Three-dimensional identification method for stratospheric downwelling leading to near-surface ozone anomaly event

Abstract

The application discloses a three-dimensional identification method for stratospheric ozone abnormal events caused by stratospheric downward transmission, and relates to the technical field of atmospheric science, which mainly comprises the following steps: obtaining the near-surface pollutant concentration data after quality control, calculating the climatological threshold of each index of the upper air dynamic characteristic data and the stratospheric tracer data in the middle troposphere, performing single-layer event preliminary screening to obtain the ground abnormal event signal, the abnormal high ozone event signal and the abnormal high potential vorticity event signal, taking the grid point of the ground abnormal event signal as the spatial reference point of the correlation determination to perform three-dimensional spatial correlation and comprehensive determination to obtain the final stratospheric ozone intrusion near-surface event data set. The three-dimensional identification method for stratospheric ozone abnormal events caused by stratospheric downward transmission can identify the process of stratospheric ozone downward transmission and its near-surface influence with high precision.

Description

Technical Field

[0001] This invention relates to the field of atmospheric science and technology, and more specifically, to a three-dimensional identification method for near-surface ozone anomalies caused by stratospheric downpropagation. Background Technology

[0002] Stratosphere-troposphere transport (STT) is the process of transporting stratospheric matter, momentum, and energy from the stratosphere to the troposphere. It transports O3-rich stratospheric air to the troposphere, leading to an increase in tropospheric O3 concentration. Under specific meteorological conditions, this can further increase near-surface O3 concentration through processes such as turbulent mixing, resulting in stratospheric intrusions to the surface (SITS) and causing O3 pollution events. STT is the main natural source of tropospheric O3 and has a significant impact on its spatiotemporal distribution and variability at different scales. SITS is a crucial process through which STT directly affects the surface. Therefore, accurately identifying and quantifying SITS events is essential for understanding the impact of STT on near-surface ozone.

[0003] Current methods for identifying STT events mainly include the "three-dimensional labeling method" which relies on dynamic processes, the stratospheric O3 tracer method which relies on air mass trajectory models (such as HYSPLIT) and atmospheric chemical models (such as CAM-chem), and diagnostic analysis methods that rely on observational data. Since STTs often occur alongside tropopause folding events, identifying tropopause folds is crucial for determining STT events. Sprenger et al. proposed a "three-dimensional labeling method" based on the vertical distribution characteristics of potential vorticity to identify tropopause folding events. This method defines the dynamic tropopause (2 PVU, potential vorticity units), calculates the depth of the tropopause fold, and determines STT events (e.g., ΔP ≥ 50 hPa). This method is relatively effective in identifying upper-level STT processes, but it mainly focuses on STT signals in the middle and upper troposphere, lacking the ability to discriminate whether STTs extend to the near-surface, and cannot be directly used to assess the impact of STTs on near-surface O3. The stratospheric O3 tracer method characterizes the specific concentrations of stratospheric O3 transported to different altitudes and regions of the troposphere by adding stratospheric O3 tracers to models. These tracers are often programmed to equal the actual model O3 concentration in the stratosphere, but once they enter the troposphere, they cease chemical generation, only undergoing chemical depletion and dry / wet deposition. This method can conveniently estimate the relative contribution of STT (Sequential Transmission Tolerance) to tropospheric O3 at different altitudes and regions, but its accuracy is affected by model parameterization and its ability to simulate subgrid-scale processes, resulting in some uncertainty. In recent years, using observational data to identify STT events has provided new insights for related research. For example, Chen et al. proposed a method to identify the impact of SITS (Sequential Transmission Tolerance) based on the hourly synergistic changes in O3 and CO at ground stations. This method determines SITS processes based on the simultaneous occurrence of a sharp rise in O3 concentration and a sharp drop in CO concentration, and quantifies the impact of SITS through ground O3 anomalies. This method can identify STT processes to some extent and quantitatively estimate the impact of STT on near-surface O3, but its criteria are easily affected by local pollution source disturbances and lack direct characterization of vertical transport processes. Therefore, the accuracy and reliability of STT event identification still need further verification.

[0004] SITS is a complex, multi-scale process. First, it is usually accompanied by dynamic processes such as tropopause folding or shedding of low pressure, which entrains ozone-rich, dry, clean air from the stratosphere into the upper and middle troposphere. Subsequently, this air mass is continuously transported downward within the troposphere through large-scale sinking, turbulent diffusion, and boundary layer mixing, ultimately affecting the near-surface area and causing abnormally high ozone concentrations at the surface, which may trigger regional ozone pollution events.

