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市場調查報告書
商品編碼
1697385

人工智慧天氣預報市場－2025年至2030年的預測

AI in Weather Prediction Market - Forecasts from 2025 to 2030
出版日期: | 出版商: Knowledge Sourcing Intelligence | 英文 140 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

人工智慧天氣預測市場預計將從 2025 年的 6,089.13 億美元成長到 2030 年的 8,913.92 億美元，在預測期內實現 7.92% 的強勁複合年成長率。

由於各個商業領域都需要準確可靠的天氣預報，因此對人工智慧主導的天氣預報技術的需求正在上升。目前的行業趨勢集中在提高預測的準確性和速度。這些系統利用衛星、氣象站和感測器的資料來識別複雜的模式，從而改善未來的天氣預測。深度學習演算法和神經網路在改善天氣預報方面發揮關鍵作用，為溫度、降水和惡劣天氣提供準確的洞察。人工智慧技術可以針對特定道路和地區做出預測，輔助城市規劃、道路維護和農業運作。

人工智慧天氣預報市場成長動力：

  • 極端天氣事件發生頻率增加是一個主要促進因素。隨著全球嚴重颶風、洪水和乾旱等惡劣天氣事件發生率的增加，天氣預報的準確性變得至關重要。透過處理龐大的資料集，人工智慧系統可以提高預測質量，使緊急服務能夠更好地預防和應對災難。例如，根據歐洲環境署2024年發布的資料，過去40年間，極端天氣事件已造成歐洲8.5萬至14.5萬人死亡，經濟損失達5兆歐元。

地理展望：

AI天氣預報市場正在跨地區呈現多樣化的成長模式：

  • 北美：由於採用了先進的技術、政府的支持性政策以及農業和能源部門對準確天氣資料的巨大需求，該地區在市場中處於領先地位。人工智慧可以提高可再生能源系統的效率和準確性，有助於提高發電量。
  • 南美洲：儘管發展落後於其他地區，但南美洲預計將在人工智慧天氣預報領域實現成長。
  • 歐洲：預計整個歐洲市場將顯著成長，德國、英國和義大利等國家將受益於可再生能源投資。
  • 中東和非洲：由於先進的災害管理系統的改進，該地區的人工智慧天氣預報正在快速成長。各國政府正大力投資建置自然災害預警系統，創造了龐大的機會。
  • 亞太地區：隨著中國和印度等國家的企業（尤其是零售和農業領域的企業）加大對數位天氣預報技術的投資，亞太地區的基於人工智慧的預報正在快速成長。 2024年11月，印度地球科學部宣布決定將人工智慧技術融入其天氣和氣候預報系統，以提高準確性和系統性能。

為什麼要購買這份報告？

  • 深刻分析：獲得涵蓋主要地區和新興地區的深入市場洞察，重點關注客戶群、政府政策和社會經濟因素、消費者偏好、垂直行業和其他子區隔。
  • 競爭格局：了解全球主要企業所採用的策略策略，並了解正確策略帶來的潛在市場滲透。
  • 市場趨勢和促進因素：探索動態因素和關鍵市場趨勢以及它們將如何影響未來的市場發展。
  • 可行的建議：利用洞察力做出策略決策，在動態環境中開闢新的業務流和收益。
  • 適用範圍廣：對於新興企業、科學研究機構、顧問公司、中小企業、大型企業都有利且划算。

它有什麼用途？

產業和市場考量、商業機會評估、產品需求預測、打入市場策略、地理擴張、資本支出決策、法律規範與影響、新產品開發、競爭影響

研究範圍

  • 2022年至2030年的歷史資料與預測
  • 成長機會、挑戰、供應鏈前景、法規結構、客戶行為和趨勢分析
  • 競爭定位、策略和市場佔有率分析
  • 細分和區域分析，包括收益成長和預測國家
  • 公司概況（特別是主要趨勢）

