CN105022101A - Strong convective cloud tracking method - Google Patents

Abstract

The invention belongs to the technical field of weather forecasting. In order to solve the problems of poor accuracy and poor applicability in the current strong convective cloud tracking method, the invention provides a strong convective cloud tracking method. The method comprises steps: a to-be-tracked strong convective cloud is determined on a first frame of satellite cloud image; all strong convective clouds on a second frame of satellite cloud image are recognized; static features of each strong convective cloud in the second frame of satellite cloud image are counted; a search area is determined on the second frame of satellite cloud image, wherein the search area uses the gravity center of the to-be-tracked strong convective cloud in the first frame of satellite cloud image as a center, and T*V serves as a radius; according to the static features of the strong convective clouds, a strong convective cloud with minimal variation is searched in the search area; and dynamic features of the strong convective clouds are calculated, and combinations of the dynamic features and the static features are used for tracking the strong convective cloud. Applicability of the strong convective cloud tracking method is improved, and strong convective cloud tracking accuracy is improved.

Description

Severe Convective Cloud Cluster method for tracing

Technical field

The invention belongs to the technical field of weather prognosis, be specifically related to a kind of Severe Convective Cloud Cluster method for tracing.

Background technology

The strong convective weathers such as the short-time strong rainfall caused by Severe Convective Cloud Cluster, thunderstorm gale, hail and wind spout cause serious threat to the people's lives and property, and people can be made to carry out prevention in advance to the forecast of Severe Convective Cloud Cluster, to reduce the loss that this type of disaster causes.It is the prerequisite making Severe Convective Cloud Cluster forecast to the tracking of Severe Convective Cloud Cluster, at present, usual use weather satellite monitoring Severe Convective Cloud Cluster, the cloud atlas data that weather satellite provides can for identifying that the differentiation situation of structural information (such as, average bright temperature, area, diameter and excentricity etc.) and the monitoring Severe Convective Cloud Cluster following the trail of Severe Convective Cloud Cluster is offered help.

A complicated problem to the description of Severe Convective Cloud Cluster motion, because Severe Convective Cloud Cluster is non-rigidity, always be in constantly displacement, deformation, expansion shrink and even divide, in the process that merges, make whole tracing process than much more difficult to the tracing problem based of general rigidity or near rigid objects in computer vision.In computer vision, there is the research of a lot of motion analysis aspect, but most of motion analysis, all suppose that object is rigidity, and the motion of Severe Convective Cloud Cluster does not obviously meet this hypothesis.

At present, there is the method for tracing of several Severe Convective Cloud Cluster below, such as: " two step back tracking methods ", the method is based on level set (Level Set) method of Sethian, be used for processing the recurrent change in topology such as such as division, fusion etc. of deformable non-rigid Convective Cloud system, solve the nonrigid problem of Severe Convective Cloud Cluster, but the method lacks the overall Dynamic profiling to the motion of cloud cluster fluid.Utilize affined transformation to describe the method for particle clouds motion, the method rebuilds the three-dimensional structure of cloud cluster by two-dimensional image sequence and movable information describes particle clouds motion, although achieve certain effect, because the model of affined transformation is too simple, be not enough to all features describing cloud cluster.The method of above-mentioned tracking Severe Convective Cloud Cluster or the overall Dynamic profiling lacked the motion of cloud cluster fluid, be not enough to all features describing cloud cluster, cause the accuracy of Severe Convective Cloud Cluster tracking poor, and cannot follow the trail of for the cloud cluster of complexity, applicability is poor.

Summary of the invention

In order to the problem that the method accuracy and applicability that solve tracking Severe Convective Cloud Cluster are at present poor, the present invention proposes a kind of Severe Convective Cloud Cluster method for tracing, to improve the applicability of Severe Convective Cloud Cluster method for tracing, improves the accuracy that Severe Convective Cloud Cluster is followed the trail of.

