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GODAE OceanView Observing System Evaluation
Task Team Webpage Co-Chairs: Dr
Peter R. Oke & Dr. Gilles Larnicol OSEval-TT mission ** OSEval-TT membership ** Observing
System Events >>>> Download OSEval-TT Work Plan here
<<<< Please note that is page is currently
under development - it was last updated on 18 January 2011 Upcoming and
ongoing activities NEW Assimilation of SSS data HYCOM group at NCEP plan to evaluate the impact of
SSS data on short-range systems for global, regional and hurricane coupled
models in an operational environment (contact Avichal Mehra for details). See also
Tranchant et al. (2008) and
Brassington and Divakaran (2009) for OSSE results that relate to the expected
impact SSS data. NEW CryoSat data availability: Although the priority of the CryoSat-II
mission is to measure changes in ice thickness over the polar regions, it has
been decided by the CryoSat team not to switch off the instruments over the
remaining regions. At this stage, it is anticipated that CryoSat
observations, for delayed-mode applications, will be made available to
scientific users around the end of 2010. Stay tuned to http://earth.esa.int/cryosat for
information regarding data, test data files, and mission operations. Technical Workshop: We have a tentative plan to hold a GODAE
OceanView and OOPC OSEval-IV Workshop in Monterey in June 2011. Details will
follow soon, but it is likely that one of the themes of the workshop will be demonstrating
the impact of in situ observations on forecast and analysis systems. NRT OSE schedule (see draft OSEval-TT work plan, above): When: what data to with-hold: who is
planning to participate Jan 2011 : Argo
: TBA Feb 2011: XBT :
UKMet, Mar 2011: TAO :
UKMet, Apr 2011: Jason-2 :
UKMet, JMA, May 2011: All altimeters
: UKMet, JMA, Jun 2011: AVHRR :
UKMet, One of the aims of the GODAE OceanView Observing
System Evaluation Task Team (OSEval-TT) is to formulate more specific
requirements for ocean observations on the basis of improved understanding of
data utility. The OSEval-TT is jointly formed by GODAE
OceanView and the Ocean Observation Panel for Climate (OOPC). Through
the task team, GODAE OceanView and OOPC partners will get organized at the
international level to provide evidence-based responses to agencies and
organizations in charge of sustaining the global and regional ocean observing
systems used for ocean monitoring and forecasting at short-range, seasonal
and decadal time-scales. This activity requires consistent protocols for
observation impact assessment, tools for routine production of appropriate
diagnostics, common sets of metrics for inter-comparison of results, and
objective methodologies for observing system design and assessment
activities. Details of past GODAE workshops
on Observing System Evaluation can be found on www.godae.org/OSE-meetings.html. Membership of
the OSEval-TT is currently under review. Membership consists of core members,
who are expected to participate in planned OSEval-TT activities; and associate
members, who are expected to be involved in OSEval-TT activities in an
advisory capacity. Core members: - Peter Oke
(Co-Chair, CSIRO) - Gilles
Larnicol (Co-Chair, CLS) - Matthew
Martin (IV-TT Co-Chair, UKMet) - Laurent
Bertino (NERSC) - Pavel Sakov (NERSC) - Avichal Mehra (NOAA) - Yosuke Fujii (JMA/MRI) - Gary Brassington (ETOOFS Chair, BoM) - Pat Hogan (NRL) - Anthony
Weaver (CERFACS) - Magdenana
Balmaseda (ECMWF) - Villy Kourafalou (UMiami) - Daniel Lea
(UKMet) - Jim Cummings (NRL) Associate
members: - Andreas
Schiller (GODAE OceanView Co-Chair, CSIRO) - Eric
Dombrowsky (GODAE OceanView Co-Chair, Mercator) - Eric
Lindstrom (OOPC Chair, NASA) - Fabrice Hernandez (IV-TT Co-Chair, Mercator) The motivation for this activity is in recognition
that the OSEval-TT has a role to play for the provision of recommendations to
the observing agencies and community, particularly during and following
`observing system events`. Here, we regard an observing system event to be a
