Dynamic Sea Research Articles

Dr. Jeffrey A. Nystuen—A PAL to acoustical oceanography

Dr. Jeffrey A. Nystuen was a visionary, innovator, proud student of life-long science learning, and friend. Jeff pioneered the development of the Passive Aquatic Listener (PAL), which was initially the Acoustic Rain Gauge (ARG). The PAL is a low-noise, broadband (100 kHz sampling rate), low-duty cycle, underwater recorder that operates according to an onboard, adaptive sampling protocol. The PAL was one of the first autonomous passive acoustic recorders that could sample for a full year with a frequency range capable of recording dolphin echolocation signals. While originally designed to detect rainfall and estimate the rate of ocean precipitation, the PAL has been used to better understand marine mammal patterns and trends, wind and storms, anthropogenic activity, and sea ice dynamics. The versatility of the PAL has evolved throughout its use from a standalone, archival autonomous recorder to a compact system integrated into Argo floats. PALs have been deployed in the Arctic, Indian, Atlantic, and Pacific Oceans in addition to many regional seas, coastal waters, freshwater lakes, and springs! The vast number of interdisciplinary questions and collaborations centered around the PAL technology highlights Jeff’s creative thinking, which has left a strong legacy in the field of acoustic oceanography.

Arctic sea ice melt pond fraction in 2000–2021 derived by dynamic pixel spectral unmixing of MODIS images

The Arctic has experienced extensive sea ice retreat in recent decades, as observed from satellite remote sensing and simulated by general circulation models. The significant low albedo of melt pond compared with snow and ice results in more absorption of radiation compared with sea ice without melt pond, which will then enhance sea ice melt to form more melt pond. This so-called positive feedback of melt pond is crucial for sea ice thermal and physical properties. The melt pond coverage varies significantly spatially and temporally and satellite remote sensing provides a possible solution in determining the spatial coverage of melt pond. This work aims to develop a new physically based algorithm for retrieving the cover fraction of melt ponds on sea ice using remote sensing data. In the newly developed algorithm, dynamic sea ice and melt pond reflectances are used in the pixel spectral unmixing for melt pond fraction (MPF) estimation. Radiative transfer models for sea ice and melt pond reflectance modeling are developed for MPF retrieval algorithm. The validation of retrieved MPF and its comparison with static pixel spectral unmixing results show that the dynamic algorithm proposed in this study has the potential of application in wide range of situations by considering dynamic spectral reflectances of melt pond and sea ice. The Arctic MPF and sea ice cover fraction (SIF) in 2000–2021 are generated by applying the proposed algorithm. The spatial and temporal characteristics of MPF and SIF are analyzed. Time series trend analysis of MPF in 2000–2021 reveals the significant increasing trend of relative MPF in the Arctic. The melt pond expansion in 2000–2021 is more obvious in the marginal areas, especially the marginal areas close to Russia coast. Trend analysis for typical regions such as Beaufort Sea, Greenland Sea, the Baffin Bay, Chukchi, East Siberian, Laptev, and Kara seas and center Arctic also reveals that the relative MPF and SIF show contrasting trend.

Arctic sea ice mass balance in a new coupled ice–ocean model using a brittle rheology framework

Abstract. Sea ice is a key component of the Earth's climate system as it modulates the energy exchanges and associated feedback processes at the air–sea interface in polar regions. These exchanges have been suggested to strongly depend on openings in the sea ice cover, which are associated with fine-scale sea ice deformations, but the importance of these processes remains poorly understood as most numerical models struggle to represent these deformations without using very costly horizontal resolutions (≃ 5 km). In this study, we present results from a 12 km resolution ocean–sea ice coupled model, the first that uses a brittle rheology to represent the mechanical behaviour of sea ice. This rheology has been shown to reproduce observed characteristics and complexity of fine-scale sea ice deformations at relatively coarse resolutions. We evaluate and discuss the Arctic sea ice mass balance of this coupled model for the period 2000–2018. We first assess sea ice quantities relevant for climate (volume, extent, and drift) and find that they are consistent with satellite observations. We evaluate components of the mass balance for which observations are available, i.e. sea ice volume export through Fram Strait and winter mass balance in the Arctic marginal seas for the period 2003–2018. Model values show a good match with observations, remaining within the estimated uncertainty, and the interannual variability of the dynamic contribution to the winter mass balance is generally well captured. We discuss the relative contributions of dynamics and thermodynamics to the sea ice mass balance in the Arctic Basin for 2000–2018. Using the ability of the model to represent divergence motions at different scales, we investigate the role of leads and polynyas in ice production. We suggest a way to estimate the contribution of leads and polynyas to ice growth in winter, and we estimate this contribution to add up to 25 %–35 % of the total ice growth in pack ice from January to March. This contribution shows a significant increase over 2000–2018. This coupled framework opens up new opportunities to understand and quantify the interplay between small-scale sea ice dynamics and ocean properties.

