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Abstract
A probabilistic precipitation forecasting model using generalized additive models (GAMs) and Bayesian
model averaging (BMA) was proposed in this paper. GAMs were used to fit the spatial-temporal precipitation
models to individual ensemble member forecasts. The distributions of the precipitation occurrence and the
cumulative precipitation amount were represented simultaneously by a single Tweedie distribution. BMA was
then used as a post-processing method to combine the individual models to form a more skillful probabilistic
forecasting model. The mixing weights were estimated using the expectation-maximization algorithm. The
residual diagnostics was used to examine if the fitted BMA forecasting model had fully captured the spatial
and temporal variations of precipitation. The proposed method was applied to daily observations at the
Yishusi River basin for July 2007 using the National Centers for Environmental Prediction ensemble forecasts.
By applying scoring rules, the BMA forecasts were verified and showed better performances compared
with the empirical probabilistic ensemble forecasts, particularly for extreme precipitation. Finally, possible
improvements and application of this method to the downscaling of climate change scenarios were discussed.
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Citation
YANG Chi, YAN Zhongwei, SHAO Yuehong. 2012: Probabilistic Precipitation Forecasting Based on Ensemble Output Using Generalized Additive Models and Bayesian Model Averaging. Journal of Meteorological Research, 26(1): 1-12. DOI: 10.1007/s13351-012-0101-8
YANG Chi, YAN Zhongwei, SHAO Yuehong. 2012: Probabilistic Precipitation Forecasting Based on Ensemble Output Using Generalized Additive Models and Bayesian Model Averaging. Journal of Meteorological Research, 26(1): 1-12. DOI: 10.1007/s13351-012-0101-8
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YANG Chi, YAN Zhongwei, SHAO Yuehong. 2012: Probabilistic Precipitation Forecasting Based on Ensemble Output Using Generalized Additive Models and Bayesian Model Averaging. Journal of Meteorological Research, 26(1): 1-12. DOI: 10.1007/s13351-012-0101-8
YANG Chi, YAN Zhongwei, SHAO Yuehong. 2012: Probabilistic Precipitation Forecasting Based on Ensemble Output Using Generalized Additive Models and Bayesian Model Averaging. Journal of Meteorological Research, 26(1): 1-12. DOI: 10.1007/s13351-012-0101-8
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