CN116577844B - Automatic east Asia cold front precipitation identification method and system - Google Patents
Automatic east Asia cold front precipitation identification method and system Download PDFInfo
- Publication number
- CN116577844B CN116577844B CN202310309258.9A CN202310309258A CN116577844B CN 116577844 B CN116577844 B CN 116577844B CN 202310309258 A CN202310309258 A CN 202310309258A CN 116577844 B CN116577844 B CN 116577844B
- Authority
- CN
- China
- Prior art keywords
- precipitation
- cold front
- area
- grid
- multiplied
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000001556 precipitation Methods 0.000 title claims abstract description 189
- 238000000034 method Methods 0.000 title claims abstract description 27
- 238000012216 screening Methods 0.000 claims abstract description 42
- 238000007781 pre-processing Methods 0.000 claims abstract description 12
- 238000009499 grossing Methods 0.000 claims description 11
- 238000004364 calculation method Methods 0.000 claims description 6
- 239000002131 composite material Substances 0.000 claims description 5
- 230000009286 beneficial effect Effects 0.000 abstract description 4
- 238000011282 treatment Methods 0.000 abstract description 4
- 230000007774 longterm Effects 0.000 abstract description 3
- 238000011160 research Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
- G01W1/10—Devices for predicting weather conditions
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Environmental & Geological Engineering (AREA)
- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Atmospheric Sciences (AREA)
- Biodiversity & Conservation Biology (AREA)
- Ecology (AREA)
- Environmental Sciences (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses an automatic identification method and system for east Asia cold front precipitation, wherein the method comprises the steps of preprocessing analysis data of a precipitation field, a horizontal wind field and a temperature field at a specific potential height, and determining the range of an initial precipitation falling area; then, the automatic identification cold front is imported to carry out screening, expansion and other treatments on the falling areas, the initial precipitation falling areas at the same moment are screened according to the longitude and latitude positions of the cold front in the automatic identification cold front data set, and the initial precipitation falling areas without the automatic identification cold front data are deleted, so that the primary screening precipitation falling areas are obtained; expanding the primary screening precipitation landing zone by two grids in the southeast direction to obtain an expanded precipitation landing zone; the overlapped part of the extended precipitation landing zone and the precipitation field is the actual precipitation landing zone finally obtained by the method. The invention can obtain better automatic identification result, realizes the automation of east Asia cold front precipitation identification, obtains a long-term quantitative data set, and is beneficial to the automation of the front surface precipitation analysis in modern weather forecast business.
Description
Technical Field
The invention belongs to the technical field of automatic precipitation identification, and particularly relates to an automatic east Asia cold front precipitation identification method and system.
Background
The cold front is used as an important weather system for generating precipitation in the east Asia, and is often associated with weather processes such as strong precipitation and the space-time distribution of the weather processes. In autumn and winter, precipitation related to frontal surface in mid-latitude areas accounts for most of total precipitation, and especially in North China and northeast China, cold front precipitation accounts for 50% -60% of total precipitation. However, in the current actual business, the cold front identification mostly depends on manual analysis, and quantitative research on frontal precipitation is less. Therefore, the realization of the automatic identification of cold front precipitation has important significance for modernization of meteorological service and scientific research of meteorological.
At present, a method for identifying frontal precipitation and a characteristic mechanism of east Asia frontal precipitation are proposed in a plurality of works, but quantitative research on east Asia frontal precipitation is less, and the existing frontal precipitation identification method is not suitable for cold front precipitation research in east Asia areas. Therefore, there is a need to propose an automatic identification method suitable for cold front precipitation in east asia.
Disclosure of Invention
The invention aims to solve the technical problems that: the automatic east Asia cold front precipitation identification method is characterized in that an automatic identification cold front precipitation data set is imported to screen an automatic identification precipitation landing zone, an expansion precipitation landing zone is positioned, an automatic identification actual precipitation landing zone is obtained by combining an actual precipitation field, automation of east Asia cold front precipitation identification is achieved, and a long-term quantification data set is obtained.
The invention adopts the following technical scheme for solving the technical problems:
the invention provides an automatic identification method for east Asia cold front precipitation, which comprises the following steps:
s1, preprocessing analysis data of a precipitation field, a horizontal wind field and a temperature field at a specific potential height, and facilitating Fortran, matlab reading and identification of an actual precipitation landing zone.
S2, determining the range of the initial precipitation landing zone for screening and expanding treatment.
S3, acquiring the specific positions of the automatic identification cold front at each moment by reading the longitude, the latitude and the corresponding time in the automatic identification cold front data set, and performing primary screening on the initial precipitation landing zone.
S4, screening initial precipitation landing areas at the same moment according to longitude and latitude positions of the cold fronts in the automatic identification cold front data set, deleting the initial precipitation landing areas without the automatic identification cold front data, and obtaining the primary screening precipitation landing areas. The primary screening precipitation landing zone is a precipitation zone affected by the cold front, and interference of precipitation landing zones irrelevant to the cold front can be eliminated.
