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，在热带地区产生的降水量占总降水量的20%。然而，我们仍然不知道他们将如何应对全球变暖。信风积云的降水可以改变云的宏观性质和边界层结构和动力学。模式中的降水发展是非常不确定的，取决于模拟设置和微物理。特别是，自动转换方案显着影响降水通量，云结构和组织。目前，没有评估不同的自动转换方案与观测减少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检测降水，阻碍了对导致降雨形成的因素的识别。降水还可以影响对流组织和环流强度，对气候敏感性产生巨大影响。降水蒸发量决定冷池的强度并影响云场组织。因此，关键是要量化蒸发率及其时空变异性。云底以下蒸发的参数化是可用的，但强烈依赖于雨滴的粒径分布。此外，在观测中，蒸发率很难直接观测。该方案的目的是回答观测中信风积云降水形成的触发因素和触发机制，并利用这些数据约束LES模式中的降水形成过程。此外，本研究的目的是量化的时空分布的云底下蒸发的行业，了解它主要取决于哪些参数。 该项目是对即将开展的EUREC 4A实地活动的补充，并利用巴巴多斯云观测站的长期数据集。将通过地面协同观测和基于云雷达多普勒频谱偏斜度的新方法来确定降雨开始和发展的特征。观测中降水的特征将用于统计评估ICON-LEM和DHARMA-LES模型中的降雨形成过程，显示模型在哪里重现了观测到的平均行为以及在哪里以及为什么会出现偏差。将利用PAMTRA前向模拟器在观测空间进行分析，利用EUREC 4A和BCO现有观测的协同作用反演蒸发率。观测剖面的时空变异性将被表征并用作验证和改进LES模式中蒸发率描述的约束条件，这项研究将有助于世界气候研究所确定的云、环流和气候敏感性的重大挑战。

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.