We have implemented a module for tropospheric aerosols (GO CART) online in the NASA Goddard Earth Observing System version 4 model and simulated global aerosol distributions for the period 2000-2006. ...The new online system offers several advantages over the previous offline version, providing a platform for aerosol data assimilation, aerosol-chemistry-climate interaction studies, and short-range chemical weather forecasting and climate prediction. We introduce as well a methodology for sampling model output consistently with satellite aerosol optical thickness (AOT) retrievals to facilitate model-satellite comparison. Our results are similar to the offline GOCART model and to the models participating in the AeroCom intercomparison. The simulated AOT has similar seasonal and regional variability and magnitude to Aerosol Robotic Network (AERONET), Moderate Resolution Imaging Spectroradiometer, and Multiangle Imaging Spectroradiometer observations. The model AOT and Angstrom parameter are consistently low relative to AERONET in biomass-burning-dominated regions, where emissions appear to be underestimated, consistent with the results of the offline GOCART model. In contrast, the model AOT is biased high in sulfate-dominated regions of North America and Europe. Our model-satellite comparison methodology shows that diurnal variability in aerosol loading is unimportant compared to sampling the model where the satellite has cloud-free observations, particularly in sulfate-dominated regions. Simulated sea salt burden and optical thickness are high by a factor of 2-3 relative to other models, and agreement between model and satellite over-ocean AOT is improved by reducing the model sea salt burden by a factor of 2. The best agreement in both AOT magnitude and variability occurs immediately downwind of the Saharan dust plume.
Aerosols from biomass burning (BB) emissions are poorly constrained in
global and regional models, resulting in a high level of uncertainty in
understanding their impacts. In this study, we compared ...six BB aerosol
emission datasets for 2008 globally as well as in 14 regions. The six BB
emission datasets are (1) GFED3.1 (Global Fire Emissions Database version 3.1), (2) GFED4s (GFED version 4 with small fires), (3) FINN1.5 (FIre
INventory from NCAR version 1.5), (4) GFAS1.2 (Global Fire Assimilation
System version 1.2), (5) FEER1.0 (Fire Energetics and Emissions Research
version 1.0), and (6) QFED2.4 (Quick Fire Emissions Dataset version 2.4).
The global total emission amounts from these six BB emission datasets
differed by a factor of 3.8, ranging from 13.76 to 51.93 Tg for organic
carbon and from 1.65 to 5.54 Tg for black carbon. In most of the regions,
QFED2.4 and FEER1.0, which are based on satellite observations of fire
radiative power (FRP) and constrained by aerosol optical depth (AOD) data
from the Moderate Resolution Imaging Spectroradiometer (MODIS), yielded
higher BB aerosol emissions than the rest by a factor of 2–4. By comparison, the BB
aerosol emissions estimated from GFED4s and GFED3.1, which are based on satellite
burned-area data, without AOD constraints, were at the low end of the range.
In order to examine the sensitivity of model-simulated AOD to the different
BB emission datasets, we ingested these six BB emission datasets separately
into the same global model, the NASA Goddard Earth Observing System (GEOS)
model, and compared the simulated AOD with observed AOD from the AErosol
RObotic NETwork (AERONET) and the Multiangle Imaging SpectroRadiometer
(MISR) in the 14 regions during 2008. In Southern Hemisphere Africa (SHAF)
and South America (SHSA), where aerosols tend to be clearly dominated by
smoke in September, the simulated AOD values were underestimated in almost all
experiments compared to MISR, except for the QFED2.4 run in SHSA. The
model-simulated AOD values based on FEER1.0 and QFED2.4 were the closest to the
corresponding AERONET data, being, respectively, about 73 % and 100 % of
the AERONET observed AOD at Alta Floresta in SHSA and about 49 % and
46 % at Mongu in SHAF. The simulated AOD based on the other four BB
emission datasets accounted for only ∼50 % of the AERONET
AOD at Alta Floresta and ∼20 % at Mongu. Overall, during
the biomass burning peak seasons, at most of the selected AERONET sites in
each region, the AOD values simulated with QFED2.4 were the highest and closest to
AERONET and MISR observations, followed closely by FEER1.0. However, the
QFED2.4 run tends to overestimate AOD in the region of SHSA, and the QFED2.4
BB emission dataset is tuned with the GEOS model. In contrast, the FEER1.0
BB emission dataset is derived in a more model-independent fashion and is
more physically based since its emission coefficients are independently
derived at each grid box. Therefore, we recommend the FEER1.0 BB emission
dataset for aerosol-focused hindcast experiments in the two biomass-burning-dominated regions in the Southern Hemisphere, SHAF, and SHSA (as well as in
other regions but with lower confidence). The differences between these six
BB emission datasets are attributable to the approaches and input data used
to derive BB emissions, such as whether AOD from satellite observations is
used as a constraint, whether the approaches to parameterize the fire
activities are based on burned area, FRP, or active fire count, and which
set of emission factors is chosen.
