Smart Micro-Weather Forecasting Market Report 2025

The smart micro-weather forecasting market size has grown rapidly in recent years. It will grow from $1.16 billion in 2024 to $1.3 billion in 2025 at a compound annual growth rate (CAGR) of 12%. Growth during the historic period is attributed to the rising adoption of artificial intelligence (AI) and the Internet of Things (IoT) in weather prediction, increased demand for accurate short-term forecasting, greater use of satellite data and remote sensing, a growing need for hyperlocal climate insights, and the increasing importance of real-time weather monitoring in critical sectors.

The smart micro-weather forecasting market size is expected to see rapid growth in the next few years. It will grow to $2.03 billion in 2029 at a compound annual growth rate (CAGR) of 11.7%. Growth in the forecast period is driven by the increasing reliance on precision agriculture, rising demand for real-time weather insights in logistics and transportation, growing adoption of climate risk management solutions, expanded use of artificial intelligence (AI)-driven predictive analytics, and a stronger need for hyperlocal forecasting in smart cities. Key trends during this time include advancements in AI and machine learning to improve predictive accuracy, innovations in Internet of Things (IoT)-enabled weather sensors, the integration of satellite imagery with ground-based data, progress in cloud-based forecasting platforms, and the development of hyperlocal weather apps and services.

The growing reliance on precision agriculture is expected to drive the expansion of the smart micro-weather forecasting market. Precision agriculture involves using advanced technologies such as sensors, drones, GPS, and analytics to optimize crop production and resource use. This approach is becoming increasingly important due to the need to boost crop yields to meet the demands of a rapidly growing population while efficiently managing resources such as water, fertilizers, and pesticides. Smart micro-weather forecasting supports precision agriculture by delivering hyper-local, real-time weather insights that help farmers make timely, data-driven decisions to improve crop yields and resource efficiency. For example, in January 2024, the Government Accountability Office, a US government agency, reported that in 2023, 27% of farms and ranches in the U.S. had adopted precision agriculture practices for managing crops or livestock. As a result, the rising reliance on precision agriculture is fueling growth in the smart micro-weather forecasting market.

Leading companies in the smart micro-weather forecasting market are focusing on innovative solutions such as high-resolution weather models to improve forecast accuracy, deliver real-time localized insights, and support better decision-making in weather-sensitive industries. High-resolution weather models simulate atmospheric conditions at very detailed spatial and temporal scales, allowing for more precise local weather patterns and location-specific forecasts. For example, in October 2022, Jua.ai AG, a Switzerland-based weather forecasting and atmospheric modeling company, launched an AI-powered weather forecasting service offering global, high-resolution predictions. This service significantly outperforms existing numerical models and enables businesses of all sizes to access more accurate and timely weather data. By applying deep learning technology, the platform enhances geospatial and temporal resolution along with update frequency, transforming meteorological analysis capabilities. These advancements are expected to boost adoption across sectors such as agriculture, energy, aviation, logistics, and insurance, where accurate, localized, and real-time weather insights are essential for operational efficiency, risk management, and strategic planning.

In January 2022, Vaisala Corporation, a Finland-based environmental and industrial measurement company, acquired Whether or Knot LLC (doing business as AerisWeather) for $26 million. This acquisition aims to accelerate Vaisala’s growth in the weather and environmental data sector by expanding its Data as a Service (DaaS) and Software as a Service (SaaS) offerings, reaching new customer segments, and strengthening its recurring revenue streams. By combining Vaisala’s advanced measurement and forecasting technologies with AerisWeather’s leading data services and developer tools, the company plans to deliver more comprehensive, accurate, and easily accessible weather and environmental insights. Whether or Knot LLC, based in the US, specializes in smart micro-weather forecasting, leveraging high-resolution data from a vast network of weather stations along with advanced datasets optimized for AI, machine learning, and real-time analytics.

Major players in the smart micro-weather forecasting market are International Business Machines Corporation, DTN LLC, AccuWeather Inc., Pelmorex Corp., Weathernews Inc., Spire Global Inc., METRAWEATHER (UK) LIMITED, The Tomorrow Companies Inc., Earth Networks Inc., Baron Weather Inc., Skymet Weather Services Private Limited, Davis Instruments Corporation, Ubimet GmbH, Sencrop SAS, Foreca Ltd., The Weather Company LLC, OpenWeather Ltd., Climavision LLC, Benchmark Labs, Atmo.ai.

North America was the largest region in the smart micro-weather forecasting market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in smart micro-weather forecasting report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa. The countries covered in the smart micro-weather forecasting market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report’s Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The rapid escalation of U.S. tariffs and the resulting trade tensions in spring 2025 are significantly impacting the utilities sector, particularly in power generation, grid infrastructure, and renewable energy projects. Higher duties on imported equipment such as turbines, transformers, solar panels, and battery storage systems have increased capital and operational costs for utility providers, forcing them to reconsider project timelines or pass on expenses to consumers through higher energy rates. The water and waste management segments are also affected, with tariffs driving up the cost of essential machinery, piping, and treatment technologies. Additionally, retaliatory tariffs have disrupted global supply chains for critical raw materials like rare earth metals used in clean energy technologies, further complicating the transition to sustainable energy sources. The sector must now prioritize domestic sourcing, digitalization, and efficiency-driven innovations to manage escalating costs while ensuring energy security and regulatory compliance.

Smart micro-weather forecasting leverages advanced sensors, data analytics, and artificial intelligence (AI) to predict highly localized weather conditions with greater accuracy. It focuses on capturing small-area variations, such as those within neighborhoods or city blocks, providing timely and precise insights that surpass traditional large-scale forecasts.

The key elements of smart micro-weather forecasting include hardware, software, and services. Hardware involves the physical devices that measure and gather atmospheric data, supplying accurate inputs for weather predictions. Forecasting is categorized into nowcasting, short-range, medium-range, and long-range types. These forecasts find applications in sectors such as agriculture, transportation, energy and utilities, aviation, marine, retail, and government and defense, serving various end-users including commercial, industrial, government, and others.

The smart micro-weather forecasting market research report is one of a series of new reports that provides smart micro-weather forecasting market statistics, including smart micro-weather forecasting industry global market size, regional shares, competitors with the smart micro-weather forecasting market share, smart micro-weather forecasting market segments, market trends, and opportunities, and any further data you may need to thrive in the smart micro-weather forecasting industry. This smart micro-weather forecasting market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The smart micro-weather forecasting market consists of revenues earned by entities by providing services such as real-time hyperlocal weather prediction, high-resolution climate monitoring, satellite-based weather analysis, and advanced modeling for short-term atmospheric changes. The market value includes the value of related goods sold by the service provider or included within the service offering. The smart micro-weather forecasting market also includes sales of advanced forecasting systems, artificial intelligence (AI)-powered weather prediction software, high-resolution sensors, internet of things (IoT)-enabled weather monitoring devices, satellite data integration tools, and cloud-based platforms. Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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