(Percent) By
Year Built Categories
Percent of Homes Damaged By Year Built
Categories
36
24
26
28
30
32
34
Pre 1980 80-96 97-2002 Post 2002
Percent Damaged
All Homes – Damage Per Square
Foot
All Homes - Damage Per Square Foot
2
2.5
D
a
m
a
g
e
P
e
r
S
q
.
F
o
o
t
0
0.5
1
1.5
< 120 120-129 130-139 140-149 > 149
D
a
m
a
g
e
P
e
r
S
q
.
F
o
o
t
Pre 1980
1980-1996
1997-2002
Post 2002
/media/loftslag/FMI_-_Disaster_Mitigation.pdf
Thursday, 14 November
Time Agenda Item
09:00 – 10:30
09:00 – 09:20
09:20 – 09:40
09:40 – 10:00
10:00 – 10:30
Potential Arctic / Mid-Latitude Linkages - East Asia (Chair: Jim Overland)
Rapid Arctic Warming in Recent Decades and Its Impact on Climate Change over East Asia
- S-J Kim
Extreme weather in northern mid-latitudes linked to cryosphere loss - Q Tang
A cause of the AO
/media/loftslag/Mid-Latitudes-Agenda1_nov2013EH.pdf
of melt water from glaciated
areas in long integrations for a warming climate.
Glacier dynamics
This problem can be qualitatively analysed by considering the continuity equation for ice vol-
ume, which may be expressed as
¶h
¶t
+
¶q
¶x
= b or
¶h
¶t
+~ ~q = b ; (1)
for a one-dimensional ice flow channel or an ice cap that flows in two horizontal dimensions,
respectively. h is ice thickness, q or ~q/media/ces/ces-glacier-scaling-memo2009-01.pdf
-2000. Over the northern parts of
the European continent, a warming of climate appears very likely already in 2011-2020. The
seasonal probabilities of warming vary from slightly below 90% to about 95%, depending on
season and location. The corresponding probability of warming for the annual mean
temperature in 2011-2020 is even higher, at least 95% (first panel in the bottom row of Figure
4.1)2. Note
/media/ces/raisanen_ruosteenoja_CES_D2.2.pdf
J A
0 100 200 30020
0
60
0
100
0
Days since Sept. 1st
Q
(m
^3
/s)
Obs
Pred−nearest
Pred−weight
Method 4 T+2: RMSE−nearest= 69.6 RMSE−weight= 44.5
S O N D J F M A M J J A
Figure 7. Observed and predicted daily discharges at vhm 64 for a forecast range (T) of 2 days
and water-year 2004–2005, using methods 1 to 4 with rescaling. The 80%, 90% and 95% pre-
diction intervals are represented by grey
/media/vedurstofan/utgafa/skyrslur/2013/VI_2013_008.pdf
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
andEnergy Directorate (NVE), Oslo, Norway2Department of Geosciences, University of Oslo, Norway3Institute for Marine and Atmospheric Research, Utrecht University, Utrecht, the Netherlands
Andreassen, L. and Oerlemans, J., 2009: Modelling long-term
summer and winter balances and the climate sensitivity of Stor-breen, Norway. Geogr. Ann. 91 A (4): 233–251.
ABSTRACT. Measurements of winter balance (bw
/media/ces/GA_2009_91A_4_Andreassen.pdf
Based on a report by
Verta et al. (2007)
92.
5
93.
0
93.
5
94.
0
94.
5
95.
0
M A MJ F J J A S O N D
Mean 19702000
Min and max 1970–2000,
natural rating curve
Target water level zone 1
Target water level zone 2
Q=+20%
Q=+10%
Q= 0%
Q=15%
Q=30%
92.90 m snow target 1
92.70 m snow target 2
Water level (m
)
Month
the regulation limits Lake Syväri has target water level zones, which are not legally
/media/ces/Water_resources_man_Veijalainen_etal.pdf
19 CMIP3 GCMs are used (Table 2.1). The horizontal grid spacing of these
models varies from 1.1 q latitude × 1.1 q longitude to 4 q latitude × 5 q longitude. For each
2 Some of the RCM simulations in the ENSEMBLES data base were conducted with funding from other sources,
including CES.
5
model, a 198-year time series (1901-2098) obtained
/media/ces/D2.3_CES_Prob_fcsts_GCMs_and_RCMs.pdf