the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 01 Jul 2024
Observations of high time-resolution and size-resolved aerosol chemical composition and microphyscis in the central Arctic: implications for climate-relevant particle properties
Abstract. Aerosols play a critical role in the Arctic’s radiative balance, influencing solar radiation and cloud formation based on their physicochemical properties (e.g., size, abundance, and chemical composition). Limited observations in the central Arctic leave gaps in understanding aerosol dynamics year-round, affecting model predictions of climate-relevant properties. Here, we present the first annual high-time resolution observations of submicron aerosol chemical composition in the central Arctic during the Arctic Ocean 2018 (AO2018) and the 2019–2020 Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expeditions. Seasonal variations in aerosol mass concentrations and chemical composition were found to be driven by typical Arctic seasonal regimes. Organic aerosols dominated the pristine summer, while anthropogenic sulfate prevailed in autumn and spring under Arctic haze conditions. Ammonium, which impacts aerosol acidity, was consistently less abundant, relative to sulfate, in the central Arctic compared to lower latitudes of the Arctic. Cyclonic (storm) activity was found to have a significant influence on aerosol variability by enhancing both emission from local sources and transport of remote aerosol, with locally wind-generated particles contributing up to 80 % (20 %) of the cloud condensation nuclei population in autumn (spring). While the analysis presented herein provides the current central Arctic aerosol baseline, which will serve to improve climate model predictions in the region, it also underscores the importance of integrating short-timescale processes, such as seasonal wind-driven aerosol sources from blowing snow and open leads/ocean in model simulations, especially in light of the declining mid-latitude anthropogenic emissions influence and the increasing local anthropogenic emissions.
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RC1: 'Comment on egusphere-2024-1912', Anonymous Referee #1, 22 Jul 2024
Review to "Observations of high time-resolution and size-resolved aerosol chemical composition and microphysics in the central Arctic: implications for climate-relevant particle properties" by Heutte et al.
The manuscript by Heutte et al. presents an annual cycle of aerosol data (number, size, composition) from the central Arctic. Data from two field projects, from August to September 2018 and from October 2019 to September 2020 are combined to obtain an annual cycle. The chemical composition data were obtained using a HR-ToF-AMS, for which a data gaps from January until February 2020 exists. Black carbon was measured using an aethalometer and a MAAP. Size distributions were measured using an SMPS system. Local contamination (exhaust from the research vessel) was identified and removed from the analysis.
Due to the logistical difficulty to obtain such data (such data can only be measured on icebreakers moored on ice floes or frozen in pack ice), such data from the central Arctic a scarce and are therefore very valuable.
The manuscript first presents the chemical composition of the aerosol during the annual cycle. Relative composition for four different time periods as well as the monthly seasonality is shown. Several case study of storm events are discussed in more detail. The influence of long-range transported particles and of blown snow and sea spray on CCN is discussed. The variation of the size distributions between different seasons is analysed by means of clustering of the SMPS size distributions. Size-resolved chemical composition (AMS) is also presented.
Overall, the manuscript is very descriptive. The measured data are presented in great detail, but often in a repetitive way, as for example in the case of the storm events. The main new finding is that wind-generated and blowing snow-generated particles contribute significantly to the CCN number, comparable to haze particles.
However, as said above, the data are very valuable such that I recommend publication.
The authors should consider to shorten the individual case descriptions in 3.2.
General comments:
The fact that the comparison between AMS and SMPS (MOSAiC only) yielded markedly different results is problematic. However, I think the approach of Heutte et al. (2023b) to use scaling factors to match AMS and SMPS volume are justified, but induces an additional uncertainty to the data.
Specific comments:
Lines 110 ff: Do Amines (e.g., TMA) play a role as well?
Line 193: floe instead of flow?
Line 250: PSL were not used for size calibration?
Line 259-260: I don't think that estimating the mode of a size distribution "by eye" is a justified method. Looking at the data in Fig 8 b) and Fig S12 b), I would think that a lognaormal fit should be able to find the maximum when the starting conditions are set properly.
Line 322-334: How many data points (what percentage of the measuring period) was excluded due to pollution?
Line 364, Fig 2 and Fig 3: Please mark in Figs 2 and 3 the five distinct periods. Also, please note in caption of Fig 2 that one of the five distinct periods does not include AMS data and therefore is not represented with a pie chart in Fig 2.
