Climate simulation ensemble - Revision history

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	<onlyinclude>An '''~~ensemble~~''' ~~is a~~ group of climate ~~model~~ simulations ~~used for~~ climate projections. Rather than running a single [[climate model]], an ensemble of thousands of model versions is run with each version of the model being slightly different from one another. This produces a result with multiple scenarios.</onlyinclude> Climate models can help understand how the Earth’s climate works. Climate models are constrained by observations in the real world and can help inform further observational efforts. They are based on physical principles such as physics, chemistry, and biology~~, on~~ how the Earth works.They can help predict future climate projections using past and present day information, such as modelling global temperature change. These models can help explain the ‘what ifs’ by running multiple scenarios at once. An ensemble of models can help represent new resources for studying ranges of plausible climate change responses in relation to a given forcing.<ref name=RE1>"8.1.2.1 Model Intercomparisons and Ensembles - AR4 WGI Chapter 8: Climate Models and their Evaluation", Ipcc.ch, 2016. [Online]. Available: https://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch8s8-1-2-1.html. [Accessed: 02- Jul- 2016].</ref> ~~Forcing means~~ the amount of energy that the Earth receives from the sun and the amount we radiate back to space. These forcing variances are determined by factors that influence our atmosphere such as greenhouse gases. Using an ensemble approach is quite beneficial~~. When~~ comparing against gridded data (two-dimensional data), ensemble results have come closest to replicating historical climate projections.<ref name=RE2>"Environment Canada - Climate Change - Canadian Climate Data and Scenarios", Canadian Climate Data and Scenarios, 2016. [Online]. Available: http://ccds-dscc.ec.gc.ca/?page=ensemblescenarios-a1b. [Accessed: 03- Jul- 2016].</ref> Ensemble projections which accurately project historical data are more likely to represent future climate scenarios more ~~efficiently~~.<ref name=RE2/>		<onlyinclude>'''Climate simulation ensembles''' group climate models simulations to make climate projections. Rather than running a single [[climate model]], an ensemble of thousands of model versions is run with each version of the model being slightly different from one another. This produces a result with multiple scenarios.</onlyinclude> Climate models can help understand how the Earth’s climate works. Climate models are constrained by observations in the real world and can help inform further observational efforts. They are based on physical principles (such as physics, chemistry, and biology) of how the Earth works. They can help predict future climate projections using past and present day information, such as modelling global temperature change. These models can help explain the ‘what ifs’ by running multiple scenarios at once, see Figure 1 below for an example.
			[[File:The 43-year Arctic amplification ratio in observations and climate models.webp.png\|center\|thumb\|600x600px\|Figure 1. Above are four climate model simulations. The thin grey lines are individual realizations, the thick black line represents the ensemble mean, and the red line is the actual observations. In this example, Rantanen, M. et al. are simulating the 43-year Arctic amplification (AA) ratio.<ref>Rantanen, M. et al. (2022). (Accessed July 13, 2026). ''The Arctic has warmed nearly four times faster than the globe since 1979'' [Online]. Available: https://www.nature.com/articles/s43247-022-00498-3</ref>]]
			An ensemble of models can help represent new resources for studying ranges of plausible climate change responses in relation to a given [[Climate forcing\|forcing]].<ref name="RE1">"8.1.2.1 Model Intercomparisons and Ensembles - AR4 WGI Chapter 8: Climate Models and their Evaluation", Ipcc.ch, 2016. [Online]. Available: https://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch8s8-1-2-1.html. [Accessed: 02- Jul- 2016].</ref> A forcing can mean the amount of energy that the Earth receives from the sun and the amount we radiate back to space. These forcing variances are determined by factors that influence our atmosphere such as greenhouse gases. Using an ensemble approach is quite beneficial: when comparing against gridded data (two-dimensional data), ensemble results have come closest to replicating historical climate projections.<ref name="RE2">"Environment Canada - Climate Change - Canadian Climate Data and Scenarios", Canadian Climate Data and Scenarios, 2016. [Online]. Available: http://ccds-dscc.ec.gc.ca/?page=ensemblescenarios-a1b. [Accessed: 03- Jul- 2016].</ref> Ensemble projections which ''accurately project historical data'' are more likely to ''represent future climate scenarios more accurately''.<ref name="RE2" />

	==Types of ensemble techniques==		==Types of ensemble techniques==
	~~===~~Initial condition ensemble~~===~~		'''Initial condition ensemble:''' This type of ensemble requires varying the initial conditions of all of the models, such as their starting [[temperature]]s, [[wind]]s and [[humidity]]. Since the [[climate system]] is chaotic, small changes in these conditions can lead to drastically different paths for the system as a whole.<ref name=ic>Climate Prediction. (Accessed May 31, 2016). ''Initial Condition Ensembles'' [Online], Available: http://www.climateprediction.net/climate-science/climate-ensembles/initial-condition-ensembles/</ref>
	This type of ensemble requires varying the initial conditions of all of the models, such as their starting [[temperature]]s, [[wind]]s and [[humidity]]. Since the [[climate system]] is chaotic, small changes in these conditions can lead to drastically different paths for the system as a whole.<ref name=ic>Climate Prediction. (Accessed May 31, 2016). ''Initial Condition Ensembles'' [Online], Available: http://www.climateprediction.net/climate-science/climate-ensembles/initial-condition-ensembles/</ref>

