D. Wijaya, Nabila Putri, Yan A. Rahmawan, S. T. Wibowo, Akhmad Y. Basuki, M. S. Fathulhuda, V. Sadarviana
We have utilized the Global Positioning System (GPS) data at 57 stations distributed over Sumatra Island to investigate spatio-temporal variations of the atmospheric precipitable water vapor (PWV). We focused on the annual and semi-annual cycles of the PWV. Our results show that Sumatra Island is divided into two distinct areas of annual and semi-annual cycles, where the boundary line between the areas is approximately at 2oS. While the annual cycle dominates the area over the southern side of 2oS, the semi-annual cycle is dominant over the northern side. Our results have further shown that the maximum phase of annual cycle occurs between January-March with considerably large amplitudes (10-15 mm). On the other side, the maximum phase of the semi-annual cycle in general occurs around November and May, whose amplitude is approximately between 1-5 mm. Our results are consistent with other results using rainfall data.
{"title":"ANNUAL AND SEMI-ANNUAL VARIATIONS OF THE GPS-DERIVED PRECIPITABLE WATER VAPOR OVER SUMATRA ISLAND","authors":"D. Wijaya, Nabila Putri, Yan A. Rahmawan, S. T. Wibowo, Akhmad Y. Basuki, M. S. Fathulhuda, V. Sadarviana","doi":"10.31172/jmg.v22i2.835","DOIUrl":"https://doi.org/10.31172/jmg.v22i2.835","url":null,"abstract":"<p align=\"justify\"><em>We have utilized the Global Positioning System (GPS) data at 57 stations distributed over Sumatra Island to investigate spatio-temporal variations of the atmospheric precipitable water vapor (PWV). We focused on the annual and semi-annual cycles of the PWV. Our results show that Sumatra Island is divided into two distinct areas of annual and semi-annual cycles, where the boundary line between the areas is </em><em>approximately a</em><em>t</em><em> 2</em><em><sup>o</sup></em><em>S. While the annual cycle dominates the area over the southern side of 2</em><em><sup>o</sup></em><em>S, the semi-annual cycle is dominant over the northern side. Our results have further shown that</em><em> the maximum phase of annual cycle </em><em>occurs</em><em> between January-March with considerably large amplitudes (10-15 mm). On the other side, the maximum phase of the semi-annual cycle in general occurs around November and May, whose amplitude is approximately between 1-5 mm. Our results are consistent with other results using rainfall data.</em><em></em></p>","PeriodicalId":32347,"journal":{"name":"Jurnal Meteorologi dan Geofisika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72726749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IDENTIFIKASI SESAR LOKAL DI WILAYAH BARAT DAYA SUMBA, INDONESIA BERDASARKAN SEBARAN HIPOSENTER GEMPABUMI DAN DATA GRAVITASI","authors":"Relly Margiono, Adinda Novitri, Anggi Pevriadi, Hilmi Zakariya","doi":"10.31172/jmg.v22i2.824","DOIUrl":"https://doi.org/10.31172/jmg.v22i2.824","url":null,"abstract":"","PeriodicalId":32347,"journal":{"name":"Jurnal Meteorologi dan Geofisika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80885596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Pratama, Ichy Lucya Resta, Faizar Farid, Wiwid Joni
{"title":"IDENTIFIKASI LAPISAN BAWAH PERMUKAAN DAERAH PROSPEK PANAS BUMI SONGA-WAYAUA BERDASARKAN METODE MAGNETOTELURIK","authors":"R. Pratama, Ichy Lucya Resta, Faizar Farid, Wiwid Joni","doi":"10.31172/jmg.v22i2.786","DOIUrl":"https://doi.org/10.31172/jmg.v22i2.786","url":null,"abstract":"","PeriodicalId":32347,"journal":{"name":"Jurnal Meteorologi dan Geofisika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84621532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rahmat Setyo Yuliatmoko, Y. Perdana, Agustya Adi Martha
