02 Dec 2020
02 Dec 2020
Status: this preprint is currently under review for the journal BG.

Quantifying the spatial extent and intensity of recent extreme drought events in the Amazon rainforest and their impacts on the carbon cycle

Phillip Papastefanou1, Christian S. Zang1, Zlatan Angelov1, Aline Anderson de Castro2, Juan Carlos Jimenez3, Luiz Felipe Campos De Rezende2, Romina Ruscica4,5,6, Boris Sakschewski7, Anna Sörensson4,5,6, Kirsten Thonicke7, Carolina Vera4,5,6, Nicolas Viovy8, Celso Von Randow2, and Anja Rammig1 Phillip Papastefanou et al.
  • 1Technical University of Munich, TUM School of Life Sciences Weihenstephan, Freising, Germany
  • 2Earth System Sciences Centre, National Institute for Spatial Research, São José dos Campos, São Paulo, Brazil
  • 3GCU/IPL, University of Valencia, Valencia. Spain
  • 4Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Departamento de Ciencias de la Atmósfera y los Océanos. Buenos Aires, Argentina
  • 5CONICET – Universidad de Buenos Aires. Centro de Investigaciones del Mar y la Atmósfera (CIMA). Buenos Aires, Argentina
  • 6CNRS – IRD – CONICET – UBA. Instituto Franco-Argentino para el Estudio del Clima y sus Impactos (UMI 3351 IFAECI). Centro de Investigaciones del Mar y la Atmósfera (CIMA). Buenos Aires, Argentina
  • 7Potsdam Institute for Climate Impact Research (PIK), Telegraphenberg A31, Potsdam, 14473, Germany
  • 8LSCE, CEA-CNRS-Univ Paris-Saclay, Saclay, France

Abstract. Over the last decades, the Amazon rainforest was hit by multiple severe drought events. Here we assess the severity and spatial extent of the extreme drought years 2005, 2010, and 2015/2016 in the Amazon region and their impacts on the carbon cycle. As an indicator of drought stress in the Amazon rainforest, we use the widely applied maximum cumulative water deficit (ΔMCWD). Evaluating an ensemble of ten state-of-the-art precipitation datasets for the Amazon region, we find that the spatial extent of the drought in 2005 ranges from 2.8 to 4.2 (mean = 3.2) million km2 (46–71 % of the Amazon basin, mean = 53 %) where ΔMCWD indicates at least moderate drought conditions (ΔMCWD anomaly < 25 mm). In 2010, the affected area was about 16 % larger, ranging from 3.1 up to 4.6 (mean = 3.7) million km2 (52–78 %, mean = 63 %). In 2016, the mean area affected by drought stress was similar to 2005 (mean = 3.2 million km2; 55 % of the Amazon basin), but the general disagreement between data sets was larger, ranging from 2.4 up to 4.1 million km2 (40–70 %). In addition, we compare differences and similarities among datasets using the self-calibrating Palmer Drought Severity Index (scPDSI) and a rainfall anomaly index (RAI). We find that scPDSI shows a much stronger, and RAI a much weaker drought impact in terms of extent and severity for 2016 compared to ΔMCWD. Using an empirical ΔMCWD-mortality relationship, we calculate biomass losses of the three drought events. We show that eight of ten datasets agree on biomass losses of about 1.8 PgC for the drought years 2005 and 2010, indicating that the more intense drought in 2005 equals a larger total area of the 2010 drought regarding biomass loss. For the 2015/2016 drought event, datasets show a large variability of biomass loss induced by drought stress ranging from 1.3 to 2.7 PgC with a mean loss of 1.8 PgC. Disagreement across datasets increased, (1) when comparing the total area of more severe and extreme drought signals and (2) when comparing spatial drought location across datasets. Generally, only half of the datasets agreed on the location of a drought event. We conclude that for deriving impacts of droughts to the Amazon Basin based on precipitation, an ensemble of datasets should be considered. This is especially relevant when assessing the impact of drought on the Amazon rainforest and its carbon cycle.

Phillip Papastefanou et al.

Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

Phillip Papastefanou et al.

Phillip Papastefanou et al.


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