Quantitative retrievals of NO2 from GOME

Lara Gunn1, Martyn Chipperfield1, Richard Siddans2 and Brian Kerridge2

School of Earth and EnvironmentInstitute of Atmospheric Sciences

1. University of Leeds

2. Rutherford Appleton Laboratory

Introduction• NO2 from GOME has been widely studied

• Still the potential for a more accurate retrieval

Constrain the stratosphere (Chemical Data Assimialtion)

Use cloud and aerosol data from ATSR-2 (GRAPE)

School of Earth and EnvironmentInstitute of Atmospheric Sciences

Input Parameters

(Atmospheric Profiles, GRAPE and GOME snr and slant

columns)

Radiative Transfer Model

(Calculates Photon Path Lengths)Retrieval Model

Optimal Estimation Calculate slant column

and surface albedo

Estimate of scaling factor and albedo

New estimate of scaling factor and

albedo

Output

(Tropospheric VCD, errors)

Input Parameters

Atmospheric Profiles

• Stratosphere

• Troposphere

• SLIMCAT 3D CTM with chemical data assimilation of long-lived species.

• Data Assimilation from 1992 on of HALOE CH4, O3, HCl, H2O.

• Detailed stratospheric chemistry scheme including heterogeneous reactions.

• 7.5o x 7.5o x 24 levels (surface - 60km)• Forced using 6-hourly L60 ECMWF

analyses (ERA-40 until 2001)

Stratosphere

Troposphere

• TOMCAT monthly mean profiles• Off-line tropospheric chemistry model

forced by ECMWF winds• 64 longitudes 32 latitudes (T21) grid over

31 levels• Model description see Arnold et al. 2005

Input Parameters

GRAPE

Cloud and Aerosol Data (GRAPE)

• GRAPE Global Retrieval of ATSR cloud Parameters and Evaluation (NERC – RAL – Oxford)

• State-of-the-art retrieval for the whole ATSR2 dataset.

• Cloud optical depth, height, temperature and aerosol particle size, type, optical depth

Input ParametersGOME sun normalised

radiance

GOME slant columns - gdp and sao

Input Parameters

(Atmospheric Profiles, GRAPE and GOME snr and sc)

Radiative Transfer Model

(Calculates Photon Path Lengths)Retrieval Model

(Dual)

Optimal Estimation

Calculate slant column and surface albedo

Estimate of scaling factor and albedo

New estimate of scaling factor and

albedo

Output

(Tropospheric VCD, errors)

Retrieval Model• Optimal Estimation theory

• xi – state vector [scaling factor, albedo]

• y – measurement vector [slant column, sun normalised radiance]

xi+1=xi+(SE-1+Ki

TSE-1Ki)-1[Ki

TSE-1(y-F(xi))-Sa

-1(xi-xa)]

Input Parameters

(Atmospheric Profiles, GRAPE and GOME albedo)

Radiative Transfer Model

(Calculates Photon Path Lengths)Retrieval Model

Optimal Estimation Calculate slant column

and surface albedo

Estimate of scaling factor and albedo

New estimate of scaling factor and

albedo

Output

(Tropospheric VCD, errors)

Radiative Transfer Code

• Optimized version of GOMETRAN• Scattering cross sections, atmospheric

profiles• Phase functions are calculated at Oxford• Simulates spectrum of radiance received

by GOME• Calculates ‘weighting functions’

(derivatives with respect to the parameters retrieved)

• Clouds as a scattering layer

Input Parameters

(Atmospheric Profiles, GRAPE and GOME snr / sc)

Radiative Transfer Model

(Calculates Photon Path Lengths)Retrieval Model

(Dual)

Optimal Estimation

Calculate slant column and surface albedo

Estimate of scaling factor and albedo

New estimate of scaling factor and

albedo

Output

(Tropospheric VCD, errors)

Output

1. Show NO2 enhancements where excepted

2. Background values are strongly negative

3. Maybe due to profiles used in model

69

1. Show NO2 enhancements where excepted

2. Background values are strongly negative

3. Concs are too high

4. Why are there bits missing???

Problems

Stratosphere

• Two Experiments– Free running

model– Model

constrained by chemical data assimilation of 4 species (CH4, HCl, H2O and O3)

• Sequential sub optimal Kalman filter is used to assimilate HALOE observations of CH4, H2O, O3 and HCl.

• Species are constrained by conservation of compact correlations in the model

(references Khattatov et al 2002, Chipperfield et al 2003)

latitude

latitude

CH4 Assimilation (Run B)

CH4 Free running (Run A)

ppbv

ppbv

Pre

ssu

re (

hP

a)

Assimilated winds (here ERA-40) known to cause too much horizontal mixing causing age of age to be too old (Schoeberl et al, 2003)

Gradients in the subtropics have increased

How does assimilation of a single long-lived tracer (CH4) and O3 lead to improvements in modelled NO2?

• N2O is altered due to the preservation of its compact correlation with CH4

• NOy is altered through compact NOy:N2O correlation.

• NOy is partitioned into the component species by model chemistry.

• Changed O3 (assimilation) also affects NOy partitioning (e.g. NO:NO2 ratio)

Assimilation Scheme

Short-lived Species Validation

NO2 vmr (ppbv)NO2 vmr (ppbv)

Pre

ssu

re (

hP

a)

Pre

ssu

re (

hP

a)

Key

Obs

Run A

Run B

ATMOS 3 SS100

10.3 N 16.3 W

ATMOS 3 SR49

71.1 S 150.3 E

Problems

Retrieval Model

Conclusions – Future work

• NO2 tropospheric VCD background negative

• NO2 tropospheric VCD are too high

• Stratospheric column calculation could be to blame!

• Correct the stratosphere

• Quantify the errors