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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

EOS Aqua AMSR-E Arctic Sea Ice Validation Program

A coordinated Arctic sea ice validation field campaign using the NASA Wallops P-3B aircraft was successfully completed in March 2003. 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 include sea ice concentration, sea ice temperature, and snow depth on sea ice. The primary instrument on the P-3B aircraft was the NOAA ETL Polarimetric Scanning Radiometer (PSR) covering the same frequencies and polarizations as the AMSR-E. This paper describes 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. The remaining flights covered portions of the Bering Sea ice edge, the Chukchi Sea, and Norton Sound. Comparisons among the satellite and aircraft PSR data sets are presented.

Cavalieri, D. J.↗
NASA NTRS1987

On the relationship between atmospheric circulation and the fluctuations in the sea ice extents of the Bering and Okhotsk Seas

The influence of the hemispheric atmospheric circulation on the sea ice covers of the Bering Sea and the Sea of Okhotsk is examined using data obtained with the Nimbus 5 electrically scanning microwave radiometer for the four winters of the 1973-1976 period. The 3-day averaged sea ice extent data were used to establish periods for which there is an out-of-phase relationship between fluctuations of the two ice covers. A comparison of the sea-level atmospheric pressure field with the seasonal, interannual, and short-term sea ice fluctuations reveal an association between changes in the phase and the amplitude of the long waves in the atmosphere and advance and retreat of Arctic ice covers.

Cavalieri, D. J.↗
NASA NTRS2001

Satellite Remote Sensing: Passive-Microwave Measurements of Sea Ice

Satellite passive-microwave measurements of sea ice have provided global or near-global sea ice data for most of the period since the launch of the Nimbus 5 satellite in December 1972, and have done so with horizontal resolutions on the order of 25-50 km and a frequency of every few days. These data have been used to calculate sea ice concentrations (percent areal coverages), sea ice extents, the length of the sea ice season, sea ice temperatures, and sea ice velocities, and to determine the timing of the seasonal onset of melt as well as aspects of the ice-type composition of the sea ice cover. In each case, the calculations are based on the microwave emission characteristics of sea ice and the important contrasts between the microwave emissions of sea ice and those of the surrounding liquid-water medium.

Parkinson, Claire L.↗
NASA NTRS1975

Study of sea ice in the Sea of Okhotsk and its influence on the Oyashio current

The author has identified the following significant results. Two photographic techniques were applied to Skylab S190A multispectral pictures for extracting oceanic patterns at the sea surface separately from cloud patterns. One is the image-masking technique and another a stereographic analysis. The extracted oceanic patterns were interpreted as areas where the amount, or the concentration of phytoplankton was high by utilizing surface data of water temperature, ocean current by GEK, and microplankton.

Watanabe, K.↗
NASA NTRS1992

Observing the advection of sea ice in the Weddell Sea using buoy and satellite passive microwave data

Data from four buoys tracked by Nimbus 6 and concurrent ice concentrations retrieved from Nimbus 7 scanning multichannel microwave radiometer data are used to investigate the progress and behavior of an area of sea ice as it drifts from the southwestern Weddell Sea. The overall drift characteristics and their relationship to ice edge displacement are examined within the framework of four zones. Three phases are identified in the large-scale behavior of the Weddell Sea ice cover, namely, a rapid equatorward and eastward advance, a quasi-equilibrium phase, and a period of rapid recession. Outbreaks of cold continental air alternate with incursions of relatively warm air from the north; warm conditions are recorded as far as 1200 km in from the ice edge in winter. Closed loops in the buoy trajectories, which are clockwise to the south of 63 deg S, reverse to become anticlockwise to the north. A coherence is observed in the response of the buoys to the passage of storms, even though the buoys separated by a distance of over 100 km.

Massom, Robert A.↗
NASA NTRS2018

Arctic Sea Ice and Its Role in Global Change

Sea ice is an important component of the global climate system. Sea ice forms, grows, and melts in the ocean. Sea ice grows during the fall and winter and melts during the spring and summer. Sea ice can melt completely in summer or survive multiple years. Sea ice can be classified by stages of development (thickness and age), that is, first-year sea ice (ice thickness typically <1.8 m) and multiyear sea ice (ice thickness typically >1.8 m). Sea ice occurs in both hemispheres. In the Northern Hemisphere, sea ice develops in the Arctic Ocean and surrounding bodies including Hudson and Baffin Bay, Gulf of St. Lawrence, the Greenland Sea, the Bering Sea, and the Sea of Okhotsk (sea ice can be observed as far south as Bohai Bay, China, ~38°N). In the Southern Hemisphere, sea ice only develops around Antarctica, reaching a maximum equatorward extension at around ~55°S).

