the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Spatially-coordinated airborne data and complementary products for aerosol, gas, cloud, and meteorological studies: The NASA ACTIVATE dataset
Mikhail D. Alexandrov
Adam D. Bell
Sharon P. Burton
Megan E. Buzanowicz
Eduard V. Chemyakin
Brian L. Collister
Anthony L. Cook
Andrea F. Corral
Ewan C. Crosbie
Bastiaan van Diedenhoven
Joshua P. DiGangi
Glenn S. Diskin
Marta A. Fenn
Richard A. Ferrare
David van Gilst
Johnathan W. Hair
David B. Harper
Miguel Ricardo A. Hilario
Chris A. Hostetler
Mary M. Kleb
John M. Kusterer
Joseph W. Lee
Richard H. Moore
Kasey E. Phillips
Claire E. Robinson
Amy Jo Scarino
Joseph S. Schlosser
Shane T. Seaman
Taylor J. Shingler
Michael A. Shook
Kenneth A. Sinclair
William L. Smith Jr.
Douglas A. Spangenberg
Snorre A. Stamnes
Kenneth L. Thornhill
Andrzej P. Wasilewski
Edward L. Winstead
Luke D. Ziemba
Abstract. The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol-cloud-meteorology interactions with applications extending from process-based studies to multi-scale model intercomparison and improvement, and remote sensing algorithm assessments and advancements. ACTIVATE used two NASA Langley Research Center aircraft, a HU-25 Falcon and King Air, to conduct systematic and spatially coordinated flights over the northwest Atlantic Ocean amounting to 162 joint flights and 17 other single-aircraft flights between 2020 and 2022 across all seasons. Data cover 574 and 592 cumulative flights hours for the Falcon and King Air, respectively. The HU-25 Falcon flew conducted profiling at different level legs below, in, and just above boundary layer clouds (< 3 km) and obtained in situ measurements of trace gases, aerosol particles, clouds, and atmospheric state parameters. In cloud-free conditions, the Falcon similarly conducted profiling at different level legs within and immediately above the boundary layer. The King Air (the high-flyer) flew at approximately ~9 km conducting remote sensing with a lidar and polarimeter while also launching dropsondes. Collectively, simultaneous data collected from both aircraft help characterize the same vertical column of the atmosphere. In addition to individual instrument files, data from the Falcon aircraft are combined into “merge files” on the publicly available data archive that are created at different time resolutions of interest (e.g., 1, 5, 10, 15, 30, 60 s, or matching an individual data product start and stop times). This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes.
Armin Sorooshian et al.
Status: final response (author comments only)
- RC1: 'Comment on essd-2023-109', Anonymous Referee #1, 19 Apr 2023
RC2: 'Comment on essd-2023-109', Jens Redemann, 25 May 2023
Review Sorooshian et al., essd-2023-109
The paper by Sorooshian et al. provides a guide for the airborne data collected in the ACTIVATE project and its best use. The main issue with data collected in airborne field campaigns is indeed that the use of data is often much easier for the campaign participants. This is because contextual knowledge on data format and known issues are often restricted to the participating science team. The ACTIVATE project in particular, due to its high number of flights hours (almost 600 hrs on each of two aircraft) and hence data volumes, is prone to such challenges. Hence, the concept of the submitted work is very much appreciated and will serve a large community beyond the ACTIVATE team. Admittedly, I struggled with the idea to exclude preliminary scientific findings in ACTIVATE from the discussions of data specifics (i.e., the subject of this paper). However, after reading the paper in its entirety, I understand the purpose of this paper, which I would generally describe as facilitating access to, and scientific use of, ACTIVATE data by a broader community than the ACTIVATE science team.
The ACTIVATE dataset is completely unique and will undoubtedly be the basis for many studies of aerosol-cloud-meteorology interactions in the future. It includes a number of excellent additions relative to previous datasets of similar scope and intent – most notably, I appreciate the creation of a collocation mask (section 5.3), the MERRA-2 reanalysis collocation exercise (section 5.5), the FLEXPART analyses (section 5.6), and the correlative satellite data inclusion (5.7).
The paper is well structured and well-written, and therefore it is easy to read. Figures and Tables are of good quality throughout. The descriptions on data details will save future users tremendous amounts of time, provided that the caveats stated in the paper will be heeded. I have no specific comments, but I include below two overarching requests for additions and a list of technical comments. I consider the authors’ addressing neither the overarching requests nor the minor suggestions as crucial for my acceptance of this manuscript. I would suggest the paper is acceptable for publication with minor revisions, and I will leave it to the authors to choose which of my suggestions to address.
- I am missing in the paper a guide on where to look in the data set to find the most relevant data for addressing the specific ACTIVATE science objectives. Given the vast amounts of data available, this could limit the use of the data if future users would have to hunt for appropriate data to address a specific science objective. Would it be possible to include a general mapping of the ACTIVATE flights (or flight periods) onto the science objectives, maybe something simply indicating the relevance of a flight (or flight period) for addressing the ACTIVATE (or additional) science objectives?
- I think the value of the “statistical survey flight” nature of 90% of the ACTIVATE flights is understated. There have only been a few campaigns that use this concept for a portion of airborne flight campaigns, instead of targeting the largest signals or most interesting atmospheric (hot spot) features. Please include a small discussion in section 2.2 highlighting how novel this approach is, how valuable it is for measuring the probability density distribution of aerosol and cloud properties in a region, and how this traces back to the processes the campaigns are after.
- Line 39: “Falcon flew conducted profiling at different level legs…” – this phrasing is awkward. Profiling at different level legs seems a contradiction in terms. The word “flew” can be struck it seems?!
- Line 43: Mention total number of dropsondes.
