Real-Time Implementation of the West Coast Operational Forecast System with Data Assimilation

Jiangtao Xu, NOAA/NOS/CO-OPS, Silver Spring, MD, United States, Alexander L Kurapov, NOAA National Ocean Service, Silver Spring, MD, United States, Eric J Bayler, NOAA/NESDIS/Center for Satellite Applications and Research (STAR), MD, United States, Aijun Zhang, Center for Operational Oceanographic Products and Services (CO-OPS), National Ocean Service (NOS), National Oceanic and Atmospheric Administration (NOAA), Silver Spring, MD, United States, Zachary Burnett, NOAA/NOS/OCS, Silver Spring, MD, United States and Gregory N Seroka, NOAA/National Ocean Service/Coast Survey Development Lab, Silver Spring, MD, United States
Abstract:
NOAA’s National Ocean Service (NOS) has collaborated with the National Environmental Satellite, Data, and Information Service (NESDIS) to develop the West Coast Operational Forecast System (WCOFS), which will be NOS’ first operational forecast system to incorporate data assimilation capabilities. Based on the Regional Ocean Modeling System (ROMS), WCOFS covers the coastal and shelf waters of Washington, Oregon, and California. It will provide forecast guidance of water level, currents, temperature, and salinity to West Coast communities, from approximately 1000 km offshore to the 10-meter isobath. The forecast guidance can be used to facilitate safe and cost-efficient navigation, identify optimal locations of fishing grounds, inform search and rescue and environmental incident response, and support other ecological applications. The ROMS four-dimensional variational (4DVAR) data assimilation system is used to constrain the initial conditions. Observations of sea surface temperature (SST) from the Visual-Infrared Imaging Radiometer System (VIIRS) and ocean-surface currents measured by high frequency (HF) radar are assimilated into the model on a daily basis. The updated initial conditions are used to drive the next nowcast/forecast cycle. 4DVAR provides dynamically consistent temporal and spatial interpolation of sparse data sets, and extends the influence of the satellite and in situ observations into the future. The assimilation of both the HF radar data and satellite SST constrains eddy variability and currents in frontal regions, which subsequently improves the accuracy of the 3-day forecast. Initial testing of assimilating satellite observations of sea surface height and other sources of SST observations are underway to constrain the model where the VIIRS and HR radar observations are not available and further improve the model forecast skill. Challenges to be addressed within the NOAA operational environment include quality assurance and quality control of real-time observations, pre-processing of the observed and modeled SSH, limited predictability of the high-frequency (tidal, inertial) surface currents, and the timely mitigation of undesirable effects, such as the manifestation of unrealistic warm/cold-water patches, resulting from erroneous and insufficient observations.