To forecast weather around the globe, scientists use general circulation models (GCMs) of the Earth’s atmosphere—simulations of atmospheric circulation based on mathematical equations that take into account factors such as the planet’s rotation and energy sources. Typically, climate models have fairly low spatial resolution (grid cells that are 100 kilometers across on average), but in order to properly predict weather in mountainous regions, higher-resolution models, with grid cells smaller than 5 kilometers, are necessary.
To counter this problem in GCMs, scientists embed two-dimensional cloud-resolving models (CRMs) that create more detailed simulations of individual clouds or cloud systems into grid columns within the global models. This approach is known as the multiscale modeling framework (MMF). However, these two-dimensional CRMs don’t take into account how the complex, three-dimensional mountain topography can influence the model output. But understanding the ways that mountainous terrain interacts with atmospheric processes to produce precipitation—known as orographic effects—is critical to predicting local weather, as rain and snow over mountains nearly always occur during storms that have formed in the rugged terrain.
Here Jung and Arakawa sought to determine if a two-dimensional representation of complex mountain terrain can accurately predict mountain precipitation. The team modeled the downstream effects of topography in both two- and three-dimensional CRMs within a single grid column of the global circulation model.
The researchers found that the two-dimensional models simulated the average surface precipitation over the GCM grid cell reasonably well, provided that an accurate measure of the mean and standard deviation of the surface elevation was included in the model.
But the two-dimensional models were less useful for predicting the winds associated with precipitation events. Still, the authors conclude that MMFs are a promising approach for simulating precipitation over mountainous terrain within single grid cells of GCMs—especially a new generation known as the quasi-three-dimensional MMF, which, among other advances, uses three-dimensional CRMs. This new modeling framework is outlined in Jung and Arakawa (Journal of Advances in Modeling Earth Systems (JAMES), 2010, doi:10.3894/JAMES.2010.2.11).
Such models will provide scientists with an even better representation to study the relationship between orographic effects and precipitation, but the quasi-three-dimensional models are still computationally costly and need further refinement before they can be widely used within global climate models. (Journal of Advances in Modeling Earth Systems (JAMES), doi:10.1002/2015MS000539, 2016)
—Kate Wheeling, Freelance Writer
Citation: Wheeling, K. (2016), Modeling weather over mountainous terrain, Eos, 97, doi:10.1029/2016EO046783. Published on 25 February 2016.