CN109426886A - A kind of climatic prediction system - Google Patents
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Abstract
The invention discloses a kind of climatic prediction systems characterized by comprising observational data;Data Assimilation system;Climatic model running subsystem;Predicting subsystem;Product subsystem;And high-performance computer;The Data Assimilation system includes Data Assimilation and support subsystem;The climatic model running subsystem includes Global vertical datum mode, global oceanic general, high-resolution East Asian mode, and the ENSO prediction mode simplified;The predicting subsystem includes forecast correction and detection subsystem;The product subsystem includes product generation and distribution subsystem;Wherein, Global vertical datum mode is coupled with global oceanic general constitutes air-sea coupled model, it is combined by using by statistical method with dynamic method, more initial values are combined with multi-mode, so that the climatic prediction system prediction time is long, accuracy is high, and calculating speed is fast, and area is with strong points.
Description
Technical field
The present invention relates to weather technical field, more particularly to a kind of climatic prediction system.
Background technique
In recent years, both at home and abroad to climatic prediction study it is unprecedented pay attention to, climatic prediction research not only with important society and
Economic significance, and have important scientific value, it is the big hot spot of scientific research in the world at present, it has also become the end of this century and
One of the sciemtifec and technical sphere that the various countries Xia Jichu first develop.The scientific basic that Short-term Climate Forecast has its solid is established at this at present
Short-range Climatic Forecast System on kind scientific basic all has shown that certain prediction strategy, still, Short-term Climate Forecast system
The problems such as uniting, it is short that there are predicted times, and accuracy is low, and calculating speed is slow, and regional specific aim is not strong.
Therefore, a kind of prediction that can be achieved to year, month, day how is provided, and accuracy rate can be higher by than the prior art
10% or so, it can also obtain a result in very short time while operational data amount is very big, and can be by using a variety of predictions
Method, aiming at the problem that climatic prediction system that different areas carries out different predictions is those skilled in the art's urgent need to resolve.
Summary of the invention
In view of this, accuracy is high, and calculating speed is fast, and area is directed to the present invention provides a kind of predicted time is long
The strong climatic prediction system of property.
To achieve the above object, the invention provides the following technical scheme:
A kind of climatic prediction system characterized by comprising observational data;The data that observational data is assimilated is same
Change system;Climatic model running subsystem;Predicting subsystem;Product subsystem;And high-performance computer;The Data Assimilation
System includes Data Assimilation and support subsystem;The climatic model running subsystem includes to extend for moon scale power
The Global vertical datum mode of forecast ensemble prediction, global oceanic general, high-resolution East Asian mode, and
Simplified ENSO prediction mode;The predicting subsystem includes forecast correction and detection subsystem;The product subsystem packet
Product generation and distribution subsystem are included;Wherein, Global vertical datum mode couples composition with global oceanic general and is used for
The air-sea coupled model of single season or multiple season global climate trend predictions, the air-sea coupled model and regional climate
Model nesting can be used for providing high-resolution East Asia seasonal climate trend prediction.
Preferably, in a kind of above-mentioned climatic prediction system, observational data can be global atmosphere observational data, can be
Global ocean observational data can be moonscope data, can be radiosonde observation data, can also be other observational datas.
Preferably, in a kind of above-mentioned climatic prediction system, which is by by power numerical model and statistics experience
Forecast combines, and is forecast using prediction error of the history analog information to dynamic mode.
Preferably, in a kind of above-mentioned climatic prediction system, the system using more initial values and multi-mode set.
Preferably, in a kind of above-mentioned climatic prediction system, the observational data which is collected into is successively same via data
Change system, mode initial fields, mode operation subsystem, predicting subsystem and product subsystem, and all system packets
Including observational data all needs to carry out information exchange with high-performance computer in real time.
