Improving the light use efficiency model for simulating terrestrial vegetation gross primary production by the inclusion of diffuse radiation across ecosystems in China |
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| Institution: | 1. Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;2. University of Chinese Academy of Sciences, Beijing 100049, China;3. National Meteorological Center, China Meteorological Administration, Beijing 100081, China;4. Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China;5. South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China;6. Northwest Plateau Institute of Biology, Chinese Academy of Sciences, Xining 810001, China;7. Institute of Geographical Sciences, Hebei Academy of Sciences, Shijiazhuang 050000, China;1. Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA;2. Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH 43210, USA;3. Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, Ann Arbor, MI 48109, USA;4. Northern Research Station, USDA Forest Service, Durham, NH 03824, USA;5. School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68583, USA;6. Department of Biology, Indiana University, Bloomington, IN 47405, USA;1. National Meteorological Center, China Meteorological Administration, Beijing 100081, China;2. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;3. Department of Biological Systems Engineering, University of Nebraska, NE 68583-0726, USA;4. Biology Department, San Diego State University, CA 92182-4614, USA;5. Department of Civil, Environmental and Geodetic Engineering, Ohio State University, OH 43210, USA;6. Atmospheric Turbulence and Diffusion Division, NOAA/ARL, TN 37831-2456, USA;7. School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611-0410, USA;8. Biosciences Division, Argonne National Laboratory, IL 60439, USA;9. Department of Biology, Indiana University, IN 47405, USA;10. Department of Geography, Indiana University, IN 47405, USA;11. Department of Geography, The George Washington University, Washington DC 20052, USA;12. Environmental Sciences Department, University of Virginia, Charlottesville, VA 22904-4123, USA;1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China; Future Earth Research Institute, Beijing Normal University (Zhuhai), Zhuhai 519087, China;2. State Engineering Laboratory of Southern Forestry Applied Ecology and Technology, Central South University of Forestry and Technology, Changsha, Hunan 410004, China;3. International Center for Ecology, Meteorology and Environment, School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China;4. CGCEO/Geography, Michigan State University, East Lansing, MI, USA;5. School of Geography and Earth Sciences, McMaster University, Hamilton, Ontario, Canada;6. Department of Geography, University of Colorado at Boulder, Boulder, CO 80309, USA;7. European Commission, Joint Research Center, Institute for Environment and Sustainability, Ispra, Italy;8. Institute of Ecology, University of Innsbruck, Sternwartestrasse 15, Innsbruck 6020, Austria;9. IBIMET-CNR, Institute of Biometeorology, National Research Council, Via Gobetti, 101, Bologna 40129, Italy;10. IBIMET-CNR, Institute of Biometeorology, National Research Council, Via G. Caproni, 8, Firenze 50145, Italy;11. Sustainable Agro-ecosystems and Bioresources Department, Research and Innovation Centre, Fondazione E. Mach, San Michele all’Adige, Italy;12. Department of Ecology, Swedish University of Agricultural Sciences, Uppsala 750 07, Sweden;13. Civil & Environmental Engineering Dept and Environmental Research Institute, University College Cork, Cork, Ireland;14. Bioclimatology Group, Büsgen Institute, Georg-August University of Göttingen, Göttingen, Germany;15. Department of Forest Ecology, Mendel University Brno, Zemedelská 3, Brno 603 00, Czech Republic;p. Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zurich, 8092 Zurich, Switzerland;q. Forest Services of Autonomous Province of Bolzano, Bolzano, Italy;r. Faculty of Science and Technology, Free University of Bolzano, Piazza Università 1, 39100, Italy;s. Finnish Forest Research Institute, Vantaa 01301, Finland;t. DREAM, CEFE, CNRS, UMR5175, 1919 route de Mende, Montpellier Cedex 5 34293, France;u. A. N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow 119071, Russia;1. Earth Resources Technology, Inc., Laurel, MD 20707, USA;2. Unversities Space Research Association, Columbia, MD 21044, USA;3. Climate and Radiation Laboratory, National Aeronautics and Space Administration Goddard Space Flight Center, Greenbelt, MD 20771, USA;4. University of Maryland Baltimore County, Baltimore, MD 21228, USA;5. Biospheric Sciences Laboratory, National Aeronautics and Space Administration/Goddard Space Flight Center, Greenbelt, MD 20771, USA;1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China;2. State Key Laboratory of Cryospheric Sciences, Cold and Arid Regions Environmental and Engineering Research Institute, The Chinese Academy of