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

2. Indian Summer Monsoon Flow
CDC, 10 Nov 2004

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

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

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

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

7. 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

8. 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

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

10. CDC, 10 Nov 2004

11. CDC, 10 Nov 2004

12. CDC, 10 Nov 2004

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

14. 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

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

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

17. 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

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

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

20. CDC, 10 Nov 2004

21. 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

22. CDC, 10 Nov 2004

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

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

25. 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

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

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

28. 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

29. Predicted and Observed Monsoon Rainfall 2002
CDC, 10 Nov 2004

30. Predicted and Observed Monsoon Rainfall 2004
CDC, 10 Nov 2004

31. 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

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

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

34. 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

35. ‘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

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

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

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

39. Climatology of Monsoon Rainfall
CDC, 10 Nov 2004

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

41. 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
(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

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

43. NCAR CAM2/Slab Ocean
CDC, 10 Nov 2004

44. CDC, 10 Nov 2004

45. 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) 2.
METEOFR
AGCM: ARPEGE (T63)
OGCM: OPA8.1 (0.5 to 2º) 3.
LODYC
AGCM: ECMWF IFS
OGCM: OPA (2ºx2º) 4.
UKMO
(HadCM3)HadAm3 (2.5ºx3.75º)
Hadley’s Ocean) 5.
MPI
AGCM: ECHAM5 (T42)
OGCM: MPI-OM1 (next generation
of HOPE) 6.
CERFACS
AGCM: ARPEGE
OGCM: OPA 8.1 7.
INGV
AGCM: ECHAM4 (T42)
A 9-member ensemble of 6-monthly forecasts issued 4 times
a year - Feb, May, August and November
CDC, 10 Nov 2004

46. CDC, 10 Nov 2004

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

48. 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

49. 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

50. 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

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

52. CDC, 10 Nov 2004

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

54. CDC, 10 Nov 2004

55. 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
( ) – ( )
Diff. Climatologies of these Periods
El Ninos
CDC, 10 Nov 2004

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

57. 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

58. 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