tangborn AIRS CO2 assimilation · 2018. 7. 17. · tangborn_AIRS _CO2_assimilation.pptx Author:...
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Assimilation of AIRS CO2 into GEOS5
Andrew Tangborn NASA/GSFC and UMBC
Acknowledgements: Steven Pawson, Lesley Ott, JPL AIRS CO2 retrieval team
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Value of Assimilating CO2 retrievals
• Direct comparison between model and observations (O-F) for both passive and assimilated observations.
• Satellite observations can be validated against in-situ observations that are nowhere near the satellite obs locations.
• Tuning of background errors (variance and correlations) by minimizing differences of the analyzed fields with in-situ data. Helps characterize model error.
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Goals of Initial Assimilation Experiments
• Determine background errors that result in most optimal solutions when compared to in-situ data (Japan Airlines and CMDL Flask)
• Characterize systematic differences between model and observations.
• Define the impact of assimilating of AIRS retrievals. Does it improve the accuracy of the CO2 distribution?
• Initial runs for Jan - Nov 2005 (still running).
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Assimilation System
• CO2 transport driven by GEOS5 (MERRA) met fields, with a 2x2.5 grid.
• Emissions from TRANSCOM (for anthropomorphic sources, 1995) and GFED (for biomass burning, year specific).
• Analysis is carried out in a univariate 3D-Var system.
• CO2 Background errors are set at a percentage of the CO2 mixing ratio (ppmv). Provides flow dependent error covariance.
• AIRS retrievals are thinned to the analysis grid.
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Background error std = 0.5% of CO2 Background error std = 0.1% of CO2
Reduced errors in Stratosphere
Analysis Increments
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Daily Mean O-F for AIRS observations Blue – passive : Red – assimilated
Jan 1 – Aug 31, 2005 -60 < lat < -30 -30 < lat < 0
0 < lat < 30 30< lat < 90
SH winter Model > obs
NH Winter Model > obs
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AIRS Mean O-Fs • Nega%ve Model bias in Winter: Does this originate in the model or observa%ons?
Either:
• Model is too high in winter (sources too large?) or • Retrievals have a nega%ve bias over cold surfaces.
• Comparisons with in‐situ data can help with this.
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Monthly Mean Differences with CMDL observations Jan - Nov 2005
30< lat < 90
-30 < lat < 0
0 < lat < 30
-90 < lat < -30
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Comparison with CMDL surface observations March – November 2005
Observa%on Loca%ons: green = mean assimila%on error is lower Red = mean assimila%on error is higher
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Regional Comparison with CMDL surface observations March – November 2005
NH
SH
N. America
Europe
Africa
Pacific
S. America and Antarc%ca
Error Bars Blue – model; Red - Assimilation
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Summary of In-Situ O-Fs • Model values are consistently larger than CMDL observa%ons.
• Consistent improvement in mean differences.
• Regional comparison shows improvement everywhere except Europe.
• Error bars show that model is most accurate in Europe (hence the difficulty to show improvements).
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Impact on CO2 fields • Zonal mean fields on April 15, Aug 15 and Nov 1, 2005.
• Monthly average surface CO2 for April and August, 2005.
• Monthly average CO2 at 500 hPa, for April and August, 2005.
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Zonal Mean CO2 April 15, 2005
Model Run Assimila%on Difference
CO2 reduced globally
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Zonal Mean August 15, 2005
Model Assimila%on Difference
Reduction in CO2 over entire column
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Zonal Mean Nov 1, 2005
Model Assimilation Difference
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Mean Surface Layer April 2005
Model Assimilation
Difference
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Mean CO2 at 500 hPa April 2005 Model Assimilation
Difference
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Mean Surface layer August 2005 Model Assimilation
Difference
Increased CO2 in Siberia
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Mean CO2 at 500 hPa August 15, 2005
Model Assimilation
Difference
General increase at high latitudes and decrease in tropics
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Conclusions • Tuning of background errors indicates an appropriate error standard
devia%on of about 0.1 % of CO2 mixing ra%o.
• Comparisons with CMDL surface data indicate that AIRS assimila%on is improving the accuracy of surface values of CO2 in GEOS5.
• Differences between GEOS5 and AIRS CO2 can parameterized by hemisphere, with a systema%c nega%ve bias in the model during winter.
Near term plans • Comparison with JAL and other aircraft data.
• Further assimilation experiments with altered emissions, convection parameters .
• Assimilate a subset of observations.