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A method for computing hourly, historical, terrain‐corrected microclimate anywhere on earth
Methods in Ecology and Evolution ( IF 6.3 ) Pub Date : 2019-12-02 , DOI: 10.1111/2041-210x.13330
Michael R. Kearney 1 , Phillipa K. Gillingham 2 , Isobel Bramer 2 , James P. Duffy 3 , Ilya M.D. Maclean 3
Affiliation  

  1. Microclimates are the thermal and hydric environments organisms actually experience, and estimates of them are increasingly needed in environmental research. The availability of global weather and terrain datasets, together with increasingly sophisticated microclimate modelling tools, makes the prospect of a global, web‐based microclimate estimation procedure feasible.
  2. We have developed such an approach for the r programming environment which integrates existing r packages for obtaining terrain and sub‐daily atmospheric forcing data (elevatr and rncep), and two complementary microclimate modelling packages (NicheMapR and microclima). The procedure can be used to generate NicheMapR’s hourly time‐series outputs of above‐ and below‐ground conditions, including convective and radiative environments, soil temperature, soil moisture and snow cover, for a single point, using microclima to account for local topographic and vegetation effects. Alternatively, it can use microclima to produce high‐resolution grids of near‐surface temperatures, using NicheMapR to derive calibration coefficients normally obtained from experimental data.
  3. We validate this integrated approach against a series of microclimate observations used previously in the tests of the respective models and show equivalent performance.
  4. It is thus now feasible to produce realistic estimates of microclimate at fine (<30 m) spatial and temporal scales anywhere on earth, from 1957 to present.


中文翻译:

一种计算地球上任何地方的每小时,历史,经地形校正的微气候的方法

  1. 小气候是生物体实际经历的热环境和水环境,在环境研究中越来越需要对它们进行估算。全球天气和地形数据集的可用性以及日趋完善的微气候建模工具,使得基于网络的全球微气候估计程序的前景变得可行。
  2. 我们为r编程环境开发了这种方法,该方法集成了用于获取地形和次日大气强迫数据(elevatrrncep)的现有r程序包,以及两个互补的微气候建模程序包(Niche M ap R和microclima)。该过程可用于产生N个iche中号AP的地上和地下的条件,包括对流和辐射的环境,土壤温度,土壤湿度和积雪,对于单点R的每小时时间序列输出,使用microclima考虑到当地的地形和植被影响。或者,它可以利用微气候来产生近地表温度的高分辨率网格,并利用Niche M ap R得出通常从实验数据中获得的校准系数。
  3. 我们针对先前在各个模型的测试中使用的一系列微气候观测值验证了这种集成方法,并显示了等效的性能。
  4. 因此,从1957年到现在,在地球上任何地方的精细(<30 m)时空尺度上,对微气候进行实际估算是可行的。
更新日期:2019-12-02
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