Global Environmental Modelling and Prediction Using Earth Observations from Space

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Global Environmental Modelling and Prediction
Using Earth Observations from Space

• Alan ONeill
• Data Assimilation Research Centre
• University of Reading

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Current future satellite coverage
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2020 Vision

• By 2020 the Earth will be viewed from space with
  better than 1km/1min resolution
• Computer power will be over 1000 times greater
  than it is today
• To exploit this technological revolution, the
  world must be digitised
• Data assimilation will create Digiworld

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An analogyrecording music

• Goal produce high-quality, well balanced CD of
  Berlin Philharmonic to play on standard home
  equipment
• Method Distribute microphones around the Royal
  Albert Hall record output from each
• Problems
• Each mike picks up only part of the sound
• Some mikes are biased
• Some are noisy
• Some record only intermittently
• Customers dont want one CD for each mike

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What is data assimilation?

• Data assimilation is the technique whereby
  observational data are combined with output from
  a numerical model to produce an optimal estimate
  of the evolving state of the system.

DARC
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Why We Need Data Assimilation

• range of observations
• range of techniques
• different errors
• data gaps
• quantities not measured
• quantities linked

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DATA ASSIMILATION SYSTEM
Error Statistics
Data Cache
A
F
O
A
Numerical Model
DAS
B
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Some Uses of Data Assimilation

• Operational weather and ocean forecasting
• Seasonal weather forecasting
• Land-surface process
• Global climate datasets
• Planning satellite measurements
• Evaluation of models and observations

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Operational geostationary satellites
GOES water vapour imagery
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Impact on NWP at the Met Office
Mar 99. 3D-Var and ATOVS
Feb/Apr 01. 2nd satellites, ATOVS SSM/I
Oct 99. ATOVS as radiances, SSM/I winds
Jul 99. ATOVS over Siberia, sea-ice from SSM/I
May 00. Retune 3D-Var
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Ozone from Mipas
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Ozone from MIPAS Sep 2003
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Ocean temp at equator Oct 2002
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ECMWF Seasonal Forecasts
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Seasonal Forecasts for Europe (DJF 1997/98)
Forecast probability of above average temperatures
Measured temperature anomaly
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CO colors, day 1
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CO colors, day 65
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CO colors, day 85
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Regional Scale Walnut Gulch (Monsoon 90)
Tombstone, AZ
Houser et al., 1998
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MERIS ocean colour
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Conclusions

• Earth observations from space are allowing us to
  build highly sophisticated global environmental
  monitoring and prediction systems
• These systems will form the basis for many policy
  and commercial decisions
• But the scientific, computing and organisational
  challenges are enormous