{"title":"DISTRIBUSI FREKUENSI GEMPA DAN DIMENSI FRAKTAL PADA SEISMIK GAP DI INDONESIA","authors":"Rahmat Setyo Yuliatmoko, Y. Perdana, Agustya Adi Martha","doi":"10.31172/jmg.v22i2.771","DOIUrl":"https://doi.org/10.31172/jmg.v22i2.771","url":null,"abstract":"","PeriodicalId":32347,"journal":{"name":"Jurnal Meteorologi dan Geofisika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89367955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gempa bumi merupakan bencana alam yang tidak dapat dicegah maupun dihindari. Oleh sebab itu, perlu dilakukan pemetaan dan pengelompokan wilayah gempa untuk mendukung upaya minimalisasi dampak yang ditimbulkan. Data yang digunakan dalam penelitian ini adalah data gempa bumi di Indonesia yang bersumber dari Badan Meteorologi, Klimatologi, dan Geofisika (BMKG). Penelitian ini menggunakan algoritma DBSCAN dalam mengelompokkan data ke dalam beberapa cluster . Metode untuk menguji validitas hasil cluster adalah dengan menggunakan Silhouette Coefficient dan Gamma Index . Hasil clustering pada penelitian ini memberikan kesimpulan bahwa dengan menggunakan algoritma DBSCAN diperoleh 3 cluster wilayah beresiko terjadi gempa bumi berdasarkan karakteristik parameter gempa bumi yang dihasilkan. Kombinasi nilai e dan MinPts yaitu 0,28 dan 3 menghasilkan nilai Silhouette Coefficient sebesar 0,81091 dan Indeks Gamma sebesar 0,98104 yang menggambarkan bahwa DBSCAN mampu mengelompokan wilayah berpesiko terjadi gempa bumi dengan cukup baik. Hasil penelitian ini dapat digunakan sebagai bahan pertimbangan suatu instansi dalam pengambilan keputusan terkait penanganan (mitigasi) bencana gempa bumi.
{"title":"PENGELOMPOKAN DATA GEMPA BUMI MENGGUNAKAN ALGORITMA DBSCAN","authors":"Rais Rahman, A. Wijayanto","doi":"10.31172/JMG.V22I1.738","DOIUrl":"https://doi.org/10.31172/JMG.V22I1.738","url":null,"abstract":"Gempa bumi merupakan bencana alam yang tidak dapat dicegah maupun dihindari. Oleh sebab itu, perlu dilakukan pemetaan dan pengelompokan wilayah gempa untuk mendukung upaya minimalisasi dampak yang ditimbulkan. Data yang digunakan dalam penelitian ini adalah data gempa bumi di Indonesia yang bersumber dari Badan Meteorologi, Klimatologi, dan Geofisika (BMKG). Penelitian ini menggunakan algoritma DBSCAN dalam mengelompokkan data ke dalam beberapa cluster . Metode untuk menguji validitas hasil cluster adalah dengan menggunakan Silhouette Coefficient dan Gamma Index . Hasil clustering pada penelitian ini memberikan kesimpulan bahwa dengan menggunakan algoritma DBSCAN diperoleh 3 cluster wilayah beresiko terjadi gempa bumi berdasarkan karakteristik parameter gempa bumi yang dihasilkan. Kombinasi nilai e dan MinPts yaitu 0,28 dan 3 menghasilkan nilai Silhouette Coefficient sebesar 0,81091 dan Indeks Gamma sebesar 0,98104 yang menggambarkan bahwa DBSCAN mampu mengelompokan wilayah berpesiko terjadi gempa bumi dengan cukup baik. Hasil penelitian ini dapat digunakan sebagai bahan pertimbangan suatu instansi dalam pengambilan keputusan terkait penanganan (mitigasi) bencana gempa bumi.","PeriodicalId":32347,"journal":{"name":"Jurnal Meteorologi dan Geofisika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76029224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Divyana Meidita, Agustya Adi Martha, Y. Setiawan, Supriyanto Rohadi
Gempa merusak pernah terjadi di sekitar Sesar Opak, Yogyakarta pada 27 Mei 2006 dengan kekuatan 6,3 M w . Sebagai upaya mitigasi, BMKG melakukan pengamatan parameter fisis dan kimiawi dengan memasang sensor parameter prekursor di Stasiun Pundong dan Piyungan, Yogyakarta. Data parameter prekursor (radon, geotemperatur, suhu udara, dan ketinggian air tanah) diperoleh dari Pusat Penelitian dan Pengembangan (Puslitbang) BMKG, sedangkan data parameter gempa bumi diperoleh dari katalog BMKG dengan kriteria magnitudo dan jarak episenter dalam radius km pada tahun 2018. Penelitian ini menganalisis variasi nilai parameter prekursor yang berasosiasi dengan aktivitas gempa bumi di wilayah Yogyakarta. Pengolahan data mengacu pada beberapa penelitian terdahulu dengan menggunakan metode statistik. Validasi dilakukan secara kuantitatif menggunakan data curah hujan dan secara kualitatif menggunakan data kondisi geologi dari studi literatur. Hasil penelitian menunjukkan adanya indikasi perubahan nilai parameter prekursor sebelum gempa bumi dengan variasi nilai yang dipengaruhi oleh besarnya parameter gempa, tetapi masih sulit dibedakan apakah anomali terjadi akibat aktivitas tektonik atau kondisi meteorologis.
