陸上・洋上風力資源と発電ポテンシャルを統合した全球グリッドデータセット
A global gridded dataset of unified onshore and offshore wind resources and power potential (原題)
Changqing xu, Tianyu Jia, Jianchuan Qi, Peng Wang, Xi Chen, Siqi Wang, Yunzhi Tang, Fangyuan Lu, Yuqiao Lan, Jing Guo, Bo Wang, Bin Zhang, Chuke Chen, Nan Li, Ming Xu, Zhaohua Wang
🤖 gxceed AI 要約
日本語
ERA5再解析データ(0.25度解像度)を用い、1980〜2025年の陸上・洋上風力資源と発電ポテンシャルを全球グリッドで評価したデータセット。容量係数・容量密度・エネルギー密度・技術ポテンシャル・開発可能ポテンシャルの5指標を、タービン配置や開発可能面積比の複数シナリオで提供する。土地利用・保護区・水深・EEZ等の空間スクリーニングを統合し、国・地域のエネルギー計画や統合評価モデルへの応用を可能にする。
English
A global gridded dataset (0.25°, 1980–2025) assessing onshore and offshore wind resources and power potential using ERA5 reanalysis. It provides five metrics—capacity factor, capacity density, energy density, technical potential, and developable potential—under multiple turbine-spacing and developable-area scenarios. Spatial screening integrates land cover, protected areas, slope, EEZ, water depth, and sea-ice constraints, supporting national energy planning and integrated assessment modeling.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本は洋上風力の導入拡大とEEZ活用を政策課題としており、本データセットは国内の資源ポテンシャル評価や再エネ導入計画、電力系統計画の基礎資料として活用余地がある。SSBJ・有報の気候関連開示におけるシナリオ分析の前提データとしても間接的に寄与しうる。
In the global GX context
As global disclosure frameworks (TCFD/ISSB/CSRD) increasingly demand transition-planning and scenario analysis, robust renewable-resource datasets underpin credible decarbonization pathways. This dataset offers a methodologically consistent global baseline for wind technical potential, useful for integrated assessment modeling and national energy planning worldwide.
👥 読者別の含意
🔬研究者:全球規模の風力ポテンシャル評価や統合評価モデル、再エネシナリオ分析の入力データとして活用できる。
🏢実務担当者:再エネ調達・立地戦略や長期の脱炭素ロードマップ策定における資源ポテンシャルの基礎情報として参照可能。
🏛政策担当者:洋上風力の導入計画やEEZ利用、電力系統計画の策定に際し、全球整合的な資源評価の根拠として活用できる。
📄 Abstract(原文)
This dataset provides a global gridded assessment of onshore and offshore wind resources and power potential from 1980 to 2025. The dataset was developed using ERA5 atmospheric reanalysis data at 0.25° spatial resolution and combines meteorology-driven wind resource modeling with globally consistent geospatial screening and technical potential assessment.The dataset includes five core metrics: capacity factor (CF), capacity density (CD), energy density (ED), technical potential (TP), and developable potential (DP). CF characterizes wind-resource availability, CD represents installed capacity density under alternative turbine layout assumptions, ED quantifies energy generation per square kilometer, TP estimates grid-cell-level technical energy potential, and DP further incorporates developable area ratios to represent deployment-related constraints.To support uncertainty and scenario analysis, the dataset provides three turbine spacing scenarios, namely dense, moderate, and sparse layouts. Developable potential is further evaluated under three developable area ratios: 0.5%, 1%, and 3%. These scenarios allow users to examine how turbine layout density and land or sea area availability influence regional and global wind power potential.The dataset covers both onshore and offshore domains using a consistent methodological framework. Spatial screening considers land-sea classification, land cover suitability, protected areas, terrain slope, exclusive economic zones, water depth, offshore distance, and sea-ice constraints. Technical modeling incorporates turbine power curves, hub-height wind speed extrapolation, air-density correction, wake-related layout assumptions, turbine availability, and transmission or system efficiency losses.All data are provided in NetCDF (.nc) format with standardized dimensions and variable names. The dataset includes hourly, monthly, and annual products, enabling applications across multiple temporal and spatial scales, including integrated assessment modeling, national and regional energy planning, renewable energy resource assessment, and power system analysis.Spatial coverage: Global onshore and offshore regionsTemporal coverage: 1980-2025Spatial resolution: 0.25° × 0.25°Data format: NetCDF (.nc)
🔗 Provenance — このレコードを発見したソース
- scidb https://doi.org/10.57760/sciencedb.35215first seen 2026-10-10 06:17:25
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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。