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Multiple-scaling methods for Monte Carlo simulations of radiative transfer in cloudy atmosphere

机译:多云大气辐射传递的蒙特卡罗模拟的多尺度方法

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摘要

Two multiple-scaling methods for Monte Carlo simulations were derived from integral radiative transfer equation for calculating radiance in cloudy atmosphere accurately and rapidly. The first one is to truncate sharp forward peaks of phase functions for each order of scattering adaptively. The truncated functions for forward peaks are approximated as quadratic functions; only one prescribed parameter is used to set maximum truncation fraction for various phase functions. The second one is to increase extinction coefficients in optically thin regions for each order scattering adaptively, which could enhance the collision chance adaptively in the regions where samples are rare. Several one-dimensional and three-dimensional cloud fields were selected to validate the methods. The numerical results demonstrate that the bias errors were below 0.2% for almost all directions except for glory direction (less than 0.4%) and the higher numerical efficiency could be achieved when quadratic functions were used. The second method could decrease radiance noise to 0.60% for cumulus and accelerate convergence in optically thin regions. In general, the main advantage of the proposed methods is that we could modify the atmospheric optical quantities adaptively for each order of scattering and sample important contribution according to the specific atmospheric conditions.
机译:从积分辐射传递方程推导了两种用于蒙特卡洛模拟的多标度方法,可以准确,快速地计算出多云环境中的辐射率。第一个是针对每个散射阶次自适应地截断相位函数的尖锐正向峰。正向峰的截断函数近似为二次函数;仅使用一个规定的参数来设置各种相位函数的最大截断分数。第二个方法是针对每个阶次散射自适应地增加光学稀薄区域中的消光系数,这可以在样品稀少的区域中自适应地增加碰撞机会。选择了几个一维和三维云场来验证该方法。数值结果表明,除荣耀方向外,几乎所有方向的偏差误差均低于0.2%(小于0.4%),使用二次函数可以实现更高的数值效率。第二种方法可以将辐射噪声降低到0.60%(对于积云),并加速光学薄区域中的会聚。通常,所提出方法的主要优点是我们可以针对每个散射阶次自适应地修改大气光学量,并根据特定的大气条件采样重要的贡献。

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