The North Atlantic warming hole (NAWH) is referred to as a reduced warming, or even cooling, of the North Atlantic during an anthropogenic‐driven global warming. A NAWH is predicted by climate models ...during the 21st century, and its pattern is already emerging in observations. Despite the known key role of the North Atlantic surface temperatures in setting the Northern Hemisphere climate, the mechanisms behind the NAWH are still not fully understood. Using state‐of‐the‐art climate models, we show that anthropogenic aerosol forcing opposes the formation of the NAWH (by leading to a local warming) and delays its emergence by about 30 years. In agreement with previous studies, we also demonstrate that the relative warming of the North Atlantic under aerosol forcing is due to changes in ocean heat fluxes, rather than air‐sea fluxes. These results suggest that the predicted reduction in aerosol forcing during the 21st century may accelerate the formation of the NAWH.
Plain Language Summary
Anthropogenic aerosols are particles suspended in the atmosphere, which were released due to anthropogenic activity. These particles have a general cooling effect on the Earth due to their interactions with radiation and with clouds. Here we show that the surface temperature in the North Atlantic Ocean is predicted to increase due to aerosol forcing (despite the global cooling). This trend is the opposite of the surface temperature trend predicted due to increase in greenhouse gases (global warming with a warming “hole” in the North Atlantic, trend known as the North Atlantic warming hole—NAWH). Using state‐of‐the‐art climate models, we show that aerosol forcing delays the formation of the NAWH by about 30 years. This trend could have important climatic impacts due to the key role of the North Atlantic surface temperatures in setting the Northern Hemisphere's climate and due to the predicted reduction in aerosol forcing in the next few decades.
Key Points
Using CMIP6 and CESM‐LE simulations, we show that aerosol forcing generates a global cooling trend with a warming in the North Atlantic
This trend opposes the North Atlantic warming hole trend due to greenhouse gases
Aerosol forcing delays the formation of the North Atlantic warming hole by about 30 years
Global mean precipitation changes due to climate change were previously shown to be relatively small and well constrained by the energy budget. However, local precipitation changes can be much more ...significant. In this paper we propose that for large enough scales, for which the water budget is closed (precipitation P roughly equals evaporation E), changes in P approach the small global mean value. However, for smaller scales, for which P and E are not necessarily equal and convergence of water vapor still plays a role, changes in P could be much larger due to dynamical contributions. Using 40 years of two reanalysis data sets, 39 Coupled Model Intercomparison Project Phase 5 (CMIP5) models and additional numerical simulations, we identify the scale of transition in the importance of the different terms in the water budget to precipitation to be ~3,500–4,000 km and demonstrate its relation to the spatial scale of precipitation changes under climate change.
Plain Language Summary
Predicting precipitation changes due to climate change is of great importance for society. We propose that the present‐day characteristic scale of the hydrological cycle (for which precipitation roughly equals evaporation) predicts the spatial scale of future precipitation changes under global warming. For smaller scales than the characteristic scale of the hydrological cycle, changes in precipitation could be much larger than the global mean change due to water vapor convergence contributions. However, above this scale the precipitation changes approach the relatively small global mean change. Using reanalysis data sets, Coupled Model Intercomparison Project Phase 5 (CMIP5) models, and additional numerical simulations, we identify the characteristic scale of the hydrological cycle to be ~3,500–4,000 km and demonstrate its relation to the spatial scale of precipitation changes under climate change. These results suggest that changes in precipitation on the regional‐continental scale could be much larger than the global mean change.
