Apresentação de Resultados do IPCC AR4 WG1

Jose A. MarengoCPTEC/INPE

OUTLINE FOR THE IPCC WORKING GROUP I CONTRIBUTION TOTHE FOURTH ASSESSMENT REPORT CLIMATE CHANGE 2007: THE PHYSICAL SCIENCE BASIS

Summary for Policymakers

Technical Summary

1. Historical Overview of Climate Change Science

2. Changes in Atmospheric Constituents and in Radiative Forcing

3. Observations: Surface and Atmospheric Climate Change

4. Observations: Changes in Snow, Ice and Frozen Ground

5. Observations: Oceanic Climate Change and Sea Level

6. Paleoclimate

7. Couplings Between Changes in the Climate System and Biogeochemistry

8. Climate Models and their Evaluation

9. Understanding and Attributing Climate Change

10. Global Climate Projections

11. Regional Climate Projections

Geographic resolution characteristic of the generations of climate models used in the IPCC Assessment Reports: FAR (1990), SAR (1996), TAR (2001), and AR4 (2007). The

Chapter 1

1990

1996

2001

2007

The complexity of climate models has increased over the last few decades. This is shown pictorially by the different features of the world included in the models.

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Chapter 3

Annual averages of the global mean sea level based on the reconstructed sea level fields since 1870 (red curve, updated from Church and White, 2006) and on tide gauges measurements since 1950 (blue curve, from Holgate and Woodworth, 2004). Units are in mm. The blue curve has been shifted by 20 mm for clarity.

Chapter 5

Variations in global mean sea level computed from satellite altimetry from January 1993 to October 2005, averaged over 65°S-65°N. Dots are 10-day estimates (from Topex/Poseidon satellite in red and Jason in green). The blue solid curve corresponds to 60-day smoothing and the straight line is the best fitting linear trend (of 2.9 ± 0.4 mm/yr and 3.2 ± 0.4 mm/yr without and with the GIA correction). Updated from Cazenave and Nerem (2004) and Leuliette et al. (2004).

Chapter 5

Estimates of the various contributions to the budget of the global mean sea level change compared with the observed rate of rise for 1961–2003 (blue) and 1993–2003 (red). The bars represent 95% errors. The errors of the separate terms have been combined in quadrature to obtain the error on their sum. Chapter 5

Time-series of global mean sea level in the past and future, relative to zero in 2001. For the period before 1870, we do not have global measurements of sea level. The solid line here is a climate model calculation (Gregory et al., 2006) of sea level change due to natural factors (volcanic and solar variability) and anthropogenic factors; the rather sudden fall early in the 19th century is mainly due to the eruption of Tambora in 1815. The grey shading shows the uncertainty on the estimated long-term rate of sea level change. We show a reconstruction of global mean sea-level from tide gauges (Church and White, 2006, Section 5.5.2.1) for 1870-2001, with uncertainties shown by shading, and from satellite altimetry (Cazenave and Nerem, 2004, Section 5.5.2.2) for 1993–2004, both as annual means. For the future we indicate the range of uncertainty due to different choices of emission scenarios. Beyond 2100 the projections are increasingly dependent on the scenario. Over many centuries or millennia, sea level could rise by several metres Chapter 6

Paleoclimate information supports the interpretation that the warmth of the last half century is unusual in at least the previous 1300 years. The last time the polar regions were significantly warmer than present for an extended period (about 125,000 years ago), reductions in polar ice volume led to 4 to 6 metres of sea level rise. Chapter 6

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Decadal mean global near surface temperatures over the 20th century from observations (black), and showing the approximate 5–95% range from IPCC AR4 model simulations with natural and anthropogenic forcings (red). Also shown is the corresponding temperature range when models are driven by natural forcings only (blue). Temperature anomalies are centred relative to the 1901–1997 mean.