人工智慧天氣預報市場細分為：

依技術

  • 機器學習
  • 深度學習
  • 其他

按服務

  • 天氣預報
  • 氣候建模
  • 惡劣天氣預報
  • 其他

按最終用途

  • 航空
  • 海洋
  • 農業
  • 能源與公共產業
  • 運輸和物流
  • 其他

按地區

  • 北美洲
  • 美國
  • 加拿大
  • 墨西哥
  • 南美洲
  • 巴西
  • 阿根廷
  • 其他
  • 歐洲
  • 英國
  • 德國
  • 法國
  • 西班牙
  • 其他
  • 中東和非洲
  • 沙烏地阿拉伯
  • UAE
  • 其他
  • 亞太地區
  • 中國
  • 日本
  • 印度
  • 韓國
  • 台灣
  • 其他

目錄

第1章 引言

  • 市場概覽
  • 市場定義
  • 研究範圍
  • 市場區隔
  • 貨幣
  • 先決條件
  • 基準年和預測年時間表
  • 相關人員的主要利益

第2章調查方法

  • 研究設計
  • 研究過程

第3章執行摘要

  • 主要發現

第4章 市場動態

  • 市場促進因素
  • 市場限制
  • 波特五力分析
  • 產業價值鏈分析
  • 分析師觀點

第5章 AI 天氣預報市場（按技術）

  • 介紹
  • 機器學習
  • 深度學習
  • 其他

第6章 AI 天氣預報市場（按服務）

  • 介紹
  • 天氣預報
  • 氣候建模
  • 惡劣天氣預報
  • 其他

第7章人工智慧天氣預報市場（依最終用途）

  • 介紹
  • 航空
  • 海洋
  • 農業
  • 能源與公共產業
  • 運輸和物流
  • 其他最終用途

第8章 AI 天氣預報市場（按地區）

  • 介紹
  • 北美洲
    • 依技術
    • 按服務
    • 按最終用途
    • 按國家
  • 南美洲
    • 依技術
    • 按服務
    • 按最終用途
    • 按國家
  • 歐洲
    • 依技術
    • 按服務
    • 按最終用途
    • 按國家
  • 中東和非洲
    • 依技術
    • 按服務
    • 按最終用途
    • 按國家
  • 亞太地區
    • 依技術
    • 按服務
    • 按最終用途
    • 按國家

第9章競爭格局及分析

  • 主要企業和策略分析
  • 市場佔有率分析
  • 合併、收購、協議和合作
  • 競爭儀錶板

第10章 公司簡介

  • Tomorrow.io（ClimaCell）
  • Google
  • IBM
  • AccuWeather
  • Microsoft
  • Nvidia
  • Jupiter Intelligence
  • DTN
  • Understory
  • WeatherFlow
  • Open Climate Fix
  • Atmo Inc.
  • Climavision
簡介目錄
Product Code: KSI061617300

The AI in weather prediction market is set to witness robust growth at a CAGR of 7.92% during the forecast period to be worth US$891.392 million in 2030 from US$608.913 million in 2025.

The demand for AI-driven weather forecasting technology is on the rise as various business sectors seek precise and reliable weather predictions. Current industry trends emphasize enhancing both the precision and speed of forecasts. These systems leverage data from satellites, weather stations, and sensors to identify intricate patterns that refine future weather estimates. Deep learning algorithms and neural networks play a crucial role in improving weather predictions, offering accurate insights into temperatures, rainfall, and severe weather events. AI technology enables predictions tailored to specific streets and neighborhoods, aiding city planning, road management, and farming practices.

Growth Drivers in the AI Weather Prediction Market:

  • The increasing frequency of extreme weather events is a significant driver. As the global incidence of severe weather phenomena such as intense hurricanes, floods, and droughts rises, the accuracy of weather forecasts becomes paramount. AI systems, by processing extensive datasets, enhance prediction quality, enabling emergency services to better prepare for and respond to disasters. For example, data from the European Environment Agency in 2024 indicated that Europe experienced between 85,000 and 145,000 deaths and incurred half a trillion euros in economic damages due to extreme weather events over the past four decades.

