Turner, Katherine 
ORCID: 0000-0003-1666-1690, Williams, Richard G ORCID: 0000-0002-3180-7558, Katavouta, Anna and Smith, Doug M
(2022)
Reconstructing upper ocean carbon variability using ARGO profiles and CMIP6 models.
Abstract
<jats:p>&lt;p&gt;Historically, ocean carbon content has been poorly sampled due to the logistical difficulties inherent in carbonate chemistry measurements. &amp;#160;As a result, global products of ocean carbon content observations have been restricted to calculate climatologies or long-term trends. Recent innovations with machine learning have provided for observational reconstructions of multidecadal and interannual carbon variability. In this work, we create a complementary method for reconstructing historical carbon variability by drawing upon the Ensemble Optimal Interpolation method used for reconstructing historical ocean heat and salinity &lt;sup&gt;[1-3]&lt;/sup&gt;. Ensemble Optimal Interpolation draws upon first-order relationships between variables and use covariances from model ensembles to propagate information from data-rich to data-sparse regions.&lt;/p&gt;&lt;p&gt;We test our method by conducting synthetic reconstructions of upper ocean carbon content using ARGO-style sampling distributions with CMIP6 ensemble covariance fields. Sensitivity tests of local carbon reconstructions suggest that around 50% of ocean carbon variability can be reconstructed using temperature and salinity measurements. Expanding the synthetic reconstructions to include irregular sampling consistent with ARGO profile locations results in a similar capacity to reconstruct ocean carbon variability, as the increased information provided from multiple sampling locations compensates for the propagation of errors within the CMIP6 covariance fields.&amp;#160; Our initial results indicate that the first-order relationships between temperature, salinity, and carbon can be used to describe a substantial proportion of historical carbon variability. In addition to showing promise for a new historical reconstruction complementary to current products, our work emphasises the important links between hydrographic and carbon variability for much of the global ocean.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;References&lt;/p&gt;&lt;p&gt;&lt;sup&gt;[1] &lt;/sup&gt;D. M. Smith and J. M. Murphy, 2007. &quot;An objective ocean temperature and salinity analysis using covariances from a global climate model,&quot; &lt;em&gt;JGR Oceans&lt;/em&gt;.&lt;/p&gt;&lt;p&gt;&lt;sup&gt;[2] &lt;/sup&gt;L. Cheng, K. E. Trenberth, J. T. Fasullo, T. Boyer, J. T. Abraham and J. Zhu, 2017. &quot;Improved estimates of ocean heat content from 1960 to 2015,&quot; &lt;em&gt;Science Advances&lt;/em&gt;.&lt;/p&gt;&lt;p&gt;&lt;sup&gt;[3] &lt;/sup&gt;L. Cheng, K. E. Trenberth, N. Gruber, J. P. Abraham, J. T. Fasullo, G. Li, M. E. Mann, X. Zhao and J. Zhu, 2020. &quot;Improved Estimates of Changes in Upper Ocean Salinity and the Hydrological Cycle,&quot; &lt;em&gt;Journal of Climate&lt;/em&gt;.&lt;/p&gt;</jats:p>
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | 14 Life Below Water, 13 Climate Action |
| Divisions: | Faculty of Science and Engineering > School of Environmental Sciences |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 09 Mar 2023 09:45 |
| Last Modified: | 20 Apr 2024 05:16 |
| DOI: | 10.5194/egusphere-egu22-8895 |
| Open Access URL: | https://doi.org/10.5194/egusphere-egu22-8895 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3168876 |
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