Electronics Letters · 2013 · 21 citations · 4 references
Cluster ComputingEnvironmental MonitoringRain RateEngineeringBucket Data ProcessingWeather ForecastingData Streaming ArchitectureEarth ScienceBucket Rain GaugesNumerical Weather PredictionManagementData IntegrationMeteorological MeasurementData ManagementMeteorologyGeographyComputer ScienceData-intensive ComputingNew AlgorithmHydrologyWater ResourcesDroughtCivil EngineeringCloud ComputingData DistributionParallel ProgrammingData Modeling
Rain attenuation prediction models at millimetre wavelengths require rain rate averaged over one minute. Currently available tipping bucket rain gauges often only provide the number of tips per minute (or a directly related quantity). In this reported work, the performance of a new algorithm devised to estimate rain rate from data gathered with such rain gauges, when used for propagation application, is investigated. To this purpose, an extensive database collected over a period of ten years is exploited. It is concluded that, even though the proposed algorithm performs well, the number of tips per minute may not be the best parameter to derive rain rate for propagation applications.
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