Meteorological high temperature early warning method, device, equipment, storage medium and program product
By dynamically generating target temperature thresholds and combining absolute and relative temperature weights, the problems of false alarms and missed alarms caused by fixed thresholds are solved, thereby improving the accuracy and sensitivity of high temperature warnings and adapting to the climate characteristics of different regions.
Patent Information
- Application Number
- CN202610067751.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-01-19
- Publication Date
- 2026-04-17
AI Technical Summary
Existing technologies use fixed temperature thresholds to determine false alarms and missed alarms caused by high ambient temperatures, which cannot adapt to the differences in abnormal high temperatures in different regions, and the early warning is inaccurate, especially in regions with high temperatures and cold regions throughout the year.
By acquiring historical maximum temperature data and absolute temperature thresholds for the target area, a relative temperature threshold is obtained through analysis. The weights of absolute and relative temperatures are determined by combining current temperature and historical data, and a target temperature threshold is dynamically generated. A weighted fusion method is then used for high temperature early warning.
Significantly reduce false alarm rates, improve the accuracy and sensitivity of early warnings, adapt to the climate characteristics of different regions, and ensure more accurate high temperature warnings in areas with consistently high temperatures and frigid regions.
Smart Images
Figure CN121884558A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of meteorological disaster early warning technology, specifically to meteorological high temperature early warning methods, devices, equipment, storage media, and program products. Background Technology
[0002] High ambient temperatures can easily disrupt the body's thermal balance, leading to heatstroke or even fatal heat exhaustion. High ambient temperatures can also cause industrial equipment malfunctions and reduce or even destroy crops. Therefore, monitoring high ambient temperatures is very important. When monitoring high ambient temperatures, it is necessary to define the high temperature threshold. Exceeding the high temperature threshold is considered to be a high temperature.
[0003] In related technologies, fixed temperature thresholds are typically used to determine environmental high temperatures. However, this method cannot adapt to the differences in abnormal high temperatures across different regions. In areas with consistently high temperatures (such as arid regions where summer temperatures can reach above 40°C), fixed thresholds (such as 35°C) are far below the local "abnormally high temperature" level, leading to frequent and unnecessary warnings. In cold or temperate regions, fixed thresholds (35°C) may be close to or exceed local historical high temperature extremes. Local residents have low tolerance for high temperatures, and the infrastructure for dealing with high temperatures is inadequate, resulting in failure to issue warnings (missed reports) or causing serious harm when the actual hazardous temperatures are reached. Summary of the Invention
[0004] This invention provides a meteorological high temperature early warning method, device, equipment, storage medium, and program product to solve the problem of failure to issue early warnings (missed reports) caused by using fixed temperature thresholds to judge high ambient temperatures in related technologies.
[0005] In a first aspect, the present invention provides a meteorological high-temperature early warning method, comprising: acquiring historical maximum temperature data and absolute temperature thresholds of a target area; analyzing the temperature critical value of the target area based on the historical maximum temperature data to obtain a relative temperature threshold; determining absolute temperature weights and relative temperature weights based on the current temperature of the target area, historical maximum temperature data, and absolute temperature thresholds; fusing the absolute temperature thresholds and relative temperature thresholds using the absolute temperature weights and relative temperature weights to obtain a target temperature threshold; judging the meteorological temperature of the target area using the target temperature thresholds; and issuing a high-temperature early warning based on the judgment result.
[0006] This invention acquires historical maximum temperature data and absolute temperature thresholds for a target area. Based on the historical maximum temperature data, it analyzes the temperature critical values of the target area to obtain relative temperature thresholds. Combined with the local climate background, the relative temperature thresholds more closely match the actual temperature thresholds of the region, avoiding the neglect of regional climate differences due to absolute thresholds. This invention determines absolute temperature weights and relative temperature weights based on the current temperature, historical maximum temperature data, and absolute temperature thresholds of the target area. Through dynamic weight allocation, it achieves a balance between absolute temperature sensitivity and relative local normal anomalies, making the weight allocation more accurate and flexible. This invention utilizes absolute temperature weights and relative temperature weights to fuse absolute temperature thresholds and relative temperature thresholds to obtain a target temperature threshold. Through weighted fusion, a target temperature threshold is generated, retaining the universality of absolute thresholds while incorporating the regional specificity of relative thresholds. This makes the results of judging the meteorological temperature of the target area using the target temperature threshold more accurate and more in line with reality. Compared with related technologies, this invention, by fusing absolute temperature thresholds and relative temperature thresholds, dynamically generates a target temperature threshold applicable to the target area, significantly reducing false alarms in perennially high-temperature areas and improving the warning sensitivity in cold / temperate regions.