Improved Analytical Formula for the SAR Doppler Centroid Estimation Standard Deviation for a Dynamic Sea Surface

The existing formulas for the synthetic aperture radar (SAR) Doppler centroid estimation standard deviation (STD) suffer from various limitations, especially for a dynamic sea surface. In this study, we derive an improved version of these formulas through three steps. First, by considering the ocean wavenumber spectrum information, a new strategy for determining the number of independent samples of the sea wave velocity field is adopted in the new formula. This is contrary to the method used in the existing formulas, where the number of SAR geometric resolution cells is taken as the number of samples assuming that adjacent SAR resolution cells are statistically uncorrelated. Second, the pulse repetition frequency and Doppler bandwidth are decoupled in the new formula, unlike in the existing formulas where they are unchangeably related to each other. Third, the effects of thermal noise and Doppler aliasing are jointly quantified in a mathematically exact manner instead of being treated separately, as in the existing formulas. Comprehensive SAR raw data simulations for the ocean surface show that the new formula has a better performance in predicting the Doppler centroid estimation STD than the existing formulas.

Long‐term patterns in ecosystem phenology near Palmer Station, Antarctica, from the perspective of the Adélie penguin

AbstractClimate change is leading to phenological shifts across a wide range of species globally. Polar oceans are hotspots of rapid climate change where sea ice dynamics structure ecosystems and organismal life cycles are attuned to ice seasonality. To anticipate climate change impacts on populations and ecosystem services, it is critical to understand ecosystem phenology to determine species activity patterns, optimal environmental windows for processes like reproduction, and the ramifications of ecological mismatches. Since 1991, the Palmer Antarctica Long‐Term Ecological Research (LTER) program has monitored seasonal dynamics near Palmer Station. Here, we review the species that occupy this region as year‐round residents, seasonal breeders, or periodic visitors. We show that sea ice retreat and increasing photoperiod in the spring trigger a sequence of events from mid‐November to mid‐February, including Adélie penguin clutch initiation, snow melt, calm conditions (low winds and warm air/sea temperature), phytoplankton blooms, shallow mixed layer depths, particulate organic carbon flux, peak humpback whale abundances, nutrient drawdown, and bacterial accumulation. Subsequently, from May to June, snow accumulates, zooplankton indicator species appear, and sea ice advances. The standard deviation in the timing of most events ranged from ~20 to 45 days, which was striking compared with Adélie penguin clutch initiation that varied <1 week. In general, during late sea ice retreat years, events happened later (~5 to >30 days) than mean dates and the variability in timing was low (<20%) compared with early ice retreat years. Statistical models showed the timing of some events were informative predictors (but not sole drivers) of other events. From an Adélie penguin perspective, earlier sea ice retreat and shifts in the timing of suitable conditions or prey characteristics could lead to mismatches, or asynchronies, that ultimately influence chick survival via their mass at fledging. However, more work is needed to understand how phenological shifts affect chick thermoregulatory costs and the abundance, availability, and energy content of key prey species, which support chick growth and survival. While we did not detect many long‐term phenological trends, we expect that when sea ice trends become significant within our LTER time series, phenological trends and negative effects from ecological mismatches will follow.

