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).

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, 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).

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.