Download Based on CFS - Dr. R. Krishnan - Indian Institute of Tropical

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
Increase in Surface Temperature
Observations
Predictions with Anthropogenic/Natural forcings
Predictions with Natrual forcings
1.0º C
IPCC 2007
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
South Asia
(5-35N, 65-95E))
Source: Kripalani et al. 2010
Summer monsoon precipitation
Observed rainfall (JJAS)
IPCC models: 20C3M
1979-1998
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)
Questions : On Attribution?
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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?
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?
All India summer monsoon rainfall
variability
Climatological Mean (JJAS)
Interannual Variability
Goswami et al., Science, 2006
Time series of count
over CI
Low & Moderate events
Heavy events (>10cm)
V. Heavy events (>15cm)
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
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
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To provide reliable input for Impact Assessment studies
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Earth System Model (ESM)
Dynamic downscaling of regional monsoon climate using high
resolution models; quantification of uncertainties
Observational monitoring: Network with other Institutions
Earth System Model (ESM)
development
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Start with an atmosphere-ocean coupled model which has
a realistic mean climate – eg. NCEP CFS
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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
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Aerosol and Chemistry Transport Module
Biogeochemistry Module (Terrestrial and Marine)
…
…
.
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
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Ocean Biogeochemistry Module coupled to MOM4. Runs are ongoing on HPC
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Aerosol Transport Module coupled to AGCM. Runs are ongoing on HPC
Basic structure
of ESM
Climatological (JJAS) mean monsoon rainfall from CFS model – 100 year free run
Climatological (JJAS) mean SST from CFS model – 100 year free run
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
CFSv2 precip JJAS 10 yr mean
CMAP precip JJAS (1980-2009)
Source: Roxy Mathew
CFSv1 precip JJAS 100 yr mean
CFSv2 runs on PRITHVI by CCCR
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
MONSOONAL
DROUGHTS
Complex
Interactive
Mechanisms
of Monsoon
Droughts
Surface Boundary
Conditions
Land
Surface
Process
SST
ENSO
Cycle
Interactive Dynamics
Other Possible Causes
Low Frequency
Intra-seasonal
30-50 day scale
North Ward
Moving Episodes
Eurasian
Snow Cover
Solar
East Ward
Moving Episodes
Volcanic
Anthropogenic
Stratospheric ?
Synoptic Scale
<One Week
Source: Sikka, 1999
S.H. mid
Latitudes
Indian and West
Pacific Ocean
N.H. mid
Latitudes
Monsoon droughts in CFS model
•Atmosphere – Ocean coupling in the tropical IndoPacific sector
Tropical central-eastern Pacific (El Nino / Modoki)
Eastern equatorial Indian Ocean (Negative IOD)
•Monsoon and mid-latitude interactions
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
Anomaly composites during
monsoon droughts: CFS model
Monsoon and Mid-latitude Interactions
Monsoon-midlatitude interactions during droughts over India
Rainfall and 850 hPa winds
Winds & temperature: 500 hPa
Droughts emanate from
prolonged monsoon-breaks
Suppressed monsoon convection
over sub-continent forces Rossby
wave response extending over
sub-tropics and mid-latitudes
Rossby response: Anomalous
Troughs over West-Central Asia
and Indo-Pak; a stagnant blocking
ridge over East Asia
Wind anomalies: 200 hPa
Decreases meridional temperature
gradient; dry winds decrease
convective instability, suppress
convection and weaken monsoon
Cold air advection from midlatitude westerly troughs cools
middle and upper troposphere
Krishnan et al. J. Atmos. Sci., 2009
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
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)
MOM4p1 forced ocean simulation – 120 year spin up
Physical and Biogeochemical Parameters for Tropical Indian Ocean
SST and currents)
SST and currents)
January
July
Chlorophyll
Chlorophyll
January
Source: Aparna, Swapna
July
Source: John Dunne, GFDL
Verification of MOM4p1 forced runs for Tropical Pacific: CORE forcing (1959 – 2004)
Reproducibility 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
Analysis of MOM4P1
runs by Raghu
MOM4p1 runs and
analysis made at
CCCR – Aparna
and Swapna
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 premonsoon 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)
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
18 June 2009
16 July 2002
14 Aug 2005
01 Aug 2004
Advection of dry air & aerosols from extra-tropics into Indian region: TN Krishnamurti et al. 2010
West Asia Blocking High
Composite of AOD @ 550 nm during
monsoon breaks – MODIS Terra / Aqua
10-19 June 2009
Winds 700-300 hPa
V. Ravi Kiran, M. Rajeevan, V.B. Rao and N.P. Rao, GRL, 2009
Active monsoon
Break monsoon
High AOD over
Arabian Sea
High AOD Indo
Gangetic plains
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
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
AOD and 850 hPa winds
JJAS temperature anomaly at 925 hPa
Aerosol minus Control
With
aerosols
Mean = 12.25 mm / day
Stdv = 0.95 mm / day
No aerosols
Mean = 12.09 mm / day
Stdv = 0.85 mm / day
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
Frequency
Aerosols
No Aerosols
Rainfall (mm / day)
Spatial map of difference in frequency of
rainfall events ( < 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
Frequency distribution of rainfall
over monsoon region (70E – 95E;
10N – 30N)
Break monsoon anomaly
composites
Rainfall
No Aerosols
V. Ravi Kiran, M. Rajeevan, V.B. Rao and N.P. Rao, GRL, 2009
Active
High AOD
Arabian
Sea
Break
High AOD Indo
Gangetic plains
Rainfall
Summary:
With Aerosols
AOD
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
With Aerosols
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.
