An observation signal generation device includes a local signal generator, a first mixer which mixes an RF signal to be observed with the local signal and outputs a first IF signal, a second mixer which mixes the RF signal and the local signal and outputs a second IF signal, an first IF filter which includes a first intermediate frequency obtained by subtracting a frequency of the local signal from a first frequency of the RF signal in a passband, includes a second intermediate frequency obtained by subtracting a frequency of the RF signal from the frequency of the local signal in an attenuation band, and filters the first IF signal to generate a first observation signal, and an second IF filter includes the first intermediate frequency in the attenuation band and the second intermediate frequency in the passband, and filters the second IF signal to generate a second observation signal.

Implementations are described herein for predicting a future climate condition in an agricultural area. In various implementations, a teleconnection model may be applied to a dataset of remote climate conditions such as water surface temperatures to identify one or more of the most influential remote climate conditions on the future climate condition in the agricultural area. A trained machine learning model may be applied to the one or more most influential remote climate conditions and to historical climate data for the agricultural area to generate data indicative of the predicted future climate condition. Based on the data indicative of the predicted future climate condition, one or more output components may be caused to render output that conveys the predicted future climate condition.

Implementations are described herein for predicting a future climate condition in an agricultural area. In various implementations, a teleconnection model may be applied to a dataset of remote climate conditions such as water surface temperatures to identify one or more of the most influential remote climate conditions on the future climate condition in the agricultural area. A trained machine learning model may be applied to the one or more most influential remote climate conditions and to historical climate data for the agricultural area to generate data indicative of the predicted future climate condition. Based on the data indicative of the predicted future climate condition, one or more output components may be caused to render output that conveys the predicted future climate condition.

A ski resort management system comprising: a data acquisition system that receives data from telemetry systems of the lift systems, of the snow generators and of the snow groomers of the ski resort; a processing station; mass storage units, containing a system database fed by the data acquisition system; and a display interface, accessible from operator terminals. The data acquisition system stores data and signals from the lift systems, the snow generators and the snow groomers in the system database. The processing station enables setting a mode of the display interface for alternatively displaying data relative to each lift system, to each snow generator or to each snow groomer, or to display, in an aggregated form, data relative to all the lift systems, all the snow generators and all the snow groomers.

A ski resort management system comprising: a data acquisition system that receives data from telemetry systems of the lift systems, of the snow generators and of the snow groomers of the ski resort; a processing station; mass storage units, containing a system database fed by the data acquisition system; and a display interface, accessible from operator terminals. The data acquisition system stores data and signals from the lift systems, the snow generators and the snow groomers in the system database. The processing station enables setting a mode of the display interface for alternatively displaying data relative to each lift system, to each snow generator or to each snow groomer, or to display, in an aggregated form, data relative to all the lift systems, all the snow generators and all the snow groomers.

A method for identifying sunny and rainy moments by utilizing multiple characteristic quantities of high-frequency satellite-ground links is provided. The method may include the following steps of: extracting multiple characteristic quantities including standard deviation, trend, maximum value, minimum value, average value, skewness, kurtosis and information entropy; selecting an optimal time window through adjustment; and finally realizing the identification of the sunny and rainy moments by utilizing a classification algorithm. According to the method for identifying the sunny and rainy moments, sunny and rainy periods can be accurately distinguished by utilizing the signals of the high-frequency satellite-ground links, and real-time monitoring of large-range sunny and rainy distribution conditions is achieved.

A radar device includes a transmission part that transmits a radar wave which has been frequency-modulated such that one measurement cycle has a rising section in which a frequency increases and a falling section in which a frequency decreases, a reception part that derives respective beat signals of the rising section and the falling section, and a signal processor that performs a precipitation determining process on the basis of an analysis of the beat signals. In the precipitation determining process, in the absence of objects other than precipitation objects from a transmission range of the radar wave, it is determined whether a spectral similarity of the frequency spectra of the rising and falling section with precipitation reference spectra is not less than a threshold, and if the spectral similarity is not less than the threshold as a result of the determination, it is determined that precipitation is present.

A radar device includes a transmission part that transmits a radar wave which has been frequency-modulated such that one measurement cycle has a rising section in which a frequency increases and a falling section in which a frequency decreases, a reception part that derives respective beat signals of the rising section and the falling section, and a signal processor that performs a precipitation determining process on the basis of an analysis of the beat signals. In the precipitation determining process, in the absence of objects other than precipitation objects from a transmission range of the radar wave, it is determined whether a spectral similarity of the frequency spectra of the rising and falling section with precipitation reference spectra is not less than a threshold, and if the spectral similarity is not less than the threshold as a result of the determination, it is determined that precipitation is present.

The present invention is related to a method for detecting and/or measuring atmospheric accretion on a suspended electrical cable span (2) of overhead power lines, said suspended electrical cable span (2) having a sag (D) and a local tension (H), and being submitted to wind pressure (w.sub.wind), comprising the steps of independently: measuring said sag (D), and optionally measuring the wind pressure (w.sub.wind), over a first time range, measuring the local tension (H) over a second time range,
the results of both steps being complemented and/or combined, so that to allow atmospheric accretion detection and/or measurement.

The present disclosure relates generally to methods, systems and computer program storage devices for generating a response to flooding. In one specific example, the present disclosure relates to methods, systems and computer program storage devices for generating one or more operational responses to flooding.