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Molina, M.J., T.A. O'Brien, G. Anderson, M. Ashfaq, K.E. Bennett, W.D. Collins, K. Dagon, J.M. Restrepo, and P.A. Ullrich (2023), A review of recent and emerging machine learning applications for climate variability and weather phenomena, Artificial Intelligence for the Earth Systems, 2, 220086, https://doi.org/10.1175/AIES-D-22-0086.1.
Touma, D., J.W. Hurrell, M. Tye, and K. Dagon (2023), The impact of stratospheric aerosol injection on extreme fire weather risk, Earth's Future, 11, e2023EF003626, https://doi.org/10.1029/2023EF003626.
Molina, M.J., J.H. Richter, A.A. Glanville, K. Dagon, J. Berner, A. Hu, and G.A. Meehl (2023), Subseasonal representation and predictability of North American weather regimes using cluster analysis, Artificial Intelligence for the Earth Systems, 2, e220051, https://doi.org/10.1175/AIES-D-22-0051.1.
Cheng, Y., K. Musselman, S. Swenson, D. Lawrence, J. Hamman, K. Dagon, D. Kennedy, and A.J. Newman (2023), Moving land models towards more actionable science: A novel application of the Community Terrestrial Systems Model across Alaska and the Yukon River Basin, Water Resources Research, 59, e2022WR032204, https://doi.org/10.1029/2022WR032204.
Dagon, K., J. Truesdale, J.C. Biard, K.E. Kunkel, G.A. Meehl, and M.J. Molina (2022), Machine learning-based detection of weather fronts and associated extreme precipitation in historical and future climates, Journal of Geophysical Research: Atmospheres, 127, e2022JD037038, https://doi.org/10.1029/2022JD037038.
Tye, M.R., K. Dagon, M.J. Molina, J.H. Richter, D. Visioni, B. Kravitz, and S. Tilmes (2022), Indices of Extremes: Geographic patterns of change in extremes and associated vegetation impacts under climate intervention, Earth System Dynamics, 13, 1233-1257, https://doi.org/10.5194/esd-13-1233-2022.
Ali, A.A., Y. Fan, M.D. Corre, M.M. Kotowska, E. Preuss-Hassler, A.N. Cahyo, F.E. Moyano, C. Stiegler, A. Röll, A. Meijide, A. Olchev, A. Ringeler, C. Leuschner, R. Ariani, T. June, S. Tarigan, H. Kreft, D. Hölscher, C. Xu, C.D. Koven, K. Dagon, R.A. Fisher, E. Veldkamp, and A. Knohl (2022), Implementing a new rubber plant functional type in the Community Land Model (CLM5) improves accuracy of carbon and water flux estimation, Land, 11, 183, https://doi.org/10.3390/land11020183.
Prabhat, K. Kashinath, M. Mudigonda, S. Kim, L. Kapp-Schwoerer, A. Graubner, E. Karaismailoglu, L. von Kleist, T. Kurth, A. Greiner, K. Yang, C. Lewis, J. Chen, A. Lou, S. Chandran, B. Toms, W. Chapman, K. Dagon, C.A. Shields, T. O'Brien, M. Wehner, and W. Collins (2021), ClimateNet: an expert-labelled open dataset and Deep Learning architecture for enabling high-precision analyses of extreme weather, Geoscientific Model Development, 14, 107-124, https://doi.org/10.5194/gmd-14-107-2021.
Dagon, K., B.M. Sanderson, R.A. Fisher, D.M. Lawrence (2020), A machine learning approach to emulation and biophysical parameter estimation with the Community Land Model, version 5, Advances in Statistical Climatology, Meteorology and Oceanography, 6, 223-244, https://doi.org/10.5194/ascmo-6-223-2020.
Xu, Y., L. Lin, S. Tilmes, K. Dagon, L. Xia, C. Diao, W. Cheng, Z. Wang, I. Simpson, and L. Burnell (2020), Climate engineering to mitigate the projected 21st-century terrestrial drying of the Americas: a direct comparison of carbon capture and sulfur injection, Earth System Dynamics, 11, 673-695, https://doi.org/10.5194/esd-11-673-2020.
Cheng, W., D.G. MacMartin, K. Dagon, B. Kravitz, S. Tilmes, J.H. Richter, M.J. Mills, and I.R. Simpson (2019), Soil moisture and other hydrological changes in a stratospheric aerosol geoengineering large ensemble, Journal of Geophysical Research: Atmospheres, 124, 12773-12793, doi:10.1029/2018JD030237
Kravitz, B., D.G. MacMartin, S. Tilmes, J.H. Richter, M.J. Mills, W. Cheng, K. Dagon, A.S. Glanville, J.- F. Lamarque, I.R. Simpson, J.J. Tribbia, and F. Vitt (2019), Comparing surface and stratospheric impacts of geoengineering with different SO2 injection strategies, Journal of Geophysical Research: Atmospheres, 124, 7900-7918, doi:10.1029/2019JD030329.
Dagon, K., and D. P. Schrag (2019), Quantifying the effects of solar geoengineering on vegetation, Climatic Change, 153, 235-251, doi:10.1007/s10584-019-02387-9.
Dagon, K., and D. P. Schrag (2017), Regional climate variability under model simulations of solar geoengineering, Journal of Geophysical Research: Atmospheres, 122, 12106-12121, doi:10.1002/2017JD027110.
Dagon, K., and D. P. Schrag (2016), Exploring the effects of solar radiation management on water cycling in a coupled land-atmosphere model, Journal of Climate, 29, 2635-2650, doi:10.1175/JCLI-D-15-0472.1.
Tobias, S. M., K. Dagon, and J. B. Marston (2011), Astrophysical fluid dynamics via direct statistical simulation, The Astrophysical Journal, 727, 127, doi:10.1088/0004-637X/727/2/127.
