CoAuthors

Marcello Passaro (DGFI-TUM, Germany); Denise Dettmering (DGFI-TUM, Germany)

Gridded maps of Sea Level Anomalies (SLA) are crucial tools for physical oceanographers, allowing for detailed descriptions of the spatial characteristics of the ocean surface. Several approaches exist to creating these gridded maps, and increasing focus is being placed on improving these maps and the scales of the processes seen within. The coastal and shelf regions are particularly interesting, which are greatly influenced by auxiliary processes such as winds and waves. 

Our study investigates the combination of altimetry-based SLA with other variables, such as SST and wind data, to provide an alternative way of producing gridded SLA fields. This study aims to fill the need for more high-frequency content in the gridded altimetry-based SLA data, mainly focusing on the coastal and shelf regions, where this is increasingly important in understanding ocean processes.
We present a gridding approach that combines wind and SST data from remote sensing within processing SLA from level L3 to L4.
 
This study uses datasets of altimetry-based SLA from the European Union’s Earth observation program CMEMS (Copernicus Marine Service) provided as along-track (L3) and gridded data (L4). We compare our gridded SLA data against the CMEMS L4 data in daily resolution on a 0.25° x 0.25° grid. For the in-use gridded CMEMS data, we could highlight the lack of variability of SLA on the Southwestern Atlantic Continental shelf for high-frequency processes and their connection to along-shore wind. We further use daily GESLA-3 tide gauge data to validate the newly gained data set. With this, we will show the potential of a new gridding method using Co-variables and discuss the impact of these Co-variables on the mesoscale and submesoscale scales of daily SLA maps in the shelf and coastal regions.