VarDyn: Dynamical joint-reconstructions of Sea Surface Height and
Temperature from multi-sensor satellite observations
Abstract
Here, the use of an hybrid methodology, VarDyn, combining minimal
physically-based constraints with a variational scheme, is demonstrated
to improve mapping capabilities of sea surface height (SSH) and
temperature (SST). Synthesizing multi-modal satellite observations,
VarDyn improves the accuracy of SSH and SST maps compared to operational
products, both in terms of RMSE and effective spatial resolution.
Expected, most improvements occur in high energetic ocean regions.
Still, the accuracy of SSH maps also slightly improves in low energetic
regions, which is a clear improvement compared to other methods. VarDyn
SSH fields and associated geostrophic velocities further reveal strong
agreements with newly available high-resolution instantaneous SWOT
estimates. Remarkably, the assimilation of SST especially benefits SSH
reconstruction when only 2 altimeters are available. The VarDyn method
thus opens robust means to refine climate SSH records, jointly
assimilating SSH from 2 altimeters and SST from microwave sensors.