Trace gases, aerosols & clouds analysed from GOME, SCIAMACHY and GOME-2. Recommendations for TROPOMI. Thomas Wagner. Satellite Group Mainz Heidelberg

MPI Mainz Germany Trace gases, aerosols & clouds analysed from GOME, SCIAMACHY and GOME-2. Recommendations for TROPOMI. Thomas Wagner Satellite Group Mainz Heidelberg with contributions from: Uni- Heidelberg Germany S. Beirle, T. Deutschmann, E. Eigemeier, C. Frankenberg, M. Grzegorski, M.F. Khokhar, S. Kühl, C.Liu, T. Marbach, K. Mies, M. Penning de Vries, U. Platt, J. Pukite Retrieval Steps Data products & scientific applications Recommendations

Achievements during the last 10 years... - Algorithm development - Global maps & discoveries - Semi-quantitative studies: - Characterisation of sources - Investigation of (intercontinental) transport - First quantitative studies - Trend studies - Determination of source strengths

Set DOAS of Atmospheric satellite Absorbers algorithms Identified developed in GOME Spectra at the Satellite Group at the Institut für Umweltphysik during the last 10 years GOME & SCIA spectral properties O 3 UV OClO HCHO O 4 H 2 O O 2 Spectral albedo 0.6 0.4 0.2 0.0 Satellite group: http://satellite.iup.uni-heidelberg.de 300 400 500 600 700 800 Wavelength [nm] SO 2 NO 2 BrO O 3 vis SCIAMACHY: 240 2300nm => CO, CH 4, CO 2

CO2 CH4 CO C. Frankenberg, SRON, Liu Cheng,MPI Mainz

Specific problems of satellite DOAS spectroscopy Spectral structures due to sun diffuser plate cause artificial offset Solution: Use of atmospheric spectrum instead of solar spectrum OClO SCD [molec/cm²] 4E+14 3E+14 2E+14 1E+14 0E+00-1E+14 GOME OClO SCD Reihe1 Atmospheric spectrum (70 SZA) Reihe2 Direct solar spectrum Unrealistic offset 45 50 55 60 65 70 75 Latitude [ ]

Use of polarisation and etalon spectra in DOAS fit) Etalon spectrum Polarisation key data

Use of polarisation and etalon spectra in DOAS fit) O4 absorption excluding additional spectra Residual excluding additional spectra O4 absorption including additional spectra Etalon spectrum

Include all relevant trace gas spectra in DOAS fit NO2 analysis excluding H2O H2O spectrum Included in GOME operational product since 1999 NO2 analysis including H2O

Vegetation spectra: 0.6 Conifers 0.6 0.4 Decidous 0.4 0.2 Grass 0.2 0.0 0.0 600 650 700 750 800 Spectral Albedo 0.08 0.06 0.04 0.08 0.06 0.04 1.04 High pass filtered albedo 1.04 1.00 1.00 Wagner et al., ACP 2007 0.96 620 640 660 680 Wavelength [nm] 0.96

Progress in quality of the DOAS fit (BrO) Wagner and Platt, Nature, 1998 OD 0.001-0.001-0.003 Mainly caused by improved Ring correction End of 1999 OD -0.005 345 350 355 360 Wavelength [nm] 0.000-0.002-0.004-0.006 345 350 355 360

Experiences in spectroscopy -investigate the spectral residuals -include spectra for polarisation, vegetation, etalon, etc. => carefully check results -include more than one Ring spectrum -include experimental ratio spectra -apply a consistent spectral calibration and cross section convolution -for specific cases advanced and/or iterative DOAS retrievals have to be applied (e.g. IMAP-DOAS)

satellite Example of radiative transfer modelling for satellite nadir geometry, 370 nm, no clouds Look from the side Rayleigh-scattering ground reflection TRACY-II Tim Deutschmann, IUP Heidelberg Look from above

satellite Example of radiative transfer modelling for satellite nadir geometry, 370 nm, with cloud (OD 40) from the surface to 8 km Look from the side Rayleigh-scattering ground reflection particle scattering TRACY-II Tim Deutschmann, IUP Heidelberg Look from above

