The distribution of precipitation and the spread in tropical upper tropospheric temperature trends in CMIP5/AMIP simulations
Abstract
Abstract Reconciling observations and simulations of tropical upper tropospheric temperature trends remains an important problem in climate science. Examining atmospheric models running over observed sea surface temperatures (SSTs), Flannaghan et al. (2014) show that this reconciliation is affected by the SST data set used and that a precipitation‐weighted SST (PSST) is valuable in explaining this result. Here we show that even for Coupled Model Intercomparison Project Phase 5 Atmospheric Model Intercomparison Project (CMIP5 AMIP) simulations forced with identical SSTs, tropical upper tropospheric temperature trends across models (and between ensemble members) show a substantial spread (standard deviation ∼10% of the average trend). About 60% of this spread between ensemble means, as well as deviations from the ensemble means, can be explained by PSST calculated from the time‐evolving precipitation in each model run. Both PSST and atmospheric temperature trends show statistical evidence for systematic differences between models. We conclude that the response of precipitation patterns to changes in SST patterns is a significant source of uncertainty for tropical temperature trends.
- Authors:
-
- Program in Atmospheric and Oceanic Sciences Princeton University Princeton New Jersey USA, Department of Geosciences Princeton University Princeton New Jersey USA
- Program in Atmospheric and Oceanic Sciences Princeton University Princeton New Jersey USA
- Geophysical Fluid Dynamics Laboratory Princeton New Jersey USA
- Publication Date:
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1402303
- Grant/Contract Number:
- SC0006841
- Resource Type:
- Publisher's Accepted Manuscript
- Journal Name:
- Geophysical Research Letters
- Additional Journal Information:
- Journal Name: Geophysical Research Letters Journal Volume: 42 Journal Issue: 14; Journal ID: ISSN 0094-8276
- Publisher:
- American Geophysical Union (AGU)
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Fueglistaler, S., Radley, C., and Held, I. M. The distribution of precipitation and the spread in tropical upper tropospheric temperature trends in CMIP5/AMIP simulations. United States: N. p., 2015.
Web. doi:10.1002/2015GL064966.
Fueglistaler, S., Radley, C., & Held, I. M. The distribution of precipitation and the spread in tropical upper tropospheric temperature trends in CMIP5/AMIP simulations. United States. https://doi.org/10.1002/2015GL064966
Fueglistaler, S., Radley, C., and Held, I. M. Tue .
"The distribution of precipitation and the spread in tropical upper tropospheric temperature trends in CMIP5/AMIP simulations". United States. https://doi.org/10.1002/2015GL064966.
@article{osti_1402303,
title = {The distribution of precipitation and the spread in tropical upper tropospheric temperature trends in CMIP5/AMIP simulations},
author = {Fueglistaler, S. and Radley, C. and Held, I. M.},
abstractNote = {Abstract Reconciling observations and simulations of tropical upper tropospheric temperature trends remains an important problem in climate science. Examining atmospheric models running over observed sea surface temperatures (SSTs), Flannaghan et al. (2014) show that this reconciliation is affected by the SST data set used and that a precipitation‐weighted SST (PSST) is valuable in explaining this result. Here we show that even for Coupled Model Intercomparison Project Phase 5 Atmospheric Model Intercomparison Project (CMIP5 AMIP) simulations forced with identical SSTs, tropical upper tropospheric temperature trends across models (and between ensemble members) show a substantial spread (standard deviation ∼10% of the average trend). About 60% of this spread between ensemble means, as well as deviations from the ensemble means, can be explained by PSST calculated from the time‐evolving precipitation in each model run. Both PSST and atmospheric temperature trends show statistical evidence for systematic differences between models. We conclude that the response of precipitation patterns to changes in SST patterns is a significant source of uncertainty for tropical temperature trends.},
doi = {10.1002/2015GL064966},
journal = {Geophysical Research Letters},
number = 14,
volume = 42,
place = {United States},
year = {Tue Jul 21 00:00:00 EDT 2015},
month = {Tue Jul 21 00:00:00 EDT 2015}
}
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