Development of HYPER-P: HYdroclimatic PERformance-enhanced Precipitation at 1 km/daily over the Europe-Mediterranean region from 2007 to 2022

Abstract. Accurate precipitation estimates are essential for a wide range of applications, including climate research (Pendergrass et al., 2017), water resource management (Camici et al., 2024; Fischer and Knutti, 2016; Kucera et al., 2013), agriculture (Beck et al., 2021; Ru et al., 2022), and natural hazard assessment (Serrano et al.,5 2010,Maggioni and Massari, 2018, Peiro et al., 2024; Smith et al., 2023). However, developing high-quality, long-term daily datasets at fine spatial resolutions remains challenging due to the inherent variability and heterogeneity of precipitation patterns. This study introduces the HYdroclimatic PERformance-enhanced Precipitation (HYPER-P, https://doi.org/10.5281/zenodo.15025514, Filippucci et al., 2024b) product, covering Europe and part of the Mediterranean basin from 2007 to 2022 at a 1 km daily resolution. HYPER-P is derived by downscaling and merging multiple data sources, including remote sensing products from Top-Down (TD) and Bottom-Up (BU) approaches, reanalysis datasets, and gridded in situ observations. The downscaling leverages on CHELSA climatology data (Karger et al., 2017), while the merging is obtained through a weighted average approach informed by Triple Collocation Analysis. Four merged products were developed based on multiple combinations of satellite products, observation and reanalysis datasets. The evaluation of these products was conducted through high-resolution validation in three Mediterranean regions with dense observational networks and coarse-resolution validation across Europe and a portion of North Africa. Results indicate that the combination of TD and BU satellite approaches enhance precipitation estimates, with merged products outperforming the parent datasets, especially in regions with sparse gauge coverage. The inclusion of ERA5-Land (Hersbach et al., 2020; Muñoz Sabater, 2019) further improves accuracy over areas characterized by complex topography. The merging of satellite products, particularly the one including ERA5-Land, shows overall strong performance, although challenges remain in validating precipitation estimates where ground observations are limited. This work contributes to advancing precipitation monitoring capabilities, offering valuable tools for scientific and operational applications across Europe and beyond.

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Publication Details

Journal
Earth system science data
Published
2025-10-10
DOI
https://doi.org/10.5194/essd-17-5221-2025
Citations
1
Primary Topic
Precipitation Measurement and Analysis
Type
article
Field-Weighted Citation Impact
1.30
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article

Development of HYPER-P: HYdroclimatic PERformance-enhanced Precipitation at 1 km/daily over the Europe-Mediterranean region from 2007 to 2022

Luca Ciabatta, Francesco Avanzi, Paolo Filippucci, Christian Massari et al.
1 citations
Earth system science data
Precipitation Measurement and Analysis
1.30
article

Development of HYPER-P: HYdroclimatic PERformance-enhanced Precipitation at 1 km/daily over the Europe-Mediterranean region from 2007 to 2022

Luca Ciabatta, Francesco Avanzi, Paolo Filippucci, Christian Massari, Luca Brocca, Hamidreza Mosaffa
article en
1 citations

Abstract

Abstract. Accurate precipitation estimates are essential for a wide range of applications, including climate research (Pendergrass et al., 2017), water resource management (Camici et al., 2024; Fischer and Knutti, 2016; Kucera et al., 2013), agriculture (Beck et al., 2021; Ru et al., 2022), and natural hazard assessment (Serrano et al.,5 2010,Maggioni and Massari, 2018, Peiro et al., 2024; Smith et al., 2023). However, developing high-quality, long-term daily datasets at fine spatial resolutions remains challenging due to the inherent variability and heterogeneity of precipitation patterns. This study introduces the HYdroclimatic PERformance-enhanced Precipitation (HYPER-P, https://doi.org/10.5281/zenodo.15025514, Filippucci et al., 2024b) product, covering Europe and part of the Mediterranean basin from 2007 to 2022 at a 1 km daily resolution. HYPER-P is derived by downscaling and merging multiple data sources, including remote sensing products from Top-Down (TD) and Bottom-Up (BU) approaches, reanalysis datasets, and gridded in situ observations. The downscaling leverages on CHELSA climatology data (Karger et al., 2017), while the merging is obtained through a weighted average approach informed by Triple Collocation Analysis. Four merged products were developed based on multiple combinations of satellite products, observation and reanalysis datasets. The evaluation of these products was conducted through high-resolution validation in three Mediterranean regions with dense observational networks and coarse-resolution validation across Europe and a portion of North Africa. Results indicate that the combination of TD and BU satellite approaches enhance precipitation estimates, with merged products outperforming the parent datasets, especially in regions with sparse gauge coverage. The inclusion of ERA5-Land (Hersbach et al., 2020; Muñoz Sabater, 2019) further improves accuracy over areas characterized by complex topography. The merging of satellite products, particularly the one including ERA5-Land, shows overall strong performance, although challenges remain in validating precipitation estimates where ground observations are limited. This work contributes to advancing precipitation monitoring capabilities, offering valuable tools for scientific and operational applications across Europe and beyond.

Earth system science dataVol. 17(10)
Research Institute for Geo-Hydrological Protection (IT), CIMA Research Foundation (IT), National Research Council (IT), University of Reading (GB)
Openalex Percentile: Top 17%
Precipitation Measurement and Analysis
1.30
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