An Observing System Simulation Experiment for an Optimal Moored Instrument
Array in the Tropical Indian Ocean
JOAQUIM BALLABRERA-POY, ERIC HACKERT, RAGHU MURTUGUDDE, AND ANTONIO J. BUSALACCHI
Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland
(Manuscript received 29 April 2005, in final form 25 January 2006)
ABSTRACT
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.
1. Introduction
Recently renewed interest in Indian Ocean (IO) ob-
servational and modeling studies is motivated by a
number of factors such as the 1997–98 Indian Ocean
dipole/zonal mode (IODZM; Saji et al. 1999; Webster
et al. 1999; Murtugudde and Busalacchi 1999) and the
fact that the IO is the only tropical ocean yet to be
equipped with a moored observational array. The vari-
ability of the tropical Pacific and Indian Oceans is in-
timately connected through an oceanic bridge provided
by the Indonesian Throughflow (ITF; see Godfrey 1996
for a review) and an atmospheric bridge through the
Walker cell (see Webster and Yang 1992). Some recent
studies even suggest that the IO can influence an evolv-
ing El Niño–Southern Oscillation (ENSO) in the Pa-
cific (Wu and Kirtman 2004; Annamalai et al. 2005) and
the secular trends in the IO are purported to have sig-
nificant impacts on Northern Hemisphere climate vari-
ability (Hoerling et al. 2004; Deser et al. 2004). How-
ever, while our knowledge of the tropical variability of
the Pacific Ocean has increased since the Tropical
Ocean Global Atmosphere (TOGA) decade, and the
implementation of the Tropical Atmosphere Ocean
(TAO) Array (McPhaden et al. 1998), our knowledge
of the variability in the IO is still limited because of the
lack of sufficient observations. Under the auspices of
the Climate Variability and Predictability (CLIVAR)
Project, the IO Panel has proposed a 35-mooring array
designed to observe the large-scale dynamical variabil-
ity in the tropical IO (information online at http://www.
clivar.org). Such an array is expected to complement
remote sensing observations that, even though provid-
ing global, high-resolution coverage of the World
Ocean, only supply information about the near-surface
oceans (Busalacchi 1997). While the IO array is still in
its design phase, the present planned version spans the
region from 55° to 95°E and varies in latitude between
16°S and 8°N. Its distribution has been chosen subjec-
tively based on the knowledge of the geographical lo-
cation of the most energetic signals within the IO, and
a set of phenomenological features such as the inter-
tropical front (ITF), cross-equatorial overturning cell,
Corresponding author address: Joaquim Ballabrera-Poy, Earth
System Science Interdisciplinary Center, University of Maryland,
College Park, College Park, MD 20742-0000.
E-mail: joaquim@essic.umd.edu
3284 J O U R N A L O F C L I M A T E VOLUME 20
DOI: 10.1175/JCLI4149.1
© 2007 American Meteorological Society
JCLI4149

and the location of upwelling zones. One of the inter-
esting features of the seasonally reversing monsoons is
the thermocline ridging along
10°S, which has many
interesting climatic and biogeochemical consequences
(Reverdin et al. 1986; Murtugudde et al. 1999; Xie et al.
2002). The air–sea interactions in the Arabian Sea and
the Bay of Bengal are expected to enhance predictive
understanding of the Asian monsoons (see Annamalai
and Murtugudde 2004 for a review) and the dynamic
and thermodynamic variability in the near-equatorial
region is part of the IODZM and the Walker cell in-
teractions (Hastenrath et al. 1993; Murtugudde et al.
2000). The intraseasonal variability is of special interest
in the Bay of Bengal (Sengupta and Ravichandran
2001). The onset and growth phases of the IODZM are
centered off of Java and Sumatra in the southeastern
IO, justifying the choice of moorings in those regions
(Annamalai et al. 2003; Zhong et al. 2005).
