Evaluation of a Cycling Mesocale Ensemble Prediction System over the Antarctic Region

The Antarctic and Southern Ocean are extremely difficult regions for numerical weather prediction (NWP) models in part due to the limited quantity and quality of observations for this remote region.  From this, a great degree of uncertainty exists in accuracy of the analyses utilized for the model initialization, lending to low confidence in forecasts and decreasing the utility of NWP models in this region as being a suitable tool for scientific studies.  The Antarctic Mesoscale Prediction System (AMPS), which is a modified version of the Advanced Research Weather and Research Forecasting (ARW-WRF), is currently the only operational mesoscale NWP model used in the southern polar region.  A new system, called Antarctic DART (A-DART), has been developed using AMPS but this time using the Data Assimilation Research Testbed (DART) with an Ensemble Kalman Filtering technique.  In the development of A-DART, different scientific problems came about which were needed to be fixed to make A-DART a more reliable tool.

In this study, the hypothesis is that an Ensemble Kalman Filter technique will produce comparable analyses for the Southern Hemisphere region as those created by 3DVAR in AMPS.  When testing this hypothesis, obstacles arose that had to be addressed which lead to experiments to try to correct these obstacles.  Initially, A-DART assimilated conventional observations such as radiosondes, ACARS, geostationary satellites, and GPSRO.  After a month of cycling, a model circulation bias was discovered in the upper atmosphere that was initially linked to a warm model bias found over the continent.  Three experiments were designed to eliminate the circulation bias by assimilating polar orbiting satellite wind data and atmospheric infrared sounder (AIRS) profiles along with a correction in the shortwave radiation scheme.  The results from this study confirm that there is an importance of assimilating a high number of observations while also assimilating high quality observations when trying to achieve an accurate analysis in the Southern Hemisphere.