Method for monitoring and evaluating low-temperature cloudy and rainy weather weather disasters

Abstract

The invention belongs to the technical field of meteorological disaster detection and evaluation, and discloses a method for monitoring and evaluating low-temperature cloudy and rainy weather weather disasters, which comprises the following steps: S1, acquiring and preprocessing meteorological data and geographic information data in a research area; s2, constructing a refined meteorological data historical database; s3, calculating low-temperature cloudy and rainy weather disaster indexes; s4, evaluating low-temperature cloudy and rainy weather disaster risks; s5, evaluating the exposure degree of the low-temperature cloudy and rainy widow disaster; s6, a low-temperature cloudy and rainy widow disaster refined risk assessment model is established; s7, checking the evaluation effect; according to the invention, from the aspects of meteorological data refinement processing, key index identification, risk assessment and inspection, a refined low-temperature cloudy and rainy widow disaster assessment result is obtained, and a basis can be provided for agricultural departments to carry out low-temperature cloudy and rainy widow disaster prevention and reduction work.

Description

Technical Field

[0001] The invention relates to the technical field of meteorological disaster detection and assessment, and in particular to a method for monitoring and assessing low-temperature, rainy and low-sun meteorological disasters. Background Art

[0002] Low temperature, cloudy and rainy weather and little sunshine refers to the disaster caused by long-term low temperature, cloudy and rainy weather and less sunshine. Low temperature, cloudy and rainy weather and little sunshine disasters include low temperature during spring sowing, low temperature during transplanting, autumn wind, autumn drizzle, little sunshine, etc. Low temperature, cloudy and rainy weather and little sunshine disasters mainly affect crops due to delayed growth during the key growth period of crops, or reduced production due to physiological disorders, diseases and insect pests induced by low temperature and high humidity conditions, and premature mildew and rot of fruits due to continuous cloudy and rainy weather. Summary of the invention

[0003] The present invention aims to provide a method for monitoring and evaluating low-temperature, cloudy, rainy and low-light meteorological disasters. By refining the meteorological data, identifying key indicators, risk assessment and inspection, a refined low-temperature, cloudy, rainy and low-light disaster assessment result is obtained, which can provide a basis for the agricultural sector to carry out low-temperature, cloudy, rainy and low-light disaster prevention and mitigation work.

[0004] In order to achieve the above object, the present invention provides the following technical solutions:

[0005] A method for monitoring and evaluating low-temperature, rainy, and low-sun meteorological disasters comprises the following steps:

[0006] S1. Collection and preprocessing of meteorological data and geographic information data in the study area

[0007] Meteorological data and geographic information data in the study area were collected, and the meteorological data of the regional automatic station were compared with the data of the conventional observation station at the same time to conduct quality control in terms of temporal and spatial consistency assessment and outlier correction; among them, the meteorological data included the daily average temperature, cumulative precipitation from 08:00 to 08:00, and sunshine hours data of the conventional meteorological observation station and the regional automatic station, and the geographic information data included the altitude;

[0008] S2. Build a refined meteorological data historical database

[0009] According to the meteorological data of conventional meteorological observation stations and regional automatic stations, the daily temperature data and precipitation data of regional automatic stations are converted into grid data according to the spatial interpolation processing and terrain correction processing methods;

[0010] S3. Calculation of low temperature, rainy and low sunshine meteorological disaster indicators

[0011] According to the grid data of step S2, if the daily precipitation is ≥ 0.1 mm, the daily average temperature is ≤ 20°C, and the duration is 5 days or more, and from the 6th day, there is a 2-day interval without precipitation, and the average sunshine hours of the process is ≤ 2 hours / day, it is a single-station low-temperature rainy and low-sun process;

[0012] S4. Risk assessment of low temperature, rainy and low-sun meteorological disasters