Geographical Outlook:

The AI in Weather Prediction market exhibits diverse growth patterns across different regions:

  • North America: This region leads the market due to its advanced technology adoption, supportive government policies, and substantial demand for accurate weather data from the agriculture and energy sectors. AI enhances the efficiency and accuracy of renewable energy systems, contributing to improved power generation.
  • South America: While still trailing other regions in development, South America is expected to expand its AI weather prediction sector. Significant market growth opportunities exist through improvements in agricultural efficiency facilitated by enhanced forecasting.
  • Europe: Notable market expansion is anticipated across Europe, with countries like Germany, the UK, and Italy benefiting from their investments in renewable energy. Increased investment in advanced weather forecasting technology by public safety authorities and economic institutions drives further advancements.
  • Middle East and Africa: This region demonstrates rapid growth in AI weather prediction driven by improvements in advanced disaster management systems. Governments are investing heavily in creating advanced warning systems for natural disasters, creating significant business opportunities.
  • Asia-Pacific: The Asia-Pacific region is experiencing rapid growth in AI-based forecasting as businesses increase their investments in digital weather forecasting technologies, particularly in the retail and agricultural sectors in countries like China and India. In November 2024, India's Ministry of Earth Sciences announced its decision to integrate AI technology into weather and climate forecasting systems to enhance accuracy and system performance.

Reasons for buying this report:-

  • Insightful Analysis: Gain detailed market insights covering major as well as emerging geographical regions, focusing on customer segments, government policies and socio-economic factors, consumer preferences, industry verticals, other sub- segments.
  • Competitive Landscape: Understand the strategic maneuvers employed by key players globally to understand possible market penetration with the correct strategy.
  • Market Drivers & Future Trends: Explore the dynamic factors and pivotal market trends and how they will shape up future market developments.
  • Actionable Recommendations: Utilize the insights to exercise strategic decision to uncover new business streams and revenues in a dynamic environment.
  • Caters to a Wide Audience: Beneficial and cost-effective for startups, research institutions, consultants, SMEs, and large enterprises.

What do businesses use our reports for?

Industry and Market Insights, Opportunity Assessment, Product Demand Forecasting, Market Entry Strategy, Geographical Expansion, Capital Investment Decisions, Regulatory Framework & Implications, New Product Development, Competitive Intelligence

Report Coverage:

  • Historical data & forecasts from 2022 to 2030
  • Growth Opportunities, Challenges, Supply Chain Outlook, Regulatory Framework, Customer Behaviour, and Trend Analysis
  • Competitive Positioning, Strategies, and Market Share Analysis
  • Revenue Growth and Forecast Assessment of segments and regions including countries
  • Company Profiling (Strategies, Products, Financial Information, and Key Developments among others)

AI In Weather Prediction Market is analyzed into the following segments:

By Technology

  • Machine Learning
  • Deep Learning
  • Others

By Services

  • Weather Forecasting
  • Climate Modeling
  • Severe Weather Prediction
  • Others

By End-User

  • Aviation
  • Marine
  • Agriculture
  • Energy and Utilities
  • Transportation and Logistics
  • Others

By Geography

  • North America
  • USA
  • Canada
  • Mexico
  • South America
  • Brazil
  • Argentina
  • Others
  • Europe
  • United Kingdom
  • Germany
  • France
  • Spain
  • Others
  • Middle East and Africa
  • Saudi Arabia
  • UAE
  • Others
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Taiwan
  • Others

TABLE OF CONTENTS

1. INTRODUCTION

  • 1.1. Market Overview
  • 1.2. Market Definition
  • 1.3. Scope of the Study
  • 1.4. Market Segmentation
  • 1.5. Currency
  • 1.6. Assumptions
  • 1.7. Base and Forecast Years Timeline
  • 1.8. Key benefits for the stakeholders

