IPCC Workgroup 1IPCC Workgroup 1Assessment Report 4 (AR4)Assessment Report 4 (AR4)

Pedro Leite da Silva Dias (*)Pedro Leite da Silva Dias (*) Instituto de Astronomia Geofísica e Ciências AtmosféricasInstituto de Astronomia Geofísica e Ciências Atmosféricas

Universidade de São PauloUniversidade de São Paulo

(*) Diretor Científico da SBMET(*) Diretor Científico da SBMET

1. Historical Overview of Climate Change Science• Progress in observations• Progress in understanding of radiative forcing, processes, and coupling• Progress in climate modeling• Advances in understanding uncertainties• Appendix: Glossary of terms

2. Changes in Atmospheric Constituents and in Radiative Forcing• Definition and utility of radiative forcing• Recent changes in greenhouse gases• Aerosols – Direct and indirect radiative forcing• Radiative forcing due to land use changes• Contrails and aircraft-induced cirrus• Variability in solar and volcanic radiative forcing• Synthesis of radiative forcing factors• GWPs and other metrics for comparing different emissions• Appendix: Techniques, error estimation, andmeasurement systems

3. Observations: Surface and Atmospheric Climate Change• Changes in surface climate• Changes in the free atmosphere• Changes in atmospheric circulation• Patterns of variability• Changes in the tropics and sub-tropics• Extra-tropical changes• Changes in extreme events• Synthesis: Consistency across observations• Appendix: Techniques, error estimation, andmeasurement systems

4. Observations: Changes in Snow, Ice and Frozen Ground• Changes in snow cover and albedo• Sea ice extent and thickness changes• Changes in glaciers and small ice caps• Changes and stability of ice shelves• Changes and stability of ice sheets• Changes in frozen ground• Appendix: Techniques, error estimation, and measurement systems

5. Observations: Oceanic Climate Change and Sea Level• Changes in ocean salinity, temperature, heat Uptake, and heat content• Biogeochemical tracers• Changes in ocean circulation and water mass formation• Sea Level: Global and regional changes• Appendix: Techniques, error estimation, and measurement systems

6. Paleoclimate• Proxy methods and their uncertainty• Inferred past climate system change• Abrupt climate change• Paleoenvironmental model evaluation and sensitivity• Synthesis: Insights into climate system behavior• Appendix: Guide to the use of paleoclimatic information

7. Couplings Between Changes in the Climate System and Biogeochemistry• Introduction to biogeochemical cycles• The carbon cycle and the climate system• Global atmospheric chemistry and climate change• Air quality and climate change• Aerosols and climate change• The changing land surface and climate• Synthesis: Interactions among cycles and processes

8. Climate Models and their Evaluation• Advances in modeling• Evaluation of contemporary climate as simulated by coupled global models• Evaluation of large scale climate variability as simulated by coupled global models• Evaluation of the key relevant processes as simulated by coupled global models• Model simulations of extremes• Climate sensitivity• Evaluation of model simulations of thresholds and abrupt events• Representing the global system with simpler models

9. Understanding and Attributing Climate Change• Radiative forcing and climate response• Seasonal-to-interannual predictions of climate change and their reliability• Understanding Pre-Industrial climate change• Understanding climate change during the Instrumental era• Appendix: Methods used to assess predictability• Appendix: Methods used to detect externally forced signals (detection/attribution)

10. Global Climate Projections• Projected radiative forcing• Timescales of response• Climate change to 2100 and beyond• Sea level projections• Scenarios and simple models• Uncertainties in global model projections

11. Regional Climate Projections• Evaluation of regionalization methods• Alternative simple methods• Projections of regional climate changes• Small islands• Uncertainties in regional projections

IPCC Work Group 1 Assessment Report AR4 Outline

Time evolution in global average atmospheric surface temperature as projected in the IPCC First Assessment Report or FAR (1990) and Second Assessment Report or SAR (1996), compared with observations. Figure 1.1 Best estimated model projections from the FAR and SAR are in solid lines with their range of estimated projections shown by the shaded areas. Annual mean observations are depicted by the thin magenta line, and a smoothed estimate from a 13-point binomial filter is shown by the thick magenta line (see Chapter 3 for more information about this filter).

. 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.

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

Schematic view of the components of the climate system, their processes and interactions.

The Earth’s annual and global mean energy balance. Source: Kiehl and Trenberth (1997).

