APM Pays Basque Petit Mars 2010

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  • FAQ 1.3, Figure 1. An idealised model of the natural greenhouse effect. See text for explanation.
  • FAQ 1.1, Figure 1. Estimate of the Earth’s annual and global mean energy balance. Over the long term, the amount of incoming solar radiation absorbed by the Earth and atmosphere is balanced by the Earth and atmosphere releasing the same amount of outgoing longwave radiation. About half of the incoming solar radiation is absorbed by the Earth’s surface. This energy is transferred to the atmosphere by warming the air in contact with the surface (thermals), by evapotranspiration and by longwave radiation that is absorbed by clouds and greenhouse gases. The atmosphere in turn radiates longwave energy back to Earth as well as out to space. Source: Kiehl and Trenberth (1997).
  • Figure 2.3. Recent CO 2 concentrations and emissions. (a) CO 2 concentrations (monthly averages) measured by continuous analysers over the period 1970 to 2005 from Mauna Loa, Hawaii (19°N, black; Keeling and Whorf, 2005) and Baring Head, New Zealand (41°S, blue; following techniques by Manning et al., 1997). Due to the larger amount of terrestrial biosphere in the NH, seasonal cycles in CO 2 are larger there than in the SH. In the lower right of the panel, atmospheric oxygen (O 2 ) measurements from flask samples are shown from Alert, Canada (82°N, pink) and Cape Grim, Australia (41°S, cyan) (Manning and Keeling, 2006). The O 2 concentration is measured as ‘per meg’ deviations in the O 2 /N 2 ratio from an arbitrary reference, analogous to the ‘per mil’ unit typically used in stable isotope work, but where the ratio is multiplied by 10 6 instead of 10 3 because much smaller changes are measured. (b) Annual global CO 2 emissions from fossil fuel burning and cement manufacture in GtC yr –1 (black) through 2005, using data from the CDIAC website (Marland et al, 2006) to 2003. Emissions data for 2004 and 2005 are extrapolated from CDIAC using data from the BP Statistical Review of World Energy (BP, 2006). Land use emissions are not shown; these are estimated to be between 0.5 and 2.7 GtC yr –1 for the 1990s (Table 7.2). Annual averages of the 13 C/ 12 C ratio measured in atmospheric CO 2 at Mauna Loa from 1981 to 2002 (red) are also shown (Keeling et al, 2005). The isotope data are expressed as δ 13 C(CO 2 ) ‰ (per mil) deviation from a calibration standard. Note that this scale is inverted to improve clarity.
  • Figure TS.6. (Top) Patterns of linear global temperature trends over the period 1979 to 2005 estimated at the surface (left), and for the troposphere from satellite records (right). Grey indicates areas with incomplete data. (Bottom) Annual global mean temperatures (black dots) with linear fits to the data. The left hand axis shows temperature anomalies relative to the 1961 to 1990 average and the right hand axis shows estimated actual temperatures, both in °C. Linear trends are shown for the last 25 (yellow), 50 (orange), 100 (magenta) and 150 years (red). The smooth blue curve shows decadal variations (see Appendix 3.A), with the decadal 90% error range shown as a pale blue band about that line. The total temperature increase from the period 1850 to 1899 to the period 2001 to 2005 is 0.76°C ± 0.19°C. {FAQ 3.1, Figure 1.}
  • Figure TS.22. Comparison of observed continental- and global-scale changes in surface temperature with results simulated by climate models using natural and anthropogenic forcings. Decadal averages of observations are shown for the period 1906 to 2005 (black line) plotted against the centre of the decade and relative to the corresponding average for 1901 to 1950. Lines are dashed where spatial coverage is less than 50%. Blue shaded bands show the 5% to 95% range for 19 simulations from 5 climate models using only the natural forcings due to solar activity and volcanoes. Red shaded bands show the 5% to 95% range for 58 simulations from 14 climate models using both natural and anthropogenic forcings. Data sources and models used are described in Section 9.4, FAQ 9.2, Table 8.1 and the supplementary information for Chapter 9. {FAQ 9.2, Figure 1}
  • Figure 1.1. Yearly global average surface temperature (Brohan et al., 2006), relative to the mean 1961 to 1990 values, and as projected in the FAR (IPCC, 1990), SAR (IPCC, 1996) and TAR (IPCC, 2001a). The ‘best estimate’ model projections from the FAR and SAR are in solid lines with their range of estimated projections shown by the shaded areas. The TAR did not have ‘best estimate’ model projections but rather a range of projections. Annual mean observations (Section 3.2) are depicted by black circles and the thick black line shows decadal variations obtained by smoothing the time series using a 13-point filter.