[0005] To achieve accurate identification and quantitative assessment of the above processes, existing methods mainly rely on techniques such as high-altitude dynamic diagnosis, chemical model tracing, or ground-based observation inversion. However, all of these methods have significant limitations, including at least the following problems: 1. Methods such as the "three-dimensional labeling method" for identifying tropopause folds can effectively diagnose the initial stage of STT (super-intrusion signal) processes. However, these methods primarily focus on the dynamic structure of the upper troposphere and lack the ability to assess the subsequent vertical descent of the intruding air mass within the troposphere and its mixing into the boundary layer. Therefore, it is impossible to confirm whether a super-intrusion event ultimately develops into a near-surface STT, resulting in a lack of assessment of its actual contribution to surface ozone pollution.

[0006] 2. The stratospheric ozone tracer method, by incorporating an inert tracer into a chemical climate model, can theoretically track the tropospheric transport path and flux of stratospheric ozone in three dimensions. However, the accuracy of this method is highly dependent on the model's parameterization accuracy for key physical processes. Inherent biases in these complex processes directly transmit to the estimation results of SITS contributions, introducing significant uncertainties. Its quantitative conclusions require rigorous verification using a large number of independent observations.

[0007] 3. Methods exemplified by Chen et al., which utilize the identification techniques based on the coordinated changes in ground-based O3 and CO, offer a new approach for directly capturing near-surface signals of SITS. However, this method faces multiple challenges in practical applications: (1) Risk of missed detection: This method uses the ground O3 concentration exceeding the "midday sub-average value" of its season as one of the key criteria. Since the near-surface ozone concentration is dominated by photochemical reactions and exhibits significant diurnal variation, the concentration at night is usually low and difficult to reach the midday seasonal average value. Therefore, this method cannot effectively identify stratospheric ozone intrusion events that occur at night or in the early morning.

[0008] (2) Susceptible to interference from non-stratospheric processes: Transregional anthropogenic pollution transport or strong photochemical processes may produce similar phenomena of synergistic changes in ground O3 and CO as SITS, leading to misjudgment.

[0009] Overcoming the shortcomings of existing technologies in determining near-surface impacts and achieving high-precision identification of the downward transport of stratospheric ozone and its near-surface impacts is an urgent problem to be solved. Summary of the Invention

[0010] The purpose of this invention is to provide a three-dimensional identification method for stratospheric downlift-induced near-surface ozone anomalies, which can accurately identify the stratospheric ozone downlift process and its near-surface impact.

[0011] This invention provides a three-dimensional identification method for near-surface ozone anomaly events caused by stratospheric downpropagation, comprising the following steps: S1: Acquire quality-controlled near-surface pollutant concentration data, mid-tropospheric and stratospheric tracer data, and upper-level dynamic characteristic data, and calculate the climatological thresholds for each indicator of the mid-tropospheric and stratospheric tracer data and upper-level dynamic characteristic data; S2: Based on the near-surface pollutant concentration data, tropospheric mid-stratospheric tracer data, upper-level dynamic characteristic data, and climatological thresholds of each indicator, a preliminary screening of single-layer events is performed to obtain ground-based anomalous event signals, anomalous high-ozone event signals, and anomalous high-level vortex event signals. S3: Based on the ground anomaly event signals, abnormal high ozone event signals, and abnormal high-level vortex event signals that occurred on the same day, and using the grid points of the ground anomaly event signals as the spatial reference points for correlation determination, three-dimensional spatial correlation and comprehensive determination are performed to obtain the final stratospheric ozone intrusion near-surface event dataset.

[0012] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described three-dimensional identification method for stratospheric downpropagation leading to near-surface ozone anomalies.

[0013] The three-dimensional identification method for near-surface ozone anomalies caused by stratospheric downpropagation provided by this invention has the following beneficial effects: This invention integrates CAM-Chem model data, reanalysis data, and ground observation data, comprising five core steps: data preparation, threshold calculation, initial screening of single-layer events, three-dimensional spatial correlation, and data output. By constructing a three-dimensional dynamic-chemical co-jurisdictional criterion, this invention overcomes the shortcomings of existing technologies in determining near-surface impacts, achieving high-precision identification of the downward transport process of stratospheric ozone and its near-surface impacts. Furthermore, by integrating ground observations, model simulations, and meteorological dynamic field data, this invention constructs a three-dimensional judgment process of "ground anomaly signal identification—mid-level verification—upper-level dynamic process tracing," significantly improving the accuracy and reliability of identifying whether stratospheric ozone affects the near-surface. Specifically, by integrating ground observations, chemical climate models, and reanalysis data, this invention constructs a vertically integrated identification system from the ground to 300 hPa, achieving three-dimensional monitoring and objective quantitative identification of stratospheric intrusion events, significantly improving the accuracy and timeliness of event determination. This method can effectively distinguish ozone concentration anomalies caused by stratospheric intrusions, providing a key technical means for environmental management departments to accurately identify and exclude such "exceptional" pollution exceedance events, thus contributing to more scientific air quality assessment and management. Simultaneously, the constructed long-term structured event dataset provides a reliable data foundation for revealing the stratospheric-tropospheric exchange patterns and their climate and environmental effects, and for improving relevant forecasting models, promoting the in-depth application of my country's independently observed data in cutting-edge environmental meteorological research. In summary, this invention not only provides objective technical tools for atmospheric chemistry and climate change research, but also provides key scientific evidence for defining and determining "stratospheric ozone intrusion exceptions" in my country, helping to distinguish between natural processes and anthropogenic pollution in environmental management practice, providing a reference for scientific air quality assessment and control policies, and offering reliable technical support for tracing the sources of air pollution, air quality forecasting, and analyzing the causes of ozone pollution in my country. Attached Figure Description

