CN110704804B - Self-adaptive hydrogel inversion method - Google Patents

Self-adaptive hydrogel inversion method Download PDF

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CN110704804B
CN110704804B CN201910367225.3A CN201910367225A CN110704804B CN 110704804 B CN110704804 B CN 110704804B CN 201910367225 A CN201910367225 A CN 201910367225A CN 110704804 B CN110704804 B CN 110704804B
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陈耀登
陈海琴
孙涛
高玉芳
王元兵
孟德明
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Nanjing University of Information Science and Technology
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Abstract

The self-adaptive hydrogel inversion method judges the corresponding mode layer and the reflectivity interval according to the input reflectivity observation, finds the corresponding weight coefficient of each hydrogel counted according to the mode background field, distributes the reflectivity to each hydrogel, and inverts the mixture ratio of the hydrogels according to an inversion formula. Has the advantages that: the types and contributions of all water condensate in intervals with different heights and different reflectivity in a research area and an actual weather situation are obtained through statistical analysis, and the water condensate self-adaptive inversion changing along with the weather situation in real time is realized.

Description

Self-adaptive hydrogel inversion method
Technical Field
The invention relates to the technical field of atmospheric science, in particular to a self-adaptive hydrogel inversion method.
Background
Water condensate such as rain, snow and aragonite is one of the key elements describing the atmospheric state of the cloud scale, and the interconversion between them, the cloud-to-rain process and their corresponding thermal and kinetic effects are very important for the forecast of the convection scale weather. The Doppler weather radar is high in space-time resolution, can monitor the occurrence and the position of convection in time, observes the three-dimensional structure and the evolution process of a convection monomer, and contains rich hydrogel information. A large number of researches show that cloud micro physical quantity is obtained through radar reflectivity inversion, and then the mode initial field is adjusted, so that the short-term forecast level of the mode convection weather can be effectively improved.
However, reflectance is a function of various water condensates, and it is difficult to invert a solution of various quantities (various water condensates) from one quantity (reflectance) without uniqueness. At present, most of hydrogel inversion methods are that the main type of the hydrogel is judged based on the reflectivity and the background temperature, then the total reflectivity is separated into various hydrogels according to a certain proportion, and then the mixing ratio of the hydrogels is calculated according to a Z-q formula. But above all the type of water condensate is difficult to identify, where the empirical setting of the reflectivity and temperature threshold for classification does not have a uniform standard value. Many scholars supplement the judgment conditions, but finally rely on the threshold value given by experience for judgment, and most of weather radars in China business are not dual-polarization radars, so that the water condensate is more difficult to distinguish. Secondly, when multiple water condensates coexist, the contribution of each condensate in the reflectivity is also empirically given, which means that the proportion of each condensate is constant in complicated and varied weather conditions, which is obviously not reasonable enough.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a self-adaptive hydrogel inversion method which comprises the following steps: from a background weather field, the composition and contribution of water condensate in different heights and different reflectivity intervals in a research area and an actual weather situation are obtained through statistical analysis, and finally, the reflectivity adaptive inversion changing along with the weather situation in real time is realized, and the method is specifically realized by the following technical scheme:
the self-adaptive hydrogel inversion method comprises the following steps:
step 1) preparing a background field, and extracting three-dimensional temperature, rainwater mixing ratio, snow mixing ratio, aragonite mixing ratio and air density variable in the background field;
step 2) calculating the average value of the air density of all grid points and the mixing ratio of each hydrogel in each reflectivity interval of each mode layer according to the formula (1);
Figure RE-GDA0002306902200000021
Figure RE-GDA0002306902200000022
Figure RE-GDA0002306902200000023
Figure RE-GDA0002306902200000024
in the formula, ref i For i intervals divided by the reflectivity in the background field, the interval setting mode is as follows: ref is 15dBZ or less 1 15-25dBZ is ref 2 25-35dBZ is ref 3 35-45dBZ is ref 4 Ref at a level of 45dBZ or more 5 ；
Figure RE-GDA0002306902200000025
Respectively, mode k layer in ref i Average air density, average rain mix, average snow mix, average shot mix of all grid points of the interval, N being the kth layer ref i The number of all grid points in the interval;
step 3) calculating the average reflectivity of three water condensates in each reflectivity interval on each mode layer according to the formula (2), and adding the reflectivities of the three water condensates to obtain the average total reflectivity;
Figure RE-GDA0002306902200000026
in the formula (I), the compound is shown in the specification,
Figure RE-GDA0002306902200000027
mode k layer upper ref i Average rain, dry snow, wet snow, and aragonite reflectivities of the intervals,
Figure RE-GDA0002306902200000028
is ref on the k-th layer i Average total reflectance of the interval;
step 4) calculating the contribution of the reflectivity of each condensate in each reflectivity interval of each mode layer in the total reflectivity by using a formula (3), and using the contribution as a lookup table;
Figure RE-GDA0002306902200000031
in the formula
