Collaborative Research: Understanding Continental/Oceanic Transition of Mesoscale Convective Systems and Tropical Cyclogenesis during the African Multidisciplinary Analysis

这项研究的主要目标是：（a）数值模拟西非季风系统的重要天气特征，包括非洲和热带东风急流、长寿命中尺度对流系统和东大西洋热带气旋生成;（B）应用数据同化以更好地量化和纠正模式偏差，因为它们与中尺度对流系统的数值模拟有关（c）在数值模式中使用不同的微物理方案进行敏感性研究，以模拟撒哈拉空气层爆发的情况。这项研究将促进对MCS过渡过程的了解，并帮助确定天气研究和预报（WRF）模型在模拟西非季风方面的优点和缺点。智力优势：该项目将：（1）对2006年非洲季风多学科分析期间离开非洲赤道线并形成热带风暴黛比和飓风海伦的热带扰动进行模拟研究，这些扰动源自西非的MCS。(2)纳入广泛的上游原位测量（例如，高分辨率地面和高空观测网络）纳入2006年选定案例的数据同化实验，并利用下游飞机测量数据验证模拟结果（即，NASA DC-8和NOAA G-IV和P-3飞机）（3）对大陆地区的MCS及其在SAL影响下向海洋环境的过渡进行高分辨率建模调查。(4)更广泛的影响：拟议的活动对于了解东大西洋热带气旋的形成以及改进这些风暴的预测非常重要。这项研究将加强佛罗里达理工学院、霍华德大学和谢赫安塔迪奥普大学之间的合作伙伴关系，并提高人力、技术和体力，以开展天气和区域气候过程领域的教育和研究工作。该项目将资助两名博士。一个在佛罗里达理工学院，一个在霍华德大学。在人类层面上，来自传统上代表性不足的群体（非洲裔和西班牙裔美国人）的学生将有独特的机会使用来自国际实地实验的数据，同时，该项目将直接提高西非研究人员在大气科学方面的能力。将努力扩大研究和教育的范围，并利用中尺度模型解决天气预报的业务问题。最后，该项目将为西非的天气预报开辟新的篇章，目前在那里的天气预报中没有使用中尺度模型;相反，这些地区的预报目前是基于欧洲或美国运行的数值天气预报模型。非洲国家有能力运行自己的模型，并使其适应本区域的特点，这将大大提高非洲的预测能力。

The primary objectives of this research are: (a) to numerically simulate important weather features of the West African monsoon system including, the African and tropical easterly Jets, long-lived mesoscale convective systems, and tropical cyclogenesis in the Eastern Atlantic; (b) to apply data assimilation for better quantifying and correcting model biases as they relate to numerical simulation of mesoscale convective systems (MCSs) and tropical cyclone genesis; and (c) to conduct sensitivity studies using different microphysical schemes in the numerical model when simulating cases with Saharan Air Layer (SAL) outbreaks. This research will advance the understanding of the MCSs transition processes as well as help identify the strengths and weaknesses of the Weather Research and Forecasting (WRF) model as it relates to simulating the West African monsoon. Intellectual Merits: This project will: (1) Undertake modeling studies of tropical disturbances that exited the African Coastline and formed Tropical Storm Debby, and Hurricane Helene, which originated from MCSs in West Africa during the 2006 African Monsoon Multidisciplinary Analysis (AMMA) period. (2) Incorporate extensive upstream in situ measurements (e.g., high resolution surface and upper air observation networks) into data assimilation experiments for selected cases from 2006 and to validate the simulation results with downstream aircraft measurements (i.e., NASA DC-8 and NOAA G-IV and P-3 aircraft) (3) Undertake high-resolution modeling investigations of MCSs over continental areas and their transition to oceanic environments under the influence of the SAL. (4) Implement the WRF model at Cheikh Anta Diop University in Dakar, Senegal for research purposes.Broader Impacts: The proposed activity is important in understanding tropical cyclone formation in the eastern Atlantic, as well as improving the prediction of these storms. This research will enhance the partnership and increase the human, technical, and physical capacity, between Florida Institute Technology, Howard University, and Cheikh Anta Diop University for undertaking educational and research efforts in the area of weather and regional climate processes. This project will fund two Ph.D. level graduate students, one at Florida Institute of Technology and one at Howard University. On the human scale, students from traditionally underrepresented groups (African and Hispanic Americans) will have the unique opportunity to work with data from an international field experiment and at the same time, the project will directly increase human capacity in the atmospheric sciences for West African researchers. There will be an effort to extend beyond research as well as education and address operational issues of weather predictions using mesoscale models. Finally, this project will open up a new chapter in weather prediction in West Africa, where mesoscale models currently are not used in weather prediction; instead, forecasts in these regions are currently based on numerical weather forecasting models that are run in either Europe or the United States. The capability to run their own models and adapt them to the characteristics of their region will significantly improve African forecasting abilities.