The Data Access Portal has information in 3 columns. An outline of the content in these columns is provided above. When first entering the search interface, all potential datasets are listed. Datasets are indicated in the map and results tabulation elements which are located in the middle column. The order of results can be modified using the "Sort by" option in the left column. On top of this column is normally relevant guidance information to user presented as collapsible elements.
If the user want to refine the search, this can be done by constraining the bounding box search. This is done in the map - the listing of datasets is automatically updated. Date constraints can be added in the left column. For these to take effect, the user has to push the button marked search. In the left column it is also possible to specific text elements to search for in the datasets. Again pushing the button marked "Search" is necessary for these to take action. Complex search patterns can be constructed using logical operators and phrases embedded in quotation marks. Logical operators include AND, OR and NOT. Remember to add space around operators. Text strings that are not quoted are trated as separate words and will match any of the words (i.e. assuming the OR operator). E.g. in order to find WMO synoptic weather station data from Verlegenhuken use the search phrase: [synop AND verlegenhuken]. Searches are case insensitive.
Other elements indicated in the left and right columns are facet searches, i.e. these are keywords that are found in the datasets and all datasets that contain these specific keywords in the appropriate metadata elements are listed together. Further refinement can be done using full text, date or bounding box constraints. Individuals, organisations and data centres involved in generating or curating the datasets are listed in the facets in the right column.
Collections
Collections allows the user to search in subsets of the existing catalogue. The collections are primarily data management projects that have been incorporated in the ADC catalogue after the project has ended. In this context the ADC is the long term access solution for these data. The collections currently served through ADC include (datasets may belong to multiple data collections):
ADC is the full collection of this service CC is the CryoClim collection
In order to search a specific data collection select that collection. If no data collection is selected all collections are searched.
AeN are data related to the Nansen Legacy project and are better explored through the SIOS Data Access Point using the collection defined there which is available through this URL.
SIOS, InfraNOR, SIOSCD, SIOSAP, SESS_* are collections related to SIOS. These are better explored through the SIOS Data Access Portal
Some cleaning is pending between InfraNOR and SIOSIN, for some of the SESS collections.
Citation of data and service
Always remember to cite data when used!
Citation information for individual datasets is often provided in the metadata. However, not all datasets have this information embedded in the discovery metadata. On a general basis a citation of a dataset include the same components as any other citation:
author,
title,
year of publication,
publisher (for data this is often the archive where it is housed),
edition or version,
access information (a URL or persistent identifier, e.g. DOI if provided)
The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
If you use data retrieved through this portal, please acknowledge the Norwegian Meteorological Institute/Arctic Data Centre.
Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)
Last metadata update: 2022-11-10T12:00:00Z
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Abstract:
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., in prep.).
Participation of the Swiss Container was co-financed by the Swiss Polar Institute and University of Helsinki. ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.941873"! ** The particle concentration data were not processed, however periods where the instrument did not measure outdoor air were removed. We used 10 sec time resolution positional data from the following datasets: Rex, M (2020), Haas, C (2020), Kanzow, T (2020), Rex, M (2021a,b).
Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)
Last metadata update: 2022-11-21T12:00:00Z
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Abstract:
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. ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.944270"! ** We used 1 sec time resolution positional data from the following datasets: PS122/1: Rex, M (2020), PS122/2: Haas, C (2020), PS122/3: Kanzow, T (2020), PS122/4: Rex, M (2021a), PS122/5: Rex, M (2021b)
Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)
Last metadata update: 2022-11-21T12:00:00Z
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Abstract:
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. ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.944258"! ** We used 1 sec time resolution positional data from the following datasets: PS122/1: Rex, M (2020), PS122/2: Haas, C (2020), PS122/3: Kanzow, T (2020), PS122/4: Rex, M (2021a), PS122/5: Rex, M (2021b)
Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)
Last metadata update: 2022-11-21T12:00:00Z
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Abstract:
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. ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.944264"! ** We used 1 sec time resolution positional data from the following datasets: PS122/1: Rex, M (2020), PS122/2: Haas, C (2020), PS122/3: Kanzow, T (2020), PS122/4: Rex, M (2021a), PS122/5: Rex, M (2021b)
Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)
Last metadata update: 2022-02-21T12:00:00Z
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Abstract:
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., in prep.). ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.941283"! ** The particle concentration data were not processed, however periods where the instrument did not measure outdoor air were removed. We used 10 sec time resolution positional data from the following datasets: Rex (2020), Haas (2020), Kanzow (2020) and Rex (2021ab).
Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)
Last metadata update: 2022-11-21T12:00:00Z
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Abstract:
This dataset contains hourly-averaged ozone 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), the Atmospheric Radiation Measurement (ARM) Program, and Swiss containers onboard Research Vessel Polarstern. The data columns include the Date and Time in Coordinated Universal Time (UTC), the latitude and longitude of the Research Vessel Polarstern, the ozone dry air mole fraction in nmol/mol, and the sampling location. ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.944393"! ** This merged dataset was created using the following datasets: Angot et al. (2022a,b) and Springston and Koontz (2019).
We used 1 sec time resolution positional data from the following datasets: PS122/1: Rex, M (2020), PS122/2: Haas, C (2020), PS122/3: Kanzow, T (2020), PS122/4: Rex, M (2021a), PS122/5: Rex, M (2021b)
Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)
Last metadata update: 2022-11-21T12:00:00Z
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Abstract:
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. ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.944272"! ** This merged dataset was created using the following datasets: Blomquist et al. (in review, a, b), Angot et al (in review), Dlugokencky et al. (2021).
We used 1 sec time resolution positional data from the following datasets: PS122/1: Rex, M (2020), PS122/2: Haas, C (2020), PS122/3: Kanzow, T (2020), PS122/4: Rex, M (2021a), PS122/5: Rex, M (2021b)
Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)
Last metadata update: 2022-11-21T12:00:00Z
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Abstract:
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. ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.944268"! ** We used 1 sec time resolution positional data from the following datasets: PS122/1: Rex, M (2020), PS122/2: Haas, C (2020), PS122/3: Kanzow, T (2020), PS122/4: Rex, M (2021a), PS122/5: Rex, M (2021b)
Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)
Last metadata update: 2022-11-21T12:00:00Z
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Abstract:
This dataset contains hourly-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. This is a merged dataset that combines cross-evaluated measurements performed in the Atmospheric Radiation Measurement (ARM) Program and Swiss containers on the D-deck of Research Vessel Polarstern, along with data from discrete whole air samples collected for post-cruise analysis at the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Laboratory (GML). The data columns include the Date and Time in Coordinated Universal Time (UTC), the latitude and longitude of the Research Vessel Polarstern, the carbon monoxide dry air mole fraction in nmol/mol, and the sampling location. ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.944389"! ** This merged dataset was created using the following datasets: Trojanowski and Springston (2019), Angot et al (in review), Petron et al. (2020).
We used 1 sec time resolution positional data from the following datasets: PS122/1: Rex, M (2020), PS122/2: Haas, C (2020), PS122/3: Kanzow, T (2020), PS122/4: Rex, M (2021a), PS122/5: Rex, M (2021b)
Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)
Last metadata update: 2022-11-21T12:00:00Z
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Abstract:
This dataset contains hourly-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. 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). The data columns include the Date and Time in Coordinated Universal Time (UTC), the latitude and longitude of the Research Vessel Polarstern, the methane dry air mole fraction in nmol/mol, and the sampling location. ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.944291"! ** This merged dataset was created using the following datasets: Blomquist et al. (in review, a, b), Angot et al (in review), Dlugokencky et al. (2021).
