共查询到20条相似文献，搜索用时 31 毫秒
1.
A three-dimensional variational ocean data assimilation system:Scheme and preliminary results 总被引：17，自引：0，他引：17
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℃ and 0.34 psu. 相似文献
2.
Toward a global ocean data assimilation system based on ensemble optimum interpolation: altimetry data assimilation experiment 总被引：3，自引：0，他引：3
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 0.1 psu 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. 相似文献
3.
Argo data assimilation in ocean general circulation model of Northwest Pacific Ocean 总被引：2，自引：0，他引：2
Xunqiang Yin Fangli Qiao Yongzeng Yang Changshui Xia Xianyao Chen 《Ocean Dynamics》2012,62(7):1059-1071
The Argo temperature and salinity profiles in 2005–2009 are assimilated into a coastal ocean general circulation model of the Northwest Pacific Ocean using the ensemble adjustment Kalman filter (EAKF). Three numerical tests, including the control run (CTL) (without data assimilation, which serves as the reference experiment), ensemble free run (EnFR) (without data assimilation), and EAKF experiment (with Argo data assimilation using EAKF), are carried out to examine the performance of this system. Using the restarts of different years as the initial conditions of the ensemble integrations, the ensemble spreads from EnFR and EAKF are all kept at a finite value after a sharp decreasing in the first few months because of the sensitive of the model to the initial conditions, and the reducing of the ensemble spread due to Argo data assimilation is not much. The ensemble samples obtained in this way can well represent the probabilities of the real ocean states, and no ensemble inflation is necessary for this EAKF experiment. Different experiment results are compared with satellite sea surface temperature (SST) data and the Global Temperature-Salinity Profile Program (GTSPP) data. The comparison of SST shows that modeled SST errors are reduced after data assimilation; the error reduction percentage after assimilating the Argo profiles is about 10?% on average. The comparison against the GTSPP profiles, which are independent of the Argo profiles, shows improvements in both temperature and salinity. The comparison results indicated a great error reduction in all vertical layers relative to CTL and the ensemble mean of EnFR; the maximum value for temperature and salinity reaches to 85?% and 80?%, respectively. The standard deviations of sea surface height are employed to examine the simulation ability, and it is shown that the mesoscale variability is improved after Argo data assimilation, especially in the Kuroshio extension area and along the section of 10°N. All these results suggest that this system is potentially useful for improving the simulation ability of oceanic numerical models. 相似文献
4.
We explore the ocean circulation estimates obtained by assimilating observational products made available by the Global Ocean
Data Assimilation Experiment (GODAE) and other sources in an incremental, four-dimensional variational data assimilation system
for the Intra-Americas Sea. Estimates of the analysis error (formally, the inverse Hessian matrix) are computed during the
assimilation procedure. Comparing the impact of differing sea surface height and sea surface temperature products on both
the final analysis error and difference between the model state estimates, we find that assimilating GODAE and non-GODAE products
yields differences between the model and observations that are comparable to the differences between the observation products
themselves. While the resulting analysis error estimates depend on the configuration of the assimilation system, the basic
spatial structures of the standard deviations of the ocean circulation estimates are fairly robust and reveal that the assimilation
procedure is capable of reducing the circulation uncertainty when only surface data are assimilated. 相似文献
5.
A series of numerical experiments for data assimilation with the Ensemble Kalman Filter (EnKF) in a shallow water model are
reported. Temperature profiles measured at a North Sea location, 55°30ˊ North and 0°55ˊ East (referred to as the CS station
of the NERC North Sea project), are assimilated in 1-D simulations. Comparison of simulations without assimilation to model
results obtained when assimilating data with the EnKF allows us to assess the filter performance in reproducing features of
the observations not accounted for by the model. The quality of the model error sampling is tested as well as the validity
of the Gaussian hypothesis underlying the analysis scheme of the EnKF. The influence of the model error parameters and the
frequency of the data assimilation are investigated and discussed. From these experiments, a set of optimal parameters for
the model error sampling are deduced and used to test the behavior of the EnKF when propagating surface information into the
water column. 相似文献
6.
Based on the Kalman filter theory, a new data-assimilation method has been used to improve the 3-D oceanic temperature field
of the Center for Ocean-Land-Atmosphere Studies (COLA) coupled general circulation model. This method is applied to assimilate
surface and subsurface temperature of in situ measurements from the Pilot Research Moored Array in the Tropical Atlantic project
(PIRATA). The assimilation of the PIRATA data produces an improved representation of the thermal state of the ocean and allows
a better estimation of other oceanographic quantities, like meridional heat fluxes and zonal currents. The present paper focuses
on the tropical Atlantic and, in particular, it contains new reconstructed temperature profiles. One-month forecast experiments
during 1999 were performed and the impact of the assimilation is discussed.