S5, expanding the primary screening precipitation landing zone to two grids in the southeast direction to obtain an expanded precipitation landing zone. Because the automatic identification cold front data set imported by the method has the characteristics of being obtained by the warm boundary of the cold front area, the primary screening precipitation falling area obtained in the step S4 is mainly located after the automatic identification cold front in practice, only the precipitation falling in the primary screening precipitation falling area is defined as cold front precipitation which can cause underestimation of the cold front precipitation, and the precipitation range identified after expansion is more accurate.
S6, determining the overlapping part of the extended precipitation landing zone and the precipitation field, namely the actual precipitation landing zone. The extended precipitation landing zone represents the maximum range of the precipitation zone affected by the cold front, and the precipitation field data is introduced to obtain the actual precipitation zone range affected by the cold front.
Further, in step S1, a horizontal wind field and a temperature field of 850hPa are selected for analyzing data; the pretreatment content is as follows: adding the precipitation of the first 6 hours and the last 6 hours of the selected time, converting the analysis data of the horizontal wind field and the temperature field into binary files as the total precipitation of the selected time, and storing the binary files, wherein the time resolution is 0.25 degrees multiplied by 0.25 degrees per hour.
Further, the specific steps of step S2 are:
s201, calculating a thermal frontal surface parameter in a region with a longitude and latitude range of 10-70 degrees N and 0-160 degrees E, wherein the specific formula is as follows:
wherein T is a temperature value obtained by performing five-point smoothing for 100 times at 850 hPa.
S202, screening to meet condition |TFP| is less than or equal to 2 multiplied by 10 -11 K/m 2 The specific formula is as follows:
wherein u is 850hPa weft horizontal wind, v is 850hPa warp horizontal wind,the temperature value obtained by five-point smoothing for 100 times is given by the composite wind of u and v, x is the weft direction, y is the warp direction and T is the temperature of 850 hPa.
Satisfy the following requirementsThe region of (1) is the cold front area is calculated.
S203, the value of the ith grid point in the 2.5 degree multiplied by 2.5 degree warp direction of the coarse grid corresponds to the average value of the (i-1) multiplied by 10+1 to the ith multiplied by 10 grid points of the fine grid of 0.25 degree multiplied by 0.25 degree, the value of the jth grid point in the weft direction corresponds to the average value of the (j-1) multiplied by 10+1 to the jth multiplied by 10 grid points of the fine grid, and through the calculation, the cold front area of the fine grid is divided into a coarse grid area, and the coarse grid area is the initial precipitation drop area.
In step S5, the grid points on the easiest side and the southwest side of the primary screening precipitation landing zone are used as references, and the two grid points on the easiest side and the two grid points on the southwest side are assigned the same values, so that the landing zone can be expanded by 5 ° to the east and the southward respectively, and the expanded landing zone is the expanded precipitation landing zone.
Further, the invention also provides an automatic east Asia cold front precipitation recognition system, which comprises:
and the data preprocessing module is used for preprocessing analysis data of the precipitation field and the horizontal wind field and the temperature field at a specific potential height.
And the initial precipitation falling zone identification module is used for screening the cold front zone by calculating the hot front parameter and the temperature advection, dividing the cold front zone into coarse grid areas and obtaining the initial precipitation falling zone.
And the cold front position identification module is used for obtaining the automatic identification cold front specific positions at all times by reading the longitude, the latitude and the corresponding time in the automatic identification cold front data set.
And the primary screening precipitation falling zone determining module is used for screening initial precipitation falling zones at the same moment according to the longitude and latitude positions of the cold fronts in the automatic identification cold front data set, deleting the initial precipitation falling zones without the automatic identification cold front data, and obtaining the primary screening precipitation falling zones.
And the expanded precipitation falling area determining module is used for expanding the primary screening precipitation falling area to two grids in the southeast direction to obtain an expanded precipitation falling area.
The actual precipitation falling area determining module is used for determining the overlapping part of the extended precipitation falling area and the precipitation field, namely the actual precipitation falling area finally obtained by the method.
Further, in the data preprocessing module, a horizontal wind field and a temperature field of 850hPa are selected to analyze data; the pretreatment content is as follows: adding the precipitation of the first 6 hours and the last 6 hours of the selected time, converting the analysis data of the horizontal wind field and the temperature field into binary files as the total precipitation of the selected time, and storing the binary files, wherein the time resolution is 0.25 degrees multiplied by 0.25 degrees per hour.
Further, in the initial precipitation landing zone identification module, the specific steps of determining the initial precipitation landing zone are as follows:
s1, calculating a thermal frontal surface parameter in a region with a longitude and latitude range of 10-70 degrees N and 0-160 degrees E, wherein the specific formula is as follows:
wherein T is a temperature value obtained by performing five-point smoothing for 100 times at 850 hPa.
