2018, Mamali, Dimitra, Marinou, Eleni, Sciare, Jean, Pikridas, Michael, Kokkalis, Panagiotis, Kottas, Michael, Binietoglou, Ioannis, Tsekeri, Alexandra, Keleshis, Christos, Engelmann, Ronny, Baars, Holger, Ansmann, Albert, Amiridis, Vassilis, Russchenberg, Herman, Biskos, George

In situ measurements using unmanned aerial vehicles (UAVs) and remote sensing observations can independently provide dense vertically resolved measurements of atmospheric aerosols, information which is strongly required in climate models. In both cases, inverting the recorded signals to useful information requires assumptions and constraints, and this can make the comparison of the results difficult. Here we compare, for the first time, vertical profiles of the aerosol mass concentration derived from light detection and ranging (lidar) observations and in situ measurements using an optical particle counter on board a UAV during moderate and weak Saharan dust episodes. Agreement between the two measurement methods was within experimental uncertainty for the coarse mode (i.e. particles having radii > 0.5 μm), where the properties of dust particles can be assumed with good accuracy. This result proves that the two techniques can be used interchangeably for determining the vertical profiles of aerosol concentrations, bringing them a step closer towards their systematic exploitation in climate models.

2022, Leinonen, Ville, Kokkola, Harri, Yli-Juuti, Taina, Mielonen, Tero, Kühn, Thomas, Nieminen, Tuomo, Heikkinen, Simo, Miinalainen, Tuuli, Bergman, Tommi, Carslaw, Ken, Decesari, Stefano, Fiebig, Markus, Hussein, Tareq, Kivekäs, Niku, Krejci, Radovan, Kulmala, Markku, Leskinen, Ari, Massling, Andreas, Mihalopoulos, Nikos, Mulcahy, Jane P., Noe, Steffen M., van Noije, Twan, O'Connor, Fiona M., O'Dowd, Colin, Olivie, Dirk, Pernov, Jakob B., Petäjä, Tuukka, Seland, Øyvind, Schulz, Michael, Scott, Catherine E., Skov, Henrik, Swietlicki, Erik, Tuch, Thomas, Wiedensohler, Alfred, Virtanen, Annele, Mikkonen, Santtu

Despite a large number of studies, out of all drivers of radiative forcing, the effect of aerosols has the largest uncertainty in global climate model radiative forcing estimates. There have been studies of aerosol optical properties in climate models, but the effects of particle number size distribution need a more thorough inspection. We investigated the trends and seasonality of particle number concentrations in nucleation, Aitken, and accumulation modes at 21 measurement sites in Europe and the Arctic. For 13 of those sites, with longer measurement time series, we compared the field observations with the results from five climate models, namely EC-Earth3, ECHAM-M7, ECHAM-SALSA, NorESM1.2, and UKESM1. This is the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five earth system models (ESMs). We found that the trends of particle number concentrations were mostly consistent and decreasing in both measurements and models. However, for many sites, climate models showed weaker decreasing trends than the measurements. Seasonal variability in measured number concentrations, quantified by the ratio between maximum and minimum monthly number concentration, was typically stronger at northern measurement sites compared to other locations. Models had large differences in their seasonal representation, and they can be roughly divided into two categories: for EC-Earth and NorESM, the seasonal cycle was relatively similar for all sites, and for other models the pattern of seasonality varied between northern and southern sites. In addition, the variability in concentrations across sites varied between models, some having relatively similar concentrations for all sites, whereas others showed clear differences in concentrations between remote and urban sites. To conclude, although all of the model simulations had identical input data to describe anthropogenic mass emissions, trends in differently sized particles vary among the models due to assumptions in emission sizes and differences in how models treat size-dependent aerosol processes. The inter-model variability was largest in the accumulation mode, i.e. sizes which have implications for aerosol-cloud interactions. Our analysis also indicates that between models there is a large variation in efficiency of long-range transportation of aerosols to remote locations. The differences in model results are most likely due to the more complex effect of different processes instead of one specific feature (e.g. the representation of aerosol or emission size distributions). Hence, a more detailed characterization of microphysical processes and deposition processes affecting the long-range transport is needed to understand the model variability.

2019, Tegen, I., Neubauer, D., Ferrachat, S., Drian, C.S.-L., Bey, I., Schutgens, N., Stier, P., Watson-Parris, D., Stanelle, T., Schmidt, H., Rast, S., Kokkola, H., Schultz, M., Schroeder, S., Daskalakis, N., Barthel, S., Heinold, B., Lohmann, U.

