@InProceedings{RosanGGOPMAHVWTBFS:2021:AsLaUs,
               author = "Rosan, Thais M. and Goldewijk, Kess Klein and Ganzenm{\"u}ller, 
                         Raphael and O'Sullivan, Michael and Pongratz, Julia and Mercado, 
                         Lina M. and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de and 
                         Heinrich, Viola and Von Randow, Celso and Wiltshire, Andrew and 
                         Tubiello, Francesco N. and Bastos, Ana and Friedlingstein, Pierre 
                         and Stich, Stephen",
          affiliation = "{University of Exeter} and {Utrecht University} and 
                         {Ludwig-Maximilians-Universit{"a}t} and {University of Exeter} 
                         and {Ludwig-Maximilians-Universit{"a}t} and {University of 
                         Exeter} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {University of Bristol} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Met Office Hadley Centre} and FAO and {Max 
                         Planck Institute for Biogeochemistry} and {University of Exeter} 
                         and {University of Exeter}",
                title = "Assessment of land use and land cover datasets for Brazil and 
                         impact on C emissions",
                 year = "2021",
         organization = "EGU General Assembly",
            publisher = "EGU",
             abstract = "Brazil is responsible for about one third of the global land use 
                         and land cover change (LULCC) carbon dioxide emissions. However, 
                         there is a disagreement among different methodologies on the 
                         magnitude and trends in emissions and their geographic 
                         distribution. One of the main uncertainties is associated with 
                         different LULCC datatasets used as input in the different 
                         approaches. In this work we perform an evaluation of LULCC 
                         datasets for Brazil, including the global dataset (HYDE 3.2) used 
                         in the annual Global Carbon Budget (GCB), and national Brazilian 
                         dataset (MapBiomas) over the period 2000-2018. We also analyze the 
                         latest global HYDE 3.3 dataset based on new FAO inventory 
                         estimates and multi-annual ESA CCI satellite-based land cover 
                         maps. Results show that the new HYDE 3.3 can represent well the 
                         observed spatial variation in cropland and pastures areas over the 
                         last decades compared to national data (MapBiomas) and shows an 
                         improvement compared to HYDE 3.2 used in GCB. However, the 
                         magnitude of LULCC assessed with HYDE 3.3 is lower than national 
                         estimates from MapBiomas. Finally, we used HYDE 3.3 as input to 
                         two different approaches included in GCB, a global bookkeeping 
                         model (BLUE) and a process-based Dynamic Global Vegetation Model 
                         (JULES-ES) to determine the impact of the new version of HYDE 
                         dataset on Brazils land-use emissions trends over the period 
                         2000-2017. Both JULES-ES and BLUE now simulate a negative land-use 
                         emissions trend for the last two decades. This negative trend is 
                         in agreement with Brazilian INPE-EM, global H\&N bookkeeping 
                         models, FAO and as reported in National GHG inventories (NGHGI), 
                         although magnitudes differ among approaches. Overall, the 
                         inclusion of the multi-annual ESA CCI Land Cover dataset to 
                         allocate spatially the FAO statistical data has improved spatial 
                         representation of agricultural area change in Brazil in the last 
                         two decades, contributing to improve global model capability to 
                         simulate Brazils LULCC emissions in agreement with national trends 
                         estimates and spatial distribution.",
  conference-location = "Online",
      conference-year = "19-30 apr.",
                  doi = "10.5194/egusphere-egu21-3065",
                  url = "http://dx.doi.org/10.5194/egusphere-egu21-3065",
             language = "en",
           targetfile = "EGU21-3065-print.pdf",
        urlaccessdate = "09 maio 2024"
}