ALBERT

Description: Microbes are dominant drivers of biogeochemical processes, yet drawing a global picture of functional diversity, microbial community structure, and their ecological determinants remains a grand challenge. We analyzed 7.2 terabases of metagenomic data from 243 Tara Oceans samples from 68 locations in epipelagic and mesopelagic waters across the globe to generate an ocean microbial reference gene catalog with 〉40 million nonredundant, mostly novel sequences from viruses, prokaryotes, and picoeukaryotes. Using 139 prokaryote-enriched samples, containing 〉35,000 species, we show vertical stratification with epipelagic community composition mostly driven by temperature rather than other environmental factors or geography. We identify ocean microbial core functionality and reveal that 〉73% of its abundance is shared with the human gut microbiome despite the physicochemical differences between these two ecosystems.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Sunagawa, Shinichi -- Coelho, Luis Pedro -- Chaffron, Samuel -- Kultima, Jens Roat -- Labadie, Karine -- Salazar, Guillem -- Djahanschiri, Bardya -- Zeller, Georg -- Mende, Daniel R -- Alberti, Adriana -- Cornejo-Castillo, Francisco M -- Costea, Paul I -- Cruaud, Corinne -- d'Ovidio, Francesco -- Engelen, Stefan -- Ferrera, Isabel -- Gasol, Josep M -- Guidi, Lionel -- Hildebrand, Falk -- Kokoszka, Florian -- Lepoivre, Cyrille -- Lima-Mendez, Gipsi -- Poulain, Julie -- Poulos, Bonnie T -- Royo-Llonch, Marta -- Sarmento, Hugo -- Vieira-Silva, Sara -- Dimier, Celine -- Picheral, Marc -- Searson, Sarah -- Kandels-Lewis, Stefanie -- Tara Oceans coordinators -- Bowler, Chris -- de Vargas, Colomban -- Gorsky, Gabriel -- Grimsley, Nigel -- Hingamp, Pascal -- Iudicone, Daniele -- Jaillon, Olivier -- Not, Fabrice -- Ogata, Hiroyuki -- Pesant, Stephane -- Speich, Sabrina -- Stemmann, Lars -- Sullivan, Matthew B -- Weissenbach, Jean -- Wincker, Patrick -- Karsenti, Eric -- Raes, Jeroen -- Acinas, Silvia G -- Bork, Peer -- New York, N.Y. -- Science. 2015 May 22;348(6237):1261359. doi: 10.1126/science.1261359.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Structural and Computational Biology, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany. sunagawa@embl.de karsenti@embl.de jeroen.raes@vib-kuleuven.be sacinas@icm.csic.es bork@embl.de. ; Structural and Computational Biology, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany. ; Department of Microbiology and Immunology, Rega Institute, KU Leuven, Herestraat 49, 3000 Leuven, Belgium. Center for the Biology of Disease, VIB, Herestraat 49, 3000 Leuven, Belgium. Department of Applied Biological Sciences, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. ; CEA-Institut de Genomique, GENOSCOPE, 2 rue Gaston Cremieux, 91057 Evry, France. ; Department of Marine Biology and Oceanography, Institute of Marine Sciences (ICM)-CSIC, Pg. Maritim de la Barceloneta, 37-49, Barcelona E08003, Spain. ; Sorbonne Universites, UPMC, Universite Paris 06, CNRS-IRD-MNHN, LOCEAN Laboratory, 4 Place Jussieu, 75005 Paris France. ; CNRS, UMR 7093, Laboratoire d'Oceanographie de Villefranche-sur-Mer, Observatoire Oceanologique, F-06230 Villefranche-sur-mer, France. Sorbonne Universites, UPMC Universite Paris 06, UMR 7093, LOV, Observatoire Oceanologique, F-06230 Villefranche-sur-mer, France. ; Ecole Normale Superieure, Institut de Biologie de l'ENS (IBENS), and Inserm U1024, and CNRS UMR 8197, F-75005 Paris, France. Laboratoire de Physique des Oceans UBO-IUEM, Place Copernic 29820 Plouzane, France. ; Aix Marseille Universite CNRS IGS UMR 7256, 13288 Marseille, France. ; Department of Ecology and Evolutionary Biology, University of Arizona, 1007 East Lowell Street, Tucson, AZ 85721, USA. ; Department of Marine Biology and Oceanography, Institute of Marine Sciences (ICM)-CSIC, Pg. Maritim de la Barceloneta, 37-49, Barcelona E08003, Spain. Department of Hydrobiology, Federal University of Sao Carlos (UFSCar), Rodovia Washington Luiz, 13565-905 Sao Carlos, Sao Paulo, Brazil. ; Ecole Normale Superieure, Institut de Biologie de l'ENS (IBENS), and Inserm U1024, and CNRS UMR 8197, F-75005 