It can be seen via above technical scheme that compared with prior art, the present invention is disclosed using by statistical method
It is combined with dynamic method, more initial values are combined with multi-mode, by by Global vertical datum mode and global ocean circulation
Mode Coupling constitutes air-sea coupled model, four modes in mode operation subsystem can also be carried out phase as needed
The coupling answered constitutes multiple coupled mode, so as to different areas, different situations is predicted accordingly, and passes through height
Project Computer carries out numerical solution, can get the prediction to the weather system situation of the following moon, season, year, so that weather is pre-
The survey time is longer, and accuracy is higher, and faster, regional specific aim is stronger for calculating speed.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
The embodiment of invention for those of ordinary skill in the art without creative efforts, can also basis
The attached drawing of offer obtains other attached drawings.
Fig. 1 attached drawing is systematic schematic diagram of the invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
The embodiment of the invention discloses a kind of predicted time is long, accuracy is high, and calculating speed is fast, and area is with strong points
Climatic prediction system.
Attached drawing 1 is please referred to, is a kind of climatic prediction system disclosed by the invention, specifically includes:
Observational data;The Data Assimilation system that observational data is assimilated;Climatic model running subsystem;Predict subsystem
System;Product subsystem;And high-performance computer;The Data Assimilation system includes Data Assimilation and support subsystem;Institute
Stating climatic model running subsystem includes the Global vertical datum mode for moon scale dynamical extended range forecast ensemble prediction, entirely
Ball ocean circulation model, high-resolution East Asian mode, and the ENSO prediction mode simplified;The predicting subsystem
It include forecast correction and detection subsystem;The product subsystem includes product generation and distribution subsystem;Wherein, global
It is pre- for single season or multiple season global climate trend that general circulation model couples composition with global oceanic general
The air-sea coupled model of survey, the air-sea coupled model is nested with A Regional Climate Model to can be used for providing high-resolution East Asia season
Save trend coefficient.
By combining statistical method with dynamic method, more initial values combine the present invention with multi-mode, pass through by
Global vertical datum mode is coupled with global oceanic general, constitutes air-sea coupled model, can also be by mode operation
Four modes in system are coupled accordingly as needed, constitute multiple coupled mode, so as to different areas, difference
Situation predicted accordingly, and numerical solution is carried out by high-performance computer.
The system is used not only for the analysis of observational data using Empirical Orthogonal Function (EOF) method, EOF method, also
For the analysis of GCM data and the design of numerical model, the concrete principle and algorithm of EOF analysis method are as follows:
One, data is standardized, extracts top n mode with EOF method.
(1), the data to be analyzed selected first, carry out data prediction, are processed into the form of anomaly, obtain one
Data matrix.
(2), the intersectionproduct of calculating matrix and its transposed matrix, obtains square matrix
If being treated as anomaly, referred to as covariance matrix;If normalized, (each row of data is averaged in i.e.
Value is 0, standard deviation 1), then referred to as related coefficient battle array.
(3), the characteristic root (λ of square matrix is calculated1,,, m) and feature vector Vm×m, the two satisfaction
Cm×m×Vm×m=Vm×m×∧m×m
It is wherein dimension diagonal matrix, i.e.,
By characteristic root λ by sequence arrangement from small to large, i.e. λ1> λ2> ... > λm, since data X is really to observe
Value, so λ should be more than or equal to 0, each corresponding column feature vector value of non-zero characteristic root.Such as λ1Corresponding feature to
Magnitude is known as first EOF mode, that is, the first row of V, i.e. EOF=V (:, 1);λkCorresponding feature vector value is known as kth
A EOF mode, that is, λkThe column that corresponding feature vector is, i.e. EOF=V (:, k).Due to the EOF dimension being calculated
Number is m × m, and the EOF dimension obtained by space-time conversion has m × n, therefore preceding n feature vector can be obtained, that is, extractable
Preceding n mode out.
Two, covariance processing and inversely processing are carried out to the N number of mode extracted.
Three, related coefficient is found out.
Four, regression equation is established.
Five, prediction result is obtained.
In order to further optimize the above technical scheme, observational data can be global atmosphere observational data, can be the whole world
Oceanographic observation data can be moonscope data, can be radiosonde observation data, can also be other observational datas.
In order to further optimize the above technical scheme, the system be by by power numerical model and statistics experimental forecast phase
In conjunction with being forecast using prediction error of the history analog information to dynamic mode.
In order to further optimize the above technical scheme, the system using more initial values and multi-mode set.
