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The Radiative Forcing Model Intercomparison Project (RFMIP) allows estimates of effective radiative forcing (ERF) in the Coupled Model Intercomparison Project phase six (CMIP6). We analyze the RFMIP output, including the new experiments from models that use the same parameterization for anthropogenic aerosols (RFMIP‐SpAer), to characterize and better understand model differences in aerosol ERF. We find little changes in the aerosol ERF for 1970–2014 in the CMIP6 multi‐model mean, which implies greenhouse gases primarily explain the positive trend in the total anthropogenic ERF. Cloud‐mediated effects dominate the present‐day aerosol ERF in most models. The results highlight a regional increase in marine cloudiness due to aerosols, despite suppressed cloud lifetime effects in that RFMIP‐SpAer experiment. Negative cloud‐mediated effects mask positive direct effects in many models, which arise from strong anthropogenic aerosol absorption. The findings suggest opportunities to better constrain simulated ERF by revisiting the optical properties and long‐range transport of aerosols. Plain Language Summary: Aerosols are particles in the atmosphere with sizes ranging from nanometers to tens of micrometers, which are emitted by natural and anthropogenic processes or formed from gases in the atmosphere. The extent to which anthropogenic aerosols affect the radiation budget of Earth is important to better understand anthropogenic climate changes. Aerosol effects on the radiation budget are simulated by complex Earth system models that informed the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Our study addresses why such model experiments show different magnitudes for aerosol radiative effects. The results point to opportunities to further improve models with existing observations of aerosol optical properties and aerosol transport over oceans in addition to the much‐studied aerosol effects on clouds. Key Points: Coupled Model Intercomparison Project phase six (CMIP6) averaged trend in aerosol effective radiative forcing (ERF) is small for 1970–2014 and weakly positive for 2000–2014Positive direct aerosol radiative effects in CMIP6 models are associated with strong aerosol absorptionDiverse and often strong cloud‐mediated effects primarily determine the magnitude of aerosol ERF in CMIP6 [ABSTRACT FROM AUTHOR]

Atmospheric iron (Fe) deposition to the open ocean affects net primary productivity, nitrogen fixation, and carbon uptake. We investigate changes in soluble Fe (SFe) deposition from the pre‐industrial period to the late 21st century using the EC‐Earth3‐Iron Earth System model. EC‐Earth3‐Iron considers various sources of Fe, including dust, fossil fuel combustion, and biomass burning, and features comprehensive atmospheric chemistry, representing atmospheric oxalate, sulfate, and Fe cycles. We show that anthropogenic activity has changed the magnitude and spatial distribution of SFe deposition by increasing combustion Fe emissions and atmospheric acidity and oxalate levels. We report that SFe deposition has doubled since the early industrial era, using the Coupled Model Intercomparison Project Phase 6 emission inventory. We highlight acidity as the main solubilization pathway for dust‐Fe and oxalate‐promoted processing for the solubilization of combustion‐Fe. We project a global SFe deposition increase of 40% by the late 21st century relative to present day under Shared Socioeconomic Pathway (SSP) 3–7.0, which assumes weak climate change mitigation policies. Conversely, SSPs with stronger mitigation pathways (1–2.6 and 2–4.5) result in 35% and 10% global decreases, respectively. Despite these differences, SFe deposition increases over the equatorial Pacific and decreases in the Southern Ocean (SO) for all SSPs. We further observe that deposition over the equatorial Pacific and SO are highly sensitive to future changes in dust emissions from Australia and South America, as well as from North Africa. Future studies should focus on the potential impact of climate‐ and human‐induced changes in dust and wildfires combined. Plain Language Summary: Marine biota needs bioavailable (or soluble) iron (Fe) as a nutrient for photosynthesis. Given that photosynthesis captures atmospheric carbon dioxide (CO2), the amount and spatial distribution of soluble Fe (SFe) deposited regulate the capacity of the ocean to store CO2 and hence can affect the global climate. The supply of Fe to the atmosphere is dominated by desert dust aerosols created by wind erosion of arid surfaces, with a minor contribution from combustion aerosols. Freshly emitted dust‐Fe is mainly insoluble but can be partly transformed into SFe species during atmospheric transport through various dissolution mechanisms mainly affected by aerosol acidity and oxalate concentrations. We conduct a modeling study to quantitatively understand how changes in aerosol and gas‐phase species emissions from the early industrial era to the late 21st century alter SFe deposition. Our simulations indicate that SFe deposition has doubled since the beginning of the industrial era. Future estimates depend upon the projected socio‐economic scenario, with solubilization being boosted in the scenario with weaker mitigation policies, and vice versa. Results show that understanding changes in aerosol acidity and oxalate concentrations are key to constrain projections of SFe deposition. Key Points: Global soluble iron deposition will increase (decrease) by 40% (35%) with weak (strong) climate mitigation policiesAerosol acidity controls the dissolution of iron from dust sources and oxalate from combustion sources in the past, present and futureFuture soluble iron deposition decreases (increases) over the Southern Ocean (the equatorial Pacific) regardless of the mitigation policy [ABSTRACT FROM AUTHOR]

