Abstract

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.

Highlights

  • Monsoon depressions (MDs) are synoptic-scale disturbances that typically spin up near the head of the Bay of Bengal, before moving northwestward over peninsular India (Sikka 1977; Hurley and Boos 2015; Hunt et al 2016a)

  • We use the Indian monsoon depression tracks of Hunt et al (2016b) and classify MD days and non MD days according to the following: if the tracking algorithm identifies an MD north of 12◦N or west of 90◦E at least once on a given date, the day is classified as an MD day for South Asia

  • This provides an extreme upper bound on the total rainfall that can be attributed to monsoon depressions

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Summary

Introduction

Monsoon depressions (MDs) are synoptic-scale disturbances that typically spin up near the head of the Bay of Bengal, before moving northwestward over peninsular India (Sikka 1977; Hurley and Boos 2015; Hunt et al 2016a). Praveen et al (2015) attributed all rainfall occurring on days with a LPA present and concluded that 60% of monsoon precipitation was due to such systems. Fletcher consistent with definitions used by the India Meteorological Department Their tracks, along with a 20 years record of high quality satellite observations of tropical rainfall through the tropical rainfall measuring mission (TRMM) multisatellite precipitation analysis (Huffman et al 2007), make it possible to accurately estimate the contribution of monsoon depressions to both mean and extreme rainfall. We examine the spatial distribution of mesoscale precipitating systems as an indicator of mesoscale organisation of convection in the vicinity of MDs. Section 2 describes the data we use and the clustering method.

ERA‐interim
Database of precipitating systems from TRMM PR
Monsoon depression tracks
General description of the DBSCAN algorithm
Objective cluster identification
Glossary
Upper bound on rainfall attributed to MDs
Assuming a fixed radius of influence
Clustering
Characteristics of precipitating systems around MDs
Discussion
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