Department of Biology and Geology, Physics and Inorganic Chemistry, Rey Juan Carlos University, Calle Tulipán s/n, Móstoles (Madrid) 28933, Spain.
Sci Data. 2017 Jun 20;4:170078. doi: 10.1038/sdata.2017.78.
Species Distribution Models (SDMs) combine information on the geographic occurrence of species with environmental layers to estimate distributional ranges and have been extensively implemented to answer a wide array of applied ecological questions. Unfortunately, most global datasets available to parameterize SDMs consist of spatially interpolated climate surfaces obtained from ground weather station data and have omitted the Antarctic continent, a landmass covering c. 20% of the Southern Hemisphere and increasingly showing biological effects of global change. Here we introduce MERRAclim, a global set of satellite-based bioclimatic variables including Antarctica for the first time. MERRAclim consists of three datasets of 19 bioclimatic variables that have been built for each of the last three decades (1980s, 1990s and 2000s) using hourly data of 2 m temperature and specific humidity. We provide MERRAclim at three spatial resolutions (10 arc-minutes, 5 arc-minutes and 2.5 arc-minutes). These reanalysed data are comparable to widely used datasets based on ground station interpolations, but allow extending their geographical reach and SDM building in previously uncovered regions of the globe.
物种分布模型 (SDM) 将物种的地理分布信息与环境层结合起来，以估计分布范围，并已广泛用于回答各种应用生态问题。然而，用于参数化 SDM 的大多数全球数据集都由从地面气象站数据中获得的空间插值气候表面组成，并且忽略了南极洲，南极洲覆盖了南半球约 20%的面积，并且越来越多地显示出全球变化的生物效应。在这里，我们引入了 MERRAclim，这是一个首次包含南极洲的基于卫星的生物气候变量的全球数据集。MERRAclim 由三个数据集组成，每个数据集包含 19 个生物气候变量，这些数据集是使用过去三十年（80 年代、90 年代和 2000 年代）的每小时 2m 温度和比湿数据构建的。我们提供了三种空间分辨率（10 弧分、5 弧分和 2.5 弧分）的 MERRAclim。这些再分析数据与基于地面站插值的广泛使用数据集具有可比性，但允许在以前未覆盖的全球区域扩展其地理范围和 SDM 构建。
