Primary ForceSMIP Publications:
Wills, R.C.J., C. Deser, K.A. McKinnon, A. Phillips, S. Po-Chedley, S. Sippel, A.L. Merrifield, C. Bône, C. Bonfils, G. Camps-Valls, S. Cropper, C. Connolly, S. Duan, H. Durand, A. Feigin, M.A. Fernandez, G. Gastineau, A. Gavrilov, E. Gordon, M. Günther, M. Höver, S. Kravtsov, Y.-N. Kuo, J. Lien, G.D. Madakumbra, N. Mankovich, M. Newman, J. Rader, J.-R. Shi, S.-I. Shin, G. Varando, 2026: Forced Component Estimation Statistical Method Intercomparison Project (ForceSMIP). In review at Journal of Climate. [Preprint]
Several more publications coming soon...
ForceSMIP Data and Code Outputs:
Tier 1 forced response estimates from all methods in the model testbed and observations: https://doi.org/10.5281/zenodo.15577519
Code for all Tier 1 methods: https://github.com/ForceSMIP/tier1-methods
Associated Publications:
Rader, J. K., C. Connolly, M. A. Fernandez, and E. M. Gordon, 2025: Attribution of the record-high 2023 SST using a deep-learning framework. Environmental Research Communications. [Published Version]
Bône, C., G. Gastineau, S. Thiria, P. Gallinari, and C. Mejia, 2024: Separation of internal and forced variability of climate using a U-Net. Journal of Advances in Modeling Earth Systems, 16 (6), e2023MS003 964. [Published Version]
Gavrilov, A., S. Kravtsov, M. Buyanova, D. Mukhin, E. Loskutov, and A. Feigin, 2024: Forced response and internal variability in ensembles of climate simulations: Identification and analysis using linear dynamical mode decomposition. Climate Dynamics, 62 (3), 1783–1810. [Published Version]
Deser, C., and A. S. Phillips, 2023: Spurious Indo-Pacific connections to internal Atlantic Multidecadal variability introduced by the global temperature residual method. Geophysical Research Letters, 50 (3), e2022GL100 574. [Published Version]
Sippel, S., N. Meinshausen, E. Székely, E. Fischer, A. G. Pendergrass, F. Lehner, and R. Knutti, 2021: Robust detection of forced warming in the presence of potentially large climate variability. Science Advances, 7 (43), eabh4429. [Published Version]
Wills, R.C.J., D.S. Battisti, K.C. Armour, T. Schneider, and C. Deser, 2020: Pattern recognition methods to separate forced responses from internal variability in climate model ensembles and observations. Journal of Climate, 33, 8693–8719. [Published Version] - an important source of inspiration for ForceSMIP
See also the following presentations about the outcomes from ForceSMIP Tier 1:
AGU Fall Meeting, Dec. 11, 2024: Forced Component Statistical Method Intercomparison Project (ForceSMIP)
EGU General Assembly, Apr. 17, 2024: Forced Component Statistical Method Intercomparison Project (ForceSMIP): First Results