Disclosed is a computing device for generating weather observation data for solving the problem. The computing device includes: a memory including computer executable components; and a processor executing following computer executable components stored in the memory, and the computer executable components may include an initial ground weather observation data recognition component recognizing observed initial ground weather observation data, and a weather data generation component trained to generate weather data of a gap region on the initial ground weather observation data by using a machine learning module.

The present disclosure describes various embodiments of systems, apparatuses, and methods for large-scale processing of weather-related data. For one such system, the system comprises a database of weather-related data providing from a plurality of weather monitoring stations and a plurality of interconnected processors for coordinating a data processing job for processing a set of input weather-related data from the database. Accordingly, the input data comprises sensor data from an array of weather monitoring stations positioned on an open shoreline during a hydrodynamic event, weather model data for the hydrodynamic event, and at least one of air-craft reconnaissance data or satellite reconnaissance data regarding the hydrodynamic event, wherein the plurality of interconnected processors are configured to assimilate the input data and generate, using machine learning, an improved weather prediction model for the hydrodynamic event. Other systems, apparatuses, and methods are also provided.

A temperature prediction system may include a data input module configured to receive data related to climate, a prediction module having installed therein a trained model for predicting a temperature based on input data from the data input module, and an output module configured to output temperature information predicted by the prediction module.

A device is specified for ascertaining a movement corridor for lightweight aircraft. The device includes a first interface, a second interface, and a processing unit. The first interface is configured to receive aircraft data relating to the lightweight aircraft, wherein the aircraft data at least contain flight properties and functions of the lightweight aircraft. The second interface is configured to receive weather data from a weather information source, wherein the weather data contain weather predictions and also current weather data and contain at least air movements in an altitude profile between a maximum altitude of the lightweight aircraft and the Earth's surface. The processing unit is configured to compare the aircraft data to the weather data and to ascertain a probable movement corridor of the aircraft.

A forecast engine is configured to analyze aerial and/or satellite images depicting a geographic area to identify the existence of solar panels within the geographic area at different times. Based on the installation time of each solar panel, the forecast engine estimates the solar power generation capacity of the solar panel. The forecast engine also analyzes meteorological data, including weather forecasts, to estimate a level of insolation at each solar panel within the geographic area across a range of times. The forecast engine can then determine the total amount of solar power generation within the given geographic area at a particular time using the solar power generation capacity of each solar panel and the level of insolation at each solar panel at the particular time.

A method, apparatus and computer program product for determining a reduced visibility event warning are described herein. In the context of a method, a location corresponding with a reduced visibility event warning may be identified. Information regarding visibility at one or more stationary positions based upon the location of the reduced visibility event warning may be received from one or more remote devices (e.g., sensing apparatuses). The method may determine a reduced visibility event warning confidence for the location corresponding with a reduced visibility event warning based upon the information regarding visibility. The method may cause the reduced visibility event warning to be published in an instance in which the reduced visibility event warning confidence satisfies a confidence threshold.

In one illustrative configuration, a system and method of air quality monitor minimization/optimization is disclosed. The method may include providing at least a first air quality monitor on a site. The first air quality monitor may be configured to generate a first set of attached parameters. The method may further include providing a SCADA system, on the site, configured to generate a set of SCADA data. The SCADA data, the first set of attached parameters may be processed to determine a redundant/sub-optimized air quality monitor, which may be removed. In other illustrative configurations, the system and method may be utilized to locate and/or quantify emissions.

Techniques for predicting solar power generation include a node measuring, using one or more sensors, a first time series of voltage readings for a first power line located at a first location, wherein a portion of power on the first power line is generated from solar irradiance on one or more first solar panels located at the first location; generating a first cross-correlation between the first time series of voltage readings and a second time series of voltage readings for a second power line located at a second location, wherein a portion of power on the second power line is generated from solar irradiance on one or more second solar panels located at the second location; and computing a wind vector based on the first location, the second location, and the first cross-correlation, wherein the wind vector is usable to forecast solar power generation at one or more other locations.

A control apparatus includes a reception section that receives a wind speed vector measured at any time point by at least one external anemometer, a wind-power prediction section that, on the basis of the received wind speed vector, predicts a wind power to be applied to the mobile body after elapse of a predetermined time period, and a control section that controls driving of the mobile body on the basis of the predicted wind power.

A reanalysis ensemble service includes a plurality of conversion utilities, each conversion utility configured to convert a specific one of a plurality of disparate climate reanalysis datasets from different sources to common format files that are temporally and spatially registered, a data analytics platform for storing and operating on the different sourced common format files, a service interface for mapping service requests to analytic operations performed on the different sourced common format files by the data analytics platform, and a services library that dynamically creates data objects from one or more of the different sourced common format files in response to the analytic operations, and delivers the data objects to the service interface.