Articles | Volume 6, issue 2
https://doi.org/10.5194/ascmo-6-91-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ascmo-6-91-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
17 Sep 2020
| 17 Sep 2020
A new energy-balance approach to linear filtering for estimating effective radiative forcing from temperature time series
Department of Mathematics, University of Exeter, Exeter, UK
David B. Stephenson
Department of Mathematics, University of Exeter, Exeter, UK
Peter A. Stott
Department of Mathematics, University of Exeter, Exeter, UK
Met Office Hadley Centre, Exeter, UK
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Short summary
We have developed a novel and fast statistical method for diagnosing effective radiative forcing (ERF), a measure of the net effect of greenhouse gas emissions on Earth's energy budget. Our method works by inverting a recursive digital filter energy balance representation of global climate models and has been successfully validated using simulated data from UK Met Office climate models. We have estimated time series of historical ERF by applying our method to the global temperature record.
We have developed a novel and fast statistical method for diagnosing effective radiative forcing...
