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At least 271 records · Page 15

Arctic atmosphere - Ice interaction studies using Nimbus-7 SMMR

The use of data from the Scanning Multichannel Microwave Radiometer (SMMR) on board Nimbus 7 for studying ice-atmosphere interactions is discussed with reference to two case studies, one for the Greenland Sea and the other for the Sea of Okhotsk, for April/May 1979. By using SMMR data, rapid changes in ice extent and concentration have been observed in association with changes in synoptic atmospheric circulation. Case studies and analyses of sample data indicate that ice concentration estimates may be accurate to within 10 percent.

Anderson, M. R.↗

Satellite Snow-Cover Mapping: A Brief Review

Satellite snow mapping has been accomplished since 1966, initially using data from the reflective part of the electromagnetic spectrum, and now also employing data from the microwave part of the spectrum. Visible and near-infrared sensors can provide excellent spatial resolution from space enabling detailed snow mapping. When digital elevation models are also used, snow mapping can provide realistic measurements of snow extent even in mountainous areas. Passive-microwave satellite data permit global snow cover to be mapped on a near-daily basis and estimates of snow depth to be made, but with relatively poor spatial resolution (approximately 25 km). Dense forest cover limits both techniques and optical remote sensing is limited further by cloudcover conditions. Satellite remote sensing of snow cover with imaging radars is still in the early stages of research, but shows promise at least for mapping wet or melting snow using C-band (5.3 GHz) synthetic aperture radar (SAR) data. Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data beginning with the launch of the first EOS platform in 1998. Digital maps will be produced that will provide daily, and maximum weekly global snow, sea ice and lake ice cover at 1-km spatial resolution. Statistics will be generated on the extent and persistence of snow or ice cover in each pixel for each weekly map, cloudcover permitting. It will also be possible to generate snow- and ice-cover maps using MODIS data at 250- and 500-m resolution, and to study and map snow and ice characteristics such as albedo. been under development. Passive-microwave data offer the potential for determining not only snow cover, but snow water equivalent, depth and wetness under all sky conditions. A number of algorithms have been developed to utilize passive-microwave brightness temperatures to provide information on snow cover and water equivalent. The variability of vegetative Algorithms are being developed to map global snow and ice cover using Earth Algorithms to map global snow cover using passive-microwave data have also cover and of snow grain size, globally, limits the utility of a single algorithm to map global snow cover.

Hall, Dorothy K.↗

Tracking of Ice Edges and Ice Floes by Wavelet Analysis of SAR Images

This paper demonstrates the use of wavelet transforms in the tracking of sequential ice features in the ERS-1 synthetic aperture radar (SAR) imagery, especially in situations where feature correlation techniques fail to yield reasonable results. Examples include the evolution of the St. Lawrence polynya and summer sea ice change in the Beaufort Sea. For the polynya, the evolution of the region of young ice growth surrounding a polynya can be easily tracked by wavelet analysis due to the large backscatter difference between the young and old ice. Also within the polynya, a 2D fast Fourier transform (FFT) is used to identify the extent of the Langmuir circulation region, which is coincident with the wave-agitated frazil ice growth region, where the sea ice experiences its fastest growth. Therefore, the combination of wavelet and FFT analysis of SAR images provides for the large-scale monitoring of different polynya features. For summer ice, previous work shows that this is the most difficult period for ice trackers due to the lack of features on the sea ice cover. The multiscale wavelet analysis shows that this method delineates the detailed floe shapes during this period, so that between consecutive images, the floe translation and rotation can be estimated.

Liu, Antony K.↗

Phytoplankton in the Beaufort and Chukchi Seas: Distributions, Dynamics and Environmental Forcing

