Collaborative Research: Spatio-Temporal (4D) Atmospheric Environments of Jet Contrail Outbreaks for Potential Mitigation of their Climatic Impacts

合作研究：急流轨迹爆发的时空 (4D) 大气环境，以潜在减轻其气候影响

• 批准号: 0819396
• 负责人: David Travis
• 金额: $ 9万
• 依托单位: University of Wisconsin-Whitewater
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2013-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0819396&HistoricalAwards=false
• 关键词: Collaborative; Research; Spatio; Temporal; 4D

Aircraft-generated contrails and their resulting cirrus clouds may exacerbate climate warming in those areas characterized by frequent commercial flights. For the United States, the majority of persisting contrails occur as clusters, or "outbreaks", which can persist over relatively large regions (i.e. U.S. Midwest) for many hours. In particular, contrail outbreaks occurring in otherwise mostly clear skies significantly modify radiation and energy budgets, and help reduce the range of temperature in the lower atmosphere between day and night. Their study would allow for evaluating human influences on climatic factors. Recently, some airline companies and foreign governments have expressed a desire to reduce aviation impacts on the environment and climate, including those related to contrails. Realization of this goal requires both a fuller understanding of the space and time-scale characteristics of outbreaks, and an ability to forecast their occurrence in a timely manner, thus potentially permitting horizontal or vertical diversion of high-altitude flights around such areas. This research will determine the geographical and meteorological space and time scales of clear-sky contrail outbreaks through analysis of high resolution satellite imagery with data from composites of key meteorological variables near aircraft cruising altitudes stratified by season and by U.S. sub-regions. These analyses will form the basis for predictive (statistical) models of outbreaks with an eye towards their eventual use in operational forecasting. Geographic Information Systems will be used for both statistical model development---using conventional meteorological data, satellite cloud and moisture retrievals, and aviation data---and for validation of outbreak events conducted on independent data and time periods. Advanced geostatistical techniques will be applied to the imagery containing the outbreaks to simulate their removal and estimate resulting impacts on the radiation and energy budgets and surface temperature. The research also will further clarify the impacts of contrails on Earth surface temperatures and will demonstrate the potential value of implementing the models by focusing on an optimal subset of outbreaks for case study investigation.

飞机产生的尾迹及其产生的卷云可能会加剧商业航班频繁地区的气候变暖。对于美国来说，大多数持续存在的尾迹以集群或“爆发”的形式出现，可以在相对较大的地区（即美国中西部）持续数小时。特别是，在原本大部分晴朗的天空中发生的尾迹爆发会显着改变辐射和能量预算，并有助于缩小低层大气白天和夜间的温度范围。他们的研究将有助于评估人类对气候因素的影响。最近，一些航空公司和外国政府表示希望减少航空对环境和气候的影响，包括与凝结尾迹相关的影响。要实现这一目标，既需要更全面地了解疫情爆发的空间和时间尺度特征，又需要能够及时预测疫情的发生，从而有可能允许在这些地区周围的高空飞行进行水平或垂直改航。这项研究将通过分析高分辨率卫星图像以及按季节和美国次区域分层的飞机巡航高度附近关键气象变量的综合数据，确定晴空轨迹爆发的地理和气象空间和时间尺度。这些分析将构成疫情爆发预测（统计）模型的基础，并着眼于它们最终在业务预测中的应用。地理信息系统将用于统计模型开发（使用传统气象数据、卫星云和水分反演以及航空数据）以及根据独立数据和时间段验证爆发事件。先进的地统计技术将应用于包含爆发的图像，以模拟其消除并估计对辐射和能量预算以及表面温度的影响。该研究还将进一步阐明凝结尾迹对地球表面温度的影响，并将通过重点关注爆发的最佳子集进行案例研究调查来展示实施模型的潜在价值。