System and method for forecasting probability of precipitation

Abstract

A system and method are disclosed for forecasting probability of precipitation values and most probable precipitation amount values for, preferably, three hour time period increments starting from the present hour through approximately hour 96 (i.e., four days) or beyond. The values are recalculated at the beginning of each hour, based upon existing forecasting information and meteorological data. The values are communicated to end users through a communications channel such as the Internet.

What is claimed is: 
     
       1. A system for calculating and communicating probability of precipitation forecasts for periods less than six hours using existing forecasting information, the system comprising:
 storage means for storing location-specific probability forecasting information; 
 a precipitation forecasting system including processing means for computing a probability of precipitation value from the forecast information for any time period interval, T, in a pre-set time period, t, wherein the precipitation forecasting system uses artificial intelligence to compute probability of precipitation values for time period intervals of length T in pre-set time periods of length t based on:
 a number of time periods within the time period interval of length T wherein a forecasted precipitation amount is a trace amount;   a number of time periods within the time period interval of length T wherein a forecasted precipitation amount is greater than or equal to a pre-set amount;   a probability of precipitation value for the pre-set time period of length t;   a probability of precipitation value for a next consecutive time period of length t; and   a probability of precipitation value for a previous consecutive time period of length t; and   
 a communications subsystem for communicating the probability of precipitation value via at least one communications channel, 
 wherein T<6 hours and t≥6 hours. 
 
     
     
       2. The system according to  claim 1 , wherein T=3 hours and t=96 hours. 
     
     
       3. The system according to  claim 1 , wherein the probability of precipitation value are is not fixed to a specific time, but are is recalculated to a present time. 
     
     
       4. The system according to  claim 1 , further comprising manipulation means for allowing a system operator to manually adjust the probability of precipitation value and the most probable precipitation amount value. 
     
     
       5. The system according to  claim 1 , wherein the storage means is a networked computer containing a digital database containing the location-specific probability forecasting information. 
     
     
       6. The system according to  claim 1 , wherein the processing means comprises a computer executing a probability forecast model. 
     
     
       7. The system according to  claim 1 , wherein the communications subsystem is a computer server connected to a network, and wherein the at least one communications channel comprises one or more web pages having the probability of precipitation value and the most probable precipitation amount value upon receiving a request from a remote client connected to the network. 
     
     
       8. The system according to  claim 1 , wherein the probability of precipitation forecast is the a current three-hour probability forecast value determined from:
   ½*(POP-3 X +POP-3 Y ),
 
 
       where POP-3 X  is a value from between 10 and 90, inclusively, and POP-3 Y  is determined from the formula:
   POP-3 Y =a*(POP-6 C )+b*(POP-6 (C+1) ) 
 
       where: 0≤a≤1 and 0≤b≤1 and POP-6 C  is the a six-hour probability of precipitation forecast value for the a current six-hour time interval already stored in the storage means and POP-6 (C+1)  is the a next consecutive six-hour time interval also already stored in the storage means. 
     
     
       9. The system according to  claim 1 , wherein the probability of precipitation forecast is the a current three-hour probability forecast value determined from:
   ½*(POP-3 X +POP-3 Y ),
 
 
       where POP-3 X  is a value from between 10 and 90, inclusively, and POP-3 Y  is determined from the formula:
   POP-3 Y =a*(POP-6 C )+b*(POP-6 (C−1) ) 
 
       where: 0≤a≤1 and 0≤b≤1 and POP-6 C  is the a six-hour probability of precipitation forecast value for the a current six-hour time interval already stored in the storage means and POP-6 (C−1)  is the a previous consecutive six-hour time interval also already stored in the storage means. 
     