Liu, Jiping↗
NASA NTRS2018

Reconstruction of Snow on Arctic Sea Ice

Snow on Arctic sea ice is a poorly observed variable that plays an important role in the Arctic climate system and impacts the remote sensing systems that monitor Arctic sea ice. We present and validate a reconstruction of Arctic snow depth based on observed sea ice motion and snowfall derived from reanalysis data. Overall, the reconstruction is in good agreement with direct measurements of snow depth from Operation IceBridge, slightly underestimating mean IceBridge snow depth. At the local scale (10 km), the reconstruction is more skilled than a weighted climatology over first year ice, but underestimates deeper snow over multiyear ice. Reconstructions of single buoy snow depths are unskilled, but the reconstruction shows skill in simulating the mean snow depth across all buoys. Spring snow depths show a lowtohigh crossArctic gradient and tend to be greatest in the Atlantic sector of the eastern Arctic. The relationship between ice type (multiyear or firstyear ice) and snow depth previously documented in the western Arctic is not evident in the eastern Arctic. Using ice type to weight snow depths for satellite ice thickness retrievals may not be justifiable in the eastern Arctic. Reconstructed snow depth across the Arctic shows significant interannual variability, suggesting that use of a fixed snow depth climatology may lead to biases in retrieved ice thickness and its variability. However, interannual variability in panArctic mean snow depth is comparable or smaller than the uncertainty in both the reconstruction and IceBridge, highlighting the need for high accuracy snow depth products and reconstructions.

sea ice↗
NASA NTRS2024

Sea ice in 2023

Antarctic sea ice extent was the lowest on record in 2023, with an annual mean of 9.81 million km 2 , beating the previous minimum of 2022. Arctic sea ice extent was also low, with an annual mean of 10.49 million km 2 , but did not break any records.

Sea ice↗
NASA NTRS1986

Surface-based passive microwave observations of sea ice in the Bering and Greenland Seas

Brightness temperatures of sea ice was measured during the Marginal Ice Zone Experiment (MIZEX) field experiments in February in the Bering Sea and in June/July in the northern Greenland Sea. In the Bering Sea thin growing sea ice types from black ice to 40 cm thick snow covered floes were investigated. Brightness temperatures increase with ice thickness up to 10 cm from values of 100 K for open water to as high as 250 K (e = 0.97) for thick ice, and a moderate dependence on snow thickness is found. In the Greenland Sea thick first and multiyear (FY, MY) ice types were studied. Brightness temperatures vary, depending on the daily melt-freeze cycle superimposed on the seasonal warming, ranging from near blackbody values for melting conditions to multiyear-like spectra when the surface layers refroze. The melt season was sufficiently advanced, however, that FY and MY ice could not be differentiated radiometrically.

Grenfell, T. C.↗
NASA NTRS2026

Changes in Arctic and Antarctic Sea-Ice Properties and Processes

Although sea ice covers ~9% of the world’s oceans, its presence, and absence, vastly alter the energetic balance of Earth’s climate. Because of geographic differences, Arctic and Antarctic sea ice have different dominant properties and processes, which produce different responses to natural variability and anthropogenic change. In this Review, we survey changes in sea-ice properties and processes of the Arctic and Antarctic environments. In the Arctic, the melt season has lengthened by ~7.4 days decade −1 (1979-2024). There has been a corresponding decrease in winter sea-ice thickness (1.6 m mean total over 1980-2023), summer surface albedo (0.03 decade −1 over 1979-2020), and spring snow depth (2.5 cm decade −1 over 1954-2024). In comparison, corresponding changes in the Antarctic are small overall due to contrasting regional and temporal trends. From a dynamic perspective, sea-ice motion in both hemispheres has increased, with 0.63 cm s −1 decade −1 in the Arctic (1978-2024) and 0.69 cm s −1 decade −1 in the Antarctic (1982-2024), whereas trends in polynya occurrence differ by region. Future research should prioritize sea-ice observations that can inform how the climate system responds to natural variability and anthropogenic change, be standardized to increase uptake by the broader scientific community, and target process-oriented interactions to support model development.

