Predicting ground temperatures across European landscapes

1. Ambient temperatures in natural environments can vary widely over short distances, especially on rugged ground where exposure to solar radiation depends on slope and aspect. Temperatures can also fluctuate rapidly, reaching values not revealed by climate data. Such fine-scale variation raises challenges for modelling species distributions under changing climates. 2. To avoid misunderstanding current species distributions and future changes, temperatures must be modelled at high resolutions. Most existing methods either require extensive parameterisation or are pre-parameterised for restricted localities and current conditions; here we describe a more versatile method intended for European landscapes under a wide range of scenarios. 3. The availability of high-resolution topographic data makes possible the use of projected solar irradiation to help predict local diurnal ground temperatures. Using time series from 83 points across Europe, we fitted statistical models for soil surface t...

1. 自然环境中的环境温度（ambient temperature）在短距离内往往存在显著差异，尤其在崎岖地形中——该类区域的太阳辐射（solar radiation）暴露量取决于坡度（slope）与坡向（aspect）。温度还可能快速波动，其实际数值无法通过常规气候数据体现。这类精细尺度的温度变异性，为气候变化背景下的物种分布（species distributions）建模带来了严峻挑战。
2. 为避免对当前物种分布及未来变化产生误判，必须以高分辨率（high resolutions）开展温度建模。现有多数建模方法要么需要大量参数化（parameterisation）工作，要么仅针对特定区域与当前环境完成预参数化；本文介绍了一种通用性更强的方法，可适用于多种情景（scenarios）下的欧洲陆地景观（European landscapes）。
3. 高分辨率地形数据（topographic data）的可用性，使得借助投影太阳辐射（projected solar irradiation）预测局地日间地表温度（diurnal ground temperatures）成为可能。研究团队利用欧洲全境83个监测点的时间序列（time series）数据，针对地表（soil surface）t……构建了统计模型（statistical models）。