Changes
On February 26, 2025 at 3:20:58 PM UTC,
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Deleted resource AWS data from Distributed sub-canopy datasets from mobile multi-sensor platforms (CH / FIN, 2018-2019) for hyper-resolution forest snow model evaluation
f | 1 | { | f | 1 | { |
2 | "author": "[{\"affiliation\": \"WSL Institute for Snow and Avalanche | 2 | "author": "[{\"affiliation\": \"WSL Institute for Snow and Avalanche | ||
3 | Research SLF\", \"affiliation_02\": \"\", \"affiliation_03\": \"\", | 3 | Research SLF\", \"affiliation_02\": \"\", \"affiliation_03\": \"\", | ||
4 | \"data_credit\": [\"collection\", \"curation\", \"publication\"], | 4 | \"data_credit\": [\"collection\", \"curation\", \"publication\"], | ||
5 | \"email\": \"giulia.mazzotti@slf.ch\", \"given_name\": \"Giulia\", | 5 | \"email\": \"giulia.mazzotti@slf.ch\", \"given_name\": \"Giulia\", | ||
6 | \"identifier\": \"0000-0003-3857-7449\", \"name\": \"Mazzotti\"}, | 6 | \"identifier\": \"0000-0003-3857-7449\", \"name\": \"Mazzotti\"}, | ||
7 | {\"affiliation\": \"University of Northumbria\", \"affiliation_02\": | 7 | {\"affiliation\": \"University of Northumbria\", \"affiliation_02\": | ||
8 | \"\", \"affiliation_03\": \"\", \"data_credit\": [\"collection\", | 8 | \"\", \"affiliation_03\": \"\", \"data_credit\": [\"collection\", | ||
9 | \"curation\"], \"email\": \"johanna.malle@northumbria.ac.uk\", | 9 | \"curation\"], \"email\": \"johanna.malle@northumbria.ac.uk\", | ||
10 | \"given_name\": \"Johanna\", \"identifier\": \"0000-0002-6185-6449\", | 10 | \"given_name\": \"Johanna\", \"identifier\": \"0000-0002-6185-6449\", | ||
11 | \"name\": \"Malle\"}, {\"affiliation\": \"WSL Institute for Snow and | 11 | \"name\": \"Malle\"}, {\"affiliation\": \"WSL Institute for Snow and | ||
12 | Avalanche Research SLF\", \"affiliation_02\": \"\", | 12 | Avalanche Research SLF\", \"affiliation_02\": \"\", | ||
13 | \"affiliation_03\": \"\", \"data_credit\": [\"publication\", | 13 | \"affiliation_03\": \"\", \"data_credit\": [\"publication\", | ||
14 | \"supervision\"], \"email\": \"jonas@slf.ch\", \"given_name\": | 14 | \"supervision\"], \"email\": \"jonas@slf.ch\", \"given_name\": | ||
15 | \"Tobias\", \"identifier\": \"0000-0003-0386-8676\", \"name\": | 15 | \"Tobias\", \"identifier\": \"0000-0003-0386-8676\", \"name\": | ||
16 | \"Jonas\"}]", | 16 | \"Jonas\"}]", | ||
17 | "author_email": null, | 17 | "author_email": null, | ||
18 | "creator_user_id": "e0656282-3e6c-40f0-a967-c78d92e9392a", | 18 | "creator_user_id": "e0656282-3e6c-40f0-a967-c78d92e9392a", | ||
19 | "date": "[{\"date\": \"2018-01-01\", \"date_type\": \"collected\", | 19 | "date": "[{\"date\": \"2018-01-01\", \"date_type\": \"collected\", | ||
20 | \"end_date\": \"2019-05-31\"}]", | 20 | \"end_date\": \"2019-05-31\"}]", | ||
21 | "doi": "10.16904/envidat.162", | 21 | "doi": "10.16904/envidat.162", | ||
22 | "funding": "[{\"grant_number\": \"169213\", \"institution\": \"Swiss | 22 | "funding": "[{\"grant_number\": \"169213\", \"institution\": \"Swiss | ||
23 | National Science Foundation SNSF\", \"institution_url\": | 23 | National Science Foundation SNSF\", \"institution_url\": | ||
24 | \"http://www.snf.ch/en/Pages/default.aspx\"}, {\"grant_number\": | 24 | \"http://www.snf.ch/en/Pages/default.aspx\"}, {\"grant_number\": | ||
