Precipitation microstructure in different Madden–Julian Oscillation phases over Sumatra

Marzuki, Marzuki; Hashiguchi, Hiroyuki; Kozu, Toshiaki; Shimomai, Toyoshi; Shibagaki, Yoshiaki; Takahashi, Yukihiro

doi:10.1016/j.atmosres.2015.08.022

Cited by 43 publications

(34 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The radar echoes were assumed as precipitation only if surface rain rate was larger than 0.1 mm/h. Furthermore, to ensure that both instruments are simultaneously observing rain, only the echoes having the radar reflectivity and Doppler velocities greater than 18 dBz and 3 m/s, respectively, were analyzed [21,15,9].…”

Section: 3 Ghz Boundary Layer Radarmentioning

confidence: 99%

“…Thus, new attenuation correction scheme [30] may have been adopted to our instrument. The instrument is reinstalled in September 2011 and few results are published in a literature [9]. However, the performance of our MRR has not yet been investigated in detail.…”

Section: Introductionmentioning

confidence: 99%

“…A pioneering study on the DSD was conducted at Bogor, west Jawa, Indonesia, by using a raindrop camera [12]. The number of study particularly at Kototabang, west Sumatra increases after Equatorial Atmosphere Radar (EAR) facilities were completed in this area [1,9,[13][14][15][16][17][18]. Furthermore, regional variability of DSD along the equatorial Indonesia has been also observed through a network of Parsivel disdrometer observation at Kototabang, Pontianak, Manado and Biak [19].…”

Section: Introductionmentioning

confidence: 99%

“…The equation relates the measured Z and the estimated R and can be derived traditionally from long-term observations of DSD [6,7]. Finally, knowledge of the DSD is also important in cloud physics [8,9], soil erosion study [10], and harvesting energy from raindrop [11].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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

Marzuki¹,

Hashiguchi²,

Shimomai³

et al. 2016

PIER M

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: 3 Ghz Boundary Layer Radarmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Marzuki¹,

Hashiguchi²,

Shimomai³

et al. 2016

PIER M

Self Cite

View full text Add to dashboard Cite

show abstract

“…This special area is predicted to be a key site for developing a large low pressure mass due to the Madden Julian Oscillation (MJO) (Yoneyama, personal communication [10]. This large low pressure area with a diameter of about 12,000 km can move eastward taking 30 to 60 days into the middle of the Pacific Ocean in relation with the occurrence of El Niñoand La Niña phenomena [11][12][13]. In this study, the Madden Julian Oscillation has come over the R/V MIRAI during the cruise, MR15-04 in the last week during the sampling 3 weeks at the fixed point of 04˚00'S102˚00'E located 50 km in the southern-eastern direction from Sumatra Island.…”

Section: Madden-julian Oscillation and Resistance To Lower Temperaturmentioning

confidence: 99%

Relationship between Cool Coma and Heat Coma Temperatures in the Oceanic Sea Skaters Halobates Collected near the Sumatra Island in the Indian Ocean

Furuki¹,

Umamoto²,

Ohoka³

et al. 2017

View full text Add to dashboard Cite

In the cruise, MR15-04 by R/V MIRAI, the samplings by the neuston net were performed in 23 rd November to 14 th December 2016 and three species of Halobates (H. germanus, H. micans, H. sp) were used for the temperature tolerance experiments after the collection. The neuston net was towed three times (3 × 15 min) on the starboard side of R/V MIRAI on the water surface with ship speed of 2 knot to water every 3 nights (19:00 -20:00) at the fixed point in the south-western direction which was located at 50 km from the Sumatra island (4˚03'S -4˚05'S, 101˚53'E) in the Indonesia. Experiments on cool coma and heat coma were performed on the three species. Seconds for recovery from cool coma and heat coma were also examined on the Halobates in this study. Cool coma temperatures, gap temperature needed (temperature from the adapted temperature) for the cool coma and seconds for the recover from cool coma ranged 13.0˚C to 25.0˚C, 3.1˚C to 16.1˚C, 1 second to 4370 seconds, respectively. Heat coma temperature, gap temperature needed for the heat coma, seconds for the recover from heat coma ranged 29.4˚C to 43.1˚C, 1.9˚C to 15.5˚C, 2 seconds to 6420 seconds, respectively. The higher temperature of cool coma temperature during the last five days was shown when Madden-Julian Oscillation has passed over the ship, R/V MIRAI than the previous 10 days in the adults of H. germanus collected at the fixed place neat to Sumatra island (One way ANOVA: F-value = 2.314, df = 7, p = 0.028). Adults of un-described species, H. sp lower cool coma temperatures shown by this un-described species might be related to that this species should be a "shore" species inhabiting shore water in which many precipitation could cause the decreased surface temperature from 30˚C -31˚C into about 25˚C. Most of adults which suffered from the cool coma recovered within 20 seconds, whereas adults which suffered heat coma at 38˚C and 39˚C needed more than 200 seconds for the recovery and many of those which did it at more than 40˚C needed more than 1000 second and some ones did not recover at all. All adults who suffered at more than 43˚C did not recover at all. There were significant and negative correlation between cool and heat coma temperatures shown by the adults of H. germanus. This correlation might imply a common physiological mechanism for lower and higher temperature tolerances for this species.

show abstract

Predicting Subseasonal Precipitation Variations Based on the Madden‐Julian Oscillation

Jones

2017

Climate Extremes

View full text Add to dashboard Cite

Precipitation microstructure in different Madden–Julian Oscillation phases over Sumatra

Cited by 43 publications

References 50 publications

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

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

Relationship between Cool Coma and Heat Coma Temperatures in the Oceanic Sea Skaters Halobates Collected near the Sumatra Island in the Indian Ocean

Predicting Subseasonal Precipitation Variations Based on the Madden‐Julian Oscillation

Contact Info

Product

Resources

About