Comparative Analysis of Daily Precipitation Using High-Resolution Reanalysis Data

As part of its responsibilities within the Spanish National Climate Change Adaptation Plan (PNACC) 2021-2030, AEMET generates and makes available to the public, through its website, climate change scenario information for Spain using statistical methods. These methods require a robust and sufficiently long observational database to enable proper training and validation, which has traditionally constrained their application to temperature and precipitation. However, the adaptation community requires information on a broader set of essential climate variables to adequately characterise the impacts of climate change on each sector. Recent studies using Artificial Intelligence show potential to generate downscaled information for a broader set of variables. However, long records from other ECV are scarce, relying on reanalysis information for training the methods.

Advances in modelling, on the other hand, have made available regional reanalysis products sich as COSMO reanalysis (Bollmeyer et al., 2015), CERRA (Schimanke et al., 2021), and ERA5-LAND (Muñoz-Sabater et al., 2024). These types of products provide historical information on a wide range of Essential Climate Variables (ECVs), offering extensive spatial coverage and physical consistency.

This study evaluates the performance of various available reanalysis products as a preliminary step towards selecting the most suitable dataset for generating high-resolution scenario information for a comprehensive set of Essential Climate Variables. Despite the focus on a complete set of ECVs, the study will focus on precipitation, as it is the variable for which AEMET has the most comprehensive data network. Different domains across the Iberian Peninsula will be analysed, with particular