[0007] In one optional implementation, the temperature threshold of the target area is analyzed based on historical maximum temperature data to obtain a relative temperature threshold, including: determining the mean and standard deviation of the maximum temperature based on historical maximum temperature data; and determining the relative temperature threshold based on the mean and standard deviation of the maximum temperature and according to the inverse function of the normal distribution of the preset cumulative probability.
[0008] In one optional implementation, the absolute temperature weight and relative temperature weight are determined based on the current temperature of the target area, historical maximum temperature data, and an absolute temperature threshold. This includes: obtaining a first absolute difference based on the absolute value of the difference between the current temperature and the absolute temperature threshold; obtaining a first negative value based on the negative of the product of the first absolute difference and a preset adjustment factor, and obtaining a first exponential value raised to the power of the first negative value of an exponential function; obtaining a second absolute difference based on the absolute value of the difference between each temperature sample in the historical maximum temperature data and the absolute temperature threshold; obtaining a second negative value based on the negative of the product of the second absolute difference and a preset adjustment factor, and obtaining a second exponential value corresponding to each temperature sample raised to the power of the second negative value of an exponential function; summing the second exponential values corresponding to multiple temperature samples to obtain a summation result; obtaining the absolute temperature weight based on the quotient of the second exponential value and the summation result; and obtaining the relative temperature weight based on the difference between 1 and the absolute temperature threshold.
[0009] In one optional implementation, the absolute temperature threshold and the relative temperature threshold are fused using absolute temperature weights and relative temperature weights to obtain the target temperature threshold, including: obtaining a first product result based on the product of the absolute temperature weights and the absolute temperature thresholds. The second product result is obtained by multiplying the relative temperature weights by the relative temperature weights; the target temperature threshold is obtained by summing the first product result and the second product result.
[0010] In one optional implementation, the meteorological temperature of the target area is determined using a target temperature threshold, and a high-temperature warning is issued based on the determination result. This includes determining whether the highest meteorological temperature of each day within a preset time period is greater than or equal to the target temperature threshold. If the highest meteorological temperature of each day within the preset time period is greater than or equal to the target temperature threshold for each day, a sustained high-temperature event is determined to have occurred, and a high-temperature warning is issued.
[0011] This invention introduces a mechanism for determining the number of consecutive days exceeding a threshold to accurately identify heat wave events that meet the criteria for the number of consecutive days, thereby avoiding an overreaction to isolated high-temperature days.
[0012] In one optional implementation, the meteorological high temperature warning method further includes: when the current temperature cannot be obtained, analyzing the temperature data of the target meteorological station based on the real-time temperature data of surrounding meteorological stations to obtain a first target temperature; obtaining a second target temperature based on the average of the historical temperature data of the target meteorological station for the same period; obtaining a first weighting coefficient and a second weighting coefficient, and using the first weighting coefficient and the second weighting coefficient to fuse the first target temperature and the second target temperature to obtain the current temperature.
[0013] This invention can provide more reliable temperature estimates when a site fails, thereby improving the accuracy of daily and persistent temperature determinations, especially in heat wave events with strong spatial heterogeneity.
[0014] Secondly, the present invention provides a meteorological high-temperature early warning device, comprising: a relative threshold determination module, used to acquire historical maximum temperature data and absolute temperature thresholds of a target area, and analyze the temperature critical value of the target area based on the historical maximum temperature data to obtain a relative temperature threshold; a weight determination module, used to determine absolute temperature weights and relative temperature weights based on the current temperature of the target area, historical maximum temperature data, and absolute temperature thresholds; a threshold fusion module, used to fuse the absolute temperature thresholds and relative temperature thresholds using the absolute temperature weights and relative temperature weights to obtain a target temperature threshold; and a high-temperature early warning module, used to judge the meteorological temperature of the target area using the target temperature thresholds, and issue a high-temperature early warning based on the judgment result.
