D W Behringer NOAA/NCEP NOAA Climate Observation Program 4 th Annual System Review

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Operational NCEP Global Ocean Data Assimilation System at NCEP: the impact of Argo salinity and TOPEX/Jason-1 altimetry. D W Behringer NOAA/NCEP NOAA Climate Observation Program 4 th Annual System Review Silver Spring, MD May 10-12, 2006. Ocean Model MOMv3 quasi-global - PowerPoint PPT Presentation

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Operational NCEP Global Ocean Data Assimilation System at NCEP: the

impact of Argo salinity and TOPEX/Jason-1 altimetry

D W Behringer NOAA/NCEPNOAA Climate Observation Program 4th Annual System Review

Silver Spring, MDMay 10-12, 2006

ClimateForecastSystem(CFS)

Ocean ModelMOMv3

quasi-global1ox1o (1/3o in tropics)

40 levels

Atmospheric ModelGFS (2003)

T6264 levels

Seasonal to Interannual Prediction at NCEP

ClimateForecastSystem(CFS)

MOMv3 GFS

Seasonal to Interannual Prediction at NCEP

Reanalysis-23DVART62L28

update of theNCEP-NCAR R1

GODAS3DVAR

XBTTAO etc

ArgoSalinity (syn.)

(TOPEX/Jason-1)

Ocean observations used in GODAS

Requirements:• A data set that spans 20+ years.• Global coverage with emphasis on the tropics.• Emphasis on the surface and upper ocean.

Consequently:• Primary reliance on ocean profiles (XBT, TAO, Argo)

and on SST (Reynolds analysis).• Stability of TAO and growth of Argo mean in situ

profiles retain central importance.• Satellite altimetry, available since 1992, arrived at a

time when ocean models were already well constrained by in situ data.

GODAS Experiments

• GDS - operational version, assimilates temperature from XBTs (xT), Argo (aT) and TAO/Triton/PIRATA (tT) and synthetic salinity (sS)

• GDSA - assimilates xT, aT, tT, sS and Argo salinity (aS)

• GDSAX - assimilates xT, sS, aT and aS. NO TAO!

• GDSTJ - assimilates xT, aT, tT, sS and TOPEX/Jason1 (TJ)

• RA6 - Previous operational system, Pacific Ocean only, assimilates xT, aT, and tT, but NOT salinity

• CON - control, model is configured as in GDS, but there is no data assimilation

GODAS Experiments

• GDS - operational version, assimilates temperature from XBTs (xT), Argo (aT) and TAO/Triton/PIRATA (tT) and synthetic salinity (sS)

• GDSA - assimilates xT, aT, tT, sS and Argo salinity (aS)

• GDSAX - assimilates xT, sS, aT and aS. NO TAO!

• GDSTJ - assimilates xT, aT, tT, sS and TOPEX/Jason1 (TJ)

• RA6 - Previous operational system, Pacific Ocean only, assimilates xT, aT, and tT, but NOT salinity

• CON - control, model is configured as in GDS, but there is no data assimilation

Model temperature and salinity vs observations in five zonal bands.

GODAS Experiments

• GDS - operational version, assimilates temperature from XBTs (xT), Argo (aT) and TAO/Triton/PIRATA (tT) and synthetic salinity (sS)

• GDSA - assimilates xT, aT, tT, sS and Argo salinity (aS)

• GDSAX - assimilates xT, sS, aT and aS. NO TAO!

• GDSTJ - assimilates xT, aT, tT, sS and TOPEX/Jason1 (TJ)

• RA6 - Previous operational system, Pacific Ocean only, assimilates xT, aT, and tT, but NOT salinity

• CON - control, model is configured as in GDS, but there is no data assimilation

Model temperature and salinity vs observations in five zonal bands.

GODAS Experiments

• GDS - operational version, assimilates temperature from XBTs (xT), Argo (aT) and TAO/Triton/PIRATA (tT) and synthetic salinity (sS)

• GDSA - assimilates xT, aT, tT, sS and Argo salinity (aS)

• GDSAX - assimilates xT, sS, aT and aS. NO TAO!

• GDSTJ - assimilates xT, aT, tT, sS and TOPEX/Jason1 (TJ)

• RA6 - Previous operational system, Pacific Ocean only, assimilates xT, aT, and tT, but NOT salinity

• CON - control, model is configured as in GDS, but there is no data assimilation

Model SSH vs TOPEX / Jason-1 SSH.

12 / 28 / 1997 - 1 / 07 / 1998

30K/mo

Concluding Remarks

• The experiments described here can only provide a preliminary look at the impact of Argo on the NCEP GODAS. Over the 2000-2005 period, the Argo array has approached full global coverage only during the last 2 years. Several more years will be needed before more definitive conclusions can be drawn, but some preliminary remarks are possible.

• The assimilation of the Argo salinity data, which are not part of the operational GODAS data set, produces a measurable improvement in the GODAS salinity field.

• A system that mixes observed and synthetic salinity profiles reduces the potential impact of the observations. If synthetic salinity profiles cannot be avoided, a more sophisticated approach to their computation could help.

• In the last few years the Argo array has replaced the XBT network as the primary source of global subsurface temperature data. However, its coverage of the tropical Pacific is not sufficient for Argo to act as a replacement or substitute for the TAO/TRITON array.

Concluding Remarks - continued

• A consistent, uninterrupted altimetry data set (TOPEX/Jason-1) has been available since late 1992, providing a good basis for testing its impact on GODAS.

• In the equatorial Pacific the assimilation of the TAO mooring data leads to a good representation of anomalous SSH in the operational GODAS (and RA6). Assimilation of T/J-1 improves GODAS SSH beyond the bounds of the TAO array and well into the subtropics.

• In the Atlantic and Indian Oceans the operational GODAS does a poor job representing the SSH anomaly field and appears to do no better than the Control experiment. In these two oceans the assimilation of T/J1greatly improves GODAS SSH.

• Comparison of the Control and GODAS experiments with an Atlantic CTD section shows that the assimilation of subsurface data (XBTs, Argo) largely serves to correct model bias. Comparison with the GODAS-TJ experiment shows that only small additional subsurface changes are needed to improve anomalous SSH.

Concluding Remarks - continued

• The question remains whether adding new data sets to the operational GODAS will have an impact on the NCEP S/I forecasts. An answer to this question is only possible after a data set is available for a period of many years (20+) spanning several ENSO events. Any conclusions drawn from retrospective forecasts over a shorter period of time would lack statistical reliability.

• In the interim, the most sensible strategy may be to work to improve both the model and the assimilation method so as to make the best possible use of the available data.

• Thus, from the perspective of S/I prediction, it is imperative to support not only the acquisition of new data, but also the development of improved techniques to make use of them.

cfs.ncep.noaa.gov/cfs/godaswww.cpc.ncep.noaa.gov/products/GODAS

The End

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