MESOSCALE – SMALL SCALE OCEANIC
VARIABILITY EFFECTS ON UNDERWATER
ACOUSTIC SIGNAL PROPAGATION
EMANUEL COELHO
SACLANT Undersea Research Centre, Viale S. Bartolomeo 400, 19038 La Spezia, Italy
E-mail: [email protected]
Naval Forces standard procedures use single sound speed profile measurements for
Active Sonar Detection Range (ADR) or Active Sonar Counter Detection Range (CDR)
estimates. These profile measurements are usually tasked to one ship or aircraft and
support centre, which then provides regular reports, disseminated throughout the force.
Rapid Environmental Assessment (REA) methodologies have been developed towards
the optimization of the ADR and CDR estimation by providing oceanographic forecast
data, consistent with the real conditions in the operation area. These methodologies
include assimilation of the available oceanographic data into the numerical models that
provide the snapshot sound speed cross-sections, which feed transmission loss models.
Although the available ocean forecast schemes include a broad range of scales, they
usually cannot account accurately for high frequency ocean phenomena (mesoscale to
small scale). Furthermore, operationally available numerical tools cannot account
accurately for 3D, non-hydrostatic phenomena, like short internal waves. To overcome
this uncertainty at present, extensive oceanographic data collection is required, which is
very expensive and likely it will not be feasible to obtain during a crisis scenario. The
present work aims to contribute for the development of a system that can complement
Naval Forces and REA procedures, by estimating ADR and CDR uncertainty due to
local oceanic variability. An “Around the Ship Modeling System” is proposed to assess
locally the initial phase uncertainty of the freely propagating modes and to include the
effects of non-hydrostatic phenomena. This system may produce locally more accurate
oceanographic field estimates and the evaluation of uncertainty error bounds on the
sound speed profile estimates. These results can then be used on transmission loss
Models for more robust ADR and CDR evaluation. An example is outlined based on a
scale analysis on the non-linear internal waves regime of an area regularly used for
Naval Exercises and a methodology is proposed for the generation of the ensemble of
possible sound speed cross sections, which can be used for transmission loss variability
assessment.
1
Introduction
In coastal regions the wind, tidal currents, river outflow and instabilities can force
oceanographic phenomena affecting the propagation of acoustical signals at active sonar
frequencies. Characteristic lengths range from meters (e.g. non-linear internal waves) to
several kilometers (e.g. internal tides and mesoscale structures) with typical periods
going from minutes to days. Furthermore, surface and internal mixed layers can be
established, and significantly change, in the range of minutes [1], developing a
homogeneous well-mixed water column and erasing all the other structures.
49
N.G. Pace and F.B. Jensen (eds.), Impact of Littoral Environmental Variability on Acoustic Predictions and
Sonar Performance, 49-54.
© 2002 Kluwer Academic Publishers. Printed in the Netherlands.
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EMANUEL COELHO
In deeper waters typical length and temporal scales can be expected to be larger.
Though internal waves can exist, they can be expected to be less energetic and mainly
forced by mixed layers depth changes and wind curl time variability. However, time
dependence on the forcing mechanisms will promote an energy transfer directly towards
inertial scales [2]. Therefore, inertial oscillations and quasi-inertial waves are likely to be
present in any dynamical system and through non-linear interactions one can expect an
energy transfer to higher frequencies and smaller scales.
In this paper, one example is introduced integrating the effects on tidally forced
internal waves and non-linear high frequency internal waves in an area normally used for
NATO Naval Exercises (e.g. Linked Seas 2000 and Strong Resolve 1998). Rapid
Environmental Assessment (REA) strategies have been developed towards the
optimization of the ADR and CDR estimation by providing forecast data, consistent with
the real conditions in the operation area [3,4]. Although the used forecast schemes
include all ranges of scales, they cannot account accurately for all high frequency
(mesoscale to small-scale) oceanographic phenomena. For an area with high variability,
like the one mentioned in the example below, this means that, though the models can
provide fair energy budgets for the several scales of the oceanographic phenomena, they
cannot produce accurate snapshots of the sound-speed profiles to be used into the
transmission loss models.
To a certain extent this is due to an uncertainty on the initial phase of the forcing
functions and to the freely propagating inertia-gravity waves resulting from the time
variability of the forcing functions. Furthermore, the used numerical models are
hydrostatic and therefore cannot account for steep topography effects and small-scale
internal waves. To overcome this uncertainty at present, extensive oceanographic data
collection is required and complex 3D models needed to be adapted. These actions will
not be feasible to perform during a crisis scenario in operational and tactical timeframes.