Abstract: In this study, we investigated the role of climatic variability and atmospheric nitrogen deposition in driving long‐term tree growth in canopy beech trees along a geographic gradient in the montane belt of the Italian peninsula, from the Alps to the southern Apennines. We sampled dominant trees at different developmental stages (from young to mature tree cohorts, with tree ages spanning from 35 to 160 years) and used stem analysis to infer historic reconstruction of tree volume and dominant height. Annual growth volume (GV) and height (GH) variability were related to annual variability in model simulated atmospheric nitrogen deposition and site‐specific climatic variables, (i.e. mean annual temperature, total annual precipitation, mean growing period temperature, total growing period precipitation, and standard precipitation evapotranspiration index) and atmospheric CO2 concentration, including tree cambial age among growth predictors. Generalized additive models (GAM), linear mixed‐effects models (LMM), and Bayesian regression models (BRM) were independently employed to assess explanatory variables. The main results from our study were as follows: (i) tree age was the main explanatory variable for long‐term growth variability; (ii) GAM, LMM, and BRM results consistently indicated climatic variables and CO2 effects on GV and GH were weak, therefore evidence of recent climatic variability influence on beech annual growth rates was limited in the montane belt of the Italian peninsula; (iii) instead, significant positive nitrogen deposition (Ndep) effects were repeatedly observed in GV and GH; the positive effects of Ndep on canopy height growth rates, which tended to level off at Ndep values greater than approximately 1.0 g m−2 y−1, were interpreted as positive impacts on forest stand above‐ground net productivity at the selected study sites. [ABSTRACT FROM AUTHOR]

We present a global assessment of the relationships between the short-wave surface albedo of forests, derived from the MODIS satellite instrument product at 0.5° spatial resolution, with simulated atmospheric nitrogen deposition rates ( Ndep), and climatic variables (mean annual temperature Tm and total annual precipitation P), compiled at the same spatial resolution. The analysis was performed on the following five forest plant functional types ( PFTs): evergreen needle-leaf forests ( ENF); evergreen broad-leaf forests ( EBF); deciduous needle-leaf forests ( DNF); deciduous broad-leaf forests ( DBF); and mixed-forests ( MF). Generalized additive models ( GAMs) were applied in the exploratory analysis to assess the functional nature of short-wave surface albedo relations to environmental variables. The analysis showed evident correlations of albedo with environmental predictors when data were pooled across PFTs: Tm and Ndep displayed a positive relationship with forest albedo, while a negative relationship was detected with P. These correlations are primarily due to surface albedo differences between conifer and broad-leaf species, and different species geographical distributions. However, the analysis performed within individual PFTs, strengthened by attempts to select 'pure' pixels in terms of species composition, showed significant correlations with annual precipitation and nitrogen deposition, pointing toward the potential effect of environmental variables on forest surface albedo at the ecosystem level. Overall, our global assessment emphasizes the importance of elucidating the ecological mechanisms that link environmental conditions and forest canopy properties for an improved parameterization of surface albedo in climate models. [ABSTRACT FROM AUTHOR]

To evaluate the effect of sampling frequency on the global monthly mean aerosol optical thickness (AOT), we use 6 years of geographical coordinates of Moderate Resolution Imaging Spectroradiometer (MODIS) L2 aerosol data, daily global aerosol fields generated by the Goddard Institute for Space Studies General Circulation Model and the chemical transport models Global Ozone Chemistry Aerosol Radiation and Transport, Spectral Radiation-transport Model for Aerosol Species and Transport Model 5, at a spatial resolution between 1.125°× 1.125° and 2°× 3°: the analysis is restricted to 60°S-60°N geographical latitude. We found that, in general, the MODIS coverage causes an underestimate of the global mean AOT over the ocean. The long-term mean absolute monthly difference between all and dark target (DT) pixels was 0.01-0.02 over the ocean and 0.03-0.09 over the land, depending on the model dataset. Negative DT biases peak during boreal summers, reaching 0.07-0.12 (30-45% of the global long-term mean AOT). Addition of the Deep Blue pixels tempers the seasonal dependence of the DT biases and reduces the mean AOT difference over land by 0.01-0.02. These results provide a quantitative measure of the effect the pixel exclusion due to cloud contamination, ocean sun-glint and land type has on the MODIS estimates of the global monthly mean AOT. We also simulate global monthly mean AOT estimates from measurements provided by pixel-wide along-track instruments such as the Aerosol Polarimetry Sensor and the Cloud-Aerosol LiDAR with Orthogonal Polarization. We estimate the probable range of the global AOT standard error for an along-track sensor to be 0.0005-0.0015 (ocean) and 0.0029-0.01 (land) or 0.5-1.2% and 1.1-4% of the corresponding global means. These estimates represent errors due to sampling only and do not include potential retrieval errors. They are smaller than or comparable to the published estimate of 0.01 as being a climatologically significant change in the global mean AOT, suggesting that sampling density is unlikely to limit the use of such instruments for climate applications at least on a global, monthly scale. [ABSTRACT FROM AUTHOR]