Impact of Atmospheric and Model Physics Perturbations on a High‐Resolution Ensemble Data Assimilation System of the Red Sea

Abstract

AbstractThe Ensemble Adjustment Kalman Filter of the Data Assimilation Research Testbed is implemented to assimilate observations of satellite sea surface temperature, altimeter sea surface height, and in situ ocean temperature and salinity profiles into an eddy‐resolving 4 km Massachusetts Institute of Technology general circulation model of the Red Sea. We investigate the impact of three different ensemble generation strategies: (1) Iexp—uses ensemble of ocean states to initialize the model on 1 January 2011 and inflates filter error covariance by 10%; (2) IAexp—adds ensemble of atmospheric forcing to Iexp; and (3) IAPexp—adds perturbed model physics to IAexp. The assimilation experiments are run for 1 year, starting from the same initial ensemble and assimilating data every 3 days.Results demonstrate that the Iexp mainly improved the model outputs with respect to assimilation‐free Massachusetts Institute of Technology general circulation model run in the first few months, before showing signs of dynamical imbalances in the ocean estimates, particularly in the data‐sparse subsurface layers. The IAexp yielded substantial improvements throughout the assimilation period with almost no signs of imbalances, including the subsurface layers. It further well preserved the model mesoscale features resulting in an improved forecast for eddies, both in terms of intensity and location. Perturbing model physics in IAPexp slightly improved the forecast statistics and also the placement of basin‐scale eddies. Increasing hydrographic coverage further improved the results of IAPexp compared to IAexp in the subsurface layers. Switching off multiplicative inflation in IAexp and IAPexp leads to further improvements, especially in the subsurface layers.