Transcript S, L = global average values of incoming solar & outgoing

Climate Modeling
Research & Applications
in Wales
John Houghton
C3W conference, Aberystwyth
26 April 2011
Computer Modeling of the
Atmosphere & Climate System
has revolutionized
• Weather Forecasting and Research
• Climate Prediction and Research
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
Parameters & Physical Processes included
in a Computer Model of the Atmosphere
Horizontal Grids for Global and Regional Models
UK Met Office
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Weather shows large variability in
space and time
Detailed weather forecasting
only possible 10 to 30 days ahead
Climate (= average weather)
also shows large variability
Is forecasting of human influence
on climate a possibility?
Components of the Climate System
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Atmosphere
Oceans
Cryosphere
Land Surface
Biosphere
All these components interact closely
Parameters & Physical Processes included in a
Coupled Atmosphere – Ocean Global Climate Model
Schematic of the Climate System
from IPCC Report 2007
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
Section of model grid in a typical global climate model
in 1990 (a) and 2007 (b)
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
Predicted & Observed changes in Global Average Temperature
after the eruption of Mount Pinatubo in 1991
from IPCC Report 1996
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
Patterns of Chaos
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
Lorenz Attractor distorted by External
Forcing (after Palmer 1999)
Future Climate under increased
Greenhouse Gas Emissions
The enhanced greenhouse effect with doubled CO2
S, L = global average values
of incoming solar & outgoing long wave radiation at top of atmosphere
Some main impacts of climate change
• More intense heat waves
• Sea level rise
• More intense hydrological cycle
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Projected changes in annual temperatures for the 2050s
The MetOffice. Hadley Center for Climate Prediction and Research.
More rain for some; less rain for others
Jun-Jul-Aug changes by 2090s
Precipitation increases very likely in high latitudes
Precipitation decreases likely in most subtropical land regions
From Summary for Policymakers, IPCC WG1 Fourth Assessment Report
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
Proportion of land surface in drought
- 3 computer simulations under A2 Emissions Scenario
(after E Burke et al, Hadley Centre)
Proportion of land under extreme
drought (from Burke 2006)
• 1980
~ 1%
• 2005
~ 3%
• 2040 (+2 deg)
~ 8%
• 2070 (+3 deg)
~ 18%
Some Feedbacks in the Climate System
• Water-vapour feedback
• Cloud – Radiation feedback
• Ocean Circulation Feedback
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• Ice – Albedo feedback
• CO2 fertilization effect
• Climate/carbon-cycle feedback
Cloud -Radiation Feedback
largest contributor to uncertainty
in climate sensitivity
to increase in greenhouse gases
Physical Processes associated with Clouds lead to feedbacks
both +ve (high clouds) & -ve (low clouds)
Clouds influence average temperature
+ 3% High Clouds
+ 0.3º
+ 3% Low Clouds
– 1.0º
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
Annual mean net Cloud Radiative Forcing (Mar 2000 - Feb 2001)
CERES instrument on NASA Terra satellite
from King et al Our Changing Planet
Ocean circulation feedback
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
Sources of Climate Data
Instruments,
in-situ, passive & active remote sensing,
mounted on
satellites, aircraft, balloons, ships,
buoys, land surface etc
Envisat - 2002
Nimbus - 1970s
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Instruments on ESA’s Earth
Observation Satellite, ENVISAT
Passive
Active
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• RA-2
• ASAR
• DORIS
AATSR
MIPAS
MERIS
SCIAMACHY
MWR
GOMOS
Illustrating
Data
Overload
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?
Possible Collaborations for C3W
in Climate Modeling
• with Met Office
• with European partners
• etc