CN110488298B - Hail early warning method based on various scale features - Google Patents
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Abstract
The invention discloses a hail prediction method based on various scale characteristics, which comprises the following steps: carrying out potential analysis on the circulation flow situation; put forward a pairFlow potential, analysis of theta se500‑700 The water vapor vertical helicity, the thermal shear advection parameter, the wet position vortex and the water vapor energy vertical helicity so as to diagnose whether the water vapor condition, the power lifting condition and the unstable condition exist in the prediction area and promote the strong convection development together; the strong convection potential is proposed, and the hail occurrence potential of the prediction area is judged through an SI index, a BLI index, a temperature dew point difference and a vertical wind shear; and substituting the diagnosis quantity of the layer height at 0 ℃ into a linear equation of the echo top height at 45dBZ and the layer height at 0 ℃ to obtain an echo top height threshold value at 45dBZ, and if the actual echo top height is more than or equal to the echo top height threshold value at 45dBZ, giving out hail early warning. The invention considers the occurrence and development characteristics of hail in multiple aspects and multiple scales, and more comprehensively describes the characteristics of hail by utilizing multiple data and adopting various modes such as potentiality analysis, diagnostic analysis and the like so as to more accurately predict the hail.
Description
Technical Field
The invention relates to the technical field of meteorological data monitoring and management, in particular to a hail early warning method based on various scale characteristics.
Background
The meteorological disasters not only affect agricultural production and people's life, but also endanger people's life and property safety. At home and abroad, researchers have studied hail, but in short-term forecasting, hail is still disastrous weather which is difficult to forecast accurately. The short-term and close forecasting and monitoring early warning of hailstones are well done, hailstone-preventing shadow work is timely carried out, and the reduction of economic loss caused by the hailstones is still a big problem faced by weather workers at present. In order to better develop hail suppression work, an effective scientific artificial hail suppression early warning method is found; by analyzing the scale characteristics of the hail-falling days and the radar echo characteristics, typical characteristics are summarized and summarized, and the extraction of hail identification indexes is one of very important means for predicting hail.
Nowadays, many researches on hail in a plurality of regions are also achievements, and the researches mainly focus on analysis of weather characteristics, structural characteristics and recognition algorithms of the hail. The early warning method for hail mainly depends on radar echo, and the early warning method combining the diagnostic quantity extracted by using the characteristics of all scales and the echo characteristics is less; most of the analysis of the diagnostic variables is the characteristics of statistical development change, and a few of the analysis is combined with the characteristics of the diagnostic variables related to all scales to obtain a threshold value for forecasting and early warning.
The method is characterized in that a scientific research worker combines the helicity with other diagnostic variables to analyze and diagnose the occurrence and development of strong convection, for example, the energy helicity is used by combining the helicity with convection effective potential energy reflecting the energy action, the common effect of power and energy on the development of strong convection weather is reflected, and the method has indication significance on the forecast of strong storms and the types thereof. Researchers have analyzed helicity as a relationship between a kinetic parameter and a thermal field to draw conclusions that ground relative helicity can be regarded as a measure of temperature advection caused by wind turning or actual wind, and the like. These have very important roles in studying rainstorm disastrous weather and conducting business forecasting. However, hail reduction mainly has three basic conditions: water vapor conditions, power conditions, and unstable conditions. The helicity is only a dynamic diagnostic quantity with a relatively obvious effect, and the indication effect on the development of strong convection can be more obvious by combining the helicity with the water vapor condition and the energy condition.
Meanwhile, in the existing research on hail, the potential trend of strong convection weather such as hail and the like is mostly obtained by means of conventional meteorological data. The occurrence and development of hail are also judged according to the atmospheric motion condition reflected by satellite data, but the occurrence of hail is difficult to forecast in advance by an inversion technology and timeliness. In the existing hail early warning method research, a Doppler radar is an important tool for hail detection and early warning, the Doppler weather radar has strong monitoring capability and timeliness, and a plurality of expert scholars use the Doppler radar to conclude the echo characteristics and the moving path of hail weather. However, the doppler weather radar is mostly used for forecasting and early warning of hail generation, and the latent early warning before the hail generation needs to be combined with feature analysis of each scale. The utilization of the Doppler weather radar cannot be limited to qualitative analysis of typical characteristics and the like of the echo.
