Interannual-to-decadal variability of the North Atlantic from an ocean data assimilation system

An ocean analysis, assimilating both surface and subsurface hydrographic temperature data into a global ocean model, has been produced for the period 1958–2000, and used to study the time and space variations of North Atlantic upper ocean heat content (HC). Observational evidence is presented for interannual-to-decadal variability of upper ocean thermal fluctuations in the North Atlantic related to the North Atlantic Oscillation (NAO) variability over the last 40 years. The assimilation scheme used in the ocean analysis is a univariate, variational optimum interpolation of temperature. The first guess is produced by an eddy permitting global ocean general circulation forced by atmospheric reanalysis from the National Center for Environmental Prediction (NCEP). The validation of the ocean analysis has been done through the comparison with objectively analyzed observations and independent data sets. The method is able to compensate for the model systematic error to reproduce a realistic vertical thermal structure of the region and to improve consistently the model estimation of the time variability of the upper ocean temperature. Empirical orthogonal function (EOF) analysis shows that an important mode of variability of the wintertime upper ocean climate over the North Atlantic during the period of study is characterized by a tripole pattern both for SST and upper ocean HC. A similar mode is found for summer HC anomalies but not for summer SST. Over the whole period, HC variations in the subtropics show a general warming trend while the tropical and north eastern part of the basin have an opposite cooling tendency. Superimposed on this linear trend, the HC variability explained by the first EOF both in winter and summer conditions reveals quasi-decadal oscillations correlated with changes in the NAO index. On the other hand, there is no evidence of correlation in time between the NAO index and the upper ocean HC averaged over the whole North Atlantic which exhibits a substantial and monotonic warming trend during the last two decades of the analysis period. The maximum correlation is found between the leading principal component of winter HC anomalies and NAO index at 1 year lag with NAO leading. For SST anomalies significant correlation is found only for winter conditions. In contrast, for HC anomalies high correlations are found also in the summer suggesting that the summer HC keeps a memory of winter conditions.     

A comparison of two methods for the assimilation of altimeter data into a shallow-water model

Two simple methods for assimilating ocean surface pressure data into a three-layer adiabatic primitive equation model are tested and compared using a twin-experiment approach. One of the methods is based on a recently presented direct insertion scheme using a quasi-geostrophic model. The method explicitly avoids making changes to the potential vorticity fields in the lower layers and the vertical current structure after assimilation is determined by this criterion. The modification required for a primitive equation framework are discussed and a comparison is made with the more familiar ‘nudging’ method of assimilation. We use root mean square errors to quantify the response of the model to the assimilation of a single complete surface pressure field and also to repeated or intermittent data available every 20 days for a period of 1 year. The two methods are almost equally effective in the short term, although the direct insertion scheme appears to be more effective in the longer term. It is suggested that this is because insertion maintains a geostrophic balance at all levels and thus avoids the generation of internal gravity waves which are needed when nudging is used to restore geostrophic currents in the deeper layers.     

An ocean data assimilation system in the Indian Ocean and west Pacific Ocean

The development and application of a regional ocean data assimilation system are among the aims of the Global Ocean Data Assimilation Experiment. The ocean data assimilation system in the regions including the Indian and West Pacific oceans is an endeavor motivated by this goal. In this study, we describe the system in detail. Moreover, the reanalysis in the joint area of Asia, the Indian Ocean, and the western Pacific Ocean(hereafter AIPOcean) constructed using multi-year model integration with data assimilation is used to test the performance of this system. The ocean model is an eddy-resolving,hybrid coordinate ocean model. Various types of observations including in-situ temperature and salinity profiles(mechanical bathythermograph, expendable bathythermograph, Array for Real-time Geostrophic Oceanography, Tropical Atmosphere Ocean Array, conductivity–temperature–depth, station data), remotely-sensed sea surface temperature, and altimetry sea level anomalies, are assimilated into the reanalysis via the ensemble optimal interpolation method. An ensemble of model states sampled from a long-term integration is allowed to change with season, rather than remaining stationary. The estimated background error covariance matrix may reasonably reflect the seasonality and anisotropy. We evaluate the performance of AIPOcean during the period 1993–2006 by comparisons with independent observations, and some reanalysis products. We show that AIPOcean reduces the errors of subsurface temperature and salinity, and reproduces mesoscale eddies. In contrast to ECCO and SODA products, AIPOcean captures the interannual variability and linear trend of sea level anomalies very well. AIPOcean also shows a good consistency with tide gauges.     

