Andrey Bril

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

An original methodology to account for aerosol and cirrus cloud contributions to reflected sunlight is described. This method can be applied to the problem of retrieving greenhouse gases from satellite-observed data and is based on the equivalence theorem with further parameterization of the photon path-length probability density function (PPDF). Monte Carlo simulation was used to validate this parameterization for a vertically nonhomogeneous atmosphere including an aerosol layer and cirrus clouds. Initial approximation suggests that the PPDF depends on four parameters that can be interpreted as the effective cloud height, cloud relative reflectance, and two additional factors to account for photon path-length distribution under the cloud. We demonstrate that these parameters can be efficiently retrieved from the nadir radiance measured in the oxygen A-band and from the H(2)O-saturated area of the CO(2) 2.0 microm spectral band.

Influence of differences in current GOSAT XCO2 retrievals on surface flux estimation

We investigated differences in the five currently-available datasets of column-integrated CO2 concentrations (XCO2) retrieved from spectral soundings collected by Greenhouse gases Observing SATellite (GOSAT) and assessed their impact on regional CO2 flux estimates. We did so by estimating the fluxes from each of the five XCO2 datasets combined with surface-based CO2 data, using a single inversion system. The five XCO2 datasets are available in raw and bias-corrected versions, and we found that the bias corrections diminish the range of the five coincident values by ~30% on average. The departures of the five individual inversion results (annual-mean regional fluxes based on XCO2-surface combined data) from the surface-data-only results were close to one another in some terrestrial regions where spatial coverage by each XCO2 dataset was similar. The mean of the five annual global land uptakes was 1.7 ± 0.3 GtC yr−1, and they were all smaller than the value estimated from the surface-based data alone.

An improved photon path length probability density function–based radiative transfer model for space‐based observation of greenhouse gases

[1] We present an improved model to describe the photon path length probability density function (PPDF) that effectively accounts for both aerosol and thin cloud effects for rapid retrieval of greenhouse gas data from space-based high spectral resolution measurements. The reasonably simple PPDF and effective transmittance parameterization permit vertical inhomogeneity of gas absorption and three plane-parallel arbitrarily located layers to account for light-scattering effects due to aerosol and clouds. The basic assumption to construct the PPDF model refers mainly to the presentation of PPDF in terms of weakly correlated aerosol and cloud path length components. The model was validated using Monte Carlo simulations of photon trajectories and tested for a representative set of atmospheric conditions in which both aerosol and clouds modified the path length significantly. This study also focused on the connection of PPDF parameters to atmospheric optical characteristics commonly utilized in the solution of radiative transfer equations. These characteristics were converted into PPDF parameters by PPDF retrieval from a very limited spectral range of simulated radiance including at least one gas absorption line. The results demonstrate that this method can be used effectively for rapid radiative transfer spectral calculations over a rather wide spectral range of radiance at given atmospheric optical characteristics. Another important application of such conversion is to account for a priori knowledge of atmospheric optical characteristics when retrieving amounts of gases within PPDF-based or other methods, such as full physics algorithms that utilize the solutions of radiative transfer equations.

Retrieval of atmospheric methane from high spectral resolution satellite measurements: a correction for cirrus cloud effects

We assessed the accuracy of methane (CH(4)) retrievals from synthetic radiance spectra particular to Greenhouse Gases Observing Satellite observations. We focused on estimating the CH(4) vertical column amount from an atmosphere that includes thin cirrus clouds, taking into account uncertain meteorological conditions. A photon path-length probability density function (PPDF)-based method was adapted to correct for atmospheric scattering effects in CH(4) retrievals. This method was shown to provide similar retrieval accuracy as compared to a carbon dioxide (CO(2))-proxy-based correction approach. It infers some advantages of PPDF-based method for methane retrievals under high variability of CO(2) abundance.

Methodology to retrieve atmospheric aerosol parameters by combining ground-based measurements of multiwavelength lidar and sun sky-scanning radiometer

This paper presents the methodology to process data of combined experiments using a Sun/sky scanning radiometer and a multi-frequency aerosol lidar. An algorithm is proposed to retrieve the optical properties of altitude-inhomogeneous aerosol layer reflecting both the vertical changes of atmospheric aerosol detected by lidars and the integral aerosol properties measured by ground-based Sun/sky radiometers.

Simultaneous retrieval of atmospheric CO2 and light path modification from space-based spectroscopic observations of greenhouse gases: methodology and application to GOSAT measurements over TCCON sites

This paper presents an improved photon path length probability density function method that permits simultaneous retrievals of column-average greenhouse gas mole fractions and light path modifications through the atmosphere when processing high-resolution radiance spectra acquired from space. We primarily describe the methodology and retrieval setup and then apply them to the processing of spectra measured by the Greenhouse gases Observing SATellite (GOSAT). We have demonstrated substantial improvements of the data processing with simultaneous carbon dioxide and light path retrievals and reasonable agreement of the satellite-based retrievals against ground-based Fourier transform spectrometer measurements provided by the Total Carbon Column Observing Network (TCCON).

Retrievals of atmospheric CO2, CH4 and optical path modifications from the GOSAT observations

We present satellite-based data of the column-averaged dry air mole fraction of atmospheric carbon dioxide (XCO2) and methane (XCH4), which were derived from the radiance spectra measured by Greenhouse gases Observing SATellite (GOSAT). We have applied new version of the Photon path-length Probability Density Function (PPDF)-based algorithm to estimate XCO2 and PPDF parameters. These parameters serve to allow for optical path modification due to atmospheric light scattering and they are retrieved simultaneously with CO2 concentration using radiance spectra from all available GOSAT short wave infrared (SWIR) bands (oxygen A-band, 1.6-μm, and 2.0-μm CO2 absorption bands). For the methane abundance, retrieved from 1.67-μm absorption band, we applied optical path correction based on PPDF parameters from 1.6-μm CO2 absorption band. Similarly to widely used CO2-proxy technique, this correction assumes identical light path modifications in 1.67-μm and 1.6-μm bands. This approach is believed to offer some advantages over the proxy technique since it does not use any prior assumptions on carbon dioxide concentrations. Both carbon dioxide and methane GOSAT retrievals were validated using ground-based Fourier Transform Spectrometer (FTS) measurements provided by the Total Carbon Column Observing Network (TCCON). For XCO2 retrievals we found subppm station-to-station bias (GOSAT versus TCCON); single-scan precision of mostly below 2 ppm (0.5%); and correlation coefficient for the Northern Hemisphere TCCON stations above 0.8. For XCH4 retrievals over TCCON sites we found single-scan precision below 1 % and correlation coefficient above 0.8.

Estimation of regional surface CO2 fluxes with GOSAT observations using two inverse modeling approaches

Inverse estimation of surface C02 fluxes is performed with atmospheric transport model using ground-based and GOSAT observations. The NIES-retrieved C02 column mixing (Xc02) and column averaging kernel are provided by GOSAT Level 2 product v. 2.0 and PPDF-DOAS method. Monthly mean C02 fluxes for 64 regions are estimated together with a global mean offset between GOSAT data and ground-based data. We used the fixed-lag Kalman filter to infer monthly fluxes for 42 sub-continental terrestrial regions and 22 oceanic basins. We estimate fluxes and compare results obtained by two inverse modeling approaches. In basic approach adopted in GOSAT Level4 product v. 2.01, we use aggregation of the GOSAT observations into monthly mean over 5x5 degree grids, fluxes are estimated independently for each region, and NIES atmospheric transport model is used for forward simulation. In the alternative method, the model-observation misfit is estimated for each observation separately and fluxes are spatially correlated using EOF analysis of the simulated flux variability similar to geostatistical approach, while transport simulation is enhanced by coupling with a Lagrangian transport model Flexpart. Both methods use using the same set of prior fluxes and region maps. Daily net ecosystem exchange (NEE) is predicted by the Vegetation Integrative Simulator for Trace gases (VISIT) optimized to match seasonal cycle of the atmospheric C02 . Monthly ocean-atmosphere C02 fluxes are produced with an ocean pC02 data assimilation system. Biomass burning fluxes were provided by the Global Fire Emissions Database (GFED); and monthly fossil fuel C02 emissions are estimated with ODIAC inventory. The results of analyzing one year of the GOSAT data suggest that when both GOSAT and ground-based data are used together, fluxes in tropical and other remote regions with lower associated uncertainties are obtained than in the analysis using only ground-based data. With version 2.0 of L2 Xc02 the fluxes appear reasonable for many regions and seasons, however there is a need for improving the L2 bias correction, data filtering and the inverse modeling method to reduce estimated flux anomalies visible in some areas. We also observe that application of spatial flux correlations with EOF based approach reduces flux anomalies.

OPTIMAL REGRESSIONS TO ESTIMATE AEROSOL PARAMETERS BY DATA OF TWO- AND THREE-WAVELENGTH LASER SOUNDING

A problem on introduction of additional a prior assumptions to construct a closed set of lidar equations at several wavelengths and on their solutions to estimate microphysical parameters of atmospheric aerosols by multi-frequency laser sounding data is discussed. Some regression relations between spectral values of aerosol backscatter and extinction coefficients in the visible and near-IR are used as the assumptions. The regressions are constructed by model considerations. The optical atmospheric aerosol model of the World Meterological Organization is taken as a basic one. The constructed regressions enable one to evaluate the solvability of, generally, ill-conditioned lidar equations and the errors in the solutions as well as to make some estimations with respect to the determination of aerosol microstructural parameters. This work has been directed towards the design of procedures and algorithms to process laser sounding data gathered routinely by lidar setups of the Institute of Physics, Belarus National Academy of Sciences, Minsk, Republic of Belarus within the frame of a number of International and National research and development programs.

Correction of atmospheric scattering effects in space-based observations of methane and carbon dioxide: model study for synthesized GOSAT spectra

This paper concerns development of a new retrieval algorithm for the processing of the Greenhouse gases Observing SATellite (GOSAT) data. GOSAT is scheduled to be launched in 2009 to monitor column amounts of CO2 and CH4. A nadir-looking Fourier-Transform Spectrometer (FTS) of Short Wavelength Infrared (SWIR, 1.6 microns and 2 microns) and 0.76 microns oxygen A-band regions are mounted on GOSAT. We focus on the methane retrievals from 1.67 μm spectral band under conditions of strong optical path modification due to atmospheric scattering. First, the algorithm of spectral channel selection is proposed to reduce the effects of uncertainties in water vapor content and solar spectrum. Two techniques for the atmospheric scattering correction are compared: one uses CO2 as a proxy gas; the second is based on the simple parameterization of photon path-length probability density function (PPDF). The latter technique includes the following steps: estimation of PPDF parameters from radiance spectra in the O2 A-band and 2.0 -μm CO2 band, the necessary correction to use these estimated parameters in the 1.58-μm CO2 and 1.67-μm CH4 bands; and, finally, CO2 and methane retrievals. Both approaches were verified by numerical simulations using an independent radiative transfer approach to produce radiance spectra expected for the GOSAT sensor. The accuracy of the retrievals in the presence of aerosols and cirrus cloud is discussed.