粉尘模型对尘源掩蔽、喷砂效率、空气密度和土地利用的敏感性:模型改进的意义

IF 3.9 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES
Janak R. Joshi
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引用次数: 0

摘要

本研究比较了使用两种常用方法表示四个重要沙尘排放参数的沙尘暴模拟结果。与基于土地利用和植被覆盖的动态尘源掩模相比,仅基于土地利用的静态掩模除了产生虚假排放外,还将尘浓度和光学深度高估了 2 倍。结果证明,植被覆盖的季节性变化会显著影响粉尘排放。在喷砂效率方面,依赖于粘土的半经验表达式产生的粉尘是基于物理的表达式的 12 倍。使用模型预测与恒定空气密度进行的模拟仅相差 8%。然而,在全球尘源地区的年度模拟中,这种差异(经常被忽视)可能在 12% 到 22% 之间。在使用相同的尘源掩码的情况下,使用更新的土地利用数据与使用旧的土地利用数据进行的模拟结果相差两倍,这表明土地利用的变化对亚利桑那州中部的区域尘埃排放有重大影响。在四对模拟中,每对模拟之间的差异通常大于气象造成的不确定性。在使用动态尘源掩模、基于物理学的喷砂效率和最新土地利用数据时,模拟结果与观测结果更为吻合。鉴于沙尘对地表条件的高度敏感性,所讨论的结果对改进天气和气候模式中的沙尘循环以及解释模式间的相互比较具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dust model sensitivity to dust source mask, sandblasting efficiency, air density, and land use: Implications for model improvement

This study compares dust storm simulations using two commonly adopted methods for representing four important dust emission parameters. Compared with a dynamic dust source mask based on land use and vegetation cover, a static mask based solely on land use overestimates dust concentration and optical depth by a factor of 2, besides generating spurious emissions. The results reinforce that seasonal variations in vegetation cover can significantly affect dust emissions. For sandblasting efficiency, a clay-dependent semiempirical expression produces 12 times more dust than does a physics-based expression. Simulations using model-predicted versus constant air density differ by only 8%. However, this difference (often overlooked) could range between 12% and 22% for annual simulations over global dust source regions. Simulations with updated versus old land use data, using the same dust source mask, differ twofold, indicating the significant impact of land use change on regional dust emission in central Arizona. The difference between simulations within each of the four pairs is generally larger than the uncertainty due to meteorology. The simulations align better with observation when using the dynamic dust source mask, the physics-based sandblasting efficiency, and the up-to-date land use data. Given the high sensitivity of dust to surface conditions, the results discussed have implications for improving the dust cycle in weather and climate models and for interpreting model intercomparisons.

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来源期刊
Atmospheric Pollution Research
Atmospheric Pollution Research ENVIRONMENTAL SCIENCES-
CiteScore
8.30
自引率
6.70%
发文量
256
审稿时长
36 days
期刊介绍: Atmospheric Pollution Research (APR) is an international journal designed for the publication of articles on air pollution. Papers should present novel experimental results, theory and modeling of air pollution on local, regional, or global scales. Areas covered are research on inorganic, organic, and persistent organic air pollutants, air quality monitoring, air quality management, atmospheric dispersion and transport, air-surface (soil, water, and vegetation) exchange of pollutants, dry and wet deposition, indoor air quality, exposure assessment, health effects, satellite measurements, natural emissions, atmospheric chemistry, greenhouse gases, and effects on climate change.
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