Sea Ice Fraction Research Articles

Evaluations of Land–Ocean Skin Temperatures of the ISCCP Satellite Retrievals and the NCEP and ERA Reanalyses

Abstract This study evaluates the skin temperature (ST) datasets of the International Satellite Cloud Climatology Project (ISCCP) D satellite product, the ISCCP FD satellite product, the 40-yr ECMWF Re-Analysis (ERA-40), the NCEP–NCAR Reanalysis, and the NCEP–Department of Energy (DOE) Atmospheric Model Intercomparison Project (AMIP)-II Reanalysis. The monthly anomalies of all the datasets are correlated to each other and to most of the ground-truth stations with correlation coefficients >0.50. To evaluate their qualities, the 5 ST datasets are used to calculate clear-sky (CS) outgoing longwave radiation (OLR) and upward surface longwave radiation (USLR); the results are compared with the Earth Radiation Budget Experiment (ERBE) satellite observation and 14 surface stations. The satellite-derived STs and ERA-40 ST tend to bias high on hot deserts (e.g., Sahara Desert), and the reanalyzed STs tend to bias low in mountain areas (e.g., Tibet). In Northern Hemisphere high-latitude regions (tundra, wetlands, deciduous needle-leaf forests, and sea ice), the CS OLR anomalies calculated using the satellite-derived STs have higher correlations and lower root-mean-squared errors with the ERBE satellite observation than those derived from using the reanalyzed STs. ERA-40 underestimates the amplitude of the seasonal ST over glaciers. All the reanalysis products (ERA-40, NCEP–NCAR, and NCEP–DOE AMIP-II) overestimate the ST during partial sea ice–covered periods in the middle-high-latitude oceans. Nonetheless, suspected spurious noises with an amplitude of 2 K in the satellite-derived STs produce a physically unviable anomaly over earth’s surface where the amplitude of the anomaly is weak (such as open-water bodies, croplands, rain forest, grasslands, hot deserts, and cold deserts). Better land–ocean–ice schemes for a reanalysis should be developed for desert regions, high plateaus, fractional sea ice–covered oceans, and seasonally snow-covered lands, where the largest ST errors are identified.

An investigation into the forces that drive ice-shelf rift propagation on the Amery Ice Shelf, East Antarctica

AbstractFor three field seasons (2002/03, 2004/05, 2005/06) we have deployed a network of GPS receivers and seismometers around the tip of a propagating rift on the Amery Ice Shelf, East Antarctica. During these campaigns we detected seven bursts of episodic rift propagation. To determine whether these rift propagation events were triggered by short-term environmental forcings, we analyzed simultaneous ancillary data such as wind speeds, tidal amplitudes and sea-ice fraction (a proxy variable for ocean swell). We find that none of these environmental forcings, separately or together, correlated with rift propagation. This apparent insensitivity of ice-shelf rift propagation to short-term environmental forcings leads us to suggest that the rifting process is primarily driven by the internal glaciological stress. Our hypothesis is supported by order-of-magnitude calculations that the glaciological stress is the dominant term in the force balance. However, our calculations also indicate that as the ice shelf thins or the rift system matures and iceberg detachment becomes imminent, short-term stresses due to winds and ocean swell may become more important.

Combined oceanic and atmospheric influences on net accumulation on Devon Ice Cap, Nunavut, Canada

AbstractAn annual net accumulation history of the high-elevation region of Devon Ice Cap, Nunavut, Canada, was reconstructed for the period 1963–2003 using five shallow firn cores. Annual net accumulation decreased significantly after 1989. To explain variability in the reconstructed annual net accumulation record, monthly and seasonal moisture-source probabilities were calculated for gridcells throughout the Arctic during 1979–2003. Seasonally, moisture-source probabilities reach a maximum in northern Baffin Bay in late summer/early fall and approach zero throughout the Arctic in winter. Late-summer/early-fall moisture-source probabilities were significantly higher around the North Open Water (NOW) Polynya during the 4 year period of highest annual net accumulation during the 1979–2003 period (1984–87), than during the 4 year period with the lowest annual net accumulation (1994–97). This is due to both a significant decrease in the sea-ice fraction and a significant increase in low-elevation atmospheric transport over the NOW area during the high net accumulation period. Anomalously low net accumulation and anomalously high firnification rates during the 1989–2003 period suggest that a change in ice dynamics, rather than a change in surface mass balance, may explain recent ice-cap thickening observed by laser altimetry.