[0014] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 This is a flowchart of a three-dimensional identification method for near-surface ozone anomalies caused by stratospheric downpropagation, provided by the present invention. Detailed Implementation

[0015] To provide a clearer understanding of the technical features, objectives, and effects of the present invention, specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0016] Figure 1 A schematic diagram of a three-dimensional identification method for stratospheric downpropagation-induced near-surface ozone anomaly events according to this embodiment is shown. In this embodiment, the three-dimensional identification method for stratospheric downpropagation-induced near-surface ozone anomaly events includes the following steps: S1: Acquire quality-controlled near-surface pollutant concentration data, mid-tropospheric and stratospheric tracer data, and upper-level dynamic characteristic data, and calculate the climatological thresholds for each indicator of the mid-tropospheric and stratospheric tracer data and upper-level dynamic characteristic data; In one exemplary embodiment, the near-surface pollutant concentration data are hourly ozone and carbon monoxide observation data of the target area, the stratospheric ozone tracer concentration data of the tropospheric mesosphere-stratospheric tracer data chemical climate model, and the upper-level dynamic characteristic data are potential vorticity data of hourly reanalysis data products. In one exemplary embodiment, the climatological thresholds for each index of the mesotropospheric stratospheric tracer data are the climatological daily average values ​​of the mesotropospheric stratospheric tracer data and their corresponding daily standard deviations. The climatological thresholds for each indicator of the upper-level dynamic characteristic data are the climatological daily average value of the upper-level dynamic characteristic data and its corresponding daily standard deviation. S2: Based on the near-surface pollutant concentration data, tropospheric mid-stratospheric tracer data, upper-level dynamic characteristic data, and climatological thresholds of each indicator, a preliminary screening of single-layer events is performed to obtain ground-based anomalous event signals, anomalous high-ozone event signals, and anomalous high-level vortex event signals. In one exemplary embodiment, the single-layer event screening includes ground-level anomalous event screening, anomalous high ozone event screening, and anomalous high-level vortex event screening. In one exemplary embodiment, the initial screening process for ground-based anomalies includes: Based on the near-surface pollutant concentration data, the climatological average value of the corresponding pollutant is first subtracted from the ground pollutant concentration data to remove the influence of background concentration. Then, the annual and hourly ozone and carbon monoxide change rates of each station are calculated. Using the 95th percentile of the hourly ozone change rate and the 5th percentile of the hourly carbon monoxide change rate as thresholds, the moment when ozone rises sharply and carbon monoxide falls sharply at the same time is selected as the starting signal for stratospheric air to reach the ground. For the moment that meets the conditions of a sharp rise in ozone and a sharp fall in carbon monoxide at the same time, the ozone concentration at that moment must exceed the seasonal average value of the corresponding station and exceed the average value of the same time in the same season, while the carbon monoxide concentration is lower than the seasonal average value. When the ozone concentration falls back to the seasonal average value or the carbon monoxide concentration rises back to above the seasonal average value, the event ends. In one exemplary embodiment, the formula for calculating the annual and hourly changes in ozone and carbon monoxide at each site is as follows:

[0017]

