25 Jul 2018
| 25 Jul 2018
Empirical growth models for the renewable energy sector
Kristoffer Rypdal
CORRESPONDING AUTHOR
Department of Mathematics and Statistics, UiT The Arctic University of Norway, 9037 Tromsø, Norway
Related authors
Kristoffer Rypdal
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2017-93, https://doi.org/10.5194/esd-2017-93, 2017
Revised manuscript not accepted
Short summary
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The paper examines the assertion that limits to growth in the renewable energy sector can be inferred statistically from historical data for installed capacity of solar and wind power. This claim has been made in the peer reviewed scientific literature and has been subject to considerable media coverage. It is demonstrated here that rational selection between an exponential and a logistic growth model cannot be made from existing data for the historical evolution of global installed capacity.
Kristoffer Rypdal and Martin Rypdal
Earth Syst. Dynam., 7, 597–609, https://doi.org/10.5194/esd-7-597-2016, https://doi.org/10.5194/esd-7-597-2016, 2016
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This comment on the paper by Lovejoy and Varotsos demonstrates that their methods for establishing nonlinearity in the global temperature response in climate models are flawed. One of their methods is based on an invalid approximation, which when corrected does not falsify the hypothesis that the response is linear. This conclusion is enforced when internal variability in the models are accounted for. The other results in their paper are also shown to be reproduced by linear-response models.
Tine Nilsen, Kristoffer Rypdal, and Hege-Beate Fredriksen
Earth Syst. Dynam., 7, 419–439, https://doi.org/10.5194/esd-7-419-2016, https://doi.org/10.5194/esd-7-419-2016, 2016
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In this article it is discussed how temperature variability on centennial timescales and longer can be described in a simplistic way. By analysing the scaling in late Holocene temperature reconstructions and longer temperature records from Greenland and Antarctic ice cores, we find that the choice of model depends heavily on the data material and timescale one chooses to emphasize. Ignoring data beyond the Holocene seems plausible when predicting temperature, but not for other purposes.
Martin Rypdal and Kristoffer Rypdal
Earth Syst. Dynam., 7, 281–293, https://doi.org/10.5194/esd-7-281-2016, https://doi.org/10.5194/esd-7-281-2016, 2016
Short summary
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We analyse scaling in temperature signals for the late quaternary climate, and focus on the effects of regime shifting events such as the Dansgaard-Oeschger cycles and the shifts between glacial and interglacial conditions. When these events are omitted from a scaling description the climate noise is consistent with a 1/f law on timescales from months to 105 years. If the events are included in the description, we obtain a model that is inherently non-stationary.
K. Rypdal
Earth Syst. Dynam., 7, 51–70, https://doi.org/10.5194/esd-7-51-2016, https://doi.org/10.5194/esd-7-51-2016, 2016
Short summary
Short summary
A conceptual model for the global temperature response to CO2 emissions is presented. Based on observation data, projections of future warming are computed for instructive emission scenarios. Delays in the initiation of global emission reduction is found to be the most important factor driving global warming over the next 2 centuries. The model is intended as a tool for communicating the issue to non-climatologists, students, policy makers, and the general public.
K. Rypdal
Earth Syst. Dynam., 6, 719–730, https://doi.org/10.5194/esd-6-719-2015, https://doi.org/10.5194/esd-6-719-2015, 2015
Short summary
Short summary
Human and natural forces drive climate change. If we have a model for the climate response to forcing, we can identify distinct fingerprints for each force, and their footprint in the observed global temperature can be determined by statistical analysis. This process is called attribution. This work examines the effect delays (long-range memory) in the climate response have on the magnitude of the various footprints. The magnitude of the human footprint turns out to be only weakly affected.
L. Østvand, T. Nilsen, K. Rypdal, D. Divine, and M. Rypdal
Earth Syst. Dynam., 5, 295–308, https://doi.org/10.5194/esd-5-295-2014, https://doi.org/10.5194/esd-5-295-2014, 2014
L. Østvand, K. Rypdal, and M. Rypdal
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esdd-5-327-2014, https://doi.org/10.5194/esdd-5-327-2014, 2014
Revised manuscript not accepted
Kristoffer Rypdal
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2017-93, https://doi.org/10.5194/esd-2017-93, 2017
Revised manuscript not accepted
Short summary
Short summary
The paper examines the assertion that limits to growth in the renewable energy sector can be inferred statistically from historical data for installed capacity of solar and wind power. This claim has been made in the peer reviewed scientific literature and has been subject to considerable media coverage. It is demonstrated here that rational selection between an exponential and a logistic growth model cannot be made from existing data for the historical evolution of global installed capacity.
