Exploitation of GNSS tropospheric gradients for severe weather monitoring and prediction

全球导航卫星系统（GNSS）已经彻底改变了定位、导航和授时，成为我们日常生活的一部分。除了这些众所周知的民用和商业应用之外，GNSS目前正在建立一个强大而多功能的地球科学观测工具，可以准确地感知大气温度，水蒸气，电离层电子含量，地球表面性质，同震变形等地球物理参数。地球物理的一个关键应用是利用GNSS地面站数据进行大气水蒸气监测。水蒸气是最丰富的温室气体，约占大气变暖的70%，在大气能量交换中起着关键作用。准确了解其高度变化的时空分布是精确模拟大气状态的先决条件，并以此为基础进行以强降水和灾害性天气事件为重点的数值天气预报，这是当前气象研究的主要挑战之一。因此，从区域地面网络获得的全球导航卫星系统水汽数据弥补了现有气象观测系统的不足，例如德国目前约有270个气象站。没有其他观测系统能提供如此高的时间和空间分辨率的数据。因此，欧洲全球导航卫星系统网络的数据已在若干国家广泛用于改进区域天气预报。然而，由于目前使用的天顶总延迟（Zenith Total Delay， ZTD）数据所提供的大气信息含量有限，目前提供的数据产品对预报系统的影响仍然有限。建议项目将率先开发和使用新一代数据产品；对流层梯度。该项目开发和提供的新数据产品预计将改善目前提供的全球导航卫星系统数据对天气预报系统的影响。该项目将解决的主要创新是：(1)为德国SAPOS网络提供高质量的ztd和近实时对流层梯度的发展（见附件SAPOS的支持信）；(2)在数值天气预报中利用ztd和对流层梯度的发展，即在天气研究与预报（WRF）模式的变分/集合数据同化系统中实施算子；(3)利用最先进的数值天气模式进行影响研究。

Global Navigation Satellite Systems (GNSS) have revolutionized positioning, navigation, and timing, becoming a common part of our everyday life. Aside from these well-known civilian and commercial applications, GNSS is currently in process to be established as a powerful and versatile observation tool for geosciences, which can accurately sense atmospheric temperature, water vapor, ionospheric electron content, Earth surface properties, co-seismic deformation and other geophysical parameters. A geophysical key application is atmospheric water vapor monitoring using GNSS ground station data. Water vapor, the most abundant greenhouse gas, accounts for about 70% of atmospheric warming and plays a key role in the atmospheric energy exchange. The precise knowledge of its highly variable spatial and temporal distribution is precondition for precise modeling of the atmospheric state as a base for numerical weather forecasts with focus to the strong precipitation and severe weather events, one of the current key challenges in weather research. GNSS water vapor data, derived from regional ground networks hereby close gaps in the established meteorological observing systems, e.g., at Germany with currently about 270 stations. No other observing system provides data with such high temporal and spatial resolution. The data from European GNSS networks are therefore already widely operationally used to improve regional weather forecasts in several countries. However, the impact of the currently provided data products to the forecast systems is still limited due to the limited atmospheric information content, which is provided by the currently used Zenith Total Delay (ZTD) data. The proposed project will pioneer the development and usage of next generation data products; tropospheric gradients. The new data products, developed and provided within the project, are expected to improve the impact of the currently provided GNSS data to weather forecast systems.The main innovations, which will be addressed by the project are:(1) Developments to provide high quality ZTDs and tropospheric gradientsin near-real-time for the German SAPOS network(see attached letter of support SAPOS);(2) Developments to make use of ZTDs and tropospheric gradients innumerical weather prediction, i.e., implement operators in thevariational/ensemble data assimilation system of theWeather Research and Forecasting (WRF) model;(3) Impact studies with the state of the art numerical weather model.