Integration of MODIS land and atmosphere products with a coupled-process model to estimate gross primary productivity and evapotranspiration from 1 km to global scales

• Published in: Global Biogeochemical Cycles
• Main Authors: Ryu, Youngryel, Baldocchi, Dennis D., Kobayashi, Hideki, van Ingen, Catharine, Li, Jie, Black, T. Andy, Beringer, Jason, van Gorsel, Eva, Knohl, Alexander, Law, Beverly E., Roupsard, Olivier
• Other Authors: Department of Environmental Science, Policy, and Management, University of California (UC), Seoul National University Seoul (SNU), eScience Group, Department of Computer Science Charlottesville (CS), University of Virginia-University of Virginia, University of Virginia, Faculty of Land and Food Systems, University of British Columbia (UBC), School of Geography and Environmental Science, Monash University Clayton, CSIRO Marine and Atmospheric Research (MAR), Commonwealth Scientific and Industrial Research Organisation Canberra (CSIRO), Georg-August-University = Georg-August-Universität Göttingen, Department of Forest Ecosystems and Society, Oregon State University (OSU), Ecologie fonctionnelle et biogéochimie des sols et des agro-écosystèmes (UMR Eco&Sols), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Centro Agronomico Tropical de Investigacion y Enseñanza (CATIE), G. Farquhar and D. de Pury gave constructive comments on their model. Martin Jung, Christian Beer, Jan Pisek, and Jing Chen kindly shared their products. In particular, we thank Deb Agarwal, Keith Jackson and Marty Humphrey for their support on the use of Microsoft Azure Cloud Computing Service. Larry Flanagan, Russ Scott, Gil Bohrer, Andrej Varlagin, Tomomichi Kato, and Rodrigo Vargas gave constructive comments on the manuscript. Y.R. was supported by NASA Headquarters under the NASA Earth and Space Science Fellowship Program (NNX08AU25H) and the Berkeley Water Center/Microsoft eScience project, and supported by Korea-Americas Cooperation Program through the National Research Foundation of Korea (NRF) funded by the Korean Ministry of Education, Science and Technology (2011-0030485). MODIS data processing was supported by Microsoft Azure cloud computing service. Data from the Tonzi and Vaira Ranches was supported by the Office of Science (BER), U.S. Department of Energy, grant DE-FG02-06ER64308. This work used eddy covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux (U.S. Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program (DE-FG02-04ER63917 and DE-FG02-04ER63911)), AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada (supported by CFCAS, NSERC, BIOCAP, Environment Canada, and NRCan), GreenGrass, KoFlux, LBA, NECC, OzFlux, TCOS-Siberia, and USCCC. We acknowledge the financial support to the eddy covariance data harmonization provided by CarboEuropeIP, FAO-GTOS-TCO, iLEAPS, Max Planck Institute for Biogeochemistry, National Science Foundation, University of Tuscia, Universite Laval and Environment Canada and U.S. Department of Energy and the database development and technical support from Berkeley Water Center, Lawrence Berkeley National Laboratory, Microsoft Research eScience, Oak Ridge National Laboratory, University of California, Berkeley, and University of Virginia.
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2011
• Subjects: upscaling; gross primary productivity; environmental sciences and ecology; geology; meteorology and atmospheric sciences; geosciences; multidisciplinary; evapotranspiration; fluxnet; [SDV]Life Sciences [q-bio]; [SDE]Environmental Sciences; Arctic
• Online Access: https://hal.inrae.fr/hal-02651212; https://doi.org/10.1029/2011GB004053

International audience We propose the Breathing Earth System Simulator (BESS), an upscaling approach to quantify global gross primary productivity and evapotranspiration using MODIS with a spatial resolution of 1-5 km and a temporal resolution of 8 days. This effort is novel because it is the first system that harmonizes and utilizes MODIS Atmosphere and Land products on the same projection and spatial resolution over the global land. This enabled us to use the MODIS Atmosphere products to calculate atmospheric radiative transfer for visual and near infrared radiation wave bands. Then we coupled atmospheric and canopy radiative transfer processes, with models that computed leaf photosynthesis, stomatal conductance and transpiration on the sunlit and shaded portions of the vegetation and soil. At the annual time step, the mass and energy fluxes derived from BESS showed strong linear relations with measurements of solar irradiance (r(2) = 0.95, relative bias: 8%), gross primary productivity (r(2) = 0.86, relative bias: 5%) and evapotranspiration (r(2) = 0.86, relative bias: 15%) in data from 33 flux towers that cover seven plant functional types across arctic to tropical climatic zones. A sensitivity analysis revealed that the gross primary productivity and evapotranspiration computed in BESS were most sensitive to leaf area index and solar irradiance, respectively. We quantified the mean global terrestrial estimates of gross primary productivity and evapotranpiration between 2001 and 2003 as 118 +/- 26 PgC yr(-1) and 500 +/- 104 mm yr(-1) (equivalent to 63,000 +/- 13,100 km(3) yr(-1)), respectively. BESS-derived gross primary productivity and evapotranspiration estimates were consistent with the estimates from independent machine-learning, data-driven products, but the process-oriented structure has the advantage of diagnosing sensitivity of mechanisms. The process-based BESS is able to offer gridded biophysical variables everywhere from local to the total global land scales with an 8-day interval over multiple ...