Satellite microwave sensors, both active scatterometers and passive radiometers, have been systematically measuring near-surface ocean winds for nearly 40 years, establishing an important legacy in studying and monitoring weather and climate variability. As an aid to such activities, the various wind datasets are being intercalibrated and merged into consistent climate data records (CDRs). The ocean wind CDRs (OW-CDRs) are evaluated by comparisons with ocean buoys and intercomparisons among the different satellite sensors and among the different data providers. Extending the OW-CDR into the future requires exploiting all available datasets, such as OSCAT-2 scheduled to launch in July 2016. Three planned methods of calibrating the OSCAT-2 σ _o measurements include 1) direct Ku-band σ _o intercalibration to QuikSCAT and RapidScat; 2) multisensor wind speed intercalibration; and 3) calibration to stable rainforest targets. Unfortunately, RapidScat failed in August 2016 and cannot be used to directly calibrate OSCAT-2. A particular future continuity concern is the absence of scheduled new or continuation radiometer missions capable of measuring wind speed. Specialized model assimilations provide 30-year long high temporal/spatial resolution wind vector grids that composite the satellite wind information from OW-CDRs of multiple satellites viewing the Earth at different local times.

Monitoring the cold and productive waters of the Gulf of Maine and their interactions with the nearby northwestern (NW) Atlantic shelf is important but challenging. Although remotely sensed sea surface temperature (SST), ocean color, and sea level have become routine, much of the water exchange physics is reflected in salinity fields. The recent invention of satellite salinity sensors, including the Soil Moisture Active Passive (SMAP) radiometer, opens new prospects in regional shelf studies. However, local sea surface salinity (SSS) retrieval is challenging due to both cold SST limiting salinity sensor sensitivity and proximity to land. For the NW Atlantic, our analysis shows that SMAP SSS is subject to an SST-dependent bias that is negative and amplifies in winter and early spring due to the SST-related drop in SMAP sensor sensitivity. On top of that, SMAP SSS is subject to a land contamination bias. The latter bias becomes noticeable and negative when the antenna land contamination factor (LC) exceeds 0.2%, and attains maximum negative values at LC = 0.4%. Coastward of LC = 0.5%, a significant positive land contamination bias in absolute SMAP SSS is evident. SST and land contamination bias components are seasonally dependent due to seasonal changes in SST/winds and terrestrial microwave properties. Fortunately, it is shown that SSS anomalies computed relative to a satellite SSS climatology can effectively remove such seasonal biases along with the real seasonal cycle. SMAP monthly SSS anomalies have sufficient accuracy and applicability to extend nearer to the coasts. They are used to examine the Gulf of Maine water inflow, which displayed important water intrusions in between Georges Banks and Nova Scotia in the winters of 2016/17 and 2017/18. Water intrusion patterns observed by SMAP are generally consistent with independent measurements from the European Soil Moisture Ocean Salinity (SMOS) mission. Circulation dynamics related to the 2016/2017 period and enhanced wind-driven Scotian Shelf transport into the Gulf of Maine are discussed.

Estuaries may be uniquely susceptible to the combined acidification pressures of atmospherically driven ocean acidification (OA), biologically driven CO₂ inputs from the estuary itself, and terrestrially derived freshwater inputs. This study utilized continuous measurements of total alkalinity (TA) and the partial pressure of carbon dioxide (pCO₂) from the mouth of Great Bay, a temperate northeastern U.S. estuary, to examine the potential influences of endmember mixing and biogeochemical transformation upon estuary buffering capacity (β–H). Observations were collected hourly over 28 months representing all seasons between May 2016 and December 2019. Results indicated that endmember mixing explained most of the observed variability in TA and dissolved inorganic carbon (DIC), concentrations of which varied strongly with season. For much of the year, mixing dictated the relative proportions of salinity‐normalized TA and DIC as well, but a fall season shift in these proportions indicated that aerobic respiration was observed, which would decrease β–H by decreasing TA and increasing DIC. However, fall was also the season of weakest statistical correspondence between salinity and both TA and DIC, as well as the overall highest salinity, TA and β–H. Potential biogeochemically driven β–H decreases were overshadowed by increased buffering capacity supplied by coastal ocean water. A simple modeling exercise showed that mixing processes controlled most monthly changes in TA and DIC, obscuring impacts from air–sea exchange or metabolic processes. Advective mixing contributions may be as important as biogeochemically driven changes to observe when evaluating local estuarine and coastal OA.

Radar scattering from ocean surfaces is investigated by 3-D numerical solution of Maxwell's equations [numerical Maxwell's model in 3-D (NMM3D)] using the ocean surface profiles stochastically generated from a 3-D Durden-Vesecky ocean spectrum. The surface integral equations (SIEs) are formulated for dielectric surfaces using Green's functions of the air and the ocean permittivities with the surface tangential electric and magnetic fields as the unknowns. In solving the SIEs using the method of moment, a fast matrix solver of the sparse matrix canonical grid is used in conjunction with Rao-Wilton-Glisson basis functions. The computation has been implemented on a high-performance parallel computing cluster for problems with up to six million surface unknowns. Unlike the two-scale model (TSM) approximation, NMM3D does not require division of the surface spectrum into large- and small-scale ocean waves. The results of backscattering simulations are compared to Aquarius satellite radar measurements for wind speeds of 5, 8, and 10 m/s and for incidence angles of 29°, 39°, and 46°. The results show that NMM3D ocean backscattering solutions at L-band are in good agreement with Aquarius satellite radar data for co-polarized VV, HH, and cross-polarized VH returns as well as for the VV/HH ratio. The azimuthal dependence of L-band backscatter is also assessed. Finally, NMM3D results are compared to TSM solutions and are shown to lie close to Aquarius data in observed VV/HH ratio, and their azimuthal dependencies.