An upper ocean general circulation model for climate studies: global simulation with seasonal cycle

The global ocean circulation with a seasonal cycle has been simulated with a two-and-a-half layer upper-ocean model. This model was developed for the purpose of coupling to an atmospheric general circulation model for climate studies on decadal time scales. The horizontal resolution is 4° latitude by 5° longitude and is thus not eddy-resolving. Effects of bottom topography are neglected. In the vertical, the model resolves the oceanic mixed layer and the thermocline. A thermodynamic sea-ice model is coupled to the mixed layer. The model is forced at the surface with seasonally varying (a) observed wind stress, (b) heat fluxes, as defined by an atmospheric equilibrium temperature, and (c) Newtonian-type surface salt fluxes. The second layer is coupled to the underlying deep ocean through Newtonian-type diffusive heat and salt fluxes, convective overturning, and mass entrainment in the upwelling regions of the subpolar gyres. The overall global distributions of mixed layer temperature, salinity and thickness are favorably reproduced. Inherent limitations due to coarse horizontal resolution result in large mixed-layer temperature errors near continental boundaries and in weak current systems. Sea ice distributions agree well with observations except in the interiors of the Ross and Weddell Seas. A realistic time rate of change of heat storage is simulated. There is also realistic heat transport from low to high latitudes.     

A zonally averaged,three-basin ocean circulation model for climate studies

A two-dimensional, three-basin ocean model suitable for long-term climate studies is developed. The model is based on the zonally averaged form of the primitive equations written in spherical coordinates. The east-west density difference which arises upon averaging the momentum equations is taken to be proportional to the meridional density gradient. Lateral exchanges of heat and salt between the basins are explicitly resolved. Moreover, the model includes bottom topography and has representations of the Arctic Ocean and of the Weddell and Ross seas. Under realistic restoring boundary conditions, the model reproduces the global conveyor belt: deep water is formed in the Atlantic between 60 and 70°N at a rate of about 17 Sv (1 Sv=10⁶ m3 s^–1) and in the vicinity of the Antarctic continent, while the Indian and Pacific basins show broad upwelling. Superimposed on this thermohaline circulation are vigorous wind-driven cells in the upper thermocline. The simulated temperature and salinity fields and the computed meridional heat transport compare reasonably well with the observational estimates. When mixed boundary conditions (i.e., a restoring condition on sea-surface temperature and flux condition on sea-surface salinity) are applied, the model exhibits an irregular behavior before reaching a steady state characterized by self-sustained oscillations of 8.5-y period. The conveyor-belt circulation always results at this stage. A series of perturbation experiments illustrates the ability of the model to reproduce different steady-state circulations under mixed boundary conditions. Finally, the model sensitivity to various factors is examined. This sensitivity study reveals that the bottom topography and the presence of a submarine meridional ridge in the zone of the Drake Passage play a crucial role in determining the properties of the model bottom-water masses. The importance of the seasonality of the surface forcing is also stressed.     

The impact of inhomogenous background errors on a global wave data assimilation system

One of the main limitations in current wave data assimilation systems is the lack of an accurate representation of the structure of the background errors. In this work, models for the observational error variance, background error variance and background error correlations are developed based on the results of previous studies. These are tested in a global wave data assimilation system and the resulting wave forecasts are verified against independent observations from buoys. Forecasts of significant wave height show substantial improvement over the Australian Bureau of Meteorology's current operational wave forecasting system. However, forecasts of peak period are not similarly improved. The regional impacts of the new assimilation scheme are found to vary on a seasonal basis. Overall, it is shown that the inclusion of a latitudinally dependent background error, and improved specification of the background and observational error variances can reduce the root-mean-square error of 24-hour forecast Significant Wave Height by almost 10%.     

