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Earth System Dynamics An interactive open-access journal of the European Geosciences Union

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Earth Syst. Dynam., 7, 851-861, 2016
https://doi.org/10.5194/esd-7-851-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
10 Nov 2016
The use of regression for assessing a seasonal forecast model experiment
Rasmus E. Benestad1, Retish Senan2, and Yvan Orsolini3 1Norwegian Meteorological Institute, Oslo, 0313, Norway
2European Centre for Medium-range Forecasts, Reading, UK
3Norwegian Institute for Air Research, Kjeller, Norway
Abstract. We show how factorial regression can be used to analyse numerical model experiments, testing the effect of different model settings. We analysed results from a coupled atmosphere–ocean model to explore how the different choices in the experimental set-up influence the seasonal predictions. These choices included a representation of the sea ice and the height of top of the atmosphere, and the results suggested that the simulated monthly mean air temperatures poleward of the mid-latitudes were highly sensitivity to the specification of the top of the atmosphere, interpreted as the presence or absence of a stratosphere. The seasonal forecasts for the mid-latitudes to high latitudes were also sensitive to whether the model set-up included a dynamic or non-dynamic sea-ice representation, although this effect was somewhat less important than the role of the stratosphere. The air temperature in the tropics was insensitive to these choices.

Citation: Benestad, R. E., Senan, R., and Orsolini, Y.: The use of regression for assessing a seasonal forecast model experiment, Earth Syst. Dynam., 7, 851-861, https://doi.org/10.5194/esd-7-851-2016, 2016.
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Short summary
Seasonal predictions have been challenging for mid-latitude regions such as Europe, and we suspect that one reason may be due to subjective choices in how the forecast models are configured. We tested how (1) the inclusion and omission of the representation of the stratosphere affect the predictions and (2) the degree of detail in the sea-ice description. The test was carried out with a set of simulations (experiments) using a technique known as "factorial regression".
Seasonal predictions have been challenging for mid-latitude regions such as Europe, and we...
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