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Volume scattering functions were measured using two instruments in waters near the Ocean Station Papa (50°N 145°W) and show consistency in estimating the$\mathrm{\chi <\#comment/>}$factor attributable to particles (${\mathrm{\chi <\#comment/>}}_p$). While${\mathrm{\chi <\#comment/>}}_p$in the study area exhibits a limited variability, it could vary significantly when compared with data obtained in various parts of the global oceans. The global comparison also confirms that the minimal variation of${\mathrm{\chi <\#comment/>}}_p$is at scattering angles near 120°. With an uncertainty of$<<\#comment/>10\mathrm{\%<\#comment/>}$,${\mathrm{\chi <\#comment/>}}_p$can be assumed as spectrally independent. For backscatter sensors with wide field of view (FOV), the averaging of scattering within the FOV reduces the values of${\mathrm{\chi <\#comment/>}}_p$needed to compute the backscattering coefficient by up to 20% at angles$<<\#comment/>{130}^{\circ <\#comment/>}$.

 

Because the diffusivity of particles undergoing the Brownian motion is inversely proportional to their sizes, the size distribution of submicron particles can be estimated by tracking their movement. This particle tracking analysis (PTA) has been applied in various fields, but mainly focused on resolving monodispersed particle populations and is rarely used for measuring oceanic particles that are naturally polydispersed. We demonstrated using Monte Carlo simulation that, in principle, PTA can be used to size natural, oceanic particles. We conducted a series of lab experiments using microbeads of NIST‐traceable sizes to evaluate the performance of ViewSizer 3000, a PTA‐based commercial instrument, and found two major uncertainties: (1) the sample volume varies with the size of particles and (2) the signal‐to‐noise ratio for particles of sizes < 200–250 nm was reduced and hence their concentration was underestimated with the presence of larger particles. After applying the volume correction, we found the instrument can resolve oceanic submicron particles of sizes greater than 250 nm with a mean absolute error of 3.9% in size and 38% in concentration.

 

Properly interpreting lidar (light detection and ranging) signal for characterizing particle distribution relies on a key parameter,${\mathrm{\chi <\#comment/>}}_p(\mathrm{\pi <\#comment/>})$, which relates the particulate volume scattering function (VSF) at 180° (${\mathrm{\beta <\#comment/>}}_p(\mathrm{\pi <\#comment/>})$) that a lidar measures to the particulate backscattering coefficient ($b_{\mathit{\text{bp}}}$). However,${\mathrm{\chi <\#comment/>}}_p(\mathrm{\pi <\#comment/>})$has been seldom studied due to challenges in accurately measuring${\mathrm{\beta <\#comment/>}}_p(\mathrm{\pi <\#comment/>})$and$b_{\mathit{\text{bp}}}$concurrently in the field. In this study,${\mathrm{\chi <\#comment/>}}_p(\mathrm{\pi <\#comment/>})$, as well as its spectral dependence, was re-examined using the VSFs measuredin situat high angular resolution in a wide range of waters.${\mathrm{\beta <\#comment/>}}_p(\mathrm{\pi <\#comment/>})$, while not measured directly, was inferred using a physically sound, well-validated VSF-inversion method. The effects of particle shape and internal structure on the inversion were tested using three inversion kernels consisting of phase functions computed for particles that are assumed as homogenous sphere, homogenous asymmetric hexahedra, or coated sphere. The reconstructed VSFs using any of the three kernels agreed well with the measured VSFs with a mean percentage difference$<<\#comment/>5\mathrm{\%<\#comment/>}$at scattering angles$<<\#comment/>{170}^{\circ <\#comment/>}$. At angles immediately near or equal to 180°, the reconstructed${\mathrm{\beta <\#comment/>}}_p(\mathrm{\pi <\#comment/>})$depends strongly on the inversion kernel.${\mathrm{\chi <\#comment/>}}_p(\mathrm{\pi <\#comment/>})$derived with the sphere kernels was smaller than those derived with the hexahedra kernel but consistent with${\mathrm{\chi <\#comment/>}}_p(\mathrm{\pi <\#comment/>})$estimated directly from high-spectral-resolution lidar andin situbackscattering sensor. The possible explanation was that the sphere kernels are able to capture the backscattering enhancement feature near 180° that has been observed for marine particles.${\mathrm{\chi <\#comment/>}}_p(\mathrm{\pi <\#comment/>})$derived using the coated sphere kernel was generally lower than those derived with the homogenous sphere kernel. Our result suggests that${\mathrm{\chi <\#comment/>}}_p(\mathrm{\pi <\#comment/>})$is sensitive to the shape and internal structure of particles and significant error could be induced if a fixed value of${\mathrm{\chi <\#comment/>}}_p(\mathrm{\pi <\#comment/>})$is to be used to interpret lidar signal collected in different waters. On the other hand,${\mathrm{\chi <\#comment/>}}_p(\mathrm{\pi <\#comment/>})$showed little spectral dependence.

 

The volume scattering functions for bulk and two submicron size fractions (passing through 0.7 μm GF/F and 0.2 μm membrane filters) were measured in the North Pacific Ocean using a LISST‐VSF to assess the contributions by submicron particles to the overall particle scattering. The contribution by submicron particles increased generally with scattering angle and peaked around 110°. The total backscattering by both submicron fractions did not vary, but that by larger particles increased, with the trophic level. Consequently, the fractional backscattering contribution by submicron particles decreased from approximately 50% to 30% as the chlorophyll‐a concentration increased from <0.1 to 0.3 mg m⁻³. Despite the experiment covering a limited range of trophic levels, our results confirm that backscattering by submicron particles in clear ocean waters is significant and seems to form a background independent of the backscattering by larger particles.

 

The goal of the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) field campaign is to develop a predictive understanding of the export, fate, and carbon cycle impacts of global ocean net primary production. To accomplish this goal, observations of export flux pathways, plankton community composition, food web processes, and optical, physical, and biogeochemical (BGC) properties are needed over a range of ecosystem states. Here we introduce the first EXPORTS field deployment to Ocean Station Papa in the Northeast Pacific Ocean during summer of 2018, providing context for other papers in this special collection. The experiment was conducted with two ships: a Process Ship, focused on ecological rates, BGC fluxes, temporal changes in food web, and BGC and optical properties, that followed an instrumented Lagrangian float; and a Survey Ship that sampled BGC and optical properties in spatial patterns around the Process Ship. An array of autonomous underwater assets provided measurements over a range of spatial and temporal scales, and partnering programs and remote sensing observations provided additional observational context. The oceanographic setting was typical of late-summer conditions at Ocean Station Papa: a shallow mixed layer, strong vertical and weak horizontal gradients in hydrographic properties, sluggish sub-inertial currents, elevated macronutrient concentrations and low phytoplankton abundances. Although nutrient concentrations were consistent with previous observations, mixed layer chlorophyll was lower than typically observed, resulting in a deeper euphotic zone. Analyses of surface layer temperature and salinity found three distinct surface water types, allowing for diagnosis of whether observed changes were spatial or temporal. The 2018 EXPORTS field deployment is among the most comprehensive biological pump studies ever conducted. A second deployment to the North Atlantic Ocean occurred in spring 2021, which will be followed by focused work on data synthesis and modeling using the entire EXPORTS data set.