An Affordable, Flexible, and More Accurate Method for Computing Radiative Transfer

Pincus, R., NOAA - CIRES Climate Diagnostics Center

Radiation Processes

Radiative Processes

Pincus, R., H.W. Barker, J.J. Morcrette, A fast, flexible approximate technique for computing radiative transfer in inhomogenous cloud fields, J. Geophys. Res., Vol. 108, No. D13, 4376, doi:10.1029/2002JD003322, 2003

Key Contributors: H.W. Barker, J.J. Morcrette

Cloud radiative feedback—the amount of solar radiation that is absorbed by clouds before it reaches the earth and bounces back into the atmosphere—is the single most important effect determining the magnitude of possible climate responses to human activity. However, cloud properties are highly complex and variable, making it difficult to create accurate model treatments of their effects. A new radiation transfer scheme, developed by a team of international researchers sponsored by DOE's Atmospheric Radiation Measurement Program (ARM), provides radiative fluxes guaranteed to be unbiased with respect to the benchmark model based on Independent Column Approximation (ICA). The technique works equally well no matter how cloud structure is specified.

Calculating radiative transfer is time consuming because fluxes and heating rates are broadband quantities that must be integrated over many spectral intervals. The ICA does an accurate job of determining domain-average fluxes in variable clouds, but is far too computationally expensive when the number of possible cloud configurations is even moderately large. The new method incorporates a Monte Carlo integration of the ICA (i.e., MCICA) to achieve a computationally efficient technique for computing radiative transfer. The method includes random sampling errors but those errors add up to a zero mean bias.

In addition, traditional radiative transfer schemes intimately couple assumptions about cloud structure with methods for computing radiative transfer. Because cloud structure and radiative transfer are conceptually and mathematically distinct, however, this is an unnatural marriage which makes the scheme inflexible, difficult to extend, and potentially susceptible to biases. The McICA completely decouples the processes of determining cloud structure within a domain for the calculation of radiative transfer. This has two advantages: the radiation code can become both simpler and more flexible, while assumptions about cloud structure can be applied uniformly to flux and heating rate calculations.

By bringing consistency and demonstrable accuracy to the treatment of cloud structure in radiation and precipitation calculations, research supported by the ARM program is helping to reduce uncertainty in global climate models. Plans are to incorporate the McICA into some high-profile weather and climate models in both the United States and the United Kingdom (Geophysical Fluid Dynamics Laboratory – NOAA/Princeton, National Center for Atmospheric Research, and Laboratory of Dynamic Meteorology – France) within the next year or two.