Articles | Volume 14, issue 11
https://doi.org/10.5194/tc-14-4165-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-14-4165-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Nov 2020
Research article |
| 24 Nov 2020
| 24 Nov 2020
The influence of föhn winds on annual and seasonal surface melt on the Larsen C Ice Shelf, Antarctica
British Antarctic Survey, Cambridge, CB3 0ET, UK
School of Earth and Environment, University of Leeds, Leeds, LS2 9JT,
UK
Institute of Geography, Friedrich–Alexander University, 91058 Erlangen, Germany
Amélie Kirchgaessner
British Antarctic Survey, Cambridge, CB3 0ET, UK
Andrew N. Ross
School of Earth and Environment, University of Leeds, Leeds, LS2 9JT,
UK
John C. King
British Antarctic Survey, Cambridge, CB3 0ET, UK
Peter Kuipers Munneke
Institute for Marine and Atmospheric Research Utrecht, Utrecht University,
Utrecht, 3508, the Netherlands
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Two types of fluctuations were studied in Hurricane Irma (2017) using model simulations. The first type of fluctuation, the eyewall replacement cycle, has a Hurricane’s eyewall replaced by a second outer eyewall that develops further out. The other type of fluctuation has no replacement of the eyewall but a disruption to its structure instead.
William Torgerson, Juliane Schwendike, Andrew Ross, and Chris J. Short
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We investigated intensity fluctuations that occurred during the rapid intensification of Hurricane Irma (2017) to understand their effects on the storm structure. Using high-resolution model simulations, we found that the fluctuations were caused by local regions of strong ascent just outside the eyewall that disrupted the storm, leading to a larger and more symmetrical storm eye. This alters the location and intensity of the strongest winds in the storm and hence the storm's impact.
Sanne B. M. Veldhuijsen, Willem Jan van de Berg, Max Brils, Peter Kuipers Munneke, and Michiel R. van den Broeke
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Firn is the transition of snow to glacier ice and covers 99 % of the Antarctic ice sheet. Knowledge about the firn layer and its variability is important, as it impacts satellite-based estimates of ice sheet mass change. Also, firn contains pores in which nearly all of the surface melt is retained. Here, we improve a semi-empirical firn model and simulate the firn characteristics for the period 1979–2020. We evaluate the performance with field and satellite measures and test its sensitivity.
Thomas Caton Harrison, Stavroula Biri, Thomas J. Bracegirdle, John C. King, Elizabeth C. Kent, Étienne Vignon, and John Turner
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Easterly winds encircle Antarctica, impacting sea ice and helping drive ocean currents which shield ice shelves from warmer waters. Reanalysis datasets give us our most complete picture of how these winds behave. In this paper we use satellite data, surface measurements and weather balloons to test how realistic recent reanalysis estimates are. The winds are generally accurate, especially in the most recent of the datasets, but important short-term variations are often misrepresented.
Lena G. Buth, Bert Wouters, Sanne B. M. Veldhuijsen, Stef Lhermitte, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-127, https://doi.org/10.5194/tc-2022-127, 2022
Manuscript not accepted for further review
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Liquid meltwater which is stored in air bubbles in the compacted snow near the surface of Antarctica can affect ice shelf stability. In order to detect the presence of such firn aquifers over large scales, satellite remote sensing is needed. In this paper, we present our new detection method using radar satellite data as well as the results for the whole Antarctic Peninsula. Firn aquifers are found in the north and northwest of the peninsula, in agreement with locations predicted by models.
Max Brils, Peter Kuipers Munneke, Willem Jan van de Berg, and Michiel van den Broeke
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Firn covers the Greenland ice sheet (GrIS) and can temporarily prevent mass loss. Here, we present the latest version of our firn model, IMAU-FDM, with an application to the GrIS. We improved the density of fallen snow, the firn densification rate and the firn's thermal conductivity. This leads to a higher air content and 10 m temperatures. Furthermore we investigate three case studies and find that the updated model shows greater variability and an increased sensitivity in surface elevation.
David N. Wagner, Matthew D. Shupe, Christopher Cox, Ola G. Persson, Taneil Uttal, Markus M. Frey, Amélie Kirchgaessner, Martin Schneebeli, Matthias Jaggi, Amy R. Macfarlane, Polona Itkin, Stefanie Arndt, Stefan Hendricks, Daniela Krampe, Marcel Nicolaus, Robert Ricker, Julia Regnery, Nikolai Kolabutin, Egor Shimanshuck, Marc Oggier, Ian Raphael, Julienne Stroeve, and Michael Lehning
The Cryosphere, 16, 2373–2402, https://doi.org/10.5194/tc-16-2373-2022, https://doi.org/10.5194/tc-16-2373-2022, 2022
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Based on measurements of the snow cover over sea ice and atmospheric measurements, we estimate snowfall and snow accumulation for the MOSAiC ice floe, between November 2019 and May 2020. For this period, we estimate 98–114 mm of precipitation. We suggest that about 34 mm of snow water equivalent accumulated until the end of April 2020 and that at least about 50 % of the precipitated snow was eroded or sublimated. Further, we suggest explanations for potential snowfall overestimation.
Zhongyang Hu, Peter Kuipers Munneke, Stef Lhermitte, Maaike Izeboud, and Michiel van den Broeke
The Cryosphere, 15, 5639–5658, https://doi.org/10.5194/tc-15-5639-2021, https://doi.org/10.5194/tc-15-5639-2021, 2021
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Antarctica is shrinking, and part of the mass loss is caused by higher temperatures leading to more snowmelt. We use computer models to estimate the amount of melt, but this can be inaccurate – specifically in the areas with the most melt. This is because the model cannot account for small, darker areas like rocks or darker ice. Thus, we trained a computer using artificial intelligence and satellite images that showed these darker areas. The model computed an improved estimate of melt.