S2, screening meets the condition that the TFP is less than or equal to 2 multiplied by 10 -11 K/m 2 The specific formula is as follows:
wherein u is 850hPa weft horizontal wind, v is 850hPa warp horizontal wind,the temperature value obtained by five-point smoothing for 100 times is given by the composite wind of u and v, x is the weft direction, y is the warp direction and T is the temperature of 850 hPa.
Satisfy the following requirementsThe region of (1) is the cold front area is calculated.
S3, the value of the ith grid point in the 2.5 degree multiplied by 2.5 degree warp direction of the coarse grid corresponds to the average value of the (i-1) multiplied by 10+1 to the ith multiplied by 10 grid points of the fine grid of 0.25 degree multiplied by 0.25 degree, the value of the jth grid point in the weft direction corresponds to the average value of the (j-1) multiplied by 10+1 to the jth multiplied by 10 grid points of the fine grid, and through the calculation, the cold front area of the fine grid is divided into a coarse grid area, and the coarse grid area is the initial precipitation drop area.
Furthermore, in the expanded precipitation falling area determining module, grid points on the easiest side and the southwest side of the primary screening precipitation falling area are used as references, the two grid points on the easiest side and the two grid points on the southwest side are assigned with the same values, the falling area can be expanded by 5 degrees to the east and the southwest respectively, and the expanded falling area is the expanded precipitation falling area.
Compared with the prior art, the invention adopts the technical proposal and has the following remarkable technical effects:
the invention provides an automatic identification method of east Asia cold front precipitation, which gradually improves the accuracy of precipitation drop zone identification through theoretical calculation and multiple treatments, obtains a relatively accurate cold front precipitation data set through re-analysis of data, and realizes the automatic identification of cold front precipitation. The invention also enriches quantitative research of cold front precipitation in east Asia, obtains a long-term quantitative data set of cold front precipitation, enables the east Asia front precipitation research not to be concentrated on a single process, improves the capability of researching the east Asia cold front precipitation from the climatology angle, and is beneficial to automation of front surface precipitation analysis in modern weather forecast business.
Drawings
Fig. 1 is a schematic overall flow chart of an automatic identification method for east asian cold front precipitation.
FIG. 2 shows the cold front and the initial precipitation drop in an embodiment of the present invention.
FIG. 3 is a schematic diagram of an automatic identification cold front introduced in an embodiment of the present invention.
FIG. 4 is a schematic view of a precipitation landing zone of a primary screen in an embodiment of the present invention.
FIG. 5 is a schematic view of an extended precipitation landing zone in an embodiment of the present invention.
FIG. 6 is a schematic diagram of an actual precipitation landing zone in an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described below with reference to the drawings and the detailed description, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which are derived by a person skilled in the art based on the embodiments of the invention, fall within the scope of protection of the invention.
In order to achieve the above purpose, the invention provides an automatic identification method of east asia cold front precipitation, as shown in fig. 1, an algorithm for automatically identifying an initial precipitation landing zone is designed, the initial landing zone is screened and expanded by introducing an automatic identification cold front, and finally an actual precipitation landing zone is positioned to obtain the automatic identification cold front precipitation. The automatic identification method comprises the following steps:
s1, selecting a precipitation field from 18 hours at 3 months in 2017 to 06 hours at 4 days in 9 months, and horizontal wind field and temperature field analysis data on 850hPa potential height at 00 hours at 9 months in 2017, wherein the data are obtained from an ERA-5 (ECMWF) in the middle of Europe, preprocessing the data, converting the horizontal wind field and temperature field data into binary files and storing the binary files, wherein the time resolution of the precipitation field data is hour by hour, the spatial resolution is 0.25 degrees multiplied by 0.25 degrees, and the precipitation field is processed into 12 hours accumulated precipitation field with 00 hours as the center, and then the precipitation amount at 00 hours is the total precipitation amount added at the front 6 hours and the rear 6 hours. In this embodiment, the obtained analysis data are respectively:
weft horizontal wind u of 850 hPa: the unit is m.s -1 The storage mode is [ longitude, latitude, u ]]，[0.0,10.0,1.0],[0.0,10.25,0.9],[0.0,10.5,1.1],[0.0,10.75,1.3],[0.0,11.0,1.3],[0.0,11.25,1.3],[0.0,11.5,0.8],[0.0,11.75,0.6],[0.012.0,0.9]...
Warp horizontal wind v of 850 hPa: the unit is m.s -1 The storage mode is [ longitude, latitude, v]，[0.0,10.0,-0.1],[0.0,10.25,-0.0],[0.0,10.5,0.1],[0.0,10.75,0.2],[0.0,11.0,0.3],[0.0,11.25,0.4],[0.0,11.5,0.7],[0.0,11.75,1.1],[0.012.0,1.2]...
