基于SMARTS模型的地面气溶胶光学深度测量Perez-Du Mortier校准算法的发展与验证

J. Dayou, Jackson Hian Wui Chang, Rubena Yusoff, Ag Sufiyan Abd Hamid, A. S. A. Hamid, F. Sulaiman, J. Sentian
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引用次数: 0

摘要

气溶胶是悬浮在空气中的小颗粒,具有广泛的时空分布。气溶胶在总柱状大气中的浓度通常用气溶胶光学深度(AOD)来测量。在长期监测站中,由于缺乏频繁的校准,准确的AOD检索往往很困难。为了克服这一问题,提出了一种结合晴空探测模型和统计滤波的近海平面Langley定标算法。它试图为兰利校准的目的产生一个仅由均匀和稳定的大气条件组成的数据集。本文采用基于辐射度的验证方法,进一步考察了该算法在不同地点、不同天、不同时间下的可行性和一致性。采用基于n DNI值的SMARTS模型对算法进行了验证。整体结果证实了所提出的校正算法在不同地点和天气条件下的测量是可行和一致的。
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Development of Perez-Du Mortier Calibration Algorithm for Ground-Based Aerosol Optical Depth Measurement with Validation using SMARTS Model
Aerosols are small particles suspended in air that have wide varying spatial and temporal distributions. The concentration of aerosol in total columnar atmosphere is normally measured using aerosol optical depth (AOD). In long-term monitoring stations, accurate AOD retrieval is often difficult due to the lack of frequent calibration. To overcome this problem, a near-sea-level Langley calibration algorithm is developed using the combination of clear-sky detection model and statistical filter. It attempts to produce a dataset that consists of only homogenous and stable atmospheric condition for the Langley calibration purposes. In this paper, a radiance-based validation method is performed to further investigate the feasibility and consistency of the proposed algorithm at different location, day, and time. The algorithm is validated using SMARTS model based n DNI value. The overall results confirmed that the proposed calibration algorithm feasible and consistent for measurements taken at different sites and weather conditions.
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