[0015] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the meteorological high temperature early warning method of the first aspect or any corresponding embodiment described above.
[0016] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the meteorological high-temperature early warning method of the first aspect or any corresponding embodiment thereof.
[0017] Fifthly, the present invention provides a computer program product, including computer instructions, which are used to cause a computer to execute the meteorological high temperature early warning method described in the first aspect or any corresponding embodiment. Attached Figure Description
[0018] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.
[0019] Figure 1 This is a schematic diagram of an application scenario according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the first type of meteorological high temperature early warning method according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the second process of the meteorological high temperature early warning method according to an embodiment of the present invention; Figure 4 This is a structural block diagram of a high-temperature weather warning device according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation
[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0021] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.
[0022] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.
[0023] As an optional application scenario of this invention, such as Figure 1 As shown, the high-temperature weather warning system may include at least one terminal device and at least one server. Figure 1 The system is illustrated in the example, which includes a computer 101, a mobile terminal 102, and a server 103, and the terminal devices such as the computer 101 and the mobile terminal 102 are connected to the server 103 through a network 110.
[0024] Specifically, the terminal device can be a smartphone, tablet, laptop, PDA, desktop computer, game console, smart TV, smart wearable device, in-vehicle terminal, VR (Virtual Reality) device, AR (Augmented Reality) device, etc. Server 103 can be a standalone physical server, a server cluster, a distributed system, or a cloud server providing cloud services. Network 110 can be a wired or wireless network, examples of which include, but are not limited to, the Internet, corporate intranet, local area network, wide area network, mobile communication network, and combinations thereof.
[0025] The hazards of high temperatures depend not only on absolute temperature (e.g., ≥35℃ poses a significant risk to human health), but also on the degree of deviation (abnormality) of temperature relative to local historical norms and the number of consecutive days. Effective early warning requires a comprehensive consideration of these three factors. In related technologies, most high-temperature warning systems use fixed temperature thresholds (e.g., a uniform setting of 35℃). A single fixed threshold cannot adapt to the different definitions of "abnormally high temperatures" in different regions, leading to a series of problems: In areas with consistently high temperatures (e.g., arid regions where summer temperatures can reach above 40℃), the fixed threshold (e.g., 35℃) is far below the local "abnormally high temperature" level, resulting in frequent and unnecessary warnings (false alarms). In cold or temperate regions, the fixed threshold (35℃) may be close to or exceed the local historical high-temperature extremes. Local residents have low tolerance to high temperatures, and the infrastructure for dealing with high temperatures is inadequate, resulting in failure to issue warnings (missed warnings) or causing serious harm when the actual hazardous temperature is reached. Heatwave hazards require the condition of "high temperatures lasting for many days," but traditional technologies mostly only detect single-day exceedances of the threshold, failing to quantify the cumulative effect. Some meteorological stations have high failure rates and are difficult to maintain (e.g., in mountainous areas), leading to missing data. Traditional interpolation methods are not well adapted to thermal events with strong spatial heterogeneity, and they do not effectively combine stable historical climate information to compensate for the lack of information, resulting in large errors and affecting the accuracy of determining single-day high temperatures and persistent heat waves.
[0026] This invention provides a method for issuing high-temperature weather warnings. By fusing relative temperature thresholds, the target temperature thresholds are made more accurate and better reflect the temperature conditions of the target area, thereby improving the accuracy of high-temperature warnings.
[0027] According to an embodiment of the present invention, a method for issuing a high-temperature weather warning is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.
[0028] This embodiment provides a method for issuing a high-temperature weather warning, which can be used in computer equipment. Figure 2 This is a first flowchart of a meteorological high-temperature early warning method according to an embodiment of the present invention, as follows: Figure 2 As shown, the process includes the following steps: Step S201: Obtain the historical maximum temperature data and absolute temperature threshold of the target area, and analyze the temperature critical value of the target area based on the historical maximum temperature data to obtain the relative temperature threshold.
