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 jp05

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?

Components of the Climate System

• 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

jp14

Projected changes in annual temperatures for the 2050s

The MetOffice. Hadley Center for Climate Prediction and Research.

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

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•

• 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

,

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 jp02

Instruments on ESA’s Earth Observation Satellite, ENVISAT

Passive

• AATSR• MIPAS• MERIS• SCIAMACHY• MWR• GOMOS

Active

• RA-2• ASAR• DORIS

IllustratingDataOverload

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