  • Figure TS.18. Annual averages of the global mean sea level based on reconstructed sea level fields since 1870 (red), tide gauge measurements since 1950 (blue) and satellite altimetry since 1992 (black). Units are in mm relative to the average for 1961 to 1990. Error bars are 90% confidence intervals. {Figure 5.13}
  • B1 and A1B have similar population projections – ca 7 billion at 2100. A2 population more than double at 15 billion. GDP/capita is 47k$, 75k$, 16k$ for B1, A1B, A2.
  • Figure SPM.5. Solid lines are multi-model global averages of surface warming (relative to 1980–1999) for the scenarios A2, A1B and B1, shown as continuations of the 20th century simulations. Shading denotes the ±1 standard deviation range of individual model annual averages. The orange line is for the experiment where concentrations were held constant at year 2000 values. The grey bars at right indicate the best estimate (solid line within each bar) and the likely range assessed for the six SRES marker scenarios. The assessment of the best estimate and likely ranges in the grey bars includes the AOGCMs in the left part of the figure, as well as results from a hierarchy of independent models and observational constraints. {Figures 10.4 and 10.29}
  • Figure SPM.7. Relative changes in precipitation (in percent) for the period 2090–2099, relative to 1980–1999. Values are multi-model averages based on the SRES A1B scenario for December to February (left) and June to August (right). White areas are where less than 66% of the models agree in the sign of the change and stippled areas are where more than 90% of the models agree in the sign of the change. {Figure 10.9}
  • FAQ 5.1, Figure 1. Time series of global mean sea level (deviation from the 1980-1999 mean) in the past and as projected for the future. For the period before 1870, global measurements of sea level are not available. The grey shading shows the uncertainty in the estimated long-term rate of sea level change (Section 6.4.3). The red line is a reconstruction of global mean sea level from tide gauges (Section, and the red shading denotes the range of variations from a smooth curve. The green line shows global mean sea level observed from satellite altimetry. The blue shading represents the range of model projections for the SRES A1B scenario for the 21st century, relative to the 1980 to 1999 mean, and has been calculated independently from the observations. Beyond 2100, the projections are increasingly dependent on the emissions scenario (see Chapter 10 for a discussion of sea level rise projections for other scenarios considered in this report). Over many centuries or millennia, sea level could rise by several metres (Section 10.7.4).
  • Figure 11.19. Annual cycle of arctic area mean temperature and percentage precipitation changes (averaged over the area north of 60°N) for 2080 to 2099 minus 1980 to 1999, under the A1B scenario. Thick lines represent the ensemble median of the 21 MMD models. The dark grey area represents the 25 and 75% quartile values among the 21 models, while the light grey area shows the total range of the models.
  • Figure 11.20. Relationship between the change in annual precipitation (%) and temperature (°C) (2080–2099 minus 1980–1999) in the Arctic (averaged over the area north of 60°N) in the MMD-A1B projections. Each point represents one model. The model ensemble mean response is indicated by the circle.
  • Figure 11.21. Annual surface temperature change between 1980 to 1999 and 2080 to 2099 in the Arctic and Antarctic from the MMD-A1B projections.