Figure 7.3. The global carbon (dioxide) cycle for the 1990s, showing main annual fluxes in GtC yr–1: preindustrial 'natural' fluxes in black and 'anthropogenic' fluxes in red. Modified from Sarmiento and Gruber (2002), with changes in poolsizes from Sabine et al. (2004a). The net terrestrial loss of –39 GtC is inferred from cumulative (fossil fuel emissions – atmospheric increase – ocean storage). The loss of –140 GtC from the 'Vegetation, Soil & detritus' compartment represents the cumulative emissions from land use change (Houghton, 2003), and requires a terrestrial biosphere sink of 101 GtC (in Sabine et al., given only as ranges of -140 to -180 GtC and 61 to 141 GtC respectively; other uncertainties given in their Table 1). Net anthropogenic exchanges with the atmosphere are taken from column 5 'AR4' in Table 7.1. Gross fluxes generally have uncertainties of more than ±20% but fractional amounts have been retained to achieve overall balance when including estimates in fractions of GtC yr–1 for riverine

transport, weathering, deep ocean burial, etc. 'GPP' is annual gross (terrestrial) primary production.

4AR Schematic representation of the multiple interactions between tropospheric chemical processes, biogeochemical cycles and the climate system. RF represents radiative forcing, UV ultraviolet radiation, and T temperature.

Global-average radiative forcing (RF) estimates and ranges in 2005 for anthropogenic carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O) and other important agents and mechanisms, together with the typical geographical extent (spatial scale) of the forcing and the assessed level of scientific understanding (LOSU). The net anthropogenic radiative forcing and its range are also shown. These require summing asymmetric uncertainty estimates from the component terms, and cannot be obtained by simple addition. Volcanic aerosols contribute an additional natural forcing but are not included in this figure due to their episodic nature.

Air holds more water vapor at Air holds more water vapor at higher temperatureshigher temperatures

Total water vaporTotal water vapor

Observations show that this is happening at the surface and in lower atmosphere: 0.55C since 1970 over global oceans and 4% more water vapor.

This means more moisture available for storms and an enhanced greenhouse effect.

Observations show that this is happening at the surface and in lower atmosphere: 0.55C since 1970 over global oceans and 4% more water vapor.

This means more moisture available for storms and an enhanced greenhouse effect.

A basic physical law tells us that the water holding capacity of the atmosphere goes up at about 7% per degree Celsius increase in temperature.

A basic physical law tells us that the water holding capacity of the atmosphere goes up at about 7% per degree Celsius increase in temperature.

How should precipitation P How should precipitation P change as the climate change as the climate

changeschanges?? With increased GHGs: increased surface heating

evaporation E and P With increased aerosols, E and P Net global effect is small and complex

With increased GHGs: increased surface heating evaporation E and P

With increased aerosols, E and P Net global effect is small and complex

Warming and T means water vapor as observed Because precipitation comes from storms gathering

up available moisture, rain and snow intensity : widely observed

But this must reduce lifetime and frequency of storms

Result: wet areas get wetter, dry areas drier

Warming and T means water vapor as observed Because precipitation comes from storms gathering

up available moisture, rain and snow intensity : widely observed

But this must reduce lifetime and frequency of storms

Result: wet areas get wetter, dry areas drier

Global Warming is unequivocal

Global Warming is unequivocal

Since 1970, rise in: Decrease in: Global surface temperatures NH Snow extent Tropospheric temperatures Arctic sea ice Global SSTs, ocean Ts Glaciers Global sea level Cold temperatures Water vapor Rainfall intensity Precipitation extratropics Hurricane intensity Drought Extreme high temperatures Heat waves

Since 1970, rise in: Decrease in: Global surface temperatures NH Snow extent Tropospheric temperatures Arctic sea ice Global SSTs, ocean Ts Glaciers Global sea level Cold temperatures Water vapor Rainfall intensity Precipitation extratropics Hurricane intensity Drought Extreme high temperatures Heat waves

More details …

Points

Long-term record, esp. CO2, CH4

N2O record not as continuous

Long-lived greenhouse gas records approximately equivalent to global mixing ratio values

Temperature record is more local to AntarcticaChange in carbon dioxide, methane and nitrous oxide

concentrations over last 650,000 years, from Antarctic ice cores, and recent atmospheric measurements. A temperature proxy timeseries is also shown.

Change in carbon dioxide, methane and nitrous oxideconcentrations and radiative forcingover last 10,000 years, and (inset) from 1750-2005 [Figure SPM-1].

