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OpenWeatherMap

OpenWeatherMap is an online service owned by OpenWeather Ltd. that delivers global weather data, including current conditions, forecasts, and historical records, primarily through application programming interfaces () designed for developers and businesses. Headquartered in , , the company was founded in 2011 and specializes in aggregating and processing meteorological information from diverse sources such as global weather models, satellites, radars, and a network of over 80,000 private weather stations to provide accurate, location-specific insights for any point on Earth. The platform offers a range of products, including the One Call 3.0 for comprehensive overviews with human-readable summaries and AI-powered assistance, as well as interactive maps and specialized dashboards for sectors like energy and monitoring. OpenWeatherMap supports hyperlocal minute-by-minute forecasts, up to 16-day daily predictions, and historical data spanning more than 46 years, enabling applications in industries such as , , and through light-speed access and customizable subscriptions. Founded by IT experts including co-founders Olga Ukolova (CEO) and Denis Ukolov (CIO), the company leverages and to enhance data accuracy and deliver over two billion weather calls daily to millions of users worldwide.

History

Founding and Early Years

OpenWeatherMap was founded in 2012 by Denis Ukolov and Olga Ukolova, a husband-and-wife team with backgrounds in IT and . The service was launched in 2012, with the formal incorporation of OpenWeather Ltd. occurring in November 2017. The initiative stemmed from their vision to democratize access to global weather information, offering it through a simple interface tailored for developers and businesses seeking to integrate real-time environmental data into applications, websites, and services. This approach addressed the need for affordable, programmable weather resources beyond traditional meteorological services, emphasizing ease of use and broad coverage. In its early years, OpenWeatherMap operated as a compact team of IT specialists and data scientists, concentrating on building core APIs that delivered current weather conditions such as , , , and for locations worldwide. Headquartered initially in , the startup leveraged sources and basic processing techniques to compile and serve this information, starting with simple and XML formats to facilitate quick adoption by the developer community. The focus remained on reliability and scalability, with initial efforts directed at ensuring the API could handle queries for thousands of cities without downtime, laying the groundwork for future expansions. A pivotal moment came with the launch of the free tier API, which allowed up to a certain number of daily calls at no cost and spurred rapid user growth by removing barriers for experimentation and prototyping. This release marked the transition from a niche tool to a go-to resource, attracting hobbyists, startups, and educators who integrated functionalities into diverse projects, from mobile apps to devices. The free tier solidified OpenWeatherMap's reputation as an accessible entry point into data services, fostering a growing community of users.

Growth and Milestones

In 2015, OpenWeatherMap expanded its reach through key integrations with services, following 's closure of its own and cloud solutions in June of that year. The company was recommended as a primary data provider for embedding in the JavaScript API, enabling developers to incorporate real-time overlays into mapping applications. Additionally, OpenWeatherMap's became the backbone for the "Bid by Weather" script in , allowing advertisers to dynamically adjust bids based on local conditions to optimize campaign performance. The platform experienced significant user base growth in the ensuing years, encompassing independent developers, businesses, and companies. By 2025, this figure had grown to more than 8 million consumers worldwide, reflecting the increasing demand for reliable weather data across industries such as , , and energy. In , OpenWeatherMap advanced its mobile accessibility with integrations into wearable and smartphone ecosystems. Its APIs were incorporated into Samsung Galaxy Watch Studio, providing developers with free access to global weather data for custom watch faces and applications on Watches. This expansion complemented broader integrations, including support for and apps, which facilitated seamless weather data delivery to users via native interfaces. By the early , OpenWeatherMap's infrastructure had scaled to generate over 2 billion weather forecasts daily, underscoring its role as a leading provider of and global meteorological insights. This milestone highlighted the platform's capacity to handle massive data volumes while maintaining high accuracy through aggregated sources and proprietary modeling. OpenWeatherMap established the OpenWeather Foundation as part of its group initiatives, emphasizing access, educational programs, and sustainability efforts in weather science. The foundation supports collaborations with universities, provides free data for research on and health, and promotes community-driven contributions to enhance global data coverage.

