Estimation of cloud top height and effective cloud cover from infrared satellite soundings

The paper deals with a new method for simultaneous determination of cloud top height and effective cloud cover, using infrared radiance data of satellite-borne instruments. These cloud properties derived from the Selective Chopper Radiometer on the Nimbus 5 satellite are compared with nearly simultaneous observations by radiosondes and with satellite images. Encouraging results for Central-Europe during January, April, July, August and October 1974, as well as numerical simulations indicate that the method proposed here, would be useful also for global application. Another advantage of the described procedure are the small amount of computing time, and that no other data are required than 3 of infrared channel values, for each sounded spot.     

An estimation of the cooling process by infrared radiation in the atmosphere

Two procedure are presented for quantitative estimation of cloud cover (N), type of clouds (C), as well as base of clouds (C_b) and top of clouds (C^t) by using radiosonde data as well as satellite cloud pictures and radiation data. The data obtained in this way can be used as input data in the model for the estimation of the vertical profile of longwave radiative cooling.     

Statistical approaches to cloud classification

For the determination of clouds from satellite data there exist in general more unknown parameters than independent observations. If the bispectral observations are used from the geostationary satellites in the solar (VIS-channel) and in the infrared (IR-channel) range to derive cloud parameters, information is needed whether a pixel radiance is from a cloud free or a cloudy scene. Statistical methods are applied to derive those informations. Various proposed statistical methods are discussed.The histogram analysis developed at the University of Cologne is described in detail: bispectral (two-dimensional) histograms are partitioned into clusters. Cloud cover results are shown. A comparison is given between the results of the histogram analysis, threshold methods (VIS- and IR threshold separately and both combined) and the spatial coherence method developed by Coakly and Bretherton. The cloud cover varies in this example by a factor of two depending on the definition of the threshold between cloud free and cloudy pixels. It is further shown that after a cluster analysis of a two-dimensional histogram the derived cloud cover is not as sensitive to the threshold as for a threshold method. The methods which are discussed here are those proposed for the International Satellite Cloud Climatology Project (ISCCP). The results are from the pilot study of the ISCCP.     

Effects of concurrent snow and cloud cover on planetary albedo

The effects of snow and cloud cover on planetary albedo are examined using observations from NOAA polar orbiting satellites. Reflected radiation was measured in the visible range (0.5 – 0.7 μm). Planetary albedos resulting from different cloud/snow cover conditions are compared using Northern Hemisphere snow cover maps, surface weather charts, satellite photos and data on land surface types. None of the cases studied show that concurrent cloud and snow cover produces significantly different planetary albedos than cloud cover alone. Cloud cover alone is found to yield higher planetary albedos than snow cover alone; the difference being greatest over forested areas. With and without snow cover present, clear-sky planetary albedos over farming and grazing lands (snow(0.45), no snow(0.15)) are found to be significantly higher than those over forested regions (snow(0.33), no snow(0.11)). Variations in satellite zenith angle are not found to produce significant effects in most cases studied.     

Delineation of possible influence of solar variability and galactic cosmic rays on terrestrial climate parameters

The present paper has investigated the associations of solar activity (SA), represented by total solar irradiance (TSI), galactic cosmic rays (GCR) and terrestrial climate parameters in particular the global cloudiness and global surface temperature. To that end, we have analysed thirty five years (1983–2018) data of these parameters and have applied the Granger-causality test in order to assess whether there is any potential predictability power of one indicator to the other. The correlations among the involved parameters are tested using Vector Auto Regression (VAR) model and variance decomposition method. As a result of the above analysis, we have found that the TSI is an important factor and has contributed about 8.77 ± 0.42% in the cosmic ray intensity variations. In case of cloud cover variations, the other three parameters (TSI, cosmic ray and global surface temperature) have played a significant role. Further, the TSI changes have contributed 1.68 ± 0.03% fluctuations in the variance of the cloud cover while the cosmic ray intensity and global surface temperature have contributed about 4.89 ± 0.08% and 10.87 ± 1.41% respectively. In case of the global surface temperature anomaly both TSI and cloud covers have contributed about 5.07 ± 0.47% and 14.42 ± 2.13% fluctuations respectively. Additionally, we have also assessed the impact of internal climate oscillations like multivariate ENSO index (MEI), north Atlantic oscillations (NAO) and quasi biennial oscillations (QBO) on cloud cover variations. The contribution of these internal oscillations e.g. ENSO, NAO and QBO in cloud cover variation were reported as 7.48 ± 1.02%, 5.51 ± 0.16% and 1.36 ± 0.43% respectively.     

