Articles | Volume 13, issue 4
https://doi.org/10.5194/esd-13-1451-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-13-1451-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Exploring the relationship between temperature forecast errors and Earth system variables
Melissa Ruiz-Vásquez
CORRESPONDING AUTHOR
Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
Friedrich Schiller University Jena, Department of Geography, Jena, Germany
Sungmin O
Department of Climate and Energy System Engineering, Ewha Womans University, Seoul, South Korea
Alexander Brenning
Friedrich Schiller University Jena, Department of Geography, Jena, Germany
Randal D. Koster
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Gianpaolo Balsamo
Research Department, European Centre for Medium-Range Weather Forecasts, Reading, UK
Ulrich Weber
Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
Gabriele Arduini
Research Department, European Centre for Medium-Range Weather Forecasts, Reading, UK
Ana Bastos
Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
Markus Reichstein
Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
René Orth
Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
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Cited
9 citations as recorded by crossref.
- State-of-the-art hydrological datasets exhibit low water balance consistency globally H. Huang et al. https://doi.org/10.5194/essd-18-3109-2026
- Skillful subseasonal ensemble predictions of heat wave onsets through better representation of land surface uncertainties Q. Zhang et al. https://doi.org/10.1038/s41612-024-00876-y
- Impact of Uncertainties in Land Surface Processes on Subseasonal Predictability of Heat Waves Onset Over the Yangtze River Valley Q. Zhang et al. https://doi.org/10.1029/2023JD038674
- Short-, medium-, and long-term reference evapotranspiration forecasting based on intelligent temperature forecast correction and regional calibration of the Hargreaves model Z. Ma et al. https://doi.org/10.1016/j.ejrh.2026.103999
- Examining the role of biophysical feedbacks on simulated temperature extremes during the Tinderbox Drought and Black Summer bushfires in southeast Australia M. Mu et al. https://doi.org/10.1016/j.wace.2024.100703
- Land surface information from satellites boost near-surface temperature forecast skill M. Ruiz-Vásquez et al. https://doi.org/10.1038/s43247-026-03298-1
- High-Accuracy Temporal Prediction via Experimental Quantum Reservoir Computing in Correlated Spins Y. Hou et al. https://doi.org/10.1103/r8ww-qw7j
- Testing the reliability of soil moisture forecast for its use in agriculture M. Bláhová et al. https://doi.org/10.1016/j.agwat.2024.109073
- Literature survey of subseasonal‐to‐seasonal predictions in the southern hemisphere S. Phakula et al. https://doi.org/10.1002/met.2170
9 citations as recorded by crossref.
- State-of-the-art hydrological datasets exhibit low water balance consistency globally H. Huang et al. https://doi.org/10.5194/essd-18-3109-2026
- Skillful subseasonal ensemble predictions of heat wave onsets through better representation of land surface uncertainties Q. Zhang et al. https://doi.org/10.1038/s41612-024-00876-y
- Impact of Uncertainties in Land Surface Processes on Subseasonal Predictability of Heat Waves Onset Over the Yangtze River Valley Q. Zhang et al. https://doi.org/10.1029/2023JD038674
- Short-, medium-, and long-term reference evapotranspiration forecasting based on intelligent temperature forecast correction and regional calibration of the Hargreaves model Z. Ma et al. https://doi.org/10.1016/j.ejrh.2026.103999
- Examining the role of biophysical feedbacks on simulated temperature extremes during the Tinderbox Drought and Black Summer bushfires in southeast Australia M. Mu et al. https://doi.org/10.1016/j.wace.2024.100703
- Land surface information from satellites boost near-surface temperature forecast skill M. Ruiz-Vásquez et al. https://doi.org/10.1038/s43247-026-03298-1
- High-Accuracy Temporal Prediction via Experimental Quantum Reservoir Computing in Correlated Spins Y. Hou et al. https://doi.org/10.1103/r8ww-qw7j
- Testing the reliability of soil moisture forecast for its use in agriculture M. Bláhová et al. https://doi.org/10.1016/j.agwat.2024.109073
- Literature survey of subseasonal‐to‐seasonal predictions in the southern hemisphere S. Phakula et al. https://doi.org/10.1002/met.2170
Saved (final revised paper)
Latest update: 25 Oct 2026
Short summary
Subseasonal forecasts facilitate early warning of extreme events; however their predictability sources are not fully explored. We find that global temperature forecast errors in many regions are related to climate variables such as solar radiation and precipitation, as well as land surface variables such as soil moisture and evaporative fraction. A better representation of these variables in the forecasting and data assimilation systems can support the accuracy of temperature forecasts.
Subseasonal forecasts facilitate early warning of extreme events; however their predictability...
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