Height dependence of the sensitivity (Box-AMF) AMF i = SCD i /VCD i Albedo: 5% Albedo: 50% e.g. Ocean e.g. Snow

Optical thickness: 50 Optical thickness: 50

Optical thickness: 4 Optical thickness: 100

Optical thickness: 20 Optical thickness: 100 Broken clouds

Influence of aerosols SCA: 1 Aerosol optical depth 0 0.5 1 2 3 Aerosol layer

Influence of aerosols Influence of the single scattering albedo on sensitivity SCA: 1 SCA: 0.9 SCA: 0.8 Aerosol optical depth 0 0.5 1 2 3 Aerosol layer

Experiences in radiative transfer modelling -take into account surface albedo, BDRF, totography, clouds, aerosols -3D effects for trace gases, clouds, aerosols -also polarisation effects are important! -RTM of ocean properties?

Example for a normalisation procedure Comparison between MOPITT & SCIAMACHY 4.00E+018 3.50E+018 3.00E+018 2.50E+018 MOPITT from0to5 from5to10 MOPITT SCIA (cloud fraction <5%) CO VCD 2.00E+018 1.50E+018 1.00E+018 Sahara 5.00E+017 0.00E+000 01.01.2004 01.07.2004 01.01.2005 01.07.2005 01.01.2006 01.07.2006 Time 4.00E+018 3.50E+018 mopitt SCI_cloudfraction0~5 3.00E+018 2.50E+018 CO 2.00E+018 1.50E+018 1.00E+018 Australia Liu Cheng, C. Frankenberg 5.00E+017 0.00E+000 01.01.2004 01.07.2004 01.01.2005 01.07.2005 01.01.2006 01.07.2006 Time

One of our first GOME tropospheric NO2 maps Carsten Leue, 1998 Tropospheric NO2 VCD

Tropospheric NO2 column density SCIAMACHY, 2003/04 Steffen Beirle NO2 VCD [10 15 molec/cm²]

Our maps help to find cleaner working places Mainz Heidelberg Tropospheric NO2 VCD, SCIAMACHY Steffen Beirle NO2 VCD [10 15 molec/cm²]

Our first NO2 image from GOME-2 (only 1 day, almost global coverage) Steffen Beirle Direct transmission of data to the antenna on the roof of our institute

Trace gases Trop. NO 2 VCD (S. Beirle) SO 2 SCD (M.F. Khokhar) SCIAMACHY, 2003/04 GOME, 1996-2001 HCHO SCD (T. Marbach) BrO VCD (J. Hollwedel) GOME, 1997 GOME, 1996-2001

Trace gases CO VCD C. Frankenberg, Liu Cheng H 2 O VCD T. Wagner SCIAMACHY, Jan., Feb. 2004 GOME, 1996-2002 CH 4 VCD C. Frankenberg (now at SRON) Glyoxal SCD S. Beirle SCIAMACHY, Aug.-Nov. 2003 SCIAMACHY, 2004

Cloud Products O2 VCD T. Wagner, M. Grzegorski Cloud top height T. Wagner GOME, 1996-2003 GOME, 1996-2003 Ring SCD T. Wagner Cloud fraction M. Grzegorski GOME, Nov., Dec. 2000 HICRU, GOME, 1996-2002

Aerosol Products UV Absorbing Aerosol index M. Penning de Vries SCIAMACHY, JAS 2004 UV Scattering Aerosol index M. Penning de Vries Preliminary results SCIAMACHY, JAS 2004

Surface properties Water Raman scat. T. Wagner Conifers T. Wagner, E. Eigemeier GOME, 1996-2003 GOME, Sept. 1998 Grass T. Wagner, E. Eigemeier Decidous T. Wagner, E. Eigemeier GOME, Sept. 1998 GOME, Sept. 1998

