The Gulf of Maine (GoM) hosts a variety of fish and sea mammals, beaches, and active commercial fishery. Understanding, monitoring, and predicting the status of and future changes in its food web and water quality are key goals of an ocean observing system that utilizes in situ buoys, gliders, shipboard surveys, satellite remote sensing, and numerical modeling. This study defines and explores the utility of a new Gulf-specific water mass exchange predictor designed to capture changes in winter inflow of fresh and cold waters from the upstream Scotian Shelf using soil moisture active passive satellite sea surface salinity (SSS) in the eastern GoM. A data assimilative ocean circulation model is used to characterize and assess results. GoM food web dynamics and water quality both depend on lower trophic productivity associated with Gulf-wide phytoplankton and zooplankton communities, and these are fundamentally controlled by water temperature and inorganic nutrients that often change due to varied exchange with the adjoining offshore North Atlantic and upstream Nova Scotian Shelf Water (SSW) that flows around southwestern Nova Scotia. Once in the Gulf, most of the SSW inflow to the eastern GoM is advected along southwestern Nova Scotia. This eastern GoM area (termed eGoM) is a useful gauge area where SSS reflects variations in SSW inflow. Results indicate that the SMAP-derived winter eGoM salinity index can help explain interannual variability in GoM conditions during the ensuing spring to summer, the seasons influenced by several advective pathways, as discussed in the study.

The Regional Ocean Modeling System (ROMS) 4-dimensional variational (4D-Var) data assimilation platform has been extended to include nested grid configurations using both one-way and two-way nesting strategies. The efficacy of this new ROMS utility is demonstrated in a model comprising three nested grids with horizontal refinement and configured for the Mid-Atlantic Bight. The three nested grids have a horizontal resolution ranging from ∼7 km to ∼0.8 km thereby capturing circulation regimes that span the Gulf Stream western boundary current, through the mesoscale eddy field, and down to the rapidly evolving and energetic submesoscale. These circulation regimes represent a challenge for any data assimilation system, and the nested 4D-Var system was found to perform well across the range of resolved space and time scales. The observational data used to constrain the ocean state estimates come from a wide range of remote sensing, in situ, and mobile platforms, along with the U.S. National Science Foundation's Ocean Observatories Initiative Pioneer Array. Several aspects of the system performance are explored and described here, including the fit of the model to the observations, the influence of data assimilation on the wave number spectra at the submesoscale, and the downscaling and upscaling of information captured by the observations.

A 15-year reanalysis (2007-2021) of circulation in the coastal ocean and adjacent deep sea of the northeast U.S. continental shelf is described. The analysis uses the Regional Ocean Modeling System (ROMS) and fourdimensional variational (4D-Var) data assimilation (DA) of observations from in situ platforms, coastal radars, and satellites. The reanalysis downscales open boundary information from the Copernicus Marine Environmental Monitoring Service (CMEMS) global analysis. The dynamic model is forced by regional meteorological analyses, observed daily river discharges, and harmonic tides that augment the open boundary conditions. A complementary analysis of the mean seasonal cycle of regional circulation, also computed using ROMS 4DVar but with climatological mean observations and forcing, is used to reduce biases in the CMEMS boundary data and to provide a dynamically and kinematically constrained Mean Dynamic Topography to use in conjunction with the assimilation of satellite altimeter sea level anomaly observations. The configuration of ROMS 4D-Var used is described, presenting details of the comprehensive suite of observations assembled, data pre-processing and quality control procedures, and background and observation error hypotheses. Control variables of the DA are the initial conditions, surface forcing, and boundary conditions of a sequence of non-overlapping 3-day analysis cycles. Comparisons to a non-assimilative version of the same ROMS model configuration show the added skill brought by assimilation of local observations. The improvement that downscaling with assimilation achieves over ocean state estimates from CMEMS and the U.S. Naval Research Laboratory Global Ocean Forecast System (GOFS) is demonstrated by the reduction in residuals of the DA, and by comparison to independent (unassimilated) observations. Wherever data volumes allow, skill assessments are made with the respect to anomalies from the mean seasonal cycle to emphasize performance at the ocean mesoscale. To highlight the utility of the analysis to inform studies related to coastal sea level variability and marine ecosystems, comparisons are made to unassimilated coastal sea level gauges and novel observations from sensors on fishing gear. The assimilation of coastal satellite altimetry data produces coastal sea level results that are coherent with observations across all time scales from interannual to tidal, while bias and correlation metrics show that bottom temperatures in regions of commercial fishing activity in the Mid-Atlantic Bight and the Gulf of Maine are modeled well.

