KR102379094B1 - Apparatus and method for evaluating seedability of snow clouds - Google Patents

Abstract

An apparatus and method for evaluating snow cloud seeding potential are disclosed. The method for evaluating the seeding possibility of a snow cloud includes the steps of receiving numerical model data including measurement values of a plurality of seeding possibility evaluation factors for a snow cloud, and for the plurality of seeding possibility evaluation factors, the seeding possibility of mapping scores for each preset section Extracting the score of each evaluation element from the score table, calculating the seeding possibility score by summing the scores of each extracted evaluation element, using a seeding possibility rating table that maps the seeding possibility grade for each preset seeding possibility score section , calculating a seedability grade for the calculated seedability score, and outputting the calculated seedability score and seedability grade.

Description

Apparatus and method for evaluating seedability of snow clouds

The present invention relates to an apparatus and method for evaluating snow cloud seeding potential.

The artificial expansion air experiment is an experiment in which silver iodide (AgI) combustion bombs, which act as ice cores, are sprayed on snow clouds in order to secure water resources to prepare for drought, so that snow clouds are activated and many ice crystals are formed so that more snow can fall. . These artificial expansion aerial experiments are mainly conducted on clouds occurring in mountainous areas. Countries that carry out artificial expansion air experiments in mountainous terrain include Japan, the United States, and the Republic of Korea. Here, Japan is conducting artificial expansion air experiments in the Echigo Mountains, and the United States is mainly performing artificial expansion air experiments in the Rocky Mountains and Sierra Nevada Mountains.

In the paper of Hashimoto et al. (2008) in the Japanese SOLA journal, the seeding potential was evaluated for winter snow clouds in the Echigo Mountains in order to effectively perform the artificial expansion aerial experiment. In this case, the seeding possibility was evaluated using the average of the evaluation factor values measured in the windward area of the Echigo Mountains where the aerial experiment was conducted. Wind Direction (WD), Wind Speed (WS: Wind Speed), liquid water path (LWP: Liquid Water Path), which is the vertically integrated cloud water content, temperature of cloud water (TQ _c ), total condensed water The mixing ratio (Qc/Qt) of the cloud water of the mixing ratio was considered, and the seeding possibility was evaluated. That is, the seeding potential was evaluated by calculating a score from the evaluation element value and grading from the calculated score. The higher the grade, the higher the seeding possibility. At this time, the wind direction was considered only from the north wind to the west wind, and was not included in the seeding possibility score. And, the average of all evaluation element values measured for 6 hours was used, and the average of the mixing ratio (Qc/Qt) of the cloud water to the mixing ratio of the total condensed water was applied at an altitude of 1-3 km.

According to the method presented in the above paper, as a result of evaluating the seeding potential of the case of the artificial expansion air experiment conducted in the Daegwallyeong region where the Taebaek Mountains of Korea are located, a very low grade was calculated. So, as a result of checking the values of each evaluation element, the mixing ratio of cloud water (Qc/Qt) to the mixing ratio of the total condensed water was 0 in most cases, and scores for wind speed were also generally in all cases. It was confirmed that a very low score was given.

Therefore, there is a need for a new evaluation factor and an evaluation technology using the same to determine the seeding possibility more appropriately and accurately for the Daegwallyeong region, a mountainous region where artificial expansion air experiments are typically performed in Korea.

An object of the present invention is to provide an apparatus and method for evaluating the seeding possibility of snow clouds that calculates the seeding possibility in an objective and scientific way in order to determine whether to perform an artificial expansion air experiment on snow clouds occurring in a mountainous region.

According to an aspect of the present invention, a method for evaluating the seeding potential of a snow cloud performed by a seeding possibility evaluation apparatus is disclosed.

The method for evaluating the seeding possibility of a snow cloud according to an embodiment of the present invention includes the steps of: receiving numerical model data including measurement values of a plurality of seedability evaluation factors for the snow cloud; Extracting the score of each evaluation element from the seeding possibility score table in which the score is mapped for each set section, calculating a seeding possibility score by summing the scores of each of the extracted evaluation factors, Seeding possibility grade for each preset seeding possibility score section calculating a seedability grade for the calculated seedability score and outputting the calculated seedability score and seedability grade by using the seedability grade table mapped to .

The plurality of seeding possibility evaluation factors are, a wind direction (WD: Wind Direction) value, a vertical wind speed (W: vertical wind speed) value, a wind speed (WS: Wind Speed) value, a liquid water path (LWP: Liquid Water Path) value, cloud water temperature (TQ _c ) value, maximum value of cloud water mixing ratio (Qc/Qt) of total condensed water mixing ratio (Max_Q), and cloud liquid water depth (CD_L: Depth of LWC (Liquid Water Content) includes at least one of the values.

