Sea fog invasion land forecasting and type identification method based on automatic meteorological station data

Abstract

The invention discloses a sea fog intrusion land forecasting and type identification method based on automatic meteorological station data. The method comprises the following steps: making a sea fog intrusion land historical data set; dividing types and degrees of sea fog invading the land; establishing a sea fog intrusion land forecasting equation, judging sea fog occurrence and land intrusion types, calculating disturbance variation of relative humidity and temperature six hours before the forecasting time, judging whether the wind direction faces the shore or not during forecasting, and calculating which value range the sea fog belongs to according to the equation if the wind direction faces the shore. According to the method for describing sea fog intrusion into land based on the automatic station, the type and degree of sea fog intrusion into land can be finely described hour by hour by using the automatic station, the degree of sea fog intrusion into land can be quantitatively predicted in advance, and a reference is provided for coastal region sea fog prediction.

Description

Technical Field

[0001] The invention relates to a method for predicting sea fog intrusion into land and identifying its type based on automatic weather station data, and belongs to the technical field of meteorology. Background Art

[0002] Sea fog refers to fog generated at sea or in coastal areas, mainly occurring in the South China Sea, the Yellow Sea, the Northwest Pacific Ocean, the Northwest Atlantic Ocean, the west coast of South America, the west coast of the United States and the coast of Australia. According to the different processes and causes of sea fog formation, sea fog is divided into four types: advection fog, radiation fog, terrain fog and mixed fog. Among them, advection fog refers to fog generated on the sea surface due to atmospheric advection, including advection cooling fog and advection evaporation fog.

[0003] Once sea fog invades land, its low visibility will cause port ships to stop sailing, threaten land transportation safety, and even cause airport flight delays and passenger detention, which will have a serious impact on social economy and travel safety. Therefore, the study of sea fog invading land has important practical significance for human society. The automatic station method developed in this work can basically accurately characterize the type and scope of sea fog invading land, providing a reference for the refined forecast and warning of sea fog.

[0004] Existing technologies for forecasting sea fog intrusion into land include the equation established by Song et al. (2022) for forecasting the intensity of sea fog intrusion into land. This forecast equation uses the contribution of specific humidity and temperature to the change of relative humidity in sea fog intrusion into land of different intensities to forecast the type of sea fog intrusion into land. However, this technical formula only considers two meteorological factors with high impact on sea fog intrusion into land, namely specific humidity and temperature, while ignoring the influence of wind direction on sea fog intrusion into land. At the same time, this technology uses relative humidity to characterize sea fog intrusion cases, which easily identifies non-sea fog intrusion cases with high relative humidity as sea fog intrusion cases. Moreover, it only considers sea fog intrusion cases in spring (March-May) while ignoring sea fog intrusion cases that may occur in other seasons. In future research, it is necessary to add high-impact meteorological factors such as wind direction to improve the forecast of the degree of sea fog intrusion into land more accurately. Summary of the invention

[0005] The purpose of the present invention is to provide a method for identifying and predicting the type of sea fog intrusion into land based on automatic weather station data, so as to overcome the shortcomings of the prior art.

[0006] A method for identifying and predicting the type of sea fog intruding into land based on automatic weather station data, characterized in that the method comprises the following steps: 1) Create a historical dataset of sea fog intrusion into land: Individual cases of sea fog intruding on land are extracted from the historical data of no less than 5 years of meteorological observation stations in the coastal area where forecasting is required, and the total number of cases of sea fog intruding on land is no less than 20 to form a data set.

[0007] 2) Classification of types and degrees of sea fog intrusion into land: Taking the angle perpendicular to the coastline as the median angle, the sea fog intrusion is divided into positive and non-positive types according to the deviation of the sea fog intrusion direction from the median angle; and the degree of sea fog intrusion is divided according to the intrusion distance.

[0008] 3) Establish the prediction equation for sea fog intrusion into land: 3.1) In the case of sea fog invading land, three meteorological factors with high correlation with visibility are selected: relative humidity, temperature, and wind direction.

[0009] 3.2) Calculate the changes in humidity and temperature disturbances in the first 6 hours for the case of sea fog intrusion into land.

[0010] 3.3) The following formula is used as the formula for determining the type of sea fog intrusion into land:

[0011] Where T represents the 6-hour disturbance change of temperature, and p is its weight; RH represents the 6-hour disturbance change of relative humidity, and q is its weight.

