Severe Weather Simulation Experiment (QuickOSSE) Using Super Constellations of GNSS Radio Occultation Satellites

Global navigation satellite system (GNSS) radio occultations (RO) over the last 10 years have proved to be a valuable and essentially unbiased data source for operational global numerical weather prediction. However, the existing sampling coverage is too sparse in both space and time to support forecasting of severe mesoscale weather.

In this study, the case study or quick observing system simulation experiment (QuickOSSE) framework is used to quantify the impact of vastly increased numbers of GNSS RO profiles on mesoscale weather analysis and forecasting. Our study focuses on a severe convective weather event that produced both a tornado and flash flooding in Oklahoma on May 31, 2013. The Weather Research and Forecasting (WRF) model is used to compute a realistic and faithful depiction of reality. This 2-km “nature run” (NR) serves as the “truth” in our study. The NR is sampled by two proposed constellations of GNSS RO receivers that would produce 250 thousand and 2.5 million profiles/day globally. These data are then assimilated using WRF and a 24-member, 18-km-resolution, physics-based ensemble Kalman filter. The data assimilation is cycled hourly and makes use of a non-local, excess phase observation operator for RO data.

The assimilation of greatly increased numbers of RO profiles produces improved analyses, particularly of the lower tropospheric moisture fields. Figure 1 (below) shows the ensemble mean and ensemble spread of low-level water vapor analyses at different points through the assimilation period. The upper row of plots is for the Control experiment (assimilating conventional observations; no GNSS RO data) and the lower row is for "ROSC-2.5M" experiment, i.e., assimilating observations from the proposed constellation of RO satellite receivers that produce ~ 2.5 million profiles globally/day.  Separately, the forecast results suggest positive impacts on convective initiation. More examples of the impact of these proposed constellations on analyses and short-range forecasts will be shown.

FIG. 1. The water vapor mixing ratio analysis uncertainty (g kg^-1, color fill) and analysis mean (g kg^-1, black contours) at approximately 140 meters AGL valid at (a, d) 1200, (b, e) 1500, and (c, f) 1800 UTC May 31, i.e., at the end of the first, fourth, and seventh one-hour WRF-DART analysis cycles, for (a, b, c) the Control experiment, and (d, e, f) the ROSC-2.5M experiment. The ensemble standard deviation is plotted in the colors shown by the color scale embedded on the right side of each panel, which runs from zero (blue) to 3.5 g kg^-1 (red), with numeric values indicated on the right of panels (c, f).