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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
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 NTRS2012

Large Decadal Decline of the Arctic Multiyear Ice Cover

The perennial ice area was drastically reduced to 38% of its climatological average in 2007 but recovered slightly in 2008, 2009, and 2010 with the areas being 10%, 24%, and 11% higher than in 2007, respectively. However, trends in extent and area remained strongly negative at -12.2% and -13.5% decade (sup -1), respectively. The thick component of the perennial ice, called multiyear ice, as detected by satellite data during the winters of 1979-2011 was studied, and results reveal that the multiyear ice extent and area are declining at an even more rapid rate of -15.1% and -17.2% decade(sup -1), respectively, with a record low value in 2008 followed by higher values in 2009, 2010, and 2011. Such a high rate in the decline of the thick component of the Arctic ice cover means a reduction in the average ice thickness and an even more vulnerable perennial ice cover. The decline of the multiyear ice area from 2007 to 2008 was not as strong as that of the perennial ice area from 2006 to 2007, suggesting a strong role of second-year ice melt in the latter. The sea ice cover is shown to be strongly correlated with surface temperature, which is increasing at about 3 times the global average in the Arctic but appears weakly correlated with the Arctic Oscillation (AO), which controls the atmospheric circulation in the region. An 8-9-yr cycle is apparent in the multiyear ice record, which could explain, in part, the slight recovery in the last 3 yr.

Arctic↗
NASA NTRS2012

Mean Dynamic Topography of the Arctic Ocean

ICESat and Envisat altimetry data provide measurements of the instantaneous sea surface height (SSH) across the Arctic Ocean, using lead and open water elevation within the sea ice pack. First, these data were used to derive two independent mean sea surface (MSS) models by stacking and averaging along-track SSH profiles gathered between 2003 and 2009. The ICESat and Envisat MSS data were combined to construct the high-resolution ICEn MSS. Second, we estimate the 5.5-year mean dynamic topography (MDT) of the Arctic Ocean by differencing the ICEn MSS with the new GOCO02S geoid model, derived from GRACE and GOCE gravity. Using these satellite-only data we map the major features of Arctic Ocean dynamical height that are consistent with in situ observations, including the topographical highs and lows of the Beaufort and Greenland Gyres, respectively. Smaller-scale MDT structures remain largely unresolved due to uncertainties in the geoid at short wavelengths.

Arctic Ocean↗
NASA NTRS2014

Changes in Arctic and Antarctic Sea Ice as a Microcosm of Global Climate Change

Polar sea ice is a key element of the climate system and has now been monitored through satellite observations for over three and a half decades. The satellite observations reveal considerable information about polar ice and its changes since the late 1970s, including a prominent downward trend in Arctic sea ice coverage and a much lesser upward trend in Antarctic sea ice coverage, illustrative of the important fact that climate change entails spatial contrasts. The decreasing ice coverage in the Arctic corresponds well with contemporaneous Arctic warming and exhibits particularly large decreases in the summers of 2007 and 2012, influenced by both preconditioning and atmospheric conditions. The increasing ice coverage in the Antarctic is not as readily explained, but spatial differences in the Antarctic trends suggest a possible connection with atmospheric circulation changes that have perhaps been influenced by the Antarctic ozone hole. The changes in the polar ice covers and the issues surrounding those changes have many commonalities with broader climate changes and their surrounding issues, allowing the sea ice changes to be viewed in some important ways as a microcosm of global climate change.

Arctic↗
NASA NTRS2014

Climate Trends in the Arctic as Observed from Space

The Arctic is a region in transformation. Warming in the region has been amplified, as expected from ice-albedo feedback effects, with the rate of warming observed to be approx. 0.60+/-0.07 C/decade in the Arctic (>64degN) compared to approx. 0.17 C/decade globally during the last three decades. This increase in surface temperature is manifested in all components of the cryosphere. In particular, the sea ice extent has been declining at the rate of approx. 3.8%/decade, whereas the perennial ice (represented by summer ice minimum) is declining at a much greater rate of approx.11.5%/decade. Spring snow cover has also been observed to be declining by −2.12%/decade for the period 1967-2012. The Greenland ice sheet has been losing mass at the rate of approx. 34.0Gt/year (sea level equivalence of 0.09 mm/year) during the period from 1992 to 2011, but for the period 2002-2011, a higher rate of mass loss of approx. 215 Gt/year has been observed. Also, the mass of glaciers worldwide declined at the rate of 226 Gt/year from 1971 to 2009 and 275 Gt/year from 1993 to 2009. Increases in permafrost temperature have also been measured in many parts of the Northern Hemisphere while a thickening of the active layer that overlies permafrost and a thinning of seasonally frozen ground has also been reported. To gain insight into these changes, comparative analysis with trends in clouds, albedo, and the Arctic Oscillation is also presented.

