Transcript AESOP: Assessing the Effects of Submesoscale Ocean Parameterizations Scott Harper Code 322, Physical Oceanography Office of Naval Research [email protected].

AESOP: Assessing the Effects of
Submesoscale Ocean Parameterizations
Scott Harper
Code 322, Physical Oceanography
Office of Naval Research
[email protected]
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Naval Requirements for Ocean Information
The US Navy requires information about the ‘battlespace
environment’ (BSE) on a variety of space and time
scales, and would like predictions of the synoptic state of
the BSE with up to a one week lead time.
While any particular application might require knowledge of
only certain ocean characteristics on limited spatial
scales, when one considers the breadth of Naval
operations, the overall requirement can seem like
“everything, anywhere.”
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A few examples of BSE impact on the Navy
ASW (Anti-Submarine Warfare)
– location of density fronts, depths of mixed layer and thermocline
for acoustic performance predictions
NSW (Naval Special Warfare)
– temperature and currents for swimmer operations, optical
properties for diver visibility
MIW (Mine Warfare)
– optical properties for mine hunting, drift predictions for floating
mines, currents and density conditions for AUV operations
Fleet Operations
– Wave conditions for surface operations, currents for search and
rescue and ship routing
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BSE Programs in Code 32 at ONR
Code 32
Ocean, Atmosphere and Space
Code 321
Sensing and Systems
Code 322
Processes and Prediction
Ocean Acoustics
Physical Oceanography
Coastal Geosciences
Marine Meteorology
One goal of Code 32 is to fund the
research necessary to address the
future BSE knowledge requirements
of the Navy, through a combination of
6.1, 6.2, and 6.3 funding dollars.
Optics and Biology
NOPP
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Restructuring of Code 322 in 2003
In 2003, the Processes and Prediction Division was re-organized to
reduce the number of overall programs, formally eliminating ‘Remote
Sensing’ and ‘High Latitude Dynamics’.
‘Ocean Optics’ and ‘Biology and Chemistry’ were combined to form the
Optics and Biology program.
Marine Meteorology incorporated the atmospheric elements of the
‘Remote Sensing’ program
‘Physical Oceanography’, ‘Ocean Modeling and Prediction’, ‘High Latitude
Dynamics’ and oceanographic elements of ‘Remote Sensing’ were
consolidated into the new Physical Oceanography program.
The division now consists of four programs: Physical Oceanography,
Marine Meteorology, Optics and Biology, and NOPP.
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Physical Oceanography Core Program
Three Major Thrust Areas:
• Boundary Layer Processes
Emphasis: Air/Sea interactions, mixed layer dynamics, bottom boundary-layer
processes, flow interactions with topography, surface waves.
• Sub-Mesoscale Processes and Parameterization
Emphasis: frontal variability, internal waves, energy cascade processes,
temperature/salinity spiciness, turbulence, mixing.
• Prediction Systems
Emphasis: nowcast and forecast modeling, assimilation, filtering, and adjoint
methods, optimal and adaptive sampling, uncertainty.
We also consider the following two thrusts as areas of future growth:
• Littoral Processes
Shallow water processes, highly nonlinear waves and internal waves, river
plumes, estuaries.
• Ocean-Acoustic Interactions
Coupled ocean-acoustic modeling and transmission loss physics.
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Additional Sources of Funding
Note: our call for planning letters was delayed this year – the
deadline for FY06 planning letters will likely be April 15th.
In addition to funding we have available through
the PO core program, we look for other
opportunities to support our efforts…
•
•
•
•
Departmental Research Initiatives within Code 32
Special Programs within ONR
Multidisciplinary University Research Initiatives
National Oceanographic Partnership Program
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Programs associated with 322PO
Current DRI’s:
• ODDAS (Optimal Deployment of Drifting Acoustic Sensors)
• AESOP (Assessing the Effects of Submesoscale Ocean Parameterizations)
• NLIWI (Non-Linear Internal Wave Initiative)
New Starts for FY06: (just decided - all details still tentative)
• IndoEx (Predicting Variability in Choke Point Straits) Murray, Harper
• Radiance in a Dynamic Ocean (Understanding Radiance through
the Air-Sea Interface) Ackleson, Drake, Vincent
• CBLAST Analysis (Supplement for focused collaboration and
extended data analysis) Ferek, Friehe, Paluszkiewicz
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Programs associated with 322PO
MURI’s:
• ASAP (Adaptive Sampling and Prediction) Curtain
• CSRE (Coherent Structures in Rivers and Estuaries) Vincent, Drake
• Real-time sea-state estimation for Ship Motion Prediction Vincent
NOPP Projects (just a few examples):
• GODAE/HYCOM (Global Ocean Data Assimilation Experiment /
Hybrid Coordinate Ocean Model)
• PARADIGM (Partnership for Advancing Interdisciplinary Global
Models)
New BAA: Assessment of Global Ocean Data Assimilation Experiment
(GODAE) Boundary Conditions for Coastal Ocean Predictions
Proposals Due March 31st!
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Undersea Persistent Surveillance
Special Program in Code 32 to explore the use of autonomous vehicles
with cooperative behavior to sense and adapt to the environment to
maximize detection of quiet submarines
Surveillance mission constraints:
• Unobtrusive undersea surveillance for targets in littoral waters
of order 103 - 104 square nautical miles, shallow and deep,
operating for months.