The wind direction value and the vertical wind speed value are reference values not applied to the calculation of the seeding possibility score, and the vertical wind speed value is given as 1 in the case of an updraft and 0 in the case of a downdraft.

The seedability score is calculated by adding up the score for the wind speed, the score for the liquid water path, the score for the cloud water temperature, the score for the maximum value, and the score for the liquid water depth.

The liquid water depth value is calculated as the thickness of the layers having the LWC of 0.01 gm ^-2 or more.

According to another aspect of the present invention, an apparatus for evaluating snow cloud seeding potential is disclosed.

The apparatus for evaluating the seeding potential of a snow cloud according to an embodiment of the present invention includes a memory storing an instruction and a processor executing the instruction, wherein the instruction includes a measurement value of a plurality of seedability evaluation factors for the snow cloud. extracting the score of each evaluation element from a seeding possibility score table in which scores are mapped for each of the preset sections with respect to the plurality of seeding possibility evaluation elements, and the score of each of the extracted evaluation elements Calculating a seedability score by summing up, calculating a seedability grade for the calculated seedability score using a seedability grade table that maps a seedability grade for each preset seedability score section, and the calculated A method for evaluating the seedability of a snow cloud is performed, including outputting a seedability score and a seedability grade.

The apparatus and method for evaluating the seeding possibility of a snow cloud according to an embodiment of the present invention calculates the seeding possibility for a snow cloud generated in a mountainous area, so that it is possible to easily determine whether to perform an artificial expansion aerial experiment in a scientific way.

1 is a flowchart illustrating a method for evaluating the seeding possibility of a snow cloud performed by an apparatus for evaluating the seeding possibility of a snow cloud according to an embodiment of the present invention.
2 to 4 are views for explaining a method for evaluating the seeding possibility of the snow cloud according to the embodiment of the present invention of FIG. 1 .
5 is a diagram schematically illustrating the configuration of a snow cloud seeding possibility evaluation apparatus according to an embodiment of the present invention.

As used herein, the singular expression includes the plural expression unless the context clearly dictates otherwise. In this specification, terms such as "consisting of" or "comprising" should not be construed as necessarily including all of the various components or various steps described in the specification, some of which components or some steps are It should be construed that it may not include, or may further include additional components or steps. In addition, terms such as "...unit" and "module" described in the specification mean a unit that processes at least one function or operation, which may be implemented as hardware or software, or a combination of hardware and software. .

Hereinafter, various embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a flowchart illustrating a method for evaluating the seeding possibility of a snow cloud performed by the apparatus for evaluating the seeding possibility of a snow cloud according to an embodiment of the present invention, and FIGS. 2 to 4 are the seeding possibility of a snow cloud according to the embodiment of the present invention of FIG. It is a figure for demonstrating an evaluation method. Hereinafter, a method for evaluating the seeding possibility of a snow cloud according to an embodiment of the present invention will be described with reference to FIG. 1 , with reference to FIGS. 2 to 4 .

In step S110, the apparatus for evaluating the seeding possibility of snow clouds receives numerical model data.

2 shows evaluation factors that can be considered for evaluating the seeding possibility of snow clouds generated in a winter mountainous region between 1 km and 3 km above sea level (ASL).

Referring to FIG. 2 , the numerical model data is a measurement value of a plurality of seeding possibility evaluation factors for snow clouds, and is a wind direction (WD: Wind Direction) value, a vertical wind speed (W: vertical wind speed) value, and a wind speed (WS: Wind Speed). ) value, the liquid water path (LWP) value, which is the vertically integrated cloud water content, the temperature (TQ _c ) value of cloud water, and the mixing ratio (Qc/Qt) of the cloud water to the mixing ratio of the total condensed water It may include a maximum value (Max_Q) and a depth of liquid water content in clouds (CD_L: Depth of LWC (Liquid Water Content)). An average of values measured for about 6 hours may be applied to each numerical model data such as this.

Here, the maximum value (Max_Q) of the mixing ratio (Qc/Qt) of the cloud water for the total condensed water mixing ratio is, in consideration of the climate of the Daegwallyeong region of the Korean Peninsula, instead of the cloud water mixing ratio for the total condensed water mixing ratio (Qc/Qt) has been applied to

In addition, the vertical wind speed (W) value is a reference value together with the wind direction (WD) value, and is one of the evaluation factors mainly considered in artificial expansion or artificial precipitation experiments performed in mountainous areas.

