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) in Monthly topsoil and near surface microclimate temperature data for Switzerland
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59 | "date": "[{\"date\": \"2012-04-01\", \"date_type\": \"created\", | 59 | "date": "[{\"date\": \"2012-04-01\", \"date_type\": \"created\", | ||
60 | \"end_date\": \"2021-12-31\"}]", | 60 | \"end_date\": \"2021-12-31\"}]", | ||
61 | "doi": "10.16904/envidat.431", | 61 | "doi": "10.16904/envidat.431", | ||
62 | "funding": "[{\"grant_number\": \"193645\", \"institution\": \"Swiss | 62 | "funding": "[{\"grant_number\": \"193645\", \"institution\": \"Swiss | ||
63 | National Science Foundation\", \"institution_url\": | 63 | National Science Foundation\", \"institution_url\": | ||
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70 | "license_title": "Creative Commons Attribution Share-Alike | 70 | "license_title": "Creative Commons Attribution Share-Alike | ||
71 | (CC-BY-SA)", | 71 | (CC-BY-SA)", | ||
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n | 78 | "metadata_modified": "2023-09-26T11:20:36.066902", | n | 78 | "metadata_modified": "2023-09-26T11:21:07.615400", |
79 | "name": | 79 | "name": | ||
80 | psoil-and-near-surface-microclimate-temperature-data-for-switzerland", | 80 | psoil-and-near-surface-microclimate-temperature-data-for-switzerland", | ||
81 | "notes": "Climate data matching the scales at which organisms | 81 | "notes": "Climate data matching the scales at which organisms | ||
82 | experience climatic conditions are often missing. Yet, such data on | 82 | experience climatic conditions are often missing. Yet, such data on | ||
83 | microclimatic conditions are required to better understand | 83 | microclimatic conditions are required to better understand | ||
84 | climate-change impacts on biodiversity and ecosystem functioning. Here | 84 | climate-change impacts on biodiversity and ecosystem functioning. Here | ||
85 | we combine a national network of microclimate temperature measurements | 85 | we combine a national network of microclimate temperature measurements | ||
86 | with a novel radiative transfer model to map monthly minimum, mean and | 86 | with a novel radiative transfer model to map monthly minimum, mean and | ||
87 | maximum temperatures during the vegetation period at a 10 meter | 87 | maximum temperatures during the vegetation period at a 10 meter | ||
88 | spatial resolution across Switzerland. The temperature measurements | 88 | spatial resolution across Switzerland. The temperature measurements | ||
89 | took place in 107 sampling plots distributed across different habitat | 89 | took place in 107 sampling plots distributed across different habitat | ||
90 | types, with 62 plots in forests, 22 below trees outside forests, and | 90 | types, with 62 plots in forests, 22 below trees outside forests, and | ||
91 | 23 in open grasslands. In each plot we measured temperature in the | 91 | 23 in open grasslands. In each plot we measured temperature in the | ||
92 | topsoil (-5cm), as well as in the air at 5cm and 100cm height above | 92 | topsoil (-5cm), as well as in the air at 5cm and 100cm height above | ||
93 | ground. Spatial interpolation was achieved by using a hybrid approach | 93 | ground. Spatial interpolation was achieved by using a hybrid approach | ||
94 | based on linear mixed effects models with input from detailed | 94 | based on linear mixed effects models with input from detailed | ||
95 | radiation estimates that account for topographic and vegetation | 95 | radiation estimates that account for topographic and vegetation | ||
96 | shading, as well as other predictor variables related to the | 96 | shading, as well as other predictor variables related to the | ||
97 | macroclimate, topography and vegetation height. Our data reveals | 97 | macroclimate, topography and vegetation height. Our data reveals | ||
