Aerosols affect Earth's climate both directly and indirectly, which is the largest uncertainty in the assessment of radiative forcings affecting anthropogenic climate change. The standard Aerosol Robotic Network (AERONET) aerosol products have been widely used for more than 30 years. Currently, there is strong community interest in the possibility of determining aerosol composition directly from remote sensing observations. This work presents the results of applying such a recently developed approach by Li et al. to extended datasets of the directional sky radiances and spectral aerosol optical depth (AOD) measured by AERONET for the retrievals of aerosol components. First, the validation of aerosol optical properties retrieved by this component approach with AERONET standard products shows good agreement. Then, spatiotemporal variations of the obtained aerosol component concentration are characterized globally, especially the absorbing aerosol species (black carbon, brown carbon, and iron oxides) and scattering aerosol species (organic carbon, quartz, and inorganic salts). Finally, we compared the black carbon (BC) and dust column concentration retrievals to the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), products in several regions of interest (Amazon zone, Desert, and Taklamakan Desert) for new insights on the quantitative assessment of MERRA-2 aerosol composition products (R = 0.60-0.85 for BC; R = 0.75-0.90 for dust). The new value-added and long-term aerosol composition product globally is available online (https://doi.org/10.6084/ m9.figshare.25415239.v1), which provides important measurements for the improvement and optimization of aerosol modeling to enhance estimation of the aerosol radiative forcing. SIGNIFICANCE STATEMENT: In the assessment of climate change, the uncertainty associated with aerosol radiative forcing is the largest one. The purpose of this study is to provide a new value-added and long-term aerosol composition (including absorbing and scattering aerosol species) inversion dataset derived from Aerosol Robotic Network (AERONET) measurements for characterizing their spatiotemporal variations at global scale. We find some new insights on the quantitative assessment of black carbon and dust column concentration products in the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Our results and aerosol composition inversion dataset will provide robust support for the overall improvement and optimization of aerosol modeling to better understand the aerosol radiative forcing.

Springtime near-surface soil thaw event is important for understanding the near-surface earth system. Previous researches based on both active and passive microwave remote sensing technologies have paid scant attention, especially at middle latitudes where the near-surface earth system has been changed substantially by climate change and human activities, and are characterized by more complex climate and land surface conditions than the permafrost areas. SSM/I brightness temperature and QuikSCAT Ku-band backscatter were applied in this study at a case study area of northern China and Mongolia in springtime of 2004. The soil freeze-thaw algorithm was employed for SSM/I data, and a random sampling technique was applied to determine the brightness temperature threshold for 37 GHz vertically polarized radiation: 258.2 and 260.1 K for the morning and evening satellite passes, respectively. A multi-step method was proposed for QuikSCAT Ku-band backscatter based on both field observed soil thaw events and the typical signature of radar backscatter time series when soil thaw event occurred. The method is mainly focuses on the estimated boundary of thaw events and detection of primary thaw date. The passive microwave remote sensing (SSM/I) based result had a good relationship with the near-surface soil temperature, while the active microwave remote sensing (QuikSCAT) based result had both relationships with temperature and soil moisture conditions. And also, QuikSCAT result identifies the geographical boundary of water-drove thaw event, which is crucial for understanding the different types of springtime near-surface soil thaw at middle latitudes.