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  1. ; ; ; ; (, Journal of Open Source Software)
    Full Text Available 
  2. ; ; ; (, Zenodo)
    Full Changelog: https://github.com/Cloud-Drift/scipy-2024-poster/compare/1.3...1.4 
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  3. ; ; ; ; (, Zenodo)
    What's Changed 🔎 type comparison with isinstance by @philippemiron in https://github.com/Cloud-Drift/clouddrift/pull/491 🧹 Update type comparison in ragged.py by @selipot in https://github.com/Cloud-Drift/clouddrift/pull/497 🧹 Update random number generator in gdp1h and gdp6h adapters by @selipot in https://github.com/Cloud-Drift/clouddrift/pull/496 🐛 fix locationtype bug in dataset by @kevinsantana11 in https://github.com/Cloud-Drift/clouddrift/pull/494 Update .zenodo.json by @selipot in https://github.com/Cloud-Drift/clouddrift/pull/498 ++ increment version (v0.40.0) by @kevinsantana11 in https://github.com/Cloud-Drift/clouddrift/pull/499 Full Changelog: https://github.com/Cloud-Drift/clouddrift/compare/v0.39.0...v0.40.0 
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  4. ; ; ; ; (, Scientific Data)
    Abstract A dataset of sea surface temperature (SST) estimates is generated from the temperature observations of surface drifting buoys of NOAA’s Global Drifter Program. Estimates of SST at regular hourly time steps along drifter trajectories are obtained by fitting to observations a mathematical model representing simultaneously SST diurnal variability with three harmonics of the daily frequency, and SST low-frequency variability with a first degree polynomial. Subsequent estimates of non-diurnal SST, diurnal SST anomalies, and total SST as their sum, are provided with their respective standard uncertainties. This Lagrangian SST dataset has been developed to match the existing and on-going hourly dataset of position and velocity from the Global Drifter Program. 
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