Quantitative Precipitation Forecasting Using Nonlinear Statistical Guidance

9714414 ffer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，以改善向全国提供的天气服务。根据该计划，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将联合评估和支持USWRP的高优先级研究。准确的降水定量预报（定量降水预报，QPF）已被证明是一个特别困难的问题，并且在过去几年中几乎没有取得进展。由于这个原因，更好的QPF技术已经被科学和操作社区确定为一个成熟的研究领域。首席研究员将研究旨在改善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年来覆盖美国落基山脉以东的每小时3次地面观测和每小时12次高空观测。其中一个涉及神经网络的设计，其输出与标准降水阈值发生的概率相对应。另一种方法涉及使用从综合数值预报中获得的天气变量的时间序列（而不是瞬时值）的类似物来指定降水概率。＊＊＊

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. ***