Ocean forecasting in terrain-following coordinates: Formulation and skill assessment of the Regional Ocean Modeling System

Systematic improvements in algorithmic design of regional ocean circulation models have led to significant enhancement in simulation ability across a wide range of space/time scales and marine system types. As an example, we briefly review the Regional Ocean Modeling System, a member of a general class of three-dimensional, free-surface, terrain-following numerical models. Noteworthy characteristics of the ROMS computational kernel include: consistent temporal averaging of the barotropic mode to guarantee both exact conservation and constancy preservation properties for tracers; redefined barotropic pressure-gradient terms to account for local variations in the density field; vertical interpolation performed using conservative parabolic splines; and higher-order, quasi-monotone advection algorithms. Examples of quantitative skill assessment are shown for a tidally driven estuary, an ice-covered high-latitude sea, a wind- and buoyancy-forced continental shelf, and a mid-latitude ocean basin. The combination of moderate-order spatial approximations, enhanced conservation properties, and quasi-monotone advection produces both more robust and accurate, and less diffusive, solutions than those produced in earlier terrain-following ocean models. Together with advanced methods of data assimilation and novel observing system technologies, these capabilities constitute the necessary ingredients for multi-purpose regional ocean prediction systems.     

A Framework for Four-Dimensional Variational Data Assimilation Based on Machine Learning

The initial field has a crucial influence on numerical weather prediction (NWP). Data assimilation (DA) is a reliable method to obtain the initial field of the forecast model. At the same time, data are the carriers of information. Observational data are a concrete representation of information. DA is also the process of sorting observation data, during which entropy gradually decreases. Four-dimensional variational assimilation (4D-Var) is the most popular approach. However, due to the complexity of the physical model, the tangent linear and adjoint models, and other processes, the realization of a 4D-Var system is complicated, and the computational efficiency is expensive. Machine learning (ML) is a method of gaining simulation results by training a large amount of data. It achieves remarkable success in various applications, and operational NWP and DA are no exception. In this work, we synthesize insights and techniques from previous studies to design a pure data-driven 4D-Var implementation framework named ML-4DVAR based on the bilinear neural network (BNN). The framework replaces the traditional physical model with the BNN model for prediction. Moreover, it directly makes use of the ML model obtained from the simulation data to implement the primary process of 4D-Var, including the realization of the short-term forecast process and the tangent linear and adjoint models. We test a strong-constraint 4D-Var system with the Lorenz-96 model, and we compared the traditional 4D-Var system with ML-4DVAR. The experimental results demonstrate that the ML-4DVAR framework can achieve better assimilation results and significantly improve computational efficiency.     

一个L波段海表盐度遥感反演的新经验模式

海表盐度是描述海洋的一个重要参量，海表盐度的微波探测是海洋遥感研究的重要内容.利用黄海实测盐度数据和海表亮温资料，建立了一个适用于黄海近岸的盐度反演模式.在没有海浪破碎情况下，利用L波段的亮温资料反演海洋表层盐度.本模式充分考虑了海面粗糙度的影响，从海水亮温和海水的介电常数反演的表层盐度和实测的表层海水盐度基本一致，其平均绝对误差为0.288psu，与同类模式相比具有较高的精度. 关键词： 盐度 亮温 辐射率 介电常数     

温盐深剖面仪与Argo数据的冬季印度洋声速剖面分析

通过某一次在东南印度洋调查工作中获得的17站位温盐深剖面仪(CTD)数据,因其表层0～10 m数据缺失,选择利用卫星遥感的海表面温度产品与中国Argo实时资料中心提供的全球海洋Argo网格数据集(BOA_Argo)中逐年月平均数据做比较,发现BOA_Argo数据集反推得到的表层温度是比较准确的.再将CTD数据与对应时间...     

Model-oriented ocean tomography using higher frequency, bottom-mounted hydrophones

A tomographic scheme is presented that ingests ocean acoustic measurements into an ocean model using data from bottom-mounted hydrophones. The short distances between source-receiver pairs (1-10 km) means arrival times at frequencies of 8-11 kHz are readily detectable and often distinguishable. The influence of ocean surface motion causes considerable variability in acoustic travel times. Techniques are presented for measuring travel times and removing the variability due to surface waves. An assimilation technique is investigated that uses differences in measured and modeled acoustic travel times to impose corrections on the oceanographic model. Equations relating travel time differences to oceanographic variables are derived, and techniques are presented for estimating the acoustic and ocean model error covariance matrices. One test case using a single source-receiver pair shows that the tomographic information can have an impact on constraining the solution of the ocean circulation model but can also introduce biases in the predictions. A second test case utilizes knowledge of a bias in a model-predicted variable to limit grid cells that are impacted by the tomographic data. In this case, using the tomographic data results in significant improvements in the model predictions without introducing any biases.     