[0018] in, and Let represent the hourly rate of change of ozone and the hourly rate of change of carbon monoxide at time t, respectively. The concentration of ozone at a certain moment. This represents the ozone concentration at the previous moment. Let be the concentration of CO at a certain moment. The concentration of CO at the previous moment; In one exemplary embodiment, the initial screening process for the abnormally high ozone event includes: extracting the multi-year average value and standard deviation of tracers for each grid point and each day of the year within the target area based on the tropospheric-stratospheric tracer data and the climatological thresholds of various indicators; when the observed values ​​of tropospheric-stratospheric tracers meet the following conditions: , When this occurs, it is determined that an abnormally high ozone event has occurred. These are observations of tracers in the middle troposphere and stratosphere. and The tracer's multi-year average and standard deviation. The lowest threshold of the national average; In an exemplary embodiment, the initial screening process for the abnormal upper-level vortex event includes: extracting the multi-year average value and standard deviation of potential vortex for each grid point and each day of the year within the target area based on the upper-level dynamic characteristic data and the climatological threshold values ​​of each indicator; when the potential vortex observation value ( )satisfy: , When this occurs, it is determined that an abnormal high-level vortex event has occurred, where 2PVU is the lowest threshold of the national average. These are potential vorticity observations. and The multi-year average value and standard deviation of potential vorticity; S3: Based on the ground anomaly event signal, the abnormal high ozone event signal, and the abnormal high-level vortex event signal that occurred on the same day, the grid points of the ground anomaly event signal are used as the spatial reference points for correlation determination. Three-dimensional spatial correlation and comprehensive determination are performed to obtain the final stratospheric ozone intrusion near-surface event dataset. In one exemplary embodiment, the process of three-dimensional spatial association includes: For each grid point Gs identified as a ground anomaly signal on date D, the latitude and longitude of grid point Gs are Lon G and Lat G Perform the following three-level spatial association determination: Ground event confirmation: Grid point Gs simultaneously meets two criteria: simultaneous reverse mutation of ozone and carbon monoxide and significant deviation from background values, and is identified as a candidate ground point affected by stratospheric intrusion. Spatial support for determining the 700 hPa anomalous ozone signal: A rectangular region with a horizontal range of 10 longitudes × 10 latitudes is constructed, centered on the ground grid point Gs and extending northeastward. The longitude range of this rectangular region is [Lon...]. G Lon G +10°], latitude range is [Lat G Lat G + 10°]; Within the rectangular area, retrieve all grid points with date D, and count the number N of grid points that were determined to have experienced an abnormally high ozone event. 700 ; Calculate the proportion P of abnormal signal points 700 = N 700 / N 700,total , where N 700,total Let P be the total number of grid points in the region. 700 If the ozone concentration is ≥ 10%, then the ground grid point Gs is considered to have obtained effective spatial support for the anomalous ozone signal at a height of 700 hPa. Spatial support determination of 300hPa high-level eddy current signal: A rectangular region of 15 degrees longitude × 15 degrees latitude is constructed, centered on the ground grid point Gs and extending northeastward to a larger horizontal range. The longitude range of this rectangular region is [Lon]. G Lon G +15°], latitude range is [Lat G Lat G + 15°]; Within the rectangular area, retrieve all grid points with date D, and count the number N of grid points that were determined to have experienced an abnormal high-level vortex event. 300 ; Calculate the proportion P of abnormal signal points 300 = N 300 / N 300,total , where N 300,total Let P be the total number of grid points in the region. 300 If the percentage is ≥ 10%, then the ground grid point Gs is considered to have obtained effective spatial support for dynamic anomaly signals at a height of 300 hPa. In one exemplary embodiment, the process of three-dimensional spatial association and comprehensive determination includes: For a ground candidate grid point Gs and a date D, a stratospheric ozone intrusion event is ultimately determined to have occurred if and only if the following three conditions are met simultaneously: Condition 1: The ground candidate grid point Gs is determined to be a ground candidate point affected by stratospheric intrusion; Condition 2: The proportion P of anomalous ozone signals at 700 hPa is within the airspace above and northeast of the candidate ground grid points and within a 10°×10° area. 700 ≥ 10%; Condition 3: The support ratio P of the 300hPa high-level eddy current signal is present above the candidate ground grid points and within a 15°×15° area to the northeast. 300 ≥ 10%; Dates D and grid points Gs that meet all the above conditions are recorded as event grid point information for a confirmed stratospheric ozone intrusion event, including its geographical location, occurrence time and intensity, forming the final stratospheric ozone intrusion near-surface event dataset.

[0019] In some embodiments, the above-described three-dimensional identification method for stratospheric downpropagation leading to near-surface ozone anomalies can also be implemented in the following ways.

[0020] This embodiment explains the present invention in detail by describing the SITS identification process from 2015 to 2022, including the following steps: Step 1: Data Preparation To comprehensively identify SITS events, it is necessary to simultaneously acquire measured, simulated, and reanalytical data at three levels: ground level, mid-tropospheric and stratosphere, and upper-level dynamic characteristics. These data correspond to near-surface pollutant concentrations, mid-tropospheric and stratosphere tracers, and upper-level dynamic characteristics, respectively, laying the data foundation for subsequent steps. Specifically: 1. Ground-based observation data: Hourly ozone (O3) and carbon monoxide (CO) observation data for the target area from March 2015 to February 2023 were obtained from the National Ambient Air Quality Monitoring Network published on the official website of the Ministry of Ecology and Environment of the People's Republic of China. The unit of O3 is micrograms per cubic meter (μg / m³). 3 The unit for CO is milligrams per cubic meter (mg / m³). 3 Remove invalid values, obvious outliers, and sites with a data missing rate exceeding 1 / 3 from the original data.

