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34 results for “Wintertime”
Wintertime subarctic new particle formation from Kola Peninsula sulphur emissions
<p><strong>Nitrate-ion (NO3-) chemical ionization (CI) </strong><strong>APi-TOF </strong><strong>masspectrometer and ion APi-TOF mass spectrometer data reported in Atmospheric Chemistry and Physics: </strong>Sipilä, M., Sarnela, N., Neitola, K., Laitinen, T., Kemppainen, D., Beck, L., Duplissy, E.-M., Kuittinen, S., Lehmusjärvi, T., Lampilahti, J., Kerminen, V.-M., Lehtipalo, K., Aalto, P. P., Keronen, P., Siivola, E., Rantala, P. A., Worsnop, D. R., Kulmala, M., Jokinen, T., and Petäjä, T.: Wintertime sub-arctic new particle formation from Kola Peninsula sulphur emissions, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2020-1202, in review, 2021.</p> <p><a href="https://zenodo.org/api/files/0375de20-1ec1-4185-82f6-ec6eda9466a5/H2SO4_vs_time_FIG3-FIG4.dat">H2SO4_vs_time_FIG3-FIG4.dat</a> </p> <p>[Matlab time, measured sulfuric acid concentration] depicted in FIGs 3c and 4c of the above publication.</p> <p><a href="https://zenodo.org/api/files/0375de20-1ec1-4185-82f6-ec6eda9466a5/SA_MSA_IA_vs_time_FIG7.dat">SA_MSA_IA_vs_time_FIG7.dat</a></p> <p>[Matlab time, measured sulfuric acid concentration, measured methane sulphonic acid concentration, measured iodic acid concentration] depicted in FIG7e of the above publication</p> <p><a href="https://zenodo.org/api/files/0375de20-1ec1-4185-82f6-ec6eda9466a5/ion_signals_vs_time_FIG7.dat">ion_signals_vs_time_FIG7.dat</a></p> <p>[Matlab time, ion signal of NO3-, ion signal of HSO4-, ion signal of H2SO4.HSO4-, ion signal of (H2SO4)2.HSO4-, ion signal of NH3.(H2SO4)3.HSO4-, ion signal of NH3.(H2SO4)4.HSO4-] depicted in FIG7f of the above publication</p> <p> </p> <p><a href="https://zenodo.org/api/files/0375de20-1ec1-4185-82f6-ec6eda9466a5/mass_defect_FIG9.dat">mass_defect_FIG9.dat</a></p> <p>[mass (Da), mass defect (Da), signal intensity (AU)] depicted in FIG9 of the above publication</p> <p>Rest of the data reported in the publication can be obtained from https://smear.avaa.csc.fi/</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Wintertime Arctic warm air intrusion detection algorithm for satellite sea ice concentration analysis
<p>This Dataset is related to the Article <em>Relevance of warm air intrusions for Arctic satellite sea ice concentration time </em>series in <em>The Cryosphere</em> (https://doi.org/10.5194/tc-2023-69).</p> <p>Provided are the core detection algorithm and a minimal working example as well as a list of all detected warm air intrusions between November 1979 and April 2020 (monthly data).</p>
Climate Record of Wintertime Wave-Affected Marginal Ice Zones in the Atlantic Arctic based on CryoSat-2,2010-2022
<p>This record contains data related to article "A 12-Year Climate Record of Wintertime Wave-Affected Marginal Ice Zones in the Atlantic Arctic based on CryoSat-2 ". Wave-affected marginal ice zone (MIZ) is an integral part of the sea ice cover, and a key region for air-ice-sea interactions in polar regions. We develop a novel retrieval algorithm for wave-affected MIZs based on the delay-Doppler radar altimeter onboard CryoSat-2 (CS2). CS2 waveform power and the waveform stack statistics are used to determine the MIZ locations. Based on the CS2 data since 2010, we generate a record of wave-affected MIZs in the Atlantic Arctic, spanning 12 winters between 2010 and 2022.</p> <p>The dataset contains two parts. First, the txt file contains retrieved MIZ locations obtained from each single track. Each column of data is represented by the corresponding CS2 product name, year, month, day, hour, regional flag (1:GS region,2:NS region,3:BS region), the start longitude and latitude of the marginal ice zone on each track, the end longitude and latitude of the marginal ice zone.