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About this collection

Extent

1 digital object.

Cite This Work

Lang, Sarah E.; Omand, Melissa M.; Lenain, Luc (2025). Data from: Airborne remote sensing of concurrent submesoscale dynamics and phytoplankton. UC San Diego Library Digital Collections. https://doi.org/10.6075/J0RN386Z

Description

This archive contains the code and data needed to generate the figures in the publication: "Airborne remote sensing of concurrent submesoscale dynamics and phytoplankton" (Lang, Sarah E; Omand, Melissa M; Lenain, Luc). In this study, we present airborne observations pairing snapshots of sub-kilometer ocean velocities and their derivatives (i.e. vorticity, divergence, and strain) with concurrent ocean color and sea surface temperature from an airborne instrument package called the Modular Aerial Sensing System (SIO). We developed airborne proxies of chlorophyll-a and particulate organic carbon, which explained about 70.7% and 65.6% of in situ variability without the need for atmospheric correction, suggesting that MASS can detect shifts in phytoplankton distributions. We also explored relationships between concurrently observed vorticity, divergence, strain, sea surface temperature, chlorophyll-a, and hyperspectral variables to illuminate the submesoscale processes that alter phytoplankton distributions. Data presented was collected as part of the Submesoscale Ocean Dynamics Experiment (S-MODE).

Date Collected

• 2021-10-29 to 2021-10-30

Date Issued

• 2025

Authors

• Lang, Sarah E.
• Lenain, Luc
• Omand, Melissa M.

Analyst

• Lang, Sarah E.

Thesis Advisor

• Omand, Melissa M.

Funding

This work was supported by NASA awards to M. Omand 80NSSC19K1037 and L. Lenain 80NSSC19K1688, with student support for S. Lang from the NASA Rhode Island Space Grant Consortium (AWD11155).

Geographic

• Global

Topics

• Airborne remote sensing
• Earth sciences
• Hyperspectral ocean color
• Ocean velocities
• Oceanography
• Sea surface temperature
• Submesoscale dynamics

Formats

View formats within this collection

• data
• text

Language

• English

Identifier

Identifier: Luc Lenain: https://orcid.org/0000-0001-9808-1563

Identifier: Melissa M. Omand: https://orcid.org/0000-0001-6928-9736

Identifier: Sarah E. Lang: https://orcid.org/0000-0002-8334-7485

Related Resources

Source data

• EUMETSAT Data Store for download of Sentinel-3 OLCI Level-2 (Full Resolution) and Sentinel-3 SLSTR Level-2 Sea Surface Temperature (SST) data: https://data.eumetsat.int/
• Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) data on PO.DAAC: https://podaac.jpl.nasa.gov/S-MODE

Reference

• X. Kang, G. Gao, Q. Hao and S. Li, "A Coarse-to-Fine Method for Cloud Detection in Remote Sensing Images," in IEEE Geoscience and Remote Sensing Letters, vol. 16, no. 1, pp. 110-114, Jan. 2019. https://doi.org/10.1109/LGRS.2018.2866499

Other resource

• Freilich, M., Lenain, L., & Gille, S. T. (2023). Characterizing the role of non-linear interactions in the transition to submesoscale dynamics at a dense filament. Geophysical Research Letters, 50, e2023GL103745. https://doi.org/10.1029/2023GL103745
• Lenain, L., Smeltzer, B. K., Pizzo, N., Freilich, M., Colosi, L., Ellingsen, S. Å., et al. (2023). Airborne remote sensing of upper-ocean and surface properties, currents and their gradients from meso to submesoscales. Geophysical Research Letters, 50, e2022GL102468. https://doi.org/10.1029/2022GL102468

Collection image

• Image source: Sarah Lang. "Concurrent SST, chl-a, current derivatives from MASS."