scholarly journals EVALUASI PEMETAAN POTENSI ENERGI SURYA BERBASIS MODEL WRF DI DESA PALIHAN DAN DESA AIKANGKUNG

2018 ◽  
Vol 15 (2) ◽  
pp. 63
Author(s):  
Bono Pranoto ◽  
Dian Galuh Cendrawati ◽  
Nurry Widya Hesty ◽  
Errie Kusriadie

Penggunaan model numerik Weather Research and Forecasting (WRF) untuk memprediksi potensi energi surya dapat digunakan sebagai langkah awal pemetaan. Peta hasil prediksi WRF perlu diverifikasi guna meningkatkan kualitas data. Dalam penelitian ini, digunakan data WRF dengan rentang tahun 2001 hingga 2010. Untuk verifikasi digunakan data observasi radiasi matahari selama 12 bulan pada 2 lokasi yaitu desa Palihan (Provinsi Yogjakarta) dan desa Aikangkung (Provinsi Nusa Tenggara Barat). Metoda yang digunakan adalah penurunan skala (downscaling), prediksi, verifikasi dan koreksi. Hasil verifikasi memperlihatkan lokasi 1 (desa Palihan) memiliki deviasi yang lebih besar (Mape=22.59%) dibanding pada lokasi 2 (desa Aikangkung) dengan nilai Mape=12.95%. Perbedaan nilai antara model WRF dan data observasi dimanfaatkan untuk mengkoreksi peta potensi energi surya. Hasil peta yang telah terkoreksi, memiliki nilai Mape = 0.0007% untuk desa Palihan dan 7% untuk desa Aikangkung.  

2019 ◽  
Vol 3 ◽  
pp. 1063
Author(s):  
Fatkhuroyan Fatkhuroyan

Satelit GPM (Global Precipitation Measurement) merupakan proyek kerjasama antara NASA (National Aeronautics and Space Administration) dan JAXA (Japan Aerospace Exploration Agency) serta lembaga internasional lainnya untuk membuat satelit generasi terbaru dalam rangka pengamatan curah hujan di bumi sejak 2014. Model Cuaca WRF (Weather Research and Forecasting) merupakan model cuaca numerik yang telah dipakai oleh BMKG (Badan Meteorologi Klimatologi dan Geofisika) untuk pelayan prediksi cuaca harian kepada masyarakat. Pada tanggal 27 November – 3 Desember 2017 telah terjadi bencana alam siklon tropis Cempaka dan Dahlia di samudra Hindia sebelah selatan pulau Jawa. Tujuan Penelitian ialah untuk mengetahui sebaran akumulasi curah hujan antara observasi satelit GPM dan model cuaca WRF, serta keakuratan model WRF terhadap observasi satelit GPM saat terjadinya bencana alam tersebut. Metode yang dipakai ialah dengan melakukan analisa meteorologi pertumbuhan terjadinya siklon tropis tersebut hingga terjadinya hujan sangat lebat secara temporal maupun spasial. Dari hasil analisa disimpulkan bahwa satelit GPM memiliki luasan sebaran curah hujan yang lebih kecil daripada sebaran hujan model cuaca WRF pada saat siklon tropis Cempaka dan Dahlia. Bias akumulasi sebaran hujan model cuaca WRF juga cukup bagus terhadap satelit GPM sehingga dapat dilakukan antisipasi dampak hujan lebat yang terjadi.


Author(s):  
Alessio Golzio ◽  
Silvia Ferrarese ◽  
Claudio Cassardo ◽  
Gugliemina Adele Diolaiuti ◽  
Manuela Pelfini

AbstractWeather forecasts over mountainous terrain are challenging due to the complex topography that is necessarily smoothed by actual local-area models. As complex mountainous territories represent 20% of the Earth’s surface, accurate forecasts and the numerical resolution of the interaction between the surface and the atmospheric boundary layer are crucial. We present an assessment of the Weather Research and Forecasting model with two different grid spacings (1 km and 0.5 km), using two topography datasets (NASA Shuttle Radar Topography Mission and Global Multi-resolution Terrain Elevation Data 2010, digital elevation models) and four land-cover-description datasets (Corine Land Cover, U.S. Geological Survey land-use, MODIS30 and MODIS15, Moderate Resolution Imaging Spectroradiometer land-use). We investigate the Ortles Cevadale region in the Rhaetian Alps (central Italian Alps), focusing on the upper Forni Glacier proglacial area, where a micrometeorological station operated from 28 August to 11 September 2017. The simulation outputs are compared with observations at this micrometeorological station and four other weather stations distributed around the Forni Glacier with respect to the latent heat, sensible heat and ground heat fluxes, mixing-layer height, soil moisture, 2-m air temperature, and 10-m wind speed. The different model runs make it possible to isolate the contributions of land use, topography, grid spacing, and boundary-layer parametrizations. Among the considered factors, land use proves to have the most significant impact on results.


2015 ◽  
Vol 156 ◽  
pp. 1-13 ◽  
Author(s):  
Theodore M. Giannaros ◽  
Vassiliki Kotroni ◽  
Konstantinos Lagouvardos

2014 ◽  
Vol 31 (9) ◽  
pp. 2008-2014 ◽  
Author(s):  
Xin Zhang ◽  
Ying-Hwa Kuo ◽  
Shu-Ya Chen ◽  
Xiang-Yu Huang ◽  
Ling-Feng Hsiao

Abstract The nonlocal excess phase observation operator for assimilating the global positioning system (GPS) radio occultation (RO) sounding data has been proven by some research papers to produce significantly better analyses for numerical weather prediction (NWP) compared to the local refractivity observation operator. However, the high computational cost and the difficulties in parallelization associated with the nonlocal GPS RO operator deter its application in research and operational NWP practices. In this article, two strategies are designed and implemented in the data assimilation system for the Weather Research and Forecasting Model to demonstrate the capability of parallel assimilation of GPS RO profiles with the nonlocal excess phase observation operator. In particular, to solve the parallel load imbalance problem due to the uneven geographic distribution of the GPS RO observations, round-robin scheduling is adopted to distribute GPS RO observations among the processing cores to balance the workload. The wall clock time required to complete a five-iteration minimization on a demonstration Antarctic case with 106 GPS RO observations is reduced from more than 3.5 h with a single processing core to 2.5 min with 106 processing cores. These strategies present the possibility of application of the nonlocal GPS RO excess phase observation operator in operational data assimilation systems with a cutoff time limit.


Author(s):  
Reneta Dimitrova ◽  
Ashish Sharma ◽  
Harindra J. S. Fernando ◽  
Ismail Gultepe ◽  
Ventsislav Danchovski ◽  
...  

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