arctic↗
NASA NTRS2016

Aircraft-Measured Indirect Cloud Effects from Biomass Burning Smoke in the Arctic and Subarctic

The incidence of wildfires in the Arctic and subarctic is increasing; in boreal North America, for example, the burned area is expected to increase by 200-300% over the next 50-100 years, which previous studies suggest could have a large effect on cloud microphysics, lifetime, albedo, and precipitation. However, the interactions between smoke particles and clouds remain poorly quantified due to confounding meteorological influences and remote sensing limitations. Here, we use data from several aircraft campaigns in the Arctic and subarctic to explore cloud microphysics in liquid-phase clouds influenced by biomass burning. Median cloud droplet radii in smoky clouds were approx. 40- 60% smaller than in background clouds. Based on the relationship between cloud droplet number (N(liq)/ and various biomass burning tracers (BBt/ across the multi-campaign data set, we calculated the magnitude of subarctic and Arctic smoke aerosol-cloud interactions (ACIs, where ACI = (1/3) x dln(N(liq))/dln(BBt)) to be approx. 0.16 out of a maximum possible value of 0.33 that would be obtained if all aerosols were to nucleate cloud droplets. Interestingly, in a separate subarctic case study with low liquid water content (0.02 gm/cu m and very high aerosol concentrations (2000- 3000/ cu cm in the most polluted clouds, the estimated ACI value was only 0.05. In this case, competition for water vapor by the high concentration of cloud condensation nuclei (CCN) strongly limited the formation of droplets and reduced the cloud albedo effect, which highlights the importance of cloud feedbacks across scales. Using our calculated ACI values, we estimate that the smoke-driven cloud albedo effect may decrease local summertime short-wave radiative flux by between 2 and 4 W/sq m or more under some low and homogeneous cloud cover conditions in the subarctic, although the changes should be smaller in high surface albedo regions of the Arctic.We lastly explore evidence suggesting that numerous northern-latitude background Aitken particles can interact with combustion particles, perhaps impacting their properties as cloud condensation and ice nuclei.

cloud microphysics↗
NASA NTRS2017

Intercomparison of Snow Depth Retrievals over Arctic Sea Ice from Radar Data Acquired by Operation IceBridge

Since 2009, the ultra-wideband snow radar on Operation IceBridge (OIB; a NASA airborne mission to survey the polar ice covers) has acquired data in annual campaigns conducted during the Arctic and Antarctic springs. Progressive improvements in radar hardware and data processing methodologies have led to improved data quality for subsequent retrieval of snow depth. Existing retrieval algorithms differ in the way the air-snow (a-s) and snow-ice (s-i) interfaces are detected and localized in the radar returns and in how the system limitations are addressed (e.g., noise, resolution). In 2014, the Snow Thickness On Sea Ice Working Group (STOSIWG) was formed and tasked with investigating how radar data quality affects snow depth retrievals and how retrievals from the various algorithms differ. The goal is to understand the limitations of the estimates and to produce a well-documented, long-term record that can be used for understanding broader changes in the Arctic climate system. Here, we assess five retrieval algorithms by comparisons with field measurements from two groundbased campaigns, including the BRomine, Ozone, and Mercury EXperiment (BROMEX) at Barrow, Alaska; a field program by Environment and Climate Change Canada at Eureka, Nunavut; and available climatology and snowfall from ERA-Interim (ECMWF (European Centre for Medium-Range Weather Forecasts) Re-Analysis) reanalysis. The aim is to examine available algorithms and to use the assessment results to inform the development of future approaches. We present results from these assessments and highlight key considerations for the production of a long-term, calibrated geophysical record of springtime snow thickness over Arctic sea ice.

