CN111598342A - Weather forecasting method and device, computer equipment and storage medium - Google Patents
Weather forecasting method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The application discloses a weather forecasting method, a weather forecasting device, computer equipment and a storage medium, and relates to the technical field of environment monitoring. The weather forecasting method comprises the steps of acquiring the number of mobile terminals accessed to a communication network in a target area within a target time period for the target area to be subjected to weather forecasting; determining a general population in a target area in a target time period according to the number of the mobile terminals; calculating the human metabolic emission heat in the target area in the target time period according to the general population; the artificial heat of the target area in the target time period is determined according to the heat discharged by the human metabolism, and the weather forecast is carried out on the target area according to the artificial heat, wherein the artificial heat of the target area is the heat brought by human activities. In the embodiment of the application, the weather forecast is carried out on the target area according to the artificial heat of the target area, and the influence of human activities on the natural climate is considered in the process of weather forecast, so that the weather forecast result is more accurate.
Description
Technical Field
The present application relates to the field of environmental monitoring technologies, and in particular, to a weather forecasting method, an apparatus, a computer device, and a storage medium.
Background
Weather conditions are closely related to people's lives, and in order to better perform productive activities, it is very important to accurately forecast weather conditions of a certain place in a certain period of time in the future.
The numerical Weather Forecasting Model WRF (English: Weather Research and Forecasting Model, Chinese: Weather Research and Forecasting Model) is a Model for Forecasting future Weather conditions based on the current atmospheric conditions. In general, the process of weather forecasting using the WRF model is: inputting the current atmospheric parameters, and performing data processing on the current atmospheric parameters to obtain the estimated atmospheric parameters of the future weather.
In practical applications, the influence of human activities on the natural climate is generally ignored in the WRF model, however, the influence of human activities on the natural climate is increasingly large, and the way of directly ignoring the influence of human activities on the natural climate may result in low accuracy of weather forecast.
Disclosure of Invention
In view of the above, it is necessary to provide a weather forecasting method, a weather forecasting apparatus, a computer device, and a storage medium for solving the problem of low accuracy of weather forecasting.
A method of weather forecasting, the method comprising:
acquiring the number of mobile terminals accessed to a communication network in a target area within a target time period for the target area to be subjected to weather prediction;
determining a general population in a target area in a target time period according to the number of the mobile terminals;
calculating the human metabolic emission heat in the target area in the target time period according to the general population;
the artificial heat of the target area in the target time period is determined according to the heat discharged by the human metabolism, and the weather forecast is carried out on the target area according to the artificial heat, wherein the artificial heat of the target area is the heat brought by human activities.
In one embodiment, determining the population of the population in the target area within the target time period based on the number of mobile terminals comprises:
taking the number of the mobile terminals as the number of the population using the mobile terminals in the target area in the target time period;
acquiring the proportional relation between the population number of the used mobile terminal and the population number of the unused mobile terminal in the target area;
and determining the total population in the target area according to the population number and the proportional relation of the mobile terminal used in the target area in the target time period.
In one embodiment, determining artificial heat for a target area within a target time period based on human metabolic emission heat includes:
acquiring heat emission quantities of a plurality of target industries in a target area in a target time period, wherein the target industries comprise at least one of industrial industry, building industry, electric power industry and traffic industry;
and summing the heat discharged by human metabolism and the heat discharged by a plurality of target industries, and taking the summation result as artificial heat of a target area in a target time period.
In one embodiment, obtaining heat emissions of a plurality of target industries within a target area over a target time period comprises:
acquiring the total heat emission amount of each target industry in a target area within a preset time period, wherein the preset time period comprises a plurality of time periods;
acquiring the heat emission proportion of each target industry in different time periods within a preset time period;
determining the heat emission proportion corresponding to each target industry in the target time period according to the heat emission proportion of each target industry in different time periods;
and determining the heat emission amount of the plurality of target industries in the target area in the target time period according to the total heat emission amount of each target industry and the heat emission proportion of each target industry in the target time period.
In one embodiment, obtaining the heat emission proportion of each target industry in different time periods within a preset time period comprises:
acquiring the distribution proportion of pollutant discharge amount of each target industry of a target area in different time periods within a preset time period;
and determining the corresponding thermal emission proportions of the target industries in different time periods according to the distribution proportions of the pollutant emission quantities of the target industries in different time periods in a preset time period.
In one embodiment, obtaining a total amount of heat emissions for each target industry within the target area over a preset time period comprises:
acquiring the historical heat emission total amount of each target industry from the energy statistics yearbook in the target area;
and determining the total heat emission amount of each target industry in a preset time period according to the historical total heat emission amount of each target industry.
In one embodiment, calculating the metabolic emissions heat of humans in a target area within a target time period based on a population of humans includes:
acquiring human activity power of different time periods in a preset time period;
determining human activity power for a target time period according to the human activity power for different time periods;
and determining the human metabolic emission heat in the target area in the target time period according to the general population and the human activity power of the target time period.
