美国的云卫星

美国的云卫星(CloudSat)是美国宇航局地球系统科学探路者(ESSP)计划的一部分,它是一项多卫星、多敏感器实验,这是美国为了测量用现有卫星测量系统无法获得的那些云特性而设计的。它将于2004年与云气溶胶激光雷达和红外探路者卫星观测任务(CALIPSO)一同发射。下面就这颗云卫星的科学目标、测量目标、编队飞行、有效载荷以及运行轨道等内容作一简要介绍。

西北太平洋主要云类型光学厚度的时空分布特征

本文利用CloudSat数据处理中心发布的二级云分类产品和云光学厚度产品,对西北太平洋上空主要云类型光学厚度的空间分布和季节变化特征进行了系统研究。使用云分类产品数据获得了西北太平洋上8类云的云量时空分布,以此为依据选择出云量较高的5类主要云。将二级云光学厚度产品中的数据与5类主要云类型进行匹配,获得了西北太平洋上主要云类型的平均光学厚度的空间分布及其季节变化特征。结果表明:西北太平洋上主要云类型的平均光学厚度分别为,高云约3~9,高层云约13~25,高积云约5~25,层积云约5~40,积云约5~30。各类云的光学厚度高值区主要分布在高纬度海域以及大洋西北尤其中国东部沿海海域,光学厚度低值主要分布在低纬度海域及信风带附近。此外,各类云的光学厚度在低纬度海域上季节变化幅度小,高纬度海域变化幅度大。以上结果可用于分析该区域不同地点及季节跨介质海洋激光通信系统的可通率,也可用于评估该区域可见光对海观测系统的探测能力等。

星载毫米波云雷达反演液态水云含水量的算法性能分析

为了充分了解毫米波雷达遥感液态水云微物理参数的性能,介绍了一种基于最优估计理论从星载毫米波雷达反演液态水云微物理参数的方法,并通过模拟试验对算法性能做了初步分析。模拟分析表明,假定云中粒子半径的垂直分布不均一,而数密度和谱宽分布均一,当观测不确定度等于1.5 dBZ时,整层廓线几何平均半径、数密度、谱宽以及液态水含量LWC(liquid water content)的相对不确定度分别为:13%、59%、15%和50%。各谱参数之间存在着一定的相关性,在计算LWC不确定性时,考虑这种互相关性可以使廓线的反演不确定度显著减小。介绍了联合雷达反射率和可见光厚度信息反演云微物理参数的方案。对比试验表明,不同的参数假定方案下,联合反演方法对反演结果的影响不同。若假定云中粒子半径的垂直分布不均一,而数密度和谱宽分布均一,则联合反演方法可使LWC反演不确定度从50%减小到27%;而若假定云中3个参数的垂直分布均不均一,联合反演对于结果的改进相对较小,仅从50%减小到了48%。

RESEARCH ON SATELLITE IMAGE PROCESSING AND RECOGNITION WITH PARALLEL ALGORITHM

Using the method of mathematical morphology,this paper fulfills filtration,segmentation and extraction of morphological features of the satellite cloud image.It also gives out the relative algorithms,which is realized by parallel C programming based on Transputer networks.It has been successfully used to process the typhoon and the low tornado cloud image.And it will be used in weather forecast.

High Performance of Imaging Extraction for Infrared Satellite Cloud Image

The isotherm is an important feature of infrared satellite cloud images (ISCI), which can directly reveal substantial information of cloud systems. The isotherm extraction of ISCI can remove the redundant information and therefore helps to compress the information of ISCI. In this paper, an isotherm extraction method is presented. The main aggregate of clouds can be segmented based on mathematical morphology. T algorithm and IP algorithm are then applied to extract the isotherms from the main aggregate of clouds. A concrete example for the extraction of isotherm based on IBM SP2 is described. The result shows that this is a high efficient algorithm. It can be used in feature extractions of infrared images for weather forecasts.