Melinda A Webster↗
NASA NTRS2013

Sea Ice

During 2013, Arctic sea ice extent remained well below normal, but the September 2013 minimum extent was substantially higher than the record-breaking minimum in 2012. Nonetheless, the minimum was still much lower than normal and the long-term trend Arctic September extent is -13.7 per decade relative to the 1981-2010 average. The less extreme conditions this year compared to 2012 were due to cooler temperatures and wind patterns that favored retention of ice through the summer. Sea ice thickness and volume remained near record-low levels, though indications are of slightly thicker ice compared to the record low of 2012.

Ice↗
NASA NTRS1991

NASA, Navy, and AES/York sea ice concentration comparison of SSM/I algorithms with SAR derived values

Previous research studies have focused on producing algorithms for extracting geophysical information from passive microwave data regarding ice floe size, sea ice concentration, open water lead locations, and sea ice extent. These studies have resulted in four separate algorithms for extracting these geophysical parameters. Sea ice concentration estimates generated from each of these algorithms (i.e., NASA/Team, NASA/Comiso, AES/York, and Navy) are compared to ice concentration estimates produced from coincident high-resolution synthetic aperture radar (SAR) data. The SAR concentration estimates are produced from data collected in both the Beaufort Sea and the Greenland Sea in March 1988 and March 1989, respectively. The SAR data are coincident to the passive microwave data generated by the Special Sensor Microwave/Imager (SSM/I).

Jentz, R. R.↗
NASA NTRSDate not supplied

A LaGrangian Perspective of the Surface Energy Budget Contributions to Sea Ice Evolution in the ‘New Arctic’

Recent Arctic warming outpaces global warming and is characterized by dramatic changes in sea ice (record sea ice loss, thinner and more seasonal ice cover), warming SSTs, and a lengthening melt season. These changes impact the surface energy budget and the sensitivity of sea ice to radiative forcing, namely an increased sensitivity of thinner ice to local radiative forcings and a weaker buffering of surface-atmosphere exchanges of heat and moisture. However, these processes are a large source of uncertainty in global climate models with prior studies finding that poor representations of downwelling longwave radiation and sea ice albedo lead to model spread in sea ice conditions. A limitation of prior work is examining sea ice-atmosphere interactions through an Eulerian framework. This study utilizes a sea ice parcel dataset in a LaGrangian framework, allowing for tracking of surface energy budget-sea ice interactions over the lifespan of individual sea ice parcels; this framework also allows for the quantification of the sea ice response to episodic weather events along with seasonal drivers, including the drivers of rapid growth and melt events. First, lag-lead relationships between relevant surface energy budget terms and sea ice thickness changes are explored to understand the atmospheric conditions preceding rapid growth and melt. The impact of episodic events- moisture intrusion, warm air outbreaks, cyclones- on sea ice growth are also investigated by stratifying first-year parcels by sea ice thickness at the end of the growth season and analyzing the effect of atmospheric variability (number and intensity of episodic events) on parcel thickness change. Lastly, parcel growth and melt and the associated radiative anomalies are compared to snowfall events/snow thickness to determine how snowfall modifies the interaction between the local surface energy budget and sea ice mass balance.

Patrick Taylor↗
NASA NTRS1998

Satellite Microwave Radar Observations of Antarctic Sea Ice

Historical data on Antarctic sea ice extent and concentration have traditionally been derived from visible and near-infrared images acquired by the polar-orbiting National Oceanic and Atmospheric Agency's (NOAA) meteorological satellites, using the Advanced Very High Resolution Radiometer (AVHRR), and more recently by the Defense Meteorological Satellite Program's Operational Linescan System (OLS). The limitation of these systems is that the majority of energy imparted to the Antarctic sea-ice system is transferred during b6y fast-moving low pressure systems. Since the Southern Ocean sea-ice cover is completely bounded at its lower latitude limit by open ocean, these "polar lows" transport large amounts of moisture (contained in warm air masses) over the outer ice cover. The result is that most, if not all, noteworthy periods of wind- and temperature-driven dynamic changes in the ice cover are accompanied by periods where the region is blanketed by cloud, and when the atmosphere is inherently more electromagnetically opaque. During storms, the probability with which the area is cloud covered is extremely high, thereby ruling out use of visible or near-infrared images as a practical method of monitoring the associated changes in ice conditions. Instead, Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and DMSP Special Sensor Microwave/imager (SSM/I) have been the primary workhorses to build up a microwave record of Antarctic sea-ice characteristics. Similar problems, however, occur in passive microwave retrievals of sea-ice concentration, and the algorithms are called into question during these periods of change. The influence of water vapor in the atmosphere alone can modify the ice concentration retrievals by fractions exceeding 105, and that retrievals of ice concentration must compensate for the atmospheric water vapor and liquid water contents.

