Surface albedo feedback (SAF) is one of the main causes of amplified warming over the Tibetan Plateau (TP). Several recent studies have used the latest reanalysis datasets to evaluate the SAF induced warming, but without fully considering the fidelity of the surface albedo change and surface downward solar radiation in the reanalysis datasets, which directly affect the amplitude of SAF induced warming. This study finds that the state-of-the-art reanalysis datasets (ERA-Interim, ERA5, MERRA, MERRA-2, JRA-55 and CRA) and climate models that participated in the Coupled Model Intercomparison Project Phase 6 (CMIP6) exhibit varying biases compared with observations in both surface albedo change and surface downward solar radiation over the TP. The state-of-the-art reanalysis datasets present no obvious advantages over the lower resolution but less constrained CMIP6 multi-model ensemble in representing SAF related processes over the TP. The surface albedo change drives most of the spread in SAF induced warming. The reanalysis datasets and CMIP6 climate models reveal a significant linear relationship between surface albedo change and its contribution to surface temperature change over the TP. Using the observation constrained linear relationship and satellite surface albedo products, the spread of warming contribution due to SAF in reanalysis datasets and climate models is greatly reduced, the estimated TP warming due to SAF is in the range of 0.26–0.50 K in winter and 0.27–0.77 K in spring over recent decades.
|Julkaisu||Journal of Geophysical Research: Atmospheres|
|DOI - pysyväislinkit|
|Tila||Julkaistu - 16 heinäk. 2022|
|OKM-julkaisutyyppi||A1 Vertaisarvioitu alkuperäisartikkeli|