End-to-end Quantification of Uncertainty for Impacts Prediction (EQUIP)
Lead Research Organisation:
London School of Economics and Political Science
Department Name: Centre for the Analysis of Time Series
Abstract
Society is becoming increasingly aware of climate change and its consequences for us. Examples of likely impacts are changes in food production, increases in mortality rates due to heat waves, and changes in our marine environment. Despite such emerging knowledge, precise predictions of future climate are (and will remain) unattainable owing to the fundamental chaotic nature of the climate system and to imperfections in our understanding, our climate simulation models and our observations of the climate system. This situation limits our ability to take effective adaptation actions. However, effective adaptation is still possible, particularly if we assess the level of precision associated with predictions, and thus quantify the risk posed by climate change. Coupled with assessments of the limitations on our knowledge, this approach can be a powerful tool for informing decision makers. Clearly, then, the quantification of uncertainty in the prediction of climate and its impacts is a critical issue. Considerable thought has gone into this issue with regard to climate change research, although a consensus on the best methods is yet to emerge. Climate impacts research, on the other hand, has focussed primarily on a different set of problems: what are the mechanisms through which climate change is likely to affect for example, agriculture and health, and what are the non-climatic influences that also need to be accounted for? Thus the research base for climate impacts is sound, but tends to be less thorough in its quantification of uncertainty than the physical climate change research that supports it. As a result, statements regarding the impacts of climate change often take a less sophisticated approach to risk and uncertainty. The logical next stage for climate impacts research is therefore to learn from the methods used for climate change predictions. Since climate and its impacts both exist within a broader earth system, with many interrelated components, this next stage is not a simple transfer of technology. Rather, it means taking an 'end-to-end' integrated look at climate and its impacts, and assessing risk and uncertainty across whole systems. These systems include not only physical and biological mechanisms, but also the decisions taken by users of climate information. The climate impacts chosen in EQUIP have been chosen to cover this spectrum from end to end. As well as aiding impacts research, end-to-end analyses are also the logical next stage for climate change research, since it is through impacts that society experiences climate change. The project focuses primarily on the next few decades, since this is a timescale of relevance for societies adapting to climate change. It is also a timescale at which our projections of greenhouse gas emissions are relatively well constrained, thus uncertainty is smaller than for, say, the end of the century. Work on longer timescales will also be carried out in order to gain a greater understanding of uncertainty. EQUIP research will build on work to date on the mechanisms and processes that lead to climate change and its impacts, since it is this understanding that forms the basis of predictive power. This knowledge is in the form of observations and experiments (e.g. experiments on crops have demonstrated that even brief episodes of high temperatures near the flowering of the crop can seriously reduce yield) and also simulation models. It is through effective use and combination of climate science and impacts science, and the models used by each community, that we will be able to quantify uncertainty, assess risk, and thus equip society to deal with climate change.
People |
ORCID iD |
Leonard Smith (Principal Investigator) |
Publications
Beven K
(2012)
On virtual observatories and modelled realities (or why discharge must be treated as a virtual variable)
in Hydrological Processes
Frigg R
(2015)
An assessment of the foundational assumptions in high-resolution climate projections: the case of UKCP09
in Synthese
Hazeleger W
(2015)
Tales of future weather
in Nature Climate Change
Lopez A
(2014)
Towards a typology for constrained climate model forecasts
in Climatic Change
Lopez A
(2013)
Robustness of pattern scaled climate change scenarios for adaptation decision support
in Climatic Change
Rowlands D
(2012)
Broad range of 2050 warming from an observationally constrained large climate model ensemble
in Nature Geoscience
Smith L
(2010)
Exploiting dynamical coherence: A geometric approach to parameter estimation in nonlinear models
in Physics Letters A
Smith L
(2014)
Probabilistic skill in ensemble seasonal forecasts
in Quarterly Journal of the Royal Meteorological Society
Smith L
(2014)
Pseudo-Orbit Data Assimilation. Part I: The Perfect Model Scenario
in Journal of the Atmospheric Sciences
Smith L
(2014)
Pseudo-Orbit Data Assimilation. Part II: Assimilation with Imperfect Models
in Journal of the Atmospheric Sciences
Smith L
(2015)
Towards improving the framework for probabilistic forecast evaluation
in Climatic Change
Smith LA
(2017)
Rising above chaotic likelihoods
in SIAM/ASA Journal on Uncertainty Quanitfication
Smith LA
(2011)
Uncertainty in science and its role in climate policy.
