Changes
On October 4, 2022 at 7:05:00 AM UTC,
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Updated description of Quantifying Surface Heat Exchange over Heterogeneous Land Surfaces at Ultra-High Spatio-Temporal Resolution from
We present a novel method for quantifying surface heat exchange over heterogeneous land surfaces at ultra-high spatio-temporal resolution. Therefore, a thermal infrared camera records 30Hz sequences of infrared frames of upright screens, that are deployed across the transition from bare ground to snow. The screen's surface temperature serves as a proxy for the local air temperature. In addition to information on the stratification of the near-surface atmospheric layer, estimations of the 2D wind field can be obtained evaluating the temperature dynamics. Here you find the data and the documented code used to create the plots in the publication.
toThe lateral transport of heat above abrupt (sub-)metre-scale steps in land surface temperature influences the local surface energy balance. We present a novel experimental method to investigate the stratification and dynamics of the near-surface atmospheric layer over a heterogeneous land surface. Using a high resolution thermal infrared camera pointing at synthetic screens, a 30Hz sequence of frames is recorded. The screens are deployed upright and horizontally aligned with the prevailing wind direction. The screen’s surface temperature serves as a proxy for the local air temperature. We developed a method to estimate near-surface two-dimensional wind fields at centimetre resolution from tracking the air temperature pattern on the screens. Wind field estimations are validated with near-surface three-dimensional short-path ultrasonic data. To demonstrate the capabilities of the screen method, we present results from a comprehensive field campaign at an alpine research site during patchy snow cover conditions. The measurements reveal an extremely heterogeneous near-surface atmospheric layer. Vertical profiles of horizontal and vertical wind speed reflect multiple layers of different static stability within 2m above the surface. A dynamic, thin stable internal boundary layer (SIBL) develops above the leading edge of snow patches protecting the snow surface from warmer air above. During pronounced gusts the warm air from aloft entrains into the SIBL and reaches down to the snow surface adding energy to the snow pack. Measured vertical turbulent sensible heat fluxes are shown to be consistent with air temperature and wind speed profiles obtained using the screen method and confirm its capabilities to investigate complex in situ near-surface heat exchange processes. Here you find the data and the documented code used to create the plots in the publication.
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Changed value of field
related_publications
toA Novel Method to Quantify Near-Surface Boundary-Layer Dynamics at Ultra-High Spatio-Temporal Resolution; accepted for publication in Boundary-Layer Meteorology
in Quantifying Surface Heat Exchange over Heterogeneous Land Surfaces at Ultra-High Spatio-Temporal Resolution
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5 | \"michael.haugeneder@slf.ch\", \"given_name\": \"Michael\", | 5 | \"michael.haugeneder@slf.ch\", \"given_name\": \"Michael\", | ||
6 | \"identifier\": \"0000-0003-3228-9868\", \"name\": \"Haugeneder\"}, | 6 | \"identifier\": \"0000-0003-3228-9868\", \"name\": \"Haugeneder\"}, | ||
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18 | "date": "[{\"date\": \"2021-04-28\", \"date_type\": \"collected\", | 18 | "date": "[{\"date\": \"2021-04-28\", \"date_type\": \"collected\", | ||
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20 | "doi": "10.16904/envidat.299", | 20 | "doi": "10.16904/envidat.299", | ||
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28 | "license_title": "WSL Data Policy", | 28 | "license_title": "WSL Data Policy", | ||
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33 | \"identifier\": \"0000-0003-3228-9868\", \"name\": \"Haugeneder\"}", | 33 | \"identifier\": \"0000-0003-3228-9868\", \"name\": \"Haugeneder\"}", | ||
