Bourassa, M. A., Zamudio, L., & O'Brien, J. J. (1999). Noninertial flow in NSCAT observations of Tehuantepec winds. J. Geophys. Res. , 104 (C5), 11311–11319.
Bourassa, M. A., Legler, D. M., & O'Brien, J. J. (1997). The use of significant wave height to improve the accuracy of wind derived stress and wave characteristics. 12th Symposium on Boundary Layers and Turbulence , , 291–292.
Bourassa, M. A., Legler, D. M., O'Brien, J. J., Stricherz, J. N., & Whalley, J. (1998). High temporal and spatial resolution animations of winds observed with the NSCAT scatterometer. In 14th International Conference on Interactive Information and Processing Systems for Meteorology, Oceanography, and Hydrology at 78th AMS Annual Meeting (pp. 556–559).
Bourassa, M. A., Smith, S. R., & O'Brien, J. J. (2002). Assimilation of scatterometer and in situ winds for regularly gridded products. In 6th Symposium on Integrated Observing Systems (pp. 161–165).
Bourassa, M. A., and P.J. Hughes. (2018). Surface Heat Fluxes and Wind Remote Sensing. In and J. Verron J. Tintoré A. Pascual E. P. Chassignet (Ed.), (pp. 245–270). Tallahassee, FL: GODAE OceanView.
Abstract: The exchange of heat and momentum through the air-sea surface are critical aspects of ocean forcing and ocean modeling. Over most of the global oceans, there are few in situ observations that can be used to estimate these fluxes. This chapter provides background on the calculation and application of air-sea fluxes, as well as the use of remote sensing to calculate these fluxes. Wind variability makes a large contribution to variability in surface fluxes, and the remote sensing of winds is relatively mature compared to the air sea differences in temperature and humidity, which are the other key variables. Therefore, the remote sensing of wind is presented in greater detail. These details enable the reader to understand how the improper use of satellite winds can result in regional and seasonal biases in fluxes, and how to calculate fluxes in a manner that removes these biases. Examples are given of high-resolution applications of fluxes, which are used to indicate the strengths and weakness of satellite-based calculations of ocean surface fluxes.
Bourassa, M. A., D. Dukhovskoy, S. L. Morey, and J, J. O'Brien. (2007). Innovations in Modeling Gulf of Mexico Surface Turbulent Fluxes. Flux News , (3), 9.
Bourassa, M. A., H. Bonekamp, P. Chang, D. Chelton, J. Courtney, R. Edson, J. Figa, Y. He, H. Hersbach, K. Hilburn, Z. Jelenak, T. Lee, W. T. Liu, D. Long, K. Kelly, R. Knabb, E. Lindstorm, W. Perrie, M. Portabella, M. Powell, E. Rodriguez, D. Smith, A. Stoffelen, V. Swail, F. Wentz. (2010). Remotely Sensed Winds and Wind Stresses for Marine Forecasting and Ocean Modeling. In D. D.E. and Stammer Harrison J. Hall (Ed.), Proceedings of OceanObs'09: Sustained Ocean Observations and Information for Society (Vol. 2).
Bourassa, M. A., R. N. Maue, S. R. Smith, P. J. Hughes, and J. Rolph. (2007). Global Winds: State of the Climate in 2006. Bulletin of the American Meteorological Society , 88 (6), 135.
Bourassa, M. A., S. T. Gille, and C. A. Clayson. (2010). Surface Fluxes: Challenges for High Latitudes: Workshop report from the U.S. CLIVAR High Latitudes Surface Flux Working Group. U.S. CLIVAR Variations , 8 (1), 7,14.
Cronin, M. F., Gentemann, C. L., Edson, J., Ueki, I., Bourassa, M., Brown, S., et al. (2019). Air-Sea Fluxes With a Focus on Heat and Momentum. Front. Mar. Sci. , 6 .
Abstract: Turbulent and radiative exchanges of heat between the ocean and atmosphere (hereafter heat fluxes), ocean surface wind stress, and state variables used to estimate them, are Essential Ocean Variables (EOVs) and Essential Climate Variables (ECVs) influencing weather and climate. This paper describes an observational strategy for producing 3-hourly, 25-km (and an aspirational goal of hourly at 10-km) heat flux and wind stress fields over the global, ice-free ocean with breakthrough 1-day random uncertainty of 15 W m–2 and a bias of less than 5 W m–2. At present this accuracy target is met only for OceanSITES reference station moorings and research vessels (RVs) that follow best practices. To meet these targets globally, in the next decade, satellite-based observations must be optimized for boundary layer measurements of air temperature, humidity, sea surface temperature, and ocean wind stress. In order to tune and validate these satellite measurements, a complementary global in situ flux array, built around an expanded OceanSITES network of time series reference station moorings, is also needed. The array would include 500–1000 measurement platforms, including autonomous surface vehicles, moored and drifting buoys, RVs, the existing OceanSITES network of 22 flux sites, and new OceanSITES expanded in 19 key regions. This array would be globally distributed, with 1–3 measurement platforms in each nominal 10° by 10° box. These improved moisture and temperature profiles and surface data, if assimilated into Numerical Weather Prediction (NWP) models, would lead to better representation of cloud formation processes, improving state variables and surface radiative and turbulent fluxes from these models. The in situ flux array provides globally distributed measurements and metrics for satellite algorithm development, product validation, and for improving satellite-based, NWP and blended flux products. In addition, some of these flux platforms will also measure direct turbulent fluxes, which can be used to improve algorithms for computation of air-sea exchange of heat and momentum in flux products and models. With these improved air-sea fluxes, the ocean’s influence on the atmosphere will be better quantified and lead to improved long-term weather forecasts, seasonal-interannual-decadal climate predictions, and regional climate projections.