Figure 3: I suggest to clearly mark the period Dec 2029-Feb 2020 with "no AMS data available" or "AMS not operational".
Line 400, 435, 522 (and maybe elsewhere): In a sentence without the other AMS species, I would prefer "organics" over "Org"
Line 572 (and chapter 2): How were the supermicron particles N>1000nm measured? If I didn't miss it, this quantity appears here for the first time.
Line 632ff: the measurements took place at ground level. Are the supermicron particles transported upwards to cloud level efficiently enough to play a role as CCN?
line 853ff + Fig 8: To reduce the noise of the AMS size distribution, one can reduce the number of bins.
Table S3: The coarse mode of the organics is likely cut off by the lens transmission. Thus, the estimated mode diameter (Table S3) for the organic coarse mode is not representative for the ambient size distribution.
Citation: https://doi.org/10.5194/egusphere-2024-1912-RC1 -
RC2: 'Comment on egusphere-2024-1912', Anonymous Referee #2, 19 Aug 2024
Based on year-long, chemically-speciated, and size-resolved PM1 measurements during two expeditions using HR-ToF-AMS and collocated instruments, the manuscript titled "Observations of high time-resolution and size-resolved aerosol chemical composition and microphysics in the central Arctic: implications for climate-relevant particle properties" by Heutte et al. presents detailed measurements of aerosol properties in the central Arctic. The comprehensive analysis reveals clear seasonality in PM1 mass concentration, chemical composition, microphysical properties, and sources, driven by typical Arctic seasonal regimes. Specifically, PM1 concentrations were lowest in summer, dominated by organic aerosols, while autumn and winter saw elevated concentrations with anthropogenic sulfate as the dominant species. The study highlights the significant role of cyclonic activity in influencing aerosol variability, where wind-generated particles contribute substantially to the CCN population, particularly in autumn. The long-range transport of anthropogenic emissions from lower latitudes also plays an important but smaller role in elevating the PM1 level in central Arctic. By comparing with observations from a set of pan-Arctic land-based stations, this study pointed out that ammonium in central Arctic appeared to be far less abundant than at lower latitudes, with potential implications in terms of aerosols’ acidity. The findings provide a baseline for central Arctic aerosol characteristics, which are crucial for improving climate model predictions.
General comments:
- This study presents a comprehensive analysis of aerosol measurements in the central Arctic, overcoming significant technical challenges associated with conducting such research in remote environments. I recommend publishing this manuscript. However, given its primary focus on measurements, it may be more appropriate to publish it as a measurement report.
- While the detailed and informative results are valuable, the manuscript is somewhat lengthy and contains some repetitive information. I suggest streamlining the content to enhance clarity and conciseness. Below are a few examples of sections that could be shortened:
P12, L351-363: The caption of Figure 2 already provides detailed information, making this paragraph somewhat repetitive and overly lengthy.
P18, L481-497: Is there a compelling reason to further divide summer into "summer" and "late summer"? Given that the PM1 chemical composition remains similar, the same HR-ToF-AMS was used, and there are no significant variations in chemical composition over years, this separation seems unnecessary. Additionally, these two periods are combined in the conclusions, so it may be more consistent not to separate them initially.
P26-P28, L697-753: While it’s important to assess whether storm-induced high concentration events observed in autumn were also present in spring (when background particle concentrations were higher during the haze) and whether their implications are comparable, instead of giving detailed case studies in spring, it might be more effective to summarize the main conclusions for spring and highlight the most significant differences, and maybe move the details to the supplementary.
Some other minor comments:
- P11, L329-331: It is unclear here if any quantitative criteria were used to assess the similarity between the AMS-measured chemical spectrum and fresh hydrocarbon emissions. Additionally, the specific fresh hydrocarbon emission profile being referenced is not clearly defined. While comparing with fresh hydrocarbon emission profiles can help identify pollution periods influenced solely by fossil fuel combustion, how are periods where fossil fuel combustion is mixed with other sources addressed if PMF analysis were not performed yet? The bulk OA profile may differ from pure fossil fuel emissions during these mixed periods, potentially making this approach less effective in excluding all local emissions from research activities. In this context, is it appropriate to label the filtered data as “unpolluted”? Besides fossil fuel combustion, are there other potential impacts from research activities, such as cooking emissions?
