A Regional Ocean Reanalysis System for Coastal Waters of China and Adjacent Seas

A regional ocean reanalysis system for the coastal waters of China and adjacent seas has been developed by the National Marine Data and Information Service(NMDIS).It produces a dataset package called CORA (China ocean reanalysis).The regional ocean model used is based on the Princeton Ocean Model with a generalized coordinate system(POMgcs).The model is parallelized by NMDIS with the addition of the wave breaking and tidal mixing processes into model parameterizations.Data assimilation is a sequential three-dimensional variational(3D-Var) scheme implemented within a multigrid framework.Observations include satellite remote sensing sea surface temperature(SST),altimetry sea level anomaly(SLA),and temperature/salinity profiles.The reanalysis fields of sea surface height,temperature,salinity,and currents begin with January 1986 and are currently updated every year. Error statistics and error distributions of temperature,salinity and currents are presented as a primary evaluation of the reanalysis fields using sea level data from tidal gauges,temperature profiles,as well as the trajectories of Argo floats.Some case studies offer the opportunity to verify the evolution of certain local circulations.These evaluations show that the reanalysis data produced provide a good representation of the ocean processes and phenomena in the coastal waters of China and adjacent seas.     

分形插值参数的遗传优化及其ARGO海温场应用试验

针对常规分形插值方法中垂直压缩因子参数无公认选择标准和有效途径的问题,提出一种分形插值的改进算法,用遗传算法对分形插值模型的垂直压缩参数进行了优化选择并进行了ARGO海温资料插值加密的对比试验。试验结果表明,经遗传优化后的分形插值方法在海温复杂细节结构和小尺度特征描述等方面较常规插值等方法更具优势,改进了分形插值结果的客观性和正确性。     

应用样条插值提高GRAPES模式物理过程反馈精度

GRAPES (Global/Regional Assimilation and PrEdiction System) 模式动力框架中垂直方向变量的跳层设置采用Charney-Phillips分布,在整层上进行位温、水物质的计算,物理过程中在半层上对其进行处理。这样在GRAPES模式中,进入物理过程之前和物理过程计算完毕之后,都要采用线性插值进行整层和半层之间物理量的转换。由于线性插值精度欠佳,为提高上述反馈过程的精度,并保证水物质的正定性,该研究引入样条插值,并在水物质的插值过程中进行保单调处理,有效减小了位温场、水物质场的预报偏差,并提升了模式的综合预报性能。     

Climate Change on Newfoundland and Labrador Shelves: Results From a Regional Downscaled Ocean and Sea-Ice Model Under an A1B Forcing Scenario 2011–2069

Climate change may affect ocean and ice conditions in coastal oceans and thus have significant impacts on coastal infrastructure, marine navigation, and marine ecosystems. In this study a three-dimensional ice–ocean model is developed to examine likely changes of ocean and ice conditions over the Newfoundland and Labrador Shelves in response to climate change. The model is configured with a horizontal grid of approximately 7?km and a vertical grid of 46 levels and is run from 1979 to 2069. The projection period is 2011 to 2069 under a median emission scenario A1B used by the Intergovernmental Panel on Climate Change. For the projection period, the surface atmospheric forcing fields used are from the Canadian Regional Climate Model over the North Atlantic. The open boundary conditions come from the Canadian Global Climate Model, Version 3 (CGCM3), adjusted for the 1981–2010 mean of the Simple Ocean Data Assimilation model output. The simulated fields over the 1981–2010 period have patterns consistent with observations. Over the Newfoundland and Labrador Shelves during the projection period, the model shows general trends of warming, freshening, and decreasing ice. From 2011 to 2069, the model projects that under A1B sea surface temperature will increase by 1.4°C; bottom temperature will increase by 1.6°C; sea surface salinity will decrease by 0.7; bottom salinity will decrease by 0.3; and sea-ice extent will decrease by 70%. The sea level will rise by 0.11?m at the St. John's tide-gauge station because of oceanographic change, and the freshwater transport of the Labrador Current will double as a result of freshening. The regional ice–ocean model reproduces more realistic present climate conditions and projects considerably different future climate conditions than CGCM3.     

样条插值在客观分析中的应用

本文用样条插值进行了高度、温度、地面气压等要素场的客观分析试验,取得了良好的结果。 本文绘出二测站的三次插值关系式,并以此为基础把二维分析问题化为有限多个一线问题,计算简单稳定,实用方便。     

GRAPES业务全球集合控制预报初值的动力升尺度方法

以生成GRAPES全球集合预报业务系统的控制预报初值为目的,基于GRAPES全球模式,开展了控制预报初值生成方法研究,发展了高分辨率初值动力升尺度方法,并检验了不同方法的可行性。通过对比不同方法产生的初始场形态,证实了仅仅对高分辨率初始场进行二维水平插值存在不足,基于静力学方程对Exner气压变量进行三维插值至关重要。结果表明,动力升尺度方法利用静力平衡关系,对全场的温压场进行调整,使之协调平衡,可以改善二维水平插值方法导致的初始位势高度场和温度场的噪音问题,产生适用于GRAPES全球集合预报业务系统的控制预报初值。     

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.     

