CN105631537A - Air quality forecast service system based on meteorological service platform - Google Patents
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Abstract
The present invention discloses an air quality forecast service system based on a meteorological service platform and provides an air quality forecast mode release method, a forecast revision method, and an estimation inspection model. With six types of pollutant concentrations outputted by a CUACE numerical mode as a basis, by using Kalman filtering and neural network correction technology, the guidance of product output by the six types of pollutant concentrations and AQI index forecast is realized, data, graphics and text are comprised, the GIS graphing ability is utilized, design and modification are carried out to process a corrected product, through making and integrated displaying and distributing modules, the sharing of a national air quality forecast product above a range of a city level is realized. A forecasting and early warning module provides six kinds of pollutant concentration monitoring live data interfaces, a pollutant drop zone concentration forecast function by user is provided, and at the same time, the product can be estimated and tested. The background service management module in a background management maintenance subsystem manages the basic information of users and image elements of a front display module. Through the implementation of the model, the forecast ability of air quality is enhanced.
Description
Technical field
Patent of the present invention belongs to information processing and the meteorological disaster field of website platform, is specifically related to the prediction of air quality operation system based on Meteorological Services platform
Background technology
Currently, China's atmospheric pollution situation is very severe, becomes increasingly conspicuous with the regional atmospheric environment problem that pellet (PM10), fine particle (PM2.5) are characteristic contamination. In order to thoroughly administer air environmental pollution, in JIUYUE, 2013 State Council has issued " prevention and control of air pollution plan ", the concrete measure that concrete plan air environmental pollution is administered, it is stipulated that " setting up monitoring and warning Emergency System, properly reply heavily contaminated weather "
Pearl River Delta City Air Quality Forecasting guide product above county level. Although 2013 achieve preliminary progress, but in service construction process, it is clearly present many-sided problems such as Monitoring Data underbraced, forecasting procedure are not deep enough, business service platform is weak, for continuing to advance whole nation environment weather monitoring and predicting and service system construction, intend the input by this project, carry out environment weather damage forecasting Warning Service system Construction.
Summary of the invention
Technical problem: the present invention is directed to current prediction of air quality system less, the feature that forecast accuracy is low, employing pattern releases the methods such as use, forecast correction, inspection and appraisal procedure, improves city AQI exponent prediction overview display; Pollutant levels and AQI exponent prediction guide product can be corrected; Air pollution quality substrate concentration can be monitored live data and carry out monitor in real time, it is provided that pollutant levels forecast and warning function; Forecast model products can be tested and assessment etc. Improve the meteorological departments at different levels prediction of air quality service ability in the whole nation and level as much as possible.
Technical scheme: based on the prediction of air quality operation system of Meteorological Services platform, its forecasting procedure comprises the steps of
1. pattern releases use:
(1-1) model predictions assay: the first step, classifying rationally mode error is interval; Second step, studies big error example; 3rd step, the dependency between analytical model error and season, weather condition; According to the above results, 4th step, determines that pattern is released by scheme;
(1-2) atmospheric chemistry model is released and is used technology
The demand that becomes more meticulous and pattern according to national, three regions and the issue environmental forecasting of relevant provinces and cities are released with the basis of technical research, forecast results such as calculating the PM10 of AQI foundation, PM2.5, ozone, carbon monoxide, sulfur dioxide, nitrogen oxides is set up mode power Statistic method when Various Seasonal/different weather according to website or lattice point, improves the accuracy of main pollution concentration forecast.
2. forecast correction technology
(2-1) monitoring materials of the 6 kinds of pollutant levels long-term sequence in prefecture-level above city, the accuracy rate that 6 kinds of pollutant levels are forecast by test mode are collected;
(2-2 for the forecast result of different pollutant levels, seek that Kalman Filtering moving average deviation is corrected, the method such as neutral net is corrected respectively, in order to introduce the up-to-date information of air in time, takes dynamic rolling to model when correcting;
(2-3) in order to solve the deviation that extreme value is simulated by pattern, simulation extreme value is corrected by rationally effective method of exploring further so that it is convergence true value;
(2-4) for different pollutant levels, on the basis of Correction Technology research and development, explore best ensemble of the correction methods method, obtain the forecast model products that accuracy rate is higher.
3. forecast model products makes
System provides the means such as customization, man-machine interaction to make the objective guide product of prediction of air quality of data form and the prediction of air quality service product of text, graphical format, the objective guide product of prediction of air quality realizes national air quality forecast model products sharing at business platforms at different levels by reporting services product library, and prediction of air quality service product is then externally offer prediction of air quality service.
