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Earth System Dynamics An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/esd-2020-6
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-2020-6
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  12 Mar 2020

12 Mar 2020

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A revised version of this preprint was accepted for the journal ESD and is expected to appear here in due course.

Calibrating large-ensemble European climate projections using observational data

Christopher H. O'Reilly1,2, Daniel J. Befort1, and Antje Weisheimer1,2 Christopher H. O'Reilly et al.
  • 1Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford
  • 2NCAS-Climate, Department of Physics, University of Oxford

Abstract. This study examines methods of calibrating projections of future regional climate using large single model ensembles (the CESM Large Ensemble and MPI Grand Ensemble), applied over Europe. The three calibration methods tested here are more commonly used for initialised forecasts from weeks up to seasonal timescales. The calibration techniques are applied to ensemble climate projections, fitting seasonal ensemble data to observations over a reference period (1920–2016). The calibration methods were tested and verified using an imperfect model approach using the historical/RCP 8.5 simulations from the CMIP5 archive. All the calibration methods exhibit a similar performance, generally improving the out-of-sample projections in comparison to the uncalibrated (bias-corrected) ensemble. The calibration methods give results that are largely indistinguishable from one another, so the simplest of these methods, namely Homogeneous Gaussian Regression, is used for the subsequent analysis. An extension to this method – applying it to dynamically decomposed data (in which the underlying data is separated into dynamical and residual components) – is also tested. The verification indicates that this calibration method produces more reliable and accurate projections than the uncalibrated ensemble for future climate over Europe. The calibrated projections for temperature demonstrate a particular improvement, whereas the projections for changes in precipitation generally remain fairly unreliable. When the two large ensembles are calibrated using observational data, the climate projections for Europe are far more consistent between the two ensembles, with both projecting a reduction in warming but a general increase in the uncertainty of the projected changes.

Christopher H. O'Reilly et al.

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Christopher H. O'Reilly et al.

Christopher H. O'Reilly et al.

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Latest update: 29 Sep 2020
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Short summary
This study examines how the output of large single model ensembles can be calibrated using observational data to provide improved future projections over Europe. Using an out-of-sample test, the calibration techniques are shown to generally improved the reliability of European climate projections for the next 40 years, particularly for regional surface temperatures.
This study examines how the output of large single model ensembles can be calibrated using...
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