A Global Paired Argo Dataset for Ocean Thermal and Salinity Responses to Tropical Cyclones (2000–2024)
Abstract. This paper presents a global paired Argo dataset documenting the upper-ocean temperature and salinity responses to tropical cyclones (TCs) during 2000–2024. The dataset was built by combining the International Best Track Archive for Climate Stewardship (IBTrACS, v04r01) with the Global Ocean Argo Scatter Dataset (Version 3.0) provided by the China Argo Real-time Data Center. On top of the original Argo quality-control flags, we applied a strict secondary screening that retained only profiles with good quality flags for temperature, salinity, and pressure at every vertical level and with a maximum sampling depth of at least 1900 m. Each TC location was first matched to candidate floats within an inclusive 1000 km search envelope, with the archived storm-relative coordinates allowing users to apply narrower distance thresholds for specific analyses. The two profiles in each pair were further required to lie within 50 km of each other to suppress horizontal mesoscale aliasing. All retained profiles were linearly interpolated onto 56 standard depth levels from the surface to 2000 m and rotated into a storm-relative Cartesian frame in which the TC center is the origin and the translation direction is aligned with the positive Y axis. The final product contains 3164876 high-quality paired records—2747731 in the Northern Hemisphere and 417145 in the Southern Hemisphere—archived as six self-describing netCDF files separated by hemisphere and time period. Spatial, vertical, and temporal composites confirm that the dataset reproduces the canonical upper-ocean response to TCs, including the hemispheric mirror asymmetry of cross-track surface cooling, the concentration of the strongest thermal anomalies within the upper ~200 m, and a peak sea surface cooling about 2.5 d after passage followed by a 1–2 week recovery. The salinity response is weaker and less spatially coherent, reflecting the competing effects of rainfall freshening, vertical mixing, and upwelling. By providing background-field profiles, response-field profiles, and their precomputed differences in a single analysis-ready record, this dataset substantially reduces the preprocessing burden for studies of TC–ocean interaction, upper-ocean heat and salt budgets, mixed-layer and near-inertial processes, and the evaluation of coupled ocean–atmosphere models. The dataset and associated data-generation code are available at https://doi.org/10.6084/m9.figshare.32820563 (Wang et al., 2026b).
This manuscript presents a global paired Argo dataset describing upper-ocean temperature and salinity responses to tropical cyclones (TCs) during 2000–2024. By integrating IBTrACS tropical cyclone best-track information with quality-controlled Argo observations, the authors construct an analysis-ready dataset containing paired background-field and response-field profiles, storm-relative coordinates, and precomputed temperature and salinity anomalies.
The dataset provides a structured resource for investigating TC-induced ocean responses based on long-term Argo observations. The manuscript describes the data sources, quality-control procedures, profile pairing strategy, coordinate transformation, and dataset structure in detail. The technical validation demonstrates that the dataset captures several commonly reported features of TC-induced upper-ocean responses, including asymmetric surface cooling patterns and temporal evolution after storm passage.
However, several aspects of the dataset construction and validation require further clarification before publication. In particular, the assumptions associated with the paired-profile approach, the definition of background and response fields, the representativeness of the retained observations, and the quantitative assessment of data uncertainty need to be further addressed. In addition, clearer illustrations of key data-processing procedures and more comprehensive statistical analyses of dataset quality would improve the transparency and reliability of the released product.
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