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1.
1 .IntroductionNondestructiveinspection (NDI)isveryimportantforensuringthereliabilityofoffshorestructuresintheirservicelives (Lauraetal.,1 996 ) .Itiswellknownthatdetectionofflawsinvolvesconsider ablestatisticaluncertainties.Asaresult,theprobabilityofdetection (POD)forallflawsofagivensizehasbeenusedintheliteraturetodefinethecapabilityofaparticularNDItechniqueinagivenen vironment.SincethedataofPODusuallyscatterlargely ,itisdifficulttodeterminewhichmodelfitstheavailabledatabest.Thismodelun…  相似文献   

2.
Prediction of coastal processes, including waves, currents, and sediment transport, can be obtained from a variety of detailed geophysical-process models with many simulations showing significant skill. This capability supports a wide range of research and applied efforts that can benefit from accurate numerical predictions. However, the predictions are only as accurate as the data used to drive the models and, given the large temporal and spatial variability of the surf zone, inaccuracies in data are unavoidable such that useful predictions require corresponding estimates of uncertainty. We demonstrate how a Bayesian-network model can be used to provide accurate predictions of wave-height evolution in the surf zone given very sparse and/or inaccurate boundary-condition data. The approach is based on a formal treatment of a data-assimilation problem that takes advantage of significant reduction of the dimensionality of the model system. We demonstrate that predictions of a detailed geophysical model of the wave evolution are reproduced accurately using a Bayesian approach. In this surf-zone application, forward prediction skill was 83%, and uncertainties in the model inputs were accurately transferred to uncertainty in output variables. We also demonstrate that if modeling uncertainties were not conveyed to the Bayesian network (i.e., perfect data or model were assumed), then overly optimistic prediction uncertainties were computed. More consistent predictions and uncertainties were obtained by including model-parameter errors as a source of input uncertainty. Improved predictions (skill of 90%) were achieved because the Bayesian network simultaneously estimated optimal parameters while predicting wave heights.  相似文献   

3.
During the sediment acoustics experiment in 1999 (SAX99), several researchers measured sound speed and attenuation. Together, the measurements span the frequency range of about 125 Hz-400 kHz. The data are unique both for the frequency range spanned at a common location, and for the extensive environmental characterization that was carried out as part of SAX99. Environmental measurements were sufficient to determine or bound the values of almost all the sediment and pore water physical property input parameters of the Biot poroelastic model for sediment. However, the measurement uncertainties for some of the parameters result in significant uncertainties for Biot-model predictions. Here, measured sound-speed and attenuation results are compared to the frequency dependence predicted by Biot theory and a simpler "effective density" fluid model derived from Biot theory. Model/data comparisons are shown where the uncertainty in Biot predictions due to the measurement uncertainties for values of each input parameter are quantified. A final set of parameter values, for use in other modeling applications e.g., in modeling backscattering (Williams et al., 2002) are given, that optimize the fit of the Biot and effective density fluid models to the sound-speed dispersion and attenuation measured during SAX99. The results indicate that the variation of sound speed with frequency is fairly well modeled by Biot theory but the variation of attenuation with frequency deviates from Biot theory predictions for homogeneous sediment as frequency increases. This deviation may be due to scattering from volume heterogeneity. Another possibility for this deviation is shearing at grain contacts hypothesized by Buckingham; comparisons are also made with this model.  相似文献   

4.
A method is introduced to calculate and to account for the uncertainties in the predictions of oil spill trajectories using a classic oil spill model. The method considers the output of the oil spill model as a function of random variables, which are the input parameters, and calculates the standard deviation of the output results which gives a measure of the uncertainty of the model given the uncertainties of the input parameters.Instead of a single trajectory that is calculated by the oil spill model using the mean values of the parameters, a band of trajectories can be defined when various simulations are done taking into account the uncertainties of the input parameters. This band of trajectories defines envelopes of the trajectories that are likely to be followed by the spill given the uncertainties of the input.The method is applied to an oil spill that occurred in open sea near Madeira Islands, in the Atlantic Ocean, in December 1989. The simulations allow the understanding of how a change in the wind direction drove the spill towards the Islands.The envelope of likely trajectories that is obtained with the uncertainty modelling shows a band of trajectories that is in better agreement with the observations than the single trajectory simulated by the oil spill model, based on mean parameters.  相似文献   

