Method for forecasting sea fog intrusion into land and identifying its type based on automatic weather station data

Abstract

A method for forecasting the intrusion of sea fog into land and identifying its types based on automatic weather station data, including making a historical dataset of the intrusion of sea fog into land; classifying the types and degrees of the intrusion of sea fog into land; establishing a forecasting equation for the intrusion of sea fog into land, discriminating the occurrence of sea fog and the types of intrusion into land, calculating the perturbation changes in relative humidity and temperature in the 6 hours before the forecasting time, and judging whether the wind direction at the forecasting time is onshore. If it is onshore, the value range of which type the sea fog belongs to is calculated according to the equation. The method for depicting the intrusion of sea fog into land based on automatic weather stations of the present invention can use automatic weather stations to depict the types and degrees of the intrusion of sea fog into land hour by hour and in a refined manner, and quantitatively forecast in advance the degree of the intrusion of sea fog into land, providing a reference for sea fog forecasting in coastal areas.

Description

Technical Field

[0001] The present invention relates to a method for forecasting the intrusion of sea fog into land and identifying its types based on automatic weather station data, belonging to the field of meteorological technology. Background Art

[0002] Sea fog refers to the fog generated over the sea or coastal areas, mainly occurring in regions such as 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 formation processes and causes of sea fog, sea fog is divided into four types: advection fog, radiation fog, terrain fog, and mixed fog. Among them, advection fog refers to the fog generated on the sea surface due to the advection of the atmosphere, including advection cooling fog and advection evaporation fog.

[0003] Once the intrusion of sea fog into land occurs, its low visibility will cause ships in ports to suspend navigation, threaten land traffic safety, and even cause flight delays at airports and passenger delays, having a serious impact on social economy and travel safety. Therefore, the research on the intrusion of sea fog into land has important practical significance for human society. The automatic station method developed in this work can basically accurately depict the types and ranges of the intrusion of sea fog into land, providing a reference basis for the refined forecasting and early warning of sea fog.

[0004] Existing technologies for forecasting the intrusion of sea fog into land, such as the equation established by Song et al. (2022) for forecasting the intensity of the intrusion of sea fog into land. This forecasting equation uses the contributions of specific humidity and temperature to the change in relative humidity in the intrusion of sea fog with different intensities to forecast the types of the intrusion of sea fog into land. However, only two high-impact meteorological factors, specific humidity and temperature, on the intrusion of sea fog into land are considered in this technical formula, while the influence of wind direction on the intrusion of sea fog into land is ignored. At the same time, using relative humidity to depict sea fog intrusion cases is likely to misidentify non-sea fog intrusion cases with high relative humidity as sea fog intrusion cases, and 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, high-impact meteorological factors such as wind direction on the intrusion of sea fog into land need to be added for improvement to more accurately forecast the degree of the intrusion of sea fog into land. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for identifying and forecasting the types of the intrusion of sea fog into land based on automatic weather station data to overcome the deficiencies of the prior art.

[0006] The method for identifying and forecasting the types of the intrusion of sea fog into land based on automatic weather station data is characterized in that the method includes the following steps:

[0007] 1) Making a historical dataset of the intrusion of sea fog into land:

[0008] Extract cases of sea fog invading land from the historical data of meteorological observation stations in the coastal area to be forecasted for at least 5 years, with the total number of cases of sea fog invading land being no less than 20, to form a dataset.

[0009] 2) Classify the types and degrees of sea fog invading land:

[0010] Taking the angle perpendicular to the coastline as the median angle, classify the invasion of sea fog into the forward type and the non - forward type according to the deviation of the sea fog invasion direction from the median angle; and classify the degree of sea fog invasion according to the invasion distance.

[0011] 3) Establish a forecasting equation for sea fog invading land:

[0012] 3.1) Select three meteorological elements, namely relative humidity, temperature, and wind direction, with high correlation with visibility, from the cases of sea fog invading land.

[0013] 3.2) Calculate the 6 - hour variation of humidity and temperature perturbations in the cases of sea fog invading land.

[0014] 3.3) Use the following formula as the formula for judging the type of sea fog invading land:

[0015]

[0016] In the formula, T represents the 6 - hour perturbation change of temperature, p is its weight; RH represents the 6 - hour perturbation change of relative humidity, q is its weight.

[0017] 3.4) When the cases are of the first to fourth types of invasion respectively, the X values are 1 to 4; according to the historical dataset, use the exhaustive method to select the values of p and q with the highest accuracy.