Severe Convective Cloud Cluster method for tracing of the present invention, the method comprises the following steps:

(1) determine to wait to follow the trail of Severe Convective Cloud Cluster on the first frame satellite cloud picture, and add up the static nature that this waits to follow the trail of Severe Convective Cloud Cluster, treat the centre of form of tracking Severe Convective Cloud Cluster, center of gravity, minimum bright temperature, the most highlighted temperature described in this static nature comprises, lower than negative 32 degrees Celsius of region areas, lower than negative 52 degrees Celsius of region areas, lower than negative 62 degrees Celsius of region areas;

(2) identify all Severe Convective Cloud Clusters on the second frame satellite cloud picture, and add up the static nature of Severe Convective Cloud Cluster described in each in described second frame satellite cloud picture;

(3) on described second frame satellite cloud picture, region of search is determined, this region of search is treated centered by the center of gravity of tracking Severe Convective Cloud Cluster in described first frame satellite cloud picture, take T*V as radius, wherein, T is the time interval of described second frame satellite cloud picture and described first frame satellite cloud picture, and V is the maximum translational speed of described Severe Convective Cloud Cluster;

(4) wait to follow the trail of the minimum Severe Convective Cloud Cluster of change degree compared with Severe Convective Cloud Cluster with described searching in described region of search, be expressed as with mathematical formulae

$\underset{k}{\arg \min }\underset{i=1}{\overset{n}{\Σ}}\left(\frac{abs(A_i-B_{ki})}{A_i}\right)$

Wherein, abs is absolute value sign, A _irepresent in described first frame satellite cloud picture i-th static nature waiting to follow the trail of Severe Convective Cloud Cluster, B _kirepresent i-th static nature of the kth Severe Convective Cloud Cluster in described second frame satellite cloud picture in region of search, when having F Severe Convective Cloud Cluster in region of search in described second frame satellite cloud picture, k=1,2,3,4,5 ... F, n are the quantity of static nature,

Should with described wait to follow the trail of the minimum Severe Convective Cloud Cluster of change degree compared with Severe Convective Cloud Cluster for described in wait to follow the trail of the position of Severe Convective Cloud Cluster on described second frame satellite cloud picture;

(5) calculate Severe Convective Cloud Cluster on the described second frame satellite cloud picture that tracks in described step (4) relative to the behavioral characteristics described first frame satellite cloud picture being waited follow the trail of Severe Convective Cloud Cluster, this behavioral characteristics comprises the change of translational speed change, move angle change, minimum bright temperature change, the change of gravity motion distance, the change of the distance between center of gravity and the centre of form, the change of excentricity and area;

(6) adopt in described step (3) and determine that the mode of region of search determines region of search on described 3rd frame satellite cloud picture, to calculate in this region of search all Severe Convective Cloud Clusters relative to the behavioral characteristics of the Severe Convective Cloud Cluster in the second frame satellite cloud picture tracked in described step (4), then searching the Severe Convective Cloud Cluster that change degree is minimum compared with the Severe Convective Cloud Cluster in the second frame satellite cloud picture tracked in described step (4) in this region of search, be expressed as with mathematical formulae

$\underset{k}{\arg \min }\[(\underset{i=1}{\overset{n}{\Σ}}{\left(\frac{abs(B_i-C_{ki})}{B_i}\right)}^2/n)+\left(\underset{j=1}{\overset{m}{\Σ}}\right(\frac{abs(B_j-C_{kj})}{B_j})/m)\]$

Wherein, abs is absolute value sign, B _irepresent i-th static nature of the Severe Convective Cloud Cluster in the described second frame satellite cloud picture tracked, C _kirepresent i-th static nature of a kth Severe Convective Cloud Cluster in region of search in described 3rd frame satellite cloud picture, n is the quantity of static nature, and m is the quantity of behavioral characteristics, B _jrepresent a jth behavioral characteristics of the Severe Convective Cloud Cluster in the described second frame satellite cloud picture tracked, C _kjrepresent a jth behavioral characteristics of a kth Severe Convective Cloud Cluster in region of search in described 3rd frame satellite cloud picture, when having G Severe Convective Cloud Cluster in region of search in described 3rd frame satellite cloud picture, k=1,2,3,4,5 ... G,

