Investigation of the effects of horizontal gradients of trace gases, aerosols and clouds on the validation of tropospheric TROPOMI products (TROPGRAD) T. Wagner, J. Remmers, S. Beirle, Y. Wang MPI for Chemistry, Mainz, Germany The Mainz 4 azimuth MAX-DOAS Effects of vertical profiles on satellite retrievals Consequences of horizontal gradients on satellite validation Summary
4-Azimuth MAX-DOAS at Mainz (Julia Remmers, MPIC) Continous measurements since Summer 2013 The instrument is located in the outskirts of Mainz
From Multi-Axis DOAS observations vertical profiles of trace gases and aerosols can be derived aerosols Zenith Sun Stratosphere 45 70 Cabauw, 03.07.2009 Spectrograph Troposphere 80 85 88 NO 2 => MAX-DOAS results are ideal for the validation of tropospheric satellite data
Dependemce of the sensitivity of satellite observations on altitude for different aerosol profiles Aerosol profile 0-1km Surface albedo: 3% SSA: 0.93 => strong aerosol effect is found only for high AOD (> about 0.5) Leitao et al., AMT 2010
MAX-DOAS profiles can be used to correct the satellite retrievals Improvement of OMI HCHO observatons over Xianghe, China, using MAX-DOAS profiles (de Smedt et al., ACP, 2015)
Change of OMI Satellite AMFs if MAX-DOAS profiles of trace gases and aerosols are used Validation study for Wuxi, China relative difference of AMF 80% 60% 40% 20% 0% -20% typical case average for pixel measurements NO 2 ecf<10 10<eCF<20 20<eCF<30 30<eCF<40 40<eCF<50 50<eCF<100 => the original satellite AMFs are systematically too high relative difference of AMF 80% 60% 40% 20% 0% typical case average for pixel measurements SO 2 The overestimation increases with increasing cloud fraction relative difference of AMF -20% 80% 60% 40% 20% ecf<10 10<eCF<20 20<eCF<30 30<eCF<40 40<eCF<50 50<eCF<100 typical case average for pixel measurements HCHO 0% Yang et al., AMTD, 2016 ecf<10 10<eCF<30 30<eCF<50 50<eCF<100 ecf bin [%]
Also clouds have a strong effect on the sensitivity of satellite observations Usually they shield tropospheric trace gases below the clouds Richter and Wagner, in The Remote Sensing of Tropospheric Composition from Space, Springer, 2011
There are also cloud effects on MAX-DOAS observations -thin clouds increase the path lenths for low elevation angles => Aerosol extinction is underestimated => Trace gas concentrations are overestimated But these effects are much smaller than for satellite observations
What aboud horizontal gradients? -usually strong gradients exist close to strong emission sources -the average gradient effect was already considered in several publications, e.g. Chen et al., ACP 2009, Ma et al., AMT, 2013) The NO2 VCD at the location of the instrument (white circle) is about 1.3 times larger than than the average of a SCIAMACHY pixel The nightime light intensity at the location of the instrument is about 1.45 times larger than the average of a SCIAMACHY pixel Chen et al., ACP, 2009
Taking the gradient effect into account brings satellite and ground based observations into better agreement Original slope: 0.54 => 0.78 Chen et al., ACP, 2009
What aboud individual measurements? (gradient effects become especially important for sensors with small ground pixels like S5P) NO 2 distribution over Bukarest TROPOMI pixel AIRMAP-MAX-DOAS measurements during ESA-AROMAT-1 campaign (IUP-Bremen, FU Berlin, Andreas Meier et al., submitted to AMT 2016)
NO 2 distribution over Paris Gradients in car-max-doas are larger than in the model TROPOMI pixel Shaiganfar et al., AMT 2015 Car MAX-DOAS measurements and CHIMERE model results 16 July 2009 (MEGAPOLI campaign)
Strong gradients close to emission sources NO 2 distribution around Mainz => also large temporal variability TROPOMI pixel Reza Shaiganfar MPIC Car-MAX-DOAS measurements during MADCAT campaign
Observations in Mainz, Germany Comparison of in situ measurements during MADCAT campaign 12 June 2013 TROPOMI pixel PM 10 [µg/m³ NO2 [ppb] 100 75 50 25 0 75 50 25 0 MZ Mombach MZ Rheinallee MZ Parcus-Str. MZ Groß. Langgasse MZ Zitadelle MZ MPIC CE-DOAS WI Ringkirche WI Schierst. Str. WI Sued
