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Biomass burning is one of the largest sources of carbonaceous aerosols in the atmosphere, significantly affecting earth’s radiation budget and climate. Tar balls, abundant in biomass burning smoke, absorb sunlight and have highly variable optical properties, typically not accounted for in climate models. Here we analyse single biomass burning particles from the Las Conchas fire (New Mexico, 2011) using electron microscopy. We show that the relative abundance of tar balls (80%) is 10 times greater than soot particles (8%). We also report two distinct types of tar balls; one less oxidized than the other. Furthermore, the mixing of soot particles with other material affects their optical, chemical and physical properties. We quantify the morphology of soot particles and classify them into four categories: ~50% are embedded (heavily coated), ~34% are partly coated, ~12% have inclusions and~4% are bare. Inclusion of these observations should improve climate model performances. Biomass burning is a major source of carbonaceous particles, including tar balls and soot, that affect earth’s climate. Studying a wildfire plume, this work identifies two types of tar balls and classifies soot according to its mixing state with implications for the calculation of aerosol radiative forcing.

Black carbon (BC) and light-absorbing organic carbon (brown carbon, BrC) play key roles in warming the atmosphere, but the magnitude of their effects remains highly uncertain. Theoretical modelling and laboratory experiments demonstrate that coatings on BC can enhance BC’s light absorption, therefore many climate models simply assume enhanced BC absorption by a factor of ∼1.5. However, recent field observations show negligible absorption enhancement, implying models may overestimate BC’s warming. Here we report direct evidence of substantial field-measured BC absorption enhancement, with the magnitude strongly depending on BC coating amount. Increases in BC coating result from a combination of changing sources and photochemical aging processes. When the influence of BrC is accounted for, observationally constrained model calculations of the BC absorption enhancement can be reconciled with the observations. We conclude that the influence of coatings on BC absorption should be treated as a source and regionally specific parameter in climate models. Uncertainties in the absorptive properties of black and brown carbon particles limit our understanding of their warming potential. Following an extensive field campaign, Liu et al . report that the magnitude of warming is dependent on particle coatings, which vary due to source and photochemical aging.

Understanding Arctic temperature variability is essential for assessing possible future melting of the Greenland ice sheet, Arctic sea ice and Arctic permafrost. Temperature trend reversals in 1940 and 1970 separate two Arctic warming periods (1910–1940 and 1970–2008) by a significant 1940–1970 cooling period. Analyzing temperature records of the Arctic meteorological stations we find that (a) the Arctic amplification (ratio of the Arctic to global temperature trends) is not a constant but varies in time on a multi‐decadal time scale, (b) the Arctic warming from 1910–1940 proceeded at a significantly faster rate than the current 1970–2008 warming, and (c) the Arctic temperature changes are highly correlated with the Atlantic Multi‐decadal Oscillation (AMO) suggesting the Atlantic Ocean thermohaline circulation is linked to the Arctic temperature variability on a multi‐decadal time scale.

We demonstrate the use of compact solar-tracking Fourier transform spectrometers (Bruker EM27/SUN) for differential measurements of the column-averaged dry-air mole fractions of CH4 and CO2 within urban areas. Using Allan variance analysis, we show that the differential column measurement has a precision of 0.01 % for XCO2 and XCH4 with an optimum integration time of 10 min, corresponding to Allan deviations of 0.04 ppm and 0.2 ppb, respectively. The sensor system is very stable over time and after relocation across the continent. We report tests of the differential column measurement, and its sensitivity to emission sources, by measuring the downwind-minus-upwind column difference ΔXCH4 across dairy farms in the Chino area, California, and using the data to verify emissions reported in the literature. Ratios of spatial column differences ΔXCH4∕ΔXCO2 were observed across Pasadena within the Los Angeles basin, indicating values consistent with regional emission ratios from the literature. Our precise, rapid measurements allow us to determine significant short-term variations (5–10 min) of XCO2 and XCH4 and to show that they represent atmospheric phenomena.Overall, this study helps establish a range of new applications for compact solar-viewing Fourier transform spectrometers. By accurately measuring the small differences in integrated column amounts across local and regional sources, we directly observe the mass loading of the atmosphere due to the influence of emissions in the intervening locale. The inference of the source strength is much more direct than inversion modeling using only surface concentrations and less subject to errors associated with small-scale transport phenomena.

