Validazione di misure nivometriche automatiche: implementazione di un algoritmo per l'identificazione e la correzione dei dai anomali

VALIDATION OF AUTOMATIC SNOW MEASUREMENTS: IMPLEMENTATION OF AN ALGORITHM FOR ANOMALOUS DATA IDENTIFICATION AND CORRECTION The network of automatic snow and weather stations provides measurements data with high temporal resolution that is used for the estimatation of the amounts of snowfalls, the assessment of avalanche danger and for a variety of applications in the hydrologic field that require highly accurate and reliable observations. Data collected by means of ultrasound snow gauges may however be distorted by a series of factors associated with meteorological conditions (snow accumulation/dispersal due to the wind action) and possible interferences during measurement, such as obstacles that temporarily cover the sensor, or the growth of grass following full snowpack melting. All data gathered by the snow measuring stations of ARPA Piemonte regularly undergo a manual quality control procedure carried out daily by snow experts, who detect and correct all possible anomalies in measurements. The aim of this study is to provide a support to manual validation of snow data through the development of an identification technique of “suspicious” data, such as possible outliers, isolated peaks or improbable values, given the seasonal trend of snowfalls. The procedure consists of a series of air temperature measures and implements a snowcover melting model to verify compatibility of snow data with the other meteorological variables measured. The algorithm was assessed by comparing automatically validated series with those manually validated by snow scientists, and results prove the accuracy of the method proposed.