  • APM Pays Basque Petit Mars 2010

    1. 1. Le changement climatique, provoqué par les activités humaines   Michel PETIT Ancien représentant de la France dans le Bureau du GIEC 5 février 2010
    2. 2. PLAN 1.Comprendre la physique du climat 2. Conséquences du changement climatique 3. Changements climatiques à venir 4. La maîtrise du changement climatique
    3. 3. 1. Comprendre la physique du climat
    4. 4. FAQ 1.3, Figure 1
    5. 5. FAQ 1.1, Figure 1
    6. 6. Forçage glaciaire et réponses Last Ice age Last interglacial
    7. 7. Meilleures et plus longues séries temporelles pour le rayonnement solaire <ul><li>AR4 Evaluation: </li></ul><ul><li>Pas de tendance observée dans l’irradiance solaire depuis 1978 Informations spectrales </li></ul><ul><li>Forçage solaire nettement inférieur au forçage du aux gaz à effet de serre serre. </li></ul>
    8. 8. Explosive Volcanic Eruptions: Proof of Fast-Response Climate Change Due to Forcing Changing forcing changes the temperature (and water vapor, etc.). If volcanoes can cool, then GHG must warm….
    9. 9. Atmosphère et révolution industrielle Les concentrations actuelles des principaux gaz à effet de serre et leur taux de croissance sont sans précédent. Dioxide de carbone Méthane Oxyde Nitreux
    10. 10. Utilisation des combustibles fossiles et concentration du CO 2
    11. 11. Figure 2.3 Variations simultanées de la concentration de CO 2 et de O 2 Composition isotopique du nouveau carbone
    12. 12. Le réchauffement est sans équivoque Température atmosphérique croissante Elévation du niveau des mers Réduction de la couverture neigeuse (NH) Et dans l’océan.. Et la haute atmosphère ….
    13. 14. Figure TS.6
    14. 15. La vapeur d’eau répond au changement climatique, elle n’est pas le moteur du changement climatique. C’est une rétroaction majeure qui amplifie le changement climatique. Nouveau dans l’AR4 (2007): Observations qui montrent la tendance à la fois dans la haute troposphère et à la surface. Rétroaction vapeur d’eau
    15. 16. Moteurs naturels et anthropiques du changement climatique Le dioxyde de carbone est le « big player ». En moyenne, il a un temps de vie de plusieurs centaines d’années dans l’atmosphère, et affecte donc le climat sur de longues échelles de temps.
    16. 17. Figure TS.22
    17. 18. Figure 1.1
    18. 19. 2. Conséquences du changement climatique
    19. 20. Figure TS.18 L Le niveau moyen de la mer
    20. 21. Le niveau moyen de la mer par altimétrie satellitaire
    21. 22. Montée du niveau de la mer 1993-2003 <ul><li>Dilatation thermique </li></ul><ul><li>Glaciers & calottes glaciaires </li></ul><ul><li>Groenland </li></ul><ul><li>Antarctique </li></ul><ul><li>Total </li></ul><ul><li>Observé </li></ul><ul><li>Observé-Total </li></ul>1,6 +/-0,5 (mm/an) 0,77 +/-0,22 (mm/an) 0,21 +/-0,07 (mm/an) 0,21 +/-0,35 (mm/an) 2,8 +/-0,7 (mm/an) 3,1 +/-0.7 (mm/an) 0,3 +/-1,0 (mm/an )
    22. 23. Changements physiques & biologiques
    23. 24. Mortalité en France en 2003
    24. 25. 3. Changements climatiques à venir
    25. 26. Emissions de gaz à effet de serre (GES)
    26. 27. Scenarios d’émissions
    27. 28. Les concentrations de CO 2 attendues au cours du XXIème siècle sont deux à quatre fois celles de l’ère préindustrielle
    28. 29. What ’ s in the pipeline and what could come Warming will increase if GHG increase. If GHG were kept fixed at current levels, a committed 0.6°C of further warming would be expected by 2100. More warming would accompany more emission. 1.8 o C = 3.2 o F 2.8 o C = 5.0 o F 3.4 o C = 6.1 o F CO2 Eq 850 600 400 0.6 o C = 1.0 o F
    29. 30. Figure SPM.5 Augmentations projetées de température
    30. 32. Variations des précipitations
    31. 33. FAQ 5.1, Figure 1 Va Variations projetées du niveau de la mer
