Model parametric uncertainty and the evolution of the Greenland ice sheet

2012 ◽  
Vol 279-280 ◽  
pp. 23
Author(s):  
Patrick J. Applegate
Keyword(s):  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Parametric Uncertainty ◽  
Model Parametric Uncertainty

scholarly journals Preliminary assessment of model parametric uncertainty in projections of Greenland Ice Sheet behavior

2011 ◽  
Vol 5 (6) ◽  
pp. 3175-3205 ◽  
Author(s):  
P. J. Applegate ◽  
N. Kirchner ◽  
E. J. Stone ◽  
K. Keller ◽  
R. Greve
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Parametric Uncertainty ◽  
Temperature And Precipitation ◽  
Input Parameters ◽  
Air Temperature Anomaly ◽  
Model Parametric Uncertainty

Abstract. Lack of knowledge about the values of ice sheet model input parameters introduces substantial uncertainty into projections of Greenland Ice Sheet contributions to future sea level rise. Computer models of ice sheet behavior provide one of several means of estimating future sea level rise due to mass loss from ice sheets. Such models have many input parameters whose values are not well known. Recent studies have investigated the effects of these parameters on model output, but the range of potential future sea level increases due to model parametric uncertainty has not been characterized. Here, we demonstrate that this range is large, using a 100-member perturbed-physics ensemble with the SICOPOLIS ice sheet model. Each model run is spun up over 125 000 yr using geological forcings, and subsequently driven into the future using an asymptotically increasing air temperature anomaly curve. All modeled ice sheets lose mass after 2005 AD. After culling the ensemble to include only members that give reasonable ice volumes in 2005 AD, the range of projected sea level rise values in 2100 AD is 30 % or more of the median. Data on past ice sheet behavior can help reduce this uncertainty, but none of our ensemble members produces a reasonable ice volume change during the mid-Holocene, relative to the present. This problem suggests that the model's exponential relation between temperature and precipitation does not hold during the Holocene, or that the central-Greenland temperature forcing curve used to drive the model is not representative of conditions around the ice margin at this time (among other possibilities). Our simulations also lack certain observed physical processes that may tend to enhance the real ice sheet's response. Regardless, this work has implications for other studies that use ice sheet models to project or hindcast the behavior of the Greenland ice sheet.

scholarly journals Probabilistic calibration of a Greenland Ice Sheet model using spatially resolved synthetic observations: toward projections of ice mass loss with uncertainties

2014 ◽  
Vol 7 (5) ◽  
pp. 1933-1943 ◽  
Author(s):  
W. Chang ◽  
P. J. Applegate ◽  
M. Haran ◽  
K. Keller
Keyword(s):  
Mass Loss ◽  
Sea Level Rise ◽  
Sea Level ◽  
Data Model ◽  
Spatial Information ◽  
Full Range ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Parametric Uncertainty ◽  
Model Parameters

Abstract. Computer models of ice sheet behavior are important tools for projecting future sea level rise. The simulated modern ice sheets generated by these models differ markedly as input parameters are varied. To ensure accurate ice sheet mass loss projections, these parameters must be constrained using observational data. Which model parameter combinations make sense, given observations? Our method assigns probabilities to parameter combinations based on how well the model reproduces the Greenland Ice Sheet profile. We improve on the previous state of the art by accounting for spatial information and by carefully sampling the full range of realistic parameter combinations, using statistically rigorous methods. Specifically, we estimate the joint posterior probability density function of model parameters using Gaussian process-based emulation and calibration. This method is an important step toward calibrated probabilistic projections of ice sheet contributions to sea level rise, in that it uses data–model fusion to learn about parameter values. This information can, in turn, be used to make projections while taking into account various sources of uncertainty, including parametric uncertainty, data–model discrepancy, and spatial correlation in the error structure. We demonstrate the utility of our method using a perfect model experiment, which shows that many different parameter combinations can generate similar modern ice sheet profiles. This result suggests that the large divergence of projections from different ice sheet models is partly due to parametric uncertainty. Moreover, our method enables insight into ice sheet processes represented by parameter interactions in the model.

scholarly journals An assessment of key model parametric uncertainties in projections of Greenland Ice Sheet behavior

2012 ◽  
Vol 6 (3) ◽  
pp. 589-606 ◽  
Author(s):  
P. J. Applegate ◽  
N. Kirchner ◽  
E. J. Stone ◽  
K. Keller ◽  
R. Greve
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Parametric Uncertainty ◽  
Temperature And Precipitation ◽  
Input Parameters ◽  
Air Temperature Anomaly ◽  
Response To Temperature

