Publications

Peer Reviewed Journal Articles

  1. Smith, T. A., Penny, S. G., Platt, J. A., & Chen, T.-C. (2024). xesn: Echo state networks powered by Xarray and Dask. Journal of Open Source Software, 9(103), 7286. https://doi.org/10.21105/joss.07286

  2. Worsnop, R. P., Scheuerer, M., Hamill, T. M., Smith, T. A., & Schlör, J. (2024). RUFCO: a deep-learning framework to post-process subseasonal precipitation accumulation forecasts. Artificial Intelligence for the Earth Systems. https://doi.org/10.1175/AIES-D-24-0020.1

  3. Smith, T. A., Penny, S. G., Platt, J. A., & Chen, T.-C. (2023). Temporal Subsampling Diminishes Small Spatial Scales in Recurrent Neural Network Emulators of Geophysical Turbulence. Journal of Advances in Modeling Earth Systems, 15(12), e2023MS003792. https://doi.org/10.1029/2023MS003792

  4. Halpern, D., Le, M. K., Smith, T. A., & Heimbach, P. (2023). Comparison of ADCP and ECCOv4r4 Currents in the Pacific Equatorial Undercurrent. Journal of Atmospheric and Oceanic Technology, 40(12), 1369-1381. https://doi.org/10.1175/JTECH-D-23-0013.1

  5. Platt, J. A., Penny, S. G., Smith, T. A., Chen, T.-C., & Abarbanel, H. D. I. (2023). Constraining chaos: Enforcing dynamical invariants in the training of reservoir computers. Chaos: An Interdisciplinary Journal of Nonlinear Science, 33(10), 103107. https://doi.org/10.1063/5.0156999

  6. Platt, J. A., Penny, S. G., Smith, T. A., Chen, T.-C., and Abarbanel, H. D. I. (2022). A systematic exploration of reservoir computing for forecasting complex spatiotemporal dynamics. Neural Networks, 153, 530–552. https://doi.org/10.1016/j.neunet.2022.06.025

  7. Penny, S. G., Smith, T. A., Chen, T.-C., Platt, J. A., Lin, H.-Y., Goodliff, M., and Abarbanel, H.D.I. (2022) Integrating Recurrent Neural Networks with Data Assimilation for Scalable Data-Driven State Estimation. Journal of Advances in Modeling Earth Systems (JAMES). 14, e2021MS002843. https://doi.org/10.1029/2021MS002843

  8. Kostov, Y., Johnson, H., Marshall, D., Forget, G., Heimbach, P., Holliday, P., Li, F., Lozier, S., Pillar, H., & Smith, T. Contrasting sources of variability in subtropical and subpolar Atlantic overturning. Nature Geosciences. https://doi.org/10.1038/s41561-021-00759-4

  9. Nguyen, A. T., Pillar, H., Ocaña, V., Bigdeli, A., Smith, T. A., & Heimbach, P. (2021). The Arctic Subpolar gyre sTate Estimate (ASTE): Description and assessment of a data‐constrained, dynamically consistent ocean‐sea ice estimate for 2002–2017. Journal of Advances in Modeling Earth Systems, 13, e2020MS002398. https://doi.org/10.1029/2020MS002398

  10. Laguë, M. M., Pietschnig, M., Ragen, S., Smith, T. A., & Battisti, D. S. (2021). Terrestrial Evaporation and Global Climate: Lessons from Northland, a Planet with a Hemispheric Continent. Journal of Climate, 34(6), 2253-2276. https://doi.org/10.1175/JCLI-D-20-0452.1

  11. Goldberg, D. N., Smith, T. A., Narayanan, S. H. K., Heimbach, P., & Morlighem, M. (2020). Bathymetric Influences on Antarctic Ice-Shelf Melt Rates. Journal of Geophysical Research: Oceans, 125(11), e2020JC016370. https://doi.org/10.1029/2020JC016370

  12. Smith, T. & Heimbach, P. (2019). Atmospheric Origins of Variability in the South Atlantic Meridional Overturning Circulation. Journal of Climate, 32(5), 14831500. https://doi.org/10.1175/JCLI-D-18-0311.1

  13. Stoll, B. L., Smith, T. A., & Deinert, M. R. (2013). Potential for rooftop photovoltaics in Tokyo to replace nuclear capacity. Environmental Research Letters, 8(1), 014042. https://doi.org/10.1088/1748-9326/8/1/014042

Peer Reviewed Conference Proceedings

  1. Osborne, A. G., Smith, T. A., & Deinert, M. R. (2013). Comparison of actinide production in traveling wave and pressurized water reactors. In Proceedings of GLOBAL 2013: International Nuclear Fuel Cycle Conference-Nuclear Energy at a Crossroads.

Preprints

  1. Smith, T. A. A Practical Formulation for an Anisotropic and Nonstationary Mat'ern Class Correlation Operator. (2022). Preprint: https://essopenarchive.org/doi/full/10.1002/essoar.10511974.1

  2. Smith, T. A. (2021). Flow aware parameterizations invigorate the simulated ocean circulation under the Pine Island ice shelf, West Antarctica. Preprint: https://essopenarchive.org/doi/full/10.1002/essoar.10507839.2

  3. Chen, T.-C., Penny, S. G., Smith, T. A., and Platt, J. A. ‘Next Generation’ Reservoir Computing: an Empirical Data-Driven Expression of Dynamical Equations in Time-Stepping Form. Preprint: https://arxiv.org/abs/2201.05193

  4. Abernathey, R., Busecke, J., Banihirwe, A., Zhang, C., & Smith, T. Xgcm: a python package for analyzing data from general circulation models. Manuscript in review at Journal of Open Source Software.