TINGKAT KESESUAIAN OUTPUT WRF TERHADAP DATA OGIMET PADA KASUS CURAH HUJAN DI DAERAH PALEMBANG

NOVISHA, BELLA and Arsali, Arsali and Ariani, Menik (2018) TINGKAT KESESUAIAN OUTPUT WRF TERHADAP DATA OGIMET PADA KASUS CURAH HUJAN DI DAERAH PALEMBANG. Undergraduate thesis, Sriwijaya University.

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Abstract

WRF (Weather Research And Forecasting) is the one of mesoscale generation numerical weather prediction models that predict the weather by describing the atmospheric conditions and expected to make good weather predictions, flexible and easy to understand. WRF is built on the Ubuntu linux operating system 16.04 LTS with the input data is Global Forecast System (GFS), the range of time from 01 to 31 December 2017 for rainfall parameters. This study uses 3 domains, the first domain is Sumatra Island, then the second domain is South Sumatra and the thrid domain is Palembang City. The visualization used observation points of Sriwijaya University (UNSRI), Climatology Station in Kenten (Kenten), Sulthan Mahmud Badaruddin II Airport (SMB II) and Bina Darma University (UBD). In order to be used for daily weather prediction purposes, there needs to be a suitability test to determine the level of output accuracy produced by WRF and in this study the WRF output is compared with Ogimet's data for the SMB II observation point and found that WRF has not been able to predict rainfall with either because the bias, accuracy and threat score is less than 1 and the false alarm value is less than 0. However for probability of detection has been considered good because the value obtained is more than 1.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: WRF Output , Rainfall, Ogimet’s Data, The Suitability
Subjects: Q Science > QC Physics > QC980-999 Climatology and weather
Q Science > QC Physics > QC994.95-999 Weather forecasting
Divisions: 08-Faculty of Mathematics and Natural Science > 45201-Physics (S1)
Depositing User: Mrs Dies Meirita Sari
Date Deposited: 14 Aug 2019 07:28
Last Modified: 14 Aug 2019 07:28
URI: http://repository.unsri.ac.id/id/eprint/4323

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