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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Recent Changes in Arctic Sea Ice Melt Onset, Freeze-Up, and Melt Season Length

In order to explore changes and trends in the timing of Arctic sea ice melt onset and freeze-up and therefore melt season length, we developed a method that obtains this information directly from satellite passive microwave data, creating a consistent data set from 1979 through present. We furthermore distinguish between early melt (the first day of the year when melt is detected) and the first day of continuous melt. A similar distinction is made for the freeze-up. Using this method we analyze trends in melt onset and freeze-up for 10 different Arctic regions. In all regions except for the Sea of Okhotsk, which shows a very slight and statistically insignificant positive trend (O.4 days/decade), trends in melt onset are negative, i.e. towards earlier melt. The trends range from -1.0day/decade for the Bering Sea to -7.3 days/decade for the East Greenland Sea. Except for the Sea of Okhotsk all areas also show a trend towards later autumn freeze onset. The Chukchi/Beaufort Seas and Laptev/East Siberian Seas observe the strongest trends with 7 days/decade. For the entire Arctic, the melt season length has increased by about 20 days over the last 30 years. Largest trends of over 1O days/decade are seen for Hudson Bay, the East Greenland Sea the Laptev/East Siberian Seas, and the Chukchi/Beaufort Seas. Those trends are statistically significant a1 the 99% level.

Markus, Thorsten↗
DOE OSTI2013

The social values at risk from sea-level rise

Analysis of the risks of sea-level rise favours conventionally measured metrics such as the area of land that may be subsumed, the numbers of properties at risk, and the capital values of assets at risk. Despite this, it is clear that there exist many less material but no less important values at risk from sea-level rise. This paper re-theorises these multifarious social values at risk from sea-level rise, by explaining their diverse nature, and grounding them in the everyday practices of people living in coastal places. It is informed by a review and analysis of research on social values from within the fields of social impact assessment, human geography, psychology, decision analysis, and climate change adaptation. From this we propose that it is the ‘lived values’ of coastal places that are most at risk from sea-level rise. We then offer a framework that groups these lived values into five types: those that are physiological in nature, and those that relate to issues of security, belonging, esteem, and self-actualisation. This framework of lived values at risk from sea-level rise can guide empirical research investigating the social impacts of sea-level rise, as well as the impacts of actions to adapt to sea-level rise. It also offers a basis for identifying the distribution of related social outcomes across populations exposed to sea-level rise or sea-level rise policies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Mapping the Spatial Footprint of Sea Breeze Winds in the Southeastern United States

Abstract Sea breeze winds are observed at various locations worldwide, but the spatially continuous mapping of sea breeze winds is rare. We have developed a scheme to map the areas of the southeastern United States (SEUS) coast influenced by sea breeze winds using a range of surface re‐analysis data to identify their occurrence. Changes in wind direction and dew point temperature are both used to detect a potential sea breeze signature, which is then confirmed by cumuliform clouds seen in satellite images or coastal fronts shown as cohesive lines in radar reflectivity images. Filters are employed to remove onshore winds not induced by the temperature difference between land and sea. From March to September 2019, this scheme identified 134 days with sea breeze occurrence somewhere in the SEUS, a frequency of 63 percent. The number of sea breezes increased from March to July and then decreased to September. Deep inland propagation of sea breezes during this period left footprints in a band parallel to the coastline up to about 220 km inland, after which the sea breeze winds quickly diminished. Comparisons show that the findings using the scheme are consistent with site observations, theoretical estimates, and idealized and semi‐idealized numerical model simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Decadal Shift of NAO-Linked Interannual Sea Level Variability along the U.S. Northeast Coast

Recent studies have linked interannual sea level variability and extreme events along the U.S. northeast coast (NEC) to the North Atlantic Oscillation (NAO), a natural internal climate mode that prevails in the North Atlantic Ocean. The correlation between the NAO index and coastal sea level north of Cape Hatteras was weak from the 1960s to the mid-1980s, but it has markedly increased since around 1987. The causes for the decadal shift remain unknown. Yet understanding the abrupt change is vital for decadal sea level prediction and is essential for risk management. Here we use a robust method, the Bayesian dynamic linear model (DLM), to explore the nonstationary NAO impact on NEC sea level. The results show that a spatial pattern change of NAO-related winds near the NEC is a major cause of the NAO–sea level relationship shift. A new index using regional sea level pressure is developed that is a significantly better predictor of NEC sea level than is the NAO and is strongly linked to the intensity of westerly winds near the NEC. Finally, these results point to the vital importance of monitoring regional changes of wind and sea level pressure patterns, rather than the NAO index alone, to achieve more accurate predictions of sea level change along the NEC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Arctic Sea Ice Volume Variability over 1901–2010: A Model-Based Reconstruction

