scholarly journals Central tropical Pacific convection drives extreme high temperatures and surface melt on the Larsen ice shelf

2021 ◽  
Author(s):  
Kyle Clem ◽  
Deniz Bozkurt ◽  
Daemon Kennett ◽  
John King ◽  
John Turner
Keyword(s):  
High Temperatures ◽  
Deep Convection ◽  
Extreme Temperature ◽  
Drake Passage ◽  
Tropical Pacific ◽  
Ice Shelf ◽  
Surface Mass ◽  
Surface Warming ◽  
Surface Melt ◽  
Larsen Ice Shelf

Abstract The northern parts of the Larsen ice shelf, eastern Antarctic Peninsula (AP) have experienced dramatic break-up since the early 1990s as a result of strong summertime surface melt, which has been linked to stronger circumpolar westerly winds. Here we show extreme summertime surface melt and high temperatures over the eastern AP and Larsen C ice shelf occur because of enhanced deep convection in the central tropical Pacific, which produces cyclonic conditions across the middle and high-latitude South Pacific, and a strong high pressure anomaly over Drake Passage. Together these transport extreme heat and moisture from low latitudes to the AP, at times in the form of "atmospheric rivers", producing strong surface warming and melt on the Larsen ice shelf by the Foehn effect. Therefore, variability in central tropical Pacific convection is crucial for interpreting past and projecting future AP surface mass balance and extreme temperature events.

Estimating Surface Melt on the Larsen Ice Shelf Using a Deep Neural Network: Opportunities and Challenges

2021 ◽  
Author(s):  
Zhongyang Hu ◽  
Peter Kuipers Munneke ◽  
Stef Lhermitte ◽  
Maaike Izeboud ◽  
Michiel van den Broeke
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Deep Neural Network ◽  
Climate Model ◽  
Climate Modeling ◽  
Coefficient Of Determination ◽  
Ice Shelf ◽  
Heterogeneous Terrain ◽  
Surface Melt ◽  
Larsen Ice Shelf

<p>Presently, surface melt over Antarctica is estimated using climate modeling or remote sensing. However, accurately estimating surface melt remains challenging. Both climate modeling and remote sensing have limitations, particularly in the most crucial areas with intense surface melt.  The motivation of our study is to investigate the opportunities and challenges in improving the accuracy of surface melt estimation using a deep neural network. The trained deep neural network uses meteorological observations from automatic weather stations (AWS) and surface albedo observations from satellite imagery to improve surface melt simulations from the regional atmospheric climate model version 2.3p2 (RACMO2). Based on observations from three AWS at the Larsen B and C Ice Shelves, cross-validation shows a high accuracy (root mean square error = 0.898 mm.w.e.d<sup>−1</sup>, mean absolute error = 0.429 mm.w.e.d<sup>−1</sup>, and coefficient of determination = 0.958). The deep neural network also outperforms conventional machine learning models (e.g., random forest regression, XGBoost) and a shallow neural network. To compute surface melt for the entire Larsen Ice Shelf, the deep neural network is applied to RACMO2 simulations. The resulting, corrected surface melt shows a better correlation with the AWS observations in AWS 14 and 17, but not in AWS 18. Also, the spatial pattern of the surface melt is improved compared to the original RACMO2 simulation. A possible explanation for the mismatch at AWS 18 is its complex geophysical setting. Even though our study shows an opportunity to improve surface melt simulations using a deep neural network, further study is needed to refine the method, especially for complicated, heterogeneous terrain.</p>

scholarly journals Antarctic Atmospheric River Climatology and Impacts

2020 ◽  
Author(s):  
Jonathan Wille ◽  
Vincent Favier ◽  
Irina V. Gorodetskaya ◽  
Cécile Agosta ◽  
Jai Chowdhry Beeman ◽  
...  
Keyword(s):  
Mass Balance ◽  
Surface Mass Balance ◽  
Ice Shelf ◽  
Surface Mass ◽  
Atmospheric Rivers ◽  
Atmospheric River ◽  
Dronning Maud Land ◽  
Antarctic Continent ◽  
Surface Melt ◽  
The Antarctic