Abstract. Lack of knowledge about the values of ice sheet model input parameters introduces substantial uncertainty into projections of Greenland Ice Sheet contributions to future sea level rise. Computer models of ice sheet behavior provide one of several means of estimating future sea level rise due to mass loss from ice sheets. Such models have many input parameters whose values are not well known. Recent studies have investigated the effects of these parameters on model output, but the range of potential future sea level increases due to model parametric uncertainty has not been characterized. Here, we demonstrate that this range is large, using a 100-member perturbed-physics ensemble with the SICOPOLIS ice sheet model. Each model run is spun up over 125 000 yr using geological forcings and subsequently driven into the future using an asymptotically increasing air temperature anomaly curve. All modeled ice sheets lose mass after 2005 AD. Parameters controlling surface melt dominate the model response to temperature change. After culling the ensemble to include only members that give reasonable ice volumes in 2005 AD, the range of projected sea level rise values in 2100 AD is ~40 % or more of the median. Data on past ice sheet behavior can help reduce this uncertainty, but none of our ensemble members produces a reasonable ice volume change during the mid-Holocene, relative to the present. This problem suggests that the model's exponential relation between temperature and precipitation does not hold during the Holocene, or that the central-Greenland temperature forcing curve used to drive the model is not representative of conditions around the ice margin at this time (among other possibilities). Our simulations also lack certain observed physical processes that may tend to enhance the real ice sheet's response. Regardless, this work has implications for other studies that use ice sheet models to project or hindcast the behavior of the Greenland Ice Sheet.

scholarly journals Probabilistic calibration of a Greenland Ice Sheet model using spatially-resolved synthetic observations: toward projections of ice mass loss with uncertainties

2014 ◽  
Vol 7 (2) ◽  
pp. 1905-1931 ◽  
Author(s):  
W. Chang ◽  
P. J. Applegate ◽  
M. Haran ◽  
K. Keller
Keyword(s):  
Mass Loss ◽  
Sea Level Rise ◽  
Sea Level ◽  
Observational Data ◽  
Spatial Information ◽  
Full Range ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Parametric Uncertainty ◽  
Model Parameters

Abstract. Computer models of ice sheet behavior are important tools for projecting future sea level rise. The simulated modern ice sheets generated by these models differ markedly as input parameters are varied. To ensure accurate ice sheet mass loss projections, these parameters must be constrained using observational data. Which model parameter combinations make sense, given observations? Our method assigns probabilities to parameter combinations based on how well the model reproduces the Greenland Ice Sheet profile. We improve on the previous state of the art by accounting for spatial information, and by carefully sampling the full range of realistic parameter combinations, using statistically rigorous methods. Specifically, we estimate the joint posterior probability density function of model parameters using Gaussian process-based emulation and calibration. This method is an important step toward probabilistic projections of ice sheet contributions to sea level rise, in that it uses observational data to learn about parameter values. This information can, in turn, be used to make projections while taking into account various sources of uncertainty, including parametric uncertainty, data–model discrepancy, and spatial correlation in the error structure. We demonstrate the utility of our method using a perfect model experiment, which shows that many different parameter combinations can generate similar modern ice sheet profiles. This result suggests that the large divergence of projections from different ice sheet models is partly due to parametric uncertainty. Moreover, our method enables insight into ice sheet processes represented by parameter interactions in the model.

The Nioghalvfjerdsfjorden glacier project, North-East Greenland: a study of ice sheet response to climatic change

1997 ◽  
pp. 95-103 ◽  
Author(s):  
Henrik Højmark Thomsen ◽  
Niels Reeh ◽  
Ole B. Olesen ◽  
Carl Egede Bøggilde ◽  
Wolfgang Starzer ◽  
...  
Keyword(s):  
Climatic Change ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
East Greenland ◽  
Changing Climate ◽  
North East ◽  
Integrated Research ◽  
Research Themes ◽  
Advance Research ◽  
Inland Ice

NOTE: This article was published in a former series of GEUS Bulletin. Please use the original series name when citing this article, for example: Højmark Thomsen, H., Reeh, N., Olesen, O. B., Egede Bøggilde, C., Starzer, W., Weidick, A., & Higgins, A. K. (1997). The Nioghalvfjerdsfjorden glacier project, North-East Greenland: a study of ice sheet response to climatic change. Geology of Greenland Survey Bulletin, 176, 95-103. https://doi.org/10.34194/ggub.v176.5073 _______________ Glaciological research was initiated in 1996 on the floating glacier tongue filling Nioghalvfjerdsfjorden in NorthEast Greenland (Fig. 1), with the aim of acquiring a better understanding of the response of the Greenland ice sheet (Inland Ice) to changing climate, and the implications for future sea level. The research is part of a three year project (1996–98) to advance research into the basic processes that contribute to changes in the ocean volume with a changing climate. Five nations are participants in the project, which is supported by the European Community (EC) Environment and Climate Programme. The Geological Survey of Denmark and Greenland (GEUS) and the Danish Polar Center are the Danish partners in the project, both with integrated research themes concentrated on and around Nioghalvfjerdsfjorden.

Could climate engineering save the Greenland Ice Sheet?

