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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Arctic Mixed-phase Clouds Simulated by a Cloud-Resolving Model: Comparison with ARM Observations and Sensitivity to Microphysics Parameterizations

Single-layer mixed-phase stratiform (MPS) Arctic clouds, which formed under conditions of large surface heat flux combined with general subsidence during a subperiod of the Atmospheric Radiation Measurement (ARM) Program Mixed-Phase Arctic Cloud Experiment (M-PACE), are simulated with a cloud resolving model (CRM). The CRM is implemented with either an advanced two-moment (M05) or a commonly used one-moment (L83) bulk microphysics scheme and a state-of-the-art radiative transfer scheme. The CONTROL simulation, that uses the M05 scheme and observed aerosol size distribution and ice nulei (IN) number concentration, reproduces the magnitudes and vertical structures of cloud liquid water content (LWC), total ice water content (IWC), number concentration and effective radius of cloud droplets as suggested by the M-PACE observations. It underestimates ice crystal number concentrations by an order of magnitude and overestimates effective radius of ice crystals by a factor of 2-3. The OneM experiment, that uses the L83 scheme, produces values of liquid water path (LWP) and ice plus snow water path (ISWP) that were about 30% and 4 times, respectively, of those produced by the CONTROL. Its vertical profile of IWC exhibits a bimodal distribution in contrast to the constant distribution of IWC produced in the CONTROL and observations.

Xu, Kuan-Man↗
NASA NTRS2009

Flashline Mars Arctic Research Station (FMARS) 2009 Expedition Crew Perspectives

The Flashline Mars Arctic Research Station (FMARS), located on the rim of the Haughton Crater on Devon Island in the Canadian Arctic, is a simulated Mars habitat that provides operational constraints similar to those which will be faced by future human explorers on Mars. In July 2009, a six-member crew inhabited the isolated habitation module and conducted the twelfth FMARS mission. The crew members conducted frequent EVA operations wearing mock space suits to conduct field experiments under realistic Mars-like conditions. Their scientific campaign spanned a wide range of disciplines and included many firsts for Mars analog research. Among these are the first use of a Class IV medical laser during a Mars simulation, helping to relieve crew stress injuries during the mission. Also employed for the first time in a Mars simulation at FMARS, a UAV (Unmanned Aerial Vehicle) was used by the space-suited explorers, aiding them in their search for mineral resources. Sites identified by the UAV were then visited by geologists who conducted physical geologic sampling. For the first time, explorers in spacesuits deployed passive seismic equipment to monitor earthquake activity and characterize the planet's interior. They also conducted the first geophysical electromagnetic survey as analog Mars pioneers to search for water and characterize geological features under the surface. The crew collected hydrated minerals and attempted to produce drinkable water from the rocks. A variety of equipment was field tested as well, including new cameras that automatically geotag photos, data-recording GPS units, a tele-presence rover (operated from Florida), as well as MIT-developed mission planning software. As plans develop to return to the Moon and go on to Mars, analog facilities like FMARS can provide significant benefit to NASA and other organizations as they prepare for robust human space exploration. The authors will present preliminary results from these studies as well as their perspectives on topics including human factors, logistics, EVA operations, and the use of social media throughout the mission.

Cusack, Stacy↗
NASA NTRS2010

The Vertical Distribution of Thin Features Over the Arctic Analysed from CALIPSO Observations: Aerosols - Part 2

Influx of aerosols from the mid-latitudes has a wide range of impacts on the Arctic atmosphere. In this study, the capability of the CALIPSO-CALIOP instrument to provide accurate observations of aerosol layers is exploited to characterize their vertical distribution, probability density functions (PDFs) of aerosol layer thickness, base and top heights, and optical depths over the Arctic for the 4-yr period from June 2006 to May 2010. It is shown that the bulk of aerosols, from about 65% in winter to 45% in summer, are confined below the lowermost kilometer of the troposphere. In the middle troposphere (3-5 km), spring and autumn seasons show slightly higher aerosol amounts compared to other two seasons. The relative vertical distribution of aerosols shows that clean continental aerosol is the largest contributor in all seasons except in summer, when layers of polluted continental aerosols are almost as large. In winter and spring, polluted continental aerosols are the second largest contributor to the total number of observed aerosol layers, whereas clean marine aerosol is the second largest contributor in summer and autumn. The PDFs of the geometrical thickness of the observed aerosol layers peak about 400-700 m. Polluted continental and smoke aerosols, which are associated with the intrusions from mid-latitudes, have much broader distributions of optical and geometrical thicknesses, suggesting that they appear more often optically thicker and higher up in the troposphere.

