Standard
Climate decision-making as a recursive process. / Leedal, David
; Jarvis, Andrew; Jackson, Lawrence.
Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014. ed. / Jim W. Hall; Siu-Kui Au; Michael Beer. American Society of Civil Engineers (ASCE), 2014. p. 2838-2846 (Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014).
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Leedal, D
, Jarvis, A & Jackson, L 2014,
Climate decision-making as a recursive process. in JW Hall, S-K Au & M Beer (eds),
Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014. Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014, American Society of Civil Engineers (ASCE), pp. 2838-2846, 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014, Liverpool, United Kingdom,
13/07/14.
https://doi.org/10.1061/9780784413609.286APA
Leedal, D.
, Jarvis, A., & Jackson, L. (2014).
Climate decision-making as a recursive process. In J. W. Hall, S.-K. Au, & M. Beer (Eds.),
Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014 (pp. 2838-2846). (Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014). American Society of Civil Engineers (ASCE).
https://doi.org/10.1061/9780784413609.286Vancouver
Leedal D
, Jarvis A, Jackson L.
Climate decision-making as a recursive process. In Hall JW, Au SK, Beer M, editors, Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014. American Society of Civil Engineers (ASCE). 2014. p. 2838-2846. (Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014). doi: 10.1061/9780784413609.286
Author
Leedal, David
; Jarvis, Andrew ; Jackson, Lawrence. /
Climate decision-making as a recursive process. Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014. editor / Jim W. Hall ; Siu-Kui Au ; Michael Beer. American Society of Civil Engineers (ASCE), 2014. pp. 2838-2846 (Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014).
Bibtex
@inproceedings{6990147e052645bfbdc2026668eb64c3,
title = "Climate decision-making as a recursive process",
abstract = "Climate science and policy making are currently dominated by model-led forecasting as a means of informing decision-making. However, given the very significant uncertainties surrounding our understanding of both the climate and socio-economic systems and their interactions, it appears more reasonable to view climate decision-making as a recursive problem led by updates based on the unfolding observed state of these systems. Not surprisingly, many aspects of the current climate decision making machinery already possess this attribute, embedded as it is in the review cycles that proliferate in this and other areas of decision-making under uncertainty. In this paper, we will illustrate the recursive nature of climate decision-making using a geoengineering case study. Because of the deep uncertainties surrounding these speculative technologies, should geoengineering ever be deployed, it seems most likely it would be deployed sequentially within a review cycle where the magnitude of deployment is conditioned on a combination of environmental observations, model forecasts, risk assessment and cost. Such frameworks contain the essential elements of a Model Predictive Control (MPC) problem. Here, we apply MPC to explore a stratospheric aerosol campaign. The experiment uses the UK Met Office Hadley Centre Global Environment Model (HadGEM2) as a surrogate for the Earth in a blind trial simulation where the objective is to define the magnitude and temporal distribution of SO2 emissions injected into the stratosphere from a northern hemisphere location equivalent to Svalbard in order to recover and then stabilize the minimum extent of the Arctic ice sheet over a period of 80 years. The control algorithm must contend with HadGEM2's considerable internal variability and non-stationary dynamics, mismatch between the control model and HadGEM2, uncertainty in future greenhouse gas forcing and a stochastic volcanic aerosol time series. We present our results and reflect on the experiment.",
author = "David Leedal and Andrew Jarvis and Lawrence Jackson",
note = "Publisher Copyright: {\textcopyright} 2014 American Society of Civil Engineers.; 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014 ; Conference date: 13-07-2014 Through 16-07-2014",
year = "2014",
doi = "10.1061/9780784413609.286",
language = "English",
series = "Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014",
publisher = "American Society of Civil Engineers (ASCE)",
pages = "2838--2846",
editor = "Hall, {Jim W.} and Siu-Kui Au and Michael Beer",
booktitle = "Vulnerability, Uncertainty, and Risk",
address = "United States",
}
RIS
TY - GEN
T1 - Climate decision-making as a recursive process
AU - Leedal, David
AU - Jarvis, Andrew
AU - Jackson, Lawrence
N1 - Publisher Copyright:
© 2014 American Society of Civil Engineers.
