TY  - JOUR
T1  - Use of NWP Model Products and Metsat Images Data for
Quantitative Precipitation Forecast
AU - Tahir, Wardah AU - Kamil Aminuddin, Ahmad AU - Shafeenar Ahmad Mohtar, Intan 
JO  - Journal of Engineering and Applied Sciences
VL  - 12
IS  - 9
SP  - 2248
EP  - 2253
PY  - 2017
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2017.2248.2253
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2017.2248.2253
KW  - Numerical Weather Prediction (NWP)
KW  -Quantitative Precipitation Forecast (QPF)
KW  -geostationary Meteorological Satellite (METSAT)
KW  -model products
KW  -tropical region
AB  - Quantitative Precipitation Forecast (QPF) from Numerical Weather Prediction (NWP) model products
combined with geostationary meteorological satellite (metsat) data as input to a flood forecasting system has
great potential to provide improved lead time for warning. In this study, a QPF Model is developed using the
artificial multilayer neural network with data inputs from selected NWP model products combined with the
metsat image features such as cloud top brightness temperature and albedo to forecast precipitation
for a flood-prone area in a tropical region. The model was used to forecast intense rainfall episodes in Kelantan
and Klang River Basins of Peninsular Malaysia. The results indicate that the model can satisfactorily produce
1h forecast with improved accuracy for larger forecast area. Performance of the model is better for Klang River
Basin with r<sup>2</sup> of 0.89 as compared to Kelantan River Basin with r<sup>2</sup> of 0.67.
ER  -