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Results:

• 61. 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

• 62. Kok_and_Veldkamp_editorial_ES-2011-4160

  agreement on use of terminology. Third, all scoping papers stress that there is no silver bullet solution, with a different view on both scale and governance being appropriate depending on the specific case. Buizer et al. (2011) are strongest on this view by presenting and discussing a framework. Termeer et al. (2010) confirm that there is no best governance approach, drawing an analogue /media/loftslag/Kok_and_Veldkamp_editorial_ES-2011-4160.pdf

• 63. Refsgaard_etal-2007-Uncertainty-EMS

  The advantage of Monte Carlo analysis is its general appli- cability and that it does not impose many assumptions on prob- ability distributions and correlations and that it can be linked to any model code. The key limitation is the large run times for computationally intensive models and the huge amount of outputs that are not always straightforward to analyse. 4.8. Multiple model simulation Multiple model /media/loftslag/Refsgaard_etal-2007-Uncertainty-EMS.pdf

• 64. Journal_of_Hydrology_Veijalainen_etal

  the cascade of uncer- tainty becomes greater, which is always the case in this kind of complex analysis of climate change and extreme events (e.g. Men- zel et al., 2006). 3.1. Climate scenarios The climate scenarios in this study are from four global climate models (GCM) and means of 19 global climate models with three SRES (IPCC, 2000) emission scenarios (A2, B1 and A1B) and four re- gional /media/ces/Journal_of_Hydrology_Veijalainen_etal.pdf

• 65. vonKorff_etal-2010

  played a role in this first phase as the author tables on decision analysis show. In summary, the comparison resulted in the reconstruction of 10 steps on which there appears to be considerable agreement among the five guides. 1. DA 1: Assemble a team for decision analysis as part of the participation design. Its members should belong to the lead agency, e.g., the water board, but can also /media/loftslag/vonKorff_etal-2010.pdf

• 66. Keskitalo_et_al-MLG_and_adaptation_FINAL

  areas: to the regional arm of the state (the county administrative boards) to coordinate adaptation; to specific governmental bodies and agencies to develop a common elevation data basis; and for the assessment of flood risk and erosion defense measures around Lake Vänern. Risks considered by the Bill include the flooding of central Gothenburg, the second largest city of Sweden (a risk /media/loftslag/Keskitalo_et_al-MLG_and_adaptation_FINAL.pdf

• 67. 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

• 68. 2005EO260001

  ) by fossil fuel burning and land-use change. As the terrestrial bio- sphere is an active player in the global carbon cycle, changes in land use feed back to the climate of the Earth through regulation of the content of atmospheric CO2, the most impor- tant greenhouse gas, and changing albedo (e.g., energy partitioning). Recently, the climate modeling community has started to develop more /media/jar/myndsafn/2005EO260001.pdf

• 69. FMI_-_Disaster_Mitigation

  Disaster Mitigation Kevin M. Simmons, Ph.D. Austin College Fulbright Research Scholar International Centre for Geohazards Oslo, Norway Economic and Societal Impacts of Tornadoes By Kevin M. Simmons and Daniel Sutter © 2010, 296 pages in paperback ISBN: 978-1-878220-99-8 AVAILABLE NOVEMBER 2010 from the American Meteorological Society and the University of Chicago Press Research Agenda /media/loftslag/FMI_-_Disaster_Mitigation.pdf

• 70. Tornado_Impacts_-_FMI_Presentation

  The Economic and Societal Impacts of Tornadoes Kevin M. Simmons Austin College Fulbright Research Scholar International Centre for GeoHazards Oslo, Norway Economic and Societal Impacts of Tornadoes By Kevin M. Simmons and Daniel Sutter © 2010, 296 pages in paperback ISBN: 978-1-878220-99-8 AVAILABLE NOVEMBER 2010 from the American Meteorological Society and the University of Chicago Press /media/loftslag/Tornado_Impacts_-_FMI_Presentation.pdf