5.
为克服典型情景模拟法的缺陷,综合考虑船舶溢油发生的随机性、海洋水动力和风场的不确定性以及环境资源的敏感性,提出基于随机情景模拟的船舶溢油危害后果定量评价方法。通过随机情景模拟和网格化统计得到敏感区的溢油污染概率和最快到达时间,结合环境敏感指数和溢油量等参数计算综合溢油危害指数,并将其作为溢油危害后果定量评价指标。结果表明:台湾海峡北部水域不同季节发生船舶溢油的危害后果大小依次为夏季(27.8)秋季(25.5)春季(21.1)冬季(16.2),夏季溢油事故对牛山岛保护区的污染概率和危害后果相对最大(P=60%,Ck=41.2),达到较高级别;其他季节东甲列岛保护区的溢油污染概率和危害指数均为最高。随机情景模拟能够弥补事故情景,为评价船舶溢油危害后果风险提供一种新方法。  相似文献   

6.
To assess the flood protection capacity of dunes in The Netherlands, a semi-probabilistic dune-erosion prediction method is currently in use in which uncertainties in input parameters of an empirical dune erosion model were taken into account, with the exception of the uncertainty in the extreme surge distribution. Previous research has shown that the surge is by far the most influential parameter affecting erosion in the currently used erosion model, which is due both to the influence of the surge level itself and to the conditional dependence of the wave height and period on the surge level in the probabilistic model used for the assessment. Furthermore, the distribution of extreme surge levels has been shown to contain large statistical uncertainty. The inclusion of uncertainty in input variables into probabilistic models results in more extreme events (in this case erosion) for the same exceedance probability, largely due to the incorporation of higher values of the input variables. The goal of the research described in this paper was to determine the impact of the inclusion of uncertainty in the extreme surge distribution on the estimate of critical erosion (erosion associated with an exceedance frequency of 10− 5 per year). The uncertainty in the surge distributions was estimated and parameterized, and was incorporated into the probabilistic model. A reduction in uncertainty was subsequently imposed to estimate what value a reduction in uncertainty can offer, in terms of the impact on critical erosion. The probabilistic technique first-order reliability method (FORM) was applied to determine the relative contribution of the uncertainty in the surge distribution (as well as the remaining stochastic variables) to the critical erosion. The impact of the inclusion of uncertainty in the surge distribution on the critical retreat distance was found to be substantial with increases ranging from 34% to 93% of the original estimate at five locations along the Dutch coast. The reduced uncertainty showed a more subtle impact, with increases in critical retreat distance ranging from 10% to 26% of the original estimate. The relative importance analysis showed that the uncertainty in the surge distribution has a strong influence, with the relative importance ranging from 10% to 23% for an exceedance frequency of 10− 5 per year.  相似文献   

7.
For more and more applications in coastal and offshore engineering, numerical simulations of waves and surges are required. An important input parameter for such simulations are wind fields. They represent one of the major sources for uncertainties in wave and surge simulations. Wind fields for such simulations are frequently obtained from numerical hindcasts with regional atmospheric models (RAMs). The skill of these atmospheric hindcasts depends, among others, on the quality of the forcing at the boundaries. Furthermore, results may vary due to uncertainties in the initial conditions. By comparing different existing approaches for forcing a regional atmospheric model, it is shown that the models' sensitivity to uncertainties in the initial conditions may be reduced when a more sophisticated approach is used that has been suggested recently. For a specific, although somewhat brief test period, it is demonstrated that an improved hindcast skill for near surface wind fields is obtained when this approach is adopted. Consequences of the reduced uncertainty in wield fields for the hindcast skill of subsequent wave modelling studies are demonstrated. Recently, this new approach has been used together with a regional atmosphere model to produce a 40-year wind hindcast for the Northeast Atlantic, the North Sea and the Baltic Sea. The hindcast is presently extended to other areas and the wind fields are used to produce 40-year high-resolution hindcasts of waves and surges for various European coastal areas.  相似文献   

