Real-time weather forecasting
Improved mechanisms for collecting information from a diverse suite of sensors and systems, calculating the current precipitation, atmospheric water vapor, atmospheric liquid water content, or precipitable water and other atmospheric-based phenomena, for example presence and intensity of fog, based upon these sensor readings, predicting future precipitation and atmospheric-based phenomena, and estimating effects of the atmospheric-based phenomena on visibility, for example by calculating runway visible range (RVR) estimates and forecasts based on the atmospheric-based phenomena.
1 . A system configured to produce weather forecasts for an identified location, comprising:
a data collector that collects high frequency weather data, and
at least one processor connected to receive the collected high frequency weather data, the at least one processor being configured to perform operations comprising:
identify a location of interest,
blend collected high frequency weather data and/or data inferred therefrom to produce a blend organized by a time-based cadence,
produce weather forecast data for the identified location of interest based at least in part on the blend organized by the time-based cadence, and
communicating the produced weather forecast data for the identified location of interest via at least one electronic network.
2 . The system of claim 1 , wherein the weather forecast data includes weather forecast transportation data.
3 . The system of claim 1 wherein the operations further comprise:
identify a further location of interest,
produce further weather forecast data for the identified further location of interest at least in part based upon the collected high frequency weather data organized by a time based cadence, and
communicating the further weather forecast data via the at least one electronic network.
4 . The system of claim 1 , where the collected high frequency weather data includes first data received during a first cadence cycle and second data received during a second cadence cycle subsequent to the first cadence cycle.
5 . The system of claim 1 , where blending includes blending first collected high frequency weather data collected during a first cadence cycle with second collected high frequency weather data collected during a second cadence cycle different from the first cadence cycle.
6 . The system of claim 5 , where blending includes blending the first collected high frequency weather data collected during a first cadence cycle with the second collected high frequency weather data collected during a second cadence cycle that occurs before the first cadence cycle starts or after the first cadence cycle ends.
7 . The system of claim 1 , where blending comprises blending collected high frequency weather data collected from a satellite microwave link during a first cadence cycle with second collected high speed weather data collected during a second cadence cycle different from the first cadence cycle.
8 . The system of claim 1 wherein the time-based cadence comprises cadence cycles having durations of 10 minutes or less.
9 . The system of claim 1 wherein the operations include making the collected high frequency weather data available for asynchronous weather forecast data production more frequently than every 10 minutes.
10 . A high speed weather forecasting system comprising:
a data collector that collects high frequency weather data, and
at least one processor connected to receive the collected high frequency weather data, the at least one processor being configured to perform operations comprising:
identify a location of interest,
produce a weather forecast for the identified location of interest at least in part based upon blending two or more collected high frequency weather datums and/or data inferred therefrom to create a blended weather datum organized by a time-based cadence,
infer a weather condition based on weather parameter estimates calculated from (a) collected high frequency weather data, and/or (b) weather data calculated based upon collected high speed weather data, and (c) the blended weather datum, and
communicating the produced weather forecast and the inferred weather condition over at least one electronic network.
11 . The high speed weather forecasting system of claim 10 wherein the operations further include inferring at least one weather datum from the blended weather datum.
12 . The high speed weather forecasting system of claim 10 wherein the operations further include estimating, at the identified location of interest, at least one weather datum based on the blended weather datum.
13 . The high speed weather forecasting system of claim 10 wherein the operations further comprise confirming a weather condition inference based upon past weather parameter information.
14 . The high speed weather forecasting system of claim 13 wherein confirming comprises performing a time series analysis and/or a trained machine learning model.
15 . The high speed weather forecasting system of claim 13 , wherein confirming comprises replacing the weather condition inference with non-inferred weather data once non-inferred weather data becomes available.
16 . The high speed weather forecasting system of claim 10 wherein the operations further comprise confirming a weather condition inference based upon future weather parameter prediction.
17 . The high speed weather forecasting system of claim 16 wherein confirming comprises performing a time series analysis and/or using a trained machine learning model, and includes replacing the weather condition inference with non-inferred weather data once non-inferred weather data becomes available.
18 . A high speed weather forecasting method for producing forecasts for specific locations, comprising performing, with at least one processor, operations comprising:
collecting high frequency weather data,
blending collected high frequency weather datums and/or weather datums inferred therefrom to create blended weather datums organized by a time-based cadence,
identifying a location of interest,
producing weather forecast data for the identified location of interest at least in part based upon the blended weather datums organized by the time-based cadence, and
communicating the weather forecast data over at least one electronic network.
19 . The high speed weather forecasting method of claim 18 , wherein the weather forecast data includes aviation weather data.
20 . The high speed weather forecasting method of claim 18 further comprising:
identifying a further location of interest,
producing further weather forecast data for the identified further location of interest at least in part based upon the collected high frequency weather data organized by a time based cadence, and at least in part based upon blending of two or more collected high frequency weather datums or data inferred therefrom, to create a blended weather datum organized by a time-based cadence, and communicating the further weather forecast data over the at least one electronic network.
21 . The high speed weather forecasting method of claim 18 , wherein collecting includes receiving first data during a first cadence cycle and receiving second data during a second cadence cycle different from the first cadence cycle.
22 . The high speed weather forecasting method of claim 18 wherein the time-based cadence has a periodicity of 10 minutes or less.
23 . The high speed weather forecasting method of claim 18 wherein the operations further include collecting the high frequency weather data more frequently than every 10 minutes.
24 . A high speed weather forecasting method comprising performing, with at least one processor:
collecting high frequency weather data,
blending two or more high frequency weather datums and/or datums inferred therefrom to create a blended weather datum organized by a time-based cadence,
identifying a location of interest,
producing weather forecast data for the identified location of interest a based upon the blended weather datum organized by the time-based cadence,
inferring a weather condition based on weather parameter estimates calculated based on the blended weather datum organized by the time-based cadence, and
communicating the inferred weather condition over at least one electronic network.
25 . The high speed weather forecasting method of claim 24 wherein blending comprises blending at least one inferred weather datum with at least one collected weather datum.
26 . The high speed weather forecasting method of claim 24 wherein the blending blends similar tile layers.
27 . The high speed weather forecasting method of claim 24 wherein the blending blends dissimilar tile layers.
28 . The high speed weather forecasting method of claim 24 further including inferring at least one weather datum from one or more collected measurements.
29 . The high speed weather forecasting method of claim 24 further including estimating at least one weather datum from one or more collected measurements at the identified location of interest.
30 . The high speed weather forecasting method of claim 24 further including confirming a weather condition inference based upon past weather parameter information.
31 . The high speed weather forecasting method of claim 30 wherein confirming comprises performing a time series analysis.
32 . The high speed weather forecasting method of claim 30 wherein confirming comprises using a trained machine learning model.
33 . The high speed weather forecasting method of claim 24 , where confirming involves replacing inferred weather data with non-inferred weather data once non-inferred weather data is available.
34 . The high speed weather forecasting method of claim 24 further including confirming an inferred weather condition based upon predicted future weather parameter information.
35 . The high speed weather forecasting method of claim 34 wherein confirming comprises performing a time series analysis and/or using a trained machine learning model, and involves replacing inferred weather data with non-inferred weather data once non-inferred weather data becomes available.