The present invention essentially comprises an application, software, system, method and combinations thereof that allow using a mobile phone's location-determining capabilities, compass, and camera, an application on the mobile device that can be used to display characteristics of weather within a predetermined distance from the mobile device by querying a remote server to gather information on the attributes about the weather within the predetermined radius of the device location.

Methods, apparatus, systems, and computer program products are provided for selecting a weather estimation algorithm and providing a weather estimate based thereon. In an example embodiment a method is provided that comprises receiving request location information by a processor, identifying one or more weather stations, and determining a distance from at least one of the one or more weather stations to a physical location indicated by the request location information. Based at least in part on the at least one determined distance, a weather estimation algorithm is selected. A weather estimation is determined for the physical location indicated by the request location information based at least on the selected weather estimation algorithm.

Systems for weather sensing and forecasting, and associated devices and methods, are disclosed herein. In some embodiments, a system for predicting a subject's perception of weather conditions is provided. The system can generate an individual profile for the subject, the individual profile including health information of the subject. The system can receive weather data including a first weather condition for a target location. The system can compare the individual profile to a plurality of different user profiles to identify one or more similar user profiles. Each similar user profile can (1) be associated with a user having similar health information as the subject, and (2) include weather perception data indicating how the user perceived a set of second weather conditions. Based on the weather data and the similar user profile(s), the system can generate a prediction of the how the subject will perceive the first weather condition.

Embodiments relate to leads and polynyas forecasting. Initially observed ice forecast data is obtained for a geographic area of interest, which is then used to generate an ice grid based on the observed ice data, where the ice grid includes grid cells that map polar regions. At this stage, daily opening rates are determined based on the ice grid, where each daily opening rate indicates an opening speed of a corresponding ice event, and daily convergence strain rates are determined based on the ice grid, where each daily convergence strain rate indicates a convergence of the corresponding ice event. For each day, a daily opening rate is weighted and then adjusting by a daily convergence strain rate. A forecasted opening rate on a target date is determined based on the weighted, adjusted daily opening rates. Predicted openings of the polar region can be rendered based on the forecasted opening rate.

Methods and apparatuses, including computer program products, are described for predicting the potential for severe weather. A computing device receives data associated with lightning activity, where the data includes lightning flash data. The computing device identifies cells of lighting activity based upon the lightning flash data and determines a movement speed, a movement direction, and a lightning rate of the cells of lightning activity based on the received data. The computing device compares the determined lightning rate to a threshold lightning rate, where the threshold rate is set based upon atmospheric conditions in a location of the cells of lightning activity. The computing device determines one or more geographical areas at risk based on the location, the movement speed, and the movement direction of the cells of lightning activity, and issues an alert to remote devices when the lightning rate exceeds a value of the threshold lightning rate.

An example method comprises receiving first historical meso-scale numerical weather predictions (NWP) and power flow information for a geographic distribution area, correcting for overfitting of the historical NWP predictions, reducing parameters in the first historical NWP predictions, training first power flow models using the first reduced, corrected historical NWP predictions and the historical power flow information for all or parts of the first geographic distribution area, receiving current NWP predictions for the first geographic distribution area, applying any number of first power flow models to the current NWP predictions to generate any number of power flow predictions, comparing one or more of the any number of power flow predictions to one or more first thresholds to determine significance of reverse power flows, and generating a first report including at least one prediction of the reverse power flow and identifying the first geographic distribution area.

Disclosed are methods, systems, and non-transitory computer-readable medium for managing energy use in a vehicle. For instance, the method may include receiving forecasted data from a first external source, receiving real-time data corresponding to at least one weather parameter at a first location at a first time, and continuously determining whether to perform an adjustment to a control parameter of the vehicle by using a machine learning model that is based on the forecasted data for the at least one weather parameter, the real-time data for the at least one weather parameter, a battery condition of the vehicle, and/or an estimated amount of energy consumed by traveling along a first navigation path.

A remote location monitoring system, for example, a home monitoring or weather monitoring system may include one or more sensors and/or receivers at a first location such as a residence or business to be monitored. The sensors and receivers may communicate with a remote central server via a gateway device and the detection data received from the sensors and receivers may be displayed via display circuitry coupled to a processor of the gateway device. The sensors, receivers, and gateway device may be controlled by users locally or remotely via the server. Users may register to receive remote notifications of weather events and other home monitoring events. Users may also access remotely sensors and receivers to configure alerts, notifications, and automatic responses for the devices and integrated appliances at the first location.

To provide a cloud observation device capable of reducing calculation cost and predicting sunshine probability by a simple method. A cloud observation device includes an image acquisition module which acquires an image in which a camera photographs the sky, a cloud extraction module which extracts clouds in the image, a sun position determination module which determines a sun position in the image, a sunshine probability calculation area setting module which sets a sunshine probability calculation area having the sun position as a base point in the image, and a sunshine probability calculation module which calculates a sunshine probability after a predetermined time has elapsed based on the sunshine probability calculation area and the extracted clouds.

An information processing apparatus 1 includes a message display module 142 which, when a predetermined event is predicted to occur at a set location of interest, displays a message indicating occurrence of the predetermined event and the time until the occurrence of the predetermined event. The location of interest may be set to a current position of the information processing apparatus 1. The information processing apparatus 1 may also include a map display module 141 that displays a map including the location of interest, wherein the message displaying module 142 displays the message in such a manner as to be superimposed on the map.