the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 03 Feb 2022
Technical Note: A High-Resolution Autonomous Record of Ice Nuclei Concentrations for Fall and Winter at Storm Peak Laboratory
Abstract. High-resolution, long-term measurements of ice nucleating particles (INPs) have been impeded by complex instrumentation that requires a trained on-site technician to operate or analyze offline. We have significantly updated the well-characterized continuous flow diffusion chamber (CFDC) instrument to run autonomously with minimal in-person handling and easy remote access. This new CFDC, the CFDC-Ice Activation Spectrometer (CFDC-IAS) was deployed for four months (October 2020–January 2021) at the mountain-top Storm Peak Laboratory site in Colorado and provided 5-minute resolution measurements daily at target temperatures of −20, −25, and −30 °C. Concentrations of INPs across all temperatures had a median value of 6 per standard liter (sL−1), and a mean of 10 sL−1 with a range of ~0–470 sL−1.
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Interactive discussion
Status: closed
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RC1: 'Comment on acp-2022-29', Gabor Vali, 19 Feb 2022
The goal of obtaining INP measurements continuously in time and over the range of temperatures covered by tropospheric clouds is a very desirable one indeed. When accompanied by other physical and chemical data about the atmospheric aerosol such measurements could be very helpful in unraveling the many uncertainties which are obstacles to usable descriptions of ice initiation in the atmosphere. From that perspective the paper is a welcome contribution. The site selected for the measurements here reported is not ideal but has advantages. Past use of the site for similar studies helps to provide some perspective.
This paper is formulated as a Technical Note but it is hard to tell the difference in emphasis between trying to accomplish two things: to demonstrate the accomplishment of continuous operation of a modified CFDC, and to show results obtained during the period of operation. Neither goal is quite accomplished satisfactorily.
The modifications of the CFDC are described in some detail but in a way that is hard to comprehend without intimate knowledge of the design and operation of the instrument. The basic theory of operation of the CFDC instruments is well documented in the literature. However, intimate details of the operation, specifically the cycling needed to maintain the ice coating on the walls, the avoidance of ice shedding from the walls and the drop/ice crystal thresholding are not well explained in this paper and are hard to track down in earlier papers. Thus, the technical details given for various changes are somewhat in the air. More importantly, it would have been very helpful to see more objective measures of assurance that the device was functioning correctly throughout the long sampling period. The comparison with a previously tested device is a good sign but, clearly, those tests were done with operator assistance while autonomous operation is another matter, specially in the case of an instrument that needs periodic rebuilding of the critical ice coatings of the inner surfaces.
The change to aluminum construction was done to provide surfaces that are more suitable for the formation of the ice layers without periodic treatment of the surfaces. This is a good step if it works, but raises questions about how the aluminum surface may have changed during the operating period and how that may have affected the ice coatings. Were the ice layers uniform over the whole surface? Were there patches without ice? Were there any controls, or specifics of the data that could be used to judge the constancy of the required conditions. This is readily done for wall temperature but is more subtle with respect to the saturation value accomplished. Perhaps there is no problem here but the readers should be provided by some assurances.
Regarding the long-term continuous record, the paper presents only a glimmer at the results. Statistics over the whole period are given in Fig. 4. The authors suggest that the 'public dataset maybe of interest ... ". This is likely to be true but the value of the dataset can't be judged from this paper. Would the overall statistics be much different if derived from intermittent sampling, say, on daily basis? How can the reader evaluate the benefits of continuous sampling? It was tempting for this reviewer to actually obtain some of the data and look for answers to the questions posed above. But, it is perhaps best done by someone with direct experience with CFDC instruments.
The analyses presented are reasonable but add little real substance. The derived surface site density values are speculative because the INP sizes are not known and may be quite different from the assumed values. The comparison with the prior parameterizations is quite short of meaningful correlations and are hard to judge because data for all temperatures are shown in saturated plots (Fig 5).
The two points are, in fact, related. Examinations of the detailed data may provide some basis for judging the adequacy of instrument performance through consistency versus erratic behaviors.
Overall, what is presented in the paper does not indicate definite problems but neither does the material show robust reasons for accepting the results. The somewhat surprising lack of INP concentrations on temperature add to justified curiosity about the validity of the data. Does shorter term data show temperature dependence at any time? Or, are all INPs in the dataset activated at temperatures at or above -20°C, the highest temperature at which measurements are made?
It appears that the authors' main focus was making an instrument capable of continuous operation. They are likely to have accomplished that goal, or came close to it. However, for measurements that are highly sensitive to instrumental conditions it is desirable to have some controls monitoring those conditions. If such information is not available and can't be re-created in retrospect, relevant disclaimers or caveats may be necessary.
To demonstrate the nature of high-resolution data (as in the title of the paper) more detail than here given would be beneficial. The title should perhaps also indicate the temperatures for which data have been obtained.
Citation: https://doi.org/10.5194/acp-2022-29-RC1 -
RC2: 'Comment on acp-2022-29', Anonymous Referee #2, 24 Feb 2022
Hodshire et al, present results obtained with a newly automated CFDC for the quantification of INPs. Although, the CFDC appears to be working autonomously, which is a major feat, I have serious questions about how the INP concentration observations are reported. The lack of temperature dependence is truly surprising and goes against the previously observed and understood dependence of temperature on the ability of aerosol particles to nucleate ice in the immersion mode. Therefore, I recommend that the authors spend some time to assess the representativeness of the reported values before the manuscript is accepted into ACP. Furthermore, a deeper analysis of the factors controlling the variability in INP concentrations should be presented.