[0029] The target area is the region where meteorological high temperature assessment is required; the historical maximum temperature data can be the daily maximum temperature data of the same period in the past 30 years (such as summer June to August). The historical maximum temperature data is cleaned (obvious outliers are removed), and the temperature critical value of the target area is analyzed based on the cleaned historical maximum temperature data.
[0030] In some optional implementations, the absolute temperature threshold is a fixed temperature threshold set according to the safe operating limits of the equipment or a recognized critical value for health risks. It can be set according to the actual situation. For example, the absolute temperature threshold can be 35°C. When the human body is exposed to an environment greater than or equal to 35°C, the risk of heatstroke increases dramatically. Therefore, the absolute temperature threshold can be set to 35°C. The absolute temperature threshold is suitable for seasonal high-temperature areas such as temperate and cold zones, because the average daily temperature in summer is often below 30°C. 35°C has significant extreme characterization significance.
[0031] In some optional implementations, the temperature threshold of the target area is analyzed based on historical maximum temperature data to obtain a relative temperature threshold, including: arranging multiple data samples in the historical maximum temperature data in ascending order, and taking the value at the 90th percentile as the relative temperature threshold.
[0032] Step S202: Determine the absolute temperature weight and relative temperature weight based on the current temperature of the target area, historical maximum temperature data, and absolute temperature threshold.
[0033] In some alternative implementations, when the current temperature can be obtained directly, it can be obtained directly from the target weather station.
[0034] In some optional implementations, when the current temperature cannot be obtained, the temperature data of the target weather station is analyzed based on the real-time temperature data of surrounding weather stations to obtain a first target temperature; a second target temperature is obtained based on the average of the historical temperature data of the target weather station for the same period; a first weighting coefficient and a second weighting coefficient are obtained, and the first target temperature and the second target temperature are fused using the first weighting coefficient and the second weighting coefficient to obtain the current temperature.
[0035] When data from the target weather station is missing, and the current temperature cannot be directly obtained from the target weather station, the Kriging interpolation method is used to estimate the first target temperature based on the real-time temperature data of surrounding weather stations that are operating normally, in order to capture the real-time spatial distribution. The long-term (e.g., 30-year) average daily maximum temperature of the target weather station for the same period (same month and day) is used as the second target temperature to characterize the climate background value. Through historical data analysis and fitting, the first weighting coefficient and the second weighting coefficient are obtained, and the sum of the first weighting coefficient and the second weighting coefficient is 1. The first target temperature and the second target temperature are fused based on the first weighting coefficient and the second weighting coefficient to obtain the current temperature.
[0036] For example, the formula for determining the current temperature is:
[0037] in, The current temperature. As the first weighting coefficient, The first target temperature, This is the second weighting coefficient. This is the second target temperature.
[0038] In this embodiment of the invention, real-time interpolation and historical climate averages are combined to improve the accuracy of the current temperature when measurements are missing, making it suitable for scenarios with strong spatial heterogeneity, such as heat waves.
[0039] Step S203: Using absolute temperature weight and relative temperature weight, the absolute temperature threshold and relative temperature threshold are fused to obtain the target temperature threshold.
[0040] The target temperature threshold is obtained by weighting the absolute temperature threshold and the relative temperature threshold.
[0041] Step S204: Use the target temperature threshold to determine the meteorological temperature of the target area, and issue a high temperature warning based on the determination result.
[0042] In some optional implementations, when the meteorological temperature of the target area is greater than or equal to the target temperature threshold, the result is determined to be a high-temperature event, and a high-temperature warning is issued.
