Collaborative Research: Improvement of Microphysical Parameterization Through Observational Verification Experiment (IMPROVE)

合作研究：通过观测验证实验改进微物理参数化（IMPROVE）

• 批准号: 9908446
• 负责人: Peter Hobbs
• 金额: $ 129.06万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-06-01 至 2004-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9908446&HistoricalAwards=false
• 关键词: Collaborative; Research; Improvement; Microphysical; Parameterization

Improvements in quantitative precipitation forecasting (QPF) have been listed as one of the top priorities of the U.S. Weather Research Program. The need for accurate QPF is especially acute along the mountainous coastal zone of western North America, where heavy precipitation and flooding are among the most significant weather hazards. Even with steady improvements in operational model resolution, quantitative precipitation forecasting has been slow to improve. This fact suggests that, in addition to increased grid resolution, other components of mesoscale models must be improved. One clearly problematic area is the bulk parameterization of grid-resolved cloud microphysics and precipitation. Under this collaborative project, two researchers from the University of Washington will execute a field program, associated data analysis and numerical modeling work, to improve quantitative precipitation forecasting in mesoscale models. The project will undertake comprehensive observational verifications and improvements of model-parameterized cloud and precipitation microphysics. The Principal Investigators will carry out two observational campaigns in the Pacific Northwest: a frontal precipitation study over the northeast Pacific Ocean offshore of Washington state in the winter of 2000/2001, and an orographic precipitation study in the Cascade Mountains of central Oregon in the winter of 2001/2002.Current bulk cloud microphysical parameterizations are based on relatively few observational studies; few dedicated efforts have been made to comprehensively evaluate the underlying assumptions and predicted hydrometeor distributions of these schemes, and to use such tests to improve the parameterizations. The only way to perform such verification in a manner that yields definitive and unambiguous results is to observe all aspects of the simulated precipitation system, from three-dimensional temperature and wind distributions to microphysical parameters such as mixing ratios and particle size distributions. This requires concurrent use of in situ cloud and precipitation microphysical observations from a well-instrumented aircraft and remotely sensed (radar) observations of the three-dimensional wind field. Recently, advances in numerical modeling, airborne microphysical measurement, and radar technology have converged to make such a study highly opportune. Furthermore, with a unique combination of scientific expertise, field project experience, observational facilities, and computing power, as well as a geographic location that experiences a high frequency of frontal and orographic winter precipitation systems, the University of Washington is ideally positioned to carry out the proposed research.(i)

改进定量降水预报（QPF）已被列为美国天气研究计划的首要任务之一。对精确的QPF的需求在北美西部沿海山区尤为迫切，那里的强降水和洪水是最严重的天气灾害之一。即使业务模式的分辨率稳步提高，定量降水预报的改进也很慢。这一事实表明，除了提高网格分辨率外，中尺度模式的其他组成部分也必须得到改进。一个明显有问题的领域是网格解析云微物理和降水的大量参数化。根据该合作项目，来自华盛顿大学的两名研究人员将执行一项实地计划，相关数据分析和数值模拟工作，以改进中尺度模式的定量降水预报。该项目将承担模式参数化云和降水微物理的综合观测验证和改进。主要研究人员将在太平洋西北部开展两次观测活动：2000/2001年冬季在华盛顿州近海的东北太平洋进行锋面降水研究，2001/2002年冬季在俄勒冈州中部的喀斯喀特山脉进行地形降水研究。目前的大块云微物理参数化是基于相对较少的观测研究；很少有专门的努力来全面评价这些方案的基本假设和预测水成物分布，并使用这些试验来改进参数化。要想获得明确而明确的结果，唯一的验证方法是观察模拟降水系统的各个方面，从三维温度和风分布到混合比和粒度分布等微物理参数。这需要同时使用来自设备齐全的飞机的现场云和降水微物理观测以及三维风场的遥感（雷达）观测。近年来，数值模拟、机载微物理测量和雷达技术的进步使这一研究变得非常合适。此外，华盛顿大学拥有独特的科学专业知识、实地项目经验、观测设施和计算能力，以及经历高频率锋面和地形冬季降水系统的地理位置，是开展拟议研究的理想条件。(我)