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Forecasting Uncertainty Met Office. Ewen McCallum Chief Meteorologist. Met Office - Exeter. Forecasting the weather. Worldwide Observations Satellite, land, ship, aircraft, radar, radiosonde, drifting buoy. Sources of Observation. Things you may not know about the Met Office. Each day:

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Forecasting Uncertainty

Met Office

Ewen McCallum

Chief Meteorologist



Forecasting the weather
Forecasting the weather

Worldwide Observations

Satellite, land, ship, aircraft, radar, radiosonde, drifting buoy



Things you may not know about the met office
Things you may not know about the Met Office

  • Each day:

    • 10 million pieces of observation data processed

    • 100,000 million pieces of information within our forecasting models

    • 8,500 weather observations, from over 3,000 sites, produced in the UK

    • 1,500 surface and over 40 upper-air observations produced by our staff


Forecasting the weather1
Forecasting the weather

Worldwide Observations

Satellite, land, ship, aircraft, radar, radiosonde, drifting buoy

Numerical Models


What is nwp
What is NWP?

  • NWP: Numerical Weather Prediction

    • Create mathematical models of the atmosphere

    • Analyse global observations

    • Giant simulator representing physical laws

    • Run the model to produce a prediction

    • Use of supercomputers in weather forecasting


Computers
Computers

NEC SX6


Nwp grid
NWP grid

  • Global 60km, 38L

  • UK 12km, 38L

  • Several relocatable Defence Models

  • 16km, 38L

  • Global Stratosphere 300km, 42L


Improvements in nwp
Improvements in NWP

Mean Sea Level Pressure N Atlantic and W Europe


Forecasting the weather2
Forecasting the weather

Worldwide Observations

Satellite, land, ship, aircraft, radar, radiosonde, drifting buoy

Numerical Models

Operations Centre



Forecasting the weather3
Forecasting the weather

Worldwide Observations

Satellite, land, ship, aircraft, radar, radiosonde, drifting buoy

Numerical Models

Operations Centre

Forecaster Consultant Media Presenters Local Centre


Media
Media

BBC


Forecasting the weather4
Forecasting the weather

Worldwide Observations

Satellite, land, ship, aircraft, radar, radiosonde, drifting buoy

Numerical Models

Operations Centre

Forecaster Consultant Media Presenters Local Centre

Customer


Revenue 2003 4
Revenue 2003/4

Income vs costs



The met office has a world leading forecasting system but nevertheless
The Met Office has a World-leading forecasting system, but nevertheless…

  • All forecasts are uncertain

  • High-profile forecast failures are now rare, but do still occur (e.g. Dec 1999 European storms)

  • Less severe errors are much more common,

    e.g.

    • medium-range forecasts

    • finer details such as timing of rainfall

  • Ensembles turn weather forecasts into Rick Management tools


The effect of chaos

The atmosphere is a chaotic system: nevertheless…“… one flap of a seagull’s wing may forever change the future course of the weather”, (Lorenz, 1963)

Up to about 3 days ahead we can usually forecast the general pattern of the weather quite accurately

Beyond 3 days Chaos becomes a major factor

The Effect of Chaos



Day nevertheless…three


Day nevertheless…seven


Day nevertheless… one


Ensembles
Ensembles... nevertheless…

Deterministic Forecast

Forecast uncertainty

Initial Condition Uncertainty

X

Analysis

Climatology

time


Ensembles1
Ensembles - nevertheless…

  • By running the model many times with small differences in initial conditions (and model formulation) we can:

  • take account of uncertainty

  • estimate probabilities and risks (eg. 30 members out of 51 = 60%)


The EPS provided a range of possible scenarios nevertheless…

Return to mild...

Range

22 K

Obs 8 deg warmer than fcst

Long cold spell...


Eps meteogram
EPS Meteogram nevertheless…

  • Plot of ensemble spread

    • Box shows 25-75% range

    • Whiskers show 95% confidence range

    • Central bar shows median – can indicate most probable

  • Summarises forecast at one location for 10 days ahead

  • Met Office calibrates ensemble forecasts to improve quality


Short range applications
Short-Range Applications nevertheless…

  • Allow us to assess uncertainty in short-range forecasts, e.g.

    • Energy demand (European Open Market)

    • autoTAF – visibility, low cloud

    • Transport – road, rail, air, shipping

    • Aircraft icing

  • Assess Uncertainty where local detail required, eg.

    • Sea breezes

    • River catchment flooding




Traditionally
Traditionally……. nevertheless…

  • Five day ahead forecasts

  • Deterministic

  • Consultative discussion

  • Subjective assessments

  • Precedent & Experience

  • Climatology

……it’s still a risky business!


“I’ve seen the forecast, how confident can I be?” nevertheless…

Can we do this job next week?

…..to hire five vessels will cost me £100,000 a day…..

What’s the chance of a reliable 24 hour weather window during the next week or so?


Giving our clients that confidence
Giving our clients that confidence nevertheless…

  • Complement the five day forecast

  • Measure the uncertainty

  • Better focus for discussion

  • Objective not subjective

  • Dynamic, not historical

  • Responds to climate shift


Typical offshore output from met office previn system
Typical nevertheless…Offshore Outputfrom Met OfficePrevin System


Looking at waves in more detail

1.5 M nevertheless…

Looking at waves in more detail


Can a probability forecast be wrong
Can a Probability Forecast be Wrong? nevertheless…

  • A single Probability Forecast cannot be right or wrong.Consider:

  • Probability of X is 30%

  • If X happens, is this right? Or wrong?

  • But… out of 100 such forecasts, X should happen 30 times.

  • Verification must be done over many forecasts


Calibration of probability forecasts
Calibration of Probability Forecasts nevertheless…

  • Calibration forecasts of a single “event” is straightforward using a reliability diagram:

  • 70% EPS prob50% issued

In practise we use a more flexible approach which can adapt to the requirements of different customers.


Can we use low probabilities? nevertheless…

  • Most extreme events are inherently improbable - how should we respond to low probabilities?

  • Event probability must be related to “climatology” for decision-making, eg.

  • 5% risk that a plane will crash - would you board it?

  • 5% risk of rain – would you play golf?

  • Decisions must be based on user’s Cost/Loss ratio

  • users with low C/L should protect at low probabilities


Making decisions simple cost loss model
Making Decisions – Simple Cost/Loss Model nevertheless…

With a probability forecast p, the user’s beststrategy is to: protect when p(event)>C/L

Averaged over many occasions this will maximise savings

Thus we have turned probability forecasts into decision tools


Summary ensembles help balance risks in an uncertain world
Summary – Ensembles help balance risks in an uncertain World!

  • We cannot get away from uncertainty

    • False Alarms and missed events are unavoidable

  • Ensembles let us turn this to our advantage

    • Reliable probability forecasts allow users to balance the impact of false alarms and missed events


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