.............................................................................................. 27
REFERENCES ..................................................................................................................... 28
Figures
Figure 1. Volcanic zones of Iceland, shown in yellow (Einarsson & Sæmundsson, 1987). .... 8
Figure 2. Mean annual number of days per year with snow covered ground
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. . . . . . . . . . . . . . . . . 28
9 Weibull shape parameter at 50 and 100 mAGL for all wind directions . . . . . . . 30
10 Average wind power density based on corrected WRF model data . . . . . . . . . 33
11 Average wind power density based on NORA10 data . . . . . . . . . . . . . . . . 34
12 Differences in wind power density between northerly and southerly winds . . . . . 35
13 Directional
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to the annual temperatures
during 20032007. The low AAR and the high mass
balance sensitivity (e.g., Jo´hannesson 1997) to a uni-
form temperature rise (Table 4) at both Torfajo¨kull and
Tindfjallajo¨kull during the warm last decade are con-
sistent with their low and narrow elevation range
(Fig. 1).
Table 3 (a) Average specific net balance (bn), at the Eyjafjallajo¨kull (E), Torfajo¨kull
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List of participants ............................................................................................... 28
NONAM Workshop Reykjavik 26 & 27 August 2010 – Summary
3
Introduction
NONAM stands for NOrdic Network on Adaptive Management in relation to climate change.
The NONAM network is one of the 10 networks funded by the Nordic Council of Ministers as
part of the Top
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to theoretical framework. I do also want to thank him for an
enjoyable time during this work, both in the office and in the field.
This work was carried out as a part of the Skaftá cauldrons research project which
was funded and supported by the Icelandic Centre For Research (RANNÍS), Kvískerja-
sjóður, the NASA Astrobiology Institute, Landsvirkjun (the National Power Com-
pany), the National Energy
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by
rescaling a dimensionless regional flood frequency distribution or growth curve, qR(D;T ), com-
mon to all sites of the homogeneous region, with the so-called index flood, µi(D), of the target
site:
bQi(D;T ) = µi(D)qR(D;T ); (1)
where bQi(D;T ) is the estimated flood quantile, i.e. the T -year flood peak discharge averaged
over duration D, at site i. The regional growth curve, qR(D;T
/media/vedurstofan/utgafa/skyrslur/2015/VI_2015_009.pdf
to be simple and therefore has important drawbacks.
Future improvements should be made in the light of applications within a larger toolbox of scenario
methods.
2008 Elsevier Ltd. All rights reserved.
* Tel.: +31 317 482422; fax: +31 317 419000.
E-mail address: kasper.kok@wur.nl.
Contents lists available at ScienceDirect
Global Environmental Change
journa l homepage: www.e lsev ier .com/ locate
/media/loftslag/Kok_JGEC658_2009.pdf
PUBLIC VIEWS ON CLIMATE CHANGE: EUROPEAN AND USA
PERSPECTIVES
IRENE LORENZONI and NICK F. PIDGEON∗
Centre for Environmental Risk and Tyndall Centre for Climate Change Research, Zuckerman
Institute for Connective Environmental Research, School of Environmental Sciences, University of
East Anglia, Norwich NR4 7TJ, UK
E-mail: i.lorenzoni@uea.ac.uk
Abstract. If uncontrolled, human influences
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