{"refrec":{"BRefID":396614,"RR":"<b>Wu, Z.; Lu, W.; Roobaert, A.; Song, L.; Yan, X.-H.; Cai, W.-J.</b> (2025). A machine-learning reconstruction of sea surface <i>p</i>CO<sub>2</sub> in the North American Atlantic Coastal Ocean Margin from 1993 to 2021. <i>ESSD 17(1)</i>: 43-63. <a href=\"https://dx.doi.org/10.5194/essd-17-43-2025\" target=\"_blank\">https://dx.doi.org/10.5194/essd-17-43-2025</a>","BEntID":394402,"PublicFlag":1,"CheckedFlag":1,"wosflag":1,"vabbflag":0,"RefStringPartII":". <i>ESSD 17(1)</i>: 43-63. <a href=\"https://dx.doi.org/10.5194/essd-17-43-2025\" target=\"_blank\">https://dx.doi.org/10.5194/essd-17-43-2025</a>","DocTypID":8,"DocType":"Journal article","MarineFlag":1,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Wu, Z.; Lu, W.; Roobaert, A.; Song, L.; Yan, X.-H.; Cai, W.-J.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Wu, Z. <i>et al.</i>","Englishabstract":"Insufficient spatiotemporal coverage of observations of the surface partial pressure of CO<sub>2</sub> (<i>p</i>CO<sub>2</sub>) has hindered precise carbon cycle studies in coastal oceans and justifies the development of spatially and temporally continuous <i>p</i>CO<sub>2</sub> data products. Earlier <i>p</i>CO<sub>2</sub> products have difficulties in capturing the heterogeneity of regional variations and decadal trends of <i>p</i>CO<sub>2</sub> in the North American Atlantic Coastal Ocean Margin (NAACOM). This study developed a regional reconstructed <i>p</i>CO<sub>2</sub> product for the NAACOM (Reconstructed Coastal Acidification Database-<i>p</i>CO<sub>2</sub>, or ReCAD-NAACOM-<i>p</i>CO<sub>2</sub>) using a two-step approach combining random forest regression and linear regression. The product provides monthly <i>p</i>CO<sub>2</sub> data at 0.25° spatial resolution from 1993 to 2021, enabling investigation of regional spatial differences, seasonal cycles, and decadal changes in <i>p</i>CO<sub>2</sub>. The observation-based reconstruction was trained using Surface Ocean CO<sub>2</sub> Atlas (SOCAT) observations as observational values, with various satellite-derived and reanalysis environmental variables known to control sea surface <i>p</i>CO<sub>2</sub> as model inputs. The product shows high accuracy during the model training, validation, and independent test phases, demonstrating robustness and a capability to accurately reconstruct <i>p</i>CO<sub>2</sub> in regions or periods lacking direct observational data. Compared with all the observation samples from SOCAT, the <i>p</i>CO<sub>2</sub> product yields a determination coefficient of 0.92, a root-mean-square error of 12.70 µatm, and an accumulative uncertainty of 23.25 µatm. The ReCAD-NAACOM-<i>p</i>CO<sub>2</sub> product demonstrates its capability to resolve seasonal cycles, regional-scale variations, and decadal trends of <i>p</i>CO<sub>2</sub> along the NAACOM. This new product provides reliable <i>p</i>CO<sub>2</sub> data for more precise studies of coastal carbon dynamics in the NAACOM region. The dataset is publicly accessible at <a href=\"https://doi.org/10.5281/zenodo.14038561\">https://doi.org/10.5281/zenodo.14038561</a> (Wu et al., 2024a) and will be updated regularly.","AbstractOtherLang":null,"BibLvlCode":"AS","StandardTitle":"A machine-learning reconstruction of sea surface <i>p</i>CO<sub>2</sub> in the North American Atlantic Coastal Ocean Margin from 1993 to 2021","OrigTitleLangCode":"en","OrigTitleLangCodeExtended":"eng","OrigTitleLangID":15,"DateLastModified":{"date":"2026-04-20 01:33:13.080831","timezone_type":1,"timezone":"+02:00"},"UserAccessRight":null,"UserAccID":null,"AuthorKeywords":"CO2 FLUXES;GLOBAL COASTAL;CLIMATOLOGY;VARIABILITY;SEASONALITY;PRODUCT;MODEL;WATER;GULF","OtherDescriptors":null,"Notes":null,"AnaPub":2025,"MonPub":null,"DateUpdate":"2025-09-26","DateCreate":"2024-11-12","SecASFANote":null,"ConfID":null,"PeerRev":1,"VlizCoreFlag":1,"WoScode":"WOS:001392607000001","VABBcode":null,"OpenAcc":1,"DOI":"10.5194/essd-17-43-2025"},"refs":null,"anarec":{"AnaID":396614,"PubliDate":2025,"Pagination":"43-63","XtraPublOfAnaID":null,"ISBN":null,"Volume":"17","Issue":"1","BRefMon":null,"BRefMonRR":null,"BRefXtra":null,"BRefXtraRR":null,"SerBRefID":229338,"SerRR":"Earth System Science Data. 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