195results about "Weather monitoring" patented technology

A method for providing location-based nowcast, comprises the steps of: a) initiation of a request, by an end-user, for a time evolution of user-selected nowcast weather parameters, the transmission of the request being made over a public communication network to a nowcast request processor; b) the determination of the end-user's actual location by the nowcast request processor; c) the nowcast request processor gathering raw weather data from data sources; d) processing the raw data into a time-series of nowcast parameter maps; e) extracting the time evolution of the user requested nowcast parameters from the time-series of nowcast parameter maps by positioning the end-user's location on said time series; and f) distributing the requested information to end-user regarding the user-selected nowcast parameters within the extracted time evolution.

In one embodiment, a wind power ramp event nowcasting system includes a wind condition analyzer for detecting a wind power ramp signal; a sensor array, situated in an area relative to a wind farm, the sensor array providing data to the wind condition analyzer; a mesoscale numerical model; a neural network pattern recognizer; and a statistical forecast model, wherein the statistical model receives input from the wind condition analyzer, the mesoscale numerical model, and the neural network pattern recognizer; and the statistical forecast model outputs a time and duration for the wind power ramp event (WPRE) for the wind farm.

A carbon credit is a generic term for any tradable certificate or permit representing the right to emit one ton of carbon dioxide or the mass of another greenhouse gas with a carbon dioxide equivalent (tCO2e) equivalent to one ton of carbon dioxide.Carbon credits and carbon markets are a component of national and international attempts to mitigate the growth in concentrations of greenhouse gases (GHGs). One carbon credit is equal to one ton of carbon dioxide, or in some markets, carbon dioxide equivalent gases. Carbon trading is an application of an emissions trading approach. Greenhouse gas emissions are capped and then markets are used to allocate the emissions among the group of regulated sources.Carbon credits can be generated by any process that conforms to ISO 14064-66 standards. Once generated, carbon credits can be stored in a distributed, Cloud-based ledger. The ledger entries can serve as a registry for carbon credits as well as the data source for an Internet-enabled trading system or financial exchange that allows the carbon credits to be sold and bought as part of the same system. The distributed ledger can provide records that combine the details of the carbon credits' origin, transaction history, and financial instructions associated with trading of the carbon credits via a distributed ledger system.

A method for passing content to at least one communicator device. The user of a communicator device registers with at least one service provider for delivering a plurality of different types of content to be passed to the at least one communicator device. A user defined priority is assigned to the at least one type of content. The user-defined priority is stored on a computer readable medium. The different types of content are passed to the at least one communicator device based on the user defined priority.

Methods, systems, and apparatus, including computer-readable storage devices, for tracking and analyzing service outages. Weather data and outage data are accessed. Based on the weather data and the outage data, weather conditions corresponding to service outages are identified. A machine learning system is trained to estimate training a machine learning system to estimate effects of weather conditions on utility systems. Data for a particular utility system is provided to the trained machine learning system, and in response, output indicating estimated effects of future weather conditions on the particular utility system is received. The information that indicates the estimated effects of future weather conditions on the particular utility system is provided for display.

The invention discloses a nowcasting method and system of a thunder cloud cluster based on the boundary recognition and tracer technique. The method performs the cloud cluster boundary recognition and topology process to establish the relationship between cloud cluster life timing and clan pedigree by using the pattern recognition technique. The method comprises the steps of performing the boundary recognition on the pre-processed radar data; respectively recognizing the life timing of each cloud cluster and the information of moving direction, velocity, area and strong center and the like ofeach cloud cluster through the six judging factors of the quadtree matching analysis factor, the overlap factor, the area factor, the circum-rectangle factor, the outline comprehensive factor and thelocal similarity determination factor; and performing linear extrapolation on the moving direction, velocity, area and the strength of the cloud cluster. The preliminary result indicates that the system and the method of the invention can realize better recognition and extrapolation forecast of the thunder cloud cluster.

A method for passing content to at least one communicator device. The user of a communicator device registers with at least one service provider for delivering a plurality of different types of content to be passed to the at least one communicator device. A user defined priority is assigned to the at least one type of content. The user defined priority is stored on a computer readable medium. The different types of content are passed to the at least one communicator device based on the user defined priority.

A computerized method of processing data for use in weather modeling is provided. The method includes receiving, from a first data source, by a first server, microwave link data including signal attenuation information. The method also includes pre-processing, in real time, by the first server, the microwave link data, thereby producing pre-processed microwave link data, The method also includes storing the pre-processed microwave link data in a first data store. The method also includes receiving, from the first data store, by a second server, the pre-processed microwave link data. The method also includes processing, on a scheduled routine, by the second server, the pre-processed microwave link data using a data transform, thereby producing first weather data.

