Radar-Derived Refractivity and Its Impact on Model Analysis and Forecasting Using Advanced Data Assimilation Methods

雷达衍生的折射率及其对使用先进数据同化方法的模型分析和预测的影响

• 批准号: 0750790
• 负责人: Robert Palmer
• 金额: $ 70.96万
• 依托单位: University of Oklahoma Norman Campus
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-01 至 2012-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0750790&HistoricalAwards=false
• 关键词: Radar; Derived; Refractivity; Its; Impact

Fine-scale variations in atmospheric moisture near the earth's surface are thought to be pivotal to skillful forecasts of a variety of weather phenomena, most notably the initiation and subsequent evolution of severe thunderstorms. While networks of relatively dense direct surface observations by automated weather stations are of considerable value, cost and other practical considerations prevent their implementation on a sufficiently fine mesh so as to capture key moisture variations required to accurately anticipate the timing and location of thunderstorm development. Likewise, while emerging means to remotely sense atmospheric water vapor via satellite borne GPS-based technology hold promise for thermodynamic profiling at larger scales, they lack the resolution required for such detailed applications. Hence ground-based remote sensing techniques are viewed as a the most promising approach for mapping moisture variations on horizontal scales 10 km, even in quiescent pre-storm environments.Recent work has suggested that operational Doppler radars may have the ability to reliably measure the near-surface refractivity field (which relates to the propagation speed of radar signals through the atmospheric medium) that is in turn strongly dependent on atmospheric moisture content. These signals can be meaningfully interpreted only when they result from reflection (or more accurately, backscatter) by stationary ground targets immediately surrounding any given radar. The work supported here centers on a systematic exploration and evaluation of this refractivity technique as applied to a variety of operational ground-based radar platforms--both those presently in use (such as the WSR-88D/NEXRAD system) and on the drawing board (such as the NSF-supported CASA celltower-mounted prototype network). This study seeks to develop a flexible yet efficient "refractivity engine" that can be used to reliably map refractivity changes from a variety of radar platforms likely to be deployed over any given region. Experiments are planned for the 2008-2010 severe storm seasons using seven strategically located Doppler radars in Oklahoma. Advanced radar simulation techniques will also be developed to conduct statistical error analyses and determine the effective resolution (i.e. fineness of the resulting measurement mesh) effectively represented by actual radar refractivity measurements. In order to assess the meteorological impact of this information, the investigators will develop the framework necessary for optimal inclusion (aka assimilation) of refractivity data as input to numerical forecast models. Using both simulated and real observations, a systematic study will be conducted to assess the impact of refractivity measurements from various/selected platforms on forecasts of thunderstorm initiation, as well as the evolution of pre-existing storms and ultimate accuracy of quantitative precipitation forecasts.Broader impacts emerging from this work will include development of software/hardware tools potentially applicable to Doppler radar networks operating across the U.S., and could ultimately contribute to improved forecasting of severe storms and precipitation. This work will also support training a new generation of students in subjects such as advanced radar signal processing, data assimilation, and numerical modeling of storms.

地球表面附近大气湿度的细微尺度变化被认为是熟练预测各种天气现象的关键，最显著的是强烈雷暴的开始和随后的演变。虽然自动化气象站相对密集的直接地面观测网络具有相当大的价值，但成本和其他实际考虑因素使其无法在足够精细的网格上实施，以便捕捉准确预测雷暴发生的时间和地点所需的关键湿度变化。同样，虽然通过星载GPS技术遥感大气水蒸气的新兴手段有望在更大范围内进行热力学分析，但它们缺乏这种详细应用所需的分辨率。因此，地面遥感技术被认为是绘制10公里水平尺度上湿度变化的最有前途的方法，即使在风暴前的静止环境中也是如此。最近的工作表明，运行中的多普勒雷达可能具有可靠地测量近地表折射率场(与雷达信号通过大气介质的传播速度有关)的能力，而近地表折射率场又强烈依赖于大气湿度。只有当这些信号是由任何给定雷达周围的静止地面目标反射(或更准确地说，后向散射)产生时，才能有意义地解释这些信号。这里支持的工作重点是系统地探索和评估应用于各种作战陆基雷达平台的折射率技术--既有目前正在使用的平台(如WSR-88D/NEXRAD系统)，也有计划中的(如NSF支持的CASA蜂窝塔安装原型网络)。这项研究试图开发一种灵活而高效的“折射率引擎”，可以用来可靠地绘制可能部署在任何给定区域的各种雷达平台的折射率变化。俄克拉荷马州计划在2008-2010年的严重风暴季节使用七个战略位置的多普勒雷达进行试验。还将开发先进的雷达模拟技术，以进行统计误差分析，并确定实际雷达折射率测量有效代表的有效分辨率(即所产生的测量网格的精细程度)。为了评估这一信息对气象的影响，研究人员将制定必要的框架，以便将折射率数据作为数值预报模式的输入数据进行最佳纳入(又称同化)。利用模拟和实际观测，将进行一项系统的研究，以评估来自不同/选定平台的折射率测量对雷暴开始预报的影响，以及先前存在的风暴的演变和定量降水预报的最终准确性。这项工作产生的广泛影响将包括开发可能适用于美国各地的多普勒雷达网的软件/硬件工具，并最终可能有助于改进对强风暴和降水的预报。这项工作还将支持培训新一代学生学习高级雷达信号处理、数据同化和风暴数值模拟等学科。