Ice-nucleating particles (INPs) are known to affect the amount of ice in mixed-phase clouds, thereby influencing many of their properties. The atmospheric INP concentration changes by orders of ...magnitude from terrestrial to marine environments, which typically contain much lower concentrations. Many modelling studies use parameterizations for heterogeneous ice nucleation and cloud ice processes that do not account for this difference because they were developed based on INP measurements made predominantly in terrestrial environments without considering the aerosol composition. Errors in the assumed INP concentration will influence the simulated amount of ice in mixed-phase clouds, leading to errors in top-of-atmosphere radiative flux and ultimately the climate sensitivity of the model. Here we develop a global model of INP concentrations relevant for mixed-phase clouds based on laboratory and field measurements of ice nucleation by K-feldspar (an ice-active component of desert dust) and marine organic aerosols (from sea spray). The simulated global distribution of INP concentrations based on these two species agrees much better with currently available ambient measurements than when INP concentrations are assumed to depend only on temperature or particle size. Underestimation of INP concentrations in some terrestrial locations may be due to the neglect of INPs from other terrestrial sources. Our model indicates that, on a monthly average basis, desert dusts dominate the contribution to the INP population over much of the world, but marine organics become increasingly important over remote oceans and they dominate over the Southern Ocean. However, day-to-day variability is important. Because desert dust aerosol tends to be sporadic, marine organic aerosols dominate the INP population on many days per month over much of the mid- and high-latitude Northern Hemisphere. This study advances our understanding of which aerosol species need to be included in order to adequately describe the global and regional distribution of INPs in models, which will guide ice nucleation researchers on where to focus future laboratory and field work.
Natural aerosols define a preindustrial baseline state from which the magnitude of anthropogenic aerosol effects on climate are calculated and are a major component of the large uncertainty in ...anthropogenic aerosol−cloud radiative forcing. This uncertainty would be reduced if aerosol environments unperturbed by air pollution could be studied in the present-day atmosphere, but the pervasiveness of air pollution makes identification of unperturbed regions difficult. Here, we use global model simulations to define unperturbed aerosol regions in terms of two measures that compare 1750 and 2000 conditions—the number of days with similar aerosol concentrations and the similarity of the aerosol response to perturbations in model processes and emissions. The analysis shows that the aerosol system in many present-day environments looks and behaves like it did in the preindustrial era. On a global annual mean, unperturbed aerosol regions cover 12% of the Earth (16% of the ocean surface and 2% of the land surface). There is a strong seasonal variation in unperturbed regions of between 4% in August and 27% in January, with the most persistent conditions occurring over the equatorial Pacific. About 90% of unperturbed regions occur in the Southern Hemisphere, but in the Northern Hemisphere, unperturbed conditions are transient and spatially patchy. In cloudy regions with a radiative forcing relative to 1750, model results suggest that unperturbed aerosol conditions could still occur on a small number of days per month. However, these environments are mostly in the Southern Hemisphere, potentially limiting the usefulness in reducing Northern Hemisphere forcing uncertainty.
Significance Uncertainty in aerosol forcing of climate since the preindustrial era hampers efforts to quantify the sensitivity of global temperature to radiative perturbations caused by human activity. Because forcings are referenced to preindustrial conditions, a large part of the uncertainty will be reduced only by accurately defining pristine aerosol conditions before air pollution. We show that pristine conditions should still be observable on a few days per month in many regions of the Earth. However, pristine cloudy regions, which are of most importance for forcing uncertainty, occur almost entirely in the Southern Hemisphere. Reduction in uncertainty of predominantly Northern Hemisphere forcing may therefore have to rely on measurements from a different hemisphere, which will limit the extent to which uncertainties can be reduced.
