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Towards Earth System Modelling for Monsoon Projections Under Changing Climate

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Title: Towards Earth System Modelling for Monsoon Projections Under Changing Climate


1
National Monsoon Mission Scoping Workshop Indian
Institute of Tropical Meteorology 11 15 April,
2011
Towards Earth System Modelling for Monsoon
Projections Under Changing Climate Based on
CFS R. Krishnan Centre for Climate Change
Research Indian Institute of Tropical
Meteorology, Pune
2
Increase in Surface Temperature
Observations Predictions with Anthropogenic/Natura
l forcings Predictions with Natrual forcings
1.0º C
IPCC 2007
3
Challenges in assessment of future changes in
South Asian monsoon rainfall
  • Wide variations and uncertainties among the IPCC
    AR4 models in capturing the mean monsoon rainfall
    over South Asia (eg., Kripalani et al. 2007,
    Annamalai et al. 2007).
  • Systematic biases in simulating the spatial
    pattern of present-day mean monsoon rainfall
    (eg., Gadgil and Sajani, 1998 Kripalani et al.
    2007)
  • Realism of present-day climate simulation is an
    essential requirement for reliable assessment of
    future changes in monsoon

4
South Asia (5-35N, 65-95E))
Source Kripalani et al. 2010
5
Summer monsoon precipitation
IPCC models 20C3M 1979-1998
Observed rainfall (JJAS)
The 20c3m simulations attempt to replicate the
overall climate variations during the period
1850-present by imposing each modeling groups
best estimates of natural (eg., solar irradiance
and volcanic aerosols) and anthropogenic (eg.
GHG, sulfate aerosols and ozone) during this
period. Seven 20C3M models (GFDL CM2.0,
GFDL-CM2.1, MPI-ECHAM5, MRI, MIROC3-HIRES,
HadCM3, NCAR-PCM Source J. Shukla)
6
Questions On Attribution?
  • How much of the observed variability of the mean
    Indian Summer Monsoon rainfall due to Climate
    Change?
  • How much of the observed increase in temperature
    over India been decreased by increasing presence
    of aerosols?

Questions On Projections of Monsoon
  • What will happen to the monsoon hydrological
    cycle 50-100 years from now under different
    scenarios? In particular, will the quantum of
    seasonal mean rainfall increase or decrease and
    if so by how much?
  • What is the uncertainty in these projections? Can
    we quantify this uncertainty?
  • How can we reduce this uncertainty?

7
  • Some indicators of regional monsoon climate
  • Observed changes in frequency of monsoon
    depressions during the last century
  • Changes in the observed extreme rainfall events
    during the 20th century
  • Question
  • Attribution How much of the observed regional
    monsoon variability is due to global warming?

8
All India summer monsoon rainfall variability
Climatological Mean (JJAS)
Interannual Variability
Goswami et al., Science, 2006
9
Time series of count over CI
Low Moderate events
Heavy events (gt10cm)
V. Heavy events (gt15cm)
10
Time series of frequency of monsoon depressions
  • Decreasing frequency of monsoon depressions
    during last 2-3 decades (eg., Rajeevan et al.,
    2000 Amin and Bhide, 2003 Dash et al., 2004)
  • Recovery in the activity of monsoon depressions
    during the recent years (2005 2007)
  • Activity of monsoon depressions modulated by
    low-frequency variability of atmospheric
    large-scale circulation on inter-decadal
    time-scales

11
Strategy on Regional Climate Change Research at
IITM Centre for Climate Change Research
(CCCR) Ministry of Earth Sciences, Govt. of India
  • To build capacity in the country in high
    resolution coupled ocean-atmosphere modelling to
    address issues on Attribution and Projection of
    regional Climate Change
  • Earth System Model (ESM)
  • To provide reliable input for Impact Assessment
    studies
  • Dynamic downscaling of regional monsoon climate
    using high resolution models quantification of
    uncertainties
  • Observational monitoring Network with other
    Institutions

12
Earth System Model (ESM) development
  • Start with an atmosphere-ocean coupled model
    which has a realistic mean climate eg. NCEP CFS
  • Fidelity in capturing the global and monsoon
    climate
  • Realistic representation of monsoon interannual
    variability
  • Features of ocean-atmosphere coupled interactions
  • Include components of the ESM
  • Aerosol and Chemistry Transport Module
  • Biogeochemistry Module (Terrestrial and Marine)
  • .

