Unified Models for Weather and Climate Predictions

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Unified Models for Weather and Climate Predictions

• J. Shukla
• Climate Program Board Retreat
• 25-26 May 2005
• Airlie Conference Center
• Warrenton, Virginia

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Advances in weather and climate prediction
require a balanced program of observations,
modeling and applications to society
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Improvement in medium-range forecast
skill 12-month running mean of anomaly
correlation () of 500hPa height forecasts
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Nastrom and Gage, 1985 A climatology of
atmospheric wavenumber spectra of wind and
temperature observed by commercial aircraft. J.
Atmos. Sci., 42, 950960.
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Vintage 1980 AGCM (Lau, 1997, BAMS
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Vintage 2000 AGCM
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Evolution of Climate Models 1980-2000 Model-simul
ated and observed rainfall anomaly (mm day-1)
1983 minus 1989
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Evolution of Climate Models 1980-2000 Model-simul
ated and observed 500 hPa height anomaly (m)
1983 minus 1989
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Variance of Model-Simulated Seasonal (JFM)
Rainfall (mm2)
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WCRP Projects
WGNE WGCM
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2005 after 25 years of WCRP
New overarching and integrating Strategic
Framework Prediction of entire climate
system (Earth System) FGGE ? extended
weather prediction TOGA ? seasonal
prediction (tropics) COPES ? climate system
prediction
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Land-Climate Interaction

• Soil wetness, vegetation, and snow
• Local modification of remote SST effects
• Enhanced predictability of circulation Ts
• Predictability of water cycle

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linear trend R2 0.4
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Weather Prediction Model of 2020

• Coupled Ocean-Land-Atmosphere Model

1 km x 1 km 100 levels Unstructured, adaptive
grids
Landscape-resolving (100 m)
1 km x 1 km 50 levels Unstructured, adaptive
grids
Assumption Computing power enhancement by a
factor of 103-104
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Convective prec. at T511
T2047
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Hurricane Ivan (2004) 5-day forecast

• Initialization 12z 11September
• Observed center pressure prior to landfall 930
  hPa at 00Z16Sept
• Predicted center pressure at that time 930 hPa
• Observed wind prior to landfall category 4
  hurricane
• Predicted wind category 4 (60m/s)
• Displacement error 50km
• Thanks to the high computational efficiency, this
  5-day forecast was done in about one hour using
  240 CPUs of one node of the Columbia ALTIX

Shading 850 wind speed (m/s) Contour sea level
pressure (hPa)
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Modeling and Computing

• Models in 2015
• Weather
• T3800 (5 km) 4 d/hr (2,160 CPUs)
• - or -
• T825 (25 km) 4 d/hr (468 CPUs)
• Climate
• T420/ 0.5 2.4 yrs/d (2,500 CPUs)
• -or-
• T420/0.5 2 mo/d (2,500 CPUs)

• Models Today
• Weather
• T254 5 d/hr on 144 CPUs
• T511 2.5 d/hr on 288 CPUs
• Climate
• T85/ 1 2.0 yrs/d on 96 CPUs
• 2X2.5/1 5.25 yrs/d on 180 CPUs

43/yr (Moores Law ) -OR- 10/yr
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Unified Global Weather and Climate Prediction
System for the 21st Century

• Increasing the skill of global high-impact
  weather forecasts
• Reducing the uncertainty of climate prediction
• Improving intraseasonal predictions of floods and
  droughts
• Designing, implementing and utilizing GEOSS data
  sets
• Assimilating high resolution data
• Enabling interactions of the physical climate
  system and the chemistry and biology of planetary
  ecosystems
• Helping policy-makers and stakeholders in
  scale-appropriate decision-making for mitigation
  and sustainable development for the benefit of
  society and the health of the planet
• Assumption Eliminating parameterizations of
  large-scale convection and resolving small-scale
  variations will enhance the predictability of
  models

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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

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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