【作者】 韩珏靖；

【导师】 王元；

【作者基本信息】 南京大学 ， 气象学， 2010， 博士

【摘要】 2005年世界气象组织(World Meteorological Organization, i.e. WMO)启动了为期10年的“观测系统研究与可预报性试验”(The Observing System Research and Predictability Experiment, i.e. THORPEX)计划,其根本目的是要加速提高1-14天的天气预报准确率, THORPEX计划下的研究项目主要包括全球观测系统的设计和示范、适应性观测试验和资料同化以及可预报性分析,其中THORPEX交互式全球大集合系统(THORPEX Interactive Grand Global Ensemble, i.e. TIGGE)是THORPEX计划的核心内容。本文从THORPEX计划下中国数值模式的预报能力和改善情况的角度出发,研究包含中国气象局(China Meteorology Administration, i.e. CMA)T213模式的多中心集合预报以及T213模式的表现,分析中国飞机观测(AMDAR, Aircraft Meteorological Data Relay)的特点并最终结合T213数值产品研究其对数值预报的改善作用。主要研究内容及结果如下：1.对包括CMA(中国气象局T213模式)集合预报,NCEP (National Centers for Environmental Prediction,美国国家环境预报中心T126模式)集合预报和ECMWF (European Center for Medium range Weather Forecasting,欧洲中期天气预报中心T399模式)集合预报的多中心集合预报产品的控制试验进行确定性分析,表明ECMWF的预报技巧最高而CMA的预报技巧最差,控制试验平均(三个数据中心的控制试验的算术平均)能显著提高单中心(尤其是CMA)的预报技巧,对湿度预报技巧的改善最为显著。控制试验平均的距平相关系数的时间序列分析表明大多数预报在初始的前六天是成功的,并且夏季的距平相关系数明显比其他季节小,预示着要素的型态预报在夏季最差(比湿的季节变化相对平缓)。均方根误差的时间序列分析则显示比湿的预报误差在夏季最大,温度和位势高度的预报误差在夏季最小；距平相关系数的空间场分析表明,夏季陆地上要素的预报能力强于海上。离散度分析显示随着预报时次的延长要素的可预报性逐渐降低,根据Brier技巧评分的结果,在预报的前5～8天里集合预报(3个数据中心控制试验集合)对天气预报有显著改进,具有概率预报技巧。2.利用2003～2007年T213模式预报场和客观分析场,采用误差分析、时滞序列、奇异值分解方法(Singular Value Decomposition, i.e. SVD),综合分析了T213模式预报误差的特征。分析结果表明,相对于短期(以24 hr为例)预报,延伸期(以240 hr为例)预报的平均误差在数值上几乎增加了一个量级,120 hr以后的预报(700-hPa温度、500-hPa位势高度、850-hPa比湿和300-hPa风场)失去预报技巧。湿度预报的平均误差最大值区域一直稳定在中低纬度,其他要素(全风速、位势高度和温度)的平均误差最大值区域则随着预报时次的增加而北移。各要素的平均误差随着预报时效的增加而递增。同期的虚温误差与其他要素(位势高度、全风速)误差具有显著的正相关关系,并且在500-hPa高度上相关性达到最高。SVD诊断结果表明短期(以24 hr为例)预报的虚温误差和位势高度误差、虚温误差和全风速误差相互影响的关键区都在中国东部海上到鄂霍次克海和俄罗斯东部；延伸期(以240hr为例)预报的虚温误差和位势高度误差、虚温误差和全风速误差相互影响的关键区都在中高纬度。3.对2004～2005年中国AMDAR观测进行了一系列分析,包括对原始报文的质量控制、数据处理与时空特点分析,并以T213客观分析资料、NCEP再分析资料和探空资料为真值场,定量分析飞机报误差的特征。结果表明AMDAR资料经质量控制后其有效观测范围主要集中在中国大陆东南部和附近沿海地区,白天(00～12UTC)的观测记录几乎是夜间(13～次日00UTC)观测记录的4倍,观测高度在0.5～8000米,由此可见,AMDAR资料对我国现有的高空观测是一个有益的补充。质量控制后可用的飞机资料仅为原始报文的28%,说明中国AMDAR资料的可用率有待进一步提高。与T213客观分析资料、NCEP再分析资料和探空资料进行定量比较,飞机报温度观测的均方根误差在2℃左右,风速观测的均方根误差大约为3～4m s-1,飞机的温度观测显然比风速观测更准确,散点分布和相关系数证明了这一结论。平均而言,温度误差在低层最大,随着高度增大而略有减小,风速误差存在从低层向中层递减而后又向高层递增的趋势。就观测时次而言,00UTC时刻温度和风场的均方根误差比其他的时刻都要大。飞机资料和探空资料廓线的比较显示两者之间存在较好的匹配,尤其是温度廓线。对AMDAR资料的误差分析表明,飞机观测存在可变系统误差和周期性可变系统误差。4.对一次梅雨锋降水过程进行模拟研究,对比飞机观测资料在降水预报中的作用。结果显示在初始场中加入飞机观测能加强模式对中尺度系统的模拟能力,降水预报的强度更接近实况。风速预报误差在4 m s-1左右,温度预报误差在2～3℃之间,飞机资料在降低模式要素的预报误差上起到了积极的作用。更多还原

