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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

The Arctic Ocean ice balance - A Kalman smoother estimate

The methodology of Kalman filtering and smoothing is used to integrate a 7-year time series of buoy-derived ice motion fields and satellite passive microwave observations. The result is a record of the concentrations of open water, first-year ice, and multiyear ice that we believe is better than the estimates based on the microwave data alone. The Kalman procedure interprets the evolution of the ice cover in terms of advection, melt, growth, ridging, and aging of first-year into multiyear ice. Generally, the regions along the coasts of Alaska and Siberia and the area just north of Fram Strait are sources of first-year ice, with the rest of the Arctic Ocean acting as a sink for first-year ice via ridging and aging. All the Arctic Ocean except for the Beaufort and Chukchi seas is a source of multiyear ice, with the Chukchi being the only internal multiyear ice sink. Export through Fram Strait is a major ice sink, but we find only about two-thirds the export and greater interannual variation than found in previous studies. There is no discernible trend in the area of multiyear ice in the Arctic Ocean during the 7 years.

Thomas, D. R.↗
NASA NTRS2001

Projected Impact of Climate Change on the Energy Budget of the Arctic Ocean by a Global Climate Model

The annual energy budget of the Arctic Ocean is characterized by a net heat loss at the air-sea interface that is balanced by oceanic heat transport into the Arctic. The energy loss at the air-sea interface is due to the combined effects of radiative, sensible, and latent heat fluxes. The inflow of heat by the ocean can be divided into two components: the transport of water masses of different temperatures between the Arctic and the Atlantic and Pacific Oceans and the export of sea ice, primarily through Fram Strait. Two 150-year simulations (1950-2099) of a global climate model are used to examine how this balance might change if atmospheric greenhouse gases (GHGs) increase. One is a control simulation for the present climate with constant 1950 atmospheric composition, and the other is a transient experiment with observed GHGs from 1950 to 1990 and 0.5% annual compounded increases of CO2 after 1990. For the present climate the model agrees well with observations of radiative fluxes at the top of the atmosphere, atmospheric advective energy transport into the Arctic, and surface air temperature. It also simulates the seasonal cycle and summer increase of cloud cover and the seasonal cycle of sea-ice cover. In addition, the changes in high-latitude surface air temperature and sea-ice cover in the GHG experiment are consistent with observed changes during the last 40 and 20 years, respectively. Relative to the control, the last 50-year period of the GHG experiment indicates that even though the net annual incident solar radiation at the surface decreases by 4.6 W(per square meters) (because of greater cloud cover and increased cloud optical depth), the absorbed solar radiation increases by 2.8 W(per square meters) (because of less sea ice). Increased cloud cover and warmer air also cause increased downward thermal radiation at the surface so that the net radiation into the ocean increases by 5.0 Wm-2. The annual increase in radiation into the ocean, however, is compensated by larger increases in sensible and latent heat fluxes out of the ocean. Although the net energy loss from the ocean surface increases by 0.8 W (per square meters), this is less than the interannual variability, and the increase may not indicate a long-term trend. The seasonal cycle of heat fluxes is significantly enhanced. The downward surface heat flux increases in summer (maximum 2 of 19 W per square meters or 23% in June) while the upward heat flux increases in winter (maximum of 16 W per square meters or 28% in November). The increased downward flux in summer is due to a combination of increases in absorbed solar and thermal radiation and smaller losses of sensible and latent heat. The increased heat loss in winter is due to increased sensible and latent heat fluxes, which in turn are due to reduced sea-ice cover. On the other hand, the seasonal cycle of surface air temperature is damped, as there is a large increase in winter temperature but little change in summer.

