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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 157 Documents
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Turbulence analysis on the flight of Etihad airways in Bangka Island using the WRF case study May 4, 2016 Bayu Retna Tri Andari; Nurjanna Joko Trilaksono; Muhammad Arif Munandar
Jurnal Meteorologi dan Geofisika Vol. 23 No. 3 (2022): Special Issue
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v23i3.912

Abstract

Accurate weather forecasts should support the increase in safety of aviation operations in Indonesia. This weather forecast is needed, especially in detecting turbulence, considering that geographically Indonesia has effective solar radiation resulting in convective cloud formation. Convective clouds can trigger turbulence then produce disruption and even accidents on flights. This research uses a case study on the Etihad Airways flight on Bangka Island on May 4, 2016. At the time of the incident, there was turbulence at 39,000 feet altitude, and the aircraft did not enter the cloudy area. The Weather Research and Forecasting (WRF) model is used to simulate the turbulence in this study, which is downscaled up to 3 km with a microphysics parameterization of WRF Single Moment 6 Class (WSM6). The results were then verified using correlation and linear regression for temperature, wind direction, wind speed, and pattern resemblance between cloud fraction and the convective nuclei distribution. The turbulence is analyzed from the south-north and west-east vertical airflow. The turbulence spotted at 06.40 UTC when there is a quite strong updraft which can cause turbulence. The turbulence parameters used, such as the eddy dissipation rate (EDR) parameter, which has a value of 0.05 , Richardson number with a value of less than 0.25, and turbulence index (TI 1) with a maximum value of 4 x 10-7 s-2 found that turbulence was in a strong category. The turbulence that occurs in this study is identified as near cloud turbulence (NCT) event due to cloud formation observed in the west of the turbulence and intense updraft activity at the location of turbulence.
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.
Analysis of Land Cover Changes to Increase Land Surface Temperature in Surabaya using Landsat Satellite Prayuda, Shanas Septy; Kusuma, Maritha Nilam
Jurnal Meteorologi dan Geofisika Vol. 24 No. 2 (2023)
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v24i2.968

Abstract

Surabaya has experienced very significant development in the last few decades. Changes in land use will cause the Urban Heat Island phenomenon. This study aims to determine how far the impact of land cover changes on the increase in surface temperature in the Surabaya. The use of Landsat satellite imagery is considered very effective in describing land cover and surface temperature because it has good spatial resolution and long data availability. During 1991 – 2020 there was a significant decrease in the amount of vegetation by 24.3%, decrease in the number of water bodies by 4.9%, and increase in the number of buildings by 29.2%. The average increase in Land Surface Temperatures was 1.40°C between decades 2 and 1, and an increase of 2.19°C between decades 3 and 2. The development of Surabaya began in the city center and then developed mainly in the west and east. The urban development model is consistent with the pattern of land surface temperature changes. Each type of land cover has special characteristics on the value of NDVI, NDBI, and surface temperature. Changes in cover from water bodies to buildings have the highest contribution to increasing the and surface temperature. There was a significant increase in hotspots in decade 3 in Surabaya which indicated an increasingly severe UHI phenomenon.
Calibration Indonesian-Numerical Weather Prediction using Geostatistical Output Perturbation Sutikno, Sutikno; Cahyoko, Fajar Dwi; Putra, Fernaldy Wananda; Makmur, Erwin Eka Syahputra; Hanggoro, Wido; Taufik, Muhamad Rifki; Aza, Vestiana
Jurnal Meteorologi dan Geofisika Vol. 24 No. 2 (2023)
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v24i2.1037

