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Bubble size distribution in surface wave breaking entraining process

Science china Earth Sciences 2007年第11期50卷 1754-1760页

作者： han lei1,2.& yuan yeli2.1 department of ocean environment,{2., Qingdao 2.6003, china 2.The First Institute of oceanography, State ocean Administration, Qingdao 2.6061, china department of ocean {2. Ocean University of China Qingdao China The First Institute of oceanography State Ocean Administration Qingdao China

From the similarity theorem, an expression of bubble population is derived as a function of the air en-trainment rate, the turbulent kinetic energy (TKE) spectrum density and the surface tension. The bubble size spectrum that we obtain has a dependence of a?2.5+nd on the bubble radius, in which nd is positive and dependent on the form of TKE spectrum within the viscous dissipation range. To relate the bubble population with wave parameters, an expression about the air entrainment rate is deduced by intro-ducing two statistical relations to wave breaking. The bubble population vertical distribution is also derived, based on two assumptions from two typical observation results.

关键词： wave breaking,bubble cloud,bubble size spectrum

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Climate change attribution of the 2.2. Henan extreme precipitation: Impacts of convective organization

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Science china Earth Sciences 2022年第10期65卷 1837-1846页

作者： han QIN Wei yuan Jun WANG Yang CHEN Panxi DAI Adam HSOBEL Zhiyong MENG Ji NIE Laboratory for Climate and ocean-Atmosphere Studies Department of Atmospheric and Oceanic SciencesSchool of PhysicsPeking UniversityBeijing 100871China Aviation Meteorological Center Civil Aviation Administration of ChinaBeijing 100621China Key Laboratory of Regional Climate-environment for Temperate East Asia(RCE-TEA) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China department of Atmospheric Science School of Earth SciencesZhejiang UniversityHangzhou 310027China department of Applied Physics and Applied Mathematics and Lamont-Doherty Earth Observatory Columbia University

In this study, we investigate the climate attribution of the 2.·7 Henan extreme precipitation event. A conditional storyline attribution method is used, based on simulations of the event with a small-domain high-resolution cloud-resolving model. Large-scale vertical motion is determined by an interactive representation of large-scale dynamics based on the quasigeostrophic omega equation, with dynamical forcing terms taken from observation-based reanalysis data. It is found that warming may lead to significant intensification of both regional-scale(10–14% K, depending on convective organization) and station-scale precipitation extremes(7–9% K^(-1)). By comparing clustered convection organized by a localized surface temperature anomaly and squall-line convection organized by vertical wind shear, we further explored how convective organization may modify precipitation extremes and their responses to warming. It is found that shear convective organization is much more sensitive to large-scale dynamic forcing and results in much higher precipitation extremes at both regional and station scales than unorganized convection is. The clustered convection increases station-scale precipitation only slightly during heavy precipitation events. For regional-scale extreme precipitation sensitivity, shear-organized convection has a larger sensitivity by 2.3% Kthan that of unorganized convection, over a wide temperature range, due to its stronger diabatic heating feedback. For the station-scale extreme precipitation sensitivity, no systemic dependence on convective organization is found in our simulations.

关键词： Extreme precipitation Global warming Climate change attribution Convective organization Hourly precipitation

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