Long-term trends in Northern European
storminess since 1850?
Frederik Schenk & Eduardo Zorita, Helmholtz-Zentrum Geesthacht, Paleoclimate, Institute for Coastal Research, contact: frederik.schenk@hzg.de
Motivation
Historical Pressure Data and Validation
Significant long-term upward trends in Northern European storminess have
been derived [1] from the 20th Century Reanalysis (20CR, [2]). Multiple reconstructions of long-term storminess in contrast do not show any robust
trends on centennial scale. Deviations of low-frequent variations between
20CR and pressure-based reconstructions significantly increase back in time
in parallel to the strong drop in the number of assimilated stations in the 20CR
model. Our hypothesis is that 20CR trends are caused by the lack of data assimilated into 20CR between 1871 till around 1940.
As only few stations are assimilated into 20CR i.e. over the sea in early
periods, we use a new field reconstruction of daily wind speeds to estimate
spatial inconsistencies of centennial trends (Fig. 3). We additionally test a reconstruction with artificially reduced predictors (Test_1850N6) to study the
effect on trends in distant regions to used stations (Fig. 3E-F). A comparison
of low-frequent variations in high annual wind speeds (95th percentiles) is
used to demonstrate increasing deviations of 20CR back in time (Fig. 4).
Table 1: Station information providing daily sea-level pressure (SLP) which is used for the
reconstruction of HiResAFF 1850-2009. (1) = EMULATE (Ansell et al., 2006), (2) = ECA&D (Klein Tank
et al., 2002), Missing values for each station are given in % for the whole period 1850-2009
Location
WMO
Lat.
Lon. Height Start
End Added Misval. Sources
(name)
Identifier [° N]
[° E]
[m]
[year] [year] [year]
[%]
2009
Bergen (Flesland)
1317 60.38
5.33
36 1868 2002
11.27 1, 2
2009
Bodo
1152 67.26 14.43
13 1868 1994
23.17 1, 2
deBilt
6260 52.10
5.18
2 1850 2009
0.02 2
2009
Goteborg
2526 55.70 11.98
155 1860 2002
6.28 1, 2
2009
Hammerodde
6193 55.30 14.78
11 1874
16.75 2
Haparanda
2196 65.82 24.13
6 1860 2002
2008
6.78 1, SMHI
Harnosand
2365 62.61 17.93
6 1860 1995
2008
6.77 1, SMHI
2009
Helsinki
2974 60.17 24.95
56 1850 2001
4.16 1, FMI
2009
Hohenpeissenberg
10962 47.80 11.02
977 1850 2002
4.28 1, 2
2009
Jena
10962 50.93 11.58
155 1850 2000
3.65 1, Jena
Kiev
33345 50.40 30.45
179 1850 1990
-25.53 1
Kremsmuenster
11012 48.05 14.13
383 1876 2009
18.39 ZAMG
Lund
2627 55.70 13.20
73 1864 2001
2008
9.38 1, SMHI
Nordby
6080 55.43
8.40
29 1874 2008
15.62 2
2009
Oksoyfyr
1448 58.07
8.05
8 1870 2002
12.62 1, 2
Riga
26422 56.81 23.89
13 1850 1990
-21.77 1
Stockholm
2485 59.33 18.05
44 1850 1998
2008
0.47 1, SMHI
StPetersburg
26063 59.93 27.96
6 1850 2000
-5.48 1
Torshavn
6011 62.02 -6.77
55 1874 2009
15.53 2
2009
Vardo
1098 70.36 31.10
15 1861 2002
43.34 1, 2
Vestervig
ECA107 56.77
8.32
19 1874 2009
15.11 2
2009
Visby
2591 57.63 18.28
47 1860 2002
6.37 1, 2
1850
Wilna
26730 54.68 25.30
156
1990
-27.45 1
DJF
JJA
correlation
grid No: 1 = signif. (p < 0.05), 0 = not significant
Fig. 1: Correlation of seasonal wind speed between HiResAFF and NCEP (1961-2007).
In contrast to 20CR, this skill will not change much in the period 1874-2008 as the number of predictors (Tab. 1) and the
distance (the RMSE) between analogs in Fig. 2 remain constant in this period.
pool of observed analogs
(RCM/Reanalysis 1958-2007)
reconstructed fields
1850-2009
Analog-Reconstruction
We use the analog-method (AM) as non-linear upscaling tool to reconstruct
High Resolution Atmospheric Forcing Fields (HiResAFF) [3] since 1850.
Based on station pressure (Tab. 1), the AM searches for the highest pattern
similarity between days since 1850 and the recent past. For the latter, fields
for the analogs are taken from a pool of atmospheric fields from a regional climate ocean model [4] forced by ERA40 reanalysis. The AM is used to redistribute these fields (predictand) according to the highest similarity concerning
the pool of observational time series (predictor) (Fig. 2).
HiResAFF: Uses all 23 stations in table 1 with updates where available.
