LAUSR

Coupled models tend to underestimate Indian summer monsoon (ISM) rainfall over most of the Indian subcontinent. Present study demonstrates that a part of dry bias is arising from the discrepancies in Oceanic Initial Conditions (OICs). Two hindcast experiments are carried out using Climate Forecast System (CFSv2) for summer monsoons of 2012–2014 in which two different OICs are utilized. With respect to first experiment (CTRL), second experiment (AcSAL) differs by two aspects: usage of high-resolution atmospheric forcing and assimilation of only ARGO observed temperature and salinity profiles for OICs. Assessment of OICs indicates that the quality of OICs is enhanced due to assimilation of actual salinity profiles. Analysis reveals that AcSAL experiment showed 10% reduction in the dry bias over the Indian land region during the ISM compared to CTRL. This improvement is consistently apparent in each month and is highest for June. The better representation of upper ocean thermal structure of tropical oceans at initial stage supports realistic upper ocean stability and mixing. Which in fact reduced the dominant cold bias over the ocean, feedback to air-sea interactions and land sea thermal contrast resulting better representation of monsoon circulation and moisture transport. This reduced bias of tropospheric moisture and temperature over the Indian land mass and also produced better tropospheric temperature gradient over land as well as ocean. These feedback processes reduced the dry bias in the ISM rainfall. Study concludes that initializing the coupled models with realistic OICs can reduce the underestimation of ISM rainfall prediction. Plain Language Summary Seasonal forecast of summer monsoon is sensitive to the upper ocean state mainly over the tropical ocean. This upper ocean state is constituted by the temperature and salinity structure, errors in these fields can mislead the seasonal forecast. Present study demonstrated that apart from actual temperature profile data, salinity profile observations based ocean reanalysis produced better ocean state. This revised ocean reanalysis based ocean initial conditions are used for the hindcast of 2012 to 2014 summer monsoon and found improvement in the seasonal forecast. Prominent dry bias in seasonal forecast of rainfall over the monsoon core region as well as over the all India is getting reduced more than 10 %, which is even higher than the variability of the summer monsoon. Detail analysis brought out that improvement in the upper ocean heat content forecast supported realistic air sea interaction in the coupled model and provided reasonable moisture to the atmosphere. This leads to better forecast of moisture transport associated with the summer monsoon resulting reduction in the precipitation biases over the India as well as neighboring oceanic regions. Overall the present study confirms that realistic ocean state in the initial condition is vital for accurate seasonal forecast of Indian summer monsoon.