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All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Ice-atmosphere interactions in the polar oceans

Sea ice forms a major reservoir in the global water cycle and both polar regions undergo a large seasonal variation in their sea ice cover. The extent of this sea ice cover is a function of both dynamic and thermodynamic interactions with the atmosphere and ocean. These sea ice atmospheric interactions are examined in terms of the atmospheric controls on ice cover, and the resulting feedbacks to the climate system. The role of sea ice in global climate change is determined. The relationship between sea ice and the synoptic scale atmospheric circulation in the North Atlantic is examined. This region is chosen for more detailed study because the project involves land ice and there is a focus on Greenland and because there have been several previous international field programs in the region and more are planned.

Crane, Robert↗
NASA NTRS2003

Studies of the Antarctic Sea Ice Edges and Ice Extents from Satellite and Ship Observations

Passive-microwave derived ice edge locations in Antarctica are assessed against other satellite data as well as in situ observations of ice edge location made between 1989 and 2000. The passive microwave data generally agree with satellite and ship data but the ice concentration at the observed ice edge varies greatly with averages of 14% for the TEAM algorithm and 19% for the Bootstrap algorithm. The comparisons of passive microwave with the field data show that in the ice growth season (March - October) the agreement is extremely good, with r(sup 2) values of 0.9967 and 0.9797 for the Bootstrap and TEAM algorithms respectively. In the melt season however (November - February) the passive microwave ice edge is typically 1-2 degrees south of the observations due to the low concentration and saturated nature of the ice. Sensitivity studies show that these results can have significant impact on trend and mass balance studies of the sea ice cover in the Southern Ocean.

Worby, Anthony P.↗
NASA NTRS1998

Variability of Arctic Sea Ice as Viewed from Space

Over the past 20 years, satellite passive-microwave radiometry has provided a marvelous means for obtaining information about the variability of the Arctic sea ice cover and particularly about sea ice concentrations (% areal coverages) and from them ice extents and the lengths of the sea ice season. This ability derives from the sharp contrast between the microwave emissions of sea ice versus liquid water and allows routine monitoring of the vast Arctic sea ice cover, which typically varies in extent from a minimum of about 8,000,000 sq km in September to a maximum of about 15,000,000 sq km in March, the latter value being over 1.5 times the area of either the United States or Canada. The vast Arctic ice cover has many impacts, including hindering heat, mass, and y momentum exchanges between the oceans and the atmosphere, reducing the amount of solar radiation absorbed at the Earth's surface, affecting freshwater transports and ocean circulation, and serving as a vital surface for many species of polar animals. These direct impacts also lead to indirect impacts, including effects on local and perhaps global atmospheric temperatures, effects that are being examined in general circulation modeling studies, where preliminary results indicate that changes on the order of a few percent sea ice concentration can lead to temperature changes of 1 K or greater even in local areas outside of the sea ice region. Satellite passive-microwave data for November 1978 through December 1996 reveal marked regional and interannual variabilities in both the ice extents and the lengths of the sea ice season, as well as some statistically significant trends. For the north polar ice cover as a whole, maximum ice extents varied over a range of 14,700,000 - 15,900,000 km(2), while individual regions showed much greater percentage variations, e.g., with the Greenland Sea experiencing a range of 740,000 - 1,1110,000 km(2) in its yearly maximum ice coverage. Although variations from year to year and region to region are large, overall the Arctic ice extents did show a statistically significant, 2.8%/ decade negative trend over the 18.2-year period. Ice season lengths, which vary from only a few weeks near the ice margins to the full year in the large region of perennial ice coverage, also experienced interannual variability, and mapping their trends allows detailed geographic information on exactly where the ice season lengthened and where it shortened. Over the 18 years, ice season lengthening occurred predominantly in the western hemisphere and was strongest in the western Labrador Sea, while ice season shortening occurred predominantly in the eastern hemisphere and was strongest in the eastern Barents Sea. Much information about other important Arctic sea ice variables has also been obtained from satellite data, including information about melt ponding, temperature, snow cover, and ice velocities. For instance, maps of ice velocities have now been made from satellite scatterometry data, including information about melt ponding, temperature, snow cover, and ice velocities.