This application relates generally to systems and methods for validating solar irradiance nowcasts, solar power nowcasts and forecasts in real-time using a network of solar power systems and solar irradiance sensors. This application also relates to systems and methods for augmenting solar irradiance forecasts and solar power forecasts in real-time using a network of solar power systems and solar irradiance sensors.

The present invention provides a short term weather forecaster for nowcasting using a Numerical Weather Predictor (NWP). The system of the present invention tracks the evolution of differences between NWP and radar based precipitation patterns and adjusts the NWP forecast to account for theses differences. These differences are due to amplitude and phase errors of the NWP, such as model misses, false alarms, intensity errors and position errors. In presuming persistency in time of these errors and in estimating precipitation pattern time evolution due to other weather conditions such as wind motion, the present system corrects the NWP short term predicted patterns to compensate for these errors, thus enhancing nowcasting accuracy.

The invention relates to a real-time weather forecast system and a real-time weather forecast method using a rain sensing device, wherein rainfall information of a specific area is collected through the rain sensing device and is transmitted to the system to be analyzed so as to work out a relatively real-time weather forecast; the real-time weather forecast system using the rain sensing device comprises the rain sensing device, a vehicle-mounted control module, a vehicle-mounted display screen, a system data center and a mobile terminal device, wherein a signal input end of the vehicle-mounted control module is connected with a signal output end of the rain sensing device; a rainfall signal sensed by the rain sensing device is transmitted to the vehicle-mounted control module; the vehicle-mounted control module is in data communication with the system data center through a communication channel; and the system data center is used for transmitting the processed data to the mobile terminal device or the vehicle-mounted display screen connected with the system through the data information channel, so that the purposes of monitoring and issuing real-time weather conditions are achieved.

The invention discloses a power grid weather predicting and early-warning system based on a numerical weather prediction model. The power grid weather predicting and early-warning system comprises a numerical weather predicting system, a micrometeorological data collection system, an MOS predicting system and a weather predicting system, the micrometeorological data collection system is connected with the MOS predicting system, the numerical weather predicting system is connected with the MOS predicting system and the weather predicting system, the MOS predicting system is connected with the weather predicting system, and the weather predicting system is used for conducting predicting, early-warning, querying, counting and analyzing on weather phenomena of an area under administration and providing a visualized graph interface by taking data obtained by the numerical weather predicting system and data obtained by the MOS predicting system as bases. The power grid weather predicting and early-warning system based on the numerical weather prediction model has the advantage that quantitative prediction can be conducted automatically without relying on external numerical weather predictions.

Described are methods and apparatuses, including computer program products, for detecting lightning activity. Waveform data indicative of lightning activity is received by a waveform sensor from one or more signal converters. The waveform data comprises a group of electromagnetic waveforms. The waveform data is filtered by a processor to remove noise frequencies. One or more uncompressed portions of the waveform data are transmitted to a processing server. Digital filter data based on the one or more uncompressed portions of waveform data are received from the processing server. One or more frequencies are removed from the waveform data based on the digital filter data. The waveform data is compressed. The compressing includes selecting one or more points on a waveform, wherein the one or more points are above a predetermined threshold. The compressing includes determining an inflection of the selected points based on a predefined algorithm.

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.

Methods and systems for generating a multi-model ensemble of global climate simulation data from a plurality of global climate simulation models (GCMs), to be used in training a neural network (NN)-based climate forecasting model, are disclosed. The methods and systems perform steps of computing a GCM validation measure for each GCM; selecting a validated subset of the GCMs, by comparing each computed GCM validation measure to a validation threshold determined based on observational historical climate data; computing a forecast skill score for each validated GCM, based on a first forecast function; selecting a validated and skillful subset of GCMs; generating one or more candidate ensembles by combining simulation data from at least two validated and skillful GCMs; computing an ensemble forecast skill score for each candidate ensemble, based on a second forecast function; and selecting a best-scored candidate ensemble. Embodiments of the present invention enable accurate climate forecasting without the need to run new dynamical global climate simulations on supercomputers.

A method, system, and device provide alert information using weather prediction data. The method includes: converting weather prediction data to a tile based tile set, the tiles each representative of a unique geographic projection of a rendered geographical area of defined size; determining for each time period of the forecast whether any of the one or more weather variables associated with each prediction geographical tile violates a weather variable threshold for the location associated with the prediction geographical tile, the determining performed by comparing for each time period of the forecast each weather variable of the one or more weather variables associated with the prediction geographical tile to the weather variable threshold for the location associated with the prediction geographical tile; and generating and communicating one or more alerts corresponding to one or more violations of the weather variable thresholds for the locations associated with the prediction geographical tiles.