Major comments:
The lack of temperature variability in the observed INP concentrations is truly surprising. The statistical methods to achieve these results need to be discussed and presented. Based on the acknowledged limit of detection (almost 1 L-1) of the CFDC, the presented results are likely not representative of the actual temperature dependence of INPs that are observed at SPL. Please discuss this limitation on the presented results and assess how meaningful the presented values are at -20 and -25 C. With this limit of detection in place, it is clear that only the upper end of INP concentrations occurring at these temperatures will be observable. This limits the meaningfulness of the presented statistics. There are several locations in the paper where this could be discussed/improved as highlighted below.
The main benefit of having high resolution and continuous INP measurements is to understand the factors that control INPs. Unfortunately, it appears as if there is no dependency on previously established controls (e.g. meteorological factors, aerosols) of INPs. Perhaps this is masked due to the discussion spanning all of the temperatures rather than only the observations at -30 C where background issues are likely less important (e.g. Brunner et al., 2021). Regardless, a deeper analysis controlling the variability of INPs should be conducted. Otherwise, the paper is more of an instrument development/proof concept (e.g. AMT paper) rather than an ACP paper.
Minor comments:
Line 30: There are now a few automated CFDC measurements that have conducted continuous measurements for longer periods of time (Möhler et al., 2021; Brunner and Kanji, 2021)
Line 42: Again this is perhaps the first of its kind at SPL but definitely not the first automated long-term mountaintop INP measurements (Brunner and Kanji, 2021).
Line 54: The WRCC climate portal reported snowfall observations are for the town of Steamboat Springs and are not representative of what is observed at SPL. The snow depth sensors and weighing rain gauges around SPL (e.g. Tower Snotel has an average SWE of ~50 inches annually) report a much higher annual snowfall amount. Please double check this.
Line 90-93: Were the aluminum walls sanded such that they were rough and able to better retain water and subsequent ice? This might be an interesting detail to add for future CFDC development.
Line 97: What determined a sampling time of 4 or 6 hours before defrosting and reicing? This is quite a difference in terms of background degradation.
Line 99-101: A background of 1 L-1 is a significant concentration when considering that typical INP concentrations at -20 C have been previously reported to range between ~0.05 and ~1 L-1 based on precipitation samples (e.g. Petters and Wright, 2015) or between ~ 0.01 and ~100 L-1 in the air (e.g. Kanji et al., 2017). How were sampling periods where the INP concentration was below the limit of detection handled? Is this accounted for in the reported statistics?
Line 129: What was the target saturation, was it the same for all temperatures?
Line 136: The lack of dependence of INP concentration on temperature here is astonishing. Furthermore, the lower estimates of the INP concentration are certainly influenced by the limit of detection (the background concentrations). This should be acknowledged here and also how measurements below the limit of detection are handled should be discussed.
Line 136-138: How efficient is the inlet at sampling precipitation particles e.g. cloud droplets? If these particles are not sampled then does this indicate that the INP measurements during precipitation are of interstitial aerosols? Also, the lack of a diurnal cycle is quite striking considering results on the influence of boundary layer intrusions on INPs at other mountaintop observatories (e.g. Lacher et al., 2018; Brunner et al., 2021). Do the aerosol concentrations have a diurnal cycle?
Line 146-148: Was the amount of precipitation along the back trajectories considered? Previous studies have suggested that precipitation can either increase or decrease INP concentrations (e.g. (Stopelli et al., 2015; Huffman et al., 2013; Mignani et al., 2021)
Line 170: Again, the lack in variability between -25 and -30 in ns values is truly surprising. This would indicate that the aerosol particles responsible for the observed ice activation would have the same efficiency at -25 as at -30 C. Typically, the INP concentration increases by an order of magnitude every 5 degrees (e.g. Atkinson et al., 2013; Murray et al., 2012)
Figure 2: Based on panel a. it looks like there are occasions where the INP concentration is higher at warmer temperatures than colder ones. This seems unphysical and again raises the issue of the importance of the background on the measurements.
Figure 4: It would be worth including the number of statistically significant observations used to make the box and whisker plots for each set temperature.
Technical comments:
Figure 1: The legend has filled markers yet the figure has open markers. Also, it might be worthwhile to add uncertainties to the reported data points to account for uncertainties in temperature.
Figure 2: As only three set temperatures were investigated, consider switching to a discrete color bar rather than a continuous one.
References:
Atkinson, J. D., Murray, B. J., Woodhouse, M. T., Whale, T. F., Baustian, K. J., Carslaw, K. S., Dobbie, S., O’Sullivan, D., and Malkin, T. L.: The importance of feldspar for ice nucleation by mineral dust in mixed-phase clouds, Nature, 498, 355, https://doi.org/10.1038/nature12278, 2013.
Brunner, C. and Kanji, Z. A.: Continuous online monitoring of ice-nucleating particles: development of the automated Horizontal Ice Nucleation Chamber (HINC-Auto), Atmospheric Meas. Tech., 14, 269–293, https://doi.org/10.5194/amt-14-269-2021, 2021.