25 | \"IME4Rad\", \"institution\": \"INTERACT \", \"institution_url\": | 25 | \"IME4Rad\", \"institution\": \"INTERACT \", \"institution_url\": | ||
26 | \"https://eu-interact.org/\"}]", | 26 | \"https://eu-interact.org/\"}]", | ||
27 | "groups": [], | 27 | "groups": [], | ||
28 | "id": "0fb10027-6f49-4953-8683-76fc83ea1154", | 28 | "id": "0fb10027-6f49-4953-8683-76fc83ea1154", | ||
29 | "isopen": false, | 29 | "isopen": false, | ||
30 | "language": "en", | 30 | "language": "en", | ||
31 | "license_id": "wsl-data", | 31 | "license_id": "wsl-data", | ||
32 | "license_title": "WSL Data Policy", | 32 | "license_title": "WSL Data Policy", | ||
33 | "license_url": | 33 | "license_url": | ||
34 | ps://www.wsl.ch/en/about-wsl/programmes-and-initiatives/envidat.html", | 34 | ps://www.wsl.ch/en/about-wsl/programmes-and-initiatives/envidat.html", | ||
35 | "maintainer": "{\"affiliation\": \"WSL Institute for Snow and | 35 | "maintainer": "{\"affiliation\": \"WSL Institute for Snow and | ||
36 | Avalanche Research SLF\", \"email\": \"giulia.mazzotti@slf.ch\", | 36 | Avalanche Research SLF\", \"email\": \"giulia.mazzotti@slf.ch\", | ||
37 | \"given_name\": \"Giulia\", \"identifier\": \"0000-0003-3857-7449\", | 37 | \"given_name\": \"Giulia\", \"identifier\": \"0000-0003-3857-7449\", | ||
38 | \"name\": \"Mazzotti\"}", | 38 | \"name\": \"Mazzotti\"}", | ||
39 | "maintainer_email": null, | 39 | "maintainer_email": null, | ||
40 | "metadata_created": "2020-03-21T15:28:56.838330", | 40 | "metadata_created": "2020-03-21T15:28:56.838330", | ||
n | 41 | "metadata_modified": "2021-08-23T14:22:37.118808", | n | 41 | "metadata_modified": "2025-02-26T15:20:58.848698", |
42 | "name": "distributed-subcanopy-datasets", | 42 | "name": "distributed-subcanopy-datasets", | ||
43 | "notes": "This dataset contains datasets of sub-canopy | 43 | "notes": "This dataset contains datasets of sub-canopy | ||
44 | meteorological variables acquired in coniferous forest stands in | 44 | meteorological variables acquired in coniferous forest stands in | ||
45 | Switzerland (Davos, Engadine) and Finland (Sodankyl\u00e4) during the | 45 | Switzerland (Davos, Engadine) and Finland (Sodankyl\u00e4) during the | ||
46 | winters 2018 and 2019. The data are presented and used in the | 46 | winters 2018 and 2019. The data are presented and used in the | ||
47 | publication: \r\nMazzotti, G., Essery, R., Webster, C., Malle, J., & | 47 | publication: \r\nMazzotti, G., Essery, R., Webster, C., Malle, J., & | ||
48 | Jonas T. (2020)\r\nProcess-level evaluation of a high-resolution | 48 | Jonas T. (2020)\r\nProcess-level evaluation of a high-resolution | ||
49 | forest snow model using observations from mobile multi-sensor | 49 | forest snow model using observations from mobile multi-sensor | ||
50 | platforms \r\nWater Resources Research, under review\r\n\r\nThe above | 50 | platforms \r\nWater Resources Research, under review\r\n\r\nThe above | ||
51 | publication must be cited when using this dataset, and the user is | 51 | publication must be cited when using this dataset, and the user is | ||
52 | referred to the publication for additional detail. \r\n\r\nData are | 52 | referred to the publication for additional detail. \r\n\r\nData are | ||
53 | grouped into 4 folders: \r\n1) Point data includes wind speed data | 53 | grouped into 4 folders: \r\n1) Point data includes wind speed data | ||
