MIRAS performance based on OS data
SMOS MIRAS IOP 6th Review, ESAC – 17 June 2013
Prepared by:
• J. Font, SMOS Co-Lead Investigator, Ocean Salinity – ICM-CSIC
MIRAS performance impact
on OS data
To review influence on OS retrieval of:
a. Anomaly issues
b. Operations
c. Changes in instrument configuration
d. Calibration issues: short and longterm drift effects
SMOS MIRAS IOP REVIEW MEETING (06)
ESAC, 17 June 2013
2
MIRAS performance impact
on OS data
OS retrieval is difficult due to:
–
Low sensitivity of Tb to OS
–
Unsolved interferometry issues
–
Incomplete knowledge of geophysical model
function
Consequences:
–
Higher impact of MIRAS performance on OS
than on SM
–
L1 and L2 processors still not optimal
–
Mission requirements only possible at L3
SMOS MIRAS IOP REVIEW MEETING (06)
ESAC, 17 June 2013
3
MIRAS performance impact
on OS data
Present situation:
–
Imperfections in instrument calibration and
image reconstruction are mitigated by L2OS
processor before retrieval (OTT method),
but significant biases remain uncorrected
–
Difficult to separate impact of MIRAS
performance from poorly corrected
geophysical variability (Sun, galaxy, TEC)
SMOS MIRAS IOP REVIEW MEETING (06)
ESAC, 17 June 2013
4
MIRAS performance impact
on OS data
1. Anomaly issues
2. Operations
• Most of specific/time-limited problems or
acquisition interruptions (anomalies, data loss or
corruption) translate into flagging of deficient L1 or
L2OS, so that are not used in building salinity maps
(L3), e.g.
•
Long gaps: “January failures” (arm A 2010,
arm B 2011)
•
Short gaps: unlocks, calibration events ...
SMOS MIRAS IOP REVIEW MEETING (06)
ESAC, 17 June 2013
5
MIRAS performance impact
on OS data
• Unexplained change in April 2010
•
Only data after Commissioning used for
statistical OS analysis
• NIR_AB Tp7 jump on 11.04.2012
•
Not tracked on L2OS since it occurred during
an orbit over land
•
No impact observed on L3 maps (probably
hidden by stronger variability sources)
SMOS MIRAS IOP REVIEW MEETING (06)
ESAC, 17 June 2013
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MIRAS performance impact
on OS data
3. Changes in instrument configuration
• No impact of changes from redundant to nominal
• Dual/Full polarisation
•
Require different OTT
•
Slightly higher OS error in FP due to higher Tb
noise, but more info on Faraday rotation
•
Commissioning data not further used for longterm OS analysis
• LO calibration at different frequencies
•
Used for specific impact studies on OS
•
No evident effect observed on L3
SMOS MIRAS IOP REVIEW MEETING (06)
ESAC, 17 June 2013
7
MIRAS performance impact
on OS data
4. Calibration issues
• Short (orbital) and long-term drifts due to imperfect
calibration
• Situation improving with improved antenna loss
models, but still not optimal
• In L2OS v550 a time-varying asc/desc OTT was
introduced to mitigate the impact of these drifts
• Monthly and not centred OTTs (DPGS) produce strong
differences wrt bi-weekly and centred (reprocessing)
• New OTT strategy for v610 (OTT post-processor)
SMOS MIRAS IOP REVIEW MEETING (06)
ESAC, 17 June 2013
8
MIRAS performance impact
on OS data
Orbital
Drift
0.5 K
Residual Tb drifts that
impact on OS errors
(1 K ≈ 2 psu) and should
be corrected by OTT
Seasonal
Drift: 1 K
Initial
Transient
12 Month
Drift
0.1 K/year
J. Tenerelli, CLS
MIRAS performance impact
on OS data
• OTT computation and ingestion has a strong impact
on retrieved OS
Reprocessed vs. operational
SMOS-Argo:
Same data but OTT bi-weekly
and computed in the middle of
the period (repro) vs. OTT
monthly and computed at the
beginning (oper)
This effect is much more
relevant than the impact of
synchronisation between OTT
and NIR calibration
SMOS MIRAS IOP REVIEW MEETING (05)
10
J. Martínez, SMOS-BEC
ESAC, 09 Nov 2012
MIRAS performance impact
on OS data
•
Unrealistic salinity variability with monthly OTT
Two maps built with 9 days of
SMOS L2OS products (asc +
desc) separated by 9 days:
24 May – 1 June 2012
11 – 19 June 2012
Using the same OTT
We observe a global freshening
that has no oceanographic
meaning in this time interval
Instrumental or external
geophysical variability?
