Sandia Peak Snowfall History – Follow Up

In my last blog post, I tried to answer the question: How has snowfall at Sandia Peak Ski Area changed over the years? Ultimately, I want to know how climate change is affecting the future of skiing in the Sandias and to develop some sense of what weather patterns are associated with particularly good or …

Sandia Peak Snowfall History

A few months ago I found out my local ski area, Sandia Peak, preemptively chose not to open for the upcoming ski season (2022/2023). It isn’t that unusual for Sandia Peak to stay closed for the season, and they were also closed last season. However, I had thought the decision to stay closed is typically …

Machine Learning for Snow Hydrology – A Follow Up

Overview Last winter I tried my hand at competing in a machine learning competition to predict snow water equivalent (SWE) across the Western United States. I learned a lot and created a two part blog series to document both the competition and my approach: Machine Learning for Snow Hydrology – A CompetitionMachine Learning for Snow …

South Foothills Weather Station

Overview I built a very unusual weather station on my roof. The measurements are pretty standard: wind, temperature, humidity – but everything else is unique, all the way down to the electronics. You can see a subset of the data, updated every 10 minutes at apps.crceanalytics.com/wxstation. It is far from the easiest or cheapest approach …

Greenland Snow Temperatures

My graduate degree research was focused on glacial hydrology, which is basically trying to figure out how water moves above, below, and through glaciers and ice sheets. Water is important because it affects things like sliding, melting, sub-glacial erosion, and geochemistry. My research utilized temperature measurements from snow on the Greenland ice sheet, and I …

Machine Learning for Snow Hydrology – Methods

This is the second part of my two part series on a machine learning competition to predict snow water equivalent (SWE). In Part 1, I describe the competition, as well as, my process for coming up with an approach for making SWE predictions at 9,067 locations across the Western US. That approach, sometimes called the …

Machine Learning for Snow Hydrology – A Competition

Part 1: Competition Overview Late last December I ran across a machine learning competition hosted by Driven Data. The goal of the competition is to predict snow water equivalent at high spatial resolution across the western US. I had never before thought of participating in a machine learning competition, although I had heard of the …

Automated QC of Environmental Data

Part 2: A Quality Control API This is the second in a two part series on automated quality control of environmental data. The first part gives an overview of quality control with some specific methods for environmental data. In this post, I describe how I created an API (api.crceanalytics.com) to automatically flag uploaded data using …