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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 415 records · Page 23
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NASA NTRS2010

Using the MicroASAR on the NASA SIERRA UAS in the Characterization of Arctic Sea Ice Experiment

The MicroASAR is a flexible, robust SAR system built on the successful legacy of the BYU microSAR. It is a compact LFM-CW SAR system designed for low-power operation on small, manned aircraft or UAS. The NASA SIERRA UAS was designed to test new instruments and support flight experiments. NASA used the MicroASAR on the SIERRA during a science field campaign in 2009 to study sea ice roughness and break-up in the Arctic and high northern latitudes. This mission is known as CASIE-09 (Characterization of Arctic Sea Ice Experiment 2009). This paper describes the MicroASAR and its role flying on the SIERRA UAS platform as part of CASIE-09.

CASIE-09(CHARACTERIZATION OF ARCTIC SEA ICE EXPERI↗
NASA NTRS1971

Remote Sensing of Sea Ice from Earth Satellites

The application of meteorological satellite data for mapping ice fields is discussed. The characteristics of the photographic records of sea ice formations are described. The derivation of the composite minimum brightness chart by computer processing of the mapped satellite vidicon data for several successive days is explained. The factors which create a quantitative delimiting of the sea ice conditions are explained.

Mcclain, E. P.↗
NASA NTRS2012

Evaluation of Arctic Sea Ice Thickness Simulated by Arctic Ocean Model Intercomparison Project Models

Six Arctic Ocean Model Intercomparison Project model simulations are compared with estimates of sea ice thickness derived from pan-Arctic satellite freeboard measurements (2004-2008); airborne electromagnetic measurements (2001-2009); ice draft data from moored instruments in Fram Strait, the Greenland Sea, and the Beaufort Sea (1992-2008) and from submarines (1975-2000); and drill hole data from the Arctic basin, Laptev, and East Siberian marginal seas (1982-1986) and coastal stations (1998-2009). Despite an assessment of six models that differ in numerical methods, resolution, domain, forcing, and boundary conditions, the models generally overestimate the thickness of measured ice thinner than approximately 2 mand underestimate the thickness of ice measured thicker than about approximately 2m. In the regions of flat immobile landfast ice (shallow Siberian Seas with depths less than 25-30 m), the models generally overestimate both the total observed sea ice thickness and rates of September and October ice growth from observations by more than 4 times and more than one standard deviation, respectively. The models do not reproduce conditions of fast ice formation and growth. Instead, the modeled fast ice is replaced with pack ice which drifts, generating ridges of increasing ice thickness, in addition to thermodynamic ice growth. Considering all observational data sets, the better correlations and smaller differences from observations are from the Estimating the Circulation and Climate of the Ocean, Phase II and Pan-Arctic Ice Ocean Modeling and Assimilation System models.

sea ice↗
NASA NTRS1984

Antarctic sea ice microwave signatures and their correlation with in situ ice observations

The general characteristics and microwave radiative properties of sea ice in the Weddell Sea region during the onset of spring are studied by using the Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) and other satellite sensors, in conjunction with in situ observations from the Mikhail Somov. The position of the ice edge, the gradient of ice concentration, and the width of the Marginal Ice Zone are inferred from the microwave data, and are found to be consistent with ship observations, especially at 18 GHz. The sensitivities of the various SMMR frequencies to surface and other effects are investigated by using multispectral cluster analysis. The results show considerable variability in emissivity, especially at 37 GHz, likely associated with varying degrees of surface wetness. Ice concentrations are derived by using two methods: one that assumes fixed emissivities for consolidated ice and an iterative procedure that accounts for the variable emissivities observed. Using the procedure that allows the emissivities to be variable gives ice concentrations that are more consistent with qualitative field observations.

