Performance Evaluation of Micro Rain Radar Over Sumatra Through Comparison With Disdrometer and Wind Profiler

Abstract

Abstract-Micro Rain Radar (MRR) is a vertical pointing microwave profiler to measure hydrometeors and related parameters in high resolution. However, it is known that the MRR suffers from certain limitations due to several factors. This paper evaluates the performance of the MRR installed at Kototabang, west Sumatra, Indonesia (0.20 • S, 100.32 • E, 864 m above sea level). The DSD and rainfall rate from the MRR standard processing method had been evaluated by using collocated measurements of MRR, Parsivel disdrometer and Optical Rain Gauge (ORG) during 2014. Furthermore, 1.3 GHz wind profiler (BLR) observation was used to examine the vertical profiles of radar reflectivity and Doppler velocity. It was found that there were noticeable differences between the MRR and Parsivel in the small and large size ends of the DSD. At small sized drop (< 1 mm), the DSD spectra of MRR was higher than that obtained by the Parsivel otherwise it was smaller for large sized drop (> 2 mm). Underestimation of large sized drops in the MRR could be responsible for the underestimation of surface rainfall rate and daily rainfall. The source of differences in the DSD seems the measurement shortcomings such as attenuation correction and vertical wind effects, particularly during heavy rain. The shortcomings were observed from the comparison of mean Doppler velocity profiles between the MRR and the BLR. While the melting layer height of the two instruments was the same, the mean Doppler velocities of MRR shown downward increasing (DI) pattern through all rainfall intensities. On the other hand, for the BLR, the DI was only observed for heavy rain (> 10 mm/h), while downward decreasing was observed for light rain (< 5 mm/h). Similar pattern was also observed for the vertical profile of radar reflectivity. Thus, some corrections are needed for heavy rain, nevertheless, the MRR installed at Kototabang can be utilized for light rain. Comparisons indicated that the mean Doppler velocity and the DSD for the light rain as well as Z-R relation were in reasonable agreement with the reference of BLR, Parsivel and previous studies using the MRR.

Vertical Characteristics of Raindrops Size Distribution over Sumatra Region from Global Precipitation Measurement Observation

“…It means there is a decrease of large-sized drops toward the surface during stratiform rain over Sumatra region, which is consistent with the VPRG trend (Figure 2b). The decreasing Dm trend for stratiform rain is followed by Nw's increase that indicates the break-up process [42]. This result is different from previous studies at Kototabang in west Sumatra using MRR [18,20,42].…”

“…The decreasing Dm trend for stratiform rain is followed by Nw's increase that indicates the break-up process [42]. This result is different from previous studies at Kototabang in west Sumatra using MRR [18,20,42]. It may be due to a small-scale variability of vertical DSD over Sumatra.…”

“…Sumatra is located in the tropical region's warm pool, which is the most active convective area in the world [23]. Several studies have been conducted to study the vertical profile of DSD over Sumatra [18,24,25]. Renggono et al [24] observed DSD's vertical profile using Equatorial Atmospheric Radar (EAR).…”

“…Renggono et al [24] observed DSD's vertical profile using Equatorial Atmospheric Radar (EAR). Marzuki et al [25] and Ramadhan et al [18,20] observed the vertical profile of DSD using Micro Rain Radar (MRR). Using this instrument, they found the rainfall type and diurnal variation of DSD in Sumatra.…”

Improving Radar Rainfall Estimation by Accounting for Microphysical Processes Using a Micro Rain Radar in West Africa

“…This discrepancy between the rain estimated by the MRR and the in-situ observations could be explained by the fact that vertical wind effects were not taken into account in the processing of MRR data. Indeed, [44] and [45] found vertical wind to be a significant source of error, especially for heavy precipitation. In addition to the effect of vertical wind, there are the effects of turbulence, air density [36] and spectral folding [45] that were not considered in the processing chain.…”