Disclosure of Invention
The invention aims to solve the problems and provide a hail early warning method based on various scale features.
In order to achieve the above object, the present invention provides a hail prediction method based on various scale features, comprising the following steps:
s1, potential analysis is carried out on the circulation flow situation: determining whether a small groove exists, if so, determining whether a ground trigger system capable of triggering convection and a high-altitude maintenance system capable of developing convection exist in the prediction area, and if so, proposing convection potential;
s2, if the convection potential exists in the prediction area, analyzing theta by using a diagnosis analysis module se500-700 The method comprises the following steps of (1) diagnosing whether a water vapor condition, a power lifting condition and an unstable condition exist in a prediction area to promote strong convection development together, and if so, proposing strong convection potential;
s3, if the prediction area has strong convection potential, judging the hail occurrence potential of the prediction area through the SI index, the BLI index, the temperature dew point difference and the vertical wind shear;
s4, if the hail occurrence potential exists in the area is predicted, further performing echo analysis on the hail occurrence potential: substituting the diagnosis quantity of the layer height at 0 ℃ into a linear equation of the echo top height at 45dBZ and the layer height at 0 ℃ to obtain an echo top height threshold value at 45dBZ, and if the actual echo top height is more than or equal to the echo top height threshold value at 45dBZ, giving out hail early warning;
hail early warning can be directly provided when strong convection echo characteristics appear in the echo analysis process.
The invention has the beneficial effects that:
1. the hail forecasting method based on the characteristics of each scale considers the occurrence and development characteristics of hail in multiple aspects and multiple scales, utilizes multiple data, adopts various modes such as potentiality analysis, diagnosis analysis and the like to more comprehensively describe the characteristics of the hail, and more accurately pre-warns the hail;
2. the physical quantity threshold values extracted through the characteristic analysis of each scale in the steps S2 and S3 can be directly used in diagnostic analysis under a special circulation situation, the subjective form analysis is changed into objectification, the subjective error among different people is reduced by the quantized threshold value range, and the method is more convenient, concise and accurate;
3. and S4, the possibility of hail occurrence is determined by utilizing a traditional mode of pre-warning according to typical echo characteristics, the relation between the echo top height of 45dBZ and the layer height of 0 ℃ is utilized, diagnosis and analysis are carried out by utilizing a threshold value of the echo top height of 45dBZ, and the possibility of hail occurrence is judged by means of combination of the echo characteristics and the threshold value, so that the method is simpler, more convenient and quicker compared with common situation analysis.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a flow chart of a hail warning method based on various scale features according to the present invention;
FIG. 2 is a diagram of the case weather analysis in an embodiment;
FIG. 3 is θ of the case in the embodiment se Water vapor vertical helicity, thermal shear advection parameters, wet-position eddy component MPV1 and MPV2 distribution diagrams;
FIG. 4 shows the case water vapor energy vertical helicity at 700hPa distribution in the embodiments;
FIG. 5 is a graph of the case reflectivity and its profile, radial velocity and its profile for an embodiment.
Detailed Description
The following describes in detail embodiments of the present invention with reference to the drawings. It should be understood that the detailed description and specific examples, while indicating the present invention, are given by way of illustration and explanation only, not limitation.
As shown in fig. 1, the hail prediction method based on the features of each scale according to the present invention includes the following steps:
s1, potential analysis is carried out on the circulation flow situation: and determining whether a small groove exists, if so, determining whether a ground triggering system capable of triggering convection and a high-altitude maintaining system capable of developing convection exist in the prediction area, and if so, proposing convection potential.
The step mainly focuses on analyzing a trigger mechanism and a maintenance mechanism of the step, observing whether ground trigger systems such as ground trunk lines, ground radial lines and frontal surfaces exist in a forecast area or not, and observing whether maintenance systems such as shear, torrent and low channels exist at high altitude or not to interact to maintain deep development of convection.
