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Evaluation of the new MODIS fAPARchl product using CLM4 and CASA
Qingyuan
Zhang, GESTAR/USRA & GSFC/NASA, qingyuan.zhang-1@nasa.gov
(Presenter)
Yen-Ben
Cheng, NASA GSFC / ERT, Inc., yen-ben.cheng@nasa.gov
(Presenter)
Tiexi
Chen, GESTAR/USRA & GSFC/NASA, chentiexi@gmail.com
Jiangfeng
Wei, U. of Texas, jwei@utexas.edu
Alexei
Lyapustin, NASA GSFC/GEST UMBC, alexei.i.lyapustin@nasa.gov
Yujie
Wang, GEST/UMBC, yujie.wang-1@nasa.gov
Current land surface models and biogeochemical models scale up photosynthesis from individual leaves to whole canopies based on vegetation structure. They have utilized leaf area index (LAI) to estimate the fraction of PAR absorbed by the vegetation canopy (fAPARcanopy) or the foliage (fAPARfoliage) and then used fAPARcanopy/fAPARfoliage to estimate the gross primary production (GPP). The Community Land Model (CLM) is now one of the most widely used land surface models and climate models using it have contributed to the Intergovernmental Panel on Climate Change (IPCC) Fourth Access Report on climate change (AR4). Previous studies have reported that CLM version 4 (CLM4), which utilizes APAR by all the leaves (APARfoliage) to calculated vegetation photosynthesis in the biogeochemistry component, tends to overestimate GPP compared with flux measurements based estimates and other process models. However, only the PAR absorbed by chlorophyll throughout the canopy (APARchl), not the PAR absorbed by the whole canopy (APARcanopy) or by the foliage of the canopy (APARfoliage), is used for canopy photosynthesis (PSN). Consequently, fAPAR by chlorophyll of the canopy (fAPARchl) should replace fAPARcanopy (i.e., FPAR) and fAPARfoliage to estimate the APAR actually driving canopy level photosynthesis (APARPSN). This biochemistry-oriented approach offers an alternative to scale-up plant photosynthesis from chloroplast level to canopy level. We retrieved 500 m fAPARchl using the PROSAIL2 and the MODerate-Resolution Imaging Spectrometer (MODIS) data which were better gridded and atmospherically corrected with the multi-angle implementation of atmospheric correction (MAIAC) algorithm. The fAPARchl products were integrated into the CLM4 and the Carnegie Ames Stanford Approach (CASA) Biosphere model. We compared the GPP estimates of the models with flux measurements based GPP. The results show that the GPP estimates using fAPARchl are superior to the estimates using fAPARcanopy. And using fAPARchl instead of fAPARcanopy mitigates the uncertainty of the simulations of CLM and CASA.
Presentation Type: Poster
Session: Poster Session 1-B
(Tue 4:30 PM)
Associated Project(s):
Poster Location ID: 14
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