Paris, France. CNRS, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. Sorbonne Universites, UPMC Universite Paris 06, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. ; Structural and Computational Biology, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany. Directors' Research, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany. ; Ecole Normale Superieure, Institut de Biologie de l'ENS (IBENS), and Inserm U1024, and CNRS UMR 8197, F-75005 Paris, France. ; CNRS, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. Sorbonne Universites, UPMC Universite Paris 06, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. ; CNRS UMR 7232, BIOM, Avenue du Fontaule, 66650 Banyuls-sur-Mer, France. Sorbonne Universites Paris 06, OOB UPMC, Avenue du Fontaule, 66650 Banyuls-sur-Mer, France. ; Stazione Zoologica Anton Dohrn, Villa Comunale, 80121 Naples, Italy. ; CEA-Institut de Genomique, GENOSCOPE, 2 rue Gaston Cremieux, 91057 Evry, France. CNRS, UMR 8030, CP5706, Evry, France. Universite d'Evry, UMR 8030, CP5706, Evry, France. ; Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, 611-001, Japan. ; PANGAEA, Data Publisher for Earth and Environmental Science, University of Bremen, Bremen, Germany. MARUM, Center for Marine Environmental Sciences, University of Bremen, Bremen, Germany. ; Department of Geosciences, Laboratoire de Meteorologie Dynamique (LMD), Ecole Normale Superieure, 24 rue Lhomond, 75231 Paris Cedex 05, France. Laboratoire de Physique des Oceans UBO-IUEM, Place Copernic, 29820 Plouzane, France. ; Ecole Normale Superieure, Institut de Biologie de l'ENS (IBENS), and Inserm U1024, and CNRS UMR 8197, F-75005 Paris, France. Directors' Research, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany. sunagawa@embl.de karsenti@embl.de jeroen.raes@vib-kuleuven.be sacinas@icm.csic.es bork@embl.de. ; Department of Microbiology and Immunology, Rega Institute, KU Leuven, Herestraat 49, 3000 Leuven, Belgium. Center for the Biology of Disease, VIB, Herestraat 49, 3000 Leuven, Belgium. Department of Applied Biological Sciences, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. sunagawa@embl.de karsenti@embl.de jeroen.raes@vib-kuleuven.be sacinas@icm.csic.es bork@embl.de. ; Department of Marine Biology and Oceanography, Institute of Marine Sciences (ICM)-CSIC, Pg. Maritim de la Barceloneta, 37-49, Barcelona E08003, Spain. sunagawa@embl.de karsenti@embl.de jeroen.raes@vib-kuleuven.be sacinas@icm.csic.es bork@embl.de. ; Structural and Computational Biology, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany. Max-Delbruck-Centre for Molecular Medicine, 13092 Berlin, Germany. sunagawa@embl.de karsenti@embl.de jeroen.raes@vib-kuleuven.be sacinas@icm.csic.es bork@embl.de.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25999513" target="_blank"〉PubMed〈/a〉

Description: Marine plankton support global biological and geochemical processes. Surveys of their biodiversity have hitherto been geographically restricted and have not accounted for the full range of plankton size. We assessed eukaryotic diversity from 334 size-fractionated photic-zone plankton communities collected across tropical and temperate oceans during the circumglobal Tara Oceans expedition. We analyzed 18S ribosomal DNA sequences across the intermediate plankton-size spectrum from the smallest unicellular eukaryotes (protists, 〉0.8 micrometers) to small animals of a few millimeters. Eukaryotic ribosomal diversity saturated at ~150,000 operational taxonomic units, about one-third of which could not be assigned to known eukaryotic groups. Diversity emerged at all taxonomic levels, both within the groups comprising the ~11,200 cataloged morphospecies of eukaryotic plankton and among twice as many other deep-branching lineages of unappreciated importance in plankton ecology studies. Most eukaryotic plankton biodiversity belonged to heterotrophic protistan groups, particularly those known to be parasites or symbiotic hosts.