GRAPES模式后处理技术改进应用研究

详细梳理了GRAEPS模式后处理系统的计算方案,进行了GRAPES模式后处理中海平面气压计算方案的改进,温度垂直插值方案的改进以及位势高度的垂直插值外插方案的改进等。假定温度廓线随地形高度变化并满足静力平衡条件,对海平面气压及位势高度外插进行改进,改进后海平面气压和低层等压面的位势高度场在青藏高原和南美洲西部等大地形处改进明显,均方根误差和距平相关系数改进较大并通过显著性检验。对温度垂直插值采用的原始插值层进行改进,使得高层等压面温度场的准确性进一步提高,统计检验评分在各区域都有不同程度的提高,尤其是热带地区和东亚地区高层温度场改善明显。这些都为模式产品用户提供了更可靠的数值模式产品。     

Evaluation of High-Resolution WRF Model Simulations of Surface Wind over the West Coast of India

This paper presents results from a statistical validation of the hindcasts of surface wind by a high-reso-ution-mesoscale atmospheric numerical model Advanced Research WRF （ARW3.3）, which is set up to force the operational coastal ocean forecast system at Indian Na- tional Centre for Ocean Information Services （INCOIS）. Evaluation is carried out based on comparisons of day-3 forecasts of surface wind with in situ and remote-sensing data. The results show that the model predicts the surface wind fields fairly accurately over the west coast of India, with high skill in predicting the surface wind during the pre-monsoon season. The model predicts the diurnal variability of the surface wind with reasonable accuracy. The model simulates the land-sea breeze cycle in the coastal region realistically, which is very clearly observed during the northeast monsoon and pre-monsoon season and is less prominent during the southwest monsoon season.     

Evaluation of a WRF dynamical downscaling simulation over California

This paper presents results from a 40 year Weather Research and Forecasting (WRF) based dynamical downscaling experiment performed at 12 km horizontal grid spacing, centered on the state of California, and forced by a 1° × 1.25° finite-volume current-climate Community Climate System Model ver. 3 (CCSM3) simulation. In-depth comparisons between modeled and observed regional-average precipitation, 2 m temperature, and snowpack are performed. The regional model reproduces the spatial distribution of precipitation quite well, but substantially overestimates rainfall along windward slopes. This is due to strong overprediction of precipitation intensity; precipitation frequency is actually underpredicted by the model. Moisture fluxes impinging on the coast seem to be well-represented over California, implying that precipitation bias is caused by processes internal to WRF. Positive-definite moisture advection and use of the Grell cumulus parameterization result in some decrease in precipitation bias, but other sources are needed to explain the full bias magnitude. Surface temperature is well simulated in all seasons except summer, when overly-dry soil moisture results in a several degree warm bias in both CCSM3 and WRF. Additionally, coastal temperatures appear to be too warm due to a coastal sea surface temperature bias inherited from CCSM3. Modeled snowfall/snowmelt agrees quite well with observations, but snow water equivalent is found to be much too low due to monthly reinitialization of all regional model fields from CCSM3 values.     

Dependence of the agcm climatology on the method of prescribing surface boundary conditions and its climatological implication

By using IAP 9L AGCM, two sets of long-term climatological integration have been per-formed with the two different interpolation procedures for generating the daily surface boundary conditions. One interpolation procedure is the so-called “traditional” scheme, for which the daily surface boundary conditions are obtained by linearly interpolating between the observed monthly mean values, however the observed monthly means cannot be preserved after interpolation. The other one is the “new” scheme, for which the daily surface boundary conditions are obtained by linearly interpolating between the "artificial" monthly mean values which are based on, but are dif-ferent from the observed ones, after interpolating with this new scheme, not only the observed monthly mean values are preserved, the time series of the new generated daily values is also more consistent with the observation. Comparison of the model results shows that the differences of the globally or zonally averaged fields between these two integrations are quite small, and this is due to the compensating effect between the different regions. However, the differences of the two patterns (the global or regional geographical distributions), are quite significant, for example, the magni-tude of the difference in the JJA mean rainfall between these two integrations can exceed 2 mm/day over Asian monsoon regions, and the difference in DJF mean surface air temperature can also exceed 2oC over this region. The fact that the model climatology depends quite strongly on the method of prescribing the daily surface boundary conditions suggests that in order to validate the climate model or to predict the short-term climate anomalies, either the " new* interpolation scheme or the high frequency surface boundary conditions (e.g., daily or weekly data instead of the monthly data) should be introduced. Meanwhile, as for the coupled model, the daily coupling scheme between the different component cli?mate models (e.g., atmospheric and oceanic general circulation models) is preferred in order to partly eliminate the “climate drift” problem which may appear during the course of direct coupling.     