Brunner, C., Brem, B. T., Collaud Coen, M., Conen, F., Hervo, M., Henne, S., Steinbacher, M., Gysel-Beer, M., and Kanji, Z. A.: The contribution of Saharan dust to the ice-nucleating particle concentrations at the High Altitude Station Jungfraujoch (3580 m a.s.l.), Switzerland, Atmospheric Chem. Phys., 21, 18029–18053, https://doi.org/10.5194/acp-21-18029-2021, 2021.
Huffman, J. A., Prenni, A. J., DeMott, P. J., Pöhlker, C., Mason, R. H., Robinson, N. H., Fröhlich-Nowoisky, J., Tobo, Y., Després, V. R., Garcia, E., Gochis, D. J., Harris, E., Müller-Germann, I., Ruzene, C., Schmer, B., Sinha, B., Day, D. A., Andreae, M. O., Jimenez, J. L., Gallagher, M., Kreidenweis, S. M., Bertram, A. K., and Pöschl, U.: High concentrations of biological aerosol particles and ice nuclei during and after rain, Atmospheric Chem. Phys., 13, 6151–6164, https://doi.org/10.5194/acp-13-6151-2013, 2013.
Kanji, Z. A., Ladino, L. A., Wex, H., Boose, Y., Burkert-Kohn, M., Cziczo, D. J., and Krämer, M.: Overview of Ice Nucleating Particles, Meteorol. Monogr., 58, 1.1-1.33, https://doi.org/10.1175/AMSMONOGRAPHS-D-16-0006.1, 2017.
Lacher, L., DeMott, P. J., Levin, E. J. T., Suski, K. J., Boose, Y., Zipori, A., Herrmann, E., Bukowiecki, N., Steinbacher, M., Gute, E., Abbatt, J. P. D., Lohmann, U., and Kanji, Z. A.: Background Free-Tropospheric Ice Nucleating Particle Concentrations at Mixed-Phase Cloud Conditions, J. Geophys. Res. Atmospheres, 123, 10,506-10,525, https://doi.org/10.1029/2018JD028338, 2018.
Mignani, C., Wieder, J., Sprenger, M. A., Kanji, Z. A., Henneberger, J., Alewell, C., and Conen, F.: Towards parameterising atmospheric concentrations of ice-nucleating particles active at moderate supercooling, Atmospheric Chem. Phys., 21, 657–664, https://doi.org/10.5194/acp-21-657-2021, 2021.
Möhler, O., Adams, M., Lacher, L., Vogel, F., Nadolny, J., Ullrich, R., Boffo, C., Pfeuffer, T., Hobl, A., Weiß, M., Vepuri, H. S. K., Hiranuma, N., and Murray, B. J.: The Portable Ice Nucleation Experiment (PINE): a new online instrument for laboratory studies and automated long-term field observations of ice-nucleating particles, Atmospheric Meas. Tech., 14, 1143–1166, https://doi.org/10.5194/amt-14-1143-2021, 2021.
Murray, B. J., O’Sullivan, D., D. Atkinson, J., and E. Webb, M.: Ice nucleation by particles immersed in supercooled cloud droplets, Chem. Soc. Rev., 41, 6519–6554, https://doi.org/10.1039/C2CS35200A, 2012.
Petters, M. D. and Wright, T. P.: Revisiting ice nucleation from precipitation samples, Geophys. Res. Lett., 42, 8758–8766, https://doi.org/10.1002/2015GL065733, 2015.
Stopelli, E., Conen, F., Morris, C. E., Herrmann, E., Bukowiecki, N., and Alewell, C.: Ice nucleation active particles are efficiently removed by precipitating clouds, Sci. Rep., 5, 16433, https://doi.org/10.1038/srep16433, 2015.
Citation: https://doi.org/10.5194/acp-2022-29-RC2 -
RC3: 'Comment on acp-2022-29', Anonymous Referee #3, 27 Feb 2022
Review of Hodshire et al. (2022): Technical Note: A High-Resolution Autonomous Record of Ice Nuclei Concentrations for Fall and Winter at Storm Peak Laboratory
General comments:
In this technical note, the authors present modifications to an automated, near-continuous INP counter, the Handix Scientific CFDC Ice Activation Spectrometer (CFDC-IAS), and data measured with the CFDC-IAS for four months at the Storm Peak Laboratory (SPL). Specifically, measurements of atmospheric INP concentrations at 10-minute resolution are presented between October 9, 2020, and January 29, 2021, with the chamber in operation for the entire period except January 3-10. Parallel APS and SMPS measurements at SPL allowed estimation of the density of active surface sites. In addition, a period of high and low INP concentration was qualitatively analyzed using NOAA HYSPLIT back trajectories.
The writing (from an editorial standpoint) is to be commended. However, relevant technical details on the design changes are missing for a technical note. Validation of the changes is lean, but what is presented is solid. The discussion of validation is brief and must be done by the reader through study of Figure 1 itself. There is too much information on atmospheric parameters other than INP concentrations (e.g., Fig. 2b-d) for a technical note. It is debatable whether the single design change qualifies for a technical note or whether it would be better included in a manuscript with an in-depth analysis of its measurements. Potentially, the manuscript aims for the latter, but in my opinion misses to qualify, as the manuscript fails to analyze and discuss important elements. An example is the observed lower INP concentrations at -30 °C than at -25 °C and -20 °C, which does not reflect the consensus of previous studies and may indicate an invalid measurement methodology, thus, should be critically reviewed by the authors. The topic of the paper is well suited for ACP. However, I suggest that the manuscript undergo a major revision to reflect the following comments:
Major comments:
- Please provide more technical information on the design changes. Also, relevant parameters and statistics are missing for an automated near-continuous INP counter. E.g.: how long are the gaps needed to renew the ice layer? What is the percentage of atmospheric measurements within the total time (atmospheric measurements divided by total time including atmospheric measurements, background measurements, cooling, warming, or temperature compensation periods, ice layer renewal, and maintenance)? How does the signal-to-noise ratio change over time (not only qualitatively, but also quantitatively)? What happens with the water needed to form the ice layer and how is it recycled?
- Are there any indications for the lower INP concentrations at -30 °C compared to -20 °C? This does not reflect the consensus of previous studies and may indicate an invalid measurement methodology, thus, should be critically reviewed by the authors.
- Please provide numbers and discuss the implications in more detail. For example, lines 136-138 state that there was little difference in medians or IQR between observations inside and outside clouds or between daytime and nighttime observations, but lack a more detailed discussion, e.g., of what these results mean and what the causes might be when comparing observed patterns of total aerosol number concentrations or other aerosol quantities. Missing discussions on implications are also true throughout the manuscript. Analysis using back trajectories has been done extensively in numerous previous studies. However, new insights remain missing, and thus, the back trajectory analysis can be left out from the manuscript. In addition, the advantage of continuous, high-resolution INP measurements is not exploited as only two events were analyzed.
Specific comments:
Abstract (lines 15-21): a very concise summary. However, it lacks an introductory sentence or two on why measuring atmospheric INP concentrations is relevant. Since the focus of the manuscript is on autonomous INP measurements, more information should be provided on the frequency of site visits required (e.g., 1/week to replace desiccant).
Chapter 2.1 (line 56): please provide the amount of snow in standard international units (mm).
Chapter 2.2 (lines 95-98): please provide measurements or estimations of the transmission fraction of particles <2.5 μm through the sample line and the diffusion dryers until entering the CFDC.
Chapter 2.2 (lines 95-108): I infer that the only supply needed to run the chamber continuously are electric energy, desiccant and nitrogen. How is the water for the ice layer recycled?
Chapter 3.2 (line 136): Please quantify “little difference” for both cases (in cloud vs. out of cloud and night vs. day).
Chapter 3.2 (line 142): Please quantify “No strong correlation” for all cases.
Chapter 3.2 (lines 143-148): Food for thought: Given the large amount of data collected over the four months, more than a qualitative comparison of two periods would have been interesting.
Chapter 3.2 (lines 143-148): Whether it is a qualitative comparison of two periods or a quantitative analysis of the entire four months, the limitations of the used tools must be addressed: what are the limitations of the analysis using back trajectories from a 1-degree GDAS reanalysis, since they are unlikely to fully resolve local features? Please explain the degree of uncertainty in the back trajectories used, e.g., by referring to previous studies where this has been analyzed at SPL.
Chapter 3.2 (lines 151-153): “Other high-elevation free tropospheric INP measurements…” implies, the presented measurements at SPL were sampling free tropospheric air masses. Please provide quantitative evidence for this statement.
Chapter 3.2 (lines 151-156) and chapter 4 (lines 197-198): There are interesting statements within these lines: short-term, high concentration events that were not picked up by previous measurement techniques. Please elaborate on these events. How frequent were they observed? How long did they last? Where there co-located signals in other aerosol parameter such as total number concentration or spikes in aerosol in a specific size bin? Can local pollution be ruled out? To my understanding, such brief events should also be captured during the three times longer sample duration used in, e.g., Lacher et al. (2018) or Brunner et al. (2021). Brunner et al. (2021) also measured continuously for one year, so their measurements should provide near identical temporal resolution. What are other reasons that other studies have missed these short events?
Chapter 3.2 (lines 163-171): As there is much emphasis on surface active site density, I would suggest to show a time series of ns and discuss ns in more detail. E.g., also looking at the number concentration of large particles. Furthermore, the fact that ns for INP at -25 °C and -30 °C are identical is striking and does not align with previous studies. This should be discussed in more detail in addition to the major comment #2.
Chapter 4 (lines 198-199): What are the different transport patterns between this and previous campaigns? Please elaborate in Chapter 3.
Figure 3: Please add the year to the title of the figure.
Figure 4: In panel a, the °-symbol is missing and in panel b, the unit of the temperature categories remains missing. For consistency, I would suggest to add the units to the axis labels (e.g., Temperature category [°C]). Also, “temperature category” form the axis labels is once capitalized and once not. Please use a consistent style.
Figure 5: The data points at -25 °C and -20 °C are shadowed by the data points at -30 °C. I would suggest adding transparency to the markers, such that more information is visible.
Literature:
Brunner, C., Brem, B. T., Collaud Coen, M., Conen, F., Steinbacher, M., Gysel-Beer, M., and Kanji, Z. A.: The diurnal and seasonal variability of ice nucleating particles at the High Altitude Station Jungfraujoch (3580 m a.s.l.), Switzerland, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2021-710, in review, 2021.
Lacher, L., DeMott, P. J., Levin, E. J. T., Suski, K. J., Boose, Y., Zipori, A., Herrmann, E., Bukowiecki, N., Steinbacher, M., Gute, E., Abbatt, J. P. D., Lohmann, U., and Kanji, Z. A.: Background freeâtropospheric ice nucleating particle concentrations at mixedâphase cloud conditions, J. Geophys. Res., 123, 10,506–10,525, 2018.
Citation: https://doi.org/10.5194/acp-2022-29-RC3 - AC1: 'Comment on acp-2022-29', Anna Hodshire, 10 May 2022
Interactive discussion
Status: closed
-
RC1: 'Comment on acp-2022-29', Gabor Vali, 19 Feb 2022
The goal of obtaining INP measurements continuously in time and over the range of temperatures covered by tropospheric clouds is a very desirable one indeed. When accompanied by other physical and chemical data about the atmospheric aerosol such measurements could be very helpful in unraveling the many uncertainties which are obstacles to usable descriptions of ice initiation in the atmosphere. From that perspective the paper is a welcome contribution. The site selected for the measurements here reported is not ideal but has advantages. Past use of the site for similar studies helps to provide some perspective.
This paper is formulated as a Technical Note but it is hard to tell the difference in emphasis between trying to accomplish two things: to demonstrate the accomplishment of continuous operation of a modified CFDC, and to show results obtained during the period of operation. Neither goal is quite accomplished satisfactorily.
The modifications of the CFDC are described in some detail but in a way that is hard to comprehend without intimate knowledge of the design and operation of the instrument. The basic theory of operation of the CFDC instruments is well documented in the literature. However, intimate details of the operation, specifically the cycling needed to maintain the ice coating on the walls, the avoidance of ice shedding from the walls and the drop/ice crystal thresholding are not well explained in this paper and are hard to track down in earlier papers. Thus, the technical details given for various changes are somewhat in the air. More importantly, it would have been very helpful to see more objective measures of assurance that the device was functioning correctly throughout the long sampling period. The comparison with a previously tested device is a good sign but, clearly, those tests were done with operator assistance while autonomous operation is another matter, specially in the case of an instrument that needs periodic rebuilding of the critical ice coatings of the inner surfaces.
The change to aluminum construction was done to provide surfaces that are more suitable for the formation of the ice layers without periodic treatment of the surfaces. This is a good step if it works, but raises questions about how the aluminum surface may have changed during the operating period and how that may have affected the ice coatings. Were the ice layers uniform over the whole surface? Were there patches without ice? Were there any controls, or specifics of the data that could be used to judge the constancy of the required conditions. This is readily done for wall temperature but is more subtle with respect to the saturation value accomplished. Perhaps there is no problem here but the readers should be provided by some assurances.
Regarding the long-term continuous record, the paper presents only a glimmer at the results. Statistics over the whole period are given in Fig. 4. The authors suggest that the 'public dataset maybe of interest ... ". This is likely to be true but the value of the dataset can't be judged from this paper. Would the overall statistics be much different if derived from intermittent sampling, say, on daily basis? How can the reader evaluate the benefits of continuous sampling? It was tempting for this reviewer to actually obtain some of the data and look for answers to the questions posed above. But, it is perhaps best done by someone with direct experience with CFDC instruments.
The analyses presented are reasonable but add little real substance. The derived surface site density values are speculative because the INP sizes are not known and may be quite different from the assumed values. The comparison with the prior parameterizations is quite short of meaningful correlations and are hard to judge because data for all temperatures are shown in saturated plots (Fig 5).
The two points are, in fact, related. Examinations of the detailed data may provide some basis for judging the adequacy of instrument performance through consistency versus erratic behaviors.
Overall, what is presented in the paper does not indicate definite problems but neither does the material show robust reasons for accepting the results. The somewhat surprising lack of INP concentrations on temperature add to justified curiosity about the validity of the data. Does shorter term data show temperature dependence at any time? Or, are all INPs in the dataset activated at temperatures at or above -20°C, the highest temperature at which measurements are made?
It appears that the authors' main focus was making an instrument capable of continuous operation. They are likely to have accomplished that goal, or came close to it. However, for measurements that are highly sensitive to instrumental conditions it is desirable to have some controls monitoring those conditions. If such information is not available and can't be re-created in retrospect, relevant disclaimers or caveats may be necessary.
To demonstrate the nature of high-resolution data (as in the title of the paper) more detail than here given would be beneficial. The title should perhaps also indicate the temperatures for which data have been obtained.
Citation: https://doi.org/10.5194/acp-2022-29-RC1 -
RC2: 'Comment on acp-2022-29', Anonymous Referee #2, 24 Feb 2022
Hodshire et al, present results obtained with a newly automated CFDC for the quantification of INPs. Although, the CFDC appears to be working autonomously, which is a major feat, I have serious questions about how the INP concentration observations are reported. The lack of temperature dependence is truly surprising and goes against the previously observed and understood dependence of temperature on the ability of aerosol particles to nucleate ice in the immersion mode. Therefore, I recommend that the authors spend some time to assess the representativeness of the reported values before the manuscript is accepted into ACP. Furthermore, a deeper analysis of the factors controlling the variability in INP concentrations should be presented.
Major comments:
The lack of temperature variability in the observed INP concentrations is truly surprising. The statistical methods to achieve these results need to be discussed and presented. Based on the acknowledged limit of detection (almost 1 L-1) of the CFDC, the presented results are likely not representative of the actual temperature dependence of INPs that are observed at SPL. Please discuss this limitation on the presented results and assess how meaningful the presented values are at -20 and -25 C. With this limit of detection in place, it is clear that only the upper end of INP concentrations occurring at these temperatures will be observable. This limits the meaningfulness of the presented statistics. There are several locations in the paper where this could be discussed/improved as highlighted below.
The main benefit of having high resolution and continuous INP measurements is to understand the factors that control INPs. Unfortunately, it appears as if there is no dependency on previously established controls (e.g. meteorological factors, aerosols) of INPs. Perhaps this is masked due to the discussion spanning all of the temperatures rather than only the observations at -30 C where background issues are likely less important (e.g. Brunner et al., 2021). Regardless, a deeper analysis controlling the variability of INPs should be conducted. Otherwise, the paper is more of an instrument development/proof concept (e.g. AMT paper) rather than an ACP paper.
Minor comments:
Line 30: There are now a few automated CFDC measurements that have conducted continuous measurements for longer periods of time (Möhler et al., 2021; Brunner and Kanji, 2021)
Line 42: Again this is perhaps the first of its kind at SPL but definitely not the first automated long-term mountaintop INP measurements (Brunner and Kanji, 2021).
Line 54: The WRCC climate portal reported snowfall observations are for the town of Steamboat Springs and are not representative of what is observed at SPL. The snow depth sensors and weighing rain gauges around SPL (e.g. Tower Snotel has an average SWE of ~50 inches annually) report a much higher annual snowfall amount. Please double check this.
Line 90-93: Were the aluminum walls sanded such that they were rough and able to better retain water and subsequent ice? This might be an interesting detail to add for future CFDC development.
Line 97: What determined a sampling time of 4 or 6 hours before defrosting and reicing? This is quite a difference in terms of background degradation.
Line 99-101: A background of 1 L-1 is a significant concentration when considering that typical INP concentrations at -20 C have been previously reported to range between ~0.05 and ~1 L-1 based on precipitation samples (e.g. Petters and Wright, 2015) or between ~ 0.01 and ~100 L-1 in the air (e.g. Kanji et al., 2017). How were sampling periods where the INP concentration was below the limit of detection handled? Is this accounted for in the reported statistics?
Line 129: What was the target saturation, was it the same for all temperatures?
Line 136: The lack of dependence of INP concentration on temperature here is astonishing. Furthermore, the lower estimates of the INP concentration are certainly influenced by the limit of detection (the background concentrations). This should be acknowledged here and also how measurements below the limit of detection are handled should be discussed.
Line 136-138: How efficient is the inlet at sampling precipitation particles e.g. cloud droplets? If these particles are not sampled then does this indicate that the INP measurements during precipitation are of interstitial aerosols? Also, the lack of a diurnal cycle is quite striking considering results on the influence of boundary layer intrusions on INPs at other mountaintop observatories (e.g. Lacher et al., 2018; Brunner et al., 2021). Do the aerosol concentrations have a diurnal cycle?
Line 146-148: Was the amount of precipitation along the back trajectories considered? Previous studies have suggested that precipitation can either increase or decrease INP concentrations (e.g. (Stopelli et al., 2015; Huffman et al., 2013; Mignani et al., 2021)
Line 170: Again, the lack in variability between -25 and -30 in ns values is truly surprising. This would indicate that the aerosol particles responsible for the observed ice activation would have the same efficiency at -25 as at -30 C. Typically, the INP concentration increases by an order of magnitude every 5 degrees (e.g. Atkinson et al., 2013; Murray et al., 2012)
Figure 2: Based on panel a. it looks like there are occasions where the INP concentration is higher at warmer temperatures than colder ones. This seems unphysical and again raises the issue of the importance of the background on the measurements.
Figure 4: It would be worth including the number of statistically significant observations used to make the box and whisker plots for each set temperature.
Technical comments:
Figure 1: The legend has filled markers yet the figure has open markers. Also, it might be worthwhile to add uncertainties to the reported data points to account for uncertainties in temperature.
Figure 2: As only three set temperatures were investigated, consider switching to a discrete color bar rather than a continuous one.
References:
Atkinson, J. D., Murray, B. J., Woodhouse, M. T., Whale, T. F., Baustian, K. J., Carslaw, K. S., Dobbie, S., O’Sullivan, D., and Malkin, T. L.: The importance of feldspar for ice nucleation by mineral dust in mixed-phase clouds, Nature, 498, 355, https://doi.org/10.1038/nature12278, 2013.
Brunner, C. and Kanji, Z. A.: Continuous online monitoring of ice-nucleating particles: development of the automated Horizontal Ice Nucleation Chamber (HINC-Auto), Atmospheric Meas. Tech., 14, 269–293, https://doi.org/10.5194/amt-14-269-2021, 2021.
Brunner, C., Brem, B. T., Collaud Coen, M., Conen, F., Hervo, M., Henne, S., Steinbacher, M., Gysel-Beer, M., and Kanji, Z. A.: The contribution of Saharan dust to the ice-nucleating particle concentrations at the High Altitude Station Jungfraujoch (3580 m a.s.l.), Switzerland, Atmospheric Chem. Phys., 21, 18029–18053, https://doi.org/10.5194/acp-21-18029-2021, 2021.
Huffman, J. A., Prenni, A. J., DeMott, P. J., Pöhlker, C., Mason, R. H., Robinson, N. H., Fröhlich-Nowoisky, J., Tobo, Y., Després, V. R., Garcia, E., Gochis, D. J., Harris, E., Müller-Germann, I., Ruzene, C., Schmer, B., Sinha, B., Day, D. A., Andreae, M. O., Jimenez, J. L., Gallagher, M., Kreidenweis, S. M., Bertram, A. K., and Pöschl, U.: High concentrations of biological aerosol particles and ice nuclei during and after rain, Atmospheric Chem. Phys., 13, 6151–6164, https://doi.org/10.5194/acp-13-6151-2013, 2013.
Kanji, Z. A., Ladino, L. A., Wex, H., Boose, Y., Burkert-Kohn, M., Cziczo, D. J., and Krämer, M.: Overview of Ice Nucleating Particles, Meteorol. Monogr., 58, 1.1-1.33, https://doi.org/10.1175/AMSMONOGRAPHS-D-16-0006.1, 2017.
Lacher, L., DeMott, P. J., Levin, E. J. T., Suski, K. J., Boose, Y., Zipori, A., Herrmann, E., Bukowiecki, N., Steinbacher, M., Gute, E., Abbatt, J. P. D., Lohmann, U., and Kanji, Z. A.: Background Free-Tropospheric Ice Nucleating Particle Concentrations at Mixed-Phase Cloud Conditions, J. Geophys. Res. Atmospheres, 123, 10,506-10,525, https://doi.org/10.1029/2018JD028338, 2018.
Mignani, C., Wieder, J., Sprenger, M. A., Kanji, Z. A., Henneberger, J., Alewell, C., and Conen, F.: Towards parameterising atmospheric concentrations of ice-nucleating particles active at moderate supercooling, Atmospheric Chem. Phys., 21, 657–664, https://doi.org/10.5194/acp-21-657-2021, 2021.
Möhler, O., Adams, M., Lacher, L., Vogel, F., Nadolny, J., Ullrich, R., Boffo, C., Pfeuffer, T., Hobl, A., Weiß, M., Vepuri, H. S. K., Hiranuma, N., and Murray, B. J.: The Portable Ice Nucleation Experiment (PINE): a new online instrument for laboratory studies and automated long-term field observations of ice-nucleating particles, Atmospheric Meas. Tech., 14, 1143–1166, https://doi.org/10.5194/amt-14-1143-2021, 2021.
Murray, B. J., O’Sullivan, D., D. Atkinson, J., and E. Webb, M.: Ice nucleation by particles immersed in supercooled cloud droplets, Chem. Soc. Rev., 41, 6519–6554, https://doi.org/10.1039/C2CS35200A, 2012.
Petters, M. D. and Wright, T. P.: Revisiting ice nucleation from precipitation samples, Geophys. Res. Lett., 42, 8758–8766, https://doi.org/10.1002/2015GL065733, 2015.
Stopelli, E., Conen, F., Morris, C. E., Herrmann, E., Bukowiecki, N., and Alewell, C.: Ice nucleation active particles are efficiently removed by precipitating clouds, Sci. Rep., 5, 16433, https://doi.org/10.1038/srep16433, 2015.
Citation: https://doi.org/10.5194/acp-2022-29-RC2 -
RC3: 'Comment on acp-2022-29', Anonymous Referee #3, 27 Feb 2022
Review of Hodshire et al. (2022): Technical Note: A High-Resolution Autonomous Record of Ice Nuclei Concentrations for Fall and Winter at Storm Peak Laboratory
General comments:
In this technical note, the authors present modifications to an automated, near-continuous INP counter, the Handix Scientific CFDC Ice Activation Spectrometer (CFDC-IAS), and data measured with the CFDC-IAS for four months at the Storm Peak Laboratory (SPL). Specifically, measurements of atmospheric INP concentrations at 10-minute resolution are presented between October 9, 2020, and January 29, 2021, with the chamber in operation for the entire period except January 3-10. Parallel APS and SMPS measurements at SPL allowed estimation of the density of active surface sites. In addition, a period of high and low INP concentration was qualitatively analyzed using NOAA HYSPLIT back trajectories.
The writing (from an editorial standpoint) is to be commended. However, relevant technical details on the design changes are missing for a technical note. Validation of the changes is lean, but what is presented is solid. The discussion of validation is brief and must be done by the reader through study of Figure 1 itself. There is too much information on atmospheric parameters other than INP concentrations (e.g., Fig. 2b-d) for a technical note. It is debatable whether the single design change qualifies for a technical note or whether it would be better included in a manuscript with an in-depth analysis of its measurements. Potentially, the manuscript aims for the latter, but in my opinion misses to qualify, as the manuscript fails to analyze and discuss important elements. An example is the observed lower INP concentrations at -30 °C than at -25 °C and -20 °C, which does not reflect the consensus of previous studies and may indicate an invalid measurement methodology, thus, should be critically reviewed by the authors. The topic of the paper is well suited for ACP. However, I suggest that the manuscript undergo a major revision to reflect the following comments:
Major comments:
- Please provide more technical information on the design changes. Also, relevant parameters and statistics are missing for an automated near-continuous INP counter. E.g.: how long are the gaps needed to renew the ice layer? What is the percentage of atmospheric measurements within the total time (atmospheric measurements divided by total time including atmospheric measurements, background measurements, cooling, warming, or temperature compensation periods, ice layer renewal, and maintenance)? How does the signal-to-noise ratio change over time (not only qualitatively, but also quantitatively)? What happens with the water needed to form the ice layer and how is it recycled?
- Are there any indications for the lower INP concentrations at -30 °C compared to -20 °C? This does not reflect the consensus of previous studies and may indicate an invalid measurement methodology, thus, should be critically reviewed by the authors.
- Please provide numbers and discuss the implications in more detail. For example, lines 136-138 state that there was little difference in medians or IQR between observations inside and outside clouds or between daytime and nighttime observations, but lack a more detailed discussion, e.g., of what these results mean and what the causes might be when comparing observed patterns of total aerosol number concentrations or other aerosol quantities. Missing discussions on implications are also true throughout the manuscript. Analysis using back trajectories has been done extensively in numerous previous studies. However, new insights remain missing, and thus, the back trajectory analysis can be left out from the manuscript. In addition, the advantage of continuous, high-resolution INP measurements is not exploited as only two events were analyzed.
Specific comments:
Abstract (lines 15-21): a very concise summary. However, it lacks an introductory sentence or two on why measuring atmospheric INP concentrations is relevant. Since the focus of the manuscript is on autonomous INP measurements, more information should be provided on the frequency of site visits required (e.g., 1/week to replace desiccant).
Chapter 2.1 (line 56): please provide the amount of snow in standard international units (mm).
Chapter 2.2 (lines 95-98): please provide measurements or estimations of the transmission fraction of particles <2.5 μm through the sample line and the diffusion dryers until entering the CFDC.
Chapter 2.2 (lines 95-108): I infer that the only supply needed to run the chamber continuously are electric energy, desiccant and nitrogen. How is the water for the ice layer recycled?
Chapter 3.2 (line 136): Please quantify “little difference” for both cases (in cloud vs. out of cloud and night vs. day).
Chapter 3.2 (line 142): Please quantify “No strong correlation” for all cases.
Chapter 3.2 (lines 143-148): Food for thought: Given the large amount of data collected over the four months, more than a qualitative comparison of two periods would have been interesting.
Chapter 3.2 (lines 143-148): Whether it is a qualitative comparison of two periods or a quantitative analysis of the entire four months, the limitations of the used tools must be addressed: what are the limitations of the analysis using back trajectories from a 1-degree GDAS reanalysis, since they are unlikely to fully resolve local features? Please explain the degree of uncertainty in the back trajectories used, e.g., by referring to previous studies where this has been analyzed at SPL.
Chapter 3.2 (lines 151-153): “Other high-elevation free tropospheric INP measurements…” implies, the presented measurements at SPL were sampling free tropospheric air masses. Please provide quantitative evidence for this statement.
Chapter 3.2 (lines 151-156) and chapter 4 (lines 197-198): There are interesting statements within these lines: short-term, high concentration events that were not picked up by previous measurement techniques. Please elaborate on these events. How frequent were they observed? How long did they last? Where there co-located signals in other aerosol parameter such as total number concentration or spikes in aerosol in a specific size bin? Can local pollution be ruled out? To my understanding, such brief events should also be captured during the three times longer sample duration used in, e.g., Lacher et al. (2018) or Brunner et al. (2021). Brunner et al. (2021) also measured continuously for one year, so their measurements should provide near identical temporal resolution. What are other reasons that other studies have missed these short events?
Chapter 3.2 (lines 163-171): As there is much emphasis on surface active site density, I would suggest to show a time series of ns and discuss ns in more detail. E.g., also looking at the number concentration of large particles. Furthermore, the fact that ns for INP at -25 °C and -30 °C are identical is striking and does not align with previous studies. This should be discussed in more detail in addition to the major comment #2.
Chapter 4 (lines 198-199): What are the different transport patterns between this and previous campaigns? Please elaborate in Chapter 3.
Figure 3: Please add the year to the title of the figure.
Figure 4: In panel a, the °-symbol is missing and in panel b, the unit of the temperature categories remains missing. For consistency, I would suggest to add the units to the axis labels (e.g., Temperature category [°C]). Also, “temperature category” form the axis labels is once capitalized and once not. Please use a consistent style.
Figure 5: The data points at -25 °C and -20 °C are shadowed by the data points at -30 °C. I would suggest adding transparency to the markers, such that more information is visible.
Literature:
Brunner, C., Brem, B. T., Collaud Coen, M., Conen, F., Steinbacher, M., Gysel-Beer, M., and Kanji, Z. A.: The diurnal and seasonal variability of ice nucleating particles at the High Altitude Station Jungfraujoch (3580 m a.s.l.), Switzerland, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2021-710, in review, 2021.
Lacher, L., DeMott, P. J., Levin, E. J. T., Suski, K. J., Boose, Y., Zipori, A., Herrmann, E., Bukowiecki, N., Steinbacher, M., Gute, E., Abbatt, J. P. D., Lohmann, U., and Kanji, Z. A.: Background freeâtropospheric ice nucleating particle concentrations at mixedâphase cloud conditions, J. Geophys. Res., 123, 10,506–10,525, 2018.
Citation: https://doi.org/10.5194/acp-2022-29-RC3 - AC1: 'Comment on acp-2022-29', Anna Hodshire, 10 May 2022
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Anna L. Hodshire
Ezra J. T. Levin
A. Gannet Hallar
Christopher N. Rapp
Dan R. Gilchrist
Ian McCubbin
Gavin R. McMeeking
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