Seasonal forecasting – prospects for
water resource management
Richard Graham, Climate Applications, Met Office Consulting
Joint meeting of the British Hydrological Society and CIWEM
Exeter University, 21st March 2007
© Crown copyright 2004
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Content
ƒClimate change and climate variability
ƒ need for reliable long-range prediction (eg. to 6 months)
is now greater than ever - to provide early warnings
ƒSeasonal prediction – a developing science
ƒ example forecasts for winters of 2005/6 & 2006/7
ƒ prediction methods – focus on winter season
ƒ probability forecasting
ƒNew forecast products for the UK water sector
ƒ examples for Thames region
ƒFuture prospects for improved prediction skill
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Climate change context:
European 2003 summer temperatures: normal by 2040s, cool by 2060s
Temperature anomaly (wrt 1961-90) °C
2060s
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observations
HadCM3 Medium-High (SRES A2)
2040s
2003
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Change in UK precipitation by the 2080s
Medium – High Emissions scenario
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Observed linear trend in precipitation 1961-2004
winter
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summer
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Winter forecasts 2005/6 and 2006/7
(two very different winters)
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Met Office winter forecast 2005/6
The outcome, DJF 2005/6
The forecast
Observed Europe temperature anomalies
A two in three chance of a colder-thanaverage winter for much of Europe. If this
holds true, parts of the UK – especially
southern regions – are expected to have
temperatures below normal
There is also an indication for a drierthan-average winter over much of the
UK.
Observed UK rainfall anomalies
Customers:
• public
• government (Cabinet office, EA)
• planners in utilities, transport, finance &
insurance, defence, aviation, local authorities
• 71% of public aware, 13% took action
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Met Office winter forecast 2006/7
The outcome, DJF 2006/7
The forecast
Near-average or warmer-than-average
temperatures are the more likely outcomes
for the winter period as a whole for UK and
much of Europe. There is potential for lower
temperatures (relative to average) in mid to
late winter.
Observed Europe temperature anomalies,
relative to 1971-2000
60N
50N
40N
15W
Best estimates slightly favour average or
above-average precipitation for the UK
−10
0
−5
−3
15E
−1
−0.5
0.5
30E
1
Difference from long term average (oC)
3
5
10
Observed UK rainfall anomalies
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Dynamical Prediction:
The Met Office Global Seasonal
Prediction model (GloSea)
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Factors driving the inter-annual variability in seasonal
conditions
larg
e
influ -scale
ence
s
‘chaos’
dry
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wet
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Dynamical Prediction
Met Office Global Seasonal (GloSea) Forecasting System
ƒ Computer model of global ocean-atmosphere system (GloSea)
ƒ version of the Hadley Centre climate model (HadCM3)
ƒ Model is run 6 months forward in time, once each month
analysed ocean/atmosphere state
GloSea model
predicted ocean/atmosphere out to 6 months
ƒ Each forecast comprises 41 ‘slightly differing’ model runs
ƒ to take account of uncertainties in the forecast process
ƒ ‘ensemble’ forecasting
Monthly forecast: more detail 1st month
ƒ Similar ensemble method (51-member ensemble system from ECMWF)
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GloSea model guidance for winter 2006/7
precipitation category, predicted from November
Tercile categories
Forecast of most likely category
Most ensemble members
predicted ‘wet’
wet
DJF
precip
average
dry
}
Equi-probable
from past
climate
Most ensemble members
predicted ‘dry’
No ‘favoured’ category
Observed precip anomalies, winter 2006/7
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Skill measured from retrospective forecasts 1987-2002
ROC scores for the lower tercile category
Skill for MAM temperature, predicted from Feb
Skill for DJF precipitation, predicted from Sep
‘good’ scores
southern Africa rainfall DJF05/6
Predicted from Sept 05
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Observed DJF05/6
Europe/UK rainfall DJF05/6
Predicted from Sept 05
Observed DJF05/6
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Statistical Prediction of the winter North
Atlantic Oscillation (NAO)
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The North Atlantic Oscillation (NAO)
North Atlantic Oscillation
Sea-surface temperature anomalies
Negative NAO
WINTER
(Schematic)
•Various studies indicate a weak forcing of the North Atlantic Ocean on the
winter North Atlantic Oscillation
•Negative NAO implies cold/dry northern Europe
•Positive NAO implies warm/wet northern Europe
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Role of N. Atlantic SST in 2005 and 2006
predicted NAO index at 6months lead
2005
2006
Correct sign
predicted in 2
years out of 3
2005
2006
Weakly positive
winter NAO
predicted
Marked negative
winter NAO
predicted
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(Rodwell
and Folland 2002)
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Inferred probability of above/below normal precipitation
from predicted NAO index
2005/6 (negative NAO predicted)
2006/7 (positive NAO predicted)
Probability of above (green/blue), below (yellow/red) DJF precipitation
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Objective combination and calibration of GloSea
and NAO-based predictions
ƒ an objective method is used to combine GloSea and
NAO forecasts (linear discriminant)
ƒ forecasts from the different methods are weighted
according to historical skill
ƒ corrects for biases in raw dynamical ensemble
forecast probabilities
ƒ allows a degree of regionalisation
ƒ allows ‘outcome’ forecasts eg. river flow rather than
rainfall
