ABSTRACT: In many applications of 3DVAR, the balance constraints can be considered via two main approaches: weak constraint method which
adds penalty terms to the cost function; and proper definition of the background error covariance matrix with non-zero cross-correlation
sub-matrices. The weak constraint approach requires determining the weighting matrices of the penalty terms. The background
error covariance approach does not require determining those additional weighting matrices. However, it is only applicable
to those linear or linearized balance constraints. A novel approach is proposed based on the background error covariance approach
by generalizing the so-called Derber-Bouttier formulation. An assimilation experiment of estimating temperature and salinity
from the sea surface dynamic height observation is given to illustrate the proposed treatments of nonlinear balance constraints.
Science in China Series D Earth Sciences 05/2012; 49(3):331-336. · 1.59 Impact Factor
ABSTRACT: A global ocean data assimilation system based on the ensemble optimum interpolation (EnOI) has been under development as the
Chinese contribution to the Global Ocean Data Assimilation Experiment. The system uses a global ocean general circulation
model, which is eddy permitting, developed by the Institute of Atmospheric Physics of the Chinese Academy of Sciences. In
this paper, the implementation of the system is described in detail. We describe the sampling strategy to generate the stationary
ensembles for EnOI. In addition, technical methods are introduced to deal with the requirement of massive memory space to
hold the stationary ensembles of the global ocean. The system can assimilate observations such as satellite altimetry, sea
surface temperature (SST), in situ temperature and salinity from Argo, XBT, Tropical Atmosphere Ocean (TAO), and other sources
in a straightforward way. As a first step, an assimilation experiment from 1997 to 2001 is carried out by assimilating the
sea level anomaly (SLA) data from TOPEX/Poseidon. We evaluate the performance of the system by comparing the results with
various types of observations. We find that SLA assimilation shows very positive impact on the modeled fields. The SST and
sea surface height fields are clearly improved in terms of both the standard deviation and the root mean square difference.
In addition, the assimilation produces some improvements in regions where mesoscale processes cannot be resolved with the
horizontal resolution of this model. Comparisons with TAO profiles in the Pacific show that the temperature and salinity fields
have been improved to varying degrees in the upper ocean. The biases with respect to the independent TAO profiles are reduced
with a maximum magnitude of about 0.25°C and 0.1psu for the time-averaged temperature and salinity. The improvements on temperature
and salinity also lead to positive impact on the subsurface currents. The equatorial under current is enhanced in the Pacific
although it is still underestimated after the assimilation.
Ocean Dynamics 04/2012; 59(4):587-602. · 1.77 Impact Factor
ABSTRACT: The adjoint approach is a variational method which is often applied to data assimilation widely in meteorology and oceanography.
It is used for analyses on observing optimization for the wind-driven Sverdrup circulation. The adjoint system developed by
Thacker and Long (1992), which is based on the GFDL Byran-Cox model, includes three components, i. e. the forward model, the
adjoint model and the optimal algorithm. The GFDL Byran-Cox model was integrated for a long time driven by a batch of ideal
wind stresses whose meridional component is set to null and zonal component is a sine function of latitudes in a rectangle
box with six vertical levels and 2 by 2 degree horizontal resolution. The results are regarded as a “real” representative
of the wind-driven Sverdrup circulation, from which the four dimensional fields are allowed to be sampled in several ways,
such as sampling at the different levels or along the different vertical sections. To set the different samples, the fields
of temperature, salinity and velocities function as the observational limit in the adjoint system respectively where the same
initial condition is chosen for 4D VAR data assimilation. By examining the distance functions which measure the misfit between
the circulation field from the control experiment of the adjoint system with a complete observation and those from data assimilation
of adjoint approach in these sensitivity experiments respectively, observing optimizations for the wind-driven Sverdrup circulation
will be suggested under a fixed observational cost.
