1. Aura Science Team meeting
The impacts of dynamics on tropical tropospheric CO inferred from Aura satellite data and GEOS-Chem model
Junhua Liu and Jennifer Logan
Harvard University
Aura Science Team meeting
Sep 14-17, 2009
Acknowledgements: Thanks to Nathaniel Livesey and Jonathan Jiang of JPL. TES, MLS teams.

2. Satellite data (TES/MLS) and the GEOS-Chem Model
Outline
Introduction
Satellite data (TES/MLS) and the GEOS-Chem Model
Driven by two versions of meteorological fields: GEOS 4 & 5
Evaluation of model performance
TES CO in the LT
MLS CO in the UT
Diagnostics of model transport
Vertical convective and advective mass fluxes
Horizontal winds
Comparison between GEOS 4 and GEOS 5 meteorological fields
MLS data as a test of vertical transport at the start of the wet season in South America
Summary

3. CO measurements from Aura (TES and MLS)
TES (Tropospheric Emission Spectrometer)
TES V003
MLS (Microwave Limb Sounder)
MLS V2.2 level 2 data

4. TES, MLS - GEOS-Chem comparisons
GEOS-Chem Simulations
v , 4o × 5o horizontal resolution
Driven by GEOS-4 or GEOS-5 meteorological fields - diff. convection parameterization
2-year simulation from Jan to Dec. 2006
Uniform prior for TES
Model profiles are sampled along the TES/MLS orbit track at the observation time, and then vertically smoothed with the TES or MLS averaging kernels.
Focus on 2005 in this talk, but show some results for 2006

5. Temporal and spatial patterns of GFED2 emissions
Aug
Sep
Jul
GFED2
2005
2006
Latitude
Longitude
South America:
Biomass burning starts one month later.
Drier in 2005 (La Nina), CO emissions in 2005 are twice the amount in 2006.
South Africa:
Relatively stable seasonality with smaller interannual variation
Courtesy of Inna Megretskaia

6. CO comparison with TES in the LT in GEOS4
GEOS-Chem w/ TESak
DIFF (GEOS – TES)
2005 GEOS-4
681hPa
Aug
Sep
Oct
Nov
Dec
South America: TES and model CO highest in Sep. and Oct., but largest underestimate also in Sep. and Oct.
Underestimate of CO in South Africa - lower fire emissions
Too much CO export in easterlies in LT to the convection region - N. of equator

7. CO comparison with MLS in UT: 215 hPa
2005
MLS
GEOS-4
2006
MLS
GEOS-4
Aug
Sep
Oct
Nov
Dec
Factor of two bias in MLS at 215 hPa [Livesey et al., 2007].
South America: CO maximum lags ~1 month in the model compared to MLS data in 2005 and 2006
East Pacific: Model CO has a large overestimate in Aug. 2005
Indonesia: overestimate in Oct. and Nov. 2006

8. GEOS-4: Vertical mass flux and CO, Aug.-Dec. 2005
688 hPa
430 hPa
226 hPa
Aug:
Amazon: barely any convection, horizontal transport dominates in LT. Large amount of CO exported to the East equatorial Pacific.
Oct & Nov
ITCZ shifts south, strongest convection contributing to maximum CO in Nov. in the UT.
Aug
Sep
Oct
Nov
Dec
Contours: upward air mass flux (convection + advection, Pa/s: [0.05, 0.12, 0.25] for 688 hPa & 430 hPa, [0.03, 0.06, 0.12] for level 226 hPa) Color: CO (ppbv).
Fires mainly in Aug/Sep, but little vertical transport
In South America, CO max. in Sep at 688hPa, in Oct. at 430hPa, in Nov. at 215hPa

9. Vertical profiles of upward mass flux
S America (18S-2S, 70W-40W)
Convection
Conv. + adv.
South America:
Largest increase in vertical upward transport in Oct. (green)
Upward mass flux reaches a higher altitude in Nov., contributing to CO max. in model
most outflow of deep convection is below 200 hPa
Above 200 hPa, slow vertical ascent air

10. Convection in GEOS-4 compared to other models (Folkins et al. 2006)
Fueglistaler et al. 2009
Compared to other models, GEOS-4 convection decays at a lower altitude – the top height of convective outflow is lower.
215 hPa - slow vertical ascent air above region of convective outflow in the TTL causes the 1-month lag of CO maximum in UT in the model.

11. CO in the UT in GEOS-4 and GEOS-5
2005: 215 hPa
MLS
GEOS-4
GEOS-5
Aug
Sep
Oct
Nov
Dec
South America: CO at 215 hPa is lower in GEOS-5 than in GEOS-4
GEOS-5 maximum occurs ~1-2 months late, later than GEOS-4
East Pacific: GEOS-5 has a better CO simulation

12. Seasonality and interannual variation of CO - S. America
From LT to UT, the lag in GEOS-5 is always greater than that in GEOS-4 UT
MLS
GEOS4_MLSak
GEOS4
GEOS5_MLSak
GEOS 5
MLS/2
GEOS 4: 1 month lag
GEOS 5: 1-3 month lag
TES
GEOS4_TESak
GEOS4
GEOS5_TESak
GEOS 5
GEOS 4: No lag
GEOS 5: 1 month lag (2006)
Optical bench warm-up to improve CO signal LT

13. Vertical transport in GEOS-4 & GEOS-5 (South America)
226 hPa
GEOS-5
Top: Vertical profile of upward transport of air in GEOS4 and GEOS5 in 2005
Right: Spatial map of upward transport with CO mixing ratio in 2005 in UT. Similar pattern in 2006.
The lag of CO maximum in GEOS-5 is greater in part because the convection decays at a lower altitude, and in part because the convection moves southward later than in GEOS-4

14. Relationship between convection and CO
South America (18-2S, 70W-40W) Sep,2005
GEOS4
GEOS5
COGEOS5/COGEOS4
GEOS4
GEOS5
convectionGEOS5/convectionGEOS4
CO source region (S. America): convection is the dominant mechanism for CO vertical redistribution. In GEOS-4, stronger convection transports more CO into UT, causing higher CO above ~650 hPa.

15. Seasonality and interannual variation of CO – East Pacific
MLS
GEOS4_MLSak
GEOS4
GEOS5_MLSak
GEOS 5
MLS/2
Vertical mass flux (Pa/s)
The vertical profiles of upward transport:
GEOS-4: Gradually decrease with height
GEOS-5: Sharp decrease around 600 hPa
MLS
GEOS4_MLSak
GEOS4
GEOS5_MLSak
GEOS 5

16. Conclusion
Over S. America, deep convection in GEOS-4 decays at too low altitude, causing the lag of the CO maximum compared to MLS observations in the UT.
The lag in GEOS-5 is greater in part because the convection decays at an even lower altitude, and in part because the convection moves southward later than in GEOS-4.
The overestimate of CO in east equatorial Pacific north of the equator results from stronger local convection, and stronger easterly winds in GEOS-4 in the lower altitude.
The overestimate disappears in GEOS-5, caused by a sharp decrease of convection near 600 hPa. Is this mechanism realistic? Comparison of GEOS met. fields with NCEP or ECMWF data would be useful.