ERA-Interim reanalysis data from the past 35 years have been used with a newly developed feature tracking algorithm to identify Indian monsoon depressions originating in or near the Bay of Bengal. These were then rotated, centralized, and combined to give a fully three-dimensional 106-depression composite structure—a considerably larger sample than any previous detailed study on monsoon depressions and their structure. Many known features of depression structure are confirmed, particularly the existence of a maximum to the southwest of the center in rainfall and other fields and a westward axial tilt in others. Additionally, the depressions are found to have significant asymmetry owing to the presence of the Himalayas, a bimodal midtropospheric potential vorticity core, a separation into thermally cold (~−1.5 K) and neutral (~0 K) cores near the surface with distinct properties, and the center has very large CAPE and very small CIN. Variability as a function of background state has also been explored, with land–coast–sea, diurnal, ENSO, active–break, and Indian Ocean dipole contrasts considered. Depressions are found to be markedly stronger during the active phase of the monsoon, as well as during La Niña. Depressions on land are shown to be more intense and more tightly constrained to the central axis. A detailed schematic diagram of a vertical cross section through a composite depression is also presented, showing its inherent asymmetric structure.

Western disturbances (WDs) are upper-level synoptic-scale systems embedded in the subtropical westerly jet stream (STWJ), often associated with extreme rainfall events in north India and Pakistan during boreal winter. Here, a tracking algorithm is applied to the upper-tropospheric vorticity field for 37 years of ERA-Interim reanalysis data, giving a catalogue of over 3000 events. These events are analysed in a composite framework: the vertical structure is explored across a large number of dynamic and thermodynamic fields, revealing a significant northwestward tilt with height, strong ascent ahead of the centre, which sits above the maximum surface precipitation, and a warm-over-cold, dry-over-moist structure, among other signatures of strong baroclinicity. Evolution of the structures of cloud cover and vertical wind speed are investigated as the composite WD passes across northern India. Cloud cover in particular is found to be particularly sensitive to the presence of the Himalayan foothills, with a significant maximum at 300 hPa approximately 1 day after the WD reaches peak intensity. k-means clustering is used to classify WDs according to both dynamical structure and precipitation footprint and the relationship between the two sets of WDs is explored. Finally, the statistical relationship between the STWJ position and WDs on interannual time-scales is explored, showing that WD frequency in north India is highly sensitive to the jet location over Eurasia. Years with a greater number of WDs feature a STWJ shifted to the south, a pattern that is substantially more coherent and reaches as far west as North America during boreal winter. This suggests that it may be possible to predict the statistics of western disturbance events on seasonal time-scales if suitable indicators of jet position can also be predicted.

While much of India is used to heavy precipitation and frequent low pressure systems during the summer monsoon, toward the northwest and into Pakistan, such events are uncommon. Here, as much as a third of the annual rainfall is delivered sporadically during the winter monsoon by western disturbances. Such events of sparse but heavy precipitation in this region of typically mountainous valleys in the north and desert in the south can be catastrophic, as in the case of the Pakistan floods of July 2010. In this study, extreme precipitation events (EPEs) in a box approximately covering this region (25°–38°N, 65°–78°E) are identified using the APHRODITE gauge-based precipitation product. The role of the large-scale circulation in causing EPEs is investigated: it is found that, during winter, it often coexists with an upper-tropospheric Rossby wave train that has prominent anomalous southerlies over the region of interest. These winter EPEs are also found to be strongly collocated with incident western disturbances whereas those occurring during the summer are found to have a less direct relationship. Conversely, summer EPEs are found to have a strong relationship with tropical lows. A detailed Lagrangian method is used to explore possible sources of moisture for such events and suggests that, in winter, the moisture is mostly drawn from the Arabian Sea, whereas during the summer, it comes from along the African coast and the Indian monsoon trough region.

Indian monsoon depressions are synoptic-scale events typically spun up in the Bay of Bengal. They usually last 4-6 days, during which they propagate northwestward across the Indian subcontinent before dissipating over northwest India or Pakistan. They can have a significant effect on monsoon precipitation, particularly in primarily agrarian northern India, and therefore quantifying their structure and variability and evaluating these in numerical weather prediction (NWP) models and general circulation models (GCMs) is of critical importance. In this study, satellite data from CloudSat and recently concluded

Indian summer monsoon precipitation is significantly modulated by synoptic-scale tropical low pressure areas (LPAs), the strongest of which are known as monsoon depressions (MDs). Despite their apparent importance, previous studies attempting to constrain the fraction of monsoon precipitation for which such systems are responsible have yielded an unsatisfyingly wide range of estimates. Here, a variant of the DBSCAN algorithm is implemented to identify nontrivial, coherent rainfall structures in TRMM-3B42 precipitation data. Using theoretical considerations and an idealised model, an effective capture radius is computed to be 200 km, providing upper-bound attribution fractions of 57% (17%) for LPAs (MDs) over the monsoon core zone and 44% (12%) over all India. These results are also placed in the context of simpler attribution techniques. A climatology of these clusters suggests that the central Bay of Bengal (BoB) is the region of strongest synoptic organisation. A k-means clustering technique is used to identify four distinct partitions of LPA (and two of MD) track, and their regional contributions to monsoon precipitation are assessed. Most synoptic rainfall over India is attributable to short-lived LPAs originating at the head of the BoB, though longer-lived systems are required to bring rain to west India and east Pakistan. Secondary contributions from systems originating in the Arabian Sea and south BoB are shown to be important for west Pakistan and Sri Lanka respectively. Finally, a database of precipitating-event types is used to show that small-scale deep convection happens independently of MDs, whereas the density of larger-scale convective and stratiform events are sensitive to their presence-justifying the use of a noise-rejecting algorithm.