Nelly Florida Riama

Previous studies highlight strong influences of large‐scale synoptic, intraseasonal, and seasonal perturbations on the diurnal cycle of the Indo‐Pacific Maritime Continent (MC). Isolating local diurnal forcing of insolation from other effects can be difficult. To address this difficulty, we introduce two new concepts: the probabilistic diurnal cycle and the coastal baseline diurnal cycle. The probabilistic approach is applicable to non‐Gaussian variables, such as rainfall and wind speed. Using seven years of observations from 31 surface stations across Indonesia, we establish the baseline diurnal cycle by identifying patterns of high probabilities across daily hours. In this baseline diurnal cycle, surface temperature rises from an early‐morning minimum to a midday peak. Weak land breezes transition to strong sea breezes in the morning, with wind speeds peaking shortly after noon before land breezes return in the late afternoon. Specific humidity plateaus near midday after its early‐morning minimum. Surface pressure exhibits a clear semidiurnal cycle driven by atmospheric tides. Rainfall typically peaks in the afternoon and reaches a minimum in the morning. This baseline diurnal cycle, primarily driven by local diurnal forcing (insolation), exists at 24 of the 31 surface stations. A significant deviation from the baseline occurs at a few stations where rainfall peaks in the early morning. This deviation appears randomly distributed in space, and its controlling mechanisms likely reside outside the atmospheric boundary layer. Processes that determine the location of the persistent early‐morning peak in rainfall warrant further investigation.

In recent decades, Earthquake Early Warning (EEW) has become an option in many countries to reduce the vulnerability to earthquake hazards. P-wave picking under noisy conditions is challenging; the accuracy of P-wave picking affects the accuracy of Peak Ground Acceleration (PGA) in the warnings issued by the EEW system. Western Java, Indonesia’s most densely populated region, has a massive infrastructure development. The lack of EEW in Indonesia, especially in western Java, makes it challenging to provide EEW to the community and end users. We employed an integrated method approach to developing onsite EEW in the western Java region, aiming to improve the lead time and accuracy of earthquake information, particularly in estimating PGA. We combined PGA estimation using Support Vector Regression (SVR) and validated it against linear regression estimates to assess its reliability across 5706 earthquake signals. This combination yields more accurate PGA estimates with high confidence when public earthquake warnings are issued. We used six features extracted from the first 3[ ]s of the P-wave to build an SVR model for predicting PGA in the EEW system. The six parameters are Pa, Pv, Pd, [ ], IV2, and CAV, which are directly correlated with PGA, magnitude, and earthquake damage potential. From an investigation of 485 earthquake events in western Java, Indonesia, that occurred between 2009 and 2023, with varying magnitudes, we obtained a threshold for the average period [ ] of 0.55[ ]s and a peak displacement (pd) of 0.4[ ]cm. PGA estimates from linear regression and machine learning approaches are pretty accurate for two damaging earthquakes: the 2009 Tasikmalaya earthquake (M 7.3) is 636.9[ ]gal, and the 2022 Cianjur earthquake (M 5.6) is 483.6[ ]gal. The use of the IPP (Initial Power of the P-wave) method provides better results than the Short Time/Long Time Average (STA/LTA), InTeg, and EQTransformer methods. Based on the study results, it is necessary to develop and implement onsite EEW using an integrated approach in Western Java, with adequate acquisition instruments and communication systems.

During the Asian Winter season, which spans from November to February, the phenomenon of cold surge often occurs, leading to increased convective activity over the western Indonesian Maritime Continent. The location of Natuna Island, situated in the southern part of the South China Sea, is of particular importance for studying cold surges due to their propagation over this area. In this study, the vertical structure of the atmosphere was analyzed using radiosonde observation data collected at the Meteorological Station of Ranai Natuna. The analysis focused on physical parameters such as air temperature and relative humidity, atmospheric kinematics including wind direction and speed, as well as atmospheric thermodynamic parameters such as Lifting Condensation Level (LCL), Level of Free Convection (LFC), Equilibrium Level (EL), Convective Available Potential Energy (CAPE), and Convective Inhibition (CIN). The results indicate that during the passage of a cold surge, air temperature (T) tends to be higher in the lower troposphere, including at the surface, but lower in the middle and upper troposphere. Relative humidity (RH) also tends to be higher during cold surges, with a significant increase in the middle and upper troposphere. In the lower troposphere, the wind direction shifts from east to northeast at a higher speed compared to when a cold surge is absent. Furthermore, the LCL and LFC heights are elevated during the presence of a cold surge, while the EL height shows an insignificant decrease. It is worth noting that intense rainfall occurs, particularly when the cold surge is more pronounced, even though the values of CAPE and CIN do not change significantly.

