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lmd_Boucher2011_abstracts.html

2011 .

(11 publications)

M. Kulmala, A. Asmi, H. K. Lappalainen, U. Baltensperger, J.-L. Brenguier, M. C. Facchini, H.-C. Hansson, Ø. Hov, C. D. O'Dowd, U. Pöschl, A. Wiedensohler, R. Boers, O. Boucher, G. de Leeuw, H. A. C. Denier van der Gon, J. Feichter, R. Krejci, P. Laj, H. Lihavainen, U. Lohmann, G. McFiggans, T. Mentel, C. Pilinis, I. Riipinen, M. Schulz, A. Stohl, E. Swietlicki, E. Vignati, C. Alves, M. Amann, M. Ammann, S. Arabas, P. Artaxo, H. Baars, D. C. S. Beddows, R. Bergström, J. P. Beukes, M. Bilde, J. F. Burkhart, F. Canonaco, S. L. Clegg, H. Coe, S. Crumeyrolle, B. D'Anna, S. Decesari, S. Gilardoni, M. Fischer, A. M. Fjaeraa, C. Fountoukis, C. George, L. Gomes, P. Halloran, T. Hamburger, R. M. Harrison, H. Herrmann, T. Hoffmann, C. Hoose, M. Hu, A. Hyvärinen, U. Hõrrak, Y. Iinuma, T. Iversen, M. Josipovic, M. Kanakidou, A. Kiendler-Scharr, A. Kirkevåg, G. Kiss, Z. Klimont, P. Kolmonen, M. Komppula, J.-E. Kristjánsson, L. Laakso, A. Laaksonen, L. Labonnote, V. A. Lanz, K. E. J. Lehtinen, L. V. Rizzo, R. Makkonen, H. E. Manninen, G. McMeeking, J. Merikanto, A. Minikin, S. Mirme, W. T. Morgan, E. Nemitz, D. O'Donnell, T. S. Panwar, H. Pawlowska, A. Petzold, J. J. Pienaar, C. Pio, C. Plass-Duelmer, A. S. H. Prévôt, S. Pryor, C. L. Reddington, G. Roberts, D. Rosenfeld, J. Schwarz, Ø. Seland, K. Sellegri, X. J. Shen, M. Shiraiwa, H. Siebert, B. Sierau, D. Simpson, J. Y. Sun, D. Topping, P. Tunved, P. Vaattovaara, V. Vakkari, J. P. Veefkind, A. Visschedijk, H. Vuollekoski, R. Vuolo, B. Wehner, J. Wildt, S. Woodward, D. R. Worsnop, G.-J. van Zadelhoff, A. A. Zardini, K. Zhang, P. G. van Zyl, V.-M. Kerminen, K. S. Carslaw, and S. N. Pandis. General overview: European Integrated project on Aerosol Cloud Climate and Air Quality interactions (EUCAARI) - integrating aerosol research from nano to global scales. Atmospheric Chemistry & Physics, 11:13061-13143, December 2011. [ bib | DOI | ADS link ]

In this paper we describe and summarize the main achievements of the European Aerosol Cloud Climate and Air Quality Interactions project (EUCAARI). EUCAARI started on 1 January 2007 and ended on 31 December 2010 leaving a rich legacy including: (a) a comprehensive database with a year of observations of the physical, chemical and optical properties of aerosol particles over Europe, (b) comprehensive aerosol measurements in four developing countries, (c) a database of airborne measurements of aerosols and clouds over Europe during May 2008, (d) comprehensive modeling tools to study aerosol processes fron nano to global scale and their effects on climate and air quality. In addition a new Pan-European aerosol emissions inventory was developed and evaluated, a new cluster spectrometer was built and tested in the field and several new aerosol parameterizations and computations modules for chemical transport and global climate models were developed and evaluated. These achievements and related studies have substantially improved our understanding and reduced the uncertainties of aerosol radiative forcing and air quality-climate interactions. The EUCAARI results can be utilized in European and global environmental policy to assess the aerosol impacts and the corresponding abatement strategies.

