Heat Flux Estimates From a Synthesis of Satellite Observations and a Hydrodynamic Model (With Application to Long Island Sound)

Estimating surface heat fluxes via direct covariance measurements or bulk formulae is observation-intensive and costly. We present a methodology whereby we estimate net surface heat fluxes as the difference between the depth-integrated heat tendencies and the depth-integrated horizontal heat exchanges in a hydrodynamic model. We calibrate the model to achieve a good representation of mixing and advection and then assimilate satellite sea surface temperature (SST) observations into the model at an 8-day scale. The SST data assimilation forces a good representation of observed temperatures and heat tendencies both at the surface and throughout the water column. We estimate the horizontal heat exchange directly from the model output and then infer the surface fluxes required to close the budget. When we apply this methodology to a model with prescribed surface heat fluxes and without data assimilation, we can recover the prescribed fluxes with an RMS error of & PLUSMN;10 W m(-2) and an r(2) of 0.998. When we compare our results to those estimated using Coupled Ocean-Atmosphere Response Experiment bulk formulae with observations in western Long Island Sound, we find similarly good agreement.