Articles | Volume 7, issue 5
https://doi.org/10.5194/gmd-7-2333-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-7-2333-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Multi-model ensemble: technique and validation
J. R. Rozante
Center for Weather Forecasting and Climate Studies, INPE, Cachoeira Paulista, SP, Brazil
D. S. Moreira
Center for Weather Forecasting and Climate Studies, INPE, Cachoeira Paulista, SP, Brazil
R. C. M. Godoy
Center for Weather Forecasting and Climate Studies, INPE, Cachoeira Paulista, SP, Brazil
A. A. Fernandes
Center for Weather Forecasting and Climate Studies, INPE, Cachoeira Paulista, SP, Brazil
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19 citations as recorded by crossref.
- Evaluation of subseasonal precipitation forecasts in the Uruguay River basin J. Badagian et al. 10.1002/joc.8634
- Subseasonal Forecast of Surface Air Temperature Using Superensemble Approaches: Experiments over Northeast Asia for 2018 S. Zhu et al. 10.1175/WAF-D-20-0096.1
- Prescreening-Based Subset Selection for Improving Predictions of Earth System Models With Application to Regional Prediction of Red Tide A. Elshall et al. 10.3389/feart.2022.786223
- High-resolution ensemble projections and uncertainty assessment of regional climate change over China in CORDEX East Asia H. Gu et al. 10.5194/hess-22-3087-2018
- Current and future potential of solar and wind energy over Africa using the RegCM4 CORDEX-CORE ensemble W. Sawadogo et al. 10.1007/s00382-020-05377-1
- Multi-Model Ensemble Prediction of Summer Precipitation in China Based on Machine Learning Algorithms J. Yang et al. 10.3390/atmos13091424
- Improving the skill of medium range ensemble rainfall forecasts over India using MoES grand ensemble (MGE)-part-I A. Dube et al. 10.1007/s00703-024-01035-x
- Multi-output Deep Learning for Bus Arrival Time Predictions N. Petersen et al. 10.1016/j.trpro.2019.09.025
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- Assessing the coastal hazard of Medicane Ianos through ensemble modelling C. Ferrarin et al. 10.5194/nhess-23-2273-2023
- Improved forecasting of thermospheric densities using multi-model ensembles S. Elvidge et al. 10.5194/gmd-9-2279-2016
- Improving Estuarine Hydrodynamic Forecasts Through Numerical Model Ensembles I. Iglesias et al. 10.3389/fmars.2022.812255
- Evaluation and correction of sub-seasonal dynamic model forecast of precipitation in eastern China L. Liu et al. 10.1007/s00382-023-06788-6
- Performance‐based projection of the climate‐change effects on precipitation extremes in East Asia using two metrics S. Kwon et al. 10.1002/joc.5954
- Improving the Accuracy of Rainfall Prediction Using Bias-Corrected NMME Outputs: A Case Study of Surabaya City, Indonesia D. Faidah et al. 10.1155/2022/9779829
- Multi‐Model Ensembles for Upper Atmosphere Models S. Elvidge et al. 10.1029/2022SW003356
- Two Models Solutions for the Douro Estuary: Flood Risk Assessment and Breakwater Effects I. Iglesias et al. 10.1007/s12237-018-0477-5
- Performance of State‐of‐the‐Art C3S European Seasonal Climate Forecast Models for Mean and Extreme Precipitation Over Africa S. Gebrechorkos et al. 10.1029/2021WR031480
- Applicability of Multimodel Ensemble Prediction of Heavy Precipitation for the Perm Region: A Case Study for the Summer of 2019 A. Vetrov & S. Kostarev 10.3103/S1068373921070037
2 citations as recorded by crossref.
- Improvements in precipitation simulation over South America for past and future climates via multi-model combination M. Coutinho et al. 10.1007/s00382-016-3346-6
- Performance of multi-model ensembles for the simulation of temperature variability over Ontario, Canada A. Samouly et al. 10.1007/s12665-018-7701-2
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