The surface air temperature increase in the southwestern United States was much larger during the last few decades than the increase in the global mean. While the global temperature increased by about 0.5 °C from 1975 to 2000, the southwestern US temperature increased by about 2 °C. If such an enhanced warming persisted for the next few decades, the southwestern US would suffer devastating consequences. To identify major drivers of southwestern climate change we perform a multiple-linear regression of the past 100 years of the southwestern US temperature and precipitation. We find that in the early twentieth century the warming was dominated by a positive phase of the Atlantic multi-decadal oscillation (AMO) with minor contributions from increasing solar irradiance and concentration of greenhouse gases. The late twentieth century warming was about equally influenced by increasing concentration of atmospheric greenhouse gases (GHGs) and a positive phase of the AMO. The current southwestern US drought is associated with a near maximum AMO index occurring nearly simultaneously with a minimum in the Pacific decadal oscillation (PDO) index. A similar situation occurred in mid-1950s when precipitation reached its minimum within the instrumental records. If future atmospheric concentrations of GHGs increase according to the IPCC scenarios (Solomon et al. in Climate change 2007: working group I. The Physical Science Basis, Cambridge, 996 pp, 2007), climate models project a fast rate of southwestern warming accompanied by devastating droughts (Seager et al. in Science 316:1181–1184, 2007; Williams et al. in Nat Clim Chang, 2012). However, the current climate models have not been able to predict the behavior of the AMO and PDO indices. The regression model does support the climate models (CMIP3 and CMIP5 AOGCMs) projections of a much warmer and drier southwestern US only if the AMO changes its 1,000 years cyclic behavior and instead continues to rise close to its 1975–2000 rate. If the AMO continues its quasi-cyclic behavior the US SW temperature should remain stable and the precipitation should significantly increase during the next few decades.

Soot particles form during combustion of carbonaceous materials and impact climate and air quality. When freshly emitted, they are typically fractal-like aggregates. After atmospheric aging, they can act as cloud condensation nuclei, and water condensation or evaporation restructure them to more compact aggregates, affecting their optical, aerodynamic, and surface properties. Here we survey the morphology of ambient soot particles from various locations and different environmental and aging conditions. We used electron microscopy and show extensive soot compaction after cloud processing. We further performed laboratory experiments to simulate atmospheric cloud processing under controlled conditions. We find that soot particles sampled after evaporating the cloud droplets, are significantly more compact than freshly emitted and interstitial soot, confirming that cloud processing, not just exposure to high humidity, compacts soot. Our findings have implications for how the radiative, surface, and aerodynamic properties, and the fate of soot particles are represented in numerical models.

We analyze monthly tropical near surface air temperature and Mauna Loa Observatory carbon dioxide (CO2) data within 1960-2016 to identify different carbon cycle responses for two El Nino types: El Ninos originating in the central tropical Pacific (CP El Nino) and El Ninos originating in the eastern tropical Pacific (EP El Nino). We find significant differences between the two types of El Nino events with respect to time delay of the CO2 rise rate that follows the increase in tropical near surface air temperatures caused by El Nino events. The average time lag of the CP El Nino is 4.0 ± 1.7 months, while the mean time lag of EP El Nino is found to be 8.5 ± 2.3 months. The average lag of all considered 1960-2016 El Ninos is 5.2 ± 2.7 months. In contrast the sensitivity of the CO2 growth rate to tropical near surface air temperature increase is determined to be about the same for both El Nino types equal to 2.8 ± 0.9 ppm yr−1 K−1 (or 5.9 ± 1.9 GtC yr−1 K−1). Our results should be useful for the understanding of the carbon cycle and constraining it in climate models.

