Evaluating NASA GEOS Simulation of Transatlantic Dust Transport and Deposition with Satellite Remote Sensing Products

Massive dust emitted from North Africa can transport long distances across the tropical Atlantic Ocean, reaching the Americas. Dust deposition along the transit adds microorganisms and essential nutrients to marine ecosystem, which has important implications for biogeochemical cycle and climate. However, assessing the dust-ecosystem–climate interactions has been hindered in part by the paucity of dust deposition measurements and large uncertainties associated with oversimplified representations of dust processes in current models. We have recently produced a unique dataset of dust optical depth, dust deposition flux, and dust loss frequency over the tropical Atlantic Ocean by using the decade-long (2007-2016) record of aerosol three-dimensional distribution from four satellite sensors, namely CALIOP, MODIS, MISR, and IASI. Dust loss frequency or removal efficiency is a useful diagnostic that makes it possible to disentangle the dust transport and removal processes from the dust emissions when identifying the major factors contributing to the uncertainties and biases in the model simulated dust deposition. In this study, we use the satellite-based dataset along with in situ observations to assess how well NASA GEOS model performs in simulating trans-Atlantic dust transport and deposition. We found that the GEOS modeling of dust deposition falls within the range of satellite-based estimates. However, this reasonable agreement in dust deposition is a compensation of the model’s underestimate of dust emissions and overestimate of dust removal efficiency. Furthermore, the overestimate of dust removal efficiency results largely from the model’s overestimate of rainfall rate. Our results provide insights into the model’s deficiencies at process level, which could better guide model improvement.