N. Bellouin, J. Rae, A. Jones, C. Johnson, J. Haywood, and O. Boucher. Aerosol forcing in the Climate Model Intercomparison Project (CMIP5) simulations by HadGEM2-ES and the role of ammonium nitrate. Journal of Geophysical Research (Atmospheres), 116:20206, October 2011. [ bib | DOI | ADS link ]

The latest Hadley Centre climate model, HadGEM2-ES, includes Earth system components such as interactive chemistry and eight species of tropospheric aerosols. It has been run for the period 1860-2100 in support of the fifth phase of the Climate Model Intercomparison Project (CMIP5). Anthropogenic aerosol emissions peak between 1980 and 2020, resulting in a present-day all-sky top of the atmosphere aerosol forcing of -1.6 and -1.4 W m-2 with and without ammonium nitrate aerosols, respectively, for the sum of direct and first indirect aerosol forcings. Aerosol forcing becomes significantly weaker in the 21st century, being weaker than -0.5 W m-2 in 2100 without nitrate. However, nitrate aerosols become the dominant species in Europe and Asia and decelerate the decrease in global mean aerosol forcing. Considering nitrate aerosols makes aerosol radiative forcing 2-4 times stronger by 2100 depending on the representative concentration pathway, although this impact is lessened when changes in the oxidation properties of the atmosphere are accounted for. Anthropogenic aerosol residence times increase in the future in spite of increased precipitation, as cloud cover and aerosol-cloud interactions decrease in tropical and midlatitude regions. Deposition of fossil fuel black carbon onto snow and ice surfaces peaks during the 20th century in the Arctic and Europe but keeps increasing in the Himalayas until the middle of the 21st century. Results presented here confirm the importance of aerosols in influencing the Earth's climate, albeit with a reduced impact in the future, and suggest that nitrate aerosols will partially replace sulphate aerosols to become an important anthropogenic species in the remainder of the 21st century.

J. M. Haywood, N. Bellouin, A. Jones, O. Boucher, M. Wild, and K. P. Shine. The roles of aerosol, water vapor and cloud in future global dimming/brightening. Journal of Geophysical Research (Atmospheres), 116:20203, October 2011. [ bib | DOI | ADS link ]

Observational evidence indicates significant regional trends in solar radiation at the surface in both all-sky and cloud-free conditions. Negative trends in the downwelling solar surface irradiance (SSI) have become known as `dimming' while positive trends have become known as `brightening'. We use the Met Office Hadley Centre HadGEM2 climate model to model trends in cloud-free and total SSI from the pre-industrial to the present-day and compare these against observations. Simulations driven by CMIP5 emissions are used to model the future trends in dimming/brightening up to the year 2100. The modeled trends are reasonably consistent with observed regional trends in dimming and brightening which are due to changes in concentrations in anthropogenic aerosols and, potentially, changes in cloud cover owing to the aerosol indirect effects and/or cloud feedback mechanisms. The future dimming/brightening in cloud-free SSI is not only caused by changes in anthropogenic aerosols: aerosol impacts are overwhelmed by a large dimming caused by increases in water vapor. There is little trend in the total SSI as cloud cover decreases in the climate model used here, and compensates the effect of the change in water vapor. In terms of the surface energy balance, these trends in SSI are obviously more than compensated by the increase in the downwelling terrestrial irradiance from increased water vapor concentrations. However, the study shows that while water vapor is widely appreciated as a greenhouse gas, water vapor impacts on the atmospheric transmission of solar radiation and the future of global dimming/brightening should not be overlooked.

P. Hanappe, A. Beurivé, F. Laguzet, L. Steels, N. Bellouin, O. Boucher, Y. H. Yamazaki, T. Aina, and M. Allen. FAMOUS, faster: using parallel computing techniques to accelerate the FAMOUS/HadCM3 climate model with a focus on the radiative transfer algorithm. Geoscientific Model Development, 4:835-844, September 2011. [ bib | DOI | ADS link ]

We have optimised the atmospheric radiation algorithm of the FAMOUS climate model on several hardware platforms. The optimisation involved translating the Fortran code to C and restructuring the algorithm around the computation of a single air column. Instead of the existing MPI-based domain decomposition, we used a task queue and a thread pool to schedule the computation of individual columns on the available processors. Finally, four air columns are packed together in a single data structure and computed simultaneously using Single Instruction Multiple Data operations. <BR /><BR /> The modified algorithm runs more than 50 times faster on the CELL's Synergistic Processing Element than on its main PowerPC processing element. On Intel-compatible processors, the new radiation code runs 4 times faster. On the tested graphics processor, using OpenCL, we find a speed-up of more than 2.5 times as compared to the original code on the main CPU. Because the radiation code takes more than 60 % of the total CPU time, FAMOUS executes more than twice as fast. Our version of the algorithm returns bit-wise identical results, which demonstrates the robustness of our approach. We estimate that this project required around two and a half man-years of work.

