Towards Improving Hurricane Intensity Forecasts

改进飓风强度预测

• 批准号: 0553491
• 负责人: T. Krishnamurti
• 金额: $ 20万
• 依托单位: Florida State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-04-01 至 2008-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0553491&HistoricalAwards=false
• 关键词: Towards; Improving; Hurricane; Intensity; Forecasts

This study is centered around a suite of mesoscale models that are to be used for research on multi-model superensemble for the improvement of hurricane intensity forecasts. This research complements prior work on multi-model superensemble for hurricane tracks and intensity where a suite of large-scale models was used. The prior research demonstrated that the superensemble-based intensity forecasts are somewhat (~20%) superior to all of the participating member models. Since the intensity of a hurricane is expected to have mesoscale signatures, the notion that a suite of mesoscale models may prove to be very useful in this regard is being explored in this research. The recent multi-aircraft reconnaissance flights and the development of newer generation mesoscale models provide a unique opportunity for carrying out such experimentation. The component areas of science in this endeavor include: i) data assimilation within global and regional models, ii) prediction experiments from a suite of mesoscale models, iii) definition of the training and forecast phase of a mesoscale multi-model superensemble and iv) execution of forecasts for these phases. The intent is to examine superensemble based forecast validations and interpretations of model biases towards hurricane intensity predictions. Broader Impacts: Being able to provide improved hurricane intensity forecasts has major societal impacts. Hurricane Katrina is an excellent (however unfortunate) example where the hurricane modeling community faced a major challenge. Although atmospheric scientists cannot prevent the loss of life and property, they can work towards improving advance warning capabilities from improved modeling. The Principal Investigator will continue his long-standing cooperation with forecasters and researchers at the National Hurricane Center.

这项研究是围绕一套中尺度模式，将用于研究多模式超增强飓风强度预报的改进。 这项研究补充了以前的工作，多模式超级飓风的轨迹和强度，其中使用了一套大规模的模型。 先前的研究表明，基于超集合的烈度预测比所有参与的成员模型都有一定的上级优势（约20%）。 由于飓风的强度预计将有中尺度的签名，一套中尺度模型可能证明是非常有用的，在这方面的概念，在这项研究中正在探讨。最近的多飞机侦察飞行和新一代中尺度模型的开发为进行这种实验提供了一个独特的机会。 这一奋进的科学组成领域包括：i）全球和区域模式内的数据同化，ii）一套中尺度模式的预测实验，iii）中尺度多模式超级系统的训练和预报阶段的定义以及iv）这些阶段的预报执行。 其目的是研究基于超能量的预测验证和对飓风强度预测模型偏差的解释。更广泛的影响：能够提供更好的飓风强度预报具有重大的社会影响。 卡特里娜飓风是一个很好的例子（无论多么不幸），飓风建模社区面临着重大挑战。 虽然大气科学家无法防止生命和财产的损失，但他们可以通过改进模型来提高预警能力。 首席研究员将继续与国家飓风中心的预报员和研究人员进行长期合作。