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉de Vargas, Colomban -- Audic, Stephane -- Henry, Nicolas -- Decelle, Johan -- Mahe, Frederic -- Logares, Ramiro -- Lara, Enrique -- Berney, Cedric -- Le Bescot, Noan -- Probert, Ian -- Carmichael, Margaux -- Poulain, Julie -- Romac, Sarah -- Colin, Sebastien -- Aury, Jean-Marc -- Bittner, Lucie -- Chaffron, Samuel -- Dunthorn, Micah -- Engelen, Stefan -- Flegontova, Olga -- Guidi, Lionel -- Horak, Ales -- Jaillon, Olivier -- Lima-Mendez, Gipsi -- Lukes, Julius -- Malviya, Shruti -- Morard, Raphael -- Mulot, Matthieu -- Scalco, Eleonora -- Siano, Raffaele -- Vincent, Flora -- Zingone, Adriana -- Dimier, Celine -- Picheral, Marc -- Searson, Sarah -- Kandels-Lewis, Stefanie -- Tara Oceans Coordinators -- Acinas, Silvia G -- Bork, Peer -- Bowler, Chris -- Gorsky, Gabriel -- Grimsley, Nigel -- Hingamp, Pascal -- Iudicone, Daniele -- Not, Fabrice -- Ogata, Hiroyuki -- Pesant, Stephane -- Raes, Jeroen -- Sieracki, Michael E -- Speich, Sabrina -- Stemmann, Lars -- Sunagawa, Shinichi -- Weissenbach, Jean -- Wincker, Patrick -- Karsenti, Eric -- New York, N.Y. -- Science. 2015 May 22;348(6237):1261605. doi: 10.1126/science.1261605.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉CNRS, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. Sorbonne Universites, Universite Pierre et Marie Curie (UPMC) Paris 06, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. vargas@sb-roscoff.fr pwincker@genoscope.cns.fr karsenti@embl.de. ; CNRS, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. Sorbonne Universites, Universite Pierre et Marie Curie (UPMC) Paris 06, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. ; Department of Ecology, University of Kaiserslautern, Erwin-Schroedinger Street, 67663 Kaiserslautern, Germany. CNRS, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. Sorbonne Universites, Universite Pierre et Marie Curie (UPMC) Paris 06, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. ; Department of Marine Biology and Oceanography, Institute of Marine Science (ICM)-Consejo Superior de Investigaciones Cientificas (CSIC), Passeig Maritim de la Barceloneta 37-49, Barcelona E08003, Spain. ; Laboratory of Soil Biology, University of Neuchatel, Rue Emile-Argand 11, 2000 Neuchatel, Switzerland. ; CNRS, FR2424, Roscoff Culture Collection, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. Sorbonne Universites, UPMC Paris 06, FR 2424, Roscoff Culture Collection, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. ; CNRS, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. Sorbonne Universites, Universite Pierre et Marie Curie (UPMC) Paris 06, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. Ecole Normale Superieure, Institut de Biologie de l'ENS (IBENS), and Inserm U1024, and CNRS UMR 8197, Paris, F-75005 France. ; Commissariat a l'Energie Atomique et aux Energies Alternatives (CEA), Institut de Genomique, GENOSCOPE, 2 rue Gaston Cremieux, 91000 Evry, France. ; CNRS FR3631, Institut de Biologie Paris-Seine, F-75005, Paris, France. Sorbonne Universites, UPMC Paris 06, Institut de Biologie Paris-Seine, F-75005, Paris, France. Ecole Normale Superieure, Institut de Biologie de l'ENS (IBENS), and Inserm U1024, and CNRS UMR 8197, Paris, F-75005 France. CNRS, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. Sorbonne Universites, Universite Pierre et Marie Curie (UPMC) Paris 06, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. ; Department of Microbiology and Immunology, Rega Institute, KU Leuven, Herestraat 49, 3000 Leuven, Belgium. Center for the Biology of Disease, VIB, Herestraat 49, 3000 Leuven, Belgium. Department of Applied Biological Sciences, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. ; Department of Ecology, University of Kaiserslautern, Erwin-Schroedinger Street, 67663 Kaiserslautern, Germany. ; Institute of Parasitology, Biology Centre, Czech Academy of Sciences, Branisovska 31, 37005 Ceske Budejovice, Czech Republic. Faculty of Science, University of South Bohemia, Branisovska 31, 37005 Ceske Budejovice, Czech Republic. ; CNRS, UMR 7093, Laboratoire d'Oceanographie de Villefranche-sur-Mer (LOV), Observatoire Oceanologique, F-06230, Villefranche-sur-Mer, France. Sorbonne Universites, UPMC Paris 06, UMR 7093, LOV, Observatoire Oceanologique, F-06230, Villefranche-sur-Mer, France. ; Commissariat a l'Energie Atomique et aux