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Some Strengths and Weaknesses of ECMWF Forecasts for the UK

Tim Hewson 15th June 2006

Contributors include: Eleanor Crompton, Tim Legg, Helen Watkin

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Contents

Synoptic Scale performance around the UK

Subjectively-verified EC OP and ensemble forecasts

Focus on adverse/severe weather

1. Snow

2. Strong Winds

3. New products – Cyclonic feature tracking

Summary of recommendations

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Synoptic Scale performance around the UK

GOOD FORECASTS

EC OP EC ENS MEAN

19/20 -

4/5 -

3/5 -

1/4 1/4

1/10 1/10

POOR FORECASTS

EC OP EC ENS MEAN

1/300 -

1/40 -

1/10 -

1/4 1/5

1/2 1/2

DAY 3

DAY 4

DAY 5

DAY 6/7

DAY 8-10

12Z Forecasts subjectively verified during 2005

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Comparison with previous years

Some signs of year on year improvement at all leads, though always a noisy signal

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Multi-model comparison

Within the ‘basket’ of international operational models, NCEP appear to have suddenly become very competitive.

Especially true in winter. Similar results seen for other lead times.

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Snow in the UK

ECMWF forecasts provide key input to early warning issue

Primarily this is through the Met Office’s calibrated, automated ‘First Guess Early Warning System’ (FGEW) derived from ensemble output. One parameter - snow ppn total.

The utility of FGEW has been revisited for the 2005/6 winter, using a number of high profile UK snow events (‘hits’ and ‘misses’ only)

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UK Snow Cases - 2005/6 winter

Nov 25th SW England - 7% *Nov 28th W/SW Midlands - 4%Dec 27th E England - 4% *Dec 30th E England - 30%Mar 3rd+ NE Scotland - 1%Mar 3rd N England - 4%Mar 12th NW of UK - 70% *Apr 10th SE England - 1%

Values show FGEW probabilities at 3/4 day lead times.Greater than 10cm snow believed to have occurred at populated altitudes in each of the above cases. All were highlighted by the media. For the convective cases highlighted in red there was little or no increase in probabilities as the event approached.

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Mar 12th 2006 – NW of UK

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Mar 12th 2006 – NW of UK

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Snow Events in the UK

Handling of frontal snow cases by the EPS and FGEW looks good, and has proved very useful to forecasters, in this and previous winters

These constitute approximately 50% (?) of all winter snow cases

Unfortunately the handling of convective cases is much worse, with EPS and FGEW generally misleading (though broadscale often useful)

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Dec 27th 2005 – E England

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Dec 27th 2005 – E England

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Nov 25th 2005 – SW England

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Nov 25th 2005 – SW England

EPS member gridbox

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Precipitation Drift

MODELS

Up to ~100km

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Precipitation totals for Cornwall / Bodmin Snow Event – Nov 2005

Key weakness of current operational

(12km) model formulation well

illustrated – snow focussed over seas.

Same is true of EC model – due to

parametrisation used

Little or no propogation inland.

Reality (≈radar) very different, partly due to slow fall speed of

snow.

contours showorography

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Options: Met Office

Parametrisation could incorporate ‘snow-drift’ effect. More appropriate for higher resolution.

The first Met Office Mesoscale model did this (lost during unification).

This aspect is very high priority for forecasting in the Met Office.

Special field modification tools being built in the short term. Inputs – convective cloud depth, wind profile, freezing level.

Higher resolution models will be used longer term

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Verification of Chief Forecaster’s Output

Forecaster’s greatest contribution in short term forecasts is in reducing errors associated with cold air convection

In winter snow is often involved

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Options: ECMWF

For ECMWF data, scope for a post processing stage, to smear out convective ppn totals inland, according to wind strength and freezing level

Worth considering, though boundary layer temperature variations add complexity

In some cases, such as the Cornwall event, this would not work – complexity of mesoscale flow patterns is also too great

Incorporation into parametrisation may be the best strategy?

Important consideration: affects other parts of Europe with coasts

information content of model runs is being wasted

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H

L

CornwallSnow event12Z 25/11/05Mesoscalestructure

0C

+5C

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Strong Winds

A strong wind representivity problem exists for fast moving systems

This arises because of diagnostic types used around the world

It is more acute because faster moving systems have a greater potential to facilitate strong winds developing inland (trajectory curvature on S flank is reduced)

Affects Met Office models, EC model, EFI (?)

