cesd 1 sages scottish alliance for geoscience, environment & society climate change: observing...
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CESDSAGES Scottish Alliance for Geoscience, Environment &
Society
Climate Change: Observing and Simulating the Past;
Predicting the FutureSimon Tett, Chair of Earth System Dynamics &
ModellingWith thanks to Gabi Hegerl, Ben Santer, Phil Jones, Keith Briffa, Peter Thorne, Philip Brohan, Nick Rayner, John Kennedy, Peter Stott, Myles Allen, Gareth Jones, John Mitchell, Geoff Jenkins, Chris Folland, David Parker, Jonathan Gregory, Bob Harwood, Richard Kenway and Claire
Jones
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What are we trying to understand?
Image created by Reto Stockli with the help of Alan Nelson, under the leadership
of Fritz Hasler
How might the earth system evolve in the future?
How and why did it evolve in the past?
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What are we modelling?
From Space Science and Engineering Center, University of Wisconsin-Madison
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Overview
• Basic physics• Modelling the climate system• Observations of climate change• Using climate models
– Understanding 20th century climate change– Role of natural drivers in natural variability– Predictions of future change– Importance of external drivers
• Concluding thoughts
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Radiation – the driver of the climate system
• Key ideas– Lots of incoming shortwave radiation (“Visible”) from
sun– Same total energy going out from Earth but peaks in
Infra-red. (“Heat”)– Surface is warmer than you’d expect from simple
radiation budget.• The bit of the climate system that radiates energy to space is
high up (where it is cooler).• Atmosphere cools with height• So surface is warmer the “greenhouse” effect• Changing the height of the atmosphere where energy gets to
space will then affect the surface temperature
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Lapse Rate
Temperature falls with height
From http://tamino.wordpress.com/
Tropical Pacific lapse rate
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Feedbacks
• Act to amplify (or decrease) warming from changes in CO2, other greenhouse gases and other climate drivers.– Blackbody – warmer planet emits more radiation and so cools.
(Negative feedback)– Water vapour – warmer atmosphere can store more water vapour.
Water vapour absorbs “heat” radiation so is a Greenhouse gas.• Most important in the upper troposphere• Warmer world will have more moisture in the atmosphere and so will trap
more heat. Positive feedback.– Clouds
• Positive feedback – “trap” “heat” radiation. Particularly true for high clouds• Negative feedback – reflect back solar radiation. Particularly true for low
clouds– Ice/Albedo feedback.
• Ice is white and reflects lots of solar energy back to space.• Melt ice and more solar radiation absorbed which in turn warms the climate..
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Snow/Ice Feedback
Image courtesy NASA/GSFC/JPL, MISR Team.
See http://visibleearth.nasa.gov/
Summer Winter
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Climate Modelling
• Atmospheric modelling has long history – first attempts, using computers, made in 1950’s.
• General Circulation Models (GCM’s) developed from numerical weather prediction models– Take physical laws and apply them to atmospheric
and oceanic motions.– Key is that GCM’s are built bottom up.– Interested in “Emergent Phenomenon”, such as
statistics of data, rather than detailed evolution.
• Other approaches but not covered in this lecture.
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Karl and Trenberth 2003
Modelling the Climate System
Main Message: Lots of things going on!
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General Circulation Models
3-D model of the circulation of the atmosphere and ocean
Fundamental equations:• Conservation of momentum• Conservation of mass• Conservation of energy• Equation of state
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Parameterized Processes
Slingo From Kevin E. Trenberth, NCAR
•Unresolved motions and processes affect the large scale flow so their effect needs to be parameterized.
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What are we trying to parameterize?
What is there…
How we parameterise
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Numerical Modelling
Cray Y-MP ~ 1990
HECToR –2008
L. F. Richardson circa 1920
Since the 1960’s super-computer computational power increased by factor of 16 every decade. Over my career increased 200-300 fold
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Observing Climate Change
• Observing system not stable
• Climate changes slowly compared to observing system.
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Global Mean Temperature
From Brohan et al, 2006
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The longer perspective
Recent warming unprecedented
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Changes in Upper Ocean temperatures
From Palmer et al, 2007
The upper ocean is warming at, when looked one way, at roughly the same rate everywhere
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Changes in the free atmosphere: Large Observational Uncertainty
From Thorne et al, 2005 & Titchner et al, 2008
Left plot shows cooling in the tropical atmosphere. Contradicts climate models which predict largest warming in the tropics.
Right hand plot shows range of possible temperature changes in tropical free atmosphere due to uncertainties in observations. Sometimes models are more reliable than observations!