Comiso, J. C.↗
NASA NTRS1991

Multi-frequency, multi-polarization SAR and radiometer sea ice classification

Microwave remotely sensed data were acquired simultaneously in March 1988 over Beaufort, Chukchi, and Bering Sea ice using the JPL multifrequency, polarimetric synthetic aperture radar (SAR), and multifrequency dual-polarization GSFC radiometer. The experiment was conducted as a series of coordinated underflights of the DMSP SSM/I satellite radiometer to validate ice products derived from its radiance values. Concurrent flights by an NRL P-3 aircraft enabled overlapping high-resolution, single-frequency images to be acquired over the same surfaces using a Ka-band scanning microwave radiometer. Precise coregistration to an accuracy of 100 m, +/- 25 m enables comparison of temporally and spatially coincident active and passive microwave datasets. Three-channel polarimetric SAR data are compared with dual-polarized radiometer data at several SSM/I frequencies, showing backscatter signatures to be highly correlated with radiometric temperatures. Further comparisons are used to evaluate ice concentration retrievals and to show how multiparameter datasets can be used to resolve ambiguities present in identifying certain sea ice forms with a single microwave instrument.

Drinkwater, Mark R.↗
NASA NTRS2012

Arctic Sea Ice Freeboard from Icebridge Acquisitions in 2009: Estimates and Comparisons with ICEsat

During the spring of 2009, the Airborne Topographic Mapper (ATM) system on the IceBridge mission acquired cross-basin surveys of surface elevations of Arctic sea ice. In this paper, the total freeboard derived from four 2000 km transects are examined and compared with those from the 2009 ICESat campaign. Total freeboard, the sum of the snow and ice freeboards, is the elevation of the air-snow interface above the local sea surface. Prior to freeboard retrieval, signal dependent range biases are corrected. With data from a near co-incident outbound and return track on 21 April, we show that our estimates of the freeboard are repeatable to within 4 cm but dependent locally on the density and quality of sea surface references. Overall difference between the ATM and ICESat freeboards for the four transects is 0.7 (8.5) cm (quantity in bracket is standard deviation), with a correlation of 0.78 between the data sets of one hundred seventy-eight 50 km averages. This establishes a level of confidence in the use of ATM freeboards to provide regional samplings that are consistent with ICESat. In early April, mean freeboards are 41 cm and 55 cm over first year and multiyear sea ice (MYI), respectively. Regionally, the lowest mean ice freeboard (28 cm) is seen on 5 April where the flight track sampled the large expanse of seasonal ice in the western Arctic. The highest mean freeboard (71 cm) is seen in the multiyear ice just west of Ellesmere Island from 21 April. The relatively large unmodeled variability of the residual sea surface resolved by ATM elevations is discussed.

Airborne Topographic Mapper (ATM)↗
NASA NTRS1996

Backscatter for Ice Sheet 2 Growth Phase in the Winter 1994 Winter Sea Ice Experiment

None. This is raw data from a data set taken during the CRRELEX94 experiment. The data are polarimetric C-band radar measurements of a saline ice sheet grown in the outdoor Geophysical Research Facility at the Cold Regions Research and Engineering Lab. See references for other descriptions of data.

sea ice ice sheet backscatter sea ice backscatter ↗
NASA NTRS1992

On the application of multifrequency polarimetric radar observations for sea-ice classification

The use of multifrequency polarimetric radar imagery to enhance the ability to separate different sea-ice types using single-frequency, single-polarization synthetic aperture radar (SAR) data is investigated. Backscatter characteristics of six radiometrically and polarimetrically distinct sea-ice types are selected in an unsupervised range-dependent analysis of multifrequency polarimetric SAR data using the maximum a posteriori (MAP) polarimetric classifier. Maximum ice discrimination is achieved with combined C- and L-band full polarimetry, and collocated passive microwave imagery suggests greater than 90 percent classification accuracy. C-band VV-pol alone achieves only 68 percent relative accuracy because it confuses multiyear and rough compressed first year ice. L-band, relative classification accuracy is 75 percent, 83 percent, and 85 percent, using HH-pol, HH- and VV-combined, or the full polarimetry, respectively. P-band is less accurate. Combinations of two frequencies at a single polarization show the greatest improvement over a single channel.

