Intercomparison of tropospheric ozone measurements from TES and OMI –

a new method using a chemical transport model as comparison platform

Lin Zhang, Daniel Jacob, Xiong Liu, Jennifer Logan, and the TES Science Team

Aura Science Team Meeting(Oct. 28, 2008)

Work supported by NASA Earth and Space Science Fellowship

Concurrent ozone measurements from IR and UV

OMI

Nadir-looking instrument measuring backscattered solar radiation (270-500 nm)

Daily global coverage at a spatial resolution of 13 x 24 km2 at nadir

Retrieve ozone at 24 ~2.5 km layers

Do they provide consistent measurements of tropospheric ozone?

What can we learn by comparing both measurements with chemical transport models?

TES

Infrared-imaging Fourier transform spectrometer (3.3-15.4 µm) 16 orbits of nadir vertical profiles at a spatial resolution of 5x8 km2 and spaced

1.6° along the orbit track every other day. Retrievals of ozone and CO at 67 levels from surface up to 0.1 hPa, version 3

data

Vertical sensitivity of TES and OMI ozone retrievals

July 2006 Degrees of Freedom for tropospheric ozone

Zonal average of Diagonal terms of AK

Averaging kernel

Both retrievals are obtained from the optimal estimation method [Rodgers, 2000]:

OMITES

Tropospheric ozone from TES and OMI

OMI observations are selected along TES pixels. The data are reprocessed with a single fixed a priori.

2006 ozone at 500 hPa averaged on 4ox5o resolution

Tropospheric ozone from TES, OMI and GEOS-Chem

The data and model results are reprocessed with a single fixed a priori. GEOS-Chem simulation in 4ox5o resolution is sampled along the TES/OMI pixels, and then smoothed by corresponding averaging kernels.

2006 ozone at 500 hPa averaged on 4ox5o resolution

Ozonesonde data from 2005-2007, available at AURA AVDC

Coincidence Criteria: < 2o longitudes & Latitudes, < 10 hours

Validation with ozonesonde

60oS-60oN, 500 hPa:

TES has a positive bias of 5.4 ± 9 ppbv

OMI has a positive bias of 3.1 ± 5 ppbv

Methods for the intercomparison

Sparse in time and space

Validation Validation

1. Sonde method: Validation with ozonesonde measurements

Methods for the intercomparison

Sparse in time and space

Validation Validation

1. Sonde method: Validation with ozonesonde measurements

2. Direct method: Compare OMI/TES directly after considering their different a priori constrains and vertical sensitivity (Apply OMI averaging kernels to TES retrievals)

Direct comparison (Rodgers and Conner, 2003)

Methods for the intercomparison

Sparse in time and space

Validation Validation

1. Sonde method: Validation with ozonesonde measurements

2. Direct method: Compare OMI/TES directly after considering their different a priori constrains and vertical sensitivity (Apply OMI averaging kernels to TES retrievals)

3. CTM method: Use GEOS-Chem CTM as a comparison platform

Comparison Comparison

Comparison

Direct comparison (Rodgers and Conner, 2003)

Methods for the intercomparison

Sparse in time and space

Validation Validation

1. Sonde method: Validation with ozonesonde measurements

2. Direct method: Compare OMI/TES directly after considering their different a priori constrains and vertical sensitivity (Apply OMI averaging kernels to TES retrievals)

3. CTM method: Use GEOS-Chem CTM as a comparison platform

Evaluation Evaluation

Interpretation Interpretation

Evaluation Interpretation

Direct comparison (Rodgers and Conner, 2003)

What do the methods actually compare?

1. Sonde method: TES – sonde/TES AK = bTES

OMI – sonde/OMI AK = bOMI

TES – OMI = bTES – bOMI

2. Direct method: AOMIbTES – bOMI + AOMI(ATES – I)(X – Xa)

3. CTM method: (TES – CTM/TES AK) – (OMI – CMT/OMI AK)

= bTES – bOMI + (ATES – AOMI)(X – XCTM)

Let

(Rodgers and Conner, 2003)

Quantify differences between TES and OMI

1. TES – OMI (sonde) = bTES – bOMI

2. TES (OMI AK) – OMI = AOMIbTES – bOMI + AOMI(ATES – I)(X – Xa)

3. TES – OMI (GC) = bTES – bOMI + (ATES – AOMI)(X – XCTM)

76 TES/OMI/sonde coincidences for 2006

500 hPa

850 hPa

In the direct method, slopes < 1 reflect application of AOMI reduce the sensitivity to diagnose the bias.

The CTM method preserves the variability of the differences in the comparison.

TES – OMI Sonde method [ppbv]

TES – OMI Sonde method [ppbv]

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Difference between TES and OMI at 500 hPa

2.6 ± 6.6 ppbv -0.1 ± 3.6 ppbv -0.3 ± 5.0 ppbvTES – OMI Mean ± 1 sigma

Sonde method Direct method CTM methodTES – OMI

Difference between TES and OMI at 850 hPa

3.3 ± 6.8 ppbv -0.3 ± 1.9 ppbv 2.7 ± 5.5 ppbvTES – OMI Mean ± 1 sigma

Sonde method Direct method CTM methodTES – OMI

Differences with GEOS-Chem at 500 hPa

Minus 3 ppbv from both TES and OMI measurements. Regions with the bias between TES and OMI larger than 10 ppbv are masked as black.

For 2006 and averaged on 4ox5o resolution

GC – sonde GC/TES AK – (TES– 3) GC/OMI AK – (OMI– 3)

Differences with GEOS-Chem at 500 hPa

Minus 3 ppbv from both TES and OMI measurements. Regions with the bias between TES and OMI larger than 10 ppbv are masked as black.

For 2006 and averaged on 4ox5o resolution

GC – sonde GC/TES AK – (TES– 3) GC/OMI AK – (OMI– 3)

Extra

2006 ozone at 500 hPa averaged on 4ox5o resolution

Tropospheric ozone measurements from TES and OMI

OMI observations are sampled along the TES pixels.

Convert the different a priori to a fixed a priori: ( )( )aa XXAIXX −′−+=′ ˆˆ

Examples of clear-sky Averaging Kernels

(a) TES (67 levels)

(b) OMI (24 layers)

15°N 40°N 60°N