How well do the CMIP6 models simulate dust aerosols?

Mineral dust impacts key processes in the Earth system, including the radiation budget, clouds, and nutrient cycles. We evaluate dust aerosols in 16 models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) against multiple reanalyses and satellite observations. Most models, and particularly the multi-model ensemble mean (MEM), capture the spatial patterns and seasonal cycles of global dust processes well. However, large uncertainties and inter-model diversity are found. For example, global dust emissions, primarily driven by model-simulated surface winds, vary by a factor of 5 across models, while the MEM estimate is double the amount in reanalyses. The ranges of CMIP6 model-simulated global dust emission, deposition, burden and optical depth (DOD) are larger than previous generations of models. Models present considerable disagreement in dust seasonal cycles over North China and North America. Here, DOD values are overestimated by most CMIP6 models, with the MEM estimate 1.2–1.7 times larger compared to satellite and reanalysis datasets. Such overestimates can reach up to a factor of 5 in individual models. Models also fail to reproduce some key features of the regional dust distribution, such as dust accumulation along the southern edge of the Himalayas. Overall, there are still large uncertainties in CMIP6 models’ simulated dust processes, which feature inconsistent biases throughout the dust lifecycle between models, particularly in the relationship connecting dust mass to DOD. Our results imply that modelled dust processes are becoming more uncertain as models become more sophisticated. More detailed output relating to the dust cycle in future intercomparison projects will enable better constraints of global dust cycles, and enable the potential identification of observationally-constrained links between dust cycles and optical properties

Significant climate impacts of aerosol changes driven by growth in energy use and advances in emission control technology

Anthropogenic aerosols have increased significantly since the industrial revolution, driven largely by growth in emissions from energy use in sectors including power generation, industry, and transport. Advances in emission control technologies since around 1970, however, have partially counteracted emissions increases from the above sectors. Using the fully coupled Community Earth System Model, we quantify the effective radiative forcing (ERF) and climate response to 1970–2010 aerosol changes associated with the above two policy-relevant emission drivers. Emissions from energy-use growth generate a global mean aerosol ERF (mean ± 1 standard deviation) of −0.31 ± 0.22 W m−2 and result in a global mean cooling (−0.35 ± 0.17 K) and a precipitation reduction (−0.03 ± 0.02 mm d−1 ). By contrast, the avoided emissions from advances in emission control technology, which benefit air quality, generate a global mean ERF of +0.21 ± 0.23 W m−2 , a global warming of +0.10 ± 0.13 K, and global mean precipitation increase of +0.01 ± 0.02 mm d−1 . Despite the relatively small changes in global mean precipitation, these two emission drivers have profound impacts at regional scales, in particular over Asia and Europe. The total net aerosol impacts on climate are dominated by energy-use growth, from Asia in particular. However, technology advances outweigh energy-use growth over Europe and North America. Various non-linear processes are involved along the pathway from aerosol and their precursor emissions to radiative forcing and ultimately to climate responses, suggesting that the diagnosed aerosol forcing and effects must be interpreted in the context of experiment designs. Further, the temperature response per unit aerosol ERF varies significantly across many factors, including location and magnitude of emission changes, implying that ERF, and the related metrics, needs to be used very carefully for aerosols. Future aerosol-related emission pathways have large temporal and spatial uncertainties; our findings provide useful information for both assessing and interpreting such uncertainties, and they may help inform future climate change impact reduction strategies.JRC.C.5-Air and Climat

Large diversity in AMOC internal variability across NEMO-based climate models

We characterise, and explore the drivers of, differences in the internal variability of the atlantic meridional overturning circulation (AMOC) across five NEMO-based CMIP6 class climate models. While the variability of AMOC variability is dominated by its lower dense limb in all models, there is large diversity in the timescale, multidecadal variability, and latitudinal coherence of AMOC across models. In particular, the UK models have much weaker AMOC multidecadal variability and latitudinal coherence. The model diversity is associated with differences in salinity-governed surface density variations which drive high-density water mass transformation (WMT) in the Greenland–Iceland–Norwegian Seas (GIN) and the Arctic. Specifically, GIN Seas WMT shows large multidecadal variability which has a major impact on AMOC variability in non-UK models. In contrast, the smaller variability in GIN Seas WMT in the UK models has limited impact on the lower latitude AMOC via the Denmark strait overflow mass transport. This leads to a latitudinally less coherent and weaker multidecadal variability of the AMOC lower limb. Such differences between UK and non-UK models are related to differences in model mean states and densification processes in the Arctic and GIN Seas. Consequently, we recommend further in-depth studies to better understand and constrain processes driving salinity changes in the Arctic and GIN Seas for more reliable representation of the AMOC in climate models

