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50 results for “ice nucleation”
Ice Nucleating Particle number concentration from low-volume sampling over the Southern Ocean during the austral summer of 2016/2017 on board the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract </strong></p> <p>Ice nucleating particles (INP) are a subclass of atmospheric aerosol particles, which can force heterogeneous freezing of cloud droplets at temperatures above -38 degrees C. In contrast, ice particles form from cloud droplets at temperatures below -38 degrees C due to homogeneous freezing, without INP. Due to their abundance, these particles can affect micro-physical properties of clouds, while acting as INP. During the Antarctic Circumnavigation Expedition (ACE) around the Southern Ocean, off-line filter sampling was performed. Filters were stored on the ship and analysed after the cruise at Leibniz-Institute for Tropospheric Research (TROPOS) concerning INP abundance. Here, we give INP number concentrations for sampling of 8 hour periods.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ACESPACE_ice_nucleating_particles_frozen_fraction_from_lowvolume_filters.csv, data file, comma-separated values</li> <li>ACESPACE_ice_nucleating_particles_number_concentration_from_lowvolume_filters.csv, data file, comma-separated values</li> <li>data_file_header_frozen_fraction.txt, metadata, text format</li> <li>data_file_header_number_concentration.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> <li>change_log.txt, metadata, text format</li> </ul> <p><strong>Change log</strong></p> <p>v1.1 - data files updated</p> <ul> <li>change dataset title to reflect low-volume sampling method</li> <li>addition of INP number concentration data from different temperatures</li> <li>addition of fraction of frozen droplets data</li> <li>addition of field blank filter data</li> <li>create separate data_file_header files</li> <li>add change log</li> </ul> <p>v1.0 - initial release of dataset</p> <p> </p>
Data from Portable Ice Nucleation Experiment during the Pallas Cloud Experiment 2022
<div> </div> <div> </div> <div>The data set contains data from the Portable Ice Nucleation Experiment during the Pallas Cloud Experiment 2022. The Level 1 data is given in its raw temporal resolution and the data is flagged. Invalid data should be removed before analysis.</div>
Data for the publication "Retrieving ice-nucleating particle concentration and ice multiplication factors using active remote sensing validated by in situ observations"
<p>This repository contains the data for the paper:</p> <p>Wieder, J., Ihn, N., Mignani, C., Haarig, M., Bühl, J., Seifert, P., Engelmann, R., Ramelli, F., Kanji, Z. A., Lohmann, U., and Henneberger, J.: Retrieving ice nucleating particle concentration and ice multiplication factors using active remote sensing validated by in situ observations, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2022-67, in review, 2022.</p> <p>More information can be found in the README files.</p> <p>Note that the scripts to reproduce the figures of the publication are available on request.</p>
Measurements of Ice Nucleating Particles in Beijing, China - Data and processing code
<p>Dataset needed to replicate findings published in the journal article "Measurements of Ice Nucleating Particles in Beijing, China, published in the Journal of Geophysical Research. The dataset contains the following:</p> <p>1. Data files containing raw data from a Continuous Flow Diffusion Chamber - Ice Activation Spectrometer (CFDC-IAS), in comma-delimited format).</p> <p>2. Data and processing files for analysis of backward air trajectories as an Igor Pro 8 packed experiment package file. Igor Pro is available from www.wavemetrics.com and a free 30-day trial version can be used to export data to other formats.</p> <p>3. Data and processing files for analysis of CFDC, APS and meteorological data, including data in the form of waves, as part of an Igor Pro 8 packed experiment package.</p>
3-D model data used to investigate the role of K-feldspar and quartz in global ice nucleation by mineral dust in mixed-phase clouds
