Real-time precipitation forecasting system
A computerized method of processing data for use in weather modeling is provided. The method includes receiving, from a first data source, by a first server, microwave link data including signal attenuation information. The method also includes pre-processing, in real time, by the first server, the microwave link data, thereby producing pre-processed microwave link data. The method also includes storing the pre-processed microwave link data in a first data store. The method also includes receiving, from the first data store, by a second server, the pre-processed microwave link data. The method also includes processing, on a scheduled routine, by the second server, the pre-processed microwave link data using a data transform, thereby producing first weather data.
1. A forecasting method including performing with at least one processor, operations comprising:
selecting a first set of precipitation intensity tiles that includes a first subject precipitation intensity tile and precipitation intensity tiles surrounding the first subject precipitation intensity tile;
classifying the first subject precipitation intensity tile as associated with a type of storm and an age of the storm;
selecting a first set of wind vector tiles that corresponds to the first set of precipitation intensity tiles;
adjusting the first subject precipitation intensity tile based on the first set of wind vector tiles thereby generating an adjusted precipitation intensity for the first subject precipitation intensity tile; and
scaling the adjusted precipitation intensity based on the type of storm and the age of the storm.
2. The forecasting method of claim 1 wherein generating adjusts only the first subject precipitation intensity tile.
3. The forecasting method of claim 1 , including:
selecting a second set of precipitation tiles including a second subject precipitation tile and precipitation intensity tiles surrounding the second subject precipitation intensity tile;
classifying the second subject precipitation intensity tile as associated with a type of storm and an age of the storm;
selecting a second set of wind vector tiles that corresponds to the second set of precipitation intensity tiles;
moving precipitation intensity into and out of the second subject precipitation intensity tile based on the second set of wind vector tiles thereby generating an adjusted precipitation intensity for the second subject precipitation intensity tile; and
scaling the adjusted precipitation intensity based on classifying the second subject precipitation intensity tile.
4. The forecasting method of claim 3 , further including processing the first and second set of precipitation tiles in parallel to determine new precipitation intensities.
5. The forecasting method of claim 1 where the first set of precipitation intensity tiles includes system-generated blended precipitation intensity.
6. The forecasting method of claim 1 further including generating the first wind vector tiles.
7. The forecasting method of claim 1 further including generating the first set of precipitation intensity tiles and first wind vector tiles in parallel.
8. The forecasting method of claim 1 where the first wind vector tiles include one or more of NWP wind vectors, radar wind vectors, and ground station wind vectors.
9. The forecasting method of claim 1 further including generating the wind vector tiles by blending wind vectors from two or more sources.
10. The forecasting method of claim 1 further including reusing the type of storm and age of storm classification.
11. The forecasting method of claim 1 further including reusing the first wind vector tiles.
12. The forecasting method of claim 1 further including forecasting wind vectors corresponding to a time step of forecast precipitation.
13. The forecasting method of claim 1 wherein the storm type and age classifications include convective or stratiform and one or rising, mature, and decaying.
14. The forecasting method of claim 1 wherein scaling the adjusted precipitation intensity includes selecting an intensity curve corresponding to the type of storm, determining a location on an intensity curve, and scaling based on a determined location and/or a time step along the curve from a determined location.
15. A method for weather forecasting including performing, with at least one processor, operations comprising:
retrieving pre-processed data from each of multiple databases wherein the pre-processed data includes at least one set of precipitation intensity tiles and at least one set of wind vector tiles;
selecting a first set of precipitation intensity tiles that includes a first subject precipitation intensity tile and precipitation intensity tiles surrounding the subject first precipitation intensity tile;
selecting a second set of precipitation intensity tiles that includes a second subject precipitation intensity tile and precipitation intensity tiles surrounding the second subject precipitation intensity tile;
selecting wind vectors; and
performing in parallel:
adjusting the first and second subject precipitation intensity tiles based on the wind vectors to generate first and second forecast precipitation intensities, respectively;
classifying the first and second subject precipitation intensity tiles as associated with type of storm and age of a storm; and
scaling the first and second forecast precipitation intensities based on the type of storm and age of storm to generate first and second scaled forecast precipitation intensities and associating the first and second scaled forecast precipitation intensity tiles with first and second forecast tiles, respectively.
16. Method of claim 15 , wherein selecting tile sets includes selecting multiple palettes of precipitation intensity tiles surrounding each of first and second subject precipitation tiles and a wind vector tile corresponding to each selected precipitation intensity tile.
17. Method of claim 15 , further including:
collecting weather parameter data concurrently from each multiple sources;
pre-processing collected data from each of the multiple sources using separate pre-processing to generate data for use in forecasting, including each pre-processing informing upon completion; and
saving pre-processed data to each of multiple data stores.