The efficacy of an ocean observing, analysis, and forecasting system for the Mid-Atlantic Bight and the Gulf of Maine is explored using the concept of array modes. The analysis-forecast system is based on a triply nested configuration of the Regional Ocean Modeling System (ROMS) in conjunction with 4-dimensional variational (4D-Var) data assimilation. The array modes identify the degrees of freedom (df) of the signal and of the noise resolved by the observations, and are used here to quantify the extent to which the existing network of platforms and instruments are able to observe the ocean across different dynamical regimes ranging from quasi-geostrophic through the mesoscale and down to the sub-mesoscale. The ocean observing system includes the U.S. National Science Foundation’s Ocean Observatories Initiative Pioneer Array. In general, it is found that the df of the signal are largely associated with in situ observations from the Pioneer Array. On the other hand, a combination of satellite remote sensing and in situ observations potentially contribute to the df of the noise associated with uncertainties in the measurements. The array modes also provide information about the reduction in the expected analysis and forecast error covariance due to assimilating the observations. Here too observations from the Pioneer Array are found to significantly influence the veracity of the analyses and forecasts, and the circulation is instrumental in propagating observational information to other parts of the model domain. An approach is presented in which the array modes are used to quantify the impact of data assimilation on the expected forecast error covariance of forecasts initialized from the 4D-Var ocean state estimates. The advantage of this approach over others in common use is that it is independent of forecast error norm and circumvents the need for generating potentially large and costly ensembles.

The Regional Ocean Modeling System (ROMS) 4-dimensional variational (4D-Var) data assimilation system was used to compute ocean state estimates of the Mid-Atlantic Bight (MAB). A three-level nested grid configuration was employed with horizontal resolution successively enhanced from 7 km down to 800 m at the innermost nest. This captures the dynamics on space- and time-scales ranging from the Gulf Stream western boundary current down to the rapidly evolving and energetic sub-mesoscale circulation. This is a companion study to Levin a al. (2020) which examined the overall impacts of the entire observing system on shelf-break exchange. This follow-on study specifically focuses on the impact of the in situ elements of the ocean observing system on the 4D-Var analyses. The particular focus here is on the Pioneer Array, a high-density observing system in the MAB designed to measure the mull-scale nature of shelf-break exchange processes. Building on Levin a al. (2020), it is found that the relative impact of observations from different components of the Pioneer Array depends on the scales of motion that are resolved by each nested grid. This is in apparent agreement with the linear theory of geostrophic adjustment despite the 0(1) Rossby number. The synergy between the observations from different observing platforms has also been quantified by comparing the observation impacts with the sensitivity of the 4D-Var analyses to changes in the observing array. It is found that while some observations do not have a significant direct impact on the analyses, they nevertheless provide essential information about the presence of circulation features, corroborating that measured by other sensors. Thus, the individual parts of the observing system can borrow strength from each other. Finally, the contribution of each component of the observing system to the expected error in the 4D-Var analyses was also quantified, where the critical role played by the Pioneer Array moorings in resolving the sub-mesoscale circulation is again highlighted.

Wintertime freshwater transport into the Gulf of Maine (GoM) is typically controlled by a seasonal velocity increase in the fresh upstream Nova Scotia Current (NSC). Repeat satellite observations from the Soil Moisture Active Passive mission have mapped significant GoM surface salinity anomalies in four of five recent winters. These satellite data are used in combination with Jordan basin buoy and model datasets to investigate the likelihood that variable wind-forcing of the NSC contributed to these anomalies. This stems from regional ocean circulation studies suggesting that strengthening of alongshore southwesterly winds on the Scotian shelf weakens NSC transport into the GoM, while cross-shore southeasterly winds may also contribute to NSC weakening, and vice versa. A 17-year time series analysis of GoM buoy and satellite data shows that near-surface salinity in the eastern GoM can indeed be modulated by both alongshore and cross-shore winds through their impact on the NSC. The NSC geostrophic current modulation correlates with buoy-observed surface salinity anomalies when using a one month advective lead time. For a shorter 5-year period, a SMAP-derived salinity anomaly index in the eastern GoM indicates a similar relation to NSC variation and also correlates with Scotian Shelf wind anomalies. The relationships between winter wind and NSC transport variability are confirmed using output from a 19-year high resolution global ocean simulation. Attribution of these local wind anomalies to basin-scale atmospheric patterns shows that most years with strong winter GoM freshening coincide with weakening of a North Atlantic Oscillation-like wind pattern. But its reversals do not always correspond with a saline GoM. This contrast suggests that wind forcing more directly controls fresh winter GoM anomalies but not salty. Instead, they are partly due to density-driven advection from neighboring warm and saline Atlantic slope water including episodic Gulf Stream instabilities.

