Impact of future Arctic shipping on high-latitude black carbon deposition

This is the final version of the article. Available from American Geophysical Union (AGU) via the DOI in this record.The retreat of Arctic sea ice has led to renewed calls to exploit Arctic shipping routes. The diversion of ship traffic through the Arctic will shorten shipping routes and possibly reduce global shipping emissions. However, deposition of black carbon (BC) aerosol emitted by additional Arctic ships could cause a reduction in the albedo of snow and ice, accelerating snowmelt and sea ice loss. Here we use recently compiled Arctic shipping emission inventories for 2004 and 2050 together with a global aerosol model to quantify the contribution of future Arctic shipping to high-latitude BC deposition. Our results show that Arctic shipping in 2050 will contribute less than 1% to the total BC deposition north of 60°N due to the much greater relative contribution of BC transported from non-shipping sources at lower latitudes. We suggest that regulation of the Arctic shipping industry will be an insufficient control on high-latitude BC deposition. Key Points Contribution of Arctic shipping to high-latitude BC deposition less than 1% Extra-Arctic sources contribute much greater Arctic BC mass than local shipping Regulation of Arctic shipping unlikely to control high-latitude BC deposition.J.B. was funded by a studentship from the Natural Environment Research Council (NERC) and by the Met Office through a CASE partnership and is now funded by a NERC grant [NE/I028858/1]. K.C. is a Royal Society Wolfson Merit Award holder. A.S.is funded by a NERC grant [NE/I015612/1] and a fellowship from the School of Earth and Environment, University of Leeds. The Editor thanks three anonymous reviewers for their assistance in evaluating this paper

Importance of tropospheric volcanic aerosol for indirect radiative forcing of climate

Observations and models have shown that continuously degassing volcanoes have a potentially large effect on the natural background aerosol loading and the radiative state of the atmosphere. We use a global aerosol microphysics model to quantify the impact of these volcanic emissions on the cloud albedo radiative forcing under pre-industrial (PI) and present-day (PD) conditions. We find that volcanic degassing increases global annual mean cloud droplet number concentrations by 40% under PI conditions, but by only 10% under PD conditions. Consequently, volcanic degassing causes a global annual mean cloud albedo effect of −1.06 W m−2 in the PI era but only −0.56 W m−2 in the PD era. This non-equal effect is explained partly by the lower background aerosol concentrations in the PI era, but also because more aerosol particles are produced per unit of volcanic sulphur emission in the PI atmosphere. The higher sensitivity of the PI atmosphere to volcanic emissions has an important consequence for the anthropogenic cloud radiative forcing because the large uncertainty in volcanic emissions translates into an uncertainty in the PI baseline cloud radiative state. Assuming a −50/+100% uncertainty range in the volcanic sulphur flux, we estimate the annual mean anthropogenic cloud albedo forcing to lie between −1.16 W m−2 and −0.86 W m−2. Therefore, the volcanically induced uncertainty in the PI baseline cloud radiative state substantially adds to the already large uncertainty in the magnitude of the indirect radiative forcing of climate

Change from aerosol-driven to cloud-feedback-driven trend in short-wave radiative flux over the North Atlantic

Aerosol radiative forcing and cloud–climate feedbacks each have a large effect on climate, mainly through modification of solar short-wave radiative fluxes. Here we determine what causes the long-term trends in the upwelling short-wave (SW) top-of-the-atmosphere (TOA) fluxes (FSW↑) over the North Atlantic region. Coupled atmosphere–ocean simulations from the UK Earth System Model (UKESM1) and the Hadley Centre General Environment Model (HadGEM3-GC3.1) show a positive FSW↑ trend between 1850 and 1970 (increasing SW reflection) and a negative trend between 1970 and 2014. We find that the 1850–1970 positive FSW↑ trend is mainly driven by an increase in cloud droplet number concentration due to increases in aerosol, while the 1970–2014 trend is mainly driven by a decrease in cloud fraction, which we attribute mainly to cloud feedbacks caused by greenhouse gas-induced warming. In the 1850–1970 period, aerosol-induced cooling and greenhouse gas warming roughly counteract each other, so the temperature-driven cloud feedback effect on the FSW↑ trend is weak (contributing to only 23 % of the ΔFSW↑), and aerosol forcing is the dominant effect (77 % of ΔFSW↑). However, in the 1970–2014 period the warming from greenhouse gases intensifies, and the cooling from aerosol radiative forcing reduces, resulting in a large overall warming and a reduction in FSW↑ that is mainly driven by cloud feedbacks (87 % of ΔFSW↑). The results suggest that it is difficult to use satellite observations in the post-1970 period to evaluate and constrain the magnitude of the aerosol–cloud interaction forcing but that cloud feedbacks might be evaluated. Comparisons with observations between 1985 and 2014 show that the simulated reduction in FSW↑ and the increase in temperature are too strong. However, the temperature discrepancy can account for only part of the FSW↑ discrepancy given the estimated model feedback strength (λ=∂FSW∂T). The remaining discrepancy suggests a model bias in either λ or in the strength of the aerosol forcing (aerosols are reducing during this time period) to explain the too-strong decrease in FSW↑, with a λ bias being the most likely. Both of these biases would also tend to cause too-large an increase in temperature over the 1985–2014 period, which would be consistent with the sign of the model temperature bias reported here. Either of these model biases would have important implications for future climate projections using these models

