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Despite continuous improvement during recent decades, state of the art global chemistry-climate models (CCMs) are still showing biases compared to observational data, illustrating remaining difficulties and challenges in the simulation of atmospheric processes governing ozone production and decay. Therefore, CCM output is frequently bias-corrected in studies seeking to explore changing air quality burdens and associated impacts on human health (e.g., Rieder et al., 2018). Here we assess the strengths and limitations of different bias correction techniques for CCM simulations with focus on maximum daily 8-hour average surface ozone. Ozone fields are chosen as ozone is known as regional pollutant and thus shows smaller spatial heterogeneity in its burden than e.g. particulate matter. Within our comparison a set of different innovative, as well as, common bias correction techniques are applied to output of selected global coupled CCMs contributing hindcast simulations to the Coupled Model Intercomparison Project Phase 6 (CMIP6). For bias correction and evaluation, we utilize gridded observational data for the European and US domains according to Schnell et al. [2014]. The statistical bias-correction techniques applied and compared are quantile mapping, delta-function, relative and mean bias correction. As surface ozone pollution is commonly associated with a strong seasonal cycle, the adjustment techniques are applied to model data on monthly basis, and skill scores for individual bias correction techniques are compared across individual CMIP6 models for both seasonal and annual timescales over the period 1995-2014. Our results highlight large differences among individual bias correction techniques and advocate for the use of more complex correction strategies involving corrections across the spatio-temporal distribution of the ozone field.References:Rieder, H.E., Fiore A.M., Clifton, O.E., Correa, G., Horowitz, L.W., Naik, V.: Combining model projections with site-level observations to estimate changes in distributions and seasonality of ozone in surface air over the U.S.A., Atmos. Env., 193, 302-315, https://doi.org/10.1016/j.atmosenv.2018.07.042, 2018.Schnell, J. L., Holmes, C. D., Jangam, A., and Prather, M. J.: Skill in forecasting extreme ozone pollution episodes with a global atmospheric chemistry model, Atmos. Chem. Phys., 14, 7721–7739, https://doi.org/10.5194/acp-14-7721-2014, 2014.

The amount of short wave radiation absorbed by dust has remained uncertain. We have developed a more accurate representation of dust absorption that is based on the observed dust mineralogical composition and accounts for very large particles. We analyze the results from two fully coupled climate simulations of 100 years in terms of their simulated precipitation patterns against observations. A striking benefit of the new dust optical and physical properties is that tropical precipitation over the Sahel, tropical North Atlantic and West Indian Ocean are significantly improved compared to observations, without degrading precipitations elsewhere. This alleviates a common persistent bias in Earth system models that exhibit a summer African monsoon that does not reach far enough north. We show that the improvements documented here for the IPSL-CM61 climate model result from both a thermodynamical and dynamical response to dust absorption, which is unrelated to natural variability. Aerosol absorption induces more water vapor advection from the ocean to the Sahel region, thereby providing an added supply of moisture available for precipitation. This work, thus, provides a path towards improving precipitation patterns in these regions by accounting for both physical and optical properties of the aerosol more realistically.

In the city centre of Vienna, Austria ozone (maximum 8 hour mean) mda8 exceedances of the threshold value of 120 μg/m³ can occur from as early as March until September, which coincides with the main local vegetation season. Biogenic volatile organic compounds (bVOCs), which are mainly emitted by forests, but also other vegetation as agricultural field crops and are precursor substances to atmospheric formaldehyde (HCHO). Thereby they contribute to the production of ozone in and around the city. On the other hand, vegetated areas reduce the ozone concentration by uptake via stomatal and cuticular pathways and soil uptake.In this study the dependency of HCHO mixing ratios, obtained from path averaged MAX-DOAS UV retrievals over the Vienna city centre, on meteorological parameters (air temperature, global radiation, boundary layer height) and vegetation drought stress indicators are analysed, focusing on the difference between drought and non-drought conditions. Following indicators are used: standardized precipitation index (SPI), relative soil saturation from the Agricultural Risk Information System (ARIS), vapour pressure deficit and satellite-based photosynthetically active radiation anomaly (fAPAR) as well as solar-induced chlorophyll fluorescence (SIF).A clear dependency of the HCHO on vegetation-related parameters and the area of origin of HCHO and its precursor substances is found. However, the strength of the relationship between the parameters changes depending on the vegetation status. The results of the observational HCHO analyses spanning 2017-2021 are compared with bVOCs estimates of the Model of Emissions of Gases and Aerosols from Nature (MEGAN). The observed ozone concentrations are compared with the ozone mixing ratios and dry deposition rates calculated by the chemical transport model developed at Meteorological Synthesizing Centre-West within the European Monitoring and Evaluation Program (EMEP MSC-W model), which includes the Deposition of Ozone for Stomatal Exchange (DO3SE) model, to better understand timing and magnitudes of sources and sinks. Possible consequences for exceedances of the mda8 ozone target value in the study region are discussed.

