z-logo
open-access-imgOpen Access
An Observing System Simulation Experiment for an Optimal Moored Instrument Array in the Tropical Indian Ocean
Author(s) -
Joaquim Ballabrera-Poy,
Eric Hackert,
Raghu Murtugudde,
Antonio J. Busalacchi
Publication year - 2007
Publication title -
journal of climate
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.315
H-Index - 287
eISSN - 1520-0442
pISSN - 0894-8755
DOI - 10.1175/jcli4149.1
Subject(s) - predictability , redundancy (engineering) , sea surface height , context (archaeology) , meteorology , environmental science , data assimilation , software deployment , sea surface temperature , equator , climatology , computer science , remote sensing , geology , latitude , geodesy , geography , mathematics , paleontology , statistics , operating system
In this paper, a series of observing system simulation experiments (OSSEs) are used to study the design of a proposed array of instrumented moorings in the Indian Ocean (IO) outlined by the IO panel of the Climate Variability and Predictability (CLIVAR) Project. Fields of the Ocean Topography Experiment (TOPEX)/Poseidon (T/P) and Jason sea surface height (SSH) and sea surface temperature (SST) are subsampled to simulate dynamic height and SST data from the proposed array. Two different reduced-order versions of the Kalman filter are used to reconstruct the original fields from the simulated observations with the objective of determining the optimal deployment of moored platforms and to address the issue of redundancy and array simplification. The experiments indicate that, in terms of the reconstruction of SSH and SST, the location of the subjectively proposed array compareS favorably with the optimally defined one. The only significant difference between the proposed IO array and the optimal array is the lack of justification for increasing the latitudinal resolution near the equator (i.e., moorings 1.5°S and 1.5°N). An analysis of the redundancy also identifies the equatorial region as the one with the largest amount of redundant information. Thus, in the context of these fields, these results may help define the prioritization of its deployment or redefine the array to extend its latitudinal extent while maintaining the same amount of stations.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here