Constraining projections of ice sheet instabilities and future sea level rise
Lead Research Organisation:
University of Leeds
Department Name: School of Earth and Environment
Abstract
The largest threat of future rapid sea level rise is from the collapse of ice sheets due to instability and runaway ice loss. It could lead to more than 1 m of sea level rise by 2100, submerging land currently home to 100 million people and causing further destruction in higher-elevation coastal regions through enhanced storm and flood risk. Predicting the future possibility of such instabilities and the resulting plausible 'worst case' sea level change is critical for adequately planning coastal defences and long term infrastructures (e.g. 150 years planning horizon), especially those for which a rare event could have devastating consequences (e.g. nuclear power plants, the Thames barrier, transport networks). Yet, this is extremely challenging, because ice sheet instabilities have not occurred since we started observing ice sheets (the record is too short and ice sheets have been stable in the recent past) and they depend on poorly understood mechanisms (e.g. sliding of ice) that occur in inaccessible areas, such as under kilometres of ice.
There is a solution: ice sheet instabilities have occurred in the geological past, for example in North America, 14,500 years ago (the time of mammoths and modern humans), producing ~7 m sea level rise in 340 years. Ancient ice sheets have left fingerprints of their activity and retreat on the landscape, which have been reconstructed in great detail in places such as the UK, Northern Europe and North America. These records of past ice sheet evolution provide an untapped goldmine of data that could be used to test and improve numerical models, informing future projections. This concept was demonstrated by DeConto and Pollard (2016), who projected Antarctic melting resulting in 15 m of sea level rise by 2500 based on constraints from 3 million years ago (the last time levels of atmospheric carbon dioxide were as high as today). However, there is an important missing piece to this work. In order to reliably translate knowledge from the past into confident future projections, the most important and complex source of uncertainty in modelling past ice sheets needs to be accounted for: the climate. This requires new statistical methods and a person with a unique combination of expertise in statistics, climate and ice sheet instabilities to lead their development. The ambition for this fellowship, is to make that person me .
I will lead an interdisciplinary team of researchers to develop and apply new statistical and physically-based tools to accurately quantify uncertainties in past, present and future climate and ice sheet evolution, thus unlocking the key potential of geological records to constrain future ice sheet instability. This will produce the first robust projection of future ice sheet instability and the resulting sea level change. It will unite and grow the three leading strands of my research: mechanisms of ice sheet instability, climate change, and uncertainty quantification, establishing me as a world leader in using geological data to constrain ice sheet behaviour and future sea level change.
There is a solution: ice sheet instabilities have occurred in the geological past, for example in North America, 14,500 years ago (the time of mammoths and modern humans), producing ~7 m sea level rise in 340 years. Ancient ice sheets have left fingerprints of their activity and retreat on the landscape, which have been reconstructed in great detail in places such as the UK, Northern Europe and North America. These records of past ice sheet evolution provide an untapped goldmine of data that could be used to test and improve numerical models, informing future projections. This concept was demonstrated by DeConto and Pollard (2016), who projected Antarctic melting resulting in 15 m of sea level rise by 2500 based on constraints from 3 million years ago (the last time levels of atmospheric carbon dioxide were as high as today). However, there is an important missing piece to this work. In order to reliably translate knowledge from the past into confident future projections, the most important and complex source of uncertainty in modelling past ice sheets needs to be accounted for: the climate. This requires new statistical methods and a person with a unique combination of expertise in statistics, climate and ice sheet instabilities to lead their development. The ambition for this fellowship, is to make that person me .
I will lead an interdisciplinary team of researchers to develop and apply new statistical and physically-based tools to accurately quantify uncertainties in past, present and future climate and ice sheet evolution, thus unlocking the key potential of geological records to constrain future ice sheet instability. This will produce the first robust projection of future ice sheet instability and the resulting sea level change. It will unite and grow the three leading strands of my research: mechanisms of ice sheet instability, climate change, and uncertainty quantification, establishing me as a world leader in using geological data to constrain ice sheet behaviour and future sea level change.
Planned Impact
The main societal benefit from my fellowship is the delivery of reliable projections of extreme sea level change, enabling more effective UK and global decision making on adaptation to and mitigation (avoidance) of dangerous future sea level rise.