Company Profile

Operations and Global Reach

OpenWeather Ltd. is a privately held company headquartered in , , specializing in the provision of data services. The organization delivers comprehensive meteorological information to clients across the globe, enabling applications in diverse sectors such as for crop management and yield prediction, and and for route optimization and . Its services cover every point on , supporting both individual developers and large enterprises with and global insights. As of 2024, OpenWeatherMap boasts over 8 million registered users worldwide and processes more than 2 billion weather forecasts daily through its infrastructure. This scale reflects significant growth from earlier figures reported around , underscoring the platform's expanding role in digital weather services amid rising demand for data-driven . The company manages approximately 5 petabytes of environmental data, ensuring and reliability for its user base. OpenWeatherMap enhances data accuracy through strategic collaborations with leading meteorological institutions, including the United Kingdom's and the ' (NOAA). These partnerships integrate official observational data, radar feeds, and model outputs to refine forecasts, with updates disseminated every 10 minutes. Additionally, the company holds memberships in prominent international bodies, such as the (WMO) and the (ESA), which facilitate access to advanced datasets and contribute to global standards in weather information dissemination.

Leadership and Organization

OpenWeather Ltd, the entity behind OpenWeatherMap, is directed by Denis Ukolov and Olga Ukolova, both appointed as directors on November 6, 2017. Ukolov, with extensive experience in IT architecture and big data technologies, leads strategic initiatives, while Ukolova contributes to operational leadership and . The organization comprises a team of IT experts and data scientists who have been advancing deep weather data science. This team emphasizes practical applications of artificial intelligence (AI), machine learning (ML), and information technology in environmental data processing, fostering technological innovation in meteorology. OpenWeather maintains an organizational focus on innovation in environmental data through the OpenWeather Foundation, which promotes open access to weather datasets and supports sustainability efforts. The foundation provides free weather data valued at £5 million annually to scientific research, education, and non-profit projects, while collaborating with over 500 universities on climate change and community protection initiatives. The company culture is characterized by passion, intelligence, and responsibility, driving a commitment to excellence in weather solutions and open-source contributions.

Products and Services

Core Weather APIs

OpenWeatherMap provides a suite of core weather APIs that enable developers to access essential meteorological data for integration into various applications. The primary offerings include the Current Weather Data , which delivers real-time conditions such as , , , and for any global location, updated frequently based on global models. This supports queries by city name, geographic coordinates, or , making it suitable for immediate weather displays in mobile apps or websites. Forecast APIs extend beyond current conditions to predict future weather patterns. The 5 Day / 3 Hour Forecast provides at three-hour intervals for up to five days, while the 16 Day / Daily Forecast offers daily summaries for up to 16 days, including highs and lows, probability, and . For shorter-term predictions, the One Call 3.0 includes a minutely forecast serving as a nowcast for up to one hour, helping users anticipate immediate events. Long-term forecasts, available through specialized endpoints in paid plans, extend up to 1.5 years with aggregated daily for planning purposes like or . Historical weather data is accessible via the History API, which provides over 46 years of hourly records dating back to 1979, allowing retrieval of past conditions for any location to support climate analysis or . All core APIs output data in or XML formats, with being the default for its lightweight structure and ease of parsing in modern programming languages. Multilingual support is integrated through human-readable weather descriptions in over 50 languages, facilitating global applications without translation overhead. Access to these APIs is structured around free and paid tiers to accommodate different usage scales. The free tier offers 1,000 API calls per day for the One Call API 3.0, sufficient for basic personal or small-scale projects. Paid subscription models, such as the , , and plans, unlock higher call limits—up to millions per month—for APIs like Current Weather and Forecasts, along with advanced features like increased historical depth and priority support, while One Call API 3.0 uses a separate pay-as-you-call model priced at 0.0015 USD per additional call beyond the free allowance. These APIs are designed specifically for , supporting seamless integration into websites, mobile applications, and () devices through simple HTTP GET requests authenticated via API keys.

