ALBERT

Description: In models, nucleation mode (1 nm〈Dp 〈10 nm) particle microphysics can be represented explicitly with aerosol microphysical processes or can be parameterized to obtain the growth and survival of nuclei to the model's lower size boundary. This study investigates how the representation of nucleation mode microphysics impacts aerosol number predictions in the TwO-Moment Aerosol Sectional (TOMAS) aerosol microphysics model running with the GISS GCM II-prime by varying its lowest diameter boundary: 1 nm, 3 nm, and 10 nm. The model with the 1 nm boundary simulates the nucleation mode particles with fully resolved microphysical processes, while the model with the 10 nm and 3 nm boundaries uses a nucleation mode dynamics parameterization to account for the growth of nucleated particles to 10 nm and 3 nm, respectively.We also investigate the impact of the time step for aerosol microphysical processes (a 10 min versus a 1 h time step) to aerosol number predictions in the TOMAS models with explicit dynamics for the nucleation mode particles (i.e., 3 nm and 1 nm boundary). The model with the explicit microphysics (i.e., 1 nm boundary) with the 10 min time step is used as a numerical benchmark simulation to estimate biases caused by varying the lower size cutoff and the time step. Different representations of the nucleation mode have a significant effect on the formation rate of particles larger than 10 nm from nucleated particles (J10) and the burdens and lifetimes of ultrafinemode (10 nmDp 70 nm) particles but have less impact on the burdens and lifetimes of CCN-sized particles. The models using parameterized microphysics (i.e., 10 nm and 3 nm boundaries) result in higher J10 and shorter coagulation lifetimes of ultrafine-mode particles than the model with explicit dynamics (i.e., 1 nm boundary). The spatial distributions of CN10 (Dp 10 nm) and CCN(0.2 %) (i.e., CCN concentrations at 0.2%supersaturation) are moderately affected, especially CN10 predictions above 700 hPa where nucleation contributes most strongly to CN10 concentrations. The lowermost-layer CN10 is substantially improved with the 3 nm boundary (compared to 10 nm) in most areas. The overprediction in CN10 with the 3 nm and 10 nm boundaries can be explained by the overprediction of J10 or J3 with the parameterized microphysics, possibly due to the instantaneous growth rate assumption in the survival and growth parameterization. The errors in CN10 predictions are sensitive to the choice of the lower size boundary but not to the choice of the time step applied to the microphysical processes. The spatial distribution of CCN(0.2 %) with the 3 nm boundary is almost identical to that with the 1 nm boundary, but that with the 10 nm boundary can differ more than 10-40% in some areas. We found that the deviation in the 10 nm simulations is partly due to the longer time step (i.e., 1 h time step used in the 10 nm simulations compared to 10 min time step used in the benchmark simulations), but, even with the same time step, the 10 nm cutoff showed noticeably higher errors than the 3 nm cutoff. In conclusion, we generally recommend using a lower diameter boundary of 3 nm for studies focused on aerosol indirect effects but down to 1 nm boundary for studies focused on CN10 predictions or nucleation.

Description: Ozone (O3) from 17 atmospheric chemistry models taking part in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) has been used to calculate tropospheric ozone radiative forcings (RFs). All models applied a common set of anthropogenic emissions, which are better constrained for the present-day than the past. Future anthropogenic emissions follow the four Representative Concentration Pathway (RCP) scenarios, which define a relatively narrow range of possible air pollution emissions. We calculate a value for the pre-industrial (1750) to present-day (2010) tropospheric ozone RF of 410 mW m2. The model range of pre-industrial to present-day changes in O3 produces a spread (+/-1 standard deviation) in RFs of +/-17%. Three different radiation schemes were used - we find differences in RFs between schemes (for the same ozone fields) of +/-10 percent. Applying two different tropopause definitions gives differences in RFs of +/-3 percent. Given additional (unquantified) uncertainties associated with emissions, climate-chemistry interactions and land-use change, we estimate an overall uncertainty of +/-30 percent for the tropospheric ozone RF. Experiments carried out by a subset of six models attribute tropospheric ozone RF to increased emissions of methane (44+/-12 percent), nitrogen oxides (31 +/- 9 percent), carbon monoxide (15 +/- 3 percent) and non-methane volatile organic compounds (9 +/- 2 percent); earlier studies attributed more of the tropospheric ozone RF to methane and less to nitrogen oxides. Normalising RFs to changes in tropospheric column ozone, we find a global mean normalised RF of 42 mW m(2) DU(1), a value similar to previous work. Using normalised RFs and future tropospheric column ozone projections we calculate future tropospheric ozone RFs (mW m(2); relative to 1750) for the four future scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) of 350, 420, 370 and 460 (in 2030), and 200, 300, 280 and 600 (in 2100). Models show some coherent responses of ozone to climate change: decreases in the tropical lower troposphere, associated with increases in water vapour; and increases in the sub-tropical to mid-latitude upper troposphere, associated with increases in lightning and stratosphere-to-troposphere transport. Climate change has relatively small impacts on global mean tropospheric ozone RF.

