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Empirical/Statistical Monsoon Prediction. Long History Blanford (1884) Walker (1918,1924) Normand (1953) And many studies in the recent decades…. Sir. Gilbert Walker. Geographical Location of some of the important precursors of Indian Monsoon Rainfall.

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empirical statistical monsoon prediction
Empirical/Statistical Monsoon Prediction

Long History

Blanford (1884)

Walker (1918,1924)

Normand (1953)

And many studies in the

recent decades…

Sir. Gilbert Walker

current practices of dynamical monsoon rainfall prediction
Current 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
We set out to examine the skills of monsoon rainfall in detail by involving long simulations made using observed SSTs with a suite of multi-model, multi-member ensemble runs.
research questions
Research Questions..?
  • How skillful are the AGCMs in simulating Monsoon Rainfall over the Indian region?
  • Is specifying SSTs a constraint on realistic monsoon simulations?
  • How sensitive are monsoon simulations to initial conditions?
  • What is the impact of coupling on Monsoon-ENSO relationships?
  • Are the ENSO related western Indian Ocean SSTs acting as negative feed-back on Monsoon-ENSO relations?

GOGA: Obs SSTs globallyDTEPOGA: Obs SSTs in Deep Tropical East Pacific and Climatological SSTs elsewhereDTEPOGA_MLM: Same as DTEPOGA but a Mixed Layer Model used in the Indian Ocean


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

  • 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.
  • General belief that the ENSO related SSTs in the Indian Ocean (particularly the 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 observations.
  • In general the monsoon-ENSO links are much stronger in fully coupled models compared to the AGCMs forced with observed/predicted 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.