scholarly journals Periglacial Lake Origin Influences the Likelihood of Lake Drainage in Northern Alaska

2021 ◽  
Vol 13 (5) ◽  
pp. 852
Author(s):  
Mark J. Lara ◽  
Melissa L. Chipman
Keyword(s):  
Spatial Distribution ◽  
Landsat Imagery ◽  
Morphological Properties ◽  
The Arctic ◽  
Subarctic Lakes ◽  
Geological Processes ◽  
Lake Formation ◽  
Lake Drainage ◽  
Elevation Model ◽  
Northern Alaska

Nearly 25% of all lakes on earth are located at high latitudes. These lakes are formed by a combination of thermokarst, glacial, and geological processes. Evidence suggests that the origin of periglacial lake formation may be an important factor controlling the likelihood of lakes to drain. However, geospatial data regarding the spatial distribution of these dominant Arctic and subarctic lakes are limited or do not exist. Here, we use lake-specific morphological properties using the Arctic Digital Elevation Model (DEM) and Landsat imagery to develop a Thermokarst lake Settlement Index (TSI), which was used in combination with available geospatial datasets of glacier history and yedoma permafrost extent to classify Arctic and subarctic lakes into Thermokarst (non-yedoma), Yedoma, Glacial, and Maar lakes, respectively. This lake origin dataset was used to evaluate the influence of lake origin on drainage between 1985 and 2019 in northern Alaska. The lake origin map and lake drainage datasets were synthesized using five-year seamless Landsat ETM+ and OLI image composites. Nearly 35,000 lakes and their properties were characterized from Landsat mosaics using an object-based image analysis. Results indicate that the pattern of lake drainage varied by lake origin, and the proportion of lakes that completely drained (i.e., >60% area loss) between 1985 and 2019 in Thermokarst (non-yedoma), Yedoma, Glacial, and Maar lakes were 12.1, 9.5, 8.7, and 0.0%, respectively. The lakes most vulnerable to draining were small thermokarst (non-yedoma) lakes (12.7%) and large yedoma lakes (12.5%), while the most resilient were large and medium-sized glacial lakes (4.9 and 4.1%) and Maar lakes (0.0%). This analysis provides a simple remote sensing approach to estimate the spatial distribution of dominant lake origins across variable physiography and surficial geology, useful for discriminating between vulnerable versus resilient Arctic and subarctic lakes that are likely to change in warmer and wetter climates.

scholarly journals A new bedrock and surface elevation dataset for modelling the Greenland ice sheet

2003 ◽  
Vol 37 ◽  
pp. 351-356 ◽  
Author(s):  
Jonathan L. Bamber ◽  
Duncan J. Baldwin ◽  
S. Prasad Gogineni
Keyword(s):  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Detailed Comparison ◽  
Radar Data ◽  
The Arctic ◽  
Small Scale ◽  
Surface Model ◽  
Rock Outcrops ◽  
Bed Topography ◽  
Elevation Model

AbstractA new digital elevation model of the surface of the Greenland ice sheet and surrounding rock outcrops has been produced from a comprehensive suite of satellite and airborne remote-sensing and cartographic datasets. The surface model has been regridded to a resolution of 5 km, and combined with a new ice-thickness grid derived from ice-penetrating radar data collected in the 1970s and 1990s. A further dataset, the International Bathymetric Chart of the Arctic Ocean, was used to extend the bed elevations to include the continental shelf. The new bed topography was compared with a previous version used for ice-sheet modelling. Near the margins of the ice sheet and, in particular, in the vicinity of small-scale features associated with outlet glaciers and rapid ice motion, significant differences were noted. This was highlighted by a detailed comparison of the bed topography around the northeast Greenland ice stream.

scholarly journals Recent Sea Ice Decline Did Not Significantly Increase the Total Liquid Freshwater Content of the Arctic Ocean

2018 ◽  
Vol 32 (1) ◽  
pp. 15-32 ◽  
Author(s):  
Qiang Wang ◽  
Claudia Wekerle ◽  
Sergey Danilov ◽  
Dmitry Sidorenko ◽  
Nikolay Koldunov ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Ocean Circulation ◽  
General Circulation ◽  
The Arctic ◽  
Sea Ice Decline ◽  
The Arctic Ocean ◽  
Eurasian Basin ◽  
The Impact

