Aurora 1.5: Extending open foundation models for weather and Earth-system applications

KUALA LUMPUR, 25 JULY 2026 —

Headline: Aurora 1.5: Extending open foundation models for weather and Earth-system applications Lead: Aurora 1.5 adds 22 more variables, hourly temporal resolution, and probabilistic ensemble forecasting to the Aurora foundation model, making it more useful for real-world weather, climate, and energy applications. The post Aurora 1.5: Extending open foundation models for weather and Earth-system applications appeared first on Microsoft Research . Body: Aurora 1.5 is a major update to the open Aurora Earth-system foundation model, adding 22 new weather variables for a broader view of atmospheric conditions, hourly forecasts, and probabilistic ensemble forecasting. Developed by Microsoft Weather as an extension of the original model from Microsoft Research AI for Science, Aurora 1.5 shows how frontier research can move into broader use: open for researchers and developers to evaluate and extend, and designed to support customers where additional data, infrastructure, and operational assurance is needed. As climate and weather-related risks continue to affect communities, infrastructure, and economies worldwide, advances in Earth-system forecasting can help improve preparedness and decision-making. Aurora is a foundation model for the Earth system developed by Microsoft Research AI for Science, first introduced in 2024 and published in Nature (opens in new tab) in 2025. It showed that a single model could be adapted to medium-range weather, ocean waves, atmospheric chemistry, and emerging climate applications, including high-resolution weather forecasting through fine-tuning. Its growing use has reinforced the value of an open, collaborative model that is easier to adapt, evaluate, and put to use. This next phase of Aurora (opens in new tab) builds on that foundation by making the model openly available for the global community to adapt, extend, and build on. Aurora 1.5 advances the broader effort to make open weather foundation models practical and scalable for organizations that rely on atmospheric and Earth-system intelligence. Alongside new variables and higher temporal resolution, Aurora 1.5 adds one of the most requested capabilities from users: ensemble forecasting. Because forecasts are sensitive to initial conditions and model uncertainty, ensembles run multiple simulations to show the range and likelihood of possible outcomes. Aurora 1.5 builds on Microsoft Research’s scientific foundation with new product engineering, cloud infrastructure, managed access, and decision-support capabilities. Together, these advances make Aurora 1.5 a valuable enterprise-grade weather solution for organizations. The breadth update adds 22 new variables to Aurora’s original 4, including representative surface, pressure-level, wind, temperature, humidity, precipitation, and radiation fields. That broader coverage makes the model more relevant for sectors that depend on integrated Earth-system signals, from energy and agriculture to transport and resilience planning. The update to hourly temporal resolution enables fine-grained detail for precision operational guidance, such as the onset of precipitation, trade decisions, or a landfalling tropical cyclone. “Aurora 1.5 is a meaningful step toward making weather foundation models more open, useful, and practical. By releasing the model openly, we give researchers, developers, and organizations a clearer path to evaluate it, adapt it, and understand where it can help. Microsoft Weather’s role is to connect that open research foundation with the data, infrastructure, and applied workflows required by enterprises to use weather intelligence responsibly and with confidence.” Get a glimpse of potential future directions for AI, with these experimental technologies from Microsoft Research. The ensemble version of Aurora 1.5 introduces stochastic perturbations to represent model uncertainty, allowing the generation of multiple forecast members to estimate the spread of possible futures. For a multitude of applications including power systems, transport, agriculture, extreme-weather planning, and climate risk, the model distribution matters as much as the best estimate. This ensemble capability was developed through multi-stage fine-tuning on top of the original Aurora model. After expanding the variable set and adding hourly temporal resolution, the team introduced controlled perturbations into the model’s latent conditioning pathway and optimized the ensemble for probabilistic forecast quality. A final round of auto-regressive fine-tuning on ECMWF High Resolution (HRES) analysis data from 2018 to 2023 improved rollout behavior and stability. Aurora’s ensemble approach summarizes uncertainty across multiple model runs. Its probabilistic forecasts outperform those of the state-of-the-art ECWMF dynamical ensemble on 88.9% of evaluated targets (Figure 1). In evaluations on all 2024–2025 tropical cyclones, Aurora 1.5 substantially reduced track errors, including roughly one-third lower track error when comparing the ensemble median to the original Aurora. An example for the devastating Hurricane Helene shows how Aurora 1.5’s skill translates to high-impact weather applications. Beyond medium-range weather applications, Terradot – part of the Microsoft Climate Innovation Fund portfolio—is working with the AI for Good Lab (opens in new tab) and the Microsoft Research Accelerator on TerraNova, using Aurora-derived weather representations (opens in new tab) to estimate and optimize carbon dioxide removal from enhanced rock weathering under real field conditions. Sasankh Munukutla, Co-Founder of Terradot, highlights , “By building on Aurora, we’re significantly advancing our R&D timelines and accelerating our path towards gigaton-scale carbon removal.” This work shows how Earth-system foundation models can support climate mitigation and public-interest science beyond forecasting, including settings where rigorous evaluation and responsible deployment matter. Aurora is also being explored with partners such as the UK Met Office, exploring how foundation models can work alongside established physics-based systems to tackle problems from weather to climate time scales. The aim is faster, more flexible forecasts that support decision-making without replacing the science behind trusted prediction. “Microsoft’s Aurora model is an exciting and promising tool, enabling Met Office scientists to bring their data and expertise to help solve climate problems and provide new kinds of climate information. Met Office and Microsoft scientists and engineers are working together every day to translate lessons from AI weather prediction into the climate information space, sharing expertise in data science and climate science. Aurora is a great platform for learning how to translate these tools for use in climate projection to make the AI climate models of the future.” Microsoft connects open research, product engineering, responsible deployment, and partner ecosystems so that models can move from scientific advance to evaluated operational use. As an example, Aurora began in Microsoft Research AI for Science and is… (AI-assisted rewrite, based on the original source)

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