Parkinson, Claire L.↗
NASA NTRS1997

Observed Hemispheric Asymmetry in Global Sea Ice Changes

From November 1978 through December 1996, the areal extent of sea ice decreased by 2.9 +/- 0.4 percent per decade in the Arctic and increased by 1.3 +/- 0.2 percent per decade in the Antarctic. The observed hemispheric asymmetry in these trends is consistent with a modeled response to a carbon dioxide-induced climate warming. The interannual variations, which are 2.3 percent of the annual mean in the Arctic, with a predominant period of about 5 years, and 3.4 percent of the annual mean in the Antarctic, with a predominant period of about 3 years, are uncorrelated.

Cavalieri, D. J.↗
NASA NTRS2014

Sea Ice Prediction Has Easy and Difficult Years

Arctic sea ice follows an annual cycle, reaching its low point in September each year. The extent of sea ice remaining at this low point has been trending downwards for decades as the Arctic warms. Around the long-term downward trend, however, there is significant variation in the minimum extent from one year to the next. Accurate forecasts of yearly conditions would have great value to Arctic residents, shipping companies, and other stakeholders and are the subject of much current research. Since 2008 the Sea Ice Outlook (SIO) (http://www.arcus.org/search-program/seaiceoutlook) organized by the Study of Environmental Arctic Change (SEARCH) (http://www.arcus.org/search-program) has invited predictions of the September Arctic sea ice minimum extent, which are contributed from the Arctic research community. Individual predictions, based on a variety of approaches, are solicited in three cycles each year in early June, July, and August. (SEARCH 2013).

Years↗
NASA NTRS1976

Surface and atmosphere parameter maps from earth-orbiting radiometers

Earlier studies have shown that an earth-orbiting electrically scanned microwave radiometer (ESMR) is capable of inferring the extent, concentration, and age of sea ice; the extent, concentration, and thickness of lake ice; rainfall rates over oceans; surface wind speeds over open water; particle size distribution in the deep snow cover of continental ice sheets; and soil moisture content in unvegetated fields. Most other features of the surface of the earth and its atmosphere require multispectral imaging techniques to unscramble the combined contributions of the atmosphere and the surface. Multispectral extraction of surface parameters is analyzed on the basis of a pertinent equation in terms of the observed brightness temperature, the emissivity of the surface which depends on wavelength and various parameters, the sensible temperature of the surface, and the total atmospheric opacity which is also wavelength dependent. Implementation of the multispectral technique is examined. Properties of the surface of the earth and its atmosphere to be determined from a scanning multichannel microwave radiometer are tabulated.

Gloersen, P.↗
NASA NTRS2004

MODIS Snow and Sea Ice Products

In this chapter, we describe the suite of Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow and sea ice products. Global, daily products, developed at Goddard Space Flight Center, are archived and distributed through the National Snow and Ice Data Center at various resolutions and on different grids useful for different communities Snow products include binary snow cover, snow albedo, and in the near future, fraction of snow in a 5OO-m pixel. Sea ice products include ice extent determined with two different algorithms, and sea ice surface temperature. The algorithms used to develop these products are described. Both the snow and sea ice products, available since February 24,2000, are useful for modelers. Validation of the products is also discussed.

Hall, Dorothy K.↗
NASA NTRS1979

Antarctic Sea Ice variations 1973 - 1975

Variations in the extent and concentration of sea ice cover on the Southern Ocean are described for the three-year period 1973-75 using information derived from the Nimbus-5 passive microwave imager.

Zwally, H. J.↗
NASA NTRS2001

Southern Ocean Climate and Sea Ice Anomalies Associated with the Southern Oscillation

