Abstract/Summary

Monsoon low-pressure systems (LPSs) are synoptic-scale systems that form during boreal summer, mainly over the head of the Bay of Bengal (BoB). However, regional varieties can also form over the Arabian Sea and near Sri Lanka. Despite their ability to cause catastrophic floods in the Indian subcontinent, there has been insufficient exploration of their predictability and prediction skill. This thesis examines LPS prediction and structure as well as large-scale controls on their frequency in Subseasonal-to-Seasonal (S2S) prediction models. Using a feature-tracking algorithm, we identify LPSs in eleven S2S models during a common reforecast period of June–September 1999–2010, verifying the results against ERA-Interim (ERA-I) and MERRA-2 reanalyses. Moreover, we examine characteristics of LPS regional varieties using ERA-I. The S2S models simulate tracks and structure of LPSs reasonably well; however, all models underestimate their frequency, and BoM, CMA and HMCR models have large biases in their simulation. The subseasonal probabilistic frequency predictions by BoM, CMA, CNRM and ECMWF models are the most accurate. Among regional varieties, Arabian Sea LPSs are least frequent. Short-lived BoB LPSs are most frequent and bring the most precipitation to eastern India. We then examine the modulation of LPSs on different time scales: the tropical intraseasonal oscillation modulates genesis of all varieties, and La Ni˜na and negative Indian Ocean Dipole enhance genesis of Sri Lankan LPSs. Most S2S models correctly simulate enhanced LPS frequency when the active phase of the Madden-Julian Oscillation is over the Indian Ocean and Maritime Continent. Large-scale conditions, such as the position of the tropical easterly jet and mid-tropospheric relative humidity, play a role in determining whether BoB LPSs continue their propagation across north-central India. These results provide a framework for understanding LPS predictability, envisaging improved disaster preparedness in the Indian subcontinent.