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Dynamical Prediction of Indian Dynamical Prediction of Indian Monsoon Rainfall and the Role ofMonsoon Rainfall and the Role of

Indian OceanIndian Ocean

K. Krishna KumarK. Krishna KumarCIRES Visiting Fellow, University of Colorado, BoulderCIRES Visiting Fellow, University of Colorado, Boulder

kkrishna@colorado.edu kkrishna@colorado.edu

Martin P. HoerlingMartin P. HoerlingClimate Diagnostics Center, BoulderClimate Diagnostics Center, Boulder

andandBalaji RajagopalanBalaji Rajagopalan

University of Colorado, BoulderUniversity of Colorado, Boulder

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Current Practices of Dynamical Current Practices of Dynamical Monsoon Rainfall PredictionMonsoon Rainfall Prediction

2-tiered approach wherein SSTs are 2-tiered approach wherein SSTs are predicted first using a coupled model and predicted first using a coupled model and then the AGCMs are forced using these then the AGCMs are forced using these SST fieldsSST fields

Use persistent SSTs to run AGCMsUse persistent SSTs to run AGCMs Dynamical Downscaling using Regional Dynamical Downscaling using Regional

Climate Models taking lateral boundary Climate Models taking lateral boundary values from AGCM Simulationsvalues from AGCM Simulations

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Skills of the Present Generation of AGCMsSkills of the Present Generation of AGCMs(Reproduced from the IRI Website)(Reproduced from the IRI Website)

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We set out to examine the skills of We set out to examine the skills of monsoon rainfall in detail by involving long monsoon rainfall in detail by involving long simulations made using observed SSTs simulations made using observed SSTs with a suite of multi-model, multi-member with a suite of multi-model, multi-member ensemble runs.ensemble runs.

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Research Questions..?Research Questions..? How skillful are the AGCMs in simulating Monsoon How skillful are the AGCMs in simulating Monsoon

Rainfall over the Indian region?Rainfall over the Indian region? Is specifying SSTs a constraint on realistic Is specifying SSTs a constraint on realistic

monsoon simulations?monsoon simulations? How sensitive are monsoon simulations to initial How sensitive are monsoon simulations to initial

conditions?conditions? What is the impact of coupling on Monsoon-ENSO What is the impact of coupling on Monsoon-ENSO

relationships?relationships? Are the ENSO related western Indian Ocean SSTs Are the ENSO related western Indian Ocean SSTs

acting as negative feed-back on Monsoon-ENSO acting as negative feed-back on Monsoon-ENSO relations?relations?

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Details of AGCMs UsedDetails of AGCMs Used

S.No.S.No. ModelModel ResolutionResolution Ens. SizeEns. Size Run LengthRun Length

11 ECHAM4ECHAM4 2.8x2.82.8x2.8 2424 1950-20021950-2002

22 ECHAM3ECHAM3 2.8x2.82.8x2.8 1010 1950-19991950-1999

33 GFDLGFDL 2.5x2.02.5x2.0 1010 1951-20021951-2002

44 NASANASA 2.8x2.82.8x2.8 99 1950-20021950-2002

55 ECPCECPC 1.8x1.81.8x1.8 77 1950-20011950-2001

66 MRF (NCEP)MRF (NCEP) 2.8x2.82.8x2.8 1313 1951-19941951-1994

77 ARPEGEARPEGE 2.8x2.82.8x2.8 88 1948-19971948-1997

88 CCM3CCM3 2.8x2.82.8x2.8 1212 1950-19991950-1999

99 CAM2CAM2 2.8x2.82.8x2.8 1515 1950-20011950-2001

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Simulation of Tropical Rain bands during DJF in Simulation of Tropical Rain bands during DJF in AGCMsAGCMs

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Simulation of Tropical Rain bands during JJA in Simulation of Tropical Rain bands during JJA in AGCMsAGCMs

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Climatology of Monsoon RainfallClimatology of Monsoon Rainfall

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Monsoon-ENSO Relation in AGCM Monsoon-ENSO Relation in AGCM SimulationsSimulations