Science in China Series D Earth Sciences 04/2012; 43(3):243-252. · 1.59 Impact Factor
ABSTRACT: The computational cost required by the Ensemble Kalman Filter (EnKF) is much larger than that of some simpler assimilation
schemes, such as Optimal Interpolation (OI) or three-dimension variational assimilation (3DVAR). Ensemble optimal interpolation
(EnOI), a crudely simplified implementation of EnKF, is sometimes used as a substitute in some oceanic applications and requires
much less computational time than EnKF. In this paper, to compromise between computational cost and dynamic covariance, we
use the idea of “dressing” a small size dynamical ensemble with a larger number of static ensembles in order to form an approximate
dynamic covariance. The term “dressing” means that a dynamical ensemble seed from model runs is perturbed by adding the anomalies
of some static ensembles. This dressing EnKF (DrEnKF for short) scheme is tested in assimilation of real altimetry data in
the Pacific using the HYbrid Coordinate Ocean Model (HYCOM) over a four-year period. Ten dynamical ensemble seeds are each
dressed by 10 static ensemble members selected from a 100-member static ensemble. Results are compared to two EnKF assimilation
runs that use 10 and 100 dynamical ensemble members. Both temperature and salinity fields from the DrEnKF and the EnKF are
compared to observations from Argo floats and an OI SST dataset. The results show that the DrEnKF and the 100-member EnKF
yield similar root mean square errors (RMSE) at every model level. Error covariance matrices from the DrEnKF and the 100-member
EnKF are also compared and show good agreement.
Advances in Atmospheric Sciences 04/2012; 26(5):1042-1052. · 0.99 Impact Factor
ABSTRACT: This study aims at assessing the relative impacts of four major components of the tropical Pacific Ocean observing system
on assimilation of temperature and salinity fields. Observations were collected over a period between January 2001 through
June 2003 including temperature data from the expendable bathythermographs (XBT), thermistor data from the Tropical Ocean
Global Atmosphere Tropical Atmosphere-Ocean (TOGA-TAO) mooring array, sea level anomalies from the Topex/Poseidon and Jason-1
altimetry (T/P-J), and temperature and salinity profiles from the Array for Real-time Geostrophic Oceanography (ARGO) floats.
An efficient three-dimensional variational analysis-based method was introduced to assimilate the above data into the tropical-Pacific
circulation model. To evaluate the impact of the individual component of the observing system, four observation system experiments
were carried out. The experiment that assimilated all four components of the observing system was taken as the reference.
The other three experiments were implemented by withholding one of the four components. Results show that the spatial distribution
of the data influences its relative contribution. XBT observations produce the most distinguished effects on temperature analyses
in the off-equatorial region due to the large amount of measurements and high quality. Similarly, the impact of TAO is dominant
in the equatorial region due to the focus of the spatial distribution. The Topex/Poseidon-Jason-1 can be highly complementary
where the XBT and TAO observations are sparse. The contribution of XBT or TAO on the assimilated salinity is made by the model
dynamics because no salinity observations from them are assimilated. Therefore, T/P-J, as a main source for providing salinity
data, has been shown to have greater impacts than either XBT or TAO on the salinity analysis. Although ARGO includes the subsurface
observations, the relatively smaller number of observation makes it have the smallest contribution to the assimilation system.
Advances in Atmospheric Sciences 01/2007; 24(3):383-398. · 0.99 Impact Factor
ABSTRACT: A new 3DVAR-based Ocean Variational Analysis System (OVALS) is developed. OVALS is capable of assimilating in situ sea water
temperature and salinity observations and satellite altimetry data. As a component of OVALS, a new variational scheme is proposed
to assimilate the sea surface height data. This scheme considers both the vertical correlation of background errors and the
nonlinear temperature-salinity relationship which is derived from the generalization of the linear balance constraints to
the nonlinear in the 3DVAR. By this scheme, the model temperature and salinity fields are directly adjusted from the altimetry
data. Additionally, OVALS can assimilate the temperature and salinity profiles from the ARGO floats which have been implemented
in recent years and some temperature and salinity data such as from expendable bathythermograph, moored ocean buoys, etc.
A 21-year assimilation experiment is carried out by using OVALS and the Tropical Pacific circulation model. The results show
that the assimilation system may effectively improve the estimations of temperature and salinity by assimilating all kinds
of observations. Moreover, the root mean square errors of temperature and salinity in the upper depth less than 420 m reach
0.63°C and 0.34 psu.
