Weather severity and characterization system
View Patent ↗A method of presenting weather phenomenon information including receiving weather data. At least one weather phenomenon represented by the weather data is identified. A plurality of current parameters related to the current state of the at least one weather phenomenon is determined. A plurality of historical parameters corresponding to one or more previous states of the at least one weather phenomenon is associated with the current state of the at least one weather phenomenon if at least one previous state of the at least one weather phenomenon has been identified. A plurality of forecasted parameters for the at least one weather phenomenon is calculated. Characteristics of the at least one weather phenomenon based on at least a first subset of the current parameters, the historical parameters, and the forecasted parameters are displayed.
1. A method of organizing weather phenomena information using a computing system comprising at least one computer, the method comprising:
(a) associating, by the at least one computer, a first dimension of a multi-dimensional database with one or more instances of weather phenomena, wherein the one or more instances of weather phenomena are identified using weather data obtained from a first type of weather data source;
(b) associating, by the at least one computer, a second dimension of the multi-dimensional database with a plurality of parameters that characterize the one or more instances of the weather phenomena, wherein the plurality of parameters are obtained using weather data obtained from the first type of weather data source and at least one second type of weather data source;
(c) associating, by the at least one computer, a third dimension of the multi-dimensional database with a plurality of storm instance-relative times, wherein the plurality of storm instance-relative times corresponds to at least the present time and one or more future times;
(d) associating, by the at least one computer, a fourth dimension of the multi-dimensional database with one or more absolute times, wherein the absolute times correspond to temporal snapshots of information contained in the first, second, and third dimensions; and
(e) associating, by the at least one computer, a fifth dimension of the multi-dimensional database with a plurality of platforms, systems, or sites of the first type of weather data source.
2. The method of claim 1 , wherein the weather phenomena includes convective storms.
3. The method of claim 1 , further comprising:
(f) reducing the dimensionality of the multi-dimensional database by combining duplicate instances of the one or more instances of the weather phenomenon identified using different data stations from the plurality of data stations, and aggregating information corresponding to the one or more instances of the weather phenomenon in the multi-dimensional database.
4. The method of claim 3 , wherein the reducing of step (f) includes normalizing the weather data from the different platforms, systems, or sites of the first type of weather data source.
5. The method of claim 1 , wherein the platforms, systems, or sites of the first type of weather data source include weather radar stations.
6. The method of claim 1 , wherein the wherein the plurality of storm instance-relative times further include one or more past times.
7. The method of claim 1 , wherein the plurality of parameters includes one or more severity indices.
8. The method of claim 7 , wherein the one or more severity indices include at least one of lightning severity, flood severity, hail severity, tornado severity, and wind severity.
9. The method of claim 8 , wherein the parameters include a composite severity index generated from at least two of the severity indices.
10. A method of organizing weather phenomena information using a computing system comprising at least one computer, the method comprising:
(a) associating, by the at least one computer, a first dimension of a multi-dimensional database with one or more unique instances of weather phenomena, wherein the one or more unique instances of weather phenomena are identified using weather data obtained from a first type of weather data source;
(b) associating, by the at least one computer, a second dimension of the multi-dimensional database with a plurality of parameters that characterize the one or more unique instances of the weather phenomena, wherein the plurality of parameters are obtained using weather data obtained from the first type of weather data source and at least one second type of weather data source;
(c) associating, by the at least one computer, a third dimension of the multi-dimensional database with a plurality of storm instance-relative times, wherein the plurality of storm instance-relative times corresponds to at least the present time and one or more future times;
(d) associating, by the at least one computer, a fourth dimension of the multi-dimensional database with one or more absolute times, wherein the absolute times correspond to temporal snapshots of information contained in the first, second, and third dimensions.
11. The method of claim 10 , wherein unique instances of the one or more weather phenomenon are formed by combining separate identifications of the same instance of the one or more weather phenomena using weather data received from different platforms, systems, or sites of the first type of weather data source.
12. The method of claim 11 , wherein the combining includes normalizing the weather data from the different platforms, systems, or sites of the first type of weather data source corresponding to the same instance of the one or more instances of the weather phenomena.
13. The method of claim 10 , wherein the platforms, systems, or sites of the first type of weather data source include weather radar stations.
14. The method of claim 10 , wherein the wherein the plurality of storm instance relative times further include one or more past times.
15. The method of claim 10 , wherein the one or more unique instances of the weather phenomena include convective storms.
16. A method of characterizing weather phenomena using a computing system comprising at least one computer, the method comprising:
(a) assimilating, by the at least one computer, in a multi-dimensional database for instances of one or more weather phenomena identified using weather data obtained from a first data station of a first type of weather data source, a plurality of parameters characterizing the instances of the one or more weather phenomena for a plurality of instance-relative times;
(b) forming, by the at least one computer, a plurality of temporal snapshots of the data assimilated in step (a); and
(c) aggregating, by the at least one computer, the plurality of temporal snapshots for a plurality of platforms, systems, or sites of the first type of weather source data, wherein the plurality of parameters includes a set of severity indices for each instance of the one or more weather phenomenon, each severity index corresponding to a normalized indication of an impact to at least one of property, population, and infrastructure from a different threat associated with the one or more weather phenomena, the set of severity indices including a composite severity index comprising an aggregate representation of at least two of the other severity indices.
17. The method of claim 16 , wherein the dimension of the multi-dimensional database in step (a) is three.
18. The method of claim 16 , wherein the forming of step (b) increases the dimension of the multi-dimensional database by one.
19. The method of claim 16 , wherein the aggregating of step (c) increases the dimension of the multi-dimensional database by one.
20. The method of claim 16 , wherein the plurality of platforms, systems, or sites of the first type of weather data source includes weather radar stations.
21. The method of claim 16 , wherein the weather phenomena include convective storms.
22. The method of claim 21 , wherein the convective storms include a thunderstorm.
23. An article of manufacture for organizing weather phenomena information, the article of manufacture comprising a computer-readable storage medium holding computer-executable instructions for performing a method comprising:
(a) associating a first dimension of a multi-dimensional database with one or more instances of weather phenomena, wherein the one or more instances of weather phenomena are identified using weather data obtained from a first type of weather data source;
(b) associating a second dimension of the multi-dimensional database with a plurality of parameters that characterize the one or more instances of the weather phenomena, wherein the plurality of parameters are obtained using weather data obtained from the first type of weather data source and at least one second type of weather data source;
(c) associating a third dimension of the multi-dimensional database with a plurality of storm instance-relative times, wherein the plurality of storm instance-relative times corresponds to at least the present time and one or more future times;
(d) associating a fourth dimension of the multi-dimensional database with one or more absolute times, wherein the absolute times correspond to temporal snapshots of information contained in the first, second, and third dimensions; and
(e) associating a fifth dimension of the multi-dimensional database with a plurality of platforms, systems, or sites of the first type of weather data source.
24. The article of manufacture of claim 23 , further comprising:
(f) reducing the dimensionality of the multi-dimensional database by combining duplicate instances of the one or more instances of the weather phenomenon identified using different data stations from the plurality of data stations, and aggregating information corresponding to the one or more instances of the weather phenomenon in the multi-dimensional database.
25. The article of manufacture of claim 23 , wherein the plurality of parameters includes a set of severity indices, the set of severity indices including a composite severity index generated from at least two of the other severity indices.