Calibrating regionally downscaled precipitation over Norway through quantile-based approaches
Journal article, 2016

Dynamical downscaling of earth system models is intended to produce high-resolution climate in- formation at regional to local scales. Current models, while adequate for describing temperature distributions at relatively small scales, struggle when it comes to describing precipitation distributions. In order to better match the distribution of observed precipitation over Norway, we consider approaches to statistical adjustment of the output from a regional climate model when forced with ERA-40 reanalysis boundary conditions. As a second step, we try to correct downscalings of historical climate model runs using these transformations built from downscaled ERA-40 data. Unless such calibrations are successful, it is difficult to argue that scenario-based downscaled climate projections are realistic and useful for decision makers. We study both full quantile cali- brations and several different methods that correct individual quantiles separately using random field models. Results based on cross-validation show that while a full quantile calibration is not very effective in this case, one can correct individual quantiles satisfactorily if the spatial structure in the data are accounted for. Interestingly, different methods are favoured depending on whether ERA-40 data or historical climate model runs are adjusted.


David Bolin

University of Gothenburg

Chalmers, Mathematical Sciences, Mathematical Statistics

Arnoldo Frigessi

Peter Guttorp

Ola Haug

Elisabeth Orskaug

Ida Scheel

Jonas Wallin

University of Gothenburg

Chalmers, Mathematical Sciences, Mathematical Statistics

Advances in Statistical Climatology, Meteorology and Oceanography

2364-3587 (eISSN)

Vol. 2 39-47

Subject Categories


Probability Theory and Statistics

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