A data-assimilative numerical model of the Northern Indian Ocean

Citation
Jw. Lopez et Lh. Kantha, A data-assimilative numerical model of the Northern Indian Ocean, J ATMOSP OC, 17(11), 2000, pp. 1525-1540
Citations number
53
Categorie Soggetti
Earth Sciences
Journal title
JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY
ISSN journal
07390572 → ACNP
Volume
17
Issue
11
Year of publication
2000
Pages
1525 - 1540
Database
ISI
SICI code
0739-0572(200011)17:11<1525:ADNMOT>2.0.ZU;2-T
Abstract
A primitive equation, three-dimensional, baroclinic circulation model has b een configured for use in the North Indian Ocean. After having been spun up by climatological winds, the model was used to generate a hindcast for 199 3-95 under synoptic forcing, both with and without assimilation of multicha nnel sea surface temperature (MCSST) and altimetric sea surface height (SSH ) anomaly data. Without data constraints, the model captures many of the sa lient oceanographic features in this region including equatorial surface an d subsurface currents, the Laccadive High Eddy, the Great Whirl, and the re versing Somali Current. However, assimilation ol altimetric data enables it to depict these features more accurately. MCSST data enable the near-surfa ce layers to be simulated more accurately. The National Aeronautics and Space Administration TOPEX precision altimeter has provided oceanographers with an important tool to study the variabilit y in the circulation of the world's oceans. The availability of SSH data fr om this altimeter provides a unique opportunity to assess the skill of a nu merical model. More important, the assimilation of TOPEX altimetric observa tions, along with satellite-observed sea surface temperatures, greatly enha nces the model's ability to estimate the dynamical and thermodynamic state of the North Indian Ocean. The data-assimilative model provides therefore a n additional tool for improving our understanding of the dynamical and ther modynamic processes in this region, through accurate hindcasts of the ocean ic state. With the availability of real-time data streams, it also enables estimates of the oceanic state to be made in real-time nowcast/forecast mod e.