Surface ocean microbiota determine cloud precursors

Abstract

One pathway by which the oceans influence climate is via the emission of sea spray that may subsequently influence cloud properties. Sea spray emissions are known to be dependent on atmospheric and oceanic physicochemical parameters, but the potential role of ocean biology on sea spray fluxes remains poorly characterized. Here we show a consistent significant relationship between seawater nanophytoplankton cell abundances and sea-spray derived Cloud Condensation Nuclei (CCN) number fluxes, generated using water from three different oceanic regions. This sensitivity of CCN number fluxes to ocean biology is currently unaccounted for in climate models yet our measurements indicate that it influences fluxes by more than one order of magnitude over the range of phytoplankton investigated.

Figure 1

Time series along the PEACETIME (ProcEss studies at the Air-sEa Interface after dust deposition in The Mediterranean sea) ship track of (a) CCN_0.1% concentrations normalized to the sea spray concentration at given particle diameter (Dp). The activation diameter of SSA into cloud droplet at 0.1% supersaturation is visible at the change of colour from purple to red (b) sea spray concentration at given diameters (Dp) normalized with the total sea spray concentration, (c) flux of sea spray aerosol number (SSA_TOT), flux of sea spray larger than 100 nm number (SSA₁₀₀), and flux of CCN at 0.5% and 0.1% supersaturation, CCN_0.5% and CCN_0.1%, respectively.

Figure 2

Correlation plots between the sea spray larger than 100 nm number fluxes (m⁻² cm⁻¹) and the three classes of organic matter in nascent sea spray (MOA, POA, OOA), Sea Surface Temperature (SST, °C), seawater cell abundances (cells ml⁻¹) for nanoeukaryotes (2–20 µm size; NanoPhyto), picoplankton (3 µm or less in size), coccolithophore-like cells, particulate organic carbon (POC, mg ml^-1), and total surface Chl-a (µg l⁻¹), from the Mediterranean cruise data set. Red datapoints indicate a significant positive correlation, Blue a significant negative correlation and grey no significant relationship at the 99.9% confidence level.

Figure 3

SSA larger than 100 nm flux number F_SSA100 (# m⁻² s⁻¹) calculated for a wind speed of 9 m s⁻¹ and 15 °C sea temperature as a function of the NanoPhyto (cells ml⁻¹) from different regions. The solid line indicates the linear fit to the data set.

Figure 4

Global CCN_0,1% emission fluxes (m⁻² s⁻¹) computed for a 15 °C temperature from satellite-based nanoplankton cell abundance in June (e) and December (f). CCN fluxes were computed using Eq. (1), and assuming that CCN_0,1% is equal to SSA₁₀₀. Median annual trends are represented for the different oceanic basins (a) ATL N: North Atlantic, ATL S: South Atlantic, MED: Mediterranean Sea; (b) PAC N: North Pacific, PAC N (South Pacific), (c) IND N (North Indian Ocean), IND S (South Indian Ocean), (d) ARC (Arctic Ocean), ANT (Southern Ocean). Maps provided (e,f) were created using R version 3.4.2. (https://www.R-project.org/).