This Severe Convective Cloud Cluster that change degree is minimum compared with the Severe Convective Cloud Cluster in the second frame satellite cloud picture tracked in described step (4) is the position of Severe Convective Cloud Cluster on described 3rd frame satellite cloud picture in the second frame satellite cloud picture tracked in described step (4);

(7) according to described step (5) and described step (6), each frame satellite cloud picture successively after described 3rd frame satellite cloud picture is waited described in tracking to follow the trail of Severe Convective Cloud Cluster.

Wherein, described step (1) comprising: (1) identifies strong convection point on the second frame satellite cloud picture; (2) carry out UNICOM's detection to described strong convection point, the set of the described strong convection point in same UNICOM region is a Severe Convective Cloud Cluster.

Wherein, in described step (2), the detection of 4 UNICOMs is carried out to described strong convection point.

Wherein, in described step (2), the detection of 8 UNICOMs is carried out to described strong convection point.

Wherein, in described step (3), the maximum translational speed V of described Severe Convective Cloud Cluster is 80km/h.

Wherein, in described step (1), identify that area is more than or equal to the Severe Convective Cloud Cluster of 250 square kilometres.

Wherein, in described each frame satellite cloud picture, the centre of form coordinate definition of described Severe Convective Cloud Cluster is:

$x=\frac{\underset{i=1}{\overset{R}{\Σ}}{x}_i}{R},y=\frac{\underset{i=1}{\overset{R}{\Σ}}{y}_i}{R}$

Wherein, x _ifor the horizontal ordinate of the marginal point of described Severe Convective Cloud Cluster, y _ifor the ordinate of the marginal point of described Severe Convective Cloud Cluster, R is the quantity of the marginal point of described Severe Convective Cloud Cluster.

Severe Convective Cloud Cluster method for tracing of the present invention has following beneficial effect:

Severe Convective Cloud Cluster method for tracing of the present invention is not only followed the trail of according to the static nature of Severe Convective Cloud Cluster, also follow the trail of according to the behavioral characteristics of Severe Convective Cloud Cluster, because same Severe Convective Cloud Cluster is from static state in the two frame satellite cloud pictures that front and back are adjacent, the centre of form of Severe Convective Cloud Cluster, the static nature such as center and area can not be undergone mutation, from dynamically, the behavioral characteristics such as the direction of motion of Severe Convective Cloud Cluster and movement velocity can not be undergone mutation, after Severe Convective Cloud Cluster minimum with determining to wait to follow the trail of static nature and behavioral characteristics change degree compared with Severe Convective Cloud Cluster in former frame satellite cloud picture in a frame satellite cloud picture be the Severe Convective Cloud Cluster that will look for.The combination of static nature and behavioral characteristics can describe Severe Convective Cloud Cluster more comprehensively more accurately, by the static nature of Severe Convective Cloud Cluster and the combination of behavioral characteristics, general Severe Convective Cloud Cluster can either be followed the trail of, also can follow the trail of the Severe Convective Cloud Cluster of complexity, improve applicability and the accuracy of Severe Convective Cloud Cluster method for tracing.Relative to static nature, behavioral characteristics more can reflect the characteristics of motion of Severe Convective Cloud Cluster exactly, Severe Convective Cloud Cluster method for tracing of the present invention with the behavioral characteristics of Severe Convective Cloud Cluster for Main Basis, with the static nature of Severe Convective Cloud Cluster for auxiliary foundation, improve the accuracy that Severe Convective Cloud Cluster is followed the trail of, contribute to the accurate forecast of meteorologist to Severe Convective Cloud Cluster.

Accompanying drawing explanation

Fig. 1 is the principle schematic of Severe Convective Cloud Cluster method for tracing of the present invention.

Embodiment

Technical scheme of the present invention is introduced below in conjunction with Fig. 1.

