QUoRUM: QUantifying and Reducing Uncertainty in Multi-Decadal Projection of Ice Sheet-Sea Level Contribution
Lead Research Organisation:
University of Edinburgh
Department Name: Sch of Geosciences
Abstract
The West Antarctic Ice Sheet contains enough ice to cause 3.3 meters of sea level rise. The ice streams of its Amundsen Sea sector, which alone could contribute up to 1.2 meters of sea level rise, are thinning faster than in any other region on earth, and have the potential for rapid collapse due to inland-deepening bedrock. Using a combination of novel inverse modelling, a comprehensive ice-sheet model, and remote sensing we will:
1) Estimate the present state of the critical Amundsen sector
2) Predict its future behaviour
3) Quantify the uncertainty of these estimates and predictions
The physics of ice-sheet retreat is qualitatively understood, but the detailed behaviour is dependent upon a very large number of parameters that cannot be measured directly (e.g, spatially-varying basal traction and ice stiffness). However, numerical ice sheet models have now evolved to the point where a number of relevant physical processes, such as grounding line movement and ice-sheet response to ocean forcing, can be represented accurately. Moreover, the satellite-observational record continues to grow, creating opportunities for assimilation of this new data into models. Such a model-data synthesis can allow key underlying and hidden physical parameters to be determined, facilitating data-driven prediction of future ice-sheet contribution to sea levels.
However, techniques for the assimilation of data using ice sheet models remain at an early stage. A considerable amount of data remains unused and fundamental questions, such as the specific information required for reliable predictions, remain unanswered. Moreover, model simulations of future behaviour of ice sheets generally do not account for the uncertainty inherent in estimates of hidden parameters, which can potentially grow with forecast horizons. Accounting for these uncertainties is vital so that informed risk and cost-benefit analyses of sea-level rise protection and adaptation can be carried out.
In the proposed project we will develop a model-based framework which will efficiently assimilate the data record for the Amundsen sector (Fig. 1), providing estimates of key physical quantities, and predictions of future behaviour. Crucially, measures of uncertainty will be provided for the estimate and predictions. We will further study the impact that different observations have on our model predictions and uncertainty therein, providing information that will be of value to future observational campaigns. While the Amundsen region is chosen as a focus in the interest of critical relevance and timeliness, the methodology can be applied more generally in other regions of Antarctica, or Greenland.
1) Estimate the present state of the critical Amundsen sector
2) Predict its future behaviour
3) Quantify the uncertainty of these estimates and predictions
The physics of ice-sheet retreat is qualitatively understood, but the detailed behaviour is dependent upon a very large number of parameters that cannot be measured directly (e.g, spatially-varying basal traction and ice stiffness). However, numerical ice sheet models have now evolved to the point where a number of relevant physical processes, such as grounding line movement and ice-sheet response to ocean forcing, can be represented accurately. Moreover, the satellite-observational record continues to grow, creating opportunities for assimilation of this new data into models. Such a model-data synthesis can allow key underlying and hidden physical parameters to be determined, facilitating data-driven prediction of future ice-sheet contribution to sea levels.
However, techniques for the assimilation of data using ice sheet models remain at an early stage. A considerable amount of data remains unused and fundamental questions, such as the specific information required for reliable predictions, remain unanswered. Moreover, model simulations of future behaviour of ice sheets generally do not account for the uncertainty inherent in estimates of hidden parameters, which can potentially grow with forecast horizons. Accounting for these uncertainties is vital so that informed risk and cost-benefit analyses of sea-level rise protection and adaptation can be carried out.
In the proposed project we will develop a model-based framework which will efficiently assimilate the data record for the Amundsen sector (Fig. 1), providing estimates of key physical quantities, and predictions of future behaviour. Crucially, measures of uncertainty will be provided for the estimate and predictions. We will further study the impact that different observations have on our model predictions and uncertainty therein, providing information that will be of value to future observational campaigns. While the Amundsen region is chosen as a focus in the interest of critical relevance and timeliness, the methodology can be applied more generally in other regions of Antarctica, or Greenland.