Impact of sea ice transport on Beaufort Gyre liquid freshwater content

The Arctic Ocean’s Beaufort Gyre (BG) is a wind-driven reservoir of relatively fresh seawater, situated beneath time-mean anticyclonic atmospheric circulation, and is covered by mobile pack ice for most of the year. Liquid freshwater accumulation in and expulsion from this gyre is of critical interest due to its potential to affect the Atlantic meridional overturning circulation and due to the importance of freshwater in modulating vertical fluxes of heat, nutrients and carbon in the ocean, and exchanges of heat and moisture with the atmosphere. Here, we investigate the hypothesis that wind-driven sea ice transport into/from the BG region influences the freshwater content of the gyre and its variability. To test this hypothesis, we use the results of a coordinated climate response function experiment with four ice-ocean models, in combination with targeted experiments using a regional setup of the MITgcm, in which we rotate the surface wind forcing vectors (thereby changing the ageostrophic component of these winds). Our results show that, via an effect on the net thermodynamic growth rate, anomalies in sea ice transport into the BG affect liquid freshwater adjustment. Specifically, increased ice import increases freshwater retention in the gyre, whereas ice export decreases freshwater in the gyre. Our results demonstrate that uncertainty in the ageostrophic component of surface winds, and in the dynamic sea ice response to these winds, has important implications for ice thermodynamics and freshwater. This sensitivity may explain some of the observed inter-model spread in simulations of Beaufort Gyre freshwater and its adjustment in response to wind forcing.

Indian Ocean dynamic sea level, its variability and projections in CMIP6 models

Indian Ocean dynamic sea level, its variability and projections in CMIP6 models

Ground-based radar interferometry for monitoring of landfast sea ice dynamics

In this work, we evaluate landfast sea ice dynamics using ground-based radar interferometry. During two field campaigns in Utqiaġvik, Alaska, we collected three ∼24-h series of measurements on 16 May 2012 and 21–23 April 2021 using the Gamma portable radar interferometer (GPRI). These data enable examination of progressive strain of landfast ice on the sub-cm scale. The results indicate near spatially uniform divergence strains exceeding 10−6 in response to an increase in offshore winds from 0 to 7 m s−1. Exceptions to uniform divergence are grounded ridges with either negligible or reduced motion. We also track uniform vertical shifts in response to cm-scale sea level change correlated with NOAA model tidal predictions. We evaluate and take steps to remove contributions from moisture variability, thereby reducing potential errors from atmospheric effects to less than 5 mm. The results suggest that the GPRI can be a valuable tool for monitoring ice-covered coastal zones. The system has possible applications for monitoring tides and ocean surges and tracking small-scale deformation of otherwise stationary ice that can lead to fracture and destabilization.

Sea surface height anomaly and geostrophic current velocity from altimetry measurements over the Arctic Ocean (2011–2020)

Abstract. Satellite altimetry missions flying over the ice-covered Arctic Ocean have opened the possibility of further understanding changes in the ocean beneath the sea ice. This requires complex processing of satellite signals emerging from the sea surface in leads within the sea ice, with efforts to generate consistent Arctic-wide datasets of sea surface height ongoing. The aim of this paper is to provide and assess a novel gridded dataset of sea surface height anomaly and geostrophic velocity, which incorporates both the ice-covered and open ocean areas of the Arctic. Data from the CryoSat-2 mission in the period 2011–2020 were gridded at monthly intervals, up to 88∘ N, using the Data-Interpolating Variational Analysis (DIVA) method. To examine the robustness of our results, we compare our dataset to independent satellite data, mooring time series and Arctic-wide hydrographic observations. We find that our dataset is well correlated with independent satellite data at monthly timescales. Comparisons to in situ ocean observations show that our dataset provides reliable information on the variability of sea surface height and surface geostrophic currents over geographically diverse regions of the Arctic Ocean and different dynamical regimes and sea ice states. At all comparison sites we find agreement with in situ observed variability at seasonal to interannual timescales. Furthermore, we find that our geostrophic velocity fields can resolve the variability of boundary currents wider than about 50 km, a result relevant for studies of Arctic Ocean circulation. Additionally, large-scale seasonal features emerge. Sea surface height exhibits a wintertime Arctic-wide maximum, with the highest amplitude over the shelves. Also, we find a basin-wide seasonal acceleration of Arctic slope currents in winter. We suggest that this dataset can be used to study not only the large-scale sea surface height and circulation, but also the regionally confined boundary currents. The dataset is available in netCDF format from PANGAEA at https://doi.org/10.1594/PANGAEA.931869 (Doglioni et al., 2021d).

