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@Article{FischerCoMuMaAgLa:2013:ExObFu,
               author = "Fischer, G. R. and Costa, Marcos H. and Murta, Fabr{\'{\i}}cio 
                         Z. and Malhado, Ana C. M. and Aguiar, Leonardo J. G. and Ladle, 
                         Richard J.",
          affiliation = "Department of Agricultural and Environmental Engineering, Federal 
                         University of Vi{\c{c}}osa, P.H. Holfs, Centro, Vi{\c{c}}osa, MG 
                         36570-000, Brazil; Institute of Biological and Health Sciences, 
                         Federal University of Alagoas, Av. Lourival Melo Mota, s/n, 
                         Tabuleiro do Martins, Macei{\'o}, AL 57072-900, Brazil and 
                         Department of Agricultural and Environmental Engineering, Federal 
                         University of Vi{\c{c}}osa, P.H. Holfs, Centro, Vi{\c{c}}osa, MG 
                         36570-000, Brazil and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and Department of Meteorology, Federal University of 
                         Pelotas, Campus Universit{\'a}rio S/N,Caixa Postal 354, Pelotas, 
                         RS 96010-900, Brazil and Department of Agricultural and 
                         Environmental Engineering, Federal University of Vi{\c{c}}osa, 
                         P.H. Holfs, Centro, Vi{\c{c}}osa, MG 36570-000, Brazil and 
                         Department of Meteorology, Federal University of Pelotas, Campus 
                         Universit{\'a}rio S/N,Caixa Postal 354, Pelotas, RS 96010-900, 
                         Brazil; Center for Weather Forecasting and Climate Studies, 
                         National Institute for Space Research, Rodovia Presidente Dutra, 
                         Cachoeira Paulista, SP 12630-000, Brazil",
                title = "Multi-site land surface model optimization: An exploration of 
                         objective functions",
              journal = "Agricultural and Forest Meteorology",
                 year = "2013",
               volume = "182-183",
                pages = "168--176",
             keywords = "biogeochemistry, calibration, ecosystem modeling, error analysis, 
                         functional group, land surface, net ecosystem exchange, numerical 
                         model, optimization, pasture, Amazonia.",
             abstract = "Land surface/ecosystem models are important tools for 
                         understanding the dynamic interactions between land surface and 
                         the atmosphere. However, to be effective these models must be 
                         carefully calibrated to accurately represent ecosystem processes. 
                         Generally, such models are calibrated for one site and then run 
                         with the same set of calibrated parameters, either for other sites 
                         or for a whole region with the same plant functional type. Here we 
                         investigate an alternative approach to the challenge of 
                         calibration. We perform multi-site calibration of net ecosystem 
                         exchange for two pasture sites in Amazonia. Twenty different 
                         objective functions (five adjustment measures subject to four 
                         calibration options) are evaluated to investigate the consistency 
                         and sensitivity of the results in a multi-site model calibration. 
                         Our results indicate that, with some restrictions regarding the 
                         choice of objective function, multi-site calibration is possible 
                         and produces consistent results across sites. Ultimately, the 
                         choice of objective function should be based on the intended use 
                         of the model. We recommend that the site-weighted method using 
                         mean absolute error as objective function should be used for 
                         shorter time scales and the site-weighted maximum bias error as 
                         objective function is better for longer time scales.",
                  doi = "10.1016/j.agrformet.2012.11.021",
                  url = "http://dx.doi.org/10.1016/j.agrformet.2012.11.021",
                 issn = "0168-1923",
                label = "scopus 2013-11",
             language = "en",
           targetfile = "Fischer_Multi-site.pdf",
        urlaccessdate = "17 jan. 2021"
}


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