[0013] The risk assessment of low temperature, cloudy, rainy and low sunshine disasters includes three types of indicators to measure disaster-causing factors, namely, the annual duration of low temperature, cloudy, rainy and low sunshine processes, the average annual occurrence frequency, and the longest annual duration. The risk of low temperature, cloudy, rainy and low sunshine disasters in each region is evaluated based on the low temperature, cloudy, rainy and low sunshine disaster risk index;

[0014] S5. Evaluation of low temperature, rainy and low-sun disaster exposure

[0015] Draw and classify the 30″×30″ grid disaster-bearing body data to divide the distribution of various crop planting areas;

[0016] S6. Refined risk assessment model for low temperature, cloudy, rainy and low-sunlight disasters

[0017] According to the low temperature, cloudy, rainy and low sunshine disaster risk index obtained in step S4 and the distribution of various crop planting areas obtained in step S5, the low temperature, cloudy, rainy and low sunshine disaster risk level of crops in each crop planting area is divided;

[0018] S7. Evaluation effect test.

[0019] Furthermore, in S2, the spatial interpolation processing includes the spatial interpolation processing of the temperature data under the complex terrain, based on the daily meteorological data and geographic information data of the conventional meteorological observation station and the regional automatic station, through spline interpolation, according to the law of temperature change with altitude, and the correction model according to the terrain height is as follows:

[0020] tp=to-(Hp-Ho)×6 / 1000

[0021] Among them, to represents the temperature of the reference point o, tp represents the temperature of any point p near point o, Ho and Hp represent the altitudes corresponding to o and p respectively. According to this method, the station data is converted into grid data.

[0022] Furthermore, in S2, the spatial interpolation processing also includes spatial interpolation processing of precipitation data, and based on the daily meteorological data and geographic information data of conventional meteorological observation stations and regional automatic stations, the station data are converted into grid data according to the Kriging spatial interpolation method.

[0023] Furthermore, in S4, the calculation formula for the low temperature, rainy and low sunshine disaster risk index is as follows:

[0024]

[0025] Where:

[0026] H i ——hazard index of the ith type of low temperature, cloudy, rainy and low-sunlight disaster factor indicator;

[0027] a i ——weight coefficient of the i-th low temperature, cloudy, rainy and low-sun disaster factor;

[0028] k is the number of disaster-causing factors of low temperature, cloudy, rainy and low-sunlight disasters.

[0029] The beneficial effects of the technical solution are:

[0030] The present invention obtains a refined low-temperature, cloudy, rainy and low-light disaster assessment result by refining the meteorological data, identifying key indicators, risk assessment and inspection, which can provide a basis for the agricultural sector to carry out low-temperature, cloudy, rainy and low-light disaster prevention and mitigation work; the detection and assessment method of the present invention is simple to operate and has a wide range of applications; the assessment result of the present invention is precise and accurate, and can avoid the occurrence of large errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 A flow chart of a method for monitoring and evaluating low-temperature, rainy, and low-sun meteorological disasters according to the present invention;

[0032] Figure 2 This is a comparison chart of the average number of days with low temperature, rain and little sunshine and the cumulative number of days with autumn wind in the province from August 1 to September 10 every year from 1951 to 2021;

[0033] Figure 3 This is a comparison chart of the cumulative number of days with low temperature, rain and little sunshine and autumn rain in the province from September 1 to November 1 every year from 1951 to 2021; DETAILED DESCRIPTION

[0034] The present invention is further described in detail below in conjunction with the accompanying drawings and embodiments:

[0035] like Figure 1 As shown, a method for monitoring and evaluating low-temperature, rainy and low-sun meteorological disasters includes the following steps:

[0036] S1. Collection and preprocessing of meteorological data and geographic information data in the study area

[0037] Meteorological data and geographic information data were collected in the study area. Meteorological data included daily average temperature, cumulative precipitation from 08:00 to 08:00, and sunshine hours at conventional meteorological observation stations and regional automatic stations, and geographic information data included altitude. The precipitation and temperature data at the regional automatic stations were compared with the data from conventional observation stations at the same time to conduct quality control in terms of spatiotemporal consistency assessment and outlier correction.