PIOMAS-20C, an Arctic sea ice reconstruction for 1901–2010, is produced by forcing the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) with ERA-20C atmospheric data. ERA-20C performance over Arctic sea ice is assessed by comparisons with measurements and data from other reanalyses. ERA-20C performs similarly with respect to the annual cycle of downwelling radiation, air temperature, and wind speed compared to reanalyses with more extensive data assimilation such as ERA-Interim and MERRA. PIOMAS-20C sea ice thickness and volume are then compared with in situ and aircraft remote sensing observations for the period of ~1950–2010. Error statistics are similar to those for PIOMAS. We compare the magnitude and patterns of sea ice variability between the first half of the twentieth century (1901–40) and the more recent period (1980–2010), both marked by sea ice decline in the Arctic. The first period contains the so-called early-twentieth-century warming (ETCW; ~1920–40) during which the Atlantic sector saw a significant decline in sea ice volume, but the Pacific sector did not. The sea ice decline over the 1979–2010 period is pan-Arctic and 6 times larger than the net decline during the 1901–40 period. Sea ice volume trends reconstructed solely from surface temperature anomalies are smaller than PIOMAS-20C, suggesting that mechanisms other than warming, such as changes in ice motion and deformation, played a significant role in determining sea ice volume trends during both periods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Sea-Ice Effects on the Alaskan Wave Climate

This study investigates the uncertainty of wave resource assessments due to sea ice in the nearshore region of Alaska using an innovative approach of combining remotely sensed data and a third-generation phase-averaged wave model. Modeling analysis focused on winter months, when high wave energy is present along with sea ice. This study includes recommendations to improve the accuracy of wave resource assessments and optimize marine and hydrokinetic device siting with consideration of sea-ice effects. Additional recommendations, based on preliminary sea-ice information in Cook Inlet, Alaska, are provided for a trajectory analysis of drifting sea ice and a collision risk assessment of sea ice and tidal turbines. The outcome of this project will provide valuable information about the level of sea-ice impact on the accuracy of wave resource assessments in the Alaska nearshore region, and of sea-ice collision risk with MHK devices and ocean observation systems during winter months when sea ice is present.

16 TIDAL AND WAVE POWER↗
NASA NTRS2012

Improvement in Simulation of Eurasian Winter Climate Variability with a Realistic Arctic Sea Ice Condition in an Atmospheric GCM

The present study investigates how much a realistic Arctic sea ice condition can contribute to improve simulation of the winter climate variation over the Eurasia region. Model experiments are set up using different sea ice boundary conditions over the past 24 years (i.e., 1988-2011). One is an atmospheric model inter-comparison (AMIP) type of run forced with observed sea-surface temperature (SST), sea ice, and greenhouse gases (referred to as Exp RSI), and the other is the same as Exp RSI except for the sea ice forcing, which is a repeating climatological annual cycle (referred to as Exp CSI). Results show that Exp RSI produces the observed dominant pattern of Eurasian winter temperatures and their interannual variation better than Exp CSI (correlation difference up to approx. 0.3). Exp RSI captures the observed strong relationship between the sea ice concentration near the Barents and Kara seas and the temperature anomaly across Eurasia, including northeastern Asia, which is not well captured in Exp CSI. Lagged atmospheric responses to sea ice retreat are examined using observations to understand atmospheric processes for the Eurasian cooling response including the Arctic temperature increase, sea-level pressure increase, upper-level jet weakening and cold air outbreak toward the mid-latitude. The reproducibility of these lagged responses by Exp RSI is also evaluated.

sea-ice↗
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 NTRS2016

Bellingshausen Sea Ice Extent Recorded in an Antarctic Peninsula Ice Core

Annual net accumulation (A(sub n)) from the Bruce Plateau (BP) ice core retrieved from the Antarctic Peninsula exhibits a notable relationship with sea ice extent (SIE) in the Bellingshausen Sea. Over the satellite era, both BP A(sub n) and Bellingshausen SIE are influenced by large-scale climatic factors such as the Amundsen Sea Low, Southern Annular Mode, and Southern Oscillation. In addition to the direct response of BP A(sub n) to Bellingshausen SIE (e.g., more open water as a moisture source), these large-scale climate phenomena also link the BP and the Bellingshausen Sea indirectly such that they exhibit similar responses (e.g., northerly wind anomalies advect warm, moist air to the Antarctic Peninsula and neighboring Bellingshausen Sea, which reduces SIE and increases A(sub n)). Comparison with a time series of fast ice at South Orkney Islands reveals a relationship between BP A(sub n) and sea ice in the northern Weddell Sea that is relatively consistent over the twentieth century, except when it is modulated by atmospheric wave patterns described by the Trans-Polar Index. The trend of increasing accumulation on the Bruce Plateau since approximately 1970 agrees with other climate records and reconstructions in the region and suggests that the current rate of sea ice loss in the Bellingshausen Sea is unrivaled in the twentieth century.

