A heavy fog forecasting method based on previous day ground meteorological elements and sounding chart

Abstract

A method for forecasting heavy fog based on the previous day's ground meteorological elements and sounding chart, using the minimum dew point temperature, minimum relative humidity, temperature dew point difference, wind speed, 20 o'clock sounding chart characteristics and the next day's minimum forecast temperature to judge whether heavy fog will occur the next day, with high prediction accuracy, simple and easy to use and promote.

Description

Technical Field

[0001] This invention belongs to the field of severe weather forecasting technology, specifically relating to a method for forecasting dense fog. Background Technology

[0002] Dense fog is a weather phenomenon where visibility is less than 500 meters, formed by the condensation (or sublimation) of water vapor (or ice crystals) suspended in the atmosphere. Dense fog primarily occurs when, under conditions of sufficient water vapor, light winds, and atmospheric stability, the air near the ground cools to a certain degree, causing the water vapor to condense into tiny water droplets suspended in the air. The formation of dense fog is closely related to temperature, humidity, wind speed, wind direction, and stratification stability. Fog forecasting is very difficult. Due to the complexity of dense fog forecasting and limited computing power, its forecast accuracy is far lower than that of heavy rain forecasting using the same model system. Currently, operational methods for dense fog forecasting mainly include meteorological methods, statistical forecasting methods, and numerical weather prediction statistical interpretation methods. Meteorological methods rely primarily on previous weather conditions, numerical weather prediction trends and element forecast results, as well as forecasters' experience, to comprehensively assess whether dense fog will occur in the future; however, their accuracy and stability are relatively poor. Numerical weather forecasting (NMR) statistical interpretation methods identify forecast factors with strong correlation to fog, establish forecast equations using statistical models, and then input the forecast factors from the numerical weather prediction into these equations to predict fog occurrence. However, most forecast factors are summarized based on meteorological characteristics at the time of fog occurrence, requiring secondary forecasting using numerical model products, which increases uncertainty. Statistical forecasting methods primarily establish forecast models based on the statistical relationship between fog and previous observed factors. However, since fog is a highly localized weather process, influencing factors vary across regions due to their unique environmental characteristics, and the importance of each factor also differs. Statistical forecast models, based on specific scenarios, are relatively coarse and have lower forecast accuracy.

[0003] Dehong Dai and Jingpo Autonomous Prefecture in Yunnan Province, my country, is located in the southern extension of the Hengduan Mountains in western Yunnan-Guizhou Plateau. The western Gaoligong Mountains extend into Dehong, creating a dissected plateau landscape that is high and steep in the northeast and low and gentle in the southwest. The highest point in the prefecture is in northern Yingjiang, at 3404.6 meters, while the lowest point is in western Yingjiang, at only 210 meters. Based on this topography, the prefecture is divided into seven zones of varying altitudes: ① high-altitude cold mountainous areas (2700-3404.6 meters); ② areas (2200-2700 meters); ③ areas (1800-2200 meters); ④ areas (1600-1800 meters); ⑤ low-altitude tropical zones (950-1100 meters); ⑥ areas (600-950 meters); and ⑦ tropical river valley monsoon forest zones (210-600 meters). Dehong has a unique climate, belonging to the South Asian subtropical monsoon climate zone. It has a large angle of solar incidence and good air transparency, making it a region with high-quality sunshine. This results in mild winters, cool summers, abundant rainfall, simultaneous rain and heat, dry and cold seasons, small annual temperature range, large daily temperature range, short frost period, and few frost days.

[0004] The complex and diverse topography of Dehong Prefecture results in distinct regional characteristics for fog distribution, making monitoring and forecasting challenging. The low-lying areas of Longchuan and Ruili in the southwest, with their low surface wind speeds, experience frequent fog. In contrast, the higher altitudes of Yingjiang and Lianghe in the north, with their stronger winds, lead to less frequent fog. Currently, there are few objective visibility forecast products available, resulting in limited forecast accuracy. Limited data from neighboring provinces show a forecast accuracy rate below 30%. Consequently, fog forecasting in Dehong Prefecture has relied heavily on subjective judgment based on experience, leading to unsatisfactory forecasts. This persistent poor forecasting has even caused forecasters to abandon fog forecasting altogether, relying primarily on real-time monitoring for early warning services. A suitable and accurate objective forecasting method for Dehong Prefecture is lacking. Summary of the Invention

[0005] To address the low accuracy of current statistical methods for fog forecasting and the lack of a local fog forecasting system in Dehong Prefecture, this invention proposes a fog forecasting method based on the previous day's conventional surface meteorological elements and radiosonde charts. This method aims to improve the accuracy of fog forecasting and early warning, and compensate for the deficiencies in fog forecasting methods in Dehong Prefecture.

