四维资料同化方法的特点分析和发展趋势

与反任意分布的观测值通过空间和时间插值分析到网格点的方法相比较，利用动力关系分析问题，其优势性十分明显，在一个能提供时间连续和动力耦合的模式预报方程中，有机地结合现在和过去的资料，即众所周知的四维资料同化。从目前经常应用的四维资料同化方法出发，详细分析了它们的特点和今后四维资料同化方法在预报模式中的应用前景。     

台风过程研究中四维资料同化方法的探讨及应用

与把任意分布的观测值通过空间和时间插值分析到网格点的方法相比较,结合动力关系分析大气场问题的方法,其优势十分明显.Charney等[1]建议在一个能提供时间连续和动力耦合的模式预报方程中,有机地结合现在和过去的资料.后来这个概念被发展为众所周知的四维资料同化(FDDA).起初,四维资料同化主要应用于全球尺度,现在,无论是动力初始化还是作为一个分析或者研究工具,四维资料同化都有效地应用在中尺度模式上[2,3].     

应用在海洋研究中的四维同化方法

本文从海洋数值模式的初始场、边界条件和模式误差三方面分析了四维同化方法的必要性,阐述了四维同化技术的含义、三种主要方法及其数学过程,并简单总结了在海洋研究中的应用情况。     

四维变分资料同化在风暴潮模拟中的平流作用分析

利用基于三维斜压非线性的普林斯顿海洋模型(POM)及其切向线性伴随模式的四维变分数据同化(4DVAR)系统对一个近岸风暴潮个例进行理想同化试验和模拟,着重分析了四维变分数据同化增水改善中的二维平流作用。试验结果表明,同化后的水位结果明显优于同化前的结果,而且同化对预报的影响主要在前5h,尤其是积分到3—4h时同化和无同化的结果差异最大,在5h后同化的影响变得非常小。从平流作用中分析得知,无论是只同化水位还是同化水位和海表流速,同化的结果都增大了沿岸和向岸的平流。与无同化结果相比,同化试验的增水改善主要是来自向岸平流的增大,但只同化水位时由于水位增大使向岸压力梯度减小从而阻碍了向岸流的进一步增大;而同时同化水位和海表流速时,由于流速也被改善,故增水改善更明显和合理。     

基于ROMS模式的南海SST与SSH四维变分同化研究

卫星遥感观测获得了大量高分辨率的海面实时信息,包括海面温度（SST）和海面高度（SSH）等,同化进入数值模式可有效提升模拟精度。本文基于ROMS模式与四维变分同化方法（4DVAR）,使用AVHRR SST和AVISO SSH数据,开展了南海区域同化实验。为检验同化的效果,分别利用HYCOM再分析资料和Argo温盐实测数据分析了同化结果的海面高度、流场及温盐剖面的精度。对比结果表明,SST和SSH的同化能够改善ROMS的模拟结果:同化后海面高度场能够更为准确地捕捉海洋的中尺度特征,与HYCOM海面高度再分析资料相比,平均绝对偏差和均方根误差分别为0.054 m和0.066 m;与HYCOM 10 m层流场相比,东向与北向流速平均绝对偏差分别为0.12 m/s和0.11 m/s,相比未同化均提升约0.01 m/s;温盐同化结果与Argo温盐实测具有较高的一致性,温度和盐度平均绝对偏差为0.45℃、0.077,均方根误差为0.91℃、0.11,单个的温盐廓线对比说明,同化结果与HYCOM再分析资料精度相当。     

Kalman滤波风暴潮数值预报四维同化模式研究进展

本文首先介绍了Kalman滤波在风暴潮数值预报中的应用，特别介绍了近年来国际上发展的一些在实际中可行的次优化Kalman滤波算法。并通过一个稳态Kalman滤波风暴潮数值预报模式的实例表明，使用资料同化可以明显改进风暴潮后报结果；资料同化能够提供更为合理的预报初始场，对风暴潮的短期预报有较明显的改进。一旦没有资料同化到模式中去，预报结果很快接近确定性模式。     