Influence of sea ice on the atmosphere: A study with an Arctic atmospheric regional climate model

The impact of the lower‐boundary forcing over ocean grid points, namely of sea surface temperature (SST), sea ice fraction, and sea ice thickness, on the mean atmospheric simulation is investigated with an Arctic atmospheric regional climate model. The assessment shows that the sea ice/SST forcing has an impact on the atmospheric simulations. The near‐surface air temperature response shows a strong, seasonally dependent sensitivity to sea ice changes. The response is small in summer but significant in winter, and changes in the marginal ice zone have the largest impact on the atmosphere. During winter, the realistic representation of the marginal sea ice zone is important as it contributes to the simulation of regional atmospheric circulation patterns and temperature profiles. Changes in sea ice thickness of the western Arctic lower boundary indicate an Arctic‐wide response in the large‐scale circulation and seem to have an impact on the troposphere‐stratosphere coupling. During summer the direct thermodynamic effect of sea ice changes is small, while the dynamic response is still of importance but smaller than in winter.

The Atmospheric Impact of Uncertainties in Recent Arctic Sea Ice Reconstructions

Abstract There are significant discrepancies between observational datasets of Arctic sea ice concentrations covering the last three decades, which result in differences of over 20% in Arctic summer sea ice extent/area and 5%–10% in winter. Previous modeling studies have shown that idealized sea ice anomalies have the potential for making a substantial impact on climate. In this paper, this theory is further developed by performing a set of simulations using the third Hadley Centre Coupled Atmospheric Model (HadAM3). The model was driven with monthly climatologies of sea ice fractions derived from three of these records to investigate potential implications of sea ice inaccuracies for climate simulations. The standard sea ice climatology from the Met Office provided a control. This study focuses on the effects of actual inaccuracies of concentration retrievals, which vary spatially and are larger in summer than winter. The smaller sea ice discrepancies in winter have a much larger influence on climate than the much greater summer sea ice differences. High sensitivity to sea ice prescription was observed, even though no SST feedbacks were included. Significant effects on surface fields were observed in the Arctic, North Atlantic, and North Pacific. Arctic average surface air temperature anomalies in winter vary by 2.5°C, and locally exceed 12°C. Arctic mean sea level pressure varies by up to 5 mb locally. Anomalies extend to 45°N over North America and Eurasia but not to lower latitudes, and with limited changes in circulation above the boundary layer. No statistically significant impact on climate variability was simulated, in terms of the North Atlantic Oscillation. Results suggest that the uncertainty in summer sea ice prescription is not critical but that winter values require greater accuracy, with the caveats that the influences of ocean–sea ice feedbacks were not included in this study.

Atlantic Thermohaline Circulation in a Coupled General Circulation Model: Unforced Variations versus Forced Changes