Trends in global tropospheric hydroxyl radical and methane lifetime since 1850 from AerChemMIP

We analyse historical (1850–2014) atmospheric hydroxyl (OH) and methane lifetime data from Coupled Model Intercomparison Project Phase 6 (CMIP6)/Aerosols and Chemistry Model Intercomparison Project (AerChemMIP) simulations. Tropospheric OH changed little from 1850 up to around 1980, then increased by around 9% up to 2014, with an associated reduction in methane lifetime. The model-derived OH trends from 1980 to 2005 are broadly consistent with trends estimated by several studies that infer OH from inversions of methyl chloroform and associated measurements; most inversion studies indicate decreases in OH since 2005. However, the model results fall within observational uncertainty ranges. The upward trend in modelled OH since 1980 was mainly driven by changes in anthropogenic near-term climate forcer emissions (increases in anthropogenic nitrogen oxides and decreases in CO). Increases in halocarbon emissions since 1950 have made a small contribution to the increase in OH, whilst increases in aerosol-related emissions have slightly reduced OH. Halocarbon emissions have dramatically reduced the stratospheric methane lifetime by about 15 %– 40 %; most previous studies assumed a fixed stratospheric lifetime. Whilst the main driver of atmospheric methane increases since 1850 is emissions of methane itself, increased ozone precursor emissions have significantly modulated (in general reduced) methane trends. Halocarbon and aerosol emissions are found to have relatively small contributions to methane trends. These experiments do not isolate the effects of climate change on OH and methane evolution; however, we calculate residual terms that are due to the combined effects of climate change and non-linear interactions between drivers. These residual terms indicate that non-linear interactions are important and differ between the two methodologies we use for quantifying OH and methane drivers. All these factors need to be considered in order to fully explain OH and methane trends since 1850; these factors will also be important for future trends

Rapidly evolving aerosol emissions are a dangerous omission from near-term climate risk assessments

Anthropogenic aerosol emissions are expected to change rapidly over the coming decades, driving strong, spatially complex trends in temperature, hydroclimate, and extreme events both near and far from emission sources. Under-resourced, highly populated regions often bear the brunt of aerosols’ climate and air quality effects, amplifying risk through heightened exposure and vulnerability. However, many policy-facing evaluations of near-term climate risk, including those in the latest Intergovernmental Panel on Climate Change assessment report, underrepresent aerosols’ complex and regionally diverse climate effects, reducing them to a globally averaged offset to greenhouse gas warming. We argue that this constitutes a major missing element in society’s ability to prepare for future climate change. We outline a pathway towards progress and call for greater interaction between the aerosol research, impact modeling, scenario development, and risk assessment communities

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.

Data supporting the manuscript "Effective radiative forcing and climate responses to 1970-2010 changes in greenhouse gases, anthropogenic aerosols and ozone"

This folder contains six files numbered in order. File01: The global mean surface temperature evolution from all the experiments analyzed File02; The CESM1 simulated aerosol burdens and AOD, used to plot both the bars and spatial maps in Figure 2 File03: The longitude, latitude grids, as well as the spatial map of 1970-2010 temperature and precipitation changes, used to plot the zonal mean and spatial maps. The observational and reanalysis data can be obtained from corresponding data sources cited in the paper File04: The spatial maps of effective radiative forcing and surface temperature responses to GHGs, aerosols and ozone. This dataset is used to plot both the spatial patterns in Figure 4, the regional mean ERF in Figure 5, the temperature sensitivity estimates in Figure 6, as well as the supporting Figure S2 and S3. File05:The spatial maps of precipitation responses to GHGs, aerosols and ozone, being used to plot the spatial patterns in Figure 7 and the zonal mean in Figure S4. File06: The probability distribution and the of global and regional mean daily precipitation. All these datasets are produced and can be read using the Python cPickle package.Zhao, Alcide; David, Stevenson; Massimo, Bollasina. (2019). Data supporting the manuscript "Effective radiative forcing and climate responses to 1970-2010 changes in greenhouse gases, anthropogenic aerosols and ozone", [dataset]. University of Edinburgh. School of GeoSciences. https://doi.org/10.7488/ds/2530