climate modeling research & applications in wales john houghton c 3 w conference, aberystwyth 26...
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Climate Modeling Research & Applications
in Wales
John Houghton
C3W conference, Aberystwyth
26 April 2011
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Computer Modeling of the Atmosphere & Climate System
has revolutionized
• Weather Forecasting and Research
• Climate Prediction and Research
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Computer Modeling of the Atmosphere & Climate System
Identifies:• starting conditions for weather or climate
Integrates:• the dynamical equations of motion• the physical equations of state, energy etc• algorithms describing all relevant processes
NOT based on empirical or statistical information
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Parameters & Physical Processes included in a Computer Model of the Atmosphere
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Horizontal Grids for Global and Regional Models
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UK Met Office jp05
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Weather shows large variability in space and time
Detailed weather forecastingonly possible 10 to 30 days
ahead
Climate (= average weather)also shows large variability
Is forecasting of human influence on climate a possibility?
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Components of the Climate System
• Atmosphere• Oceans• Cryosphere• Land Surface• Biosphere
All these components interact closely
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Parameters & Physical Processes included in a Coupled Atmosphere – Ocean Global Climate Model
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Schematic of the Climate System from IPCC Report 2007
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Computer Modeling of the Climate
an essential tool that provides the means
to add together all the non-linear processes and effects including positive & negative feedbacks
Essential for estimating future climate
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Section of model grid in a typical global climate model in 1990 (a) and 2007 (b)
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Climate (= average weather) shows large variability from month to month, year to year
Global Climate (= patterns of climate averaged over globe)
shows clear response to external forcing factors, e.g.
• Changes in Solar Radiation
• Volcanoes
• Greenhouse gases
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Predicted & Observed changes in Global Average Temperature after the eruption of Mount Pinatubo in 1991
from IPCC Report 1996
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Changes in Global Mean Temperature in 20th century • as observed (black) • as simulated by ensemble of models (red & blue)– with natural and anthropogenic forcings (a) - with natural forcings only (b)
From IPCC Report 2007
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Patterns of Chaos
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LORENZ ATTRACTOR A solution of set of three coupled differential equations, dx/dt = σ (y - x), dy/dt = x (ρ - z) - y, dz/dt = x y - β z, that arise in studies of atmospheric convection
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Lorenz Attractor distorted by External Forcing (after Palmer 1999)
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Future Climate under increased Greenhouse Gas
Emissions
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The enhanced greenhouse effect with doubled CO2
S, L = global average values of incoming solar & outgoing long wave radiation at top of atmosphere
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Some main impacts of climate change
• More intense heat waves
• Sea level rise
• More intense hydrological cycle
jp14
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Projected changes in annual temperatures for the 2050s
The MetOffice. Hadley Center for Climate Prediction and Research.
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More rain for some; less rain for othersJun-Jul-Aug changes by 2090s
Precipitation increases very likely in high latitudes
Precipitation decreases likely in most subtropical land regionsFrom Summary for Policymakers, IPCC WG1 Fourth Assessment Report
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Increased global average surface temperature leads on average to:
• More evaporation of water vapour from oceans
• More water vapour in atmosphere
• More average precipitation (as now observed)
• More latent heat release into atmosphere*
• More intense hydrological cycle
• Increase in risk of floods and droughts
* from condensation of water vapour - a large source of energy
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Proportion of land surface in drought- 3 computer simulations under A2 Emissions
Scenario (after E Burke et al, Hadley
Centre)
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Proportion of land under extreme drought (from Burke 2006)
• 1980 ~ 1%
• 2005 ~ 3%
• 2040 (+2 deg) ~ 8%
• 2070 (+3 deg) ~ 18%
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Some Feedbacks in the Climate System
• Water-vapour feedback
• Cloud – Radiation feedback
• Ocean Circulation Feedback•
• Ice – Albedo feedback
• CO2 fertilization effect
• Climate/carbon-cycle feedback
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Cloud -Radiation Feedback
largest contributor to uncertainty in climate sensitivity
to increase in greenhouse gases
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Physical Processes associated with Clouds lead to feedbacks both +ve (high clouds) & -ve (low clouds)
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Clouds influence average temperature
+ 3% High Clouds + 0.3º
+ 3% Low Clouds – 1.0º
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Polluted clouds have smaller particles - leading to • more reflection of sunlight from the cloud top, • less radiation at the surface, • less precipitation & • longer cloud lifetime
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Annual mean net Cloud Radiative Forcing (Mar 2000 - Feb 2001)
CERES instrument on NASA Terra satellite
from King et al Our Changing Planet
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Ocean circulation feedback
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Estimates of Heat Transport by the Oceans (terawatts, 1012W )
Note -average solar radiation on 106 km2 ~ 250 terawatts
,
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How can models be validated?
• Comparison with Recent Climate
• Comparison with Past Climates
• Comparison with particular events
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Sources of Climate Data
Instruments, in-situ, passive & active remote
sensing, mounted on satellites, aircraft, balloons, ships,
buoys, land surface etc
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Envisat - 2002
Nimbus - 1970s jp02
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Instruments on ESA’s Earth Observation Satellite, ENVISAT
Passive
• AATSR• MIPAS• MERIS• SCIAMACHY• MWR• GOMOS
Active
• RA-2• ASAR• DORIS
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IllustratingDataOverload
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Examples of Climate Modeling Research Projects
• How well can models describe extreme weather?
• How well can models forecast extreme climate events e.g. floods, droughts, storms etc – timing &
location?
• Cloud- Radiation Feedback What is its average sign & size of how do they vary?
• How well do models describe Ocean-Circulation Feedback on Climate?
• What are the influences of particles (aerosols) on climate?
• What is the relative influence of different greenhouse gases?
• How can human communities adapt to climate change?
• What model improvements could best help mitigation policy?
• What can we learn from past climates?
• How can models represent sub-grid-scale motions more accurately?
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Possible Collaborations for C3W in Climate Modeling
• with Met Office
• with European partners
• etc