CN107179568A - A kind of precipitation forecast accuracy assessment method - Google Patents
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- CN107179568A CN107179568A CN201710370025.4A CN201710370025A CN107179568A CN 107179568 A CN107179568 A CN 107179568A CN 201710370025 A CN201710370025 A CN 201710370025A CN 107179568 A CN107179568 A CN 107179568A
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Abstract
Forecast area is divided into some grids the invention discloses a kind of precipitation forecast accuracy assessment method, including step 1；The total precipitation error in step 2 CALCULATING PREDICTION region, determines whether the total precipitation error is qualified；Step 3 CALCULATING PREDICTION region period precipitation maximum error；Determine whether period precipitation maximum error is qualified；The existing time error in step 4 CALCULATING PREDICTION region period precipitation peak；Determine whether the existing time error in period precipitation peak is qualified；Step 5 calculates grid precipitation maximum error；Determine whether grid precipitation maximum error is qualified；Step 6 calculates rainfall center offset errors；Determine whether rainfall center offset errors are qualified；The step 7 setting evaluation time cycle；Step 8, determination evaluation sample size；Step 9 determines that qualified number of times carries out synthesis precision calculating according to the error amount of step 26；Solve precipitation forecast accuracy assessment do not seek unity of standard it is serious the problems such as constrain effect and the function of precipitation forecast.
Description
Technical field
The invention belongs to precipitation forecast accuracy assessment technology, more particularly to a kind of precipitation forecast accuracy assessment method.
Background technology
Weather forecast is exactly the rule using Atmosphere changes, according to current and recent weather situation, to a certain area not
The weather conditions come in the regular period are predicted.Numerical weather forecast is to carry out the pre- of digital quantization to future weather situation
Report, with the development of computer technology, the progress of observation method, and gos deep into, Numerical Weather to atmospheric physical processes understanding
Forecast has made much progress, the Main Means as weather forecast.The Numerical Precipitation Forecast that wherein becomes more meticulous is weather forecast skill
A technology most difficult in art, it needs to utilize high-performance computer computing, is simulated and reflected by the equation of numerical model
The differentiation of the various meteorological elements of atmospheric condition.
Forecast of Precipitation in high resolution, as the forecast to following precipitation particular number value, is comprehensive utilization modem weather forecast skill
Art and information technology, particularly internet cloud computing technique, rely on high-spatial and temporal resolution numerical forecasting product and the live number of history
According to by text based, descriptive, qualitatively traditional weather forecast product system, developing into fixed point, quantitative, high space-time
The modem weather forecast model products system of resolution ratio, its achievement is widely used in water conservancy, electric power, traffic, the energy, insurance, medium, meal
The industries such as drink, tourism, environment.
It is the inevitable requirement of social development that precipitation forecast achievement, which more becomes more meticulous, but due to lacking the mark of forecast precision evaluation
Accurate, it is impossible to which that the quality of forecast result is made an appraisal, grade is beyond count where its precision, to Forecast of Precipitation in high resolution
Achievement causes obstacle in the application of every profession and trade；Serious effect and the function for constraining precipitation forecast.
The content of the invention：
The technical problem to be solved in the present invention：A kind of precipitation forecast accuracy assessment method is provided, to solve prior art pair
The accuracy assessment of precipitation forecast, which is not sought unity of standard, to be caused seriously to constrain the technical problems such as effect and the function of precipitation forecast.
Technical solution of the present invention：
A kind of precipitation forecast accuracy assessment method, it includes：
Step 1, forecast area is divided into some grids；
The total precipitation error in step 2, CALCULATING PREDICTION region, determines whether the total precipitation error is qualified；
Step 3, CALCULATING PREDICTION region period precipitation maximum error；Determine whether period precipitation maximum error closes
Lattice；
The existing time error in step 4, CALCULATING PREDICTION region period precipitation peak；Determine whether the existing time error in period precipitation peak closes
Lattice；
Step 5, calculating grid precipitation maximum error；Determine whether grid precipitation maximum error is qualified；
Step 6, calculating rainfall center offset errors；Determine whether rainfall center offset errors are qualified；
Step 7, setting evaluation time cycle；
Step 8, determination evaluation sample size；
Step 9, determine qualified number of times according to step 2-6 error amount, carry out synthesis precision calculating.