A weather forecasting apparatus, the apparatus comprising:
the acquisition module is used for acquiring the number of mobile terminals accessed to a communication network in a target area within a target time period for the target area to be subjected to weather prediction;
the population determining module is used for determining the general population in the target area in the target time period according to the number of the mobile terminals;
the metabolism determining module is used for calculating the human metabolism emission heat in the target area in the target time period according to the general population;
the weather forecast module is used for determining artificial heat of the target area in the target time period according to the heat discharged by the metabolism of human beings and conducting weather forecast on the target area according to the artificial heat, wherein the artificial heat of the target area is heat brought by human activities.
A computer device comprising a memory and a processor, the memory storing a computer program that when executed by the processor performs the steps of:
acquiring the number of mobile terminals accessed to a communication network in a target area within a target time period for the target area to be subjected to weather prediction;
determining a general population in a target area in a target time period according to the number of the mobile terminals;
calculating the human metabolic emission heat in the target area in the target time period according to the general population;
the artificial heat of the target area in the target time period is determined according to the heat discharged by the human metabolism, and the weather forecast is carried out on the target area according to the artificial heat, wherein the artificial heat of the target area is the heat brought by human activities.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring the number of mobile terminals accessed to a communication network in a target area within a target time period for the target area to be subjected to weather prediction;
determining a general population in a target area in a target time period according to the number of the mobile terminals;
calculating the human metabolic emission heat in the target area in the target time period according to the general population;
the artificial heat of the target area in the target time period is determined according to the heat discharged by the human metabolism, and the weather forecast is carried out on the target area according to the artificial heat, wherein the artificial heat of the target area is the heat brought by human activities.
The beneficial effects brought by the technical scheme provided by the embodiment of the application at least comprise:
the weather forecast method, the weather forecast device, the computer equipment and the storage medium can provide the accuracy of the weather forecast. In the weather forecasting method, the computer equipment can acquire the number of mobile terminals accessed to a communication network in a target area within a target time period for the target area to be subjected to weather forecasting; determining a general population in a target area in a target time period according to the number of the mobile terminals; calculating the human metabolic emission heat in the target area in the target time period according to the general population; the artificial heat of the target area in the target time period is determined according to the heat discharged by the human metabolism, and the weather forecast is carried out on the target area according to the artificial heat, wherein the artificial heat of the target area is the heat brought by human activities. In the embodiment of the application, the weather forecast is carried out on the target area according to the artificial heat of the target area, and the influence of human activities on the natural climate is considered in the process of weather forecast, so that the weather forecast result is more accurate.
Drawings
FIG. 1 is a block diagram of a computer device according to an embodiment of the present disclosure;
fig. 2 is a flowchart of a method for forecasting a dirty weather according to an embodiment of the present disclosure;
fig. 3 is a flowchart of a method for determining a general population according to an embodiment of the present disclosure;
FIG. 4 is a flowchart of a method for determining artificial heat of a target area according to an embodiment of the present disclosure;
FIG. 5 is a flow chart of a method of determining heat emissions of a target industry provided by an embodiment of the present application;
FIG. 6 is a flow chart of a method of determining heat emission proportions for various target industries over different time periods as provided by an embodiment of the present application;
FIG. 7 is a schematic diagram of a daily variation distribution curve of pollutant discharge rate according to an embodiment of the present application;
FIG. 8 is a flow chart of a method for determining metabolic emissions of heat from a human in a target area according to an embodiment of the present disclosure;
fig. 9 is a block diagram of a weather forecasting apparatus according to an embodiment of the present disclosure.
Detailed Description
To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
Weather conditions are closely related to people's lives, and in order to better perform productive activities, it is very important to accurately forecast weather conditions of a certain place in a certain period of time in the future.
The numerical Weather Forecasting Model WRF (English: Weather Research and Forecasting Model, Chinese: Weather Research and Forecasting Model) is a Model for Forecasting future Weather conditions based on the current atmospheric conditions. In general, the process of weather forecasting using the WRF model is: inputting the current atmospheric parameters, carrying out numerical calculation through a large computer under the condition of certain initial values and side values, solving a fluid mechanics and thermodynamics equation set describing the weather evolution process, and predicting the atmospheric motion state and the weather phenomenon in a certain time period in the future.
At present, the numerical weather forecast model system can provide weather forecast with high reliability, and the forecast of specific meteorological elements such as temperature reaches a considerable precision.
However, as the standard of living of people gradually increases, on the one hand a large number of people gather in cities, and everyone generates heat radiation. On the other hand, in cities, industrial activities, electric power activities, traffic activities and construction activities are more and more frequent, and a large amount of heat radiation is also generated. The heat generated by human activity is called artificial heat. Man-made heat has a great influence on the urban heat island effect and the atmospheric turbulence of the area where the city is located. At present, in a large-scale urban group, artificial heat damages a temperature reversion structure of a boundary layer in the early morning, so that the ground air temperature at night is increased.
In practical applications, the influence of human activities on the natural climate is generally ignored in the WRF model, and the influence of artificial heat on the climate is not considered, however, the influence of human activities on the natural climate is increasingly large, and the way of directly ignoring the influence of human activities on the natural climate may result in low accuracy of weather forecast.
