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At least 271 records · Page 15

Sea Ice Deformation Is Not Scale Invariant Over Length Scales Greater Than A Kilometer

In March and April 2021, buoys were deployed in the Beaufort Sea, Arctic Ocean, to measure sea-ice horizontal deformation over spatial scales that had not been previously achieved. Geodetic-quality position measurements allowed measurements of strain-rate over lengths from about 200 m to 2 km. Conventional ice-drifters extended spatial coverage up to about 100 km. Past studies find there is multi-fractal behavior for horizontal sea-ice deformation from 10 to 1000 km. Our results demonstrate that such behavior does not hold when including spatial scales below 10 km. We find that sea-ice deformation is not scale in variant between the scale of individual sea-ice floes and aggregates of floes. Therefore, we cannot expect the same physical laws or forcing to describe sea-ice kinematics over these regimes, nor can we assume log-log linear behavior for mean deformation. Using this scaling behavior as a metric to validate models that resolve sea ice floes and their interactions is hence not recommended.

Jennifer K. Hutchings↗

Evaluation of Arctic Sea Ice Thickness Simulated by Arctic Ocean Model Intercomparison Project Models

Six Arctic Ocean Model Intercomparison Project model simulations are compared with estimates of sea ice thickness derived from pan-Arctic satellite freeboard measurements (2004-2008); airborne electromagnetic measurements (2001-2009); ice draft data from moored instruments in Fram Strait, the Greenland Sea, and the Beaufort Sea (1992-2008) and from submarines (1975-2000); and drill hole data from the Arctic basin, Laptev, and East Siberian marginal seas (1982-1986) and coastal stations (1998-2009). Despite an assessment of six models that differ in numerical methods, resolution, domain, forcing, and boundary conditions, the models generally overestimate the thickness of measured ice thinner than approximately 2 mand underestimate the thickness of ice measured thicker than about approximately 2m. In the regions of flat immobile landfast ice (shallow Siberian Seas with depths less than 25-30 m), the models generally overestimate both the total observed sea ice thickness and rates of September and October ice growth from observations by more than 4 times and more than one standard deviation, respectively. The models do not reproduce conditions of fast ice formation and growth. Instead, the modeled fast ice is replaced with pack ice which drifts, generating ridges of increasing ice thickness, in addition to thermodynamic ice growth. Considering all observational data sets, the better correlations and smaller differences from observations are from the Estimating the Circulation and Climate of the Ocean, Phase II and Pan-Arctic Ice Ocean Modeling and Assimilation System models.

sea ice↗

Sea Ice Thickness, Freeboard, and Snow Depth products from Operation IceBridge Airborne Data

The study of sea ice using airborne remote sensing platforms provides unique capabilities to measure a wide variety of sea ice properties. These measurements are useful for a variety of topics including model evaluation and improvement, assessment of satellite retrievals, and incorporation into climate data records for analysis of interannual variability and long-term trends in sea ice properties. In this paper we describe methods for the retrieval of sea ice thickness, freeboard, and snow depth using data from a multisensor suite of instruments on NASA's Operation IceBridge airborne campaign. We assess the consistency of the results through comparison with independent data sets that demonstrate that the IceBridge products are capable of providing a reliable record of snow depth and sea ice thickness. We explore the impact of inter-campaign instrument changes and associated algorithm adaptations as well as the applicability of the adapted algorithms to the ongoing IceBridge mission. The uncertainties associated with the retrieval methods are determined and placed in the context of their impact on the retrieved sea ice thickness. Lastly, we present results for the 2009 and 2010 IceBridge campaigns, which are currently available in product form via the National Snow and Ice Data Center

sea ice thickness↗

A New Study of Sea Spray Optical Properties from Multi-Sensor Spaceborne Observations

