Abstract Time series prediction of rain attenuation from rain rate measurement during rain is made by using Synthetic Storm Technique (SST) for Ka and Q band signal for a temperate location, Vigo, Spain. Rain rate and rain attenuation data for the three year measurement period from 2016 to 2018 have been used to test the validity of the SST model at the present location. As we move from the Ka band to the Q band, larger value of predicted rain attenuation for the same rain rate is observed. For a single rain event, better prediction depends on the actual storm speed measured for the present location. But the long term statistics of predicted rain attenuation are insensitive to storm translation speed. Applicability of the SST model is tested for predicting diurnal, monthly and yearly statistics. Comparison between prediction and measurements are done for both first (rain attenuation occurrence) and second order (fade duration) statistics. Good matching has been observed between prediction and measurement for single rain event as well as for long term statistics. Prediction errors are found to be less than 0.5 dB in all the cases which proves the efficiency of the SST model for the present location.

中文翻译：

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合成风暴技术在 Ka 和 Q 波段降雨衰减预测中的应用，适用于西班牙 Vigo 温带地区

摘要 通过对西班牙维戈的 Ka 和 Q 波段信号使用合成风暴技术 (SST) 进行降雨期间降雨率测量的降雨衰减时间序列预测。利用2016年至2018年三年测量期的降雨率和雨衰数据来检验SST模型在当前位置的有效性。当我们从 Ka 波段移动到 Q 波段时，观察到相同降雨率的预测雨衰值更大。对于单个降雨事件，更好的预测取决于当前位置测量的实际风暴速度。但是预测降雨衰减的长期统计数据对风暴平移速度不敏感。测试 SST 模型的适用性以预测日、月和年统计数据。对一阶（雨衰发生）和二阶（衰落持续时间）统计进行预测和测量之间的比较。在预测和测量单一降雨事件以及长期统计数据之间已经观察到良好的匹配。在所有情况下发现预测误差都小于 0.5 dB，这证明了 SST 模型对当前位置的有效性。