8.
Bayesian methods are useful in fisheries stock assessment because they provide a conceptually elegant and statistically rigorous approach to making decisions under uncertainty. The application of Bayesian stock assessment methods in the management of Namibian orange roughy Hoplosthethus atlanticus within the 200 mile EEZ of Namibia is reviewed. Time-series of relative abundance are short and their reliability in indicating abundance trends is uncertain. The development of informative prior probability density functions (pdfs) for the constants of proportionality (q) for hydro-acoustic, commercial trawl swept area, and research trawl swept area indices produced statistically consistent prior estimates of absolute abundance for each of the three grounds where more than one index of abundance was available. The posterior pdfs for stock assessment model parameters were used to account for uncertainty in evaluations of the potential consequences of alternative harvesting policies under a stock reduction model in which catch removals were assumed to account for any declines. It appears that all orange roughy stocks off Namibia have been depleted below the limit reference point (50% of long-term unfished biomass). However, the stock reduction model could not easily account for the large declines in indices on the four fishing grounds over the period from 1995 until 1999 when the informative priors for q were applied. In the 2000 stock assessment, the Bayesian procedure was updated to account formally for uncertainty in model structures that could explain the decline in abundance. The possibility of very low stock abundance could still not be discounted when these uncertainties were accounted for. Although this most recent methodology applies more statistical rigour, its complexity has hindered its acceptance in Namibia. However, if it is worth quantifying risks and uncertainties in future stock assessments for the provision of precautionary management advice, it is proposed that the assessment protocols adopted be probabilistic to account for uncertainty in model parameters, that careful attention be given to subjective judgements about their inputs and the representation of uncertainty within them, and that, where appropriate, alternative hypotheses about stock abundance and mechanisms for catchability and stock decline be taken into account.  相似文献   

9.
We seek to determine if a small number of measurements of upper ocean temperature and currents can be used to make estimates of the drag coefficient that have a smaller range of uncertainty than previously found. We adopt a numerical approach using forward models of the ocean’s response to a tropical cyclone, whereby the probability density function of drag coefficient values as a function of wind speed that results from adding realistic levels of noise to the simulated ocean response variables is sought. Allowing the drag coefficient two parameters of freedom, namely the values at 35 and at 45 m/s, we found that the uncertainty in the optimal value is about 20% for levels of instrument noise up to 1 K for a misfit function based on temperature, or 1.0 m/s for a misfit function based on 15 m velocity components. This is within tolerable limits considering the spread of measurement-based drag coefficient estimates. The results are robust for several different instrument arrays; the noise levels do not decrease by much for arrays with more than 40 sensors when the sensor positions are random. Our results suggest that for an ideal case, having a small number of sensors (20–40) in a data assimilation problem would provide sufficient accuracy in the estimated drag coefficient.  相似文献   

10.
The primary objective of this study is to introduce a stochastic framework based on generalized polynomial chaos (gPC) for uncertainty quantification in numerical ocean wave simulations. The techniques we present can be easily extended to other numerical ocean simulation applications. We perform stochastic simulations using a relatively new numerical method to simulate the HISWA (Hindcasting Shallow Water Waves) laboratory experiment for directional near-shore wave propagation and induced currents in a shallow-water wave basin. We solve the phased-averaged equation with hybrid discretization based on discontinuous Galerkin projections, spectral elements, and Fourier expansions. We first validate the deterministic solver by comparing our simulation results against the HISWA experimental data as well as against the numerical model SWAN (Simulating Waves Nearshore). We then perform sensitivity analysis to assess the effects of the parametrized source terms, current field, and boundary conditions. We employ an efficient sparse-grid stochastic collocation method that can treat many uncertain parameters simultaneously. We find that the depth-induced wave-breaking coefficient is the most important parameter compared to other tunable parameters in the source terms. The current field is modeled as random process with large variation but it does not seem to have a significant effect. Uncertainty in the source terms does not influence significantly the region before the submerged breaker whereas uncertainty in the incoming boundary conditions does. Considering simultaneously the uncertainties from the source terms and boundary conditions, we obtain numerical error bars that contain almost all experimental data, hence identifying the proper range of parameters in the action balance equation.  相似文献   

11.
The PDFs (probability density functions) and probability of a ship rolling under the random parametric and forced excitations were studied by a semi-analytical method. The rolling motion equation of the ship in random oblique waves was established. The righting arm obtained by the numerical simulation was approximately fitted by an analytical function. The irregular waves were decomposed into two Gauss stationary random processes, and the CARMA (2, 1) model was used to fit the spectral density function of parametric and forced excitations. The stochastic energy envelope averaging method was used to solve the PDFs and the probability. The validity of the semi-analytical method was verified by the Monte Carlo method. The C11 ship was taken as an example, and the influences of the system parameters on the PDFs and probability were analyzed. The results show that the probability of ship rolling is affected by the characteristic wave height, wave length, and the heading angle. In order to provide proper advice for the ship''s manoeuvring, the parametric excitations should be considered appropriately when the ship navigates in the oblique seas.  相似文献   