Increase since 1750 is unprecedented in record

CO2 radiative forcing has increased by 20% in last 10 years

CO2

CH4

N2O

North-South CO2 gradient is related to fossil fuel emissions [Figure 7.5]

Oxygen and carbon isotope record show anthropogenic cause [Figure 2.3]

Carbon dioxide increases are due to anthropogenic Carbon dioxide increases are due to anthropogenic emissionsemissions

Global fossil fuel CO2 emissions are increasing

CO2 chemically stable long-lived well-mixed

Temporal evolution of the majorHalocarbons [Figure 2.6]

Some species (CFC-11, CFC-12) flattening or going down because of Protocols Some species (HCFC-22, SF6) increasingOverall slight increase in halocarbon radiative forcing since the time of the TARNot elucidated on in SPM, as recently evaluated in IPCC/TEAP (2005) report

Timescales

• Timescales vary for the different RF agents• For CO2, there are a host of processes involved,

which gives rise to a range of values corresponding to several different lifetimes

difficult thus to characterize CO2’s lifetime by a single value.

Similar problems for other species e.g., CH4.

Determination of CombinedAnthropogenic RF

• Derive central estimate and range for the individual terms

• Uncertainty assumed to be represented by a normal distribution and 90% confidence interval.

• Some of the agents have an asymmetric range about the central estimate: tropospheric ozone, direct aerosol and cloud-albedo aerosol effects

• Performed Monte Carlo calculations to derive a probability density function for the combined anthropogenic radiative forcing estimate

Computing Radiative ForcingComputing Radiative Forcing[1750-2005][1750-2005]

• Long-Lived Greenhouse Gases (LLGHGs): Use the observed record, together with radiative transfer calculations, to determine the Radiative Forcing.

• For other species e.g., aerosols, tropospheric ozone, observations are less extensive, there is more spatial inhomogeneity.Other methods e.g., three-dimensional chemistry-transport models, together with relevant observations, used to determine the Radiative Forcing.

Since the TAR, improved understanding and better quantification of the forcing mechanisms

Aerosol Direct and Indirect ForcingsAerosol Direct and Indirect Forcings

• Global observations available only over the past approximately 25 years.

• Models used that describe the transport and distribution of aerosols based on natural and anthropogenic emissions.

Aerosol species:Sulphate, nitrate, fossil fuel organic carbon, fossil fuel black carbon, biomass burning, mineral dust, sea salt

(‘red’ = significant anthropogenic component)

Aerosol-cloud

interactionsOnly the change of cloud albedo induced by aerosols in the context of liquid water clouds, is considered to be radiative forcing

Other processes are not considered as radiative forcings. However, they are included in climate models that explicitly consider the relevant processes

Aerosol effects on ice clouds are poorly understood, and are not quantified.

Aerosol cloud interactions [Figure 7.20]

Total aerosol optical depth (natural+anthropogenic components) at mid-visible wavelength, from satellite instruments, and complemented

by two different kinds of ground-based measurements [Figure TS-4 (top)]

Observations reveal the presence and provide quantitative aspects. Aerosol transport-forcing models better tested and constrained. More improved estimate of the Aerosol Direct Radiative Forcing.

January to March, 2001

Estimates of the Aerosol Direct Radiative Forcing (sulphate, fossil fuel black and organic carbon, biomass burning, dust and nitrate) from different models [Fig. 2.13]

More models that contain aerosol species beyond sulphate

Observations used to apply constraints to combined aerosol direct radiative forcing

Best estimate-0.5 W/m2

Range:-0.9 to -0.1

W/m2

Estimates of the Cloud Albedo radiative forcing due to aerosols from different models [Figure 2.14]

More model studies since the TAR, many include more species

Those with more aerosol species or constrained by satellite observations have a weaker radiative forcing

Best estimate:-0.7 W/m2

Range:-1.8 to -0.3 W/m2

Computed Radiative Forcing due to Tropospheric Ozone change sincepre-industrial times, based on Chemistry-Transport and GCM

Best estimate and range based on better modelingMEDIUM level of scientific understanding

Best est.:0.35 W/m2

Range:0.25 to 65

W/m2

Reconstruction of the Total Solar Irradiance [Figure 2.17]

New reconstruction yields smaller solar radiative forcing estimate than in the TAR- based on: a) solar magnetic flux model rather than proxy data; b) better understanding of recent variations; c) re-evaluation of variations in Sun-like stars

Revised solar radiative forcing much smaller than long-lived greenhouse gas forcing since pre-industrial times

Solar indirect effects on stratospheric ozone not included

Best estimate: 0.12 W/m2

Range: 0.06 to 0.30 W/m2

Visible optical depth from stratospheric sulphate aerosols in theaftermath of explosive volcanic eruptions [Fig. 2.18]

Explosive volcanic eruptions are episodic. Aerosols from an explosive volcanic eruption are transitory (lasting ~1-2 years).