Abstract

Indonesian-Numerical Weather Prediction (INA-NWP) is a numerical-based weather forecast method that has been developed by the Meteorology, Climatology and Geophysics Agency. However, the forecast is still unable to produce accurate weather forecasts. Geostatistical Output Perturbation (GOP) is a weather forecast method derived from only one deterministic output. GOP takes into consideration the spatial correlation among multiple locations simultaneously. GOP is capable to identify spatial dependency patterns that are associated with error models. This study aims to obtain calibrated forecasts for daily maximum and minimum temperature variables using GOP at 10 meteorological stations in Surabaya and surrounding areas. The stages in performing temperature forecasts using GOP are obtaining regression coefficient estimators, then calculating empirical semivariograms and estimating spatial parameters. Based on several weather forecast indicators, such as RMSE and CRPS, GOP is better than INA-NWP in terms of precision and accuracy.
VARIABILITAS INTERANNUAL HUJAN MONSUN INDONESIA: REVIEW ARTIKEL TENTANG PENGARUH GAYA EKSTERNALNYA Mulsandi, Adi; Koesmaryono, Yonny; Hidayat, Rahmat; Faqih, Akhmad; Sopaheluwakan, Ardhasena
Jurnal Meteorologi dan Geofisika Vol. 24 No. 2 (2023)
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v24i2.1049

Abstract

The IMR variability is notorious for its hydrometeorological disasters. This paper examines recent studies on IMR and the main factors controlling its variability. The focus of this study is to investigate the impact of the atmosphere-ocean interaction that acts as the external forcing of IMR in the tropical Indian and Pacific Oceans. Specifically, the study will examine the influence of two climate phenomena, namely the El Nino Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) and their interdecadal changes associated Pacific Decadal Oscillation (PDO), on the IMR. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach. Furthermore, data sets (such as rainfall, wind field, and SST) spanning 1990-2020 were used to verify the key findings. In general, this study concludes that the majority of the authors coincided with the following conclusion: ENSO and IOD events impact IMR by changing its amplitude, duration, intensity, and frequency of mean and extreme rainfall. Additionally, it has been shown that their impacts on IMR are most substantial during the dry seasons, specifically in June, July, and August (JJA), and not as strong as during the wet seasons, specifically in December, January, and February (DJF). Spatially, the effects of ENSO and IOD on IMR variability are clearly found more eastward and westward of the region, respectively. The expansions towards the east and west directions were facilitated by the displacement of the ascending and descending of Walker circulation patterns in the Indonesian region, respectively. Given the interannual fluctuations in IMR, caused mainly by ocean-atmosphere interactions, the knowledge gap of atmospheric factors like the Quasi-Biennial Oscillation (QBO) must be investigated in the future, as suggested by previous research and our preliminary study.
Modification of The Thermal Comfort Index Based on Perceptions for Urban Tourism Around Jakarta Hidayat, Nizar Manarul; Hidayati, Rini; Turyanti, Ana; Al Maula, Sugha Faiz
Jurnal Meteorologi dan Geofisika Vol. 25 No. 1 (2024)
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v25i1.1051

Abstract

Climate interaction directly correlates with an individual's comfort response. One's comfort can be quantified by perceiving environmental conditions at tourist locations. This study aims to identify climatic and non-climatic factors that affect thermal comfort based on visitor perception. In addition, the Holiday Climate Index (HCI) is modified to equalize visitors' perceptions. The research locations, namely Taman Mini Indonesia Indah (TMII), Kebun Raya Bogor (KRB), and Taman Safari Indonesia (TSI), are characterized by distinct topographies. This study identifies thermal comfort factors based on 552 questionnaire responses from purposive sampling. Analyzing factors influencing thermal comfort using ordinal logistic regression with Uncomfortable Class (0) and Comfortable Class (1). Model performance metrics, such as accuracy, precision, recall, and F1 score, are calculated using a confusion matrix. In general, the best time to feel comfortable is in the morning. Overall, climatic factors such as thermal sensation and rainfall events influence thermal comfort, while non-climatic factors have no effect. The model's implication is to provide an equation in the probability of someone feeling comfortable or uncomfortable based on the predictors. Furthermore, a modification index at TMII adjusted the HCI-urban's weighting, ratings, and comfort thresholds to match visitors' perceptions at that time. The results demonstrate that HCI-urban effectively provides comfortable and comfortable assessments. However, it has not yet been able to capture perceptions of discomfort, unlike the modified index. This research can provide added value to the tourism industry in terms of maintaining environmental comfort during the dry season.
Improving Short-Term Weather Forecasting using Support Vector Machine Method in North Barito Wulandari, Ayu Vista; Trilaksono, Nurjanna Joko; Ryan, Muhammad
Jurnal Meteorologi dan Geofisika Vol. 25 No. 2 (2024)
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v25i2.1096