机载C波段全极化SAR海面风矢量反演理论研究及实验验证

机载全极化SAR海面风矢量反演研究对于近海岸复杂气象条件下风矢量探测具有重要意义. 本文从极化散射理论出发,通过分析全极化SAR探测数据与海面风矢量的关系, 设计了全极化SAR海面风矢量反演方案.依据机载SAR高机动性和全极化两个探测特点, 针对VV极化探测数据,提出了基于最大似然估计的海面风矢量反演方法,并设计了飞行实验方案; 针对VH极化探测数据,提出了通过带约束最优拟合的VH极化海面散射模型反演风速, 再利用CMOD5地球物理模型函数计算风向的海面风矢量反演方法. 利用机载全极化SAR探测的台风'海葵'边缘数据,开展了海面风矢量反演实验研究. 研究结果表明,两种风矢量反演方法均可不借助辅助信息,反演复杂气象条件下的海面风矢量. 前者反演风向、风速的均方根误差分别为18.0°, 1.8 m/s, 后者反演风向、风速的均方根误差分别为9.3°, 1.2 m/s,后者的反演精度优于前者. 这是因为VH极化归一化雷达截面与风向和雷达入射角无关,仅与风速密切相关, 更适合复杂气象条件下的海面风矢量反演. 关键词： 机载全极化SAR 海面风矢量 理论研究 实验验证     

New data assimilation system DNDAS for high-dimensional models

The tangent linear(TL) models and adjoint(AD) models have brought great difficulties for the development of variational data assimilation system. It might be impossible to develop them perfectly without great efforts, either by hand, or by automatic differentiation tools. In order to break these limitations, a new data assimilation system, dual-number data assimilation system(DNDAS), is designed based on the dual-number automatic differentiation principles. We investigate the performance of DNDAS with two different optimization schemes and subsequently give a discussion on whether DNDAS is appropriate for high-dimensional forecast models. The new data assimilation system can avoid the complicated reverse integration of the adjoint model, and it only needs the forward integration in the dual-number space to obtain the cost function and its gradient vector concurrently. To verify the correctness and effectiveness of DNDAS, we implemented DNDAS on a simple ordinary differential model and the Lorenz-63 model with different optimization methods. We then concentrate on the adaptability of DNDAS to the Lorenz-96 model with high-dimensional state variables. The results indicate that whether the system is simple or nonlinear, DNDAS can accurately reconstruct the initial condition for the forecast model and has a strong anti-noise characteristic. Given adequate computing resource, the quasi-Newton optimization method performs better than the conjugate gradient method in DNDAS.     

Light reflection from a rough liquid surface including wind-wave effects in a scattering atmosphere

Visible and near-IR images of the ocean surface, taken from remote satellites, often contain important information of near-surface or sub-surface processes, which occur on, or over the ocean. Remote measurements of near surface winds, sea surface temperature and salinity, ocean color and underwater bathymetry, all, one way or another, depend on how well we understand sea surface roughness. However, in order to extract useful information from our remote measurements, we need to construct accurate models of the transfer of solar radiation inside the atmosphere as well as, its reflection from the sea surface. To approach this problem, we numerically solve the radiative transfer equation (RTE) by implementing a model for the atmosphere-ocean system. A one-dimensional atmospheric radiation model is solved via the widely known doubling and adding method and the ocean body is treated as a boundary condition to the problem. The ocean surface is modeled as a rough liquid surface which includes wind interaction and wave states, such as wave age. The model can have possible applications to the retrieval of wind and wave states, such as wave age, near a Sun glint region.     

Radiative transfer solutions for coupled atmosphere ocean systems using the matrix operator technique

Accurate radiative transfer models are the key tools for the understanding of radiative transfer processes in the atmosphere and ocean, and for the development of remote sensing algorithms. The widely used scalar approximation of radiative transfer can lead to errors in calculated top of atmosphere radiances. We show results with errors in the order of±8% for atmosphere ocean systems with case one waters. Variations in sea water salinity and temperature can lead to variations in the signal of similar magnitude. Therefore, we enhanced our scalar radiative transfer model MOMO, which is in use at Freie Universität Berlin, to treat these effects as accurately as possible. We describe our one-dimensional vector radiative transfer model for an atmosphere ocean system with a rough interface. We describe the matrix operator scheme and the bio-optical model for case one waters. We discuss some effects of neglecting polarization in radiative transfer calculations and effects of salinity changes for top of atmosphere radiances. Results are shown for the channels of the satellite instruments MERIS and OLCI from 412.5 nm to 900 nm.     

