<p><strong>Abstract: </strong>Hail detection using information from satellite and weather radar is the right choice due to spatial and temporal variability of the phenomenon of high hail. Some algorithms that use single polarization radar data have been developed for hail detection. One method that has been applied in Reflectivity-based Hail Warning or ZHAIL radar product is the Waldvogel method. This research aims to find new threshold criteria for the application of the Waldvogel method in the Jakarta weather radar observation area which is grouped into three regions based on the distance of weather radar observation. In this research, hail events from 2010 to 2019 have been analysed. Analysis of weather and weather radar data was carried out to determine the climatological characteristics of reflectivity values, reflectivit heights, and freezing levels as parameters to be used to determine the criteria for modification in the Waldvogel method. The reflectifity and reflectivity values are obtained from the processing of radar data, while the freezing level is generated from the processing of the Himawari satellite image in the infrared channel. Waldvogel's algorithm with the three modifications that have been produced, then tested using Critical Success Index, Possibility of Detection, and False Alram Ratio, calculations on the percentage value of Probability Of Hail. The results of the research is the reflectivity values, reflectivity altitude and the most accurate freezing level applied to each region that was differentiated according to the weather radar distance radius observation. Better accuracy of the application of Waldvogel method is expected to reduce therougheffects ofthehail phenomenon.</p><p><strong>Abstrak: </strong>Metode Waldvogel merupakan metode deteksi hujan es yang mengubah reflectivity dari pengamatan radar menjadi produk Reflectivity-based Hail Warning atau ZHAIL. Penggunaan metode Waldvogel masih perlu disesuaikan dengan kondisi wilayah tropis termasuk Indonesia. Penelitian ini bertujuan untuk menemukan kriteria ambang batas baru untuk penerapan metode Waldvogel di daerah pengamatan radar cuaca Jakarta sehingga diperoleh akurasi metode Waldvogel yang lebih baik. Kriteria ambang dikelompokkan menjadi tiga wilayah berdasarkan jarak cakupan radar cuaca (wilayah I : <30 km, wilayah II : 30-100 km dan wilayah III : 100-150 km). Analisis data radar cuaca dilakukan untuk menentukan karakteristik klimatologis dari nilai reflectivity maksimum, ketinggian reflectivity maksimum, dan ketinggian freezing level sebagai parameter yang akan digunakan untuk menentukan kriteria modifikasi dalam metode Waldvogel. Verfikasi parameter diujikan dengan nilai Probability of Hail (POH), False Alarm Ratio (FAR), Possibility of Detection (POD), dan Critical Success Index (CSI). Hasil verifikasi menunjukan metode Waldvogel modiifikasi menghasilkan performa yang lebih baik dibandingkan metode Waldvogel awal untuk wilayah I dan II dengan kriteria metode Waldvogel modifikasi yang paling baik yaitu Waldvogel 3. Sedangkan untuk wilayah III, nilai kriteria yang lebih baik adalah Waldvogel tanpa modifikasi. Akurasi yang lebih baik dari penerapan metode Waldvogel diharapkan dapat mengurangi dampak buruk yang ditimbulkan dari fenomena hujan es</p>
<p class="AbstractEnglish"><strong>Abstract: </strong>The Quasi Linear Convective System (QLCS) is a meso-scale convective weather system that has the potential to bring heavy rains and destructive strong winds. One of the Quasi Linear Convective Systems (QLCS) that have occurred in Indonesia is the QLCS that was formed in Bengkulu on November 10, 2017. QLCS can be identified using weather radar observations through maximum reflectivity imagery that forms long lines. WRF-ARW (Weather Research and Forecasting - Advanced Research) weather modeling is able to simulate meso-scale atmospheric conditions. This study aims to examine the phenomenon of QLCS using identification of weather radar observations and the results of WRF-ARW modeling. The results showed a QLCS with a length of 82 km, began to form at 09:30 UTC and reached its peak at 10.50 UTC with a maximum reflectivity of 63 dBz. Atmospheric dynamics conditions in the form of wind / streamline patterns, vertical velocity, relative humidity, Convective Available Potential Energy (CAPE) and cloud fraction from WRF-ARW model outputs show a suitable pattern and support the occurrence of convective systems around the scene. Wind patterns at the time of the event indicate a convergence region. Meanwhile the vertical velocity value reaches a peak of 0.8 Pa / s before QLCS starts entering the mature phase. The relative humidity is 95% - 100% and the CAPE value reaches 1000 J / Kg to 1500 J / Kg. Cloud fraction in the layer near the surface reaches 1%. Verification results with observational data show that rainfall parameters produce smaller errors compared to the results of verification reflectivity values. This shows that the WRF-ARW model is still inaccurate in modeling reflectivity data.</p><p class="AbstrakIndonesia"><strong>Abstrak: </strong><em>Quasi Linear Convective System</em> (QLCS) merupakan sistem cuaca konvektif skala meso yang berpotensi membawa hujan lebat dan angin kencang yang sifatnya merusak. Salah satu <em>Quasi Linear Convective System</em> (QLCS) yang pernah terjadi di Indonesia adalah QLCS yang terbentuk di Bengkulu pada tanggal 10 November 2017. QLCS dapat diidentifikasi menggunakan pengamatan radar cuaca melalui citra <em>reflectivity</em> maksimum yang membentuk garis memanjang. Pemodelan cuaca WRF-ARW (<em>Weather Research and Forecasting </em><em>–</em><em> Advanced Research</em>) mampu mensimulasikan kondisi atmosfer skala meso. Penelitian ini bertujuan untuk mengkaji fenomena QLCS dengan menggunakan identifikasi pengamatan radar cuaca dan hasil permodelan WRF-ARW. Hasil penelitian menunjukkan QLCS dengan panjang 82 km, mulai terbentuk pada pukul 09.30 UTC dan mencapai puncaknya pada pukul 10.50 UTC dengan <em>reflectivity</em> maksimum 63 dBz. Kondisi dinamika atmosfer yang berupa pola angin/<em>streamline</em>, <em>vertical velocity</em>, kelembapan relatif,<em> Convective Available Potential Energy</em> (CAPE) dan <em>cloud fraction</em> hasil keluaran model WRF-ARW menunjukan pola yang sesuai dan mendukung terjadinya sistem konvektif di sekitar lokasi kejadian. Pola angin pada waktu kejadian menunjukan adanya daerah konvergensi. Sementara itu nilai <em>verti</em><em>c</em><em>al</em> <em>velocity</em> mencapai puncaknya 0.8 Pa/s pada saat sebelum QLCS mulai memasuki fase matang. Kelembaban relatif sebesar 95% - 100% dan nilai CAPE mencapai 1000 J/Kg hingga 1500 J/Kg. <em>Cloud fraction</em> di lapisan dekat permukaan mencapai 1 %. Hasil verifikasi dengan data observasi menunjukan parameter curah hujan menghasilkan <em>error </em>yang lebih kecil dibandingkan dengan <em>error</em> hasil verifikasi nilai <em>reflectivity</em>. Hal tersebut menunjukan bahwa model WRF-ARW masih kurang akurat dalam memodelkan data <em>reflectivity</em><em>.</em></p>
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