Dr Nicola Maher
Senior Research Fellow
Chief Investigator for the the ARC Centre of Excellence for Weather of the 21st Century, PhD (UNSW 2016)
email Nicola.Maher@anu.edu.au
link ANU Researcher Portal profile

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Affiliations

  Groups

Research interests

My research uses global coupled climate models to investigate the dynamics, impacts and future changes modes of climate variability. My research interests lie in the following areas:

  1. Single Model Initial-Condition Large Ensemble (SMILE ) modelling -investigate the forced response to greenhouse gases and internal variability
  2. Develop/leverage new tools - machine learning/artificial intelligence (e.g. neural networks, long-term short-term memory network, ensemble classifiers)
  3. Understand future projections - particularly projections of internal variability and extreme events
  4. ENSO research - dynamics, teleconnections and ENSO itself in a warming world

Projects

Teaching information

I teach 4 weeks on climate modelling, dynamics and models of variability as well as the fieldtrip of https://programsandcourses.anu.edu.au/course/emsc3039 

I teach a half day on climate models into https://programsandcourses.anu.edu.au/course/envs8003 

 

Supervised students

Location

J7.210

Publications

Google Scholar Profile: scholar.google.com/citations

Journal Publications 
*Denotes student led papers


Submitted/In Review

  1. *Sengupta, A., King, A.D., Brown, J.R.,Maher, N. Freund, M.B., Ziehn, T., Ong, E.Q.Y., Taschetto, A., McGregor, S. and Dittus, A. Persistence of an El Niño‑like mean state and elevated ENSO amplitude post net‑zero. submitted to Nature Communications Earth and Environment
  2. Maher, N., Deser, C. and O’Brien, J.P. A Multi‑Model Assessment of Evolving Forced Changes in Northern Hemisphere Modes  of Atmospheric Circulation Variability and the Role of the Tropical Pacific submitted to Climate Dynamics
  3. Fasullo, J.T., Caron, J.M., Phillips, A.S., Maher, N., Deser C. and Lee, J. Forced Changes in Modes of Variability in E3SM andCESM submitted to Journal of Climate
  4. Lewis, H., Rampal, N., Gibson, P.B., Harrington, L.J., Holgate, C.M., Ukkola A.M. and Maher, N. Generative AI‑Downscaling of Large Ensembles Project Unprecedented Future Droughts . submitted to Weather and Climate Extremes
  5. Borowiak, A., King, A., Brown, J., Shaw, J., Maher, N., Harrington, L., Hawkins, E., Joshi, M., Liu, J., Pinto, I., Min, S‑K. and Sillmann, J. Methods for estimating the time of emergence of climate change signals Submitted to Nature Reviews
     

