The Role of the Basic State in Determining the Predictability of

Tropical RainfallAndrew Turner, Pete Inness and Julia Slingo.

Talk Outline• Motivation.• Systematic errors in the UKMO climate model.• Flux adjustments used to correct the mean state.• Does the warmer mean state influence variability?• Future work.

Motivation

• South east Asian monsoon affects the lives of more than 2 billion people.

• Could correcting systematic mean-state errors in coupled GCMs improve the simulated behaviour of the monsoon on all timescales?

• Does this improve the prospects for seasonal and climate change prediction?

UK Met Office Hadley Centre model: HadCM3 L30

• HadCM3

- atmosphere: 3.75° x 2.5° x 30 levels,

- ocean: 1.25° x 1.25° x 20 levels,

- integrated for 100 years.

• ECMWF reanalyses ERA40 (1958-1997)

• CMAP (1979-1997) rainfall data (Xie & Arkin 1997).

• HadCM3 simulates south-westerly monsoon flow but it is too strong, adversely affected by biases in the model.

• west Pacific warm pool confined to Maritime continent and equatorial central Pacific too cool

excessive Pacific trades

• Maritime Continent too warm

excessive westerly inflow to the region from the Indian Ocean via a Gill response (Gill, 1980)

Simulation of summer mean climate

Flux adjustment applied over 10°N-10°S in HadCM3

• First implemented by Inness et al. (2003) to study MJO.

• Annual cycle of ocean-surface heat flux adjustments is applied in the tropical Pacific and Indian oceans.

Improvements to the summer (JJAS) mean state

• Central equatorial Pacific warmed.

• Flux adjustments reduce westward bias in the Pacific.

• Excessive trades are reduced.

• Much better rainfall picture over Indian Ocean, Bay of Bengal and Maritime Continent; much more like CMAP.

HadCM3 0.740

HadCM3FA 0.876

ERA40 1.084

Stan. Dev. DMI Nino-3

HadCM3 1.22 0.94

HadCM3FA 2.06 1.21

ERA40 1.60 0.85

What effect on the Variability?

Regression coefficients (m/s per °C)

Response of Nino4 region 10m zonal winds to Nino3

SSTs

Stochastic Forcing

• El Nino excited by stochastic forcing (Lengaigne et al. 2004, J. Climate, submitted).

• More and stronger WWEs found in the flux adjusted model, consistent with improved MJO (Inness et al, 2003).

Larger ENSO magnitude with flux adjustments, coupled with stronger trade wind response to SSTs

Stronger monsoon-ENSO teleconnection.

Flux adjustments also improve the timing of the Indian rainfall-ENSO teleconnection.

What effect on the monsoon-ENSO teleconnection?

Summary• Flux adjustments partially correct systematic biases in

HadCM3, giving monsoon and Pacific systems a better mean.

• Monsoon much more variable due to stronger Pacific variability and better wind response.

• Monsoon-ENSO teleconnection timed better.• Greater stochastic forcing on intraseasonal timescale

contributes to broader ENSO periodicity.• GCMs must have the correct basic state and the right level

of stochastic forcing in the coupled system in order to accurately represent global teleconnections.

Future Work

• Warmer mean state has consequences for both climate and variability of monsoon systems.

• Set-up and tune SPEEDY model in Reading.

• Apply knowledge to results of greenhouse gas climate change integrations of SPEEDY and HadCM3.

References• Codron et al. (2001) “Monsoon Dynamics: Predictability of Monsoons”

Journal of Climate 14.• Gill (1980) “Some simple solutions for heat-induced tropical circulation”

Q.J. Roy. Met. Soc. 106.• Inness et al. (2003) “Simulation of the Madden-Julien Oscillation in a

coupled GCM part II: the Role of the Basic State” Journal of Climate 16.• Lengaigne et al. (2003) “Coupled mechanisms involved in the triggering

of El Nino by a Westerly Wind Event” submitted, Journal of Climate.• Webster & Yang (1992) “Monsoon and ENSO: selectively interactive

systems” Q.J. Roy. Met. Soc. 118.• Webster et al. (1998) “Monsoons: processes, predictability, and prospects

for prediction” J. Geophys. Res 103.