Publications

For a complete list see my Google Scholar profile.

Ault, T. R. et al. (2013). Characterizing decadal to centennial variability in the equatorial pacific during the last millennium. Geophysical Research Letters, 40, 3450–3456. https://doi.org/10.1002/grl.50647
Barboza, L. A. et al. (2019). Efficient Reconstructions of Common Era Climate via Integrated Nested Laplace Approximations. Journal of Agricultural, Biological and Environmental Statistics. https://doi.org/10.1007/s13253-019-00372-4
Brierley, C. M. et al. (2020). Large-scale features and evaluation of the PMIP4-CMIP6 midHolocene simulations. Climate of the Past, 16(5), 1847–1872. https://doi.org/10.5194/cp-16-1847-2020
Chen, S. et al. (2016). A high-resolution speleothem record of western equatorial pacific rainfall: Implications for holocene ENSO evolution. Earth and Planetary Science Letters, 442, 61–71. https://doi.org/10.1016/j.epsl.2016.02.050
Comboul, Maud et al. (2015). Paleoclimate sampling as a sensor placement problem. Journal of Climate, 28, 7717–7740. https://doi.org/10.1175/JCLI-D-14-00802.1
Comboul, M. et al. (2014). A probabilistic model of chronological errors in layer-counted climate proxies: Applications to annually banded coral archives. Climate of the Past, 10(2), 825–841. https://doi.org/10.5194/cp-10-825-2014
Cropper, S. et al. (2023). Revisiting a Constraint on Equilibrium Climate Sensitivity From a Last Millennium Perspective. Geophysical Research Letters, 50(20), e2023GL104126. https://doi.org/10.1029/2023GL104126
Dee, S., Emile-Geay, J., et al. (2015). PRYSM: An open-source framework for PRoxY System Modeling, with applications to oxygen-isotope systems. Journal of Advances in Modeling Earth Systems, 7(3), 1220–1247. https://doi.org/10.1002/2015MS000447
Dee, S., Noone, D., et al. (2015). SPEEDY-IER: A fast atmospheric GCM with water isotope physics. Journal of Geophysical Research: Atmospheres, 120(1), 2014JD022194. https://doi.org/10.1002/2014JD022194
Dee, Sylvia G. et al. (2020). No consistent ENSO response to volcanic forcing over the last millennium. Science, 367(6485), 1477–1481. https://doi.org/10.1126/science.aax2000
Dee, S. G. et al. (2017). Improved spectral comparisons of paleoclimate models and observations via proxy system modeling: Implications for multi-decadal variability. Earth and Planetary Science Letters, 476(Supplement C), 34–46. https://doi.org/10.1016/j.epsl.2017.07.036
Dee, Sylvia G. et al. (2016). On the utility of proxy system models for estimating climate states over the common era. Journal of Advances in Modeling Earth Systems, 8. https://doi.org/10.1002/2016MS000677
Dutay, J.-C. et al. (2010). Helium isotopic constraints on simulated ocean circulations: Implications for abyssal theories. Environmental Fluid Mechanics, 10(1), 257–273. Retrieved from http://dx.doi.org/10.1007/s10652-009-9159-y
Emile-Geay, J. (2023). Data analysis in the earth & environmental sciences (11th ed., p. 265). FigShare. https://doi.org/10.6084/m9.figshare.1014336
Emile-Geay, J. et al. (2009). Pacific Decadal Variability in the view of linear equatorial wave theory. J. Phys. Oceanogr., 39, 203–218.
