
Contributed two robust data analysis features to the lter/lterwg-resilience repository, focusing on environmental data processing and visualization using R and SQL. Developed an R script to analyze Vapor Pressure Deficit distributions across networks, processing daily weather data to compute mean annual values and generate visual outputs, with automated local and Google Drive storage. Additionally, implemented a repeatable workflow for climate extremes analysis, enabling cross-network insights by calculating Tmax percentiles from Daymet data and visualizing exceedance events over time. Emphasized reproducibility and maintainability through comprehensive scripting, thorough code annotation, and robust input/output handling throughout both feature implementations.
Month: 2025-08 — Delivered a repeatable climate extremes analysis capability for the lterwg-resilience repo, enabling cross-network insights into Tmax exceedances using Daymet data. Key deliverable: Tmax Percentile Analysis and Visualization (R).
Month: 2025-08 — Delivered a repeatable climate extremes analysis capability for the lterwg-resilience repo, enabling cross-network insights into Tmax exceedances using Daymet data. Key deliverable: Tmax Percentile Analysis and Visualization (R).
February 2025: Delivered a focused feature in lter/lterwg-resilience that enables Vapor Pressure Deficit (VPD) distribution analysis across multiple networks. Implemented an R script to process daily weather data, compute mean annual VPD, and generate two visualizations (histogram and dot plot). Outputs are saved locally and uploaded to Google Drive, with robust IO handling and thorough code annotations to improve reproducibility.
February 2025: Delivered a focused feature in lter/lterwg-resilience that enables Vapor Pressure Deficit (VPD) distribution analysis across multiple networks. Implemented an R script to process daily weather data, compute mean annual VPD, and generate two visualizations (histogram and dot plot). Outputs are saved locally and uploaded to Google Drive, with robust IO handling and thorough code annotations to improve reproducibility.

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