l bengtsson 14.6.07 bosön, stockholm multiscale modeling and simulation in science predictability...

L Bengtsson 14.6.07Bosön, Stockholm

Multiscale modeling and simulation in Science

Predictability of weather and climate

What have we learned from comprehensive modeling studies?

Lennart BengtssonMPI for Met. Hamburg

ESSC, Uni. ReadingMany thanks to

J. Shukla



We may regard the present state of the universe as the effect of its past and the cause of its future. An intellect which at a certain moment would know all forces that set nature in motion, and all positions of all items of which nature is composed, if this intellect were also vast enough to submit these data to analysis, it would embrace in a single formula the movements of the greatest bodies of the universe and those of the tiniest atom; for such an intellect nothing would be uncertain and the future just like the past would be present before its eyes.

Laplace Essai philosophique sur les probabilités



• CLIMATE PREDICTION AND CHAOS

• “ For want of a nail, the shoe was lost;

• For want of a shoe, the horse was lost;

• For want of a horse, the rider was lost;

• For want of a rider, the battle was lost;

• For want of a battle, the kingdom was lost “



• Predictability of weather



St. Petersburg prediction 10.1 2006

17th onward ca -30 C



Example of ultra-high predictabilityObserved and simulated QBO

Note the marked changes in wind direction at 10-30 hPa every 26-28 month



Predictability of weather and climate.


• Predictability of atmospheric flow (from mid latitude weather prediction to the

quasi-biennal oscillation)

Predictability of weather (how close are we to the limit?)

Coupled ocean atmosphere modes (El Nino-Southern Oscillation)

What do we mean by climate predictability?

(what is predictable?)

Climate and climate change predictability Concluding remarks



A Fundamental Question in Weather Predictability

A Dynamical System is :

TYPE 1 – characterized by an infinite range of predictability

TYPE 2 – the range of predictability is finite, but can be increased indefinitely by decreasing the size of the initial error

TYPE 3 – the range of predictability is finite and intrinsically limited

Does the Weather Constitute a Type 2 or a Type 3 System?



The Growth of Very Small Errors

• Basic Idea – Reduce the Size of the Initial Error by putting it on smaller and smaller scales

• Ultimate Predictability controlled by the predictability time T = time necessary for the error to propagate “upscale” from very, very small initial scale to a finite, pre-chosen scale

• How does T behave as the initial error gets infinitely small? This tells us if we have TYPE 2 or TYPE 3 behavior!

• For a Spectrum E(k) ~ k -3 or steeper :

T becomes infinite (thus TYPE 2)

• For a Spectrum E(k) less steep than k -3 :

T is finite (thus TYPE 3)

Nastrom and Gage, 1985: A climatology of atmosphericwavenumber spectra of wind and temperature observed by commercialaircraft. J. Atmos. Sci., 42, 950–960.



Does the Observed -5/3 Spectrum Imply that the Range of Predictability Cannot be Lengthened by Reducing Initial

Error?

• Perhaps the eddies associated with the observed -5/3 spectrum do not interact with the large scale



Improvements in NWP from Miyakoda (1972) to 2002. Courtesy ECMWF

How long to get to D+10 in winter?



The principle of error reduction in data assimilation



Improvement in medium-range forecast skill

12-month running mean of anomaly correlation (%) of 500hPa height forecasts



Lorenz, E. N., 1982: Atmospheric Predictability Experiments with a Large Numerical Model. Tellus, 34, 505-513

• Estimates of the lower and upper bounds of predictability of instantaneous weather patterns for ECMWF forecast system

• Lower bound: skill of “current” operational forecasting procedures

• Upper bound: Growth of initial error, defined as the difference between two forecasts valid at the same time

(Lorenz curves)

“Additional improvements at extended range may be realized if the one-day forecast is capable of being improved significantly.”



Predictive skill ( Z 500 hPa) for the NHand predictability estimates ( for 6 ( red) and 24 hr (blue)

increments)



Evolution of 1-Day Forecast Error, Lorenz Error

Growth, and Forecast Skill for ECMWF Model (500 hPa NH Winter)

1982 1987 1992 1997 2002

“Initial error” (1-dayforecast error) (m) 20 15 14 14 8

Doubling time (days) 1.9 1.6 1.5 1.5 1.2

Forecast skill (day 5 ACC) 0.65 0.72 0.75 0.78 0.84

2007

8

1.2*

0.91

From ECMW *est



ECMWF EPS: Forecast Started 8th January 2005 00UTC (GUDRUN)

From L Froude, ESSC



ECMWF EPS: Forecast Started 6th January 2005 00UTC

From L Froude, ESSC



Predictive skill and predictability of storm tracksfor different observing systems

NH

SH

From L Froude, ESSC



Conclusions Weather predictability

• Predictability of actual weather is limited to a few days.• Predictability of synoptic weather systems is likely limited by ca

two weeks. Improvements has come through smaller initial errors due to better observations and more advanced data-assimilation.

• Predictability of the general weather type varies between different regions, for different seasons and for different situations and can be from weeks to several months.

• There are atmospheric patterns such as QBO that have almost unlimited predictability.



