Coupled Clouds and Chemistry of the Giant Planets— A Case for Multiprobes

In seeking to understand the formation of the giant planets and the origin of their atmospheres, the heavy element abundance in well-mixed atmosphere is key. However, clouds come in the way. Thus, composition and condensation are intimately intertwined with the mystery of planetary formation and atmospheric origin. Clouds also provide important clues to dynamical processes in the atmosphere. In this chapter we discuss the thermochemical processes that determine the composition, structure, and characteristics of the Jovian clouds. We also discuss the significance of clouds in the big picture of the formation of giant planets and their atmospheres. We recommend multiprobes at all four giant planets in order to break new ground.     

The Changing Face of Titan’s Haze: Is it all Dynamics?

Titan’ atmosphere shows some similarities with that of the Earth, in terms of composition and surface pressure. Also, its seasonal cycle is similar, as Titan’ obliquity is about 27^°(23^°,5 for the Earth), although it is about 30 times as long. Titan’ haze exhibits an albedo contrast (NSA for North-South Asymmetry) that is changing seasonally. From the analysis of Voyager and Hubble Space Telescope data, we learned that at short visible wavelengths, the albedo of the winter hemisphere is lower by 10-20% than that of the summer hemisphere. This asymmetry peaks at 450 nm and reaches maximum amplitude around Titan’ equinoxes. It reverses in about five years, faster than a season which spans seven years. At longer wavelengths, longward of 700 nm, the asymmetry is inverted. The NSA reversal process in the red and in the UV seems to lead the reversal in the blue by 1 or 2 years. No valid explanation exists for this lag, at least in the red. The results from a recent model which couples atmospheric dynamics, haze microphysics and transport, as well as photochemistry, show that the NSA and its seasonal changes can be explained by an accumulation of haze particles at the winter pole. This is due to the pole-to-pole Hadley circulation pattern that is present during most of Titan’ year and rapidly disrupts at the time of the equinoxes. This model can also explain the observed cooler stratospheric temperatures and higher abundances of heavy hydrocarbons and nitriles in the winter polar region. In addition, it provides a mechanism for the formation of a detached haze layer around 300–400 km altitude, as well as the existence of a polar hood. Thus, it appears that the latitudinal contrasts we observe on Titan are conveniently tracing for us the dynamical behavior of its atmosphere.     

基于深度学习的日间逐小时地表PM2.5浓度反演

以长三角地区作为研究区域,提出了使用深度学习算法来实现主被动遥感数据结合反演地表PM2.5浓度的方法。基于MPL观测数据,使用雾霾层高度(HLH)替换了边界层高度(BLH)特征,对已有的基于气溶胶光学厚度(AOD)结合大气BLH来反演PM2.5浓度的算法进行了改进。为提高数据覆盖率,对研究区域内的MAIAC AOD进行了填补与评估。利用多种机器学习算法实现了日间逐小时的PM2.5浓度估算,模型验证相关性最高可达0.87。该方法能够为观测气候变化、应对大气污染提供有效帮助。     

海上雾霾天气下基于能见度的舰载机目视着舰风险评估方法研究

针对雾霾天气对舰载机目视着舰安全性的影响难以量化的问题,利用激光雷达在近海的能见度观测数据,反演海上雾霾天气下飞行员目视着舰的斜程能见度的状况,提出 1种基于能见度指标的目视着舰风险评估方法,将舰载机着舰过程中飞行员频繁的目测压力,转变为舰上数据测量、风险评估和应对措施等程序化工作,将定性的安全分析转变为定量的风险评估和安全指导,谋求在现有着舰控制模式下有效降低飞行员着舰压力,提升指挥引导效率,为低能见度下舰载机目视着舰训练提供理论依据和实践指导。     

透光率/雾度仪校准结果的不确定度评定

主要讨论了透光率/雾度仪的校准方法,并对校准结果的测量不确定度进行了评定.     

MRF模型去雾算法在机场场面监视中的应用

面对日益严峻的雾霾天气对民航业的影响,在雾霾天气下的机场场面监视方面,文章提出了一种基于MRF模型的去雾霾算法,并利用CNC去雾霾效果评价体系与Retinex、He等传统去雾霾算法的去雾效果进行了对比,可以看出,MRF模型去雾霾算法对场面监视的雾霾图像具有较好的效果性和鲁棒性。