MET 112 Global Climate Change - Lecture 11MET 112 Global Climate Change - Lecture 11

Future PredictionsFuture PredictionsCraig ClementsCraig Clements

San Jose State UniversitySan Jose State University

Climate Change and humans

Anthropogenic increases in – greenhouse-gas concentrations– sulfate aerosols due to anthropogenic

emissions Emission scenarios have been developed Changes in solar irradiance and volcanic

aerosols– Unpredictable and difficult to model

Q: How do we predict what the future climate will be like?

A: We use global models of the earth system

Global Climate Models (GCMs)

Sequence of Steps

1. Estimate future GHGs concentration

2. Using future GHG levels, calculate what future climate (e.g. temp, precip) will be like.

3. Assess the uncertainty of the predictions

Calculation of Future CO2 Concentrations

Carbon Cycle Model – Simulates atmosphere-biosphere and atmosphere-ocean interactions

CO2 Emissions -How much is going into atmosphere

CO2 Concentration - How much remains in atmosphere

Carbon Cycle Models

Atmosphere/ocean and atmosphere/biosphere interactions not well understood

Model calculations contain uncertainty; the largest uncertainty: – Future uptake of carbon by the biosphere– Future uptake of carbon by the oceans

Past and Projected Future CO2 Concentrations (Back-Up)(ppm) Parts per million

Observations

Model

projections

Global Population Type of energy generation

– Fossil intensive

– Renewable energy Growth of Economy Type of Economy

– Material based

– Service and information based Cooperation among countries

– More homogeneous - share technologies

– More isolated - larger divide between rich/poor countries

What factors affect future CO2 levels?

The IPCC based its projections on six emission scenarios, running each one through sophisticated climate simulation programs.

Gov

erna

nce

Development

Local

Global

EnvironmentalEconomic

A1 B1

B2A2Adapted from Arnell et al. (2004). Global Environmental Change, 14:3-20

A1BA1FIA1T

Gross Domestic Product Growth at 2100

Gov

erna

nce

Development

Local

Global

EnvironmentalEconomic

A1 B1

B2A2Adapted from Arnell et al. (2004). Global Environmental Change, 14:3-20

Energy Use at 2100

Gov

erna

nce

Development

Local

Global

EnvironmentalEconomic

A1 B1

B2A2Adapted from Arnell et al. (2004). Global Environmental Change, 14:3-20

Gov

erna

nce

Development

Local

Global

EnvironmentalEconomic

B1

B2A2Adapted from Arnell et al. (2004). Global Environmental Change, 14:3-20

A1B

A1FI

A1T

Technological Change at 2100

Country A

Country BCountry C

Scenarios (1)

Scenarios (2)

A1 storyline– World of rapid economic growth– Population peaks 2050– Different branches dependent on energy type/use

A1FI – Fossil intensive – continued dependence on coal/oil

A1T – Non-fossil intensive energy use (Technology) A1B – Balance between fossil and non-fossil

A2 storyline– Heteorogenous world –technologies are not shared

across borders, – population continues to increase

Scenarios (3)

B1 storyline– Similar population as A1– Global exchange/cooperation– Change in economic structures from product

oriented to service oriented.– Focus on social and economic sustainability

B2 storyline– Population like A2– Similar environmental and social focus– More regionally oriented (not as much

exchange between countries).

CO2 emissions for various scenarios

Note: global

population

peaks in 2050

and declines

in some

scenarios

Why a peak around 2050?

Projected CO2 Concentrations for Various Scenarios

Note that even the low-emission scenarios result in greatly increased CO2 concentrations by the year 2100– Max concentration (of scenarios shown): 970 ppm– Min concentration (of scenarios shown): 550 ppm– (Compare with current value: 370 ppm)

Climate Model

A climate model is a mathematical representation of the physical processes that control climate– Basically everything that affects climate– Sun, atmosphere (greenhouse gases,

aerosols), hydrosphere, land surface, cryosphere

Equations are very complicated– Some of the world’s largest supercomputers

are running climate models

Climate Modeling: Super Computers

One frame of an IBM Power5-575 series system. NCAR's “Blue Vista” will have 16 frames.

Blue Vista will need over 250 kilowatts of power to operate. The average personal computer consumes 0.12 kilowatts .

78 IBM POWER5 nodes. Each node will have eight POWER5 simultaneous multithreading (SMT) processors

16 gigabytes of memory.

NCAR’s “Blue Vista” IBM Power5

Model Schematic

Climate Model

Changes in greenhouse-gas concentrations and changes in albedo due to aerosols

Climate change (i.e. temperature, precipitation etc.)

Model Sensitivity

Models (like the atmosphere) are sensitive systems.

They can respond differently to the same radiative forcing, e.g., a doubling of CO2

– This means that different models give different answers to the same problem

– Thus, we use a range of models to determine the range of possible future scenarios.

Model Verification: Can it be done?

Before you can trust any of these models, they must be verified.– We can use past climate as a test.

If your model can simulate the past climate, then there is a reasonable chance that the

model can accurately predict future climate.

Can we predict changes in past climate?

Source: IPCC Climate Change 2007: The Physical Science Basis—Summary for Policymakers.

Global Average Surface Temperature

Source: IPCC Climate Change 2007: The Physical Science Basis—Summary for Policymakers.

These experiments demonstrate that

1. The warming of the entire 20th century is largely due to humans

2. The warming of the last 50 years is largely due to humans.

3. Natural factors are largely responsible for the warming of the 20th century

4. Natural factors are not important in the early 20th century, but more important in the last part of the 20th century.

Climate models

1. Are not useful for predicting the temperature changes observed during the 20th century.

2. Show that volcanic eruptions and changes in sunlight are responsible for most of the changes observed over the 20th century.

3. Can predict the 20th century observed temperature changes with natural factors only.

4. Can only predict the 20th century observed temperature changes when they include both human and natural contributions.

What conclusions can you infer from these model experiments?

1. Models can reasonably predict

temperature variations over the last

150 years.

2. Most of the observed warming in the

past 50 years is attributable to human

activities.

Carbon Emissions

UNEP 2003

Notes on Temperature Projections

Projected Warming: 2000 – 2100 ranges from ~1.4°C to ~5.8°C.

Curves represent warming produced for seven scenarios by a model with average sensitivity.

Each bar on the right represents a range of warming produced – by models of differing sensitivies for a

specific scenario.

Land areas are projected to warm more than the oceans with the greatest warming at high latitudes

Annual mean temperature change, 2071 to 2100 relative to 1990: Global Average in 2085 = 3.1oC

Some areas are projected to become wetter, others drier with an overall increase projected

Annual mean precipitation change: 2071 to 2100

Relative to 1990

Sea Level

Sea Level Rise

Annual mean precipitation change: 2071 to 2100 Relative to 1990

Recent Sea Level Changes

Future predictions: main changes in climate

Higher temperatures - especially on land

– Arctic shows the largest warming Hydrological cycle more intense

– More rain overall Sea levels rise

– Why? Changes at regional level –hard to predict More intense weather (extremes)

– Floods, droughts etc.

Questions

1. Based on the A1FI scenario, what is the

predicted CO2 concentration, temperature

change and sea level change in 2100?2. Based on the B1 scenario, what is the

predicted CO2 concentration, temperature change and sea level change in 2100?

3. Explain the differences.

If CO2 emissions were stabilized at present day values, CO2 concentrations would

1. Continue to increase

2. Stabilize

3. Start to decrease