Key Points
The present‐day characteristic scale of the hydrological cycle predicts the spatial scale of precipitation changes under climate change
Using reanalysis data sets and CMIP5 models, we identify the characteristic scale of the hydrological cycle to be ~3,500–4,000 km
These results suggest that changes in precipitation on the continental scale could be much larger than the global mean change
Precipitation plays a crucial role in the Earth's energy balance, the water cycle, and the global atmospheric circulation. Aerosols, by direct interaction with radiation and by serving as cloud ...condensation nuclei, may affect clouds and rain formation. This effect can be examined in terms of energetic constraints, that is, any aerosol‐driven diabatic heating/cooling of the atmosphere will have to be balanced by changes in precipitation, radiative fluxes, or divergence of dry static energy. Using an aqua‐planet general circulation model (GCM), we show that tropical and extratropical precipitation have contrasting responses to aerosol perturbations. This behavior can be explained by contrasting ability of the atmosphere to diverge excess dry static energy in the two different regions. It is shown that atmospheric heating in the tropics leads to large‐scale thermally driven circulation and a large increase in precipitation, while the excess energy from heating in the extratropics is constrained due to the effect of the Coriolis force, causing the precipitation to decrease.
Plain Language Summary
Precipitation, as the Earth's only natural source of fresh water, is of great importance for society. Climate change, besides changing the mean surface temperature and its distribution, is expected to change the precipitation's temporal and spatial distribution and, to a lesser extent, the global mean precipitation. One important agent in precipitation changes is anthropogenic aerosols. In this paper we study the response of precipitation to aerosol perturbations at different latitudes. Previously, it was proposed that aerosols drive a slowdown of the hydrological cycle. In addition, it was shown that, due to energy budget conservation, absorbing aerosols leads to a reduction in the global mean precipitation. Here we show that the response in the tropics is the opposite of the global mean response and of the extratropical response. Specifically, we show that the same aerosol perturbation generally increases precipitation in the tropics and decreases precipitation in the extratropics. This behavior can be explained by the contrasting ability of the atmosphere to diverge excess dry static energy in the tropics and extratropics. We also show that local aerosol perturbations could affect precipitation in remote regions due to a formation of large‐scale circulation.
Key Points
Aerosol effect on precipitation is examined in terms of energetic constraints
Aerosol perturbation generally increases precipitation in the tropics and decreases precipitation in the extratropics
This behavior can be explained by contrasting ability of the atmosphere to diverge excess dry static energy in the two different regions
Quantifying effective radiative forcing due to aerosol‐cloud interactions (EERFACI) remains a largely uncertain process, and the magnitude remains unconstrained in general circulation models. ...Previous studies focus on the magnitude of ERFACI arising from all cloud types, or examine it in the framework of dynamical regimes. Aerosol forcing due to aerosol‐cloud interactions in the HadGEM3‐GA7.1 global climate model is decomposed into several global observational cloud regimes. Regimes are assigned to model gridboxes and forcing due to aerosol‐cloud interactions is calculated on a regime‐by‐regime basis with a 20‐year averaging period. Patterns of regime occurrence are in good agreement with satellite observations. ERFACI is then further decomposed into three terms, representing radiative changes within a given regime, transitions between different cloud regimes, and nonlinear effects. The total global mean ERFACI is −1.03 Wm−2. When decomposed, simulated ERFACI is greatest in the thick stratocumulus regime (−0.51 Wm−2).
Plain Language Summary
The effect of anthropogenic aerosol emissions on clouds is highly uncertain in climate models. Many previous attempts to reduce this uncertainty have focused on examining all cloud types as a whole. This work sets out a framework to examine one measure of aerosol‐cloud interactions when the effect is split by different cloud types. This framework is applied to the HadGEM3‐GA7.1 climate model. It is found that thick stratocumulus clouds exhibit the strongest aerosol‐cloud interactions, especially those found off the west coast of both North and South America, and West Africa. It is hoped that this will lead to a greater understanding of how these interactions manifest themselves in different cloud types, and that this methodology will promote the use of constraints on specific cloud types, to provide potentially greater reductions in the aforementioned uncertainty.