The main objective of this paper is therefore to introduce methodologies, concepts and
hypothesis, which can guide future research on these topics. The proposed data analysis
procedures are presented in Sect. 2. They follow the concept of “Around-The-Ship”
ocean modeling, adapted and updated within tactical timeframes. Under this concept,
available data from forecast models and actual observed local data is used to run simple
process or feature models and fast relocatable high-resolution small domain ocean
models. The results of these schemes are then used to extrapolate the local ship or other
platform observations to a surrounding area within a range up to typically 10–20 km. As
a process-modeling example, in Sect. 3 a test case for non-linear internal waves will be
analyzed and a scale analysis performed using analytical solutions. In Sect. 4 the
implementation example is discussed and concluding remarks presented.
2
Ocean variability models (NATO Tactical Ocean Modeling System)
The NATO Tactical Ocean Modeling System (NTOMS) flowchart is shown in Fig. 1.
The main goal of the system is to estimate coherent oceanic fields directly from local
(platform based) observations, taking into account historical data, regional models
analysis and forecasts and remote sensing data. It acts as an interface between local
observations and the regional ocean models, such that once new measurements are made
they are directly used to update the estimates of surrounding coherent fields, that can be
used for assimilation into the regional models instead of the point observations. The
system intends to cover spatial scales from meters to tenths kilometers and temporal
MESOSCALE – SMALL SCALE VARIABILITY EFFECTS
51
scales from minutes up to 24 hours. Depending on the scenarios, several modules and
increased complexity can be set.
Figure 1 - The NATO Tactical Ocean Modeling flowchart.
One can expect that the coherent fields surrounding the platform will not be
consistently observed. Therefore, the first step of the system consist on a statistical
modeling approach which will allow the detection and classification of these coherent
structures by adaptively implementing simple analytical solutions and evaluating its
correlation with the along-track observed data.
Traditional oceanic forecast systems provide daily or 12 h forecasts for the next 2–4
days. As mentioned above, the model spatial and temporal resolution can be adapted
accordingly to the high frequency phenomena, but free propagating waves and locally
forced high frequency waves are not well predicted due to uncertainty in the initial and
boundary conditions. Therefore, depending on the strategy, the model outputs should be
interpreted as mean fields between the sequential forecasts or as representing one
ensemble of possible realizations of the fields, within the considered period.
The second step of NTOMS aims to overcome this limitation, by producing local
“Around-the-Ship”, less accurate, shorter term predictions that are consistent with the
along-track ship observations. These short-term forecasts are based on initial guesses
feeding simple feature modeling or fast high performance relocatable models from
which the predicted fields are estimated. The complexity and the feature models to be
used, depend on each scenario and require an expert interpretation of the observed fields.
For the purpose of this paper, one case will be addressed. Non-linear internal wave
and wind forced normal modes modules will be used for local ocean variability
estimation based on observed fields and forcing conditions in an area frequently used for
Naval Exercises.
3
Non-linear internal wave test case
The occurrence of non-linear internal waves is not easily predicted. Furthermore, the
models that are now available for REA follow the hydrostatic approximation and
therefore cannot accurately account for these features.
These waves can be responsible for significant variability at the thermocline levels,
forcing isopycnic displacements of the order of 10s of meters, in the range of minutes.
Surface signatures of these features can be seen through satellite SAR images [5,6] and
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EMANUEL COELHO
significant differences in repeated profile measurements can suggest their occurrence
[7].
Using appropriate scale analysis one can assess if these features are likely or not in a
certain area and based on the background stratification and the measurement of one
property like wavelength through SAR imagery, it can be possible to estimate their range
of amplitudes and phase velocities. Furthermore, if they can be correlated with
topographical features, one can estimate the variability using historical remote sensing
and in-situ data, even if the local conditions do not allow for SAR imagery
interpretation.
However, an accurate nowcast and forecast of these features usually requires
dedicated assets and observations that are not easily performed from organic ships and
available modeling is still not applicable operationally [8], though some preliminary
implementations of operational schemes have been attempted in some areas.
In this work, a non-linear mode internal wave model is used, following the
procedure described in Ostrovky et al. [9]. This model is set to run based on initial
profiles estimated through XBT’s or other similar instruments and then uses wavelength
information interpreted either from actual or historical SAR imagery. As an alternative
method, differences between consecutive or historical profiles at the same location can
be used as estimates of the maximum amplitude of the non-linear internal wave
oscillations. Also, it is assumed tidal currents are known.
Using this methodology, sound speed cross-sections are then estimated between two
consecutive points crossing the internal wave field. These estimates can be produced for
different initial phase and relative orientation and other relevant degrees of freedom
determined by the geometry of the area and available data.
As an implementation example, data from the INTIFANTE’00 cruise is used, see
Refs. [10,11]. During this campaign off the west coast of Portugal, simultaneous
measurements of shipborn profiling systems and moorings were made superimposed to
SAR imagery as described in [6]. In Fig. 2 one can see the NLIW signatures and the
cross-section observed through a yo-yo CTD from the NRP “D. Carlos”.
Figure 2. Along track temperature profiles observed during the INTIFANTE’00 cruise. The
profiles where observed using a yo-yo CTD from the NRP “D. Carlos”, while crossing the train of
Non-Linear Internal Waves (NLIW), as shown in the image on the left side.