For example, the vertical wind speed (W) value, like the wind direction (WD) value, is the average of values measured between 1 km and 3 km above sea level. 1 may be assigned, and if it is less than 0, 0 may be assigned to indicate that a downdraft occurs. However, the vertical wind speed (W) value and the wind direction (WD) value are not reflected in the seeding possibility score to be described later. The reason for doing this is that, as a result of calculating the average of values measured for 6 hours for vertical wind speed (W) and comparing them, it was derived that there is no discriminatory power.

And, the depth of liquid water content in clouds (CD_L: Depth of LWC (Liquid Water Content)) is an evaluation factor for the liquid water content of clouds, which is the most important factor in the aviation test for precipitation. is the thickness. The liquid water depth value of this cloud can be calculated from the thickness of the layers with an LWC of 0.01 gm ^-2 or more. The reason for this is that the thicker the liquid water present in the cloud, the greater the seeding effect will be.

In step S120 , the apparatus for evaluating the seeding potential of the snow cloud calculates a seeding potential score by using the input numerical model data.

For example, the apparatus for evaluating the seedability of the snow cloud may calculate the seedability score TS by using the input numerical model data as shown in the following equation.

[Equation 1]

TS = S _WS + S _LWP + S _TQC + S _{MAX_Q} + S _{CD_L}

where S _WS is the score for wind speed, S _LWP is the score for the liquid water path, S _TQC is the score for cloud water temperature, S _{MAX_Q} is the score for the maximum value of the mixing ratio, and S _{CD_L} is the score for the cloud It is a score for the depth of the liquid water.

That is, the snow cloud seeding possibility evaluation device includes a wind speed (WS) value, a liquid water path (LWP) value that is a vertically integrated cloud water content, and a temperature (TQ _c ) value of cloud water. , the maximum value (Max_Q) of the mixing ratio of cloud water (Qc/Qt) and the depth of liquid water in the cloud (CD_L: Depth of LWC (Liquid Water Content)) of the total condensed water mixing ratio The score of each evaluation element may be extracted from the mapped seedability score table, and the score of each extracted evaluation element may be summed to calculate a seedability score.

For example, the seedability score table may be represented as shown in FIG. 3 .

Referring to FIG. 3 , in the seeding possibility score table, a section of each evaluation element is divided into a total of five, and each section can be assigned from 0 to 4 points at 1-point intervals. In the case of wind speed, in the prior art, the section was set to a very high value, so it is not suitable for the Korean Peninsula where the seeding effect appears even when the wind speed is weak. .

And, the score for vertical wind speed (W: vertical wind speed) and wind direction (WD: Wind Direction) is a reference value, and is represented by 0 or 1, and as described above, it is not added to the seeding possibility score.

And, in the seeding possibility score table shown in FIG. 3, the maximum value (Max_Q) of the mixing ratio (Qc/Qt) of the cloud water to the mixing ratio of the total condensed water and the liquid water depth of the cloud (CD_L: Depth of LWC (Liquid Water Content) )), each section is set using the average of the values measured at the Daegwallyeong point when performing the artificial expansion air experiment conducted in Daegwallyeong in 2018 and 2019.

In step S130, the apparatus for evaluating the seeding potential of the snow cloud calculates a seedability grade for the calculated seedability score by using the seedability grade table in which the seedability grade is mapped for each preset seedability score section.

For example, the seedability rating table may be represented as shown in FIG. 4 .

Referring to FIG. 4 , in the seedability level table, there may be a total of five seedability levels of A, B, C, D, and E.

In step S140 , the apparatus for evaluating the seedability of the snow cloud outputs the calculated seedability score and the seedability grade.

For example, the apparatus for evaluating the seedability of snow clouds may output the calculated information as a text file or output it through an output device such as a display.

The snow cloud seeding possibility evaluation apparatus according to an embodiment of the present invention as described above may determine whether to conduct the experiment by performing an evaluation using the prediction data before performing the artificial expansion aviation experiment. And, after the experiment is finished, a numerical model is established using the experimental result data, and the seeding possibility evaluation of the experimental case can be re-analyzed.

5 is a diagram schematically illustrating the configuration of a snow cloud seeding possibility evaluation apparatus according to an embodiment of the present invention.

Referring to FIG. 5 , the apparatus for evaluating snow cloud seeding potential according to an embodiment of the present invention includes a processor 10 , a memory 20 , a communication unit 30 , and an interface unit 40 .

The processor 10 may be a CPU or a semiconductor device that executes processing instructions stored in the memory 20 .

