| 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 | 191 | 2020 |
| 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 | 29 | 2021 |
| 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 | 24 | 2022 |
| Predictability horizons in the global carbon cycle inferred from a perfect‐model framework A Spring, T Ilyina Geophysical Research Letters 47 (9), e2019GL085311, 2020 | 21 | 2020 |
| 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 | 17 | 2020 |
| climpred: Verification of weather and climate forecasts RX Brady, A Spring Journal of Open Source Software 6 (59), 2781, 2021 | 9 | 2021 |
| 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 | 6 | 2021 |
| 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 | 4 | 2022 |
| Process-based analysis of terrestrial carbon flux predictability I Dunkl, A Spring, P Friedlingstein, V Brovkin Earth System Dynamics 12 (4), 1413-1426, 2021 | 4 | 2021 |
| 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 | 3 | 2023 |
| 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 |
Tatiana IlyinaOcean Biogeochemistry Group Lead, Max Planck Institute for MeteorologyVerified email at mpimet.mpg.de
