General Description: Data Assimilation

see also: dynamics and numerics | initial and boundary conditions | physical parameterizations | external parameters | code and parallelization | GME assimilation
Last updated: September 2011

Basic Method

Continuous four-dimensional data assimilation based on observation nudging, with lateral spreading of upper-air observation increments along horizontal surfaces. Explicit balancing by a hydrostatic temperature correction for surface pressure updates, a geostrophic wind correction, and a hydrostatic upper-air pressure correction.

Assimilated Atmospheric Observations

Radiosonde (wind, temperature, humidity), aircraft (wind, temperature), wind profiler (wind), and surface-level data (SYNOP, SHIP, BUOY: pressure, wind, humidity). Optionally RASS (temperature), and ground-based GPS (integrated water vapour) data. Surface-level temperature is used for the soil moisture analysis only.

Radar derived rain rates

Assimilation of near surface rain rates based on latent heat nudging. It locally adjusts the three-dimensional thermodynamical field of the model in such a way that the modelled precipitation rates should resemble the observed ones.

Surface and Soil Fields

Additional two-dimensional intermittent analysis:

• Soil Moisture Analysis
  Daily adjustment of soil moisture by a variational method (Hess, 2001) in order to improve 2-m temperature forecasts; use of a Kalman-Filter-like background weighting.
• Sea Surface Temperature Analysis
  Daily Cressman-type correction, and blending with global analysis. Use of external sea ice cover analysis.
• Snow Depth Analysis
  6-hourly analysis by weighted averaging of snow depth observations, and use of snowfall data and predicted snow depth.