The embodiment of the application provides a weather forecasting method, which comprises the steps of acquiring the number of mobile terminals accessed to a communication network in a target area within a target time period for the target area to be subjected to weather forecasting; determining a general population in a target area in a target time period according to the number of the mobile terminals; calculating the human metabolic emission heat in the target area in the target time period according to the general population; the artificial heat of the target area in the target time period is determined according to the heat discharged by the human metabolism, and the weather forecast is carried out on the target area according to the artificial heat, wherein the artificial heat of the target area is the heat brought by human activities. In the embodiment of the application, the weather forecast is carried out on the target area according to the artificial heat of the target area, and the influence of human activities on the natural climate is considered in the process of weather forecast, so that the weather forecast result is more accurate.
In the following, a brief description will be given of an implementation environment related to the weather forecasting method provided in the embodiment of the present application.
The weather forecast method provided by the application can be applied to the computer device shown in fig. 1, and the computer device can be a terminal, a notebook computer, a tablet computer, a desktop computer and the like. The internal structure of the computer device may be as shown in fig. 1. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing numerical weather forecast models. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a weather forecasting method.
Those skilled in the art will appreciate that the configuration shown in fig. 1 is a block diagram of only a portion of the configuration associated with the present application and does not constitute a limitation on the terminal to which the present application is applied, and that a particular terminal may include more or less components than those shown in fig. 1, or may combine certain components, or have a different arrangement of components.
Referring to fig. 2, a flowchart of a weather forecasting method provided by an embodiment of the present application is shown, where the weather forecasting method may be applied to a computer device in the implementation environment shown in fig. 1, and as shown in fig. 2, the weather forecasting method may include the following steps:
The target area may refer to an area where weather prediction is to be performed, and optionally, the target area may refer to a city or a city group. The mobile terminal may be referred to as a handset.
In the embodiment of the application, the WRF model needs to acquire artificial heat data once every fixed time interval, for example, the WRF model acquires artificial heat once every 1 hour interval, and from 0 o ' clock in the early morning, the WRF model needs to acquire artificial heat data once at 1 o ' clock in the early morning and at 2 o ' clock in the early morning respectively. Accordingly, in the embodiment of the present application, the number of mobile terminals accessing the communication network in the target area needs to be determined every 1 hour interval.
For example: the WRF model has acquired artificial fever at 8 am and needs to acquire artificial fever at 9 am next time, and the target time period in this embodiment refers to the hour between 8 am and 9 am.
The obtaining of the number of the mobile terminals accessing the communication network in the target area in the target time period specifically means: the number of mobile terminals in the target area accessing the communication network between 8 am and 9 am is obtained.
With the development of mobile communication technology, the popularity of mobile terminals has reached a very high rate. When the mobile terminal is powered on or powered off, calls or receives and sends short messages, accesses the mobile internet, even switches base stations and the like, corresponding mobile communication signaling data can be generated by each action of the mobile terminal, and the mobile communication signaling data can accurately record the position and the activity time of a communication base station when a user of the mobile terminal moves in a mobile communication network. According to the accurate coordinates of the communication base station, the number of the mobile terminals which are accessed to the network through the communication base station in the target time period can be determined, and the positions of the mobile terminal users with the error ranges within 500m of the urban area and 1000m of the suburban area can be obtained. Therefore, the present embodiment may determine the number of mobile terminals in the target area in the target time period through the mobile communication signaling data.
In real life, most of middle and young people are user groups of mobile terminals, and the number of users using the mobile terminals is small among the elderly and children. In the embodiment of the application, the population age structure of the target area can be obtained from the Chinese statistics yearbook, and the proportion of the middle-aged and young-aged population in the target area in the total population of the target area can be determined according to the population age structure of the target area.
In the embodiment of the application, the number of the mobile terminals accessing to the network in the target area in the target time period can be determined as the number of the middle-aged and young-aged people in the target area in the target time period;
and then determining the general population in the target area in the target time period according to the number of the middle-young-aged population in the target area in the target time period and the proportion of the middle-young-aged population in the general population of the target area.
In the embodiment of the application, the metabolism emission heat of the unit population in one day can be acquired, the metabolism emission heat of the unit population in the target time period is calculated according to the target time period, and then the metabolism emission heat of the general population and the metabolism emission heat of the unit population in the target time period are multiplied to obtain the human metabolism emission heat of the general population.
And 204, determining artificial heat of the target area in the target time period according to the human metabolism discharge heat, and performing weather forecast on the target area according to the artificial heat, wherein the artificial heat of the target area is heat brought by human activities.
Man-made heat is heat due to human activities, and includes not only human metabolic emissions but also industrial emissions, which may include heat generated by aspects such as industrial activities, electrical activities, construction activities, and transportation activities. It should be noted that human activities are involved in a large number of cases, and in the embodiment of the present application, only four major cases with high heat generation are illustrated.
In the embodiment of the application, the industrial activity heat, the electric activity heat, the building activity heat and the traffic activity heat in the target area in the target time period can be obtained through the Chinese energy statistics yearbook.
And then summing the human metabolism emission heat and the industrial activity heat, the electric power activity heat, the building activity heat and the traffic activity heat to obtain the human heat of the target area in the target time period.
