CN108897072A - A kind of the cloud amount Numerical Prediction Method and forecast system of the distant satellite of business - Google Patents
A kind of the cloud amount Numerical Prediction Method and forecast system of the distant satellite of business Download PDFInfo
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Abstract
The present invention relates to a kind of cloud amount Numerical Prediction Method of the distant satellite of business and forecast system, the cloud amount Numerical Prediction Method of the distant satellite of business of the invention includes the following steps：Cloud amount prog chart is extracted from operational forecast database；Cloud amount prog chart is partitioned into the multiple cloud amount to match with multiple traveling track lattice points of the distant satellite of quotient and forecasts lattice point；Each cloud amount forecast lattice point corresponding with its position should be searched according to the coordinate pair of each traveling track lattice point；The cloud amount forecast data for including in each cloud amount forecast lattice point is extracted respectively, and is satellite orbit total amount of cloud forecast data by each cloud amount data summarization.Forecasting procedure and forecast system of the invention is based on cloud amount prog chart and calculates satellite orbit total amount of cloud forecast data, the short-term planning of 48h~for 24 hours can be forecast to provide using the cloud amount of future 48h in cloud amount prog chart~for 24 hours for the distant satellite of quotient, so that the distant satellite of quotient avoids cloud amount multizone, reduces the waste paper rate of the distant satellite of quotient and increase the service life of the distant satellite of quotient.
Description
Technical field
The present invention relates to the cloud amount Numerical Prediction Method of aerospace meteorology field more particularly to a kind of distant satellite of business and
Forecast system.
Background technique
Commercial Remote Sensing Satellites (the hereinafter referred to as distant satellite of quotient) have high spatial, temporal resolution, and overlay area is wide, manufactures
The advantages that at low cost, there is extensive and important application in global every profession and trade.The distant satellite of the quotient in China " high scape No.1 " 01/02
Satellite was succeeded in sending up on December 28th, 2016, and 03/04 satellite smoothly goes up to the air on January 9th, 2018 again, and composition China is first
Has high quick, multi-modal imaging ability commercial satellite constellation, not only the images number such as available multiple spot, multi-ribbon splicing
According to three-dimensional acquisition can also be carried out.This 4 0.5m high-resolution satellites run on its track with 90 ° of angles, are persistently counted
According to acquisition.After four star networkings, global any point can be realized 1 day and be revisited, and indicate the entirely autonomous remote sensing satellite commercialization in China
Operating service has stepped the first step.With the commercial operation for the distant satellite of Chinese quotient that " high scape No.1 " is representative, high score will be broken
Remote sensing market is by the situation of foreign countries' monopolization, further satisfaction country significant development Strategic Demand.
The distant satellite of quotient not only survey of territorial resources, mapping, in terms of provide good service, also answer extensively
It is commented for industries such as urban planning, map making, City supervision, forestry, environmental protection, resource managements, while also in industrial plants
Estimate, many aspects such as banking and insurance business and Internet industry are exhibited one's skill to the full, provide high-precision for industry-level and personal consumption user
Satellite data.
For the shooting of the distant satellite of quotient, satellite inherent parameters, weather conditions, signal and number biography etc. can all influence it
Shooting, wherein total amount of cloud is to influence a key factor of satellite shooting, and historical statistics shows that the distant satellite waste paper rate of quotient exists
70% or so, wherein 90% or more waste paper is since the masking of cloud causes.The distant satellite launch of quotient and the cost of operation are substantially
Fixed, after transmitting is entered the orbit, in-orbit life-span, shooting number, swing frequency have just determined substantially；The society of the distant satellite of quotient
Benefit is from efficient, high-quality satisfaction country and industry requirement, and the quantity for the image that its economic benefit is then directly provided by it
It is determined with quality.
By taking first 4 constellations of high scape No.1 as an example, constellation has substar imaging, side-sway imaging, continuous strip, more
The multiple-working modes such as strips mosaic, three-dimensional imaging, multi-target imaging；It can precisely realize that substar is imaged rapidly, conventional side
Pivot angle is up to 30 °, can reach 45 ° when executing key task, certain wide-angle side-sway can accordingly sacrifice its service life.Gao Jingyi
Number single satellite can acquire 900,000 km daily2Image can shoot about 73,000,000 scapes within 8 years projected lives of constellation；Existing
Have under 70% waste paper rate, usable image is 20,000,000 scapes or so.Due to its transmitting, operation cost be it is approximately fixed, such as
The more accurate cloud of fruit is forecast so that waste paper rate reduction by 10%, can also accordingly reduce number of oscillations, usable image is about 28,000,000
Scape, directly increase economic benefit 30% or so.It, can in time efficiently also, in the disaster reduction and prevention task such as earthquake, forest fire
Ground provides decision support product.
At the beginning of the operation of high scape No.1, the climatic statistics value of global cloud amount historical data is utilized for shooting task rule
It draws, there are three crucial problems not to solve for this method：
First, what total amount of cloud historical statistics reflected is the Climatological Mean Values in some season of this area, specific to the distant satellite of quotient
The a certain scape of a certain rail shoot task, the reference significance of history average is little；
Second, for high scape No.1 business planning, it is most important that the short-term planning of 48h~for 24 hours, and for 24 hours in
Task arrangement is closed in short-term based on the forecast of high-accuracy cloud amount, at present the technology or blank of this respect；
Third, the shooting of high scape No.1 are divided with a rail one scape.As polar-orbiting satellite, the high each mistake of scape No.1
Border can shoot " rail " satellite strip data, for convenient for management and subsequent processing, whole rail is cut according to breadth, be formed
One by one close to " scape " of equilateral parallelogram.High scape No.1 breadth 12km, each scape, that is, 12*12km range need to mention
For 0.1 ° of * 0.1 ° of cloud amount Grid data.Global cloud amount forecast is made a general survey of, there is no the products of additional space range；And it directlys adopt
Neighboring lattice points value can bring apparent error as forecast result.