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Impact of Initial Conditions on Monsoon SimulationsImpact of Initial Conditions on Monsoon Simulations

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ENSO Warm-Cold Composites of Precipitation and ENSO Warm-Cold Composites of Precipitation and TemperatureTemperature

in CAM2 (uncoupled) and Observationsin CAM2 (uncoupled) and Observations

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Monsoon-ENSO Teleconnections: Coupled vs. Uncoupled Monsoon-ENSO Teleconnections: Coupled vs. Uncoupled ModelsModels

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GOGA: Obs SSTs GOGA: Obs SSTs globallyglobally

DTEPOGA: Obs SSTs in DTEPOGA: Obs SSTs in Deep Tropical East Deep Tropical East Pacific and Pacific and Climatological SSTs Climatological SSTs elsewhereelsewhere

DTEPOGA_MLM: Same DTEPOGA_MLM: Same as DTEPOGA but a as DTEPOGA but a Mixed Layer Model Mixed Layer Model used in the Indian used in the Indian OceanOcean

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Progressive Progressive Improvement in Improvement in Monsoon Rainfall Monsoon Rainfall Simulation Skills:Simulation Skills: 1. 1. Un-coupled AMIP Un-coupled AMIP

2.2. Un-coupled AMIP Un-coupled AMIP only in only in eastern eastern tropical Pacific and tropical Pacific and Climatological Climatological SSTs SSTs elsewhere elsewhere

3.3. AMIP in the Pacific AMIP in the Pacific and Mixed and Mixed Layer Model Layer Model in the Indian in the Indian OceanOcean

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SummarySummary The skills of current generation AGCMs in simulating monsoon rainfall in India The skills of current generation AGCMs in simulating monsoon rainfall in India

even when forced with observed SSTs are very low.even when forced with observed SSTs are very low. However, there appears to be much higher predictive potential as evidenced by However, there appears to be much higher predictive potential as evidenced by

the large PERPROG skills.the large PERPROG skills. No clear hint of higher skills either for models with better monsoon climatology or No clear hint of higher skills either for models with better monsoon climatology or

when multi-model-super ensembles are involved.when multi-model-super ensembles are involved. Specification of SSTs in the Indian Ocean appears to be the main reason for the Specification of SSTs in the Indian Ocean appears to be the main reason for the

low-skills.low-skills. An interactive ocean-atmosphere in the Indian Ocean (using even a simple mixed An interactive ocean-atmosphere in the Indian Ocean (using even a simple mixed

layer ocean model) produces more realistic monsoon simulations compared to layer ocean model) produces more realistic monsoon simulations compared to specifying actual or climatological SSTs.specifying actual or climatological SSTs.

General belief that the ENSO related SSTs in the General belief that the ENSO related SSTs in the Indian Ocean Indian Ocean (particularly the (particularly the western Indian Ocean and the Arabian Sea) might act as a negative feedback on western Indian Ocean and the Arabian Sea) might act as a negative feedback on Monsoon-ENSO teleconnections appears to be wrong based on the above Monsoon-ENSO teleconnections appears to be wrong based on the above observations.observations.

In general the monsoon-ENSO links are much stronger in fully coupled models In general the monsoon-ENSO links are much stronger in fully coupled models compared to the AGCMs forced with observed/predicted SSTs.compared to the AGCMs forced with observed/predicted SSTs.

The 2-tiered approach currently being pursued in seasonal forecasting needs The 2-tiered approach currently being pursued in seasonal forecasting needs immediate revision to achieve higher forecast skills for the Indian region. We immediate revision to achieve higher forecast skills for the Indian region. We also believe, this might be true for some other countries located in the warm pool also believe, this might be true for some other countries located in the warm pool region in the west Pacific and the Indian Ocean.region in the west Pacific and the Indian Ocean.

