Search NASA⌕ Search

SEARCH · Search NASA

Results for “Sea Ice”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Estimating the Arctic Cloud-Sea Ice Feedback With Observations during the EOS Period

Arctic sea ice responds to and drives Arctic climate change. The interactions between Arctic sea ice and clouds represent a mechanism through which sea ice can drive climate change. We composite active remote sensing satellite cloud properties for ice-free, marginal ice zone (MIZ), and ice-covered surfaces during MIZ crossing events to investigate the influence of the transition from an ice-covered to an ice-free surface on low-level clouds. We demonstrate that the event-based methodology controls for large-scale meteorological factors and isolates the sea ice effect on clouds. We find larger cloud fraction and total water content below ~1.5 km over ice-free relative to ice-covered surfaces during non-summer months, indicating a low-level cloud sensitivity to Arctic sea ice decline. During summer, results show larger cloud fraction and water content over ice-free surfaces, however the differences are statistically indistinguishable. Evidence is provided that atmospheric thermodynamic profile differences cause the cloud property differences, namely that ice-free footprints are warmer, moister, have more positive surface turbulent fluxes and are less stable than their ice-covered counterparts. Ice-free and ice-covered surface cloud property differences scale with surface temperature differences such that cloud property differences are only found in the presence of a surface temperature difference. We conclude that surface temperature differences modulate the cloud response to sea ice loss through influences on surface turbulent fluxes and lower tropospheric stability. The results imply a positive non-summer sea ice-cloud feedback and that up to a 0.02 cloud fraction and 0.05 g m 3 total water content increase in fall are due to the observed sea ice decline.

Patrick C. Taylor↗
NASA NTRS2001

Trends in the Length of the Southern Ocean Sea Ice Season: 1979-1999

Satellite data can be used to observe the sea ice distribution around the continent of Antarctica on a daily basis and hence to determine how many days a year have sea ice at each location. This has been done for each of the 21 years 1979-1999. Mapping the trends in these data over the 21-year period reveals a detailed pattern of changes in the length of the sea ice season around Antarctica. Most of the Ross Sea ice cover has undergone a lengthening of the sea ice season, whereas most of the Amundsen Sea ice cover and almost the entire Bellingshausen Sea ice cover have undergone a shortening of the sea ice season. Results around the rest of the continent, including in the Weddell Sea, are more mixed, but overall, more of the Southern Ocean experienced a lengthening of the sea ice season than a shortening. For instance, the area experiencing a lengthening of the sea ice season by at least 1 day per year is 5.8 x 10(exp 6) sq km, whereas the area experiencing a shortening of the sea ice season by at least 1 day per year is less than half that, at 2.8 x 10(exp 6) sq km. This contrasts sharply with what is happened over the same period in the Arctic, where, overall, there has been some depletion of the ice cover, including shortened sea ice seasons and decreased ice extents.

Parkinson, Claire L.↗
NASA NTRS2013

Shape-Constrained Segmentation Approach for Arctic Multiyear Sea Ice Floe Analysis

The melting of sea ice is correlated to increases in sea surface temperature and associated climatic changes. Therefore, it is important to investigate how rapidly sea ice floes melt. For this purpose, a new Tempo Seg method for multi temporal segmentation of multi year ice floes is proposed. The microwave radiometer is used to track the position of an ice floe. Then,a time series of MODIS images are created with the ice floe in the image center. A Tempo Seg method is performed to segment these images into two regions: Floe and Background.First, morphological feature extraction is applied. Then, the central image pixel is marked as Floe, and shape-constrained best merge region growing is performed. The resulting tworegionmap is post-filtered by applying morphological operators.We have successfully tested our method on a set of MODIS images and estimated the area of a sea ice floe as afunction of time.