12.
基于模型相似度拟合的海杂波统计方法   总被引:1,自引:0,他引:1  
赵荻  孟俊敏  张晰  郎海涛 《海洋学报》2015,37(5):112-120
本文提出一种基于模型相似度拟合的海杂波统计方法。首先根据合成孔径雷达(SAR)图像计算瑞利分布、对数正态分布、韦布尔分布、K分布、G0分布5种经典的海杂波分布的概率密度函数,然后根据模型间的相似度准则拟合得到新的海杂波分布模型。文章利用四景不同类型的真实SAR数据对算法的拟合性能进行了评价,结果显示利用该算法得到的拟合模型与真实SAR数据的平均Kullback-Leibler距离仅为0.015 84,远优于其他分布模型。基于该拟合模型的恒虚警率舰船检测算法对四景SAR数据的平均检测精度达到95.75%,在控制虚警和漏检方面均优于采用其他模型的同类方法。  相似文献   

13.
Prediction of coastal hazards due to climate change is fraught with uncertainty that stems from complexity of coastal systems, estimation of sea level rise, and limitation of available data. In-depth research on coastal modeling is hampered by lack of techniques for handling uncertainty, and the available commercial geographical information systems (GIS) packages have only limited capability of handling uncertain information. Therefore, integrating uncertainty theory with GIS is of practical and theoretical significance. This article presents a GIS-based model that integrates an existing predictive model using a differential approach, random simulation, and fuzzy set theory for predicting geomorphic hazards subject to uncertainty. Coastal hazard is modeled as the combined effects of sea-level induced recession and storm erosion, using grid modeling techniques. The method is described with a case study of Fingal Bay Beach, SE Australia, for which predicted responses to an IPCC standard sea-level rise of 0.86 m and superimposed storm erosion averaged 12 m and 90 m, respectively, with analysis of uncertainty yielding maximum of 52 m and 120 m, respectively. Paradoxically, output uncertainty reduces slightly with simulated increase in random error in the digital elevation model (DEM). This trend implies that the magnitude of modeled uncertainty is not necessarily increased with the uncertainties in the input parameters. Built as a generic tool, the model can be used not only to predict different scenarios of coastal hazard under uncertainties for coastal management, but is also applicable to other fields that involve predictive modeling under uncertainty.  相似文献   

14.
Prediction of coastal hazards due to climate change is fraught with uncertainty that stems from complexity of coastal systems, estimation of sea level rise, and limitation of available data. In-depth research on coastal modeling is hampered by lack of techniques for handling uncertainty, and the available commercial geographical information systems (GIS) packages have only limited capability of handling uncertain information. Therefore, integrating uncertainty theory with GIS is of practical and theoretical significance. This article presents a GIS-based model that integrates an existing predictive model using a differential approach, random simulation, and fuzzy set theory for predicting geomorphic hazards subject to uncertainty. Coastal hazard is modeled as the combined effects of sea-level induced recession and storm erosion, using grid modeling techniques. The method is described with a case study of Fingal Bay Beach, SE Australia, for which predicted responses to an IPCC standard sea-level rise of 0.86 m and superimposed storm erosion averaged 12 m and 90 m, respectively, with analysis of uncertainty yielding maximum of 52 m and 120 m, respectively. Paradoxically, output uncertainty reduces slightly with simulated increase in random error in the digital elevation model (DEM). This trend implies that the magnitude of modeled uncertainty is not necessarily increased with the uncertainties in the input parameters. Built as a generic tool, the model can be used not only to predict different scenarios of coastal hazard under uncertainties for coastal management, but is also applicable to other fields that involve predictive modeling under uncertainty.  相似文献   