[0021] 2.700 hPa Data: Stratospheric ozone tracer (O3S) concentration data were obtained from historical simulations of the Chemical Climate Module (CAM-Chem) in the Community Earth System Model, Version 2 (CESM2). 700 hPa isobaric data were extracted, with a temporal resolution of 6 hours and an original spatial resolution of 0.95° × 1.25°. The unit for O3S is (ppbv). Since the model's original output is terrain-following Sigma coordinates, this case study uses the model's built-in surface pressure (PS) and three-dimensional pressure field variables. Bilinear interpolation was used to vertically interpolate the O3S concentration from the Sigma coordinates to the standard isobaric surface to unify the coordinate framework.

[0022] 3.300 hPa Data: Potential vorticity (PV) data were obtained from the fifth-generation hourly reanalysis data product (ERA5) released by the European Centre for Medium-Range Weather Forecasts (ECMWF). 300 hPa isobaric surface data were extracted, with an hourly temporal resolution and an original spatial resolution of 0.5° × 0.5°. PV is measured in Kelvin·m²·kg·s (K·m²). 2 ·kg -1 ·s -1 It is commonly represented by its simplified unit, PVU (1 PVU = 10). -6 K·m 2 ·kg -1 ·s -1 ).

[0023] Step 2: Threshold Calculation In this case, based on multi-year historical data, to establish an objective climatological benchmark, a unified 34-year historical data series from 1990 to 2023 was used to calculate the climatological thresholds for various indicators at both the 700 hPa and 300 hPa layers, providing an objective basis for subsequent identification of stratospheric ozone intrusion events. The specific calculations are as follows: O3S threshold at 700 hPa: Based on CAM-Chem model data from 1990 to 2023, the 34-year average (i.e., climatological daily average) of O3S concentration at 700 hPa altitude and its corresponding daily standard deviation were calculated for subsequent screening of events at 700 hPa altitude.

[0024] PV threshold at 300 hPa: Based on ERA5 reanalysis data from 1990 to 2023, the 34-year average (i.e., climatological daily average) of the PV value at 300 hPa altitude and its corresponding daily standard deviation were calculated for subsequent screening of events at the 300 hPa altitude.

[0025] Step 3: Identification of Vertical Layering Anomaly Signals Input the prepared data at different altitude levels, run the program independently at different altitudes, and initially screen out possible anomalous signal points. The specific steps are as follows: Step 3.1: Preliminary identification of ground-based anomalous signals. Based on the hourly O3 and CO observation data from ground stations that have undergone quality control in Step 1, and utilizing the characteristics of high O3 concentration and low CO concentration in stratospheric air masses, preliminary identification of ground-based anomalous signals that may be caused by stratospheric intrusion is conducted.

[0026] 1. Synchronous reverse mutation of O3 and CO: First, subtract the climatological average value of the corresponding pollutants from the O3 and CO data to remove the influence of background concentration, and then calculate the annual and hourly O3 and CO change rates of each station.

[0027]

[0028]

[0029] in, and Let O3 and CO represent the hourly rate of change and the hourly rate of change, respectively, at time t. The concentration of ozone at a certain moment. This represents the ozone concentration at the previous moment. Let be the concentration of CO at a certain moment. This represents the CO concentration at the previous moment. (In terms of annual...) The 95th percentile and The 5th percentile was used as the threshold to screen out the moments when O3 rises sharply and CO falls sharply in sync, which were used as the starting signals for when stratospheric air might reach the ground.

[0030] 2. Significant deviations of O3 and CO from background values: For moments meeting the criteria of a sharp increase in O3 and a simultaneous sharp decrease in CO, the O3 concentration at that moment must exceed the seasonal average for that station and also exceed the average for the same time of year. Simultaneously, the CO concentration must be below its seasonal average. The event ends when the O3 concentration falls back to the seasonal average or the CO concentration rises above the seasonal average. The results are stored in the list `station_number`.

[0031] 3. Ground observation data is converted into grid data with a spatial resolution of 0.95°×1.25°. That is, ground observation data and mid-to-high-altitude model data need to be converted into a unified geographic grid with a spatial resolution of 0.95°×1.25°. The ground station data is then gridded. Based on the latitude and longitude coordinates of each station, its observation data is assigned to the nearest neighbor grid point. The criterion is: if a station is located within ±0.475° (latitude) and ±0.625° (longitude) of the center point of a grid, it is assigned to that grid. The results are stored in the file `station_number_grid`.

[0032] Example: The spatial range corresponding to the grid point (30°N, 120°E) is latitude 29.525°–30.475°N and longitude 119.375°–120.625°E; all station data within this range are merged into this grid point. Grid value calculation: For all station data belonging to the same grid, the arithmetic mean is taken as the hourly O3 and CO concentration values ​​for that grid. If there are no stations within a grid, it is marked as missing.