Figure RE-GDA0002306902200000032
Respectively, the k-th layer ref i The contribution of rain, dry snow, wet snow, and aragonite in the total reflectance within the interval;
step 5) input reflectance observation Z e First, the mode layer k and the reflectivity section ref corresponding to the reflectivity observation are determined i Inquiring the height corresponding to the observation of the reflectivity and the contribution of each water condensate in the interval of the reflectivity in a lookup table, and solving an equivalent reflectivity factor corresponding to each water condensate through a formula (4);
Figure RE-GDA0002306902200000033
step 6) returning the mixing ratio of each water condensate according to the formula (5),
Figure RE-GDA0002306902200000034
where ρ is the air density of the corresponding pattern mesh in the background, qrn, qds, qws, and qgr are the inverted mixture ratios of rain, dry snow, wet snow, and shot, respectively, and the final snow mixture ratio qsn = qds + qws.
The adaptive hydrogel inversion method is further designed in such a way that the background field in the step 1) is a forecast field integrated from the previous moment to the current moment.
The invention has the following advantages:
the adaptive hydrogel inversion method provided by the invention starts from a background weather field, and obtains the contribution of each hydrogel in the total reflectivity in different height and different reflectivity intervals in a research area and an actual weather situation through statistical analysis, thereby realizing the adaptive inversion of the hydrogel which changes in real time along with the weather situation and the research area. The method can avoid the threshold value and the weight coefficient which are given by experience in the traditional hydrogel inversion method, and effectively improve the accuracy of the hydrogel inversion.
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FIG. 1 is a flow chart of a method for water condensate inversion.
Detailed Description
The present invention will be described in detail with reference to the accompanying drawings.
Referring to FIG. 1, the adaptive hydrogel inversion method provided in this example inputs a radar reflectivity observation Z e And judging the mode layer and the reflectivity interval corresponding to the model layer, finding out the corresponding water condensate weight coefficients Crain, csinow and Cglap counted according to the mode background field, distributing the reflectivity to each water condensate, and inverting the water condensate mixing ratio according to an inversion formula. The method specifically comprises the following steps:
step 1) preparing a background field, and extracting three-dimensional temperature, rainwater mixing ratio, snow mixing ratio, aragonite mixing ratio and air density variable.
And 2) calculating the average values of the air density and the mixing ratio of the water condensate of all grid points of each mode layer aiming at each reflectivity interval of each mode layer according to the formula (1).
Figure RE-GDA0002306902200000041
Figure RE-GDA0002306902200000042
Figure RE-GDA0002306902200000043
Figure RE-GDA0002306902200000051
In the formula, ref i For i intervals divided by reflectivity in the background field, the suggested interval setting mode is as follows: ref is 15dBZ or less 1 15-25dBZ is ref 2 25-35dBZ is ref 3 35-45dBZ is ref 4 Ref at 45dBZ or more 5 ；
Figure RE-GDA0002306902200000052
Respectively, mode k layer in ref i Average air density, average rain mix, average snow mix, average shot mix of all grid points of the interval, N being the kth layer ref i The number of all grid points in the interval;
and 3) calculating the average reflectivity of the three water condensates in each reflectivity interval on each mode layer according to the formula (2), and adding the reflectivities of the three water condensates to obtain the average total reflectivity.
Figure RE-GDA0002306902200000053
In the formula (I), the compound is shown in the specification,
Figure RE-GDA0002306902200000054
mode k layer upper ref i The average rain, dry snow, wet snow, and aragonite reflectivities of the intervals,
Figure RE-GDA0002306902200000055
is ref on the k-th layer i Average total reflectance of the interval;
and 4) calculating the contribution of the reflectivity of each condensate in each reflectivity interval of each mode layer in the total reflectivity by using a formula (3), and taking the contribution as a lookup table.
Figure RE-GDA0002306902200000056
In the formula (I), the compound is shown in the specification,
Figure RE-GDA0002306902200000057
respectively a k-th layer ref i The contribution of rain, dry snow, wet snow, and aragonite in the total reflectance within the interval;
step 5) input reflectance observation Z e First, the mode layer k and the reflectivity section ref corresponding to the reflectivity observation are determined i And in a look-up tableThe contribution of each water condensate in the interval of the height and the reflectivity corresponding to the reflectivity observation is inquired, and the equivalent reflectivity factor of each water condensate is obtained through a formula (4).
Figure RE-GDA0002306902200000061
Step 6) returning the mixing ratio of each water condensate according to the formula (5),
Figure RE-GDA0002306902200000062
where ρ is the air density of the corresponding pattern mesh in the background, qrn, qds, qws, and qgr are the inverted mixture ratios of rain, dry snow, wet snow, and shot, respectively, and the final snow mixture ratio qsn = qds + qws.
In this embodiment, the background field in step 1) is a forecast field integrated from a previous time to a current time.
In the step 4), the contribution of each water condensate in the total reflectivity under different conditions (different heights and different reflectivity intervals) is counted according to the mode background field, and the result is applied to the subsequent inversion process.
The weight assigned to each condensate by the reflectivity in step 5) is derived from the statistical result of the background field in step 4).
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (2)

