Rainfall Estimation from Tropospheric Attenuation Affecting Satellite Links

Abstract

A novel methodology for estimating rainfall rate from satellite signals is presented. The proposed inversion algorithm yields rain rate estimates by making opportunistic use of the downlink signal and exploiting local ancillary meteorological information (0 °C isotherm height and monthly convectivity index), which can be extracted on a Global basis from Numerical Weather Prediction (NWP) products. The methodology includes different expressions to take the different impact of stratiform and convective rain events on the link into due account. The model accuracy in predicting the rain rate is assessed (and compared to the one of other models), both on a statistical and on an instantaneous basis, by exploiting a full year of data collected in Milan, in the framework of the Alphasat Aldo Paraboni propagation experiment.

Rainfall Monitoring Based on Machine Learning by Earth-Space Link in the Ku Band

“…To diminish the effects caused by magnitude, it is necessary to normalize the feature so that their values fall into a specified range. In this article, we scale our features into the range [0,1] based on the following equation [34] (13) where xi,min and xi,max are the minimum and maximum values of each feature, respectively. The means and standard deviations of each normalized feature during rainy and dry periods are given in Table II.…”

“…Barthes et al used the OELs from television satellite located at geostationary earth orbit (GEO) and successfully retrieved the rain intensity in Paris area [8]. In space, there are hundreds of GEO satellites operated by broadcast and telecommunication companies, and satellites emit stable microwave signal in C (4-8 GHz) and Ku (12)(13)(14)(15)(16)(17)(18) GHz) bands towards the earth. Theoretically speaking, three GEO satellites are capable of covering the whole globe expect polar regions, and with sufficient OELs it is possible to monitor the global precipitation.…”

“…They made use of four OELs to successfully retrieve 2D rain maps with high resolution in Vivarais region in the south of France. Now there are many researches demonstrating that the GEO OELs are qualified for real-time rainfall monitoring [10][11][12][13].…”

“…Different from HML, there are more complex factors affecting OEL because it penetrates the whole troposphere. Due to the effects of no-rain atmospheric factors such as gasses, cloud and turbulence [12,13], two critical issues need to be addressed in the application of OELs: (1) identification of rain and no-rain periods; and (2) determination of attenuation baseline. It is worth noting that the two issues also exist in the use of HMLs.…”

“…Schleiss et al introduced a moving time window to calculate attenuation caused by the factors other than rain [20]. Many researchers also suggested that the attenuation baseline during rain period can be obtained by interpolation according to the signal before and after rainfall [8,12,13]. However, if the rainfall lasts long time, the delay of rainfall measurements will become obvious.…”