Seminar Speaker: Assistant Professor, Troy Zaremba-Mississippi State University

Toward Predicting Orographic Updrafts in Complex Terrain

Since leaving Illinois, I have worked on a number of different research problems, but I have continued coming back to the same question that motivated much of my Ph.D.: can we predict the vertical motions produced when atmospheric flow encounters complex terrain? These terrain-tied updrafts strongly influence supercooled liquid water, cloud structure, and snowfall, yet their location, strength, and depth can change substantially from one storm to another.

My first attempt to extend this work during my postdoc at the University of Washington used a season-long WRF simulation from SNOWIE and EOF analysis to identify the dominant patterns of orographic vertical-motion variability. The analysis revealed recurring changes in the presence, orientation, width, and intensity of terrain-tied updrafts, but it also highlighted an important limitation: EOFs are useful for describing how the vertical-motion field varies after the fact, not for predicting what updrafts should develop from a particular environment.

That question became a major focus of my work with S2noCliME, the Snow Sensitivity to Clouds in a Mountain Environment field campaign conducted near Steamboat Springs, Colorado, during winter 2024–2025. As part of my UW postdoc, I combined the extensive S2noCliME observational dataset with a 500-m seasonal WRF simulation. One approach has been to rank periods by the strength of terrain-tied ascent upstream of Storm Peak Laboratory and then apply those rankings to radar and in situ observations. These “updraft stacks” reveal systematic transitions from weak, shallow cloud and precipitation regimes to stronger ascent characterized by faster cross-barrier flow, reduced stability, greater supercooled liquid water, deeper radar echoes, and precipitation growth extending farther downstream of the terrain. The results suggest that updraft strength provides a relatively simple way to organize much of the observed variability, while also showing that environmental conditions control both the magnitude and structure of the response.

The next step is to move from organizing these patterns to predicting them. Initial U-Net experiments suggest that two-dimensional vertical-motion structures can be predicted surprisingly well from upstream wind, stability, and terrain. Going forward, I want to extend this framework into three dimensions and ask whether relationships learned in one mountain environment can generalize across storms and ultimately across mountain ranges.

https://illinois.zoom.us/j/87247933909?pwd=Yg9a5afZrUDAodWJBhap3HvxzMVVeo.1

Meeting ID: 872 4793 3909     Pass Code: 202496