LBLRTM Description


(a) IASI spectrum in equivalent brightness temperature for JAVIEx campaign
(b) spectral variability and noise for the four IASI pixels being averaged
(c) observed - LBLRTM_v11.6 using the radiosonde as input into the calcuation
(d) observed - LBLRTM_v11.6 using the retrieved atmospheric profile, and
(e) the inital guess (a priori) and retrieved surface emissivity
(plot from [Shephard et al., 2009])

 
 

LBLRTM (Line-By-Line Radiative Transfer Model) is an accurate line-by-line model that is efficient and highly flexible.

Some important LBLRTM attributes are as follows:

  • the Voigt line shape is used at all atmospheric levels with an algorithm based on a linear combination of approximating functions;
  • it has been and continues to be extensively validated against atmospheric radiance spectra from the ultra-violet to the sub-millimeter;
  • it incorporates the self- and foreign-broadened water vapor continuum model, MT_CKD as well as continua for carbon dioxide, and for the collision induced bands of oxygen at 1600 cm-1 and nitrogen at 2350 cm-1.;
  • all parameters on the HITRAN line database are used including the pressure shift coefficient, the halfwidth temperature dependence and the coefficient for the self-broadening of water vapor;
  • a version of the Total Internal Partition Function (TIPS) program is used for the temperature dependence of the line intensities;
  • the effects of CO2 line coupling are treated as  first order with the coefficients for carbon dioxide generated from  Niro et al. (2005);
  • temperature dependent cross section data such as those available with the HITRAN database may be used to treat the absorption due to heavy molecules, e.g. the halocarbons;
  • an algorithm is implemented for the treatment of the variation of the Planck function within a vertically inhomogeneous layer as discussed in Clough et al. (1992);
  • algorithmic accuracy of LBLRTM is approximately 0.5% and the errors associated with the computational procedures are of the order of five times less than those associated with the line parameters so that the limiting error is that attributable to the line parameters and the line shape;
  • its computational efficiency mitigates the computational burden of the line-by-line flux and cooling rate calculation [Clough et al., 1992], for example linear algebraic operations are used extensively in the computationally intensive parts of LBLRTM so that vectorization is particularly effective with a typical vectorized acceleration of 20;
  • FFT instrument function with a choice of 9 apodization functions;
  • includes a realistic spectral sea surface emissivity model in the infrared [Masuda, et. al., 1988, Wu and Smith, 1997];
  • input atmospheric profiles in either altitude or pressure coordinates;
  • interfaces with other radiative transfer models (like RRTM), and as the forward model for inversion algorithms (e.g. Tropospheric Emission Spectrometer (TES) and Infrared Atmospheric Sounding Interferometer (IASI)).
  • These attributes provide spectral radiance calculations with accuracies consistent with the measurements against which they are validated and with computational times that greatly facilitate the application of the line-by-line approach to current radiative transfer applications.

  • LBLRTM inputs are obtained by running the LNFL program with a line file database for the spectral lines and cross sections for the heavy molecules.  LBLRTM solar inputs are obtained by running the solar source function program.


    LBLRTM heritage is from FASCODE [Clough et al., 1981, 1992] with its initial development at AER supported under the Department of Energy ARM Program.The Department of Energy ARM Program and NASA, through a subcontract with the Jet Propulsion Laboratory, support the continued advancements of LBLRTM .


     
    Clough, S. A., F. X. Kneizys, L. S. Rothman, and W. O. Gallery, Atmospheric spectral transmittance and radiance:FASCOD1B, Proc. of Soc. Photo. Opt. Instrum. Eng., 277, 152-166, 1981.
    Clough, S. A., F. X. Kneizys, and R. W. Davies, Line shape and the water vapor continuum, Atmos. Res., 23, 229-241, 1989.
    Clough, S. A., M. J. Iacono and J.-L. Moncet, Line-by-line calculation of atmospheric fluxes and cooling rates:Application to water vapor, J. Geophys. Res., 97, 15761-15785, 1992.
    Gamache, R. R, R. L. Hawkins, and L. S. Rothman, Total internal partition sums in the temperature range 70-3000K:atmospheric linear molecules, J. Mol. Spectrosc., 142, 205-219, 1990.
    Musuda, K., T. Takashima, and Y. Takayama. Emissivity of pure and sea waters for the model sea surface in the infrared window regions. Remote Sens. Environ., 24, 313-329, 1988.
    Niro F., K. Jucks, J.-M. Hartmann, Spectra calculations in central and wing regions of CO2 IR bands. IV : Software and database for the computation of atmospheric spectra, in J Quant Spectrosc Radiat Transfer. Vol. 95, 2005, pp. 469-481
    Rothman, L. S., R. R. Gamache, R. Tipping, C. P. Rinsland, M. A. H. Smith, D. C. Benner, V. Malathy Devi, J.-M. Flaud, C. Camy-Peyret, A. Goldman, S. T. Massie, L. R. Brown, and R. A. Toth, HITRAN molecular database:Edition '92, J. Quant. Spectrosc. Radiat. Transfer, 48, 469-508, 1992.
    Shephard M.W., S.A. Clough, V.H. Payne, W. L. Smith, S. Kireev, and K. E. Cady-Pereira, Performance of the line-by-line radiative transfer model (LBLRTM) for temperature and species retrievals: IASI case studies from JAIVEx, Atmos. Chem. Phys. Discuss., 9, 9313-9366, 2009.
    Wu, X. and L. Smith. Emissivity of rough sea surface for 8-13 mm: modeling and verification. Appl. Opt., 36, 2609-2619, 1997

     


    Atmospheric and Environmental Research Inc. (AER)