D. B. Clark, L. M. Mercado, S. Sitch, C. D. Jones, N. Gedney, M. J. Best, M. Pryor, G. G. Rooney, R. L. H. Essery, E. Blyth, O. Boucher, R. J. Harding, C. Huntingford, and P. M. Cox. The Joint UK Land Environment Simulator (JULES), model description - Part 2: Carbon fluxes and vegetation dynamics. Geoscientific Model Development, 4:701-722, September 2011. [ bib | DOI | ADS link ]

The Joint UK Land Environment Simulator (JULES) is a process-based model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Many studies have demonstrated the important role of the land surface in the functioning of the Earth System. Different versions of JULES have been employed to quantify the effects on the land carbon sink of climate change, increasing atmospheric carbon dioxide concentrations, changing atmospheric aerosols and tropospheric ozone, and the response of methane emissions from wetlands to climate change. <BR /><BR /> This paper describes the consolidation of these advances in the modelling of carbon fluxes and stores, in both the vegetation and soil, in version 2.2 of JULES. Features include a multi-layer canopy scheme for light interception, including a sunfleck penetration scheme, a coupled scheme of leaf photosynthesis and stomatal conductance, representation of the effects of ozone on leaf physiology, and a description of methane emissions from wetlands. JULES represents the carbon allocation, growth and population dynamics of five plant functional types. The turnover of carbon from living plant tissues is fed into a 4-pool soil carbon model. <BR /><BR /> The process-based descriptions of key ecological processes and trace gas fluxes in JULES mean that this community model is well-suited for use in carbon cycle, climate change and impacts studies, either in standalone mode or as the land component of a coupled Earth system model.

M. J. Best, M. Pryor, D. B. Clark, G. G. Rooney, R. L. H. Essery, C. B. Ménard, J. M. Edwards, M. A. Hendry, A. Porson, N. Gedney, L. M. Mercado, S. Sitch, E. Blyth, O. Boucher, P. M. Cox, C. S. B. Grimmond, and R. J. Harding. The Joint UK Land Environment Simulator (JULES), model description - Part 1: Energy and water fluxes. Geoscientific Model Development, 4:677-699, September 2011. [ bib | DOI | ADS link ]

This manuscript describes the energy and water components of a new community land surface model called the Joint UK Land Environment Simulator (JULES). This is developed from the Met Office Surface Exchange Scheme (MOSES). It can be used as a stand alone land surface model driven by observed forcing data, or coupled to an atmospheric global circulation model. The JULES model has been coupled to the Met Office Unified Model (UM) and as such provides a unique opportunity for the research community to contribute their research to improve both world-leading operational weather forecasting and climate change prediction systems. In addition JULES, and its forerunner MOSES, have been the basis for a number of very high-profile papers concerning the land-surface and climate over the last decade. JULES has a modular structure aligned to physical processes, providing the basis for a flexible modelling platform.

S. Verma, C. Venkataraman, and O. Boucher. Attribution of aerosol radiative forcing over India during the winter monsoon to emissions from source categories and geographical regions. Atmospheric Environment, 45:4398-4407, August 2011. [ bib | DOI | ADS link ]