Time-series of remotely sensed distributions of phytoplankton, sea ice, surface temperature, albedo, and clouds were examined to evaluate the impact of the variability of environmental conditions and physical forcing on the phytoplankton distribution in the Beaufort and Chukchi Seas. Large-scale distributions of these parameters were studied for the first time using weekly and monthly composites from April 1998 through September 2002. The basic data set used in this study are phytoplankton pigment concentration derived from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), ice concentration obtained from the Special Sensor Microwave Imager (SSM/I) and surface temperature, cloud cover, and albedo derived from the Advanced Very High Resolution Radiometer (AVHRR). Seasonal variations of the sea ice cover was observed to be the dominant environmental factor as the ice edge blooms followed the retreating marginal ice zones northward. Blooms were most prominent in the southwestern Chukchi Sea, and were especially persistent immediately north of the Bering Strait in nutrient- rich Anadyr water and in some fronts. Chlorophyll concentrations are shown to increase from a nominal value during onset of melt in April to a maximum value in mid-spring or summer depending on location. Large interannual variability of ice cover and phytoplankton distributions was observed with the year 1998 being uniquely associated with an early season occurrence of a massive bloom. This is postulated to be caused in part by a rapid response of phytoplankton to an early retreat of the sea ice cover in the Beaufort Sea region. Correlation analyses showed relatively high negative correlation between chlorophyll and ice concentration with the correlation being highest in May, the correlation coefficient being -0.45. 1998 was also the warmest among the five years globally and the sea ice cover was least extensive in the Beaufort-Khukchi Sea region, partly because of the 1997-98 El Nino. Strong correlations were noted between ice extent and surface temperature, the correlation coefficient being highest at - 0.79 in April, during the onset of the bloom period

Wang, Jian↗

Expected scientific yield of Seasat-A and its application to Corps of Engineers programs

The Corps of Engineers interest in SEASAT-A is a natural outgrowth of its mission to protect and manage the Nation's shorelines. In regard to the expected payload on SEASAT-A the following general study areas can be identified: gravity waves, wind waves, wind-wave interaction, storms and hurricanes, ice, coastal currents, tsunamis, and to a very small extent geoid modelling as it applies to determination of sea level and tides.

Teleki, P. G.↗

Late quaternary time series of Arabian Sea productivity: Global and regional signals

Modern annual floral and faunal production in the northwest Arabian Sea derives primarily from upwelling induced by strong southwest winds during June, July, and August. Indian Ocean summer monsoon winds are, in turn, driven by differential heating between the Asian continent and the Indian ocean to the south. This differential heating produces a strong pressure gradient resulting in southwest monsoon winds and both coastal and divergent upwelling off the Arabian Peninsula. Over geologic time scales (10(exp 4) to 10(exp 6) years), monsoon wind strength is sensitive to changes in boundary conditions which influence this pressure gradient. Important boundary conditions include the seasonal distribution of solar radiation, global ice volume, Indian Ocean sea surface temperature, and the elevation and albedo of the Asian continent. To the extent that these factors influence monsoon wind strength, they also influence upwelling and productivity. In addition, however, productivity associated with upwelling can be decoupled from the strength of the summer monsoon winds via ocean mechanisms which serve to inhibit or enhance the nutrient supply in the intermediate waters of the Indian Ocean, the source for upwelled waters in the Arabian Sea. To differentiate productivity associated with wind-induced upwelling from that associated with other components of the system such as nutrient sequestering in glacial-age deep waters, we employ a strategy which monitors independent components of the oceanic and atmospheric subsystems. Using sediment records from the Owen Ridge, northwest Arabian Sea, we monitor the strength of upwelling and productivity using two independent indicators, percent G. bulloides and opal accumulation. We monitor the strength of southwest monsoon winds by measuring the grain-size of lithogenic dust particles blown into the Arabian Sea from the surrounding deserts of the Somali and Arabian Peninsulas. Our current hypothesis is that the variability associated with the 41 kyr power in the G. bulloides and opal accumulation records derive from nutrient availability in the intermediate waters which are upwelled via monsoon winds. This hypothesis is testable by comparison with Cd records of intermediate and deep waters of the Atlantic and Indian Ocean.

