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- ItemThe ECOMA 2007 campaign: Rocket observations and numerical modelling of aerosol particle charging and plasma depletion in a PMSE/NLC layer(München : European Geopyhsical Union, 2009) Brattli, A.; Lie-Svendsen, Ø.; Svenes, K.; Hoppe, U.-P.; Strelnikova, I.; Rapp, M.; Latteck, R.; Torkar, K.; Gumbel, J.; Megner, L.; Baumgarten, G.The ECOMA series of rocket payloads use a set of aerosol particle, plasma, and optical instruments to study the properties of aerosol particles and their interaction with the ambient plasma environment in the polar mesopause region. In August 2007 the ECOMA-3 payload was launched into a region with Polar Mesosphere Summer Echoes (PMSE) and noctilucent clouds (NLC). An electron depletion was detected in a broad region between 83 and 88 km, coincident with enhanced density of negatively charged aerosol particles. We also find evidence for positive ion depletion in the same region. Charge neutrality requires that a population of positively charged particles smaller than 2 nm and with a density of at least 2×108 m−3 must also have been present in the layer, undetected by the instruments. A numerical model for the charging of aerosol particles and their interaction with the ambient plasma is used to analyse the results, showing that high aerosol particle densities are required in order to explain the observed ion density depletion. The model also shows that a very high photoionisation rate is required for the particles smaller than 2 nm to become positively charged, indicating that these may have a lower work function than pure water ice.
- ItemSeasonal variation of nocturnal temperatures between 1 and 105 km altitude at 54° N observed by lidar(München : European Geopyhsical Union, 2008) Gerding, M.; Höffner, J.; Lautenbach, J.; Rauthe, M.; Lübken, F.-J.Temperature soundings are performed by lidar at the mid-latitude station of Kühlungsborn (Germany, 54° N, 12° E). The profiles cover the complete range from the lower troposphere (~1 km) to the lower thermosphere (~105 km) by simultaneous and co-located operation of a Rayleigh-Mie-Raman lidar and a potassium resonance lidar. Observations have been done during 266 nights between June 2002 and July 2007, each of 3–15 h length. This large and unique data set provides comprehensive information on the altitudinal and seasonal variation of temperatures from the troposphere to the lower thermosphere. The remaining day-to-day-variability is strongly reduced by harmonic fits at constant altitude levels and a representative data set is achieved. This data set reveals a two-level mesopause structure with an altitude of about 86–87 km (~144 K) in summer and ~102 km (~170 K) during the rest of the year. The average stratopause altitude is ~48 km throughout the whole year, with temperatures varying between 258 and 276 K. From the fit parameters amplitudes and phases of annual, semi-annual, and quarter-annual variations are derived. The amplitude of the annual component is largest with amplitudes of up to 30 K in 85 km, while the quarter-annual variation is smallest and less than 3 K at all altitudes. The lidar data set is compared with ECMWF temperatures below about 70 km altitude and reference data from the NRLMSISE-00 model above. Apart from the temperature soundings the aerosol backscatter ratio is measured between 20 and 35 km. The seasonal variation of these values is presented here for the first time.
- ItemHomogeneous and heterogeneous ice nucleation at LACIS: Operating principle and theoretical studies(München : European Geopyhsical Union, 2011) Hartmann, S.; Niedermeier, D.; Voigtländer, J.; Clauss, T.; Shaw, R.A.; Wex, H.; Kiselev, A.; Stratmann, F.At the Leipzig Aerosol Cloud Interaction Simulator (LACIS) experiments investigating homogeneous and heterogeneous nucleation of ice (particularly immersion freezing in the latter case) have been carried out. Here both the physical LACIS setup and the numerical model developed to design experiments at LACIS and interpret their results are presented in detail. Combining results from the numerical model with experimental data, it was found that for the experimental parameter space considered, classical homogeneous ice nucleation theory is able to predict the freezing behavior of highly diluted ammonium sulfate solution droplets, while classical heterogeneous ice nucleation theory, together with the assumption of a constant contact angle, fails to predict the immersion freezing behavior of surrogate mineral dust particles (Arizona Test Dust, ATD). The main reason for this failure is the compared to experimental data apparently overly strong temperature dependence of the nucleation rate coefficient. Assuming, in the numerical model, Classical Nucleation Theory (CNT) for homogeneous ice nucleation and a CNT-based parameterization for the nucleation rate coefficient in the immersion freezing mode, recently published by our group, it was found that even for a relatively effective ice nucleating agent such as pure ATD, there is a temperature range where homogeneous ice nucleation is dominant. The main explanation is the apparently different temperature dependencies of the two freezing mechanisms. Finally, reviewing the assumptions made during the derivation of the CNT-based parameterization for immersion freezing, it was found that the assumption of constant temperature during ice nucleation and the chosen ice nucleation time were justified, underlining the applicability of the method to determine the fitting coefficients in the parameterization equation.
