CN116049726B - Method, device, equipment and storage medium for classifying rainfall types of Qinghai-Tibet plateau in summer - Google Patents
Method, device, equipment and storage medium for classifying rainfall types of Qinghai-Tibet plateau in summer Download PDFInfo
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Abstract
The invention discloses a method, a device, equipment and a storage medium for classifying rainfall types of Qinghai-Tibet plateau in summer, wherein the method comprises the following steps: step 1, acquiring summer Qinghai-Tibet plateau precipitation data measured by a satellite-borne double-frequency rain measuring radar, calculating precipitation related physical quantity and setting a related threshold value according to the summer Qinghai-Tibet plateau precipitation data; step 2, judging the specific precipitation type of each precipitation pixel in the rainfall data of the Qinghai-Tibet plateau in summer according to the precipitation related physical quantity and the set related threshold value, and obtaining the specific precipitation type corresponding to each precipitation pixel; and step 3, calculating the average reflectivity factor profile and the vertical speed profile of the precipitation pixels of different precipitation types according to the classification result of the precipitation pixels. The method can overcome the defect that the existing DPR precipitation type classification algorithm is not suitable for the Qinghai-Tibet plateau in summer, and obtain the correct plateau precipitation type of the Qinghai-Tibet plateau in summer.
Description
Technical Field
The invention relates to the field of atmospheric science research, in particular to a method and a device for classifying rainfall types of Qinghai-Tibet plateau in summer.
Background
Precipitation types play an important role in both the fields of atmospheric science and meteorological applications. Different types of precipitation correspond to different relationships between the radar echo intensity Z and the precipitation rate R, namely Z-R relationships, so that accurate precipitation type classification can be realized, and the accuracy of inverting the precipitation rate by using the radar detection result can be improved. The micro-physical process of different types of precipitation is different, and accurate precipitation type classification is helpful for understanding cloud physical characteristics, so that the micro-physical parameterization scheme in a numerical mode is improved. Two major types of precipitation exist in reality: convection precipitation and lamellar precipitation, which have different thermodynamic structures, result in their different latent heat vertical structures, while latent heat directly acts on the atmospheric circulation, thereby affecting weather and climate, so that accurate precipitation type classification is also of great significance for studying latent heat and weather forecast.
At present, a precipitation type identification algorithm of a satellite-borne double-frequency rain radar, namely a DPR precipitation intensity inversion algorithm, comprises a V scheme, namely a Vertical profiling method scheme, an H scheme, namely Horizontal pattern method and DFR m Scheme, i.e. Dual-frequency ratio method, and falls moisture reduction into three categories: convection precipitation, lamellar precipitation, and other types of precipitation. V scheme and DFR m The scheme is based on the principle of detecting the bright zone to identify the layered precipitation, but the elevation of the Qinghai-Tibet plateau approaches to the zero-degree layer height of the non-plateau area in summer, which often causes the layered precipitationMisjudgment is identified, so V scheme and DFR m The scheme is not suitable for identifying the precipitation type of Tibet plateau. The H scheme is based on echo horizontal structural characteristics to identify convection precipitation, but the convection in summer of Qinghai-Tibet plateau is mainly weak convection, and the judgment threshold value of the convection precipitation set in the H scheme is too high, so that the H scheme is not suitable for identifying the type of the plateau precipitation.
In addition, in the DPR precipitation intensity inversion algorithm, due to the fact that raindrop spectrums, precipitation rates, latent heat vertical structures and the like are different due to precipitation types, the precipitation type classification algorithm of the DPR precipitation intensity inversion algorithm has the defect that plateau weak convection is misjudged to be lamellar precipitation, the precipitation type classification error can cause inversion errors of a plurality of precipitation parameters on a Tibet plateau, different types of precipitation reflectivity factor profiles and vertical speed profiles cannot be accurately given, and an accurate Tibet plateau precipitation type data set cannot be provided. Therefore, how to provide a classification method suitable for the rainfall type in the Qinghai-Tibet plateau in summer is a problem to be solved.
In view of this, the present invention has been made.
Disclosure of Invention
The invention aims to provide a method, a device, equipment and a storage medium for classifying the type of precipitation in a Qinghai-Tibet plateau in summer, which can accurately classify the type of precipitation in the Qinghai-Tibet plateau in summer, accurately give out different types of precipitation reflectivity factor profiles and vertical speed profiles, facilitate the provision of a new Qinghai-Tibet plateau precipitation type data set, provide technical support and data guarantee for the deep study of a cloud precipitation three-dimensional structure, a latent heat structure and the like in a precipitation event, and solve the technical problems in the prior art.
The invention aims at realizing the following technical scheme:
a method for classifying the type of rainfall in Qinghai-Tibet plateau in summer, comprising the following steps:
and step 3, calculating the average reflectivity factor profile and the vertical speed profile of the precipitation pixels of different precipitation types according to the classification results of all the precipitation pixels.