Comparison of CloudSat Cloud Liquid Water Paths in Arctic Summer Using Ground-Based Microwave Radiometer

Arctic clouds strongly influence the regional radiation balance, temperature, melting of sea ice, and freezing of sea water. Despite their importance, there is a lack of systematic and reliabie observations of Arctic clouds. The CloudSat satellite launched in 2006 with a 94GHz Cloud Profiling Radar （CPR） may contribute to close this gap. Here we compare one of the key parameters, the cloud liquid water path （LWP） retrieved from CloudSat observations and from microwave radiometer （MWR） data taken during the ASCOS （Arctic Summer Cloud Ocean Study） cruise of the research vessel Oden from August to September 2008. Over the 45 days of the ASCOS cruise, collocations closer than 3 h and 100 km were found in only 9 d, and collocations closer than 1 h and 30 km in only 2 d. The poor correlations in the scatter plots of the two LWP retrievals can be explained by the patchiness of the cloud cover in these two days （August 5th and September 7th）, as confirmed by coincident MODIS （Moderate-resolution Imaging Spectroradiome- ter） images. The averages of Oden-observed LWP values are systematically higher （40-70 g m-2） than the corresponding CloudSat observations （0-50 g m2）. These are cases of generally low LWP with presumably small droplets, and may be explained by the little sensitivity of the CPR to small droplets or by the surface clutter.

Using Satellite Data to Analyze the Initiation and Evolution of Deep Convective Clouds

In this study, two deep convective cloud cases were analyzed in detail to study their initiation and evolution. In both cases, all deep convective clouds were positioned at the rear of the cold front cloud bands and propagated backward. Satellite data showed that prior to initiation of the deep convective clouds, thermodynamic and moist conditions were favorable for their formation. In the morning, a deep convective cloud at the rear of cold front cloud band propagated backward, the outflow boundary of which created favorable conditions for initiation. An additional deep convective cloud cluster moved in from the west and interacted with the outflow boundary to develop a mesoscale convective system(MCS) with large, ellipse-shaped deep convective clouds that brought strong rainfall. The initiation and evolution of these clouds are shown clearly in satellite data and provide significant information for nowcasting and short-term forecasting.

An Observational Study of Typhoon Imbudo in 2003

Typhoon Imbudo was a super-typhoon over the northwestern Pacific in 2003. It caused tremendous damage when it made landfalls in the Philippines and China. This paper documents observational analyses of Typhoon Imbudo during its landfall in China. All available observations are used to study its motion, intensity changes, convection, structure and precipitation. Best-track data indicate that Imbudo moved west-northwestward until 1800 UTC 23 July and then turned northwestward. FNL (final) analysis data show that the motion of Imbudo is dominated by changes of the subtropical high. At Imbudo's mature stage, the minimum sea level pressure dropped to 910 hPa and the maximum sustained winds were as high as 67 m s 1, which is the intensity of a super-typhoon. The surface wind field exhibited asymmetric characteristics. Polar-orbiting satellite imagery also manifested convective asymmetry before Imbudo made landfall in China. Analyzed the vertical wind shear, it is shown that the convection has a downshear-left pattern. All kinds of precipitation data were used to identify the asymmetric characteristic of the rainfall associated with the Imbudo. The maximum rainfalls were located in the southern boundary area between Guangxi and Guangdong. However, the lack of in situ observations limited further analyses of this typhoon.

Local Spiral Curves Simulating Based on Hough Transformation and Center Auto-Locating of Developing Typhoon

In the developing phase of typhoon formation, the spiral belt partly emerges in satellite cloud images. This research starts from images and moves on to graphics and then to representation and recognition. Following this route, local spiral cloud belt is segmented from the raw images using image segmentation, the spiral information is extracted using mathematic morphology, and local spiral curves are detected using Hough transformation. The problem of center locating of developing typhoon has finally been solved through a search algorithm of spiral curve. For No. 99082008 cloud image, the result produced by the algorithm in this paper is at 122..3 degree west longitude, 117.5 degree north latitude. The real typhoon center location was at 122.4 degree west longitude, 18 degree north latitude.

