Title
A future of extreme precipitation and droughts in the Peruvian Andes
Date Issued
01 December 2023
Access level
open access
Resource Type
journal article
Author(s)
Potter E.R.
Fyffe C.L.
Orr A.
Quincey D.J.
Ross A.N.
Rangecroft S.
Medina K.
Burns H.
Llacza A.
Jacome G.
Hellström R.
Castro J.
Cochachin A.
Montoya N.
Pellicciotti F.
Publisher(s)
Nature Research
Abstract
Runoff from glacierised Andean river basins is essential for sustaining the livelihoods of millions of people. By running a high-resolution climate model over the two most glacierised regions of Peru we unravel past climatic trends in precipitation and temperature. Future changes are determined from an ensemble of statistically downscaled global climate models. Projections under the high emissions scenario suggest substantial increases in temperature of 3.6 °C and 4.1 °C in the two regions, accompanied by a 12% precipitation increase by the late 21st century. Crucially, significant increases in precipitation extremes (around 75% for total precipitation on very wet days) occur together with an intensification of meteorological droughts caused by increased evapotranspiration. Despite higher precipitation, glacier mass losses are enhanced under both the highest emission and stabilization emission scenarios. Our modelling provides a new projection of combined and contrasting risks, in a region already experiencing rapid environmental change.
Volume
6
Issue
1
Language
English
OCDE Knowledge area
Meteorología y ciencias atmosféricas
Scopus EID
2-s2.0-85165313277
Source
npj Climate and Atmospheric Science
ISSN of the container
23973722
Sponsor(s)
Funding text 1
This research was conducted under the Peru GROWS and PEGASUS projects, which were both funded by NERC (grants NE/S013296/1 and NE/S013318/1, respectively) and CONCYTEC through the Newton-Paulet Fund. The Peruvian part of the Peru GROWS project was conducted within the framework of the call E031-2018-01-NERC “Glacier Re-search Circles”, through its executing unit FONDECYT (Contract No. 08-2019-FON-DECYT). We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Supplementary Table 7 of this paper) for producing and making available their model output. We thank SENAMHI, UNASAM, ANA, UNSAAC, and Compañia Minera Antamina for the observational data used in the historical bias correction, and we also thank Mario Rohrer at MeteoSwiss for assisting in data access. Thanks to J. Scott Hosking, Charles Simpson, Risa Ueno and Arthur Lutz for their advice on the statistical downscaling method. We acknowledge the Polar Data Centre for archiving the data used in this manuscript. This article is dedicated to the memory of Ing. Alejo Cochachin Rapre.
Funding text 2
This research was funded jointly between Peruvian and UK funding agencies, and roles and responsibilities were agreed amongst collaborators before the start of the project. This manuscript is a collaboration between Peruvian and UK researchers, as well as international partners, and all authors were involved throughout the manuscript process. Peruvian research and reports have been cited where appropriate for this study. Acknowledgements
Sources of information:
Directorio de Producción Científica
Servicio Nacional de Meteorología e Hidrología del Perú
Instituto Nacional de Investigación en Glaciares y Ecosistemas de Montaña