<p>Atmospheric rivers, broadly defined as narrow yet long bands of strong horizontal vapor transport typically imbedded in a low level jet ahead of a cold front of an extratropical cyclone, provide a sub-tropical connection to the Antarctic continent and are observed to significantly impact the affected region’s surface mass balance over short, extreme events. When an atmospheric river makes landfall on the Antarctic continent, their signature is clearly observed in increased downward longwave radiation, cloud liquid water content, surface temperature, snowfall, surface melt, and moisture transport.</p><p>Using an atmospheric river detection algorithm designed for Antarctica and regional climate simulations from MAR, we created a climatology of atmospheric river occurrence and their associated impacts on surface melt and snowfall. Despite their rarity of occurrence over Antarctica (maximum frequency of ~1.5% over a given point), they have produced significant impacts on melting and snowfall processes. From 1979-2017, atmospheric rivers landfalls and their associated radiative flux anomalies and foehn winds accounted for around 40% of the total summer surface melt on the Ross Ice Shelf (approaching 100% at higher elevations in Marie Byrd Land) and 40-80% of total winter surface melt on the ice shelves along the Antarctic Peninsula. On the other side of the continent in East Antarctica, atmospheric rivers have a greater influence on annual snowfall variability. There atmospheric rivers are responsible for 20-40% of annual snowfall with localized higher percentages across Dronning Maud Land, Amery Ice Shelf, and Wilkes Land.</p><p>Atmospheric river landfalls occur within a highly amplified polar jet pattern and often are found in the entrance region of a blocking ridge. Therefore, atmospheric river variability is connected with atmospheric blocking variability over the Southern Ocean. There has been a significant increase in atmospheric river activity over the Amundsen-Bellingshausen sea and coastline and into Dronning Maud Land region from 1980-2018. Meanwhile, there is a significant decreasing trend in the region surrounding Law Dome. Our results suggest that atmospheric rivers play a significant role in the Antarctic surface mass balance, and that any future changes in atmospheric blocking or tropical-polar teleconnections may have significant impacts on future surface mass balance projections.</p>

scholarly journals Improving Surface Melt Estimation over Antarctica Using Deep Learning: A Proof-of-Concept over the Larsen Ice Shelf

2021 ◽  
Author(s):  
Zhongyang Hu ◽  
Peter Kuipers Munneke ◽  
Stef Lhermitte ◽  
Maaike Izeboud ◽  
Michiel van den Broeke
Keyword(s):  
Deep Learning ◽  
Climate Model ◽  
High Surface ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Climate Modelling ◽  
Ice Shelf ◽  
Surface Melt ◽  
Mlp Model ◽  
Larsen Ice Shelf

Abstract. Accurately estimating surface melt volume of the Antarctic Ice Sheet is challenging, and has hitherto relied on climate modelling, or on observations from satellite remote sensing. Each of these methods has its limitations, especially in regions with high surface melt. This study aims to demonstrate the potential of improving surface melt simulations by deploying a deep learning model. A deep-learning-based framework has been developed to correct surface melt from the regional atmospheric climate model version 2.3p2 (RACMO2), using meteorological observations from automatic weather stations (AWSs), and surface albedo from satellite imagery. The framework includes three steps: (1) training a deep multilayer perceptron (MLP) model using AWS observations; (2) correcting moderate resolution imaging spectroradiometer (MODIS) albedo observations, and (3) using these two to correct the RACMO2 surface melt simulations. Using observations from three AWSs at the Larsen B and C Ice Shelves, Antarctica, cross-validation shows a high accuracy (root mean square error = 0.95 mm w.e. per day, mean absolute error = 0.42 mm w.e. per day, and coefficient of determination = 0.95). Moreover, the deep MLP model outperforms conventional machine learning models (e.g., random forest regression, XGBoost) and a shallow MLP model. When applying the trained deep MLP model over the entire Larsen Ice Shelf, the resulting, corrected RACMO2 surface melt shows a better correlation with the AWS observations for two out of three AWSs. However, for one location (AWS 18) the deep MLP model does not show improved agreement with AWS observations, likely due to the heterogeneous drivers of melt within the corresponding coarse resolution model pixels. Our study demonstrates the opportunity to improve surface melt simulations using deep learning combined with satellite albedo observations. On the other hand, more work is required to refine the method, especially for complicated and heterogeneous terrains.

scholarly journals Improving surface melt estimation over the Antarctic Ice Sheet using deep learning: a proof of concept over the Larsen Ice Shelf

2021 ◽  
Vol 15 (12) ◽  
pp. 5639-5658
Author(s):  
Zhongyang Hu ◽  
Peter Kuipers Munneke ◽  
Stef Lhermitte ◽  
Maaike Izeboud ◽  
Michiel van den Broeke
Keyword(s):  
Deep Learning ◽  
Climate Model ◽  
Ice Sheet ◽  
Katabatic Wind ◽  
Ice Shelf ◽  
Antarctic Ice Sheet ◽  
Surface Melt ◽  
Mlp Model ◽  
The Antarctic ◽  
Larsen Ice Shelf

