CN105954821A - Typical rainfall event selection method for numerical atmospheric model - Google Patents

Typical rainfall event selection method for numerical atmospheric model Download PDF

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CN105954821A
CN105954821A CN201610248862.5A CN201610248862A CN105954821A CN 105954821 A CN105954821 A CN 105954821A CN 201610248862 A CN201610248862 A CN 201610248862A CN 105954821 A CN105954821 A CN 105954821A
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rainfall
numerical value
atmospheric model
typical
value atmospheric
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CN105954821B (en
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刘佳
李传哲
田济扬
严登华
于福亮
王洋
聂汉江
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China Institute of Water Resources and Hydropower Research
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    • G01—MEASURING; TESTING
    • G01W—METEOROLOGY
    • G01W1/00—Meteorology
    • G01W1/10—Devices for predicting weather conditions

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Abstract

The present invention relates to a typical rainfall event selection method for a numerical atmospheric model. The method comprises: a typical rainfall event classification method based on individual rainfall amount; a rainfall time inhomogeneity calculation method; a rainfall spatial inhomogeneity calculation method; and a typical rainfall event selection method based on a rainfall spatial-temporal inhomogeneity coefficient. In the invention, the standardized typical rainfall event selection method is provided for selection and adjustment of a numerical atmospheric model from the perspective of rainfall amount and spatial-temporal distribution, the rainfall type is quantitatively described, and the simulation accuracy of the numerical atmospheric model for different types of rainfall in a certain research area is measured, which can not only provide the basis for model setting in the research area, but also shows that the model is more suitable for which type of rainfall, provides the basis for model selection and provides reasonable numerical atmospheric model simulation plans with respect to different types of rainfall for relevant departments such as meteorology, water conservancy and the like. The typical rainfall event selection method of the invention can be widely applied.

