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All Journal Jurnal Fisika Unand International Journal of Remote Sensing and Earth Sciences (IJReSES)
Abdullah Ali
BMKG
Earth & Planetary Sciences Electrical & Electronics Engineering Energy Materials Science & Nanotechnology Physics

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PRELIMINARY STUDY OF HORIZONTAL AND VERTICAL WIND PROFILE OF QUASI-LINEAR CONVECTIVE UTILIZING WEATHER RADAR OVER WESTERN JAVA REGION, INDONESIA Abdullah Ali; Riris Adrianto; Miming Saepudin
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 15, No 2 (2018)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1580.469 KB) | DOI: 10.30536/j.ijreses.2018.v15.a3075

Abstract

One of the weather phenomena that potentially cause extreme weather conditions is the linear-shaped mesoscale convective systems, including squall lines. The phenomenon that can be categorized as a squall line is a convective cloud pair with the linear pattern of more than 100 km length and 6 hours lifetime. The new theory explained that the cloud system with the same morphology as squall line without longevity threshold. Such a cloud system is so-called Quasi-Linear Convective System (QLCS), which strongly influenced by the ambient dynamic processes, include horizontal and vertical wind profiles. This research is intended as a preliminary study for horizontal and vertical wind profiles of QLCS developed over the Western Java region utilizing Doppler weather radar. The following parameters were analyzed in this research, include direction pattern and spatial-temporal significance of wind speed, divergence profile, vertical wind shear (VWS) direction, and intensity profiles, and vertical velocity profile. The subjective and objective analysis was applied to explain the characteristics and effects of those parameters to the orientation of propagation, relative direction, and speed of the cloud system’s movement, and the lifetime of the system. Analysis results showed that the movement of the system was affected by wind direction and velocity patterns. The divergence profile combined with the vertical velocity profile represents the inflow which can supply water vapor for QLCS convective cloud cluster. Vertical wind shear that effect QLCS system is only its direction relative to the QLCS propagation, while the intensity didn’t have a significant effect.
Implementasi Metode Deteksi Hujan Es Berbasis Data Radar Cuaca Menggunakan Algoritma Severe Hail Index (SHI) Abdullah Ali; Umi Sa’adah
Jurnal Fisika Unand Vol 11 No 3 (2022)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (344.313 KB) | DOI: 10.25077/jfu.11.3.380-386.2022

Abstract

Metode Severe Hail Index (SHI)  ini merupakan metode pendeteksian hujan es yang paling komprehensif dengan output berupa indeks probabilitas hujan es (pada setiap ukuran) dalam satuan Jm-1s-1, probabilitas severe hail dalam satuan %, dan prakiraan ukuran maksimum batu es yang mencapai permukaan dalam satuan milimeter. Penelitian ini bertujuan mengimplementasikan metode SHI sebagai detektor dan prediktor kejadian hujan es di Indonesia. Dari 13 kejadian hujan es diperoleh nilai maksimum indeks probabilitas hujan es untuk setiap ukuran sebesar 269 Jm-1s-1 dan nilai minimum 0 Jm-1s-1, nilai maksimum indeks probabilitas severe hail sebesar 64.4 % dan nilai minimum 0%, sedangkan nilai maksimum prakiraan ukuran maksimum batu es mencapai 63.76 mm dan minimum 8.25 mm. Simulasi dilakukan dengan membandingkan nilai SHI dengan WT yang kemudian digunakan untuk menentukan nilai POD (Possibility of Detection), CSI (Critical Succes Index), dan FAR (False Alarm Ratio). POD pada simulasi ini diperoleh nilai 0.307 dan 0.230, FAR 0.0, dan CSI 0.307. FAR bernilai 0.0 menunjukkan metode ini mempunyai tingkat kesalahan yang sangat kecil untuk mendeteksi atau memperdiksi adanya huajan es namun nilai POD masih tergolong rendah, sehingga metode ini juga cukup sulit untuk mendeteksi eksistenesi hail di lapangan. Hasil simulasi tersebut menunjukkan bahwa perlunya modifikasi pada perumusan WT untuk meningkatkan performa metode SHI dalam mendeteksi dan memprediksi kejadian hujan es.
Monitoring Perubahan Tutupan Lahan di Kota Blitar Berbasis Algoritma Random Forest Abdullah Ali
Jurnal Fisika Unand Vol 12 No 3 (2023)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jfu.12.3.409-415.2023

