metoppv/improver
May 2025 – Sep 2025
2 Months active
Languages Used
Python
Technical Skills
Data ProcessingScientific ComputingUnit TestingAPI DevelopmentCode RefactoringMeteorology
Katie-Howard
PROFILE
Katie-howard
Kathryn Howard contributed to the metoppv/improver repository by developing two targeted features over a two-month period. She implemented zero-value masking in the recursive filter plugin, enhancing data integrity by preventing value propagation into zero-valued regions and ensuring original mask reapplication. Later, she delivered the TemperatureSaturatedAirParcel plugin, enabling core Lifted Index calculations by computing the temperature of a saturated air parcel lifted adiabatically from the Cloud Condensation Level. Both features were built in Python and included comprehensive unit tests, demonstrating skills in scientific computing, data processing, and API development. Her work improved diagnostic accuracy and workflow reliability for meteorological applications.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
373
Activity Months2
Your Network
48 people
Work History
September 2025
1 Commits • 1 Features
Sep 1, 2025Month: 2025-09 | Repository: metoppv/improver Key outcomes: - Feature delivered: TemperatureSaturatedAirParcel Plugin for Lifted Index calculations. This plugin computes the temperature of a saturated air parcel lifted adiabatically from the Cloud Condensation Level (CCL) to a target pressure level, enabling core Lifted Index (LI) computations. Includes unit tests and API integration for the new functionality. Impact: - Enables core LI diagnostic workflows and improves forecast diagnostics accuracy by expanding the set of parcel-based stability metrics available to downstream models and QA checks. Quality and traceability: - Implemented unit tests for the new plugin and integrated with the existing API surface, ensuring reliability and maintainability. Changes tied to commit 7834b209e0bd30e7554940f08b85c3918350f37a (Eppt 2442 lifted index temperature). Technologies/skills demonstrated: - Python plugin architecture, unit testing (pytest), API integration, and end-to-end workflow alignment within metoppv/improver. Overall: this work adds a targeted capability for Lifted Index calculations with tests and API integration, delivering measurable business and technical value in forecast diagnostics.
1 Commits • 1 Features
Sep 1, 2025Month: 2025-09 | Repository: metoppv/improver Key outcomes: - Feature delivered: TemperatureSaturatedAirParcel Plugin for Lifted Index calculations. This plugin computes the temperature of a saturated air parcel lifted adiabatically from the Cloud Condensation Level (CCL) to a target pressure level, enabling core Lifted Index (LI) computations. Includes unit tests and API integration for the new functionality. Impact: - Enables core LI diagnostic workflows and improves forecast diagnostics accuracy by expanding the set of parcel-based stability metrics available to downstream models and QA checks. Quality and traceability: - Implemented unit tests for the new plugin and integrated with the existing API surface, ensuring reliability and maintainability. Changes tied to commit 7834b209e0bd30e7554940f08b85c3918350f37a (Eppt 2442 lifted index temperature). Technologies/skills demonstrated: - Python plugin architecture, unit testing (pytest), API integration, and end-to-end workflow alignment within metoppv/improver. Overall: this work adds a targeted capability for Lifted Index calculations with tests and API integration, delivering measurable business and technical value in forecast diagnostics.
September 2025
May 2025
1 Commits • 1 Features
May 1, 2025Concise monthly summary for 2025-05 for metoppv/improver focusing on key features, bugs fixed, impact and skills demonstrated.
May 2025
1 Commits • 1 Features
May 1, 2025Concise monthly summary for 2025-05 for metoppv/improver focusing on key features, bugs fixed, impact and skills demonstrated.
Activity
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Quality Metrics
Correctness95.0%
Maintainability80.0%
Architecture80.0%
Performance70.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
API DevelopmentCode RefactoringData ProcessingMeteorologyScientific ComputingUnit Testing
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