15.
不确定海洋环境中基于贝叶斯理论的多声源定位算法   总被引:2,自引:0,他引:2  
环境参数失配导致定位性能大幅度下降是匹配场定位所面临的难题之一。应用贝叶斯理论对环境聚焦,是当前解决该难题的研究热点。环境聚焦方法的实质是将未知环境参数和声源位置联合优化估计,当出现多个目标时,估计的参数会随着声源个数成倍增加,因此不得不利用有限的观测信息来实现众多参数的估计。本文采用最大似然比方法,获得信号源谱和误差项的最大似然估计,实现这些敏感性较弱参数的间接反演,有效降低了反演参数维数和定位算法复杂度。针对遗传算法的早熟和稳定性差的问题,改进了似然函数的经验表达式。将多维后验概率密度在参数起伏变化范围内积分,得到反演参数的一维边缘概率分布,求解最优值的同时进行反演结果的不确定性分析。本文仿真了位于相同距离、不同深度的两个声源,使用仿真实验验证了提出算法的有效性。  相似文献   

16.
We present an overview of Markov chain Monte Carlo, a sampling method for model inference and uncertainty quantification. We focus on the Bayesian approach to MCMC, which allows us to estimate the posterior distribution of model parameters, without needing to know the normalising constant in Bayes' theorem. Given an estimate of the posterior, we can then determine representative models (such as the expected model, and the maximum posterior probability model), the probability distributions for individual parameters, and the uncertainty about the predictions from these models. We also consider variable dimensional problems in which the number of model parameters is unknown and needs to be inferred. Such problems can be addressed with reversible jump (RJ) MCMC. This leads us to model choice, where we may want to discriminate between models or theories of differing complexity. For problems where the models are hierarchical (e.g. similar structure but with a different number of parameters), the Bayesian approach naturally selects the simpler models. More complex problems require an estimate of the normalising constant in Bayes' theorem (also known as the evidence) and this is difficult to do reliably for high dimensional problems. We illustrate the applications of RJMCMC with 3 examples from our earlier working involving modelling distributions of geochronological age data, inference of sea-level and sediment supply histories from 2D stratigraphic cross-sections, and identification of spatially discontinuous thermal histories from a suite of apatite fission track samples distributed in 3D.  相似文献   

17.
This paper applies nonlinear Bayesian inversion to seabed reflection data to estimate viscoelastic parameters of the upper sediments. The inversion provides maximum a posteriori probability (MAP) parameter estimates with uncertainties quantified in terms of marginal probability distributions, variances, and credibility intervals; interparameter relationships are quantified by correlations and joint marginal distributions. The inversion is applied to high-resolution reflectivity data from two sites in the Strait of Sicily. One site is characterized by low-speed sediments, resulting in data with a well-defined angle of intromission; the second is characterized by high-speed sediments, resulting in a critical angle. Data uncertainties are quantified using several approaches, including maximum-likelihood (ML) estimation, treating uncertainties as nuisance parameters in the inversion, and analysis of experimental errors. Statistical tests are applied to the data residuals to validate the assumed uncertainty distributions. Excellent results (i.e., small uncertainties) are obtained for sediment compressional-wave speed, compressional attenuation, and density; shear parameters are less well determined although low shear-wave speeds are indicated. The Bayesian analysis provides a quantitative comparison of inversion results for the two sites in terms of the resolution of specific geoacoustic parameters, and indicates that the geoacoustic information content is significantly higher for intromission data  相似文献   

18.
《Coastal Engineering》2004,51(4):277-296
A cyclone induced storm surge and flood forecasting system that has been developed for the northern Bay of Bengal is presented. The developed system includes a cyclone forecasting model that uses statistical models for forecasting of the cyclone track and maximum wind speed, and an analytical cyclone model for generation of cyclone wind and pressure fields. A data assimilation system has been developed that allows updating of the cyclone parameters based on air pressure and wind speed observations from surface meteorological stations. The forecasted air pressure and wind fields are used as input in a 2D hydrodynamic model for forecasting storm surge levels and associated flooding. An efficient uncertainty prediction procedure based on Harr's point estimation method has been implemented as part of the forecasting system for prediction of the uncertainties of the forecasted storm surge levels and inundation areas caused by the uncertainties in the cyclone track and wind speed forecasts. The developed system is applied on a severe cyclone that hit Bangladesh in April 1991. The simulated storm surge and associated flooding are highly sensitive to the cyclone data. The cyclone data assimilation system provides a more accurate cyclone track when the cyclone approaches the coastline, which results in a significant improvement of the storm surge and flood predictions. Application of the uncertainty prediction procedure shows that the large uncertainties of the cyclone track and intensity forecasts result in large uncertainties of the forecasted storm surge levels and flood extend. The forecasting system shows very good forecasting capabilities up to 24 h before the actual landfall.  相似文献   

