Computing devices, systems, and methods described in various embodiments herein may relate to a light detection and ranging (lidar) system. An example computing device could include a controller having at least one processor and at least one memory. The at least one processor is configured to execute program instructions stored in the at least one memory so as to carry out operations. The operations include receiving information identifying an environmental condition surrounding a vehicle, the environmental condition being at least one of fog, mist, snow, dust, or rain. The operations also include determining a range of interest within a field of view of the lidar system based on the received information. The operations also include adjusting at least one of: a return light detection time period, sampling rate, or filtering threshold, for at least a portion of the field of view based on the determined range of interest.

A system and method for outputting weather data associated with a user-specified location based on a user-specified weather inquiry, including weather data output based on user-specified weather conditions, locations output based on a user-specified weather inquiry, notifications output regarding weather-related warnings, and notifications output based on weather-related notification thresholds.

A system and method for outputting weather data associated with a user-specified location based on a user-specified weather inquiry, including weather data output based on user-specified weather conditions, locations output based on a user-specified weather inquiry, notifications output regarding weather-related warnings, and notifications output based on weather-related notification thresholds.

In a method for determining, in particular predicting, at least one meteorological quantity for describing a current and/or past and/or future weather situation using a data processing device, (a) first meteorological parameters obtained from first measurements are assigned to grid points of a first grid. In the method, (b) at least one setting parameter, which can be entered via an interface, in particular a user interface, is received, and (c) the at least one meteorological quantity is determined from the first meteorological parameters, dependent on the at least one setting parameter, by applying a first algorithm, wherein preferably, the determined meteorological quantity is output at a user interface and/or is transmitted by an electronic message sending device.

In a method for determining, in particular predicting, at least one meteorological quantity for describing a current and/or past and/or future weather situation using a data processing device, (a) first meteorological parameters obtained from first measurements are assigned to grid points of a first grid. In the method, (b) at least one setting parameter, which can be entered via an interface, in particular a user interface, is received, and (c) the at least one meteorological quantity is determined from the first meteorological parameters, dependent on the at least one setting parameter, by applying a first algorithm, wherein preferably, the determined meteorological quantity is output at a user interface and/or is transmitted by an electronic message sending device.

System and other embodiments described herein relate to a sensor system used on a control line that measures atmospheric conditions. In one embodiment, a sensor system may have a main body attached to a line. The sensor system may use a directional sensor that determines direction of airflow according to rotation of the main body about the line. The sensor system may also have a generator coupled to the main body. The sensor system may also use a flow sensor that measures speed of the airflow according to a vortex generated from rotation of the generator in open air.

System and other embodiments described herein relate to a sensor system used on a control line that measures atmospheric conditions. In one embodiment, a sensor system may have a main body attached to a line. The sensor system may use a directional sensor that determines direction of airflow according to rotation of the main body about the line. The sensor system may also have a generator coupled to the main body. The sensor system may also use a flow sensor that measures speed of the airflow according to a vortex generated from rotation of the generator in open air.

The Abstract, as originally filed on November 5, 2021, is retained.

The Abstract, as originally filed on November 5, 2021, is retained.

A method for estimating quantitative precipitation by combining observation data of a weather radar and rain gauges includes: acquiring original accumulated data of rain gauges and original accumulated precipitation data of a weather radar to obtain rain gauge-weather radar data G/R pairs matched in the same grid; calculating an observation error of the original accumulated precipitation data of the weather radar through the G/R pairs, and detecting abnormal data to generate an initial correction factor field; determining whether a distance correlation exists between the initial correction factor field and the observation error, and if yes, adjusting the initial correction factor field, and correcting the original accumulated precipitation data of the weather radar through the adjusted correction factor field to obtain corrected accumulated precipitation data of the weather radar; and if not, obtaining the corrected accumulated precipitation data of the weather radar directly through a mean field bias (MFB) factor.