The anomalies in the climate and sea ice cover of the Southern Ocean and their relationships with the Southern Oscillation (SO) are investigated using a 17-year of data set from 1982 through 1998. We correlate the polar climate anomalies with the Southern Oscillation index (SOI) and examine the composites of these anomalies under the positive (SOI > 0), neutral (0 > SOI > -1), and negative (SOI < -1) phases of SOL The climate data set consists of sea-level pressure, wind, surface air temperature, and sea surface temperature fields, while the sea ice data set describes its extent, concentration, motion, and surface temperature. The analysis depicts, for the first time, the spatial variability in the relationship of the above variables and the SOL The strongest correlation between the SOI and the polar climate anomalies are found in the Bellingshausen, Amundsen and Ross sea sectors. The composite fields reveal anomalies that are organized in distinct large-scale spatial patterns with opposing polarities at the two extremes of SOI, and suggest oscillating climate anomalies that are closely linked to the SO. Within these sectors, positive (negative) phases of the SOI are generally associated with lower (higher) sea-level pressure, cooler (warmer) surface air temperature, and cooler (warmer) sea surface temperature in these sectors. Associations between these climate anomalies and the behavior of the Antarctic sea ice cover are clearly evident. Recent anomalies in the sea ice cover that are apparently associated with the SOI include: the record decrease in the sea ice extent in the Bellingshausen Sea from mid- 1988 through early 199 1; the relationship between Ross Sea SST and ENSO signal, and reduced sea ice concentration in the Ross Sea; and, the shortening of the ice season in the eastern Ross Sea, Amundsen Sea, far western Weddell Sea, and the lengthening of the ice season in the western Ross Sea, Bellingshausen Sea and central Weddell Sea gyre over the period 1988-1994. Four ENSO episodes over the last 17 years contributed to a negative mean in the SOI (-0.5). In each of these episodes, significant retreats in the Bellingshausen/Amundsen Sea were observed providing direct confirmation of the impact of SO on the Antarctic sea ice cover.

Kwok, R.↗
DOE OSTI2023

Assessing the Robustness of Arctic Sea Ice Bi‐Stability in the Presence of Atmospheric Feedbacks

Abstract Arctic sea‐ice loss is influenced by multiple positive feedbacks, sparking concerns of accelerated loss in the coming years or even a tipping point, where a sea‐ice equilibrium disappears at a given CO 2 value and sea ice rapidly evolves to a new steady state. Such a tipping point would imply a bi‐stability of the Arctic climate—where multiple steady‐state Arctic climates are possible at the same CO 2 value. Previous works have sought to establish the existence of bi‐stability using a range of models, from zero‐dimensional sea ice thermodynamic models to fully coupled global climate models, with conflicting results. Here, we present a new model of the Arctic that includes both sea‐ice thermodynamics and key atmospheric feedbacks in a simple framework. We exploit the model's simplicity to identify physical mechanisms that control the timing and extent of sea‐ice bi‐stability, and the abruptness of ice loss. We show that longwave radiation feedbacks can have a strong influence on Arctic surface climate from atmospheric temperature increases alone, even without major contributions from clear‐sky moisture or convective clouds suggested previously. While winter sea‐ice bi‐stability is robust to changes in uncertain model parameters in this study, summer sea ice is more sensitive. Finally, our model indicates that positive feedbacks may modulate the CO 2 threshold of sea‐ice loss and the width of bi‐stability much more strongly than the abruptness of loss. These results lead to a comprehensive understanding of the conditions that favor Arctic sea‐ice bi‐stability, particularly the role of atmospheric feedbacks, in both future and past climates.

Meteorology & Atmospheric Sciences↗
NASA NTRS1973

Polar sea ice observations by means of microwave radiometry

Principles pertinent to the utilization of 1.55 cm wavelength radiation emanating from the surface of the earth for studying the changing characteristics of polar sea ice are briefly reviewed. Recent data obtained at that wavelength with an imaging radiometer on-board the Nimbus 5 satellite are used to illustrate how the seasonal changes in extent of sea ice in both polar regions may be monitored free of atmospheric interference. Within a season, changes in the compactness of the sea ice are also observed from the satellite. Some substantial areas of the Arctic sea ice canopy identified as first-year ice in the past winter were observed not to melt this summer, a graphic illustration of the eventual formation of multiyear ice in the Arctic. Finally, the microwave emissivity of some of the multiyear ice areas near the North Pole was found to increase significantly in the summer, probably due to liquid water content in the firm layer.

