a radiative transfer module for calculating photolysis rates and solar heating in climate models: solar-j v7.5
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2017
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Abstract
Solar-J is a comprehensive radiative transfer model for
the solar spectrum that addresses the needs of both solar heating and
photochemistry in Earth system models. Solar-J is a spectral extension of
Cloud-J, a standard in many chemical models that calculates photolysis rates
in the 0.18–0.8 µm region. The Cloud-J core consists of an eight-stream
scattering, plane-parallel radiative transfer solver with corrections for
sphericity. Cloud-J uses cloud quadrature to accurately average over
correlated cloud layers. It uses the scattering phase function of aerosols
and clouds expanded to eighth order and thus avoids isotropic-equivalent
approximations prevalent in most solar heating codes. The spectral extension
from 0.8 to 12 µm enables calculation of both scattered and absorbed
sunlight and thus aerosol direct radiative effects and heating rates
throughout the Earth's atmosphere.
The Solar-J extension adopts the correlated-k gas absorption bins, primarily water vapor, from the shortwave Rapid Radiative Transfer Model for general circulation model (GCM) applications (RRTMG-SW). Solar-J successfully matches RRTMG-SW's tropospheric heating profile in a clear-sky, aerosol-free, tropical atmosphere. We compare both codes in cloudy atmospheres with a liquid-water stratus cloud and an ice-crystal cirrus cloud. For the stratus cloud, both models use the same physical properties, and we find a systematic low bias of about 3 % in planetary albedo across all solar zenith angles caused by RRTMG-SW's two-stream scattering. Discrepancies with the cirrus cloud using any of RRTMG-SW's three different parameterizations are as large as about 20–40 % depending on the solar zenith angles and occur throughout the atmosphere.
Effectively, Solar-J has combined the best components of RRTMG-SW and Cloud-J to build a high-fidelity module for the scattering and absorption of sunlight in the Earth's atmosphere, for which the three major components – wavelength integration, scattering, and averaging over cloud fields – all have comparably small errors. More accurate solutions with Solar-J come with increased computational costs, about 5 times that of RRTMG-SW for a single atmosphere. There are options for reduced costs or computational acceleration that would bring costs down while maintaining improved fidelity and balanced errors.
The Solar-J extension adopts the correlated-k gas absorption bins, primarily water vapor, from the shortwave Rapid Radiative Transfer Model for general circulation model (GCM) applications (RRTMG-SW). Solar-J successfully matches RRTMG-SW's tropospheric heating profile in a clear-sky, aerosol-free, tropical atmosphere. We compare both codes in cloudy atmospheres with a liquid-water stratus cloud and an ice-crystal cirrus cloud. For the stratus cloud, both models use the same physical properties, and we find a systematic low bias of about 3 % in planetary albedo across all solar zenith angles caused by RRTMG-SW's two-stream scattering. Discrepancies with the cirrus cloud using any of RRTMG-SW's three different parameterizations are as large as about 20–40 % depending on the solar zenith angles and occur throughout the atmosphere.
Effectively, Solar-J has combined the best components of RRTMG-SW and Cloud-J to build a high-fidelity module for the scattering and absorption of sunlight in the Earth's atmosphere, for which the three major components – wavelength integration, scattering, and averaging over cloud fields – all have comparably small errors. More accurate solutions with Solar-J come with increased computational costs, about 5 times that of RRTMG-SW for a single atmosphere. There are options for reduced costs or computational acceleration that would bring costs down while maintaining improved fidelity and balanced errors.
| Reference Key |
hsu2017geoscientifica
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|---|---|
| Authors | ;J. Hsu;M. J. Prather;P. Cameron-Smith;A. Veidenbaum;A. Nicolau |
| Journal | international journal of quantum chemistry |
| Year | 2017 |
| DOI |
10.5194/gmd-10-2525-2017
|
| URL | |
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