Changes in aerosols cause a change in net top-of-the-atmosphere
(ToA) short-wave and long-wave radiative fluxes; rapid adjustments in clouds,
water vapour and temperature; and an effective radiative ...forcing (ERF)
of the planetary energy budget. The diverse sources of model uncertainty and
the computational cost of running climate models make it difficult to isolate
the main causes of aerosol ERF uncertainty and to understand how observations
can be used to constrain it. We explore the aerosol ERF uncertainty by using
fast model emulators to generate a very large set of aerosol–climate model
variants that span the model uncertainty due to 27 parameters
related to atmospheric and aerosol processes. Sensitivity analyses shows that
the uncertainty in the ToA flux is dominated (around 80 %) by uncertainties
in the physical atmosphere model, particularly parameters that affect cloud
reflectivity. However, uncertainty in the change in ToA flux caused by
aerosol emissions over the industrial period (the aerosol ERF) is controlled
by a combination of uncertainties in aerosol (around 60 %) and physical
atmosphere (around 40 %) parameters. Four atmospheric and aerosol parameters
account for around 80 % of the uncertainty in short-wave ToA flux (mostly
parameters that directly scale cloud reflectivity, cloud water content or
cloud droplet concentrations), and these parameters also account for around
60 % of the aerosol ERF uncertainty. The common causes of uncertainty mean
that constraining the modelled planetary brightness to tightly match
satellite observations changes the lower 95 % credible aerosol ERF value from
−2.65 to −2.37 W m−2. This
suggests the strongest forcings (below around −2.4 W m−2)
are inconsistent with observations. These results show that, regardless of
the fact that the ToA flux is 2 orders of magnitude larger than the aerosol
ERF, the observed flux can constrain the uncertainty in ERF because their
values are connected by constrainable process parameters. The key to reducing
the aerosol ERF uncertainty further will be to identify observations that can
additionally constrain individual parameter ranges and/or combined parameter
effects, which can be achieved through sensitivity analysis of perturbed
parameter ensembles.
The interannual variability of the greenhouse gases methane
(CH4) and tropospheric ozone (O3) is largely driven by natural variations in global emissions and meteorology. The El Niño–Southern
...Oscillation (ENSO) is known to influence fire occurrence, wetland emission
and atmospheric circulation, affecting sources and sinks of CH4 and
tropospheric O3, but there are still important uncertainties associated
with the exact mechanism and magnitude of this effect. Here we use a
modelling approach to investigate how fires and meteorology control the
interannual variability of global carbon monoxide (CO), CH4 and O3
concentrations, particularly during large El Niño events. Using a
three-dimensional chemical transport model (TOMCAT) coupled to a
sophisticated aerosol microphysics scheme (GLOMAP) we simulate changes to
CO, hydroxyl radical (OH) and O3 for the period 1997–2014. We then use
an offline radiative transfer model to quantify the climate impact of
changes to atmospheric composition as a result of specific drivers. During the El Niño event of 1997–1998, there were increased emissions
from biomass burning globally, causing global CO concentrations to increase
by more than 40 %. This resulted in decreased global mass-weighted
tropospheric OH concentrations of up to 9 % and a consequent 4 %
increase in the CH4 atmospheric lifetime. The change in CH4
lifetime led to a 7.5 ppb yr−1 increase in the global mean CH4
growth rate in 1998. Therefore, biomass burning emission of CO could account
for 72 % of the total effect of fire emissions on CH4 growth rate in
1998. Our simulations indicate that variations in fire emissions and meteorology
associated with El Niño have opposing impacts on tropospheric O3
burden. El Niño-related changes in atmospheric transport and humidity
decrease global tropospheric O3 concentrations leading to a −0.03 W m−2 change in the O3 radiative effect (RE). However, enhanced fire emission of precursors such as nitrogen oxides (NOx) and CO
increase O3 and lead to an O3 RE of 0.03 W m−2. While globally
the two mechanisms nearly cancel out, causing only a small change in global
mean O3 RE, the regional changes are large – up to −0.33 W m−2 with potentially important consequences for atmospheric heating and
dynamics.
