Leveraging Regional Earth System Models to Understand the Changing Climate
Monthly mean geopotential height at 500 hPa for a series of RESM simulations. The top row shows the variability of the atmospheric circulation depending on the forcing. The bottom row shows the reliance of the RESM simulation on the 500 hPa forcing data.
Image courtesy of Mark Seefeldt, University of Colorado, Boulder
A fully coupled regional Earth system model (RESM) is comprised of component models representing the atmosphere – ocean – land – and sea ice in the Earth’s climate system. A RESM is forced on the boundaries by an atmospheric reanalysis or larger global earth system model. An atmosphere-only RESM frequently takes on the characteristics of the forcing dataset. This study reveals that in a fully coupled RESM the results for the lower half of the atmosphere and the surface take on driven predominantly by the modeling system.
The results of the study are significant because it shows the independence of a fully coupled RESM from the forcing data in producing simulations of weather and climate. The coupled interactions with the land – ocean – sea ice component models at the surface provide the freedom for the model to develop its own climatic state rather than being drive by the boundary conditions. The RESM has the benefits of a regional model with fewer limitations being drawn from the forcing data.
A set of decadal simulations were completed and evaluated for gains using the Regional Arctic System Model (RASM) to dynamically downscale data from a global Earth system model and two atmospheric reanalyses. RASM is a fully coupled atmosphere–land–ocean–sea ice regional Earth system model. Nudging to the forcing data is applied to approximately the top half of the atmospheric domain. The results show that for the top half of the atmosphere, the RASM simulations follow closely to that of the forcing data, regardless of the forcing data. The results for the lower half of the atmosphere, as well as the surface, show a clustering of atmospheric state and surface fluxes based on the modeling system. Biases, in comparison to reanalyses, are evident in the Earth system model forced simulations for the top half of the atmosphere but are not present in the lower atmosphere. While the RASM simulations tended to go to the same mean state for the lower atmosphere, there are a differences in the variability and changes of weather patterns across the ensemble of simulations. These differences in the weather result in variances in the sea ice and oceanic states.