Data of dynamic downscaled extreme events for the coastal region of Southern Brazil

doi: 10.4121/12721367.v3
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
Datacite citation style:
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
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
choose version:
version 3 - 2021-03-18 (latest)
version 2 - 2020-04-20 version 1 - 2019-10-07
usage stats
2120
views
563
downloads
geolocation
Southern region of Brazil
lat (N): -29.5
lon (E): -49
view on openstreetmap
time coverage
2004/2018
licence
cc-0.png logo CC0
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.
history
  • 2020-04-20 first online
  • 2021-03-18 published, posted
publisher
4TU.Centre for Research Data
format
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
references
funding
  • CAPES, 88881.146046/2017-01
organizations
Federal University of Santa Catarina, Department of Physics, Climate and Meteorology Laboratory, Brazil

DATA

files (2)