Correcting method of Argo data based on HydroBase I
Taiyo Kobayashi1, Yasuko Ichikawa2,
Yasushi Takatsuki2, Toshio Suga1,
Naoto Iwasaka1, Kentaro Ando2,
Keisuke Mizuno2, Nobuyuki Shikama1,
and Kensuke Takeuchi1
― Introduction of Potential Conductivity ―
New method to correct conductivity data measured by Argo float is
developed. In this method, many climatological profile data of
HydroBase can be used as the reference to correct Argo data
by introducing a new variable named "potential conductivity".
The corrected Argo data by this method become much better in
comparison with the CTD data independently observed by R/V Mirai
at almost the same time and location.
Also the corrected data suggest that this method does not
strictly depend on the quality and quantity of the climatological data.
Key words: Argo project, Quality Control, HydroBase,
Conductivity sensor correction
1: Frontier Observational Research System for Global Change, Climate Variations
Observational Research Program
2: Japan Marine Science and Technology Center, Ocean Research Development
In this study, we introduce a correcting-method of Argo (salinity) data,
which is planed to be used in Japan Argo delayed-mode database
Firstly, we show the horizontal movements of two Argo floats,
WMO 29032 and 29033, used in this study.
They were deployed in March 2000 and drifted in the sea for more
than one year.
Fig. 1: Horizontal distribution of locations observed by the Argo floats
(WMO 29032 and 29033) with climatological bottle sampling data.
Red circles represent stations of WOCE-CTD data.
Note that the location of the profile #11 of WMO29033 was not fixed.
Examples of the salinity/conductivity sensor drift equipped with Argo floats.
Example 1: Sudden drift (WMO 29033)
Salinity drift occurred between profiles #10 and #12
when it was drifting near sea surface for about 3 months in summer
due to the insufficiency of its buoyancy (here after "summer vacation").
Fig. 2: T-S diagram of WMO 29033 observations.
The red and blue circles represent the profiles #1-10 and #12-19,
Example 2: Slowly drift (WMO 29032)
Salinity drift became large between profiles #8 and #11.
This float also took 3 moths "summer vacation",
and its influence to the sensor should appear the data between
profiles #6 and #7.
Its sensor, however, was hardly damaged at that time,
but about 2 months later.
The sensor drifting was very slowly, and continued for about 4
Fig. 3: T-S diagram of WMO 29032 observations.
The red, blue, and green circles represent the profiles
#1-8, #9-10, and #11-13, respectively
Development of correcting method
Detect of conductivity sensor drift
Argo floats observe temperature, conductivity,
and pressure of seawater, and then calculate
salinity and transmit its value to us via ARGOS system.
So it is considered that we can obtain better-corrected
Argo salinity data by correcting its conductivity values.
Conductivity observed by Argo floats is
calculated with the following equation:
C = C( S, T, P)
T: in situ temperature
P: in situ pressure
In this study, we use conductivity ratio R,
which is written with C as follows:
R = C( S, T, P) / C( 35, 15, 0 ).
Here after, it is written as
R = sal78( S, T, P). .......(1)
Firstly, we examine that sensor drift can be detected
in the conductivity data.
However, clear differences between the data before
and after of the "summer vacation"
cannot be detected in theta-R diagram of WMO 29033.
Fig. 4: Relation of potential temperature and conductivity
ratio for the data observed by WMO29033.
Red and blue circles represent the data before and after "summer
The conductivity ratio is also affected by pressure,
so we plotted the Argo data at the isobar surfaces.
At each isobar, the data are almost arrayed on
two lines of before and after "summer vacation",
and the two data groups are clearly discriminated.
However, the lines of the before/after "summer vacation"
in different isobars are not arrayed on one line,
therefore the difference of data drift can not be
detected in the whole view (see Fig. 5b).
Following to the relation of in situ temperature and
we introduced a new value "potential conductivity ratio",
theta = theta( S, T, P, Pref), ........(2)
R_theta = sal78( S, theta, Pref). .....(3)
theta: potential temperature
Pref: Reference pressure
In this study, we use simply Pref = 0 dbar.
After that, the conductivity sensor drift can be
clearly discriminated in the whole view (see Figs. 5c and 6).
