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Iceberg-hosted sediments and atmospheric dust transport potentially bioavailable iron to the Arctic and Southern oceans as ferrihydrite. Ferrihydrite is nanoparticulate and more soluble, as well as potentially more bioavailable, than other iron (oxyhydr)oxide minerals (lepidocrocite, goethite, and hematite). A suite of more than 50 iceberg-hosted sediments contain a mean content of 0.076 wt % Fe as ferrihydrite, which produces iceberg-hosted Fe fluxes ranging from 0.7 to 5.5 and 3.2 to 25 Gmoles yr−1 to the Arctic and Southern oceans respectively. Atmospheric dust (with little or no combustion products) contains a mean ferrihydrite Fe content of 0.038 wt % (corresponding to a fractional solubility of  ∼  1 %) and delivers much smaller Fe fluxes (0.02–0.07 Gmoles yr−1 to the Arctic Ocean and 0.0–0.02 Gmoles yr−1 to the Southern Ocean). New dust flux data show that most atmospheric dust is delivered to sea ice where exposure to melting/re-freezing cycles may enhance fractional solubility, and thus fluxes, by a factor of approximately 2.5. Improved estimates for these particulate sources require additional data for the iceberg losses during fjord transit, the sediment content of icebergs, and samples of atmospheric dust delivered to the polar regions.

This paper presents an analysis of the mineral dust aerosol modelled by five Earth system models (ESMs) within the project entitled Coordinated Research in Earth Systems and Climate: Experiments, kNowledge, Dissemination and Outreach (CRESCENDO). We quantify the global dust cycle described by each model in terms of global emissions, together with dry and wet deposition, reporting large differences in the ratio of dry over wet deposition across the models not directly correlated with the range of particle sizes emitted. The multi-model mean dust emissions with five ESMs is 2836 Tg yr−1 but with a large uncertainty due mainly to the difference in the maximum dust particle size emitted. The multi-model mean of the subset of four ESMs without particle diameters larger than 10 µ m is 1664 (σ=651) Tg yr−1. Total dust emissions in the simulations with identical nudged winds from reanalysis give us better consistency between models; i.e. the multi-model mean global emissions with three ESMs are 1613 (σ=278) Tg yr−1, but 1834 (σ=666) Tg yr−1 without nudged winds and the same models. Significant discrepancies in the globally averaged dust mass extinction efficiency explain why even models with relatively similar global dust load budgets can display strong differences in dust optical depth. The comparison against observations has been done in terms of dust optical depths based on MODIS (Moderate Resolution Imaging Spectroradiometer) satellite products, showing global consistency in terms of preferential dust sources and transport across the Atlantic. The global localisation of source regions is consistent with MODIS, but we found regional and seasonal differences between models and observations when we quantified the cross-correlation of time series over dust-emitting regions. To faithfully compare local emissions between models we introduce a re-gridded normalisation method that can also be compared with satellite products derived from dust event frequencies. Dust total deposition is compared with an instrumental network to assess global and regional differences. We find that models agree with observations within a factor of 10 for data stations distant from dust sources, but the approximations of dust particle size distribution at emission contributed to a misrepresentation of the actual range of deposition values when instruments are close to dust-emitting regions. The observed dust surface concentrations also are reproduced to within a factor of 10. The comparison of total aerosol optical depth with AERONET (AErosol RObotic NETwork) stations where dust is dominant shows large differences between models, although with an increase in the inter-model consistency when the simulations are conducted with nudged winds. The increase in the model ensemble consistency also means better agreement with observations, which we have ascertained for dust total deposition, surface concentrations and optical depths (against both AERONET and MODIS retrievals). We introduce a method to ascertain the contributions per mode consistent with the multi-modal direct radiative effects, which we apply to study the direct radiative effects of a multi-modal representation of the dust particle size distribution that includes the largest particles.

