The 2005/06 UK and European winter:
the UCL forecast and its assessment
against observations
precipitation and windspeed across the UK
and Europe.
Dept. of Space and Climate Physics,
Benfield UCL Hazard Research Centre,
University College London
North Atlantic Oscillation
(NAO)
The European winter of 2005/06 was
notably cold, dry and calm (Weather, 61,
pp. 94 and 108). Provisional data from the
NCEP/NCAR climate re-analysis (Kalnay et al.
1996) suggest that for Europe as a whole
(region 35°N–65°N, 15°W–35°E) the winter of
2005/06 was the coldest since 2002/03 and
the least windy since records began in
1950/51. For the UK as a whole it was the
coldest winter since 2000/01 (Weather, 61,
pp. 94). How well did the publicly-available
seasonal outlooks anticipate the nature and
severity of this unusual winter? Companion
papers in this issue (Graham et al. 2006;
Folland et al. 2006) describe the scientific
basis and performance of the seasonal forecasts issued by the Met Office for winter
2005/06. Here we describe the outlook
issued by University College London (UCL)
for winter 2005/06 and assess its retrospective performance for temperature,
The UCL and Met Office winter outlooks for
2005/06 were underpinned by a forecast of
the winter North Atlantic Oscillation. The
North Atlantic Oscillation (NAO) is the dominant influence on winter climate variability
over the North Atlantic, Europe and eastern
North America (Walker and Bliss 1932; van
Loon and Rogers 1978; Osborn 2006). Yearto-year changes in the strength and sign of
the winter NAO are linked to interannual
variability in wintertime temperature, precipitation and storminess over the North
Atlantic and across Europe (Hurrell 1995;
Marshall et al. 2001; Trigo et al. 2002). The
correlation between these climate parameters and the ‘winter NAO’, defined henceforth as NAODJF where DJF is the 3-month
winter period December–January–February,
reaches 0.7 (p < 0.001; 1950–1 to 2004/05) at
certain locations. Thus, skilful NAO seasonal
forecasts could bring socio-economic benefits by forewarning of winter climate
anomalies and their impacts on business
revenue, commerce and society.
The NAO is an oscillation in atmospheric
pressure between the North Atlantic’s subpolar (Icelandic) low pressure and subtropical (Azores) high pressure regions. The
NAO has two phases (+ve and –ve). A +ve
NAO DJF is associated with a deeper Icelandic
low and strengthened Azores high compared to the norm. A –ve NAODJF is associated with a weaker Icelandic low and weaker
Azores high than the norm. The schematic in
Fig. 1 illustrates the different physical nature
of +ve and –ve NAODJF winters and their different climate impacts. A +ve NAODJF is
linked to warm, wet and stormy winters over
north-west Europe, and to dry and calm
winters over the Mediterranean. In contrast
a –ve NAODJF is linked to cold, dry and calm
winters over north-west Europe and to wet
and stormy winters over the Mediterranean.
Weather – December 2006, Vol. 61, No. 12
Mark A. Saunders
Adam S. R. Lea
UCL forecast model for NAODJF
The UCL NAODJF forecast model used to predict NAODJF 2005/06 comprises an ensemble
of two separate statistical forecasts made
with prior June/July Northern Hemisphere
Fig. 1 The physical nature and ‘typical’ winter climate impacts of positive and negative phases of the North Atlantic Oscillation (NAO). Image courtesy of Prof Martin
Visbeck, Leibniz-Institut fuer Meereswissenschaften (IFM-GEOMAR).
347
The 2005/06 UK and European winter
Weather – December 2006, Vol. 61, No. 12
348
(a)
(b)
Fig. 2 The associations between summer sub-polar surface air temperature, summer Northern Hemisphere snow cover, and the upcoming winter NAO for the period
1972/73 to 2001/02. (a) The correlation pattern significance between detrended time series of gridded June–July 2 m surface air temperature and June–July Northern
Hemisphere snow extent. Significances are corrected for serial correlation. The shading also denotes where the correlation is positive (orange through red) or negative
(light through dark blue). (b) The strength and significance of the correlation between the lagged sub-polar zonal air temperature difference TSP = (North America +
Eurasia)/2 – South Greenland and upcoming winter NAODJF indices. The correlations from detrended time-series are plotted. Dashed lines display the confidence levels
of non-zero correlation between TSP and the MSLP NAODJF index assessed using a 2-tailed Student’s t-test after correction for serial correlation. The bi-monthly lagged
TSP intervals range from JF (January–February) through to ND (November–December). (After Saunders et al. (2003) and Fletcher and Saunders (2006)).