</p> <p>Second,the gridded dataset is based on the along-track MIZ retrieval results, and it records the presence of the MIZ on the monthly basis. The latitude-longitude grid is adopted, with 2 degrees of longitude spacing and 1 degree of latitude spacing. Each file contains the following variables: the time, the MIZ flag, and the location flag. In this new version, we provide files in both NetCDF and GeoTIFF formats for users to download.</p>
Nitrate and Salinity sampled in West Falmouth Harbor during the wintertime between 2011 and 2024
West Falmouth Harbor (West Falmouth, MA, USA) has been experiencing a dramatic increase in nitrogen loading from an upgradient municipal wastewater treatment facility since the early 2000's. As part of a long-term study into the effects of this nitrogen enrichment, we have measured nitrate concentrations and salinity in water samples collected during the winter months (January, February, March) from the surface waters of the two basins with groundwater inputs impacted by nitrate from the contaminated aquifer. We use these in an open water mixing model to calculate the spatially averaged groundwater nitrate concentration in our manuscript, which we use to calculate the total nitrogen loading to these two basins. This manuscript can be found at DOI: 10.1007/s12237-025-01630-0
Data from: Reduced snow cover increases wintertime nitrous oxide (N2O) emissions from an agricultural soil in the upper U.S. Midwest
Throughout most of the northern hemisphere, snow cover decreased in almost every winter month from 1967 to 2012. Because snow is an effective insulator, snow cover loss has likely enhanced soil freezing and the frequency of soil freeze–thaw cycles, which can disrupt soil nitrogen dynamics including the production of nitrous oxide (N2O). We used replicated automated gas flux chambers deployed in an annual cropping system in the upper Midwest US for three winters (December–March, 2011–2013) to examine the effects of snow removal and additions on N2O fluxes. Diminished snow cover resulted in increased N2O emissions each year; over the entire experiment, cumulative emissions in plots with snow removed were 69% higher than in ambient snow control plots and 95% higher than in plots that received additional snow (P < 0.001). Higher emissions coincided with a greater number of freeze–thaw cycles that broke up soil macroaggregates (250–8000 µm) and significantly increased soil inorganic nitrogen pools. We conclude that winters with less snow cover can be expected to accelerate N2O fluxes from agricultural soils subject to wintertime freezing.
Wintertime new particle formation in the rural area of North China Plain: influencing factors and possible formation mechanism
<p><strong>data for <em>Wintertime new particle formation in the rural area of North China Plain: influencing factors and possible formation mechanism</em></strong></p>
A climatology of thermodynamic vs. dynamic Arctic wintertime sea ice thickness effects during the CryoSat-2 era: Data
<p>Data for:</p> <p>Anheuser, J., Liu, Y., and Key, J.: A climatology of thermodynamic vs. dynamic Arctic wintertime sea ice thickness effects during the CryoSat-2 era, submitted to: The Cryosphere. 2022</p> <p>Code can be found at:</p> <pre>https://doi.org/10.5281/zenodo.7987926</pre>
Data from: Reduced snow cover increases wintertime nitrous oxide (N2O) emissions from an agricultural soil in the upper U.S. Midwest
Open the record for dataset details and reuse information.
Data for: Wintertime coastal upwelling in Lake Geneva: An efficient transport process for deep-water renewal in a large, deep lake
<p>Combining field measurements, 3D numerical modeling and Lagrangian particle tracking,<br> we investigated wind-driven, Ekman-type coastal upwelling during the weakly stratified winter period 2017/2018<br> in Lake Geneva, a large and deep lake in western Europe. The data include measurements from<br> moored Acoustic Doppler Current Profilers (ADCP) and vertical temperature profiles<br> along with the corresponding 3D modeling and particle tracking results.<br> The three-dimensional model used in this study is based on the MIT General<br> Circulation Model (MITgcm, http://mitgcm.org/, https://doi.org/10.1029/96JC02775).<br> The particle tracking code is based on ctracker (https://doi.org/10.5281/zenodo.1034118).</p>
Wintertime daily Arctic sea ice surface form drag from ASCAT during 2006-2021
<p>This dataset contains wintertime (Nov-Apr) daily Arctic sea ice surface form drag derived from ASCAT (2006-2021). The spatial resolution is 12.5*12.5 km projected onto a polar stereographic grid. The daily file (in netCDF format) contains three variables: Cdnfr, Cdn, and SIC_90_label. Cdnfr is the surface form drag (at 10m and in neutral stability), which is only valid for pixels with sea ice concentration (SIC) over 90%. Cdn is the total drag coefficient over sea ice as a sum of skin drag, surface form drag (Cdnfr), and floe form drag. SIC_90_label is a binary map labeling pixels with SIC>90% as 1. The geolocation information is provided in "PS_12500_grid_lat_lon.nc", which contains longitude and latitude for each grid cell and projection information. For the use of the dataset and details of the retrieval algorithm, please cite and read the following paper:<br>Zhang Z, Hui F, Shokr M, et al. Winter Arctic Sea Ice Surface Form Drag During 1999–2021: Satellite Retrieval and Spatiotemporal Variability[J]. IEEE Transactions on Geoscience and Remote Sensing, 2023, doi: 10.1109/TGRS.2023.3347694.</p>
Wintertime daily Arctic sea ice surface form drag from QuikSCAT during 1999-2009
<p>This dataset contains wintertime (Nov-Apr) daily Arctic sea ice surface form drag derived from QuikSCAT (1999-2009). The spatial resolution is 12.5*12.5 km projected onto a polar stereographic grid. The daily file (in netCDF format) contains three variables: Cdnfr, Cdn, and SIC_90_label. Cdnfr is the surface form drag (at 10m and in neutral stability), which is only valid for pixels with sea ice concentration (SIC) over 90%. Cdn is the total drag coefficient over sea ice as a sum of skin drag, surface form drag (Cdnfr), and floe form drag. SIC_90_label is a binary map labeling pixels with SIC>90% as 1. The geolocation information is provided in "PS_12500_grid_lat_lon.nc", which contains longitude and latitude for each grid cell and projection information. For the use of the dataset and details of the retrieval algorithm, please cite and read the following paper:</p> <p>Zhang Z, Hui F, Shokr M, et al. Winter Arctic Sea Ice Surface Form Drag During 1999–2021: Satellite Retrieval and Spatiotemporal Variability[J]. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 2023, doi: 10.1109/TGRS.2023.3347694.</p>
GR6901 wintertime North American daily anomalous surface temperature data
<p>20 years of wintertime (December-February) North American daily anomalous surface temperature from a model simulation. The daily data has had a 7-day low-pass filter applied, and has been weighted for this analysis.</p>
Complementary aerosol mass spectrometry elucidates sources of wintertime sub-micron particle pollution in Fairbanks, Alaska during ALPACA 2022
Open the record for dataset details and reuse information.
Dataset for "Possible Wintertime Sources of Fine Particles in an Urban Environment"
<p>Dataset associated with "Possible Wintertime Sources of Fine Particles in an Urban Environment", Meskhidze et al., (2019), Journal of Geophysical Research. The files are tarball archives compressed using XZ utils. To limit single file size, the data are archived at the directory level. The total extracted data volume is 126.8 GB. README.md (markdown format) provides further information about the data format and files distributed inside the archive. SP2.README.md explains the SP2 data. A README.md further explaining the SMPS data is included in the compressed archived directory.</p>
Modeled wintertime sea ice drift, sea ice thickness, dynamic sea surface height and sea ice drift budget terms in the Arctic
<p>Modeled wintertime sea ice drift, sea ice thickness, dynamic sea surface height and sea ice drift budget terms in the Arctic between 1981 and 2020.</p>
Molecular and 13C isotopic composition of diacids and related compounds in wintertime PM2.5 at three sites over Northeast Asia – Data set
<p>To investigate the spatial changes in atmospheric organic aerosols (OA) loading and composition over the northeast Asian region, fine aerosols (PM<sub>2.5</sub>) were collected at three sites: Tianjin (TJ), North China and in Padori (PD) and Daejeon (DJ), South Korea, during winter 2019. We studied the molecular distributions and compound-specific carbon isotopic composition (δ<sup>13</sup>C) of dicarboxylic acids (diacids), oxocarboxylic acids (oxoacids) and α-dicarbonyls as well as the carbonaceous and inorganic ionic components in two sets of selected samples, representing a clean and a polluted period, during the campaign. Based on the molecular distributions and δ<sup>13</sup>C of diacids and related compounds and mass ratios and linear relations of selected species, we discuss the origins of OA and the influence of long-range transported air masses on their loading and composition over Northeast Asia.</p>
Radiative transfer model and datasets for Li et al. (2023), 'Wintertime low-level clouds over sea ice cool the Arctic climate system'
<p>Source code for the radiative transfer model (RAPRAD) and cloud radiative flux data used in the study Li et al. (2022).</p>
Secondary formation of aerosols under typical high-humidity conditions in wintertime Sichuan Basin, China: A contrast to the North China Plain
<p>The Sichuan Basin is one of the regions suffering from severe haze pollution in southwest China. However, the secondary aerosol formation in this region is poorly understood. In this study, the chemical compositions of PM<sub>2.5</sub> and molecular compositions of water-soluble organics in wintertime Sichuan were measured to investigate the aerosol sources and formation under typical high relative humidity (RH) conditions. Strong correlations between PM<sub>2.5</sub>, carbonaceous aerosols and K<sup>+</sup> suggested obvious influence of biomass burning. The impacts of biomass burning were also supported by the dominance of primarily emitted reduced/less oxidized nitrogen-containing organics as well as the high peak intensities of secondarily formed nitrocatechols and methyl-nitrocatechols. High humidity (average RH=80%) and aerosol liquid water (ALW) in Sichuan obviously facilitated the secondary formation of sulfate, nitrate and secondary organic aerosols (SOA). The average sulfate oxidation ratio and nitrogen oxidation ratio in Sichuan were 2.5 and 3.1 times of those in winter Beijing (average RH= 27%). This suggested higher potentials of SO<sub>2</sub> and NO<sub>x</sub> to form sulfate and nitrate under high-RH conditions.<sub> </sub>The abundant aqueous-SOA formation in Sichuan was supported by the dominance of organosulfates (OSs) and nitrooxy-OSs in mass spectra of water-soluble organics, while the OSs in winter Beijing were quite limited. The more abundant OS formation in Sichuan was attributed to the much higher RH, ALW, aerosol acidity and sulfate, which favored the acidic sulfate-catalyzed aqueous-phase reactions for OS formation. Higher concentrations of biogenic volatile organic compounds were additional reasons for the more abundant OSs in Sichuan than in Beijing.</p>
Snow-Induced Perturbations in Nitrous Acid (HONO) Levels: Insights into Heterogeneous Reactions During Wintertime in Mid-Latitude Regions
<ol> <li>Variations in HONO, PM2.5, NO2, and HONO/NO2 concentrations data</li> <li>Time series data of pollutants</li> </ol>
Data archive for the peer-reviewed journal article "Major source categories of PM2.5 oxidative potential in wintertime Beijing and surroundings based on online dithiothreitol-based field measurements"
<p>This data archive accompanying the article "Major source categories of PM2.5 oxidative potential in wintertime Beijing and surroundings based on online dithiothreitol-based field measurements", which was accepted in April 2024 in the peer-reviewed journal <strong><em>Science of the Total Environment</em></strong>. This data archive contains the processed OPvDTT measurements, chemical speciation of PM2.5, and source contribution used in the manuscript.</p>
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