Average and Variability Characteristics of Orographic Precipitation at Multiple Scales

两个主要的实地项目，南阿尔卑斯山的中尺度阿尔卑斯计划（MAP）（1999）和华盛顿和俄勒冈州的通过观测验证实验改进微物理参数化（IMPROVE）（2000和2001）已经获得了许多关于地形降水机制的新发现。 这项研究将建立和扩展几个关键结果的微物理学和动力学的地形降水使用特殊的观察中获得的地图和改进，国家气象局业务数据集，并与中尺度模型输出的比较。通过对地图和IMPROVE数据集的分析，出现了一个重要的主题，即地形降水在空间和时间上的多尺度变化。 对于2 km尺度，地形上的阻塞流与非阻塞流会出现不同的三维降水模式。 小尺度降水特征向上游发展并向山区漂移。 与此同时，其他小规模的特征也被锁定在地形上。 在山脉上流动的空气包经常会交叉彼此的路径，扰乱热力学和微物理特性。 研究的第一部分将建立在这些发现的基础上，通过检查几个冬季的业务国家气象局WSR-88 D雷达和高空探测从降水事件在南部华盛顿和北方俄勒冈州。 降水模式、频率、空间和时间的变化以及与沿海和喀斯喀特山脉的关系将以便于与合作的主要研究者提供的区域中尺度模型输出进行客观比较的方式加以描述。对MAP数据集的分析揭示了在降水强度范围很广的数百米尺度上的微物理变化，以及0 ℃以上和0 ℃以下水平的堆积对在地形降水中观察到的高降水效率的重要性。 对IMPROVE数据集的分析表明，小尺度对流翻转是降水增强的一种机制。 研究的第二部分将扩展和完善这些结果。 尚未回答的关键问题涉及小尺度对流翻转的频率以及小尺度垂直空气运动和降水强度的联合变率的细节。 对现有数据集的垂直指向雷达和降水测量数据的分析将侧重于从总体特性方面描述小尺度变异的特征。知识价值：改进定量降水预报是美国天气研究计划的一项重大举措。 本研究将评估来自MAP和IMPROVE研究的地形降水机制的新概念模型的适用性。 将评估对垂直空气运动的次网格尺度变率进行参数化的潜在需要。 所开发的方法将有助于今后使用业务雷达数据集来例行评估预报模式的性能。更广泛的影响：结果将与区域业务预报界分享，并在相关课程的研讨会和客座讲座中分享。 该项目将涉及一名研究生和一名本科生研究助理的教育和培训。

Two major field programs, the Mesoscale Alpine Programme (MAP) (1999) in the southern Alps and the Improvement of Microphysical PaRameterization through Observational Verification Experiment (IMPROVE) (2000 and 2001) in Washington and Oregon have yielded many new findings regarding orographic precipitation mechanisms. This research will build on and extend several key results regarding the microphysics and dynamics of orographic precipitation using special observations obtained in the MAP and IMPROVE, National Weather Service operational data sets, and comparisons with mesoscale model output. An important theme emerging from the analysis of the MAP and IMPROVE data sets is the variability of orographic precipitation over multiple scales in space and time. For scales 2 km, different three-dimensional patterns of precipitation occur in blocked versus unblocked flow over terrain. Small-scale precipitation features develop upstream and drift toward the mountains. Simultaneously, other small-scale features develop that are locked to terrain. Air parcels flowing over mountains often cross each other's paths, scrambling both sets of thermodynamic and microphysical properties. The first component of the research will build on these findings by examining several winter seasons of operational National Weather Service WSR-88D radar and upper-air soundings from precipitation events in southern Washington and northern Oregon. Precipitation patterns, their frequency, variability in space and time, and relationships to the coastal and Cascade mountain ranges will be characterized in a manner to facilitate objective comparison to regional mesoscale model output supplied by a collaborating Principal Investigator. Analyses of the MAP data sets have revealed microphysical variability at the scale of hundreds of meters within a wide range of precipitation intensities as well as the importance of accretion both above and below the 0 degree C level to the high precipitation efficiencies observed in orographic precipitation. Analyses of the IMPROVE data sets indicate small-scale convective overturning as a mechanism of precipitation enhancement. The second component of the research will extend and refine these results. Key unanswered questions relate to the frequency of small-scale convective overturning and the details of the joint variability of small-scale vertical air motions and precipitation intensity. Analysis of vertically pointing radar and precipitation measurements from existing data sets will focus on characterization of small-scale variability in terms of ensemble properties. Intellectual merit: Improvement of quantitative precipitation forecasting is a major initiative of the U.S. Weather Research Program. This research will evaluate the applicability of the new conceptual models of orographic precipitation mechanisms derived from MAP and IMPROVE studies. The potential need for parameterizations of sub-grid scale variability of vertical air motion will be evaluated. Methods developed will facilitate future use of operational radar data sets to routinely evaluate forecast model performance. Broader impacts: Results will be shared with the regional operational forecast community as well as within seminars and guest lectures for relevant courses. The project will involve the education and training of a graduate student and an undergraduate research assistant.