The National Weather Service has a critical need to produce the best possible real-time and retrospective analyses at high spatial and temporal resolution as part of its Digital Services Program. Such analyses are in demand in a range of applications that include creation and verification of gridded forecasts, coastal zone and fire management, dispersion modeling for the transport of hazardous material, aviation and surface transportation management, and impact studies of climate change on the regional scale. To help meet this need, the so-called Analysis of Record (AOR) program which places particular attention on the analysis of weather and climate conditions near the surface was initiated in October 2004. Three distinct phases are foreseen for the AOR program, namely, the real time mesoscale analysis (RTMA), the true AOR, and the reanalysis. The first phase, ie. the RTMA, seeks to enhance existing analysis capabilities and generate CONUS-scale real-time hourly analyses for the National Digital Forecast Database. This is the pre-AOR phase and can be regarded as the proof-of-concept effort of the whole AOR program. In the second phase, the time constraint is to be relaxed and the analysis sought with the help of the best available analysis techniques. Finally, the reanalysis phase is intended for the retrospective application of the AOR to generate a robust climatological dataset. This work reports on the development of the RTMA at the National Centers for Environmental Predictions (NCEP) and the Earth System Research Laboratory (ESRL), which has been underway since December of 2004.

The RTMA consists of the hourly 5km resolution 2DVar analysis of surface observations over the NDFD CONUS grid. The system uses one-hour forecasts from the 13km Rapid Update Cycle (RUC) downscaled to the NDFD grid resolution as background, and analyzes surface temperature, specific humidity, wind, and surface pressure. In addition, it computes a diagnostic field of dew-point temperature as well as gridded estimates of the analysis uncertainty for each analyzed grid. Besides the usual land synoptic, METAR, ship, buoy and C-MAN observations, the RTMA also assimilates high density observations from various Mesonets as well as satellite SSM/I wind speeds and QuickSCAT ocean surface winds. The main component of the RTMA is NCEP's Grid-point Statistical Interpolation (GSI) analysis system. Originally a 3DVar system only, the GSI was modified to support a 2DVar capability for the assimilation of surface observations. A distinct characteristic of the GSI application to the RTMA is the use of anisotropic background error covariances of quasi-Gaussian form and synthesized with the help of spatial recursive filters. The sequential line-filtering "hexad" algorithm which is used with these filters allows for the implementation of any arbitrary anisotropy, as prescribed by the centered and normalized second-moment "aspect" tensor of spatial dispersion, provided it is a sufficiently smooth function of space. Using the Riishojgaard method, the covariance shapes in the RTMA are prescribed to display controlled degrees of correlation with the underlying terrain field, background potential temperature, and wind field.

Results from the RTMA internal evaluation as well as the challenges associated with the assimilation of the various observation types will be presented. A discussion will also be offered on on-going work to further improve the assimilation system. This includes expanding the covariance model by incorporating additional background diagnostics in its formulation, use of cross-validation methods for parameter selection and tuning within the recursive filter, improving the forward models to account for the boundary layer structure, and use of a variational quality control for the observations. The envisaged analysis of additional weather elements within the RTMA system will also be discussed.