As shown in fig. 2, the case weather analysis plot shows the 200hPa, 500hPa, 700hPa weather analysis and T-logp plots, with the solid lines being the trough lines, the yellow regions being the dry regions, the double solid lines being the shear lines, the orange arrows being the high altitude rush current, the red arrows being the low altitude rush current, and the blue regions being the wet regions. Cases exist with ground trunk to ground line, shear, rapids, low trough. The proposed case has convection potential.
S2, if the convection potential exists in the prediction area, analyzing theta by using a diagnosis analysis module se500-700 The method comprises the following steps of determining the vertical helicity of water vapor, thermal shear advection parameters, wet position vortex and the vertical helicity of water vapor energy to diagnose whether favorable water vapor conditions, power lifting conditions and unstable conditions exist in a prediction region or not so as to promote strong convection development, and if the favorable water vapor conditions, the power lifting conditions and the unstable conditions exist in the prediction region, the strong convection potentiality is provided.
Through theta se500-700 And judging whether the prediction area has an unstable condition, a water vapor condition and a power lifting condition which are beneficial to strong convection generation or not according to the water vapor vertical helicity and the thermal shear advection parameters, and judging whether the unstable condition, the water vapor condition and the power lifting condition promote the strong convection generation or not through the wet position vortex and the water vapor energy vertical helicity.
Judging existence of unstable conditions of the prediction region: theta se500-700 The actual value is between-10 and 0 ℃.
Judging the water vapor condition of the prediction area: and the water vapor vertical helicity is greater than 0, is a diagnostic quantity obtained by combining the vertical helicity and the water vapor related physical quantity specific humidity, and determines that the water vapor condition favorable for strong convection exists in the prediction area.
The vertical helicity of the water vapor better reflects the upward conveying of the water vapor, and the indicating effect on the occurrence and development of strong precipitation is more obvious. And analyzing and calculating the vertical helicity of the water vapor in the prediction region to be greater than zero 6 hours before the hailstones occur in the convection process, and promoting the convection development when the prediction region is in a high-value region and is under a favorable water vapor condition.
In the above formula，H p In the vertical helicity of water vapor, ω is the vertical velocity in the isobaric coordinate system, ρ is the density, q is the specific humidity, and v is the wind speed.
Judging the existence of the power lifting condition of the prediction area: the thermal shear advection parameter is greater than 0, and the prediction region positive value large value region is positioned in the middle lower layer of the troposphere.
The thermal shear advection parameters organically combine dynamic factors and thermal factors such as vertical shear of a horizontal wind field, horizontal gradient of generalized site temperature, horizontal divergence, vertical gradient of generalized site temperature and the like, and can comprehensively characterize the dynamic structural characteristics of vertical shear of an air wind field on a hailstorm land, low-layer convergence and high-layer divergence in the hailstorm process. And the abnormal value is a positive value, and when the thermal shear advection parameter of the diagnosis area is greater than 0 and the high-value positive value area of the prediction area is positioned in the middle lower layer of the troposphere, the diagnosis area is judged to be in a favorable dynamic lifting condition.
In the above formula, J is thermal shear advection parameter, u and v are velocity components in X direction and Y direction in isobaric coordinate system, and theta is generalized temperature.
The judgment of strong convection is promoted by the unstable condition, the water vapor condition and the power lifting condition together: when the low-level wet vortex MPV1<0 and MPV2>0 in the troposphere of the prediction region, the prediction region is a cross region of a convection unstable region and a normal-wet inclined pressure region;
when the vertical helicity of the water vapor energy is a negative value in the prediction region and the center of the negative value above the prediction region is positioned in the lower stratum of the troposphere, the vertical helicity of the water vapor energy is a diagnostic quantity obtained by combining the vertical helicity with the water vapor related physical quantity, namely the humidity and the energy related physical quantity generalized temperature.
When the conditions of favorable thermal power and water vapor are met, the thermal power property and the water vapor effect of the atmosphere can be comprehensively reflected by utilizing the water vapor energy vertical helicity and the wet position vortex. The change of the wet vortex can reflect the enhancement and the weakening of the symmetric instability, and has obvious indication significance for the occurrence of strong convection weather. When the lower layer in the troposphere of the prediction region is a convection unstable region (MPV 1< 0); the upper troposphere is a weak stable zone. The prediction area is positioned in a corresponding area where a positive wet inclined pressing area (MPV 2> 0) and a convection unstable area are superposed, so that the release of unstable energy and the development of convection are facilitated. When the vertical helicity of the water vapor energy is a negative value in the diagnosis area and the center of the negative value above the diagnosis area is positioned in the lower layer of the troposphere, the development of strong convection is promoted under the combined action of favorable water vapor, power and unstable conditions in the diagnosis area.