The decomposition of cloud–aerosol forcing in the UK Earth System Model (UKESM1)

Climate variability in the North Atlantic influences processes such as hurricane activity and droughts. Global model simulations have identified aerosol–cloud interactions (ACIs) as an important driver of sea surface temperature variability via surface aerosol forcing. However, ACIs are a major cause of uncertainty in climate forcing; therefore, caution is needed in interpreting the results from coarse-resolution, highly parameterized global models. Here, we separate and quantify the components of the surface shortwave effective radiative forcing (ERF) due to aerosol in the atmosphere-only version of the UK Earth System Model (UKESM1) and evaluate the cloud properties and their radiative effects against observations. We focus on a northern region of the North Atlantic (NA) where stratocumulus clouds dominate (denoted the northern NA region) and a southern region where trade cumulus and broken stratocumulus dominate (southern NA region). Aerosol forcing was diagnosed using a pair of simulations in which the meteorology is approximately fixed via nudging to analysis; one simulation has pre-industrial (PI) and one has present-day (PD) aerosol emissions. This model does not include aerosol effects within the convective parameterization (but aerosol does affect the clouds associated with detrainment) and so it should be noted that the representation of aerosol forcing for convection is incomplete. Contributions to the surface ERF from changes in cloud fraction (fc), in-cloud liquid water path (LWPic) and droplet number concentration (Nd) were quantified. Over the northern NA region, increases in Nd and LWPic dominate the forcing. This is likely because the already-high fc there reduces the chances of further large increases in fc and allows cloud brightening to act over a larger region. Over the southern NA region, increases in fc dominate due to the suppression of rain by the additional aerosols. Aerosol-driven increases in macrophysical cloud properties (LWPic and fc) will rely on the response of the boundary layer parameterization, along with input from the cloud microphysics scheme, which are highly uncertain processes. Model grid boxes with low-altitude clouds present in both the PI and PD dominate the forcing in both regions. In the northern NA, the brightening of completely overcast low cloud scenes (100 % cloud cover, likely stratocumulus) contributes the most, whereas in the southern NA the creation of clouds with fc of around 20 % from clear skies in the PI was the largest single contributor, suggesting that trade cumulus clouds are created in response to increases in aerosol. The creation of near-overcast clouds was also important there. The correct spatial pattern, coverage and properties of clouds are important for determining the magnitude of aerosol forcing, so we also assess the realism of the modelled PD clouds against satellite observations. We find that the model reproduces the spatial pattern of all the observed cloud variables well but that there are biases. The shortwave top-of-the-atmosphere (SWTOA) flux is overestimated by 5.8 % in the northern NA region and 1.7 % in the southern NA, which we attribute mainly to positive biases in low-altitude fc. Nd is too low by −20.6 % in the northern NA and too high by 21.5 % in the southern NA but does not contribute greatly to the main SWTOA biases. Cloudy-sky liquid water path mainly shows biases north of Scandinavia that reach between 50 % and 100 % and dominate the SWTOA bias in that region. The large contribution to aerosol forcing in the UKESM1 model from highly uncertain macrophysical adjustments suggests that further targeted observations are needed to assess rain formation processes, how they depend on aerosols and the model response to precipitation in order to reduce uncertainty in climate projections

The scavenging processes controlling the seasonal cycle in Arctic sulphate and black carbon aerosol