Observational constraint of simulated aerosol and cloud
properties is an essential part of building trustworthy climate models for
calculating aerosol radiative forcing. Models are usually tuned to ...achieve
good agreement with observations, but tuning produces just one of many
potential variants of a model, so the model uncertainty cannot be determined.
Here we estimate the uncertainty in aerosol effective radiative forcing (ERF)
in a tuned climate model by constraining 4 million variants of the
HadGEM3-UKCA aerosol–climate model to match nine common observations
(top-of-atmosphere shortwave flux, aerosol optical depth, PM2.5, cloud
condensation nuclei at 0.2 % supersaturation (CCN0.2), and
concentrations of sulfate, black carbon and organic carbon, as well as
decadal trends in aerosol optical depth and surface shortwave radiation.) The
model uncertainty is calculated by using a perturbed parameter ensemble that
samples 27 uncertainties in both the aerosol model and the physical climate
model, and we use synthetic observations generated from the model itself to
determine the potential of each observational type to constrain this
uncertainty. Focusing over Europe in July,
we show that the aerosol ERF uncertainty can be reduced by about 30 % by
constraining it to the nine observations, demonstrating that producing
climate models with an observationally plausible “base state” can
contribute to narrowing the uncertainty in aerosol ERF. However, the
uncertainty in the aerosol ERF after observational constraint is large
compared to the typical spread of a multi-model ensemble. Our results
therefore raise questions about whether the underlying multi-model
uncertainty would be larger if similar approaches as adopted here were
applied more widely. The approach presented in this study could be used to
identify the most effective observations for model constraint. It is hoped
that aerosol ERF uncertainty can be further reduced by introducing
process-related constraints; however, any such results will be robust only if
the enormous number of potential model variants is explored.
The vertical profile of aerosol is important for its radiative effects, but weakly constrained by observations on the global scale, and highly variable among different models. To investigate the ...controlling factors in one particular model, we investigate the effects of individual processes in HadGEM3-UKCA and compare the resulting diversity of aerosol vertical profiles with the inter-model diversity from the AeroCom Phase II control experiment. In this way we show that (in this model at least) the vertical profile is controlled by a relatively small number of processes, although these vary among aerosol components and particle sizes. We also show that sufficiently coarse variations in these processes can produce a similar diversity to that among different models in terms of the global-mean profile and, to a lesser extent, the zonal-mean vertical position. However, there are features of certain models' profiles that cannot be reproduced, suggesting the influence of further structural differences between models. In HadGEM3-UKCA, convective transport is found to be very important in controlling the vertical profile of all aerosol components by mass. In-cloud scavenging is very important for all except mineral dust. Growth by condensation is important for sulfate and carbonaceous aerosol (along with aqueous oxidation for the former and ageing by soluble material for the latter). The vertical extent of biomass-burning emissions into the free troposphere is also important for the profile of carbonaceous aerosol. Boundary-layer mixing plays a dominant role for sea salt and mineral dust, which are emitted only from the surface. Dry deposition and below-cloud scavenging are important for the profile of mineral dust only. In this model, the microphysical processes of nucleation, condensation and coagulation dominate the vertical profile of the smallest particles by number (e.g. total CN >3 nm), while the profiles of larger particles (e.g. CN>100 nm) are controlled by the same processes as the component mass profiles, plus the size distribution of primary emissions. We also show that the processes that affect the AOD-normalised radiative forcing in the model are predominantly those that affect the vertical mass distribution, in particular convective transport, in-cloud scavenging, aqueous oxidation, ageing and the vertical extent of biomass-burning emissions.
Despite ongoing efforts, the vertical distribution of aerosols globally is
poorly understood. This in turn leads to large uncertainties in the
contributions of the direct and indirect aerosol forcing ...on climate. Using
the Global Aerosol Synthesis and Science Project (GASSP) database – the
largest synthesised collection of in situ aircraft measurements currently
available, with more than 1000 flights from 37 campaigns from around the
world – we investigate the vertical structure of submicron aerosols across
a wide range of regions and environments. The application of this unique
dataset to assess the vertical distributions of number size distribution and
cloud condensation nuclei (CCN) in the global aerosol–climate model
ECHAM-HAM reveals that the model underestimates accumulation-mode particles
in the upper troposphere, especially in remote regions. The processes
underlying this discrepancy are explored using different aerosol
microphysical schemes and a process sensitivity analysis. These show that
the biases are predominantly related to aerosol ageing and removal rather
than emissions.
