Storm signals

October 26, 2023
Maureen Searcy

Mid-latitude cyclone on the first day of summer
A mid-latitude cyclone on the first day of summer. (NOAA GOES East satellite)

Climate scientist Tiffany Shaw will study whether climate predictions were right, for the right reasons.

The accuracy of weather forecasts affects much of our daily lives. Knowing whether it will rain helps you plan accordingly: clothes, transportation, and in the case of a storm, safety. Meteorologists consider observations at a given time and, based on their models, make predictions every six hours for two weeks. And if the prediction was off — “a forecast bust, as they say,” explains Geophysical Sciences professor Tiffany Shaw — meteorologists can figure out what went wrong and improve the model accordingly.

Climate forecasts work in much the same way, except it can take years — even decades — to find out if a projection was a bust. For more than 40 years, physical[1] climate scientists like Shaw have been predicting how the global climate has changed in the historical period and how it might change into the 21st century under different emission scenarios. Now we are really coming into a time where the predicted signals are beginning to emerge in observations and scientists can ask: are those changes consistent with what we predicted? And if not, is there a problem with our models or are we simply seeing natural variations in climate? Shaw hopes to answer these questions as part of a new project in collaboration with the National Oceanic and Atmospheric Administration (NOAA).

Seasonal storm strength

Shaw’s past work has focused on the “harbingers of the future” due to the burning of fossil fuels, with extensive research on the response of the atmosphere to anthropogenic climate change, including the response of midlatitude weather systems (highs and lows) that form the so-called storm track. In particular, both theory and generations of climate models have predicted that in the southern hemisphere, storms should get stronger throughout the winter; winds or temperature fluctuations should increase, and precipitation should become more extreme. “In the northern hemisphere, our models predict that storms should get weaker in summer, even though they already are weaker to begin with.”

That prediction has since been observed; it’s in the data. “So what we’re asking of the models is: did it get the right answer for the right reason? We need models that not only capture the signal of storm weakening in summer but capture the physical mechanisms underlying the observation,” Shaw explains. In the southern hemisphere there is a clear underestimate, and the research will work to understand why the discrepancy exists by looking at the physical mechanisms of the emerging signal and testing different hypotheses.

Shaw’s project, “Confronting climate model trends with observations: Extratropical storm tracks and their associated extreme events,” is part of NOAA’s Modeling, Analysis, Predictions and Projections Program, which supports advances in the development and application of Earth system models and analyses to help prepare society for the impacts of climate change. Shaw is the principal investigator of the three-year project, partnering with National Center for Atmospheric Research scientist Dr. Isla Simpson as co-PI and collaborating with NOAA Geophysical Fluid Dynamics Laboratory scientists Drs. Pu Lin and Zhihong Tan.

The team will take observations from over the past four decades, including ground and satellite measurements of radiation, precipitation, temperature, and clouds, and combine them in a way that can be easily compared to existing climate model predictions. The goal is to quantify the same variables on the same grid with the same time-frequency, for an apples-to-apples comparison.

NOAA will provide much of the observation-based data as well as powerful models developed in NOAA labs. The starting point for the comparison will be to identify trends from SPEAR (Seamless System for Prediction and EArth System Research), a high-resolution climate model that stretches from 1921 through the end of the 21st century, which “pushes the boundaries of the highest quality predictions that we can make with the most fine-grained resolution that we have.”

The SPEAR data will be compared to a suite of other climate model predictions at lower resolution to “probe the model predictions and test whether model resolution might be the source of some discrepancies,” says Shaw. The research will also perform the most comprehensive comparison of climate model predictions with observations that has been performed thus far, across all regions and in other seasons, especially as they relate to extreme weather events.

Climate engineering

One particular focus of the project will be storm tracking over land, particularly North America. Storms are common over the oceans, but land-based storms impact “so much of the way we live,” notes Shaw, “influencing how our societies are shaped, affecting agriculture and infrastructure.” It’s crucial that climate forecasts are as accurate as possible to “prepare society for what’s happening already, but also what will continue to unfold.”

Shaw says it transcends preparation, as well, citing UChicago’s new Climate Systems Engineering initiative (CSEi), led by Geophysical Sciences professor David Keith. “The idea that we can engineer the climate hinges on our ability to understand and predict it.” If scientists want to perturb the climate system in some way to achieve some desired outcome, it’s crucial for them to know how that action will play out, and climate models are the key to that foresight.

“I think my colleague [and fellow CSEi executive committee member] David Archer had the best way to describe climate engineering,” says Shaw: “We’re in the driver’s seat, whether we like it or not.” And an accurate forecast will help us prepare for the ride.

[1] Physical climate scientists are concerned with elements such as temperature, winds, precipitation, moisture, and even chemistry, as opposed to scientists who might study the effects of climate change on living organisms, for instance.

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