[0038] S2. Build a refined meteorological data historical database

[0039] Based on the historical data of daily temperature, precipitation and sunshine hours from conventional meteorological observation stations and regional automatic stations, the daily station data are converted into grid data by spatial interpolation, terrain correction and other methods; the sunshine hours are refined.

[0040] Among them, the spatial interpolation processing includes the spatial interpolation processing of temperature data under complex terrain. According to the daily meteorological data and geographic information data of conventional meteorological observation stations and regional automatic stations, through spline interpolation, considering the law of temperature change with altitude, the formula corrected according to terrain height is as follows:

[0041] tp=to-(Hp-Ho)×6 / 1000 (1)

[0042] Among them, to represents the temperature of the reference point o, tp represents the temperature of any point p near point o, Ho and Hp represent the altitudes corresponding to o and p respectively. According to this method, the station data is converted into grid data.

[0043] Spatial interpolation processing also includes spatial interpolation processing of precipitation data. Based on the daily meteorological data and geographic information data of conventional meteorological observation stations and regional automatic stations, the station data are converted into grid data according to the Kriging spatial interpolation method.

[0044] S3. Calculation of low temperature, rainy and low sunshine meteorological disaster indicators

[0045] According to the grid data of step S2, if there is a period of daily precipitation ≥ 0.1 mm, daily average temperature ≤ 20°C, and the duration is 5 days or more, and from the 6th day, there is a 2-day interval without precipitation, and the average sunshine hours of the process are ≤ 2 hours / day, it is determined to be a single-station low-temperature, cloudy, rainy and little sunshine process; wherein, the first day that meets the determination conditions of the low-temperature, cloudy, rainy and little sunshine process is the start day of the low-temperature, cloudy, rainy and little sunshine process, and the last day that meets the determination conditions of the low-temperature, cloudy, rainy and little sunshine process is the end day of the low-temperature, cloudy, rainy and little sunshine process;

[0046] S4. Risk assessment of low temperature, rainy and low-sun meteorological disasters

[0047] The risk assessment of low temperature, cloudy, rainy and little sunshine disasters includes three types of indicators for measuring disaster-causing factors, namely, the annual duration of low temperature, cloudy, rainy and little sunshine processes, the average annual occurrence frequency, and the longest annual duration. The risk of low temperature, cloudy, rainy and little sunshine disasters in each region is evaluated based on the low temperature, cloudy, rainy and little sunshine disaster risk index; the calculation formula of the low temperature, cloudy, rainy and little sunshine disaster risk index is as follows:

[0048]

[0049] Where:

[0050] H i ——hazard index of the ith type of low temperature, cloudy, rainy and low-sunlight disaster factor indicator;

[0051] a i ——weight coefficient of the i-th low temperature, cloudy, rainy and low-sun disaster factor;

[0052] k——the number of disaster-causing factors of low temperature, cloudy, rainy and low-sunlight disasters;

[0053] The weight coefficient is obtained by expert scoring method or information entropy weight method;

[0054] S5. Evaluation of low temperature, rainy and low-sun disaster exposure

[0055] Draw and classify the 30″×30″ grid hazard-bearing body data of Guizhou Province issued by the National Risk Survey Office;

[0056] S6. Refined risk assessment model for low temperature, cloudy, rainy and low-sunlight disasters

[0057] According to the low temperature, cloudy, rainy and low sunshine disaster risk index obtained in step S4 and the distribution of various crop planting areas obtained in step S5, the low temperature, cloudy, rainy and low sunshine disaster risk level of crops in each crop planting area is divided;

[0058] S7, evaluation effect test, based on the actual low temperature, rainy and low-light disasters in the past to evaluate the effect of the detection and evaluation method of the present invention.

