Global Biogeochemical Cycles · 2008 · 479 citations · 81 references
Vegetation PhotosynthesisEngineeringTerrestrial Ecosystem ProductivityClimate ModelingCanopy MicrometeorologyEarth System ScienceBiogeochemical ModelEarth ScienceTerrestrial EcosystemVegetation-atmosphere InteractionsRespiration ModelBiosphere ParameterizationPhotosynthesisCarbon SequestrationBiogeochemistryEcosystem PhotosynthesisBiosphere-atmosphere InteractionsEarth's ClimateClimate Dynamics
The capability to provide reliable patterns of surface flux for fine‑scale inversions is presently limited by the number of vegetation classes for which NEE can be constrained by the current network of eddy flux sites and by the accuracy of MODIS data and data for sunlight. We present VPRM, a satellite‑based assimilation scheme that estimates hourly NEE for 12 North American biomes, motivated by the need for reliable, fine‑grained first‑guess CO₂ flux fields for inverse modeling at continental and smaller scales. VPRM uses a simple mathematical structure with minimal parameters, assimilating MODIS‑derived EVI and LSWI along with high‑resolution sunlight and temperature data, and is optimized with in‑situ NEE and environmental observations from AmeriFlux and Fluxnet Canada eddy‑covariance towers. Cross‑validation demonstrates that VPRM accurately predicts hourly to monthly NEE for sites with similar vegetation, and it consistently partitions NEE into GEE and respiration, estimates half‑saturation irradiance, and provides annual NEE sums at all optimized eddy‑flux sites.
We present the Vegetation Photosynthesis and Respiration Model (VPRM), a satellite‐based assimilation scheme that estimates hourly values of Net Ecosystem Exchange (NEE) of CO 2 for 12 North American biomes using the Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI), derived from reflectance data of the Moderate Resolution Imaging Spectroradiometer (MODIS), plus high‐resolution data for sunlight and air temperature. The motivation is to provide reliable, fine‐grained first‐guess fields of surface CO 2 fluxes for application in inverse models at continental and smaller scales. An extremely simple mathematical structure, with minimal numbers of parameters, facilitates optimization using in situ data, with finesse provided by maximal infusion of observed NEE and environmental data from networks of eddy covariance towers across North America (AmeriFlux and Fluxnet Canada). Cross validation showed that the VPRM has strong prediction ability for hourly to monthly timescales for sites with similar vegetation. The VPRM also provides consistent partitioning of NEE into Gross Ecosystem Exchange (GEE, the light‐dependent part of NEE) and ecosystem respiration ( R , the light‐independent part), half‐saturation irradiance of ecosystem photosynthesis, and annual sum of NEE at all eddy flux sites for which it is optimized. The capability to provide reliable patterns of surface flux for fine‐scale inversions is presently limited by the number of vegetation classes for which NEE can be constrained by the current network of eddy flux sites and by the accuracy of MODIS data and data for sunlight.
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Dennis Baldocchi, Eva Falge, Lianhong Gu et al. · Bulletin of the American Meteorological Society · 2001 · 3.9K citations · Full text
Earth Observation, Carbon Dioxide, Environmental Monitoring +21
Solar Radiation and Productivity in Tropical Ecosystems
J. L. Monteith · Journal of Applied Ecology · 1972 · 2.7K citations