We introduce and evaluate aerosol simulations with the global aerosol-climate model ECHAM6.3-HAM2.3, which is the aerosol component of the fully coupled aerosol-chemistry-climate model ECHAM-HAMMOZ. Both the host atmospheric climate model ECHAM6.3 and the aerosol model HAM2.3 were updated from previous versions. The updated version of the HAM aerosol model contains improved parameterizations of aerosol processes such as cloud activation, as well as updated emission fields for anthropogenic aerosol species and modifications in the online computation of sea salt and mineral dust aerosol emissions. Aerosol results from nudged and free-running simulations for the 10-year period 2003 to 2012 are compared to various measurements of aerosol properties. While there are regional deviations between the model and observations, the model performs well overall in terms of aerosol optical thickness, but may underestimate coarse-mode aerosol concentrations to some extent so that the modeled particles are smaller than indicated by the observations. Sulfate aerosol measurements in the US and Europe are reproduced well by the model, while carbonaceous aerosol species are biased low. Both mineral dust and sea salt aerosol concentrations are improved compared to previous versions of ECHAM-HAM. The evaluation of the simulated aerosol distributions serves as a basis for the suitability of the model for simulating aerosol-climate interactions in a changing climate.

2017, Jungclaus, J.H., Bard, E., Baroni, M., Braconnot, P., Cao, J., Chini, L.P., Egorova, T., Evans, M., Fidel González-Rouco, J., Goosse, H., Hurtt, G.C., Joos, F., Kaplan, J.O., Khodri, M., Klein Goldewijk, K., Krivova, N., Legrande, A.N., Lorenz, S.J., Luterbacher, J., Man, W., Maycock, A.C., Meinshausen, M., Moberg, A., Muscheler, R., Nehrbass-Ahles, C., Otto-Bliesner, B.I., Phipps, S.J., Pongratz, J., Rozanov, E., Schmidt, G.A., Schmidt, H., Schmutz, W., Schurer, A., Shapiro, A.I., Sigl, M., Smerdon, J.E., Solanki, S.K., Timmreck, C., Toohey, M., Usoskin, I.G., Wagner, S., Wu, C.-J., Leng Yeo, K., Zanchettin, D., Zhang, Q., Zorita, E.

The pre-industrial millennium is among the periods selected by the Paleoclimate Model Intercomparison Project (PMIP) for experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and the fourth phase of the PMIP (PMIP4). The past1000 transient simulations serve to investigate the response to (mainly) natural forcing under background conditions not too different from today, and to discriminate between forced and internally generated variability on interannual to centennial timescales. This paper describes the motivation and the experimental set-ups for the PMIP4-CMIP6 past1000 simulations, and discusses the forcing agents orbital, solar, volcanic, and land use/land cover changes, and variations in greenhouse gas concentrations. The past1000 simulations covering the pre-industrial millennium from 850 Common Era (CE) to 1849 CE have to be complemented by historical simulations (1850 to 2014 CE) following the CMIP6 protocol. The external forcings for the past1000 experiments have been adapted to provide a seamless transition across these time periods. Protocols for the past1000 simulations have been divided into three tiers. A default forcing data set has been defined for the Tier 1 (the CMIP6 past1000) experiment. However, the PMIP community has maintained the flexibility to conduct coordinated sensitivity experiments to explore uncertainty in forcing reconstructions as well as parameter uncertainty in dedicated Tier 2 simulations. Additional experiments (Tier 3) are defined to foster collaborative model experiments focusing on the early instrumental period and to extend the temporal range and the scope of the simulations. This paper outlines current and future research foci and common analyses for collaborative work between the PMIP and the observational communities (reconstructions, instrumental data).

2014, Pietikäinen, J.-P., Mikkonen, S., Hamed, A., Hienola, A.I., Birmili, W., Kulmala, M., Laaksonen, A.

This work describes improvements in the regional aerosol–climate model REMO-HAM in order to simulate more realistically the process of atmospheric new particle formation (NPF). A new scheme was implemented to simulate OH radical concentrations using a proxy approach based on observations and also accounting for the effects of clouds upon OH concentrations. Second, the nucleation rate calculation was modified to directly simulate the formation rates of 3 nm particles, which removes some unnecessary steps in the formation rate calculations used earlier in the model. Using the updated model version, NPF over Europe was simulated for the periods 2003–2004 and 2008–2009. The statistics of the simulated particle formation events were subsequently compared to observations from 13 ground-based measurement sites. The new model shows improved agreement with the observed NPF rates compared to former versions and can simulate the event statistics realistically for most parts of Europe.