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35 | "metadata_created": "2022-02-24T16:15:53.573278", | 35 | "metadata_created": "2022-02-24T16:15:53.573278", | ||
n | 36 | "metadata_modified": "2022-05-16T11:45:05.118395", | n | 36 | "metadata_modified": "2022-10-04T07:05:00.002285", |
37 | "name": "weird", | 37 | "name": "weird", | ||
n | 38 | "notes": "We present a novel method for quantifying surface heat | n | 38 | "notes": "The lateral transport of heat above abrupt |
39 | exchange over heterogeneous land surfaces at ultra-high | 39 | (sub-)metre-scale steps in land surface temperature influences the | ||
40 | spatio-temporal resolution. Therefore, a thermal infrared camera | 40 | local surface energy balance. We present a novel experimental method | ||
41 | records 30Hz sequences of infrared frames of upright screens, that are | 41 | to investigate the stratification and dynamics of the near-surface | ||
42 | deployed across the transition from bare ground to snow. The screen's | 42 | atmospheric layer over a heterogeneous land surface. Using a high | ||
43 | resolution thermal infrared camera pointing at synthetic screens, a | ||||
44 | 30Hz sequence of frames is recorded. The screens are deployed upright | ||||
45 | and horizontally aligned with the prevailing wind direction. The | ||||
43 | surface temperature serves as a proxy for the local air temperature. | 46 | screen\u2019s surface temperature serves as a proxy for the local air | ||
44 | In addition to information on the stratification of the near-surface | 47 | temperature. We developed a method to estimate near-surface | ||
45 | atmospheric layer, estimations of the 2D wind field can be obtained | 48 | two-dimensional wind fields at centimetre resolution from tracking the | ||
46 | evaluating the temperature dynamics.\r\nHere you find the data and the | 49 | air temperature pattern on the screens. Wind field estimations are | ||
50 | validated with near-surface three-dimensional short-path ultrasonic | ||||
51 | data. To demonstrate the capabilities of the screen method, we present | ||||
52 | results from a comprehensive field campaign at an alpine research site | ||||
53 | during patchy snow cover conditions. The measurements reveal an | ||||
54 | extremely heterogeneous near-surface atmospheric layer. Vertical | ||||
55 | profiles of horizontal and vertical wind speed reflect multiple layers | ||||
56 | of different static stability within 2m above the surface. A dynamic, | ||||
57 | thin stable internal boundary layer (SIBL) develops above the leading | ||||
58 | edge of snow patches protecting the snow surface from warmer air | ||||
59 | above. During pronounced gusts the warm air from aloft entrains into | ||||
60 | the SIBL and reaches down to the snow surface adding energy to the | ||||
61 | snow pack. Measured vertical turbulent sensible heat fluxes are shown | ||||
62 | to be consistent with air temperature and wind speed profiles obtained | ||||
63 | using the screen method and confirm its capabilities to investigate | ||||
64 | complex in situ near-surface heat exchange processes.\r\nHere you find | ||||
47 | documented code used to create the plots in the publication.", | 65 | the data and the documented code used to create the plots in the | ||
66 | publication.", | ||||
48 | "num_resources": 3, | 67 | "num_resources": 3, | ||
49 | "num_tags": 8, | 68 | "num_tags": 8, | ||
50 | "organization": { | 69 | "organization": { | ||
51 | "approval_status": "approved", | 70 | "approval_status": "approved", | ||
52 | "created": "2021-08-23T15:25:48.676190", | 71 | "created": "2021-08-23T15:25:48.676190", | ||
53 | "description": "The research group \u00abSnow Hydrology\u00bb | 72 | "description": "The research group \u00abSnow Hydrology\u00bb | ||
54 | investigates snow as a component of the hydrological cycle. In the | 73 | investigates snow as a component of the hydrological cycle. In the | ||
55 | Alps a significant percentage of precipitation comes in the form of | 74 | Alps a significant percentage of precipitation comes in the form of | ||
56 | snow. The timing of snow melt thus influences the annual dynamics of | 75 | snow. The timing of snow melt thus influences the annual dynamics of | ||
