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Assessing the impact of
observations on ocean forecasts
and reanalyses
Peter Oke and Gilles Larnicol
CSIRO and CLS
May 2015
Talk Outline
 GODAE OceanView and the OSEval Task Team
 OSEval-TT mission
 Examples of OSEval activities
 OSEval plans
Coastal Ocean and
Shelf Seas Task
Team (COSS-TT)
Pierre De Mey &
Villy Kourafalou
Intercomparison
and Validation Task
Team (IV-TT)
Fabrice Hernandez &
Greg Smith
Marine Ecosystem
Analysis and
Prediction Task
Team (MEAP-TT)
Katja Fennel & Marion Gehlen
Observing System
Evaluation Task
Team (OSEval-TT)
Peter Oke & Gilles Larnicol
Coupled
Prediction Task
Team (CP-TT)
Hal Richie & Chris Harris
Data Assimilation
Task Team (DA-TT)
Matt Martin & Andy Moore
OSEval Activities
 Capacity building;
 Routine monitoring;
 Community Observing
System Experiments; &
 Inter-comparisons of
observation impacts.
Co-Chairs:
Peter Oke (CSIRO)
Gilles Larnicol (CLS)
OSEval-TT mission
is to support observational
community by demonstrating
the impact of observations
on ocean forecast and
reanalysis systems
Associate members:
3Fabrice Hernandez (Mercator)
4Matt Martin (UKMet)
5Hans Bonekamp (EUMETSAT)
5Craig Donlon (ESA)
1CLIVAR GSOP rep.
2CGOV OSS-TT rep.
3GOV IV-TT rep.
4GOV DA-TT rep.
5GOV Patron rep.
TT Members:
1Magdalena Balmaseda (ECMWF)
Laurent Bertino (NERSC)
Pat Hogan (NRL)
Yosuke Fujii (JMA/MRI)
2Villy Kourafalou (UMiami)
Daniel Lea (UKMet)
Elisabeth Remy (Merc. Oc.)
Greg Smith (EnvC)
Clementa Tanajura (REMO)
Guimei Liu (NMEFC)
OSEval meetings
Paris – 2007 … OSEval-TT founded
Toulouse – 2009
Towards routine monitoring
Toulouse – 2014 … OSEval & E-AIMS & CLIVAR/GSOP
Santa Cruz – 2011 … OSEval & inter-comparisons
Some OSEval activities are simple
and practical – just involving model
inter-comparisons
Numberofbuoys
returningdata
Totaldatareturn
(%)
2010 2011 2012 2013
JMA example of inter-comparisons
demonstrating obs impacts
2010 2011 2012 2013
JAS 2010: Complete TAO array  agreement between systems  high confidence
JMA example of inter-comparisons
demonstrating obs impacts
TAO observations are essential for seasonal prediction
Fujii et al. (2014; QJRMS) – TPOS community paper
JAS 2013: Degraded TAO array  disagreement between systems  low confidence
Some diagnostics from data
assimilation systems quantify the
impacts of assimilated observations:
… they’re inexpensive to calculate
… but they’re not easily understood
… we’re working on making these
meaningful to everybody
TOPAZ example of obs-
impact diagnostics
 100-member EnKF;
 Assimilating SLA, SST, ice
concentration & drift, T/S - ~400K
obs/week
 We can compute inexpensive
diagnostics for every assimilation
cycle to show the impact of every
observation
 Helps identify bad observations or
under-sampling … where obs have
significant impact
SRF = Spread Reduction Factor …
quantifies how much each observation
reduces analysis error.
