Vinicius Jose Amaral1, Olivier Marchal2, Jong-Mi Lee3, Phoebe J Lam1, Montserrat Roca Martí4 and Ken Buesseler5, (1)University of California Santa Cruz, Department of Ocean Sciences, Santa Cruz, United States, (2)Woods Hole Oceanographic Institution, Department of Geology and Geophysics, Woods Hole, MA, United States, (3)University of California Santa Cruz, Ocean Sciences, Santa Cruz, CA, United States, (4)Universitat Autònoma de Barcelona (UAB), Institut de Ciència i Tecnologia Ambientals (ICTA-UAB), Cerdanyola del Vallès, Spain, (5)Woods Hole Oceanographic Institution, Department of Marine Chemistry & Geochemistry, Woods Hole, United States
The processes of particle aggregation and particle disaggregation are of
paramount importance for the downward transport of particulate material
and of their chemical constituents through the oceanic water column.
Particle aggregation tends to increase the size of particles and thus to
enhance their gravitational settling speed, whereas particle
disaggregation redistributes material into the smaller size classes.
However, our current observational understanding of the rates of
particle (dis)aggregation in oceanic waters remains severely limited as
these processes are difficult to measure directly. Here, following the
work of R. Murnane and colleagues undertaken in the 1990s, we apply an
inverse method to fit the equations of a two particle size class model
to size-fractionated data of particulate organic carbon and lithogenic
material (Ti and Al) from the EXPORTS cruise in the eastern North
Pacific. The outcome of the fit is an estimate of apparent rate
constants of particle (dis)aggregation rates and of their uncertainties
in the upper 500 m of the water column at a number of stations and
depths sampled during the cruise. Our estimates represent the integrated
effects of all processes contributing to particle (dis)aggregation, in
contrast to other projects of the EXPORTS program that are dedicated to
a few of such processes. Our estimates of particle cycling rates deduced
from the inversion of chemical tracer data thus provide a valuable
quantitative constraint to which rates derived from other approaches
could be compared.