2. RESEARCH METHODOLOGY

  • 2.1. Research Design
  • 2.2. Research Process

3. EXECUTIVE SUMMARY

  • 3.1. Key Findings

4. MARKET DYNAMICS

  • 4.1. Market Drivers
  • 4.2. Market Restraints
  • 4.3. Porter's Five Forces Analysis
    • 4.3.1. Bargaining Power of Suppliers
    • 4.3.2. Bargaining Power of Buyers
    • 4.3.3. Threat of New Entrants
    • 4.3.4. Threat of Substitutes
    • 4.3.5. Competitive Rivalry in the Industry
  • 4.4. Industry Value Chain Analysis
  • 4.5. Analyst View

5. AI IN WEATHER PREDICTION MARKET BY TECHNOLOGY

  • 5.1. Introduction
  • 5.2. Machine Learning
  • 5.3. Deep Learning
  • 5.4. Others

6. AI IN WEATHER PREDICTION MARKET BY SERVICES

  • 6.1. Introduction
  • 6.2. Weather Forecasting
  • 6.3. Climate Modeling
  • 6.4. Severe Weather Prediction
  • 6.5. Others

7. AI IN WEATHER PREDICTION MARKET BY END-USER

  • 7.1. Introduction
  • 7.2. Aviation
  • 7.3. Marine
  • 7.4. Agriculture
  • 7.5. Energy and Utilities
  • 7.6. Transportation and Logistics
  • 7.7. Other End-Users

8. AI IN WEATHER PREDICTION MARKET BY GEOGRAPHY

  • 8.1. Introduction
  • 8.2. North America
    • 8.2.1. By Technology
    • 8.2.2. By Services
    • 8.2.3. By End User
    • 8.2.4. By Country
      • 8.2.4.1. USA
      • 8.2.4.2. Canada
      • 8.2.4.3. Mexico
  • 8.3. South America
    • 8.3.1. By Technology
    • 8.3.2. By Services
    • 8.3.3. By End User
    • 8.3.4. By Country
      • 8.3.4.1. Brazil
      • 8.3.4.2. Argentina
      • 8.3.4.3. Others
  • 8.4. Europe
    • 8.4.1. By Technology
    • 8.4.2. By Services
    • 8.4.3. By End User
    • 8.4.4. By Country
      • 8.4.4.1. United Kingdom
      • 8.4.4.2. Germany
      • 8.4.4.3. France
      • 8.4.4.4. Spain
      • 8.4.4.5. Others
  • 8.5. Middle East and Africa
    • 8.5.1. By Technology
    • 8.5.2. By Services
    • 8.5.3. By End User
    • 8.5.4. By Country
      • 8.5.4.1. Saudi Arabia
      • 8.5.4.2. UAE
      • 8.5.4.3. Others
  • 8.6. Asia Pacific
    • 8.6.1. By Technology
    • 8.6.2. By Services
    • 8.6.3. By End User
    • 8.6.4. By Country
      • 8.6.4.1. China
      • 8.6.4.2. Japan
      • 8.6.4.3. India
      • 8.6.4.4. South Korea
      • 8.6.4.5. Taiwan
      • 8.6.4.6. Others

9. COMPETITIVE ENVIRONMENT AND ANALYSIS

  • 9.1. Major Players and Strategy Analysis
  • 9.2. Market Share Analysis
  • 9.3. Mergers, Acquisitions, Agreements, and Collaborations
  • 9.4. Competitive Dashboard

10. COMPANY PROFILES

  • 10.1. Tomorrow.io (ClimaCell)
  • 10.2. Google
  • 10.3. IBM
  • 10.4. AccuWeather
  • 10.5. Microsoft
  • 10.6. Nvidia
  • 10.7. Jupiter Intelligence
  • 10.8. DTN
  • 10.9. Understory
  • 10.10. WeatherFlow
  • 10.11. Open Climate Fix
  • 10.12. Atmo Inc.
  • 10.13. Climavision