Articles | Volume 21, issue 3
https://doi.org/10.5194/hess-21-1477-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/hess-21-1477-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
CFSv2-based sub-seasonal precipitation and temperature forecast skill over the contiguous United States
Department of Civil and Environmental Engineering, Princeton
University, Princeton, New Jersey 08544, USA
Department of Crop, Soil, and Environmental Sciences, Auburn
University, Auburn, Alabama 36849, USA
Eric F. Wood
Department of Civil and Environmental Engineering, Princeton
University, Princeton, New Jersey 08544, USA
Xing Yuan
CAS Key Laboratory of Regional Climate-Environment for Temperate East
Asia (RCE-TEA), Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
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Latest update: 15 Nov 2024
Short summary
This study evaluated dynamic climate model sub-seasonal forecasts for important precipitation and temperature indices over the contiguous United States. The presence of active Madden-Julian Oscillation (MJO) events improved weekly mean precipitation forecast skill over most regions. Sub-seasonal forecast indices calculated from the daily forecast showed higher skill than temporally downscaled forecasts, suggesting the usefulness of the daily forecast for sub-seasonal hydrological forecasting.
This study evaluated dynamic climate model sub-seasonal forecasts for important precipitation...
Special issue