[0018] 3.5) Use the obtained values of p and q to calculate the X values of each type of sea fog invasion in the historical dataset.

[0019] 4) Discriminate the occurrence of sea fog and the type of sea fog invading land

[0020] 4.1) Calculate the perturbation changes of relative humidity and temperature in the 6 hours before the forecasting time according to the formula in 3.2);

[0021] 4.2) Judge whether the wind direction at the forecasting time is onshore;

[0022] 4.3) If it is onshore, then according to the values of p and q determined in 3.4), calculate the X value at the forecasting time, and judge which value range in 3.5) this X value belongs to, so as to realize the forecasting and type identification of sea fog invading land.

[0023] In step 1) mentioned above, select the cases of sea fog invading land according to the following four - step discrimination:

[0024] 1.1) Start from the station farthest from the shore to determine whether fog (visibility less than 1 km) appears and the fog duration is greater than 3 hours;

[0025] 1.2) After fog appears at a certain station, determine whether the reduction in visibility gradually decreases from the direction far from the shore to the direction towards the shore, and more than 50% of the stations in the onshore direction successively show a decrease in visibility;

[0026] 1.3) When step 1.2 is satisfied, determine whether the direction of the accompanying wind during this period is also towards the shore;

[0027] 1.4) If steps 1.2 and 1.3 are satisfied and there is a phenomenon that the visibility at a land station is less than 1 km, it is determined that sea fog invades the land.

[0028] The above step 2) divides the types and degrees of sea fog invading the land, including the following steps:

[0029] 2.1) Divide different path types along the coastline direction.

[0030] Take the angle perpendicular to the coastline as the intermediate value angle (abbreviation: median angle), and take the angle from the landing point of the sea fog invading the land to the farthest foggy station from the landing point 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 the forward type; when the angle of the sea fog invading the land is between α° and 90°, it is classified as the non-forward type;

[0031] α° is obtained from the historical dataset of sea fog invading the land. According to the historical dataset, α° is the angle that makes 50% of the cases within the range of α° around the median angle.

[0032] 2.2) According to the statistical dataset of sea fog invasion cases for more than 5 years, starting from the landing point of the sea fog invading the land, take the distance to the farthest foggy station from the starting point as the invasion distance of this time; divide the degree of sea fog invasion by 25%, 50%, 75%, and 100% of the farthest invasion distance. The invasion distance within 25% of the farthest invasion distance is the first type of invasion, 25% to 50% is the second type of invasion, 50% to 75% is the third type of invasion, and 75% to 100% is the fourth type of invasion.

[0033] The above step 3.2) calculates the 6-hour change amount of the first two highly correlated element perturbations in the sea fog invasion cases on land, specifically as follows:

[0034]

[0035] In the formula, A represents the 6-hour perturbation change amount of a certain element, represents the perturbation of this element at the forecast time step, represents the perturbation of this element at the time step six hours before the forecast time step, Indicates the value of the element at the time six hours before the forecast time; calculate the results of the two meteorological elements of relative humidity and temperature according to the formula respectively.

[0036] The automatic station method of the present invention can depict the type and degree of sea fog invading land hour by hour and in a refined manner. The equation for forecasting the degree of sea fog invading land of the present invention can predict the degree of sea fog invading land in advance, providing a reference for sea fog forecasting in coastal areas. Brief Description of the Drawings

[0037] Figure 1 It is a flow chart of the method for forecasting the invasion of sea fog into land and identifying the type based on automatic weather station data of the present invention. Detailed Embodiments

[0038] The present invention will be further described below in conjunction with the structural block diagram. As Figure 1 shown, the method for identifying and forecasting the type of sea fog invading land based on automatic weather station data is characterized in that the method includes the following steps:

[0039] 1) Make a historical dataset of sea fog invading land. Extract the cases of sea fog invading land from the historical data of meteorological observation stations in the shore area to be forecasted to form a dataset; the historical dataset is required to have no less than 5 years of data and no less than 20 total cases of sea fog invading land.

[0040] 2) Divide the type and degree of sea fog invading land.

[0041] 3) Establish an equation for forecasting the invasion of sea fog into land.

[0042] 4) Discriminate the occurrence of sea fog and the type of invasion into land.

[0043] In step 1), the cases of sea fog invading land are selected according to the following four-step discrimination:

[0044] 1.1) Start judging from the station farthest from the shore whether fog (visibility less than 1 km) appears and the fog duration is greater than 3 hours;

[0045] 1.2) After fog appears at a station, judge whether the reduction of visibility decreases sequentially from the direction far from the shore to the direction towards the shore, and more than 50% of the stations in the direction towards the shore sequentially show a decrease in visibility;

[0046] 1.3) When the second step is satisfied, judge whether the direction of the accompanying wind is also towards the shore during this period;

[0047] 1.4) If the second and third steps are satisfied and there is a phenomenon that the visibility at a land station is less than 1 km, it is judged that sea fog has invaded the land.