54 | measured with stationary meteorological stations\r\n2) Transect data | 54 | measured with stationary meteorological stations\r\n2) Transect data | ||
55 | includes data of incoming short- and longwave radiation, air and snow | 55 | includes data of incoming short- and longwave radiation, air and snow | ||
56 | surface temperature acquired with an automated calblecar system along | 56 | surface temperature acquired with an automated calblecar system along | ||
57 | within-stand transects\r\n3) Grid data includes data of incoming | 57 | within-stand transects\r\n3) Grid data includes data of incoming | ||
58 | short- and longwave radiation, air and snow surface temperature | 58 | short- and longwave radiation, air and snow surface temperature | ||
59 | acquired on 40x40m gridded plots using a handheld instrument, as well | 59 | acquired on 40x40m gridded plots using a handheld instrument, as well | ||
60 | as snow depth data measured at the same grids. \r\n\r\nCanopy | 60 | as snow depth data measured at the same grids. \r\n\r\nCanopy | ||
61 | structure information derived from hemispherical images is included | 61 | structure information derived from hemispherical images is included | ||
62 | for each all surveyed locations as well, and an overview of the field | 62 | for each all surveyed locations as well, and an overview of the field | ||
63 | sites is provided. \r\n\r\n\r\n\r\n\r\n", | 63 | sites is provided. \r\n\r\n\r\n\r\n\r\n", | ||
n | 64 | "num_resources": 5, | n | 64 | "num_resources": 4, |
65 | "num_tags": 5, | 65 | "num_tags": 5, | ||
66 | "organization": { | 66 | "organization": { | ||
67 | "approval_status": "approved", | 67 | "approval_status": "approved", | ||
68 | "created": "2021-08-23T15:25:48.676190", | 68 | "created": "2021-08-23T15:25:48.676190", | ||
69 | "description": "The research group \u00abSnow Hydrology\u00bb | 69 | "description": "The research group \u00abSnow Hydrology\u00bb | ||
70 | investigates snow as a component of the hydrological cycle. In the | 70 | investigates snow as a component of the hydrological cycle. In the | ||
71 | Alps a significant percentage of precipitation comes in the form of | 71 | Alps a significant percentage of precipitation comes in the form of | ||
72 | snow. The timing of snow melt thus influences the annual dynamics of | 72 | snow. The timing of snow melt thus influences the annual dynamics of | ||
73 | runoff from alpine watersheds. Of particular interest for our research | 73 | runoff from alpine watersheds. Of particular interest for our research | ||
74 | is to enhance estimations of snow water resources and subsequent melt | 74 | is to enhance estimations of snow water resources and subsequent melt | ||
75 | water discharge.\r\n\r\nThe research group covers a broad range of | 75 | water discharge.\r\n\r\nThe research group covers a broad range of | ||
76 | projects and methods. The latest measuring techniques are used to | 76 | projects and methods. The latest measuring techniques are used to | ||
77 | investigate snow distribution patterns in alpine terrain, e.g. laser | 77 | investigate snow distribution patterns in alpine terrain, e.g. laser | ||
78 | scanning or radar technology. We use different types of numerical | 78 | scanning or radar technology. We use different types of numerical | ||