Aerosol-induced absorption of shortwave radiation can modify the climate through local atmospheric heating, which affects lapse rates, precipitation, and cloud formation. Presently, the total amount of aerosol absorption is poorly constrained, and the main absorbing aerosol species (black carbon (BC), organic aerosols (OA), and mineral dust) are diversely quantified in global climate models. As part of the third phase of the Aerosol Comparisons between Observations and Models (AeroCom) intercomparison initiative (AeroCom phase III), we here document the distribution and magnitude of aerosol absorption in current global aerosol models and quantify the sources of intermodel spread, highlighting the difficulties of attributing absorption to different species. In total, 15 models have provided total present-day absorption at 550 nm (using year 2010 emissions), 11 of which have provided absorption per absorbing species. The multi-model global annual mean total absorption aerosol optical depth (AAOD) is 0.0054 (0.0020 to 0.0098; 550 nm), with the range given as the minimum and maximum model values. This is 28 % higher compared to the 0.0042 (0.0021 to 0.0076) multi-model mean in AeroCom phase II (using year 2000 emissions), but the difference is within 1 standard deviation, which, in this study, is 0.0023 (0.0019 in Phase II). Of the summed component AAOD, 60 % (range 36 %–84 %) is estimated to be due to BC, 31 % (12 %–49 %) is due to dust, and 11 % (0 %–24 %) is due to OA; however, the components are not independent in terms of their absorbing efficiency. In models with internal mixtures of absorbing aerosols, a major challenge is the lack of a common and simple method to attribute absorption to the different absorbing species. Therefore, when possible, the models with internally mixed aerosols in the present study have performed simulations using the same method for estimating absorption due to BC, OA, and dust, namely by removing it and comparing runs with and without the absorbing species. We discuss the challenges of attributing absorption to different species; we compare burden, refractive indices, and density; and we contrast models with internal mixing to models with external mixing. The model mean BC mass absorption coefficient (MAC) value is 10.1 (3.1 to 17.7) m2 g−1 (550 nm), and the model mean BC AAOD is 0.0030 (0.0007 to 0.0077). The difference in lifetime (and burden) in the models explains as much of the BC AAOD spread as the difference in BC MAC values. The difference in the spectral dependency between the models is striking. Several models have an absorption Ångstrøm exponent (AAE) close to 1, which likely is too low given current knowledge of spectral aerosol optical properties. Most models do not account for brown carbon and underestimate the spectral dependency for OA.

Stratospheric ozone and water vapor are key components of the Earth system, and past and future changes to both have important impacts on global and regional climate. Here we evaluate long-term changes in these species from the pre-industrial (1850) to the end of the 21st century in CMIP6 models under a range of future emissions scenarios. There is good agreement between the CMIP multi-model mean and observations for total column ozone (TCO), although there is substantial variation between the individual CMIP6 models. For the CMIP6 multi-model mean, global mean TCO has increased from ~300 DU in 1850 to ~305 DU in 1960, before rapidly declining in the 1970s and 1980s following the use and emission of halogenated ozone depleting substances (ODSs). TCO is projected to return to 1960’s values by the middle of the 21st century under the SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0 and SSP5-8.5 scenarios, and under the SSP3-7.0 and SSP5-8.5 scenarios TCO values are projected to be ~10 DU higher than the 1960’s values by 2100. However, under the SSP1-1.9 and SSP1-1.6 scenarios, TCO is not projected to return to the 1960’s values despite reductions in halogenated ODSs due to decreases in tropospheric ozone mixing ratios. This global pattern is similar to regional patterns, except in the tropics where TCO under most scenarios is not projected to return to 1960’s values, either through reductions in tropospheric ozone under SSP1-1.9 and SSP1-2.6, or through reductions in lower stratospheric ozone resulting from an acceleration of the Brewer-Dobson Circulation under other SSPs. In contrast to TCO, there is poorer agreement between the CMIP6 multi-model mean and observed lower stratospheric water vapour mixing ratios, with the CMIP6 multi-model mean underestimating observed water vapour mixing ratios by ~0.5 ppmv at 70hPa. CMIP6 multi-model mean stratospheric water vapor mixing ratios in the tropical lower stratosphere have increased by ~0.5 ppmv from the pre-industrial to the present day and are projected to increase further by the end of the 21st century. The largest increases (~2 ppmv) are simulated under the future scenarios with the highest assumed forcing pathway (e.g. SSP5-8.5). Tropical lower stratospheric water vapor, and to a lesser extent TCO, show large variations following explosive volcanic eruptions.