[0012] 3.4) When the cases are of type 1 to 4 intrusions, the values ​​of X range from 1 to 4. Based on the historical data set, the exhaustive method is used to select the value with the highest accuracy to confirm the values ​​of p and q.

[0013] 3.5) Using the obtained p and q values, calculate the X value for each type of sea fog intrusion in the historical data set.

[0014] 4) Identify the types of sea fog occurrence and land invasion 4.1) Calculate the disturbance change of relative humidity and temperature in the 6 hours before the forecast time according to the formula in 3.2); 4.2) Determine whether the wind direction is onshore during the forecast; 4.3) If it is heading towards the shore, the X value at the forecast time is calculated based on the p and q values ​​determined in 3.4), and it is determined which value range in 3.5) the X value belongs to, thereby realizing the forecast and type identification of sea fog intrusion into land.

[0015] In step 1), the cases of sea fog intrusion into land are selected according to the following four steps: 1.1) Starting from the station farthest from the shore, determine whether fog occurs (visibility is less than 1 km) and whether the fog lasts for more than 3 hours; 1.2) When fog appears at a station, determine whether the visibility decreases gradually from far offshore to shoreward, and whether more than 50% of the stations in the shoreward direction have reduced visibility in turn; 1.3) When step 1.2 is met, determine whether the direction of the accompanying wind during this period is also onshore; 1.4) If steps 1.2 and 1.3 are met, and visibility is less than 1 km at any land station, it is judged that sea fog has invaded the land.

[0016] The step 2) classifying the types and extent of sea fog intrusion into land includes the following steps: 2.1) Different path types are divided along the coastline.

[0017] The angle perpendicular to the coastline is taken as the median angle (abbreviated as the median angle), and the angle from the landing point where the sea fog invades the land to the farthest foggy station from the landing point is taken as the direction of the sea fog intrusion into the land; if the angle of the sea fog intrusion into the land is within the range of α° around the median angle, it is classified as positive type; when the angle of the sea fog intrusion into the land is between α° and 90°, it is classified as non-positive type; α° is obtained based on the historical data set of sea fog intrusion on land. According to the historical data set, α° is the angle that makes 50% of the cases fall within the median angle α°.

[0018] 2.2) Based on the statistical data set of sea fog intrusion cases over the past five years, the landing point of sea fog intrusion on land is taken as the starting point, and the distance of the farthest foggy station from the starting point is taken as the intrusion distance; the degree of sea fog intrusion is divided into 25%, 50%, 75%, and 100% of the farthest intrusion distance. The intrusion distance within 25% of the farthest intrusion distance is classified as Class I intrusion, 25% to 50% as Class II intrusion, 50% to 75% as Class III intrusion, and 75% to 100% as Class IV intrusion.

[0019] The step 3.2) calculates the changes in the first 6 hours of the disturbance of the first two highly correlated elements in the case of sea fog intrusion into land, as follows:

[0020] Where A represents the disturbance change of a certain element in the first 6 hours, represents the disturbance of the element at the forecast time, It represents the disturbance of the element six hours before the forecast time. It indicates the value of the element six hours before the forecast time; the two meteorological elements of relative humidity and temperature are calculated according to the formula.

[0021] The automatic station method of the present invention can accurately describe the type and degree of sea fog intrusion into land hour by hour. The equation for predicting the degree of sea fog intrusion into land of the present invention can predict the degree of sea fog intrusion into land in advance, providing a reference for sea fog forecasting in coastal areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 The present invention is a flow chart of the method for predicting and identifying the type of sea fog intrusion into land based on automatic weather station data. DETAILED DESCRIPTION

[0023] The present invention will be further described below in conjunction with the structural block diagram. Figure 1 As shown, the method for identifying and forecasting the type of sea fog intrusion into land based on automatic weather station data is characterized in that the method comprises the following steps: 1) Prepare a historical data set of sea fog intrusion on land. Extract individual cases of sea fog intrusion on land from the historical data of meteorological observation stations in the coastal area where forecasts are required to form a data set; the historical data set is required to have no less than 5 years of data and a total of no less than 20 cases of sea fog intrusion on land.

[0024] 2) Classify the types and extent of sea fog intrusion into land.

[0025] 3) Establish the prediction equation for sea fog intrusion into land.

[0026] 4) Identify the types of sea fog that occurs and invades land.

