Comparison of Satellite Cloud Image and Radar of Precipitation Process on July 31st,2007

Based on the data of satellite cloud image and Doppler radar,the rainstorm process from July 31st,2007 to August 1st,2007 in Liaoning was analyzed.The precipitation in Fushun and Haicheng was more than 100 mm,and 6 h precipitation in Fushun and Dandong was more than 50 mm.Through the analysis of strong precipitation period,the structure of clouds had a little decline from the stage of development to maturity.The gray value and gradient degree around were both larger in the center of heavy precipitation.

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.

CLOUD IMAGE DETECTION BASED ON MARKOV RANDOM FIELD

In order to overcome the disadvantages of low accuracy rate, high complexity and poor robustness to image noise in many traditional algorithms of cloud image detection, this paper proposed a novel algorithm on the basis of Markov Random Field (MRF) modeling. This paper first defined algorithm model and derived the core factors affecting the performance of the algorithm, and then, the solving of this algorithm was obtained by the use of Belief Propagation (BP) algorithm and Iterated Conditional Modes (ICM) algorithm. Finally, experiments indicate that this algorithm for the cloud image detection has higher average accuracy rate which is about 98.76% and the average result can also reach 96.92% for different type of image noise.

A Method of Identifying Thunderstorm Clouds in Satellite Cloud Image Based on Clustering

In this paper,the clustering analysis is applied to the satellite image segmentation,and a cloud-based thunderstorm cloud recognition method is proposed in combination with the strong cloud computing power.The method firstly adopts the fuzzy C-means clustering(FCM)to obtain the satellite cloud image segmentation.Secondly,in the cloud image,we dispose the‘high-density connected’pixels in the same cloud clusters and the‘low-density connected’pixels in different cloud clusters.Therefore,we apply the DBSCAN algorithm to the cloud image obtained in the first step to realize cloud cluster knowledge.Finally,using the method of spectral threshold recognition and texture feature recognition in the steps of cloud clusters,thunderstorm cloud clusters are quickly and accurately identified.The experimental results show that cluster analysis has high research and application value in the segmentation processing of meteorological satellite cloud images.

Tropical Cyclone Cloud Image Segmentation by the B-Spline Histogram with Multi-Scale Transforms

An efficient tropical cyclone（TC） cloud image segmentation method is proposed by combining the curvelet transform,the cubic B-Spline curve,and the continuous wavelet transform.In order to enhance the global and local contrast of the original TC cloud image,a second-generation discrete curvelet transform is implemented for the original TC cloud image.Based on our prior work,the low frequency components are enhanced by using an incomplete Beta transform and the genetic algorithm in the curvelet domain. Then the enhanced TC cloud image is used to segment the main body of the TC from the TC cloud image. First,pre-processing is implemented by B-Spline curves to the original TC cloud image to remove unrelated small cloud masses.A region of interest（ROI） which includes the main body of TC can thus be obtained. Second,the gray-level histogram of ROI is obtained.In order to reduce oscillations of the histogram,the gray-level histogram is smoothed by cubic B-Spline curves and the B-Spline histogram is obtained.The one dimensional continuous wavelet transform is employed for the curvature curve of the B-Spline histogram. A new segmentation cost criterion is given by combining threshold,error,and structure similarity.The optimally segmented image can be obtained by the criterion in the continuous wavelet domain.The optimally segmented image is post-processed to obtain the final segmented TC image.The experimental results show that the main body of TC can be effectively segmented from the complex background in the TC cloud image by the proposed algorithm.

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.

Estimation of Cloud Motion Using Cross-Correlation

This paper describes the estimation of cloud motion using lag cross-correlation. In order to compute the lag cross correlation, the Bayes Decision method is used first to identify cloud and surface of earth. Then cloud motion vectors are retrieved at a subset of points through multiple applications of a cross-correlation analysis. An objective analysis is used to define displacement at every satellite pixel throughout the domain and smooth the local inconsistencies. Cloud motions are then produced with a backward trajectory technique by using these displacement vectors.

