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Results:

• 61. Keranen_Jaana_CES_2010

  tunnisteväriSeuraukset Scenario probability high ACT MONITOR Consequence probabi lity low after control methods PREPARE PREPARE Scenario probability low Consequence probabili ty high after control methods Likely Very unl ikely Very likely Virtuall y certain Unlikely V e r y l i k e l y L i k e l y V e r y u n l i k e l y Excepti onally unlikely = major consequences = moder ate consequences = minor /media/ces/Keranen_Jaana_CES_2010.pdf

• 62. Alam_Ashraful_CES_2010

  (ECT) Working paths and machinery transportation + C Rotation period Plant production and transportation Site preparation a r b o n Planting E n e r d i o Thinnings/ harvesting operations h di g y i x i d e Emission parametersEcosystem model S ort stance transportation Long distance n p u t E m i s Emission calculation tool transportation Chipping s i o n CO2 balance 14 Energy wood /media/ces/Alam_Ashraful_CES_2010.pdf

• 63. Group-1_Scenarios-for-AWM

  i on c a p ac i t y A r ea of r e s i d en c e (Flood p r one /non p r one a r eas) Un c e r t a n t i e s H i g h wi l l i n g n e s s t o p a y L o w wi l l i n g nes to pay D i k e s H i gh t a x a t i on - E arly w arn i n g s y s t e m s - Sof t s t r uct u r a l m e as u r e s -Community training L o w taxation Risk P e r c e p t i o n B e n e f i /media/loftslag/Group-1_Scenarios-for-AWM.pdf

• 64. Lettenmaier_Dennis_CES_2010pdf

  Withdrawal Reliability Grand Coulee Recreation Reliability R e l i a b i l i t y ( % , m o n t h l y b a s e d ) Control Period 1 Period 2 Period 3 RCM 2040-2069 60 80 100 120 140 Firm Hydropower Annual Flow Deficit at McNary P e r c e n t o f C o n t r o l R u n C l i m a t e PCM Control Climate and Current Operations PCM Projected Climate and Current Operations PCM Projected /media/ces/Lettenmaier_Dennis_CES_2010pdf.pdf

• 65. VI_2014_006

  the com- plexity of the hydrological processes through modelling, but its application is usually limited to the short-range. Although the results demonstrated a great potential for this method, its success- ful application in real-time will strongly depend on the quality and availability of streamflow observations, which can be poor or simply missing during periods of variable durations, e.g /media/vedurstofan/utgafa/skyrslur/2014/VI_2014_006.pdf

• 66. Recent publications

  61, 1-18. Oddur Sigurðsson (2011). Iceland glaciers. Í: V. P. Singh, P. Singh & U. K. Haritashya (ritstj.). Encyclopedia of Snow, Ice and Glaciers. Springer, Dordrecht, s. 630-636. Árni Snorrason, Jórunn Harðardóttir & Þorsteinn Þorsteinsson (2011). Climate and Energy Systems – Project Structure. In: Þorsteinn Þorsteinsson & Halldór Björnsson (eds.), Climate Change and Energy Systems. Impacts /about-imo/arctic/completed-projects/publications/

• 67. Eyjafjallajökull eruption 2010 - the role of IMO

  Arason T., Geirsson H., Karlsdóttir S., Hjaltadóttir S., Ólafsdóttir U., Thorbjarnardóttir B., Skaftadóttir T., Sturkell E., Jónasdóttir E.B., Hafsteinsson G., Sveinbjörnsson H., Stefánsson R., and Jónsson T.V., 2005, Forecasting and Monitoring a Subglacial Eruption in Iceland, Eos, Vol. 86, No. 26, p. 245-252, 28 June 2005. Location Location of the weather radar at Keflavik airport /earthquakes-and-volcanism/articles/nr/2072

• 68. Climate and Modeling Scenarios

  information. Weather, Climate, and Society, 2:2, 148-167. Kjellström, E., Boberg, F., Castro, M., Christensen, J.H., Nikulin, G., & Sanchez, E., (2010a). On the use of daily and monthly temperature and precipitation statistics as a performance indicator for regional climate models. Climate Research, in press. Doi: 10.3354/cr00932. Kjellström, E., Nikulin, G., Hansson, U., Strandberg, G. & Ullerstig /ces/publications/nr/1680

• 69. Cradden_Lucy_CES_2010

  Capacity (A) F r e q u e n c y control future +0.4std dev (as % of mean) -0.68max -8.32min -1.74mean % change June 2010 15 Time series 450 500 550 600 650 700 Hour C a p a c i t y ( A ) Typical year of control period Seasonal average rating Calculated capacity 450 500 550 600 650 700 Hour C a p a c i t y ( A ) Typical year under future scenario Calculated capacity Seasonal average /media/ces/Cradden_Lucy_CES_2010.pdf

• 70. Dyrrdal_Anita_CES_2010

  Results W i n t e r t e m p e r a t u r e Max snow depth Trend slope Number of snow days Period II P e r i o d I I I Max snow depth Number of snow days Norwegian Meteorological Institute met.no Correlation analysis (1961-08) 138 mutual stations Introduction Data & Methods Results Correlation with winter temperature Correlation with winter precipitation In warmer regions both snow parameters /media/ces/Dyrrdal_Anita_CES_2010.pdf