climate-trends
CommunityQuantify climate trends and extremes for research.
Education & Research#mann-kendall#climate trends#extreme indices#sen's slope#etccdi#xclim#ipcc figures
Authorxjtulyc
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Climate trend analysis and attribution-style reporting require statistically defensible calculations of monotonic trends and changes in extreme precipitation and temperature indices across decades.
Core Features & Use Cases
- Trend detection: Runs Mann-Kendall trend testing and estimates trend magnitude with Sen’s slope to support significance and direction in time-series climate studies.
- Extreme indices (ETCCDI): Computes ETCCDI-style metrics such as RX1day, R10mm, TX90p, and other percentile/extreme frequency indicators using xclim-compatible workflows.
- IPCC-style outputs: Produces research-ready visualizations and warming-stripe/IPCC AR6-inspired figures suitable for reports and publications, including “observed vs. model-projection” comparisons.
Quick Start
Use the climate-trends Skill to analyze a daily temperature and precipitation dataset and generate trend results plus ETCCDI extreme indices and IPCC-style figures.
Dependency Matrix
Required Modules
xclimscipymatplotlibnumpyxarraypandascartopy
Components
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: climate-trends Download link: https://github.com/xjtulyc/awesome-rosetta-skills/archive/main.zip#climate-trends Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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