【Abstract】 THORPEX (The Observing System Research and Predictability Experiment) is a 10-year international research and development programme sponsored by WMO (World Meteorological Organization) to accelerate improvements in the accuracy of one-day to two-week high impact weather forecasts for the benefit of society, the economy and the environment stewardship. Its sub-programmes mainly include global observing system design and demonstration、targeting and assimilation of observations、predictability research, among which TIGGE (THORPEX Interactive Grand Global Ensemble) is a key component of THORPEX. Therefore, this paper is focused on the prediction ability and improvement of CMA (China Meteorology Administration) T213 model under THORPEX background, analysis of the MCGE (Multi-Center Grand Ensemble) which includes T213 forecast and the performance of single T213 prediction is presented, as well as the characteristics of China AMDAR (Aircraft Meteorological Data Relay) reports. Finally, a model test with T213 products illustrating the improvement of numerical prediction by the use of AMDAR data is given. The main conclusions are summarized as follows:1. In order to evaluate the forecasting ability of TIGGE control data, a verification is conducted on products of China Meteorology Administration (CMA T213 model)、National Centers for Environmental Prediction (NCEP T126 model) and European Center for Medium range Weather Forecasting (ECMWF T399 model) of TIGGE project for the 12 month time period of 1 Feb.2008 to 31 Dec.2008. Results of deterministic verification illustrate that the forecast skill of ECMWF is the best while that of CMA is the worst, furthermore, mean value of the control runs of three EPSs involved in the Multi-Center Grand Ensemble (MCGE) (hereafter control mean) could improve the forecast skill of single center (greastest improvement for CMA), especially for specific humidity. Analysis of Anomaly Correlation Coefficient (ACC) time series shows that most forecasts are successful to day 6, meanwhile the daily forecast exhibits a seasonal trend that the prediction accuracy in summer is poorer than other seasons, the seasonal variation is slight for specific humidity. Root Mean Square Error (RMSE) time series analysis illustrates that forecast error of specific humidity is the worst in summer, while forecast error of temperature and geo-potential height in summer is smaller than other seasons. Spatial analysis of control mean data in summer shows the forecast ability on land is better than that over ocean. Probabilistic verifications of spread indicate forecast probabilities decrease as the forecast time increases, according to the Brier Skill Score (BSS) analysis, the potential improvement over the climatological forecast is good for 5-8 days onward.2. In order to evaluate the forecasting ability of Chinese mid-range numerical weather prediction model-T213, error analysis、lag correlation and singular value decomposition (SVD) are performed on the forecasting field and objective analysis fields of T213 model from 2003 to 2007. Results show that the average error of extended-range forecast (240 hr) is nearly a magnitude larger than that of short-term forecast (24 hr), the forecast result is not so good after 120 hr (for 700-hPa temperature、500-hPa geo-potential height、850-hPa specific humidity and 300-hPa wind). The maximum error region of specific humidity is steady at middle-low latitude, while the maximum error region of other variables (resultant wind、geo-potential height and temperature) of 240 hr is further north than that of 24 hr. The average error of variables increases with the forecasting time increasing. There is a distinct positive correlation between virtual temperature error and geo-potential height (or resultant wind) error at the same prediction time, and the correlation coefficient is largest at 500-hPa.24-h SVD analysis shows, the key area for the influence between virtual temperature error and geo-potential height (or resultant wind) error locates off the coast of East China、Sea of Okhotsk and over eastern Russia. SVD analysis of 240 hr forecasting field indicates the key area for the influence between virtual temperature error and geo-potential height (or resultant wind) error locates consistently in mid-high latitude.3. A study of meteorological reports from Aircraft Meteorological Data Relay (AMDAR) System has been performed to estimate the characteristics of observation errors. Results show that the spatio-temporal distribution of data is non-uniformed: after quality control (QC) AMDAR reports mainly locate on southeast China and the littoral nearby, diurnal observations (00～12UTC) are much more than nightly observations (13～00UTC), and the height of data is from 0.5 to 8000 meters. Valid number of AMDAR reports after QC is almost 28% of original data, which indicates that the usability has to be improved. Results of comparison between AMDAR reports and T213 objective data、between AMDAR reports and NCEP reanalysis data and between AMDAR reports and sounding data illustrate that RMSE of temperature and wind are around 2℃and 3～4 m s-1 respectively, temperature observation is more accurate than wind, which is also proved by scatter plot and correlation coefficient analysis. On average, temperature error is largest in low level and slightly decreases with the increase of height, while wind error decreases from low to middle level and then increases to high level. RMSE of temperature and wind at 00UTC are larger than other observation time. Profile comparison of AMDAR reports and sounding data shows temperature and wind matches well, especially for temperature. According to error analysis, variable systematic error and periodic systematic error are likely to be included in observation data.4. A simulation of Mei-Yu front associated with heavy rainfall in 2005 are studied in order to testify the influence of aircraft observations on NWP (Numerical Weather Prediction) model forecast performance. Analysis shows that with the modification of first-guess field by AMDAR data, there is a positive impact on mesoscale simulation, and the rain intensity are more consistent with the observation. Forecast error of wind speed is around 4 ms-1, temperature forecast error is from 2 to 3℃, the accuracy rate is improved by AMDAR data.更多还原