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Technical note: the simple diagnostic photosynthesis and respiration model (SDPRM)

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Badawy,  Bakr Abdel Aziz Mohamed
Inverse Data-driven Estimation, Dr. C. Rödenbeck, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Rödenbeck,  Christian
Inverse Data-driven Estimation, Dr. C. Rödenbeck, Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Heimann,  Martin
Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Reichstein,  Markus
Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Carvalhais,  Nuno
Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Citation

Badawy, B. A. A. M., Rödenbeck, C., Heimann, M., Reichstein, M., & Carvalhais, N. (2013). Technical note: the simple diagnostic photosynthesis and respiration model (SDPRM). Biogeosciences, 10, 6485-6508. doi:10.5194/bg-10-6485-2013.


Cite as: https://hdl.handle.net/11858/00-001M-0000-000E-BAA1-9
Abstract
We present a Simple Diagnostic Photosynthesis and Respiration Model (SDPRM) that has been developed based on pre-existing formulations. The photosynthesis model is based on the light use efficiency logic for calculating the gross primary production (GPP), while the ecosystem respiration (Reco) is a modified version of an Arrhenius-type equation. SDPRM is driven by satellite-derived fAPAR (fraction of Absorbed Photosynthetically Active Radiation) and climate data from the National Center for Environmental Prediction/National Center for Atmospheric Research Reanalysis (NCEP/NCAR). The model estimates 3-hourly values of GPP for seven major biomes and daily Reco. The motivation is to provide a priori fields of surface CO2 fluxes with fine temporal and spatial scales for atmospheric CO2 inversions. The estimated fluxes from SDPRM showed that the model is capable of producing flux estimates consistent with the ones inferred from atmospheric CO2 inversion or simulated from process-based models. In this Technical Note, different analyses were carried out to test the sensitivity of the estimated fluxes of GPP and CO2 to their driving forces. The spatial patterns of the climatic controls (temperature, precipitation, water) on the interannual variability of GPP are consistent with previous studies, even though SDPRM has a very simple structure and few adjustable parameters and hence it is much easier to modify in an inversion than more sophisticated process-based models. In SDPRM, temperature is a limiting factor for the interannual variability of Reco over cold boreal forest, while precipitation is the main limiting factor of Reco over the tropics and the southern hemisphere, consistent with previous regional studies.