Abstract The freshwater stored in the Arctic Ocean is an important component of the global climate system. Currently the Arctic liquid freshwater content (FWC) has reached a record high since the beginning of the last century. In this study we use numerical simulations to investigate the impact of sea ice decline on the Arctic liquid FWC and its spatial distribution. The global unstructured-mesh ocean general circulation model Finite Element Sea Ice–Ocean Model (FESOM) with 4.5-km horizontal resolution in the Arctic region is applied. The simulations show that sea ice decline increases the FWC by freshening the ocean through sea ice meltwater and modifies upper ocean circulation at the same time. The two effects together significantly increase the freshwater stored in the Amerasian basin and reduce its amount in the Eurasian basin. The salinification of the upper Eurasian basin is mainly caused by the reduction in the proportion of Pacific Water and the increase in that of Atlantic Water (AW). Consequently, the sea ice decline did not significantly contribute to the observed rapid increase in the Arctic total liquid FWC. However, the changes in the Arctic freshwater spatial distribution indicate that the influence of sea ice decline on the ocean environment is remarkable. Sea ice decline increases the amount of Barents Sea branch AW in the upper Arctic Ocean, thus reducing its supply to the deeper Arctic layers. This study suggests that all the dynamical processes sensitive to sea ice decline should be taken into account when understanding and predicting Arctic changes.

Danian Mollusks from the Prince Creek Formation, Northern Alaska, and Implications for Arctic Ocean Paleogeography

1993 ◽  
Vol 67 (S35) ◽  
pp. 1-35 ◽  
Author(s):  
Louie Marincovich
Keyword(s):  
Arctic Ocean ◽  
World Ocean ◽  
Ocean Basin ◽  
The Arctic ◽  
The North ◽  
The World ◽  
The Arctic Ocean ◽  
Molluscan Fauna ◽  
Endemic Genera ◽  
Northern Alaska

The marine molluscan fauna of the Prince Creek Formation near Ocean Point, northern Alaska, is of Danian age. It is the only diverse and abundant Danian molluscan fauna known from the Arctic Ocean realm, and is the first evidence for an indigenous Paleocene shallow-water biota within a discrete Arctic Ocean Basin faunal province.A high percentage of endemic species, and two endemic genera, emphasize the degree to which the Arctic Ocean was geographically isolated from the world ocean during the earliest Tertiary. Many of the well-preserved Ocean Point mollusks, however, also occur in Danian faunas of the North American Western Interior, the Canadian Arctic Islands, Svalbard, and northwestern Europe, and are the basis for relating this Arctic Ocean fauna to that of the Danian world ocean.The Arctic Ocean was a Danian refugium for some genera that became extinct elsewhere during the Jurassic and Cretaceous. At the same time, this nearly landlocked ocean fostered the evolution of new taxa that later in the Paleogene migrated into the world ocean by way of the northeastern Atlantic. The first Cenozoic occurrences are reported for the bivalves Integricardium (Integricardium), Oxytoma (Hypoxytoma), Placunopsis, Tancredia (Tancredia), and Tellinimera, and the oldest Cenozoic records given for the bivalves Gari (Garum), Neilo, and Yoldia (Cnesterium). Among the 25 species in the molluscan fauna are four new gastropod species, Amauropsis fetteri, Ellipsoscapha sohli, Mathilda (Fimbriatella) amundseni, and Polinices (Euspira) repenningi, two new bivalve genera, Arcticlam and Mytilon, and 15 new bivalve species, Arcticlam nanseni, Corbula (Caryocorbula) betsyae, Crenella kannoi, Cyrtodaria katieae, Gari (Garum) brouwersae, Integricardium (Integricardium) keenae, Mytilon theresae, Neilo gryci, Nucula (Nucula) micheleae, Nuculana (Jupiteria) moriyai, Oxytoma (Hypoxytoma) hargrovei, Placunopsis rothi, Tancredia (Tancredia) slavichi, Tellinimera kauffmani, and Yoldia (Cnesterium) gladenkovi.

Expansion of the Trade in Northern Alaska and Western Arctic Canada

2018 ◽  
Author(s):  
John R. Bockstoce
Keyword(s):  
San Francisco ◽  
Fur Trade ◽  
The Arctic ◽  
Arctic Canada ◽  
Trading Company ◽  
Whaling Industry ◽  
Western Arctic ◽  
Northern Alaska

This chapter focuses on the development and advance of the arctic fur trade to the year 1914: the decline of the shore whaling industry and the rise of the market for white fox furs; the beginning of the dispersal of trapping families along the coast; the importance of the Cape Smythe Whaling and Trading Company at Barrow, Alaska; and the activities of H. Liebes and Company, furriers of San Francisco.

scholarly journals Dynamical Downscaling Data for Studying Climatic Impacts on Hydrology, Permafrost, and Ecosystems in Arctic Alaska

