Sea level ECV quality assessment via global ocean model assimilation
Event: 2015 Ocean Surface Topography Science Team Meeting
Session: Quantifying Errors and Uncertainties in Altimetry data
Presentation type: Type Poster
Contribution: PDF file
We aim to quantify improvements in Sea Level (SL) data obtained through the ESA - Climate Change Initiative (cci) effort and to test the consistency of the Essential Climate Variable (ECV) of Sea Level (SL_ECV) with other ECVs through the assimilation process. For this purpose we assimilate SSH data jointly with in situ ocean data into the GECCO2 assimilation framework. Because the dynamically consistent ocean state estimation adjusts only uncertain model parameters to bring the model into consistency with ocean observations, improvements in data products can be investigated by studying the residuals between the different data products and the constrained model. With this approach and the assimilation of SL_ECV_V0 we are able to demonstrate that in many regions the SL_ECV has been improved from version V0 (AVISO product) to version V1 (SL_cci product). However, there are regions where SL_ECV_V1 is further away from the model "truth". In contrast we find clear improvements due to the updated improved data set SL_ECV_V1.1 for these comparisons. The improvement gets even more evident when using the changed model "truth" due to the assimilation of the improved data set SL_ECV_V1.1.