Energies Alternatives (CEA), Institut de Genomique, GENOSCOPE, 2 rue Gaston Cremieux, 91000 Evry, France. CNRS, UMR 8030, CP5706, Evry, France. Universite d'Evry, UMR 8030, CP5706, Evry, France. ; Institute of Parasitology, Biology Centre, Czech Academy of Sciences, Branisovska 31, 37005 Ceske Budejovice, Czech Republic. Faculty of Science, University of South Bohemia, Branisovska 31, 37005 Ceske Budejovice, Czech Republic. Canadian Institute for Advanced Research, 180 Dundas Street West, Suite 1400, Toronto, Ontario M5G 1Z8, Canada. ; Ecole Normale Superieure, Institut de Biologie de l'ENS (IBENS), and Inserm U1024, and CNRS UMR 8197, Paris, F-75005 France. ; MARUM, Center for Marine Environmental Sciences, University of Bremen, 28359 Bremen, Germany. CNRS, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. Sorbonne Universites, Universite Pierre et Marie Curie (UPMC) Paris 06, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680 Roscoff, France. ; Stazione Zoologica Anton Dohrn, Villa Comunale, 80121 Naples, Italy. ; Ifremer, Centre de Brest, DYNECO/Pelagos CS 10070, 29280 Plouzane, France. ; Center for the Biology of Disease, VIB, Herestraat 49, 3000 Leuven, Belgium. Ecole Normale Superieure, Institut de Biologie de l'ENS (IBENS), and Inserm U1024, and CNRS UMR 8197, Paris, F-75005 France. ; Structural and Computational Biology, European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, 69117 Heidelberg, Germany. Directors' Research, EMBL, Meyerhofstrasse 1, 69117 Heidelberg, Germany. ; Structural and Computational Biology, European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, 69117 Heidelberg, Germany. Max-Delbruck-Centre for Molecular Medicine, 13092 Berlin, Germany. ; CNRS UMR 7232, Biologie Integrative des Organismes Marins (BIOM), Avenue du Fontaule, 66650 Banyuls-sur-Mer, France. Sorbonne Universites Paris 06, Observatoire Oceanologique de Banyuls (OOB) UPMC, Avenue du Fontaule, 66650 Banyuls-sur-Mer, France. ; Aix Marseille Universite, CNRS IGS UMR 7256, 13288 Marseille, France. ; Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, 611-0011, Japan. ; PANGAEA, Data Publisher for Earth and Environmental Science, University of Bremen, Bremen, Germany. MARUM, Center for Marine Environmental Sciences, University of Bremen, 28359 Bremen, Germany. ; Bigelow Laboratory for Ocean Sciences, East Boothbay, ME 04544, USA. National Science Foundation, Arlington, VA 22230, USA. ; Department of Geosciences, Laboratoire de Meteorologie Dynamique (LMD), Ecole Normale Superieure, 24 rue Lhomond, 75231 Paris Cedex 05, France. Laboratoire de Physique des Oceans, Universite de Bretagne Occidentale (UBO)-Institut Universitaire Europeen de la Mer (IUEM), Place Copernic, 29820 Plouzane, France. ; Structural and Computational Biology, European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, 69117 Heidelberg, Germany. ; Commissariat a l'Energie Atomique et aux Energies Alternatives (CEA), Institut de Genomique, GENOSCOPE, 2 rue Gaston Cremieux, 91000 Evry, France. CNRS, UMR 8030, CP5706, Evry, France. Universite d'Evry, UMR 8030, CP5706, Evry, France. vargas@sb-roscoff.fr pwincker@genoscope.cns.fr karsenti@embl.de. ; Directors' Research, EMBL, Meyerhofstrasse 1, 69117 Heidelberg, Germany. Ecole Normale Superieure, Institut de Biologie de l'ENS (IBENS), and Inserm U1024, and CNRS UMR 8197, Paris, F-75005 France. vargas@sb-roscoff.fr pwincker@genoscope.cns.fr karsenti@embl.de.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25999516" target="_blank"〉PubMed〈/a〉

Description: The International Continental Scientific Drilling Program (ICDP) has long espoused studies of deep subsurface life, and has targeted fundamental questions regarding subsurface life, including the following: "(1) What is the extent and diversity of deep microbial life and what are the factors limiting it? (2) What are the types of metabolism/carbon/energy sources and the rates of subsurface activity? (3) How is deep microbial life adapted to subsurface conditions? (4) How do subsurface microbial communities affect energy resources? And (5) how does the deep biosphere interact with the geosphere and atmosphere?" (Horsfield