Temperature and Humidity Forecast via Univariate Partial Least Square and Principal Component Analysis
DOI:
https://doi.org/10.22452/mjs.sp2019no2.1Keywords:
MOS; NWP; PCA; PLS; Temperature and HumidityAbstract
Indonesian Meteorology, Climatology, and Geophysics (BMKG) uses Numerical Weather Prediction (NWP) for short-term weather forecast but gives bias result. Therefore, this study implements Model Output Statistics (MOS) for temperature and humidity forecast. This study using maximum temperature (Tmax), minimum temperature (Tmin), and humidity (RH) which are called response variables and NWP is predictor variable. The results show that the performance of the prediction model is considered to be good and intermediate criteria, i.e. Tmax in all stations has intermediate, Tmin in three stations is good, and humidity in three stations is also good. The best Percentage Improval (%IM) is obtained in Tmin because PLS is able to correct 89.94% of biased NWP.
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