dc.description.abstract | Weather satellite observations are used widely for the quantitative precipitation forecast (QPF) of typhoon rainfall because they can provide relevant atmospheric parameters over both the ocean and land. Microwave observations by satellites have become the main data in forecasting tropical rainfall potential (TRaP) in a 24-h period (Kidder et al., 2005). The improved Tropical Rainfall Potential (I-TRaP) technique presented by Liu et al. in 2011 is a useful method for typhoon quantitative precipitation estimation and a powerful tool for rain-band monitoring before the typhoon makes landfall in Taiwan.
However, the method only provides single prediction which may pose a difficulty when using single sensor or time segment data. To smooth the random error made by single forecast and quantify the uncertainties in prediction, this study seeks to adopt ensemble forecasts to help to provide more reliable predictions. In other words, the goal of this study is to construct a new ensemble I-TRaP technique for typhoon rainfall potential. Besides that, to consider about different rainfall types within a typhoon, the rain-band of a typhoon is separated into two parts: inner rain-band (circulation affected rainfall) and outer rain-band (terrain affected rainfall). This study again constructed another ensemble potential model called the Ensemble I-TRaP B model (“B” stands for “bi-types”), to consider the two rainfall types. Then, the results including that the performances of both ensemble methods in 24-h QPE and the ability of forecasts for different time periods are investigated.
There are 77 typhoons from 2001 to 2012 used for long term statistics. Comparing to the I-TRaP model, the ensemble technique (i.e. Ensemble I-TRaP model), and the new model which additionally considering the two rainfall types (i.e. Ensemble I-TRaP B models) can both promote the correlation coefficient from 0.53 to 0.62, and decrease root-mean-square from 81.68 mm to 64.05 mm and to 63.76 mm respectively. It shows that this ensemble technique is useful for improving the rainfall pattern estimation in short accumulated periods, and moreover, it did better forecasting in long periods with a higher correlation coefficient. The results suggest that using the ensemble technique may improve I-TRaP, and considering rainfall types can again promote the rainfall amount prediction. | en_US |