GFIT3: A full physics retrieval algorithm for remote sensing of greenhouse gases in the presence of aerosols
Zhao-Cheng Zeng, UCLA, zcz@gps.caltech.edu (Presenter)
Vijay Natraj, JPL, vijay.natraj@jpl.nasa.gov
Feng Xu, The University of Oklahoma, fengxu@ou.edu
Sihe Chen, Caltech, sihechen@caltech.edu
Fang-Ying Gong, Caltech, fangying@caltech.edu
Thomas Pongetti, Caltech, thomas.j.pongetti@jpl.nasa.gov
Keeyoon Sung, JPL, keeyoon.sung@jpl.nasa.gov
Geoffrey Toon, JPL, geoffrey.c.toon@jpl.nasa.gov
Stanley Sander, JPL, stanley.p.sander@jpl.nasa.gov
Yuk Yung, Caltech, yly@gps.caltech.edu
Remote sensing of greenhouse gases (GHGs) in cities, where high GHG emissions are typically associated with heavy aerosol loading, is challenging due to retrieval uncertainties caused by imperfect characterization of scattering by aerosols. We investigate this problem by developing GFIT3, a full physics algorithm to retrieve GHGs (CO2 and CH4) by accounting for aerosol scattering effects in polluted urban atmospheres. In particular, the algorithm includes coarse (including sea salt and dust) and fine (including organic carbon, black carbon, and sulfate) mode aerosols in the radiative transfer model. The performance of GFIT3 is assessed using high spectral resolution observations over the Los Angeles (LA) megacity made by the California Laboratory for Atmospheric Remote Sensing–Fourier Transform Spectrometer (CLARS–FTS). CLARS–FTS is located on Mt. Wilson, California, at 1.67?km?a.s.l. overlooking the LA basin, and makes observations of reflected sunlight in the near-infrared spectral range. The first set of evaluations are performed by conducting retrieval experiments using synthetic spectra. We find that errors in the retrievals of column-averaged dry-air mole fractions of CO2 (XCO2) and CH4 (XCH4) due to uncertainties in the aerosol optical properties and atmospheric a priori profiles are less than 1?% on average. This indicates that atmospheric scattering does not induce a large bias in the retrievals when the aerosols are properly characterized. The methodology is then further evaluated by comparing GHG retrievals using GFIT3 with those obtained from the CLARS-GFIT algorithm (used for currently operational CLARS retrievals) that does not account for aerosol scattering. We find a significant correlation between retrieval bias and aerosol optical depth (AOD). Comparison of GFIT3 AOD retrievals with collocated ground-based observations from AERONET shows that the developed algorithm produces very accurate results, with biases in AOD estimates of about 0.02. Finally, we assess the uncertainty in the widely used tracer-tracer ratio method to obtain CH4 emissions based on CO2 emissions and find that using the CH4?/?CO2 ratio effectively cancels out biases due to aerosol scattering.
Poster: Poster_Zeng__31_25.pdf
Presentation Type: Poster
Session: 2.5a Retrieval algorithms and methods for inter-instrument and product Cal/Val
Session Date: Tuesday (6/15) 12:00 PM