We examine the aerosol radiative effects due to aerosols emitted from different emission sectors (anthropogenic and natural) and originating from different geographical regions within and outside India during the northeast (NE) Indian winter monsoon (January-March). These studies are carried out through aerosol transport simulations in the general circulation (GCM) model of the Laboratoire de Météorologie Dynamique (LMD). The model estimates of aerosol single scattering albedo (SSA) show lower values (0.86-0.92) over the region north to 10degN comprising of the Indian subcontinent, Bay of Bengal, and parts of the Arabian Sea compared to the region south to 10degN where the estimated SSA values lie in the range 0.94-0.98. The model estimated SSA is consistent with the SSA values inferred through measurements on various platforms. Aerosols of anthropogenic origin reduce the incoming solar radiation at the surface by a factor of 10-20 times the reduction due to natural aerosols. At the top-of-atmosphere (TOA), aerosols from biofuel use cause positive forcing compared to the negative forcing from fossil fuel and natural sources in correspondence with the distribution of SSA which is estimated to be the lowest (0.7-0.78) from biofuel combustion emissions. Aerosols originating from India and Africa-west Asia lead to the reduction in surface radiation (-3 to -8 W m -2) by 40-60% of the total reduction in surface radiation due to all aerosols over the Indian subcontinent and adjoining ocean. Aerosols originating from India and Africa-west Asia also lead to positive radiative effects at TOA over the Arabian Sea, central India (CNI), with the highest positive radiative effects over the Bay of Bengal and cause either negative or positive effects over the Indo-Gangetic plain (IGP).

N. Huneeus, M. Schulz, Y. Balkanski, J. Griesfeller, J. Prospero, S. Kinne, S. Bauer, O. Boucher, M. Chin, F. Dentener, T. Diehl, R. Easter, D. Fillmore, S. Ghan, P. Ginoux, A. Grini, L. Horowitz, D. Koch, M. C. Krol, W. Landing, X. Liu, N. Mahowald, R. Miller, J.-J. Morcrette, G. Myhre, J. Penner, J. Perlwitz, P. Stier, T. Takemura, and C. S. Zender. Global dust model intercomparison in AeroCom phase I. Atmospheric Chemistry & Physics, 11:7781-7816, August 2011. [ bib | DOI | ADS link ]

This study presents the results of a broad intercomparison of a total of 15 global aerosol models within the AeroCom project. Each model is compared to observations related to desert dust aerosols, their direct radiative effect, and their impact on the biogeochemical cycle, i.e., aerosol optical depth (AOD) and dust deposition. Additional comparisons to Angström exponent (AE), coarse mode AOD and dust surface concentrations are included to extend the assessment of model performance and to identify common biases present in models. These data comprise a benchmark dataset that is proposed for model inspection and future dust model development. There are large differences among the global models that simulate the dust cycle and its impact on climate. In general, models simulate the climatology of vertically integrated parameters (AOD and AE) within a factor of two whereas the total deposition and surface concentration are reproduced within a factor of 10. In addition, smaller mean normalized bias and root mean square errors are obtained for the climatology of AOD and AE than for total deposition and surface concentration. Characteristics of the datasets used and their uncertainties may influence these differences. Large uncertainties still exist with respect to the deposition fluxes in the southern oceans. Further measurements and model studies are necessary to assess the general model performance to reproduce dust deposition in ocean regions sensible to iron contributions. Models overestimate the wet deposition in regions dominated by dry deposition. They generally simulate more realistic surface concentration at stations downwind of the main sources than at remote ones. Most models simulate the gradient in AOD and AE between the different dusty regions. However the seasonality and magnitude of both variables is better simulated at African stations than Middle East ones. The models simulate the offshore transport of West Africa throughout the year but they overestimate the AOD and they transport too fine particles. The models also reproduce the dust transport across the Atlantic in the summer in terms of both AOD and AE but not so well in winter-spring nor the southward displacement of the dust cloud that is responsible of the dust transport into South America. Based on the dependency of AOD on aerosol burden and size distribution we use model bias with respect to AOD and AE to infer the bias of the dust emissions in Africa and the Middle East. According to this analysis we suggest that a range of possible emissions for North Africa is 400 to 2200 Tg yr-1 and in the Middle East 26 to 526 Tg yr-1.

O. Boucher. Atmospheric science: Seeing through contrails. Nature Climate Change, 1:24-25, April 2011. [ bib | DOI | ADS link ]

Contrails formed by aircraft can evolve into cirrus clouds indistinguishable from those formed naturally. These 'spreading contrails' may be causing more climate warming today than all the carbon dioxide emitted by aircraft since the start of aviation.