Since the 1970s, the main direction of development of the numerical weather forecast as global prediction technology, to meteorological section
Development brings revolutionary progress, supports the constantly improve of forecast accuracy.There are multiple meteorological numbers both at home and abroad at present
It is worth Forecast Mode, such as GRAPES, T639, ECMWF, NCEP etc. and total amount of cloud forecast, but the time-space resolution of each mode is provided
Rate, product scope, Time effect forecast etc. are variant, also different in the forecast accuracy of different zones, and at present not
There is the spatial resolution of numerical model to meet the needs of high scape No.1.Therefore, how the total of spatial and temporal resolution meet demand is provided
Cloud amount forecast model products become a critical issue of the distant satellite commercial operating service of quotient.
It is therefore proposed that a kind of the cloud amount Numerical Prediction Method and forecast system of the distant satellite of business.
Summary of the invention
In view of the above problems, the present invention is proposed to overcome the above problem in order to provide one kind or at least be partially solved
The cloud amount Numerical Prediction Method and forecast system of the distant satellite of the business of the above problem, the forecasting procedure and forecast system are based on
Cloud amount prog chart calculates satellite orbit total amount of cloud forecast data, can reduce the waste paper rate of the distant satellite of quotient and increases the distant satellite of quotient
Service life.
According to an aspect of the present invention, the cloud amount Numerical Prediction Method of the distant satellite of business provided by the invention, including
Following steps：Cloud amount prog chart is extracted from operational forecast database；Cloud amount prog chart is partitioned into and the distant satellite of quotient
Multiple cloud amount that multiple traveling track lattice points match forecast lattice point；According to the coordinate pair of each traveling track lattice point should search with
The corresponding each cloud amount in its position forecasts lattice point；The cloud amount forecast data for including in each cloud amount forecast lattice point is extracted respectively, and
It is satellite orbit total amount of cloud forecast data by each cloud amount data summarization.
Further, cloud amount prog chart is partitioned into multiple traveling track lattice points with the distant satellite of quotient by following formula
The multiple cloud amount forecast lattice point to match：
Wherein, CsThe cloud amount predicted value at predicted position s obtained for interpolation, CiFor the predicted value at i-th of lattice point, λi
For the weight of the predicted value at i-th of lattice point, n is lattice values number.
Further, it should be searched by following formula according to the coordinate pair of each traveling track lattice point corresponding with its position
Each cloud amount forecast lattice point：
Wherein, LONmFor the longitude at m scape center, LONmnFor the longitude on 4 vertex of m scape, n=1,2,3,4；
LATmFor the latitude at m scape center, LATmnFor the latitude on 4 vertex of m scape, n=1,2,3,4；
Each cloud amount, which is extracted, by following formula forecasts the cloud amount forecast data for including in lattice point：
Wherein, CmIt is (LON for center longitude and latitudem、LATm) m scape cloud amount predicted value, CmjAround scape central point
The cloud amount predicted value of j-th of lattice point, j=1,2,3,4；RmjFor the distance between j-th of lattice point and scape center.
Further, the cloud amount Numerical Prediction Method of the distant satellite of the business further includes：It is pre- from multiple business numerical value
Suitable operational forecast database is chosen in report database.
Further, multiple business numerical forecast database includes GRAPES operational forecast mode, T639 business number
It is worth Forecast Mode, ECMWF operational forecast mode and NCEP operational forecast mode.
According to another aspect of the present invention, the cloud amount Numerical Prediction System of the distant satellite of business provided by the invention, packet
It includes：Cloud amount prog chart extraction module, for extracting cloud amount prog chart from operational forecast database；Cloud amount forecasts lattice point
Matching module, for cloud amount prog chart to be partitioned into the multiple cloud amount to match with multiple traveling track lattice points of the distant satellite of quotient
Forecast lattice point；Cloud amount forecasts lattice point searching module, for that should be searched and its position phase according to the coordinate pair of each traveling track lattice point
Corresponding each cloud amount forecasts lattice point；Satellite orbit total amount of cloud forecast data extraction module, for extracting each cloud amount forecast respectively
The cloud amount forecast data for including in lattice point, and be satellite orbit total amount of cloud forecast data by each cloud amount data summarization.
It further, include to realize matched following formula in cloud amount forecast lattice point matching module：
Wherein, CsThe cloud amount predicted value at predicted position s obtained for interpolation, CiFor the predicted value at i-th of lattice point, λi
For the weight of the predicted value at i-th of lattice point, n is lattice values number.
Further, cloud amount forecast lattice point searching module includes the following formula realized and searched：
Wherein, LONmFor the longitude at m scape center, LONmnFor the longitude on 4 vertex of m scape, n=1,2,3,4；
LATmFor the latitude at m scape center, LATmnFor the latitude on 4 vertex of m scape, n=1,2,3,4；
Satellite orbit total amount of cloud forecast data extraction module includes the following formula realized and extracted：
Wherein, CmIt is (LON for center longitude and latitudem、LATm) m scape cloud amount predicted value, CmjAround scape central point
The cloud amount predicted value of j-th of lattice point, j=1,2,3,4；RmjFor the distance between j-th of lattice point and scape center.
Further, the cloud amount Numerical Prediction System of the distant satellite of the business further includes：Operational forecast data
Module is chosen in library, for choosing suitable operational forecast database from multiple business numerical forecast database.
Compared with prior art, the present invention having the following advantages that：
1. forecasting procedure and forecast system of the invention can be pre- using the cloud amount of future 48h in cloud amount prog chart~for 24 hours
Report is that the distant satellite of quotient provides the short term ephemeris planning of 48h~for 24 hours, and for 24 hours in being faced in short-term based on what high-accuracy cloud amount was forecast
Nearly task arrangement, so that the distant satellite of quotient avoids the region more than cloud amount, to reduce the waste paper rate of the distant satellite of quotient and increase the distant satellite of quotient
Service life；
2. cloud amount prog chart is partitioned into multiple traveling rails with the distant satellite of quotient by forecasting procedure and forecast system of the invention
Multiple cloud amount that road lattice point matches forecast that lattice point, the cloud amount that can provide spatial and temporal resolution meet demand for the distant satellite of quotient are pre-
Report lattice point.