Gloersen, P.↗
NASA NTRS2014

NASA Team 2 Sea Ice Concentration Algorithm Retrieval Uncertainty

Satellite microwave radiometers are widely used to estimate sea ice cover properties (concentration, extent, and area) through the use of sea ice concentration (IC) algorithms. Rare are the algorithms providing associated IC uncertainty estimates. Algorithm uncertainty estimates are needed to assess accurately global and regional trends in IC (and thus extent and area), and to improve sea ice predictions on seasonal to interannual timescales using data assimilation approaches. This paper presents a method to provide relative IC uncertainty estimates using the enhanced NASA Team (NT2) IC algorithm. The proposed approach takes advantage of the NT2 calculations and solely relies on the brightness temperatures (TBs) used as input. NT2 IC and its associated relative uncertainty are obtained for both the Northern and Southern Hemispheres using the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) TB. NT2 IC relative uncertainties estimated on a footprint-by-footprint swath-by-swath basis were averaged daily over each 12.5-km grid cell of the polar stereographic grid. For both hemispheres and throughout the year, the NT2 relative uncertainty is less than 5%. In the Southern Hemisphere, it is low in the interior ice pack, and it increases in the marginal ice zone up to 5%. In the Northern Hemisphere, areas with high uncertainties are also found in the high IC area of the Central Arctic. Retrieval uncertainties are greater in areas corresponding to NT2 ice types associated with deep snow and new ice. Seasonal variations in uncertainty show larger values in summer as a result of melt conditions and greater atmospheric contributions. Our analysis also includes an evaluation of the NT2 algorithm sensitivity to AMSR-E sensor noise. There is a 60% probability that the IC does not change (to within the computed retrieval precision of 1%) due to sensor noise, and the cumulated probability shows that there is a 90% chance that the IC varies by less than +/-3%. We also examined the daily IC variability, which is dominated by sea ice drift and ice formation/melt. Daily IC variability is the highest, year round, in the MIZ (often up to 20%, locally 30%). The temporal and spatial distributions of the retrieval uncertainties and the daily IC variability is expected to be useful for algorithm intercomparisons, climate trend assessments, and possibly IC assimilation in models.

Sea Ice↗
NASA NTRS1991

Operational satellites and the global monitoring of snow and ice

The altitudinal dependence of the global warming projected by global climate models is at least partially attributable to the albedo-temperature feedback involving snow and ice, which must be regarded as key variables in the monitoring for global change. Statistical analyses of data from IR and microwave sensors monitoring the areal coverage and extent of sea ice have led to mixed conclusions about recent trends of hemisphere sea ice coverage. Seasonal snow cover has been mapped for over 20 years by NOAA/NESDIS on the basis of imagery from a variety of satellite sensors. Multichannel passive microwave data show some promise for the routine monitoring of snow depth over unforested land areas.

Walsh, John E.↗
NASA NTRS1987

A multifrequency microwave radiometer of the future

The design of the High-Resolution Multifrequency Microwave Radiometer (HMMR), which is to be installed on EOS, is described. The HMMR is to consist of the Advanced Microwave Sounding Unit (AMSU), the Advanced Mechanically Scanned Radiometer (AMSR), and the Electronically Scanned Thinned Array Radiometer (ESTAR). The AMSU is a 20-channel microwave radiometer system designed to measure profiles of atmospheric temperature and humidity and the AMSR is a microwave imager with channels at 6, 10, 18, 21, 37, and 90 GHz for measuring snow cover over land, the age and areal extent of sea ice, the intensity of precipitation over oceans and land, and the amount of water in the atmosphere. ESTAR is an imaging radiometer operating near 1.4 GHz capable of obtaining global maps of surface soil moisture with a spatial resolution of about 10 km. The antenna and signal processing utilized in the ESTAR to achieve the real aperture resolution are examined.

