دورية أكاديمية

New insights on the prevalence of drizzle in marine stratocumulus clouds based on a machine learning algorithm applied to radar Doppler spectra

التفاصيل البيبلوغرافية
العنوان: New insights on the prevalence of drizzle in marine stratocumulus clouds based on a machine learning algorithm applied to radar Doppler spectra
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
الوصف
تدمد:16807316
16807324
DOI:10.5194/acp-22-7405-2022