Satellite Precipitation Measurement by Unknown

Author:Unknown
Language: eng
Format: epub
ISBN: 9783030245689
Publisher: Springer International Publishing

Fig. 12.3Block diagram of precipitation type classification model

12.3 Melting Layer Detection

In the GPM DPR dual-frequency classification module, melting layer top and bottom heights for each qualified vertical profile are detected. The main information used in the model is the DFRm profile and its vertical variation. Referring to Fig. 12.1, we consider “DFRm pair” exists when both point B and C are detected. Then the melting layer top is defined as the height at which the slope of the DFRm hits a peak value. The melting layer bottom is defined as the height at which the DFRm has a local minimum value. Two horizontal dashed lines in Fig. 12.1 illustrate the melting layer top and bottom height for the profile using the above definition.

The criteria described above have been compared with other existing criteria in the literature using different radar parameters. Tilford et al. (2001) used the gradient of reflectivity (Z m) to detect the bright band top and bottom for stratiform rain type. The linear depolarization ratio (LDR) has been pointed out by many researchers as an important signature in melting phase detection, with certain thresholds determined for different hydrometeor particles (Smyth and Illingworth 2006; Bandera et al. 1998; Tan and Goddard 1995; Hines 1983). Typical vertical profiles of reflectivity as well as the corresponding velocity for stratiform and convective type were extensively studied by Fabry and Zawadzki (1995). Baldini and Gorgucci (2006) mentioned that the rapid change of the hydrometeor fall velocity is an implication of the melting layer. The curvature of velocity was used by Zrnić et al. (1994) in characterizing the melting boundaries. Klaassen (1988) found that the melting bottom can be detected by maximum of velocity. Table 12.1 summarize the comparison of melting layer detections between criteria in DFRm method and other existing criteria. The comparison results using airborne radar data (NAMMA, GRIP and Wakasa Bay experiment). From the table, estimations from the DFRm method match best with velocity-based criteria with normalized bias of 1.3% and 2.2% for melting layer top and bottom respectively. The DFRm method also compares well with the LDR criteria, with a −28 dB threshold, the bias between these two criteria is around −2.8%. Details can be found in Le and Chandrasekar (2013b). Figure 12.4 is the block diagram of melting layer detection used in the most updated version of dual-frequency classification module.Table 12.1Comparisons of melting layer boundaries between different criteria for NAMMA, GRIP and Wakasa Bay data

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