Le Vine, D.↗
NASA NTRS1993

Climate forcings and feedbacks

Global temperature has increased significantly during the past century. Understanding the causes of observed global temperature change is impossible in the absence of adequate monitoring of changes in global climate forcings and radiative feedbacks. Climate forcings are changes imposed on the planet's energy balance, such as change of incoming sunlight or a human-induced change of surface properties due to deforestation. Radiative feedbacks are radiative changes induced by climate change, such as alteration of cloud properties or the extent of sea ice. Monitoring of global climate forcings and feedbacks, if sufficiently precise and long-term, can provide a very strong constraint on interpretation of observed temperature change. Such monitoring is essential to eliminate uncertainties about the relative importance of various climate change mechanisms including tropospheric sulfate aerosols from burning of coal and oil smoke from slash and burn agriculture, changes of solar irradiance changes of several greenhouse gases, and many other mechanisms. The considerable variability of observed temperature, together with evidence that a substantial portion of this variability is unforced indicates that observations of climate forcings and feedbacks must be continued for decades. Since the climate system responds to the time integral of the forcing, a further requirement is that the observations be carried out continuously. However, precise observations of forcings and feedbacks will also be able to provide valuable conclusions on shorter time scales. For example, knowledge of the climate forcing by increasing CFC's relative to the forcing by changing ozone is important to policymakers, as is information on the forcing by CO2 relative to the forcing by sulfate aerosols. It will also be possible to obtain valuable tests of climate models on short time scales, if there is precise monitoring of all forcings and feedbacks during and after events such as a large volcanic eruption or an El Nino.

Hansen, James↗
NASA NTRS2007

Arctic Sea Ice Parameters from AMSR-E Data using Two Techniques, and Comparisons with Sea Ice from SSM

We use two algorithms to process AMSR-E data in order to determine algorithm dependence, if any, on the estimates of sea ice concentration, ice extent and area, and trends and to evaluate how AMSR-E data compare with historical SSM/I data. The monthly ice concentrations derived from the two algorithms from AMSR-E data (the AMSR-E Bootstrap Algorithm, or ABA, and the enhanced NASA Team algorithm, or NT2) differ on average by about 1 to 3%, with data from the consolidated ice region being generally comparable for ABA and NT2 retrievals while data in the marginal ice zones and thin ice regions show higher values when the NT2 algorithm is used. The ice extents and areas derived separately from AMSR-E using these two algorithms are, however, in good agreement, with the differences (ABA-NT2) being about 6.6 x 10(exp 4) square kilometers on average for ice extents and -6.6 x 10(exp 4) square kilometers for ice area which are small compared to mean seasonal values of 10.5 x 10(exp 6) and 9.8 x 10(exp 6) for ice extent and area: respectively. Likewise, extents and areas derived from the same algorithm but from AMSR-E and SSM/I data are consistent but differ by about -24.4 x 10(exp 4) square kilometers and -13.9 x 10(exp 4) square kilometers, respectively. The discrepancies are larger with the estimates of extents than area mainly because of differences in channel selection and sensor resolutions. Trends in extent during the AMSR-E era were also estimated and results from all three data sets are shown to be in good agreement (within errors).

Comiso, Josefino C.↗
NASA NTRSDate not supplied

International Satellite Cloud Climatology Project (ISCCP) Ice Snow Product in Native (NAT) Format (ISCCP_ICESNOW_NAT)

Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=112 Km; Longitude_Resolution=112 Km; Temporal_Resolution=5-day].

SNOW COVER↗
NASA NTRS2011

Seafloor Control on Sea Ice

The seafloor has a profound role in Arctic sea ice formation and seasonal evolution. Ocean bathymetry controls the distribution and mixing of warm and cold waters, which may originate from different sources, thereby dictating the pattern of sea ice on the ocean surface. Sea ice dynamics, forced by surface winds, are also guided by seafloor features in preferential directions. Here, satellite mapping of sea ice together with buoy measurements are used to reveal the bathymetric control on sea ice growth and dynamics. Bathymetric effects on sea ice formation are clearly observed in the conformation between sea ice patterns and bathymetric characteristics in the peripheral seas. Beyond local features, bathymetric control appears over extensive ice-prone regions across the Arctic Ocean. The large-scale conformation between bathymetry and patterns of different synoptic sea ice classes, including seasonal and perennial sea ice, is identified. An implication of the bathymetric influence is that the maximum extent of the total sea ice cover is relatively stable, as observed by scatterometer data in the decade of the 2000s, while the minimum ice extent has decreased drastically. Because of the geologic control, the sea ice cover can expand only as far as it reaches the seashore, the continental shelf break, or other pronounced bathymetric features in the peripheral seas. Since the seafloor does not change significantly for decades or centuries, sea ice patterns can be recurrent around certain bathymetric features, which, once identified, may help improve short-term forecast and seasonal outlook of the sea ice cover. Moreover, the seafloor can indirectly influence cloud cover by its control on sea ice distribution, which differentially modulates the latent heat flux through ice covered and open water areas.

Nghiem, S. V.↗