S150 Understanding the Effects of Wildfire Smoke on Solar Radiation

Sunday, 28 January 2024
Hall E (The Baltimore Convention Center)
Evan Chladny, University of Oklahoma, Norman, OK

Handout (4.3 MB)

Among the many factors that impact how much solar radiation reaches Earth’s surface, wildfire smoke and other particulate matter can block a substantial amount of light. Large wildfires can inject smoke as high as the stratosphere, and while the close-proximity effects of this wildfire smoke have previously been studied, the downstream effects are more nebulous. Therefore, diagnosing the spatial and temporal correlations between smoke and direct-normal solar radiation on a broad scale has importance in the meteorological community.

To understand this relationship, I employ the High-Resolution Rapid Refresh (HRRR) model’s Vertically Integrated Smoke (VIS) data and compare it to direct-normal solar radiation measurements from the Atmospheric Radiation Measurement user facility’s Southern Great Plains Multifilter Rotating Shadowband Radiometer (MFRSR) network. The 13 MFRSR devices in Kansas and Oklahoma track the sun across the sky and measure direct-beam radiation data. Using data from January 1, 2021, to July 31, 2023, I utilize the HRRR-VIS hourly analysis to identify days where smoke was present over each station. I can then calculate the total reduction from expected maximum radiation using MFRSR measurements and a standard solar model.

Two interesting features have presented themselves. First, there is a critical threshold where smoke values greater than 150 mg per square meter have a significant impact on the reduction of solar radiation. Second, there seems to be a spatial and temporal trend in the data, wherein the geographic locations of the fire as well as time of year alter the properties of the smoke and thus create a range of reductions in solar radiation. I aim to continue investigating how the origin of wildfires, and when they take place, impacts the smoke and solar radiation reduction. I am also eager to fit a regression with the data based on these factors, with potential applications in the use of artificial intelligence for solar forecasting. This research aims to give further insight into the many complex variables that must be considered to accurately understand the effects of wildfire smoke on solar radiation.

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