Abstract. Accurately estimating the surface melt volume of the Antarctic Ice Sheet is challenging and has hitherto relied on climate modeling or observations from satellite remote sensing. Each of these methods has its limitations, especially in regions with high surface melt. This study aims to demonstrate the potential of improving surface melt simulations with a regional climate model by deploying a deep learning model. A deep-learning-based framework has been developed to correct surface melt from the regional atmospheric climate model version 2.3p2 (RACMO2), using meteorological observations from automatic weather stations (AWSs) and surface albedo from satellite imagery. The framework includes three steps: (1) training a deep multilayer perceptron (MLP) model using AWS observations, (2) correcting Moderate Resolution Imaging Spectroradiometer (MODIS) albedo observations, and (3) using these two to correct the RACMO2 surface melt simulations. Using observations from three AWSs at the Larsen B and C ice shelves, Antarctica, cross-validation shows a high accuracy (root-mean-square error of 0.95 mm w.e. d−1, mean absolute error of 0.42 mm w.e. d−1, and a coefficient of determination of 0.95). Moreover, the deep MLP model outperforms conventional machine learning models and a shallow MLP model. When applying the trained deep MLP model over the entire Larsen Ice Shelf, the resulting corrected RACMO2 surface melt shows a better correlation with the AWS observations for two out of three AWSs. However, for one location (AWS 18), the deep MLP model does not show improved agreement with AWS observations; this is likely because surface melt is largely driven by factors (e.g., air temperature, topography, katabatic wind) other than albedo within the corresponding coarse-resolution model pixels. Our study demonstrates the opportunity to improve surface melt simulations using deep learning combined with satellite albedo observations. However, more work is required to refine the method, especially for complicated and heterogeneous terrains.

scholarly journals Climatically induced retreat and collapse of northern Larsen Ice Shelf, Antarctic Peninsula

1998 ◽  
Vol 27 ◽  
pp. 86-92 ◽  
Author(s):  
Helmut Rott ◽  
Wolfgang Rack ◽  
Thomas Nagler ◽  
Pedro Skvarca
Keyword(s):  
Mass Balance ◽  
Antarctic Peninsula ◽  
High Sensitivity ◽  
Ice Shelf ◽  
Landsat Images ◽  
Surface Mass ◽  
Ice Shelves ◽  
Radar Images ◽  
Near Future ◽  
Larsen Ice Shelf

The areal changes of the northern Larsen Ite Shelf (LIS), Antarctic Peninsula, between March 1986 and March 1997 have been analyzed, based on synthetic aperture radar images of the European remote-sensing satellites ERS-1 and ERS-2 and on Landsat images. This analysis is complemented by data on ice motion and surface mass balance which have been obtained during several field campaigns since the early 1980s. After a period of retreat, coinciding with atmospheric warming and with decreasing net accumulation at the surface due to melt losses, the two northernmost sections of LIS disintegrated almost completely within a few days in January 1995. Recent observations of the ice-shelf section north of Jason Peninsula, which is presently the northernmost section of LIS, show increased summer melt and intensification of the rifting processes, probably causing accelerated retreat of this section in the near future. The retreat and the disintegration event of LIS indicate high sensitivity of ice shelves to prolonged perturbations of the mass balance.

Surface mass balance and melting projections over the Amundsen coastal region, West Antarctica

2020 ◽  
Author(s):  
Nicolas Jourdain ◽  
Marion Donat-Magnin ◽  
Christoph Kittel ◽  
Cécile Agosta ◽  
Charles Amory ◽  
...  
Keyword(s):  
Mass Balance ◽  
Projection Method ◽  
Surface Mass Balance ◽  
West Antarctica ◽  
Ice Shelf ◽  
Near Surface ◽  
Surface Mass ◽  
Ice Shelves ◽  
The Future ◽  
Surface Melt

