In this study the impact of extreme cyclones on Arctic sea ice in summer is investigated. Examined in particular are relative thermodynamic and dynamic contributions to sea ice volume budgets in the ...vicinity of Arctic summer cyclones in 2012 and 2016. Results from this investigation illustrate that sea ice loss in the vicinity of the cyclone trajectories during each year was associated with different dominant processes: thermodynamic processes (melting) in the Pacific sector of the Arctic in 2012, and both thermodynamic and dynamic processes in the Pacific sector of the Arctic in 2016. Comparison of both years further suggests that the Arctic minimum sea ice extent is influenced by not only the strength of the cyclone, but also by the timing and location relative to the sea ice edge. Located near the sea ice edge in early August in 2012, and over the central Arctic later in August in 2016, extreme cyclones contributed to comparable sea ice area (SIA) loss, yet enhanced sea ice volume loss in 2012 relative to 2016. Central to a characterization of extreme cyclone impacts on Arctic sea ice from the perspective of thermodynamic and dynamic processes, we present an index describing relative thermodynamic and dynamic contributions to sea ice volume changes. This index helps to quantify and improve our understanding of initial sea ice state and dynamical responses to cyclones in a rapidly warming Arctic, with implications for seasonal ice forecasting, marine navigation, coastal community infrastructure, and designation of protected and ecologically sensitive marine zones.
Abstract
The ideal environment for extratropical cyclone development includes strong vertical shear of horizontal wind and low static stability in the atmosphere. Arctic sea ice loss enhances the ...upward flux of energy to the lower atmosphere, reducing static stability. This suggests that Arctic sea ice loss may facilitate more intense storms over the Arctic Ocean. However, prior research into this possibility has yielded mixed results with uncertain cause and effect. This work has been limited either in scope (focusing on a few case studies) or resolution (focusing on seasonal averages). In this study, we extend this body of research by comparing the intensification rate and maximum intensity of individual cyclones to local sea ice anomalies. We find robust evidence that reduced sea ice in winter (December–March) strengthens Arctic cyclones by enhancing the surface turbulent heat fluxes and lessening static stability while also strengthening vertical shear of horizontal wind. We find weaker evidence for this connection in spring (April–June). In both seasons, lower sea ice concentration also enhances cyclone-associated precipitation. Although reduced sea ice also weakens static stability in September/October (when sea ice loss has been especially acute), this does not translate to stronger storms because of coincident weakening of wind shear. Sea ice anomalies also have little or no connection to cyclone-associated precipitation in these months. Therefore, future sea ice reductions (e.g., related to delayed autumn freeze-up) will likely enhance Arctic cyclone intensification in winter and spring, but this relationship is sensitive to simultaneous connections between sea ice and wind shear.
Significance Statement
Sea ice is a barrier between the ocean and atmosphere, limiting the exchange of energy between them. As the amount of sea ice in the Arctic Ocean declines, the ocean can transfer more heat to the atmosphere above in fall and winter. It is theorized that this extra energy may help intensify storms that pass through the Arctic. We examine individual storms over the Arctic Ocean and what sea ice conditions they experience as they develop. We find that storms intensify more when sea ice is lower than normal in the winter season only. This relationship may contribute to stronger Arctic winter storms in the future, including heavier precipitation and stronger winds (which can enhance wave heights and coastal erosion).
Geophysical systems are often assumed to follow Gaussian probability density functions; however, deviations from Gaussian behaviour can shed light on the underlying dynamics. For the large-scale ...motion of the Arctic sea ice, such deviations have been interpreted as signatures of structure in dynamic flow fields. In this study, we use higher-order moments (skewness and kurtosis) to identify spatiotemporal changes in the Beaufort Gyre (BG) and the Transpolar Drift (TPD) sea-ice drift patterns. Higher-order moments of satellite-derived ice drift speeds are examined over the winter period of 2006–2017 to describe the persistence of features like the BG and TPD, and their variation over time. Index patterns indicate that the periphery of the BG can be identified by a combination of high positive skewness and high kurtosis in the ice drift time series on an annual basis.