     
       10. The system according to  claim 1 , wherein the probability of precipitation forecast is the a current three-hour probability forecast value determined from:
   ½*(POP-3 X +POP-3 Y ),
 
 
       where POP-3 X  is a value from between 10 and 90, inclusively, and POP-3 Y  is determined from the formula:
   POP-3 Y =a*max(POP-6 C ,POP-6 (C−1) ) 
 
       where: 0≤a≤1 and POP-6 C  is the a six-hour probability of precipitation forecast value for the a current six-hour time interval already stored in the storage means and POP-6 (C−1)  is the a previous consecutive six-hour time interval also already stored in the storage means. 
     
     
       11. The system according to  claim 1 , wherein in addition to the probability of precipitation forecast, also calculated are probability forecasts for specific types of precipitation, including but not limited to, the selected from one of a probability of rain, the a probability of snow, the a probability of ice, and the a probability of thunderstorms. 
     
     
       12. The system according to  claim 1 , wherein most probable precipitation amount values are calculated for some or all of the time period intervals T. 
     
     
       13. A system for calculating and communicating probability of precipitation forecasts for periods that are not fixed to specific pre-set times using existing forecasting information, the system comprising:
 storage means for storing location-specific probability forecasting information; 
 a precipitation forecasting system including processing means for computing a probability of precipitation value from the forecast information for any time period interval, T, in a pre-set time period, t, wherein the precipitation forecasting system uses artificial intelligence to compute probability of precipitation values for time period intervals of length T in the pre-set time periods of length t based on:
 a number of time periods within the time period interval of length T wherein a forecasted precipitation amount is a trace amount;   a number of time periods within the time period interval of length T wherein a forecasted precipitation amount is greater than or equal to a pre-set amount;   a probability of precipitation value for the pre-set time period of length t;   a probability of precipitation value for a next consecutive time period of length t; and   a probability of precipitation value for a previous consecutive time period of length t; and   
 a communications subsystem for communicating the probability of precipitation value via at least one communications channel, 
 wherein the probability of precipitation value are is not fixed to a specific pre-set time, but are is recalculated to a present time. 
 
     
     
       14. The system according to  claim 13 , wherein T<6 hours and t≥6 hours. 
     
     
       15. The system according to  claim 13 , wherein T=3 hours and t=96 hours. 
     
     
       16. The system according to  claim 13 , further comprising manipulation means for allowing a system operator to manually adjust the probability of precipitation value and the most probable precipitation amount value. 
     
     
       17. The system according to  claim 13 , wherein the processing means comprises a computer executing a probability forecast model. 
     
     
       18. The system according to  claim 13 , wherein the communications subsystem is a computer server connected to a network, and wherein the at least one communications channel comprises one or more web pages having the probability of precipitation value and the most probable precipitation amount value upon receiving a request from a remote client connected to the network. 
     
     
       19. The system according to  claim 13 , wherein the probability of precipitation forecast is the a current three-hour probability forecast value determined from:
   ½*(POP-3 X +POP-3 Y ),
 
 
       where POP-3 X  is a value from between 10 and 90, inclusively, and POP-3 Y  is determined from the formula:
   POP-3 Y =a*(POP-6 C )+b*(POP-6 (C+1) ) 
 
       where: 0≤a≤1 and 0≤b≤1 and POP-6 C  is the a six-hour probability of precipitation forecast value for the current six-hour time interval already stored in the storage means and POP-6 (C+1)  is the a next consecutive six-hour time interval also already stored in the storage means. 
     
     
       20. The system according to  claim 13 , wherein the probability of precipitation forecast is the a current three-hour probability forecast value determined from:
   ½*(POP-3 X +POP-3 Y ),
 
 
       where POP-3 X  is a value from between 10 and 90, inclusively, and POP-3 Y  is determined from the formula:
   POP-3 Y =a*(POP-6 C )+b*(POP-6 (C−1) ) 
 
       where: 0≤a≤1 and 0≤b≤1 and POP-6 C  is the a six-hour probability of precipitation forecast value for the current six-hour time interval already stored in the storage means and POP-6 (C−1)  is the a previous consecutive six-hour time interval also already stored in the storage means. 
     
