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Journal ArticleDOI

Simulation of More Realistic Upper-Ocean Processes from an OGCM with a New Ocean Mixed Layer Model

Yign Noh, Chan Joo Jang1, Toshio Yamagata1, Peter C. Chu1, Cheol-Ho Kim1 
01 May 2002-Journal of Physical Oceanography (American Meteorological Society)-Vol. 32, Iss: 5, pp 1284-1307

AbstractA new ocean mixed layer model (OMLM) was embedded into an ocean general circulation model (OGCM) with the aim of providing an OGCM that is ideal for application to a climate model by predicting the sea surface temperature (SST) more accurately. The results from the new OMLM showed a significant improvement in the prediction of SST compared to the cases of constant vertical mixing and the vertical mixing scheme by Pacanowski and Philander. More accurate prediction of the SST from the new OMLM reduces the magnitude of the restoring term in the surface heat flux and thus provides a simulated ocean that can be coupled to the atmospheric general circulation model more naturally. The new OMLM was also shown to improve various other features of the OGCM such as the mixed layer depth and the equatorial circulation.

Topics: Ocean general circulation model (61%), Mixed layer (56%), Sea surface temperature (55%), Ocean current (53%), Climate model (51%)

Summary (2 min read)

1. Introduction

  • Another problem regarding the restoring boundary condition employed in OGCMs involves the magnitude of the restoring timescale t.
  • Therefore, in this paper the authors attempted to reproduce more realistic upper ocean processes such as SST and MLD over the global ocean by including a new OMLM in an OGCM and to realize more realistic surface heat flux in the OGCM.

2. Model and experiment

  • This study employed the Pacanowski et al. (1991) version of the Bryan–Cox–Semtner OGCM.
  • The model was integrated for 24 years, which is believed to be sufficient for examining the changes in the heat flux and temperature in the upper ocean (Sterl and Kattenberg 1994).
  • The model is a second-order turbulence closure model using eddy diffusivity, but it produces a well-mixed layer even under the stabilizing heat flux, consistent with the observation and the bulk-type OMLMs (i.e., Kraus and Turner 1977), whereas most other OMLMs using eddy diffusivity lead to strong stratification and shear near the surface (i.e., Mellor and Yamada 1982).
  • See Noh and Kim (1999) for more detailed description of the model.
  • There are various sources of mixing below the mixed layer: for example, internal wave breaking, vertical shear, and double diffusion.

3. Results

  • A. Comparison between the restoring and combined surface thermal forcing (EXPs A0 and A1) Figure 1 shows the annual mean volume transport streamfunction obtained from EXPs A0 and A1, respectively.
  • Also, it is observed that the depth to which equatorial upwelling occurs becomes shallower in EXP C1 than in EXP A1.
  • The results from EXP A1 do not have a well-mixed upper layer and show a too diffused thermocline.
  • The authors have demonstrated throughout the previous section that more realistic features of the upper ocean, such as SST, MLD, and the equatorial circulation, could be reproduced by including the new OMLM.
  • Accordingly, the seasonal cycle of the hemispheric mean SST in EXP C2 (Fig. 20) does not deviate much further compared to the case of EXP C1, although the rms difference of the simulated SST from the observed SST becomes much larger (not shown).

4. Conclusions and discussion

  • When the heat flux is given by the form of the climatological heat flux plus a restoring term toward the climatological SST, more accurate prediction of SST helps to reduce the magnitude of the restoring term, and thus relieve various problems associated with the restoring boundary condition in the OGCM.
  • Finally, it is shown that the new OMLM still maintains an improved level in the resultant surface heat flux and seasonal cycle of the hemispheric mean SST under a longer restoring timescale of 60 days.
  • It will be interesting to investigate how the vertical mixing scheme affects the deep ocean using simulation results from a much longer period of integration.
  • Further improvement may be required in both the model and the forcing data for more accurate prediction.
  • First, the authors express their gratitude to Prof. J. W. Kim of Yonsei University, who inspired and supported us in the development of their OGCM with strong conviction.

