Impact of Argo Salinity Observations on Ocean Analyses

Impact of Argo Salinity Observations on Ocean Analyses

Acknowledgement:

Gregg Johnson (TAO servicing cruise data)Willa Zhu (retrieving recent TAO servicing cruise data)Dave Behringer (quality-controlled XBT data)

Chaojiao Sun, Michele RieneckerChristian Keppenne, Jossy Jacob, Robin Kovach

NASA/GSFC Global Modeling and Assimilation Office (GMAO)

Previous studies have shown that assimilating temperature and synthetic salinity has an impact on salinity and current fields (Sun et al., 2006).

Motivation

• Experiment details: 2000-2004, focusing on the last year 2004 Experiment 1 (“ARGO”): assimilates Argo temperature and salinity, in addition to the

assimilation of subsurface temperature observations and synthetic salinity profiles (where no Argo salinity data is available).

Experiment 2: (“NARGO”): no Argo data used, only subsurface temperature (XBT and moorings) observations and synthetic salinity profiles are assimilated.

Experiment 3: (“MODEL”): model simulation without any assimilation.

• Observations

XBT (QC by NCEP/Dave Behringer)

TAO/TRITON/PIRATA (delayed mode, QC by PMEL)

Argo (delayed mode, QC by GODAE/Monterey server)• Forcing:

+ Atlas/SSMI time varying wind stress

+ E-P forcing, with P from GPCP monthly mean precipitation

+ NCEP CDAS1 SW (for penetrating radiation) & LH (for evaporation)

+ relaxation to Reynolds SST

• Salinity analysis validation: independent observations CTD casts from TAO servicing cruises

Purpose: To assess the impact of Argo salinity assimilation on ocean analyses using independent salinity observations.

Observation and model errorsObservation error estimates are based on the vertical temperature and salinity gradient, with the

maximum and minimum specified as the following: Argo salinity error: minimum 0.03 psu, maximum 0.20 psuSynthetic salinity error: minimum 0.05 psu, maximum 0.30 psu.Temperature observation error: minimum 0.3oC, maximum 0.7oC.

Model errors are assigned uniformly (based on ensembles model simulations):Temperature error: 0.77oCSalinity error: 0.20 psu

Profile distribution and volume in 2004 in the tropical band of 10S-10N

180E; Dec 3-12 2004

MODEL simulation

ARGO analysis

NARGO analysis

TAO CTD casts: Jun 20-29,1004

Note: color scale of model simulation and analyses does not exactly match that of CTD casts plotted at the EPIC website. Pink line denotes the mixed layer depth.

MODEL simulation

ARGO analysis

NARGO analysis

TAO CTD casts: Jun 20-29,1004155W, 8S-12N

# of Argo obs. Apr-May-Jun,2004: 67

# of Argo obs. during Jun 20-29: 8

# of Argo obs. in Jun 2004: 26

TAO CTD casts: Jun 20-29,1004155W, 8S-12N

Number of ARGO profiles during and before the CTD casts. Note that the same ARGO analysis is shown in all three analysis plots.

Mean and STD of differences between analysis, model simulation and independent CTD observations

Surface Salinity at Equatorial Pacific (2000-2004)

TAO ARGO NARGO MODEL

Surface Salinity at 180W (2000-2004)ARGO NARGO MODEL

150m Salinity at 180W (2000-2004)ARGO NARGO MODEL

Argo makes a difference:

Synthetic salinity profiles derived from Levitus T-S climatology are useful in reducing subsurface model salinity bias.

Argo salinity observations reduce the impact of climatology of the synthetic salinity, introducing more subsurface variability than in the MODEL or NARGO cases

Argo salinity observations improve the comparison with independent CTD observations in the overall salinity structure [horizontal and vertical gradients]

Subsurface salinity assimilation impacts surface salinity distribution.

Aquarius:Aquarius data will help:

validation assimilation for the surface layers

Conclusions

Future work

• Validate salinity at depth and currents

• Assimilate available surface salinity data to evaluate the impact of surface salinity from Aquarius

GMAO treatment of salinity via TS – scheme: T and S assimilation • S comes from ARGO when available• Synthetic S(z) - T(z) is used with T-S relation from Levitus climatology to generate a synthetic S(z) “consistent” with temperature variations• No modification of salinity in the model’s surface mixed layer; salinity varies according to estimated E-P

Climatology T(z)Climatology T(z) Climatology S(z)

Observed T(z)

Schematic of the derivation of synthetic salinity profiles.