Antarctic contribution to future sea level from ice shelf basal melt as constrained by ice discharge observations

Abstract. Antarctic mass loss is the largest contributor to uncertainties in sea level projections on centennial time scales. In this study we aim to constrain future projections of the contribution of Antarctic dynamics by using ice discharge observations. The contribution of Antarctica's ice discharge is computed with ocean thermal forcing from 14 Earth system models (ESMs) and linear response functions (RFs) from 16 ice sheet models for 3 shared socioeconomic pathway (SSP) scenarios. New compared to previous studies, basal melt sensitivities to ocean temperature changes were calibrated on four decades of observed ice discharge changes rather than using observation-based basal melt sensitivities. Calibration improved historical performance but did not reduce the uncertainty in the projections. The results show that even with calibration the acceleration during the observational period is underestimated for the Amundsen Region, indicating that ice and/or ocean processes are not well represented. Also the relative contribution of the Amundsen Region is underestimated. The Amundsen Region contribution and sea level acceleration are improved by choosing an Amundsen Region-specific calibration (rather than Antarctic-wide), quadratic basal melt parameterisation (rather than linear) and thermal forcing near the ice shelf base (rather than the deepest layer above the continental shelf). With these methodological choices we arrive at a median dynamic sea level contribution of 0.12 m for SSP1-2.6, 0.14 m for SSP2-4.5 and 0.17 m for SSP5-8.5 in 2100 relative to 1995–2014, sitting in between projections of previous multimodel studies (ISMIP6 emulator and LARMIP-2). Our results show that constraining the basal melt parameterisation on Amundsen Region ice discharge rather than applying the median basal melt sensitivities used in LARMIP-2 and the mean Antarctic distribution of ISMIP6 leads to higher sea level contributions. However, differences in basal melt sensitivities alone cannot explain the differences in our projections compared to the emulated ISMIP6 and LARMIP-2. We conclude that uncertainties associated with ESMs and ice sheet models affect the projected sea level contribution more than our methodological choices in the calibration and basal melt computation.

Spatial variability of dissolved nickel is enhanced by mesoscale dynamics in the Gulf of Mexico

The Gulf of Mexico (GoM) is one of the most dynamic marginal seas in the world owing to the intrusion of the Loop Current and the shedding of anticyclonic eddies (LCE) that travel westward across the Gulf. However, the impacts of these mesoscale dynamics on the supply and removal of bioessential trace metals in surface waters remain unclear. We study the impact of mesoscale eddies on the distribution of dissolved nickel (Ni), a biologically active element scarcely studied in the region. The vertical distribution of Ni was determined in the deep-water region of the GoM during summer of 2017, when two anticyclonic LCE (Quantum and Poseidon) were present. Nutrient-like profiles of Ni in the GoM resemble those from the Atlantic Ocean, but they showed high spatial variability within the first 1000 m, which was associated with the impact of mesoscale eddies. Similarly to subtropical gyres, macronutrients were almost depleted in surface waters, while Ni never fell below 1.51 nmol kg-1, suggesting low Ni lability or alternatively, slow biological uptake compared to that of macronutrients. In particular, lowest levels of Ni and macronutrients (PO4 and NO3) were recorded in surface waters of the anticyclonic eddies and the Loop Current area. Anticyclonic LCEs deepened these Ni-poor waters pushing the Ni-rich core of Tropical Atlantic Central Water up to 600 m, whereas its shallowest position (up to 200 m) was recorded under cyclonic conditions in Campeche Bay. This eddy-induced vertical displacement of water masses also affected the integrated Ni and macronutrient concentrations in the upper 350 m but without modifying their stoichiometries. We suggest that a significant decrease in surface inventories of Ni and macronutrient in areas impacted by LCEs is a consequence of the trapping of the water within eddies, the biological uptake of Ni and macronutrients combined with their limited replenishment from below, which likely affects autotrophic groups. In conclusion, the mesoscale dynamic permanently present in the GoM play an important role in modifying the vertical distribution of Ni and macronutrients as well as their availability in the upper water column of this marginal sea.