Biases in aerosol optical depths (AOD) and land surface albedos in the AeroCom models are manifested in the top-of-atmosphere (TOA) clear-sky reflected shortwave (SW) fluxes. Biases in the SW fluxes from AeroCom models are quantitatively related to biases in AOD and land surface albedo by using their radiative kernels. Over ocean, AOD contributes about 25% to the urn:x-wiley:19422466:media:jame21429:jame21429-math-0001S–urn:x-wiley:19422466:media:jame21429:jame21429-math-0002N mean SW flux bias for the multi-model mean (MMM) result. Over land, AOD and land surface albedo contribute about 40% and 30%, respectively, to the urn:x-wiley:19422466:media:jame21429:jame21429-math-0003S–urn:x-wiley:19422466:media:jame21429:jame21429-math-0004N mean SW flux bias for the MMM result. Furthermore, the spatial patterns of the SW flux biases derived from the radiative kernels are very similar to those between models and CERES observation, with the correlation coefficient of 0.6 over ocean and 0.76 over land for MMM using data of 2010. Satellite data used in this evaluation are derived independently from each other, consistencies in their bias patterns when compared with model simulations suggest that these patterns are robust. This highlights the importance of evaluating related variables in a synergistic manner to provide an unambiguous assessment of the models, as results from single parameter assessments are often confounded by measurement uncertainty. Model biases in land surface albedos can and must be corrected to accurately calculate TOA flux. We also compare the AOD trend from three models with the observation-based counterpart. These models reproduce all notable trends in AOD except the decreasing trend over eastern China and the adjacent oceanic regions due to limitations in the emission data set.

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.

The amount of shortwave radiation absorbed by dust has remained uncertain. We have developed a more accurate representation of dust absorption that is based on the observed dust mineralogical composition and accounts for very large particles. We analyze the results from two fully-coupled climate simulations of 100 years in terms of their simulated precipitation patterns against observations. A striking benefit of the new dust optical and physical properties is that tropical precipitations over Sahel, tropical North Atlantic and West Indian Ocean are significantly improved compared to observations, without degrading precipitations elsewhere. This alleviates a persistent bias in earth system models that exhibit a summer African monsoon that does not reach far enough North. We show that the improvement results from a thermodynamical and dynamical response to dust absorption is unrelated to natural variability. Aerosol absorption induces more water vapor advection from the ocean to the Sahel, thereby providing an added supply of moisture available for precipitation. This work thus provides a path towards improving precipitation patterns in these regions by more realistically accounting for both physical and optical properties of the aerosol.

Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the state-of-the-art modelling of aerosol optical properties is assessed from 14 global models participating in the phase III control experiment (AP3). The models are similar to CMIP6/AerChemMIP Earth System Models (ESMs) and provide a robust multi-model ensemble. Inter-model spread of aerosol species lifetimes and emissions appears to be similar to that of mass extinction coefficients (MECs), suggesting that aerosol optical depth (AOD) uncertainties are associated with a broad spectrum of parameterised aerosol processes. Total AOD is approximately the same as in AeroCom phase I (AP1) simulations. However, we find a 50 % decrease in the optical depth (OD) of black carbon (BC), attributable to a combination of decreased emissions and lifetimes. Relative contributions from sea salt (SS) and dust (DU) have shifted from being approximately equal in AP1 to SS contributing about 2∕3 of the natural AOD in AP3. This shift is linked with a decrease in DU mass burden, a lower DU MEC, and a slight decrease in DU lifetime, suggesting coarser DU particle sizes in AP3 compared to AP1. Relative to observations, the AP3 ensemble median and most of the participating models underestimate all aerosol optical properties investigated, that is, total AOD as well as fine and coarse AOD (AODf, AODc), Ångström exponent (AE), dry surface scattering (SCdry), and absorption (ACdry) coefficients. Compared to AERONET, the models underestimate total AOD by ca. 21 % ± 20 % (as inferred from the ensemble median and interquartile range). Against satellite data, the ensemble AOD biases range from −37 % (MODIS-Terra) to −16 % (MERGED-FMI, a multi-satellite AOD product), which we explain by differences between individual satellites and AERONET measurements themselves. Correlation coefficients (R) between model and observation AOD records are generally high (R>0.75), suggesting that the models are capable of capturing spatio-temporal variations in AOD. We find a much larger underestimate in coarse AODc (∼ −45 % ± 25 %) than in fine AODf (∼ −15 % ± 25 %) with slightly increased inter-model spread compared to total AOD. These results indicate problems in the modelling of DU and SS. The AODc bias is likely due to missing DU over continental land masses (particularly over the United States, SE Asia, and S. America), while marine AERONET sites and the AATSR SU satellite data suggest more moderate oceanic biases in AODc. Column AEs are underestimated by about 10 % ± 16 %. For situations in which measurements show AE > 2, models underestimate AERONET AE by ca. 35 %. In contrast, all models (but one) exhibit large overestimates in AE when coarse aerosol dominates (bias ca. +140 % if observed AE < 0.5). Simulated AE does not span the observed AE variability. These results indicate that models overestimate particle size (or underestimate the fine-mode fraction) for fine-dominated aerosol and underestimate size (or overestimate the fine-mode fraction) for coarse-dominated aerosol. This must have implications for lifetime, water uptake, scattering enhancement, and the aerosol radiative effect, which we can not quantify at this moment. Comparison against Global Atmosphere Watch (GAW) in situ data results in mean bias and inter-model variations of −35 % ± 25 % and −20 % ± 18 % for SCdry and ACdry, respectively. The larger underestimate of SCdry than ACdry suggests the models will simulate an aerosol single scattering albedo that is too low. The larger underestimate of SCdry than ambient air AOD is consistent with recent findings that models overestimate scattering enhancement due to hygroscopic growth. The broadly consistent negative bias in AOD and surface scattering suggests an underestimate of aerosol radiative effects in current global aerosol models. Considerable inter-model diversity in the simulated optical properties is often found in regions that are, unfortunately, not or only sparsely covered by ground-based observations. This includes, for instance, the Sahara, Amazonia, central Australia, and the South Pacific. This highlights the need for a better site coverage in the observations, which would enable us to better assess the models, but also the performance of satellite products in these regions. Using fine-mode AOD as a proxy for present-day aerosol forcing estimates, our results suggest that models underestimate aerosol forcing by ca. −15 %, however, with a considerably large interquartile range, suggesting a spread between −35 % and +10 %.

Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, the relative contributions of the world's major source regions to the global dust cycle remain poorly constrained. This problem hinders accounting for the potentially large impact of regional differences in dust properties on clouds, the Earth's energy balance, and terrestrial and marine biogeochemical cycles. Here, we constrain the contribution of each of the world's main dust source regions to the global dust cycle. We use an analytical framework that integrates an ensemble of global aerosol model simulations with observationally informed constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth (DAOD). We obtain a dataset that constrains the relative contribution of nine major source regions to size-resolved dust emission, atmospheric loading, DAOD, concentration, and deposition flux. We find that the 22–29 Tg (1 standard error range) global loading of dust with a geometric diameter up to 20 µm is partitioned as follows: North African source regions contribute ∼ 50 % (11–15 Tg), Asian source regions contribute ∼ 40 % (8–13 Tg), and North American and Southern Hemisphere regions contribute ∼ 10 % (1.8–3.2 Tg). These results suggest that current models on average overestimate the contribution of North African sources to atmospheric dust loading at ∼ 65 %, while underestimating the contribution of Asian dust at ∼ 30 %. Our results further show that each source region's dust loading peaks in local spring and summer, which is partially driven by increased dust lifetime in those seasons. We also quantify the dust deposition flux to the Amazon rainforest to be ∼ 10 Tg yr−1, which is a factor of 2–3 less than inferred from satellite data by previous work that likely overestimated dust deposition by underestimating the dust mass extinction efficiency. The data obtained in this paper can be used to obtain improved constraints on dust impacts on clouds, climate, biogeochemical cycles, and other parts of the Earth system.

This paper presents an analysis of the mineral dust aerosol modelled by five Earth System Models (ESM) within the Coordinated Research in Earth Systems and Climate: Experiments, kNowledge, Dissemination and Outreach (CRESCENDO) project. We quantify the global dust cycle described by each model in terms of global emissions together with dry and wet depositions, reporting large differences in 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 was 2954 Tg yr−1 but with a large uncertainty due mainly to the difference in maximum dust particle size emitted. For the subset of ESMs without particles larger than 10 μm we obtained 1664 (σ = 650) Tg yr−1. Total dust emissions with identical nudged winds from reanalysis give us better consistency between models with 1530 (σ = 282) Tg yr−1. Significant discrepancies in the globally averaged dust mass extinction efficiency explain why even models with relatively similar dust load global budgets can display strong differences in dust optical depths. The comparison against observations has been done in terms of dust optical depths based on MODIS satellite products, showing a global consistency in terms of preferential dust sources and transport across the Atlantic. However, 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 normalization method, that also can be compared with satellite products derived from dust events frequencies. Dust total depositions are compared with instrumental network to assess global and regional differences. We found that models agree with observations distant from dust sources within a factor 10, 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 observational dust surface concentrations also are reproduced within a factor 10. The comparison of total aerosol optical depths with AERONETv3 stations where dust is dominant shows large differences between models, however with an increase of the inter-model consistency when the simulations are conducted with nudged-winds. The increase of the model ensemble consistency also means a better agreement with observations, which we have ascertained for dust total deposition, surface concentrations and optical depths (against both AERONETv3 and MODIS-DOD retrievals). We estimated the direct radiative effects of a multi-modal representation of the dust particle size distribution that includes the largest particles measured at FENNEC experiment. We introduced a method to ascertain the contributions per mode consistent with the multimodal direct radiative effects.