If OTT correction was OK for
one map, certainly not for the
other one
SMOS MIRAS IOP REVIEW MEETING (06)
ESAC, 17 June 2013
11
MIRAS performance impact
on OS data
Other details still under discussion
SMOS MIRAS IOP REVIEW MEETING (06)
ESAC, 17 June 2013
12
MIRAS performance impact
on OS data
Seasonal effects
• Seasonal variability of geophysical conditions (Sun
and galaxy position) requires time-varying OTT to
cope for L1 (Sun removal) and L2 (galactic glint
modelling) processors deficiencies
• But also some seasonal or long-term variability
linked to instrument behaviour seems also to be
present (see next slides)
SMOS MIRAS IOP REVIEW MEETING (06)
ESAC, 17 June 2013
13
MIRAS performance impact
on OS data
•
Retrieved mean salinity drift during 2012
SSS1 – same results with SSS2/3,
P. Spurgeon, ARGANS
Same trend with ascending/descending, so not TEC, Sun or galaxy
Seemingly related to instrument behaviour
Relating SSS map biases to
Hovmoller plots of biases
J. Tenerelli, CLS
Jun,Jul,Aug 2012
Nov,Dec,Jan 2012/3
SSS bias transforms into first
Stokes bias nearly linearly
J. Tenerelli, CLS
Jun,Jul,Aug 2012
Nov,Dec,Jan 2012/3
SSS bias transforms into first
Stokes bias nearly linearly
J. Tenerelli, CLS
Jun,Jul,Aug 2012
Nov,Dec,Jan 2012/3
AF-FOV bias trends:
40oS to 5oN
Trends of one-slope and calibrated L1 solutions for AF-FOV mean
bias in (Tx+Ty)/2 compared to trends in latitudinally-averaged
Tp7 deviations. Tp7 curves are offset to fit on these figures.
J. Tenerelli, CLS
First Stokes biases in asc and desc passes exhibit a long-term trend
that is not present in Tp7. Also amplitude of bias drop late in year in
descending passes is increasing from year to year while the
variation of Tp7 is not. So perhaps a thermal effect is not the whole
story; perhaps L-band brightness of sun plays a role.
Comparison to NIR TA drift:
40oS to 5oN
J. Tenerelli, CLS
Overall, for
ascending passes
there is good
correspondence
between NIR TA
evolution (red and
blue curves) and
AF-FOV bias with
and without direct
sun correction
(cyan and green
curves).
Latitudinal biases of Tvwind
at 7m/s
L1C v504
1. Latitudinal drifts in TBwind deduced from SMOS TB of
v3 and v5 are observed, especially at low incidence
July
angles in EAFFOV and at large incidence angle above
50°in the front of the FOV.
2. Inaccuracies in modeling of Tbgal, Tbflat, Tbatm and
Faraday rotation can not explain the latitudinal drifts in
TBwf
TBwind.
3. Empirical estimate of TBwind versus WS from SMOS TB
is dependent on various seasons and on the TB versions.
X. Yin & J. Boutin,
LOCEAN
Latitudinal biases :
seasonal behaviour
Total drifts from 55S to 0S are close in July and
August and are different to the value in December
July Aug
Dec.
Orbital dynamics of Tp7 are close in July and
August and are different to the value in December
X. Yin & J. Boutin,
LOCEAN
MIRAS performance impact
on OS data
Conclusions:
–
General: difficult to extract MIRAS performance
impact from OS products
–
Anomalies and operation issues result in data loss
or flagging, then not used for OS
–
No impact of configuration changes
–
Imperfect calibration mitigation addressed
through OTT (only partly successful)
–
Unexplained orbital and seasonal effects present
–
Longer time-scale drifts observed, maybe linked to
instrument behaviour
SMOS MIRAS IOP REVIEW MEETING (06)
ESAC, 17 June 2013
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