Global Warming: What do we really know?

Inez FungUniversity of California, BerkeleyMSRI Climate Change Summer School July 14 2008

Planck’s Law:The amount and spectrum of radiation emitted by a blackbody is uniquely determined by its temperature

Max Planck (1858 – 1947) Max Planck (1858 – 1947) Nobel Prize 1918Nobel Prize 1918

Emission from warm bodies peak at short wavelengths

wavelength

620 K

380 K

1. Power Source: Blackbody Radiation

Sun: ~6000K :0.5m (shortwave)Earth: ~300K :10m (longwave)

What is a greenhouse gas?

C OO

CO O

O OC

symmetric

bending 15 m

asymmetric 4.3 m

Greenhouse effect: Radiation at specific wavelengths excite CO2 into higher energy states: energy is “absorbed” by the CO2 molecules

Earth’s Energy Balance: without GHG

Shortwave Longwave

3070

NN22

70

50 absorbed by sfc

100

20 absorbed by atm

20

Sensible heat

Latent heat

Earth’s Energy Balance: with GHG

COCO22, H, H22O, GHGO, GHG

Longwave

70

95114

23

7

50 absorbed by sfc

Shortwave

30

20 absorbed by atm

100

Incoming from Sun:High energy,

short wavelength

Outgoing from EarthLow energy

Long wavelength

0.5 m

10 m20 m

Earth Spectrum

What do we really know?

• Climate Forcing• Climate Feedback• Climate Response

– Equilibrium (?5000 years)– Transient (<500 years)

• Climate Projections

Changing Composition of Earth’s Atmosphere

Ancient air bubbles trapped in ice contains info about past atm composition

The Last

500,000 yearsand the

last 200

years

Climate Forcing: expressed as a change in radiative heating (W/m2) at surface for a given change in trace gas composition or other change external to the climate system

Hansen PNAS 2001

Cumulative climate forcing since 1800

Ship Tracks:- more cloud condensation nuclei- smaller drops- more drops- more reflective- energy balance

What do we really know?

• Climate Forcing• Climate Feedback• Climate Response

– Equilibrium (?5000 years)– Transient (<500 years)

• Climate Projections

Climate Feedback

Given a climate forcing (e.g. CO2 increase) initial warming

• Amplifying loops (positive feedback) magnify the warming

• Diminishing loops (negative feedback)

Climate Feedbacks

Warming

Evaporation from ocean,Increase water vapor in atmEnhance greenhouse effect

Increase cloud cover;Decrease absorption of solar energy

Decrease snow cover;Decrease reflectivity of surfaceIncrease absorption of solar energy

What do we really know?

• Climate Forcing• Climate Feedback• Climate Response

– Equilibrium (?5000 years)– Transient (<500 years)

• Climate Projections

At equilibrium (thousands of years):

High CO2 --> warm; Low CO2 --> cold

J. Hansen

Warmest 7: 1998, 2002, 2003, 2004, 2005, 2006,

2007Amplification of warming due to decrease of albedo (melting of snow and ice)

Warming greatest at high latitudes

Melting glaciers on Greenland--> feedback

--> accelerating warming

Oceans: Bottleneck to warminglong memory of climate system

• 4000 meters of water, heated from above

• Stably stratified • Very slow diffusion of

chemicals and heat to deep ocean

• Fossil fuel CO2: • 200 years emission,• penetrated to upper 500-1000

m

Slow warming of oceans --> continue evaporation, continue warming

What do we really know?

• Climate Forcing• Climate Feedback• Climate Response

– Equilibrium (?5000 years)– Transient (<500 years)

• Climate Projections

Weather Prediction by Numerical Process

Lewis Fry Richardson 1922

Weather Prediction by Numerical Process

Lewis Fry Richardson 1922

• Grid over domain • Predict pressure,

temperature, wind

Temperature -->density Pressure

Pressure gradient Wind temperature

Weather Prediction by Numerical Process

Lewis Fry Richardson 1922

• Predicted: 145 mb/ 6 hrs

• Observed: -1.0 mb / 6 hs€

∂ps

∂t

First Successful Numerical Weather Forecast: March

1950•Grid over US

•24 hour, 48 hour forecast

•33 days to debug code and do the forecast

•Led by J. Charney (far left) who figured out the quasi-geostrophic equations

ENIAC: <10 words of read/write

memory

Function tables(read memory)

16 operations in each time step

Platzman, Bull. Am Meteorol. Soc. 1979

Reasons for success in 1950

• More & better observations after WWII--> initial conditions + assessment

• Faster computers & correct computational math (24 hour forecast in 24 hours)

• Improved physics - – Atm flow is quasi 2-D (Ro<<1) – quasi-geostrophic vorticity equations– filtered out gravity waves– Initial C: pressure (no need for u,v) t ~30 minutes (instead of 5-10

minutes)

Continued Success Since 1950

• More & better observations

• Faster computers and advanced computational mathematics

• Improved physics

mass

energy

water vapor

momentum

)(

...),,,(

,...),(

)(

),(;