2014, Tjernström, M., Leck, C., Birch, C.E., Bottenheim, J.W., Brooks, B.J., Brooks, I.M., Bäcklin, L., Chang, R.Y.-W., de Leeuw, G., Di Liberto, L., de la Rosa, S., Granath, E., Graus, M., Hansel, A., Heintzenberg, J., Held, A., Hind, A., Johnston, P., Knulst, J., Martin, M., Matrai, P.A., Mauritsen, T., Müller, M., Norris, S.J., Orellana, M.V., Orsini, D.A., Paatero, J., Persson, P.O.G., Gao, Q., Rauschenberg, C., Ristovski, Z., Sedlar, J., Shupe, M.D., Sierau, B., Sirevaag, A., Sjogren, S., Stetzer, O., Swietlicki, E., Szczodrak, M., Vaattovaara, P., Wahlberg, N., Westberg, M., Wheeler, C.R.

The climate in the Arctic is changing faster than anywhere else on earth. Poorly understood feedback processes relating to Arctic clouds and aerosol–cloud interactions contribute to a poor understanding of the present changes in the Arctic climate system, and also to a large spread in projections of future climate in the Arctic. The problem is exacerbated by the paucity of research-quality observations in the central Arctic. Improved formulations in climate models require such observations, which can only come from measurements in situ in this difficult-to-reach region with logistically demanding environmental conditions. The Arctic Summer Cloud Ocean Study (ASCOS) was the most extensive central Arctic Ocean expedition with an atmospheric focus during the International Polar Year (IPY) 2007–2008. ASCOS focused on the study of the formation and life cycle of low-level Arctic clouds. ASCOS departed from Longyearbyen on Svalbard on 2 August and returned on 9 September 2008. In transit into and out of the pack ice, four short research stations were undertaken in the Fram Strait: two in open water and two in the marginal ice zone. After traversing the pack ice northward, an ice camp was set up on 12 August at 87°21' N, 01°29' W and remained in operation through 1 September, drifting with the ice. During this time, extensive measurements were taken of atmospheric gas and particle chemistry and physics, mesoscale and boundary-layer meteorology, marine biology and chemistry, and upper ocean physics. ASCOS provides a unique interdisciplinary data set for development and testing of new hypotheses on cloud processes, their interactions with the sea ice and ocean and associated physical, chemical, and biological processes and interactions. For example, the first-ever quantitative observation of bubbles in Arctic leads, combined with the unique discovery of marine organic material, polymer gels with an origin in the ocean, inside cloud droplets suggests the possibility of primary marine organically derived cloud condensation nuclei in Arctic stratocumulus clouds. Direct observations of surface fluxes of aerosols could, however, not explain observed variability in aerosol concentrations, and the balance between local and remote aerosols sources remains open. Lack of cloud condensation nuclei (CCN) was at times a controlling factor in low-level cloud formation, and hence for the impact of clouds on the surface energy budget. ASCOS provided detailed measurements of the surface energy balance from late summer melt into the initial autumn freeze-up, and documented the effects of clouds and storms on the surface energy balance during this transition. In addition to such process-level studies, the unique, independent ASCOS data set can and is being used for validation of satellite retrievals, operational models, and reanalysis data sets.

2017, Meinshausen, Malte, Vogel, Elisabeth, Nauels, Alexander, Lorbacher, Katja, Meinshausen, Nicolai, Etheridge, David M., Fraser, Paul J., Montzka, Stephen A., Rayner, Peter J., Trudinger, Cathy M., Krummel, Paul B., Beyerle, Urs, Canadell, Josep G., Daniel, John S., Enting, Ian G., Law, Rachel M. Law, Lunder, Chris R., O'Doherty, Simon, Prinn, Ron G., Reimann, Stefan, Rubino, Mauro, Velders, Guus J.M., Vollmer, Martin K., Wang, Ray H.J., Weiss, Ray

