Indian Monsoon Variability and Predictability K Indian Monsoon Variability and Predictability K. Krishna Kumar CIRES Visiting Fellow kkrishna@colorado.edu Collaborators: Martin P. Hoerling Climate Diagnostics Center, Boulder and Balaji Rajagopalan University of Colorado, Boulder CDC, 10 Nov 2004

Indian Summer Monsoon Flow CDC, 10 Nov 2004

Mean Annual Cycle of All-India Mean Monthly Rainfall CDC, 10 Nov 2004

The Stability of the Indian Summer Monsoon CDC, 10 Nov 2004

All-India Summer Monsoon Rainfall (1871-2003) (Based on IITM Homogeneous Monthly Rainfall Data Set) CDC, 10 Nov 2004

Total Foodgrain Production in India and its Relation to Indian Rainfall CDC, 10 Nov 2004

Crop Area under crop (mn. hec) Irrigated area under crop (mn. hec.) Irrigated area as % of total area under crops Foodgrains 121 45 37 Rice 43 19 Wheat 23 84 Non-foodgrains 61 31 Groundnut 9 2 20 Cotton 7 3 33 Sugarcane 4 86 Total 183 64 35 IRRIGATION CDC, 10 Nov 2004

Empirical/Statistical Monsoon Prediction Long History Blanford (1884) Himalayan Snow-Monsoon Walker (1918,1924) Southern Osc. - Monsoon Normand (1953) And many studies in the recent decades… Sir. Gilbert Walker CDC, 10 Nov 2004

All-India Summer Monsoon Rainfall (1871-2003) (Based on IITM Homogeneous Monthly Rainfall Data Set) CDC, 10 Nov 2004

CDC, 10 Nov 2004

CDC, 10 Nov 2004

CDC, 10 Nov 2004

Composite SSTA of Drought (*) and Normal (*) Monsoon Years El Nino-Drought El Nino-Normal Difference CDC, 10 Nov 2004

Sea Surface Temp Anomalies in 1982 & 1997 JJA 82 Monsoon Rainfall: -13% SON 82 JJA 97 SON 97 Monsoon Rainfall: +2% CDC, 10 Nov 2004

Sea Surface Temp Anomalies: 1987 & 2002 Monsoon Rainfall: -18% JJA 87 SON 87 JJA 02 SON 02 Monsoon Rainfall: -19% CDC, 10 Nov 2004

Observed SST, Precipitation, Velocity Potential (200hPa) differences between composites of El Nino/Drought and El Nino/Normal years CDC, 10 Nov 2004

Idealized AGCM Experiments: AGCM: CCM3 (T42, 18 vert levels) A 20-member Ensemble with different atmospheric initial conditions is performed for each of the two El Nino flavors Runs initiated from 1st November and continued for 14 months until the end of December. The first two-months of simulations discarded. Climatological SSTs prescribed outside of ENSO region Control Expt: 150 year run is made with monthly-evolving climatological SSTs globally CDC, 10 Nov 2004

CCM3 SST, Precipitation, Velocity Potential (200hPa) differences between composites of El Nino/Drought and El Nino/Normal years CDC, 10 Nov 2004

Dominant EOFs in Tropical Pacific SSTs (Jan 1948- Sept 2004) (Trenberth and Stepaniak, 2001) CDC, 10 Nov 2004

CDC, 10 Nov 2004

Idealized SST Experiments with CCM3 3 sets of 10-member ensemble runs for (1) EOF1 (2) EOF1+EOF2 and (3) EOF1-EOF2 are performed by ramping the magnitude of SST anomaly patterns from 0 to 2σ at a rate of 0.2σ per year (in all 11 years). CDC, 10 Nov 2004

CDC, 10 Nov 2004

Increasing influence of TNI/EOF2 on the Indian Monsoon in recent decades Relation of NINO Indices and TNI on Monsoon NINO3.4 and TNI: 1871-2000 (Trenberth & Stepaniak, 2001) TNI Krishna Kumar et al (Science, 1999) CDC, 10 Nov 2004