Mineral dust aerosols represent an active component of the Earth’s climate system, by interacting with radiation directly, and by modifying clouds and biogeochemistry. Mineral dust from polar ice cores over the last million years can be used as paleoclimate proxy, and provide unique information about climate variability, as changes in dust deposition at the core sites can be due to changes in sources, transport and/or deposition locally. Here we present results from a study based on climate model simulations using the Community Climate System Model. The focus of this work is to analyze simulated differences in the dust concentration, size distribution and sources in current climate conditions and during the Last Glacial Maximum at specific ice core locations in Antarctica, and compare with available paleodata. Model results suggest that South America is the most important source for dust deposited in Antarctica in current climate, but Australia is also a major contributor and there is spatial variability in the relative importance of the major dust sources. During the Last Glacial Maximum the dominant source in the model was South America, because of the increased activity of glaciogenic dust sources in Southern Patagonia-Tierra del Fuego and the Southernmost Pampas regions, as well as an increase in transport efficiency southward. Dust emitted from the Southern Hemisphere dust source areas usually follow zonal patterns, but southward flow towards Antarctica is located in specific areas characterized by southward displacement of air masses. Observations and model results consistently suggest a spatially variable shift in dust particle sizes. This is due to a combination of relatively reduced en route wet removal favouring a generalized shift towards smaller particles, and on the other hand to an enhanced relative contribution of dry coarse particle deposition in the Last Glacial Maximum.

We quantify the effective radiative forcing (ERF) of anthropogenic aerosols modelled by the aerosol–climate model CAM5.3-MARC-ARG. CAM5.3-MARC-ARG is a new configuration of the Community Atmosphere Model version 5.3 (CAM5.3) in which the default aerosol module has been replaced by the two-Moment, Multi-Modal, Mixing-state-resolving Aerosol model for Research of Climate (MARC). CAM5.3-MARC-ARG uses the ARG aerosol-activation scheme, consistent with the default configuration of CAM5.3. We compute differences between simulations using year-1850 aerosol emissions and simulations using year-2000 aerosol emissions in order to assess the radiative effects of anthropogenic aerosols. We compare the aerosol lifetimes, aerosol column burdens, cloud properties, and radiative effects produced by CAM5.3-MARC-ARG with those produced by the default configuration of CAM5.3, which uses the modal aerosol module with three log-normal modes (MAM3), and a configuration using the modal aerosol module with seven log-normal modes (MAM7). Compared with MAM3 and MAM7, we find that MARC produces stronger cooling via the direct radiative effect, the shortwave cloud radiative effect, and the surface albedo radiative effect; similarly, MARC produces stronger warming via the longwave cloud radiative effect. Overall, MARC produces a global mean net ERF of -1.79±0.03 W m−2, which is stronger than the global mean net ERF of -1.57±0.04 W m−2 produced by MAM3 and -1.53±0.04 W m−2 produced by MAM7. The regional distribution of ERF also differs between MARC and MAM3, largely due to differences in the regional distribution of the shortwave cloud radiative effect. We conclude that the specific representation of aerosols in global climate models, including aerosol mixing state, has important implications for climate modelling.

Interannual variability in desert dust is widely observed and simulated, yet the sensitivity of these desert dust simulations to a particular meteorological dataset, as well as a particular model construction, is not well known. Here we use version 4 of the Community Atmospheric Model (CAM4) with the Community Earth System Model (CESM) to simulate dust forced by three different reanalysis meteorological datasets for the period 1990–2005. We then contrast the results of these simulations with dust simulated using online winds dynamically generated from sea surface temperatures, as well as with simulations conducted using other modeling frameworks but the same meteorological forcings, in order to determine the sensitivity of climate model output to the specific reanalysis dataset used. For the seven cases considered in our study, the different model configurations are able to simulate the annual mean of the global dust cycle, seasonality and interannual variability approximately equally well (or poorly) at the limited observational sites available. Overall, aerosol dust-source strength has remained fairly constant during the time period from 1990 to 2005, although there is strong seasonal and some interannual variability simulated in the models and seen in the observations over this time period. Model interannual variability comparisons to observations, as well as comparisons between models, suggest that interannual variability in dust is still difficult to simulate accurately, with averaged correlation coefficients of 0.1 to 0.6. Because of the large variability, at least 1 year of observations at most sites are needed to correctly observe the mean, but in some regions, particularly the remote oceans of the Southern Hemisphere, where interannual variability may be larger than in the Northern Hemisphere, 2–3 years of data are likely to be needed.

Purpose of Review Natural archives are imprinted with signs of the past variability of some aerosol species in connection to major climate changes. In certain cases, it is possible to use these paleo-observations as a quantitative tool for benchmarking climate model simulations. Where are we on the path to use observations and models in connection to define an envelope on aerosol feedback onto climate? Recent Findings On glacial-interglacial time scales, the major advances in our understanding refer to mineral dust, in terms of quantifying its global mass budget, as well as in estimating its direct impacts on the atmospheric radiation budget and indirect impacts on the oceanic carbon cycle. Summary Even in the case of dust, major uncertainties persist. More detailed observational studies and model intercomparison experiments such as in the Paleoclimate Modelling Intercomparison Project phase 4 will be critical in advancing the field. The inclusion of new processes such as cloud feedbacks and studies focusing on other aerosol species are also envisaged.

