CliMA Publications

Submitted/in press

  • E. Cleary, A. Garbuno-Inigo, S. Lan, T. Schneider, A.M. Stuart, 2020: Calibrate, emulate, sample, Journal of Computational Physics, submitted.
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  • Z. Shen, K.G. Pressel, Z. Tan, T. Schneider, 2020: Statistically steady state large-eddy simulations forced by an idealized GCM: 1. Forcing framework and simulation characteristics, Journal of Advances in Modeling Earth Systems, submitted.
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  • B. Gallet and R. Ferrari, 2020: The vortex gas scaling regime of baroclinic turbulence, Proceedings of the National Academy of Sciences, in press.
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  • A. Ramadhan, G. L. Wagner, C. Hill, J.-M. Campin, V. Churavy, T. Besard, A. Souza, A. Edelman, J. Marshall, and R. Ferrari, 2020: Oceananigans.jl: Fast and friendly geophysical fluid dynamics on GPUs, Journal of Open Source Software, submitted.
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  • Garbuno-Inigo, A., F. Hoffmann, W. Li, and A. M. Stuart, 2020: Interacting Langevin diffusions:
    gradient structure and ensemble Kalman sampler, SIAM Journal on Applied Dynamical Systems, in press.
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2020

  • Novak, L., T. Schneider, and F. Ait-Chaalal, 2020: Midwinter suppression of storm tracks in an idealized zonally symmetric setting, Journal of the Atmospheric Sciences, 77, 297-313.
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2019

2018

  • Callies, J., and R. Ferrari, 2018: Baroclinic instability in the presence of convection. Journal of Physical Oceanography, 48, 1543–1553.
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  • A.M. Stuart and A.L. Teckentrup, 2018: Posterior consistency for Gaussian process approximations of Bayesian posterior distributions. Mathematics of Computation, 87, 721-753.
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  • Tan, Z., C. M. Kaul, K. G. Pressel, Y. Cohen, T. Schneider, and J. Teixeira, 2018: An extended eddy-diffusivity mass-flux scheme for unified representation of subgrid-scale turbulence and convection. Journal of Advances in Modeling Earth Systems, 10, 770-800.
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  • Callies, J., and R. Ferrari, 2018: Note on the rate of restratification in the baroclinic spindown of fronts. Journal of Physical Oceanography, 48, 45–60.
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2017

  • Schneider, T., S. Lan, A. Stuart, and J. Teixeira, 2017: Earth system modeling 2.0: A blueprint for models that learn from observations and targeted high-resolution simulations. Geophysical Research Letters, 44, 12,396–12,417, doi:10.1002/2017GL076101.
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  • C. Schillings and A.M. Stuart, 2017: Analysis of the ensemble Kalman filter for inverse problems. SIAM J Numerical Analysis, 55, 1264-1290.
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  • M.A. Iglesias, K. Lin, S. Lu, A.M. Stuart, 2017: Filter based methods for statistical linear inverse problems. Communications in Math. Sciences, 15, 1867-1896.
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  • Schneider, T., J. Teixeira, C. S. Bretherton, F. Brient, K. G. Pressel, C. Schär, and A. P. Siebesma, 2017: Climate goals and computing the future of clouds. Nature Climate Change, 7, 3-5.
    Free Read-Only Version Official version