the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 22 Oct 2026
Argo Trajectories Reveal Changing Core-Peripheral Partitioning of Gulf Stream Transport
Abstract. Long-term Gulf Stream transport estimates diverge, partly because existing observing systems sample different locations and cross-stream extents. Most studies assess transport at fixed sections, leaving changes in the core and surrounding flow unresolved. Here, we develop a Core-Peripheral Transport Decomposition Method using Argo float trajectories from 2003 to 2024. We identify the mean core band from velocity gradients and quantify core-band and peripheral transport from annual mean time series. Core-band transport shows no significant trend, while peripheral transport declines at −4.99 Sv yr-1 before 2017 and recovers at +20.01 Sv yr-1 afterward. The core fraction of the fixed-latitude total rises from approximately 33 % to more than 100 % in 2015 and 2019, before decreasing to 26 % at the end of the record. Validation against shipboard ADCP observations yields significant interannual correlation (R = 0.667). These results reveal changing cross-stream transport partitioning and provide an observational basis for interpreting divergent Gulf Stream transport estimates across observing systems.
- Preprint
(3243 KB) - Metadata XML
-
Supplement
(394 KB) - BibTeX
- EndNote
Status: open (until 17 Dec 2026)
- RC1: 'Comment on egusphere-2026-6294', Anonymous Referee #1, 09 Nov 2026 reply
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 205 | 86 | 28 | 319 | 54 | 31 | 29 |
- HTML: 205
- PDF: 86
- XML: 28
- Total: 319
- Supplement: 54
- BibTeX: 31
- EndNote: 29
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Review of 'Argo trajectories reveal changing core-peripheral partitioning of Gulf Stream transprot' by Luo et al.
Review:
This submission has zero merit and should be summarily rejected from this and any other scientific journal.
The analysis is fatally flawed. While it is true that Argo floats provide estimates of ocean currents at the surface and at their parking depths, this information is not sufficient to meaningfully infer the full-depth profiles of ocean currents required to estimate transport. This fact does not deter the authors, who unabashedly extrapolate from two points to full-depth profiles, claiming a vertical resolution of 50 m (Fig. 2). It gets worse. Argo floats are nominally spaced about every 3° in the global ocean; that is, some 300-km apart on average. They profile once every 10 days. Yet the authors claim to be able to make annual sections with 100-m cross-section resolution (Fig. 2) and longitudinal separation between sections of less than 20 km (100 sections over 20° of longitude, line 113). The authors claim to use approximately 4,400 subsurface velocity estimates covering a 20-year period. That is about 220 data points per year or barely 2 data points for each of their 100 sections per year. It is simply preposterous that the authors claim to be able to define temporal variability or to be able to partition transport in any way.
Though no more reason should be needed to reject this submission, here are a few more:
- It lacks any serious error analysis (which would reveal the nonsensical nature of the method).
- The introduction inaccurately represents prior work. As the authors would know had they read Volkov et al. (2024), Piecuch & Beal's inference of a weakening Gulf Stream transport relied on incorrectly processed data; upon correction, the Gulf Stream transport in the Florida Strait is stable over the instrumental record.
- Fig. 5, which purports to show the Gulf Stream velocity structure, bears no resemblance to any of the countless synoptic or mean transects across the Gulf Stream in the literature.
- The shipboard ADCP data used in Fig. 7 is clearly from the MV Oleander. The text claims (Line 215 and 295) that these data were obtained from the University of Hawaii Sea Level Center. This is obviously wrong; the UH Sea Level Center only provides tide gauge data. More likely, the data were found via the University of Hawaii's Currents Group, which is involved in the Oleander sampling. This sort of gross inaccuracy in data attribution could easily be due to use of generative AI; it would not surprise me if much of the analysis/manuscript results from unsupervised use of AI.
Ideally, this submission would never see the light of day. It is that bad. Unfortunately, the submission is already public and has been picked up by the ubiquitous AI agents. The only upside of it having been submitted to this journal is that this review will be permanently and publicly associated with the submission, hopefully preventing this from ever being published as human-vetted scientific research.