- P13, L367-368: Given that the MOCCHA data covers only August to September and is defined as late summer, would it be more accurate to state, “Furthermore, we argue that the MOCCHA data from summer 2018 can be considered representative of the central Arctic Ocean late summer conditions”?
- P13, Figure 2: Would it be clearer to indicate the absence of AMS data between December 2019 and March 2020 by creating a larger gap between the pie charts for Oct-Dec and Mar-May, accompanied by a note such as ‘Data not available’?
- P13, L371: There is inconsistency on the abbreviation of black carbon, alternating between eBC and BC.
- P15, L395: Are there any quantitative results showing the significance of the temperature drop in October?
- P17, L449: It’s unclear how the background periods/concentrations were defined. Were clean periods, in the absence of pollution, identified as background periods? What are the background concentration levels in other seasons? Or, does the term "background PM1 concentration" refer to the monthly median PM1 concentration? If so, I question whether it’s appropriate to refer to this as the background concentration.
- P17, L461-463: Is there any trajectory analysis that supports this conclusion?
- P19, L523-524: Why was only the SO4 sink enhanced, and not Org, if they were transported together? Could it be that Org has stronger local emissions or formation?
- P23, L626-627: What could be the reason for the elevated background before the second storm case? Is it still valid to treat this elevated period as a background period?
- P28, L758: It is unclear why these two periods were selected. Could you provide brief context or justification?
Citation: https://doi.org/10.5194/egusphere-2024-1912-RC2 -
RC3: 'Comment on egusphere-2024-1912', Anonymous Referee #3, 30 Aug 2024
Heutte et al. present results from the MOCCA and MOSAiC ship-cruises, aiming a year-long measurement of the physicochemical properties of ambient aerosol in the central Arctic. The authors deployed high-resolution time-of-flight aerosol mass spectrometry (HR-ToF-AMS) to analyze the bulk aerosol chemical composition. Further, particle size distribution measurements were conducted and discussed together with the chemical analysis. The authors showed that the seasonal evolution of the aerosol composition is in line with earlier findings from pan-Arctic land-based measurements. Interestingly, ammonium concentrations in the central Arctic were far below measured concentrations at lower latitude land-based stations with potential implication on particle acidity. Individual events were selected to demonstrate the influence of long-range transport, blowing snow etc. on aerosol physicochemical characteristics in autumn and summer. Indeed, spring and autumn composition are largely influenced by such short-term events like wind-driven blowing snow events and synoptically-driven long-range transport.
This work is important for our better understanding of the seasonality in Arctic aerosol. And I highly appreciate the effort of obtaining this data set with all known challenges and technical complexities, especially in the harsh remote environment. The study is in line with the aims and scopes of the journal. Concerns and suggestions (including major issues) are described below.
During revision, the authors should work to improve the writing. There are a few “paragraphs” that consist of 1-3 sentences each and as such do not represent full paragraphs with fully developed thoughts. Please consider to incorporate these sentences into longer paragraphs. A few examples:
- Lines 71-77
- Lines 116-119
- Lines 186-190
- Lines 202-205
- Lines 476-480
- Lines 693-696
There are many sentences that are far too long and as such reduce readability. Please shorten here and/or separate in two or more sentences. A few examples:
- Lines 38-41
- Lines 41-45
- Lines 156-160
- Lines 252-255
- Lines 361-364
- Lines 437-440
- Lines 443-446
- Lines 451-455
- Lines 476-480
- Lines 535-538
- Lines 802-806
Further, the manuscript is very lengthy and partly repetitive. Please re-consider if you can shorten or summarize some paragraphs (some suggestions are listed below). The readability of the manuscript would further benefit from removing redundant sub-clauses, fillers, details in parentheses etc. (some of which are listed below).
Major comments:
- 3.1.1, Sect. 3.1.5, and lines 880 ff: What about methanesulfonic acid (MSA)? As MSA plays a major role for the sulfur content in Arctic summer, you should consider looking into the detection of MSA with the HR-ToF-AMS. The publication by Zorn et al. (2008) provides information on how to extract mass concentration for MSA from HR-ToF-AMS field measurements. Further, you might can use the MSA-to-sulfate as well as the Org-to-sulfate ratios to better discriminate the contribution from anthropogenic and marine sources to particulate sulfur and organics (see Willis et al. (2017)). Along with your large distance to the open ocean, it is highly interesting to see if MSA and marine-biogenic organics still play a role.
