Published on 07 December 2020 |

Version First

Airborne Radar Quality Control with Machine Learning

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DesRosiers, Alexander;Bell, Michael M.

Description

This repository contains the radar data collected by ELDORA required to train and test the random forest model discussed in "Airborne radar quality control with machine learning" by Alexander DesRosiers and Michael M. Bell at the Colorado State University Department of Atmospheric Science. The model used in the manuscript is also contained in a '.pkl' file. Upon publication, a link to the paper will be provided here. Finer points of the methodology were discussed in the manuscript and the python script (make_radarQC_rf_model.py) is commented to guide users through the process of creating the model.

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.1

FAIR Score

13%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Zenodo

Assigned Domain

Subfield

Atmospheric Science

Field

Earth and Planetary Sciences

Domain

Physical Sciences

Confidence Score

95%

Source

Open Alex

Keywords

RadarQuality ControlMachine LearningRandom Forest

Normalization Factors

FT

30.77

CTw

1.00

MTw

1.00