Observational Limitations to the Emergence of Climate Signals

Abstract Using model projections to study the emergence of observable climate signals presumes omniscient knowledge about the climate system. In reality, observational knowledge suffers from data quality and availability issues, for instance data gaps, changes in instrumentation, issues due to gridd...

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Main Authors: Louis Rivoire, Marianna Linz, Jingyuan Li
Format: Article
Language:English
Published: Wiley 2024-07-01
Series:Geophysical Research Letters
Subjects:
Online Access:https://doi.org/10.1029/2024GL109638
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author Louis Rivoire
Marianna Linz
Jingyuan Li
author_facet Louis Rivoire
Marianna Linz
Jingyuan Li
author_sort Louis Rivoire
collection DOAJ
description Abstract Using model projections to study the emergence of observable climate signals presumes omniscient knowledge about the climate system. In reality, observational knowledge suffers from data quality and availability issues, for instance data gaps, changes in instrumentation, issues due to gridding and retrieval algorithms. Overlooking such deficiencies leads to misrepresentations of the time of emergence (ToE). We introduce a new definition of ToE that accounts for observational limitations, and show that significant corrections to the ToE may be necessary to achieve the same statistical confidence as would be afforded by omniscient knowledge. We also show how our method can inform future observational needs and observing systems design.
format Article
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institution OA Journals
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1944-8007
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spelling doaj-art-e65d1328ca31486699fb6154e6e282dd2025-08-20T01:51:55ZengWileyGeophysical Research Letters0094-82761944-80072024-07-015114n/an/a10.1029/2024GL109638Observational Limitations to the Emergence of Climate SignalsLouis Rivoire0Marianna Linz1Jingyuan Li2Department of Earth and Planetary Sciences Harvard University Cambridge MA USADepartment of Earth and Planetary Sciences Harvard University Cambridge MA USAScripps Institution of Oceanography University of California at San Diego La Jolla CA USAAbstract Using model projections to study the emergence of observable climate signals presumes omniscient knowledge about the climate system. In reality, observational knowledge suffers from data quality and availability issues, for instance data gaps, changes in instrumentation, issues due to gridding and retrieval algorithms. Overlooking such deficiencies leads to misrepresentations of the time of emergence (ToE). We introduce a new definition of ToE that accounts for observational limitations, and show that significant corrections to the ToE may be necessary to achieve the same statistical confidence as would be afforded by omniscient knowledge. We also show how our method can inform future observational needs and observing systems design.https://doi.org/10.1029/2024GL109638time of emergencelong‐term trendsclimate trendstrend detectionobservational uncertaintiesinternal variability
spellingShingle Louis Rivoire
Marianna Linz
Jingyuan Li
Observational Limitations to the Emergence of Climate Signals
Geophysical Research Letters
time of emergence
long‐term trends
climate trends
trend detection
observational uncertainties
internal variability
title Observational Limitations to the Emergence of Climate Signals
title_full Observational Limitations to the Emergence of Climate Signals
title_fullStr Observational Limitations to the Emergence of Climate Signals
title_full_unstemmed Observational Limitations to the Emergence of Climate Signals
title_short Observational Limitations to the Emergence of Climate Signals
title_sort observational limitations to the emergence of climate signals
topic time of emergence
long‐term trends
climate trends
trend detection
observational uncertainties
internal variability
url https://doi.org/10.1029/2024GL109638
work_keys_str_mv AT louisrivoire observationallimitationstotheemergenceofclimatesignals
AT mariannalinz observationallimitationstotheemergenceofclimatesignals
AT jingyuanli observationallimitationstotheemergenceofclimatesignals