High-resolution weather analyses, forecasts and climatologies over coastal regions are very valuable for many applications, including economic development, environmental control and homeland-security campaigns. However, analyzing and forecasting weather in these regions can be challenging because 1) flows can be very complicated, especially in regions of complex terrain; 2) local circulations are multi-scale processes forced in part by sea-land contrasts and orography; and 3) observations are normally too sparse, especially over water, to properly resolve either the macro- or micro-scale aspects of local circulations.

In the last three years, NCAR, in collaboration with the Army Test and Evaluation Command (ATEC), has developed a multi-scale weather analysis and forecast (RTFDDA) system. The system employs a Four-Dimensional Data Assimilation (FDDA) method where observations are dynamically combined into a full-physics mesoscale model (MM5) to generate real-time analyses and short-term forecasts on multi-scale domains. The grid increments of the model domains vary from a few hundred meters to tens of kilometers. By incorporating detailed terrain, coastline masks, and land-use information, and by using the synoptic-scale model analyses from the NWS and various real-time mesoscale observations, the RTFDDA system has proven capable of forecasting realistic local circulations. As of August, 2004, the NCAR/ATEC RTFDDA system has been implemented at about 20 sites globally, to support various projects and missions.

In this paper, case studies and examples will be presented from the RTFDDA operations over coastal regions, including the US Army Aberdeen Proving Ground (APG) in the Chesapeake Bay area, the 2004-Athens Olympics area, and the Hawaii islands and California coastal regions. Monthly averages of the RTFDDA analyses are used to derive climatological features of local, coastal circulations.