• Innovative technologies integrated into distributed scalable
systems.
• Systems at all scales that are deployable, affordable and
effective for large area, persistent coverage.
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A simple view of ocean prediction
Surface Forcing
Initial
Ocean
State
Numerical Model
Predicted
Ocean
State
Lateral Boundary Forcing
A better ocean prediction may result from improvements in:
• the initial conditions (via data assimilation, better climatology)
• the boundary forcing (coupling with high fidelity atmospheric models,
application of appropriate lateral BC’s)
• the robustness and reliability of the numerical model used for
integration.
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The AESOP DRI
In this DRI, we are only trying to address the
fidelity of the numerical models - and further,
we’re only examining issues concerning the
subgrid-scale (SGS) parameterizations.
For the resolution of the models we’re considering,
the SGS physics are in the submesoscale
on the order of ( 50m – 5km)
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Some additional context
“Oceanic general circulation models must parameterize the
effect of subgrid-scale motions and generally do so with
diffusion terms. The following questions then arise: do
oceanic observations allow inferences about mixing and
diffusion coefficients – if so, how do ‘observed’
coefficients compare with those used in numerical
models; can mixing rates be predicted from an
understanding of the processes involved; does it matter;
and are the results of numerical models sensitive to the
choice of the diffusion coefficients?”
- from a report on the 1989 ‘Aha Huiliko’a meeting
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Some additional context
“The parameterization of small-scale processes in
numerical models is a basic science issue. It will only be
resolved as numerical modelers and small-scale
observers collaborate, pooling their expertise and
resources and providing essential cross checks for each
other. The meeting in Honolulu was an attempt to
stimulate such collaboration, and it is encouraging that
many of the participants left the meeting with joint
projects on their minds – in the best of the Aloha spirit.”
- conclusion of the 1989 ‘Aha Huiliko’a meeting report
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Some operational modeling plans at NAVO
FY07:
Global HYCOM at 1/12° (7 km) res
Regional NCOM or HYCOM at 2-4km res
Coastal model (tbd) at 500m-1500m res
FY09:
Global HYCOM at 1/25° (3.5 km) res
Regional model unnecessary
Coastal model (tbd) at 500m-1500m res
The need to assess the parameterizations
that are being used in numerical models
is more urgent than ever.
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AESOP: An Analogy?
A Fable
A Parameterization
The Goat and the Goatherd
Turbulence Closure Schemes
A goatherd had sought to bring back
a stray goat to his flock. He whistled
and sounded his horn in vain; the
straggler paid no attention to the
summons. At last the Goatherd threw
a stone, breaking the goat’s horn. He
begged the Goat not to tell his
master. The Goat replied, "Why, you
silly fellow, the horn will speak
though I be silent."
One can estimate the local eddy
viscosity that arises from shear,
dissipation, and buoyancy using the local
Reynolds stresses and vertical shear
along with a generic length scale for
turbulent motions.
Moral: Do not attempt to hide things
which cannot be hid
Moral: Do not attempt to hide things
which cannot be hid (?)
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Meeting Objectives
• Get everyone introduced, and understand what
capabilities each group is bringing to the project
• Define and refine the specific project goals
• Determine the observations, model runs and
diagnostics that will be required
• Draft an observation plan including
– List of observational assets
– Platforms and vessels required
– Rough timeline of what is in the water and when
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Meeting Objectives, continued
• Work out relevant partnering (Mixing Process
Teams)
• Decide on the next meeting (host, location, date,
goals, and what must be done by then)
• Determine if there are any crucial pieces of the
puzzle missing from this group
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Coordination with other programs
• ASAP MURI (What can we provide in real time? How can we use
their operational predictions of the area?)
• UPS (observational assets and modeling work - e.g. Pierre
Lermusiaux will be exploring different parameterizations in this area
using HOPS)
• NSF (coordinate ship scheduling, coordinate with potential NSFfunded work in Monterey Bay)
• LOCO DRI (if they are in MB in ’06)
• NPS observational program
• CenCOOS observing system
• MARS and the MBARI observational program
• NOPP GODAE Boundary Condition group?
• Other NOPP projects
• Other ONR efforts from core programs (PO, MM, OA)
• NRL modeling efforts (e.g. RTP for coupled modeling in MB)
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Coordination with other programs
The coordination bit is important not only for the UNOLS
ship requests, but also because there are a number of
opportunities for parallel work, interesting science, and
perhaps most importantly, developing a more
comprehensive data set for making parameterization
assessments.
The assumption behind the CPT initiative at NSF was that
the data exists to verify the parameterizations for their
class of problems. I’m not convinced we have the data
set required for ours – that’s what we might be trying to
build.
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Straight from the workshop last year…
Some examples of questions we hope to address:
•What are the physical processes that are difficult to
parameterize, limiting our ability to run realistic highresolution simulations?
•How should one choose between parameterizations?
•What is an “improved” parameterization?
•Can we define the processes that dominate the dynamics at
various resolutions?
•How sensitive are synoptic model predictions to the
parameterized viscosity and diffusion?
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Straight from the workshop last year…
Some desired products we hope to generate:
• new methods for assessing parameterizations
• new knowledge about submesoscale ocean processes
• insight into the relative importance of different processes at
various resolutions
• information on how current parameterizations affect ocean
predictions
• new methods to evaluate high-resolution models and their
predictions
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