Numerical Improvements in the Exchange of Heat and Momentum at the Atmosphere-Ocean Interface

The NASA Salinity Processes in the Upper Ocean Regional Study (SPURS) was conducted over the sub-tropical North Atlantic Ocean from September 2012 to October 2013. One of the primary goals of the field campaign was to gain a better understanding of the processes modulating Sea Surface Salinity (SSS) in an attempt to close the freshwater budget over the domain using oceanic and atmospheric observations. The program supported 3-D oceanographic salinity, temperature and velocity structure measurements using multiple observational platforms, including a surface mooring, research vessels, and autonomous vehicles. These in-situ measurements only recorded measurements over a subset of the domain. Consequently, spatial variations in the physical processes, such as evaporative fluxes, were not captured.

As a solution, the Weather Research and Forecasting model (WRF) was used to resolve the spatial variations in surface fluxes over the larger domain including regions lacking observations. Initially, an ensemble of numerical simulations were performed to identify the surface physics and boundary layer schemes that produced the most realistic surface fluxes when compared to observations. Each ensemble member was run over the temporal length of the SPURS campaign, from September 16 – October 30 2012, using multiple 36-h simulations initialized daily though the extended time period. For the latent heat flux (LHF), all ensemble members produced an overestimation compared to both the bulk fluxes and direct covariance measurements (mean model bias +39 W/m^2). The Mellor-Yamada Nakanishi and Niino (MYNN) surface physics parameterization in conjunction with the MYNN2.5 boundary layer scheme produced the smallest root mean square error.

Subsequently, the MYNN surface physics module was then improved using a bulk surface flux algorithm for the exchange of heat and momentum developed during the Coupled Ocean-Atmosphere Response Experiment (COARE3.5; Edson et al. 2013), and validated with observations gathered during SPURS. These modifications reduced the WRF model bias, making it useful tool for analyzing and understanding spatial variations in surface fluxes over the domain, as well as the contributions of surface fluxes to the regional fresh water budget.