In the embodiment of the present application, the process of performing weather forecast on the target area according to artificial heat may be:
the artificial heat of the target area in the preset target time period can be periodically input into the WRF model, and the WRF model solves a hydromechanics and thermodynamics equation set describing the weather evolution process according to the acquired multiple meteorological parameters of the target area and the artificial heat of the target area, so that the atmospheric motion state and the weather phenomenon of the target area in a certain time period in the future can be predicted.
It should be noted that, in the embodiment of the present application, the WRF model may acquire artificial heat of the target area once every fixed time interval, and perform weather forecast according to the acquired artificial heat. Wherein the fixed time period may be one hour or 2 hours. The time period between the last time of acquiring artificial heat and the current time of acquiring artificial heat by the WRF model is a target time period.
According to the weather forecasting method provided by the embodiment, the general population in the target area in the target time period can be accurately acquired through the number of the mobile terminals accessed to the communication network, so that the heat discharged by human metabolism of the general population is determined. And determining artificial heat of the target area within the target time period based on the human metabolic emission heat and the industrial emission heat. And weather forecast is carried out on the target area according to the artificial heat of the target area, and the influence of human activities on natural climate is considered in the process of weather forecast, so that the weather forecast result is more accurate.
In one embodiment, as shown in fig. 3, the method of determining the general population in the target area during the target time period in step 202 further comprises the following:
Since the number of mobile terminals accessing the communication network is approximately consistent with the number of users of the mobile terminals, in the embodiment of the present application, the number of mobile terminals accessing the communication network in the target area within the target time period may be determined as the number of people using the mobile terminals in the target area within the target time period.
Optionally, in this embodiment of the application, as can be seen from the content disclosed in step 201, the number of mobile terminals located in a town and the number of mobile terminals located in a rural area in the target area may be determined according to the mobile communication signaling data.
The number of mobile terminals located in a town is then determined as the number of populations of using mobile terminals located in the town in the target area. The number of mobile terminals located in the rural area is determined as the number of the population using mobile terminals located in the rural area in the target area.
In the embodiment of the present application, the proportional relationship between the number of the population using the mobile terminal and the number of the population not using the mobile terminal in the target area may generally include a proportional relationship between the number of the population using the mobile terminal and the number of the population not using the mobile terminal in the town population, and a proportional relationship between the number of the population using the mobile terminal and the number of the population not using the mobile terminal in the rural population.
Generally, the coverage of mobile terminal users in the urban market is relatively high, accounting for nearly 80%. Whereas the coverage of mobile terminal users in rural areas is relatively low, occupying a proportion of about 21.0%.
And step 303, determining the total population in the target area according to the population number and the proportional relation of the mobile terminal used in the target area in the target time period.
In the embodiment of the application, the total town population in the target area can be determined according to the number of the population using the mobile terminal in the town and the proportional relationship between the number of the population using the mobile terminal in the town population and the number of the population not using the mobile terminal in the town population.
And determining the total rural population in the target area according to the number of the population using the mobile terminal in the rural area and the proportional relation between the number of the population using the mobile terminal in the rural population and the number of the population not using the mobile terminal.
And summing the total town population and the total rural population in the target area to obtain the total population in the target area.
The embodiment determines the general population in the target area in the target time period through the number of the mobile terminals, and improves the accurate statistics of the metabolic emission heat of human beings in the target area, so that the artificial heat data in the target area is more accurate, the influence of human activities on the weather can be more accurately reflected in the weather forecasting process, and the accuracy of the weather forecasting is improved.
In one embodiment, as shown in fig. 4, the method for determining artificial heat of the target area in the target time period according to the human metabolic emission heat in step 204 further comprises the following steps:
Wherein the target industry comprises at least one of an industrial industry, a construction industry, a power industry, and a transportation industry.
In the embodiment of the application, the obtaining of the heat emission amounts of the multiple target industries may refer to obtaining of heat emission amounts of the industrial industries, heat emission amounts of the building industries, heat emission amounts of the power industries and heat emission amounts of the traffic industries.
In the embodiment of the application, the heat emission of the target industry is generally expressed by standard coal. Wherein the standard coal is coal with a calorific value of 7000 kcal/kg. It is a representation of standard energy. Because coal, oil, natural gas, electricity and other energy sources have different calorific values, in order to compare the calorific values and calculate and examine the energy consumption and the utilization effect of the energy consumption in various departments of national economy, a standard conversion unit of standard coal is generally adopted.
The heat emission of the power industry is generally expressed by the consumption of thermal power standard coal in a target area. The heat emission of the industrial industry is generally converted from the heat generated by consumed weather gas or coal to standard coal consumption. The heat emission of the building industry and the heat emission of the traffic industry are generally converted from consumed electric energy, natural gas, coal and the like into standard coal consumption.
In an alternative implementation, the process of obtaining the heat emission amounts of a plurality of target industries in the target area in the target time period may be: the total heat discharged in the last year by the industrial industry of the target area is obtained from the annual book of Chinese energy statistics. The average is calculated according to the total heat discharged in the last year, and the average daily heat discharge amount in the last year in the industrial industry can be obtained.