sub-polar surface air temperatures and with
prior June/July Northern Hemisphere snow
cover (Saunders et al. 2003; Fletcher and
Saunders 2006). This multi-model anticipates whether NAODJF will be above or
below median – for a range of NAO indices –
in 65%–76% of the winters during the
1972/73 to 2005/06 period of reliable snow
cover monitoring (Robinson et al. 1993). The
basis for this model is the study of Fletcher
and Saunders (2006) who, in a standardized
comparison of NAODJF hindcast skill for
different published predictors against three
NAODJF indices and over three extended
periods (1900–2001, 1950–2001 and 1972–
2001), conclude that the highest and most
significant hindcast skill for all periods and
all NAODJF indices is achieved with TSP, an
index of prior summer sub-polar Northern
Hemisphere air temperature. Warm season
snow cover provides a limited enhancement
to the hindcast skill from TSP alone for the
period 1972/73 to 2005/06. Figure 2 shows
the recent empirical link between TSP, summer snow cover and NAODJF.
The suggested physical mechanism for
how summer TSP may influence NAODJF is as
follows. Summer TSP is associated with a
contemporaneous anomaly in North
Atlantic mid-latitude zonal wind. This leads
to an anomaly pattern in North Atlantic sea
surface temperature (SST) which persists
through autumn. Autumn SSTs may force a
direct thermal NAODJF response or initiate an
NAODJF response via a third variable. Fletcher
and Saunders (2006) present observational
evidence to support this multi-step dynamical link. Although this physical mechanism is
plausible, the existence of another underlying root influence which forces the
variability in TSP as well as all associated
linking variables cannot be ruled out.
Numerical model experiments with
prescribed TSP will be required to resolve this
question.
NAODJF 2005/06 forecast and
verification
UCL issued its forecast for NAODJF 2005/06
on 7 October 2005 through its http://
climate.mssl.ucl.ac.uk website. The forecast
comprised deterministic and tercile probability forecasts for three leading NAODJF
indices. These indices were (a) the standardized difference in mean sea level pressure
(MSLP) between south-west Iceland and
Gibraltar (Jones et al. 1997) compiled by the
Climatic Research Unit at the University of
East Anglia; henceforth the CRU NAODJF index.
(b) the NAO teleconnection index maintained by the US Climate Prediction Center
(CPC) and computed from the rotated principal component analysis of monthly
Northern Hemisphere 700 mbar geopotential heights (Barnston and Livezey 1987);
henceforth the CPC NAODJF index. (c) the
leading principal component of North
Atlantic DJF MSLP over the same (20°N–70°N,
90°W–40°E) sector employed by Hurrell
(1995); henceforth the MSLP NAODJF index.
The UCL deterministic and tercile probabilistic forecasts for the 2005/06 NAODJF are
shown in Tables 1 and 2 together with their
verifications. The deterministic forecasts are
compared to the 1972/73 to 2004/05
climate norm NAODJF values. Additionally,
Fig. 3 displays graphically the UCL forecast
for the CRU NAODJF index 2005/06 in terms of
probability of exceedance. The CRU NAODJF
index is selected as it is arguably the NAODJF
index most strongly linked to European
winter temperature, precipitation and windspeed. The main points to note from Tables 1
and 2 and from Fig. 3 are: (1) the 2005/06
winter NAO fell at the 12th–40th percentile
historically and was the lowest NAODJF since
the winter of 1995/96; (2) The UCL deterministic forecasts showed skill compared to
climate norm forecasts for all three NAODJF
indices. The CPC NAODJF index was predicted
to within 0.06 of its actual value; (3) The
tercile probability forecasts gave the CRU
NAODJF index as five times more likely to lie in
the lowest tercile than in the highest tercile
historically. The lowest terciles were also
favoured for the CPC and MSLP NAODJF indices.
The verifications showed that the CRU and
MSLP NAODJF indices 2005/06 fell in the lowest
tercile but that the CPC NAODJF index just fell
in the middle tercile. Overall the UCL forecasts slightly over-predicted the CRU and
MSLP indices but closely predicted the CPC
index.
Here we examine retrospectively the implications of the UCL winter 2005/06 NAO forecast for temperature, precipitation and
windspeed anomalies for the UK and mainland Europe. We also compute the most likely anomalies in these weather parameters if
the NAODJF had been forecast perfectly.
