Platform for Producing Alerts Related to Severe Weather and Non-Weather Events
A first device may receive data inputs from data sources corresponding to raw weather, non-weather, and/or environmental data. The first device may generate targeted alerts based on the data inputs and transmit the targeted alerts to a second device associated with a user.
1 . A first device, comprising:
one or more processors to:
receive data inputs from data sources corresponding to raw weather data, environmental data, and non-weather data;
generate targeted alerts based on the data inputs and transmit the targeted alerts to a second device associated with a user; and
wherein the one or more processors are further utilized to inform and alert a meteorologist when additional raw weather, environmental data, and non-weather data critical in the forecasting of severe weather, environmental, and non-weather events affect the targeted alerts, the data sources comprising thresholds unique to a location of each user, including a) a time in advance of an identified severe weather, environmental, and non-weather event and b) a distance proximity of the identified event to determine whether risk locations are coincident with a user location and the threshold to generate the targeted alerts aided by the meteorologist.
2 . The first device of claim 1 , wherein the one or more processors are further utilized to present available information in an audio or video format and allow for a situational awareness of the current state of the weather and the environment.
3 . The first device of claim 1 , wherein the data sources include one or more of the following: observed weather data sources, doppler radar, historical weather data sources, historical model runs and resulting forecasts, historical ensemble model runs and resulting forecasts, historical analog inputs, historical global/regional re-analyses/re-forecasts, patterns provided by meteorologists, datasets that represent the locations of the user or a physical asset of a user.
4 . The first device of claim 1 , wherein the data sources further comprise: c) a threshold breach of a qualifier to an identified event.
5 . The first device of claim 4 , wherein the weather data sources further comprise: doppler radar, historical model runs and resulting forecasts, patterns provided by meteorologists, and datasets that represent the locations of the user or a physical asset of a user.
6 . The first device of claim 4 , wherein the weather data sources further comprise: historical environmental data sources, observed weather data sources, and historical model runs. resulting forecasts, historical environmental data sources and observed weather data sources.
7 . The first device of claim 4 , wherein the one or more processors are further utilized to curate and perform normalization processes on the data inputs to extract key data elements.
8 . The first device of claim 4 , where the data sources comprise: observed weather data sources, doppler radar, historical weather data sources, historical model runs and resulting forecasts, historical ensemble model runs and resulting forecasts, historical analog inputs, historical global/regional re-analyses/re-forecasts, patterns provided by meteorologists, and datasets that represent the locations of the user or a physical asset of a user.
9 . The first device of claim 1 , wherein the risk location is coincident with a present and possible future locations of the user.
10 . A method, comprising:
receiving by a first device data inputs from data sources corresponding to raw weather, non-weather, and environmental data; and
generating targeted alerts based on the data inputs and transmitting the targeted alerts to a second device associated with a user; and
wherein the one or more processors are further utilized to inform and alert a meteorologist when additional raw weather, environmental data, and non-weather data critical in the forecasting of severe weather, environmental, and non-weather events affect the targeted alerts, the data sources comprising thresholds unique to a location of each user, including a) a time in advance of an identified severe weather, environmental, and non-weather event and b) a distance proximity of the identified event to determine whether risk locations are coincident with a user location and the threshold to generate the targeted alerts aided by the meteorologist.
11 . The method of claim 10 , wherein the one or more processors are further utilized to present available information in an audio or video format and allow for a situational awareness of the current state of the weather and the environment.
12 . The method of claim 10 , wherein the data sources include one or more of the following: observed weather data sources, doppler radar, historical weather data sources, historical model runs and resulting forecasts, historical ensemble model runs and resulting forecasts, historical analog inputs, historical global/regional re-analyses/re-forecasts, patterns provided by meteorologists, datasets that represent the locations of the user or a physical asset of a user.
13 . The first device of claim 10 , wherein the data sources further comprise: c) a threshold breach of a qualifier to an identified event.
14 . The first device of claim 13 , wherein the weather data sources further comprise: historical environmental data sources, observed weather data sources, and historical model runs. resulting forecasts, historical environmental data sources and observed weather data sources.
15 . The first device of claim 13 , wherein the one or more processors are further utilized to curate and perform normalization processes on the data inputs to extract key data elements.
16 . The first device of claim 13 , wherein the weather data sources further comprise: historical environmental data sources and observed weather data sources.
17 . The first device of claim 13 , wherein the data sources comprise: observed weather data sources, doppler radar, historical weather data sources, historical model runs and resulting forecasts, historical ensemble model runs and resulting forecasts, historical analog inputs, historical global/regional re-analyses/re-forecasts, patterns provided by meteorologists, and datasets that represent the locations of the user or a physical asset of a user.
18 . The first device of claim 10 , wherein the risk location is coincident with a present and possible future locations of the user.
19 . A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to:
receive by a first device data inputs data inputs from data sources corresponding to raw weather, non-weather, and environmental data; and
generate targeted alerts based on the data inputs and transmit the targeted alerts to a second device associated with a user; and
wherein the one or more processors are further utilized to inform and alert a meteorologist when additional raw weather, environmental data, and non-weather data critical in the forecasting of severe weather, environmental, and non-weather events affect the targeted alerts, the data sources comprising thresholds unique to a location of each user, including a) a time in advance of an identified severe weather, environmental, and non-weather event and b) a distance proximity of the identified event to determine whether risk locations are coincident with a user location and the threshold to generate the targeted alerts aided by the meteorologist.
20 . The non-transitory computer-readable medium of claim 19 , wherein one or more instructions that, when executed by one or more processors, cause the one or more processors to display available information in a graphical format and allow for a situational awareness of the current state of the weather and the environment.
21 . The non-transitory computer-readable medium of claim 19 , wherein the data sources include one or more of the following: observed weather data sources, doppler radar, historical weather data sources, historical model runs and resulting forecasts, historical ensemble model runs and resulting forecasts, historical analog inputs, historical global/regional re-analyses/re-forecasts, patterns provided by meteorologists, datasets that represent the locations of the user or a physical asset of a user.
22 . The first device of claim 19 , wherein the data sources further comprise: c) a threshold breach of a qualifier to an identified event.
23 . The first device of claim 22 , wherein the weather data sources further comprise: historical environmental data sources, observed weather data sources, and historical model runs. resulting forecasts, historical environmental data sources and observed weather data sources.
24 . The first device of claim 22 , wherein the one or more processors are further utilized to curate and perform normalization processes on the data inputs to extract key data elements.
25 . The first device of claim 22 , wherein the data sources comprise: observed weather data sources, doppler radar, historical weather data sources, historical model runs and resulting forecasts, historical ensemble model runs and resulting forecasts, historical analog inputs, historical global/regional re-analyses/re-forecasts, patterns provided by meteorologists, and datasets that represent the locations of the user or a physical asset of a user.
26 . The first device of claim 19 , wherein the risk location is coincident with a present and possible future locations of the user.