Operation IceBridge↗
NASA NTRS2018

An Overview of Recent NASA Airborne Science Projects in the Arctic Using Manned and Unmanned Aircraft

As NASA prepares to launch ICESAT-II there are significant efforts underway to plan for aircraft under-flights to calibrate the onboard lasers and to validate data products. This presentation will begin with an overview of recent airborne science missions including Operation Ice Bridge that have focused observations on the arctic. This will be followed by results from recent NASA sponsored unmanned aircraft missions and a discussion how these new observing technologies can contribute to future research in the Arctic. Information on recent icing wind tunnel testing and comparisons with icing prediction models will also be shared leading to discussions on specific challenges in adapting systems to harsh arctic conditions.

Aircraft↗
NASA NTRS2020

Dependence of Atmospheric Transport into the Arctic on the Extent of the Hadley Cell

Recent studies have shown a large spread in the transport of atmospheric tracers into the Arctic among a suite of chemistry climate models, and have suggested that this is related to the multi–model spread in the meridional extent of the Hadley Cell (HC). Here we examine the HC–transport relationship using an idealized model, where we can vary the mean circulation and isolate its impact on transport to the Arctic. It is shown that the poleward transport depends on the relative position between the northern edge of the HC and the tracer source, with maximum poleward transport occurring when the HC edge lies near the middle of the source region. Such dependence highlights the critical role of near–surface transport by Eulerian mean circulation rather than eddy mixing in the free troposphere. These results suggest that variations in the HC extent and the tracer source region are both important for modeling Arctic composition.

Atmospheric transport↗
NASA NTRS2021

Elevation Dependent Warming in the Eastern Siberian Arctic

There is evidence for elevation-dependent warming (EDW) in many mountainous regions, including the Alps, Rockies, and Tibetan Plateau, all of which are in mid-latitudes. Most studies finding evidence of EDW indicate that both recent decadal and future projected warming rates are greater at higher elevations. In this study, we examine the roles of Arctic amplification and elevation on future warming rates in winter and summer in eastern Siberia (50-70°N; 80-180°E). This region includes four major river basins that flow into the Arctic Ocean (the Yenisei, Lena, Indigirka, and Kolyma) and intersects with mountain ranges in northern Mongolia and eastern Siberia. We analyse projected 21st century temperature projections using a six-member ensemble of the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM4) with a radiative forcing of 8.5 W m-2. Projected warming rates in winter for the 21st century are dominated by Arctic amplification, which leads to significantly larger warming rates at higher latitudes, with latitudinal gradients of about 0.16°C per degree latitude. In summer, the latitudinal gradient is near zero (0.02°C per degree of latitude). Within specific latitude bands, we also find EDW. However, unlike most mid-latitude locations where warming rates are greater at higher elevations, we find that future warming rates are smaller at higher elevations for this high-latitude region, particularly during winter, with statistically significant rates varying between -0.70 and -2.46 °C/km for different 5° latitude bands. The decrease in warming rates with elevation in winter at the highest latitudes is primarily attributed to strong inversions and changes in the lapse rate as free-air temperatures warm at slower rates than surface temperatures. In summer, the elevation dependence is much weaker than in winter but still statistically significant and negative in all but the most northern latitude band with values ranging between -0.10 and -0.56 °C/km.

elevation-dependent warming (EDW)↗
NASA NTRS2022

Potential Link Between Ice Nucleation and Climate Model Spread in Arctic Amplification

Arctic amplification (AA) is simulated by all global climate models, however the spread in the degree of projected warming is large and the underlying mechanisms driving it are poorly understood. The impact of the temperature dependence of immersion freezing on cloud feedbacks and AA is studied using NASA's GEOS-5 model. Parameterizations that exhibit low ice-nucleating particle (INP) concentrations in the high Arctic during summer are found to weaken the cloud-phase feedback. This allows sunlight to readily melt sea-ice in the summer, which decreases the stability of the lower troposphere, causing a decrease in wintertime cloud fraction over open ocean. Arctic amplification was found to span from ∼1.4 to >2.6, which spans 30% of the spread in AA in the coupled model intercomparison project models, depending on the temperature dependence of immersion freezing. These results suggest that summertime INP concentrations may provide an observational constraint on AA.

