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Quantifying Uncertainty in an Operational Environment – Risky

weather forecasts

Chris TubbsAssociation of Project Management Thursday 24th October 2013

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Talk structure

• Introduction

• Compiling a forecast – 2-3 days

• Introducing uncertainty – 4-5 days

• Uncertain forecasts; 6-15 day, 16-30 day (monthly) and seasonal forecasting

• Converting uncertainty into risks for customers

• Looking to the future and questions

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Compiling a forecast-Forecasting Process

Observations

4-D winds, rainfall, temperatures…….

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du = ∂p – fvdt ∂xdv = ∂p + fu dt ∂yp = RTρ

Interpretation, Risk Analysis & Communication

Knowledge

70 levels25km

80km high

Creating weather services

Forecast Model

Observations

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Numerical modelling

Weather and Climate Models are huge computer codes based on fundamental mathematical equations of motion, thermodynamics and radiative transfer

These govern:

Flow of air and water - winds in the atmosphere, currents in the ocean.

Exchange of heat between the atmosphere and the earth’s surface / ocean

Release of latent heat by condensation during the formation of clouds and raindrops

Absorption of sunshine and emission of thermal (infra-red) radiation

Numerical methods must conserve mass, energy, momentum, water and tracers

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Operational Forecasting Models: October 2013

Global25km 70L2.5 day forecast twice/day6 day forecast twice/day+24 member EPS at 60km twice/day

N.Atlantic/European (NAE) bec Euro412km bec 4km 70L2.5 bec 5 day f’cast 4 times per day+24 member EPS at 18km twice/day

UK-V1.5km 70L 1.5 day forecast 8 times per day2012: +24 member EPS at 2.2km

Met Office Global Regional Ensemble Prediction System = MOGREPS

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Resolution: Observed & Forecast Accumulations for the Carlisle Flood

12 km

4 km 1 km

Hand analysis of gauges and radar

12 km 1 km

Model Orography

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Resolution: fog prediction

Visibility (m)

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The growth of computer power

LEO 1

MERCURY

IBM 360/195

KDF 9

CYBER 205

ETA 10 CRAY YMP8

CRAY C90

CRAY T3E

10T

1T

100G

10G

1G

100M

10M

1M

100K

10K

1K

100

10

NEC SX-6

NEC SX-8 IBM P6

IBM P7

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Data Assimilation

• The challenge:

• To compute the model state from which the resulting forecast best matches the available observations

T-3 T-2 T-1 T+0 T+1 T+2 T+3 T+144

First guess

Observations

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Global performance by lead timeRMS surface pressure error over the NE Atlantic

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1982 2012

1-day f/c

4-day f/c

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1-2 days ahead

• Additional benefits from our high resolution (1km and 4km) models

• Automated warning products from MOGREPS ensemble system

• Weather system can be monitored before it reaches UK

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3 to 5 days ahead

• Deterministic global model outputs and ensembles

And forecaster interpretation…..’added value’

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3 to 5 days ahead…

Within the current NSWWS timescales

• So we have all of this weather information to enable us to give a ‘most likely’ scenario and potential what if’s

• Increased confidence

• Higher risk can be identified

• Details will still be subject to change and should be treated as best estimates

• Worth realising that the weather system causing the event will often not even have formed yet!

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3 to 5 days ahead…what action can be taken?

• We present these pieces of the jigsaw to other interested parties and partners

• Whole ethos of Hazard Centre

• NSWWS is impact based

• Typical example of Heavy Rain -

• Flood Forecast Centre (FFC) can use rain forecast and add more info in terms of assessing an impact

• Construct a communication plan with key messaging

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Quantifying uncertainty with ensembles

time

Forecast uncertainty

Climatology

Initial Condition Uncertainty

X

Deterministic Forecast

Analysis

CHAOS

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Probability of precipitation >5mm in 12 hours

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Pictorial representation ofuncertainty

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Spaghetti plot of fronts

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Dalmatian plot of lows and depths

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6 to 15 days aheadCan we detect anything at all?