Severe Convective Cloud Cluster method for tracing of the present invention comprises the following steps:

(1) as shown in Figure 1, first frame Cloud Figure 10 determines wait to follow the trail of Severe Convective Cloud Cluster 13, and add up this and wait to follow the trail of the static nature of Severe Convective Cloud Cluster 13, this static nature comprise wait to follow the trail of Severe Convective Cloud Cluster 13 the centre of form, center of gravity, minimum bright temperature, the most highlighted temperature, lower than negative 32 degrees Celsius of region areas, lower than negative 52 degrees Celsius of region areas, lower than negative 62 degrees Celsius of region areas;

(2) all Severe Convective Cloud Clusters on second frame Cloud Figure 11 are identified, particularly, second frame Cloud Figure 11 identifies strong convection point, then UNICOM's detection is carried out to the strong convection point that this identifies, namely first UNICOM region is set, the size in this UNICOM region is fixing, the set of the strong convection point in so same UNICOM region is a Severe Convective Cloud Cluster, 4 UNICOMs can be adopted to detect, here " 4 " refer to the size in UNICOM region, also 8 UNICOMs can be adopted to detect, the size that " 8 " are here UNICOM region.Wherein, identify and filter out the Severe Convective Cloud Cluster that area is more than or equal to 250 square kilometres, carry out step below, Severe Convective Cloud Cluster area being less than to 250 square kilometres is directly given up, because the Severe Convective Cloud Cluster that area is less may be the noise produced in identifying, also be likely the very short Severe Convective Cloud Cluster of life cycle, what such strong Severe Convective Cloud Cluster was followed the trail of has little significance.

Then add up the static nature of each Severe Convective Cloud Cluster in second frame Cloud Figure 11, this static nature comprise the centre of form of Severe Convective Cloud Cluster, center of gravity, minimum bright temperature, the most highlighted temperature, lower than negative 32 degrees Celsius of region areas, lower than negative 52 degrees Celsius of region areas, lower than negative 62 degrees Celsius of region areas.

(3) on second frame Cloud Figure 11, region of search is determined, this region of search is treated centered by the center of gravity of tracking Severe Convective Cloud Cluster 13 in first frame Cloud Figure 10, take T*V as radius, wherein, T is the time interval of second frame Cloud Figure 11 and first frame Cloud Figure 10, V is the maximum translational speed of Severe Convective Cloud Cluster, find by observing a large amount of Severe Convective Cloud Cluster, the translational speed of Severe Convective Cloud Cluster is usually within 80km/h, so the maximum translational speed V of Severe Convective Cloud Cluster gets 80km/h here.

Usually comprising multiple Severe Convective Cloud Cluster in region of search on (4) second frame Cloud Figure 11, searching the Severe Convective Cloud Cluster minimum with waiting to follow the trail of change degree compared with Severe Convective Cloud Cluster 13 in this region of search, being expressed as with mathematical formulae

$\underset{k}{\arg \min }\underset{i=1}{\overset{n}{\Σ}}\left(\frac{abs(A_i-B_{ki})}{A_i}\right)$

Wherein, abs is absolute value sign, A _irepresent in first frame Cloud Figure 10 i-th static nature waiting to follow the trail of Severe Convective Cloud Cluster 13, B _kirepresent i-th static nature of the kth Severe Convective Cloud Cluster in second frame Cloud Figure 11 in region of search, when having F Severe Convective Cloud Cluster in region of search in second frame Cloud Figure 11, k=1,2,3,4,5 ... F, n are the quantity of static nature,

Severe Convective Cloud Cluster that should be minimum with waiting to follow the trail of change degree compared with Severe Convective Cloud Cluster 13 is wait to follow the trail of the position of Severe Convective Cloud Cluster 13 on second frame Cloud Figure 11, have found the Severe Convective Cloud Cluster minimum with waiting to follow the trail of change degree compared with Severe Convective Cloud Cluster 13 and namely achieves the tracking of waiting to follow the trail of Severe Convective Cloud Cluster 13.

