Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1

<b>Note: </b>Version 3.1 supersedes all previous releases. Version 3.0 has been deprecated due to the discovery of a data inconsistency in the calculation of net longwave radiation in the source code used to generate the dataset. As a result, there is a general positive bias in potential evapotranspiration (ET₀) and a consequent lower (drier) bias in the Aridity Index (AI) in affected outputs. This issue has been fully corrected in v3.1, and all ET₀ and AI products have been recomputed using the corrected method. We are grateful for the numerous feedback from users and in particular to Dr. Pushpendra Raghav, Research Scientist, Department of Civil Engineering, University of Alabama, for identifying and bringing this issue to our attention. We recommend all users migrate to Version 3.1 and discontinue use of the previous v3.0.***********************************************************************************************************************************<b>NOTE: </b>The recently released Future Global Aridity Index and PET Database (CMIP_6) is now available at:https://doi.org/10.57760/sciencedb.nbsdc.00086High-resolution (30 arc-seconds) global raster datasets of average monthly and annual potential evapotranspiration (PET) and aridity index (AI) for two historical (1960-1990; 1970-2000) and two future (2021-2040; 2041-2060) time periods for each of 22 CIMP6 Earth System Models across four emission scenarios (SSP: 126, 245, 370, 585). The database also includes three averaged multi-model ensembles produced for each of the four emission scenarios:**************************************************************************************************************************The Global Aridity Index (Global-AI) and Global Reference Evapo-Transpiration (Global-ET0) datasets provided in Version 3.1 of the Global Aridity Index and Potential Evapo-Transpiration (ET0) Database (Global-AI_PET_v3.x1) provide high-resolution (30 arc-seconds) global raster data for the 1970-2000 period, related to evapotranspiration processes and rainfall deficit for potential vegetative growth, based upon implementation of the FAO-56 Penman-Monteith Reference Evapotranspiration (ET₀) equation.Aridity Index represent the ratio between precipitation and ET₀, thus rainfall over vegetation water demand (aggregated on annual basis). Under this formulation, Aridity Index values increase for more humid conditions, and decrease with more arid conditions. The Aridity Index values reported within the <i>Global-AI</i> geodataset have been multiplied by a factor of 10,000 to derive and distribute the data as integers (with 4 decimal accuracy). This multiplier has been used to increase the precision of the variable values without using decimals. The Readme File is provided with a detailed description of the dataset files. A peer-reviewed article is now available with a description of the methodology and a technical evaluation.The Global-AI_PET_v3 datasets are provided for non-commercial use in standard GeoTiff format, at 30 arc seconds or ~ 1km at the equator.The Python programming source code used to run the calculation of ET0 and AI is provided and available online on Figshare at:https://figshare.com/articles/software/Global_Aridity_Index_and_Potential_Evapotranspiration_Climate_Database_v3_-_Algorithm_Code_Python_/20005589Peer-Review Reference and Proper Citation:Zomer, R.J.; Xu, J.; Trabuco, A. 2022. Version 3 of the Global Aridity Index and Potential Evapotranspiration Database. Scientific Data 9, 409. https://www.nature.com/articles/s41597-022-01493-1<br><br><br>

<b>注意：</b>3.1版本取代所有过往发布版本。由于生成该数据集的源代码中发现净长波辐射计算存在数据不一致问题，3.0版本已被弃用。受影响的输出结果中，潜在蒸散量（potential evapotranspiration, ET₀）普遍存在正偏差，由此导致干旱指数（Aridity Index, AI）出现偏低（偏干旱）的偏差。该问题已在v3.1版本中得到完全修正，所有ET₀和AI产品均已采用修正后的方法重新计算。我们感谢众多用户的反馈，特别感谢阿拉巴马大学土木工程系研究科学家Pushpendra Raghav博士发现并向我们通报了该问题。我们建议所有用户升级至3.1版本，停止使用过往的v3.0版本。
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<b>重要提示：</b>最新发布的未来全球干旱指数与潜在蒸散量数据库（CMIP_6）现已上线，链接为：https://doi.org/10.57760/sciencedb.nbsdc.00086
该数据集包含高分辨率（30角秒）的全球栅格数据，涵盖22个CMIP6地球系统模式在4种共享社会经济路径（Shared Socioeconomic Pathways, SSP：126、245、370、585）排放情景下的两个历史时段（1960-1990、1970-2000）以及两个未来时段（2021-2040、2041-2060）的月均、年均潜在蒸散量（potential evapotranspiration, PET）与干旱指数（AI）。本数据库还包含针对4种排放情景分别构建的3个多模式集合平均数据集：
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全球干旱指数与潜在蒸散量（ET₀）数据库（Global-AI_PET_v3.x1）3.1版本所提供的全球干旱指数（Global-AI）与全球参考蒸散量（Global-ET0）数据集，基于FAO-56 Penman-Monteith参考蒸散量（ET₀）公式构建，包含1970-2000时段的高分辨率（30角秒）全球栅格数据，用于表征潜在植被生长所需的蒸散过程与降水亏缺情况。
干旱指数为降水量与ET₀的比值，即年尺度汇总的降雨量与植被需水量之比。据此公式计算，干旱指数数值越高代表气候越湿润，越低则代表气候越干旱。本<i>Global-AI</i>地理数据集所记录的干旱指数数值已乘以10000倍，以整数形式存储并分发数据（精度可达4位小数）。该乘数用于在不使用小数的前提下提升变量数值的精度。数据集文件的详细说明请参见附带的自述文件（Readme File）。本数据集的方法学与技术评估已发表于同行评议期刊。
Global-AI_PET_v3系列数据集以标准GeoTiff格式提供，仅可用于非商业用途，数据分辨率为30角秒，在赤道处约为1公里。
用于计算ET₀与AI的Python源代码已公开上传至Figshare平台，链接为：https://figshare.com/articles/software/Global_Aridity_Index_and_Potential_Evapotranspiration_Climate_Database_v3_-_Algorithm_Code_Python_/20005589
同行评议参考文献与规范引用格式：Zomer, R.J.; Xu, J.; Trabuco, A. 2022. 全球干旱指数与潜在蒸散量数据库第3版. 科学数据(Scientific Data) 9, 409. https://www.nature.com/articles/s41597-022-01493-1