基于四维变分同化方法的南海中尺度涡后报实验

海洋中尺度涡在本质上是属于满足准地转平衡的大尺度运动,因此理论上,其在短时间内的运动将主要受到准地转平衡关系的约束,而外部强迫场的影响在短期内不会明显改变其运动特征。基于上述思想,我们提出了一种基于四维变分同化初始场的中尺度涡旋预报方案。为了检验该方案的可行性,本文使用区域海洋模式(regional ocean modeling system, ROMS)和其内建的增量强约束四维变分同化(incremental strong constraint four dimensional variational, I4D-Var)模块,建立了一个南海海洋同化模拟系统。首先,通过I4D-Var方法将AVISO卫星高度计资料同化到海洋数值模拟中,获得了理想的中尺度涡同化模拟结果。同化、模式模拟和观测三者的中尺度涡统计结果表明,该同化系统模拟的南海中尺度涡的路径、半径、海表高度异常和振幅等特征信息与AVISO(Archiving ValidationandInterpolationofSatelliteOceanographicData)观测结果高度吻合,同时在深度上的分析表明,涡旋对应的温度、盐度和密度均得到有效的调整。然后,将该同化系统的模拟结果做为初始场,对某一特定时段的南海中尺度涡进行了后报模拟和结果的定量化分析。通过比较后报模拟与观测资料中对应涡旋的海表面高度异常(sea surface height anomalies, SSHA)相关系数、涡心差距和半径绝对误差,证明该方案的中尺度涡后报时效至少可达10 d以上。后报实验结果验证了该中尺度涡预报方案的可行性,从而为中尺度涡的预报提供一定的理论基础和可行性方案。     

南海北部海洋四维变分同化试验研究

为了研究四维变分同化方法在南海北部海洋数值预报中的适用性,使用海洋区域模式(ROMS),建立了南海北部海洋资料四维变分同化系统,进行了温盐廓线和海面温度数据同化试验,初步对比分析了三种四维变分实现方法的同化效果。研究结果表明,四维变分同化方法具有较好的同化效果,其中,增量强约束方法(I4DVar)具有较好的稳定性,其稳定性高于4DPSAS和R4DVar。本文研究成果为建立南海业务化海洋四维变分同化及预报系统奠定技术基础。     

四维变分同化技术在风暴潮数值模拟中的应用

利用区域海洋模式ROMS(Regional Ocean Modelling System)及其四维变分同化模块,建立了具有资料同化能力的东中国海风暴潮数值模式,通过将海洋站水位观测资料同化到风暴潮模式中,提高了模式对风暴潮的模拟精度。四维变分同化技术能够在整个同化时间窗口保持动力协调,使模拟结果在该时间窗口内最大程度的靠近观测,同时,得到了最优预报初始场。利用该模式,对两次温带风暴潮过程进行了数值模拟,结果表明:在同化窗口内,同化对模拟精度有明显的提高;结束同化之后,得到的最优预报初始场对临近预报精度也有一定提高。     

ATOVS反演数据在大气中尺度模式MM5中的同化试验

基于中国海洋大学卫星地面站接收到的NOAA系列卫星数据,利用1种神经网络反演方法获取大气温度、湿度及风矢量垂直廓线数据。以2004年第14号台风"云娜"为例,在中尺度气象模式MM5中运用松弛逼近法对这些反演数据进行了一系列同化试验。结果表明:仅同化温度与湿度的效果比同时同化风矢量、温度与湿度的效果好;台风的路径与强度有所改善,不采用人造涡旋方案时同化效果相对采用人造涡旋方案时更能体现出改进作用。     

海洋数据同化与数据融合技术应用综述

简述了不同数据同化和数据融合方法在海洋环境监测与预测方面的应用、国内外相关业务单位的海洋分析和预报系统的现状,以及海洋数据同化将来的业务化应用的发展趋势。四维变分和集合卡尔曼滤波正在成为国际上海洋环境分析与预报的主要应用方向,海-气耦合数据同化以及海冰数据同化是目前数据同化方法研究的热点。     

一种新型的非对称台风海面气压场和风场模型

采用台风外围闭合特征等压线等要素,对圆对称的藤田气压模型进行改进,推导出不含有关参数的非对称台风海面气压场和考虑到径向梯度风的风场模型,并利用该模型对给湛江地区造成了严重风暴潮灾的几次台风过程的海面气压场和风场进行了模拟。结果表明,改进后的台风气压场和风场模型更方便准确。     

海洋科学中的数据同化方法--意义、结构与发展现状

卫星观测数据的同化技术已成为海洋动力学研究的一个有效手段。详细讨论了数据同化方法的意义、系统结构及其发展近况，并总结了海洋科学研宄中的应用及发展状况．     

Impact of Multisatellite Altimeter Data Assimilation on Wave Analysis and Forecast