Chapter 8

Forçante natural

Forçante natural+antropogenica

Global mean temperature anoamlies, as observed (black line, HadCRUT2v, Parker et al., 2004) and as modelled by a range of climate models when the simulations include (a) both anthropogenic and natural forcings and (b) natural forcings only. The multimodel ensemble mean is shown in grey, and individual simulations are shown in colour, with curves of the same colour indicating different ensemble members for the same model.

Chapter 9

Forçante natural+antropogenica

Forçante natural

OBSV

OBSV

Trends in observed and simulated temperature changes over the 1901–2005 (left column) and 1979–2005 (right column) periods. Note scales are different between columns.

Chapter 9

Comparison of IPCC AR4 C20C3M model simulations containing all forcings (red shaded regions) and IPCC AR4 C20C3M model simulations containing natural forcings only (blue shaded regions) with the observed (HadCRUT2v, Parker et al., 2004) Chapter 9

Chapter 9

Solid lines are multi-model global averages of surface warming (relative to 1980-99) for the scenarios A2, A1B and B1, shown as continuations of the 20th century simulations. Shading denotes the plus/minusone standard deviation range of individual model annual means. The number of AOGCMs run for a given time period and scenario is indicated by the coloured numbers at the bottom part of the panel. Chapter 10

Multi-model mean of annual mean surface warming (surface air temperature change, in °C) for the scenarios B1 (top), A1B (middle) and A2 (bottom), and three time periods, 2011–2030 (left), 2046–2065 (middle), and 2080–2099 (right). Stippling denotes regions where the multi-model ensemble mean exceeds the intermodel standard deviation. Anomalies are given relative to the average of the period 1980–1999.

Chapter 10

Multi-model mean changes of surface air temperature (°C, left), precipitation (mm/day, middle), and sea level pressure (hPa, right) for boreal winter (DJF, top) and summer (JJA, bottom). Changes are given for the scenarios SRES A1B, for the period 2080–2099 relative to 1980–1999. Stippling denotes areas where the magnitude of the multi-model ensemble mean exceeds the inter-model standard deviation. Chapter 10

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.

Chapter 10

Multi model mean changes in a) precipitation (mm/day), b) soil moisture content (%), c) runoff (kg/m2s), and d) evaporation (mm/day). Note that “soil moisture content” is the best estimate of this quantity supplied by each model, but calculations vary across models. Changes are given as annual means for the scenarios SRES A1B, for the period 2080–2099 relative to 1980–1999. Stippling denotes areas where the magnitude of the multi-model ensemble mean exceeds the inter-model standard deviation. Chapter 10

Changes in extremes based on multi-model simulations from nine global coupled climate models, adapted from Tebaldi et al. (2006). a) Globally averaged changes in precipitation intensity (defined as the annual total precipitation divided by the number of wet days) for a low (SRES B1), middle (SRES A1B), and high (SRES A2) scenario. b) Changes of spatial patterns of precipitation intensity based on simulations between two 20-year means (2080–2099 minus 1980–1999) for the A1B scenario. c) Globally averaged changes in dry days (defined as the annual maximum number of consecutive dry days). d) changes of spatial patterns of dry days based on simulations between two 20-year means (2080–2099 minus 1980–1999) for the A1B scenario. Chapter 10

Extremos climáticos

Chapter 10

Extremos climáticos

Warming for Central America, Amazonaz and southern South American regions for: 1900–2000 as observed (black line) and as simulated (red envelope); and for 2001–2100 as simulated for the A1B emission scenario (green envelope). The set of AR4 AOGCM simulations used for both periods are only those with all forcings in the 20th century (eleven simulations).

Chapter 11

Consensus AR4 GCM A1B temperature and precipitation changes over Central and South America. Top row: Annual mean, December-January-February, and June-July-August temperature change between 1980–1999 in the 20C3M simulations and 2080-2099 in A1B, averaged over 21 models. Middle row: same for fractional change in precipitation. Bottom row: number of models out of 21 that project precipitation to increase.

Chapter 11

2080-99 A1B – 1980-99 20C3M

Annual DJF JJA

2080-99 A1B – 1980-99 20C3M

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