Optionally, the heat emission amount of the industrial industry per day can be averaged to each time period, so that the heat emission amount of the industrial industry corresponding to the target time period can be obtained.
The heat emission amount of the building industry, the heat emission amount of the power industry and the heat emission amount of the traffic industry in the target time period can refer to an acquisition method of the heat emission amount of the industrial industry, and details are not repeated herein.
In another alternative implementation, as shown in fig. 5, the process of obtaining heat emissions of a plurality of target industries within a target area over a target time period may include the steps of:
Wherein the preset time period comprises a plurality of time periods.
In the embodiment of the present application, the preset time period may be one month, one week, or one day.
Taking the preset time period as one day as an example, the preset time period including a plurality of time periods may refer to: a day includes 24 hours, and every 1 or several hours may be taken as one time period, or a fixed time period may be taken as one time period. Multiple time periods may be included within a day.
In the embodiment of the present application, the process of acquiring the total amount of heat emission of each target industry in the target area within the preset time period includes the following steps:
and A1, acquiring historical heat emission total quantity of each target industry from the energy statistics yearbook in the target area.
The energy source statistics yearbook can be an energy source statistics yearbook of a target area, and can also be obtained from Chinese energy source statistics yearbook.
Wherein, the historical total heat emission can generally refer to the total heat emission of one year or several years.
A2, determining the total heat emission amount of each target industry in a preset time period according to the historical total heat emission amount of each target industry.
Taking the traffic industry as an example, the total heat emission amount of the traffic industry in the target area of the previous year can be obtained from the energy statistics yearbook. The total heat emission amount of the traffic industry in the previous year is averaged to each day (in the embodiment, the preset time period is taken as one day for example), so that the total heat emission amount of the traffic industry in the target area within one day is obtained.
The process of acquiring the total heat emission of the industrial industry, the power industry and the building industry is similar to that of the transportation industry, and is not described herein again.
According to the embodiment of the application, people can frequently move in the daytime, all target industries are in an active state, and the heat emission amount is large according to living habits of people. At night, human activities are reduced, activity frequency of each target industry is reduced, and heat emission is less. Accordingly, during the day, the artificial heat is greater during the day than at night. Therefore, the amount of heat discharged in different time periods is different within the preset time period.
In order to determine the artificial heat in the target time period more accurately, in the embodiment of the application, the heat emission proportion of each target industry in different time periods in a day needs to be determined.
In an alternative implementation, as shown in fig. 6, the process of determining the heat emission proportion of each target industry at different time periods may include the following:
In the embodiment of the present application, a preset time period is one day, and each hour is one time period, which is taken as an example, for each target industry, daily variation distribution of pollutant emission rate of each target industry in a target area within one day may be obtained.
As shown in fig. 7, daily variation distribution curves of the emission rates of pollutants in the industrial industry, the electric power industry, and the traffic industry are respectively shown in fig. 7.
From the daily variation profile of the discharge rate of pollutants of the power industry shown in fig. 7, the discharge rate of pollutants of the power industry at different time periods can be obtained. In the embodiment of the present application, the emission ratios of the pollutant emission rates in different time periods in one day may be calculated, and the emission ratios are determined as the distribution ratios of the pollutant emission amounts in the power industry in different time periods in one day, and the content shown in table 1 may be obtained by referring to fig. 7.
TABLE 1
The method for acquiring the distribution proportion of different time periods in the building industry, the traffic industry and the industrial industry within the preset time period is similar to that in the power industry, and is not described herein again.
As shown in fig. 7, taking the power industry as an example, wherein the pollutant emission rate of the power industry between 8 o 'clock and 9 o' clock is low, human activities gradually start. In the period from 10 o 'clock to 16 o' clock, human activities are in a relatively active state, and the pollutant emission rate is relatively high, which means that the coal consumption of thermal power generation is relatively large, and the corresponding generated heat is relatively large. In the period from 16 to 21, the human activity frequency gradually decreases, the pollutant discharge rate continuously decreases, and correspondingly, the heat generated by the power industry also decreases. From 21 o 'clock to 5 a' clock in the morning, the human beings are in a rest state, the pollutant rate of the power industry emission is the lowest, and correspondingly, the heat generated by the power industry is also the lowest.
Therefore, as can be seen from fig. 7, the course of the pollutant emission rate of the power industry within one day can be used to reflect the course of the heat emission amount of the power industry within one day.
In the embodiment of the application, the distribution ratio of the pollutant emission amount of the power industry at different hours in a day can be used as the heat emission ratio of the power industry at different hours in the day.
The determination process of the heat emission proportion of other target industries is the same, and is not described in detail.
On the basis of obtaining the heat emission ratios of the target industries in a plurality of time periods within one day, determining the target time period, and obtaining the heat emission ratios corresponding to different target industries in the target time period.
In the embodiment of the present application, a target time period is from 8 am to 9 am, and it can be known from fig. 7 and table 1 that the pollutant discharge rate of the power industry from 8 am to 9 am is 1.2, and the discharge rate accounts for 4.9%. Therefore, the heat emission proportion of the power industry in the target time period is 4.9%.