Field significance of performance measures in the context of regional climate model evaluation. Part 1: temperature

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as “field” or “global” significance. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ^° grid resolution. Monthly temperature climatology for the 1990–2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. In winter and in most regions in summer, the downscaled distributions are statistically indistinguishable from the observed ones. A systematic cold summer bias occurs in deep river valleys due to overestimated elevations, in coastal areas due probably to enhanced sea breeze circulation, and over large lakes due to the interpolation of water temperatures. Urban areas in concave topography forms have a warm summer bias due to the strong heat islands, not reflected in the observations. WRF-NOAH generates appropriate fine-scale features in the monthly temperature field over regions of complex topography, but over spatially homogeneous areas even small biases can lead to significant deteriorations relative to the driving reanalysis. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is distribution-free, robust to spatial dependence, and accounts for time series structure.     

INTERPOLATION TECHNIQUE FOR SPARSE DATA BASED ON INFORMATION DIFFUSION PRINCIPLE-ELLIPSE MODEL

Addressing the difficulties of scattered and sparse observational data in ocean science,a new interpolation technique based on information diffusion is proposed in this paper.Based on a fuzzy mapping idea,sparse data samples are diffused and mapped into corresponding fuzzy sets in the form of probability in an interpolation ellipse model.To avoid the shortcoming of normal diffusion function on the asymmetric structure,a kind of asymmetric information diffusion function is developed and a corresponding algorithm-ellipse model for diffusion of asymmetric information is established.Through interpolation experiments and contrast analysis of the sea surface temperature data with ARGO data,the rationality and validity of the ellipse model are assessed.     

Assessment of interpolated ERA-40 reanalysis temperature and precipitation against observations of the Balkan Peninsula

Due to their ready availability and temporal and spatial consistency, reanalysis data are widely used within the climate community. Nevertheless, higher spatial resolutions are often required and statistical interpolation techniques are applied to increase the data resolution. This work aims to derive a set of high spatial resolution data through three-dimensional interpolation of daily temperature and precipitation. Thin plate spline interpolation has been chosen and used to interpolate ERA-40 temperature and precipitation from a coarse grid (110 km) into a finer one of 1-km spatial resolution. The study evaluates the method by comparing the simulated variables with available in situ meteorological measurements. The chosen stations are distributed over the study region and, most importantly, contain information from a range of altitudes. The results indicate that accounting for the topography in the interpolation process improves the comparisons, with the biggest improvements being evident in the most mountainous areas. The method is found to be better in estimating temperature than precipitation fields. Moreover, the method performs better for maximum temperature in high altitudes and for minimum temperature in low altitudes.     

Simulation of meteorological fields over a land-water-land terrain and comparison with observations

A numerical two-dimensional-mesoscale model with a level 1.5 closure scheme for turbulence is described. The model is used to simulate the boundary layer over coastal complex terrain. Meteorological data available from the Øresund land-sea-land terrain experiment are used to study the performance of the model. The model could simulate generally observed complexities in the mean wind and temperature fields. Internal boundary layers over the water and land surfaces were identified by the height of lowest value in the turbulence kinetic energy profile and this showed good agreement with radiosonde (RS) observations.Some disagreements with the data were also noticed, especially near the surface. The wind speed was over-predicted. Attempts were made to improve the model performance by adopting different schemes for model initialisation. Results showed that initialisation with an early model start time and observed wind profile near the inflow boundary improved the performance. The wind speed over-prediction could be further minimised by using a more realistic objective initialisation scheme. The problem centred around the proper estimation of the turbulent diffusion coefficient K through the closure scheme. Despite using the most popular empirical relationships in the level 1.5 closure scheme, these differences persisted. While this needs further investigation, the present model can be used to supply wind fields for practical purposes such as air pollution calculations.     

