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Now showing 1 - 10 of 26
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    The 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.
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    Seasonal 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.
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    Homogeneous 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.
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    Emulating 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.
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    Modelling 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.
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    Towards 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.
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    Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 - Part 1: Model description and calibration
    (München : European Geopyhsical Union, 2011) Meinshausen, M.; Raper, S.C.B.; Wigley, T.M.L.
    Current scientific knowledge on the future response of the climate system to human-induced perturbations is comprehensively captured by various model intercomparison efforts. In the preparation of the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), intercomparisons were organized for atmosphere-ocean general circulation models (AOGCMs) and carbon cycle models, named "CMIP3" and "C4MIP", respectively. Despite their tremendous value for the scientific community and policy makers alike, there are some difficulties in interpreting the results. For example, radiative forcings were not standardized across the various AOGCM integrations and carbon cycle runs, and, in some models, key forcings were omitted. Furthermore, the AOGCM analysis of plausible emissions pathways was restricted to only three SRES scenarios. This study attempts to address these issues. We present an updated version of MAGICC, the simple carbon cycle-climate model used in past IPCC Assessment Reports with enhanced representation of time-varying climate sensitivities, carbon cycle feedbacks, aerosol forcings and ocean heat uptake characteristics. This new version, MAGICC6, is successfully calibrated against the higher complexity AOGCMs and carbon cycle models. Parameterizations of MAGICC6 are provided. The mean of the emulations presented here using MAGICC6 deviates from the mean AOGCM responses by only 2.2% on average for the SRES scenarios. This enhanced emulation skill in comparison to previous calibrations is primarily due to: making a "like-with-like comparison" using AOGCM-specific subsets of forcings; employing a new calibration procedure; as well as the fact that the updated simple climate model can now successfully emulate some of the climate-state dependent effective climate sensitivities of AOGCMs. The diagnosed effective climate sensitivity at the time of CO2 doubling for the AOGCMs is on average 2.88 °C, about 0.33 °C cooler than the mean of the reported slab ocean climate sensitivities. In the companion paper (Part 2) of this study, we examine the combined climate system and carbon cycle emulations for the complete range of IPCC SRES emissions scenarios and the new RCP pathways.
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    Explaining global surface aerosol number concentrations in terms of primary emissions and particle formation
    (München : European Geopyhsical Union, 2010) Spracklen, D.V.; Carslaw, K.S.; Merikanto, J.; Mann, G.W.; Reddington, C.L.; Pickering, S.; Ogren, J.A.; Andrews, E.; Baltensperger, U.; Weingartner, E.; Boy, M.; Kulmala, M.; Laakso, L.; Lihavainen, H.; Kivekäs, N.; Komppula, M.; Mihalopoulos, N.; Kouvarakis, G.; Jennings, S.G.; O'Dowd, C.; Birmili, W.; Wiedensohler, A.; Weller, R.; Gras, J.; Laj, P.; Sellegri, K.; Bonn, B.; Krejci, R.; Laaksonen, A.; Hamed, A.; Minikin, A.; Harrison, R.M.; Talbot, R.; Sun, J.
    We synthesised observations of total particle number (CN) concentration from 36 sites around the world. We found that annual mean CN concentrations are typically 300–2000 cm−3 in the marine boundary layer and free troposphere (FT) and 1000–10 000 cm−3 in the continental boundary layer (BL). Many sites exhibit pronounced seasonality with summer time concentrations a factor of 2–10 greater than wintertime concentrations. We used these CN observations to evaluate primary and secondary sources of particle number in a global aerosol microphysics model. We found that emissions of primary particles can reasonably reproduce the spatial pattern of observed CN concentration (R2=0.46) but fail to explain the observed seasonal cycle (R2=0.1). The modeled CN concentration in the FT was biased low (normalised mean bias, NMB=−88%) unless a secondary source of particles was included, for example from binary homogeneous nucleation of sulfuric acid and water (NMB=−25%). Simulated CN concentrations in the continental BL were also biased low (NMB=−74%) unless the number emission of anthropogenic primary particles was increased or a mechanism that results in particle formation in the BL was included. We ran a number of simulations where we included an empirical BL nucleation mechanism either using the activation-type mechanism (nucleation rate, J, proportional to gas-phase sulfuric acid concentration to the power one) or kinetic-type mechanism (J proportional to sulfuric acid to the power two) with a range of nucleation coefficients. We found that the seasonal CN cycle observed at continental BL sites was better simulated by BL particle formation (R2=0.3) than by increasing the number emission from primary anthropogenic sources (R2=0.18). The nucleation constants that resulted in best overall match between model and observed CN concentrations were consistent with values derived in previous studies from detailed case studies at individual sites. In our model, kinetic and activation-type nucleation parameterizations gave similar agreement with observed monthly mean CN concentrations.