The above description is only an overview of the technical scheme of the present invention, in order to better understand the technical means of the present invention,
And it can be implemented in accordance with the contents of the specification, and in order to allow above and other objects of the present invention, feature and advantage can
It is clearer and more comprehensible, the followings are specific embodiments of the present invention.
Detailed description of the invention
By reading the following detailed description of the preferred embodiment, various other advantages and benefits are general for this field
Logical technical staff will become clear.The drawings are only for the purpose of illustrating a preferred embodiment, and is not considered as to this hair
Bright setting.And throughout the drawings, the same reference numbers will be used to refer to the same parts.In the accompanying drawings：
Fig. 1 is the cloud amount Numerical Prediction Method block diagram of the distant satellite of business of the invention；
Fig. 2 is the cloud amount Numerical Prediction Method flow chart of the distant satellite of business of the invention；
Fig. 3 is that the distant satellite of " high scape No.1 " quotient of the embodiment of the present invention shoots " rail ", " scape " schematic diagram；
Fig. 4 is eyeball and tested point relation schematic diagram in Kriging regression of the present invention；
Fig. 5 is the inconsistent schematic diagram of eyeball lattice point numerical value in Kriging regression of the present invention；
Fig. 6 is variation function curve in Kriging regression of the present invention；
Fig. 7 is grid schematic diagram near a certain scape in the distant satellite shooting track of quotient of the embodiment of the present invention；
Fig. 8 is that the cloud amount Numerical Prediction System of the distant satellite of business of the invention connects block diagram,
In the accompanying drawings, 1- traveling track lattice point, 2- traveling track lattice point, 3- traveling track lattice point, 4- traveling track lattice
Point, 5- cloud amount forecast that lattice point, 6- cloud amount forecast that lattice point, 7- cloud amount forecast that lattice point, 8- cloud amount forecast lattice point, 9- and traveling track
The corresponding cloud amount of lattice site forecasts that lattice point, 10- cloud amount forecast grid, 11- traveling track.
Specific embodiment
Exemplary embodiments of the present disclosure are described in more detail below with reference to accompanying drawings.Although showing this public affairs in attached drawing
The exemplary embodiment opened, it being understood, however, that may be realized in various forms the disclosure without the implementation that should be illustrated here
Set by example.On the contrary, these embodiments are provided to facilitate a more thoroughly understanding of the present invention, and can be by the disclosure
Range is fully disclosed to those skilled in the art.
Those skilled in the art of the present technique are appreciated that unless expressly stated, singular " one " used herein, " one
It is a ", " described " and "the" may also comprise plural form.It is to be further understood that being arranged used in specification of the invention
Diction " comprising " refer to that there are the feature, integer, step, operation, element and/or component, but it is not excluded that in the presence of or addition
Other one or more features, integer, step, operation, element, component and/or their group.
Those skilled in the art of the present technique are appreciated that unless otherwise defined, all terms used herein (including technology
Term and scientific term), there is meaning identical with the general understanding of those of ordinary skill in fields of the present invention.Also
It should be understood that those terms such as defined in the general dictionary, it should be understood that have and the context of the prior art
In the consistent meaning of meaning otherwise will not be solved with idealization or meaning too formal and unless by specific definitions
It releases.
Fig. 1 is the cloud amount Numerical Prediction Method block diagram of the distant satellite of business of the invention, as shown in Figure 1, the present invention mentions
The cloud amount Numerical Prediction Method of the distant satellite of the business of confession, includes the following steps：Cloud is extracted from operational forecast database
Measure prog chart；Cloud amount prog chart is partitioned into the multiple cloud amount to match with multiple traveling track lattice points of the distant satellite of quotient to forecast
Lattice point；Each cloud amount forecast lattice point corresponding with its position should be searched according to the coordinate pair of each traveling track lattice point；It extracts respectively
The cloud amount forecast data for including in each cloud amount forecast lattice point out, and be the forecast of satellite orbit total amount of cloud by each cloud amount data summarization
Data.Wherein, cloud amount prog chart includes the coordinate position data of lattice point cloud amount forecast data and each lattice point.Traveling track lattice point
Including its coordinate position data.Cloud amount forecast lattice point includes the coordinate position data of lattice point cloud amount forecast data and each lattice point.This
The forecasting procedure and forecast system of invention, which can be that quotient is distant using the cloud amount forecast of future 48h in cloud amount prog chart~for 24 hours, to be defended
Star provides the short term ephemeris planning of 48h~for 24 hours, and for 24 hours in task peace closed on based on the forecast of high-accuracy cloud amount in short-term
Row, so that the distant satellite of quotient avoids the region more than cloud amount, to reduce the waste paper rate of the distant satellite of quotient and increase the service life of the distant satellite of quotient,
In addition, cloud amount prog chart is partitioned into multiple traveling track lattice with the distant satellite of quotient by forecasting procedure and forecast system of the invention
Multiple cloud amount forecast lattice point that point matches can provide the cloud amount forecast lattice of spatial and temporal resolution meet demand for the distant satellite of quotient
Point.
Specifically, as shown in Fig. 2, the present invention is first by existing operational forecast database comparative analysis, choosing
More suitable operational forecast database out；Then business interpolation method is selected from a variety of interpolation methods, to business number
Cloud amount prog chart in value forecast data library carries out interpolation and obtains the cloud amount forecast lattice point for meeting the distant satellite spatial resolution ratio of quotient,
Each cloud amount corresponding with its position finally should be searched according to the coordinate pair of the distant satellite traveling track lattice point of quotient and forecast lattice point, point
The cloud amount forecast data for including in each cloud amount forecast lattice point is indescribably taken out, and is the total cloud of satellite orbit by each cloud amount data summarization
Measure forecast data.Using cloud amount forecasting procedure of the invention, carries out commerce services for high-resolution Commercial Remote Sensing Satellites and skill is provided
Art is supported.Wherein, interpolation method can be to be any in bilinear interpolation, inverse distance weighted interpolation and Kriging regression, preferably gram
In golden interpolation.
