Global Snow-free Leaf Area Index Dataset for Earth System Modeling – Year 2018

The snow-free Leaf Area Index (LAI) dataset is a global monthly LAI product developed for land surface and earth system modeling. It covers the period from 1985 to 2020 at 500 m spatial resolution and aims to constrain the underestimation of LAI in snow-covered regions caused by snow contamination. The dataset was generated by integrating reprocessed MODIS Collection 6.1 LAI and GIMMS LAI4g products with plant functional type (PFT) information. Snow-affected areas were identified using satellite-based observations, and LAI was corrected at the PFT level using leaf lifespan constraints derived from the TRY plant trait database. The resulting snow-free LAI better represents the phenology of evergreen vegetation and is intended to support studies of vegetation–snow interactions, land surface processes, and earth system modeling. The dataset provides monthly LAI and SAI at 500 m spatial resolution globally, distributed as NetCDF-4 format files. Each file covers a 5° × 5° geographic region containing 1200 × 1200 pixels (0.00416667° or 15 arc-seconds per pixel) in the WGS84 coordinate system. The global land surface is divided into 1,447 regional tiles, with files named according to the convention RG_LatN_LonW_LatS_LonE.LSAI500m.YYYY.nc, where the latitude and longitude bounds define the tile coverage and YYYY indicates the year. Each file contains four primary data variables: MONTHLY_LC_LAI and MONTHLY_LC_SAI representing 500 m grid LAI and SAI values with dimensions (12 months × 1200 lat × 1200 lon), and MONTHLY_PFT_LAI and MONTHLY_PFT_SAI providing PFT LAI and SAI values with dimensions (12 months × 16 PFTs × 1200 lat × 1200 lon). Grid LAI (SAI) and PFT LAI (SAI) are both available for user selection according to research demands. The grid LAI (SAI) is calculated as the area-weighted average of PFT LAI (SAI). All LAI and SAI values are stored as unsigned byte integers with a scale factor of 0.1 and units of m2/m2, requiring multiplication by 0.1 to obtain physical values. The 16 plant functional types include various tree, shrub, grass, and crop categories ranging from tropical to boreal biomes. Coordinate variables (lat, lon, pft, mon) are included with appropriate metadata.无雪叶面积指数（Leaf Area Index, LAI）数据集是一款面向陆面与地球系统模拟研发的全球逐月LAI产品。其时间覆盖范围为1985年至2020年，空间分辨率为500米，旨在解决积雪污染引发的积雪覆盖区域LAI低估问题。 该数据集通过融合经再处理的MODIS Collection 6.1 LAI与GIMMS LAI4g产品，以及植物功能型（plant functional type, PFT）信息生成。研究团队利用卫星观测识别受积雪影响的区域，并基于TRY植物性状数据库推导的叶片寿命约束条件，在植物功能型层面完成LAI校正。经修正后的无雪LAI能够更精准地反映常绿植被的物候特征，可用于支撑植被-积雪相互作用、陆面过程及地球系统模拟等相关研究。 本数据集以NetCDF-4格式文件分发，提供全球范围内500米分辨率的逐月LAI与SAI数据。每个文件对应一个5°×5°的地理区域，采用WGS84坐标系，包含1200×1200个像素（单个像素对应0.00416667°，即15弧秒）。全球陆面被划分为1447个区域瓦片，文件命名遵循RG_LatN_LonW_LatS_LonE.LSAI500m.YYYY.nc规范，其中经纬度边界定义了瓦片覆盖范围，YYYY代表对应年份。 每个文件包含4个核心数据变量：MONTHLY_LC_LAI与MONTHLY_LC_SAI代表500米网格尺度的LAI与SAI值，维度为(12个月 × 1200个纬度像素 × 1200个经度像素)；MONTHLY_PFT_LAI与MONTHLY_PFT_SAI则提供植物功能型层面的LAI与SAI值，维度为(12个月 × 16种植物功能型 × 1200个纬度像素 × 1200个经度像素)。用户可根据研究需求选择网格LAI（SAI）或植物功能型LAI（SAI）数据，其中网格LAI（SAI）通过植物功能型LAI（SAI）的面积加权平均计算得到。 所有LAI与SAI值均以无符号字节整数存储，缩放因子为0.1，单位为m²/m²，需乘以0.1方可获得实际物理量值。16种植物功能型涵盖了从热带到寒带生物群系的各类乔木、灌木、草本与作物类别。数据集中包含坐标变量（lat、lon、pft、mon）及配套元数据。