Key Points
The majority of effective radiative forcing in HadGEM3‐GA7.1 comes from stratocumulus clouds
Forcing from marine stratocumulus clouds is highly sensitive to aerosol perturbations
Decomposing radiative forcing by cloud regimes can be a useful technique to gain insights into climate model predictions
Emulators, or reduced complexity climate models, are surrogate Earth system models (ESMs) that produce projections of key climate quantities with minimal computational resources. Using time‐series ...modeling or more advanced machine learning techniques, data‐driven emulators have emerged as a promising avenue of research, producing spatially resolved climate responses that are visually indistinguishable from state‐of‐the‐art ESMs. Yet, their lack of physical interpretability limits their wider adoption. In this work, we introduce FaIRGP, a data‐driven emulator that satisfies the physical temperature response equations of an energy balance model. The result is an emulator that (a) enjoys the flexibility of statistical machine learning models and can learn from data, and (b) has a robust physical grounding with interpretable parameters that can be used to make inference about the climate system. Further, our Bayesian approach allows a principled and mathematically tractable uncertainty quantification. Our model demonstrates skillful emulation of global mean surface temperature and spatial surface temperatures across realistic future scenarios. Its ability to learn from data allows it to outperform EBMs, while its robust physical foundation safeguards against the pitfalls of purely data‐driven models. We also illustrate how FaIRGP can be used to obtain estimates of top‐of‐atmosphere radiative forcing and discuss the benefits of its mathematical tractability for applications such as detection and attribution or precipitation emulation. We hope that this work will contribute to widening the adoption of data‐driven methods in climate emulation.
Plain Language Summary
Emulators are simplified climate models that can be used to rapidly explore climate scenarios—they can run in less than a minute on an average computer. They are key tools used by the Intergovernmental Panel on Climate Change to explore the diversity of possible future climates. Data‐driven emulators use advanced machine learning techniques to produce climate predictions that look very similar to the predictions of complex climate models. However, they are not easy to interpret, and therefore to trust in practice. In this work, we introduce FaIRGP, a data‐driven emulator based on physics. The emulator is flexible and can learn from data to improve its predictions, but is also grounded on physical energy balance relationships, which makes it robust and interpretable. The model performs well in predicting future global and local temperatures under realistic future scenarios, outperforming purely physics‐driven or purely data‐driven models. Further, the probabilistic nature of our model allows for mathematically tractable uncertainty quantification. By gaining trust in such a data‐driven yet physically grounded model, we hope the climate science community can benefit more widely from their potential.
Key Points
We introduce FaIRGP, a Bayesian machine learning emulator for global and local mean surface temperatures that builds upon a physically based simple climate model
The model improves upon both purely physically‐driven and purely data‐driven baseline emulators on several metrics across realistic future scenarios
The model is fully mathematically tractable, which makes it a convenient and easy‐to‐use probabilistic tool for the emulation of surface temperatures, but also for downstream applications such as detection and attribution or precipitation emulation
Aerosol‐cloud interactions (ACI) in warm clouds are the primary source of uncertainty in effective radiative forcing (ERF) during the historical period and, by extension, inferred climate ...sensitivity. The ERF due to ACI (ERFaci) is composed of the radiative forcing due to changes in cloud microphysics and cloud adjustments to microphysics. Here, we examine the processes that drive ERFaci using a perturbed parameter ensemble (PPE) hosted in CAM6. Observational constraints on the PPE result in substantial constraints in the response of cloud microphysics and macrophysics to anthropogenic aerosol, but only minimal constraint on ERFaci. Examination of cloud and radiation processes in the PPE reveal buffering of ERFaci by the interaction of precipitation efficiency and radiative susceptibility.
Plain Language Summary
Uncertainty in predicting future global temperature inferred from the historical record of warming is dominated by how much the warming due to greenhouse gases has been offset by the cooling due to aerosols. Aerosols are small liquid and solid particles that play an important role in cloud formation. The majority of cooling from aerosols is through reflecting incoming solar radiation back to space by cloud. In this study, we constrain an ensemble of possible global model configurations with observations of cloud properties and radiation to reduce uncertainty in the response of clouds and ultimately radiation to anthropogenic aerosol. While observations substantially reduce the uncertainty in both changes in the number of droplets and amount of liquid cloud, the constraint on aerosol cooling is minimal. We argue that the relatively weak constraint is because large changes in cloudiness are accompanied by small change in reflected sunlight due to increased cloudiness.