1998 JFM SST [oC]

JFM SST Climatology [oC]

1998 JFM SST Anomaly [oC]

El Nino/Southern OscillationEl Nino/Southern Oscillation



El Nino changes precipitation patterns

Evolution of Climate Models

1980-2000Model-simulated and observed

500 hPa height anomaly (m) 1983 minus 1989

Vintage 2000AGCM



20 Years: 1980-19994 Times per Year: Jan., Apr., Jul., Oct.6 Member Ensembles

Kirtman, 2003

Current Limit of Predictability of ENSO (Nino3.4)Potential Limit of Predictability of ENSO



Prediction of Atlantic hurricaneswith a general circulation model

integrated over 30 years

ECHAM5/OM ERA-40



Predictability of large-scale climate anomaly patterns

• The predictability of ENSO is likely to be from several months to a few years. There are large variations in predictability. Present predictability assessment suffers from rather poor coupled models and later work is expected to change this.

• The same is true for well developed land surface patterns.

• Long term anomalies over Europe (NAO) have limited predictability

• The fact that very long semi-persistent pattern occur both in reality and in models suggest that predictability in some regions (such as in the Sahel region) are longer.

• Here we need more active basic research.





• Predictability of atmospheric flow (from mid latitude weather prediction to the quasi-

biennal oscillation)



What do we mean by climate predictability? (what is predictable?)




Köppen climate zones

Main groups• A: Tropical rainy climate, all months > +18 C• B: Dry climate, Evaporation > Precipitation• C: Mild humid climate, coldest month +18 C - -3 C• D: Snowy - forest climate, coldest month < -3C but warmest > +10• E: Polar climate , warmest month < +10 C• ET: Tundra climate, warmest month > 0 C

• Subgroups• f : Moist, no dry seasons• w: Dry season in winter• s : Dry season in summer



ECHAM5simulated

ERA40determined

from analyses.

Köppen climate zones



Warmest and coldest season in Europe 1500-2003

Luterbacher et al(2004), Xoplaki et al (2005)



50-year trends>0.23 corresponds to 95% significance

T

PZ 850

Sea

ice



Observation and model statisticsLuterbacher et al., 2005 ( Temp. in C)

(a) Luterbacher (2005) (b) Model Annual DJF JJA Annual DJF JJA Mean 8.13 -2.31 16.83 7.39 -2.30 16.96 Stand. dev. 0.41* 1.15 0.47 0.55 1.23 0.55 Min. 6.61

(1695) -5.69 (1695/96)

15.62 (1821)

5.41 (16)

-7.45 (15)

15.55 (170)

Max. 9.40 (1822)

-0.09 (1842/43)

18.18 (1757)

9.41 (78)

1.47 (52)

19.08 (459)

Max.-Min. 2.79 5.60 2.56 4.00 8.92 3.53



Climate predictability

• Internal climate modes lasting up to several decades are likely to exist in the climate system. Whether these are predictable is still an open question

• Model studies suggest that such internal modes have dominated climate variations during the last several centuries

• It is hardly feasible to infer any changes in external forcing from meteorological records for the period 1500 to 1900.

• Models are capable to reproduce the observed climatology with considerably accuracy ( e.g.Koeppen)





• Predictability of atmospheric flow (from mid latitude weather prediction to the quasi-

biennal oscillation)



What do we mean by climate predictability? (what is predictable?)




Delworth and Knutson, 2000

Monte-Carlo simulations with a coupled AO GCM: one out five simulations almost perfectly reproduced the observed global temperature variability.

obs

exp 3



Resultat från den senaste klimatutvärderingen

Observerad och beräknad temperaturändring



CoupledModelT63L31

Present climate

Future climate



• Predictability of snow in Germany



Ensemble climate trends averaged fordifferent time-periods

(T/decade)

1-30 years 1-80 years



Climate change predictability

• Changes in climate patterns during the last 50 years are now with high probability due to changes in atmospheric composition (greenhouse gases and aerosols)

• The trade off between the two cannot easily be done as they both have very similar climate pattern signatures. It can well be that we are underestimating the effect of greenhouse gases and overestimating reflecting aerosols or vice versa

• However, a marked positive feedback from anthropogenic greenhouse gases via water vapor and surface albedo is most likely.

• Future climate scenarios include considerable internal regional variations which can mask or enhance climate warming for several decades. Typical examples from the last century are the warm 1930s and 40s and cold 1960s and 70s.

• Robust climate change trends for specific regions require probably 50-100 years



Concluding Remarks

• The largest obstacles in realizing the potential predictability of weather and climate are inaccurate models and insufficient observations, rather than an intrinsic limit of predictability.

– In the last 30 years, most improvements in weather forecast skill have arisen due to improvements in models and assimilation techniques

• The next big challenge is to build a hypothetical “perfect” model which can replicate the statistical properties of past observed climate (means, variances, covariances and patterns of covariability), and use this model to estimate the limits of weather and climate predictability

– The model must represent ALL relevant phenomena, including ocean, atmosphere, and land surface processes and the interactions among them



END

Any questions?

l bengtsson 14.6.07 bosön, stockholm multiscale modeling and simulation in science predictability...

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