Aerosol scattering effects on water vapor retrievals over the Los Angeles Basin

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Abstract

In this study, we propose a novel approach to describe the scattering effects of atmospheric aerosols in a complex urban environment using water vapor (H2O) slant column measurements in the near infrared. This approach is demonstrated using measurements from the California Laboratory for Atmospheric Remote Sensing Fourier Transform Spectrometer on the top of Mt. Wilson, California, and a two-stream-exact single scattering (2S-ESS) radiative transfer (RT) model. From the spectral measurements, we retrieve H2O slant column density (SCD) using 15 different absorption bands between 4000 and 8000 cm-1. Due to the wavelength dependence of aerosol scattering, large variations in H2O SCD retrievals are observed as a function of wavelength. Moreover, the variations are found to be correlated with aerosol optical depths (AODs) measured at the AERONET-Caltech station. Simulation results from the RT model reproduce this correlation and show that the aerosol scattering effect is the primary contributor to the variations in the wavelength dependence of the H2O SCD retrievals. A significant linear correlation is also found between variations in H2O SCD retrievals from different bands and corresponding AOD data; this correlation is associated with the asymmetry parameter, which is a first-order measure of the aerosol scattering phase function. The evidence from both measurements and simulations suggests that wavelength-dependent aerosol scattering effects can be derived using H2O retrievals from multiple bands. This understanding of aerosol scattering effects on H2O retrievals suggests a promising way to quantify the effect of aerosol scattering on greenhouse gas retrievals and could potentially contribute towards reducing biases in greenhouse gas retrievals from space.

Figures

  • Figure 1. Schematic diagram of CLARS-FTS measurement geometries for western Pasadena and the AERONET site at Caltech. CLARS-FTS has two modes of operation, including Los Angeles Basin Survey mode (LABS; in solid red) and the Spectralon Viewing Observation mode (SVO; in blue). An example of light path change due to aerosol scattering along the path from the basin to the mountain top is illustrated (in dotted red). Also shown is the light path of AERONET-Caltech (in green).
  • Figure 2. The normalized radiances, obtained by dividing the spectra by the maximum radiance, of the 15 H2O absorption bands selected for retrieving H2O SCDs from CLARS-FTS measurements. These radiances are spectral fits using the CLARS-FTS measurements in western Pasadena on 1 March 2013 with a solar zenith angle (SZA) of 41.45◦. Solid black curves are fits to the spectra, including contributions of all trace gases and solar lines, from spectral measurements by the FTS, and dashed blue curves are the estimated contribution of H2O absorption to the spectral fits. Contributions of other species in these spectral regions are not shown. Central wavelength and information content (IC) value of each band used for retrieving H2O content are also indicated.
  • Table 1. Central wavelengths and band widths of the 15 H2O absorption bands and the corresponding information contents for retrievals of only H2O SCD (IC_a) and for simultaneous retrievals of H2O SCD and AOD (IC_b).
  • Figure 3. Daily Variations of CLARS H2O SCD retrievals for the western Pasadena target and AOD measurements from AERONET-Caltech station on 1 March 2013 (left column panels) and 28 September 2013 (right column panels). H2O SCD retrievals from SVO mode are shown in (a), and from LABS mode for western Pasadena are shown in (b). The corresponding standard deviations of H2O SCD retrievals, a measure of the degree of variation in the retrievals, are shown in (c) and the AOD measurements from AERONET-Caltech are shown in (d).
  • Figure 4. Correlation between daily averaged standard deviation of H2O SCDs, a measure of retrieval differences, from 12:00 to 14:00 LT, and the corresponding averaged AOP, calculated by scaling AOD data (1020 nm) from AERONET based on CLARS geometry, for two time periods in 2013. (a) Winter and spring, including January to May, in which the coefficient of determination (R2) is 0.53 and [slope, intercept]= [0.08± 0.03, −0.09± 0.21] with 95 % confidence bounds from linear regression. No December data from AERONET are available in 2013. (b) Summer and autumn from June to November, in which R2 is 0.49 and [slope, intercept]= [0.04± 0.01, −0.03± 0.16]. In total, there are 68 days of daily mean data available in 2013, out of which 27 days are for winter–spring and 40 days are for summer–autumn.
  • Figure 5. Monthly-averaged climatological aerosol composition (as percentages of total optical depth averaged over the 15 H2O absorption bands) for the five composite MERRA aerosols (black carbon, organic carbon, sulfate, dust, and sea salt) in the daytime (13:00 LT).
  • Table 2. Aerosol single scattering properties, computed using the GOCART model∗, for the five types of aerosols (black carbon, organic carbon, sulfate, dust, and sea salt) used in the study. Single Scattering Albedo (SSA) and asymmetry parameter (g) are averaged values over the 15 H2O absorption bands.
  • Figure 6. (a) Case I: scaling factors for H2O SCDs retrieved from the simulated synthetic spectral radiance of the 15 chosen bands using the 2S-ESS RT model with AOD data from AERONET-Caltech on 1 March 2013. The scaling factors are mean-centered by subtracting the mean to clearly show the variations in the retrievals; (b) Case II: same as (a) except that the AOD is fixed at the clear-day level, in which the lowest AOD in 2013 is used for all hours across the day; (c) Case III: same as (a) except that the AOD is set to be zero for all hours across the day; (d) Comparison between CLARS measurements and results from the three RT model experiments in (a)–(c) in terms of standard deviations, a measure of variations in H2O SCDs retrieved from the 15 chosen bands. The standard deviations are normalized to be between 0 and 1 for both measurements and simulations. The half-hourly mean of the CLARS data is calculated to obtain the maximum and minimum for the normalization.

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Zeng, Z. C., Zhang, Q., Natraj, V., Margolis, J. S., Shia, R. L., Newman, S., … Yung, Y. L. (2017). Aerosol scattering effects on water vapor retrievals over the Los Angeles Basin. Atmospheric Chemistry and Physics, 17(4), 2495–2508. https://doi.org/10.5194/acp-17-2495-2017

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