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/Natural forcings
Predictions with Natrual forcings
1.0º C
IPCC 2007 2

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 3

4. South Asia
(5-35N, 65-95E))
Source: Kripalani et al. 2010 4

5. Summer monsoon precipitation Observed rainfall (JJAS)
IPCC models: 20C3M
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) 5

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 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 (>10cm)
V. Heavy events (>15cm)

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 SST from CFS model – 100 year free run
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. CFSv2 precip JJAS 10 yr mean CMAP precip JJAS (1980-2009)
CFSv2 runs on PRITHVI by CCCR
Source: Roxy Mathew 16 16

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 Source: Sikka, 1999
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
Solar
Volcanic
Anthropogenic
North Ward
Moving Episodes
East Ward
Moving Episodes
Stratospheric ?
Synoptic Scale
<One Week
Source: Sikka, 1999
S.H. mid
Latitudes
Indian and West
Pacific Ocean
N.H. mid
Latitudes 19

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. SST and wind (850 hPa) anomalies in the CFS model
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. Monsoon-midlatitude interactions during droughts over India
Anomaly composites during monsoon droughts: CFS model
Monsoon and Mid-latitude Interactions
Rainfall and 850 hPa winds
Winds & temperature: 500 hPa
Wind anomalies: 200 hPa
Monsoon-midlatitude interactions during droughts over India
Cold air advection from mid-
latitude westerly troughs cools
middle and upper troposphere
Rossby response: Anomalous
Troughs over West-Central Asia
and Indo-Pak; a stagnant blocking
ridge over East Asia
Suppressed monsoon convection
over sub-continent forces Rossby
wave response extending over
sub-tropics and mid-latitudes
Decreases meridional temperature
gradient; dry winds decrease
convective instability, suppress
convection and weaken monsoon
Droughts emanate from
prolonged monsoon-breaks
Krishnan et al. J. Atmos. Sci., 2009 22

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. Phytoplankton – Zooplankton – Detrius – Nutrient food web model
Marine ecosystem and biogeochemistry modelling
Marine phytoplankton absorb sunlight within the 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) 24

25. MOM4p1 forced ocean simulation – 120 year spin up
Physical and Biogeochemical Parameters for Tropical Indian Ocean
SST and currents)
Chlorophyll
January
July
January
July
Source: Aparna, Swapna 25

26. Source: John Dunne, GFDL

27. Reproducibility of the simulated SST and Chlorophyll variability
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

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 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. Dry monsoon spell: 10 – 19 June, 2009
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
14 Aug 2005
01 Aug 2004
16 July 2002

31. Composite of AOD @ 550 nm during monsoon breaks – MODIS Terra / Aqua
Advection of dry air & aerosols from extra-tropics into Indian region: TN Krishnamurti et al. 2010
Composite of 550 nm during monsoon breaks – MODIS Terra / Aqua
West Asia Blocking High
10-19 June 2009
Winds hPa
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. Boundary and Initial conditions
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
Microphysical core calculates coagulation of aerosol particles, condensation of gas-phase sulfuric acid on the aerosol surface, binary nucleation of sulfate, and water uptake
Sulfur cycle model treats the prognostic variables DMS, sulfur dioxide, sulfate and their gas- and aqueous-phase reaction pathways, using pre-calculated monthly mean oxidant fields
Aerosol radiative properties and sink processes (dry deposition, sedimentation, and wet deposition) are parameterised based on dependence on the prognostic aerosol size distribution, composition, and mixing state and coupled to the ECHAM5 meteorology.
Aerosol radiative properties are calculated in the frame work of Mie theory. For each aerosol mode, effective refractive indices are calculated
The effective complex refractive indices and the Mie size parameters for each mode serve as input to look-up tables for the aerosol radiative properties, providing extinction cross section, single scattering albedo, and asymmetry parameter to the ECHAM5 radiation scheme
Aerosol wet deposition is parameterised in terms of the aerosol size distribution and mixing state via mode-specific scavenging ratios, specifying embedded and interstitial aerosol fractions in the cloudy part of a grid box and in convective updrafts.
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) 32 32

33. Rainfall & low level winds (JJAS)
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. JJAS temperature anomaly at 925 hPa
AOD and 850 hPa winds
JJAS temperature anomaly at 925 hPa
Aerosol minus Control

35. With aerosols No aerosols
Mean = mm / day
Stdv = 0.85 mm / day
Mean = mm / day
Stdv = 0.95 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

36. Frequency Rainfall (mm / day) Frequency distribution of rainfall
No Aerosols
Aerosols
Frequency distribution of rainfall
over monsoon region (70E – 95E;
10N – 30N)
Frequency
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

37. Rainfall No Aerosols With Aerosols AOD Break monsoon anomaly
composites
High AOD
Arabian Sea
Active
Break
High AOD Indo
Gangetic plains
V. Ravi Kiran, M. Rajeevan, V.B. Rao and N.P. Rao, GRL, 2009
No Aerosols
With Aerosols
Rainfall
AOD
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. 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
JJAS SLP and winds 850 hPa
JJAS rainfall
High resolution monsoon simulations: Global model with zoom over monsoon domain
Source: Sabin

41. High resolution ( ~ 35 km) dynamical downscaling simulations using LMDZ over South Asia: Proposed at CCCR
Historical ( ): 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 ( ): 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 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 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
Source: Deepashree Raje

48. Preliminary results : Testing
Observed discharge m3s-1
Testing for years

49. Features of Dynamic Climate Data Portal
CCCR Outreach Web Portal
CCCR Climate Data Web Portal
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:
Step 1: Click on the above URL
Centre for Climate Change Research
Indian Institute of Tropical Meteorology, Pashan , Pune –
Ministry of Earth Sciences, Govt. of India
CCCR

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
Quantify 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

51. Thank you