***** Dataset title *****

Cloud Condensation Nuclei number concentrations over the Southern Ocean during the austral summer of 2016/2017 on board the Antarctic Circumnavigation Expedition (ACE).

***** Dataset abstract *****

Cloud Condensation Nuclei (CCN) are a subclass of atmospheric aerosol particles, which can be activated to cloud droplets at a certain supersaturation, with respect to water. Due to their abundance, these particles can affect micro-physical properties of clouds, while acting as CCN. It was found that CCN are relevant for the Earth’s radiation budget, by affecting cloud albedo and lifetime. When giving a number concentration of CCN, also the supersaturation at which it was measured has to be given. 

With additional information on particle number size distribution, the hypothetical diameter of particle activation (critical diameter) was derived. Further, the particle hygroscopicity parameter (kappa) was calculated using the critical diameter. Values of kappa can be a proxy for bulk chemical composition of the sampled CCN population.

Our dataset gives CCN number concentrations measured by a CCN counter (type CCN-100 by DMT, Boulder, US) operated at five different levels of supersaturation (0.15%, 0.2%, 0.3%, 0.5%, 1%) during the Antarctic Circumnavigation Expedition (ACE) cruise over the Southern Ocean, as part of the ACE-SPACE project. Temporal coverage is from December 20, 2016 to March 19, 2017. We give 5-minute averaged and quality controlled CCN number concentrations, critical diameter and kappa values.

***** Original data collection *****

The original CCN data are the output of a Cloud Condensation Nuclei Counter (CCNC, type “CCN-100”) by Droplet Measurements Technologies. Particle number size distribution (PNSD) are the output of an custom-built Scanning Mobility Particle Sizer (SMPS; Schmale et al., 2017) and an Aerosol Particle Size (APS, model 3321 by TSI). Throughout the cruise, the CCNC, SMPS, and APS instruments were operated inside the aerosol container constructed by Paul Scherrer Institute, situated on the foredeck of the R/V Akademik Tryoshnikov. CCNC, SMPS, and APS were run on a shared standard Global Atmosphere Watch aerosol inlet (PM10) with a total flow rate of 0,5 L/min. The CCNC was operated with a flow ratio (sample flow/sheat flow) of 1/10. More on the set-up in the aerosol container can be found in the cruise report (https://doi.org/10.5281/zenodo.1443511).

Original output files were stored in real-time on a computer, as CSV files, situated in the PSI laboratory container. DMT measurement software V.5.0.6 was used to collect the data.
 
The data did not undergo any processing during the initial process of collection.

***** Data processing *****

Each level of supersaturation (SS) was run for a period of exactly 10 minutes. The raw output of the instrument is CCN number concentration (N_CCN) at a given SS and temperature of the measurement column (T_col) at 1 Hz resolution. The first 5 minutes of each 10-minute period were not considered further, to ensure stable thermal conditions in the measurement column of the instrument. In the remaining 5-minute period, the following data quality criteria were applied: values were only considered valid if (1) the instrument’s internal thermal stability control reported thermally stable conditions, and (2) the absolute difference between set and read temperature of the optics was smaller than 2K.

Remaining N_CCN were corrected to standard conditions (T_base=273.15K, p_base=1013.25hPa) using the temperature (T_inlet) and pressure (p_inlet) at the inlet system in the following formula:
N_CCN_corr = N_CCN * (( p_inlet * T_base )/(T_inlet * p_base)).

Further, the 5-minute period was divided into five 1 minute-long segments and a data filter was used, indicating which 1-minute period is contaminated by exhaust air of the ship’s stack. Excluding 1-minute time steps indicated by the data filter as containing stack contamination, averaging was performed for a maximum of five continuous 1-minute long segments within the 5-minute long period, using the mean of all valid values. The time stamp given for every value is indicating the start of each 5-minute averaging period.

Particle number size distributions (PNSD) from the SMPS (http://doi.org/10.5281/zenodo.2636700) and APS (http://doi.org/10.5281/zenodo.2636709) were merged by applying a mode-fitting technique analogue to Modini et al. (2015), that itself is based on what is described in Khlystov et al. (2004). For further information on the mode-fitting technique, please contact Robin L. Modini (robin.modini@psi.ch). For each N_CCN_corr, the closest PNSD within 1 hour was identified (if possible) and the following process was performed following Kristensen et al. (2015): integration of the PNSD from largest to smallest particle diameter until the resulting particle number equals N_CCN_corr. Respective particle diameter of this equality is the critical diameter (D_crit). Further, the particle hygroscopicity parameter (KAPPA) was calculated using a formula given in Petters and Kreidenweis (2006). For both the derivation of D_crit and KAPPA, uncertainty in measurement and methodology were taken into account by a Monte-Carlo approach analogue to Herenz et al. (2018).

Data processing was done using Python 2.7.14 on Ipython 5.4.1

Please contact the data contact person (given above) for more information on the code and computer environment needed if you wish to reproduce this processing or know more.

