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All Journal Agromet Indonesian Journal of Agricultural Science Jurnal Matematika & Sains Jurnal Tataloka Jurnal Sains Dirgantara JURNAL METEOROLOGI DAN GEOFISIKA Jurnal Tanah dan Iklim Jurnal Meteorologi dan Geofisika
Tri Wahyu Hadi
Graduate Program Of Earth Sciences, Faculty Of Earth Sciences And Technology, Institut Teknologi Bandung, Bandung, Indonesia
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Earth & Planetary Sciences Education Energy Mathematics Physics

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 1 
Analysis of Synoptic Disturbance in Maritim Continent Using Spherical Harmonics Transformation Method Sayful Amri; Faiz Rohman Fajary; Tri Wahyu Hadi
Agromet Vol. 34 No. 2 (2020): DECEMBER 2020
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.34.2.89-99

Abstract

This study aims to modify the idea of ​​WK99-analyzing the existence of signature in wave-number and frequency spectrum when the analyzed Outgoing Longwave Radiation (OLR) data is associated with a unique phenomenon in Maritime Continent (MC), Borneo vortex (BV). Although BV is often related to easterly equatorial wave disturbances, there was no specific study to examine its behavior in the spectral domain. The purpose of this study is to develop a method to diagnose certain signatures of BV through spectrum analysis of OLR data when BV occurs. In contrast to previous studies, to present the unique phenomenon in MC as a target for diagnostics, spectrum analysis is performed by Spherical Harmonics (SH). The results of the OLR data spectrum comparison when BV occurs with the OLR data spectrum when BV does not occur that in the anti-symmetrical component when BV occurs, the tropical depression-mixed Rossby gravity (TD-MRG) wave spectrum is stronger, especially in zonal wave-numbers 5 to 10 and frequencies 0.12 to 0.2. Similar to the anti-symmetrical component, the TD-MRG spectrum of the symmetrical component is also stronger at zonal wave-numbers 5 to 10 and frequencies 0.12 to 0.2. Moreover, the westward-propagating inertio-gravity (WIG) wave spectrum in the symmetrical component is also stronger at the time of BV than when there is no BV, especially at zonal wave-numbers 7 to 13 and frequencies 0.38 to 0.5. It can be concluded that when BV occurs, equatorial waves that propagate to the west, especially the types of TD-MRG and WIG waves are stronger than when BV did not occur. The results of durational grouped spectrum analysis of OLR data when BV occurs indicate that the longer the duration of BV occurs, the stronger the spectrum of TD-MRG and WIG wave types gets.
The Study of Wind Field ERA-20C in Monsoon Domains for Rainfall Predictor in Indonesia (Java, Sumatra, and Borneo) Trinah Wati; Tri Wahyu Hadi; Ardhasena Sopaheluwakan; Lambok M Hutasoit
Agromet Vol. 37 No. 1 (2023): JUNE 2023
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.37.1.34-43

Abstract

In recent years, various research institutions have developed diverse global data reanalysis projects. This provides an opportunity to gain long-term of meteorological data for local scale. This study aims to select the potential predictor of wind fields u and v of the ERA-20C dataset, a reanalysis dataset, at 850 mb from seven domains or windows of Asian, Maritime Continent, Australian, and Western North Pacific monsoon related physically to rainfall anomaly patterns in Indonesia. The vector wind velocity scalar was obtained by using a Helmholtz decomposition to separate the total circulation v = (u,v) into the divergent component/velocity potential (χ) or Phi and rotational component/stream function (ψ) or Psi for obtaining the scalar variable of vector wind velocity. The method applied Singular value decomposition (SVD) to identify pairs of spatial patterns (expansion coefficients) between the predictors of Phi and Psi in seven domains, with rainfall data from 48 stations in Java, Sumatra, and Borneo Islands from 1981 to 2010. The results revealed that spatial patterns correlations of Java Islands were the highest in the Maritime Continent monsoon domain (80o−150o E and 15oS−15o N), while Sumatra and Borneo Island were in the Western North Pacific monsoon domain (100o–130o E and 5o–15o N) with predictor Psi. The lowest correlation for Java, Sumatra, and Borneo was the Australian monsoon domain (110o E–130o E and 5o S–15o S) with predictor Phi. In general, spatial pattern correl-ations of Java Island were higher than others, agreeing with monsoonal rainfall type dominantly in the region.
Implementation of Bayesian Model Averaging Method to Calibrate Monthly Rainfall Ensemble Prediction over Java Island Muharsyah, Robi; Hadi, Tri Wahyu; Indratno, Sapto Wahyu
Agromet Vol. 34 No. 1 (2020): JUNE 2020
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1296.784 KB) | DOI: 10.29244/j.agromet.34.1.20-33

Abstract

Bayesian Model Averaging (BMA) is a statistical post-processing method for producing probabilistic forecasts from an ensemble prediction in the form of predictive Probability Density Function (PDF). BMA is commonly used to calibrate Ensemble Prediction System (EPS) in a shorter-range forecast. Here, we applied the BMA for a longer forecast at a seasonal interval. This study aimed to develop the implementation of the BMA method to calibrate the seasonal forecast (long range) of monthly rainfall from the RAW output of the EPS European Center for Medium-Range Weather Forecasts (ECMWF) system 4 model (ECS4). This model was calibrated with observational data from 26 stations over Java Island in 1981-2018. BMA predictive PDF was generated with a gamma distribution, which was obtained based on two training schemes, namely sequential (BMA-JTS) and conditional (BMA-JTC) training windows. Generally, both of BMA-JTS and BMA-JTC were able to produce better distribution characteristics of ensemble prediction than that of RAW model ECS4. Both BMA methods showed a good performance as indicated by a high accuracy, small bias, and small uncertainty to the observed rainfall. Our findings revealed that BMA-JTC was able to improve the quality of probabilistic forecasts of below and above normal events. The improvement was shown in most stations over Java Island, in which the model was a good skill forecast based on Brier Skill Score (BSS).
Co-Authors Agus Safril Al Habib, Abdul Hamid Ardhasena Sopaheluwakan Arief Suryantoro Aries Kristianto Aser Rouw Bayong Tjasyono H. Kasih Djoko Santoso Abi Suroso Dudy Darmawan Wijaya Eddy Hermawan Eddy Hermawan Edi Riawan, Edi Elza Surmaini Elza Surmaini Elza Surmaini Elza Surmaini Faiz Rohman Fajary Findy Renggono Findy Renggono Giriharta, I Wayan Gita H.K., Bayong Tjasyono Hadi, Safwan Hamzah Latief Hutauruk, Rheinhart Hutauruk, Rheinhart C H Indra Gustari Indratno, Sapto Wahyu Irma Nurlela Kasdi Subagyono Kasdi Subagyono Lambok M. Hutasoit M. Ridho Syahputra Mega Puspawardhany Muharsyah, Robi Nanang T. Puspito Nanang Tyasbudi Puspito Noersomadi Noersomadi Nurry Widya Hesty Rahmanto, Edi Safwan Hadi Sayful Amri Subagyono, Kasdi Trilaksono, Nurjanna Joko Trinah Wati Udjianna S. Pasaribu Yoku, Priskila Wilhelmina Yolanda, Selvy