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1284 V
OLUME
32JOURNAL OF PHYSICAL OCEANOGRAPHY
q 2002 American Meteorological Society
Simulation of More Realistic Upper-Ocean Processes from an OGCM with a New
Ocean Mixed Layer Model
Y
IGN
N
OH AND
C
HAN
J
OO
J
ANG
*
Department of Atmospheric Sciences, Yonsei University, Seoul, Korea
T
OSHIO
Y
AMAGATA
Department of Earth and Planetary Physics, University of Tokyo, Tokyo, Japan
P
ETER
C. C
HU
Department of Oceanography, Naval Postgraduate School, Monterey, California
C
HEOL
-H
O
K
IM
Korean Oceanographic Research and Development Institute, Ansan, Korea
(Manuscript received 10 July 2000, in final form 25 July 2001)
ABSTRACT
A new ocean mixed layer model (OMLM) was embedded into an ocean general circulation model (OGCM)
with the aim of providing an OGCM that is ideal for application to a climate model by predicting the sea surface
temperature (SST) more accurately. The results from the new OMLM showed a significant improvement in the
prediction of SST compared to the cases of constant vertical mixing and the vertical mixing scheme by Pacanowski
and Philander. More accurate prediction of the SST from the new OMLM reduces the magnitude of the restoring
term in the surface heat flux and thus provides a simulated ocean that can be coupled to the atmospheric general
circulation model more naturally. The new OMLM was also shown to improve various other features of the
OGCM such as the mixed layer depth and the equatorial circulation.
1. Introduction
Extensive efforts have been devoted to the advance
of the ocean general circulation model (OGCM) during
last few decades, with the intention of simulating the
present climate and predicting the future climate. For
the purpose of climate prediction, the OGCM must be
coupled to an atmospheric general circulation model
(AGCM), along with the properly represented air–sea
interaction. This particularly requires accurate predic-
tion of the sea surface temperature (SST) from the
OGCM. Hence, we should regard the accurate predic-
tion of SST as the most important prerequisite of the
OGCM for its application to climate prediction.
From the early stage of OGCMs the surface boundary
condition of temperature in OGCMs has been given
*Current affiliation: Korean Oceanographic Research and Devel-
opment Institute, Ansan, Korea.
Corresponding author address: Prof. Yign Noh, Department of
Atmospheric Sciences, Yonsei University, Seoul 120-749, Korea.
E-mail: noh@atmos.yonsei.ac.kr
predominantly by the restoring boundary condition in
which the simulated SST is restored toward the cli-
matological SST. That is, the surface heat flux Q is
given by
Q 5
r
C Dz (T* 2 T )/
t
,
p 1 SS
(1)
or it is incorporated into the equation of temperature in
the first layer as
]T (T* 2 T )
SS
1 ···5 . (2)
]t
t
Here
t
is the restoring timescale, T
S
is the temperature
of the first model layer, is the observed SST,
r
isT*
S
the density, C
p
is the specific heat of seawater, and Dz
1
is the thickness of the first layer of the model.
The restoring boundary condition has been favored
in particular since it insures that the simulated SST will
not drift far from the climatological SST and, thus, helps
to reproduce an ocean that is close to the climatological
ocean, even in the presence of considerable defective-
ness of the model. Its widespread use is also attributed
to the fact that there were no available reliable clima-