Rignot, Eric↗
NASA NTRS1991

Multifrequency polarimetric synthetic aperture radar observations of sea ice

The present study introduces a fully polarimetric airborne SAR data set of sea ice. Images were acquired in the Beaufort, Bering, and Chukchi seas in March 1988. Statistics of the magnitude, phase, and polarization of complex backscattered signals recorded by three-frequency SAR are examined for various scenes with different ice characteristics. Results indicate that combinations of frequency and polarization enhance current capability to distinguish ice of different properties using single-frequency fixed-polarization-microwave radar. A specific example is the polarimetric identification of new ice formation which may not be easily distinguished in ERS-1 5.3-GHz VV polarization of SAR data. Such findings are consistent with theoretical model simulations of scattering characteristics of sea ice.

Drinkwater, Mark R.↗
NASA NTRS1992

A toy model linking atmospheric thermal radiation and sea ice growth

A simplified analytical model of sea ice growth is presented where the atmosphere is in thermal radiative equilibrium with the ice. This makes the downwelling longwave radiation reaching the ice surface an internal variable rather than a specified forcing. Analytical results demonstrate how the ice state depends on properties of the ice and on the externally specified climate.

Thorndike, A. S.↗
NASA NTRS1994

On the Validation of Satellite-Derived Sea Ice Surface Temperature

The surface temperature of sea ice controls the rate of ice growth and heat exchange between the ocean and the atmosphere. An algorithm for the satellite retrieval of ice surface temperature has recently been published, but due to the lack of validation data has not been extensively tested. In this paper, data from a recent Arctic field experiment is used in an attempt to validate that algorithm. While the procedure is, in principle, straightforward, we demonstrate that validation is complicated by a variety of factors, including incorrectly assumed atmospheric conditions, undetected clouds in the satellite data, spatial and temporal variability in the surface temperature field, and surface and satellite measurement errors. Comparisons between surface temperatures determined from upwelling broadband longwave radiation, spatial measurements of narrow-band radiation, thermocouples buried just below the snow surface, and narrow-band satellite data show differences of 1 to 3 deg. C. The range in these independent measurements indicates the need for specially designed validation experiments utilizing narrow-band radiometers on aircraft to obtain broad spatial coverage.

Key, J.↗
NASA NTRS1998

Modal Behavior of Hemispheric Sea Ice Covers

Recent papers have described 18-year trends and annual oscillations in the Arctic and Antarctic sea ice extents, areas, and enclosed open water areas based on a newly-formulated 18.2-year ice concentration time series. This time series includes data for the entire Arctic and Antarctic ice covers, as well as for previously defined subregions consisting of 5 sectors in the Antarctic and 9 regions in the Arctic. It was obtained by fine-tuning the sea ice algorithm tie points individually for each of the four sensors used to acquire the data. In this paper, we extend these analyses to an examination of the intrinsic modes of these time series, obtained by means of Empirical Mode Decomposition, with emphasis on periodicities greater than the annual cycle. Quasibiennial and quasiquadrennial oscillations observed with a different technique and reported earlier for the first 8.8 years of this time series were also observed in the present series. However, the intrinsic modes were not monochromatic; they feature frequency as well as amplitude modulation within their respective frequency bands. Modal periods of up to 18 years are observed, with important implications for the trend analyses published earlier. These results are compared with the oscillations in the Length-of-Day and North Atlantic Oscillation parameters similarly determined for the same 18.2-year period.

