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Results:

• 41. VI_2009_012

  Mw(v) plotted against log distance. The coefficient of correlation between Mw(v) and log distance is 0.24. High correlation coefficients have been shown to affect parameter estimates in one step regression methods (see Fukushima and Tanaka, 1990). The Ci values were also calculated from the derived PGA values. Instead of constructing another magnitude scale based on acceleration it was decided /media/vedurstofan/utgafa/skyrslur/2009/VI_2009_012.pdf

• 42. Public-Choice-2012---McGuiness-and-Walker---Foundations-of-the-Ostrom-workshop---institutional-analysis,-polycentricity,-and-self-governance-of-the-commons

  The well-being of any human community is critically dependent on continued access to natural and man-made resources. Decades before sustainability became a popular slogan, the Ostroms began to investigate the conditions under which natural resources can be man- aged in a sustainable manner. The origins of the Workshop approach can be traced back at least as far as “State Administration of Natural /media/loftslag/Public-Choice-2012---McGuiness-and-Walker---Foundations-of-the-Ostrom-workshop---institutional-analysis,-polycentricity,-and-self-governance-of-the-commons.pdf

• 43. Public-Choice-2012---Teyssier---Inequity-and-risk-aversion-in-sequential-public-good-games

  individuals act like homo-œconomicus agents (see for example Andreoni 1988; Berg et al. 1995; Camerer 2003; Forsythe et al. 1994; Isaac et al. 1984). Recent developments in public-choice theory have taken a behavioral approach to broaden the analysis of collective action. The introduction of social preferences, such as altruism, inequity aversion or trust, may mean that optimal collective choices /media/loftslag/Public-Choice-2012---Teyssier---Inequity-and-risk-aversion-in-sequential-public-good-games.pdf

• 44. Hare-2011-ParticipatoryModelling

  are labelled according to the geographical area of application. Examples such as Zürich and Hase II have already been reviewed and categorized in Hare et al. (2003) and Bots and van Daalen (2008), respectively. The entire Iskar process, of which Iskar (Phase I) is a part, has been categorized by Barreteau et al. (2010). All are included in this review to provide alternative analytical perspectives /media/loftslag/Hare-2011-ParticipatoryModelling.pdf

• 45. 2011_005

  in Appendix III. 4.2 Preferred layout of the network The Iceland CGPS network has been installed mostly through research grants of different projects with various collaborators. As a result the network coverage is uneven around the country. Areas outside of the active plate boundary have hardly any GPS stations and the network coverage is lacking for large part of the plate boundary, many /media/vedurstofan/utgafa/skyrslur/2011/2011_005.pdf

• 46. 2013_001_Nawri_et_al

  and a pressure of 1013.25 hPa. In the case of Iceland, the climate deviates significantly from these standard atmospheric conditions. Additionally, terrain elevation varies considerably across the island. Therefore, seasonal and annual differences in air density from the standard value, as well as spatial variability, need to be taken into account. Approximate air density can be calculated by assuming /media/vedurstofan/utgafa/skyrslur/2013/2013_001_Nawri_et_al.pdf

• 47. D2.3_CES_Prob_fcsts_GCMs_and_RCMs

  Institution BCCR-BCM2.0 Bjerknes Centre for Climate Research, Norway CGCM3.1 (T47) Canadian Centre for Climate Modelling and Analysis CGCM3.1 (T63) same as previous CNRM-CM3 Météo-France CSIRO-MK3.0 CSIRO Atmospheric Research, Australia ECHAM5/MPI-OM Max Planck Institute (MPI) for Meteorology, Germany ECHO-G University of Bonn and Model & Data Group, Germany; Korean Meteorological Agency GFDL /media/ces/D2.3_CES_Prob_fcsts_GCMs_and_RCMs.pdf

• 48. raisanen_ruosteenoja_CES_D2.2

  Model Institution BCCR-BCM2.0 Bjerknes Centre for Climate Research, Norway CGCM3.1 (T47) Canadian Centre for Climate Modelling and Analysis CGCM3.1 (T63) same as previous CNRM-CM3 Météo-France CSIRO-MK3.0 CSIRO Atmospheric Research, Australia ECHAM5/MPI-OM Max Planck Institute (MPI) for Meteorology, Germany ECHO-G University of Bonn and Model & Data Group, Germany; Korean Meteorological Agency GFDL /media/ces/raisanen_ruosteenoja_CES_D2.2.pdf

• 49. Journal_of_Hydrology_Veijalainen_etal

  A second, but usually smaller, increase in runoff oc- curs in the autumn. In northern Finland more than 95% of annual maximum floods are caused by spring snowmelt (cf. Fig. 7a). Also the small upstream lakes in the northern part of the lake area and the northernmost of the coastal rivers fall mainly into this cat- egory. In most coastal rivers the major floods can be caused by either snowmelt /media/ces/Journal_of_Hydrology_Veijalainen_etal.pdf

• 50. VI_2014_005

  lines). Additionally, the aver- age profiles for offshore distances to the coast of up to 30 km are shown by the black lines. For temperature, the dashed lines indicate linear projection from the two lowest model levels to 2 m above ground. A comparison of monthly averages of simulated 2-m temperature with station measurements, both for SURFEX and projected values, is shown in Figure 8. On average /media/vedurstofan/utgafa/skyrslur/2014/VI_2014_005.pdf