冰核观测中两种滤膜采样方法的比较

大气冰核观测是研究自然冷云降水和人工影响天气的一项基础性工作,滤膜—扩散云室法是观测冰核浓度的主要方法之一。为检测分析两种滤膜采集方法对冰核观测结果的影响,2011—2015年用自制的大气颗粒物采样器和FA-3型撞击式9级采样器开展了平行采样试验,采集的滤膜样本均在同一静力扩散云室中进行冰核活化显现分析。结果表明：自制采样器较9级采样器观测的冰核浓度高数倍甚至数十倍,但两者随季节和不同气象条件的变化表现出一致的起伏特征。自制采样器适用于对大气中总的冰核浓度分布及理化特征研究;9级采样器适用于对PM₁₀中不同粒径段大气冰核浓度和尺度分布以及理化特征的研究。滤膜法对冰核数量的低估与采样体积成正比,改变采样器气泵的抽气流量和控制采样体积对改进“体积效应”影响均有明显效果。     

大气水分循环方程

任何地点的降水量可能来自地球的任何地点的水分蒸发。为了定量描述大气中的这种水分循环的复杂过程,我们引入了两个概念性的工具:大气水分辐合函数和大气水分辐散函数,并且建立了用它们描述大气水分循环的方程组。     

野外科学观测研究台站（网络）和科学数据中心建设发展

中国科学院地理科学与资源研究所成立80年来,十分重视野外台站（网络）和科学数据中心的建设,取得了辉煌成就。研究所建立了4个野外观测研究网络,引领了中国生态系统研究网络的建设与发展;成立了2个国家级科学数据中心,1个中国科学院数据中心,1个数据出版系统并于2016年加入了世界数据系统;拥有2个国家级野外观测研究站,1个中国科学院野外研究站,形成了独具特色的野外观测研究平台和数据共享服务平台。本文回顾了中国生态系统研究网络、国家生态系统观测研究网络、中国通量观测研究网络、中国物候观测网和禹城站、拉萨站、千烟洲站以及地球系统科学数据中心、生态科学数据中心、资源环境科学数据中心和全球变化科学研究数据出版系统的发展历程。地理资源所台站（网络）从无到有,不断发展壮大,引领了中国野外观测研究事业的发展,支撑了地理学、生态学等重要科学成果产出,科技支撑能力和示范能力大幅提升,有力支撑了华北平原、青藏高原以及南方山地丘陵区的生态文明建设;成为中国地球系统科学、野外台站、资源环境等学科和领域最大的科学数据汇聚中心,数据共享服务成效显著,在国内外具有广泛影响力。在未来发展中,地理资源所将充分发挥野外台站（网络）综合中心作用,强化生态系统、碳水通量、物候等观测研究网络的能力建设,稳步提升野外观测研究站条件保障能力和科学数据中心的数据汇聚能力、分析挖掘能力以及共享服务能力,持续推动和引领中国科学数据的共享,在科学研究和支撑国家需求等方面做出更大贡献。     

自然地理学创新发展与展望

自然地理学自中国科学院地理科学与资源研究所建立以来一直是立所的核心学科,长期以服务国家重大需求为使命,在综合自然地理、气候、地貌、水文、土壤地理、生物地理、化学地理等各学科领域取得一批重要科技成果和进展,奠定了自然地理各分支学科在国内外的优势,为国家科技创新、区域经济社会可持续发展做出了重要贡献。本文回顾了中国科学院地理科学与资源研究所自然地理学的创新发展历程,总结了自然地理学取得的学术成就与标志性进展,并展望了中国科学院地理科学与资源研究所自然地理学未来发展,提出以陆地表层要素—过程交互作用机制,陆地表层格局动态研究,陆地表层系统过程的综合集成与模拟,陆地表层系统有序人类活动的可持续范式和调控机制为核心的发展战略。     

中国科学院地质研究所的成立与中央地质调查所的传承

1913年成立的中央地质调查所(成立时称农商部地质调查所)是中国建立的第一个国家级科研机构,代表了中国现代科学的起始,在中国现代科学发展史上具有举足轻重的地位.在它成立后的几十年间,中央地质调查所在区域地质调查、矿产资源勘查、大地构造学、地震学、土壤学、古生物与古人类学等众多领域,取得了一系列举世瞩目的学术成就,是民国...     