Description: As part of the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP), we evaluate the historical black carbon (BC) aerosols simulated by 8 ACCMIP models against observations including 12 ice core records, long-term surface mass concentrations, and recent Arctic BC snowpack measurements. We also estimate BC albedo forcing by performing additional simulations using offline models with prescribed meteorology from 1996-2000. We evaluate the vertical profile of BC snow concentrations from these offline simulations using the recent BC snowpack measurements. Despite using the same BC emissions, the global BC burden differs by approximately a factor of 3 among models due to differences in aerosol removal parameterizations and simulated meteorology: 34 Gg to 103 Gg in 1850 and 82 Gg to 315 Gg in 2000. However, the global BC burden from preindustrial to present-day increases by 2.5-3 times with little variation among models, roughly matching the 2.5-fold increase in total BC emissions during the same period.We find a large divergence among models at both Northern Hemisphere (NH) and Southern Hemisphere (SH) high latitude regions for BC burden and at SH high latitude regions for deposition fluxes. The ACCMIP simulations match the observed BC surface mass concentrations well in Europe and North America except at Ispra. However, the models fail to predict the Arctic BC seasonality due to severe underestimations during winter and spring. The simulated vertically resolved BC snow concentrations are, on average, within a factor of 2-3 of the BC snowpack measurements except for Greenland and the Arctic Ocean. For the ice core evaluation, models tend to adequately capture both the observed temporal trends and the magnitudes at Greenland sites. However, models fail to predict the decreasing trend of BC depositions/ice core concentrations from the 1950s to the 1970s in most Tibetan Plateau ice cores. The distinct temporal trend at the Tibetan Plateau ice cores indicates a strong influence from Western Europe, but the modeled BC increases in that period are consistent with the emission changes in Eastern Europe, the Middle East, South and East Asia. At the Alps site, the simulated BC suggests a strong influence from Europe, which agrees with the Alps ice core observations. At Zuoqiupu on the Tibetan Plateau, models successfully simulate the higher BC concentrations observed during the non-monsoon season compared to the monsoon season but overpredict BC in both seasons. Despite a large divergence in BC deposition at two Antarctic ice core sites, some models with a BC lifetime of less than 7 days are able to capture the observed concentrations. In 2000 relative to 1850, globally and annually averaged BC surface albedo forcing from the offline simulations ranges from 0.014 to 0.019Wm2 among the ACCMIP models. Comparing offline and online BC albedo forcings computed by some of the same models, we find that the global annual mean can vary by up to a factor of two because of different aerosol models or different BC-snow parameterizations and snow cover. The spatial distributions of the offline BC albedo forcing in 2000 show especially high BC forcing (i.e., over 0.1W/sq. m) over Manchuria, Karakoram, and most of the Former USSR. Models predict the highest global annual mean BC forcing in 1980 rather than 2000, mostly driven by the high fossil fuel and biofuel emissions in the Former USSR in 1980.

Description: We use simultaneous observations of tropospheric ozone and outgoing longwave radiation (OLR) sensitivity to tropospheric ozone from the Tropospheric Emission Spectrometer (TES) to evaluate model tropospheric ozone and its effect on OLR simulated by a suite of chemistry-climate models that participated in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The ensemble mean of ACCMIP models show a persistent but modest tropospheric ozone low bias (5-20 ppb) in the Southern Hemisphere (SH) and modest high bias (5-10 ppb) in the Northern Hemisphere (NH) relative to TES ozone for 2005-2010. These ozone biases have a significant impact on the OLR. Using TES instantaneous radiative kernels (IRK), we show that the ACCMIP ensemble mean tropospheric ozone low bias leads up to 120mW/ sq. m OLR high bias locally but zonally compensating errors reduce the global OLR high bias to 39+/- 41mW/ sq. m relative to TES data. We show that there is a correlation (Sq. R = 0.59) between the magnitude of the ACCMIP OLR bias and the deviation of the ACCMIP preindustrial to present day (1750-2010) ozone radiative forcing (RF) from the ensemble ozone RF mean. However, this correlation is driven primarily by models whose absolute OLR bias from tropospheric ozone exceeds 100mW/ sq. m. Removing these models leads to a mean ozone radiative forcing of 394+/- 42mW/ sq. m. The mean is about the same and the standard deviation is about 30% lower than an ensemble ozone RF of 384 +/- 60mW/ sq. m derived from 14 of the 16 ACCMIP models reported in a companion ACCMIP study. These results point towards a profitable direction of combining satellite observations and chemistry-climate model simulations to reduce uncertainty in ozone radiative forcing.

