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At least 289 records · Page 16

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↗

Predicting September Arctic Sea Ice: A Multimodel Seasonal Skill Comparison

This study quantifies the state of the art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multimodel dataset of retrospective seasonal predictions of September Arctic sea ice is created and analyzed, consisting of community contributions from 17 statistical models and 17 dynamical models. Prediction skill is compared over the period 2001–20 for predictions of pan-Arctic sea ice extent (SIE), regional SIE, and local sea ice concentration (SIC) initialized on 1 June, 1 July, 1 August, and 1 September. This diverse set of statistical and dynamical models can individually predict linearly detrended pan-Arctic SIE anomalies with skill, and a multimodel median prediction has correlation coefficients of 0.79, 0.86, 0.92, and 0.99 at these respective initialization times. Regional SIE predictions have similar skill to pan-Arctic predictions in the Alaskan and Siberian regions, whereas regional skill is lower in the Canadian, Atlantic, and central Arctic sectors. The skill of dynamical and statistical models is generally comparable for pan-Arctic SIE, whereas dynamical models outperform their statistical counterparts for regional and local predictions. The prediction systems are found to provide the most value added relative to basic reference forecasts in the extreme SIE years of 1996, 2007, and 2012. SIE prediction errors do not show clear trends over time, suggesting that there has been minimal change in inherent sea ice predictability over the satellite era. Overall, this study demonstrates that there are bright prospects for skillful operational predictions of September sea ice at least 3 months in advance.

54 ENVIRONMENTAL SCIENCES↗

Diversity and Distribution of Hydrocarbon-Degrading Genes in the Cold Seeps from the Mediterranean and Caspian Seas

Marine cold seeps are unique ecological niches characterized by the emergence of hydrocarbons, including methane, which fosters diverse microbial communities. This study investigates the diversity and distribution of hydrocarbon-degrading genes and organisms in sediments from the Caspian and Mediterranean Seas, utilizing 16S rRNA and metagenomic sequencing to elucidate microbial community structure and functional potential. Our findings reveal distinct differences in hydrocarbon degrading gene profiles between the two seas, with pathways for aerobic and anaerobic hydrocarbon degradation co-existing in sediments from both basins. Aerobic pathways predominate in the surface sediments of the Mediterranean Sea, while anaerobic pathways are favored in the surface sediments of the anoxic Caspian Sea. Additionally, sediment depths significantly influence microbial diversity, with variations in gene abundance and community composition observed at different depths. Aerobic hydrocarbon-degrading genes decrease in diversity with depth in the Mediterranean Sea, whereas the diversity of aerobic hydrocarbon-degrading genes increases with depth in the Caspian Sea. These results enhance our understanding of microbial ecology in cold seep environments and have implications for bioremediation practices targeting hydrocarbon pollutants in marine ecosystems.

Microbiology↗

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.↗

The 14 month wind stressed residual circulation (pole tide) in the North Sea

From published research it is known that a quasi-periodic 14 month atmospheric pressure oscillation of a few tenths of a millibar exists in the region of the North and Baltic Seas. At some time in the cycle the associated wind stress has a westerly component that drives a circulation in the North Sea. The results of a dynamical model and comparisons with several North Sea residual circulation studies show that a large sea level gradient results along the Dutch coast. It is this feature that has been referred to as the enhanced pole tide. The dynamical similarity of this pole tide in the North and Baltic Seas to the annual and seasonal wind forced circulations is considered. It is inferred that the large deviations of the pole tide from equilibrium at coastal stations are the result of this sea level set up forces by the 14 month wind stress cycle.

Oconnor, W. P.↗

Large-scale short-period sea ice atmosphere interaction

Changes in the microwave brightness temperature measured by the Electrically Scanning Microwave Radiometer (ESMR) flown on board the Nimbus V satellite reveal large-scale sea ice fluctuations in the Antarctic marginal ice zone. These ice margin fluctuations arre predominantly wave numbers 1-4, with phase speeds of about 3 m/s independent of wave number. The spatial pattern and eastward advection of the sea ice anomalies match those of the atmospheric sea level pressure, and are consistent with sea ice displacement due to surface wind stress. Examination of the outgoing longwave radiation indicates that suppression of high clouds in regions of increased sea ice inc reases the radiative cooling which contributes to maintaining the ice. Data from three winter seasons indicate about a one-third probability of occurence of this large scale high frequency sea ice atmosphere interaction during any given 2-week period in winter.

Cahalan, Robert F.↗

A microwave radiometer weather-correcting sea ice algorithm

A new algorithm for estimating the proportions of the multiyear and first-year sea ice types under variable atmospheric and sea surface conditions is presented, which uses all six channels of the SMMR. The algorithm is specifically tuned to derive sea ice parameters while accepting error in the auxiliary parameters of surface temperature, ocean surface wind speed, atmospheric water vapor, and cloud liquid water content. Not only does the algorithm naturally correct for changes in these weather conditions, but it retrieves sea ice parameters to the extent that gross errors in atmospheric conditions propagate only small errors into the sea ice retrievals. A preliminary evaluation indicates that the weather-correcting algorithm provides a better data product than the 'UMass-AES' algorithm, whose quality has been cross checked with independent surface observations. The algorithm performs best when the sea ice concentration is less than 20 percent.

Walters, J. M.↗