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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. [ABSTRACT FROM AUTHOR]

Continental shelves are thought to be affected disproportionately by climate change and are a large contributor to global air–sea carbon dioxide (CO 2) fluxes. It is often reported that low-latitude shelves tend to act as net sources of CO 2 , whereas mid- and high-latitude shelves act as net sinks. Here, we combine a high-resolution regional model with surface water time series and repeat transect observations from the Scotian Shelf, a mid-latitude region in the northwest North Atlantic, to determine what processes are driving the temporal and spatial variability of partial pressure of CO 2 (p CO 2) on a seasonal scale. In contrast to the global trend, the Scotian Shelf acts as a net source. Surface p CO 2 undergoes a strong seasonal cycle with an amplitude of ∼ 200–250 µ atm. These changes are associated with both a strong biological drawdown of dissolved inorganic carbon (DIC) in spring (corresponding to a decrease in p CO 2 of 100–200 µ atm) and pronounced effects of temperature, which ranges from 0 ∘ C in the winter to near 20 ∘ C in the summer, resulting in an increase in p CO 2 of ∼ 200–250 µ atm. Throughout the summer, events with low surface water p CO 2 occur associated with coastal upwelling. This effect of upwelling on p CO 2 is also in contrast to the general assumption that upwelling increases surface p CO 2 by delivering DIC-enriched water to the surface. Aside from these localized events, p CO 2 is relatively uniform across the shelf. Our model agrees with regional observations, reproduces seasonal patterns of p CO 2 , and simulates annual outgassing of CO 2 from the ocean of +1.7±0.2 mol C m -2 yr -1 for the Scotian Shelf, net uptake of CO 2 by the ocean of -0.5±0.2 mol C m -2 yr -1 for the Gulf of Maine, and uptake by the ocean of -1.3±0.3 mol C m -2 yr -1 for the Grand Banks. [ABSTRACT FROM AUTHOR]

Climate change is one of the biggest challenges facing development and continuation of sustainable aquaculture in temperate regions. We primarily consider the ecological and physical resilience of aquaculture in the Gulf of Maine (GoM), where a thriving industry includes marine algae, extensive and intensive shellfish aquaculture, and a well‐established Atlantic salmon industry, as well as the infrastructure required to support these economically important ventures. The historical record of sea surface temperature in the GoM, estimated from gridded, interpolated in situ measurements, shows considerable interannual and decade‐scale variability superimposed on an overall warming trend. Climate model projections of sea surface temperature indicate that the surface waters in the GoM could warm 0.5–3.5°C beyond recent values by the year 2100. This suggests that, while variability will continue, anomalous warmth of marine heatwaves that have been observed in the past decade could become the norm in the GoM ca. 2050, but with the most significant impacts to existing aquaculture along the southernmost region of the coast. We consider adaptations leading to aquacultural resilience despite the effects of warming, larger numbers of harmful nonindigenous species (including pathogens and parasites), acidification, sea‐level rise, and more frequent storms and storm surges. Some new species will be needed, but immediate attention to adapt existing species (e.g. preserve/define wild biodiversity, breed for temperature tolerance and incorporate greater husbandry) and aquaculture infrastructure can be successful. We predict that these measures and continued collaboration between industry, stakeholders, government and researchers will lead to sustaining a vibrant working waterfront in the GoM. [ABSTRACT FROM AUTHOR]

ROMS, a high-resolution regional ocean model, was used to study how climate change may affect the northwestern Atlantic Ocean. A control (CTRL) simulation was conducted for the recent past (1976-2005), and simulations with additional forcing at the surface and lateral boundaries, obtained from three different global climate models (GCMs) using the RCP8.5 scenario, were conducted to represent the future (2070-99). The climate change response was obtained from the difference between the CTRL and each of the three future simulations. All three ROMS simulations indicated large increases in sea surface temperatures (SSTs) over most of the domain except off the eastern U.S. seaboard resulting from weakening of the Gulf Stream. There are also substantial intermodel differences in the response, including a southward shift of the Gulf Stream in one simulation and a slight northward shift in the other two, with corresponding changes in eddy activity. The depth of maximum warming varied among the three simulations, resulting in differences in the bottom temperature response in coastal regions, including the Gulf of Maine and the West Florida Shelf. The surface salinity decreased in the northern part of the domain and increased in the south in all three experiments, although the freshening extended much farther south in one ROMS simulation relative to the other two, and also relative to the GCM that provided the large-scale forcing. Thus, while high resolution allows for a better representation of currents and bathymetry, the response to climate change can vary considerably depending on the large-scale forcing. [ABSTRACT FROM AUTHOR]

Adding to the challenge of predicting fishery recruitment in a changing environment is downscaling predictions to capture locally divergent trends over a species' range. In recent decades, the American lobster (Homarus americanus) fishery has shifted poleward along the northwest Atlantic coast, one of the most rapidly warming regions of the world's oceans. Building on evidence that early post‐settlement life stages predict future fishery recruitment, we describe enhancements to a forecasting model that predict landings using an annual larval settlement index from 62 fixed sites among 10 study areas from Rhode Island, USA to New Brunswick, Canada. The model is novel because it incorporates local bottom temperature and disease prevalence to scale spatial and temporal changes in growth and mortality. For nine of these areas, adding environmental predictors significantly improved model performance, capturing a landings surge in the eastern Gulf of Maine, and collapse in southern New England. On the strength of these analyses, we project landings within the next decade to decline to near historical levels in the Gulf of Maine and no recovery in the south. This approach is timely as downscaled ocean temperature projections enable decision makers to assess their options under future climate scenarios at finer spatial scales. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]