Planned Impact
Who might benefit from this research?
a) Government departments with remits of mitigation of adaptation to climate change risks (BEIS and DEFRA). Subgroups concerned with adaptation to sea level rise should be kept aware of current activities and research outcomes in the area of projected sea level rise to inform planning and risk analyses, and those concerned with mitigation will be concerned with "tipping points" and threshold behaviour involving ice-sheet loss in response to climate change.
b) Non-departmental agencies with statutory duties to monitor and plan for flooding risk (e.g. UK Environment Agency, Scottish Environmental Protection Agency (SEPA)). As the impacts of ice loss in West Antarctica on sea levels are felt strongly in the Northern Hemisphere, the outcomes from the proposed research (quantified uncertainties of Amundsen sea level contribution under different warming scenarios) could be used to predict UK coastal flooding.
c) Information sources for government and policy-makers (e.g. SPICE - Scottish parliamentary information resource to provide briefing notes to MSPs, and CAMERAS -- Coordinated Agenda for Marine, Environment and Rural Affairs Science)
d) International space agencies such as ESA (European Space Agency), which seek to optimize the scientific and societal impact generated from the data their satellites gather.
e) The general public: Sea level rise impacts all those living along or close to a coast. The public has a vested interest in the potential for future sea level rise -- and also, in how certain the projections of sea level actually are.
f) NERC, NSF, and other funding agencies engaged in environmental and sea-level research. The decision-makers in these agencies should be kept informed on where and how observational campaigns can have the largest impact on reducing uncertainty in future sea-level rise.
How might they benefit from this research?
a) Engagement with Scottish and UK policy makers. We will engage with stakeholders through ClimateXChange (CXC), Scotland's centre of expertise on climate change, by responding directly through 'call-down mode' requests from agencies and information providers and by working directly with the CXC Policy team to produce reports. Additionally, the PI will visit the Met Office and liaise with the Met Office-Hadley Centre Climate Program, which feeds directly to DEFRA and BEIS.
b) Economic benefit: The quantified uncertainties in our projections comprise risk probabilities that will be of use to agencies involved with planning and protection of coastal environments and infrastructure across the world. Quantified risk will allow these planners to make optimal economic decisions.
c) Allocation of funding of Antarctic fieldwork: it is vital that our results be visible to the relevant decision makers within NERC, such as the Climate System and Earth System Science theme leaders and the Living with Environmental Change programme. We will draft a white paper detailing our results and their significance for policymakers and their relevance in directing future Antarctic research.
d) Public engagement: While the computational tools used in the proposed study are highly mathematical, the current public interest in "big data" and the "data science revolution" provides an entryway for the team to discuss with the public how these mathematical techniques can be used to benefit the public, and not just large corporations. The proposed workshop for adjoint models used in the climate sciences will be organised with the central aim of generating materials for public consumption to educate the public on data science-oriented work in the earth sciences. The intended target is secondary school students transitioning to University, who will be reached through a Massive Open Online Course (MOOC) in geo-data science methods and applications, for which funding is already secured.
a) Government departments with remits of mitigation of adaptation to climate change risks (BEIS and DEFRA). Subgroups concerned with adaptation to sea level rise should be kept aware of current activities and research outcomes in the area of projected sea level rise to inform planning and risk analyses, and those concerned with mitigation will be concerned with "tipping points" and threshold behaviour involving ice-sheet loss in response to climate change.
b) Non-departmental agencies with statutory duties to monitor and plan for flooding risk (e.g. UK Environment Agency, Scottish Environmental Protection Agency (SEPA)). As the impacts of ice loss in West Antarctica on sea levels are felt strongly in the Northern Hemisphere, the outcomes from the proposed research (quantified uncertainties of Amundsen sea level contribution under different warming scenarios) could be used to predict UK coastal flooding.
c) Information sources for government and policy-makers (e.g. SPICE - Scottish parliamentary information resource to provide briefing notes to MSPs, and CAMERAS -- Coordinated Agenda for Marine, Environment and Rural Affairs Science)
d) International space agencies such as ESA (European Space Agency), which seek to optimize the scientific and societal impact generated from the data their satellites gather.
e) The general public: Sea level rise impacts all those living along or close to a coast. The public has a vested interest in the potential for future sea level rise -- and also, in how certain the projections of sea level actually are.
f) NERC, NSF, and other funding agencies engaged in environmental and sea-level research. The decision-makers in these agencies should be kept informed on where and how observational campaigns can have the largest impact on reducing uncertainty in future sea-level rise.
