https://github.com/tbep-tech/tbcmp-rainfall-trends
Repository to re-assess rainfall trends across the Tampa Bay Coastal Master Plan project area utilizing methods from: https://doi.org/10.1029%2F2019GL083235 .
https://github.com/tbep-tech/tbcmp-rainfall-trends
Last synced: 3 days ago
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Repository to re-assess rainfall trends across the Tampa Bay Coastal Master Plan project area utilizing methods from: https://doi.org/10.1029%2F2019GL083235 .
- Host: GitHub
- URL: https://github.com/tbep-tech/tbcmp-rainfall-trends
- Owner: tbep-tech
- Created: 2026-06-03T17:21:39.000Z (16 days ago)
- Default Branch: main
- Last Pushed: 2026-06-03T21:26:14.000Z (15 days ago)
- Last Synced: 2026-06-03T22:10:02.794Z (15 days ago)
- Language: R
- Size: 2.76 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
Tampa Bay Coastal Master Plan Project Area — Rainfall Extremes Trend Analysis
Replicates key analyses from:
Wright, D.B., Bosma, C.D., & Lopez-Cantu, T. (2019). "U.S. Hydrologic Design Standards Insufficient Due to Large Increases in Frequency of Rainfall Extremes." Geophysical Research Letters, 46, 8144-8153. https://doi.org/10.1029/2019GL083235
Scope: All GHCN-Daily stations within the Tampa Bay Coastal Master Plan project area
Study period: 1900–2025 (extending the paper's primary analysis window)
Analyses replicated:
1. GHCN station retrieval and spatial filter to TBCMP county boundaries
2. Exceedance counting relative to NOAA Atlas 14 IDF estimates (Section 3.1)
3. Negative binomial regression trend analysis (Section 3.1)
4. Rainstorm cluster identification (Section 3.2 / Section 2.4)
5. Design-vs-observed ARI comparison (Section 3.3 / Section 2.5)
6. Publication-quality figures for all analyses
Dependencies (install once before sourcing):
install.packages(c("tidyverse", "sf", "terra", "rnoaa", "MASS", "pscl", "zoo", "lubridate", "ggplot2", "patchwork", "scales", "httr", "jsonlite", "tigris", "units"))
Data sources fetched automatically at runtime:
1. GHCN-Daily via rnoaa::ghcnd_*()
2. NOAA Atlas 14 IDF values via NOAA Precipitation Frequency Data Server (PFDS) REST API
3. Tampa Bay watershed boundary via internal shapefile, fallback is the USGS StreamStats or NHD boundary (a local GeoJSON fallback is provided if API is unavailable)
Translation to R: Claude.AI and Ed Sherwood