Miller, James R.↗
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↗
DOE OSTI2025

Predictive links between microbial communities and biological oxygen utilization in the Arctic Ocean

Microbial metabolism influences rates of net community production (NCP), exerting a direct biological control on marine oxygen and carbon fluxes. In the Arctic, it is increasingly important to understand and quantify this process, as ecological and oceanographic conditions shift due to changing climate. Here, we describe potential ecological links between pelagic microbial diversity and an NCP precursor, biological oxygen utilization, using machine learning and paired observations of community structure and metabolic activity from a seasonally and spatially variable transect of the Arctic Ocean (2019–2020 MOSAiC Expedition). Community structure was determined using 16S (prokaryotic) and 18S (eukaryotic) rRNA gene amplicon sequencing, and metabolic activity was derived from ΔO 2 /Ar. Using self-organizing maps, we identified clear successional patterns in observed microbial community structure that were seasonally driven in the upper ocean and vertically stratified with depth. Metabolic activity was also stratified, with a primarily net heterotrophic water column (median −1.5% biological oxygen saturation), excepting periodic oxygen supersaturation (maximum: 13.6%) within the mixed layer. Using DNA sequences as predictor variables, we then constructed a random forest regression model that reliably reconstructed biological oxygen concentrations (root mean squared error = 4.14 μmol kg −1 ). Top predictors from this model were from heterotrophic (bacteria) or potentially mixotrophic (dinoflagellate) taxa. These analyses highlight biologically driven diagnostic tools that can be used to expand biogeochemical datasets and improve the microbial perspectives and metabolisms represented in ecological models of net productivity and carbon flux in a changing Arctic Ocean.

Chamberlain, Emelia J. [Univ. of San Diego, San Di↗
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 NTRS1993

Diurnal tides in the Arctic Ocean

A 2D numerical model with a space grid of about 14 km is applied to calculate diurnal tidal constituents K(1) and O(1) in the Arctic Ocean. Calculated corange and cotidal charts show that along the continental slope, local regions of increased sea level amplitude, highly variable phase and enhanced currents occur. It is shown that in these local regions, shelf waves (topographic waves) of tidal origin are generated. In the Arctic Ocean and Northern Atlantic Ocean more than 30 regions of enhanced currents are identified. To prove the near-resonant interaction of the diurnal tides with the local bottom topography, the natural periods of oscillations for all regions have been calculated. The flux of energy averaged over the tidal period depicts the gyres of semitrapped energy, suggesting that the shelf waves are partially trapped over the irregularities of the bottom topography. It is shown that the occurrence of near-resonance phenomenon changes the energy flow in the tidal waves. First, the flux of energy from the astronomical sources is amplified in the shelf wave regions, and afterwards the tidal energy is strongly dissipated in the same regions.

Kowalik, Z.↗
NASA NTRS2023

Upper Arctic Ocean Properties and Relationships with Sea Ice in CMIP6 Historical Simulations

While current-generation CMIP and OMIP models have clear biases in their upper Arctic Ocean hydrography, it is less clear how these biases impact the models' ability to simulate the observed Arctic sea ice mean state and trends. In this study we seek to quantify cross-relationship between sea ice and ocean states in CMIP6 historical simulations and identify common model behaviors. Multi-model mean (MMM) simulations exhibit accelerated changes in the ice and ocean system since the late 20th century. Underlying the MMM is strong inter-model variation in the simulated ice and ocean mean states and their temporal variability including trends. Despite such inter-model differences, all models show a similar ratio between sea ice reduction and upper ocean warming such that models with higher ocean warming also have higher SIE reduction and vice versa. Our results also highlight the urgent needs of reliable Arctic Ocean observations or data products in order to better contextualize modeling results.

Upper Arctic Ocean↗
NASA NTRS1998

The Arctic Ocean Perennial Ice Zone

This study shows that: 1) the NSCAT backscatter fields provide an estimate of the PIZ coverage of the Arctic Ocean; and, 2) the decrease in PIZ area over the winter gives an indication of the PIZ area exported through Fram Strait.