Practical global oceanic state estimation

The problem of oceanographic state estimation, by means of an ocean general circulation model (GCM) and a multitude of observations, is described and contrasted with the meteorological process of data assimilation. In practice, all such methods reduce, on the computer, to forms of least-squares. The global oceanographic problem is at the present time focussed primarily on smoothing, rather than forecasting, and the data types are unlike meteorological ones. As formulated in the consortium Estimating the Circulation and Climate of the Ocean (ECCO), an automatic differentiation tool is used to calculate the so-called adjoint code of the GCM, and the method of Lagrange multipliers used to render the problem one of unconstrained least-squares minimization. Major problems today lie less with the numerical algorithms (least-squares problems can be solved by many means) than with the issues of data and model error. Results of ongoing calculations covering the period of the World Ocean Circulation Experiment, and including among other data, satellite altimetry from TOPEX/POSEIDON, Jason-1, ERS- 1/2, ENVISAT, and GFO, a global array of profiling floats from the Argo program, and satellite gravity data from the GRACE mission, suggest that the solutions are now useful for scientific purposes. Both methodology and applications are developing in a number of different directions.     

基于集合卡尔曼变换的东中国海声学 敏感区判定方法*

为改善海洋与水声环境预报质量,针对常规观测成本高、资料利用率低等问题,将适应性观测方法应用于海洋声学领域。结合海洋-声学耦合模式与集合卡尔曼转换敏感区诊断方法,以东中国海宫古海峡北部区域为验证区,计算并分析不同条件下海洋环境敏感区与声学敏感区分布,通过观测系统模拟试验验证适应性观测对验证区预报的提升效果。结果表明,两种敏感区位置随时间间隔增加均向验证区上游移动,海洋环境敏感区相比于声学敏感区分布更为集中,且平移特征更明显;对海洋环境敏感区和声学敏感区添加适应性观测均能提升海洋与水声环境的预报质量,提升效果随时间间隔增加而减小,在某种类型敏感区的适应性观测对相对应参数的预报质量提升效果优于对其他类型敏感区进行观测的效果。     

Electromagnetic backscattering from one-dimensional drifting fractal sea surface Ⅱ:Electromagnetic backscattering model

Sea surface current has a significant influence on electromagnetic(EM) backscattering signals and may constitute a dominant synthetic aperture radar(SAR) imaging mechanism. An effective EM backscattering model for a one-dimensional drifting fractal sea surface is presented in this paper. This model is used to simulate EM backscattering signals from the drifting sea surface. Numerical results show that ocean currents have a significant influence on EM backscattering signals from the sea surface. The normalized radar cross section(NRCS) discrepancies between the model for a coupled wavecurrent fractal sea surface and the model for an uncoupled fractal sea surface increase with the increase of incidence angle,as well as with increasing ocean currents. Ocean currents that are parallel to the direction of the wave can weaken the EM backscattering signal intensity, while the EM backscattering signal is intensified by ocean currents propagating oppositely to the wave direction. The model presented in this paper can be used to study the SAR imaging mechanism for a drifting sea surface.     

El Niño prediction and predictability

El Niño-Southern Oscillation (ENSO) is by far the most energetic, and at present also the most predictable, short-term fluctuation in the Earth’s climate system, though the limits of its predictability are still a subject of considerable debate. As a result of over two-decades of intensive observational, theoretical and modeling efforts, ENSO’s basic dynamics is now well understood and its prediction has become a routine practice at application centers all over the world. The predictability of ENSO largely stems from the ocean–atmosphere interaction in the tropical Pacific and the low-dimensional nature of this coupled system. Present ENSO forecast models, in spite of their vast differences in complexity, exhibit comparable predictive skills, which seem to have hit a plateau at moderate level. However, mounting evidence suggests that there is still room for improvement. In particular, better model initialization and data assimilation, better simulation of surface heat and freshwater fluxes, and better representation of the relevant processes outside of the tropical Pacific, could all lead to improved ENSO forecasts.     

海洋赤潮温度盐度双参数检测技术研究

针对海洋赤潮的实时监测和预报,提出了一种通过检测海水中布里渊散射回波信号,获取海洋赤潮水体温度和盐度分布信息的双参数检测技术。通过分析布里渊散射理论,建立基于机载蓝绿激光雷达的布里渊散射信号频移量和布里渊散射信号能量与海水温度和盐度的关系模型。通过仿真计算,可由海水中的蓝绿激光布里渊散射回波信号的频移量和能量,分别得出海表及海水50 m深度以内温度和盐度的分布情况,从而可以实现海水温度和盐度的双参数实时获取,为实时判断海洋赤潮的消长过程提供理论依据。     

基于Argo资料和混合层模式的淡水通量产品重构

海表淡水通量对于了解和模拟海洋大气过程具有重要作用,然而不同淡水通量的定量估计差别较大.基于混合层盐度平衡模式,利用Argo资料和OSCAR(海洋表面流实时分析场)流场相结合重构了2002-2008年逐周海表淡水通量产品.通过将重构产品与其他卫星产品和TAO(热带大气海洋观测网)观测进行对比分析表明,重构的淡水通量产品不仅能抓住其季节性信号,而且能够体现淡水通量的高频特征.该逐周淡水通量产品对海洋气候变化研究具有重要作用.     

