@article{1a3ea2ab082d4d1f9b0119357dc6e23b,
title = "Underestimating Internal Variability Leads to Narrow Estimates of Climate System Properties",
abstract = "Probabilistic estimates of climate system properties often rely on the comparison of model simulations to observed temperature records and an estimate of the internal climate variability. In this study, we investigate the sensitivity of probability distributions for climate system properties in the Massachusetts Institute of Technology Earth System Model to the internal variability estimate. In particular, we derive probability distributions using the internal variability extracted from 25 different Coupled Model Intercomparison Project Phase 5 models. We further test the sensitivity by pooling variability estimates from models with similar characteristics. We find the distributions to be highly sensitive when estimating the internal variability from a single model. When merging the variability estimates across multiple models, the distributions tend to converge to a wider distribution for all properties. This suggests that using a single model to approximate the internal climate variability produces distributions that are too narrow and do not fully represent the uncertainty in the climate system property estimates.",
author = "Libardoni, {Alex G.} and Forest, {Chris E.} and Sokolov, {Andrei P.} and Erwan Monier",
note = "Funding Information: This work was supported by U.S. Department of Energy (DOE), Office of Science under Award DE-FG02-94ER61937 and other government, industry, and foundation sponsors of the MIT Joint Program on the Science and Policy of Global Change. For a complete list of sponsors and U.S. government funding sources, see http://globalchange.mit.edu/sponsors/current. This research was partially supported by the National Science Foundation (NSF) through the NSF Cooperative Agreement GEO-1240507. We acknowledge the World Climate Research Program's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups listed in the supporting information included with this paper for producing and making available their model output. For CMIP the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. A. G. L. also recognizes the valuable discussions and suggestions made by K. Davis, K. Keller, and R. Najjar in the development of this work. The model data will be stored and available at http://www.datacommons.psu.edu/ or directly at https://doi.org/10.26208/f3x1-pt27 website. Publisher Copyright: {\textcopyright}2019. The Authors.",
year = "2019",
month = aug,
day = "28",
doi = "10.1029/2019GL082442",
language = "English (US)",
volume = "46",
pages = "10000--10007",
journal = "Geophysical Research Letters",
issn = "0094-8276",
publisher = "American Geophysical Union",
number = "16",
}