M
AY
2002 1285NOH ET AL.
tological heat flux data and that the simulation solely
based on the prescribed heat flux suffers from drift from
the climatological values with time because of the ab-
sence of feedback (Cane 1994; Seager et al. 1995;
McWilliams 1996).
Nonetheless, the restoring boundary condition im-
poses various serious problems for realistic simulation
of the ocean using an OGCM. The most conspicuous
defect is that the accurate prediction of SST leads to
the unrealistic situation of no heat flux at the sea surface.
It also diminishes the amplitude of the annual cycle and
causes a phase lag compared to the climatological SST
(Haidvogel and Bryan 1992). Meanwhile, it leads to
weakened convective overturning and thus reduced ther-
mohaline circulation since it tries to maintain the cli-
matological SST (Mikolajewicz and Maier-Reimer
1994; Cai and Chu 1996; Toggweiler et al. 1989). Ac-
cordingly, it was pointed out that the so-called ther-
mohaline catastrophe may be related to inadequacy of
the restoring boundary condition (Cai and Godfrey
1995; Rahmstorf and Willebrand 1995). Moreover,
strong artificial damping to the climatological SST sup-
presses the variability at the sea surface, which must
originate naturally from the internal ocean dynamics,
and thus leads to the serious underestimation of sea
surface height variability and eddy kinetic energy in the
high-resolution OGCM compared to the satellite data
(Stammer et al. 1996; Ishikawa et al. 1997).
The restoring boundary condition of the OGCM is
particularly inappropriate in a climate model in which
heat flux is calculated directly from the AGCM instead
of by the restoring term. Relaxation of the restoring term
for the coupling to the AGCM leads to the generation
of spurious oscillatory behavior in the OGCM (Cai and
Chu 1996). It may be caused by the fact that the re-
storing boundary condition forces the simulated result
toward an unnatural condition dictated by the clima-
tological SST, thus making it inconsistent with the in-
ternal ocean dynamics controlled by the model.
Another problem regarding the restoring boundary
condition employed in OGCMs involves the magnitude
of the restoring timescale
t
. The restoring timescaleused
in present OGCMs is typically about 30 days (Semtner
and Chervin 1992; Stammer et al. 1996; Marotzke and
Willebrand 1991). However, analyses of the observed
data revealed that sensitivity of the surface heat flux to
variations of SST must be much weaker than presumed
in the above values, which implies that
t
must be much
longer (Seager et al. 1995; Barnier 1998; Chu et al.
1998). For example, Barnier (1998) and Frankigonoul
et al. (1998) suggested that the restoring timescale must
be at least twice as long.
Recently, improvement of the restoring boundary
condition has been attempted by combining the restoring
term with the climatological heat flux Q*. That is,
Q 5 Q* 1
r
C Dz (T* 2 T )/
t
.
p 1 SS
(3)
We will call the surface thermal forcing given in the
form of (3) the combined boundary condition hereafter
in the present paper. It has become increasingly widely
used as more reliable data for Q* has become available
(Ezer and Mellor 1992; Masumoto and Yamagata 1996;
Mikolajewicz and Maier-Reimer 1994; Sterl and Kat-
tenberg 1994; Barnier et al. 1995; Stammer et al. 1996;
Maltrud et al. 1998). They also suggested that the value
of
t
can be interpreted as
r
C Dz
p 1
t
52 (4)
(]Q/]T )
*
ST
S
(Masumoto and Yamagata 1996; Barnier et al. 1995;
Maltrud et al. 1998).
One obvious advantage of the combined boundary
condition over the restoring boundary condition is that,
if the model can predict SST accurately, the heat flux
in the model approaches the climatological heat flux.
As the restoring term becomes negligible, the model
SST becomes controlled by the ocean dynamics rather
than the restoring term (Barnier 1998). This will help
to remove most problems associated with the restoring
boundary condition mentioned above.
This implies, however, that the restoring term in (3)
should be sufficiently small compared to Q* for the
combined boundary condition to really yield improved
results of the OGCM. Nonetheless, it has not been ex-
amined whether the restoring term is sufficiently smaller
than Q* in the aforementioned applications of the com-
bined boundary condition. Of course, this cannot be
obtained simply by increasing
t
because the simulated
SST T
S
deviates farther from the climatological SST
as the restoring becomes weaker with increasing
t
.T*
S
The reduction of the restoring term ( 2 T
S
)/
t
canT*
S
be obtained only by predicting the SST accurately from
the model. The most important factor in the accurate
prediction of SST is the ocean mixed layer process,
which controls the vertical transfer of heat below the
sea surface. This suggests that the improved OGCM
with realistic surface heat flux and sufficiently small
restoring term cannot be obtained simply by switching
from the restoring boundary condition to the combined
boundary condition, but should be accompanied by the
improvement of the mixed layer process in the OGCM
as well.
Recently, Stammer et al. (1996), Maltrud et al.(1998),
and Jiang et al. (1999) compared the results of OGCMs
using the restoring and combined boundary conditions
and observed some improvements such as enhancement
of western boundary currents and the poleward heat
transport. However, it is not yet clear whether the com-
bined boundary condition can provide more realistic
upper-ocean conditions, such as in the predictions of
SST and surface heat flux, than the restoring boundary
condition. Moreover, they did not account for the effects
of mixed layer processes.
Various ocean mixed layer models (OMLM) have
been developed to predict SST and mixed layer depth

