Abstract: This dataset focuses on extratropical cyclones (ETCs) over the North Atlantic Ocean (NATL) during the extended winter seasons, spanning from October to April, between 1985 and 2022. The relationship between moisture uptake and precipitation in various mesoscale ETC structures remains an active research area. The provision of moisture parameters through tracer dispersion models enhances our understanding of moisture dynamics, the behaviour of ETCs, and the associated meteorological fields. Description: The dataset was constructed through dynamic downscaling of ERA5 reanalysis data using the Weather Research and Forecasting (WRF) model, in conjunction with the Lagrangian dispersion model FELXPART-WRF. It consists of 6-hourly time intervals with a horizontal resolution of 0.18°. This database is completely described in Coll-Hidalgo, P., Gimeno-Sotelo, L., Fernández-Alvarez, J.C. et al. North Atlantic Extratropical Cyclone Tracks and Lagrangian-Derived Moisture Uptake Dataset. Sci Data 11, 1258 (2024). https://doi.org/10.1038/s41597-024-04091-5 The dataset includes: Detailed tracking of ETCs across the North Atlantic: Date in year-month-day format hh (in UTC): Hour in Coordinated Universal Time latitude (degrees north): Latitude in degrees north longitude (degrees west): Longitude in degrees west MSLP (hPa): Mean sea level pressure in hectopascals (hPa) Radius (km): Cyclone radius in kilometres (km) Last closed isobar (hPa): Pressure at the last closed isobar in hectopascals (hPa) Low-level thermal wind parameter (VTL) High-level thermal wind parameter (VTU) The thermal asymmetry parameter (B) Two-Dimensional Masks Shaping ETCs: Radius Warm Conveyor Belt (WCB) footprint Related Areas A theoretical boundary encompassing a broader extent of the ETC circulation within a spiral shape Cyclone Moisture Uptake-Related Variables by ETCs life timesteps: Total moisture uptake Discrete Moisture Uptake (10-Day Backward) Moisture uptake by layers from the surface to 100 hPa. Dataset Repository Information This repository contains the dataset for the years 1985-1999. For users interested in datasets from subsequent periods, please refer to the following links: Years 2000-2014: Access the dataset hereYears 2015-2022: Access the dataset here A GitHub repository is available, providing example code that demonstrates how to use and handle the dataset effectively.