Interannual to decadal sea level variability in the subpolar North Atlantic: the role of propagating signals

Abstract. The gyre-scale, dynamic sea surface height (SSH) variability signifies the spatial redistribution of heat and freshwater in the ocean, influencing the ocean circulation, weather, climate, sea level, and ecosystems. It is known that the first empirical orthogonal function (EOF) mode of the interannual SSH variability in the North Atlantic exhibits a tripole gyre pattern, with the subtropical gyre varying out of phase with both the subpolar gyre and the tropics, influenced by the low-frequency North Atlantic Oscillation. Here, we show that the first EOF mode explains the majority (60 %–90 %) of the interannual SSH variance in the Labrador and Irminger Sea, whereas the second EOF mode is more influential in the northeastern part of the subpolar North Atlantic (SPNA), explaining up to 60 %–80 % of the regional interannual SSH variability. We find that the two leading modes do not represent physically independent phenomena. On the contrary, they evolve as a quadrature pair associated with a propagation of SSH anomalies from the eastern to the western SPNA. This is confirmed by the complex EOF analysis, which can detect propagating (as opposed to stationary) signals. The analysis shows that it takes about 2 years for sea level signals to propagate from the Iceland Basin to the Labrador Sea, and it takes 7–10 years for the entire cycle of the North Atlantic SSH tripole to complete. The observed westward propagation of SSH anomalies is linked to shifting wind forcing patterns and to the cyclonic pattern of the mean ocean circulation in the SPNA. The analysis of regional surface buoyancy fluxes in combination with the upper-ocean temperature and salinity changes suggests a time-dependent dominance of either air–sea heat fluxes or advection in driving the observed SSH tendencies, while the contribution of surface freshwater fluxes (precipitation and evaporation) is negligible. We demonstrate that the most recent cooling and freshening observed in the SPNA since about 2010 were mostly driven by advection associated with the North Atlantic Current. The results of this study indicate that signal propagation is an important component of the North Atlantic SSH tripole, as it applies to the SPNA.

Model-based deep reinforcement learning for data-driven motion control of an under-actuated unmanned surface vehicle: Path following and trajectory tracking

Unmanned surface vehicles (USVs) are a promising marine robotic platform for numerous potential applications in ocean space due to their small size, low cost, and high autonomy. Modelling and control of USVs is a challenging task due to their intrinsic nonlinearities, strong couplings, high uncertainty, under-actuation, and multiple constraints. Well designed motion controllers may not be effective when exposed in the complex and dynamic sea environment. The paper presents a fully data-driven learning-based motion control method for an USV based on model-based deep reinforcement learning. Specifically, we first train a data-driven prediction model based on a deep network for the USV by using recorded input and output data. Based on the learned prediction model, model predictive motion controllers are presented for achieving trajectory tracking and path following tasks. It is shown that after learning with random data collected from the USV, the proposed data-driven motion controller is able to follow trajectories or parameterized paths accurately with excellent sample efficiency. Simulation results are given to illustrate the proposed deep reinforcement learning scheme for fully data-driven motion control without any a priori model information of the USV.

Discretization of Sea Ice Dynamics in the Tangent Plane to the Sphere by a CD‐Grid‐Type Finite Element

AbstractWe present a new discretization of sea ice dynamics on the sphere. The approach describes sea ice motion in tangent planes to the sphere. On each triangle of the mesh, the ice dynamics are discretized in a local coordinate system using a CD‐grid‐like non‐conforming finite element method. The development allows a straightforward coupling to the C‐grid like ocean model in Icosahedral Non‐hydrostatic‐Ocean model, which uses the same infrastructure as the sea ice module. Using a series of test examples, we demonstrate that the non‐conforming finite element discretization provides a stable realization of large‐scale sea ice dynamics on the sphere. A comparison with observation shows that we can simulate typical drift patterns with the new numerical realization of the sea ice dynamics.

