Corak Nicholas K, Thornton Peter E, Lowman Lauren E L
Department of Engineering, Wake Forest University, Winston-Salem, NC, USA.
Department of Physics, Wake Forest University, Winston-Salem, NC, USA.
Sci Data. 2025 Feb 12;12(1):256. doi: 10.1038/s41597-025-04544-5.
Vapor pressure deficit (VPD) is a critical variable in assessing drought conditions and evaluating plant water stress. Gridded products of global and regional VPD are not freely available from satellite remote sensing, model reanalysis, or ground observation datasets. We present two versions of the first gridded VPD product for the Continental US and parts of Northern Mexico and Southern Canada (CONUS+) at a 1 km spatial resolution and daily time step. We derived VPD from Daymet maximum daily temperature and average daily vapor pressure and scale the estimates based on (1) climate determined by the Köppen-Geiger classifications and (2) land cover determined by the International Geosphere-Biosphere Programme. Ground-based VPD data from 253 AmeriFlux sites representing different climate and land cover classifications were used to improve the Daymet-derived VPD estimates for every pixel in the CONUS+ grid to produce the final datasets. We evaluated the Daymet-derived VPD against independent observations and reanalysis data. The CONUS+ VPD datasets will aid in investigating disturbances including drought and wildfire, and informing land management strategies.
水汽压亏缺(VPD)是评估干旱状况和评估植物水分胁迫的关键变量。全球和区域VPD的网格化产品无法从卫星遥感、模式再分析或地面观测数据集中免费获取。我们展示了美国大陆以及墨西哥北部和加拿大南部部分地区(CONUS+)的首个网格化VPD产品的两个版本,空间分辨率为1公里,时间步长为每日。我们根据Daymet的日最高气温和日平均水汽压得出VPD,并基于(1)柯本-盖格气候分类确定的气候和(2)国际地圈-生物圈计划确定的土地覆盖对估算值进行尺度转换。利用代表不同气候和土地覆盖分类的253个AmeriFlux站点的地面VPD数据,对CONUS+网格中每个像素的Daymet得出的VPD估算值进行改进,以生成最终数据集。我们将Daymet得出的VPD与独立观测数据和再分析数据进行了评估。CONUS+ VPD数据集将有助于调查包括干旱和野火在内的干扰,并为土地管理策略提供信息。