TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015.

TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015.
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DOI:
10.1038/sdata.2017.191
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发表时间:
2018-01-09
期刊:
影响因子:
9.8
通讯作者:
Hegewisch KC
Hegewisch KC
中科院分区:
综合性期刊2区
文献类型:
--
作者:
Abatzoglou JT;Dobrowski SZ;Parks SA;Hegewisch KC

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我们介绍了TerraClimate,这是一个高空间分辨率(1/24°,~4公里)的全球陆地表面1958-2015年逐月气候和气候水分平衡的数据集。TerraClimate使用气候辅助插值法,将来自WorldClim数据集的高空间分辨率气候常态与来自其他来源的较粗分辨率随时间变化(即,每月)的数据结合在一起,以产生关于降水、最高和最低温度、风速、水汽压和太阳辐射的每月数据集。TerraClimate还使用水量平衡模型生成月度地表水平衡数据集,该模型结合了参考蒸散、降水、温度和内插的植物可提取土壤水分容量。这些数据为全球尺度的生态和水文研究提供了重要的投入,这些研究需要高空间分辨率和时变的气候和气候水平衡数据。我们使用年温度、降雨量、从站点数据计算的参考蒸散量以及来自径流计的年径流来验证TerraClimate的时空特征。TerraClimate数据集显示,相对于分辨率较高的网格数据集,总体平均绝对误差有了显著改善,空间真实感增强。
We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958–2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.
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