SEA ICE FLOE↗
NASA NTRS1999

Airborne Spectral Measurements of Surface-Atmosphere Anisotropy for Arctic Sea Ice and Tundra

Angular distributions of spectral reflectance for four common arctic surfaces: snow-covered sea ice, melt-season sea ice, snow-covered tundra, and tundra shortly after snowmelt were measured using an aircraft based, high angular resolution (1-degree) multispectral radiometer. Results indicate bidirectional reflectance is higher for snow-covered sea ice than melt-season sea ice at all wavelengths between 0.47 and 2.3 pm, with the difference increasing with wavelength. Bidirectional reflectance of snow-covered tundra is higher than for snow-free tundra for measurements less than 1.64 pm, with the difference decreasing with wavelength. Bidirectional reflectance patterns of all measured surfaces show maximum reflectance in the forward scattering direction of the principal plane, with identifiable specular reflection for the melt-season sea ice and snow-free tundra cases. The snow-free tundra had the most significant backscatter, and the melt-season sea ice the least. For sea ice, bidirectional reflectance changes due to snowmelt were more significant than differences among the different types of melt-season sea ice. Also the spectral-hemispherical (plane) albedo of each measured arctic surface was computed. Comparing measured nadir reflectance to albedo for sea ice and snow-covered tundra shows albedo underestimated 5-40%, with the largest bias at wavelengths beyond 1 pm. For snow-free tundra, nadir reflectance underestimates plane albedo by about 30-50%.

Arnold, G. Thomas↗
NASA NTRS2016

Antarctic Sea-Ice Freeboard and Estimated Thickness from NASA's ICESat and IceBridge Observations

ICESat completed 18 observational campaigns during its lifetime from 2003 to 2009. Data from all of the 18 campaign periods are used in this study. Most of the operational periods were between 34 and 38 days long. Because of laser failure and orbit transition from 8-day to 91-day orbit, there were four periods lasting 57, 16, 23, and 12 days. IceBridge data from 2009, 2010, and 2011 are used in this study. Since 2009, there are 19 Airborne Topographic Mapper (ATM) campaigns, and eight Land, Vegetation, and Ice Sensor (LVIS) campaigns over the Antarctic sea ice. Freeboard heights are derived from ICESat, ATM and LVIS elevation and waveform data. With nominal densities of snow, water, and sea ice, combined with snow depth data from AMSR-E/AMSR2 passive microwave observation over the southern ocean, sea-ice thickness is derived from the freeboard. Combined with AMSR-E/AMSR2 ice concentration, sea-ice area and volume are also calculated. During the 2003-2009 period, sea-ice freeboard and thickness distributions show clear seasonal variations that reflect the yearly cycle of the growth and decay of the Antarctic pack ice. We found no significant trend of thickness or area for the Antarctic sea ice during the ICESat period. IceBridge sea ice freeboard and thickness data from 2009 to 2011 over the Weddell Sea and Amundsen and Bellingshausen Seas are compared with the ICESat results.

Antarctic↗
NASA NTRS1998

Spatial Distribution of Trends and Seasonality in the Hemispheric Sea Ice Covers

We extend earlier analyses of a 9-year sea ice data set that described the local seasonal and trend variations in each of the hemispheric sea ice covers to the recently merged 18.2-year sea ice record from four satellite instruments. The seasonal cycle characteristics remain essentially the same as for the shorter time series, but the local trends are markedly different, in some cases reversing sign. The sign reversal reflects the lack of a consistent long-term trend and could be the result of localized long-term oscillations in the hemispheric sea ice covers. By combining the separate hemispheric sea ice records into a global one, we have shown that there are statistically significant net decreases in the sea ice coverage on a global scale. The change in the global sea ice extent, is -0.01 +/- 0.003 x 10(exp 6) sq km per decade. The decrease in the areal coverage of the sea ice is only slightly smaller, so that the difference in the two, the open water within the packs, has no statistically significant change.

Gloersen, P.↗
NASA NTRS2003

EOS Aqua AMSR-E Arctic Sea Ice Validation Program: Arctic2003 Aircraft Campaign Flight Report

In March 2003 a coordinated Arctic sea ice validation field campaign using the NASA Wallops P-3B aircraft was successfully completed. This campaign was part of the program for validating the Earth Observing System (EOS) Aqua Advanced Microwave Scanning Radiometer (AMSR-E) sea ice products. The AMSR-E, designed and built by the Japanese National Space Development Agency for NASA, was launched May 4, 2002 on the EOS Aqua spacecraft. The AMSR-E sea ice products to be validated include sea ice concentration, sea ice temperature, and snow depth on sea ice. This flight report describes the suite of instruments flown on the P-3, the objectives of each of the seven flights, the Arctic regions overflown, and the coordination among satellite, aircraft, and surface-based measurements. Two of the seven aircraft flights were coordinated with scientists making surface measurements of snow and ice properties including sea ice temperature and snow depth on sea ice at a study area near Barrow, AK and at a Navy ice camp located in the Beaufort Sea. Two additional flights were dedicated to making heat and moisture flux measurements over the St. Lawrence Island polynya to support ongoing air-sea-ice processes studies of Arctic coastal polynyas. The remaining flights covered portions of the Bering Sea ice edge, the Chukchi Sea, and Norton Sound.

