Assessing the potential impact of assimilating total surface current velocities in the Met Office’s global ocean forecasting system

Representing and forecasting global ocean velocities is challenging. Velocity observations are scarce and sparse, and are rarely assimilated in a global ocean configuration. Recently, different satellite mission candidates have been proposed to provide surface velocity measurements. To assess the impact of assimilating such data, Observing System Simulation Experiments (OSSEs) have been run in the Mercator Ocean International analysis and forecasting global 1/4° system. Results show that assimilating simulated satellite surface velocities in addition to classical observations has a positive impact on the predicted currents at the surface and below to some extent. Compared to an experiment that assimilates only the classical observations, the surface velocity root-mean-squared error (RMSE) is reduced, especially in the Tropics. From a certain depth depending on the region (e.g. 200 m in the Tropics) however, slight degradations can be spotted. Temperature and salinity RMSEs are generally slightly degraded except in the Tropics where there is a small improvement at the surface and sub-surface. Sea surface height results are mixed, with some areas having reduced RMSE and some increased. The OSSEs reported here constitute a first study and aim to provide first insights on the features that improve by assimilating surface velocity data, and those which need to be worked on.

Impact of assimilating satellite surface velocity observations in the Mercator Ocean International analysis and forecasting global 1/4° system

Mirouze,

Rémy,

Lellouche

et al. 2024

Assessing the potential impact of assimilating total surface current velocities in the Met Office’s global ocean forecasting system

Waters,

Martin,

Bell

et al. 2024

Accurate prediction of ocean surface currents is important for marine safety, ship routing, tracking of pollutants and in coupled forecasting. Presently, velocity observations are not routinely assimilated in global ocean forecasting systems, largely due to the sparsity of the observation network. Several satellite missions are now being proposed with the capability to measure Total Surface Current Velocities (TSCV). If successful, these would substantially increase the coverage of ocean current observations and could improve accuracy of ocean current forecasts through data assimilation. In this paper, Observing System Simulation Experiments (OSSEs) are used to assess the impact of assimilating TSCV in the Met Office’s global ocean forecasting system. Synthetic observations are generated from a high-resolution model run for all standard observation types (sea surface temperature, profiles of temperature and salinity, sea level anomaly and sea ice concentration) as well as TSCV observations from a Sea surface KInematics Multiscale monitoring (SKIM) like satellite. The assimilation of SKIM like TSCV observations is tested over an 11 month period. Preliminary experiments assimilating idealised single TSCV observations demonstrate that ageostrophic velocity corrections are not well retained in the model. We propose a method for improving ageostrophic currents through TSCV assimilation by initialising Near Inertial Oscillations with a rotated incremental analysis update (IAU) scheme. The OSSEs show that TSCV assimilation has the potential to significantly improve the prediction of velocities, particularly in the Western Boundary Currents, Antarctic Circumpolar Current and in the near surface equatorial currents. For global surface velocity the analysis root-mean-square-errors (RMSEs) are reduced by 23% and there is a 4-day gain in forecast RMSE. There are some degradations to the subsurface in the tropics, generally in regions with complex vertical salinity structures. However, outside of the tropics, improvements are seen to velocities throughout the water column. Globally there are also improvements to temperature and sea surface height when TSCV are assimilated. The TSCV assimilation largely corrects the geostrophic ocean currents, but results using the rotated IAU method show that the energy at inertial frequencies can be improved with this method. Overall, the experiments demonstrate significant potential benefit of assimilating TSCV observations in a global ocean forecasting system.

The impact of simulated total surface current velocity observations on operational ocean forecasting and requirements for future satellite missions

Waters,

Martin,

Mirouze

et al. 2024

Operational forecasts rely on accurate and timely observations and it is important that the ocean forecasting community demonstrates the impact of those observations to the observing community and its funders while providing feedback on requirements for the design of the ocean observing system. One way in which impact of new observations can be assessed is through Observing System Simulation Experiments (OSSEs). Various satellite missions are being proposed to measure Total Surface Current Velocities (TSCV). This study uses OSSEs to assess the potential impact of assimilating TSCV observations. OSSEs have been performed using two global ocean forecasting systems; the Met Office’s (MetO) Forecasting Ocean Assimilation Model and the Mercator Ocean International (MOI) system. Developments to the individual systems, the design of the experiments and results have been described in two companion papers. This paper provides an intercomparison of the OSSEs results from the two systems. We show that global near surface velocity analysis root-mean-squared-errors (RMSE) are reduced by 20-30% and 10-15% in the MetO and MOI systems respectively, we also demonstrate that the percentage of particles forecast to be within 50 km of the true particle locations after drifting for 6 days has increased by 9%/7%. Furthermore, we show that the global subsurface velocities are improved down to 1500m in the MetO system and down to 400m in the MOI system. There are some regions where TSCV assimilation degrades the results, notably the middle of the gyres in the MetO system and at depth in the MOI system. Further tuning of the background and observation error covariances are required to improve performance in these regions. We also provide some recommendations on TSCV observation requirements for future satellite missions. We recommend that at least 80% of the ocean surface is observed in less than 4 to 5 days with a horizontal resolution of 20 to 50 km. Observations should be provided within one day of measurement time to allow real time assimilation and should have an accuracy of 10 cm/s in the along and across track direction and uncertainty estimates should be provided with each measurement.