Improving Retrievals of Tropospheric NO
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Improving Retrievals of Tropospheric NO 2. Randall Martin, Dalhousie and Harvard-Smithsonian Lok Lamsal, Gray O’Byrne, Aaron van Donkelaar, Dalhousie Ed Celarier, Eric Bucsela, Joanna Joiner, NASA Folkert Boersma, Ruud Dirksen, KNMI Chao Luo, Yuhang Wang, Georgia Tech. September 14, 2009

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Improving Retrievals of Tropospheric NO 2

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Improving retrievals of tropospheric no 2

Improving Retrievals of Tropospheric NO2

Randall Martin, Dalhousie and Harvard-Smithsonian

Lok Lamsal, Gray O’Byrne, Aaron van Donkelaar, Dalhousie

Ed Celarier, Eric Bucsela, Joanna Joiner, NASA

Folkert Boersma, Ruud Dirksen, KNMI

Chao Luo, Yuhang Wang, Georgia Tech

September 14, 2009

Air Quality Working Group

Aura Meeting

Leiden, Netherlands


Seasonal differences between omi no 2 products

Seasonal Differences Between OMI NO2 Products

Direct Validation Has Not Arbitrated

Standard (SP)

DOMINO (DP)

DP-SP

DJF 2005

JJA 2005

0.1 1 2 3 4 5 6 7 8 9 10 Tropospheric NO2 Column (1015 molecules cm-2)

-5 -3 -1 1 3 5 Δ(1015 molecules cm-2)

Lamsal et al., JGR, submitted


Improving retrievals of tropospheric no 2

Indirect Validation of OMI

(A)In-situ surface NO2 measurements from the SEARCH (photolytic) and EPA/AQS (molybdenum) networks at rural sites in Eastern US

Use GEOS-Chem NO2 profiles to estimate surface-level NO2 from OMI (Lamsal et al., JGR, 2008)

  • (B) Updated bottom-up emission inventories for 2005-2006

Apply GEOS-Chem to infer top-down emissions from OMI by mass balance (Martin et al., JGR,2003)


Improving retrievals of tropospheric no 2

Multiple Approaches Yield Similar Results

SEARCH “True” NO2”, Southeast U.S.

AQS/EPA “Corrected” NO2, Eastern U.S.

NOx Emissions, US + Canada

NOx Emissions, SEARCH domain

Lamsal et al., JGR, submitted


Improving retrievals of tropospheric no 2

Stratosphere-troposphere Separation and AMF Together Explain Difference Between DP and SP

Air mass factor Strat-trop separation Combined

ΔTropospheric NO2 Column DP – SP (1015 molecules cm-2)

Lamsal et al., JGR, submitted


Improving retrievals of tropospheric no 2

Produce DP_GC From DP Averaging Kernels and GEOS-Chem NO2 Profiles

SEARCH “True” NO2”, Southeast U.S.

AQS/EPA “Corrected” NO2, Eastern U.S.

NOx Emissions, US + Canada

NOx Emissions, SEARCH domain

Lamsal et al., JGR, submitted


Surface reflectivity lambertian equivalent reflectivity ler

Surface ReflectivityLambertian Equivalent Reflectivity (LER)


Omi ler kleipool et al 2008 best represents surface ler

OMI LER (Kleipool et al. 2008) Best Represents Surface LER

Cloud-, Snow-, and Aerosol- Free LER (2005-2007)

Use MODIS/Aqua to Eliminate Cloud and Aerosol from OMI Scenes

Use NISE Snow Flag to Eliminate Snow

LER Difference of 2%  15-30% Bias in NO2 (Martin et al., 2002; Boersma et al., 2004)

O’Byrne et al., JGR, submitted


Improving retrievals of tropospheric no 2

Unrealistic Relation in OMI NO2 versus Cloud & Snow

≥ 5cm of snow

0 > snow < 5cm

no snow

(In situ NO2 data show variation < 15%)

Winter OMI NO2 over Calgary & Edmonton

Winter Mean Trop. NO2 (molec/cm2)

OMI Reported Cloud Fraction

O’Byrne et al., JGR, submitted


Improving retrievals of tropospheric no 2

Large Spatial Variation in Snow-Covered Surface LERCurrent Algorithms Assume Snow Reflectivity = 0.6

0 0.2 0.4 0.6 0.8 1

Snow-covered Surface LER (unitless)

Snow Weakly Represented in Previous ClimatologiesLeads to Ambiguity in Accounting for Snow

OMI LER

-0.6

-0.8

-0.4

-0.2

0

0.2

Snow-Covered LER Difference (Previous Climatology – Snow-Covered Surface LER)

O’Byrne et al., JGR, submitted


Improving retrievals of tropospheric no 2

Spatially-Varying Biases in OMI NO2 over Snow

  • To correct NO2 retrieval for snow

  • Use snow-covered surface reflectivity

  • Use MODIS-determined cloud-free scenes to correct clouds

  • NO2 bias for MODIS-determined cloud-free scenes

  • Positive (negative) bias from underestimated (overestimated) surface LER

  • OMI reports clouds when surface LER is underestimated

With All Cloud

Fractions

With Cloud

Fraction

Threshold (f < 0.3)

-50

0

100

O’Byrne et al., JGR, submitted


Recommendations

Recommendations

  • Remote Sensing Community:

  • Use two reflectivity databases: one snow-free, one for snow

  • Switch from TOMS or GOME reflectivity databases to OMI

  • Switch from annual mean to monthly mean NO2 profiles for SP

  • Evaluate Stratosphere-Troposphere Separation

  • Develop instrumentation with finer spatial resolution

  • (more cloud-free scenes reduces dependence on assumed profile )

  • Following DP, include Averaging Kernels (or Scattering Weights) in trace gas products so the user can remove the effect of the assumed profile

  • Ground-based Measurement Needs:

    • span satellite footprint

    • full year

    • research quality (e.g. NO2)

    • vertical profile

Modeling Community:

Continue develop representation of vertical profile


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