High-resolution weather forecasting gets more accurate, faster

In the world of weather computer forecast models you have the high-res models that can forecast a storm down to city level but only a couple of days in advance, and then you have the large scale global models that are less than precise but can cover the whole globe seven days out. There are also other limitations to global models including smoothing out mountains into hills which can impact the ability for the computers to accurately predict how precipitation will behave in mountainous areas. But now there is a happy median between the two.

Hydrologists at the National Center for Atmospheric Research (NCAR) are developing the Intermediate Complexity Atmospheric Research Model (ICAR) which gives researchers increased accuracy using only a tiny fraction of the computing resources. “ICAR is about 80 percent as accurate as WRF in the mountainous areas we studied,” said NCAR scientist Ethan Gutmann, who is leading the development of ICAR. “But it only uses 1 percent of the computing resources. I can run it on my laptop.”

How much precipitation falls in the mountains — and when — is vitally important for communities in the American West and elsewhere that rely on snowpack to act as a frozen reservoir of sorts. Water managers in these areas are extremely interested in how a changing climate might affect snowfall and temperature, and therefore snowpack, in these regions.

But since global climate models with low resolution are not able to accurately represent the complex topography of mountain ranges, they are unsuited for answering these questions. So, ICAR uses small adjustments to statistics, like drying out areas that are too wet, or vice versa. What results isn’t a completely accurate depiction of what could happen, but it will usually be closer than they’ve ever been.

To read more about the new ICAR model and how it could change the way computer forecast models work, check out the article here.


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