Stratospheric ozone and water vapour are key components of the Earth system, and past and future changes to both have important impacts on global and regional climate. Here we evaluate long-term changes in these species from the pre- industrial (1850) to the end of the 21st century in CMIP6 models under a range of future emissions scenarios. There is good agreement between the CMIP multi-model mean and observations, although there is substantial variation between the individual CMIP6 models. For the CMIP6 multi-model mean, global total column ozone (TCO) has increased from ∼300 DU in 1850 to ∼305 DU in 1960, before rapidly declining in the 1970s and 1980s following the use and emission of halogenated ozone depleting substances (ODSs). TCO is projected to return to 1960s values by the middle of the 21st century under the SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0 and SSP5-8.5 scenarios, and under the SSP3-7.0 and SSP5-8.5 scenarios TCO values are projected to be ∼10 DU higher than the 1960s values by 2100. However, under the SSP1-1.9 and SSP1-1.6 scenarios, TCO is not projected to return to the 1960s values despite reductions in halogenated ODSs due to decreases in tropospheric ozone mixing ratios. This global pattern is similar to regional patterns, except in the tropics where TCO under most scenarios is not projected to return to 1960s values, either through reductions in tropospheric ozone under SSP1-1.9 and SSP1-2.6, or through reductions in lower stratospheric ozone resulting from an acceleration of the Brewer-Dobson Circulation under other SSPs. CMIP6 multi-model mean stratospheric water vapour mixing ratios in the tropical lower stratosphere have increased by ∼0.5 ppmv from the pre-industrial to the present day and are projected to increase further by the end of the 21st century. The largest increases (∼2 ppmv) are simulated under the future scenarios with the highest assumed forcing pathway (e.g. SSP5-8.5). Both TCO and tropical lower stratospheric water vapour show large variability following explosive volcanic eruptions.

Biogenic secondary organic aerosol (SOA) is formed as a result of the atmospheric oxidation of gas-phase biogenic volatile organic compounds (BVOCs). Here, we evaluate the ability of five European Earth System Models (CNRM-ESM2-1, EC-Earth3, IPSL-CM6, NorESM1.2, UKESM1) to capture the amount, and behaviour, of biogenic SOA in the atmosphere.The ESMs cover a range of complexity in terms of their representation of the sources and processing of biogenic SOA (i.e., from a fixed climatology of SOA amount to an interactive BVOC emission scheme followed by atmospheric processing).We combine station measurements of BVOC emission and atmospheric BVOC concentrations with remotely sensed isoprene emission estimates to evaluate the models’ representation of the sources of biogenic SOA. We use organic aerosol mass and particle number concentration measurements from a number of forested sites to evaluate the ability of the models to capture the seasonal cycle in the amount of biogenic SOA present, as well as its impact on the aerosol size distribution. Whilst the models appear to capture the seasonal cycle in organic aerosol well for a boreal forest site, the ESMs consistently over-predict the amount of organic aerosol present at a tropical forest location. Finally, we explore the ability of these models to capture the observed relationships between organic aerosol mass, or particle number, and temperature. We find that the ESMs equipped with vegetation models that generate BVOC emissions interactively are able to capture well the strength of the observed relationship between temperature and organic aerosol mass. This lends confidence to the ability of these ESMs to accurately represent changes in atmospheric composition driven by climate.