Abstract A 1200-yr unforced control run and future climate change simulations using the Parallel Climate Model (PCM), a coupled atmosphere–ocean–land–sea ice global model with no flux adjustments and relatively high resolution (∼2.8° for the atmosphere and 2/3° for the oceans) are analyzed for changes in Atlantic Ocean circulations. For the forced simulations, historical greenhouse gas and sulfate forcing of the twentieth century and projected forcing for the next two centuries are used. The Atlantic thermohaline circulation (THC) shows large multidecadal (15–40 yr) variations with mean-peak amplitudes of 1.5–3.0 Sv (1 Sv ≡ 106 m3 s−1) and a sharp peak of power around a 24-yr period in the control run. Associated with the THC oscillations, there are large variations in North Atlantic Ocean heat transport, sea surface temperature (SST) and salinity (SSS), sea ice fraction, and net surface water and energy fluxes, which all lag the variations in THC strength by 2–3 yr. However, the net effect of the SST and SSS variations on upper-ocean density in the midlatitude North Atlantic leads the THC variations by about 6 yr, which results in the 24-yr period. The simulated SST and sea ice spatial patterns associated with the THC oscillations resemble those in observed SST and sea ice concentrations that are associated with the North Atlantic Oscillation (NAO). The results suggest a dominant role of the advective mechanism and strong coupling between the THC and the NAO, whose index also shows a sharp peak around the 24-yr time scale in the control run. In the forced simulations, the THC weakens by ∼12% in the twenty-first century and continues to weaken by an additional ∼10% in the twenty-second century if CO2 keeps rising, but the THC stabilizes if CO2 levels off. The THC weakening results from stabilizing temperature increases that are larger in the upper and northern Atlantic Ocean than in the deep and southern parts of the basin. In both the control and forced simulations, as the THC gains (loses) strength and depth, the separated Gulf Stream (GS) moves southward (northward) while the subpolar gyre centered at the Labrador Sea contracts from (expands to) the east with the North Atlantic Current (NAC) being shifted westward (eastward). These horizontal circulation changes, which are dynamically linked to the THC changes, induce large temperature and salinity variations around the GS and NAC paths.

Top‐of‐atmosphere shortwave broadband observed radiance and estimated irradiance over polar regions from Clouds and the Earth's Radiant Energy System (CERES) instruments on Terra

Empirical angular distribution models for estimating top‐of‐atmosphere shortwave irradiances from radiance measurements over permanent snow, fresh snow, and sea ice are developed using CERES measurements on Terra. Permanent snow angular distribution models depend on cloud fraction, cloud optical thickness, and snow brightness. Fresh snow and sea ice angular distribution models depend on snow and sea ice fraction, cloud fraction, cloud optical thickness, and snow and ice brightness. These classifications lead to 10 scene types for permanent snow and 25 scene types for fresh snow and sea ice. The average radiance over clear‐sky permanent snow is more isotropic with satellite viewing geometry than that over overcast permanent snow. On average, the albedo of clear‐sky permanent snow varies from 0.65 to 0.68 for solar zenith angles between 60° and 80°, while the corresponding albedo of overcast scenes varies from 0.70 to 0.73. Clear‐sky permanent snow albedos over Antarctica estimated from two independent angular distribution models are consistent to within 0.6%, on average. Despite significant variability in sea ice optical properties with season, the estimated mean relative albedo error is −1.0% for very dark sea ice and 0.1% for very bright sea ice when albedos derived from different viewing angles are averaged. The estimated regional root‐mean‐square (RMS) relative albedo error is 5.6% and 2.6% when the sea ice angular distribution models are applied to a region that contains very dark and very bright sea ice, respectively. Similarly, the estimated relative albedo bias error for fresh snow is −0.1% for very dark snow scenes and 0.1% for very bright snow scenes. The estimated regional RMS relative albedo error is 3.5% and 5.0% when angular distribution models are applied to a region that contains very dark and very bright fresh snow, respectively. These error estimates are only due to angular distribution model error and do not include the error caused by scene identification.

Sea ice concentrations in the Weddell Sea: A comparison of SSM/I, ULS, and GCM data

The sea ice fraction in the interior of the pack, especially in winter, is important for climate studies and for validation of sea ice models. When ice concentration is high, a difference of only a few percent in ice fraction can have a major effect on the ocean‐air fluxes. Satellite estimates of the ice fraction in the Antarctic winter based on microwave emissions are typically 90–95%, with values from the “Bootstrap” algorithm higher than the “NASA team”. However coupled ocean‐atmosphere models usually show higher concentrations. A recent evaluation for the Arctic has shown that the true winter ice fractions can be very high, above 99%. Upward looking sonar data from the Weddell Sea is used to show that Antarctic concentrations are higher than previously estimated, and to reevaluate climate model results in this light. The bootstrap algorithm is found to provide a better fit to the sonar data.

