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Rick Pernak edited this page Feb 1, 2021 · 6 revisions

RRTMG_LW is a radiative transfer model that utilizes the correlated-k approach to calculate longwave fluxes and heating rates efficiently and accurately for application to GCMs.

Clear sky comparison of the latest version of RRTMG_LW relative to LBLRTM.

Key Features

Key features of RRTMG_LW are:

  • Absorption coefficient data for the k-distributions are obtained directly from the line-by-line radiative transfer model, LBLRTM, which has been extensively validated against observations, principally at the ARM SGP site. Data are consistent with those used in RRTM_LW_v3.0.1, which is described on its wiki.
  • Fluxes and heating rates can be calculated over sixteen contiguous bands in the longwave (10-3250 cm-1, or 3.08-1000 microns). The individual band ranges (in wavenumbers, cm-1) are:
Band v1 v2
1 10 350
2 350 500
3 500 630
4 630 700
5 700 820
6 820 980
7 980 1080
8 1080 1180
9 1180 1390
10 1390 1480
11 1480 1800
12 1800 2080
13 2080 2250
14 2250 2380
15 2380 2600
16 2600 3250
  • When results are integrated over the full longwave spectrum, the 2600-3250 cm-1 band includes a small adjustment to add the contribution over the spectral interval from 3250 cm-1 to infinity.
  • Modeled molecular absorbers are water vapor, carbon dioxide, ozone, nitrous oxide, methane, oxygen, nitrogen and several halocarbons (CFC-11, CFC-12, CFC-22, and CCL4)
  • Uses reduced set of g-intervals (140) for integration over absorption in each band relative to full set of g-intervals used in RRTM_LW (256)
  • Includes McICA (Monte-Carlo Independant Column Approximation) capability to represent sub-grid cloud variability with random, maximum-random, maximum, exponential, and exponential-random options for cloud overlap; the exponential and exponential-random methods allow specification of the required decorrelation length as a constant or as a variable that varies as a function of latitude and day of the year; References: Barker et al. (2003); Pincus et al., JGR, (2003); Oreopoulos et al., ACP, (2012)
  • Performs radiative transfer for a single (diffusivity) angle (angle = 53° secant angle = 1.66) and improves accuracy in profiles with high water by varying the angle in some bands as a function of total column water
  • Coding has been reformatted to use many FORTRAN90 features
  • Model able to run either as a column model or as a callable subroutine
  • Fluxes calculated by RRTMG_LW agree with those computed by LBLRTM within 1.0 W m-2 at all levels, and the computed cooling rates generally agree to within 0.1 K day-1 in the troposphere and 0.3 K day-1 in the stratosphere
  • Water clouds:
    • The optical properties of water clouds are calculated for each spectral band from the Hu and Stamnes parameterization. The optical depth, single-scattering albedo, and asymmetry parameter are parameterized as a function of cloud equivalent radius and liquid water path.
    • Reference: Hu, Y. X., and K. Stamnes, An accurate parameterization of the radiative properties of water clouds suitable for use in climate models. J. Climate, Vol. 6, 728-742, 1993.
  • Ice clouds:
    • The optical properties of ice clouds are calculated for each spectral band from the Fu et al. ice particle parameterization.
    • Reference: Fu, Yang, and Sun, J. Climate, Vol 11, 1998, pp. 2223-2237, 1998.
  • Aerosols:
    • Aerosol absorption in the longwave can be included by providing the bulk aerosol optical depth at the mid-point of each spectral band.
  • Absorption coefficients and other initialization data can be optionally input through a netCDF data file. This feature was developed and provided by Patrick Hofmann and Robert Pincus of NOAA.
  • An optional feature is available to calculate the change in upward flux by layer as a function of surface temperature. This can be used to approximate adjustments in upward flux caused only by a change in surface temperature in a GCM at time intervals between full radiation calls. This is derived using the pre-calculated derivative of the Planck function with respect to temperature.

RRTMG_LW vs. RRTM_LW

Key differences between RRTMG_LW and RRTM_LW are:

  • RRTMG_LW uses reduced set of g-intervals (140) for integration over absorption in each band relative to full set of g-intervals used in RRTM_LW (256).
  • RRTMG_LW includes McICA (Monte-Carlo Independant Column Approximation) capability to represent sub-grid cloud variability with random, maximum-random, maximum, exponential, and exponential-random options for cloud overlap; References: Barker et al. (2003); Pincus et al., JGR, (2003); Oreopoulos et al., ACP, (2012); RRTM_LW does not have McICA, but it does include representations for random and maximum-random cloud overlap.
  • RRTMG_LW performs radiative transfer only for a single (diffusivity) angle (angle = 53° secant angle = 1.66) and varies this angle to improve accuracy in profiles with high water; RRTM_LW can use multiple angles for radiative transfer
  • RRTMG_LW coding has been reformatted to use many FORTRAN90 features.
  • RRTMG_LW includes aerosol absorption capability.
  • RRTMG_LW can be used as a callable subroutine and adapted for use within global or regional models.
  • RRTMG_LW can optionally read the required input data either from a netCDF file or from the original RRTM_LW source data statements.
  • RRTMG_LW can provide the change in upward flux with respect to surface temperature, dF/dT, by layer for total sky and clear sky.
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