[0027] In step 1), the cases of sea fog intrusion into land are selected according to the following four steps: 1.1) Starting from the station farthest from the shore, determine whether fog occurs (visibility is less than 1 km) and whether the fog lasts for more than 3 hours; 1.2) When fog appears at a station, determine whether the visibility decreases from far offshore to shoreward, and whether more than 50% of the stations in the shoreward direction have reduced visibility; 1.3) When step 2 is met, determine whether the direction of the accompanying wind during this period is also onshore; 1.4) If steps 2 and 3 are met, and visibility is less than 1 km at any land station, it is judged that sea fog has invaded the land.

[0028] The step 2) classifying the types and extent of sea fog intrusion into land includes the following steps: 2.1) Different path types are divided along the coastline.

[0029] The angle perpendicular to the coastline is taken as the median angle (abbreviated as the median angle), and the angle from the landing point where the sea fog invades the land to the farthest foggy station from the landing point is taken as the direction of the sea fog intrusion into the land; if the angle of the sea fog intrusion into the land is within the range of α° around the median angle, it is classified as positive type; when the angle of the sea fog intrusion into the land is between α° and 90°, it is classified as non-positive type; α° is obtained based on the historical data set of sea fog intrusion on land. According to the historical data set, α° is the angle that makes 50% of the cases fall within the median angle α°.

[0030] 2.2) Based on the statistical data set of sea fog intrusion cases over the past five years, the landing point of sea fog intrusion on land is taken as the starting point, and the distance of the farthest foggy station from the starting point is taken as the intrusion distance; the degree of sea fog intrusion is divided into 25%, 50%, 75%, and 100% of the farthest intrusion distance. The intrusion distance within 25% of the farthest intrusion distance is classified as Class I intrusion, 25% to 50% as Class II intrusion, 50% to 75% as Class III intrusion, and 75% to 100% as Class IV intrusion.

[0031] The step 3) establishing a sea fog intrusion land prediction equation comprises the following steps: 3.1) According to the correlation between meteorological elements and visibility, four meteorological elements with high correlation with visibility are selected: relative humidity, temperature, wind speed and wind direction.

[0032] 3.2) Calculate the changes in humidity and temperature disturbances in the first 6 hours of the case of sea fog intrusion into land as follows:

[0033] Where A represents the disturbance change of a certain element in the first 6 hours, represents the disturbance of the element at the forecast time, It represents the disturbance of the element six hours before the forecast time. It indicates the value of the element six hours before the forecast time; the two meteorological elements of relative humidity and temperature are calculated according to the formula.

[0034] 3.3) Determine the type of sea fog intrusion into land using the following formula:

[0035] Where T represents the 6-hour disturbance change of temperature, and p is its weight; RH represents the 6-hour disturbance change of relative humidity, and q is its weight.

[0036] 3.4) When the case is a type I intrusion, the value of X is 1, when the case is a type II intrusion, the value of X is 2, when the case is a type III intrusion, the value of X is 3, and when the case is a type IV intrusion, the value of X is 4; Based on the historical data set, the exhaustive method is used to select the method with the highest accuracy to confirm the values ​​of p and q.

[0037] 3.5) Based on the values ​​of p and q determined in 3.4), use the formula in 3.4) to calculate the range of values ​​for each type of sea fog intrusion in the historical data set.

[0038] 4) Identify the types of sea fog occurrence and land invasion 4.1) Calculate the disturbance change of relative humidity and temperature in the 6 hours before the forecast time according to the formula in 3.2); 4.2) Determine whether the wind direction is onshore during the forecast: if the wind blows from the ocean to the land, the wind direction is onshore; if the wind blows from the land to the ocean, the wind direction is not onshore; 4.3) According to the values ​​of p and q determined in step 3.4, calculate the value of X using the formula in step 3.4, and determine which category of the value range obtained in 3.5) the value of X belongs to, thereby realizing the forecast and type identification of sea fog intrusion into land.

[0039] The present invention is based on the method of describing the sea fog intrusion into land by automatic stations, and can use automatic stations to achieve hourly and refined description of the type and degree of sea fog intrusion into land, providing a basis for sea fog research. At the same time, the sea fog intrusion into land forecasting equation provided by the present invention can predict the degree of sea fog intrusion into land in advance according to the different contributions of meteorological elements in sea fog intrusion into land of different intensities, providing a reference for sea fog forecasting in coastal areas.