[0043] The high-temperature early warning method provided in this embodiment acquires historical maximum temperature data and absolute temperature thresholds for the target area. Based on the historical maximum temperature data, it analyzes the temperature critical values of the target area to obtain a relative temperature threshold. Combined with the local climate background, the relative temperature threshold is made more closely aligned with the actual temperature thresholds of the region, avoiding the neglect of regional climate differences due to absolute thresholds. This embodiment determines absolute temperature weights and relative temperature weights based on the current temperature, historical maximum temperature data, and absolute temperature thresholds of the target area. Through dynamic weight allocation, a balance is achieved between absolute temperature sensitivity and relative local anomalies, making the weight allocation more accurate and flexible. This embodiment utilizes absolute temperature weights and relative temperature weights to fuse absolute temperature thresholds and relative temperature thresholds to obtain a target temperature threshold. Through weighted fusion, a target temperature threshold is generated, retaining the universality of absolute thresholds while incorporating the regional specificity of relative thresholds. This makes the results of judging the meteorological temperature of the target area using the target temperature threshold more accurate and more consistent with reality. Compared with related technologies, this embodiment, by fusing absolute temperature thresholds and relative temperature thresholds, dynamically generates a target temperature threshold applicable to the target area, significantly reducing false alarms in perennially high-temperature areas and improving the early warning sensitivity in cold / temperate regions.
[0044] This embodiment provides a method for issuing a high-temperature weather warning, which can be used in computer equipment. Figure 3 This is a second flowchart of the meteorological high-temperature early warning method according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps: Step S301: Obtain the historical maximum temperature data and absolute temperature threshold of the target area, and analyze the temperature critical value of the target area based on the historical maximum temperature data to obtain the relative temperature threshold.
[0045] Specifically, step S302 includes: Step S3011: Determine the mean and standard deviation of the maximum temperature based on historical maximum temperature data.
[0046] Step S3012: Based on the average maximum temperature and the standard deviation of the maximum temperature, determine the relative temperature threshold according to the inverse function of the normal distribution of the preset cumulative probability.
[0047] The preset cumulative probability can be 90%. For example, the formula for determining the relative temperature threshold can be:
[0048] in, This is a relative temperature threshold. The average of the highest temperatures. The standard deviation of the highest temperature. It is the inverse function of the normal distribution.
[0049] In some alternative implementations, when the historical maximum temperature data approximately follows a normal distribution, the mean and standard deviation of the historical maximum temperature data are calculated, and the temperature critical value corresponding to a 90% probability is calculated using the inverse function of the normal distribution as a relative temperature threshold.
[0050] For example, in location A ℃, ℃, then the relative temperature threshold is: = ℃ In this embodiment of the invention, the relative temperature threshold is dynamically generated based on regional climate differences, reflecting a dynamic benchmark value that reflects the climate characteristics of a specific region. It represents the upper limit of the typical summer high temperature level in the region (such as the 90th percentile) relative to the starting point of the local historical "abnormal high temperature".
[0051] Step S302: Determine the absolute temperature weight and relative temperature weight based on the current temperature of the target area, historical maximum temperature data, and absolute temperature threshold.
[0052] Specifically, step S302 includes: Step S3021: Obtain the first absolute difference based on the absolute value of the difference between the current temperature and the absolute temperature threshold; obtain the first negative value based on the negative number of the product of the first absolute difference and the preset adjustment factor; and obtain the first exponential value based on the first negative power of the exponential function.
[0053] Step S3022: Obtain the second absolute difference based on the absolute value of the difference between each temperature sample in the historical highest temperature data and the absolute temperature threshold; obtain the second negative value based on the negative number of the product of the second absolute difference and the preset adjustment factor; and obtain the second exponential value corresponding to each temperature sample based on the second negative power of the exponential function.
[0054] Step S3023: Summate the second index values corresponding to multiple temperature samples to obtain the summation result. Obtain the absolute temperature weight based on the quotient of the second index value and the summation result.
[0055] For example, the formula for determining the absolute temperature weight is:
[0056] in, Weighted by absolute temperature As an adjustment factor, it can be 0.5. The current temperature. The absolute temperature threshold. The highest temperature in history Temperature samples.
[0057] In this embodiment of the invention, according to the above formula, if the current temperature Very close (e.g. |) |<1℃), indicating that the temperature is within the highly sensitive range of the absolute threshold. At this time, The information provided is of higher value (lower uncertainty) and should be given [reward / granted ... Higher weight (increase) If the current temperature keep away (e.g., arid regions) = 40℃), but significantly higher than the local relative temperature threshold. (For example, location B) =41.2°C), indicating that although the temperature is high, it is likely still within the upper limit of the "normal" range for the local area. At this point, the relative threshold... It can better reflect whether it is abnormal relative to the local norm and should be given Higher weight (increase) value).
