Journal Publications
Mamalakis A., E.A. Barnes and I. Ebert-Uphoff, (2022) Using XAI baselines to answer different science questions, submitted.
Le, V.V.P., et al. (2021) Climate-driven changes in the predictability of seasonal precipitation, submitted.
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15. Mamalakis, A., E.A. Barnes and I. Ebert-Uphoff, (2022) Investigation of the fidelity of explainable artificial intelligence methods in applications of convolutional neural networks in geoscience, Artificial Intelligence for the Earth Systems, accepted.
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14. Mamalakis, A., I. Ebert-Uphoff and E.A. Barnes, (2022) “Explainable Artificial Intelligence in Meteorology and Climate Science: Model fine-tuning, calibrating trust and learning new science” in Beyond explainable Artificial Intelligence by Holzinger et al. (Editors), Springer Lecture Notes on Artificial Intelligence, open access at: https://link.springer.com/chapter/10.1007/978-3-031-04083-2_16
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13. Mamalakis, A., I. Ebert-Uphoff and E.A. Barnes, (2022) Neural network attribution methods for problems in Geoscience: A novel synthetic benchmark dataset, Environmental Data Science, DOI: 10.1017/eds.2022.7.
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12. Mamalakis, A., A. AghaKouchak, J.T. Randerson and E. Foufoula-Georgiou, (2022) Hotspots of Predictability: Identifying regions of high precipitation predictability at seasonal timescales from limited time series observations, Water Resources Research, 58(5), e2021WR031302.
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​11. Le, P.V.V., C. Guilloteau, A. Mamalakis and E. Foufoula-Georgiou (2021) Underestimated MJO variability in CMIP6 models, Geophysical Research Letters, https://doi.org/10.1029/2020GL092244.
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​10. Mamalakis, A., J.T. Randerson, J.-Y. Yu, M.S. Pritchard, G. Magnusdottir, P. Smyth, P.A. Levine, S. Yu and E. Foufoula-Georgiou (2021) Zonally contrasting shifts of the tropical rainbelt in response to climate change, Nature Climate Change, 11, 143–151.
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9. Guilloteau C., A. Mamalakis, L. Vulis, P. Le, T Georgiou, E. Foufoula-Georgiou (2020) Rotated spectral principal component analysis (rsPCA) for identifying dynamical modes of variability in climate systems, J. Climate, https://doi.org/10.1175/JCLI-D-20-0266.1
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8. Stevens A., R., Willett, A. Mamalakis, E. Foufoula-Georgiou, J. Randerson, P. Smyth, S. Wright and A. Tejedor (2020) Graph-guided regularized regression of Pacific Ocean climate variables to increase predictive skill of southwestern US winter precipitation, J. Climate, https://doi.org/10.1175/JCLI-D-20-0079.1.
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7. Mamalakis, A., J.-Y. Yu, J.T. Randerson, A. AghaKouchak, and E. Foufoula-Georgiou (2019) Reply to: A critical examination of a newly proposed interhemispheric teleconnection to Southwestern US winter precipitation, Nature Communications, https://doi.org/10.1038/s41467-019-10531-3
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6. Mamalakis, A. and V. Kaleris (2019) Estimation of seawater retreat timescales in homogeneous and confined coastal aquifers based on dimensional analysis, Hydrological Sciences Journal, doi:10.1080/02626667.2018.1552787
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4. Mamalakis, A., J.-Y. Yu, J.T. Randerson, A. AghaKouchak, and E. Foufoula-Georgiou (2018) A new interhemispheric teleconnection increases predictability of winter precipitation in southwestern US, Nature Communications, doi: 10.1038/s41467-018-04722-7 (50 most read articles)
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3. Mamalakis A., A. Langousis, R. Deidda and M. Marrocu (2017) A parametric approach for simultaneous bias correction and high-resolution downscaling of climate model rainfall, Water Resour. Res., doi: 10.1002/2016WR019578 (Editor's highlights)
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2. Langousis A., A. Mamalakis, M. Puliga and R. Deidda (2016) Threshold detection for the generalized Pareto distribution: Review of representative methods and application to the NOAA NCDC daily rainfall database Water Resour. Res., doi: 10.1002/2015WR018502.
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1. Langousis A., A. Mamalakis, R. Deidda and M. Marrocu (2016) Assessing the relative effectiveness of statistical downscaling and distribution mapping in reproducing rainfall statistics based on climate model results, Water Resour. Res., doi:10.1002/2015WR017556
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