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metocean-statistics

Apply EVA methods to historical wave, wind, and current data for extreme metocean conditions.

2|Updated Dec 6, 2022
Search Tags:#statistical-analysis#metocean#extreme-value-analysis#gev#pot#return-periods#directional-analysis
One-click install
npx skills add https://github.com/vamseeachanta/worldenergydata --skill metocean-statistics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: metocean-statistics
Source: https://github.com/vamseeachanta/worldenergydata/tree/main/.claude/skills/metocean-statistics
Command: npx skills add https://github.com/vamseeachanta/worldenergydata --skill metocean-statistics

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Statistical metocean analysis enables engineers and researchers to quantify extreme conditions, understand joint behaviors of waves, wind, and currents, and derive design criteria and safety guidelines from historical data.

Core Features & Use Cases

  • Extreme Value Analysis: block maxima and POT methods with GEV/GPD fitting to estimate return levels and confidence intervals.
  • Joint Probability & Environmental Contours: analyze Hs-Tp distributions, compute environmental contours (IFORM/direct sampling) for design envelopes, and assess joint exceedance risks.
  • Directional Statistics: compute directional statistics and wave/wind roses to capture directional dependencies and sector-based risks.
  • Temporal Analysis: monthly, seasonal, and annual statistics to identify trends, variability, and exceedance patterns.
  • Operational & Fatigue Applications: support fatigue analysis, weather window definition, and design criteria development using multi-parameter statistics.

Quick Start

Run a complete metocean statistics workflow to generate extreme-value metrics, joint distributions, and directional insights for design and safety decisions.

Frequently Asked Questions about metocean-statistics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate extreme metocean return periods from historical wave and wind data?▼

Extreme metocean return periods are calculated by applying extreme value analysis methods like block maxima and Peaks-Over-Threshold (POT) to historical wave and wind data. This process fits GEV or GPD distributions to estimate return levels and confidence intervals.

What is the best way to generate environmental contours for offshore design criteria?▼

Environmental contours for offshore design are generated by analyzing joint Hs-Tp distributions using IFORM or direct sampling methods. This analyzes joint wave and wind behaviors to compute design envelopes and assess joint exceedance risks.

How does directional statistics improve wave and wind risk assessment?▼

Directional statistics improve risk assessment by computing wave and wind roses to capture directional dependencies. This identifies sector-based risks and directional extremes across monthly, seasonal, and annual scales for engineering design.

Can I use block maxima and POT methods for seasonal metocean analysis?▼

Block maxima and POT methods can be applied across monthly, seasonal, and annual scales for metocean analysis. They identify temporal trends, variability, and exceedance patterns to support fatigue analysis and weather window definition.

What outputs do I get from a statistical metocean analysis workflow?▼

Statistical metocean analysis produces return level tables, fitted distribution parameters, diagnostics, and plots. These outputs quantify extreme conditions and are suitable for direct inclusion in engineering design and safety reports.

When should I use GEV distribution fitting instead of GPD for extreme value analysis?▼

GEV distribution fitting is used for block maxima approaches, while GPD applies to Peaks-Over-Threshold (POT) methods. Both estimate return levels and confidence intervals, with the choice depending on the extreme value analysis method selected.

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