A large source of cloud condensation nuclei from new particle formation in the tropics

Abstract

Cloud condensation nuclei (CCN) can affect cloud properties and therefore Earth’s radiative balance1,2,3. New particle formation (NPF) from condensable vapours in the free troposphere has been suggested to contribute to CCN, especially in remote, pristine atmospheric regions4, but direct evidence is sparse, and the magnitude of this contribution is uncertain5,6,7. Here we use in situ aircraft measurements of vertical profiles of aerosol size distributions to present a global-scale survey of NPF occurrence. We observe intense NPF at high altitudes in tropical convective regions over both Pacific and Atlantic oceans. Together with the results of chemical-transport models, our findings indicate that NPF persists at all longitudes as a global-scale band in the tropical upper troposphere, covering about 40 per cent of Earth’s surface. Furthermore, we find that this NPF in the tropical upper troposphere is a globally important source of CCN in the lower troposphere, where CCN can affect cloud properties. Our findings suggest that the production of CCN as new particles descend towards the surface is not adequately captured in global models, which tend to underestimate both the magnitude of tropical upper tropospheric NPF and the subsequent growth of new particles to CCN sizes.

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Fig. 1: New particle formation and growth to CCN sizes in the tropical convective region.

Image courtesy of K. Bogan, Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder.

Fig. 2: Average aerosol properties from ATom 1 and 2.
Fig. 3: The relationship between CS7, temperature and NPF.
Fig. 4: Evidence for particle growth on descent.

Data availability

The full ATom data set is publicly available15, as are data specific to this analysis65.

Code availability

Code for the model CESM with the base version of CARMA is available online66 as is code for GEOS-Chem with TOMAS and APM67. Code used to analyse ATom data and model output, and recent modifications to CARMA, GEOS-Chem and CAM5 with APM used here, is available on request.

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Acknowledgements

We thank J. Kazil, G. Feingold, T. Goren, D. Fahey and K. Aikin for contributing to this analysis, and the ATom leadership team, science team and crew for contributions to the ATom measurements. We acknowledge support from the US NASA Earth System Science Pathfinder Program under awards NNH15AB12I, NNX15AJ23G, NNX15AH33A and 80NSSC19K0124, and from the US National Oceanic and Atmospheric Administration (NOAA) Health of the Atmosphere and Atmospheric Chemistry, Carbon Cycle, and Climate Programs. A.K. was supported by the Austrian Science Fund’s Erwin Schrodinger Fellowship J-3613. J.R.P., J.K.K., K.R.B. and A.L.H. were supported by the US Department of Energy’s Atmospheric System Research, an Office of Science, Office of Biological and Environmental Research program, under grants DE-SC0019000 and DE-SC0011780; the US National Science Foundation (NSF), Atmospheric Chemistry program, under grant AGS-1559607; and the NOAA, Office of Science, Office of Atmospheric Chemistry, Carbon Cycle, and Climate Program, under cooperative agreement award NA17OAR430001. G.L. and F.Y. acknowledge funding support from NASA under grant NNX17AG35G and from the NSF under grant AGS-1550816. B.W. and M.D. have received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation framework program under grant 640458 (A-LIFE) and from the University of Vienna. P.Y. acknowledges the second Tibetan Plateau Scientific Expedition and Research Program (2019QZKK0604).

Author information

C.J.W., A.K., C.A.B., M.D., B.W., K.D.F., D.M.M., P.C.-J., B.A.N., J.L.J. and T.B. collected the data, and C.J.W. wrote the manuscript with contributions from C.A.B., A.K., J.R.P., K.D.F., D.M.M., P.C.-J., J.L.J. and E.A.R. C.J.W., A.K. and C.A.B. analysed the size distributions. M.D. and B.W. analysed cloud properties. K.D.F. and D.M.M. analysed single-particle compositions, and P.C.-J., B.A.N. and J.L.J. analysed bulk particle composition. J.K.K., A.L.H., K.R.B. and J.R.P. ran GEOS-Chem-TOMAS and J.R.P. developed methods for understanding relevant tropical dynamics. G.L. and F.Y. ran GEOS-Chem-APM and CAM5-APM, and P.Y. ran CESM-CARMA. E.A.R. ran the ATom back trajectories. D.A. and J.C.W. developed the relative differencing method.