A novel approach to a Brillouin–LIDAR for remote sensing of the ocean temperature

Ocean temperature profiles are of great importance in oceanography. For instance, an efficient remote sensing measurement technique of these profiles will facilitate climate studies and improvements in weather forecast. In this paper we describe developments towards a practical implementation of a Brillouin–LIDAR system capable of measuring temperature profiles in the ocean. In particular, we focus on our recent work on fiber amplifiers and a receiver unit based on a Faraday anomalous dispersion optical filter. PACS 42.79.Qx; 42.60.By; 42.62.Fi; 42.68.Xy; 42.50.Nn     

Long-term memory dynamics of continental and oceanic monthly temperatures in the recent 125 years

For both Northern and Southern hemispheres, the long-term memory dynamics for continent and ocean temperature records in the recent 125 years is studied in this paper. It is found that the records exhibit long-range memory and multifractality characteristics where large temperature anomalies display a more random behavior than the overall time series. A 256-month moving window was used to compute the time evolution of the fractal scaling exponent, giving the following results: (i) Ocean temperatures are more persistent than land temperatures, a result already reported in recent publications, (ii) All records show multifractality features, reflecting the nonlinear behavior of the temperature dynamics. Continent temperatures present sharper multifractal spectra than ocean temperatures, (iii) The persistency, as revealed by the scaling exponent, for ocean temperatures displays a cyclic behavior around a nearly constant average value of 22 years, (iv) The persistency for the Northern Hemisphere land temperature is also cyclical but with an increasing trend, and (v) The time at which the Northern Hemisphere continent temperature persistency will converge into the Northern Hemisphere ocean behavior was estimated with linear and exponential extrapolation functions, showing hitting dates around 2050±20 A.D. Potential implications of these results concerning the nature of climate change are also discussed.     

Separation of the electron localization and interaction in bismuth film resistance

The temperature dependence of the correction to electrical conductivity, Δσ, of Bi thin films (～100–200 Å thick) is measured in the region of the electron localization and interaction effects. The measurements are made without magnetic field and with magnetic fields both perpendicular and parallel to the film surface. Without magnetic field the dependence Δσ(In T) is determined by the total contribution from both effects. As the magnetic field increases, the localization contribution to Δσ decreases and at certain field values it is essentially absent so that the character of Δσ(In T) dependence is determined only by the interaction effect.     

国家气候中心大气环流模式冬季模式误差特征分析

本文利用1982—2010年国家气候中心第二代月动力延伸预测系统中大气环流模式(BCC_AGCM)的回报资料和美国国家环境预测中心和美国国家大气研究中心(NCEP/NCAR)再分析资料,分析了该模式对冬季气温预测的误差特征及其与外强迫的联系.结果表明模式能够在整体上较好地反映出欧亚区域冬季气温的变化趋势,能抓住东亚冬季风区气温年际变化的主要空间模态,对东亚冬季风区冬季气温具有一定的预报能力.预报误差的空间分布和时间演变特征的结果表明,误差在陆地大于海洋,高纬地区大于低纬地区,同时与海拔高度也有密切关系.预报误差的主要模态与一些关键区域的海温和海冰存在显著的相关性,表明模式对外强迫异常的响应能力存在缺陷.这为结合模式对关键区海温和海冰异常的响应能力,有针对性地改进模式对东亚冬季风区冬季气温的预测能力提供了依据.     

环境扰动约束下的稀疏贝叶斯定位方法

针对匹配场被动定位技术对海洋环境扰动敏感的问题,提出了一种基于稀疏贝叶斯学习的稳健匹配场处理方法。该方法通过分析环境扰动情况下的声场构成,建立了海洋环境扰动模型,同时结合水下定位问题的稀疏性,将匹配场被动定位问题表述为稀疏信号重构问题。然后,使用稀疏贝叶斯学习方法迭代更新目标位置及模型失配权向量,收敛至最优稀疏解作为目标定位结果。最后使用仿真数据和北厄尔巴岛的海试数据对算法进行了验证,仿真和实验结果表明:该算法在海洋环境模型失配情况下也能够准确定位,且能分辨水平间距为100 m的两个目标。因此,基于稀疏贝叶斯学习的稳健匹配场处理方法能够有效利用海洋环境扰动声场结构和水下定位稀疏特性,以增强匹配场处理的稳健性和定位精度,并且具有应对多源定位问题的能力。