     
       21. The system according to  claim 13 , wherein the probability of precipitation forecast is the a current three-hour probability forecast value determined from:
   ½*(POP-3 X +POP-3 Y ),
 
 
       where POP-3 X  is a value from between 10 and 90, inclusively, and POP-3 Y  is determined from the formula:
   POP-3 Y =a*max(POP-6 C ,POP-6 (C−1) ) 
 
       where: 0≤a≤1 and POP-6 C  is the six-hour probability of precipitation forecast value for the current six-hour time interval already stored in the storage means and POP-6 (C−1)  is the previous consecutive six-hour time interval also already stored in the storage means. 
     
     
       22. The system according to  claim 13 , wherein in addition to the probability of precipitation forecast, also calculated are probability forecasts for specific types of precipitation, including but not limited to, the selected from one of a probability of rain, the a probability of snow, the a probability of ice, and the a probability of thunderstorms. 
     
     
       23. The system according to  claim 13 , wherein most probable precipitation amount values are calculated for some or all of the time period intervals T. 
     
     
       24. A system for calculating and communicating probability of precipitation forecasts using existing forecasting information, the system comprising:
 a precipitation forecasting system including: 
 a probability of precipitation forecast model for computing a probability of precipitation value for a time interval, T, within a pre-set time period, t, wherein T<6 hours and t≥6 hours, and wherein the probability of precipitation model uses artificial intelligence to compute probability of precipitation values for the time intervals of length T in pre-set time periods of length t based on:
 a number of time periods within the time interval of length T wherein a forecasted precipitation amount is a trace amount; 
 a number of time periods within the time interval of length T wherein a forecasted precipitation amount is greater than or equal to a pre-set amount; 
 a probability of precipitation value for the pre-set time period of length t; 
 a probability of precipitation value for a next consecutive time period of length t; and 
 a probability of precipitation value for a previous consecutive time period of length t; 
 
 a most probable precipitation amount forecast model for computing a precipitation amount value corresponding to each probability of precipitation value; and 
 a communications device for communicating the probability of precipitation and precipitation amount values electronically to a remote requester. 
 
     
     
       25. The system according to  claim 24 , wherein T=3 hours and t=96 hours. 
     
     
       26. The system according to  claim 24 , wherein the probability of precipitation value are is not fixed to a specific time, but are is recalculated to the present time. 
     
     
       27. The system according to  claim 24 , wherein in addition to the probability of precipitation forecast, also calculated are probability forecasts for specific types of precipitation, including but not limited to, the selected from one of a probability of rain, the a probability of snow, the a probability of ice, and the a probability of thunderstorms. 
     
     
       28. The system according to  claim 24 , wherein the communications device is a network server connected to the Internet having a web page generator for sending web content in response to a request from a client computer connected to the Internet. 
     
     
       29. The system according to  claim 24 , wherein the communications device is one of a wired or wireless telephony system, a pager, radio or television broadcast system and a hardcopy printout. 
     
     
       30. A computer-implemented method of calculating probability of precipitation and most probable amount of precipitation forecasts for selected time periods and locations and communicating the same to end users, comprising the steps of, at a precipitation forecasting system:
 (a) storing probability of precipitation values from meteorological forecast models; 
 (b) calculating, by the precipitation forecasting system, a location-specific probability of precipitation value for each consecutive time period intervals, T, contained within the pre-set time period, t, wherein the precipitation forecasting system uses artificial intelligence to compute probability of precipitation values for time period intervals of length T in pre-set time periods of length t based on:
 a number of time periods within the time period interval of length T wherein the most probable amount of precipitation is a trace amount; 
 a number of time periods within the time period interval of length T wherein the most probable amount of precipitation is greater than or equal to a pre-set amount; 
 a probability of precipitation value for the pre-set time period of length t; 
 a probability of precipitation value for a next consecutive time period of length t; and 
 a probability of precipitation value for a previous consecutive time period of length t; 
 
