The accuracy of surface rainfall observations in complex topographic regions remains challenging, particularly for sub-daily and daily temporal resolutions. This study assesses the accuracy of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (GPM) IMERG in the mountainous region of Sumatra using optical rain gauge (ORG) data from Kototabang, West Sumatra, Indonesia [100.32° E, 0.20° S, 865 m above sea level (ASL)] during the 15-year observation period (2002–2016). The validation methods tested are based on the direct [point-to-pixel (PtP)] and the indirect methods of IMERG to the point gauge. The indirect methods used include mean, median (med), linear interpolation (LI), nearest-neighbor interpolation (NI), Inverse Distance Weighting (IDW) interpolation, and kriging (Krg) interpolation. The IMERG data validation generally indicates better correlation coefficient (CC) and critical success index (CSI) values for the indirect methods than the PtP method. For hourly data, the CC (CSI) values across all indirect methods range around 0.28 (0.28), while using the PtP method, CC is 0.25 (0.27). For daily data, nearly all indirect methods show a CC value of 0.50, except for the NI method which exhibits a CC of 0.47, the same as the CC value from the PtP method. Besides CC and CSI, the root mean square error (RMSE) and relative bias (RB) values of the indirect methods also show slightly better values than the PtP method. Despite the differing accuracy and probability detection between the direct and indirect IMERG data validation methods, the discrepancies in CC and CSI values between the methods are not impressive. Thus, the choice of validation method for complex topographic regions can be tailored based on the data processing capabilities and specific needs.

Floods in Indonesia are often triggered by heavy rainfall with a long duration. Such heavy rainfall was influenced by several factors include seasons, Madden-Julian oscillation (MJO), and La Nina. The number of flood events in Indonesia in term of seasons, MJO, and La Nina has been observed from the Indonesian National Board for Disaster Management (BNPB) data from 2008 to 2020. Flood events in Indonesia during the 13-year observation showed the increase of annual trend in accordance with the global disasters trend. Floods events showed a significant seasonal variation with maximum number of occurence during January and February and minimum during August, coincided with the monthly rainfall pattern concerning the monsoon seasons in Indonesia. Furthermore, the MJO strongly modulated the number of flooding in Indonesia, where the flood occurence during strong MJO is more than twofold compared to weak MJO. The peak number of flood events during strong MJO was observed in 3, 4, 5 phases. In addition, La Nina modulated the number of flood events more significantly in the wet season, while in the dry season, La Nina effect was not significant compared to seasonal variation.

Diurnal cycles are the main factor determining the rain pattern in the Indonesian maritime continent. In-depth research regarding diurnal rainfall patterns is very important for strategic planning of urban area development. This study analyzes the influence of the season on diurnal rainfall patterns in the New Capital City of Indonesia (IKN) based on Integrated Multi-satellite Retrievals for GPM (IMERG) data from January 2001 to April 2019 with a data resolution of 0.1°–30 min. Analysis of the influence of the season on the diurnal pattern was observed based on the parameters of precipitation amount (PA), precipitation frequency (PF), and precipitation intensity (PI). An increase in PA and PF values was observed from November to May, while a decrease in PA and PF values was observed from June to October. The highest increases in PA and PF values were observed in March, April, and December, which are consistent with the peak of seasonal rainfall in IKN. The dominant increase in PA and PF values in that month was caused by an increase in the percentage of occurrence of long-duration (> 6 h) rainfall. On the other hand, an increase in the value of PI shows a non-uniform pattern following the season which indicates the season factor is not the main triggering factor of PI. Furthermore, the seasonal factor also affects the time of the diurnal rain peak in IKN. Peak rainfall is observed during July–August [1300–1400 local solar time (LST)] compared to other months (1500–1600 LST). The earlier diurnal peak time of rainfall is a result of reduced cloud cover during July–August, which intensifies solar insolation and accelerates the attainment of thermal contrast.

