This study derives two observation-based global monthly mean dust aerosol optical depth (DAOD) climatological datasets from 2007 to 2019, one based on Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and the other on Moderate Resolution Imaging Spectroradiometer (MODIS) observations. The CALIOP dataset includes dust vertical extinction profiles, while the MODIS dataset distinguishes dust from non-dust aerosols based on particle size, shape, and absorption properties. Both datasets are compared with previous studies and collocated Aerosol Robotic Network (AERONET) coarse-mode AOD, showing reasonable agreement. The global annual mean DAOD is 0.032 and 0.067 for CALIOP and MODIS, respectively. CALIOP DAOD generally correlates well with MODIS DAOD, but is significantly smaller, especially over the Sahara, tropical Atlantic Ocean, Caribbean Sea, and Arabian Sea. Adjusting the CALIOP lidar ratio reduces the difference. The datasets are used to study the spatial and temporal climatology of dust, showing similar seasonal and interannual variations, including a declining trend of DAOD in key dust regions. The study highlights the importance of comparing satellite-based DAOD datasets to improve understanding and modeling of dust aerosols.This study derives two observation-based global monthly mean dust aerosol optical depth (DAOD) climatological datasets from 2007 to 2019, one based on Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and the other on Moderate Resolution Imaging Spectroradiometer (MODIS) observations. The CALIOP dataset includes dust vertical extinction profiles, while the MODIS dataset distinguishes dust from non-dust aerosols based on particle size, shape, and absorption properties. Both datasets are compared with previous studies and collocated Aerosol Robotic Network (AERONET) coarse-mode AOD, showing reasonable agreement. The global annual mean DAOD is 0.032 and 0.067 for CALIOP and MODIS, respectively. CALIOP DAOD generally correlates well with MODIS DAOD, but is significantly smaller, especially over the Sahara, tropical Atlantic Ocean, Caribbean Sea, and Arabian Sea. Adjusting the CALIOP lidar ratio reduces the difference. The datasets are used to study the spatial and temporal climatology of dust, showing similar seasonal and interannual variations, including a declining trend of DAOD in key dust regions. The study highlights the importance of comparing satellite-based DAOD datasets to improve understanding and modeling of dust aerosols.