sea ice↗
NASA NTRS2017

Improving Our Understanding of Antarctic Sea Ice with NASA's Operation IceBridge and the Upcoming ICESat-2 Mission

Antarctic sea ice is a crucial component of the global climate system. Rapid sea ice production regimes around Antarctica feed the lower branch of the Southern Ocean overturning circulation through intense brine rejection and the formation of Antarctic Bottom Water (e.g., Orsi et al. 1999; Jacobs 2004), while the northward transport and subsequent melt of Antarctic sea ice drives the upper branch of the overturning circulation through freshwater input (Abernathy et al. 2016). Wind-driven trends in Antarctic sea ice (Holland Kwok 2012) have likely increased the transport of freshwater away from the Antarctic coastline, significantly altering the salinity distribution of the Southern Ocean (Haumann et al. 2016). Conversely, weaker sea ice production and the lack of shelf water formation over the Amundsen and Bellingshausen shelf seas promote intrusion of warm Circumpolar Deep Water onto the continental shelf and the ocean-driven melting of several ice shelves fringing the West Antarctic Ice Sheet (e.g., Jacobs et al. 2011; Pritchard et al. 2012; Dutrieux et al. 2014). Sea ice conditions around Antarctica are also increasingly considered an important factor impacting local atmospheric conditions and the surface melting of Antarctic ice shelves (e.g., Scambos et al. 2017). Sea ice formation around Antarctica is responsive to the strong regional variability in atmospheric forcing present around Antarctica, driving this bimodal variability in the behavior and properties of the underlying shelf seas (e.g., Petty et al. 2012; Petty et al. 2014).

Arctic↗
NASA NTRS2018

Remote Sensing of Antarctic Sea Ice with Coordinated Aircraft and Satellite Data Acquisitions

Remote sensing of Antarctic sea ice is required to characterize properties of the vast sea ice cover to understand its long-term increase in contrast to the decrease of Arctic sea ice. For this objective, the OIB/TanDEM-X Coordinated Science Campaign (OTASC) was successfully conducted in 2017 to obtain contemporaneous and collocated remote sensing data from NASA's Operation IceBridge (OIB) and the German Aerospace Center (DLR) TanDEM-X Synthetic Aperture Radar (SAR) system at X-band together with Sentinel-1 and RADARSAT-2 SARs at C-band in conjunction with WorldView satellite spectral sensors, surface measurements, and field observations. The Weddell Sea and the Ross Sea were two primary regions while SAR data were also collected over six other regions in the Southern Ocean. Satellite SAR data included both polarimetric and interferometric capabilities to infer snow and sea ice information in three dimensions (3D), while OIB/P-3 aircraft data include snow radar together with altimeter data for snow and sea ice observations in 3D over the Weddell Sea. Across the Ross Sea, IcePOD and AntNZ/York-University flights were carried out together with satellite SAR data acquisitions.

OIB↗
NASA NTRS2024

Physics of the Seasonal Sea Ice Zone

The seasonal sea ice zone encompasses the region between the winter maximum and summer minimum sea ice extent. In both the Arctic and Antarctic, the majority of the ice cover can now be classified as seasonal. Here, we review the sea ice physics that governs the evolution of seasonal sea ice in the Arctic and Antarctic, spanning sea ice growth, melt, and dynamics and including interactions with ocean surface waves as well as other coupled processes. The advent of coupled wave–ice modeling and discrete-element modeling, together with improved and expanded satellite observations and field campaigns, has yielded advances in process understanding. Many topics remain in need of further investigation, including rheologies appropriate for seasonal sea ice, wave-induced sea ice fracture, welding for sea ice freeze-up, and the distribution of snow on seasonal sea ice. Future research should aim to redress biases (such as disparities in focus between the Arctic and Antarctic and between summer and winter processes) and connect observations to modeling across spatial scales.