- Line 52: The implication that the study of all interactions related to anthropogenic forcing absolutely require airborne measurements seems a stretch.
- Line 59: please specify the targeted seasons.
- Line2 81-86: The wording makes it unclear if these are the original ACTIVATE science objectives. Please clarify.
- Line 86: Please specify the number of flight hours targeted for the threshold and baseline science mission, if possible, and/or state how the number traces to science objectives.
- Line 106: Please comment briefly on impact of deviations on science.
- Line 117: Unclear wording. How does one ascent provide multiple profiles?
- Line 122: Please define conditions of high aircraft coincidence.
- Line 128: Is there a reason to mix units (min and km) for the clear ensembles only?
- Line 139: Please use high-flying aircraft throughout.
- Line 149: I find the nomenclature of L1 and L2 unfortunate, given the remote sensing community's use of the letter L to designate processing levels of remote sensing data.
- Line 179-190: Grammatically, there is a mix of conditions (i + ii) and actions (iii + iv) which reads awkwardly. Also, the bulletized list conflicts with the list one level higher (also i to v).
- Line 191: Awkward phrasing. I suggest replacing “underneath” with "in coordination with".
- Line 195: Suggest tot replace “data” with “instruments”.
- Line 198” I think that we did such unicorn aerosol modules in ORACLES-2016, unless the emphasis is on severe clear sky conditions (in which case you can ignore this comment). The paper by Xu et al. (2021) is a joint lidar-polarimeter retrieval with in situ aircraft validation for such a case. Happy for you to ignore this comment - I do not mean to be petty.
- Line 212: A reference to the Tudor Hill site observations would be helpful.
- Line 254-257: Some information on the availability of the derived lidar products would be helpful (i.e., how often were conditions conducive for deriving these products), maybe as percentage of the availability of primary data.
- Line 411: Practically, where do readers find instrument team contact information? This info is not provided in Tables 3 or 5.
- Line 509: Please include a recommendation for how to approximate total ambient extinction from the 2021-2022 flights when the scattering coefficients and f(RH) were observed for submicron aerosol only.
- Line 532: If the results in Figure 7 are representative of the closure in CN, please provide the closure results for Figure 7d in statistical formats (i.e., fit equation, bias error, mean absolute error), as those will be useful to estimate the expected accuracy of the CN measurements. A reference back to (comparison with) the uncertainty stated in Table 5 would be great.
- Line 540: Please add a description of the SS scanning pattern and/or the general approach for cycling through the SS range.
- Line 574: see also comment 20) above: Please discuss the impact of calculating total extinction in this way (i.e., by combining submicron scattering and total absorption).
- Line 577: I think you should clarify that these are only ambient values if absorption humidification is equal to unity.
- Line 594-595: Awkward phrasing to me.
- Line 639: Please replace “generated” with “generate”.
- Line 652: Particle shapes would affect calibrations as well.
- Line 654: Please add “particle” before “size”.
- Line 708: Please discuss the latest version of merge files and whether they should be considered "final". Until what time should users expect updates to merge files based on updates of individual instrument files?
- Line 722: I think that the parenthetical comment should be moved to end of sentence.
- Line 726: Maybe refer back to Fig. 2 to remind reader of acronyms?
- Line 757: Do you mean above the aircraft or do you mean in the direct beam towards the sun? From the rest of the paragraph it seems you are talking about the latter? If so, please change this wording.
- Entire section 5.7: After reading this subsection, I am mildly confused about the resolution of the various satellite products as they are included in these contextual files. The first part of the section speaks to L3 (1x1 deg data), while later on in the section full resolution data is discussed. Could you please state clearly at the beginning of the section which resolutions are included and what the intended use of the gridded vs. native resolution data is? The info is all there I think, it is just presented in a slightly confusing order (to me).
- Section 6: I am unclear about the exact motivation for highlighting this particular flight. The first sentence indicates that this flight was representative of the majority of flights, while latter discussion paints the picture of a "golden day". Is it really both? To be clear, I appreciated the discussion, I would like to just understand better whether or not to think of this as a canonical ACTIVATE flight or a special flight when science objectives were particularly well met.
- Line 884: I suggest to replace “without” with “no”.
- Figure 1: Maybe use slightly thinner lines for flight tracks? They appear as a bit of a blob of lines.
Armin Sorooshian et al.
Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment ACTIVATE Science Team https://doi.org/10.5067/SUBORBITAL/ACTIVATE/DATA001
Armin Sorooshian et al.
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The paper by Sorooshian et al. describes the datasets associated with the ACTIVATE field campaign. The description is very thorough including the flights, measurement techniques and additional derived products that greatly support the usage of the data for answering science questions. One minor comments if that it would be great if authors could add a section on summary of science results available so far or to come leading to answering the science questions of the investigation. Additional by line comments below
Comments by Line
Introduction: It would be good to summarize other field campaigns performed in the region that had some similarities (for instance, DoE’s Two-Column Aerosol Project, maybe IMPACTS too) and also mention other aerosol-cloud focused field campaigns performed in other regions to provide context on where this campaign fits
Table 2. Associated to this table, it would be nice to have a visual reference of the flight track and cloud conditions for each flight to allow looking for flights by visual inspection. For this purpose a multi-panel Figure could be added to the Appendix with the flight track over a representative visible image for that day
Section 3.4. Is N_a the only variable planned to be derived jointly? If there are others please list them, including the ones that are improvements over the ones measured by each instrument individually.
809-810. Can you describe a bit more how the residence time is computed and plotted? I think I understand Fig 8b (for a given time, see what fraction of particles are at what height) but Fig 8a is a bit more confusing as it seems to be mixing multiple times
Table 2. Some sentences seem to be cutoff on the “Special notes” columns (e.g., for RF 5).