Devasthale, Abhya↗
NASA NTRS2011

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 somewhat in 2008, 2009 and 2010 with the areas being 10%, 24%, and 11% higher than in 2007, respectively. However, the trends in the extent and area remain strongly negative at -12.2% and -13.5 %/decade, respectively. The thick component of the perennial ice, called multiyear ice, as detected by satellite data in the winters of 1979 to 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 % per decade, respectively, with record low value in 2008 followed by higher values in 2009, 2010 and 2011. Such high rate in the decline of the thick component of the Arctic ice cover means a reduction in 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 three times global average in the Arctic but appears weakly correlated with the AO which controls the dynamics of the region. An 8 to 9-year cycle is apparent in the multiyear ice record which could explain in part the slight recovery in the last three years.

Comiso, Josefino C.↗
NASA NTRS2012

On the Influence of North Pacific Sea Surface Temperature on the Arctic Winter Climate

Differences between two ensembles of Goddard Earth Observing System Chemistry-Climate Model simulations isolate the impact of North Pacific sea surface temperatures (SSTs) on the Arctic winter climate. One ensemble of extended winter season forecasts is forced by unusually high SSTs in the North Pacific, while in the second ensemble SSTs in the North Pacific are unusually low. High Low differences are consistent with a weakened Western Pacific atmospheric teleconnection pattern, and in particular, a weakening of the Aleutian low. This relative change in tropospheric circulation inhibits planetary wave propagation into the stratosphere, in turn reducing polar stratospheric temperature in mid- and late winter. The number of winters with sudden stratospheric warmings is approximately tripled in the Low ensemble as compared with the High ensemble. Enhanced North Pacific SSTs, and thus a more stable and persistent Arctic vortex, lead to a relative decrease in lower stratospheric ozone in late winter, affecting the April clear-sky UV index at Northern Hemisphere mid-latitudes.

Hurwitz, Margaret M.↗
NASA NTRS2012

The Contributions of Chemistry and Transport to Low Arctic Ozone in March 2011 Derived from Aura MLS Observations

Stratospheric and total columns of Arctic O3 (63-90 N) in late March 2011 averaged 320 and 349 DU, respectively. These values are 74 DU lower than averages for the previous 6 years. We use Aura MLS O3 observations to quantify the roles of chemistry and transport and find there are two major reasons for low O3 in March 2011: heterogeneous chemical loss and a late final warming that delayed the resupply of O3 until April. Daily vortex-averaged partial columns in the lowermost stratosphere (p greater than 133 hPa) and middle stratosphere (p less than 29 hPa) are unaffected by local heterogeneous chemistry and show a near total lack of transport into the vortex between late January and late March, contributing to the observed low column. The lower stratospheric (LS) column (133-29 hPa) is affected by both heterogeneous chemistry and transport. Low interannual variability of Aura MLS 0 3 columns and temperature inside the Arctic vortex (2004-2011) shows that the transport contribution to vortex O3 in fall and early winter is nearly the same each year. The descent of MLS N2O vortex profiles in 2011 provides an estimate of O3 transported into the LS column during late winter. By quantifying the role of transport we determine that PSC-driven chemical loss causes 80 (plus or minus 10) DU of vortex-averaged O3 loss by late March 2011. Without heterogeneous chemical loss, March 2011 vortex O3 would have been ~40 DU lower than normal due to the late final warming and resupply of O3 which did not occur until April.

Strahan, S. E.↗
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 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 NTRS2015

Hybrid Glacier Inventory, Gravimetry and Altimetry (HIGA) Mass Balance Product for Greenland and the Canadian Arctic

