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市场调查报告书
商品编码
1697385

人工智慧天气预报市场－2025年至2030年的预测

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个工作天内

价格
简介目录

人工智慧天气预测市场预计将从 2025 年的 6,089.13 亿美元成长到 2030 年的 8,913.92 亿美元，在预测期内实现 7.92% 的强劲复合年增长率。

由于各个商业领域都需要准确可靠的天气预报，因此对人工智慧主导的天气预报技术的需求正在上升。目前的行业趋势集中在提高预测的准确性和速度。这些系统利用卫星、气象站和感测器的资料来识别复杂的模式，从而改善未来的天气预测。深度学习演算法和神经网路在改善天气预报方面发挥关键作用，为温度、降水和恶劣天气提供准确的洞察。人工智慧技术可以针对特定道路和地区做出预测，辅助城市规划、道路维护和农业运作。

人工智慧天气预报市场成长动力：

  • 极端天气事件发生频率增加是一个主要驱动因素。随着全球严重飓风、洪水和干旱等恶劣天气事件发生率的增加，天气预报的准确性变得至关重要。透过处理庞大的资料集，人工智慧系统可以提高预测质量，使紧急服务能够更好地预防和应对灾难。例如，根据欧洲环境署2024年发布的资料，过去40年间，极端天气事件已造成欧洲8.5万至14.5万人死亡，经济损失达5兆欧元。

地理展望：

AI天气预报市场正在跨地区呈现多样化的成长模式：

  • 北美：由于采用了先进的技术、政府的支持性政策以及农业和能源部门对准确天气资料的巨大需求，该地区在市场中处于领先地位。人工智慧可以提高可再生能源系统的效率和准确性，有助于提高发电量。
  • 南美洲：儘管发展落后于其他地区，但南美洲预计将在人工智慧天气预报领域实现成长。
  • 欧洲：预计整个欧洲市场将显着成长，德国、英国和义大利等国家将受益于可再生能源投资。
  • 中东和非洲：由于先进的灾害管理系统的改进，该地区的人工智慧天气预报正在快速成长。各国政府正大力投资建置自然灾害预警系统，创造了庞大的机会。
  • 亚太地区：随着中国和印度等国家的企业（尤其是零售和农业领域的企业）加大对数位天气预报技术的投资，亚太地区的基于人工智慧的预报正在快速成长。 2024年11月，印度地球科学部宣布决定将人工智慧技术融入其天气和气候预报系统，以提高准确性和系统性能。

为什么要购买这份报告？

  • 深刻分析：获得涵盖主要地区和新兴地区的深入市场洞察，重点关注客户群、政府政策和社会经济因素、消费者偏好、垂直行业和其他子区隔。
  • 竞争格局：了解全球主要企业所采用的策略策略，并了解正确策略带来的潜在市场渗透。
  • 市场趋势和驱动因素：探索动态因素和关键市场趋势以及它们将如何影响未来的市场发展。
  • 可行的建议：利用洞察力做出策略决策，在动态环境中开闢新的业务流和收益。
  • 适用范围广：对于新兴企业、科学研究机构、顾问公司、中小企业、大型企业都有利且划算。

它有什么用途？

产业和市场考量、商业机会评估、产品需求预测、打入市场策略、地理扩张、资本支出决策、法律规范与影响、新产品开发、竞争影响

研究范围

  • 2022年至2030年的历史资料与预测
  • 成长机会、挑战、供应链前景、法规结构、客户行为和趋势分析
  • 竞争定位、策略和市场占有率分析
  • 细分和区域分析，包括收益成长和预测国家
  • 公司概况（特别是主要趋势）

人工智慧天气预报市场细分为：

依技术

  • 机器学习
  • 深度学习
  • 其他的

按服务

  • 天气预报
  • 气候建模
  • 恶劣天气预报
  • 其他的

按最终用途

  • 航空
  • 海洋
  • 农业
  • 能源与公共产业
  • 运输和物流
  • 其他的

按地区

  • 北美洲
  • 美国
  • 加拿大
  • 墨西哥
  • 南美洲
  • 巴西
  • 阿根廷
  • 其他的
  • 欧洲
  • 英国
  • 德国
  • 法国
  • 西班牙
  • 其他的
  • 中东和非洲
  • 沙乌地阿拉伯
  • UAE
  • 其他的
  • 亚太地区
  • 中国
  • 日本
  • 印度
  • 韩国
  • 台湾
  • 其他的

目录

第一章 引言

  • 市场概览
  • 市场定义
  • 研究范围
  • 市场区隔
  • 货币
  • 先决条件
  • 基准年和预测年时间表
  • 相关人员的主要利益

第二章调查方法

  • 研究设计
  • 研究过程

第三章执行摘要

  • 主要发现

第四章 市场动态

  • 市场驱动因素
  • 市场限制
  • 波特五力分析
  • 产业价值链分析
  • 分析师观点

第五章 AI 天气预报市场（按技术）

  • 介绍
  • 机器学习
  • 深度学习
  • 其他的

第六章 AI 天气预报市场（按服务）

  • 介绍
  • 天气预报
  • 气候建模
  • 恶劣天气预报
  • 其他的

第七章人工智慧天气预报市场（依最终用途）

  • 介绍
  • 航空
  • 海洋
  • 农业
  • 能源与公共产业
  • 运输和物流
  • 其他最终用途

第八章 AI 天气预报市场（按地区）

  • 介绍
  • 北美洲
    • 依技术
    • 按服务
    • 按最终用途
    • 按国家
  • 南美洲
    • 依技术
    • 按服务
    • 按最终用途
    • 按国家
  • 欧洲
    • 依技术
    • 按服务
    • 按最终用途
    • 按国家
  • 中东和非洲
    • 依技术
    • 按服务
    • 按最终用途
    • 按国家
  • 亚太地区
    • 依技术
    • 按服务
    • 按最终用途
    • 按国家

第九章竞争格局及分析

  • 主要企业和策略分析
  • 市场占有率分析
  • 合併、收购、协议和合作
  • 竞争仪錶板

第十章 公司简介

  • Tomorrow.io（ClimaCell）
  • Google
  • IBM
  • AccuWeather
  • Microsoft
  • Nvidia
  • Jupiter Intelligence
  • DTN
  • Understory
  • WeatherFlow
  • Open Climate Fix
  • Atmo Inc.
  • Climavision
简介目录
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