Kristoffer Rypdal and Martin Rypdal
Earth Syst. Dynam., 7, 597–609, https://doi.org/10.5194/esd-7-597-2016, https://doi.org/10.5194/esd-7-597-2016, 2016
Short summary
Short summary
This comment on the paper by Lovejoy and Varotsos demonstrates that their methods for establishing nonlinearity in the global temperature response in climate models are flawed. One of their methods is based on an invalid approximation, which when corrected does not falsify the hypothesis that the response is linear. This conclusion is enforced when internal variability in the models are accounted for. The other results in their paper are also shown to be reproduced by linear-response models.
Tine Nilsen, Kristoffer Rypdal, and Hege-Beate Fredriksen
Earth Syst. Dynam., 7, 419–439, https://doi.org/10.5194/esd-7-419-2016, https://doi.org/10.5194/esd-7-419-2016, 2016
Short summary
Short summary
In this article it is discussed how temperature variability on centennial timescales and longer can be described in a simplistic way. By analysing the scaling in late Holocene temperature reconstructions and longer temperature records from Greenland and Antarctic ice cores, we find that the choice of model depends heavily on the data material and timescale one chooses to emphasize. Ignoring data beyond the Holocene seems plausible when predicting temperature, but not for other purposes.
Martin Rypdal and Kristoffer Rypdal
Earth Syst. Dynam., 7, 281–293, https://doi.org/10.5194/esd-7-281-2016, https://doi.org/10.5194/esd-7-281-2016, 2016
Short summary
Short summary
We analyse scaling in temperature signals for the late quaternary climate, and focus on the effects of regime shifting events such as the Dansgaard-Oeschger cycles and the shifts between glacial and interglacial conditions. When these events are omitted from a scaling description the climate noise is consistent with a 1/f law on timescales from months to 105 years. If the events are included in the description, we obtain a model that is inherently non-stationary.
K. Rypdal
Earth Syst. Dynam., 7, 51–70, https://doi.org/10.5194/esd-7-51-2016, https://doi.org/10.5194/esd-7-51-2016, 2016
Short summary
Short summary
A conceptual model for the global temperature response to CO2 emissions is presented. Based on observation data, projections of future warming are computed for instructive emission scenarios. Delays in the initiation of global emission reduction is found to be the most important factor driving global warming over the next 2 centuries. The model is intended as a tool for communicating the issue to non-climatologists, students, policy makers, and the general public.
K. Rypdal
Earth Syst. Dynam., 6, 719–730, https://doi.org/10.5194/esd-6-719-2015, https://doi.org/10.5194/esd-6-719-2015, 2015
Short summary
Short summary
Human and natural forces drive climate change. If we have a model for the climate response to forcing, we can identify distinct fingerprints for each force, and their footprint in the observed global temperature can be determined by statistical analysis. This process is called attribution. This work examines the effect delays (long-range memory) in the climate response have on the magnitude of the various footprints. The magnitude of the human footprint turns out to be only weakly affected.
L. Østvand, T. Nilsen, K. Rypdal, D. Divine, and M. Rypdal
Earth Syst. Dynam., 5, 295–308, https://doi.org/10.5194/esd-5-295-2014, https://doi.org/10.5194/esd-5-295-2014, 2014
L. Østvand, K. Rypdal, and M. Rypdal
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esdd-5-327-2014, https://doi.org/10.5194/esdd-5-327-2014, 2014
Revised manuscript not accepted
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Short summary
Empirical models for growth of renewable power are compared; the exponential, logistic, and power-law models. It is shown that the latter is a natural model for growth that slows down due to various constraints, yet not experiencing the effect of an upper limit defined by physical boundaries. One cannot conclude that this model is preferable based on the historical data only, but the predictions also align well with scenarios based on macroeconomic modelling that meet the two-degree target.
Empirical models for growth of renewable power are compared; the exponential, logistic, and...
