Application of a probability density function-based atmospheric light-scattering correction to carbon dioxide retrievals from GOSAT over-sea observations

作者：Bril Andrey^*; Oshchepkov Sergey; Yokota Tatsuya

来源：Remote Sensing of Environment, 2012, 117: 301-306.

DOI：10.1016/j.rse.2011.10.005

• Greenhouse gases
• Satellite remote sensing
• Inverse methods

We present the application of a photon path length probability density PPDF) formalism to atmospheric carbon dioxide (CO2) retrievals from reflected sunlight measured by the Greenhouse Gases Observing Satellite (GOSAT) over the ocean. GOSAT short-wave infrared (SWIR) radiance spectra detected over the ocean surface were shown to be strongly affected by atmospheric light-scattering. In particular, retrievals of column-averaged CO2 dry-volume mixing ratios (XCO2) were characterised by steady negative bias and significant scatter when optical path modification due to high variability of clouds and aerosols was neglected. Considering that the ocean surface in SWIR is dark in all directions except that of sun-glint observation, PPDF radiative transfer modelling was simplified by neglecting the contribution of photons that interacted with both aerosols/cloud particles and the ocean surface. This permitted implementation of an atmospheric correction technique based on simultaneous retrievals of CO2 concentrations and two PPDF parameters: effective altitude of the aerosol layer and relative layer reflectivity. Using this correction, both bias and scatter of carbon dioxide retrievals were significantly reduced. The retrieval results of XCO2 statistically agreed (both spatially and temporally) with those predicted by the atmospheric transport model.

• 出版日期2012-2-15