2016 ◽  
Author(s):  
Lei Cai ◽  
Vladimir A. Alexeev ◽  
Christopher D. Arp ◽  
Benjamin M. Jones ◽  
Anna Liljedahl ◽  
...  
Keyword(s):  
Observational Data ◽  
Dynamical Downscaling ◽  
Dew Point ◽  
Climatic Variables ◽  
The Arctic ◽  
Linear Scaling ◽  
Permafrost Degradation ◽  
Near Surface ◽  
Temperature Bias ◽  
Northern Alaska

Abstract. Climatic changes are most pronounced in northern high latitude regions. Yet, there is a paucity of observational data, both spatially and temporally, such that regional-scale dynamics are not fully captured, limiting our ability to make reliable projections. In this study, a group of dynamical downscaling products were created for the period 1950 to 2100 to better understand climate change and its impacts on hydrology, permafrost, and ecosystems at a resolution suitable for northern Alaska. An ERA-interim reanalysis dataset and the Community Earth System Model (CESM) served as the forcing mechanisms in this dynamical downscaling framework, and the Weather Research & Forecast (WRF) model, embedded with an optimization for the Arctic (Polar WRF), served as the Regional Climate Model (RCM). This downscaled output consists of multiple climatic variables (precipitation, temperature, wind speed, dew point temperature, and surface air pressure) for a 10 km grid spacing at three-hour intervals. The modeling products were evaluated and calibrated using a bias-correction approach. The ERA-interim forced WRF (ERA-WRF) produced reasonable climatic variables as a result, yielding a more closely correlated temperature field than precipitation field when long-term monthly climatology was compared with its forcing and observational data. A linear scaling method then further corrected the bias, based on ERA-interim monthly climatology, and bias-corrected ERA-WRF fields were applied as a reference for calibration of both the historical and the projected CESM forced WRF (CESM-WRF) products. Biases, such as, a cold temperature bias during summer and a warm temperature bias during winter as well as a wet bias for annual precipitation that CESM holds over northern Alaska persisted in CESM-WRF runs. The linear scaling of CESM-WRF eventually produced high-resolution downscaling products for the Alaskan North Slope for hydrological and ecological research, together with the calibrated ERA-WRF run, and its capability extends far beyond that. Other climatic research has been proposed, including exploration of historical and projected climatic extreme events and their possible connections to low-frequency sea-atmospheric oscillations, as well as near-surface permafrost degradation and ice regime shifts of lakes. These dynamically downscaled, bias corrected climatic datasets provide improved spatial and temporal resolution data necessary for ongoing modeling efforts in northern Alaska focused on reconstructing and projecting hydrologic changes, ecosystem processes and responses, and permafrost thermal regimes. The dynamical downscaling methods presented in this study can also be used to create more suitable model input datasets for other sub-regions of the Arctic. Supplementary data are available at https://doi.org/10.1594/PANGAEA.863625.

Estimating the ice thickness of the Müller Ice Cap using an inversion of the shallow ice approximation

2021 ◽  
Author(s):  
Ann-Sofie Priergaard Zinck ◽  
Aslak Grinsted
Keyword(s):  
Remote Sensing Data ◽  
The Arctic ◽  
Ice Thickness ◽  
Potential Contribution ◽  
Mean Squared Errors ◽  
Ice Caps ◽  
Ice Cap ◽  
Regression Parameters ◽  
Digital Elevation ◽  
Elevation Model

<p><span>The ice thickness of the Müller Ice Cap, Arctic Canada, is estimated using regression parameters obtained from an inversion of the shallow ice approximation by the use of a single Operation IceBridge flight line in combination with the glacier outline, surface slope, and elevation. The model is compared with an iterative inverse method of estimating the bedrock topography using PISM as a forward model. In both models the surface elevation is given by the Arctic Digital Elevation Model. The root mean squared errors of the ice thickness on the ice cap is 131 m and 139 m for the shallow ice inversion and the PISM model, respectively. Including the outlet glaciers increases the root mean squared errors to 136 m and 396 m, respectively. </span></p><p><span>The simplicity of the shallow ice inversion model, combined with the good results and the fact that only remote sensing data is needed, means that there is a possibility of applying this model in a global glacier thickness estimate by using the Randolph Glacier Inventory. Most global glacier estimates only provide the volume and not the ice thickness of the glaciers. Hence, global ice thickness models is of great importance in quantifying the potential contribution of sea level rise from the glaciers and ice caps around the globe. </span></p>

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