Impact of satellite-based lake surface observations on the initial state of HIRLAM weather forecasting system

Abstract:

Lake Surface Water Temperature (LSWT) observations are used to improve the lake surface state in the High Resolution Limited Area Model (HIRLAM), a three-dimensional numerical weather prediction (NWP) model. Satellite-derived LSWT observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Along-Track Scanning Radiometer (AATSR) are first evaluated against in-situ measurements for a selection of large to medium-size lakes during the open-water season. Three experiments were then run over northern Europe for two winters (2010-2011 and 2011-2012), which involved the assimilation of remote-sensing LSWT observations into the HIRLAM analysis. In the baseline experiment, the prognostic lake parameterization inside the forecast model provided the background for the LSWT analysis by the lake parameterizations of the Fresh-water Lake model (FLake) integrated in HIRLAM. No satellite observations were used in this experiment. In the second experiment, remote-sensing observations were included along with the FLake model and in-situ observations. In the third experiment, satellite observations were used to correct the background provided by the previous analysis, excluding the FLake parameterization scheme.

Results encourage work to describe better the initial state of the lake surface in NWP models by combining satellite observations and lake parameterizations via advanced data assimilation methods. It has been learned that space-borne observations are beneficial for the description of lake surface state even without parameterizations when FLake alone would have led to too early break-up in spring. In order to utilize the space-borne and in-situ observations along with lake parameterization for the improvement of the weather forecast, methods to connect the analyzed LSWT and ice cover to the prognostic in-lake variables are needed to fully benefit from the space-borne observations.