Emile-Geay, J. et al. (2013). Toward a semantic web of paleoclimatology. Geochemistry, Geophysics, Geosystems, 14(2), 457–469. https://doi.org/10.1002/ggge.20067
Emile-Geay, J. et al. (2009). Geothermal heating, diapycnal mixing and the abyssal circulation. Ocean Science, 5(2), 203–217. https://doi.org/10.5194/os-5-203-2009
Emile-Geay, J. et al. (2016). Paleoclimate data standards. PAGES Magazine, 24, 47. https://doi.org/10.22498/pages.24.1.47
Emile-Geay, J. et al. (2016). Inferring climate variability from nonlinear proxies: Application to palaeo-ENSO studies. Climate of the Past, 12(1), 31–50. https://doi.org/10.5194/cp-12-31-2016
Emile-Geay, Julien et al. (2025). Temporal comparisons involving paleoclimate data assimilation: Challenges & remedies. Journal of Climate. https://doi.org/10.1175/JCLI-D-24-0101.1
Emile-Geay, Julien et al. (2020). Past ENSO variability. In M. J. McPhaden et al. (Eds.), El niño southern oscillation in a changing climate (pp. 87–118). American Geophysical Union (AGU). https://doi.org/10.1002/9781119548164.ch5
Emile-Geay, Julien et al. (2018). LinkedEarth: supporting paleoclimate data standards and crowd curation. Past Global Change Magazine, 26(2), 62–63. https://doi.org/10.22498/pages.26.2.62
Emile-Geay, J. et al. (2017). Climate dynamics with the last millennium reanalysis. PAGES Magazine, 25(3), 162. https://doi.org/10.22498/pages.25.3.162
Emile-Geay, J. et al. (2016). Links between tropical pacific seasonal, interannual and orbital variability during the holocene. Nature Geosci, 9(2), 168–173. https://doi.org/10.1038/ngeo2608
Emile-Geay, J. et al. (2013a). Estimating Central Equatorial Pacific SST variability over the Past Millennium. Part 1: Methodology and Validation. J. Clim., 26, 2302–2328. https://doi.org/10.1175/JCLI-D-11-00510.1
Emile-Geay, J. et al. (2013b). Estimating Central Equatorial Pacific SST variability over the Past Millennium. Part 2: Reconstructions and Implications. J. Clim., 26, 2329–2352. https://doi.org/10.1175/JCLI-D-11-00511.1
Emile-Geay, J. et al. (2008). Volcanoes and ENSO over the Past Millennium. J. Clim., 21, 3134–3148. https://doi.org/10.1175/2007JCLI1884.1
Emile-Geay, J. et al. (2007). El Niño as a mediator of the solar influence on climate. Paleoceanography, 22(3), A3210+. https://doi.org/10.1029/2006PA001304
Emile-Geay, J. et al. (2003). Warren revisited: Atmospheric freshwater fluxes and “Why is no deep water formed in the North Pacific”. Journal of Geophysical Research (Oceans), 108, 3178–+. https://doi.org/10.1029/2001JC001058
Emile-Geay, J. and McKay, N. and Kaufman, D. and von Gunten, L. and Wang, J. and Anchukaitis, K. and Abram, N. and Addison, J. and Curran, M. and Evans, M. and Henley, B. and Hao, Z. and Martrat, B. and McGregor, H. and Neukom , R. and Pederson, G. and Stenni, B. and Thirumalai, K. and Werner, J. and Xu, C. and Divine, D. and Dixon, B. and Gergis, J. and Mundo, I. and Nakatsuka, T. and Phipps, S. and Routson, C. and Steig, E. and Tierney, J. and Tyler, J. and Allen, K. and Bertler, N. and Björklund and Chase, B. and Chen, M. and Cook, E. and de Jong, R. and DeLong, K. and Dixon, D. and Ekaykin, A. and Ersek V. and Filipsson, H. and Francus, P. and Freund, M. and Frezzotti, M. and Gaire, N. and Gajewski, K. and Ge, Q. and Goosse, H. and Gornostaeva, A. and Grosjean, M. and Horiuchi, K. and Hormes, A. and Husum, K. and Isaksson , E. and Kandasamy, S. and Kawamura, K. and Kilbourne, K. and Koc, N. and Leduc, G. and Linderholm, H. and Lorrey, A. and Mikhalenko, V. and Mortyn, G. and Motoyama, H. and Moy, A. and Mulvaney, R. and Munz, P. and Nash, D. and Oerter, H. and Opel, T. and Orsi, A. and Ovchinnikov, D. and Porter, T. and Roop, H. and Saenger, C. and Sano, M. and Sauchyn, D. and Saunders, K. and Seidenkrantz, M. and Severi, M. and Shao, X. and Sicre, M. and Sigl, M. and Sinclair, K. and St. George, S. and St. Jacques, J. and Thamban, M. and Thapa, U. and Thomas, E. and Turney, C. and Uemura, R. and Viau, A. and Vladimirova, D. and Wahl, E. and White, J. and Yu, Z. and Zinke, J. (2017). A global multiproxy database for temperature reconstructions of the Common Era. Scientific Data, 4, 170088 EP. https://doi.org/10.1038/sdata.2017.88
