Prediction of Indian Summer-Monsoon Onset Variability: A Season in Advance

Abstract

Monsoon onset is an inherent transient phenomenon of Indian Summer Monsoon and it was never envisaged that this transience can be predicted at long lead times. Though onset is precipitous, its variability exhibits strong teleconnections with large scale forcing such as ENSO and IOD and hence may be predictable. Despite of the tremendous skill achieved by the state-of-the-art models in predicting such large scale processes, the prediction of monsoon onset variability by the models is still limited to just 2–3 weeks in advance. Using an objective definition of onset in a global coupled ocean-atmosphere model, it is shown that the skillful prediction of onset variability is feasible under seasonal prediction framework. The better representations/simulations of not only the large scale processes but also the synoptic and intraseasonal features during the evolution of monsoon onset are the comprehensions behind skillful simulation of monsoon onset variability. The changes observed in convection, tropospheric circulation and moisture availability prior to and after the onset are evidenced in model simulations, which resulted in high hit rate of early/delay in monsoon onset in the high resolution model.

Climatology of landfalling atmospheric Rivers and associated heavy precipitation over the Indian coastal regions

“…In the context of non‐stationary climate, the seasonal and sub‐seasonal prediction of monsoonal rainfall based on large‐scale atmospheric circulation is a prominent concept (Kumar et al ., 1995; Mekanik and Imteaz, 2013; Surendran et al ., 2015). Some attempts have been made in recent studies over the Indian region (Kashid and Maity, 2012; Pradhan et al ., 2017). The present study explored such an insight in the context of seasonal characterization of AR frequency and found that SOI, IOD and Niño 3.4 can be useful predictors.…”

An Improved Prediction of Indian Summer Monsoon Onset From State‐of‐the‐Art Dynamic Model Using Physics‐Guided Data‐Driven Approach

“…Numerous and extensive studies have been done to evaluate the skill of the model in forecasting various aspects of monsoon like the seasonal mean precipitation (Jiang et al, ; Shukla et al, ), monsoon intraseasonal oscillations (Roxy et al, ; Sharmila et al, ), and monsoon‐El Nino–Southern Oscillation teleconnection (Kim et al, ). However, only very few studies have looked at the forecasting skill of ISM onset by CFSv2 (Pradhan et al, ; Saha, Pokhrel, et al, ). Most of these studies evaluated the skill of onset prediction by CFSv2 using different circulation‐based indices, but none attempted to improve the skill for onset prediction.…”

“…Multiple onset indices have been defined based on the large-scale circulation pattern and thermodynamics associated with the initiation of summer monsoon. The most widely used large-scale onset indices in literature (Pradhan et al, 2017;Sabeerali et al, 2012;Sahana et al, 2015;Saini et al, 2011;Singh et al, 2017) are the ΔTT-based index (Xavier et al, 2007), the hydrological onset and withdrawal index (HOWI; Fasullo & Webster, 2003), and the onset circulation index (OCI; Wang et al, 2009). These onset indices based on monsoon dynamics can be effectively used for the estimation of monsoon onset from model simulations.…”

Detection, variability, and predictability of monsoon onset and withdrawal dates: A review

“…Pradhan et al . () used a large‐scale method (Goswami and Xavier, ; Xavier et al ., ) and found forecast skill of the regional‐scale Indian onset at a 3‐month lead‐time using the Indian Institute of Tropical Meteorology version of the CFSv2 model. Bombardi et al .…”