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Results:

• 1. VI_2020_004

  et al., 2002), lava flows at Etna (Favalli et al., 2009) and Fogo Volcano (Richter et al., 2016); for volcanogenic floods at Öræfajökull volcano (Pagneux et al., 2015). Probabilistic hazard maps for tephra fallout have been produced for Mt. Etna (Scollo et al., 2013), Campi Flegrei (Costa et al., 2009), Ruapehu (Bonadonna et al., 2005; Hurst & Smith, 2004), Indonesian volcanoes (Jenkins et al /media/vedurstofan-utgafa-2020/VI_2020_004.pdf

• 2. Kjellstrom_Erik_CES_2010

  AN ENSEMBLE OF REGIONAL CLIMATE CHANGE SCENARIOS FOR THE NORDIC COUNTRIES Erik Kjellström, Martin Drews, Jens Hesselbjerg Christensen, Jan Erik Haugen, Hilde Haakenstad and Igor Shkolnik A changing climate in the Nordic region Climate change in Northern Sweden: Comparing 2071-2100 vs 1961-1990 (SRES A1B) Lind & Kjellström, 2008 A changing wind climate in the Nordic region? DJF MAM JJA SON /media/ces/Kjellstrom_Erik_CES_2010.pdf

• 3. Kok_1-scenarios-lecture-1

  for communication. A Project goal - exploration vs decision support: I. Inclusion of norms? : descriptive vs normative II. Vantage point: forecasting vs backcasting III. Subject: issue-based, area-based, institution-based IV. Time scale: long term vs short term V. Spatial scale: global/supranational vs national/local Scenarios – types (van Notten et al., 2003) WHY? and FOR WHOM? B Process design /media/loftslag/Kok_1-scenarios-lecture-1.pdf

• 4. Eyjafjallajokull_SK_20101214_1

  obscure observations incl. radar. Interaction with wind is poorly understood  hard to extract a meaningful top height. Dry ash has low reflectivity Plume height during eruption Dry ash shows poor radar reflectiivity IMO researchers are looking carefully at the plume. complex vertical structure plume height modulated by strong winds SO2 vs Ash Ash resuspension – possible problem On June 4-5th /media/vedurstofan/myndasafn/Eyjafjallajokull_SK_20101214_1.pdf

• 5. VI_2015_007

  using best index flood model for each set: µi(D = 0) vs. bµi(D = 0). Solid red line corresponds to the 1:1 line. Top-left: IFM-CLU with model no. 11. Top-right: IFM-ROI with model no. 5. Bottom-left: IFM-WaSiM with model no. 4. 27 4.3.2 Flood quantiles estimation The different variations of the IFM proposed in this study, i.e. IFM-CLU, IFM-ROI and IFM- WaSiM, developed with twelve index flood /media/vedurstofan/utgafa/skyrslur/2015/VI_2015_007.pdf

• 6. VI_2020_011_en

  /media/vedurstofan-utgafa-2020/VI_2020_011_en.pdf

• 7. Kok_2-scenarios-lecture-2

  -11:30 Practical examples + conclusions • Exploratory scenario development – SAS approach • Group model building - Fuzzy Cognitive Maps • Normative scenario development - Backcasting Conclusions LECTURE 2 Scenario development In practice Content Lecture 2: scenario development in practice •Story-And-Simulation approach •Fuzzy Cognitive Mapping •Backcasting A Project goal - exploration vs /media/loftslag/Kok_2-scenarios-lecture-2.pdf

• 8. Lettenmaier_Dennis_CES_2010pdf

  21 15% 55 26 5% 5546% of world's GDP 2233% of world’s population 10%0%Runoff decreases by Continental U.S. and Alaska All scenarios Top 200 basins Precipitation change per degree T change vs evaporation change per degree T All scenarios Top 200 basins Precipitation change per degree T change vs runoff change per degree T A1B scenario Top 200 basins Precipitation change per Degree T change /media/ces/Lettenmaier_Dennis_CES_2010pdf.pdf

• 9. Group3-The-future-of-the-Finnish-national-road-network

  to the big roads (noise reduction vs. durability of asphalt), scientists in road technology, firms 0 10000 20000 30000 40000 50000 60000 1 9 8 5 1 9 9 0 1 9 9 5 2 0 0 0 2 0 0 5 2 0 1 0 2 0 1 5 2 0 2 0 2 0 2 5 2 0 3 0 pass_cars (mln. Pkm) pass_cars (mln. Pkm) Projection of passenger kilometers Socio-economic scenario Climate scenario Worst case (4.4 C increase; 17 % increase in prec /media/loftslag/Group3-The-future-of-the-Finnish-national-road-network.pdf

• 10. CES_D2.4_solar_CMIP3

  by the various models. In the large figure, months from Jan- uary (1) to December (12) are depicted. On the right-top corner there is an enlarged illustration for November-February, i.e., the months with the weakest incident radiation. Unit: MJ m−2 month−1. analysis would corrupt the results severely. Therefore, the present analysis will be based on 18 models, with the CSIRO model excluded. Evaluation /media/ces/CES_D2.4_solar_CMIP3.pdf