Gloersen, Per↗
NASA NTRS2004

Annual Cycles of Multiyear Sea Ice Coverage of the Arctic Ocean: 1999-2003

For the years 1999-2003, we estimate the time-varying perennial ice zone (PIZ) coverage and construct the annual cycles of multiyear (MY, including second year) ice coverage of the Arctic Ocean using QuikSCAT backscatter, MY fractions from RADARSAT, and the record of ice export from satellite passive microwave observations. An area balance approach extends the winter MY coverage from QuikSCAT to the remainder of the year. From these estimates, the coverage of MY ice at the beginning of each year is 3774 x 10(exp 3) sq km (2000), 3896 x 10(exp 3) sq km (2001), 4475 x 10(exp 3) sq km (2002), and 4122 x 10(exp 3) sq km (2003). Uncertainties in coverage are approx.150 x 10(exp 3) sq km. In the mean, on 1 January, MY ice covers approx.60% of the Arctic Ocean. Ice export reduces this coverage to approx.55% by 1 May. From the multiple annual cycles, the area of first-year (FY) ice that survives the intervening summers are 1192 x 10(exp 3) sq km (2000), 1509 x 10(exp 3) sq km (2001), and 582 x 10(exp 3) sq km (2002). In order for the MY coverage to remain constant from year to year, these replenishment areas must balance the overall area export and melt during the summer. The effect of the record minimum in Arctic sea ice area during the summer of 2002 is seen in the lowest area of surviving FY ice of the three summers. In addition to the spatial coverage, the location of the PIZ is important. One consequence of the unusual location of the PIZ at the end of the summer of 2002 is the preconditioning for enhanced export of MY ice into the Barents and Kara seas. Differences between the minimums in summer sea ice coverage from our estimates and passive microwave observations are discussed.

Arctic Ocean↗
NASA NTRS1988

Numerical simulations of the profile properties of undeformed first-year sea ice during the growth season

A model is presented for estimating salinity profiles for the first-year sea ice during the growth season, in which ice growth equations were coupled with salt entrapment and brine drainage relations to obtain the relationship between the initial ice salinity and the ice-growth velocity and seawater salinity, as well as the subsequent drainage of brine from the ice. The results obtained were found to be in reasonable agreement with field observations in that they showed characteristic C-shaped profiles similar to natural profiles. The average ice salinity values were also in reasonable agreement with field data. The predicted ice property profiles give composite plate properties that are significantly different from bulk property estimates that would result by assuming that sea ice could be represented as a homogeneous plate.

Cox, G. F. N.↗
NASA NTRS1991

Ku band airborne radar altimeter observations of marginal sea ice during the 1984 Marginal Ice Zone Experiment

Pulse-limited, airborne radar data taken in June and July 1984 with a 13.8-GHz altimeter over the Fram Strait marginal ice zone are analyzed with the aid of large-format aerial photography, airborne synthetic aperture radar data, and surface observations. Variations in the radar return pulse waveforms are quantified and correlated with ice properties recorded during the Marginal Ice Zone Experiment. Results indicate that the wide-beam altimeter is a flexible instrument, capable of identifying the ice edge with a high degree of accuracy, calculating the ice concentration, and discriminating a number of different ice classes. This suggests that microwave radar altimeters have a sensitivity to sea ice which has not yet been fully exploited. When fused with SSM/I, AVHRR and ERS-1 synthetic aperture radar imagery, future ERS-1 altimeter data are expected to provide some missing pieces to the sea ice geophysics puzzle.

Drinkwater, Mark R.↗
NASA NTRS1991

Antarctic Sea ice variations and seasonal air temperature relationships

Data through 1987 are used to determine the regional and seasonal dependencies of recent trends of Antarctic temperature and sea ice. Lead-lag relationships involving regional sea ice and air temperature are systematically evaluated, with an eye toward the ice-temperature feedbacks that may influence climatic change. Over the 1958-1087 period the temperature trends are positive in all seasons. For the 15 years (l973-l987) for which ice data are available, the trends are predominantly positive only in winter and summer, and are most strongly positive over the Antarctic Peninsula. The spatially aggregated trend of temperature for this latter period is small but positive, while the corresponding trend of ice coverage is small but negative. Lag correlations between seasonal anomalies of the two variables are generally stronger with ice lagging the summer temperatures and with ice leading the winter temperatures. The implication is that summer temperatures predispose the near-surface waters to above-or below-normal ice coverage in the following fall and winter.

Weatherly, John W.↗