Variabilidade na produção primária líquida em modelos de superfície para sítios sul-americanos

• Ano de defesa: 2013
• Autor(a) principal: Silveira, Marcos Corrêa
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; BR; Meteorologia; UFSM; Programa de Pós-Graduação em Meteorologia
• Palavras-chave em Português: Biomassa de carbono; NPP; Modelos de superfície; LBA; LBA-DMIP; Carbon biomass; Land Surface Models; CNPQ::CIENCIAS EXATAS E DA TERRA::GEOCIENCIAS::METEOROLOGIA
• Link de acesso: http://repositorio.ufsm.br/handle/1/10273

This study analyzes simulations of Net Primary Production (NPP) from 15 different landsurface models (LSMs) and biomass pools from 6 different LSMs using meteorological conditions measured at 8 sites from Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) project as drivers. The models were not calibrated for the sites. The sites are divided into four biome types: Evergreen Broadleaf Forests (4 sites); Deciduous Broadleaf Forest (1 site); Savanna (1 site); Pasture/Agriculture (2 sites). The mean daily cycles, monthly and annual means of NPP were intercompared and evaluated. There were considerable differences among the NPP simulations, and some of these differences reached up to two orders of magnitude in nocturnal values. Seasonality in dry periods of the NPP could be observed in some models for all biome types. The annual mean NPP simulations from two Evergreen Broadleaf Forests (K34 and K67 sites) were compared with the observations. In general, the simulations by most models do not represent very well the observations; however, the mean value from all simulations is able to represent the observed data. In general, models that represented the Dynamic Vegetation Carbon Fluxes and Nitrogen Cycling Models (DVN) were those that better represented the observed values, suggesting that a more specific description of the vegetation dynamics capture, even without calibration, the carbon exchanges with enough accuracy. The simulated biomass is also divergent between the models, although the distribution of that biomass follows the expected patterns for each biome type. Therefore, we believe that a model calibration can improve the simulations results.