Radar Reflectivity Simulation with a Numerical Cloud-Resolving Model for Dual-Frequency Terahertz Weather Radar

We proposed a dual-frequency terahertz weather radar to observe the distribution of cloud water and water vapor using a machine learning approach. The radar reflectivity data observed by the W-and D-band radars were simulated by using the output of the numerical cloud-resolving model. Our case study indicated that the dual-frequency terahertz radar that we are developing could detect non-precipitating clouds, and that the dual-frequency ratio, which is well correlated with the cloud water and water vapor contents, could be analyzed. This method can be used to generate training data for machine learning.