[0006] The technical solution adopted in this invention is as follows: A method for fog forecasting based on the previous day's surface meteorological elements and radiosonde charts, comprising determining fog forecasting indicators for Dehong Dai and Jingpo Autonomous Prefecture and making fog forecasts based on the determined indicators, including: Indicator 1: Lowest dew point temperature Td between 15:00 and 18:00 on the same day min >Forecast the lowest temperature Tn for the next day min ; Index 2: Minimum relative humidity Rh between 15:00 and 18:00 on the same day min >a, minimum dew point temperature Td min >b, temperature-dew point difference (T-Td) <c; where the values ​​of a, b, and c for each county and city in Dehong Dai and Jingpo Autonomous Prefecture are as follows: In Mangshi and Lianghe County, the percentage of a was 40%, while in Ruili City and Longchuan County, the percentage of a was 30%. The temperature in Mangshi was 7.5℃, in Lianghe County and Longchuan County it was 4.5℃, and in Ruili City it was 6℃. The temperature in Mangshi is 15℃, in Lianghe County it is 14℃, and in Longchuan County and Ruili City it is 17℃. Indicator 3: The 2-minute average wind speed V of northerly or westerly winds after the lowest dew point temperature occurs between 15:00 and 18:00 on the same day. 2min <d; where the values ​​of d for each county and city in Dehong Dai and Jingpo Autonomous Prefecture are: Mangshi 2m / s, Lianghe County 5m / s, Longchuan County and Ruili City 3m / s; Indicator 4: Tengchong Station, the closest station to Dehong Dai and Jingpo Autonomous Prefecture. The 20-hour radiosonde chart (T-InP chart) of Tengchong Station shows a "dry upper layer and wet lower layer" pattern. When the temperature-dew point difference (t-td) is ≤7℃, the extension height of the wet layer is between 750hPa and 600hPa, and the lifting condensation height is below 750hPa. For Mangshi and Lianghe County, if indicators 1 to 4 above are met simultaneously, heavy fog can be predicted for the next morning. For Longchuan County and Ruili City, if indicators 1 to 3 above are met simultaneously, heavy fog can be predicted for the next morning.

[0007] The present invention has the following beneficial effects: 1. The fog forecasting index of this invention selects meteorological elements and radiosonde charts from the previous day as forecasting factors, without overly relying on forecasting models. Since current domestic and international research on fog forecasting indices largely relies on numerical weather prediction of meteorological elements, the instability of model forecasts increases the difficulty and uncertainty of forecasting. However, the forecasting index of this invention uses real-time factors such as the lowest dew point temperature, minimum relative humidity, temperature-dew point difference, wind speed, and radiosonde chart characteristics at 20:00, as well as the lowest forecast temperature of the following day, to determine whether fog will occur the next day. This provides a wider range of real-time factors for reference, reducing reliance on forecasting models. Furthermore, the method of using radiosonde chart characteristics at 20:00 to forecast the occurrence of fog the following day is pioneering.

[0008] 2. This invention fills a long-standing gap in objective fog forecasting methods in Dehong Prefecture. Yunnan Province is located on a low-latitude plateau with extremely complex terrain. Recent research on fog in Yunnan has largely focused on its characteristics and causes, with limited research on fog forecasting and forecasting indicators. Currently, systematic research on fog in Dehong Prefecture is lacking, as are corresponding objective forecasting indicators. Fog forecasts rely heavily on forecasters' subjective experience, resulting in low accuracy and reliability. Furthermore, fog warnings are mostly based on actual conditions, with almost no lead time. Therefore, the proposed fog forecasting indicators for Dehong Prefecture fill this gap in objective fog forecasting methods.

[0009] 3. The method of this invention effectively improves the lead time for fog forecasting and warning. In operational applications, fog forecasts are generally not possible several days in advance; forecasts and warnings are usually issued close to the event. Using the forecast indicators determined by the method of this invention, fog forecasts for Ruili City and Longchuan County can be concluded around 6 PM the day before, while fog forecasts for Mangshi and Lianghe County can be concluded after analyzing radiosonde data after 8 PM the day before. Since fog in Dehong Prefecture mainly occurs between 7 AM and 11 AM, forecasts for fog occurrence can be made 8 to 13 hours before the event, significantly improving the lead time for fog forecasting and warning.

