Precipitation life cycle in trade wind cumuli

信风积云在地球的辐射收支中起着至关重要的作用，产生了热带地区总降雨量的20%。然而，我们仍然不知道他们将如何应对全球变暖。来自信风积云的降水可以改变云的宏观性质以及边界层的结构和动力学。模式中的降水发展是非常不确定的，依赖于模拟装置和微物理。特别是，自动转换方案显著影响降水通量、云结构和组织。目前，没有通过观测对不同的自动转换方案进行评估，从而减少了降雨过程中的不确定性。在地面观测中，基于雷达反射率的方法在后期阶段探测降水，阻碍识别导致降雨的因素。降水还可以影响对流组织和环流强度，对气候敏感性有很大影响。降水蒸发决定冷池强度，影响云场组织。因此，量化蒸发率及其时空变异性是关键。云底以下蒸发的参数化是可行的，但很大程度上依赖于雨滴的尺寸分布。此外，在观测中，蒸发率很难直接观测到。该方案的目的是回答观测中信风积云的降水形成是什么以及如何触发的问题，并利用这些数据来约束LES模式中的降水形成过程。此外，本研究的目的是量化行业中云下蒸发的时空分布，了解其主要依赖于哪些参数。该项目是对即将开展的EUREC4A实地活动的补充，并利用巴巴多斯云观测站的长期数据集。将通过协同地面观测和根据云雷达多普勒谱的偏斜度来探测降雨开始的新方法，来确定降雨开始和发展的特征。观测中的降水特征将被用来在ICON-LEM和Dharma-les模式中对降雨形成过程进行统计评估，显示该模式在哪里再现了观测到的平均行为，以及在哪里和为什么会出现偏差。分析将通过PAMTRA正向模拟器在观测空间进行。将利用EUREC4A和BCO内现有观测的协同作用来恢复蒸发率。观测廓线的时空变异性将被表征并用作约束，以验证和改进LES模式中对蒸发率的描述。这项研究将为被世界气候研究组织确定为高度优先研究的云、环流和气候敏感性大挑战做出贡献。

Trade wind cumulus clouds play a vital role in the Earth's radiation budget and produce up to 20% of the total precipitation in the tropics. However, we still don't know how they will respond to global warming. Precipitation from trade wind cumuli can alter cloud macroscopic properties and the boundary layer structure and dynamics. Precipitation development in models is very uncertain, being dependent on simulation setup and microphysics. In particular, the autoconversion scheme dramatically affects precipitation flux, cloud structure, and organization. Currently, no evaluations of the different autoconversion schemes with observations reduced the uncertainties in rain processes. In ground-based observations, radar reflectivity based approaches detect precipitation at an advanced stage, hindering the identification of factors causing rain formation. Precipitation can also impact convection organization and circulation intensity with massive effects on climate sensitivity. Evaporation of precipitation determines the intensity of cold pools and influence the cloud field organization. It is hence key to quantify evaporation rates and their spatiotemporal variability. Parametrizations of evaporation below cloud base are available but strongly depend on the drop size distribution of raindrops. Also, in the observations, evaporation rates are hard to observe directly. The goal of this proposal is to answer the question of what and how triggers precipitation formation in trade wind cumulus clouds in observations and exploit these data to constrain rain formation process in LES models. Moreover, this research aims to quantify the spatiotemporal distribution of evaporation below cloud base in the trades, understanding on which parameters it mainly depends. The project is complementary to the upcoming EUREC4A field campaign and exploits the long-term dataset of the Barbados Cloud Observatory (BCO). Characterization of precipitation onset and development will be achieved through synergetic ground-based observations and novel approaches based on the skewness of the cloud radar Doppler spectrum to detect rain onset. The characterization of precipitation in observations will be used to evaluate the rain formation process in the ICON-LEM and DHARMA-LES models statistically, showing where the model reproduce the observed mean behaviors and where and why biases occur. The analysis will be developed in the observational space by means of the PAMTRA forward simulator.Evaporation rates will be retrieved exploiting the synergy of observations available within EUREC4A and at BCO. The spatiotemporal variability of the observed profiles will be characterized and used as a constraint to verify and improve the description of evaporation rates in LES models.This research will contribute to the Grand Challenge on Clouds, circulation, and climate sensitivity identified by the World Climate Research as high priority research.