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INDONESIA
Jurnal Meteorologi dan Geofisika
Published by Pusat Penelitian dan Pengembangan, Badan Meteorologi Klimatologi dan Geofisika
ISSN : 14113082     EISSN : 25275372     DOI : https://doi.org/10.31172/jmg
Core Subject : Science,
Earth & Planetary Sciences Energy Physics
Jurnal Meteorologi dan Geofisika (JMG) is a scientific research journal published by the Research and Development Center of the Meteorology, Climatology, and Geophysics Agency (BMKG) as a means to publish research and development achievements in Meteorology, Climatology, Air Quality and Geophysics.
Arjuna Subject : Ilmu Bumi dan Planet (semua kategori) - Ilmu Bumi dan Planet (Lain-Lain)
Articles 7 Documents
 1 
Search results for , issue "Vol. 24 No. 1 (2023)" : 7 Documents clear
STRESS ANALYSIS AND CHARACTERISTICS DUE TO THE SOUTH JAVA EARTHQUAKE, APRIL 10, 2021 Sulastri Sulastri; Rahmat Setyo Yuliatmoko
Jurnal Meteorologi dan Geofisika Vol. 24 No. 1 (2023)
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v24i1.770

Abstract

The April 10, 2021, earthquake in the south of East Java was classified as destructive. The secondary impact of this earthquake was quite significant. Many houses collapsed, and not a few casualties. This earthquake is unique because usually, destructive earthquakes occur at shallow depths, but earthquakes with a magnitude of 6.1 are classified as medium-depth earthquakes at sea. The earthquake in the south of East Java is classified as an intraplate earthquake because it is located on the continental plate, not in the plate contact area. The question is whether the damage that occurred to the building was purely due to the magnitude of the stress released by the earthquake or whether there were other factors. This study uses seismogram data for the earthquake south of East Java on April 10, 2021, with a radius (∆) of 300-1000 recorded at MEEK, MORW, and ARMA stations in Australia. It calculates the amount of stress based on the stress drop, while the stress column determines the stress mechanism. Calculation of stress drop from the source spectrum is obtained by the deconvolution method, namely the seismogram component separation technique in the form of Source (f), Path (f), Site (f), and Instrument (f). The analysis of the observed displacement spectrum used the Nelder Mead Simplex nonlinear inversion method. Meanwhile, the Stress Columb calculation was obtained using the Columb 3.3 program from the United States Geological Survey (USGS). The result of this research is that the stress drop value is 1.69 MPa, with the type of focus mechanism being a thrust fault in the sea. The earthquake in the south of East Java was caused by rock activity in the intraplate. The value of the stress drop is more significant when compared to the subduction contact area. This area is of intraplate rock with various variations, and earthquakes are rare. This study aims to analyze the stress, both the magnitude of the stress drop and the mechanism of the column stress results, so that the stress caused by the earthquake can be known and why the earthquake in the south of East Java is destructive. The quake in Southeast Java is classified as dangerous, not because of the magnitude of the stress generated or its mechanism. The damage was due to the amplification of earthquake waves in the building. The injury occurred because most of the buildings were built on soft soil, especially in several areas in East Java, such as Lumajang, Pasuruan, Trenggalek, Probolinggo, Ponorogo, Jember, Tulunggagung, Nganjuk, Pacitan, and several urban areas, namely Blitar, Kediri, Malang, and Stone. So, there is a need for earthquake disaster mitigation, especially in densely populated areas that live on soft soil. This mitigation effort is to minimize the occurrence of casualties by building buildings according to earthquake-resistant standards and avoiding development in the regions that have the potential for amplification of earthquake waves.
COMPARISON ANALYSIS OF HIMAWARI 8, CHIRPS AND GSMaP DATA TO DETECT RAIN IN INDONESIA Rido Dwi Ismanto; Indah Prasasti; Hana Listi Fitriana
Jurnal Meteorologi dan Geofisika Vol. 24 No. 1 (2023)
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v24i1.863