The availability of surface rainfall data with high spatial -temporal resolution is needed to understand the diurnal rainfall characteristics in the Indonesian Maritime Continent (IMC) to improve the accuracy of weather and climate models in this region. This study validates the accuracy of the Final Run product of IMERG data version 06B (V06B) and version 07A (V07A), which have a resolution of 0.1 degrees - 30 min for diurnal rainfall analysis over IMC. Validation was conducted for precipitation amount (PA), precipitation frequency (PF), and precipitation intensity (PI), by recording 302 automatic rain gauges (RG) every 10 min from January 2014 to September 2021. IMERG V06B and V07A perform well in observing diurnal PA and PF but struggle in observing diurnal PI compared to RG observations. This has been determined by the correlation coefficient (CC) values of IMERG V06B (V07) data, which are 0.76 (0.72) for PA, 0.77 (0.76) for PF, and 0.21 (0.13) for PI. The IMERG data align to an extent with RG observations for the PA value, having a small relative bias (RB). The results also display a systematic PF and PI values error. The high false alarm ratio (FAR) of IMERG data suggests rain detection errors, leading to overestimated PF values. Additionally, the underestimation of PI values is due to the limitation of IMERG data in observing extreme and small-scale rain events. About 86.10% (78.14%) and 81.45% (81.78) of IMERG V06B (IMERG V07A) data show a peak time difference of <3h for PA and PF when compared with RG observations. Overall, IMERG V06B performs better than V07, possibly due to inaccurate orbits of GPROF data, removal of SAPHIR satellite observations, and inter -calibration issues with CORRA and GPCP data. Continuous monitoring and data improvements are necessary to improve the accuracy and reliability of IMERG data in detecting diurnal rainfall patterns in the IMC region.

This study employs the Okada Method to analyze the horizontal seismic deformation of the Palu earthquake on September 28, 2018, with a magnitude of 7.5 Mw. Data from InaCORS stations (WATP, CPRE, CPAL, TOBP, and CMLI) strategically positioned near the earthquake epicenter were processed using Gfortran software, and deformation was mapped using GMT software. The analysis focuses on the 100 Days of Year (DOY) period from August 6 to November 28, 2018. Results indicate that during the co-seismic phase (DOY 272), InaCORS stations experienced deformations ranging from 477.130 mm to 7.7852 mm. The magnitude of deformation varied based on station proximity to the epicenter, with the largest displacement observed at TOBP and the smallest at CPRE. Station movements were divergent, with northern stations shifting northward and southern stations moving southward. Subsurface slip reached 1449.23 mm, affecting an area measuring 145 km by 76 km at a depth of 8 km, dip of 65˚, strike of 351˚, and rake of -46˚. These findings contribute valuable insights into the seismic impact on the Earth's crust, aiding seismic hazard assessments in the region

This study examines the land-sea contrast in the vertical structure of precipitation over Sumatra and its surrounding ocean using eight years (2014-2021) of dual-frequency precipitation radar (DPR) data from the Global Precipitation Measurement (GPM) mission. The study area is segmented into Ocean, Coast I (west coast), Land I (west of Barisan Mountains), Land II (east of Barisan Mountains), and Coast II (east coast). The effective reflectivity factor (Z(e)), rainfall rate (R), and two raindrop size distribution (DSD) parameters, namely the mass-weighted mean diameter (D-m) and the normalized intercept (N-w), were analyzed. Stratiform and deep convective rainfall were the most frequent types in Coast I, followed by Ocean, Land I, Land II, and Coast II. In contrast, shallow convective rainfall was the most common type in Ocean, followed by Coast I, Land I, Land II, and Coast II. The average rain top height (RTH) was found to be higher in Land II and Coast II than in Ocean, Coast I, and Land I, in accordance with the surface rainfall intensity pattern previously reported by other studies. Furthermore, the data on heavy ice precipitation demonstrated an increase from the ocean to the coast and land, with a significant number of instances observed in Land I, Land II, and Coast II, in addition to Coast I. This contrast in heavy ice precipitation and RTH influences DSD. The land-sea contrast of DSD is more pronounced for deep convective rains. Deep convective exhibited a lower frequency of large raindrops over the ocean than over the coast and land, as reflected in the D-m profile. Conversely, raindrop concentration, particularly small drops, was higher at sea. The percentage of D-m > 2 mm at sea was approximately 2%, rising to 4-6% in Land II and Coast II. The land-sea contrast in the vertical structure of precipitation over Sumatra exhibited apparent diurnal variation. Larger D-m and smaller N-w were observed over Land I and Coast I, particularly in the afternoon and evening, correlating with peak rainfall. This pattern aligns with heavy ice precipitation profiles, vertical relative humidity (RH), and wind profiles. This study highlights the complexities and potential discrepancies between vertical precipitation profiles and surface precipitation data, underscoring the nuanced nature of land-sea precipitation migration.