The total precipitation error in CALCULATING PREDICTION region described in step 2, determines the whether qualified method of the total precipitation error
For：Missed the absolute value of the relative error in forecast area between the total precipitation and predicted value as the total precipitation in forecast area
Difference, it is qualified that the total precipitation error, which is less than 25%, and the total precipitation error formula is in forecast area：
Period precipitation maximum error in CALCULATING PREDICTION region described in step 3；Determining period precipitation maximum error is
No qualified method is：Day part precipitation in forecast area is ranked up, maximum therein is period precipitation maximum,
Period precipitation maximum error is the absolute value for surveying the relative error between period precipitation maximum and predicted value, period
Precipitation worst error≤25% is qualified
The existing time error in period precipitation peak in CALCULATING PREDICTION region described in step 4；Determining the existing time error in period precipitation peak is
No qualified method is：The absolute value of relative error between actual measurement period precipitation peak is current between predicted value is period precipitation peak
Existing time error, is calculated by formula (3), and existing time error≤25% in period precipitation peak is qualified
Grid precipitation maximum error is calculated described in step 5；Determine whether grid precipitation maximum error is qualified
Method is：Grid precipitation in forecast area is ranked up, maximum therein is grid precipitation maximum, grid precipitation
Amount maximum error is the absolute value for surveying the relative error between grid precipitation maximum and predicted value, is calculated by formula (4),
Lattice point precipitation maximum error≤25% is qualified
Rainfall center offset errors are calculated described in step 6；Determine the whether qualified method of rainfall center offset errors
For：Rainfall center offset errors：Reflect error of the precipitation in forecast area distribution, calculated by formula (5), rainfall center skew
It is qualified to be worth error≤25%
The setting evaluation time cycle described in step 7, the evaluation cycle is set to year.
Evaluation sample size is determined described in step 8, evaluation sample size is 30% of all sample numbers in the evaluation cycle, is pressed
Formula (6) is calculated, and result of calculation round numbers, decimal place rounds up
Synthesis precision computational methods are：Whether qualified calculate according to step 2 to 65 indexs respectively to every sample, will close
The indicator-specific statistics of lattice is that the total precipitation forecasts that qualified number of times, period precipitation maximum forecast that qualified number of times, period precipitation peak show
The qualified number of times of Time Forecast, lattice point precipitation maximum forecast that qualified number of times, rainfall center deviant forecast qualified number of times, by formula
(7) calculate, obtain synthesis precision
In formula：N1 is that the total precipitation forecasts qualified number of times；N2 is that period precipitation maximum forecasts qualified number of times；N3 is the period
The qualified number of times of the existing Time Forecast in precipitation peak；N4 is that grid maximum rainfall value difference forecasts qualified number of times；N5 is rainfall center deviant
Forecast qualified number of times.
It also includes synthesis precision rank division method, and its method is：Synthesis precision is more than or equal to 85% accuracy class
For first；Synthesis precision is less than 85%, and more than 75% accuracy class is second；Synthesis precision is less than 75%, is third more than 65%.
Beneficial effects of the present invention：
Precipitation forecast value is carried out the division that becomes more meticulous by the present invention, and the precision of Forecast of Precipitation in high resolution is commented by combination
It is fixed, index is included in forecast area between the total precipitation, period precipitation maximum, period precipitation peak are current, lattice point precipitation most
Big value, rainfall center deviant etc.；It is approximately rectangular area by forecast area, is then divided into some grids by application demand,
Each scale error is calculated, qualified number of times is counted；Finally give precipitation forecast synthesis precision；Finally according to synthesis precision
Grade carries out category forecast；Solving prior art and the accuracy assessment of precipitation forecast is not sought unity of standard causes seriously to constrain
The technical problem such as the effect of precipitation forecast and function.
Embodiment：
A kind of precipitation forecast accuracy assessment method, it includes：
Step 1, forecast area is divided into some grids；It is approximately rectangular area by forecast area, then by by application
Demand is divided into some grids.
