Revised GNSS-RO observation uncertainties in the Met Office NWP system

Abstract

The diagnostics of Desroziers et al. have been used to estimate the uncertainties of Global Navigation Satellite System Radio Occultation (GNSS-RO) observations. Compared with the uncertainties that are currently operational, the new uncertainties are smaller and vary with height, latitude, satellite identifier, and other variables. The initial tests allowed the observation uncertainties to vary with latitude, satellite identifier, and the tangent-point height of the observation. Using these uncertainties for a winter period demonstrated clear improvements in the weather forecast skill. Further tests showed that this improvement derived from the variation of the uncertainties with satellite identifier and from using a smooth variation with latitude—the current method gives a sharp change in the uncertainty at 30° intervals in latitude. The diagnosis method indicated a maximum in the observation uncertainty just above the tropical tropopause (around 20 km). Experiments demonstrated that the high values for the observation uncertainty in this region degrade the forecast performance. It is suggested that this is a sign that this method is identifying some model errors incorrectly as observation errors, which may be a consequence of the known assumptions of the method being violated. The uncertainties diagnosed in this study were calculated over a one-month period in winter 2017/2018, and the initial tests were conducted using a three-month period for the same winter. Using uncertainties that vary with latitude, height, and satellite identifier in an experiment for summer 2018 resulted in a much smaller increase in forecast skill than for the winter period. Therefore uncertainties were diagnosed that vary with quantities other than latitude. The most effective of these is to allow the observation uncertainties to vary with the average temperature between the Earth's surface and 20 km. Uncertainties that vary with this and with satellite identifier and height give good forecast skill improvements in both seasons.