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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.

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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Observing rotation and deformation of sea ice with synthetic aperture radar

The ESA's ERS-1 satellite will carry SARs over the polar regions; an important component in the use of these data is an automated scheme for the extraction of sea ice velocity fields from a sequence of SAR images of the same geographical region. The image pyramid area-correlation hierarchical method is noted to be vulnerable to uncertainties for sea ice rotations greater than 10-15 deg between SAR observations. Rotation-invariant methods can successfully track isolated floes in the marginal ice zone. Hu's (1962) invariant moments are also worth considering as a possible basis for rotation-invariant tracking methods. Feature tracking is inherently robust for tracking rotating sea ice, but is limited when features are floe-lead boundaries. A variety of techniques appears neccessary.

Vesecky, J. F.↗
NASA NTRS2001

The Potential of Using Landsat 7 Data for the Classification of Sea Ice Surface Conditions During Summer

During spring and summer, the Surface of the Arctic sea ice cover undergoes rapid changes that greatly affect the surface albedo and significantly impact the further decay of the sea ice. These changes are primarily the development of a wet snow cover and the development of melt ponds. As melt pond diameters generally do not exceed a couple of meters, the spatial resolutions of sensors like AVHRR and MODIS are too coarse for their identification. Landsat 7, on the other hand, has a spatial resolution of 30 m (15 m for the pan-chromatic band). The different wavelengths (bands) from blue to near-infrared offer the potential to distinguish among different surface conditions. Landsat 7 data for the Baffin Bay region for June 2000 have been analyzed. The analysis shows that different surface conditions, such as wet snow and meltponded areas, have different signatures in the individual Landsat bands. Consistent with in-situ albedo measurements, melt ponds show up as blueish whereas dry and wet ice have a white to gray appearance in the Landsat true-color image. These spectral differences enable the distinction of melt ponds. The melt pond fraction for the scene studied in this paper was 37%.

Markus, Thorsten↗
NASA NTRS1991

A comparison of sea ice parameters computed from Advanced Very High Resolution Radiometer and Landsat satellite imagery and from airborne passive microwave radiometry

AVHRR-derived sea ice parameters from the Bering Sea are compared with those computed from nearly coincident (within 6 hr) Landsat MSS imagery and from the Aircraft Multichannel Microwave Radiometer (AMMR) flown on the NASA DC-8 in order to evaluate the accuracy and reliability of AVHRR-mapped sea-ice concentration and ice edge. Mean ice-concentration differences between AVHRR near-infrared (channel 2) and Landsat MSS data ranged from -0.8 to 1.8 percent with a mean value of 0.5 percent; rms differences ranged from 6.8 to 17.7 percent. Mean differences were larger for AVHRR thermal infrared (channel 4) ice concentrations ranging from -2.2 to 8.4 percent with rms differences from 8.6 to 26.8 percent. Mean differences between AVHRR channel 2 concentrations and the AMMR data ranged from -19.7 to 18.9 percent, while rms values went from 17.0 to 44.8 percent.

Emery, W. J.↗
NASA NTRS2017

The Regional Influence of the Arctic Oscillation and Arctic Dipole on the Wintertime Arctic Surface Radiation Budget and Sea Ice Growth

An analysis of 2000-2015 monthly Clouds and the Earth's Radiant Energy System-Energy Balanced and Filled (CERES-EBAF) and Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA2) data reveals statistically significant fall and wintertime relationships between Arctic surface longwave (LW) radiative flux anomalies and the Arctic Oscillation (AO) and Arctic Dipole (AD). Signifying a substantial regional imprint, a negative AD index corresponds with positive downwelling clear-sky LW flux anomalies (greater than10W m(exp -2)) north of western Eurasia (0 deg E-120 deg E) and reduced sea ice growth in the Barents and Kara Seas in November-February. Conversely, a positive AO index coincides with negative clear-sky LW flux anomalies and minimal sea ice growth change in October-November across the Arctic. Increased (decreased) atmospheric temperature and water vapor coincide with the largest positive (negative) clear-sky flux anomalies. Positive surface LW cloud radiative effect anomalies also accompany the negative AD index in December-February. The results highlight a potential pathway by which Arctic atmospheric variability influences the regional surface radiation budget over areas of Arctic sea ice growth.