- 3.1.1: Can you explain the enhanced nitrate signal in August and September compared to June and July (Sect. 3.1.5)? In particular, which form of nitrates was observed here – organic nitrates or ammonium nitrate? The latter one plays obviously a minor role with regard to the very low ammonium mass concentration. It would be worth to check the presence of organic nitrates with the HR-ToF-AMS data.
- Sect 3.1.2: Similar to the comment above - Which form of nitrates do you observed here in October to December? Ammonium is not available (below DL)– please consider the presence of organic nitrates.
- 3.2 and Lines 880 ff: Is it correct that aerosol particles were also collected and subsequently analyzed by offline-techniques (by Pratt et al.)? As your results on the abundance of sea spray in spring and autumn provide an important part of your manuscript, your analysis could benefit from such additional evidence by aerosol off-line techniques. You can obtain more information on mixing states (internal mixing with organics?), size and maybe even mass.
Minor comments:
- Your abstract would generally benefit from a few more sentences elucidating your main results. For example, I suggest to add a sentence on the comparison between your central Arctic ship-based measurements and the pan-Arctic land-based observations like it was discussed in Sect. 3.1.6 and in lines 914 ff. Another example, I think your results on enhanced BC from blowing snow and sublimation is important and should be mentioned in the abstract.
- Line 39: “emissions” instead of “emission”
- Line 86: Do you mean “aged organics” instead of “aged sulfate”?
- Lines 91-94: Please re-formulate this sentence. Suggestion: “There are a few key mechanisms that control particle activation potential, for example, atmospheric aging […]”
- Lines 103-107: Please re-formulate this sentence. Suggestion: “This is associated with […]. As a result, the summertime Arctic (June-August) is characterized […].”
- Lines 106-109: Please re-formulate as there are too many “and”, “or” and commas that reduce readability.
- Lines 106-114: Please also check references from the aircraft-based mission NETCARE in summer 2014. As for example: Willis et al. (2016), Willis et al. (2017), and Koellner et al. (2021).
- Line 134: Please re-formulate: ”[…] and an observation bias in the central Arctic summer.”
- Your introduction could benefit from a few sentences elaborating the representativeness of your ship-based measurements (or more general ground-based measurements in the boundary layer) compared to the aerosol vertical column with respect to low inversions, influence of low-level clouds etc. (see references Willis et al. (2019), Schulz et al. (2019), and Köllner et al. (2021)).
- Line 182: Do you mean “These two expeditions were set up to […]” instead of “[…] set out to […]”?
- Line 183: Remove “driving” – redundant.
- Lines 193-194: Remove “To provide context into the sea ice extent during that year,” – redundant.
- Lines 195-196: Please re-formulate: “Polarstern was in general […], except for the drift […].”
- Line 240: Remove “(A.M.)” – redundant as it is mentioned above. Please check throughout the manuscript.
- Lines 257-258: Remove “Therefore, this does not […] for example.” – redundant.
- Lines 358-359: Please re-formulate. Suggestion: “Figure 3 shows the annual cycle of each species with monthly statistics.”
- Your discussion would generally benefit from a few sentences describing how representative was your measurement period (MOCCHA and MOSAiC) compared to the climatological mean.
- Figure 3 caption last line: Do you mean “[…] not reported for December 2019 until February 2020 and July 2020 […]”?
- Line 410: Please change “contribution of sea salt in the autumn aerosol budget” to “contribution of sea salt to the aerosol budget in autumn”.
- 3.1.5: I suggest to discuss Sect. 3.1.5 and 3.1.1 together. I understand the separation between MOSAiC and MOCCHA data. However, the results and discussion are comparable. This would largely shorten the manuscript.
- Lines 489-490: Please remove “(i.e. change […])”- redundant.
- Line 416: Remove “also”.
- 3.1.2- 3.1.4: I miss a discussion on the abundance and sources of BC. Especially, for spring, I think BC is an important player for the Arctic haze period. I suggest to add a few more sentences on the abundance and sources of BC during your measurements.
- Line 465: Do you really mean “lower stratosphere”? To my knowledge, both references (Fisher et al. (2011) and Willis et al. (2019)) do not focus on the stratosphere. The authors show the contrast in acidity between the boundary layer and the free troposphere.