et al., 2014) Many ICDP-sponsored drilling projects have included a deep-life component; however, to date, not one project has been driven by deep-life goals, in part because geomicrobiologists have been slow to initiate deep biosphere-driven ICDP projects. Therefore, the Deep Carbon Observatory (DCO) recently partnered with the ICDP to sponsor a workshop with the specific aim of gathering potential proponents for deep-life-driven ICDP projects and ideas for candidate drilling sites. Twenty-two participants from nine countries proposed projects and sites that included compressional and extensional tectonic environments, evaporites, hydrocarbon-rich shales, flood basalts, Precambrian shield rocks, subglacial and subpermafrost environments, active volcano–tectonic systems, megafan deltas, and serpentinizing ultramafic environments. The criteria and requirements for successful ICDP applications were presented. Deep-life-specific technical requirements were discussed and it was concluded that, while these procedures require adequate planning, they are entirely compatible with the sampling needs of other disciplines. As a result of this workshop, one drilling workshop proposal on the Basin and Range Physiographic Province (BRPP) has been submitted to the ICDP, and several other drilling project proponents plan to submit proposals for ICDP-sponsored drilling workshops in 2016.

Description: This paper describes the pre-operational analysis and forecasting system developed during MACC (Monitoring Atmospheric Composition and Climate) and continued in MACC-II (Monitoring Atmospheric Composition and Climate: Interim Implementation) European projects to provide air quality services for the European continent. The paper gives an overall picture of its status at the end of MACC-II (summer 2014). This system is based on seven state-of-the art models developed and run in Europe (CHIMERE, EMEP, EURAD-IM, LOTOS-EUROS, MATCH, MOCAGE and SILAM). These models are used to calculate multi-model ensemble products. The MACC-II system provides daily 96 h forecasts with hourly outputs of 10 chemical species/aerosols (O3, NO2, SO2, CO, PM10, PM2.5, NO, NH3, total NMVOCs and PAN + PAN precursors) over 8 vertical levels from the surface to 5 km height. The hourly analysis at the surface is done a posteriori for the past day using a selection of representative air quality data from European monitoring stations. The performances of the system are assessed daily, weekly and 3 monthly (seasonally) through statistical indicators calculated using the available representative air quality data from European monitoring stations. Results for a case study show the ability of the median ensemble to forecast regional ozone pollution events. The time period of this case study is also used to illustrate that the median ensemble generally outperforms each of the individual models and that it is still robust even if two of the seven models are missing. The seasonal performances of the individual models and of the multi-model ensemble have been monitored since September 2009 for ozone, NO2 and PM10 and show an overall improvement over time. The change of the skills of the ensemble over the past two summers for ozone and the past two winters for PM10 are discussed in the paper. While the evolution of the ozone scores is not significant, there are improvements of PM10 over the past two winters that can be at least partly attributed to new developments on aerosols in the seven individual models. Nevertheless, the year to year changes in the models and ensemble skills are also linked to the variability of the meteorological conditions and of the set of observations used to calculate the statistical indicators. In parallel, a scientific analysis of the results of the seven models and of the ensemble is also done over the Mediterranean area because of the specificity of its meteorology and emissions. The system is robust in terms of the production availability. Major efforts have been done in MACC-II towards the operationalisation of all its components. Foreseen developments and research for improving its performances are discussed in the conclusion.

