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  • 11. ved-eng-2014

    24-hr mm prec.days >=1.0 mm Reykjavík 963.1 121 112 37.6 223 160 Stafholtsey 829.4 97 28.0 182 144 Bláfeldur 1460.7 97 32.0 272 195 Stykkishólmur 678.8 96 87 20.0 218 136 Litla-Ávík 835.0 96 34.1 267 164 Bergstaðir 458.2 98 22.6 177 92 Sauðanesviti 1017.5 115 28.2 239 158 Akureyri 743.7 152 133 23.0 225 133 Grímsstaðir 514.8 146 128 22.5 228 133 Miðfjarðarnes 765.0 120 36.4 233 /media/vedurstofan/utgafa/skylduskil/ved-eng-2014.pdf
  • 12. Traffc-maintenance_expenditures

    229 1 587 160 1970 18 591 42 413 2 166 86 101 - 892 5 131 2 310 201 - - - 157 805 1 652 904 1969 17 559 38 840 2 313 93 776 - 922 4 562 1 571 - - - - 159 543 1 832 354 1968 13 474 36 376 3 074 104 519 - 1 080 4 131 1 156 - - - - 163 811 1 964 368 1967 11 139 34 495 5 940 95 857 - 419 3 032 1 087 - - - - 151 968 1 936 249 1966 9 835 32 581 8 349 94 777 - 587 4 205 1 743 - - - - 152 077 2 032 936 /media/loftslag/Traffc-maintenance_expenditures.pdf
  • 13. 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
  • 14. The weather in Iceland in 2018

    of bright sunshine hours in June have not been as few since 1914. It was sunny in Reykjavík in March, August and September. In Akureyri the number of bright sunshine hours was above normal in March, June and September but below normal in April, July, August and October. Sea level pressure The annual average in Reykjavík was 1003.0 hPa, 2.9 below the 1961 to 1990 mean. The absolute /about-imo/news/the-weather-in-iceland-in-2018
  • 15. 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
  • 16. BIBD_windrose_2005-2014

    W N (Number of observations for wind direction) Icelandic Met Office 02. júl. 2015 36 2 69 4 138 2 187 3 151 2 106 7 83 1 58 1 36 0 20 3 17 6 14 5 14 9 11 0 10 6 13 0 16 7 29 8 55 2 73 0 95 6 140 7 98 9 41 9 20 2 17 7 8 1 6 4 4 8 3 7 5 7 4 4 4 5 7 3 9 2 18 5 Wind rose BIBD January 2005−2014 90 80 70 60 50 40 30 2010360350340 330 320 310 300 290 280 270 /media/vedur/BIBD_windrose_2005-2014.pdf
  • 17. Paper-Olafur-Rognvaldsson_91

    the opportunity to model river runoff and glacier mass balance both in the current climate and also in a hypothetical future climate based on the CE /VO climate change scenarios. The climate of Iceland is largely governed by the interaction of orography and extra-tropical cyclones, both of which can be described quite accurately by present day atmospheric models. As a result, dynamical downscaling /media/ces/Paper-Olafur-Rognvaldsson_91.pdf
  • 18. Paper-Olafur-Rognvaldsson_92

    for Meteorological Research, Reykjavík, Iceland 5Bergen School of Meteorology, Geophysical Insitute, University of Bergen, Norway †Corresponding author: or@belgingur.is, Orkugarður, Grensásvegur 9, 108 Reykjavík ABSTRACT Atmospheric flow over Iceland has been simulated for the period Jan- uary 1961 to July 2006, using the mesoscale MM5 model driven by initial and boundary data from the ECMWF. Firstly /media/ces/Paper-Olafur-Rognvaldsson_92.pdf
  • 19. 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 AMSAnnual Maxima Series CCCloseness Coefficient CDOClimate Data Operator EVA – Extreme Value Analysis GP – Generalized Pareto ICRA – Icelandic /media/vedurstofan-utgafa-2020/VI_2020_008.pdf
  • 20. VI_2022_006_extreme

    77 91 109 Hraunaveita 132 116 136 159 117 140 169 Kvíslaveita 48 42 49 58 42 51 61 Sultartangi 66 57 68 80 58 69 84 Þingvallavatn 96 84 99 117 85 102 123 Þórisvatn 47 41 49 57 42 50 60 Tungnaá 76 67 79 92 67 80 98 Ufsarlón 104 92 108 126 93 112 134 36 Figure 19 – 1M5 maps for catchment Hálslón based on the ICRA dataset without projection (top left), with RCP 2.6 and 10th percentile /media/vedurstofan-utgafa-2022/VI_2022_006_extreme.pdf

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