1286 V
OLUME
32JOURNAL OF PHYSICAL OCEANOGRAPHY
(MLD), usually for a horizontally homogeneous upper
ocean. Since Pacanowski and Philander’s (1981) simple
prescription. For vertical mixing affected by stratifica-
tion, several OMLMs have been embedded into the
OGCM, and their effects were tested. The embedded
OMLM is either the turbulence closure model (Mellor
and Yamada 1982; Large et al. 1994; Gaspar et al. 1990)
or the bulk model (Kraus and Turner 1967; Price et al.
1986). The former is usually applied to the z-or
s
-
coordinate models, and the latter to the isopycnal mod-
els. For example, Rosati and Miyakoda (1988) and Ezer
(2000) examined the Mellor–Yamada model in the
OGCM, Large et al. (1997) and Large and Gent (1999)
examined the K-profile parameterization (KPP) model
by Large et al. (1994), and Blanke and Delecluse (1993)
examined the model by Gaspar et al. (1990). On the
other hand, Sterl and Kattenberg (1994), Oberhuber
(1993), and Bleck et al. (1989) combined bulk-type
models, similar to Kraus and Turner (1967), into an
OGCM. Meanwhile, Chen et al. (1994) suggested an-
other bulk model that hybridizes the Kraus–Turner mod-
el and the model by Price et al. (1986).
Nevertheless, it has not been shown clearly that the
prediction of the global SST could be significantly im-
proved by including the OMLM. For example, the Mel-
lor–Yamada model was found to cause excessively high
SST under heating, and thus it could not provide much
improvement compared to the case without the OMLM
under monthly mean surface forcing (Rosati and Mi-
yakoda 1988). Large et al. (1997) reported a less than
5% decrease in the rms of the potential temperature
anomaly over the upper 903 m when the KPP model
was included, but they did not examine the effects of
the OMLM on spatial and temporal variations of the
SST anomaly. Meanwhile, in most other cases the ap-
plication was restricted to a regional ocean (Blanke and
Delecluse 1993; Sterl and Kattenberg 1994; Chen et al.
1994; Large and Gent 1999; Ezer 2000).
Therefore, in this paper we attempted to reproduce
more realistic upper ocean processes such as SST and
MLD over the global ocean by including a new OMLM
in an OGCM and to realize more realistic surface heat
flux in the OGCM. In this way we hope to provide an
OGCM that can be naturally coupled to an AGCM.
Investigation was made through three stages of ex-
periments. First, we examined an OGCM under both
restoring and combined boundary conditions for tem-
perature for the case of constant vertical mixing. Sec-
ond, we investigated OGCMs under the combined
boundary condition with different mixed layer process-
es: the constant vertical mixing, the widely used vertical
mixing scheme by Pacanowski and Philander (1981),
and a new OMLM. Here a new OMLM was developed
for the OGCM based on the model by Noh and Kim
(1999). Finally we repeated the experiments with longer
restoring timescale for the case of the OGCM with the
new OMLM. The results were analyzed from the per-
spective of the improvement of the upper-oceanprocess.
2. Model and experiment
a. OGCM
This study employed the Pacanowski et al. (1991) ver-
sion of the Bryan–Cox–Semtner OGCM. The model do-
main covered the global ocean up to 808 latitude in both
hemispheres. The horizontal grid spacing was 18 in both
latitude and longitude. The vertical grids were made of 21
levels whose thickness increased with depth from 20 m
at the surface to 1000 m at the bottom. To avoid instability
at high latitudes a simple symmetric finite impulse filter
was applied in both hemispheres beyond 558. Realistic
bottom topography was used as much as possible within
the limits of grid resolution, including nine islands and a
rather realistic Indonesian archipelago.
Horizontal eddy viscosity A
M
and diffusivity A
H
were
1 3 10
8
cm
2
s
21
and 1 3 10
7
cm
2
s
21
, respectively.
Fluxes of heat and salinity were fixed to zero at the
bottom and at the side wall. Bottom friction was given
by C
D
| u | u with C
D
5 0.0025, and a no-slip boundary
condition was applied at the sidewall.
Vertical eddy viscosity K
M
and diffusivity K
H
were
given by 1 and 0.2 cm
2
s
21
, respectively, in the case of
constant vertical mixing. Convection is implemented by
applying very large eddy diffusivity (K
H
5 10
5
cm
2
s
21
), whenever unstable.
In the case with the Pacanowski and Philander scheme
(1981) K
M
and K
H
were given by
K
0
K 51K , (5)
MM0
2
(1 1 aRi)
K
M
K 51K , (6)
HH0
1 1 aRi
where the empirical constants were given by a 5 5, K
0
5 50 cm
2
s
21
, K
M0
5 0.0134 cm
2
s
21
, and K
H0
5 0.001
34 cm
2
s
21
. Here Ri is the Richardson number
2
N
Ri 5 , (7)
22
(]u/]z) 1 (]
y
/]z)
where N is the Brunt–Va¨isa¨la¨ frequency.
The model was started from a state of rest, with an-
nual mean temperature and salinity distributions by Lev-
itus (1982), and forced by Hellerman and Rosenstein
(1983) wind stress climatology. To prescribe the heat
flux at the surface the reanalysis data from the National
Centers for Environmental Prediction (NCEP) were
used. Meanwhile, optimally interpolated SST (OISST)
(Reynolds and Smith 1994) data were used for SST
instead of Levitus data for more accurate prescription
of the surface boundary condition. For the surface forc-
ing the monthly mean data were used with a linear in-
terpolation at each time step. Heat flux, given by Q in
(3), was set to zero when the SST is below 228C, as-
suming that the sea surface is covered by ice. Surface
salinity was restored to the climatological value of Lev-
itus (1982) with a restoring timescale of 30 days

