Description: These datasets contain the total particle number concentrations and normalized size distributions (dN/dlogDp) of excited, fluorescent, and hyper-fluorescent particles of sizes 0.5 to 20 μm (optical diameter). The normalized size distribution datasets are split into 20 size bins: 0.5 - 0.6 μm, 0.6 - 0.72 μm, 0.72 - 0.87 μm, 0.87 - 1.05 μm, 1.05 - 1.26 μm, 1.26 - 1.51 μm, 1.51 - 1.82 μm, 1.82 - 2.19 μm, 2.19 - 2.63 μm, 2.63 - 3.16 μm, 3.16 - 3.8 μm, 3.8 - 4.57 μm, 4.57 - 5.5 μm, 5.5 - 6.61 μm, 6.61 - 7.95 μm, 7.95 - 9.56 μm, 9.56 - 11.50 μm, 11.5 - 13.83 μm, 13.83- 16.63 μm and 16.63 - 20 μm. The data were measured by a WIBS-NEO (Wideband Integrated Bioaerosol Sensor, model New Electronics option) by droplet measurement techniques ltd. The data were processed using the IGOR WIBS toolkit V1.36 (DMT) and python version 3.9.7. These datasets have been averaged to 1 hour time resolution. The datasets were cleaned from local pollution sources by applying a pollution flag developed by Beck et al. (2022a,b), which is based on the rate of change in particle number concentration with 1 min time resolution. Data points with more than 10 polluted minutes within an hour were removed from the WIBS datasets. Time periods with zero filter measurements and time periods with unstable flow that affected number concentrations have been removed from the dataset. The WIBS measures the size, asymmetry and fluorescence of particles with an optical diameter of 0.5 – 20 µm. Detected particles are excited by two UV flashlamps at wavelengths of 280 and 370 nm and their emitted fluorescence is measured by two photomultipliers with bandwidths of 310 - 400 nm, and 420 - 650 nm. The WIBS counts excited particles at a maximum frequency of 125 Hz, which corresponds to a maximum concentration of 2.5*104 particles/L with a sample flow of 0.3 L/min. Excited particles were classified as fluorescent if their fluorescent intensity exceeded the background intensity by three standard deviations (3σ) and as hyper-fluorescent if the fluorescent intensity exceeded the background intensity by 9σ. Excited particles with a lower fluorescent intensity were considered to be non-fluorescent. The background fluorescence was determined by measuring the fluorescent signal in the measurement chamber in absence of particles. Background measurements were performed every 26 h. The combination of two excitation wavelengths and two detector wavebands allows the classification of fluorescent particles into seven types: A, B, C, AB, AC, BC, and ABC (Perring et al. (2015); Savage et al. (2017)). For further information about the instrumental setup, refer to Heutte et al. (Submitted).

Description: This dataset contains CCN concentrations at five supersaturation levels, averaged to 1 min time resolution, measured during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern, using the model CCN-100 from Droplet Measurement Technologies (DMT, Boulder, USA). Detailed description of the measurement principle can be found in e.g. Roberts & Nenes (2005). The instrument was located behind an automated valve, which switched hourly between a total and an interstitial air inlet, with upper cutoff sizes of 40 and 1 µm respectively (Heutte et al., Submitted; Beck et al., 2022; Dada et al., 2022). The measurements were performed in 1-h cycles, with a 0.5 L/min sample flow and a 2 L/min make up flow, where the supersaturations 0.15, 0.2, 0.3, 0.5 and 1.0 % were measured. The supersaturation of 0.15 % is measured for 20 min, as it takes longer to equilibrate, and the remaining supersaturations were measured for 10 min each. The instrument was calibrated in July 2019 before the campaign, and in March and April 2020 during the campaign. Based on the inter-variability of the calculated supersaturation levels during these calibrations, we can expect values ranging from 0.15-0.20, 0.20-0.25, 0.29-0.33, 0.43-0.5, 0.78-1.0 % for the nominal supersaturations of 0.15, 0.2, 0.3, 0.5 and 1.0 %, respectively. The counting error for the CCNC is associated with the error in the optical counting of particles and is about 10 %. Data were removed during the cooling cycle (i.e., the time when the measurement cycle starts again and the temperature is cooled to set the lowest supersaturation), which corresponds roughly to the first 10 min of each hour (so 50 % of the 0.15 % supersaturation period). Additionally, the first minute of the transition between supersaturations was removed before averaging the data to 1 min time resolution. During some time periods, a difference pattern of mean and standard deviation of the measurements between even and odd hours was observed, most probably caused by a persistent pressure drop in the inlet lines, resulting in a proportional reduction of the concentration measurements. For correction, the 1-h arithmetic mean of interstitial inlet measurements and the mean of the two adjacent hours of total inlet measurements were subtracted, and the resulting difference was added as a constant to the data points of the interstitial inlet measurements. The dataset contains a pollution mask for local pollution (predominantly exhaust from the Research Vessel Polarstern) with 0 indicating clean, and 1 indicating polluted periods (Beck et al., 2022; Beck et al., 2022).