Drinkwater, Mark R.↗
NASA NTRS2022

Turbulent Heat Flux, Downward Longwave Radiation and Large-Scale Atmospheric Circulation Associated with the Wintertime Barents-Kara Sea Extreme Sea Ice Loss Events

We investigate wintertime extreme sea ice loss events on synoptic to subseasonal time scales over the Barents-Kara Sea, where the largest sea ice variability is located. Consistent with previous studies, extreme sea ice loss events are associated with moisture intrusions over the Barents-Kara Sea, which are driven by the large-scale atmospheric circulation. In addition to the role of downward longwave radiation associated with moisture intrusions, which is emphasized by previous studies, our analysis shows strong turbulent heat fluxes are associated with extreme sea ice melting events, with both turbulent sensible and latent heat fluxes contributing, though turbulent sensible heat fluxes dominate. Our analysis also shows that these events are connected to tropical convective anomalies. A dipole pattern of convective anomalies with enhanced convection over the Maritime Continent and suppressed convection over the central to eastern Pacific is consistently detected about 6 to 10 days prior to extreme sea ice loss events. This pattern is associated with either the Madden-Julian Oscillation (MJO) or El Niño–Southern Oscillation (ENSO). Composites show that extreme sea ice loss events are connected to tropical convection via Rossby wave propagation in the midlatitudes. However, tropical convective anomalies alone are not sufficient to trigger extreme sea ice loss events, suggesting that extratropical variability likely modulates the connection between tropical convection and extreme sea ice loss events.

Turbulent heat flux↗
NASA NTRS2022

Turbulent Heat Flux, Downward Longwave Radiation, and Large-Scale Atmospheric Circulation Associated with Wintertime Barents–Kara Sea Extreme Sea Ice Loss Events

We investigate wintertime extreme sea ice loss events on synoptic to subseasonal time scales over the Barents–Kara Sea, where the largest sea ice variability is located. Consistent with previous studies, extreme sea ice loss events are associated with moisture intrusions over the Barents–Kara Sea, which are driven by the large-scale atmospheric circulation. In addition to the role of downward longwave radiation associated with moisture intrusions, which is emphasized by previous studies, our analysis shows that strong turbulent heat fluxes are associated with extreme sea ice melting events, with both turbulent sensible and latent heat fluxes contributing, although turbulent sensible heat fluxes dominate. Our analysis also shows that these events are connected to tropical convective anomalies. A dipole pattern of convective anomalies with enhanced convection over the Maritime Continent and suppressed convection over the central to eastern Pacific is consistently detected about 6–10 days prior to extreme sea ice loss events. This pattern is associated with either the Madden–Julian oscillation (MJO) or El Nino–Southern Oscillation (ENSO). Composites show that extreme sea ice loss events are connected to tropical convection via Rossby wave propagation in the midlatitudes. However, tropical convective anomalies alone are not sufficient to trigger extreme sea ice loss events, suggesting that extratropical variability likely modulates the connection between tropical convection and extreme sea ice loss events.

Arctic↗
NASA NTRS1981

An optical model for the microwave properties of sea ice

The complex refractive index of sea ice is modeled and used to predict the microwave signatures of various sea ice types. Results are shown to correspond well with the observed values of the complex index inferred from dielectic constant and dielectric loss measurements performed in the field, and with observed microwave signatures of sea ice. The success of this modeling procedure vis a vis modeling of the dielectric properties of sea ice constituents used earlier by several others is explained. Multiple layer radiative transfer calculations are used to predict the microwave properties of first-year sea ice with and without snow, and multiyear sea ice.

Gloersen, P.↗