Integration of Climate and Weather Information for Improving 15-Day-Ahead Accumulated Precipitation Forecasts

Skillful medium-range weather forecasts are critical for water resources planning and management. This study aims to improve 15-day-ahead accumulated precipitation forecasts by combining biweekly weather and disaggregated climate forecasts. A combination scheme is developed to combine reforecasts fr...

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Bibliographic Details
Published in:Journal of hydrometeorology 2013-02, Vol.14 (1), p.186-202
Main Authors: Wang, Hui, Sankarasubramanian, A., Ranjithan, Ranji S.
Format: Article
Language:English
Subjects:
Climate models
Employment forecasting
Forecasting models
Numerical weather forecasting
Point forecasts
Precipitation
Probability forecasts
Time series forecasting
Weather
Weather forecasting
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Summary:Skillful medium-range weather forecasts are critical for water resources planning and management. This study aims to improve 15-day-ahead accumulated precipitation forecasts by combining biweekly weather and disaggregated climate forecasts. A combination scheme is developed to combine reforecasts from a numerical weather model and disaggregated climate forecasts from ECHAM4.5 for developing 15-day-ahead precipitation forecasts. Evaluation of the skill of the weather–climate information (WCI)-based biweekly forecasts under leave-five-out cross validation shows that WCI-based forecasts perform better than reforecasts in many grid points over the continental United States. Correlation between rank probability skill score (RPSS) and disaggregated ECHAM4.5 forecast errors reveals that the lower the error in the disaggregated forecasts, the better the performance of WCI forecasts. Weights analysis from the combination scheme also shows that the biweekly WCI forecasts perform better by assigning higher weights to the better-performing candidate forecasts (reforecasts or disaggregated ECHAM4.5 forecasts). Particularly, WCI forecasts perform better during the summer months during which reforecasts have limited skill. Even though the disaggregated climate forecasts do not perform well over many grid points, the primary reason WCI-based forecasts perform better than the reforecasts is due to the reduction in the overconfidence of the reforecasts. Since the disaggregated climate forecasts are better dispersed than the reforecasts, combining them with reforecasts results in reduced uncertainty in predicting the 15-day-ahead accumulated precipitation.
ISSN:1525-755X
1525-7541
DOI:10.1175/JHM-D-11-0128.1