A classification device for the type of rainfall in the Qinghai-Tibet plateau in summer, which is used for realizing the classification method of the invention, and comprises the following steps:
the device comprises a precipitation related physical quantity acquisition unit, a pixel precipitation type classification unit, a reflectivity factor and a vertical speed profile acquisition unit; wherein,,
the rainfall-related physical quantity acquisition unit can acquire summer Qinghai-Tibet plateau rainfall data measured by the satellite-borne double-frequency rain measuring radar, and calculate rainfall-related physical quantity and set related threshold values through the summer Qinghai-Tibet plateau rainfall data;
the pixel precipitation type classification unit is in communication connection with the precipitation related physical quantity acquisition unit, and can sequentially judge the specific precipitation type of each precipitation pixel in the summer Qinghai-Tibet plateau precipitation data according to the precipitation related physical quantity calculated by the precipitation related physical quantity acquisition unit and the set related threshold value to obtain the specific precipitation type corresponding to each precipitation pixel;
the reflectivity factor and vertical speed profile acquisition unit is in communication connection with the pixel precipitation type classification unit, and can calculate and obtain the average reflectivity factor profile and vertical speed profile of the precipitation pixels of different precipitation types according to the classification result of the precipitation pixels obtained by the pixel precipitation type classification unit.
A processing apparatus, comprising:
at least one memory for storing one or more programs;
at least one processor capable of executing one or more programs stored in the memory, which when executed by the processor, enable the processor to implement the methods of the present invention.
A readable storage medium storing a computer program which, when executed by a processor, is capable of carrying out the method according to the invention.
Compared with the prior art, the method, the device, the equipment and the storage medium for classifying the rainfall types of the Qinghai-Tibet plateau in summer have the beneficial effects that:
the method mainly divides the summer water content of a plateau into strong convection precipitation, weak convection precipitation, shallow convection precipitation and other types of precipitation according to the horizontal structural characteristics of the reflectivity factors of the satellite-borne double-frequency rain radar. In addition, the classification method of the invention performs example verification and preliminary statistical analysis, solves the problem that the conventional DPR precipitation type classification algorithm misjudges the plateau weak convection precipitation as layered precipitation, and provides technical support and data assurance for subsequent precipitation rate, latent heat inversion and plateau summer precipitation characteristic research. In order to determine the requirements of threshold values and the like, the physical parameters and related variables of the precipitation of the Qinghai-Tibet plateau and the Anhui province in China in summer are compared and analyzed.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of a method for classifying the type of precipitation in the Qinghai-Tibet plateau in summer according to an embodiment of the invention.
FIG. 2 is a schematic diagram showing probability density distribution of physical quantities related to precipitation in summer 6, 7 and 8 months in Qinghai-Tibet plateau from 2014 to 2020; wherein, (a), (b), (c) and (d) are probability density distributions of maximum reflectivity factor, reflectivity difference, echo top height and cloud thickness respectively, wherein in the figure, the line A1 represents Qinghai-Tibet plateau, and the line A2 represents Anhui province; (e) Probability density distribution of reflectance difference under different maximum reflectance factor intervals of Qinghai-Tibet plateau; (f) The probability density distribution of the reflectance difference under different maximum reflectance factor intervals is obtained for the Anhui province in China.
FIG. 3 is a schematic diagram showing the horizontal distribution of precipitation types and the cross section verification of reflectivity factors given by the conventional DPR precipitation type classification algorithm and the classification method according to the present invention in two cases of precipitation events provided by the present invention; wherein (a) and (b) are respectively the first and second near-surface precipitation rate distributions of the plateau summer precipitation example detected by the DPR, and AB indicates the section position; (c) And (d) precipitation type distributions respectively given for the DPR precipitation type classification algorithm; (e) And (f) respectively giving precipitation type distribution for the classification method of the invention; (g) And (h) respectively obtaining a first radar reflectivity factor profile and a second radar reflectivity factor profile of the example and a corresponding precipitation type of a precipitation pixel given by a DPR precipitation type classification algorithm; (i) And (j) respectively providing corresponding precipitation types for the precipitation pixels provided by the classification method.
FIG. 4 is a schematic diagram of average reflectivity factors and average vertical velocity profiles of different precipitation types given by the conventional DPR precipitation type classification algorithm and the classification method according to the present invention in two precipitation events provided by the present invention; wherein, lines A1, A2 and A3 respectively represent other types of precipitation, convection precipitation and lamellar precipitation profiles, and lines B1, B2, B3 and B4 respectively represent other types of precipitation, shallow convection precipitation, strong convection precipitation and weak convection precipitation profiles.
Fig. 5 is a schematic diagram showing probability density distribution of different precipitation types of reflection factors with height in summer of the Qinghai-Tibet plateau from 2014 to 2020 according to the conventional DPR precipitation type classification algorithm and the classification method of the invention.
Fig. 6 is a schematic structural diagram of a classification device for rainfall types in the Qinghai-Tibet plateau in summer according to the embodiment of the invention.
Detailed Description
The technical scheme in the embodiment of the invention is clearly and completely described below in combination with the specific content of the invention; it will be apparent that the described embodiments are only some embodiments of the invention, but not all embodiments, which do not constitute limitations of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.
The terms that may be used herein will first be described as follows:
the term "and/or" is intended to mean that either or both may be implemented, e.g., X and/or Y are intended to include both the cases of "X" or "Y" and the cases of "X and Y".