Jenny V. Turton, Philipp Hochreuther, Nathalie Reimann, and Manuel T. Blau
The Cryosphere, 15, 3877–3896, https://doi.org/10.5194/tc-15-3877-2021, https://doi.org/10.5194/tc-15-3877-2021, 2021
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We assess the climatic controls of melt lake development, melt duration, melt extent, and the spatial distribution of lakes of 79°N Glacier. There is a large interannual variability in the areal extent of the lakes and the maximum elevation of lake development, which is largely controlled by the summertime air temperatures and the snowpack thickness. Late-summer lake development can be prompted by spikes in surface mass balance. There is some evidence of inland expansion of lakes over time.
Neil P. Hindley, Corwin J. Wright, Alan M. Gadian, Lars Hoffmann, John K. Hughes, David R. Jackson, John C. King, Nicholas J. Mitchell, Tracy Moffat-Griffin, Andrew C. Moss, Simon B. Vosper, and Andrew N. Ross
Atmos. Chem. Phys., 21, 7695–7722, https://doi.org/10.5194/acp-21-7695-2021, https://doi.org/10.5194/acp-21-7695-2021, 2021
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One limitation of numerical atmospheric models is spatial resolution. For atmospheric gravity waves (GWs) generated over small mountainous islands, the driving effect of these waves on atmospheric circulations can be underestimated. Here we use a specialised high-resolution model over South Georgia island to compare simulated stratospheric GWs to colocated 3-D satellite observations. We find reasonable model agreement with observations, with some GW amplitudes much larger than expected.
Craig Poku, Andrew N. Ross, Adrian A. Hill, Alan M. Blyth, and Ben Shipway
Atmos. Chem. Phys., 21, 7271–7292, https://doi.org/10.5194/acp-21-7271-2021, https://doi.org/10.5194/acp-21-7271-2021, 2021
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We present a new aerosol activation scheme suitable for modelling both fog and convective clouds. Most current activation schemes are designed for convective clouds, and we demonstrate that using them to model fog can negatively impact its life cycle. Our scheme has been used to model an observed fog case in the UK, where we demonstrate that a more physically based representation of aerosol activation is required to capture the transition to a deeper layer – more in line with observations.
Eric Keenan, Nander Wever, Marissa Dattler, Jan T. M. Lenaerts, Brooke Medley, Peter Kuipers Munneke, and Carleen Reijmer
The Cryosphere, 15, 1065–1085, https://doi.org/10.5194/tc-15-1065-2021, https://doi.org/10.5194/tc-15-1065-2021, 2021
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Snow density is required to convert observed changes in ice sheet volume into mass, which ultimately drives ice sheet contribution to sea level rise. However, snow properties respond dynamically to wind-driven redistribution. Here we include a new wind-driven snow density scheme into an existing snow model. Our results demonstrate an improved representation of snow density when compared to observations and can therefore be used to improve retrievals of ice sheet mass balance.
Baptiste Vandecrux, Ruth Mottram, Peter L. Langen, Robert S. Fausto, Martin Olesen, C. Max Stevens, Vincent Verjans, Amber Leeson, Stefan Ligtenberg, Peter Kuipers Munneke, Sergey Marchenko, Ward van Pelt, Colin R. Meyer, Sebastian B. Simonsen, Achim Heilig, Samira Samimi, Shawn Marshall, Horst Machguth, Michael MacFerrin, Masashi Niwano, Olivia Miller, Clifford I. Voss, and Jason E. Box
The Cryosphere, 14, 3785–3810, https://doi.org/10.5194/tc-14-3785-2020, https://doi.org/10.5194/tc-14-3785-2020, 2020
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In the vast interior of the Greenland ice sheet, snow accumulates into a thick and porous layer called firn. Each summer, the firn retains part of the meltwater generated at the surface and buffers sea-level rise. In this study, we compare nine firn models traditionally used to quantify this retention at four sites and evaluate their performance against a set of in situ observations. We highlight limitations of certain model designs and give perspectives for future model development.
Vincent Verjans, Amber A. Leeson, Christopher Nemeth, C. Max Stevens, Peter Kuipers Munneke, Brice Noël, and Jan Melchior van Wessem
The Cryosphere, 14, 3017–3032, https://doi.org/10.5194/tc-14-3017-2020, https://doi.org/10.5194/tc-14-3017-2020, 2020
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Ice sheets are covered by a firn layer, which is the transition stage between fresh snow and ice. Accurate modelling of firn density properties is important in many glaciological aspects. Current models show disagreements, are mostly calibrated to match specific observations of firn density and lack thorough uncertainty analysis. We use a novel calibration method for firn models based on a Bayesian statistical framework, which results in improved model accuracy and in uncertainty evaluation.
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Short summary
Föhn winds are warm and dry downslope winds in the lee of a mountain range, such as the Antarctic Peninsula. Föhn winds heat the ice of the Larsen C Ice Shelf at the base of the mountains and promote more melting than during non-föhn periods in spring, summer and autumn in both model output and observations. Especially in spring, when they are most frequent, föhn winds can extend the melt season by over a month and cause a similar magnitude of melting to that observed in summer.
Föhn winds are warm and dry downslope winds in the lee of a mountain range, such as the...
