Abstract
Vapor Pressure Deficit (VPD) is a principle mediator of global terrestrial CO 2 uptake and water vapor loss through plant stomata. As such, methods to estimate VPD accurately and efficiently are critical for ecosystem and climate modeling efforts. Based on prior work relating energy partitioning, remotely sensed land surface temperature (LST), and VPD, we developed simple linear models to predict VPD using saturated vapor pressure calculated from MODIS LST at a number of different temporal and spatial resolutions. We developed and assessed the LST–VPD models using three data sets: (1) instantaneous and daytime average ground-based VPD and radiometric temperature from the Soil Moisture Experiments in 2002 (SMEX02); (2) daytime average VPD from AmeriFlux eddy covariance flux tower observations; and (3) estimated daytime average VPD from Global Surface Summary of Day (GSSD) observations. We estimated model parameters for VPD estimation both regionally (MOD11 A2) and globally (MOD11 C2) with RMSE values ranging from .32 to .38 kPa. VPD was overestimated along coastlines and underestimated in arid regions with low vegetation cover. Also, residuals were larger with higher VPDs because of the non-linear function of saturation vapor pressure with LST. Linear relationships were seen at multiple scales and appear useful for estimation purposes within a range of 0 to 2.5 kPa.
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