Cavalieri, D. J.↗
NASA NTRS2012

Arctic Low Cloud Changes as Observed by MISR and CALIOP: Implication for the Enhanced Autumnal Warming and Sea Ice Loss

Retreat of Arctic sea ice extent has led to more evaporation over open water in summer and subsequent cloud changes in autumn. Studying recent satellite cloud data over the Arctic Ocean, we find that low (0.5-2 km) cloud cover in October has been increasing significantly during 2000-2010 over the Beaufort and East Siberian Sea (BESS). This change is consistent with the expected boundary-layer cloud response to the increasing Arctic evaporation accumulated during summer. Because low clouds have a net warming effect at the surface, October cloud increases may be responsible for the enhanced autumnal warming in surface air temperature, which effectively prolong the melt season and lead to a positive feedback to Arctic sea ice loss. Thus, the new satellite observations provide a critical support for the hypothesized positive feedback involving interactions between boundary-layer cloud, water vapor, temperature and sea ice in the Arctic Ocean.

Wu, Dong L.↗
NASA NTRS2007

Thin Sea-Ice Thickness as Inferred from Passive Microwave and In Situ Observations

Since microwave radiometric signals from sea-ice strongly reflect physical conditions of a layer near the ice surface, a relationship of brightness temperature with thickness is possible especially during the early stages of ice growth. Sea ice is most saline during formation stage and as the salinity decreases with time while at the same time the thickness of the sea ice increases, a corresponding change in the dielectric properties and hence the brightness temperature may occur. This study examines the extent to which the relationships of thickness with brightness temperature (and with emissivity) hold for thin sea-ice, approximately less than 0.2 -0.3 m, using near concurrent measurements of sea-ice thickness in the Sea of Okhotsk from a ship and passive microwave brightness temperature data from an over-flying aircraft. The results show that the brightness temperature and emissivity increase with ice thickness for the frequency range of 10-37 GHz. The relationship is more pronounced at lower frequencies and at the horizontal polarization. We also established an empirical relationship between ice thickness and salinity in the layer near the ice surface from a field experiment, which qualitatively support the idea that changes in the near-surface brine characteristics contribute to the observed thickness-brightness temperature/emissivity relationship. Our results suggest that for thin ice, passive microwave radiometric signals contain, ice thickness information which can be utilized in polar process studies.

Naoki, Kazuhiro↗
NASA NTRSDate not supplied

A Daily Surface Melt Product From Passive Microwave Swath Observations for Arctic Sea Ice Studies

Most passive microwave sea ice data products are produced with daily gridded brightness temperatures. However, a single polar-orbiting passive microwave instrument makes many measurements per day where swaths overlap in the polar regions. These level 1 swath brightness temperature observations can be used to derive information on sub-daily sea ice processes. One such process is the rapid transition of snow and ice between freezing and melting due to diurnal freeze-thaw cycling or brief warming events in the pre-melt season. Here, a new method utilizing the sub-daily variability in swath-to-swath observations is used to produce daily, binary maps of the melting status on Arctic Sea ice using Level 1C brightness temperatures from the Special Sensor Microwave Imager and Sounder (SSM/I-SSMIS) data record. The resulting data set will enable investigations of the frequency, inter-annual variability, and spatial extent of brief surface melting events occurring in the winter and shoulder seasons outside of the traditional summer melt season.

Angela C. Bliss↗
NASA NTRS1995

Polarimetric signatures of sea ice. 1: Theoretical model

Physical, structral, and electromagnetic properties and interrelating processes in sea ice are used to develop a composite model for polarimetric backscattering signatures of sea ice. Physical properties of sea ice constituents such as ice, brine, air, and salt are presented in terms of their effects on electromagnetic wave interactions. Sea ice structure and geometry of scatterers are related to wave propagation, attenuation, and scattering. Temperature and salinity, which are determining factors for the thermodynamic phase distribution in sea ice, are consistently used to derive both effective permittivities and polarimetric scattering coefficients. Polarmetric signatures of sea ice depend on crystal sizes and brine volumes, which are affected by ice growth rates. Desalination by brine expulsion, drainage, or other mechanisms modifies wave penetration and scattering. Sea ice signatures are further complicated by surface conditions such as rough interfaces, hummocks, snow cover, brine skim, or slush layer. Based on the same set of geophysical parameters characterizing sea ice, a composite model is developed to calculate effective permittivities and backscattering covariance matrices at microwave frequencies to interpretation of sea ice polarimetric signatures.

