Chemical and physical properties of cloud residuals measured during the Ny-Ålesund Aerosol Cloud Experiment 2019 – 2020

Yvette Gramlich, Karolina Siegel, Sophie Haslett, Gabriel Freitas, Radovan Krejci, Paul Zieger, Claudia Mohr

Molecular-level information about the chemical composition of cloud residuals, measured with a filter inlet for gases and aerosols coupled to an iodide high resolution time-of-flight mass spectrometer (FIGAERO-CIMS). In addition, the data also contains the corresponding number size distributions of the cloud residuals, and the sum of cloud residuals and interstitial aerosol particles, as well as the back trajectories for the cloud cases considered in the study.

The data provide information about the chemical and physical properties of aerosol particles acting as cloud condensation nuclei or ice nucleating particles in the Arctic.

It were collected during the Ny-Ålesund Aerosol Cloud Experiment (NASCENT, 2019 – 2020) at the Zeppelin Observatory on Svalbard and covers 14 cloud cases from December 2019 until December 2020.

Citation

Yvette Gramlich, Karolina Siegel, Sophie Haslett, Gabriel Freitas, Radovan Krejci, Paul Zieger, Claudia Mohr (2023) Chemical and physical properties of cloud residuals measured during the Ny-Ålesund Aerosol Cloud Experiment 2019 – 2020. Dataset version 1. Bolin Centre Database. https://doi.org/10.17043/zeppelin-gramlich-2023-nascent-1

References

Gramlich, Y., Siegel, K., Haslett, S. L., Freitas, G., Krejci, R., Zieger, P., & Mohr, C. (2023). Revealing the chemical characteristics of Arctic low-level cloud residuals – in situ observations from a mountain site. Atmospheric Chemistry and Physics, 23(12), 6813–6834. https://doi.org/10.5194/acp-23-6813-2023

Stein, A. F., Draxler, R. R., Rolph, G. D., Stunder, B. J. B., Cohen, M. D., & Ngan, F. (2015). NOAA’s HYSPLIT Atmospheric Transport and Dispersion Modeling System. Bulletin of the American Meteorological Society, 96(12), 2059–2077. https://doi.org/10.1175/BAMS-D-14-00110.1

Rolph, G., Stein, A., & Stunder, B. (2017). Real-time Environmental Applications and Display sYstem: READY. Environmental Modelling & Software, 95, 210–228. https://doi.org/10.1016/j.envsoft.2017.06.025

Data description

The dataset contains 5 xlsx files described below, as well as copies as 10 csv files, one for each sheet.

1. File FIGAERO-CIMS_cloud_residual_signals_in_ions.xlsx: molecular-level chemical composition information of 14 cloud residual samples (labelled Dec 25, 2019 until Dec 9, 2020), background subtracted signal (in ion counts), molecular formula, and the measured mass to charge ratio (m/z).

   • Column 1: measured mass to charge ratio in Thomson (Th).
   • Column 2: molecular formula, unknown compounds indicated as “unknown”.
   • Column 3 – 16: background subtracted cloud residual signals in ion counts (ions) from December 25, 2019 until December 9, 2020.

2. File Cloud_case_May18.xlsx:

   • Sheet FIGAERO-CIMSsignal_ions: background subtracted signal (in ion counts) of the molecular-level chemical composition of aerosol particles before and after a cloud case on May 18, 2020.

     • Column 1: measured mass to charge ratio in Thomson (Th).
     • Column 2: molecular formula, unknown compounds indicated as “unknown”.
     • Column 3 – 4: background subtracted signals of aerosol particles before (column 3) and after (column 4) the cloud case, in ion counts (ions).

   • Sheet sampling times: respective sampling times with the FIGAERO-CIMS

     • Column 1: name of the FIGAERO-CIMS sample (as in column 3-4 in sheet FIGAERO-CIMSsignal_ions).
     • Column 2: start of the FIGAERO-CIMS sampling time, in UTC.
     • Column 3: end of the FIGAERO-CIMS sampling time, in UTC.

   • Sheet visibility: time series of the visibility (measured with a visibility sensor) during this cloud case.

     • Column 1: time, in UTC.
     • Column 2: visibility, in m.

   • Sheet Size_distributions: average and median number size distributions (dN/dlogD in cm⁻³) before, during, and after the cloud case (measured with a DMPS, size range 5 – 708 nm, bin midpoint).

     • Column 1: diameter (bin midpoint), in m.
     • Column 2 – 7: dN/dlogD, in cm⁻³, in the header name of each column it is stated if it is the average, median and if it is before, during or after the cloud case (e.g. dN_dlogD_before_average [cm⁻³] refers to the average dN/dlogD before the cloud case).

3. File Number_size_distr.xlsx: mean, median and standard deviation of the cloud residual number size distributions (dN/dlogD in cm⁻³) for all cloud residual measurements. This data is spread in two sheets. The reason for this is the slightly different size bins of the DMPS system in 2019 and 2020 (10 nm – 945 nm, bin midpoint).

   • Sheet dN_dlogD_DMPS1_year_2020: values for the cloud residual samples in the year 2020.

     • Column 1: Diameter (bin midpoint), in m.
     • Column 2 – 40: dN/dlogD, in cm⁻³, in the header name of each column it is stated if it is the mean, median or one standard deviation (mean, median, std, respectively) and the cloud residual sample day (e.g. May 18, 2020 mean [cm⁻³] refers to the mean dN/dlogD for the cloud residual sample on May 18, 2020).

   • Sheet dN_dlogD_DMPS1_year_2019: values for the cloud residual sample in the year 2019.

     • Columns and units similar to Sheet dN_dlogD_DMPS1_year_2020.

   • Sheet dN_dlogD_DMPS2: corresponding number size distributions of the total particles (sum of cloud residuals and interstitial aerosol particles, measured with a DMPS, size range 5 – 708 nm, bin midpoint).

     • Columns and units similar to Sheet dN_dlogD_DMPS1_year_2020.

4. File GCVI_vis_data.xlsx: number of hours per month when visibility was below 1000 m, and when it was below 1000 m and the GCVI was on in addition.

   • Column 1: month and year.
   • Column 2: number of hours when visibility was below 1000 m and GCVI (used to sample cloud residuals) was in operation.
   • Column 3: number of hours when visibility was below 1000 m.

5. File trajectoires.xlsx: HYSPLIT back trajectories for the cloud case on May 18, 2020 as well as the other cloud cases in 2020. The data were created using 3-hourly archive data from GDAS.

   • Column 1: time, in UTC.
   • Column 2 – 6: hours back, geographical location, altitude and rainfall, at the given time; respective units in brackets of the columns.

More information about the data can be found in Gramlich et al. (2022). Information about the trajectories can be found in Stein et al. (2015) and Rolph et al. (2017).

Comments

The cloud residuals and the total aerosol particles were measured with two different Differential Mobility Particle Sizer (DMPS).