in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Suckling E
(2013)
An Evaluation of Decadal Probability Forecasts from State-of-the-Art Climate Models
in Journal of Climate
Thompson E
(2019)
Escape from model-land
in Economics
Description | See summary at URL link below |
Exploitation Route | tbc |
Sectors | Agriculture Food and Drink Communities and Social Services/Policy Energy Environment Government Democracy and Justice Transport |
URL | http://www.lse.ac.uk/CATS/ResearchGrants/EQUIP/EQUIP-Leaflet.pdf |
Description | The EQUIP project developed methods for generating predictions of climate and its impacts that carefully quantify uncertainty. Our main foci were crops, heatwaves, droughts and marine ecosystems. We also developed understanding of how to communicate uncertainty better, and how uncertain information should be interpreted and used. Impacts included: Improved quantification of uncertainty EQUIP made both specific methodological advances and broader conclusions on good practice; it highlighted that not all uncertainties are equally important. For example, greenhouse gas emissions are more important than model initial conditions for predicting changes in hot extremes (Hanlon et al., 2013a). We also developed methods to quantify sources of uncertainty, including assessments of which aspects of climate and crop simulation contribute most to predictive uncertainty (Watson and Challinor, 2013). EQUIP identified sources of uncertainty that are often ignored when assessing climate impacts, for example the choice of bias correction method (Hawkins et al., 2013). |
First Year Of Impact | 2013 |
Sector | Environment,Government, Democracy and Justice |
Impact Types | Policy & public services |
Description | Briefing report: Curation of climate information |
Geographic Reach | National |
Policy Influence Type | Influenced training of practitioners or researchers |
URL | http://www.lse.ac.uk/CATS/Resources/CATS-Briefings.aspx |
Description | Briefing report: Implications of expert assessment of climate model (in)adequacy |
Geographic Reach | National |
Policy Influence Type | Influenced training of practitioners or researchers |
URL | http://www.lse.ac.uk/CATS/Resources/CATS-Briefings.aspx |
Description | Briefing report: Insights about uncertainty in the Global Calculator |
Geographic Reach | National |
Policy Influence Type | Influenced training of practitioners or researchers |
URL | http://www.lse.ac.uk/CATS/Resources/CATS-Briefings.aspx |
Description | Climate KIC (funding via DECC) |
Amount | £60,000 (GBP) |
Organisation | King's College London |
Department | Depression Case Control Study (DeCC) |
Sector | Academic/University |
Country | United Kingdom |
Start | 08/2013 |
End | 08/2015 |
Description | Decision Making Under Uncertainty |
Amount | £329,042 (GBP) |
Funding ID | EP/P016847/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 01/2017 |
End | 12/2018 |
Description | EPSRC SECURE Network feasibility studies |
Amount | £3,000 (GBP) |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 05/2016 |
End | 01/2017 |
Description | H2020-SC5-2014-two-stage. Topic: SC5-16-2014 |
Amount | € 248,461 (EUR) |
Funding ID | EP-210185204 |
Organisation | European Commission |
Sector | Public |
Country | European Union (EU) |
Start | 05/2015 |
End | 05/2019 |
Description | HEIF5 bid fund (via LSE) |
Amount | £50,600 (GBP) |
Funding ID | 1-RAT-3996 |
Organisation | Higher Education Innovation Funding (HEIF) |
Sector | Public |
Country | United Kingdom |
Start | 02/2017 |
End | 06/2018 |
Description | HEIF5 bid fund (via LSE) |
Amount | £23,861 (GBP) |
Funding ID | 1-RAT-3993 |
Organisation | Higher Education Innovation Funding (HEIF) |
Sector | Public |
Country | United Kingdom |
Start | 01/2017 |
End | 03/2018 |
Description | NERC Advanced training/PPSDA |
Amount | £21,451 (GBP) |
Organisation | Natural Environment Research Council |
