An optimal fitting approach to improve the GISS ModelE aerosol optical property parameterization using AERONET data
An optimal fitting approach to improve the GISS ModelE aerosol optical property parameterization using AERONET data
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DOI：
10.1029/2010jd013909
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发表时间：
2010-08-28
影响因子：
4.4
通讯作者：
Carlson, Barbara E.
中科院分区：
文献类型：
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作者：
Li, Jing;Liu, Li;Carlson, Barbara E.
我们使用 AERONET 地面测量的最佳拟合方法改进了更新的 2000 年纽约戈达德空间研究所 ModelE 气溶胶光学特性参数化。模型气溶胶光学特性（例如光学深度）是使用化学输运模型中的气溶胶质量密度场、米氏散射参数、假设外部混合的每种气溶胶种类的规定干燥尺寸以及吸湿性参数化来计算的。模型与 AERONET 测量的光学深度 (AOD) 和埃指数 (AE) 之间的比较表明，大气环流模型 (GCM) 气溶胶参数化具有较平坦的 AOD 光谱依赖性，因此偏差 AE 非常低，这表明模型中使用的气溶胶尺寸太大。 GCM AE 的季节变化也与 AERONET 数据不一致。基于这些结果，我们将 GCM 气溶胶尺寸确定为约束最差的参数，并开发了一种最佳拟合技术，通过最小化 6 个 AERONET 波长下 GCM 和 AERONET AOD 之间的总均方误差来调整 GCM 气溶胶干燥尺寸。调整气溶胶的干燥尺寸后，GCM AE 与 AERONET 数据之间的一致性得到改善。六个波长的拟合 AOD 与大多数生物质燃烧、灰尘和农村地区的 AERONET 数据非常匹配。其他气溶胶类型的结果也大大改善。最佳拟合尺寸的全球分布显示出区域统一的特征，这允许生成地理上不同尺寸的数据集。其他因素引起的模型不确定性也用不确定性参数来表示，主要归因于气溶胶质量浓度、米氏散射参数、相对湿度和AERONET测量的误差。每个误差源的相对贡献取决于相关的气溶胶类型。吸收光学深度和 AE 光谱依赖性之间的进一步比较提供了有关吸收气溶胶和 GCM 细粗模比的附加信息，这些信息将在未来的研究中解决。
We improve the updated 2000 Goddard Institute for Space Studies, New York, ModelE aerosol optical property parameterization using an optimal fitting approach with AERONET ground measurements. The model aerosol optical properties, such as optical depth, are calculated using the aerosol mass density field from a chemical transport model, Mie scattering parameters, a prescribed dry size for each aerosol species assuming external mixing, and a hygroscopicity parameterization. A comparison between the model-and AERONET-measured optical depth (AOD) and Angstrom exponent (AE) indicates that the general circulation model (GCM) aerosol parameterization has a flatter AOD spectral dependence, thus a very low biased AE, which suggests that the aerosol sizes used in the model are too large. The seasonal variation of GCM AE also disagrees with that of AERONET data. On the basis of these results, we identify GCM aerosol size as the most poorly constrained parameter and develop an optimal fitting technique to adjust the GCM aerosol dry size by minimizing the total mean square error between the GCM and AERONET AOD at the six AERONET wavelengths. After adjusting the aerosol's dry size, the agreement between the GCM AE with AERONET data is improved. The fitted AOD at the six wavelengths closely matches AERONET data over most biomass burning, dust, and rural regions. The results are also greatly improved for the other aerosol types. The global distribution of the optimally fitted sizes displays regionally uniform characteristics, which allows the generation of a geographically varying size data set. Model uncertainty caused by other factors is also represented by an uncertainty parameter, which is mainly attributed to errors from aerosol mass concentration, Mie scattering parameters, relative humidity, and AERONET measurements. The relative contribution of each of these errors sources depends on the relevant aerosol type. Further comparison between the absorption optical depth and AE spectral dependence provides additional information on absorbing aerosols and GCM fine-to-coarse mode ratio, which will be addressed in future research.