Ice Nucleation↗
NASA NTRSDate not supplied

Isolating the Surface Type Influence on Arctic Cloud Properties

In response to anthropogenic climate change, substantial declines in sea ice have been observed. An urgent question is whether and how clouds respond to the changing Arctic surface. Due to the important radiative influence of clouds, the response of clouds to sea ice cover change constitutes a potentially important climate feedback within the Arctic. The sign of this feedback is strongly influenced by the seasonality of the cloud response to sea ice loss. Given the importance of this phenomenon, previous research focused on using observations of inter-annual variability to quantify the cloud-sea ice relationship. However, the reliance on inter-annual variability to assess the covariance between clouds and sea ice make it challenging to control for the influence of large-scale meteorology on the clouds. We have devised an approach that applies an in situ, airborne observational strategy to quantify the influence of surface type on Arctic clouds to satellite data. Our event-based method composites cloud property differences for ocean, marginal ice zone, and sea ice surface types for >5000 MIZ crossing events. We find that cloud properties in non-summer months below ~1.5 km are influenced by surface type such that greater cloud fraction and water content are found over ocean relative to sea ice regions. Results are statistically significantly at the 95% confidence level. During summer, the surface type does not influence the cloud properties. The primary cause of the surface type dependent cloud property differences is the thermodynamic profiles differences that occur between the two surface types: namely, ocean footprints are warmer, moister, have more positive surface turbulent fluxes and are less stable than their sea ice counterparts. We find that the differences in thermodynamic profiles by surface type that correspond to the cloud property differences also explains a significant portion of the variability across events. Our analysis provides evidence that the influence of surface type on cloud properties fundamentally occurs due to the inherent surface temperature differences between the surface types. Significant surface type influences on cloud properties are only found in the presence of surface temperature differences between the surface types and only non-summer months meet this criterion. A conceptual model of this process is as follows, fundamental properties of the ocean and sea ice surface types (e.g., surface albedo, heat capacity/thermal inertia, surface roughness, and thermal conductance) lead to systematic differences in the surface temperature by surface type. In response to this surface temperature difference, atmosphere boundary layer processes (including turbulent mixing and radiation) communicate the surface temperature differences to the lower atmosphere driving the greater stability over sea ice than ocean. These differences in the background thermodynamic state profiles between the surface types yield atmospheric conditions that are more conducive to cloud development over ocean than sea ice. The details of these boundary layer processes are sensitive to the surface type but may not be fundamental to the resulting thermodynamic structure and cloud differences. Thus, our results indicate that to accurately model that cloud response to sea ice loss in climate models the surface type properties that yield the systematic differences in ocean and sea ice temperature (e.g., surface albedo, surface turbulent fluxes parameters, and thermal conductance) must be accurately represented.

Arctic radiation budget↗
NASA NTRS2022

Clean Air Policies Are Key for Successfully Mitigating Arctic Warming

A tighter integration of modeling frameworks for climate and air quality is urgently needed to assess the impacts of clean air policies on future Arctic and global climate. We combined a new model emulator and comprehensive emissions scenarios for air pollutants and greenhouse gases to assess climate and human health co-benefits of emissions reductions. Fossil fuel use is projected to rapidly decline in an increasingly sustainable world, resulting in far-reaching air quality benefits. Despite human health benefits, reductions in sulfur emissions in a more sustainable world could enhance Arctic warming by 0.8 °C in 2050 relative to the 1995–2014, thereby offsetting climate benefits of greenhouse gas reductions. Targeted and technically feasible emissions reduction opportunities exist for achieving simultaneous climate and human health co-benefits. It would be particularly beneficial to unlock a newly identified mitigation potential for carbon particulate matter, yielding Arctic climate benefits equivalent to those from carbon dioxide reductions by 2050.

Atmospheric chemistry↗
NASA NTRS2022

Arctic Biogeochemical and Optical Properties of Dissolved Organic Matter Across River to Sea Gradients

Arctic landscapes are warming and becoming wetter due to changes in precipitation and the timing of snowmelt which consequently alters seasonal runoff and river discharge patterns. These changes in hydrology lead to increased mobilization and transport of terrestrial dissolved organic matter (DOM) to Arctic coastal seas where significant impacts on biogeochemical cycling can occur. Here, we present measurements of dissolved organic carbon (DOC) and chromophoric DOM (CDOM) in the Yukon River-to-Bering Sea system and two river plumes on the Alaska North Slope which flow into the Beaufort Sea. Our sampling characterized optical and biogeochemical properties of DOM during high and low river discharge periods for the Yukon River-Bering Sea system. The average DOC concentration at the multiple Yukon River mouths ranged from a high of 10.36 mg C L-1 during the ascending limb of the 2019 freshet (late May), 6.4 mg C L-1 during the descending limb of the 2019 freshet (late June), and a low of 3.86 mg C L-1 during low river discharge in August 2018. CDOM absorption coefficient at 412 nm (aCDOM(412)) averaged 8.23 m-1, 5.07 m-1, and 1.9 m-1, respectively. Several approaches to model DOC concentration based on its relationship with CDOM properties demonstrated cross-system seasonal and spatial robustness for these Arctic coastal systems despite spanning an order of magnitude decrease in DOC concentration from the lower Yukon River to the Northern Bering Sea as well as the North Slope systems. “Snapshot” fluxes of DOC and CDOM across the Yukon River Delta to Norton Sound were calculated from our measurements and modeled water fluxes forced with upstream USGS river gauge data. Our findings suggest that during high river flow, DOM reaches the delta largely unaltered by inputs or physical and biogeochemical processing and that the transformations of Yukon River DOM largely occur in the plume. However, during low summer discharge, multiple processes including local precipitation events, microbial decomposition, photochemistry, and likely others can alter the DOM properties within the lower Yukon River and Delta prior to flowing into Norton Sound.