Abstract

The need for rainfall data, especially for areas where the number of observation stations is not very close, is very important for local climate analysis activities. This data need can be met, one of which is from remote sensing data, such as Himawari 8. The Himawari 8 rainfall data are data derived using the INSAT Multi-Spectral Rainfall Algorithm (IMSRA) method based on the infrared channel on the Himawari 8 satellite. However, research on the IMSRA method was carried out using a case study of a region in India. Thus, validation is needed to determine the ability of Himawari 8 rainfall data to detect rain in Indonesia. The data used for comparison are CHIRPS and GSMaP rainfall data. In addition, BMKG rainfall data are used as benchmark data. The technique used for validation is using the Contingency Table method. The results of the validation show that the rain detection ability for Himawari 8 rainfall data is relatively good, namely 66% for 2019 and 85% for 2020. In addition, the ability to detect rain using Himawari 8 rainfall data is quite good compared to the ability to detect rain using CHIRPS rainfall data and GSMaP rainfall data.
THERMAL STRESS PROJECTION BASED ON TEMPERATURE-HUMIDITY INDEX (THI) UNDER CLIMATE CHANGE SCENARIO Iis Widya Harmoko; Rochdi Wasono; Tiani Wahyu Utami; Fatkhurokhman Fauzi; Iqbal Kharisudin
Jurnal Meteorologi dan Geofisika Vol. 24 No. 1 (2023)
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v24i1.867

Abstract

The degradation of green open spaces and the phenomenon of deforestation in Indonesia has increased discomfort in the region. Furthermore, if allowed to continue, the increase in temperature caused by greenhouse gases worsens the situation. Increased temperature and reduced air humidity are related to thermal stress, affecting human comfort and health. Thermal stress is measured based on the Temperature Humidity Index (THI), which calculates temperature and relative humidity variables. This study analyses THI projections under climate change scenarios RCP4.5 and RCP8.5. This study uses statistical downscaling and bias correction of Quantile Delta Mapping (QDM) to equalize the local climate. This study is divided into four 20-year periods from 2021 to 2100 to evaluate THI changes in future projections. Based on the study results, it is known that from 2041-2060, several big cities in Indonesia experienced an increase in THI and were included in the category of 50% of the population feeling uncomfortable. THI increased in the third and fourth periods. Areas that experienced a significant increase in THI were urban areas that lacked green open land and were densely populated. Surabaya City and Madura Island are the areas with the highest THI index.
KATEGORISASI STASIUN SEISMIK DAN PENGARUHNYA DALAM PENENTUAN PARAMETER MAGNITUDO GEMPABUMI BMKG Muhammad Fahmi Nugraha; Afnimar Afnimar; M. Taufik Gunawan; M. Ramdhan; Iman Fatchurochman; Nova Heryandoko
Jurnal Meteorologi dan Geofisika Vol. 24 No. 1 (2023)
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v24i1.886

Abstract

The responsibility to send information within five minutes causes the magnitude disseminated by BMKG only from limited seismic records. The result shows that the magnitude produced in the first five minutes can fluctuate and cause a difference in the final magnitude. In the SeisComP system at BMKG, the event magnitudes of each type of magnitude MLv, mb, mB, and Mwp, are the result of the station magnitude average using trimmed mean, so the largest or smallest station magnitudes will become outliers and are eliminated in event magnitude calculation. However, the drawback of the trimmed mean is seismic stations that always tend to be outliers have the potential to be still involved in determining the event magnitude in the early minutes so that it can disrupt the magnitude calculation. This study aims to reduce the fluctuations in determining the magnitude in the first five minutes by identifying seismic stations that are often eliminated by the trimmed mean method and classifying them. We validate them with the site quality of the station and create two main categories of seismic stations. The first category is primary stations to determine the location and magnitude of earthquakes. The second category is secondary stations used only at the earthquake site, then tested using SeisComP playback by replaying 256 earthquake events. The results show a correlation where good site quality will also produce a good magnitude value, indicated by 285 seismic stations, and can be categorized as primary stations. The remaining 126 seismic stations are categorized as secondary stations. The playback results show that the fluctuation of magnitude determination in the first five minutes using the primary station can be reduced, as indicated by the mean residual and the deviation to the final magnitude.
WRF-MODEL PARAMETERIZATION TEST FOR PREDICTING EXTREME HEAVY RAINFALL EVENT OVER KETAPANG REGENCY Fazrul Rafsanjani Sadarang
Jurnal Meteorologi dan Geofisika Vol. 24 No. 1 (2023)
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v24i1.924

