Weather forecasting systems and methods

• US 8,818,029 B1
• Filed: 10/24/2011
• Issued: 08/26/2014
• Est. Priority Date: 05/27/2010
• Status: Active Grant

• Current Assignee: Board of Trustees of The University of Alabama (University of Alabama System)
• Original Assignee: Board of Trustees of The University of Alabama (University of Alabama System)
• Inventors: Mecikalski, John, MacKenzie, Wayne M. Jr., Walker, John Robert
• Primary Examiner(s): Bitar, Nancy
• Application Number:
  US13/280,021
• Time in Patent Office: 1,037 Days
• Field of Search: None
• US Class Current: 382/103
• CPC Class Codes: G01W 1/10 Devices for predicting weather conditions computers per se G06; display devices G09
• CPC Class Codes: G06V 20/13 Satellite images

Abstract

A weather forecasting system has weather forecasting logic that receives raw image data from a satellite. The raw image data has values indicative of light and radiance data from the Earth as measured by the satellite, and the weather forecasting logic processes such data to identify cumulus clouds within the satellite images. For each identified cumulus cloud, the weather forecasting logic applies interest field tests to determine a score indicating the likelihood of the cumulus cloud forming precipitation and/or lightning in the future within a certain time period. Based on such scores, the weather forecasting logic predicts in which geographic regions the identified cumulus clouds will produce precipitation and/or lighting within during the time period. Such predictions may then be used to provide a weather map thereby providing users with a graphical illustration of the areas predicted to be affected by precipitation within the time period.

Claims

1. A weather forecasting system, comprising:

memory for storing satellite image data; and

logic configured to identify a first cloud object within a first image of the satellite image data, the first object representing a cumulus cloud that is not producing precipitation, the logic configured to identify, within a second image of the satellite image data, a second cloud object representing the cumulus cloud based on the first cloud object identified in the first image, the logic configured to compare the first and second cloud objects to make a prediction whether the cumulus cloud represented by the first and second cloud objects will produce precipitation or lightning in the future, wherein the first cloud object is associated with a geographic region different than a geographic region associated with the second cloud object,

wherein the second image has a plurality of pixels, each of the pixels representing a respective geographic region, wherein the logic is configured to analyze the pixels of the second image to identify cumulus cloud pixels within the second image, each cumulus cloud pixel indicating that at least a portion of a cumulus cloud is within the geographic region associated with the respective cumulus cloud pixel, wherein the logic is configured to cluster a plurality of contiguous cumulus cloud pixels in the second image to define the second cloud object, and wherein the logic is configured to compare the first and second cloud objects for determining whether the cumulus cloud is represented by both the first cloud object and the second cloud object.

2. The system of claim 1, wherein the logic is configured to compare reflectivity and infrared values associated with the first and second cloud objects, and wherein the prediction is based on comparisons of the reflectivity and infrared values.

3. The system of claim 1, wherein the logic further configured to define, based on the prediction, weather forecasting data indicative of geographic regions likely to receive precipitation or lightning from the cumulus cloud in the future.

4. The system of claim 1, wherein the first and second images are both infrared images.

5. The system of claim 1, wherein the logic is configured to identify a pixel of the first image representing a coldest region of the cumulus cloud, wherein the logic is configured to identify a pixel of the second image representing a coldest region of the cumulus cloud, and wherein the logic is configured to compare the pixel of the first image representing the coldest region of the cumulus cloud and the pixel of the second image representing the coldest region of the cumulus cloud.

6. The system of claim 1, wherein the first image is based on light at a first wavelength, and wherein the second image is based on light at a second wavelength different than the first wavelength.

7. The system of claim 1, wherein the logic is configured to perform a plurality of interest field checks on the first and second cloud objects, wherein for each of the interest field checks the logic is configured to mathematically combine a respective pixel value of the first cloud object and a respective pixel value of the second cloud object to provide a combined value and to compare the combined value to a threshold.

8. The system of claim 1, wherein the logic is configured to compare the first and second cloud objects to predict whether the cumulus cloud represented by the first and second cloud objects will produce precipitation and lightning in the future.

21. The system of claim 1, wherein the logic is further configured to compare the first and second cloud objects, in response to a determination that the same cumulus cloud is represented by both the first cloud object and the second cloud object, for determining a score indicative of a likelihood that the cumulus cloud will produce precipitation or lightning in the future.

22. The system of claim 1, wherein the logic is configured to compare a shape of the cumulus cloud as defined by the first cloud object to a shape of the cumulus cloud as defined by the first cloud object.

23. The system of claim of claim 22, wherein the logic is configured to compare a size of the cumulus cloud as defined by the first cloud object to a size of the cumulus cloud as defined by the second cloud object.

9. A weather forecasting method, comprising:

storing, in memory, satellite image data;

identifying a first cloud object within a first image of the satellite image data, the first cloud object representing a cumulus cloud that is not producing precipitation;

associating the first cloud object with a first geographic region;

identifying a second cloud object within a second image of the satellite image data based on the identifying the first cloud object, the second cloud object representing the cumulus cloud;

associating the second cloud object with a second geographic region different than the first geographic region, wherein the second image has a plurality of pixels, each of the pixels representing a respective portion of the second geographic region;

comparing the first and second cloud objects;

predicting whether the cumulus cloud will produce precipitation or lightning in the future based on the comparing;

analyzing the pixels of the second image;

identifying cumulus cloud pixels within the second image based on the analyzing, each cumulus cloud pixel indicating that at least a portion of a cumulus cloud is within a geographic region associated with the respective cumulus cloud pixel;

clustering a plurality of contiguous cumulus cloud pixels in the second image to define the second cloud object; and

determining whether the cumulus cloud is represented by both the first cloud object and the second cloud object based on the comparing.

10. The method of claim 9, wherein the comparing comprises comparing reflectivity and infrared values associated with the first and second cloud objects.

11. The method of claim 9, wherein the first and second images are both infrared images.

12. The method of claim 9, further comprising:

identifying a pixel of the first image representing a coldest region of the cumulus cloud; and

identifying a pixel of the second image representing a coldest region of the cumulus cloud, wherein the comparing comprises comparing the pixel of the first image representing the coldest region of the cumulus cloud and the pixel of the second image representing the coldest region of the cumulus cloud.

13. The method of claim 9, wherein the first image is based on light at a first wavelength, and wherein the second image is based on light at a second wavelength different than the first wavelength.

14. The method of claim 9, further comprising:

performing a plurality of interest field checks on the first and second cloud objects; and

for each of the interest field checks, mathematically combining a respective pixel value of the first cloud object with a respective pixel value of the second cloud object, thereby providing a combined value, and comparing the combined value to a threshold.

15. The method of claim 9, further comprising:

tracking the cumulus cloud over time; and

defining, based on the predicting and the tracking, weather forecasting data indicative of geographic regions predicted to receive precipitation from the cumulus cloud in the future.

16. The method of claim 15, further comprising displaying the weather forecasting data.

17. The method of claim 9, wherein the predicting comprises predicting whether the cumulus cloud will produce precipitation and lightning in the future based on the comparing.

18. The method of claim 9, further comprising displaying an indication via an output interface based on the predicting.

19. The system of claim 9, wherein the comparing comprises comparing a shape of the cumulus cloud as defined by the first cloud object to a shape of the cumulus cloud as defined by the second cloud object.

20. The system of claim 19, wherein the comparing comprises comparing a size of the cumulus cloud as defined by the first cloud object to a size of the cumulus cloud as defined by the second cloud object.