Atmosphere condition prediction method

Details Atmosphere condition prediction method Atmosphere condition prediction method

2003-05-29

2004-10-05

McElheny, Jr., Donald (Department: 2857)

Data processing: measuring, calibrating, or testing

Measurement system in a specific environment

Earth science

Reexamination Certificate

active

06801856

ABSTRACT:

TECHNICAL FIELD
This invention relates to a gas status forecast method, one designed to be capable of determining a gas status (wind direction, wind speed, etc.), which is detailed in terms of space and time, accurately in a short time based on meteorological observation data which are rough in terms of space and time. By utilizing the gas status (wind speed site data) determined by the present invention, the diffusion status (diffusion range, diffusion concentration) of a diffused substance released from a diffusion source can be forecast by computation.
BACKGROUND ART
A diffusion status forecast system is under development which, if a radioactive substance is released to the outside by accident from facilities dealing with nuclear substances, forecasts the diffusion range of the radioactive substance and the concentrations of the radioactive substance at different locations, and predicts areas which may be endangered by the radioactive substance.
In this diffusion status forecast system, a gas status is forecast by computation, and then a diffusion status is forecast based on the gas status.
In more detail, the diffusion status of the radioactive substance is investigated as follows: First, partial differential equations, which analyze atmospheric phenomena, are solved based on meteorological observation data such as meteorological GPV (Grid Point Value) data and data from AMEDAS, etc. The solutions give wind directions and wind speeds at many evaluation locations (grip point positions) at constant time intervals (e.g., 10-minute intervals) during the period of time from the instant of occurrence of an event (e.g., release of a nuclear substance to the outside) until a point in time which is a predetermined time after the occurrence of the event. That is, a gas status representing wind speed site data at constant time intervals is determined.
Then, the concentration and properties of the diffused substance released, and the above wind speed site data are substituted into a diffusion equation for computing the diffused state of the substance, thereby computing the concentrations of the diffused substance at the respective grid point positions at the respective time intervals.
In this manner, the diffusion range of the radioactive substance released, and the concentrations of the radioactive substance at the different locations can be forecast.
The meteorological observation data, for example, meteorological GPV data, are delivered online from th Meteorological Business Support Center very 12 hours. The meteorological GPV data show meteorological data (wind velocity vectors (wind direction, wind speed), atmospheric pressure, temperature, moisture content) at a plurality of elevations (the elevations at 20 points from the earth's surface up to 10 Km high in the sky) at locations (called “parent grid point positions”) where a plurality of latitudinal virtual lines, which extend along a north-south direction on the earth's surface and which are spaced from each other in an east-west direction on the earth's surface by a prescribed distance (2 Km), cross a plurality of longitudinal virtual lines, which extend along the east-wet direction on the earth's surface and which are spaced from each other in the north-south direction on the earth's surface by a prescribed distance (2 Km). In addition, the meteorological GPV data are delivered online as the meteorological data at the respective parent grid point positions which comprise a total of 51 hours of data obtained at 3-hour intervals, such as at the start of delivery, 3 hours after delivery, 6 hours after delivery, and 9 hours after delivery.
The above-mentioned meteorological data at the parent grid point positions, as the meteorological GPV data, are presented at a long distance of 2 Km between the parent grid point positions in terms of space, and at a long interval of 3 hours in terms of time. Thus, the diffusion concentrations of the diffused substance cannot be computed only based on the gas status (wind direction, wind speed) data shown by the meteorological data at these parent grip point positions.
Hence, there is need to determine the gas status (wind direction, wind speed, etc.), which is detailed in terms of time as well as space, from the meteorological observation data rough spatially and rough in terms of time, by performing computations according to partial differential equations for analyzing atmospheric phenomena.
A description will now be presented of a conventional gas status forecast method which determines a gas status (wind direction, wind speed, etc.), which is detailed in terms of space and time, from the meteorological observation data rough in terms of space and time, by performing computations using partial differential equations for analyzing atmospheric phenomena.
According to the conventional technology, as shown in
FIG. 8
, child grid point positions (indicated by □ and ▪ in the drawing) are set between parent grid point positions (indicated by ◯ in the drawing) set in calculation areas to be calculated (specific areas preset in the earth's surface). The parent grid point positions, as stated earlier, are arranged at the locations where a plurality of latitudinal virtual lines, which extend along the north-south direction on the earth's surface and which are spaced from each other in the east-west direction on the earth's surface by a distance of 2 Km, cross a plurality of longitudinal virtual lines, which extend along the east-wet direction on the earth's surface and which are spaced from each other in the north-south direction on the earth's surface by a distance of 2 Km.
The child grid point positions, on the other hand, are arranged at the locations where a plurality of latitudinal virtual lines, which extend along the north-south direction on the earth's surface and which are spaced from each other in the east-west direction on the earth's surface by a constant distance (50 m), cross a plurality of longitudinal virtual lines, which extend along the east-wet direction on the earth's surface and which are spaced from each other in the north-south direction on the earth's surface by a constant distance (50 m).
In
FIG. 8
, only four of the parent grid point positions are shown, but these parent grid point positions are set so as to be distributed and arranged all over the calculation area. In
FIG. 8
, moreover, the child grid point positions are shown only in the area surrounded by the four parent grid point positions, but these child grid point positions are set so as to be distributed and arranged all over the calculation area.
As an example, a case in which computation was started 10 minutes after the time of online delivery of the meteorological GPV data will be described, as shown in FIG.
9
.
[1] Computation of meteorological data at the start of computation is carried out in the following manner:
[1-1] The meteorological data at the parent grid point position I are obtained by time interpolation computation of the meteorological GPV data at the parent grid point position I 10 minutes before the start of computation (i.e., the time of delivery of meteorological GPV data), and the meteorological GPV data at the parent grid point position I 2 hours and 50 minutes after the start of computation (i.e., 3 hours after delivery of meteorological GPV data). The time interpolation computation is a method for obtaining data according to time, based on the meteorological GPV data at the time of delivery and the meteorological GPV data 3 hours after delivery, such that the data at midpoint in terms of time (i.e., 1 hour and 30 minutes after delivery) is the average of both meteorological GPV data, the data at a point in time nearer the time of delivery is closer to the meteorological GPV data at the time of delivery, and the data at a point in time nearer the point in time 3 hours after delivery is closer to the meteorological GPV data obtained 3-hours after delivery.
Similarly, the meteorologic

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