 (c) calculating, by the precipitation forecasting system, a most probable precipitation amount corresponding to each of the probability of precipitation values; 
 (d) calculating, by the precipitation forecasting system, a location-specific probability of precipitation value for each t/T pairs of consecutive probability of precipitation values; and 
 (e) communicating via at least one communications channel said location-specific probability of precipitation values for each consecutive time period intervals, T, said most probable precipitation amount, and said probability of precipitation value for each t/T pairs, to an end user. 
 
     
     
       31. The system according to  claim 13 , wherein the storage means is a networked computer containing a digital database containing the location-specific probability forecasting information. 
     
     
       32. The system according to claim 13, wherein the location-specific probability forecasting information includes information about a specific location. 
     
     
       33. The system according to claim 1, further comprising an input module for manually entering an adjusted probability of precipitation value. 
     
     
       34. The system according to claim 13, further comprising an input module for manually entering an adjusted probability of precipitation value. 
     
     
       35. The system according to claim 1, wherein the time period, T, is selected from one of 1, 2, 3, 4, 5, 6, 10, 12, 15, 30, 45, 60, 120, 180, 240, and 300 minutes. 
     
     
       36. The system according to claim 1, wherein the pre-set time period, t, is selected from one of 6, 7, 8, 9, 10, 12, 24, 36, 48, and 96 hours. 
     
     
       37. The system according to claim 13, wherein the time period, T, is selected from one of 1, 2, 3, 4, 5, 6, 10, 12, 15, 30, 45, 60, 120, 180, 240, and 300 minutes. 
     
     
       38. The system according to claim 13, wherein the pre-set time period, t, is greater than or equal to T and is selected from one of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 24, 36, 48, and 96 hours. 
     
     
       39. The system according to claim 24, wherein the time period, T, is selected from one of 1, 2, 3, 4, 5, 6, 10, 12, 15, 30, 45, 60, 120, 180, 240, and 300 minutes. 
     
     
       40. A system for calculating and communicating probability of precipitation forecasts, the system comprising:
 a storage device for storing location-specific probability forecasting information;   a processing device for computing a probability of precipitation value from the forecast information for any pre-determined time period, T, in a pre-set time period, t, that is greater than or equal to the pre-determined time period, wherein the processing device uses artificial intelligence to compute probability of precipitation values for pre-determined time periods of length T in pre-set time periods of length t based on:
 a number of time periods within the time pre-determined period of length T wherein a forecasted precipitation amount is a trace amount; 
 a number of time periods within the pre-determined time period of length T wherein a forecasted precipitation amount is greater than or equal to a pre-set amount; 
 a probability of precipitation value for the pre-set time period of length t; 
 a probability of precipitation value for a next consecutive time period of length t; and 
 a probability of precipitation value for a previous consecutive time period of length t; and 
   a communications subsystem for communicating the probability of precipitation value via at least one communications channel.   
     
     
       41. A system for calculating and communicating probability of precipitation forecasts for periods that are not fixed to specific pre-set times, the system comprising:
 a storage device for storing location-specific probability forecasting information;   a processing device for computing a probability of precipitation value from the forecast information for any time period, T, in a pre-set time period, t, wherein the probability of precipitation values are not fixed to a specific pre-set time, but are recalculated to a present time, and wherein the processing device uses artificial intelligence to compute probability of precipitation values for time periods of length T in pre-set time periods of length t based on:
 a number of time periods within the time period of length T wherein a forecasted precipitation amount is a trace amount; 
 a number of time periods within the time period of length T wherein a forecasted precipitation amount is greater than or equal to a pre-set amount; 
 a probability of precipitation value for the pre-set time period of length t; 
 a probability of precipitation value for a next consecutive time period of length t; and 
 a probability of precipitation value for a previous consecutive time period of length t; and 
   a communications subsystem for communicating the probability of precipitation value via at least one communications channel.   
     