Description

A kind of typical catchment choosing method for numerical value atmospheric model
Technical field
The present invention relates to numerical value rainfall forecast technical field, be specifically related to a kind of typical rainfall for numerical value atmospheric model Event choosing method
Background technology
The simulation of rainfall and forecast not only life for people provides convenient, and contribute to people take measures to reduce or Avoid the loss that the natural disaster caused because of rainfall is likely to result in.Since numerical value atmospheric model occurs, quantitative rainfall simulation Becoming a reality with forecast, the computer technology of development, the more renewal of numerical value atmospheric model and improvement provide strong Technical support.But due to rainfall forming process with occur by large scale atmospheric circulation, ocean current, sea position, land, landform, underlay Many impacts such as face and mankind's activity, therefore there is many uncertainties in the spatial and temporal distributions of rainfall, and its forecast difficulty is the most relatively Other meteorological elements are big.
From the point of view of a certain numerical value atmospheric model, such as WRF pattern, before rainfall is simulated or forecasts by it, it is right to need The initial fields of this pattern, physical parameter scheme, resolution etc. are configured, and for the spatial and temporal distributions of different regions with accumulative The rainfall play that rainfall is the most different, the simulation of different plan of establishment acquisitions or the certain difference that predicted the outcome, some is arranged The simulation of scheme and forecast result are more nearly measured value, and the simulation of other schemes is poor with forecast result.But at present for Certain numerical value atmospheric model, does not form a set of typical case's method of choosing of catchment, judge its plan of establishment if appropriate for The simulation of this study area type rainfall and forecast.To a certain degree, the tool that arranges of numerical value atmospheric model bears the character of much blindness.
Summary of the invention
The present invention devises a kind of typical catchment choosing method for numerical value atmospheric model, comprehensive consideration rainfall Time inhomogeneities, spatial non-uniformity and single storm, its solve the technical problem that be how to choose typical case catchment Probe into a certain numerical value atmospheric model to the rainfall simulation of study area and Prediction version, thus be that this pattern is to certain type rainfall Simulation provide the optimal plan of establishment with forecast.
In order to solve the technical problem of above-mentioned existence, present invention employs below scheme:
A kind of typical catchment choosing method for numerical value atmospheric model, including following step:
Step 1, choosing of numerical value atmospheric model and choosing of driving data；
Step 2, typical catchment based on single storm are classified；
Step 3, typical catchment based on secondary rainfall space-time inhomogeneities are chosen；
Step 4, the physical parameter scheme of numerical value atmospheric model and the setting of Grid Nesting scheme and simulation.
The most conventional driving data source has two kinds, and one is the product of Environmental forecasting centre (NCEP), bag Include FNL and GFS data；Another kind is the product of European Center for Medium Weather Forecasting (ECMWF), including ERA40 and ECMWF Forcast data.Wherein FNL and ERA40 is for the simulation of history catchment, and GFS and ECMWF forcast will be for future The forecast of catchment.Driving data provides the initial condition of pattern simulation and forecast, different data for numerical value atmospheric model Final simulation or forecast result there is certain impact.Therefore in step 1 driving data choose the most important.
Different numerical value atmospheric models have different physical parameter schemes.As a example by current state-of-the-art WRF pattern, its bag The principal physical process contained has microphysical processes, Parameterization process, land surface emissivity, boundary region etc..Wherein, Microphysical Process is primarily referred to as the formation of cloud particle, increases and formed the microphysics process of precipitation, along with phase transformation and the energy thereof of water The change procedure of amount；Cumulus Convection Process along with cloud cluster generate, development, vigorous and due to temperature do not concurrently form right Stream, the closest with contacting of Precipitation Process；Land surface emissivity directly affects surface water heat flux, and affect lower atmosphere layer circulation and The simulation of Vapor convergence amount；The influence of arrangement lower atmosphere layer key element of boundary region, and also can be to upper atmosphere by vertical transport Produce impact.Each physical process contains again various physical parameters scheme, and these Parameterization Scheme are all to concrete physics The mathematical description of process, is specifically shown in following table:
The combination of different physical scheme can produce considerable influence to analog result, directly affects rainfall simulation with pre- The accuracy of report, therefore arranges physical parameter scheme the most crucial to then numerical value atmospheric model in step 4.
Grid Nesting scheme is the NO emissions reduction scheme of exponential quantity atmospheric model, owing to the product of NCEP or ECMWF is to make With the operation acquisition of Global Model, spatial resolution is relatively low, generally 0.5 ° × 0.5 ° or 1 ° × 1 °, it is impossible in being directly used in Little yardstick numerical value atmospheric simulation and forecast.And the Numerical Weather simulation of reality is with forecast, the size of mesh opening of innermost layer should be less than 10km × 10km, the simulation that can make numerical value atmospheric model is more fine with forecast, can accurate description local weather conditions.Number Value atmospheric model is commonly used three layers of nested grid and is carried out NO emissions reduction, i.e. outermost layer grid the most slightly, and intermediate layer grid takes second place, innermost layer Grid is the thinnest, as the size of three-layer network lattice is respectively the nested scheme of 45km, 15km, 5km or 10km, 3km, 1km etc..Different Simulation and the forecast result impact of Grid Nesting scheme logarithm value atmospheric model bigger.Therefore step 4 arranges Grid Nesting Scheme is the most crucial for numerical value atmospheric model.
Further, step 2 single storm is divided into following 6 grades altogether:
Grade numbers 1 2 3 4 5 6
Single storm (mm) 0.1～10 10～25 25～50 50～100 100～200 ＞ 200
。
Further, step 3 proposes a kind of aggregative indicator e weighing time rainfall space-time inhomogeneities.
Further, when the secondary rainfall space-time inhomogeneities aggregative indicator in step 3 is by rainfall based on rainfall anomaly method Between nonuniformity coefficient epWith rainfall space nonuniformity coefficient e based on estimation of deviationsTogether decide on；