Description: The eruption of Mount Tambora (Indonesia) in April 1815 is the largest documented volcanic eruption in history. It is associated with a large global cooling during the following year, felt particularly in parts of Europe and North America, where the year 1816 became known as the "year without a summer". This paper describes an effort made to collect surface meteorological observations from the early instrumental period, with a focus on the years of and immediately following the eruption (1815–1817). Although the collection aimed in particular at pressure observations, correspondent temperature observations were also recovered. Some of the series had already been described in the literature, but a large part of the data, recently digitised from original weather diaries and contemporary magazines and newspapers, is presented here for the first time. The collection puts together more than 50 sub-daily series from land observatories in Europe and North America and from ships in the tropics. The pressure observations have been corrected for temperature and gravity and reduced to mean sea level. Moreover, an additional statistical correction was applied to take into account common error sources in mercury barometers. To assess the reliability of the corrected data set, the variance in the pressure observations is compared with modern climatologies, and single observations are used for synoptic analyses of three case studies in Europe. All raw observations will be made available to the scientific community in the International Surface Pressure Databank.

Description: The eruption of Mount Tambora (Indonesia) in April 1815 is the largest documented volcanic eruption in history. It caused a large global cooling during the following year, felt particularly in parts of Europe and North America, where the year 1816 became known as the "year without a summer". This paper describes an effort made to collect surface meteorological observations from the early instrumental period, with a focus on the years immediately following the eruption (1815–1817). Although the collection aimed in particular at pressure observations, correspondent temperature observations were also recovered. Some of the series had already been described in the literature, but a large part of the data, recently digitised from original weather diaries and contemporary magazines and newspapers, is presented here for the first time. The collection puts together more than fifty sub-daily series from land observatories in Europe and North America, and from ships in the tropics. The pressure observations have been corrected for temperature and gravity and reduced to mean sea level, moreover an additional statistical correction was applied to take into account common error sources in mercury barometers. To assess the reliability of the corrected dataset, the variance of the pressure observations is compared with modern climatologies and single observations are used for synoptic analyses of three case studies in Europe. All raw observations will be made available to the scientific community in the International Surface Pressure Databank.

Description: Daily global analyses and 5 day forecasts are generated in the context of the European Monitoring Atmospheric Composition and Climate (MACC) project using an extended version of the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). IFS now includes modules for chemistry, deposition and emission of reactive gases, aerosols, and greenhouse gases, and the 4-dimensional variational data assimilation scheme makes use of multiple satellite observations of atmospheric composition in addition to meteorological observations. This paper describes the data assimilation setup of the new Composition-IFS (C-IFS) with respect to reactive gases and validates analysis fields of ozone (O3), carbon monoxide (CO), and nitrogen dioxide (NO2) for the year 2008 against independent observations and a control run without data assimilation. The largest improvement in CO by assimilation of MOPITT CO columns is seen in the lower troposphere of the Northern Hemisphere (NH) Extratropics during winter, and during the South African biomass burning season. The assimilation of several O3 total column and stratospheric profile retrievals greatly improves the total column, stratospheric and upper tropospheric O3 analysis fields relative to the control run. The impact on lower tropospheric ozone, which comes from the residual of the total column and stratospheric profile O3 data, is smaller, but nevertheless there is some improvement particularly in the NH during winter and spring. The impact of the assimilation of OMI tropospheric NO2 columns is small because of the short lifetime of NO2, suggesting that NO2 observations would be better used to adjust emissions instead of initial conditions. The results further indicate that the quality of the tropospheric analyses and of the stratospheric ozone analysis obtained with the C-IFS system has improved compared to the previous "coupled" model system of MACC.

Description: The European MACC (Monitoring Atmospheric Composition and Climate) project is preparing the operational Copernicus Atmosphere Monitoring Service (CAMS), one of the services of the European Copernicus Programme on Earth observation and environmental services. MACC uses data assimilation to combine in situ and remote sensing observations with global and regional models of atmospheric reactive gases, aerosols, and greenhouse gases, and is based on the Integrated Forecasting System of the European Centre for Medium-Range Weather Forecasts (ECMWF). The global component of the MACC service has a dedicated validation activity to document the quality of the atmospheric composition products. In this paper we discuss the approach to validation that has been developed over the past 3 years. Topics discussed are the validation requirements, the operational aspects, the measurement data sets used, the structure of the validation reports, the models and assimilation systems validated, the procedure to introduce new upgrades, and the scoring methods. One specific target of the MACC system concerns forecasting special events with high-pollution concentrations. Such events receive extra attention in the validation process. Finally, a summary is provided of the results from the validation of the latest set of daily global analysis and forecast products from the MACC system reported in November 2014.