19.
In this work a method for estimating parameters of practical ship manoeuvring models based on the combination of RANSE computations and System Identification procedure is investigated, considering as test case a rather slender twin screw and two rudders ship. The approach consists in the estimation of the hydrodynamic coefficients applying System Identification to a set of free running manoeuvres obtained from an in-house unsteady RANS equations solver, which substitute the usually adopted experimental tests at model or full scale. In this alternative procedure the numerical quasi-trials (in terms of kinematic parameters time histories and, if needed, forces time histories) are used as input for the System Identification procedure; the aim of this approach is to reduce external disturbances that, if not properly considered in the mathematical model, may compromise the identification results, or at least amplify the well-known “cancellation effects”. Furthermore, the CFD results provide information both in terms of flow field variables and hydrodynamic forces on the manoeuvring ship. These data may be adopted for a better understanding of the complex flow during manoeuvres, especially at stern, providing also additional information about the interaction between the various appendages (including rudders) and the hull. The identification procedure is based on an off-line genetic algorithm used for minimizing the discrepancy between the reference manoeuvres from CFD and those simulated with the system based modular model. The discrepancy was measured considering different metric functions and simplified formulations which consider only the main macroscopic parameters of the manoeuvre; the metrics have been analyzed in terms of their capability in reproducing the time histories and in limiting the cancellation effect of the hydrodynamic derivatives.  相似文献   

20.
Satellite-derived phytoplankton pigment absorption(a_(ph)) has been used as a key predictor of phytoplankton photosynthetic efficiency to estimate global ocean net primary production(NPP). In this study, an a_(ph)-based NPP model(Ab PM) with four input parameters including the photosynthetically available radiation(PAR), diffuse attenuation at 490 nm(K_d(490)), euphotic zone depth(Z_(eu)) and the phytoplankton pigment absorption coefficient(a_(ph)) is compared with the chlorophyll-based model and carbon-based model. It is found that the Ab PM has significant advantages on the ocean NPP estimation compared with the chlorophyll-based model and carbonbased model. For example, Ab PM greatly outperformed the other two models at most monitoring sites and had the best accuracy, including the smallest values of RMSD and bias for the NPP estimate, and the best correlation between the observations and the modeled NPPs. In order to ensure the robustness of the model, the uncertainty in NPP estimates of the Ab PM was assessed using a Monte Carlo simulation. At first, the frequency histograms of simple difference(δ), and logarithmic difference(δ~(LOG)) between model estimates and in situ data confirm that the two input parameters(Z_(eu) and PAR) approximate the Normal Distribution, and another two input parameters(a_(ph) and K_d(490)) approximate the logarithmic Normal Distribution. Second, the uncertainty in NPP estimates in the Ab PM was assessed by using the Monte Carlo simulation. Here both the PB(percentage bias), defined as the ratio of ΔNPP to the retrieved NPP, and the CV(coefficient of variation), defined as the ratio of the standard deviation to the mean are used to indicate the uncertainty in the NPP brought by input parameter to Ab PM model. The uncertainty related to magnitude is denoted by PB and the uncertainty related to scatter range is denoted by CV.Our investigations demonstrate that PB of NPP uncertainty brought by all parameters with an annual mean of5.5% covered a range of –5%–15% for the global ocean. The PB uncertainty of Ab PM model was mainly caused by a_(ph); the PB of NPP uncertainty brought by a_(ph) had an annual mean of 4.1% for the global ocean. The CV brought by all the parameters with an annual mean of 105% covered a range of 98%–134% for global ocean. For the coastal zone of Antarctica with higher productivity, the PB and CV of NPP uncertainty brought by all parameters had annual means of 7.1% and 121%, respectively, which are significantly larger than those obtained in the global ocean. This study suggests that the NPPs estimated by Ab PM model are more accurate than others, but the magnitude and scatter range of NPP errors brought by input parameter to Ab PM model could not be neglected,especially in the coastal area with high productivity. So the improving accuracy of satellite retrieval of input parameters should be necessary. The investigation also confirmed that the SST related correction is effective for improving the model accuracy in low temperature condition.  相似文献   

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