Consistency between sun-induced chlorophyll fluorescence and gross primary production of vegetation in North America

Consistency between sun-induced chlorophyll fluorescence and gross primary production of... Accurate estimation of the gross primary production (GPP) of terrestrial ecosystems is vital for a better understanding of the spatial-temporal patterns of the global carbon cycle. In this study, we estimate GPP in North America (NA) using the satellite-based Vegetation Photosynthesis Model (VPM), MODIS images at 8-day temporal and 500m spatial resolutions, and NCEP-NARR (National Center for Environmental Prediction-North America Regional Reanalysis) climate data. The simulated GPP (GPPVPM) agrees well with the flux tower derived GPP (GPPEC) at 39 AmeriFlux sites (155 site-years). The GPPVPM in 2010 is spatially aggregated to 0.5 by 0.5° grid cells and then compared with sun-induced chlorophyll fluorescence (SIF) data from Global Ozone Monitoring Instrument 2 (GOME-2), which is directly related to vegetation photosynthesis. Spatial distribution and seasonal dynamics of GPPVPM and GOME-2 SIF show good consistency. At the biome scale, GPPVPM and SIF shows strong linear relationships (R2>0.95) and small variations in regression slopes (4.60–5.55gCm−2day−1/mWm−2nm−1sr−1). The total annual GPPVPM in NA in 2010 is approximately 13.53PgCyear−1, which accounts for ~11.0% of the global terrestrial GPP and is within the range of annual GPP estimates from six other process-based and data-driven models (11.35–22.23PgCyear−1). Among the seven models, some models did not capture the spatial pattern of GOME-2 SIF data at annual scale, especially in Midwest cropland region. The results from this study demonstrate the reliable performance of VPM at the continental scale, and the potential of SIF data being used as a benchmark to compare with GPP models. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Remote Sensing of Environment Elsevier

Consistency between sun-induced chlorophyll fluorescence and gross primary production of vegetation in North America

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Publisher
Elsevier
Copyright
Copyright © 2016 Elsevier Inc.
ISSN
0034-4257
D.O.I.
10.1016/j.rse.2016.05.015
Publisher site
See Article on Publisher Site

Abstract

Accurate estimation of the gross primary production (GPP) of terrestrial ecosystems is vital for a better understanding of the spatial-temporal patterns of the global carbon cycle. In this study, we estimate GPP in North America (NA) using the satellite-based Vegetation Photosynthesis Model (VPM), MODIS images at 8-day temporal and 500m spatial resolutions, and NCEP-NARR (National Center for Environmental Prediction-North America Regional Reanalysis) climate data. The simulated GPP (GPPVPM) agrees well with the flux tower derived GPP (GPPEC) at 39 AmeriFlux sites (155 site-years). The GPPVPM in 2010 is spatially aggregated to 0.5 by 0.5° grid cells and then compared with sun-induced chlorophyll fluorescence (SIF) data from Global Ozone Monitoring Instrument 2 (GOME-2), which is directly related to vegetation photosynthesis. Spatial distribution and seasonal dynamics of GPPVPM and GOME-2 SIF show good consistency. At the biome scale, GPPVPM and SIF shows strong linear relationships (R2>0.95) and small variations in regression slopes (4.60–5.55gCm−2day−1/mWm−2nm−1sr−1). The total annual GPPVPM in NA in 2010 is approximately 13.53PgCyear−1, which accounts for ~11.0% of the global terrestrial GPP and is within the range of annual GPP estimates from six other process-based and data-driven models (11.35–22.23PgCyear−1). Among the seven models, some models did not capture the spatial pattern of GOME-2 SIF data at annual scale, especially in Midwest cropland region. The results from this study demonstrate the reliable performance of VPM at the continental scale, and the potential of SIF data being used as a benchmark to compare with GPP models.

Journal

Remote Sensing of EnvironmentElsevier

Published: Sep 15, 2016

References

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