***** Quality checking *****

We followed the standard operating procedure (SOP) given in Gysel & Stratmann (2014). 

Quality flags were not used. Output not matching criteria (given in the quality checking section) was not processed further.

All values given are of best possible data quality. Only with ancillary data, quality checks can be done as outlined in Schmale et al. (2017).

***** Standards *****

There are no international standards for CCN number concentration values, to our best knowledge. We adhere to the recommendations in Schmale et al. (2017) and Gysel & Stratmann (2014).

***** Further information for interpreting the data and using the dataset *****

Filters: There are no filters commonly used with this type of dataset, to our best knowledge.

Timescales: The time scales of the main phenomena of the data are detailed in Schmale et al. (2019c) and Tatzelt et al. (in prep.).

Interpolation: Interpolation over missing values should not be done.

Aggregation to lower temporal resolution: Whether aggregation to lower temporal resolution yields reasonable results depends on the research question. It is best to contact the data contact before making a decision.

***** Dataset contents *****

- ACESPACE_cloud_condensation_nuclei_number_concentration_SS015.csv, data file, comma-separated values
- ACESPACE_cloud_condensation_nuclei_number_concentration_SS020.csv, data file, comma-separated values
- ACESPACE_cloud_condensation_nuclei_number_concentration_SS030.csv, data file, comma-separated values
- ACESPACE_cloud_condensation_nuclei_number_concentration_SS050.csv, data file, comma-separated values
- ACESPACE_cloud_condensation_nuclei_number_concentration_SS100.csv, data file, comma-separated values
- ACESPACE_cloud_condensation_nuclei_critical_diameter_SS015.csv, data file, comma-separated values
- ACESPACE_cloud_condensation_nuclei_critical_diameter_SS020.csv, data file, comma-separated values
- ACESPACE_cloud_condensation_nuclei_critical_diameter_SS030.csv, data file, comma-separated values
- ACESPACE_cloud_condensation_nuclei_critical_diameter_SS050.csv, data file, comma-separated values
- ACESPACE_cloud_condensation_nuclei_critical_diameter_SS100.csv, data file, comma-separated values
- ACESPACE_cloud_condensation_nuclei_hygroscopicity_parameter_SS015.csv, data file, comma-separated values
- ACESPACE_cloud_condensation_nuclei_hygroscopicity_parameter_SS020.csv, data file, comma-separated values
- ACESPACE_cloud_condensation_nuclei_hygroscopicity_parameter_SS030.csv, data file, comma-separated values
- ACESPACE_cloud_condensation_nuclei_hygroscopicity_parameter_SS050.csv, data file, comma-separated values
- ACESPACE_cloud_condensation_nuclei_hygroscopicity_parameter_SS100.csv, data file, comma-separated values
- data_file_header_number_concentration.txt, metadata, text
- data_file_header_critical_diameter.txt, metadata, text
- data_file_header_hygroscopicity_parameter.txt, metadata, text
- change_log.txt, metadata, text
- README.txt, metadata, text

The files listed above contain Cloud Condensation Nuclei (CCN) number concentration (N_CCN), critical diameter (D_crit) and particle hygroscopicity parameter (KAPPA) values for the Antarctic Circumnavigation Expedition from in-situ measurements. Each file contains only N_CCN, D_crit or KAPPA values for one of the five measured levels of supersaturation (SS), e.g., N_CCN at SS=0.15% in ACESPACE_cloud_condensation_nuclei_number_concentration_SS015.csv or N_CCN at SS=0.2% in ACESPACE_cloud_condensation_nuclei_number_concentration_SS020.csv etc. In addition, for each N_CCN value the respective temperature of the CCNCs measurement column (T_col) is given. Values are from 1 Hz measurements and averaged to represent 5-minute intervals.

For every given value of CCN number concentration, the respective supersaturation level is given, although files only contain values for one level only. Additionally, longitude and latitude for the ship’s position at the start time of the averaging period are given.

For latitude and longitude nan values are given, in cases where positioning data was not available for the given time period. There are no nan values for CCN number concentration included, in a way that only quality assured data is given.

***** Dataset contact *****

Christian Tatzelt, Leibniz Institute for Tropospheric Research, Germany. ORCID 0000-0001-7795-5372. Email: tatzelt@tropos.de
Silvia Henning, Leibniz Institute for Tropospheric Research, Germany. ORCID 0000-0001-9267-7825. Email: henning@tropos.de
Robert L. Modini, Paul Scherrer Institute, Switzerland. ORCID 0000-0002-2982-1369. Email: robin.modini@psi.ch

***** Dataset citation *****

Please cite this dataset as: 
Tatzelt, C., Henning, S., Tummon, F., Hartmann, M., Baccarini, A., Welti, A., Lehtipalo, K., Schmale, J. and Modini, R. (2020). Cloud Condensation Nuclei number concentrations over the Southern Ocean during the austral summer of 2016/2017 on board the Antarctic Circumnavigation Expedition (ACE). (Version 1.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.4415495