[0048] The step 2) of dividing the type and degree of sea fog invading land includes the following steps:

[0049] 2.1) Divide different path types along the coastline direction.

[0050] Take the angle perpendicular to the coastline as the median angle (abbreviation: median angle), and take the angle from the landing point where sea fog invades the land to the farthest foggy site from the landing point as the direction of sea fog invading the land; if the angle of sea fog invading the land is within the range of α° around the median angle, it is classified as the forward type; when the angle of sea fog invading the land is between α° and 90°, it is classified as the non-forward type;

[0051] α° is obtained from the historical dataset of sea fog invading the land. According to the historical dataset, α° is the angle that makes 50% of the cases within the range of α° around the median angle.

[0052] 2.2) According to the statistical dataset of sea fog invading cases over 5 years, take the landing point where sea fog invades the land as the starting point, and take the distance to the farthest foggy site from the starting point as the invasion distance for this time; divide the degree of sea fog invasion by 25%, 50%, 75%, and 100% of the farthest invasion distance. An invasion within 25% of the farthest invasion distance is classified as a type I invasion, 25% to 50% as a type II invasion, 50% to 75% as a type III invasion, and 75% to 100% as a type IV invasion.

[0053] The said step 3) Establish a forecasting equation for sea fog invading the land, including the following steps:

[0054] 3.1) According to the correlation between meteorological elements and visibility, select four meteorological elements with high correlation with visibility: relative humidity, temperature, wind speed, and wind direction.

[0055] 3.2) Calculate the change amount in the first 6 hours of the disturbance of humidity and temperature in the cases of sea fog invading the land, as follows:

[0056]

[0057] In the formula, A represents the disturbance change amount in the first 6 hours of a certain element, represents the disturbance of this element at the forecasting time step, represents the disturbance of this element at the time step 6 hours before the forecasting time step, represents the value of this element at the time step 6 hours before the forecasting time step; calculate the results of the two meteorological elements of relative humidity and temperature respectively according to the formula.

[0058] 3.3) Judge the type of sea fog invading the land according to the following formula:

[0059]

[0060] In the formula, T represents the disturbance change amount in 6 hours of temperature, p is its weight; RH represents the disturbance change amount in 6 hours of relative humidity, q is its weight.

[0061] 3.4) When the individual case is a type I intrusion, the value of X is 1; when the individual case is a type II intrusion, the value of X is 2; when the individual case is a type III intrusion, the value of X is 3; when the individual case is a type IV intrusion, the value of X is 4. According to 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.

[0062] 3.5) According to the values of p and q determined in 3.4), use the formula in 3.4) to calculate the value range of each type of sea fog intrusion in the historical data set.

[0063] 4) Discriminate the occurrence of sea fog and the type of land invaded

[0064] 4.1) Calculate the perturbation changes in relative humidity and temperature in the 6 hours before the forecast time according to the formula in 3.2).

[0065] 4.2) Judge whether the wind direction at the forecast time is onshore: 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.

[0066] 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 judge which value range obtained in 3.5) the value of X belongs to, so as to realize the forecast and type identification of sea fog invading the land.

[0067] The method for depicting sea fog invading the land based on an automatic weather station in the present invention can use the automatic weather station to depict the type and degree of sea fog invading the land hour by hour and in a refined manner, providing a basis for sea fog research. At the same time, the equation for forecasting sea fog invading the land provided by the present invention forecasts the degree of sea fog invading the land in advance according to the different contributions of meteorological elements in sea fog invading the land with 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 relative 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 change in temperature disturbance in the first 6 hours, and p is its weight; RH represents the change in relative humidity disturbance in the first 6 hours, 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 change in relative humidity and temperature disturbances in the 6 hours before the forecast time; 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 relative humidity and temperature disturbances in the first 6 hours of the case of sea fog intrusion into land as follows: ， Where A represents the change in relative humidity or temperature disturbance in the first 6 hours. Represents the disturbance of relative humidity or temperature at the forecast time. Indicates the disturbance of relative humidity or temperature 6 hours before the forecast time. It indicates the value of relative humidity or temperature 6 hours before the forecast time; the disturbance change of relative humidity and temperature is calculated according to the formula.

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