Aerosol radiative forcing uncertainty affects estimates of climate sensitivity and limits model skill in terms of making climate projections. Efforts to
improve the representations of physical ...processes in climate models, including extensive comparisons with observations, have not significantly
constrained the range of possible aerosol forcing values. A far stronger constraint, in particular for the lower (most-negative) bound, can be
achieved using global mean energy balance arguments based on observed changes in historical temperature. Here, we show that structural deficiencies in a climate model, revealed as inconsistencies among observationally constrained cloud properties in the model, limit the effectiveness of observational constraint of the uncertain physical processes. We sample the uncertainty in 37 model parameters related to aerosols, clouds, and radiation in a perturbed parameter ensemble of the UK Earth System Model and evaluate 1 million model variants (different parameter settings from Gaussian
process emulators) against satellite-derived observations over several cloudy regions. Our analysis of a very large set of model variants exposes
model internal inconsistencies that would not be apparent in a small set of model simulations, of an order that may be evaluated during model-tuning efforts. Incorporating observations associated with these inconsistencies weakens any forcing constraint because they require a wider range of parameter values to accommodate conflicting information. We show that, by neglecting variables associated with these inconsistencies, it is possible to reduce the parametric uncertainty in global mean aerosol forcing by more than 50 %, constraining it to a range (around −1.3 to −0.1 W m−2) in close agreement with energy balance constraints. Our estimated aerosol forcing range is the maximum feasible constraint using our structurally imperfect model and the chosen observations. Structural model developments targeted at the identified inconsistencies would enable a larger set of observations to be used for constraint, which would then very likely narrow the uncertainty further and possibly alter the central estimate. Such an approach provides a rigorous pathway to improved model realism and reduced uncertainty that has so far not been achieved through the normal model development approach.
The effect of observational constraint on the ranges of
uncertain physical and chemical process parameters was explored in a global
aerosol–climate model. The study uses 1 million variants of the ...Hadley Centre General Environment Model version 3
(HadGEM3) that sample 26 sources of uncertainty, together with over 9000
monthly aggregated grid-box measurements of aerosol optical depth, PM2.5,
particle number concentrations, sulfate and organic mass concentrations.
Despite many compensating effects in the model, the procedure constrains the
probability distributions of parameters related to secondary organic
aerosol, anthropogenic SO2 emissions, residential emissions, sea spray
emissions, dry deposition rates of SO2 and aerosols, new particle
formation, cloud droplet pH and the diameter of primary combustion
particles. Observational constraint rules out nearly 98 % of the model
variants. On constraint, the ±1σ (standard deviation) range
of global annual mean direct radiative forcing (RFari) is reduced by
33 % to −0.14 to −0.26 W m−2, and the 95 % credible interval (CI)
is reduced by 34 % to −0.1 to −0.32 W m−2. For the global annual
mean aerosol–cloud radiative forcing, RFaci, the ±1σ
range is reduced by 7 % to −1.66 to −2.48 W m−2, and the 95 % CI by
6 % to −1.28 to −2.88 W m−2. The tightness of the constraint is
limited by parameter cancellation effects (model equifinality) as well as
the large and poorly defined “representativeness error” associated with
comparing point measurements with a global model. The constraint could also
be narrowed if model structural errors that prevent simultaneous agreement
with different measurement types in multiple locations and seasons could be
improved. For example, constraints using either sulfate or PM2.5
measurements individually result in RFari±1σ ranges
that only just overlap, which shows that emergent constraints based on one
measurement type may be overconfident.
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