Key Points
Models with lower precipitation efficiency result in larger mean‐state liquid water path (LWP) and larger adjustments in LWP to aerosol
Larger mean‐state LWP coincides with lower albedo susceptibility to LWP
The combination of these processes results in buffering of the radiative effect of LWP adjustments
The spaceborne Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument provides valuable information on the vertical distribution of global aerosol and is often used to evaluate vertical ...aerosol distributions in general circulation models (GCMs). Here we show, however, that the detection limit of the CALIOP retrievals mean background aerosol is not detected, leading to substantially skewed statistics that moreover differ significantly by product. In the CALIOP Level 2 product this missing low‐backscatter aerosol results in the retrieved aerosol distribution significantly overrepresenting aerosol backscatter and extinction in the middle and upper troposphere if taken to be representative of the undetected aerosol. The CALIOP Level 3 product assumes no aerosol where none is detected, which then leads to an underestimation in the aerosol extinction profile in the upper troposphere. Using the ECHAM‐HAM GCM, we estimate that the mean fraction of aerosol undetected by CALIOP daytime (nighttime) retrievals is 41% (44%) globally.
Plain Language Summary
The spaceborne Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument provides valuable information on the vertical distribution of global aerosol and is often used to evaluate vertical aerosol distributions in general circulation models (GCMs). Here we show, however, that the detection limit of the CALIOP retrievals mean background aerosol is not detected, leading to substantially skewed statistics that depend on assumptions about the missing aerosol. Using the ECHAM‐HAM GCM, we estimate that the mean fraction of aerosol undetected by CALIOP daytime (nighttime) retrievals is 41% (44%) globally.
Key Points
Current CALIOP data products are shown to provide only an upper bound on modeled aerosol concentrations in the free troposphere
The practice of filling in missing retrievals has a disproportionate effect in the free troposphere where most aerosol is undetected
By interacting with radiation, aerosols perturb the Earth’s energy budget and thus the global precipitation amount. It was previously shown that aerosol‐radiation interactions lead to a reduction in ...the global‐mean precipitation amount. We have further demonstrated in aqua‐planet simulations that the local response to absorbing aerosols differs between the tropics and the extra‐tropics. In this study we incorporate an energy budget perspective to further examine the latitudinal‐dependence of the effect of aerosol‐radiation interaction on precipitation in idealized global simulations. We demonstrate that the transition between a positive local precipitation response in the tropics and a negative local precipitation response in the extra‐tropics occurs at relatively low latitudes (∼10°), indicating a transition between the deep‐tropics (in which the Coriolis force is low, hence direct thermally driven circulation, and associated divergence/convergence of energy/moisture, can form as a result of the diabatic‐heating) and their surroundings. In addition, we gradually increase the level of complexity of the simulations and demonstrate that, in the case of absorbing aerosols, the effect of land is to counteract some of the response both inside and outside the deep‐tropics due to the reduction in surface latent‐heat flux that opposes the diabatic‐heating. The effect of scattering aerosols is also examined and demonstrates a decrease in precipitation over land in both the tropics and extra‐tropics and no effect over the ocean. Finally, we examine these results in a more realistic set‐up and demonstrate that, although the physical mechanisms still operate, they are not significant enough to be discerned from the model’s natural‐variability.