98 | strong horizontal and vertical variability in microclimate | 98 | strong horizontal and vertical variability in microclimate | ||
99 | temperature, particularly for maximum temperatures at 5 cm above the | 99 | temperature, particularly for maximum temperatures at 5 cm above the | ||
100 | ground and within the topsoil. Compared to macroclimate conditions as | 100 | ground and within the topsoil. Compared to macroclimate conditions as | ||
101 | measured by weather stations outside forests, diurnal air and topsoil | 101 | measured by weather stations outside forests, diurnal air and topsoil | ||
102 | temperature ranges inside forests were reduced by up to 3.0 and 7.8 | 102 | temperature ranges inside forests were reduced by up to 3.0 and 7.8 | ||
103 | \u00b0C, respectively, while below trees outside forests, e.g. in | 103 | \u00b0C, respectively, while below trees outside forests, e.g. in | ||
104 | hedges and below solitary trees, this buffering effect was 1.8 and 7.2 | 104 | hedges and below solitary trees, this buffering effect was 1.8 and 7.2 | ||
105 | \u00b0C. We also found that in open grasslands, maximum temperatures | 105 | \u00b0C. We also found that in open grasslands, maximum temperatures | ||
106 | at 5 cm above ground are on average 3.4 \u00b0C warmer than that of | 106 | at 5 cm above ground are on average 3.4 \u00b0C warmer than that of | ||
107 | macroclimate, suggesting that in such habitats heat exposure close to | 107 | macroclimate, suggesting that in such habitats heat exposure close to | ||
108 | the ground is often underestimated when using macroclimatic data. | 108 | the ground is often underestimated when using macroclimatic data. | ||
109 | After accounting for macroclimate effects, microclimate patterns were | 109 | After accounting for macroclimate effects, microclimate patterns were | ||
110 | primarily driven by radiation, with particularly strong effects on | 110 | primarily driven by radiation, with particularly strong effects on | ||
111 | maximum temperatures. Results from spatial block cross-validation | 111 | maximum temperatures. Results from spatial block cross-validation | ||
112 | revealed predictive accuracies as measured by RSME\u2019s ranging from | 112 | revealed predictive accuracies as measured by RSME\u2019s ranging from | ||
113 | 1.18 to 3.43 \u00b0C, with minimum temperatures generally being | 113 | 1.18 to 3.43 \u00b0C, with minimum temperatures generally being | ||
114 | predicted more accurately than maximum temperatures. The microclimate | 114 | predicted more accurately than maximum temperatures. The microclimate | ||
115 | maps presented here enable a more biologically relevant perspective | 115 | maps presented here enable a more biologically relevant perspective | ||
116 | when analysing climate-species interactions, which is expected to lead | 116 | when analysing climate-species interactions, which is expected to lead | ||
117 | to a better understanding of biotic and ecosystem responses to climate | 117 | to a better understanding of biotic and ecosystem responses to climate | ||
118 | and land use change.\r\n", | 118 | and land use change.\r\n", | ||
119 | "num_resources": 3, | 119 | "num_resources": 3, | ||
120 | "num_tags": 7, | 120 | "num_tags": 7, | ||
121 | "organization": { | 121 | "organization": { | ||
122 | "approval_status": "approved", | 122 | "approval_status": "approved", | ||
123 | "created": "2016-08-08T20:30:16.444200", | 123 | "created": "2016-08-08T20:30:16.444200", | ||
124 | "description": "The availability of consistent and comprehensible | 124 | "description": "The availability of consistent and comprehensible | ||
125 | spatial data is fundamental for scientific research, in particular in | 125 | spatial data is fundamental for scientific research, in particular in | ||
126 | the context of long term observation series. An adequate documentation | 126 | the context of long term observation series. An adequate documentation | ||