In the above formula, MPV is the wet vortex, ζ is the vertical vorticity, f is the transition parameter, θ se Is a false equivalent temperature.
In the above formula, M p The vertical helicity of water vapor energy, q is specific humidity and theta is generalized potential temperature.
Specifically, cases with convection potential are analyzed diagnostically using θ, as shown in FIG. 3 se500-700 Describing its unstable condition. Analyzing and calculating theta 12 hours and 6 hours before hail occurs in the convection process se500-700 The stability of the layer junction is known, theta, 12 hours ago to 6 hours ago se500-700 Tending to become negative with the center of the negative gradually encompassing the diagnostic region. Diagnosis by comparing the regions of diagnosis theta 6 hours ago se500-700 And judging an unstable condition if the actual value is less than 0 ℃. In case of theta se500-700 Negative values, -5 ℃ in the threshold range, so the case is in unstable conditions.
In the case, the vertical helicity of water vapor is 0.1-0.2X 10 4 ·kg·m -2 ·s -6 >0, and is in a high value region, and thus is determined to be in favorable moisture conditions.
In the case that the thermal shear advection parameter J is greater than 0, the prediction area is positive, and the center of the positive value of the diagnosis area is located at the position which is 600hPa and is deviated from the north, which indicates that the thermal shear advection parameter J is in a favorable dynamic lifting condition.
In the case the wet vortices are empty above the prediction region until 450hPa is MPV1<0; the upper troposphere above 400hPa is a weak stable zone. MPV1 negative values have a central value of 1.5PVU, lying around 600 hPa. The upper part of the prediction area is positioned in a positive wet inclined pressure area (MPV 2> 0), which is beneficial to the release of unstable energy and the development of convection. As shown in fig. 4, the whole prediction area is located in a negative value area of the vertical helicity of the water vapor energy, and the prediction area is located in a negative value central area, so that the strong convection development is promoted under the combined action of the water vapor, the power and the unstable conditions.
And S3, if the prediction area has strong convection potential, judging the hail occurrence potential of the prediction area through the SI index, the BLI index, the temperature dew point difference and the vertical wind shear.
And carrying out statistical analysis by utilizing SI index, BLI index, temperature dew point difference and vertical wind shear characteristics under hail weather to obtain a diagnostic quantity threshold value aiming at hail, and carrying out hail potential judgment on the predicted area. Judging the occurrence potential of hail in the prediction area: SI is less than or equal to-0.02 ℃, BLI is less than or equal to 0, and temperature dew point difference (T-T) d ) 700hPa Vertical wind shear V at 5 deg.C or below 300hPa -V 700hPa ≥12m/s。
At SI of less than or equal to-0.02 deg.C, BLI of less than or equal to 0 deg.C, and temperature dew point difference (T-T) d ) 700hPa Vertical wind shear V at 5 deg.C or below 300hPa -V 700hPa And when the signal is more than or equal to 12m/s, enhancing echo observation and preparing hail early warning.
BLI =0 ≦ 0, temperature dew point difference (T-T) in case d ) 700hPa Vertical wind shear V at 1-5 deg.C 300hPa -V 700hPa And if the frequency is not less than 13m/s and not less than 12m/s, providing reinforced echo observation and preparing hail early warning.
S4, if the hail occurrence potential exists in the area is predicted, further performing echo analysis on the hail occurrence potential: substituting the diagnosis quantity of the layer height at 0 ℃ into a linear equation of the echo top height at 45dBZ and the layer height at 0 ℃ to obtain an echo top height threshold value at 45dBZ, and if the actual echo top height is more than or equal to the echo top height threshold value at 45dBZ, giving out hail early warning;
hail early warning can be directly provided when strong convection echo characteristics appear in the echo analysis process.