- 3.1.6 and Fig. 4: I do not understand why the authors have chosen variable time periods for averaging across the stations? And isn’t it more appropriate to select pan-Arctic measurements only for the sampling period of MOCCA and MOSAiC for comparison reasons?
- 4a bottom (nitrate): It is difficult to identify any trend or comparison with the station as the range of y-axis is too large. Please adjust it.
- Lines 523-524: I do not understand your hypothesis. Why should have sulfate and organics different sink processes if they have the same origin and transport way? Isn’t it more feasible that different sources can explain the discrepancy? Anyhow, this is very speculative if you have no evidence (trajectories, modelling etc.).
- Line 530: This paragraph is in general very long. I suggest to start here a new paragraph with the topic of “ammonium in the central Arctic”.
- Line 532: This is a very important result!
- Lines 538-540: Please consider if it is really necessary to show Fig. 4b if you discuss this subfigure with only one sentence.
- 3.2: Can you explain the reasons for selecting particularly these four events/case studies?
- Lines 522-523: I cannot find the answer to the question “How often do we observe significant …?” in Sect. 3.2. I guess the answer is given in Sect. 3.3. Please re-structure or re-formulate this.
- Sects 3.2.1 and 3.2.2: Please re-consider if it necessary to discuss “spring” and “autumn” events separately as results and implications are comparable. It would probably shorten the paper if you discuss it in a more compact way and leave details for the reader in the Supplement.
- 5/6: Change “expect” to “except”. The blue tones for nitrate and NaCl are difficult to differentiate. Please consider if it is necessary to show both “LF” parameters in (a) and (b) – redundant?
- Lines 591 ff: This paragraph would benefit from a topic sentence stating the main message of this paragraph.
- Line 591: In general, how did you define you background periods?
- Lines 601-603: Please shorten this sentence. Suggestion: ”[…] by a factor of 4 to 7 depending on the SS levels.”
- Line 693-694: Please re-formulate. Suggestion: “Overall, CCN number concentrations are influenced by both wind-driven local aerosol production from blowing snow and SSA as well as from long-range transported aerosol under cyclonic conditions. Yet, the latter process plays a minor role.”
- Line 700: Remove “logically” – redundant.
- Line 711 and others: Is it really necessary to indicate the coefficients in parenthesis? I suggest to remove these details from the main text as it limits readability.
- Line 754: I suggest to state “[…] during spring and autumn” instead of “transitions seasons”.
- Line 791: I suggest to start here a new paragraph for better readability.
- Line 792: Remove “more” -redundant.
- Line 795-797: The comparisons are incomplete as written.
- Line 797: I guess it is possible to check the transport time scales with your trajectory analysis. Any indications?
- Line 829: Remove “were”.
- Line 830: I suggest to start here a new paragraph for better readability.
- Line 886: What is meant by “That is,”?
- Line 932: Remove the details in parenthesis.
References:
Zorn, S. R., et al.: Characterization of the South Atlantic marine boundary layer aerosol using an aerodyne aerosol mass spectrometer, Atmos. Chem. Phys., 8, 4711–4728, https://doi.org/10.5194/acp-8-4711-2008, 2008.
Willis, M. D., et al.: Evidence for marine biogenic influence on summertime Arctic aerosol, Geophys. Res. Lett., 44, 6460–6470, doi:10.1002/2017GL073359, 2017.
Willis, M. D., et al.: Growth of nucleation mode particles in the summertime Arctic: a case study, Atmos. Chem. Phys., 16, 7663–7679, https://doi.org/10.5194/acp-16-7663-2016, 2016.
Köllner, F., et al.: Chemical composition and source attribution of sub-micrometre aerosol particles in the summertime Arctic lower troposphere, Atmos. Chem. Phys., 21, 6509–6539, https://doi.org/10.5194/acp-21-6509-2021, 2021.
Willis, M. D., et al.: Aircraft-based measurements of High Arctic springtime aerosol show evidence for vertically varying sources, transport and composition, Atmos. Chem. Phys., 19, 57–76, https://doi.org/10.5194/acp-19-57-2019, 2019.
Schulz, H., et al.: High Arctic aircraft measurements characterising black carbon vertical variability in spring and summer, Atmos. Chem. Phys., 19, 2361–2384, https://doi.org/10.5194/acp-19-2361-2019, 2019.