Science in China Series D Earth Sciences 01/2006; 49(11):1212-1222. · 1.59 Impact Factor
ABSTRACT: Four existing sea surface temperature (SST) assimilation schemes are evaluated in terms of their performances in assimilating the advanced very high resolution radiometer pathfinder best SST data in the South China Sea using the Princeton Ocean Model. Schemes 1 and 2 project SST directly to subsurface according to model-based correlations between SST and subsurface temperature. The difference between these two schemes is related to the order of vertical projection and horizontal optimal interpolation (OI). In Scheme 1, the spatially non-uniform SST observations are first projected to subsurface levels, followed by horizontal OI at each level. While in Scheme 2, the remotely sensed SSTs are first optimally interpolated to all grid points at the surface, followed by projecting gridded SSTs to subsurface levels. Scheme 3 assumes that the mixed layer is well mixed and has a uniform temperature vertically. In Scheme 4, SST is propagated to subsurface levels using a linear relationship of temperature between any two neighboring depths (Scheme 4a) or between surface and subsurface (Scheme 4b), which is derived by empirical orthogonal function (EOF) technique. To verify the results of the four schemes, the authors use the hydrographic data from two cruises during the South China Sea Monsoon Experiment in April and June 1998. It was shown that all four schemes could improve the SST field by reducing about 50% of the root mean square errors (RMSEs). All but Scheme 3 can improve model thermocline structure that is too diffused otherwise, though the RMSEs increase in the thermocline, especially for Scheme 2 when the model has opposite bias between upper layers and lower layers. Scheme 3 fails in the subsurface depth by increasing the thermocline depth, especially when there is a cold model bias. Projecting SST downward by EOF technique can deepen the depth of assimilation especially in Scheme 4a. Both Schemes 4a and b can correct the bias in the mixed layer and do not change the vertical thermal structure.
Continental Shelf Research.
ABSTRACT: We analyze four-dimensional structures of upwelling and Pearl River plume in the northern South China Sea (NSCS) during the summer of 2008 based on data assimilation. An Ensemble Kalman Smoother scheme is employed in the Princeton Ocean Model. It is found that the Pearl River plume axis extended eastward along with the surface current and swerved offshore twice near (116°E, 22.6°N) and (117.5°E, 22.8°N) before reaching the Taiwan Strait. The vertical transect of salinity along the plume axis indicates that the Pearl River freshwater could affect salinity distribution down to a depth of 10–20 m. Anomalously warm water is found in the upper layer, which could be attributed to the intensified stratification and suppressed vertical mixing caused by the freshwater of the plume capping the upwelling west of 116°E. The varying winds from upwelling favorable to downwelling favorable could induce a low-salinity water lens at the center of the model domain. Upwelling in the NSCS initially occurred at 114.5°E, to the east of the Pearl River Estuary, intensified eastward, and reached its maximum near Shantou (116.7°E, 23.2°N). Since current-induced upwelling appeared mainly in Shantou due to the widened shelf, it is found that even if the wind-induced upwelling was shut down in Shanwei by downwelling favorable wind on July 4, the upwelling still existed in Shantou. Moreover, because the direction of large-scale current was in favor of upwelling in the NSCS that cannot be reversed by varying local winds over a short time period, the upwelling shutdown time is longer for both wind-induced and current-induced upwelling in Shantou than for mainly wind-induced upwelling in Shanwei. The steeper slope in Shanwei also shortens the upwelling shutdown time there.Research highlights► The upwelling and plume in the NSCS during summer 2008 are presented using EnKS assimilative model. ► For current-induced upwelling in Shantou and steeper slope in Shanwei, upwelling shutdown time is longer in Shantou. ► The varying winds from upwelling to downwelling favorable induced a low-salinity water lens. ► The depth of freshwater changed sharply at 116°E because of the horizontal shear of vorticity.
Ocean Modelling. 36:228-241.
ABSTRACT: Major forecast errors on the background error covariance from initial conditions, atmospheric forcing, model open boundary conditions, and the river discharges are examined in a coastal model of northern South China Sea. The analysis of background error covariance matrix produced by model ensemble shows that the perturbations of the initial conditions and atmospheric forcing play major roles in producing and maintaining the amplitude of ensemble spread except for the sea surface height (SSH) field. The perturbation of model open boundary conditions can influence ensemble spread of all variables and covariance between temperature and velocity or between temperature and SSH. The perturbation of river discharge mainly affects the covariance of salinity in river estuary. A data assimilation experiment of northern South China Sea is conducted using ensemble Kalman filter (EnKF) in the Princeton Ocean Model. In the experiment the ensemble model forecasts are made by perturbing the above mentioned four major model inputs. The assimilated data include sea-surface temperature (SST) and conductive–temperature–depth (CTD) observations. The assimilation experiment suggests that assimilating SST and CTD data can effectively improve the model simulation that has a shallower thermocline and weaker plume comparing to the observations. Moreover, consistent with these improvements of temperature and salinity, the along-shore velocity, cross-shore velocity, and characters of water mass are also corrected, respectively.Research Highlights► Major forecast errors on the background error covariance are examined in a coastal model. ► Assimilating SST and CTD data improved the simulation of thermocline and plume. ► Consistent with the improvements of T and S, the velocity and characters of water mass are also corrected.
Continental Shelf Research 31(6). · 2.09 Impact Factor