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Model Applications
• Understanding 20th century climate change
• The role of natural and human drivers in climate variability
• Future scenarios
• Summary: external drivers important in explaining observed climate variability and future climate change
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What might cause observed change?
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Internal variability – variability generated within the climate
system
Recent tropical Pacific ocean temperatures from IRI
source http://www.ldeo.columbia.edu/NAO by Martin Visbeck
The North Atlantic Oscillation
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Natural Factors that might effect climate: Volcanoes
20001850
Volcanic Aerosol depth
0
0.2
Large tropical volcanoes inject sulphur dioxide into the Stratosphere where it stays for 2-3 years. Effect is to make an aerosol that scatters light and so cools climate.
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Natural Factors that might effect climate: Solar Irradiance
Solar activity (sunspots etc) & irradiance changes with 11-year solar cycle. There are long term changes in solar activity – the Maunder Minimum being one example. Converting this to changes in solar irradiance can be done though very uncertain. “Sun-like” starts which show activity variations have been used to estimate irradiance changes. Recent work (astronomical) and modelling (Lean et al) suggests there may be no significant long term variation in solar irradiance.
1700 2000
200
0
Sunspot Number
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Human Factors that might affect climate: Aerosols
Thanks to Met Office
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Human Factors that might affect climate: Greenhouse gases
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Ice cores
Flasks
1700 1800 1900 2000Year
600
800
1000
1200
1400
1600
1800Mauna Loa
Observatory
Ice cores1700 1800 1900
Year
260
280
300
320
340
360
380CO2 MMR*106 CH4 MMR*109
Greenhouse gas concentrations have changed over the last century. Their effect is to decrease the transmission of heat radiation by the atmosphere. So should warm climate.
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Understanding and Attributing Climate Change in the 4th Assessment
Globe, Land, Ocean and individual continents all likely show human induced warming. Warming effect of greenhouses gases likely offset by other human and natural drivers
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Modelling the last 500 years
• How important are external drivers compared to internal climate variability?
• Simulation with fixed drivers – “internal” variability alone.
• Simulation with only natural drivers– Sun & Volcanic eruptions
• Simulation with human and natural drivers– Natural + changes in greenhouse gases,
aerosols, and land-surface properties
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Natural Drivers
Annual: Slow changes with large negative forcings (from volcanoes)
25-year Gaussian filter. Solar and Volcanic forcing as important as one
another. “Maunder Minimum” includes volcanic contribution. Tambora is
largest eruption of last 500 years. Late 20th century is also a volcanically active
period.
Solar
Volcanic
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Effect of natural drivers
Both hemispheres change together as does the land & ocean though there are some differences. Natural variability is about ±0.3K compared to “internal” variability of ±0.1K. So Natural forcings are an important driver of global-scale temperature
variability
SH has less variability (as more ocean) than does NH
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Naturally driven variability
Effect of natural drivers is to increase variability in the tropics
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Adding human drivers
Greenhouse gases
AerosolsVolcanoes
SunTot. Natural
Total Human
Aerosols and volcanoes offset some GHG and solar warming
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Temperature Changes with human drivers included
Effect of human drivers is to warm climate so that it warms outside envelope of natural variability by mid-late 19th century in southern hemisphere land and by mid 20th century in northern hemisphere
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Effect of human drivers of climate
Shows impact of human drivers on zonal-average temperature. Tropics warm first and warming is significant by mid 19th century. Northern hemisphere warming delayed by aerosol cooling in simulation
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Predicting the Future
Material in this section from IPCC 4th assessment report.
Results based on multi-model archive. Typically show average across all model simulations with uncertainties from range
Scenarios used to drive models. Self-consistent atmospheric concentrations of CO2 and other greenhouse gases. Based on different human development paths
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Best estimate for low scenario (B1) is 1.8°C (likely range is 1.1°C to 2.9°C), and for high scenario (A1FI) is 4.0°C (likely range is 2.4°C to 6.4°C).
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Projected warmingin 21st century expected to begreatest over land and at most high northern latitudesand least over the Southern Ocean and parts of the North Atlantic Ocean
Projections of Future Changes in Climate
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Projections of Future Changes in Climate
Precipitation increases very likely in high latitudes
Decreases likely in most subtropical land regions
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Is climate changing faster than we thought it would?
• Lot of argument has been about reality of climate change– Are observations good?– Is the sun responsible for warming?– Feedbacks are weak so that future warming not likely
to be a great threat?• General consensus (see 4th Assessment report)
is that climate is changing, likely due to human influences and agreement between different models as to likely warming.
• But could models be underestimating future climate change?
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What does the future hold?
Ensemble of “perturbed physics” models showing large uncertainty range of future warming. Which are right?
