Published March 26, 2021 | Version 1.0
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Auxiliary data set for Mäkinen et al. (2021) Bayesian Classification of Meteorological and Non-Meteorological Targets in Polarimetric Weather Radar Measurements

Creators

  • 1. Finnish Meteorological Institute

Contributors

Project leader:

Description

Auxiliary data for the paper Mäkinen et al. 2021. Bayesian Classification of Meteorological and Non-Meteorological Targets in Polarimetric Weather Radar Measurements. Submitted to Remote Sensing. The data consist of a XML record of radar observation metadata defining the classifier training set, and the data for the Naive Bayes multicore classifier used in the paper. The files are in plaintext and self-documenting.

Files

cases.xml

Files (971.4 kB)

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Checksum: md5:0e790b47995e1a41937438d4a6eda0d6

PID: http://hdl.handle.net/11304/628a6753-9a17-455f-8617-5879cd59bfa0
779.2 kB
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Checksum: md5:8b3533ebc8179f6e3e3c99f41573f59d

PID: http://hdl.handle.net/11304/dc583552-3e03-43aa-a422-176be0bc1083
192.2 kB
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Additional details

Identifiers

URL
https://etsin.fairdata.fi/dataset/717184b8-0062-416d-905d-2d6f0d6ea7c3
B2SHARE Legacy Record ID
84832a794ea5442896acd5567944fb3b

FMI metadata

Link to external data location (URL)
http://fmi-opendata-radar-volume-hdf5.s3-website-eu-west-1.amazonaws.com/
Geolocation
POLYGON ((60 20, 60 30, 70 30, 70 20, 60 20))
Lineage
FMI Bayesian polarimetric classifier version 1.0
Topic category
climatologyMeteorologyAtmosphere
Source data
FMI radar volume HDF5 archive
Supplemental information
FMI radar volumes are available through Amazon AWS S3
Process step
Statistical data from radar observations listed and manually classified in cases.xml is collected to create a defining data set nb32_multicore.dat for a Bayesian classifier.