Sciences, Lanzhou, Gansu 730000, China;3. International Center for Ecology, Meteorology and Environment, Nanjing University of Information Science and Technology, Nanjing 210044, China;4. Department of Environmental Sciences, University of Toledo, Toledo, OH 43606, USA;5. State Engineering Laboratory of Southern Forestry Applied Ecology and Technology, Central South University of Forestry and Technology, Changsha, Hunan 410004, China;6. Department of Environmental Systems Science, ETH Zurich, Universitätsstrasse 2, 8092 Zurich, Switzerland;7. College of Forestry, Oregon State University, Corvallis, OR 97331, USA;8. McMaster Centre for Climate Change and School of Geography and Earth Sciences, McMaster University, Hamilton, Ontario, Canada;9. School of Geography and Environmental Science, Monash University, Clayton, Victoria 3800, Australia;10. Institute of Hydrology and Meteorology, Technische Universität Dresden, Dresden, Germany;11. Faculty of Land and Food Systems, University of British Columbia, Vancouver, BC, Canada;12. Department of Geography, University of Colorado at Boulder, Boulder, CO 80309-0260, USA;13. European Commission, Joint Research Center, Institute for Environment and Sustainability, Ispra, Italy;14. Institut d’Astrophysique et de Géophysique, Université de Liège, Bat. B5c, 17 Allée du Six Aout, B-4000 Liege, Belgium;15. Sustainable Agro-ecosystems and Bioresources Department, IASMA Research and Innovation Centre, Fondazione Edmund Mach, 38010 San Michele all’Adige, TN, Italy;p. University of Antwerpen, Department of Biology, Universiteitsplein 1, B-2610 Wilrijk, Belgium;q. Max Planck Institute for Biogeochemistry, Jena, Germany;r. Laboratoire des Sciences du CLimat et de l’Environnement, IPSL, CEA-CNRS-UVSQ Orme des Merisiers, F-91191 Gif sur Yvette, France;s. Civil & Environmental Engineering Department, Environmental Research Institute, University College Cork, Ireland;t. Forest Services, Autonomous Province of Bolzano, Via Brennero 6, 39100 Bolzano, Italy;u. Faculty of Science and Technology, Free University of Bolzano, Piazza Università 5, 39100 Bolzano, Italy;v. CNR – Institute of Biometeorology, 50145 Florence, Italy;w. CIRAD, UMR Eco & Sols (Ecologie Fonctionnelle & Biogéochimie des Sols et des Agro-écosystèmes), 34060 Montpellier, France;x. CATIE (Tropical Agricultural Centre for Research and Higher Education), 7170 Turrialba, Costa Rica;y. A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow 119071, Russia;z. Institute of Ecology, University of Innsbruck, Innsbruck 6020, Austria;1. Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill 27599, NC, USA;2. Institute for the Environment, University of North Carolina at Chapel Hill, Chapel Hill 27599, NC, USA;3. School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China;4. Eastern Forest Environmental Threat Assessment Center, Southern Research Station, USDA Forest Service, Raleigh 27606, NC, USA;5. Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074, China;6. School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China |
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| Abstract: | Qualification of gross primary production (GPP) of terrestrial ecosystem over large areas is important in understanding the response of terrestrial ecosystem to global climate change. While light use efficiency (LUE) models were widely used in regional carbon budget estimates, few studies consider the effect of diffuse radiation on LUE caused by clouds using a big leaf model. Here we developed a cloudiness index light use efficiency (CI-LUE) model based on the MOD17 model algorithm to estimate the terrestrial ecosystem GPP, in which the base light use efficiency encompassed the cloudiness index, maximum LUE and clear sky LUE. GPP measured at seven sites from 2003 to 2007 in China were used to calibrate and validate the CI-LUE model. The results showed that at forest sites and cropland site the CI-LUE model outperformed the Vegetation Photosynthesis Model (VPM), Terrestrial Ecosystem Carbon flux model (TEC), MOD17 model algorithm driven by in situ meteorological measurements and MODIS GPP products, especially the R2 of simulated GPP against flux measurements at Dinghushan forest site increased from 0.17 (MODIS GPP products) to 0.61 (CI-LUE). Instead, VPM model had the best agreement with GPP measurements followed by CI-LUE model and lastly TEC model at two grassland sites. Meanwhile, GPP calculated by CI-LUE model has less underestimation under cloudy skies in comparison with MOD17 model. This study demonstrated the potential of the CI-LUE model in improving GPP simulations resulting from the inclusion of diffuse radiation in regulating the base light use efficiency and maximum light use efficiency. |
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| Keywords: | Cloudiness index Cloudiness index light use efficiency (CI-LUE) model Eddy covariance flux MOD17 model |
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