Climate Sensitivity – measure of feedbacks. “Long tail” suggests there may be strong feedbacks.
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Sea-ice (its ½ what is should be)
Is this unexpected? Are we missing something fundamental in our understanding of the Earth system?
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Sea-Ice
NASA/GODDARD SPACE FLIGHT CENTER SCIENTIFIC
VISUALIZATION STUDIO; (DATA) ROB GERSTON, GSFC
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Circulation change important for regional changes
Observations
Model mean
Human influence detected on Sea Level Pressure BUT magnitude under-simulated in Northern Hemisphere (e.g. Gillett et al., 2005)
These problems will affect regional model simulations and regional predictions
Multi-model archiveFrom Gabi Hegerl
NH SH
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UK Extreme events
Tewkesbury 2007Photograph: Daniel Berehulak/GettyImages
Met Office figures show that May to July in the England and Wales Precipitation is the wettest in a record that began in 1766.
We must learn from the events of recent days. These rains were unprecedented, but it would be wrong to suppose that such an event could never happen again…. (Hazel Blears, House of Commons, July 2007)
Is it human induced climate change or natural variability?
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UK changes
Precipitation (blue) and temperature (red) for 1931-80 and 1981-date (dashed)
High summer drying and warming. Rest warming and moistening
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Change over last century
Observations distinct from zero, consistent with all and inconsistent with natural. Implies human influence on UK climate.
Does model underestimate high summer changes?
Natural
All
Obs
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Summary & Conclusions
• Basic understanding of the climate system explains greenhouse effect and why would expect warming in response to changing atmospheric composition
• Details of response come from feedbacks• Climate models are built “bottom up” not top down.
Uncertainties arise from need to parameterize unresolved phenomenon
• Interested in the emergent behaviour which is not easily predictable from basic physics in model.
• Instrumental observations of surface temperature back to mid 19th century
• This, and other observations, show clear evidence of warming and climate change.
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Summary & Conclusions
• Using models and observations to establish that:– 20th century climate change is likely to be human driven with
greenhouse gas warming being offset by natural and other human drivers
– That external drivers are an important driver of natural climate variability
– That humans might have affected 19th century tropical climate.– Climate change has already happened and will continue to
happen regardless of what we do.– But will be large if emissions are not reduced.
• Models may be underestimating changes to come particularly those related to changes in atmospheric circulation.– This has important consequences for regional (i.e. UK) climate
change.
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The End!
Thanks for listening
Any Questions?
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Extra Material
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(Natural) Variability in Extreme events can be large
From Allan et al, 2008
20’s 60’s 90’s
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Trends since 1800
1800-2006
July-Aug
CET
1800-2006
Oct-May
CET
1800-2006
July-Aug
EWP
1800-2006
Oct-May
EWP
Obs 0.42 K/Cent
0.50 K/Cent
-8.2 % /Cent
6.3% /Cent
Model 0.35 K/Cent
+/- 0.2
0.41K/Cent
+/- 0.3
Biggest difference is +/- 0.3
2.6 % /Cent +/- 9%
1.7% /Cent +/- 4%
Biggest difference is 10%
Model not capturing drying trend
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• Available observed weather data are limited before 1950 and almost non-existent before 1850.
• Many more observations exist, in logbooks, reports and other paper records (mostly in the UK). If we digitised them we could improve the climate record and extend it back to 1800.
• Hadley Centre digitised observations from Royal Navy Ships logbooks for WW2. These give a much-improved picture of 1940s climate.
Digitisation as a source of new data
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1998 & 2007
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Another feedback: The Carbon cycle
From Friedlingstein et al, 2006. Plots shows additional CO2 from feedbacks between climate change and carbon cycle. Values vary between 25 and 225 ppm at 2100 mostly due to land-carbon cycle feedbacks.
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Relative Contributions
Greenhouse gases
Other human
Natural
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Assessing Recent Change
Observed trend (K/decade) marked with X where outside maximum absolute 50-year trend from Natural. + where outside maximum trend. Recent changes are outside simulated natural variability over large parts of the world. Suggests that natural systems are already being affected by climate change
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Fig 9.18b
Observed (black) and simulated 1901-1998 precipitation trends
ObservationsMulti-model mean
Model range
Thin solid line model’s all forcing response detected in obs
Figure from IPCC WGI Ch9 (Hegerl, Zwiers et al)
Zonal 20th century precipitation change
Changes in rainfall over NH underestimated by models?
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Ranking
From John Kennedy & the Met Office
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Radiation
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Timeseries of UK records
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Actual heat waves
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Future changes in the Hydrological Cycle