<p>These simulations were run by Chemical Transport Model TM4-ECPL covering the years 2009-01 to 2016-12 and are used for the bellow publication:</p> <p>Chatziparaschos, M., Daskalakis, N., Myriokefalitakis, S., Kalivitis, N., Nenes, A.,<br> Gonçalves Ageitos, M., Costa-Surós, M., Pérez García-Pando, C., Zanoli, M., Vrekoussis,<br> M., and Kanakidou, M.: Role of K-feldspar and quartz in global ice nucleation by mineral dust in mixed-phase clouds,<br> Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2022-551, in press 2023.</p> <p>Laboratory: Environmental Chemical Processes Laboratory (EPCL), Department of Chemistry, University of Crete, Heraklion.<br> contact: Kanakidou Maria <mariak@uoc.gr></p> <p>Model resolution: 2x3<br> Model Levels: 25</p> <p>Data info:</p> <p>DU_m2m(time, lev, lat, lon)<br> short_name :DU_m2m<br> long_name : Dust mode 2 mass accumulation</p> <p>DU_m3m(time, lev, lat, lon)<br> short_name : DU_m3m<br> long_name : Dust mode 3 mass coarse</p> <p>qua2_acc(time, lev, lat, lon)<br> short_name :qua2_acc<br> long_name :Quartz – accumulation mode</p> <p>qua2_coa(time, lev, lat, lon)<br> short_name :qua2_coa<br> long_name :Quartz – coarse mode</p> <p>FEL_acc(time, lev, lat, lon)<br> short_name :FEL_acc<br> long_name : K-Feldspar – accumulation mode</p> <p>FEL_coa(time, lev, lat, lon)<br> short_name :FEL_coa<br> long_name : K-Feldspar – coarse mode</p> <p>INP_QUA(time, lev, lat, lon)<br> short_name :INP_QUA<br> long_name :Ice Nucleating Particles derived form Quartz</p> <p>INP_FELD(time, lev, lat, lon)<br> short_name :INP_FELD<br> long_name :Ice Nucleating Particles derived form K-Feldpsar</p> <p> </p>
Dataset to: Terrestrial runoff is an important source of biological ice-nucleating particles in Arctic marine systems
<p>The dataset contains supplementary information to the manuscript "Terrestrial runoff is an important source of biological ice-nucleating particles in Arctic marine systems"</p> <p>The file <a href="https://zenodo.org/api/records/14988900/draft/files/INP_data_all_samples.csv/content" target="_blank" rel="noopener noreferrer">INP_data_all_samples.csv</a> contains information on the ice nucleation measurements for all samples presented.</p> <p>The file "<a href="https://zenodo.org/api/records/14044414/draft/files/Significant_taxa_list_16S.xlsx/content" target="_blank" rel="noopener noreferrer">Significant_taxa_list_16S.xlsx</a>" contains a list of the bacterial taxa that significantly correlated with the concentration of INPs observed in the samples, while the file <a href="https://zenodo.org/api/records/14044414/draft/files/Significant_taxa_list_18S.xlsx/content" target="_blank" rel="noopener noreferrer">Significant_taxa_list_18S.xlsx</a> contains the same information for the microalgae. </p> <p>The relative abundance of the taxa in each sample is indicated in the columns "F" to "T". </p>
Dataset for "Bioaerosol diversity and Ice nucleating particles in the North-Western Himalayan Region"
<p>Dataset for "Bioaerosol diversity and Ice nucleating particles in the North-Western Himalayan Region". Contains data and scripts to reproduce the figures in the manuscript. See README.md for more information.</p>
Dataset for "Experimental determination of the relationship between organic aerosol viscosity and ice nucleation at upper free tropospheric conditions"
<p><strong>Data and scripts used to create the figures in the manuscript titled: "Experimental determination of the relationship between organic aerosol viscosity and ice nucleation at upper free tropospheric conditions"</strong></p>
Raw data of the manuscript "The Ice Nucleation Activity of Black and Brown Soot"
<p>Raw data of the manuscript "The Ice Nucleation Activity of Black and Brown Soot" to be published in the Journal of Geophysical Research 2018</p>
Dataset to: Vertical distribution of ice nucleating particles over the boreal forest of Hyytiälä, Finland
<p>This repository contains the datasets used in the study 'Vertical distribution of ice nucleating particles over the boreal forest of Hyytiälä, Finland'. Detailed information and technical aspects of the data can be found in the publication.</p>
CESM2 simulation output used in the study "On the links between ice nucleation, cloud phase, and climate sensitivity in CESM2"
<p>Provided is all CESM2 model output used to generate figures in the study, for which a preprint is at 'https://doi.org/10.22541/essoar.167214452.25853014/v1'. File names indicate the experiment names used in the study. For each model experiment, there is one file containing variables in a present-day (PD) simulation, plus a second file containing cloud feedbacks calculated by the Zelinka et al 2012 kernel method (comparing PD to PD with 4K warming uniformly added to sea surface temperatures).</p>
Model output from "The chance of freezing – a conceptional study to parameterize temperature-dependent freezing by including randomness of ice-nucleating particle concentrations"
<p>Model output from "The chance of freezing – a conceptional study to parameterize temperature-dependent freezing by including randomness of ice-nucleating particle concentrations", accepted for publication in Atmospheric Chemistry and Physics, 2023, same authors.<br> The simulations were done using MIMICA version4 (Savre at el., 2014) and the data includes all model output presented in the publication.</p>