planned or unplanned loss or gain of instruments. Examples of observation
events include data outages due to altimeter safe-hold or loss, launch of a
new satellite, loss or deployment of Argo floats, etc. Reactions to these
types of events are likely to be irregular, specific short
term actions for the OSEval-TT. In these cases, the OSEval-TT will
provide feedback to observational agencies to demonstrate the impact of such
events on the quality of ocean analysis and forecast products generated
routinely under GODAE OceanView. In practice, the OSEval-TT co-chairs will
solicit input from OSEval-TT members. This input will be consolidated by the
OSEval-TT co-chairs and forwarded to the GODAE OceanView co-chairs for
dissemination to observation agencies and GODAE patrons. To date, members of the OSEval-TT or their
associates have responded to the following observing system events: Availability of SSS data HYCOM group at NCEP plan to evaluate the impact of
SSS data on short-range systems for global, regional and hurricane coupled
models in an operational environment (contact Avichal Mehra from NOAA for
details). Extension of life for Jason-1: Posters presented at OSTST (October 2010) Continuation of Jason-1 processing (June 2009): Following the CalVal period for Jason-2, there was
some discussion about whether Jason-1 data processing should continue in the
inter-leaved orbit. The OSTST chair asked the GODAE OceanView co-chairs to
provide a demonstration of the benefits of retaining Jason-1 and Jason-2
together in inter-leaved orbits. Demonstrations were
provided by the UKMet, BoM, and Mercator. These results were compiled
by the OSEval-TT co-chairs and the GODAE OceanView co-chairs and disseminated
to the OSTST. Requirements for the SMOS and Aquarius missions: Publications by Brassington and Divakaran (2009) and Tranchant et
al. (2008). A technical description of techniques
used for observing system evaluation and design follows. A good overview,
from the NWP literature, is Rabier et al. (2008): Observing System Experiments (OSEs): OSEs involve the systematic denial of a
sub-set of observations, and the evaluation of the degradation in quality of
the resulting analyses and forecasts. The degradation quantifies the impact
of the with-held observations. Relevant references: Balmaseda et al. (2007), Oke and
Schiller (2007; GRL) Observing System Simulation Experiments
(OSSEs): OSSEs, sometimes referred to as twin experiments,
typically use two different models. One model is used to perform a `truth`
run - and it is treated as if it is the real ocean. The truth run is sampled
in a manner that mimics either an existing or future observing system -
yielding synthetic observations. The synthetic observations are assimilated
into the second model, and the model performance is evaluated by comparing it
against the truth run. Relevant references: Ballabrera-Poy et al. (2007), Schiller
et al. (2004), Vecchi and Harrison (2007) Analysis
self-sensitivities Coming soon Relevant references: Cardinala et al. (2004) Singular
vector analysis Coming soon Relevant references: Fujii et al. (2008a,b) Forecast
sensitivities Coming soon Relevant references: Langland and Baker (2004) Adaptive
sampling Coming soon Relevant references: Bishop et al. (2001), O`Kane et al.
(2010) Ensemble
Transform Kalman Filter Coming soon Relevant
references: Bishop et
al. (2001) Publications A list of publications relevant
to observing system design and evaluation follows. This list is incomplete.
Please send any relevant references to Peter Oke. Atlas, R., R. N. Hoffman, S. M. Leidner, J. Sienkiewicz, T.-W. Yu, S. C. Bloom, E. Brin, J. Ardizzone, J. Terry, D.
Bungato, J. C. Jusemm 2001. The effects of marine winds from scatterometer
data on weather analysis and forecasting. B. Am. Meterol. Soc., 82,
1965-1990. Balmaseda, M.A., D. Anderson, and A. Vidard. 2007. Impact of Argo on
analyses of the global ocean.
Geophysical Research Letters 34(L16605): doi:10.1029/2007GL030452. Balmaseda, M.A., and D.
Anderson. 2009. Impact of
initialization strategies and observations on seasonal forecast skill.