The cloud amount Numerical Prediction Method of the distant satellite of business further includes：From multiple business numerical forecast database
Choose suitable operational forecast database.Multiple business numerical forecast database includes GRAPES operational forecast mould
Formula, T639 operational forecast mode, ECMWF operational forecast mode and NCEP operational forecast mode.
Cloud amount prog chart is partitioned by following formula match with multiple traveling track lattice points of the distant satellite of quotient it is more
A cloud amount forecasts lattice point：
Wherein, CsThe cloud amount predicted value at predicted position s obtained for interpolation, CiFor the predicted value at i-th of lattice point, λi
For the weight of the predicted value at i-th of lattice point, n is lattice values number.
It is pre- that each cloud amount corresponding with its position should be searched according to the coordinate pair of each traveling track lattice point by following formula
Report lattice point：
Wherein, LONmFor the longitude at m scape center, LONmnFor the longitude on 4 vertex of m scape, n=1,2,3,4；
LATmFor the latitude at m scape center, LATmnFor the latitude on 4 vertex of m scape, n=1,2,3,4；
Each cloud amount, which is extracted, by following formula forecasts the cloud amount forecast data for including in lattice point：
Wherein, CmIt is (LON for center longitude and latitudem、LATm) m scape cloud amount predicted value, CmjAround scape central point
The cloud amount predicted value of j-th of lattice point, j=1,2,3,4；RmjFor the distance between j-th of lattice point and scape center.
Embodiment
Using the distant satellite cloudiness reporting services of " high scape No.1 " quotient as example, the present invention is described further.This cloud amount
The background of reporting services is that for " high scape No.1 " 01/02 satellite after on December 28th, 2016 succeeds in sending up, in January, 2017 is formal
Has operation ability.High scape No.1 commercial operation planning needs to provide 0.1 ° * 0.1 ° global total amount of cloud forecast model products, most important
Be 48h~for 24 hours short-period forecast.
The shooting of high scape No.1 is with " rail ", " scape " come what is divided.As polar-orbiting satellite, passing by can shoot every time
One " rail " satellite strip data, for convenient for management and subsequent processing, whole rail is cut according to breadth, formation connects one by one
" scape " of nearly equilateral parallelogram.Fig. 3 is that the distant satellite of " high scape No.1 " quotient shoots " rail ", " scape " schematic diagram, in figure
The left side is " rail " for shooting, and the right is specific " scape ".High scape No.1 breadth 12km, each scape, that is, 12km*12km model
It encloses, is approximately 0.1 ° * 0.1 °, i.e., the cloud amount service product of high scape No.1 is really directed to its each scape and provides.Thus, needle
High scape No.1 commercial operation is planned, it is desirable to provide 0.1 ° * 0.1 ° global cloud amount Grid data.Therefore, how space-time is provided
The total amount of cloud forecast model products of resolution ratio meet demand become a critical issue of the distant satellite commercial operating service of quotient.
For " high scape No.1 " the distant satellite of quotient, the cloud amount Numerical Prediction Method of the distant satellite of business proposed by the present invention, such as
It is specific as follows shown in Fig. 2：
Step 1 selects suitable operational forecast database from multiple business numerical forecast database
Numerical weather forecast is the main direction of development of global prediction technology, and there are many meteorological numerical value is pre- both at home and abroad at present
Report mode, commonly includes GRAPES, T639, ECMWF and NCEP, and each mode profile is as follows：
GRAPES：GRAPES is the Numerical Prediction System of new generation of China Meteorological Administration's independent research, is that full name in English is " complete
The contracting of ball/region assimilation forecast system " (Global/Regional Assimilation and Prediction System)
It writes, the formal business in 2015.
T639：T639 is the global numerical operational forecast system developed by China Meteorological Administration's numerical forecast center, is
The abbreviation of the whole world T639L60 medium-range numerical forecast mode.Mode resolution ratio with higher, reaches global horizontal resolution
30 kilometers, 60 layers of vertical resolution, top of model reaches 0.1 hundred pas.In formal service operation in 2008.
ECMWF：ECMWF is " European Center for Medium Weather Forecasting " (European Centre for Medium-Range
Weather Forecasts) abbreviation, Numerical Prediction Models be global development earliest, precision is higher, stable industry
Business mode, in the service operation of decades, the forecast level of ECMWF is in the world in numerous Numerical Prediction Models in surpassing one
The position of flowing water standard.
NCEP：NCEP is Environmental forecasting centre (National Center of Environment
Prediction abbreviation), multiple business Numerical Prediction Models are in first-class level in the world, such as mesoscale Numerical-Mode
Formula MM5 and WRF.
Spatial and temporal resolution, product scope, the Time effect forecast of above-mentioned each mode etc. are variant, and table 1 is the main number in the whole world
It is worth the basic parameter statistical form of Forecast Mode cloud amount, seen from table 1, there is no the spatial resolutions of numerical model to meet at present
The demand of high scape No.1.In identical Time effect forecast, compare each model predictions range, horizontal resolution, vertical level, when
Between resolution ratio, primary condition and mode stability and accuracy rate, to determine operational forecast database.
Table 1
Since high scape No.1 commercial operation planning needs to provide 0.1 ° * 0.1 ° global cloud amount Grid data, preferably divide
Resolution and 0.1 ° * 0.1 ° immediate ECMWF are as suitable operational forecast database.
