Development of Novel Convection Nowcasting Techniques for Southeast Asia

背景和意义东南亚的海洋大陆地区包括印度尼西亚、马来西亚、菲律宾和巴布亚新几内亚。这是一个地形复杂的地区，也是全球强降雨的热点地区。图1所示的飑线等风暴在该地区很常见，通常是山体滑坡和洪水的原因。1-5天时间尺度的数值天气预报技术仍然很低，通常没有超过每日持续性预报的技术（即明天的天气与今天相同）。“临近预报”使用当前天气的详细描述（例如从卫星观测），并推断未来6小时，以产生短期天气预报。在海洋大陆地区，热带对流系统可以有几个小时到一天多的生命周期，这意味着有机会更好地利用临近预报技术来帮助天气预报。项目细节和目标利用地球同步卫星观测进行临近预报的最简单方法是使用~11 μ m红外通道的亮温来识别冷云顶。更复杂的系统使用来自多个渠道的信息;例如利用白天红外线和水汽通道的亮温结合可见光反射率来估计对流降雨率。东南亚一些国家，如印度尼西亚和马来西亚，运行着一个降水雷达网络，气象局一直在例行地制作高分辨率的自2017年以来，海洋大陆的确定性和集合预报将利用光流和机器学习方法及时向前传播观测结果，并将卫星和雷达观测结果与数值模式预报相结合。雷达和模式预报的结合预计将大大改进对流开始的临近预报，因为预计这将使人们能够利用允许对流的模式和白天可见通道卫星观测来确定辐合线。综合临近预报系统的设计将可选地包括闪电观测，这已被证明可大大改进基于卫星的临近预报。闪电传感器目前正在为即将推出的Himawari卫星进行可行性研究，全球闪电数据集可通过全球闪电定位网络数据集获得选定时期的数据。（图2）结合地面雷达和高分辨率模式预报制作东南亚地区的定量雨量临近预报和短期预报，测试期比较新预报与现有天气预报和持续性预报的技巧图2左图：Himawari-8卫星的艺术家再现。图片来源：MELCO。右图：Himawari-8卫星拍摄的印度尼西亚和马来西亚上空云层的卫星图像。上图：全彩色图像。下图：红外线图像，非常冷的云顶，表明强降雨是粉红色的。培训你将在利兹大学工作，由来自利兹大学、爱丁堡大学和英国气象局埃克塞特的气象和临近预报专家监督。您将获得强大的专业知识，使用遥感，动力气象学，天气预报和数据分析的技术组合，以开发和测试新的天气预报工具。项目输出该项目将开发短期降水预报质量的阶跃变化（长达6-12小时的提前时间），这将提高东南地区的能力。

Background and RationaleThe Maritime Continent region of Southeast Asia contains the countries of Indonesia, Malaysia, Philippines and Papua New Guinea. It is a region of complex topography and a global hotspot for intense rainfall. Storms such as the squall line featured in Figure 1 are common across the region and are regularly the cause of landslides and flooding.The skill of numerical weather forecasts on the 1-5 day timescale remains low, often with little skill beyond that provided by a daily persistence forecast (i.e. the weather tomorrow will be the same as today). "Nowcasting" uses detailed descriptions of the current weather (from satellite observations for example) and extrapolates up to 6 hours into the future to produce a short range weather forecast. In the Maritime Continent region, tropical convective systems can have lifetimes of several hours up to more than a day, which means there is an opportunity to make better use of the nowcasting techniques to aid weather forecasting.Project details and objectivesThe simplest way to nowcast with geostationary satellite observations is to use brightness temperature at the ~11 um infrared channel to identify cold cloud tops. More complex systems use information from multiple channels; e.g. estimating convective rain rate from a combination of brightness temperature at both the infrared and water vapour channels with visible reflectivity during the day.A number of countries in Southeast Asia, such as Indonesia and Malaysia, operate a precipitation radar network and the Met Office has been routinely producing high resolution (convection-permitting) deterministic and ensemble forecasts over the Maritime Continent since 2017.Optical flow and machine learning approaches will be utilised to forward propagate the observations in time and to integrate the satellite and radar observations with numerical model forecasts. The integration of the radar and model forecasts is expected to lead to significant improvements in nowcasting of convective initiation, as it is expected to enable the identification of convergence lines using the convection-permitting model and visible channel satellite observations during the day. The integrated nowcasting system would be designed to optionally include lightning observations, which have been shown to significantly improve satellite-based nowcasts. Lightning sensors are currently subject to feasibility studies for upcoming Himawari satellites, and global lightning datasets are available for selected periods through the World Wide Lightning Location Network dataset.Objectives:Develop a blended nowcasting system that combines high quality Himawari satellite data (Figure 2) with ground-based radar and high resolution model forecastsProduce quantitative rainfall nowcasts and short-term forecasts over Southeast Asia for a test periodCompare the skill of the new forecasts with existing weather forecasts and persistence forecastsFigure 2 Left: Artist rendition of the Himawari-8 Satellite. Image credit: MELCO. Right: Satellite images of clouds over Indonesia and Malaysia from the Himawari-8 Satellite. Top: full-colour image. Bottom: infrared image, where very cold cloud tops that suggest heavy rainfall are coloured pink.TrainingYou will be based at the University of Leeds and be supervised by Meteorology and Nowcasting experts from University of Leeds, University of Edinburgh and the Met Office, Exeter. You will gain strong expertise in using a mix of techniques in remote sensing, dynamical meteorology, weather forecasting and data analysis to develop and test a new weather forecasting tool.Project outputsThe project will develop a step-change in the quality of short-term precipitation forecasts (up to 6-12 hours lead time), which will improve the ability of Southeast