ESMValGroup/ESMValTool
Jun 2026 – Jun 2026
1 Month active
Languages Used
No languages
Technical Skills
Climate ScienceData AnalysisData VisualizationDocumentationIrisMatplotlib
Naomi Parsons
PROFILE
Naomi Parsons
Contributed to the ESMValGroup/ESMValTool repository by developing two features focused on climate data diagnostics. Enhanced the Sea Ice Sensitivity Analysis by integrating observational datasets, refactoring statistical calculations to leverage Pandas DataFrames, and extending configuration with a CMIP7-specific recipe for standardized model-observation evaluation. Improved the Radiation Budget Diagnostic by introducing an alias parameter for dataset configurations and updating plotting routines to use these aliases in legend labels, facilitating clearer data interpretation. All changes were supported by comprehensive documentation and recipe updates. Work was carried out collaboratively, utilizing Python, Pandas, and Matplotlib to advance scientific computing workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
1,413
Activity Months1
Your Network
59 peopleWork History
June 2026
3 Commits • 2 Features
Jun 1, 2026June 2026 monthly summary for ESMValTool (ESMValGroup/ESMValTool): Delivered key features for Sea Ice Sensitivity Analysis and Radiation Budget diagnostics. Sea Ice Enhancements integrate observational datasets into the sensitivity diagnostic, refactor statistical calculations to Pandas DataFrames, and extend configuration with a CMIP7-specific recipe for standardized CMIP7 vs observations evaluation. This work included two commits: d9f84e65547fbd8adb02127e3aff0515f5f996ef and c7e666fe8cc0e0b8174af097be8bf1c8518b8271. The Radiation Budget Diagnostic now supports an alias parameter for dataset configurations and updates plotting labels accordingly, enabling clearer legends and easier interpretation (commit 1a79a3739cee4fd6571671085b8d2e0c78e1cb92). These changes were complemented by documentation and recipe updates.
3 Commits • 2 Features
Jun 1, 2026June 2026 monthly summary for ESMValTool (ESMValGroup/ESMValTool): Delivered key features for Sea Ice Sensitivity Analysis and Radiation Budget diagnostics. Sea Ice Enhancements integrate observational datasets into the sensitivity diagnostic, refactor statistical calculations to Pandas DataFrames, and extend configuration with a CMIP7-specific recipe for standardized CMIP7 vs observations evaluation. This work included two commits: d9f84e65547fbd8adb02127e3aff0515f5f996ef and c7e666fe8cc0e0b8174af097be8bf1c8518b8271. The Radiation Budget Diagnostic now supports an alias parameter for dataset configurations and updates plotting labels accordingly, enabling clearer legends and easier interpretation (commit 1a79a3739cee4fd6571671085b8d2e0c78e1cb92). These changes were complemented by documentation and recipe updates.
June 2026
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture93.4%
Performance86.6%
AI Usage60.0%
Skills & Technologies
Programming Languages
No languages yet
Technical Skills
Climate ScienceData AnalysisData VisualizationDocumentationIrisMatplotlibNumPyPandasPythonSciPyScientific ComputingYAMLreStructuredText
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