Enhanced Estimation of Rainfall from Opportunistic Microwave Satellite Signals

• Published in: IEEE transactions on geoscience and remote sensing 2024-01, Vol.62, p.1-1
• Main Authors: Angeloni, S., Adirosi, E., Sapienza, F., Giannetti, F., Francini, F., Magherini, L., Valgimigli, A., Vaccaro, A., Melani, S., Antonini, A., Baldini, L.
• Format: Article
• Language: English
• Subjects: Algorithms; Correlation coefficient; Correlation coefficients; Data acquisition; Digital Video Broadcasting; Estimation; Gauges; microwave satellite link; Modems; Physical characteristics; Physical properties; Precipitation; Rain; Rain gauges; Rain retrieval; Rainfall; rainfall attenuation; Rainfall rate; Receivers; Root-mean-square errors; Satellite broadcasting; Spatial variations; Velocity measurement; Weather forecasting
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2023.3349100

Physical characteristics of precipitation, like temporal and spatial variability, jointly with coverage and costs of conventional meteorological devices for quantitative rainfall estimation (i.e., rain gauges, disdrometers, weather radars) make the precipitation monitoring a complex task. However, real time rainfall maps are an important tool for many applications, dealing with environment, social activities, and business. Recently, the use of "opportunistic" methods to estimate rainfall has been investigated, highlighting the possibility to exploit inexpensive opportunities to augment information about precipitation. This paper deals with SmartLNBs (Smart Low-Noise Block converters), which are commercially available interactive digital video broadcasting (DVB) receivers designed to be used as bidirectional modems for commercial interactive TV applications. In the last few years an algorithm that converts the SmartLNB raw data into attenuation values, from which the rainfall rate is obtained, has been developed and evaluated. The aim of this paper is to describe the improvements of the rainfall estimation from SmartLNBs brought by significant changes in the data acquisition from SmartLNB and by algorithms' update. One year of data collected in Rome and Tuscany (Italy) are analyzed to test the performance of SmartLNB in estimating rainfall accumulation with respect to co-located rain gauges and disdrometer in the new configuration. Comparing SmartLNB and disdrometer data in Rome we obtained Root Mean Square Error equal to 7.7 mm, Normalized Mean Absolute Error equal to 44%, with a correlation coefficient of 0.91, that can point out the maturity of the technique.