Data for figures in "Next-generation ice nucleating particle sampling on aircraft: Characterization of the High-volume flow aERosol particle filter sAmpler (HERA)"
<p>Atmospheric ice nucleating particle (INP) concentration data from the free troposphere are sparse, but urgently needed to understand vertical transport processes of INPs and their influence on cloud formation and properties. Here, we introduce the new High-volume flow aERosol particle filter sAmpler (HERA) which was specially developed for installation on research aircraft and subsequent offline INP analysis. HERA is a modular system constisting of a sampling unit and a powerful pump unit and has several features which were integrated specifically for INP sampling. Firstly, the pump unit enables sampling at flow rates exceeding 100 L min<sup>−1</sup>, which is well above typical flow rates of aircraft INP sampling systems described in the literature (~10 L min<sup>−1</sup>). Consequently, required sampling times to capture rare, high-temperature INPs (≥-15 °C) are reduced in comparison to other systems and potential source regions of INPs can be confined more precisely. Secondly, the sampling unit is designed as a seven-way valve, enabling switching between six filter holders and a bypass with one filter being sampled at a time. In contrast to other aircraft INP sampling systems, the valve position is controlled remotely via software so that manual filter changes in-flight are eliminated and the potential for sample contamination is decreased. This design is compatible with a high degree of automation, i.e., triggering filter changes depending on parameters like flight altitude, geographical location, temperature, or time. In addition to the design and principle of operation of HERA, this paper presents laboratory characterization experiments with size-selected test substances, i.e., SNOMAX® and Arizona Test Dust. The particles were sampled on filters with HERA, varying either particle diameter (300 nm to 800 nm) or flow rate (10 L min<sup>−1</sup> to 100 L min<sup>−1</sup>) between experiments. The subsequent offline INP analysis showed good agreement with literature data and comparable sampling efficiencies for all investigated particle sizes and flow rates. Furthermore, the deposition efficiency of atmospheric INPs in HERA was compared to a straightforward filter sampler and good agreement was found. Finally, results from the first campaign of HERA on the High Altitude and LOng range research aircraft (HALO) demonstrate the functionality of the new system in the context of aircraft application.</p> <p>The given csv files contain the data for reproducing the figures in the publication. The data structure of the csv files is explained in the README file.</p>
Data for: Low temperature ice nucleation of sea spray and secondary marine aerosols under cirrus cloud conditions
<p>Sea spray aerosols (SSA) represent one of the most abundant aerosol types on a global scale and have been observed at all altitudes including the upper troposphere. SSA has been explored in recent years as a source of ice nucleating particles (INPs) in cirrus clouds due to the ubiquity of cirrus clouds and the uncertainties in their radiative forcing. This study expands upon previous works on low temperature ice nucleation of SSA by investigating the effects of atmospheric aging of SSA and the ice nucleating activity of newly formed secondary marine aerosols (SMA) using an oxidation flow reactor. Polydisperse aerosol distributions were generated from a Marine Aerosol Reference Tank (MART) filled with 120 L of real or artificial seawater and were dried to very low relative humidity to crystallize the salt constituents of SSA prior to their subsequent freezing, which was measured using a Continuous Flow Diffusion Chamber (CFDC). Results show that for both primary SSA (pSSA), and the aged SSA and SMA (aSSA+SMA) at temperatures > 220 K, homogeneous conditions (92–97 % relative humidity with respect to water (RHw)) were required to freeze 1 % of the particles. However, below 220 K, heterogeneous nucleation occurs for both pSSA and aSSA+SMA at much lower RHw, where up to 1 % of the aerosol population freezes between 75–80 % RHw. Similarities between freezing behaviors of the pSSA and aSSA+SMA at all temperatures suggest that the contributions of condensed organics onto the pSSA or alteration of functional groups in pSSA via atmospheric aging did not hinder the major heterogeneous ice nucleation process at these cirrus temperatures that has previously been shown to be dominated by the crystalline salts. Occurrence of 1% frozen fraction of SMA, generated in the absence of primary SSA, was observed at/near water saturation below 220 K, suggesting it is not an effective INP at cirrus temperatures, similar to findings in the literature of other organic aerosols. Thus, any SMA coatings on the pSSA would only decrease the ice nucleation behavior of pSSA if the organic components were able to significantly delay water uptake of the inorganic salts, and apparently, this was not the case. Results from this study demonstrate the ability of lofted primary sea spray particles to remain an effective ice nucleator at cirrus temperatures, even after atmospheric aging has occurred over a period of days in the marine boundary layer prior to lofting. We were not able to address aging processes under upper tropospheric conditions.</p>
Ice-Nucleating Particle Concentrations from the MC2/ISLAS 2021 campaign in Andenes, and NorESM2 simulations with observationally constrained INPs
<p>This dataset containts the data for the article <strong>Using a region-specific ice-nucleating particle parameterization improves the representation of Arctic clouds in a global climate model </strong>(https://doi.org/10.5194/acp-25-1617-2025), published in Atmospheric Chemistry and Physics (ACP). It consists of ice-nucleating particle (INP) measurements collected as part of the MC2/ISLAS campaign in Andenes, Norway (69<em>° </em>18’ N, 16<em>°</em> 07’ E) in 2021. Additionally, it consists of simultaneous aerosol measurements, back trajectories for the INP measurement times, and model data from the Norwegian Earth System model (Seland et al., 2020) where INP concentrations where constrained in the Arctic using these INP measurements. </p> <p><strong>Abstract:</strong></p> <p><em>Projections of global climate change and Arctic amplification are sensitive to the representation of low-level cloud phase in climate models. Ice-nucleating particles (INPs) are necessary for primary cloud ice formation at temperatures above approximately -38 °C, and thus significantly affect cloud phase and cloud radiative effect. Due to their complex and insufficiently understood variability, INPs constitute an important modelling challenge, especially in remote regions with few observations, such as the Arctic. In this study, INP observations were carried out at Andenes, Norway in March 2021. These observations were used as a basis for an Arctic-specific and purely temperature-dependent INP parameterization, and implemented into the Norwegian Earth System Model. This implementation results in an annual average increase in cloud liquid water path (CLWP) of 70 % for the Arctic, and improves the representation of cloud phase compared to satellite observations. The change in CLWP in boreal autumn and winter is found to likely be the dominant contributor to the annual average increase in net surface cloud radiative effect of 2 W m<sup>-2</sup>. This large surface flux increase brings the simulation into better agreement with Arctic ground-based measurements. Despite that the model cannot respond fully to the INP parameterization change due to fixed sea surface temperatures, Arctic surface air temperature increases with 0.7 °C in boreal autumn. These findings indicate that INPs could have a significant impact on Arctic climate, and that a region-specific INP parameterization can be a useful tool to improve cloud representation in the Arctic region.</em></p> <p>The dataset contains three subsets:</p> <p>i) <strong>aerosol_data:</strong> Observations of Ice-Nucleating Particles (INPs) in Andenes, Norway, March 2021, as well as simultaneous aerosol measurements</p> <p>ii) <strong>INP_trajectories: </strong>Back trajectories at the time of INP measurements</p> <p>iii) <strong>model_data: </strong>Simulations with NorESM2 using the Andenes 2021 INP observations to constrain INPs in the Arctic</p> <p>Additionally, scripts for visualizing the data and for reproducing the NorESM2 model setup can be found in the folder <strong>scripts. </strong>The data folders and scripts folder should be in the same repository when running the scripts.</p> <p>Some of the scripts use other openly available datasets. The availability of these are listed below. All the specific datasets can also be provided to the user upon request. </p> <p>The CALIOP L2 data used to derive SLF metrics (used in Fig07.py) and the CERES EBAF data (used in Fig12.py) can be downloaded freely at <a href="https://search.earthdata.nasa.gov/" rel="nofollow">https://search.earthdata.nasa.gov/</a>. The derived SLF metrics can also be found at Bruno (2022), and are also described in Hofer et al. (2024) and Shaw et al. (2022). The CALIPSO-GOCCP data product (used in Fig08.py) can be downloaded from https://climserv.ipsl.polytechnique.fr/cfmip-obs/Calipso_goccp.html. The surface radiation flux (used in Fig13.py) can be downloaded freely at <a href="https://www.pangaea.de/" rel="nofollow">https://www.pangaea.de/</a>. The ERA5 data used to produce the back trajectories can be found at https://doi.org/10.24381/cds.bd0915c6. The colormap from Crameri et al. (2020) was used when preparing the figures. </p> <p>References:</p> <ul> <li>Bruno, O. (2022). Distributions of supercooled liquid fraction from CALIOP V4 [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.8289058" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.8289058</a></li> <li>Crameri, F., Shephard, G.E. & Heron, P.J. The misuse of colour in science communication. <em>Nat Commun</em> <strong>11</strong>, 5444 (2020). https://doi.org/10.1038/s41467-020-19160-7</li> <li>Hofer, S., Hahn, L.C., Shaw, J.K. et al. Realistic representation of mixed-phase clouds increases projected climate warming. Commun Earth Environ 5, 390 (2024). <a href="https://doi.org/10.1038/s43247-024-01524-2" rel="nofollow">https://doi.org/10.1038/s43247-024-01524-2</a></li> <li>Seland, Ø., Bentsen, M., Olivié, D., Toniazzo, T., Gjermundsen, A., Graff, L. S., Debernard, J. B., Gupta, A. K., He, Y.-C., Kirkevåg, A., Schwinger, J., Tjiputra, J., Aas, K. S., Bethke, I., Fan, Y., Griesfeller, J., Grini, A., Guo, C., Ilicak, M., Karset, I. H. H., Landgren, O., Liakka, J., Moseid, K. O., Nummelin, A., Spensberger, C., Tang, H., Zhang, Z., Heinze, C., Iversen, T., and Schulz, M.: Overview of the Norwegian Earth System Model (NorESM2) and key climate response of CMIP6 DECK, historical, and scenario simulations, Geoscientific Model Development, 13, 6165–6200, <a href="https://doi.org/10.5194/gmd-13-6165-2020" rel="nofollow">https://doi.org/10.5194/gmd-13-6165-2020</a>, 2020.</li> <li>Shaw, J., McGraw, Z., Bruno, O., Storelvmo, T., & Hofer, S. (2022). Using satellite observations to evaluate model microphysical representation of Arctic mixed-phase clouds. Geophysical Research Letters, 49, e2021GL096191. <a href="https://doi.org/10.1029/2021GL096191" rel="nofollow">https://doi.org/10.1029/2021GL096191</a></li> </ul>
Importance of high-latitude sources for ice-nucleating particles in cold-air outbreaks and the implications for cloud-phase feedback
<p>This dataset contains FLEXPART results and codes for data analysis and visualization used in the MRes research project. </p> <p>Numpy arrays for FLEXPART data are in "data_flexpart.zip" with longitude and latitude coordination files.</p> <p>Codes for data analysis and visualization are in "ipynb.zip". Codes were written in Python language. Codes are categorized by figures in the article. </p>
Data and code availibility for the paper "Ice-nucleating agents in sea spray aerosol identified and quantified with a holistic multi-modal freezing model" by Alpert et al.
<p>The data and codes used in the paper "Ice-nucleating agents in sea spray aerosol identified and quantified with a holistic multi-modal freezing model" by Alpert et al., published in <em>Science Advances</em> are included in this collection. Detailed descriptions of the files are given in the readme file.</p>
Data and metadata associated with ice-nucleating particles during the 2022 Arctic Cold Air Outbreak Campaign
<p>Data and metadata associated with analysis of ice-nucleating particle concentrations and aerosol-size distributions measured during the March 2022 Arctic Cold Air Outbreak campaign.</p> <p>Contains INP concentrations and aerosol-size normalisations of these, parametrisations of these, SEM data and metadata and backtrajectory modelling inputs and results.</p>
Dataset for manuscript "Gaps in our understanding of ice-nucleating particle sources exposed by global simulation of the UK Earth System Model"
<p>Datasets and Jupyterlab python script for plotting all figures relevant to the mansucript "Gaps in our understanding of ice-nucleating particle sources exposed by global simulation of the UK Earth System Model" by Herbert et al.</p> <p>https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1538/</p> <p>Data needs to be unzipped and paths (input and output) updated in the jupyterlab python script.</p> <p> </p>
A new parameterisation for homogeneous ice nucleation driven by highly variable dynamical forcings
<p>This archive contains the data associated with the preprint of the article <em>"A New Parameterization for Homogeneous Ice Nucleation Driven by Highly Variable Dynamical Forcings."</em> The collection includes datasets used to construct the initial conditions for forcing an air parcel model with ice physics, outputs produced by the parcel model, and data necessary for generating the plots presented in the paper. A README file is provided, offering a detailed explanation of the contents and structure of the archive,</p>
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