1. Planning coastal flood protection
Businesses and governments planning adaptation measures rely on international and national assessments of sea level change (e.g. Intergovernmental Panel on Climate Change report, IPCC AR5; UK climate projections, UKCP). Lack of knowledge on near-future ice sheet collapse meant that AR5 did not assess this worst-case scenario for sea level rise. However, this is crucial information for extreme event contingency planning (e.g. nuclear power plant flooding or Thames Barrier failure in London). For this purpose, the most recent UKCP assessment provided a 'plausible extreme' scenario from expert opinion and extrapolations, but a newly discovered mechanism of ice sheet instability could lead to even greater sea level rise.
This fellowship will support me to revolutionise projections of 'plausible extreme' sea level rise, using robust quantification from complex ice sheet models that incorporate our best understanding of ice dynamics and comprehensive past/present observations. I will deliver projections up to 2300 AD, that are needed by public and private sector planners of long term infrastructure (100-200 years) such as transport, coastal defence and nuclear power plants; enabling more reliable and effective planning of these vital services. The energy industry will strongly benefit because there are 9 nuclear power stations relying on coastal flood defences. It is imperative for UK population safety and energy security that those defences are not breached. My results will enable the Office for Nuclear Regulation to more reliably assess safety and energy companies to more effectively plan flood defences.The Environment Agency; the Department for Environment, Food and Rural Affairs; major UK cities (e.g. London, Bristol, Liverpool) and local councils (e.g. in Yorkshire near the Humber and coastal Lincolnshire) will benefit in the long term from improved flood risk management ensuring better investment and potentially saving billions of pounds by avoiding unnecessary or ineffective infrastructure and preventing flood damage.
My work will benefit the Met Office by providing (i) an improved version of the BISICLES ice sheet model, part of the flagship UK Earth System Model used for IPCC climate projections, and (ii) data on the probability of future ice sheet instabilities that feed UK climate projections.
Internationally, this work will help large coastal cities (Ho Chi Minh City, Mumbai, Bangkok, Shanghai, New Orleans...) and Small Island States (Papua New Guinea, Fiji, the Maldives, Tuvalu...) plan for sea level rise. Governments worldwide rely on projections from the IPCC, which my fellowship will directly inform.
2. Avoiding dangerous sea level change
I will determine the thresholds in sea level response to warming when ice sheet instabilities are triggered. This knowledge gap is possibly the biggest hindrance to determining dangerous climate change associated with ice sheet collapse. Filling it is critical for reaching meaningful, international agreements on mitigating climate change. Sea level rise is a global problem, and unlike the complexity of atmospheric changes, it presents a threat that is easier for a person without related expertise to understand, with the potential to provide clear red lines for 'this is safe, this is not'. As such, it provides strong motivation to establish detailed, actionable measures to meet internationally agreed targets, such as the Paris Agreement to keep global temperature rise below 2 degrees Celsius.
These benefits will be realised in the short to medium term (5-12 years after the fellowship starts) when our results are included in UK and international assessments of sea level change.
1. Planning coastal flood protection
Businesses and governments planning adaptation measures rely on international and national assessments of sea level change (e.g. Intergovernmental Panel on Climate Change report, IPCC AR5; UK climate projections, UKCP). Lack of knowledge on near-future ice sheet collapse meant that AR5 did not assess this worst-case scenario for sea level rise. However, this is crucial information for extreme event contingency planning (e.g. nuclear power plant flooding or Thames Barrier failure in London). For this purpose, the most recent UKCP assessment provided a 'plausible extreme' scenario from expert opinion and extrapolations, but a newly discovered mechanism of ice sheet instability could lead to even greater sea level rise.
This fellowship will support me to revolutionise projections of 'plausible extreme' sea level rise, using robust quantification from complex ice sheet models that incorporate our best understanding of ice dynamics and comprehensive past/present observations. I will deliver projections up to 2300 AD, that are needed by public and private sector planners of long term infrastructure (100-200 years) such as transport, coastal defence and nuclear power plants; enabling more reliable and effective planning of these vital services. The energy industry will strongly benefit because there are 9 nuclear power stations relying on coastal flood defences. It is imperative for UK population safety and energy security that those defences are not breached. My results will enable the Office for Nuclear Regulation to more reliably assess safety and energy companies to more effectively plan flood defences.The Environment Agency; the Department for Environment, Food and Rural Affairs; major UK cities (e.g. London, Bristol, Liverpool) and local councils (e.g. in Yorkshire near the Humber and coastal Lincolnshire) will benefit in the long term from improved flood risk management ensuring better investment and potentially saving billions of pounds by avoiding unnecessary or ineffective infrastructure and preventing flood damage.
