Downward Convective Moisture Transport Dominated by a Few Overshooting Clouds in Marine and Continental Shallow Convection

IF 4.6 2区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES Journal of Advances in Modeling Earth Systems Pub Date : 2025-03-18 DOI:10.1029/2024MS004489
Heng Xiao, Adam Varble, Colleen Kaul, Johannes Mülmenstädt
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Abstract

In a previous study (Xiao et al., 2023, https://doi.org/10.1029/2022ms003526), we found that ignoring the moist convective downdrafts associated with overshooting clouds in parameterizations can lead to significant biases in the simulated depth and liquid water content of a shallow cloud layer. In this study, we seek to better quantify the properties of the clouds responsible for these moist downdrafts to help improve shallow convection parameterizations. We apply a 3-D cloud-tracking algorithm to large-eddy simulations (LESs) of marine and continental shallow convection. We find that top 1% and 2% of the tracked cloud population ranked by lifetime-mean cloud-base mass flux can explain 90%–95% of the total downward moisture transport in the upper cloud layer whereas top 10%–20% is required to explain 90%–95% of the total upward moisture transport near mean cloud base. The vertical structure of the clouds in the top 1% and 2% (the overshooting “deep mode”) is also distinctively different from that of the rest of the cloud population (the “shallow mode”). Shallow convection parameterizations need to capture accurately the properties and convective transports of the clouds in both the deep and shallow modes. To do that, our results suggest that mass-flux parameterizations need to (a) accurately predict the size and number of the deep-mode clouds and (b) explicitly represent overshooting cloud updrafts and associated moist downdrafts.

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海洋和大陆浅对流中以少量过冲云为主的向下对流水汽输送
在之前的一项研究中(Xiao et al., 2023, https://doi.org/10.1029/2022ms003526),我们发现在参数化中忽略与过冲云相关的潮湿对流下降气流会导致浅层云层模拟深度和液态水含量的显著偏差。在这项研究中,我们试图更好地量化造成这些潮湿下沉气流的云的特性,以帮助改善浅对流参数化。本文将三维云跟踪算法应用于海洋和大陆浅层对流大涡模拟。我们发现,按终生平均云底质量通量排序的跟踪云群的前1%和前2%可以解释上层云层中总向下输送的90%-95%,而平均云底附近总向上输送的90%-95%需要前10%-20%来解释。顶部1%和2%的云的垂直结构(超调的“深模态”)也明显不同于其他云的垂直结构(“浅模态”)。浅对流参数化需要准确地捕捉云在深模和浅模下的性质和对流输送。要做到这一点,我们的结果表明,质量通量参数化需要(a)准确地预测深模云的大小和数量,(b)明确地表示超调云上升气流和相关的潮湿下降气流。
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来源期刊
Journal of Advances in Modeling Earth Systems
Journal of Advances in Modeling Earth Systems METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
11.40
自引率
11.80%
发文量
241
审稿时长
>12 weeks
期刊介绍: The Journal of Advances in Modeling Earth Systems (JAMES) is committed to advancing the science of Earth systems modeling by offering high-quality scientific research through online availability and open access licensing. JAMES invites authors and readers from the international Earth systems modeling community. Open access. Articles are available free of charge for everyone with Internet access to view and download. Formal peer review. Supplemental material, such as code samples, images, and visualizations, is published at no additional charge. No additional charge for color figures. Modest page charges to cover production costs. Articles published in high-quality full text PDF, HTML, and XML. Internal and external reference linking, DOI registration, and forward linking via CrossRef.
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