Surface Temp Anomaly over North America: DJF 1983 1998 1988 2003 CDC, 10 Nov 2004

Summary so far… Stronger El Nino events are necessary for bigger monsoonal droughts – but not all El Nino events result in droughts The two El Nino flavors that produce drought/normal monsoons appear to be linked to the interplay between EOF1 and EOF2 of Tropical eastern Pacific SSTs While there is proven skill in predicting EOF1 at a reasonably longer lead-time, it is not yet clear if EOF2 has predictability so that it can be utilized in monsoon rainfall prediction The two El Nino flavors identified here have implications for tropical-wide seasonal rainfall anomalies as well as for the El Nino related north American teleconnections CDC, 10 Nov 2004

Prediction and Predictability of Indian Monsoon Rainfall CDC, 10 Nov 2004

Operational Official Monsoon Forecasts from India Meteorological Dept: 1988-2004 CDC, 10 Nov 2004

Popular Practices of Dynamical Monsoon Rainfall Prediction 2-tiered approach wherein SSTs are predicted first using a coupled model and then the AGCMs are forced using these SST fields Use persistent SSTs to run AGCMs Dynamical Downscaling using Regional Climate Models taking lateral boundary values from AGCM Simulations DEMETER CDC, 10 Nov 2004

Predicted and Observed Monsoon Rainfall 2002 CDC, 10 Nov 2004

Predicted and Observed Monsoon Rainfall 2004 CDC, 10 Nov 2004

We set out to examine the skills of monsoon rainfall in detail by involving long simulations made using observed SSTs (known as AMIP or GOGA) with a suite of multi-model, multi-member ensemble runs. CDC, 10 Nov 2004

Details of AGCMs Used S.No. Model Resolution Ens. Size Run Length 1 ECHAM4 2.8x2.8 24 1950-2002 2 ECHAM3 10 1950-1999 3 GFDL 2.5x2.0 1951-2002 4 NASA 9 5 ECPC 1.8x1.8 7 1950-2001 6 MRF (NCEP) 13 1951-1994 ARPEGE 8 1948-1997 CCM3 12 CAM2 15 CDC, 10 Nov 2004

Annual cycle of Indian Rainfall (8-30N; 70-90E) in AGCMS Land-Sea Land-only CDC, 10 Nov 2004

Questions??? How much is the SST driven Predictability in Indian Monsoon Rainfall? How sensitive are Indian monsoon rainfall simulations to the atmospheric initial conditions? How are the actual skills of model simulated Monsoon Rainfall compared to obs.? CDC, 10 Nov 2004

‘Perfect Prog’ Skills of Monsoon PERPROG For each of the AGCMs, the Monsoon Rainfall (8-30N; 70-90E) simulated in one ensemble run is correlated with the mean of Remaining runs CDC, 10 Nov 2004

Actual Skill (Corr. bet GCM rain and Obs.) Observed Indian Monsoon Rainfall Index (IITM) is used to compute correlations CDC, 10 Nov 2004

Impact of Initial Conditions on Monsoon Simulations CDC, 10 Nov 2004

Monsoon-ENSO Relation in AGCM Simulations Observed CDC, 10 Nov 2004

Climatology of Monsoon Rainfall CDC, 10 Nov 2004

ENSO Warm-Cold Composites of Precipitation and Temperature in CCM3 (uncoupled) and Observations CDC, 10 Nov 2004

Mixed Layer Model (MLM) Experiments GFDL R30 (14 Vertical levels) 31-layer Mixed Layer Model (Gasper, 1988; Alexander et al 2000) Observed SSTs prescribed in the region 15S-15N and 172E to South American Coast. In the rest of world oceans (all ice-free), SST changes are predicted by MLM 16-member simulations made for the period 1950-1999 (for more details see Lau and Nath, 2003) NCAR CAM2/Slab Ocean (Saravanan) The prescription of SSTs is similar to the above experiment (for more details see Giannini et al 2004) CDC, 10 Nov 2004

