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The effect of seasonally and spatially varying chlorophyll on Bay of Bengal surface ocean properties and the South Asian Monsoon

Giddings, J., Matthews, A. J., Klingaman, N. P. ORCID: https://orcid.org/0000-0002-2927-9303, Heywood, K. J., Joshi, M. and Webber, B. G. M. (2020) The effect of seasonally and spatially varying chlorophyll on Bay of Bengal surface ocean properties and the South Asian Monsoon. Weather and Climate Dynamics, 1 (2). pp. 635-655. ISSN 2698-4024

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To link to this item DOI: 10.5194/wcd-1-635-2020

Abstract/Summary

Chlorophyll absorbs solar radiation in the upper ocean, increasing mixed-layer radiative heating and sea surface temperatures (SST). Although the influence of chlorophyll distributions in the Arabian Sea on the southwest monsoon has been demonstrated, there is a current knowledge gap in how chlorophyll distributions in the Bay of Bengal influence the southwest monsoon. The solar absorption caused by chlorophyll can be parameterized as an optical parameter, h2, the scale depth of absorption of blue light. Seasonally and spatially varying h2 fields in the Bay of Bengal were imposed in a 30-year simulation using an atmospheric general circulation model coupled to a mixed layer thermodynamic ocean model to investigate the effect of chlorophyll distributions on regional SST, southwest monsoon circulation and precipitation. There are both direct local upper-ocean effects, through changes in solar radiation absorption and indirect remote atmospheric responses. The depth of the mixed layer relative to the perturbed solar penetration depths modulates the response of SST to chlorophyll. The largest SST response of 0.5°C to chlorophyll forcing occurs in coastal regions, where chlorophyll concentrations are high (> 1 mg m-3), and when climatological mixed layer depths shoal during the intermonsoon periods. Precipitation increases significantly by up to 3 mm day-1 across coastal Myanmar during the southwest monsoon onset and over northeast India and Bangladesh during the Autumn intermonsoon period, decreasing model biases.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > NCAS
Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:93441
Publisher:EGU

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