Will coupling the Met Office forecast model to an ocean model improve weather predictions in the tropics?

将气象局预报模型与海洋模型相结合是否会改善热带地区的天气预报？

• 批准号: 2457057
• 金额: --
• 依托单位: University of East Anglia
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2457057
• 关键词: Will; coupling; Met; Office; forecast

Scientific background: Numerical weather prediction (NWP) is the main tool behind weather forecasting of rainfall, temperature, winds and other meteorological variables. These forecasts are relied on for business planning, to protect life and property and by the general public. NWP is based on computer models of the physical laws that govern the atmosphere. The Met Office (CASE partner) runs one of the most advanced NWP systems in the world. As part of their ongoing drive to improve forecasts, they are moving beyond their "atmosphere-only" model and trialling a new "coupled ocean-atmosphere" NWP system including ocean processes. This is likely to improve forecast skill, particularly in the Tropics, where there are long-lived weather systems that interact strongly with the ocean, such as the Madden-Julian Oscillation (MJO), which is hard to forecast and linked to hazardous weather.Research methodology: You will join a team of weather, climate and NWP experts at UEA and the Met Office. You will assess the forecast skill of atmosphere-only and coupled configurations of the Met Office NWP model to quantify the benefit of coupling, focusing on the Tropics and the MJO. Additionally, you will perform a process-based analysis to determine the atmospheric and oceanic mechanisms behind any increase in skill. You will provide recommendations to the Met Office for future development of their coupled NWP system. Training: You will be trained in the analysis of NWP model output using the python programming language, including use of specific python modules developed by the Met Office for analysing and visualising model output. Depending on your background, you will be trained in atmospheric physics, meteorology and oceanography to equip you for the process-based analysis. In addition to frequent teleconferences with the Met Office co-supervisors, you will undertake visits to the Met Office for training in running and analysing the Met Office model. You will present your work at an international scientific conference.

科学背景：数值天气预报（NWP）是天气预报降雨，温度，风和其他气象变量的主要工具。这些预测被用于商业规划，以保护生命和财产以及公众。NWP是基于控制大气的物理定律的计算机模型。英国气象局（CASE合作伙伴）运行着世界上最先进的NWP系统之一。作为他们不断改进预报的努力的一部分，他们正在超越他们的“仅大气”模型，并试验一个新的“耦合海洋-大气”NWP系统，包括海洋过程。这可能会提高预报技能，特别是在热带地区，那里有与海洋强烈相互作用的长期天气系统，例如Madden-Julian Oscillation（MJO），这很难预测并与危险天气有关。研究方法：您将加入UEA和气象局的天气，气候和NWP专家团队。您将评估气象局NWP模型的仅大气和耦合配置的预报技能，以量化耦合的好处，重点是热带和MJO。此外，您将执行基于过程的分析，以确定任何技能增加背后的大气和海洋机制。您将向气象局提供关于其耦合NWP系统未来发展的建议。培训内容：您将接受使用Python编程语言分析NWP模型输出的培训，包括使用由气象局开发的特定Python模块来分析和可视化模型输出。根据您的背景，您将接受大气物理学，气象学和海洋学的培训，以使您能够进行基于过程的分析。除了与气象局共同主管频繁的电话会议，您将进行访问气象局在运行和分析气象局模型的培训。您将在国际科学会议上展示您的工作。