The determination process of the heat emission proportion of other target industries is the same, and is not described in detail.
And step 504, determining the heat emission amount of the plurality of target industries in the target area in the target time period according to the total heat emission amount of each target industry and the heat emission proportion of each target industry in the target time period.
In the embodiment of the application, the total heat emission amount of the power industry in one day can be multiplied by the heat emission proportion of the target time period from 8 to 9 points to obtain the heat emission amount of the power industry in the target time period from 8 to 9 points.
The determination process of the heat emission proportion of other target industries is the same, and is not described in detail.
In the embodiment of the application, the characteristics of heat discharge of each target industry in different time periods are fully considered, and the accuracy of artificial heat data of the target area in the target time period is improved, so that the accuracy of weather forecast is improved.
And step 402, summing the heat discharged by the human metabolism and the heat discharged by the multiple target industries, and taking the sum result as the human heat of the target area in the target time period.
In the embodiment of the application, the heat discharged by human metabolism in the target time period, for example, the hour between 8 a.m. and 9 a.m., and the heat discharged by the industrial industry, the heat discharged by the building industry, the heat discharged by the power industry and the heat discharged by the traffic industry in the hour between 8 a.m. and 9 a.m., can be summed to obtain a summation result, and the summation result is used as artificial heat of the target area in the target time period.
In the embodiment of the application, different target industries release different amounts of heat emission in different time periods within a preset period, so that artificial heat of a target area in different time periods within the preset period is different, and the artificial heat of different target time periods input into the WRF model is different, so that the WRF model can more accurately acquire climate differences of the target area in different time periods, and the accuracy of weather forecast is improved.
In one embodiment, as shown in fig. 8, the method for calculating the metabolic emission heat of human beings in the target area in the target time period according to the general population in step 203 further comprises the following steps:
Human beings have large activity and high activity power in the daytime. The activity amount is small at night, and the activity power is low. In the embodiment of the present application, the activity power of human beings at different time periods within one day is preset, for example, at 7 o 'clock to 23 o' clock each day, the activity power of human beings is about 171W, and other time is about 70W.
At step 802, a human activity power for a target time period is determined based on human activity powers for different time periods.
In the embodiment of the present application, still taking a target time period from 8 to 9 as an example, in the target time period from 8 to 9, the human activity power is 171W.
In step 803, the human metabolic emission heat in the target area in the target time period is determined according to the general population and the human activity power in the target time period.
In the embodiment of the application, the total population can be multiplied by the human activity power in the target time period from 8 to 9 points to obtain the total activity power of the total population in the target area in the target time period from 8 to 9 points, namely the heat discharged by human metabolism.
According to the embodiment of the application, different human activity powers are set at different time periods according to human activity characteristics, so that the determined human metabolism emission heat is more accurate, the data accuracy of artificial heat of a target area in a target time period is improved, and the accuracy of weather forecast is improved.
Referring to fig. 9, a block diagram of a weather forecasting apparatus provided in an embodiment of the present application is shown, where the weather forecasting apparatus may be configured in the computer device shown in fig. 1. As shown in fig. 9, the weather forecasting apparatus may include an acquisition module 901, a population determination module 902, a metabolism determination module 903, and a weather forecasting module 904, wherein:
an obtaining module 901, configured to obtain, for a target area to be subjected to weather prediction, the number of mobile terminals accessing a communication network in the target area in a target time period;
a population determining module 902, configured to determine a general population in a target area within a target time period according to the number of mobile terminals;
a metabolism determination module 903 for calculating the amount of heat discharged by human metabolism in a target area in a target time period according to the general population;
and the weather forecasting module 904 is used for determining artificial heat of the target area in the target time period according to the heat discharged by the metabolism of the human beings and forecasting weather of the target area according to the artificial heat, wherein the artificial heat of the target area is heat brought by human activities.
In one embodiment, the population determination module 902 is further configured to use the number of mobile terminals as the population using the mobile terminals in the target area for the target time period; acquiring the proportional relation between the population number of the used mobile terminal and the population number of the unused mobile terminal in the target area; and determining the total population in the target area according to the population number and the proportional relation of the mobile terminal used in the target area in the target time period.
In one embodiment, the weather forecast module 904 is further configured to obtain heat emissions of a plurality of target industries within the target area within the target time period, the target industries including at least one of an industrial industry, a construction industry, a power industry, and a transportation industry; and summing the heat discharged by human metabolism and the heat discharged by a plurality of target industries, and taking the summation result as artificial heat of a target area in a target time period.
In one embodiment, the weather forecast module 904 is further configured to obtain a total amount of heat emissions of each target industry within the target area within a preset time period, wherein the preset time period includes a plurality of time periods; acquiring the heat emission proportion of each target industry in different time periods within a preset time period; determining the heat emission proportion corresponding to each target industry in the target time period according to the heat emission proportion of each target industry in different time periods; and determining the heat emission amount of the plurality of target industries in the target area in the target time period according to the total heat emission amount of each target industry and the heat emission proportion of each target industry in the target time period.