The linear relationship between the 0 ℃ layer height and the 45dBZ echo top height is as follows:
H 0 ≥2500m，Y＝2090.723+1.161X；
H 0 <2500m，Y＝5621.526+1.821X；
in the formula, H 0 Is the 0 ℃ slice height, X is the 0 ℃ slice height diagnostic, and Y is the 45dBZ echo top height threshold.
And according to the echo characteristics obtained by statistics, bringing the diagnosis quantity of the 0 ℃ layer height into a linear equation of the echo top height of 45dBZ and the layer height of 0 ℃ according to whether the layer height of 0 ℃ exceeds 2500m, and judging the possibility of hail occurrence by judging whether the diagnosis reaches a related threshold value.
According to the development of the hail cloud and the time interval of 6 minutes, the strong development stage of the hail cloud can be missed; and selecting radar data from one hour before hail suppression to one hour before hail suppression, and analyzing the relation between the peak height of the strong echo and the layer height of 0 ℃. The hail suppression system not only ensures that the mature stage of hail development can be captured, but also can provide forecast and early warning before hail suppression, and provides time for hail suppression operation.
The height and the central intensity of the echo of the radar can be changed according to the change of the 0 ℃ layer height. The relation between the top height of the strong echo obtained after the change of the 0 ℃ layer and the height of the 0 ℃ layer is considered, so that the relation between the top height and the height of the 0 ℃ layer is described, and the accuracy of describing the complex relation between the top height and the height of the 0 ℃ layer is improved. It is statistically known that the difference between the height of the top of the strong echo and the height of the layer at 0 ℃ is significantly different when the layer height at 0 ℃ is higher or lower than 2500 m. The linear relationship between the analysis of the strong echo top height and the 0 ℃ layer height thus takes into account the seasonal variation of the 0 ℃ layer height, above which the relationship is analyzed in both cases with a limit of 2500 m.
The echo intensity of the hailstone cloud from the development stage to the maturation stage can range from 35dBZ to 60dBZ. The invention analyzes the correlation between the echo top height of 35dBZ-60dBZ and the layer height at 0 ℃ according to the case, and obtains that the echo top height of 45dBZ has stronger correlation with the layer height at 0 ℃, and the possibility that the layer height at 0 ℃ changes along with the echo top height of 45dBZ is higher. Therefore, a linear relation between the echo top height of 45dBZ and the layer height at 0 ℃ is selected as the hail criterion.
And further, analyzing the probability of the hailstorm in a short time by using the reflectivity and radial velocity characteristics of the hailstorm-probable cases. When strong convective echo characteristics are observed: when medium cyclones appear in the radial velocity diagram and the like, early warning can be directly provided.
In case H 0 =1232.6 for X, actual H 45dBZ >Y; as shown in FIG. 5, the reflectivity profile shows a weak echo region, and the radial velocity profile has no obvious characteristic features. Therefore, the case can provide hail early warning.
The invention combines the characteristics of all scales, considers multi-aspect data capable of reflecting the occurrence and development of hail, extracts related diagnosis quantity and obtains a representative physical quantity threshold value. The invention mainly judges the possibility of hail occurrence according to the means of combining the circulation situation, the relevant physical quantity, the echo characteristics and the threshold value to forecast and warn.
The preferred embodiments of the present invention have been described in detail with reference to the accompanying drawings, however, the present invention is not limited to the specific details of the above embodiments, and various simple modifications can be made to the technical solution of the present invention within the technical idea of the present invention, and these simple modifications are within the protective scope of the present invention.
It should be noted that the various technical features described in the above embodiments can be combined in any suitable manner without contradiction, and the invention is not described in any way for the possible combinations in order to avoid unnecessary repetition.
In addition, any combination of the various embodiments of the present invention can be made, and the same should be considered as the disclosure of the present invention as long as the idea of the present invention is not violated.