A. Mangold, H. de Backer, B. de Paepe, S. Dewitte, I. Chiapello, Y. Derimian, M. Kacenelenbogen, J.-F. LéOn, N. Huneeus, M. Schulz, D. Ceburnis, C. O'Dowd, H. Flentje, S. Kinne, A. Benedetti, J.-J. Morcrette, and O. Boucher. Aerosol analysis and forecast in the European Centre for Medium-Range Weather Forecasts Integrated Forecast System: 3. Evaluation by means of case studies. Journal of Geophysical Research (Atmospheres), 116:3302, February 2011. [ bib | DOI | ADS link ]

A near real-time system for assimilation and forecasts of aerosols, greenhouse and trace gases, extending the ECMWF Integrated Forecasting System (IFS), has been developed in the framework of the Global and regional Earth-system Monitoring using Satellite and in-situ data (GEMS) project. The GEMS aerosol modeling system is novel as it is the first aerosol model fully coupled to a numerical weather prediction model with data assimilation. A reanalysis of the period 2003-2009 has been carried out with the same system. During its development phase, the aerosol system was first run for the time period January 2003 to December 2004 and included sea salt, desert dust, organic matter, black carbon, and sulfate aerosols. In the analysis, Moderate Resolution Imaging Spectroradiometer (MODIS) total aerosol optical depth (AOD) at 550 nm over ocean and land (except over bright surfaces) was assimilated. This work evaluates the performance of the aerosol system by means of case studies. The case studies include (1) the summer heat wave in Europe in August 2003, characterized by forest fire aerosol and conditions of high temperatures and stagnation, favoring photochemistry and secondary aerosol formation, (2) a large Saharan dust event in March 2004, and (3) periods of high and low sea salt aerosol production. During the heat wave period in 2003, the linear correlation coefficients between modeled and observed AOD (550 nm) and between modeled and observed PM2.5 mass concentrations are 0.82 and 0.71, respectively, for all investigated sites together. The AOD is slightly and the PM2.5 mass concentration is clearly overestimated by the aerosol model during this period. The simulated sulfate mass concentration is significantly correlated with observations but is distinctly overestimated. The horizontal and vertical locations of the main features of the aerosol distribution during the Saharan dust outbreak are generally well captured, as well as the timing of the AOD peaks. The aerosol model simulates winter sea salt AOD reasonably well, however, showing a general overestimation. Summer sea salt events show a better agreement. Overall, the assimilation of MODIS AOD data improves the subsequent aerosol predictions when compared with observations, in particular concerning the correlation and AOD peak values. The assimilation is less effective in correcting a positive (PM2.5, sulfate mass concentration, Angström exponent) or negative (desert dust plume AOD) model bias.

T. Andrews, M. Doutriaux-Boucher, O. Boucher, and P. M. Forster. A regional and global analysis of carbon dioxide physiological forcing and its impact on climate. Climate Dynamics, 36:783-792, February 2011. [ bib | DOI | ADS link ]

An increase in atmospheric carbon dioxide concentration has both a radiative (greenhouse) effect and a physiological effect on climate. The physiological effect forces climate as plant stomata do not open as wide under enhanced CO2 levels and this alters the surface energy balance by reducing the evapotranspiration flux to the atmosphere, a process referred to as `carbon dioxide physiological forcing'. Here the climate impact of the carbon dioxide physiological forcing is isolated using an ensemble of twelve 5-year experiments with the Met Office Hadley Centre HadCM3LC fully coupled atmosphere-ocean model where atmospheric carbon dioxide levels are instantaneously quadrupled and thereafter held constant. Fast responses (within a few months) to carbon dioxide physiological forcing are analyzed at a global and regional scale. Results show a strong influence of the physiological forcing on the land surface energy budget, hydrological cycle and near surface climate. For example, global precipitation rate reduces by ˜3% with significant decreases over most land-regions, mainly from reductions to convective rainfall. This fast hydrological response is still evident after 5 years of model integration. Decreased evapotranspiration over land also leads to land surface warming and a drying of near surface air, both of which lead to significant reductions in near surface relative humidity (˜6%) and cloud fraction (˜3%). Patterns of fast responses consistently show that results are largest in the Amazon and central African forest, and to a lesser extent in the boreal and temperate forest. Carbon dioxide physiological forcing could be a source of uncertainty in many model predicted quantities, such as climate sensitivity, transient climate response and the hydrological sensitivity. These results highlight the importance of including biological components of the Earth system in climate change studies.

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