دورية أكاديمية
New insights on the prevalence of drizzle in marine stratocumulus clouds based on a machine learning algorithm applied to radar Doppler spectra
العنوان: | New insights on the prevalence of drizzle in marine stratocumulus clouds based on a machine learning algorithm applied to radar Doppler spectra |
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المؤلفون: | Z. Zhu, P. Kollias, E. Luke, F. Yang |
المصدر: | Atmospheric Chemistry and Physics, Vol 22, Pp 7405-7416 (2022) |
بيانات النشر: | Copernicus Publications, 2022. |
سنة النشر: | 2022 |
المجموعة: | LCC:Physics LCC:Chemistry |
مصطلحات موضوعية: | Physics, QC1-999, Chemistry, QD1-999 |
الوصف: | The detection of the early growth of drizzle particles in marine stratocumulus clouds is important for studying the transition from cloud water to rainwater. Radar reflectivity is commonly used to detect drizzle; however, its utility is limited to larger drizzle particles. Alternatively, radar Doppler spectrum skewness has proven to be a more sensitive quantity for the detection of drizzle embryos. Here, a machine learning (ML)-based technique that uses radar reflectivity and skewness for detecting small drizzle particles is presented. Aircraft in situ measurements are used to develop and validate the ML algorithm. The drizzle detection algorithm is applied to three Atmospheric Radiation Measurement (ARM) observational campaigns to investigate the drizzle occurrence in marine boundary layer clouds. It is found that drizzle is far more ubiquitous than previously thought; the traditional radar-reflectivity-based approach significantly underestimates the drizzle occurrence, especially in thin clouds with liquid water paths lower than 50 g m−2. Furthermore, the drizzle occurrence in marine boundary layer clouds differs among the three ARM campaigns, indicating that the drizzle formation, which is controlled by the microphysical process, is regime dependent. A complete understanding of the drizzle distribution climatology in marine stratocumulus clouds calls for more observational campaigns and continuing investigations. |
نوع الوثيقة: | article |
وصف الملف: | electronic resource |
اللغة: | English |
تدمد: | 1680-7316 1680-7324 |
Relation: | https://acp.copernicus.org/articles/22/7405/2022/acp-22-7405-2022.pdf; https://doaj.org/toc/1680-7316; https://doaj.org/toc/1680-7324 |
DOI: | 10.5194/acp-22-7405-2022 |
URL الوصول: | https://doaj.org/article/8086c5f634f249e9be20eb88ad8665a8 |
رقم الأكسشن: | edsdoj.8086c5f634f249e9be20eb88ad8665a8 |
قاعدة البيانات: | Directory of Open Access Journals |
تدمد: | 16807316 16807324 |
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DOI: | 10.5194/acp-22-7405-2022 |