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首页> 外文期刊>Atmosphere >On the Importance of Aerosol Composition for Estimating Incoming Solar Radiation: Focus on the Western African Stations of Dakar and Niamey during the Dry Season
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On the Importance of Aerosol Composition for Estimating Incoming Solar Radiation: Focus on the Western African Stations of Dakar and Niamey during the Dry Season

机译:关于估算进入的太阳辐射的气溶胶成分的重要性:集中在干旱季节的达喀尔和尼亚美的西非气象站

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The article investigates the impact of aerosol composition on the estimation of the downwelling surface shortwave flux (DSSF). This initiative forms part of the efforts to improve the DSSF distributed by the Land Surface Analysis Satellite Application Facility (LSA-SAF). This operational product assumes invariant aerosol properties under clear sky conditions, which can be inaccurate for some regions of the world. This is the case of West Africa, where aerosol activity is not only highly variable due to frequent dust storms but also rich because of the coexistence of different aerosol species. This study was carried out over the West African stations of Dakar and Niamey, which represent different aerosol scenarios. Several dates during the dry season of 2006 were selected and classified into four different day types according to aerosol activity: standard, clean, mixture and dusty days. The diurnal evolution of DSSF and its direct and diffuse components were estimated for the selected dates by the current LSA-SAF algorithm and two other approaches using aerosol measurements from the Aerosol Robotic Network (AERONET) as input. The first alternative approach took the diurnal evolution of the total aerosol optical depth (AOD) into account, assuming a default desert aerosol type. Experiments with this method showed a significant improvement in the estimated DSSF compared to the current LSA-SAF algorithm. For example, root mean square error (RMSE) improved from 170 W/m2 to 50 W/m2 for dusty days in Dakar and from 73 W/m2 to 21 W/m2 for mixture days in Niamey. This improvement resulted from the consideration of a time-varying AOD, which accounted for the rapidly changing aerosol load for these two day types. The second alternative approach tested included consideration of the diurnal variation of the aerosol load and composition. Again, this was done using AERONET data on the fine and coarse aerosol modes, which may be associated with different sized dust particles, sea salt, or soot from biomass burning (depending on the date). This enhanced consideration of the aerosol composition greatly improved the estimation of the diffuse component of the DSSF, further reducing the RMSE during mixture days from 50 W/m2 to less than 10 W/m2. This improvement mainly came from consideration of the right scattering properties of the aerosol particles, which may be significantly different for each aerosol type.
机译:本文研究了气溶胶成分对下流表面短波通量(DSSF)估计的影响。该计划是改进陆面分析卫星应用设施(LSA-SAF)分发的DSSF的努力的一部分。该操作产品在晴朗的天空条件下假设气溶胶特性不变,这在世界某些地区可能不准确。西非就是这种情况,那里的气溶胶活动不仅由于频繁的沙尘暴而变化很大,而且由于不同气溶胶种类的共存而变得很丰富。这项研究是在代表不同气溶胶情景的达喀尔和尼亚美的西非气象站上进行的。根据气溶胶活动,选择了2006年旱季中的几个日期并将其分为四种不同的日类型:标准日,清洁日,混合日和多尘天。利用当前的LSA-SAF算法和其他两种方法,使用来自气溶胶机器人网络(AERONET)的气溶胶测量值作为输入,估算了选定日期的DSSF及其直接和扩散成分的日变化。假设默认沙漠气溶胶类型,第一种替代方法考虑了总气溶胶光学深度(AOD)的日变化。与目前的LSA-SAF算法相比,使用此方法进行的实验表明,估计的DSSF有了显着改善。例如,达喀尔多尘天的均方根误差(RMSE)从170 W / m 2 提高到50 W / m 2 ,从73 W / m 2 到21 W / m 2 。这种改进是由于考虑了随时间变化的AOD而引起的,这是这两天两种类型的气溶胶负荷快速变化的原因。测试的第二种替代方法包括考虑气溶胶负荷和成分的日变化。再次,这是使用AERONET数据进行的精细和粗糙气溶胶模式完成的,这可能与不同大小的尘埃颗粒,海盐或生物质燃烧产生的烟尘有关(取决于日期)。对气溶胶成分的更多考虑大大改善了DSSF扩散成分的估计,进一步将混合天数的RMSE从50 W / m 2 降低到小于10 W / m 2 。该改进主要来自对气溶胶颗粒正确的散射特性的考虑,对于每种气溶胶类型,散射特性可能会显着不同。

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