Geophysical Research Letters 36(L01701):doi:10.1029/
2008GL035561. Ballabrera-Poy,
J., E. Hackert, R. Murtugudde, and A.J. Busalacchi. 2007. An observing system
simulation experiment for an optimal moored instrument array in the tropical
Indian Ocean. Journal of Climate 20:3249-3268. Barth, N. and C. Wunsch, 1990: Oceanographic experiment
design by simulated annealing. J. Phys. Oceanogr.,
20, 1249-1263. Benkiran, M and E. Greiner.
2007. Data assimilation of drifter velocities in the Mercator Ocean system.
Mercator Ocean quarterly newsletter 25, Available online at www.mercator-ocean.fr/documents/lettre/lettre_25_en.pdf. Benkiran, M., E. Greiner, S. Giraud St
Albin, E. Dombrowsky, D. Jourdan and M. Faillot. 2008. Impact
study of the number Space Altimetry observing systems on the altimeter data
assimilation in the Mercator-Ocean system. In preparation. Berliner, L. M., Q. Lu, and C. Snyder, 1999:
Statistical design for adaptive weather observations. J. Atmos. Sci., 56,
2536-2552. Bishop, C. H., B. J. Etherton, S.
J. Majumdar, 2001: Adaptive sampling with the ensemble transform Kalman
filter. Part I: Theoretical aspects. Mon. Weath. Rev., 129, 420-436. Bishop, C. H., C. A. Reynolds, M. K. Tippett, 2003. Optimization of
the fixed global observing network in a simple model. 60, 1471-1489. Bishop, C. H., B. J. Etherton, S. J. Majumdar, 2006. Verification
region selection and data assimilation for adaptive sampling. 132, 915-933. Brassington, G. B., and P. Divakaran. 2009. The theoretical impact of
remotely sensed sea surface salinity observations in a multi-variate
assimilation system. Ocean Modelling, 27, 70-81. Cardinala, C., S. Pezzulli and E.
Andersson. 2004. Influence-matrix diagnostic of a data assimilation system,
Quarterly Journal of the Royal Meteorological Society 130:2767-2786. Desroziers, G., P. Brousseau, B.
Chapnick, 2005. Use of randomization to diagnose the impact of observations
on analyses and forecasts. Q. J. R. Meteorol. Soc., 131, 2821-2837. Fiorelli et al., 2004: Multi-AUV
Control and adaptive sampling in Monterey Bay, Proc. IEEE Autonomous
Underwater vehicles. Fujii, Y., H. Tsujino, N. Usui, H.
Nakano, and M. Kamachi. 2008a. Application of singular vector analysis to the
Kuroshio large meander. Journal of Geophysical Research, 113(C07026):doi:10.1029/2007JC004476. Fujii, Y., T. Yasuda, S.
Matsumoto, M. Kamachi, and K. Ando 2008b. Observing System Evaluation (OSE)
using the El Nino forecasting system in Japan Meteorological Agency.
Proceedings of the oceanographic society of Japan fall meeting (in Japanese). Guinehut, S.,
G. Larnicol and P.-Y. le Traon. 2002. Design of an
array of profiling floats in the North Atlantic from model simulations.
Journal of Marine Systems 35:1-9. Guinehut, S.,
P.-Y. Le Traon, G. Larnicol and S. Phillips. 2004. Combining
Argo and remote-sensing data to estimate the ocean three-dimensional
temperature fields - a first approach based on simulated observations.
Journal of Marine Systems 46:85-98. Hackert, E. C., R. N. Miller and A. J.
Busalacchi, 1998: An optimized design for a moored instrument array in the
tropical Atlantic Ocean. J. Geophys. Res., 103, 7491-7509. Hirschi, J., J. Baehr, J. Marotzke, J. Stark, S.
Cunningham, and J.-O. Beismann, 2003: A monitoring
design for the Atlantic meridional overturning circulation. Geophys. Res.