Claims

1. A method for forecasting and identifying sea fog intrusion into land based on automatic weather station data, characterized in that The method comprises the following steps: 1) Create a historical dataset of sea fog intrusion into land: Extract individual cases of sea fog intruding on land from the historical data of meteorological observation stations in the coastal area where forecasts are required for no less than 5 years, and the total number of cases of sea fog intruding on land shall be no less than 20 to form a data set; 2) Classification of types and degrees of sea fog intrusion into land: Taking the angle perpendicular to the coastline as the median angle, the sea fog intrusion is divided into positive type and non-positive type according to the deviation between the sea fog intrusion direction and the median angle; and the degree of sea fog intrusion is divided according to the intrusion distance; 3) Establish the prediction equation for sea fog intrusion into land: 3.1) In the case of sea fog invading land, four meteorological factors with high correlation with visibility, namely relative humidity, temperature, wind speed and wind direction, were selected; 3.2) Calculate the changes in humidity and temperature disturbances in the first 6 hours for the case of sea fog intrusion into land; 3.3) The following formula is used as the formula for determining the type of sea fog intrusion into land: ， Where T represents the 6-hour disturbance change of temperature, and p is its weight; RH represents the 6-hour disturbance change of relative humidity, and q is its weight; 3.4) When the cases are of type 1 to 4 intrusions, the values ​​of X range from 1 to 4. Based on the historical data set, the exhaustive method is used to select the value with the highest accuracy to confirm the values ​​of p and q. 3.5) Using the obtained p and q values, calculate the X value of each type of sea fog intrusion in the historical data set; 4) Identify the types of sea fog occurrence and land invasion: 4.1) Calculate the disturbance change of relative humidity and temperature in the 6 hours before the forecast time according to the formula in step 3.2); 4.2) Determine whether the wind direction is onshore during the forecast; 4.3) If it is heading towards the shore, calculate the X value at the forecast time according to the p and q values ​​determined in step 3.4), and determine which value range the X value belongs to in step 3.5), thereby realizing the forecast and type identification of sea fog intrusion into land.

2. The method for predicting and identifying the type of sea fog intrusion into land based on automatic weather station data according to claim 1, characterized in that In step 1), the cases of sea fog intrusion into land are selected according to the following four steps: 1.1) Determine whether fog occurs from the station farthest from the shore: visibility is less than 1 km and the fog lasts for more than 3 hours; 1.2) When fog appears at a station, determine whether the visibility decreases gradually from far offshore to shoreward, and whether more than 50% of the stations in the shoreward direction have reduced visibility in turn; 1.3) When step 1.2) is met, determine whether the direction of the accompanying wind during this period is also onshore; 1.4) If steps 1.2) and 1.3) are met, and there is a land station with visibility less than 1 km, it is judged that sea fog has invaded the land.

3. The method for predicting and identifying the type of sea fog intrusion into land based on automatic weather station data according to claim 1, characterized in that The step 2) classifying the types and extent of sea fog intrusion into land includes the following steps: 2.1) Different path types along the coastline The angle perpendicular to the coastline is taken as the median angle, and the angle from the landing point where the sea fog invades the land to the farthest foggy station from the landing point is taken as the direction of the sea fog invading the land. If the angle of the sea fog invading the land is within the range of α° around the median angle, it is classified as positive type; when the angle of the sea fog invading the land is between α° and 90°, it is classified as non-positive type. α° is obtained based on the historical data set of sea fog intrusion into land. According to the historical data set, α° is the angle that makes 50% of the cases fall within the median angle α°; 2.2) Based on the statistical data set of sea fog intrusion cases over the past five years, the landing point of sea fog intrusion on land is taken as the starting point, and the distance of the farthest foggy station from the starting point is taken as the intrusion distance; the degree of sea fog intrusion is divided into 25%, 50%, 75%, and 100% of the farthest intrusion distance. The intrusion distance within 25% of the farthest intrusion distance is classified as Class I intrusion, 25% to 50% as Class II intrusion, 50% to 75% as Class III intrusion, and 75% to 100% as Class IV intrusion.

4. The method for predicting and identifying the type of sea fog intrusion into land based on automatic weather station data according to claim 1, characterized in that The step 3.2) calculates the changes in the first 6 hours of the disturbance of the first two highly correlated elements in the case of sea fog intrusion into land, as follows: ， Where A represents the disturbance change of a certain element in the first 6 hours, represents the disturbance of the element at the forecast time, It represents the disturbance of the element six hours before the forecast time. It indicates the value of the element six hours before the forecast time; the two meteorological elements of relative humidity and temperature are calculated according to the formula.

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