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Article

Evaluation of TIGGE Precipitation Forecast and Its Applicability in Streamflow Predictions over a Mountain River Basin, China

by 1, 1,2,3,*, 4, 1 and 1
1
Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, China Meteorological Administration, Wuhan 430205, China
2
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China
3
Three Gorges National Climatological Observatory, Yichang 443099, China
4
Wuhan Central Meteorological Observatory, Hubei Meteorological Service, Wuhan 430074, China
*
Author to whom correspondence should be addressed.
Academic Editors: Xushu Wu, Jiabo Yin and Shengzhi Huang
Water 2022, 14(15), 2432; https://doi.org/10.3390/w14152432
Received: 29 June 2022 / Revised: 1 August 2022 / Accepted: 2 August 2022 / Published: 5 August 2022
The number of numerical weather prediction (NWP) models is on the rise, and they are commonly used for ensemble precipitation forecast (EPF) and ensemble streamflow prediction (ESP). This study evaluated the reliabilities of two well-behaved NWP centers in the Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE), the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP), in EPF and ESP over a mountain river basin in China. This evaluation was carried out based on both deterministic and probabilistic metrics at a daily temporal scale. The effectiveness of two postprocessing methods, the Generator-based Postprocessing (GPP) method, and the Bayesian Model Averaging (BMA) method were also investigated for EPF and ESP. Results showed that: (1) The ECMWF shows better performances than NCEP in both EPF and ESP in terms of evaluation indexes and representation of the hydrograph. (2) The GPP method performs better than BMA in improving both EPF and ESP performances, and the improvements are more significant for the NCEP with worse raw performances. (3) Both ECMWF and NCEP have good potential for both EPF and ESP. By using the GPP method, there are desirable EPF performances for both ECMWF and NCEP at all 7 lead days, as well as highly skillful ECMWF ESP for 1~5 lead days and average moderate skillful NCEP ESP for all 7 lead days. The results of this study can provide a reference for the applications of TIGGE over mountain river basins. View Full-Text
Keywords: TIGGE; ensemble precipitation forecast (EPF); postprocess; ensemble streamflow prediction (ESP); mountainous river basin TIGGE; ensemble precipitation forecast (EPF); postprocess; ensemble streamflow prediction (ESP); mountainous river basin
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MDPI and ACS Style

Xiang, Y.; Peng, T.; Gao, Q.; Shen, T.; Qi, H. Evaluation of TIGGE Precipitation Forecast and Its Applicability in Streamflow Predictions over a Mountain River Basin, China. Water 2022, 14, 2432. https://doi.org/10.3390/w14152432

AMA Style

Xiang Y, Peng T, Gao Q, Shen T, Qi H. Evaluation of TIGGE Precipitation Forecast and Its Applicability in Streamflow Predictions over a Mountain River Basin, China. Water. 2022; 14(15):2432. https://doi.org/10.3390/w14152432

Chicago/Turabian Style

Xiang, Yiheng, Tao Peng, Qi Gao, Tieyuan Shen, and Haixia Qi. 2022. "Evaluation of TIGGE Precipitation Forecast and Its Applicability in Streamflow Predictions over a Mountain River Basin, China" Water 14, no. 15: 2432. https://doi.org/10.3390/w14152432

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