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Interactions over South Asia between tropical depressions (TDs) and extratropical storms known as western disturbances (WDs) are known to cause extreme precipitation events, including those responsible for the 2013 floods over northern India. In this study, existing databases of WD and TD tracks are used to identify potential WD–TD interactions from 1979 to 2015; these are filtered according to proximity and intensity, leaving 59 cases that form the basis of this paper. Synoptic charts, vorticity budgets, and moisture trajectory analyses are employed to identify and elucidate common interaction types among these cases. Two broad families of interaction emerge. First, a dynamical coupling of the WD and TD, whereby either the upper- and lower-level vortices superpose (a vortex merger), or the TD is intensified as it passes into the entrance region of a jet streak associated with the WD (a jet-streak excitation). Second, a moisture exchange between the WD and TD, whereby either anomalous moisture is advected from the TD to the WD, resulting in anomalous precipitation near the WD (a TD-to-WD moisture exchange), or anomalous moisture is advected from the WD to the TD (a WD-to-TD moisture exchange). Interactions are most common in the post-monsoon period as the subtropical jet, which brings WDs to the subcontinent, returns south; there is a smaller peak in May and June, driven by monsoon onset vortices. Precipitation is heaviest in dynamically coupled interactions, particularly jet-streak excitations. Criteria for automated identification of interaction types are proposed, and schematics for each type are presented to highlight key mechanisms. [ABSTRACT FROM AUTHOR]

India Meteorological Department (IMD) has been using a Limited Area Model (LAM) on operational basis for the forecast up to 48 hours with the first guess fields for objective analysis and lateral boundary conditions from the global spectral model (T-80) run of the National Center for Medium Range Weather Forecasting (NCMRWF), New Delhi. In this paper the model code has been modified and made more flexible, delinking it from the NCMRWF (T-80). This has allowed the use of initial and boundary conditions directly from the NCEP Global Forecast System (GFS) products available at the resolution of 1° × 1° lat./long. The main interest in this study is to improve the analysis and forecast in the short range time scale (up to 72 hours) by improving the model (LAM) resolution and using better Initial and boundary conditions from the NCEP GFS instead of the NCMRWF T-80 model. Simulation experiments are performed on wide variety of synoptic situations which occur very often over the Indian sub-continent. The performance evaluation in terms of qualitative comparison between the model simulated outputs against actual observations and the outputs of the operational model indicates that the modified version of the model is capable to provide a improved numerical guidance on the occurrence of heavy rainfall in the 48-72 hours forecast scale. [ABSTRACT FROM AUTHOR]

The summer monsoon rainfall affects most of the population of the Indian subcontinent. A slight variation of strength and spatial distribution in monsoon rains has huge societal impacts. So understanding the significance of its variability and the factors that control this variability is an imperative task. The Indian monsoon (also regarded as a global phenomenon) varies with the global climatic components like geopotential height, sea surface temperature, outgoing long-wave radiation and mean sea level pressure. The paper presents a statistical analysis of rainfall (over India) and climatic components (over the Arabian Peninsula) and the relationship between them. The period (1979–2013) shows a decrease in monsoon rainfall over the country. During this period, there was an increase in the tropospheric temperature over the Arabian Peninsula. Rainfall showed a direct relationship with the tropospheric temperature and thickness that gets stronger during the period (1979–2013). Except for the northeastern region of India, the rest showed a strong positive correlation with the middle and upper tropospheric temperature over the Arabian Peninsula while the lower tropospheric temperature showed a weak relationship. However, this correlation gets weakened during the El Nino and La Nina years. The findings will be helpful to enhance the Indian rainfall variation and the climatic factors responsible for this variation. [ABSTRACT FROM AUTHOR]