Sea ice drift and deformation, namely sea ice dynamics, play a significant role in atmosphere–ice–ocean coupling. Deformation patterns in sea ice can be observed over a wide range of spatial and ...temporal scales, though high-resolution objective quantification of these features remains difficult. In an effort to better understand local deformation of sea ice, we adapt the trajectory-stretching exponents (TSEs), quasi-objective measures of Lagrangian stretching in continuous media, to sea ice buoy data and develop a temporal analysis of TSE time series. Our work expands on previous ocean current studies that have shown TSEs provide an approximation of Lagrangian coherent structure diagnostics when only sparse trajectory data are available. As TSEs do not require multiple buoys, we find they have an expanded range of use when compared with traditional Eulerian buoy-array deformation metrics and provide local-stretching information below the length scales possible when averaging over buoy arrays. We verify the ability of TSEs to temporally and spatially identify dynamic features for three different sea ice datasets. The ability of TSEs to quantify trajectory stretching is verified by concurrent ice fracture in buoy neighborhoods ranging from tens to hundreds of kilometers in diameter, as well as the temporal concurrence of significant storm events.
A rise in Arctic shipping activity resulting from global warming and resource exploitation is expected to increase the likelihood of aquatic invasive species (AIS) introductions in the region. In ...this context, the potential threat of future AIS incursions at a Canadian Arctic regional scale was examined. Habitat suitability under current environmental conditions and future climate change scenarios was projected for a subset of eight potential invaders ranked as having a high risk of establishment in the Canadian Arctic based on dispersal pathways/donor regions, biological attributes and invasion history: (1)
Amphibalanus improvisus
, (2)
Botrylloides violaceus
, (3)
Caprella mutica
, (4)
Carcinus maenas
, (5)
Littorina littorea
, (6)
Membranipora membranacea
, (7)
Mya arenaria
and (8)
Paralithodes camtschaticus
. Habitat modelling was performed using MaxEnt based on globally known native and non-native occurrence records and environmental ranges for these species. Results showed that under current environmental conditions the habitat is suitable in certain regions of the Canadian Arctic such as the Hudson Complex and Beaufort Sea for
L. littorea
,
M. arenaria
and
P. camtschaticus
. Under a future climate change scenario, all species showed poleward gains in habitat suitability with at least some regions of the Canadian Arctic projected to be suitable for the complete suite of species modelled. The use of these models is helpful in understanding potential future AIS incursions as a result of climate change and shipping at large spatial scales. These approaches can aid in the identification of high risk regions and species to allow for more focused AIS monitoring and research efforts in response to climate change.
Abstract
The seasonal ice-free period in the Hudson Bay Complex (HBC) has grown longer in recent decades in response to warming, both from progressively earlier sea-ice retreat in summer and later ...sea-ice advance in fall. Such changes disrupt the HBC ecosystem and ice-based human activities. In this study, we compare 102 simulations from 37 models participating in phase 6 of the Coupled Model Intercomparison Project to the satellite passive microwave record and atmospheric reanalyses. We show that, throughout the HBC, models simulate an ice-free period that averages 30 d longer than in satellite observations. This occurs because seasonal sea-ice advance is unrealistically late and seasonal sea-ice retreat is unrealistically early. We find that much of the ice-season bias can be linked to a warm bias in the atmosphere that is associated with a southerly wind bias, especially in summer. Many models also exhibit an easterly wind bias during winter and spring, which reduces sea-ice convergence on the east side of Hudson Bay and impacts the spatial patterns of summer sea-ice retreat. These results suggest that, for many models, more realistic simulation of atmospheric circulation would improve their simulation of HBC sea ice.
Abstract
The Arctic seasonal halocline impacts the exchange of heat, energy, and nutrients between the surface and the deeper ocean, and it is changing in response to Arctic sea ice melt over the ...past several decades. Here, we assess seasonal halocline formation in 1975 and 2006–12 by comparing daily, May–September, salinity profiles collected in the Canada Basin under sea ice. We evaluate differences between the two time periods using a one-dimensional (1D) bulk model to quantify differences in freshwater input and vertical mixing. The 1D metrics indicate that two separate factors contribute similarly to stronger stratification in 2006–12 relative to 1975: 1) larger surface freshwater input and 2) less vertical mixing of that freshwater. The larger freshwater input is mainly important in August–September, consistent with a longer melt season in recent years. The reduced vertical mixing is mainly important from June until mid-August, when similar levels of freshwater input in 1975 and 2006–12 are mixed over a different depth range, resulting in different stratification. These results imply that decadal changes to ice–ocean dynamics, in addition to freshwater input, significantly contribute to the stronger seasonal stratification in 2006–12 relative to 1975. These findings highlight the need for near-surface process studies to elucidate the impact of lateral processes and ice–ocean momentum exchange on vertical mixing. Moreover, the results may provide insight for improving the representation of decadal changes to Arctic upper-ocean stratification in climate models that do not capture decadal changes to vertical mixing.
