Quantifying the Benefits of Altimetry Assimilation in Seasonal Forecasts of the Upper Ocean

Satellite altimetry measurements of sea surface height provide near-global ocean state observations on sub-monthly time scales, which are not always utilized by seasonal climate forecasting systems. As early as the mid-1990s, attempts were made to assimilate altimetry observations to initialize climate models. These experiments demonstrated improved ocean forecasting skill, especially compared to experiments that did not assimilate subsurface ocean temperature information. Nowadays, some operational climate forecasting models utilize altimetry in their assimilation systems, whereas others do not. Here, we assess the impact of altimetry assimilation on seasonal prediction skill of ocean variables in two climate forecasting systems that are from the European Centre for Medium-Range Weather Forecasts (SEAS5) and the Australian Bureau of Meteorology (ACCESS-S). We show that assimilating altimetry improves the initialization of subsurface ocean temperatures, as well as seasonal forecasts of monthly variability in upper-ocean heat content and sea level. Skill improvements are largest in the subtropics, where there are typically less subsurface ocean observations available to initialize the forecasts. In the tropics, there are no noticeable improvements in forecast skill. The positive impact of altimetry assimilation on forecast skill related to the subsurface ocean does not seem to affect predictions of sea surface temperature. Whether this is because current forecasting systems are close to the potential predictability limit for the ocean surface, or perhaps altimetry observations are not fully exploited, remains a question. In summary, we find that utilizing altimetry observations improves the overall global ocean forecasting skill, at least for upper-ocean heat content and sea level.