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• 41. ECONOMIC_EFFECTS_OF_CLIMATE_CHANGE_ON_THE_TOURISM_SECTOR_IN_SPAIN

  /lexuriserv/lexuriserv.do?uri=com:2007:0002:FIN:EN:PDF, 13 April 2009. [2] WTO, World Tourism Organization (2008): “Climate Change and Tourism - Responding to Global Challenges”, UNWTO, 9 July 2008, Madrid, Spain. Available at: http://www.unwto.org/media/news/en/press_det.php?id=1411&idioma=E, 7 March 2010. [3] Mooney, J.E. y Miller, M.L. (2009): “Climate change: Creating demand for sustainable /media/loftslag/ECONOMIC_EFFECTS_OF_CLIMATE_CHANGE_ON_THE_TOURISM_SECTOR_IN_SPAIN.pdf

• 42. Perrels-CBA

  operational cost, etc.) and the annual revenues • consider an appropriate discount rate and assess NPV (net present value), IRR (internal rate of return), and net cash flows • rank alternatives by score level • SCBA: social CBA – total benefits -/- total costs for society, in this case benefits and costs often don’t accrue (entirely) to the same organisation due to the public nature of a project /media/loftslag/Perrels-CBA.pdf

• 43. CES_D2_2_poster_3x3

  CMIP3 Multimodel Dataset: A New Era in Climate Change Research. Bulletin of the Americal Meteorological Society, 88, 1383-1394. Naki enovi , N. and R. Swart (Eds.) 2000: Emission Scenarios. A Special Report of Working Group III of the Intergovernmental Panel on Climate Change. Cambridge University Press, 599 pp. Räisänen, J. and L. Ruokolainen 2006: Probabilistic forecasts of near-term climate /media/ces/CES_D2_2_poster_3x3.pdf

• 44. Keranen_Jaana_CES_2010

  of fu tu re clim ate, hydro lo gic al m o del or wind m odel. Conse quen c e catego ry Like lih ood of th e consequ ence s to the e ne rgy pr od uc tion R isk r educ tio n / con trol / po tential D istribution netw ork P ow er p lan t En erg y sour ce, (e.g . catchme nt area , pe at or b iomass prod uctio n area ) Like lihood of th e phen om ena Sc en arios and Ph enom ena /media/ces/Keranen_Jaana_CES_2010.pdf

• 45. VI_2019_009

  To distinguish between rain and snow, the volume is com- pared to the water equivalent but the volume of snow is ten times larger. Figure 1. How PWD22 determines the type of precipitation. Using the information about the changes of the backscatter signal, water equivalent and temper- ature the Vaisala Present Weather Detector can give information about the type of precipitation. It is also used /media/vedurstofan-utgafa-2019/VI_2019_009.pdf

• 46. VI_Arsskyrsla_2018_vef

  grundvelli myndatöku með flygildum og leysimælitæki (TLS) hefur verið notað við kortlagningu flóðfara og við mat á útbreiðslu og umfangi hlaupa. Þétt net jarðskjálftamæla, sem staðsettir eru á jökulskerjum eða grafnir í jökul, hefur gefið góða raun við ákvörðun á dýpi jarðskjálfta undir jöklum. Kvikuhreyfingar hafa þannig verið kortlagðar og myndun gosrása staðfest af meiri nákvæmni en áður. Þó /media/vedurstofan/utgafa/arsskyrslur/VI_Arsskyrsla_2018_vef.pdf

• 47. VI_2020_004

  .................... 85 8 Figure 57 50% PM10 probability map for an eruption like 1362 at Öræfajökull ..................... 86 Figure 58 The probability of exceedance curve at key locations (Öræfajökull) ...................... 87 Figure 59 Tephra accumulation rate on the ground on 7 May 1982 (Öræfajökull) ................. 88 Figure 60 Tephra accumulation rate on the ground on 5 May 1981 (Öræfajökull /media/vedurstofan-utgafa-2020/VI_2020_004.pdf

• 48. Isskyrsla_20100407

  N66°44.92' W025°08.94' 79. N66°45.01' W025°08.50' 80. N66°46.32' W025°10.27' 81. N66°46.73' W025°07.19' 82. N66°46.01' W025°04.86' 83. N66°46.22' W025°04.33' 84. N66°47.12' W025°06.45' 85. N66°47.26' W025°04.36' 86. N66°48.44' W025°03.60' 87. N66°49.10' W025°04.45' 88. N66°51.68' W025°03.27' 89. N66°53.36' W024°59.25' 90. N66°55.39' W024°58.89' 91. N66°55.82' W024°58.13' 92. N66°56.15' W025°01.15 /media/hafis/skyrslur_lhg/Isskyrsla_20100407.pdf

• 49. CES_D2.4_VMGO

  size. References 1. Meehl, G.A., C. Covey, T. Delworth, M. Latif, B. McAvaney, J.F.B. Mitchell, R.J. Stouffer and K.E. Taylor, 2007: The WCRP CMIP3 Multimodel Dataset: A New Era in Climate Change Research, BAMS, 88, 1383-1394, DOI: 10.1175/BAMS-88-9-1383. 2. Naki �enovi � N., J. Alcamo, G. Davis, B. de Vries, J Fenhann, S. Gaffin, K. Gregory, A.Grübler, T.Y. Jung, T. Kram, E.L. La Rovere /media/ces/CES_D2.4_VMGO.pdf

• 50. 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