My work will benefit the Met Office by providing (i) an improved version of the BISICLES ice sheet model, part of the flagship UK Earth System Model used for IPCC climate projections, and (ii) data on the probability of future ice sheet instabilities that feed UK climate projections.
Internationally, this work will help large coastal cities (Ho Chi Minh City, Mumbai, Bangkok, Shanghai, New Orleans...) and Small Island States (Papua New Guinea, Fiji, the Maldives, Tuvalu...) plan for sea level rise. Governments worldwide rely on projections from the IPCC, which my fellowship will directly inform.
2. Avoiding dangerous sea level change
I will determine the thresholds in sea level response to warming when ice sheet instabilities are triggered. This knowledge gap is possibly the biggest hindrance to determining dangerous climate change associated with ice sheet collapse. Filling it is critical for reaching meaningful, international agreements on mitigating climate change. Sea level rise is a global problem, and unlike the complexity of atmospheric changes, it presents a threat that is easier for a person without related expertise to understand, with the potential to provide clear red lines for 'this is safe, this is not'. As such, it provides strong motivation to establish detailed, actionable measures to meet internationally agreed targets, such as the Paris Agreement to keep global temperature rise below 2 degrees Celsius.
These benefits will be realised in the short to medium term (5-12 years after the fellowship starts) when our results are included in UK and international assessments of sea level change.
Organisations
Publications
Astfalck L
(2024)
Coexchangeable process modelling for uncertainty quantification in joint climate reconstruction
in Journal of the American Statistical Association
Ely J
(2019)
Recent progress on combining geomorphological and geochronological data with ice sheet modelling, demonstrated using the last British-Irish Ice Sheet
in Journal of Quaternary Science
Erb M
(2022)
Reconstructing Holocene temperatures in time and space using paleoclimate data assimilation
in Climate of the Past
Fewster R
(2020)
Drivers of Holocene palsa distribution in North America
in Quaternary Science Reviews
Gandy N
(2019)
Exploring the ingredients required to successfully model the placement, generation, and evolution of ice streams in the British-Irish Ice Sheet
in Quaternary Science Reviews
Gandy N
(2021)
Collapse of the Last Eurasian Ice Sheet in the North Sea Modulated by Combined Processes of Ice Flow, Surface Melt, and Marine Ice Sheet Instabilities
in Journal of Geophysical Research: Earth Surface
Gandy N
(2023)
De-Tuning Albedo Parameters in a Coupled Climate Ice Sheet Model to Simulate the North American Ice Sheet at the Last Glacial Maximum
in Journal of Geophysical Research: Earth Surface
Hancock C
(2023)
Global Synthesis of Regional Holocene Hydroclimate Variability Using Proxy and Model Data
in Paleoceanography and Paleoclimatology
Izumi K
(2022)
Impacts of the PMIP4 ice sheets on Northern Hemisphere climate during the last glacial period
in Climate Dynamics
Description | This project has developed new methods for sampling and quantifying uncertainty in climate and ice sheet evolution over long timescales. This included a statistical method using the Bayes Linear theorem to reconstruct multi-dimensional (e.g. time, latitude, longitude) climate fields using output from different models and sparse observations. Using this method, we produced a new reconstruction of monthly mean sea surface temperatures at the Last Glacial Maximum and ensembles of plausible monthly maps that can be used as inputs for atmosphere models. We have also demonstrated that the Last Glacial Maximum can be used as a stringent test of coupled climate-ice sheet models. We have revealed that the FAMOUS-ice model had been overtuned to modern-day observations of the Greenland ice sheet. By developing efficient uncertainty quantification techniques, we successfully de-tuned the model to produce plausible simulations of the Northern Hemisphere ice sheets and climate at the Last Glacial Maximum, 21,000 years ago and the Penultimate Glacial Maximum, 140,000 years ago. We are currently linking past and future simulations to demonstrate how geological constraints on past ice sheets can inform future sea level projections. |
