| Tropical cyclones (TC) present a tremendous challenge for numerical weather prediction (NWP). Poorly specified initial conditions (i.e. model analyses) are one of the primary sources of forecast error, and high resolution observations are needed to rectify the problem. A geostationary Doppler radar instrument, NEXRAD-In-Space (NIS), has been proposed for this very purpose. A set of observing system simulation experiments (OSSE) is conducted to assess the potential role of data from NIS in improving prediction of TC via improved representation of the TC in the model analysis.; Using the University of Wisconsin Nonhydrostatic Modeling System (UW-NMS) together with an ensemble Kalman filter (EnKF), it is demonstrated that, for a typical Atlantic basin TC, NIS-observed Doppler radial velocity ( VR) and equivalent reflectivity factor (Z e) are effective in significantly reducing analysis errors. When computed over the entire grid, the degree of improvement ranges from 20 to 80 percent relative to the control (CTL) simulation, while a more homogeneous degree of improvement (50 to 80 percent) is demonstrated at locations where observations have been assimilated. Furthermore, when examination of observation impact is restricted to those surface regions with significant weather (V surf > 34 kt and/or rain rate > 12.5 mm h-1), a nearly uniform improvement of 60 to 80 percent is apparent. In general, a four to six hour assimilation window is sufficient to achieve statistical convergence (i.e. produce errors that are asymptotic relative to control).; In order to determine the degree to which the improved analysis leads to improved forecast results, a 48-hour integration is initialized from an analysis produced by assimilating both VR and Ze. Significant impact on both intensity and track are noted, with a 65 percent reduction in intensity error and 56 percent reduction in track error relative to CTL over the forecast period. In general, errors relating to surface wind are more effectively reduced than those relating to rain rate, as is evident from Brier Skill Scores (BSS) computed for a number of wind and rain rate thresholds. |