Hegyi, Bradley M.↗
NASA NTRS1989

Review and status of remote sensing of sea ice

The status of obtaining geophysical observations through the interpretation of satellite data over sea ice is discussed. It is pointed out that the community working in this area has grown in size and sophistication over the last decade, that the connection between microscopic properties of ice and its microwave behavior is now being understood, and that a good deal of accurate satellite-derived information on sea ice can now be obtained. Areas of ongoing, as well as needed, work are outlined, especially in the understanding of first-year- and old-ice microwave properties, and it is pointed out that the efficient advance of remote sensing will require more active participation of scientists focused on in situ studies.

Carsey, Frank↗
NASA NTRS2001

Correlation Studies of Sea Ice Concentration with Surface Temperature and Meltponding

The spatial and temporal variability of sea ice concentrations derived from passive microwave data is studied in conjunction with co-registered high resolution infrared and visible satellite data. Cloud free infrared and visible data provide surface temperature and large scale surface characteristics, respectively, that can be used to better understand regional and seasonal fluctuations in ice concentrations. Results from correlation analysis of ice concentration versus surface temperature data show the intuitively expected negative relationship but the strength in the relationship is unexpectedly very strong. In the Antarctic, the correlation is consistently very high spatially when yearly anomalies are used, and not so high in some areas when seasonal anomalies are used, especially during spring and summer. In the monthly anomalies, the correlation is also good, especially in dynamically active regions. The expanse in the anomalies in surface temperature are shown to go way beyond the sea ice regions into the open ocean and continental areas, suggesting strong atmospheric forcing. Weak correlations are normally found in highly consolidated areas, where large changes in temperature do not cause large changes in ice concentration on a short term, and in open ocean polynya areas, where the change in ice concentration may be cause by melt from the underside of the ice. In the Arctic, strong correlations between surface temperature and ice concentration are evident for all seasons except during the summer. In the summer, factors such as meltponding, surface wetness, and ice breakup, as detected by high resolution visible data, contributes to larger uncertainties in the determination of ice concentration and the lack of good correlation of the variables.

Comiso, J. C.↗
NASA NTRS2011

Large-Scale Surveys of Snow Depth on Arctic Sea Ice from Operation IceBridge

We show the first results of a large ]scale survey of snow depth on Arctic sea ice from NASA fs Operation IceBridge snow radar system for the 2009 season and compare the data to climatological snow depth values established over the 1954.1991 time period. For multiyear ice, the mean radar derived snow depth is 33.1 cm and the corresponding mean climatological snow depth is 33.4 cm. The small mean difference suggests consistency between contemporary estimates of snow depth with the historical climatology for the multiyear ice region of the Arctic. A 16.5 cm mean difference (climatology minus radar) is observed for first year ice areas suggesting that the increasingly seasonal sea ice cover of the Arctic Ocean has led to an overall loss of snow as the region has transitioned away from a dominantly multiyear ice cover.

Kurtz, Nathan T.↗
NASA NTRS2020

Arctic Snow Depth and Sea Ice Thickness From ICESat‐2 and CryoSat‐2 Freeboards: A First Examination

We present a first examination of Arctic sea ice snow depth estimates from differencing satellite lidar (ICESat‐2) and radar (CryoSat‐2) freeboards. These estimates cover the period between 14 October 2018 and the end of April 2019. Snow depth is related to freeboard differences by the refractive index/bulk density of the snow layer—the only free parameter in the approach. Area‐averaged snow depth ranges from 9 cm (on first‐year ice: 5 cm, multiyear ice: 14 cm) in late October to 19 cm (first‐year ice: 17 cm, multiyear ice: 27 cm) in April; on average, this snow is thinner over FYI. Spatial patterns and gradients of snow depth estimates compare well with reconstructions using snowfall from ERA‐Interim and ERA5, although snowfall from ERA5 is systematically higher. For all months, the results suggest that ~50% of the total freeboard is comprised of snow. Retrievals are within a few centimeters of snow depth data acquired by Operation IceBridge in April 2019. Sources of uncertainties associated with this freeboard‐differencing approach are discussed. Further, sea ice thicknesses calculated using the retrieved snow depth and a modified climatology are contrasted. Comparatively, the snow depth and calculated ice thickness using a modified climatology are higher by ~5 cm and 0.33 m, although these differences are not uniform throughout the season. Snow accumulation was slower between October and December but increased between December and January, unlike the modified climatology, which exhibited a monotonic accumulation for all months. Future opportunities for assessment and improvement of these estimates are discussed.