The terms "comprises," "comprising," "includes," "including," "has," "having" or other similar referents are to be construed to cover a non-exclusive inclusion. For example: including a particular feature (e.g., a starting material, component, ingredient, carrier, formulation, material, dimension, part, means, mechanism, apparatus, step, procedure, method, reaction condition, processing condition, parameter, algorithm, signal, data, product or article of manufacture, etc.), should be construed as including not only a particular feature but also other features known in the art that are not explicitly recited.
The term "consisting of … …" is meant to exclude any technical feature element not explicitly listed. If such term is used in a claim, the term will cause the claim to be closed, such that it does not include technical features other than those specifically listed, except for conventional impurities associated therewith. If the term is intended to appear in only a clause of a claim, it is intended to limit only the elements explicitly recited in that clause, and the elements recited in other clauses are not excluded from the overall claim.
When concentrations, temperatures, pressures, dimensions, or other parameters are expressed as a range of values, the range is to be understood as specifically disclosing all ranges formed from any pair of upper and lower values within the range of values, regardless of whether ranges are explicitly recited; for example, if a numerical range of "2 to 8" is recited, that numerical range should be interpreted to include the ranges of "2 to 7", "2 to 6", "5 to 7", "3 to 4 and 6 to 7", "3 to 5 and 7", "2 and 5 to 7", and the like. Unless otherwise indicated, numerical ranges recited herein include both their endpoints and all integers and fractions within the numerical range.
The terms "center," "longitudinal," "transverse," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," etc. refer to an orientation or positional relationship based on that shown in the drawings, merely for ease of description and to simplify the description, and do not explicitly or implicitly indicate that the apparatus or element in question must have a particular orientation, be constructed and operated in a particular orientation, and therefore should not be construed as limiting the present disclosure.
The method, the device, the equipment and the storage medium for classifying the rainfall types of the Qinghai-Tibet plateau in summer provided by the invention are described in detail below. What is not described in detail in the embodiments of the present invention belongs to the prior art known to those skilled in the art. The specific conditions are not noted in the examples of the present invention and are carried out according to the conditions conventional in the art or suggested by the manufacturer. The reagents or apparatus used in the examples of the present invention were conventional products commercially available without the manufacturer's knowledge.
As shown in fig. 1, the embodiment of the invention provides a method for classifying the type of the Qinghai-Tibet plateau precipitation in summer, which is a method for classifying the type of the Qinghai-Tibet plateau precipitation by using satellite-borne dual-frequency rain radar data, and comprises the following steps:
and 3, calculating the average reflectivity factor profile and the vertical speed profile of the precipitation pixels of different precipitation types according to the classification result of the precipitation pixels, and determining the vertical structural characteristics of the different types of precipitation reflectivity factors and the vertical speeds of the Qinghai-Tibet plateau through the average reflectivity factor profile and the vertical speed profile of the precipitation pixels of different precipitation types.
Preferably, in step 1 of the above method, calculating the precipitation-related physical quantity and setting the related threshold value by the summer Qinghai-Tibet plateau precipitation data in the following manner includes:
(a) Maximum reflectance factor (Z max ) For non-altitude cases, the maximum reflectance factor definition references Z in the DPR-H scheme max Definition, i.e. Z max Representing a maximum reflectivity factor of a clutter-free region between a position 1.5km below the zero-degree layer height and the ground; for Qinghai-Tibet plateau, Z is as high as 1.5km below zero max The reflectivity factor corresponding to the bottom layer of the clutter-free area is defined, and the zero-degree layer height and the bottom layer height of the clutter-free area are given by the double-frequency rain radar data. Since the Ku band radar echo signal threshold is 15dBZ, Z max If the maximum reflectivity factor of the pixel is smaller than the near-surface precipitation rate threshold value, marking the maximum reflectivity factor of the pixel as a default value;
(b) The difference of reflectivity (DZ) is the difference between the maximum reflectivity factor of the precipitation pixel and the average value of the maximum reflectivity factors of a plurality of precipitation pixels around the precipitation pixel, wherein the precipitation pixels around the precipitation pixel refer to all precipitation pixels in a circle with the precipitation pixel as a center and a radius of 11 km;
(c) Echo Top Height (STH), which is the highest layer Height corresponding to 15dBZ of radar reflectivity factors of three layers continuously from the Top of the precipitation profile downwards;
(d) Cloud Thickness (CT) is the echo top height of the precipitation pixel minus the bottom height of the clutter-free region;
according to the maximum reflectivity factor, the reflectivity difference and the echo top height of each precipitation pixel calculated in the step 11, calculating to obtain the maximum reflectivity factor, the echo top height of the Tibet plateau and probability density distribution of the reflectivity difference under different maximum reflectivity factors, setting the threshold value of the strong convection precipitation reflectivity of the plateau as 30dBZ, setting the threshold value of the strong convection precipitation echo top height as 10.6km and setting the threshold value of the strong convection precipitation reflectivity difference as 3dB; the threshold value of the reflectivity of the low-convection precipitation on the plateau is set to 18dBZ, the threshold value of the reflectivity difference of the low-convection precipitation is set to-1.5 dB, and the threshold value for distinguishing the echo top height of the low-convection precipitation from the echo top height of the shallow-convection precipitation is set to 7.5 km.