We present a novel inversion algorithm that generates a mass balance field that is simultaneously consistent with independent observations of glacier inventory derived from optical imagery, cryosphere-attributed mass trends derived from satellite gravimetry, and ice surface elevation trends derived from airborne and satellite altimetry. We use this algorithm to assess mass balance across Greenland and the Canadian Arctic over the Sep-2003 to Oct- 2009 period at 26 kilometers resolution. We evaluate local algorithm-inferred mass balance against forty in situ point observations. This evaluation yields a root mean squared error (RMSE) of 0.15 mWE/a ( 0.15 meters (water equivalent) per annum), and highlights a paucity of in situ observations from regions of high dynamic mass loss and peripheral glaciers. We assess mass losses of 212 plus or minus 67 Gigatons per annum to the Greenland ice sheet proper, 38 Gigatons per annum to peripheral glaciers in Greenland, and 42 Gigatons per annum to glaciers in the Canadian Arctic. These magnitudes of mass loss are dependent on the gravimetry-derived spherical harmonic mass trend we invert. We spatially partition the transient glacier continuity equation by differencing algorithm inferred mass balance from modeled surface mass balance, in order to solve the horizontal divergence of ice flux as a residual. This residual ice dynamic field infers flux divergence (or submergent flow) in the ice sheet accumulation area and at tidewater margins, and flux convergence (or emergent flow) in land-terminating ablation areas, which is consistent with continuum mechanics theory.

Altimetry↗
NASA NTRS2016

Arctic Cut-Off High Drives the Poleward Shift of a New Greenland Melting Record

Large-scale atmospheric circulation controls the mass and energy balance of the Greenland ice sheet through its impact on radiative budget, runoff and accumulation. Here, using reanalysis data and the outputs of a regional climate model, we show that the persistence of an exceptional atmospheric ridge, centered over the Arctic Ocean, was responsible for a poleward shift of runoff, albedo and surface temperature records over the Greenland during the summer of 2015. New records of monthly mean zonal winds at 500 hPa and of the maximum latitude of ridge peaks of the 5,700+/-50 m isohypse over the Arctic were associated with the formation and persistency of a cutoff high. The unprecedented (1948-2015) and sustained atmospheric conditions promoted enhanced runoff, increased the surface temperatures and decreased the albedo in northern Greenland, while inhibiting melting in the south, where new melting records were set over the past decade. Subject terms: Earth sciences Atmospheric science Climate science

drainage↗
NASA NTRS2018

Arctic Ocean Primary Productivity: The Response of Marine Algae to Climate Warming and Sea Ice Decline

Highlights: 1. Satellite estimates of ocean primary productivity (i.e., the rate at which marine algae transform dissolved inorganic carbon into organic material) were higher in 2018 (relative to the 2003-17 mean) for three of the nine investigated regions (the Eurasian Arctic, Bering Sea, and Baffin Bay). 2. All regions continue to exhibit positive trends over the 2003-18 period, with the strongest trends for the Eurasian Arctic, Barents Sea, Greenland Sea, and North Atlantic. 3. The regional distribution of relatively high (low) chlorophyll-a concentrations can often be associated with a relatively early (late) breakup of sea ice cover.

Frey, K.E.↗
NASA NTRS2019

Surface Height and Sea Ice Freeboard of the Arctic Ocean from ICESat-2: Characteristics and Early Results

We present the first winter season of surface height and sea ice freeboards of the Arctic Ocean from the new ICESat-2 (IS-2) mission. The Advanced Topographic Laser Altimeter System (ATLAS) onboard has six photon-counting beams for surface profiling with a 10-kHz pulse-rate (inter-pulse distance ~0.7m) and footprints of ~17m. Geolocated heights assigned to individual photons scattered from the surface allow significant flexibility in the construction of height distributions used in surface finding. For IS-2 sea ice products, a fixed 150-photon aggregate is used to control height precision and obtain better along-track resolution over high reflectance surfaces. Quasi-specular returns in openings as narrow as ~27m, crucial for freeboard calculations, are resolved. The fixed photon aggregate results in unique variable along-track resolutions and non-uniform sampling (17m x 27m to 17m x 200m for the strong beams) of the surface. The six profiling beams – three pairs separated by 3.3 km with a strong and weak beam in each pair – provide correlated statistics at regional length scales for assessment of beam-to-beam retrieval consistency and accuracy. Analysis shows along-track height precisions of ~2cm, and agreement in the monthly freeboard distributions across the strong beams to 1-2cm. In this paper, we describe briefly the approaches used in surface height and freeboard retrievals from ATLAS photon clouds, and detail the key features of these along-track sea ice products, focusing on the first release of data collected over the Arctic Ocean, which spans the period between October 14, 2018 – the start of data collection – and the end of March 2019.