In one embodiment, the weather forecast module 904 is further configured to obtain distribution ratios of pollutant emissions of each target industry of the target area in different time periods within a preset time period; and determining the corresponding thermal emission proportions of the target industries in different time periods according to the distribution proportions of the pollutant emission quantities of the target industries in different time periods in a preset time period.
In one embodiment, the weather forecast module 904 is further configured to obtain historical heat emission totals for each target industry from the energy statistics yearbook within the target area; and determining the total heat emission amount of each target industry in a preset time period according to the historical total heat emission amount of each target industry.
In one embodiment, the metabolism determination module 903 is further configured to obtain human activity power of different time periods within a preset time period; determining human activity power for a target time period according to the human activity power for different time periods; and determining the human metabolic emission heat in the target area in the target time period according to the general population and the human activity power of the target time period.
For the specific definition of the weather forecasting device, reference may be made to the above definition of the weather forecasting method, which is not described herein again. The modules in the weather forecast apparatus may be implemented in whole or in part by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment of the present application, there is provided a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring the number of mobile terminals accessed to a communication network in a target area within a target time period for the target area to be subjected to weather prediction; determining a general population in a target area in a target time period according to the number of the mobile terminals; calculating the human metabolic emission heat in the target area in the target time period according to the general population; the artificial heat of the target area in the target time period is determined according to the heat discharged by the human metabolism, and the weather forecast is carried out on the target area according to the artificial heat, wherein the artificial heat of the target area is the heat brought by human activities.
In one embodiment of the application, the processor when executing the computer program further performs the steps of: taking the number of the mobile terminals as the number of the population using the mobile terminals in the target area in the target time period; acquiring the proportional relation between the population number of the used mobile terminal and the population number of the unused mobile terminal in the target area; and determining the total population in the target area according to the population number and the proportional relation of the mobile terminal used in the target area in the target time period.
In one embodiment of the application, the processor when executing the computer program further performs the steps of: acquiring heat emission quantities of a plurality of target industries in a target area in a target time period, wherein the target industries comprise at least one of industrial industry, building industry, electric power industry and traffic industry; and summing the heat discharged by human metabolism and the heat discharged by a plurality of target industries, and taking the summation result as artificial heat of a target area in a target time period.
In one embodiment of the application, the processor when executing the computer program further performs the steps of: acquiring the total heat emission amount of each target industry in a target area within a preset time period, wherein the preset time period comprises a plurality of time periods; acquiring the heat emission proportion of each target industry in different time periods within a preset time period; determining the heat emission proportion corresponding to each target industry in the target time period according to the heat emission proportion of each target industry in different time periods; and determining the heat emission amount of the plurality of target industries in the target area in the target time period according to the total heat emission amount of each target industry and the heat emission proportion of each target industry in the target time period.
In one embodiment of the application, the processor when executing the computer program further performs the steps of: acquiring the distribution proportion of pollutant discharge amount of each target industry of a target area in different time periods within a preset time period; and determining the corresponding thermal emission proportions of the target industries in different time periods according to the distribution proportions of the pollutant emission quantities of the target industries in different time periods in a preset time period.
In one embodiment of the application, the processor when executing the computer program further performs the steps of: acquiring the historical heat emission total amount of each target industry from the energy statistics yearbook in the target area; and determining the total heat emission amount of each target industry in a preset time period according to the historical total heat emission amount of each target industry.
In one embodiment of the application, the processor when executing the computer program further performs the steps of: acquiring human activity power of different time periods in a preset time period; determining human activity power for a target time period according to the human activity power for different time periods; and determining the human metabolic emission heat in the target area in the target time period according to the general population and the human activity power of the target time period.
The implementation principle and technical effect of the computer device provided by the embodiment of the present application are similar to those of the method embodiment described above, and are not described herein again.
In an embodiment of the application, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of:
acquiring the number of mobile terminals accessed to a communication network in a target area within a target time period for the target area to be subjected to weather prediction; determining a general population in a target area in a target time period according to the number of the mobile terminals; calculating the human metabolic emission heat in the target area in the target time period according to the general population; the artificial heat of the target area in the target time period is determined according to the heat discharged by the human metabolism, and the weather forecast is carried out on the target area according to the artificial heat, wherein the artificial heat of the target area is the heat brought by human activities.
In one embodiment of the application, the computer program, when executed by the processor, may further implement the steps of: taking the number of the mobile terminals as the number of the population using the mobile terminals in the target area in the target time period; acquiring the proportional relation between the population number of the used mobile terminal and the population number of the unused mobile terminal in the target area; and determining the total population in the target area according to the population number and the proportional relation of the mobile terminal used in the target area in the target time period.
In one embodiment of the application, the computer program, when executed by the processor, may further implement the steps of: acquiring heat emission quantities of a plurality of target industries in a target area in a target time period, wherein the target industries comprise at least one of industrial industry, building industry, electric power industry and traffic industry; and summing the heat discharged by human metabolism and the heat discharged by a plurality of target industries, and taking the summation result as artificial heat of a target area in a target time period.
