Articles | Volume 18, issue 9
https://doi.org/10.5194/gmd-18-2479-2025
https://doi.org/10.5194/gmd-18-2479-2025
Model description paper
 | 
05 May 2025
Model description paper |  | 05 May 2025

ZEMBA v1.0: an energy and moisture balance climate model to investigate Quaternary climate

Daniel F. J. Gunning, Kerim H. Nisancioglu, Emilie Capron, and Roderik S. W. van de Wal

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Cited articles

Abe-Ouchi, A., Saito, F., Kawamura, K., Raymo, M. E., Okuno, J., Takahashi, K., and Blatter, H.: Insolation-driven 100,000-year glacial cycles and hysteresis of ice-sheet volume, Nature, 500, 190–193, https://doi.org/10.1038/nature12374, 2013. a, b
Ahn, S., Khider, D., Lisiecki, L. E., and Lawrence, C. E.: A probabilistic Pliocene–Pleistocene stack of benthic δ18O using a profile hidden Markov model, Dyn. Stat. Clim. Syst., 2, dzx002, https://doi.org/10.1093/climsys/dzx002, 2017. a
Annan, J. D., Hargreaves, J. C., and Mauritsen, T.: A new global surface temperature reconstruction for the Last Glacial Maximum, Clim. Past, 18, 1883–1896, https://doi.org/10.5194/cp-18-1883-2022, 2022. a, b, c, d, e, f, g, h, i, j
Argus, D. F., Peltier, W. R., Drummond, R., and Moore, A. W.: The Antarctica component of postglacial rebound model ICE-6G_C (VM5a) based on GPS positioning, exposure age dating of ice thicknesses, and relative sea level histories, Geophys. J. Int., 198, 537–563, https://doi.org/10.1093/gji/ggu140, 2014. a, b, c
Balmes, K. A. and Fu, Q.: The diurnally-averaged aerosol direct radiative effect and the use of the daytime-mean and insolation-weighted-mean solar zenith angles, J. Quant. Spectrosc. Radiat. Transf., 257, 107363, https://doi.org/10.1016/j.jqsrt.2020.107363, 2020. a
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This work documents the first results from ZEMBA: an energy balance model of the climate system. The model is a computationally efficient tool designed to study the response of climate to changes in the Earth's orbit. We demonstrate that ZEMBA reproduces many features of the Earth's climate for both the pre-industrial period and the Earth's most recent cold extreme – the Last Glacial Maximum. We intend to develop ZEMBA further and investigate the glacial cycles of the last 2.5 million years.
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