[0033] Step 3.2: Preliminary Identification of Anomalous Signals at 700 hPa. Based on the 700 hPa O3S data obtained in Step 1, this step will use the climatological threshold calculated in Step 2 to preliminarily identify anomalous signals that may indicate ozone intrusion at this altitude.

[0034] Call the daily climatological threshold dataset generated in step 2, and extract the multi-year average O3S value for each grid point and each day of the year within the target area. ) and its standard deviation ( ).

[0035] For each grid point, check its O3S observation value daily. If on a certain day The following conditions must be met:

[0036]

[0037] This indicates that an abnormally high ozone signal event at the 700 hPa level occurred at that grid point on that day. 15 ppbv is the lowest threshold of the national average. The results are stored in the file CAM-Chem_number_grid.

[0038] Step 3.3: Preliminary Identification of 300 hPa Anomalous Signals. Based on the 300 hPa potential vorticity data obtained in Step 1, this step will use the climatological threshold calculated in Step 2 to preliminarily identify dynamic anomaly signals that may occur at this altitude and are related to stratospheric intrusion.

[0039] Call the daily climatological threshold dataset generated in step 2, and extract the multi-year average PV of each grid point and each day of the year within the target area. ) and its standard deviation ( ).

[0040] For each grid point, check its PV observation value daily. If on a certain day The following conditions must be met:

[0041]

[0042] This indicates that an anomalous high-level vortex signal event at the 300 hPa level occurred at that grid point on that day. Here, 2PVU is the lowest threshold of the national average. The original high-resolution grid points identified as anomalous events are assigned to a 0.95° × 1.25° target grid based on their latitude and longitude. The results are stored in the file ERA5_number_grid.

[0043] Step 4: Comprehensive Confirmation of the Incident This step aims to perform three-dimensional correlation and fusion analysis on the independent event signals initially screened at different altitudes in Step 3, in order to comprehensively determine whether an event is a true SITS event. Stratospheric intrusion events that can significantly affect ground-level ozone concentrations should exhibit spatiotemporal consistency in the vertical direction (from near the stratosphere to the ground). The specific process is as follows: Step 4.1: Three-dimensional association determination criteria The basic time unit is the day. Anomalous signals at all levels (ground, 700 hPa, 300 hPa) must occur on the same day to qualify for spatial correlation determination. Spatially, the ground anomalous signal grid points output in step 3.1 are used as the spatial reference points for correlation determination.

[0044] For each grid point Gs identified as a ground anomaly signal on date D (whose latitude and longitude are (Lon G Lat G Perform the following three-level spatial association determination: 1. Surface event confirmation: Grid point Gs must have passed the screening in step 3.1, that is, it must simultaneously meet the two criteria of "synchronous reverse mutation" of O3 and CO and "significant deviation from background value" to be identified as a candidate surface point that may be affected by stratospheric intrusion.

[0045] Spatial support for determining the 2.700 hPa anomalous ozone signal: A rectangular region with a horizontal range of 10 longitudes × 10 latitudes is constructed, centered on the ground grid point Gs and extending northeastward (i.e., the transport direction of stratospheric intrusion into China). The longitude range of this region is [Lon G Lon G +10°], latitude range is [Lat G Lat G +10°).

[0046] Within the defined area, retrieve all grid points with date D. Count the number of grid points identified in step 3.2 as having experienced a "700 hPa abnormally high ozone signal event," and denote this as N. 700 .

[0047] Calculate the proportion P of abnormal signal points 700 = N 700 / N 700,total , where N 700,total This represents the total number of grid points within the region. If P 700 If the value is ≥ 10%, then the ground grid point Gs is considered to have obtained effective spatial support for the anomalous ozone signal at a height of 700 hPa.

[0048] 3.300 hPa high-level eddy current signal spatial support determination: A rectangular region of 15 degrees longitude × 15 degrees latitude is constructed, centered on the ground grid point Gs and extending northeastward to the outermost horizontal region. The longitude range of this region is [Lon G Lon G +15°], latitude range is [Lat G Lat G +15°).

[0049] Within the defined area, retrieve all grid points with date D. Count the number of grid points identified in step 3.3 as having experienced a "300 hPa abnormal high-level vortex signal event," and denote this as N. 300 .

[0050] Calculate the proportion P of abnormal signal points 300 = N 300 / N 300,total , where N 300,total This represents the total number of grid points within the region. If P 300 If the percentage is ≥ 10%, then the ground grid point Gs is considered to have obtained effective spatial support for dynamic anomaly signals at a height of 300 hPa.

[0051] Step 4.2: Comprehensive Judgment For a ground candidate grid point Gs and a date D, a "stratospheric ozone intrusion event" is ultimately determined to have occurred if and only if the following three conditions are met simultaneously: Condition 1: Gs is a valid ground candidate point (satisfying condition 1 of step 4.1).

