In the past four years, the National Center for Atmospheric Research (NCAR) and the Army Test and Evaluation Command (ATEC) have been developing a multi-scale (with grid sizes of 0.5-45 km), rapidly cycling (at time intervals of 1-12 hours), real-time four-dimensional data assimilation and forecasting (RTFDDA) system. The RTFDDA system is based on the PSU-NCAR MM5 model and uses continuous data assimilation that employs the forecast model with Newtonian relaxation terms.

The atmospheric model is coupled to the Noah land surface model. Traditionally, land surface model initial conditions (i.e. soil temperature, volumetric soil moisture, snow cover) have been initialized from the much coarser resolution ETA model initial analysis. Because local and regional forcing induced by small-scale heterogeneity in surface conditions are critical for the Army test range operations, more accurate surface conditions are required to initialize the coupled RTFDDA/Noah land surface model (LSM) system. One of the latest additions to the RTFDDA system is the development and implementation of a high resolution land-surface data assimilation system (HRLDAS) that provides a continuous analysis of the land-surface state for each of the model domains. The HRLDAS utilizes model-derived atmospheric forcing for some variables, but observed incident shortwave radiation and precipitation fields to drive the Noah LSM in uncoupled mode to simulate the long-term evolution of the land state. HRLDAS fields are currently being used as initial conditions to the MM5 in real-time tests. This presentation will describe the real time implementation of the HRLDAS system and illustrate its impact on the performance of the forecast system through the analysis of a few case studies during the summer of 2004.