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

National Monsoon Mission Scoping Workshop Indian Institute of Tropical Meteorology

11 – 15 April, 2011

IPCC 2007

1.0º C1.0º C

Increase in Surface TemperatureIncrease in Surface Temperature

ObservationsPredictions with Anthropogenic/Natural forcingsPredictions with Natrual forcings

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 precipitationSummer monsoon precipitation

IPCC models: 20C3M1979-1998Observed 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)

Questions : On Attribution?Questions : On Attribution?

How much of the observed variability of the mean Indian How much of the observed variability of the mean Indian Summer Monsoon rainfall due to Climate Change?Summer Monsoon rainfall due to Climate Change?

How much of the observed increase in temperature over India How much of the observed increase in temperature over India been decreased by increasing presence of aerosols?been decreased by increasing presence of aerosols?

Questions : On Projections of Questions : On Projections of MonsoonMonsoon

What will happen to the monsoon hydrological cycle 50-100 What will happen to the monsoon hydrological cycle 50-100 years from now under different scenarios? In particular, will the years from now under different scenarios? In particular, will the quantum of seasonal mean rainfall increase or decrease and if so quantum of seasonal mean rainfall increase or decrease and if so by how much?by how much?

What is the uncertainty in these projections? Can we quantify What is the uncertainty in these projections? Can we quantify this uncertainty?this uncertainty?

How can we reduce 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)

•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

Time series of frequency of monsoon depressions

Strategy on Regional Strategy on Regional Climate Change Research at IITMClimate Change Research at IITM

Centre for Climate Change Research (CCCR)Centre for Climate Change Research (CCCR)Ministry of Earth Sciences, Govt. of IndiaMinistry of Earth Sciences, Govt. of India

To build capacity in the country in high resolution coupled To build capacity in the country in high resolution coupled ocean-atmosphere modelling to address issues on ocean-atmosphere modelling to address issues on Attribution Attribution and Projection and Projection of regional Climate Changeof regional Climate Change

Earth System Model (ESM)Earth System Model (ESM)

To provide reliable input for Impact Assessment studies To provide reliable input for Impact Assessment studies Dynamic downscaling of regional monsoon climate using high Dynamic downscaling of regional monsoon climate using high

resolution models; quantification of uncertaintiesresolution models; quantification of uncertainties

Observational monitoring: Network with other Institutions Observational monitoring: Network with other Institutions

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) … … .

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 modelPlan to include ESM components in the CFS-2 coupled ocean-atmosphere model

CFS-2 coupled ocean-atmosphere model simulations on HPC initiatedCFS-2 coupled ocean-atmosphere model simulations on HPC initiated

Ocean Biogeochemistry Module coupled to MOM4. Runs are ongoing on HPCOcean Biogeochemistry Module coupled to MOM4. Runs are ongoing on HPC

Aerosol Transport Module coupled to AGCM. Runs are ongoing on HPCAerosol 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)

CFSv1 precip JJAS 100 yr mean

CFSv2 runs on PRITHVI by CCCR

Source: Roxy Mathew

CFS modelJJAS 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

Interannual variability of summer monsoon rainfall in the CFS model – 100 year free runDomain: 70E-90E; 10N-30N

Time in years

Anthropogenic

Surface BoundaryConditions

Land Surface Process

SSTEurasian

Snow Cover

Other Possible Causes

Solar

ENSOCycle

Low FrequencyIntra-seasonal

30-50 day scale

Synoptic Scale<One Week

Volcanic

Stratospheric

M O N S O O N A L D R O U G H T S

Interactive Dynamics

North Ward Moving Episodes

East WardMoving Episodes

S.H. midLatitudes

Indian and West Pacific Ocean

N.H. mid Latitudes

Complex Interactive Mechanisms of Monsoon Droughts

Source: Sikka, 1999

?