Sensitivity of MAX-DOAS measurements is high within the entire TROPOMI ground pixel Box AMF 0-1km, 360 nm, no aerosols 50 km elevation: 1 SCIA: 30 km x 60 km 0 km TROPOMI 7.5 x 7.5 km² -50 km -50 km 0 km 50 km
Sensitivity of MAX-DOAS measurements is high within the entire TROPOMI ground pixel Box AMF 0-1km, 360 nm, aerosols: 0-1km, OD 0.3 50 km elevation: 1 SCIA: 30 km x 60 km 0 km TROPOMI 7.5 x 7.5 km² -50 km -50 km 0 km 50 km
Let s first consider a simple case clear sky in 1D S5P field of view left profile VCD: 3e16 right profile VCD: 3e16 MAX-DOAS MAX-DOAS is in the center of satellite pixel, no horizontal gradient => Satellite VCD = MAX-DOAS VCD
MAX-DOAS in center of satellite pixel, 1D gradient S5P field of view left profile VCD: 2e16 right profile VCD: 4e16 MAX-DOAS => Satellite VCD = average of MAX-DOAS VCDs
MAX-DOAS at edge of satellite pixel, 1D gradient S5P field of view left profile VCD: 2e16 right profile VCD: 4e16 MAX-DOAS => Satellite VCD = high MAX-DOAS VCD
MAX-DOAS at edge of satellite pixel, 1D gradient S5P field of view left profile VCD: 2e16 right profile VCD: 4e16 MAX-DOAS => Satellite VCD = low MAX-DOAS VCD
Effect of clouds S5P field of view left profile VCD: 2e16 right profile VCD: 4e16 MAX-DOAS => Satellite VCD = low MAX-DOAS VCD
Effect of clouds S5P field of view left profile VCD: 2e16 right profile VCD: 4e16 MAX-DOAS => Satellite VCD = high MAX-DOAS VCD
Examples for horizontal gradients from MAX-DOAS Observations during MADCAT campaign, Mainz, Summer 2013 Observations of the oxygen dimer O 4 : an asymmetry is introduced by the viewing geometry Sun Azimuth
The measured O 4 SCDs (red points) are divided by RTM results (blue line) O 4
The measured O 4 SCDs (red points) are divided by RTM results (blue line) Often almost no azimuthal dependence remains O 4 O 4 ratio
The measured O 4 SCDs (red points) are divided by RTM results (blue line) Often almost no azimuthal dependence remains In some cases strong azimuthal dep. is found => aerosol gradients O 4 O 4 ratio O 4 ratio
The measured O 4 SCDs (red points) are divided by RTM results (blue line) Often almost no azimuthal dependence remains In some cases strong azimuthal dep. is found => aerosol gradients O 4 O 4 ratio O 4 ratio NO 2 ratio 15:00 16:00 17:00 18:00 For NO 2 strong spatial gradients and temporal variability are found
Instead of analysing the 4 azimuall azimuth directions sperately, in the future, all viewing directions (azimuth and elevation angles) should be inverted simultanseously 50 km elevation: 1 SCIA: 30 km x 60 km 0 km TROPOMI 7.5 x 7.5 km² -50 km -50 km 0 km 50 km
Summary: Horizontal gradients appear typically close to strong emission sources. These situations are the main focus for satellite validation of tropospheric trace gases For new sensors with small ground pixels the whole ground pixel can be sensed by MAX-DOAS Horizontal gradients of trace gases, aerosols and clouds can be determined from MAX-DOAS observations The gradients have to be considered in satellite validation We will use 4-azimuth MAX-DOAS observations in Mainz, Germany for S5P validation
NO 2 distribution over Paris Gradients in car-max-doas are larger than in the model TROPOMI pixel Shaiganfar et al., AMT 2015 Car MAX-DOAS measurements and CHIMERE model results 16 July 2009 (MEGAPOLI campaign)
So far, the 4 azimuall azimuth directions are analysed sperately In the future, all viewing directions (azimuth and elevation angles) should be inverted simultanseously 50 km elevation: 1 0 km SCIA: 30 km x 60 km TROPOMI 7.5 x 7.5 km² -50 km -50 km 0 km 50 km
From the 3D spherical Monte Carlo RTM MCARTIM (Tim Deutschmann) the spatially dependent sensitivity of MAX-DOAS observations can be determined (2D, 3D Box AMF) Visualisation of a Monte-Carlo radiative transfer simulation (yellow: surface reflection, red: Rayleigh scattering, green: particle scattering)
High-speed 2-D MAX-DOAS instruments moveable telescope with strong & precise motor Similar instruments are used by Uni Colorado Uni Heidelberg AIOFM Hefei BIRA Brussels