Monitoring global surface temperature variations using cloud data sets

One of the by-products of cloud data sets such as that of the International Satellite Cloud Climatology Project (ISCCP) is global information on longwave window brightness temperatures for clear skies. These brightness temperatures depend mainly on the actual surface temperature with only a slight dependence on atmospheric water vapor. Thus, it may be possible to monitor long-term temperature variations using such data. The current methods for such monitoring depend on conventional surface observations and are subject to uncertainties due to inadequate spatial sampling. To test this idea monthly clear sky brightness temperatures from the six-year Nimbus-7 cloud data set are analyzed and compared to conventional estimates of surface temperature fluctuations.     

A comprehensive statistical study of cloud base height using ceilometer over western India

A comprehensive statistical analysis of the cloud base height (CBH) measured by ground-based Vaisala ceilometer (CL31) has been performed to study different layers of the cloud in the lower troposphere up to 7.5?km height over Ahmedabad, western India during 2014 and 2015. The total observations (～69%) of cloud by using ceilometer show annual cloud occurrence frequency of around 64%. Seasonal variation of CBH and cloud occurrence frequency reveal that the maximum/minimum cloud cover is found during southwest (SW) Indian summer monsoon/pre-monsoon season. Three CBHs (CBH1, CBH2, and CBH3) are presented in monsoon period due to high cloud occurrence, and two CBHs (CBH1 and CBH2) are observed in other seasons due to low cloud occurrence by ceilometer over the observational site. The CBH1 (～100–2000?m) and CBH2 (500–3000?m) are observed during SW monsoon and summer season, respectively. The CBH3 is occurred usually in SW monsoon season. Moreover, the cloud cover during the day and night time shows that the occurrence of cloud is more frequent in daytime than nighttime during pre-monsoon and post-monsoon season. The statistical analysis of cloud with ground-based observations is also performed in this study that may be useful for the development/improvement of regional weather and climate models to reduce the uncertainty in the prediction.     

Remote sensing applications in the meteorology and operational hydrology programmes of WMO

Remote sensing from satellites continues to have a very large impact on the activities of the World Meteorological Organization (WMO) and continues to provide very great benefits to meteorological services throughout the world. Meteorological satellites provide remotely sensed data which can be converted into meteorological measurements such as cloud cover, cloud motion vectors, surface temperature, vertical profiles of atmospheric temperature and humidity, snow and ice cover, ozone and various radiation measurements. The meteorological satellites are part of the global operations of the World Weather Watch Programme which serves as the basic programme of the WMO by supporting other programmes and activities. Satellite measurements are critical to the success of many different components in the World Climate Programme. Special projects are being designed for the 1990s to take advantage of the data from satellite systems designed primarily to provide land or ocean observations. The Applications of Meteorology Programme makes use of remotely sensed data to provide products and services to agricultural, aeronautical and marine activities. The transfer of knowledge and technology in satellite remote sensing applications are important elements of the Technical Co-operation and the Education and Training Programmes.     

Remote sensing of clouds

The extraction of information on cloud cover from present-day multispectral satellite images poses a challenge to the remote sensing specialist. When approached one pixel at a time, the derived cloud cover parameters are inherently nonunique. More information is needed than is available in the radiances from each channel of an isolated pixel. The required additional information can be obtained for each scene, however, by analyzing the distribution of pixels in the multi-dimensional space of channel radiances. The cluster patterns in this space yield statistical information that points to the most likely solution for that scene. The geostationary and polar orbiting meteorological satellites all have, at a minimum, a solar reflection channel in the visible spectrum and a thermal infrared channel in the 8–12 micron window. With the information from the cluster patterns and application of the equations of radiative transfer, the measurements in those channels will yield cloud cover fraction, optical thickness, and cloud-top temperature for an assumed microphysical model of the cloud layer. Additional channels, such as the 3.7 micron channel on the AVHRR of the polar orbiting meteorological satellites, will will yield information on the microphysical model—e.g., distinguishing small liquid liquid droplets (typical of low level clouds) from large ice particles (typical of cirrus and the tops of cumulonimbus). New channels to be included in future satellite missions will provide information on cloud height, independent of temperature, and on a particle size and thermodynamic phase, independently of each other. A proposed STS mission using lidar will pave the way for the use of active sensors that will provide more precise information on cloud height and probe the structure of thin cirrus and the top layer of of the thicker cloud.     

