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EPS – Earth atmosphere science Science Highlights 2005-2011

EPS – Earth atmosphere science Science Highlights 2005-2011. Ilse Aben , Otto Hasekamp, Jochen landgraf, Sander Houweling et al. Avri Selig (Head of Division EPS). CLIMATE CO 2 and CH 4 strongest anthropogenic greenhouse gases Aerosols by far largest uncertain anthropogenic contribution

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EPS – Earth atmosphere science Science Highlights 2005-2011

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  1. EPS – Earth atmosphere scienceScience Highlights 2005-2011 Ilse Aben, Otto Hasekamp, Jochen landgraf, Sander Houweling et al. Avri Selig (Head of Division EPS)

  2. CLIMATE • CO2 and CH4 strongest anthropogenic greenhouse gases • Aerosols by far largest uncertain anthropogenic contribution • Water vapor is strongest greenhouse gas • AIR QUALITY / TROPOSPHERIC CHEMISTRY • CO air pollutant and affects the oxidizing capacity atmosphere • Aerosols directly affect human health

  3. Interannual variability biomass burning : Gloudemans, ACP, 2009 CO SCIAMACHY 2006 relatively wet year and BB low. Emission estimates of CO sources using SCIAMACHY data and atmospheric modeling is on-going. South America

  4. Long range transport of pollution : model + + + + South America South Africa Australia Enhanced CO levels central Australia due to South American Biomass Burning Gloudemans et al., 2006

  5. Why is methane increasing ? Frankenberg et al., JGR 2011 Clear impact visible of radiation damage. Nonetheless, SCIAMACHY clearly shows recent increase in CH4. Investigation of which sources increased is on-going (atmospheric modelers)

  6. Improvements to the SCIAMACHY data • resolved major spectroscopic issues (CH4 and H2O) • Solved latitudinal and seasonal bias, and H2O correlation SCIA /model SAHARA SCIA /model Frankenberg et al., ACP 2008 ECMWF H2O Frankenberg et al., GRL 2008

  7. Inverse modelling (CO, CH4, CO2) Optimized concentrations Estimate emissions A priori emissions Transport model + optimizer Satellite measurements Optimized fluxes

  8. SCIAMACHY inferred surface fluxes of CH4 InSitu-only InSitu-only A priori InSitu+SCIA A priori InSitu+SCIA Increase in fast growing economies Anomalous warm conditions in the Arctic

  9. CH4 CO2 Height Height Concentration Sensitivity Greenhouse Gas Retrieval from GOSAT • Main challenge: Account for scattering by aerosols and thin clouds: • Proxy approach for CH4 (SCIAMACHY heritage) •  drawback: assumes XCO2 is known • Full Physics algorithm for CO2 and CH4: Retrieve aerosol • properties (amount, size, height) together with CO2 and CH4 SUN Scattering layer? Planetary boundary layer: Sources and sinks. O2 CO2 EARTH 9 9 9

  10. XCH4 from GOSAT: two retrieval methods Full physics: Proxy: Validation studies performed over 12 ground-based measurement stations: Similar overall precision (15 ppb) and relative accuracy (5 ppb,0.27%) for both methods at ground-based stations. Butz et al., 2011 Schepers et al. However, model comparisons indicate both methods show larger deviations under specific circumstances.

  11. XCO2 from GOSAT: From validation to global maps Comparison to ground-based measurements: overall precision of 2.8 ppm, accuracy of 1 ppm (0.25%). 2 years of global maps June to August 2009 Butz et al., 2011 Guerlet et al. CH4 and CO2 data ready to be used for source/sink estimates !

  12. Water cycle and isotopologues The rainout effect Water vapor is depleted in HDO w.r.t. Ocean Water vapor is even more depleted after rainfall Image from http://www.sahra.arizona.edu/ HDO=0.031% H2O Evaporation and condensation changes the relative amount of HDO. Thus measuring HDO/H2O gives information about condensation/ evaporation history of water.