Satellite altimetry has become an important discipline in the development of sea-state forecasting or more generally in operational oceanography. Météo-France Marine and Oceanography Division is much involved in altimetry, in which it is also one of the main operational customers. Sea-state forecasts are produced every day with the help of numerical models assimilating Fast Delivery Product altimeter data from ESA ERS-2 satellite, available in real-time (3–5 h). These forecasts are transmitted to seamen as part of safety mission of persons and properties, or specific assistance for particular operations. With the launch of ENVISAT (from ESA, launched on 1 March 2002, to take over the ERS mission) and JASON-1 (from CNES/NASA, launched on 7 December 2001, successor of TOPEX/Poseidon), we have an unprecedented opportunity of improved coverage with the availability in quasi-real-time of data from several altimeters. The objective of this study is to evaluate the impact of using multisources of altimeter data in real-time, to improve wave model analyses and forecasts, at global scale. Since July 2003, Météo-France injects the wind/wave JASON-1 Operational Sensor Data Record on the WMO Global Transmitting System, making them available in near real-time to the international meteorological community. Similarly, fast delivery altimeter data of ENVISAT will improve coverage and contribute to the constant progress of marine meteorology. For this purpose, significant wave height time series were generated using the Wave Model WAM and the assimilation of altimeter wave heights from two satellites ERS-2 and JASON-1. The results were then compared to Geosat Follow-On (GFO, U.S. Navy Satellite) and moored buoy wave data. It is shown that the impact of data assimilation, when two (ERS-2 and JASON-1) or three (ERS-2 with JASON-1 and GFO) sources of data are used instead of one (ERS-2), in term of significant wave height, is larger in wave model analyses but smaller in wave model forecasts. However, there is no improvement in terms of wave periods, both in the analysis and forecast periods.     

Arctic sea ice concentration and thickness data assimilation in the FIO-ESM climate forecast system

To improve the Arctic sea ice forecast skill of the First Institute of Oceanography-Earth System Model (FIO-ESM) climate forecast system, satellite-derived sea ice concentration and sea ice thickness from the Pan-Arctic Ice-Ocean Modeling and Assimilation System (PIOMAS) are assimilated into this system, using the method of localized error subspace transform ensemble Kalman ?lter (LESTKF). Five-year (2014–2018) Arctic sea ice assimilation experiments and a 2-month near-real-time forecast in August 2018 were conducted to study the roles of ice data assimilation. Assimilation experiment results show that ice concentration assimilation can help to get better modeled ice concentration and ice extent. All the biases of ice concentration, ice cover, ice volume, and ice thickness can be reduced dramatically through ice concentration and thickness assimilation. The near-real-time forecast results indicate that ice data assimilation can improve the forecast skill significantly in the FIO-ESM climate forecast system. The forecasted Arctic integrated ice edge error is reduced by around 1/3 by sea ice data assimilation. Compared with the six near-real-time Arctic sea ice forecast results from the subseasonal-to-seasonal (S2S) Prediction Project, FIO-ESM climate forecast system with LESTKF ice data assimilation has relatively high Arctic sea ice forecast skill in 2018 summer sea ice forecast. Since sea ice thickness in the PIOMAS is updated in time, it is a good choice for data assimilation to improve sea ice prediction skills in the near-real-time Arctic sea ice seasonal prediction.     

中尺度数值预报模式(MM5)在海面风场预报中的应用

本文简要介绍了在工作站上运行有限区域海面风场数值预报业务化系统的情况。该系统以MM5V3作为主要框架,选定了积云对流和边界层参数化方案,准备了三种侧边界方案,以确保有限区域海面风场数值预报业务化的运行。半年多的准业务运行表明,系统运行稳定,海面风场预报效果较好,除能直接给有关业务单位参考外,还提供给有关海洋数值预报模式使用。     

Impact of Ocean Mean Dynamic Topography on Satellite Data Assimilation

The response of an eddy-permitting ocean model to changes imposed by the use of different mean dynamic topographies (MDT) is analyzed in a multivariate assimilation context, allowing the evaluation of this impact, not only on the surface circulation, but also on the interior ocean representation. The assimilation scheme is a reduced-order sequential Kalman filter (SEEK). In a first set of experiments, high resolution sea surface temperature, along-track sea surface height and sea surface salinity from climatology are assimilated into a 1/3° resolution North and Tropical Atlantic version of the HYCOM model. In a second experiment, in situ profile data are assimilated in addition to the surface measurements.

The first set of experiments illustrates that important differences in the representation of the horizontal model circulation pattern are related to differences in the MDT used. The objective of assimilation is to improve the representation of the 3D ocean state. However, the imperfect representation of the mean dynamic topography appears to be an important limiting factor with regard to the degree of realism obtained in the simulated flow.

Vertical temperature and salinity profiles are key observations to drive a general circulation ocean model toward a more realistic state. The second set of experiments shows that assimilating them in addition to sea surface measurements is a far from trivial exercise. A specific difficulty is due to inconsistencies between the dynamic topography diagnosed from in situ observations and that diagnosed from sea surface height. These two fields obtained from different data sources do not contain exactly the same information. In order to overcome this difficulty, a strategy is proposed and validated.