Exploitation Route | The dataset generated by our statistical methods and climate-ice sheet models will be useful to researchers investigating environmental changes during the Quaternary (e.g. climate, peatland, ocean circulation, landscape evolution, sea level, vegetation). In particular, the data can be used as input for other climate, sea level, vegetation, or ecosystem models. It may also be used to reconstruct the past evolution of Northern Hemisphere ice sheets to gain information on sea level and solid earth processes. Our uncertainty quantification work will inform future development of old and new versions of the UK Climate model (Unified Model and UK Earth System Model) by the Met Office and NCAS-climate modelling. The statistical techniques we developed are applicable to a wide range of domains involving complex models with large uncertainties. |
Sectors | Digital/Communication/Information Technologies (including Software) Environment |
Description | Re-evalution of rapid ice sheet expansion during glacial period with a comprehensive ice sheet climate coupled model |
Amount | ¥12,556,000 (JPY) |
Organisation | Japan Society for the Promotion of Science (JSPS) |
Sector | Public |
Country | Japan |
Start | 02/2023 |
End | 07/2023 |
Description | UK SWAIS 2C |
Amount | £382,375 (GBP) |
Funding ID | NE/X009351/1 |
Organisation | Natural Environment Research Council |
Sector | Public |
Country | United Kingdom |
Start | 01/2024 |
End | 12/2026 |
Description | Understanding rising seas and ice by linking coupled models and past climates |
Amount | £634,311 (GBP) |
Funding ID | NE/T007443/1 |
Organisation | Natural Environment Research Council |
Sector | Public |
Country | United Kingdom |
Start | 12/2020 |
End | 05/2023 |
Title | Bayes Linear statistical method for reconstructing multidimensional climate fields from climate model output and sparse observational data. |
Description | Any experiment with climate models relies on a potentially large set of spatiotemporal boundary conditions. These can represent both the initial state of the system and/or forcings driving the model output throughout the experiment. These boundary conditions are typically fixed using available reconstructions in climate modelling studies; however, in reality, they are highly uncertain, that uncertainty is unquantified, and the effect on the output of the experiment can be considerable. We develop efficient quantification of these uncertainties that combines relevant data from multiple models and observations. Starting from the coexchangeability model, we develop a coexchangeable process model to capture multiple correlated spatiotemporal fields of variables. We demonstrate that further exchangeability judgements over the parameters within this representation lead to a Bayes linear analogy of a hierarchical model. We use the framework to provide a joint reconstruction of sea-surface temperature and sea-ice concentration boundary conditions at the last glacial maximum (23-19 kya) and use it to force an ensemble of ice-sheet simulations using the FAMOUS-Ice coupled atmosphere and ice-sheet model. We demonstrate that existing boundary conditions typically used in these experiments are implausible given our uncertainties and demonstrate the impact of using more plausible boundary conditions on ice-sheet simulation. |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2024 |
Provided To Others? | Yes |
Impact | This method enabled our team to produce a reconstruction of monthly mean sea surface temperatures at the Last Glacial Maximum with quantified uncertainties. We were then able to produce ensembles of plausible monthly sea surface temperatures and used them as input to a coupled atmosphere-ice sheet model to evaluate the effect of this uncertainty on northern hemisphere ice sheets. |
Title | LGM North America FAMOUS-ice simulation |
Description | Archived files for manuscript "De-tuning a coupled Climate Ice Sheet Model to simulate the North American Ice Sheet at the Last Glacial Maximum" by Gandy et al., in prep. Contents; >Netcdf time series for key variables from FAMOUS >Netcdf time series from the Glimmer ice sheet model All experiments are not archived online to reduce the total file size, this is one simulation (from Wave 2) of 380. To receive all the output files please contact Niall Gandy (n.gandy@shu.ac.uk). |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
Impact | We are currently using this dataset to constrain and improve the FAMOUS-ice coupled climate-ice sheet model and to demonstrate what past ice sheet changes can tell us about future projections of the Greenland ice sheet and sea level rise. |
URL | https://data.mendeley.com/datasets/8kswwpnjyz/1 |