Cooperation and
Development, Paris, 2006).
2. R. H. Webb, J. L. Betancourt, U.S. Geol. Surv. Water-
Supply Paper 2379, 1 (1992).
3. C. A. Woodhouse, S. T. Gray, D. M. Meko, Water Resour.
Res. 42, W05415 (2006).
4. Intergovernmental Panel on Climate Change (IPCC), in
Climate Change 2007: The Physical Science Basis,
Contribution of Working Group (WG) 1 to the Fourth
Assessment Report of the IPCC (AR4
/media/loftslag/Milly_etal-2008-Stationarity-dead-Science.pdf
and possibly the stake-
holders at different phases of the modelling project.
Many QA guidelines exist such as Middlemis (2000) and
Van Waveren et al. (1999). The HarmoniQuA project (Schol-
ten et al., 2007; Refsgaard et al., 2005a) has developed a com-
prehensive set of QA guidelines for multiple modelling
domains combined with a supporting software tool, MoST
(downloadable via http
/media/loftslag/Refsgaard_etal-2007-Uncertainty-EMS.pdf
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
the contiguous USA. 30th Annual Applied Geography Conference, Indianapolis, October 2007. 10 pp.
Clausen, N.-E., Lundsager, P., Barthelmie, R., Holttinen, H., Laakso, T. & Pryor, S.C. (2007). Wind Power. In: J. Fenger (Ed.) Impacts of Climate Change on Renewable Energy Sources: Their role in the Nordic energy system, Nord 2007:003, 105-128.
Clausen N.E., Pryor S.C., Larsén X.G., Hyvönen R
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variability
Models
Emission scenarios
2000 2100
LEVEL OF
UNCERTAINTY
Near future End of the
century
Natural climate variability + +
Climate model sensitivity (+) ++
Emission scenarios ++
Source: J. Räisänen (Univ. of Helsinki)
Probabilistic forecasts
of temperature change
in southern Finland
(1971-2000 barb2right 2011-2020)
Temperature change (ºC)
P
r
o
b
a
b
i
l
i
t
y
d
e
n
s
i
t
y
(
1
/
º
C
/media/loftslag/Case_B___Road_transport_operation_and_infrastructure_planning.pdf
by
the modal occurrences shown in Figure 9, is equal to the seasonal mean field.
The eight modal mean MSLP fields, together with the corresponding average centred temporal
tendencies of the MSLP field (d p=d tjt0 = (p(t0 + d t) p(t0 d t))=2d t, with d t = 2 days) in
winter are shown in Figure 10. In summer, the spatial patterns of mean MSLP fields are similar
but less distinct, with weaker pressure
/media/vedurstofan/utgafa/skyrslur/2015/VI_2015_005.pdf
Change 19 (2009) 122–133
A R T I C L E I N F O
Article history:
Received 14 November 2007
Received in revised form 21 August 2008
Accepted 25 August 2008
Keywords:
Fuzzy Cognitive Maps
Scenario
Participation
Resilience
Brazil
A B S T R A C T
The main drawback of the Story-and-Simulation approach is the weak link between qualitative and
quantitative scenarios. A semi-quantitative tool, Fuzzy
/media/loftslag/Kok_JGEC658_2009.pdf