Seasonal Forecasting

Simon Masonsimon@iri.columbia.edu

Seasonal Forecasting Using the Climate Predictability ToolBangkok, Thailand, 12 – 16 January 2015

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Introduction“Are you, Socrates, the one who is called the Expert?”

“Not if it is better,” Socrates replied, “to be called the Idiot.”

“It would be better to be called the Idiot than the Expert Meteorologist!”

Xenophon, Memorabilia

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Forecasting

Why is forecasting the weather and climate so difficult?

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Dramatis Personae• Pythagoras, the mathematician• Daedalus, the inventor• Zeus, Father of Gods and men

Negotiated deal• Temperature atop Etna today will

be 1.8°C colder than the square of the temperature yesterday.

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Forecasting a simple (?) systemEtna has a mean temperature of about 0.5°C, and standard deviation of about 1.0°C. If Sunday was 0.3°C:

2today yesterdayTemp Temp 1.8 C

Daedalus’s thermometer was off by five one thousandths of a degree (0.005°C)

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Weather prediction

What do we need to know to make a good prediction?– The current state (initial conditions)– How the current state will evolve

So there are two sources of uncertainty:– The current state (use an ensemble)– How the current state will evolve (use multiple models)

How do we know how the current state will evolve?– What causes it to evolve?– How has it evolved in the past?

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Spot the Ball Competition• Where is the ball now?• Where will the ball be in 20 seconds?• Who will win the match?

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Sources of Predictability

• We can make forecasts at different timescales because there are different reasons why the predictions can work:– days: current weather– months: sea-surface temperatures– years: sub-surface ocean temperatures– decades: atmospheric composition

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El Niño and global climate• Sea-surface temperatures, especially in the equatorial Pacific, can

affect the frequency and intensity of different weather patterns

Typical El Niño impact during December - February

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Thailand MAM rainfall and SSTs

Correlations between pre-monsoon (March – May) rainfall in Thailand and global sea-surface temperatures (SSTs), 1961 – 2010.

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Seasonal prediction• We make seasonal forecasts by predicting the statistics of

weather rather than the actual weather at any specific time.– Based on historical relationships– By looking at the statistics of lots of very long-range

weather forecasts, ideally from lots of different models

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Summary

• To forecast the weather we need to know:– What is the current weather?– How will the weather evolve?

• Because of errors in answering both questions, we cannot predict the weather beyond a few days.

• There are influences on the atmosphere that affect what type of weather patterns are more or less likely to occur – primarily sea temperatures for predicting the next few months.

• We predict the effect of these influences in two possible ways:– Looking at evidence for influences in the past– Modeling the processes that cause the effects