Retrievals of aerosol optical depth (AOD) from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite sensor require the assumption of an extinction-to-backscatter ratio, also known as the lidar ratio. This paper evaluates a new method to calculate lidar ratio of sea spray aerosol using two independent sources: the AOD from Synergized Optical Depth of Aerosols (SODA) and the integrated attenuated backscatter from CALIOP. The method applied in this study allows particulate lidar ratio to be calculated for individual CALIOP retrievals of single aerosol layer columns over the ocean. Analyses are carried out using CALIOP level 2, 5km sea spray aerosol layer products and collocated SODA nighttime data from December 2007 to December 2009. The global mean lidar ratio for sea spray aerosols was found to be 26 sr, roughly 30 higher than the one prescribed by CALIOP. Data analysis also showed considerable spatiotemporal variability in calculated lidar ratio over different parts of the remote oceans. The calculated aerosol lidar ratios are shown to be inversely related to the mean ocean surface wind speed: increase in ocean surface wind speed (U10) from 0 to 15 ms-1 reduces the mean lidar ratios for sea spray particles from 32 sr (for 0 U10 4 ms-1) to 22 sr (for U10 15 ms-1). Such changes in the lidar ratio are expected to have a corresponding effect on sea spray AOD. The outcomes of this study are relevant for future improvements of the SODA and CALIOP operational product and could lead to more accurate retrievals of sea spray AOD.

aerosol optical depth↗

Teleconnections, Midlatitude Cyclones and Aegean Sea Turbulent Heat Flux Variability on Daily Through Decadal Time Scales

We analyze daily wintertime cyclone variability in the central and eastern Mediterranean during 1958-2001, and identify four distinct cyclone states, corresponding to the presence or absence of cyclones in each basin. Each cyclone state is associated with wind flows that induce characteristic patterns of cooling via turbulent (sensible and latent) heat fluxes in the eastern Mediterranean basin and Aegean Sea. The relative frequency of occurrence of each state determines the heat loss from the Aegean Sea during that winter, with largest heat losses occurring when there is a storm in the eastern but not central Mediterranean (eNOTc), and the smallest occurring when there is a storm in the central but not eastern Mediterranean (cNOTe). Time series of daily cyclone states for each winter allow us to infer Aegean Sea cooling for winters prior to 1985, the earliest year for which we have daily heat flux observations. We show that cyclone states conducive to Aegean Sea convection occurred in 1991/1992 and 1992/1993, the winters during which deep water formation was observed in the Aegean Sea, and also during the mid-1970s and the winters of 1963/1964 and 1968/1969. We find that the eNOTc cyclone state is anticorrelated with the North Atlantic Oscillation (NAO) prior to 1977/1978. After 1977/1978, the cNOTe state is anticorrelated with both the NAO and the North Caspian Pattern (NCP), showing that the area of influence of large scale atmospheric teleconnections on regional cyclone activity shifted from the eastern to the central Mediterranean during the late 1970s. A trend toward more frequent occurrence of the positive phase of the NAO produced less frequent cNOTe states since the late 1970s, increasing the number of days with strong cooling of the Aegean Sea surface waters.

cyclones↗

Revisiting the Potential of Melt Pond Fraction as a Predictor for the Seasonal Arctic Sea Ice Extent Minimum

The rapid change in Arctic sea ice in recent decades has led to a rising demand for seasonal sea ice prediction. A recent modeling study that employed a prognostic melt pond model in a stand-alone sea ice model found that September Arctic sea ice extent can be accurately predicted from the melt pond fraction in May. Here we show that satellite observations show no evidence of predictive skill in May. However, we find that a significantly strong relationship (high predictability) first emerges as the melt pond fraction is integrated from early May to late June, with a persistent strong relationship only occurring after late July. Our results highlight that late spring to mid summer melt pond information is required to improve the prediction skill of the seasonal sea ice minimum. Furthermore, satellite observations indicate a much higher percentage of melt pond formation in May than does the aforementioned model simulation, which points to the need to reconcile model simulations and observations, in order to better understand key mechanisms of melt pond formation and evolution and their influence on sea ice state.

sea ice↗

Ice Melt, Sea Level Rise and Superstorms: Evidence from Paleoclimate Data, Climate Modeling, and Modern Observations that 2C Global Warming Could Be Dangerous