M
AY
2002 1287NOH ET AL.
F
IG
. 1. Annual mean volume transport streamfunction (Sv): (a) EXP A0 and (b) EXP A1.
throughout all experiments. The model was integrated
for 24 years, which is believed to be sufficient for ex-
amining the changes in the heat flux and temperature
in the upper ocean (Sterl and Kattenberg 1994).
b. OMLM
Recent measurements of the microstructure of the oce-
anic boundary layer from various field experiments have
revealed that dynamic processes of the oceanic boundary
layer is fundamentally different from that of the atmo-
spheric boundary layer (see, e.g., Drennan et al. 1996;
Terray et al. 1996). Particularly they observed that tur-
bulent kinetic energy (TKE) is enhanced remarkably near
the sea surface, unlike near the rigid boundary of the
atmospheric boundary layer. A high level of TKE near the
sea surface helps to maintain the well-mixed layer in the
upper ocean. This also makes downward flux of TKE
important in the TKE budget of the upper mixed layer,
while rendering TKE production by the mean velocity
shear relatively unimportant (Noh 1996).
Noh and Kim (1999) recently developed a new OMLM,
taking these observational evidences into consideration.
The model is a second-order turbulence closure model
using eddy diffusivity, but it produces a well-mixed layer
even under the stabilizing heat flux, consistent with the
observation and the bulk-type OMLMs (i.e., Kraus and
Turner 1977), whereas most other OMLMs using eddy
diffusivity lead to strong stratification and shear near the
surface (i.e., Mellor and Yamada 1982).
The model calculates the vertical eddy viscosity K
M
,
the eddy diffusivity of temperature and salinity K
H
, and
the eddy diffusivity of turbulent kinetic energy K
E
by
K 5 Sql, (8)
MM
K 5 Sql, (9)
HH
K 5 Sql, (10)
EE

1288 V
OLUME
32JOURNAL OF PHYSICAL OCEANOGRAPHY
F
IG
. 2. Distributions of the SST anomaly (8C) for EXP A0: (a) annual mean, (b) Jan, and (c)
Jul. Contour interval is 18C, and solid and dashed lines represent positive and negative anomalies,
respectively. Areas with an SST anomaly larger than 18C are shaded.

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6,142 citations


Journal ArticleDOI
Abstract: If model parameterizations of unresolved physics, such as the variety of upper ocean mixing processes, are to hold over the large range of time and space scales of importance to climate, they must be strongly physically based. Observations, theories, and models of oceanic vertical mixing are surveyed. Two distinct regimes are identified: ocean mixing in the boundary layer near the surface under a variety of surface forcing conditions (stabilizing, destabilizing, and wind driven), and mixing in the ocean interior due to internal waves, shear instability, and double diffusion (arising from the different molecular diffusion rates of heat and salt). Mixing schemes commonly applied to the upper ocean are shown not to contain some potentially important boundary layer physics. Therefore a new parameterization of oceanic boundary layer mixing is developed to accommodate some of this physics. It includes a scheme for determining the boundary layer depth h, where the turbulent contribution to the vertical shear of a bulk Richardson number is parameterized. Expressions for diffusivity and nonlocal transport throughout the boundary layer are given. The diffusivity is formulated to agree with similarity theory of turbulence in the surface layer and is subject to the conditions that both it and its vertical gradient match the interior values at h. This nonlocal “K profile parameterization” (KPP) is then verified and compared to alternatives, including its atmospheric counterparts. Its most important feature is shown to be the capability of the boundary layer to penetrate well into a stable thermocline in both convective and wind-driven situations. The diffusivities of the aforementioned three interior mixing processes are modeled as constants, functions of a gradient Richardson number (a measure of the relative importance of stratification to destabilizing shear), and functions of the double-diffusion density ratio, Rρ. Oceanic simulations of convective penetration, wind deepening, and diurnal cycling are used to determine appropriate values for various model parameters as weak functions of vertical resolution. Annual cycle simulations at ocean weather station Papa for 1961 and 1969–1974 are used to test the complete suite of parameterizations. Model and observed temperatures at all depths are shown to agree very well into September, after which systematic advective cooling in the ocean produces expected differences. It is argued that this cooling and a steady salt advection into the model are needed to balance the net annual surface heating and freshwater input. With these advections, good multiyear simulations of temperature and salinity can be achieved. These results and KPP simulations of the diurnal cycle at the Long-Term Upper Ocean Study (LOTUS) site are compared with the results of other models. It is demonstrated that the KPP model exchanges properties between the mixed layer and thermocline in a manner consistent with observations, and at least as well or better than alternatives.