Arctic Ocean↗
NASA NTRS1973

Sea ice and surface water circulation, Alaskan continental shelf

The author has identified the following significant results. Sediments contributed by the Copper River in the Gulf of Alaska are carried westward along the shore as a distinct plume. Oceanic water relatively poor in suspended material appears to intrude near Montague Island, and turbid water between Middleton Island and Kayak Island is the result of Ekman between transport. An anticlockwise surface water circulation is observed in this region. Ground truth data indicate striking similarity with ERTS-1 imagery obtained on October 12, 1972. Observations of ERTS-1 imagery reveal that various characteristics and distribution of sea ice in the Arctic Ocean can be easily studied. Formation of different types of sea ice and their movement is quite discrenible. Sea ice moves parallel to the cost in near shore areas and to the northerly direction away from the coast.

Wright, F. F.↗
NASA NTRS1984

Dynamics of coupled ice-ocean system in the marginal ice zone: Study of the mesoscale processes and of constitutive equations for sea ice

This study is aimed at the modelling of mesoscale processed such as up/downwelling and ice edge eddies in the marginal ice zones. A 2-dimensional coupled ice-ocean model is used for the study. The ice model is coupled to the reduced gravity ocean model (f-plane) through interfacial stresses. The constitutive equations of the sea ice are formulated on the basis of the Reiner-Rivlin theory. The internal ice stresses are important only at high ice concentrations (90-100%), otherwise the ice motion is essentially free drift, where the air-ice stress is balanced by the ice-water stress. The model was tested by studying the upwelling dynamics. Winds parallel to the ice edge with the ice on the right produce upwilling because the air-ice momentum flux is much greater that air-ocean momentum flux, and thus the Ekman transport is bigger under the ice than in the open water. The upwelling simulation was extended to include temporally varying forcing, which was chosen to vary sinusoidally with a 4 day period. This forcing resembles successive cyclone passings. In the model with a thin oceanic upper layer, ice bands were formed.

Hakkinen, S.↗
NASA NTRS1996

(abstract) High-Resolution Satellite Microwave Radar Observation of Climate-Related Sea-Ice Anomalies

Since 1991 a suite of international satellites have collected large amounts of high-resolution microwave radar images over Arctic and Antarctic sea ice. Together with complementary synthetic aperture radar (SAR) 100 m resolution microwave imaging, these data provide a powerful tool for addressing the characteristics of sea ice which directly influence the polar oceans and climate.

NSCAT Arctic Antarctic imaging open-ocean polynyas↗
NASA NTRS2007

Physical and Radiative Characteristics and Long Term Variability of the Okhotsk Sea Ice Cover

Much of what we know about the large scale characteristics of the Okhotsk Sea ice cover comes from ice concentration maps derived from passive microwave data. To understand what these satellite data represents in a highly divergent and rapidly changing environment like the Okhotsk Sea, we analyzed concurrent satellite, aircraft, and ship data and characterized the sea ice cover at different scales from meters to tens of kilometers. Through comparative analysis of surface features using co-registered data from visible, infrared and microwave channels we evaluated how the general radiative and physical characteristics of the ice cover changes as well as quantify the distribution of different ice types in the region. Ice concentration maps from AMSR-E using the standard sets of channels, and also only the 89 GHz channel for optimal resolution, are compared with aircraft and high resolution visible data and while the standard set provides consistent results, the 89 GHz provides the means to observe mesoscale patterns and some unique features of the ice cover. Analysis of MODIS data reveals that thick ice types represents about 37% of the ice cover indicating that young and new ice represent a large fraction of the lice cover that averages about 90% ice concentration, according to passive microwave data. A rapid decline of -9% and -12 % per decade is observed suggesting warming signals but further studies are required because of aforementioned characteristics and because the length of the ice season is decreasing by only 2 to 4 days per decade.

