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: 0819416
• 负责人: Andrew Carleton
• 金额: $ 11万
• 依托单位: Pennsylvania State Univ University Park
• 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=0819416&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.

飞机产生的轨迹及其产生的卷云可能会加剧以商业飞行频繁为特征的地区的气候变暖。对美国来说，大多数持续的轨迹是以集群或“爆发”的形式出现的，可以在相对较大的地区(即美国中西部)持续数小时。特别是，在其他大部分晴朗的天空中爆发的轨迹极大地改变了辐射和能量收支，并有助于缩小低层大气白天和夜间的温度范围。他们的研究将允许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达了减少航空对环境和气候的影响的愿望，包括与轨迹有关的影响。实现这一目标既需要更充分地了解疫情的空间和时间尺度特征，也需要能够及时预测疫情的发生，从而有可能使高空飞行在这些地区周围水平或垂直改道。这项研究将通过对高分辨率卫星图像的分析，利用飞机巡航高度附近按季节和美国分地区分层的关键气象变量合成数据，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预测(统计)模型的基础，着眼于它们最终在业务预测中的使用。地理信息系统将用于建立统计模型-使用常规气象数据、卫星云和湿度反演以及航空数据-以及验证根据独立数据和时间段进行的疫情事件。将对含有疫情的图像应用先进的地质统计学技术，以模拟其清除情况，并估计由此对辐射和能量收支以及地表温度造成的影响。这项研究还将进一步阐明尾迹对地球表面温度的影响，并将通过侧重于病例研究调查的最佳暴发子集来证明实施这些模型的潜在价值。