The use of regression for assessing a seasonal forecast model experiment
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 cho...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2016-11-01
|
| Series: | Earth System Dynamics |
| Online Access: | http://www.earth-syst-dynam.net/7/851/2016/esd-7-851-2016.pdf |
| Summary: | 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. |
|---|---|
| ISSN: | 2190-4979 2190-4987 |