The Relative Calibration Adjustment Technique for Calibrating Australian Operational Radars in Near Real-Time

Rain radars provide three-dimensional information on the distribution of hydrometeors at high spatial (O(1 km)) and temporal (O(10 min)) resolution over an area roughly the size of a climate model grid-box. They are therefore in principle ideally suited to study processes that are sub-grid scale to climate models thereby supporting the development of parametrizations of such processes. They are also ideally placed to evaluate high-resolution simulations of precipitating cloud systems. However, to be useful for those purposes, they need to be well calibrated and contain information that is easily compared to models.

In order to properly and swiftly calibrate radar reflectivity, we develop and apply a Relative Calibration Adjustment (RCA) technique. The RCA technique is a statistical calibration method that uses the probability distribution of clutter area reflectivity near the stationary, ground-based radar to provide near-real-time estimates of the relative calibration of reflectivity data. This radar calibration method is shown to be a powerful benchmarking tool for monitoring datasets as it is (1) efficient - it automatically finds data that require a deeper investigation; (2) precise - it shows any change in radar's calibration; and (3) rapid. Nevertheless, the RCA needs to be used complementary with other calibration techniques so that it provides an absolute calibration. This is achieved by comparison with the space-borne radars TRMM and GPM.

We demonstrate the utility if the RCA method by applying it both to the calibration of a long-term (>15 years) research radar data set (CPOL in Darwin, 11°S, 131°E), and also to monitor the Australian operational weather radars.