The system as described collects and utilizes weather data sensor information in order to rapidly collect and update weather forecasts using real-time weather data collected at high rates of frequency, and use this collected high frequency weather data to rapidly correct and update the weather forecasts generated by the system.

Methods and apparatuses, including computer program products, are described for predicting the potential for severe weather. Data associated with lightning activity is received by a computing device. A location, a movement speed, a movement direction, and a lightning rate of one or more cells of lightning activity are determined by the computing device based on the received data. The lightning rate is compared, by the computing device, to a threshold lightning rate. One or more geographical areas at risk are determined by the computing device based on the location, the movement speed and the movement direction of the one or more cells of lightning activity. An alert is issued by the computing device to one or more remote devices monitoring the geographical areas when the lightning exceeds a value of the threshold lightning rate.

Methods and systems for generating a neural network (NN)-based climate forecasting model are disclosed. The methods and systems perform steps of generating a multi-model ensemble of global climate simulation data by combining simulation data from at least two global climate simulation models; pre-processing the multi-model ensemble of global climate simulation data, where the pre-processing comprises at least one action of spatial re-gridding, temporal homogenization, and data augmentation; training the NN-based climate forecasting model on the pre-processed multi-model ensemble of global climate simulation data; and validating the NN-based climate forecasting model using observational historical climate data. Embodiments of the present invention enable accurate climate forecasting without the need to run new dynamical global climate simulations on supercomputers. Also disclosed are benefits of the new methods, and alternative embodiments of implementation.

The technology relates to determining general weather conditions affecting the roadway around a vehicle, and how such conditions may impact driving and route planning for the vehicle when operating in an autonomous mode. For instance, the on-board sensor system may detect whether the road is generally icy as opposed to a small ice patch on a specific portion of the road surface. The system may also evaluate specific driving actions taken by the vehicle and / or other nearby vehicles. Based on such information, the vehicle's control system is able to use the resultant information to select an appropriate braking level or braking strategy. As a result, the system can detect and respond to different levels of adverse weather conditions. The on-board computer system may share road condition information with nearby vehicles and with remote assistance, so that it may be employed with broader fleet planning operations.

The present document describes a method for generating and displaying a succession of short-term weather forecasts, also called nowcasts, in selectable time increments. A system for preparing nowcasts, called nowcaster, is used for preparing short-term forecasted weather values with a default time increment between each one of them. The method receives a chosen time increment from a user and the prepared forecasted weather values. The method comprises an aggregator that re-packages the forecasted weather values in the chosen time increments. A succession of short-term weather forecasts, which is a collection of forecasted weather values at the chosen time increment, is then outputted.

A system and method are provided for graphically displaying a weather hazard. The system is comprised of a display system coupled to a processor that is configured to retrieve weather information from a database and determine the severity of weather hazard present within a predetermined distance. The severity of the weather hazard is based on the phase of flight and type of weather hazards present within the weather envelope. The weather symbology that graphically represents the severe weather hazard within a weather envelope is rendered on the display.

The invention discloses a power grid equipment area convection weather forecasting method based on a cross correlation tracking method, comprising the steps of: determining radar echo motion vector characteristics in dependence on radar historic data; performing extrapolation calculation on radar echo and wind fields in dependence on the radar echo motion vector characteristics to obtain extrapolated radar echo and wind fields; and performing superposed display and analysis on extrapolated radar echo and wind fields, and power grid equipment geographic information. In the power grid equipment area convection weather forecasting method, radar echo is extrapolated to obtain motion vector characteristics of future radar echo; nowcasting of radar echo and wind fields in future is performed by utilizing the motion vector characteristics; and the technology is applied to an electric power GIS system to obtain power grid area equipment echo intensity and wind field forecasting early warning information.

The invention provides a multi-information integration-based thunder and lightning monitoring and forecasting method for electric transmission and transformation equipment, which is characterized by comprising the steps of 1, establishing a thunderstorm potential forecasting model and establishing a Hubei province thunderstorm potential forecasting equation; 2, establishing a thunderstorm nowcasting model, and selecting a radar composite reflectivity factor (CR), an echo top height (ET) and a vertical integrated liquid water (VIL) as nowcasting factors to lock the thunderstorm based on the stepwise decreasing FAR method; at the same time, in combination with the monitoring information of a lightning position finder, forecasting the possible area wherein the thunderstorm appears within 30 minutes in the future; 3, establishing a thunder and lightning monitoring and forecasting system for a power transmission line. According to the technical scheme of the invention, the precipitation area and the probability of the thunderstorm in different areas can be accurately forecasted. The method is high in accuracy, strong in practicability and good in reliability.