应用小波收缩方法剔除MODIS热红外波段数据条带噪声

采用多元并扫方式 (1km分辨率 1 0元并扫 ,5 0 0m分辨率 2 0元并扫 ,2 5 0m分辨率 4 0元并扫 )的MODIS传感器由于各探测单元在轨响应差异而引起的条带噪声对MODIS定量产品的反演计算精度造成一定影响。这种影响在MODIS的热红外波段尤其明显。为了尽可能减少这种影响 ,提高MODIS定量产品反演精度 ,提出应用小波收缩方法剔除MODIS数据条带噪声。研究首先使用连续小波变换方法分析MODIS条带数据 ,确定MODIS数据条带噪声在小波系数域中的尺度。其次 ,在分析条带噪声模式的基础上 ,使用小波收缩方法对MODIS 1B数据进行噪声剔除计算。最后比较了分别使用噪声剔除前后的两组MODIS 1B数据反演得到的部分云和大气定量遥感产品 ,结果表明 ,使用剔除噪声后的MODIS

第4章 地球大气的卫星观测

卫星气象学是大气科学中的一个相对较新的分支。该领域出现在20世纪50年代末的冷战时期,它建立在二战后火箭技术发展的基础上。在不到70年的时间里,卫星观测改变了科学家观察和研究地球的方式。本文将讨论我们在理解卫星观测能量和水循环、天气预报和大气成分方面的一些关键进展。虽然卫星气象学的发展离不开世界各国的推动,但在有限篇幅的美国百年气象学会纪念文集上,本文的重点是介绍美国在这方面的成就。

INVESTIGATING THE ROLE OF THE UPPER-LEVELS IN TROPICAL CYCLONE GENESIS

Despite decades of theoretical research and observational studies, a good understanding of tropical cyclone genesis(TCG) remains elusive. One school of theories proposes that TCG within an African Easterly Wave results from “bottom-up” development of cyclonic vorticity that is contingent upon favorable conditions in the lower-troposphere and boundary layer. Our observational study suggests that while lower-tropospheric forcing is a necessary condition for this type of TCG, it may not be sufficient in some cases, and that environmental conditions in the upper levels can have an influence. Specifically, we find evidence to suggest that pre-TCG upper-tropospheric flow patterns characterized by core-connecting outflow vents to the environment can in certain situations provide a modulating effect on Atlantic tropical disturbances trying to develop. Patterns of nearenvironment upper-level inertial stability, divergence, outflow setup, and mass evacuation are identified and related to surface development. The study employs high-resolution satellite-derived wind data, aircraft GPS dropwindsondes, composite fields, multivariate objective analyses, and case studies to help identify conditions in the upper-level environment that can play a role in Atlantic TCG events.

Analysis of air quality variability in Shanghai using AOD and API data in the recent decade

We use the aerosol optical depth （AOD） measured by the moderate resolution imaging spectrometer （MOD1S） onboard the Terra satellite, air pollution index （API） daily data measured by the Shanghai Environmental Monitoring Center （SEMC）, and the ensemble empirical mode decomposition （EEMD） method to analyze the air quality variability in Shanghai in the recent decade. The results indicate that a trend with amplitude of 1.0 is a dominant component for the AOD variability in the recent decade. During the World Expo 2010, the average AOD level reduced 30% in comparison to the long-term trend. Two dominant annual components decreased 80% and 100%. This implies that the air quality in Shanghai was remarkably improved, and environmental initiatives and comprehensive actions for effective. AOD and API reducing air pollution are variability analysis results indicate that semi-annual and annual signals are dominant components implying that the monsoon weather is a dominant factor in modulating the AOD and API variability. The variability of AOD and API in selected districts located in both downtown and suburban areas shows similar trends; i.e., in 2000 the AOD began a monotonic increase, reached the maxima around 2006, then monotonically decreased to 2011 and from around 2006 the API started to decrease till 2011. This indicates that the air quality in the entire Shanghai area, whether urban or suburban areas, has remarkably been improved. The AOD improved degrees （IDS） in all the selected districts are （8.6±1.9）%, and API IDS are （9.2±7.1）%, ranging from a minimum value of 1.5% for Putuo District to a maximum value of 22% for Xuhui District.

Towards an objective historical tropical cyclone dataset for the Australian region

The appropriate design of infrastructure in tropical cyclone(TC)prone regions requires an understanding of the hazard risk profile underpinned by an accurate,homogenous long-term TC dataset.The existing Australian region TC archive,or’best track’(BT),suffers from inhomogeneities and an incomplete long-term record of key TC parameters.This study assesses mostly satellite-based objective techniques for 1981-2016,the period of a geostationary satellite imagery dataset corrected for navigation and calibration issues.The satellite-based estimates of Australian-region TCs suffer from a general degradation in the 1981-1988 period owing to lower quality and availability of satellite imagery.The quality of the objective techniques for both intensity and structure is compared to the reference BT 2003-2016 estimates.For intensity the Advanced Dvorak Technique algorithm corresponds well with the BT 2003-2016,when the algorithm can use passive microwave data(PMW)as an input.For the period prior to 2003 when PMW data is unavailable,the intensity algorithm has a low bias.Systematic corrections were made to the non-PMW objective estimates to produce an extended(1989-2016)homogeneous dataset of maximum wind that has sufficient accuracy to be considered for use where a larger homogeneous sample size is valued over a shorter more accurate period of record.An associated record of central pressure using the Courtney-Knaff-Zehr wind pressure relationship was created.For size estimates,three techniques were investigated:the Deviation Angle Variance and the’Knaff’techniques(IR-based),while the’Lok’technique used model information(ECMWF reanalysis dataset and TC vortex specification from ACCESS-TC).However,results lacked sufficient skill to enable extension of the reliable period of record.The availability of scatterometer data makes the BT 2003-2016 dataset the most reliable and accurate.Recommendations regarding the best data source for each parameter for different periods of the record are summarised.

Analysis of spatio-temporal variability of aerosol optical depth with empirical orthogonal functions in the Changjiang River Delta, China

This work aims to analyze the spatial and temporal variability of aerosol optical depth （AOD） from 2000 to 2012 in the Changjiang River Delta （CRD）, China. US Terra satellite moderate resolution imaging spectroradiometer （MODIS） AOD and Angstrom exponent （a） data constitute a baseline, with the empirical orthogonal functions （EOFs） method used as a major data analysis method. The results show that the maximum value of AOD observed in June is 1.00±0.12, and the lowest value detected in December is 0.40±0.05. AOD in spring and summer is higher than in autumn and winter. On the other hand, the a-value is lowest in spring （0.86±0.10）, which are affected by coarse particles. High a-value appears in summer （1.32±0.05）, which indicate that aerosols are dominated by fine particles. The spatial distribution of AOD has a close relationship with terrain and population density. Generally, high AODs are distributed in the lowlying plains, and low AODs in the mountainous areas. The spatial and temporal patterns of seasonal AODs show that the first three EOF modes cumulatively account for 77% of the total variance. The first mode that explains 67% of the total variance shows the primary spatial distribution of aerosols, i.e., high AODs are distributed in the northern areas and low AODs in the southern areas. The second mode （7%） shows that the monsoon climate probably plays an important role in modifying the distribution of aerosols, especially in summer and winter. In the third mode （3%）, this distribution of aerosols usually occurs in spring and winter when the prevailing northwestern or western winds could bring aerosol particles from the inland areas into thecentral regions of the CRD.