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

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

Monsoon-midlatitude interactions during droughts over India

Cold air advection from mid- latitude westerly troughs coolsmiddle 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

Rainfall and 850 hPa winds

Winds & temperature: 500 hPa

Wind anomalies: 200 hPa

Anomaly composites during monsoon droughts: CFS model

Krishnan et al. J. Atmos. Sci., 2009

Monsoon and Mid-latitude Interactions

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 phytoplankton absorb sunlight within the 350 - 700 nm spectral range Marine phytoplankton absorb sunlight within the 350 - 700 nm spectral range and thereby modulate heat flux in the upper oceanand thereby modulate heat flux in the upper ocean

Ecosystem response in the tropical Indian Ocean is linked with the seasonal cycle Ecosystem response in the tropical Indian Ocean is linked with the seasonal cycle of monsoon winds and Indian Ocean circulation of monsoon winds and Indian Ocean circulation

Variations in ocean biology influenced by climate phenomena - El Nino, IODVariations in ocean biology influenced by climate phenomena - El Nino, IOD

Marine ecosystem and biogeochemistry modelling

Phytoplankton – Zooplankton – Detrius – Nutrient food web model

(Doney et al. 1996, Fasham et al. 2001, Moore et al. 2001, 2004)

SST and currents)

Chlorophyll Chlorophyll

SST and currents)

MOM4p1 forced ocean simulation – 120 year spin up

Physical and Biogeochemical Parameters for Tropical Indian Ocean

January

January

July

July

Source: Aparna, Swapna

Source: John Dunne, GFDL

SST Anomaly, EOF1, (59.89 %): (1948 – 1992)

Analysis of MOM4P1 runs by Raghu

Loop 5: (1959 – 2004)

MOM4p1 runs and analysis made at CCCR – Aparna and Swapna

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

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 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)

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

18 June 2009 16 July 2002 14 Aug 2005 01 Aug 2004

Dry air

West Asia Blocking High

10-19 June 2009Winds 700-300 hPa

Advection of dry air & aerosols from extra-tropics into Indian region: TN Krishnamurti et al. 2010

Composite of AOD @ 550 nm during monsoon breaks – MODIS Terra / Aqua

High AOD overArabian Sea

Active monsoon Break monsoon

High AOD IndoGangetic plains

V. Ravi Kiran, M. Rajeevan, V.B. Rao and N.P. Rao, GRL, 2009

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

Modeling the effects of Aerosols on the South Asian Monsoon

ExperimentExperiment Boundary and Initial conditionsBoundary and Initial conditions

ControlControl AGCMAGCM Climatological SST. Ensemble runs (22 members) starting Climatological SST. Ensemble runs (22 members) starting from 22 perturbed IC of March and runs go through December from 22 perturbed IC of March and runs go through December

AerosolAerosol AGCM + Aerosol AGCM + Aerosol Module (HAM)Module (HAM)

Climatological SST. Ensemble runs (22 members) starting Climatological SST. Ensemble runs (22 members) starting from 22 perturbed IC of March and runs go through Decemberfrom 22 perturbed IC of March and runs go through December

Rainfall & low level winds (JJAS)

AGCM with aerosol transport

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

No aerosols

Mean = 12.09 mm / day

Stdv = 0.85 mm / day

Mean = 12.25 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

Frequency distribution of rainfall over monsoon region (70E – 95E; 10N – 30N)

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

No Aerosols

Aerosols

Rainfall (mm / day)

Fre

quen

cy

Break monsoon anomaly

composites

No Aerosols

With Aerosols

Rainfall

Rainfall

AOD

With Aerosols

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.

High AOD Arabian Sea

ActiveBreak

High AOD IndoGangetic plains

V. Ravi Kiran, M. Rajeevan, V.B. Rao and N.P. Rao, GRL, 2009

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

LMDZ global atmospheric model: Variable resolution with zooming capability

Source: Sabin, CCCR

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 hPaJJAS rainfall

High resolution monsoon simulations: Global model with zoom over monsoon domain

Source: Sabin

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

High resolution ( ~ 35 km) dynamical downscaling simulations using LMDZ over South Asia: Proposed at CCCR

Hydrologic Impacts of Climate ChangeHydrologic Impacts of Climate Change Large scale hydrologic impactsLarge scale hydrologic impacts

Continental water balance projectionsContinental water balance projections Water resource projections for IndiaWater resource projections for India Large scale water mass variationLarge scale water mass variation

River discharge projectionsRiver discharge projections Runoff computation from GCMs with global river channel networkRunoff computation from GCMs with global river channel network

Lateral movement of water Lateral movement of water River flow model for river routing River flow model for river routing

Runoff and discharge projections using macroscale hydrologic Runoff and discharge projections using macroscale hydrologic models – Eg. Water Gap Global Hydrology Model (WGHM)models – Eg. Water Gap Global Hydrology Model (WGHM)

Global datasets for landuse, soil types, vegetation coverGlobal datasets for landuse, soil types, vegetation cover River routing linear modelsRiver routing linear models Validation with global datasets: Global Runoff Data Center (GRDC)Validation with global datasets: Global Runoff Data Center (GRDC)

