Abstract
Abstract. The regional climate model REMO was coupled with the FLake lake model to include an interactive treatment of lakes. Using this new version, the Fenno-Scandinavian climate and lake characteristics were studied in a set of 35-year hindcast simulations. Additionally, sensitivity tests related to the parameterization of snow albedo were conducted. Our results show that overall the new model version improves the representation of the Fenno-Scandinavian climate in terms of 2 m temperature and precipitation, but the downside is that an existing wintertime cold bias in the model is enhanced. The lake surface water temperature, ice depth and ice season length were analyzed in detail for 10 Finnish, 4 Swedish and 2 Russian lakes and 1 Estonian lake. The results show that the model can reproduce these characteristics with reasonably high accuracy. The cold bias during winter causes overestimation of ice layer thickness, for example, at several of the studied lakes, but overall the values from the model are realistic and represent the lake physics well in a long-term simulation. We also analyzed the snow depth on ice from 10 Finnish lakes and vertical temperature profiles from 5 Finnish lakes and the model results are realistic.
Highlights
The interactions between the atmosphere and the underlying surface are among the most important factors in climate and numerical weather prediction (NWP) modeling (Mironov, 2008; Samuelsson et al, 2010)
Our analysis showed that the lake surface water temperatures (LWTs) in REMOFL are 3–7 ◦C higher on average during summer than those in REMO-ST
The regional climate model REMO was interactively coupled with the lake model FLake (REMO– FLake)
Summary
The interactions between the atmosphere and the underlying surface are among the most important factors in climate and numerical weather prediction (NWP) modeling (Mironov, 2008; Samuelsson et al, 2010). In regional climate models (RCMs), lakes have been historically taken into account by setting the related variables (e.g., surface temperature and ice conditions) to follow external data, which often have been derived from the same data source as the lateral boundary data for the atmospheric variables. This approach can be applied in regions with a low fractional area of lakes, whereas regions with a large fractional area of lakes suffer from the limited interactions between lakes and the atmosphere. Mironov et al (2010) introduced FLake into the numerical weather prediction model COSMO and showed that the coupling improved the prediction of lake surface temperatures, the freeze-up of lakes and the ice breakup across Europe. The article is structured as follows: first, REMO, FLake and the implementation structure are described in Sect. 2; in Sects. 3 and 4 a detailed analysis of the results is given; in Sect. 5, the main conclusions are discussed
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