Helmholtz-Zentrum Geesthacht, 2017-03-29

Tailoring climate information to the local scale and impact modeling activities

WP4 interfaces the results from long climate integrations in WP2 and WP3, uncertainty analysis in WP5 and impact modelling requirements of WPs 6, 7, 8, 12, 13 and 14. As part of this processes an investigation of user requirement has been performed.

For this purpose a “user requirement form” has been devised. Results of this user questionnaire have been analysed. The far majority of the requests concern daily data on temperature (daily mean, minimum and maximum), precipitation, longwave and shortwave radiation and humidity (absolute and relative). Some users also requested information on surface winds, pressure (mean sea level as well as surface pressure). A minority of the user also needed other types information, like snow depth, or derived statistics (like number of heatwaves, number of frost days, number of consecutive dry days, changes in extremes precipitation).

There are two modelling streams in IMPACT2C: one based on regional climate model simulations at 25 km resolution from the ENSEMBLES project (the so-called “Fast-track”), and one based on EURO-CORDEX simulations at 12 km resolution (the so-called “Slow-track”). To facilitate the use of the data, all modelling data has been provided to the user community in a common data format (common grid, and time calendar, common meta data).

RCM Driving GCM RCPs
CSC-REMO2009 MPI-ESM-LR 2.6, 4.5, 8.5
SMHI-RCA4 EC-EARTH 2.6, 4.5, 8.5
SMHI-RCA4 HadGEM2-ES 4.5, 8.5
EURO-CORDEX simulations used in IMPACT2C
Systematic errors in the climate models lead to biases in the outcome of model simulations. Many applications (e.g. impact models) require data that is corrected for these model biases, in particular if the impact model is non-linearly dependent on the meteorological input. This is for instance the case if the system is very dependent on whether or not a certain threshold is exceeded for a specific variable. Therefore, large efforts have been made on creating a data set that is corrected for systematic biases.

After this correction indeed the modelled distribution and the observed one match very well over most part of Europe. Bias correction could only be done for variables for which long term gridded observations are available. For temperature (mean, minimum and maximum) we use E-OBS, for radiation we used WFDEI (WATCH forcing data Era-interim, which is a blend between observations and model results). A small effort has been put on correction of surface wind biases for wind power estimates.

The drawback of bias correction is that it may lead to loss of consistency between meteorological variables. E.g., bias correction of temperature implies a correction of absolute humidity or relative humidity or both in order to retain physical consistency. Based on physical arguments, we have chosen to adjust the absolute humidity, and provided this corrected field to the users.

A large data base of processed model results as detailed above has been created, containing 5 processed model results for ENSEMBLES, and 11 processed model results for EURO-CORDEX model results. For each model simulation 23 model fields (corrected as well as uncorrected) have been provided for EURO-CORDEX model results and 18 fields for ENSEMBLES model results.

From these processed model data 11 climate change indices have been computed, covering heatwaves, cold spells, and heavy precipitation. In addition, we investigated changes in surface humidity which is an indicator of potential changes in the intensity of heavy showers.

Figure 1. Changes in the number of frost days derived from the two RCP2.6 EURO-CORDEX simulations (click image to enlarge) Figure 1. Changes in the number of frost days derived from the two RCP2.6 EURO-CORDEX simulations (click image to enlarge)


KNMI (lead)


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