Published 

  1. Cheng, M., Maher, N. and Ellwood, M.J. Temperature‑normalised net primary production reveals resource‑driven controls and structural limitations in Southern Ocean productivity projections. Accepted in Environmental Research Letters
  2. *Jeffree, J., Maher, N., Amaya, D. and Dommenget, D. Adapting analogue forecasting to compare ENSO remote influences across different models and regions. Accepted in Climate Dynamics
  3. *Satpathy, S., Franzke, C., Yuan, N., Maher, N., Park, W. and Lee, S‑S. Anthropogenic Climate Change‑driven Atmospheric Angular Momentum Increases Length of Day. Accepted in npj climate and atmospheric science
  4. Stevenson, S., Deser, C., Coats, S., Falster, G., Konecky, B., Maher, N., and Pfleger, C. Present Day Tropical Convection De‑ termines Future Equatorial Pacific Temperature Trends Accepted in Science Advances
  5. *Kiani, R.S., Brown, J.R., King, A.D., Vincent, C. and Maher, N. 2026. Evaluation of CMIP6 models in simulating Australian Monsoon over Northern Australia International Journal of Climatology e70282. https://doi.org/10.1002/joc.70282
  6. Suarez‑Gutierrez, L. and Maher, N.+. 2026. Temperature variability projections remain uncertain after constraining them to best performing SMILEs Nature Communications 17, 314 https://doi.org/10.1038/s41467‑025‑67005‑y +co‑first author
  7. *Huang, A.T., Maher, N. and McGregor, S. ENSO’s impacts on Australia’s future rainfall risk. accepted in Geophysical Research Letters
  8. *Cheng, M., Maher, N. and Ellwood, M.J. 2025. Evaluating the performance of CMIP6 models in simulating Southern Ocean biogeochemistry Biogeosciences 22, 7269–7291, https://doi.org/10.5194/bg‑22‑7269‑2025
  9. King A.D., Alastrué de Asenjo, E., Maycock, A., Ziehn, T., Borowiak, A.R., Clark, S. and Maher, N. 2025. Detectability of post net zero climate changes and the effects of delay in emissions cessation Earth’s Future 2025EF006918. https://doi.org/10.1029/20
  10. Schneider, D.P., Maher, N., Dong, Y. and Kay J.E. and Capotondi, A. 2025. Observable polar and Atlantic sea surface salinity trends have emerged while the noisy Pacific hesitates. Environmental Research: Climate 4 045002, doi:10.1088/27525295/ae065b
  11. Amaya, D.J., Maher, N., Deser, C., Jacox, M.G., Alexander, M.A., Newman, M., Dias, J. and Lou, J. Linking Projected Changes in Seasonal Climate Predictability and ENSO Amplitude Journal of Climate, 38, 675–688, https://doi.org/10.1175/JCLID‑23‑0648.1
  12. King, A.D., Ziehn, T., Chamberlain, M., Borowiak A.R., Brown, J.R., Cassidy L., Dittus, A.J., Grose, M., Maher, N., Paik, S., Perkins‑Kirkpatrick, S.E. and Sengupta, A. (2024) Exploring climate stabilisation at different global warming levels in ACCESS‑ESM‑1.5. Earth System Dynamics 15, 1353–1383, https://doi.org/10.5194/esd‑15‑1353‑2024
  13. Kay, J.E., Liang, Y‑C., Zhou, S‑N. and Maher, N.. (2024) Sea ice feedbacks cause more greenhouse cooling. Environmental Research: Climate 3 041003 doi:10.1088/2752‑5295/ad8026
  14. Capotondi, A., McGregor, S., McPhaden, M.J., Cravatte, S., Holbrook, N.J., Imada, Y., Sanchez, S.C., Sprintall, J., Stuecker,  M.F., Ummenhofer, C.C., Zeller, M., Farneti, R., Graffino G., Hu S., Karnauskas K.B., Kosaka Y., Kucharski F., Mayer M., Qiu B., Santoso A., Taschetto A.S., Wang F., Zhang X., Holmes R.M., Luo J‑J, Maher, N. Martinez‑Villalobos, C., Naha, R., Stevenson, S., Sullivan, A., van Rensch, P. (2023) Mechanisms of Tropical Pacific Decadal Variability. Nature Reviews Earth & Environment 4, 754–769 https://www.nature.com/articles/s43017-023-00486-xwww.nature.com/articles/s43017-023-00486-x
  15. Malagón-Santos, V., Slangen, A. B. A., Hermans, T. H. J., Dangendorf, S., Marcos, M., and Maher, N.. Improving Statistical Projections of Ocean Dynamic Sea-level Change Using Pattern Recognition Techniques, EGUsphere Ocean Science 19, 499-515 https://doi.org/10.5194/os-19-499-2023
  16. Maher, N., Wills, R.C.J., DiNezio, P., Klavans, J., Milinski, S., Sanchez, S.C., Stevenson, S., Stuecker, M.F. and Wu, X. The future of the El Niño-Southern Oscillation: Using large ensembles to illuminate time-varying responses and inter-model differences. Earth System Dynamics 14, 413-431 https://doi.org/10.5194/esd-14-413-2023
  17. ​Maher, N., Kay, J.E.. and Capotondi, A. Modulation of ENSO Teleconnections over North America by the Pacific Decadal Oscillation, Environmental Research Letters 17 114005 https://doi.org/10.1088/1748-9326/ac9327
  18. Maher, N., Tabarin, T.P. and Milinski, S. (2022). Combining machine learning and SMILEs to classify, better understand, and project changes in ENSO events, Earth System Dynamics, https://doi.org/10.5194/esd-2021-105