13
  • Ongoing efforts towards development of Earth
    System Model (ESM) to address the Scientific
    Challenges of Global Climate Change and the Asian
    Monsoon System
  • Plan to include ESM components in the CFS-2
    coupled ocean-atmosphere model
  • CFS-2 coupled ocean-atmosphere model simulations
    on HPC initiated
  • Ocean Biogeochemistry Module coupled to MOM4.
    Runs are ongoing on HPC
  • Aerosol Transport Module coupled to AGCM. Runs
    are ongoing on HPC

Basic structure of ESM
14
Climatological (JJAS) mean monsoon rainfall from
CFS model 100 year free run
Climatological (JJAS) mean SST from CFS model
100 year free run
15
Taylor diagram of spatial pattern of
climatological seasonal mean (JJAS) rainfall
CFS Model High pattern correlation with
observed rainfall over India (IMD gridded
Dataset)
Source Seasonal Prediction Group, IITM
16
Source Roxy Mathew
17
(No Transcript)
18
Interannual variability of summer monsoon
rainfall in the CFS model 100 year free
run Domain 70E-90E 10N-30N
Time in years
CFS model JJAS climatological mean rain rate
5.80 mm / day (red line) Standard Deviation
of JJAS rain rate 0.82 mm / day Observed
rainfall (IMD) JJAS climatological mean rain
rate 7.5 mm /day Standard Deviation
0.85 mm / day
19
M O N S O O N A L D R O U G H T S
Complex Interactive Mechanisms of Monsoon
Droughts
Surface Boundary Conditions
Land Surface Process
SST
Eurasian Snow Cover
ENSO Cycle
Interactive Dynamics
Other Possible Causes
Low Frequency Intra-seasonal 30-50 day scale
Anthropogenic
Solar
Volcanic
North Ward Moving Episodes
Stratospheric
East Ward Moving Episodes
?
Synoptic Scale ltOne Week
Source Sikka, 1999
S.H. mid Latitudes
Indian and West Pacific Ocean
N.H. mid Latitudes
20
Monsoon droughts in CFS model
  • Atmosphere Ocean coupling in the tropical
    Indo-Pacific sector
  • Tropical central-eastern Pacific (El Nino /
    Modoki)
  • Eastern equatorial Indian Ocean (Negative IOD)
  • Monsoon and mid-latitude interactions

21
Monsoon drought composites in CFS model
Rainfall and wind (850 hPa) anomalies
SST and wind (850 hPa) anomalies in the CFS model
  • Anomalous warming of
  • the tropical Indo-Pacific
  • Atmosphere Ocean Coupled Interaction
  • Bjerknes-type feedback
  • El Nino - Modoki
  • Negative IOD

22
Anomaly composites during monsoon droughts CFS
model
Monsoon and Mid-latitude Interactions
Krishnan et al. J. Atmos. Sci., 2009
23
ESM components
  • Strong Monsoon Seasonal Cycle Unique feature of
    tropical Indian Ocean
  • Aerosols transport
  • Terrestrial and Marine Ecosystem
  • Quantify the effects of aerosol variability on
    the South Asian Monsoon - Aerosol transport
    module
  • Quantify the climate response to variations in
    the regional ecosystem - Ecosystem and
    biogeochemical modeling

