External data for lake parameterization in Numerical Weather Prediction and climate modeling

Lake parameterizations in atmospheric modeling include a set of external data to indicate and to map physical properties of lakes. The main challenge is the need to consider all the lakes in the atmospheric model domain and to specify the corresponding parameters. For Numerical Weather Prediction (NWP), we also need the data to initialize the lake time-dependent variables (so-called cold start data). The first steps to make the set of lake parameters for the needs of atmospheric modeling are described in this paper. The mean lake depth was chosen to be the key lake parameter for which direct measurements were collected and processed. The Global Land Cover Characteristics (GLCC) dataset was used for mapping, and the mapping method was based on a probabilistic approach. Empirical Probability Density Functions were used to project the lake information onto the target grid of an atmospheric model. The pseudo-periodical regime of the lake model was used to obtain the initial fields of lake variables.