Clemens, Steven C.↗

Trends in Surface Temperature at High Latitudes

The earliest signal of a climate change is expected to be found in the polar regions where warming is expected to be amplified on account of ice-albedo feedbacks associated with the high reflectivity of snow and ice. Because of general inaccessibility, there is a general paucity of in situ data and hence the need to use satellite data to observe the large-scale variability and trends in surface temperature in the region. Among the most important sensors for monitoring surface temperature has been the Advanced Very High Resolution Radiometer (AVHRR) which was first launched in 1978 and has provided continuous thermal infrared data since 1981. The top of the atmosphere data are converted to surface temperature data through various schemes that accounts for the unique atmospheric and surface conditions in the polar regions. Among the highest source of error in the data is cloud masking which is made more difficult in the polar region because of similar Signatures of clouds and snow lice covered areas. The availability of many more channels in the Moderate Resolution Imaging Spectroradiometer (MODIS) launched on board Terra satellite in December 1999 and on board Aqua in May 2002 (e.g., 36 visible and infrared channels compared to 5 for AVHRR) made it possible to minimize the error. Further capabilities were introduced with the Advanced Microwave Scanning Radiometer (AMSR) which has the appropriate frequency channels for the retrieval of sea surface temperature (SST). The results of analysis of the data show an amplified warming in the Arctic region, compared with global warming. The spatial distribution of warming is, however, not uniform and during the last 3 decades, positive temperature anomalies have been most pronounced in North America, Greenland and the Arctic basin. Some regions of the Arctic such as Siberia and the Bering Sea surprisingly show moderate cooling but this may be because these regions were anomalously warm in the 1980s when the satellite record started. Also, the SST in the Arctic basin is observed to be anomalously high in 2007 when the perennial ice cover declined dramatically to its lowest extent. In the Antarctic, surface temperature trends are much more moderate with the most positive trends occurring in the Antarctic Peninsula and parts of Western Antarctica while some cooling are observed in the Antarctic Plateau and the Ross Sea. The trends in SST in the region is similar to global averages but precipitation from more evaporation may have a key role in the spatial distribution of surface temperature in the ice covered region

Comiso, Josefino C.↗

Surface Melting Over the Greenland Ice Sheet Derived From Enhanced Resolution Passive Microwave Brightness Temperatures (1979–2019)

Surface melting is a major component of the Greenland ice sheet surface mass balance, and it affects sea level rise through direct runoff and the modulation of ice dynamics and hydrological processes, supraglacially, englacially and subglacially. Passive microwave (PMW) brightness temperature observations are of paramount importance in studying the spatial and temporal evolution of surface melting due to their long temporal coverage (1979–present) and high temporal resolution (daily). However, a major limitation of PMW datasets has been the relatively coarse spatial resolution, which has historically been of the order of tens of kilometers. Here, we use a newly released PMW dataset (37 GHz, horizontal polarization) made available through a NASA “Making Earth System Data Records for Use in Research Environments” (MeASUREs) program to study the spatiotemporal evolution of surface melting over the Greenland ice sheet at an enhanced spatial resolution of 3.125 km. We assess the outputs of different detection algorithms using data collected by automatic weather stations (AWSs) and the outputs of the Modèle Atmosphérique Régional (MAR) regional climate model. We found that sporadic melting is well captured using a dynamic algorithm based on the outputs of the Microwave Emission Model of Layered Snowpack (MEMLS), whereas a fixed threshold of 245 K is capable of detecting persistent melt. Our results indicate that, during the reference period from 1979 to 2019 (from 1988 to 2019), surface melting over the ice sheet increased in terms of both duration, up to 4.5 (2.9) d per decade, and extension, up to 6.9 % (3.6 %) of the entire ice sheet surface extent per decade, according to the MEMLS algorithm. Furthermore, the melting season started up to 4.0 (2.5) d earlier and ended 7.0 (3.9) d later per decade. We also explored the information content of the enhanced-resolution dataset with respect to the one at 25 km and MAR outputs using a semi-variogram approach. We found that the enhanced product is more sensitive to local-scale processes, thereby confirming the potential of this new enhanced product for monitoring surface melting over Greenland at a higher spatial resolution than the historical products and for monitoring its impact on sea level rise. This offers the opportunity to improve our understanding of the processes driving melting, to validate modeled melt extent at high resolution and, potentially, to assimilate these data in climate models.