{"title":"Analisis Perubahan Parameter Fisis dan Kimiawi Sebagai Studi Prekursor Gempa Bumi di Wilayah Yogyakarta","authors":"Divyana Meidita, Agustya Adi Martha, Y. Setiawan, Supriyanto Rohadi","doi":"10.31172/JMG.V22I1.766","DOIUrl":"https://doi.org/10.31172/JMG.V22I1.766","url":null,"abstract":"Gempa merusak pernah terjadi di sekitar Sesar Opak, Yogyakarta pada 27 Mei 2006 dengan kekuatan 6,3 M w . Sebagai upaya mitigasi, BMKG melakukan pengamatan parameter fisis dan kimiawi dengan memasang sensor parameter prekursor di Stasiun Pundong dan Piyungan, Yogyakarta. Data parameter prekursor (radon, geotemperatur, suhu udara, dan ketinggian air tanah) diperoleh dari Pusat Penelitian dan Pengembangan (Puslitbang) BMKG, sedangkan data parameter gempa bumi diperoleh dari katalog BMKG dengan kriteria magnitudo dan jarak episenter dalam radius km pada tahun 2018. Penelitian ini menganalisis variasi nilai parameter prekursor yang berasosiasi dengan aktivitas gempa bumi di wilayah Yogyakarta. Pengolahan data mengacu pada beberapa penelitian terdahulu dengan menggunakan metode statistik. Validasi dilakukan secara kuantitatif menggunakan data curah hujan dan secara kualitatif menggunakan data kondisi geologi dari studi literatur. Hasil penelitian menunjukkan adanya indikasi perubahan nilai parameter prekursor sebelum gempa bumi dengan variasi nilai yang dipengaruhi oleh besarnya parameter gempa, tetapi masih sulit dibedakan apakah anomali terjadi akibat aktivitas tektonik atau kondisi meteorologis.","PeriodicalId":32347,"journal":{"name":"Jurnal Meteorologi dan Geofisika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81715471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Olatunji, Ahmed Muyiwa Emiola, Adewale Warith Adebisi
The study aimed to determine the exposure levels of the subsurface aquiferous layers, owing to the alarming rate of contamination of the groundwater within 8.150 0N - 8.156 0N and 4.244 0E - 4.248 0E. Thus, aquifers' overlying layers, resistivity, and thickness anomalies were determined to generate an aquifer vulnerability map. A multi-criteria decision method of estimated Groundwater confinement, Overlying strata, Depth to Aquifer, and Topography index approach was implemented. Schlumberger's Vertical Electrical Sounding technique was implemented to acquire 30 Vertical Electrical Sounding points under a maximum half-current electrode separation (AB/2) of 65 m. IP2Win geophysical software packages were used to analyze the varying layer resistivity, depth, thickness, and also the sounding curves of the study area. The 2D model revealed a maximum of four geo-electric layers. The layers' resistivity and thickness ranges are clayey silt topsoil (52.5-1104 Ωm; 0.5-9.59 m), weathered layer (10.3-804 Ωm; 0.6-12.1 m), fractured basement (5.5-50832 Ωm; 6.7-18.1 m) and fresh basement (8.3-27348 Ωm; infinity m). On the Groundwater Overlying Strata Depth to Aquifer and Topography model scale, the area is generally characterized by the moderate vulnerability. Implying here is that aquifers have a moderate protective capacity in which the overlying strata above the aquifer are mostly impermeable layers (clay and silt) of high thickness and low porosity.
