In response to the need for improved weather prediction capabilities in support of the U.S. Antarctic Program's field operations, the Antarctic Mesoscale Prediction System (AMPS) was implemented in October 2000. AMPS employs the Polar MM5, a version of the fifth-generation Pennsylvania State University-NCAR Mesoscale Model optimized for use over ice sheets. The modeling system consists of several domains ranging in horizontal resolution from 90 km covering a large part of the Southern Hemisphere to 3.3 km over the complex terrain surrounding McMurdo, the hub of U.S. operations. The performance of the 30-km AMPS domain versus observations from manned and automatic weather stations is statistically evaluated for a 2-yr period from September 2001 through August 2003. The simulated 12-36-h surface pressure and near-surface temperature at most sites have correlations of r > 0.95 and r > 0.75, respectively, and small biases. Surface wind speeds reflect the complex topography and generally have correlations between 0.5 and 0.6, and positive biases of 1-2 m s(-1). In the free atmosphere, r > 0.95 (geopotential height), r > 0.9 (temperature), and r > 0.8 (wind speed) at most sites. Over the annual cycle, there is little interseasonal variation in skill. Over the length of the forecast, a gradual decrease in skill is observed from hours 0-72. One exception is the surface pressure, which improves slightly in the first few hours, due in part to the model adjusting from surface pressure biases that are caused by the initialization technique over the high, cold terrain. The impact of the higher-resolution model domains over the McMurdo region is also evaluated. It is shown that the 3.3-km domain is more sensitive to spatial and temporal changes in the winds than the 10-km domain, which represents an overall improvement in forecast skill, especially on the windward side of the island where the Williams Field and Pegasus runways are situated, and in the lee of Ross Island, an important area of mesoscale cyclogenesis (although the correlation coefficients in these regions are still relatively low).
