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1664892

基於人工智慧的氣候建模市場機會、成長動力、產業趨勢分析和 2025 - 2034 年預測

AI-Based Climate Modelling Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2025 - 2034

出版日期: 2024年12月04日 | 出版商:

Global Market Insights Inc. | 英文 180 Pages | 商品交期: 2-3個工作天內

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簡介目錄

2024 年全球基於人工智慧的氣候建模市場規模達到 2.664 億美元，預計 2025 年至 2034 年期間複合年成長率將達到驚人的 23.1%。這一成長是由人們對氣候變遷及其嚴重影響的認知不斷提高所推動的，推動了對先進工具的需求，以有效預測和減輕氣候相關風險。人工智慧的創新，特別是機器學習和深度學習，使得氣候預測更加精確、細緻和即時，改變了氣候科學的模式。

該市場的主要驅動力之一是災害風險管理對預測工具的需求不斷增加。由於氣候變遷導致極端天氣事件變得越來越頻繁，政府和組織正在轉向人工智慧驅動的模型來進行預警系統和戰略準備。這些尖端工具增強了減少經濟損失和保護弱勢群體的能力，對於全球復原力建設工作至關重要。

市場範圍
起始年份	2024
預測年份	2025-2034
起始值	2.664 億美元
預測值	20億美元
複合年成長率	23.1％

基於人工智慧的氣候建模市場分為軟體和服務。 2024 年，軟體領域佔據 80% 的市場佔有率，預計將大幅成長，到 2034 年將達到 14 億美元。先進的演算法和機器學習框架使這些工具能夠處理大量氣候資料，提供準確的預測和可操作的見解。農業、能源和災害管理等領域嚴重依賴這些解決方案進行即時、數據驅動的決策。

根據應用，市場分為天氣預報、氣候預測、減少災害風險、環境監測等。 2024 年，天氣預報領域佔最大佔有率，為 45%。人工智慧模型分析包括衛星影像和氣象資料在內的大量資料集，以提供精確的預測，使企業能夠更好地規劃營運並有效降低風險。

2024 年，美國基於人工智慧的氣候建模市場佔據了 80% 的收入佔有率，預計到 2034 年將達到 5 億美元。對人工智慧研發的大量投資，加上對氣候適應力、災害管理和環境永續性的關注，刺激了複雜氣候建模工具的創新。此外，政府推動氣候重點技術的措施進一步促進了市場成長。

報告內容

第 1 章：方法論與範圍

研究設計
- 研究方法
- 資料收集方法
基礎估計和計算
- 基準年計算
- 市場估計的主要趨勢
預測模型
初步研究與驗證
- 主要來源
- 資料探勘來源
市場定義

第 2 章：執行摘要

第 3 章：產業洞察

產業生態系統分析
供應商概況
- 基於人工智慧的氣候建模軟體供應商
- 服務提供者
- 經銷商
- 最終用戶
利潤率分析
定價分析
專利格局
成本明細
技術與創新格局
重要新聞及舉措
監管格局
衝擊力
- 成長動力
  - 提高應對氣候變遷影響的意識和緊迫性
  - 人工智慧的技術進步，包括機器學習和深度學習模型
  - 政府和組織對氣候調適計畫的投資不斷增加
  - 農業、能源和災害風險管理等領域對預測工具的需求
- 產業陷阱與挑戰
  - 高品質、綜合的氣候資料有限，尤其是在發展中地區
  - 人工智慧模型的長期氣候預測的複雜性和固有的不確定性
成長潛力分析
波特的分析
PESTEL 分析

第4章：競爭格局

介紹
公司市佔率分析
競爭定位矩陣
戰略展望矩陣

第5章：市場估計與預測：按組件，2021 - 2034 年

主要趨勢
軟體
服務

第6章：市場估計與預測：依部署模式，2021 - 2034 年

主要趨勢
本地
雲

第 7 章：市場估計與預測：按技術，2021 - 2032 年

主要趨勢
機器學習
深度學習
自然語言處理 (NLP)
電腦視覺
其他

第 8 章：市場估計與預測：按應用，2021 - 2032 年

主要趨勢
天氣預報
氣候預測
減少災害風險
環境監測
其他

第 9 章：市場估計與預測：按地區，2021 - 2034 年

主要趨勢
北美洲
- 美國
- 加拿大
歐洲
- 英國
- 德國
- 法國
- 西班牙
- 義大利
- 俄羅斯
- 北歐
亞太地區
- 中國
- 印度
- 日本
- 韓國
- 澳新銀行
- 東南亞
拉丁美洲
- 巴西
- 墨西哥
- 阿根廷
中東及非洲
- 阿拉伯聯合大公國
- 南非
- 沙烏地阿拉伯

第10章：公司簡介

Amazon Web Services (AWS)
Arundo Analytics
Atmos AI
Blue Sky Analytics
ClimateAi
Cloudera
DTN
Google
Hewlett Packard Enterprise (HPE)
IBM
Jupiter Intelligence
Microsoft
NVIDIA
Open Climate Fix
Oracle Corporation
SAS Institute
Spire Global
The Weather Company
Tomorrow.io
Weather Technologies

簡介目錄

Product Code: 12534

The Global AI-Based Climate Modelling Market reached USD 266.4 million in 2024 and is forecasted to grow at an impressive CAGR of 23.1% from 2025 to 2034. This growth is propelled by heightened awareness of climate change and its severe impacts, driving the need for advanced tools to predict and mitigate climate-related risks effectively. Innovations in artificial intelligence, particularly in machine learning and deep learning, have enabled more precise, granular, and real-time climate predictions, transforming the landscape of climate science.