Modelling the impacts of persistent Antarctic polynyas with an atmosphere–sea-ice general circulation model

Abstract A coupled atmosphere–sea-ice model is used to assess the effect of Antarctic polynyas on the heat exchange between the surface and the atmosphere, the ice production rate within the polynyas, and the possible mechanisms of formation and maintenance of the polynyas. Results are presented for sensitivity studies with the model using prescribed minimum open-water fractions (25% and 30%) at a number of locations around the coast of East Antarctica and in the Amundsen, Ross and Weddell Seas. Although to some extent unphysical for the ocean, this technique allows the heat fluxes and freezing rates to be computed for the constrained conditions compared with an unconstrained control simulation. The model simulations suggest that Antarctic coastal polynyas, including the Mertz Glacier polynya, are primarily latent heat polynyas (where the heat loss from open water is balanced by the latent heat released with ice production) rather than sensible heat ones (where the heat loss is balanced by heat from the deep ocean). When a polynya exists, the turbulent latent heat flux from the ocean surface to the atmosphere can increase several times in magnitude and the average latent heat flux (over open-water and sea-ice fractions) can be sustained at over 60 W m −2 . The sensible heat flux changes sign and increases by about 2 orders of magnitude. This loss of turbulent heat (sensible plus latent) is offset only slightly by increased absorbed short-wave radiation in winter, but this offset increases greatly in spring when more short-wave radiation is available. In the polynyas, the large heat loss to the atmosphere is mostly balanced by the heat released due to ice formation, and this is accompanied by a high rate of salt rejection. The average ice production simulated in the polynyas is more than 11 m/year, with 5 m formed during 3 months of winter. These results provide quantitative support for the sustained high ice-freezing rates in polynyas estimated in other studies, which have used satellite and in situ observational data.

A Case Study of Regional Climate Anomalies in the Arctic: Performance Requirements for a Coupled Model

Abstract Simulations of Arctic climate require treatment of land, ocean, ice, and atmospheric processes, and are further complicated by the dynamic nature of the sea ice cover. Here, the ability of a climate system model to simulate conditions over the Arctic Ocean during April–September 1990, a period of anomalous atmospheric circulation and sea ice conditions, is investigated. Differences between observations and model results are used to gain insight into the mechanisms that contributed to the observed record reduction in ice extent in late summer. The coupled model reproduces the general patterns seen in comparison sea level pressure fields in most months, but the discrepancies significantly affect the model’s ability to simulate details of sea ice transport and warm air advection linked to the unusual ice conditions. The use of prescribed sea ice fraction in the climate model yields relatively small changes in the surface energy balance compared to the fully-coupled simulation with dynamic ice cover,...

Recent increase in the length of the melt season of perennial Arctic sea ice

General circulation models predict that greenhouse gas induced global warming will be amplified in the Arctic as a result of temperature‐albedo feedback. Whilst recent observations of decreasing Arctic sea ice extent are consistent with this scenario, the possibility that such a trend is attributable to local effects at the ice margins rather than to atmospheric warming cannot be dismissed. In the absence of direct air temperature measurements, warming over Arctic sea ice may be inferred from an increasing duration of the summer melt season. Analysis presented here of the dates of spring melt and autumn freeze‐up observed over a large fraction of perennial Arctic sea ice using passive microwave data from the SMMR and SSM/I from 1979 to 1996 reveals an increase of 5.3 days (8%) per decade in the number of melt days per summer.

