New AI foundation model offers insights beyond forecasting
for scientists, developers, and businesses to better understand and
analyze weather and climate data
YORKTOWN HEIGHTS, N.Y.,
Sept. 23, 2024 /PRNewswire/ -- IBM
(NYSE: IBM) today announced a new AI foundation model for a variety
of weather and climate use cases, available in open-source to the
scientific, developer, and business communities. Developed by IBM
and NASA, with contributions from Oak Ridge National Laboratory,
the model offers a flexible, scalable way to address a variety of
challenges related to short-term weather as well as long-term
climate projection.
Because of its unique design and training regime, the weather
and climate foundation model can tackle far more applications than
existing weather AI models, as outlined in a paper recently
published on arXiv, "Prithvi WxC: Foundation Model for Weather and
Climate." Potential applications include creating targeted
forecasts based on local observations, detecting and predicting
severe weather patterns, improving the spatial resolution of global
climate simulations, and improving how physical processes are
represented in numerical weather and climate models. In one
experiment in the above identified paper, the foundation model
accurately reconstructed global surface temperatures from a random
sample of only five percent original data, suggesting a broader
application to problems in data assimilation.
This model was pre-trained on 40 years of Earth observation data
from NASA's Modern-Era Retrospective analysis for Research and
Applications, Version 2 (MERRA-2). As a foundation model, it has a
unique architecture which allows it to be fine-tuned to global,
regional, and local scales. This flexibility makes it suited for a
range of weather studies.
The foundation model is available for download on Hugging Face,
along with two fine-tuned versions of the model that tackle
specific scientific and industry-relevant applications. These
are:
- Climate and weather data downscaling: A common
meteorological practice is downscaling—inferring high-resolution
outputs from low-resolution variables. Typical data inputs include
temperature, precipitation, and surface winds, all of which can
have varied resolutions. The model can depict both weather and
climate data at up to 12x resolution, generating localized
forecasts and climate projections. The fine-tuned downscaling model
is available on the IBM Granite page on Hugging Face.
- Gravity wave parameterization: Gravity waves are
ubiquitous throughout the atmosphere and can affect many
atmospheric processes related to climate and weather, such as cloud
formation and aircraft turbulence. Traditionally, existing
numerical climate models have not sufficiently captured gravity
waves, which leads to uncertainties in terms of how exactly gravity
waves can affect climate processes. This weather and climate
foundation model can help scientists better estimate gravity wave
generation, to improve the accuracy of numerical weather and
climate models and constrain uncertainty when simulating future
weather and climate events. This gravity wave parameterization
model is being released as part of the NASA-IBM Prithvi family of
models on Hugging Face.
"Advancing NASA's Earth science for the benefit of humanity
means delivering actionable science in ways that are useful to
people, organizations, and communities. The rapid changes we're
witnessing on our home planet demand this strategy to meet the
urgency of the moment," said Karen St.
Germain, director of the Earth Science Division of NASA's
Science Mission Directorate. "The NASA foundation model will help
us produce a tool that people can use: weather, seasonal, and
climate projections to help inform decisions on how to prepare,
respond, and mitigate."
"This space has seen the emergence of large AI models that focus
on a fixed dataset and single use case — primarily forecasting. We
have designed our weather and climate foundation model to go beyond
such limitations so that it can be tuned to a variety of inputs and
uses," said Juan Bernabe-Moreno,
Director of IBM Research Europe and IBM's Accelerated Discovery
Lead for Climate and Sustainability. "For example, the model can
run both on the entire earth as well as in a local context. With
such flexibility on the technology side, this model is well-suited
to help us understand meteorological phenomena such as hurricanes
or atmospheric rivers, reason about future potential climate risks
by increasing the resolution of climate models, and finally inform
our understanding of imminent severe weather events."
"As a premier research institution and computing facility, we're
focused on supporting teams to make research breakthroughs across
many areas of science," said Arjun Shankar, director of the
National Center for Computational Sciences at Oak Ridge National
Laboratory. "Our collaboration with IBM and NASA to support the
creation of the Prithvi weather and climate foundation model was a
key part of our goal to bring advanced computing and data to
problems of national importance, in this case, for weather and
climate applications, which need continued computational science
and model skill improvements to be impactful."
IBM has already collaborated with Environment and Climate Change
Canada (ECCC) with a view to test the flexibility of the model with
additional weather forecasting use cases. With the model, ECCC is
exploring very short-term precipitation forecasts using a technique
called precipitation nowcasting that ingests real-time radar data
as input. The team is also testing the downscaling approach from
global model forecasts at 15 km to km-scale resolution.
This weather and climate model is part of a larger collaboration
between IBM Research and NASA to use AI technology to explore our
planet, and joins the Prithvi family of AI foundation models. Last
year, IBM and NASA made the Prithvi geospatial AI foundation model
the largest open-source geospatial AI model available on Hugging
Face. This geospatial foundation model has since been used by
governments, companies, and public institutions to examine changes
in disaster patterns, biodiversity, land use, and other geophysical
processes. The foundation model and the gravity wave
parameterization model can be accessed through the NASA-IBM Hugging
Face page and the downscaling model can be accessed through the IBM
Granite Hugging Face page.
About IBM
IBM is a leading provider of global hybrid
cloud and AI, and consulting expertise. We help clients in more
than 175 countries capitalize on insights from their data,
streamline business processes, reduce costs and gain the
competitive edge in their industries. Thousands of governments and
corporate entities in critical infrastructure areas such as
financial services, telecommunications and healthcare rely on IBM's
hybrid cloud platform and Red Hat OpenShift to affect their digital
transformations quickly, efficiently and securely. IBM's
breakthrough innovations in AI, quantum computing,
industry-specific cloud solutions and consulting deliver open and
flexible options to our clients. All of this is backed by IBM's
long-standing commitment to trust, transparency, responsibility,
inclusivity and service.
Media Contact
Bethany Hill
McCarthy
IBM Research Communications
bethany@ibm.com
Ashley Peterson
IBM Research Communications
Ashley.peterson@ibm.com
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