Memory 20 may include various types of volatile or non-volatile storage media. For example, the memory 20 may include ROM, RAM, or the like.

For example, the memory 20 may store instructions for performing the method for evaluating the seeding possibility of a snow cloud according to an embodiment of the present invention.

The communication unit 30 is a means for transmitting and receiving data with other devices through a communication network.

The interface unit 40 may include a network interface and a user interface for accessing a network.

On the other hand, the components of the above-described embodiment can be easily grasped from a process point of view. That is, each component may be identified as a respective process. In addition, the process of the above-described embodiment can be easily understood from the point of view of the components of the apparatus.

In addition, the technical contents described above may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc. alone or in combination. The program instructions recorded on the medium may be specially designed and configured for the embodiments or may be known and available to those skilled in the art of computer software. Examples of the computer-readable recording medium include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floppy disks. - includes magneto-optical media, and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions include not only machine language codes such as those generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like. A hardware device may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

The above-described embodiments of the present invention have been disclosed for purposes of illustration, and various modifications, changes, and additions will be possible within the spirit and scope of the present invention by those skilled in the art having ordinary knowledge of the present invention, and such modifications, changes and additions should be considered as belonging to the following claims.

10: Processor
20: memory
30: communication department
40: interface unit

Claims (10)

In the seeding possibility evaluation method of the snow cloud performed by the seeding possibility evaluation device,
Wind Direction (WD) value, vertical wind speed (W) value, wind speed (WS: Wind Speed) value, liquid water path (LWP: Liquid Water Path) value, which is the vertically integrated cloud water content, In the snow cloud including the temperature (TQc) value of cloud water, the maximum value (Max_Q) of the mixing ratio of cloud water by the mixing ratio of condensed water, and the depth of liquid water in the cloud (CD_L: Depth of LWC (Liquid Water Content)) receiving numerical model data including measurement values of a plurality of seedability evaluation factors for
For the plurality of seedability evaluation factors, the score of each evaluation factor is extracted from the seeding possibility score table in which scores are mapped for each preset section, and the score for the extracted wind speed, the score for the liquid water path, and the cloud calculating a seedability score by summing the score for the water temperature, the score for the maximum value, and the score for the liquid water depth;
calculating a seedability rating for the calculated seedability score using a seedability rating table in which a seedability rating is mapped for each preset seedability score interval; and
outputting the calculated seedability score and seedability grade;
The liquid water depth value is a method for evaluating the seeding possibility of snow clouds, characterized in that the LWC is calculated as the thickness of the layers of 0.01 gm ^-2 or more.
delete According to claim 1,
The wind direction value and the vertical wind speed value are reference values that are not applied to the calculation of the seeding possibility score,
The method for evaluating the seeding possibility of snow clouds, characterized in that the vertical wind speed value is given as 1 in the case of an updraft and 0 in the case of a downdraft.
delete delete In the snow cloud seeding possibility evaluation device,
memory to store instructions; and
A processor that executes the instructions,
The command is
Wind Direction (WD) value, vertical wind speed (W) value, wind speed (WS: Wind Speed) value, liquid water path (LWP: Liquid Water Path) value, which is the vertically integrated cloud water content, In the snow cloud including the temperature (TQc) value of cloud water, the maximum value (Max_Q) of the mixing ratio of cloud water by the mixing ratio of condensed water, and the depth of liquid water in the cloud (CD_L: Depth of LWC (Liquid Water Content)) receiving numerical model data including measurement values of a plurality of seedability evaluation factors for
For the plurality of seedability evaluation factors, the score of each evaluation factor is extracted from the seeding possibility score table in which scores are mapped for each preset section, and the score for the extracted wind speed, the score for the liquid water path, and the cloud calculating a seedability score by summing the score for the water temperature, the score for the maximum value, and the score for the liquid water depth;
calculating a seedability rating for the calculated seedability score using a seedability rating table in which a seedability rating is mapped for each preset seedability score interval; and
performing a seeding possibility evaluation method of a snow cloud comprising the step of outputting the calculated seedability score and seedability grade;
The liquid water depth value is an apparatus for evaluating snow cloud seeding potential, characterized in that the LWC is calculated as the thickness of the layers of 0.01 gm ^-2 or more.
delete 7. The method of claim 6,
The wind direction value and the vertical wind speed value are reference values that are not applied to the calculation of the seeding possibility score,
The vertical wind speed value is an apparatus for evaluating the seeding possibility of snow clouds, characterized in that 1 is given in the case of an updraft, and 0 is given in the case of a downdraft. delete delete

Images