Sea-Ice Melt-Pond Fraction as Determined from Low Level Aerial Photographs

Surface melt features on Arctic sea ice contribute greatly to variations in surface energy absorption and exchange. This factor, when coupled with the spatial variability of melt-pond fractional coverage emphasizes the importance of calculating the rate at which the snow cover to melt-pond proportional area changes. The small area of many melt features, especially in the early spring, demand high resolution imagery to accurately determine melt-pond coverage. This study utilizes a time series of low level photographic infrared images collected from a tethered balloon to quantify the change in melt-pond fractional cover during the spring transitional period. The data were gathered as a component of the Seasonal Sea Ice Monitoring and Modelling Site (SIMMS) field experiment for 1995, conducted near Resolute, NWT, in the Canadian Arctic Archipelago. Analysis of the imagery indicates a linear growth rate of melt-pond coverage to a maximum ponding of just over 50%. Incorporation of microclimatic variables collected during SIMMS'95 reveals triggers to the onset of pond development. It is important to develop methods to characterize the evolution of melt-feature area as thermodynamic sea-ice models have shown sensitivity to variables associated with surface ponding.

Regional climate model of the Arctic atmosphere

A regional climate model of the whole Arctic using the dynamical package of the High‐Resolution Limited Area Model (HIRLAM) and the physical parameterizations of the Hamburg General Circulation Model (ECHAM3) has been applied to simulate the climate of the Arctic north of 65°N at a 50‐km horizontal resolution. The model has been forced by the European Centre for Medium‐Range Weather Forecasts (ECMWF) analyses at the lateral boundaries and with climatological or actual observed sea surface temperatures and sea ice cover at the lower boundary. The results of simulating the Arctic climate of the troposphere and lower stratosphere for January 1991 and July 1990 have been described. In both months the model rather closely reproduces the observed monthly mean circulation. While the general spatial patterns of surface air temperature, mean sea level pressure, and geopotential are consistent with the ECMWF analyses, the model shows biases when the results are examined in detail. The largest biases appear during winter in the planetary boundary layer and at the surface. The underestimated vertical heat and humidity transport in the model indicates the necessity of improvements in the parameterizations of vertical transfer due to boundary layer processes. The tropospheric differences between model simulations and analyses decrease with increasing height. The temperature bias in the planetary boundary layer can be reduced by increasing the model sea ice thickness. The use of actual observed sea surface temperatures and sea ice cover leads only to small improvements of the model bias in comparison with climatological sea surface temperatures and sea ice cover. The validation of model computed geopotential, radiative fluxes, surface sensible and latent heat fluxes and clouds against selected station data shows deviations between model simulations and observations due to shortcomings of the model. This first validation indicates that improvements in the physical parameterization packages of radiation and in the description of sea ice thickness and sea ice fraction are necessary to reduce the model bias.

Scene identification and its effect on cloud radiative forcing in the Arctic

Measurements of cloud radiative forcing in polar regions are less reliable than at lower latitudes because of the difficulty in distinguishing between clouds and ice‐ or snow‐covered surfaces. Scene identification can, however, be improved by using multispectral narrow‐band radiances. Comparisons were made between scenes identified by the Earth Radiation Budget Experiment (ERBE) algorithm and those deduced from Advanced Very High Resolution Radiometer (AVHRR) radiances in the Arctic for 4 days in July 1985. It was found that they differ significantly from each other both in geotype and in cloud cover. For instance, regions of clear fractional sea ice according to the AVHRR analysis are assigned as being cloudy over open ocean by the ERBE analysis owing to incorrect specification of the sea ice extent. Zonal averages over 2.5° wide bands, of fluxes over clear and cloudy regions and hence also cloud forcing, are determined over the Arctic using radiances measured by the AVHRR on NOAA 9 to identify the nature of the scene and the ERBE radiometer to provide broadband radiances. Results are compared with fluxes and cloud forcing determined solely from ERBE radiometer data. Over the southern portion of the domain, where fractional sea ice was prevalent, the ERBE‐based values of net cloud forcing were as much as 50 W m−2 smaller than values determined when the scene identification was based on AVHRR measurements. At higher latitudes the ERBE‐estimated cloud forcing was larger than that from the AVHRR, and the magnitude of the difference was smaller.