Single storm foundation rainfall spatial and temporal distributions inhomogeneities on the basis of single storm is classified, to each grade Coefficient e chooses the most further, and this coefficient is by rain time nonuniformity coefficient epWith space nonuniformity coefficient esIt is calculated； Wherein, the rain time nonuniformity coefficient e of jth precipitation stationpjRainfall anomaly method is used to represent:
e p j = Σ i = 1 n | P i j - P j ‾ | n P j ‾ - - - ( 1 )
In formula: PijFor the rainfall of jth precipitation station i-th hour, unit is mm；N is rainfall hourage；For jth Individual precipitation station n hour interior hourly average rainfall；
P j ‾ = 1 n Σ i = 1 n P i j - - - ( 2 )
esRepresent with rainfall deviation factor:
e s = Σ j = 1 m | K j - 1 | 2 m - 1 - - - ( 3 )
In formula: Kj=Pj/ P, PjFor the single storm of jth precipitation station, unit be mm, P be the areal rainfall of study area, single Position is mm；M is precipitation station number；
e = Σ j = 1 m e p j | P j P - 1 | 2 m - 1 - - - ( 4 ) .
Further, secondary rainfall space-time inhomogeneities aggregative indicator e in step 3 is divided into following 6 grades:
e ＜ 0.1 0.1～0.3 0.3～0.5 0.5～0.7 0.7～0.9 ＞ 0.9
Grade The most uneven The most uneven Uneven Uniformly The most uniform The most uniform
。
Further, the typical catchment type in step 3 is divided into following 36 kinds altogether:
Further, step 4 is according to the typical catchment type determined in above-mentioned steps 3, and each type chooses 2～3 Rainfall, utilizes numerical value atmospheric model to be simulated respectively, proposes suitable simulation or forecasting procedure for each rain types, It is not only this pattern pattern in study area and offer foundation is set, and illustrate that this pattern is more suitable for that rain types, with Time choose offer foundation for pattern.
This typical catchment choosing method being used for numerical value atmospheric model has the advantages that
(1) present invention is from rainfall and spatial and temporal distributions angle thereof, for numerical value atmospheric model choose and setting provides A kind of choosing method of standardized typical case's catchment, quantitative description rain types, weigh in a certain study area, number The value atmospheric model simulation precision to dissimilar rainfall, is possible not only to arrange offer for this pattern pattern in study area and depends on According to, and can illustrate that this pattern is more suitable for that rain types, choose offer foundation, for meteorological, water conservancy for pattern simultaneously There is provided rational numerical value atmospheric model modeling scheme Deng relevant department for different rain types, there is general applicability.
(2) present invention proposes a kind of composite target evaluating rainfall spatial and temporal distributions inequality, and enters degree of irregularity Row classification, is divided into 36 kinds based on this index by rain types, passes judgment on the suitability of different rain types for numerical value atmospheric model Provide new method, provide foundation for choosing of numerical value atmospheric model and setting.
Detailed description of the invention
Below in conjunction with embodiment, the present invention will be further described:
The technical solution adopted in the present invention is the one proposed based on single storm and rainfall spatial and temporal distributions inhomogeneities For the typical catchment choosing method of numerical value atmospheric model, implement according to following steps:
(1) the choosing and arranging of numerical value atmospheric model: choose a kind of generally acknowledge both at home and abroad to rainfall simulation and the value of forecasting All preferably numerical value atmospheric model, such as WRF, and sets the initial fields of this pattern, physical parameter scheme, resolution etc. Put.
(2) typical catchment based on single storm classification: from history rainfall play, classifying and selecting 6 groups is the most equal The single storm of level, as shown in table 1.
Table 1 single storm table of grading
Grade numbers 1 2 3 4 5 6
Single storm (mm) 0.1～10 10～25 25～50 50～100 100～200 ＞ 200
(3) typical catchment based on rainfall space-time inhomogeneities is chosen: on the basis of (2), to each grade Single storm choose the most further according to rainfall spatial and temporal distributions inhomogeneities coefficient e, this coefficient is uneven by rain time Even coefficient epWith space nonuniformity coefficient esIt is calculated.Wherein, the rain time nonuniformity coefficient e of jth precipitation stationpjUse Rainfall anomaly method represents:
e p j = Σ i = 1 n | P i j - P j ‾ | n P j ‾ - - - ( 1 ) ;
In formula: PijFor the rainfall of jth precipitation station i-th hour, unit is mm；N is rainfall hourage；For jth Individual precipitation station n hour interior hourly average rainfall；
P j ‾ = 1 n Σ i = 1 n P i j - - - ( 2 ) ;
esRepresent with rainfall deviation factor:
e s = Σ j = 1 m | K j - 1 | 2 m - 1 - - - ( 3 ) ;
In formula: Kj=Pj/ P, PjFor the single storm of jth precipitation station, unit be mm, P be the areal rainfall of study area, single Position is mm；M is precipitation station number；
e = Σ j = 1 m e p j | P j P - 1 | 2 m - 1 - - - ( 4 ) ;
E is carried out classification, represents the degree of irregularity of rainfall, be shown in Table 2.
Table 2e hierarchical table
e ＜ 0.1 0.1～0.3 0.3～0.5 0.5～0.7 0.7～0.9 ＞ 0.9
Grade The most uneven The most uneven Uneven Uniformly The most uniform The most uniform
Therefore, typical case's catchment can be divided into 36 kinds, the most as shown in table 3.
Table 3 typical case's catchment type
Typical case's catchment type Rainfall Grade numbers E-value Typical case's catchment type Rainfall Grade numbers E-value
1 1 ＜ 0.1 19 4 ＜ 0.1
2 1 0.1～0.3 20 4 0.1～0.3
3 1 0.3～0.5 21 4 0.3～0.5
4 1 0.5～0.7 22 4 0.5～0.7
5 1 0.7～0.9 23 4 0.7～0.9
6 1 ＞ 0.9 24 4 ＞ 0.9
7 2 ＜ 0.1 25 5 ＜ 0.1
8 2 0.1～0.3 26 5 0.1～0.3
9 2 0.3～0.5 27 5 0.3～0.5
10 2 0.5～0.7 28 5 0.5～0.7
11 2 0.7～0.9 29 5 0.7～0.9
12 2 ＞ 0.9 30 5 ＞ 0.9
13 3 ＜ 0.1 31 6 ＜ 0.1
14 3 0.1～0.3 32 6 0.1～0.3
15 3 0.3～0.5 33 6 0.3～0.5
16 3 0.5～0.7 34 6 0.5～0.7
17 3 0.7～0.9 35 6 0.7～0.9
18 3 ＞ 0.9 36 6 ＞ 0.9
(4) setting of numerical value atmospheric model and simulation: according to above-mentioned typical case's catchment type, each type chooses 2-3 Field rainfall, utilizes numerical value atmospheric model to be simulated respectively, proposes suitable simulation or forecast side for each rain types Method, is possible not only to arrange offer foundation for this pattern pattern in study area, and it is that to illustrate that this pattern is more suitable for Rain types, chooses offer foundation for pattern simultaneously.
Above in conjunction with embodiment, the present invention is carried out exemplary description, it is clear that the realization of the present invention is not by above-mentioned side The restriction of formula, if the various improvement that the method design that have employed the present invention is carried out with technical scheme, or the most improved by this Bright design and technical scheme directly apply to other occasion, the most within the scope of the present invention.