High resolution regional climate change scenarios
and quantification of uncertainties
Provide reliable inputs for impact assessments and contribute to IPCC AR5
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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.
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Two member 19 year (1989 : 2007) run of WRF (50 km) model
completed. ERA Interim LBC
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One member 19 year (1989 : 2007) run of RegCM (50 km) model
completed. ERA Interim LBC
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One member 10 year (1979 : 1988) run of LMDZ (50 km) model
completed
LMDZ global atmospheric model: Variable resolution with zooming capability
Source: Sabin, CCCR
High resolution monsoon simulations: Global model with zoom over monsoon domain
JJAS rainfall
JJAS SLP and winds 850 hPa
LMD model
1 degree (Global)
LMDZ model
1/3 degree zoom for
Monsoon Domain
(40-110E; 15S-30N)
&
1 degree outside
Initial runs made at CCCR on PRITHVI, IITM
Source: Sabin
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
Hydrologic Impacts of Climate Change
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Large scale hydrologic impacts
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Continental water balance projections
Water resource projections for India
Large scale water mass variation
River discharge projections
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Runoff computation from GCMs with global river channel network
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Runoff and discharge projections using macroscale hydrologic models – Eg. Water Gap
Global Hydrology Model (WGHM)
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Lateral movement of water
River flow model for river routing
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
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Multimodel ensemble of GCM simulations
Uncertainty quantification of key hydrologic parameters at large scales
Exploring adaptation and mitigation measures
Source: Deepashree Raje
Macroscale hydrologic modeling
Hydrologic Impacts of Climate Change
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Variable infiltration capacity (VIC) macroscale model (Liang et al., 1994) at 1 deg. by 1 deg.
resolution over Indian region
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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
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Simulation of water balances for 1 deg x 1 deg grids
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Inputs are time series of daily or sub-daily meteorological drivers (e.g. precipitation, air
temperature, wind speed)
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Land-atmosphere fluxes, and the water and energy balances at the land surface, are simulated
at a daily or sub-daily time step
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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)
43
Data sources
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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
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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)
44
DEM for study region
River routing for study basins
45
98°0'0"E
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Soil Mapping Unit (SMU) classification
41°0'0"N
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Land cover classification
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46
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Preliminary results : Calibration
Ganga river discharge at Farakka
80000
60000
15000
Observed discharge m3s-1
40000
Narmada river discharge at
Garudeshwar
10000
5000
20000
0
Jan 1965 May 1966 Sep 1967 Feb 1969 Jun 1970
-20000
0
Jan 1965 May 1966 Sep 1967 Feb 1969 Jun 1970
-5000
Narmada river discharge at Jamtara
Krishna river discharge at Vijayawada
5000
20000
4000
15000
3000
2000
1000
0
Jan
-1000 1965 May 1966 Sep 1967 Feb 1969 Jun 1970
10000
5000
0
Jan 1965 May 1966 Sep 1967 Feb 1969 Jun 1970
-5000
Calibration using data from four discharge stations : Farakka (Ganga), Jamtara (Narmada), Garudeshwar
(Narmada), Vijayawada (Krishna) for years 1965-1970
Source: Deepashree Raje
47
Preliminary results : Testing
Ganga river discharge at Farakka (testing)
80000
70000
60000
50000
40000
30000
20000
10000
0
Jan 1971
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
Jan 1971
Observed discharge m3s-1
15000
Narmada river discharge at Garudeshwar
(testing)
10000
5000
May 1972
Sep 1973
Feb 1975
0
Jan 1971
Narmada discharge at Jamtara (testing)
May 1972
Sep 1973
Feb 1975
May 1972
Sep 1973
Feb 1975
Krishna discharge at Vijayawada (testing)
8000
7000
6000
5000
4000
3000
2000
1000
0
Jan 1971
May 1972
Testing for years 1971 - 1975
Sep 1973
Feb 1975
CCCR Climate Data Web Portal
http://www.cccr.res.in
Features of Dynamic Climate Data Portal

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.hpc:8080/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
CCCR
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., Atmosphereocean 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
Quantify
to IPCC AR5 report through its activity
uncertainties in regional monsoon projections using results from multiple models
Share
model data and conduct inter-disciplinary collaborative research towards impact assessment,
vulnerability and adaptation.
Hydrological
Modeling recently started