79 | models to calculate snow water resources based on input data from | 79 | models to calculate snow water resources based on input data from | ||
80 | meteorological monitoring networks. These models are being used to | 80 | meteorological monitoring networks. These models are being used to | ||
81 | predict the consequences of climate change on the water balance of | 81 | predict the consequences of climate change on the water balance of | ||
82 | mountain watersheds. The models also constitute a valuable tool for | 82 | mountain watersheds. The models also constitute a valuable tool for | ||
83 | our operational services, such as periodic snow hydrological | 83 | our operational services, such as periodic snow hydrological | ||
84 | bulletins, which contribute to the federal flood prevention and | 84 | bulletins, which contribute to the federal flood prevention and | ||
85 | forecasting system.\r\n\r\nThe research group \u00abSnow | 85 | forecasting system.\r\n\r\nThe research group \u00abSnow | ||
86 | Hydrology\u00bb is based in Davos and ensures the link between other | 86 | Hydrology\u00bb is based in Davos and ensures the link between other | ||
87 | Davosian research groups and the research unit \u201dMountain | 87 | Davosian research groups and the research unit \u201dMountain | ||
88 | Hydrology and Mass Movements\u201d in Birmensdorf.", | 88 | Hydrology and Mass Movements\u201d in Birmensdorf.", | ||
89 | "id": "d66115d3-c4f9-4f6e-8ff1-5791549e0386", | 89 | "id": "d66115d3-c4f9-4f6e-8ff1-5791549e0386", | ||
90 | "image_url": "", | 90 | "image_url": "", | ||
91 | "is_organization": true, | 91 | "is_organization": true, | ||
92 | "name": "snow-hydrology", | 92 | "name": "snow-hydrology", | ||
93 | "state": "active", | 93 | "state": "active", | ||
94 | "title": "Snow Hydrology", | 94 | "title": "Snow Hydrology", | ||
95 | "type": "organization" | 95 | "type": "organization" | ||
96 | }, | 96 | }, | ||
97 | "owner_org": "d66115d3-c4f9-4f6e-8ff1-5791549e0386", | 97 | "owner_org": "d66115d3-c4f9-4f6e-8ff1-5791549e0386", | ||
98 | "private": false, | 98 | "private": false, | ||
99 | "publication": "{\"publication_year\": \"2020\", \"publisher\": | 99 | "publication": "{\"publication_year\": \"2020\", \"publisher\": | ||
100 | \"EnviDat\"}", | 100 | \"EnviDat\"}", | ||
101 | "publication_state": "published", | 101 | "publication_state": "published", | ||
102 | "related_datasets": "", | 102 | "related_datasets": "", | ||
103 | "related_publications": "Mazzotti, G., Essery, R., Webster, C., | 103 | "related_publications": "Mazzotti, G., Essery, R., Webster, C., | ||
104 | Malle, J., & Jonas T. (2020)\r\nProcess-level evaluation of a | 104 | Malle, J., & Jonas T. (2020)\r\nProcess-level evaluation of a | ||
105 | high-resolution forest snow model using observations from mobile | 105 | high-resolution forest snow model using observations from mobile | ||
106 | multi-sensor platforms \r\nWater Resources Research, under review", | 106 | multi-sensor platforms \r\nWater Resources Research, under review", | ||
107 | "relationships_as_object": [], | 107 | "relationships_as_object": [], | ||
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109 | "resource_type": "dataset", | 109 | "resource_type": "dataset", | ||
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242 | "restricted": "{\"level\": \"public\", \"allowed_users\": \"\", | ||||
243 | \"shared_secret\": \"\"}", | ||||