由于地下水在8.150 n - 8.156 n和4.244 e - 4.248 e范围内的污染警戒率，本研究旨在确定地下含水层的暴露水平。因此，确定含水层的上覆层、电阻率和厚度异常，生成含水层易损性图。提出了一种估算地下水约束、上覆地层、含水层深度和地形指数法的多准则决策方法。采用斯伦贝谢的垂直电测深技术，在最大半电流电极间距(AB/2)为65 m的条件下获得了30个垂直电测深点。利用IP2Win地球物理软件包对研究区各层电阻率、深度、厚度及测深曲线进行了分析。二维模型显示最多有四个地电层。各层电阻率及厚度范围为黏性粉土表土(52.5 ~ 1104 Ωm;0.5-9.59 m)，风化层(10.3-804 Ωm;0.6-12.1 m)，断裂基底(5.5-50832 Ωm;6.7-18.1 m)和新鲜地下室(8.3-27348 Ωm;在地下水上覆层至含水层深度和地形模型尺度上，该地区总体上具有中等脆弱性特征。这意味着含水层具有中等的保护能力，其上覆层主要是高厚度、低孔隙度的不透水层(粘土和粉砂)。
{"title":"AQUIFER VULNERABILITY EVALUATION IN SOUTHWESTERN NIGERIA FROM AHP-GODT MODEL USING GEO-ELECTRICAL DERIVED PARAMETERS","authors":"S. Olatunji, Ahmed Muyiwa Emiola, Adewale Warith Adebisi","doi":"10.31172/JMG.V22I1.764","DOIUrl":"https://doi.org/10.31172/JMG.V22I1.764","url":null,"abstract":"The study aimed to determine the exposure levels of the subsurface aquiferous layers, owing to the alarming rate of contamination of the groundwater within 8.150 0N - 8.156 0N and 4.244 0E - 4.248 0E. Thus, aquifers' overlying layers, resistivity, and thickness anomalies were determined to generate an aquifer vulnerability map. A multi-criteria decision method of estimated Groundwater confinement, Overlying strata, Depth to Aquifer, and Topography index approach was implemented. Schlumberger's Vertical Electrical Sounding technique was implemented to acquire 30 Vertical Electrical Sounding points under a maximum half-current electrode separation (AB/2) of 65 m. IP2Win geophysical software packages were used to analyze the varying layer resistivity, depth, thickness, and also the sounding curves of the study area. The 2D model revealed a maximum of four geo-electric layers. The layers' resistivity and thickness ranges are clayey silt topsoil (52.5-1104 Ωm; 0.5-9.59 m), weathered layer (10.3-804 Ωm; 0.6-12.1 m), fractured basement (5.5-50832 Ωm; 6.7-18.1 m) and fresh basement (8.3-27348 Ωm; infinity m). On the Groundwater Overlying Strata Depth to Aquifer and Topography model scale, the area is generally characterized by the moderate vulnerability. Implying here is that aquifers have a moderate protective capacity in which the overlying strata above the aquifer are mostly impermeable layers (clay and silt) of high thickness and low porosity.","PeriodicalId":32347,"journal":{"name":"Jurnal Meteorologi dan Geofisika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86643108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pulau Sulawesi dan Nusa Tenggara Timur (NTT) merupakan wilayah yang memiliki tatanan tektonik kompleks, sehingga penting untuk menggambarkan kondisi bawah permukaan wilayah tersebut. Metode Ambient Noise Tomography (ANT) digunakan untuk memahami struktur tektonik tersebut dengan mencitrakan struktur kerak atas di bawah area penelitian ini. Pada penelitian ini, kami menggunakan data waveform komponen vertikal dari Januari 2020 hingga Mei 2021 dari 89 seismograf INATEWS- BMKG di Pulau Sulawesi dan NTT. Secara umum, tahap pertama dimulai dari pemrosesan data berfokus pada persiapan data tunggal dan korelasi silang untuk memperkiraan fungsi Green antara pasangan stasiun. Estimasi waktu tempuh kelompok gelombang Rayleigh untuk periode 2 s dan 12 s diperoleh dari waktu tunda hasil korelasi silang. Peta yang diperoleh menunjukkan variasi kecepatan gelombang Rayleigh di daerah penelitian berkisar antara 1,8 – 2,5 km/s. Teknik analisis frekuensi-waktu (Frequency-Time Analysis) digunakan untuk mendapatkan kurva dispersi untuk mengukur kecepatan kelompok antar stasiun. Kecepatan grup digunakan sebagai input dalam inversi tomografi. Proses tomografi dilakukan dengan menggunakan FMST v1.1 dimana pemodelan forward dan inverse dilakukan secara iteratif. Hasil pemodelan untuk periode 2 s menunjukkan bahwa Sulawesi Barat dan Sulawesi Utara memiliki anomali kecepatan yang lebih rendah (1,8 km/s) dibandingkan wilayah lain (2,0 – 2,3 km/s). Pada periode 12 s anomali kecepatan rendah berada di wilayah Sulawesi Utara. Anomali kecepatan rendah ini berkorespondensi dengan gunung berapi dan dataran Inter-Volcano yang berumur Kuarter di Sulawesi. Sementara untuk wilayah NTT nilai kecepatan gelombang Rayleigh berkisar antara 1,8 – 2,4 km/s.