Description: This dataset contains raw particle number concentration data measured during the year long MOSAiC expedition from October 2019 to September 2020. The measurement was performed in the Swiss aerosol container on the D-deck of Research Vessel Polarstern using an inlet with an upper cut-off of 1 µm (called also interstitial inlet). Data were collected by a Condensation Particle Counter (CPC) model 3025 (TSI Inc.) in 10 s resolution with a lower cut-off diameter of 3 nm. More detailed information about its position and the measurement setup can be found in (Beck et al., 2022). Participation of the Swiss Container was co-financed by the Swiss Polar Institute and University of Helsinki.

Description: This dataset contains corrected particle number concentration data measured during the year long MOSAiC expedition from October 2019 to September 2020. The measurement was performed in the Swiss aerosol container on the D-deck of Research Vessel Polarstern using an inlet with an upper cut-off of 1 µm (called also interstitial inlet). Data were collected by a Condensation Particle Counter (CPC) model 3025 (TSI Inc.) in 10 s resolution with a lower cut-off diameter of 3 nm. More detailed information about its position and the measurement setup can be found in (Beck et al., 2022). The data are cleaned from calibration and zero-check filter periods and the time-stamps of all data points was synchronized to its closest 10 s interval. Some periods of the measurements were corrected for a step in the signal (see file description). Participation of the Swiss Container was co-financed by the Swiss Polar Institute and University of Helsinki.

Description: This dataset contains minute-averaged methane dry air mole fractions measured during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern. Data were collected by cavity ring-down spectroscopy using a commercial Picarro instrument (model G2401). The minute-averaged dry air mole fractions were adjusted after cross-evaluation against discrete whole air samples collected for post-cruise analysis at the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Laboratory. Pollution spikes due to local anthropogenic pollution sources (e.g., exhaust by the vessel's engine and vents, skidoos, helicopters, on-ice diesel generators) were identified and flagged as follows. For each data point, the gradient (time derivative) was calculated (Beck et al., 2022). Data points corresponding to an abnormally high gradient (〉 1.5 times the interquartile range) and neighboring points were discarded. The function “despike” from R package oce (version 1.3-0) was then applied to the time-series to remove any remaining local pollution spikes. Briefly, this function first linearly interpolates across any gaps (missing values). Then, it calculates a running median spanning k elements. The result of these two steps is the “reference” time-series. The standard deviation of the difference between values and the reference is then calculated. Values that differ from the reference by more than n times this standard deviation are considered to be spikes and eliminated. The function was applied once with n = 1 and k = 61 (~ 1 hour). The data columns include the Date and Time in Coordinated Universal Time (UTC), the latitude and longitude of Research Vessel Polarstern, the MOSAiC event label, the original methane dry air mole fraction in nmol/mol, the adjusted methane dry air mole fraction in nmol/mol after cross-evaluation, and a pollution flag where 'yes' means that local pollution was detected.

Description: This dataset contains minute-averaged ozone mole fractions measured during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern. Data were collected using a 2B Technologies instrument (model 205). The minute-averaged mole fractions were adjusted after cross-evaluation against measurements performed in the Atmospheric Radiation Measurement (ARM) Program container using a Thermo Fisher Scientific model 49i instrument. Negative spikes due to local anthropogenic pollution sources (e.g., exhaust by the vessel's engine and vents, skidoos, helicopters, on-ice diesel generators) were identified and flagged using the function “despike” from R package oce (version 1.3-0). Briefly, this function first linearly interpolates across any gaps (missing values). Then, it calculates a running median spanning k elements. The result of these two steps is the “reference” time-series. The standard deviation of the difference between values and the reference is then calculated. Values that differ from the reference by more than n times this standard deviation are considered to be spikes and eliminated. The function was applied twice with different k values (k = 1439 (1 day) and k = 61 (1 hour)) and n = 3. The data columns include the Date and Time in Coordinated Universal Time (UTC), the latitude and longitude of Research Vessel Polarstern, the MOSAiC event label, the original ozone mole fractions in nmol/mol, the adjusted ozone mole fractions in nmol/mol after cross-evaluation, and a pollution flag where 'yes' means that local pollution was detected.

