CN109426886A - A kind of climatic prediction system - Google Patents
A kind of climatic prediction system Download PDFInfo
- Publication number
- CN109426886A CN109426886A CN201710754778.5A CN201710754778A CN109426886A CN 109426886 A CN109426886 A CN 109426886A CN 201710754778 A CN201710754778 A CN 201710754778A CN 109426886 A CN109426886 A CN 109426886A
- Authority
- CN
- China
- Prior art keywords
- subsystem
- mode
- data
- climatic
- global
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012937 correction Methods 0.000 claims abstract description 5
- 238000001514 detection method Methods 0.000 claims abstract description 5
- 241001269238 Data Species 0.000 claims description 4
- PEDCQBHIVMGVHV-UHFFFAOYSA-N Glycerine Chemical compound OCC(O)CO PEDCQBHIVMGVHV-UHFFFAOYSA-N 0.000 claims description 4
- 239000000203 mixture Substances 0.000 claims description 3
- 230000001932 seasonal effect Effects 0.000 claims description 2
- 238000000034 method Methods 0.000 abstract description 10
- 238000007619 statistical method Methods 0.000 abstract description 3
- 239000011159 matrix material Substances 0.000 description 7
- 238000004458 analytical method Methods 0.000 description 3
- 230000008878 coupling Effects 0.000 description 2
- 238000010168 coupling process Methods 0.000 description 2
- 238000005859 coupling reaction Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Human Resources & Organizations (AREA)
- Tourism & Hospitality (AREA)
- Economics (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Marketing (AREA)
- Theoretical Computer Science (AREA)
- Development Economics (AREA)
- General Physics & Mathematics (AREA)
- Educational Administration (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Game Theory and Decision Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
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.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710754778.5A CN109426886A (en) | 2017-08-29 | 2017-08-29 | A kind of climatic prediction system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710754778.5A CN109426886A (en) | 2017-08-29 | 2017-08-29 | A kind of climatic prediction system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109426886A true CN109426886A (en) | 2019-03-05 |
Family
ID=65503422
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710754778.5A Pending CN109426886A (en) | 2017-08-29 | 2017-08-29 | A kind of climatic prediction system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109426886A (en) |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101852871A (en) * | 2010-05-25 | 2010-10-06 | 南京信息工程大学 | Short-term climate forecasting method based on empirical mode decomposition and numerical value set forecasting |
| CN104392097A (en) * | 2014-10-24 | 2015-03-04 | 封国林 | Seasonal precipitation analogue prediction method based on seasonal prediction mode |
| CN105678420A (en) * | 2016-01-06 | 2016-06-15 | 南京信息工程大学 | Cross-year and long-effectiveness climate prediction method |
| CN106251022A (en) * | 2016-08-08 | 2016-12-21 | 南京信息工程大学 | A kind of Short-term Climate Forecast method based on polyfactorial multiparameter similar set |
-
2017
- 2017-08-29 CN CN201710754778.5A patent/CN109426886A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101852871A (en) * | 2010-05-25 | 2010-10-06 | 南京信息工程大学 | Short-term climate forecasting method based on empirical mode decomposition and numerical value set forecasting |
| CN104392097A (en) * | 2014-10-24 | 2015-03-04 | 封国林 | Seasonal precipitation analogue prediction method based on seasonal prediction mode |
| CN105678420A (en) * | 2016-01-06 | 2016-06-15 | 南京信息工程大学 | Cross-year and long-effectiveness climate prediction method |
| CN106251022A (en) * | 2016-08-08 | 2016-12-21 | 南京信息工程大学 | A kind of Short-term Climate Forecast method based on polyfactorial multiparameter similar set |
Non-Patent Citations (2)
| Title |
|---|
| 张培群 等: "动力气候模式预测***业务化及其应用", 《应用气象学报》 * |
| 贾小龙 等: "我国短期气候预测技术进展", 《应用气象学报》 * |
Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111027166A (en) * | 2019-07-30 | 2020-04-17 | 天津大学 | Method for rapidly analyzing ocean elements in sea area around boat position |
| 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 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109426886A (en) | A kind of climatic prediction system | |
| US9825580B2 (en) | Method for constructing real-time solar irradiation metering network of gigawatts level photovoltaic power generation base | |
| Wang et al. | China׳ s regional assessment of renewable energy vulnerability to climate change | |
| CN106443833B (en) | A kind of numerical weather forecast method based on cloud computing | |
| CN103336995B (en) | The construction method of a kind of million kilowatt photovoltaic generation base light simultaneous measurement network | |
| CN111815041B (en) | Seawater temperature field prediction method based on improved EOF | |
| CN104182594A (en) | Method for drawing power system wind area graph | |
| CN112132365B (en) | Multi-scale feature-based forecast wind speed correction method and system | |
| CN112016588B (en) | Space autocorrelation clustering method facing remote correlation mode | |
| Hao et al. | Oasis cold island effect and its influence on air temperature: a case study of Tarim Basin, Northwest China | |
| Feng et al. | Relative roles of local disturbance, current climate and paleoclimate in determining phylogenetic and functional diversity in Chinese forests | |
| Ramon et al. | A perfect prognosis downscaling methodology for seasonal prediction of local-scale wind speeds | |
| Xu et al. | Effects of current climate, paleo-climate, and habitat heterogeneity in determining biogeographical patterns of evergreen broad-leaved woody plants in China | |
| Xing et al. | A practical wind farm siting framework integrating ecosystem services—A case study of coastal China | |
| Koo et al. | Future distributions of warm-adapted evergreen trees, Neolitsea sericea and Camellia japonica under climate change: ensemble forecasts and predictive uncertainty | |
| Weekes et al. | Low‐cost wind resource assessment for small‐scale turbine installations using site pre‐screening and short‐term wind measurements | |
| Li et al. | Spatiotemporal scale-dependent effects of urban morphology on meteorology: A case study in Beijing using observations and simulations | |
| CN110503064A (en) | A kind of power grid icing mima type microrelief automatic identifying method and system | |
| CN109214710A (en) | The evaluation method and system of haze numerical forecast result based on three factors | |
| Gan et al. | Wind power ramp forecasting based on least-square support vector machine | |
| CN112101608A (en) | Offshore wind farm site selection method and device | |
| CN106897790B (en) | Wind power prediction method and device for selecting optimal forecast grid point | |
| Shrivastava et al. | Performance of NCUM global weather modeling system in predicting the extreme rainfall events over the central India during the Indian summer monsoon 2016 | |
| Haibin et al. | Visualizing patterns of genetic landscapes and species distribution of Taxus wallichiana (Taxaceae), based on GIS and ecological niche models | |
| CN112446155A (en) | Method for obtaining spatial pattern simulation model of target crops |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190305 |