57 | runoff from alpine watersheds. Of particular interest for our research | 76 | runoff from alpine watersheds. Of particular interest for our research | ||
58 | is to enhance estimations of snow water resources and subsequent melt | 77 | is to enhance estimations of snow water resources and subsequent melt | ||
59 | water discharge.\r\n\r\nThe research group covers a broad range of | 78 | water discharge.\r\n\r\nThe research group covers a broad range of | ||
60 | projects and methods. The latest measuring techniques are used to | 79 | projects and methods. The latest measuring techniques are used to | ||
61 | investigate snow distribution patterns in alpine terrain, e.g. laser | 80 | investigate snow distribution patterns in alpine terrain, e.g. laser | ||
62 | scanning or radar technology. We use different types of numerical | 81 | scanning or radar technology. We use different types of numerical | ||
63 | models to calculate snow water resources based on input data from | 82 | models to calculate snow water resources based on input data from | ||
64 | meteorological monitoring networks. These models are being used to | 83 | meteorological monitoring networks. These models are being used to | ||
65 | predict the consequences of climate change on the water balance of | 84 | predict the consequences of climate change on the water balance of | ||
66 | mountain watersheds. The models also constitute a valuable tool for | 85 | mountain watersheds. The models also constitute a valuable tool for | ||
67 | our operational services, such as periodic snow hydrological | 86 | our operational services, such as periodic snow hydrological | ||
68 | bulletins, which contribute to the federal flood prevention and | 87 | bulletins, which contribute to the federal flood prevention and | ||
69 | forecasting system.\r\n\r\nThe research group \u00abSnow | 88 | forecasting system.\r\n\r\nThe research group \u00abSnow | ||
70 | Hydrology\u00bb is based in Davos and ensures the link between other | 89 | Hydrology\u00bb is based in Davos and ensures the link between other | ||
71 | Davosian research groups and the research unit \u201dMountain | 90 | Davosian research groups and the research unit \u201dMountain | ||
72 | Hydrology and Mass Movements\u201d in Birmensdorf.", | 91 | Hydrology and Mass Movements\u201d in Birmensdorf.", | ||
73 | "id": "d66115d3-c4f9-4f6e-8ff1-5791549e0386", | 92 | "id": "d66115d3-c4f9-4f6e-8ff1-5791549e0386", | ||
74 | "image_url": "", | 93 | "image_url": "", | ||
75 | "is_organization": true, | 94 | "is_organization": true, | ||
76 | "name": "snow-hydrology", | 95 | "name": "snow-hydrology", | ||
77 | "state": "active", | 96 | "state": "active", | ||
78 | "title": "Snow Hydrology", | 97 | "title": "Snow Hydrology", | ||
79 | "type": "organization" | 98 | "type": "organization" | ||
80 | }, | 99 | }, | ||
81 | "owner_org": "d66115d3-c4f9-4f6e-8ff1-5791549e0386", | 100 | "owner_org": "d66115d3-c4f9-4f6e-8ff1-5791549e0386", | ||
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84 | \"EnviDat\"}", | 103 | \"EnviDat\"}", | ||
85 | "publication_state": "published", | 104 | "publication_state": "published", | ||
86 | "related_datasets": "", | 105 | "related_datasets": "", | ||
87 | "related_publications": "A Novel Method to Quantify Near-Surface | 106 | "related_publications": "A Novel Method to Quantify Near-Surface | ||
88 | Boundary-Layer Dynamics at Ultra-High Spatio-Temporal Resolution; | 107 | Boundary-Layer Dynamics at Ultra-High Spatio-Temporal Resolution; | ||
t | 89 | submitted and under review", | t | 108 | accepted for publication in Boundary-Layer Meteorology", |
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99 | "description": "Data measured with a 3D short-path ultrasonic | 118 | "description": "Data measured with a 3D short-path ultrasonic | ||
100 | anemometer in close vicinity to the screens. Note that the time stamps | 119 | anemometer in close vicinity to the screens. Note that the time stamps | ||
101 | are in local time (GMT+2).", | 120 | are in local time (GMT+2).", | ||
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187 | "spatial_info": "Switzerland", | 206 | "spatial_info": "Switzerland", | ||
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189 | "subtitle": "", | 208 | "subtitle": "", | ||