The productivity of the Amazon rainforest is constrained by the availability of nutrients, in particular phosphorus (P). Deposition of long‐range transported African dust is recognized as a ...potentially important but poorly quantified source of phosphorus. This study provides a first multiyear satellite‐based estimate of dust deposition into the Amazon Basin using three‐dimensional (3‐D) aerosol measurements over 2007–2013 from the Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP). The 7 year average of dust deposition into the Amazon Basin is estimated to be 28 (8–48) Tg a−1 or 29 (8–50) kg ha−1 a−1. The dust deposition shows significant interannual variation that is negatively correlated with the prior‐year rainfall in the Sahel. The CALIOP‐based multiyear mean estimate of dust deposition matches better with estimates from in situ measurements and model simulations than a previous satellite‐based estimate does. The closer agreement benefits from a more realistic geographic definition of the Amazon Basin and inclusion of meridional dust transport calculation in addition to the 3‐D nature of CALIOP aerosol measurements. The imported dust could provide about 0.022 (0.006–0.037) Tg P of phosphorus per year, equivalent to 23 (7–39) g P ha−1 a−1 to fertilize the Amazon rainforest. This out‐of‐basin phosphorus input is comparable to the hydrological loss of phosphorus from the basin, suggesting an important role of African dust in preventing phosphorus depletion on timescales of decades to centuries.
Key Points
About 28 Tg of Saharan dust is deposited into the Amazon yearly
African dust plays an important role in preventing phosphorus depletion
Ambiguity and inconsistency in model‐observation comparison is clarified
Quantitative estimations of atmospheric aerosol absorption are rather uncertain due to the lack of reliable information about the global distribution. Because the information about aerosol properties ...is commonly provided by single-viewing photometric satellite sensors that are not sensitive to aerosol absorption. Consequently, the uncertainty in aerosol radiative forcing remains one of the largest in the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC AR5 and AR6). Here, we use multi-angular polarimeters (MAP) to provide constraints on emission of absorbing aerosol species and estimate global aerosol absorption optical depth (AAOD) and its climate effect. Our estimate of modern-era mid-visible AAOD is 0.0070 that is higher than IPCC by a factor of 1.3-1.8. The black carbon instantaneous direct radiative forcing (BC DRF) is +0.33 W/m
+0.17, +0.54. The MAP constraint narrows the 95% confidence interval of BC DRF by a factor of 2 and boosts confidence in its spatial distribution.
Many types of aerosols have lifetimes long enough for their transcontinental transport, making them potentially important contributors to air quality and climate change in remote locations. We ...estimate that the mass of aerosols arriving at North American shores from overseas is comparable with the total mass of particulates emitted domestically. Curbing domestic emissions of particulates and precursor gases, therefore, is not sufficient to mitigate aerosol impacts in North America. The imported contribution is dominated by dust leaving Asia, not by combustion-generated particles. Thus, even a reduction of industrial emissions of the emerging economies of Asia could be overwhelmed by an increase of dust emissions due to changes in meteorological conditions and potential desertification.
Cloud drop condensation nuclei (CCN) and ice nuclei (IN) particles determine to a large extent cloud microstructure and, consequently, cloud albedo and the dynamic response of clouds to ...aerosol‐induced changes to precipitation. This can modify the reflected solar radiation and the thermal radiation emitted to space. Measurements of tropospheric CCN and IN over large areas have not been possible and can be only roughly approximated from satellite‐sensor‐based estimates of optical properties of aerosols. Our lack of ability to measure both CCN and cloud updrafts precludes disentangling the effects of meteorology from those of aerosols and represents the largest component in our uncertainty in anthropogenic climate forcing. Ways to improve the retrieval accuracy include multiangle and multipolarimetric passive measurements of the optical signal and multispectral lidar polarimetric measurements. Indirect methods include proxies of trace gases, as retrieved by hyperspectral sensors. Perhaps the most promising emerging direction is retrieving the CCN properties by simultaneously retrieving convective cloud drop number concentrations and updraft speeds, which amounts to using clouds as natural CCN chambers. These satellite observations have to be constrained by in situ observations of aerosol‐cloud‐precipitation‐climate (ACPC) interactions, which in turn constrain a hierarchy of model simulations of ACPC. Since the essence of a general circulation model is an accurate quantification of the energy and mass fluxes in all forms between the surface, atmosphere and outer space, a route to progress is proposed here in the form of a series of box flux closure experiments in the various climate regimes. A roadmap is provided for quantifying the ACPC interactions and thereby reducing the uncertainty in anthropogenic climate forcing.
