KR-102960933-B1 - NUMERICAL MODELING DEVICE FOR COMPOSITE CLOUD SEEDING ANALYSIS AND METHOD THEREOF

KR102960933B1KR 102960933 B1KR102960933 B1KR 102960933B1KR-102960933-B1

Abstract

The numerical modeling device for analyzing composite seeding artificial rainfall according to the present invention comprises: a seeding information collection unit that extracts spatiotemporal data and material data, respectively, from seeding log data received from a seeding execution device and generates a raw data set combined into an interlinkable structure; a seeding information preprocessing unit that converts the raw data set to correspond to the grid system and time integration structure of a numerical model to generate a numerical model input data structure including a grid index, a time index, a material type identifier, and a converted physical quantity; a material characteristic mapping unit that maps a set of material characteristic parameters corresponding to the material type identifier of the numerical model input data structure to generate an extended data structure linked to a calculation module of the numerical model; a seeding material contribution calculation unit that calculates the independent contribution of each seeding material by linking the extended data structure with the current grid state variable of the numerical model and generates integrated contribution data by summing the independent contributions; and a seeding effect analysis unit that calculates final precipitation prediction data by applying the integrated contribution data as an input variable for updating the state variable of the numerical model and generates seeding effect evaluation data based on the integrated contribution data and the final precipitation prediction data.

Inventors

임윤규
장기호
벨로리드 밀로슬라브
노용훈
고아름
조중현

Dates

Publication Date: 20260512
Application Date: 20260303

Claims (10)

A seeding information collection unit that extracts spatiotemporal data and material data, respectively, from seeding log data received from a seeding execution device and generates a raw data set combined into an interconnected structure; A seeding information preprocessing unit that converts the above raw data set to correspond to the grid system and time integration structure of the numerical model, and generates a numerical model input data structure including a grid index, a time index, a material type identifier, and a converted physical quantity; A material property mapping unit that maps a set of material property parameters corresponding to a material type identifier of the numerical model input data structure to generate an extended data structure linked to the calculation module of the numerical model; A seeding material contribution calculation unit that calculates the independent contribution of each seeding material by linking the extended data structure and the current grid state variable of the numerical model, and generates integrated contribution data by summing the independent contributions; and A numerical modeling device for analyzing composite seeding artificial rainfall, comprising a seeding effect analysis unit that applies the integrated contribution data as an input variable for updating the state variable of the numerical model to calculate final precipitation prediction data, and generates seeding effect evaluation data based on the integrated contribution data and the final precipitation prediction data.
In paragraph 1, The above spatiotemporal data includes at least one of a seeding time value, latitude coordinates, longitude coordinates, and altitude, and The above material data is a numerical modeling device for complex seeding artificial rainfall analysis that includes material type information for identifying the type of seeding material and emission information of the seeding material.
In paragraph 1, The above seeding information collection unit is, The spacetime parsing engine and the matter parsing engine are operated in parallel to extract the spacetime data and matter data, respectively, and A numerical modeling device for complex seeding artificial rainfall analysis that, when multiple seeding materials are recorded in the same time interval, reconstructs material type-specific data corresponding to the multiple seeding materials through a merged event processing process so that they are distinguished and identified within a single event structure.
In paragraph 1, The above seeding information preprocessing unit is, A numerical modeling device for composite seeding artificial rainfall analysis comprising a spatial mapping engine and a physical quantity conversion engine, wherein the physical quantity conversion engine normalizes emission information included in the material data based on the volume or area of a corresponding grid and converts it into a unit mass flux or concentration increment value.
In paragraph 1, The above material property mapping unit is, A material property lookup table is provided that uses the above material type identifier as an identification key and stores a set of material property parameters of the corresponding material as a result value. A set of basic material property parameters is extracted from the above lookup table using fixed parameter call logic, and A numerical modeling device for composite seeding artificial rainfall analysis configured such that the set of material characteristic parameters is scaled according to input concentration conditions by reflecting a correction coefficient to the set of basic material characteristic parameters by referencing the converted physical quantity through dynamic parameter correction logic.
In paragraph 1, The above seeding material contribution calculation unit is, When multiple seeding materials exist within the same grid, branching logic is provided to assign individual processing paths so that each material is separated into independent computational units based on the set of material characteristic parameters. Calculate the above independent contribution for each substance through an individual contribution calculation engine, and A numerical modeling device for composite seeding artificial rainfall analysis that generates integrated contribution data by summing the independent contributions based on a single grid through an integrated output engine.
In paragraph 1, The above seeding effect analysis unit is, It is equipped with scenario alignment logic that sets a state with specific seeding conditions applied as a reference scenario and sets the numerical model output result with different seeding conditions applied as a comparison scenario, and The above scenario alignment logic is a numerical modeling device for composite seeding artificial rainfall analysis that aligns and maps the precipitation distribution, cumulative precipitation, change in cloud water concentration, and change in ice crystal concentration for each scenario on the same spatial grid system to calculate grid unit difference attributes and spatial statistical attributes.
A step of generating a raw data set by extracting spatiotemporal data and material data, respectively, from seeding log data received from a seeding execution device and combining them into an interconnected structure; A step of converting the above raw data set to correspond to the grid system and time integral structure of the numerical model to generate a numerical model input data structure including a grid index, a time index, a material type identifier, and a converted physical quantity; A step of generating an extended data structure linked to a calculation module of the numerical model by mapping a set of material property parameters corresponding to a material type identifier of the numerical model input data structure; The independent contribution of each seeding material is calculated by linking the above-mentioned extended data structure with the current lattice state variable of the above-mentioned numerical model, and A step of generating integrated contribution data by summing the above independent contributions; A step of calculating final precipitation prediction data by applying the above integrated contribution data as an input variable for updating the state variable of the above numerical model; and A numerical modeling method for composite seeding artificial rainfall analysis comprising the step of generating seeding effect evaluation data based on the above integrated contribution data and final precipitation prediction data.
In paragraph 8, The above spatiotemporal data includes at least one of a seeding time value, latitude coordinates, longitude coordinates, and altitude, and A numerical modeling method for analyzing composite seeding artificial rainfall, comprising material data including material type information for identifying the type of seeding material and emission information of the seeding material.
A computer-readable storage medium for storing one or more programs, wherein the one or more programs are configured to be executed by one or more processors of an electronic device, and the one or more programs include instructions for performing the method of any one of claims 8 and 9.

Description

Numerical Modeling Device and Method for Composite Cloud Seeding Analysis The present invention relates to a numerical modeling apparatus and method for analyzing composite seeding artificial rainfall. Due to climate change and the increasing frequency of localized droughts, artificial rainfall technology is attracting attention as an important weather control measure for securing water resources and stabilizing agriculture. As one such weather control technology, artificial rainfall is a method that increases the probability of inducing precipitation by generating and growing clouds through the spraying of seeding substances into the atmosphere. In this technology, the sprayed particles act as cloud condensation nuclei (CCN) or ice nuclei (IN), condensing supersaturated water vapor or promoting the formation of ice crystals, thereby inducing weather phenomena that lead to the growth of cloud particles and precipitation. Seeding materials include sodium chloride (NaCl), silver iodide (AgI), and calcium chloride (CaCl₂), and each material exhibits different activity as a nucleus for condensation and ice crystal formation depending on its characteristics. For instance, particle size (in μm units), number concentration (Nt), water solubility, and thermal stability are directly related to the cloud particle formation rate. Cloud seeding technology proceeds by spraying seeding materials into the upper atmosphere via aircraft, rockets, or ground launchers, after which the particles condense water vapor within the cloud to induce the formation of raindrops or ice crystals. However, since the effectiveness of artificial rainfall experiments is complexly influenced by various meteorological factors such as atmospheric conditions, cloud thermodynamic structure, water vapor distribution, and upper-level wind speed, it is very difficult to quantitatively evaluate the extent to which the actually dispersed seeding material contributed to precipitation formation. Therefore, simulation analysis using numerical models is utilized in the design and post-event analysis phases of artificial rainfall experiments. Existing numerical models operate by increasing particle concentration based solely on input information regarding the application time and altitude of seeding materials. However, this structure has limitations, requiring the establishment of separate models for different material types or the application of characteristic values for a single material. Consequently, there is a structural problem in that it is impossible to simultaneously calculate and reflect multiple seeding materials with different particle characteristics within a single model on the same grid. FIG. 1 is a schematic block diagram of a numerical modeling system for analyzing composite seeding artificial rainfall according to an embodiment of the present invention. FIG. 2 is a schematic block diagram of a numerical modeling device according to an embodiment of the present invention. FIG. 3 is a schematic block diagram of a processor according to an embodiment of the present invention. FIG. 4 is a flowchart illustrating a numerical modeling method for analyzing composite seeding artificial rainfall according to an embodiment of the present invention. FIGS. 5 (a) to (c) is a diagram illustrating a numerical modeling method for analyzing composite seeding artificial rainfall according to an embodiment of the present invention. The advantages and features of the present invention and the methods for achieving them will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below but can be implemented in various different forms. These embodiments are provided merely to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the present invention, and the present invention is defined only by the scope of the claims. The terms used in this specification are for describing embodiments and are not intended to limit the invention. In this specification, the singular form includes the plural form unless specifically stated otherwise in the text. The terms "comprises" and/or "comprising" as used in this specification do not exclude the presence or addition of one or more other components in addition to the components mentioned. Throughout the specification, the same reference numerals refer to the same components, and "and/or" includes each of the mentioned components and all combinations of one or more. Although terms such as "first," "second," etc., are used to describe various components, these components are not limited by these terms. These terms are used merely to distinguish one component from another. Therefore, the first component mentioned below may be the second component within the technical scope of the invention. Unless otherwise defined, all terms u