基于卫星云图的大区域云层预测方法

云层覆盖是影响对地观测卫星成像的一个重要问题,如果遥感图像中云层比例太高,或者特定目标不可见,则遥感图像就会失效。对地观测卫星能够根据云层预测信息,在多个观测目标之间进行选择。面向对地观测卫星任务规划的应用,设计了大区域范围的短期云层预测方法,首先通过光流法获取云运动矢量,然后依据云运动矢量外推获得预测的云层图像,同时引入拉普拉斯算子刻画云层运动过程中的扩散现象,利用风云二号卫星的真实云图序列数据,通过神经网络的反向传播算法优化扩散因子,以提升云层预测的效果。通过对结果进行分析,引入的拉普拉斯算子方法能够提高云层预测的精度,80%分位数的云层覆盖率误差约为11.7%,该精度的云层预测可以用于指导对地观测卫星任务规划。     

1/3含口盖复合材料柱壳后屈曲性能

工程结构中复合材料柱壳已经得到了广泛使用,并且屈曲是其结构设计的一个主要问题。由于试验结果与线性屈曲理论分析结果的巨大偏差,线性特征值屈曲分析只能作为结构的一个初步评估方法,进一步分析可选用含初始几何缺陷的后屈曲分析。本文以轴压载荷下的1/3含口盖复合材料柱壳为研究对象,建立ABAQUS有限元模型,分别进行了基于Buckle算法的线性特征值屈曲分析、基于Riks法的含初始几何缺陷的非线性后屈曲分析,所得应变、载荷数值结果与试验结果吻合。非线性Riks后屈曲分析显示结构具有后屈曲承载能力和稳定的后屈曲平衡路径,能更准确地捕捉临界屈曲载荷,所得屈曲模态也更加贴近试验屈曲模态,因此,在设计上以含初始几何缺陷的Riks法得到的结果更加真实可靠。进行了含口盖复合材料柱壳的初始几何缺陷的敏感性分析,结果表明该结构对初始几何缺陷是非常敏感的,为了提高结构抗屈曲性能,应提高加工工艺质量,减少初始几何缺陷。     

面向战斗机云作战的构造型仿真平台架构

随着大数据、云计算、物联网、移动互联网等信息技术的迅猛发展与广泛应用,新的作战模式不断涌现,以任务分布式指控流程为核心的云作战成为一种全新的跨域全维作战样式。在分析作战云与云作战特征的基础上,结合传统作战仿真流程提出了云作战体系仿真流程,并提出了云作战构造型仿真平台框架的总体方案设计与系统功能设计。通过云作战构造型仿真示例,对比了传统作战样式与云作战样式的观察-调整-决策-行动（OODA）循环,结果表明,云作战样式能够有效缩短OODA循环时间。      

Robust extension of the simple sea-surface irradiance model to handle cloudy conditions for the global ocean using satellite remote sensing data

Sea-surface solar radiation (abbreviated as photosynthetically available radiation, PAR) in the visible wavelength (400–700 nm) is an essential parameter to estimate marine primary productivity and understanding phytoplankton dynamics, upper ocean physics and biogeochemical processes. Although many remote-sensing models were developed to estimate daily PAR (DPAR) from ocean colour data, these models often produce biases in the DPAR products under cloudy-sky and complex atmospheric conditions due to the lack of parameterization to deal with the cloud cover conditions and insufficient in-situ DPAR data. This study presents an Extended Sea-surface Solar Irradiance Model (ESSIM) for estimating DPAR over the global ocean. The ESSIM uses the direct and diffuse components from the Simple sea-surface Solar Irradiance Model (SSIM) along with a new parameter to handle cloudy conditions. The ESSIM produced DPAR products with greater accuracy under both clear and cloudy conditions. Its performance was tested on the time-series MODIS-Aqua images and compared with the concurrent in-situ data and the results from two global models. Results showed that the DPAR values produced by ESSIM agree with in-situ data better than the global models for all-sky conditions (with a mean relative error of 11.267 %; a root mean square error of 5.563 Em^?2day^?1; and a mean net bias of 2.917 Em^?2day^?1). The ESSIM performed slightly better than the SSIM for clear conditions and the Frouin's Operational Algorithm (FOA) for all-sky conditions. As the new parameterization accounts for cloudy conditions, the ESSIM produced more accurate results for cloud cover conditions across latitudes (up to 60°). The time-series Level-3 binned MODIS-Aqua data (global gridded) also demonstrated that the ESSIM improved the accuracy of DPAR products and produced spatially and temporally consistent DPAR products over the global ocean regardless of the seasons and sky conditions.     