Description: This dataset contains minute-averaged carbon monoxide dry air mole fractions measured during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern. Data were collected by cavity ring-down spectroscopy using a commercial Picarro instrument (model G2401). The minute-averaged dry air mole fractions were adjusted after cross-evaluation against discrete whole air samples collected for post-cruise analysis at the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Laboratory. Pollution spikes due to local anthropogenic pollution sources (e.g., exhaust by the vessel's engine and vents, skidoos, helicopters, on-ice diesel generators) were identified and flagged as follows. For each data point, the gradient (time derivative) was calculated (Beck et al., 2022). Data points corresponding to an abnormally high gradient (〉 1.5 times the interquartile range) and neighboring points were discarded. The function “despike” from R package oce (version 1.3-0) was then applied to the time-series to remove any remaining local pollution spikes. Briefly, this function first linearly interpolates across any gaps (missing values). Then, it calculates a running median spanning k elements. The result of these two steps is the “reference” time-series. The standard deviation of the difference between values and the reference is then calculated. Values that differ from the reference by more than n times this standard deviation are considered to be spikes and eliminated. The function was applied once with n = 3 and k = 61 (~ 1 hour). The data columns include the Date and Time in Coordinated Universal Time (UTC), the latitude and longitude of Research Vessel Polarstern, the MOSAiC event label, the original carbon monoxide dry air mole fraction in nmol/mol, the adjusted carbon monoxide dry air mole fraction in nmol/mol after cross-evaluation, and a pollution flag where 'yes' means that local pollution was detected.

Description: This dataset contains minute-averaged sulfur dioxide mole fractions measured during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern. Data were collected by pulsed fluorescence using a Thermo Fisher Scientific instrument (model 43i). The minute-resolution mole fractions were adjusted after cross-evaluation against a certified sulfur dioxide standard at the end of the expedition at the Swiss Laboratories for Materials Science and Technology (EMPA). Spikes due to local anthropogenic pollution sources (e.g., exhaust by the vessel's engine and vents, skidoos, helicopters, on-ice diesel generators) were identified and flagged as follows. For each data point, the gradient (time derivative) was calculated (Beck et al., 2022). Data points corresponding to an abnormally high gradient (〉 1.5 times the interquartile range) and neighboring points were discarded. The function “despike” from R package oce (version 1.3-0) was then applied to the time-series to remove any remaining local pollution spikes. Briefly, this function first linearly interpolates across any gaps (missing values). Then, it calculates a running median spanning k elements. The standard deviation of the difference between values and the reference is then calculated. The result of these two steps is the “reference” time-series. Values that differ from the reference by more than n times this standard deviation are considered to be spikes and eliminated. The function was applied once with n = 1 and k = 61 (~ 1 hour). The data columns include the Date and Time in Coordinated Universal Time (UTC), the latitude and longitude of Research Vessel Polarstern, the MOSAiC event label, the sulfur dioxide mole fractions in nmol/mol, a pollution flag where 'yes' means that local pollution was detected, and a detection limit flag where 'yes' indicates that the concentration was below the lower detectable limit of 1 nmol/mol.

Description: This dataset contains hourly-averaged carbon dioxide dry air mole fractions measured during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. This is a merged dataset that combines cross-evaluated measurements performed in the University of Colorado (CU) and Swiss containers on Research Vessel Polarstern, along with cross-evaluated measurements performed on sea ice at Met City, and discrete whole air samples collected for post-cruise analysis at the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Laboratory (GML). This merged dataset is recommended for further use by the community. The data columns include the Date and Time in Coordinated Universal Time (UTC), the latitude and longitude of the Research Vessel Polarstern, the carbon dioxide dry air mole fraction in µmol/mol, and the sampling location.

Description: This dataset contains carbon dioxide dry air mole fractions measured during the year-long MOSAiC expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern. Data were collected by cavity ring-down spectroscopy using a commercial Picarro instrument (model G2401). The minute-averaged dry air mole fractions were adjusted after cross-evaluation against discrete whole air samples collected for post-cruise analysis at the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Laboratory. Pollution spikes due to local anthropogenic pollution sources (e.g., exhaust by the vessel's engine and vents, skidoos, helicopters, on-ice diesel generators) were identified and flagged as follows. For each data point, the gradient (time derivative) was calculated (Beck et al., 2022). Data points corresponding to an abnormally high gradient (〉 1.5 times the interquartile range) and neighboring points were discarded. The function “despike” from R package oce (version 1.3-0) was then applied to the time-series to remove any remaining local pollution spikes. Briefly, this function first linearly interpolates across any gaps (missing values). Then, it calculates a running median spanning k elements. The result of these two steps is the “reference” time-series. The standard deviation of the difference between values and the reference is then calculated. Values that differ from the reference by more than n times this standard deviation are considered to be spikes and eliminated. The function was applied once with n = 1 and k = 61 (~ 1 hour). The data columns include the Date and Time in Coordinated Universal Time (UTC), the latitude and longitude of Research Vessel Polarstern, the MOSAiC event label, the original carbon dioxide dry air mole fraction in µmol/mol, the adjusted carbon dioxide dry air mole fraction in µmol/mol after cross-evaluation, and a pollution flag where 'yes' means that local pollution was detected.