从GTS获得的海洋温、盐资料在BCC海洋同化系统中的质量控制及同化结果初步分析

介绍了从全球电信系统(GTS)上获得的海洋温度、盐度观测资料在中国国家气候中心(BCC)新一代海洋同化系统中的应用情况。通过资料的质量控制判断温、盐观测的重复记录、观测深度、地形、极端值、气候变率、层结、空间差异,有效地过滤了错误的或不可靠的观测信息。质量控制后,将温、盐观测资料加入同化系统,有效地改进了模块化全球海洋环流模式MOM4中的全球热带、副热带海洋,尤其是太平洋地区的多年平均海表温度、盐度场分布特征;此外,同化温、盐资料对南北半球中纬度地区的海表温度分布特征也有明显的改进。对比同化前后的均方根误差(RMSE)发现,同化后大部分海区,尤其是热带海洋的海表温度/盐度的均方根误差明显降低,降幅通常在0.1—1.0℃/psu,模拟与观测的海表温、盐分布特征也更为接近。进一步分析指出,同化明显地改善了模式对Nino3、Nino4区海温时间演变特征的模拟,同化后的Nino3海温与最优插值海表温度的差异减小,但其通常在上半年改进较多(差值绝对值多在0.5℃左右),而在下半年则改进较少(差值绝对值常达1℃左右);Nino4区的海温特征则改进明显,其与最优插值海表温度的差值绝对值通常都控制在0.5℃以下。     

The Interannual Variability and Predictability in a Global Climate Model

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A study on combining global and regional climate model results for generating climate scenarios of temperature and precipitation for the Netherlands

Climate scenarios for the Netherlands are constructed by combining information from global and regional climate models employing a simplified, conceptual framework of three sources (levels) of uncertainty impacting on predictions of the local climate. In this framework, the first level of uncertainty is determined by the global radiation balance, resulting in a range of the projected changes in the global mean temperature. On the regional (1,000–5,000 km) scale, the response of the atmospheric circulation determines the second important level of uncertainty. The third level of uncertainty, acting mainly on a local scale of 10 (and less) to 1,000 km, is related to the small-scale processes, like for example those acting in atmospheric convection, clouds and atmospheric meso-scale circulations—processes that play an important role in extreme events which are highly relevant for society. Global climate models (GCMs) are the main tools to quantify the first two levels of uncertainty, while high resolution regional climate models (RCMs) are more suitable to quantify the third level. Along these lines, results of an ensemble of RCMs, driven by only two GCM boundaries and therefore spanning only a rather narrow range in future climate predictions, are rescaled to obtain a broader uncertainty range. The rescaling is done by first disentangling the climate change response in the RCM simulations into a part related to the circulation, and a residual part which is related to the global temperature rise. Second, these responses are rescaled using the range of the predictions of global temperature change and circulation change from five GCMs. These GCMs have been selected on their ability to simulate the present-day circulation, in particular over Europe. For the seasonal means, the rescaled RCM results obey the range in the GCM ensemble using a high and low emission scenario. Thus, the rescaled RCM results are consistent with the GCM results for the means, while adding information on the small scales and the extremes. The method can be interpreted as a combined statistical–dynamical downscaling approach, with the statistical relations based on regional model output.     

Observational and modelling studies of Amazonia interannual climate variability

The interannual variability of climate in the Amazon basin is studied using precipitation and river level anomalies observed near the March/April rainy season peak for the period 1980–86, supported by satellite imagery of tropical convection. Evaluation of this data in conjunction with the corresponding circulation and sea-surface temperature (SST) anomaly patterns indicates that abundant rainy seasons in Northern Amazonia are characterized by anomalously cold surface waters in the tropical eastern Pacific, and negative/positive SST anomalies in the tropical North/South Atlantic, accelerated Northeast trades and a southward displaced Intertropical Convergence Zone (ITCZ) over the Atlantic sector. Years with deficient rainfall show broadly opposite patterns.General circulation model (GCM) experiments using observed SST in three case studies were aimed at testing the teleconnections between SST and Amazon climate implied by the empirical analysis. The GCM-generated surface fields resemble the corresponding observers fields most closely over the tropical Pacific and, with one exception, over the tropical Atlantic as well. The modeled precipitation features, along the Northwest coast of South America, anomalies of opposite sign to the North and South of the equator, in agreement with observations and results from a different GCM. Similarities in simulations run from different initial conditions, but using the same global SST, indicate broad consistency in response to common boundary forcing.     

