## The Ocean
### SARAL/AltiKa a Data Into Operational Systems
#### 2.3.2. Assimilation of SLA Data in the Mercator Ocean System  
SARAL/AltiKa 35-day repeat orbit altimeter is well suited for the monitoring of mesoscale variability and to complement Jason-series observations (e.g., [16]). Its low noise level due to the use of Ka-band also allows a better resolution of along-track mesoscale signals [5]. SARAL/AltiKa thus provides essential altimeter observations for global ocean analysis and forecasting. The along track SARAL/AltiKa SLA observations has been successfully assimilated in the Mercator Ocean analysis and forecasting systems since 31 July 2013, only five months after the satellite launch. We analyse here its specific contribution in addition to other altimeters for global ocean analysis and forecasts. The new Copernicus global ocean system at \(1/12^{\circ}\) benefits from important improvements that lead to significant reduction of the analysis and forecast SLA errors. The observation errors for SST and SLA  
Figure 6: Relative contribution in percentage of each altimeter in the multi-mission NRT DUACS maps during the 2013–2017 period and link with altimeter events. The contribution is derived from the degrees of freedom of signal. The SARAL/AltiKa contribution is in blue, the plain curve corresponding to the repetitive period and the dotted curve to the drifting period.  
Figure 7: Relative increase in percentage of the number of point used to compute an Envisat/SARAL/AltiKa mean profile relatively to the previous a ERS-2/Envisat mean profile over: European Seas (**left**); and zooming over the Danish Straits (**right**).  
are now dynamically adjusted using an approach proposed by [17]. In 2015, SARAL/Altika diagnosed SLA observation errors have a global mean RMS of 3.6 cm, comparable to the Jason-2 error but lower than the one for HY-2A and CryoSat-2. This error estimate includes the mean dynamic topography, model representativity and processing error. The lower values are around 2 cm in the centre of the gyres but can reach more than 10 cm in high energetic regions, such as western boundary currents and the Antarctic circumpolar current.  
Observing System Evaluation (OSE) experiments, covering the year 2015, have been carried out with this new system to assess the impact of an increase number of altimeters. Figure 8 shows the relative reduction of the SSH forecast Mean Square Error (MSE) due to the assimilation of SARAL/AltiKa ; Cryosat-2, Jason-2 and HY-2A being already assimilated. The impact is significant and highly regionally dependent. Innovation (observation minus model forecast) statistics are computed with Cryosat-2, Jason-2 and HY-2A data. The normalized SLA error difference between the experiment without and with SARAL/AltiKa SLA assimilated reaches 40% at mid-latitudes, whereas, in the same OSE but with the global 1/4\({}^{\circ}\) system, it reaches only 25% (not shown). This could be interpreted as a need of a higher density of observation to constrain the smaller scales of the 1/12\({}^{\circ}\) ocean model compared to the 1/4\({}^{\circ}\) system. The assimilation of SARAL/AltiKa SLA allows a gain of 0.8 day to get the same level of forecast error but without SARAL/AltiKa. The comparison of the estimated surface velocity fields in the different OSEs with subsurface drifters also shows an improvement with the addition of SARAL/AltiKa, even if three altimeter data sets have already been assimilated.