An impact assessment of GPS radio occultation data on prediction of a rapidly developing cyclone over the southern ocean

• Published in: Monthly Weather Review
• Other Authors: Chen, Shu-Ya (author), Wee, Tae-Kwon (author), Kuo, Ying-Hwa (author), Bromwich, David (author)
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Meteorological Society 2014
• Subjects: Antarctic; East Antarctica; Southern Ocean; The Antarctic; Antarc*; Antarctica
• Online Access: http://nldr.library.ucar.edu/repository/collections/OSGC-000-000-021-255; https://doi.org/10.1175/MWR-D-14-00024.1

The impact of global positioning system (GPS) radio occultation (RO) data on an intense synoptic-scale storm that occurred over the Southern Ocean in December 2007 is evaluated, and a synoptic explanation of the assessed impact is offered. The impact is assessed by using the three-dimensional variational data assimilation scheme (3DVAR) of the Weather Research and Forecasting (WRF) Model Data Assimilation system (WRFDA), and by comparing two experiments: one with and the other without assimilating the refractivity data from four different RO missions. Verifications indicate significant positive impacts of the RO data in various measures and parameters as well as in the track and intensity of the Antarctic cyclone. The analysis of the atmospheric processes underlying the impact shows that the assimilation of the RO data yields substantial improvements in the large-scale circulations that in turn control the development of the Antarctic storm. For instance, the RO data enhanced the strength of a 500-hPa trough over the Southern Ocean and prevented the katabatic flow near the coast of East Antarctica from an overintensification. This greatly influenced two low pressure systems of a comparable intensity, which later merged together and evolved into the major storm. The dominance of one low over the other in the merger dramatically changed the track, intensity, and structure of the merged storm. The assimilation of GPS RO data swapped the dominant low, leading to a remarkable improvement in the subsequent storm’s prediction. AGS-1033112 NNX12AP89G 60031541