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    Sensitivity of polar stratospheric ozone loss to uncertainties in chemical reaction kinetics
    (Göttingen : Copernicus GmbH, 2009) Kawa, S.R.; Stolarski, R.S.; Newman, P.A.; Douglass, A.R.; Rex, M.; Hofmann, D.J.; Santee, M.L.; Frieler, K.
    The impact and significance of uncertainties in model calculations of stratospheric ozone loss resulting from known uncertainty in chemical kinetics parameters is evaluated in trajectory chemistry simulations for the Antarctic and Arctic polar vortices. The uncertainty in modeled ozone loss is derived from Monte Carlo scenario simulations varying the kinetic (reaction and photolysis rate) parameters within their estimated uncertainty bounds. Simulations of a typical winter/spring Antarctic vortex scenario and Match scenarios in the Arctic produce large uncertainty in ozone loss rates and integrated seasonal loss. The simulations clearly indicate that the dominant source of model uncertainty in polar ozone loss is uncertainty in the Cl2O 2 photolysis reaction, which arises from uncertainty in laboratory-measured molecular cross sections at atmospherically important wavelengths. This estimated uncertainty in JCl 2O2 from laboratory measurements seriously hinders our ability to model polar ozone loss within useful quantitative error limits. Atmospheric observations, however, suggest that the Cl2O2 photolysis uncertainty may be less than that derived from the lab data. Comparisons to Match, South Pole ozonesonde, and Aura Microwave Limb Sounder (MLS) data all show that the nominal recommended rate simulations agree with data within uncertainties when the Cl2O2 photolysis error is reduced by a factor of two, in line with previous in situ ClOx measurements. Comparisons to simulations using recent cross sections from Pope et al. (2007) are outside the constrained error bounds in each case. Other reactions producing significant sensitivity in polar ozone loss include BrO + ClO and its branching ratios. These uncertainties challenge our confidence in modeling polar ozone depletion and projecting future changes in response to changing halogen emissions and climate. Further laboratory, theoretical, and possibly atmospheric studies are needed.
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    On microphysical processes of noctilucent clouds (NLC): Observations and modeling of mean and width of the particle size-distribution
    (Göttingen : Copernicus, 2010) Baumgarten, G.; Fiedler, J.; Rapp, M.
    Noctilucent clouds (NLC) in the polar summer mesopause region have been observed in Norway (69° N, 16° E) between 1998 and 2009 by 3-color lidar technique. Assuming a mono-modal Gaussian size distribution we deduce mean and width of the particle sizes throughout the clouds. We observe a quasi linear relationship between distribution width and mean of the particle size at the top of the clouds and a deviation from this behavior for particle sizes larger than 40 nm, most often in the lower part of the layer. The vertically integrated particle properties show that 65% of the data follows the linear relationship with a slope of 0.42±0.02 for mean particle sizes up to 40 nm. For the vertically resolved particle properties (Δz = Combining double low line 0.15 km) the slope is comparable and about 0.39±0.03. For particles larger than 40 nm the distribution width becomes nearly independent of particle size and even decreases in the lower part of the layer. We compare our observations to microphysical modeling of noctilucent clouds and find that the distribution width depends on turbulence, the time that turbulence can act (cloud age), and the sampling volume/time (atmospheric variability). The model results nicely reproduce the measurements and show that the observed slope can be explained by eddy diffusion profiles as observed from rocket measurements. © 2010 Author(s).