1. Assimilation of Cloudy AMSU-A Microwave Radiances in 4D-Var
Una O’Keeffe
Thanks to Martin Sharpe and Stephen English
IPWG Workshop, Melbourne
October 2006
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2. Cloud liquid water incrementing operator Assimilation set up
Overview
Motivation
AMSU-A 23GHz and 31Ghz
Cloud liquid water incrementing operator
Assimilation set up
Assimilation results
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3. Motivation Cloud liquid water has large impact on microwave radiances
Currently low peaking AMSU-A channels are not assimilated if significant water is present
Significant data gaps due to cloud
AMSU-A window channels contain information on liquid water which is not currently exploited
Step towards assimilation of AMSR high resolution cloud and precipitation-affected radiances
© Crown copyright 2004

4. Information on cloud liquid water
RTTOV8 with clw emission
RTTOV8 without clw emission
NOAA-16 Obs
23GHz
31GHz
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5. O-B Stats for IRclear RTTOV – 31GHz
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6. O-B Stats for MWcloudy RTTOV – 31GHz
Mwcloudy (failed rain test) – with active cloud in rttov7
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7. Cloud Incrementing Operator
Total moisture analysis variable used in 4D-Var
Need cloud incrementing operator that relates liquid water and specific humidity to the total water control variable
Cx+ = Cx + KCw’
Cx = model state (q,qcl,qcf,cf)
Cw’ = analysis increment (T’,p’,qT’)
K = incremental transform variable between control variable space and model parameter space (uses linearised physics).
Sharpe,2005
© Crown copyright 2004

8. Currently formulated with full field total water
1D-Var Preprocessor
Currently formulated with full field total water
Up to 8% of solutions are rejected in 1D-Var with this approach
Data volume in 3D-Var is not reduced but is biased away from cloudy areas, giving negative impact
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9. Assimilation Experiment Set Up
Configuration: 3DVar, Dec05 four week period
10 day run to generate clear air bias corrections
Cloudy obs 23+31GHz assimilation trial
assimilate NOAA-16 AMSU-A 23GHz and 31GHz
extra-tropics sea only
for all cloud conditions except for where rain flag is on
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10. Analysis Increments
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11. Analysis Increments
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12. Impact on large scale fields fit to analysis
NH | TROPICS | SH
50hPa height
850hPa humidity
Most fields improved in SH
500hPa and 250hPa temp
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13. Fit to observations 31GHz
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14. Fit to observations 31GHz
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15. Bias Correction of Cloudy Data…???
For this test, used N16 HIRS to define ‘clear air’ and bias corrected clear air data
Operationally, also want to use N15, N17, N18
Options:
Bias correct clear air data only – ignores large cloudy biases
Bias correct all data – may degrade clear air assimilation
© Crown copyright 2004

16. Current Status Testing different bias corrections
Investigations of 1D-Var rejections indicated issue with high retrieved LWP on the first iteration causing failures. A fix is now in place
Operational implementation planned for early 2007
Plans
SSMI/SSMIS
AMSR
AMSU-B + ice incrementing operator
© Crown copyright 2004

17. Some significant changes to lower level humidity cf analysis
Summary
Assimilation of cloudy AMSU-A 23GHz and 31GHz data gives consistent positive impacts in SH and tropics
Some significant changes to lower level humidity cf analysis
Cloud fields improved
Unresolved issues with bias correction
© Crown copyright 2004

18. Questions?
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