Evaluation of ocean data assimilation in CAS-ESM-C: Constraining the SST field

A weakly coupled assimilation system, in which SST observations are assimilated into a coupled climate model(CASESM-C) through an ensemble optimal interpolation scheme, was established. This system is a useful tool for historical climate simulation, showing substantial advantages, including maintaining the atmospheric feedback, and keeping the oceanic fields from drifting far away from the observation, among others. During the coupled model integration, the bias of both surface and subsurface oceanic fields in the analysis can be reduced compared to unassimilated fields. Based on 30 model years of output from the system, the climatology and interannual variability of the climate system were evaluated. The results showed that the system can reasonably reproduce the climatological global precipitation and SLP, but it still suffers from the double ITCZ problem. Besides, the ENSO footprint, which is revealed by ENSO-related surface air temperature, geopotential height and precipitation during El Ni ?no evolution, is basically reproduced by the system. The system can also simulate the observed SST–rainfall relationships well on both interannual and intraseasonal timescales in the western North Pacific region, in which atmospheric feedback is crucial for climate simulation.     

WRF-EnSRF卫星资料同化模块的构建研究

为加强国内卫星资料在同化系统中的应用,在自主构建的新一代WRF-EnSRF同化系统中,采用RTTOV辐射传输模式作为观测算子,并建立卫星资料读取、偏差订正及质量控制等子模块,构建出WRF-EnSRF卫星资料同化系统.运用该同化系统,同时同化NOAA-16的AMSU-A和AMSU-B的辐射率资料,进行华南暴雨过程的卫星资料同化数值模拟试验.试验结果表明:偏差订正后亮温资料拟合结果基本位于主对角线上,偏差有所降低.从TS评分看,同化试验对中雨及大雨部分的降水落区以及暴雨级别以上的降水强度的模拟效果有改善.试验证明,建立的卫星同化系统是可运行的.     

数值天气预报业务模式现状与展望

基于新疆区域同化预报系统（简称“DOGRAFS”）,选取新疆伊犁河谷地区2016年7月31日—8月1日的强降水过程,利用常规观测资料和卫星微波辐射资料进行同化敏感试验,其中控制试验仅同化常规地面和探空资料,敏感试验在常规观测基础上分别增加微波温度（AMSU-A）、湿度（MHS）和温、湿度（AMSU-A、MHS）资料,并对2016年7月进行连续试验,以初步探究卫星微波温、湿度资料同化对新疆降水预报的影响。从关键要素增量的垂直和水平分布来看,仅同化AMSU-A资料与同时同化AMSU-A和MHS资料对初始场温度、位势高度和湿度的调整均比较显著,其低层温度和位势高度为正增量,中、高层为负增量,湿度场增量中心集中在800—600 hPa。而仅同化MHS资料对温度和位势高度的影响较小,对湿度场有所“微调”,但可更好地修正补充降水过程中的水汽信息。从降水预报和客观检验结果来看,同化AMSU-A资料总体为负效果;而同化MHS资料对于整个降水落区和大阈值降水的预报均有明显优势。

     

REM模式伴随系统的建立及其四维变分资料同化初步试验

Regional-Eta-Coordinate-Model（REM）中尺度模式对中国区域性降水显示出公认的较高预报能力,建立其四维变分资料同化系统是完善该模式,进一步提高其预报效果的重要工作。本研究编写了REM模式的切线性模式和伴随模式,介绍了建立REM模式伴随系统的过程,并利用实际天气个例资料,分别对REM模式的切线性模式、伴随模式及定义的目标函数梯度进行了正确性检验,检验结果表明对REM模式的切线性模式及伴随模式编写是成功的。利用REM模式的伴随系统,对1998年06月08日00时到09日00时和2000年08月01日00时到02日00时两个实际天气个例进行了四维变分资料同化试验。从数值试验的结果分析可以看到,进行四维变分资料同化后,两个天气个例在预报结束时刻其预报结果对风场和湿度场的预报都有明显改善,对温度场和高度场的预报也有所改善。对于累积降水的预报,两个个例利用四维变分资料同化后得到的初始场进行的预报结果则有较大不同,在个例1中,变分同化后对降水中心的位置和降水强度的预报都有明显改善,预报结果更接近于观测场;个例2中,变分同化后对降水中心位置和强度的预报则没有改善,产生这种现象的原因可能是由于定义的目标函数中没有加进背景场项,也可能是由于采用的观测资料时次比较少,还需要进一步进行研究和试验。     