Detection of coffee berry necrosis by digital image processing of landsat 8 oli satellite imagery

Coffee berry necrosis is a fungal disease that, at a high level, significantly affects coffee productivity. With the advent of surface mapping satellites, it was possible to obtain information about the spectral signature of the crop on a time scale pertinent to the monitoring and detection of plant phenological changes. The objective of this paper was to define the best machine learning algorithm that is able to classify the incidence CBN as a function of Landsat 8 OLI images in different atmospheric correction methods. Landsat 8 OLI images were acquired at the dates closest to sampling anthracnose field data at three times corresponding to grain filling period and were submitted to atmospheric corrections by DOS, ATCOR, and 6SV methods. The images classified by the algorithms of machine learning, Random Forest, Multilayer Perceptron and Naive Bayes were tested 30 times in random sampling. Given the overall accuracy of each test, the algorithms were evaluated using the Friedman and Nemenyi tests to identify the statistical difference in the treatments. The obtained results indicated that the overall accuracy and the balanced accuracy index were on an average around 0.55 and 0.45, respectively, for the Naive Bayes and Multilayer Perceptron algorithms in the ATCOR atmospheric correction. According to the Friedman and Nemenyi tests, both algorithms were defined as the best classifiers. These results demonstrate that Landsat 8 OLI images were able to identify an incidence of the coffee berry necrosis by means of machine learning techniques, a fact that cannot be observed by the Pearson correlation.     

Astronomical Image Co-adding Method based on Wide-field Image Deconvolution

Due to the atmospheric turbulence, the static aberration, tracking and pointing errors of telescopes, the point spread functions (PSFs) in different fields of view are different. Meanwhile, there are different PSFs in the images obtained by different telescopes. The quality of co-adding image is limited by the image with the poorest quality, and finally the resolution and sensitivity of the quad-channel telescope will also be affected. Dividing the image into some regions with the same type of PSF, and deconvolving these regions can improve the quality of the co-adding image. According to this theory, an image restoration algorithm based on the PSF clustering is proposed. Firstly, this paper makes the PSF clustering analysis by using Self-Organizing Maps, and makes the image segmentation based on the result of the PSF clustering analysis, then using the clustered PSFs to make deconvolutions on the sub-images. Then, the restored sub-images after deconvolution are joined together. Finally, by through the image registration and co-adding, the image with a high signal to noise ratio can be obtained. The result shows that the signal to noise ratio of the astronomical images are improved with our method, and the detection capability on faint stars is also improved.     

1951—2018年衢州市椪柑采摘期连阴雨天气变化特征

基于1951—2018年衢州市椪柑采摘期降水量、雨日、日照时数、相对湿度等逐日气象资料,应用统计分析和小波分析方法,分析椪柑采摘期连阴雨天气变化特征及其大气环流背景.结果表明:1951—2018年衢州椪柑采摘期连阴雨日数、次数和强度呈略微增加趋势、滑动3d无雨次数呈减少趋势;滑动3d无雨次数存在明显的5a、7a和15a...     

Characterization of diurnal cycles in ZTD from a decade of global GPS observations

The diurnal cycle of the tropospheric zenith total delay (ZTD) is one of the most obvious signals for the various physical processes relating to climate change on a short time scale. However, the observation of such ZTD oscillations on a global scale with traditional techniques (e.g. radiosondes) is restricted due to limitations in spatial and temporal resolution. Nowadays, the International GNSS Service (IGS) provides an important data source for investigating the diurnal and semidiurnal cycles of ZTD and related climatic signals. In this paper, 10 years of ZTD data from 1997 to 2007 with a 2-hour temporal resolution are derived from global positioning system (GPS) observations taken at 151 globally distributed IGS reference stations. These time series are used to investigate diurnal and semidiurnal oscillations. Significant diurnal and semidiurnal oscillations of ZTD are found for all GPS stations used in this study. The diurnal cycles (24 hours period) have amplitudes between 0.2 and 10.9 mm with an uncertainty of about 0.5 mm and the semidiurnal cycles (12 h period) have amplitudes between 0.1 and 4.3 mm with an uncertainty of about 0.2 mm. The larger amplitudes of the diurnal and semidiurnal ZTD cycles are observed in the low-latitude equatorial areas. The peak times of the diurnal cycles spread over the whole day, while the peak value of the semidiurnal cycles occurs typically about local noon. These GPS-derived diurnal and semidiurnal ZTD signals are similar with the surface pressure tides derived from surface synoptic pressure observations, indicating that atmospheric tides are the main driver of the diurnal and semidiurnal ZTD variations.     

珠江口二类水体水色三要素的优化反演

根据2003年1月份珠江口实测资料获得了适合该海域的相关参数,建立了适用于该海域的二类水体水色三要素优化反演模型,同步优化反演得到了与2003年1月25～26日实测站点相对应的2003年1月29日的SeaWiFs图像像元点的水色三要素,反演与实测水色三要素的平均相对误差分别为：叶绿素14．9％,悬浮泥沙12．1％,黄色物质13．6％。研究结果说明本研究建立的优化反演模型比较适用于珠江口二类水体水色三要素的反演,且具有较高的反演精度。