Post on 15-Feb-2017
The Science and Practice of Seasonal Climate Prediction at FUNCEME
Liqiang Sun
January 22, 2013
If we can’t predict the weather next week, why do we think we can make prediction for next season?
We can’t predict the weather for next season, but under some conditions, we can say something useful about the climate for next season.
Weather vs. ClimateWEATHER
Weather is the day to day evolution of the atmosphere. We experience it as rain or sunny, hot or cold, windy or calm.
weather worries:
Should I bring my umbrella to work today?
CLIMATEThe most basic aspect of climate is the long term average of weather. Its what we expect for a particular region at a particular time of year (for example, hot and muggy in NYC during summer).
climate concerns, on average:Should I live in NYC because its so hot and muggy in the summer?Climate also includes the range of possibilities (for example, the warmest and coldest temperature ever).
climate concerns, on variability:Should I buy new snow tires for my car, in case it's a bad winter?
The atmosphere is a dynamical system
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Weather Forecast vs. Climate Forecast
In general,
Advection Forcing
Weather Forecast – Initial Condition Problem
Weather Forecast -Predictability of the First Kind
Sensitivity to initial conditions Predictability depends on state of the
system The memory of the atmosphere to initial
conditions is limited to approximately 10 days
Climate Forecast (2-tiered)– Primarily External Forcing Problem(Predictability of the Second Kind)
The atmosphere is so strongly forced by the underlying ocean that integrations with fairly large differences in the atmospheric initial conditions converge, when forced by the same SST (Shukla and Kinter 2006).
Seasonal Climate Prediction
Exact sequence of daily weather during a season (e.g. 3 month) is impossible to predict. (beyond deterministic predictability limit)
We predict “statistics” of weather during a season.
OUTLINE
Sources of Climate Predictability
Prediction Methodology
Forecast Product and Format
Forecast Verification
Improving the Forecasts
Summary
Prediction and Predictability Predictability is a physical characteristic of the
natural system, and not altered by forecasting methodologies.
Estimated predictability is system dependent.
Predictability varies with location and season
Predictability is the top limit of the actual prediction skill
Sources of Climate Predictability – External Forcing
Changes in boundary conditions can influence the characteristics of weather, and thus influence the seasonal climate.
If future evolution in the boundary conditions can be anticipated, then from the knowledge of their influences on global atmospheric circulation, skillful seasonal predictions are possible.
A key requirement in making successful seasonal climate forecasts is understanding atmospheric responses to a broad range of anomalous boundary forcings.
SST forcing is principle among the boundary conditions influencing atmospheric seasonal variability. Others include soil moisture, snow cover, volcano eruption, and etc.
Tropical Pacific – Average State
El NinoTrade winds get weakerWarm water flows back eastwardConvection moves eastwardWinds weaken further, etc.
La NiñaTrade winds get strongerMore warm water pushed westwardConvection enhanced in western PacificWinds strengthen further, etc.
“Expected” Climate
Anomalies during ENSO
Events
A real-time forecast
OUTLINE
Sources of Climate Predictability
Prediction Methodology
Forecast Product and Format
Forecast Verification
Improving the Forecasts
Summary
Prediction ToolsEmpirical Models
Dynamical Models
AGCM (two-tiered process) CGCM (one-tiered process)
Prediction Systems:empirical vs. dynamical system
ADVANTAGES
Based on actual, real-worldobserved data. Knowledge ofphysical processes not needed.
Many climate relationshipsquasi-linear, quasi-Gaussian------------------------------------Uses proven laws of physics.Quality observational data not required (but helpful for val-idation). Can handle casesthat have never occurred.
DISADVANTAGES
Depends on quality and length of observed data
Does not fully account for climate change, or new climate situations.------------------------------ Some physical laws must be abbreviated or statis- tically estimated, leading to errors and biases.
Computer intensive.
Empi-rical
-------
Dyna-mical
Dynamical Prediction System:2-tiered vs. 1-tiered forecast system ADVANTAGES
Two-way air-sea interaction,as in real world (required Where fluxes are as important as large scale ocean dynamics)
--------------------------------------More stable, reliable SST inthe prediction; lack of driftthat can appear in 1-tier system
Reasonably effective for regionsimpacted most directly by ENSO
DISADVANTAGES
Model biases amplify (drift); flux corrections
Computationally expensive------------------------------ Flawed (1-way) physics, especially unacceptable in tropical Atlantic and Indian oceans (monsoon)
1-tier
------
2-tier
Forecast Mean
Climate Forecast: Signal + Uncertainty
“SIGNAL”
The SIGNAL represents the ‘most likely’ outcome.
The NOISE represents internal atmospheric chaos, uncertainties in the boundary conditions, and errors in the models.
“NOISE”
Historical distribution Climatological Average
Forecast distribution
BelowNormal
AboveNormal
Near-Normal
OUTLINE
Sources of Climate Predictability
Prediction Methodology
Forecast Product and Format
Forecast Verification
Improving the Forecasts
Summary
Forecast Product
3-month mean precipitation and surface temperature SST anomalies Soil Moisture Extreme Events (heat wave, cyclone, …) Weather within Climate (dry spell, wet spell, precipitation
frequency) Onset of Rainy Season Monsoon (index) Crop Growing Period Evaporation Ground Solar Radiation
Forecast Format Tercile probability Probability Distribution Function (PDF) Forecast in Context
Seasonal Forecast
http://www.funceme.br/DEMET/index.htm

The UK Met Office 2009 summer forecast issued in April
Britain will have first decent ‘barbecue summer’ in three years with temperatures regularly above 80FBritain is expected to bask in a hot and dry summer with temperatures regularly reach 86F(30C), forecasters have predicted.
The Telegraph, April 30, 2009
Media’s interpretation of UKMO forecast
Media’s Media’s reaction toward the forecast
As millions of Britons holiday at home after that promise of a ‘barbecue summer’, how did the Met Office get it so wrong?
Daily Mail, 30 July 2009
UK Met Office becomes Wet Office?
OUTLINE
Sources of Climate Predictability
Prediction Methodology
Forecast Product and Format
Forecast Verification
Improving the Forecasts
Summary
Forecast VerificationReliability and resolution are general attributes of probabilistic forecasts, and need to be verified.
Reliability - agreement between forecast probability and mean observed frequency
Resolution - A category should occur more frequently as its probability increases, and less frequently as the probability decreases
Reliability & resolution are independent attributes
OUTLINE
Sources of Climate Predictability
Prediction Methodology
Forecast Product and Format
Forecast Verification
Improving the Forecasts
Summary
Improving the Forecasts model development, improve observation coverage and accuracy, enhance data assimilation techniques, and advance our understanding of seasonal
climate variability.
Summary
Seasonal forecasting relies on boundary conditions and exploits predictability of second kind
ENSO is the most important source of seasonal predictability. Multi-model ensemble technique has become the common
practice in seasonal climate forecasts. The verification of ensemble forecasts requires a sufficient
number of verification samples and involves the application of probabilistic skill metrics.
Seasonal climate forecast remains a challenge. It is essential to continue model development, improve observation coverage and accuracy, enhance data assimilation techniques, and advance our understanding of seasonal climate variability.
Quiz
If you want to predict the climate over Ceara next season, what do you think you'd need to know?
Thank YouObrigado谢谢