- ItemEmulating atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 - Part 2: Applications(München : European Geopyhsical Union, 2011) Meinshausen, M.; Raper, S.C.B.; Wigley, T.M.L.Intercomparisons of coupled atmosphere-ocean general circulation models (AOGCMs) and carbon cycle models are important for galvanizing our current scientific knowledge to project future climate. Interpreting such intercomparisons faces major challenges, not least because different models have been forced with different sets of forcing agents. Here, we show how an emulation approach with MAGICC6 can address such problems. In a companion paper (Meinshausen et al., 2011a), we show how the lower complexity carbon cycle-climate model MAGICC6 can be calibrated to emulate, with considerable accuracy, globally aggregated characteristics of these more complex models. Building on that, we examine here the Coupled Model Intercomparison Project's Phase 3 results (CMIP3). If forcing agents missed by individual AOGCMs in CMIP3 are considered, this reduces ensemble average temperature change from pre-industrial times to 2100 under SRES A1B by 0.4 °C. Differences in the results from the 1980 to 1999 base period (as reported in IPCC AR4) to 2100 are negligible, however, although there are some differences in the trajectories over the 21st century. In a second part of this study, we consider the new RCP scenarios that are to be investigated under the forthcoming CMIP5 intercomparison for the IPCC Fifth Assessment Report. For the highest scenario, RCP8.5, relative to pre-industrial levels, we project a median warming of around 4.6 °C by 2100 and more than 7 °C by 2300. For the lowest RCP scenario, RCP3-PD, the corresponding warming is around 1.5 °C by 2100, decreasing to around 1.1 °C by 2300 based on our AOGCM and carbon cycle model emulations. Implied cumulative CO2 emissions over the 21st century for RCP8.5 and RCP3-PD are 1881 GtC (1697 to 2034 GtC, 80% uncertainty range) and 381 GtC (334 to 488 GtC), when prescribing CO2 concentrations and accounting for uncertainty in the carbon cycle. Lastly, we assess the reasons why a previous MAGICC version (4.2) used in IPCC AR4 gave roughly 10% larger warmings over the 21st century compared to the CMIP3 average. We find that forcing differences and the use of slightly too high climate sensitivities inferred from idealized high-forcing runs were the major reasons for this difference.
- ItemModelling of sea salt concentrations over Europe: Key uncertainties and comparison with observations(München : European Geopyhsical Union, 2011) Tsyro, S.; Aas, W.; Soares, J.; Sofiev, M.; Berge, H.; Spindler, G.Sea salt aerosol can significantly affect the air quality. Sea salt can cause enhanced concentrations of particulate matter and change particle chemical composition, in particular in coastal areas, and therefore should be accounted for in air quality modelling. We have used an EMEP Unified model to calculate sea salt concentrations and depositions over Europe, focusing on studying the effects of uncertainties in sea salt production and lifetime on calculation results. Model calculations of sea salt have been compared with EMEP observations of sodium concentrations in air and precipitation for a four year period, from 2004 to 2007, including size (fine/coarse) resolved EMEP intensive measurements in 2006 and 2007. In the presented calculations, sodium air concentrations are between 8% and 46% overestimated, whereas concentrations in precipitation are systematically underestimated by 65–70% for years 2004–2007. A series of model tests have been performed to investigate the reasons for this underestimation, but further studies are needed. The model is found to reproduce the spatial distribution of Na+ in air and precipitation over Europe fairly well, and to capture most of sea salt episodes. The paper presents the main findings from a series of tests in which we compare several different sea spray source functions and also look at the effects of meteorological input and the efficiency of removal processes on calculated sea salt concentrations. Finally, sea salt calculations with the EMEP model have been compared with results from the SILAM model and observations for 2007. While the models produce quite close results for Na+ at the majority of 26 measurement sites, discrepancies in terms of bias and temporal correlation are also found. Those differences are believed to occur due to differences in the representation of source function and size distribution of sea salt aerosol, different meteorology used for model runs and the different models' resolution. This study contributes to getting a better insight on uncertainties associated with sea salt calculations and thus facilitates further improvement of aerosol modelling on both regional and global scales.