Step 2: it is preferred that interpolation method
Operational forecast database can provide the cloud amount numerical forecast lattice values of corresponding spatial and temporal resolution, and ECMWF is
0.125 ° * 0.125 ° forecast by 3h (0~120h) and by the global total amount of cloud of 6h (126~240h), will provide for high scape No.1
0.1 ° * 0.1 ° of lattice point product, direct substituted with neighboring lattice points value generallyd use can bring apparent error.
Experimental Comparison is carried out below by way of to common interpolation method, compares different interpolation methods using satellite actual measurement cloud amount
Predicted value, preferred business interpolation method out.
There are four types of the interpolation method of service application is usual：Bilinear interpolation, inverse distance weighted interpolation, spline interpolation and gram
In golden interpolation, wherein since spline interpolation needs the cloud amount data of upper and lower level, and what is forecast at present is total amount of cloud data, thus this
Stage does not use Spline Interpolation Method.
Pilot time slot is 1 day 00 March in 2017 when 31 days 00 March (universal time), utilizes State Satellite Meterological Center
FY-2E fixed statellite is used as actual measurement cloud amount by 0.1 ° × 0.1 ° lattice point total amount of cloud data of 3h, same to European center (ECMWF)
When time 0.125 ° by 3h × 0.125 ° of total amount of cloud forecast data be interpolated into 0.1 ° × 0.1 ° of result and verified.Verifying
East Asia and South Asia partial region (70 °~140 ° E, 0 °~60 ° N) are chosen in region, using the point-by-point matched method of inspection, cloud amount
Using percent value, obatained score is determined according to the absolute value D of the difference of the cloud amount predicted value of interpolation acquisition and measured value,
Table 2 is total amount of cloud forecast verification standards of grading table.
Table 2
| D | <5 | 5≤D<10 | 10≤D<15 | 15≤D<20 | 20≤D<25 | 25≤D<30 | 30≤D<35 | ≥35 |
| Score | 1 | 0.9 | 0.8 | 0.7 | 0.6 | 0.5 | 0.4 | 0 |
Interpolation is verified using cross-validation method, that is, is assumed that the meteorological element value of each website is unknown, need to be passed through week
The value of website is enclosed to estimate, then calculates the error of all website actual measurement cloud amount values and estimated value, and assessment errors method is come with this
Superiority and inferiority.Two kinds of factors of root mean square (RMSIE) of mean absolute error (MAE) and interpolation error quadratic sum have been counted as assessment
Standard is excellent with the small interpolation method of error.Wherein, MAE represents the possible error range of estimated value, and RMSIE then reflects utilization
The estimation sensitivity and extreme value effect of sampling point.
Table 3 is the error statistics table of three kinds of interpolation methods, with the minimum preferably business interpolation method of error.
Table 3
| Interpolation method | MAE | RMSIE |
| Bilinear interpolation | 34.14 | 43.54 |
| Anti- distance weighting interpolation | 34.14 | 43.54 |
| Kriging regression | 34.13 | 43.53 |
When interpolation method is preferred, 3 Chinese rose wind and cloud systems were not yet active due to 2017, selected regional cloud amount in March point
Cloth is relatively simple, normally behave as it is cloudy or cloudless under the influence of weather system, i.e., it is usual relative to some lattice point cloud amount value
It is 100 or 0, and interpolation result difference is only just embodied in cloud boundary, therefore the difference of various methods is not obvious, such as
Shown in table 3, Kriging regression effect is slightly better than other methods.And with the work of the local cloud systems such as monsoon cloud system, Qinghai-Tibet Platean
Jump, the increase of cloud bounds had both considered distance, it is contemplated that the advantage of the Kriging regression method of spatial distribution can be more
Add obvious.Accordingly, it is preferred that business interpolation method is Kriging regression.Interpolation formula is as follows：
In formula：Cs is the cloud amount predicted value at the predicted position s that interpolation obtains, and Ci is the predicted value at i-th of lattice point, λ
I is the weight of the predicted value at i-th of lattice point, and n is lattice values number.Wherein, weight λ i depend on lattice point, predicted position away from
From and predicted position around lattice values between spatial relationship model of fit.By the step, to 0.125 ° × 0.125 °
Total amount of cloud forecasts Grid data Ci (eyeball in lower example) interpolation, obtains the Cs at 0.1 ° × 0.1 ° of position s (in lower example
Tested point) cloud amount forecast lattice values.
Example is as follows：
As shown in figure 4, setting tested point O coordinate as (0,0), around there is eyeball known to ten coordinates, numerical value, it is as follows
Shown in figure：The range that it is 3 away from tested point distance that circle, which is indicated,.The first step, A (0,1), the B (- 1, -2), C being chosen in range
As measurement point, measured value is respectively C for (3,0) and four points of D (0, -3)A、CB、CCAnd CD, interpolation obtains the numerical value at O, i.e.,：
Co=λACA+λBCB+λCCC+λDCD
Second step establishes spatial fitting model, calculates the every bit separated by distance h to corresponding position.Formula is such as
Under：
In formula, n indicates that distance is the number of regular length, and Sh indicates the variation function variance yields of regular length.
1) in the case where ABCD lattice point numerical value is all 0 (cloudless)：
ShIt is each apart from it is upper all be 0, summation is also 0 after inputting the λ weight of each eyeball.
2) in the case where lattice point numerical value around is all 100 (all cloudy)：
Similarly, ShIt is each apart from it is upper all be 0, summation is also 100 after inputting the λ weight of each eyeball.
3) in the case where around lattice point numerical value is different, it is assumed that A, C=0, B=90, D=100, as shown in Fig. 5, it is desirable that
Obtain the numerical value at O；
Third step establishes variation function curve：It is fitted sample by selection mutation model and obtains variation function curve,
And then calculate interpolation result.And can the superiority and inferiority of mutation model determine the variability that be effectively fitted sample, for interpolation knot
Fruit influences very big.Below for illustrating, linear fit formula is selected.
In conjunction with following linear fit formula：
Obtain regression equation y=791.76x+782.48, as shown in Figure 6.