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The Climatic Impacts on The Climatic Impacts on Indian AgricultureIndian Agriculture

K. Krishna KumarK. Krishna KumarK. Rupa Kumar, R.G. Ashrit, N.R. Deshpande K. Rupa Kumar, R.G. Ashrit, N.R. Deshpande

and James Hansen (IRI, New York)and James Hansen (IRI, New York)

Indian Institute of Tropical Meteorology, Indian Institute of Tropical Meteorology, Pune, IndiaPune, India

((krishna@tropmet.res.inkrishna@tropmet.res.in))

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ObjectivesObjectives

• To generate data on all-India and state-level To generate data on all-India and state-level Agricultural IndicesAgricultural Indices

• To Identify Crops and Regions in India having To Identify Crops and Regions in India having strong Climatic Signal which can be used for strong Climatic Signal which can be used for Developing various Climate Applications Developing various Climate Applications initiatives/programs involving National and Multi-initiatives/programs involving National and Multi-national Institutions and Individual Scientistsnational Institutions and Individual Scientists

• Establishing Climate Signal in various Agricultural Establishing Climate Signal in various Agricultural Indices has implications for Climate Change Indices has implications for Climate Change Impact Assessment Studies as wellImpact Assessment Studies as well

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Agriculture Agriculture FactsFacts

India lives mainly in its villages, 600,000 of them Roughly 65% of the population is rural India’s growth in per capita food production during 1979-92

was about 1.6% per annum – the highest in the world during this period

Agriculture provides livelihood to about 65% of the labor force Agriculture contributes nearly 29% to the GDP In terms of fertilizer consumption, India ranks 4th in the world About 43% of India’s geographical area is used for agriculture

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IRRIGATIONIRRIGATION CropCropArea Area under under crop crop (mn. (mn. hec)hec)

Irrigated Irrigated area area

under under crop crop (mn. hec.)(mn. hec.)

Irrigated Irrigated area as % area as % of total of total

area area under under cropscrops

FoodgrainsFoodgrains 121121 4545 3737

RiceRice 4343 1919 4545

WheatWheat 2323 1919 8484

Non-Non-foodgrainsfoodgrains

6161 1919 3131

GroundnutGroundnut 99 22 2020

CottonCotton 77 33 3333

SugarcaneSugarcane 44 33 8686

TotalTotal 183183 6464 3535

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DATADATA

Production/Area/ YieldProduction/Area/ Yield• Total foodgrains• Kharif/Rabi Rice• Winter Wheat• Groundnut• Sorghum• Cereals• Oilseeds• Pulses• Sugarcane

SourceSource

• Agricultural Situation in Agricultural Situation in IndiaIndia

• India Data BaseIndia Data Base

OrganizationsOrganizations

• Center for Monitoring Center for Monitoring Indian EconomyIndian Economy

• Dept. of Agriculture and Dept. of Agriculture and Cooperation, Ministry of Cooperation, Ministry of Agriculture, Govt. of Agriculture, Govt. of IndiaIndia

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Crop AreasCrop Areas

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Monsoon Monsoon VariabilityVariability

Intraseasonal Interannual Decadal/Century Millennia & longer

Onset/withdrawal; Active and break-monsoon phases;30-50 day oscillations; severe rainstorms

Droughts and floods

Changes in the frequency of droughts and floods

Changes in the areal extents of monsoons

Atmospheric variability;tropical-midlatitude interactions;Soil moisture;Sea surface temperatures

Atmospheric interactions;El Niño/ Southern Oscillation;Top layers of tropical oceans;Snow cover;Land surface characteristics

Monsoon circulation variations;Deep ocean changes;Greenhouse gases increase;Human activities;Biospheric changes;Volcanic dust

Global climate excursions;Ice ages;Warm epochs;Sun-earth geometry

Factors

Factors

Features

Features

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All-India Summer Monsoon Rainfall (1871-2001)All-India Summer Monsoon Rainfall (1871-2001)(Based on IITM Homogeneous Monthly Rainfall Data Set)(Based on IITM Homogeneous Monthly Rainfall Data Set)

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JJA-1JJA-1 SON-1SON-1

DJF-1DJF-1 MAMMAM

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Regional Climate Signal in Regional Climate Signal in Indian Agriculture IndicesIndian Agriculture Indices

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Area under Area under Major Food Major Food Crops in Crops in India and % India and % Irrigated Irrigated during during 1950-19981950-1998

