Abstract
Surface all-wave net radiation (Rn) is a crucial variable driving many terrestrial latent heat (LE) models that estimate global LE. However, the differences between different Rn products and their impact on global LE estimates still remain unclear. In this study, we evaluated two Rn products, Global LAnd Surface Satellite (GLASS) beta version Rn and Modern-Era Retrospective Analysis for Research and Applications-version 2 (MERRA-2) Rn, from 2007–2017 using ground-measured data from 240 globally distributed in-situ radiation measurements provided by FLUXNET projects. The GLASS Rn product had higher accuracy (R2 increased by 0.04–0.26, and RMSE decreased by 2–13.3 W/m2) than the MERRA-2 Rn product for all land cover types on a daily scale, and the two Rn products differed greatly in spatial distribution and variations. We then determined the resulting discrepancies in simulated annual global LE using a simple averaging model by merging five diagnostic LE models: RS-PM model, SW model, PT-JPL model, MS-PT model, and SIM model. The validation results showed that the estimated LE from the GLASS Rn had higher accuracy (R2 increased by 0.04–0.14, and RMSE decreased by 3–8.4 W/m2) than that from the MERRA-2 Rn for different land cover types at daily scale. Importantly, the mean annual global terrestrial LE from GLASS Rn was 2.1% lower than that from the MERRA-2 Rn. Our study showed that large differences in satellite and reanalysis Rn products could lead to substantial uncertainties in estimating global terrestrial LE.
Highlights
Understanding the dynamics of global terrestrial water and carbon fluxes is urgent for the mitigation of climate change, which is characterized by global warming associated with increasing carbon dioxide (CO2) concentrations
Jiang et al found a large gap between CERES-SYN, MERRA-2, JRA55, and Global LAnd Surface Satellite (GLASS) Rn products that were validated using in situ observation data [10]
Our result showed that GLASS Rn had higher accuracy than MERRA-2 Rn for all land cover types on a daily scale (R2 increased by 0.04–0.26, and RMSE decreased by 2–13.3 W/m2)
Summary
Understanding the dynamics of global terrestrial water and carbon fluxes is urgent for the mitigation of climate change, which is characterized by global warming associated with increasing carbon dioxide (CO2) concentrations. There are currently many satellite and reanalysis Rn products available at regional and global scales Among these Rn products, reanalysis Rn datasets, e.g., MERRA-2, have a high temporal resolution (hourly) but the rather coarse spatial resolution (>20 km) [22]. Several studies have evaluated the accuracy of Rn products using ground-observed data from in situ measurements, and they have found that there are critical uncertainties and differences between several Rn products [26,27]. The uncertainty in the global Rn products can lead to uncertainty in terrestrial LE estimation from multiple diagnostic models. We evaluated Global LAnd Surface Satellite (GLASS) beta version Rn and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) Rn products and detected the impacts of these Rn products on annual global terrestrial LE. We evaluated the effects of Rn on estimated terrestrial LE at the site and global scales
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