Enhancing Climate Resilience with Borealis Weather: High-Resolution Environmental Forecasting

Transforming Key IndustriesHybrid modelHigh-Resolution Environmental Forecasting

Addressing the Climate Challenge

Climate change is reshaping weather patterns globally, leading to more frequent and severe weather events that significantly impact . As the planet warms, industries including agriculture, energy, water management, and disaster preparedness face escalating challenges. The World Meteorological Organization estimates that since 1970, weather-related disasters have caused over 2 million deaths and $3.64 trillion in economic losses globally1. By 2030, half of the world’s population is projected to live in coastal areas at risk of floods, storms, and tsunamis, underscoring the urgent need for precise weather forecasting technologies.

The Need for Advanced Forecasting

Addressing the impact of changing weather patterns demands precise, data-driven responses. In agriculture, climate shifts affect crop viability and farming practices, requiring accurate local weather data for optimal crop selection and water management. The energy sector must adapt to shifting consumption patterns influenced by extreme temperatures, necessitating granular forecasts to manage load effectively. Water resource management is becoming increasingly critical as irregular rainfall patterns and extreme weather events strain supplies. Enhanced flood prediction capabilities are essential for improving disaster response, reducing economic losses, and saving lives.

Introducing Borealis Weather: Precision in Forecasting

Borealis Weather is a hybrid AI-physics model developed by Recursive that creates high-resolution weather data from low-resolution satellite and ground observations, combined with neural network interpolation and topography-based physics modeling. Its hybrid approach is designed for accuracy, with annual temperature predictions within a margin of error of less than ±1℃. The model offers a native spatial resolution of 300 meters, up-scalable to 100 meters with additional computational power. When supplied with sufficiently-detailed topological maps and data sources, the system can be scaled to even higher resolutions such as predictions at the square-meter level.

Hybrid Model: Physics + Machine Learning

Hybrid Model: Physics + Machine Learning
Windspeed Distribution by Geographic Location
Precipitation in Japan and Near Mount Fuji - Adding Topography

Transforming Key Industries

Agriculture: Borealis Weather enables farmers to optimize crop selection and management practices, which can increase efficiency by 10-30% by precisely timing planting and irrigation based on local weather conditions2. This precision allows for better resource allocation, ultimately leading to higher crop yields and more sustainable farming practices.

Energy: In the energy sector, Borealis Weather's ability to predict consumption at a micro-level allows utilities to implement effective demand-response strategies. This improves grid stability, reduces energy wastage, and helps in the efficient management of renewable energy sources like wind and solar power.3

Water Management: Detailed climate predictions from Borealis facilitate more efficient water use and storage strategies. This capability is crucial for areas prone to water scarcity, enabling substantial economic savings by reducing the need for costly water imports or infrastructure expansions. By accurately predicting rainfall patterns, Borealis helps in planning and managing water resources more effectively.

Disaster Preparedness: Borealis enhances flood risk management by providing early warnings and enabling proactive measures. This data can be used in machine learning methods that increase flood forecasting accuracy by up to 50%, minimizing property and infrastructure damage, and protecting lives4. Improved disaster preparedness contributes to both economic resilience and public safety.

“Understanding the atmosphere, its dynamics and the implications of its effects is of tremendous importance for the future of humanity. Whether it's about making informed decisions on where to place energy-collecting devices, where precipitation will provide an environment for food growth, where we can extract clean drinking water, or understanding large-scale changes through time - we seek to create a computable, high-resolution, digital twin of the atmosphere.“

Photo of David Landup, ML Engineer

David Landup, ML Engineer

What Makes Borealis Weather Special?

Borealis Weather stands out by integrating data from a vast array of input sources, including weather stations, satellite imagery, and topographical information to offer precise predictions for rain, wind, and temperature.

Temperature Forecasts: With an average error margin of just ±1℃, Borealis Weather's temperature predictions are vital for public health, helping communities prepare for extreme weather conditions and enabling more efficient energy management for heating and cooling needs.

Wind Predictions: Accurate wind forecasts are crucial for the renewable energy sector, allowing for the optimization of wind turbine operations and contributing to more efficient renewable energy production.

Rainfall Predictions: Precise rainfall forecasts aid in flood management and agricultural planning, ensuring optimal water resource use and contributing to improved crop yields. Borealis currently has a 30% lower error rate than the current global state-of-the-art in Japan.

Data Fusion and Upscaling diagram

Looking Ahead with Borealis Weather

Borealis Weather is continuously evolving to meet the growing demands of a changing climate. The integration of advanced neural forecasting systems, such as GraphCast, will soon enable hyper-local predictions of future weather events. In the coming years, Recursive aims to create a digital twin of the environment, starting with a focus on Japan. This enhancement will model environmental dynamics in real-time, offering a transformative tool for decision-making in response to climate change.

Partnering for a Sustainable Future

For anyone interested in using Borealis Weather, Recursive offers customization services and support. Our mission is to create a fairer, more sustainable society through the use of advanced technology. We offer AI system development and consultation services, combining our expertise in artificial intelligence with domain knowledge from diverse industries, including environment, energy, medical, pharmaceutical, food, and retail. Our engineers and consultants are passionate about developing world-class technology in order to leave behind a better environment and society for future generations.

For more information on how Recursive can help you solve weather related issues with Borealis, please contact us.


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About Recursive

Value provided by Recursive

Bringing innovation to business and solving social issues with AI technology

In order to build a sustainable society and environment, companies are required to transform the socio-economic and business practices that have caused problems in the past. And we know that AI technology is a tool with high potential for realizing sustainable innovation. Recursive has defined and focused on four areas where the use of AI is particularly effective in sustainability.

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Accelerate Innovation →Increase Productivity→Deliver better work and education→Prepare for future risks

Recursive's reason for existence

Build a fairer, more sustainable society

By utilizing technology, realize a fairer and more sustainable society

Innovative approaches that utilize AI technology lead to fundamental and sustainable solutions to social issues. We continue to work with companies to create these solutions while prioritizing ethics.

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