Climate Change Data Portal
| DOI | 10.5194/bg-21-605-2024 |
| Microclimate mapping using novel radiative transfer modelling | |
| Zellweger, Florian; Sulmoni, Eric; Malle, Johanna T.; Baltensweiler, Andri; Jonas, Tobias; Zimmermann, Niklaus E.; Ginzler, Christian; Karger, Dirk Nikolaus; De Frenne, Pieter; Frey, David; Webster, Clare | |
| 发表日期 | 2024 |
| ISSN | 1726-4170 |
| EISSN | 1726-4189 |
| 起始页码 | 21 |
| 结束页码 | 2 |
| 卷号 | 21期号:2 |
| 英文摘要 | Climate data matching the scales at which organisms experience climatic conditions are often missing. Yet, such data on microclimatic conditions are required to better understand climate change impacts on biodiversity and ecosystem functioning. Here we combine a network of microclimate temperature measurements across different habitats and vertical heights with a novel radiative transfer model to map daily temperatures during the vegetation period at 10 m spatial resolution across Switzerland. Our results reveal strong horizontal and vertical variability in microclimate temperature, particularly for maximum temperatures at 5 cm above the ground and within the topsoil. Compared to macroclimate conditions as measured by weather stations outside forests, diurnal air and topsoil temperature ranges inside forests were reduced by up to 3.0 and 7.8 degrees C, respectively, while below trees outside forests, e.g. in hedges and below solitary trees, this buffering effect was 1.8 and 7.2 degrees C, respectively. We also found that, in open grasslands, maximum temperatures at 5 cm above ground are, on average, 3.4 degrees C warmer than those of the macroclimate, suggesting that, in such habitats, heat exposure close to the ground is often underestimated when using macroclimatic data. Spatial interpolation was achieved by using a hybrid approach based on linear mixed-effect models with input from detailed radiation estimates from radiative transfer models that account for topographic and vegetation shading, as well as other predictor variables related to the macroclimate, topography, and vegetation height. After accounting for macroclimate effects, microclimate patterns were primarily driven by radiation, with particularly strong effects on maximum temperatures. Results from spatial block cross-validation revealed predictive accuracies as measured by root mean squared errors ranging from 1.18 to 3.43 degrees C, with minimum temperatures being predicted more accurately overall than maximum temperatures. The microclimate-mapping methodology presented here enables a biologically relevant perspective when analysing climate-species interactions, which is expected to lead to a better understanding of biotic and ecosystem responses to climate and land use change. |
| 语种 | 英语 |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology |
| WOS类目 | Ecology ; Geosciences, Multidisciplinary |
| WOS记录号 | WOS:001168779600001 |
| 来源期刊 | BIOGEOSCIENCES
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/303808 |
| 作者单位 | Swiss Federal Institutes of Technology Domain; Swiss Federal Institute for Forest, Snow & Landscape Research; Swiss Federal Institutes of Technology Domain; Swiss Federal Institute for Forest, Snow & Landscape Research; Ghent University; University of Oslo |
| 推荐引用方式 GB/T 7714 | Zellweger, Florian,Sulmoni, Eric,Malle, Johanna T.,et al. Microclimate mapping using novel radiative transfer modelling[J],2024,21(2). |
| APA | Zellweger, Florian.,Sulmoni, Eric.,Malle, Johanna T..,Baltensweiler, Andri.,Jonas, Tobias.,...&Webster, Clare.(2024).Microclimate mapping using novel radiative transfer modelling.BIOGEOSCIENCES,21(2). |
| MLA | Zellweger, Florian,et al."Microclimate mapping using novel radiative transfer modelling".BIOGEOSCIENCES 21.2(2024). |
| 条目包含的文件 | 条目无相关文件。 | |||||
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