Impact of Model Physics on Seasonal Forecasts of Surface Air Temperature in the Arctic

The impacts of model physics and initial sea ice thickness on seasonal forecasts of the surface energy budget and air temperature in the Arctic during summer were investigated based on Climate Forecast System version 2 (CFSv2) simulations. The model physics change includes the enabling of a stratus cloud scheme and the removal of the artificial upper limit constraint on the bottom heat flux from ocean water to sea ice. The impact of initial sea ice thickness was examined by initializing the model with sea ice thickness from the Pan-Arctic Ice Ocean Modelling and Assimilation System (PIOMAS). Model output was compared to that from a control run which did not impose physics changes and used Climate Forecast System Reanalysis (CFSR) sea ice thickness. After applying the physics modification to either sea ice thickness initialization, the simulated total cloud cover more closely resembles the observed monthly variations except for the mid-summer reduction. Over the Chukchi/Bering Sea, the model physics modification reduces the seasonal forecast bias in surface air temperature by 24%. However, the use of initial PIOMAS sea ice thickness alone worsens the surface air temperature predictions. The experiment with physics modifications and initial PIOMAS sea ice thickness achieves the best surface air temperature improvement over the Chukchi/Bering Sea where the area-weighted forecast bias is reduced by 71% from 1.05 K down to -0.3 K compared with the control run. Our study supports other results that surface temperature and sea ice characteristics are highly sensitive to the Arctic cloud and radiation formulations in models and need priority in model validation.