Modeling for insight, not numbers

Bloomfield, Stefan D.; Updegrove, Daniel A.

doi:10.1002/he.36919813509

Cited by 4 publications

(1 citation statement)

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“…As an example, in our case, running the CESM model for 200 years and ignoring the first 150 years for the regression of N against T, would allow us to predict the further evolution of the model. We argue that the quote 'modelling for insight, not numbers' makes an essential point here [102]. We have to conclude that the global linear forcing feedback model may be of limited value to estimate quantities like the ECS of the real world, or at least we have to be more careful in understanding and quantifying in which range of forcings, timescales and climate states a simple model with a constant feedback parameter can be adequately used.…”

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confidence: 99%

Feedbacks, climate sensitivity and the limits of linear models

Knutti

Rugenstein

2015

Phil. Trans. R. Soc. A.

128

118

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The term 'feedback' is used ubiquitously in climate research, but implies varied meanings in different contexts. From a specific process that locally affects a quantity, to a formal framework that attempts to determine a global response to a forcing, researchers use this term to separate, simplify and quantify parts of the complex Earth system. We combine new model results with a historical and educational perspective to organize existing ideas around feedbacks and linear models. Our results suggest that the state- and forcing-dependency of feedbacks are probably not appreciated enough, and not considered appropriately in many studies. A non-constant feedback parameter likely explains some of the differences in estimates of equilibrium climate sensitivity from different methods and types of data. Clarifying the value and applicability of the linear forcing feedback framework and a better quantification of feedbacks on various timescales and spatial scales remains a high priority in order to better understand past and predict future changes in the climate system.

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confidence: 99%

Feedbacks, climate sensitivity and the limits of linear models

Knutti

Rugenstein

2015

Phil. Trans. R. Soc. A.

128

118

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Meeting the Modeling Needs of Future Energy Systems

et al. 2017

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Structural changes in the energy sector have created considerable challenges for regulators, energy consumers, and suppliers. Energy researchers rely on quantitative modeling approaches to address these challenges. At the Karlsruhe Institute of Technology, we have developed several models to analyze today's and the future's energy markets to address the challenges for electricity networks as a result of intermittent renewable and decentralized power and heat supply and to find solutions for integrating demand response. This paper presents a survey of these approaches and discusses further challenges. The developed models have proved to be suitable for answering a range of research questions related to structural changes. As the energy sector remains in a constant state of flux, these models need to be further developed. This means coupling different energy sectors and markets and improving their technical accuracy as well as their spatial and temporal resolutions.

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Decision Support Systems and the Art of Enrollment Management

Beeler

1989

NASPA Journal

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Modeling for insight, not numbers

Abstract: Recent experience in higher education indicates that modeling can be used effectively without compromising academic values. In fact, college and university administrators are finding that models can be learning devices as well as decision‐making aids.

Cited by 4 publications

References 13 publications

Feedbacks, climate sensitivity and the limits of linear models

Feedbacks, climate sensitivity and the limits of linear models

Meeting the Modeling Needs of Future Energy Systems

Decision Support Systems and the Art of Enrollment Management

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