Arctic↗
NASA NTRS2023

Fire in the Arctic: Current Trends and Future Pathways

Wildland fires in the Arctic are expected to become more frequent and more severe. In recent years, extreme fire seasons have been documented across the Pan-Arctic and boreal in five of the last seven years – including large wildfires in Greenland in 2017 and 2019 over tundra and high carbon soil landscapes and an earlier start of extreme fire seasons in 2023. Future Arctic and boreal fire regimes will experience increased fire risk though the end of this century (McCarty et al., 2021, Senande-Rivera et al., 2022). The main factors affecting the severity and frequency of wildland fires are fuels (vegetated biomass and type of biomass) and fuel condition (dryness), fire weather conditions (relative humidity, drought, precipitation), and ignition (human-caused, lightning). Climate change directly influences all of these drivers, and indirectly also some human-caused ignitions.

Fire↗
NASA NTRS1964

Radio Noise Problems in Arctic Regions

Three main types of radio noise should be considered when establishing noise levels for communication purposes or in experiments utilizing radio techniques in Arctic regions. These are atmospheric and man-made noise, and precipitation static. National Bureau of Standards radio noise data obtained hourly at Arctic and Antarctic stations on eight .fixed frequencies between 51 kc and 20 Mc/s are analyzed to show the characteristics of the three types. The diurnal and seasonal variations of atmospheric radio noise at high latitudes are explainable in terms of changes in propagation factors and in the distribution of world thunderstorm activity. In both northern and southern Arctic regions atmospheric noise decreases during polar cap absorption (PCA), most markedly in the h.f. band. The probable magnitude of man-made noise in the h.f. band is estimated from data taken during PCA, when atmospheric noise is absent. At Thule man-made noise on 2.5 and 5 Mc/s appears to be 57 and 49 dB above kTB (where kTB is antenna thermal noise power), respectively, while at Byrd Station the values are about 20 and 12 dB respectively. Precipitation static is generated on exposed antennas during periods of blowing snow (blizzards). The noise power magnitude can be at least 50 dB above man-made and atmospheric levels, but the maximum enhancement cannot be ascertained because of missing data. In winter and spring months at Byrd Station radio data dependent upon exposed antennas may be lost 10-30 per cent of the time due to precipitation static alone.

Radio Noise↗
NASA NTRS1974

Monitoring Arctic Sea ice using ERTS imagery

Because of the effect of sea ice on the heat balance of the Arctic and because of the expanding economic interest in arctic oil and other minerals, extensive monitoring and further study of sea ice is required. The application of ERTS data for mapping ice is evaluated for several arctic areas, including the Bering Sea, the eastern Beaufort Sea, parts of the Canadian Archipelago, and the Greenland Sea. Interpretive techniques are discussed, and the scales and types of ice features that can be detected are described. For the Bering Sea, a sample of ERTS imagery is compared with visual ice reports and aerial photography from the NASA CV-990 aircraft.

Barnes, J. C.↗
NASA NTRS1978

Effect of solar activity on the frequency of occurrence of major anomalies in the Arctic

Major air pressure and temperature anomalies in certain arctic regions were studied with a view toward predicting their occurrence. Correlations are sought between the frequency of arctic anomalies and solar activity, or specifically the Wolf number and the index of geomagnetic disturbance. Graphic techniques are used to show that solar activity has a definite influence on the frequency of occurrence of major anomalies of pressure and temperature in the Arctic.

Bolotinskaya, M. S.↗