Preferably, in step 2 of the above method, the determining of the specific precipitation type is sequentially performed on each precipitation pixel in the summer Qinghai-Tibet plateau precipitation data according to the following manner, so as to obtain the specific precipitation type corresponding to each precipitation pixel, including:
step 21, judging whether the precipitation pixel is judged to be other types of precipitation by the DPR precipitation type classification algorithm, if so, classifying the precipitation pixel to be other types of precipitation, wherein other types of precipitation echo signals are most likely to be clutter according to the DPR precipitation type classification algorithm, and if not, executing step 22;
(22a) The maximum reflectivity factor exceeds the plateau strong convection precipitation reflectivity threshold;
(22b) The reflectivity difference exceeds a strong convection precipitation reflectivity difference threshold;
(22c) The echo top height exceeds a Gao Yuanjiang convection echo top height threshold;
step 23, judging whether the precipitation related physical quantity of the precipitation pixel meets the following weak convection precipitation judging conditions at the same time, if yes, determining that the precipitation type of the precipitation pixel is weak convection precipitation, and if not, executing step 24, wherein the weak convection precipitation judging conditions comprise:
(23a) The maximum reflectivity factor is distributed between 18dBZ and the threshold value of the high-intensity convection precipitation reflectivity of the plateau;
(23b) The reflectance difference is distributed between-1.5 dB and the threshold value of the reflectance difference of the strong convection precipitation;
(23c) The echo top height exceeds an echo top height distinguishing threshold value of weak convection precipitation and shallow convection precipitation;
and step 24, determining the precipitation type of the precipitation pixel as shallow convection precipitation.
Preferably, in step 3 of the above method, according to the classification result of the precipitation pixels, an average reflectivity factor profile and an average vertical velocity profile of the precipitation pixels of different precipitation types are calculated in the following manner, including:
selecting the grid points of ERA-5 data closest to each precipitation pixel and closest in time interval for matching, and obtaining the vertical speed of each precipitation pixel;
and averaging the layer-by-layer reflectivity factors and the vertical speeds of the precipitation pixels with the same precipitation types to obtain an average reflectivity factor profile and a vertical speed profile of strong convection precipitation, weak convection precipitation, shallow convection precipitation and other types of precipitation.
Preferably, the above-mentioned ERA-5 data has a grid horizontal resolution of 0.25 degrees, giving a vertical velocity of 37 layers total from 100hPa to 1 hPa.
As shown in fig. 6, an embodiment of the present invention provides a device for classifying rainfall types in Qinghai-Tibet plateau in summer, which is configured to implement the method described above, including:
the device comprises a precipitation related physical quantity acquisition unit, a pixel precipitation type classification unit, a reflectivity factor and a vertical speed profile acquisition unit; wherein,,
the rainfall-related physical quantity acquisition unit can acquire summer Qinghai-Tibet plateau rainfall data measured by the satellite-borne double-frequency rain measuring radar, and calculate rainfall-related physical quantity and set related threshold values through the summer Qinghai-Tibet plateau rainfall data;
the pixel precipitation type classification unit is in communication connection with the precipitation related physical quantity acquisition unit, and can sequentially judge the specific precipitation type of each precipitation pixel in the summer Qinghai-Tibet plateau precipitation data according to the precipitation related physical quantity calculated by the precipitation related physical quantity acquisition unit and the set related threshold value to obtain the specific precipitation type corresponding to each precipitation pixel;
the reflectivity factor and vertical velocity profile acquisition unit is in communication connection with the pixel precipitation type classification unit, and can calculate and obtain the average reflectivity factor profile and the average vertical velocity profile of the precipitation pixels of different precipitation types according to the classification result of the precipitation pixels obtained by the pixel precipitation type classification unit.
The embodiment of the invention also provides a processing device, which comprises:
at least one memory for storing one or more programs;
at least one processor capable of executing one or more programs stored in the memory, which when executed by the processor, enable the processor to implement the methods described above.
The embodiment of the invention further provides a readable storage medium storing a computer program, which when executed by a processor, can implement the method described above.
In summary, the classification method of the embodiment of the invention can overcome the defect that the existing DPR precipitation type classification algorithm is not suitable for the Qinghai-Tibet plateau in summer, obtain the correct plateau precipitation type, and carry out precipitation type classification again on the precipitation result detected by the long-time radar by the method, so that a new Qinghai-Tibet plateau precipitation type data set can be provided, and further technical support and data guarantee are provided for deep research on the cloud precipitation three-dimensional structure, latent heat structure and the like in precipitation events.
In order to clearly show the technical scheme and the technical effects, the method, the device, the equipment and the storage medium for classifying the type of the rainfall in the summer Tibet plateau are described in detail in the following by using specific embodiments.
Example 1
The embodiment of the invention provides a method for classifying rainfall types of a Qinghai-Tibet plateau in summer, which is a method for classifying acquired data of the Qinghai-Tibet plateau in summer detected by a satellite-borne dual-frequency rain detection radar, wherein the rainfall classification is based on pixel level data detected by the satellite-borne dual-frequency rain detection radar, namely, each rainfall pixel in each track corresponds to one rainfall type, and comprises the following steps: strong convection precipitation, weak convection precipitation, shallow convection precipitation, and other types of precipitation. The track data used is DPR secondary product-2 ADPR, the horizontal resolution of the undersea point is 5km, the vertical resolution is 0.125km, and the radar reflectivity factor profile of each precipitation pixel from the ground surface to 22km height can be given out, and the precipitation three-dimensional structure in the track can be obtained.
