Greenhouse Gas Satellite Remote Sensing from GOSAT

1. Greenhouse Gas Satellite Remote Sensing from GOSAT Robert Parker, Austin Cogan and Hartmut Boesch EOS Group, University of Leicester Thanks to Annmarie Fraser and Liang Feng and Paul Palmer School of GeoSciences, University of Edinburgh

2. GOSAT • First dedicated Greenhouse Gas measuring satellite • Launched on 23 January 2009 by JAXA • Payload carries 2 instruments: • TANSO Fourier Transform Spectrometer (FTS): • Provides spectrally-resolved radiances for 4 shortwave-IR (polarized) and thermal-IR bands • Covers several absorption bands of CO2, CH4, H2O and O2 • Cloud aerosol imager (CAI): • 4 broadband channels from UV to SWIR with high spatial resolution that provide cloud information

3. UoL FP Retrieval • UoL FP Algorithm: OCO (ACOS) Full Physics Optimal Estimation algorithm (O’Dell et al., 2011, Boesch et al.,2011) – similar to ACOS algorithm • CO2 and CH4 Full Physics Retrieval: • Fit to O2 A Band, 2.06μm CO2 Band and 1.61 μm CO2 or 1.65 μm CH4 Band • CO2 / CH4 profile and scaling factors for CH4, H2O • Extinction profiles of 2 aerosol types and 1 cirrus type • Surface pressure (Surface Pressure renormalisation is applied) • O2 A Band zero level offset (fluorescence + non-linearity correction) • CH4 Retrieval (CH4/CO2 proxy): • Fit to CO2 Band at 1.61μm + 1.65 μm CH4 Band • Retrieves CO2 and CH4 profiles • Modelled aerosol optical depth Pre-filtering: SNR > 50, land surface Cloud Screening: O2 A Band retrieval(Micro window): surface pressure difference < 20 hPa CH4 OE Retrieval: Spectral Fit to CH4 and CO2 Bands CO2 (or CH4) OE Retrieval: Simultaneous Spectral Fit to O2 and two CO2 (CH4) Bands Post-filtering: Quality of Fit (χ2) A Posterior Error Number of Diverging Steps Post-filtering: Quality of Fit (χ2) A Posterior Error Surface Pressure Bias Aerosol/Cirrus Optical Depth Number of Diverging Steps and a few more

4. The “Proxy” Retrieval • Clouds and aerosols can significantly change the light-path and hence the inferred concentrations by scattering light • The proxy approach performs a retrieval of an additional species which travels the same light-path • This ratios out majority of scattering effects • CO2 is used as proxy gas as it varies far less than methane and is spectrally close • For accurate retrieval of CO2 we need to describe: • Multiple-scattering • Aerosols and Clouds • Polarization • Spherical Geometry • Surface properties • Instrument properties • Solar flux • Gas absorption • Spectroscopy (incl. line-mixing) • Relies on model CO2 to convert ratio back to VMR [Courtesy to C. O’Dell, CSU]

5. Validation against ground-based TCCON • TCCON (Total carbon column observing network): • Network of ground-based Fourier Transform Spectrometers • Provide precise and accurate total columns of CO2, CH4 and other gases • Columns are calibrated against aircraft in-situ profiles (by applying spectroscopic correction factor) • Validation uses all cloud-free GOSAT overpasses within +/-5o and 2 hours Calibration against in-situ profiles (Wunch et al., 2010)

6. Validation of GOSAT Proxy XCH4 • Correlations typically between 0.4 and 0.7 • Estimated single-sounding precision between 10-15 ppb • Site-dependent bias between -0.6 and 8 ppb

7. Global Annual GOSAT XCH4

8. Global Monthly GOSAT XCH4 (Proxy) • Key features • India/China – September – Rice paddies • Alaska/Boreal Asia – NH Summer – Wetlands/Wildfires • Africa/S. America – Biomass burning Updated version of Parker et al., 2011 GRL

9. Regional comparison of GOSAT with GEOS-Chem Updated version of Parker et al., 2011 GRL

10. Validation of GOSAT XCO2 Cogan et al., Atmospheric carbon dioxide retrieved from the Greenhouse gases Observing SATellite: Comparison with ground-based TCCON observations and model comparison, ACP, Paper in prep.

11. Regional GOSAT-Model Comparisons GOSAT H + M Gain data included

12. Seasonal GOSAT-Model Comparisons

13. Seasonal GOSAT-Model Comparisons with Bias Correction Bias-correction based on regression against pseudo-observations >25oS (similar to Wunch et al., 2011)

14. Summary • Global multi-year GOSAT CH4 (proxy method) and CO2 retrieved at Leicester. Full physics CH4 retrieval are underway • From validation against TCCON we find • Bias of 0.1 - 0.9% with precision of 0.4 - 0.8% for proxy CH4 • Bias of 0.02 - 0.2% with precision of 0.5 - 0.8% for CO2 • Comparisons to GEOS-Chem models show • Very high consistency for methane (r=0.85) • Good agreement (r=0.65) for CO2 but some apparent biases over Sahara and central Asia which can be reduced by bias-correction methods • Flux inversions (Edinburgh) of GOSAT data underway • Further improvements are expected from implementation of new aerosol scheme for our CO2 and CH4 FP retrievals and recent updates to spectroscopy (JPL) and new L1B data (v1.50 data) • Collaborations with several NCEO partners (Edinburgh, RAL, Leeds, KCL) and involvement in number of internat. projects: ESA CCI, FP7 MACC-II, FP7 InGOS

15. Phase 2 Activity • Further develop and improve the GHG retrieval (CO2 and CH4 and CO2/CH4 ratio) for generation of long-time series from GOSAT. • Continued characterization and validation of the retrieval and interact closely with inverse modelling and land surface modelling groups on the use of the datasets • Expand the retrieval for upcoming (OCO-2 or S5P) and proposed missions (Carbonsat, GOSAT-2, Tansat, TCM) for generation of new datasets and inter-calibration of data from different missions • Challenge land surface models (such as Jules or SDGVM) with regional Name-based modelling studies (currently under development) • Exploit additional capabilities of GOSAT/OCO-like sensor: plant fluorescence, aerosol vertical distribution, H2O profiles over land