Assessment of the effectiveness of POLYMODE data assimilation by a numerical barotropic model for synoptic motions

This paper considers the results of numerical experiments involving POLYMODE data assimilation by a barotropic model for synoptic ocean dynamics. The model's response the data assimilation for various space-time discretenesses of assimilation is studied. Results derived from the application of optimal interpolation algorithms and modified optimal filtration algorithms are compared. Qualitative similarity to the calculations carried out through the simulation modelling technique is noted. Optimal assimilation algorithms are determined, depending on the space-time discreteness used. An optimal sampling discreteness for the POLYMODE conditions is suggested.Translated by Vladimir A. Puchkin.     

Spectral barotropic model for the prediction of synoptic currents in the open part of the ocean

We consider a quasigeostrophic spectral model used for the prediction of synoptic currents in the barotropic ocean. The spectral method is based on the expansion of the current function in a double series in cosines. An algorithm of numerical evaluation of the nonlinear term in the equation of potential eddy is described in detail. __________ Translated from Morskoi Gidrofizicheskii Zhurnal, No. 4, pp. 62–69, July–August, 2006.     

Optimization of the data assimilation algorithm in a model for synoptic dynamics of the velocity field

The results of numerical experiments involving data assimilation by a non-linear model for synoptic dynamics of the ocean are given. The results of application of simplified optimal filtration algorithms (with the correlation error function being parametrized for both linear and non-linear variants) and of the optimal interpolation are intercompared. The use of a non-linear equation to predict average values and a linear one to predict dispersion in the filtration algorithm is suggested as most appropriate for the cases, when anisotropy of the correlation function is to be included. In other cases, it is considered worth-while to apply optimal interpolation.Translated by V. Puchkin.     

Effectiveness of data assimilation using probabilistic techniques in a model for synoptic velocity field evolution

The results of numerical experiments involving data assimilation by linear and non-linear models for synoptic ocean dynamics are presented. This paper considers the model's response to data assimilation at diverse values of the relative error in the determination of the initial fields and space-time discreteness of data assimilation. The data obtained using the optimal filtering are compared with those provided by the optimal interpolation (OI). A qualitative difference in the response of the linear and non-linear models to data assimilation is noted. The limiting values of the time-space discreteness of observations assimilation are determined, which allow correct application of OI.Translated by Vladimir A. Puchkin.     

A singular evolutive extended Kalman filter to assimilate ocean color data in a coupled physical–biochemical model of the North Atlantic ocean

Within the European DIADEM project, a data assimilation system for coupled ocean circulation and marine ecosystem models has been implemented for the North Atlantic and the Nordic Seas. One objective of this project is to demonstrate the relevance of sophisticated methods to assimilate satellite data such as altimetry, surface temperature and ocean color, into realistic ocean models. In this paper, the singular evolutive extended Kalman (SEEK) filter, which is an advanced assimilation scheme where three-dimensional, multivariate error statistics are taken into account, is used to assimilate ocean color data into the biological component of the coupled system. The marine ecosystem model, derived from the FDM model [J. Mar. Res. 48 (1990) 591], includes 11 nitrogen and carbon compartments and describes the synthesis of organic matter in the euphotic zone, its consumption by animals of upper trophic levels, and the recycling of detritic material in the deep ocean. The circulation model coupled to the ecosystem is the Miami isopycnic coordinate ocean model (MICOM), which covers the Atlantic and the Arctic Oceans with an enhanced resolution in the North Atlantic basin. The model is forced with realistic ECMWF ocean/atmosphere fluxes, which permits to resolve the seasonal variability of the circulation and mixed layer properties. In the twin assimimation experiments reported here, the predictions of the coupled model are corrected every 10 days using pseudo-measurements of surface phytoplankton as a substitute to chlorophyll concentrations measured from space. The diagnostics of these experiments indicate that the assimilation is feasible with a reduced-order Kalman filter of small rank (of order 10) as long as a sufficiently good identification of the error structure is available. In addition, the control of non-observed quantities such as zooplankton and nitrate concentrations is made possible, owing to the multivariate nature of the analysis scheme. However, a too severe truncation of the error sub-space downgrades the propagation of surface information below the mixed layer. The reduction of the actual state vector to the surface layers is therefore investigated to improve the estimation process in the perspective of sea-viewing wide field-of-view sensor (SeaWiFS) data assimilation experiments.     

