The National Weather Service (NWS) forecasters prepare operational forecasts of meteorological conditions for the Great Lakes and U.S. coastal waters. The methodology used for the verification of these forecasts in terms of forecast accuracy and skill is by comparison to observations and the climatology of maritime platforms such as buoys and Coastal-Marine Automated Network Stations (C-MANs).

NWS performance goals are set to continually improve the skill for these human generated forecasts based upon our baseline capabilities. As attention and detailed examination increases on the Government Performance Results Act (GPRA) goals for results-based organizations such as the NWS, it is critical to better understand these skill scores, and how incremental improvements can be made to forecasting skill as measured by verification statistics.

Some of these forecast skill improvements are associated with the implementation of new technology, access to new sources of meteorological and oceanographic data, and forecaster training. We postulate that some of the variability seen in the marine verification skill scores can also be attributed to the natural climate changes.

We endeavor to improve NWS marine forecasts through a better understanding of how the variability in weather and climate influences NWS marine verification skill scores. A study to investigate these links between mean climate patterns and anomalies and marine verification skill scores is underway. This study is intended to assist in the identification of systematic factors such as forecast biases that may be linked to mean climate patterns. Preliminary results of the study will be presented.