7-8 November 2014
ICIMOD, Kathmandu, Nepal
Climate change and the South Asian
monsoon
Water and Air Challenges
in the HKH
International Workshop on
Under Climate and Environmental Change:
Dra Andy
Turner*Approach
Opportunities Using
Transdisciplinary
*NCAS-Climate,
7–8 November 2014
University of Reading, UK
Organized by International Centre for Integrated Mountain Development (ICIMOD)
Supported by Universität Hamburg, Cluster of Excellence Integrated Climate System Analysis
and Prediction (CliSAP), University of Reading, Walker Institute
Thanks to H. Annamalai, Liang Guo, Richard Levine,
Deepthi Marathayil
7-8 November 2014
ICIMOD, Kathmandu, Nepal
The monsoon in South Asia – major
modelling challenges and changing
climate
Dr Andy Turner*
*NCAS-Climate,
University of Reading, UK
Thanks to H. Annamalai, Liang Guo, Richard Levine,
Deepthi Marathayil
Seasonal 925hPa wind changes and
monsoons
DJF
West African Monsoon
JJA
Asian Monsoon
Austral Monsoon
Seasonal daily precipitation changes and
monsoons
DJF
West African Monsoon
JJA
Asian Monsoon
Austral Monsoon
Outline
 
 
 
 
Skill of the CMIP3/5 models at monsoon simulation
and future projections
The Arabian Sea as an example of model error – and
its impact
The role of anthropogenic aerosol emissions in the
20th century monsoon
The HKH at the confluence of tropical monsoons and
mid-latitude weather systems
Monsoon precipitation biases – a large
monsoon metrics exercise
 
 
From Sperber, …,Turner et al. (2012), Climate
Dynamics.
Large range of
skill at
simulating the
mean monsoon
precipitation in
CMIP3 and
CMIP5 models.
Mean JJAS precipitation
(left) and bias versus GPCP
obs (right)
Multi-model mean monsoon
precipitation biases in CMIP/5
 
CMIP3 and CMIP5 models show large dry biases over
India but wet biases over the WEIO and Maritime
Continent in boreal summer.
Beware
counterintuitive
colour scale.
Sperber, Annamalai, Kang, Kitoh, Moise, Turner, Wang and Zhou (2012)
Climate Dynamics.
Multi-model mean circulation biases in
CMIP3/5
 
Weak Somali Jet in CMIP3 and CMIP5.
Mean JJAS 850hPa winds (left) and bias versus ERA-40 (right)
Relationship between circulation and
precipitation biases in CMIP3/5
 
Strong evidence for connection between biases in
monsoon circulation and precipitation.
Scatter diagram of
pattern correlations of
simulation of JJAS
precipitation & 850hPa
winds
Sperber, Annamalai, Kang, Kitoh, Moise, Turner, Wang and Zhou (2012)
Climate Dynamics.
Future projections of mean monsoon
precipitation
JJAS precipitation change for CMIP3 models: 1pctto2x-picntrl
22xCMIP3 MME mean
 
 
4xCMIP3
Mean JJAS precipitation is shown to increase for much of South,
Southeast and East Asia with increasing CO2 concentrations.
From Turner & Annamalai (2012) Nature Climate Change 2
‘Reasonable model’ future projections
support multi-model mean
JJAS precipitation change for CMIP3/5 models: 1pctto2x-picntrl
4xCMIP5
 
4xCMIP3
Four CMIP5 models selected according to their pattern correlation for
monsoon precipitation over South, Southeast and East Asia
monsoon domain. (CCSM4, CNRM-CM5, GFDL-CM3, NorESM1-M.)
Uncertainties in IPCC 1pctto2x mean
projections
Large uncertainty in mean JJA rainfall change over Asian monsoon?
from Turner & Slingo (2009b) Atmos. Sci. Lett. 10
Mean monsoon change: summary
 
CMIP (IPCC) models offer huge diversity of skill at
simulating the South Asian monsoon
 
Projections of mean monsoon rain under increased
GHG forcing are generally positive but with large
diversity over the magnitude and spatial pattern
 
Increases occur owing to the enhanced availability of
moisture over the warmer Indian Ocean
 
Projections remain consistent when “best” models are
selected
Model uncertainty: Arabian Sea as an
example (Levine & Turner 2013, Clim. Dyn.)
 
CMIP5 models with cold springtime Arabian Sea a
weakened seasonal cycle of rainfall and lower
absolute rainfall levels under warming scenario
(RCP8.5)
Biases in the monsoon onset
 
 
Onset pentad using method of
Wang & Linho.
Delayed onset in CMIP3 and
CMIP5 models.
From Sperber et al. (2013) Clim. Dyn.; also Sperber & Annamalai (2014) Clim. Dyn.
Biases in the monsoon onset
 
 
Rainfall, wind KE, circulation indices all show later
monsoon onset in coupled GCMs (dotted) compared to
AGCMs (solid)
CMIP5 models all show delayed northward advance of
monsoon belt compared to AGCM version’ and later onset
at each gridpoint
Turner (2014, in
preparation)
Some issues relating to model bias
 
Coupled models as used in IPCC (CMIP5) still suffer
large biases for the monsoon but they are out best
option
 
Example SST cold Arabian Sea SST biases lead to:
 
- 
weakened monsoon rainfall
- 
Delayed monsoon onset
- 
Reduced response to GHG increases
See Levine & Turner (2012, Climate Dynamics),
Levine et al. (2013, Climate Dynamics), Marathayil et
al., (2013, Environ. Phys. Letts.) for more information
The uncertain role of aerosol for the
South Asian monsoon
All: 25 GCMs
BL: 14 GCMs with aerosol indirect effects
BR: 11 GSMs with direct effect only.
Area mean is calculated over South Asia
(5-35N,65-90E).
Seasonal (JJA) South Asia
precipitation, CMIP5 historical
runs: timeseries and late 20th
century minus pre-industrial
Guo, Turner & Highwood
(2014, Atmos. Chem. &
Phys. Disc.)
The uncertain role of aerosol for the
South Asian monsoon
All: 25 GCMs
BL: 14 GCMs with aerosol indirect effects
BR: 11 GSMs with direct effect only.
Area mean is calculated over South Asia
(5-35N,65-90E).
Guo, Turner & Highwood
(2014, Atmos. Chem. &
Phys. Disc.)
Some issues in monsoon-aerosol
modelling
 
Complexity of aerosol effects included in models
matters
 
Aerosol emissions have been large enough to reduce
monsoon rainfall over South Asia – counteracting
GHG
 
Both local and large-scale (hemispheric) effects are
important
 
Future RCPs rely on decreases in future aerosol
emissions. Can we rely on them?
 
See Guo, Turner, Highwood, ACPD (soon) for details
 
Irrespective of climate impacts, aerosol represent an
air quality problem
Key role of mid-latitude interactions with the
tropical monsoons: Pakistan 2010 vs. UA2013
Upper level flow July 2010
Upper level flow June 2013
Charts from Climate Prediction Center/NCEP and University of
Reading archive of ECMWF analysis
H
L
14-21 June 2013 upper level streamfunction
L
23-30 July 2010 upper level streamfunction
The end
Thank you!
See Turner & Annamalai (2012) Nature Climate Change 2:
587-595 or http://dx.doi.org/doi:10.1038/nclimate1495
[email protected]