Abstract

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.

Highlights

  • A major challenge in simulating the Earth’s climate is the tracking of solar energy, its absorption, and scattering within and reflection from the Earth system in the presence of heterogeneously distributed clouds and aerosols

  • In a chemistry–climate model, Solar-J supplies the needs of solar heating of the atmosphere and surface, photolysis rates, and photosynthetic activity

  • Climate models are increasingly including short-lived gases and aerosols as radiative forcing components, and the accurate simulation of these under different climates requires some level of interactive chemistry and photolysis rates

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Summary

Introduction

A major challenge in simulating the Earth’s climate is the tracking of solar energy, its absorption, and scattering within and reflection from the Earth system in the presence of heterogeneously distributed clouds and aerosols. We present here Solar-J version 7.5, a radiative transfer model based on the computationally optimized photolysis code, Cloud-J (Prather, 2015). As finer grid resolutions and massively parallel computing are being pursued to enable more realistic atmospheric interactions with the land, ocean, and biosphere in climate modeling, the radiative transfer codes implemented in most of the global models remain in their simplest possible analytical form of two-stream scattering. With this approximation, all upward and downward scattering occurs at a single angle, and the scattering must be treated as isotropic, i.e., independent of sun angle.

Solar-J spectral configuration
Clouds and aerosols
Clear sky
Low-level marine stratus cloud
Tropical cirrus clouds
65.7 W m-2 100 50 0
Solar-J versus RRMTG-SW
Computer science options
Other parameterizations for wavelength bins
Conclusions
Full Text
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