Please use this identifier to cite or link to this item: http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/2570
Title: Monsoons to Mixing in the Bay of Bengal: Multiscale Air-Sea Interactions and Monsoon Predictability
Authors: GOSWAMI, B. N.
Rao, Suryachandra A.
Sengupta, Debasis
CHAKRAVORTY, SOUMI
Dept. of Earth and Climate Science
Keywords: Skillful prediction
South Asian monsoon
Modeling of processes
Freshwater pools
Monsoon Predictability
Monsoons to Mixing
2016
Issue Date: Jul-2016
Publisher: Oceanography Society
Citation: Oceanography, 1, 18 - 27.
Abstract: Skillful prediction of the “active” and “break” spells of monsoon intraseasonal oscillations during the South Asian monsoon season is crucial for the socio-economic fate of one-sixth of the world’s population, yet it remains a grand challenge problem. The limited skill of our coupled weather and climate models is largely due to our inability to represent the complex multiscale interactions of the north Indian Ocean and the atmosphere. Air-sea interactions are at the heart of not only the climatological mean annual cycle of the South Asian monsoon but also its synoptic, subseasonal, interannual, and decadal variability. With high local monsoon precipitation and discharge from major rivers (Ganges-Brahmaputra, Irrawaddy), the Bay of Bengal (BoB) exhibits the lowest surface salinities in the tropics as well as unique thermal stratification, making it a natural laboratory for studying multiscale interactions ranging from planetary-scale monsoons to submesoscale mixing in freshwater pools. The current ocean component of coupled models is inadequate for simulating the BoB’s upper-ocean thermal structure with fidelity. To further improve monsoon forecasts on intraseasonal and interannual time scales, we need new high-resolution and high-frequency observations over the BoB to fill the gap in our understanding of how the ocean mixes in highly fresh regions, and we need modeling of processes that will convert this understanding to parameterizations of mixing that can be used to improve large-scale ocean models.
URI: http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/2570
https://doi.org/10.5670/oceanog.2016.35
ISSN: 1042-8275
Appears in Collections:JOURNAL ARTICLES

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