Fig. 5: Relations of (a) potential temperature and salinity,
(b) potential temperature and conductivity ratio,
and (c) potential temperature and potential conductivity ratio
for WMO 29033 data on the isobar surfaces.
Circles and stars represent data before
and after "summer vacation", respectively.
Light-blue, blue, red, and green represent data observed
at 1200, 1300, 1400, and 1500 dbar, respectively.
Fig. 6: Same as Fig. 4 but for potential conductivity ratio.
Thus, Argo data in deep layers are directly
corrected by the local climatological data.
On the other hand, those in middle and
surface layers are extrapolated by the
relation in the deep layers.
- A linear local climatological relation of theta and
R_theta in the middle/deep layers is estimated by
the least squares method from the climatological
profile data set, HydroBase (Fig. 7a).
- "True" values of R_theta (R_theta_"true")
are calculated from its observed theta based on
the local climatological relation (Fig. 7a).
- A linear relation of the observed and "true"
values of R_theta, namely a correcting-equation,
is estimated by the least squares method (Fig. 7c).
R_theta_"true" = a * R_theta_obs + b........(4)
Note that value of a in the above equation is
restricted within 1 plus/minus 0.001 to
obtain a reasonable and stable correction.
- Finally, corrected R_theta is calculated
from the observed values by the equation (4).
Then, corrected salinity data are obtained.
Fig. 7: An example to correct Argo data (yellow)
based on the climatology (black). (a)
Estimation of a local climatological relation
of potential temperature and potential
conductivity ratio (the light-blue line),
(b) drift of potential conductivity ratio from
the local climatological relation, and (c)
estimation of a correcting-equation of
potential conductivity ratio of Argo data
(the light-blue line).
Corrected results and its comparison
with CTD observation by R/V Mirai
In order to confirm the sensor drift of WMO 29033,
a CTD cast was conducted at 27.502°N 148.086°E
by R/V Mirai on February 17, 2001.
This CTD station is apart six days in time and
75 km in space from 18th station of
WMO 29033 at 27.498°N 148.859°E on
February 11, 2001 (see Fig. 1).
By using this CTD data, we examine
a performance of the above correcting method,
in which the local climatology was historical
profile data in area 1214_ABh.
Correcting result 1
Corrected Argo data almost overlap with
R/V Mirai CTD data except for those in the
sea surface layer, where time and spatial
variations are very large.
Therefore, this correcting method seems
to work well.
Fig. 8: Corrected Argo data (red) based on
the climatology with WOCE-CTD data (black).
Orange and blue circles represent the raw
Argo data and CTD data observed by R/V Mirai,
Correcting result 2
As shown in Fig. 1, historical profile data
in the area 1214_ABh contains WOCE-CTD data set,
which has a huge number of highly quality data.
Thus, to examine dependence of the correcting method
performance on quality/quantity of the local climatology,
we conducted another Argo data correction
with the same way except for without WOCE-CTD data
for the local climatology.
Corrected results are relatively good although
the corrected data is slightly saline in
Fig. 9: Same as Fig. 8 but for climatology
without WOCE-CTD data.
Salinity differences from the CTD data by
R/V Mirai are shown in Fig. 10.
The raw Argo data shows about 0.029 plus/minus
0.011 psu higher salinity than the Mirai CTD data.
On the other hand, the corrected Argo data with
WOCE-CTD data set reduces its salinity difference
to 0.007 plus/minus 0.010 psu, that without
WOCE-CTD to 0.014 plus/minus 0.016 psu.
Fig. 10: Salinity difference from the CTD data
observed by R/V Mirai.
Red and blue
circles represent the corrected Argo data based
on climatology with and without WOCE-CTD data,
Light-blue circles represent the raw Argo data.
Considering to the differences in the time
and space between the observations of the
Argo float and the R/V Mirai CTD cast,
the correcting-method developed in this study
is sufficient to correct the Argo salinity data,
in which its conductivity sensor seems
to be drifted.
Also it is suggested that this method is
almost independent on the quality and quantity
of the climatological data set.
The method described in this study is a prototype;
therefore, we will continue to improve the method
to achieve the goal of the Argo program for data
accuracy in salinity, within 0.01 psu.
We wish to express thanks to Prof. G.C.
Johnson for his discussions.