precip_analyze_aorc
Retrieves and processes AORC precipitation data for HEC-RAS/HMS models. Handles spatial averaging over watersheds, temporal aggregation, DSS export, and Atlas 14 design storms. Use when working with historical precipitation, AORC data, calibration workflows, design storm generation, rainfall analysis, SCS Type II distributions, AEP events, 100-year storms, or generating precipitation boundary conditions for rain-on-grid models.
npx skills add majiayu000/claude-skill-registry --skill precip-analyze-aorc-gpt-cmdr-ras-commander --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Analyzing AORC Precipitation **Purpose**: Navigate precipitation workflows for HEC-RAS/HMS models using AORC historical data and Atlas 14 design storms. **This skill is a NAVIGATOR** - it points you to the primary sources containing complete workflows and API documentation. For implementation details, always refer to the primary sources below. ## Primary Sources (Read These First!) ### 1. Complete API Reference and Workflows **`ras_commander/precip/CLAUDE.md`** (329 lines - AUTHORITATIVE SOURCE) Contains: - Complete module organization (PrecipAorc, StormGenerator) - Full API reference with all methods - Step-by-step AORC workflow (retrieval, spatial averaging, temporal aggregation, export) - Step-by-step Atlas 14 workflow (query, generate, apply ARF, export) - Multi-event workflows - Performance characteristics - Dependencies and installation **THIS IS THE PRIMARY DOCUMENTATION** - use it for all detailed questions. ### 2. AORC Demonstration Notebook **`examples/900_aorc_precipitation.ipynb`** Live working example showing: - AORC data retrieval from cloud storage - Spatial averaging over watersheds - Temporal aggregation to HEC-RAS intervals - Export to DSS and CSV formats - Inte
- Primary Sources (Read These First!)
- 1. Complete API Reference and Workflows
- 2. AORC Demonstration Notebook
- 3. Atlas 14 Single-Project Workflow
- 4. Atlas 14 Multi-Project Batch Processing
- Quick Start
- AORC Historical Data (30 seconds)
- Atlas 14 Design Storm (30 seconds)
- When to Use This Skill
- Core Concepts (Brief)
- AORC Dataset
- NOAA Atlas 14
- Temporal Distributions
- Areal Reduction Factors (ARF)
pip install ras-commander[precip] # Includes all precipitation dependencies OR pip install xarray rasterio geopandas
What does the precip_analyze_aorc skill do?
Retrieves and processes AORC precipitation data for HEC-RAS/HMS models. Handles spatial averaging over watersheds, temporal aggregation, DSS export, and Atlas 14 design storms. Use when working with historical precipitation, AORC data, calibration workflows, design storm generation, rainfall analysis, SCS Type II distributions, AEP events, 100-year storms, or generating precipitation boundary conditions for rain-on-grid models.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill precip-analyze-aorc-gpt-cmdr-ras-commander --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.