simulations of the atmospheric circulation on a water-covered earth mike/ape/working group on...

Simulations of the atmospheric circulation

on a water-covered Earth

http://www.met.reading.ac.uk/~mike/APE/

Working Group on Numerical Experimentation - WGNE

David WilliamsonNCAR

Mike BlackburnUniversity of Reading

Peter Gleckler (PCMDI)Brian Hoskins (Reading)Richard Neale (CDC, now NCAR)

APE Modelling Groups

- Space & Atmospheric Physics, Imperial College 28 February 2006 -



Outline

• Motivation and context

• Experimental design + participants

• Aspects of climate – mean and variability

• Conclusions + next steps

“Compare idealised climates simulated by global atmospheric circulation models (AGCMs) being developed and used for numerical weather prediction and climate research.”

“Provide a benchmark of current model behaviour and stimulate research to understand the causes of inter-model differences.”

IPCC (2001)

Climate changes over the next few decades are predicted to be much larger than we have seen so far…

Uncertainty in climate predictions- IPCC TAR (2001) -



Evaluation of Atmospheric GCMs- an experimental hierarchy -

1D / 2D idealised flows

Dynamical core

Idealised moist core Aqua-planet AMIP

•Full complexity GCM

- unique dynamics

- unique moist parameterizations

•Difficult to isolate reasons for differences

•Aqua-planet idealises the planet, not the model!

•Dry dynamics

- linear relaxation to climatology

- Rayleigh friction boundary layer

•Unrealistic sensitivities

•Aim for

- single idealised moist parameterization

- minimal complexity to represent processes

•Use in all dynamical cores

•Sensitivity of a moist atmosphere to dynamical formulation



• Moist processes are replaced by linear temperature relaxation + drag

• Sensitivities to numerical options different from the complete GCM

• Highlights moist feedbacks in climate

Dynamical Core behaviour

zonal mean Temperature

semi-Lagrangian versus Eulerian advection

Chen & Bates (1996); Chen et al (1997)

moist GCM dynamical core



Berlin Academy competition (1746):

To determine “the order and the law which winds would have to observe if the Earth were surrounded everywhere by an ocean, so as to find at all times the direction and the velocity of the wind for every place”

Historical aside ….

Egger and Pelkowski (2006)

• Led to the first mathematical models of atmospheric motion

• 11 entries, including d’Alembert and Bernoulli

• Tidal oscillations only (rotation + gravitational attraction)

• Expressly excluded effects of radiational heating, though recognised as important for the complete problem

Won by d’Alembert: 2 layer model of atmosphere + ocean



The Experiment

• Complete GCMs but idealised planet

• More constrained experiment than real-world benchmark (AMIP)

• Facilitate understanding of model differences and sensitivities

• No land / orography

• 8 idealised sea surface temperature (SST) distributions

• 5 symmetric SSTs span a range of tropical climates

• Local and global-scale SST anomalies

• 3-year climate (following spin-up)

• Following Neale & Hoskins (2000)

Symmetric SST profiles

Latitude

SS

T (

degC

)

SST anomaly experiments

3KW1

1KEQ 3KEQ



APE Modelling Groups

Group Location Model Resoln Features

AGU for APE Japan (consortium) AFES v.1.15 T39 L48 Spectral, eulerian

CGAM Reading, UK HadAM3 N48 L30 3.75º x 2.5º grid

CSIRO Aspendale, Australia CCAM-4-12 C48 L18 ~220km conformal cubic grid

DWD Mainz, Germany GME 29.1.1 ni=64 L31 ~1º icosahedral-hexagonal grid

ECMWF Reading, UK IFS Cycle 29r2 TL159 L60 Spectral, semi-lagrangian

FRCGC Yokohama, Japan NICAM 7km L54 icosahedral grid, non-hydro.

GFDL Princeton, USA AM2p14 N72 L24 2.5º x 2º grid (IPCC)

GSFC Maryland, USA NSIPP-1 N48 L34 3.75º x 3º grid

K1-Japan Japan (collaboration) CCSR/NIES 5.7 T42 L20 s-l moisture and cloud

LASG Beijing, China SAMIL R42 L9 Spectral, eulerian

MGO St. Petersburg, Russia MGO-gcm T30 L14 Spectral

MIT Cambridge, USA MIT-gcm C32 L40 ~280km cubed sphere

NCAR Boulder, USA CCSM-CAM3 T42 L26 Spectral, eulerian

UKMO Exeter, UK pre-HadGAM1 N96 L38 1.875º x 1.25º grid, s-lagrangian

Range of tropical states

Precipitation (mm/day)



Zonal Average Hydrological CyclePrecipitation (mm/day)

Evaporation (mm/day)

different scale



Convective / stratiform precip.



