edu.ucar.opensky::articles:26073 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-24T19:58:38.502134 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d7t43z0p https://doi.org/10.5281/zenodo.7199961 https Related Dataset #1 Internal variability and forcing influence model-satellite differences in the rate of tropical tropospheric warming Internal variability and forcing influence model-satellite differences in the rate of tropical tropospheric warming 2022-11-22T00:00:00Z publication https://n2t.org/ark:/85065/d7t43z0p https://doi.org/10.1073/pnas.2209431119 Po-Chedley, S. author Fasullo, John T. author Siler, N. author Labe, Z. M. author Barnes, E. A. author Bonfils, C. J. W. author Santer, B. D. author UCAR/NCAR - Library publisher Climate-model simulations exhibit approximately two times more tropical tropospheric warming than satellite observations since 1979. The causes of this difference are not fully understood and are poorly quantified. Here, we apply machine learning to relate the patterns of surface-temperature change to the forced and unforced components of tropical tropospheric warming. This approach allows us to disentangle the forced and unforced change in the model-simulated temperature of the midtroposphere (TMT). In applying the climate-model-trained machine-learning framework to observations, we estimate that external forcing has produced a tropical TMT trend of 0.25 +/- 0.08 K.decade(-1) between 1979 and 2014, but internal variability has offset this warming by 0.07 +/- 0.07 K.decade(-1). Using the Community Earth System Model version 2 (CESM2) large ensemble, we also find that a discontinuity in the variability of prescribed biomass-burning aerosol emissions artificially enhances simulated tropical TMT change by 0.04 K.decade(-1). The magnitude of this aerosol-forcing bias will vary across climate models, but since the latest generation of climate models all use the same emissions dataset, the bias may systematically enhance climate-model trends over the satellite era. Our results indicate that internal variability and forcing uncertainties largely explain differences in satellite-versus-model warming and are important considerations when evaluating climate models. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. None eng geoscientificInformation