# Extreme Droughs in the Peruvian Amazon Region (2000-2024)
## 2 Materials and Methods  
### Data Sources  
To estimate the drought-related variables, we used monthly mean data from the ERA5 reanalysis ([[https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels-monthly-means?tab=download](https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels-monthly-means?tab=download)]([https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels-monthly-means?tab=download](https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels-monthly-means?tab=download)), accessed on 6 February 2025; [36; 37]), which includes precipitation, air and land surface temperature, evapotranspiration, accessed on, and surface energy flux data. ERA5 is the fifth generation of the European Centre for Medium-range Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate, and it is produced by the Copernicus Climate Change Service (C3S) at ECMWF.  
For precipitation information, we decided to use several databases that combine satellite, model, and in situ information because of the scarcity of pluviometric data in the Peruvian Amazon region. The Peruvian Interpolation data of the PERUVIAN Hydrometeorological Service, SENAMHI's Climatological and Hydrological Observations (PISCO) database [38; 39], was initially considered, but in the end, it was not used, because previous evaluation showed that the absence of surface rainfall stations in the southern Peruvian Amazon region caused misrepresentation of the rainfall distribution. The IMERG (Global Precipitation Mission Integrated Multi-satellite Retrievals for GPM) database [40], obtained from the compatible information from the satellite constellation radiometers and the radar on board the main GPM satellite, was tested too, but preliminary comparison with other databases showed that this dataset seems to overestimate precipitation in the Peruvian Amazon basin, so it was discarded.  
On the other hand, the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS 2.0) precipitation database has been successfully used by several authors in the region, as [41; 42; 43]. It is based on 0.05\({}^{\circ}\) resolution satellite imagery and in situ station data, and it is aimed at trend analysis and seasonal drought monitoring [[https://data.chc.ucsb.edu/products/CHIRPS-2.0/global_monthly/netcdf/](https://data.chc.ucsb.edu/products/CHIRPS-2.0/global_monthly/netcdf/)]([https://data.chc.ucsb.edu/products/CHIRPS-2.0/global_monthly/netcdf/](https://data.chc.ucsb.edu/products/CHIRPS-2.0/global_monthly/netcdf/)), accessed on 6 February 2025; [44]. Another precipitation data source that was used is the Multi-Source Weighted-EnsemblePrecipitation (MSWEP) [[https://www.glob2o.org/mswep/](https://www.glob2o.org/mswep/)]([https://www.glob2o.org/mswep/](https://www.glob2o.org/mswep/)), accessed on 6 February 2025; which is a global precipitation product with a 3-hourly 0.1\({}^{\circ}\) resolution merging gauge, satellite, and reanalysis data [45]. This dataset has been used in South America, including the Amazon forest, by [46; 47] and others, with good results. The monthly precipitation product of ERA5, which has been thoroughly tested in the world, including tropical and Amazon forests [48; 49], was also used. To obtain water deficit, the evapotranspiration from ERA5 was combined with precipitation from the three datasets. The data sources, variables and units have been summarized in Table 1.