[0058] Step S3024: Obtain the relative temperature weight based on the difference between 1 and the absolute temperature threshold.
[0059] For example, the formula for determining the relative temperature weight is:
[0060] in, As a relative temperature weight, The absolute temperature weighting is used.
[0061] Step S303: Using absolute temperature weight and relative temperature weight, the absolute temperature threshold and relative temperature threshold are fused to obtain the target temperature threshold.
[0062] Specifically, step S303 includes: Step S3031: Obtain the first product result based on the product of the absolute temperature weight and the absolute temperature threshold.
[0063] Step S3032: Obtain the second product result based on the product of the relative temperature weight and the relative temperature weight.
[0064] Step S3033: Obtain the target temperature threshold by summing the first product result and the second product result.
[0065] For example, the formula for determining the target temperature threshold is:
[0066] in, The target temperature threshold, As a relative temperature weight, Weighted by absolute temperature The absolute temperature threshold. This represents the relative temperature threshold.
[0067] For example, on a certain day in location B ℃, ℃, ℃, , ,but ℃, only when Only when the temperature reaches 40℃ (close to the local normal) will the daily high temperature judgment be triggered, which avoids alarming when the temperature reaches 40℃ (close to the local normal).
[0068] For example, on a certain day in location C ℃, ℃, ℃, , ,but ℃, only when A single-day high temperature determination is only triggered when the temperature reaches ℃, because The temperature reached ℃, thus triggering a single-day high-temperature determination.
[0069] Step S304: Use the target temperature threshold to determine the meteorological temperature of the target area, and issue a high temperature warning based on the determination result.
[0070] Specifically, step S304 includes: Step S3041: Determine whether the highest meteorological temperature of each day within the preset time period is greater than or equal to the target temperature threshold; if the highest meteorological temperature of each day within the preset time period is greater than or equal to the target temperature threshold for each day, then determine that a continuous high temperature event has occurred, and issue a high temperature warning.
[0071] For example, a sliding window counting method is used to mark heat wave events. Based on daily meteorological temperature data of a certain station / location, a fixed-length sliding window (e.g., 6 days) is defined, and this window is moved forward day by day starting from the first day of the time series. Statistics are then collected within the current window (e.g., the first...). i Heaven to the Di i (+5 days) Check if the daily meteorological temperature is greater than or equal to the target temperature threshold for that day / location. If the temperature for all consecutive N days (e.g., 6 days) within the window is greater than or equal to the target temperature threshold for that day / location, then mark the date range covered by the window as having experienced a sustained high-temperature event (heat wave).
[0072] The high-temperature weather warning method provided in this embodiment dynamically weights absolute and relative temperature thresholds. The weighting parameters are adaptively adjusted based on real-time observed temperature / historical observation temperature for the same period, reducing the false alarm rate and resolving the systematic bias caused by climate differences in related technologies. This embodiment of the invention is based on a sliding window counting algorithm to detect in real time the frequency of grid temperatures exceeding dynamic thresholds within N consecutive days (e.g., 6 days), accurately marking persistent heat wave events and quantifying the cumulative destructive intensity of heat waves.
[0073] This embodiment also provides a high-temperature weather warning device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.
[0074] This embodiment provides a meteorological high-temperature early warning device, such as... Figure 4 As shown, it includes: The relative threshold determination module 401 is used to obtain the historical maximum temperature data and absolute temperature threshold of the target area, and to analyze the temperature critical value of the target area based on the historical maximum temperature data to obtain the relative temperature threshold.
[0075] The weight determination module 402 is used to determine the absolute temperature weight and relative temperature weight based on the current temperature of the target area, the historical highest temperature data, and the absolute temperature threshold.
[0076] The threshold fusion module 403 is used to fuse the absolute temperature threshold and the relative temperature threshold using absolute temperature weight and relative temperature weight to obtain the target temperature threshold.