Claims (7)
1. The hail prediction method based on the features of all scales is characterized by comprising the following steps of:
s1, potential analysis is carried out on the circulation flow situation: determining whether a small groove exists, if so, determining whether a ground trigger system capable of triggering convection and a high-altitude maintenance system capable of developing convection exist in the prediction area, and if so, proposing convection potential;
s2, if the convection potential exists in the prediction area, analyzing theta by using a diagnosis analysis module se500-700 The system comprises a water vapor vertical helicity, a thermal shear advection parameter, a wet position vortex and a water vapor energy vertical helicity, and is used for diagnosing whether a water vapor condition, power lifting and an unstable condition exist in a prediction region to promote strong convection development together, and if the water vapor condition, the power lifting and the unstable condition exist, strong convection potentiality is proposed, and the method is specifically realized as follows: through theta se500-700 The water vapor vertical helicity and the thermal shear advection parameters are used for respectively judging whether an unstable condition, a water vapor condition and a power lifting condition which are beneficial to strong convection exist in the prediction area, and judging whether the unstable condition, the water vapor condition and the power lifting condition jointly promote the strong convection to occur or not through the wet position vortex and the water vapor energy vertical helicity;
s3, if the prediction area has strong convection potential, judging the hail occurrence potential of the prediction area through the SI index, the BLI index, the temperature dew point difference and the vertical wind shear;
s4, if the hail occurrence potential exists in the area is predicted, further performing echo analysis on the hail occurrence potential: substituting the diagnostic quantity of the layer height at 0 ℃ into a linear equation of the echo top height at 45dBZ and the layer height at 0 ℃ to obtain an echo top height threshold value at 45dBZ, and if the actual echo top height is more than or equal to the echo top height threshold value at 45dBZ, giving out hail early warning;
hail early warning can be directly provided when strong convection echo characteristics appear in the echo analysis process.
2. The hail prediction method based on various scale features according to claim 1, wherein the judgment of existence of a prediction region instability condition is: theta se500-700 The actual value is between-10 and 0 ℃.
3. The hail prediction method based on various scale features of claim 1, wherein the judgment of the area moisture condition is predicted: and the water vapor vertical helicity is greater than 0, is a diagnostic quantity obtained by combining the vertical helicity and the water vapor related physical quantity specific humidity, and determines that the water vapor condition favorable for strong convection exists in the prediction area.
4. The hail prediction method based on various scale features as claimed in claim 1, wherein the judgment that favorable dynamic lift conditions exist in the prediction area is: the thermal shear advection parameter is greater than 0, and the prediction region positive value large value region is positioned in the middle lower layer of the troposphere.
5. The hail prediction method based on various scale features of claim 1, wherein the unstable condition, the steam condition and the dynamic lifting condition together facilitate the judgment of the occurrence of strong convection: when the low-level wet vortex components MPV1<0 and MPV2>0 in the troposphere of the prediction region, the prediction region is a cross region of a convection unstable region and a normal-wet inclined pressure region;
when the vertical helicity of the water vapor energy is a negative value in the prediction region and the center of the negative value above the prediction region is positioned in the lower stratum of the troposphere, the vertical helicity of the water vapor energy is a diagnostic quantity obtained by combining the vertical helicity with the water vapor related physical quantity, namely the humidity and the energy related physical quantity generalized temperature.
6. The hail prediction method based on scale features of claim 1, wherein the diagnostic quantity threshold for hail is derived by statistical analysis using the diagnostic quantity features under hail weather; judging the occurrence potential of hail in the prediction area: SI is less than or equal to-0.02 ℃, BLI is less than or equal to 0, and temperature dew point difference (T-T) d ) 700hPa Vertical wind shear V at 5 deg.C or below 300hPa -V 700hPa ≥12m/s。
7. The method for hail prediction based on scale features of claim 1, wherein the linear relationship between 0 ℃ layer height and 45dBZ echo top height is as follows:
H 0 ≥2500m，Y＝2090.723+1.161X；
H 0 <2500m，Y＝5621.526+1.821X；
in the formula, H 0 Is the 0 ℃ slice height, X is the 0 ℃ slice height diagnostic, and Y is the 45dBZ echo top height threshold.
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| CN114384610B (en) * | 2021-12-28 | 2024-02-20 | 中国人民解放军94201部队 | Hail short-term fall prediction method, hail short-term fall prediction device, electronic equipment and storage medium |
| CN114648181B (en) * | 2022-05-24 | 2022-11-18 | 国能大渡河大数据服务有限公司 | Rainfall forecast correction method and system based on machine learning |
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