[0059] The present invention can obtain refined low-temperature, cloudy, rainy and low-light disaster assessment results by refining the meteorological data, identifying key indicators, risk assessment and inspection, and can provide a basis for the agricultural sector to carry out low-temperature, cloudy, rainy and low-light disaster prevention and mitigation work; the detection and assessment method of the present invention is simple to operate and has a wide range of applications; the assessment results of the present invention are precise and accurate, and can avoid the occurrence of large errors.

[0060] In this embodiment, Guizhou Province is taken as the evaluation and detection object. According to the distribution of the annual average number of days of low temperature, cloudy, rainy and little sunshine processes in Guizhou Province from 1978 to 2020 obtained by the low temperature, cloudy, rainy and little sunshine meteorological disaster index evaluation in step S03, it can be concluded that the areas with a larger annual average number of days of low temperature, cloudy, rainy and little sunshine processes are mainly concentrated in the central and western parts. The longest duration is in Dafang, reaching 121.3 days, followed by Xishui, Nayong and Kaiyang, with annual durations ranging from 94 to 99 days.

[0061] like Figure 2 It is a comparison chart of the average number of days with low temperature, rain, and little sunshine and the cumulative number of days with autumn wind in the province from August 1 to September 10 every year from 1951 to 2021, which is obtained according to the evaluation of the low temperature, rain, and little sunshine meteorological disaster index in step S03. Among them, the bar chart is the number of days with little sunshine during the autumn wind period, and the line chart is the cumulative number of days with autumn wind. The correlation in years with weak autumn wind is poor, but the time correlation coefficient between the cumulative annual number of days in years with strong autumn wind and the statistical value of the locally revised low temperature, rain, and little sunshine meteorological disaster index can reach 0.7. The locally revised low temperature, rain, and little sunshine meteorological disaster index can basically reflect the disastrous nature of low temperature, rain, and little sunshine in years of autumn wind disasters.

[0062] like Figure 3 It is a comparison chart of the number of days with low temperature, rain and little sunshine and the cumulative number of days with autumn rain in the province from September 1 to November 1 every year from 1951 to 2021, obtained according to the evaluation of the low temperature, rain and little sunshine meteorological disaster index in step S03. Among them, the bar chart represents the number of days with little sunshine during the autumn rain period, and the line chart represents the cumulative number of days with autumn rain. The correlation between the average annual cumulative number of days in the autumn rain index period in the province and the annual cumulative number of days of the locally revised low temperature, rain and little sunshine meteorological disaster index reaches 0.84. The locally revised low temperature, rain and little sunshine meteorological disaster index can basically reflect the disaster-causing nature of low temperature, rain and little sunshine in the autumn wind disaster year. Among them, the more serious autumn rain event occurred in 2020. The number of stations with low temperature, rain and little sunshine for more than 15 days in the province reached 63 stations, among which the number of days at Kaiyang, Wanshan and Dafang stations all exceeded 60 days, which were 63 days, 62 days and 60 days respectively. The three stations were all composed of about 5-6 cumulative low temperature, rain and little sunshine processes.

[0063] In addition, according to the refined risk assessment model of low temperature, cloudy and rainy with little sunshine disaster in step S6, the risk level zoning of low temperature disaster rice in Guizhou Province is obtained. The high-risk level is mainly in the central and northern parts of Anshun City, the central part of Qianxinan Prefecture, the central and eastern part of Qiannan Prefecture, the western and southeastern parts of Qiandongnan Prefecture, the western and eastern parts of Tongren City, and the southeastern part of Zunyi City. The low risk level is mainly distributed in most areas of Bijie City and Liupanshui City. S6, refined risk assessment model of low temperature, cloudy and rainy with little sunshine disaster.

[0064] In summary, this embodiment can accurately monitor and evaluate the distribution of wheat, corn and rice planting areas in Guizhou Province, as well as the risk classification of low temperature, cloudy, rainy and low-light meteorological disasters in each planting area, providing a more accurate basis for the agricultural department to carry out low temperature, cloudy, rainy and low-light disaster prevention and mitigation work.