24
Marine ecosystem and biogeochemistry modelling
  • Marine phytoplankton absorb sunlight within the
    350 - 700 nm spectral range and thereby modulate
    heat flux in the upper ocean
  • Ecosystem response in the tropical Indian Ocean
    is linked with the seasonal cycle of monsoon
    winds and Indian Ocean circulation
  • Variations in ocean biology influenced by climate
    phenomena - El Nino, IOD

Phytoplankton Zooplankton Detrius Nutrient
food web model
(Doney et al. 1996, Fasham et al. 2001, Moore et
al. 2001, 2004)
25
MOM4p1 forced ocean simulation 120 year spin up
Physical and Biogeochemical Parameters for
Tropical Indian Ocean
January
July
January
July
Source Aparna, Swapna
26
Source John Dunne, GFDL
27
Verification of MOM4p1 forced runs for Tropical
Pacific CORE forcing (1959 2004) Reproducibil
ity of the simulated SST and Chlorophyll
variability
Analysis of MOM4P1 runs by Raghu Loop 5 (1959
2004)
SST Anomaly, EOF1, (59.89 ) (1948 1992)
MOM4p1 runs and analysis made at CCCR Aparna
and Swapna
28
Analysis of MOM4P1 runs by Raghu
MOM4p1 runs and analysis made at CCCR Aparna
and Swapna
29
Modeling the effects of aerosols on the South
Asian monsoon
  • GHG have contributed to a total of 2.7 Wm-2 to
    the greenhouse effect since 1850. The
    contribution of aerosols other non-greenhouse
    factors is less certain (IPCC AR4, 2007)
  • Contrasting views on the impact of anthropogenic
    aerosols on South Asian monsoon climate
  • Weakening of monsoon circulation via., solar
    dimming (eg. Ramanathan et al. 2005)
  • Elevated Heat Pump (EHP) theory Aerosol heating
    over Tibetan Plateau during pre-monsoon months
    would intensify the monsoon Hadley circulation
    (eg. Lau et al. 2006)
  • EHP hypothesis is not supported in CALIPSO Lidar
    satellite observations (Kuhlmann and Quass, 2010)

30
Desert air and aerosol incursions during dry
Indian monsoon spells - TN Krishnamurti et al.
2010
Vertically integrated lower tropospheric (950
700 hPa) specific humidity (kg / kg)
Dry monsoon spell 10 19 June, 2009
Wet monsoon spell 14 20 July, 2009
Dry air
01 Aug 2004
18 June 2009
14 Aug 2005
16 July 2002
31
Advection of dry air aerosols from
extra-tropics into Indian region TN Krishnamurti
et al. 2010
Composite of AOD _at_ 550 nm during monsoon breaks
MODIS Terra / Aqua
West Asia Blocking High
V. Ravi Kiran, M. Rajeevan, V.B. Rao and N.P.
Rao, GRL, 2009
Break monsoon
Active monsoon
High AOD over Arabian Sea
High AOD Indo Gangetic plains
32
Modeling the effects of Aerosols on the South
Asian Monsoon
HAM (Hamburg Aerosol Module) Predicts evolution
of an ensemble of 7 interacting internally and
externally-mixed aerosol modes. Compounds
considered are Sulfate, Black Carbon, Organic
Carbon, Sea Salt, Mineral Dust
  • Main Components
  • Microphysical core (coagulation of aerosols,
    condensation of gas-phase SO2 on aerosol surface)
  • Aerosol radiative properties sink processes
  • Aerosol wet deposition
  • Emissions of mineral-dust (based on 10 m winds)
  • Sea salt emissions (based on 10 m winds)
  • Sulfur cycle (Inputs monthly oxidant fields )
  • Emissions of DMS (Inputs DMS sea-water
    concentrations calculations using 10m winds,
    SST)
  • Terrestrial biogenic DMS emissions are prescribed
  • AeroCom inventory for all other compounds