Atmospheric greenhouse gas (GHG) concentrations are at unprecedented, record-high levels compared to the last 800000 years. Those elevated GHG concentrations warm the planet and – partially offset by net cooling effects by aerosols – are largely responsible for the observed warming over the past 150 years. An accurate representation of GHG concentrations is hence important to understand and model recent climate change. So far, community efforts to create composite datasets of GHG concentrations with seasonal and latitudinal information have focused on marine boundary layer conditions and recent trends since the 1980s. Here, we provide consolidated datasets of historical atmospheric concentrations (mole fractions) of 43 GHGs to be used in the Climate Model Intercomparison Project – Phase 6 (CMIP6) experiments. The presented datasets are based on AGAGE and NOAA networks, firn and ice core data, and archived air data, and a large set of published studies. In contrast to previous intercomparisons, the new datasets are latitudinally resolved and include seasonality. We focus on the period 1850–2014 for historical CMIP6 runs, but data are also provided for the last 2000 years. We provide consolidated datasets in various spatiotemporal resolutions for carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), as well as 40 other GHGs, namely 17 ozone-depleting substances, 11 hydrofluorocarbons (HFCs), 9 perfluorocarbons (PFCs), sulfur hexafluoride (SF6), nitrogen trifluoride (NF3) and sulfuryl fluoride (SO2F2). In addition, we provide three equivalence species that aggregate concentrations of GHGs other than CO2, CH4 and N2O, weighted by their radiative forcing efficiencies. For the year 1850, which is used for pre-industrial control runs, we estimate annual global-mean surface concentrations of CO2 at 284.3ppm, CH4 at 808.2ppb and N2O at 273.0ppb. The data are available at https://esgf-node.llnl.gov/search/input4mips/ and http://www.climatecollege.unimelb.edu.au/cmip6. While the minimum CMIP6 recommendation is to use the global- and annual-mean time series, modelling groups can also choose our monthly and latitudinally resolved concentrations, which imply a stronger radiative forcing in the Northern Hemisphere winter (due to the latitudinal gradient and seasonality).

2011, Rose, D., Gunthe, S.S., Su, H., Garland, R.M., Yang, H., Berghof, M., Cheng, Y.F., Wehner, B., Achtert, P., Nowak, A., Wiedensohler, A., Takegawa, N., Kondo, Y., Hu, M., Zhang, Y., Andreae, M.O., Pöschl, U.

Size-resolved chemical composition, mixing state, and cloud condensation nucleus (CCN) activity of aerosol particles in polluted mega-city air and biomass burning smoke were measured during the PRIDE-PRD2006 campaign near Guangzhou, China, using an aerosol mass spectrometer (AMS), a volatility tandem differential mobility analyzer (VTDMA), and a continuous-flow CCN counter (DMT-CCNC). The size-dependence and temporal variations of the effective average hygroscopicity parameter for CCN-active particles (κa) could be parameterized as a function of organic and inorganic mass fractions (forg, finorg) determined by the AMS: κa,p=κorg·forg + κinorg·finorg. The characteristic κ values of organic and inorganic components were similar to those observed in other continental regions of the world: κorg≈0.1 and κinorg≈0.6. The campaign average κa values increased with particle size from ~0.25 at ~50 nm to ~0.4 at ~200 nm, while forg decreased with particle size. At ~50 nm, forg was on average 60% and increased to almost 100% during a biomass burning event. The VTDMA results and complementary aerosol optical data suggest that the large fractions of CCN-inactive particles observed at low supersaturations (up to 60% at S≤0.27%) were externally mixed weakly CCN-active soot particles with low volatility (diameter reduction <5% at 300 °C) and effective hygroscopicity parameters around κLV≈0.01. A proxy for the effective average hygroscopicity of the total ensemble of CCN-active particles including weakly CCN-active particles (κt) could be parameterized as a function of κa,p and the number fraction of low volatility particles determined by VTDMA (φLV): κt,p=κa,p−φLV·(κa,p−κLV). Based on κ values derived from AMS and VTDMA data, the observed CCN number concentrations (NCCN,S≈102–104 cm−3 at S = 0.068–0.47%) could be efficiently predicted from the measured particle number size distribution. The mean relative deviations between observed and predicted CCN concentrations were ~10% when using κt,p, and they increased to ~20% when using only κa,p. The mean relative deviations were not higher (~20%) when using an approximate continental average value of κ≈0.3, although the constant κ value cannot account for the observed temporal variations in particle composition and mixing state (diurnal cycles and biomass burning events). Overall, the results confirm that on a global and climate modeling scale an average value of κ≈0.3 can be used for approximate predictions of CCN number concentrations in continental boundary layer air when aerosol size distribution data are available without information about chemical composition. Bulk or size-resolved data on aerosol chemical composition enable improved CCN predictions resolving regional and temporal variations, but the composition data need to be highly accurate and complemented by information about particle mixing state to achieve high precision (relative deviations <20%).

