for the retrieval of vegetation green leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR) from surface reflectances was developed and implemented for operational processing prior to the launch of the moderate resolution imaging spectroradiometer (MODIS) aboard the TERRA platform in December of 1999. The performance of the algorithm has been extensively tested in prototyping activities prior to operational production. Considerable attention was paid to characterizing the quality of the product and this information is available to the users as quality assessment (QA) accompanying the product. The MODIS LAI/FPAR product has been operationally produced from day one of science data processing from MODIS and is available free of charge to the users from the Earth Resources Observation System (EROS) Data Center Distributed Active Archive Center. Current and planned validation activities are aimed at evaluating the product at several field sites representative of the six structural biomes. Example results illustrating the physics and performance of the algorithm are presented together with initial QA and validation results. Potential users of the product are advised of the provisional nature of the product in view of changes to calibration, geolocation, cloud screening, atmospheric correction and ongoing validation activities. D

Policies to reduce emissions from deforestation would benefit from clearly derived, spatially explicit, statistically bounded estimates of carbon emissions. Existing efforts derive carbon impacts of land-use change using broad assumptions, unreliable data, or both. We improve on this approach using satellite observations of gross forest cover loss and a map of forest carbon stocks to estimate gross carbon emissions across tropical regions between 2000 and 2005 as 0.81 petagram of carbon per year, with a 90% prediction interval of 0.57 to 1.22 petagrams of carbon per year. This estimate is 25 to 50% of recently published estimates. By systematically matching areas of forest loss with their carbon stocks before clearing, these results serve as a more accurate benchmark for monitoring global progress on reducing emissions from deforestation.

Variability in precipitation regimes at seasonal and longer time scales strongly influences ecosystem dynamics in arid and semi‐arid regions. In this paper, we use time series of global precipitation and satellite normalized difference vegetation index (NDVI) data to analyze joint spatial and temporal variability between terrestrial ecosystems and precipitation regimes. Accumulated monthly rainfall anomalies are quantified using a standardized precipitation index (SPI), which provides a better measure of ecologically significant precipitation excess or deficit at growing season time scales relative to monthly precipitation data. Results from canonical correlation analysis reveal geographically extensive patterns of joint NDVI‐SPI variability suggestive of strong climate‐biosphere coupling. Further, leading modes of covariability are shown to be related to large‐scale ocean‐atmosphere circulation anomalies. These results illustrate the global extent and sensitivity of ecosystems susceptible to climate change‐induced perturbations in precipitation regimes.

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