Published September 20, 2022
| Version v1
Dataset
Open
HiP-RI: High-resolution spatial assessment of precipitation using in-situ and remote sensing data in the Cordillera Blanca, Peru
Authors/Creators
- 1. Edwin
- 2. Katy
- 3. Hairo
- 4. Eduardo
- 5. Waldo
- 6. Antoine
- 7. Thomas
- 8. Gerardo
- 9. Alejo
- 10. Johannes
- 11. Ernesto
Description
The HiP-RI product was obtained from CHIRP, PERSIANN and GPM datasets, also vegetation products (NDVI-BOKU), topography (DEM SRTM) and data from 38 meteorological stations (2012-2020) were used to estimate precipitation in the Cordillera Blanca, northern sector of the Peruvian Andes. The observed data underwent quality control. A Gaussian filter, resampling and temporal homogenization at monthly scale were applied to the raster data. Subsequently, a linear regression model was built with the different datasets that served as predictors for precipitation spatialization. This allowed obtaining the best R2 values between the in situ data and those estimated with the model (HiP-RI). The results obtained were satisfactory with R2 values higher than 0.60 and an RMSE = 54%.
Files
2012-01_MOD.tif
Files
(46.3 MB)
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