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  "author": "[{\"affiliation\": \"Alfred-Wegener-Institut 
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  "author": "[{\"affiliation\": \"Alfred-Wegener-Institut 
            
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Helmholtz-Zentrum f\\u00fcr Polar- und Meeresforschung\", 
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Helmholtz-Zentrum f\\u00fcr Polar- und Meeresforschung\", 
            
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\"affiliation_02\": \"WSL Institute for Snow and Avalanche Research 
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\"affiliation_02\": \"WSL Institute for Snow and Avalanche Research 
            
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SLF\", \"affiliation_03\": \"\", \"data_credit\": [\"collection\", 
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SLF\", \"affiliation_03\": \"\", \"data_credit\": [\"collection\", 
            
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\"supervision\"], \"email\": \"julia.martin@awi.de\", \"given_name\": 
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\"supervision\"], \"email\": \"julia.martin@awi.de\", \"given_name\": 
            
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\"Julia\", \"identifier\": \"0000-0002-5336-9245\", \"name\": 
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\"Julia\", \"identifier\": \"0000-0002-5336-9245\", \"name\": 
            
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\"Martin\"}, {\"affiliation\": \"WSL Institute for Snow and Avalanche 
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\"Martin\"}, {\"affiliation\": \"WSL Institute for Snow and Avalanche 
            
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Research SLF, Davos Dorf, Switzerland\", \"affiliation_02\": \"SLF\", 
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Research SLF, Davos Dorf, Switzerland\", \"affiliation_02\": \"SLF\", 
            
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\"affiliation_03\": \"\", \"data_credit\": [\"collection\", 
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\"affiliation_03\": \"\", \"data_credit\": [\"collection\", 
            
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\"validation\", \"publication\", \"supervision\"], \"email\": 
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\"validation\", \"publication\", \"supervision\"], \"email\": 
            
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\"schneebeli@slf.ch\", \"given_name\": \"Martin\", \"identifier\": 
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\"schneebeli@slf.ch\", \"given_name\": \"Martin\", \"identifier\": 
            
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\"0000-0003-2872-4409\", \"name\": \"Schneebeli\"}]",
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\"0000-0003-2872-4409\", \"name\": \"Schneebeli\"}]",
            
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  "date": "[{\"date\": \"2018-01-01\", \"date_type\": \"collected\", 
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  "date": "[{\"date\": \"2018-01-01\", \"date_type\": \"collected\", 
            
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\"end_date\": \"2019-12-31\"}]",
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\"end_date\": \"2019-12-31\"}]",
            
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  "doi": "10.16904/envidat.333",
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  "doi": "10.16904/envidat.333",
            
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  "funding": "[{\"grant_number\": \"\", \"institution\": \"WSL 
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Institute for Snow and Avalanche Research SLF\", \"institution_url\": 
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Institute for Snow and Avalanche Research SLF\", \"institution_url\": 
            
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\"\"}]",
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  "license_title": "Creative Commons Zero - No Rights Reserved (CC0 
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  "license_title": "Creative Commons Zero - No Rights Reserved (CC0 
            
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1.0)",
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  "maintainer": "{\"affiliation\": \"Alfred-Wegener-Institut 
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  "maintainer": "{\"affiliation\": \"Alfred-Wegener-Institut 
            
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Helmholtz-Zentrum f\u00fcr Polar- und Meeresforschung\", \"email\": 
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Helmholtz-Zentrum f\u00fcr Polar- und Meeresforschung\", \"email\": 
            
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\"julia.martin@awi.de\", \"given_name\": \"Julia\", \"identifier\": 
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\"julia.martin@awi.de\", \"given_name\": \"Julia\", \"identifier\": 
            
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\"\", \"name\": \"Martin\"}",
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\"\", \"name\": \"Martin\"}",
            
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  "metadata_modified": "2023-02-19T04:42:58.651465",
            
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  "name": "icecube_microct_snow_grainsize",
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  "name": "icecube_microct_snow_grainsize",
            
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  "notes": "The specific surface area (SSA) of different snow types 
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  "notes": "The specific surface area (SSA) of different snow types 
            
40
were measured with the IceCube instrument and the Scanco Medical 
40
were measured with the IceCube instrument and the Scanco Medical 
            
