EGU2020-3631, updated on 09 Jan 2024
https://doi.org/10.5194/egusphere-egu2020-3631
EGU General Assembly 2020
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

The vertical profile of tropical temperature trends: Persistent model biases in the context of forced and internal variability

Dann Mitchell1, Eunice Lo1, William Seviour1, and Lorenzo Polvani2
Dann Mitchell et al.
  • 1Cabot Institute for the Environment, and School of Geographical Sciences, University of Bristol, Bristol, UK (d.m.mitchell@bristol.ac.uk)
  • 2Department of Applied Physics & Applied Mathematics, and Lamont-Doherty Earth Observatory, Columbia University, New York, NY USA

Tropospheric and stratospheric tropical temperature trends in recent decades have been notoriously hard to simulate using climate models, notably in the upper troposphere.  Aside from the warming signal itself, this has broader implications, e.g. atmospheric circulation trends depend on latitudinal temperature gradients. In this study, tropical temperature trends in the CMIP6 models are examined, from 1979 to 2014, and contrasted with trends from the RICH/RAOBCORE radiosondes, and the ERA5/5.1 reanalysis.  Confirming previous studies, we find considerable warming biases in the CMIP6 modeled trends, and show that these biases are linked to biases in surface temperature (the models warm too much).  We also uncover previously undocumented biases in the lower-middle stratosphere: the CMIP6 models appear unable to capture the time evolution of stratospheric cooling, which is non-monotonic owing to the Montreal Protocol. This troposphere-warming, stratospheric-cooling fingerprint of climate change is therefore not well captured in CMIP6 models. Finally, we quantify the relative roles of individual climate forcings in tropspheric and stratospheric temperatures, including that of internal variability.

How to cite: Mitchell, D., Lo, E., Seviour, W., and Polvani, L.: The vertical profile of tropical temperature trends: Persistent model biases in the context of forced and internal variability, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3631, https://doi.org/10.5194/egusphere-egu2020-3631, 2020.