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Extratropical cyclones, including winter westerly disturbances (WWD) over central Asia, are fundamental features of the atmosphere that maintain energy, momentum, and moisture at global scales while intimately linking large-scale circulation to regional-scale meteorology. Within high mountain Asia, WWD are the primary contributor to regional precipitation during winter. In this work, we present a novel WWD tracking methodology, which provides an inventory of location, timing, intensity, and duration of events, allowing for a comprehensive study of the factors that relate WWD to orographic precipitation, on an individual event basis and in the aggregate. We identify the relationship between the strength of disturbances, the state of the background environment during their propagation, and precipitation totals in the Karakoram/western Himalaya. We observe significant differences in convective and mechanical instability contributions to orographic precipitation as a function of the relationship between the intensity of WWD and the background temperature and moisture fields, which exhibit strong intraseasonal variability. Precipitation is primarily orographically forced during intense WWD with strong cross-barrier winds, while weaker WWD with similar precipitation totals are observed to benefit from enhanced instability due to high moisture content and temperature at low levels, occurring primarily in the late winter/premonsoon. The contribution of these factors is observed to fluctuate on a per-case basis, indicating important influences of intraseasonal oscillations and tropical-extratropical interactions on regional precipitation.

Abstract: The Indian monsoon system (IMS) is among the most complex and important climatic features on land. This study proposes a simple and robust method to investigate large-scale variations and changes in the IMS that accounts for fluctuations in amplitude, onset, and duration of the summer monsoon, including active and break phases, and the postmonsoon season. This study uses 35 years (1979–2013) of daily data from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) at 1° resolution and indicates great potential for application to other reanalyses and climate model datasets. The method is based on combined EOF (CEOF) analysis of variables associated with the IMS’s seasonal cycle (precipitation, circulation at 10 m, and temperature and specific humidity at 2 m). The first CEOF (CEOF-1) explains ~40% of the total variance and represents the continental-scale Asian monsoon. The second CEOF (CEOF-2) explains 11% of the variance and characterizes the Indian monsoon variability, including increased precipitation over western, central, and northern parts of India and the monsoon onset and demise over those regions. Thus, CEOF-2 is referred to as the large-scale index for the Indian monsoon system (LIMS). It is shown that LIMS’s amplitude is strongly correlated with the total June–September precipitation over India. LIMS is continuous in time and can be used to evaluate significant postmonsoon rainfall events that often affect the Indian subcontinent. Moreover, LIMS exhibits spectral variance on intraseasonal time scales that are associated with active and break phases of the monsoon during summer and enhanced rainfall in the postmonsoon period.