The distance of O point to ABCD each point is respectively 1,2.23,3 and 3, is brought into regression equation and acquires respective semi-square
Difference, semivariance is smaller, then for the observation point closer to the value of required point, the weight of imparting is higher, the weight of each eyeball and each
It is positively correlated from the inverse of semivariance.
In conjunction with ensemble average formula λA+λB+λC+λD=1, the weight for acquiring O point to ABCD each point is respectively 0.38,
0.24、0.19、0.19。
The value for finally acquiring O point is 40.6.
Step 3: obtaining 0.1 ° * 0.1 ° of cloud amount Grid data
Based on the business numerical model product that step 1 obtains, in conjunction with the preferred business interpolation method of step 2, interpolation is obtained
Obtain 0.1 ° * 0.1 ° of total amount of cloud Grid data.
Fig. 7 is grid schematic diagram near the high a certain scape of scape No.1 obtained using the method for the present invention, as shown in fig. 7,
In 0.1 ° * 0.1 ° of cloud amount forecast grid 10, point 9 in traveling track is the central point of a certain scape, i.e., with traveling track lattice point
The corresponding cloud amount in position forecasts lattice point, and 4 lattice points of grid where having it around it (8) put by point 5, point 6, point 7
Lattice point cloud amount forecast data.The cloud amount forecast data of this 4 lattice points can finely be forecast to provide basic number for the cloud amount of a certain scape
According to.As seen from Figure 7, pass through the longitude and latitude data of 4 vertex (1,2,3,4) of the scape, the longitude and latitude of this available scape central point 9
Angle value.
Step 4: each cloud amount corresponding with its position should be searched according to the coordinate pair of the distant satellite traveling track lattice point of quotient
It forecasts lattice point, extracts the cloud amount forecast data for including in each cloud amount forecast lattice point respectively, and be to defend by each cloud amount data summarization
Star orbital road total amount of cloud forecast data provides high scape No.1 a certain scape cloud amount forecast model products.
Based on 0.1 ° of * 0.1 ° of numerical forecast lattice point product that step 3 obtains, according to the distant satellite traveling track lattice point of quotient
Coordinate pair should search each cloud amount forecast lattice point corresponding with its position, and can be obtained center longitude is (LONm、LATm)
The cloud amount predicted value of a certain scape.Specific calculating process is as follows：
The first step calculates the latitude and longitude value of a certain scape central point.
Central point is calculated first with the latitude and longitude value on 4 vertex of the scape for a certain scape on satellite shooting track
Latitude and longitude value, group of equations is as follows：
Wherein, LONmnFor the longitude on 4 vertex of m-th of scape, n=1,2,3,4, LATmnFor 4 vertex of the m scape
Latitude, n=1,2,3,4.
For example, the longitude on a certain four vertex of scape is：LONm1=117.6 °, LONm2=117.74 °, LONm3=
117.56°,LONm4=117.69 °；Latitude is：LATm1=36.49 °, LATm2=36.47 °, LATm3=36.33 °, LATm4=
36.3°.Due to the range very little of a scape, the method for arithmetic average is directlyed adopt to acquire the longitude and latitude of central point.
That is, the longitude of scape central point is：
The latitude of scape central point is：
Second step calculates the cloud amount value of a certain scape.
The cloud amount forecast data for including in each cloud amount forecast lattice point is extracted respectively, obtains the cloud amount value of a certain scape, specifically
Accounting equation is as follows：
Wherein, CmFor the cloud amount predicted value of a certain scape, CmjFor the cloud amount predicted value of j-th of lattice point around scape central point, Rmj
For the distance between j-th of lattice point and scape center.
Such as：The cloud amount predicted value of 4 lattice points is respectively C around a certain scapem1=80, Cm2=75, Cm3=65, Cm4=
70；The distance between scape center is once Rm1=5km, Cm2=7.5km, Cm3=3km, Cm4=5.5km.
Then, the cloud amount predicted value of a certain scape：
The distant satellite cloudiness forecasting model of quotient constructed by above-mentioned equation group can be obtained the cloud amount forecast knot of a certain scape
Fruit.If the cloud amount predicted value of the m scape acquired in this example is 73.45.
The distant satellite of quotient as high-spatial and temporal resolution, high scape No.1 propose rigors for cloud amount forecast model products, and
Demand is not satisfied in the spatial resolution of existing numerical model, if directly substituted with neighboring lattice points value, can bring apparent mistake
Difference.Using method of the invention, in the distant satellite cloudiness reporting services of quotient, provides and meet high scape No.1 commercial operation planning
The cloud amount forecast model products of demand.
We utilize (generation when 31 days 00 May in State Satellite Meterological Center FY-2E fixed statellite 1 day 00 March in 2017
When boundary) by 3h 0.1 ° × 0.1 ° lattice point total amount of cloud data as measured data, time total amount of cloud is pre- while acquisition to the present invention
Report (the following 48h is forecast by 3h) is verified.Validation region selection Eurasia eastern region (70 °~140 ° E, 0 °~60 °
N), i.e. East Asia and South Asia partial region, using the point-by-point matched method of inspection, cloud amount uses percent value, according to weather report value with
The absolute value D of the difference of measured value determines obatained score, standards of grading table such as table 2.
Table 4 is the Eurasia 2017.3.1-2017.5.31 eastern region total amount of cloud numerical forecast scoring statistical form, such as
Shown in table 4, with 10 ° × 10 ° for a region, the score in region is averaged, time forecast overall region is flat when obtaining more
Equal score.By table as it can be seen that using method of the invention, in validation region 48h forecast accuracy 0.570~0.763 it
Between, average 0.650, forecast accuracy is higher and more stable, technical support can be provided for the distant satellite shooting planning of quotient,
Has important application value in its commerce services.