Surface melting↗

Alaska: Glaciers of Kenai Fjords National Park and Katmai National Park and Preserve (Chapter 12)

Much recent research points to the shrinkage of the Earth's small glaciers, however, few studies have been performed to quantify the amount of change over time. We measured glacier-extent changes in two national parks in southeastern Alaska. There are hundreds of glaciers in Kenai Fjords National Park (KEFJ) and Katmai National Park and Preserve (KATM) covering over 2373 sq km of parkland. There are two primary areas of glaciation in KEFJ - the Harding Icefield and the Grewingk-Yalik Glacier Complex, and three primary areas of glaciation in KATM - the Mt. Douglas area, the Kukak Volcano to Mt. Katmai area and the Mt. Martin area. We performed glacier mapping using satellite imagery, from the 1970s, 1980s, and from 2000. Results of the analysis show that there has been a reduction in the amount of glacier ice cover in the two parks over the study period, of approximately 22 sq km of ice, approximately - 1.6% from 1986 to 2000 (for KEFJ), and of approximately 76 sq km of glacier ice, or about -7.7% from 1986187 to 2000 (for KATM). In the future, measurements of surface elevation changes of these ice masses should be acquired; together with our extent-change measurements, the volume change of the ice masses can then be determined to estimate their contribution to sea-level rise. The work is a continuation of work done in KEFJ, but in KATM, our measurements represent the first comprehensive study of the glaciers in this remote, little-studied area.

Giffen, Bruce A.↗

Sea ice and surface water circulation, Alaskan Continental Shelf

The author has identified the following significant results. The boundaries of land-fast ice, distribution of pack ice, and major polynya were studied in the vicinity of the Bering Strait. Movement of pack ice during 24 hours was determined by plotting the distinctly identifiable ice floes on ERTS-1 imagery obtained from two consecutive passes. Considerably large shallow area along the western Seward Peninsula just north of the Bering Strait is covered by land fast ice. This ice hinders the movement of ice formed in eastern Chukchi Sea southward through the Bering Strait. The movement of ice along the Russian coast is relatively faster. Plotting of some of the ice floes indicated movement of ice in excess of 30 km in and south of the Bering Strait between 6 and 7 March, 1973. North of the Bering Strait the movement approached 18 km. The movement of ice observed during March 6 and 7 considerably altered the distribution and extent of polynya. These features when continually plotted should be of considerable aid in navigation of ice breakers. The movement of ice will also help delineate the migration and distribution of sea mammals.

Wright, F. F.↗

Tethered balloon-borne profile measurements of atmospheric properties in the cloudy atmospheric boundary layer over the Arctic sea ice during MOSAiC: Overview and first results

The tethered balloon-borne measurement system BELUGA (Balloon-bornE moduLar Utility for profilinG the lower Atmosphere) was deployed over the Arctic sea ice for 4 weeks in summer 2020 as part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition. Using BELUGA, vertical profiles of dynamic, thermodynamic, aerosol particle, cloud, radiation, and turbulence properties were measured from the ground up to a height of 1,500 m. BELUGA was operated during an anomalously warm period with frequent liquid water clouds and variable sea ice conditions. Three case studies of liquid water phase, single-layer clouds observed on 3 days (July 13, 23, and 24, 2020) are discussed to show the potential of the collected data set to comprehensively investigate cloud properties determining cloud evolution in the inner Arctic over sea ice. Simulated back-trajectories show that the observed clouds have evolved within 3 different air masses (“aged Arctic,” “advected over sea ice,” and “advected over open ocean”), which left distinct fingerprints in the cloud properties. Strong cloud top radiative cooling rates agree with simulated results of previous studies. The weak warming at cloud base is mostly driven by the vertical temperature profile between the surface and cloud base. In-cloud turbulence induced by the cloud top cooling was similar in strength compared to former studies. From the extent of the mixing layer, it is speculated that the overall cloud cooling is stronger and thus faster in the warm oceanic air mass. Larger aerosol particle number concentrations and larger sizes were observed in the air mass advected over the sea ice and in the air mass advected over the open ocean.

