Developing a Comprehensive and Augmented Multi-decadal Remote-sensing Observations of Dust (CAMRO-Dust) Data Record for Earth Science Research and Applications

Desert dust is abundant and recognized as an integral component of the Earth system that influences weather and climate via a suite of complex interactions with the energy, water, and carbon cycles. Dust storms cause detrimental losses of human life and economic activities through degrading air quality, spreading diseases, disrupting transportation, and reducing efficiency of solar power generation. There has been growing attention in the past decades to advancing the research of dust cycle and its tight coupling with other bio-geo-chemical components of the Earth system and human dimension. However, dust varies greatly across a wide range of temporal and spatial scales, resulting from a combination of sporadic nature of dust events, large variability of transport and removal processes, and the tight and complex coupling of dust with other components of the Earth system. Although data assimilation has been widely used in the satellite era to impose strong constraint on aerosol optical depth, dust is at most weakly constrained due to large uncertainty in model simulations of aerosol components and vertical distribution. Dust deposition from the reanalysis would suffer from a mass imbalance issue. It is thus critical to develop a comprehensive, remote-sensing observations based, and self-consistent global dust data record over multi-decadal time scales. Built upon our extensive experience in satellite remote sensing, machine learning, and aerosol modeling, we propose to develop a Comprehensive and Augmented Multi-decadal Remote-sensing Observations of Dust (CAMRO-Dust) data record by integrating multiple satellites (MODIS, VIIRS, IIR, and CALIOP) and developing novel approaches. Dust properties include dust optical depth at both mid-visible and thermal infrared wavelengths, fine and coarse dust vertical distributions, dust deposition fluxes into oceans, and dust PM_2.5. The so-produced dynamically consistent data record of dust can be used to advance the observational understandings of the interannual variability and trend of dust over recent decades, dust direct radiative effects on both solar and terrestrial radiation, air quality and health impacts of dust, and dust fertilizing effect on oceanic ecosystems. The comprehensive dust data set can also be used to systematically evaluate global and regional air quality, climate, and earth system models and effectively guide the reduction of modeling uncertainties. In this presentation, we will provide an overview of the CAMRO-Dust and several initial efforts.