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

https://doi.org/10.1016/j.rse.201110005 Get rights and content

Abstract

We present the application of a photon path length probability density function (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.

Highlights

► PPDF-based atmospheric correction of GOSAT over-sea CO2 observation was performed. ► GOSAT PPDF-retrievals detected spatial and temporal variations of XCO2 over-oceans. ► Precision of XCO2 retrievals over-oceans was preliminary estimated as 1–2 ppmv.

Introduction

Atmospheric carbon dioxide (CO2) is generally accepted as a dominant anthropogenic greenhouse gas. Because of its high contribution to global radiative forcing (1.66 ± 0.17 Wm−2), atmospheric CO2 is an important factor in global climate change (IPCC, 2007). However, current knowledge about carbon dioxide sources and sinks is still insufficient for reliable climate predictions. Ground-based CO2 observations are too sparse to sufficiently reduce uncertainties in source and sink characterisation. Satellite observations provide global coverage, but their retrieval efficiency for gas can be limited by the high variability of atmospheric light-scattering and ground-surface properties when interpreting reflected sunlight. Retrieval precision and accuracy requirements have been discussed elsewhere (Baker et al., 2010, Chevallier et al., 2007, Rayner and O'Brien, 2001). For column-averaged CO2 dry-volume mixing ratios (XCO2), a precision of ~ 1% (2.5 ppmv) or better for monthly means at the regional scale is required to improve estimates of surface CO2 fluxes based on in situ measurements (Houweling et al., 2004, Patra et al., 2003, Rayner and O'Brien, 2001). Generally, XCO2 could be monitored from space using short-wavelength infrared (SWIR) measurements of reflected sunlight, which are sensitive to CO2 abundances in the atmospheric boundary layer (Crisp et al., 2004).
Atmospheric light-scattering by aerosols and cloud particles remains a major source of XCO2 retrieval errors that exceed the precision limits (Aben et al., 2007, Dufour and Breon, 2003, Mao and Kawa, 2004, O'Brien and Rayner, 2002, Reuter et al., 2010). Several approaches have been proposed to correct the impact of atmospheric light-scattering when retrieving column-averaged gas values. In so-called full-physics algorithms (Butz et al., 2009, Connor et al., 2008, Yoshida, 2011), a limited number of effective aerosol and/or cloud characteristics are included in the state vector for their simultaneous retrieval with target gas amounts. Recent studies (Bril et al., 2007, Oshchepkov et al., 2008) have proposed light-scattering corrections based on analyses of photon path length statistics. The measured signal is expressed in terms of a photon path length probability density function (PPDF) with further parameterization of the PPDF. This method is very rapid because it excludes time-consuming radiative transfer computations from the retrieval procedure. In this study, we present a methodology and initial results of simultaneous XCO2 and PPDF retrievals from Greenhouse Gases Observing Satellite (GOSAT) over-sea observations.
GOSAT was launched on 23 January 2009 to monitor the global distributions of atmospheric carbon dioxide and methane. The satellite has a sun-synchronous orbit at an altitude of 666 km and a 3-day recurrence with the descending node around 12:48 local time. The GOSAT mission instruments are the Thermal and Near infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS) and -Cloud and Aerosol Imager (TANSO-CAI) (Kuze et al., 2009).
The TANSO-FTS has three narrow bands in the SWIR region (0.76, 1.6, and 2.0 μm) which are used for XCO2 and PPDF retrievals. For SWIR bands, incident light is divided by a polarization beam splitter and then simultaneously recorded as two orthogonal polarization components (hereafter called P and S components). The TANSO-FTS instantaneous field of view is 15.8 mrad, which corresponds to a nadir footprint diameter of about 10.5 km. The pointing mechanism of the TANSO-FTS enables off-nadir observations, e.g., sun-glint over-sea observations. Because of the limited driving angles of the pointing mirror (± 35° in the cross-track direction and ± 20° in the along-track direction), GOSAT performs sun-glint measurements within narrow (~ 30°) near-equator latitude ranges. More details on the TANSO-FTS have been provided by Kuze et al. (2009).