Arctic↗

Evaporation from the Southern Ocean Estimated on the Basis of AIRS Satellite Data

Evaporation plays an important role in the global water and energy cycles and, hence, in climate change. Evaporation over the Southern Ocean, where the Antarctic sea ice coverage has a large annual cycle, is poorly quantified. In this study, daily evaporation is estimated for the Southern Ocean with a sea‐ice‐specific algorithm, using surface temperature and air humidity from National Aeronautics and Space Administration's Atmospheric Infrared Sounder (AIRS), and wind speeds from Modern‐Era Retrospective Analysis for Research and Applications, Version 2 (MERRA‐2), reanalysis during 2003–2016. An uncertainty of 34% was found in the evaporation product. The results indicate that annual evaporation has considerable interannual and regional variability, but with a decreasing trend during the study period over most of the Southern Ocean. There are, however, areas where evaporation has increased, specifically in the Ross Sea in winter and summer, with smaller positive trends in spring and fall. Overall, the changes in the difference between the surface specific humidity and the air specific humidity, and to a much lesser extent in the wind speed, are the main drivers for the changes in evaporation throughout the year. During spring and fall months, changes to the sea ice cover, which alter the surface specific humidity, are the main drivers for the change, but in summer and winter the main driver is the air‐specific humidity. Air masses originating from the Antarctic continent (south) are associated with cold and dry conditions, which increase evaporation, whereas air masses from lower latitudes in the Southern Ocean (north) are associated with warm and moist conditions, decreasing evaporation. Comparisons with other reanalysis evaporation products produce similar trends, although annual averages differ.

Boisvert, Linette↗

Sensitivity of a thermodynamic sea ice model with leads to time step size

The characteristics of sea ice models, developed to study the physics of the growth and melt of ice at the ocean surface and the variations in ice extent, depend on the size of the time step. Thus, to study longer-term variations within a reasonable computer budget, a model with a scheme allowing longer time steps has been constructed. However, the results produced by the model can definitely depend on the length of the time step. The sensitivity of a model to time-step size can be reduced by appropriate approaches. The present investigation is concerned with experiments which use a formulation of a lead parameterization that can be considered as a first step toward the development of a lead parameterization suitable for a use in long-term climate studies.

Ledley, T. S.↗

Reducing Spread in Climate Model Projections of a September Ice-Free Arctic

This paper addresses the specter of a September ice-free Arctic in the 21st century using newly available simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We find that large spread in the projected timing of the September ice-free Arctic in 30 CMIP5 models is associated at least as much with different atmospheric model components as with initial conditions. Here we reduce the spread in the timing of an ice-free state using two different approaches for the 30 CMIP5 models: (i) model selection based on the ability to reproduce the observed sea ice climatology and variability since 1979 and (ii) constrained estimation based on the strong and persistent relationship between present and future sea ice conditions. Results from the two approaches show good agreement. Under a high-emission scenario both approaches project that September ice extent will drop to approx. 1.7 million sq km in the mid 2040s and reach the ice-free state (defined as 1 million sq km) in 2054-2058. Under a medium-mitigation scenario, both approaches project a decrease to approx.1.7 million sq km in the early 2060s, followed by a leveling off in the ice extent.

simulation↗

Dramatic Contrasts in Arctic vs Antarctic Sea Ice Trends in 3-D Visualizations and Compilations of Monthly Record Highs and Lows

New visualizations dramatically display the decreases in Arctic sea ice coverage over the years 1979-2015, apparent in each month of the year, with not a single record high in ice extents occurring in any month since 1986, a time period with 75 monthly record lows. Results are less dramatic in the Antarctic, but intriguingly in the opposite direction, with only 6 record lows since 1986 and 45 record highs.

SMMR↗

Extensive Liquid Meltwater Storage in Firn Within the Greenland Ice Sheet

The accelerating loss of mass from the Greenland ice sheet is a major contribution to current sea level rise. Increased melt water runoff is responsible for half of Greenlands mass loss increase. Surface melt has been increasing in extent and intensity, setting a record for surface area melt and runoff in 2012. The mechanisms and timescales involved in allowing surface melt water to reach the ocean where it can contribute to sea level rise are poorly understood. The potential capacity to store this water in liquid or frozen form in the firn (multi-year snow layer) is significant, and could delay its sea-level contribution. Here we describe direct observation of water within a perennial firn aquifer persisting throughout the winter in the southern ice sheet,where snow accumulation and melt rates are high. This represents a previously unknown storagemode for water within the ice sheet. Ice cores, groundairborne radar and a regional climatemodel are used to estimate aquifer area (70 plue or minus 10 x 10(exp 3) square kilometers ) and water table depth (5-50 m). The perennial firn aquifer represents a new glacier facies to be considered 29 in future ice sheet mass 30 and energy budget calculations.