Spatial variation in carbon source use and trophic position of ringed seals across a latitudinal gradient of sea ice

Anthropogenic climate change is causing changes to the Arctic sea-ice system with implications for the magnitude and timing of Arctic pelagic and ice-associated (sympagic) primary production that influences food web interactions. Ringed seals (Pusa hispida) are generalist predators that, as a species experience vastly different icescapes from low to high-Arctic latitudes. Quantifying spatial variation in their diet can help us understand how changes in sea-ice dynamics affect trophic interactions in Arctic marine food webs. However, multiple complementary analytical tools to examine variation in carbon source use and trophic dynamics in the diet of ringed seals have not yet been applied across their latitudinal range in the Arctic. We conducted stable isotope analysis (δ13C and δ15N) and measured highly branched isoprenoid diatom lipid biomarkers of ringed seals from the low, intermediate, and high Arctic (from 61.1°N to 77.5°N) to investigate spatial variation in their carbon source use and trophic position in relation to sea-ice dynamics. Both δ13C and highly branched isoprenoids indicated that ringed seals from higher latitudes had more sympagic carbon in their diet (liver δ13C: −18.3 ± 0.2 ‰, HBI: 89.9 ± 2.08 %) than ringed seals at lower latitudes (liver δ13C: −21.1 ± 0.1 ‰, HBI: 22.0 ± 2.73 %). Ringed seal trophic position increased from the low (3.78 ± 0.02) to high (4.76 ± 0.03) Arctic, suggesting increased fish consumption or a different trophic structure coinciding with the latitudinal change in carbon source. Ringed seals demonstrated a clear shift from low to high Arctic in the relative contribution of phytoplanktonic vs sympagic primary production. These patterns are likely linked to the vastly different icescapes in these environments and demonstrate that shifts in primary producer composition and Arctic food webs can be identified in ringed seal diets. Information on these prey and energy shifts over large spatial scales also provides insights into potential future changes to Arctic ecosystem function with continued sea-ice decline.

An unstructured CD-grid variational formulation for sea ice dynamics

We present a new unstructured CD-grid formulation of the elastic-viscous-plastic rheology, where the velocity unknowns are co-located at the edges. Our framework of choice is the Model for Prediction Across Scales (MPAS) within E3SM, the climate model of the U.S. Department of Energy, although our approach is general and could be applied to other models as well. The mesh cells in our analysis have n sides, with n greater than or equal to three. Given an initial mesh, we compute the divergence of the stress using a sub-grid, which introduces two separate sets of cells that may differ in shape or be equal depending on the initial topology of the initial mesh. The proposed approach is of higher order compared to the existing B-grid discretization of MPAS-Seaice, and does not need stabilization as other CD-grid formulations on unstructured grids. Our new methodology will contribute to transitioning the dynamics of MPAS-Seaice to a CD-grid mesh, facilitating improved coupling with MPAS-Ocean and reducing numerical errors associated with interpolation.

First Report of Elasmobranchii and Osteichthyans from the Fox Hills Formation (Late Cretaceous), Poison Springs Locality, Northeastern Colorado

Isolated sandstone and siltstone outcrops of the Late Cretaceous (Campanian-Maastrichtian) Fox Hills Formation occur at the Poison Springs Locality in northeastern Colorado. These nearshore deposits document the western margin of the Fox Hills Sea and have yielded elasmobranch and osteichthyan remains. Seventeen elasmobranch species from eleven families including Squatina hassei, Plicatoscyllium derameei, Cretorectolobus olsoni, Carcharias samhammeri, Odontaspis aculeatus, Cretalamna cf. C. feldmanni, Palaeogaleus navarroensis, Galeorhinus girardoti, Archaeotriakis rochelleae, Pseudomyledaphus sp., Pseudohypolophus mcnultyi, Ischyrhiza avonicola, Ptychotrygon winni, Ptychotrygon greybullensis, Ptychotrygon sp., Dasyatis sp., and Rhombodus levis and five osteichthlyan species from four families including Melvius sp., Paralbula casei, Enchodus dirus, Enchodus sp., and Hadrodus sp. were identified. This paleofauna is essentially the same as the Fox Hills Formation paleofauna recovered from North Dakota and extends the geographic range of the Late Cretaceous Fox Hills fish paleocommunity to far western shores of the Fox Hills Sea. The Poison Springs fish paleofauna consists of a mix of freshwater, brackish water/estuarine and shallow marine, and open marine taxa reflecting the dynamic Fox Hills Sea coastal margin. This fish paleocommunity included predaceous, durophagous bottom feeders, shallow marine piscivores, and open water ambush predators. Some taxa are restricted to the northern Western Interior Seaway, but most are more cosmopolitan and range to the Texas-Gulf Coast, Mississippi Embayment, and Atlantic Coastal Plain. A few have also been found in Europe and North Africa. This Late Cretaceous Fox Hills Formation fish paleofauna provides additional evidence for extinctions of marine fish at the end of the Cretaceous.

