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The Great Atlantic Sargassum Belt (GASB) first appeared in 2011 and quickly became the largest interconnected floating biome globally. Sargassum spp. requires both phosphorus (P) and nitrogen (N) for growth, yet the sources fueling the GASB are unclear. Here, we use coral–bound nitrogen isotopes from six coral cores to reconstruct N2 fixation, the primary source of bioavailable N to the surface ocean across the wider Caribbean over the past 120 years. Our data indicate that changes in N2 fixation were controlled by multidecadal and interannual changes in the supply of excess P from equatorial upwelling in the Atlantic. We show that the supply of P from equatorial upwelling and N from the N2 fixation response can explain the extent of the GASB since 2011. # Equatorial upwelling of phosphorus drives Atlantic N~2~ fixation and *Sargassum* blooms This Excel file contains time series data combining coral geochemical records (δ¹⁵N and δ¹⁸O), climate indices, Sargassum biomass, and major riverine outflows. The dataset integrates multiple spatially distributed records to examine long-term variability in nutrient dynamics, climate forcing, and ecological responses in the Caribbean and tropical Atlantic. Values that were not available or are missing are indicated as N/A. ## Column Reference Table File: Caribbean_data_for_DRYAD.xlsx | Column Name | Description | | :----------------------------------- | :------------------------------------------------------------------------------------------------- | | **Year\_CR\_Turneffe** | Calendar year of sampling for coral records from Turneffe Atoll (Belize) and Cahuita (Costa Rica). | | **Cahuita Costa Rica\_d18O\_ts** | Coral δ¹⁸O time series from Cahuita, Costa Rica (proxy for SST and freshwater input). | | **d15N\_CR** | Coral-bound δ¹⁵N from Cahuita, Costa Rica (proxy for nitrogen source/processing). | | **Turneffe Atoll\_d18O\_ts** | Coral δ¹⁸O time series from Turneffe Atoll, Belize. | | **d15N\_Turneffe** | Coral-bound δ¹⁵N from Turneffe Atoll. | | **Date\_MQ** | Sampling date for Martinique (MQ) site. | | **d18O\_MQ** | Coral δ¹⁸O from Martinique. | | **d15N\_MQ** | Coral δ¹⁵N from Martinique. | | **Year Bermuda** | Calendar year for Bermuda coral samples. | | **d15N Bermuda** | Coral δ¹⁵N from Bermuda. | | **Year\_CUBA** | Calendar year for Cuban coral records. | | **d15N\_CUBA** | Coral δ¹⁵N from Cuba. | | **d15N\_Mexico** | Coral δ¹⁵N from Mexico. | | **Year\_Tobago** | Calendar year for Tobago coral samples. | | **d15N\_Tobago** | Coral δ¹⁵N from Tobago. | | **Year AMM** | Year corresponding to Atlantic Meridional Mode (AMM) values. | | **AMM\_SST** | Sea Surface Temperature anomalies associated with the AMM. | | **AMM\_Wind** | Wind anomalies associated with the AMM. | | **AMO** | Atlantic Multidecadal Oscillation index value. | | **average\_year** | Averaged year across all coral records included. | | **AVERAGE\_rescaled** | Composite δ¹⁵N record rescaled across sites. | | **error\_propagated** | Propagated error estimate for the rescaled average. | | **AVERAGE\_rescaled\_noCR\_BM\_TB** | Rescaled δ¹⁵N average excluding Costa Rica, Bermuda, and Tobago. | | **error\_propagated2** | Propagated error for the reduced-site average. | | **Months Sargassum** | Month of Sargassum observation. | | **Monthly Sargassum biomass (tons)** | Monthly biomass estimates of pelagic Sargassum (tons). | | **Year\_SST\_SSS** | Year corresponding to SST/SSS data. | | **SST\_10-20N\_20-60W** | Sea Surface Temperature average over 10–20°N, 20–60°W. | | **SSS\_10-20N\_20-60W** | Sea Surface Salinity average over the same region. | | **U\_windstress\_10\_20N\_58\_62W** | Zonal wind stress (10–20°N, 58–62°W). | | **windspeed\_0\_20N\_20\_50W** | Mean wind speed (0–20°N, 20–50°W). | | **Geo\_u\_12\_18N\_60\_80W (CC)** | Geostrophic zonal velocity (12–18°N, 60–80°W), Caribbean Current proxy. | | **DU\_scav\_areaweight** | Dust deposition (scavenging flux, area-weighted). | | **DU\_ddep\_areaweight** | Dust dry deposition (area-weighted). | | **BC\_scav\_areaweight** | Black carbon scavenging flux (area-weighted). | | **Bc\_ddep\_areaweight** | Black carbon dry deposition (area-weighted). | | **BC\_total\_areaweight** | Total black carbon deposition (area-weighted). | | **DU\_total\_areaweight** | Total dust deposition (area-weighted). | | **Obidos\_Amazon\_m3\_s** | Amazon River discharge at Óbidos station (m³/s). | | **Ciudad Bolivar\_Orinoco\_m3\_s** | Orinoco River discharge at Ciudad Bolívar (m³/s). | | **Year Pstar** | Year corresponding to P\* (phosphorus excess) record. | | **Pstar** | Phosphorus excess (indicator of nutrient balance, micro Molar). | | **Amazon\_outflow\_date** | Date of Amazon outflow measurement. | | **Amazon\_outflow\_km3** | Amazon River outflow volume (km³). | | **Orinoco\_outflow\_date** | Date of Orinoco outflow measurement. | | **Orinoco\_outflow\_km3** | Orinoco River outflow volume (km³). | Links to other publicly accessible locations of the data: * [https://climexp.knmi.nl](http://...) Data was derived from the following sources: * Climate Explorer was used for gridded satellite-derived products (SST, SSS, windspeed, windstress) by using the geographical extent as indicated in the manuscript ## Code/Software No software was used for data analysis, and the codes used for figures and data analyses are available on GitHub ([https://github.com/marinejon/](https://github.com/marinejon/)) 