Received: 24 April 2001 / Accepted: 8 March 2002 相似文献
7.
An implementation of the Ensemble Kalman filter (EnKF) with a coupled ice–ocean model is presented. The model system consists of a dynamic–thermodynamic ice model using the elastic-viscous-plastic (EVP) rheology coupled with the HYbrid Coordinate Ocean Model (HYCOM). The observed variable is ice concentration from passive microwave sensor data (SSM/I). The assimilation of ice concentration has the desired effect of reducing the difference between observations and model. Comparison of the assimilation experiment with a free-run experiment shows that there are large differences, especially in summer. In winter the differences are relatively small, partly because the atmospheric forcing used to run the model depends upon SSM/I data. The assimilation has the strongest impact close to the ice edge, where it ensures a correct location of the ice edge throughout the simulation. An inspection of the model ensemble statistics reveals that the error estimates of the model are too small in winter, partly a result of too low model ice-concentration variance in the central ice pack. It is found that the ensemble covariance between ice concentration and sea-surface temperature in the same grid cell is of the same sign (negative) throughout the year. The ensemble covariance between ice concentration and salinity is more dependent upon the physical mechanisms involved, with ice transport and freeze/melt giving different signs of the covariances. The ice-transport and ice-melt mechanisms also impact the ice-concentration variance and the covariance between ice concentration and ice thickness. The ensemble statistics show a high degree of complexity, which to some extent merits the use of computationally expensive assimilation methods, such as the Ensemble Kalman filter. The present study focuses on the assimilation of ice concentration, but it is understood that assimilation of other datasets, such as sea-surface temperature, would be beneficial.Responsible Editor: Jin-Song von Storch 相似文献
8.
A complex and highly dynamical ocean region, the Agulhas Current System plays an important role in the transfer of energy, nutrients and organic material from the Indian to the Atlantic Ocean. Its dynamics are not only important locally, but affect the global ocean-atmosphere system. In working towards improved ocean reanalysis and forecasting capabilities, it is important that numerical models simulate mesoscale variability accurately—especially given the scarcity of coherent observational platforms in the region. Data assimilation makes use of scarce observations, a dynamical model and their respective error statistics to estimate a new, improved model state that minimises the distance to the observations whilst preserving dynamical consistency. Qualitatively, it is unclear whether this minimisation directly translates to an improved representation of mesoscale dynamics. In this study, the impact of assimilating along-track sea-level anomaly (SLA) data into a regional Hybrid Coordinate Ocean Model (HYCOM) is investigated with regard to the simulation of mesoscale eddy characteristics. We use an eddy-tracking algorithm and compare the derived eddy characteristics of an assimilated (ASSIM) and an unassimilated (FREE) simulation experiment in HYCOM with gridded satellite altimetry-derived SLA data. Using an eddy tracking algorithm, we are able to quantitatively evaluate whether assimilation updates the model state estimate such that simulated mesoscale eddy characteristics are improved. Additionally, the analysis revealed limitations in the dynamical model and the data assimilation scheme, as well as artefacts introduced from the eddy tracking scheme. With some exceptions, ASSIM yields improvements over FREE in eddy density distribution and dynamics. Notably, it was found that FREE significantly underestimates the number of eddies south of Madagascar compared to gridded altimetry, with only slight improvements introduced through assimilation, highlighting the models’ limitation in sustaining mesoscale activity in this region. Interestingly, it was found that the threshold for the maximum eddy propagation velocity in the eddy detection scheme is often exceeded when data assimilation relocates an eddy, causing the algorithm to interpret the discontinuity as eddy genesis, which directly influences the eddy count, lifetime and propagation velocity, and indirectly influences other metrics such as non-linearity. Finally, the analysis allowed us to separate eddy kinetic energy into contributions from detected mesoscale eddies and meandering currents, revealing that the assimilation of SLA has a greater impact on mesoscale eddies than on meandering currents. 相似文献
9.
