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Aaron Spring
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Current and emerging developments in subseasonal to decadal prediction
WJ Merryfield, J Baehr, L Batté, EJ Becker, AH Butler, CAS Coelho, ...
Bulletin of the American Meteorological Society 101 (6), E869-E896, 2020
2012020
Predictable Variations of the Carbon Sinks and Atmospheric CO2 Growth in a Multi‐Model Framework
T Ilyina, H Li, A Spring, WA Müller, L Bopp, MO Chikamoto, ...
Geophysical Research Letters 48 (6), e2020GL090695, 2021
282021
Outcomes of the wmo prize challenge to improve subseasonal to seasonal predictions using artificial intelligence
F Vitart, AW Robertson, A Spring, F Pinault, R Roškar, W Cao, S Bech, ...
Bulletin of the American Meteorological Society 103 (12), E2878-E2886, 2022
272022
Predictability horizons in the global carbon cycle inferred from a perfect‐model framework
A Spring, T Ilyina
Geophysical Research Letters 47 (9), e2019GL085311, 2020
222020
Inherent uncertainty disguises attribution of reduced atmospheric CO2 growth to CO2 emission reductions for up to a decade
A Spring, T Ilyina, J Marotzke
Environmental Research Letters 15 (11), 114058, 2020
182020
climpred: Verification of weather and climate forecasts
RX Brady, A Spring
The Journal of Open Source Software 6 (59), 2021
152021
Trivial improvements in predictive skill due to direct reconstruction of the global carbon cycle
A Spring, I Dunkl, H Li, V Brovkin, T Ilyina
Earth System Dynamics 12 (4), 1139-1167, 2021
72021
Process-based analysis of terrestrial carbon flux predictability
I Dunkl, A Spring, P Friedlingstein, V Brovkin
Earth System Dynamics 12 (4), 1413-1426, 2021
62021
Reconstructions and predictions of the global carbon budget with an emission-driven Earth system model
H Li, T Ilyina, T Loughran, A Spring, J Pongratz
Earth System Dynamics 14 (1), 101-119, 2023
42023
Reconstructions and predictions of the global carbon budget with an emission-driven earth system model
H Li, T Ilyina, T Loughran, A Spring, J Pongratz
Earth System Dynamics Discussions 2022, 1-26, 2022
42022
Advancements and Challenges in Assessing and Predicting the Global Carbon Cycle Variations Using Earth System Models
H Li, T Ilyina, I Dunkl, A Spring, S Brune, WA Müller, R Bernardello, ...
EGU24, 2024
2024
Variations of the CO2 fluxes and atmospheric CO2 in multi-model predictions with an interactive carbon cycle
H Li, A Spring, S Brune, R Bernardello, L Bopp, W Merryfield, J Mignot, ...
EGU General Assembly Conference Abstracts, EGU-14765, 2023
2023
Internal variability obscures COVID-19 emission reductions in global atmospheric CO2
A Spring, H Li, T Ilyina
npj Climate Action 47, 2023
2023
Multi-model comparison of carbon cycle predictability in initialized perfect-model simulations
A Spring, H Li, T Ilyina, R Bernardello, Y Ruprich-Robert, E Tourigny, ...
EGU General Assembly Conference Abstracts, EGU22-8031, 2022
2022
CliMetLab and Pangeo use case: Machine learning data pipeline for sub-seasonal To seasonal prediction (S2S)
A Spring, F Vitart, B Raoult
EGU22, 2022
2022
Withdrawn: Flow-dependent skill in S2S forecasts with and without stochastic parameterizations
J Berner, A Jaye, A Spring
102nd American Meteorological Society Annual Meeting, 2022
2022
State-dependent forecast skill on the S2S-timescale: An application of the python forecast verification package" climpred"
J Berner, A Spring, A Jaye
AGU Fall Meeting Abstracts 2021, A43H-02, 2021
2021
Internal variability and potential predictability of the global carbon cycle in a perfect-model framework
A Spring
Universität Hamburg Hamburg, 2021
2021
Process-based analysis of land carbon flux predictability
I Dunkl, A Spring, V Brovkin
EGU General Assembly Conference Abstracts, EGU21-2093, 2021
2021
Earth system predictions of the carbon sinks and atmospheric CO2 growth: new insights and lessons from DCPP
T Ilyina, H Li, W Müller, A Spring
EGU General Assembly Conference Abstracts, EGU21-2529, 2021
2021
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