The total vertical column density contains stratospheric and tropospheric concentrations Enhanced Tropospheric BrO concentrations during polar spring (Wagner & Platt, 1998) Bromine Explosion With assumption: trop. BrO between 0 and 500m Stratospheric offset tropospheric mixing ratio [ppt] 0 20 40

Many discoveries, here an example of strong OClO increase due to mountain lee waves (Sven Kühl, IUP-Heidelberg, JGR, 2004) Almost complete activation over an altitude range of about 10 km On the 21 st of January, a sudden increase of the OClO SCDs is seen over northern Scandinavia, the same region where strong activity of mountain waves has been reported for the same day (Dörnbrack et al., 1999).

(Steffen Beirle, IUP Heidelberg) NO 2 Production by Biomass Burning Correlation of the NO2 VCD with Fire Counts for different regions of the world South America North America Central Africa (east) Indonesia North Australia Eastern Russia

Seasonal variation of the CO distribution JFM 2004, 2005 JJA 2004, 2005

Dependence of tropospheric BrO on latitude and time Arctic Latitude [degree] 85 80 75 70 65 60 55 50 SZA > 87 => Relationship between bromine explosion and one year old sea ice 45 40 Dec January February March April May June 1 2 3 4 [1013 molec/cm²] Wagner et al., JGR, 2001 85 80 75 SZA > 87 Antarctic Latitude [degree] 70 65 60 55 50 45 40 1 2 3 4 [1013 molec/cm²] Average Extension of Sea Ice Jun July August September October November Dec Frost Flowers

NO 2 Production by Lightning Lightning Activity and GOME- NO 2 for selected months 6 NO 2 [10 14 molec/cm 2 ] 5 4 3 monthly mean values 2 0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 Lightning Activity [Flashes/day/pixel] (Steffen Beirle, IUP Heidelberg, Adv. Space Res., 2004) From our study (if simply extrapolated): 2.8 (0.8 14) Tg [N] / yr

Investigation of transport processes: comparison with models Intercontinental transport of anthropogeneous NO 2 measured by GOME and modeled by FLEXPART [Stohl et al., ACP, 2003]

Investigation of transport processes: comparison with models Difference: NAO + -NAO - (winter 1996-2002) Model results from FLEXPART GOME tropospospheric NO 2 Influence of the North Atlantic Oscillation on the tropospheric transport paths [Eckhardt et al., ACP, 2003]

Change of global circulation due to El-Nino Relative deviation of the GOME H2O VCD from the long year mean October 1997 March 1998 humidity Wagner et al., JGR, 2005

Time series of monthly anomalies of the H 2 O VCD and the temperature 0.9 0.8 0.7 Wagner et al., JGR, 2006 5.E+21 4.E+21 3.E+21 Whole Earth Temperature anomaly [K] 0.6 0.5 0.4 0.3 0.2 2.E+21 1.E+21 0.E+00-1.E+21-2.E+21 H2O anomaly [molec/cm²] 0.1 temp_anomaly H2O_anomaly -3.E+21 0 1996 1997 1998 1999 2000 2001 2002 2003 Time -4.E+21 Tropics (30 N - 30 S) 6.00E+21 5.00E+21 4.00E+21 3.00E+21 temp_anomaly H2O_anomaly Trop_3030_H2O_anomaly Trop_-30 bis+30 0.9 0.8 0.7 0.6 2.00E+21 0.5 1.00E+21 0.4 7E+21 0.00E+00 0.3 H2O VCD anomaly [molec/cm²] 5E+21 3E+21 1E+21-1E+21-3E+21-5E+21 y = 9.6E+21x - 3.2E+21 R 2 = 0.57 0 0.2 0.4 0.6 0.8 Temperature anomaly [K] -1.00E+21-2.00E+21-3.00E+21-4.00E+21 Jan. 96 Jan. 97 Jan. 98 Jan. 99 Jan. 00 Jan. 01 Jan. 02 Jan. 03 => strong water vapour feedback Similar findings from study after Pinatubo eruption (Soden et al., 2002) 0.2 0.1 0-0.1