18. A forecasting apparatus including at least one processor configured to perform operations comprising:
selecting a first set of precipitation intensity tiles that includes a first subject precipitation intensity tile and precipitation intensity tiles surrounding the first subject precipitation intensity tile;
classifying the first subject precipitation intensity tile as associated with a type of storm and an age of the storm;
selecting a first set of wind vector tiles that corresponds to the first set of precipitation intensity tiles;
adjusting the first subject precipitation intensity tile based on the first set of wind vector tiles thereby generating an adjusted precipitation intensity for the first subject precipitation intensity tile; and
scaling the adjusted precipitation intensity based on the type of storm and the age of the storm.
19. The forecasting apparatus of claim 18 wherein generating adjusts only the first subject precipitation intensity tile.
20. The forecasting apparatus of claim 18 , wherein the processor is further configured to perform operations comprising:
selecting a second set of precipitation tiles including a second subject precipitation tile and precipitation intensity tiles surrounding the second subject precipitation intensity tile;
classifying the second subject precipitation intensity tile as associated with a type of storm and an age of the storm;
selecting a second set of wind vector tiles that corresponds to the second set of precipitation intensity tiles;
moving precipitation intensity into and out of the second subject precipitation intensity tile based on the second set of wind vector tiles thereby generating an adjusted precipitation intensity for the second subject precipitation intensity tile; and
scaling the adjusted precipitation intensity based on classifying the second subject precipitation intensity tile.
21. The forecasting method of claim 20 , wherein the processor is configured to process the first and second set of precipitation tiles in parallel to determine new precipitation intensities.
22. The forecasting apparatus of claim 18 where the first set of precipitation intensity tiles includes system-generated blended precipitation intensity.
23. The forecasting apparatus of claim 18 wherein the processor is further configured to generate the first wind vector tiles.
24. The forecasting apparatus of claim 18 wherein the processor is further configured to process the first set of precipitation intensity tiles and first wind vector tiles in parallel.
25. The forecasting apparatus of claim 18 where the first wind vector tiles include one or more of NWP wind vectors, radar wind vectors, and ground station wind vectors.
26. The forecasting apparatus of claim 18 wherein the processor is further configured to generate the wind vector tiles by blending wind vectors from two or more sources.
27. The forecasting apparatus of claim 18 wherein the processor is further configured to reuse the type of storm and age of storm classification.
28. The forecasting apparatus of claim 18 wherein the processor is further configured to reuse the first wind vector tiles.
29. The forecasting apparatus of claim 18 wherein the processor is further configured to generate wind vectors corresponding to a time step of forecast precipitation.
30. The forecasting apparatus of claim 18 wherein the storm type and age classifications include convective or stratiform and one or rising, mature, and decaying.
31. The forecasting apparatus of claim 18 wherein scaling the adjusted precipitation intensity includes selecting an intensity curve corresponding to the type of storm, determining a location on an intensity curve, and scaling based on a determined location and/or a time step along the curve from a determined location.
32. An apparatus for weather forecasting including at least one processor configured to perform operations comprising:
retrieving pre-processed data from each of multiple databases wherein the pre-processed data includes at least one set of precipitation intensity tiles and at least one set of wind vector tiles;
selecting a first set of precipitation intensity tiles that includes a first subject precipitation intensity tile and precipitation intensity tiles surrounding the subject first precipitation intensity tile;
selecting a second set of precipitation intensity tiles that includes a second subject precipitation intensity tile and precipitation intensity tiles surrounding the second subject precipitation intensity tile;
selecting wind vectors; and
performing in parallel:
adjusting the first and second subject precipitation intensity tiles based on the wind vectors to generate first and second forecast precipitation intensities, respectively;
classifying the first and second subject precipitation intensity tiles as associated with type of storm and age of a storm; and
scaling the first and second forecast precipitation intensities based on the type of storm and age of storm to generate first and second scaled forecast precipitation intensities and associating the first and second scaled forecast precipitation intensity tiles with first and second forecast tiles, respectively.
33. Apparatus of claim 32 , wherein selecting tile sets includes selecting multiple palettes of precipitation intensity tiles surrounding each of first and second subject precipitation tiles and a wind vector tile corresponding to each selected precipitation intensity tile.
34. Apparatus of claim 32 , wherein the processor is further configured to perform operations:
collecting weather parameter data concurrently from each multiple sources;
pre-processing collected data from each of the multiple sources using separate pre-processing to generate data for use in forecasting, including each pre-processing informing upon completion; and
saving pre-processed data to each of multiple data stores.