4. forecast model products overview display
Set up national forecast model products overview display and enquiry module, realize that complete national environment weather is monitored 6 kinds of (PM10, PM2.5, SO2, NO2, CO, O3, lower same) pollutant levels occurring area forecast product and national prefectural level above city AQI exponent prediction products and carry out overview display; Realize 6 kinds of pollutant levels monitoring live data and historical data are carried out the query and statistical analysis of time, spatial dimension, classification.
5. forecast model products distribution
By the prediction of air quality product made, adopt multiple transmission channel, it is achieved distribute prediction of air quality product for different user object, it is ensured that user receives air quality service product on time.
6. value of forecasting inspection
Attach most importance to prediction of air quality AQI, value of forecasting inspection methods of marking and standards of grading are set up in research, prediction of air quality validity check is for air quality six key element (SO2, NO2, CO, O3, PM10, PM2.5), AQI grade and primary pollutant, and one is the methods of marking and the standards of grading that adopt statistical indicator method (average deviation, mean error, correlation coefficient etc.) to set up each key element; Two is set up the inspection of the air quality 24-72h value of forecasting with reference to " meteorological department's City Air Quality Forecasting quality examination and management Tentative Measures ". Other environment weather forecast key element is referred to prediction of air quality validity check and sets up methods of marking and standards of grading.
Based on the multiple statistical indicator value of forecasting method of inspection, adopt shown in following table:
Utilize multiple statistical indicator method to key element 24-72 hour forecast result inspection (P is predicted value, and O is observation) of environment weather
Set up the inspection of air quality 24h, 48h and the 72h value of forecasting. The scoring of prediction of air quality degree of accuracy is evaluated by following statistical model:
S=0.1f1+0.4f2+0.5f3
Wherein: S is forecast degree of accuracy scoring (taking 1 decimal), f1 is forecast primary pollutant correctness scoring, and f2 is forecast rank correctness scoring, and f3 is forecast index degree of accuracy scoring.
(6-1) primary pollutant correctness scoring (f1)
If the primary pollutant of forecast is consistent with fact, then it is judged to that primary pollutant forecast is correct, is otherwise mistake. Primary pollutant forecast correctness scoring is by 100 points of calculating, and primary pollutant forecast correctly gets a mark of 100, and mistake obtains 0 point.
(6-2) rank correctness scoring (f2) is forecast
Various pollutant rank correctness according to the form below scoring every day:
| Forecast fact | One-level | Two grades | Three grades | Level Four | Pyatyi | Six grades |
| One-level | 100 | 80 | 50 | 0 | 0 | 0 |
| Two grades | 80 | 100 | 80 | 50 | 0 | 0 |
| Three grades | 50 | 80 | 100 | 80 | 50 | 0 |
| Level Four | 0 | 50 | 80 | 100 | 80 | 50 |
| Pyatyi | 0 | 0 | 50 | 80 | 100 | 80 |
| Six grades | 0 | 0 | 0 | 50 | 80 | 100 |
One day, six kinds of pollutant level of accuracy comprehensive gradings took average, were calculated as follows:
F2=a1G1+a2G2+a3G3+a4G4+a5G5+a6G6
In formula: f2 is forecast rank correctness scoring (taking 1 decimal), G1, G2, G3, G4, G5, G6 are the level of accuracy scoring of six kinds of pollutant (SO2, NO2, CO, O3, PM2.5, PM10), a1, a2, a3, a4, a5, a6 are weight coefficient (first and second pollutant value is 0.35,0.25, and other pollutant value is 0.1).
(6-3) index degree of accuracy scoring (f3) is forecast
City Air Quality Forecasting forecasts air quality with the value range of air pollution index (AQI). One day, the scoring of certain air pollutants exponent prediction degree of accuracy was calculated as follows:
Hi represents i-th kind of pollutant index forecast degree of accuracy scoring, if Hi < 0, then Hi value is 0.
Six kinds of air pollutants Index A QI forecast that degree of accuracy comprehensive grading takes its average, can be calculated by following formula:
F3=b1H1+b2H2+b3H3+b4H4+b5H5+b6H6
In formula: f3 is forecast index degree of accuracy scoring (taking 1 decimal), H1, H2, H3, H4, H5, H6 respectively six kinds of pollutant AQI exponent prediction degree of accuracy scoring, b1, b2, b3, b4, b5, b6 be weight coefficient (according to six kinds of pollutant AQI indexes from big to small respectively value be 0.5,0.3,0.05,0.05,0.05,0.05).
7. mode evaluation
(7-1) representative observation website is selected, according to hour observation data and a forecast data, calculate the average deviation of 6 kinds of major pollutants 24h, 48h, 72h timeliness concentration predictions, root-mean-square-deviation and error percentile, the deviation situation of test mode forecast result respectively.