We use numerical climate simulations, paleoclimate data, and modern observations to study the effect of growing ice melt from Antarctica and Greenland. Meltwater tends to stabilize the ocean column, inducing amplifying feedbacks that increase subsurface ocean warming and ice shelf melting. Cold meltwater and induced dynamical effects cause ocean surface cooling in the Southern Ocean and North Atlantic, thus increasing Earth's energy imbalance and heat flux into most of the global ocean's surface. Southern Ocean surface cooling, while lower latitudes are warming, increases precipitation on the Southern Ocean, increasing ocean stratification, slowing deepwater formation, and increasing ice sheet mass loss. These feedbacks make ice sheets in contact with the ocean vulnerable to accelerating disintegration. We hypothesize that ice mass loss from the most vulnerable ice, sufficient to raise sea level several meters, is better approximated as exponential than by a more linear response. Doubling times of 10, 20 or 40 years yield multi-meter sea level rise in about 50, 100 or 200 years. Recent ice melt doubling times are near the lower end of the 10-40-year range, but the record is too short to confirm the nature of the response. The feedbacks, including subsurface ocean warming, help explain paleoclimate data and point to a dominant Southern Ocean role in controlling atmospheric CO2, which in turn exercised tight control on global temperature and sea level. The millennial (500-2000-year) timescale of deep-ocean ventilation affects the timescale for natural CO2 change and thus the timescale for paleo-global climate, ice sheet, and sea level changes, but this paleo-millennial timescale should not be misinterpreted as the timescale for ice sheet response to a rapid, large, human-made climate forcing. These climate feedbacks aid interpretation of events late in the prior interglacial, when sea level rose to C6-9m with evidence of extreme storms while Earth was less than 1 C warmer than today. Ice melt cooling of the North Atlantic and Southern oceans increases atmospheric temperature gradients, eddy kinetic energy and baroclinicity, thus driving more powerful storms. The modeling, paleoclimate evidence, and ongoing observations together imply that 2 C global warming above the preindustrial level could be dangerous. Continued high fossil fuel emissions this century are predicted to yield (1) cooling of the Southern Ocean, especially in the Western Hemisphere; (2) slowing of the Southern Ocean overturning circulation, warming of the ice shelves, and growing ice sheet mass loss; (3) slowdown and eventual shutdown of the Atlantic overturning circulation with cooling of the North Atlantic region; (4) increasingly powerful storms; and (5) nonlinearly growing sea level rise, reaching several meters over a timescale of 50-150 years. These predictions, especially the cooling in the Southern Ocean and North Atlantic with markedly reduced warming or even cooling in Europe, differ fundamentally from existing climate change assessments. We discuss observations and modeling studies needed to refute or clarify these assertions.

Computer simulation↗

Importance of Atmospheric Feedbacks in Simulating the Seasonal Cycle of the Antarctic Sea Ice and Its Response to Perturbations

The seasonal cycle of the Antarctic sea ice extent is largely controlled by the evolution of the insolation received at the top of the atmosphere. However, sea ice processes and feedbacks with the ocean and the atmosphere can modulate this seasonal cycle. Here, the atmospheric feedbacks are quantified in a series of idealized sensitivity experiments performed with an eddy-permitting (1/4°) NEMO-LIM3 Southern Ocean configuration, including a representation of ice shelf cavities, in which the model was either driven by an atmospheric reanalysis or coupled to the COSMO-CLM 2 regional atmospheric model. In these experiments, sea ice thermodynamics and dynamics as well as the exchanges with the ocean and atmosphere are strongly perturbed. This perturbation is achieved by modifying snow and ice thermal conductivities, the vertical mixing in the ocean top layers, the effect of freshwater uptake/release upon sea ice growth/melt, ice dynamics and surface albedo. We show that the changes in surface heat fluxes are very different between the configurations driven by the reanalysis and those coupled to the atmosphere. Atmospheric feedbacks enhance the response of the modelled winter ice extent to any of the perturbed processes, and the enhancement is strongest when the albedo is modified. The response of sea ice volume and extent to changes in entrainment of subsurface warm waters to the ocean surface is also greatly amplified by the coupling with the atmosphere. By contrast, the atmospheric feedbacks can damp the impact of the perturbations affecting the heat conductivity through sea ice.

