AI for Climate Risk: Difference between revisions
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* [https://huggingface.co/papers/2409.13598 '''Prithvi WxC'''](open-source) In collaboration with NASA, IBM built a '''general-purpose AI foundation model''' that could be customized for a range of practical weather and climate applications, at varying spatial scales. Potential applications include creating targeted forecasts from local weather data, predicting extreme weather events, improving the spatial resolution of global climate simulations, and improving the representation of physical processes in conventional weather and climate models. | * [https://huggingface.co/papers/2409.13598 '''Prithvi WxC'''](open-source) In collaboration with NASA, IBM built a '''general-purpose AI foundation model''' that could be customized for a range of practical weather and climate applications, at varying spatial scales. Potential applications include creating targeted forecasts from local weather data, predicting extreme weather events, improving the spatial resolution of global climate simulations, and improving the representation of physical processes in conventional weather and climate models. | ||
* [https://arxiv.org/abs/2405.13063 '''Aurora'''] A foundation model developed by Microsoft that can do high-resolution (11-km) weather forecast and even air pollution forecast. | * [https://arxiv.org/abs/2405.13063 '''Aurora'''] A foundation model developed by Microsoft that can do high-resolution (11-km) weather forecast and even air pollution forecast. | ||
==== AI for Weather forecast ==== | |||
* [https://deepmind.google/discover/blog/graphcast-ai-model-for-faster-and-more-accurate-global-weather-forecasting/ '''GraphCast'''] Global weather forecast model developed by Google DeepMind. | * [https://deepmind.google/discover/blog/graphcast-ai-model-for-faster-and-more-accurate-global-weather-forecasting/ '''GraphCast'''] Global weather forecast model developed by Google DeepMind. | ||
* [https://github.com/198808xc/Pangu-Weather '''Panggu'''](open-source) Global weather forecast model developed by Huawei, China | * [https://github.com/198808xc/Pangu-Weather '''Panggu'''](open-source) Global weather forecast model developed by Huawei, China | ||
* '''[https://github.com/tpys/FuXi Fuxi]'''(open-source) Global weather forecast model developed by Fudan University, China | * '''[https://github.com/tpys/FuXi Fuxi]'''(open-source) Global weather forecast model developed by Fudan University, China | ||
==== Climate Downscaling ==== | |||
==== | |||
==== Climate Risk Forecasting ==== | |||
* [https://www.sciencedirect.com/science/article/pii/S2589915524000191 A nonstationary stochastic simulator for clustered regional hydroclimatic extremes to characterize compound flood risk] | * [https://www.sciencedirect.com/science/article/pii/S2589915524000191 A nonstationary stochastic simulator for clustered regional hydroclimatic extremes to characterize compound flood risk] | ||
* [https://github.com/jtbuch/smlfire1.0 A stochastic ML model of wildfire activity in western US] | * [https://github.com/jtbuch/smlfire1.0 A stochastic ML model of wildfire activity in western US] | ||
* [https://onlinelibrary.wiley.com/doi/10.1111/ele.14018 A statistical model] to create gridded (4-km spatial resolution), monthly predictions of burn area as a function of climatic variables. | * [https://onlinelibrary.wiley.com/doi/10.1111/ele.14018 A statistical model] to create gridded (4-km spatial resolution), monthly predictions of burn area as a function of climatic variables. | ||
==== AI for exposure ==== | ==== AI for exposure mapping ==== | ||
Revision as of 12:29, 16 October 2024
AI Foundation Model for Weather and Climate
- Prithvi WxC(open-source) In collaboration with NASA, IBM built a general-purpose AI foundation model that could be customized for a range of practical weather and climate applications, at varying spatial scales. Potential applications include creating targeted forecasts from local weather data, predicting extreme weather events, improving the spatial resolution of global climate simulations, and improving the representation of physical processes in conventional weather and climate models.
- Aurora A foundation model developed by Microsoft that can do high-resolution (11-km) weather forecast and even air pollution forecast.
AI for Weather forecast
- GraphCast Global weather forecast model developed by Google DeepMind.
- Panggu(open-source) Global weather forecast model developed by Huawei, China
- Fuxi(open-source) Global weather forecast model developed by Fudan University, China
Climate Downscaling
Climate Risk Forecasting
- A nonstationary stochastic simulator for clustered regional hydroclimatic extremes to characterize compound flood risk
- A stochastic ML model of wildfire activity in western US
- A statistical model to create gridded (4-km spatial resolution), monthly predictions of burn area as a function of climatic variables.