The method is shown in fig. 1, and comprises the following steps:
(a) Maximum reflectance factor (Z max ) For non-altitude cases, the maximum reflectance factor definition references Z in the DPR-H scheme max Definition, i.e. Z max Representing a maximum reflectivity factor of a clutter-free region between a position 1.5km below the zero-degree layer height and the ground; for Qinghai-Tibet plateau, Z is as high as 1.5km below zero max The reflectivity factors corresponding to the bottom layer of the clutter-free area are defined, and the zero-degree layer height and the bottom layer height of the clutter-free area are given by the double-frequency rain radar data, and the threshold value of the Ku-band radar echo signal is 15dBZ, so that Z is the same max If the pixel is smaller than the threshold value, the maximum reflectivity factor of the pixel is recorded as a default value;
(b) The difference of reflectivity (DZ) is the difference between the maximum reflectivity factor of the precipitation pixel and the average value of the maximum reflectivity factors of a plurality of precipitation pixels around the precipitation pixel, wherein the precipitation pixels around the precipitation pixel refer to all precipitation pixels in a circle with the precipitation pixel as a center 11km radius;
(c) Echo Top Height (STH), which is the highest layer Height corresponding to 15dBZ of radar reflectivity factors of three layers continuously from the Top of the precipitation profile downwards;
(d) Cloud Thickness (CT) is the echo top height of the precipitation pixel minus the bottom height of the clutter-free region;
preferably, the judgment can be sequentially carried out according to the coordinate numbers of the pixels on the track;
the probability density distributions of the four precipitation-related physical quantities, namely, the maximum reflectance factor, the reflectance difference, the echo top height and the cloud thickness, are shown in fig. 2 (a) - (d), and in fig. 2, the line A1 represents Qinghai-Tibet plateau, and the line A2 represents Anhui province. To keep the occupancy of the high-intensity convection precipitation sample at Qinghai-Tibet plateau consistent with the occupancy of precipitation samples exceeding the DPR-H protocol convection threshold (40 dBZ) in Anhui province, 30dBZ was set as the high-intensity convection precipitation reflectivity threshold. The echo top height can well indicate the strength of rising motion in a precipitation rain cluster, the rising motion of convection precipitation is vigorous, and the echo top height is high; the calculation shows that the average echo top height of the pixels with the maximum reflectivity factor of the Qinghai-Tibet plateau exceeding 30dBZ is 10.6km, so the 10.6km is set as the threshold value of the altitude of the plateau strong convection echo top. From fig. 2 (a), it can be seen that the maximum reflectance factor probability density for a Tibet plateau reaches a maximum at 18dBZ, so 18dBZ is set as the plateau weak convection precipitation reflectance factor threshold.
According to the threshold value of the reflectivity factors of the strong and weak convection precipitation of the Qinghai-Tibet plateau, dividing the maximum reflectivity factors of the plateau precipitation into three sections: 15-18dBZ, 18-30dBZ and more than 30dBZ. Their corresponding reflectivity difference probability densities are shown in (e) of fig. 2, which shows that as the maximum reflectivity factor of the picture element increases, the corresponding reflectivity differences also increase continuously; it can also be seen that the difference in reflectivity at the intersection of A3 and A4 in fig. 2 is 3dB, so 3dB is set as the strong convection precipitation reflectivity difference threshold; in FIG. 2, A4 and A5 intersect at-1.5 dB, so-1.5 dB is set as the threshold value of the difference of the reflectivity of the weak convection precipitation; in addition, research shows that the average precipitation profile detected by the rain measuring radar has slope mutation at the height of 7.5km, and the plateau atmosphere is near saturation below 7.5km, so the height of 7.5km is used as an echo top height distinguishing threshold value for distinguishing weak convection precipitation from shallow convection precipitation.
step 21, judging whether the precipitation pixel is judged to be other types of precipitation by the DPR precipitation type classification algorithm, if so, classifying the precipitation pixel to be other types of precipitation, wherein other types of precipitation echo signals are most likely to be clutter according to the DPR precipitation type classification algorithm, and if not, executing step 22;
(22a) The maximum reflectivity factor exceeds the plateau strong convection precipitation reflectivity threshold;
(22b) The reflectivity difference exceeds a strong convection precipitation reflectivity difference threshold;
(22c) The echo top height exceeds a Gao Yuanjiang convection echo top height threshold;
step 23, judging whether the physical quantity related to precipitation of the precipitation pixel meets the following conditions, if yes, determining that the precipitation type of the precipitation pixel is weak convection precipitation, and if not, executing step 24, wherein the conditions comprise:
(23a) The maximum reflectance factor is distributed between 18dBZ and the plateau strong convection reflectance threshold;
(23b) The reflectance difference is distributed between-1.5 dB and the threshold value of the reflectance difference of the strong convection precipitation;
(23c) The echo top height exceeds an echo top height distinguishing threshold value of weak convection precipitation and shallow convection precipitation;
and step 24, determining the precipitation type of the precipitation pixel as shallow convection precipitation.