Mineral dust aerosols participate in the climate system and biogeochemistry processes due to its interactions with key components of Earth Systems: radiation, clouds, soil and chemical components. A central element to improve our understanding of mineral dust is through its modeling with Earth Systems Models where all these interactions are included. However, current simulations of dust variability exhibit important uncertainties and biases, which are model-dependent, whose cause is our imperfect knowledge about how to best represent the dust life cycle. For these reasons a continuous evaluation of the performance and properties of the different models compared against measurements is a crucial step to improve our knowledge of the dust cycle and its role in the climate system and biogeochemical cycles. Here we present an exhaustive evaluation of mineral dust aerosols in CRESCEND-ESMs over global, regional and local scales. We compare models against three networks of instruments for total dust deposition flux, yearly surface concentrations, and optical depths. Global and regional dust optical depths are compared with MODIS and MISR derived products. Specific analyses are done over the Sahel region where improved and compressive dust observational datasets are available. The results indicate that all the models capture the general properties of the global dust cycle, although the role of larger particles remains challenging. Differences are partially due to surface winds as nudged simulations improve the inter-model comparison and the performance in optical depth compared to MODIS. At the regional scale, there is an optical depth reasonable agreement over main source areas, but a joint inter-comparison including fluxes and concentration indicates larger differences. At the local scale, the uncertainties increase and current models are not able to reproduce together several observables at the same time.

Assessment of anthropogenic radiative forcing requires a robust understanding of the composition of the pre-industrial baseline atmosphere from which calculations are madeIt is often assumed that fire activity and the associated aerosol emissions were lower in the pre-industrial period than in the present day. However, some lines of evidence suggest that fire activity may have halved since the pre-industrial period. Here we compare the simulated ratio of pre-industrial (c.1750CE and c.1850CE) to present-day black carbon surface concentrations in five ESMs (CNRM-ESM2-1, EC-Earth3, IPSL-CM6, NorESM1.2, UKESM1), using historical fire emissions from the Sixth Coupled Model Intercomparison Project (CMIP6), to the ratio in Northern Hemisphere ice-core records. We find that when forced with CMIP6 fire emissions all ESMs overestimate the present-day to pre-industrial black carbon ratio. This is consistent with previous studies and suggests that the contribution of fire to the composition of the pre-industrial atmosphere may be too low. If the contrast between the pre-industrial and present-day atmospheres in these models is too great, they are likely to overestimate the strength of the anthropogenic aerosol radiative forcing. We extend our analysis to include additional ESMs providing historical simulations for CMIP6, as included in the IPCC’s Sixth Assessment Report.

Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the present day modelling of aerosol optical properties has been assessed using simulated data representative for the year 2010, from 14 global aerosol models participating in the Phase III Control experiment. The model versions are close or equal to those used for CMIP6 and AerChemMIP and inform also on bias in state of the art ESMs. Modelled column optical depths (total, fine and coarse mode AOD) and Angstrom Exponents (AE) were compared both with ground based observations from the Aerosol Robotic Network (AERONET, version 3) as well as space based observations from AATSR-SU instruments. In addition, the modelled AODs were compared with MODIS (Aqua and Terra) data and a satellite AOD data-set (MERGED-FMI) merged from 12 different individual AOD products. Furthermore, for the first time, the modelled near surface scattering (under dry conditions) and absorption coefficients were evaluated against measurements made at low relative humidity at surface in-situ GAW sites. Statistics are based mainly on normalised mean biases and Pearson correlation coefficients from colocated model and observation data in monthly resolution. Hence, the results are mostly representative for the regions covered by each of the observation networks. Model biases established against satellite data yield insights into remote continental areas and oceans, where ground-based networks lack site coverage. The satellite data themselves are evaluated against AERONET observations, to test our aggregation and re-gridding routines, suggesting relative AOD biases of −5 %, −6 %, +9 % and +18 % for AATSR-SU, MERGED-FMI, MODIS-aqua and MODIS-terra, respectively, with high correlations exceeding 0.8. Biases of fine and coarse AOD and AE in AATSR are found to be +2 %, −16 % and +14.7 % respectively, at AERONET sites, with correlations of the order of 0.8. The AeroCom MEDIAN and most of the participating models underestimate the optical properties investigated, relative to remote sensing observations. AERONET AOD is underestimated by 21 % ± 17 %. Against satellite data, the model AOD biases range from −38 % (MODIS-terra) to −17 % (MERGED-FMI). Correlation coefficients of model AODs with AERONET, MERGED-FMI and AATSR-SU are high (0.8–0.9) and slightly lower against the two MODIS data-sets (0.6–0.8). Investigation of fine and coarse AODs from the MEDIAN model reveals biases of −10% ± 20 % and −41 % ± 29 % against AERONET and −13 % and −24 % against AATSR-SU, respectively. The differences in bias against AERONET and AATSR-SU are in agreement with the established satellite bias against AERONET. These results indicate that most of the AOD bias is due to missing coarse AOD in the regions covered by these observations. Underestimates are also found when comparing the models against the surface GAW observations, showing AeroCom MEDIAN mean bias and inter-model variation of −44 % ± 22 % and −32 % ± 34 % for scattering and absorption coefficients, respectively. Dry scattering shows higher underestimation than AOD at ambient relative humidity and is in agreement with recent findings that suggest that models tend to overestimate scattering enhancement due to hygroscopic growth. Broadly consistent negative bias in AOD and scattering suggest a general underestimate in aerosol effects in current global aerosol models. The large diversity in the surface absorption results suggests differences in the model treatment of light absorption by black carbon (BC), dust (DU) and to a minor degree, organic aerosol (OA). Considerable diversity is found among the models in the simulated near surface absorption coefficients, particularly in regions associated with dust (e.g. Sahara, Tibet), biomass burning (e.g. Amazonia, Central Australia) and biogenic emissions (e.g. Amazonia). Regions associated with high anthropogenic BC emissions such as China and India exhibit comparatively good agreement for all models. Evaluation of modelled column AEs shows an underestimation of 9 % ± 24 % against AERONET and −21 % against AATSR-SU. This suggests that overall, models tend to overestimate particle size, with implications for lifetime and radiative transfer calculations. An investigation of modelled emissions, burdens and lifetimes, mass-specific-extinction coefficients (MECs) and optical depths (ODs) for each species and model reveals considerable diversity in most of these parameters. These are discussed in detail for each model individually. Inter-model spread of aerosol species lifetime appears to be similar to that of mass extinction coefficients, suggesting that AOD uncertainties are still associated to a broad spectrum of parameterised aerosol processes.