Experiment Boundary and Initial conditions
Control AGCM Climatological SST. Ensemble runs (22 members) starting from 22 perturbed IC of March and runs go through December
Aerosol AGCM Aerosol Module (HAM) Climatological SST. Ensemble runs (22 members) starting from 22 perturbed IC of March and runs go through December
33
AGCM with aerosol transport
Rainfall low level winds (JJAS)
Aerosol minus Control
Very slight increase in precipitation over
monsoon trough region
Simulations of HAM coupled to an AGCM on
PRITHVI ,CCCR, IITM
34
AOD and 850 hPa winds
JJAS temperature anomaly at 925 hPa Aerosol
minus Control
35
Time series of the JJAS seasonal mean monsoon
rainfall averaged over the region (70E 100 E
10N 30N) based on the 22 member ensemble
realizations for the two AGCM experiments (a)
With aerosols (b) No aerosols
36
Frequency distribution of rainfall over monsoon
region (70E 95E 10N 30N)
Frequency
Rainfall (mm / day)
Spatial map of difference in frequency of
rainfall events ( lt 50 mm / day) between the
Aerosol and Control simulations. The daily
rainfall at each grid point covers the June to
September monsoon season for 22 years
37
Break monsoon anomaly composites
Summary Conducted two sets of 22 member
ensemble AGCM runs with and without aerosols.
Both runs use prescribed monthly climatological
SST The frequency of low moderate rainfall
events over the Indo-Gangetic plains shows very
slight increase in Aerosol run as compared to
no-aerosol simulation Interannual variability
of monsoon rainfall in the 2 experiments is
uncorrelated AOD changes during break monsoons
in the GCM are broadly consistent with the
observed AOD anomaly pattern Monsoon internal
dynamics is dominantly seen. Role of aerosols in
affecting the monsoon rainfall and circulation is
being investigated.
38
High resolution regional climate change
scenarios and quantification of uncertainties
Provide reliable inputs for impact assessments
and contribute to IPCC AR5
  • High resolution dynamic downscaling of monsoon
    Baseline climate runs using WRF, RegCM and LMDZ
    partially completed. Future climate scenario
    runs to be initiated in January 2011.
  • Two member 19 year (1989 2007) run of WRF (50
    km) model completed. ERA Interim LBC
  • One member 19 year (1989 2007) run of RegCM (50
    km) model completed. ERA Interim LBC
  • One member 10 year (1979 1988) run of LMDZ (50
    km) model completed

39
LMDZ global atmospheric model Variable
resolution with zooming capability
Source Sabin, CCCR
40
Source Sabin
41
High resolution ( 35 km) dynamical downscaling
simulations using LMDZ over South Asia Proposed
at CCCR
Historical (1890-2005) Includes natural and
anthropogenic (GHG, aerosols, land cover etc)
climate forcing during the historical period
(1890 2005) 106 years Historical Natural
(1890 2005) Includes only natural climate
forcing during the historical period (1890
2005) 106 years
RCP 4.5 scenario (2006-2100) Future projection
run which includes both natural and anthropogenic
forcing based on the IPCC AR5 RCP 4.5 climate
scenario . The evolution of GHG and
anthropogenic aerosols in RCP 4.5 scenario
produces a global radiative forcing of 4.5 W
m-2 by 2100
42
Hydrologic Impacts of Climate Change
  • Large scale hydrologic impacts
  • Continental water balance projections
  • Water resource projections for India
  • Large scale water mass variation
  • River discharge projections
  • Runoff computation from GCMs with global river
    channel network
  • Lateral movement of water
  • River flow model for river routing
  • Runoff and discharge projections using macroscale
    hydrologic models Eg. Water Gap Global
    Hydrology Model (WGHM)
  • Global datasets for landuse, soil types,
    vegetation cover
  • River routing linear models
  • Validation with global datasets Global Runoff
    Data Center (GRDC)
  • Uncertainty modeling and decision support
  • Multimodel ensemble of GCM simulations
  • Uncertainty quantification of key hydrologic
    parameters at large scales
  • Exploring adaptation and mitigation measures