[0077] The high temperature warning module 404 is used to determine the meteorological temperature of the target area using the target temperature threshold and issue a high temperature warning based on the determination result.
[0078] In some alternative implementations, the relative threshold determination module 401 includes: The temperature data determination unit is used to determine the mean and standard deviation of the maximum temperature based on historical maximum temperature data.
[0079] The relative threshold determination unit is used to determine the relative temperature threshold based on the average maximum temperature and the standard deviation of the maximum temperature, according to the inverse function of the normal distribution of the preset cumulative probability.
[0080] In some alternative implementations, the weight determination module 402 includes: The first exponent value determination unit is used to obtain a first absolute difference based on the absolute value of the difference between the current temperature and the absolute temperature threshold; to obtain a first negative value based on the negative number of the product of the first absolute difference and a preset adjustment factor; and to obtain a first exponent value based on the first negative power of the exponent function.
[0081] The second exponent value determination unit is used to obtain the second absolute difference based on the absolute value of the difference between each temperature sample in the historical highest temperature data and the absolute temperature threshold; to obtain the second negative value based on the negative number of the product of the second absolute difference and the preset adjustment factor; and to obtain the second exponent value corresponding to each temperature sample based on the second negative power of the exponent function.
[0082] The absolute weight determination unit is used to sum the second exponent values corresponding to multiple temperature samples to obtain the summation result. The absolute temperature weight is obtained based on the quotient of the second exponent value and the summation result.
[0083] The relative weight determination unit is used to obtain the relative temperature weight based on the difference between 1 and the absolute temperature threshold.
[0084] In some alternative implementations, the threshold fusion module 403 includes: The first product unit is used to obtain the first product result based on the product of the absolute temperature weight and the absolute temperature threshold.
[0085] The second product unit is used to obtain the second product result based on the product of the relative temperature weights.
[0086] The threshold fusion unit is used to obtain the target temperature threshold based on the sum of the first product result and the second product result.
[0087] In some alternative implementations, the high-temperature warning module 404 includes: The high temperature warning unit is used to determine whether the highest meteorological temperature of each day within a preset time period is greater than or equal to the target temperature threshold. If the highest meteorological temperature of each day within the preset time period is greater than or equal to the corresponding target temperature threshold, it is determined that a continuous high temperature event has occurred, and a high temperature warning is issued.
[0088] In some optional implementations, the high-temperature weather warning device also includes: The first target temperature determination module is used to analyze the temperature data of the target weather station based on the real-time temperature data of the surrounding weather stations when the current temperature cannot be obtained, and obtain the first target temperature.
[0089] The second target temperature determination module is used to obtain the second target temperature based on the average historical temperature data of the target meteorological station for the same period.
[0090] The current temperature determination module is used to obtain the first weighting coefficient and the second weighting coefficient, and to fuse the first target temperature and the second target temperature using the first weighting coefficient and the second weighting coefficient to obtain the current temperature.
[0091] The high-temperature weather warning device provided in this embodiment of the invention can execute the high-temperature weather warning method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method. Further functional descriptions of the various modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.
[0092] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.
[0093] The following is a detailed reference. Figure 5 The diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 501, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 502 or a program loaded from memory 508 into random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of the electronic device. The processor 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.
[0094] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 508 including, for example, magnetic tapes, hard disks, etc.; and communication devices 509. Communication device 509 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 5 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.
[0095] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a memory 508, or installed from a ROM 502. When the computer program is executed by the processor 501, it performs the functions defined in the meteorological high-temperature early warning method of the embodiments of the present invention.
[0096] Figure 5 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.
[0097] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the high-temperature weather warning method shown in the above embodiments is implemented.
[0098] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.
[0099] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.
Claims
1. A method for issuing a high-temperature weather warning, characterized in that, The method includes: Obtain historical maximum temperature data and absolute temperature thresholds for the target area; analyze the temperature critical values of the target area based on the historical maximum temperature data to obtain relative temperature thresholds; The absolute temperature weight and relative temperature weight are determined based on the current temperature of the target area, the historical highest temperature data, and the absolute temperature threshold. The absolute temperature threshold and the relative temperature threshold are fused using the absolute temperature weight and the relative temperature weight to obtain the target temperature threshold; The meteorological temperature of the target area is determined using the target temperature threshold, and a high temperature warning is issued based on the determination result.
