1. Data collection and 1 st preprocessing Action 2.4-2.5 : Large scale Hydrological cycle Valerio Lucarini (1,2) Ida Kriegerová (1) Róbert Danihlík (1) (1)CINFAI Unit of Camerino, Italy (2)University of Camerino, Italy Bratislava, June 27, 2006 HYDROCARE Hydrological cycle of the CADSES region

2. 2 Area of interest CADSES region defined by INTERREG III B CADSES Neighbourhood Programme The area bounded by 0° - 40° longitude and 35° - 60° latitude HYDROCARE Hydrological cycle of the CADSES region Bratislava, June 27, 2006

3. 3 Data collection  ERA-40 and NCEP/NCAR reanalysis  Global Climate Models Data – IPCC 4 th Climate Model Data Portal  Regional Climate Models Control Data – The PRUDENCE project  Observation data – discharge data – Global Runoff Data Centre Daily (monthly) values of  Total precipitation  Evaporation  Runoff Period of 01.01.1961 – 31.12.2000 HYDROCARE Hydrological cycle of the CADSES region Bratislava, June 27, 2006

4. 4 Data preprocessing I Danube river basin – 807 000 km 2 Calculation of E (evaporation), P (precipitation), P-E (balance) based on data from RCMs (The Prudence project) Period of 1961 – 1990 Driving data (HadAM3H A2) provided by Met Office, Hadley Center UK Discharge data (observed) provided by Global Runoff Data Centre GIS data using ArcGis 9.0 HYDROCARE Hydrological cycle of the CADSES region Bratislava, June 27, 2006 Basic equation of Hydrology:

5. 5 HYDROCARE Hydrological cycle of the CADSES region Bratislava, June 27, 2006 Res.-dependent No. cells Basin Area/ size of a cell 2000 cells if 20 Km x 20 Km Cells defined via Voronoi polyg. Area-weighted fields Danube catchment

6. 6 HYDROCARE Hydrological cycle of the CADSES region Bratislava, June 27, 2006 Results: average balance vs.variability

7. 7 HYDROCARE Hydrological cycle of the CADSES region Bratislava, June 27, 2006 Precipitation MODELSDr.data CLM_GKSS_germany 0,91 HIRHAM_METNO_norway 0,90 CHRM_ETH_swiss 0,87 PROMES_UCM_spain 0,87 RACMO_KNMI_netherland 0,93 REMO_germany 0,88 SMHI_25_sweden 0,84 SMHI_50_sweden 0,89 DMI_12_denmark 0,85 DMI_25_denmark 0,87 DMI_50_denmark 0,80 ICTP_italy 0,84 Correlation coefficient: Models vs. driving data and Precipitation vs Evaporation Normalized precipitation P vs E DRIVING DATA0,90 CLM_GKSS_germany0,81 HIRHAM_METNO_norway0,58 CHRM_ETH_swiss0,84 PROMES_UCM_spain0,04 RACMO_KNMI_netherland0,69 REMO_germany0,82 SMHI_25_sweden0,87 SMHI_50_sweden0,89 DMI_12_denmark0,91 DMI_25_denmark0,90 DMI_50_denmark0,92 ICTP_italy0,80

8. 8 HYDROCARE Hydrological cycle of the CADSES region Bratislava, June 27, 2006 Evaporation MODELSDr.data CLM_GKSS_germany 0,66 HIRHAM_METNO_norway 0,53 CHRM_ETH_swiss 0,70 PROMES_UCM_spain -0,16 RACMO_KNMI_netherland 0,71 REMO_germany 0,72 SMHI_25_sweden 0,75 SMHI_50_sweden 0,79 DMI_12_denmark 0,73 DMI_25_denmark 0,76 DMI_50_denmark 0,75 ICTP_italy 0,66 Correlation coefficient: Models vs. driving data Time correlations: normalized evaporation

9. 9 HYDROCARE Hydrological cycle of the CADSES region Bratislava, June 27, 2006 Water balance MODELSdr.dataobs.data DRIVING DATA 10,02 CLM_GKSS_germany0,920,02 HIRHAM_METNO_norway0,920,05 CHRM_ETH_swiss0,890,08 PROMES_UCM_spain0,900,06 RACMO_KNMI_netherland0,930,11 REMO_germany0,860,15 SMHI_25_sweden0,85-0,08 SMHI_50_sweden0,890,08 DMI_12_denmark0,86-0,01 DMI_25_denmark0,85-0,01 DMI_50_denmark0,780,14 ICTP_italy0,850,19 Correlation coefficient: Models vs. driving data and observed data Time correlations: normalized balance

10. 10 Bratislava, June 27, 2006