Source Deepashree Raje
43
Macroscale hydrologic modeling Hydrologic Impacts
of Climate Change
  • Variable infiltration capacity (VIC) macroscale
    model (Liang et al., 1994) at 1 deg. by 1 deg.
    resolution over Indian region
  • subgrid variability in land surface vegetation
    classes
  • subgrid variability in the soil moisture storage
    capacity, which is represented as a spatial
    probability distribution
  • subgrid variability in topography through the use
    of elevation bands
  • spatial subgrid variability in precipitation
  • Simulation of water balances for 1 deg x 1 deg
    grids
  • Inputs are time series of daily or sub-daily
    meteorological drivers (e.g. precipitation, air
    temperature, wind speed)
  • Land-atmosphere fluxes, and the water and energy
    balances at the land surface, are simulated at a
    daily or sub-daily time step
  • Daily runoff and baseflow routed using
    independent routing model (Lohmann et al., 1996)
  • Calibration and validation of model using current
    meteorologic forcings and observed discharge data
    in three river basins (Narmada, Ganga, Krishna)

44
Data sources
  • Digital elevation data at 1 km (USGS)
  • Land cover classification (UMD) at 1 km (UMD)
  • Soil texture mapping at 0.0833 deg (FAO)
  • Hydrologic data analysis using GIS
  • Basin delineations
  • Flow directions and accumulations at fine and
    coarse resolution (1 deg) grids
  • Area-weighted derived soil property maps at 1 deg
  • Area-weighted landcover maps at 1 deg
  • Discharge validation with global datasets
    Global runoff data center (GRDC)

45
DEM for study region
River routing for study basins
46
Soil Mapping Unit (SMU) classification
Land cover classification
47
Preliminary results Calibration
Observed discharge m3s-1
  • Calibration using data from four discharge
    stations Farakka (Ganga), Jamtara (Narmada),
    Garudeshwar (Narmada), Vijayawada (Krishna) for
    years 1965-1970

Source Deepashree Raje
48
Preliminary results Testing
Observed discharge m3s-1
  • Testing for years 1971 - 1975

49
Features of Dynamic Climate Data Portal
CCCR Climate Data Web Portal http//www.cccr.res.i
n
  • Visualize data with on-the-fly graphic
  • Easy and user friendly analysis of climate data
    through graphical display on the browser with one
    click
  • Example IMD daily rainfall (1951 to 2009)
  • URL http//cccr.hpc8080/CCCR
  • Step 1 Click on the above URL
  • Centre for Climate Change Research
  • Indian Institute of Tropical Meteorology, Pashan
    , Pune 411 008
  • Ministry of Earth Sciences, Govt. of India

50
Summary
  • Long term plans ( 3 years) to develop an Earth
    System Model (ESM)
  • A global atmosphere-ocean coupled model (CFS) is
    operational. A century long simulation and
    several other runs have been performed
  • Aspects of global and regional monsoon climate
    are realistically captured by CFS model
  • Realistic features of monsoon interannual
    variability is seen from the CFS simulations
    (e.g., Atmosphere-ocean coupling over tropical
    Indo-Pacific, Monsoon and mid-latitude
    interactions, etc)
  • Plans to improve the simulation of present day
    monsoon climate in the CFS model. Need to reduce
    model systematic biases.
  • Ongoing efforts to include ESM components in CFS
    model (ie., Aerosol transport module, Marine and
    Terrestrial Ecosystem and Biogeochemistry
    module, Sea-Ice module, etc).
  • Dynamic downscaling of regional monsoon climate
    using high resolution models
  • Downscaling simulations of present day and
    future monsoon climate scenarios will be
    completed by early 2012
  • Contribute to IPCC AR5 report through its
    activity

51
Thank you
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