Sea surface temperature (SST) from four Nucleus for European Modelling of the Ocean (NEMO) model simulations is analyzed to study the bulk flux parameterization to compute SST over the Hudson Bay ...Complex (HBC) for the summer months (August and September) from 2002 to 2009. The NEMO simulation was forced with two atmospheric forcing sets with different resolutions: the Coordinated Ocean-ice Reference Experiment, version 2 (COREv2), as the lower resolution and the Canadian Meteorological Centre's Global Deterministic Prediction System Reforecasts (CGRF) as the higher resolution. The CGRF forcing is also implemented in the third and fourth runs using different runoff data and different NEMO resolutions (1/12° versus 1/4°). Results show that all four modelled SSTs followed observed SST patterns, with regional differences in SST bias between simulations with different atmospheric forcing. The SST differences are small between simulations forced with the same atmospheric forcing but with different model resolution or runoff. This implies that the model resolution and runoff have a small effect on the simulated SST in the HBC. Moreover, to better capture the effect of near-surface temperature (T
air
) on simulated SST, we conducted three analyses using the Haney flux linearization formula. Results from these assessments did not indicate any direct influence on the model-simulated SSTs by T
air
. Looking at the heat flux as a signature for SST showed that both averaged spatial distribution and time series of net heat flux produced by the three CGRF forcing simulations were higher than the net heat flux generated by the CORE 2 simulation. This was generally true for all four components of the total heat flux (sensible, latent, shortwave, and longwave) individually as well. Total heat flux in summer is governed by the shortwave heat flux, with values up to 120 W m
−2
in August, and the longwave heat flux is the main contributor to the total heat flux differences. These heat flux differences lead to corresponding colder model SSTs for the CGRF runs and warmer SSTs for the CORE 2 simulations.
Pulses of ocean primary productivity during the fall season are frequent in the mid-latitudes when ocean cooling and wind-driven turbulence erode the surface stratification and allow the injection of ...nutrients into the euphotic zone. This phenomenon is often referred to as a phytoplankton fall bloom, and can play an essential role in the survival of marine species during winter. In Hudson Bay, we found that pelagic fall blooms are triggered when the convective mixing, forced mainly by atmospheric cooling and to a lesser extent to wind-driven turbulence, expands the mixed layer, ventilates the pycnocline, and likely erodes the nitracline. Ocean color observations were used to assess the seasonal variability of phytoplankton photo-acclimation state from the ratio of phytoplankton carbon (Cphy) to chlorophyll-a concentration (chla). Cphy was estimated using the satellite-derived particulate backscattering coefficient (bbp) after subtraction of the non-algal backscattering background. We found a systematic increase in Cphy and Cphy:chla from mid-summer to fall season indicating that fall blooms are potentially productive in term of organic carbon fixation.
The Beaufort Gyre (BG) typically rotates anticyclonically and exerts an important control on Arctic Sea ice dynamics. Previous studies have shown reversals in the BG to rotate cyclonically during ...summer months and, in recent decades, throughout the annual cycle. In this investigation, we explore the synoptic climatology of atmospheric forcing and its relationship to sea ice motion and BG reversals. A catalog of daily synoptic weather types is generated for the Beaufort Sea Region covering the period 1979 to 2006 using NCEP/NCAR reanalysis mean sea level pressure data, principle components, and k‐means cluster analyses. Mean synoptic type frequency, persistence, and duration values are calculated for each synoptic type and contrasted between the summer and winter seasons. Daily synoptic types are linked to changes in sea ice vorticity by using correlation analysis on lagged sea ice vorticity data. Lag correlations are found between synoptic types and sea ice vorticity smoothed over a 12‐week running mean and show that cyclonic types, which promote southerly or easterly atmospheric circulation over the southern Beaufort Sea, commonly precede summer reversals. Furthermore, significant seasonal within‐type variability in sea ice vorticity is detected within the synoptic types illustrating the importance of seasonal variability on these processes.
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