sea ice↗
DOE OSTI2012

Decadal and long-term sea level variability in the tropical Indo-Pacific Ocean

In this study, we analysed decadal and long-term steric sea level variations over 1966–2007 period in the Indo-Pacific sector, using an ocean general circulation model forced by reanalysis winds. The simulated steric sea level compares favourably with sea level from satellite altimetry and tide gauges at interannual and decadal timescales. The amplitude of decadal sea level variability (up to ~5 cm standard deviation) is typically nearly half of the interannual variations (up to ~10 cm) and two to three times larger than long-term sea level variations (up to 2 cm). Zonal wind stress varies at decadal timescales in the western Pacific and in the southern Indian Ocean, with coherent signals in ERA-40 (from which the model forcing is derived), NCEP, twentieth century and WASWind products. Contrary to the variability at interannual timescale, for which there is a tendency of El Niño and Indian Ocean Dipole events to co-occur, decadal wind stress variations are relatively independent in the two basins. In the Pacific, those wind stress variations drive Ekman pumping on either side of the equator, and induce low frequency sea level variations in the western Pacific through planetary wave propagation. The equatorial signal from the western Pacific travels southward to the west Australian coast through equatorial and coastal wave guides. In the Indian Ocean, decadal zonal wind stress variations induce sea level fluctuations in the eastern equatorial Indian Ocean and the Bay of Bengal, through equatorial and coastal wave-guides. Wind stress curl in the southern Indian Ocean drives decadal variability in the south-western Indian Ocean through planetary waves. Decadal sea level variations in the south–western Indian Ocean, in the eastern equatorial Indian Ocean and in the Bay of Bengal are weakly correlated to variability in the Pacific Ocean. Even though the wind variability is coherent among various wind products at decadal timescales, they show a large contrast in long-term wind stress changes, suggesting that long-term sea level changes from forced ocean models need to be interpreted with caution.

Meteorology & Atmospheric Sciences↗
DOE OSTI2013

Do indicators influence communication in SEA? — Experience from the Chinese practice

Indicators have become one of the primary tools for Strategic Environmental Assessment (SEA) in the Chinese context, but what does this use of indicators mean for communication within the SEA processes? This article explores how the selection and use of indicators influence the communication between different stakeholders involved in SEA. The article provides a conceptual communication model covering directions and level of communication. Using this model on empirical findings from interviews with two specific SEA cases and from general experience collected through an online survey, the results suggest that indicators are used mainly in internal communication although a change of approach, with more external communication and stakeholder engagement, is taking place as a consequence of working with indicators in the SEA. However, the external communication mainly involves the experts and other relevant sectors (planning, energy, land use, forestry, etc.), the involvement of the public and NGOs is still not well implemented in Chinese SEA practice, and the direction of communication is mainly one-way channel of providing information rather than a two-way channel of dialogue and participation. Highlights: • Exploring indicators' influence on the communication in SEA with Chinese experience. • Providing a conceptual model covering directions and level of communication in SEA. • Empirical findings from two specific SEA cases and collected general experience. • The external communication mainly involves the experts and other sectors. • More one-way information provision than two-way dialogue and participation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Moving beyond the total sea ice extent in gauging model biases

Here, reproducing characteristics of observed sea ice extent remains an important climate modeling challenge. This study describes several approaches to improve how model biases in total sea ice distribution are quantified, and applies them to historically forced simulations contributed to phase 5 of the Coupled Model Intercomparison Project (CMIP5). The quantity of hemispheric total sea ice area, or some measure of its equatorward extent, is often used to evaluate model performance. A new approach is introduced that investigates additional details about the structure of model errors, with an aim to reduce the potential impact of compensating errors when gauging differences between simulated and observed sea ice. Using multiple observational datasets, several new methods are applied to evaluate the climatological spatial distribution and the annual cycle of sea ice cover in 41 CMIP5 models. It is shown that in some models, error compensation can be substantial, for example resulting from too much sea ice in one region and too little in another. Error compensation tends to be larger in models that agree more closely with the observed total sea ice area, which may result from model tuning. The results herein suggest that consideration of only the total hemispheric sea ice area or extent can be misleading when quantitatively comparing how well models agree with observations. Further work is needed to fully develop robust methods to holistically evaluate the ability of models to capture the finescale structure of sea ice characteristics; however, the “sector scale” metric used here aids in reducing the impact of compensating errors in hemispheric integrals.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Tropical Pacific SST Drivers of Recent Antarctic Sea Ice Trends

