Impact of Assimilating Simulated Surface Velocity from a Wide Swath Satellite
Scott R Smith1, Robert William Helber2, John Osborne1, Joseph Matthew D'Addezio2, Matthew Carrier2, Innocent Souopgui3, Alexis LaRosa4, Charlie N. Barron5 and Gregg A. Jacobs6, (1)U.S. Naval Research Laboratory, Stennis Space Center, United States, (2)U.S. Naval Research Laboratory, Ocean Dynamics and Prediction, Stennis Space Center, United States, (3)University of Southern Mississippi, Department of Marine Science, Slidell, LA, United States, (4)Science & Engineering Apprenticeship Program, Stennis Space Center, MS, United States, (5)Naval Research Laboratory, Ocean Sciences Division, Stennis Space Center, MS, United States, (6)US Naval Research Laboratory, Ocean Sciences Division, Stennis Space Center, MS, United States
Abstract:
Results from a set of Observing System Simulation Experiments (OSSE) demonstrate forecasting skill from assimilating surface velocity observations in the North Arabian Sea using the Navy Coupled Ocean Data Assimilation (NCODA) system in 3D-variational mode (3DVAR). NCODA/3DVAR is one of the primary tools that the Navy uses operationally to ingest, process, and assimilate ocean observations in near-real time, and is used in several different operational ocean prediction systems. Two NCODA/3DVAR deficiencies, however, are: 1) SSH observations have to be assimilated indirectly via synthetic temperature and salinity profiles, and 2) the inability to assimilate velocity observations properly. NCODA/3DVAR lacks the mechanism to correlate velocities with temperature and salinity, which is required for dynamically consistent and stable velocity and direct SSH assimilation.
This presentation describes a new version of NCODA/3DVAR developed with a covariance database constructed using historical ocean observations, and implemented to cross-correlate velocity observation with temperature and salinity throughout the water column producing dynamically consistent analyses. We evaluate this new system using OSSEs with velocity observations sampled from a Nature run in a wide swath pattern as if from one of the proposed velocity observing satellites: SKIM or WaCM. These velocity observations are assimilated into a different model run and then compared to the Nature run. In order to demonstrate the added value of having wide swath surface velocity observations in our prediction system, these results are compared with a similar OSSE assimilating SSH observations from the same wide swath pattern using the current method of synthetics.