The total precipitation error in step 2, CALCULATING PREDICTION region, determines whether the total precipitation error is qualified；
The total precipitation error in CALCULATING PREDICTION region described in step 2, determines the whether qualified method of the total precipitation error
For：Missed the absolute value of the relative error in forecast area between the total precipitation and predicted value as the total precipitation in forecast area
Difference, it is qualified that the total precipitation error, which is less than 25%, and the total precipitation error formula is in forecast area：
Step 3, CALCULATING PREDICTION region period precipitation maximum error；Determine whether period precipitation maximum error closes
Lattice；
Period precipitation maximum error in CALCULATING PREDICTION region described in step 3；Determining period precipitation maximum error is
No qualified method is：Day part precipitation in forecast area is ranked up, maximum therein is period precipitation maximum,
Period precipitation maximum error is the absolute value for surveying the relative error between period precipitation maximum and predicted value, period
Precipitation worst error≤25% is qualified
The existing time error in step 4, CALCULATING PREDICTION region period precipitation peak；Determine whether the existing time error in period precipitation peak closes
Lattice；
The existing time error in period precipitation peak in CALCULATING PREDICTION region described in step 4；Determining the existing time error in period precipitation peak is
No qualified method is：The absolute value of relative error between actual measurement period precipitation peak is current between predicted value is period precipitation peak
Existing time error, is calculated by formula (3), and existing time error≤25% in period precipitation peak is qualified
Step 5, calculating grid precipitation maximum error；Determine whether grid precipitation maximum error is qualified；
Grid precipitation maximum error is calculated described in step 5；Determine whether grid precipitation maximum error is qualified
Method is：Grid precipitation in forecast area is ranked up, maximum therein is grid precipitation maximum, grid precipitation
Amount maximum error is the absolute value for surveying the relative error between grid precipitation maximum and predicted value, is calculated by formula (4),
Lattice point precipitation maximum error≤25% is qualified
Step 6, calculating rainfall center offset errors；Determine whether rainfall center offset errors are qualified；
Rainfall center offset errors are calculated described in step 6；Determine the whether qualified method of rainfall center offset errors
For：Rainfall center offset errors：Reflect error of the precipitation in forecast area distribution, calculated by formula (5), rainfall center skew
It is qualified to be worth error≤25%
Step 7, setting evaluation time cycle；
The setting evaluation time cycle described in step 7, the evaluation cycle is set to year.
It is annual that forecast precision is evaluated once, prior year Forecast of Precipitation in high resolution precision is carried out before March 31 next year
Evaluation.
Step 8, determination evaluation sample size；
Evaluation sample size is determined described in step 8, evaluation sample size is 30% of all sample numbers in the evaluation cycle, is pressed
Formula (6) is calculated, and result of calculation round numbers, decimal place rounds up
All play precipitation forecasts in periodic regime will be evaluated to sort by the total precipitation size, from the field that the total precipitation is maximum
It is secondary to start, the play of evaluation sample size is extracted as evaluation sample.
Step 9, determine qualified number of times according to step 2-6 error amount, carry out synthesis precision calculating.
Synthesis precision computational methods are：Whether qualified calculate according to step 2 to 65 indexs respectively to every sample, will close
The indicator-specific statistics of lattice is that the total precipitation forecasts that qualified number of times, period precipitation maximum forecast that qualified number of times, period precipitation peak show
The qualified number of times of Time Forecast, lattice point precipitation maximum forecast that qualified number of times, rainfall center deviant forecast qualified number of times, by formula
(7) calculate, obtain synthesis precision
In formula：N1 is that the total precipitation forecasts qualified number of times；N2 is that period precipitation maximum forecasts qualified number of times；N3 is the period
The qualified number of times of the existing Time Forecast in precipitation peak；N4 is that grid maximum rainfall value difference forecasts qualified number of times；N5 is rainfall center deviant
Forecast qualified number of times.
It also includes synthesis precision rank division method, and its method is：Synthesis precision is more than or equal to 85% accuracy class
For first；Synthesis precision is less than 85%, and more than 75% accuracy class is second；Synthesis precision is less than 75%, is third more than 65%.