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Thames region products, winter 2006/7
- developed with the Environment
Agency
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Historical frequencies for rainfall categories – Thames
region
DJF precipitation probabilities, Thames: historical
35
30
Probability
25
20
15
10
5
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>180
161-180
141-160
121-140
101-120
81-100
61-80
41-60
<40
0
climatology (light
blue) based data
on 1914-2005
analysed on 5km
grid over Thames
region
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Combined dynamical/statistical prediction
for Thames region
GloSea: 4 model grid points closest to
Thames region
2
3
4
Predicted winter NAO index
5
2006
7
8
9
10
0
Weakly positive
winter NAO
predicted
1
1
2
13
14
6
9
17
22
18
23 24
15
2
19
7
8
20
4
3
5
25
calibrated using hindcasts and Thames
precip timeseries 1959-2001 (43yrs)
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p ro b a b ility (% )
Calibrated probabilities for quintile categories:
Thames region DJF 06/7, forecast from November
40
20
0
20% is climatological
probability
33.6%
9.4%
<73.3%
18.2%
20.8%
73.3% to
87.7%
87.7% to 106.2% to >127.3%
106.2%
127.3%
18.0%
precipitation range (% of normal)
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Projecting quintile forecast probabilities onto historical
frequencies – Thames region
DJF precipitation probabilities, Thames: historical
35
30
Probability
25
20
15
10
5
9.4
18.2 33.6
20.8
73.3 87.8 106.2 127.3
18.0
>180
161-180
v. wet
20.0
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141-160
121-140
101-120
v. dry
81-100
61-80
41-60
<40
0
climatology (light
blue) based data
on 1914-2005
analysed on 5km
grid over Thames
region
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Probability forecast for Thames region precip – winter
(DJF) 2006/7
DJF precipitation probabilities, Thames: historical and forecast
observed
= 140%
35
30
Probability
25
20
15
10
5
9.4
18.2 33.6
20.8
73.3 87.8 106.2 127.3
18.0
>180
161-180
v. wet
20.0
© Crown copyright 2004
141-160
121-140
101-120
v. dry
81-100
61-80
41-60
<40
0
climatology (light
blue) based data
on 1914-2005
analysed on 5km
grid over Thames
region
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>180
161-180
141-160
121-140
101-120
81-100
61-80
2006/7
41-60
40
35
30
25
20
15
10
5
0
2005/6
<40
Probability
Observed anomaly
2005/6 = 80%
40
35
30
25
20
15
10
5
0
Probability
Comparison of forecast 2005/6 with forecast 2006/7:
precipitation anomaly Oct-Nov-Dec-Jan-Feb, predicted from
September
Rainfall anomaly (% of 71-00)
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climatology
forecast
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Prospects for improving skill
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Observations:
Recent expansion of ARGO float array
Jan 1996
Jan 2006
Argo
network
ƒ Recent expansion of the ARGO float array is likely helping to
initialise sub-surface ocean temperatures in GloSea
ƒ improving prediction of SST anomaly ‘re-emergence’
ƒ thereby improving dynamical seasonal predictions
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Improve the dynamical model:
eg. response to North Atlantic SST is too weak
Idealised experiments from CGAM, Centre
for Global Atmospheric Modelling, Reading
May
2005
Observed DJF
composites
conditional
on type of
May SST
dipole (+ve or
–ve)
Forecast
DJF05/6
Real-time GloSea
prediction DJF05/6
Long-term
skill DJF
HadAM3
response to
SST dipole
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Skill from retrospective
forecasts 1987-2002
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Summary
ƒ seasonal forecasts to 6-months ahead are generated each
month, providing guidance for all seasons
ƒ global dynamical model
ƒ statistical techniques also used for winter and summer seasons
ƒ prediction skill for precipitation is currently low in Europe/UK
region – but likely sufficient (in some seasons) to add value over
use of climatology
ƒ best physical understanding is for the winter season – when
(predictable) North Atlantic forcing of the NAO is a key factor
ƒ good evidence that success is higher than ‘average’ in years
when ‘forcing’ is strong (forecaster judgment still needed!)
ƒ the process of developing specific seasonal forecast products for
the water industry has commenced – we need your input!
ƒ a specific program for improving prediction skill over the
Europe/UK region is underway
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Improved post-processing:
eg. include pattern correction in calibration/downscaling
2
3
7
4
8
5
9
10
0
‘nearest grid box’
1
1
2
13
14
6
9
17
22
18
23 24
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15
‘regression from key
selected grid-boxes’
2
19
7
8
20
4
3
5
25
ƒ Use of optimally selected grid-points helps
correct systematic ‘pattern’ biases in dynamical
model forecasts
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Forecast for spring 2007…
Temperature
ƒ There is a 70% probability that the mean spring
season temperatures will be above the 1971-2000
long-term average over most of western Europe,
including the UK. These conditions would follow a 12month period that has been the warmest on record.
Precipitation
ƒ Signals for precipitation are mixed over Europe, and in
most regions there is no clear indication for either
above or below normal. For the UK, best estimates
slightly favour average or a continuation of aboveaverage rainfall for the spring season as a whole.
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…. outlook to summer 2007
ƒ A preliminary assessment, based on climate trends
and initial forecast signals, favours a summer warmer
than the 1971-2000 mean. This would continue recent
trends, with the last summer below the 1971-2000
mean now nearly 10 years ago in 1998.
ƒ At this time, it is too early to assess the likelihood of
very-warm mean summer conditions such as those
experienced in 2003 or 2006.
ƒ Full forecast will be issued in April
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Questions & Answers
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