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Modelling the relationship between liquid water content and cloud droplet number concentration observed in low clouds in the summer Arctic and its radiative effects

机译:夏季北极低云中液体含水量与云液滴数集中的关系及其辐射效应

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Low clouds persist in the summer Arctic with important consequences for the radiation budget. In this study, we simulate the linear relationship between liquid water content (LWC) and cloud droplet number concentration (CDNC) observed during an aircraft campaign based out of Resolute Bay, Canada, conducted as part of the Network on Climate and Aerosols: Addressing Key Uncertainties in Remote Canadian Environments study in July 2014. Using a single-column model, we find that autoconversion can explain the observed linear relationship between LWC and CDNC. Of the three autoconversion schemes we examined, the scheme using continuous drizzle (Khairoutdinov and Kogan, 2000) appears to best reproduce the observed linearity in the tenuous cloud regime (Mauritsen et al., 2011), while a scheme with a threshold for rain (Liu and Daum, 2004) best reproduces the linearity at higher CDNC. An offline version of the radiative transfer model used in the Canadian Atmospheric Model version 4.3 is used to compare the radiative effects of the modelled and observed clouds. We find that there is no significant difference in the upward longwave cloud radiative effect at the top of the atmosphere from the three autoconversion schemes (p=0.05) but that all three schemes differ at p=0.05 from the calculations based on observations. In contrast, the downward longwave and shortwave cloud radiative effect at the surface for the Wood?(2005b) and Khairoutdinov and Kogan?(2000) schemes do not differ significantly (p=0.05) from the observation-based radiative calculations, while the Liu and Daum?(2004) scheme differs significantly from the observation-based calculation for the downward shortwave but not the downward longwave fluxes.
机译:低云在夏季北极持续存在,对辐射预算的重要后果。在这项研究中,我们在加拿大彻底的湾在气候和气溶胶的一部分中,我们模拟了飞机运动期间观察到的液体含水量(LWC)和云液滴数浓度(CDNC)之间的线性关系:解决键远程加拿大环境中的不确定性在2014年7月的读取。使用单列模型,我们发现AutoConversion可以解释LWC和CDNC之间观察到的线性关系。在我们审查的三种自动变压方案中,使用连续毛毛仪(Khairoutdinov和Kogan,2000)的计划似乎最佳地再现了脆弱的云制度(Mauritsen等,2011)中观察到的线性度,而雨水阈值(刘和Daum,2004)最佳再现在较高CDNC的线性。加拿大大气模型4.3中使用的辐射传输模型的离线版本用于比较所建模和观察云的辐射效果。我们发现,从三个自动增压方案的大气层顶部的向上长波云辐射效果没有显着差异(P = 0.05),但是所有三种方案在基于观察结果的计算中的计算差异。相比之下,木材表面的向下长波和短波束辐射效果?(2005b)和Khairoutdinov和Kogan?(2000)方案与刘观察的辐射计算没有显着差异(p = 0.05),而刘和daum?(2004)方案与基于观察的计算的下向下短波但不是向下的长波助焊剂的计算显着不同。

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