Arctic Ocean ice flux area balance↗
NASA NTRS2021

Sea Surface Height Anomalies of the Arctic Ocean from Icesat-2: A First Examination and Comparisons with Cryosat-2

Accurately resolving spatio-temporal variations in sea surface height across the polar oceans is key to improving our understanding of ocean circulation variability and change. Here, we examine the first two years (2018-2020) of Arctic Ocean sea surface height anomalies (SSHA) from the photon-counting laser altimeter onboard NASA’s ICE, Cloud, and Land Elevation Satellite-2 (ICESat-2). ICESat-2 SSHA estimates are compared to estimates from ESA’s CryoSat-2 mission, including semi-synchronous along-track measurements from the recent CRYO2ICE orbit alignment campaign. There are documented residual centimeter-scale range biases between the ICESat-2 beams (in release-003 data) and we opted for a single-beam approach in our comparisons. We find good agreement in the along-track estimates (spatial correlation coefficient >0.8 and mean differences <0.03 m) as well as in the gridded monthly SSHA estimates (temporal correlation coefficient of 0.76 and a mean difference of 0.01 m) from the two altimeters, suggesting ICESat-2 adds to the CryoSat-2 SSHA estimates.

ICESat-2↗
NASA NTRS2021

Extreme High Greenland Blocking Index Leads to the Reversal of Davis and Nares Strait Net Transport Towards the Arctic Ocean

Baffin Bay exports Arctic Water to the North Atlantic while receiving northward flowing Atlantic Water. Warm Atlantic Water has impacted the retreat of tidewater glaciers draining the Greenland Ice Sheet. Periods of enhanced Atlantic Water transport into Baffin Bay have been observed, but the oceanic processes are still not fully explained. At the end of 2010 the net transport at Davis Strait, the southern gateway to Baffin Bay, reversed from southward to northward for a month, leading to significant northward oceanic heat transport into Baffin Bay. This was associated with an extreme high in the Greenland Blocking Index and a stormtrack path that shifted away from Baffin Bay. Thus fewer cyclones in the Irminger Sea resulted in less frequent northerly winds along the western coast of Greenland, allowing anomalous northward penetration of warm waters, reversing the volume and heat transport at Davis Strait.

Davis Strait↗
NASA NTRS2001

Storm-driven Mixing and Potential Impact on the Arctic Ocean

Observations of the ocean, atmosphere, and ice made by Ice-Ocean Environmental Buoys (IOEBs) indicate that mixing events reaching the depth of the halocline have occurred in various regions in the Arctic Ocean. Our analysis suggests that these mixing events were mechanically forced by intense storms moving across the buoy sites. In this study, we analyzed these mixing events in the context of storm developments that occurred in the Beaufort Sea and in the general area just north of Fram Strait, two areas with quite different hydrographic structures. The Beaufort Sea is strongly influenced by inflow of Pacific water through Bering Strait, while the area north of Fram Strait is directly affected by the inflow of warm and salty North Atlantic water. Our analyses of the basin-wide evolution of the surface pressure and geostrophic wind fields indicate that the characteristics of the storms could be very different. The buoy-observed mixing occurred only in the spring and winter seasons when the stratification was relatively weak. This indicates the importance of stratification, although the mixing itself was mechanically driven. We also analyze the distribution of storms, both the long-term climatology as well as the patterns for each year in the last two decades. The frequency of storms is also shown to be correlated- (but not strongly) to Arctic Oscillation indices. This study indicates that the formation of new ice that leads to brine rejection is unlikely the mechanism that results in the type of mixing that could overturn the halocline. On the other hand, synoptic-scale storms can force mixing deep enough to the halocline and thermocline layer. Despite a very stable stratification associated with the Arctic halocline, the warm subsurface thermocline water is not always insulated from the mixed layer.

Yang, Jiayan↗
NASA NTRS1985

Characteristics of Arctic Ocean ice determined from SMMR data for 1979 - Case studies in the seasonal sea ice zone

Sea ice data derived from the Scanning Multichannel Microwave Radiometer are examined for sections of the Arctic Ocean during early summer 1979. The temporary appearance of spuriously high multiyear ice fractions in the seasonal ice zones of the Kara and Barents Seas is a result of surface melt phenomena and the relative responses of the different channels to these effects. These spurious signatures can provide early identification of melt onset and additional information on surface characteristics.