The climatology and interannual variability of the East Asian summer monsoonsimulated by a weakly coupled data assimilation system

为了改进耦合模式对东亚夏季风的模拟,本文发展了一个基于中国科学院地球系统模式的海洋资料同化系统。基于该同化系统,本文开展了同化观测海温的试验,并将同化试验的结果与传统的AMIP试验进行比较。结果表明,同化系统显著改进了对西北太平洋地区降水的气候态和季节循环、与ENSO和东亚夏季风相关联的东亚地区的降水和环流异常等的模拟。本文的工作表明,海气相互作用对东亚夏季风的模拟非常重要。耦合框架下的海洋资料同化系统可以在引入观测信息的同时不切断海气相互作用,这是同化试验较之AMIP试验有显著改进的原因所在。     

A new strategy for global climate protection

This essay proposes an innovative institutional strategy for global climate protection, quite distinct from but ultimately complementary to the UNFCCC climate treaty negotiations. Our “building block” strategy relies on a variety of smaller-scale transnational cooperative arrangements, involving not only states, but also subnational jurisdictions, firms, and civil society organizations, to undertake activities whose primary goal is not climate mitigation but which will achieve greenhouse gas reductions as a byproduct. This strategy avoids the problems inherent in developing an enforceable, comprehensive treaty regime by mobilizing other incentives—including economic self-interest, energy security, cleaner air, and furtherance of international development— to motivate a range of actors to cooperate on actions that will also produce climate benefits. The strategy uses three specific models of regime formation (club, linkage, and dominant actor models) which emerge from economics, international relations, and organizational behavior, to develop a variety of transnational regimes that are generally self-enforcing and sustainable, avoiding the free rider and compliance problems endemic in collective action to provide public goods. These regimes will contribute to global climate action not only by achieving emissions reductions in the short term, but also by creating global webs of cooperation and trust, and by linking the building block regimes to the UNFCCC system through greenhouse gas monitoring and reporting systems. We argue that the building blocks regimes would thereby help secure eventual agreement on a comprehensive climate treaty.     

A global analysis of austral summer ocean wave variability during SAM–ENSO phase combinations

Anticipating and mitigating wave-related hazards rely heavily on understanding wave variability drivers. Here, we describe wave conditions related to concurrent Southern Annular Mode (SAM) and El Niño–Southern Oscillation (ENSO) phases during the austral summer. To identify such conditions, significant wave height (Hs) and peak wave period (Tp) daily anomalies were composited during different SAM–ENSO phase combinations over the last four decades (1979–2018). Surface wind anomalies were also composited to assist in the interpretation of wave conditions. The composites show significant wave variability across all ocean basins and in several semi-enclosed seas throughout the different SAM–ENSO phase combinations. The Southern, Indian, and Pacific Oceans generally experience the strongest Tp anomalies during combinations of SAM phases with El Niño, and the weakest Tp anomalies during combinations of SAM phases with La Niña. The anomalously large waves observed in the south-western Pacific, Tasman Sea, and the Southern Ocean, previously ascribed to ENSO conditions, seem to be instead associated with the SAM variability. SAM-related atmospheric conditions are found to be able to modulate the intensity of ENSO-related winds over the South China Sea, which, in turn, alter the magnitude of waves in that region. These and other wave anomaly structures described here, especially those contrasting the behaviour expected for a given ENSO phase, such as the one found along the California coast, stress the importance of understanding relationships between wave parameters and climate patterns interactions.