Technical Note: The Simple Diagnostic Photosynthesis and Respiration Model (SDPRM)
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 (<i>R&...
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doaj-7b8aec6d1ffe4b28bfd95bc4d133c52e2020-11-24T22:40:06ZengCopernicus PublicationsBiogeosciences1726-41701726-41892013-10-0110106485650810.5194/bg-10-6485-2013Technical Note: The Simple Diagnostic Photosynthesis and Respiration Model (SDPRM)B. BadawyC. RödenbeckM. ReichsteinN. CarvalhaisM. HeimannWe 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 (<i>R</i><sub>eco</sub>) 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 <i>R</i><sub>eco</sub>. The motivation is to provide a priori fields of surface CO<sub>2</sub> fluxes with fine temporal and spatial scales for atmospheric CO<sub>2</sub> inversions. The estimated fluxes from SDPRM showed that the model is capable of producing flux estimates consistent with the ones inferred from atmospheric CO<sub>2</sub> 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 CO<sub>2</sub> 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 <i>R</i><sub>eco</sub> over cold boreal forest, while precipitation is the main limiting factor of <i>R</i><sub>eco</sub> over the tropics and the southern hemisphere, consistent with previous regional studies.http://www.biogeosciences.net/10/6485/2013/bg-10-6485-2013.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
B. Badawy C. Rödenbeck M. Reichstein N. Carvalhais M. Heimann |
spellingShingle |
B. Badawy C. Rödenbeck M. Reichstein N. Carvalhais M. Heimann Technical Note: The Simple Diagnostic Photosynthesis and Respiration Model (SDPRM) Biogeosciences |
author_facet |
B. Badawy C. Rödenbeck M. Reichstein N. Carvalhais M. Heimann |
author_sort |
B. Badawy |
title |
Technical Note: The Simple Diagnostic Photosynthesis and Respiration Model (SDPRM) |
title_short |
Technical Note: The Simple Diagnostic Photosynthesis and Respiration Model (SDPRM) |
title_full |
Technical Note: The Simple Diagnostic Photosynthesis and Respiration Model (SDPRM) |
title_fullStr |
Technical Note: The Simple Diagnostic Photosynthesis and Respiration Model (SDPRM) |
title_full_unstemmed |
Technical Note: The Simple Diagnostic Photosynthesis and Respiration Model (SDPRM) |
title_sort |
technical note: the simple diagnostic photosynthesis and respiration model (sdprm) |
publisher |
Copernicus Publications |
series |
Biogeosciences |
issn |
1726-4170 1726-4189 |
publishDate |
2013-10-01 |
description |
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 (<i>R</i><sub>eco</sub>) 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 <i>R</i><sub>eco</sub>. The motivation is to provide a priori fields of surface CO<sub>2</sub> fluxes with fine temporal and spatial scales for atmospheric CO<sub>2</sub> inversions. The estimated fluxes from SDPRM showed that the model is capable of producing flux estimates consistent with the ones inferred from atmospheric CO<sub>2</sub> 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 CO<sub>2</sub> 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 <i>R</i><sub>eco</sub> over cold boreal forest, while precipitation is the main limiting factor of <i>R</i><sub>eco</sub> over the tropics and the southern hemisphere, consistent with previous regional studies. |
url |
http://www.biogeosciences.net/10/6485/2013/bg-10-6485-2013.pdf |
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