Claims (7)

1. for a typical catchment choosing method for numerical value atmospheric model, including following step:
Step 1, choosing of numerical value atmospheric model and choosing of driving data；
Step 2, typical catchment based on single storm are classified；
Step 3, typical catchment based on secondary rainfall space-time inhomogeneities are chosen；
Step 4, the physical parameter scheme of numerical value atmospheric model and the setting of Grid Nesting scheme and simulation.
The most according to claim 1 for the typical catchment choosing method of numerical value atmospheric model, it is characterised in that: step 2 single storm are divided into following 6 grades altogether:
Typical catchment choosing method for numerical value atmospheric model the most according to claim 1 or claim 2, it is characterised in that: Step 3 proposes a kind of aggregative indicator e weighing time rainfall space-time inhomogeneities.
The most according to claim 3 for the typical catchment choosing method of numerical value atmospheric model, it is characterised in that: step Secondary rainfall space-time inhomogeneities aggregative indicator in 3 is by rain time nonuniformity coefficient e based on rainfall anomaly methodpWith based on The rainfall space nonuniformity coefficient e of estimation of deviationsTogether decide on；
Single storm foundation rainfall spatial and temporal distributions inhomogeneities coefficient on the basis of single storm is classified, to each grade E chooses the most further, and this coefficient is by rain time nonuniformity coefficient epWith space nonuniformity coefficient esIt is calculated；Wherein, The rain time nonuniformity coefficient e of jth precipitation stationpjRainfall anomaly method is used to represent:
In formula: PijFor the rainfall of jth precipitation station i-th hour, unit is mm；N is rainfall hourage；For jth rain N hour interior hourly average rainfall in amount station；
esRepresent with rainfall deviation factor:
In formula: Kj=Pj/ P, PjFor the single storm of jth precipitation station, unit be mm, P be the areal rainfall of study area, unit is mm；M is precipitation station number；
The most according to claim 4 for the typical catchment choosing method of numerical value atmospheric model, it is characterised in that: step Secondary rainfall space-time inhomogeneities aggregative indicator e in 3 is divided into following 6 grades:
6. according to the typical catchment choosing method being used for numerical value atmospheric model described in claim 3 or 4, it is characterised in that: Typical catchment type in step 3 is divided into following 36 kinds altogether:
7. according in any of the one of claim 1-5 for the typical catchment choosing method of numerical value atmospheric model, its It is characterised by: step 4 is chosen according to the typical catchment type determined in above-mentioned steps 3, every kind of typical catchment type The rainfall of 2-3 field, utilizes numerical value atmospheric model to be simulated respectively, proposes suitable simulation or forecast for each rain types Method, is not only this numerical value atmospheric model pattern in study area and arranges offer foundation, and this numerical value atmospheric model is described It is more suitable for that rain types, chooses offer foundation for pattern simultaneously.
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CN110619433A (en) * 2019-09-17 2019-12-27 国网湖南省电力有限公司 Rapid selection method and system for power grid rainstorm numerical mode parameterization scheme
CN110930282A (en) * 2019-12-06 2020-03-27 中国水利水电科学研究院 Local rainfall type analysis method based on machine learning
CN111414723A (en) * 2020-04-29 2020-07-14 中国水利水电科学研究院 Method for analyzing surface rainfall error by using WRF (write-once-read-many) mode
CN111414723B (en) * 2020-04-29 2021-06-25 中国水利水电科学研究院 Method for analyzing surface rainfall error by using WRF (write-once-read-many) mode

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