127 | of the data quality and its history finally enables users to work | 127 | of the data quality and its history finally enables users to work | ||
128 | responsibly with these data.\r\n\r\nAs the research community gets | 128 | responsibly with these data.\r\n\r\nAs the research community gets | ||
129 | closer and the sharing of data becomes more common and important a | 129 | closer and the sharing of data becomes more common and important a | ||
130 | simple and intuitive access to these environmental data is a key | 130 | simple and intuitive access to these environmental data is a key | ||
131 | factor in large projects. Methods of spatial information analysis | 131 | factor in large projects. Methods of spatial information analysis | ||
132 | allow to build and link complex process models of different scientific | 132 | allow to build and link complex process models of different scientific | ||
133 | fields.\r\n\r\n###Tasks and main research\r\n\r\n* Developing | 133 | fields.\r\n\r\n###Tasks and main research\r\n\r\n* Developing | ||
134 | innovative methods to store the history, quality and accuracy of | 134 | innovative methods to store the history, quality and accuracy of | ||
135 | spatial & temporal data (event oriented spatial databases), developing | 135 | spatial & temporal data (event oriented spatial databases), developing | ||
136 | and implementing a method database, particularly in the context of the | 136 | and implementing a method database, particularly in the context of the | ||
137 | projects National Forest Inventory NFI and Datacenter Nature and | 137 | projects National Forest Inventory NFI and Datacenter Nature and | ||
138 | Landscape DNL\r\n* Analysing spatial and temporal data and modelling | 138 | Landscape DNL\r\n* Analysing spatial and temporal data and modelling | ||
139 | natural phenomena and processes\r\n* Developing algorithms for open | 139 | natural phenomena and processes\r\n* Developing algorithms for open | ||
140 | and intuitive search in geo-databases (e.g. ontologies)\r\n* | 140 | and intuitive search in geo-databases (e.g. ontologies)\r\n* | ||
141 | Developing and implementing concepts to provide spatially distributed | 141 | Developing and implementing concepts to provide spatially distributed | ||
142 | geographic information (virtual database)\r\n* Developing methods to | 142 | geographic information (virtual database)\r\n* Developing methods to | ||
143 | handle the uncertainties and inaccuracies (due to measurement and | 143 | handle the uncertainties and inaccuracies (due to measurement and | ||
144 | spatial resolution) of spatial data when used in models\r\n* | 144 | spatial resolution) of spatial data when used in models\r\n* | ||
145 | Maintaining and advancing the NFI-database and the Datacenter Nature | 145 | Maintaining and advancing the NFI-database and the Datacenter Nature | ||
146 | and Landscape (DNL), developing software for the NFI and DNL\r\n* | 146 | and Landscape (DNL), developing software for the NFI and DNL\r\n* | ||
147 | Maintaining and advancing the Geographical Information System of the | 147 | Maintaining and advancing the Geographical Information System of the | ||
148 | WSL\r\n* Knowledge transfer at university level, mainly through | 148 | WSL\r\n* Knowledge transfer at university level, mainly through | ||
149 | teaching positions, support and supervision of Master- and PhD-theses | 149 | teaching positions, support and supervision of Master- and PhD-theses | ||
150 | in the main topics of the GIS-Group\r\n\r\n__Further information__: | 150 | in the main topics of the GIS-Group\r\n\r\n__Further information__: | ||
151 | organization/research-units/forest-resources-and-management/gis.html", | 151 | organization/research-units/forest-resources-and-management/gis.html", | ||
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155 | "name": "gis", | 155 | "name": "gis", | ||
156 | "state": "active", | 156 | "state": "active", | ||
157 | "title": "GIS", | 157 | "title": "GIS", | ||
