Articles | Volume 12, issue 4
https://doi.org/10.5194/essd-12-2971-2020
https://doi.org/10.5194/essd-12-2971-2020
Data description paper
 | 
20 Nov 2020
Data description paper |  | 20 Nov 2020

A Last Glacial Maximum forcing dataset for ocean modelling

Anne L. Morée and Jörg Schwinger

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Cited articles

Alexandre, A., Landais, A., Vallet-Coulomb, C., Piel, C., Devidal, S., Pauchet, S., Sonzogni, C., Couapel, M., Pasturel, M., Cornuault, P., Xin, J., Mazur, J.-C., Prié, F., Bentaleb, I., Webb, E., Chalié, F., and Roy, J.: The triple oxygen isotope composition of phytoliths as a proxy of continental atmospheric humidity: insights from climate chamber and climate transect calibrations, Biogeosciences, 15, 3223–3241, https://doi.org/10.5194/bg-15-3223-2018, 2018. 
Annan, J. D. and Hargreaves, J. C.: A new global reconstruction of temperature changes at the Last Glacial Maximum, Clim. Past, 9, 367–376, https://doi.org/10.5194/cp-9-367-2013, 2013. 
Bouttes, N., Paillard, D., Roche, D. M., Brovkin, V., and Bopp, L.: Last Glacial Maximum CO2 and δ13C successfully reconciled, Geophys. Res. Lett., 38, L02705, https://doi.org/10.1029/2010GL044499, 2011. 
Braconnot, P. and Kageyama, M.: Shortwave forcing and feedbacks in Last Glacial Maximum and Mid-Holocene PMIP3 simulations, Philos. T. Roy. Soc. A, 373, 20140424, https://doi.org/10.1098/rsta.2014.0424, 2015. 
Braconnot, P., Otto-Bliesner, B., Harrison, S., Joussaume, S., Peterchmitt, J.-Y., Abe-Ouchi, A., Crucifix, M., Driesschaert, E., Fichefet, Th., Hewitt, C. D., Kageyama, M., Kitoh, A., Laîné, A., Loutre, M.-F., Marti, O., Merkel, U., Ramstein, G., Valdes, P., Weber, S. L., Yu, Y., and Zhao, Y.: Results of PMIP2 coupled simulations of the Mid-Holocene and Last Glacial Maximum – Part 1: experiments and large-scale features, Clim. Past, 3, 261–277, https://doi.org/10.5194/cp-3-261-2007, 2007. 
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Short summary
This dataset consists of eight variables needed in ocean modelling and is made to support modelers of the Last Glacial Maximum (LGM; 21 000 years ago) ocean. The LGM is a time of specific interest for climate researchers. The data are based on the results of state-of-the-art climate models and are the best available estimate of these variables for the LGM. The dataset shows clear spatial patterns but large uncertainties and is presented in a way that facilitates applications in any ocean model.
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