Be introduced for Fig. 1, wait the centre of form of following the trail of Severe Convective Cloud Cluster 13, center of gravity, minimum bright temperature, the most highlighted temperature, lower than negative 32 degrees Celsius of region areas, lower than negative 52 degrees Celsius of region areas, value lower than negative 62 degrees Celsius of region areas is respectively A1, A2, A3, A4, A5, A6 and A7, a Severe Convective Cloud Cluster is searched in region of search on second frame Cloud Figure 11, the centre of form of this Severe Convective Cloud Cluster, center of gravity, minimum bright temperature, the most highlighted temperature, lower than negative 32 degrees Celsius of region areas, lower than negative 52 degrees Celsius of region areas, value lower than negative 62 degrees Celsius of region areas is respectively B1, B2, B3, B4, B5, B6 and B7, if

$\begin{array}{c}H=\frac{abs(A1-B1)}{A1}+\frac{abs(A2-B2)}{A2}+\frac{abs(A3-B3)}{A3}+\frac{abs(A4-B4)}{A4}+\\ \frac{abs(A5-B5)}{A5}+\frac{abs(A6-B6)}{A6}+\frac{abs(A7-B7)}{A7}\end{array}$

When the value of H is minimum, this Severe Convective Cloud Cluster is wait to follow the trail of the position of Severe Convective Cloud Cluster 13 on second frame Cloud Figure 11, as shown in Figure 1, the H value of the Severe Convective Cloud Cluster 14 tracked is minimum, then the Severe Convective Cloud Cluster 14 tracked follows the trail of the position of Severe Convective Cloud Cluster 13 on second frame Cloud Figure 11 for waiting.

(5) Severe Convective Cloud Cluster 14 tracked on second frame Cloud Figure 11 is calculated relative to the behavioral characteristics first frame Cloud Figure 10 waiting follow the trail of Severe Convective Cloud Cluster 13, this behavioral characteristics comprises the change of translational speed change, move angle change, minimum bright temperature change, the change of gravity motion distance, the change of the distance between center of gravity and the centre of form, the change of excentricity and area, and the information of these behavioral characteristics all can be calculated by satellite cloud picture.

Wherein, in satellite cloud picture, the centre of form coordinate definition of Severe Convective Cloud Cluster is:

$x=\frac{\underset{i=1}{\overset{R}{\Σ}}{x}_i}{R},y=\frac{\underset{i=1}{\overset{R}{\Σ}}{y}_i}{R}$

Wherein x _ithe horizontal ordinate of the marginal point of Severe Convective Cloud Cluster, y _ifor the ordinate of the marginal point of Severe Convective Cloud Cluster, R is the quantity of the marginal point of Severe Convective Cloud Cluster.

(6) determine that the mode of described region of search determines region of search on the 3rd frame Cloud Figure 12 in employing above-mentioned steps (3), to calculate in this region of search all Severe Convective Cloud Clusters relative to the behavioral characteristics of the Severe Convective Cloud Cluster 14 tracked, this behavioral characteristics comprises translational speed change, move angle changes, minimum bright temperature change, the change of gravity motion distance, the change of the distance between center of gravity and the centre of form, the change of excentricity and the change of area, then the Severe Convective Cloud Cluster that change degree is minimum compared with the Severe Convective Cloud Cluster 14 tracked is searched in the region of search on the 3rd frame Cloud Figure 12, be expressed as with mathematical formulae:

$\underset{k}{\arg \min }\[(\underset{i=1}{\overset{n}{\Σ}}{\left(\frac{abs(B_i-C_{ki})}{B_i}\right)}^2/n)+\left(\underset{j=1}{\overset{m}{\Σ}}\right(\frac{abs(B_j-C_{kj})}{B_j})/m)\]$