Five-point smoothing is performed on the 850hPa temperature for 100 times, and the temperature value T is: the unit is K, and the storage mode is [ longitude, latitude, T ], [0.0,10.0,292.9], [0.0,10.25,292.9], [0.0,10.5,292.9], [0.0,10.75,292.9], [0.0,11.0,292.9], [0.0,11.25,292.8], [0.0,11.5,292.8], [0.0,11.75,292.8], [0.012.0,292.7]. Total 180121 grid points.
Precipitation field tp: the unit m is stored in the modes of [ longitude, latitude, tp ], [0.0,10.0,0.0], [0.0,10.25,0.0], [0.0,10.5,0.0], [0.0,10.75,0.0], [0.0,11.0,0.0], [0.0,11.25,0.0], [0.0,11.5,0.0], [0.0,11.75,0.0], [0.012.0,0.0]. Total 180121 grid points.
S2, determining the range of an initial precipitation landing zone for screening and expanding, wherein the method specifically comprises the following steps:
s201, calculating a thermal frontal surface parameter at 2017, 9, 4 and 00 days in a region with a longitude and latitude range of 10-70 degrees N and 0-160 degrees E, wherein the specific formula is as follows:
wherein T is a temperature value obtained by performing five-point smoothing for 100 times at 850 hPa.
S202, screening to meet condition |TFP| is less than or equal to 2 multiplied by 10 -11 K/m 2 The specific formula is as follows:
wherein u is 850hPa weft horizontal wind, v is 850hPa warp horizontal wind,the temperature value obtained by five-point smoothing for 100 times is given by the composite wind of u and v, x is the weft direction, y is the warp direction and T is the temperature of 850 hPa.
Satisfy the following requirementsAs a cold front at 2017, 9, 4, and 00. The specific data are: (466,194), (466,195), (466,196), (467,197), (467,198), (468,198), (467,199), (468,199), (469,199) the total of 180121 grid points.
S203, the value of the ith grid point in the warp direction of the coarse grid (2.5 degrees multiplied by 2.5 degrees) corresponds to the average value of the (i-1) multiplied by 10+1 to the ith multiplied by 10 grid points of the fine grid (0.25 degrees multiplied by 0.25 degrees), the value of the jth grid point in the weft direction corresponds to the average value of the (j-1) multiplied by 10+1 to the jth multiplied by 10 grid points of the fine grid, and through the calculation, the cold front area of the fine grid is divided into coarse grid areas, and the coarse grid areas are initial precipitation falling areas at the time of 9 months and 4 days of 2017 and 00. The specific data are: (45,21), (46,21), (45, 20), (46,20), (47,20), (46,19), (47,19), (46,18), (45,17) are the 1792 grid points.
As shown in fig. 2 (a), the shadow area is a cold front area, the resolution is 0.25 ° x 0.25 °, it can be seen that two cold front areas with larger ranges are calculated in the areas of 55 ° to 65 ° N, 65 ° to 95 ° E and 55 ° to 65 ° N, 95 ° to 120 ° E, and in addition, some cold front areas with smaller ranges exist. The hatched area in fig. 2 (b) is an initial precipitation drop area with coarse grid points (2.5 ° ×2.5 °), and it can be seen that after the cold front area is flaked, the front area is treated as a continuous area, which is beneficial to the subsequent treatment of the area.
S3, acquiring the specific positions of the automatic identification cold front at each moment by reading the longitude, the latitude and the corresponding time in the automatic identification cold front data set, and performing primary screening on the initial precipitation landing zone. And reading the longitude and latitude in the cold front data set by using python at the time of 2017, 9 and 4 days, and storing the longitude and latitude in an array to obtain two automatic cold front specific positions under the moment in the 10 DEG-70 DEG N and 0-160 DEG E area shown in figure 3, wherein the center points of the two cold fronts are respectively positioned near 85 DEG E, 60 DEG N and 110 DEG E and 50 DEG N. Fig. 3 shows the relationship between the imported automatic identification cold front and the sea level air pressure field at the corresponding moment, wherein the black thick solid line is the automatic identification cold front at 2017, 9, 4 and 00 days, the black thin contour line is the sea level air pressure field at the corresponding moment, the air pressure value corresponding to the contour line is marked on the contour line, the high and low pressure centers are marked on the center of the contour line, and the automatic identification cold front is basically positioned in the low pressure center and the groove area of the sea level air pressure field. The specific data of the automatic identification cold front are as follows: latitude: 56.00, 56.25, 56.50, 56.75, 58.75, 59.00, 62.50, 63.75, 48.50..245 total, longitude: 72.45, 74.15, 75.78, 78.85, 80.28, 84.20, 91.03, 91.75, 94.91.