Evolution of errors in the altimetric bathymetry model used by Google Earth and GEBCO

We analyze errors in the global bathymetry models of Smith and Sandwell that combine satellite altimetry with acoustic soundings and shorelines to estimate depths. Versions of these models have been incorporated into Google Earth and the General Bathymetric Chart of the Oceans (GEBCO). We use Japan Agency for Marine-Earth Science and Technology (JAMSTEC) multibeam surveys not previously incorporated into the models as “ground truth” to compare against model versions 7.2 through 12.1, defining vertical differences as “errors.” Overall error statistics improve over time: 50th percentile errors declined from 57 to 55 to 49 m, and 90th percentile errors declined from 257 to 235 to 219 m, in versions 8.2, 11.1 and 12.1. This improvement is partly due to an increasing number of soundings incorporated into successive models, and partly to improvements in the satellite gravity model. Inspection of specific sites reveals that changes in the algorithms used to interpolate across survey gaps with altimetry have affected some errors. Versions 9.1 through 11.1 show a bias in the scaling from gravity in milliGals to topography in meters that affected the 15–160 km wavelength band. Regionally averaged (>160 km wavelength) depths have accumulated error over successive versions 9 through 11. These problems have been mitigated in version 12.1, which shows no systematic variation of errors with depth. Even so, version 12.1 is in some respects not as good as version 8.2, which employed a different algorithm.     

Numerical experiments with data assimilation in the simplest dynamic-stochastic model for the ocean's synoptic variability closed at the level of the second moments

The results of numerical experiments with data assimilation in a non-linear model of the synoptic dynamics of the world's oceans are reported. The model's response to the data assimilation is studied at different values of the relative error in determining the initial fields and assimilation discreteness. The results of application of the algorithms of optimum filtration and optimum interpolation are compared. The advantages of the filtration algorithm employed are discussed only for the case of small errors in determining the initial fields and low assimilation discreteness. The possibility of deterioration of the prediction estimates in data assimilation with discreteness less than the typical time of variability of the average fields is noted.Translated by Mikhail M. Trufanov.     

Coupling a two-way nested primitive equation model and a statistical SST predictor of the Ligurian Sea via data assimilation

A primitive equation model and a statistical predictor are coupled by data assimilation in order to combine the strength of both approaches. In this work, the system of two-way nested models centred in the Ligurian Sea and the satellite-based ocean forecasting (SOFT) system predicting the sea surface temperature (SST) are used. The data assimilation scheme is a simplified reduced order Kalman filter based on a constant error space. The assimilation of predicted SST improves the forecast of the hydrodynamic model compared to the forecast obtained by assimilating past SST observations used by the statistical predictor. This study shows that the SST of the SOFT predictor can be used to correct atmospheric heat fluxes. Traditionally this is done by relaxing the model SST towards the climatological SST. Therefore, the assimilation of SOFT SST and climatological SST are also compared.     

GRAPES模式在一次近海强风预报中的应用

利用GRAPES模式和广东自动站资料,从天气学的角度对比、分析研究了GRAPES模式预告在2010年12月15—17日广东出现强冷空气天气过程中上川岛附近海域强风的对应关系。结果表明,在此次近海强风的过程中,GRAPES模式的预报能力及其提前量,在实际冷空气海洋强风预报业务中值得参考,模式气压场的预报与实况没有明显的差异,强度基本一致,模式区域风向风速预报与实况较为吻合,模式单点预报能提前量为60 h报出风向风速的突变,并且时间误差在3 h左右,模式提前量达60 h以上。     

Availability of an equation to evaluate error by optical path discretization in radiative transfer computation based on the successive order of scattering method

The availability of an equation to evaluate the influence of multiple scattering in the single scattering process corresponding to a layer of arbitrary optical thickness was established. In order to confirm the validity of this equation, the radiance distribution in this layer was computed using a plane–parallel layer model based on the successive order of scattering method. The relative errors in a radiance distribution computed were evaluated as a function of optical thickness by the derived equation. It was shown that this equation provides a theoretical background for determining layer thickness using the plane–parallel layer model.     

Diagnosis of vertical velocities with the QG Omega equation: a relocation method to obtain pseudo-synoptic data sets

The quantification of vertical motion and vertical fluxes is essential in our ability to predict and tolerate climate change. However, diagnostic estimations might be affected by the errors arising from the necessary compromise between spatio-temporal resolution and cost of hydrographic surveys. Observations of a numerical ocean model have been made in order to test the accuracy of different sampling strategies and their possible a-posteriori corrections. A simple first-order correction method, computing a pseudo-synoptic data set from a non-synoptic data set and involving a geostrophic relocation of the stations is shown to correct significantly the synopticity error in hydrographic data, derived QG vertical motion and vertical temperature fluxes. Sensitivity analyses also show that the lack of synopticity is more critical than other factors, including the sampling resolution, the level of no-motion and the analysis.     