Low-Frequency Dynamic Ocean Response to Barometric-Pressure Loading

Abstract Changes in dynamic manometric sea level ζm represent mass-related sea level changes associated with ocean circulation and climate. We use twin model experiments to quantify magnitudes and spatiotemporal scales of ζm variability caused by barometric pressure pa loading at long periods ( month) and large scales () relevant to Gravity Recovery and Climate Experiment (GRACE) ocean data. Loading by pa drives basin-scale monthly ζm variability with magnitudes as large as a few centimeters. Largest ζm signals occur over abyssal plains, on the shelf, and in marginal seas. Correlation patterns of modeled ζm are determined by continental coasts and H/f contours (H is ocean depth and f is Coriolis parameter). On average, ζm signals forced by pa represent departures of and from the inverted-barometer effect ζib on monthly and annual periods, respectively. Basic magnitudes, spatial patterns, and spectral behaviors of ζm from the model are consistent with scaling arguments from barotropic potential vorticity conservation. We also compare ζm from the model driven by pa to ζm from GRACE observations. Modeled and observed ζm are significantly correlated across parts of the tropical and extratropical oceans, on shelf and slope regions, and in marginal seas. Ratios of modeled to observed ζm magnitudes are as large as ∼0.2 (largest in the Arctic Ocean) and qualitatively agree with analytical theory for the gain of the transfer function between ζm forced by pa and wind stress. Results demonstrate that pa loading is a secondary but nevertheless important contributor to monthly mass variability from GRACE over the ocean.

Winter Ice Dynamics in a Semi-Closed Ice-Covered Sea: Numerical Simulations and Satellite Data

The White Sea is a small shallow sea covered by ice in winter. There are very few numerical models of this sea. For the ice-free sea, much data has been collected, but for winter only a small amount (satellite data only). We use our finite-element numerical model Jasmine and satellite data to trace the ice advection and exchange between parts of the White Sea. The aim of the investigation is to adjust the model to adequately reproduce the White Sea ice dynamics. By comparing satellite data on sea-ice concentration with the model prediction, we show that the model describes sea-ice dynamics well, and use it to estimate ice flow from bays to the middle part of the sea and ice exchange through the narrow strait. Ice exchange between neighbouring parts of the sea is shown to be intensive, with large dispersion compared to the time-mean, and bays are shown to be ice producers, while the Gorlo straight is shown to accept ice. We demonstrate that the model is a tool that can be used to better understand the winter regime of the sea.

Drift simulation of a floating offshore wind turbine with broken mooring lines in a dynamic sea condition

This study investigates the aero-hydro-mooring coupled dynamics of the National Renewable Energy Laboratory (NREL) offshore 5-MW baseline wind turbine supported by the Offshore Code Comparison Collaboration Continuation (OC4) DeepCwind semisubmersible floating platform by considering the effects of suddenly broken mooring behaviour. The wind and wave loads can be selected as the Cummins time-domain equation inputs based on the Norwegian Petroleum Directorate wind and Joint North Sea Wave Project wave spectrums. The nonlinear viscous drag was estimated using the quadratic damping matrix rather than Morison's element. Additionally, the quadratic transfer function matrix was used to calculate the slow-drift force. Compared to the multi-segmented quasi-static mooring model, the lump-mass method is a dynamic mooring model that can solve real-time motion on the platform. Once a single or a pair of mooring lines is intentionally disconnected from the floating platform at a certain time, the transient responses of mooring line tensions and turbine performance will be evaluated. The novelty of this study is that the drift trajectories and power performances of OC4 DeepCwind semisubmersible floating offshore wind turbine under different conditions of environmental loads and broken mooring lines can be approximately estimated in the offshore wind farm. The analysis can be used for the environmental impact assessment in harsh sea conditions.