Nobita Hill, a tourist site in Padang City, is undergoing development as a tourist destination that offers a bird's-eye view of Padang City. Unfortunately, the hilly topography with steep slopes increases the risk of landslides in this area. In order to address the problem, the community service team from the Physics Department of Andalas University has carried out a six-month community service program from July to December 2022. It focused on disaster awareness education and used a qualitative approach. This activity aims to socialize disaster mitigation efforts, especially those related to landslides and earthquakes, considering that Padang City is also prone to earthquakes. The results of this activity showed an increase in the knowledge of the local community after the socialization, but repeated activities are needed to achieve optimal results. This ongoing activity is essential to ensure continuous improvement in the community's understanding of disaster mitigation and to support efforts to make Bukit Nobita a disaster-resilient area. Thus, this activity makes a positive contribution to shaping a safe, sustainable, and disaster-resilient tourism environment.

Ultra-low frequency (ULF) emissions and total electron content (TEC) anomalies are potential earthquake precursors for short-term earthquake prediction. This study comprehensively examines ULF emissions and TEC anomalies associated with the Sumatra earthquakes spanning 2019-2020. Precursor ULF emissions are identified through the polarization power ratio calculations involving Z-component and H-component geomagnetic data, meticulously recorded by the Magnetik Acquisition Data System (MAGDAS). Employing the Single Station Function Transfer technique, ULF anomalies directed toward the epicenter of earthquakes are recognized as reliable precursors. Among the 29 earthquakes scrutinized, 25 were heralded by ULF emissions acting as precursors. Among these, 15 instances solely exhibited ULF emissions, unaccompanied by TEC anomalies, while the remaining ten were linked to TEC anomalies. The investigation of TEC anomalies employs advanced autocorrelation techniques rooted in the analysis of correlation coefficient deviations. TEC anomalies are meticulously acquired from the observations of the Sumatran GPS Array (SuGAr) stations. Furthermore, this study illuminates a positive correlation (R = 0.65) between the lead time of ULF emissions and TEC anomalies. Moreover, the frequency of ULF emissions and TEC anomalies also showcases a direct relationship with earthquake magnitude. Heightened frequencies of ULF emissions and TEC anomalies as earthquake precursors correspond to more significant magnitudes in ensuing earthquakes. The outcomes of this research significantly augment the understanding of employing ULF emissions and TEC anomalies as effective earthquake precursors in the context of Sumatra.

Background The Suban area of Curup Rejang Lebong is a tourist region in Bengkulu Province, Indonesia, close to the active Ketaun and Musi faults, which are segments of the Sumatra Fault System (SFS). However, no studies have been conducted in this area to assess how geological structures affect seismic ground motions and contribute to seismic hazard and risk assessment. Methods The first study of seismic microzonation in the Suban area of Curup City by ambient noise measurements was conducted at 100 sites, spaced ~ 1 km apart, with 60 min of data acquisition for each site. All microseismic data were processed using the Horizontal to Vertical Spectral Ratios (HVSR) method. Results The HVSR method revealed the amplification factors ( A 0 ) ranging from 1.23 to 8.26 times, corresponding to natural frequency ( f 0 ) variations between 1.24 and 9.67 Hz. About 13% and 55% of the sites show high (6 ≤ A 0 ≤ 9) and medium (3 ≤ A 0 ≤ 6) amplifications, respectively, predominantly in the western parts of the study area, consistent with a high seismic vulnerability index ( K g ). Furthermore, we also estimated the ground shear strain (GSS) of the region using the Kanai method with two large historical earthquakes at the Ketahun segment in 1943 (Mw 7.4) and the Musi segment in 1979 (Mw 6.0). The K g value is consistent with the GSS values and indicates areas of severe damage during the historic earthquakes. Conclusions Thus, the western parts of the Suban region are vulnerable to severe damage from an earthquake. These findings could provide valuable insights for future planning and risk management efforts aimed at minimizing the impact of earthquakes in the Suban region.