[0010] 4. The method of the present invention not only provides a variety of ground meteorological elements and radiosonde elements that are indicative of fog forecasting, but also determines quantitative indicators for each county and city in Dehong Prefecture. The calculation is simple and the method is convenient to use.

[0011] This invention identifies meteorological indicators and forecasting methods applicable to fog in various counties and cities of Dehong Prefecture by collecting and analyzing conventional surface meteorological parameters and radiosonde maps from historical fog occurrences and the day before. This method closely integrates with the meteorological characteristics of Dehong Prefecture, is simple, efficient, and provides accurate forecasts. Attached Figure Description

[0012] Figure 1 This is a technical roadmap for fog forecasting in Ruili City and Longchuan County, Dehong Prefecture. Figure 2 This is a technical roadmap for fog forecasting in Mangshi and Lianghe counties of Dehong Prefecture. Detailed Implementation

[0013] The invention will be further described below with reference to the embodiments and accompanying drawings.

[0014] Example 1: Fog Forecasting Methods in Ruili City and Longchuan County A method for forecasting dense fog based on the previous day's surface meteorological elements and the conditions of Ruili City and Longchuan County, such as... Figure 1 As shown, the method involves determining fog forecasting indicators for Ruili City and Longchuan County and making fog forecasts based on these indicators. The fog forecasting indicators include: Indicator 1: Lowest dew point temperature Td between 15:00 and 18:00 on the same day min >Forecast the lowest temperature Tn for the next day min ; Index 2: Minimum relative humidity Rh between 15:00 and 18:00 on the same day min >30%; the lowest dew point temperature Td in Longchuan County min >4.5℃, the lowest dew point temperature Td in Ruili City min >6℃; Temperature-dew point difference (T-Td) <17℃; Indicator 3: The 2-minute average wind speed V of northerly or westerly winds after the lowest dew point temperature occurs between 15:00 and 18:00 on the same day. 2min <3m / s; The following day's lowest temperature Tn was read and analyzed using existing numerical models. min and minimum dew point temperature Td min Minimum relative humidity Rh min Temperature-dew point difference (T-Td), 2-minute average wind speed V of northerly or westerly winds 2min If the above-mentioned surface meteorological elements such as indicators 1 to 3 are met simultaneously, it can be predicted that dense fog will occur in Ruili City and Longchuan County the next morning; if the above-mentioned indicators 1 to 3 are not met simultaneously, it can be predicted that dense fog will not occur in Ruili City and Longchuan County the next morning.

[0015] Example 2: Fog Forecasting Methods in Mangshi and Lianghe Counties A method for forecasting dense fog in Mangshi and Lianghe counties based on the previous day's surface meteorological data, such as... Figure 2 As shown, the method involves determining fog forecasting indicators for Mangshi and Lianghe counties and making fog forecasts based on these indicators. The fog forecasting indicators include: Indicator 1: Lowest dew point temperature Td between 15:00 and 18:00 on the same day min >Forecast the lowest temperature Tn for the next day min ; Index 2: Minimum relative humidity Rh between 15:00 and 18:00 on the same day min >40%; Mangshi's lowest dew point temperature Td min >7.5℃, the lowest dew point temperature Td in Lianghe County min >4.5℃; temperature-dew point difference (T-Td) in Mangshi <15℃, temperature-dew point difference (T-Td) in Lianghe County <14℃; Indicator 3: After the lowest dew point temperature occurs between 15:00 and 18:00 on the same day, the 2-minute average wind speed V of the northerly or westerly winds in Mangshi. 2min <2m / s, the 2-minute average wind speed V of northerly or westerly winds in Lianghe County 2min <5m / s; Indicator 4: The 20-hour radiosonde chart (T-InP chart) at Tengchong station shows a "dry upper layer and wet lower layer" pattern. When the temperature-dew point difference (t-td) is ≤7℃, the extension height of the wet layer is between 750hPa and 600hPa, and the condensation height is below 750hPa. Since there is no radiosonde station in Dehong Prefecture, the Tengchong radiosonde station (Tengchong Station), located in Baoshan City, Yunnan Province, which is the closest to Dehong, was selected.

