Title: Improving the performance of remote sensing models for capturing intra- and inter-annual variations in daily GPP: An analysis using global FLUXNET tower data
Authors: VERMA M.FRIEDL MARK A.LAW BEVERLYBONAL DAMIENKIELY GERALDBLACK A.WOHLFAHRT G.MOORS E.J.MONTAGNANI LEONARDOMARCOLLA B.TOSCANO PVARLAGIN ANDREJROUPSARD OLIVIERCESCATTI ALESSANDROARAIN ALTAF M.D'ODORICO PETRA
Citation: AGRICULTURAL AND FOREST METEOROLOGY vol. 214-215 p. 416-429
Publisher: ELSEVIER SCIENCE BV
Publication Year: 2015
JRC N°: JRC99997
ISSN: 0168-1923
URI: http://www.sciencedirect.com/science/article/pii/S0168192315007108?via%3Dihub
http://publications.jrc.ec.europa.eu/repository/handle/JRC99997
DOI: 10.1016/j.agrformet.2015.09.005
Type: Articles in periodicals and books
Abstract: Accurate and reliable estimates of gross primary productivity (GPP) are required for monitoring the globalcarbon cycle at different spatial and temporal scales. Because GPP displays high spatial and temporal vari-ation, remote sensing plays a major role in producing gridded estimates of GPP across spatiotemporalscales. In this context, understanding the strengths and weaknesses of remote sensing-based models ofGPP and improving their performance is a key contemporary scientific activity. We used measurementsfrom 157 research sites (∼470 site-years) in the FLUXNET “La Thuile” data and compared the skills of11 different remote sensing models in capturing intra- and inter-annual variations in daily GPP in sevendifferent biomes. Results show that the models were able to capture significant intra-annual variationin GPP (Index of Agreement = 0.4–0.80) in all biomes. However, the models’ ability to track inter-annualvariation in daily GPP was significantly weaker (IoA < 0.45). We examined whether the inclusion of differ-ent mechanisms that are missing in the models could improve their predictive power. The mechanismsincluded the effect of sub-daily variation in environmental variables on daily GPP, factoring-in differentialrates of GPP conversion efficiency for direct and diffuse incident radiation, lagged effects of environmen-tal variables, better representation of soil-moisture dynamics, and allowing spatial variation in modelparameters. Our analyses suggest that the next generation remote sensing models need better represen-tation of soil-moisture, but other mechanisms that have been found to influence GPP in site-level studiesmay not have significant bearing on model performance at continental and global scales.
JRC Directorate:Space, Security and Migration

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