Nghiem, S. V.↗
NASA NTRS2014

Implications of Arctic Sea Ice Decline for the Earth System

Arctic sea ice decline has led to an amplification of surface warming and is projected to continue to decline from anthropogenic forcing, although the exact timing of ice-free summers is uncertain owing to large natural variability. Sea ice reductions affect surface heating patterns and the atmospheric pressure distribution, which may alter midlatitude extreme weather patterns. Increased light penetration and nutrient availability during spring from earlier ice breakup enhances primary production in the Arctic Ocean and its adjacent shelf seas. Ice-obligate marine mammals may be losers, whereas seasonally migrant species may be winners from rapid sea ice decline. Tundra greening is occurring across most of the Arctic, driven primarily by warming temperatures, and is displaying complex spatial patterns that are likely tied to other factors. Sea ice changes are affecting greenhouse gas exchanges as well as halogen chemistry in the Arctic. This review highlights the heterogeneous nature of Arctic change, which is vital for researchers to better understand.

Decline↗
NASA NTRS1990

Spatial cross-correlation of Antarctic Sea ice and seabed topography

A time series of derived sea ice concentrations as observed about Antarctica by the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) satellite in 1983 is considered. The degree of spatial cross correlation between these data and seabed topography is quantified. The approach is to implement a statistical image processing filter designed to extract local patterns of spatial cross correlation over the entire sea ice field as it undergoes daily changes. Throughout the sea ice, it was found that large scale variations in sea ice concentration correlate systematically with variations in the topography of the seabed. Generally speaking, high concentrations of sea ice occur over deep ocean, whereas areas of encavement, early dissipation and polynya formation develop over topographic features of high elevation. The latter was studied in detail with respect to the features Maud Rise, Astrid Ridge and the continental shelf in the Cosmonaut and Ross Seas. In each case, it is shown that an encavement in sea ice, a polynya, or both develops in the vicinity of the feature in question. As these results are quantified in terms of spatial cross correlation, a potential role is inferred for seabed topography in such fluctuations in the sea ice about Antarctica.

Deveaux, Richard D.↗
NASA NTRS1995

Polarimetric Signatures of Sea Ice: Theoretical Model - Part 1

Physical, structural, and electromagnetic properties and interrelating processes in sea ice are used to develop a composite model for polarimetric backscattering signatures of sea ice. Physical properties of sea ice constituents such as ice, brine, air, and salt are presented in terms of their effects on electromagnetic wave interactions. Sea ice structure and geometry of scatterers are related to wave propagation, attenuation, and scattering. Temperature and salinity, which are determining factors for the thermodynamic phase distribution in sea ice, are consistently used to derive both effective permittivities and polarimetric scattering coefficients. Polarimetric signatures of sea ice depend on crystal sizes and brine volumes, which are affected by ice growth rates. Desalination by brine expulsion, drainage, or other mechanisms modifies wave penetration and scattering. Sea ice signatures are further complicated by surface conditions such as rough interfaces, hummocks, snow cover, brine skim, or slush layer. Based on the same set of geophysical parameters characterizing sea ice, a composite model is developed to calculate effective permittivities and backscattering covariance matrices at microwave frequencies for interpretation of sea ice polarimetric signatures.

Nghiem, S. V.↗
NASA NTRS1997

A Microwave Technique for Mapping Ice Temperature in the Arctic Seasonal Sea Ice Zone

A technique for deriving ice temperature in the Arctic seasonal sea ice zone from passive microwave radiances has been developed. The algorithm operates on brightness temperatures derived from the Special Sensor Microwave/Imager (SSM/I) and uses ice concentration and type from a previously developed thin ice algorithm to estimate the surface emissivity. Comparisons of the microwave derived temperatures with estimates derived from infrared imagery of the Bering Strait yield a correlation coefficient of 0.93 and an RMS difference of 2.1 K when coastal and cloud contaminated pixels are removed. SSM/I temperatures were also compared with a time series of air temperature observations from Gambell on St. Lawrence Island and from Point Barrow, AK weather stations. These comparisons indicate that the relationship between the air temperature and the ice temperature depends on ice type.