Accurate and current rainfall analysis is crucial for planning and development in the new capital city of Indonesia (IKN). This study examines the effect of the Madden-Julian Oscillation (MJO) on rainfall variability in IKN using a 20-year dataset of Integrated Multi-Satellite Retrievals for GPM (IMERG) version 6 and automatic weather station (AWS) data. The study analyzes flood events in IKN by examining flood information provided by the National Agency for Disaster Countermeasures (BNPB) from 2008 to 2022 and the contribution of the MJO to these events. The findings indicate that the MJO significantly influences rainfall variability in IKN, with a more pronounced effect during the dry season (JJASO) than in the wet season (NDJFMAM). This is demonstrated by the higher occurrence of wet days and increased daily rainfall intensity, which is linked to extreme rainfall and longer-duration events, mainly between midnight and morning (0400–0600 LST). Notably, although floods are more common during the rainy season, the MJO can intensify flood events in IKN during the dry season. Therefore, when developing an effective flood disaster mitigation system for IKN, it is crucial to consider the amplitude and phase of the MJO.

The Barisan Mountains influence atmospheric circulation in Sumatra and surrounding areas. Yet, precipitation patterns in eastern Sumatra, especially along the coast, are poorly understood. This study examines diurnal precipitation cycles in coastal seas and small islands of eastern Sumatra, utilizing 2015–2021 IMERG Version 06 rainfall data, data from 21 island rain gauges, and ERA5 reanalysis data to assess precipitation through three parameters: precipitation amount (PA), precipitation frequency (PF), and precipitation intensity (PI). The diurnal cycle of PA and PF is more pronounced than PI. Distinct diurnal precipitation patterns emerge between coastal seas and small islands despite their shared east coast location on Sumatra. Coastal seas exhibit early morning precipitation peaks forming Sumatras squall, influenced by offshore Sumatra and Malay Peninsula propagations, accentuated by high wind speeds. Coastal shape, land topography, and Sumatra's island size also impact coastal sea precipitation. On small islands, rainfall peaks earlier (12:00–15:00 LT) with gentle winds, indicating local convection due to land heating dominance. In addition, the low-amplitude topography of Bangka and Belitung islands also increase rainfall, so PA and PF are higher on these islands than on other small islands. Seasonal analysis reveals rising PA and PF near the equator during the dry southeast monsoon (SEM), linked to the dominant Inter-Tropical Convergence Zone (ITCZ). Conversely, areas like Bangka, Belitung, and the South Coast of Sumatra, farther from the equator, witness higher PA and PF during the wet northwest monsoon (NWM). The South Coast of Sumatra saw a substantial PA increase during NWM, about 60% higher than the southeast dry period. Despite varying cycle amplitudes, peak times for PA and PF remain consistent across seasons. MJO analysis during NWM highlights heightened PA and PF amplitudes across eastern Sumatra, especially over equator-adjacent coastal regions and small islands, reaching 40–70% above non-active MJO phases. In summary, this research examines diurnal precipitation variations in coastal seas and small islands of eastern Sumatra, enhancing understanding of regional climate patterns and factors impacting precipitation cycles in the area.

