Articles | Volume 24, issue 1
https://doi.org/10.5194/hess-24-1-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-1-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Jan 2020
Research article |
| 03 Jan 2020
| 03 Jan 2020
Significant spatial patterns from the GCM seasonal forecasts of global precipitation
Tongtiegang Zhao
CORRESPONDING AUTHOR
Center of Water Resources and Environment, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Civil Engineering, Sun Yat-Sen University, Guangzhou, 510275, China
Wei Zhang
IIHR-Hydroscience & Engineering, University of Iowa, Iowa City,
52242, USA
Yongyong Zhang
Key Laboratory of Water Cycle and Related Land Surface Processes,
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
Zhiyong Liu
Center of Water Resources and Environment, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Civil Engineering, Sun Yat-Sen University, Guangzhou, 510275, China
Xiaohong Chen
CORRESPONDING AUTHOR
Center of Water Resources and Environment, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Civil Engineering, Sun Yat-Sen University, Guangzhou, 510275, China
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Cited
20 citations as recorded by crossref.
- A five-parameter Gamma-Gaussian model to calibrate monthly and seasonal GCM precipitation forecasts Z. Huang et al. https://doi.org/10.1016/j.jhydrol.2021.126893
- Correspondence relationship between ENSO teleconnection and anomaly correlation for GCM seasonal precipitation forecasts T. Zhao et al. https://doi.org/10.1007/s00382-021-05925-3
- Coupling coordination and spatiotemporal dynamic evolution between urbanization and geological hazards–A case study from China Z. Zhang & Y. Li https://doi.org/10.1016/j.scitotenv.2020.138825
- Midwinter Dry Spells Amplify Post‐Fire Snowpack Decline B. Hatchett et al. https://doi.org/10.1029/2022GL101235
- Improving seasonal precipitation forecasts in the Western United States through statistical downscaling B. Vernon et al. https://doi.org/10.1088/1748-9326/add02c
- Evaluating variogram models and kriging approaches for analyzing spatial trends in precipitation simulations from global climate models A. Batool et al. https://doi.org/10.1007/s11600-025-01545-1
- Research on the Spatio-Temporal Dynamic Evolution Characteristics and Influencing Factors of Electrical Power Consumption in Three Urban Agglomerations of Yangtze River Economic Belt, China Based on DMSP/OLS Night Light Data Y. Zhong et al. https://doi.org/10.3390/rs13061150
- Application-specific optimal model weighting of global climate models: A red tide example A. Elshall et al. https://doi.org/10.1016/j.cliser.2022.100334
- The Severity of the 2014–2015 Snow Drought in the Oregon Cascades in a Multicentury Context L. Dye et al. https://doi.org/10.1029/2022WR032875
- Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province M. Nejadrekabi et al. https://doi.org/10.1007/s13762-021-03852-8
- A physical-based two-source evapotranspiration model with Monin–Obukhov similarity theory M. Khan et al. https://doi.org/10.1080/15481603.2020.1857625
- Determination of water required to recover from hydrological drought: Perspective from drought propagation and non-standardized indices J. Wu et al. https://doi.org/10.1016/j.jhydrol.2020.125227
- A global-drive analysis of ecosystem respiration in the Arctic and Third Pole X. Ma et al. https://doi.org/10.1016/j.ecolind.2022.109668
- Detection of spatial and temporal precipitation patterns using remotely sensed data in the Paranapanema River Basin, Brazil from 2000 to 2021 R. Manzione https://doi.org/10.1007/s43832-023-00035-z
- Attributing correlation skill of dynamical GCM precipitation forecasts to statistical ENSO teleconnection using a set-theory-based approach T. Zhao et al. https://doi.org/10.5194/hess-25-5717-2021
- Book Recommendation System using Machine learning and Collaborative Filtering . Ashlesha Bachhav et al. https://doi.org/10.48175/IJARSCT-7687
- Skill decreases in real-time seasonal climate prediction due to decadal variability C. Shao et al. https://doi.org/10.1007/s00382-023-06800-z
- Enhancing daily runoff forecasting with a dual-domain deep learning model W. Wang et al. https://doi.org/10.1016/j.asoc.2026.115537
- Spatial association of anomaly correlation for GCM seasonal forecasts of global precipitation T. Zhao et al. https://doi.org/10.1007/s00382-020-05384-2
- Evaluating interannual variability in 1-month CFSv2 forecasts with different lead times at monthly and daily scales in South Korea S. Ha et al. https://doi.org/10.1088/2515-7620/adcdcf
20 citations as recorded by crossref.
