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Andrew Turner UKCDS Bangladesh Delegation Visit Wednesday 3 March 2010 Key modes of climate variability over South Asia and uncertainties in future climate projections

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UKCDS Bangladesh Delegation Visit Wednesday 3 March 2010. Key modes of climate variability over South Asia and uncertainties in future climate projections. Andrew Turner. Introduction. - PowerPoint PPT Presentation

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Page 1: Andrew Turner

Andrew Turner

UKCDS Bangladesh Delegation Visit Wednesday 3 March 2010

Key modes of climate variability over South Asia and uncertainties

in future climate projections

Page 2: Andrew Turner

Introduction

Climate of Bangladesh is particularly influenced by the South Asian summer monsoon, in addition to tropical cyclones and other low-pressure systems.This talk particularly focuses on:– the skill with which monsoon processes on various

timescales are modelled;– the uncertainty in future projections of the regional

climate, particularly in the IPCC AR4 / CMIP3 database.

Page 3: Andrew Turner

Outline

IntroductionHow is the mean monsoon and its seasonal cycle simulated in models?How certain are projections of change to seasonal mean rainfall?What about modes of monsoon variability and their teleconnections?Can we say anything about changes to short-timescale variability?Summary

Page 4: Andrew Turner

The mean monsoon...

Few models can simulate the major precipitation centers and their interannual variation.

from Annamalai et al. (2007) J. Climate

Page 5: Andrew Turner

...and its seasonal cycle

Only 6 CMIP3 models can reasonably simulate both the spatial distribution and seasonal cycle of rainfall over South Asia!

from Annamalai et al. (2007) J. Climate

Page 6: Andrew Turner

Uncertainties in late 21st century IPCC AR4 A1B mean projections

In this scenario, reasonable agreement between coupled climate models on surface temperature changes in the South Asia region: 3–4˚C Inter-model spread of precipitation projections is large for all the monsoon systems, including South Asia.

from Meehl et al. (2007) Global Climate Projections in the IPCC AR4

Page 7: Andrew Turner

Uncertainties in late 21st century IPCC AR4 A1B mean projections

From Turner & Slingo (2009b) Atmos. Sci. Lett. 10

Large uncertainty in mean JJA rainfall change over Bangladesh?

Page 8: Andrew Turner

Interannual variability and relationship with ENSO

Climate models have difficulty with these teleconnections, thus inhibiting accurate seasonal prediction.

Flooding in Bangladesh linked to the Southern Oscillation. El Niño events also influence upstream precipitation (e.g., Chowdhury, 2003, Theor. Appl. Climatol.) need institutional collaboration.

from Turner et al. (2005), Q. J. R. Meteorol. Soc. 131

Page 9: Andrew Turner

Interannual variability and relationship with ENSOThe ENSO-monsoon correlation waxes and wanes, and is currently in a weakened phase. Is this related to warming?

Variation in teleconnections on decadal timescales needs to be considered when designing seasonal forecasts.

Page 10: Andrew Turner

Boreal summer intraseasonal variability

EOF reconstruction of OLR during the active-break cycle of the monsoon.

Based on finding the patterns that explain the most variance of OLR in a 20-100 day period during the monsoon season

Note the distinct NW-SE tilt of the bands of active and suppressed convection

Taken from Annamalai & Sperber (2005) J. Atmos. Sci.

Page 11: Andrew Turner

Daily OLR anomalies + ‘MJO’ modal projection (Matt Wheeler)

‘MJO’ mode by filtering in the zonal wavenumber / frequency domain, Wheeler & Weickmann (2001)

Symmetric Anti-symmetric

‘MJO’ strongly implicated in 2009 summer: April to August

Page 12: Andrew Turner

Model capability at simulating BSISV

OBS

Northward propagation

From Sperber & Annamalai (2008) Clim. Dyn.

time

latit

ude

Page 13: Andrew Turner

OBS

eastward propagation

Model capability at simulating BSISVtim

e

longitude

Page 14: Andrew Turner

• Very few coupled climate models are able to simulate the northward and eastward propagation inherent to intraseasonal variability during boreal summer.

• More needs to be understood about the physical processes involved before we can be sure how their climate responses can be assessed.

Model capability at simulating BSISV

Page 15: Andrew Turner

A possible projection of BSISV at 2xCO2?

This example uses the Hadley Centre model HadCM3, which is able to well capture the seasonal cycle of rainfall in the region and northward propagation of BSISV.

Active and break modes of BSISV potentially intensified?

Active convection Break convection

2xCO2 minus control

from Turner & Slingo (2009a), Q. J. R. Meteorol. Soc. 135

Page 16: Andrew Turner

Spatial change in HadCM3: mean & subseasonal extremes

Changes in response to 2xCO2 in simulations with HadCM3: percentile extremes calculated for each JJA season then meaned.

from Turner & Slingo (2009a), Q. J. R. Meteorol. Soc. 135

Mean precipitation change 99th subseasonal percentile change

Response of subseasonal extreme is closely tied to signal of seasonal mean change.

Page 17: Andrew Turner

Uncertainty in spatial pattern of change to subseasonal rainfall extremes

Considerable uncertainty in mean and extreme projections. Predominantly positive in sign. Qualitative similarity, although extreme changes are of

larger magnitude.

Page 18: Andrew Turner

Allen & Ingram (2002) suggested changes to the heaviest rainfall events could be predicted based on the climate sensitivity and increases in atmospheric moisture suggested by Clausius-Clapeyron.Turner & Slingo (2009a) showed that this could also apply locally for the South Asia region in HadCM3.

Predictability in changes to the heaviest rainfall

Maximum increase of around 13%, as predicted by atmospheric warming at 2xCO2 and Clausius-Clapeyron. 13% 2.17K 6% / K

ratio

1xCO2

2xCO2

Page 19: Andrew Turner

Predictability in changes to the heaviest events: 3 case studies

We examine 3 model case studies of different behaviour in predictions vs. measured changes:

1) Changes above those predicted: gfdl_cm2_1 and 5 others (6/15).

2) Changes below predictions: ipsl_cm4 and 2 others (3/15).

3) Changes inline with predictions: cnrm_cm3 and 5 others (6/15), as well as HadCM3.

Some models suggest remarkable predictability of changes to maximum precipitation intensity based on thermodynamic arguments.Allen & Ingram (2002) argued that monsoons could undergo larger increases due to feedbacks between latent heat release and moisture convergence.

Page 20: Andrew Turner

Rainfall statistics

CMIP3 models overestimate drizzle at the expense of heavy precipitation.

Can we trust projections of extremes?

observations

Page 21: Andrew Turner

Summary

State-of-the-art coupled models have some skill in simulating the monsoon and its seasonal cycle of rainfall in South Asia.Short timescale variability and teleconnections could be improved.Further research is required to narrow the range of uncertainty in climate projections.

Page 22: Andrew Turner

Thank You

Email: [email protected]

Web: www.met.rdg.ac.uk/~sws05agt