Section snippets

Retrieval algorithm

The retrieval procedure was based on the constrained minimization of the residual between the predicted R and observed R⁎ spectral radiance. According to the Gauss–Newton method, the estimate can be found iteratively by the maximum a posteriori approach (Rodgers, 2004) asXk+1=Xk+KkTSY−1Kk+Sa−1−1KkTSY−1Y*−Y(Xk)+Sa−1Xa−Xk,where Xk is a state vector at the kth iteration, Xa is an a priori state vector, SY is the covariance matrix of measurements Y*, Sa is a covariance matrix of a priori data Xa,

DOAS-based retrievals

To demonstrate potential errors due to atmospheric light-scattering, we first considered the XCO2 retrievals according to a DOAS-based technique (assuming PPDF parameters α = ρ = 0). We used GOSAT observations for 9 days (three repeat satellite cycles) in April 2009 that were pre-selected by National Institute for Environmental Studies (NIES) operational data processing as clear-sky under certain quality criteria. This data set corresponds to the FTS SWIR L2 Data Product (V01.10), available with

Conclusions

We presented an application of a PPDF-based method to atmospheric CO2 retrievals from GOSAT over-ocean observations. NIES global atmospheric tracer transport model data were used for the tentative estimates of the retrieval errors. SWIR radiance spectra generated from TANSO-FTS over-sea measurements were shown to be strongly affected by optical path modification due to atmospheric light-scattering. Neglecting these effects led to negative bias and large scatter of retrieved XCO2. Even for ~ 5%

Acknowledgements

GOSAT is a joint project promoted by the Japan Aerospace Exploration Agency (JAXA), the Ministry of the Environment (MOE), and the National Institute for Environmental Studies (NIES), Japan. We thank S. Maksyutov and D. Belikov for providing XCO2 modelled data.

References (23)

  • I. Aben et al.

    Uncertainties in the space-based measurements of CO2 columns due to scattering in the Earth's atmosphere

    Journal of Quantitative Spectroscopy and Radiative Transfer

    (2007)
  • D. Crisp

    The orbiting carbon observatory (OCO) mission

    Advances in Space Research

    (2004)
  • D.F. Baker et al.

    Carbon source/sink information provided by column CO2 measurements from the orbiting carbon observatory

    Atmospheric Chemistry and Physics

    (2010)
  • D. Belikov et al.

    Mass-conserving tracer transport modelling on a reduced latitude–longitude grid with NIES-TM

    Geoscientific Model Development

    (2011)
  • A. Bril et al.

    Parameterization of aerosol and cirrus cloud effects on reflected sunlight spectra measured from space: Application of the equivalence theorem

    Applied Optics

    (2007)
  • A. Butz et al.

    Retrievals of atmospheric CO2 from simulated space-borne measurements of backscattered near-infrared sunlight: Accounting for aerosol effects

    Applied Optics

    (2009)
  • F. Chevallier et al.

    Contribution of the orbiting carbon observatory to the estimation of CO2 sources and sinks: Theoretical study in a variational data assimilation framework

    Journal of Geophysical Research

    (2007)
  • B.J. Connor et al.

    Orbiting carbon observatory: Inverse method and prospective error analysis

    Journal of Geophysical Research

    (2008)
  • E. Dufour et al.

    Spaceborne estimate of atmospheric CO2 column by use of the differential absorption method: Error analysis

    Applied Optics

    (2003)
  • S. Houweling et al.

    Inverse modeling of CO2 sources and sinks using satellite data: A synthetic inter-comparison of measurement techniques and their performance as a function of space and time

    Atmospheric Chemistry and Physics

    (2004)
  • IPCC

    Climate change 2007: The physical science basis

    • View full text
    Copyright © 2011 Elsevier Inc. All rights reserved.