R Kwok↗
NASA NTRS2020

Gully Formation at the Haughton Impact Structure (Arctic Canada) Through the Melting of Snow and Ground Ice, with Implications for Gully Formation on Mars

The formation of gullies on Mars has been the topic of active debate and scientific study since their first discovery by Malin and Edgett in 2000. Several mechanisms have been proposed to account for gully formation on Mars, from “dry” mass movement processes, release of water or brine from subsurface aquifers, and the melting of near-surface ground ice or snowpacks. In their global documentation of martian gullies, report that gullies are confined to ~27–83°S and ~28–72°N latitudes and span all longitudes. Gullies on Mars have been documented on impact crater walls and central uplifts, isolated massifs, and on canyon walls, with crater walls being the most common situation. In order to better understand gully formation on Mars, we have been conducting field studies in the Canadian High Arctic over the past several summers, most recently in summer 2018 and 2019 under the auspices of the Canadian Space Agency-funded Icy Mars Analogue Program. It is notable that the majority of previous studies in the Arctic and Antarctica, including our recent work on Devon Island, have focused on gullies formed on slopes generated by regular endogenic geological processes and in “regular” bedrock. How-ever, as noted above, meteorite impact craters are the most dominant setting for gullies on Mars. Impact craters provide an environment with diverse lithologies – including impact-generated and impact-modified rocks – and slope angle, and thus greatly variable hill slope processes could occur within a localized area. Here, we investigate the formation of gullies within the Haughton impact structure and compare them to gullies formed in unimpacted target rock in the nearby Thomas Lee Inlet

Osinski, G. R.↗
NASA NTRS2019

Seasonal Variations of Arctic Low-Level Clouds and its Linkage to Sea Ice Seasonal Variations

Using CALIPSO-CloudSat-Clouds and the Earth's Radiant Energy System (CERES)-Moderate Resolution Imaging Spectrometer (MODIS) (C3M) dataset, this study documents the seasonal variation of sea ice, cloud, and related atmospheric properties in the Arctic region (70°N–82°N) during the period 2007-2010. The surface type stratification used reveals the surface type influence on the Arctic cloud liquid water path (LWP)seasonality. Four surface types are defined: i) Permanent Ocean, ii) Land, iii) Permanent Ice, and iv) Transient Sea Ice. The Transient Ice regions are further divided into sub-regions according to the onset dates of melt/freeze season. Results show that the sea ice cover has no significant direct influence on the seasonal variation of the water vapor in the lower troposphere and the low-level cloud LWP. Rather, the role played by sea ice appear indirect by modifying the surface temperature response to increased solar insolation and influencing lower tropospheric stability (LTS). The results suggest that the combined increase in atmospheric water vapor due to warming air temperatures and the weakening of the inversion strength that governs the seasonal structure of cloud LWP. Over Transient Ice regions, the results suggest that the May peak in LWP coincides with a decrease in LTS and that is insensitive to melt and freeze onset. Variations in melt and freeze onset set are found to influence probably distribution of cloud LWP where regions of earlier melt and later freeze onset how a higher likelihood of larger values.

Yueyue Yu↗
NASA NTRS2020

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

The snow layer atop Arctic sea ice is an important component of the climate system. In winter, the insulating effects of snow slow the rate of ice growth. In spring, the onset of ice surface melt is delayed until the highly reflective snow layer disappears. During summer, meltwater from snow collects in depressions to form melt ponds, which enhances the absorption of solar radiation leading to more rapid surface warming. Presently, there are no routine measurements of snow depth suitable for assessing the impact of climate changes on the precipitation and accumulation of snow on sea ice.Our current understanding of snow depth is limited and has been based on field measurements conducted in the middle of last century and from airborne surveys conducted over the last decade. In this paper, we combine the measurements from two altimetry missions (ICESat‐2 and CryoSat‐2) to calculate snow depth over the entire Arctic Ocean. ICESat‐2 (a lidar) and CryoSat‐2 (a radar) measure the heights to the top and bottom of the snow layer, respectively. Differencing the two heights provides an estimate of the thickness of the snow layer. This paper describes this novel approach and an assessment of the snow depth estimates.

