Saharan Dust Fertilizing Atlantic Ocean and Amazon Rainforest via Long-range Transport and Deposition: A Perspective from Multiyear Satellite Measurements

Massive dust emitted from Sahara desert is carried by trade winds across the tropical Atlantic Ocean, reaching the Amazon Rainforest and Caribbean Sea. Airborne dust degrades air quality and interacts with radiation and clouds. Dust falling to land and ocean adds essential nutrients that could increase the productivity of terrestrial and aquatic ecosystems and modulate the biogeochemical cycles and climate. The resultant climate change will feed back on the production of dust in Sahara desert and its subsequent transport and deposition. Understanding the connections among the remote ecosystems requires an accurate quantification of dust transport and deposition flux on large spatial and temporal scales, in which satellite remote sensing can play an important role. We provide the first multiyear satellite-based estimates of altitude-resolved across-Atlantic dust transport and deposition based on eight-year (2007-2014) record of aerosol three-dimensional distributions from the CALIPSO lidar. On a basis of the 8-year average, 179 Tg (million tons) of dust leaves the coast of North Africa and is transported across Atlantic Ocean, of which 102, 20, and 28 Tg of dust is deposited into the tropical Atlantic Ocean, Caribbean Sea, and Amazon Rainforest, respectively. The dust deposition adds 4.3 Tg of iron and 0.1 Tg of phosphorus to the tropical Atlantic Ocean and Caribbean Sea where the productivity of marine ecosystem depends on the availability of these nutrients. The 28 Tg of dust provides about 0.022 Tg of phosphorus to Amazon Rainforest yearly that replenishes the leak of this plant-essential nutrient by rains and flooding, suggesting an important role of Saharan dust in maintaining the productivity of Amazon rainforest on timescales of decades or centuries. We will also discuss seasonal and interannual variations of the dust transport and deposition, and comparisons of the CALIOP-based estimates with model simulations.