We used 1 sec time resolution positional data from the following datasets: PS122/1: Rex, M (2020), PS122/2: Haas, C (2020), PS122/3: Kanzow, T (2020), PS122/4: Rex, M (2021a), PS122/5: Rex, M (2021b)
Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)
Last metadata update: 2022-11-10T12:00:00Z
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Abstract:
This dataset contains a pollution flag in 1 min time resolution. It is derived by the pollution detection algorithm (PDA) based on the corrected particle number concentration data (DOI upcoming) measured during the year long MOSAiC expedition from October 2019 to September 2020. With pollution, we refer to emission from the exhaust of the ship stack, snow groomers, diesel generators, ship vents, helicopters and other. Pollution hence reflects locally emitted particles and trace gases, which are not representative of the central Arctic ambient concentrations. The PDA identifies and flags periods of polluted data in the particle number concentration dataset five steps. The first and most important step identifies polluted periods based on the gradient (time-derivative) of a concentration over time. If this gradient exceeds a given threshold, data are flagged as polluted. Further pollution identification steps are a simple concentration threshold filter, a neighboring points filter (optional), a median and a sparse data filter (optional). The detailed methodology of the derivation of the pollution flag is described in Beck et al. (Atmos. Meas. Tech., in prep). A description and download link to the used particle number concentration dataset can be found here: doi:10.1594/PANGAEA.941886. The code of the PDA can be found on Zenodo (Beck et al., 2021; doi:10.5281/zenodo.5761101).
Participation of the Swiss Container was co-financed by the Swiss Polar Institute and University of Helsinki. ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.941335"! ** This dataset contains a pollution flag in 1 min time resolution and the corresponding particle number concentration data (doi:10.1594/PANGAEA.941886). The data columns include Event, Time, Latitude, Longitude, Particle number concentration and a pollution flag to indicate polluted periods (0=not polluted, 1=polluted). The pollution flag is derived from the Pollution Detection Algorithm (PDA), a python-based open access script to automatically detect contamination in remote atmospheric time series (Beck et al., Atmos. Meas. Tech., in prep.). The following parameters were used in the PDA script to derive this pollution flag:
Remark_1: The corrected particle number concentration may still contain some minor artefacts and a critical review of the data by an expert is required. The pollution flag is based on the above mentioned parameters. If needed, the PDA can be tuned to be stricter. The decision whether a single data point is affected by pollution is up to the user and requires an expert review.
Remark_2: This pollution mask can be applied to other particle and trace measurements obtained during MOSAiC. Please see Beck et al., Atmos. Meas. Tech., in prep. for a detailed discussion.
Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)
Last metadata update: 2022-11-10T12:00:00Z
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Abstract:
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., in prep.). 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. ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.941886"! ** Some periods of the measurements were affected by repeated step changes in the particle number concentrations. This was caused by a valve, which was positioned in the line behind (downstream) the CPC and switched between a total air inlet and an interstitial inlet. During odd hours (i.e. 1 am, 3 am etc.) the valve was open to the interstitial inlet, during even hours to the total inlet. During the affected periods (less than ten periods with a duration of less than 12 hours, except for a three-day period from Dec. 08, 2019 to Dec. 10, 2019), the measured particle number concentrations behind the interstitial inlet are lower compared to the previous and the following hour behind the total inlet. To correct for these step changes in concentration, we calculated two correction factors, i.e. at the beginning and at the end of the affected period. The two correction factors are derived by dividing the median particle number concentrations of 3 minutes before (after) the start (end) of the affected period by the median particle number concentration of 3 minutes after (before) the start (end) of the affected period. Each data point of the affected period was then corrected by multiplying its particle number concentration by the linearly interpolated correction factor at the corresponding timestamp. The corrected data set may still contain minor artefacts related to the step change correction, i.e. small deviations of the number concentration in the order of < 10 %. The counting uncertainty of a CPC is nominally 10 %. Depending on how the dataset is used this might be relevant or not.
The dataset has a time resolution of 10 sec. More detailed information about the measurement setup can be found in (Beck et al., in prep.). The data columns include Time, Latitude, Longitude, Particle number concentration and a correction flag (0=uncorrected, 1 = corrected).
We used 10 sec time resolution positional data from the following datasets: Rex, M (2020), Haas, C (2020), Kanzow, T (2020), Rex, M (2021a,b).
Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC)
Last metadata update: 2022-11-21T12:00:00Z
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Abstract:
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. ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.944248"! ** We used 1 sec time resolution positional data from the following datasets: PS122/1: Rex, M (2020), PS122/2: Haas, C (2020), PS122/3: Kanzow, T (2020), PS122/4: Rex, M (2021a), PS122/5: Rex, M (2021b)