Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal melt
<p>Antarctica's Lambert Glacier drains about one-sixth of the ice from the East Antarctic Ice Sheet and is considered stable due to the strong buttressing provided by the Amery Ice Shelf. While previous projections of the sea-level contribution from this sector of the ice sheet have predi...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2024-11-01
|
| Series: | The Cryosphere |
| Online Access: | https://tc.copernicus.org/articles/18/5207/2024/tc-18-5207-2024.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846166767562391552 |
|---|---|
| author | S. Jantre M. J. Hoffman N. M. Urban T. Hillebrand M. Perego S. Price J. D. Jakeman |
| author_facet | S. Jantre M. J. Hoffman N. M. Urban T. Hillebrand M. Perego S. Price J. D. Jakeman |
| author_sort | S. Jantre |
| collection | DOAJ |
| description | <p>Antarctica's Lambert Glacier drains about one-sixth of the ice from the East Antarctic Ice Sheet and is considered stable due to the strong buttressing provided by the Amery Ice Shelf. While previous projections of the sea-level contribution from this sector of the ice sheet have predicted significant mass loss only with near-complete removal of the ice shelf, the ocean warming necessary for this was deemed unlikely. Recent climate projections through 2300 indicate that sufficient ocean warming is a distinct possibility after 2100. This work explores the impact of parametric uncertainty on projections of the response of the Lambert–Amery system (hereafter “the Amery sector”) to abrupt ocean warming through Bayesian calibration of a perturbed-parameter ice-sheet model ensemble. We address the computational cost of uncertainty quantification for ice-sheet model projections via statistical emulation, which employs surrogate models for fast and inexpensive parameter space exploration while retaining critical features of the high-fidelity simulations. To this end, we build Gaussian process (GP) emulators from simulations of the Amery sector at a medium resolution (4–20 km mesh) using the Model for Prediction Across Scales (MPAS)-Albany Land Ice (MALI) model. We consider six input parameters that control basal friction, ice stiffness, calving, and ice-shelf basal melting. From these, we generate 200 perturbed input parameter initializations using space filling Sobol sampling. For our end-to-end probabilistic modeling workflow, we first train emulators on the simulation ensemble and then calibrate the input parameters using observations of the mass balance, grounding line movement, and calving front movement with priors assigned via expert knowledge. Next, we use MALI to project a subset of simulations to 2300 using ocean and atmosphere forcings from a climate model for both low- and high-greenhouse-gas-emission scenarios. From these simulation outputs, we build multivariate emulators by combining GP regression with principal component dimension reduction to emulate multivariate sea-level contribution time series data from the MALI simulations. We then use these emulators to propagate uncertainty from model input parameters to predictions of glacier mass loss through 2300, demonstrating that the calibrated posterior distributions have both greater mass loss and reduced variance compared to the uncalibrated prior distributions. Parametric uncertainty is large enough through about 2130 that the two projections under different emission scenarios are indistinguishable from one another. However, after rapid ocean warming in the first half of the 22nd century, the projections become statistically distinct within decades. Overall, this study demonstrates an efficient Bayesian calibration and uncertainty propagation workflow for ice-sheet model projections and identifies the potential for large sea-level rise contributions from the Amery sector of the Antarctic Ice Sheet after 2100 under high-greenhouse-gas-emission scenarios.</p> |
| format | Article |
| id | doaj-art-9b00a5c33e004ae6bc138cbed75cdfa5 |
| institution | Kabale University |
| issn | 1994-0416 1994-0424 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The Cryosphere |
| spelling | doaj-art-9b00a5c33e004ae6bc138cbed75cdfa52024-11-15T10:19:06ZengCopernicus PublicationsThe Cryosphere1994-04161994-04242024-11-01185207523810.5194/tc-18-5207-2024Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal meltS. Jantre0M. J. Hoffman1N. M. Urban2T. Hillebrand3M. Perego4S. Price5J. D. Jakeman6Applied Mathematics Group, Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USAFluid Dynamics and Solid Mechanics Group, Los Alamos National Laboratory, Los Alamos, NM, USAApplied Mathematics Group, Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USAFluid Dynamics and Solid Mechanics Group, Los Alamos National Laboratory, Los Alamos, NM, USACenter for Computing Research, Sandia National Laboratories, Albuquerque, NM, USAFluid