The Global Atmosphere-aerosol Model ICON-A-HAM2.3-Initial Model Evaluation and Effects of Radiation Balance Tuning on Aerosol Optical Thickness.
The Global Atmosphere-aerosol Model ICON-A-HAM2.3-Initial Model Evaluation and Effects of Radiation Balance Tuning on Aerosol Optical Thickness.
复制标题
全球大气 - 卫生型模型图标-A-HAM2.3初始模型评估以及辐射平衡调谐对气溶胶光学厚度的影响。
DOI：
10.1029/2021ms002699
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发表时间：
2022-04
影响因子：
6.8
通讯作者：
Tegen, I
中科院分区：
文献类型：
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作者：
Salzmann, M.;Ferrachat, S.;Tully, C.;Munch, S.;Watson-Parris, D.;Neubauer, D.;Drian, C. Siegenthaler-Le;Rast, S.;Heinold, B.;Crueger, T.;Brokopf, R.;Muelmenstadt, J.;Quaas, J.;Wan, H.;Zhang, K.;Lohmann, U.;Stier, P.;Tegen, I
ECHAM6.3-HAM2.3 全球大气-气溶胶模型中的汉堡气溶胶模块版本 2.3 (HAM2.3) 与最近开发的二十面体非静水力 ICON-A (icon-aes-1.3.00) 全球大气模型耦合，产生新的 ICON-A-HAM2.3 大气-气溶胶模型。 ICON-A 和 ECHAM6.3 主机模型使用不同的动力核心、亚网格尺度湍流引起的垂直混合参数化以及辐射平衡调谐的参数设置。在这里，我们研究了模拟气溶胶光学厚度 (AOT) 的不同宿主模型的作用，并评估使用 HAM2.3 和 ECHAM6-HAM2.3 双矩云微物理方案对几个气象变量的影响。敏感性运行表明，由于宿主模型的湿对流参数化中参数的默认设置不同，ICON-A-HAM2.3 中纠正了副热带海洋上的正 AOT 偏差。与 ICON-A-HAM2.3 和 ECHAM6.3-HAM2.3 中的 MODIS 卫星仪器反演相比，全球平均 AOT 偏差较低，但 ICON-A-HAM2.3 中的偏差更大，因为亚马逊、非洲雨林和北印度洋上空的负 AOT 偏差不再由副热带海洋上的高偏差补偿。 ICON-A-HAM2.3 相对于 AERONET 站点的 AOT 观测结果显示出适度的改进。与标准 ICON-A 和标准 ECHAM6.3 相比，ICON-A-HAM2.3 中将多个气象变量的偏差组合成一个数字的多变量偏差分数更大。在热带地区，这种多变量偏差在 ICON-A-HAM2.3 和 ECHAM6.3-HAM2.3 中具有相似的程度。在温带地区，ICON-A-HAM2.3 的多变量偏差比 ECHAM6.3-HAM2.3 更小。引入了新的 ICON-A-汉堡气溶胶模块版本 2.3 (HAM2.3) 全球大气-气溶胶模型 模拟气溶胶光学厚度 (AOT) 对使用两种不同宿主模型但研究相同气溶胶模块的敏感性 由于宿主模型中的参数设置不同，在 ICON-A-HAM2.3 中纠正了亚热带海洋上的正 AOT 偏差
The Hamburg Aerosol Module version 2.3 (HAM2.3) from the ECHAM6.3‐HAM2.3 global atmosphere‐aerosol model is coupled to the recently developed icosahedral nonhydrostatic ICON‐A (icon‐aes‐1.3.00) global atmosphere model to yield the new ICON‐A‐HAM2.3 atmosphere‐aerosol model. The ICON‐A and ECHAM6.3 host models use different dynamical cores, parameterizations of vertical mixing due to sub‐grid scale turbulence, and parameter settings for radiation balance tuning. Here, we study the role of the different host models for simulated aerosol optical thickness (AOT) and evaluate impacts of using HAM2.3 and the ECHAM6‐HAM2.3 two‐moment cloud microphysics scheme on several meteorological variables. Sensitivity runs show that a positive AOT bias over the subtropical oceans is remedied in ICON‐A‐HAM2.3 because of a different default setting of a parameter in the moist convection parameterization of the host models. The global mean AOT is biased low compared to MODIS satellite instrument retrievals in ICON‐A‐HAM2.3 and ECHAM6.3‐HAM2.3, but the bias is larger in ICON‐A‐HAM2.3 because negative AOT biases over the Amazon, the African rain forest, and the northern Indian Ocean are no longer compensated by high biases over the sub‐tropical oceans. ICON‐A‐HAM2.3 shows a moderate improvement with respect to AOT observations at AERONET sites. A multivariable bias score combining biases of several meteorological variables into a single number is larger in ICON‐A‐HAM2.3 compared to standard ICON‐A and standard ECHAM6.3. In the tropics, this multivariable bias is of similar magnitude in ICON‐A‐HAM2.3 and in ECHAM6.3‐HAM2.3. In the extra‐tropics, a smaller multivariable bias is found for ICON‐A‐HAM2.3 than for ECHAM6.3‐HAM2.3. The new ICON‐A‐Hamburg Aerosol Module version 2.3 (HAM2.3) global atmosphere‐aerosol model is introduced The sensitivity of simulated aerosol optical thickness (AOT) to using two different host models but the same aerosol module is investigated A positive AOT bias over subtropical oceans is remedied in ICON‐A‐HAM2.3 because of a different parameter setting in the host model