[0016] When all four indicators mentioned above are met, it can be predicted that heavy fog will occur in Mangshi and Lianghe County the next morning; when none of the four indicators are met, it can be predicted that heavy fog will not occur in Mangshi and Lianghe County the next morning.

[0017] The forecast indicators of this invention were applied to historical cases for testing, and it was found that they can significantly reduce the false alarm rate, improve forecast accuracy, and increase the lead time for warnings. Further widespread application of the forecast indicators to meteorological stations in various counties of Dehong Prefecture demonstrated significant effectiveness in fog forecasting, particularly in Longchuan County, where fog is most frequent. Table 1 shows the forecasting results of the fog forecast indicators and methods of this invention in Longchuan County.

[0018]

[0019] According to the Longchuan County Meteorological Observatory, during the 120-day observation period from November 2021 to February 2022, conditions 1, 2, and 3 were met simultaneously 29 times, with 24 instances of dense fog, resulting in a forecast accuracy rate of 82.3%. The 5 instances of false alarms all showed fog levels less than 750 meters. On 91 occasions, conditions 1, 2, and 3 were not met simultaneously, but the following day's actual observations showed no dense fog, consistent with the actual situation. The forecast indicator system of this invention effectively avoids false alarms and missed forecasts of the past few years, improving the accuracy and lead time of dense fog forecasts. In particular, the quantitative establishment of wind speed provides highly accurate forecasts for the first day of fog appearance after rainfall and the last day of consecutive foggy days, improving upon the past situation where qualitative forecasts lacked certainty regarding the initial and final fog days.

[0020] The Longchuan County Meteorological Bureau issues accurate fog warnings daily at 5 PM. The following morning, it collects real-time fog images from nine townships through WeChat groups for township meteorological information officers and the county-wide geological disaster WeChat group. Analyzing the patterns and intensity of the fog, the bureau continuously adjusts the target townships for its fog warnings, resulting in a very high accuracy rate. Simultaneously, the bureau publicizes the warnings at 7 PM the day before on the Longchuan Media Group's "Hometown of Munao Zongge" WeChat official account and video account, providing accurate and timely meteorological services to departments such as traffic safety and agricultural production in Longchuan County.

[0021] Yingjiang County in Dehong Prefecture does not issue fog forecasts because it only has an average of 0.5 days of heavy fog per year.

Claims

1. A method for forecasting dense fog based on the previous day's surface meteorological elements and radiosonde images, characterized in that, The method involves determining fog forecasting indicators for Dehong Dai and Jingpo Autonomous Prefecture and making fog forecasts based on these indicators, including: Indicator 1: Lowest dew point temperature Td between 15:00 and 18:00 on the same day min >Forecast the lowest temperature Tn for the next day min ; Index 2: Minimum relative humidity Rh between 15:00 and 18:00 on the same day min >a, minimum dew point temperature Td min >b, temperature-dew point difference (T-Td) <c; where the values ​​of a, b, and c for each county and city in Dehong Dai and Jingpo Autonomous Prefecture are as follows: In Mangshi and Lianghe County, the percentage of a was 40%, while in Ruili City and Longchuan County, the percentage of a was 30%. The temperature in Mangshi was 7.5℃, in Lianghe County and Longchuan County it was 4.5℃, and in Ruili City it was 6℃. The temperature in Mangshi is 15℃, in Lianghe County it is 14℃, and in Longchuan County and Ruili City it is 17℃. Indicator 3: The 2-minute average wind speed V of northerly or westerly winds after the lowest dew point temperature occurs between 15:00 and 18:00 on the same day. 2min <d; where the values ​​of d for each county and city in Dehong Dai and Jingpo Autonomous Prefecture are: Mangshi 2m / s, Lianghe County 5m / s, Longchuan County and Ruili City 3m / s; Indicator 4: The 20-hour radiosonde chart of Tengchong Station, which is closest to Dehong Dai and Jingpo Autonomous Prefecture, shows a "dry upper layer and wet lower layer" pattern. When the temperature-dew point difference (t-td) is ≤7℃, the extension height of the wet layer is between 750hPa and 600hPa, and the lifting condensation height is below 750hPa. For Mangshi and Lianghe County, if indicators 1 to 4 above are met simultaneously, heavy fog can be predicted for the next morning. For Longchuan County and Ruili City, if indicators 1 to 3 above are met simultaneously, heavy fog can be predicted for the next morning.

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