The number concentration and properties of aerosol particles serving as cloud condensation nuclei (CCN) are important for understanding cloud properties, including in the tropical Atlantic marine boundary layer (MBL), where marine cumulus clouds reflect incoming solar radiation and obscure the low-albedo ocean surface. Studies linking aerosol source, composition, and water uptake properties in this region have been conducted primarily during the summertime dust transport season, despite the region receiving a variety of aerosol particle types throughout the year. In this study, we compare size-resolved aerosol chemical composition data to the hygrocopicity parameter κ derived from size-resolved CCN measurements made during the Elucidating the Role of Clouds-Circulation Coupling in Climate (EUREC4A) and Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) campaigns from January to February 2020. We observed unexpected periods of wintertime long-range transport of African smoke and dust to Barbados. During these periods, the accumulation-mode aerosol particle and CCN Number concentrations as well as the proportions of dust and smoke particles increased, whereas average κ slightly decreased (κ = 0.46 +/- 0.10) from marine background conditions (κ = 0.52 +/- 0.09) when the particles were mostly composed of marine organics and sulfate. Size-resolved chemical analysis shows that smoke particles were the major contributor to the accumulation mode during long-range transport events, indicating that smoke is mainly responsible for the observed increase in CCN number concentrations. Earlier studies conducted at Barbados have mostly focused on the role of dust in CCN, but our results show that aerosol hygroscopicity and CCN number concentrations during wintertime long-range transport events over the tropical North Atlantic are also affected by African smoke. Our findings highlight the importance of African smoke for atmospheric processes and cloud formation over the Caribbean. In the file “Dust_Mass_Conc_Royer2022” dust mass concentrations in grams per meter^3 are provided for each day of sampling. These data were used to generate Figure 2a in the manuscript. The file “Particle_Type_#fract_Royer2022” contains data obtained through CCSEM/EDX analysis and used to generate the temporal chemistry plot (Figure 4) provided in the manuscript. The data contains particle numbers for each particle type identified on stage 3 of the sampler, total particle numbers analyzed for the entire stage 3 sample, as well as particle number fractions in % values. In the file “Size-resolved_chem_Royer2022” we provide particle # and number fraction (%) values used to generate size-resolved chemistry plots in the manuscript (Figures 5a and 5b). The file includes all particle numbers and number fractions for sea salt, aged sea salt, dust+sea salt, dust, dust+smoke, smoke, sulfate, and organic particles in each size bin from 0.1 through 8.058 um during cumulative clean marine periods and CAT Event 1 as described in the manuscript. The file “K_at_0.16S_Royer2022” contains κ values calculated at 0.16% supersaturation (S) throughout the entire sampling period. These data were specifically used to generate the plot in Figure 7a. The file “CCN#_at_0.16S_Royer2022” contains cloud condensation nuclei (CCN) values calculated at 0.16% supersaturation (S) throughout the entire sampling period. These data were used to create the CCN portion of the plot in Figure 7b. 

Abstract. The number concentration and properties of aerosol particles serving ascloud condensation nuclei (CCN) are important for understanding cloudproperties, including in the tropical Atlantic marine boundary layer (MBL), where marine cumulus clouds reflect incoming solar radiation and obscure thelow-albedo ocean surface. Studies linking aerosol source, composition, andwater uptake properties in this region have been conducted primarily duringthe summertime dust transport season, despite the region receiving a varietyof aerosol particle types throughout the year. In this study, we comparesize-resolved aerosol chemical composition data to the hygroscopicityparameter κ derived from size-resolved CCN measurements made duringthe Elucidating the Role of Clouds–Circulation Coupling in Climate (EUREC4A) and Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) campaigns from January to February 2020. Weobserved unexpected periods of wintertime long-range transport of Africansmoke and dust to Barbados. During these periods, the accumulation-mode aerosol particle and CCN number concentrations as well as the proportions ofdust and smoke particles increased, whereas the average κ slightlydecreased (κ=0.46±0.10) from marine backgroundconditions (κ=0.52±0.09) when the submicron particles were mostly composed of marine organics and sulfate. Size-resolved chemicalanalysis shows that smoke particles were the major contributor to theaccumulation mode during long-range transport events, indicating that smokeis mainly responsible for the observed increase in CCN numberconcentrations. Earlier studies conducted at Barbados have mostly focused onthe role of dust on CCN, but our results show that aerosol hygroscopicity and CCN number concentrations during wintertime long-range transport events over the tropical North Atlantic are also affected by African smoke. Ourfindings highlight the importance of African smoke for atmospheric processesand cloud formation over the Caribbean. 