Description: Aerosols have important impacts on air quality and climate, but the processes affecting their removal from the atmosphere are not fully understood and are poorly constrained by observations. This makes modelled aerosol lifetimes uncertain. In this study, we make use of an observational constraint on aerosol lifetimes provided by radionuclide measurements and investigate the causes of differences within a set of global models. During the Fukushima Dai-Ichi nuclear power plant accident of March 2011, the radioactive isotopes cesium-137 (Cs-137) and xenon-133 (Xe-133) were released in large quantities. Cesium attached to particles in the ambient air, approximately according to their available aerosol surface area. Cs-137 size distribution measurements taken close to the power plant suggested that accumulation mode (AM) sulfate aerosols were the main carriers of cesium. Hence, Cs-137 can be used as a proxy tracer for the AM sulfate aerosol's fate in the atmosphere. In contrast, the noble gas Xe-133 behaves almost like a passive transport tracer. Global surface measurements of the two radioactive isotopes taken over several months after the release allow the derivation of a lifetime of the carrier aerosol. We compare this to the lifetimes simulated by 19 different atmospheric transport models initialized with identical emissions of Cs-137that were assigned to an aerosol tracer with each model's default properties of AM sulfate, and Xe-133 emissions that were assigned to a passive tracer. We investigate to what extent the modelled sulfate tracer can reproduce the measurements, especially with respect to the observed loss of aerosol mass with time. Modelled Cs-137and Xe-133 concentrations sampled at the same location and times as station measurements allow a direct comparison between measured and modelled aerosol lifetime. The e-folding lifetime e, calculated from station measurement data taken between 2 and 9 weeks after the start of the emissions, is 14.3 days (95% confidence interval 13.1-15.7 days). The equivalent modelled e lifetimes have a large spread, varying between 4.8 and 26.7 days with a model median of 9.42.3 days, indicating too fast a removal in most models. Because sufficient measurement data were only available from about 2 weeks after the release, the estimated lifetimes apply to aerosols that have undergone long-range transport, i.e. not for freshly emitted aerosol. However, modelled instantaneous lifetimes show that the initial removal in the first 2 weeks was quicker (lifetimes between 1 and 5 days) due to the emissions occurring at low altitudes and co-location of the fresh plume with strong precipitation. Deviations between measured and modelled aerosol lifetimes are largest for the northernmost stations and at later time periods, suggesting that models do not transport enough of the aerosol towards the Arctic. The models underestimate passive tracer (Xe-133) concentrations in the Arctic as well but to a smaller extent than for the aerosol (Cs-137) tracer. This indicates that in addition to too fast an aerosol removal in the models, errors in simulated atmospheric transport towards the Arctic in most models also contribute to the underestimation of the Arctic aerosol concentrations.

Description: The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) consists of a series of time slice experiments targeting the long-term changes in atmospheric composition between 1850 and 2100, with the goal of documenting composition changes and the associated radiative forcing. In this overview paper, we introduce the ACCMIP activity, the various simulations performed (with a requested set of 14) and the associated model output. The 16 ACCMIP models have a wide range of horizontal and vertical resolutions, vertical extent, chemistry schemes and interaction with radiation and clouds. While anthropogenic and biomass burning emissions were specified for all time slices in the ACCMIP protocol, it is found that the natural emissions are responsible for a significant range across models, mostly in the case of ozone precursors. The analysis of selected present-day climate diagnostics (precipitation, temperature, specific humidity and zonal wind) reveals biases consistent with state-of-the-art climate models. The model-to- model comparison of changes in temperature, specific humidity and zonal wind between 1850 and 2000 and between 2000 and 2100 indicates mostly consistent results. However, models that are clear outliers are different enough from the other models to significantly affect their simulation of atmospheric chemistry.

Description: The TwO-Moment Aerosol Sectional (TOMAS) microphysics model has been integrated into the state-of-the- art general circulation model, GISS ModelE2. This paper provides a detailed description of the ModelE2-TOMAS model and evaluates the model against various observations including aerosol precursor gas concentrations, aerosol mass and number concentrations, and aerosol optical depths. Additionally, global budgets in ModelE2-TOMAS are compared with those of other global aerosol models, and the ModelE2-TOMAS model is compared to the default aerosol model in ModelE2, which is a one-moment aerosol (OMA) model (i.e. no aerosol microphysics). Overall, the ModelE2- TOMAS predictions are within the range of other global aerosol model predictions, and the model has a reasonable agreement (mostly within a factor of 2) with observations of sulfur species and other aerosol components as well as aerosol optical depth. However, ModelE2-TOMAS (as well as ModelE2-OMA) cannot capture the observed vertical distribution of sulfur dioxide over the Pacific Ocean, possibly due to overly strong convective transport and over-predicted precipitation. The ModelE2-TOMAS model simulates observed aerosol number concentrations and cloud condensation nuclei concentrations roughly within a factor of 2. Anthropogenic aerosol burdens in ModelE2-OMA differ from ModelE2-TOMAS by a few percent to a factor of 2 regionally, mainly due to differences in aerosol processes including deposition, cloud processing, and emission parameterizations. We observed larger differences for naturally emitted aerosols such as sea salt and mineral dust, as those emission rates are quite different due to different upper size cutoff assumptions.