    32. 34. VULNERABILITE AU NIVEAU DE LA MER <ul><li>les zones urbaines côtières peu élevées, en </li></ul><ul><li>particulier celles qui sont sujettes à affaissement </li></ul><ul><li>les petites îles, en particulier les atolls coralliens </li></ul><ul><li>les deltas, avec 300 millions d’habitants vivant dans 40 d’entre eux, en particulier les sept grands deltas asiatiques avec une population totale dépassant déjà les 200 millions et celui du Nil où la densité est la plus élevée </li></ul>
    33. 35. Relative vulnerability of coastal deltas as indicated by estimates of the population potentially displaced by current sea-level trends to 2050 (extreme > 1 million, high 50 000 to 1 million, medium 5000 to 50 000) D Deltas côtiers
    34. 36. Productivité agricole
    35. 39. Figure 11.19 Températures & précipitations en Arctique
    36. 40. Figure 11.20 Précipitations & températures arctiques
    37. 41. Figure 11.21 Augmentations de la T° en Arctique & Antarctique
    38. 42. Evolution de la géographie
    39. 43. Conséquences du changement climatique
    40. 44. Evolution des risques
    41. 47. 4. Maîtrise du changement climatique
    42. 48. Variations depuis 1970 ….
    43. 49. La concentration en CO 2 , la température et le niveau de la mer continuent à croître longtemps après que les émissions aient été réduites
    44. 50. La stabilisation de la concentration en gaz carbonique exige une réduction importante des émissions
    45. 51. S Scenario de stabilisation de la concentration
    46. 52. Le carbone fossile
    47. 53. Energie primaire
    48. 54. Emissions de CO 2
    49. 55. Gaz à Effet de Serre
    50. 56. Contribution des divers secteurs
    51. 57. 10 milliards de tonnes par an en « équivalent pétrole » Pétrole Gaz Charbon Bois,… Nucléaire Hydro Renouv 35% 21% 23,5% 6,8%
    52. 58. Emissions & rendements
    53. 59. Technology <ul><li>The range of stabilization levels can be achieved by </li></ul><ul><ul><li>deployment of a portfolio of technologies that are currently available and </li></ul></ul><ul><ul><li>those that are expected to be commercialised in coming decades. </li></ul></ul><ul><li>This assumes that appropriate and effective incentives are in place for development, acquisition, deployment and diffusion of technologies and for addressing related barriers </li></ul>
    54. 62. TIC & Développement durable – CoS AFNOR – 15 octobre 2009 TIC et Développement durable ( Etude Smart 2020)
    55. 63. <ul><li>La téléprésence (travail à distance à domicile ou dans des télécentres), - permet d’économiser des transports - permet d’améliorer la qualité de vie professionnelle - participe à l’aménagement du territoire - mais nécessite une couverture du territoire en haut voire très haut débit (téléréunions professionnelles de haute qualité) </li></ul><ul><li>Actions proposées: - Soutien au démarrage des télécentres - Normalisation des interfaces, - Etat exemplaire vitrine du télétravail </li></ul>DETIC – CGIET Section T&S – 12 novembre 2009 Développer la téléprésence
    56. 64. <ul><li>Développer les bâtiments intelligents </li></ul><ul><li>La maquette numérique des bâtiments et des quartiers permet une conception optimisée des bâtiments - Meilleure isolation, économie de chauffage - Meilleure conception de la ville donc économie de transports - Meilleur pilotage des équipements (capteurs, compteurs intelligents) donc économie d’électricité. </li></ul><ul><li>Encourager les acteurs à définir le concept de réseaux domiciliaires, et à définir leurs interfaces avec les différents équipements impliqués (dont les compteurs intelligents) </li></ul>DETIC – CGIET Section T&S – 12 novembre 2009 Recommandations spécifiques