In this study, we used the Weather Research and Forecasting (WRF) version 4.2.1 model to simulate the characteristics of a rainfall-induced landslide that occurred on November 28 in Samigaluh, Kulonprogo. In addition, we investigated 22 different microphysics (MP) schemes to see how sensitive they were. The WRF model was employed with three nested domains, the innermost of which had a 1 km grid spacing and explicit convection. The model was run for 73 hours with GFS initial conditions from 00:00 UTC on November 26, 2018. We used reflectivity profiles from the Weather Radar in Yogyakarta and data from rain gauge stations in Kulonprogo to validate the simulated properties of the rainfall. Despite employing identical initial and boundary conditions and model settings, the MP approaches have significant variances in their thunderstorm simulations. To begin with, practically all of the extreme convection simulation methods over Samigaluh had the same pattern as the reported storm. For example, on November 27, radar data indicated the passage of three convective cores above Samigaluh, which the model in most MP schemes simulated. In comparison, the Ferrier_old scheme did an excellent job of simulating the convective cores' observable features. The MP schemes also had difficulties modeling the storm's updrafts. The Ferrier old scheme simulated surface rainfall distributions closer to data than the other three schemes (Goddard GCE, Morrison2, and WDM5). On the other hand, all four MP systems did an excellent job of simulating the convective variations associated with the thunderstorm. The model's generated reflectivity profiles, which showed three convective cores, were similar to the observed reflectivity profile. These characteristics match the simulated convective profiles, which peaked between 10 and 15 kilometers. The current research reveals that the microphysical systems in thunderstorm simulations have a lot of sensitivity and variability. The study also underlines the necessity for a multi-observational program such as Year of Maritime Continent (YMC) to improve the parameterization of cloud microphysics and land surface processes throughout the Indonesian region. 

A major earthquakes struck the Majene Regency, in West Sulawesi province, Indonesia, on 15 January 2021 at 02.28 local time, the hypocenter is 2.97°S, 118.99°E, depth 38.0 km, with moment magnitude Mw 6.2 with an epicenter located about 6 km Northeast Majene, West Sulawesi. This large event causing extensive damage, great economic loss and casualties in the Majene city and surrounding region. The mainshock preceded by significant foreshock on 14 January 2021 at 14.35 local time, 3°S, 118.94°E, depth 10.0 km Mw 5.9, epicenter was located at about 4 km Northwest of Majene. The faulting orientation of the mainshock, and foreshock was strike = 330°, dip = 17°, and slip = 59°, and strike = 353°, dip = 29°, and slip = 61°, respectively, is possibly related to Mamuju-Majene thrust fault. Focal mechanism solutions for the earthquakes indicate rupture occurred thrust fault with low dip angle. The mainshock was followed by low aftershocks productivity may due to homogeneous faulting systems and relatively uniform stress state in that region. We use hypocenter relocation, stress drop, coulomb stress and seismic hazard (PSHA) to investigate the earthquake characteristics and seismic hazard analysis. The distribution of hypocenter relocations indicate aftershock ruptured northern extension of the mainshock. This result supports that the highest of acceleration is the north component of the three component recorded acceleration, this detect the components of directivity toward the north for the foreshock distribution.

In this study, tweets related to fires in Riau, Sumatra, were identified using carefully selected keywords for the 2014–2019 timeframe. The TAGGS algorithm was applied, which allows for geoparsing based on the user’s nationality and hometown and on direct referrals to specific locations such as name of province or name of city in the message itself. Online newspapers covering Riau were analyzed for the year 2019 to provide additional information about the reasons why fires occurred and other factors, such as impact on people’s health, animal mortality related to ecosystem disruption, visibility, decrease in air quality and limitations in the government firefighting response. Correlation analysis between meteorological information, Twitter activity and satellite-derived hotspots was conducted. The existing approaches that BMKG and other Indonesian agencies use to detect fire activity are reviewed and a novel approach for early fire detection is proposed based on the crowdsourcing of tweets. The policy implications of these results suggest that crowdsourced data can be included in the fire management system in Indonesia to support early fire detection and fire disaster mitigation efforts.

Early detection that results in early warning of forest fires occurrences in Indonesia, which are strongly related to land management practices (including peatlands), is necessary to mitigate land and forest fires in Indonesia. Riau has been chosen in this study because of its vulnerability to forest fires. The remoteness of this region is one reason for developing alternative warning tools using meteorological and social media information. This study identified tweets related to fires using carefully selected keywords, geoparsed to select messages relevant to fire occurrences, and binned within several Indonesian sub-regions in Riau Province. Content analysis was performed for 31 related online local newspapers. Assessment to study the correlation between meteorological and Twitter information with the forest fires was conducted. Existing approaches that the BMKG and other Indonesian agencies use to detect fire activities are reviewed, and a novel approach based on crowdsourcing of tweets is proposed. The results show a correlation between meteorological information and Twitter activity with satellites derived hotspot information. The policy implications of these results suggest that information should be included in the fire management system in Indonesia to support fire early detection as part of fire disaster mitigation efforts.