AI-Based Climate Modelling Market - IMG1

One of the primary drivers of this market is the increasing demand for predictive tools in disaster risk management. With extreme weather events becoming more frequent due to climate change, governments and organizations are turning to AI-driven models for early warning systems and strategic preparedness. These cutting-edge tools enhance capabilities to minimize economic losses and safeguard vulnerable populations, proving critical in resilience-building efforts globally.

Market Scope
Start Year	2024
Forecast Year	2025-2034
Start Value	$266.4 Million
Forecast Value	$2 Billion
CAGR	23.1%

The AI-based climate modelling market is segmented into software and services. In 2024, the software segment dominated with an 80% market share and is projected to grow significantly, reaching USD 1.4 billion by 2034. The widespread adoption of software solutions stems from their versatility and scalability across industries. Advanced algorithms and machine learning frameworks empower these tools to process vast amounts of climate data, delivering accurate forecasts and actionable insights. Sectors such as agriculture, energy, and disaster management heavily rely on these solutions for real-time, data-driven decision-making.

By application, the market is categorized into weather forecasting, climate prediction, disaster risk reduction, environmental monitoring, and others. The weather forecasting segment held the largest share-45%-in 2024. This dominance is attributed to the critical need for accurate, real-time weather predictions across sectors like agriculture, energy, and transportation. AI models analyze extensive datasets, including satellite imagery and meteorological data, to deliver precise forecasts, enabling businesses to better plan operations and mitigate risks effectively.

The U.S. AI-based climate modelling market captured a substantial 80% revenue share in 2024 and is projected to reach USD 500 million by 2034. This leadership is fueled by the country's robust technological infrastructure and a strong presence of leading technology companies and startups. Significant investments in AI research and development, coupled with a focus on climate resilience, disaster management, and environmental sustainability, have spurred the innovation of sophisticated climate modeling tools. Additionally, governmental initiatives to advance climate-focused technologies further bolster market growth.

Report Content

Chapter 1 Methodology & Scope

1.1 Research design
- 1.1.1 Research approach
- 1.1.2 Data collection methods
1.2 Base estimates and calculations
- 1.2.1 Base year calculation
- 1.2.2 Key trends for market estimates
1.3 Forecast model
1.4 Primary research & validation
- 1.4.1 Primary sources
- 1.4.2 Data mining sources
1.5 Market definitions

Chapter 2 Executive Summary

2.1 Industry 360⁰ synopsis, 2021 - 2034

Chapter 3 Industry Insights

3.1 Industry ecosystem analysis
3.2 Supplier landscape
- 3.2.1 AI-based climate modelling software providers
- 3.2.2 Service providers
- 3.2.3 Distributors
- 3.2.4 End users
3.3 Profit margin analysis
3.4 Pricing analysis
3.5 Patent Landscape
3.6 Cost Breakdown
3.7 Technology & innovation landscape
3.8 Key news & initiatives
3.9 Regulatory landscape
3.10 Impact forces
- 3.10.1 Growth drivers
  - 3.10.1.1 Increasing awareness and urgency to address climate change impacts
  - 3.10.1.2 Technological advancements in AI, including machine learning and deep learning models
  - 3.10.1.3 Rising investments by governments and organizations in climate resilience initiatives
  - 3.10.1.4 Demand for predictive tools in sectors like agriculture, energy, and disaster risk management
- 3.10.2 Industry pitfalls & challenges
  - 3.10.2.1 Limited availability of high-quality and comprehensive climate data, especially in developing regions
  - 3.10.2.2 Complexity and inherent uncertainties in long-term climate predictions by AI models
3.11 Growth potential analysis
3.12 Porter’s analysis
3.13 PESTEL analysis

Chapter 4 Competitive Landscape, 2024

4.1 Introduction
4.2 Company market share analysis
4.3 Competitive positioning matrix
4.4 Strategic outlook matrix

Chapter 5 Market Estimates & Forecast, By Component, 2021 - 2034 ($Bn)

5.1 Key trends
5.2 Software
5.3 Services

Chapter 6 Market Estimates & Forecast, By Deployment Mode, 2021 - 2034 ($Bn)

6.1 Key trends
6.2 On-premises
6.3 Cloud

Chapter 7 Market Estimates & Forecast, By Technology, 2021 - 2032 ($Bn)

7.1 Key trends
7.2 Machine learning
7.3 Deep learning
7.4 Natural Language Processing (NLP)
7.5 Computer vision
7.6 Others

Chapter 8 Market Estimates & Forecast, By Application, 2021 - 2032 ($Bn)

8.1 Key trends
8.2 Weather forecasting
8.3 Climate prediction
8.4 Disaster risk reduction
8.5 Environmental monitoring
8.6 Others

Chapter 9 Market Estimates & Forecast, By Region, 2021 - 2034 ($Bn)

9.1 Key trends
9.2 North America
- 9.2.1 U.S.
- 9.2.2 Canada
9.3 Europe
- 9.3.1 UK
- 9.3.2 Germany
- 9.3.3 France
- 9.3.4 Spain
- 9.3.5 Italy
- 9.3.6 Russia
- 9.3.7 Nordics
9.4 Asia Pacific
- 9.4.1 China
- 9.4.2 India
- 9.4.3 Japan
- 9.4.4 South Korea
- 9.4.5 ANZ
- 9.4.6 Southeast Asia
9.5 Latin America
- 9.5.1 Brazil
- 9.5.2 Mexico
- 9.5.3 Argentina
9.6 MEA
- 9.6.1 UAE
- 9.6.2 South Africa
- 9.6.3 Saudi Arabia