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This winter’s ‘one storm’! -12Z 10/1/06

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18Z

=Strong Wind Zone

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00Z

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06Z

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12Z

X

No strongwinds expected here??!

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Solution

New but simple lower tropospheric wind diagnostics are required

Interrogation of every model timestep should be usedAnalogous to rainfall accumulationsName of resulting plan view field would be (eg) ‘Max

10m wind in 6 hours up to VT’This would emphasise damage swathes

Similar ideas should be used for interrogating temperatures, etc – why not correlate (MOS) with model max temperature, rather than model 12Z temperature (as in talk yesterday!) ?

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Cyclonic windstorms

Even with improved diagnostic selection, models still fail to fully represent details and strength of damaging windstorms

Resolution and boundary layer issues.. 4+kts rms 10m wind speed error in EC over Europe.

For the more extreme events recalibration is unreliable and ill-specified

Windstorms are however related to synoptic features - commonly a cyclone, which often evolves from a frontal wave – and which models can represent

A feature-based approach is used widely within operational forecasting

Therefore use feature-tracking within model forecasts as a conduit for understanding and forecasting windstorms

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Objective Cyclonic Features - Snapshot

Frontal Wave

Barotropic Low

Diminutive Wave

Frontal Wave (weak)

Diminutive Wave (weak)

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Conceptual Cyclone Life-Cycle

0 3 4 5 6

2-d Front Frontal wavecyclone

Frontal fracture

T-bone Mature cyclone

1

Diminutivefrontal wave

2

Frontal wave

After Shapiro and Keyser (1990) – stages 3-6

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Example: Windstorm Damage,19 Nov 04, Slovakia

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Storm track, 12h interval00Z, 18th Nov 04 to 12Z, 22nd

1 2

1

2

3

3

4

4

5

6

5

6

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Application to ECMWF ensemble data

As part of THORPEX / TIGGE

Code used out to 15 days

Different post-processing strategies required for different lead times

Under development - 2 examples presented

Thanks to Helen Watkin

Processing code will soon be running at ECMWF

Also being used in Met Office MOGREPS ensemble

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Example Storm in EC Ensemble forecasts

Click on featureTo follow evolution

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Feature-Specific plumes

MSLP

Vorticity

Max 1km WindWithin 300kmRadius of feature

Feature tracks

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Longer Ranges - use feature track density

T+120

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Summary of Requests/Recommendations

New diagnostics required that utilise multi time-step interrogation – especially for near surface winds

Improved re-derivation of EFI, SOT, SPS based on the above?

Strategy for addressing snow-drift? – views of other member states?

Archive of forecasts of severe events, or hindcasts of these from more recent models, valuable for testing new approaches, such as cyclonic feature tracking

More web-based diagnostics – eg from Operational runs - would help Met Office forecasting effort at all lead times - see last year’s wish list – this still applies!

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Supplementary slides follow

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Nov 28th 2005 – W/SW Midlands

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Nov 28th 2005 – W/SW Midlands

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Dec 30th 2005 – E England

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Dec 30th 2005 – E England

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Mar 3rd 2006 – NE Scotland / N England

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Mar 3rd 2006 – NE Scotland / N England

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Apr 10th 2006 – SE England

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Apr 10th 2006 – SE England

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Scope for Improvement

Forecasters are usually able to improve upon raw (Met Office) model output, using different models, knowledge of systematic errors, comparison with current trends

Degree of improvement could potentially be increased by making more use of the high quality ECMWF operational run, which at present is under-utilised

WISH LIST! –

3 hourly data, T+0 to T+48

Instantaneous total ppn rates, plus cloud cover and mslp (same format?!)

Separate plots showing dynamic /convective rain and snow components

10m mean wind and likely gust strength

Sub areas – parts of Europe ?

Timely appearance on ECMWF web site is crucial (probably the most expedient route for making this data available)

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Extras for ‘Wish List’

Meteograms to include overlapping 24-hour rainfall totals (but still in 6 hour blocks)

Total cloud cover – is this ‘altitude weighted’, or is 8 oktas cirrus considered ‘cloudy’? Weighting would be preferable

Postage stamps showing estimated surface gusts, with colour-shading for high values

Cluster ensemble means for mslp, thickness, annotated with percentages of members

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Accreditation

WAFCWorld Area Forecast Centre