Feedbacks play a fundamental role in determining the magnitude of the response of the climate system to external forcing, such as from anthropogenic emissions. The latest generation of Earth system models include aerosol and chemistry components that interact with each other and with the biosphere. These interactions introduce a complex web of feedbacks which it is important to understand and quantify. This paper addresses the multiple pathways for aerosol and chemical feedbacks in Earth system models. This is achieved by extending previous formalisms which include CO2 concentrations as a state variable to a formalism which in principle includes the concentrations of all climate-active atmospheric constituents. This framework is demonstrated by applying it to the Earth system models participating in CMIP6 with a focus on the non-CO2 reactive gases and aerosols (methane, ozone, sulphate aerosol, organic aerosol and dust). We find that the overall climate feedback through chemistry and aerosols is negative in the CMIP6 Earth system models due to increased negative forcing from aerosols with warmer temperatures. Through diagnosing changes in methane emissions and lifetime we find that if Earth system models were to allow methane to vary interactively, methane positive feedbacks (principally wetland methane emissions and biogenic VOC emissions) would offset much of the aerosol feedbacks.

The Geostationary Emission Explorer for Europe (G3E) is a concept for a geostationary satellite sounder that aims to constrain the sources and sinks of greenhouse gases carbon dioxide (CO2) and methane (CH4) for continental-scale regions. Its primary focus is on central Europe. G3E carries a spectrometer system that collects sunlight backscattered from the Earth's surface and atmosphere in the near-infrared (NIR) and shortwave-infrared (SWIR) spectral range. Solar absorption spectra allow for spatiotemporally dense observations of the column-average concentrations of carbon dioxide (XCO2), methane (XCH4), and carbon monoxide (XCO). The mission concept in particular facilitates sampling of the diurnal variation with several measurements per day during summer. Here, we present the mission concept and carry out an initial performance assessment of the retrieval capabilities. The radiometric performance of the 4 grating spectrometers is tuned to reconcile small ground-pixel sizes (~2 km × 3 km at 50° latitude) with short single-shot exposures (~2.9 s) that allow for sampling continental regions such as central Europe within 2 h while providing a sufficient signal-to-noise ratio. The noise errors to be expected for XCO2, XCH4, and XCO are assessed through retrieval simulations for a European trial ensemble. Generally, single-shot precision for the targeted XCO2 and XCH4 is better than 0.5 % with some exception for scenes with low infrared surface albedo observed under low sun conditions in winter. For XCO, precision is generally better than 10 %. Performance for aerosol and cirrus loaded atmospheres is assessed by mimicking G3E's slant view on Europe for an ensemble of atmospheric scattering properties used previously for evaluating nadir-viewing low-Earth-orbit (LEO) satellites. While retrieval concepts developed for LEO configurations generally succeed in mitigating aerosol- and cirrus-induced retrieval errors for G3E's setup, residual errors are somewhat greater in geostationary orbit (GEO) than in LEO. G3E's deployment in the vicinity of the Meteosat Third Generation (MTG) satellites has the potential to make synergistic use of MTG's sounding capabilities e.g. with respect to characterization of aerosol and cloud properties or with respect to enhancing carbon monoxide retrievals by combining G3E's solar and MTG's thermal infrared spectra.

