Characteristics of Precipitation Diurnal Cycle over a Mountainous Area of Sumatra Island including MJO and Seasonal Signatures Based on the 15-Year Optical Rain Gauge Data, WRF Model and IMERG

Marzuki, Marzuki; Muharsyah, Robi; Ramadhan, Ravidho; Tangang, Fredolin; Amirudin, Abdul Azim; Hashiguchi, Hiroyuki; Shimomai, Toyoshi; Vonnisa, Mutya

doi:10.3390/atmos13010063

Cited by 15 publications

(10 citation statements)

References 51 publications

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“…Although most stations showed that IMERG overestimated rainfall, 35.4% of MRG and 41.8% of AWS stations showed that IMERG underestimated it. The dominance of the overestimated value from the observations of hourly rainfall found in this study was consistent with the pattern of overestimation often found from IMERG observations [15,42,67,68]. From all continuous statistical quantities, it can be seen that the accuracy of hourly rainfall observations from IMERG at IMC still needs to be improved.…”

Section: Hourly Assessmentsupporting

confidence: 89%

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Evaluation of GPM IMERG Performance Using Gauge Data over Indonesian Maritime Continent at Different Time Scales

et al. 2022

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Accurate precipitation observations are crucial for water resources management and as inputs for a gamut of hydrometeorological applications. Precipitation data from Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (GPM) (IMERG) have recently been widely used to complement traditional rain gauge systems. However, the satellite precipitation data needs to be validated before being widely used in the applications and this is still missing over the Indonesian maritime continent (IMC). We conducted a validation of the IMERG product version 6 for this region. The evaluation was carried out using gauge data in the period from 2016 to 2020 for three types of IMERG: Early (E), Late (L), and Final (F) from annual, monthly, daily and hourly data. In general, the annual and monthly data from IMERG showed a good correlation with the rain gauge, with the mean correlation coefficient (CC) approximately 0.54–0.78 and 0.62–0.79, respectively. About 80% of stations in the IMC area showed a very good correlation between gauge data and IMERG-F estimates (CC = 0.7–0.9). For the daily assessment, the CC value was in the range of 0.39 to 0.44 and about 40% of stations had a correlation of 0.5–0.7. IMERG had a fairly good ability to detect daily rain in which the average probability of detection (POD) for all stations was above 0.8. However, the false alarm ratio (FAR) value is quite high (<0.5). For hourly data, IMERG’s performance was still poor with CC around 0.03–0.28. For all assessments, IMERG generally overestimated rainfall in comparison with rain gauge. The accuracy of the three types of IMERG in IMC was also influenced by season and topography. The highest and lowest CC values were observed for June–July–August and December–January–February, respectively. However, categorical statistics (POD, FAR and critical success index) did not show any clear seasonal variation. The CC value decreased with higher altitude, but with slight difference for each IMERG type. For all assessments conducted, IMERG-F generally showed the best rainfall observations in IMC, but with slightly difference from IMERG-E and IMERG-L. Thus, IMERG-E and IMERG-L data that had a faster latency than IMERG-F show potential to be used in rainfall observations in IMC.

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Section: Hourly Assessmentsupporting

confidence: 89%

“…For the Maritime Continent area itself, the validation of rainfall in hourly resolution has never been done, with the highest temporal resolution validated so far in Maritime Continent being daily. The accuracy of hourly rainfall data is critical for IMC in view of the dominant diurnal variation of rainfall in this area [5,17,67].…”

Section: Hourly Assessmentmentioning

confidence: 99%

Evaluation of GPM IMERG Performance Using Gauge Data over Indonesian Maritime Continent at Different Time Scales

et al. 2022

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“…These 1-min data are then summed to obtain daily data that will be used to validate the IMERG-F. As a quality control, we only used data that were complete within one day of observation. The ORG data at Kototabang has been widely used in several studies, which shows its reliability in rainfall observations (Marzuki et al, 2009(Marzuki et al, , 2013(Marzuki et al, , 2022Marzuki, Hiroyuki, et al, 2016). The ORG in Kototabang collected data from 2002 to 2016.…”

Section: Optical Rain Gauge Datamentioning

confidence: 99%

Ground Validation of GPM IMERG-F Precipitation Products with the Point Rain Gauge Records on the Extreme Rainfall Over a Mountainous Area of Sumatra Island

Ramadhan

Marzuki

Muharsyah

et al. 2022

jppipa, pendidikan ipa, fisika, biologi, kimia

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Accurate satellite precipitation estimates over areas of complex topography are still challenging, while such accuracy is of importance to the adoption of satellite data for hydrological applications. This study evaluated the ability of Integrated Multi-satellitE Retrievals for GPM -Final (IMERG) V06 product to observe the extreme rainfall over a mountainous area of Sumatra Island. Fifteen years of optical rain gauge (ORG) observation at Kototabang, West Sumatra, Indonesia (100.32°E, 0.20°S, 865 m above sea level), were used as reference surface measurement. The performance of IMERG-F was evaluated using 13 extreme rain indexes formulated by the Expert Team on Climate Change Detection and Indices (ETCCDI). The IMERG-F overestimated the values of all precipitation amount-based indices (PRCPTOT, R85P, R95P, and R99P), three precipitation frequency-based indices (R1mm, R10mm, R20mm), one precipitation duration-based indices (CWD), and one precipitation intensity-based indices (RX5day). Furthermore, the IMERG-F underestimated the values of precipitation frequency-based indices (R50mm), one precipitation duration-based indices (CDD), one precipitation intensity-based indices (SDII). In terms of correlation, only five indexes have a correlation coefficient (R) > 0.5, consistent with Kling–Gupta Efficiency (KGE) value. These results confirm the need to improve the accuracy of the IMERG-F data in mountainous areas.

