Diurnal Corrections of Short-Term Surface Temperature Forecasts Using the Kalman Filter

Abstract Surface temperature forecasts from numerical weather prediction models are known to have systematic errors, partly due to poor resolution of the topography and deficiencies in the physical formulation. The Kalman filter theory provides an excellent tool for combining observations and forecasts to correct such systematic errors. As detailed in this paper, deviations between temperature forecasts and observations were studied at several locations in Norway. It was found that the sign and magnitude of the deviations varied considerably in both time and space. Moreover, the diurnal variation of the systematic errors increased as the diurnal variation between daytime and nighttime increased. A Kalman filter model has been constructed that allows for diurnally varying corrections. Eight corrections, valid at 0000, 0300, 0600, 0900, 1200, 1500, 1800, and 2100 UTC, are calculated simultaneously. These corrections, which are weighted means of previous differences between observations and forecasts, are ap...