WG 3: Snow data assimilation and validation methods for NWP and hydrological models

Task 3.1: Overview of the various snow observations used in NWP, hydrology and climate studies for different purposes including validation and data assimilation (e.g. different snow observations are used in different environmental applications). For data assimilation, different methods are used in NWP and hydrology. The overview will allow to assess the current situation and to understand future perspectives. Also, links between different communities of users of snow observations will be established. A critical review of snow models utilizing physical snow parameters as input and used as parametrization schemes or for downstream applications (CROCUS, Snowpack, SNTHERM) will be included.

Task 3.2: Finding a new method for combining satellite observations with conventional in-situ snow measurements and modelling results: Microwave satellite observations are combined with conventional in-situ observations in some products (Hydro-SAF), while optical satellite observations together with conventional in-situ observations are assimilated into NWP models. Sustainable principles to combine all types of information should be found. This will allow advanced assimilation of new and forthcoming satellite observations of different snow properties (snow-melt, snow extent and SWE). This approach will also need new methods to update non-observed simulated physical snow variables (such as snow wetness, density profiles and mechanical properties) based on the observed ones (such as snow depth and extent).

Task 3.3: Looking for strategies towards a more extended usage of conventional snow observations to include observations from high-resolution national networks into NWP, hydrological and climate models, as the use of data from national networks is currently very limited. Their impact will be assessed and recommendations how to increase their availability will be given.

Task 3.4: Acquiring more information about observational errors relevant for DA by establishing links between the modelling and measurement communities via WG1 and WG2. These links will also provide the users’ feedback to the measurement community by reporting about the quality of data and potential problems.