CLIPC - Bias-corrected data

The CLIPC project provides access to climate information of direct relevance to a wide variety of users, from scientists to policy makers and private sector decision makers. Information will include data from satellite and in-situ observations, climate models and re-analyses, transformed data products to enable impacts assessments and climate change impact indicators.

This page documents the datasets produced by the Meteorologisk institutt within the CLIPC project under the deliverable ”D6.1 : Climate model data for Europe, bias-corrected when necessary, for CCII-T1 calculation. Documented dataset”. The deliverable is focussing on bias-corrected data at three different resolutions:

1. Global climate model (GCM) data interpolated to a common 2° × 2° grid,
2. Regional climate model (RCM) data at the EURO-CORDEX 0.44° (~ 50 km × 50 km) grid
3. RCM data at the EURO-CORDEX 0.11° (~ 12 km × 12 km) grid

The Meteorologisk institutt will provide data for 2. and 3.

Currently, the bias-corrected datasets are available through links on this page (see below) and at the CLIPC milestone page but will eventually become available through ESGF. The datasets now published as CLIPC Deliverable D6.1 is one of the first ensemble of multi-method bias correction datasets derived from the published EURO-CORDEX RCM ensemble at two spatial resolutions and complemented by bias corrected GCM data.

• Bias corrected EUR44-CORDEX and EUR11-CORDEX RCM data from SMHI are available here
• Bias corrected EUR11-CORDEX RCM data from Met Norway are available at the Arctic Data Centre ( Thredds catalog)

NOTE THAT THIS IS ARE PRELIMINARY DATA PUBLICATIONS. DATA FORMAT, AVAILABILITY AND CONTENT MAY CHANGE WITHOUT NOTICE.
PLEASE: REPORT, IF YOU FIND SOMETHING STRANGE IN THE DATA to Andreas Dobler

All EURO-CORDEX simulations are published under the CORDEX terms of use. Until further notice, the terms of use for the bias-corrected data are the same as those from the uncorrected EURO-CORDEX simulations obtained from ESGF servers (and an overview on the restriction will follow as soon as the ESGF servers are online again).

We acknowledge the following grants and work. Please include them when using or redistributing the bias-corrected CLIPC data.

• The CLIPC EU project (grant agreement #607418)
• The EURO4M FP7 project (grant agreement #242093) for the EURO-CORDEX 0.11° reference/training data MESAN
• Gudmundsson, L., Bremnes, J. B., Haugen, J. E., and Engen-Skaugen, T., 2012: Technical Note: Downscaling RCM precipitation to the station scale using statistical transformations – a comparison of methods, Hydrol. Earth Syst. Sci., 16, 3383-3390, doi:10.5194/hess-16-3383-2012 for the bias-correction method (quantile mapping).

The method from the Meteorologisk institutt uses the R package qmap: Statistical transformations for post-processing climate model output. Basically, it performs a quantile mapping of the simulated time series to observed ones for each grid point. It does so by estimating values for regularly spaced quantiles of the empirical cumulative distribution function and using these estimates to perform a quantile mapping. Details on the method can be found in Gudmundsson et al. (2012, doi:10.5194/hess-16-3383-2012). The set-up includes a linear interpolation between the fitted transformed values, and simulated values lying outside the range of the training period (e.g., from climate projections) are extrapolated using the correction found for the highest quantile of the training period, as suggested by Boé et al. (2007, doi: 10.1002/joc.1602). Furthermore, the method includes an adjustment of wet-day frequencies.

So far, the GCM-RCM model combinations listed in Table 1 have become available at 0.11° from EURO-CORDEX and have been corrected. The bias correction has been applied to the variables precipitation (pr) and near-surface air temperature (tas). Further corrections will include daily minimum near-surface air temperature (tasmin) and daily maximum near-surface air temperature (tasmax).

Andreas Dobler 2015/06/30 09:02