<p>We present Surface Mass Balance (SMB) and surface melt rates projections in West Antarctica for the end of the 21<sup>st</sup> century using the MAR regional atmosphere and firn model (Gallée 1994; Agosta et al. 2019) forced by a CMIP5-rcp85 multi-model-mean seasonal anomaly added to the ERA-Interim 6-hourly reanalysis.</p><p> </p><p>First of all, we assess the validity of our projection method, following a perfect-model approach, with MAR constrained by the ACCESS-1.3 present-day and future climates. Changes in large-scale variables are well captured by our anomaly-based projection method, and errors on surface melting and SMB projections are typically 10%.</p><p> </p><p>Based on the CMIP5-rcp85 multi-model mean, SMB over the grounded ice sheet in the Amundsen sector is projected to increase by 35% over the 21<sup>st</sup> century. This corresponds to a SMB sensitivity to near-surface warming of 8.3%.°C<sup>-1</sup>. Increased humidity, resulting from both higher water vapour saturation in warmer conditions and decreased sea-ice concentrations, are shown to favour increased SMB in the future scenario.</p><p> </p><p>Ice-shelf surface melt rates at the end of the 21<sup>st</sup> century are projected to become 6 to 15 times larger than presently, depending on the ice shelf under consideration. This is due to enhanced downward longwave radiative fluxes related to increased humidity, and to an albedo feedback leading to more absorption of shortwave radiation. Interestingly, only three ice shelves produce runoff (Abbot, Cosgrove and Pine Island) in the future climate. For the other ice shelves (Thwaites, Crosson, Dotson, Getz), the future melt-to-snowfall ratio remains too low to produce firn air depletion and subsequent runoff.</p><p> </p>

scholarly journals Projected increases in surface melt and ice loss for the Northern and Southern Patagonian Icefields

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Claudio Bravo ◽  
Deniz Bozkurt ◽  
Andrew N. Ross ◽  
Duncan J. Quincey
Keyword(s):  
Climate Model ◽  
Regional Climate ◽  
Historical Period ◽  
Emission Scenarios ◽  
Recent Past ◽  
Model Data ◽  
Surface Mass ◽  
The Mean ◽  
Surface Melt ◽  
Frontal Ablation

AbstractThe Northern Patagonian Icefield (NPI) and the Southern Patagonian Icefield (SPI) have increased their ice mass loss in recent decades. In view of the impacts of glacier shrinkage in Patagonia, an assessment of the potential future surface mass balance (SMB) of the icefields is critical. We seek to provide this assessment by modelling the SMB between 1976 and 2050 for both icefields, using regional climate model data (RegCM4.6) and a range of emission scenarios. For the NPI, reductions between 1.5 m w.e. (RCP2.6) and 1.9 m w.e. (RCP8.5) were estimated in the mean SMB during the period 2005–2050 compared to the historical period (1976–2005). For the SPI, the estimated reductions were between 1.1 m w.e. (RCP2.6) and 1.5 m w.e. (RCP8.5). Recently frontal ablation estimates suggest that mean SMB in the SPI is positively biased by 1.5 m w.e., probably due to accumulation overestimation. If it is assumed that frontal ablation rates of the recent past will continue, ice loss and sea-level rise contribution will increase. The trend towards lower SMB is mostly explained by an increase in surface melt. Positive ice loss feedbacks linked to increasing in meltwater availability are expected for calving glaciers.

scholarly journals Sensitivity of the dynamics of Pine Island Glacier, West Antarctica, to climate forcing for the next 50 years

2014 ◽  
Vol 8 (5) ◽  
pp. 1699-1710 ◽  
Author(s):  
H. Seroussi ◽  
M. Morlighem ◽  
E. Rignot ◽  
J. Mouginot ◽  
E. Larour ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Three Dimensional ◽  
Major Contributor ◽  
West Antarctica ◽  
Climatic Impact ◽  
Ice Shelf ◽  
Ice Dynamics ◽  
Surface Mass ◽  
Grounding Line

Abstract. Pine Island Glacier, a major contributor to sea level rise in West Antarctica, has been undergoing significant changes over the last few decades. Here, we employ a three-dimensional, higher-order model to simulate its evolution over the next 50 yr in response to changes in its surface mass balance, the position of its calving front and ocean-induced ice shelf melting. Simulations show that the largest climatic impact on ice dynamics is the rate of ice shelf melting, which rapidly affects the glacier speed over several hundreds of kilometers upstream of the grounding line. Our simulations show that the speedup observed in the 1990s and 2000s is consistent with an increase in sub-ice-shelf melting. According to our modeling results, even if the grounding line stabilizes for a few decades, we find that the glacier reaction can continue for several decades longer. Furthermore, Pine Island Glacier will continue to change rapidly over the coming decades and remain a major contributor to sea level rise, even if ocean-induced melting is reduced.

scholarly journals Observationally constrained surface mass balance of Larsen C ice shelf, Antarctica