Specialized Features and Integrations

OpenWeatherMap offers interactive weather maps that enable users to visualize meteorological data through overlays such as , , , , and clouds, with 15 distinct layers available for current, forecast, and historical conditions dating back to March 2019. These maps support integration into websites and applications via tile-based , allowing developers to overlay information on custom interfaces for enhanced user engagement. Additionally, the platform provides systems that deliver notifications for events, aggregating data from national warning systems worldwide to cover phenomena like storms, floods, and . The Dashboard further refines this by offering tailored forecasts and alerts for high-impact events, aiding industries such as and logistics in proactive decision-making. For mobile and device integrations, OpenWeatherMap supports embedding its into and applications, facilitating the development of weather-enabled apps that access without building proprietary systems. The service extends to wearable devices, including integration with through Galaxy Watch Studio, where developers can incorporate OpenWeatherMap's free to display global weather information directly on watch faces and complications. In third-party ecosystems, OpenWeatherMap embeds seamlessly into via compatibility, a recommendation from following the 2015 closure of its own weather services, enabling location-based weather visualizations on interactive maps. It also integrates with (formerly AdWords) for weather-targeted advertising campaigns, allowing businesses to optimize location-based services by factoring in real-time meteorological conditions. Enterprise users benefit from additional services like custom analytics, which provide tailored insights into weather patterns for sectors such as energy and transportation, often combined with bulk data downloads in or formats for offline analysis. These bulk downloads include current, forecast, and historical datasets spanning over 46 years, downloadable as prepared files or custom coordinate sets to support large-scale data processing. Developer resources are robust, with official repositories offering code samples, libraries, and examples in languages like , , and to simplify implementation. Comprehensive documentation covers endpoints, , and best practices, including a curated list of open-source projects via the Awesome OpenWeather repository for community-driven integrations.

Technology and Innovations

Data Sources and Processing

OpenWeatherMap aggregates its primary weather data from a network of global meteorological agencies, including the (NOAA), the United Kingdom's , the European Centre for Medium-Range Weather Forecasts (ECMWF), and Environment Canada. This data is supplemented by observational inputs from over 82,000 weather stations, radar systems, satellites, rain gauges, and other sensors deployed worldwide. These sources provide a foundation of raw meteorological observations, ensuring comprehensive coverage of atmospheric conditions across diverse geographies. Data collection occurs through real-time feeds from these global and local networks, with updates integrated as frequently as every 10 minutes to capture dynamic patterns. Weather stations contribute ground-level measurements of , , , and , while radars detect intensity and movement, and satellites offer overhead imagery for , sea surface temperatures, and storm tracking. This multi-source approach enables the aggregation of both surface and upper-atmospheric , forming a robust for subsequent processing. The processing pipeline begins with cleaning and validation of incoming data to remove outliers, correct instrumental errors, and ensure temporal and spatial consistency. Aggregation then combines these validated inputs from disparate sources into unified datasets, harmonizing formats and resolving discrepancies for reliable outputs. This backend workflow prioritizes accuracy by cross-referencing observations against established benchmarks, resulting in processed data suitable for high-resolution applications, such as hourly intervals. OpenWeatherMap's coverage extends to virtually any location on , facilitated by built-in geocoding that supports queries by / coordinates, city names, or ZIP codes for over 200,000 populated places and remote areas alike. Quality assurance aligns with (WMO) standards through the use of compliant sources like reports from stations and integration with agency-verified feeds, achieving low error rates such as mean absolute errors of approximately 0.5°C for temperature nowcasts. This framework delivers consistent, high-resolution data essential for applications requiring precise environmental insights.

AI and Machine Learning Applications

OpenWeatherMap integrates (AI) and (ML) to enhance the accuracy of weather forecasts and enable precise nowcasting. By employing convolutional neural networks and other ML algorithms, the platform refines models with inputs from radars, satellites, and over 82,000 weather stations, achieving improved short-term and storm predictions. These techniques, developed through collaborations with organizations like NOAA and the , allow for forecasts that outperform traditional methods in and environments. Machine learning applications at OpenWeatherMap extend to predictive modeling of environmental , including anomaly detection in weather patterns. AI-driven algorithms analyze historical and datasets to identify events such as storms or droughts, providing early warnings and assessments for vulnerable regions. This capability supports intelligent by processing vast volumes of to detect deviations from normal patterns, enhancing reliability in applications like monitoring. Innovations in leverage the team's expertise to deliver sector-specific solutions, such as customized weather intelligence for industries. For energy, models optimize renewable resource predictions, including and wind speeds at multiple heights, using long-term climate data spanning over 46 years to inform grid management and production planning. In , predictive modeling via the employs for crop health monitoring, pest outbreak forecasting, and optimization, integrating with weather analytics to tailor recommendations for specific fields. These advancements address dynamic environmental challenges, offering data-driven insights that improve operational efficiency across sectors. Looking forward, OpenWeatherMap's AI features emphasize long-term insights, enabling customized datasets for in and through advanced parameter optimization and scenario modeling. This includes AI-enhanced simulations for variability, supporting sustainable practices like forecasting and adaptive farming strategies amid global changes.

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