Simulations to explore impact of calibration of model parameters on climate sensitivity

Raw data used in study, in preparation, by Tett et al. PP data, is a format used by the Met Office for its weather and climate model data output. Data can be read by the Iris Python module from conda-forge. See https://scitools.org.uk/iris/docs/latest/ for documentaton on the package.

## Access ##
This dataset is held in the Edinburgh DataVault, directly accessible only to authorised University of Edinburgh users. External users are very welcome to request access to a copy of the data by contacting the Principal Investigator, Contact Person or Data Manager named on this page once the paper has been accepted. University of Edinburgh users who wish to have direct access should consult the information about retrieving data from the DataVault at: http://www.ed.ac.uk/is/research-support/datavault .

This study investigates the hypothesis that a significant portion of spread in climate model projections of sea ice is due to poorly-constrained model parameters. New automated methods for optimization are applied to multiple parameters and the strength of the climate feedbacks investigated with a suite of standard coupled simulations. This dataset supports a manuscript which, at the time of deposit, is still in preparation.

Tett, S; Mineter, M "Simulations to explore impact of calibration of model parameters on climate sensitivity" [dataset] (2019) Edinburgh DataVault. https://doi.org/10.7488/84b585fc-57d2-4e5a-b3a3-694f70534a02