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At least 469 records · Page 26

Potential Basin-Scale Estimates of Arctic Snow Depth with Sea Ice Freeboards from CryoSat-2 and ICESat-2: An Exploratory Analysis

The potential of deriving snow depth estimates using differences in freeboard heights from CryoSat-2 (CS-2) and ICESat-2 (IS-2) is examined. In our analysis, we use lidar freeboard from the Airborne Topographic Mapper (ATM) on Operation IceBridge (OIB) as proxy of IS-2 total (snow plus ice) freeboard. Snow depths are estimates from the OIB snow radar. Differences in height between the total (ATM) and ice (CS-2) freeboards are related to snow depth by the refractive index of the snow layer, which is dependent on snow density. For two years (2014 and 2015), regression of the ATM and CS-2 freeboard differences against OIB snow depth gives correlations of approximately 0.80, estimated eta (sub s) of 1.21, and standard errors of 8 centimeters. The resulting refractive index, eta (sub s), can be compared to that expected of the Arctic snow cover in early spring (1.25 plus or minus 0.05). The expected biases and variability in the regression analysis are discussed. Results suggest that snow depth can be estimated from the freeboard differences. The benefits of adjusting the orbit of CS-2 for providing more optimized overlaps between IS-2 and CS-2 are considered.

Sea ice↗

Rising Oceans Guaranteed: Arctic Land Ice Loss and Sea Level Rise

This paper reviews sea level contributions from land ice across the Arctic, including Greenland. We summarize ice loss measurement methods, ice loss mechanisms, and recent observations and projections, and highlight research advances over the last 3-5 years and remaining scientific challenges.

glaciers↗

Arctic and Boreal Model Development in GMAO

Ongoing research in the GMAO seeks to improve the representation atmospheric, land, and ocean processes in the boreal Arctic and other polar regions. This talk touches on a range of topics, including improvements to sea ice and land ice representation in our subseasonal-to-seasonal prediction system and the initiation of a new collaborative effort with the Cryospheric Sciences Laboratory to develop a high resolution, polar-focused atmospheric reanalysis.

Arctic Boreal↗

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

We present a first examination of Arctic sea ice snow depth estimates from differencing satellite lidar (ICESat‐2) and radar (CryoSat‐2) freeboards. These estimates cover the period between 14 October 2018 and the end of April 2019. Snow depth is related to freeboard differences by the refractive index/bulk density of the snow layer—the only free parameter in the approach. Area‐averaged snow depth ranges from 9 cm (on first‐year ice: 5 cm, multiyear ice: 14 cm) in late October to 19 cm (first‐year ice: 17 cm, multiyear ice: 27 cm) in April; on average, this snow is thinner over FYI. Spatial patterns and gradients of snow depth estimates compare well with reconstructions using snowfall from ERA‐Interim and ERA5, although snowfall from ERA5 is systematically higher. For all months, the results suggest that ~50% of the total freeboard is comprised of snow. Retrievals are within a few centimeters of snow depth data acquired by Operation IceBridge in April 2019. Sources of uncertainties associated with this freeboard‐differencing approach are discussed. Further, sea ice thicknesses calculated using the retrieved snow depth and a modified climatology are contrasted. Comparatively, the snow depth and calculated ice thickness using a modified climatology are higher by ~5 cm and 0.33 m, although these differences are not uniform throughout the season. Snow accumulation was slower between October and December but increased between December and January, unlike the modified climatology, which exhibited a monotonic accumulation for all months. Future opportunities for assessment and improvement of these estimates are discussed.

Arctic Ocean↗

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↗

Indian Ocean warming as key driver of long-term positive trend of Arctic Oscillation

Arctic oscillation (AO), which is the most dominant atmospheric variability in the Northern Hemisphere (NH) during the boreal winter, significantly affects the weather and climate at mid-to-high latitudes in the NH. Although a climate community has focused on a negative trend of AO in recent decades, the significant positive trend of AO over the last 60 years has not yet been thoroughly discussed. By analyzing reanalysis and Atmospheric Model Inter-comparison Project (AMIP) datasets with novel pacemaker experiments, we found that sea surface temperature warming in the Indian Ocean is conducive to the positive trend of AO from the late 1950s. The momentum flux convergence by stationary waves due to the Indian Ocean warming plays an important role in the positive trend of AO, which is characterized by a poleward shift of zonal-mean zonal winds. In addition, the reduced upward propagating wave activity flux over the North Pacific due to Indian Ocean warming also plays a role to strengthen the polar vortex, subsequently, it contributes to the positive trend of AO. Our results imply that the respective warming trend of tropical ocean basins including Indian Ocean, which is either anthropogenic forcing or natural variability or their combined effect, should be considered to correctly project the future AO’s trend.

