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Results:

• 21. QA on the eruption in Eyjafjallajökull 2010

  health, for example the respiratory system. The fluorine content is approximately 850 mg/kg according to chemical analysis carried out by the Institute of Earth Sciences, University of Iceland, on a sample taken 19 April. An earlier sample since 14 April only measured 25-35 mg/kg of fluorine because the water vapour from melting ice rinsed the ash. When the eruption progressed, water became less /earthquakes-and-volcanism/articles/nr/1880

• 22. Hydropower - Glacier, Snow and Ice

  (2010). An updated gridded precipitation data set for Iceland. 62-63. Einarsson, B., & Jónsson, S. (2010). The effect of climate change on runoff from two watersheds in Iceland. p. 86-87. (joint work with the hydrological modelling group) Jóhannesson, T., Aðalgeirsdóttir, G., Ahlstrøm, A., Andreassen, L.M., Beldring, S., H. Björnsson, H., Crochet, P., Einarsson, B., Elvehøy, H., Guðmundsson, S /ces/publications/nr/1940

• 23. PhD_course-Programme_26Aug2011-final

  Christian Refsgaard, GEUS All week AP Adriaan Perrels, FMI All week SK Sigrún Karsldóttir, IMO All week FU Frederik Uldal, University of Copenhagen Logistic support Course material Papers and book chapters - recommended reading Henriksen HJ, Barlebo HC (2008) Reflections on the use of Bayesian belief networks for adaptive management. Journal of Environmental Management, 88, 1025- 1036. doi:10.1016 /media/vedurstofan/PhD_course-Programme_26Aug2011-final.pdf

• 24. NOMEK09_Report

  Hermannsdóttir (Media) Sveinn Brynjólfsson (Avalanche) Theodor Freyr Hervarsson (Aviation) Guðrún Nína Petersen (Forecast errors) SMHI: Andreas Carlsson (Dynamics/NWP) Anna Eronn (Satellite) met.no: Bjørn Røsting (Dynamics) FMI: Vesa Nietosvaara (Online sessions and website) Elena Saltikoff (Radar-distans teaching) DMI: Claus Petersen (Slippery Roads) EUMETSAT: Jochen Kerkmann (Satellite /media/vedurstofan/utgafa/skyrslur/2009/NOMEK09_Report.pdf

• 25. VI_2013_006

  stability, e.g. CAPE, in global numerical weather prediction models to mask out potential thunderstorm areas. Such a global system might be useful to monitor large areas of poorly monitored volcanoes, e.g. the chain of volcanoes in the Aleutian Islands, with its heavy air-traffic above. Conclusions An automatic monitoring system has been developed that estimates eruption site location based /media/vedurstofan/utgafa/skyrslur/2013/VI_2013_006.pdf

• 26. VI_2020_008

  by the Peak-over-Threshold with MLE applied on daily and 24-hour accumulated precipitation from the ICRA. ............................... 58 8 Glossary 1M5 – Daily or 24-hour precipitation return level with a 5-year return period AMS – Annual Maxima Series CC – Closeness Coefficient CDO – Climate Data Operator EVA – Extreme Value Analysis GP – Generalized Pareto ICRA – Icelandic /media/vedurstofan-utgafa-2020/VI_2020_008.pdf

• 27. Climatic-Change-2012---Personality-type-differences-between-Ph.D.-climate-experts-and-general-public---implications-for-communication

  RM, Capraro MM (2002) Myers-Briggs Type Indicator score reliability across studies: a meta-analytic reliability generalization study. Educ Psychol Meas 62:590–602 Carlson JG (1985) Recent assessments of the Myers-Briggs Type Indicator. J Personal Assess 49:356–365 Carlyn M (1977) An assessment of the Myers-Briggs Type Indicator. J Personal Assess 41:461–473 Clack GB, Allen J, Cooper D et al (2004 /media/loftslag/Climatic-Change-2012---Personality-type-differences-between-Ph.D.-climate-experts-and-general-public---implications-for-communication.pdf

• 28. Climate and Modeling Scenarios

  & Ruosteenoja, K. (2009). Comparing regional risks in producing turnip rape and oilseed rape - Impacts of climate change and breeding. Acta agriculturae Scandinavica 59B:2, 129-138. doi:10.1080/09064710802022895 (http://www.ingentaconnect.com/content/tandf/sagb/2009/00000059/00000002/art00004). Pryor, S.C., Barthelmie, R.J., Clausen, N.E., Drews, M., MacKellar, N. & Kjellström, E. (2010). Analyses /ces/publications/nr/1680

• 29. Kok_2-scenarios-lecture-2

  extreem events C6; qual nat. systems C7; policies C8; price of resources C9; other sectors C10; industry C11; inrastructure Crimea - Ukraine Manaus - Brazil From FCM to model input FCM – strong points • Easy to develop and apply. The approach is highly intuitive, it can quickly be explained and applied to any new situation. • High level of integration. A FCM can contain any type of information /media/loftslag/Kok_2-scenarios-lecture-2.pdf

• 30. Kok_et_al._TFSC_published_2011

  ]. There is ample experience with backcasting, and consequently much has been said about the underlying principles (e.g. [20]), the methodological 838 K. Kok et al. / Technological Forecasting & Social Change 78 (2011) 835–851 Author's personal copy framework (e.g. [8,30–32]), and practical applications (e.g. [33–35]). Also the combination between backcasting and other types of scenarios has been /media/loftslag/Kok_et_al._TFSC_published_2011.pdf