Study on Causes of a Local Heavy Rainstorm Process in Shandong Province

Based on conventional meteorological observation data, NECP 1°×1° reanalysis data, precipitation data from automatic weather stations on the ground, FY- 2E satellite cloud images, and so forth, the circulation background, formation mechanism and features of a satellite cloud image of a local heavy rainstorm process in Shandong Province during August 8-9 in 2010 were analyzed. The results showed that the slow eastward movement of short-wave trough at middle and high latitudes, the stable maintenance of the subtropical high and ground cyclone, and the strong development of extra low-level southeast flow were large-scale circulation back- grounds of occurrence of the rainstorm; the rainstorm generated under the effects of mesoscale echo clusters or echo belts and mesoscale convective cloud clusters; precipitation mainly happened in periods when convective cloud clusters generated, developed and matured, and short-time heavy precipitation mainly appeared in the west, southwest and south of convective cloud clusters; extra low-level southeast flow was very conducive to the occurrence of short-time heavy precipitation; mesoscale convective systems rose in the whole troposphere, and the constant enhancement of low-level θse frontal zone provided favorable unstable energy for the occurrence of convective heavy rainfall.

Preliminary Evaluation of Cloud Fraction Simulations by GAMIL2 Using COSP

The Cloud Feedback Model Intercomparisons Project (CFMIP) Observation Simulator Package (COSP) is adopted in the Grid-point Atmospheric Model of IAP LASG (GAMIL2) during CFMIP at Phase II to evaluate the model cloud fractions in a consistent way with satellite observations. The cloud simulation results embedded in the Atmospheric Model Intercomparison Project (AMIP) control experiment are presented using three satellite simulators: International Satellite Cloud Climatology Project (ISCCP), Moderate Resolution Imaging Spectroradiometer (MODIS), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar onboard the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Overall, GAMIL2 can produce horizontal distributions of the low cloud fraction that are similar to the satellite observations, and its similarities to the observations on different levels are shown in Taylor diagrams. The discrepancies among satellite observations are also shown, which should be considered during evaluation.

A Case Study of Impact of FY-2C Satellite Data in Cloud Analysis to Improve Short-Range Precipitation Forecast

Chinese FengYun-2C(FY-2C) satellite data were combined into the Local Analysis and Prediction System(LAPS) model to obtain three-dimensional cloud parameters and rain content. These parameters analyzed by LAPS were used to initialize the Global/Regional Assimilation and Prediction System model(GRAPES) in China to predict precipitation in a rainstorm case in the country. Three prediction experiments were conducted and were used to investigate the impacts of FY-2C satellite data on cloud analysis of LAPS and on short range precipitation forecasts. In the first experiment, the initial cloud fields was zero value. In the second, the initial cloud fields were cloud liquid water, cloud ice, and rain content derived from LAPS without combining the satellite data. In the third experiment, the initial cloud fields were cloud liquid water, cloud ice, and rain content derived from LAPS including satellite data. The results indicated that the FY-2C satellite data combination in LAPS can show more realistic cloud distributions, and the model simulation for precipitation in 1–6 h had certain improvements over that when satellite data and complex cloud analysis were not applied.

Remote Sensing Monitoring of Tobacco Field Based on Phenological Characteristics and Time Series Image―A Case Study of Chengjiang County, Yunnan Province, China

Using three-phase remote sensing images of China-Brazil Earth Resources Satellite 02B (CBERS02B) and Landsat-5 TM, tobacco field was extracted by the analysis of time series image based on the different phenological characteristics between tobacco and other crops. The spectral characteristics of tobacco and corn in luxuriant growth stage are very similar, which makes them difficult to be distinguished using a single-phase remote sensing image. Field film after tobacco seedlings transplanting can be used as significant sign to identify tobacco. Remote sensing interpre- tation map based on the fusion image of TM and CBERS02B's High-Resolution (HR) camera image was used as stan- dard reference material to evaluate the classification accuracy of Spectral Angle Mapper (SAM) and Maximum Like- lihood Classifier (MLC) for time series image based on full samples test method. SAM has higher classification accu- racy and stability than MLC in dealing with time series image. The accuracy and Kappa of tobacco coverage extracted by SAM are 83.4% and 0.692 respectively, which can achieve the accuracy required by tobacco coverage measurement in a large area.

