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Climate Intelligence

Provides multi-domain climate data analysis including emissions, renewable energy, carbon markets, policy, risk, finance, innovation, attribution, and net-ze...
提供多领域气候数据分析,涵盖排放、可再生能源、碳市场、政策、风险、金融、创新、归因以及净零...
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#adaptation#carbon-market#carbon-pricing#climate#climate-risk#climate-tech#emissions#esg#green-finance#latest#ndc#net-zero#paris-agreement#renewable-energy#sustainability

概述

Climate Intelligence Engine

Capabilities

#CapabilityInputOutput
-----------------------------
1Emissions DashboardCountry / sector / scopeCO2/CH4 emissions (absolute, per-capita, intensity), trend analysis, carbon budget remaining
2Renewable Energy TrackerTechnology + regionInstalled capacity (GW), capacity factor, LCOE trajectory, investment flows, pipeline projects
3Carbon Market MonitorMarket (EU ETS / China ETS / voluntary)Spot price, futures curve, auction clearing, market coverage, policy changes
4Physical Climate Risk AssessmentLocation / asset / sectorHazard exposure (flood, heat, drought, wildfire), return periods, adaptation cost estimates
5Climate Policy ComparatorCountries + policy areaNDC ambition, net-zero target year, implementation status, policy instrument mix, effectiveness evidence
6ESG Disclosure NavigatorJurisdiction + company sizeApplicable frameworks (ISSB, CSRD, SEC), reporting deadlines, materiality requirements, assurance standards
7Climate Finance IntelligenceInstrument type + regionIssuance volumes, pricing (greenium), use-of-proceeds, taxonomy alignment, fund flow trends
8Climate Tech Innovation RadarTechnology + TRL rangeTechnology readiness, cost curve, key players, funding rounds, deployment milestones, scalability assessment
9Extreme Weather AttributionEvent + locationAttribution confidence, return period shift, climate vs. natural variability, economic damage estimates
10Net-Zero Progress TrackerEntity (country / company)Target year, interim milestones, emissions trajectory vs. pathway, credibility assessment

Workflow

User Query
  │
  ├─ [Step 1] Classify → domain (9 climate domains) + geography + time horizon + analysis depth
  │
  ├─ [Step 2] Source routing:
  │   └─ Scientific: IPCC, NASA, NOAA, Copernicus, Global Carbon Project
  │   └─ Energy: IEA, IRENA, BloombergNEF
  │   └─ Policy: UNFCCC, Climate Action Tracker, WRI
  │   └─ Markets/ESG: CDP, MSCI ESG, Carbon Brief
  │
  ├─ [Step 3] Multi-source retrieval + cross-validation
  │
  ├─ [Step 4] Apply domain-specific analytics:
  │   └─ Emissions: carbon budget math, sectoral decomposition
  │   └─ Energy: LCOE comparison, learning rate projections
  │   └─ Policy: ambition gap analysis (NDCs vs. 1.5°C/2°C pathways)
  │   └─ Risk: hazard × exposure × vulnerability framework
  │
  ├─ [Step 5] Structured output with data vintage, source URLs, confidence levels
  │
  └─ [Step 6] Uncertainty disclosure: model ranges, scenario assumptions, data gaps

Output Formats

Country Emissions Profile

MetricValueYearGlobal RankTrend (5Y)
----------------------------------------------
Total CO2 (Gt)↑↓→
Per-capita CO2 (t)
CO2 intensity (kg/$GDP)
Methane (MtCO2e)
Cumulative historical (%)
NDC target
Net-zero target year

Carbon Market Dashboard

MarketSpot Price1Y RangeCoverage (% emissions)Market Stability MechanismKey Reform
--------------------------------------------------------------------------------------------
EU ETS€XX€XX-XX~36%MSRCBAM phase-in
China ETS¥XX¥XX-XX~40%None yetExpansion to sectors
UK ETS£XX£XX-XX~28%Cost ContainmentLink to EU?

Climate Risk Heatmap

HazardLocationCurrent Probability2050 Projection (RCP 4.5)2050 Projection (RCP 8.5)Adaptation Options
----------------------------------------------------------------------------------------------------------------
Coastal flood1-in-X year
Extreme heatX days >35°C
DroughtSPI index

Usage Guidelines

  1. Scenario transparency — always specify RCP/SSP scenario (e.g., RCP 4.5, SSP2-4.5) for projections
  2. Data vintage mandatory — climate data evolves rapidly; flag any data point >6 months old
  3. Uncertainty communication — report ranges, not point estimates, for projections; cite model ensemble spread
  4. Policy neutrality — present data and analysis; avoid advocacy language
  5. Multi-language — search and summarize across English, Chinese, French, Spanish, German, Japanese, Arabic
  6. Scientific integrity — distinguish between IPCC consensus (high confidence), emerging research, and advocacy positions

Examples

Example 1: Country Emissions Deep-Dive

User: "Analyze India's emissions trajectory and net-zero credibility"

Output: Historical emissions profile, sectoral breakdown (power, industry, transport, agriculture), NDC ambition vs. fair-share benchmarks, renewable deployment rate vs. required pathway, credibility scorecard.

Example 2: Carbon Market Comparison

User: "Compare EU ETS and China ETS — which is more effective?"

Output: Side-by-side dashboard (price, coverage, cap trajectory, offset rules, MRV rigor, market stability mechanisms); effectiveness assessment based on emissions reduction in covered sectors.

Example 3: Climate Tech Scan

User: "What's the state of direct air capture (DAC) technology in 2026?"

Output: Technology primer, current global capacity (ktCO2/year), cost ($/tCO2) and learning rate, key players (Climeworks, Carbon Engineering, Heirloom), funding (DOE hubs, Frontier buyers club), scalability bottlenecks, 2030 projection.


Data Base: references/climate_sources.json — 15 authoritative sources, 9 climate domains, emissions ranking, Paris Agreement timeline.

Last Updated: June 2026

Free Tier: Available. This skill aggregates public climate data; no proprietary satellite or commercial data accessed.

(内容由AI生成,仅供参考)

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-06-01 21:32

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