Investigation of the uncertainties of simulated optical properties of brown carbon in two Asian sites using a modified bulk aerosol optical scheme of the Community Atmospheric Model version 5.3 (CAM5.3)

Recent studies have suggested that brown carbon (BrC), an absorbing component in organic aerosol (OA), has strong absorption in the near-ultraviolet wavelengths, and contributes to regional and global radiative forcing. However, the inclusion of BrC in global climate models leads to significant uncertainties in estimated radiative forcing, mainly attributed to uncertain BrC properties and relevant BrC parameters assigned in the model. In this study, we modified the bulk aerosol optical scheme (BAOS) in the Community Atmospheric Model version 5.3 (CAM5.3) by including BrC absorption and evaluated the performance of the modified BAOS by comparing the simulated aerosol absorption with observed data in two Asian cities, Kanpur, India and Nanjing, China. The simulated total aerosol absorption (B_abs) and absorption Angstrom exponent (AAE) in modified BAOS show a decent closure to two-year surface observational data obtained on sites. The mean relative errors are around 30% in Kanpur and even below 20% in Nanjing. Our results show that the inclusion of BrC remedies the underestimated total aerosol absorption by 13% and 11% on average at Kanpur and Nanjing, respectively, exhibiting a better agreement with ground-based observations of aerosol absorption at both sites. We also conducted a series of sensitivity experiments to quantify the uncertainties caused by varying parameters related to BrC. The model simulations suggest that the imaginary refractive index of BrC and the mixing state of fine-mode particles are the two most important factors contributing to the uncertainties in BrC optical properties calculated in BAOS at the two Asian sites.近期研究表明，有机气溶胶（OA）中的吸光组分棕碳（BrC）在近紫外波段具有显著吸收特性，进而对区域及全球辐射强迫产生重要贡献。然而，在全球气候模式中纳入棕碳参数会导致辐射强迫估算结果出现显著不确定性，这一问题主要源于模式中棕碳的属性及相关赋值参数存在不确定性。本研究对社区大气模式版本5.3（CAM5.3）中的整体气溶胶光学方案（BAOS）进行改进，加入棕碳吸收效应，并通过对比印度坎普尔、中国南京两座亚洲城市的观测数据与模拟气溶胶吸光结果，评估了改进后BAOS的模拟性能。改进方案模拟得到的总气溶胶吸光度（B_abs）与吸收埃斯特朗指数（AAE），与站点获取的两年地表观测数据吻合度较好。其中坎普尔站的平均相对误差约为30%，南京站的平均相对误差甚至低于20%。研究结果显示，纳入棕碳参数后，坎普尔与南京站的总气溶胶吸光度平均低估问题分别得到13%与11%的修正，两地气溶胶吸光度的地面观测结果与模拟结果的一致性均得到显著提升。本研究还开展了一系列敏感性试验，以量化棕碳相关参数变化带来的模拟不确定性。模式模拟结果表明，棕碳的虚部折射率与细模态颗粒物的混合状态，是影响两座亚洲城市BAOS中棕碳光学特性计算不确定性的两大关键因素。