Week 7 Blog Post: Digging Deeper into the Why

• After spending last week grouping cameras by elevation and visually comparing snow depth trends, I realized it wasn’t enough to just see differences—I wanted to understand why those differences exist. This week, I focused on exploring the underlying reasons for the trends I was seeing, especially the roles of elevation and burn severity in shaping snow accumulation and melt behavior.

What stood out most were the comparisons between cameras placed at nearly identical elevations but with differing burn severities. Take Cameras 518 and 1994, for example. Both are located at high elevations, yet Camera 1994 consistently held more snow. Why? The answer seems to lie in albedo—the reflectivity of the ground surface. Burn areas like the one around Camera 518 have more charred ground and fewer reflective surfaces, which causes more solar radiation to be absorbed and accelerates snowmelt. Camera 1994, in contrast, reflects more sunlight, helping preserve its snowpack longer.

I noticed a similar pattern when comparing Cameras 727 and 308. Despite being practically at the same elevation, Camera 727—situated in a less severely burned area—retained snow longer and saw higher overall accumulation. Camera 308, in the more scorched terrain, lost snow more quickly after each storm. The snow depth dropped sharply after precipitation events, pointing to lower retention capacity likely caused by increased exposure to sunlight and reduced canopy cover.

I also revisited the scatter plot of burn severity versus camera elevation. This plot revealed a clear inverse relationship: the more severely burned the area, the lower the elevation. These trends have begun to paint a consistent picture—burn severity doesn’t just affect how much snow falls, but how long it sticks around. That distinction is important when thinking about water availability later in the season.

This week really helped shift my thinking from “what am I seeing?” to “why am I seeing it?” It’s a big step toward building a model that isn’t just predictive, but informed by the physical processes at play.