Erb, M. P. et al. (2020). Atmospheric dynamics drive most interannual U.S. droughts over the last millennium. Science Advances, 6(32), eaay7268. https://doi.org/10.1126/sciadv.aay7268
Feng, X. et al. (2021). A multidecadal-scale tropically driven global teleconnection over the past millennium and its recent strengthening. Journal of Climate, 34(7), 2549–2565. https://doi.org/10.1175/JCLI-D-20-0216.1
Fischer, H. et al. (2018). Palaeoclimate constraints on the impact of 2 \(\,^{\circ}\)c anthropogenic warming and beyond. Nature Geoscience. https://doi.org/10.1038/s41561-018-0146-0
Guillot, D. et al. (2015). Statistical paleoclimate reconstructions via Markov random fields. Ann. Applied. Statist., 324–352. https://doi.org/10.1214/14-AOAS794
Hakim, G. J. et al. (2016). The last millennium climate reanalysis project: Framework and first results. Journal of Geophysical Research: Atmospheres, 121, 6745–6764. https://doi.org/10.1002/2016JD024751
Herweijer, C. et al. (2007). North American droughts of the last millennium from a gridded network of tree-ring data. J. Climate, 20, 1353–1376.
Hu, J. et al. (2019). Deciphering oxygen isotope records from chinese speleothems with an isotope-enabled climate model. Paleoceanography and Paleoclimatology, 34(12), 2098–2112. https://doi.org/10.1029/2019PA003741
Hu, J. et al. (2018). Impact of convective activity on precipitation  in isotope-enabled general circulation models. Journal of Geophysical Research: Atmospheres, 123(23), 13, 595–13, 610. https://doi.org/10.1029/2018JD029187
Hu, J. et al. (2017). Correlation-based interpretations of paleoclimate data – where statistics meet past climates. Earth and Planetary Science Letters, 459, 362–371. https://doi.org/10.1016/j.epsl.2016.11.048
James, A., Emile-Geay, J., et al. (2025). Global speleothem analysis reveals state-dependent hydrological response to orbital forcing. Paleoceanography and Paleoclimatology, 40(8), e2024PA005098. https://doi.org/10.1029/2024PA005098
James, A., Hu, J., et al. (2025). Regime Shifts in Holocene Paleohydrology as Recorded by Asian Speleothems. Paleoceanography and Paleoclimatology, 40(1), e2024PA004974. https://doi.org/10.1029/2024PA004974
James, A. et al. (2024). Detecting Paleoclimate Transitions With Laplacian Eigenmaps of Recurrence Matrices (LERM). Paleoceanography and Paleoclimatology, 39(1), e2023PA004700. https://doi.org/10.1029/2023PA004700
Kaufman, D. et al. (2020). A global database of holocene paleotemperature records. Scientific Data, 7(1), 115. https://doi.org/10.1038/s41597-020-0445-3
Khider, Deborah et al. (2022). Pyleoclim: Paleoclimate timeseries analysis and visualization with python. Paleoceanography and Paleoclimatology, 37(10), e2022PA004509. https://doi.org/10.1029/2022PA004509
Khider, Deborah et al. (2019). PaCTS v1.0: A Crowdsourced Reporting Standard for Paleoclimate Data. Paleoceanography and Paleoclimatology. https://doi.org/10.1029/2019PA003632
Khider, D. et al. (2015). A Bayesian, multivariate calibration for Globigerinoides ruber Mg/Ca. Geochemistry, Geophysics, Geosystems, 16, 2916–2932. https://doi.org/10.1002/2015GC005844
Khider, D. et al. (2011). Assessing El Niño-Southern Oscillation Variability During the Past Millennium. Paleoceanography, 26(PA3222). https://doi.org/10.1029/2011PA002139
King, J. M. et al. (2021). A data assimilation approach to last millennium temperature field reconstruction using a limited high-sensitivity proxy network. Journal of Climate, 1–64. https://doi.org/10.1175/JCLI-D-20-0661.1
Manety, S. et al. (2022). PaleoRec: A sequential recommender system for the annotation of paleoclimate datasets. Environmental Data Science, 1, e4. https://doi.org/10.1017/eds.2022.3