244 | "size": null, | ||||
245 | "state": "active", | ||||
246 | "url": "", | ||||
247 | "url_type": null | ||||
248 | } | 222 | } | ||
249 | ], | 223 | ], | ||
250 | "spatial": | 224 | "spatial": | ||
251 | 12646484375,66.85071923380283],[20.01708984375,66.85071923380283]]]}", | 225 | 12646484375,66.85071923380283],[20.01708984375,66.85071923380283]]]}", | ||
252 | "spatial_info": "Switzerland, Finland", | 226 | "spatial_info": "Switzerland, Finland", | ||
253 | "state": "active", | 227 | "state": "active", | ||
254 | "subtitle": "", | 228 | "subtitle": "", | ||
255 | "tags": [ | 229 | "tags": [ | ||
256 | { | 230 | { | ||
257 | "display_name": "FOREST SNOW", | 231 | "display_name": "FOREST SNOW", | ||
258 | "id": "444e598a-05a6-4580-a7f7-320363f2c387", | 232 | "id": "444e598a-05a6-4580-a7f7-320363f2c387", | ||
259 | "name": "FOREST SNOW", | 233 | "name": "FOREST SNOW", | ||
260 | "state": "active", | 234 | "state": "active", | ||
261 | "vocabulary_id": null | 235 | "vocabulary_id": null | ||
262 | }, | 236 | }, | ||
263 | { | 237 | { | ||
264 | "display_name": "FOREST STRUCTURE", | 238 | "display_name": "FOREST STRUCTURE", | ||
265 | "id": "2505c446-1d1a-4885-940d-5672247367c1", | 239 | "id": "2505c446-1d1a-4885-940d-5672247367c1", | ||
266 | "name": "FOREST STRUCTURE", | 240 | "name": "FOREST STRUCTURE", | ||
267 | "state": "active", | 241 | "state": "active", | ||
268 | "vocabulary_id": null | 242 | "vocabulary_id": null | ||
269 | }, | 243 | }, | ||
270 | { | 244 | { | ||
271 | "display_name": "METEOROLOGICAL DATA", | 245 | "display_name": "METEOROLOGICAL DATA", | ||
272 | "id": "63dda86a-7179-4b95-987d-041455f5cb6e", | 246 | "id": "63dda86a-7179-4b95-987d-041455f5cb6e", | ||
273 | "name": "METEOROLOGICAL DATA", | 247 | "name": "METEOROLOGICAL DATA", | ||
274 | "state": "active", | 248 | "state": "active", | ||
275 | "vocabulary_id": null | 249 | "vocabulary_id": null | ||
276 | }, | 250 | }, | ||
277 | { | 251 | { | ||
278 | "display_name": "SNOW ENERGY BALANCE", | 252 | "display_name": "SNOW ENERGY BALANCE", | ||
279 | "id": "a7d36b90-e828-4a1f-b017-bdc27fcdc8cf", | 253 | "id": "a7d36b90-e828-4a1f-b017-bdc27fcdc8cf", | ||
280 | "name": "SNOW ENERGY BALANCE", | 254 | "name": "SNOW ENERGY BALANCE", | ||
281 | "state": "active", | 255 | "state": "active", | ||
282 | "vocabulary_id": null | 256 | "vocabulary_id": null | ||
283 | }, | 257 | }, | ||
284 | { | 258 | { | ||
285 | "display_name": "SNOW MODELS", | 259 | "display_name": "SNOW MODELS", | ||
286 | "id": "ed98ff87-fd78-4730-8748-95b8d33002bc", | 260 | "id": "ed98ff87-fd78-4730-8748-95b8d33002bc", | ||
287 | "name": "SNOW MODELS", | 261 | "name": "SNOW MODELS", | ||
288 | "state": "active", | 262 | "state": "active", | ||
289 | "vocabulary_id": null | 263 | "vocabulary_id": null | ||
290 | } | 264 | } | ||
291 | ], | 265 | ], | ||
292 | "title": "Distributed sub-canopy datasets from mobile multi-sensor | 266 | "title": "Distributed sub-canopy datasets from mobile multi-sensor | ||
293 | platforms (CH / FIN, 2018-2019) for hyper-resolution forest snow model | 267 | platforms (CH / FIN, 2018-2019) for hyper-resolution forest snow model | ||
294 | evaluation", | 268 | evaluation", | ||
295 | "type": "dataset", | 269 | "type": "dataset", | ||
296 | "url": null, | 270 | "url": null, | ||
297 | "version": "1.0" | 271 | "version": "1.0" | ||
298 | } | 272 | } |