41
microCT 40. In addition, the snow particles created during the 
41
microCT 40. In addition, the snow particles created during the 
            
42
preparation of IceCube samples were counted. The difference in SSA 
42
preparation of IceCube samples were counted. The difference in SSA 
            
43
between these instruments is explained by the formation of the surface 
43
between these instruments is explained by the formation of the surface 
            
44
particles. A numerical simulation using TARTES simulation support the 
44
particles. A numerical simulation using TARTES simulation support the 
            
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observations.",
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observations.",
            
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  "num_resources": 8,
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  "num_resources": 8,
            
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  "num_tags": 5,
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  "num_tags": 5,
            
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  "organization": {
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  "organization": {
            
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    "approval_status": "approved",
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    "approval_status": "approved",
            
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    "created": "2018-11-15T15:22:01.175490",
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    "created": "2018-11-15T15:22:01.175490",
            
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    "description": "The Research Unit investigates the physical 
51
    "description": "The Research Unit investigates the physical 
            
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properties of snow and its exchange processes with the soil and 
52
properties of snow and its exchange processes with the soil and 
            
53
atmosphere. The aim is to understand the formation of alpine natural 
53
atmosphere. The aim is to understand the formation of alpine natural 
            
54
hazards such as avalanches, floods and slope instabilities and of the 
54
hazards such as avalanches, floods and slope instabilities and of the 
            
55
interactions between the cryosphere and climate change. To this end, 
55
interactions between the cryosphere and climate change. To this end, 
            
56
the unit also studies the microstructure and metamorphism of 
56
the unit also studies the microstructure and metamorphism of 
            
57
snow.\r\n\r\nOur research is an essential basis for understanding the 
57
snow.\r\n\r\nOur research is an essential basis for understanding the 
            
58
macro-level changes in the snowpack, as avalanche formation, water 
58
macro-level changes in the snowpack, as avalanche formation, water 
            
59
transport in the snowpack and interactions of snow with vehicles and 
59
transport in the snowpack and interactions of snow with vehicles and 
            
60
sports equipment. This makes it possible to find out what role snow 
60
sports equipment. This makes it possible to find out what role snow 
            
61
and wet or frozen ground play in the formation of natural hazards, how 
61
and wet or frozen ground play in the formation of natural hazards, how 
            
62
they influence the Earth's climate and how global climate change 
62
they influence the Earth's climate and how global climate change 
            
63
affects the permafrost formation.\r\n\r\nThe experiments in this unit 
63
affects the permafrost formation.\r\n\r\nThe experiments in this unit 
            
64
take place in laboratories (cold labs, computer tomograph, wind 
64
take place in laboratories (cold labs, computer tomograph, wind 
            
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tunnel) and on test areas in the field. The results flow into the 
65
tunnel) and on test areas in the field. The results flow into the 
            
66
development of numerical model systems that are applied in climate 
66
development of numerical model systems that are applied in climate 
            
67
analysis and natural hazard warning. We regularly supply snow 
67
analysis and natural hazard warning. We regularly supply snow 
            
68
hydrological analyses to the responsible offices at the Federal Office 
68
hydrological analyses to the responsible offices at the Federal Office 
            
69
for the Environment (FOEN) to prevent and predict flood situations 
69
for the Environment (FOEN) to prevent and predict flood situations 
            
70
during snowmelt.\r\n\r\nThe research unit works with partners within 
70
during snowmelt.\r\n\r\nThe research unit works with partners within 
            
71
WSL, with research institutions in cryosphere research, with partners 
71
WSL, with research institutions in cryosphere research, with partners 
            
72
in the field of high-performance computing and model development, as 
72
in the field of high-performance computing and model development, as 
            
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well as with warning and local safety services and industry.",
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well as with warning and local safety services and industry.",
            
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    "image_url": 
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    "image_url": 
            
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    "is_organization": true,
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    "is_organization": true,
            
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    "name": "snow-and-atmo",
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    "name": "snow-and-atmo",
            
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    "state": "active",
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    "state": "active",
            
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    "title": "Snow and Atmosphere",
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    "title": "Snow and Atmosphere",
            
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    "type": "organization"
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    "type": "organization"
            
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  },
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  },
            