Wherein, abs is absolute value sign, B _irepresent i-th static nature of the Severe Convective Cloud Cluster 14 tracked, C _kirepresent i-th static nature of a kth Severe Convective Cloud Cluster in region of search in described 3rd frame satellite cloud picture, n is the quantity of static nature, and m is the quantity of behavioral characteristics, B _jrepresent a jth behavioral characteristics of the Severe Convective Cloud Cluster 14 tracked, C _kjrepresent a jth behavioral characteristics of a kth Severe Convective Cloud Cluster in region of search in the 3rd frame Cloud Figure 12, when having G Severe Convective Cloud Cluster in region of search in the 3rd frame Cloud Figure 12, k=1, 2, 3, 4, 5 ... G, in this formula, the part that compares for static nature adds square, it is the weight in order to reduce static nature, increase the weight of behavioral characteristics, because relative to static nature, behavioral characteristics more can reflect the characteristics of motion of Severe Convective Cloud Cluster exactly, with the behavioral characteristics of Severe Convective Cloud Cluster for Main Basis, with the static nature of Severe Convective Cloud Cluster for auxiliary foundation is followed the trail of Severe Convective Cloud Cluster, improve the accuracy that Severe Convective Cloud Cluster is followed the trail of.

As shown in Figure 1, Severe Convective Cloud Cluster 15 is Severe Convective Cloud Clusters that change degree is minimum compared with the Severe Convective Cloud Cluster 14 tracked, then Severe Convective Cloud Cluster 14 position on three frame Cloud Figure 12 of this Severe Convective Cloud Cluster 15 for tracking.

(7) according to step (5) and step (6), each frame satellite cloud picture successively after the 3rd frame Cloud Figure 12 is followed the trail of wait follow the trail of Severe Convective Cloud Cluster.

Claims (7)

1. a Severe Convective Cloud Cluster method for tracing, is characterized in that, the method comprises the following steps:

(1) determine to wait to follow the trail of Severe Convective Cloud Cluster on the first frame satellite cloud picture, and add up the static nature that this waits to follow the trail of Severe Convective Cloud Cluster, treat the centre of form of tracking Severe Convective Cloud Cluster, center of gravity, minimum bright temperature, the most highlighted temperature described in this static nature comprises, lower than negative 32 degrees Celsius of region areas, lower than negative 52 degrees Celsius of region areas, lower than negative 62 degrees Celsius of region areas;

(2) identify all Severe Convective Cloud Clusters on the second frame satellite cloud picture, and add up the static nature of Severe Convective Cloud Cluster described in each in described second frame satellite cloud picture;

(3) on described second frame satellite cloud picture, region of search is determined, this region of search is treated centered by the center of gravity of tracking Severe Convective Cloud Cluster in described first frame satellite cloud picture, take T*V as radius, wherein, T is the time interval of described second frame satellite cloud picture and described first frame satellite cloud picture, and V is the maximum translational speed of described Severe Convective Cloud Cluster;

(4) wait to follow the trail of the minimum Severe Convective Cloud Cluster of change degree compared with Severe Convective Cloud Cluster with described searching in described region of search, be expressed as with mathematical formulae

$\underset{k}{\arg \min }\underset{i=1}{\overset{n}{\Σ}}\left(\frac{ads(A_i-B_{ki})}{A_i}\right)$

Wherein, abs is absolute value sign, A _irepresent in described first frame satellite cloud picture i-th static nature waiting to follow the trail of Severe Convective Cloud Cluster, B _kirepresent i-th static nature of the kth Severe Convective Cloud Cluster in described second frame satellite cloud picture in region of search, when having F Severe Convective Cloud Cluster in region of search in described second frame satellite cloud picture, k=1,2,3,4,5 ... F, n are the quantity of static nature,

Should with described wait to follow the trail of the minimum Severe Convective Cloud Cluster of change degree compared with Severe Convective Cloud Cluster for described in wait to follow the trail of the position of Severe Convective Cloud Cluster on described second frame satellite cloud picture;

(5) calculate Severe Convective Cloud Cluster on the described second frame satellite cloud picture that tracks in described step (4) relative to the behavioral characteristics described first frame satellite cloud picture being waited follow the trail of Severe Convective Cloud Cluster, this behavioral characteristics comprises the change of translational speed change, move angle change, minimum bright temperature change, the change of gravity motion distance, the change of the distance between center of gravity and the centre of form, the change of excentricity and area;