Estimation of ocean circulation is investigated via assimilation of satellite measurements of the dynamic ocean topography (DOT) into the global finite-element ocean model (FEOM). The DOT was obtained by means of a geodetic approach from carefully cross-calibrated multi-mission altimeter data and GRACE gravity fields. The spectral consistency was achieved by consistently filtering both, the sea surface and the geoid. The filter length is determined by the spatial resolution of the gravity field and corresponds to approximately 241 km half width for the GRACE-based gravity field model ITG-Grace03s.The assimilation of the geodetic DOT was performed by employing a local singular evolutive interpolated Kalman (SEIK) filter in combination with the method of weighting of observations. It is shown that this approach leads to a successful assimilation technique that reduced the RMS difference between the model and the data from 16 cm to 5 cm during one year of assimilation. The ocean model returns an optimized mean dynamic ocean topography. The effects of assimilation on transport estimates across several hydrographic World Ocean Circulation Experiment (WOCE) sections show improvements compared to the FEOM run without data assimilation. As a result of the assimilation, DOT estimates are available in the polar or coastal regions where the geodetic estimates from satellite data alone are not adequate. Furthermore, more realistic features of the ocean can be seen in these areas compared to those obtained using the filtered data fields. 相似文献
10.
本文介绍了国家气候中心发展的一个全球海洋碳循环环流模式,并分析评估了该模式的基本性能.该模式是在美国地球物理流体动力学实验室(GFDL,Geophysical Fluid Dynamics Laboratory)的全球海洋环流模式MOM4(Modular Ocean Model Version 4)基础上发展的一个垂直方向40层、包含生物地球化学过程的全球三维海洋碳循环环流模式,简称为MOM4_L40(Modular Ocean Model Version 4 With 40Levels).该模式在气候场强迫下长期积分1000年,结果分析表明,与观测相比,模式较好地模拟了海洋温度、盐度、总二氧化碳、总碱、总磷酸盐的表面和垂直分布特征.模拟的海洋总二氧化碳分布与观测基本相符,表层为低值区,其下为高值区,高值区域位于10°S—60°N之间,但2000m以上模拟值较观测偏小,2000m以下模拟值较观测偏大.总体来说,MOM4_L40模式是一个可信赖的海洋碳循环过程模拟研究工具. 相似文献
11.
Rama Rao Karri Abhijit Badwe Xuan Wang Ghada El Serafy Julius Sumihar Vladan Babovic Herman Gerritsen 《Ocean Dynamics》2013,63(1):43-61
Hydrodynamic models are commonly used for predicting water levels and currents in the deep ocean, ocean margins and shelf seas. Their accuracy is typically limited by factors, such as the complexity of the coastal geometry and bathymetry, plus the uncertainty in the flow forcing (deep ocean tide, winds and pressure). In Southeast Asian waters with its strongly hydrodynamic characteristics, the lack of detailed marine observations (bathymetry and tides) for model validation is an additional factor limiting flow representation. This paper deals with the application of ensemble Kalman filter (EnKF)-based data assimilation with the purpose of improving the deterministic model forecast. The efficacy of the EnKF is analysed via a twin experiment conducted with the 2D barotropic Singapore regional model. The results show that the applied data assimilation can improve the forecasts significantly in this complex flow regime. 相似文献
12.
Benchmarking the mesoscale variability in global ocean eddy-permitting numerical systems 总被引：1，自引：1，他引：0
Andrea Cipollone Simona Masina Andrea Storto Doroteaciro Iovino 《Ocean Dynamics》2017,67(10):1313-1333
The role of data assimilation procedures on representing ocean mesoscale variability is assessed by applying eddy statistics to a state-of-the-art global ocean reanalysis (C-GLORS), a free global ocean simulation (performed with the NEMO system) and an observation-based dataset (ARMOR3D) used as an independent benchmark. Numerical results are computed on a 1/4 ° horizontal grid (ORCA025) and share the same resolution with ARMOR3D dataset. This “eddy-permitting” resolution is sufficient to allow ocean eddies to form. Further to assessing the eddy statistics from three different datasets, a global three-dimensional eddy detection system is implemented in order to bypass the need of regional-dependent definition of thresholds, typical of commonly adopted eddy detection algorithms. It thus provides full three-dimensional eddy statistics segmenting vertical profiles from local rotational velocities. This criterion is crucial for discerning real eddies from transient surface noise that inevitably affects any two-dimensional algorithm. Data assimilation enhances and corrects mesoscale variability on a wide range of features that cannot be well reproduced otherwise. The free simulation fairly reproduces eddies emerging from western boundary currents and deep baroclinic instabilities, while underestimates shallower vortexes that populate the full basin. The ocean reanalysis recovers most of the missing turbulence, shown by satellite products , that is not generated by the model itself and consistently projects surface variability deep into the water column. The comparison with the statistically reconstructed vertical profiles from ARMOR3D show that ocean data assimilation is able to embed variability into the model dynamics, constraining eddies with in situ and altimetry observation and generating them consistently with local environment. 相似文献
13.
