Global Forecast Impact of GPS-RO Observations

A portion of Spire’s company mission is the collection of spatially and temporally dense, and accurate GPS Radio Occultation (GPS-RO) observations from a constellation of CubeSats, which are designed and manufactured in house. Projecting Spire’s early growth into the future, it is expected that within a relatively short time, the number and density of GPS-RO observations will sky-rocket over the entire globe. With the availability of such a set of real-time observations, we expect to see great improvement in numerical weather prediction forecasts, especially given that the Spire GPS-RO observations are similar in quality to those of the COSMIC mission.

In this study, the impact of the currently available Spire GPS-RO observations on the global short-term forecast will be quantified using standard data assimilation methods, including 4DEnVar and 3DVar, over a series of data-denial experiments. Considerations for the data assimilation configuration and observation usage in this study will follow knowledge gleaned from similar previous studies that assimilated GPS-RO observations from Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) and Challenging Minisatellite Payload (CHAMP) and found that the GPS-RO information leads to forecast model bias and RMS error reduction. Those studies will guide such choices as the assimilation of bending angle vs. refractivity, quality control, observation operator, and the interaction of GPS-RO observations with other standard datasets routinely assimilated. The improvement of the forecasts in studies using GPS-RO observations from other platforms lead us to expect that the assimilation of Spire GPS-RO observations will also lead to improvement of the global short-term forecast.