Sentinel-5 (S5) and its precursor (S5P) are future European satellite missions aiming at global monitoring of methane (CH4) column-average dry air mole fractions (XCH4). The spectrometers to be deployed onboard the satellites record spectra of sunlight backscattered from the Earth's surface and atmosphere. In particular, they exploit CH4 absorption in the shortwave infrared spectral range around 1.65 μm (S5 only) and 2.35 μm (both S5 and S5P) wavelength. Given an accuracy goal of better than 2 % for XCH4 to be delivered on regional scales, assessment and reduction of potential sources of systematic error such as spectroscopic uncertainties is crucial. Here, we investigate how spectroscopic errors propagate into retrieval errors on the global scale. To this end, absorption spectra of a ground-based Fourier transform spectrometer (FTS) operating at very high spectral resolution serve as estimate for the quality of the spectroscopic parameters. Feeding the FTS fitting residuals as a perturbation into a global ensemble of simulated S5- and S5P-like spectra at relatively low spectral resolution, XCH4 retrieval errors exceed 0.6 % in large parts of the world and show systematic correlations on regional scales, calling for improved spectroscopic parameters.

The main challenges of measuring precipitation are related to the spatio-temporal variability of the drop-size distribution, to the uncertainties that condition the modeling of that distribution, and to the instrumental errors present in the in situ estimations. This PhD dissertation proposes advances in all these questions. The relevance of the spatial variability of the drop-size distribution for remote sensing measurements and hydro-meteorology field studies is asserted by analyzing the measurement of a set of disdrometers deployed on a network of 5 squared kilometers. This study comprises the spatial variability of integral rainfall parameters, the ZR relationships, and the variations within the one moment scaling method. The modeling of the drop-size distribution is analyzed by applying the MaxEnt method and comparing it with the methods of moments and the maximum likelihood. The instrumental errors are analyzed with a compressive comparison of sampling and binning uncertainties that affect actual devices. These analysis are further extended in several appendices where an error analysis is developed and new studies are proposed. The relevance of the pre-processing of disdrometric measurements is also assessed. The data-sets evaluated comprise experimental measurements of the GPM (NASA-JAXA) ground validation satellite mission and synthetic distributions generated computationally., PhD Thesis Dissertation. Main results are in English (Chapters 8, 9, 10; appendix A, C). The introduction, the description of the empirical information and pre-processing are in Spanish. A version with the figures at full-resolution may be download at: http://blog.ramiro-checa.info/pages/Research

As emphasized by the Intergovernmental Panel for Climate Change (IPCC), aerosols contribute the largest uncertainty to global radiative forcing budget estimates. The uncertainty stems largely from the lack of information related to global aerosol distributions, composition, and aging effects in the atmosphere, all of which affect aerosol radiative properties.Of the two major categories of aerosols, natural and anthropogenic, natural aerosols remain the largest source of the uncertainty. This limits our capacity to measure and attribute total climate forcings. Without a firm understanding of total climate forcing, our ability to predict its evolution over time diminishes and limits the development of adaptation strategies for future climate change.Aerosolized mineral dust is the largest single component of the global aerosol mass budget, making up nearly half of annual particle emissions to the atmosphere. Mineral dust aerosols influence the global climate through both direct interactions with radiation (scattering and absorption in the visible and IR regions) as well as indirect interactions with radiation (by serving as cloud condensation nuclei (CCN) or ice nuclei (IN)). One potentially important aspect of dust aerosols is that they are able to uptake and heterogeneously react with gases. Henceforth, mineral dust may also play a significant but mostly unknown role in secondary organic aerosol (SOA) formation in the atmosphere.While the combination of the complex reaction pathways and processing mechanisms inherent to the dust/organic system is hampering our understanding of dust and organic aerosols on global climate, and despite a great number of progresses on climate-relevant properties of mineral dust and SOA in these past ten years, studies of the heterogeneous chemistry occurring between dust and organic species are sparse.The CLImate relevant processing of Mineral Dust by volatile Organic compounds (CLIMDO) project tackles this under-explored science question by proposing the first comprehensive process-driven project addressing the reactivity of complex and realistic mineral dust/organic systems to better understand how dust and VOCs influence the global climate system.CLIMDO will investigate the heterogeneous interaction of mineral dust with two of the most common organic SOA precursors: glyoxal and methylglyoxal from ubiquitous anthropogenic and biogenic sources, thought combination of innovative laboratory experiments in a well-controlled and characterized environment (the atmospheric simulation chamber CESAM) and advanced flow reactors and optical cells), the development of novel modelling schemes of both the reaction mechanisms and the resulting optical properties of mineral dust, and new simulations of the global direct radiative effect and SOA distribution using the LMDzOR-INCA.This presentation describes the strategy and workplan of the CLIMDO project, including dissemination of results and open data, to inform the science community and foster and cluster new collaborations.