Key Points
Quantifying aerosol‐cloud‐climate interactions is a major challenge
The science of existing and emerging new observational methods is reviewed
A roadmap for in situ and remote sensing energy closure experiments is provided
Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the state-of-the-art modelling of aerosol optical properties is assessed from 14 global models ...participating in the phase III control experiment (AP3). The models are similar to CMIP6/AerChemMIP Earth System Models (ESMs) and provide a robust multi-model ensemble. Inter-model spread of aerosol species lifetimes and emissions appears to be similar to that of mass extinction coefficients (MECs), suggesting that aerosol optical depth (AOD) uncertainties are associated with a broad spectrum of parameterised aerosol processes.
Total AOD is approximately the same as in AeroCom phase I (AP1) simulations. However, we find a 50 % decrease in the optical depth (OD) of black carbon (BC), attributable to a combination of decreased emissions and lifetimes. Relative contributions from sea salt (SS) and dust (DU) have shifted from being approximately equal in AP1 to SS contributing about 2∕3 of the natural AOD in AP3. This shift is linked with a decrease in DU mass burden, a lower DU MEC, and a slight decrease in DU lifetime, suggesting coarser DU particle sizes in AP3 compared to AP1.
Relative to observations, the AP3 ensemble median and most of the participating models underestimate all aerosol optical properties investigated, that is, total AOD as well as fine and coarse AOD (AODf, AODc), Ångström exponent (AE), dry surface scattering (SCdry), and absorption (ACdry) coefficients. Compared to AERONET, the models underestimate total AOD by ca. 21 % ± 20 % (as inferred from the ensemble median and interquartile range). Against satellite data, the ensemble AOD biases range from −37 % (MODIS-Terra) to −16 % (MERGED-FMI, a multi-satellite AOD product), which we explain by differences between individual satellites and AERONET measurements themselves. Correlation coefficients (R) between model and observation AOD records are generally high (R>0.75), suggesting that the models are capable of capturing spatio-temporal variations in AOD. We find a much larger underestimate in coarse AODc (∼ −45 % ± 25 %) than in fine AODf (∼ −15 % ± 25 %) with slightly increased inter-model spread compared to total AOD. These results indicate problems in the modelling of DU and SS. The AODc bias is likely due to missing DU over continental land masses (particularly over the United States, SE Asia, and S. America), while marine AERONET sites and the AATSR SU satellite data suggest more moderate oceanic biases in AODc.
Column AEs are underestimated by about 10 % ± 16 %. For situations in which measurements show AE > 2, models underestimate AERONET AE by ca. 35 %. In contrast, all models (but one) exhibit large overestimates in AE when coarse aerosol dominates (bias ca. +140 % if observed AE < 0.5). Simulated AE does not span the observed AE variability. These results indicate that models overestimate particle size (or underestimate the fine-mode fraction) for fine-dominated aerosol and underestimate size (or overestimate the fine-mode fraction) for coarse-dominated aerosol. This must have implications for lifetime, water uptake, scattering enhancement, and the aerosol radiative effect, which we can not quantify at this moment.
Comparison against Global Atmosphere Watch (GAW) in situ data results in mean bias and inter-model variations of −35 % ± 25 % and −20 % ± 18 % for SCdry and ACdry, respectively. The larger underestimate of SCdry than ACdry suggests the models will simulate an aerosol single scattering albedo that is too low. The larger underestimate of SCdry than ambient air AOD is consistent with recent findings that models overestimate scattering enhancement due to hygroscopic growth. The broadly consistent negative bias in AOD and surface scattering suggests an underestimate of aerosol radiative effects in current global aerosol models.
Considerable inter-model diversity in the simulated optical properties is often found in regions that are, unfortunately, not or only sparsely covered by ground-based observations. This includes, for instance, the Sahara, Amazonia, central Australia, and the South Pacific. This highlights the need for a better site coverage in the observations, which would enable us to better assess the models, but also the performance of satellite products in these regions.