{"title":"PENCITRAAN STRUKTUR KECEPATAN GELOMBANG RAYLEIGH DI PULAU SULAWESI DAN NUSA TENGGARA TIMUR MENGGUNAKAN AMBIENT NOISE TOMOGRAPHY","authors":"M. Fadhilah","doi":"10.31172/JMG.V22I1.778","DOIUrl":"https://doi.org/10.31172/JMG.V22I1.778","url":null,"abstract":"Pulau Sulawesi dan Nusa Tenggara Timur (NTT) merupakan wilayah yang memiliki tatanan tektonik kompleks, sehingga penting untuk menggambarkan kondisi bawah permukaan wilayah tersebut. Metode Ambient Noise Tomography (ANT) digunakan untuk memahami struktur tektonik tersebut dengan mencitrakan struktur kerak atas di bawah area penelitian ini. Pada penelitian ini, kami menggunakan data waveform komponen vertikal dari Januari 2020 hingga Mei 2021 dari 89 seismograf INATEWS- BMKG di Pulau Sulawesi dan NTT. Secara umum, tahap pertama dimulai dari pemrosesan data berfokus pada persiapan data tunggal dan korelasi silang untuk memperkiraan fungsi Green antara pasangan stasiun. Estimasi waktu tempuh kelompok gelombang Rayleigh untuk periode 2 s dan 12 s diperoleh dari waktu tunda hasil korelasi silang. Peta yang diperoleh menunjukkan variasi kecepatan gelombang Rayleigh di daerah penelitian berkisar antara 1,8 – 2,5 km/s. Teknik analisis frekuensi-waktu (Frequency-Time Analysis) digunakan untuk mendapatkan kurva dispersi untuk mengukur kecepatan kelompok antar stasiun. Kecepatan grup digunakan sebagai input dalam inversi tomografi. Proses tomografi dilakukan dengan menggunakan FMST v1.1 dimana pemodelan forward dan inverse dilakukan secara iteratif. Hasil pemodelan untuk periode 2 s menunjukkan bahwa Sulawesi Barat dan Sulawesi Utara memiliki anomali kecepatan yang lebih rendah (1,8 km/s) dibandingkan wilayah lain (2,0 – 2,3 km/s). Pada periode 12 s anomali kecepatan rendah berada di wilayah Sulawesi Utara. Anomali kecepatan rendah ini berkorespondensi dengan gunung berapi dan dataran Inter-Volcano yang berumur Kuarter di Sulawesi. Sementara untuk wilayah NTT nilai kecepatan gelombang Rayleigh berkisar antara 1,8 – 2,4 km/s.","PeriodicalId":32347,"journal":{"name":"Jurnal Meteorologi dan Geofisika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91135401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Sumatran fault is a right lateral active inland fault in southern Sumatra, Indonesia. Although historical earthquake records have shown that magnitude 7 class earthquakes have occurred during the last century, the slip rates along the Sumatran fault have not been studied in detail. This is the first research using a new dense GPS array, in which stations are orthogonal to the fault, to analyze the fault slip rates along the Kumering and Semangko segments in southern Sumatra. In this study, we process GPS data from 14 campaign and continuous GPS points. The results show velocities of 14 mm/yr and 15 mm/yr for these two fault segments, respectively. Our estimated geodetic slip rate suggests that the Sumatran fault has a relatively homogeneous slip rate from southern to northern Sumatra.