Africa is a critical source of biomass burning (BB) aerosols, and its importance is increasing. The African Combustion Aerosol Collaborative Intercomparison Analysis (ACACIA) Pilot Project set to optically characterize BB aerosol generated from sub-Saharan African fuels. We used a photoacoustic spectrometer as a reference instrument to determine the multiple-scattering correction factor Cλ for an AE33 aethalometer at three wavelengths, which produced weighted mean values of C370=3.69, C470=5.65, and C520=6.39. Cλ increased with wavelength and C370 was statistically independent of the others, suggesting a single Cλ is insufficient, especially in BB scenarios. While a dependence of Cλ on burning state was not found, Cλ was shown to strongly relate to particle single scattering albedo (SSA, ω). When Cλ was plotted against SSA, values slowly rose at low SSA values, followed by a sharp rise around an SSA of ∼ 0.9; indicating a larger correction needed for less absorbing aerosol. A number of functions operating on either SSA or Cλ were explored and the best function was -Cλ/(1-Cλ)=Aω+B. This is an important parametrization of Cλ specifically geared towards BB aerosol from African fuels under different aging states, and is of particular importance for future field work in that continent. An Ångström matrix plot shows that African BB aerosol can have values more akin to dust, which demonstrates that these fuels are distinct in their wavelength dependence from more typical BB aerosol. Lastly, we examined the mass extinction and absorbance cross sections for BB aerosol generated for the same fuels with two different tube furnace setups. Not only is this combustion method flexible, it was found to be reproducible between labs.

Optical properties of flame-generated black carbon (BC) containing soot particles were quantified at multiple wavelengths for particles produced using two different flames: a methane diffusion flame and an ethylene premixed flame. Measurements were made for (i) nascent soot particles, (ii) thermally denuded nascent particles, and (iii) particles that were coated and then thermally denuded, leading to the collapse of the initially lacy, fractal-like morphology. The measured mass absorption coefficients (MACs) depended on soot maturity and generation but were similar between flames for similar conditions. For mature soot, here corresponding to particles with volume-equivalent diameters >∼160 nm, the MAC and absorption Ångström exponent (AAE) values were independent of particle collapse while the single-scatter albedo increased. The MAC values for these larger particles were also size-independent. The mean MAC value at 532 nm for larger particles was 9.1±1.1 m2 g−1, about 17 % higher than that recommended by Bond and Bergstrom (2006), and the AAE was close to unity. Effective, theory-specific complex refractive index (RI) values are derived from the observations with two widely used methods: Lorenz–Mie theory and the Rayleigh–Debye–Gans (RDG) approximation. Mie theory systematically underpredicts the observed absorption cross sections at all wavelengths for larger particles (with x>0.9) independent of the complex RI used, while RDG provides good agreement. (The dimensionless size parameter x=πdp/λ, where dp is particle diameter and λ is wavelength.) Importantly, this implies that the use of Mie theory within air quality and climate models, as is common, likely leads to underpredictions in the absorption by BC, with the extent of underprediction depending on the assumed BC size distribution and complex RI used. We suggest that it is more appropriate to assume a constant, size-independent (but wavelength-specific) MAC to represent absorption by uncoated BC particles within models.

An accurate simulation and projection of future warming are needed for a proper policy response to expected climate change. We examine the simulations of the mean global and Arctic surface air temperatures by the CMIP6 (Climate Models Intercomparison Project phase 6) climate models. Most models overestimate the observed mean global warming. Only seven out of 19 models considered simulate global warming that is within ±15% of the observed warming between the average of the 2014–2023 and 1961–1990 reference period. Ten models overestimate global warming by more than 15% and only one of the models underestimates it by more than 15%. Arctic warming is simulated by the CMIP6 climate models much better than the mean global warming. The reason is an equal spread of over and underestimates of Arctic warming by the models, while most of the models overestimate the mean global warming. Eight models are within ±15% of the observed Arctic warming. Only three models are accurate within ±15% for both mean global and Arctic temperature simulations.