Test_1850N6: Only 6 stations (in red) are used for the whole period since 1850.
.
target fields
from RCM
A
C
Based on station SLP, days a
and c etc. have the highest
pattern similarity with the 1st
B
A
C
and 2nd January 1850. The AM
upscaling
P(t)
P(u)
t
γ
α
1850-01-01
1850-01-02
assumes that also corresponding
station data
or proxy
b
a
c
1959-02-07
2005-01-02
1963-12-10
min || P(u) – P(t) ||
station data/proxy
(predictor 1850-2009)
u
fields A and B should be quite
similar given that SLP has a
strong physical link to predict
pool of observed analogs
(predictand 1958-2007)
pressure and wind fields.
Fig. 2: Analog-upscaling combining station pressure (predictor) and atmospheric fields from regional climate models [3].
Centennial trends of median and 95th percentile wind speeds 1871-2008
20th Century Reanalysis
HiResAFF
Test_1850N6
Spread in trends for 95th pctl.
A) 95th pctl.
C) 95th pctl.
E) 95th pctl.
G) 95th pctl. 20CR
B) 50th pctl.
D) 50th pctl.
F) 50th pctl.
H) 95th pctl. HiResAFF
trends [m/s per 100years]
trends [m/s per 100years]
trends [m/s per 100years]
Fig. 3: Comparison of long-term trends [in m/s per 100 years] for storminess (annual 95th pctl.) and median (annual 50th pctl. ) wind speeds for the period 1871-2008. A) and B): Ensemble mean trend estimated from all 56 members from near-surface
(sigma995) wind from 20CR. C) and D): Trends of the annual 50th and 95th percentile of near-surface (10 m) wind from HiResAFF. E) and F): same as C-D for Test_1850N6 using only six stations over the central domain (Tab. 1). G: absolute spread of trends
between the ensemble max. and min. trends of annual 95th pctl. H: abslute spread between trends of HiResAFF and Test_1850N6. White areas show no significant trends (p < 0.05) using a t-test. Horizontal resolution 2°x2° (20CR) and 0.25°x0.25° (HiResAFF).
Variability of storminess since 1850
NE-Atlantic
7.6
4.2
7.2
wind speed anomalies [m/s]
7.8
7
7.4
6.8
7.2
6.6
7
6.6
3
4
2.8
3.8
Northern Scandinavia
6.4
6.8
1860
1880
1900
1920
1940
1960
1980
Discussion
3.6
6.2
2000 3.8
1860
1880
1900
1920
1940
3.2
1960
4
2.6
2000
1980
3
Eastern Baltic Sea
3.6
3.8
3
2.8
3.4
2.8
3.6
2.6
2000
3.4
3.2
3
6.2
5.2
Central Scandinavia
1860
1900
1920
1940
1960
5.4
North Sea
6
1880
1980
1860
1880
1900
1920
1940
1960
1980
2.6
2000
3.8
Baltic Proper
5.2
5
5.8
5
5.6
3.6
4.8
5.4
5.2
4.8
1860
1880
1900
1920
1940
1960
1980
4.6
2000
4.6
1860
1880
1900
1920
1940
1960
1980
3.4
2000
20CR ensemble spread
20CR ensemble mean
HiResAFF
3.6
3.6
2.6
3.2
3.4
3.4
2.4
3.2
3
3.2
Belarus
3
Germany
2.8
1860
1880
1900
1920
1940
3
1960
1980
1860
1880
1900
1920
1940
1960
1980
2.2
2000
2.8
2000
Fig. 4: Long-term (30a) variations of annual 95th pctl. wind speeds of 20CR (green) vs. HiResAFF (blue).
Deviations are highest in the W (over Sea) with an unusually calm early period in 20CR.
HiResAFF confirms earlier studies [4] showing increased storminess in the
1990s and 1880s while 20CR shows very low storm activity in the early period
(Fig. 4) causing spurious upward trends. Deviations are largest in the western
and northern domain where only very few stations are assimilated into 20CR
before 1940. Also Test_1850N6 (Fig. 3 E-F) with an artifically reduced number
of predictors (Tab. 1) shows that the analog-reconstruction would lead to comparable „spurious“ trends in regions not covered well by stations (N and W).
We argue that trends derived from HiResAFF are reliable as the number
of stations and the distance between analogs remains constant since 1874.
Estimations of long-term trends in storminess should not rely on 20CR in the
early period in this region.
References:
[1] Donat et al., 2011, GRL, 38
[3] Schenk & Zorita, 2012, CPD 8
Helmholtz-Zentrum Geesthacht • Max-Planck-Straße 1 • 21502 Geesthacht • Phone +49 (0)4152 87-1862 • Fax +49 (0)4152 87-2832 • www.hzg.de
Contact: Frederik Schenk
[2] Compo et al., 2011, Q. J. R. Meteorol. Soc. 137
[4] Krüger & von Storch, 2011, J. Climate 24