A new circulation model of the western North Pacific Ocean based on the parallelized version of the Princeton Ocean Model and incorporating the Local Ensemble Transform Kalman Filter (LETKF) data assimilation scheme has been developed. The new model assimilates satellite data and is tested for the period January 1 to April 3, 2012 initialized from a 24-year simulation to estimate the ocean state focusing in the South China Sea (SCS). Model results are compared against estimates based on the optimum interpolation (OI) assimilation scheme and are validated against independent Argo float and transport data to assess model skills. LETKF provides improved estimates of the western North Pacific Ocean state including transports through various straits in the SCS. In the Luzon Strait, the model confirms, for the first time, the three-layer transport structure previously deduced in the literature from sparse observations: westward in the upper and lower layers and eastward in the middle layer. This structure is shown to be robust, and the related dynamics are analyzed using the results of a long-term (18 years) unassimilated North Pacific Ocean model. Potential vorticity and mass conservations suggest a basin-wide cyclonic circulation in the upper layer of the SCS (z?>??570 m), an anticyclonic circulation in the middle layer (?570 m?≥?z?>??2,000 m), and, in the abyssal basin (<?2,000 m), the circulation is cyclonic in the north and anticyclonic in the south. The cyclone–anticyclone abyssal circulation is confirmed and explained using a deep-layer reduced-gravity model as being caused by overflow over the deep sill of the Luzon Strait, coupled with intense, localized upwelling west of the strait. 相似文献
14.
V. Yesubabu C. V. Srinivas K. B. R. R. Hariprasad R. Baskaran 《Pure and Applied Geophysics》2014,171(8):2023-2042
In this work, the impact of assimilation of conventional and satellite remote sensing observations (Oceansat-2 winds, MODIS temperature/humidity profiles) is studied on the simulation of two tropical cyclones in the Bay of Bengal region of the Indian Ocean using a three-dimensional variational data assimilation (3DVAR) technique. The Weather Research and Forecasting (WRF)-Advanced Research WRF (ARW) mesoscale model is used to simulate the severe cyclone JAL: 5–8 November 2010 and the very severe cyclone THANE: 27–30 December 2011 with a double nested domain configuration and with a horizontal resolution of 27 × 9 km. Five numerical experiments are conducted for each cyclone. In the control run (CTL) the National Centers for Environmental Prediction global forecast system analysis and forecasts available at 50 km resolution were used for the initial and boundary conditions. In the second (VARAWS), third (VARSCAT), fourth (VARMODIS) and fifth (VARALL) experiments, the conventional surface observations, Oceansat-2 ocean surface wind vectors, temperature and humidity profiles of MODIS, and all observations were respectively used for assimilation. Results indicate meager impact with surface observations, and relatively higher impact with scatterometer wind data in the case of the JAL cyclone, and with MODIS temperature and humidity profiles in the case of THANE for the simulation of intensity and track parameters. These relative impacts are related to the area coverage of scatterometer winds and MODIS profiles in the respective storms, and are confirmed by the overall better results obtained with assimilation of all observations in both the cases. The improvements in track prediction are mainly contributed by the assimilation of scatterometer wind vector data, which reduced errors in the initial position and size of the cyclone vortices. The errors are reduced by 25, 21, 38 % in vector track position, and by 57, 36, 39 % in intensity, at 24, 48, 72 h predictions, respectively, for the two cases using assimilation of all observations. Simulated rainfall estimates indicate that while the assimilation of scatterometer wind data improves the location of the rainfall, the assimilation of MODIS profiles produces a realistic pattern and amount of rainfall, close to the observational estimates. 相似文献
15.
Yasumasa Miyazawa Toru Miyama Sergey M. Varlamov Xinyu Guo Takuji Waseda 《Ocean Dynamics》2012,62(4):645-659
We investigated the feasibility of the ensemble Kalman filter (EnKF) to reproduce oceanic conditions south of Japan. We have
adopted the local ensemble transformation Kalman filter algorithm based on 20 members’ ensemble simulations of the parallelized
Princeton Ocean Model (the Stony Brook Parallel Ocean Model) with horizontal resolution of 1/36°. By assimilating satellite
sea surface height anomaly, satellite sea surface temperature, and in situ temperature and salinity profiles, we reproduced
the Kuroshio variation south of Japan for the period from 8 to 28 February 2010. EnKF successfully reproduced the Kuroshio
path positions and the water mass property of the Kuroshio waters as observed. It also detected the variation of the steep
thermohaline front in the Kii Channel due to the intrusion of the Kuroshio water based on the observation, suggesting efficiency
of EnKF for detection of open and coastal seas interactions with highly complicated spatiotemporal variability. 相似文献
16.
