Abstract
Abstract. The High Resolution Limited Area Model (HIRLAM), used for the operational numerical weather prediction in the Finnish Meteorological Institute (FMI), includes prognostic treatment of lake surface state since 2012. Forecast is based on the Freshwater Lake (FLake) model integrated into HIRLAM. Additionally, an independent objective analysis of lake surface water temperature (LSWT) combines the short forecast of FLake to observations from the Finnish Environment Institute (SYKE). The resulting description of lake surface state – forecast FLake variables and analysed LSWT – was compared to SYKE observations of lake water temperature, freeze-up and break-up dates, and the ice thickness and snow depth for 2012–2018 over 45 lakes in Finland. During the ice-free period, the predicted LSWT corresponded to the observations with a slight overestimation, with a systematic error of +0.91 K. The colder temperatures were underrepresented and the maximum temperatures were too high. The objective analysis of LSWT was able to reduce the bias to +0.35 K. The predicted freeze-up dates corresponded well to the observed dates, mostly within the accuracy of a week. The forecast break-up dates were far too early, typically several weeks ahead of the observed dates. The growth of ice thickness after freeze-up was generally overestimated. However, practically no predicted snow appeared on lake ice. The absence of snow, presumably due to an incorrect security coefficient value, is suggested to be also the main reason for the inaccurate simulation of the lake ice melting in spring.
Highlights
Lakes influence the energy exchange between the surface and the atmosphere, the dynamics of the atmospheric boundary layer and the near-surface weather
Throughout the following text, the analysed lake surface water temperature (LSWT) refers to the result of optimal interpolation analysis (OI) analysis, where Freshwater Lake (FLake) forecast has been used as background (Sect. 2.2), while the forecast LSWT refers to the value diagnosed from the mixed layer water temperature predicted by FLake (Sect. 2.1)
In situ lake observations from the Finnish Environment Institute were used for validation of the High Resolution Limited Area Model (HIRLAM) numerical weather prediction (NWP) model, which is applied operationally at the Finnish Meteorological Institute
Summary
Lakes influence the energy exchange between the surface and the atmosphere, the dynamics of the atmospheric boundary layer and the near-surface weather. The aim of the present study is to validate the lake surface state forecast by the operational HIRLAM NWP model using the in situ LSWT measurements, lake ice freeze-up and break-up dates, and measurements of ice and snow thickness by the Finnish Environment Institute (Suomen Ympäristökeskus, SYKE). For this purpose, HIRLAM analyses and forecasts archived by FMI were compared with the observations by SYKE over the lakes of Finland from spring 2012 to summer 2018. This is the longest available detailed dataset that allows the user to evaluate how well the lake surface state is simulated by an operational NWP model that applies FLake parametrizations
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