VERIFICATION OF TYPHOON FORECASTS BY THE GRAPES MODEL

Four landfalling typhoon cases in 2005 were selected for a numerical simulation study with the Global/Regional Assimilation and Prediction System (GRAPES) model. The preliminary assessment results of the performance of the model, including the predictions of typhoon track, landfall time, location and intensity, etc., are presented and the sources of errors are analyzed. The 24-hour distance forecast error of the typhoon center by the model is shown to be about 131 km, while the 48-hour error is 252 km. The model was relatively more skilful at forecasts of landfall time and locations than those of intensity at landfall. On average, the 24-hour forecasts were slightly better than the 48-hour ones. An analysis of data impacts indicates that the assimilation of unconventional observation data is essential for the improvement of the model simulation. The model could also be improved by increasing model resolution to simulate the mesoscale and fine scale systems and by improving methods of terrain refinement processing.     

ASSIMILATION OF OBSERVED SURFACE WIND WITH GRAPES

With the advances of numerical weather simulation and reduced data assimilation updating cycle, surface observation data assimilation becomes more and more important in data assimilation systems. It is widely accepted that a better data assimilation system should contain the restriction of thermodynamic processes in the surface layer. Therefore, in this paper, a new surface wind observation operator is utilized in Global and Regional Assimilation PrEdiction System_3D-Variance (GRAPES_3D-Var), with the restriction of thermodynamic process in the planetary boundary layer (PBL). In order to research the ability of this new surface wind observation operator in assimilation and forecasting, a series of experiments are operated by using the GRAPES model. The main results indicate that this new method of surface wind observation operator has positive impact on the forecast with the GRAPES model.     

GRAPES与MM5产品业务应用质量对比

分别以GRAPES和MM5为核心建立中尺度数值预报业务系统,并对2006年6～8月温度和降水预报产品业务应用效果进行严格的检验。结果表明:GRAPES和MM5对黑龙江省都具有较强的预报能力,温度预报两者相当,24h降水预报GRAPES总体好于MM5,48h降水预报MM5总体好于GRAPES。两个中尺度数值预报业务系统的产品,对实现精细化预报有重要的作用,可以作为加工预报产品的基础。     

GRAPES模式切线性垂直扩散方案的误差分析和改进

针对GRAPES四维变分同化系统的升级, 研究了GRAPES模式垂直扩散方案线性化问题。通过2005年8月7—27日21个个例的批量试验, 发现在GRAPES模式垂直扩散方案源代码的基础上逐句线性化得到的切线性垂直扩散方案即使能通过正确性测试试验, 在少数情况下也会存在很大误差。切线性模式计算的扰动气压场和扰动风场可能出现明显异常, 这种异常与垂直扩散方案中地表动量通量的强非线性有关。如果在切线性垂直扩散方案中忽略地表动量通量扰动, 既可以避免异常的出现, 又不影响其他正常时刻的计算精度。修改后的切线性垂直扩散方案能够在所有变量上一致地提高切线性模式的计算精度。     

Possible Sources of Forecast Errors Generated by the Global/Regional Assimilation and Prediction System for Landfalling Tropical Cyclones. Part Ⅱ: Model Uncertainty

This paper investigates the possible sources of errors associated with tropical cyclone (TC) tracks forecasted using the Global/Regional Assimilation and Prediction System (GRAPES). In Part I, it is shown that the model error of GRAPES may be the main cause of poor forecasts of landfalling TCs. Thus, a further examination of the model error is the focus of Part II. Considering model error as a type of forcing, the model error can be represented by the combination of good forecasts and bad forecasts. Results show that there are systematic model errors. The model error of the geopotential height component has periodic features, with a period of 24 h and a global pattern of wavenumber 2 from west to east located between 60°S and 60°N. This periodic model error presents similar features as the atmospheric semidiurnal tide, which reflect signals from tropical diabatic heating, indicating that the parameter errors related to the tropical diabatic heating may be the source of the periodic model error. The above model errors are subtracted from the forecast equation and a series of new forecasts are made. The average forecasting capability using the rectified model is improved compared to simply improving the initial conditions of the original GRAPES model. This confirms the strong impact of the periodic model error on landfalling TC track forecasts. Besides, if the model error used to rectify the model is obtained from an examination of additional TCs, the forecasting capabilities of the corresponding rectified model will be improved.     