Atmospheric feedbacks↗

Sea Ice Concentration and Extent

Among the most seasonal and most dynamic parameters on the surface of the Earth is sea ice which at any one time covers about 3-6% of the planet. In the Northern Hemisphere, sea ice grows in extent from about 6 x 10(exp 6) sq km to 16 x 10(exp 6) sq km, while in the Southern Hemisphere, it grows from about 3 x 10(exp 6) sq km to about 19 x 10(exp 6) sq km (Comiso, 2010; Gloersen et al., 1992). Sea ice is up to about 2-3 m thick in the Northern Hemisphere and about 1 m thick in the Southern Hemisphere (Wadhams, 2002), and compared to the average ocean depth of about 3 km, it is a relatively thin, fragile sheet that can break due to waves and winds or melt due to upwelling of warm water. Being constantly advected by winds, waves, and currents, sea ice is very dynamic and usually follows the directions of the many gyres in the polar regions. Despite its vast expanse, the sea ice cover was previously left largely unstudied and it was only in recent years that we have understood its true impact and significance as related to the Earths climate, the oceans, and marine life.

sea ice extent↗

An Evaluation of Sea Surface Temperature as Measured by the Nimbus 1 High Resolution Infrared Radiometer

An analysis of Nimbus I HRIR data over various parts of the world indicated limited success in deriving sea surface temperatures to within 3 to 6 K of aircraft radiation measurements (8- 13 microns) and synoptic-climatological ship sea surface temperature data. The areas studied included the east, west and Gulf coasts of the United States, West Greenland, Nova Scotia, southern Japan, the eastern Mediterranean Sea, Caspian Sea, Persian Gulf, and the Indian Ocean. At night, thin clouds which may fill the radiometer's field of view make it difficult to interpret the absolute values of derived sea surface temperature. During the daytime, the HRIR data is unusable for oceanographic temperature analysis because the contamination by reflected solar radiation mixes with the emitted radiation. Future satellite instrumentation, consisting of a HFUR radiometer (10-11 microns) when used in conjunction with television. data, will delineate cloud free ocean areas and permit the daily derivation of sea surface temperatures from approximately 10 to 30 Percent of the world's oceanic regions.

Allison, Lewis J.↗

Monitoring Arctic Sea ice using ERTS imagery

Because of the effect of sea ice on the heat balance of the Arctic and because of the expanding economic interest in arctic oil and other minerals, extensive monitoring and further study of sea ice is required. The application of ERTS data for mapping ice is evaluated for several arctic areas, including the Bering Sea, the eastern Beaufort Sea, parts of the Canadian Archipelago, and the Greenland Sea. Interpretive techniques are discussed, and the scales and types of ice features that can be detected are described. For the Bering Sea, a sample of ERTS imagery is compared with visual ice reports and aerial photography from the NASA CV-990 aircraft.

Barnes, J. C.↗

Investigation of radar discrimination of sea ice

The ability of radar to discriminate sea ice types and their thickness was studied. Radar backscatter measurements at 400 MHz (multi-polarization) and 13.3 GHz (VV polarization) obtained from NASA Earth Resources Aircraft Program Mission 126 were analyzed in detail. The scatterometer data were separated into seven categories of sea ice according to age and thickness as interpreted from stereo aerial photographs. The variations of radar backscatter cross-section with sea ice thickness at various angles are presented at the two frequencies. There is a reversal of angular character of radar return from sea ice less than 18 cm thick at the two frequencies. Multi-year ice (sea ice greater than 180 cm thick) gives strongest return at 13.3 GHz. First-year ice (30 cm to 90 cm thick) gives strongest return at 400 MHz. Open water can be differentiated at both the frequencies. Four-polarization 16.5 GHz radar imagery was also obtained. Open water and three categories of sea ice can be identified on the images. The results of the imagery analysis are consistent with the radar scatterometer results.

Parashar, S. K.↗

A theory of sea scatter at large incident angles

Radar sea scatter at large incident angles (30 deg or greater) is investigated using a model which takes into account theoretically-calculated small- and large-scale wave perturbations as well as measured sea surface slope densities and sea spectra obtained from empirical observations. Effects of incident angle, polarization, frequency, wind speed and anisotropic characteristics of the sea surface may be studied by application of the model. In particular, it is found that the increase in backscattering coefficients with wind velocity is due primarily to the growth of the sea spectrum and secondarily to the interaction between small- and large-scale perturbations. Furthermore, differences in upwind and downwind observations may be attributed to anisotropic properties of the sea spectrum. Theoretical findings derived from the model are compared with experimental data, and good agreement is found.