Using fine-mode AOD as a proxy for present-day aerosol forcing estimates, our results suggest that models underestimate aerosol forcing by ca. −15 %, however, with a considerably large interquartile range, suggesting a spread between −35 % and +10 %.
Atmospheric aerosol distributions from 2000 to 2007 are simulated with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model to attribute light absorption by aerosol to its composition ...and sources from pollution, dust, and biomass burning. The 8-year, global averaged total aerosol optical depth (τ), absorption optical depth (τa), and single scattering albedo (ω) at 550 nm are estimated at 0.14, 0.0086, and 0.95, respectively, with sulfate making the largest fraction of τ (37%), followed by dust (30%), sea salt (16%), organic matter (OM) (13%), and black carbon (BC) (4%). BC and dust account for 43% and 53% of τa, respectively. From a model experiment with "tagged" sources, natural aerosols are estimated to be 58% of τ and 53% of τa, with pollution and biomass burning aerosols to share the rest. Comparing with data from the surface sunphotometer network AERONET, the model tends to reproduce much better the AERONET direct measured data of τ and the Ångström exponent (α) than its retrieved quantities of ω and τa. Relatively small in its systematic bias of τ for pollution and dust regions, the model tends to underestimate τ for biomass burning aerosols by 30–40%. The modeled α is 0.2–0.3 too low (particle too large) for pollution and dust aerosols but 0.2–0.3 too high (particle too small) for the biomass burning aerosols, indicating errors in particle size distributions in the model. Still, the model estimated ω is lower in dust regions and shows a much stronger wavelength dependence for biomass burning aerosols but a weaker one for pollution aerosols than those quantities from AERONET. These comparisons necessitate model improvements on aerosol size distributions, the refractive indices of dust and black carbon aerosols, and biomass burning emissions in order to better quantify the aerosol absorption in the atmosphere.
Integrating liquid metal (LM) particles into compliant polymers presents an innovative approach for developing intelligent and adaptable systems in stretchable electronics, wearable devices, soft ...robotics, and other emerging technologies. However, the inherent electrically insulative nature of these solid‐liquid composites, compounded by the gallium oxide shell surrounding LM droplets, poses a significant challenge in establishing conductive pathways, especially for small droplet sizes and ultrasoft elastomers. Here, an interface modification approach that addresses this bottleneck and enables the synthesis of highly stretchable and printable composites with LM microparticles (<2 µm) is presented. Polyvinylpyrrolidone (PVP) is used to functionalize these small LM inclusions, weakening the particle‐matrix interface, and facilitating the formation of a conductive percolating network under tensile strain. Optimized synthesis parameters result in printed conductive traces with excellent electrical conductivity (0.2 Ω cm−1), ultra‐high elongation at break (>900% strain), and minimal resistance change (≈131%). Furthermore, this comprehensive study of the electromechanical response of these stretchable conductors under various strain rates reveals their exceptional stability under dynamic loading conditions, surpassing the performance of conductive traces composed of sprayed liquid metal. Finally, the potential application of these multifunctional materials in stretchable circuitry, addressing the demand for high stretchability and stability in wearable electronics, is demonstrated.
A particle‐matrix interface modification strategy is introduced to synthesize ultra‐stretchable (900% strain) and highly conductive liquid metal (LM) elastomer composites. PVP‐functionalized LM microparticles form a strain‐insensitive conductive network once stretched to 60% strain. These printed conductors show higher stability across a wide range of strain rates in comparison to pure LM.
The Atlantic Multidecadal Oscillation (AMO) is characterized by a horseshoe pattern of sea surface temperature (SST) anomalies and has a wide range of climatic impacts. While the tropical arm of AMO ...is responsible for many of these impacts, it is either too weak or completely absent in many climate model simulations. Here we show, using both observational and model evidence, that the radiative effect of positive low cloud and dust feedbacks is strong enough to generate the tropical arm of AMO, with the low cloud feedback more dominant. The feedbacks can be understood in a consistent dynamical framework: weakened tropical trade wind speed in response to a warm middle latitude SST anomaly reduces dust loading and low cloud fraction over the tropical Atlantic, which warms the tropical North Atlantic SST. Together they contribute to the appearance of the tropical arm of AMO. Most current climate models miss both the critical wind speed response and two positive feedbacks though realistic simulations of them may be essential for many climatic studies related to the AMO.
Key Points
Low cloud over the tropical North Atlantic is highly sensitive to SST
Trade wind speed response to midlatitude SST anomaly is critical to understand tropical arm of AMO
Models do not simulate the cloud and dust feedback and miss the tropical arm of AMO
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