S4, as shown in FIG. 4, screening initial precipitation landing areas at the same moment according to the longitude and latitude positions of two automatic cold front identification devices in 2017, 9, 4 and 00, and deleting the initial precipitation landing areas without the automatic cold front identification data. For example, the lattice point where the cold front is automatically identified at this moment is defined as (i 1, j 1), the lattice point where the initial precipitation falls is defined as (i 2, j 2), the values of i1 and i2 range from 1 to 641, the values of j1 and j2 range from 1 to 281, and the find () function of matlab is used, and if (i 1, j 1) and (i 2, j 2) have the same lattice point, the whole area where (i 2, j 2) is located is reserved. After screening, the two automatic identification cold fronts respectively correspond to two non-deleted falling areas, namely the primary screening precipitation falling areas when the two areas are 00. The primary screening precipitation landing zone is a precipitation zone affected by the cold front, and interference of precipitation landing zones irrelevant to the cold front can be eliminated. The specific data of the primary screening precipitation area are as follows: (45,21), (46,21), (45, 20), (46,20), (47,20), (46,19), (47,19), (46,18), (45,17) are the 1792 grid points.
S5, as shown in fig. 5, on the basis of the grid points on the easiest and southwest boundaries of the first-screened precipitation landing zone at time of 2017, 9, 4, and 00, for example, a grid point coordinate is (i, j), if (i, j) is not equal to 0 value and (i+1, j) =0, the eastern boundary is determined, and similarly, if (i, j) is not equal to 0 value and (i, j+1) =0, the southward boundary is determined, the same value as the grid point (i, j) is assigned to the grid points (i+1, j), (i+2, j) on the east side and the grid points (i, j+1), (i, j+2) on the south side, and the same assignment operation is carried out on all grid points on the southeast boundary of the falling area, so that the falling area can be expanded by 5 degrees eastward and southeast respectively, and the expanded falling area is the expanded precipitation falling area when 00 is obtained. In fig. 5, the black thick solid line is an automatically identified cold front at 2017, 9, 4 and 00, the hatched area is an extended precipitation landing area at a corresponding moment, the light part of the hatched area is the primary screening precipitation landing area obtained in step S4, and the dark part shows the range of two grid distances extending eastwly and southward. Specific data of the extended precipitation landing zone are: (45,21), (46,21), (47,21), (45, 20), (46,20), (47,20), (48,20), (49,20), (46,19), (47,19), (48,19) are total 1792 grid points.
S6, as shown in FIG. 6, identifying the precipitation falling in the extended precipitation landing zone, and obtaining the actual precipitation landing zone. The specific contents are as follows: in the area with the longitude and latitude ranging from 10 degrees to 70 degrees N and 0 to 160 degrees E, firstly dividing an expanded precipitation falling area of a coarse grid (2.5 degrees multiplied by 2.5 degrees) into fine grids (0.25 degrees multiplied by 0.25 degrees), namely copying the value of the ith grid point in the warp direction of the coarse grid to each grid point from (i-1) multiplied by 10+1 to (i×10) of the fine grid, and copying the value of the jth grid point in the weft direction of the coarse grid to each grid point from (j-1) multiplied by 10+1 to (j×10) of the fine grid so as to correspond to the precipitation field of the fine grid at 2017, 9 months and 4 days 00. And (3) the overlapping part of the divided fine grid points and the precipitation field at the time of 00 is the actual precipitation landing area at the moment. Fig. 6 shows the correspondence between the actual precipitation area, the automatic identification cold front and the sea level air pressure field at time of 4 days of 2017, 9, and the sea level air pressure field at time, wherein the black thick solid line is the automatic identification cold front at the time, the shadow area is the range of the actual precipitation area, the darker the color of the shadow area is the more precipitation in the area, and in addition, the black thin contour line is the sea level air pressure field at the corresponding time and is marked with the air pressure value and the high-low pressure center corresponding to the contour line. The specific data of the actual precipitation area are as follows: the storage mode is grid point serial number x, y and precipitation tp: [ x, y, tp ], [470,193,13.09], [471,193,14.14], [472,193,15.00], [473,193,15.57], [474,193,15.80], [475,193,15.66], [470,194,13.48], [471,194,14.56], [472,194,15.44], [473,194,16.03]. Total 180121 grid points.
The embodiment of the invention also provides an automatic east Asia cold front precipitation recognition system, which comprises a data preprocessing module, an initial precipitation landing zone recognition module, a cold front position recognition module, a primary screening precipitation landing zone determination module, an extended precipitation landing zone determination module, an actual precipitation landing zone determination module and a computer program capable of running on a processor. It should be noted that each module in the above system corresponds to a specific step of the method provided by the embodiment of the present invention, and has a corresponding functional module and beneficial effect of executing the method. Technical details not described in detail in this embodiment may be found in the methods provided in the embodiments of the present invention.
The above embodiments are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereto, and any modification made on the basis of the technical scheme according to the technical idea of the present invention falls within the protection scope of the present invention.
