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Detection and attribution of aerosol–cloud interactions in large-domain large-eddy simulations with the ICOsahedral Non-hydrostatic model

机译:用ICOSAHEDRAL非静水压模型检测和归因于大域大涡模拟中的气雾云相互作用

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Clouds and aerosols contribute the largest uncertainty to current estimates and interpretations of the Earth’s changing energy budget. Here we use a new-generation large-domain large-eddy model, ICON-LEM (ICOsahedral Non-hydrostatic Large Eddy Model), to simulate the response of clouds to realistic anthropogenic perturbations in aerosols serving as cloud condensation nuclei (CCN). The novelty compared to previous studies is that (i)?the LEM is run in weather prediction mode and with fully interactive land surface over a large domain and (ii)?a large range of data from various sources are used for the detection and attribution. The aerosol perturbation was chosen as peak-aerosol conditions over Europe in 1985, with more than fivefold more sulfate than in 2013. Observational data from various satellite and ground-based remote sensing instruments are used, aiming at the detection and attribution of this response. The simulation was run for a selected day (2?May?2013) in which a large variety of cloud regimes was present over the selected domain of central Europe. It is first demonstrated that the aerosol fields used in the model are consistent with corresponding satellite aerosol optical depth retrievals for both 1985 (perturbed) and 2013 (reference) conditions. In comparison to retrievals from ground-based lidar for 2013, CCN profiles for the reference conditions were consistent with the observations, while the ones for the 1985 conditions were not. Similarly, the detection and attribution process was successful for droplet number concentrations: the ones simulated for the 2013 conditions were consistent with satellite as well as new ground-based lidar retrievals, while the ones for the 1985 conditions were outside the observational range. For other cloud quantities, including cloud fraction, liquid water path, cloud base altitude and cloud lifetime, the aerosol response was small compared to their natural variability. Also, large uncertainties in satellite and ground-based observations make the detection and attribution difficult for these quantities. An exception to this is the fact that at a large liquid water path value (LWP ?200gm?2), the control simulation matches the observations, while the perturbed one shows an LWP which is too large. The model simulations allowed for quantifying the radiative forcing due to aerosol–cloud interactions, as well as the adjustments to this forcing. The latter were small compared to the variability and showed overall a small positive radiative effect. The overall effective radiative forcing (ERF) due to aerosol–cloud interactions (ERFaci) in the simulation was dominated thus by the Twomey effect and yielded for this day, region and aerosol perturbation ?2.6Wm?2. Using general circulation models to scale this to a global-mean present-day vs. pre-industrial ERFaci yields a global ERFaci of ?0.8Wm?2.
机译:云和烟雾溶解为当前估计和地球变化能源预算的解释提供了最大的不确定性。在这里,我们使用新一代大型域大涡模型图标 - LEM(ICOSAHEDRAL非静液压大型涡流模型),以模拟云的响应,以适用于云凝结核(CCN)的气溶胶中的现实人体扰动。与以前的研究相比的新颖性是(i)?lem在天气预报模式中运行,并且在大域中的完全交互陆地表面和(ii)?来自各种来源的大量数据用于检测和归属。将气溶胶扰动选择为1985年欧洲的峰 - 气溶胶条件,比2013年更多的硫酸盐。使用各种卫星和地面遥感仪器的观测数据,针对这种反应的检测和归因。仿真是为选定的一天运行(2?2013),其中各种云制度存在于中欧所选领域。首先说明模型中使用的气溶胶场与1985(扰动)和2013(参考)条件的相应卫星气溶胶光学深度检索一致。与2013年地面LIDAR的检索相比,参考条件的CCN型材与观察结果一致,而1985年条件的条件则不一致。同样,检测和归因过程对于液滴数浓度成功:模拟2013条条件的内容与卫星以及新的基于地面的激光雷达检索一致,而1985年的条件是在观察范围之外的。对于其他云量,包括云分数,液体水路,云基海拔高度和云寿命,与其自然变异性相比,气溶胶反应较小。此外,卫星和地面观察中的大不确定性使得这些数量的检测和归因变得困难。这是一个例外的事实,即在大型液体水路值(LWP?200GM?2),控制仿真与观察结果相匹配,而扰动的仿真显示了一个太大的LWP。由于气溶胶云相互作用,因此允许量化辐射强制的模型模拟,以及对该强迫的调整。与变异性相比,后者较小,并显示出小的阳性辐射效果。因此,模拟中由于气溶胶云相互作用(ERFACI)引起的整体有效辐射强制(ERF)由Twomey效应主导,并屈服于该日,区域和气溶胶扰动?2.6WM?2。使用普通循环模型将其扩展到全球平均当天与前工业Erfaci产生了一个全球Erfaci?0.8WM?2。
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