Pattern correlation (Wilks 2006) is then
employed to assess how well the ‘Forecast
from predicted NAODJF’ and ‘Forecast from
actual NAODJF’ weather anomaly maps across
Europe compare to the observed anomaly
Weather – December 2006, Vol. 61, No. 12
maps for winter 2005/06. Pattern correlation
is a simple technique for quantifying how
well one weather map resembles another
weather map. Monthly NCEP/NCAR global
re-analysis project data (Kalnay et al, 1996)
are employed for the historical gridded
records of 2 m air temperature, accumulated
precipitation and 10 m windspeed back to
1950/51, and for the observed anomalies in
these parameters during winter 2005/06.
All anomalies are interpolated on to a
0.5 degree grid and expressed relative to the
1971/72 to 2000/01 climate norm.
The procedure for computing the
‘Forecast from predicted NAODJF’, values for
Implications for temperature,
precipitation and windspeed
The 2005/06 UK and European winter
Fig. 3 The UCL forecast for the CRU NAODJF index 2005/06 displayed in terms of probability of exceedance
and compared against the 1972/73 to 2004/05 climatology.
temperature, precipitation and windspeed
is as follows. Each winter between 1950/51
and 2004/05 is assigned a weighting value
determined from the forecast probability
distribution function for the 2005/06 CRU
NAODJF index. This weighting value is the
probability from this distribution corresponding to the value of the CRU NAODJF index in
each historical winter. The implied forecast
anomaly in each weather parameter at each
grid point follows by taking the mean of the
individual probability weighted yearly values for that particular weather parameter at
each grid point. The ‘Forecast from actual
NAODJF’ values for temperature, precipitation
and windspeed are calculated as follows.
They comprise composite gridded maps of
the relevant weather parameter based on all
years between 1950/51 and 2004/05 where
the CRU NAODJF index was between –1.22 and
–0.22 inclusive (ie within 0.50 of the actual
CRU NAODJF index value in 2005/06 (Table 1)).
It should be stressed that while the ‘Forecast
from predicted NAODJF’ and ‘Forecast from
actual NAODJF’ weather anomaly maps
indicate the most likely anomalies across
Europe, the uncertainties (not shown) in
these forecasts can be high.
Figures 4 and 5 display the most likely
anomalies in winter 2005/06 2 m air temperature, accumulated precipitation and 10 m
windspeed across the whole of Europe
based on the UCL-predicted and actual CRU
NAODJF index values. The observed anomalies
in each parameter are also included for
reference. For temperature, the ‘Forecast
from predicted NAODJF’ anticipated the UK
and much of mainland Europe (except the
south-east) being 0.0 to 1.0 degC colder
Table 1
Verification of UCL Deterministic Forecasts for 2005–06 NAODJF
NAO Index
Climate Norm ± SD
(1972–3 to 2004–05)
Forecast ± FE
2005–06
Observed
2005–06
Percentile
2005–06
0.58 ± 1.32
–0.12 ±1.01–
–0.72
12th
CRU NAODJF index
CPC NAODJF index
0.28 ± 0.65
0.07 ± 0.55
–0.13
42nd
MSLP NAODJF index
0.36 ± 1.17
0.02 ± 0.96
–0.31
30th
SD = Standard Deviation
FE = Forecast Error = Standard deviation of errors from cross-validated hindcasts from 1972–73 to 2004–05
Table 2
Verification of UCL Tercile Probabilistic Forecasts for 2005–06 NAODJF
CRU NAODJF index
Tercile
probability
CPC NAODJF index
Below Normal Above
normal
normal
MSLP NAODJF index
Below
normal
Normal
Above
normal
Below
normal
Normal
Above
normal
Forecast (%)
55
34
10
45
36
19
44
38
19
Climate (%)
33.3
33.3
33.3
33.3
33.3
33.3
33.3
33.3
33.3
Actual (%)
100
0
0
0
100
0
100
0
0
349
The 2005/06 UK and European winter
Weather – December 2006, Vol. 61, No. 12
Fig. 4 The most likely anomalies in winter 2005/06 2 m air temperature and accumulated precipitation across Europe based on (a) the UCL forecast for the CRU NAODJF
index and (b) the actual CRU NAODJF index. The observed anomalies are displayed in row (c). Note that in the maps showing precipitation anomalies, orange denotes
above average and blue denotes below average amounts.
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The 2005/06 UK and European winter
Weather – December 2006, Vol. 61, No. 12
Fig. 5 The most likely anomalies in winter 2005/06 10 m windspeed across Europe based on (a) the UCL forecast for the CRU NAODJF
index and (b) the actual CRU NAODJF index. The observed anomalies are displayed in panel (c).