Claims (4)
1. An automatic east Asia cold front precipitation identification method is characterized by comprising the following steps:
s1, preprocessing analysis data of a precipitation field and a horizontal wind field and a temperature field of 850 hPa;
s2, determining the range of an initial precipitation landing zone, which comprises the following substeps:
s201, calculating a thermal frontal surface parameter in a region with a longitude and latitude range of 10-70 degrees N and 0-160 degrees E, wherein the specific formula is as follows:
wherein T is a temperature value obtained after 100 times of five-point smoothing at 850 hPa;
s202, screening to meet condition |TFP| is less than or equal to 2 multiplied by 10 -11 K/m 2 The specific formula is as follows:
wherein u is 850hPa weft horizontal wind, v is 850hPa warp horizontal wind,five-point smoothing is carried out for 100 times for the temperature of u and v composite wind, x is the weft direction, y is the warp direction and T is 850 hPa;
satisfy the following requirementsThe region of (1) is the calculated cold front area;
s203, the value of the ith grid point in the 2.5 degree multiplied by 2.5 degree warp direction of the coarse grid corresponds to the average value of the (i-1) multiplied by 10+1 to the ith multiplied by 10 grid points of the fine grid of 0.25 degree multiplied by 0.25 degree, the value of the jth grid point in the weft direction corresponds to the average value of the (j-1) multiplied by 10+1 to the jth multiplied by 10 grid points of the fine grid, and through the calculation, the cold front area of the fine grid is divided into a coarse grid area, and the coarse grid area is the initial precipitation drop area;
s3, acquiring the specific positions of the automatic identification cold front at each moment by reading the longitude and latitude and the corresponding time in the automatic identification cold front data set;
s4, screening initial precipitation landing areas at the same moment according to longitude and latitude positions of the cold fronts in the automatic cold front identification data set, deleting the initial precipitation landing areas without the automatic cold front identification data, and obtaining primary screening precipitation landing areas;
s5, expanding the primary screening precipitation landing zone to two grids in the southeast direction to obtain an expanded precipitation landing zone, wherein the specific content is as follows:
taking grid points on the easiest side and the southwest side of the primary screening precipitation falling area as references, assigning the same values for the two grid points on the easiest side and the two grid points on the southwest side, and expanding the falling area to the east and the southwest by 5 degrees respectively, wherein the expanded falling area is the expanded precipitation falling area;
s6, determining the overlapping part of the extended precipitation landing zone and the precipitation field, namely the actual precipitation landing zone.
2. The automatic identification method of east asian cold front precipitation according to claim 1, wherein in step S1, the content of the pretreatment is: adding the precipitation of the first 6 hours and the last 6 hours of the selected time, converting the analysis data of the horizontal wind field and the temperature field into binary files as the total precipitation of the selected time, and storing the binary files, wherein the time resolution is 0.25 degrees multiplied by 0.25 degrees per hour.
3. An automatic east asia cold front precipitation identification system, comprising:
the data preprocessing module is used for preprocessing analysis data of a precipitation field and a horizontal wind field and a temperature field of 850 hPa;
the initial precipitation falling zone identification module is used for screening cold front zones by calculating hot front parameters and temperature advection, dividing the cold front zones into coarse grid zones, and obtaining the initial precipitation falling zone, and comprises the following steps:
s1, calculating a thermal frontal surface parameter in a region with a longitude and latitude range of 10-70 degrees N and 0-160 degrees E, wherein the specific formula is as follows:
wherein T is a temperature value obtained after 100 times of five-point smoothing at 850 hPa;
s2, screening meets the condition that the TFP is less than or equal to 2 multiplied by 10 -11 K/m 2 The specific formula is as follows:
wherein u is 850hPa weft horizontal wind, v is 850hPa warp horizontal wind,five-point smoothing is carried out for 100 times for the temperature of u and v composite wind, x is the weft direction, y is the warp direction and T is 850 hPa;
satisfy the following requirementsThe region of (1) is the calculated cold front area;
s3, the value of the ith grid point in the 2.5 degree multiplied by 2.5 degree warp direction of the coarse grid corresponds to the average value of the (i-1) multiplied by 10+1 to the ith multiplied by 10 grid points of the fine grid of 0.25 degree multiplied by 0.25 degree, the value of the jth grid point in the weft direction corresponds to the average value of the (j-1) multiplied by 10+1 to the jth multiplied by 10 grid points of the fine grid, and through the calculation, the cold front area of the fine grid is divided into a coarse grid area, and the coarse grid area is the initial precipitation drop area;
the cold front position identification module is used for obtaining the specific position of the automatic identification cold front at each moment by reading the longitude, the latitude and the corresponding time in the automatic identification cold front data set;
the primary screening precipitation falling zone determining module is used for screening initial precipitation falling zones at the same moment according to longitude and latitude positions of the cold fronts in the automatic identification cold front data set, deleting the initial precipitation falling zones without the automatic identification cold front data, and obtaining primary screening precipitation falling zones;
the expanded precipitation falling area determining module is used for expanding the primary screening precipitation falling area towards the southeast direction by two grids to obtain an expanded precipitation falling area, and the specific content is as follows:
taking grid points on the easiest side and the southwest side of the primary screening precipitation falling area as references, assigning the same values for the two grid points on the easiest side and the two grid points on the southwest side, and expanding the falling area to the east and the southwest by 5 degrees respectively, wherein the expanded falling area is the expanded precipitation falling area;
the actual precipitation falling area determining module is used for determining the overlapping part of the extended precipitation falling area and the precipitation field, namely the actual precipitation falling area finally obtained by the method.