This is the final version of the article. Available from European Geosciences Union via the DOI in this record.The seasonal cycle in Arctic aerosol is typified by high concentrations of large aged anthropogenic particles transported from lower latitudes in the late Arctic winter and early spring followed by a sharp transition to low concentrations of locally sourced smaller particles in the summer. However, multi-model assessments show that many models fail to simulate a realistic cycle. Here, we use a global aerosol microphysics model (GLOMAP) and surface-level aerosol observations to understand how wet scavenging processes control the seasonal variation in Arctic black carbon (BC) and sulphate aerosol. We show that the transition from high wintertime concentrations to low concentrations in the summer is controlled by the transition from ice-phase cloud scavenging to the much more efficient warm cloud scavenging in the late spring troposphere. This seasonal cycle is amplified further by the appearance of warm drizzling cloud in the late spring and summer boundary layer. Implementing these processes in GLOMAP greatly improves the agreement between the model and observations at the three Arctic ground-stations Alert, Barrow and Zeppelin Mountain on Svalbard. The SO4 model-observation correlation coefficient (R) increases from:-0.33 to 0.71 at Alert (82.5 N), from-0.16 to 0.70 at Point Barrow (71.0 N) and from-0.42 to 0.40 at Zeppelin Mountain (78 N). The BC model-observation correlation coefficient increases from-0.68 to 0.72 at Alert and from-0.42 to 0.44 at Barrow. Observations at three marginal Arctic sites (Janiskoski, Oulanka and Karasjok) indicate a far weaker aerosol seasonal cycle, which we show is consistent with the much smaller seasonal change in the frequency of ice clouds compared to higher latitude sites. Our results suggest that the seasonal cycle in Arctic aerosol is driven by temperature-dependent scavenging processes that may be susceptible to modification in a future climate. © 2012 Author(s).JB was funded by a studentship from the Natural Environment Research Council and by the Met Office through a CASE partnership. KC is a Royal Society Wolfson Merit Award holder. We would like to thank Neil Gordon for providing low cloud satellite climatologies from the MODIS satellite and Dr Graham Mann for his comments and assistance. The authors acknowledge the Canadian National Atmospheric Chemistry (NAtChem) Database and its data contributing agencies/ organizations for the provision of the Sulphate mass data for the years 2000–2002, used in this publication. The agency responsible for all data contributions from the the NAtChem Database is the Canadian Arctic aerosol programme. The authors acknowledge and thank the scientists and data-providers of the Norwegian institute of air research (NILU), the National ocean and atmospheric administration (NOAA) and the EMEP observation network for the provision of BC and sulphate mass data used in this publication

Opinion: Cloud-phase climate feedback and the importance of ice-nucleating particles

Shallow clouds covering vast areas of the world's middle- and high-latitude oceans play a key role in dampening the global temperature rise associated with CO2. These clouds, which contain both ice and supercooled water, respond to a warming world by transitioning to a state with more liquid water and a greater albedo, resulting in a negative “cloud-phase” climate feedback component. Here we argue that the magnitude of the negative cloud-phase feedback component depends on the amount and nature of the small fraction of aerosol particles that can nucleate ice crystals. We propose that a concerted research effort is required to reduce substantial uncertainties related to the poorly understood sources, concentration, seasonal cycles and nature of these ice-nucleating particles (INPs) and their rudimentary treatment in climate models. The topic is important because many climate models may have overestimated the magnitude of the cloud-phase feedback, and those with better representation of shallow oceanic clouds predict a substantially larger climate warming. We make the case that understanding the present-day INP population in shallow clouds in the cold sector of cyclone systems is particularly critical for defining present-day cloud phase and therefore how the clouds respond to warming. We also need to develop a predictive capability for future INP emissions and sinks in a warmer world with less ice and snow and potentially stronger INP sources

Comparing the impact of environmental conditions and microphysics on the forecast uncertainty of deep convective clouds and hail

Severe hailstorms have the potential to damage buildings and crops. However, important processes for the prediction of hailstorms are insufficiently represented in operational weather forecast models. Therefore, our goal is to identify model input parameters describing environmental conditions and cloud microphysics, such as the vertical wind shear and strength of ice multiplication, which lead to large uncertainties in the prediction of deep convective clouds and precipitation. We conduct a comprehensive sensitivity analysis simulating deep convective clouds in an idealized setup of a cloud-resolving model. We use statistical emulation and variance-based sensitivity analysis to enable a Monte Carlo sampling of the model outputs across the multi-dimensional parameter space. The results show that the model dynamical and microphysical properties are sensitive to both the environmental and microphysical uncertainties in the model. The microphysical parameters lead to larger uncertainties in the output of integrated hydrometeor mass contents and precipitation variables. In particular, the uncertainty in the fall velocities of graupel and hail account for more than 65 % of the variance of all considered precipitation variables and for 30 %–90 % of the variance of the integrated hydrometeor mass contents. In contrast, variations in the environmental parameters – the range of which is limited to represent model uncertainty – mainly affect the vertical profiles of the diabatic heating rates

Emulation of a complex global aerosol model to quantify sensitivity to uncertain parameters

