the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 15 Dec 2025
Evaluating Long-term Seasonal Variability of Aerosol Optical Properties in Colorado
Abstract. Aerosol particles resulting from both wildfires and dust events introduce considerable uncertainty into both climate research and public health assessments. These challenges are becoming particularly evident in the western U.S. To gain a deeper understanding of western U.S. aerosol properties, we analyzed 13 years (2011–2024) of surface in-situ aerosol optical data from Storm Peak Laboratory (SPL) in northwestern Colorado, and 6 years (2019–2024) of surface in-situ aerosol optical data from Table Mountain (BOS) in central Colorado. The aerosol optical properties at both sites demonstrate a strong summer wildfire smoke signal (peaking in August) and evidence of springtime dust events. BOS exhibited higher aerosol loading than SPL, particularly during spring and winter, consistent with the proximity of BOS to urban sources and its lower elevation. While the general patterns observed for SPL are consistent with a previous climatological analysis (covering the period 2011–2016) for the site, the longer SPL dataset used here shows that there has been a significant increase in extreme wildfire smoke events for 2017–2024 relative to 2011–2016. Both summer and fall exhibit statistically significant increasing trends in the upper percentiles of scattering coefficient with trends of 10 ± 1 % yr-1 at the 98th percentile in the summer and 2.4 ± 0.4 % yr-1 at the 96th percentile in the fall. Co-variability among some of the aerosol optical properties is used to further identify aerosol types and temporal patterns, demonstrating similarities between the two sites.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-5845', Anonymous Referee #1, 07 Jan 2026
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RC2: 'Comment on egusphere-2025-5845', Anonymous Referee #2, 09 Jan 2026
Review of Boedicker et al, Evaluating long-term seasonal variability of aerosol optical properties in Colorado
This paper discusses seasonal variability, climatology, and long-term trends in aerosol optical properties measured at two sites in Colorado: a high elevation remote site, and another nearer to the urban Front Range. Results show similar seasonality in aerosol optical properties, suggesting regional and long-range transport affect these sites, although magnitudes of aerosol loading are higher at the lower elevation site, consistent with additional urban influence. Trend analysis suggests that the highest aerosol scattering coefficients have increased in summer and fall, consistent that extreme wildfire events are influencing the haziest days. This paper is well-written and the analysis is sound. The authors do a great job of compiling and summarizing a large amount of data. I recommend publication after addressing comments below.
Overall comments:
The authors use relationships between optical properties to try and identify aerosol types and composition. They could take advantage of long-term composition data near these sites from the IMPROVE and CSN networks. These data have been reported in Hand et al (2024, https://doi.org/10.1029/2024JD042579) and may help place the results of this paper into the context of what has been reported for the aerosol composition in this same region and to discuss whether their results appear consistent with measured composition.
Have the authors compared size-related optical properties to each other? For example, the ratio of scattering a 1 um to 10 um compared to SAE? Or BFR
“Data” are commonly referred to in the plural within scientific literature, but there are many instances in this paper where it is referred to as the singular. Consider using the plural consistently.
When referring to trends, it is helpful to refer to a trend as “negative” (or “positive”) rather than “decreasing” (or “increasing”) because the trend itself is a rate. For example, for decreasing light scattering, the trend is negative. Consider replacing these instances in the text.
Organizational comment: It might be useful to reorganize the paper so that the trend analysis comes at the end. In this way the reader can contextualize the patterns observed in the data to how they have changed over time.
Figures: It would help to increase the font on the axis labels. It’s difficult to see the difference between the subscripts for “sp” and “ap” for scattering and absorption, respectively.
Other Comments
Line 75: The Storm Peak Laboratory and Table Mountain Field Site acronyms have been previously introduced and so could be used here.
Line 79: Define GAW
Line 104: Aerodynamic diameter is usually greater than physical diameter (Dp ~ Dae*SQRT((Chi/rho_p)), where Dp is physical diameter, Dae is aerodynamic diameter, Chi is shape factor, and rho_p is particle density.
Line 111: Acronyms for light scattering and backscattering have been introduced and can be substituted here.
Line 115: What are the uncertainties in scattering and absorption?
Line 138: Change “wavelength” to “wavelengths”
Line 139: Was this filtering also applied to analyses of light scattering and absorption, or only for calculated properties? Uncertainties in these calculated values could be calculated by propagating uncertainties in scattering and absorption. It would be helpful to provide these uncertainties, especially given the map of aerosol types shown later.
Line 170: What completeness criteria did the authors apply to calculate the parameters used in the trends? As well as in the climatological properties?
Line 173-174: Explicitly mention what is shown in Figure 2 and 3 (rather than group them together in the text).
Line 175: Add “respectively” after “BOS”
Line 207: It appears contradictory that in Lines 199-200 the authors state that during the May event limited upward and westward transport to SPL occurred.
Line 220: Why isn’t May included?
Line 227: Presumably all the light scattering data used for these trends are for RH<40% so the impacts of RH on scattering are not influencing these trends. Did the authors investigate these trends as a function of RH even below 40%? It is important to remind the reader that these trends are for aerosol properties considered to be “dry”.
Line 237: Trends in SAE in spring are ~0. If dust has decreased, wouldn’t SAE likely increase? Since winter and spring trends diverge over the 80th percentile (and presumably the increase in spring is related to dust) wouldn’t you expect to see this in the SAE? Do you see this impact on other size-related parameters?
Line 240: Light scattering in winter is quite low (according to Figure 3). What is the uncertainty in SAE during these months? Are the trends in the lowest percentiles reliable?
Line 248: “Consistent attributable” appears to be a typo.
Line 275: These have been defined and the acronyms could be used here.
Line 275: and also for fall for BFR.
Line 286: The acronym could be used here.
Line 298: What do the authors mean by “anthropogenic biomass burning”?
Line 303: Figure S11 shows number of hours- number of hours of what?
Line 323: Can the authors explain why the particles have become less absorbing but there appears to be more smoke in the later period?
Line 325: Is the SPL site influenced by residential wood combustion in Steamboat?
Line 377 and associated discussions of clusters: Please include the cluster number after each mention as it’s easier to find on the plot.
Line 381: Figure S16: This seems like a step change for all seasons. Does this make sense that BC dominates all seasons and all seasons see this change?
Line 428/9: The acronyms for scattering can be used here.
Figure Captions
Figure 2: Add “a” and “b” in the caption. Include that these data in (a) and (b) correspond to RH< 40%.
Figure 3: Include the years in the caption.
Figure 4: Provide years for trends and include RH < 40%. Here the significance is given by alpha but the rest of the text it is referred to as a p-value (like line 167).
Figure 1: Change S14 to S12.
Figure S7: Include the location in the caption.
Figure S8: Include (a), (b), etc in the caption. What is the difference between a-b and c-d?
Figure S11: Captions states “histogram” but axis reads “# of hours” ?
Citation: https://doi.org/10.5194/egusphere-2025-5845-RC2
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Comments on « Evaluating long-term seasonal variability of aerosol optical properties in Colorado” from Boedicker et al.
Five and fourteen years of aerosol in-situ data at BOS and SPL, respectively, were analyzed in this study to infer the climatology of aerosol in remote sites of Colorado. If BOS is situated in the vicinity of cities, SPL is a remote high-altitude station with less influence of aerosol from the planetary boundary layer. The study presents the diurnal and seasonal cycles of parameters measured by the nephelometer and filter-based absorption photometers and discusses the impact of dust and wildfires and shows that BB influence is increasing due to climate changes.
Major comments:
Minor comments: