cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25378/janelia.24256111
title: Manual organelle segmentations (crop234) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of Interphase COS-7 cell (jrc_cos7-1a)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of extracellular space, plasma membrane, mitochondrial membrane, mitochondrial lumen, vesicle membrane, endosome membrane, vesicle lumen, endoplasmic reticulum lumen, endoplasmic reticulum membrane, lysosome lumen, lysosome membrane, endosome lumen, microtubule out, microtubule in, cytosol, lysosome, endosome, vesicle, mitochondria, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective in jrc_cos7-1a using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop234<b>Primary Annotator</b>: Alyson Petruncio<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Annotated data dimensions (µm)</b>: 0.8 x 0.8 x 0.8 (x, y, z)<b>Annotated data offset (nm)</b>: 10670 x 5160 x 2760 (x, y, z)<b>Classes annotated</b>: extracellular space, plasma membrane, mitochondrial membrane, mitochondrial lumen, vesicle membrane, endosome membrane, vesicle lumen, endoplasmic reticulum lumen, endoplasmic reticulum membrane, lysosome lumen, lysosome membrane, endosome lumen, microtubule out, microtubule in, cytosol, lysosome, endosome, vesicle, mitochondria, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_cos7-1a/jrc_cos7-1a.zarr/recon-1/labels/groundtruth/crop234<b>Source (EM) dataset ID</b>: jrc_cos7-1a<b>Source (EM) voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 41.22 x 8.74 x 3.63 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.24943716<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_cos7-1a<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.
DOI: 10.25378/janelia.24256111.v1
title: Manual organelle segmentations (crop234) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of Interphase COS-7 cell (jrc_cos7-1a)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of extracellular space, plasma membrane, mitochondrial membrane, mitochondrial lumen, vesicle membrane, endosome membrane, vesicle lumen, endoplasmic reticulum lumen, endoplasmic reticulum membrane, lysosome lumen, lysosome membrane, endosome lumen, microtubule out, microtubule in, cytosol, lysosome, endosome, vesicle, mitochondria, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective in jrc_cos7-1a using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop234<b>Primary Annotator</b>: Alyson Petruncio<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Annotated data dimensions (µm)</b>: 0.8 x 0.8 x 0.8 (x, y, z)<b>Annotated data offset (nm)</b>: 10670 x 5160 x 2760 (x, y, z)<b>Classes annotated</b>: extracellular space, plasma membrane, mitochondrial membrane, mitochondrial lumen, vesicle membrane, endosome membrane, vesicle lumen, endoplasmic reticulum lumen, endoplasmic reticulum membrane, lysosome lumen, lysosome membrane, endosome lumen, microtubule out, microtubule in, cytosol, lysosome, endosome, vesicle, mitochondria, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_cos7-1a/jrc_cos7-1a.zarr/recon-1/labels/groundtruth/crop234<b>Source (EM) dataset ID</b>: jrc_cos7-1a<b>Source (EM) voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 41.22 x 8.74 x 3.63 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.24943716<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_cos7-1a<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.
DOI: 10.25378/janelia.24260971
title: Manual organelle segmentations (crop291) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of interphase COS-7 cell (jrc_cos7-1b)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of extracellular space, plasma membrane, mitochondrial membrane, mitochondrial lumen, vesicle membrane, endosome membrane, vesicle lumen, endoplasmic reticulum lumen, endoplasmic reticulum membrane, endosome lumen, microtubule out, microtubule in, cytosol, endosome, vesicle, mitochondria, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective in jrc_cos7-1b using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop291<b>Primary Annotator</b>: Woohyun Park<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Annotated data dimensions (µm)</b>: 0.8 x 0.8 x 0.8 (x, y, z)<br><br><b>Annotated data offset (nm)</b>: 11480 x 5302 x 702 (x, y, z)<b>Classes annotated</b>: extracellular space, plasma membrane, mitochondrial membrane, mitochondrial lumen, vesicle membrane, endosome membrane, vesicle lumen, endoplasmic reticulum lumen, endoplasmic reticulum membrane, endosome lumen, microtubule out, microtubule in, cytosol, endosome, vesicle, mitochondria, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_cos7-1b/jrc_cos7-1b.zarr/recon-1/labels/groundtruth/crop291<b>Source (EM) dataset ID</b>: jrc_cos7-1b<b>Source (EM) voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 40.69 x 9.05 x 2.23 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.24944601<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_cos7-1b<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.
DOI: 10.25378/janelia.24260971.v1
title: Manual organelle segmentations (crop291) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of interphase COS-7 cell (jrc_cos7-1b)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of extracellular space, plasma membrane, mitochondrial membrane, mitochondrial lumen, vesicle membrane, endosome membrane, vesicle lumen, endoplasmic reticulum lumen, endoplasmic reticulum membrane, endosome lumen, microtubule out, microtubule in, cytosol, endosome, vesicle, mitochondria, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective in jrc_cos7-1b using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop291<b>Primary Annotator</b>: Woohyun Park<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Annotated data dimensions (µm)</b>: 0.8 x 0.8 x 0.8 (x, y, z)<br><br><b>Annotated data offset (nm)</b>: 11480 x 5302 x 702 (x, y, z)<b>Classes annotated</b>: extracellular space, plasma membrane, mitochondrial membrane, mitochondrial lumen, vesicle membrane, endosome membrane, vesicle lumen, endoplasmic reticulum lumen, endoplasmic reticulum membrane, endosome lumen, microtubule out, microtubule in, cytosol, endosome, vesicle, mitochondria, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_cos7-1b/jrc_cos7-1b.zarr/recon-1/labels/groundtruth/crop291<b>Source (EM) dataset ID</b>: jrc_cos7-1b<b>Source (EM) voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 40.69 x 9.05 x 2.23 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.24944601<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_cos7-1b<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.
DOI: 10.25326/219
title: SAFIRE ATR42: PMA/2D-S dataset

description: The 2D-S cloud microphysics dataset contains microphysics in situ measurements gathered during EUREC4A field campaign with a 2D-Stereo (2D-S) probe installed on the SAFIRE ATR-42 (right-hand underwing pod). The dataset contains one file per flight, 19 files in total.
The 2D-S is an Optical Array Probe that images cloud, drizzle and rain particles in the 10-1280 µm size range (nominal, extended to 2.56 mm in post-processing) onto a linear array of 128 photodiodes with a resolution of 10 µm. The silhouette of each particle crossing the sample area (laser sheet) is reconstructed and recorded as a black and white image by the probe. 
The retrieval of particles' geometrical descriptors (size, area, perimeter, ...) from the 2D images is done in post-processing, once most artifacts are corrected (noisy pixel and shattering/splashing event removal, size correction for out-of-focus particles : see process level description field). 

The concentrations in the first bins (e.g. up to 30 µm) is a topic of active debate as counts resulting from spurious detection (e.g. noisy pixel) amplified by the shallow depth of field may yield overestimated concentrations.

Available microphysical parameters are Particle Size Distribution (PSD), Total concentration (NT) and Liquid Water Content (LWC, assuming particles are spherical with a density of 1g/cm3 ), given at a frequency of 1 Hz. Data acquisition was synchronized with the ATR-42 GPS synchronized clock and the data is geolocalized using aircraft position.
DOI: 10.25378/janelia.24260752
title: Manual organelle segmentations (crop259) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of interphase COS-7 cell (jrc_cos7-1b)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of extracellular space, plasma membrane, vesicle membrane, endosome membrane, vesicle lumen, endoplasmic reticulum exit site lumen, endoplasmic reticulum exit site membrane, endoplasmic reticulum lumen, endoplasmic reticulum membrane, endosome lumen, microtubule out, microtubule in, cytosol, endosome, vesicle, endoplasmic reticulum exit site, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective in jrc_cos7-1b using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop259<b>Primary Annotator</b>: Diana Ramirez<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Annotated data dimensions (µm)</b>: 0.8 x 0.8 x 0.8 (x, y, z)<b>Annotated data offset (nm)</b>: 9300 x 4608 x 248 (x, y, z)<b>Classes annotated</b>: extracellular space, plasma membrane, vesicle membrane, endosome membrane, vesicle lumen, endoplasmic reticulum exit site lumen, endoplasmic reticulum exit site membrane, endoplasmic reticulum lumen, endoplasmic reticulum membrane, endosome lumen, microtubule out, microtubule in, cytosol, endosome, vesicle, endoplasmic reticulum exit site, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_cos7-1b/jrc_cos7-1b.zarr/recon-1/labels/groundtruth/crop259<b>Source (EM) dataset ID</b>: jrc_cos7-1b<b>Source (EM) voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 40.69 x 9.05 x 2.23 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.24944601<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_cos7-1b<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.
DOI: 10.25378/janelia.24260752.v1
title: Manual organelle segmentations (crop259) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of interphase COS-7 cell (jrc_cos7-1b)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of extracellular space, plasma membrane, vesicle membrane, endosome membrane, vesicle lumen, endoplasmic reticulum exit site lumen, endoplasmic reticulum exit site membrane, endoplasmic reticulum lumen, endoplasmic reticulum membrane, endosome lumen, microtubule out, microtubule in, cytosol, endosome, vesicle, endoplasmic reticulum exit site, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective in jrc_cos7-1b using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop259<b>Primary Annotator</b>: Diana Ramirez<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Annotated data dimensions (µm)</b>: 0.8 x 0.8 x 0.8 (x, y, z)<b>Annotated data offset (nm)</b>: 9300 x 4608 x 248 (x, y, z)<b>Classes annotated</b>: extracellular space, plasma membrane, vesicle membrane, endosome membrane, vesicle lumen, endoplasmic reticulum exit site lumen, endoplasmic reticulum exit site membrane, endoplasmic reticulum lumen, endoplasmic reticulum membrane, endosome lumen, microtubule out, microtubule in, cytosol, endosome, vesicle, endoplasmic reticulum exit site, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_cos7-1b/jrc_cos7-1b.zarr/recon-1/labels/groundtruth/crop259<b>Source (EM) dataset ID</b>: jrc_cos7-1b<b>Source (EM) voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 40.69 x 9.05 x 2.23 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.24944601<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_cos7-1b<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.
DOI: 10.25326/297
title: SAFIRE ATR42: CAMERA dataset

description: The CAMERA dataset contains high resolution images acquired during the EUREC4A campain.
Two sets of images are available.
The WINDOW images correspond to high frequency images (10 frames per second) acquired through the ATR window on the side of
the horizontally-staring lidar and radar instruments. The resolution of the images is 1936 × 1456 pixels and a wide angle lens
having a 4.8 mm focal length was used.
The DOWN images correspond to the downward images acquired with at a moderate frequency (1 frame per second). The resolution of the images are 2048 × 1088 pixels.
Each set of images are classified by fly number directory and fly pattern (R ou L pattern) directory described in the YAML files.

Additionally to visualize quickly the fly, avi movie are available in the fly number directory.
DOI: 10.25326/220
title: SAFIRE ATR42: UHSAS dataset

description: The UHSAS aerosol dataset contains microphysics in situ measurements gathered during EUREC4A field campaign with a UHSAS-A (airborne version) probe installed on the SAFIRE ATR-42 (lower left-hand pod on the fuselage section). 
The dataset contains one file per flight, 19 files in total.
The UHSAS is an optical-scattering aerosol particle spectrometer commercialized by Droplet Measurement Technologies (DMT). 
It sizes and counts particles in the 0.06 – 1 µm range and sorts them into 99 size bins. 
The working principle is as follows: external air is drawn at a controled sample flow rate (about 50 sccm) through an inlet into the instrument body where it intersects a laser beam (Nd3+:Y LiF4 laser @ 1064 nm). 
The light scattered by each aerosol particle is collected by two pairs of Mangin collection optics and measured with a dual Avalanche photodiode/low-gain PIN photodiode detection system.  
The size of each particle is derived from the measured scattered intensity using the Rayleigh (40-300nm) or Mie (300-1000nm) scattering models.


Available parameters are Particle Size Distribution (PSD), Total concentration (NT), given at a frequency of 1 Hz. 
Data acquisition was synchronized with the ATR-42 GPS synchronised clock and the data is geolocated using aircraft position.
DOI: 10.25326/209
title: SAFIRE ATR42: PMA/CDP-2 dataset

description: The CDP-2 cloud microphysics dataset contains microphysics in situ measurements gathered during EUREC4A field campaign with a CDP-2 installed on the SAFIRE ATR-42 (left-hand underwing pod).
The CDP-2 is a cloud particle spectrometer that counts and sizes cloud droplets in the 2-50 micrometer range into 30 size classes with a resolution of 1 to 2 µm. 
The raw data (counts per second) is processed using DMT built-in sizing & counting algorithms. The probe sample volume is calculated using the true TAS (ATR-42 Core measurements) and calibrated sample area (measured at LaMP facility in 12/2019).
The dataset contains one file per flight, 19 files in total. 
Measurements in the sub cloud layer reveal that the CDP-2 reponds to non-cloud droplet particles, e.g. large/ultra large aerosols. These particles may not satisfy the underlying assumption made in CDP-2 sizing algorithms (particles scatter light as spherical liquid water particles with an index of refraction of 1.33).
In the CDP-2 files, a choice was made not to filter out the measurements taken in non-cloudy area so that further investigations on large aerosols may be conducted, at least qualitatively. However, the CDP-2 response to such aerosol particles is unknown, therefore data taken in non-cloudy area is prone to unquantified errors.  
Available parameters are Particle Size Distribution (PSD), Total concentration (NT) and Liquid Water Content (LWC, assuming particles are spherical with a density of 1g/cm3 ), given at a frequency of 1 Hz. 
Data acquisition was synchronized with the ATR-42 GPS synchronised clock and the data is geolocated using aircraft position.