The relevance of coupled climate model WRF-CTSM for land-atmosphere interactions analysis

A credible assessment of spatial and temporal variability of the water and energy budget is of viable importance for the quantification of the observed changes and prediction of extremes in a changing climate. However, an accurate representation of feedback mechanisms between the land surface and the atmosphere is a key source of uncertainty in climate models.

WRF-CTSM (Weather Research and Forecasting model, WRF, and Community Terrestrial Systems Model, CTSM) is a state-of-the-art modelling tool that represents the forefront in the climate modelling community and unifies the recent model development activities across weather, climate, water and ecosystem research. This study is the first to provide a systematic regional scale assessment of the WRF-CTSM coupled climate model performance in the European context - in the high-latitude region encompassing Norway, Sweden and Finland.

A 10-year-long regional WRF-CTSM simulation (2010-2020) using meteorological boundary conditions from the ERA5 reanalysis is performed on a 10.5 km horizontal resolution to evaluate the representation of hydroclimatic variables through comparison against ERA5 and a range of observational datasets. Changes in boundary layer variables such as soil and near-surface air temperature, soil moisture and snowpack are essential for the assessment of the land-atmosphere feedbacks in this region and are thus selected as central for the analysis of the model skill. Besides the WRF-CTSM simulations using default CTSM settings, this study investigates the added value of including the recently developed Hillslope Hydrology model in WRF-CTSM runs that has the potential to improve the understanding of the role of topography and hydrology on the soil moisture and snowpack variability.

Preliminary results indicate the capacity of WRF-CTSM to identify the high-temperature susceptible areas in Norway, Sweden and Finland and reproduce the interannual variability and spatial patterns of hydroclimatic variables in the respective region.