Potential and limitations of convection-permitting CNRM-AROME climate modelling in the French Alps

Despite continued progress and a growing literature assessing regional climate change worldwide, modeling and assessing climate characteristics in mountainous regions remain challenging. Yet the stakes are high in these regions. As significant changes affect glaciers and snowpack, having
cascading effects on regional hydrology, quantifying them as accurately as possible is necessary for societal actors to adapt and reduce the growing climate risks.

Convection permitting climate modelling is a promising avenue for climate change research and services, particularly in mountainous regions. Work is required to evaluate the results of high resolution simulations against relevant reference dataset and put them in a broader context against coarser resolution modeling frameworks.

Our research assesses the potentials and limitations of high resolution climate models to represent past and future changes in snow conditions in the European Alps.

Here, we present an insight from the convection permitting climate model (CPRCM) CNRM-AROME ran at 2.5 km horizontal resolution over a large pan-Alpine domain in the European Alps, using either the ERA-Interim or CNRM-CM5 output as boundary conditions.

Annual and seasonal characteristics of four variables (2m temperature, total precipitation, solid fraction of precipitation and snow depths) are compared over the French Alps with the local reanalysis S2M, and raw or adjusted, with the ADAMONT method, simulations of the regional
climate model CNRM-ALADIN driven either by the ERA-Interim reanalysis or the CNRM-CM5 global climate model.

The study generally highlights similar differences in past and future climate between the datasets, as well as obstacles to the use of some CNRM-AROME outputs as they stand. These consist of excessive accumulation of snow on the ground above 1800 m a.s.l., as well as lower temperature
values at same elevations than the S2M reanalysis and the ADAMONT-adjusted outputs.

Nevertheless, clear advantages of CNRM-AROME simulations compared to raw CNRM-ALADIN outputs appear, concerning the temperature fields, the better representation of precipitations, as well as the spatial variability closer to the reference data.