How might they benefit from this research?
a) Engagement with Scottish and UK policy makers. We will engage with stakeholders through ClimateXChange (CXC), Scotland's centre of expertise on climate change, by responding directly through 'call-down mode' requests from agencies and information providers and by working directly with the CXC Policy team to produce reports. Additionally, the PI will visit the Met Office and liaise with the Met Office-Hadley Centre Climate Program, which feeds directly to DEFRA and BEIS.
b) Economic benefit: The quantified uncertainties in our projections comprise risk probabilities that will be of use to agencies involved with planning and protection of coastal environments and infrastructure across the world. Quantified risk will allow these planners to make optimal economic decisions.
c) Allocation of funding of Antarctic fieldwork: it is vital that our results be visible to the relevant decision makers within NERC, such as the Climate System and Earth System Science theme leaders and the Living with Environmental Change programme. We will draft a white paper detailing our results and their significance for policymakers and their relevance in directing future Antarctic research.
d) Public engagement: While the computational tools used in the proposed study are highly mathematical, the current public interest in "big data" and the "data science revolution" provides an entryway for the team to discuss with the public how these mathematical techniques can be used to benefit the public, and not just large corporations. The proposed workshop for adjoint models used in the climate sciences will be organised with the central aim of generating materials for public consumption to educate the public on data science-oriented work in the earth sciences. The intended target is secondary school students transitioning to University, who will be reached through a Massive Open Online Course (MOOC) in geo-data science methods and applications, for which funding is already secured.
Organisations
Publications
Barnes J
(2021)
The transferability of adjoint inversion products between different ice flow models
in The Cryosphere
Christie FDW
(2023)
Inter-decadal climate variability induces differential ice response along Pacific-facing West Antarctica.
in Nature communications
Goldberg D
(2020)
Bathymetric influences on Antarctic ice-shelf melt rates
Goldberg D
(2023)
The Non-Local Impacts of Antarctic Subglacial Runoff
in Journal of Geophysical Research: Oceans
Goldberg D
(2020)
Bathymetric influences on Antarctic ice-shelf melt rates
Goldberg D
(2020)
Bathymetric influences on Antarctic ice-shelf melt rates
Description | Big picture (with selected publications) Barnes et al 2021: One can cast this as an important prerequisite to further work, (which most people would just totally ignore!). This paper establishes a baseline for model uncertainty amongst ISSM/STREAMICE/Úa and also of initialisation uncertainty -- both of which are small with variability well explained. Gudmundsson et al 2023: then establishes that most of the ice shelf is doing very little buttressing -- and hence anything that happens to the existing ice shelf does not have a significant impact on future SLR. Morlighem et al (submitted) in collaboration with DOMINOS, MICI is very unlikely to happen this century. So, these papers establish that (a) our models are "good" at least compared with others, (b) we are not missing MICI for century scale projections, and (c) ultimate losses from TG will depend only on melt and ice loss of newly formed ice shelf over the 21st century. And so in this sense, it sets things up for the coupled modeling we are doing now One final piece is coupled ice-ocean modelling in response to 21st century climate warming, which is in process at this time. |
Exploitation Route | Our findings suggest that the most likely source of loss of ice from Thwaites glacier is due to ice ocean interactions. This should provide a guide for others to study this process rather than ice-shelf breakup or marine ice cliff collapse. |
Sectors | Environment |
Title | Grounding-line and ice-flow change observations along West Antarctica's Pacific-facing margin, 2003-2015, supporting "Inter-decadal climate variability induces differential ice response along Pacific-facing West Antarctica". |
Description | This dataset contains the grounding-line and ice-velocity change observations presented in Christie et al. (Nature Communications, 2023). Data are provided in ESRI .shp (grounding line location and change records) and .TIF (ice velocity and change records) formats, and detailed information about the data collection methods, sources and other technical information can be found within the accompanying README files inside the .ZIP folder. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://www.repository.cam.ac.uk/handle/1810/344420 |
Title | Output of several experiments with Fenics_ice over Smith, Pope, and Kohler Glaciers |
Description | Output of several experiments with Fenics_ice over Smith, Pope, and Kohler Glaciers. The code to produce this output can be found in the following repository; Smith_glacier More information on how to read and plot this data can be found in the smith glacier repository wiki: Citation for the smith glacier repository used to produce this data:
https://zenodo.org/badge/latestdoi/101511241Citation for the Fenics_ice version used to produce this data: https://zenodo.org/badge/latestdoi/417440075 |
Type Of Material | Database/Collection of data |
Year Produced | 2023 |
Provided To Others? | Yes |
URL | https://zenodo.org/record/7612242 |