- ItemComplex refractive indices of Saharan dust samples at visible and near UV wavelengths: A laboratory study(München : European Geopyhsical Union, 2012) Wagner, R.; Ajtai, T.; Kandler, K.; Lieke, K.; Linke, C.; Müller, T.; Schnaiter, M.; Vragel, M.We have retrieved the wavelength-dependent imaginary parts of the complex refractive index for five different Saharan dust aerosol particles of variable mineralogical composition at wavelengths between 305 and 955 nm. The dust particles were generated by dispersing soil samples into a laboratory aerosol chamber, typically yielding particle sizes with mean diameters ranging from 0.3 to 0.4 μm and maximum diameters from 2 to 4 μm. The extinction and absorption coefficients as well as the number size distribution of the dust particles were simultaneously measured by various established techniques. An inversion scheme based on a spheroidal dust model was employed to deduce the refractive indices. The retrieved imaginary parts of the complex refractive index were in the range from 0.003 to 0.005, 0.005 to 0.011, and 0.016 to 0.050 at the wavelengths 955, 505, and 305 nm. The hematite content of the dust particles was determined by electron-microscopical single particle analysis. Hematite volume fractions in the range from 1.1 to 2.7% were found for the different dusts, a range typical for atmospheric mineral dust. We have performed a sensitivity study to assess how accurately the retrieved imaginary refractive indices could be reproduced by calculations with mixing rule approximations using the experimentally determined hematite contents as input.
- ItemAtmospheric dust modeling from meso to global scales with the online NMMB/BSC-Dust model – Part 2: Experimental campaigns in Northern Africa(München : European Geopyhsical Union, 2012) Haustein, K.; Pérez, C.; Baldasano, J.M.; Jorba, O.; Basart, S.; Miller, R.L.; Janjic, Z.; Black, T.; Nickovic, S.; Todd, M.C.; Washington, R.; Müller, D.; Tesche, M.; Weinzierl, B.; Esselborn, M.; Schladitz, A.The new NMMB/BSC-Dust model is intended to provide short to medium-range weather and dust forecasts from regional to global scales. It is an online model in which the dust aerosol dynamics and physics are solved at each model time step. The companion paper (Pérez et al., 2011) develops the dust model parameterizations and provides daily to annual evaluations of the model for its global and regional configurations. Modeled aerosol optical depth (AOD) was evaluated against AERONET Sun photometers over Northern Africa, Middle East and Europe with correlations around 0.6–0.7 on average without dust data assimilation. In this paper we analyze in detail the behavior of the model using data from the Saharan Mineral dUst experiment (SAMUM-1) in 2006 and the Bodélé Dust Experiment (BoDEx) in 2005. AOD from satellites and Sun photometers, vertically resolved extinction coefficients from lidars and particle size distributions at the ground and in the troposphere are used, complemented by wind profile data and surface meteorological measurements. All simulations were performed at the regional scale for the Northern African domain at the expected operational horizontal resolution of 25 km. Model results for SAMUM-1 generally show good agreement with satellite data over the most active Saharan dust sources. The model reproduces the AOD from Sun photometers close to sources and after long-range transport, and the dust size spectra at different height levels. At this resolution, the model is not able to reproduce a large haboob that occurred during the campaign. Some deficiencies are found concerning the vertical dust distribution related to the representation of the mixing height in the atmospheric part of the model. For the BoDEx episode, we found the diurnal temperature cycle to be strongly dependant on the soil moisture, which is underestimated in the NCEP analysis used for model initialization. The low level jet (LLJ) and the dust AOD over the Bodélé are well reproduced. The remaining negative AOD bias (due to underestimated surface wind speeds) can be substantially reduced by decreasing the threshold friction velocity in the model.
- ItemNumerical simulations of mixing conditions and aerosol dynamics in the CERN CLOUD chamber(München : European Geopyhsical Union, 2012) Voigtländer, J.; Duplissy, J.; Rondo, L.; Kürten, A.; Stratmann, F.To study the effect of galactic cosmic rays on aerosols and clouds, the Cosmics Leaving OUtdoor Droplets (CLOUD) project was established. Experiments are carried out at a 26.1 m3 tank at CERN (Switzerland). In the experiments, the effect of ionizing radiation on H2SO4 particle formation and growth is investigated. To evaluate the experimental configuration, the experiment was simulated using a coupled multidimensional computational fluid dynamics (CFD) – particle model. In the model the coupled fields of gas/vapor species, temperature, flow velocity and particle properties were computed to investigate mixing state and mixing times of the CLOUD tank's contents. Simulation results show that a 1-fan configuration, as used in first experiments, may not be sufficient to ensure a homogeneously mixed chamber. To mix the tank properly, two fans and sufficiently high fan speeds are necessary. The 1/e response times for instantaneous changes of wall temperature and saturation ratio were found to be in the order of few minutes. Particle nucleation and growth was also simulated and particle number size distribution properties of the freshly nucleated particles (particle number, mean size, standard deviation of the assumed log-normal distribution) were found to be distributed over the tank's volume similar to the gas species.
