Monthly Anomaly Database of Atmospheric and Oceanic Parameters in the Tropical Atlantic Ocean

Type Article
Date 2022-04
Language English
Author(s) Varona H.L.ORCID1, Hernandez F.1, 2, Bertrand ArnaudORCID3, Araujo M.ORCID1
Affiliation(s) 1 : Department of Oceanography (DOCEAN), Federal University of Pernambuco, Recife, PE, Brazil
2 : Institut de Recherche pour le Développement (IRD), LEGOS, Univ Toulouse, CNRS, CNES, Toulouse, France
3 : Institut de Recherche pour le Développement (IRD), MARBEC, Univ Montpellier, CNRS, Ifremer, Sète, France
Source Data In Brief (2352-3409) (Elsevier BV), 2022-04 , Vol. 41 , P. 107969 (13p.)
DOI 10.1016/j.dib.2022.107969
WOS© Times Cited 4
Keyword(s) MARDAO dataset, TAAD dataset, Anomaly, Tropical Atlantic, Climate change
Abstract

The Tropical Atlantic Ocean Database and Monthly Anomalies of River Discharge on Atlantic Ocean datasets encompass the monthly anomalies of a variety of physical, biogeochemical parameters from the tropical Atlantic Ocean and the monthly anomalies of river runoff in the Atlantic Ocean and its adjacent seas. The parameters used as the base for the computation of anomalies come from the TROPFLUX, GPCP, ASCAT, SODA, GODAS, DASK, SeaWiFS, OAFLUX, WAVEWATCH III, NOAA/ESRL 20th Century Reanalysis, GLOBAL_REANALYSIS_BIO_001_029, GLOBAL_REANALYSIS_BIO_001_033, OCEANCOLOUR_GLO_OPTICS_L4_REP_OBSERVATIONS_009_081, OSCAR, SMOS, MODIS-Aqua, CO2_Flux, and GRDC datasets. Several of the anomaly data are redundant, but come from different data sources making comparative studies possible. For ease of use, both datasets are provided in NetCDF format, CF convention. These datasets include 18 files in NetCDF format, which facilitates its handling due to the diversity of freeware tools that exist and are structured in two-, three- and four-dimensional grids. All these anomalies can be useful to oceanographers, meteorologists, ecologists and other researchers for studies of climate variation in the tropical Atlantic Ocean. These datasets are hosted at https://www.seanoe.org/data/00718/82962/ and https://data.mendeley.com/datasets/pn5b35vn6s/1.

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