A method for estimating the presence of rain performed on a computer and characterised in that it comprises the steps of - inserting a set of static parameters, said set of static parameters comprising standard deviations (5, 6) for at least two Kalman filters (9, 10), "epsilonStart" and "epsilonStop" thresholds expressed in dB, the minimum value of the instantaneous Es/N0 ratio where the instantaneous ratio Es/NO is defined as the ratio between the average radiofrequency energy of a satellite signal received by a user terminal, TRU, during a symbol interval and the monolateral power density of the total white Gaussian additive noise, i.e. including both the one captured by the receiving antenna of the TRU and the one generated internally to the receiver circuits, the duration of the sliding window for estimating the standard deviation of output samples, the lag time measured from the beginning of the precipitation event, the threshold for the value of the estimated standard deviation used to identify the end of a precipitation event, - inserting a set of dynamic parameters, said set of dynamic parameters comprising an isotherm height above sea level and a thickness of a melting layer in the troposphere, - measuring an instantaneous Es/NO value, - comparing said instantaneous Es/NO value with said minimum value of the instantaneous Es/NO ratio, - setting the instantaneous Es/NO values lower than said minimum value of the instantaneous Es/NO ratio equal to said minimum value of the instantaneous Es/NO ratio, - sending said values to a first Kalman filter designed to remove disturbances due to tropospheric scintillation and gravitational perturbations on the orbit of the satellite, said first Kalman filter having a KalmanST output, - sending said values to a second Kalman filter configured with different standard deviation values of the process noise, said second Kalman filter having a KalmanFT output, - defining the beginning of a precipitation event if a difference between said KalmanST output and said KalmanFT output exceeds said "epsilonStart" threshold value, - defining the end of a precipitation event if a difference between said KalmanST output and said KalmanFT output is lower than said "epsilonStop" threshold value, - converting the measure of the total attenuation of the satellite signal induced by rain along the path (in dB) into an estimate of rainfall intensity (in mm/h) based on a two-layer - melting layer and liquid layer - tropospheric model through a univocal relationship analytically described by an algebraic equation with a non-explicit solution. - inserting a set of static parameters, said set of static parameters comprising standard deviations (5, 6) for at least two Kalman filters (9, 10), "epsilonStart" and "epsilonStop" thresholds expressed in dB, the minimum value of the instantaneous Es/N0 ratio where the instantaneous ratio Es/NO is defined as the ratio between the average radiofrequency energy of a satellite signal received by a user terminal, TRU, during a symbol interval and the monolateral power density of the total white Gaussian additive noise, i.e. including both the one captured by the receiving antenna of the TRU and the one generated internally to the receiver circuits, the duration of the sliding window for estimating the standard deviation of output samples, the lag time measured from the beginning of the precipitation event, the threshold for the value of the estimated standard deviation used to identify the end of a precipitation event, - inserting a set of dynamic parameters, said set of dynamic parameters comprising an isotherm height above sea level and a thickness of a melting layer in the troposphere, - measuring an instantaneous Es/NO value, - comparing said instantaneous Es/NO value with said minimum value of the instantaneous Es/NO ratio, - setting the instantaneous Es/NO values lower than said minimum value of the instantaneous Es/NO ratio equal to said minimum value of the instantaneous Es/NO ratio, - sending said values to a first Kalman filter designed to remove disturbances due to tropospheric scintillation and gravitational perturbations on the orbit of the satellite, said first Kalman filter having a KalmanST output, - sending said values to a second Kalman filter configured with different standard deviation values of the process noise, said second Kalman filter having a KalmanFT output, - defining the beginning of a precipitation event if a difference between said KalmanST output and said KalmanFT output exceeds said "epsilonStart" threshold value, - defining the end of a precipitation event if a difference between said KalmanST output and said KalmanFT output is lower than said "epsilonStop" threshold value, - converting the measure of the total attenuation of the satellite signal induced by rain along the path (in dB) into an estimate of rainfall intensity (in mm/h) based on a two-layer - melting layer and liquid layer - tropospheric model through a univocal relationship analytically described by an algebraic equation with a non-explicit solution.