1. An adaptive hydrogel inversion method is characterized by comprising the following steps:
step 1) preparing a background field, and extracting three-dimensional temperature, rainwater mixing ratio, snow mixing ratio, aragonite mixing ratio and air density variable in the background field;
step 2) calculating the average values of the air density of all grid points and the mixing ratio of all hydraulic substances in each reflectivity interval of each mode layer according to the formula (1);
Figure FDA0003926686920000011
in the formula, ref i For i intervals divided by reflectivity in the background field, the interval setting mode is as follows: ref is 15dBZ or less 1 15-25dBZ is ref 2 25-35dBZ is ref 3 35-45dBZ is ref 4 Ref at a level of 45dBZ or more 5 ；
Figure FDA0003926686920000012
Respectively, mode k layer in ref i Average air density, average rain mix, average snow mix, average aragonite mix of all grid points of the section, N is kth layer ref i The number of all grid points in the interval;
step 3) calculating the average reflectivity of three water condensates in each reflectivity interval on each mode layer according to the formula (2), and adding the reflectivities of the three water condensates to obtain the average total reflectivity;
Figure FDA0003926686920000013
in the formula (I), the compound is shown in the specification,
Figure FDA0003926686920000021
is a mode k upper ref i Average rain, dry snow, wet snow, and aragonite reflectivities of the intervals,
Figure FDA0003926686920000022
is ref on the k-th layer i Average total reflectance of the interval;
step 4) calculating the contribution of the reflectivity corresponding to each hydrogel in each reflectivity interval of each mode layer in the total reflectivity by using a formula (3), and taking the contribution as a lookup table;
Figure FDA0003926686920000023
in the formula (I), the compound is shown in the specification,
Figure FDA0003926686920000024
respectively, the k-th layer ref i The contribution of rain, dry snow, wet snow, and aragonite in the total reflectance within the interval;
step 5) input reflectance observation Z e First, the mode layer k and the reflectivity section ref corresponding to the reflectivity observation are determined i Inquiring the height corresponding to the observed reflectivity and the contribution of each water condensate in the interval of the reflectivity in a lookup table, and calculating the equivalent reflectivity factor corresponding to each water condensate through a formula (4);
Figure FDA0003926686920000025
step 6) returning the mixing ratio of each water condensate according to the formula (5),
Figure FDA0003926686920000031
where ρ is the air density of the corresponding pattern mesh in the background, qrn, qds, qws, and qgr are the inverted mixture ratios of rain, dry snow, wet snow, and shot, respectively, and the final snow mixture ratio qsn = qds + qws.
2. The adaptive hydrogel inversion method according to claim 1, wherein the background field in step 1) is a predictor field integrated from a previous time to a current time.
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