meltwater↗

Energy Exascale Earth System Model v2.0.1

First patch release of v2.0.0 Changes since v2.0.0 [Important change] Fix ocean threading bug seen in debug cases on Chrysalis with Intel 20.0.4. Was introduced around time of v2.0.0 tag. Does not change v2.0.0 answers on Chrysalis because those didn't use threading or debugging. [EAM] Add semi-lagrangian tracer transport for theta-l (F90 and C++), add new algorithm for finding tropopause, add DSCREAM to allow v2 and SCREAM settings in same code such as adjust_ps [EAM-MMF] 60L default, allow C++ back end of RRTMGP (EAM too). [EAMxx] add nu-top functionality, fix forcing functor, add ttype9 and dcmip2012 tests 2.1, 2.2, and 3 HOMME: remove obsolete remap algs, option to specify dynamics alg indep of tracer, new sponge layer, add imex tests [ELM] Add topography-based subgrid (topounits), add FATES-ELM Nitro., Phos. and CH4 coupling, add land-use ts for NARRM, add lulc for SSP3 RCP7, Fix nutrient fertilization exp test and carbon isotope flux, Fix xactive lnd dry deposition, add lake water storage option, fix plant hydraulics 2d params, fix carbon budget calc, fix soil nutrient conc. bug, fix mosart dam bug, add test for new ELM, MOSART features, fix bug in O3 dry dep stomatal resistances, fix plant hydraulics restart BFB error, update mkmapdata. [MOSART] fix bug for reading the latitude from an unstructured input file, fix oversat in bubble test. [MPAS-ocean] Add CFC11, CFC12 tracers, add 2D spherical transport tests, fix del4 tracer mixing, add MARBL ocean tracer mixing, modify harmonic analysis options, add GPU port of vmix routines, fix calc of ML-averaged BV freq. [MPAS-seaice] Change extents of initial polar disks for oRRS18to6v3 grid, fix ice BGC with MARBL, update spherical test cases, fix DON coupling, Remove Cf from sea ice constants. [MPAS-landice] add CRYO1850-4xCO2 compset [CIME] add GCP, ANL GCE, Spock, Perlmutter, deprecate config_compilers.xml, fix and clean-up cmake macros, fix slurm bindings, refactor CIME internal testing, cleanup SCORPIO perf data, allow position independent compset naming, [also] update v2 benchmarking suite, extend e3sm_prod with throughput and memory checks

E3SM Project, DOE↗

Assessing Prior Emergent Constraints on Surface Albedo Feedback in CMIP6

An emergent constraint (EC) is a popular model evaluation technique, which offers the potential to reduce intermodel variability in projections of climate change. Two examples have previously been laid out for future surface albedo feedbacks (SAF) stemming from loss of Northern Hemisphere (NH) snow cover (SAF snow ) and sea ice (SAF ice ). These processes also have a modern-day analog that occurs each year as snow and sea ice retreat from their seasonal maxima, which is strongly correlated with future SAF across an ensemble of climate models. The newly released CMIP6 ensemble offers the chance to test prior constraints through out-of-sample verification, an important examination of EC robustness. Here, we show that the SAF snow EC is equally strong in CMIP6 as it was in past generations, while the SAF ice EC is also shown to exist in CMIP6, but with different, slightly weaker characteristics. We find that the CMIP6 mean NH SAF exhibits a global feedback of 0.25 ± 0.05 W m -2 K -1 , or ~61% of the total global albedo feedback, largely in line with prior generations despite its increased climate sensitivity. Additionally, the NH SAF can be broken down into similar contributions from snow and sea ice over the twenty-first century in CMIP6. Crucially, intermodel variability in seasonal SAF snow and SAF ice is largely unchanged from CMIP5 because of poor outlier simulations of snow cover, surface albedo, and sea ice thickness. These outliers act to mask the noted improvement from many models when it comes to SAF ice , and to a lesser extent SAF snow .

58 GEOSCIENCES↗