The MSAS and RSAS Surface Analysis Systems

Patricia A. Miller and Michael F. Barth (NOAA Forecast Systems Laboratory)

Surface data is crucial for mesoscale weather forecasting because its time and space resolution is unmatched among in situ observations. The Mesoscale Analysis and Prediction System (MAPS) and the Rapid Update Cycle (RUC) Surface Assimilation Systems (MSAS/RSAS) exploit the resolution of surface data by providing timely and detailed surface analyses. MSAS runs operationally at NWS Forecast Offices as part of the AWIPS workstation, and contributes quality control information to the AWIPS Quality Control and Monitoring System. RSAS (also known as the RUC Surface or "RUCS" system) runs operationally at the NWS's National Centers for Environmental Prediction (NCEP), with backup services provided by the Forecast Systems Laboratory Central Facility. RSAS is currently the only data assimilation system at NCEP providing subhourly updates to its gridded output, 5 minutes past the hour for more timely analyses, and the 20 minutes past for later arriving observations. Both systems have the advantages of speed and closer fit to the observations. They produce a one-level, analysis-only grid and, therefore, require very few compute resources. Also, because the systems do not initialize a forecast model, the analysis is performed on the actual surface terrain and not along a model topography. Hence no model surface-to-station elevation extrapolations are required, all surface observations may be used, and the fit to the observations is maximized.

Since rough terrain can complicate surface analyses, the MSAS/RSAS systems attempt to obtain analyses with improved spatial continuity through careful choice of analysis methods and variables. MSAS/RSAS, for example, incorporates elevation and potential temperature differences in the correlation functions used to model the spatial correlation of the surface observations. The resulting functions help to take into account physical blocking by mountainous terrain, and improve the representation of surface gradients. In addition, the analysis variables were chosen, whenever possible, in such a way as to minimize the effects of varying terrain. Potential temperature, for instance, is analyzed instead of surface temperature because it varies more smoothly over mountainous terrain when the boundary layer is relatively deep and well mixed.

The domain and resolution configurations of the MSAS/RSAS systems are flexible. The default AWIPS system currently provides hourly analyses on a 60-km grid covering the 48 contiguous states (CONUS) and neighboring areas of Canada and Mexico. However, each forecast office is allowed to modify the location, size, and resolution of its local MSAS domain, and also the background fields utilized in the MSAS analyses. Changes in the domain size are linked to changes in the grid resolution in such a way as to minimize AWIPS impacts and guarantee that overall MSAS computational demands remain the same. The RSAS system at NCEP currently features a 15-km grid stretching from Alaska in the north to Central America in the south.

We will describe MSAS and RSAS, and will also discuss future plans and possibilities.