Table 4
Table 4 is further analyzed different zones average forecast accuracy can be seen that region of the equator (0 °~10 ° N,
Average Accuracy 0.611) and high latitude area (50 °~60 ° N, Average Accuracy 0.6200) it is integrally relatively low compared with its colatitude；
In addition, the Bay of Bengal (20 °~30 ° N, 90 °~100 ° E, Average Accuracy 0.584) and Qinghai-Tibet Platean (30 °~40 ° N, 90 °
~100 ° of E, forecast accuracy 0.598) it is the lower area of accuracy rate.Reflect that the present invention is quasi- to the forecast of large scale cloud system
True rate is higher, and the region that equator, this kind of local cloud system in the Bay of Bengal are multiple, and Qinghai-Tibet Platean are typical meteorological pre- in this way
Difficult point region is reported, requires to carry out further research to improve cloud amount forecast accuracy.For other seasons and the whole world remaining
The forecast and verifying work in area, will also deepen continuously with the accumulation of the distant satellite data of quotient.
It is worth noting that, an important goal of the high distant satellite system construction of scape No.1 quotient is the first stage 4 resolutions
Rate is the constellation of 0.5m, day acquisition capacity reach 3,000,000 square kilometres, realize domestic ten big cities (Beijing, Shanghai, Guangzhou,
Shenzhen, Tianjin, Chongqing, Shenyang, Chengdu, Xi'an, Wuhan) the primary ability of coverings in 3 days, with 03/04 star January 9 in 2018
Day, smoothly lift-off was entered the orbit, this target becomes a reality.And the present invention to domestic ten metropolitan cloud amount forecast accuracies 0.67
Left and right can provide the total amount of cloud forecast model products for having very much reference value for its shooting planning, reduce waste paper rate, improve planning effect
Rate has significant economic and social benefit.
Fig. 8 is that the cloud amount Numerical Prediction System of the distant satellite of business of the invention connects block diagram, as shown in figure 8, of the invention
The cloud amount Numerical Prediction System of the distant satellite of the business of offer, including：Cloud amount prog chart extraction module is used for from business numerical value
Cloud amount prog chart is extracted in forecast data library；Cloud amount forecasts lattice point matching module, distant with quotient for being partitioned into cloud amount prog chart
Multiple cloud amount that multiple traveling track lattice points of satellite match forecast lattice point；Cloud amount forecasts lattice point searching module, is used for basis
The coordinate pair of each traveling track lattice point should search each cloud amount forecast lattice point corresponding with its position；Satellite orbit total amount of cloud is pre-
Data extraction module is reported, for extracting the cloud amount forecast data for including in each cloud amount forecast lattice point respectively, and by each cloud amount number
According to summarizing for satellite orbit total amount of cloud forecast data.
It include to realize matched following formula in cloud amount forecast lattice point matching module：
Wherein, CsThe cloud amount predicted value at predicted position s obtained for interpolation, CiFor the predicted value at i-th of lattice point, λi
For the weight of the predicted value at i-th of lattice point, n is lattice values number.
Cloud amount forecast lattice point searching module includes the following formula realized and searched：
Wherein, LONmFor the longitude at m scape center, LONmnFor the longitude on 4 vertex of m scape, n=1,2,3,4；
LATmFor the latitude at m scape center, LATmnFor the latitude on 4 vertex of m scape, n=1,2,3,4；
Satellite orbit total amount of cloud forecast data extraction module includes the following formula realized and extracted：
Wherein, CmIt is (LON for center longitude and latitudem、LATm) m scape cloud amount predicted value, CmjAround scape central point
The cloud amount predicted value of j-th of lattice point, j=1,2,3,4；RmjFor the distance between j-th of lattice point and scape center.
The cloud amount Numerical Prediction System of the distant satellite of business further includes：Operational forecast database chooses mould
Block, for choosing suitable operational forecast database from multiple business numerical forecast database.Multiple business numerical value is pre-
Reporting database includes GRAPES operational forecast mode, T639 operational forecast mode, ECMWF operational forecast mould
Formula and NCEP operational forecast mode.
System embodiment described above is only schematical, wherein the unit as illustrated by the separation member
It may or may not be physically separated, component shown as a unit may or may not be physics
Unit, it can it is in one place, or may be distributed over multiple network units.It can select according to the actual needs
Some or all of the modules therein is selected to achieve the purpose of the solution of this embodiment.Those of ordinary skill in the art are not paying
In the case where creative labor, it can understand and implement.
Through the above description of the embodiments, those skilled in the art can be understood that each embodiment
It can realize by means of software and necessary general hardware platform, naturally it is also possible to pass through hardware.Based on such reason
Solution, substantially the part that contributes to existing technology can embody above-mentioned technical proposal in the form of software products in other words
Out, which may be stored in a computer readable storage medium, such as ROM/RAM, magnetic disk, CD, packet
Some instructions are included to use so that a computer equipment (can be personal computer, server or the network equipment etc.) executes
Method described in certain parts of each embodiment or embodiment.
In addition, it will be appreciated by those of skill in the art that although some embodiments in this include institute in other embodiments
Including certain features rather than other feature, but the combination of the feature of different embodiment means to be in model of the invention
Within enclosing and form different embodiments.For example, in the following claims, embodiment claimed is appointed
Meaning one of can in any combination mode come using.
The purpose of the present invention, technical solution and embodiment is described in detail in above-described specific descriptions,
It should be understood that the specific example of invention described above, is not intended to limit the scope of protection of the present invention, it is all at this
Within the spirit and principle of invention, any modification, equivalent substitution, improvement and etc. done, and with new after the relevant technologies progress
Source of information and Numerical Prediction Models, and forecast range spatial and temporal scales refinement, statistical product, interpolation and weighted calculation side
The increase or improvement of method, should all be included in the protection scope of the present invention.
