Articles | Volume 16, issue 14
https://doi.org/10.5194/gmd-16-4283-2023
https://doi.org/10.5194/gmd-16-4283-2023
Model description paper
 | 
28 Jul 2023
Model description paper |  | 28 Jul 2023

TIMBER v0.1: a conceptual framework for emulating temperature responses to tree cover change

Shruti Nath, Lukas Gudmundsson, Jonas Schwaab, Gregory Duveiller, Steven J. De Hertog, Suqi Guo, Felix Havermann, Fei Luo, Iris Manola, Julia Pongratz, Sonia I. Seneviratne, Carl F. Schleussner, Wim Thiery, and Quentin Lejeune

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Cited articles

Alexeeff, S. E., Nychka, D., Sain, S. R., and Tebaldi, C.: Emulating mean patterns and variability of temperature across and within scenarios in anthropogenic climate change experiments, Climatic Change, 146, 319–333, https://doi.org/10.1007/s10584-016-1809-8, 2018. a
Benjamini, Y. and Hochberg, Y.: benjamini_hochberg1995, J. Roy. Stat. Soc. B, 57, 289–300, 1995. a
Beusch, L., Gudmundsson, L., and Seneviratne, S. I.: Emulating Earth system model temperatures with MESMER: from global mean temperature trajectories to grid-point-level realizations on land, Earth Syst. Dynam., 11, 139–159, https://doi.org/10.5194/esd-11-139-2020, 2020. a, b
Boisier, J. P., De Noblet-Ducoudré, N., Pitman, A. J., Cruz, F. T., Delire, C., Van Den Hurk, B. J., Van Der Molen, M. K., Mller, C., and Voldoire, A.: Attributing the impacts of land-cover changes in temperate regions on surface temperature and heat fluxes to specific causes: Results from the first LUCID set of simulations, J. Geophys. Res.-Atmos., 117, 1–16, https://doi.org/10.1029/2011JD017106, 2012. a
Boysen, L. R., Brovkin, V., Pongratz, J., Lawrence, D. M., Lawrence, P., Vuichard, N., Peylin, P., Liddicoat, S., Hajima, T., Zhang, Y., Rocher, M., Delire, C., Séférian, R., Arora, V. K., Nieradzik, L., Anthoni, P., Thiery, W., Laguë, M. M., Lawrence, D., and Lo, M.-H.: Global climate response to idealized deforestation in CMIP6 models, Biogeosciences, 17, 5615–5638, https://doi.org/10.5194/bg-17-5615-2020, 2020. a, b
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Short summary
Tree cover changes play a significant role in climate mitigation and adaptation. Their regional impacts are key in informing national-level decisions and prioritising areas for conservation efforts. We present a first step towards exploring these regional impacts using a simple statistical device, i.e. emulator. The emulator only needs to train on climate model outputs representing the maximal impacts of aff-, re-, and deforestation, from which it explores plausible in-between outcomes itself.