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Institute of Environmental Physics and Remote Sensing IUP/IFE-UB Physics/Electrical Engineering Department 1 [email protected] Institute of Environmental Physics and Institute of Remote Sensing University of Bremen Tropospheric NO 2 Height Determination Andreas Richter, A. Hilboll, and J. P. Burrows S5P Verification Meeting Bremen, November 29, 2013

Institute of Environmental Physics and Remote Sensing IUP/IFE-UB Physics/Electrical Engineering Department 1 [email protected] Institute

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Institute of Environmental Physics and Remote SensingIUP/IFE-UB Physics/Electrical Engineering

Department 1

[email protected]

Institute of Environmental Physics and

Institute of Remote Sensing

University of Bremen

Tropospheric NO2 Height Determination

Andreas Richter, A. Hilboll, and J. P. Burrows

S5P Verification MeetingBremen, November 29, 2013

[email protected]

Introduction

• Satellite observations provide nice global maps of tropospheric NO2

• Absolute values depend strongly on assumed vertical distribution• This information currently comes completely from a priori dataÞ Can‘t we do better than that?

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What triggered this study?

• Monthly GOME-2 tropospheric NO2 data are missing most of the large values

• These were removed by cloud filtering as aerosol was so thick that data were classified as partially cloudy

No cloud screening

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Is it only Aerosols?

• Even without cloud screening, there are data gaps over pollution hot spots on some days

• This is due to quality checking as these fits are poor

No Chisq. screening

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Why are the fits poorer at strong pollution?

• There are large and clearly structured residuals in fits over pollution hot spots

• This is not random noise!

• Comparison to NO2 cross-sections shows that scaling of NO2 should change over fitting window

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Wavelength dependence of Air Mass Factor

• For constant albedo, AMF of NO2 layer close to the surface increases with wavelength in a Rayleigh atmosphere

• For a surface layer, this can be a significant effect• With radiative transfer modelling and a formal inversion, this should

provide information on the altitude of the NO2

About +/- 20%

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Empirical Approach

• Take standard NO2 x-section

• Scale to increase amplitude with wavelength

• Orthogonalise to leave NO2 columns unchanged

When introduced in the fit, large residuals are fixed

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Results Empirical Approach

• The empirical NO2 AMF proxy is found over the pollution hotspot in China

• It is not found at other locations where the NO2 slant column is large

• There is some noise in the retrieval of the proxy

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Results Empirical Approach: OMI

• As for GOME-2 data, the empirical NO2 AMF proxy is found over the pollution hotspot in China

• There is more noise than in GOME-2 data• Problems with row anomaly

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Is there more than China?

• Fit is improved by AMF proxy everywhere over pollution hotspots

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Comparison to NO2 columns

• Overall pattern similar to NO2 map

• Differences in distributions of maxima

• Artefacts over water• noise

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Impact of Clouds

• On many days in winter, very large NO2 slant columns are observed over Europe and the US

• The NO2 AMF proxy picks up only very few of these signals

• This is linked to the fact that most of the events are related to cloudy scenes or snow on the surface, resulting in small wavelength dependence

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Sensitivity Study

• Ratio of AMF proxy and NO2 has strong dependence on NO2 layer height

• Dependence on albedo is small between 3% and 7%

Synthetic data:• Rayleigh atmosphere• Constant albedo• NO2 layer in different altitudes• DOAS fit on spectra• NO2 temperature dependence

corrected by using 2 NO2 x-sections• AMF proxy included

• Ratio of AMF proxy / NO2 to normalise signal

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Sensitivity Study: SZA

• Effect varies with SZA; larger effect at larger SZA• At large SZA, AMF proxy also found for elevated NO2

• Dependence on albedo is small between 3% and 7%

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Sensitivity Study: Bright Surfaces

Þ multiple scattering over bright surfaces is stronger at shorter wavelengths

Þ wavelength dependence of AMF is inverted

• Increasing albedo reduces effect as expected for reduced importance of Rayleigh scattering

• For large albedo (> 50%), negative fit factors are found for AMF proxy => wavelength dependence is inverted and only weakly dependent on altitude

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Impact of Aerosols and Clouds

Shielding

• Similar effect for both, AMF proxy and NO2 => will cancel in ratio

• Ratio will give layer height for cloud free part of pixel

Light path enhancement

• Light path enhancement in clouds / aerosols depends only weakly on wavelength

• Effect on NO2 but no effect on AMF proxy

• Ratio will no longer be representative of NO2 layer height

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Case Study Highveld

• NO2 plume from Highveld power plants can be tracked onto the ocean

• NO2 SC values increase downwind of the source

• AMF Proxy also has higher values within the plume, but– Is more narrow– Has largest values at beginning of plume, not at the end of it

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What about larger wavelength difference?

• Tropospheric signal much smaller in UV fit• Ratio between two fits depends on location (=> NO2 height)

• BUT: UV fit is noisy

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Summary

• A simple empirical pseudo-cross-section was used to detect and correct the AMF wavelength dependence of tropospheric NO2 in GOME-2 data

• Application improves NO2 fits over pollution hotspots under clear sky conditions

• As expected, the signature is not found over clouds and bright surfaces or in cases of large stratospheric NO2

• The results can at least give an indication for where an AMF for BL NO2 is appropriate

• Tests on synthetic data suggest that for good signal to noise, an effective NO2 layer height can be determined

• Using more separated wavelengths and applying a formal inversion including aerosol properties might provide more vertical information

• Application to more data also from OMI and S5P foreseenFunding by DLR Bonnunder Contract 50EE1247