{"title":"GEODETIC SLIP RATE ESTIMATES FOR THE KUMERING AND SEMANGKO SEGMENTS OF THE SUMATERA FAULT","authors":"I. Meilano, S. Susilo, E. Gunawan, Budi Parjanto","doi":"10.31172/JMG.V22I1.802","DOIUrl":"https://doi.org/10.31172/JMG.V22I1.802","url":null,"abstract":"The Sumatran fault is a right lateral active inland fault in southern Sumatra, Indonesia. Although historical earthquake records have shown that magnitude 7 class earthquakes have occurred during the last century, the slip rates along the Sumatran fault have not been studied in detail. This is the first research using a new dense GPS array, in which stations are orthogonal to the fault, to analyze the fault slip rates along the Kumering and Semangko segments in southern Sumatra. In this study, we process GPS data from 14 campaign and continuous GPS points. The results show velocities of 14 mm/yr and 15 mm/yr for these two fault segments, respectively. Our estimated geodetic slip rate suggests that the Sumatran fault has a relatively homogeneous slip rate from southern to northern Sumatra.","PeriodicalId":32347,"journal":{"name":"Jurnal Meteorologi dan Geofisika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73801391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. D. Hutapea, Donaldi S Permana, Alfan S. Praja, Linda F. Muzayanah
Radar cuaca sangat berpotensi untuk memberikan estimasi curah hujan beresolusi tinggi secara spasial dan temporal yang dapat meningkatkan akurasi prakiraan dini cuaca ekstrim dan juga dapat menyediakan informasi curah hujan pada wilayah yang tidak mempunyai stasiun pengamatan curah hujan. Radar cuaca tidak dapat secara langsung mengukur intensitas curah hujan, melainkan berdasarkan hubungan empiris antara reflektifitas radar ( Z ) dan tingkat curah hujan ( R ) dalam hubungan Z-R ( Z = AR b ). Pada penelitian ini, metode optimalisasi digunakan untuk menentukan konstanta A dan b yang sesuai untuk wilayah Surabaya di provinsi Jawa Timur. Data reflektifitas pada radar Surabaya dan data curah hujan per jam dari stasiun Juanda Surabaya pada periode Desember 2014 - Februari 2015 digunakan dalam studi ini. Hasil studi menunjukkan bahwa hubungan Z - R dengan persamaan Z = 110 R 1,6 menghasilkan estimasi curah hujan yang memiliki indikator statistik lebih baik dibandingkan dengan estimasi dari persamaan Marshall-Palmer (MP, Z = 200 R 1,6 ) dan Rosenfeld (Ros, Z = 250 R 1,2 ) sehingga dapat meningkatkan akurasiestimasi curah hujan di wilayah Surabaya. Weather radar can potentially provide rainfall estimates with high spatial and temporal resolution in which improving the early warning accuracy of extreme weather and also provide rainfall estimates in areas with insufficient rainfall stations. Weather radar cannot directly be used to measure the rainfall intensity, but based on an empirical relationship between the reflectivity (Z) and rainfall rate (R) in the Z-R relationship (Z = AR b ). In this study, an optimization method was used to determine suitable constants A and b for Surabaya, East Java province. The reflectivity data from Surabaya radar and hourly rainfall data at Juanda station in Surabaya during a period of December 2014 - February 2015 were used in this study. The results show that a Z-R relationship in the form of equation Z = 110R 1,6 produces rainfall estimates with a better statistical indicator than ones produced by Marshall-Palmer (MP, Z = 200R 1,6 ) and Rosenfeld (R os , Z = 250R 1,2 ) relationships , making it suitable for improving the accuracy of rainfall estimates for Surabaya.