Correspondence to Christina J. Williamson.

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Extended data figures and tables

Extended Data Fig. 1 Location of ATom measurements.

a, ATom 1 (gold) and ATom 2 (blue) measurements by latitude and longitude. b, c, Altitude and latitude of measurements over the Pacific Ocean (b) and Atlantic Ocean (c). TCRs are highlighted in red (for ATom 1) and dark blue (for ATom 2). The world map was made with Natural Earth68Source Data.

Extended Data Fig. 2 Identifying the tropical convective region.

Shown are average measured relative humidity over water (RHwater; blue); number concentration of particles of 3 nm or more (N3 nm; red); and cloud fraction from reanalysis meteorology (dashed black) at pressures between 200 hPa and 400 hPa. a, b, ATom 1 Pacific (a) and Atlantic (b) transects. c, d, ATom 2 Pacific (c) and Atlantic (d) transects. We take the central peak in relative humidity to be the intertropical convergence zone (ITCZ), and define a tropical convective region (TCR) between the minima on either side of this peak (grey shaded region). These minima correspond to latitudes 2.5° N to 17.5° N for ATom 1 Pacific; 2.5° N to 27.5° N for ATom 1 Atlantic; 27.5° S to 2.5° S for ATom 2 Pacific; and 7.5° S to 22.5° S for ATom 2 AtlanticSource Data.

Extended Data Fig. 3 Modelled global concentrations of particles larger than 3 nm.

Shown are the monthly mean number concentration of particles bigger than 3 nm in the free troposphere at pressures less than 600 hPa (weighted by grid-box height), modelled for August 2016 (left) and February 2017 (right). a, b, CESM-CARMA; c, d, CAM5-APM; e, f, GEOS-Chem-APM; and g, h, GEOS-Chem-TOMAS. Horizontal black lines mark the TCR defined by the ATom data. GEOS-Chem-TOMAS (g, h) shows higher number concentrations of N3 particles outside the TCR than do the other models. This is partly the effect of the 2009 volcanic emissions, which are included in the emissions database for this model. The world maps are made using Natural Earth68Source Data.

Extended Data Fig. 4 Condensation and coagulation rates.

a, Relationship between the gas-phase condensation rate onto particles larger than 7 nm, the coagulation rate between 5-nm particles and all other particles, and the total aerosol surface area (2.6–4,800 nm), which show a strongly linear relationship. b, The contribution of each particle-size mode to the average condensation rate in the TCR as a function of pressure. The graph shows that the coagulation sink is not always dominated by particles larger than 60 nm, but that, especially at high altitudes, particles of 12–60 nm (the Aitken mode) can dominate the coagulation sink, and must therefore be considered. Lines show the 50th percentile and shaded areas the 25th to 75th percentile rangeSource Data.

Extended Data Fig. 5 TCR back trajectories.

30-day back trajectories were calculated every minute of flight time within the TCRs. ad, Pressures from the time of minimum pressure of the trajectory to the flight track are plotted for all back trajectories from ATom 1 Pacific (a) and Atlantic (b) and ATom 2 Pacific (c) and Atlantic (d) observations. Colours distinguish separate trajectories. The general slope of increasing pressure with time indicates a general descending motion of the air. e, Histogram showing instantaneous descent rates (one point every 3 h) for all trajectories within the indicated pressure bins. The skew at all altitudes towards positive descent rates is evidence of an overall descending motion of the air. The mean descent rate is higher at higher altitudes, and almost 0 at the lowest altitudes, which is to be expected as this is often within the marine boundary layer where the air cannot descend further. f, Average fraction of time that trajectories spent in cloud between the time of minimum pressure and the flight track. In-cloud time is taken to be times when relative humidities are 90% or more (an overestimate). It is binned by the pressure on the flight track (not the pressure of the trajectory itself, as in e). For measurements made at pressures of less than 850 hPa, the air spent less than 5% of its time in cloud on average. For air at pressures of more than 850 hPa, this time increased to around 14%. This shows that most of the particles descend with the air instead of being removed by clouds. g, h, Histograms of the latitudes of trajectories between the minimum pressure and flight track for ATom 1 (g) and ATom 2 (h), coloured by pressure of the point on the flight track. Except for at the lowest altitudes, air parcels entering the flight track mostly remain within the tropics (with histograms peaking around the equator). Peaks shift towards the summer hemisphere with the season, in the same manner as the TCRsSource Data.

