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HFR data Quality Control assessment Jupyter Notebook

This Python-based Jupyter notebook focuses on providing basic routines for inspecting the HFR-derived surface current dataset produced by the operational Near Real Time (NRT) workflow of the European HFR Node. The inspection is useful for assessing the datasets and modify the processing and QC parameters, if needed.

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Basic

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Abbreviation HFR_QC_Assessment_Jupyter_Notebook
Research Infrastructure Jerico
Resource Providers CNR-ISMAR-SP
Webpage https://github.com/LorenzoCorgnati/HFR-TT_workshop_Lerici_2025_training_JupyterNotebook
Marketing

Description: Includes general, non-technical information intended for users interested in the resource.

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Description This Python-based Jupyter notebook focuses on providing basic routines for inspecting the HFR-derived surface current dataset produced by the operational Near Real Time (NRT) workflow of the European HFR Node. The inspection is useful for assessing the datasets and modify the processing and QC parameters, if needed.
Logo https://www.hfrnode.eu/wp-content/uploads/2023/05/HFR_node_logo.jpg
Use Cases https://doi.org/10.17605/OSF.IO/DFQ3W
Classification

Description: Information regarding the scientific context, structure, and access details of the resource, including scientific domains and subdomains, service types, eligibility criteria, and more.

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Access Types Virtual
Access mode Free
Categories Training and support
Categories Processing and analysis
Categories Security and operations
Scientific Domain Natural Sciences
Scientific Sub-Domain Natural Sciences. Earth & Related Environmental Sciences
Scientific Sub-Domain Natural Sciences. Computer & Information Sciences
Sub Category Training and support. Education and training
Sub Category Processing and analysis. Data analysis
Sub Category Processing and analysis. Data management
Sub Category Security and operations. Operations and infrastructure management services
Target Users Providers
Target Users Research Communities
Target Users Researchers
Target Users Students
Availability

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Geographic Availability Worldwide
Language Availability English (en)
Location

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Resource Geographic Location Worldwide
Contact

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Helpdesk Email lorenzopaolo.corgnati@cnr.it
Main contact Lorenzo Paolo Corgnati
Public contact Lorenzo Paolo Corgnati; lorenzopaolo.corgnati@cnr.it
Security Contact Email lorenzopaolo.corgnati@cnr.it
Dependencies

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Related Platforms European and global High Frequency Radar community; European HFR Node; EuroGOOS High Frequency Radar Task Team
Related Resources Python packages: pandas; fsspec; xarray; hvplot; os; intake; cf_xarray; panel; numpy; matplotlib; xoak
Required Resources Internet Connection; Environment supporting Jupyter notebooks
Maturity

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Change Log Publication of the resource
Last Update 2025-05-30
Life Cycle Status Operational
Open Source Technologies Python packages: pandas; fsspec; xarray; hvplot; os; intake; cf_xarray; panel; numpy; matplotlib; xoak
Standards CF-1.11; ISO8601; ACDD
Version 1.0.0
trl: Technology Readiness Level 9 - actual system proven in operational environment
attribution

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Funding Body European Commission (EC)
Funding Body National Research Council (CNR)
Funding Programs European Earth Observation Programme (COPERNICUS)
Management

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Access Policy https://github.com/LorenzoCorgnati/HFR-TT_workshop_Lerici_2025_training_JupyterNotebook/blob/main/LICENSE
Helpdesk Page https://github.com/LorenzoCorgnati/HFR-TT_workshop_Lerici_2025_training_JupyterNotebook
Terms of Use https://github.com/LorenzoCorgnati/HFR-TT_workshop_Lerici_2025_training_JupyterNotebook/blob/main/LICENSE
User Manual https://github.com/LorenzoCorgnati/HFR-TT_workshop_Lerici_2025_training_JupyterNotebook/blob/main/README.md
Order

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Order Type Fully open
Financial

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Additional Info
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Provider CNR-ISMAR La Spezia
system:type Service
Management Info
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Author Corgnati Lorenzo Paolo
Maintainer Corgnati Lorenzo Paolo
Version 1
Last Updated 9 December 2025, 12:15 (CET)
Created 4 December 2025, 15:09 (CET)