Temperature Extreme events
Droughts Storms
Climate 1 +++ ++/‐‐ + ++ + +++
Climate 2 ++ + + + +
Climate 3 ‐ +/‐ +++ ‐ ++ ++
The socio economic conditions in 2050 describe three different worlds, which are represented by the
pictures in Figure 1.
Figure 1: Qualitative description of the three different socio economic set of conditions (Society 1 to 3).
Society 1
/media/loftslag/Group2-report.pdf
and our intention is to run these models dur-
ing times of hazardous events and even on a daily
basis to further improve monitoring.
Avalanche monitoring has progressed. The em-
phasis is now on improving our services, especially
to the Icelandic Road and Coastal Administration
with regard to transport. The reason is that com-
munity structure has changed considerably in recent
years and the need
/media/vedurstofan/utgafa/arsskyrslur/VED_AnnualReport-2013_screen.pdf
level in Skeidará waned. The last sign of a
crater explosion was seen at GRF early on 6
November, leaving only a weak tremor signal
from the remnants of the jökulhlaup. The
jökulhlaup fi nally ended in early December,
after ~0.8 km3 of water had drained from the
Grímsvötn lake (J. Hardardóttir, personal com-
munication, 2005).
Location and Volume Constraints
Earthquake locations at Grímsvötn
/media/jar/myndsafn/2005EO260001.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
domain and data followed by the description
of the mass balance model. Subsequently modeled mass balance will be presented along with
the evaluation of the RCM output. Finally we will discuss the relationship of modeled mass
balance and biases in the RCM data and will conclude on the suitability of the latter for future
scenarios.
2 Model Domain and Data
2.1 Model Domain
Paakitsôq is the name
/media/ces/ces_geus_paakitsoq_full_report.pdf
those
that can be deduced from the unit hydrograph for these watersheds. This implies that
physical description of some processes is compromised for better overall calibration
performance. This is a drawback for future scenario modelling for example because bias
correction and scaling defined for present conditions may not be valid for future conditions
and a proper modelling of physical
/media/ces/2010_017.pdf
evapotranspiration
scheme; and iii) by applying glacier melt parameters calibrated by mass balance
measurements instead of river discharge data. The National Energy Authority has
supported this work with contracts on hydrological modelling and groundwater research.
Further description of these improvements is given in Einarsson & Jónsson, (2010).
After these improvements had been implemented
/media/ces/2010_016.pdf
The NOMEK Memorandum of Understanding has been followed for the past
three years and formalises the principles which are used arranging the
course. The courses have now run over more than 10 years and over the
years small changes to the principles of how the course is run and funded
have been introduced by the changing host. This formal description of the
principles for the NOMEK has been
/media/vedurstofan/utgafa/skyrslur/2009/NOMEK09_Report.pdf
are:
Scenarios are plausible descriptions of how the future may
develop, based on a coherent and internally consistent set of
assumptions about key relationships and driving forces. (focus
on system description)
Scenarios are credible, challenging, and relevant stories about
how the future might unfold that can be told in both words and
numbers. (focus on value for end users and other
/media/loftslag/Kok_1-scenarios-lecture-1.pdf
the com-
plexity of the hydrological processes through modelling, but its application is usually limited to
the short-range. Although the results demonstrated a great potential for this method, its success-
ful application in real-time will strongly depend on the quality and availability of streamflow
observations, which can be poor or simply missing during periods of variable durations, e.g
/media/vedurstofan/utgafa/skyrslur/2014/VI_2014_006.pdf