Extended Data Fig. 6 Average size distributions.

ac, Average size distributions in TCRs at pressures between 250 hPa and 300 hPa, 600 hPa and 800 hPa, and 800 hPa and 1,000 hPa respectively. Regions of biomass burning or dust plumes have been excluded. Except for particles larger than 100 nm in CAM5-APM, the models show fewer particles than do the ATom observations. All models except for CAM5-APM also show strong evidence of cloud processing, in the form of the dip in the size distribution around 60–100 nm in b, c. This indication of cloud processing25 is far less pronounced in the ATom data, suggesting that too many particles are being cloud processed in the models. b also shows average size distributions measured between 900 hPa and 1,000 hPa over the contiguous USA and Alaska, as examples of continental size distributions. BL, boundary layerSource Data.

Extended Data Fig. 7 Chemical composition of particles in the TCRs.

a, Organic and sulfate mass of particles, measured by the AMS (for particles of 50–500 nm) and PALMS (for particles of 150–500 nm), and ambient relative humidity (RHw), with data affected by biomass burning and dust plumes being removed. (The AMS excludes ATom 2 measurements for the Pacific Ocean, where the overall mass was too low to measure sulfate and organic components.) Both methods for measuring organic and sulfate mass have limitations in this regime (the AMS is close to the detection limit, and PALMS cannot measure particles smaller than 150 nm), so perfect agreement is not expected. However, the low sulfate mass at high altitude seems robust, as it is supported by both measurements, and differences between the organic concentrations obtained by PALMS and AMS suggest that organics dominate the composition of smaller particles at high altitudes. b, Size-resolved volume in the TCRs. Between 400 hPa and 800 hPa, the median diameter by volume, and the majority of the aerosol volume, is within the measured 50–500-nm range. The composition results should thus be regarded as informative within this pressure range. dV/dlogDp, log-normalized volume concentration. c, d, Modelled sulfate and organic masses over the same regions, compared with measurementsSource Data.

Extended Data Fig. 8 Details from NMASS data.

a, Identifying instrumental noise in particle measurements, using Fourier transforms of the number concentration of particles larger than 3 nm (N3) as measured in the first NMASS channel for 30 min of data at different altitudes and different total concentrations. b, Concentrations from the first and second channels of NMASS 1 (red solid and blue dotted lines respectively), and the calculated relative difference (black), for an example time period. Missing data occur when the aircraft flew through a cloud and the data were discarded. A relative difference of three standard deviations (3 sigma) is shown with a dashed horizontal line. Any relative difference larger than this is considered statistically significantSource Data.

Extended Data Fig. 9 Sensitivity studies and radiative effects.

af, Modelled N60 values (ac) and condensation sinks (df) in the GEOS-Chem-TOMAS (a, d), GEOS-Chem-APM (b, e) and CESM-CARMA (c, f) models, showing the base model run (red), the nucleation rates increased by a factor of ten between 28° N and 28° S at pressures of less than 600 hPa (orange), oceanic emissions of DMS tripled (light blue), cloud processing on descent reduced by a factor of ten (dark blue), and nucleation turned off between 28° N and 28° S at pressures of less than 600 hPa (dashed). These modelling results are compared with the ATom 1 Pacific observations (black and grey). gj, Simulated aerosol indirect effect (difference in radiative effect) of tropical upper tropospheric NPF (g, h, GEOS-Chem-TOMAS; i, j, GEOS-Chem-APM), for the base (g, i) and reduced cloud processing (h, j) cases, calculated by turning off nucleation at 28° N to 28° S at pressures below 600 hPa. k, The seasonal cycle of this global aerosol indirect effect from GEOS-Chem-TOMAS, for the base (red) and reduced cloud processing (blue) cases. Maps made using Natural Earth68Source Data.

Extended Data Table 1 Relevant properties of the models used here

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Williamson, C.J., Kupc, A., Axisa, D. et al. A large source of cloud condensation nuclei from new particle formation in the tropics. Nature 574, 399–403 (2019). https://doi.org/10.1038/s41586-019-1638-9

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