In order to further optimize the above technical scheme, the observational data which is collected into is successively via Data Assimilation system
System, mode initial fields, mode operation subsystem, predicting subsystem and product subsystem, and all systems include seeing
Survey data all needs to carry out information exchange with high-performance computer in real time.
In order to further optimize the above technical scheme, specific embodiment are as follows:
The first step, by global atmosphere observational data, global ocean observational data, moonscope data, radiosonde observation data,
And other observational datas are transferred to after assimilating observational data via atmosphere data assimilation system and ocean data assimilation system
Mode initial fields choose assimilation data.
Second step, into mode operation subsystem comprising there is a Global vertical datum mode, global oceanic general,
High-resolution East Asian mode, simplified ENSO prediction mode and Global vertical datum mode and global ocean ring
The air-sea coupled model that stream mode is coupled to form.
Third step is forecast and is detected into predicting subsystem comprising has forecast correction and detection subsystem.
4th step carries out the generation and distribution of product into product subsystem comprising has product to generate subsystem and produce
Product distribution subsystem.
All embodiments are that operation is realized on high-performance computer thereon, ultimately form the generation of product and divide
Hair.
Each embodiment in this specification is described in a progressive manner, the highlights of each of the examples are with other
The difference of embodiment, the same or similar parts in each embodiment may refer to each other.For device disclosed in embodiment
For, since it is corresponded to the methods disclosed in the examples, so being described relatively simple, related place is said referring to method part
It is bright.
The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present invention.
Various modifications to these embodiments will be readily apparent to those skilled in the art, as defined herein
General Principle can be realized in other embodiments without departing from the spirit or scope of the present invention.Therefore, of the invention
It is not intended to be limited to the embodiments shown herein, and is to fit to and the principles and novel features disclosed herein phase one
The widest scope of cause.
Claims (5)
1. a kind of climatic prediction system characterized by comprising observational data;The Data Assimilation that observational data is assimilated
System;Climatic model running subsystem;Predicting subsystem;Product subsystem;And high-performance computer;The Data Assimilation system
System includes Data Assimilation and support subsystem;The climatic model running subsystem includes to extend in advance for moon scale power
Report the Global vertical datum mode of ensemble prediction, global oceanic general, high-resolution East Asian mode, Yi Jijian
The ENSO prediction mode of change;The predicting subsystem includes forecast correction and detection subsystem;The product subsystem includes
There are product generation and distribution subsystem;Wherein, Global vertical datum mode couples composition with global oceanic general for single
The air-sea coupled model of a season or multiple season global climate trend predictions, the air-sea coupled model and regional climate mould
Formula nesting can be used for providing high-resolution East Asia seasonal climate trend prediction.
2. a kind of climatic prediction system according to claim 1, which is characterized in that observational data can be global atmosphere sight
Survey data can be global ocean observational data, can be moonscope data, can be radiosonde observation data, can also be
Other observational datas.
3. a kind of climatic prediction system according to claim 1, which is characterized in that the system is by by power Numerical-Mode
Formula and statistics experimental forecast combine, and are forecast using prediction error of the history analog information to dynamic mode.
4. a kind of climatic prediction system according to claim 1, which is characterized in that the system is using more initial values and more
The set of mode.
5. a kind of climatic prediction system according to claim 1, which is characterized in that the observational data that the system is collected into according to
It is secondary via Data Assimilation system, mode initial fields, mode operation subsystem, predicting subsystem and product subsystem, and institute
Stating all systems includes that observational data all needs to carry out information exchange with high-performance computer in real time.
