We present a new record of ice thickness change, reconstructed at nearly 100,000 sites on the Greenland Ice Sheet (GrIS) from laser altimetry measurements spanning the period 1993-2012, partitioned into changes due to surface mass balance (SMB) and ice dynamics. We estimate a mean annual GrIS mass loss of 243 ± 18 Gt·y The spatial pattern of dynamic mass loss changed over this time as dynamic thinning rapidly decreased in southeast Greenland but slowly increased in the southwest, north, and northeast regions. Most outlet glaciers have been thinning during the last two decades, interrupted by episodes of decreasing thinning or even thickening. Dynamics of the major outlet glaciers dominated the mass loss from larger drainage basins, and simultaneous changes over distances up to 500 km are detected, indicating climate control. However, the intricate spatiotemporal pattern of dynamic thickness change suggests that, regardless of the forcing responsible for initial glacier acceleration and thinning, the response of individual glaciers is modulated by local conditions. Recent projections of dynamic contributions from the entire GrIS to SLR have been based on the extrapolation of four major outlet glaciers. Considering the observed complexity, we question how well these four glaciers represent all of Greenland's outlet glaciers.Greenland Ice Sheet | laser altimetry | mass balance | ice dynamics
Geothermal heat flux (GHF) is a crucial boundary condition for making accurate predictions of ice sheet mass loss, yet it is poorly known in Greenland due to inaccessibility of the bedrock. Here we use a machine learning algorithm on a large collection of relevant geologic features and global GHF measurements and produce a GHF map of Greenland that we argue is within ∼15% accuracy. The main features of our predicted GHF map include a large region with high GHF in central-north Greenland surrounding the NorthGRIP ice core site, and hot spots in the Jakobshavn Isbrae catchment, upstream of Petermann Gletscher, and near the terminus of Nioghalvfjerdsfjorden glacier. Our model also captures the trajectory of Greenland movement over the Icelandic plume by predicting a stripe of elevated GHF in central-east Greenland. Finally, we show that our model can produce substantially more accurate predictions if additional measurements of GHF in Greenland are provided. Plain Language Summary The heat generated at the interior regions of Earth (geothermal heat flux, GHF) can be high enough to melt the bottom layers of ice sheets, decrease friction between ice and bedrock, and increase ice discharge to the ocean. This heat, however, cannot be directly measured in ice sheets because the bedrock is inaccessible. Here we present a novel approach to estimate this heat. We combine all the available geologic, tectonic, and GHF data that are available on all continents. We then establish a complex relationship between GHF and all the geologic-tectonic features using machine learning techniques and then predict the GHF for the Greenland Ice Sheet. We utilize all information from available ice cores and bedrock boreholes to improve the GHF prediction in Greenland. Thus, the new GHF map honors tectonic settings, regional geology, and measurements from ice cores and can be used as an important input parameter to numerical ice sheet models that aim at lowering the uncertainties of future sea level rise predictions. This study derives a new map of GHF for the GrIS using statistical relationships between global heat flux observations and the combined influence of local geology and regional tectonic setting. Compilations of global RESEARCH LETTER 10.1002/2017GL075661 Key Points: • A new geothermal heat flux map of Greenland is obtained within ∼15% accuracy using machine learning techniques • The new map honors regional geology, tectonic settings, and ice core measurements • Pockets of high heat flux are predicted in central-north Greenland and upstream of several fast-flowing outlet glaciers
The thermal state at the bed of a large ice sheet is a critical boundary condition governing its future evolution. Radar surveys provide an opportunity for direct but remote observation of the ice-sheet bed, and therefore offer a means of constraining numerical ice-sheet models at the ice–bed interface. Here we have processed results of radar surveys of the Greenland Ice Sheet undertaken by the Program for Arctic Regional Climate Assessment (PARCA) between 1999 and 2003, to explore this opportunity. We consider the robustness of the measurements in the context of uncertain dielectric losses in the ice sheet, concluding that the observed radar signal characteristics reflect the character of the bed itself rather than that of uncertain englacial absorption. However, the identification of thaw is restricted to areas where subglacial water has sufficient depth to influence the radar reflection. We derive a map of inferred areas of subglacial thaw, and compare our results with other studies predicting regions with temperate bed. We show that in many areas the radar inferences of ponded water lie within areas predicted to be thawed by modelling and radiostratigraphy. There is clear disagreement in certain areas, suggesting the presence of high geothermal flux anomalies.
Icebergs represent nearly half of the mass loss from the Greenland Ice Sheet and provide a distributed source of freshwater along fjords which can alter fjord circulation, nutrient levels, and ultimately the Meridional Overturning Circulation. Here we present analyses of high resolution optical satellite imagery using convolutional neural networks to accurately delineate iceberg edges in two East Greenland fjords. We find that a significant portion of icebergs in fjords are comprised of small icebergs that were not detected in previously-available coarser resolution satellite images. We show that the preponderance of small icebergs results in high freshwater delivery, as well as a short life span of icebergs in fjords. We conclude that an inability to identify small icebergs leads to inaccurate frequency-size distribution of icebergs in Greenland fjords, an underestimation of iceberg area (specifically for small icebergs), and an overestimation of iceberg life span.
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