Using Optimisation Algorithms to tune Climate Models (OptClim)
Using Optimisation Algorithms to tune Climate Models (OptClim)
批准号:
NE/L012146/1
负责人:
Simon Tett
金额:
$19.26万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2014
资助国家:
英国
项目状态:
已结题
起止时间:
2014 至 --
中文摘要
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英文摘要
OptCliM will bring into climate modelling advances from mathematical optimization research. Our focus is upon parameterised processes that represent physics that are unresolved within climate models. These unresolved processes are represented through equations that include fixed parameters, with a typical climate model having around a hundred parameters. For example, thunderstorms not only generate heavy rain but are also one route for moisture into the atmosphere. One of the parameters expresses the rate at which moist air in the storm is mixed into the atmosphere. A range of values for each parameter is consistent with theory and measurement with changes in some parameters having a dramatic effect on future climate predictions. It is therefore necessary to have realistic parameter values in order to adequately model past or future climates. OptCliM responds to the need for an automatic and objective method to produce models consistent with reality. Currently the values used in climate models are chosen by manually adjusting several of them until the model produces an acceptable simulation of the current average climate. This process is very expensive in person time; it is not objective, not reproducible, and relies heavily on individual, if expert, judgement. OptCliM will develop iterative methods that use optimisation algorithms to automatically adjust many parameters so that models are consistent with observations. Beginning from any set of parameter values within the allowed ranges, the optimisation algorithm determines an initial set of model configurations to be run. On completion of these runs, the simulations are compared against the observations, and used to define parameter values for further runs until progress halts or the difference between simulation and observations are small. The challenges in applying such methods to climate models arise from the inherent noisiness of climate, and the computational expense of each model run. We will bring into climate modelling three alternative algorithms to find which is most effective in terms of making a model consistent with a range of different observations, and achieving that goal with minimum computing time and cost.OptCliM will:1) Allow researchers to more easily generate parameter sets that produce realistic models allowing a better understanding of past and future climate change. 2) Provide an objective and transparent method to combine models and specified observations. 3) Through our impact plan contribute to the development of the new UK earth system model, UKESM1.4) Open further development of methods for a more systematic exploration of uncertainty in climate modelling, for example generating parameter value sets that sample observational uncertainty to lead to a cloud of plausible models.
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DOI:
10.5194/egusphere-egu22-7895
发表时间:
2022
期刊:
影响因子:
--
作者:
[Tett S]
通讯作者:
Tett S
DOI:
10.1007/s00382-017-3581-5
发表时间:
2017
期刊:
Climate Dynamics
影响因子:
4.6
作者:
[L. Roach;S. Tett;M. Mineter;K. Yamazaki;C. Rae]
通讯作者:
L. Roach;S. Tett;M. Mineter;K. Yamazaki;C. Rae
A derivative-free optimisation method for global ocean biogeochemical models
全球海洋生物地球化学模型的无导数优化方法
DOI:
10.5194/gmd-2021-175
发表时间:
2021
期刊:
影响因子:
--
作者:
[Oliver S]
通讯作者:
Oliver S
Does Model Calibration Reduce Uncertainty in Climate Projections?
模型校准是否会降低气候预测的不确定性?
DOI:
10.1175/jcli-d-21-0434.1
发表时间:
2022
期刊:
Journal of Climate
影响因子:
4.9
作者:
[Tett S]
通讯作者:
Tett S
DOI:
10.1007/s10107-020-01505-1
发表时间:
2018-05
期刊:
Mathematical Programming
影响因子:
2.7
作者:
[Naman Agarwal;Nicolas Boumal;Brian Bullins;C. Cartis]
通讯作者:
Naman Agarwal;Nicolas Boumal;Brian Bullins;C. Cartis
共 6 条
Metrics for Emissions Removal Limits for Nature
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批准号:NE/P019749/1
-
项目类别:Research Grant
-
资助金额:$31.01万
-
财政年份:2017
-
负责人:Simon Tett
-
依托单位:
Playing Games to Understand Multiple Hazards and Risk from Climate Change on Interdependent Infrastructure.
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批准号:NE/R009023/1
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项目类别:Research Grant
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资助金额:$6.43万
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财政年份:2017
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负责人:Simon Tett
-
依托单位:
ICE-IMPACT: International Consortium for the Exploitation of Infrared Measurements of PolAr ClimaTe
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批准号:NE/N013786/1
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项目类别:Research Grant
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资助金额:$9.26万
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财政年份:2016
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负责人:Simon Tett
-
依托单位:
What are the roles of natural and human drivers in historical changes in the Atlantic Meridional Circulation?
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批准号:NE/G007861/1
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项目类别:Research Grant
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资助金额:$26.81万
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财政年份:2009
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负责人:Simon Tett
-
依托单位:
海外基金