Several efforts are now under way to assist in the
design of the IO array with observing system simulation
experiments [OSSEs; e.g., see Schiller et al. (2004); and,
in this issue, Vecchi and Harrison (2007) and Oke and
Schiller (2007)]. Some of these studies scrutinize the
design of the IO array as a component of a multi-
instrument global observing system (as, e.g., remote
sensing, Argo floats, and/or XBT drops from ships of
opportunity). Here the design of the IO array is con-
sidered on its own as the moored array should provide,
independently of other additional instruments, a stream
of geographically constant, temporally homogeneous
flow of surface and subsurface data for the study of the
climate variability of the IO.
The goal of the research carried out here is twofold.
First, we objectively validate the predetermined loca-
tions of the moorings through the analysis of the error
structure obtained from a reduced-space Kalman filter.
Second, we identify the most redundant moorings of
the proposed array to find out if the proposed array
may be simplified. Because a single array cannot en-
compass all relevant spatial and temporal scales, the
focus of this study will be on determining the optimal
mooring sites that best observe the large-scale, in-
terseasonal-to-interannual variability in the IO.
The experiments used in this work are based on a set
of OSSEs that allow the assessment of the impact of a
new observing system in a data assimilation experiment
using simulated observations. The approach used in this
work differs from previous approaches (see, e.g.,
Halem et al. 1982; Atlas 1997; Vecchi and Harrison
2007; Oke and Schiller 2007) in the sense that the ob-
servations used in our assimilation experiments come
from observed fields of satellite sea surface height (La-
gerloef et al. 1999) and sea surface temperature (Reyn-
olds and Smith 1994). Although the data to be assimilated
are based on actual observations, they will be used to
simulate the values of dynamic heights and upper-ocean
temperatures retrieved by the moored platforms of the
observation array. Using analyzed fields to simulate ob-
servations allows us to avoid the problem of how real-
istic the data generated by the model are. [A note aside,
it might be argued that fitting the IO array to Ocean
Topography Experiment (TOPEX)/Poseidon and Jason
(TPJ) and Reynolds data does not provide a new source
of information as SSH and SST are already well observed.
Nevertheless, the costly maintenance of satellite plat-
forms, the impact of cloud contamination of SST re-
trievals, and the need to further reduce errors from SST
and SSH for prediction models cannot be overstated.]
To provide an objective justification of the spatial
sampling “subjectively” proposed by the IO Panel, we
will closely follow the method that Hackert et al.
(1998) used to determine the optimal deployment of
moored platforms in the tropical Atlantic Ocean of the
Pilot Research Moored Array in the Tropical Atlantic
(PIRATA; Servain et al. 1998). The underlying as-
sumption in this methodology is that the placement of
moorings that best reproduces the error structure of the
data assimilation system is considered to be optimal. As
described in section 4a, every grid point in the error
field will be considered a feasible member of the ob-
serving network. The objective selection of the optimal
locations is estimated with the help of a full Kalman
filter (KF; Kalman and Bucy 1960) defined on a coarser
grid. To address the issue of redundancy and array sim-
plification, we will identify the most redundant moor-
ings of the array. Redundancy of each mooring will be
measured by comparing the results obtained from the
assimilation with and without that particular mooring.
While some degree of redundancy is necessary in op-
erational observational systems (to provide a better es-
timate of the parameters to be observed and to mini-
mize the detrimental effects of the failure or vandalism
of one or more instruments), we will query if any moor-
ing provides the same information as the rest of the array.
The outline of the paper is as follows. In section 2, we
will describe the data used in this study. The ocean
models (linear and nonlinear) are described in section
3. The optimal analysis using the linear ocean model is
discussed in section 4. Section 5 introduces the simpli-
fication of the array. The last section contains a final
discussion and conclusions.
2. Data
Observations of SSH come from TOPEX/Poseidon
and Jason (TPJ) data, with a 17-cm bias correction ap-
plied to the Jason observations (G. Mitchum 2005, per-
1 JULY 2007 B A L L A B R E R A - P O Y E T A L . 3285