@Article{PapastefanouZACJRRSSTVVVR:2022:AsDiPr,
               author = "Papastefanou, Phillip and Zang, Christian S. and Angelov, Zlatan 
                         and Castro, Aline Anderson de and Jimenez, Juan Carlos and 
                         Rezende, Luiz Felipe Campos de and Ruscica, Romina C. and 
                         Sakschewski, Boris and S{\"o}rensson, Anna A. and Thonicke, 
                         Kirsten and Vera, Carolina and Viovy, Nicolas and Von Randow, 
                         Celso and Rammig, Anja",
          affiliation = "{Technical University of Munich} and {Weihenstephan-Triesdorf 
                         University of Applied Sciences} and {Technical University of 
                         Munich} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {University of Valencia} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Universidad de Buenos Aires} and {Potsdam 
                         Institute for Climate Impact Research (PIK)} and {Universidad de 
                         Buenos Aires} and {Potsdam Institute for Climate Impact Research 
                         (PIK)} and {Universidad de Buenos Aires} and {Universit{\'e} 
                         Paris-Saclay} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Technical University of Munich}",
                title = "Recent extreme drought events in the Amazon rainforest: assessment 
                         of different precipitation and evapotranspiration datasets and 
                         drought indicators",
              journal = "Biogeosciences",
                 year = "2022",
               volume = "19",
                pages = "3843--3861",
             abstract = "Over the last decades, the Amazon rainforest has been hit by 
                         multiple severe drought events. Here, we assess the severity and 
                         spatial extent of the extreme drought years 2005, 2010 and 2015/16 
                         in the Amazon region and their impacts on the regional carbon 
                         cycle. As an indicator of drought stress in the Amazon rainforest, 
                         we use the widely applied maximum cumulative water deficit (MCWD). 
                         Evaluating nine state-of-the-art precipitation datasets for the 
                         Amazon region, we find that the spatial extent of the drought in 
                         2005 ranges from 2.2 to 3.0 (mean = 2.7) ×106 km2 (37 % 51 % of 
                         the Amazon basin, mean = 45 %), where MCWD indicates at least 
                         moderate drought conditions (relative MCWD anomaly < 
                         \−0.5). In 2010, the affected area was about 16 % larger, 
                         ranging from 3.0 up to 4.4 (mean = 3.6) ×106 km2 (51 %74 %, mean = 
                         61 %). In 2016, the mean area affected by drought stress was 
                         between 2005 and 2010 (mean = 3.2 × 106 km2 ; 55 % of the Amazon 
                         basin), but the general disagreement between datasets was larger, 
                         ranging from 2.4 up to 4.1 × 106 km2 (40 %69 %). In addition, we 
                         compare differences and similarities among datasets using the 
                         self-calibrating Palmer Drought Severity Index (scPDSI) and a 
                         dry-season rainfall anomaly index (RAI). We find that scPDSI shows 
                         a stronger and RAI a much weaker drought impact in terms of extent 
                         and severity for the year 2016 compared to MCWD. We further 
                         investigate the impact of varying evapotranspiration on the 
                         drought indicators using two state-of-the-art evapotranspiration 
                         datasets. Generally, the variability in drought stress is most 
                         dependent on the drought indicator (60 %), followed by the choice 
                         of the precipitation dataset (20 %) and the evapotranspiration 
                         dataset (20 %). Using a fixed, constant evapotranspiration rate 
                         instead of variable evapotranspiration can lead to an 
                         overestimation of drought stress in the parts of Amazon basin that 
                         have a more pronounced dry season (for example in 2010). We 
                         highlight that even for well-known drought events the spatial 
                         extent and intensity can strongly depend upon the drought 
                         indicator and the data sources it is calculated with. Using only 
                         one data source and drought indicator has the potential danger of 
                         under- or overestimating drought stress in regions with high 
                         measurement uncertainty, such as the Amazon basin.",
                  doi = "10.5194/bg-19-3843-2022",
                  url = "http://dx.doi.org/10.5194/bg-19-3843-2022",
                 issn = "1726-4170",
             language = "en",
           targetfile = "bg-19-3843-2022.pdf",
        urlaccessdate = "05 maio 2024"
}