PY - 2014
Y1 - 2014
N2 - Climate science and policy making are currently dominated by model-led forecasting as a means of informing decision-making. However, given the very significant uncertainties surrounding our understanding of both the climate and socio-economic systems and their interactions, it appears more reasonable to view climate decision-making as a recursive problem led by updates based on the unfolding observed state of these systems. Not surprisingly, many aspects of the current climate decision making machinery already possess this attribute, embedded as it is in the review cycles that proliferate in this and other areas of decision-making under uncertainty. In this paper, we will illustrate the recursive nature of climate decision-making using a geoengineering case study. Because of the deep uncertainties surrounding these speculative technologies, should geoengineering ever be deployed, it seems most likely it would be deployed sequentially within a review cycle where the magnitude of deployment is conditioned on a combination of environmental observations, model forecasts, risk assessment and cost. Such frameworks contain the essential elements of a Model Predictive Control (MPC) problem. Here, we apply MPC to explore a stratospheric aerosol campaign. The experiment uses the UK Met Office Hadley Centre Global Environment Model (HadGEM2) as a surrogate for the Earth in a blind trial simulation where the objective is to define the magnitude and temporal distribution of SO2 emissions injected into the stratosphere from a northern hemisphere location equivalent to Svalbard in order to recover and then stabilize the minimum extent of the Arctic ice sheet over a period of 80 years. The control algorithm must contend with HadGEM2's considerable internal variability and non-stationary dynamics, mismatch between the control model and HadGEM2, uncertainty in future greenhouse gas forcing and a stochastic volcanic aerosol time series. We present our results and reflect on the experiment.
AB - Climate science and policy making are currently dominated by model-led forecasting as a means of informing decision-making. However, given the very significant uncertainties surrounding our understanding of both the climate and socio-economic systems and their interactions, it appears more reasonable to view climate decision-making as a recursive problem led by updates based on the unfolding observed state of these systems. Not surprisingly, many aspects of the current climate decision making machinery already possess this attribute, embedded as it is in the review cycles that proliferate in this and other areas of decision-making under uncertainty. In this paper, we will illustrate the recursive nature of climate decision-making using a geoengineering case study. Because of the deep uncertainties surrounding these speculative technologies, should geoengineering ever be deployed, it seems most likely it would be deployed sequentially within a review cycle where the magnitude of deployment is conditioned on a combination of environmental observations, model forecasts, risk assessment and cost. Such frameworks contain the essential elements of a Model Predictive Control (MPC) problem. Here, we apply MPC to explore a stratospheric aerosol campaign. The experiment uses the UK Met Office Hadley Centre Global Environment Model (HadGEM2) as a surrogate for the Earth in a blind trial simulation where the objective is to define the magnitude and temporal distribution of SO2 emissions injected into the stratosphere from a northern hemisphere location equivalent to Svalbard in order to recover and then stabilize the minimum extent of the Arctic ice sheet over a period of 80 years. The control algorithm must contend with HadGEM2's considerable internal variability and non-stationary dynamics, mismatch between the control model and HadGEM2, uncertainty in future greenhouse gas forcing and a stochastic volcanic aerosol time series. We present our results and reflect on the experiment.
UR - http://www.scopus.com/inward/record.url?scp=84933574797&partnerID=8YFLogxK
U2 - 10.1061/9780784413609.286
DO - 10.1061/9780784413609.286
M3 - Conference contribution/Paper
AN - SCOPUS:84933574797
T3 - Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014
SP - 2838
EP - 2846
BT - Vulnerability, Uncertainty, and Risk
A2 - Hall, Jim W.
A2 - Au, Siu-Kui
A2 - Beer, Michael
PB - American Society of Civil Engineers (ASCE)
T2 - 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014
Y2 - 13 July 2014 through 16 July 2014
ER -
