Impact of GPS radio occultation data assimilation on regional weather predictions

Abstract

The impact of GPS radio occultation (RO) data assimilation on severe weather predictions in East Asia is introduced and reviewed. Both the local observation operator that assimilates the retrieved refractivity as local point measurement, and the nonlocal observation operator that assimilates the integrated retrieved refractivity along a straight raypath have been utilized in WRF 3DVAR to improve the initial analysis of the model. A general evaluation of the impact of these approaches on Asian regional analysis and daily prediction is provided in this paper. In general, the GPS RO data assimilation may improve prediction of severe weather such as typhoons and Mei-yu systems when COSMIC data were available, ranging from several points in 2006 to a maximum of about 60 in 2007 and 2008 in this region. Based on a number of experiments, regional model predictions at 5 km resolution were not significantly influenced by different observation operators, although the nonlocal observation operator sometimes results in slightly better track forecast. These positive impacts are seen not only in typhoon track prediction but also in prediction of local heavy rainfall associated with severe weather over Taiwan. The impact of 56 GPS RO soundings on track prediction of Cyclone Gonu (2007) over the Indian Ocean is also appealing when compared to other tracks assimilated with different observations. From a successive evaluation of skill scores for real-time forecasts on Mei-yu frontal systems operationally conducted over a longer period and predictions of six typhoons in 2008, assimilation of GPS RO data appears to have some positive impact on regional weather predictions, on top of existent assimilation with all other observations.