10-11 December 2007, Park Inn Hotel, York

http://www.ncas.ac.ukNCAS Conference 2007

10-11 December 2007, Park Inn Hotel, York

The Indian monsoon and climate change

Andrew Turner, Julia Slingo & Pete Inness

NCAS-Climate

Walker Institute for Climate System Research, University of Reading


Introduction

Indian summer monsoon affects the lives of more than 2 billion people across South Asia, and provides more than 75% of total annual rainfall.

Agricultural and industrial consumers require reliable source of water, together with an appropriate forecast on seasonal and intraseasonal timescales.

How monsoon characteristics may change in the future is a key goal of climate research.


Outline

Introduction

Model details

The mean monsoon

Extremes & active-break cycles

Interannual variability and predictability

Decadal-timescale uncertainties

Summary


Model experiments

Hadley Centre coupled model HadCM3 run at high vertical resolution (L30).

This better represents intraseasonal tropical convection1 and has an improved atmospheric response to El Niño2.

Control (1xCO2) and future climate (2xCO2) integrations used to test the impact of increased GHG forcing.Further integration of each climate scenario to test the role of systematic model biases.

1P.M. Inness, J.M. Slingo, S. Woolnough, R. Neale, V. Pope (2001). Clim. Dyn. 17: 777--793.

2H. Spencer, J.M. Slingo (2003). J. Climate 16: 1757--1774.


Mean response of the monsoon to 2xCO2


Mean monsoon response in the AR4 models

Fig 10.91: some consistency in the JJA response of precipitation over India to A1B forcing with 2xCO2 result (but within inter-model spread).

Fig 10.121: less than 80% of models agree on annual mean change in precip over India.

1G. Meehl et al. (2007) Global Climate Projections. In: Climate Change 2007: The Physical Science Basis.

10.9 10.12Of the six AR4 models which reasonably simulate the monsoon precipitation climatology of the 20th century, all show general increases in seasonal rainfall over India in the 1pctto2x runs2.

2H. Annamalai, K. Hamilton, K. R. Sperber (2007). J. Climate 20: 1071--1092


Systematic model bias and the uncertain response to 2xCO2


Uncertainty in monsoon precipitation response to 2xCO2

Systematic bias seems to mask full impact of changing climate

1A.G. Turner, P.M. Inness, J.M. Slingo (2007a). QJRMS 133: 1143—1157.


Intraseasonal variability & extreme events

Intraseasonal modes represent the largest variations of the Indian summer monsoon.2002 2007


Active-break index

Simple active-break index constructed from All-India rainfall.

Active-break events defined as rainfall anomaly to seasonal cycle lying outside ±1σ, persisting for at least five days.


Absolute precipitation in active & break events

Clear intensification of active and break events at 2xCO2.

Intensification of break anomalies at 2xCO2 is tempered by wetter climatological seasonal cycle.


Interannual variability

Year-to-year variability increases at 2xCO2 (+24% using Webster-Yang index).

Increases are predominantly tied to ENSO.

1xCO2

2xCO2

strong-weak monsoon precip and 850hPa wind


Monsoon-ENSO teleconnections: lag correlations

The teleconnection is generally robust with increased CO2 forcing.

Systematic model bias can have a dramatic impact on the teleconnection to ENSO.

1A.G. Turner, P.M. Inness, J.M. Slingo (2007a). QJRMS 133: 1143—1157.

JJAS Indian rainfall vs. Niño-3 SST


Monsoon-ENSO teleconnection: moving correlations

Recent decades have seen a marked decline in the strength of the teleconnection.

HadISST vs. All-India gauge data

Model teleconnection varies with similar amplitude to observations despite fixed CO2 forcing.

model rainfall


Interdecadal uncertainty?

One possible source of uncertainty lies in El Nino, which is known to consist of different mechanisms1,2 which vary in strength over time.

1A.V. Federov, S.G. Philander (2001). J. Clim. 14: 3086—3101.

2E. Guilyardi (2006). Clim. Dyn. 26: 329—348.

Such changes to the nature of El Nino have been found in 2xCO2 model integrations, with associated impacts on the monsoon3.

3A.G. Turner, P.M. Inness, J.M. Slingo (2007b). QJRMS 133: 1159—1173.


Summary

Some qualitative agreement on future increases in the mean monsoon.

Systematic model biases may mask the full climate change signal in monsoon regions.

Increases in monsoon variability on interannual and intraseasonal timescales.

Interdecadal variations in the monsoon and its drivers add additional uncertainty to climate change projections.

Documents

10-11 December 2007, Park Inn Hotel, York