[0052] Condition 2: The proportion P of the anomalous ozone signal at 700 hPa in the airspace above and within a 10°×10° area to the northeast is supported. 700 ≥ 10%.

[0053] Condition 3: The support ratio P of the 300 hPa high-level vortex dynamic signal in the airspace above and within a 15°×15° area to the northeast. 300 ≥ 10%.

[0054] Points (date D, grid point Gs) that meet all the above conditions are recorded as a confirmed stratospheric ozone intrusion event. The results are stored in the list SITS_number.

[0055] Step 5: Data Output The SITS timing and feature information, finally filtered through steps 1-4, is output to a text file in a standard format to form a long-term time-series dataset. The output information includes the time and location of the SITS occurrence, as well as its intensity. In other words, it obtains gridded information on events that meet the criteria, including their geographical location, occurrence time, and intensity, forming the final dataset of stratospheric ozone intrusion near-surface events.

[0056] This invention integrates ground observations, model simulations, and meteorological dynamic field data to construct a three-dimensional judgment process: "ground anomaly signal identification—mid-level verification—upper-level dynamic process tracing." This significantly improves the accuracy and reliability of identifying whether stratospheric ozone affects the near-surface environment. This method not only provides an objective technical tool for atmospheric chemistry and climate change research but also offers crucial scientific evidence for defining and determining "stratospheric ozone intrusion exceptions" in my country. It helps distinguish between natural processes and anthropogenic pollution in environmental management practices and provides a reference for scientific assessment and control policies for air quality.

[0057] This embodiment provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described three-dimensional identification method for stratospheric downpropagation leading to near-surface ozone anomalies.

[0058] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A three-dimensional identification method for stratospheric downpropagation-induced near-surface ozone anomaly events, characterized in that, Includes the following steps: S1: Acquire quality-controlled near-surface pollutant concentration data, mid-tropospheric and stratospheric tracer data, and upper-level dynamic characteristic data, and calculate the climatological thresholds for each indicator of the mid-tropospheric and stratospheric tracer data and upper-level dynamic characteristic data; S2: Based on the near-surface pollutant concentration data, tropospheric mid-stratospheric tracer data, upper-level dynamic characteristic data, and climatological thresholds of each indicator, a preliminary screening of single-layer events is performed to obtain ground-based anomalous event signals, anomalous high-ozone event signals, and anomalous high-level vortex event signals. S3: Based on the ground anomaly event signals, abnormal high ozone event signals, and abnormal high-level vortex event signals that occurred on the same day, and using the grid points of the ground anomaly event signals as the spatial reference points for correlation determination, three-dimensional spatial correlation and comprehensive determination are performed to obtain the final stratospheric ozone intrusion near-surface event dataset.

2. The three-dimensional identification method for stratospheric downpropagation-induced near-surface ozone anomaly events according to claim 1, characterized in that, The near-surface pollutant concentration data are hourly ozone and carbon monoxide observation data for the target area; the stratospheric ozone tracer concentration data from the tropospheric-stratospheric tracer data chemical climate model; and the upper-level dynamic characteristic data are potential vorticity data from hourly reanalysis data products.

3. The three-dimensional identification method for stratospheric downpropagation-induced near-surface ozone anomaly events according to claim 1, characterized in that, The climatological thresholds for each indicator of the mesotropospheric and stratospheric tracer data are the daily climatological averages and their corresponding daily standard deviations of the mesotropospheric and stratospheric tracer data; the climatological thresholds for each indicator of the upper-level dynamic characteristic data are the daily climatological averages and their corresponding daily standard deviations of the upper-level dynamic characteristic data.

4. The three-dimensional identification method for stratospheric downpropagation-induced near-surface ozone anomaly events according to claim 1, characterized in that, The initial screening of single-layer events includes initial screening of ground-based abnormal events, initial screening of abnormally high ozone events, and initial screening of abnormally high-level vortex events.

5. The three-dimensional identification method for stratospheric downpropagation-induced near-surface ozone anomaly events according to claim 4, characterized in that, The initial screening process for ground-based anomalies includes: based on the near-surface pollutant concentration data, firstly, subtracting the climatological average value of the corresponding pollutant from the ground-based pollutant concentration data to remove the influence of background concentration; then, calculating the annual and hourly ozone and carbon monoxide change rates for each station; using the 95th percentile of the annual hourly ozone change rate and the 5th percentile of the hourly carbon monoxide change rate as thresholds, screening out moments when ozone rises sharply and carbon monoxide falls sharply in sync, as the starting signal for stratospheric air reaching the ground; for moments that satisfy the condition of a sharp rise in ozone and a sharp fall in carbon monoxide in sync, and where the ozone concentration at that moment exceeds the seasonal average value for that station and exceeds the average value for the same time in that season, and the carbon monoxide concentration is lower than the seasonal average value, the event ends when the ozone concentration falls back to the seasonal average value or the carbon monoxide concentration rises back above the seasonal average value.