4. The automatic identification system of east asian cold front precipitation according to claim 3, wherein the data preprocessing module comprises the following preprocessing contents: adding the precipitation of the first 6 hours and the last 6 hours of the selected time, converting the analysis data of the horizontal wind field and the temperature field into binary files as the total precipitation of the selected time, and storing the binary files, wherein the time resolution is 0.25 degrees multiplied by 0.25 degrees per hour.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310309258.9A CN116577844B (en) | 2023-03-28 | 2023-03-28 | Automatic east Asia cold front precipitation identification method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310309258.9A CN116577844B (en) | 2023-03-28 | 2023-03-28 | Automatic east Asia cold front precipitation identification method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116577844A CN116577844A (en) | 2023-08-11 |
| CN116577844B true CN116577844B (en) | 2024-02-09 |
Family
ID=87532909
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310309258.9A Active CN116577844B (en) | 2023-03-28 | 2023-03-28 | Automatic east Asia cold front precipitation identification method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116577844B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117853949B (en) * | 2024-03-07 | 2024-05-14 | 南京信息工程大学 | Deep learning method and system for identifying cold front by using satellite cloud image |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20120101952A (en) * | 2011-03-07 | 2012-09-17 | 부경대학교 산학협력단 | Processing system for temperature field of diffusion model using weather diagnostic model and processing method therefor |
| KR20130056835A (en) * | 2011-11-22 | 2013-05-30 | 부산대학교 산학협력단 | System and method for assessing future climatic change of the east asian summer monsoon |
| CN103163568A (en) * | 2013-04-04 | 2013-06-19 | 李平 | Method for forecasting heavy rainfall by boundary aggregation method |
| KR20140082534A (en) * | 2012-12-24 | 2014-07-02 | 부산대학교 산학협력단 | System and Method for physically based forecasting of East Asian summer monsoon precipitation |
| CN106950612A (en) * | 2017-03-14 | 2017-07-14 | 天津大学 | It is a kind of to be used for automatic identification and the method for drawing cold front in meteorology |
| CN109086818A (en) * | 2018-07-25 | 2018-12-25 | 中国海洋大学 | Oceanic front recognition methods and device |
| CN110489619A (en) * | 2019-07-11 | 2019-11-22 | 董甫 | The method and system of warm area's heavy rain identification and classification |
| CN110502801A (en) * | 2019-07-25 | 2019-11-26 | 天津大学 | Ocean temperature cutting edge of a knife or a sword automatic tracing and characteristic parameter information extracting method |
| CN111414991A (en) * | 2020-02-21 | 2020-07-14 | 中国人民解放军国防科技大学 | Meteorological frontal surface automatic identification method based on multivariate regression |
| JP2021001861A (en) * | 2019-06-05 | 2021-01-07 | 青山シビルエンジニヤリング株式会社 | Rainfall prediction system |
| CN112765832A (en) * | 2021-02-02 | 2021-05-07 | 南京信息工程大学 | Automatic identification and correction method for continental europe |
| CN114565056A (en) * | 2022-03-15 | 2022-05-31 | 中科三清科技有限公司 | Machine learning-based cold-front identification method and device, storage medium and terminal |
| CN115239014A (en) * | 2022-08-10 | 2022-10-25 | 广西电网有限责任公司电力科学研究院 | Heavy rainfall disaster-causing power failure user scale dynamic prediction method and system |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8315961B2 (en) * | 2009-07-14 | 2012-11-20 | Mitsubishi Electric Research Laboratories, Inc. | Method for predicting future environmental conditions |
| US8930299B2 (en) * | 2010-12-15 | 2015-01-06 | Vaisala, Inc. | Systems and methods for wind forecasting and grid management |
| CN105512767B (en) * | 2015-12-15 | 2019-06-11 | 武汉大学 | A kind of Flood Forecasting Method of more leading times |
-
2023
- 2023-03-28 CN CN202310309258.9A patent/CN116577844B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20120101952A (en) * | 2011-03-07 | 2012-09-17 | 부경대학교 산학협력단 | Processing system for temperature field of diffusion model using weather diagnostic model and processing method therefor |
| KR20130056835A (en) * | 2011-11-22 | 2013-05-30 | 부산대학교 산학협력단 | System and method for assessing future climatic change of the east asian summer monsoon |
| KR20140082534A (en) * | 2012-12-24 | 2014-07-02 | 부산대학교 산학협력단 | System and Method for physically based forecasting of East Asian summer monsoon precipitation |
| CN103163568A (en) * | 2013-04-04 | 2013-06-19 | 李平 | Method for forecasting heavy rainfall by boundary aggregation method |