Reverse catenary equation of the embedded installation line and application to the kinematic model for drag anchors

The penetration behavior and trajectory of the drag anchor in seabed soils are not only determined by properties of the anchor and soil, but also controlled by the installation line especially the segment embedded in the soil. Correctly understanding and describing reverse catenary properties of the embedded line are crucial for improving the drag embedment performance, precisely predicting the anchor trajectory, and solving the positioning problem in offshore applications. The investigation on reverse catenary problems demonstrates that, the reverse catenary shape of the embedded line has to be solved almost through numerical incremental methods. In the present study, based on the mechanical model for the embedded line, the relationship between the tension and geometry of the embedded line, and the interactional equation between the anchor and embedded line are derived. By introducing the concept of the initial embedment depth of the installation line, the reverse catenary equation and the expression for calculating the length of the embedded line are obtained for soils with a linear strength, and the position of the embedment point can be reasonably solved through the derived reverse catenary equation. The reverse catenary equation is then introduced into the kinematic model for drag anchors, which combines the drag anchor, the installation line and the movement of the anchor handling vessel being an interactional system. More information related to the drag embedment problem can be definitely gained through the present work, including not only the anchor behaviors such as the trajectory, penetration direction and ultimate embedment depth, but also the properties of the installation line for both the embedded and horizontal segments. By comparing with drum centrifuge tests and model flume experiments, the efficiency of the theoretical method for predicting the anchor trajectory is well verified.     

Response of a coupled ocean-ice-atmosphere model to data assimilation in the tropical zone of the Pacific Ocean

This paper deals with numerical experiments based on the coupled ECHAM-HOPE model. The results of experiments are analyzed. The initial fields for the calculations over time periods from one month to one year are constructed based on the results of the data assimilation of temperature profiles from TOGA-TAO moorings. The perturbations of the initial fields and the propagation of these perturbations with specific computational time intervals are analyzed on the basis of the results of these experiments. It is shown that the strongest impacts of the perturbations are localized in specific regions of the World Ocean corresponding to the energetically active zones of the Earth. The mechanism of the transition of these perturbations is also studied. Different statistical properties of the ensemble of experiments are presented.     

A model for the prediction of in-line vortex-induced vibrations of cylindrical elements in a non-uniform steady flow

The method presently adopted in the offshore industry for predicting the amplitude of vibration of circular cylinders undergoing in-line vortex-induced excitation is demonstrated to be valid only for structures in uniform flows at sub-critical Reynolds numbers.A model which predicts the response of structural elements experiencing this phenomenon where the diameter, mass, and velocity of flow varies along the length of the structure is presented. Comparison between the results of this method and available experimental measurements is made.The model is structured to be an easily applied design tool producing an upper-bound estimate.     

Comparison of methods for argo drifters data assimilation into a hydrodynamical model of the ocean

Different data assimilation methods such as an extended Kalman filter, the optimal interpolation method, and a method based on the Fokker-Planck equation applications are considered. Data from the ARGO drifters are assimilated into the HYCOM shallow water model (University of Miami, USA). Throughout the study, the schemes and methods of parallel computations with an MPI library are used. The results of the computations with assimilations are compared between themselves and with independent observations. The method based on the Fokker-Planck equation and the extended Kalman filter are preferable because they give better results than the optimal interpolation scheme. The various model characteristics of the ocean, such as the heat content fields and others, are analyzed after the data assimilation.     

基于长短时记忆神经网络的台风路径临近预报模型

It is of vital importance to reduce injuries and economic losses by accurate forecasts of typhoon tracks. A huge amount of typhoon observations have been accumulated by the meteorological department, however, they are yet to be adequately utilized. It is an effective method to employ machine learning to perform forecasts. A long short term memory(LSTM) neural network is trained based on the typhoon observations during 1949–2011 in China's Mainland, combined with big data and data mining technologies, and a forecast model based on machine learning for the prediction of typhoon tracks is developed. The results show that the employed algorithm produces desirable 6–24 h nowcasting of typhoon tracks with an improved precision.     

Comparative analysis of the methods used for the determination of the optical parameters of waters in the black sea according to the data of satellite measurements

We demonstrate the possibility of determination of the spectral characteristics of absorption and backward scattering of light in the Black Sea according to the data of a SeaWiFS satellite device. We use specially selected data of observations obtained under favorable atmospheric conditions. It is shown that the results of calculations performed by using different methods are almost identical and weakly depend on the model parameters of the spectral course of the coefficients of absorption of light by yellow substance and its scattering by suspended particles.     

Application of a 3-D chemical fate prediction model (FATE3D) to predict dioxin concentrations in the Tokyo Bay

A 3-D chemical fate prediction model (FATE3D) was applied to predict the dioxin concentrations in the seawater of Tokyo Bay, Japan. The simulations were carried out for a period of one year (from September 2002 to August 2003). Parameters such as meteorological data, flow field conditions, concentrations and sinking rates of organic particulate matter, initial and boundary conditions, and loading fluxes and physico-chemical properties of dioxins were used as the model inputs.The simulation results compared favorably with the field measurements of dioxin concentrations in the bay for both the particulate and dissolved phases, indicating the validity and predictive capability of the model. Furthermore, the differences in the seasonal cycles and distributions between the particulate- and dissolved-phase dioxins in the bay were estimated from the simulation results.However, the particulate-phase dioxin concentrations in the bottom layers (+1 m from the bottom) were underestimated, probably because the resuspension process was not taken into account in the model. The improvement of the model's predictive capability, including the resuspension process, shall be the focus of our next study.