Convective (mm/day)

Stratiform (mm/day)

Hydrological Cycle: NCAR model

Courtesy of David Williamson, NCAR

Precipitation: contributions to resolution dependence, T42 / T85

params.

timestep grid

Truncn. diffusion

params.at T42




Inter-tropical Convergence Zone

• When does convection break through the trade-wind inversion?

• Many interacting processes

• ITCZ location sensitive to all these processes in models

Emanuel (1994)

[ Evap – Precip ] Surface Wind ECMWF - APE control (time average)

(mm/day)Cool 30º lat.

Eq. Warm

average 5ºN-5ºS

Tropical Variability (precipitation)



(mm/day)

Tropical Variability (precipitation)

average 5ºN-5ºShttp://www.met.reading.ac.uk/~mike/APE/


Higher resolution models

NICAMIcosahedral L54

7km grid

non-hydrostaticno convective param.

IFS Cy29r2TL159 L60

~125km grid

pre-HadGAM1N96 L38

1.25° x 1.875°

GMEIcosahedral L31

~100km grid

(mm/day)



Observations + Theory

Observed variability (OLR)

• Hierarchy of convective organisation

Tim

e

Time-longitude section of transient OLR averaged between the equator and 5N from May to July in 1980. (Nakazawa, 1988)

Zonal Wavenumber

Fre

quen

cy (

CP

D)

UKMO_n96 sym. spectrum (precip)

Observed sym. spectrum (OLR)

Images from Yoshi-Yuki Hayashi; Yukiko Yamada; NOAA CDC

Tropical rainfall: spectra

APE control

10°S – 10°N

6hour grid-box averages

LASG

FRCGC

HadGAM1 (umet)

N48

N96

AGUGSFC

CSIRO

MGONCAR



Tropical rainfall: Stratiform fraction

APE control

10°S – 10°N



AG

U

CG

AM

DW

D

EC

MW

F

GF

DL

GS

FC

K1J

AP

AN

LA

SG

MG

O

MIT

NC

AR

UM

ET

_48

UM

ET

_96

CS

IRO

_a

CS

IRO

_b

FR

CG

C

Some correlation with spectral shape

Wider SST maximum in tropics

Stronger SST gradient : displaced poleward

Response of zonal climate to SST

qobs-control

Working Group on Numerical Experimentation - WGNE http://www.met.reading.ac.uk/~mike/APE/

cntl

qobs

latitude

SS

T (

degC

)

m=1 SST anomaly generates planetary waves

Expect stationary momenum fluxes to alter zonal flow

3kw1-control

Zonal mean differences

SST anomaly

Working Group on Numerical Experimentation - WGNE http://www.met.reading.ac.uk/~mike/APE/



Storm-track statistics

• Tracking of storm features using 6 hourly sea-level pressure

• NCAR model for all 8 SSTs

Courtesy of Kevin Hodges, ESSC, Reading

Mean Intensity

latitude

Pre

ssur

e an

omal

y (h

Pa)

Track Density

latitude

Num

ber

per

mon

th in

5º

radi

us

peakcntlqobsflatcntl5n1keq3keq3kw1

Zonal speed

Zon

al s

peed

(m

s-1)

latitude



Storm-track statistics

• Tracking of storm features using 6 hourly sea-level pressure

• 6 models for “flat” SST

Courtesy of Kevin Hodges, ESSC, Reading

Track Density

latitude

Num

ber

per

mon

th in

5º

radi

us

Mean Intensity

latitude

Pre

ssur

e an

omal

y (h

Pa)



Low Frequency Variability

• Significant zonal wavenumber m=5 in 3-year means

• Slow propagation, c = 1.7ms-1

• Significant correlation with annular mode variability

Courtesy of Masahiro Watanabe,

Hokkaido University. GRL 32, L05701. (2005)

1-point correlation maps: 10-day low-pass surf. pressure

EOFs of 10-day low-pass streamfunction =0.3

Ref 51.6N

Global Energy Balance

APE control experiment:

3 year averages +

temporal variability

Net flux (toa; surface)

sw_dn TOA sw_up

sw TOA lw





Cloud + Albedo



Summary

• Documenting a wide variety of model behaviours

• No convergence for Δx>100km – basic tropical features not resolved?

• Attempts to understand sensitivities in individual models

• Additional experiments needed to understand model differences (e.g. no cloud-radiative feedback; fixed radiation; SCM)

• Diagnostics focus: Tropical wave activity Diurnal cycle Mid-latitude variability & storm-tracks

• Issues: Reference solution is unknown Resolution convergence? (HPEs + parameterizations)

simulations of the atmospheric circulation on a water-covered earth mike/ape/working group on...

Documents

grid csiro aspendale

moist gcm dynamical

keq slide

ocean slide

grid ipcc gsfc maryland

dynamical formulation

eulerian cgam reading

slagrangian slide