CLIM 690: Scientific Basis of Climate Change Climate Models and Their Evaluation.

CLIM 690: Scientific Basis of Climate Change

Climate Models and Their Evaluation


• Substitute for reality• Closely mimics some

essential elements• Omits or poorly mimics

non-essential elements

What is a Model?


• Quantitative and/or qualitative representation of natural processes (may be physical or mathematical)

• Based on theory• Suitable for testing “What if…?” hypotheses• Capable of making predictions

What is a Model?


What is a Model?

Input Data Model Output Data

Tunable Parameters

What output data might we consider for a typical

climate model?

What input data might we consider for a typical

climate model?

What are the tunable parameters of interest?

CLIMATE DYNAMICS OF THE PLANET EARTH

S

Ω

a

g

T4

WEATHER

CLIMATE .

hydrodynamic instabilities of shear flows; stratification & rotation; moist thermodynamics

day-to-day weather fluctuations; wavelike motions: wavelength, period, amplitude

T_

y,U

_

yT

_

z,U

_

z

S, , a, g, ΩO3

H2OCO2

stationary waves (Q, h*), monsoons

h*: mountains, oceans (SST)w*: forest, desert (soil wetness)

(albedo)


Example of a Model:Earth’s Energy Balance

THEORY:

Energy conservation: Change inenergy due to difference in fluxes

Solar Radiation

S = 1380 Wm-2

(plane, parallel)

Planetary Emission

Qt

FI FO 0


Example of a Model:Earth’s Energy Balance

THEORY:

Energy conservation: Change inenergy due to difference in fluxes

MODEL: Assume radiative equilibrium

INCOMING FLUX = OUTGOING FLUX

(1 - ) S ( a2) = Qe (4 a2)

Qe = 1/4 (1 - ) S

Measured albedo () = 0.31Measured planetary Qe = 237 Wm-2 Blackbody temperature (T4 law): 254 KMeasured surface Qes = 390 Wm-2 Blackbody temperature (T4 law): 288 K

Atmosphere absorbs 153 Wm-2 Greenhouse effect: 34 K

Solar Radiation

S = 1380 Wm-2

(plane, parallel)

Planetary Emission

Qt

FI FO 0


• Equations of motions and laws of thermodynamics to predict rate of change of:

T, P, V, q, etc. (A, O, L, CO2, etc.)

• 10 Million Equations: 100,000 Points X 100 Levels X 10 Variables

• With Time Steps of: ~ 10 Minutes

• Use Supercomputers

What is a Climate Model?


Model Complexity:Development of Climate/Earth System Models

Ultimate: all physico-biogeochemical Earth System


• Validation– Confirmation that formulation of model conforms to intent

(equations, algorithms, units, specified parameters etc.)– Confirmation that outputs are, within tolerable limits, as expected

for given inputs• Verification

– Comparison with known, measured (observed) quantities– Means, variability (frequency, amplitude, phase)– Spatial structure (scale, shape, amplitude)– Simulation: confirms theory for specified circumstances (e.g.

specified boundary conditions) – Prediction: accurately reproduces time series of observed

evolution from specified initial conditions• (Inter-)Comparison

– Comparison among different models’ outputs for identical inputs

What is Model Evaluation?


• Example: ENSO Prediction– Comparison of many salient characteristics of

ENSO with observations and among models– Coupled ocean-atmosphere models with

specified, observed initial conditions and external forcing (e.g. GHG concentrations)

What is Model Evaluation?


Jin et al. 2008 Climate Dynamics

SST along the equator

Annual Mean Difference from Observations



SST along the equator in the Pacific (mean annual cycle) - lead time 1-3 months



SST along the equator in the Pacific (mean annual cycle) - lead time 4-6 months



Standard Deviation Difference from Observations


(a)

(b)

(c)


RMSEInterannual Variability

Interannual Variability

Intr

a-en

sem

ble

Var

iabi

lity

Ann

ual C

ycle

Err

or

Intr

a-en

sem

ble

Var

iabi

lity



Cor

rela

tion

Forecast Lead (months)


Evaluating the IPCC Models


Figure 8.2

OBS (contours) & mean MME error (shades)

SST(1980-1999)SAT(1961-1990)

MME RMS error


Figure 8.3

SST & SATst. dev.

OBS (contours) & mean MME error (shades)


RMS errorw.r.t. ERBE

mean error in SWTOA

mean error in OLR


OBS

Annual Mean Precipitation1980-1999

MME


Climate Model Fidelity and Projections of Climate ChangeJ. Shukla, T. DelSole, M. Fennessy, J. Kinter and D. Paolino

Geophys. Research Letters, 33, doi10.1029/2005GL025579, 2006

CLIM 690: Scientific Basis of Climate Change Climate Models and Their Evaluation.

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