The following examples are given: in fig. 3, (a) and (b) show the first and second near-surface precipitation rate distributions of the plateau summer precipitation detected by the DPR respectively, AB indicates the section position, in fig. 3, (c) and (d) show the precipitation type distribution given by the DPR precipitation type classification algorithm, in fig. 3, (e) and (f) show the precipitation type distribution given by the classification method of the present invention respectively, in fig. 3, (g) and (h) show the corresponding precipitation types of the precipitation pixels given by the two exemplary radar reflectivity factor sections and the DPR precipitation type classification algorithm respectively, and in fig. 3, (i) and (j) show the corresponding precipitation types of the precipitation pixels given by the classification method of the present invention respectively. The above shows that unlike the existing DPR precipitation type classification algorithm which classifies most of the pixels as lamellar precipitation, the classification method of the invention classifies more strongly convective precipitation and weakly convective precipitation. From the sectional view, the classifying method classifies the pixels with columnar strong reflectivity factors and higher echo tops as strong convection precipitation, and classifies the pixels with stronger reflectivity factors and non-uniform distribution of echo tops as weak convection precipitation, which is consistent with the fact that the Qinghai-Tibet plateau is more isolated and weakly convection in summer, thus preliminarily embodying the rationality of the classifying method.
And step 3, calculating the average reflectivity factor profile and the vertical speed profile of the precipitation pixels of different precipitation types according to the classification result. The vertical speed is from ERA-5 to analyze the data hour by hour, and the lattice points of ERA-5 data which are closest to the precipitation pixel and are closest in time interval are selected for matching. The grid horizontal resolution of the ERA-5 data is 0.25 degrees, giving a total vertical velocity of 37 layers from 100hPa to 1 hPa. Fig. 4 shows a first precipitation example in the left column and a second precipitation example in the right column, respectively, with the DPR precipitation type classification algorithm shown in (a) - (b) in fig. 4 and the inventive classification method shown in (c) - (d) in fig. 4, with the average reflectance factor profile for different precipitation types, and with the DPR precipitation type classification algorithm shown in (e) - (f) in fig. 4 and the inventive classification method shown in (g) - (h) in fig. 4, with the average vertical velocity profile for different precipitation types. In fig. 4, lines A1, A2, A3 represent other types of precipitation, convection precipitation, and lamellar precipitation profiles, respectively, and lines B1, B2, B3, and B4 represent other types of precipitation, shallow convection precipitation, strong convection precipitation, and weak convection precipitation profiles, respectively. It can be seen from fig. 4 that there is no obvious difference between the vertical velocity profiles of the convection precipitation and the lamellar precipitation of the DPR precipitation type classification algorithm, but the reflectivity factors and vertical velocities of the strong convection precipitation, the weak convection precipitation, the shallow convection precipitation and other types of precipitation established by the classification method of the present invention are sequentially reduced, and the rationality is again verified.
FIG. 5 is a graph showing the probability density distribution of the reflectance factors of all precipitation, convection precipitation, lamellar precipitation, strong convection precipitation, weak convection precipitation, shallow convection precipitation with respect to height in summer at the Qinghai-Tibet plateau of 2014-2020, wherein (a) in FIG. 5 shows the probability density distribution of the reflectance factors of all precipitation with respect to height; fig. 5 (b) shows the probability density distribution of the reflectance factor of the convective precipitation with respect to the height; fig. 5 (c) shows the probability density distribution of the reflectance factor of the lamellar precipitation with respect to height; fig. 5 (d) shows the probability density distribution of the reflectivity factor of strongly convective precipitation over height; fig. 5 (e) shows the probability density distribution of the reflectivity factor of the weakly convective precipitation over height; the probability density distribution of the reflectivity factor over height for shallow convective precipitation is shown in fig. 5 (f). The strong convection precipitation reflectivity factors are distributed in 15-50dBZ, and the strong convection precipitation reflectivity factors are mostly linearly increased along with the decrease of the height; the low convection precipitation is mainly distributed in 15-30dBZ from the ground to 11km high reflectivity factors; the reflectivity factor of shallow convection precipitation at 5-9km height is mainly distributed at 15-25dBZ.
Example 2
As shown in fig. 6, the embodiment of the invention further provides a device for classifying rainfall types of Qinghai-Tibet plateau in summer, which comprises:
the rainfall-related physical quantity acquisition unit can acquire summer Qinghai-Tibet plateau rainfall data measured by the satellite-borne double-frequency rainfall radar, and calculate the rainfall-related physical quantity and set a related threshold value according to the summer Qinghai-Tibet plateau rainfall data;
the pixel precipitation type classification unit is in communication connection with the precipitation related physical quantity acquisition unit, and can sequentially judge the specific precipitation type of each precipitation pixel in the summer Qinghai-Tibet plateau precipitation data according to the precipitation related physical quantity calculated by the precipitation related physical quantity acquisition unit and the set related threshold value to obtain the specific precipitation type corresponding to each precipitation pixel;
the reflectivity factor and vertical speed profile acquisition unit is in communication connection with the pixel precipitation type classification unit and can calculate the average reflectivity factor profile and vertical speed profile of the precipitation pixels of different precipitation types according to the classification result of the precipitation pixels obtained by the pixel precipitation type classification unit. The vertical velocity is derived from ERA-5 analyzing the data on an hour-by-hour basis, and space-time matching is performed using a distance and time nearest method.
