Soil Field Model Interoperability: Challenges and Impact on Screen Temperature Forecast Skill during the Nordic Winter

Abstract

he high-resolution (4-km grid length) Met Office (UKMO) Unified Model forecasts driven by the coarser-resolution (8-km grid length) High-Resolution Limited-Area Model (HIRLAM), UM4, often produce significantly colder screen-level (2 m) temperatures in winter over Norway than forecast with HIRLAM itself. To diagnose the main error source of this cold bias this study focuses on the forecast initial and lateral boundary conditions, particularly the initialization of soil moisture and temperature. The soil variables may be used differently by land surface schemes of varying complexity, representing a challenge to model interoperability. In a set of five experiments, daily UM4 forecasts are driven by alternating initial and lateral boundary conditions from two different parent models: HIRLAM and Met Office North Atlantic and Europe (NAE). The experiment period is November 2007. Points for scientific examination into the topics of model interoperability and sensitivity to soil initial conditions are identified. The soil moisture is the main error source and is therefore important also in winter, rather than being a challenge only in summer. The day-to-day variability in the forecast error is large with the larger errors on days with strong longwave heat loss at the surface (i.e., the forecast sensitivity to soil moisture content is significant but variable). The much drier soil in HIRLAM compared to NAE reduces the heat capacity of the soil layers and affects the heat flux from the surface soil layer to the surface. Normalizing the respective soil moisture fields reduces these differences. The impact of ground snow is quite limited.