NSF NCAR's next-generation atmospheric model garners significant community interest
JUN 12, 2024 - BY LAURA SNIDER
A flexible, next-generation atmospheric model with the capability to accurately model weather, both regionally and globally, has been garnering increasing interest from user groups around the world, including weather forecasters, government agencies, climate scientists, private companies, and beyond.
The Model for Prediction Across Scales (MPAS) was developed by the U.S. National Science Foundation National Center for Atmospheric Research (NSF NCAR). It's one of the tools the organization is investing in to help bridge a gap that exists between high-resolution regional weather modeling and low-resolution global climate modeling.
"MPAS development has been a priority for NSF NCAR because we believe in its potential to help connect the weather and climate research communities," said NSF NCAR Director Everette Joseph. "For example, it's imperative that we improve our ability to predict how climate change will affect severe weather at the community scale, and MPAS is one of the ways we are working toward doing that. I'm thrilled to see its use taking off in the community. As has always been the case, our models evolve and improve the more the community begins to use them and contribute back what they've learned. This is what community modeling is all about."
MPAS's promise lies, in part, in its unique grid system. The honeycomb-like mesh allows the model to simultaneously simulate the atmosphere over some parts of the globe in high resolution, capturing small-scale weather phenomena like thunderstorms, and over other parts in low resolution, capturing large-scale atmospheric flow. Practically speaking, this creates a tool that could both be useful as an atmospheric model for weather researchers, who typically run regional simulations at high resolution over days and weeks, and as an atmospheric component of an Earth system model for climate researchers, who typically run global simulations at low resolution over decades and even centuries.
Weather and climate research communities in the United States have historically relied on separate models, which has made it challenging to study how climate change affects weather in detail, and current climate and weather models are not well suited for the opposite community's needs. For example, it's challenging for scientists to run a climate model at extremely high resolution over a small area or to run a weather model globally on long timescales and get realistic looking outcomes. MPAS can't fix all the problems, but NSF NCAR researchers say it has the potential to help bridge the existing gap.
Forecasters and researchers from across the spectrum of weather and climate communities are now actively using MPAS - either as a stand-alone model or by using just the model's dynamical core as part of a different modeling system. The dynamical core is the heart of a model, and it solves the equations that describe how air and heat flow through the atmosphere. NOAA's National Severe Storms Laboratory is experimenting with using the MPAS dynamical core for extremely high-resolution regional weather forecasts, for example, while researchers at NSF NCAR and their university collaborators are working to connect it to models of other Earth system components - including the ocean, land, and sea ice - to facilitate its use in climate science.
SEE FULL ARTICLE HERE
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Rachel Dammann
UCAR, UCP and NSF NCAR
Boulder CO
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