A 3rd Order WENO GLM-MHD Scheme for Magnetic Reconnection

A new numerical scheme of 3rd order Weighted Essentially Non-Oscillatory (WENO)type for 2.5D mixed GLM-MHD in Cartesian coordinates is proposed. The MHD equations are modified by combining the arguments as by Dellar and Dedner et al to couple the divergence constraint with the evolution equations using a Generalized Lagrange Multiplier (GLM). Moreover, the magnetohydrodynamic part of the GLM-MHD system is still in conservation form. Meanwhile, this method is very easy to add to an existing code since the underlying MHD solver does not have to be modified. To show the validation and capacity of its application to MHD problem modelling,interaction between a magnetosonic shock and a denser cloud and magnetic reconnection problems are used to verify this new MHD code. The numerical tests for 2D Orszag and Tang's MHD vortex,interaction between a magnetosonic shock and a denser cloud and magnetic reconnection problems show that the third order WENO MHD solvers are robust and yield reliable results by the new mixed GLM or the mixed EGLM correction here even if it can not be shown that how the divergence errors are transported as well as damped as done for one dimensional ideal MHD by Dedner et al.      

The morphology of fair weather cumulus cloud fields as remotely-sensed from satellites and some applications

The morphology of fair weather Cumulus cloud field over several ocean areas distributed globally has been studied using LANDSAT data. Distribution functions of cloud size, spacing, perimeter and other relevant parameters have been derived, as well as their correlations and moments.Examples of distribution functions of cloud size, cloud spacing and fractal dimension of the cloud fields over oceanic areas are given and applied to several problem in Cu convection.     

Experiment for mapping land cover and it’s change in southeastern Sri Lanka utilizing 250 m resolution MODIS imageries

Utilizing freely available MODIS NDVI and Natural color imageries of 250 m spatial resolution produced by NASA, an experiment was made to map land-cover and its change with an emphasis on vegetation cover in southeastern Sri Lanka, which plays a vital role for control of green house gas. For the change detection purpose, 1987 land cover map made by present authors from Landsat MSS image and extensive ground truth survey data was used as the base map. The result of the experiment shows that MODIS data are useful to make a land cover map of 250 m spatial resolution for tropical areas with high cloud coverage like Sri Lanka. It was found that the forest cover decrease amounted as large as 21% in 19 years time span in southeastern Sri Lanka, the prominent forest region of the country. On the other hand homestead/vegetation and mixed vegetation/scrub dominant categories increased by 13.7% and 7.1%, respectively. These changes are considered due to a large clearance of forest areas for agriculture and building houses to accommodate increasing inhabitants.     

遥感图像云检测方法综述

光学遥感图像中云层会对地面信息进行不同程度的遮挡,造成了地表观测信息的模糊和缺失,极大地影响遥感图像的成像质量。因此,对遥感图像中云层覆盖的检测和评估是进一步分析和利用遥感图像信息的基础和关键。通过充分的调研和对比总结,梳理了20世纪90年代以来,国内外基于遥感图像的云检测方法的发展趋势和代表性工作。将基于遥感图像的云检测方法分为三类：基于光谱阈值的方法、基于经典机器学习的方法以及基于深度学习的方法。总结了当前国内外云检测公开数据集,并对比了部分代表性工作的云检测精度。此外,简要梳理了与云检测相关的云雾(霾)检测、云雪检测、云阴影检测以及云去除等方法。对当前云检测相关工作中存在的问题和未来的发展趋势进行了分析和展望。     

The possible applications of Meteosat for monitoring the rain season in the Sahel zone: The case of Senegal

The use of geostationary meteorological satellites for monitoring climate is relatively well known. However, the application of satellite data for agronomical purposes is still far form being operational. Recent work shows the possibility of establishing statistical models adapted to each region which can predict rain to within a time interval of 12 to 24 hours, based on the analysis of cloud cover. In the same way, thermal IR images may be used, employing the quasi-linear relationship between surface temperature and real evapotranspiration E.T.R. This is the objective of the project on monitoring the hydric balance in Senegal, associating INRA-IRAT and LERTS in France, ISRA and Meteorologie Nationale in Senegal. The first results obtained by Assad et al from two Meteosat images taken during 1979 establishing an inverse relationship between surface temperature and rain, over the total area of Senegal, were maintained for 16 images taken during the 1984 and 1985 rain period. Their analyses show that it is possible : - To identify the most favorable sowing periods, - to diagnose periods of high climatic risk for crops, and to cartograph rain distribution from spatial variations in surface temperature.     

磁云—高速流相互作用的数值模拟

对１９７８年８月２７至２８日期间观测到的磁云与尾随高速流的相互作用进行数值模拟，基本拟合了１ＡＵ处的观测剖面。模拟结果表明，磁云－高速流系统将导致前向快，慢激波和后向快激波的形成。