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.

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

CO measurements from Aura (TES and MLS)

MLS (Microwave Limb Sounder)• MLS V2.2 level 2 data

TES (Tropospheric Emission Spectrometer) TES V003

TES, MLS - GEOS-Chem comparisons

GEOS-Chem Simulations

• v08-02-01, 4o × 5o horizontal resolution• Driven by GEOS-4 or GEOS-5 meteorological fields - diff.

convection parameterization• 2-year simulation from Jan. 2005 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

Aug

Sep

Jul

Aug

GFED2

Temporal and spatial patterns of GFED2 emissions

Courtesy of Inna Megretskaia 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

2005 2006

Longitude

Lat

itu

de

• 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

2005 GEOS-4681hPa

CO comparison with TES in the LT in GEOS4

TES GEOS-Chem w/ TESak DIFF (GEOS – TES)

Aug

Sep

Oct

Nov

Dec

• 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

CO comparison with MLS in UT: 215 hPa

Factor of two bias in MLS at 215 hPa [Livesey et al., 2007].

2006MLS GEOS-42005MLS GEOS-4

Aug

Sep

Oct

Nov

Dec

GEOS-4: Vertical mass flux and CO, Aug.-Dec. 2005

• 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

Aug:Amazon: barely any convection, horizontal transport dominates in LT. Large amount of CO exported to the East equatorial Pacific.

Oct & NovITCZ shifts south, strongest convection contributing to maximum CO in Nov. in the UT.

688 hPa 430 hPa 226 hPa

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).

Aug

Sep

Oct

Nov

Dec

Vertical profiles of upward mass flux

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

S America (18S-2S, 70W-40W)

Convection Conv. + adv.

Fueglistaler et al. 2009

Convection in GEOS-4 compared to other models (Folkins et al. 2006)

• 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.

CO in the UT in GEOS-4 and GEOS-5

• 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

MLS GEOS-4 GEOS-52005: 215 hPa

Aug

Sep

Oct

Nov

Dec

GEOS 4: No lagGEOS 5: 1 month lag (2006)

From LT to UT, the lag in GEOS-5 is always greater than that in GEOS-4

GEOS 4: 1 month lagGEOS 5: 1-3 month lag

Seasonality and interannual variation of CO - S. America

LT

UT

Optical bench warm-up to improve CO signal

MLSGEOS4_MLSakGEOS4

GEOS5_MLSakGEOS 5

TESGEOS4_TESakGEOS4GEOS5_TESakGEOS 5

MLS/2

Vertical transport in GEOS-4 & GEOS-5 (South America)

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

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.

GEOS-4 GEOS-5 226 hPa

Relationship between convection and CO

• 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.

convectionGEOS5/convectionGEOS4

CO

GE

OS

5/C

OG

EO

S4

GEOS4

GEOS5

GEOS4

GEOS5

South America (18-2S, 70W-40W) Sep,2005

Seasonality and interannual variation of CO – East Pacific

The vertical profiles of upward transport:GEOS-4: Gradually decrease with heightGEOS-5: Sharp decrease around 600 hPa

Vertical mass flux (Pa/s)

MLSGEOS4_MLSakGEOS4GEOS5_MLSakGEOS 5

MLSGEOS4_MLSakGEOS4GEOS5_MLSakGEOS 5

MLS/2

• 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.

Conclusion