Rain attenuation prediction model for satellite communications based on the Météo-France ensemble prediction system PEARP

Abstract

Abstract. This paper presents an example of the usage of ensemble weather forecasting for the control of satellite-based communication systems. Satellite communication systems become increasingly sensitive to weather conditions as their operating frequency increases to avoid electromagnetic spectrum congestion and enhance their capacity. In the microwave domain, electromagnetic waves that are conveying information are attenuated between the satellite and Earth terminals in the presence of hydrometeors (mostly rain drops and more marginally cloud droplets). To maintain a reasonable level of service availability, even with adverse weather conditions considering the scarcity of amplification power in spacecraft, fade mitigation techniques have been developed. The general idea behind those fade mitigation techniques is to reroute, change the characteristics or reschedule the transmission in the case of too-significant propagation impairments. For some systems, a scheduling on how to use those mechanisms some hours in advance is required, making assumptions on the future weather conditions affecting the link. To this aim the use of weather forecast data to control the attenuation compensation mechanisms seems of particular interest to maximize the performances of the communication links and hence of the associated economic value. A model to forecast the attenuation on the link based on forecasted rainfall amounts from deterministic or ensemble weather forecasting is presented and validated. In a second phase, the model's application to a simplified telecommunication system allows us to demonstrate the valuable contribution of weather forecasting in the system's availability optimization or in the system's throughput optimization. The benefit of using ensemble forecasts rather than deterministic ones is demonstrated as well.

A Survey of Rain Fade Models for Earth–Space Telecommunication Links—Taxonomy, Methods, and Comparative Study

“…The validation is a good agreement between measured and predicted attenuation using this model, but has not been compared with other important rain attenuation models high The size of the area is not defined for a specific set of parameters [92] Not validated -…”

“…Empirical models SAM model [32] Singapore [33] Garcia [34] GSST [66] LU model [68] Karasawa [88] Breakpoint [29] Unified [89] YLO model [12] Statistical models M-K model [90] MARIMA [91] ITU-R P.618 [45] PEARP [92] Das Model 1 [93] Physical models Bryant [37] Crane TC [94] PM Model [95] SC EXCELL [62] Fade models Japan [96] Das model 2 [97] ITU-R P.1623 [98] Dao model [99] Learning-based AANN [100] The SAM model [32] has evolved through some previously published articles [101].…”

“…The PEARP model [92] is based on the probability of exceeding the attenuation threshold level. The steps of the PEARP model are shown in Algorithm 13.…”

Satellite to Ground Station, Attenuation Prediction for 2.4-72GHz Using LTSM, An Artificial Recurrent Neural Network Technology

“…They used a Ka-band with an antenna with a diameter of above 7.2m in tropical regions to prove this. Dahman et al [3] propose a binary decision probabilistic method for Ka frequency rain attenuation forecast using a predetermined threshold. It is a known protocol adjusted for probabilistic weather forecasts in a communication satellite control loop.…”

Rain Attenuation Estimation with the Numerical Weather Prediction Model WRF: Impact of Rain Drop Size Distribution for a Temperate Climate

“…Notably good statistical agreements were reported at 20.2 GHz in the south of France for small scale diversity sites over a one-year period [11]. Other studies have shown promises for the applications of NWP forecasts directly to FMTs [12], [13], or similarly for space missions [14], [15]. A more thorough statistical validation of the NWP performances would however still benefit any design based on them.…”