A framework for reconstructing marine heatwaves from individual foraminifera in sedimentary archives

Marine heatwaves (MHWs) are warm sea surface temperature (SST) anomalies with substantial ecological and economic consequences. Observations of MHWs are based on relatively short instrumental records, which limit the ability to forecast these events on decadal and longer timescales. Paleoclimate rec...

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Published in:Frontiers in Marine Science
Main Authors: Casey Saenger, Carlos Jimenez-Diaz, Alexander Gagnon, Alan Mix, Andrew Ross, Tongtong Xu
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-10-01
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fmars.2024.1321254/full
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author Casey Saenger
Carlos Jimenez-Diaz
Alexander Gagnon
Alan Mix
Andrew Ross
Tongtong Xu
author_facet Casey Saenger
Carlos Jimenez-Diaz
Alexander Gagnon
Alan Mix
Andrew Ross
Tongtong Xu
author_sort Casey Saenger
collection DOAJ
container_title Frontiers in Marine Science
description Marine heatwaves (MHWs) are warm sea surface temperature (SST) anomalies with substantial ecological and economic consequences. Observations of MHWs are based on relatively short instrumental records, which limit the ability to forecast these events on decadal and longer timescales. Paleoclimate reconstructions can extend the observational record and help to evaluate model performance under near future conditions, but paleo-MHW reconstructions have received little attention, primarily because marine sediments lack the temporal resolution to record short-lived events. Individual foraminifera analysis (IFA) of paleotemperature proxies presents an intriguing opportunity to reconstruct past MHW variability if strong relationships exist between SST distributions and MHW metrics. Here, we describe a method to test this idea by systematically evaluating relationships between MHW metrics and SST distributions that mimic IFA data using a 2000-member linear inverse model (LIM) ensemble. Our approach is adaptable and allows users to define MHWs based on multiple duration and intensity thresholds and to model seasonal biases in five different foraminifera species. It also allows uncertainty in MHW reconstructions to be calculated for a given number of IFA measurements. An example application of our method at 12 north Pacific locations suggests that the cumulative intensity of short-duration, low-intensity MHWs is the strongest target for reconstruction, but that the error on reconstructions will rely heavily on sedimentation rate and the number of foraminifera analyzed. This is evident when a robust transfer function is applied to new core-top oxygen isotope data from 37 individual Globigerina bulloides at a site with typical marine sedimentation rates. In this example application, paleo-MHW reconstructions have large uncertainties that hamper comparisons to observational data. However, additional tests demonstrate that our approach has considerable potential to reconstruct past MHW variability at high sedimentation rate sites where hundreds of foraminifera can be analyzed.
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spelling doaj-art-a9c66dab8a3a43c5a3019d6d5e7900a42025-08-20T00:26:48ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452024-10-011110.3389/fmars.2024.13212541321254A framework for reconstructing marine heatwaves from individual foraminifera in sedimentary archivesCasey Saenger0Carlos Jimenez-Diaz1Alexander Gagnon2Alan Mix3Andrew Ross4Tongtong Xu5Department of Geology and Program in Marine and Coastal Science, Western Washington University, Bellingham, WA, United StatesDepartment of Geology and Program in Marine and Coastal Science, Western Washington University, Bellingham, WA, United StatesSchool of Oceanography, University of Washington, Seattle, WA, United StatesCollege of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR, United StatesCollege of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR, United StatesNational Oceanographic and Atmospheric Administration, Physical Sciences Laboratory, Boulder, CO, United StatesMarine heatwaves (MHWs) are warm sea surface temperature (SST) anomalies with substantial ecological and economic consequences. Observations of MHWs are based on relatively short instrumental records, which limit the ability to forecast these events on decadal and longer timescales. Paleoclimate reconstructions can extend the observational record and help to evaluate model performance under near future conditions, but paleo-MHW reconstructions have received little attention, primarily because marine sediments lack the temporal resolution to record short-lived events. Individual foraminifera analysis (IFA) of paleotemperature proxies presents an intriguing opportunity to reconstruct past MHW variability if strong relationships exist between SST distributions and MHW metrics. Here, we describe a method to test this idea by systematically evaluating relationships between MHW metrics and SST distributions that mimic IFA data using a 2000-member linear inverse model (LIM) ensemble. Our approach is adaptable and allows users to define MHWs based on multiple duration and intensity thresholds and to model seasonal biases in five different foraminifera species. It also allows uncertainty in MHW reconstructions to be calculated for a given number of IFA measurements. An example application of our method at 12 north Pacific locations suggests that the cumulative intensity of short-duration, low-intensity MHWs is the strongest target for reconstruction, but that the error on reconstructions will rely heavily on sedimentation rate and the number of foraminifera analyzed. This is evident when a robust transfer function is applied to new core-top oxygen isotope data from 37 individual Globigerina bulloides at a site with typical marine sedimentation rates. In this example application, paleo-MHW reconstructions have large uncertainties that hamper comparisons to observational data. However, additional tests demonstrate that our approach has considerable potential to reconstruct past MHW variability at high sedimentation rate sites where hundreds of foraminifera can be analyzed.https://www.frontiersin.org/articles/10.3389/fmars.2024.1321254/fullmarine heatwavespaleoclimatepaleoceanographyplanktic foraminiferaindividual foraminifera analysislinear inverse model
spellingShingle Casey Saenger
Carlos Jimenez-Diaz
Alexander Gagnon
Alan Mix
Andrew Ross
Tongtong Xu
A framework for reconstructing marine heatwaves from individual foraminifera in sedimentary archives
marine heatwaves
paleoclimate
paleoceanography
planktic foraminifera
individual foraminifera analysis
linear inverse model
title A framework for reconstructing marine heatwaves from individual foraminifera in sedimentary archives
title_full A framework for reconstructing marine heatwaves from individual foraminifera in sedimentary archives
title_fullStr A framework for reconstructing marine heatwaves from individual foraminifera in sedimentary archives
title_full_unstemmed A framework for reconstructing marine heatwaves from individual foraminifera in sedimentary archives
title_short A framework for reconstructing marine heatwaves from individual foraminifera in sedimentary archives
title_sort framework for reconstructing marine heatwaves from individual foraminifera in sedimentary archives
topic marine heatwaves
paleoclimate
paleoceanography
planktic foraminifera
individual foraminifera analysis
linear inverse model
url https://www.frontiersin.org/articles/10.3389/fmars.2024.1321254/full
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