     
       42. A system for calculating and communicating probability of precipitation forecasts, the system comprising:
 a probability of precipitation system including:   a probability of precipitation forecast model for computing a probability of precipitation value for a time period, T, within a pre-set time period, t, that is greater than or equal to the time period, wherein the probability of precipitation forecast model uses artificial intelligence to compute probability of precipitation values for time periods of length T in pre-set time periods of length t based on:
 a number of time periods within the time period of length T wherein a forecasted precipitation amount is a trace amount; 
 a number of time periods within the time period of length T wherein a forecasted precipitation amount is greater than or equal to a pre-set amount; 
 a probability of precipitation value for the pre-set time period of length t; 
 a probability of precipitation value for a next consecutive time period of length t; and 
 a probability of precipitation value for a previous consecutive time period of length t; 
   a most probable precipitation amount forecast model for computing a precipitation amount value corresponding to each probability of precipitation value; and   a communications device for communicating the probability of precipitation and precipitation amount values electronically to a remote requestor.   
     
     
       43. A computer-implemented method for calculating and communicating at least one probability of precipitation forecast, comprising the steps of, at a precipitation forecasting system:
 determining by the precipitation forecasting system, a first probability of precipitation value for a first time period, T, within a pre-set time period, t, based upon:
 a number of time periods within the first time period, T, wherein a forecasted precipitation amount is a trace amount; and 
 a number of time periods within the first time period, T, wherein a forecasted precipitation amount is greater than or equal to a pre-set amount; 
   determining, by the precipitation forecasting system, a second probability of precipitation value for a second time period overlapping at least a part of the first time period, based upon:
 a probability of precipitation value for the pre-set time period of length t; 
 a probability of precipitation value for a next consecutive time period of length t; or 
 a probability of precipitation value for a previous consecutive time period of length t; 
   determining, by the precipitation forecasting system, a third probability of precipitation value based on the first and second values; and   communicating the third probability of precipitation value via at least one communications channel.   
     
     
       44. The method according to claim 43, further comprising the step of adjusting the third probability of precipitation value before performing the step of communicating the value. 
     
     
       45. The method according to claim 43, further comprising the step of determining a fourth probability of precipitation value for a third time period that is equal in duration to the first time period, wherein the first and third time periods are within the pre-set time period, t. 
     
     
       46. The method according to claim 45, further comprising the step of determining a fifth probability of precipitation value based on the third and fourth probability of precipitation values. 
     
     
       47. The method according to claim 43, wherein the third probability of precipitation value is a probability of precipitation of rain, snow, or ice. 
     
     
       48. The method according to claim 43, wherein the third probability of precipitation value is communicated as a percentage chance. 
     
     
       49. The method according to claim 43, further comprising communicating a most probable amount value for the first time period via the least one communications channel. 
     
     
       50. The method according to claim 49, wherein the most probable amount value is a numerical value representing the most probable amount of precipitation that may fall during the first time period, expressed in equivalent inches of water. 
     
     
       51. The method according to claim 43, wherein the step of communicating the third probability of precipitation value includes a graphic depicting when during the pre-set time period precipitation will likely occur. 
     
     
       52. The method according to claim 43, wherein the communications channel is the Internet. 
     
     
       53. The method according to claim 43, wherein the first time period is selected from one of 1, 2, 3, 4, 5, 6, 10, 12, 15, 30, 45, 60, 120, 180, 240 and 300 minutes. 
     
     
       54. The method according to claim 43, wherein the pre-set time period is selected from one of 1, 2, 3, 4, 5, 6, 7, 8, 10, 24, 36, 48, and 96 hours. 
     