Sector | Public |
Country | United Kingdom |
Start | 09/2013 |
End | 01/2014 |
Description | NERC Pure Assocs (follow on) |
Amount | £156,684 (GBP) |
Funding ID | NE/M008304/1 |
Organisation | Natural Environment Research Council |
Sector | Public |
Country | United Kingdom |
Start | 09/2014 |
End | 03/2016 |
Description | PURE Associates call |
Amount | £28,022 (GBP) |
Funding ID | PA13-038 |
Organisation | Natural Environment Research Council |
Sector | Public |
Country | United Kingdom |
Start | 11/2013 |
End | 04/2014 |
Description | PURE Associates call |
Amount | £26,452 (GBP) |
Funding ID | PA13-036 |
Organisation | Natural Environment Research Council |
Sector | Public |
Country | United Kingdom |
Start | 09/2013 |
End | 05/2014 |
Description | RNLI Hyper Local Weather Data |
Amount | £20,000 (GBP) |
Organisation | Royal National Lifeboat Institution |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 09/2015 |
End | 11/2016 |
Description | Lighthill Risk Network |
Organisation | Lighthill Risk Network |
Country | United Kingdom |
Sector | Charity/Non Profit |
PI Contribution | Professor Smith and CATS have been providing mathematical calculations to answer the insurance sector's questions regarding skill scores, which is hoped will lead to an industry-supported code of good practice |
Collaborator Contribution | - |
Impact | The Lighthill Risk Network have provided match-funding for a HEIF5 bid fund award secured by Smith/CATS (see further funding section) |
Start Year | 2017 |
Description | Lloyd's |
Organisation | Lloyds Bank |
Country | United Kingdom |
Sector | Private |
PI Contribution | Research into the investigation of how probability of geophysical events is used within the insurance sector |
Collaborator Contribution | - |
Impact | Two PhDs: one part-funded directly by Lloyd's - 'Examining the decision-relevance of climate model information for the insurance industry', completed in 2011 (the student is now a senior scientists at the Met Office Hadley Centre); and one undertaken by a member of Lloyd's - 'Extreme insurance and the dynamics of risk', completed in 2016. The collaboration with Lloyd's also help Smith/CATS secure further funding (see 'Further funding section - HEIF5 bid fund) |
Start Year | 2007 |
Description | Winton |
Organisation | Winton Capital Management |
Country | United Kingdom |
Sector | Private |
PI Contribution | CATS (Smith and Stainforth) have contributed to discussions of creating a Climate Prediction Market. Two events on this topic have been held so far - October 2016 and January 2017 |
Collaborator Contribution | As per above |
Impact | none as yet |
Start Year | 2016 |
Description | ISF 2016 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Leonard Smith gave two talks ('Sculpted Ensembles: exploiting a modern data assimilation technique to enhance early warning of high impact events' and 'Prediction, Projection and Probability: Quantifying uncertain scientific insights regarding the far future') at the 36th International Symposium on Forecasting, Santander, Spain. The talks sparked questions from and discussion with both other academics and industry practitioners. |
Year(s) Of Engagement Activity | 2016 |
URL | https://forecasters.org/isf |
Description | LSE Works talk |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Public/other audiences |
Results and Impact | A talk given as part of the 'LSE Works' series which aims to showcase the research of LSE faculty in an accessible manner. The talk, entitled 'Coping with Deep Uncertainty: jellyfish, super-storms and nuclear stewardship' was delivered to an audience: approximately 200 people - a mix of academic, industry/business and general public. One of the discussants was a member of industry. |
Year(s) Of Engagement Activity | 2017 |
URL | http://www.lse.ac.uk/Events/2017/03/20170315t1830vHKT/Coping-with-Deep-Uncertainty |