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。改进地形降水预测需要理论、实地研究和长期观测的持续整合。虽然以前的大部分工作都集中在地形降水的稳态过程，很少的工作已经做了间歇性降水细胞嵌入在广泛的降水区域。目前的数值模式不能一致地再现地形降水模式在时间尺度上的个别风暴和空间尺度对应的个别地形山脊。工作的假设是，这些问题在很大程度上是由于在稳态和间歇性的过程中的代表性的models.A集成的建模和观测研究将在沿海俄勒冈州的错误。国家气象局天气雷达网和高空探测网的观测结果以及专门部署的垂直指向雷达和测雨仪的观测结果将用于确定间歇性降水单元的特征和评价模式输出。作为研究的结果，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型配置，沿着捕获俄勒冈州地区预报集合不确定性所需的环境条件变化子集。拟议的工作还将解决数值天气预报模型和地形降水的中尺度可预测性的冰微物理参数化，这一联合地形降水研究的总体长期目标是提高冬季定量降水预报在山区地形，这是一个广泛的影响。这些预报质量的提高也对洪水预报和减灾、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。一些本科生研究助理也将接受培训，做数据分析。研究结果将由学生在研究研讨会上以海报的形式展示，如每年春季和夏季由北卡罗来纳州州立大学和纽约州立大学斯托尼布鲁克举行的研讨会。以纽约州斯托尼布鲁克为中心的实时预报模型将定期在校园每周学生会议期间和国家气象局的区域办事处作为预报讨论的一部分。根据这一建议，将编制供本科生和研究生班使用的关于用雷达业务数据评价模型输出的教学单元。项目资金将用于加强校园研究基础设施，提高数据服务器的储存能力和维护外地仪器。研究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.