JCSDA-internal/ioda-converters
Oct 2024 – Mar 2025
2 Months active
Languages Used
PythonCMake
Technical Skills
Data ConversionData ProcessingPandasPythonAtmospheric Science Data ProcessingCMakeLists Management
Jérôme Barré
PROFILE
Jérôme Barré
Worked on the JCSDA-internal/ioda-converters repository to enhance atmospheric science data processing workflows, focusing on air quality and satellite measurement data. Delivered data quality improvements for the AirNow converter by refactoring variable mappings, updating pollutant unit conversions, and strengthening missing-value filtering, which improved the accuracy and completeness of converted datasets. Enhanced the TEMPO data pipeline by introducing new metadata variables for quality control and bias correction, refactoring metadata handling for consistency, and updating tests to ensure reliability. Utilized Python, Pandas, and NetCDF handling to implement robust data conversion and processing solutions, supporting more reliable downstream analytics and operational products.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
273
Activity Months2
Your Network
48 peopleShared Repositories
14
Work History
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for JCSDA-internal/ioda-converters. Delivered enhancements to TEMPO data quality control and bias correction metadata, refactored metadata handling for consistency, and updated tests to align with changes, resulting in improved data quality assessment for atmospheric measurements. No major bugs reported within the scope of this repository for March 2025; contributions focused on robustness and reliability of TEMPO processing with clearer metadata and naming conventions.
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for JCSDA-internal/ioda-converters. Delivered enhancements to TEMPO data quality control and bias correction metadata, refactored metadata handling for consistency, and updated tests to align with changes, resulting in improved data quality assessment for atmospheric measurements. No major bugs reported within the scope of this repository for March 2025; contributions focused on robustness and reliability of TEMPO processing with clearer metadata and naming conventions.
March 2025
October 2024
1 Commits • 1 Features
Oct 1, 2024Month: 2024-10 — Focused on delivering data quality improvements for the AirNow converter in JCSDA-internal/ioda-converters. Implemented refactored variable mappings, updated unit conversions for pollutants, and enhanced data filtering to handle missing values more robustly, resulting in more accurate and complete converted air quality data. The work reduces downstream data quality issues and improves reliability of air quality products used by researchers and operations.
October 2024
1 Commits • 1 Features
Oct 1, 2024Month: 2024-10 — Focused on delivering data quality improvements for the AirNow converter in JCSDA-internal/ioda-converters. Implemented refactored variable mappings, updated unit conversions for pollutants, and enhanced data filtering to handle missing values more robustly, resulting in more accurate and complete converted air quality data. The work reduces downstream data quality issues and improves reliability of air quality products used by researchers and operations.
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture70.0%
Performance60.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CMakePython
Technical Skills
Atmospheric Science Data ProcessingCMakeLists ManagementData ConversionData ProcessingNetCDF HandlingPandasPythonPython Scripting
Repositories Contributed To
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