Mineral dust acts both as a tracer and a forcing agent of climate change. Past dust variability, imprinted in paleodust records from natural archives, offers the unique opportunity to reconstruct the global dust cycle within a range of possibilities that plausibly encompass future variations in response to climate change and land-cover and land-use changes. Dust itself has direct and indirect feedbacks on the climate system, through impacts on the atmosphere radiative budget and the carbon cycle. Starting from well-constrained reconstructions of the present and past dust cycle, we focus on quantifying dust direct impacts on the atmospheric radiation. We discuss the intrinsic effects of dust onto climate, and how changes in the global dust budget and surface conditions modulate the effective impacts on surface temperatures and precipitation. Most notably, the presence of dust tends to enhance the West African monsoon and warm the Arctic. We also highlight how different choices in terms of dust optical properties and size distributions may yield opposite results, and what are the observational constraints we can use to make an informed choice of model parameters. Finally, we discuss how dust variability might have influenced ongoing climate transitions in the past. In particular we found that a reduction in dust load, along with a reduced cryosphere cover, acted to offset Arctic warming during the deglaciation, potentially playing a role in shaping the Northern Hemisphere deglacial dynamics.

Abstract Mineral dust acts both as a tracer and a forcing agent of climate change. Past dust variability, imprinted in paleodust records from natural archives, offers the unique opportunity to reconstruct the global dust cycle within a range of possibilities that plausibly encompass future variations in response to climate change and land-cover and land-use changes. Dust itself has direct and indirect feedbacks on the climate system, through impacts on the atmosphere radiative budget and the carbon cycle. Starting from well-constrained reconstructions of the present and past dust cycle, we focus on quantifying dust direct impacts on the atmospheric radiation. We discuss the intrinsic effects of dust onto climate, and how changes in the global dust budget and surface conditions modulate the effective impacts on surface temperatures and precipitation. Most notably, the presence of dust tends to enhance the West African monsoon and warm the Arctic. We also highlight how different choices in terms of dust optical properties and size distributions may yield opposite results, and what are the observational constraints we can use to make an informed choice of model parameters. Finally, we discuss how dust variability might have influenced ongoing climate transitions in the past. In particular we found that a reduction in dust load, along with a reduced cryosphere cover, acted to offset Arctic warming during the deglaciation, potentially playing a role in shaping the Northern Hemisphere deglacial dynamics.

Estimating past aerosol radiative effects and their uncertainties is an important topic in climate science. Aerosol radiative effects propagate into large uncertainties in estimates of how present and future climate evolves with changing greenhouse gas emissions. A deeper understanding of how aerosols affected the atmospheric energy budget under past climates is hindered in part by a lack of relevant paleo-observations and in part because less attention has been paid to the problem. Because of the lack of information we do not seek here to determine the change in the radiative forcing due to aerosol changes but rather to estimate the uncertainties in those changes. Here we argue that current uncertainties from emission uncertainties (90 % confidence interval range spanning 2.8 W m−2) are just as large as model spread uncertainties (2.8 W m−2) in calculating preindustrial to present-day aerosol radiative effects. There are no estimates of radiative forcing for important aerosols such as wildfire and dust aerosols in most paleoclimate time periods. However, qualitative analysis of paleoclimate proxies suggests that changes in aerosols between different past climates are similar in magnitude to changes in aerosols between the preindustrial and present day; plus, there is the added uncertainty from the variability in aerosols and fires in the preindustrial. From the limited literature we crudely estimate a paleoclimate aerosol uncertainty for the Last Glacial Maximum relative to preindustrial of 4.8 W m−2, and we estimate the uncertainty in the aerosol feedback in the natural Earth system over the paleoclimate (Last Glacial Maximum to preindustrial) to be about 3.2 W m−2 K−1. In order to more accurately assess the uncertainty in historical aerosol radiative effects, we propose a new model intercomparison project, which would include multiple plausible emission scenarios tested across a range of state-of-the-art climate models over the historical period. These emission scenarios would then be compared to the available independent aerosol observations to constrain which are most probable. In addition, future efforts should work to characterize and constrain paleo-aerosol forcings and uncertainties. Careful propagation of aerosol uncertainties in the literature is required to ensure an accurate quantification of uncertainties in projections of future climate changes.