The specific implementation process of each unit in the device corresponds to each processing step of the method embodiment.
It is noted that what is not described in detail in the embodiments of the present invention belongs to the prior art known to those skilled in the art.
In summary, the classification method of the embodiment of the invention provides a precipitation type classification method based on radar reflectivity factor level characteristics, which can overcome the defect that a DPR precipitation type classification algorithm misjudges the weak convection of a plateau as layered precipitation, so that the plateau summer precipitation is more reasonably classified, the plateau summer precipitation characteristics are conveniently further researched, and technical support and data assurance are provided for the inversion of the subsequent DPR precipitation rate, latent heat and related precipitation parameters.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the scope of the present invention should be included in the scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims. The information disclosed in the background section herein is only for enhancement of understanding of the general background of the invention and is not to be taken as an admission or any form of suggestion that this information forms the prior art already known to those of ordinary skill in the art.
Claims (8)
1. A method for classifying the type of rainfall in the Qinghai-Tibet plateau in summer, which is characterized by comprising the following steps:
step 1, acquiring summer Qinghai-Tibet plateau precipitation data measured by a satellite-borne double-frequency rain measuring radar, and calculating relevant physical quantity of precipitation and setting relevant threshold values through the summer Qinghai-Tibet plateau precipitation data;
step 2, according to the calculated precipitation related physical quantity and the set related threshold value, judging the specific precipitation type of each precipitation pixel in the summer Qinghai-Tibet plateau precipitation data in sequence to obtain the specific precipitation type corresponding to each precipitation pixel; the method comprises the steps of sequentially judging the specific precipitation type of each precipitation pixel in the summer Qinghai-Tibet plateau precipitation data in the following manner to obtain the specific precipitation type corresponding to each pixel, and comprises the following steps:
step 21, judging whether the DPR precipitation type classification algorithm judges the precipitation pixel as other types of precipitation, if so, classifying the precipitation pixel as other types of precipitation, and if not, executing step 22;
step 22, judging whether the precipitation related physical quantity of the precipitation pixel meets any one of the following strong convection precipitation judgment conditions, if yes, determining that the precipitation type of the precipitation pixel is strong convection precipitation, and if not, executing step 23, wherein the strong convection precipitation judgment conditions comprise:
(22a) The maximum reflectivity factor exceeds the plateau strong convection precipitation reflectivity threshold; the maximum reflectivity factor is the maximum reflectivity factor of the clutter-free area between the position 1.5km below the zero-degree layer height and the ground, and if the height 1.5km below the zero-degree layer is lower than the bottom layer height of the clutter-free area, the maximum reflectivity factor is the reflectivity factor corresponding to the bottom layer of the clutter-free area; if the maximum reflectivity factor is smaller than the threshold value set by the Ku wave band radar echo signal, marking the maximum reflectivity factor of the precipitation pixel as a default value;
(22b) The reflectivity difference exceeds a strong convection precipitation reflectivity difference threshold; the reflectivity difference is the difference between the maximum reflectivity factor of the precipitation pixel and the average value of the maximum reflectivity factors of the precipitation pixels around the precipitation pixel, wherein the precipitation pixels around the precipitation pixel refer to all precipitation pixels in a circle with the 11km radius with the precipitation pixel with the maximum reflectivity factor as the center;
(22c) The echo top height exceeds a Gao Yuanjiang convection echo top height threshold;
step 23, judging whether the precipitation related physical quantity of the precipitation pixel meets the following weak convection precipitation judging conditions at the same time, if yes, determining that the precipitation type of the precipitation pixel is weak convection precipitation, and if not, executing step 24, wherein the weak convection precipitation judging conditions comprise:
(23a) The maximum reflectivity factor is distributed between 18dBZ and the threshold value of the high-intensity convection precipitation reflectivity of the plateau;
(23b) The reflectance difference is distributed between-1.5 dB and the threshold value of the reflectance difference of the strong convection precipitation;
(23c) The echo top height exceeds an echo top height distinguishing threshold value of weak convection precipitation and shallow convection precipitation;
step 24, determining the precipitation type of the precipitation pixel as shallow convection precipitation;
and step 3, calculating the average reflectivity factor profile and the vertical speed profile of the precipitation pixels of different precipitation types according to the classification results of all the precipitation pixels.
2. The method for classifying a type of summer tibetan plateau precipitation according to claim 1, wherein in step 1, the variables are calculated and the relevant thresholds are set by the summer tibetan plateau precipitation data in the following manner, comprising:
step 11, setting a near-surface precipitation rate threshold value to be 0mm/h for each track pixel in the dual-frequency rain radar data, judging the pixel as a precipitation pixel when the near-surface precipitation rate is larger than the threshold value, and calculating the following variables as precipitation related physical quantities for the precipitation pixel:
the echo top height is the highest layer height corresponding to 15dBZ of radar reflectivity factors of three layers continuously downwards from the top of the precipitation profile;
step 12, setting a relevant threshold value:
according to the maximum reflectivity factor, the reflectivity difference and the echo top height of each precipitation pixel calculated in the step 11, calculating to obtain the maximum reflectivity factor, the echo top height of the Qinghai-Tibet plateau and probability density distribution of the reflectivity difference under different maximum reflectivity factors, setting the threshold value of the strong convection precipitation reflectivity of the plateau as 30dBZ, the threshold value of the echo top height of the strong convection precipitation as 10.6km and the threshold value of the strong convection precipitation reflectivity as 3dB; the threshold value of the reflectivity of the low-convection precipitation on the plateau is set to 18dBZ, the threshold value of the reflectivity difference of the low-convection precipitation is set to-1.5 dB, and the threshold value for distinguishing the echo top height of the low-convection precipitation from the echo top height of the shallow-convection precipitation is set to 7.5 km.
