Developing a dynamic-statistical downscaling framework for wind speed prediction for the Beijing 2022 Winter olympics
- 4 June 2024
- journal article
- research article
- Published by Springer Nature in Climate Dynamics
- Vol. 62 (8) , 7345-7363
Abstract
No abstract availableKeywords
Funding Information
- National Key Research and Development Program of China (2020YFF0304401, 2021YFE0113800)
This publication has 40 references indexed in Scilit:
- Short-term wind speed prediction using hybrid machine learning techniquesEnvironmental Science and Pollution Research, 2021
- An Experiment on the Prediction of the Surface Wind Speed in Chongli Based on the WRF Model: Evaluation and CalibrationAdvances in Atmospheric Sciences, 2021
- Comparison of ERA5 surface wind speed climatologies over Europe with observations from the HadISD datasetInternational Journal of Climatology, 2021
- Using Machine-Learning Methods to Improve Surface Wind Speed from the Outputs of a Numerical Weather Prediction ModelBoundary-Layer Meteorology, 2021
- Near-surface mean and gust wind speeds in ERA5 across Sweden: towards an improved gust parametrizationClimate Dynamics, 2020
- Gridded probabilistic weather forecasts with an analog ensembleQuarterly Journal of the Royal Meteorological Society, 2017
- Statistical downscaling and dynamical downscaling of regional climate in China: Present climate evaluations and future climate projectionsJournal of Geophysical Research: Atmospheres, 2016
- Statistical downscaling of general circulation model outputs to precipitation—part 1: calibration and validationInternational Journal of Climatology, 2014
- Statistical downscaling of daily mean temperature, pan evaporation and precipitation for climate change scenarios in Haihe River, ChinaTheoretical and Applied Climatology, 2009
- Statistical and dynamical downscaling of the Seine basin climate for hydro‐meteorological studiesInternational Journal of Climatology, 2007