This paper explores the impact of the individual components of a coastal ocean observing system on estimates of the circulation derived from a state-of-the-art analysis and forecast system for the Mid-Atlantic Bight and Gulf of Maine. The foundation of these activities is the Regional Ocean Modeling System 4-dimensional variational (4D-Var) data assimilation platform, which is run in support of the Mid-Atlantic Regional Association Coastal Ocean Observing System as part of the U.S. Integrated Ocean Observing System. The specific focus of this study is on the impact of remote sensing observations from both space- and land-based platforms on estimates of cross-shelf transport in the vicinity of the National Science Foundation Ocean Observatories Initiative Pioneer array. Sea surface temperature (SST) and sea surface height (SSH) were found to have, on average, a similar impact on the transport estimates. However, during a typical 3-day 4D-Var assimilation cycle, approximately two orders of magnitude more observations of SST than SSH are used in the model, and closer analysis shows that each altimeter measurement has approximately 50 times more impact on the transport estimates than an individual SST observation. This highlights the value of altimetry data for ocean state estimation, and the significance of expanding the altimeter constellation. The observations that are most impactful of all are in situ measurements of temperature and salinity, which have typically 3–4 times more impact than an individual SSH datum. A robust geographical distribution of the observation impacts emerges across a range of transport metrics which results from the combined influence of space-time dynamical interpolation and error covariance information within the 4D-Var system. The observation impact calculations suggest that High Frequency (HF) radar estimates of surface currents have relatively little direct influence on cross-shelf transport estimates. However, quantification of the sensitivity of these same estimates to changes in the observing system indicate that HF radar observations indirectly provide important information. This is understood in the current system by appealing to the idea of borrowing strength from the field of statistics in which some observations (satellite remote sensing in the case considered here) can borrow strength from other, seemingly less important observations.

We describe “Doppio”, a ROMS-based (Regional Ocean Modeling System) model of the Mid-Atlantic Bight and Gulf of Maine regions of the northwestern North Atlantic developed in anticipation of future applications to biogeochemical cycling, ecosystems, estuarine downscaling, and near-real-time forecasting. This free-running regional model is introduced with circulation simulations covering 2007– 2017. The ROMS configuration choices for the model are detailed, and the forcing and boundary data choices are described and explained. A comprehensive observational data set is compiled for skill assessment from satellites and in situ observations from regional associations of the U.S. Integrated Ocean Observing Systems, including moorings, autonomous gliders, profiling floats, surface-current-measuring coastal radar, and fishing fleet sensors. Doppio’s performance is evaluated with respect to these observations by representation of subregional temperature and salinity error statistics, as well as velocity and sea level coherence spectra. Model circulation for the Mid-Atlantic Bight and Gulf of Maine is visualized alongside the mean dynamic topography to convey the model’s capabilities.

A nested configuration of the Regional Ocean Modeling System (ROMS) comprising three grids was used in conjunction with a 4-dimensional variational (4D-Var) data assimilation system to compute ocean state estimates of the Mid-Atlantic Bight (MAB). The three nested grids have a horizontal resolution ranging from ∼7 km to ∼0.8 km and capture circulation regimes that span the Gulf Stream western boundary current, through the mesoscale eddy field, and down to the rapidly evolving and energetic sub-mesoscale. All of these circulation regimes are challenging for any data assimilation system, yet the 4D-Var system was found to perform well across this range of space- and time-scales. The observational data used to constrain the ocean state estimates comes from a wide range of remote sensing, in situ, and mobile platforms. An adjoint-based procedure was used to compute the impact of each observing platform on several different indexes that describe the position of the MAB front, stratification, and associated cross-shelf exchange processes in the vicinity of the U.S. National Science Foundation’s Ocean Observatories Initiative Pioneer Array. The impact of observations from each observing platform on the chosen indexes varies across the three grids. It is a function of several factors that include the nature of the background circulation and the level of error assumed for the background ocean state and the observations. The geographic distribution of the observation impacts is remarkably robust across the various indexes and the three grids. In addition, observations that are both local to and remote from the target regions that define each index can exert a significant influence on the circulation. Variations in the observation impacts through time can be used to identify observations that exert unexpectedly large influence on the 4D-Var analyses (i.e, outliers), and routine monitoring of observation impacts is a useful indicator of the efficacy of different components of the observing system. Also, the observation impacts were found to be a useful performance indicator for the data assimilation system.