2020, Beer, Christof G., Hendricks, Johannes, Righi, Mattia, Heinold, Bernd, Tegen, Ina, Groß, Silke, Sauer, Daniel, Walser, Adrian, Weinzierl, Bernadett

It was hypothesized that using mineral dust emission climatologies in global chemistry climate models (GCCMs), i.e. prescribed monthly-mean dust emissions representative of a specific year, may lead to misrepresentations of strong dust burst events. This could result in a negative bias of model dust concentrations compared to observations for these episodes. Here, we apply the aerosol microphysics submodel MADE3 (Modal Aerosol Dynamics model for Europe, adapted for global applications, third generation) as part of the ECHAM/MESSy Atmospheric Chemistry (EMAC) general circulation model. We employ two different representations of mineral dust emissions for our model simulations: (i) a prescribed monthly-mean climatology of dust emissions representative of the year 2000 and (ii) an online dust parametrization which calculates wind-driven mineral dust emissions at every model time step. We evaluate model results for these two dust representations by comparison with observations of aerosol optical depth from ground-based station data. The model results show a better agreement with the observations for strong dust burst events when using the online dust representation compared to the prescribed dust emissions setup. Furthermore, we analyse the effect of increasing the vertical and horizontal model resolution on the mineral dust properties in our model. We compare results from simulations with T42L31 and T63L31 model resolution (2.8∘×2.8∘ and 1.9∘×1.9∘ in latitude and longitude, respectively; 31 vertical levels) with the reference setup (T42L19). The different model versions are evaluated against airborne in situ measurements performed during the SALTRACE mineral dust campaign (Saharan Aerosol Long-range Transport and Aerosol-Cloud Interaction Experiment, June–July 2013), i.e. observations of dust transported from the Sahara to the Caribbean. Results show that an increased horizontal and vertical model resolution is able to better represent the spatial distribution of airborne mineral dust, especially in the upper troposphere (above 400 hPa). Additionally, we analyse the effect of varying assumptions for the size distribution of emitted dust but find only a weak sensitivity concerning these changes. The results of this study will help to identify the model setup best suited for future studies and to further improve the representation of mineral dust particles in EMAC-MADE3.

2011, Meinshausen, M., Smith, S.J., Calvin, K., Daniel, J.S., Kainuma, M.L.T., Lamarque, J., Matsumoto, K., Montzka, S.A., Raper, S.C.B., Riahi, K., Thomson, A., Velders, G.J.M., van Vuuren, D.P.P.

We present the greenhouse gas concentrations for the Representative Concentration Pathways (RCPs) and their extensions beyond 2100, the Extended Concentration Pathways (ECPs). These projections include all major anthropogenic greenhouse gases and are a result of a multi-year effort to produce new scenarios for climate change research. We combine a suite of atmospheric concentration observations and emissions estimates for greenhouse gases (GHGs) through the historical period (1750-2005) with harmonized emissions projected by four different Integrated Assessment Models for 2005-2100. As concentrations are somewhat dependent on the future climate itself (due to climate feedbacks in the carbon and other gas cycles), we emulate median response characteristics of models assessed in the IPCC Fourth Assessment Report using the reduced-complexity carbon cycle climate model MAGICC6. Projected 'best-estimate' global-mean surface temperature increases (using inter alia a climate sensitivity of 3°C) range from 1.5°C by 2100 for the lowest of the four RCPs, called both RCP3-PD and RCP2. 6, to 4.5°C for the highest one, RCP8. 5, relative to pre-industrial levels. Beyond 2100, we present the ECPs that are simple extensions of the RCPs, based on the assumption of either smoothly stabilizing concentrations or constant emissions: For example, the lower RCP2. 6 pathway represents a strong mitigation scenario and is extended by assuming constant emissions after 2100 (including net negative CO2 emissions), leading to CO2 concentrations returning to 360 ppm by 2300. We also present the GHG concentrations for one supplementary extension, which illustrates the stringent emissions implications of attempting to go back to ECP4. 5 concentration levels by 2250 after emissions during the 21st century followed the higher RCP6 scenario. Corresponding radiative forcing values are presented for the RCP and ECPs.