- ItemAsymmetry and uncertainties in biogeophysical climate-vegetation feedback over a range of CO2 forcings(München : European Geopyhsical Union, 2014) Willeit, M.; Ganopolski, A.; Feulner, G.Climate–vegetation feedback has the potential to significantly contribute to climate change, but little is known about its range of uncertainties. Here, using an Earth system model of intermediate complexity we address possible uncertainties in the strength of the biogeophysical climate–vegetation feedback using a single-model multi-physics ensemble. Equilibrium experiments with halving (140 ppm) and doubling (560 ppm) of CO2 give a contribution of the vegetation–climate feedback to global temperature change in the range −0.3 to −0.1 °C and −0.1 to 0.2 °C, respectively. There is an asymmetry between warming and cooling, with a larger, positive vegetation–climate feedback in the lower CO2 climate. Hotspots of climate–vegetation feedback are the boreal zone, the Amazon rainforest and the Sahara. Albedo parameterization is the dominant source of uncertainty in the subtropics and at high northern latitudes, while uncertainties in evapotranspiration are more relevant in the tropics. We analyse the separate impact of changes in stomatal conductance, leaf area index and vegetation dynamics on climate and we find that different processes are dominant in lower and higher CO2 worlds. The reduction in stomatal conductance gives the main contribution to temperature increase for a doubling of CO2, while dynamic vegetation is the dominant process in the CO2 halving experiments. Globally the climate–vegetation feedback is rather small compared to the sum of the fast climate feedbacks. However, it is comparable to the amplitude of the fast feedbacks at high northern latitudes where it can contribute considerably to polar amplification. The uncertainties in the climate–vegetation feedback are comparable to the multi-model spread of the fast climate feedbacks.
- ItemTowards global empirical upscaling of FLUXNET eddy covariance observations: Validation of a model tree ensemble approach using a biosphere model(München : European Geopyhsical Union, 2009) Jung, M.; Reichstein, M.; Bondeau, A.Global, spatially and temporally explicit estimates of carbon and water fluxes derived from empirical up-scaling eddy covariance measurements would constitute a new and possibly powerful data stream to study the variability of the global terrestrial carbon and water cycle. This paper introduces and validates a machine learning approach dedicated to the upscaling of observations from the current global network of eddy covariance towers (FLUXNET). We present a new model TRee Induction ALgorithm (TRIAL) that performs hierarchical stratification of the data set into units where particular multiple regressions for a target variable hold. We propose an ensemble approach (Evolving tRees with RandOm gRowth, ERROR) where the base learning algorithm is perturbed in order to gain a diverse sequence of different model trees which evolves over time. We evaluate the efficiency of the model tree ensemble (MTE) approach using an artificial data set derived from the Lund-Potsdam-Jena managed Land (LPJmL) biosphere model. We aim at reproducing global monthly gross primary production as simulated by LPJmL from 1998–2005 using only locations and months where high quality FLUXNET data exist for the training of the model trees. The model trees are trained with the LPJmL land cover and meteorological input data, climate data, and the fraction of absorbed photosynthetic active radiation simulated by LPJmL. Given that we know the "true result" in the form of global LPJmL simulations we can effectively study the performance of the MTE upscaling and associated problems of extrapolation capacity. We show that MTE is able to explain 92% of the variability of the global LPJmL GPP simulations. The mean spatial pattern and the seasonal variability of GPP that constitute the largest sources of variance are very well reproduced (96% and 94% of variance explained respectively) while the monthly interannual anomalies which occupy much less variance are less well matched (41% of variance explained). We demonstrate the substantially improved accuracy of MTE over individual model trees in particular for the monthly anomalies and for situations of extrapolation. We estimate that roughly one fifth of the domain is subject to extrapolation while MTE is still able to reproduce 73% of the LPJmL GPP variability here. This paper presents for the first time a benchmark for a global FLUXNET upscaling approach that will be employed in future studies. Although the real world FLUXNET upscaling is more complicated than for a noise free and reduced complexity biosphere model as presented here, our results show that an empirical upscaling from the current FLUXNET network with MTE is feasible and able to extract global patterns of carbon flux variability.