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162 | "publication": "{\"publication_year\": \"2023\", \"publisher\": | 162 | "publication": "{\"publication_year\": \"2023\", \"publisher\": | ||
163 | \"EnviDat\"}", | 163 | \"EnviDat\"}", | ||
164 | "publication_state": "published", | 164 | "publication_state": "published", | ||
165 | "related_datasets": "", | 165 | "related_datasets": "", | ||
166 | "related_publications": "", | 166 | "related_publications": "", | ||
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169 | "resource_type": "dataset", | 169 | "resource_type": "dataset", | ||
170 | "resource_type_general": "dataset", | 170 | "resource_type_general": "dataset", | ||
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175 | "created": "2023-08-17T11:33:42.589822", | 175 | "created": "2023-08-17T11:33:42.589822", | ||
176 | "description": "Predicted microclimate air temperatures at 5 cm | 176 | "description": "Predicted microclimate air temperatures at 5 cm | ||
177 | above ground. 10 m spatial resolution raster files are provided for | 177 | above ground. 10 m spatial resolution raster files are provided for | ||
178 | mean daily minimum (tmin), mean (tmean) and maximum (tmax) | 178 | mean daily minimum (tmin), mean (tmean) and maximum (tmax) | ||
179 | temperatures during each month from April (04) to October (10) over | 179 | temperatures during each month from April (04) to October (10) over | ||
180 | the period between 2012 to 2021.", | 180 | the period between 2012 to 2021.", | ||
181 | "doi": "", | 181 | "doi": "", | ||
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207 | "created": "2023-08-17T11:41:09.918996", | 207 | "created": "2023-08-17T11:41:09.918996", | ||
208 | "description": "Predicted microclimate air temperatures at 100 | 208 | "description": "Predicted microclimate air temperatures at 100 | ||
209 | cm above ground. 10 m spatial resolution raster files are provided for | 209 | cm above ground. 10 m spatial resolution raster files are provided for | ||
210 | mean daily minimum (tmin), mean (tmean) and maximum (tmax) | 210 | mean daily minimum (tmin), mean (tmean) and maximum (tmax) | ||
211 | temperatures during each month from April (04) to October (10) over | 211 | temperatures during each month from April (04) to October (10) over | ||
212 | the period between 2012 to 2021.", | 212 | the period between 2012 to 2021.", | ||
213 | "doi": "", | 213 | "doi": "", | ||
214 | "format": "ZIP", | 214 | "format": "ZIP", | ||
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237 | "created": "2023-08-17T11:42:07.719671", | 239 | "created": "2023-08-17T11:42:07.719671", | ||
238 | "description": "Predicted microclimate topsoil temperatures at 5 | 240 | "description": "Predicted microclimate topsoil temperatures at 5 | ||
239 | cm below ground. 10 m spatial resolution raster files are provided for | 241 | cm below ground. 10 m spatial resolution raster files are provided for | ||
240 | mean daily minimum (tmin), mean (tmean) and maximum (tmax) | 242 | mean daily minimum (tmin), mean (tmean) and maximum (tmax) | ||
241 | temperatures during each month from April (04) to October (10) over | 243 | temperatures during each month from April (04) to October (10) over | ||
242 | the period between 2012 to 2021.", | 244 | the period between 2012 to 2021.", | ||
243 | "doi": "", | 245 | "doi": "", | ||
244 | "format": "ZIP", | 246 | "format": "ZIP", | ||
245 | "hash": "", | 247 | "hash": "", | ||
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247 | "last_modified": "2023-08-17T13:42:38.420000", | 249 | "last_modified": "2023-08-17T13:42:38.420000", | ||
248 | "metadata_modified": "2023-08-17T11:42:39.157408", | 250 | "metadata_modified": "2023-08-17T11:42:39.157408", | ||
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259 | "size": null, | 261 | "size": null, | ||
260 | "state": "active", | 262 | "state": "active", | ||
261 | "url": | 263 | "url": | ||
