Quantitative Precipitation Forecasting Using Nonlinear Statistical Guidance

小行星9714414 美国天气研究计划（USWRP）是一项跨部门活动，旨在执行和实施必要的研究，以改善向国家提供的天气服务。 根据这一方案，国家科学基金会、国家海洋和大气管理局、国家航空航天局和海军研究办公室正在联合评估和支持美国水资源研究计划高度优先的研究。 降水量的精确定量预报（定量降水预报，QPF）已被证明是一个特别困难的问题，在过去几年中取得的进展很少。 出于这个原因，更好的QPF技术已经被科学界和操作界确定为一个研究成熟的领域。 主要研究者将研究旨在改善QPF的统计技术的新应用。 本研究将采用两种非线性方法，统计数据来自33年的3小时地面观测和12小时高空观测，覆盖美国落基山脉以东。 一个涉及的神经网络的设计与输出对应的标准降水阈值的发生概率。 另一种方法涉及使用从集合数值预报获得的天气变量的时间序列（而不是瞬时值）的模拟来指定降水概率。 ***

9714414 Pfeffer The U.S. Weather Research Program (USWRP) is an interagency activity designed to perform and implement the research necessary to improve the delivery of weather services to the nation. Under this Program, the National Science Foundation, the National Oceanic and Atmospheric Administration, the National Aeronautics and Space Administration and the Office of Naval Research are jointly evaluating and supporting research of high priority to the USWRP. Accurate quantitative forecasting of precipitation (Quantitative Precipitation Forecasting, QPF) has proven to be an especially difficult problem and one where little progress has been made over the last several years. For this reason, better QPF techniques has been identified by both the scientific and operational communities as an area ripe for research. The Principal Investigator will investigate new applications of statistical techniques designed to improve QPF. Two nonlinear methodologies will be pursued in this research with statistics derived from 33 years of 3-hourly surface observations and 12-hourly upper air observations covering the United States east of the Rocky Mountains. One involves the design of neural networks with outputs that correspond to the probability of occurrence of standard precipitation threshold values. The other methodology involves the use of analogs of time sequences (rather than instantaneous values) of synoptic variables obtained from ensemble numerical forecasts to specify precipitation probabilities. ***