Impact of the Dynamic Observation Error of COSMIC RO Bending Angle Data on Tropical Cyclone Sinlaku (2008)

Prediction of tropical cyclones (TCs) is one of the challenges in numerical weather prediction (NWP) since they occur mostly over open oceans where conventional observations are scarce. Therefore, the global navigation satellite system (GNSS) radio occultation (RO) observations are expected to help predict TCs due to their global distribution, accurate measurements and high vertical resolution. One of the most important components to assimilation RO data is the estimate of the observation errors that are defined by statistical functions in most of the current operational systems. However, the statistical-based estimate can be inaccurate and degrade the analysis and forecast especially in the lower troposphere over tropical regions due to the presence of large moisture gradients. In this study, we present the estimation of the dynamic observation errors of COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) RO bending angle data and investigate their impact on the forecast of tropical cyclones. We conduct sensitivity experiments over a 6-week period with 6-hourly continuously cycles during August 2008 using the framework of the Global Forecast System (GFS) and the Gridpoint Statistical Interpolation (GSI) data assimilation.

Results show that the use of COSMIC bending angle dynamic errors can improve TCs’ track forecast in the 3-6 days forecast. In this talk, we will present the data impact on various fields leading to TCs’ development and movement. Particularly, we will demonstrate how the environmental flows are changed in the dynamic error experiment and thus TC Sinlaku were steered northwestward rather than northward as seen in the control experiment.