(7-2) compliance evaluation
Select representative observation website, according to hour observation data and a forecast data, calculate the correlation coefficient of 6 kinds of major pollutants 24h, 48h, 72h timeliness concentration predictions and observation respectively, the concordance of test mode forecast.
(7-3) assessment of settling in an area is polluted
Adopt the target method of inspection (Objectmethod), the evaluation profile value of forecasting to polluting scope of settling in an area.
(7-4) exceed standard day/daily forecast up to standard assessment
Feature according to prediction of air quality service, (excellent for six class levels of contamination, good, slight pollution, intermediate pollution, serious pollution, severe contamination), the respectively index such as the hit rate of model predictions, empty report rate, rate of failing to report, air quality is exceeded standard the value of forecasting of day and day up to standard by evaluation profile.
Beneficial effect
The enforcement of the technical program, prediction of air quality system will be built up, it is effectively improved the prediction of air quality ability of National Meteorological Center, and can promote the use of in national meteorological departments at different levels, judge that air pollution situation, the at utmost impact of pollution abatement weather provide technical support and decision references for relevant department in conjunction with practical situation, provide healthy guide for the public.
Accompanying drawing explanation
Fig. 1 is a kind of prediction of air quality operation system structured flowchart based on Meteorological Services platform.
Detailed description of the invention
Prediction of air quality system each generic module is combined, is assembled, forms the big granularity service that can be used by upper layer application better. Prediction of air quality system module is in combination, assembling process, it is also desirable to use the sorts of systems resource service that database elements module provides.
Specific embodiment of the invention case is given below:
(1) Forecast Mode NWP product application module is released by model predictions inspection and atmospheric chemistry model and is provided 6 kinds of pollutant levels forecast model products with the CUACE numerical model output after improving to carry out pattern by technology to release use, generate national prefectural level 6 kinds of above city pollutant levels and AQI exponent prediction guide product. User is according to the analysis to live or historical data etc., national prefectural level 6 kinds of above city pollutant levels and AQI exponent prediction guide product are carried out product correct, generate revised national prefectural level 6 kinds of above city pollutant levels and AQI exponent prediction guide product. User exports national prefectural level 6 kinds of above city pollutant levels and AQI exponent prediction guide product as required, and output of products form includes data product, graphic product and textual products.
(2) forecast correction pattern is according to the analysis to live or historical data etc., monitoring materials and AQI exponent prediction product to 6 kinds of pollutant levels long-term sequence, the accuracy rate that pollutant levels are forecast by test mode, utilize Kalman Filtering moving average deviation to correct, 6 kinds of pollutant levels and AQI exponent prediction product are corrected by the method such as neutral net, it is ensured that product is accurate. Utilize thematic charting ability abundant for GIS, design and amendment drawing board, revised prediction of air quality product is reprocessed, makes prediction of air quality product both artistic and practical. User exports national prefectural level 6 kinds of above city pollutant levels and AQI exponent prediction product as required, and output of products form includes data product, graphic product and textual products.
(3) forecast model products makes the prediction of air quality product data that module inputs according to user, and Auto-matching has made drawing board, it is achieved automatization, customization make prediction of air quality product. Prediction of air quality product, according to the analysis to live or historical data etc., is corrected by user, then utilizes thematic map ability abundant for GIS, makes prediction of air quality product as required. There is provided and export 6 kinds of pollutant levels and AQI index objective forecast product with data product form, it is provided that with text, the graphic product form output prediction of air quality service product such as 6 kinds of pollutant air quality concentration and AQI exponent prediction figure.
(4) overview display module realizes forecast model products visualization function and realizes relating to all product data visual display function on map vector of prediction of air quality business; Wherein product data specifically include and 1. observe data: the observation data of the Atmospheric components such as PM2.5 that China Meteorological Administration's atmospheric environment observation net is observed, PM10, carbon dioxide, total amount of ozone, atmospheric aerosol, reactant gas. These data divide live data and historical data; Air quality is carried out the data of real-time monitored by state environmental monitoring master station National Environmental air monitering net; The data such as the ozone of satellite data institute inverting, NO2, SO2; 2. mode data: the atmospheric chemistry model forecast data to air pollutant concentration; 3. prediction of air quality data etc. Realize the forecast model products query statistic function all data to relating to prediction of air quality business simultaneously, realize the query statistic function according to one or more combination conditions such as time, area of space, classifications, and query statistic result visualization is shown on map, or with chart, Document type data output. And the amplification of map, reduce, refresh, the basic operation such as roaming, the management of figure layer, map display range management etc.
(5) air quality About The Guiding Forecast product is handed down to meteorological department of each province by National Meteorological Center's reporting services product library by forecast model products distribution module, provincial its revised prediction of air quality product is uploaded to China Meteorological Administration, it is achieved national air quality forecast model products is shared in country, region, province and district city level Four.