Abstract To resolve the various types of biological ice nuclei (IN) with atmospheric models, an extension of the empirical parameterization (EP) (Phillips et al. 2008; 2013) is proposed to predict the active IN from multiple groups of primary biological aerosol particles (PBAPs). Our approach is to utilize coincident observations of PBAP sizes, concentrations, biological composition, and ice-nucleating ability. The parameterization organizes the PBAPs into five basic groups: fungal spores, bacteria, pollen, viral particles, plant/animal detritus, algae, and their respective fragments. This new biological component of the EP was constructed by fitting predicted concentrations of PBAP IN to those observed at the Amazon Tall Tower Observatory (ATTO) site located in the central Amazon. The fitting parameters for pollen and viral particles, plant/animal detritus, which are much less active as IN than fungal and bacterial groups, are constrained based on their ice nucleation activity from the literature. The parameterization has empirically derived dependencies on the surface area of each group (except algae), and the effects of variability in their mean sizes and number concentrations are represented via their influences on the surface area. The concentration of active algal IN is estimated from literature-based measurements. Predictions of this new biological component of the EP are consistent with previous laboratory and field observations not used in its construction. The EP scheme was implemented in a 0D parcel model. It confirms that biological IN account for most of the total IN activation at temperatures warmer than −20°C and at colder temperatures dust and soot become increasingly more important to ice nucleation. 

Atmospheric aerosol particles with a high viscosity may become inhomogeneously mixed during chemical processing. Models have predicted gradients in condensed phase reactant concentration throughout particles as the result of diffusion and chemical reaction limitations, termed chemical gradients. However, these have never been directly observed for atmospherically relevant particle diameters. We investigated the reaction between ozone and aerosol particles composed of xanthan gum and FeCl 2 and observed the in situ chemical reaction that oxidized Fe 2+ to Fe 3+ using X-ray spectromicroscopy. Iron oxidation state of particles as small as 0.2 μm in diameter were imaged over time with a spatial resolution of tens of nanometers. We found that the loss off Fe 2+ accelerated with increasing ozone concentration and relative humidity, RH. Concentric 2-D column integrated profiles of the Fe 2+ fraction, α , out of the total iron were derived and demonstrated that particle surfaces became oxidized while particle cores remained unreacted at RH = 0–20%. At higher RH, chemical gradients evolved over time, extended deeper from the particle surface, and Fe 2+ became more homogeneously distributed. We used the kinetic multi-layer model for aerosol surface and bulk chemistry (KM-SUB) to simulate ozone reaction constrained with our observations and inferred key parameters as a function of RH including Henry's Law constant for ozone, H O3 , and diffusion coefficients for ozone and iron, D O3 and D Fe , respectively. We found that H O3 is higher in our xanthan gum/FeCl 2 particles than for water and increases when RH decreased from about 80% to dry conditions. This coincided with a decrease in both D O3 and D Fe . In order to reproduce observed chemical gradients, our model predicted that ozone could not be present further than a few nanometers from a particle surface indicating near surface reactions were driving changes in iron oxidation state. However, the observed chemical gradients in α observed over hundreds of nanometers must have been the result of iron transport from the particle interior to the surface where ozone oxidation occurred. In the context of our results, we examine the applicability of the reacto-diffusive framework and discuss diffusion limitations for other reactive gas-aerosol systems of atmospheric importance. 

Abstract. The science guiding the EUREC4A campaign and its measurements is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, EUREC4A marked a turning point in our ability to observationally study factors influencing clouds in the trades, how they will respond to warming, and their link to other components of the earth system, such as upper-ocean processes or the life cycle of particulate matter. This characterization was made possible by thousands (2500) of sondes distributed to measure circulations on meso- (200 km) and larger (500 km) scales, roughly 400 h of flight time by four heavily instrumented research aircraft; four global-class research vessels; an advanced ground-based cloud observatory; scores of autonomous observing platforms operating in the upper ocean (nearly 10 000 profiles), lower atmosphere (continuous profiling), and along the air–sea interface; a network of water stable isotopologue measurements; targeted tasking of satellite remote sensing; and modeling with a new generation of weather and climate models. In addition to providing an outline of the novel measurements and their composition into a unified and coordinated campaign, the six distinct scientific facets that EUREC4A explored – from North Brazil Current rings to turbulence-induced clustering of cloud droplets and its influence on warm-rain formation – are presented along with an overview of EUREC4A's outreach activities, environmental impact, and guidelines for scientific practice. Track data for all platforms are standardized and accessible at https://doi.org/10.25326/165 (Stevens, 2021), and a film documenting the campaign is provided as a video supplement.