Uncertainty modeling and decision supportUncertainty modeling and decision support Multimodel ensemble of GCM simulationsMultimodel ensemble of GCM simulations Uncertainty quantification of key hydrologic parameters at large scalesUncertainty quantification of key hydrologic parameters at large scales Exploring adaptation and mitigation measuresExploring adaptation and mitigation measures

Source: Deepashree Raje

Macroscale hydrologic Macroscale hydrologic modelingmodeling

Hydrologic Impacts of Climate ChangeHydrologic Impacts of Climate Change

43

Variable infiltration capacity (VIC) macroscale model (Liang et al., 1994) Variable infiltration capacity (VIC) macroscale model (Liang et al., 1994) at 1 deg. by 1 deg. resolution over Indian regionat 1 deg. by 1 deg. resolution over Indian region

subgrid variability in land surface vegetation classessubgrid variability in land surface vegetation classes subgrid variability in the soil moisture storage capacity, which is represented as a subgrid variability in the soil moisture storage capacity, which is represented as a

spatial probability distributionspatial probability distribution subgrid variability in topography through the use of elevation bandssubgrid variability in topography through the use of elevation bands spatial subgrid variability in precipitationspatial subgrid variability in precipitation

Simulation of water balances for 1 deg x 1 deg gridsSimulation of water balances for 1 deg x 1 deg grids

Inputs are time series of daily or sub-daily meteorological drivers (e.g. Inputs are time series of daily or sub-daily meteorological drivers (e.g. precipitation, air temperature, wind speed) precipitation, air temperature, wind speed)

Land-atmosphere fluxes, and the water and energy balances at the land Land-atmosphere fluxes, and the water and energy balances at the land surface, are simulated at a daily or sub-daily time step surface, are simulated at a daily or sub-daily time step

Daily runoff and baseflow routed using independent routing model Daily runoff and baseflow routed using independent routing model (Lohmann et al., 1996)(Lohmann et al., 1996)

Calibration and validation of model using current meteorologic forcings Calibration and validation of model using current meteorologic forcings and observed discharge data in three river basins (Narmada, Ganga, and observed discharge data in three river basins (Narmada, Ganga, Krishna)Krishna)

Data sourcesData sources Digital elevation data at 1 km (USGS)Digital elevation data at 1 km (USGS) Land cover classification (UMD) at 1 km Land cover classification (UMD) at 1 km

(UMD)(UMD) Soil texture mapping at 0.0833 deg (FAO)Soil texture mapping at 0.0833 deg (FAO) Hydrologic data analysis using GISHydrologic data analysis using GIS

Basin delineationsBasin delineations Flow directions and accumulations at fine and coarse Flow directions and accumulations at fine and coarse

resolution (1 deg) gridsresolution (1 deg) grids Area-weighted derived soil property maps at 1 degArea-weighted derived soil property maps at 1 deg Area-weighted landcover maps at 1 degArea-weighted landcover maps at 1 deg Discharge validation with global datasets : Discharge validation with global datasets :

Global runoff data center (GRDC)Global runoff data center (GRDC)44

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River routing for study basins

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25°0'0"N

24°0'0"N

23°0'0"N

22°0'0"N

21°0'0"N

20°0'0"N

19°0'0"N

18°0'0"N

17°0'0"N

16°0'0"N

15°0'0"N

14°0'0"N

13°0'0"N

12°0'0"N

11°0'0"N

10°0'0"N

9°0'0"N

8°0'0"N

7°0'0"N

6°0'0"N

5°0'0"N

Soil Mapping Unit (SMU) classification

Land cover classification

Preliminary results : Preliminary results : CalibrationCalibration

Calibration using data from four discharge stations : Farakka (Ganga), Jamtara Calibration using data from four discharge stations : Farakka (Ganga), Jamtara (Narmada), Garudeshwar (Narmada), Vijayawada (Krishna) for years 1965-1970(Narmada), Garudeshwar (Narmada), Vijayawada (Krishna) for years 1965-1970

47

Observed discharge m3s-1

Source: Deepashree Raje

Preliminary results : Preliminary results : TestingTesting

Testing for years 1971 - 1975Testing for years 1971 - 1975

Observed discharge m3s-1

CCCR

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 Climate Data Web Portalhttp://www.cccr.res.in

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 modelsDownscaling 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