A strengthening of the Amundsen Sea low from 1979 to 2013 has been shown to largely explain the observed increase in Antarctic sea ice concentration in the eastern Ross Sea and decrease in the Bellingshausen Sea. Here it is shown that while these changes are not generally seen in freely running coupled climate model simulations, they are reproduced in simulations of two independent coupled climate models: one constrained by observed sea surface temperature anomalies in the tropical Pacific and the other by observed surface wind stress in the tropics. This analysis confirms previous results and strengthens the conclusion that the phase change in the interdecadal Pacific oscillation from positive to negative over 1979–2013 contributed to the observed strengthening of the Amundsen Sea low and the associated pattern of Antarctic sea ice change during this period. New support for this conclusion is provided by simulated trends in spatial patterns of sea ice concentrations that are similar to those observed. These results highlight the importance of accounting for teleconnections from low to high latitudes in both model simulations and observations of Antarctic sea ice variability and change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Relative Importance of Antarctic Sea Ice Loss within the Response to Greenhouse Warming

Abstract The response to Antarctic sea ice loss within a coupled modeling framework is examined in comparison to the response to Arctic sea ice loss and within the context of general greenhouse warming. Sea ice loss responses are found to be linear (particularly in response to Antarctic or global sea ice loss) with respect to the degree of imposed perturbation and additive when perturbations are applied in hemispheres separately and concurrently. Globally, and in the tropical Pacific in particular, Antarctic sea ice loss plays a relatively larger role than Arctic sea ice loss in both the atmosphere and the ocean, within the parameters of our experiments. The pattern of response to Antarctic sea ice loss is also found to more closely resemble that of greenhouse warming, again particularly in the tropics. An extension to multiparameter pattern scaling is developed to include a scaling factor for Antarctic change in addition to those for tropical warming and Arctic sea ice loss. The decomposition is applied to the modeled response to Antarctic sea ice loss to break it down into component partial responses that scale with Antarctic, tropical, and Arctic changes. This reveals the aspects of the response that are directly related to Antarctic change, such as an equatorward intensification of tropical precipitation in the Northern Hemisphere, and those that are modified via the induced changes in the tropics and Arctic, such as Northern Hemisphere temperature change. With this, we hope to gain a deeper understanding of the role of each of these changes for the development of physical mechanisms of the response.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Capturing the interactions between ice sheets, sea level and the solid Earth on a range of timescales: a new “time window” algorithm

Retreat and advance of ice sheets perturb the gravitational field, solid surface and rotation of the Earth, leading to spatially variable sea-level changes over a range of timescales $\textit{O}$ (10 0–6 years), which in turn feed back onto ice-sheet dynamics. Coupled ice-sheet–sea-level models have been developed to capture the interactive processes between ice sheets, sea level and the solid Earth, but it is computationally challenging to capture short-term interactions $\textit{O}$ (10 0–2 years) precisely within longer $\textit{O}$ (10 3–6 years) simulations. The standard forward sea-level modelling algorithm assigns a uniform temporal resolution in the sea-level model, causing a quadratic increase in total CPU time with the total number of input ice history steps, which increases with either the length or temporal resolution of the simulation. In this study, we introduce a new “time window” algorithm for 1D pseudo-spectral sea-level models based on the normal mode method that enables users to define the temporal resolution at which the ice loading history is captured during different time intervals before the current simulation time. Utilizing the time window, we assign a fine temporal resolution $\textit{O}$ (10 0–2 years) for the period of ongoing and recent history of surface ice and ocean loading changes and a coarser temporal resolution $\textit{O}$ (10 3–6 years) for earlier periods in the simulation. This reduces the total CPU time and memory required per model time step while maintaining the precision of the model results. We explore the sensitivity of sea-level model results to the model temporal resolution and show how this sensitivity feeds back onto ice-sheet dynamics in coupled modelling. We apply the new algorithm to simulate sea-level changes in response to global ice-sheet evolution over two glacial cycles and the rapid collapse of marine sectors of the West Antarctic Ice Sheet in the coming centuries and provide appropriate time window profiles for each application. The time window algorithm reduces the total CPU time by ~ 50 % in each of these examples and changes the trend of the total CPU time increase from quadratic to linear. This improvement would increase with longer simulations than those considered here. Our algorithm also allows for coupling time intervals of annual temporal scale for coupled ice-sheet–sea-level modelling of regions such as West Antarctica that are characterized by rapid solid Earth response to ice changes due to the thin lithosphere and low mantle viscosities.

59 BASIC BIOLOGICAL SCIENCES↗