There is often a lot of uncertainty

• Ensemble outputs are main source of information

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Increased reach - 6 to 15 days ahead

• Forecasters are good at:

• - linking atmospheric patterns to potential severe weather

• - identifying trends (e.g. mobile to block, cold to warm)

Sometimes there are hints of the following:

Prolonged rain Windy conditionsSnow Prolonged heat or cold

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Meteogram for 15 days, cloud, precipitation, winds (speed and direction) and temperatures

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MSLP ensemble mean every 12 hours to T+240 (10 days)

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Shannon entropy, a measure of spread

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6 to 15 days ahead…what action can be taken?

• We wouldn’t be able to supply details for any particular region this far out BUT

Heads up information can be useful to open up discussions (e.g. PWS-Advisors, Internal Comms)

These things can be couched in terms of risk, albeit low

Awareness

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Monthly and seasonal forecasts

• Knowing 6-15 day trends, especially if there is high confidence, helps to extend to monthly

• Sometimes ideas around continuation of a spell/climatology can help eg anticyclonic October = warm start, cold end

• Seasonal forecasts rely on Global drivers, eg North Atlantic Oscillation (+ve = mild), El Nino, SST anomalies, Arctic Sea Ice, Tropical Storms

• Most only have skill in winter half of year in Europe. Better in Tropics.

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Our key role as a forecaster is…

Identifying the potential for high impact weather….

• 6 to 15 day lead time

• 3 to 5 day lead time

0 to 2 day lead time

as we approach the ‘event’

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Converting uncertainty into risks for customers

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Weather Impact Matrix

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6 to 15 days ahead…what action can be taken?

• We wouldn’t be able to supply details for any particular region this far out BUT

Heads up information can be useful to open up discussions (e.g. PWS-Advisors, Internal Comms)

These things can be couched in terms of risk, albeit low

Awareness

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3 to 5 days ahead…

Within the current NSWWS timescales

• So we have all of this weather information to enable us to give a ‘most likely’ scenario and potential what if’s

• Increased confidence

• Higher risk can be identified

• Details will still be subject to change and should be treated as best estimates

• Worth realising that the weather system causing the event will often not even have formed yet!

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3 to 5 days ahead…what action can be taken?

• We present these pieces of the jigsaw to other interested parties and partners

• Whole ethos of Hazard Centre

• NSWWS is impact based

• Typical example of Heavy Rain -

• Flood Forecast Centre (FFC) can use rain forecast and add more info in terms of assessing an impact

• Construct a communication plan with key messaging

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Covering risk due to lingering uncertainties

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Example of uncertainty to risks for Met Office customers

• Open Road forecasts for Highways Agencies (HA) & local authorities since mid 1980’s to determine need for overnight winter road gritting

• Tendency of customers and Met Office to be risk averse, why is that?

• Main reason is 10 to one risk ratio, ie cost of service (£20k) is a tenth of average claim (£200k), and 100 to one ration for each gritting run (£2k)

• Therefore whenever the risk of a frost occurring rises above 10% it is cost effective to grit

• More useful to EA when deciding on flood prevention measures

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Looking to the Future

• Better quantification of uncertainty – the UK 2.2km ensemble

• Better nowcasts – an hourly UK NWP cycle

• New and improved specialist models, eg Weymouth Bay 500m model

• Better forecasts for global sites & longer ranges – a higher resolution global model

• Longer forecasts – addition of monthly and seasonal forecast information

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Harbour Wall: 300 (245V332) 09 KT(backed 60 degrees between 1120 and 1200 Z)Buoy: 340 07 KTIsle of Portland: 270 07 KT

1200 Z

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28/09Z UK300 VT 29/0900 Z

Extreme gusts associated with line convection

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So to conclude….

• Improvements in science have given us opportunities to provide useful advice at longer lead times

• We do need to manage expectations (because weather forecasting is not an exact science)

• Communication is key (knowing how/when/what) and also the risks involved for our customers

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Any questions?