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Total Total Foodgrain Foodgrain Production in Production in India and its India and its Relation to Relation to Indian Indian RainfallRainfall

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Kharif Rice Kharif Rice Production Production in India in India and its and its Relation to Relation to Indian Indian RainfallRainfall

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Total Total Wheat Wheat Production Production in India in India and its and its Relation to Relation to Indian Indian RainfallRainfall

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Kharif Groundnut Production

and its relation to

Indian Rainfall

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Total Sorghum

Production and its

relation to Indian

Rainfall

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Global Climate Signal in Global Climate Signal in Indian AgricultureIndian Agriculture

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SummarySummary Most rainfed crops show statistically

significant relation with Regional and Global Climatic Factors, the exception being Sorghum.

Wheat and Sugarcane, the two most irrigated crops, do not show any climatic signal.

Groundnut and Kharif (Summer) Rice in India show very strong regional and global climatic signals and should be targeted for climate application as well as climate change impact assessment studies.

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Predicted and Observed Monsoon Rainfall 2002Predicted and Observed Monsoon Rainfall 2002

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Schematic view of sea surface temperature and tropical rainfall in the the equatorial Pacific Ocean during normal, El Niño, and La Niña conditions

..

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Global Impacts Global Impacts of ENSOof ENSO

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Low-frequency co-variability of Monsoon Low-frequency co-variability of Monsoon Rainfall and ENSORainfall and ENSO

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Difference in the Composites of Winter (Prior to Monsoon) Surface Air Difference in the Composites of Winter (Prior to Monsoon) Surface Air Temperatures over the Eurasian Region during El Nino Events pre-Temperatures over the Eurasian Region during El Nino Events pre-

1980 and post-1980 periods1980 and post-1980 periods

(1981-97) – (1951-80)(1981-97) – (1951-80)El NinosEl Ninos

Diff. Climatologies of these PeriodsDiff. Climatologies of these Periods

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Relation between Indian Monsoon Rainfall and Relation between Indian Monsoon Rainfall and 200 (A,B) and the Composites of 200 (A,B) and the Composites of 200 for El Nino 200 for El Nino

Events pre-,post-80’s (C,D)Events pre-,post-80’s (C,D)

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Sea Surface Temp Anomalies in 1982 & Sea Surface Temp Anomalies in 1982 & 19971997

JJA 82 SON 82

JJA 97 SON 97

Monsoon Rainfall: -13%

Monsoon Rainfall: +2%

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Sea Surface Temp Anomalies: 1987 & Sea Surface Temp Anomalies: 1987 & 20022002

JJA 87 SON 87

JJA 02 SON 02

Monsoon Rainfall: -18%

Monsoon Rainfall: -19%

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Precipitation Anomalies: JJAPrecipitation Anomalies: JJA

1982 1997

1987 2002

Monsoon Rainfall: -13% Monsoon Rainfall: +2%

Monsoon Rainfall: -18% Monsoon Rainfall: -19%

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Precipitation Anomaly in NE Australia (DJF) and NE Precipitation Anomaly in NE Australia (DJF) and NE Brazil (JFM) in 1988 and 1998Brazil (JFM) in 1988 and 1998

1988 1998

1988 1998

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Surface Temp Anomaly over North Surface Temp Anomaly over North America: DJFAmerica: DJF

1983 1998

1988 2003

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Precipitation/Forecasts of SST and Precipitation in JAS 2002 by Different GCMs

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SST Patterns Used for ENSO SST Patterns Used for ENSO ExperimentsExperiments

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SST Patterns Used for Indian Ocean SST Patterns Used for Indian Ocean ExperimentsExperiments

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AA

AA

CC

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Response of Indian Monsoon Rainfall to DifferentResponse of Indian Monsoon Rainfall to DifferentEl Nino Related SST PatternsEl Nino Related SST Patterns

Model Model MonsooMonsoon n RainfallRainfall

ENSO - ENSO - CTLCTL

NINODL-NINODL-NINONINO

ENSOGW-ENSOGW-ENSOENSO

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