Evaluation of HARMONIE reanalyses of
surface air temperature and wind speed
over Iceland
Nikolai Nawri
VÍ 2014-005
Skýrsla
2
Evaluation of HARMONIE reanalyses of
surface air temperature and wind
speed over Iceland
VÍ 2014- 005
ISSN 1670- 8261
Skýrsla
+354 522 60 00
vedur @vedur . is
Veður st of a Íslands
Búst aðaveg ur 7 – 9
108 Reyk j avík
Nik olai Nawr i/media/vedurstofan/utgafa/skyrslur/2014/VI_2014_005.pdf
...................................................................................... 30
7 References .................................................................................................. 31
Appendix I - Identification of homogeneous groups of catchments obtained with
the ROI technique and associated growth curves .............................................. 33
Appendix II - WaSiM daily flow simulations: Best run verification for the cali-
bration
/media/vedurstofan/utgafa/skyrslur/2015/VI_2015_007.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
In Iceland, floods are primarily of three different origins (Snorra-
son et al., 2012): (i) meteorological floods induced by rain and which are often combined with
melting of snow and ice, (ii) floods due to ice formation and release within river channels, and
(iii) glacier outburst floods which originate in marginal lakes, formed in glacier dammed side
valleys, or subglacial lakes, formed as a result
/media/vedurstofan/utgafa/skyrslur/2013/VI_2013_008.pdf
Withdrawal
Reliability
Grand Coulee
Recreation
Reliability
R
e
l
i
a
b
i
l
i
t
y
(
%
,
m
o
n
t
h
l
y
b
a
s
e
d
)
Control
Period 1
Period 2
Period 3
RCM
2040-2069
60
80
100
120
140
Firm
Hydropower
Annual Flow
Deficit at
McNary
P
e
r
c
e
n
t
o
f
C
o
n
t
r
o
l
R
u
n
C
l
i
m
a
t
e
PCM Control Climate and
Current Operations
PCM Projected Climate
and Current Operations
PCM Projected
/media/ces/Lettenmaier_Dennis_CES_2010pdf.pdf
and corrected data
-5 0 5 10 15
1
.
0
1
.
5
2
.
0
2
.
5
3
.
0
3
.
5
Temperature,°C
P
r
e
c
i
p
i
t
a
t
i
o
n
,
m
m
/
d
a
y
Jan
Feb Mar
Apr
May
Jun
JulAug
Sep
OctNov
Dec
Year
obs ALUKSNE
DMI 1961-1990 ALUKSNE
mod DMI 1961-1990 ALUKSNE
JanFeb
Mar
Apr
May
Jun
Jul
AugSep
Oct
Nov
Dec
Year
Jan
Feb
ar
Apr
May
Jun
Jul
Aug
Sep
Nov
Dec ear
After the
correction all 3
climate models
agree with
observed data
/media/ces/Kurpniece_Liga_CES_2010.pdf
ECHAM4/OPYC3 NorClim/HIRHAM 25x25 km
'Empirical Adjustment' to 1 x 1 km
100
150
200
250
300
350
400
450
500
550
600
650
700
750
800
850
900
1 10 100 1000
Return period (years)
P
e
a
k
d
a
i
l
y
d
i
s
c
h
a
r
g
e
(
m
3
/
s
)
1981-2010 GEV from annual max series
2021-2050 GEV from annual max series
2021 - 2050 Annual maximum series
1981 - 2010 Annual maximum series
1981-2010
200-year flood
2021
/media/ces/Lawrence_Deborah_CES_2010.pdf
not representative of present or future climate
conditions?
Winter mean T in Helsinki (1961-2008)
1961-
20081961-
1990
Temperature (°C)
P
r
o
b
a
b
i
l
i
t
y
d
e
n
s
i
t
y
-12 4
Simplest case: change in mean climate,
with no change in the magnitude of variability
If variability changes as well, the two tails of the distribution
(e.g., warm and cold) will be affected differently.
IPCC (2001
/media/ces/RaisanenJouni_CES_2010.pdf
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