6. The three-dimensional identification method for stratospheric downpropagation-induced near-surface ozone anomaly events according to claim 4, characterized in that, The initial screening process for abnormally high ozone events includes: based on the tropospheric and stratospheric tracer data and climatological thresholds for various indicators, extracting the multi-year average value and standard deviation of tracers for each grid point and each day of the year within the target area; when the observed values ​​of tropospheric and stratospheric tracers meet the following conditions: , When this occurs, it is determined that an abnormally high ozone event has occurred. These are observations of tracers in the middle troposphere and stratosphere. and The tracer's multi-year average and standard deviation. The lowest threshold of the national average.

7. The three-dimensional identification method for stratospheric downpropagation-induced near-surface ozone anomaly events according to claim 4, characterized in that, The initial screening process for the abnormal high-level vortex event includes: based on the upper-level dynamic characteristic data and the climatological thresholds of various indicators, extracting the multi-year average value and standard deviation of potential vortex for each grid point and each day of the year within the target area, when the observed potential vortex value ( )satisfy: , When this occurs, it is determined that an abnormal high-level vortex event has occurred, in which case, It is the lowest threshold of the national average. These are potential vorticity observations. and This represents the multi-year average value and standard deviation of potential vorticity.

8. The three-dimensional identification method for stratospheric downpropagation-induced near-surface ozone anomaly events according to claim 1, characterized in that, The process of three-dimensional spatial association includes: For each grid point Gs identified as a ground anomaly signal on date D, the latitude and longitude of grid point Gs are Lon G and Lat G Perform the following three-level spatial association determination: Ground event confirmation: Grid point Gs simultaneously meets two criteria: simultaneous reverse mutation of ozone and carbon monoxide and significant deviation from background values, and is identified as a candidate ground point affected by stratospheric intrusion. Spatial support for determining the 700 hPa anomalous ozone signal: A rectangular region with a horizontal range of 10 longitudes × 10 latitudes is constructed, centered on the ground grid point Gs and extending northeastward. The longitude range of this rectangular region is [Lon]. G Lon G +10°], latitude range is [Lat G Lat G + 10°]; Within the rectangular area, retrieve all grid points with date D, and count the number N of grid points that were determined to have experienced an abnormally high ozone event. 700 ; Calculate the proportion P of abnormal signal points 700 = N 700 / N 700,total , where N 700,total Let P be the total number of grid points in the region. 700 If the ozone concentration is ≥ 10%, then the ground grid point Gs is considered to have obtained effective spatial support for the anomalous ozone signal at a height of 700 hPa. Spatial support determination of 300hPa high-level eddy current signal: A rectangular region of 15 degrees longitude × 15 degrees latitude is constructed, centered on the ground grid point Gs and extending northeastward to a larger horizontal range. The longitude range of this rectangular region is [Lon]. G Lon G +15°], latitude range is [Lat G Lat G + 15°]; Within the rectangular area, retrieve all grid points with date D, and count the number N of grid points that were determined to have experienced an abnormal high-level vortex event. 300 ; Calculate the proportion P of abnormal signal points 300 = N 300 / N 300,total , where N 300,total Let P be the total number of grid points in the region. 300 If the percentage is ≥ 10%, then the ground grid point Gs is considered to have obtained effective spatial support for dynamic anomaly signals at a height of 300 hPa.

9. The three-dimensional identification method for stratospheric downpropagation-induced near-surface ozone anomaly events according to claim 1, characterized in that, The process of three-dimensional spatial correlation and comprehensive determination includes: For a ground candidate grid point Gs and a date D, a stratospheric ozone intrusion event is ultimately determined to have occurred if and only if the following three conditions are met simultaneously: Condition 1: The ground candidate grid point Gs is determined to be a ground candidate point affected by stratospheric intrusion; Condition 2: The proportion P of anomalous ozone signals at 700 hPa is within the airspace above and northeast of the candidate ground grid points and within a 10°×10° area. 700 ≥ 10%; Condition 3: The support ratio P of the 300hPa high-level eddy current signal is present above the candidate ground grid points and within a 15°×15° area to the northeast. 300 ≥ 10%; Dates D and grid points Gs that meet all the above conditions are recorded as event grid point information for a confirmed stratospheric ozone intrusion event, including its geographical location, occurrence time and intensity, forming the final stratospheric ozone intrusion near-surface event dataset.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the three-dimensional identification method for stratospheric downpropagation leading to near-surface ozone anomalies as described in any one of claims 1-9.

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