MESOSCALE – SMALL SCALE VARIABILITY EFFECTS
53
In [10] there was shown evidence of NLIW in the area slightly conditioned by the
spring-neap tide cycle. Furthermore, the NLIW showed 0-70% likelihood at this site
depending on the spring-neap cycle and overall is about 30% likely to occur.
Furthermore, observed temperature profiles showed vertical displacement of about
50 m to 35 m during the passage of non-linear internal waves in periods of about 3 h.
The first empirical mode dominated the motion with the first eigenvalue ranging from
70% to 90%. Also, using the method developed by Inall, et al. [12], consistent transport
estimates between theoretical (two layer theory) and observed (ADCP) showed
maximum values ranging from 10 m2/s to 2.5 m2/s with the dispersion term not always
being negligible, balancing non-linear terms, suggesting KDV theory is applicable
In Fig. 3 we have one realization using a 2-layer nonlinear internal wave model by
fixing wavelength and number of waves in the train, as it can be determined by the SAR
images described in [6]. This realization can be assumed to be a possible outcome of a
random variable and used for transmission loss variability computations, as described
above. In this example, the amplitudes of the components and the initial relative phase
of each component determine the degrees of freedom.
Figure 3. Realization from internal wave model.
4
Concluding remarks
At the present time the available ocean forecast tools do not allow for accurate small
scale, short-term predictions. This paper proposes a methodology which, when
implemented, might complement the available REA products for small areas and within
short time periods. In order to develop this concept and demonstrate the improvements
the NATO Tactical Modeling System (NTOMS) was presented. This system will
integrate several modules starting from on-track data acquisition and processing
capabilities, to small domain “Around-the-Ship”, short-term, relocatable-domain
numerical modeling. These tasks will be part of a SACLANTCEN project named
NTOMS, starting 2003.
Acknowledgements
The author wishes to thank the Instituto Hidrografico – Portuguese Navy and the teams
of the Universidade do Algarve, ENEIA and DERA, participating in the INTIFANTE00
and INTIFANTE01 for their cooperation.
54
EMANUEL COELHO
References
1. Coelho, E.F. and Stanton, T.P., Tidal mixing over steep topography. In Proc. 2nd
International Conference in Air-Sea Interaction and on Meteorology and Oceanography
of the Coastal Zone, edited by A.M.S., Lisbon, Portugal, 1994.
2. Gill, A.E., Atmosphere-Ocean Dynamics (Academic Press, N.Y., 1982).
3. Sellschopp, J., Exercise Linked Seas 2000, SACLANTCEN CD-ROM, 2000.
4. Vitorino, J. and Monteiro, M.J., Swordfish 2001 - A study of the oceanographic conditions
off Cape São Vicente (SW Portugal) using data assimilation models. 3ª assembleia LusoEspanhola Geofisica, Valencia, Spain, 2002.
5. Jeans, D.R.G. and Sherwin, T.J., The evolution and energetics of large amplitude nonlinear
internal waves on the Portuguese Shelf, J. Marine Res. 59, 327–353 (2001).
6. Small, J. and Dovey, P., INTIFANTE99 oceanographic data report. Defense Evaluation and
Research Agency (DERA) Report, 1999, 58 pp.
7. Rodrigues, O., Jesus, S., Stephan, Y., Coelho, E.F., Demoulin, X. and Porter, M.B.,
Nonlinear soliton interaction with acoustic signals: Focusing effects, J. Comp. Acoust. 8
(2), 347–363 (2000).
8. Lonzano, C.J., Robinson, A.R., Arango, H.G., Gandopadhyay, A., Sloan, Q., Haley, P.,
Anderson, L. and Leslie, W., An interdisciplinary ocean prediction system: assimilation
strategies and structured data models. In Modern Approaches to Data Assimilation in
Ocean Modelling, edited by P. Malanotte-Rizzoli (Elsevier Oceanography Series, Elsevier
Science, The Netherlands, 1996) pp. 413–452.
9. Ostrovsky, L.A. and Stepanyants, Y.A., Do solitons exist in the ocean? Rev. Geophys. 27,
(Aug. 1989).
10. Coelho, E.F., Clemente, C., Quaresma, L., Beja, J., Caldas, J. and Marreiros, M., Submarine
canyons near-inertial ocean dynamics – Recent work on the Nazare and Setubal systems.
In Canyons Workshop, Sitges-Barcelona, April 2002.
11. Jesus, S.M, Coelho, E., Onofre, J., Picco, P., Soares, C. and Lopes, C., The INTIFANTE’00
sea trial: preliminary source localization and ocean tomography data analysis. In Proc.
MTS/IEEE Oceans 2001, Honolulu, Hawaii, USA, 2001.
12. Inall, M.E., Shapiro, G.I. and Sherwin, T.J., Mass transport by non-linear internal waves on
the Malin Shelf, Cont. Shelf Res. 21, 1449–1472 (2001).