Citation: https://doi.org/10.5194/egusphere-2024-1912-RC3 - AC1: 'Comment on egusphere-2024-1912', Benjamin Heutte, 09 Oct 2024
Data sets
Aerosol chemical composition during the Arctic Ocean 2018 expedition Lubna Dada, Julia Schmale, Kaspar Daellenbach, and Andrea Baccarini https://doi.org/10.17043/oden-ao-2018-aerosol-ams-1
Equivalent black carbon concentration measured with an aethalometer AE33 during the Arctic Ocean 2018 expedition Benjamin Heutte, Andrea Baccarini, Paul Zieger, and Julia Schmale https://doi.org/10.17043/oden-ao-2018-aerosol-ebc-ae33-1
Size distribution of interstitial and total particles between 18 and 660 nm collected during the Arctic Ocean 2018 expedition Andrea Baccarini and Julia Schmale https://doi.org/10.17043/oden-ao-2018-aerosol-smps-1
Bulk size-resolved chemical composition and mass concentration of non-refractory submicron aerosols measured in the Swiss container during MOSAiC 2019/2020 Benjamin Heutte, Lubna Dada, Hélène Angot, Kaspar R. Daellenbach, Imad El Haddad, Ivo Beck, Lauriane Quéléver, Tuija Jokinen, Tiia Laurila, and Julia Schmale https://doi.org/10.1594/PANGAEA.961009
Equivalent black carbon concentration in 10 minutes time resolution, measured in the Swiss container during MOSAiC 2019/2020 Benjamin Heutte, Ivo Beck, Lauriane Quéléver, Tuija Jokinen, Tiia Laurial, Lubna Dada, and Julia Schmale https://doi.org/10.1594/PANGAEA.952251
AOS: Scanning-Mobility Particle Sizer Kuang et al. https://doi.org/10.5439/1476898
Aerodynamic Particle Sizer spectrometer (APS) aerosol number concentrations, measured in the Swiss container during MOSAiC 2019/2020 Nora Bergner, Ivo Beck, Lauriane Quéléver, Tuija Jokinen, Tiia Laurila, Lubna Dada, and Julia Schmale https://doi.org/10.1594/PANGAEA.960923
Cloud Condensation Nuclei (CCN) concentrations measured in the Swiss container during MOSAiC 2019/2020 Nora Bergner, Benjamin Heutte, Hélène Angot, Lubna Dada, Ivo Beck, Lauriane Quéléver, Tuija Jokinen, Tiia Laurial, and Julia Schmale https://doi.org/10.1594/PANGAEA.961131
Carbon dioxide dry air mole fractions measured during MOSAiC 2019/2020 Hélène Angot, Byron Blomquist, Dean Howard, Stephen Archer, Ludovic Bariteau, Ivo Beck, Detlev Helmig, Jacques Hueber, Hans-Werner Jacobi, Tuija Jokinen, Xin Lan, Tiia Laurila, Monica Madronich, Kevin Posman, Lauriane Quéléver, and Julia Schmale https://doi.org/10.1594/PANGAEA.944272
AOS: ambient nephelometer measurements, with calibrations applied at b1-level and above Koontz et al. https://doi.org/10.5439/1228051
Atmospheric snow particle flux in the Central Arctic during MOSAiC 2019-20 M. Frey, D. Wagner, A. Kirchgaessner, T. Uttal, and M. Shupe https://doi.org/10.5285/7d8e401b-2c75-4ee4-a753-c24b7e91e6e9
Sea ice lead fractions from SAR-derived sea ice divergence in the Transpolar Drift during MOSAiC 2019/2020 Luisa von Albedyll https://doi.org/10.1594/PANGAEA.963671
Continuous meteorological surface measurement during POLARSTERN cruise PS122/1 Holger Schmithüsen https://doi.org/10.1594/PANGAEA.935221
Continuous meteorological surface measurement during POLARSTERN cruise PS122/2 Holger Schmithüsen https://doi.org/10.1594/PANGAEA.935222
Continuous meteorological surface measurement during POLARSTERN cruise PS122/3 Holger Schmithüsen https://doi.org/10.1594/PANGAEA.935223
Continuous meteorological surface measurement during POLARSTERN cruise PS122/4 Holger Schmithüsen https://doi.org/10.1594/PANGAEA.935224
Continuous meteorological surface measurement during POLARSTERN cruise PS122/5 Holger Schmithüsen https://doi.org/10.1594/PANGAEA.935225
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