3. The method according to claim 2, wherein in the step 11, the echo profile of each pixel is from the earth surface up to 22km, 176 layers are added, the vertical resolution is 0.125km, and the zero-degree layer height and the clutter-free region bottom layer height are given by the satellite-borne double-frequency rain radar data.
4. The method for classifying the rainfall types of the Qinghai-Tibet plateau in summer according to claim 1, wherein in the step 3, the average reflectivity factor profile and the vertical velocity profile of the rainfall pixels of different rainfall types are calculated according to the classification result of all the rainfall pixels in the following manner, and the method comprises the following steps:
selecting the grid points of ERA-5 data closest to each precipitation pixel in distance and time to match, and obtaining the vertical speed of each precipitation pixel;
and averaging the layer-by-layer reflectivity factors and the vertical speeds of the precipitation pixels with the same precipitation types to obtain an average reflectivity factor profile and an average vertical speed profile of strong convection precipitation, weak convection precipitation, shallow convection precipitation and other types of precipitation.
5. The method for classifying a type of precipitation in the summer tibetan plateau according to claim 4, wherein the ERA-5 data has a grid horizontal resolution of 0.25 degrees, giving a vertical velocity of 37 layers from 100hPa to 1 hPa.
6. A classification apparatus for summer tibetan plateau precipitation types, characterized by implementing the classification method according to any one of claims 1-5, comprising:
the device comprises a precipitation related physical quantity acquisition unit, a pixel precipitation type classification unit, a reflectivity factor and a vertical speed profile acquisition unit; wherein,,
the rainfall-related physical quantity acquisition unit can acquire summer Qinghai-Tibet plateau rainfall data measured by the satellite-borne double-frequency rain measuring radar, and calculate rainfall-related physical quantity and set related threshold values through the summer Qinghai-Tibet plateau rainfall data;
the pixel precipitation type classification unit is in communication connection with the precipitation related physical quantity acquisition unit, and can sequentially judge the specific precipitation type of each precipitation pixel in the summer Qinghai-Tibet plateau precipitation data according to the precipitation related physical quantity calculated by the precipitation related physical quantity acquisition unit and the set related threshold value to obtain the specific precipitation type corresponding to each precipitation pixel; the method comprises the steps of sequentially judging the specific precipitation type of each precipitation pixel in the summer Qinghai-Tibet plateau precipitation data according to the following mode to obtain the specific precipitation type corresponding to each pixel, and comprises the following steps:
step 21, judging whether the DPR precipitation type classification algorithm judges the precipitation pixel as other types of precipitation, if so, classifying the precipitation pixel as other types of precipitation, and if not, executing step 22;
step 22, judging whether the precipitation related physical quantity of the precipitation pixel meets any one of the following strong convection precipitation judgment conditions, if yes, determining that the precipitation type of the precipitation pixel is strong convection precipitation, and if not, executing step 23, wherein the strong convection precipitation judgment conditions comprise:
(22a) The maximum reflectivity factor exceeds the plateau strong convection precipitation reflectivity threshold;
(22b) The reflectivity difference exceeds a strong convection precipitation reflectivity difference threshold;
(22c) The echo top height exceeds a Gao Yuanjiang convection echo top height threshold;
step 23, judging whether the precipitation related physical quantity of the precipitation pixel meets the following weak convection precipitation judging conditions at the same time, if yes, determining that the precipitation type of the precipitation pixel is weak convection precipitation, and if not, executing step 24, wherein the weak convection precipitation judging conditions comprise:
(23a) The maximum reflectivity factor is distributed between 18dBZ and the threshold value of the high-intensity convection precipitation reflectivity of the plateau;
(23b) The reflectance difference is distributed between-1.5 dB and the threshold value of the reflectance difference of the strong convection precipitation;
(23c) The echo top height exceeds an echo top height distinguishing threshold value of weak convection precipitation and shallow convection precipitation;
step 24, determining the precipitation type of the precipitation pixel as shallow convection precipitation;
the reflectivity factor and vertical velocity profile acquisition unit is in communication connection with the pixel precipitation type classification unit, and can calculate and obtain the average reflectivity factor profile and the average vertical velocity profile of the precipitation pixels of different precipitation types according to the classification result of the precipitation pixels obtained by the pixel precipitation type classification unit.
7. A processing apparatus, comprising:
at least one memory for storing one or more programs;
at least one processor capable of executing one or more programs stored in the memory, which when executed by the processor, cause the processor to implement the method of any of claims 1-5.
8. A readable storage medium storing a computer program, characterized in that the method according to any one of claims 1-5 is implemented when the computer program is executed by a processor.
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