The Impact of MetOp and Other Satellite Data within the Met Office Global NWP System Using an Adjoint-Based Sensitivity Method

Abstract The role of observations in reducing 24-h forecast errors is evaluated using the adjoint-based forecast sensitivity to observations (FSO) method developed within the Met Office global numerical weather prediction (NWP) system. The impacts of various subsets of observations are compared, with emphasis on space-based observations, particularly those from instruments on board the European Organisation for the Exploitation of Meteorological Satellites Meteorological Operational-A (MetOp-A) platform. Satellite data are found to account for 64% of the short-range global forecast error reduction, with the remaining 36% coming from the assimilation of surface-based observation types. MetOp-A data are measured as having the largest impact of any individual satellite platform (about 25% of the total impact on global forecast error reduction). Their large impact, compared to that of NOAA satellites, is mainly due to MetOp's additional sensors [Infrared Atmospheric Sounding Interferometer (IASI), Global Navigation Satellite System (GNSS) Receiver for Atmospheric Sounding (GRAS), and the Advanced Scatterometer (ASCAT)]. Microwave and hyperspectral infrared sounding techniques are found to give the largest total impacts. However, the GPS radio occultation technique is measured as having the largest mean impact per profile of observations among satellite types. This study demonstrates how the FSO technique can be used to assess the impact of individual satellite data types in NWP. The calculated impacts can be used to guide improvements in the use of currently available data and to contribute to discussions on the evolution of future observing systems.