Correlation of the monthly anomalies of the H 2 O VCD and surface temperature Change of the H2O VCD per Kelvin [10 21 molec/cm²]

[%] Correlation of the monthly anomalies of the cloud fraction and surface temperature Change of the effective cloud fraction per Kelvin

Variation of the cloud top height with surface temperature derived from the correlation analysis Wagner et al., ACPD 2008 Change of the cloud top height per Kelvin [km]

Trends in China Comparison of trop. NO 2 from GOME and SCIAMACHY 1996-2001 2003-2004 GOME narrow mode SCIAMACHY *10 15 molecules/cm 2 S. Beirle, IUP Heidelberg

0.04 Global average trends O2 anomaly HICRU anomaly 0.00-0.04 0.04 0.00-0.04 Monthly anomalies from 60 S to 60 N +0.2km over 7 years O2 absorption -0.80% over 7 years HICRU cloud fraction +0.33% over 7 years H2O anomaly [molec/cm ] 4E+21 0E+0-4E+21 H2O VCD +2.1% over 7 years temp. anom. [K] 0.80 0.40 0.00 temperature +0.10 K over 7 years 1996 1997 1998 1999 2000 2001 2002 2003 2004 Time

Anthropogenic sources: NO x from ships Estimated NO x emissions (Endresen et al.) GOME NO 2 VCD (Meridional high-pass filter applied) Beirle et al., GRL, 2004 (similar results also from A. Richter, IUP Bremen) 10 13 molec/cm 2

Anthropogenic sources: NO x from ships Lifetime estimation: 3.7 hours Ship emissions (Gg [N]/yr): 26 (11-81) Winter: ITCZ south, Summer: ITCZ north EDGAR: 34 Endresen: 41-54 Corbett: 22/44 Beirle et al., GRL, 2004

Ship-emissions: SCIAMACHY NO 2 2003-2006, 2D high-passfiltered NO2 VCD Steffen Beirle AMVER ship density (% of total)

Ship-emissions: GOME HCHO 1996-2003, 1D highpass-filtered HCHO SCD (winter) Thierry Marbach AMVER ship density (% of total)

Comparison with model results CH 4 VCD from SCIAMACHY C. Frankenberg, IUP Heidelberg J.F. Meirink, KNMI, Utrecht Science, March 2005 SCIAMACHY, Aug-Nov 2003 TM3 model, Aug-Nov 2003

Difference SCIAMACHY Model, Aug-Nov 2003 C. Frankenberg, IUP Heidelberg The largest differences can be seen in tropical broadleaf evergreen forests Science, March 2005 In agreement with recent findings of a new CH 4 source from plants under aerobic conditions Keppler et al., Nature 2006 MODIS Enhanced Vegetation Index

Summary of the last 10 years:...the new satellite sensors exceeded the expectations: The global distribution of several tropospheric trace gases could be detected, many unexpected observations New insight in distribution and characteristics of sources New insights in atmospheric transport pathways Trend studies Global inverse modelling => New View!

Recommendations for TROPOMI Avoid polarisation sensitivity Avoid spectral structures caused by diffuser plate (or other parts) Avoid undersampling (IR channel) Enable the use one Fraunhofer (solar) spectrum for all observations => scanning mirror concept?

Recommendations for TROPOMI Include additional IR channel (~1600nm for CO2 and CH4) (also for cloud water phase) Decide which spatial resolution is really required, based on chemical model data and radiative transfer modelling Start UV channel at 300nm (SO2 retrieval), NIR channel at <610nm (O4, vegetation spectra)

Many thanks for your attention! Satellite Group April 2007