Higher SRF  greater impacts Sakov et al. 2012; Ocean Science
Impact of altimetry
Impact of SST
Impact of Ice Concentration
Impact of Ice velocity (u)
Impact of Ice velocity (v)
Impact of temperature (Argo)
Impact of salinity (Argo)
Some studies contribute to
discussions about options for
future observational arrays
Mercator OSSE example: application to wide-swath altimetry
M. Benkiran
and E. Remy
“Truth” – from a 3 km res
model “J1+J2+En” “7-km SWOT”
Step 1: 3-km model is treated as the true ocean
Step 2: sampling represents traditional and wide-swath altimetry
Step 3: assimilated synthetic “obs” back into model – and assess
Mercator OSSE example: application to wide-swath altimetry
M. Benkiran
and E. Remy
0.0 0.5 1.0 0.0 0.5 1.0
0.0 0.5 1.0
No assimilation “J1+J2+En” “7-km SWOT”
Correlation of SSH with “truth” …
Indicates that one SWOT altimeter is better than 3
traditional altimeters for high-resolution forecasting
R= 0.59 R= 0.80R= 0.72
Some studies exploit operational
forecasts systems and simply
withhold all, or some,
observations to quantify how the
forecasts degrade with the
missing observations
GIOPS example of
OSE: impact of loss
of all observations
Canadian operational ocean
forecast system simulating
the degradation in skill
following a complete loss of
observations …
The system reverts to
the skill of a free model
run over a 3 months
period.
All data: assimilates
altimetry, satellite SST, Argo,
XBT, and data from moorings.
Courtesy of Greg Smith
GOV OSEval-TT plans
1. Observation Impact
Statements
1. Annual Community Observing
System Experiments
1. Impact and exploitation of
satellite salinity observations
(proposal to ESA in preparation)
Summary
 OSEval-TT community is active – regularly undertaking studies
to assess past, present, or future observing systems
 OSEval-TT has promoted several practical approaches to
observing system evaluation
 Annual community OSEs are planned …
 Broader engagement with the observational community is sought
… how can we help?
Community OSEval papers
Fujii, Y., J. Cummings, Y. Xue, A. Schiller, T. Lee, O. Alves, M. Balmaseda, B. Cornuelle, M. Martin, S.
Masuda, P. R. Oke, E. Remy, G. Vernieres, X. Yang, 2015: Evaluation of the Tropical Pacific Observing
System from the Ocean Data Assimilation Perspective, Quarterly Journal of the Royal
Meteorological Society, in press.
Oke, P. R., G. Larnicol, E. M. Jones, V. Kourafalou, A. K. Sperrevik, F. Carse, C. A. S. Tanajura, B. Mourre, M.
Tonani, G. B. Brassington, M. Le Henaff, G. R. Halliwell, Jr., R. Atlas, A. M. Moore, C. A. Edwards, M. J.
Martin, A. A. Stellar, A. Alvarez, P. De Mey, M. Iskandarani, 2014: Assessing the impact of
observations on ocean forecasts and reanalyses: Part 2, Regional applications. Journal of
Operational Oceanography, in press.
Oke, P. R., G. Larnicol, Y. Fujii, G. C. Smith, D. J. Lea, S Guinehut, E. Remy, M. Alonso Balmaseda, T. Rykova,
D. Surcel-Colan, M. J. Martin, A. A. Sellar, S. Mulet, I. Pujol, 2014: Assessing the impact of
observations on ocean forecasts and reanalyses: Part 1, Global studies. Journal of Operational
Oceanography, in press.
Larnicol, G., P. R. Oke, GODAE OceanView Observing System Evaluation (OSEval) Task Team news, 2013:
Mercator Newsletters, 13, 3-5.
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.
Annual Community Observing System Experiments
 All GODAE OceanView partners perform a single OSE, once a
year, for community evaluation.