| CN106950612A (en) * | 2017-03-14 | 2017-07-14 | 天津大学 | It is a kind of to be used for automatic identification and the method for drawing cold front in meteorology |
| CN109086818A (en) * | 2018-07-25 | 2018-12-25 | 中国海洋大学 | Oceanic front recognition methods and device |
| JP2021001861A (en) * | 2019-06-05 | 2021-01-07 | 青山シビルエンジニヤリング株式会社 | Rainfall prediction system |
| CN110489619A (en) * | 2019-07-11 | 2019-11-22 | 董甫 | The method and system of warm area's heavy rain identification and classification |
| CN110502801A (en) * | 2019-07-25 | 2019-11-26 | 天津大学 | Ocean temperature cutting edge of a knife or a sword automatic tracing and characteristic parameter information extracting method |
| CN111414991A (en) * | 2020-02-21 | 2020-07-14 | 中国人民解放军国防科技大学 | Meteorological frontal surface automatic identification method based on multivariate regression |
| CN112765832A (en) * | 2021-02-02 | 2021-05-07 | 南京信息工程大学 | Automatic identification and correction method for continental europe |
| CN114565056A (en) * | 2022-03-15 | 2022-05-31 | 中科三清科技有限公司 | Machine learning-based cold-front identification method and device, storage medium and terminal |
| CN115239014A (en) * | 2022-08-10 | 2022-10-25 | 广西电网有限责任公司电力科学研究院 | Heavy rainfall disaster-causing power failure user scale dynamic prediction method and system |
Non-Patent Citations (3)
| Title |
|---|
| An Objective Identification Method for Wintertime Cold Fronts in Eurasia;Mengru FENG, Yujing QIN*, and Chuhan LU;《ADVANCES IN ATMOSPHERIC SCIENCES》;第38卷;1695-1705 * |
| Barry Pickthall.《帆船》.中国海洋大学出版社,2020,119-121. * |
| 基于自动识别的近三十年华北地区冬季冷锋活动异常 及其可能成因;秦育婧;《气象学报》;第80卷(第5期);721-731 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116577844A (en) | 2023-08-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110058328B (en) | Multi-mode combined downscaling prediction method for northeast summer rainfall | |
| CN116577844B (en) | Automatic east Asia cold front precipitation identification method and system | |
| CN104200484A (en) | Distributed photovoltaic system ultra-short-term power output prediction method based on cloud cluster characteristic analysis | |
| CN115878731B (en) | Automatic warm front identification method | |
| KR20180060287A (en) | Method and system for predicting heavy rainfall using numerical weather prediction model prognostic variables | |
| CN113807583B (en) | Subseasonal prediction method based on dynamic statistics combination of low-frequency increment space-time coupling | |
| CN114881345A (en) | Social and economic exposure degree estimation method for storm and high wind combined disaster in climatic change | |
| CN110619291B (en) | Method for identifying nonlinear response relationship between plant coverage and climate factor | |
| CN111652126A (en) | Inversion radiation method based on satellite cloud picture | |
| CN110991769A (en) | Method for quantifying influence of summer arctic cyclone on sea ice | |
| CN112946643B (en) | Offshore wind power extraction method and system based on time sequence radar remote sensing | |
| CN111815020A (en) | South wall radiation prediction method based on solar radiation climate characteristic identification | |
| CN114996943B (en) | Mesoscale numerical simulation method for reservoir storage climate effect evaluation | |
| Trivedi et al. | Numerical simulation of a super cyclonic storm, Orissa 1999: impact of initial conditions | |
| CN115828054A (en) | Method for automatically identifying south branch groove by improving Laplace | |
| CN112883577B (en) | Method for generating typical scene of output of offshore wind farm and storage medium | |
| CN114707687A (en) | Method and system for predicting ten-day rainfall based on tropical atmosphere sub-season oscillation signals | |
| CN115936387B (en) | Photovoltaic power station solar energy resource assessment method based on photometry data | |
| KR102626758B1 (en) | System and method for predicting medium-range track of tropical cyclone | |
| CN116260141B (en) | Reconstruction method and system for power of photovoltaic power station and reconstruction terminal | |
| CN117872508B (en) | Automatic tracking method for cold front path in European and Asian area | |
| CN116362047A (en) | Method and device for determining normal working wind speed of heliostat based on DNI and wind speed | |
| CN116482781A (en) | Prediction method for precipitation extension period in early flood season in south China | |
| CN117724192A (en) | Method, device, equipment and storage medium for monitoring convection primary | |
| Gigant et al. | Case Study of Impact Evaluation of Agrivoltaic Structure Sizing on Water Availability for Wheat: Microclimate Simulations for Agrivoltaics System Performance Assessment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |