the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 06 Oct 2023
Intercomparison of Fast airborne Ozone Instruments to measure Eddy Covariance Fluxes: Spatial variability in deposition at the ocean surface and evidence for cloud processing
Randall Chiu
Florian Obersteiner
Alessandro Franchin
Teresa Campos
Adriana Bailey
Christopher Webster
Andreas Zahn
Rainer Volkamer
Abstract. The air-sea exchange of ozone is controlled by chemistry involving halogens, dissolved organic carbon and sulfur in the sea surface microlayer. Calculations also indicate faster ozone photolysis at aqueous surfaces, but the role of clouds as ozone sink is currently not well established. Fast response ozone sensors offer opportunities to measure eddy covariance (EC) ozone fluxes in the marine boundary layer. However, intercomparisons of fast airborne O3 sensors, and EC O3 fluxes measured on aircraft have not been conducted before. In April 2022, the TI3GER (Technical Innovation Into Iodine and GV aircraft Environmental Research) field campaign deployed three fast ozone sensors (gas chemiluminescence and a combination of UV absorption with coumarin chemiluminescence detection, CID) together with a fast water vapor sensor and anemometer to study iodine chemistry in the troposphere and stratosphere over Colorado and over the Pacific Ocean near Hawaii and Alaska. Here, we present an instrument comparison between the NCAR Fast O3 instrument (FO3, gas-phase CID) and two KIT Fast AIRborne Ozone instruments (FAIRO, UV absorption and coumarin CID). The sensors have comparable precision <0.4 % Hz-0.5 (0.15 ppbv Hz-0.5), and ozone volume mixing ratios (vmr) generally agreed within 2 % over a wide range of environmental conditions: 10 < O3 < 1000 ppbv; below detection < NOx < 7 ppbv; and 2 ppmv < H2O < 4 % VMR. Both instrument designs are demonstrated to be suitable for EC flux measurements and were able to detect O3 fluxes with exchange velocities (defined as positive for upward) as slow as -0.010 ± 0.004 cm s-1, which is in the lower range of previously reported measurements. Additionally, we present two case studies: one in which the direction of ozone and water vapor fluxes were reversed (vO3 = +0.134 ± 0.005 cm s-1), suggesting that overhead evaporating clouds could be a strong ozone sink; and another in which ozone fluxes vO3 are negative (varying by a factor of 6–10 from -0.036 ± 0.006 to -0.003 ± 0.004 cm s-1), while the water vapor fluxes are consistently positive due to evaporation from the ocean surface and spatially homogeneous. Future work is needed to better understand the role of clouds as a possibly widespread sink of ozone in the remote marine boundary layer, and to elucidate possible drivers (physical, chemical, or biological) of the variability in ozone exchange velocities on fine spatial scales (~20 km) over remote oceans.
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Randall Chiu et al.
Status: open (extended)
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RC1: 'Comment on amt-2023-198', Anonymous Referee #1, 16 Nov 2023
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Overview:
Chiu et al. present a comparison of airborne measurements of ozone mixing ratios and vertical fluxes in the marine boundary layer from three different fast ozone sensors recently deployed on a GV aircraft. Measurements from the three instruments were shown to compare well and overall flux uncertainty was assessed from mean and deviation of the three flux measurements which is a useful addition to understanding of ozone flux uncertainties. The authors also present a modified flux limit-of-detection method building on the cross-covariance method of Langford et al. (2015) but with refinement of the time scales which is a nice addition. Finally the authors present some case studies to demonstrate the utility of the observed ozone exchange velocities which potentially imply reactions on cloud droplets as a sink of ozone and spatial variability in ozone deposition to the ozone surface on small spatial scales. My two broad comments are 1.) that while the measurements seem to be of a high quality, some relevant details of the flight campaign and data processing are lacking in places (see specific comments below), and 2.) that the analysis of the case studies are underdeveloped and conclusions of cloud loss and spatial heterogeneity are need more support if they are to be included. I appreciate that these case study results are not the primary focus of this methods paper, but the authors are still making conclusions about ozone loss to clouds that I believe need more support. Some specific comments on this are included in the major comments below. Overall the comparison of the airborne ozone measurements is novel and valuable and is suitable for AMT with some revision. The interpretation of the case studies seem reasonable but require additional information in order to support the conclusions of the authors. If the above points are addressed then this work will likely be a useful contribution to AMT.
Major Comments:
Line 96: Some additional discussion of the EC flux leg design is needed in the main text, not just table S1. What were the lengths of these flux legs? What is the airspeed of the aircraft? Were stacked legs flown at multiple altitudes in the same location? Were vertical profiles out of the boundary layer performed to constrain the potential entrainment term?
Relatedly, basic details of the eddy covariance data processing and quality control are missing. For example, was there a stationarity criteria applied to the flux data, what is the impact of high pass attenuation for the closed path sensors and was a correction applied. What are the random and systematic turbulent sampling errors (Lenschow et al. 1994, https://doi.org/10.1175/1520-0426(1994)011%3C0661:HLILEW%3E2.0.CO;2) ? These types of details are needed for a proper evaluation of the methods and results presented.
Line 255: The large time desynchronization mid-flight mentioned around line 255 even after applying the manual synchronization method is concerning. Inlet flow would have to vary strongly as a function with altitude or clock drift would seemingly have to be non-linear to describe this behavior. Were either of the inlets for the ozone instruments pressure and or mass flow controlled? What implications are there for systematic flux uncertainty if flow rate changed significantly as a function of altitude?
Figure 5. Some additional analysis of the spectral response would be appreciated in the SI. Generally it would be useful to validate that there is no significant high-frequency attenuation for the ozone instruments and comment on any attenuation corrections applied.
Section 3.5: My primary comment on the manuscript relates to this section as a whole. There are limited conclusions that you can draw from an eddy covariance flux measurement at a specific altitude in isolation. Interpreting the measured flux values to infer source or sink terms requires some knowledge of the vertical profile of (here) ozone mixing ratios and fluxes. The magnitude of the surface deposition and the entrainment flux at the top of the boundary layer influence what the measured flux magnitude (and direction) will be at some altitude in the boundary layer in addition to chemical source and sink terms at the measurement altitude. The O3 vertical profile shown in Figure 6 shows lower O3 mixing ratios aloft then a weak turnover at ~1200 m, however it is not clear what the boundary layer top is and what the profile is above that. While the measured ozone flux could be indicative of loss on evaporating cloud droplets, there may be contributions from entrainment of ozone depleted air from the free troposphere into the boundary layer. At a minimum some marking of the boundary layer height, ozone mixing ratios above the boundary layer, and the cloud depth would be quite useful on this figure. More generally I encourage you to present these results as vertical flux divergence figures ( see Wolfe et. al. (2015) (https://doi.org/10.1002/2015GL065839) and Conley et. al. (2011) for examples). Some estimate of entrainment velocities in the clear sky case could also be useful both as a valuable result in their own right, but also to aid in interpretation of the cloud loss argument (see Faloona et al., https://doi.org/10.1175/JAS3541.1)
Similarly for Fig 7 and the related discussion, I agree that the observed variability in measured O3 exchange velocity is not due to turbulence and reflects some variability in the oceanic or atmospheric chemical state. However you do have at least some additional information that can be used to constrain this observed behavior. Are O3 mixing ratios changing significantly across the flux segments? How do the vertical profiles and the beginning and end of this segment compare?
Overall, I don’t think the interpretations suggested by the authors are unreasonable, however they should be presented in a more comprehensive way with more relevant constraints.
Minor Comments:
Line 36: The implications of the observed high variability of v(O3) should be made more explicit in the abstract.
Line 61: Much is made of the rarity of comparison studies of ozone flux but there is no motivation for specific knowledge gaps that such comparisons can provide. To my knowledge there has not been much suggestion in the literature that instrument uncertainty is a major driver of overall uncertainty in parameterizing ozone deposition. Some synthesis of the literature and implications from previous comparison studies would be welcome here to motivate this study.
Line 70: Hannun et al. (https://doi.org/10.5194/amt-13-6877-2020) presented airborne EC flux results over the ocean and a comparison of mixing ratio measurements from a new broadband cavity-enhanced UV absorption instrument with an NO chemiluminescence instrument on the NASA DC-8 aircraft during the FIREX-AQ campaign.
Line 109: An estimate of the total volumetric inlet residence time would be useful. Same for the FAIRO instruments.
Line 170: How many of these anticorrelation synchronization anchors do you generally get in a flight? Do you use events at all altitudes or only ones at low altitudes relevant for the flux sampling conditions.
Figure 5: What is driving the shift in the cospectra toward higher frequencies on RF6 and the rapid fall off in spectral power at frequencies below 0.1 Hz? Could be due to the detrending method or due to real atmospheric turbulent structure. Analysis of the vertical wind power spectra would help clarify.
Relatedly at Line 226, it is not clear that a fixed detrending window of 10 s is appropriate when boundary layer height and cloudiness and thus convective strength are varying between flux legs. Some additional justification would be useful.
Line 318: Filtering out low signal to noise flux measurements does not seem totally appropriate. These measurements provide real information on the flux magnitude (e.g. that they are below the LOD). Excluding those values from an average of the ozone flux would artificially bias the magnitude low, much like excluding below LOD gas phase mixing ratio measurements would add a high bias to the mean. This is of minor importance in this paper since flux results are mostly considered in the context of case studies from single flux legs, but I want to raise this as a general point in the data interpretation.
Line 363: How are the “relatively smooth areas of cross-correlation near the candidate peak” identified?
Technical Comments:
Line 143: Give inlet diameter in cm or mm instead of inches.
Citation: https://doi.org/10.5194/amt-2023-198-RC1
Randall Chiu et al.
Randall Chiu et al.
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