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Climate and Water Presentation of climate change and its impacts on quantity and quality of water Harri Koivusalo1, Teemu Kokkonen2, Ari Jolma3, Hanne Laine2, Olli Varis2 1 Finnish Forest Research Institute, Joensuu Research Unit 2 Helsinki University of Technology, Laboratory of Water Resources 3 Helsinki University of Technology, Laboratory of Geoinformation and Positioning Technology Terms of reference • Considering the potential impacts of climate variability and change on water resources, as well as uncertainties involved in assessing the impacts – To study and report how scenarios provided by regional climate models should be presented to the end users dealing with water resources management – To study and report how assessments based on environmental simulation models and regional climate scenarios can be condensed and presented to the endusers in a readily comprehensible form – To liaise with and receive feedback from those experts of the Association working on assessing the effects of climate change on water resources Background Climate and lake impacts in Europe (2003-2005) • Participants • Project outline PROJECTION Developing scenarios of the future climate ATTRIBUTION Quantifying the effects of historical changes in the climate on lake dynamics SIMULATION Modelling the effects of future changes in the climate on lake dynamics PREDICTION Assessing- the impact of the projected changes on lake dynamics IMPLICATION Policy and socio-economics Climate and lake modelling in CLIME Weather generator Observations HadAM3 UK Metoffice PROBE HadRM3p ECHAM4/OPYC3 Max-Planck, Germany UK Metoffice RCAO SMHI GWLF PROTECH CLIME-DSS • Visualises climate change across Europe • Summarises how climate change affects lake characteristics – Visualise the difference between control (1961-1990) and future (2071-2100) periods • How successful was the presentation in CLIME-DSS? Expert opinions about dissemination of climate change Esurveyspro survey service http://www.esurveyspro.com Respondents a) Southern Europe Northern Europe Caucasus / Middle East Other (Central Europe / Turkey) Eastern Europe • Internet survey to > 160 people in RA VI countries • 37 replies Western Europe 0 b) 10 20 30 Governance Research Consultancy Other Teaching Industry 0 c) 10 20 30 40 50 hydrology meteorology water and sanitary engineering information technology agricultural and forest sciences 0 10 20 30 Respondents % 40 50 Wintertime prepitation (RCAO-E) • Clarity of the mapbased presentation of precipitation? sufficiently All North Europe Outside North Europe well poorly 0 10 20 30 40 50 Respondents % 60 70 80 Different ways representing climate change impact on precipitation Respondents % 50 change in the mean annual precipitation 40 30 change in the mean seasonal precipitation 20 change in the minimum annual precipitation 10 re so le va m nt ew ha tr el ev an no t nre le va nt no op in io n re le va nt change in the maximum short term precipitation 50 predicted mean annual future precipitation 40 30 predicted mean seasonal future precipitation 20 predicted minimum annual future precipitation 10 predicted minimum seasonal future precipitation re le so va m nt ew ha tr el ev an no t nre le va nt no op in io n re le va nt 0 ve ry b) Respondents % • Absolute precipitation in future change in the minimum seasonal precipitation 0 ve ry • Change between future (20702100) and control (1960-1990) periods a) predicted maximum short term future precipitation • Clarity of the mapbased presentation of air temperature? Summertime air temperature sufficiently All Hydrologists Meteorologists poorly well 0 10 20 30 40 Respondents % 50 60 Different ways representing climate change impact on air temperature • Absolute air temperature in future b) Respondents % • Change between future (2070-2100) and control (1960-1990) periods a) 60 50 40 30 20 10 re le so va m nt ew ha tr el ev an no t nre le va nt no op in io n 50 40 30 20 10 re le so va m nt ew ha tr el ev an t no nre le va nt no op in io n re le va nt 0 ve ry Respondents % ve ry re le va nt 0 change in the mean annual air temperature change in the mean seasonal air temperature change in the annual maximum air temperature change in the seasonal maximum air temperature change in the annual minimum air temperature change in the seasonal minimum air temperature predicted mean annual future air temperature predicted mean seasonal future air temperature predicted annual maximum future air temperature predicted seasonal maximum future air temperature predicted annual minimum future air temperature predicted seasonal minimum future air temperature • Clarity in presenting seasonal values of hydrometeorological variables in selected location? informative somewhat informative very informative no opinion non-informative 0.00 10.00 20.00 30.00 Respondents % 40.00 50.00 • Clarity in presenting range of seasonal runoff in selected location? informative somewhat informative very informative no opinion non-informative 0.00 10.00 20.00 30.00 Respondents % 40.00 50.00 • Clarity in presenting change in climate depicted as climate migration from one region to another? informative somewhat informative very informative no opinion non-informative 0.00 10.00 20.00 30.00 Respondents % 40.00 50.00 Relevance of selected lake variables Different ways representing climate change impact on water quality 50 40 30 20 10 Respondents Respondents % % • Change between future and control algae level 50 60 40 50 30 40 20 30 10 20 10 0 0 ve ve ry ry re re le lev va a nt nt r r so so ele elev m me va an ew w nt t ha ha tr tr el ele ev v a a n no o nt nt n- nre re le lev va a nt nt no no op op in ini io on n b) a) re le so va m nt ew ha tr el ev an t no nre le va nt no op in io n re le va nt 0 ve ry • Change between future and control nutrient level Respondents % a) change in the load change in the nutrient load change in the nutrient load change in the nutrient load change in the nutrient load change in the nutrient load mean annual nutrient mean seasonal maximum annual maximum seasonal minimum annual minimum seasonal predicted mean annual nutrient load (in the future) change in the mean annual algae predicted mean seasonal nutrient concentration load change in the mean seasonal algae predicted maximum annual nutrient concentration load change in the maximum annual predicted maximum seasonal algae concentration nutrient load change in the maximum seasonal predicted minimum annual nutrient algae concentration load change in the minimum annual predicted minimum seasonal nutrient algae concentration load change in the minimum seasonal algae concentration Change in hydrometeorological variables → Change in a lake variable Current level of a lake variable in a season Projected level of a lake variable Probability distributions characterise current and projected levels of a lake variable • Clarity in presenting the current and predicted distributions for average summer time DOC concentration? a) b) while direction of change can be detected it is not easy no opinion direction of change can be easily detected while change in variability can be detected it is not easy no opinion change in variability can be easily detected direction of change cannot be detected change in variability cannot be detected 0 10 20 30 Respondents % 40 0 10 20 30 Respondents % 40 50 Conclusions • Map-based tool well suited for disseminating RCM results – view large areas or select a point for detailed examination • Coloured visualisations and tabulated information equally informative and useful • Methods behind the visualisations and tables should be more transparent • Web pages: http://clime.tkk.fi/jrc/ – Contact: • [email protected] • [email protected] Future activities on “Climate and Water” in WMO RA VI WGH • Role of reservoirs in the changing climate – Implications on water balance, greenhouse gases, etc. – Exploitation of global GIS data – Reservoirs and climate change in RA VI countries • Adaptation to climate change – Water resources management in changing climate – Use of reservoirs in the adaptation – Flood risk mitigation, drought risk alleviation MANY THANKS TO ALL RESPONDENTS River Iijoki, 65°22’ 26°47’, 27 Nov 08