Abstract

Heavy rains that cause floods and landslides in the Ketapang Regency can be predicted by utilizing the weather research and forecast (WRF) model. The WRF model used, of course, needs to be configured to represent the conditions that exist in Ketapang Regency. This study evaluates the combination of cumulus and microphysics parameterization, producing the best prediction of 24-hour accumulated rainfall. The combination of cumulus and microphysics parameterization tested as many as 24 schemes which later will be obtained which combination can produce the best prediction of rainfall accumulation with the comparison of rainfall measured at the Observation Station of the Meteorology, Climatology, and Geophysics Agency (BMKG) in Ketapang Regency. The results show that combining the KF-Scheme cumulus parameterization scheme and the Kessler-Scheme microphysics can better predict 24-hour accumulated rainfall than other tested parameterization schemes. This result is based on the root mean square error (RMSE), which shows that this combination scheme produces the smallest value and large correlation coefficient (CORR). From this research, it can also be seen that cumulus parameterization has a more dominant role than microphysics parameterization.
EVALUATION OF THE CORDEX-SEA MODELS PERFORMANCE IN SIMULATING CHARACTERISTICS OF WET SEASON IN INDONESIA Rini Hidayati; Supari Supari; Alif Akbar Syafrianno; Akhmad Faqih
Jurnal Meteorologi dan Geofisika Vol. 24 No. 1 (2023)
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v24i1.965

Abstract

Indonesia's climate is known to be challenging to adequately simulate by climate models because of the complexity of the weather system and sea-land distribution. Model evaluation is essential to measure confidence in the model results. This study evaluates the performance of the CORDEX-SEA model in simulating monthly rainfall patterns and the characteristics of seasonal rainfall, i.e., pattern, timing, length, and intensity, in Indonesia during 1986-2005. The performance of weighted (WMME) and unweighted ensemble methods are also calculated. Corrected CHIRPS data with similar seasonal patterns with point observation data is used as reference data to evaluate models. Percentage of the agreement of seasonal patterns between models and observation, FAR, and POD values were used to assess the model's ability to simulate seasonal patterns. WMME has the best seasonal patterns agreement with observation, 67% of all grids. The best model performance is shown by monsoonal patterns, with a POD value of 83% by WMME. Otherwise, all models could not describe an anti-monsoonal pattern, with a small POD (0-33%) and a high FAR (60-100%). In simulating the wet season on climatological, annual, and annual mean scales, both MMEs have similar performance and are better than individual models, with WMME performing best. However, on an annual scale, the yearly wet season produced by all models tends to approach its climatology value, making it less reliable in extreme years. Most models have higher daily and monthly rainfall than observation. In conclusion, the weighted ensemble method describes Indonesia's rainy season well, thus providing a reasonable basis for further research in climate projection analysis.
OVERSHOOTING TOP OF CONVECTIVE CLOUD IN EXTREME WEATHER EVENTS OVER JAVA REGION BASED ON VISUAL IDENTIFICATION OF HIMAWARI 8 IMAGERY Bony Septian Pandjaitan; Akhmad Faqih; Furqon Alfahmi; Perdinan .
Jurnal Meteorologi dan Geofisika Vol. 24 No. 1 (2023)
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v24i1.967

Abstract

Overshooting top (OT) in convective clouds is an essential feature in extreme weather nowcasting performed by weather forecasters to represent the core location of the severe region of the convective cloud. In addition, we can estimate the location of extreme weather events by utilising OT climatology. Unfortunately, it cannot be realised in tropical Indonesia, especially on Java Island at present, because there still needs to be more research on the presence of OT in extreme weather events. This research aims to study the presence of OT in extreme weather events on Java Island using extreme weather reports and the Himawari 8 satellite data. We detect the presence or absence of OT patterns at the location of the extreme weather event with Visual identification by using a visible channel (0.64 μm) with a spatial resolution of 500 m and sandwich products. We found that about 87% of extreme weather occurred accompanied by the appearance of OT patterns from convective clouds. A parallax effect of Himawari 8 caused the detected OT location in the southwest direction of the actual location. Extreme weather events accompanied by the OT feature of convective clouds most often occur in the transitional period of the rainy to dry season (MAM) and the rainy season (DJF). Meanwhile, extreme weather events rarely occur during the dry season (JJA). Extreme weather events accompanied by OT often occur from midday to late afternoon. OT in this study has a diameter between 2-15 km during extreme weather events. A time lag between the appearance of OT and extreme weather events in Java Island gives us opportunities for approximating and nowcasting the extreme weather events.

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