GRAPES模式标准初始化方案设计与实现

文章介绍了GRAPES模式标准初始化系统的方案设计及程序结构,对3种不同方案产生的初始场进行了分析。结果表明：水平风场、温度场、位温场对插值方法的精度并不是很敏感,而高度场以及气压Exner函数则对垂直插值方法的精度要求很高;在3种模式变量产生方案中,方案一的效果较差,但它计算速度快,在地形梯度不大的地方可以选择使用;方案二与方案三的效果则比较好,用户可根据自己的需求任意选择。GRAPES模式标准初始化系统在完成其主要功能的同时,通过灵活的程序设计,对标准初始化系统的区域、分辨率、垂直层次、水平插值方法、垂直插值方法等的任意选取,使得标准初始化系统可以很容易满足模式初值的各种需求,为模式开发研究实验提供了各种便利。     

用初始方程二层模式模拟一月和七月全球海平面气压场

用低分辨率的初始方程二层模式在给定下垫面温度下模拟了一月及七月全球海平面气压场,其中加热项主要是感热垂直输送。计算采用守恒的Lilly空间差分格式及Matsuno的时间差分格式。海平面气压的初值给成常数值,高空的风速及气温的初值给成纬向平均的气侯值。在数值模拟中,下垫面温度用一月及七月的气候实际值。计算的冬半球海平面气压与观测值相当一致,而夏半球的结果稍差些。本模式所求得的全球海平面气压场能与实况相比,结果并不差于高分辨率的复杂模式。     

Impacts of land surface and sea surface temperatures on the onset date of the South China Sea summer monsoon

The present study analyzes the differences in spatial and temporal variations of surface temperatures between early and late onset years of the South China Sea summer monsoon (SCSSM). It is found that when the land surface temperature north of 40^oN is lower (higher) and the sea surface temperature over the South China Sea-western North Pacific (SCS-WNP) is higher (lower) in winter, the onset of the SCSSM begins earlier (later). When the land surface temperature north of 40^oN is higher (lower) and the sea surface temperature over the SCS-WNP is lower (higher) in spring, the onset of the SCSSM occurs earlier (later). The reason why the anomalies of the land surface temperatures north of 40^oN can influence the atmospheric circulation is investigated by analysis of the wind and temperature fields. In order to verify the mechanisms of influence over the land and sea surface temperature distribution patterns and test the ability of the p-σ regional climate model (p-σ RCM9) to simulate the SCSSM onset, three types of years with early, normal, and late SCSSM onset are selected and the SCSSM regimes are numerically simulated. According to the results obtained from five sensitive experiments, when the land surface temperature is higher in the eastern part, north of 40^oN, and lower in the western part, north of 40^oN, and it rises faster in the eastern coastal regions and the Indian Peninsula, while the sea surface temperatures over the SCS-WNP are lower, the early onset of the SCSSM can be expected.     

基于DEM修订的新疆区域气温空间插值精度优化研究

为研究新疆地区气温的空间变异性,以新疆66个国家气象台站1981—2010年月平均气温和30 m空间分辨率DEM数据为基础,采用传统插值法、基于DEM多元线性回归插值和基于DEM修正的空间插值方法对新疆区域气温数据进行栅格化,并分析年平均气温与海拔的相关关系。通过采用反距离权重法(IDW),普通克里格法(Kriging),样条函数法(Spline)和趋势面分析法(Trend)4种空间插值方法对气象要素进行直接插值、气温多元回归模型残差结果插值、基于DEM修正插值对比分析。通过针对插值方法进行基于MAE和RMSIE的交叉验证,结果表明传统插值方法、基于多元线性回归和基于DEM修正4种空间插值精度均为IDWKrigingSplineTrend。反距离权重(IDW)空间插值方法最优,基于DEM修正IDW插值、基于多元线性回归IDW插值与传统IDW插值精度分别是0.039、0.477、1.038,插值结果客观的表达了新疆区域气温随空间梯度的变化趋势。     

1986—1987厄尔尼诺事件的数值模拟

用高分辨率自由表面热带太平洋环流模式，在观测到的风应力和热量、水汽通量驱动下，对１９８６—１９８７厄尔尼诺（Ｅ１Ｎｉｎｏ）事件进行了数值模拟。各种变量场的时空结构及其演变表明，模式成功地模拟出１９８６—１９８７厄尔尼诺现象。始于１９８６年年中，赤道西太平洋的西风异常所推动的向东表层洋流不断向中、东太平洋输送暖水，至１１月份，大量暖水在日界线附近堆积，造成海面上升（达３２ｃｍ）和斜温层（用２０℃等温线深度表示）加深。１９８６年年底的强西风异常激发出赤道Ｋｅｌｖｉｎ波，并向赤道东太平洋和南美沿岸传播，使那里的斜温层加深和海面上升，且具有双峰结构；Ｋｅｌｖｉｎ波所伴随的垂直冷平流的减弱造成赤道中、东太平洋海表温度上升；１９８７年春季在中、东太平洋和南美沿岸地区存在强的正海表温度异常，并伴随着整个赤道太平洋斜温层东西方向变平、赤道潜流弱而中心位置变浅。厄尔尼诺相伴随的热带太平洋环流异常首先于１９８７年年中从东太平洋开始消失，而中、西太平洋则一直维持到１９８８年初。