	Ensembles made with the same model but different initial conditions only characterize the uncertainty associated with internal climate variability, whereas multi-model ensembles including simulations by several models also include the impact of model differences.<ref name=IPCC_SREX>IPCC, 2012: Glossary of terms. In: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation [Field, C.B., V. Barros, T.F. Stocker, D. Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea, K.J. Mach, G.-K. Plattner, S.K. Allen, M. Tignor, and P.M. Midgley (eds.)]. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC). Cambridge University Press, Cambridge, UK, and New York, NY, USA, pp. 555-564.</ref> Therefore these ensembles can be a good method to validate the type of model used, by comparing it to the real-world climate system's past development, known as a [[hindcast]] (in contrast to a [[forecast]]).<Ref name=ic/>		Ensembles made with the same model but different initial conditions only characterize the uncertainty associated with internal climate variability, whereas multi-model ensembles including simulations by several models also include the impact of model differences.<ref name=IPCC_SREX>IPCC, 2012: Glossary of terms. In: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation [Field, C.B., V. Barros, T.F. Stocker, D. Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea, K.J. Mach, G.-K. Plattner, S.K. Allen, M. Tignor, and P.M. Midgley (eds.)]. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC). Cambridge University Press, Cambridge, UK, and New York, NY, USA, pp. 555-564.</ref> Therefore these ensembles can be a good method to validate the type of model used, by comparing it to the real-world climate system's past development, known as a [[hindcast]] (in contrast to a [[forecast]]).<Ref name=ic/>

	~~===~~Perturbed parameter ensemble~~===~~		'''Perturbed parameter ensemble:''' In climate models, certain [[parameter]]s carry a larger [[uncertainty]] than others, thus making it hard to determine the true effect they have on the final results. In perturbed parameter ensembles, model parameters are varied in a systematic manner which aims to produce a more objective estimate of modelling uncertainty.<ref name=IPCC_SREX/> The most thorough way to do this is to run a massive ensemble experiment which test all relevant parameters in every possible combination with one another.<ref name=ppe>Climate Prediction. (Accessed May 31, 2016). ''Perturbed Physics Ensemble'' [Online], Available: http://www.climateprediction.net/climate-science/climate-ensembles/perturbed-physics-ensembles/</ref>
	In climate models, certain [[parameter]]s carry a larger [[uncertainty]] than others, thus making it hard to determine the true effect they have on the final results. In perturbed parameter ensembles, model parameters are varied in a systematic manner which aims to produce a more objective estimate of modelling uncertainty.<ref name=IPCC_SREX/> The most thorough way to do this is to run a massive ensemble experiment which test all relevant parameters in every possible combination with one another.<ref name=ppe>Climate Prediction. (Accessed May 31, 2016). ''Perturbed Physics Ensemble'' [Online], Available: http://www.climateprediction.net/climate-science/climate-ensembles/perturbed-physics-ensembles/</ref>

	~~===~~Forcing ensemble~~===~~		'''Forcing ensemble:''' A model can be introduced to different types of [[Climate forcing\|forcing]], so a forcing ensemble is designed to represent uncertainty in past and future forcing of climate change projections.
	A model can be introduced to different types of forcing, so a forcing ensemble is designed to represent uncertainty in past and future forcing of climate change projections.

	~~===~~Grand ensemble~~===~~		'''Grand ensemble:''' A grand ensemble is a minimum of two or more nested ensembles.
	A grand ensemble is a minimum of two or more nested ensembles.

	In the video below Professor of Instruction [https://www.eoas.ubc.ca/~~about~~/~~faculty/S.Harris.html~~ Dr. Harris]<ref>This video is used with the gracious permission of Dr. S. Harris in a private communication with Jason Donev on 2016-6-12.</ref> explains how climate models are put together to have the most meaningful output:		In the video below, Professor of Instruction [https://www.eoas.ubc.ca/people/saraharris Dr. Harris]<ref>This video is used with the gracious permission of Dr. S. Harris in a private communication with Jason Donev on 2016-6-12.</ref> explains how climate models are put together to have the most meaningful output:

	<html>		<html>
	<iframe width="760" height="455" src="https://www.youtube.com/embed/aVJYwVGrrVs" frameborder="0" allowfullscreen></iframe>		<iframe width="760" height="455" src="https://www.youtube.com/embed/aVJYwVGrrVs" frameborder="0" allowfullscreen></iframe>
	</html>		</html>

