Can I read Assessment of gridded datasets of various near surface temperature variables over Heihe River Basin: Uncertainties, spatial heterogeneity and clear-sky bias on EtoBox?

Assessment of gridded datasets of various near surface temperature variables over Heihe River Basin: Uncertainties, spatial heterogeneity and clear-sky bias by Shuo Xu; Dongdong Wang; Shunlin Liang; Yuling Liu; Aolin Jia is a Environmental Science article available to read on EtoBox.

What is Assessment of gridded datasets of various near surface temperature variables over Heihe River Basin: Uncertainties, spatial heterogeneity and clear-sky bias about?

Near-surface temperatures, such as air, land surface, and soil temperatures, play significant roles in surface radiation and energy balance. This study assessed nine gridded near-surface temperature products and analyzed the spatial heterogeneity and clear-sky bias of these temperature variables, using extensive measurements collected at Heihe River Basin. The MXD21 (MOD21 and MYD21) product had the lowest root mean square error (RMSE) (3.35 K) among all skin temperature products but a high percentage of missing values (48.4 %). All-weather skin temperature products had comparable accuracy for the interpolated cloudy-sky cases (RMSE 4.92 K) and observed clear-sky pixels (RMSE 3.42 K). For air temperature, AMSR2 had the lowest RMSE (2.48 K), but a high percentage of invalid data (32.5 %); and ERA5 had a worse accuracy (RMSE 3.87 K) but a high spatial resolution and gap-free data coverage. Comparing products from the same data source, air and soil temperatures had higher accuracies than skin temperature. Among the different variables of temperature, the 0 cm soil temperature and skin temperature had higher spatiotemporal heterogeneity than the air temperature and the soil temperature

Who reads Assessment of gridded datasets of various near surface temperature variables over Heihe River Basin: Uncertainties, spatial heterogeneity and clear-sky bias?

Author

Shuo Xu; Dongdong Wang; Shunlin Liang; Yuling Liu; Aolin Jia

Publisher

Elsevier BV

Published

2023

Language

EN

Field

Environmental Science (Physical Sciences)