St.Germain, Karen M.↗
NASA NTRS2020

Arctic Ocean Primary Productivity: The Response of Marine Algae to Climate Warming and Sea Ice Decline

Autotrophic single-celled algae living in sea ice (ice algae) and water column (phytoplankton) are the main primary producers in the Arctic Ocean. Through photosynthesis, they transform dissolved inorganic carbon into organic material. Consequently, primary production provides a key ecosystem service by providing energy to the entire food web in the oceans. Primary productivity is strongly dependent upon light availability and the presence of nutrients, and thus is highly seasonal in the Arctic. The melting and retreat of sea ice during spring are strong drivers of primary production in the Arctic Ocean and its adjacent shelf seas, owing to enhanced light availability and stratification (Barber et al. 2015; Leu et al. 2015; Ardyna et al. 2017). Recent studies have emphasized that primary production occurs under lower light conditions and earlier in the seasonal cycle than previously recognized (Randelhoff et al. 2020). Other studies suggest that increased nutrient supply have also influenced overall production (Henley et al. 2020; Lewis et al. 2020). Furthermore, while declines in Arctic sea ice extent over the past several decades (see essay Sea Ice) have contributed substantially to shifts in primary productivity throughout the Arctic Ocean, the response of primary production to sea ice loss has been both seasonally and spatially variable (e.g., Tremblay et al. 2015; Hill et al. 2018). Here we present satellite-based estimates of algal chlorophyll-a (occurring in all species of phytoplankton), based on ocean color, and subsequently provide calculated primary production estimates. These results are shown for ocean areas with less than 10% sea ice concentration and, therefore, do not include production by sea ice algae or under-ice phytoplankton blooms, which can be significant (e.g., Lalande et al. 2019).

K. E. Frey↗
NASA NTRS1983

Nimbus 7 SMMR observations of the Bering Sea ice cover during March 1979

Sea ice concentration contour maps derived from the 0.81 cm wavelength channels on the Nimbus 7 scanning multichannel microwave radiometer (SMMR) are compared with surface and aircraft data and with sea ice charts derived from the TIROS-N satellite imagery. The regional ice and weather data and the derivation of the TIROS ice charts are discussed, and the Nimbus 7 SMMR data and the physical basis of the algorithm used to retrieve ice concentrations are described. A detailed comparison of the SMMR imagery with all available surface, satellite, and meteorological data for two days in March, 1979 is made. The results show that the ice concentration maps derived from the 0.81 cm wavelength SMMR radiances provide accurate information on both the ice edge position and the location of low and high ice concentration regions within the Bering Sea pack ice.

Cavalieri, D. J.↗
NASA NTRS2011

Observations of Recent Arctic Sea Ice Volume Loss and Its Impact on Ocean-Atmosphere Energy Exchange and Ice Production

Using recently developed techniques we estimate snow and sea ice thickness distributions for the Arctic basin through the combination of freeboard data from the Ice, Cloud, and land Elevation Satellite (ICESat) and a snow depth model. These data are used with meteorological data and a thermodynamic sea ice model to calculate ocean-atmosphere heat exchange and ice volume production during the 2003-2008 fall and winter seasons. The calculated heat fluxes and ice growth rates are in agreement with previous observations over multiyear ice. In this study, we calculate heat fluxes and ice growth rates for the full distribution of ice thicknesses covering the Arctic basin and determine the impact of ice thickness change on the calculated values. Thinning of the sea ice is observed which greatly increases the 2005-2007 fall period ocean-atmosphere heat fluxes compared to those observed in 2003. Although there was also a decline in sea ice thickness for the winter periods, the winter time heat flux was found to be less impacted by the observed changes in ice thickness. A large increase in the net Arctic ocean-atmosphere heat output is also observed in the fall periods due to changes in the areal coverage of sea ice. The anomalously low sea ice coverage in 2007 led to a net ocean-atmosphere heat output approximately 3 times greater than was observed in previous years and suggests that sea ice losses are now playing a role in increasing surface air temperatures in the Arctic.

Kurtz, N. T.↗