The El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) are widely recognized as the leading modes of climate variability in the tropics. This paper investigates the impact of different ENSO positions and IOD events on Indonesian rainfall during the period 1950–2021. The ENSO position is determined by the largest value of four Niño indices: Niño 1+2, Niño 3, Niño 3.4, and Niño 4. These ENSO positions are hereafter referred to as El-Niño/La-Niña 1+2, El-Niño/La-Niña 3, El-Niño/La-Niña 3.4, and El-Niño/La-Niña 4, respectively. The Dipole Mode Index (DMI) was used to observe IOD events. Different ENSO positions and IOD events result in different responses to Indonesian rainfall, obtained from the European Center for Medium-Range Weather Forecasts (ECMWF) ERA-5 data. The most significant decrease in rainfall occurs during the June-to-Septempber (JJAS) season of El-Niño 3. Conversely, during El-Niño 3.4, rainfall increases in the Sumatra and part of Kalimantan regions. The most significant increase in rainfall occurs during La-Niña 3.4, followed by La-Niña 4, La-Niña 3, and La-Niña 1+2. During a positive IOD phase, the southern part of western Indonesia experiences a decrease in precipitation of more than 30%. A more significant decrease in rainfall (>40%) occurs when a positive IOD co-occurs with El-Niño. During a negative IOD phase, Indonesia's rainfall patterns become more spatially variable. An increase in rainfall is more pronounced when a negative IOD co-occurs with La-Niña. The difference in Indonesian rainfall during different ENSO positions and IOD phases is related to differences in atmosphere-ocean interaction during each condition.

Fish deaths in Maninjau Lake have been frequently reported. Apart from fishery activities, this can also be caused by changes in atmospheric conditions around Lake Maninjau due to changes in land cover around Lake Maninjau. Therefore, this study analyzes land cover changes and deforestation in 2001 and 2020 and their relationships with surface temperature and rainfall. Rainfall data and extreme temperatures were obtained from the Integrated Multi-satellite Retrievals for GPM (IMERG) and ECMWF v5 (ERA5), respectively. Land cover data based on the Landsat satellite is used to see land changes. The results showed a decrease in the amount of vegetated land every year and an increase in residential and building land and agricultural land, which correlates with an increase in the surface temperature in the Maninjau area. Furthermore, the results also show a coherent relationship between rainfall trends and areas of deforestation.

This study is a preliminary assessment of the latest version of the Global Satellite Measurement of Precipitation (GSMaP version 08) data, which were released in December 2021, for the Indonesian Maritime Continent (IMC), using rain gauge (RG) observations from December 2021 to June 2022. Assessments were carried out with 586 rain gauge (RG) stations using a point-to-pixel approach through continuous statistical and contingency table metrics. It was found that the coefficient correlation (CC) of GSMaP version 08 products against RG observations varied between low (CC = 0.14–0.29), moderate (CC = 0.33–0.45), and good correlation (CC = 0.72–0.75), for the hourly, daily, and monthly scales with a tendency to overestimate, indicated by a positive relative bias (RB). Even though the correlation of hourly data is still low, GSMaP can still capture diurnal patterns in the IMC, as indicated by the compatibility of the estimated peak times for the precipitation amount and frequency. GSMaP data also manage to observe heavy rainfall, as indicated by the good of detection (POD) values for daily data ranging from probability 0.71 to 0.81. Such a good POD value of daily data is followed by a relatively low false alarm ratio (FAR) (FAR < 0.5). However, the GSMaP overestimates light rainfall (R < 1 mm/day); as a consequence, it overestimates the consecutive wet days (CWD) and number of days with rainfall ≥ 1 mm (R1mm) indices, and underestimates the consecutive dry days (CDD) extreme rain index. GSMaP daily data accuracy depends on IMC’s topographic conditions, especially for GSMaP real-time data. Of all GSMaP version 08 products evaluated, outperformed post-real-time non-gauge-calibrated (GSMaP_MVK), and followed by post-real-time gauge-calibrated (GSMaP_Gauge), near-real-time gauge-calibrated (GSMaP_NRT_G), near-real-time non-gauge-calibrated (GSMaP_NRT), real-time gauge-calibrated (GSMaP_Now_G), and real-time non-gauge-calibrated (GSMaP_Now). Thus, GSMaP near-real-time data have the potential for observing rainfall in IMC with faster latency.