The value of coupled assimilation is discussed using an intermediate coupled model in which the wind stress is the only atmospheric state which is slavery to model sea surface temperature (SST). In the coupled assimilation analysis, based on the coupled wind–ocean state covariance calculated from the coupled state ensemble, the ocean state is adjusted by assimilating wind data using the ensemble Kalman filter. As revealed by a series of assimilation experiments using simulated observations, the coupled assimilation of wind observations yields better results than the assimilation of SST observations. Specifically, the coupled assimilation of wind observations can help to improve the accuracy of the surface and subsurface currents because the correlation between the wind and ocean currents is stronger than that between SST and ocean currents in the equatorial Pacific. Thus, the coupled assimilation of wind data can decrease the initial condition errors in the surface/subsurface currents that can significantly contribute to SST forecast errors. The value of the coupled assimilation of wind observations is further demonstrated by comparing the prediction skills of three 12-year (1997–2008) hindcast experiments initialized by the ocean-only assimilation scheme that assimilates SST observations, the coupled assimilation scheme that assimilates wind observations, and a nudging scheme that nudges the observed wind stress data, respectively. The prediction skills of two assimilation schemes are significantly better than those of the nudging scheme. The prediction skills of assimilating wind observations are better than assimilating SST observations. Assimilating wind observations for the 2007/2008 La Niña event triggers better predictions, while assimilating SST observations fails to provide an early warning for that event. 相似文献
17.
The local ensemble transform Kalman filter (LETKF) is implemented with the Weather Research and Forecasting (WRF) model, and
real observations are assimilated to assess the newly-developed WRF-LETKF system. The WRF model is a widely-used mesoscale
numerical weather prediction model, and the LETKF is an ensemble Kalman filter (EnKF) algorithm particularly efficient in
parallel computer architecture. This study aims to provide the basis of future research on mesoscale data assimilation using
the WRF-LETKF system, an additional testbed to the existing EnKF systems with the WRF model used in the previous studies.
The particular LETKF system adopted in this study is based on the system initially developed in 2004 and has been continuously
improved through theoretical studies and wide applications to many kinds of dynamical models including realistic geophysical
models. Most recent and important improvements include an adaptive covariance inflation scheme which considers the spatial
and temporal inhomogeneity of inflation parameters. Experiments show that the LETKF successfully assimilates real observations
and that adaptive inflation is advantageous. Additional experiments with various ensemble sizes show that using more ensemble
members improves the analyses consistently. 相似文献
18.
Validation and application of an ensemble Kalman filter in the Selat Pauh of Singapore 总被引：1，自引：1，他引：0
The effectiveness of an ensemble Kalman filter (EnKF) is assessed in the Selat Pauh of Singapore using observing system simulation
experiment. Perfect model experiments are first considered. The perfect model experiments examine the EnKF in reducing the
initial perturbations with no further errors than those in the initial conditions. Current velocity at 15 observational sites
from the true ocean is assimilated every hour into the false ocean. While EnKF reduces the initial velocity error during the
first few hours, it fails after one tidal cycle (approximately 12 h) due to the rapid convergence of the ensemble members.
Successively, errors are introduced in the surface wind forcing. A random perturbation ε is applied independently to each ensemble member to maintain the ensemble spread. The assimilation results showed that the
success of EnKF depends critically on the presence of ε, yet it is not sensitive to the magnitude of ε, at least in the range of weak to moderate perturbations. Although all experiments were made with EnKF only, the results
could be applicable in general to all other ensemble-based data assimilation methods. 相似文献
19.
Ocean Dynamics - Roles of atmospheric variabilities in the formation of Indian Ocean Dipole (IOD) were investigated using an ocean general circulation model and different atmospheric forcing... 相似文献
20.
Problems of the variational data assimilation for the primitive equation ocean model constructed at the Institute of Numerical
Mathematics, Russian Academy of Sciences are considered. The model has a flexible computational structure and consists of
two parts: a forward prognostic model, and its adjoint analog. The numerical algorithm for the forward and adjoint models
is constructed based on the method of multicomponent splitting. The method includes splitting with respect to physical processes
and space coordinates. Numerical experiments are performed with the use of the Indian Ocean and the World Ocean as examples.
These numerical examples support the theoretical conclusions and demonstrate the rationality of the approach using an ocean
dynamics model with an observed data assimilation procedure. 相似文献