  13. -80 -170 Less HDO  -260 Frankenberg et al., Science, 2009 • first global (satellite) observations of HDO (dD-water) vapour lowest layers atmosphere • models clearly deficient • great potential for hydrological cycle research

  14. Aerosol Retrieval: PARASOL • At SRON a novel algorithm has been developed for aerosol properties • making full use of PARASOL multi-angle photo-polarimetric measurements • Microphysical properties (size, refractive index) are explicitly retrieved instead of assuming "standard" aerosol models  also more accurate optical properties. • This is essential step toward better understanding of the role of aerosols in climate Forth Crete Hier nog plaatje brekingsindex Hasekamp et al., J. Geophys. Res., 2011

  15. Conclusions • Greenhouse Gases (CH4, CO2) Pioneering results from SCIAMACHY. GOSAT allows sub% accuracy. Scientific interpretation on-going using atmospheric modeling. • Carbon Monoxide SCIAMACHY first instrument to deliver total CO columns. Interpretation focused on Biomass Burning and long range transport • Water isotopologues Unique SCIAMACHY product potential to provide new insight in water cycle • Aerosol Novel retrieval method developed for PARASOL providing new products essential for climate research TROPOMI and SPEX SAC 8 Dec. 2009

  16. SAC 8 Dec. 2009

  17. SAC 8 Dec. 2009

  18. SADDU meeting 1-2 Mar 2011, Bremen Applications of inverse modeling at SRON-EPS • Compounds: CO2, CH4, CO • Verification of satellite instruments • Scientific interpretation of the measurements • Support the design of new missions

  19. SADDU meeting 1-2 Mar 2011, Bremen Application to CH4 retrieval from SCIAMACHY Measurements (bias corrected) Optimized model A priori model Bias correction

  20. SADDU meeting 1-2 Mar 2011, Bremen From SCIAMACHY to GOSAT Improved fit residuals point to a significant gain In consistency between model and measurements

  21. FUTURE : TROPOMI launch Dec. 2014 • TROPOMI UV-VIS-NIR-SWIR push-broom spectrometer • Dutch-European (ESA) joint development (initiated by NL- science-industry) • Heritage SCIAMACHY and OMI • SWIR : CO, CH4, HDO/H2O • Strongly improved spatial resolution (7x7km2 vs 120,60x30km2), higher sensitivity (CO 10-20x higher) SCIAMACHY (CO) OMI TROPOMI

  22. The Next Step: SPEX • PARASOL is at the forefront of aerosol satellite remote sensing, but has a • number of shortcomings. The most important improvements addressed by • SPEX are: • Improvement of polarimetric accuracy for refractive index retrieval. • Increase number of viewing angles to distinguish clouds and aerosols. • Extend spectral range to SWIR for coarse aerosol characterization

  23. SAC 8 Dec. 2009

  24. AOT refractive index The need for Multi-Angle Polarization Measurements, land measurements Using intensity (l) only does not provide all the required information on aerosol. Therefore we aim to use the polarisation(l) of scattered light and multi-viewing observations Intensity, 2 viewing angles ------ Intensity, 17 viewing angles ……… 17 view. + polarisation multi-angle photo-polarimetric measurements are essential for aerosol retrieval over land Camelot, 2009

  25. Why is methane increasing again ? Satellite data are global • 2nd most important anthropogenic greenhouse gas • Global emissions CH4 well known • Emissions individual sources uncertain • Variation of certain sources with climatological parameters uncertain • (inter-annual variation), future projections uncertain

  26. Carbon cycle : CO2, CH4, CO SCIAMACHY SWIR (Short Wave Infra Red) measurements • Carbon Monoxide (CO) : • precursor of trop.O3 • affects CH4 and CO2 • proxy for long range transport • emissions uncertain Large inter-annual variability due to Biomass Burning. Reduction in 2006 speculated to be result of regulations. Gloudemans et al.,ACP, 2009 De Laat et al, JGR, in press

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