Study of Designation Algorithm of the Melting Layer Based on S-Band Dual-Polarization Radar
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Abstract:
Based on the principle of the melting layer detection algorithm (MLDA) from National Severe Storms Laboratory, some detection tests are carried out using S-band dual-polarization radar volume data from Jinan and Qingdao radar stations in July and August 2020. According to the test results, some improvement measures such as radial continuity check, increasing the range of scan elevation and adjusting the threshold of total radar bin number for identifying the melting layer are integrated into the MLDA, and the recognition effect of MLDA on the melting layer before and after improvement are compared and the conclusions are as follows. The melting layer could be identified by the MLDA, but the mean absolute error of the top height of the melting layer is large and the melting layer bottom height is too low. After the radial continuity check is integrated into the MLDA (MLDA-R1), the mean absolute error of the top height of the melting layer gets smaller obviously, the temperature of the bottom height and the thickness of the melting layer are within a reasonable range, but the number of the test not having detected the melting layer increases markedly. On the basis of the MLDA-R1, 3.3° elevation is added to the scanning area (MLDA-R2) and the threshold of total number of radar bin for recognizing the melting layer is adjusted (MLDA-R3). Then, the number of the test not having detected the melting layer is significantly reduced, and the identification effect of the height information of the melting layer is improved. Some areas containing precipitation echo and non-precipitation echo could be falsely detected as the melting layer by MLDA after improvement so that the recognition effect of the melting layer is influenced. In general, MLDA after the improvement is more applicable to S-band dual-polarization radar in China and it can be utilized to support the radar hydrometer classification and quantitative precipitation estimation.