Chan, H. L.↗

Time-dependence of sea-ice concentration and multiyear ice fraction in the Arctic Basin

Microwave images of sea ice obtained by Nimbus-5 and the NASA CV-990 airborne laboratory are used to determine the time variation of the sea-ice concentration and multiyear ice fraction within the pack ice in the Arctic Basin. The images, constructed from data acquired from the electrically scanned microwave radiometer, are analyzed for four seasons during 1973-1975. Observations indicate significant variations in the sea-ice concentration in the spring, late fall, and early winter. Sea-ice concentrations as low as 50% were detected in large areas in the interior of the Arctic polar sea-ice pack. The applicability of passive-microwave remote sensing for monitoring the time dependence of sea-ice concentration is considered.

Gloersen, P.↗

The response of the Goddard general circulation model to sea ice boundary conditions

The effect of variation in the location of Arctic sea ice boundaries on the model's mean monthly climatology was examined. When sea ice boundaries were at their maximum extent the differences resulted in the January-February climatology. Sea level pressure was higher over the Barents Sea, in the Davis Strait, and in the Sea of Okhotsk. Pressure was lower by as much as 8 mb in the North Atlantic between Iceland and the British Isles, and in the Gulf of Alaska. Pressure rises in the eastern subtropical regions of the North Atlantic and North Pacific accompanied pressure falls in the Gulf of Alaska and Icelandic region. Geopotential heights at 500 mb were more than 100 gpm lower in the Bering Sea, and more than 120 gpm lower in the Icelandic region. Zonally averaged temperatures were cooler by 4 deg C below 3800 mb between 50 deg and 70 deg N with little change elsewhere. Zonally averaged geopotentials were lower by as much as 70 gpm in the mid-troposphere between 50/-70 deg N and zonal winds increased by as much as 3 m s in the mid-troposphere between 35/-50 deg N.

Herman, G.↗

An optical model for the microwave properties of sea ice

The complex refractive index of sea ice is modeled and used to predict the microwave signatures of various sea ice types. Results are shown to correspond well with the observed values of the complex index inferred from dielectic constant and dielectric loss measurements performed in the field, and with observed microwave signatures of sea ice. The success of this modeling procedure vis a vis modeling of the dielectric properties of sea ice constituents used earlier by several others is explained. Multiple layer radiative transfer calculations are used to predict the microwave properties of first-year sea ice with and without snow, and multiyear sea ice.

Gloersen, P.↗

Global mean sea level - Indicator of climate change

A critical discussion is presented on the use by Etkins and Epstein (1982) of combined surface air temperature and sea level time series to draw conclusions concerning the discharge of the polar ice sheets. It is objected by Robock that they used Northern Hemisphere land surface air temperature records which are unrepresentative of global sea surface temperature, and he suggests that externally imposed volcanic dust and CO2 forcings can adequately account for observed temperature changes over the last century, with global sea level changing in passive response to sea change as a result of thermal expansion. Hansen et al. adduce evidence for global cooling due to ice discharge that has not exceeded a few hundredths of a degree centigrade in the last century, precluding any importance of this phenomenon in the interpretation of global mean temperature trends for this period. Etkins and Epstein reply that since their 1982 report additional evidence has emerged for the hypothesis that the polar ice caps are diminishing. It is reasserted that each of the indices discussed, including global mean sea surface temperature and sea level, polar ice sheet mass balance, water mass characteristics, and the spin rate and axis of rotation displacement of the earth, are physically linked and can be systematically monitored, as is currently being planned under the auspices of the National Climate Program.

Robock, A.↗

Antartic sea ice, 1973 - 1976: Satellite passive-microwave observations

Data from the Electrically Scanning Microwave Radiometer (ESMR) on the Nimbus 5 satellite are used to determine the extent and distribution of Antarctic sea ice. The characteristics of the southern ocean, the mathematical formulas used to obtain quantitative sea ice concentrations, the general characteristics of the seasonal sea ice growth/decay cycle and regional differences, and the observed seasonal growth/decay cycle for individual years and interannual variations of the ice cover are discussed. The sea ice data from the ESMR are presented in the form of color-coded maps of the Antarctic and the southern oceans. The maps show brightness temperatures and concentrations of pack ice averaged for each month, 4-year monthly averages, and month-to-month changes. Graphs summarizing the results, such as areas of sea ice as a function of time in the various sectors of the southern ocean are included. The images demonstrate that satellite microwave data provide unique information on large-scale sea ice conditions for determining climatic conditions in polar regions and possible global climatic changes.

Zwally, H. J.↗