Indian Ocean↗

Disturbances in North American Boreal Forest and Arctic Tundra: Impacts, Interactions, and Responses

Ecosystems in the North American Arctic-Boreal Zone (ABZ) experience a diverse set of disturbances associated with wildfire, permafrost dynamics, geomorphic processes, insect outbreaks and pathogens, extreme weather events, and human activity. Climate warming in the ABZ is occurring at over twice the rate of the global average, and as a result the extent, frequency, and severity of these disturbances are increasing rapidly. Disturbances in the ABZ span a wide gradient of spatiotemporal scales and have varying impacts on ecosystem properties and function. However, many ABZ disturbances are relatively understudied and have different sensitivities to climate and trajectories of recovery, resulting in considerable uncertainty in the impacts of climate warming and human land use on ABZ vegetation dynamics and in the interactions between disturbance types. Here we review the current knowledge of ABZ disturbances and their precursors, ecosystem impacts, temporal frequencies, spatial extents, and severity. We also summarize current knowledge of interactions and feedbacks among ABZ disturbances and characterize typical trajectories of vegetation loss and recovery in response to ecosystem disturbance using satellite time-series. We conclude with a summary of critical data and knowledge gaps and identify priorities for future study.

high-latitude↗

Exploring the Arctic Ocean With Sailing Robots

The Arctic Ocean is changing rapidly as the planet warms, but studying it presents challenges: it’s a remote area that is often covered by sea ice. As CHELLE GENTEMANN, MARISOL GARCÍA-REYES and JORGE VAZQUEZ-CUERVO explain, using autonomous solar-powered sailing robots is a safe, reliable and climate-friendly way to collect the data we need.

Arctic↗

The Transformation and Export of Organic Carbon Across an Arctic River-Delta-Ocean Continuum

The Arctic Ocean is surrounded by land that feeds highly seasonal rivers with water enriched in high concentrations of dissolved and particulate organic carbon (DOC and POC). Explicit estimates of the flux of organic carbon across the land-ocean interface are difficult to quantify and many interdependent processes makes source attribution difficult. A high-resolution 3-D biogeochemical model was built for the lower Yukon River and coastal ocean to estimate biogeochemical cycling across the land-ocean continuum. The model solves for complex reactions related to organic carbon transformation, including mechanistic photodegradation and multi-reactivity microbial processing, DOC to POC flocculation, and phytoplankton dynamics. The baseline DOC and POC flux out of the delta from April to September 2019, was 977 and 536 Gg C (~80% of the annual total), but only 50% of the DOC and 25% of the POC exited the plume across the 10 m isobath. Microbial breakdown of DOC accounted for a net loss of 168 Gg C (17% of delta export) within the plume and photodegradation accounted for a net loss of 46.6 Gg C DOC (5% of delta export) in 2019. Flocculation decreased the total organic carbon flux by only 6.4 Gg C (~1%), while POC sinking accounted for 63.3 Gg C (10%) settling in the plume. The loss of chromophoric dissolved organic matter (CDOM) due to photodegradation increased the light available for phytoplankton growth throughout the coastal ocean, demonstrating the secondary effects that organic carbon reactions can have on biological processes and the net coastal carbon flux.

Land-Ocean Continuum↗

Greenland and Canadian Arctic Ice Temperature Profiles Database

Here, we present a compilation of 95 ice temperature profiles from 85 boreholes from the Greenland ice sheet and peripheral ice caps, as well as local ice caps in the Canadian Arctic. Profiles from only 31 boreholes (36 %) were previously available in open-access data repositories. The remaining 54 borehole profiles (64 %) are being made digitally available here for the first time. These newly available profiles, which are associated with pre-2010 boreholes, have been submitted by community members or digitized from published graphics and/or data tables. All 95 profiles are now made available in both absolute (meters) and normalized (0 to 1 ice thickness) depth scales and are accompanied by extensive metadata. These metadata include a transparent description of data provenance. The ice temperature profiles span 70 years, with the earliest profile being from 1950 at Camp VI, West Greenland. To highlight the value of this database in evaluating ice flow simulations, we compare the ice temperature profiles from the Greenland ice sheet with an ice flow simulation by the Parallel Ice Sheet Model (PISM). We find a cold bias in modeled near-surface ice temperatures within the ablation area, a warm bias in modeled basal ice temperatures at inland cold-bedded sites, and an apparent underestimation of deformational heating in high-strain settings. These biases provide process level insight on simulated ice temperatures.

Greenland↗

Studies on Arctic survival.

Aircrew Arctic survival situation simulation experiments with survivors staying close to aircraft and walking across difficult terrain from emergency location

Aksnes, E. G.↗

Aircraft measurements of microwave emission from Arctic Sea Ice

Measurements of the microwave emission from Arctic Sea ice were made with aircraft at 8 wavelengths ranging from 0.510 cm to 2.81 cm. The expected contrast in emissivities between ice and water was observed at all wavelengths. Distributions of sea ice and open water were mapped from altitudes up to 11 km in the presence of dense cloud cover. Different forms of ice also exhibited strong contrasts in emissivity. Emissivity differences of up to 0.2 were observed between two types of ice at 0.811 cm wavelength. The higher emissivity ice type is tentatively identified as having been formed more recently than the lower emissivity ice.

Wilheit, T. T.↗

Remote sensing in marine geology: Arctic to Caribbean

The applications of remote sensing to coastal dynamics of both nearshore and offshore waters are discussed. Results of aerial photographic analysis of four areas are presented. The study areas include the Arctic (Beaufort Sea), the Pacific Northwest, San Francisco Bay, and St. John, Virgin Islands (Project Tektite).

Carlson, P. R.↗