Dynamics and Solid Mechanics Group, Los Alamos National Laboratory, Los Alamos, NM, USACenter for Computing Research, Sandia National Laboratories, Albuquerque, NM, USA<p>Antarctica's Lambert Glacier drains about one-sixth of the ice from the East Antarctic Ice Sheet and is considered stable due to the strong buttressing provided by the Amery Ice Shelf. While previous projections of the sea-level contribution from this sector of the ice sheet have predicted significant mass loss only with near-complete removal of the ice shelf, the ocean warming necessary for this was deemed unlikely. Recent climate projections through 2300 indicate that sufficient ocean warming is a distinct possibility after 2100. This work explores the impact of parametric uncertainty on projections of the response of the Lambert–Amery system (hereafter “the Amery sector”) to abrupt ocean warming through Bayesian calibration of a perturbed-parameter ice-sheet model ensemble. We address the computational cost of uncertainty quantification for ice-sheet model projections via statistical emulation, which employs surrogate models for fast and inexpensive parameter space exploration while retaining critical features of the high-fidelity simulations. To this end, we build Gaussian process (GP) emulators from simulations of the Amery sector at a medium resolution (4–20 km mesh) using the Model for Prediction Across Scales (MPAS)-Albany Land Ice (MALI) model. We consider six input parameters that control basal friction, ice stiffness, calving, and ice-shelf basal melting. From these, we generate 200 perturbed input parameter initializations using space filling Sobol sampling. For our end-to-end probabilistic modeling workflow, we first train emulators on the simulation ensemble and then calibrate the input parameters using observations of the mass balance, grounding line movement, and calving front movement with priors assigned via expert knowledge. Next, we use MALI to project a subset of simulations to 2300 using ocean and atmosphere forcings from a climate model for both low- and high-greenhouse-gas-emission scenarios. From these simulation outputs, we build multivariate emulators by combining GP regression with principal component dimension reduction to emulate multivariate sea-level contribution time series data from the MALI simulations. We then use these emulators to propagate uncertainty from model input parameters to predictions of glacier mass loss through 2300, demonstrating that the calibrated posterior distributions have both greater mass loss and reduced variance compared to the uncalibrated prior distributions. Parametric uncertainty is large enough through about 2130 that the two projections under different emission scenarios are indistinguishable from one another. However, after rapid ocean warming in the first half of the 22nd century, the projections become statistically distinct within decades. Overall, this study demonstrates an efficient Bayesian calibration and uncertainty propagation workflow for ice-sheet model projections and identifies the potential for large sea-level rise contributions from the Amery sector of the Antarctic Ice Sheet after 2100 under high-greenhouse-gas-emission scenarios.</p>https://tc.copernicus.org/articles/18/5207/2024/tc-18-5207-2024.pdf |
| spellingShingle | S. Jantre M. J. Hoffman N. M. Urban T. Hillebrand M. Perego S. Price J. D. Jakeman Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal melt The Cryosphere |
| title | Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal melt |
| title_full | Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal melt |
| title_fullStr | Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal melt |
| title_full_unstemmed | Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal melt |
| title_short | Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal melt |
| title_sort | probabilistic projections of the amery ice shelf catchment antarctica under conditions of high ice shelf basal melt |
| url | https://tc.copernicus.org/articles/18/5207/2024/tc-18-5207-2024.pdf |
| work_keys_str_mv | AT sjantre probabilisticprojectionsoftheameryiceshelfcatchmentantarcticaunderconditionsofhighiceshelfbasalmelt AT mjhoffman probabilisticprojectionsoftheameryiceshelfcatchmentantarcticaunderconditionsofhighiceshelfbasalmelt AT nmurban probabilisticprojectionsoftheameryiceshelfcatchmentantarcticaunderconditionsofhighiceshelfbasalmelt AT thillebrand probabilisticprojectionsoftheameryiceshelfcatchmentantarcticaunderconditionsofhighiceshelfbasalmelt AT mperego probabilisticprojectionsoftheameryiceshelfcatchmentantarcticaunderconditionsofhighiceshelfbasalmelt AT sprice probabilisticprojectionsoftheameryiceshelfcatchmentantarcticaunderconditionsofhighiceshelfbasalmelt AT jdjakeman probabilisticprojectionsoftheameryiceshelfcatchmentantarcticaunderconditionsofhighiceshelfbasalmelt |