Description: This paper describes the pre-operational analysis and forecasting system developed during MACC (Monitoring Atmospheric Composition and Climate) and continued in the MACC-II (Monitoring Atmospheric Composition and Climate: Interim Implementation) European projects to provide air quality services for the European continent. This system is based on seven state-of-the art models developed and run in Europe (CHIMERE, EMEP, EURAD-IM, LOTOS-EUROS, MATCH, MOCAGE and SILAM). These models are used to calculate multi-model ensemble products. The paper gives an overall picture of its status at the end of MACC-II (summer 2014) and analyses the performance of the multi-model ensemble. The MACC-II system provides daily 96 h forecasts with hourly outputs of 10 chemical species/aerosols (O3, NO2, SO2, CO, PM10, PM2.5, NO, NH3, total NMVOCs (non-methane volatile organic compounds) and PAN+PAN precursors) over eight vertical levels from the surface to 5 km height. The hourly analysis at the surface is done a posteriori for the past day using a selection of representative air quality data from European monitoring stations. The performance of the system is assessed daily, weekly and every 3 months (seasonally) through statistical indicators calculated using the available representative air quality data from European monitoring stations. Results for a case study show the ability of the ensemble median to forecast regional ozone pollution events. The seasonal performances of the individual models and of the multi-model ensemble have been monitored since September 2009 for ozone, NO2 and PM10. The statistical indicators for ozone in summer 2014 show that the ensemble median gives on average the best performances compared to the seven models. There is very little degradation of the scores with the forecast day but there is a marked diurnal cycle, similarly to the individual models, that can be related partly to the prescribed diurnal variations of anthropogenic emissions in the models. During summer 2014, the diurnal ozone maximum is underestimated by the ensemble median by about 4 μg m−3 on average. Locally, during the studied ozone episodes, the maxima from the ensemble median are often lower than observations by 30–50 μg m−3. Overall, ozone scores are generally good with average values for the normalised indicators of 0.14 for the modified normalised mean bias and of 0.30 for the fractional gross error. Tests have also shown that the ensemble median is robust to reduction of ensemble size by one, that is, if predictions are unavailable from one model. Scores are also discussed for PM10 for winter 2013–1014. There is an underestimation of most models leading the ensemble median to a mean bias of −4.5 μg m−3. The ensemble median fractional gross error is larger for PM10 (~ 0.52) than for ozone and the correlation is lower (~ 0.35 for PM10 and ~ 0.54 for ozone). This is related to a larger spread of the seven model scores for PM10 than for ozone linked to different levels of complexity of aerosol representation in the individual models. In parallel, a scientific analysis of the results of the seven models and of the ensemble is also done over the Mediterranean area because of the specificity of its meteorology and emissions. The system is robust in terms of the production availability. Major efforts have been done in MACC-II towards the operationalisation of all its components. Foreseen developments and research for improving its performances are discussed in the conclusion.

Description: A representation of atmospheric chemistry has been included in the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The new chemistry modules complement the aerosol modules of the IFS for atmospheric composition, which is named C-IFS. C-IFS for chemistry supersedes a coupled system in which chemical transport model (CTM) Model for OZone and Related chemical Tracers 3 was two-way coupled to the IFS (IFS-MOZART). This paper contains a description of the new on-line implementation, an evaluation with observations and a comparison of the performance of C-IFS with MOZART and with a re-analysis of atmospheric composition produced by IFS-MOZART within the Monitoring Atmospheric Composition and Climate (MACC) project. The chemical mechanism of C-IFS is an extended version of the Carbon Bond 2005 (CB05) chemical mechanism as implemented in CTM Transport Model 5 (TM5). CB05 describes tropospheric chemistry with 54 species and 126 reactions. Wet deposition and lightning nitrogen monoxide (NO) emissions are modelled in C-IFS using the detailed input of the IFS physics package. A 1 year simulation by C-IFS, MOZART and the MACC re-analysis is evaluated against ozonesondes, carbon monoxide (CO) aircraft profiles, European surface observations of ozone (O3), CO, sulfur dioxide (SO2) and nitrogen dioxide (NO2) as well as satellite retrievals of CO, tropospheric NO2 and formaldehyde. Anthropogenic emissions from the MACC/CityZen (MACCity) inventory and biomass burning emissions from the Global Fire Assimilation System (GFAS) data set were used in the simulations by both C-IFS and MOZART. C-IFS (CB05) showed an improved performance with respect to MOZART for CO, upper tropospheric O3, and wintertime SO2, and was of a similar accuracy for other evaluated species. C-IFS (CB05) is about 10 times more computationally efficient than IFS-MOZART.