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191 | { | 210 | { | ||
192 | "display_name": "2D TEMPERATURE FIELD", | 211 | "display_name": "2D TEMPERATURE FIELD", | ||
193 | "id": "d55ac0d2-0bc0-46a7-889c-1b926d075511", | 212 | "id": "d55ac0d2-0bc0-46a7-889c-1b926d075511", | ||
194 | "name": "2D TEMPERATURE FIELD", | 213 | "name": "2D TEMPERATURE FIELD", | ||
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196 | "vocabulary_id": null | 215 | "vocabulary_id": null | ||
197 | }, | 216 | }, | ||
198 | { | 217 | { | ||
199 | "display_name": "2D WIND FIELD", | 218 | "display_name": "2D WIND FIELD", | ||
200 | "id": "660e5d4d-0c68-4484-a4f2-9d21b9029260", | 219 | "id": "660e5d4d-0c68-4484-a4f2-9d21b9029260", | ||
201 | "name": "2D WIND FIELD", | 220 | "name": "2D WIND FIELD", | ||
202 | "state": "active", | 221 | "state": "active", | ||
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204 | }, | 223 | }, | ||
205 | { | 224 | { | ||
206 | "display_name": "INFRARED THERMOGRAPHY", | 225 | "display_name": "INFRARED THERMOGRAPHY", | ||
207 | "id": "3c841345-45cd-4a99-9c34-69a891d5ea38", | 226 | "id": "3c841345-45cd-4a99-9c34-69a891d5ea38", | ||
208 | "name": "INFRARED THERMOGRAPHY", | 227 | "name": "INFRARED THERMOGRAPHY", | ||
209 | "state": "active", | 228 | "state": "active", | ||
210 | "vocabulary_id": null | 229 | "vocabulary_id": null | ||
211 | }, | 230 | }, | ||
212 | { | 231 | { | ||
213 | "display_name": "NEAR-SURFACE ATMOSPHERIC LAYER", | 232 | "display_name": "NEAR-SURFACE ATMOSPHERIC LAYER", | ||
214 | "id": "93a597d5-cb9f-43d2-b7ca-dd50a368608b", | 233 | "id": "93a597d5-cb9f-43d2-b7ca-dd50a368608b", | ||
215 | "name": "NEAR-SURFACE ATMOSPHERIC LAYER", | 234 | "name": "NEAR-SURFACE ATMOSPHERIC LAYER", | ||
216 | "state": "active", | 235 | "state": "active", | ||
217 | "vocabulary_id": null | 236 | "vocabulary_id": null | ||
218 | }, | 237 | }, | ||
219 | { | 238 | { | ||
220 | "display_name": "PATCHY SNOW COVER", | 239 | "display_name": "PATCHY SNOW COVER", | ||
221 | "id": "61d8a21a-8ef9-4900-8050-bf3e84c05fc5", | 240 | "id": "61d8a21a-8ef9-4900-8050-bf3e84c05fc5", | ||
222 | "name": "PATCHY SNOW COVER", | 241 | "name": "PATCHY SNOW COVER", | ||
223 | "state": "active", | 242 | "state": "active", | ||
224 | "vocabulary_id": null | 243 | "vocabulary_id": null | ||
225 | }, | 244 | }, | ||
226 | { | 245 | { | ||
227 | "display_name": "SNOW MELT", | 246 | "display_name": "SNOW MELT", | ||
228 | "id": "4452e5c9-c707-4c61-bd1c-28816181a043", | 247 | "id": "4452e5c9-c707-4c61-bd1c-28816181a043", | ||
229 | "name": "SNOW MELT", | 248 | "name": "SNOW MELT", | ||
230 | "state": "active", | 249 | "state": "active", | ||
231 | "vocabulary_id": null | 250 | "vocabulary_id": null | ||
232 | }, | 251 | }, | ||
233 | { | 252 | { | ||
234 | "display_name": "SNOW-ATMOSPHERE INTERACTIONS", | 253 | "display_name": "SNOW-ATMOSPHERE INTERACTIONS", | ||
235 | "id": "9d4df93a-3291-49a2-8c72-565088f48c09", | 254 | "id": "9d4df93a-3291-49a2-8c72-565088f48c09", | ||
236 | "name": "SNOW-ATMOSPHERE INTERACTIONS", | 255 | "name": "SNOW-ATMOSPHERE INTERACTIONS", | ||
237 | "state": "active", | 256 | "state": "active", | ||
238 | "vocabulary_id": null | 257 | "vocabulary_id": null | ||
239 | }, | 258 | }, | ||
240 | { | 259 | { | ||
241 | "display_name": "SURFACE HEAT EXCHANGE", | 260 | "display_name": "SURFACE HEAT EXCHANGE", | ||
242 | "id": "cb61d6bd-bf4d-4fd6-a8e2-8dbbbd90d418", | 261 | "id": "cb61d6bd-bf4d-4fd6-a8e2-8dbbbd90d418", | ||
243 | "name": "SURFACE HEAT EXCHANGE", | 262 | "name": "SURFACE HEAT EXCHANGE", | ||
244 | "state": "active", | 263 | "state": "active", | ||
245 | "vocabulary_id": null | 264 | "vocabulary_id": null | ||
246 | } | 265 | } | ||
247 | ], | 266 | ], | ||
248 | "title": "Quantifying Surface Heat Exchange over Heterogeneous Land | 267 | "title": "Quantifying Surface Heat Exchange over Heterogeneous Land | ||
249 | Surfaces at Ultra-High Spatio-Temporal Resolution", | 268 | Surfaces at Ultra-High Spatio-Temporal Resolution", | ||
250 | "type": "dataset", | 269 | "type": "dataset", | ||
251 | "url": null, | 270 | "url": null, | ||
252 | "version": "1.0" | 271 | "version": "1.0" | ||
253 | } | 272 | } |