- A five-parameter Gamma-Gaussian model to calibrate monthly and seasonal GCM precipitation forecasts Z. Huang et al. https://doi.org/10.1016/j.jhydrol.2021.126893
- Correspondence relationship between ENSO teleconnection and anomaly correlation for GCM seasonal precipitation forecasts T. Zhao et al. https://doi.org/10.1007/s00382-021-05925-3
- Coupling coordination and spatiotemporal dynamic evolution between urbanization and geological hazards–A case study from China Z. Zhang & Y. Li https://doi.org/10.1016/j.scitotenv.2020.138825
- Midwinter Dry Spells Amplify Post‐Fire Snowpack Decline B. Hatchett et al. https://doi.org/10.1029/2022GL101235
- Improving seasonal precipitation forecasts in the Western United States through statistical downscaling B. Vernon et al. https://doi.org/10.1088/1748-9326/add02c
- Evaluating variogram models and kriging approaches for analyzing spatial trends in precipitation simulations from global climate models A. Batool et al. https://doi.org/10.1007/s11600-025-01545-1
- Research on the Spatio-Temporal Dynamic Evolution Characteristics and Influencing Factors of Electrical Power Consumption in Three Urban Agglomerations of Yangtze River Economic Belt, China Based on DMSP/OLS Night Light Data Y. Zhong et al. https://doi.org/10.3390/rs13061150
- Application-specific optimal model weighting of global climate models: A red tide example A. Elshall et al. https://doi.org/10.1016/j.cliser.2022.100334
- The Severity of the 2014–2015 Snow Drought in the Oregon Cascades in a Multicentury Context L. Dye et al. https://doi.org/10.1029/2022WR032875
- Spatial statistics techniques for SPEI and NDVI drought indices: a case study of Khuzestan Province M. Nejadrekabi et al. https://doi.org/10.1007/s13762-021-03852-8
- A physical-based two-source evapotranspiration model with Monin–Obukhov similarity theory M. Khan et al. https://doi.org/10.1080/15481603.2020.1857625
- Determination of water required to recover from hydrological drought: Perspective from drought propagation and non-standardized indices J. Wu et al. https://doi.org/10.1016/j.jhydrol.2020.125227
- A global-drive analysis of ecosystem respiration in the Arctic and Third Pole X. Ma et al. https://doi.org/10.1016/j.ecolind.2022.109668
- Detection of spatial and temporal precipitation patterns using remotely sensed data in the Paranapanema River Basin, Brazil from 2000 to 2021 R. Manzione https://doi.org/10.1007/s43832-023-00035-z
- Attributing correlation skill of dynamical GCM precipitation forecasts to statistical ENSO teleconnection using a set-theory-based approach T. Zhao et al. https://doi.org/10.5194/hess-25-5717-2021
- Book Recommendation System using Machine learning and Collaborative Filtering . Ashlesha Bachhav et al. https://doi.org/10.48175/IJARSCT-7687
- Skill decreases in real-time seasonal climate prediction due to decadal variability C. Shao et al. https://doi.org/10.1007/s00382-023-06800-z
- Enhancing daily runoff forecasting with a dual-domain deep learning model W. Wang et al. https://doi.org/10.1016/j.asoc.2026.115537
- Spatial association of anomaly correlation for GCM seasonal forecasts of global precipitation T. Zhao et al. https://doi.org/10.1007/s00382-020-05384-2
- Evaluating interannual variability in 1-month CFSv2 forecasts with different lead times at monthly and daily scales in South Korea S. Ha et al. https://doi.org/10.1088/2515-7620/adcdcf
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