Satellite salinity from the Soil Moisture Active Passive (SMAP) mission and in situ observations are used to diagnose the source of a significant increase in warm and salty surface water entering the Gulf of Maine (GoM) in the winter of 2017-2018. SMAP salinity anomaly data indicate that this event was related to a salty feature that moved along the northwestern Atlantic shelf break from near the Grand Banks southwest towards the GoM over eight months before entering the Gulf in December 2017 to January 2018. Satellite altimetry, sea surface salinity, and sea surface temperature data suggest that, before entering the GoM, the salty feature interacted with Gulf Stream meanders and eddies several times, helping to sustain the water mass. It is likely that feature interactions with a warm Gulf Stream meander took place in the fall of 2017, helping to advect high salinity water onto the shelf and then into the GoM as a surface trapped feature in late fall 2017. According to satellite salinity data, this episode led to significant salinification (about 1 psu) in the northeastern GoM. Interior GoM buoy salinity data agree in showing four months of increased GoM salinity of the upper 50 m starting in November 2017. Buoy T/S analyses characterize this surface inflow as modified warm Atlantic slope water, typically seen only below 100 m and previously unobserved at the surface in the 15-year buoy record. This new salty water circulated cyclonically along the GoM coastline and mixed into the deeper Gulf through February 2018. Its intrusion may have also enhanced the cyclonic winter circulation in the Gulf. GoM surface salinity anomalies ended abruptly in early March 2018 coincident with the occurrence of a bomb cyclone and its associated strong upper ocean mixing.

The along-shelf momentum balance of the Mid-Atlantic Bight (MAB) coastal ocean includes a significant contribution from the along-shelf gradient in sea level. This sea level tilt, of order 10(-7), and other features of the mean sea level are not captured well in global mean dynamic topography (MDT) derived from hydrographic observations or satellite altimetry and gravity data, and is poorly represented in global and basin scale dynamical models. This is problematic for applications that would use coastal satellite altimeter data to estimate total water level above datum. We have produced a MDT for the MAB using the Regional Ocean Modeling System (ROMS) with 4-dimensional variational (4D-Var) data assimilation configured to obtain climatological annual and monthly mean results. The observations assimilated were a regional hydrographic climatology of temperature and salinity, and long-term mean velocity from HF-radar, shipboard ADCP, and current-meters. Assimilation adjusts the 3-dimensional ocean state, boundary conditions, and air-sea fluxes to minimize the model-data misfit. The assimilation of mean velocity data is vital to obtaining a realistic circulation result. The MDT exhibits a strong across-shelf sea level slope in geostrophic balance with the southwestward mean flow. The subtle along-shelf tilt is recovered and is relatively uniform throughout the MAB inside the 50 m isobath, but on the southern outer shelf it reverses sign and drives significant across-isobath flow, partially draining the southward mean transport. In the north, across-shelf flow is offshore in the surface and bottom Ekman layers, but largely balanced locally by inflow in the interior depth range.

Coastal ocean models that downscale global operational models are widely used to study regional circulation at enhanced resolutions.When operated as nowcast/forecast systems, these models offer predictions that can provide actionable guidance for maritime applications.A nowcast/forecast system for the northeast U.S. coastal ocean is described in this chapter to illustrate, by example, the many practical issues to be considered when configuring such a model for operational oceanography applications.The system uses the Regional Ocean Modeling System (ROMS) and four-dimensional variational data assimilation of observations from a comprehensive network of in situ platforms, coastal radars, and satellites.The emergence of open access web data services that adhere to community conventions for metadata descriptions for coordinate systems and geo-scientific data types, and support geospatial search and sub-setting, are shown to foster inter-operability of data and model usage, accelerate the test, validate and acceptance cycle for modeling system enhancements, streamline the addition of new data streams, facilitate operational monitoring of the system, and enable novice users to view and download model outputs to underpin the generation of higher level ocean information products.

This study provides a regional coastal ocean assessment of global upper ocean current data developed by the GlobCurrent (GC) project. These gridded data synthesize multiple satellite altimeter and wind model inputs to estimate both Geostrophic and Ekman-layer velocities. While the GC product was mostly devised and intended for open ocean studies, the present objective is to assess whether its data quality nearer the coast is suitable for other applications. The key ground truth sources are long-term mean and time series observations on the Northwestern Atlantic (NWA) shelf derived from Acoustic Doppler Current Profilers (ADCP) and high frequency (HF) radar networks in both the Mid-Atlantic Bight (MAB) and the Gulf of Maine (GoM). Results indicate that mean geostrophic currents across the MAB and the offshore GoM agree to roughly 10% in speed and 10 degree in direction with the in situ depth-averaged currents, with correlation levels of 0.5–0.8 at seasonal and longer time scales. Interior GoM comparisons at 5 coastal buoys show much less agreement. One likely source of GoM error is shown to be the GC mean dynamic topography near the coast. Comparison to near-surface MAB HF radar current measurements on the MAB shelf shows significant GC data improvement when including the surface Ekman term. Overall, the study results imply that application of GlobCurrent data may prove useful in coastal seas with broad continental shelves such as the MAB or Scotian shelf, but that large inaccuracies inside the GoM diminish its utility there.

