Fernandez-Palomino, Carlos Antonio; Hattermann, Fred F.; Krysanova, Valentina; Lobanova, Anastasia; Vega-Jácome, Fiorella; Lavado, Waldo; Santini, William; Aybar, Cesar; Bronstert, Axel (2021): Rain for Peru and Ecuador (RAIN4PE). V. 1.0. GFZ Data Services. https://doi.org/10.5880/pik.2020.010
Status
I N R E V I E W : Fernandez-Palomino, Carlos Antonio; Hattermann, Fred F.; Krysanova, Valentina; Lobanova, Anastasia; Vega-Jácome, Fiorella; Lavado, Waldo; Santini, William; Aybar, Cesar; Bronstert, Axel (2021): Rain for Peru and Ecuador (RAIN4PE). V. 1.0. GFZ Data Services. https://doi.org/10.5880/pik.2020.010
Abstract
RAIN4PE is a novel daily gridded precipitation dataset obtained by merging multi-source precipitation data (satellite-based Climate Hazards Group InfraRed Precipitation, CHIRP (Funk et al. 2015), reanalysis ERA5 (Hersbach et al. 2020), and ground-based precipitation) with terrain elevation using the random forest regression method. Furthermore, RAIN4PE is hydrologically corrected using streamflow data in catchments with precipitation underestimation through reverse hydrology. Hence, RAIN4PE is the only gridded precipitation product for Peru and Ecuador, which benefits from maximum available in-situ observations, multiple precipitation sources, elevation data, and is supplemented by streamflow data to correct the precipitation underestimation over páramos and montane catchments.
The RAIN4PE data are available for the terrestrial land surface between 19°S-2°N and 82-67°W, at 0.1° spatial and daily temporal resolution from 1981 to 2015. The precipitation dataset is provided in netCDF format.
For a detailed description of the RAIN4PE development and evaluation of RAIN4PE applicability for hydrological modeling of Peruvian and Ecuadorian watersheds, readers are advised to read Fernandez-Palomino et al. (2021).
Additional Information
Acknowledgements
The authors thank the East Africa Peru India Climate Capacities (EPICC) Project for funding this research within the International Climate Initiative (IKI) funded by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU).
Authors
Fernandez-Palomino, Carlos Antonio;Potsdam Institute for Climate Impact Research, Potsdam, Germany;Institute of Environmental Science and Geography, University of Potsdam, Potsdam, Germany
Hattermann, Fred F.;Potsdam Institute for Climate Impact Research, Potsdam, Germany
Krysanova, Valentina;Potsdam Institute for Climate Impact Research, Potsdam, Germany
Lobanova, Anastasia;Potsdam Institute for Climate Impact Research, Potsdam, Germany
Vega-Jácome, Fiorella;Hidrología – Estudios e Investigaciones Hidrológicas, Servicio Nacional de Meteorología e Hidrología del Perú, LIMA, Peru
Lavado, Waldo;Hidrología – Estudios e Investigaciones Hidrológicas, Servicio Nacional de Meteorología e Hidrología del Perú, LIMA, Peru
Santini, William;Institut de Recherche pour le Développement (IRD), GET, CNRS, UPS, CNES, Toulouse, France
Aybar, Cesar;Department of Geoinformatics – Z_GIS, University of Salzburg, Salzburg, Aust
Bronstert, Axel;Institute of Environmental Science and Geography, University of Potsdam, Potsdam, Germany
Contact
Fernandez-Palomino
(Researcher); Potsdam Institute for Climate Impact Research, Potsdam, Germany;
Contributors
Fernandez-Palomino
Funders
Bundesministerium für Umwelt, Naturschutz und Reaktorsicherheit:
International Climate Initiative (IKI)
Keywords
Andes, Amazon, Peru, precipitation, streamflow, random forest, reverse hydrology
CharacterString: RAIN4PE is a novel daily gridded precipitation dataset obtained by merging multi-source precipitation data (satellite-based Climate Hazards Group InfraRed Precipitation, CHIRP (Funk et al. 2015), reanalysis ERA5 (Hersbach et al. 2020), and ground-based precipitation) with terrain elevation using the random forest regression method. Furthermore, RAIN4PE is hydrologically corrected using streamflow data in catchments with precipitation underestimation through reverse hydrology. Hence, RAIN4PE is the only gridded precipitation product for Peru and Ecuador, which benefits from maximum available in-situ observations, multiple precipitation sources, elevation data, and is supplemented by streamflow data to correct the precipitation underestimation over páramos and montane catchments.
The RAIN4PE data are available for the terrestrial land surface between 19°S-2°N and 82-67°W, at 0.1° spatial and daily temporal resolution from 1981 to 2015. The precipitation dataset is provided in netCDF format.
For a detailed description of the RAIN4PE development and evaluation of RAIN4PE applicability for hydrological modeling of Peruvian and Ecuadorian watersheds, readers are advised to read Fernandez-Palomino et al. (2021).
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;Potsdam Institute for Climate Impact Research, Potsdam, Germany;Institute of Environmental Science and Geography, University of Potsdam, Potsdam, Germany
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