Use of High Resolution Field Data to Improve Model Microphysics and Investigate Orographic Precipitation Processes

使用高分辨率现场数据改进模型微物理并研究地形降水过程

• 批准号: 0094524
• 负责人: Brian Colle
• 金额: $ 25.15万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-02-01 至 2005-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0094524&HistoricalAwards=false
• 关键词: Use; Resolution; Field; Data; Improve

Accurate prediction of precipitation amounts (quantitative precipitation forecasting; QFP) is a difficult forecasting problem, but one that has a potentially high societal benefit. For this reason, the U.S. Weather Research Program has identified QPF as a high priority research area. The primary objectives of this project are to use high-resolution field observations to verify and improve the numerical representation of microphysics in mesoscale models and to document the three-dimensional structures and physical mechanisms of orographic precipitation.This research is motivated by the fact that QPF continues to be a difficult problem for numerical weather prediction models. Recent studies have suggested that increasing horizontal resolution to a few kilometers often does not lead to more accurate precipitation forecasts, even over areas of complex terrain such as the Pacific Northwest, where the mesoscale flow is highly deterministic and the precipitation is mostly stratiform. There is growing evidence suggesting that these problems are associated with deficiencies in model microphysics. Therefore, a major objective of this project is to use remotely sensed (radar) observations, in situ aircraft data, and ground measurements to verify and improve the bulk microphysical schemes in mesoscale models. In order to evaluate the model microphysics for different types of environmental conditions, this study will utilize field data from IPEX (Intermountain Precipitation EXperiment) over northeast Utah, PACJET (PACific Landfalling JETs) along the West Coast, and IMPROVE (Improvement of Microphysical PaRameterization through Observational Verification Experiment) over the Oregon Cascades.These field studies also provide an opportunity to study the detailed three-dimensional structures and physical mechanisms associated with orographic precipitation. For example, radar and in situ aircraft data will illustrate how the orographic cloud and microphysics are modified by blocking and mountain wave dynamics as well as latent heating/cooling within the cloud. These observational results will also be compared and augmented with high-resolution model simulations. Overall, understanding these sensitivities combined with improvements to the bulk microphysical schemes will help improve quantitative precipitation forecasting.

降水量的准确预测（定量降水预报; QFP）是一个困难的预测问题，但有潜在的高社会效益。 因此，美国气象研究计划将QPF确定为高优先级研究领域。 本项目的主要目标是利用高分辨率的野外观测资料来验证和改进中尺度模式中微物理的数值表达，并记录地形降水的三维结构和物理机制，这一研究的动机是，QPF仍然是一个困难的问题，数值天气预报模式。 最近的研究表明，将水平分辨率提高到几公里通常不会导致更准确的降水预报，即使在复杂地形的地区，如太平洋西北部，中尺度流是高度确定性的，降水主要是层状的。 越来越多的证据表明，这些问题与模型微观物理学的缺陷有关。 因此，该项目的一个主要目标是利用遥感（雷达）观测、现场飞机数据和地面测量来验证和改进中尺度模型中的整体微物理方案。 为了评估不同类型环境条件下的模型微物理，本研究将利用IPEX的现场数据（山间降水试验）在犹他州东北部，PACJET（太平洋登陆木星）沿着西海岸，和改善（通过观测验证实验改进微物理参数化）。这些实地研究还提供了一个机会，研究详细的三个-与地形降水有关的空间结构和物理机制。 例如，雷达和现场飞机数据将说明地形云和微物理是如何被阻塞和山波动力学以及云内的潜热加热/冷却所改变的。 这些观测结果还将与高分辨率模式模拟进行比较和补充。 总体而言，了解这些敏感性结合改进散装微物理方案将有助于提高定量降水预报。