Abstract

Flooding is a recurring issue in North Barito Regency due to the overflow of the Barito River. Weather forecasts in the region rely mainly on Numerical Weather Prediction (NWP) models, which often fail to capture local details due to their grid-based homogenization. To address this limitation, statistical techniques such as Model Output Statistics (MOS) can enhance NWP outputs by representing local conditions more accurately . MOS establishes statistical relationships between response variables (predictands) and predictor variables derived from NWP outputs, enabling operational applications without the need for advanced instruments. This study utilizes rainfall data from 2021-2022 from the Beringin Meteorological Station in North Barito as the response variable, while data from the Integrating Forecasting System (IFS) model serve as the predictor variables. The Support Vector Machine (SVM) method is employed to identify the relationship between predictor and response variables. By integrating the MOS technique with the SVM method, this research aims to improve the accuracy of weather forecasting, particularly for short-term predictions in North Barito. This approach demonstrates the potential to enhance localized weather predictions by addressing the limitations of conventional NWP models. The results indicate a consistent reduction in RMSE across all experiments conducted. Furthermore, the SVM model showed notable improvements in bias values and exhibited a stronger correlation compared to the original outputs from the IFS model. The percentage improvement (%IM) in rainfall forecasts, following correction using the SVM model, increased by 5.03%. The percentage improvement (%IM) in rainfall forecasts, following correction using the SVM model, increased by 5.03% for use as a predictor variable in the applied SVM method. In contrast, a combination of surface pressure, temperature across various layers, and rainfall proved to be the the most effective input variables for enhancing the accuracy of weather forecasting in North Barito using the SVM model.
Comparative Analysis of Diurnal and Seasonal Variations in Precipitation of Mesoscale Convective System and Non-Mesoscale Convective System over Borneo Island Azka, Mukhamad Adib; Trilaksono, Nurjanna Joko
Jurnal Meteorologi dan Geofisika Vol. 25 No. 2 (2024)
Publisher : Pusat Penelitian dan Pengembangan BMKG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31172/jmg.v25i2.1101

Abstract

Convective storms, which play a critical role in producing severe weather events, are often associated with mesoscale convective systems (MCS). The most favorable tropical regions for MCS development include the Indonesian Maritime Continent (IMC), with Borneo Island being a prominent area. Borneo Island features unique topography and is influenced by the surrounding oceans, resulting in MCS with the largest average size and most extended lifespan compared to other islands within the IMC. Previous studies on MCS focused on occurrence statistics and case studies. However, analyses distinguishing characteristics of MCS and non-MCS precipitation remain limited over the IMC. This study examines the diurnal and seasonal variations and their respective contributions over Borneo Island. MCS identification and tracking were performed using the Flexible Object Tracker (FLEXTRKR) algorithm. The results indicate that MCS precipitation typically occurs from nighttime to early morning, while non-MCS precipitation primarily occurs during the daytime until the evening. Furthermore, MCS precipitation occurs more frequently over the ocean, while non-MCS precipitation is primarily observed over land. Seasonally, MCS precipitation is most prominent during the December–January–February (DJF) season, particularly over the South China Sea, parts of West Kalimantan, Sarawak, Central Kalimantan, and the Java Sea. Conversely, MCS precipitation is less dominant during the June–July–August (JJA) season. The contribution of precipitation produced by MCS exceeds 50% of the total precipitation, whereas non-MCS precipitation contributes approximately 20–40%. The differences in precipitation produced by MCS and non-MCS clouds will affect for soil water content, vulnerability to hydrometeorological disasters, and further understanding of climate and weather.

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