  19. ​Ward, B., F.S.R. Pausata, and Maher, N. (2021). The sensitivity of the ENSO to volcanic aerosol spatial distribution in the MPI large ensemble. Earth System Dynamics. Earth System Dynamics, 12, 975–996, https://doi.org/10.5194/esd-12-975-2021
  20. Suarez-Gutierrez, L, Maher, N, and Milinski, S. (2021). Exploiting large ensembles for a better yet simpler climate model evaluation. Climate Dynamics.  https://doi.org/10.1007/s00382-021-05821-w
  21. Maher, N., Power, S and Marotzke J. (2021). More accurate quantification of model-to-model agreement in externally forced climatic responses over the coming century. Nature Communications 12, 788 https://doi.org/10.1038/s41467-020-20635-w
  22. Milinski, S.,  Maher, N., and Olonscheck, D.  (2020). How large does a large ensemble need to be? Earth System Dynamics 11, 885-901 doi.org/10.5194/esd-11-885-2020
  23. Fiedler, S., Crueger, T., D'Agostino, R., Peters, P., Becker, T., Leutwyler, D., Paccini, L., Burdanowitz, J., Buehler, S.A., Cortes, A.U., Dauhut, T., Dommenget, D., Fraedrich, K., Jungandreas, L., Maher, N., Naumann, A.K., Rugenstein, M., Sakradzija, M., Schmidt, H., Sielmann, F., Stephan, C., Timmreck, C., Zhu, X. and Stevens, B. (2020). Simulated Tropical Precipitation Assessed Across Three Major Phases of the Coupled Model Intercomparison Project (CMIP). Monthly Weather Review, 148 (9): 3653–3680 https://doi.org/10.1175/MWR-D-19-0404.1
  24. Lehner, F., Deser, C., Maher, N., Marotzke, J., Fischer, E., Brunner, L., Knutti, R., and Hawkins, E.  (2020). Partitioning climate projection uncertainty with multiple Large Ensembles and CMIP5/6 Earth System Dynamics  https://doi.org/10.5194/esd-2019-93
  25. Maher, N., Lehner, F and Marotzke J. (2020). Quantifying the role of internal variability in the climate we will observe in the coming decades. Environmental Research Letters. https://doi.org/10.1088/1748-9326/ab7d02
  26. Perry, S.J., McGregor, S., Sen Gupta, A., England, E. and Maher, N. (2020). Projected late 21st Century changes to the regional impacts of the El Nino-Southern Oscillation. Climate Dynamics. link.springer.com/article/10.1007/s00382-019-05006-6
  27. Maher, N., Milinski, S., Suarez-Gutierrez, L., Botzet, M. Dobrynin, M., Kornblueh, L., Kröger, J., Takano, Y.,  Ghosh, R., Hedemann, C., Li, C., Li, H., Manzini, E., Notz, D., Putrasahan, D., Boysen, L., Claussen, M., Ilyina, T., Olonscheck, D., Raddatz, T., Stevens, B. and Marotzke, J. (2019). The Max Planck Institute Grand Ensemble: Enabling the Exploration of Climate System Variability. JAMES https://doi.org/10.1029/2019MS001639
  28. Maher, N., Matei, D., Milinski, S., and Marotzke, J. (2018). ENSO change in climate projections: Forced response or internal variability? Geophys. Res. Lett., 45. doi.org/10.1029/2018GL079764 
  29. Maher, N. England, M. H., Sen Gupta, A. and Spence, P. (2018), Role of Pacific trade winds in driving ocean temperature during the recent slowdown and projections under a wind trend reversal, Clim Dyn. doi.org/10.1007/s00382-017-3923-3 
  30. Donat M. G., Lowry, A. L., Alexander, L. V., O’Gorman, P. A. and Maher, N. (2016), More extreme rain in the driest and wettest regions of the globe. Nature Climate Change, doi:10.1038/nclimate2941
  31. Maher W., Maher, N., Taylor, A., Krikowa, F., and Mikac, K. M. (2016). The use of the marine gastropod, Cellana tramoserica as a biomonitor of metal contamination in near shore environments, Environ. Monit. Assess, doi: 10.1007/s10661-016-5380-6
  32. Maher, N., McGregor, S., England, M. H., and Sen Gupta, A. (2015), Effects of volcanism on tropical variability, Geophys. Res. Lett., 42 ,6024–6033
  33. Meehl, G. A., Teng, H., Maher, N. and England, M. H. (2015), Effects of Mt Pinatubo eruption on decadal climate prediction skill, Geophys. Res. Lett., 42, 10,840–10,846, doi:10.1002/ 2015GL066608.
  34. England, M. H., Kajtar, J. N., Maher ,N. (2015), Robust warming projections despite the recent hiatus, Nature Climate Change, 5, 394-396
  35. Griffin, J., Latief, H., Kongko, W., Harig, S., Horspool, N., Hanung, R., Rojali, A., Maher, N., Fuchs, A., Hossen, J., Upi, S., Dewanto, S. E., Rakowsky, N. and Cummins, P. (2015), An evaluation of onshore digital elevation models for modeling tsunami inundation zones. Frontiers in Earth Science, 3, 32
  36. Maher, N., Sen Gupta, A., and England, M. E. (2014), Drivers of decadal hiatus periods in the 20th and 21st centuries, Geophys. Res. Lett., 41, 5978–5986
  37. Griffiths, R.W, Maher, N and Hughes, G.O. (2011) ,Ocean stratification under oscillatory surface buoyancy forcing, J. Mar. Res., 69, 523-543 


