Interplay Between Subseasonal Rainfall and Global Predictors in Modulating Interannual to Multidecadal Predictability of the ISMR. Issue 1 (11th January 2021) - Saha, Subodh Kumar; Konwar, Mahen; Pokhrel, Samir; Hazra, Anupam; Chaudhari, Hemantkumar S.; Rai, Archana
Abstract: Skillful prediction of the Indian Summer Monsoon Rainfall (ISMR) has been a bottleneck problem for more than 100 years. The low seasonal predictability is attributed primarily to the chaotic nature of the subseasonal variability. Here, we show that these subseasonal variabilities rather have significant predictable contributions to the seasonal ISMR, varying on the interannual to multidecadal timescale. The subseasonal modes being the building blocks of the monsoon, their net linear contribution may approximate the predictability limit of the ISMR. It is estimated that an average of about 76% ( R ∼ 0.87) of the ISMR variance predictable around the 1960s is decreased to about 64% ( R ∼ 0.79) in the recent past four decades. It is suggested that improvements in the simulation of subseasonal, particularly the synoptic variability will be key to further improve the seasonal ISMR forecast skill. Plain Language Summary: Skillful prediction of seasonal (June‐to‐September) Indian Summer Monsoon Rainfall (ISMR) has been always a big challenge for the forecasters due to its complex nature of feedback. From the perspective of seasonal prediction, the subseasonal variability of the monsoon rainfall is primarily considered as noise (e.g., Webster et al., 1998). However, using 118 years of observed rainfall data, we show that subseasonal modes of monsoon (i.e., synoptic, supersynoptic, and intraseasonal oscillation) linked with the primary global predictors, contribute significantly to the seasonal anomaly of the ISMR. The complex association of subseasonal modes with the global predictors, which vary on interannual to the multidecadal timescale, shapes the predictability of the ISMR. As a result, the prediction of seasonal ISMR is more accurate in some decades than the others. It is estimated that an average of about 76% ( R ∼ 0.87) of the interannual ISMR variance was predictable around the 1960s and that has now decreased to about 64% ( R ∼ 0.79) in the past four decades. It is suggested that a better understanding of the mechanisms of subseasonal modes and consequently their reasonable simulation (space‐time statistics, particularly the synoptic variability) is the key to further improve the seasonal ISMR forecast. Key Points: The subseasonal variability, generally considered as noise, is found to have a significant predictable contribution to the seasonal Indian Summer Monsoon Rainfall (ISMR) The synoptic variability contributes a maximum to the ISMR predictability followed by supersynoptic and Monsoon Intraseasonal Oscillations A complex phase relationship between predictors and subseasonal variance modulates the ISMR predictability on decadal to multidecadal timescale