Forecasting model must survey the accuracy assessment of precipitation and predicted value by same area, identical period and reach requirement
Afterwards, reporting services can be carried out in next year.
Forecast precision and application
A) forecast achievement of the synthesis precision more than second class can be used for the formal forecast of the sector applications such as water conservancy, agricultural.
B) synthesis precision can be used for the referential forecast of the sector applications such as water conservancy, agricultural in the forecast achievement of third class.
C) forecast achievement of the synthesis precision below third class is only used for referential forecast.
Gridded data can be obtained with interpolation method by actual measurement station data by evaluating measured data used in the present invention, also may be used
Obtained from national weather department associated mechanisms.
Claims (10)
1. a kind of precipitation forecast accuracy assessment method, it includes：
Step 1, forecast area is divided into some grids；
The total precipitation error in step 2, CALCULATING PREDICTION region, determines whether the total precipitation error is qualified；
Step 3, CALCULATING PREDICTION region period precipitation maximum error；Determine whether period precipitation maximum error is qualified；
The existing time error in step 4, CALCULATING PREDICTION region period precipitation peak；Determine whether the existing time error in period precipitation peak is qualified；
Step 5, calculating grid precipitation maximum error；Determine whether grid precipitation maximum error is qualified；
Step 6, calculating rainfall center offset errors；Determine whether rainfall center offset errors are qualified；
Step 7, setting evaluation time cycle；
Step 8, determination evaluation sample size；
Step 9, determine qualified number of times according to step 2-6 error amount, carry out synthesis precision calculating.
2. a kind of precipitation forecast accuracy assessment method according to claim 1, it is characterised in that：Calculating described in step 2
The total precipitation error in forecast area, determining the total precipitation error, whether qualified method is：By the total precipitation in forecast area
The absolute value of relative error between predicted value is less than 25% as the total precipitation error in forecast area, the total precipitation error
To be qualified, the total precipitation error formula is in forecast area：
3. a kind of precipitation forecast accuracy assessment method according to claim 1, it is characterised in that：Calculated described in step 3 pre-
Report region period precipitation maximum error；Determining period precipitation maximum error, whether qualified method is：By forecast district
Day part precipitation is ranked up in domain, and maximum therein is period precipitation maximum, and period precipitation maximum error is
The absolute value of the relative error between period precipitation maximum and predicted value is surveyed, period precipitation worst error≤25% is
It is qualified
4. a kind of precipitation forecast accuracy assessment method according to claim 1, it is characterised in that：Calculated described in step 4 pre-
Report the existing time error in region period precipitation peak；Determining the existing time error in period precipitation peak, whether qualified method is：Survey the period
The absolute value of relative error between precipitation peak is current between predicted value is the existing time error in period precipitation peak, is calculated by formula (3),
Existing time error≤25% in period precipitation peak is qualified
5. a kind of precipitation forecast accuracy assessment method according to claim 1, it is characterised in that：Net is calculated described in step 5
Lattice precipitation maximum error；Determining grid precipitation maximum error, whether qualified method is：By grid in forecast area
Precipitation is ranked up, and maximum therein is grid precipitation maximum, and grid precipitation maximum error is actual measurement grid
The absolute value of relative error between precipitation maximum and predicted value, is calculated by formula (4), and lattice point precipitation maximum error≤
25% is qualified
6. a kind of precipitation forecast accuracy assessment method according to claim 1, it is characterised in that：Drop is calculated described in step 6
Heart offset errors in the rain；Determining rainfall center offset errors, whether qualified method is：Rainfall center offset errors：Instead
Error of the precipitation in forecast area distribution is reflected, is calculated by formula (5), rainfall center offset errors≤25% is qualified
7. a kind of precipitation forecast accuracy assessment method according to claim 1, it is characterised in that：Setting is commented described in step 7
Fix time the cycle, the evaluation cycle is set to year.
