The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/12721367

Danilo Souza; R. (Renato) Ramos da Silva (2021): Data of dynamic downscaled extreme events for the coastal region of Southern Brazil. Version 3. 4TU.ResearchData. dataset. https://doi.org/10.4121/12721367.v3

Dataset

x choose version: version 2 - 2020-04-20 version 1 - 2019-10-07

• Oceanography
• Atmospheric Sciences
• Atmosphere and Weather

climate change, climate model, extreme events, master thesis, numerical modeling, regional modeling

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2004/2018

CC0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Danilo Souza, R. (Renato) Ramos da Silva

This dataset was created for the Danilo Couto de Souza's master thesis. The results were further sent to publication. In this dataset there is processed data of extreme events for the coastal region of southern Brazil. It also contains observed (form meteorological stations) and reanalysis data (GPM/TRMM and MERRA-2) for the same period, for model validation purposes. Those events were dynamically downscaled using the Ocean-Land Atmosphere Model (OLAM) set up with a high resolution grid for the study area. This dataset also contains Python language scripts used for comparing the modelled data and the observed/reanalysis equivalents. See also the publication containing the analysis of this dataset.

• 2020-04-20 first online

• 2021-03-18 published, posted

4TU.Centre for Research Data

media types: application/octet-stream, application/pdf, application/postscript, application/vnd.google-earth.kml+xml, application/vnd.oasis.opendocument.spreadsheet, application/x-netcdf, application/zip, image/png, image/tiff, text/csv, text/plain, text/x-python

Ocean-Land Atmosphere Model (OLAM) performance for major extreme meteorological events near the coastal region of southern Brazil

• 10.3354/cr01651

• CAPES, 88881.146046/2017-01

Federal University of Santa Catarina, Department of Physics, Climate and Meteorology Laboratory, Brazil