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Results:

• 31. 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

• 32. 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

• 33. 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

• 34. The weather in Iceland in 2022

  was particularly cold; the temperature was 5 °C below average in both places. It hasn't been this cold in Reykjavík in December for over 100 year. Precipitation The year 2022 was unusually wet in Reykjavík. It was relatively wet in the capital in the beginning of the year, with March exceptionally wet. It was the wettest March on record, with total precipitation almost triple the average precipitation /about-imo/news/the-weather-in-iceland-in-2022

• 35. 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

• 36. 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

• 37. 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

• 38. 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

• 39. 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

• 40. 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