McKay, Nicholas P. et al. (2018). Linked paleo data: A resource for open, reproducible, and efficient paleoclimatology. Past Global Change Magazine, 26(2), 71–71. https://doi.org/10.22498/pages.26.2.71
McKay, N. P. et al. (2016). Technical note: The linked paleo data framework : A common tongue for paleoclimatology. Climate of the Past, 12(4), 1093–1100. https://doi.org/10.5194/cp-12-1093-2016
McKay, N. P. et al. (2021). geoChronR – an R package to model, analyze, and visualize age-uncertain data. Geochronology, 3(1), 149–169. https://doi.org/10.5194/gchron-3-149-2021
Neukom, R. et al. (2019). Consistent multidecadal variability in global temperature reconstructions and simulations over the common era. Nature Geoscience, 12(8), 643–649. https://doi.org/10.1038/s41561-019-0400-0
Partin, J. W. et al. (2013). Multidecadal rainfall variability in south pacific convergence zone as revealed by stalagmite geochemistry. Geology. https://doi.org/10.1130/G34718.1
Power, S. et al. (2021). Decadal climate variability in the tropical pacific: Characteristics, causes, predictability, and prospects. Science, 374(6563), eaay9165. https://doi.org/10.1126/science.aay9165
Singh, H. K. A. et al. (2018). Insights into atlantic multidecadal variability using the last millennium reanalysis framework. Climate of the Past, 14(2), 157–174. https://doi.org/10.5194/cp-14-157-2018
Tardif, R. et al. (2019). Last millennium reanalysis with an expanded proxy database and seasonal proxy modeling. Climate of the Past, 15(4), 1251–1273. https://doi.org/10.5194/cp-15-1251-2019
Thompson, D. M. et al. (2013). Coral-model comparison highlighting the role of salinity in long-term trends. PAGES Newsletter, 21(2), 60–61. https://doi.org/10.1029/2011GL048224
Thompson, D. M. et al. (2011). Comparison of observed and simulated tropical climate trends using a forward model of coral. Geophys. Res. Lett., 38, L14706. https://doi.org/10.1029/2011GL048224
Vaccaro, A. et al. (2021). Climate field completion via markov random fields: Application to the HadCRUT4.6 temperature dataset. Journal of Climate, 34(10), 4169–4188. https://doi.org/10.1175/JCLI-D-19-0814.1
Walter, R. M. et al. (2023). The CoralHydro2k database: a global, actively curated compilation of coral \(\delta^{18}\)O and Sr \(/\) Ca proxy records of tropical ocean hydrology and temperature for the Common Era. Earth System Science Data, 15(5), 2081–2116. https://doi.org/10.5194/essd-15-2081-2023
Wang, Jianghao et al. (2015). Fragility of reconstructed temperature patterns over the common era: Implications for model evaluation. Geophysical Research Letters, 42, 7162–7170. https://doi.org/10.1002/2015GL065265
Wang, J. et al. (2014). Evaluating climate field reconstruction techniques using improved emulations of real-world conditions. Climate of the Past, 10(1), 1–19. https://doi.org/10.5194/cp-10-1-2014
Yang, W. et al. (2024). Last millennium hurricane activity linked to endogenous climate variability. Nature Communications, 15(1), 816. https://doi.org/10.1038/s41467-024-45112-6
Zhu, F. et al. (2024). cfr (v2024.1.26): A python package for climate field reconstruction. Geoscientific Model Development, 17(8), 3409–3431. https://doi.org/10.5194/gmd-17-3409-2024
Zhu, Feng et al. (2023). A pseudoproxy emulation of the PAGES 2k database using a hierarchy of proxy system models. Scientific Data, 10(1), 624. https://doi.org/10.1038/s41597-023-02489-1
Zhu, Feng et al. (2022). A re-appraisal of the ENSO response to volcanism with paleoclimate data assimilation. Nature Communications, 13(1), 747. https://doi.org/10.1038/s41467-022-28210-1
Zhu, Feng et al. (2020). Resolving the differences in the simulated and reconstructed temperature response to volcanism. Geophysical Research Letters, 47(8), e2019GL086908. https://doi.org/10.1029/2019GL086908
Zhu, Feng et al. (2019). Climate models can correctly simulate the continuum of global-average temperature variability. Proceedings of the National Academy of Sciences, 116(18), 8728. https://doi.org/10.1073/pnas.1809959116