Surface Radiative Flux Bias Reduction Through Regionally Varying Cloud Fraction Parameter Nudging in a Global Coupled Forecast System

James A. Ridout; Neil P. Barton; Matthew A. Janiga; Carolyn A. Reynolds; Jackie C. May; Clark Rowley; Craig H. Bishop

Surface Radiative Flux Bias Reduction Through Regionally Varying Cloud Fraction Parameter Nudging in a Global Coupled Forecast System

2021

Abstract A simple parameter nudging procedure is described that systematically reduces near‐analysis time errors in the surface net shortwave flux in the Navy ESPC (Earth System Prediction Capability) system, a global coupled forecast system that is the product of a continuing development effort at the U. S. Naval Research Laboratory. The procedure generates geographically varying perturbations to one of the cloud fraction parameters in the atmospheric model component of the system during the data assimilation cycle, resulting in large improvements in near‐analysis time surface net shortwave flux biases. After a several week spin‐up period, the global RMSE of the succeeding 10‐day mean bias computed for lead times of 6–12 hours is reduced by 40 percent. Results from application of the approach in a series of 45‐day integrations show that improvements are realized at longer forecast lead times as well. The global RMSE of the surface net shortwave flux averaged over these integrations improves by 37 percent for lead times from 1–5 days, decreasing to 18 percent for lead times from 31–45 days. The corresponding longwave flux errors are slightly degraded, ranging from a 2 percent increase for lead times from 1–5 days to a 0.5 percent increase for lead times from 31–45 days. Global‐mean reductions in ground and sea surface temperature errors are obtained through most of the 45‐day integration period due to improvements over ocean and polar regions. Potential steps for extension and operational application of the method are discussed.

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