Representation of Bay of Bengal upper-ocean salinity in general circulation models

TitleRepresentation of Bay of Bengal upper-ocean salinity in general circulation models
Publication TypeJournal Article
Year of Publication2016
AuthorsChowdary J.S, Srinivas G., Fousiya T.S, Parekh A., Gnanaseelan C., Seo H, MacKinnon JA
JournalOceanography
Volume29
Pagination38-49
Date Published2016/06
Type of ArticleArticle
ISBN Number1042-8275
Accession NumberWOS:000380572500008
Keywordsclimate forecast; data assimilation system; fresh-water discharge; global ocean; mixed-layer; research moored array; salinity; sea-surface; seasonal; summer monsoon; system; tropical indian-ocean; variability
Abstract

The Bay of Bengal (BoB) upper-ocean salinity is examined in the National Centers for Environmental Prediction-Climate Forecasting System version 2 (CFSv2) coupled model, Modular Ocean Model version 5 (MOM5), and Indian National Centre for Ocean Information Services Global Ocean Data Assimilation System (INC-GODAS). CFSv2 displays a large positive salinity bias with respect to World Ocean Atlas 2013 in the upper 40 m of the water column. The prescribed annual mean river discharge and excess evaporation are the main contributors to the positive bias in surface salinity. Overestimation of salinity advection also contributes to the high surface salinity in the model during summer. The surface salinity bias in MOM5 is smaller than in CFSv2 due to prescribed local freshwater flux and seasonally varying river discharge. However, the bias is higher around 70 m in summer and 40 m in fall. This bias is attributed to excessive vertical mixing in the upper ocean. Despite the fact that representation of salinity in INC-GODAS is more realistic due to data assimilation, the vertical mixing scheme still imposes systematic errors. The small-scale processes that control oceanographic turbulence are not adequately resolved in any of these models. Better parameterizations based on dedicated observational programs may help improve freshwater representation in regional and global models.

DOI10.5670/oceanog.2016.37
Short TitleOceanography
Student Publication: 
No