351
The 2005/06 UK and European winter
Weather – December 2006, Vol. 61, No. 12
than the norm. The ‘Forecast from actual
NAODJF’ anticipated a similar pattern but with
temperatures slightly colder at 0.0 to 1.5
degC below norm. The observed temperature anomalies in winter 2005/06 show that
mainland Europe had temperatures over
2.0 degC colder than the norm but that the
northern half of the UK and northern
Scandinavia had temperatures 0.0 to
1.5 degC warmer than the norm. The pattern
correlation between the ‘Forecast from predicted NAODJF’ map and the observed weather anomaly map is 0.13; this rises to 0.40
when comparing the ‘Forecast from actual
NAODJF’ and the observed weather anomaly
maps. These values indicate weak pattern
similarity with the ‘Forecast from actual
NAODJF’ offering closer resemblance to the
actual winter 2005/06 temperature pattern.
However, even if the CRU NAODJF index value
in 2005/06 had been predicted perfectly the
temperatures over much of mainland
Europe would have been over-predicted
by 1 to 2 degC and the temperatures over
the northern UK and Scandinavia underpredicted by 1 to 1.5 degC.
For precipitation (Fig. 4) and windspeed
(Fig. 5) the resemblance between the forecast and observed weather anomaly maps is
higher than for temperature. The observed
pattern of winter 2005/06 precipitation
shows that north-west Europe had belowaverage precipitation (up to 40% below),
while south-east Europe had above-average
precipitation (up to 40% above). The pattern
correlation between the ‘Forecast from predicted NAODJF’ map and the observed weather anomaly map is 0.52; this rises to 0.60
when comparing the ‘Forecast from actual
NAODJF’ and the observed weather anomaly
maps. Winter 2005/06 windspeed was
below-norm everywhere in Europe except
northern Italy and southernmost France. In
many places the windspeed was more than
40% below average, making 2005/06 the
least windy European winter since at least
1950/51 (according to the NCEP/NCAR
climate re-analysis data). The pattern correlation for windspeed between the ‘Forecast
from predicted NAODJF’ map and the
observed weather anomaly map is 0.52; this
is similar to the 0.51 value from comparing
the ‘Forecast from actual NAODJF’ and the
observed weather anomaly maps. Despite
these positive pattern resemblances the
NAODJF – based forecasts in general underpredicted the magnitude of the observed
anomalies for precipitation and windspeed.
Summary
352
The winter 2005/06 North Atlantic
Oscillation was the most negative NAODJF
since 1995/96. The UCL deterministic and
probabilistic statistical seasonal forecasts for
the 2005/06 NAODJF showed reasonable precision for all three NAODJF indices. We have
examined the most likely anomalies in
winter 2005/06 temperature, precipitation
and windspeed across the UK and whole of
Europe based on the UCL forecast CRU NAODJF
index and on the observed CRU NAODJF index
2005/06. Weather predictions from the UCL
forecast NAODJF index show positive pattern
correlations with the observed anomaly
maps for all three weather parameters.
Pattern resemblances were best for precipitation and windspeed. A perfect forecast of
the CRU NAODJF index would have given
improved pattern correlations for temperature and precipitation. However, even with a
perfect prediction of the winter 2005/06
NAO, the true nature of the cold, dry and
calm conditions characterising this unusual
winter for much of Europe would have been
under-predicted.
Outlook for 2006/07 European
winter
UCL issued its extended range forecast for
the 2006/07 winter North Atlantic
Oscillation on 25 August 2006 (http://
climate.mssl.ucl.ac.uk). The forecast anticipates NAODJF being near-neutral to slightly
above-norm. The tercile probability projections for the CRU NAODJF index 2006/07 are
32% for above-average, 43% for nearaverage and 25% for below-average. The
forecast document includes gridded projections for the most likely anomalies in 2 m air
temperature, accumulated precipitation
and 10 m windspeed across Europe based
on the forecast CRU NAODJF index.
Acknowledgements
This work was supported in part by funding
from the UK Natural Environment Research
Council. We thank Chris Fletcher and
Benjamin Lloyd-Hughes for helpful discussions. We acknowledge the Snow Data
Resource Center at Rutgers University for
snow extent records (http://climate.
rutgers.edu/snowcover) and NOAA- CIRES,
Climate Diagnostics Center, Boulder,
Colorado for the NCEP/NCAR Global
Re-analysis Project Data.
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Correspondence to: Prof. Mark Saunders,
Department of Space and Climate Physics,
University College London, Holmbury St Mary,
Dorking, Surrey, RH5 6NT.
e-mail: mas@mssl.ucl.ac.uk
© Royal Meteorological Society, 2006
doi: 10.1256/wea.183.06