微软发布 Aurora 1.5 开源地球系统基础模型

At a glance

• Aurora 1.5 is a major extension of Microsoft’s Aurora Earth System foundation model that adds 22 more weather variables relevant to energy, agriculture, transport, and climate risk, along with hourly temporal resolution and probabilistic ensemble forecasting.
• Released as open source on GitHub with model checkpoints on Hugging Face, Aurora 1.5 enables researchers and developers to use, evaluate, and build on the model.
• Aurora 1.5 connects open research to Microsoft Weather services, linking the model with data, infrastructure, managed access, and operational use for weather and Earth-system applications.

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.

What is Aurora?

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.

What is new in Aurora 1.5?

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.

Figure 1: Illustration of the capabilities of Aurora 1.5 ensemble for predicting new impactful parameters such as total cloud cover and solar radiation. Ensemble mean and standard deviation are shown.

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.”

Sridhar Iyer, Corporate Vice President, Microsoft AI

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Ensemble Forecasting in Aurora 1.5 Unlocks More Confident Decisions in the Face of Weather Uncertainty

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.

Figure 2. Comparing Aurora 1.5’s probabilistic forecasts with the ECMWF ensemble forecast. The shading shows relative probabilistic forecast error, using ECMWF ENS as the baseline: blue areas indicate where Aurora 1.5 performs better, and red areas indicate where it performs worse. Across upper-air geopotential, temperature, and humidity, together with five surface variables, Aurora 1.5 outperforms ECMWF ENS on 88.9% of the evaluated variable-and-lead-time targets.

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.

Figure 3. Hurricane Helene ensemble forecast from Aurora 1.5, showing multiple plausible storm tracks starting at 0 UTC on September 24, 2024. The probabilistic ensemble forecast envelops the verified track, effectively capturing uncertainty in the storm’s progression.

Figure 4. Aurora 1.5 reduces track error relative to the original model across lead times. Ensemble mean and median tracks are used for diagnostics, with the median showing the strongest gains, reaching roughly one-third lower error by day 5. Results reflect track position only.

Beyond weather: Aurora as an Earth-system foundation

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.