Development of Novel Convection Nowcasting Techniques for Southeast Asia

背景和理由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等国。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，经常造成山体滑坡和洪水。1-5天时间尺度的数值天气预报的技巧仍然很低，除了每日持续预报（即明天的天气与今天的天气相同）之外，通常没有什么技巧。“临近预报”使用对当前天气的详细描述（例如，从卫星观测），并外推到未来6小时，以产生短期天气预报。在海洋大陆地区，热带对流系统的寿命可以从几个小时到一天以上，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利用~ 11um红外通道的亮度温度来识别冷云顶。更复杂的系统使用来自多个渠道的信息；例如，根据日间红外线及水蒸汽通道的亮温及可见光反射率综合估算对流雨量。东南亚的一些国家，如印度尼西亚和马来西亚，运营着降水雷达网络，自2017年以来，英国气象局一直在定期对海洋大陆进行高分辨率（允许对流的）确定性和整体预报。将利用光流和机器学习方法及时前向传播观测结果，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导致对流起始的临近预报方面的重大改进，因为预计它将能够利用允许对流的模式和白天的可见信道卫星观测来识别辐合线。集成的临近预报系统将被设计为可选地包括闪电观测，这已被证明可以显著改善基于卫星的临近预报。闪电传感器目前正在为即将到来的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在选定时期获得。目标：开发一个混合临近预报系统，将高质量的Himawari卫星数据（图2）与地面雷达和高分辨率模式预报相结合。在一个测试周期内，对东南亚地区的降水进行定量临近预报和短期预报。将新预报的技能与现有的天气预报和持续预报进行比较。图2左：Himawari-8卫星的艺术再现。图片来源：新濠国际右图：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：全彩图片。下图：红外图像，其中非常冷的云顶显示为粉红色，表明有大雨。你将在利兹大学工作，由利兹大学、爱丁堡大学和埃克塞特气象局的气象和临近预报专家指导。您将在使用遥感、动态气象学、天气预报和数据分析等技术组合开发和测试新的天气预报工具方面获得强大的专业知识。项目产出项目将逐步提高短期降水预报的质量（提前6-12小时），从而提高东南地区的预报能力

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