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 propertie...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2019-08-01
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| Series: | Geophysical Research Letters |
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| Online Access: | https://doi.org/10.1029/2019GL082442 |
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| author | Alex G. Libardoni Chris E. Forest Andrei P. Sokolov Erwan Monier |
| author_facet | Alex G. Libardoni Chris E. Forest Andrei P. Sokolov Erwan Monier |
| author_sort | Alex G. Libardoni |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-1998bce7d15549f8a9c63f9bafb519c6 |
| institution | OA Journals |
| issn | 0094-8276 1944-8007 |
| language | English |
| publishDate | 2019-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geophysical Research Letters |
| spelling | doaj-art-1998bce7d15549f8a9c63f9bafb519c62025-08-20T02:12:20ZengWileyGeophysical Research Letters0094-82761944-80072019-08-014616100001000710.1029/2019GL082442Underestimating Internal Variability Leads to Narrow Estimates of Climate System PropertiesAlex G. Libardoni0Chris E. Forest1Andrei P. Sokolov2Erwan Monier3Department of Meteorology and Atmospheric Science Pennsylvania State University University Park PA USADepartment of Meteorology and Atmospheric Science Pennsylvania State University University Park PA USAJoint Program on the Science and Policy of Global Change Massachusetts Institute of Technology Cambridge MA USAJoint Program on the Science and Policy of Global Change Massachusetts Institute of Technology Cambridge MA USAAbstract 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.https://doi.org/10.1029/2019GL082442climate sensitivityuncertainty quantificationcalibrating global net radiative forcinginternal climate variabilityclimate/Earth system feedbackscalibrating transient climate response |
| spellingShingle | Alex G. Libardoni Chris E. Forest Andrei P. Sokolov Erwan Monier Underestimating Internal Variability Leads to Narrow Estimates of Climate System Properties Geophysical Research Letters climate sensitivity uncertainty quantification calibrating global net radiative forcing internal climate variability climate/Earth system feedbacks calibrating transient climate response |
| title | Underestimating Internal Variability Leads to Narrow Estimates of Climate System Properties |
| title_full | Underestimating Internal Variability Leads to Narrow Estimates of Climate System Properties |
| title_fullStr | Underestimating Internal Variability Leads to Narrow Estimates of Climate System Properties |
| title_full_unstemmed | Underestimating Internal Variability Leads to Narrow Estimates of Climate System Properties |
| title_short | Underestimating Internal Variability Leads to Narrow Estimates of Climate System Properties |
| title_sort | underestimating internal variability leads to narrow estimates of climate system properties |
| topic | climate sensitivity uncertainty quantification calibrating global net radiative forcing internal climate variability climate/Earth system feedbacks calibrating transient climate response |
| url | https://doi.org/10.1029/2019GL082442 |
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