The concept of electromagnetic induction is very important in understanding and developing modern electrical technology. Some factors cause students to often find it difficult to understand electromagnetic induction material in school is that this material involves abstract concepts such as magnetic flux, magnetic field changes, and emf. For some students, understanding these concepts may be difficult due to a lack of direct experience or concrete representations. Enrichment of physics material on electromagnetic induction has been implemented at SMA N 1 Gunung Talang. This service activity aims to improve students' understanding of the basic concepts of Electromagnetic Induction in Class XII. This service consists of three stages including: preparation, implementation and evaluation. The evaluation of this activity was carried out by comparing the pre-test results before enrichment and the post-test scores of students after being given enrichment material by the lecturer (service team). The results obtained show an increase in student knowledge towards understanding the concept of electromagnetic induction. This service activity can be an effort for school and university cooperation to support student success in understanding physics concepts that are considered complicated

The diurnal cycle of rainfall is the primary circulation of the atmosphere, which is highly dependent on an area's topographic conditions, land surface, and land-sea contrast. Understanding diurnal characteristics are beneficial in providing an overview of regional weather and the influence of topography on the diurnal cycle of rainfall. From previous research, it can be seen that there are differences in the diurnal cycle between the western and eastern parts of Sumatra. However, research in the eastern part of Sumatra is very limited, especially on small islands. Therefore, in this study, the diurnal rainfall characteristic on small islands of east Sumatra, i.e., Bangka Belitung Islands, from December 2015 to October 2019, was investigated using rain gauge and Integrated Multi-satellite Retrieval for GPM (IMERG) data. The diurnal characteristics of rainfall are defined as precipitation amount (PA), precipitation frequency (PF), and precipitation intensity (PI). The average PA, PF, and PI on the island by rain gauge (IMERG) observation, respectively, are 0.15–0.27 mm/h (0.22–0.35 mm/h), 2.69–4.88

The accurate prediction of extreme rain events is essential for the management and mitigation of hydrometeorological disasters. The Himawari-8 satellite provides cloud observations that can accurately forecast short-term extreme rain events using the Brightness Temperature (BT) data and Brightness Temperature Difference (BTD) method. The statistical evaluation of this method was conducted using optical rain gauge data taken from Kototabang, West Sumatra, Indonesia (100.32 degrees E, 0.20 degrees S) to determine the best threshold for detecting extreme rain. We used three bands, bands 11 (B11), 13 (B13) and 15 (B15) and tested three combinations of BTDs from these bands, namely BTD1 (B11-B13), BTD2 (B13-B15), and BTD3 (BTD1-BTD2). This study emphasizes the importance of parameter selection in extreme rain identification and forecasting using cloud BT and BTD methods. Effective parameter optimization is essential for adapting these approaches to different rainfall intensities, therefore selecting appropriate thresholds is necessary. The research particularly highlights the impact of temperature and rainfall intensity on BT accuracy, with BT excelling at 250 K for light rain but showing reduced accuracy as rainfall intensity increases. BTD1 demonstrates improved accuracy with higher rainfall intensity, especially at a 3 K threshold, allowing for predictions of extreme rain events with a 10-20 min lead time. However, the limitation of this threshold is shown by consistent critical success index (CSI). Therefore, BTD1 with threshold 0 K give better performances with good accuracy, CSI and false alarm ratio (FAR) for various rain intensities. BTD2 shows improved accuracy at lower thresholds with reduced rainfall intensity and at the 3 K threshold, offering potential for extreme rainfall anticipation, but with declining CSI as rainfall intensity rises. The 0 K threshold, despite high probability of detection (POD), yields increased FAR in moderate to severe rainfall scenarios. BTD3 generally exhibits increased accuracy and CSI with rising rainfall intensity, except at the -3 K threshold, with the 0 K threshold standing out as the optimal choice, providing a 10-20 min lead time for intense rain predictions. This study shows that the selection of the appropriate BT and BTD techniques, and parameter values should align with specific rainfall levels and forecasting goals.

Diurnal rainfall is a dominant local phenomenon in the maritime continent due to the land–sea interaction. Factors controlling rain on small tropical islands may differ from large islands, resulting in the difference in the diurnal rainfall pattern. In this work, we investigated the diurnal rainfall in small islands of Riau Islands using automatic rain gauge (ARG) and Integrated Multi-satellite Retrieval for GPM (IMERG) data from December 2015 to October 2019. Diurnal rainfall in Riau Islands was observed in terms of precipitation amount (PA), precipitation frequency (PF), and precipitation intensity (PI). Mean PA, PF, and PI values from gauge observations show variation values, that is, 0.16–0.35 mm/h (PA), 1.67–3.20