    57. 65. <ul><li>Dans le secteur du bâtiment, contrôler la consommation d’électricité </li></ul><ul><li>Promouvoir le contrôle de la consommation électrique par le déploiement massif d’outils intelligents de mesure, d’affichage et de pilotage de la consommation des appartements, immeubles et quartiers - réseaux domiciliaires - capteurs interconnectés par des interfaces standardisées - affichage simple des consommations usage par usage </li></ul>DETIC – CGIET Section T&S – 12 novembre 2009 Recommandations spécifiques
    58. 66. <ul><li>Optimiser le transport et la logistique </li></ul><ul><li>Promouvoir la dématérialisation sans couture de la chaine d’information logistique, en intégrant les étiquettes électroniques (RFID) </li></ul>DETIC – CGIET Section T&S – 12 novembre 2009 Recommandations spécifiques
    59. 67. <ul><li>Avoir une démarche analytique sur l’empreinte Carbone de l’entreprise </li></ul><ul><li>Evaluer l’empreinte carbone de l’entreprise </li></ul><ul><li>Contribuer (notamment au niveau européen) au développement d’outils de mesure pour des comparaisons entre entreprises et intégrer l’empreinte carbone complète (production et usage) des équipements et services TIC dans une étude d’impact approfondie en vue d’un développement durable </li></ul>DETIC – CGIET Section T&S – 12 novembre 2009 Recommandations spécifiques
    60. 68. <ul><li>Dématérialisation </li></ul><ul><li>Généraliser la dématérialisation de toutes les chaines d’échange d’informations, contrats ou document administratifs (travail sur les outils d’authentification, l’interopérabilité, et les standards d’échange) </li></ul>DETIC – CGIET Section T&S – 12 novembre 2009 Recommandations spécifiques
    61. 69. Mitigation potential <ul><li>Economic potential: </li></ul><ul><ul><li>takes into account social costs and benefits and social discount rates, </li></ul></ul><ul><ul><li>assuming that market efficiency is improved by policies and measures and </li></ul></ul><ul><ul><li>barriers are removed </li></ul></ul><ul><li>Market potential: </li></ul><ul><ul><li>based on private costs and private discount rates </li></ul></ul><ul><ul><li>expected to occur under forecast market conditions </li></ul></ul><ul><ul><li>including policies and measures currently in place </li></ul></ul><ul><ul><li>noting that barriers limit actual uptake </li></ul></ul>
    62. 70. Comparison between global economic mitigation potential and projected emissions increase in 2030
    63. 71. Economic mitigation potentials by sectors in 2030 from bottom up studies
    64. 72. What are the macro-economic costs in 2030? [1] This is global GDP based market exchange rates. [2] The median and the 10 th and 90 th percentile range of the analyzed data are given. [3] The calculation of the reduction of the annual growth rate is based on the average reduction during the period till 2030 that would result in the indicated GDP decrease in 2030. [4] The number of studies that report GDP results is relatively small and they generally use low baselines. <ul><li>Costs are global average for least cost appoaches from top-down models </li></ul><ul><li>Costs do not include co-benefits and avoided climate change damages </li></ul>< 0.12 < 3 Not available 445-535 [4] <0.1 0.2 – 2.5 0.6 535-590 < 0.06 -0.6 – 1.2 0.2 590-710 Reduction of average annual GDP growth rates [3] (percentage points) Range of GDP reduction [2] (%) Median GDP reduction [1] (%) Trajectories towards stabilization levels (ppm CO 2 -eq)
    65. 73. Illustration of cost numbers GDP without mitigation GDP with stringent mitigation GDP Time 80% current 77% ~1 year
    66. 74. Eruptions volcaniques: Preuves de la réponse rapide du climat à un forçage Le forçage « volcan » change la température (la vapeur d’eau,…). Si les volcans peuvent refroidir, alors, les GES doivent réchauffer…