## 1 Introduction  
Considering the spatial coverage of a single weather radar, the nationwide radar network can enhance the utilization of a weather radar in monitoring severe weather, radar rainfall estimation, hydrometeor classification algorithm, and short-term range forecasting of precipitation. Uniform quality maintenance among the individual radar observations in the network is the primary concern in terms of the utilization of the entire network. A heterogeneous radar network consisting of different frequencies, models, manufacturers, dual-polarization capability, and production years makes it difficult to maintain the same quality of radar data across the network. Even in a homogeneous radar network, establishing a regular radar calibration and monitoring procedure is essential to ensure high-quality data because miscalibration of individual radars results in considerable discrepancies in radar measurements over the network. Moreover, the miscalibration strongly affects the overall performance of network-based operational radar applications, such as nationwide quantitative precipitation estimation (QPE), quantitative precipitation forecasting, and hydrometeor classification algorithm. Unfortunately, miscalibration of radar reflectivity (\(Z_{\text{H}}\)) frequently occurs due to malfunctions of radar components and cannot be ignored in terms of supporting 24-hour routine weather forecasts. The real-time implementation of the accurate calibration of \(Z_{\text{H}}\) and its monitoring continues to be challenging despite regular maintenance and inspections(i.e., monthly, quarterly, and annual on-site inspections). Therefore, we aimed to develop an automated technique for real-time monitoring and calibration of \(Z_{\rm H}\) for an operational S-band dual-polarization weather radar. Various calibration approaches have been proposed for \(Z_{\rm H}\); they can be divided into three categories: (1) known reference sources such as the sun, a metal sphere, ground clutter (GC), and self-calibrated signal generator [1; 2; 3; 4; 5; 6; 7], (2) self-consistency (SC) principle between polarimetric observations [8; 9; 10; 11; 12; 13], and (3) comparison with external instruments such as disdrometer, vertically pointing radar, and space-borne weather radar [14; 15; 16; 17; 18; 19; 20; 21]. The SC principle is widely utilized for the \(Z_{\rm H}\) calibration of operational polarization weather radar because this approach does not require any comparative analysis using other instruments and external signal sources. The calibration bias of \(Z_{\rm H}\) can be estimated by calculating the phase-related observations from power-related observations during rain. Unfortunately, it is impossible to monitor the change in calibration bias during the non-precipitation period and snow in the winter season. The GC, which is an ever-present echo, can be used to monitor changes in calibration bias. The monitoring of radar calibration using GC was first introduced by [PERSON] [22]. [PERSON] et al. [7] introduced a relative calibration adjustment (RCA) technique to monitor the calibration status of an S-band dual-polarization radar. This technique uses the probability distribution of GC reflectivity (\(Z_{\rm C}\)) located near the radar at low elevation angles. [PERSON] et al. [7] found that the distribution of \(Z_{\rm C}\) can vary owing to the change in precipitation intensity, but the statistics of the \(Z_{\rm C}\) are relatively stable. In addition, the RCA technique can be applied to a radar located in significant anomalous propagation (AP) conditions because the statistics of \(Z_{\rm C}\) showed no significant change in AP conditions [7]. [PERSON] et al. [23] developed the RCA technique to monitor NASA's polarimetric surveillance radar in near-real-time during the Iowa Flood Studies (IFIoodS) Global Precipitation Measurements (GPM) field campaign. The RCA changed owing to a subtle change in the elevation angle of the antenna, a malfunctioning modulator, and a change in calibration bias. [PERSON] et al.