Other points raised for Other points raised for clarityclarity

• Galactic cosmic rays: Not-evaluated - no proven physical mechanism, and studies comparing with changes in global cloud cover are inconsistent.

• Aviation: Linear contrails radiative forcing only evaluated. Aviation induced cirrus too uncertain to quantify. Other aviation effects implicitly included in other radiative forcing terms.

• Water vapour is a powerful greenhouse gas, but changes are associated with the climate response/feedback and not included on the forcing “bar-plot” [Fig. SPM-2]. Climate models include this feedback in their evaluation of temperature changes

Radiative Forcing of Climate [1750 to 2005]Radiative Forcing of Climate [1750 to 2005]

Best estimate and range for individual terms; ranges given by 90% confidence interval.

Note differences in spatial scale

Time-scale: varies between mechanisms;difficult to characterize CO2’s lifetime by a single value.

RADIATIVE FORCING (RF) COMPONENTS{Global-average estimates and ranges; typical geographical

extent and assessed level of scientific understanding}

Combining anthropogenic forcing estimatesCombining anthropogenic forcing estimates

•Combined anthropogenic forcing is not straight sum of individual terms.•Tropospheric ozone, cloud-albedo, contrails asymmetric range about the central estimate•Uncertainties for the agents represented by normal distributions except: contrail (lognormal); discrete values trop. ozone, direct aerosol, cloud albedo•Monte Carlo calculations to derive probability density functions for the combined effect•Only derived for the global-mean

Combining anthropogenic forcing estimatesCombining anthropogenic forcing estimates

Fig. 2.20

Figure TS-5 (Panel B)

Combined anthropogenic forcing is not straight sum of individual terms.

Tropospheric ozone, cloud-albedo, contrails asymmetric range about the central estimate

Uncertainties for the agents represented by normal distributions except: contrail (lognormal); discrete values trop. ozone, direct aerosol (sulphate, fossil fuel black and organic carbon, biomass burning), cloud albedo

Monte Carlo calculations to derive probability density functions for the combined effect

Only derived for the global-mean

Illustrative examples of the instantaneous change in the spatial distribution of the RF and surface forcing due

to natural+anthropogenic forcings between 1860 and 2000

LLGHG forcing dominates the top-of-the-atmosphere change Surface forcing has features different from RFSpatial patterns of forcing are not indicative of the climate response pattern

A global cloud-resolving AGCM3.5 km-grid model

10-day integrationin ~2 elapsed dayson 320 ES nodes

t = 15 sec

Changes in key global climate parameters since 1973, compared to the scenarios of the IPCC [shown as dashed lines (A1FI, light blue; A1B, purple; A1T, blue; A2, red; B1, yellow; and B2, green) and gray ranges in all panels]. (a) Monthly carbon dioxide concentration and its trend line at Mauna Loa, Hawaii (blue) up to January 2007, from Scripps in collaboration with NOAA. (b) Annual global-mean land and ocean combined surface temperature from GISS (red) and the Hadley Centre (blue) up to 2006, with their trends. (c) Sea-level data based primarily on tide gauges (annual, red) and from satellite altimeter (blue) and their trends. All trends are non-linear trend lines and are computed with an embedding period of 11 years and a minimum roughness criterion at the end, except for the satellite altimeter where a linear trend was used because of the shortness of the series. For temperature and sea level, data are shown as deviations from the trend-line value in 1990, the base year of the IPCC scenarios.

Previous IPCC projections have not Previous IPCC projections have not exaggerated but may in some respects even exaggerated but may in some respects even have underestimated the change.have underestimated the change.

Science, Feb 2007

Aerosol-Cloud Interactions

• Only the change of albedo induced by aerosols in the context of liquid water clouds, is considered to be RFG

• Other processes such as “semi-direct effect”, “lifetime effect”, are not considered as RFs. However, there are included in climate models that explicitly consider the relevant processes.

• Aerosol effects on ice clouds are poorly understood and are not quantified.

