# The Explore2–2022 climate projections dataset for impact studies over France

## TL;DR

This paper introduces a new dataset of climate projections for France, designed to study climate impacts on water resources and support adaptation planning.

## Contribution

The novel contribution is a bias-corrected regional climate dataset for France, combining EURO-CORDEX and CMIP6 data with a reduced ensemble size for practical use.

## Key findings

- The dataset includes 10 climate variables at daily resolution for impact modeling.
- It supports analysis of uncertainty sources and climate change robustness across scenarios.
- Four contrasting climate narratives were developed for practical adaptation planning.

## Abstract

Within the Explore2 national project, a new set of bias-corrected regional climate projections sub-sampled from the EURO-CORDEX (EUR11) ensemble has been produced to describe the impact of climate change on water resources and to support impact studies over mainland France. This dataset has been specially selected to reflect the expected changes in temperature and precipitation of the complete EURO-CORDEX (EUR11) ensemble while taking those of CMIP6 into account as consistency constraint. Yet, the selection allows to obtain a smaller ensemble size to handle with. The process of GCM/RCM couples selection is fully described in the article. The dataset makes it possible to characterize and partition the various sources of uncertainty about the evolution of the climate in France, by taking into account three greenhouse gas emission scenarios (RCP 2.6, RCP 4.5 and RCP 8.5), multiple regional climate models (allowing to dispose to 9 to 17 GCM/RCM couples depending on the emission scenario), two methods of statistical bias correction (ADAMONT and CDF-t) and continuous time series to explore internal variability.

This dataset contains 10 climate variables at daily resolution, enabling the calculation of a very large number of climate impact indicators, as well as its use to drive a wide variety of hydrological models in France. Examples of climate change representations suitable for this dataset are provided for cumulative precipitation at seasonal scale. These representation methods are intended to guide potential users of this data when aiming to characterize the robustness of the changes (according to individual simulations, time horizons or climate change scenarios) and to identify contrasting scenarios across a territory. A narrative approach is also proposed to facilitate the exploration of individual projections of climate change, allowing for a more accurate consideration of inter-annual variability and extremes Four narratives were selected among the 17 GCM/RCM couples in collaboration with hydrologists which correspond to contrasting changes of temperature and precipitation in order to reflect a plurality of contrasting possible climate futures within the dispersion of the Explore2–2022 dataset.

The richness of this dataset and the inclusion of the most recent regional climate simulations for France justified its use in constructing and illustrating the reference warming trajectory for climate change adaptation (TRACC) in France, backed by the 3rd National Climate Change Adaptation Plan.

The Explore2 project worked to build a data-set meeting the FAIR Data Principles1 to maximize transparency, easiness and re-usability of data.