Book Chapters 

  1. McGregor, S., Khodri, M., Maher, N., Ohba, M., Pausata, F. and Stevenson, S. (2020) The effect of strong volcanic eruptions on ENSO. McPhaden, M.J., Santoso, S. and Cai, W. (Eds.) El Nino Southern Oscillation in a Changing Climate American Geophysical Union

Special Issue Preface/Perspective 

  1. Maher, N, Milinski, S and Ludwig, R (2021). Large ensemble climate model simulations: introduction, overview, and future prospects for utilising multiple types of large ensemble, Earth System Dynamics, 12, 401–418, https://doi.org/10.5194/esd-12-401-2021

Conference Papers 

  1. Vietinghoff, D, Heine, C., Böttinger, M., Maher, N., Jungclaus, J.H., Scheuermann, G. (2021). Visual Analysis of Spatio-Temporal Trends in Time-Dependent Ensemble Data Sets on the Example of the North Atlantic Oscillation. PacificVis

White Papers 

  1. Maher, N., DiNezio, P., Capotondi, A. and Kay, J. (2021). Identifying precursors of daily to seasonal hydrological extremes over the USA using deep learning techniques and climate model ensembles. AI4ESP: Artificial Intelligence for Earth System Predictability. Department of Energy. https://www.ai4esp.org/files/AI4ESP1087_Maher_Nicola.pdf


Other Publications 

  1. Suarez-Gutierrez, L, Maher, N, and Milinski, S.  (2020). Evaluating the internal variability and forced response in Large Ensembles. US CLIVAR Variations, 18, 2.
  2. Maher, N. (2018). Natural drivers of interannual to decadal variations in surface climate. BAMOS, 31(2), 9-12