Deep Learning-Based Temperature and Salinity Reconstruction and derived Geostrophic Currents in the Fram Strait with 3-Day resolution on EASE-Grid 2.0 at 6.25km (Version 1)

hdl:21.14106/194f2f05496e582ce225576978e0565db791cc66

Werner-Pelletier, Nicolas et al.

Dataset
Summary
[ Derived from parent entry - See data hierarchy tab ]

This dataset collection provides observation-constrained reconstructions of Arctic Ocean hydrography and diagnostic geostrophic circulation for the period 2011–2021. The datasets were generated using a Long Short-Term Memory neural network trained with in situ hydrographic profiles and satellite-derived surface information, including sea surface temperature, sea surface salinity, and absolute dynamic topography. The framework estimates temperature and salinity anomalies relative to GLORYS12V1 reanalysis, which are then used to obtain reconstructed three-dimensional temperature and salinity fields on 102 WOA standard depth levels at 3-day temporal resolution. The collection includes one pan-Arctic product on a 25 km EASE2 grid and four regional 6.25 km products covering the main Arctic gateways: Bering Strait, Davis Strait, Fram Strait, and the Barents Sea Opening. The datasets also include model-based uncertainty estimates, surface input fields and absolute dynamic height, supporting studies of Arctic freshwater variability, circulation change, and climate model evaluation.
Project
FRESH-CARE (Unraveling FRESHwater and ocean Currents changes in the Arctic using REmote sensing)
Spatial Coverage
Longitude -29.21 to 24.55 Latitude 76.33 to 81.23
Temporal Coverage
2011-01-04 to 2021-12-28 (standard)
Use constraints
Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/)
Data Catalog
World Data Center for Climate
Access constraints
registered users
Size
8.99 GiB (9655995455 Byte)
Format
NetCDF
Status
completely archived
Creation Date
Review Date
2026-07-03
Download Permission
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Preview data headers
Cite as
[ Derived from parent entry - See data hierarchy tab ]
Werner-Pelletier, Nicolas; Crespin, Julia; Rosquete-Estevez, Aleida; Sánchez-Urrea, María; Hoareau, Nina; Martin, Mario; Umbert, Marta (2026). Deep Learning-Based Temperature and Salinity Reconstruction and derived Geostrophic Currents in the Pan-Arctic Ocean with 3-Day resolution on EASE-Grid 2.0 at 25km (Version 1). World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/DLRec-AO_v1

BibTeX RIS
VariableUnit
eastward_sea_water_velocity
CF
m s-1
geopotential_height
CF
m
height_above_mean_sea_level
CF
m
northward_sea_water_velocity
CF
m s-1
sea_surface_height_above_geoid
CF
m
sea_surface_salinity
CF
1e-3
sea_surface_temperature
CF
degC
sea_water_potential_temperature
CF
degC
sea_water_practical_salinity
CF
1e-3
sea_water_practical_salinity_anomaly
1e-3
sea_water_temperature
CF
degC
sea_water_temperature_anomaly
CF
degC
sea_water_x_velocity
CF
m s-1
sea_water_y_velocity
CF
m s-1

Parent

Deep Learning-Based Reconstruction of Temperature and Salinity in the Arctic Ocean and derived Geostrophic Currents (Version 1)
Details

Parent project(s)

Unraveling FRESHwater and ocean Currents changes in the Arctic using REmote sensing

[Entry acronym: DLRec-AO_v1_Fram] [Entry id: 5370441]