Preliminary schedule of Community OSEs:
Initial time End time Data with-held Due date
7/2013 12/2013 Degraded Argo array (-20%) 4/2015
7/2014 12/2014
X altimeter(s) of the
constellation (TBD)
4/2016
7/2015 12/2015 Tropical moorings 4/2017
7/2016 12/2016 X% of Argo (TBD) 4/2018
7/2017 12/2017
X altimeter(s) of the
constellation (TBD)
4/2019

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C3.04: Assessing the impact of observations on ocean forecasts and reanalyses - Peter Oke

  • 1. Assessing the impact of observations on ocean forecasts and reanalyses Peter Oke and Gilles Larnicol CSIRO and CLS May 2015
  • 2. Talk Outline  GODAE OceanView and the OSEval Task Team  OSEval-TT mission  Examples of OSEval activities  OSEval plans
  • 3. Coastal Ocean and Shelf Seas Task Team (COSS-TT) Pierre De Mey & Villy Kourafalou Intercomparison and Validation Task Team (IV-TT) Fabrice Hernandez & Greg Smith Marine Ecosystem Analysis and Prediction Task Team (MEAP-TT) Katja Fennel & Marion Gehlen Observing System Evaluation Task Team (OSEval-TT) Peter Oke & Gilles Larnicol Coupled Prediction Task Team (CP-TT) Hal Richie & Chris Harris Data Assimilation Task Team (DA-TT) Matt Martin & Andy Moore
  • 4. OSEval Activities  Capacity building;  Routine monitoring;  Community Observing System Experiments; &  Inter-comparisons of observation impacts. Co-Chairs: Peter Oke (CSIRO) Gilles Larnicol (CLS) OSEval-TT mission is to support observational community by demonstrating the impact of observations on ocean forecast and reanalysis systems Associate members: 3Fabrice Hernandez (Mercator) 4Matt Martin (UKMet) 5Hans Bonekamp (EUMETSAT) 5Craig Donlon (ESA) 1CLIVAR GSOP rep. 2CGOV OSS-TT rep. 3GOV IV-TT rep. 4GOV DA-TT rep. 5GOV Patron rep. TT Members: 1Magdalena Balmaseda (ECMWF) Laurent Bertino (NERSC) Pat Hogan (NRL) Yosuke Fujii (JMA/MRI) 2Villy Kourafalou (UMiami) Daniel Lea (UKMet) Elisabeth Remy (Merc. Oc.) Greg Smith (EnvC) Clementa Tanajura (REMO) Guimei Liu (NMEFC)
  • 5. OSEval meetings Paris – 2007 … OSEval-TT founded Toulouse – 2009 Towards routine monitoring Toulouse – 2014 … OSEval & E-AIMS & CLIVAR/GSOP Santa Cruz – 2011 … OSEval & inter-comparisons
  • 6. Some OSEval activities are simple and practical – just involving model inter-comparisons
  • 7. Numberofbuoys returningdata Totaldatareturn (%) 2010 2011 2012 2013 JMA example of inter-comparisons demonstrating obs impacts 2010 2011 2012 2013
  • 8. JAS 2010: Complete TAO array  agreement between systems  high confidence JMA example of inter-comparisons demonstrating obs impacts TAO observations are essential for seasonal prediction Fujii et al. (2014; QJRMS) – TPOS community paper JAS 2013: Degraded TAO array  disagreement between systems  low confidence
  • 9. Some diagnostics from data assimilation systems quantify the impacts of assimilated observations: … they’re inexpensive to calculate … but they’re not easily understood … we’re working on making these meaningful to everybody
  • 10. TOPAZ example of obs- impact diagnostics  100-member EnKF;  Assimilating SLA, SST, ice concentration & drift, T/S - ~400K obs/week  We can compute inexpensive diagnostics for every assimilation cycle to show the impact of every observation  Helps identify bad observations or under-sampling … where obs have significant impact SRF = Spread Reduction Factor … quantifies how much each observation reduces analysis error. Higher SRF  greater impacts Sakov et al. 2012; Ocean Science Impact of altimetry Impact of SST Impact of Ice Concentration Impact of Ice velocity (u) Impact of Ice velocity (v) Impact of temperature (Argo) Impact of salinity (Argo)
