Apparatus and associated methods relate to determining metrics of water particles in clouds by directing light pulses at a cloud and measuring a peak, a post-peak value and a high-frequency fluctuation of light signals reflected from the cloud. The light pulses include: a first pulse having circularly polarized light of a first wavelength; and a second pulse of a second wavelength. The reflected light signals include: a first reflected light signal having left-hand circular polarization of the first wavelength; a second reflected light signal having right-hand circular polarization of the first wavelength; and a third reflected light signal of the second wavelength. An extinction coefficient and a backscatter coefficient are determined based on the measured peak and post-peak slopes of the first and second reflected light signals. The measured high-frequency fluctuations of the three reflected light signals can be used to calculate cloud particle sizes.

A wind forecasting system configured to generate forecasted wind conditions for a time interval based on wind data derived from flight log data collected from a plurality of aerial vehicles operating in a first area. The forecasted wind conditions can be used by an aerial route management system to generate a flight plan for an aerial vehicle from a start location to an end location in the first area during the time interval.

Embodiments include a wireless mote network having a plurality of motes, wherein each of the plurality of motes includes a processing unit in communication with a communications device. Each of the motes includes at least a sensor configured to monitor an environmental condition in an area around the mote or an actuator configured to control one or more external systems. The wireless mote network also includes a central communications device configured to communicate with one or more of the motes within a range of the central communications device and a controller configured to communicate with the central communications device, to receive one or more signals indicative of the environmental condition of one or more of the plurality of motes, and to transmit one or more control signals indicating an operation of the actuator to one or more of the plurality of motes.

Satellite images from vast historical archives are analyzed to predict severe storms. We extract and summarize important visual storm evidence from satellite image sequences in a way similar to how meteorologists interpret these images. The method extracts and fits local cloud motions from image sequences to model the storm-related cloud patches. Image data of an entire year are adopted to train the model. The historical storm reports since the year 2000 are used as the ground-truth and statistical priors in the modeling process. Experiments demonstrate the usefulness and potential of the algorithm for producing improved storm forecasts. A preferred method applies cloud motion estimation in image sequences. This aspect of the invention is important because it extracts and models certain patterns of cloud motion, in addition to capturing the cloud displacement.

Satellite images from vast historical archives are analyzed to predict severe storms. We extract and summarize important visual storm evidence from satellite image sequences in a way similar to how meteorologists interpret these images. The method extracts and fits local cloud motions from image sequences to model the storm-related cloud patches. Image data of an entire year are adopted to train the model. The historical storm reports since the year 2000 are used as the ground-truth and statistical priors in the modeling process. Experiments demonstrate the usefulness and potential of the algorithm for producing improved storm forecasts. A preferred method applies cloud motion estimation in image sequences. This aspect of the invention is important because it extracts and models certain patterns of cloud motion, in addition to capturing the cloud displacement.

A method of generating individualized real-time weather and environmental information, including receiving weather or environmental condition data from weather and environmental sensors, analyzing the data received from the sensors to generate weather and environmental information, and transmitting the information to a communicator device. The method may include determining a spatial range of a sensor and/or determining if a communicator device is within close proximity of a sensor. The sensors may be mounted in fixed locations along a roadway or a railway. The sensors may be approximately equidistant.

A method of generating individualized real-time weather and environmental information, including receiving weather or environmental condition data from weather and environmental sensors, analyzing the data received from the sensors to generate weather and environmental information, and transmitting the information to a communicator device. The method may include determining a spatial range of a sensor and/or determining if a communicator device is within close proximity of a sensor. The sensors may be mounted in fixed locations along a roadway or a railway. The sensors may be approximately equidistant.

The DYNAMIC AIRCRAFT THREAT CONTROLLER MANAGER APPARATUSES, METHODS AND SYSTEMS (“DATCM”) transforms flight profile information, terrain, weather/atmospheric data and flight parameter data via DATCM components into comprehensive hazard avoidance optimized flight plans. Comprehensive hazard avoidance includes synergistic comprehensive turbulence and airfoil-specific icing data. In one implementation, the DATCM comprises a processor and a memory disposed in communication with the processor and storing processor-issuable instructions to receive anticipated flight plan parameter data, obtain weather data based on the flight plan parameter data, obtain atmospheric data based on the flight plan parameter data, and determine a plurality of four-dimensional grid points based on the flight plan parameter data. The DATCM may then determine comprehensive hazards mappings. With (near) real-time comprehensive hazard information and/or predictive turbulence/icing forecast specific to airfoil type and/or profile parameters, the DATCM may allow aircraft to avoid areas where comprehensive hazard is greater than a predetermined threshold and/or avoid areas where turbulence/icing may occur.

The DYNAMIC AIRCRAFT THREAT CONTROLLER MANAGER APPARATUSES, METHODS AND SYSTEMS (“DATCM”) transforms flight profile information, terrain, weather/atmospheric data and flight parameter data via DATCM components into comprehensive hazard avoidance optimized flight plans. Comprehensive hazard avoidance includes synergistic comprehensive turbulence and airfoil-specific icing data. In one implementation, the DATCM comprises a processor and a memory disposed in communication with the processor and storing processor-issuable instructions to receive anticipated flight plan parameter data, obtain weather data based on the flight plan parameter data, obtain atmospheric data based on the flight plan parameter data, and determine a plurality of four-dimensional grid points based on the flight plan parameter data. The DATCM may then determine comprehensive hazards mappings. With (near) real-time comprehensive hazard information and/or predictive turbulence/icing forecast specific to airfoil type and/or profile parameters, the DATCM may allow aircraft to avoid areas where comprehensive hazard is greater than a predetermined threshold and/or avoid areas where turbulence/icing may occur.

Systems and methods are disclosed to downscale the resolution of a coarse-resolution soil moisture data. Coarse-resolution soil moisture data may include data cells that each represent a geographic region having at least one dimension greater than or equal to 1 km. A plurality of fine-resolution supplemental soil moisture data may be received that includes at least one of soil data, vegetation data, topography data, and climate data. The fine-resolution supplemental soil moisture data comprising data cells that each represent a geographic region having at least one dimension less than or equal to 100 meters. The coarse-resolution soil moisture data may be downscaled to fine-resolution soil moisture data using the plurality of fine-resolution supplemental soil moisture data, the fine-resolution soil moisture data comprising data cells that each represent a geographic region having at least one dimension less than 100 meters.