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“…The Inter-tropical convergence zone (ITCZ) strongly influences the seasonal rainfall in this region, along with the southeast and northwest monsoons [27][28][29]. As a result, Kototabang has 2 peaks in the rainy season, occurring in March-April and November-December [20,22]. Additionally, the area exhibits a significant diurnal rainfall pattern, with the peak rainfall occurring in the afternoon between 1600 -1700 Local Time (LT) [22,30,31].…”

Section: Study Area and Optical Rain Gauge Datamentioning

confidence: 99%

“…The localized rainfall pattern in this region means that surface rainfall data with high accuracy and resolution is needed to improve regional weather and climate forecasting models. Previous evaluations have shown that the IMERG data in the IMC still needs improvement, especially for daily and hourly resolution and in areas with complex topography [19][20][21][22][23][24]. The IMC region has a complex land surface and numerous mountains due to its location in the Ring of Fire.…”

Section: Introductionmentioning

confidence: 99%

Bias Correction of IMERG Data in the Mountainous Areas of Sumatra Based on A Single Gauge Observation

Ramadhan,

Marzuki,

Suryanto

et al. 2024

Trends Sci

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The performance of surface precipitation data from satellite precipitation products (SPPs) in mountainous areas has greater error and bias than in plain areas. In this study, linear scaling (LS), local intensity (LOCI), power transformation (PT), and cumulative distribution function (CDF) methods are used to correct the bias of Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) data in the mountainous region of Sumatra based on long-term and high-resolution optical rain gauge (ORG) observations. The ORG is installed at Equatorial Atmospheric Observatory (EAO) in Kototabang, West Sumatra, Indonesia (100.32 °E, 0.20 °S, 865 m above sea level (ASL) with an observation period from 2002 to 2016. The impact of the bias correction method is tested based on accuracy and capability detection tests. The bias correction method is more effective at the daily resolution than the hourly resolution of the IMERG data in the mountainous region of Sumatra. The LS method exhibited the best improvement in accuracy with reduced root-mean-square error (RMSE) and relative bias (RB), although there was no significant increase in coefficient correlation (CC) values. However, the accuracy improvement was not observed in the bias correction for hourly data. The lack of improvement in the accuracy of the hourly IMERG data is due to the high local variability of rainfall in the mountainous area of Sumatra. The high data variability causes large differences in the mean and variance of the IMERG calibration and evaluation data periods. On the other hand, the LOCI, PT, and CDF methods were successfully improved the rain detection capability of IMERG, as indicated by the better critical succession index (CSI) values compared to the original hourly and daily IMERG data. It increased the CSI value by reducing false alarms for rain with intensity below 2 mm/h. Furthermore, the CDF method can improve the analysis of extreme rainfall in the mountainous region of Sumatra by improving the estimation of the extreme rainfall index. Therefore, these methods can be applied to improve the accuracy and detectability of IMERG data in the mountainous region of Sumatra. However, the scale factor and transfer function constructed in this study need to be further evaluated on other rain gauge observation data in Sumatra’s mountainous region to improve performance. HIGHLIGHTS The LS method shows the best improvement in the accuracy of IMERG data in the mountainous area of Sumatera compared to the LOCI, PT, and CDF methods, as indicated by the largest decrease in RMSE and RB values CSI values prove that LOCI, PT, and CDF methods successfully improve the detection capability of IMERG hourly and daily data in the mountainous region of Sumatra The CDF method shows the best quality in improving extreme rainfall observations in the mountainous region of Sumatra GRAPHICAL ABSTRACT

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Characteristics of Precipitation Diurnal Cycle over a Mountainous Area of Sumatra Island including MJO and Seasonal Signatures Based on the 15-Year Optical Rain Gauge Data, WRF Model and IMERG

Cited by 15 publications

References 51 publications

Evaluation of GPM IMERG Performance Using Gauge Data over Indonesian Maritime Continent at Different Time Scales

Evaluation of GPM IMERG Performance Using Gauge Data over Indonesian Maritime Continent at Different Time Scales

Ground Validation of GPM IMERG-F Precipitation Products with the Point Rain Gauge Records on the Extreme Rainfall Over a Mountainous Area of Sumatra Island

Bias Correction of IMERG Data in the Mountainous Areas of Sumatra Based on A Single Gauge Observation

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