Reconstruction of historical site-scale dust optical depth (DOD) time series from surface dust records and satellite retrievals in northern China: application to the evaluation of DOD in CMIP6 historical simulations

Abstract

Abstract The biases generated by state-of-the-art climate models in simulating dust optical depth (DOD) remain to be detailed. Here a site-scale DOD dataset in March–August over northern China (NC) during 1980–2001 was reconstructed using the empirical relationship between MODIS-retrieved DOD and dust-event frequencies during 2001–2021. Then, through the combined use of MODIS-based and reconstructed DOD, we evaluated the reproducibility of DOD from 10 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the historical period (1980–2001 and 2002–2014) and under different Shared Socioeconomic Pathways (SSPs) during 2015–2021. The results demonstrate that CMIP6 models and multi-model ensemble mean (MEM) are capable of capturing the spatial pattern of DOD, but with considerable uncertainty and inter-model variability in magnitude. Regionally-averaged DOD is underestimated by 56.09% during 1980–2001 and overestimated by 30.97% during 2002–2014 in MEM over NC. Simultaneously, the inter-model standard deviations are greater than MEM during 2002–2014, suggesting large discrepancies among individual models. Very few models accurately capture the trends in DOD, which can mainly be attributed to the different trends in simulated wind speed (WS), soil moisture, and vegetation cover, and their contributions to dust evolution. Under 4 SSPs, despite the best correlation between SSP1-2.6-modeled and MODIS DOD over Gobi Desert (GD), overestimation of DOD is still observed. More models under SSP1-2.6 capture the positive DOD trend, mainly attributable to positive changes in simulated WS over GD.