8. a kind of precipitation forecast accuracy assessment method according to claim 1, it is characterised in that：Determine to comment described in step 8
Determine sample size, evaluation sample size is 30% of all sample numbers in the evaluation cycle, is calculated by formula (6), result of calculation is rounded
Number, decimal place rounds up
9. a kind of precipitation forecast accuracy assessment method according to claim 1, it is characterised in that：Synthesis precision computational methods
For：Whether qualified calculate according to step 2 to 65 indexs respectively to every sample, be that the total precipitation is pre- by qualified indicator-specific statistics
Qualified number of times, period precipitation maximum is reported to forecast the qualified number of times of the existing Time Forecast in qualified number of times, period precipitation peak, lattice point precipitation
Measure maximum and forecast that qualified number of times, rainfall center deviant forecast qualified number of times, calculated by formula (7), obtain synthesis precision
In formula：N1 is that the total precipitation forecasts qualified number of times；N2 is that period precipitation maximum forecasts qualified number of times；N3 is period precipitation
The qualified number of times of the existing Time Forecast in peak；N4 is that grid maximum rainfall value difference forecasts qualified number of times；N5 forecasts for rainfall center deviant
Qualified number of times.
10. a kind of precipitation forecast accuracy assessment method according to claim 1, it is characterised in that：It also includes comprehensive essence
Rank division method is spent, its method is：It is first that synthesis precision, which is more than or equal to 85% accuracy class,；Synthesis precision is less than 85%,
More than 75% accuracy class is second；Synthesis precision is less than 75%, is third more than 65%.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108802859A (en) * | 2018-06-06 | 2018-11-13 | 中国气象局北京城市气象研究所 | A kind of method of Objective Test On Numberical precipitation forecast tensor |
| WO2018214364A1 (en) * | 2017-05-23 | 2018-11-29 | 贵州东方世纪科技股份有限公司 | Precipitation forecast accuracy assessment method |
| CN109871988A (en) * | 2019-01-28 | 2019-06-11 | 河海大学 | A kind of flood forecasting early warning precision analytical method |
| CN111639810A (en) * | 2020-06-01 | 2020-09-08 | 宁波市水利水电规划设计研究院有限公司 | Rainfall forecast precision evaluation method based on flood prevention demand |
| CN116068676A (en) * | 2023-03-07 | 2023-05-05 | 南京气象科技创新研究院 | General comprehensive evaluation method for rainfall forecast cross-magnitude |
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| US5406481A (en) * | 1993-06-30 | 1995-04-11 | Nippon Telegraph And Telephone Corporation | Rainfall, snowfall forecast apparatus and method |
| CN105068153A (en) * | 2015-06-19 | 2015-11-18 | 中国气象科学研究院 | Regional automatic rainfall station hourly rainfall data quality control system and method |
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| CN107179568A (en) * | 2017-05-23 | 2017-09-19 | 贵州东方世纪科技股份有限公司 | A kind of precipitation forecast accuracy assessment method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2018214364A1 (en) * | 2017-05-23 | 2018-11-29 | 贵州东方世纪科技股份有限公司 | Precipitation forecast accuracy assessment method |
| CN108802859A (en) * | 2018-06-06 | 2018-11-13 | 中国气象局北京城市气象研究所 | A kind of method of Objective Test On Numberical precipitation forecast tensor |
| CN109871988A (en) * | 2019-01-28 | 2019-06-11 | 河海大学 | A kind of flood forecasting early warning precision analytical method |
| CN109871988B (en) * | 2019-01-28 | 2021-06-01 | 河海大学 | Flood forecast early warning precision analysis method |
| CN111639810A (en) * | 2020-06-01 | 2020-09-08 | 宁波市水利水电规划设计研究院有限公司 | Rainfall forecast precision evaluation method based on flood prevention demand |
| CN111639810B (en) * | 2020-06-01 | 2023-05-09 | 宁波市水利水电规划设计研究院有限公司 | Rainfall forecast precision assessment method based on flood prevention requirements |
| CN116068676A (en) * | 2023-03-07 | 2023-05-05 | 南京气象科技创新研究院 | General comprehensive evaluation method for rainfall forecast cross-magnitude |
| CN116068676B (en) * | 2023-03-07 | 2023-06-02 | 南京气象科技创新研究院 | General comprehensive evaluation method for rainfall forecast cross-magnitude |
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