(6) adopt in described step (3) and determine that the mode of region of search determines region of search on described 3rd frame satellite cloud picture, to calculate in this region of search all Severe Convective Cloud Clusters relative to the behavioral characteristics of the Severe Convective Cloud Cluster in the second frame satellite cloud picture tracked in described step (4), then searching the Severe Convective Cloud Cluster that change degree is minimum compared with the Severe Convective Cloud Cluster in the second frame satellite cloud picture tracked in described step (4) in this region of search, be expressed as with mathematical formulae

$\underset{k}{\arg \min }\[(\underset{i=1}{\overset{n}{\Σ}}{\left(\frac{abs(B_i-C_{ki})}{B_i}\right)}^2/n)+\left(\underset{j=1}{\overset{m}{\Σ}}\right(\frac{abs(B_j-C_{kj})}{B_j})/m)\]$

Wherein, abs is absolute value sign, B _irepresent i-th static nature of the Severe Convective Cloud Cluster in the described second frame satellite cloud picture tracked, C _kirepresent i-th static nature of a kth Severe Convective Cloud Cluster in region of search in described 3rd frame satellite cloud picture, n is the quantity of static nature, and m is the quantity of behavioral characteristics, B _jrepresent a jth behavioral characteristics of the Severe Convective Cloud Cluster in the described second frame satellite cloud picture tracked, C _kjrepresent a jth behavioral characteristics of a kth Severe Convective Cloud Cluster in region of search in described 3rd frame satellite cloud picture, when having G Severe Convective Cloud Cluster in region of search in described 3rd frame satellite cloud picture, k=1,2,3,4,5 ... G,

This Severe Convective Cloud Cluster that change degree is minimum compared with the Severe Convective Cloud Cluster in the second frame satellite cloud picture tracked in described step (4) is the position of Severe Convective Cloud Cluster on described 3rd frame satellite cloud picture in the second frame satellite cloud picture tracked in described step (4);

(7) according to described step (5) and described step (6), each frame satellite cloud picture successively after described 3rd frame satellite cloud picture is waited described in tracking to follow the trail of Severe Convective Cloud Cluster.

2. Severe Convective Cloud Cluster method for tracing according to claim 1, is characterized in that, described step (1) comprising: (1) identifies strong convection point on the second frame satellite cloud picture; (2) carry out UNICOM's detection to described strong convection point, the set of the described strong convection point in same UNICOM region is a Severe Convective Cloud Cluster.

3. Severe Convective Cloud Cluster method for tracing according to claim 2, is characterized in that, in described step (2), carries out the detection of 4 UNICOMs to described strong convection point.

4. Severe Convective Cloud Cluster method for tracing according to claim 2, is characterized in that, in described step (2), carries out the detection of 8 UNICOMs to described strong convection point.

5. the Severe Convective Cloud Cluster method for tracing according to any one of claim 1-4, is characterized in that, in described step (3), the maximum translational speed V of described Severe Convective Cloud Cluster is 80km/h.

6. the Severe Convective Cloud Cluster method for tracing according to any one of claim 1-4, is characterized in that, in described step (1), identifies that area is more than or equal to the Severe Convective Cloud Cluster of 250 square kilometres.

7. the Severe Convective Cloud Cluster method for tracing according to any one of claim 1-4, is characterized in that, in described each frame satellite cloud picture, the centre of form coordinate definition of described Severe Convective Cloud Cluster is:

$x=\frac{\underset{i=1}{\overset{R}{\Σ}}{x}_i}{R},y=\frac{\underset{i=1}{\overset{R}{\Σ}}{y}_i}{R}$

Wherein, x _ifor the horizontal ordinate of the marginal point of described Severe Convective Cloud Cluster, y _ifor the ordinate of the marginal point of described Severe Convective Cloud Cluster, R is the quantity of the marginal point of described Severe Convective Cloud Cluster.