Deliverable No. D2.2 Recommendations on the coupling methodology in prediction and climate models

• Main Authors: Msadek, Rym, Maisonnave, Eric, Valcke, Sophie, Blockley, Ed, Svensson, Gunilla, Holt, Jareth, Voldoire, Aurore, Keeley, Sarah, Arduini, Gabriele, Sandu, Irina
• Format: Text
• Language: English
• Published: Zenodo 2019
• Subjects: Arctic; Sea ice
• Online Access: https://dx.doi.org/10.5281/zenodo.3567788; https://zenodo.org/record/3567788

Different practices are currently being used to couple the different components of global models for weather forecasts (several days to weeks ahead) and climate applications (several decades to centuries). This report provides a summary of the coupling methods currently used for Numerical Weather Prediction (NWP) and climate applications. We have reviewed the different approaches employed in the community and used them as a motivation to design novel experiments aimed at improving the coupling between the atmosphere, ocean and sea ice. The results of these experiments, together with prior results from the literature, have guided the recommendations provided in this report. To improve coupling methodology in NWP and climate models, we recommend using fluxes that are consistent at the interface between the atmosphere, the ocean and the sea ice. More specifically, we show that accounting for the differences in horizontal resolution between the different components of the Earth System when computing the surface fluxes, or accounting for the different sea ice thickness categories can lead to small but detectable differences in the representation of key variables like Arctic sea ice extent and volume. Even if the differences are small, computing the fluxes in a consistent way is more physical and could lead to a better representation of the atmospheric boundary layer and consequently of near-surface weather. We further show that the representation of key physical processes such as snow over sea ice is essential for a realistic representation of near surface temperature in coupled models and it is particularly important for NWP. Representing processes such as snow over sea ice is key to reduce model biases in the polar regions and hence to improve short term predictions and the representation of the model climate. We expect that the results presented in this report will help weather and climate model developments in the future.