GFDL R30/MLM (16 Members) CDC, 10 Nov 2004

NCAR CAM2/Slab Ocean CDC, 10 Nov 2004

CDC, 10 Nov 2004

DEMETER A 9-member ensemble of 6-monthly forecasts issued 4 times S. No. Model Description Hindcast Period 1. ECMWF AGCM: NWP/IFS (T95) OGCM: HOPE (0.3 to 1.4º) 1958-2001 2. METEOFR AGCM: ARPEGE (T63) OGCM: OPA8.1 (0.5 to 2º) 3. LODYC AGCM: ECMWF IFS OGCM: OPA (2ºx2º) 1974-2001 4. UKMO (HadCM3)HadAm3 (2.5ºx3.75º) Hadley’s Ocean) 1959-2001 5. MPI AGCM: ECHAM5 (T42) OGCM: MPI-OM1 (next generation of HOPE) 1969-2001 6. CERFACS AGCM: ARPEGE OGCM: OPA 8.1 1980-2001 7. INGV AGCM: ECHAM4 (T42) 1973-2001 A 9-member ensemble of 6-monthly forecasts issued 4 times a year - Feb, May, August and November CDC, 10 Nov 2004

CDC, 10 Nov 2004

DEMETER Predicted and Observed NINO3.4 CDC, 10 Nov 2004

Summary The skills of current generation AGCMs in simulating monsoon rainfall in India even when forced with observed SSTs are very low. However, there appears to be much higher predictive potential as evidenced by the large PERPROG skills. No clear hint of higher skills either for models with better monsoon climatology or when multi-model-super ensembles are involved. Specification of SSTs in the Indian Ocean appears to be the main reason for the low-skills. An interactive ocean-atmosphere in the Indian Ocean (using even a simple mixed layer ocean model) produces more realistic monsoon simulations compared to specifying actual or climatological SSTs. The 2-tiered approach currently being pursued in seasonal forecasting needs 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 region in the west Pacific and the Indian Ocean. Further evaluation of skills and problems in DEMETER are needed. CDC, 10 Nov 2004

Thank You!!! CIRES/CU Balaji / Vijay Gupta Randy Marty Jon, Gary, Taiyi, Jamie, Jean, Lucia, Systems guys… IITM All of you… CDC, 10 Nov 2004

Response of Indian Monsoon Rainfall to Different El Nino Related SST Patterns Model Monsoon Rainfall ENSO - CTL NINODL- NINO ENSOGW- ENSO CDC, 10 Nov 2004

All-India Summer Monsoon Rainfall, 1871-1999 CDC, 10 Nov 2004

CDC, 10 Nov 2004

Low-frequency co-variability of Monsoon Rainfall and ENSO CDC, 10 Nov 2004

CDC, 10 Nov 2004

Difference in the Composites of Winter (Prior to Monsoon) Surface Air Temperatures over the Eurasian Region during El Nino Events pre-1980 and post-1980 periods (1981-97) – (1951-80) Diff. Climatologies of these Periods El Ninos CDC, 10 Nov 2004

ENSO Warm-Cold Composites of Precipitation and Temperature in CAM2 (uncoupled) and Observations CDC, 10 Nov 2004

GOGA: Obs SSTs globally DTEPOGA: Obs SSTs in Deep Tropical East Pacific and Climatological SSTs elsewhere DTEPOGA_MLM: Same as DTEPOGA but a Mixed Layer Model used in the Indian Ocean CDC, 10 Nov 2004

Progressive Improvement in Monsoon Rainfall Simulation Skills: 1 Progressive Improvement in Monsoon Rainfall Simulation Skills: 1. Un-coupled AMIP 2.Un-coupled AMIP only in eastern tropical Pacific and Climatological SSTs elsewhere 3.AMIP in the Pacific and Mixed Layer Model in the Indian Ocean CDC, 10 Nov 2004