Articles | Volume 29, issue 12
https://doi.org/10.5194/hess-29-2727-2025
https://doi.org/10.5194/hess-29-2727-2025
Research article
 | 
01 Jul 2025
Research article |  | 01 Jul 2025

A novel framework for analyzing rainy season dynamics in semi-arid environments: a case study in the Peruvian Rio Santa basin

Lorenz Hänchen, Emily Potter, Cornelia Klein, Pierluigi Calanca, Fabien Maussion, Wolfgang Gurgiser, and Georg Wohlfahrt

Data sets

Bias-corrected temperature and precipitation data from the WRF regional climate model output, Cordillera Blanca and Vilcanota-Urubamba regions, Peru, from 1980 to 2018 (Version 1.0) E. Potter et al. https://doi.org/10.5285/2cf25580-9b79-440f-8505-6230dd377877

Precipitation and temperature data from statistically downscaled CMIP5 models, Cordillera Blanca and Vilcanota-Urubamba regions, Peru, from 2019 to 2100 (Version 1.0) E. Potter et al. https://doi.org/10.5285/67ceb7c8-218c-46e1-9927-cfef2dd95526

Precipitation and temperature climate change indices calculated from WRF data and statistically downscaled CMIP5 models, Cordillera Blanca and Vilcanota-Urubamba regions, Peru, from 1980 to 2100 (Version 1.0) E. Potter et al. https://doi.org/10.5285/b56d30e8-edaa-4225-96d7-fcc689e930c7

MOD13Q1 MODIS/Terra vegetation indices 16-day L3 global 250m SIN grid V006 K. Didan https://doi.org/10.5067/MODIS/MOD13Q1.006

MODIS/Terra vegetation indices 16-day L3 global 250m SIN grid V006 K. Didan https://doi.org/10.5067/MODIS/MYD13Q1.006

Model code and software

Code to recreate the analysis and figures of: ``A Novel Framework for Analyzing Rainy Season Dynamics in semi-arid environments: A case study for the Peruvian Rio Santa Basin'' (v1.0) Lorenz Hänchen et al. https://doi.org/10.5281/zenodo.13952139

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Short summary
In semi-arid regions, the timing and duration of the rainy season are crucial for agriculture. This study introduces a new framework for improving estimations of the onset and end of the rainy season by testing how well they fit local vegetation data. We improve the performance of existing methods and present a new one with higher performance. Our findings can help us to make informed decisions about water usage, and the framework can be applied to other regions as well.
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