Matulla, Christoph* Matulla, Christoph* Central Institute for Meteorology and Geodynamics, Austria Namyslo, Joachim** Namyslo, Joachim** German National.

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Presentation transcript:

Matulla, Christoph* Matulla, Christoph* Central Institute for Meteorology and Geodynamics, Austria Namyslo, Joachim** Namyslo, Joachim** German National Meteorological Service, Germany Andre, Konrad Central Institute for Meteorology and Geodynamics, Austria Chimani, Barbara Central Institute for Meteorology and Geodynamics, Austria * ** STS 49TRA2014 Paris 14‒17 avril 2014 D ESIGN GUIDELINE FOR A C LIMATE P ROJECTION D ATA BASE AND SPECIFIC CLIMATE INDICES FOR R OADS : C LI PD A R

Please insert here your affiliation logo First author’s name Structure of the presentation  Introduction  Data and Methods  Results  Outlook STS 492TRA2014 Paris 14‒17 avril 2014 Matulla et al. +

Please insert here your affiliation logo First author’s name Data and Methods  Regional scale past & climate change projections  17 members (A1B) temperature, precipitation  Continental scale past & climate change projections  8 members A1B, A2 temperature 850hPa  Cause Effect Tensor: CET2 & Climate Indices: CIs STS 493TRA2014 Paris 14‒17 avril 2014 Matulla et al. CET2: CIs→Assets

Please insert here your affiliation logo First author’s name Possible future of cold winters in Fennoscandia Select coldest past seasons Apply an EOF analysis to continental past data Calculate the first future time coefficient Compare the near and far future time coefficient to the past STS 494TRA2014 Paris 14‒17 avril 2014 Matulla et al.

Please insert here your affiliation logo First author’s name Select hottest past seasons Apply an EOF analysis to continental past data Calculate the first future time coefficient Compare the near and far future time coefficient to the past Possible future of hot summers in the Iberian Peninsula STS 495TRA2014 Paris 14‒17 avril 2014 Matulla et al.

Please insert here your affiliation logo First author’s name Cold index days in Central Europe Climate indices (CIs) CI (frost days): T min <0°C CI (ice days): T max <0°C Compare the far future (2071‒2100) to past (1961‒1990) conditions STS 496TRA2014 Paris 14‒17 avril 2014 Matulla et al. days Tmax < 0°C days Tmin < 0°C Frostdays Icedays

Please insert here your affiliation logo First author’s name Climate indices (CIs) CI (summer days): T max ≥25°C CI (hot days): T max ≥ 30°C Compare the far future (2071‒2100) to past (1961‒1990) conditions Warm index days in Central Europe STS 497TRA2014 Paris 14‒17 avril 2014 Matulla et al. days Tmax ≥ 30°C Summerdays Hotdays days Tmax ≥ 25°C

Please insert here your affiliation logo First author’s name Climate indices (CIs) CI (hot days and tropical nights): T max ≥30°C and T night,min >20°C Compare the near (2021‒2050) and far (2071‒2100) future to the past (1961‒1990) conditions Potential rutting days in Central Europe STS 498TRA2014 Paris 14‒17 avril 2014 Matulla et al. Near future (2021‒2050) Far future (2071‒2100)

Please insert here your affiliation logo First author’s name Climate indices (CIs) CI (mass movement day): P day >25.6 mm and P 3day >37.3 mm Compare the near (2021‒2050) and far (2071‒2100) future to the past (1961‒1990) conditions Potential “landslides” in Central Europe STS 499TRA2014 Paris 14‒17 avril 2014 Matulla et al. Near future (2021‒2050) Far future (2071‒2100)

Please insert here your affiliation logo First author’s name Design Guideline - principles STS 4910TRA2014 Paris 14‒17 avril 2014 Matulla et al.  Internal climate variability: Averaging of climate projection data (periods of 30 y, at least 10 y)  Ensemble building: consider model diversity, many members (enable 15 th /85 th Percentiles)  Downscaling (proposal) = = statistical regionalization + bias correction  Ensemble Approach (make ensemble statistics)  Use preferably simple impact models (otherwise: only a case study may be possible) ……

Please insert here your affiliation logo First author’s name Outlook  Enlarge the region stepwise by consistently including further European countries  Use new scenarios (RCPs of EURO-CORDEX)  Avoid the mixing of datasets  Ensure highest quality of data – no breaks along borders  Include air traffic and railway transport  Expand the analysis to further CIs (e.g. damage of bridges, water to street level) STS 4911TRA2014 Paris 14‒17 avril 2014 Matulla et al.

STS 49TRA2014 Paris 14‒17 avril 2014 T HANK YOU FOR YOUR ATTENTION ! ‒ The CliPDaR team ‒ Acknowledgements: BMVBS/German Joint Research Programme KLIWAS: Impacts of climate change on Waterways and navigation - Searching for options of adaptation Autobahnen- und Schnellstrassen-Finanzierungs- AG Federal Ministry of Transport, Innovation and Technology of the Republic of Austria German Federal Highway Research Institute