Daily values of mean, minimum, maximum temperature and total precipitation from the SMHI RCA-ECHAM5 transient climate change simulation for the period 1961-2099 have been corrected for biases according to Dosio and Paruolo, 2011: Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: Evaluation on the present climate, J. Geophys. Res., 116, D16106, DOI: 10.1029/2011JD015934. These data have been produced from a transient climate change simulation for the period 1951-2099 driven by the coupled global model ECHAM5/OMI of the Max-Planck-Institut für Meteorologie according to the SRES A1B marker scenario. 121 different meteorological fields are stored in the database from this simulation; of these, 7 are saved 4 times daily, 4 are saved twice daily, and the rest is saved once daily. This simulation has been produced as part of Research Theme 3 (RT3) of the EU FP6 project ENSEMBLES (http://ensemblesrt3.dmi.dk/). Information on the simulations can be found at http://ensemblesrt3.dmi.dk/, in the special issue 44 of Climate Research (2010), or in the ENSEMBLES final report available at http://http://ensembles-eu.metoffice.com/docs/Ensembles_final_report_Nov09.pdf.
Lineage: Simulation data from a regional numerical climate model with lateral and sea-surface conditions determined from the output of the ECHAM5 coupled global model. The simulation was produced at the Swedish Meteorological and Hydrological Institute (http://www.smhi.se/en) with the regional climate model RCA3.0. (UUID: fcc9011e-5e33-11e1-9105-0017085a97ab). Daily values of mean, minimum, maximum temperature and total precipitation from this simulation have been corrected for biases according to Dosio and Paruolo, 2011: Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: Evaluation on the present climate, J. Geophys. Res., 116, D16106, DOI: 10.1029/2011JD015934
Dosio, Alessandro (2026): Bias corrected high resolution temperature and precipitation projection for Europe in daily temporal resolution from the SMHI RCA regional climate model driven by boundary conditions from the ECHAM5/OMI global circulation model according to SRES A1B scenario, 1961-2099 (ENSEMBLES).. European Commission, Joint Research Centre [Dataset] doi: 10.2905/JRC.B98M020 PID: http://data.europa.eu/89h/jrc-climate-smhirca_a1b_echam5-r3_eobs_1961-1990_1961-2100
air temperatureatmosphereatmospheric precipitationclimatic alterationclimatic changeclimatic experimentclimatologygreenhouse gasman-made climate changemeteorological geographical featuresmeteorological parametermeteorology
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A statistical bias correction technique is applied to a set of
high resolution climate change simulations for Europe from 11 state-of-theart
regional climate models (RCMs) from the project ENSEMBLES. Modelled
and observed daily values of mean, minimum and maximum temperature
and total precipitation are used to construct transfer functions for the
period 1961-1990, which are then applied to the decade 1991-2000, where the
results are evaluated. By using a large ensembles of model runs and a long
construction period, we take into account both inter-model variability, and
longer (e.g. decadal) natural climate variability. Results show that the technique
performs successfully for all variables over large part of the European
continent, for all seasons. In particular, the probability distribution functions
(PDFs) of both temperature and precipitation are greatly improved, especially
in the tails, i.e., increasing the capability of reproducing extreme events.
When the statistics of bias corrected results are ensemble-averaged, the result
is very close to the observed ones. The bias correction technique is also
able to improve statistics that depend strongly on the temporal sequence of
the original field, such as the number of consecutive dry days and the total
amount of precipitation in consecutive heavy precipitation episodes, which
are quantities that may have a large influence on e.g. hydrological or crop
impact models. Bias-corrected projections of RCMs are hence found to be
potentially useful for the assessment of impacts of climate change over Europe.
A statistical bias correction technique is applied to twelve high-resolution climate change simulations of temperature and precipitation over Europe, under the SRES A1B scenario, produced for the EU project ENSEMBLES. The bias correction technique is based on a transfer function, estimated on current climate, which affects the whole Probability Distribution Function (PDF) of variables, and which is assumed constant between the current and future climate. The impact of bias correction on 21st Century projections, their inter-model variability, and the climate change signal is investigated, with focus being on discrepancies between the original and the bias-corrected results. As assessing the impact of climate change is significantly dependent on the frequency of extreme events, we also analyze the evolution of the shape of the PDFs, and extreme events indices. Results show that the ensemble mean climate change signal and its inter-model variability are generally conserved. However, the impact of the bias correction varies amongst regions, seasons and models, and differences up to 0.5 C for the summer temperature climate change signal are found in Southern Europe. Finally the bias correction is found to influence the probability of extreme events like extremely hot or frost days, which also impacts the climate change signal.
