Collaborative Research: Intermittent and Steady State Processes in Orographic Precipitation

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。改进地形降水预报需要继续将理论、实地研究和长期观测结合起来。虽然以前关于地形降水的大部分工作都集中在稳态过程上，但对广泛降水区域内的间歇性降水单元所做的工作很少。目前的数值模式不能在单个风暴的时间尺度和对应于单个地形脊的空间尺度上一致地再现地形降水模式。工作假设是，这些问题在很大程度上是由于模型中稳态和间歇过程的表示错误造成的。将在俄勒冈沿海地区进行综合建模和观测研究。来自国家气象局天气雷达网和高空探测网的观测，以及专门部署的垂直指向雷达和分差仪的观测，将用于表征间歇性降水单元并评估模式输出。由于研究的结果，间歇性地形降水及其相对于总地形降水的重要性将被量化。将定义实际模拟间歇性地形降水所需的数值模式配置，以及捕获俄勒冈地区预报集合不确定性所需的环境条件变化子集。建议的工作还将涉及数值天气预报模式中冰微物理的参数化和地形降水的中尺度可预测性。本次联合地形降水研究的总体长期目标是提高山地地形冬季降水定量预报，影响广泛。这些预报质量的提高还对洪水预报和减灾、雪崩控制、淡水资源管理和气候变化影响产生了更广泛的影响。其他更广泛的影响包括支持和培训研究生作为研究助理。几名本科生研究助理也将接受数据分析方面的培训。研究结果将由学生作为海报展示在研究研讨会上，如每年春夏两季由北卡罗来纳州立大学和纽约州立大学石溪分校举办的研讨会。实时预报模型以纽约州石溪市为中心运行，将定期作为校园每周学生会议和国家气象局地区办事处预报讨论的一部分。根据这项建议，将在本科和研究生课程中创建关于使用雷达数据评估模型输出的教育模块。项目资金将用于加强校园研究基础设施，包括提升数据服务器存储容量和维护现场仪器。结果将在会议报告和期刊文章中传播。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Improved forecasting of orographic precipitation requires continued integration of theory, field studies, and long term observations. While much of the previous work on orographic precipitation has focused on steady-state processes, little work has been done on intermittent precipitation cells embedded in broad regions of precipitation. Current numerical models cannot consistently reproduce orographic precipitation patterns at time scales of individual storms and spatial scales corresponding to individual terrain ridges. The working hypothesis is that these problems are in large part a result of errors in the representation of steady state and intermittent processes within the models.An integrated modeling and observational study will be conducted in coastal Oregon. Observations from the National Weather Service weather radar network and upper air sounding network, and observations from specially-deployed vertically pointing radars and disdrometers will be used to characterize intermittent precipitation cells and to evaluate model output. As a result of the study intermittent orographic precipitation and its relative importance compared to total orographic precipitation will be quantified. The numerical model configuration needed to realistically model intermittent orographic precipitation will be defined, along with the subset of variations in environmental conditions needed for capturing the forecast ensemble uncertainty in the Oregon region. The proposed work also will address the parameterization of ice microphysics in numerical weather prediction models and mesoscale predictability of orographic precipitation.The overall long-term goal of this joint orographic precipitation research is to improve winter quantitative precipitation forecasts in mountainous terrain, which is a broad impact. Improved quality of these forecasts also has broader impacts for flood forecasts and mitigation, avalanche control, fresh water resources management, and climate change impacts. Other broader impacts include support and training of graduate students as research assistants. Several undergraduate research assistants will also be trained to do data analysis. Results will be presented by students as posters at research symposia such as the ones held by North Carolina State University and SUNY Stony Brook each spring and summer. The real-time forecast model runs centered on Stony Brook, NY will be regularly used as part of forecast discussions during weekly student meetings on campus and by the regional offices of the National Weather Service. Educational modules on evaluation of model output with operational radar data to be used in undergraduate and graduate classes will be created under this proposal. Project funds will be used to enhance campus research infrastructure in terms of upgrading data server storage capacity and maintenance of field instruments. Results will be disseminated in conference presentations and journal articles.