Japan Meteorology Agency (JMA) developed SATAID (Satellite Animation and Interactive Diagnosis) application to display and to retrieve some meteorology parameter values in satellite image data. This paper studies the use of the application in analyzing the Jakarta flood February 1st, 2008 and the Yogyakarta Tropical cyclone February 18th, 2007. The procedure described in this paper can be applied in another issues as a reference material in analyzing SATAID image data.
<p>To explore the characteristics of Northerly Cold Surge during Years of the Maritime Continent Campaign 2021, intensive observation was used to detect the modification processes of the air mass at the head of cold surge, convection development, and severe weather including torrential rainfall using several methods such as the intensive upper-air observation at Jakarta and Pangkal Pinang, vapor variation observation with GNSS network, and precipitation radar network. During this campaign, 7 CENS (Cross-Equatorial Northerly Surge) events were observed according to Hattori&#8217;s criteria. The results of the intensive observation show that all of 7 CENS events occurred in association with the negative SST anomaly over the Java Sea with CENS6 (18 &#8211; 21 February 2021) induced extreme rainfall (over 150 mm/day) in the southern part of Jakarta. The significant negative SST anomaly was continued over the inland & marginal seas of Indonesia under the strong northerly surge condition during this campaign.</p>
Siklon tropis memiliki pengaruh yang sangat luas terhadap beragam parameter meteorologi. Analisis terhadap kejadian siklon tropis dapat dilakukan pada berbagai macam parameter dengan berbagai teknik yang berbeda. Pada penelitian ini dibahas mengenai identifikasi pola data curah hujan di Jawa dan Madura bertepatan dengan terjadinya siklon tropis Cempaka pada akhir bulan November 2017 di perairan selatan Jawa. Analisis data dilakukan menggunakan Self-Organizing Map (SOM) dan Hierarchical Clustering. Hasil yang diperoleh menunjukkan terdapat 4 kelompok pola curah hujan dominan berkaitan dengan siklon tropis Cempaka. Analisis temporal dan spasial terhadap keempat kelompok tersebut menunjukkan bahwa siklon tropis Cempaka berpengaruh kuat terhadap sebaran curah hujan di Jawa dan Madura.
Pada kajian ini dilakukan evaluasi penggunaan beberapa skema konvektif pada model WRF (Weather Research and Forecasting) untuk prediksi cuaca di wilayah Indonesia. Terdapat tiga skema konvektif yang akan dievaluasi yaitu; skema konvektif cumulus BMJ (Betts Miller Janjic), KF (Kain Fritsch), dan GD (Grell 3D ensemble). Data yang digunakan untuk evaluasi adalah data curah hujan per 3 jam dan data angin per 12 jam (level ketinggian; permukaan, 850, 500, 250 mb) dari hasil pengolahan model WRF dan observasi selama periode bulan Agustus 2011 dan Februari 2012 di stasiun Juanda-Surabaya dan Cengkareng-Jakarta. Hasil verifikasi dari tiga skema konvektif pada model WRF terhadap data observasi menunjukkan bahwa untuk prakiraan curah hujan, penggunaan skema konvektif BMJ lebih baik dari skema KF dan GD, dan untuk prakiraan arah dan kecepatan angin skema BMJ dan GD relatif lebih baik dari skema KF. Berdasarkan analisis hasil verifikasi yang diperoleh, pemilihan skema konvektif cumulus BMJ cenderung lebih baik dari skema konvektif KF dan GD untuk di aplikasikan pada model WRF.
A daily mean rainfall in a month forecast method is presented in this paper. The method provides spatial forecast over Indonesia and employs ensemble of Machine Learning and Artificial Intelligence algorithms as its forecast models. Each spatial grid in the forecast output is processed as an individual dataset. Therefore, each location in the forecast output has different stacked ensemble models as well as their model parameter settings. Furthermore, the best ensemble model is chosen for each spatial grid. The input dataset of the model consists of eight climate data (i.e., East and West Dipole Mode Index, Outgoing Longwave Radiation, Southern Oscillation Index, and Nino 1.2, 3, 4, 3.4) and monthly rainfall reanalysis data, ranging from January 1982 until December 2019. There are four assessment procedures performed on the models: daily mean rainfall establishment as a response function of climate patterns, and one-up to three-month lead forecast. The results show that, based on their performance, these non-Physical models are considerable to complement the existing forecast models.
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