Abstract

Perubahan penggunaan lahan harus dimonitor dan dievaluasi untuk menghindari dampak lingkungan jangka panjang. Penelitian ini bertujuan untuk melakukan monitoring penggunaan/penutup lahan di Kota Blitar menggunakan metode klasifikasi supervised learning Random Forest (RF). Basis data yang digunakan adalah citra satelit LANDSAT dengan multitemporal tahun 2001, 2011, dan 2021 yang diolah menggunakan platform geospasial berbasis cloud Google Earth Engine (GEE). Uji akurasi hasil klasifikasi RF menunjukkan nilai koefisien kappa lebih dari 0,7 sehingga hasil klasifikasi dapat dilanjutkan untuk dianalisis perubahannya. Analisis jarak dari jalan digunakan sebagai faktor pendorong perubahan penggunaan lahan. Pada tiga kecamatan di Kota Blitar, tren luasan jenis tutupan vegetasi selalu menurun dari tahun 2001-2021, terkecuali kecamatan Sukorejo yang mengalami kenaikan 30,84 ha pada tahun 2021. Pada jenis tutupan sawah/perkebunan, hanya Kecamatan Kepanjen Kidul yang mengalami kenaikan pada tahun 2011 sebesar 18,74 ha, namun luasannya berkurang kembali pada tahun 2021 sebesar 5,04 ha. Jenis tutupan lahan terbangun selalu meningkat pada seluruh kecamatan, dengan rata-rata peningkatan sebesar 104,43 ha dalam kurun waktu 2001-2021. Perubahan menjadi lahan terbangun cenderung terjadi pada jaringan jalan utama Kota Blitar dengan radius 500m.
SPATIAL ANALYSIS OF QUANTITATIVE PRECIPITATION FORECAST ACCURACY BASED ON STRUCTURE AMPLITUDE LOCATION (SAL) TECHNIQUE Abdullah Ali; Achmad Rifani; Supriatna Supriatna; Yunus Subagyo Swarinoto; Umi Sa'adah
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 20, No 2 (2023)
Publisher : Ikatan Geografi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2023.v20.a3854

Abstract

Quantitative Precipitation Forecast (QPF) is the final product of a short-term forecasting algorithm (nowcasting) based on weather radar data which is widely used in hydrometeorological aspects. The calculation of the accuracy value using point data on a rainfall gauge often causes a double penalty problem because the QPF prediction results are in the form of spatial objects. This study aims to apply object-based spatial verification in analyzing the accuracy of QPF based on the Short Term Ensemble Prediction System (STEPS) algorithm using the SAL technique. The verification process is carried out by calculating the index value of the structure component (S), amplitude (A), and location (L) in the QPF prediction results based on the results of weather radar observations. The index values for components S and A have a range of -2 to 2, and 0 to 1 for component L with a perfect value of 0. The case study used is the occurrence of heavy rains that caused flooding in Bogor Regency in 2020. SAL verification results from 26 case studies used shows the average value of the components S, A, and L, respectively 0.51, 0.38, and 0.21. As many as 75% of all case studies have S and L component values less than 0.5 which indicate the structure and location of the QPF prediction object is close to the structure and location of the object of observation. A positive value in component A indicates that the QPF prediction results based on the STEPS algorithm tend to be overestimated but on a low scale, namely 0.38 out of 2.
Co-Authors Achmad Rifani Miming Saepudin Riris Adrianto Supriatna Supriatna Umi Sa'adah Umi Sa’adah Umi Sa’adah Yunus Subagyo Swarinoto