2. The method according to claim 1, characterized in that, The step of analyzing the temperature threshold of the target area based on the historical highest temperature data to obtain a relative temperature threshold includes: Based on the historical maximum temperature data, determine the mean and standard deviation of the maximum temperature; Based on the mean of the highest temperature and the standard deviation of the highest temperature, the relative temperature threshold is determined according to the inverse function of the normal distribution of the preset cumulative probability.
3. The method according to claim 1 or 2, characterized in that, The step of determining the absolute temperature weight and relative temperature weight based on the current temperature of the target area, the historical highest temperature data, and the absolute temperature threshold includes: The first absolute difference is obtained based on the absolute value of the difference between the current temperature and the absolute temperature threshold. The first negative value is obtained by taking the negative of the product of the first absolute difference and the preset adjustment factor, and the first exponential value is obtained by raising the first negative value to the power of the exponential function. The second absolute difference is obtained by taking the absolute value of the difference between each temperature sample in the historical highest temperature data and the absolute temperature threshold. The second negative value is obtained by multiplying the second absolute difference by the preset adjustment factor, and the second exponential value corresponding to each temperature sample is obtained by raising the second negative value to the power of the exponential function. The second index values corresponding to multiple temperature samples are summed to obtain a summation result. The absolute temperature weight is obtained based on the quotient of the second index value and the summation result. The relative temperature weight is obtained based on the difference between 1 and the absolute temperature threshold.
4. The method according to claim 1 or 2, characterized in that, The step of fusing the absolute temperature threshold and the relative temperature threshold using the absolute temperature weight and the relative temperature weight to obtain the target temperature threshold includes: The first product result is obtained by multiplying the absolute temperature weight by the absolute temperature threshold. The second product result is obtained by multiplying the relative temperature weight by the relative temperature weight; The target temperature threshold is obtained by summing the first product result and the second product result.
5. The method according to claim 1 or 2, characterized in that, The step of determining the meteorological temperature of the target area using the target temperature threshold and issuing a high-temperature warning based on the determination result includes: Determine whether the highest meteorological temperature of each day within a preset time period is greater than or equal to the target temperature threshold. If the highest meteorological temperature of each day within the preset time period is greater than or equal to the target temperature threshold for each day, then determine that a sustained high temperature event has occurred and issue a high temperature warning.
6. The method according to claim 1 or 2, characterized in that, The method further includes: When the current temperature cannot be obtained, the temperature data of the target weather station is analyzed based on the real-time temperature data of the surrounding weather stations to obtain the first target temperature; The second target temperature is obtained based on the average historical temperature data of the target meteorological station for the same period. Obtain a first weighting coefficient and a second weighting coefficient, and use the first weighting coefficient and the second weighting coefficient to fuse the first target temperature and the second target temperature to obtain the current temperature.
7. A meteorological high-temperature early warning device, characterized in that, The device includes: The relative threshold determination module is used to acquire historical maximum temperature data and absolute temperature thresholds for the target area, and analyze the temperature critical value of the target area based on the historical maximum temperature data to obtain the relative temperature threshold. The weight determination module is used to determine the absolute temperature weight and the relative temperature weight based on the current temperature of the target area, the historical highest temperature data, and the absolute temperature threshold. The threshold fusion module is used to fuse the absolute temperature threshold and the relative temperature threshold using the absolute temperature weight and the relative temperature weight to obtain the target temperature threshold; The high temperature warning module is used to determine the meteorological temperature of the target area using the target temperature threshold, and to issue a high temperature warning based on the determination result.
8. An electronic device, characterized in that, include: The system includes a memory and a processor, which are interconnected and the memory stores computer instructions. The processor executes the computer instructions to perform the high-temperature weather warning method according to any one of claims 1 to 6.
9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the meteorological high-temperature early warning method according to any one of claims 1 to 6.
10. A computer program product, characterized in that, It includes computer instructions, which are used to cause a computer to execute the meteorological high temperature early warning method according to any one of claims 1 to 6.