Anderson, M. R.↗
NASA NTRS2011

October Cloud Increases Over the Arctic Ocean as Observed by MISR and CALIPSO

The Beaufort and East Siberian Sea (BESS) shows a large increase in surface air temperature (SAT) in the recent decade for months of Sep-Nov, and NASA's Terra satellite have provided valuable measurements for this important decade of the intensified Arctic warming. In particular, MISR data since 2000 and CALIPSO cloud measurements since 2006 reveal a significant increase of low cloud cover in October, which is largest in the daylight Arctic months (March-October). Causes of the warming remain unclear; but increased absorption of summer solar radiation and autumn low cloud formation have been suggested as a positive ice-temperature-cloud feedback in the Arctic. The observed increase of low cloud cover supports the theorized positive ice-temperature-cloud feedback, whereby more open water in the Arctic Ocean increases summer absorption of solar radiation, and subsequent evaporation, which leads to more low clouds in autumn. Trapping longwave radiation, these clouds effectively lengthen the melt season and reduce perennial ice pack formation, making sea ice more vulnerable to the next melt season

Wu, Dong L.↗
NASA NTRS1994

Arctic ocean radiative fluxes and cloud forcing estimated from the ISCCP C2 cloud dataset, 1983-1990

Radiative fluxes and cloud forcings for the ocean areas of the Arctic are computed from the monthly cloud product of the International Satellite Cloud Climatology Project (ISCCP) for 1983-90. Spatially averaged short-wave fluxes are compared well with climatological values, while downwelling longwave fluxes are significantly lower. This is probably due to the fact that the ISCCP cloud amounts are underestimates. Top-of-the-atmosphere radiative fluxes are in excellent agreement with measurements from the Earth Radiation Budget Experiment (ERBE). Computed cloud forcings indicate that clouds have a warming effect at the surface and at the top of the atmosphere during winter and a cooling effect during summer. The net radiative effect of clouds is larger at the surface during winter but greater at the top of the atmosphere during summer. Overall the net radiative effect of clouds at the top of the atmosphere is one of cooling. This is in contrast to a previous result from ERBE data showing arctic cloud forcings have a net warming effect. Sensitivities to errors in input parameters are generally greater during winter with cloud amount being the most important paarameter. During summer the surface radiation balance is most sensitive to errors in the measurements of surface reflectance. The results are encouraging, but the estimated error of 20 W/sq m in surface net radiative fluxes is too large, given that estimates of the net radiative warming effect due to a doubling of CO2 are on the order of 4 W/sq m. Because it is difficult to determine the accuracy of results with existing in situ observations, it is recommended that the development of improved algorithms for the retrieval of surface radiative properties be accompanied by the simultaneous assembly of validation datasets.

Schweiger, Axel J.↗
NASA NTRS2012

Arctic Ocean Freshwater: How Robust are Model Simulations

The Arctic freshwater (FW) has been the focus of many modeling studies, due to the potential impact of Arctic FW on the deep water formation in the North Atlantic. A comparison of the hindcasts from ten ocean-sea ice models shows that the simulation of the Arctic FW budget is quite different in the investigated models. While they agree on the general sink and source terms of the Arctic FW budget, the long-term means as well as the variability of the FW export vary among models. The best model-to-model agreement is found for the interannual and seasonal variability of the solid FW export and the solid FW storage, which also agree well with observations. For the interannual and seasonal variability of the liquid FW export, the agreement among models is better for the Canadian Arctic Archipelago (CAA) than for Fram Strait. The reason for this is that models are more consistent in simulating volume flux anomalies than salinity anomalies and volume-flux anomalies dominate the liquid FW export variability in the CAA but not in Fram Strait. The seasonal cycle of the liquid FW export generally shows a better agreement among models than the interannual variability, and compared to observations the models capture the seasonality of the liquid FW export rather well. In order to improve future simulations of the Arctic FW budget, the simulation of the salinity field needs to be improved, so that model results on the variability of the liquid FW export and storage become more robust.

Jahn, A.↗