Data assimilation and parametrisation of lakes in HIRLAM

Abstract

ABSTRACTWhen the resolution of numerical weather prediction (NWP) and climate models increases, it becomes more and more important to correctly account for the lake–atmosphere interactions. One possible way to handle lake effects is to use a lake model, which treats the lake surface temperature and ice conditions as prognostic variables. Such a parametrisation eliminates the traditional for NWP need to prescribe lake characteristics based on long-term climate averages. At the same time, new in situ and satellite measurements are becoming available for an operational practice. This offers the possibility to assimilate lake observations into the NWP models. We study the applicability of the prognostic and observation-based approaches and compare both. As a first step towards integrated lake data assimilation and forecasting in NWP, we suggest using the results of the prognostic lake parametrisation as the background for objective analysis (spatialisation) of the lake water surface temperature observations. We run NWP experiments in the Nordic conditions, where the freezing and melting of lakes can significantly influence local weather. Our results indicate that a lake model, usually used in climate studies, works well also in the NWP model even without assimilation of observations. However, it is possible to improve the description of the changing lake surface state by using good observation data. In this case, the lake model provides a better background for the data assimilation than a lake surface temperature climatology.