AI 中文总结
研究聚焦深对流上升气流速度，虽对流有效位能常用于解释最大上升气流速度，但它并非完美预测指标。本文利用方程学习识别相关关系，发现风暴前CAPE和局部平均边界层垂直速度共同解释近半方差，强度峰值时特定组合解释89%方差，突出了相关因素对对流强度的作用。
AI 中文摘要
深对流上升气流速度在地球气候系统中起关键作用，影响极端降水、闪电和行星能量收支。虽然对流有效位能（CAPE）广泛用于解释最大上升气流速度（$w_{\max}$），但它并非完美预测指标，上升气流还受夹卷、边界层动力学、压力扰动和凝结负荷影响。本文利用方程学习识别将环境和云内条件与$w_{\max}$联系起来的紧凑且具有物理可解释性的关系。对于风暴前预测，CAPE和局部平均边界层垂直速度（$\overline{w_{\mathrm{bl}}}$）共同解释了不同状态下$w_{\max}$近一半的方差（$R^2 = 0.47$）。在强度峰值时，一个简单的近似伯努利不变量结合最大压力扰动和最大云凝结量解释了89%的方差（$R^2 = 0.89$）。结果突出了$\overline{w_{\mathrm{bl}}}$与CAPE一样是对流强度的重要调节因素，并表明动压在单个上升气流中起重要作用。
英文摘要
Deep convective updraft velocities play a key role in the Earth's climate system, influencing precipitation extremes, lightning, and the planetary energy budget. While Convective Available Potential Energy (CAPE) is widely used to explain maximum updraft velocity ($w_{\max}$), CAPE is an imperfect predictor as updrafts are also influenced by entrainment, boundary layer dynamics, pressure perturbations, and condensate loading. However, the relative importance of these processes and how they interact to set $w_{\max}$ in individual clouds remains unclear. Here, we use equation learning to identify compact, physically interpretable relationships linking environmental and in-cloud conditions to $w_{\max}$ in individual tracked clouds across idealized radiative-convective equilibrium regimes spanning a range of sea surface temperatures and radiative cooling rates. For pre-storm prediction, CAPE and local mean boundary layer vertical velocity ($\overline{w_{\mathrm{bl}}}$) together explain nearly half the variance in $w_{\max}$ across regimes ($R^2=0.47$). While CAPE captures regime-mean differences, it has little predictive value within a single simulation. $\overline{w_{\mathrm{bl}}}$ is essential for capturing cloud-to-cloud variability, including the suppression of $w_{\max}$ even at high CAPE values. At the time of peak intensity, a simple approximate Bernoulli-like invariant combining maximum pressure perturbation and maximum cloud condensate explains 89\% of the variance ($R^2=0.89$). The tight link between $w_{\max}$ and pressure perturbation supports the sticky thermals hypothesis and highlights the importance of dynamic pressure effects, often neglected in updraft theories. These results highlight $\overline{w_{\mathrm{bl}}}$ as an important regulator of convective intensity alongside CAPE, and demonstrate that dynamic pressure plays an important role within individual updrafts.
Comments25 pages, 9 figures. Submitted to Atmospheric Chemistry and Physics (ACP)
