@article {RN109,
	title = {Air-Sea Fluxes With a Focus on Heat and Momentum},
	journal = {Frontiers in Marine Science},
	volume = {6},
	year = {2019},
	pages = {430},
	type = {Journal Article},
	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{\textendash}2 and a bias of less than 5 W m{\textendash}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{\textendash}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{\textendash}3 measurement platforms in each nominal 10{\textdegree} by 10{\textdegree} 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{\textquoteright}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.},
	keywords = {air-sea heat flux, autonomous surface vehicle, ICOADS, latent heat flux, ocean wind stress, OceanSITES, satellite-based ocean monitoring system, surface radiation},
	issn = {2296-7745},
	doi = {10.3389/fmars.2019.00430},
	url = {https://www.frontiersin.org/article/10.3389/fmars.2019.00430},
	author = {Cronin, Meghan F. and Gentemann, Chelle L. and Edson, James and Ueki, Iwao and Bourassa, Mark and Brown, Shannon and Clayson, Carol Anne and Fairall, Chris W. and Farrar, J. Thomas and Gille, Sarah T. and Gulev, Sergey and Josey, Simon A. and Kato, Seiji and Katsumata, Masaki and Kent, Elizabeth and Krug, Marjolaine and Minnett, Peter J. and Parfitt, Rhys and Pinker, Rachel T. and Stackhouse, Paul W. and Swart, Sebastiaan and Tomita, Hiroyuki and Vandemark, Douglas and Weller, A. Robert and Yoneyama, Kunio and Yu, Lisan and Zhang, Dongxiao}
}
@article {RN28,
	title = {A regime-dependent retrieval algorithm for near-surface air temperature and specific humidity from multi-microwave sensors},
	journal = {Remote Sensing of Environment},
	volume = {215},
	year = {2018},
	pages = {199-216},
	type = {Journal Article},
	abstract = {Near-surface specific humidity (qa) and air temperature (Ta) over the global ocean are important meteorological variables, but they cannot be retrieved directly from remote sensing. Many efforts have been made to develop algorithms that derive qa and Ta from multisensor microwave and/or infrared observations using in situ measurements as training datasets. However, uncertainty remains large in the resultant qa and Ta retrievals. In this study, 147 moored surface buoys are used to examine how buoy measured qa and Ta are related to satellite microwave brightness temperature (Tb) on the spatial scale from the warm/humid tropics to the cold/dry high latitudes. It is found that the Tb {\textendash} qa and Tb {\textendash} Ta relations are structured along two distinct, near-linear bands, with the primary band in the warm/humid regime and a secondary (weaker) band in the cold/dry regime. The step-like transition (or separation) between the two regimes occurs at 8{\textendash}10 g kg-1 for qa and 14{\textendash}17 {\textdegree}C for Ta. The evidence suggests that one algorithm may not be sufficient to extract qa and Ta from Tb in all regimes. Therefore, a high-latitude enhancement is added to the global algorithm so that the qa and Ta retrievals in the dry/cold regime can be specifically addressed. The new algorithms are applied to 11 microwave sensors, including SSM/I, SSMIS, and AMSU-A, from 1988 to 2016. Based on the 475,717 buoy collocations during the 29-year period, the retrieved qa and Ta have root-mean-square differences of 0.82 g kg-1 and 0.51 {\textdegree}C, respectively.

},
	keywords = {Microwave passive sensors, Moored surface buoys, Multisensor retrieval, Near-surface air temperature and specific humidity, Retrieval algorithm},
	issn = {00344257},
	doi = {10.1016/j.rse.2018.06.001},
	url = {https://staging-ddpp.dimensions.ai/details/publication/pub.1104605412},
	author = {Yu, Lisan and Jin, Xiangze}
}