262 | "https://os.zhdk.cloud.switch.ch/macro2micro/topsoil.zip", | 264 | "https://os.zhdk.cloud.switch.ch/macro2micro/topsoil.zip", | ||
263 | "url_type": null | 265 | "url_type": null | ||
264 | } | 266 | } | ||
265 | ], | 267 | ], | ||
266 | "spatial": | 268 | "spatial": | ||
267 | 838],[10.49203,47.80838],[10.49203,45.81802],[5.95587,45.81802]]]}]}", | 269 | 838],[10.49203,47.80838],[10.49203,45.81802],[5.95587,45.81802]]]}]}", | ||
268 | "spatial_info": "Switzerland", | 270 | "spatial_info": "Switzerland", | ||
269 | "state": "active", | 271 | "state": "active", | ||
270 | "subtitle": "", | 272 | "subtitle": "", | ||
271 | "tags": [ | 273 | "tags": [ | ||
272 | { | 274 | { | ||
273 | "display_name": "BIODIVERSITY", | 275 | "display_name": "BIODIVERSITY", | ||
274 | "id": "cb53f136-b0e5-418c-a3d3-cda8d0945ec6", | 276 | "id": "cb53f136-b0e5-418c-a3d3-cda8d0945ec6", | ||
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276 | "state": "active", | 278 | "state": "active", | ||
277 | "vocabulary_id": null | 279 | "vocabulary_id": null | ||
278 | }, | 280 | }, | ||
279 | { | 281 | { | ||
280 | "display_name": "CLIMATE CHANGE", | 282 | "display_name": "CLIMATE CHANGE", | ||
281 | "id": "7586fd99-56bd-4c44-ace2-14d87ec1dd9b", | 283 | "id": "7586fd99-56bd-4c44-ace2-14d87ec1dd9b", | ||
282 | "name": "CLIMATE CHANGE", | 284 | "name": "CLIMATE CHANGE", | ||
283 | "state": "active", | 285 | "state": "active", | ||
284 | "vocabulary_id": null | 286 | "vocabulary_id": null | ||
285 | }, | 287 | }, | ||
286 | { | 288 | { | ||
287 | "display_name": "ECOLOGY", | 289 | "display_name": "ECOLOGY", | ||
288 | "id": "ac917ce0-9057-40ba-95f8-41e3e6e51ad4", | 290 | "id": "ac917ce0-9057-40ba-95f8-41e3e6e51ad4", | ||
289 | "name": "ECOLOGY", | 291 | "name": "ECOLOGY", | ||
290 | "state": "active", | 292 | "state": "active", | ||
291 | "vocabulary_id": null | 293 | "vocabulary_id": null | ||
292 | }, | 294 | }, | ||
293 | { | 295 | { | ||
294 | "display_name": "FOREST", | 296 | "display_name": "FOREST", | ||
295 | "id": "90cd0d8f-8df0-4b78-ac11-6e38c2a22106", | 297 | "id": "90cd0d8f-8df0-4b78-ac11-6e38c2a22106", | ||
296 | "name": "FOREST", | 298 | "name": "FOREST", | ||
297 | "state": "active", | 299 | "state": "active", | ||
298 | "vocabulary_id": null | 300 | "vocabulary_id": null | ||
299 | }, | 301 | }, | ||
300 | { | 302 | { | ||
301 | "display_name": "MICROCLIMATE", | 303 | "display_name": "MICROCLIMATE", | ||
302 | "id": "6dd2e5e9-1dde-4594-977a-5072b241442c", | 304 | "id": "6dd2e5e9-1dde-4594-977a-5072b241442c", | ||
303 | "name": "MICROCLIMATE", | 305 | "name": "MICROCLIMATE", | ||
304 | "state": "active", | 306 | "state": "active", | ||
305 | "vocabulary_id": null | 307 | "vocabulary_id": null | ||
306 | }, | 308 | }, | ||
307 | { | 309 | { | ||
308 | "display_name": "RADIATION TRANSFER", | 310 | "display_name": "RADIATION TRANSFER", | ||
309 | "id": "931ceb8e-885e-4242-8139-91fe02cea7b6", | 311 | "id": "931ceb8e-885e-4242-8139-91fe02cea7b6", | ||
310 | "name": "RADIATION TRANSFER", | 312 | "name": "RADIATION TRANSFER", | ||
311 | "state": "active", | 313 | "state": "active", | ||
312 | "vocabulary_id": null | 314 | "vocabulary_id": null | ||
313 | }, | 315 | }, | ||
314 | { | 316 | { | ||
315 | "display_name": "STATISTICAL INTERPOLATION", | 317 | "display_name": "STATISTICAL INTERPOLATION", | ||
316 | "id": "c8bba65c-d9dc-4a6a-8fc8-571d39afca4a", | 318 | "id": "c8bba65c-d9dc-4a6a-8fc8-571d39afca4a", | ||
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319 | "vocabulary_id": null | 321 | "vocabulary_id": null | ||
320 | } | 322 | } | ||
321 | ], | 323 | ], | ||
322 | "title": "Monthly topsoil and near surface microclimate temperature | 324 | "title": "Monthly topsoil and near surface microclimate temperature | ||
323 | data for Switzerland", | 325 | data for Switzerland", | ||
324 | "type": "dataset", | 326 | "type": "dataset", | ||
325 | "url": null, | 327 | "url": null, | ||
326 | "version": "1.0" | 328 | "version": "1.0" | ||
327 | } | 329 | } |