2016 ◽  
Author(s):  
Patrick J. Applegate ◽  
K. Keller
Keyword(s):  
Sea Level Rise ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Sea Level ◽  
Computer Model ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Upper Atmosphere ◽  
Climate Engineering ◽  
Air Temperatures

Engineering the climate through albedo modification (AM) could slow, but probably would not stop, melting of the Greenland Ice Sheet. Albedo modification is a technology that could reduce surface air temperatures through putting reflective particles into the upper atmosphere. AM has never been tested, but it might reduce surface air temperatures faster and more cheaply than reducing greenhouse gas emissions. Some scientists claim that AM would also prevent or reverse sea-level rise. But, are these claims true? The Greenland Ice Sheet will melt faster at higher temperatures, adding to sea-level rise. However, it's not clear that reducing temperatures through AM will stop or reverse sea-level rise due to Greenland Ice Sheet melting. We used a computer model of the Greenland Ice Sheet to examine its contributions to future sea level rise, with and without AM. Our results show that AM would probably reduce the rate of sea-level rise from the Greenland Ice Sheet. However, sea-level rise would likely continue even with AM, and the ice sheet would not regrow quickly. Albedo modification might buy time to prepare for sea-level rise, but problems could arise if policymakers assume that AM will stop sea-level rise completely.

scholarly journals Response of the Energy Balance on the Margin of the Greenland Ice Sheet to Temperature Changes

1990 ◽  
Vol 36 (123) ◽  
pp. 217-221 ◽  
Author(s):  
Roger J. Braithwaite ◽  
Ole B. Olesen
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Air Temperature ◽  
Sensible Heat Flux ◽  
Ice Sheet ◽  
Temperature Response ◽  
Greenland Ice Sheet ◽  
Energy Balance Model ◽  
Balance Model ◽  
Sensible Heat

AbstractDaily ice ablation on two outlet glaciers from the Greenland ice sheet, Nordbogletscher (1979–83) and Qamanârssûp sermia (1980–86), is related to air temperature by a linear regression equation. Analysis of this ablation-temperature equation with the help of a simple energy-balance model shows that sensible-heat flux has the greatest temperature response and accounts for about one-half of the temperature response of ablation. Net radiation accounts for about one-quarter of the temperature response of ablation, and latent-heat flux and errors account for the remainder. The temperature response of sensible-heat flux at QQamanârssûp sermia is greater than at Nordbogletscher mainly due to higher average wind speeds. The association of high winds with high temperatures during Föhn events further increases sensible-heat flux. The energy-balance model shows that ablation from a snow surface is only about half that from an ice surface at the same air temperature.

scholarly journals Melt season duration and ice layer formation on the Greenland ice sheet, 2000–2004

2007 ◽  
Vol 112 (F4) ◽  
Author(s):  
Libo Wang ◽  
Martin Sharp ◽  
Benoit Rivard ◽  
Konrad Steffen
Keyword(s):  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Layer Formation

scholarly journals Large subglacial source of mercury from the southwestern margin of the Greenland Ice Sheet

2021 ◽  
Author(s):  
Jon R. Hawkings ◽  
Benjamin S. Linhoff ◽  
Jemma L. Wadham ◽  
Marek Stibal ◽  
Carl H. Lamborg ◽  
...  
Keyword(s):  
Natural Waters ◽  
Inorganic Mercury ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Annual Runoff ◽  
Arctic Ecosystems ◽  
High Mercury ◽  
Southwestern Margin ◽  
High Concentrations ◽  
Dissolved Mercury

AbstractThe Greenland Ice Sheet is currently not accounted for in Arctic mercury budgets, despite large and increasing annual runoff to the ocean and the socio-economic concerns of high mercury levels in Arctic organisms. Here we present concentrations of mercury in meltwaters from three glacial catchments on the southwestern margin of the Greenland Ice Sheet and evaluate the export of mercury to downstream fjords based on samples collected during summer ablation seasons. We show that concentrations of dissolved mercury are among the highest recorded in natural waters and mercury yields from these glacial catchments (521–3,300 mmol km−2 year−1) are two orders of magnitude higher than from Arctic rivers (4–20 mmol km−2 year−1). Fluxes of dissolved mercury from the southwestern region of Greenland are estimated to be globally significant (15.4–212 kmol year−1), accounting for about 10% of the estimated global riverine flux, and include export of bioaccumulating methylmercury (0.31–1.97 kmol year−1). High dissolved mercury concentrations (~20 pM inorganic mercury and ~2 pM methylmercury) were found to persist across salinity gradients of fjords. Mean particulate mercury concentrations were among the highest recorded in the literature (~51,000 pM), and dissolved mercury concentrations in runoff exceed reported surface snow and ice values. These results suggest a geological source of mercury at the ice sheet bed. The high concentrations of mercury and its large export to the downstream fjords have important implications for Arctic ecosystems, highlighting an urgent need to better understand mercury dynamics in ice sheet runoff under global warming.

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