Contribution of Ground-Based Cloud Observation to Satellite-Based Cloud Discrimination

One of the biggest factors to deteriorate the satellite product quality is cloud coverage. Therefore, cloud masking process is important to improve the quality of various satellite products. However, satellite-based cloud discrimination algorithm has been developing and efficient ground-based cloud observations are necessary to validate satellite-based cloud discrimination. The purpose of this study is to develop the efficient ground-based cloud observation methodology using whole sky camera. This paper deals with methods how to discriminate cloud portions on whole sky image, how to apply the ground-based cloud observation to the validations for satellite products. For the cloud discrimination on whole sky image, we propose SI （sky index） and BI （brightness index） calculated from RGB （red, green and blue） channels. SI shows the extent of the blueness and gray scale and BI indicates the extent of the brightness. Sun, cloud and blue sky portions are divided by SI and BI threshold. As an application of ground-based cloud observation for the validation of satellite products, clouds portions discriminated from whole sky image are projected onto ground surface with map coordinate. We also examine to compare with cloud portions on whole sky images and MODIS （MODerate resolution Imaging Spectroradiometer） image as one of experiments. The proposed ground-based cloud observation method and its extension to satellite-based cloud discrimination should be connected to improve the quality of satellite products.

Satellite Retrieval of a Strong Hailstorm Process

A case of hailstorm process occurring on 24 June 2006 in northwestern China was studied using satellite retrieval methodology. The particle effective radius (re) in the cloud tops was calculated by the reflectance in the 3.7 μm channel, and cloud-top microphysical properties were vividly represented using the RGB visual multispectral classification scheme. The microphysical zones of clouds and the processes of hail formation and develop-ment are inferred using the relations of cloud-top temperature (T) versus re for the tops of convective clouds. The results show that particle effective radius was smaller near the cloud base of hailstorm. There was a deep zone of diffusional droplet growth at the low level where the particles grew slowly with height, and there existed an evident area of small ice particles in the cloud top, suggesting the existence of a strong updraft in the clouds. The low glaciated temperature indicated a great depth from the cloud base to the glaciation height, which provided a deep layer of supercooled water for hail growth.

Daytime precipitation identification scheme based on multiple cloud parameters retrieved from visible and infrared measurements

Visible and infrared(VIR) measurements and the retrieved cloud parameters are commonly used in precipitation identification algorithms, since the VIR observations from satellites, especially geostationary satellites, have high spatial and temporal resolutions. Combined measurements from visible/infrared scanner(VIRS) and precipitation radar(PR) aboard the Tropical Rainfall Measuring Mission(TRMM) satellite are analyzed, and three cloud parameters, i.e., cloud optical thickness(COT), effective radius(Re), and brightness temperature of VIRS channel 4(BT4), are particularly considered to characterize the cloud status. By associating the information from VIRS-derived cloud parameters with those from precipitation detected by PR, we propose a new method for discriminating precipitation in daytime called Precipitation Identification Scheme from Cloud Parameters information(PISCP). It is essentially a lookup table(LUT) approach that is deduced from the optimal equitable threat score(ETS) statistics within 3-dimensional space of the chosen cloud parameters. South and East China is selected as a typical area representing land surface, and the East China Sea and Yellow Sea is selected as typical oceanic area to assess the performance of the new scheme. It is proved that PISCP performs well in discriminating precipitation over both land and oceanic areas. Especially, over ocean, precipitating clouds(PCs) and non-precipitating clouds(N-PCs) are well distinguished by PISCP, with the probability of detection(POD) near 0.80, the probability of false detection(POFD) about 0.07, and the ETS higher than 0.43. The overall spatial distribution of PCs fraction estimated by PISCP is consistent with that by PR, implying that the precipitation data produced by PISCP have great potentials in relevant applications where radar data are unavailable.