0)(

)(ˆ12

2

qonCondensatiEvapqutq

GHGCOqTfLW

aerosolscloudsfSW

TLHSHLWSWTutT

qTfRTp

ut

uFkgpuuutu

ℑ+−=∇•+∂∂

==

ℑ++++=∇•+∂∂

==

=•∇+∂∂

ℑ+++∇−=×Ω+∇•+∂∂

r

bbr

r

rrrrrr

ρρ

ρρ

ρ

Atmosphere

ℑ convective mixing

Modern climate models

• Forcing: solar irradiance, volanic aerosols, greenhouse gases, …

• Predict: T, p, wind, clouds, water vapor, soil moisture, ocean current, salinity, sea ice, …

• Very high spatial resolution:<1 deg lat/lon resolution~50 atm layers~30 ocn layers~10 soil layers

==> 6.5 million grid boxes

• Very small time steps (~minutes)

• Ensemble runs (multiple experiments)

Model experiments (e.g. 1800-2100) take weeks to months on supercomputers

Processes in Climate Models

• Radiative transfer: solar & terrestrial

• phase transition of water

• Convective mixing

• cloud microphysics

• Evapotranspirat’n• Movement of heat

and water in soils

A B + water vapor + greenhouse Warming

A C + water vapor + cloud cover + greenhouse - absorption of sunlight

C

275 280 285 290 295 3000

5

10

15

20

25

30

35

40

1 2 3 4 5 6

Temperature (K)

Sat

ura

tio

n V

apo

r P

ress

ure

(m

b)

A

B

liquid

vapor

Ice Liquid + absorption of sunlight

100% relative humidity

C

Climate Dial: Three phases of water

AttributionAttribution

• are observed changes consistent with

expected responses to forcings

inconsistent with alternative explanations

Observations

Climate model: All forcing

Climate model: Solar+volcanic only

IPCC AR4

21stC warming depends on rate of CO2

increase

20thC stabilizn:CO2 constant at 380 ppmv for the 21stC

21thC “Business as usual”:CO2 increasing 380 to 680 ppmv

Meehl et al. (Science 2005)

greatest over land & at most high N latitudes

and least over the South. Ocean & parts of the N Atlantic Ocean

Projections of Climate Change

IPCC AR4

9oF

7oF

3oF

Multi-model Projections of Climate Change

IPCC AR4

Uncertainties in global projections:2020: concurrence2050: depend on CO2 increase2100: depend on CO2 increase and ocean response time

Inter-model range

Stern Review 2006

Stern Review 2006

PROBLEM: The Elusive Carbon Sink

• Only half of the CO2 produced by human activities is remaining in the atmosphere

• Where are the sinks that are absorbing over 40% of the CO2 that we emit?

– Land or ocean?– Eurasia/North America?

• Why does CO2 buildup vary dramatically with nearly uniform emissions?

• How will CO2 sinks respond to climate change?

Cumulative Ocean Carbon Sink of FF

CO2

(Cumulative)Sabine et al 2004

• Thermocline: barrier to transport of perturbations to depth

• Thermohaline circulation: lateral transport of perturbation

Warm-wet

Warm-dry

T, Soil Moisture Index}

Regression ofNPP vs T

NPP decreases with carbon-climate coupling

Fung et al. Evolution of carbon sinks in a changing climate. PNAS 2005

21st Century Correlations & Regressions: FF= SRES A2 ; = Coupled minus

Uncoupled

With SRES A2 (fast FF emission): as CO2 increases• Capacity of land and ocean to store carbon

decreases (slowing of photosyn; reduce soil C turnover time; slower thermocline mixing …)

• Airborne fraction increases --> accelerate global warming

Fung et al. Evolution of carbon sinks in a changing climate. PNAS 2005

Airborne fraction=atm increase /Fossil fuel emission

Changing Carbon Sink Capacity

Ocean

momentum

mass

energy

salinity

€

∂r

u 2∂t+

r u 2 • ∇

r u 2 + 2Ω×

r u 2 = −

1

ρ 0∇p +

r F +

r τ 0

wind stress{

∇ •r u 2 +

∂w

∂z= 0

0 = −∂p

∂z+ ρg; ρ = f (T, s )

∂T

∂t+

r u 3 • ∇T = Q

0

surface heating{

+ ℑ (T )

∂s

∂t+

r u 3 • ∇s =

s0ρ 0Δz

(E − P )0

freshwater flux1 2 4 4 3 4 4

+ ℑ (s)

Numerical Weather Prediction

( ~ days)

Initial Conditions

t = 0 hr

Prediction t = 6 hr 12 18 24

•Predict evolution of state of atmosphere (t)

•Error grows w time --> limit to weather prediction

Seasonal Climate Prediction ( El – Nino Southern Oscillation )

{ Initial Conditions}

Atm + Ocn t = 0

{Prediction}

t = 1 month 2 3

• Coupled atmosphere-ocean instability• Require obs of initial states of both atm & ocean, esp. Equatorial Pacific• {Ensemble} of forecasts • Forecast statistics (mean & variance) – probability• Now – experimental forecasts (model testing in ~months)