3,442 citations


01 Jan 1982
Abstract: A project to objectively analyze historical ocean temperature, salinity, oxygen, and percent oxygen saturation data for the world ocean has recently been completed at the National Oceanic and Atmospheric Administration's (NOAA) Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey. The results of the project are being made available through distribution of the Climatological Atlas of the World Ocean (NOAA Professional Paper No. 13), and through distribution of magnetic tapes containing the objective analyses. The sources of data used in the project were the Station Data, Mechanical Bathythermograph, and Expendable Bathythermograph files of the National Oceanographic Data Center (NODC) in Washington, D.C., updated through 1977–1978. The raw data were subjected to quality control procedures, averaged by one-degree squares, and then used as input to an objective analysis procedure that fills in one-degree squares containing no data and smooths the results. Due to the lack of synoptic observations for the world ocean, the historical data are composited by annual, seasonal, and (for temperature) monthly periods.

3,029 citations


Book
01 Jun 1982
Abstract: A project to objectively analyze historical ocean temperature, salinity, oxygen, and percent oxygen saturation data for the world ocean has recently been completed at the National Oceanic and Atmospheric Administration's (NOAA) Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey. The results of the project are being made available through distribution of the Climatological Atlas of the World Ocean (NOAA Professional Paper No. 13), and through distribution of magnetic tapes containing the objective analyses. The sources of data used in the project were the Station Data, Mechanical Bathythermograph, and Expendable Bathythermograph files of the National Oceanographic Data Center (NODC) in Washington, D.C., updated through 1977–1978. The raw data were subjected to quality control procedures, averaged by one-degree squares, and then used as input to an objective analysis procedure that fills in one-degree squares containing no data and smooths the results. Due to the lack of synoptic observations for the world ocean, the historical data are composited by annual, seasonal, and (for temperature) monthly periods.

2,892 citations


Journal ArticleDOI
Abstract: The new NOAA operational global sea surface temperature (SST) analysis is described. The analyses use 7 days of in situ (ship and buoy) and satellite SST. These analyses are produced weekly and daily using optimum interpolation (OI) on a 1° grid. The OI technique requires the specification of data and analysis error statistics. These statistics are derived and show that the SST rms data errors from ships are almost twice as large as the data errors from buoys or satellites. In addition, the average e-folding spatial error scales have been found to be 850 km in the zonal direction and 615 km in the meridional direction. The analysis also includes a preliminary step that corrects any satellite biases relative to the in situ data using Poisson's equation. The importance of this correction is demonstrated using recent data following the 1991 eruptions of Mt. Pinatubo. The OI analysis has been computed using the in situ and bias-corrected satellite data for the period 1985 to present.

2,692 citations


"Simulation of More Realistic Upper-..." refers methods in this paper

  • ...Meanwhile, optimally interpolated SST (OISST) (Reynolds and Smith 1994) data were used for SST instead of Levitus data for more accurate prescription of the surface boundary condition....

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  • ...OISST represents Optimally Interpolated SST data (Reynolds and Smith 1994)....

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Frequently Asked Questions (1)
Q1. What are the contributions mentioned in the paper "Simulation of more realistic upper-ocean processes from an ogcm with a new ocean mixed layer model" ?

A new ocean mixed layer model ( OMLM ) was embedded into an ocean general circulation model ( OGCM ) with the aim of providing an OGCM that is ideal for application to a climate model by predicting the sea surface temperature ( SST ) more accurately. More accurate prediction of the SST from the new OMLM reduces the magnitude of the restoring term in the surface heat flux and thus provides a simulated ocean that can be coupled to the atmospheric general circulation model more naturally.