(6) forecast verification contrasts with pollutant levels predicted value according to 6 kinds of pollutant levels monitoring live data of air quality with forecast accuracy checking function system in evaluation module, calculates pollutant levels forecast accuracy. AQI exponent prediction deviation function system monitors live data according to air pollution quality substrate concentration, and inspection AQI exponent prediction deviation also calculates bias contribution, and AQI exponent prediction bias contribution is shown with chart or textual form, exported. AQI rank forecast departure function monitors live data according to air pollution quality substrate concentration, and inspection AQI rank forecast departure also calculates bias contribution, and AQI rank forecast departure result is shown with chart or textual form, exported. Primary pollutant forecasts that preparatory function system monitors live data according to air pollution quality substrate concentration, and whether inspection air quality primary pollutant forecast is correct; Primary pollutant is forecast, and incorrect result data carries out contrast display, output in map vector and chart.
Claims (1)
1., based on the prediction of air quality operation system of Meteorological Services platform, comprise the steps of
1. pattern releases use:
(1-1) model predictions assay: the first step, classifying rationally mode error is interval; Second step, studies big error example; 3rd step, the dependency between analytical model error and season, weather condition; According to the above results, 4th step, determines that pattern is released by scheme;
(1-2) atmospheric chemistry model is released and is used technology
The demand that becomes more meticulous and pattern according to national, three regions and provincial, and municipal level issue environmental forecasting are released with the basis of technical research, forecast results such as calculating the PM10 of AQI foundation, PM2.5, ozone, carbon monoxide, sulfur dioxide, nitrogen oxides is set up mode power Statistic method when Various Seasonal/different weather according to website or lattice point, improves the accuracy of main pollution concentration forecast;
2. forecast correction technology
(2-1) monitoring materials of the 6 kinds of pollutant levels long-term sequence in prefecture-level above city, the accuracy rate that 6 kinds of pollutant levels are forecast by test mode are collected;
(2-2) for the forecast result of different pollutant levels, seek that Kalman Filtering moving average deviation is corrected, the method such as neutral net is corrected respectively, in order to introduce the up-to-date information of air in time, takes dynamic rolling to model when correcting;
(2-3) in order to solve the deviation that extreme value is simulated by pattern, simulation extreme value is corrected by rationally effective method of exploring further so that it is convergence true value;
(2-4) for different pollutant levels, on the basis of Correction Technology research and development, explore best ensemble of the correction methods method, obtain the forecast model products that accuracy rate is higher;
3. forecast model products makes
System provides the means such as customization, man-machine interaction to make the objective guide product of prediction of air quality of data form and the prediction of air quality service product of text, graphical format, the objective guide product of prediction of air quality realizes national air quality forecast model products sharing at business platforms at different levels by reporting services product library, and prediction of air quality service product is then externally offer prediction of air quality service;
4. forecast model products overview display
Set up national forecast model products overview display and enquiry module, it is achieved complete national environment weather 6 kinds of PM10, PM2.5, SO2, NO2, CO, O3 pollutant levels occurring area forecast products of monitoring and above city, national prefectural level AQI exponent prediction product are carried out overview display; Realize 6 kinds of pollutant levels monitoring live data and historical data are carried out the query and statistical analysis of time, spatial dimension, classification;
5. forecast model products distribution
By the prediction of air quality product made, adopt multiple transmission channel, it is achieved distribute prediction of air quality product for different user object, it is ensured that user receives air quality service product on time;
6. value of forecasting inspection
Attaching most importance to prediction of air quality AQI, value of forecasting inspection methods of marking and standards of grading are set up in research, and prediction of air quality validity check is for air quality six key element SO2, NO2, CO, O3, PM10, PM2.5, AQI grade and primary pollutant;
7. mode evaluation
(7-1) forecast departure assessment
Select representative observation website, according to hour observation data and a forecast data, calculate the average deviation of 6 kinds of major pollutants 24h, 48h, 72h timeliness concentration predictions, root-mean-square-deviation and error percentile, the deviation situation of test mode forecast result respectively;
(7-2) compliance evaluation
Select representative observation website, according to hour observation data and a forecast data, calculate the correlation coefficient of 6 kinds of major pollutants 24h, 48h, 72h timeliness concentration predictions and observation respectively, the concordance of test mode forecast;
(7-3) assessment of settling in an area is polluted
Adopt the target method of inspection (Objectmethod), the evaluation profile value of forecasting to polluting scope of settling in an area;
(7-4) exceed standard day/daily forecast up to standard assessment
Feature according to prediction of air quality service, for six class levels of contamination, respectively the hit rate of model predictions, empty report rate, rate of failing to report index, air quality is exceeded standard the value of forecasting of day and day up to standard by evaluation profile.
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