  Skilful prediction of the seasonal Indian summer monsoon (ISM) rainfall
(ISMR) at least one season in advance has great socio-economic value. It
represents a lifeline for about a sixth of the world's population. The ISMR
prediction remained a challenging problem with the sub-critical skills of the
dynamical models attributable to limited understanding of the interaction among
clouds, convection, and circulation. The variability of cloud hydrometeors
(cloud ice and cloud water) in different time scales (3-7 days, 10-20 days and
30-60 days bands) are examined from re-analysis data during Indian summer
monsoon (ISM). Here, we also show that the 'internal' variability of cloud
hydrometeors (particularly cloud ice) associated with the ISM sub-seasonal
(synoptic + intra-seasonal) fluctuations is partly predictable as they are
found to be tied with slowly varying forcing (e.g., El Ni\~no and Southern
Oscillation). The representation of deep convective clouds, which involve ice
phase processes in a coupled climate model, strongly modulates ISMR variability
in association with global predictors. The results from the two sensitivity
simulations using coupled global climate model (CGCM) are provided to
demonstrate the importance of the cloud hydrometeors on ISM rainfall
predictability. Therefore, this study provides a scientific basis for improving
the simulation of the seasonal ISMR by improving the physical processes of the
cloud on a sub-seasonal time scale and motivating further research in this
direction.