[0065] The above is only an embodiment of the present invention, and the common knowledge such as the known specific technical solutions or characteristics in the solution is not described in detail here. It should be pointed out that for those skilled in the art, several modifications and improvements can be made without departing from the technical solution of the present invention, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A method for monitoring and evaluating low-temperature, rainy, and low-sun meteorological disasters, characterized in that: The following steps are involved: S1. Collection and preprocessing of meteorological data and geographic information data in the study area Meteorological data and geographic information data in the study area were collected, and the meteorological data of the regional automatic station were compared with the data of the conventional observation station at the same time to conduct quality control in terms of temporal and spatial consistency assessment and outlier correction; among them, the meteorological data included the daily average temperature, cumulative precipitation from 08:00 to 08:00, and sunshine hours data of the conventional meteorological observation station and the regional automatic station, and the geographic information data included the altitude; S2. Build a refined meteorological data historical database According to the meteorological data of conventional meteorological observation stations and regional automatic stations, the daily temperature data and precipitation data of regional automatic stations are converted into grid data according to the spatial interpolation processing and terrain correction processing methods; Spatial interpolation processing includes spatial interpolation processing of temperature data under complex terrain. According to the daily meteorological data and geographic information data of conventional meteorological observation stations and regional automatic stations, spline interpolation is performed, and according to the law of temperature change with altitude, the model is corrected according to the terrain height as follows: tp=to-(Hp-Ho)×6 / 1000; Among them, to represents the temperature of the reference point o, tp represents the temperature of any point p near point o, Ho and Hp represent the altitudes corresponding to o and p respectively. According to this method, the station data is converted into grid data; S3. Calculation of low temperature, rainy and low sunshine meteorological disaster indicators According to the grid data of step S2, if there is a period of daily precipitation ≥ 0.1 mm, daily average temperature ≤ 20 ℃, and the duration is 5 days or more, and from the 6th day, there is a 2-day interval without precipitation, and the average sunshine hours of the process is ≤ 2 hours / day, it is a single-station low-temperature rainy and low-sun process; S4. Risk assessment of low temperature, rainy and low-sun meteorological disasters The risk assessment of low temperature, cloudy, rainy and low sunshine disasters includes three types of indicators to measure disaster-causing factors, namely, the annual duration of low temperature, cloudy, rainy and low sunshine processes, the average annual occurrence frequency, and the longest annual duration. The risk of low temperature, cloudy, rainy and low sunshine disasters in each region is evaluated based on the low temperature, cloudy, rainy and low sunshine disaster risk index; S5. Evaluation of low temperature, rainy and low-sun disaster exposure Draw and classify the 30″×30″ grid disaster-bearing body data to divide the distribution of various crop planting areas; S6. Refined risk assessment model for low temperature, cloudy, rainy and low-sunlight disasters According to the low temperature, cloudy, rainy and low sunshine disaster risk index obtained in step S4 and the distribution of various crop planting areas obtained in step S5, the low temperature, cloudy, rainy and low sunshine disaster risk level of crops in each crop planting area is divided; S7. Evaluation effect test.

2. The method for monitoring and evaluating low-temperature, rainy, and low-sun meteorological disasters according to claim 1 is characterized by: In S2, the spatial interpolation processing also includes the spatial interpolation processing of precipitation data. According to the daily meteorological data and geographic information data of conventional meteorological observation stations and regional automatic stations, the station data are converted into grid data according to the Kriging spatial interpolation method.

3. The method for monitoring and evaluating low-temperature, rainy, and low-sun meteorological disasters according to claim 1 is characterized by: In S4, the calculation formula for the low temperature, rainy and low sunshine disaster risk index is as follows: Where: No. A hazard index of low temperature, cloudy, rainy and low-sunlight disaster factors; ——No. Weight coefficients of low temperature, cloudy, rainy and low-sunlight disaster factors; k ——The number of disaster-causing factors of low temperature, cloudy, rainy and low-sunlight disasters.

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