2017 ◽  
Vol 11 (6) ◽  
pp. 2411-2426 ◽  
Author(s):  
Peter Kuipers Munneke ◽  
Daniel McGrath ◽  
Brooke Medley ◽  
Adrian Luckman ◽  
Suzanne Bevan ◽  
...  
Keyword(s):  
Mass Balance ◽  
Climate Model ◽  
Regional Climate ◽  
Snow Accumulation ◽  
Airborne Radar ◽  
Surface Mass Balance ◽  
Spatial And Temporal Patterns ◽  
Ice Shelf ◽  
The West ◽  
Surface Mass

Abstract. The surface mass balance (SMB) of the Larsen C ice shelf (LCIS), Antarctica, is poorly constrained due to a dearth of in situ observations. Combining several geophysical techniques, we reconstruct spatial and temporal patterns of SMB over the LCIS. Continuous time series of snow height (2.5–6 years) at five locations allow for multi-year estimates of seasonal and annual SMB over the LCIS. There is high interannual variability in SMB as well as spatial variability: in the north, SMB is 0.40 ± 0.06 to 0.41 ± 0.04 m w.e. year−1, while farther south, SMB is up to 0.50 ± 0.05 m w.e. year−1. This difference between north and south is corroborated by winter snow accumulation derived from an airborne radar survey from 2009, which showed an average snow thickness of 0.34 m w.e. north of 66° S, and 0.40 m w.e. south of 68° S. Analysis of ground-penetrating radar from several field campaigns allows for a longer-term perspective of spatial variations in SMB: a particularly strong and coherent reflection horizon below 25–44 m of water-equivalent ice and firn is observed in radargrams collected across the shelf. We propose that this horizon was formed synchronously across the ice shelf. Combining snow height observations, ground and airborne radar, and SMB output from a regional climate model yields a gridded estimate of SMB over the LCIS. It confirms that SMB increases from north to south, overprinted by a gradient of increasing SMB to the west, modulated in the west by föhn-induced sublimation. Previous observations show a strong decrease in firn air content toward the west, which we attribute to spatial patterns of melt, refreezing, and densification rather than SMB.

scholarly journals Surface mass balance and water stable isotopes derived from firn cores on three ice rises, Fimbul Ice Shelf, Antarctica

2016 ◽  
Vol 10 (6) ◽  
pp. 2763-2777 ◽  
Author(s):  
Carmen P. Vega ◽  
Elisabeth Schlosser ◽  
Dmitry V. Divine ◽  
Jack Kohler ◽  
Tõnu Martma ◽  
...  
Keyword(s):  
High Resolution ◽  
Stable Isotope ◽  
Mass Balance ◽  
Temporal Variability ◽  
Ice Cores ◽  
Surface Mass Balance ◽  
Ice Shelf ◽  
Climate Signal ◽  
Surface Mass ◽  
Water Stable Isotope

Abstract. Three shallow firn cores were retrieved in the austral summers of 2011/12 and 2013/14 on the ice rises Kupol Ciolkovskogo (KC), Kupol Moskovskij (KM), and Blåskimen Island (BI), all part of Fimbul Ice Shelf (FIS) in western Dronning Maud Land (DML), Antarctica. The cores were dated back to 1958 (KC), 1995 (KM), and 1996 (BI) by annual layer counting using high-resolution oxygen isotope (δ18O) data, and by identifying volcanic horizons using non-sea-salt sulfate (nssSO42−) data. The water stable isotope records show that the atmospheric signature of the annual snow accumulation cycle is well preserved in the firn column, especially at KM and BI. We are able to determine the annual surface mass balance (SMB), as well as the mean SMB values between identified volcanic horizons. Average SMB at the KM and BI sites (0.68 and 0.70 mw. e. yr−1) was higher than at the KC site (0.24 mw. e. yr−1), and there was greater temporal variability as well. Trends in the SMB and δ18O records from the KC core over the period of 1958–2012 agree well with other previously investigated cores in the area, thus the KC site could be considered the most representative of the climate of the region. Cores from KM and BI appear to be more affected by local meteorological conditions and surface topography. Our results suggest that the ice rises are suitable sites for the retrieval of longer firn and ice cores, but that BI has the best preserved seasonal cycles of the three records and is thus the most optimal site for high-resolution studies of temporal variability of the climate signal. Deuterium excess data suggest a possible effect of seasonal moisture transport changes on the annual isotopic signal. In agreement with previous studies, large-scale atmospheric circulation patterns most likely provide the dominant influence on water stable isotope ratios preserved at the core sites.

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