适用于GRAPES模式C-P边界层方案的设计和实现

基于K廓线闭合方案,通过考虑不稳定边界层和稳定边界层中热量交换系数在半层上求取及下边界条件的设置,将温湿倾向在整层上直接计算,设计了Charney-Phillips跳点（简称C-P跳点）的边界层方案,使之与GRAPES全球模式的C-P跳点相协调,解决了Lorenz跳点物理过程与C-P跳点动力框架耦合时插值造成的不协调问题,同时避免了耦合时反复插值造成的误差,提高了边界层物理过程参数化方案及其反馈的准确性和合理性。试验表明:C-P跳点边界层方案因为避免了温度和湿度在垂直方向上的插值,消除了温湿变量在垂直方向上的锯齿状抖动,使温湿廓线分布更合理,减小了模式预报误差,形势场的预报效果也得到一定改善。C-P边界层方案的应用提升了GRAPES全球模式的总体预报性能。     

GRAPES全球切线性和伴随模式的调优

伴随技术是四维变分同化（4DVar）系统中计算代价函数梯度的最佳办法,切线性和伴随模式的效果和效率直接影响着4DVar系统的发展。基于GRAPES（Global and Regional Assimilation PrEdiction System）全球切线性和伴随模式1.0版本,利用GRAPES全球模式2.0版本在并行框架和性能等方面的改善,重新优化和设计了GRAPES全球切线性伴随模式2.0版本,提高了GRAPES全球切线性和伴随模式的效果和效率,优化了切线性模式程序结构,使其计算时间最优可控制在非线性模式的1.2倍以内;采用在切线性模式中保存基态的方法,重构了伴随模式的程序结构,使其计算时间最优控制在非线性模式的1.5倍以内;在GRAPES全球切线性物理过程的设计中,将线性物理过程的轨迹基态计算和切线性扰动计算解耦,提高了GRAPES全球切线性和伴随模式的计算效果和效率。     

COSMIC掩星资料同化对台风“天兔”预报影响的试验

台风数值预报的关键之一在于给定准确的模式初始场。本文使用气象、电离层和气候星座观测系统(COSMIC)的卫星资料,通过资料同化技术改善数值天气预报模式的初始场,进而评估数据同化技术对台风(或热带气旋)预报的改善效果。使用我国自主研发的数值天气预报模式,对1319号台风“天兔”进行模拟试验,对温度场、湿度场、涡度散度场及假相当位温场进行诊断分析。试验结果表明,与同化常规探空资料相比,COSMIC资料的同化可减小模式预报台风路径误差,台风附近降水落区更为集中。研究评估了掩星资料同化对模式的改进作用,并能为台风预报技术和防灾减灾提供参考。     

华南复杂地形下GRAPES_Meso3km对流尺度模式前汛期精细化降水预报评估

为深入认识GRAPES_Meso(Global/Regional Assimilation and Prediction System)3 km对流尺度区域模式对华南前汛期精细化降水的预报性能,为模式改进及业务应用提供参考依据,利用广东省86个站点逐小时观测降水资料和国家气象信息中心多源融合降水资料,针对广东省复杂地形特点,结合距海岸线的远近及站点地形特点,将86个站划分为沿海东部、沿海西部和内陆地区三个子区域,采用二分类降水预报检验方法,定量评估了2020年5月18日—6月18日华南前汛期降水预报效果。结果显示,GRAPES_Meso 3 km模式精细化降水预报技巧受广东复杂地形影响较大,广东沿海东部和内陆地区24 h时累积降水的小雨、中雨、大雨量级预报成功指数(Threat Score,TS)、公平成功指数(Equitable Threat Score,ETS)评分高于沿海西部地区,尽管暴雨预报评分具有此相同特征,但三个子区域的暴雨预报评分总体较低;从3 h累积降水预报评分看,沿海东部、沿海西部及内陆地区等三个子区域存在明显的日变化特征,但是沿海东部及西部与内陆地区表现有所不同,沿海东部和西部降水预报评分夜间较低(预报偏差偏高),白天相对较高(预报偏差偏低),而内陆地区则是夜间较高(预报偏差偏低),白天相对较低(预报偏差偏高)。沿海西部预报评分相对较低的原因是由于检验时段内广东地区存在一个弱的风切变,而沿海西部大部分地区正好处于切变线南侧的温度高值区控制,但模式模拟该区域的日平均温度较实况偏低,导致沿海西部模式预报降水空报较多,降低其降水预报技巧。     

基于扰动模式的四维变分资料同化系统框架的设计完善和数值试验

为了建立一个应用于区域数值预报的四维变分资料同化（4DVar）系统,在近期开发的扰动预报模式GRAPES_PF基础上,开发完善增量四维变分同化系统框架。该框架中暂不包含物理过程（长短波辐射、边界层过程、对流参数化和云微物理等）。对比业务使用的GRAPES 3DVar系统,增加了温度控制变量。将无量纲Exner气压与流函数的线性风压平衡方程直接在地形追随垂直坐标面上求解,且通过广义共轭余差法（GCR）求解扰动亥姆霍兹（Helmholtz）伴随方程。利用人造“探空”资料对2015年10月台风“彩虹”进行了理想数值试验。试验结果表明,所开发的扰动四维变分同化框架得到了预期的结果,即同化更多资料并反复受到模式约束的四维变分同化系统能有效改善初值质量,进而改善区域数值预报。建立的区域四维变分同化框架合理可行,为进一步发展包含完整物理过程的区域四维变分同化系统奠定了研究基础。