Key Points
Energy budget perspective is used to examine the latitudinal dependence of the effect of aerosol‐radiation interaction on precipitation
A transition between a positive response in the tropics and a negative response in the extra‐tropics occurs at relatively low latitudes
Scattering and absorbing aerosol effects on precipitation over land and ocean and under more realistic conditions are examined
The south-eastern Atlantic Ocean (SEA) is semi-permanently covered by one of
the most extensive stratocumulus cloud decks on the planet and experiences
about one-third of the global biomass burning ...emissions from the southern
Africa savannah region during the fire season. To get a better understanding
of the impact of these biomass burning aerosols on clouds and the radiation
balance over the SEA, the latest generation of the UK Earth System Model
(UKESM1) is employed. Measurements from the CLARIFY and ORACLES flight
campaigns are used to evaluate the model, demonstrating that the model has
good skill in reproducing the biomass burning plume. To investigate the
underlying mechanisms in detail, the effects of biomass burning aerosols on
the clouds are decomposed into radiative effects (via absorption and
scattering) and microphysical effects (via perturbation of cloud
condensation nuclei – CCN – and cloud microphysical processes).
July–August means are used to characterize aerosols, clouds, and the
radiation balance during the fire season. Results show that around 65 % of CCN
at 0.2 % supersaturation in the SEA can be attributed to biomass burning.
The absorption effect of biomass burning aerosols is the most significant on clouds and radiation. Near the continent, it increases the
supersaturation diagnosed by the activation scheme, while further from the
continent it reduces the altitude of the supersaturation. As a result, the
cloud droplet number concentration responds with a similar pattern to the
absorption effect of biomass burning aerosols. The microphysical effect,
however, decreases the supersaturation and increases the cloud droplet
concentration over the ocean, although this change is relatively small. The
liquid water path is also significantly increased over the SEA (mainly
caused by the absorption effect of biomass burning aerosols) when biomass
burning aerosols are above the stratocumulus cloud deck. The microphysical
pathways lead to a slight increase in the liquid water path over the ocean.
These changes in cloud properties indicate the significant role of biomass
burning aerosols for clouds in this region. Among the effects of biomass
burning aerosols on the radiation balance, the semi-direct radiative effects
(rapid adjustments induced by the radiative effects of biomass burning aerosols)
have a dominant cooling impact over the SEA, which offset the warming direct
radiative effect (radiative forcing from biomass burning aerosol–radiation
interactions) and lead to an overall net cooling radiative effect in the SEA.
However, the magnitude and the sign of the semi-direct effects are sensitive
to the relative location of biomass burning aerosols and clouds, reflecting
the critical task of the accurate modelling of the biomass burning plume and
clouds in this region.
The change in planetary albedo due to aerosol–cloud interactions during the industrial era is the leading source of uncertainty in inferring Earth’s climate sensitivity to increased greenhouse gases ...from the historical record. The variable that controls aerosol–cloud interactions in warm clouds is droplet number concentration. Global climate models demonstrate that the present-day hemispheric contrast in cloud droplet number concentration between the pristine Southern Hemisphere and the polluted Northern Hemisphere oceans can be used as a proxy for anthropogenically driven change in cloud droplet number concentration. Remotely sensed estimates constrain this change in droplet number concentration to be between 8 cm−3 and 24 cm−3. By extension, the radiative forcing since 1850 from aerosol–cloud interactions is constrained to be −1.2 W·m−2 to −0.6 W·m−2. The robustness of this constraint depends upon the assumption that pristine Southern Ocean droplet number concentration is a suitable proxy for preindustrial concentrations. Droplet number concentrations calculated from satellite data over the Southern Ocean are high in austral summer. Near Antarctica, they reach values typical of Northern Hemisphere polluted outflows. These concentrations are found to agree with several in situ datasets. In contrast, climate models show systematic underpredictions of cloud droplet number concentration across the Southern Ocean. Near Antarctica, where precipitation sinks of aerosol are small, the underestimation by climate models is particularly large. This motivates the need for detailed process studies of aerosol production and aerosol–cloud interactions in pristine environments. The hemispheric difference in satellite estimated cloud droplet number concentration implies preindustrial aerosol concentrations were higher than estimated by most models.
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