A Semianalytic Energy Balance Climate Model with Explicit Sea Ice and Snow Physics

Abstract An energy balance climate model (EBCM) is presented having 1) a seasonal cycle; 2) surface-air, land-sea, and latitudinal resolution; 3) simulation of sea ice in terms of a number of explicit physical processes and in such a way that the sea ice fraction in any given zone changes continuously during the course of the seasonal cycle; 4) simulation of a continuously varying land-snow fraction in terms of explicit physical processes; and 5) a detailed treatment of surface and planetary albedo. A semianalytic solution is used which permits use of 6 day time steps, with very little dependence of the simulated climate on the choice of time step length for time steps of 1 to 6 days. Model sensitivity to internal parameter changes is investigated. The temperature response to a doubling of the drag coefficients for the vertical fluxes of latent and sensible heat is complex, and involves radiative constraints, the effect of stronger coupling to the large thermal inertia of the mixed layer, and ice and snow...

A microwave radiometer weather‐correcting sea ice algorithm

An algorithm is developed which uses six channels of the Scanning Multichannel Microwave Radiometer to estimate fractions of multiyear and first‐year sea ice types under variable atmospheric and sea surface conditions. Previously published sea ice algorithms have used a minimal number of channels and have therefore avoided most problems associated with noisy data as well as detailed atmospheric correction. Algorithms used for retrieval of atmospheric parameters concentrate on a statistical approach utilizing as many channels as possible. The present work attempts to synthesize these two classes of algorithms by using several radiometer data channels. This 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. The four additional environmental parameters are derived only for the purpose of correcting the sea ice parameters at the expense of accepting absolute errors in the derivation of the secondary parameters. These large errors propagate small errors in the resultant sea ice fractions. This weather‐correcting algorithm performs at least as well, if not better, than the first‐generation algorithms over consolidated ice and appears to perform very well when the sea ice concentration is less than 20%. To this end, the results are compared with the results of two algorithms that appear in the published literature. Unlike one of the algorithms that employs a weather filter, this new algorithm utilizes the radiative transfer equation to correct for these effects and thus eliminates false retrievals of sea ice without discarding data. The penalty that is paid is that more computer resources are required.

Determination of sea ice parameters with the NIMBUS 7 SMMR

A method of determining sea ice parameters using dual‐polarized multispectral radiance data obtained with the NIMBUS 7 Scanning Multichannel Microwave Radiometer (SMMR) is presented. Sea ice concentration is determined both at a 60‐km resolution from the polarization at the 1.7‐cm wavelength and at a 30‐km resolution using the polarization at the 0.81‐cm wavelength. Multiyear sea ice fraction is obtained from the spectral gradient ratio, which is the difference of the 0.81 cm and the 1.7 cm vertically polarized radiances divided by their sum. In addition, an ice temperature is calculated from the 4.6‐cm vertical channel radiances. The use of radiance ratios greatly reduces uncertainties in the derived parameters resulting from temporal and horizontal spatial variations of ice temperature. Observed SMMR radiances from selected areas in the Arctic region for the period February 3–7, 1979, are used in computing algorithm coefficients. Polar maps of sea ice concentration, multiyear fraction, and ice temperature are illustrated for this period. The variation of the mean and standard deviation of ice concentration and multiyear ice fraction for a region of perennial ice cover over the first 11 months of SMMR operation is also presented. The standard deviation about the mean for the computed concentration varies from 2 to 5% over the 11‐month period, while that of the multiyear fraction is about 8% for all but the summer months. Discrimination between first‐year and multiyear sea ice during the summer period is indeterminate largely because the general surface melt conditions mask the distinguishing properties of the two ice types. Based on the time variation of ice concentration and multiyear fraction for the central Arctic region and on an analysis of histograms of these parameters, the precision of the calculated ice concentration is estimated to be in the range of 5–9% and that of the multiyear fraction in the range of 13–25%. Comparisons are made between the calculated sea ice parameters and information obtained from previous studies using aircraft, submarine, and surface observations. From these comparisons it is concluded that the absolute accuracy of the SMMR parameters remains uncertain. The precision of the sea ice concentration is sufficient to provide useful data on the large‐scale polar ice cover, but further study is required to increase the confidence in the multiyear ice fraction which at present contains significant uncertainties.