天气雷达非常有潜力为我们提供空间和时间上高分辨率的降水预报，这可以提高极端早期天气预报的准确度，也可以为没有降水观测站的地区提供降水信息。气象雷达无法直接测量降水的强度，但可以根据雷达光(Z)与Z (Z = AR b)关系的经验关系来判断。在这项研究中，优化方法被用来确定适合爪哇东部泗水地区的A和b常数。2014年12月至2015年2月，泗水Juanda站的反射数据和每小时的降雨数据被用于这项研究。研究结果表明,Z = 110方程Z - R与R 160所产生的降雨量估计方程的估计相比,有更好的统计指标Marshall-Palmer (MP, Z = 200 R 1.6)和罗森菲尔德(Ros, Z = 250 R = 120),以便提高akurasiestimasi泗水地区的降雨量。天气雷达可以提供高度的空间和时间决心的估计，这就产生了极端天气准确的预测，也提供了对现有现有辐射数据的估计。天气雷达无法恢复的强度，但基于Z-R关系中Z和rainfall之间的经验关系。在这项研究中，一种乐观的方法被用来确定一种可靠的方法来支持泗水，东爪哇省。2014年12月9日至2月，泗水站的反射数据在此研究中被使用。results秀那a Z-R关系in The form of equation Z = 110R 160 produces rainfall保守with a better统计比制作单位Marshall-Palmer势力指示器(MP, Z = 200R一台1.6)和罗森菲尔德(R = os, Z = 250R 1.2)评比》relationships,让它suitable for improving rainfall保守为泗水。
{"title":"MODIFIKASI KONSTANTA PERSAMAAN Z-R RADAR SURABAYA UNTUK PENINGKATAN AKURASI ESTIMASI CURAH HUJAN","authors":"T. D. Hutapea, Donaldi S Permana, Alfan S. Praja, Linda F. Muzayanah","doi":"10.31172/jmg.v21i2.545","DOIUrl":"https://doi.org/10.31172/jmg.v21i2.545","url":null,"abstract":"Radar cuaca sangat berpotensi untuk memberikan estimasi curah hujan beresolusi tinggi secara spasial dan temporal yang dapat meningkatkan akurasi prakiraan dini cuaca ekstrim dan juga dapat menyediakan informasi curah hujan pada wilayah yang tidak mempunyai stasiun pengamatan curah hujan. Radar cuaca tidak dapat secara langsung mengukur intensitas curah hujan, melainkan berdasarkan hubungan empiris antara reflektifitas radar ( Z ) dan tingkat curah hujan ( R ) dalam hubungan Z-R ( Z = AR b ). Pada penelitian ini, metode optimalisasi digunakan untuk menentukan konstanta A dan b yang sesuai untuk wilayah Surabaya di provinsi Jawa Timur. Data reflektifitas pada radar Surabaya dan data curah hujan per jam dari stasiun Juanda Surabaya pada periode Desember 2014 - Februari 2015 digunakan dalam studi ini. Hasil studi menunjukkan bahwa hubungan Z - R dengan persamaan Z = 110 R 1,6 menghasilkan estimasi curah hujan yang memiliki indikator statistik lebih baik dibandingkan dengan estimasi dari persamaan Marshall-Palmer (MP, Z = 200 R 1,6 ) dan Rosenfeld (Ros, Z = 250 R 1,2 ) sehingga dapat meningkatkan akurasiestimasi curah hujan di wilayah Surabaya. Weather radar can potentially provide rainfall estimates with high spatial and temporal resolution in which improving the early warning accuracy of extreme weather and also provide rainfall estimates in areas with insufficient rainfall stations. Weather radar cannot directly be used to measure the rainfall intensity, but based on an empirical relationship between the reflectivity (Z) and rainfall rate (R) in the Z-R relationship (Z = AR b ). In this study, an optimization method was used to determine suitable constants A and b for Surabaya, East Java province. The reflectivity data from Surabaya radar and hourly rainfall data at Juanda station in Surabaya during a period of December 2014 - February 2015 were used in this study. The results show that a Z-R relationship in the form of equation Z = 110R 1,6 produces rainfall estimates with a better statistical indicator than ones produced by Marshall-Palmer (MP, Z = 200R 1,6 ) and Rosenfeld (R os , Z = 250R 1,2 ) relationships , making it suitable for improving the accuracy of rainfall estimates for Surabaya.","PeriodicalId":32347,"journal":{"name":"Jurnal Meteorologi dan Geofisika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88983511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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