The source of discrepancies in aerosol-cloud-precipitation interactions between GCM and A-Train retrievals
The source of discrepancies in aerosol-cloud-precipitation interactions between GCM and A-Train retrievals
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DOI：
10.5194/acp-16-15413-2016
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发表时间：
2016-12-13
影响因子：
6.3
通讯作者：
Takemura, Toshihiko
中科院分区：
文献类型：
--
作者：
Michibata, Takuro;Suzuki, Kentaroh;Takemura, Toshihiko
由于其非线性复杂性，气溶胶与云的相互作用是气候模式中最不确定的过程之一。一个关键的复杂性产生于云可能以两种相反的方式对受扰动的气溶胶作出反应，其特点是传统的“云寿命”假说和最近的“缓冲系统”假说。它们在气候模拟中的重要性仍然知之甚少。本文从大气环流模式（GCM）和A-Train遥感的角度，通过面向过程的模式评价，研究了暖云中液态水路径（LWP）对气溶胶扰动的响应。在模型结果和观测值之间的LWP响应中发现了系统差异。模型结果表明，随着气溶胶负荷的增加，LWP几乎在全球范围内均匀增加，而a - train的LWP响应符号因区域而异。除了微物理因素外，卫星观测到的低wp响应与气象和/或宏观物理因素密切相关。该模式没有重现云敏感性的这种变化（即LWP对受扰动气溶胶的敏感性），因为自转换过程的参数化只假设了云滴数增加对降雨形成的抑制，而没有考虑通过增强蒸发和降水作为LWP负响应机制的宏观物理方面。在降水微物理中也发现了模式偏差，这表明即使存在少量云水，模式也容易产生雨水。这基本上导致了不切实际的频繁和小雨的预估，云对气溶胶扰动的敏感度很高。
Aerosol-cloud interactions are one of the most uncertain processes in climate models due to their nonlinear complexity. A key complexity arises from the possibility that clouds can respond to perturbed aerosols in two opposite ways, as characterized by the traditional "cloud lifetime" hypothesis and more recent "buffered system" hypothesis. Their importance in climate simulations remains poorly understood. Here we investigate the response of the liquid water path (LWP) to aerosol perturbations for warm clouds from the perspective of general circulation model (GCM) and A-Train remote sensing, through process-oriented model evaluations. A systematic difference is found in the LWP response between the model results and observations. The model results indicate a near-global uniform increase of LWP with increasing aerosol loading, while the sign of the response of the LWP from the A-Train varies from region to region. The satellite-observed response of the LWP is closely related to meteorological and/or macrophysical factors, in addition to the microphysics. The model does not reproduce this variability of cloud susceptibility (i.e., sensitivity of LWP to perturbed aerosols) because the parameterization of the autoconversion process assumes only suppression of rain formation in response to increased cloud droplet number, and does not consider macrophysical aspects that serve as a mechanism for the negative responses of the LWP via enhancements of evaporation and precipitation. Model biases are also found in the precipitation microphysics, which suggests that the model generates rainwater readily even when little cloud water is present. This essentially causes projections of unrealistically frequent and light rain, with high cloud susceptibilities to aerosol perturbations.