Collaborative Research: ITR: Framework for Optimal Merging of Multi-sensor Spatial Data and Multi-model, Multi-analysis Ensemble Forecasts of Heavy Precipitation and Floods

该项目的目的是将卫星和地面数据与降水和洪水的数值天气预报模型、水文模型和神经网络模型相结合，以开发适合当地地区的强降水和洪水预报技术。重点地区将是阿巴拉契亚、尼泊尔、莫桑比克和巴西的河流流域，这些地区对降水有显著的地形影响。该项目是一名水文学家和一名气象学家之间的合作，涉及具有信息技术专长的支助人员。这项工作将科学计算和机器学习技术与气象学和水文学相结合。临近山区的特大洪涝灾害预报在世界上许多地方都是一个重要问题。如果取得成功，这项研究将发展出一种方法，然后可以加以调整，用于这种预测的业务用途。

The aim of this project is to integrate satellite and ground-based data with numerical weather prediction models, hydrological models and neural network models of precipitation and flooding, in order to develop techniques for forecasting heavy precipitation and flooding that are tailored to local regions. The focus regions will be river basins in Appalachia, Nepal, Mozambique and Brazil where there are significant orographic influences on precipitation. The project is a collaboration between a hydrologist and a meteorologist and involves support personnel with expertise in information technology. The work combines scientific computing and machine learning techniques with meteorology and hydrology. The forecasting of heavy floods in areas adjacent to mountainous regions is an important problem in many places around the world. If successful, the research would develop an approach that could then be adapted to operational use for such forecasting.