Ground-Based Cloud Using Exponential Entropy/Exponential Gray Entropy and UPSO

Objective and accurate classification model or method of cloud image is a prerequisite for accurate weather monitoring and forecast.Thus safety of aircraft taking off and landing and air flight can be guaranteed.Thresholding is a kind of simple and effective method of cloud classification.It can realize automated ground-based cloud detection and cloudage observation.The existing segmentation methods based on fixed threshold and single threshold cannot achieve good segmentation effect.Thus it is difficult to obtain the accurate result of cloud detection and cloudage observation.In view of the above-mentioned problems,multi-thresholding methods of ground-based cloud based on exponential entropy/exponential gray entropy and uniform searching particle swarm optimization(UPSO)are proposed.Exponential entropy and exponential gray entropy make up for the defects of undefined value and zero value in Shannon entropy.In addition,exponential gray entropy reflects the relative uniformity of gray levels within the cloud cluster and background cluster.Cloud regions and background regions of different gray level ranges can be distinguished more precisely using the multi-thresholding strategy.In order to reduce computational complexity of original exhaustive algorithm for multi-threshold selection,the UPSO algorithm is adopted.It can find the optimal thresholds quickly and accurately.As a result,the real-time processing of segmentation of groundbased cloud image can be realized.The experimental results show that,in comparison with the existing groundbased cloud image segmentation methods and multi-thresholding method based on maximum Shannon entropy,the proposed methods can extract the boundary shape,textures and details feature of cloud more clearly.Therefore,the accuracies of cloudage detection and morphology classification for ground-based cloud are both improved.

Analysis on A Heavy Rain to Rainstorm Weather Process in Liaoning Province

By using the synoptic chart,the physical quantity field,the satellite cloud image and the meteorological elements in the single station,a typical heavy rain to rainstorm weather process which occurred in Liaoning during August 18-20 in 2009 was comprehensively analyzed.The results showed that this process was a weather process which was affected by the upper trough and the subtropical high.Baikal Lake split cold air and Hetao cold air shifted eastward and formed the vortex.The subtropical high extended westward,lifted northward,and the warm wet airflow in the edge cut in.The low-altitude jet stream accelerated the transportation of water vapor,and several active meso-scale convective cloud clusters which appeared in 588 line periphery in the right side of high-altitude jet stream outlet gradually merged with the westerlies system.It caused that the strong mixed precipitation process occurred.

Diagnosis of An Infrequent Regional Hail Weather Course in Gansu

Based on routine weather charts, numerical predication products and satellite cloud images, the causes of an infrequent regional hail weather process occurred in east of Gansu on Aug. 2, 2006 were diagnosed and analyzed. The results showed that the hail weather process occurred at the abnormal large-scale circulation leading the system to west. When the cold trough, which was separated by the north cold vortex, moved southward through Hetao and then intersected with 300 hPa jet stream and the surface cold front, that led to the strong convection. There were strong upward motion and unstable stratification in hail area, three MCS in satellite cloud, and a character of formed arch shape echo on radar echo charts.

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.

A CONVECTIVE RAINFALL ESTIMATE TECHNIQUE DEVELOPED BY NSMC OF CHINA

In order to reveal the relation between strong convective cloud characteristics and rainfall rate, over 20000 hourly raingauge data from 333 weather stations and the corresponding 4000 convective cloud infrared images of GMS-4 during the period of 1992—1994 in Henan,Hubei and Sichuan Provinces were studied.The results show that cloud top temperature,temperature gradient,the growth of cloud,overshooting top and the normalized distance between a cloud covering pixels and the cluster center have certain relations to cloud precipitation.These relations can vary with different geographical regions.Based on the study above,a convective rainfall estimation technique was developed by the scientists in National Satellite Meteorological Center of China.Its average error is 30% for daily precipitation with a correlation coefficient of 0.69.