Sensitivity analysis of atmospheric models is necessary to identify the processes that lead to uncertainty in model predictions, to help understand model diversity through comparison of driving processes, and to prioritise research. Assessing the effect of parameter uncertainty in complex models is challenging and often limited by CPU constraints. Here we present a cost-effective application of variance-based sensitivity analysis to quantify the sensitivity of a 3-D global aerosol model to uncertain parameters. A Gaussian process emulator is used to estimate the model output across multi-dimensional parameter space, using information from a small number of model runs at points chosen using a Latin hypercube space-filling design. Gaussian process emulation is a Bayesian approach that uses information from the model runs along with some prior assumptions about the model behaviour to predict model output everywhere in the uncertainty space. We use the Gaussian process emulator to calculate the percentage of expected output variance explained by uncertainty in global aerosol model parameters and their interactions. To demonstrate the technique, we show examples of cloud condensation nuclei (CCN) sensitivity to 8 model parameters in polluted and remote marine environments as a function of altitude. In the polluted environment 95 % of the variance of CCN concentration is described by uncertainty in the 8 parameters (excluding their interaction effects) and is dominated by the uncertainty in the sulphur emissions, which explains 80 % of the variance. However, in the remote region parameter interaction effects become important, accounting for up to 40 % of the total variance. Some parameters are shown to have a negligible individual effect but a substantial interaction effect. Such sensitivities would not be detected in the commonly used single parameter perturbation experiments, which would therefore underpredict total uncertainty. Gaussian process emulation is shown to be an efficient and useful technique for quantifying parameter sensitivity in complex global atmospheric models

Contribution of regional aerosol nucleation to low-level CCN in an Amazonian deep convective environment: results from a regionally nested global model

Global model studies and observations have shown that downward transport of aerosol nucleated in the free troposphere is a major source of cloud condensation nuclei (CCN) to the global boundary layer. In Amazonia, observations show that this downward transport can occur during strong convective activity. However, it is not clear from these studies over what spatial scale this cycle of aerosol formation and downward supply of CCN is occurring. Here, we aim to quantify the extent to which the supply of aerosol to the Amazonian boundary layer is generated from nucleation within a 1000 km regional domain or from aerosol produced further afield and the effectiveness of the transport by deep convection. We run the atmosphere-only configuration of the HadGEM3 climate model incorporating a 440 km × 1080 km regional domain over Amazonia with 4 km resolution. Simulations were performed over several diurnal cycles of convection. Below 2 km altitude in the regional domain, our results show that new particle formation within the regional domain accounts for only between 0.2 % and 3.4 % of all Aitken and accumulation mode aerosol particles, whereas nucleation that occurred outside the domain (in the global model) accounts for between 58 % and 81 %. The remaining aerosol is primary in origin. Above 10 km, the regional-domain nucleation accounts for up to 66 % of Aitken and accumulation mode aerosol, but over several days very few of these particles nucleated above 10 km in the regional domain are transported into the boundary layer within the 1000 km region, and in fact very little air is mixed that far down. Rather, particles transported downwards into the boundary layer originated from outside the regional domain and entered the domain at lower altitudes. Our model results show that CCN entering the Amazonian boundary layer are transported downwards gradually over multiple convective cycles on scales much larger than 1000 km. Therefore, on a 1000 km scale in the model (approximately one-third the size of Amazonia), trace gas emission, new particle formation, transport and CCN production do not form a “closed loop” regulated by the biosphere. Rather, on this scale, long-range transport of aerosol is a much more important factor controlling CCN in the boundary layer

Exploring How Eruption Source Parameters Affect Volcanic Radiative Forcing Using Statistical Emulation

The radiative forcing caused by a volcanic eruption is dependent on several eruption source parameters such as the mass of sulfur dioxide (SO2) emitted, the eruption column height, and the eruption latitude. General circulation models with prognostic aerosol and chemistry schemes can be used to investigate how each parameter influences the volcanic forcing. However, the range of multidimensional parameter space that can be explored is restricted because such simulations are computationally expensive. Here we use statistical emulation to explore the radiative impact of eruptions over a wide covarying range of SO2 emission magnitudes, injection heights, and eruption latitudes based on only 30 simulations. We use the emulators to build response surfaces to visualize and predict the sulfate aerosol e-folding decay time, the stratospheric aerosol optical depth, and net radiative forcing of thousands of different eruptions. We find that the volcanic stratospheric aerosol optical depth and net radiative forcing are primarily determined by the mass of SO2 emitted, but eruption latitude is the most important parameter in determining the sulfate aerosol e-folding decay time. The response surfaces reveal joint effects of the eruption source parameters in influencing the net radiative forcing, such as a stronger influence of injection height for tropical eruptions than high-latitude eruptions. We also demonstrate how the emulated response surfaces can be used to find all combinations of eruption source parameters that produce a particular volcanic response, often revealing multiple solutions