Lett., 30, 1413, doi:10.1029/2002GL016776. Kallberg, P., 1984: Performance of some di_erent
FGGE observation subsets for a period in November 1979. Data Assimilation
Systems and Observing System Experiments with particular emphasis on FGGE,
Vol. 1, ECMWF, 203-228. Kharne, S. P., and J. L. Anderson, 2006: An
examination of ensemble filters based adqaptive observation methodologies.
Tellus, 58A, 179-195. Kharne, S. P., and J. L. Anderson, 2006: A methodology
for fixed observational network design: theory and application to a simulated
global prediction system. 58A, 523-537. Kuo, T. H., X. Zou, and W. Huang, 1998: The
impact of global positioning system data on the prediction of an
extratropical cyclone: An observing system simulation experiment. Dyn. Atmos.
Oceans, 27 (1-4), 439-470. Langland, R. H., and N.
L. Baker. 2004. Estimation of observation impact using the NRL atmospheric
variational data assimilation adjoint system. Tellus 56A:189-201. Lawson, W. G., J. A. Hansen, 2004: Implications
of stochastic and deterministic filters as ensemble-based data assimilation
methods in varying regimes of error growth. Mon. Weath. Rev., 132, 1966-1981. Le Henaff, M., P. De Mey,
P. Marsaleix. 2009. Assessment of observational networks with the representer
matrix specra method - application to a 3D coastal model of the Bay of
Biscay. Ocean Dynamics 59:3-20. Le Henaff, M., 2008: Contribution of a Wide-Swath Altimeter in a Shelf
Seas Assimilation System: Impact of the Satellite Roll Errors. Journal of
Atmospheric and Oceanic Technology 25(11). Le Henaff, M., 2008: Assessment of observational networks with the
Representer Matrix Spectra method—application to a 3D coastal model of the
Bay of Biscay. Ocean
Dynamics Le Traon, P.-Y. and G. Dibarboure. 2002. Velocity mapping
capabilities of present and future altimeter missions: The role of high
frequency signals. Journal of Atmospheric and Oceanic Technology
19:2077-2088. Lorenz, E. N., K. A. Emmanuel, 1998. Optimal sites
for supplementary weather observations: simulation with a small model. J.
Atmos. Sci., 55, 399-414. McIntosh, P. C., 1987: Systematic design of
observational arrays, J. Phys. Oceanogr., 17,
885-902. Miyoshi, T., S. Yamane, 2007. Local ensemble
transform Kalman filtering with an AGCM at a T159/L48 resolution. Mon.
Weath. Rev., 135, 3841-3861. Morss, R. E., D. S. Battisti, 2004. Designing efficient observing
networks for ENSO prediction. J. Climate, 17, 3074-3089. Mourre, B., P. De Mey, Y. Menare, F. Lyard, C. Le Provost, 2006:
Relative performance of future altimeter systems and tide gauges in
constraining a model of North Sea high-frequency barotropic dynamics, Ocean
Dynamics, 56, 473-486. O`Kane, T. J., P. R. Oke, P. A. Sandery, 2010: Predicting the East Australian
Current: Errors of the day, Ocean Modelling, submitted. Oke, P. R., T. J. O`Kane, 2010: Observing system design and
assessment. Operational Oceanography in the 21st Century,
Brassington, G. B., A. Schiller, Eds., Springer, in
press. Oke, P. R., M. Balmaseda, M. Benkiran, J. A. Cummings, E. Dombrowsky,
Y. Fujii, S. Guinehut, G. Larnicol, P.-Y. Le Traon,
and M. J. Martin, 2010: Observational requirements of GODAE Systems. In
Proceedings of OceanObs`09: Sustained Ocean Observations and Information for
Society (Vol. 2), Venice, Italy, 21-25 September 2009, Hall, J., Harrison, D.