In one embodiment of the application, the computer program, when executed by the processor, may further implement the steps of: acquiring the total heat emission amount of each target industry in a target area within a preset time period, wherein the preset time period comprises a plurality of time periods; acquiring the heat emission proportion of each target industry in different time periods within a preset time period; determining the heat emission proportion corresponding to each target industry in the target time period according to the heat emission proportion of each target industry in different time periods; and determining the heat emission amount of the plurality of target industries in the target area in the target time period according to the total heat emission amount of each target industry and the heat emission proportion of each target industry in the target time period.
In one embodiment of the application, the computer program, when executed by the processor, may further implement the steps of: acquiring the distribution proportion of pollutant discharge amount of each target industry of a target area in different time periods within a preset time period; and determining the corresponding thermal emission proportions of the target industries in different time periods according to the distribution proportions of the pollutant emission quantities of the target industries in different time periods in a preset time period.
In one embodiment of the application, the computer program, when executed by the processor, may further implement the steps of: acquiring the historical heat emission total amount of each target industry from the energy statistics yearbook in the target area; and determining the total heat emission amount of each target industry in a preset time period according to the historical total heat emission amount of each target industry.
In one embodiment of the application, the computer program, when executed by the processor, may further implement the steps of: acquiring human activity power of different time periods in a preset time period; determining human activity power for a target time period according to the human activity power for different time periods; and determining the human metabolic emission heat in the target area in the target time period according to the general population and the human activity power of the target time period.
The implementation principle and technical effect of the computer-readable storage medium provided in the embodiment of the present application are similar to those of the method embodiment described above, and are not described herein again.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the claims. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A weather forecasting method, the method comprising:
acquiring the number of mobile terminals accessed to a communication network in a target area within a target time period for the target area to be subjected to weather prediction;
determining a general population in the target area in the target time period according to the number of the mobile terminals;
calculating the human metabolic emission heat in the target area in the target time period according to the general population;
and determining artificial heat of the target area in the target time period according to the human metabolism discharge heat, and performing weather forecast on the target area according to the artificial heat, wherein the artificial heat of the target area is heat brought by human activities.
2. The method of claim 1, wherein the determining a general population in the target area in the target time period according to the number of the mobile terminals comprises:
taking the number of the mobile terminals as the population number of the mobile terminals used in the target area in the target time period;
acquiring the proportional relation between the population number of the used mobile terminals and the population number of the unused mobile terminals in the target area;
and determining the total population in the target area according to the population number of the mobile terminals used in the target area in the target time period and the proportional relation.
3. The method of claim 1, wherein said determining artificial heat for the target area for the target time period from the human metabolic emission heat comprises:
acquiring heat emission amounts of a plurality of target industries in the target area in the target time period, wherein the target industries comprise at least one of an industrial industry, a building industry, an electric power industry and a traffic industry;
summing the human metabolic emission heat and the heat emission of the plurality of target industries, and taking the summation result as artificial heat of the target area in the target time period.
4. The method of claim 3, wherein said obtaining heat emissions of a plurality of target industries within the target area over the target time period comprises:
acquiring the total heat emission amount of each target industry in the target area within a preset time period, wherein the preset time period comprises a plurality of time periods;
acquiring the heat emission proportion of each target industry in different time periods within the preset time period;
determining the heat emission proportion corresponding to each target industry in the target time period according to the heat emission proportion of each target industry in different time periods;
and determining the heat emission amount of the plurality of target industries in the target area in the target time period according to the heat emission total amount of each target industry and the heat emission proportion of each target industry corresponding to the target time period.
5. The method of claim 4, wherein the obtaining the heat emission proportions for each of the target industries at different time periods within the preset time period comprises:
acquiring the distribution proportion of pollutant discharge amount of each target industry of the target area in different time periods within the preset time period;
and determining the corresponding heat emission proportion of each target industry in different time periods according to the distribution proportion of the pollutant emission of each target industry in different time periods in the preset time period.
6. The method of claim 4, wherein said obtaining a total amount of heat emissions for each of said target industries within said target area over a preset time period comprises:
obtaining the historical heat emission total amount of each target industry from the energy statistics yearbook in the target area;
and determining the total heat emission amount of each target industry in the preset time period according to the historical total heat emission amount of each target industry.
7. The method of claim 1, wherein calculating the human metabolic emission calories within the target area for the target time period based on the population comprises:
acquiring human activity power of different time periods in a preset time period;
determining a human activity power for the target time period from the human activity powers for the different time periods;
determining human metabolic emission heat in the target area within the target time period according to the population and the human activity power for the target time period.
8. A weather forecasting apparatus, characterized in that the apparatus comprises:
the system comprises an acquisition module, a weather prediction module and a weather prediction module, wherein the acquisition module is used for acquiring the number of mobile terminals accessed to a communication network in a target area within a target time period for the target area to be subjected to weather prediction;
the population determining module is used for determining the general population in the target area in the target time period according to the number of the mobile terminals;
the metabolism determining module is used for calculating the human metabolism emission heat in the target area in the target time period according to the general population;
and the weather forecast module is used for determining artificial heat of the target area in the target time period according to the heat discharged by the human metabolism, and carrying out weather forecast on the target area according to the artificial heat, wherein the artificial heat of the target area is heat brought by human activities.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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