The summertime eastward jet (SEJ) located around 12 degrees N, 110 degrees E-113 degrees E, as the offshore extension of the Vietnam coastal current, is an important feature of the South China Sea (SCS) surface circulation in boreal summer. Analysis of satellite-derived sea level and sea surface wind data during 1992-2012 reveals pronounced interannual variations in its surface strength (S-SEJ) and latitudinal position (Y-SEJ). In most of these years, the JAS (July, August, and September)-mean S-SEJ fluctuates between 0.17 and 0.55 m s(-1), while Y-SEJ shifts between 10.7 degrees N and 14.3 degrees N. These variations of the SEJ are predominantly contributed from the geostrophic current component that is linked to a meridional dipole pattern of sea level variations. This sea level dipole pattern is primarily induced by local wind changes within the SCS associated with the El Nino-Southern Oscillation (ENSO). Enhanced (weakened) southwest monsoon at the developing (decaying) stage of an El Nino event causes a stronger (weaker) SEJ located south (north) of its mean position. Remote wind forcing from the tropical Pacific can also affect the sea level in the SCS via energy transmission through the Philippine archipelago, but its effect on the SEJ is small. The impact of the oceanic internal variability, such as eddy-current interaction, is assessed using an ocean general circulation model (OGCM). Such impact can lead to considerable year-to-year changes of sea level and the SEJ, equivalent to approximate to 20% of the observed variation. This implies the complexity and prediction difficulty of the upper ocean circulation in this region.

During the first two weeks of November 2009, a field experiment was conducted in the Mid-Atlantic Bight region to demonstrate a coastal ocean observatory that can collect observations from heterogeneous platforms and forecast fields from four different ocean models, provide multi-model ensemble forecasts based on either an equal weighting (EQ) or objective weighting (OBJ) method, and use model forecasts in a path planning system to relocate autonomous gliders. This experiment is a prototype for the command and control component of cyberinfrastructure of the Ocean Observatories Initiative funded by the National Science Foundation. The four individual models use different forcing fields, boundary conditions and data assimilation techniques, and have resolutions varying from 2km to 15km. Our results indicate that for sea surface temperature and surface currents, the OBJ ensemble outperforms the four individual models, while the EQ ensemble can also provide an effective way to improve individual model forecasts. In terms of glider path planning, the OBJ ensemble has a performance similar to the best individual model, which has the finest horizontal resolution. This field experiment demonstrates the first-ever use of ensemble current forecasts to guide glider path planning in the context of real-time data collection and ocean model forecasting.

The coastal northeast United States was heavily impacted by hurricanes Irene and Sandy. Track forecasts for both hurricanes were quite accurate days in advance. Intensity forecasts, however, were less accurate, with the intensity of Irene significantly over-predicted, and the rapid acceleration and intensification of Sandy just before landfall under-predicted. By operating a regional component of the Integrated Ocean Observing System (IOOS), we observed each hurricane's impact on the ocean in real-time, and we studied the impacted ocean's influence on each hurricane's intensity.Summertime conditions on the wide Mid-Atlantic continental shelf consist of a stratified water column with a thin (10m-20m) warm surface layer (24-26C) covering bottom Cold Pool water (8-10C). As the leading edge of Irene tracked along the coast, real-time temperature profiles from an underwater glider documented the mixing and broadening of the thermocline that rapidly cooled the surface by up to 8C, well before the eye passed over. Atmospheric forecast sensitivity studies indicate that the over prediction of intensity in Irene could be eliminated using the observed colder surface waters. In contrast, Hurricane Sandy arrived in the late Fall of 2012 after seasonal cooling had already deepened and decreased surface layer ocean temperatures by 8C. The thinner layer of cold bottom water still remaining before Sandy was forced offshore by downwelling favorable winds, resulting in little change in ocean surface temperature as Sandy crossed and mixed the shelf waters. Atmospheric sensitivity studies indicate that because there was little ocean cooling, there was little reduction in hurricane intensity as Sandy came ashore. Results from Irene and Sandy illustrate the important role of the U.S. IOOS in providing the best estimate of the rapidly evolving ocean conditions to atmospheric modelers forecasting the intensity of hurricanes. Data from IOOS may enable improved hurricane forecasting in the future.