E. & Stammar, D., Eds., ESA Publication WPP-306. Oke, P. R., M. Balmaseda, M. Benkiran, J. A. Cummings, E. Dombrowsky,
Y. Fujii, S. Guinehut, G. Larnicol, P.-Y. Le Traon,
and M. J. Martin, 2009: Observing System Evaluations using GODAE systems,
Oceanography, 22(3), 144-153. Oke, P. R., P. Sakov and E. Schulz, 2009: A comparison of shelf
observation platforms for assimilation into an eddy-resolving ocean model.
Dynamics of Atmospheres and Oceans, 48, 121-142, doi:10.1016/j.dynatmoce.2009.04.002. Oke, P. R., and A. Schiller, 2007: Impact of Argo, SST and altimeter
data on an eddy-resolving ocean reanalysis. Geophysical Research Letters, 34,
L19601, doi:10.1029/2007GL031549. Oke, P. R., and A. Schiller 2007: A model-based assessment and design
of an optimal mooring array for the Indian Ocean. Journal of Climate, 20,
3269-3283. Pascual A., Y. Faugere,
G. Larnicol and P.-Y. Le Traon. 2006. Improved
description of the ocean mesoscale variability by combining four satellite
altimeters, Geophysical Research Letters 33:doi:10.1029/2005
GL024633. Pascual A., M.I. Pujol,
G. Larnicol, P.-Y. Le Traon, M. H. Rio. 2007.
Mesoscale Mapping Capabilities of Multisatellite Altimeter Missions: First Results
with Real Data in the Mediterranean Sea. Journal of Marine Systems
65:190-211. Pascual A., C. Boone, G.
Larnicol, P.Y. Le Traon. 2008. On the quality of real time altimeter gridded
fields: comparison with in situ data, Journal of Atmospheric and Oceanic
Technology, doi: 10.1175/2008JTECHO556 Rabier, F., P. Gauthier, C. Cardinali, R. Langland, M. Tsyrulnikov, A.
Lorenc, P. Steinle, R. Gelaro, and K. Koizumi. 2008. An update on
THORPEX-related research in data assimilation and observing strategies. Nonlinear
Processes in Geophysics 15:81-94. Sakov, P., and P. R. Oke. 2008. Objective array design: Application to
the tropical Indian Ocean, Journal of Atmospheric and Oceanic Technology
25:794-807. Schiller, A., S. E. Wijffels and G. A.
Meyers, 2004: Design requirements for an Argo float array in the Indian Ocean
inferred from observing system simulation experiments. Journal of Atmospheric
and Oceanic Technology, 21, 1598-1620. Smith, N. R., and G. Meyers, 1996: An evaluation of expendable
bathythermograph and Tropical Atmosphere-Ocean Array data for monitoring
tropical ocean variability. J. Geophys. Res., 101, 28489-28501. Tranchant, B., C.E. Testut, L. Renault, N.
Ferry, F. Birol, P. Brasseur. 2008. Expected impact of the future SMOS and
Acquarius ocean surface salinity missions in the Mercator Ocean operational
systems: new perspectives to monitor ocean circulation. Remote Sensing of
Environment 112:1476-1487. Tremolet, Y.,
2008. Computation of observation sensitivity and observation impact in
incremental variational data assimilation. Tellus, 60A, 964-978. Vecchi, G.A.,
and M.J. Harrison. 2007. An observing system simulation experiment for the
Indian Ocean. Journal of Climate, 20:3300-3343. Vidard, A., D.L.T.
Anderson, and M. Balmaseda. 2007. Impact of ocean observation systems on
ocean analysis and seasonal forecasts, Monthly Weather Review 135:409-429. Vigan, X., C. Provost, R. Bleck, P.
Courtier, 2000. Sea surface velocities from the sea surface temperature image
sequence, 1. Method and validation using primitive equation model output.
Journal of Geophysical Research 105:19499-19514. Walstad, L. J., D. J. McGillicuddy, 2000.
Data assimilation for coastal observing systems. Oceanography, 13, 47-53. Zhang, S., M. J. Harrison, A. Rosati, A. Wittenberg, 2007: System design and evaluation of
coupled ensemble data assimilation for global oceanic climate studies, Mon.
Weath. Rev., 135, 3541-3564. |
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