ENSO as viewed from different models

Carbon dynamics and feedbacks: land and ocean

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Changes in global atmospheric CO2 concentrations: (a) annual changes (bars) and 5-yr means (black lines),of global CO2 concentrations, from Scripps Institution of Oceanography observations (mean of South Pole and Mauna Loa; Keeling and Whorf, 2004, updated); (upper –): annual increases that would occur if 100% of fossil fuel emissions (Marland et al, 2006, updated as described in Ch. 2) stayed in the atmosphere; and (red line) 5-yr mean annual increases from NOAA data (mean of Samoa and Mauna Loa, Conway and Tans, 2004, updated); (b) Fraction of fossil fuel emissions remaining in the atmosphere each year (“Airborne fraction”, l), 5-yr mean (line –) (Scripps data), and mean since 1958 (---). Note (¯) the anomalously low airborne fraction

in the early 1990s.

The 4°x5° estimates of sea-to-air flux of CO2 shown here have been computed using 940,000 measurements of surface water pCO2 collected since 1956 and averaged monthly, together with NCEP/NCAR 41-year mean monthly wind speeds and a (10-m wind speed)2 dependence on the gas transfer rate (Wanninkhof, 1992). The fluxes have been normalized to the year 1995, using techniques described in Takahashi et al. (2002), who had used wind speeds taken at the 0.995 sigma level (about 40 m above the sea surface). The annual flux of CO2 for 1995 with 10-m winds is -1.6 GtC yr-1, with an approximate uncertainty (see footnote 1) of ±1 GtC yr‑1 mainly due to uncertainty in the gas exchange velocity and limited data coverage. The global flux consists of the uptake of anthropogenic CO2 of -2.2 GtC yr‑1 plus an estimated outgassing of 0.6 GtC yr‑1, mainly as a result of oxidation of organic carbon borne by rivers (Figure 7.3). The monthly flux values with 10-m winds used here are available from T. Takahashi at [http://www.ldeo.columbia.edu/res/pi/CO2/carbondioxide/pages/ air_sea_flux_rev1.html].

(a) Atmospheric CO2 emissions, historical atmospheric CO2 levels and predicted CO2 concentrations from the given emission time series, together with changes in ocean pH based on horizontally averaged chemistry. The emission time series is based on the mid-range IS92a emission scenario (solid line) prior to 2100 and then assumes that emissions continue until fossil fuel reserves decline. (b) Estimated maximum change in surface ocean pH as a function of final atmospheric CO2 pressure, and the transition time over which this CO2 pressure is linearly approached from 280 p.p.m. A: glacial−interglacial CO2 changes. B: slow changes over the past 300 Myr. C: historical changes in ocean surface waters. D: unabated fossil-fuel burning over the next few centuries. Source: Caldeira and Wickett (2003).

Carbon-Climate Futures

Carbon Flux: Ocean to Air

-10-8-6-4-202468

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Cox et al (2000)

Friedlingstein et al (2001)

Carbon Flux: Land to Air

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Global Mean Temperature

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sius

Coupled climate—vegetation models project dramatically different futures (CO2, vegetation, T) using different ecosystem models.

~ 2º Kin 2100 T=5T=3

Coupled simulations of climate and the carbon cycle

Slide: A.S. Denning

CO2 => 700 => 500

Uncertainties in carbon cycle feedbacks estimated from analysis of the results from the C4MIP models. Each effect is given in terms of its impact on the mean airborne fraction over the simaultion period (typically 1860-2100), with bars showing the uncertainty range based on the ranges of effective sensitivity parameters given in Tables 7.5 and 7.6. The lower 3 bars are direct response to carbon dioxide increase (see section 7.3.5 for details), the middle 4 bars show impacts of climate change on the carbon cycle, and the top black bar shows the range of climate-carbon cycle feedbacks given by the C4MIP models

Relevância desta questão para o Brasil….

Mudança Climática no modelo do Haddley Center

Lat: 15oS - 0oNLon: 70oW - 50oWCO2 interativo e vegetação dinâmica 2090s - 1990s

Retrocesso da floresta amazônica por mudança climática

1850 2000 2100

• LBA teve profundo impacto no 4AR:

•Papel dos aerossóis no balanço radiativo

•Conjuntos de dados para validação de parametrizações de processos de superfície, ciclos bio-geoquímicos, parametrização da convecção úmida

•Observações e análises do efeito da mudança do uso da terra.

•Grande número de referências no 4AR a artigos relacionados com o LBA. parameterizations,