R. Kwok↗
NASA NTRS2020

Decay of the Snow Cover Over Arctic Sea Ice From ICESat‐2 Acquisitions During Summer Melt in 2019

From the onset of melt in early June, corresponding declines in Ice, Cloud, and Land Elevation Satellite‐2 (ICESat‐2) freeboard and surface albedo can be seen over the entire Arctic sea ice cover. In the 2019 summer, area‐averaged freeboard decreased from 34 cm prior to melt to a minimum of 12 cm in August while the area‐averaged albedo decreased from ~0.7 to 0.38 for the same period. Calculations using ICESat‐2 freeboards and modeled ice thickness from Pan‐Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) give area‐averaged snow depths ranging from 17 cm prior to melt to 3 cm in August over seasonal ice and from 34 to 4 cm over multiyear ice. Mean rates of snow ablation (including evaporation) in mid‐June were as high as 2 cm/day, comparable to field records from other years. Increases in freeboard after mid‐August in the high latitude (>80°N) multiyear ice cover, north of the Greenland coast, are likely due to earlier freeze‐up and snow accumulation in these regions with shorter melt seasons.

R Kwok↗
NASA NTRS2021

Landsat Derived Bathymetry of Lakes on the Arctic Coastal Plan of Northern Alaska

The Pleistocene sand sea on the Arctic Coastal Plain (ACP) of northern Alaska is underlain by anancient sand dune field, a geological feature that affects regional lake characteristics. Many of these lakes, whichcover approximately 20 % of the Pleistocene sand sea, are relatively deep (up to 25 m). In addition to the nat-ural importance of ACP sand sea lakes for water storage, energy balance, and ecological habitat, the need forwinter water for industrial development and exploration activities makes lakes in this region a valuable resource.However, ACP sand sea lakes have received little prior study. Here, we collect in situ bathymetric data to test12 model variants for predicting sand sea lake depth based on analysis of Landsat-8 Operational Land Imager(OLI) images. Lake depth gradients were measured at 17 lakes in midsummer 2017 using a Humminbird 798ciHD SI Combo automatic sonar system. The field-measured data points were compared to red–green–blue (RGB)bands of a Landsat-8 OLI image acquired on 8 August 2016 to select and calibrate the most accurate spectral-depth model for each study lake and map bathymetry. Exponential functions using a simple band ratio (withbands selected based on lake turbidity and bed substrate) yielded the most successful model variants. For eachlake, the most accurate model explained 81.8 % of the variation in depth, on average. Modeled lake bathymetrieswere integrated with remotely sensed lake surface area to quantify lake water storage volumes, which rangedfrom 1.056×10−3to 57.416×10−3km3. Due to variations in depth maxima, substrate, and turbidity betweenlakes, a regional model is currently infeasible, rendering necessary the acquisition of additional in situ datawith which to develop a regional model solution. Estimating lake water volumes using remote sensing will fa-cilitate better management of expanding development activities and serve as a baseline by which to evaluatefuture responses to ongoing and rapid climate change in the Arctic. All sonar depth data and modeled lakebathymetry rasters can be freely accessed at https://doi.org/10.18739/A2SN01440 (Simpson and Arp, 2018) andhttps://doi.org/10.18739/A2HT2GC6G (Simpson, 2019), respectively.

Claire E Simpson↗
NASA NTRS2019

The Salience of Nonlinearities in the Boreal Winter Response to ENSO: Arctic Stratosphere and Europe

The Arctic stratospheric response to El Niño (EN) and La Niña (LN) is evaluated in a 41 member ensemble of the period 1980 to 2009 in the Goddard Earth Observing System Chemistry-Climate Model. We consider whether the responses to EN and LN are equal in magnitude and opposite in sign, whether the responses to moderate and extreme events are proportion-ate, and if the response depends on whether sea surface temperature anomalies (SSTs) peak in the Eastern Pacific (EP) or Central Pacific (CP). There is no indication of any nonlinearities between EN and LN, though in ~ 15% of the ensemble members the stratospheric sudden warming (SSW) frequencies for EN and LN are similar, suggesting that a similar SSW frequency for EN and LN, as has occurred over the past ~ 60 years, can occur by chance. The response to extreme EN events is not proportionate to the amplitude of the underlying SST anomalies in spring. EP EN events preferentially increase zonal wavenumber 1 and decrease zonal wavenumber 2 as compared to CP EN events, however the zonal-mean Arctic stratospheric and subpolar surface response is generally little different between EP EN and CP EN once one accounts for the relative weakness of CP events. These differences between EP and CP events and between moderate and extreme EN events only emerge if at least 25 events are composited, however, due to the small signal-to-noise ratio, and hence these differences may be of little practical benefit.

Sea surface temperature anomalies (SSTs) peak in t↗