Claims (10)
1. a kind of cloud amount Numerical Prediction Method of the distant satellite of business, which is characterized in that include the following steps：
Cloud amount prog chart is extracted from operational forecast database；
Cloud amount prog chart is partitioned into the multiple cloud amount to match with multiple traveling track lattice points of the distant satellite of quotient and forecasts lattice point；
Each cloud amount forecast lattice point corresponding with its position should be searched according to the coordinate pair of each traveling track lattice point；
The cloud amount forecast data for including in each cloud amount forecast lattice point is extracted respectively, and is satellite orbit by each cloud amount data summarization
Total amount of cloud forecast data.
2. the cloud amount Numerical Prediction Method of the distant satellite of business according to claim 1, which is characterized in that pass through following public affairs
Cloud amount prog chart is partitioned into the multiple cloud amount to match with multiple traveling track lattice points of the distant satellite of quotient and forecasts lattice point by formula：
Wherein, CsThe cloud amount predicted value at predicted position s obtained for interpolation, CiFor the predicted value at i-th of lattice point, λiIt is i-th
The weight of predicted value at a lattice point, n are lattice values number.
3. the cloud amount Numerical Prediction Method of the distant satellite of business according to claim 2, which is characterized in that pass through following public affairs
Formula should search each cloud amount corresponding with its position according to the coordinate pair of each traveling track lattice point and forecast lattice point：
Wherein, LONmFor the longitude at m scape center, LONmnFor the longitude on 4 vertex of m scape, n=1,2,3,4；LATmFor m
The latitude at scape center, LATmnFor the latitude on 4 vertex of m scape, n=1,2,3,4；
Each cloud amount, which is extracted, by following formula forecasts the cloud amount forecast data for including in lattice point：
Wherein, CmIt is (LON for center longitude and latitudem、LATm) m scape cloud amount predicted value, CmjIt is j-th around scape central point
The cloud amount predicted value of lattice point, j=1,2,3,4；RmjFor the distance between j-th of lattice point and scape center.
4. the cloud amount Numerical Prediction Method of the distant satellite of business according to claim 3, which is characterized in that further include：From
Suitable operational forecast database is chosen in multiple business numerical forecast database.
5. the cloud amount Numerical Prediction Method of the distant satellite of business according to claim 4, which is characterized in that multiple business number
Value forecast data library includes GRAPES operational forecast mode, T639 operational forecast mode, ECMWF operational forecast
Mode and NCEP operational forecast mode.
6. a kind of cloud amount Numerical Prediction System of the distant satellite of business, which is characterized in that including：
Cloud amount prog chart extraction module, for extracting cloud amount prog chart from operational forecast database；
Cloud amount forecasts lattice point matching module, for cloud amount prog chart to be partitioned into multiple traveling track lattice point phases with the distant satellite of quotient
Matched multiple cloud amount forecast lattice point；
Cloud amount forecasts lattice point searching module, corresponding with its position for that should be searched according to the coordinate pair of each traveling track lattice point
Each cloud amount forecasts lattice point；
Satellite orbit total amount of cloud forecast data extraction module, it is pre- for extracting the cloud amount for including in each cloud amount forecast lattice point respectively
Count off evidence, and be satellite orbit total amount of cloud forecast data by each cloud amount data summarization.
7. the cloud amount Numerical Prediction System of the distant satellite of business according to claim 6, which is characterized in that cloud amount forecasts lattice
It include to realize matched following formula in point matching module：
Wherein, CsThe cloud amount predicted value at predicted position s obtained for interpolation, CiFor the predicted value at i-th of lattice point, λiIt is i-th
The weight of predicted value at a lattice point, n are lattice values number.
8. the cloud amount Numerical Prediction System of the distant satellite of business according to claim 7, which is characterized in that cloud amount forecasts lattice
Point searching module includes the following formula realized and searched：
Wherein, LONmFor the longitude at m scape center, LONmnFor the longitude on 4 vertex of m scape, n=1,2,3,4；LATmFor m
The latitude at scape center, LATmnFor the latitude on 4 vertex of m scape, n=1,2,3,4；
Satellite orbit total amount of cloud forecast data extraction module includes the following formula realized and extracted：
Wherein, CmIt is (LON for center longitude and latitudem、LATm) m scape cloud amount predicted value, CmjIt is j-th around scape central point
The cloud amount predicted value of lattice point, j=1,2,3,4；RmjFor the distance between j-th of lattice point and scape center.
9. the cloud amount Numerical Prediction System of the distant satellite of business according to claim 8, which is characterized in that further include：Industry
Business numerical forecast database chooses module, for choosing suitable operational forecast from multiple business numerical forecast database
Database.
10. the cloud amount Numerical Prediction System of the distant satellite of business according to claim 9, which is characterized in that multiple business
Numerical forecast database includes that GRAPES operational forecast mode, T639 operational forecast mode, ECMWF business numerical value are pre-
Report mode and NCEP operational forecast mode.
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| US20050246103A1 (en) * | 2004-04-30 | 2005-11-03 | Nec Toshiba Space Systems, Ltd. | Weather forecast data distributing system and method |
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| CN103472501A (en) * | 2013-09-06 | 2013-12-25 | 中国气象科学研究院 | Cloud and aerial total cloud amount detection method and system |
| CN103810376A (en) * | 2014-01-17 | 2014-05-21 | 浙江大学 | Ground daily rainfall predicting method based on satellite remote sensing and regression Kriging |
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| US20050246103A1 (en) * | 2004-04-30 | 2005-11-03 | Nec Toshiba Space Systems, Ltd. | Weather forecast data distributing system and method |
| CN101969207A (en) * | 2010-09-16 | 2011-02-09 | 国网电力科学研究院 | Photovoltaic ultra-short term power predicting method based on satellite remote sensing and meteorology telemetry technology |
| CN103472501A (en) * | 2013-09-06 | 2013-12-25 | 中国气象科学研究院 | Cloud and aerial total cloud amount detection method and system |
| CN103810376A (en) * | 2014-01-17 | 2014-05-21 | 浙江大学 | Ground daily rainfall predicting method based on satellite remote sensing and regression Kriging |
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