  • 11. Some studies contribute to discussions about options for future observational arrays
  • 12. Mercator OSSE example: application to wide-swath altimetry M. Benkiran and E. Remy “Truth” – from a 3 km res model “J1+J2+En” “7-km SWOT” Step 1: 3-km model is treated as the true ocean Step 2: sampling represents traditional and wide-swath altimetry Step 3: assimilated synthetic “obs” back into model – and assess
  • 13. Mercator OSSE example: application to wide-swath altimetry M. Benkiran and E. Remy 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 No assimilation “J1+J2+En” “7-km SWOT” Correlation of SSH with “truth” … Indicates that one SWOT altimeter is better than 3 traditional altimeters for high-resolution forecasting R= 0.59 R= 0.80R= 0.72
  • 14. Some studies exploit operational forecasts systems and simply withhold all, or some, observations to quantify how the forecasts degrade with the missing observations
  • 15. GIOPS example of OSE: impact of loss of all observations Canadian operational ocean forecast system simulating the degradation in skill following a complete loss of observations … The system reverts to the skill of a free model run over a 3 months period. All data: assimilates altimetry, satellite SST, Argo, XBT, and data from moorings. Courtesy of Greg Smith
  • 16. GOV OSEval-TT plans 1. Observation Impact Statements 1. Annual Community Observing System Experiments 1. Impact and exploitation of satellite salinity observations (proposal to ESA in preparation)
  • 17. Summary  OSEval-TT community is active – regularly undertaking studies to assess past, present, or future observing systems  OSEval-TT has promoted several practical approaches to observing system evaluation  Annual community OSEs are planned …  Broader engagement with the observational community is sought … how can we help?
  • 18. Community OSEval papers Fujii, Y., J. Cummings, Y. Xue, A. Schiller, T. Lee, O. Alves, M. Balmaseda, B. Cornuelle, M. Martin, S. Masuda, P. R. Oke, E. Remy, G. Vernieres, X. Yang, 2015: Evaluation of the Tropical Pacific Observing System from the Ocean Data Assimilation Perspective, Quarterly Journal of the Royal Meteorological Society, in press. Oke, P. R., G. Larnicol, E. M. Jones, V. Kourafalou, A. K. Sperrevik, F. Carse, C. A. S. Tanajura, B. Mourre, M. Tonani, G. B. Brassington, M. Le Henaff, G. R. Halliwell, Jr., R. Atlas, A. M. Moore, C. A. Edwards, M. J. Martin, A. A. Stellar, A. Alvarez, P. De Mey, M. Iskandarani, 2014: Assessing the impact of observations on ocean forecasts and reanalyses: Part 2, Regional applications. Journal of Operational Oceanography, in press. Oke, P. R., G. Larnicol, Y. Fujii, G. C. Smith, D. J. Lea, S Guinehut, E. Remy, M. Alonso Balmaseda, T. Rykova, D. Surcel-Colan, M. J. Martin, A. A. Sellar, S. Mulet, I. Pujol, 2014: Assessing the impact of observations on ocean forecasts and reanalyses: Part 1, Global studies. Journal of Operational Oceanography, in press. Larnicol, G., P. R. Oke, GODAE OceanView Observing System Evaluation (OSEval) Task Team news, 2013: Mercator Newsletters, 13, 3-5. 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.
  • 19. Annual Community Observing System Experiments  All GODAE OceanView partners perform a single OSE, once a year, for community evaluation. Preliminary schedule of Community OSEs: Initial time End time Data with-held Due date 7/2013 12/2013 Degraded Argo array (-20%) 4/2015 7/2014 12/2014 X altimeter(s) of the constellation (TBD) 4/2016 7/2015 12/2015 Tropical moorings 4/2017 7/2016 12/2016 X% of Argo (TBD) 4/2018 7/2017 12/2017 X altimeter(s) of the constellation (TBD) 4/2019