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Cited By (12)
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CN110543987A (en) * | 2019-08-28 | 2019-12-06 | 向波 | Intelligent climate prediction system |
CN110909297A (en) * | 2019-11-22 | 2020-03-24 | 清华大学 | Numerical prediction set coupling assimilation system and method |
CN111027166A (en) * | 2019-07-30 | 2020-04-17 | 天津大学 | Method for rapidly analyzing ocean elements in sea area around boat position |
CN111208586A (en) * | 2020-01-20 | 2020-05-29 | 山东超越数控电子股份有限公司 | Weather forecasting method and system based on mesoscale sea air coupling mode |
CN112036617A (en) * | 2020-08-17 | 2020-12-04 | 国电大渡河流域水电开发有限公司 | Dynamic-statistical objective quantitative climate prediction method and system |
CN113359726A (en) * | 2021-06-04 | 2021-09-07 | 中山大学 | Method and system for predicting maximum turbid zone |
CN113377513A (en) * | 2021-06-17 | 2021-09-10 | 吉林大学 | Process scheduling optimization method for global coupled climate mode |
CN113407524A (en) * | 2021-06-30 | 2021-09-17 | 国家气候中心 | Climate system mode multi-circle layer coupling data assimilation system |
CN113486515A (en) * | 2021-07-06 | 2021-10-08 | 国家气候中心 | Sub-season-annual scale integrated climate mode set prediction system |
CN114841442A (en) * | 2022-05-10 | 2022-08-02 | 中国科学院大气物理研究所 | Strong coupling method and system applied to atmosphere-ocean observation data |
CN115081314A (en) * | 2022-06-01 | 2022-09-20 | 中国气象科学研究院 | Method and device for correcting climate prediction model |
CN116304491A (en) * | 2023-05-11 | 2023-06-23 | 长江三峡集团实业发展(北京)有限公司 | Assimilation method and system for marine anomaly observation data |
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CN111027166B (en) * | 2019-07-30 | 2024-06-07 | 天津大学 | Rapid analysis method for ocean elements of ocean area around ship position |
CN110543987A (en) * | 2019-08-28 | 2019-12-06 | 向波 | Intelligent climate prediction system |
CN110909297A (en) * | 2019-11-22 | 2020-03-24 | 清华大学 | Numerical prediction set coupling assimilation system and method |
WO2021097917A1 (en) * | 2019-11-22 | 2021-05-27 | 清华大学 | Ensemble coupled assimilation system and method for numerical prediction |
CN111208586A (en) * | 2020-01-20 | 2020-05-29 | 山东超越数控电子股份有限公司 | Weather forecasting method and system based on mesoscale sea air coupling mode |
CN112036617A (en) * | 2020-08-17 | 2020-12-04 | 国电大渡河流域水电开发有限公司 | Dynamic-statistical objective quantitative climate prediction method and system |
CN113359726B (en) * | 2021-06-04 | 2022-12-13 | 中山大学 | Method and system for predicting maximum turbid zone |
CN113359726A (en) * | 2021-06-04 | 2021-09-07 | 中山大学 | Method and system for predicting maximum turbid zone |
CN113377513A (en) * | 2021-06-17 | 2021-09-10 | 吉林大学 | Process scheduling optimization method for global coupled climate mode |
CN113377513B (en) * | 2021-06-17 | 2024-04-05 | 吉林大学 | Process scheduling optimization method for global coupling climate mode |
CN113407524A (en) * | 2021-06-30 | 2021-09-17 | 国家气候中心 | Climate system mode multi-circle layer coupling data assimilation system |
CN113486515B (en) * | 2021-07-06 | 2022-04-05 | 国家气候中心 | Sub-season-annual scale integrated climate mode set prediction system |
CN113486515A (en) * | 2021-07-06 | 2021-10-08 | 国家气候中心 | Sub-season-annual scale integrated climate mode set prediction system |
CN114841442A (en) * | 2022-05-10 | 2022-08-02 | 中国科学院大气物理研究所 | Strong coupling method and system applied to atmosphere-ocean observation data |
CN114841442B (en) * | 2022-05-10 | 2024-04-26 | 中国科学院大气物理研究所 | Strong coupling method and system applied to atmosphere-ocean observation data |
CN115081314A (en) * | 2022-06-01 | 2022-09-20 | 中国气象科学研究院 | Method and device for correcting climate prediction model |
CN116304491A (en) * | 2023-05-11 | 2023-06-23 | 长江三峡集团实业发展(北京)有限公司 | Assimilation method and system for marine anomaly observation data |
CN116304491B (en) * | 2023-05-11 | 2023-08-08 | 长江三峡集团实业发展(北京)有限公司 | Assimilation method and system for marine anomaly observation data |
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Application publication date: 20190305 |