     
       55. The method according to claim 43, wherein there are a plurality of time intervals before and after the first time period, and a plurality of equal time intervals within the first time period, further comprising the steps of:
 determining whether the amount of precipitation for each of the equal time intervals within the first time period is equal to zero;   if it is not determined that the amount of precipitation for each of the equal time intervals within the first time period is equal to zero, determining whether the amount of precipitation for each of the equal time intervals within the first time period is less than or equal to a trace amount; and   determining whether the amount of precipitation for at least one time interval before the first time period and the amount of precipitation for at least one time interval after the first time period is greater than or equal to 0.01 inches.   
     
     
       56. The method according to claim 43, further comprising the step of:
 determining for each of a plurality of equal time intervals within the first time period, T, whether the amount of precipitation for each of the plurality of equal time intervals is less than or equal to a trace amount.   
     
     
       57. A system for calculating and communicating probability of precipitation forecasts, the system comprising:
 a storage device for storing location-specific probability forecasting information;   a precipitation forecasting system including a processing device for computing a probability of precipitation value from the forecast information for each of a plurality of pre-determined time periods, T, in a pre-set time period, t, wherein the pre-set time period is greater than or equal to the plurality of pre-determined time periods, and wherein the probability of precipitation forecasting system uses artificial intelligence to compute probability of precipitation values for pre-determined time periods of length T in pre-set time periods of length t based on:
 a number of time periods within the pre-determined time period of length T wherein a forecasted precipitation amount is a trace amount; 
 a number of time periods within the pre-determined time period of length T wherein a forecasted precipitation amount is greater than or equal to a pre-set amount; 
 a probability of precipitation value for the pre-set time period of length t; 
 a probability of precipitation value for a next consecutive time period of length t; and 
 a probability of precipitation value for a previous consecutive time period of length t; and 
   a communications subsystem for communicating the probability of precipitation values via at least one communications channel.   
     
     
       58. A system for calculating and communicating probability of precipitation forecasts for periods that are not fixed to specific pre-set times, the system comprising:
 a storage device for storing location-specific probability forecasting information;   a precipitation forecasting system including a processing device for computing a probability of precipitation value from the forecast information for each of a plurality of time periods, T, in a pre-set time period, t, wherein the probability of precipitation values are not fixed to a specific pre-set time, but are recalculated to a present time, and wherein the precipitation forecasting system uses artificial intelligence to compute probability of precipitation values for time periods of length T in pre-set time periods of length t based on:
 a number of time periods within the time period of length T wherein a forecasted precipitation amount is a trace amount; 
 a number of time periods within the time period of length T wherein a forecasted precipitation amount is greater than or equal to a pre-set amount; 
 a probability of precipitation value for the pre-set time period of length t; 
 a probability of precipitation value for a next consecutive time period of length t; and 
 a probability of precipitation value for a previous consecutive time period of length t; and 
   a communications subsystem for communicating the probability of precipitation values via at least one communications channel.   
     
     
       59. A system for calculating and communicating probability of precipitation forecasts, the system comprising:
 a precipitation forecasting system including:   a probability of precipitation forecast model for computing a probability of precipitation value for each of a plurality of time periods, T, in a pre-set time period, t, wherein the pre-set time period is greater than or equal to the plurality of time periods, and wherein the precipitation forecast model uses artificial intelligence to compute probability of precipitation values for time periods of length T in pre-set time periods of length t based on:
 a number of time periods within the time period of length T wherein a forecasted precipitation amount is a trace amount; 
 a number of time periods within the time period of length T wherein a forecasted precipitation amount is greater than or equal to a pre-set amount; 
 a probability of precipitation value for the pre-set time period of length t; 
 a probability of precipitation value for a next consecutive time period of length t; and 
 a probability of precipitation value for a previous consecutive time period of length t; 
   a most probable precipitation amount forecast model for computing a precipitation amount value corresponding to each of the probability of precipitation values; and   a communications device for communicating each of the probability of precipitation and most probable precipitation amount values electronically to a remote requestor.