of Icelandic glaciers 1992–1997). Rep.
OS-98082 (in Icelandic), National Energy Authority, Reykjavík.
Sigurðsson, O., Thorsteinsson Th., Ágústsson S. M. and Einarsson B. 2004.
Afkoma Hofsjökuls 1997–2004. (Mass balance of Hofsjökull 1997–2004.) Rep.
OS-2004/029, National Energy Authority, Reykjavík.
Uppala, S.M., and 45 co-authors 2005. The ERA-40 re-analysis. Q. J. R. Mete-
orol. Soc., 131, 2961
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hydrological model. J. Hydrol., 267, 40–52.
Jasper, K., and Kaufmann P. 2003. Coupled runoff simulations as validation
tools for atmospheric models at the regional scale. Q. J. R. Meteorol. Soc., 129,
673–692.
Jóhannesson, T., Aðalgeirsdóttir G., Björnsson H., Crochette P., Elíasson E.
B., Guðmundsson S., Jónsdóttir J. F., Ólafsson H., Pálsson F., Rögnvaldsson
Ó., Sigurðsson O., Snorrason Á
/media/ces/Paper-Olafur-Rognvaldsson_92.pdf
properly even if the
sample size is increased and systematic biases may be expected.
2.2.3 Predictors
Mean sea level pressure (MSLP), geopotential height (Z), specific humidity (q) and tempera-
ture (T) at different pressure levels are considered in this study to describe the meteorological
situations at the synoptic scale and to identify weather analogues. The MSLP and geopotential
height (Z) describe
/media/vedurstofan/utgafa/skyrslur/2014/VI_2014_006.pdf
leads to
c =
h1u1 h2u2
h1 h2
: (3.2)
Using the Manning equation for discharge per unit width, q,
q =
1
n0
hR2=3H S
1=2
0 ; (3.3)
where n0 is the Manning coefficient, h is the flow depth, RH is the hydraulic radius
and S0 is mean channel slope; the relationships: u h2=3, q h5=3 and u q2=5 can
18
be derived for a wide rectangular channel for which RH h and u = q=h. Now using
u1h1 = q1, u2h2
/media/vedurstofan/utgafa/skyrslur/2009/VI_2009_006_tt.pdf
: 3601/B2007.EEA53004 and 3601/RO/CLC/
B2007.EEA52971, Landmælingar Íslands, Reykjavik, Iceland.
Bechtold, P., Köhler, M., Jung, T., Doblas-Reyes, F., Leutbecher, M., Rodwell, M. J., Vitart, F.,
and Balsamo, G. (2008). Advances in simulating atmospheric variability with the ECMWF
model: from synoptic to decadal time-scales. Q. J. R. Meterol. Soc., 134:1337–1351.
Brousseau, P., Berre, L., Bouttier
/media/vedurstofan/utgafa/skyrslur/2014/VI_2014_005.pdf
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/media/loftslag/Outline_for_the_case_Road_maintenance_in_a_changing_climate.pdf
Q. J. R. Meteorol.
Soc., 137, 409-422.
Giesen, R. H., Andreassen, L. M., Oerlemans, J., & van den Broeke, M. R. (2014). Surface
energy balance in the ablation zone of Langfjordjøkelen, an arctic, maritime glacier in
northern Norway. J. Glaciol., 60(219), 57-70.
Seity, Y., Brousseau, P., Malardel, S., Hello, G., Bénard, P., Bouttier, F., . . . Masson, V. (2011).
The AROME-France convective-scale
/media/vedurstofan/utgafa/skyrslur/2015/VI_2015_006.pdf
time-series.
For wind energy assessments, the main emphasis is on an accurate determination of average wind
power density. As discussed in previous sections, average power density is approximately propor-
tional to the mean cube of wind speed. Rescaling factors for modelled wind speed time-series,
interpolated to station locations, are therefore defined here as 3
q
S3o=S3m. Aside from
/media/vedurstofan/utgafa/skyrslur/2013/2013_001_Nawri_et_al.pdf