Evaluation and Comparison of Global Ensemble Prediction Systems for Probabilistic Forecasting of Heavy Rainfalls (Case Study: Kan Basin, Iran)

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GOODARZI LEILA; BANIHABIB MOHAMMAD EBRAHIM; GHAFARIAN PARVIN; ROOZBAHANI ABBAS

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Journal: Physical Geography Research Year:2018 | Volume:50 | Issue:1 Page(s): 29-30

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Information Journal Paper

Title

Evaluation and Comparison of Global Ensemble Prediction Systems for Probabilistic Forecasting of Heavy Rainfalls (Case Study: Kan Basin, Iran)

Author(s)

GOODARZI LEILA | BANIHABIB MOHAMMAD EBRAHIM | GHAFARIAN PARVIN | ROOZBAHANI ABBAS | Issue Writer Certificate

Keywords

Ensemble Prediction Systems (EPS)Q1

heavy rainfallQ1

Kan BasinQ1

uncertaintyQ1

Abstract

Introduction: heavy rainfalls in small basins can lead to devastating flash flood with fatalities and tremendous damages. Thus, forecasting of heavy rainfall is an important step in development of a flood warning system. Various models were used for rainfall forecasting such as artificial neural network (Moustris et al. 2011), time series models (Sapmson et al, 2013), wavelet theory (Partal and Kiş i, 2007), and regression tree model (Fallahi et al, 2011). In recent decades, the Numerical Weather Prediction (NWP) models were widely applied for weather prediction. Numerical weather predictions (NWPs) usually have uncertainties in initial conditions and model structures. In recent decades, Ensemble Prediction Systems (EPS) have been increasingly used to capture the uncertainties in NWPs. Several operational centers, including the European Centre for Medium-Range Weather Forecasts (ECMWF), the National Centers for Environmental Prediction (NCEP), the Japan Meteorological Agency (JMA), and the United Kingdom Meteorological Office (UKMO) offer valuable operational numerical predictions at a global scale (Hsiao et al, 2013)...

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APA: Copy

GOODARZI, LEILA, BANIHABIB, MOHAMMAD EBRAHIM, GHAFARIAN, PARVIN, & ROOZBAHANI, ABBAS. (2018). Evaluation and Comparison of Global Ensemble Prediction Systems for Probabilistic Forecasting of Heavy Rainfalls (Case Study: Kan Basin, Iran). PHYSICAL GEOGRAPHY RESEARCH QUARTERLY, 50(1 ), 29-30. SID. https://sid.ir/paper/368199/en

Vancouver: Copy

GOODARZI LEILA, BANIHABIB MOHAMMAD EBRAHIM, GHAFARIAN PARVIN, ROOZBAHANI ABBAS. Evaluation and Comparison of Global Ensemble Prediction Systems for Probabilistic Forecasting of Heavy Rainfalls (Case Study: Kan Basin, Iran). PHYSICAL GEOGRAPHY RESEARCH QUARTERLY[Internet]. 2018;50(1 ):29-30. Available from: https://sid.ir/paper/368199/en

IEEE: Copy

LEILA GOODARZI, MOHAMMAD EBRAHIM BANIHABIB, PARVIN GHAFARIAN, and ABBAS ROOZBAHANI, “Evaluation and Comparison of Global Ensemble Prediction Systems for Probabilistic Forecasting of Heavy Rainfalls (Case Study: Kan Basin, Iran),” PHYSICAL GEOGRAPHY RESEARCH QUARTERLY, vol. 50, no. 1 , pp. 29–30, 2018, [Online]. Available: https://sid.ir/paper/368199/en

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