Nishio, Fumihiko↗
NASA NTRS2020

Enhanced Eddy Activity in the Beaufort Gyre in Response to Sea Ice Loss

The Beaufort Gyre freshwater content has increased since the 1990s, potentially stabilizing in recent years. The mechanisms proposed to explain the stabilization involve either mesoscale eddy activity that opposes Ekman pumping or the reduction of Ekman pumping due to reduced sea ice?ocean surface stress. However, the relative importance of these mechanisms is unclear. Here, we present observational estimates of the Beaufort Gyre mechanical energy budget and show that energy dissipation and freshwater content stabilization by eddies increased in the late-2000s. The loss of sea ice and acceleration of ocean currents after 2007 resulted in enhanced mechanical energy input but without corresponding increases in potential energy storage. To balance the energy surplus, eddy dissipation and its role in gyre stabilization must have increased after 2007. Our results imply that declining Arctic sea ice will lead to an increasingly energetic Beaufort Gyre with eddies playing a greater role in its stabilization.

Armitage, Thomas W.K.↗
NASA NTRS2014

Profiling Sea Ice with a Multiple Altimeter Beam Experimental Lidar (MABEL)

The sole instrument on the upcoming ICESat-2 altimetry mission is a micropulse lidar that measures the time-of-flight of individual photons from laser pulses transmitted at 532 nm. Prior to launch, MABEL serves as an airborne implementation for testing and development. In this paper, we provide a first examination of MABEL data acquired on two flights over sea ice in April 2012: one north of the Arctic coast of Greenland, and the other in the East Greenland Sea.We investigate the phenomenology of photon distributions in the sea ice returns. An approach to locate the surface and estimate its elevation in the distributions is described, and its achievable precision assessed. Retrieved surface elevations over relatively flat leads in the ice cover suggest that precisions of several centimeters are attainable. Restricting the width of the elevation window used in the surface analysis can mitigate potential biases in the elevation estimates due to subsurface returns at 532 nm. Comparisons of nearly coincident elevation profiles from MABEL with those acquired by an analog lidar show good agreement.Discrimination of ice and open water, a crucial step in the determination of sea ice free board and the estimation of ice thickness, is facilitated by contrasts in the observed signal background photon statistics. Future flight lines will sample a broader range of seasonal ice conditions for further evaluation of the year-round profiling capabilities and limitations of the MABEL instrument.

Lidar↗
NASA NTRS2018

Snow in the Changing Sea-Ice Systems

Snow is the most reflective, and also the most insulative, natural material on Earth. Consequently, it is an integral part of the sea-ice and climate systems. However, the spatial and temporal heterogeneities of snow pose challenges for observing, understanding and modelling those systems under anthropogenic warming. Here, we survey the snow-ice system, then provide recommendations for overcoming present challenges. These include: collecting process-oriented observations for model diagnostics and understanding snow-ice feedbacks, and improving our remote sensing capabilities of snow for monitoring large-scale changes in snow on sea ice. These efforts could be achieved through stronger coordination between the observational, remote sensing and modelling communities, and would pay dividends through distinct improvements in predictions of polar environments.

Snow↗
NASA NTRS1993

A recent sea-ice retreat west of the Antarctic Peninsula

Satellite passive microwave data show a record decrease in sea ice extent in the Bellingshausen Sea from mid-1988 through early 1991. The change coincides with more southerly surface winds, increased cyclonic activity and rising surface air temperatures, which reached historic highs along the west coast of the Antarctic Peninsula in 1989. Preceded by high ice cover in 1986-87, the retreat was most evident during summer in the formerly perennial sea-ice field over the continental shelf. Ocean heat storage probably contributed to the persistence and coastal propagation of this anomaly.

Jacobs, Stan S.↗