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Adjoint sensitivity of global cloud droplet number to aerosol and dynamical parameters

机译:全局云滴数量对气溶胶和动力学参数的伴随敏感性

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We present the development of the adjoint of a comprehensive cloud droplet formation parameterization for use in aerosol-cloud-climate interaction studies. The adjoint efficiently and accurately calculates the sensitivity of cloud droplet number concentration (CDNC) to all parameterization inputs (e.g., updraft velocity, water uptake coefficient, aerosol number and hygroscopicity) with a single execution. The adjoint is then integrated within three dimensional (3-D) aerosol modeling frameworks to quantify the sensitivity of CDNC formation globally to each parameter. Sensitivities are computed for year-long executions of the NASA Global Modeling Initiative (GMI) Chemical Transport Model (CTM), using wind fields computed with the Goddard Institute for Space Studies (GISS) Global Circulation Model (GCM) II', and the GEOS-Chem CTM, driven by meteorological input from the Goddard Earth Observing System (GEOS) of the NASA Global Modeling and Assimilation Office (GMAO). We find that over polluted (pristine) areas, CDNC is more sensitive to updraft velocity and uptake coefficient (aerosol number and hygroscopicity). Over the oceans of the Northern Hemisphere, addition of anthropogenic or biomass burning aerosol is predicted to increase CDNC in contrast to coarse-mode sea salt which tends to decrease CDNC. Over the Southern Oceans, CDNC is most sensitive to sea salt, which is the main aerosol component of the region. Globally, CDNC is predicted to be less sensitive to changes in the hygroscopicity of the aerosols than in their concentration with the exception of dust where CDNC is very sensitive to particle hydrophilicity over arid areas. Regionally, the sensitivities differ considerably between the two frameworks and quantitatively reveal why the models differ considerably in their indirect forcing estimates.
机译:我们提出了用于气溶胶-云-气候相互作用研究的综合性云滴形成参数化伴随物的开发。伴随程序一次执行即可有效,准确地计算出云滴数浓度(CDNC)对所有参数化输入(例如,上升气流速度,吸水系数,气溶胶数和吸湿性)的敏感性。然后将伴随物集成到三维(3-D)气溶胶建模框架中,以全局量化CDNC形成对每个参数的敏感性。使用戈达德空间研究所(GISS)全球环流模型(GCM)II'和GEOS计算的风场,对NASA全球建模倡议(GMI)化学品运输模型(CTM)全年执行的敏感性进行计算。 -Chem CTM,由NASA全球建模和同化办公室(GMAO)的戈达德地球观测系统(GEOS)进行气象输入。我们发现在受污染的(原始)区域,CDNC对上升气流速度和吸收系数(气溶胶数和吸湿性)更加敏感。在北半球的海洋上,与致使CDNC降低的粗模式海盐相比,增加人为或生物质燃烧的气溶胶预计会增加CDNC。在南大洋,CDNC对海盐最为敏感,海盐是该地区的主要气溶胶成分。在全球范围内,预计CDNC对气溶胶吸湿性变化的敏感性低于其浓度,而灰尘除外,因为CDNC对干旱地区的颗粒亲水性非常敏感。从地区上看,这两个框架之间的敏感性差异很大,并从数量上揭示了为什么模型的间接强迫估计差异很大。

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