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首页> 外文期刊>SOLA: Scientific Online Letters on the Atmosphere >Improved Dust Forecast by Assimilating MODIS IR-Based Nighttime AOT in the ADAM2 Model
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Improved Dust Forecast by Assimilating MODIS IR-Based Nighttime AOT in the ADAM2 Model

机译：通过在ADAM2模型中吸收基于MODIS IR的夜间AOT改进了粉尘预报

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摘要

A data assimilation (DA) system employing day- and nighttime aerosol optical thickness (AOT) was developed for the Asian Dust Aerosol Model 2 (ADAM2), using the optimal interpolation (OI) method. The DA system assimilated nighttime AOT for dust retrieved from MODIS infrared (IR) measurements with an artificial neural network (ANN) approach. An Asian dust case that occurred during 14-18 March 2009 was simulated using ADAM2. To examine the impact of the inclusion of nighttime AOT on forecasts of the data assimilation system, experiments were performed with different assimilation cycles (i.e., DA1: 24-hour cycle with daytime MODIS AOT only, DA2: 12-hour cycle with additional nighttime AOT). A control simulation was also performed without data assimilation (CTL). Forecasts were assessed using MODIS-derived AOT distributions as well as ground-based skyradiometer, PM10, and lidar observations. The model-estimated vertical distribution of the dust extinction coefficient was also compared with lidar measurements. Both experiments (DA1, DA2) were found to have improved forecasting, but DA2 outperformed DA1. Results suggest that the ANN-based nighttime AOT contributes more positively to the forecasting through better temporal coverage for data assimilation.
机译：使用最佳插值（OI）方法，为亚洲粉尘气溶胶模型2（ADAM2）开发了采用昼夜气溶胶光学厚度（AOT）的数据同化（DA）系统。 DA系统使用人工神经网络（ANN）方法将夜间AOT吸收了从MODIS红外（IR）测量中获取的粉尘。使用ADAM2模拟了2009年3月14日至18日发生的亚洲尘埃事件。为了检查包含夜间AOT对数据同化系统的预测的影响，使用不同的同化周期（即DA1：仅使用白天MODIS AOT的24小时周期，DA2：具有附加夜间AOT的12小时周期）进行了实验）。还进行了没有数据同化（CTL）的控制仿真。预测是使用MODIS得出的AOT分布以及地面辐射计，PM10和激光雷达观测进行评估的。模型估计的消光系数垂直分布也与激光雷达测量结果进行了比较。发现两个实验（DA1，DA2）的预测均得到改善，但DA2的表现优于DA1。结果表明，基于ANN的夜间AOT通过更好地覆盖数据同化的时间覆盖范围，对预测做出了更积极的贡献。

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