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  "private": false,
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  "publication": "{\"publication_year\": \"2022\", \"publisher\": 
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  "publication": "{\"publication_year\": \"2022\", \"publisher\": 
            
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\"EnviDat\"}",
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\"EnviDat\"}",
            
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  "publication_state": "published",
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  "publication_state": "published",
            
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  "related_datasets": "",
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  "related_datasets": "",
            
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  "related_publications": "",
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  "related_publications": "",
            
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  "relationships_as_object": [],
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  "relationships_as_object": [],
            
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  "relationships_as_subject": [],
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  "relationships_as_subject": [],
            
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  "resource_type": "dataset",
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  "resource_type": "dataset",
            
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  "resource_type_general": "dataset",
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      "description": "The file contains all micro-CT and IC 
            
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measurements for snow types A, B, C, D and E used in our study. All 
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measurements for snow types A, B, C, D and E used in our study. All 
            
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samples were processed (and stored)  in a cold laboratory at 
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samples were processed (and stored)  in a cold laboratory at 
            
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-15\u00b0C. ",
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artificial particles for snow types A, B, C, D and E, including the 
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artificial particle mass in the Petri dish.",
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figure 1 of the co-located density and SSA measurement at Summit, 
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Greenland in May 2015, conducted by Schneebeli, Proksch, Schmid.",
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Greenland in May 2015, conducted by Schneebeli, Proksch, Schmid.",
            
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originally produced to investigate the influence of black carbon on 
            
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D. ",
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      "description": "These experiments investigate different possible 
            
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307
errors by measuring the specific surface area (SSA) of snow with the 
            
308
near infrared method. The influence of black carbon on this 
308
near infrared method. The influence of black carbon on this 
            
309
measurement was disproved, the theory was therefore validated. It 
309
measurement was disproved, the theory was therefore validated. It 
            
310
shows that sunlight has no influence on the measurement with the 
310
shows that sunlight has no influence on the measurement with the 
            
311
IceCube. Wind drift snow as thin layer on the sample can increase the 
311
IceCube. Wind drift snow as thin layer on the sample can increase the 
            
312
measured value of the specific surface by a few percent. This could be 
312
measured value of the specific surface by a few percent. This could be 
            
313
part of the error, observed in former measurements at SLF. As 
313
part of the error, observed in former measurements at SLF. As 
            
314
reference for the measured SSA values with the near infrared method, 
314
reference for the measured SSA values with the near infrared method, 
            
315
computer tomography was used to verify the SSA values.",
315
computer tomography was used to verify the SSA values.",
            
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specific surface of snow with the near infrared method - Philipp 
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      "id": "5981533d-0247-484c-b2d6-1a96eda26df6",
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      "id": "5981533d-0247-484c-b2d6-1a96eda26df6",
            
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      "name": "INTERCOMPARISON",
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      "name": "INTERCOMPARISON",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "MICROCT",
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      "display_name": "MICROCT",
            
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      "id": "541f3d66-a3fb-401f-9f14-34e72a38517b",
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      "id": "541f3d66-a3fb-401f-9f14-34e72a38517b",
            
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      "name": "MICROCT",
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      "name": "MICROCT",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "SNOW",
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      "display_name": "SNOW",
            
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      "id": "c4e9ea3f-6149-45ce-8631-c872b96a9537",
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      "id": "c4e9ea3f-6149-45ce-8631-c872b96a9537",
            
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      "name": "SNOW",
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      "name": "SNOW",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
375
    },
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    },
            
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    {
376
    {
            
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      "display_name": "SPECIFIC SURFACE AREA",
377
      "display_name": "SPECIFIC SURFACE AREA",
            
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      "id": "428df482-f861-4da3-99ff-0f1a9824ccfa",
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      "id": "428df482-f861-4da3-99ff-0f1a9824ccfa",
            
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      "name": "SPECIFIC SURFACE AREA",
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      "name": "SPECIFIC SURFACE AREA",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    }
382
    }
            
383
  ],
383
  ],
            
384
  "title": "IceCube_microCT_Snow_grainsize",
384
  "title": "IceCube_microCT_Snow_grainsize",
            
385
  "type": "dataset",
385
  "type": "dataset",
            
386
  "url": null,
386
  "url": null,
            
387
  "version": "1.0"
387
  "version": "1.0"
            
388
}
388
}