			== For Further Reading ==

			* [[Global climate model]]
			* [[Uncertainty]]
			* [[Climate system]]
			* [[Climate forcing]]
			* Or explore a [[Special:Random\|random page]]

	==References==		==References==
	{{reflist}}		{{reflist}}
			[[Category: Uploaded]]

Jmdonev: 1 revision imported: From the summer

2016-09-17T22:29:34Z

1 revision imported: From the summer

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Jmdonev at 03:52, 26 July 2016

2016-07-26T03:52:05Z

New page

[[Category:Done 2016-04-30]]
<onlyinclude>An '''ensemble''' is a group of climate model simulations used for climate projections. Rather than running a single [[climate model]], an ensemble of thousands of model versions is run with each version of the model being slightly different from one another. This produces a result with multiple scenarios.</onlyinclude> Climate models can help understand how the Earth’s climate works. Climate models are constrained by observations in the real world and can help inform further observational efforts. They are based on physical principles such as physics, chemistry, and biology, on how the Earth works.They can help predict future climate projections using past and present day information, such as modelling global temperature change. These models can help explain the ‘what ifs’ by running multiple scenarios at once. An ensemble of models can help represent new resources for studying ranges of plausible climate change responses in relation to a given forcing.<ref name=RE1>"8.1.2.1 Model Intercomparisons and Ensembles - AR4 WGI Chapter 8: Climate Models and their Evaluation", Ipcc.ch, 2016. [Online]. Available: https://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch8s8-1-2-1.html. [Accessed: 02- Jul- 2016].</ref> Forcing means the amount of energy that the Earth receives from the sun and the amount we radiate back to space. These forcing variances are determined by factors that influence our atmosphere such as greenhouse gases. Using an ensemble approach is quite beneficial. When comparing against gridded data (two-dimensional data), ensemble results have come closest to replicating historical climate projections.<ref name=RE2>"Environment Canada - Climate Change - Canadian Climate Data and Scenarios", Canadian Climate Data and Scenarios, 2016. [Online]. Available: http://ccds-dscc.ec.gc.ca/?page=ensemblescenarios-a1b. [Accessed: 03- Jul- 2016].</ref> Ensemble projections which accurately project historical data are more likely to represent future climate scenarios more efficiently.<ref name=RE2/>

==Types of ensemble techniques==
===Initial condition ensemble===
This type of ensemble requires varying the initial conditions of all of the models, such as their starting [[temperature]]s, [[wind]]s and [[humidity]]. Since the [[climate system]] is chaotic, small changes in these conditions can lead to drastically different paths for the system as a whole.<ref name=ic>Climate Prediction. (Accessed May 31, 2016). ''Initial Condition Ensembles'' [Online], Available: http://www.climateprediction.net/climate-science/climate-ensembles/initial-condition-ensembles/</ref>

Ensembles made with the same model but different initial conditions only characterize the uncertainty associated with internal climate variability, whereas multi-model ensembles including simulations by several models also include the impact of model differences.<ref name=IPCC_SREX>IPCC, 2012: Glossary of terms. In: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation [Field, C.B., V. Barros, T.F. Stocker, D. Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea, K.J. Mach, G.-K. Plattner, S.K. Allen, M. Tignor, and P.M. Midgley (eds.)]. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC). Cambridge University Press, Cambridge, UK, and New York, NY, USA, pp. 555-564.</ref> Therefore these ensembles can be a good method to validate the type of model used, by comparing it to the real-world climate system's past development, known as a [[hindcast]] (in contrast to a [[forecast]]).<Ref name=ic/>

===Perturbed parameter ensemble===
In climate models, certain [[parameter]]s carry a larger [[uncertainty]] than others, thus making it hard to determine the true effect they have on the final results. In perturbed parameter ensembles, model parameters are varied in a systematic manner which aims to produce a more objective estimate of modelling uncertainty.<ref name=IPCC_SREX/> The most thorough way to do this is to run a massive ensemble experiment which test all relevant parameters in every possible combination with one another.<ref name=ppe>Climate Prediction. (Accessed May 31, 2016). ''Perturbed Physics Ensemble'' [Online], Available: http://www.climateprediction.net/climate-science/climate-ensembles/perturbed-physics-ensembles/</ref>

===Forcing ensemble===
A model can be introduced to different types of forcing, so a forcing ensemble is designed to represent uncertainty in past and future forcing of climate change projections.

===Grand ensemble===
A grand ensemble is a minimum of two or more nested ensembles.

In the video below Professor of Instruction [https://www.eoas.ubc.ca/about/faculty/S.Harris.html Dr. Harris]<ref>This video is used with the gracious permission of Dr. S. Harris in a private communication with Jason Donev on 2016-6-12.</ref> explains how climate models are put together to have the most meaningful output:

<html>
<iframe width="760" height="455" src="https://www.youtube.com/embed/aVJYwVGrrVs" frameborder="0" allowfullscreen></iframe>
</html>

==References==
{{reflist}}