区域气候预报自忆模式的研究与计算

从一个区域气候预报自忆模式出发,运用１９５１￣１９９７年江苏省月温度,降水和区域５００ｈＰａ高度场格点资料,确定了自忆函数的具体形式,研究了它的周期性,试作了江苏省１９８７￣１９９７年汛期降水和温度预报。     

长江三角洲汛期预报模式的研究及其初步应用

在短期自忆气候模式的基础上 ,着重考虑了区域性降水特点 ,组合均生函数时序模型 ,构造了区域降水预报模式。以降水预报为实例 ,计算表明 ,它能滚动制作月、季、年降水预报 ,尤其对汛期 (6～ 8月 )降水预报 ,具有相当好的预报能力。     

利用OSU/NCC模式进行我国汛期季度和年度短期气候预测的试验

该文利用OSU/NCC全球大气环流模式耦合全球混合层海洋与海冰模式, 采用集合预报的方法, 对中国汛期降水进行了1982~1995年共14年的季度和年度综合性预报试验研究.结果表明:该模式对我国汛期降水具有一定的季度和年度预报能力, 而对部分地区有较强的预报能力.     

最优多因子动态配置的东北汛期降水相似动力预报试验

基于中国气象局国家气候中心季节预报业务模式27a(1983—2009年)预报结果和同期美国气候预报中心组合降水分析(CMAP)资料及国家气候中心气候系统诊断预报室74项环流指数和NOAA40个气候指数(1951—2009年),提出了客观定量化的最优多因子动态配置汛期降水相似-动力预测新技术,并对中国东北地区汛期降水进行了预报试验。利用历史资料有用信息估算模式预报误差原理,选取4个历史相似年对应模式误差来估算当前模式预报误差。通过单因子交叉检验距平相关系数确定主导因子及演化相似因子,结合当前及前期优化多因子组合配置确定预报因子集,最后利用历史相似年对应模式误差来估算当前模式预报误差并订正国家气候中心季节预报业务模式的预报结果,得到预报的汛期降水。对2005—2009年进行独立样本检验的结果表明,此技术对中国东北地区汛期降水有一定预报技巧。证实了利用历史资料估计业务模式预报误差的另类途径是可行的,显示了在业务预报应用中的潜在能力。     

中尺度数值预报模式REM在2002年湖南汛期的实时降水预报试验

本文对中尺度数值预报模式REM的特点和2002年湖南汛期的降水预报试验方案进行了介绍。为了检验其预报效果，分别对整个试验期间(6～8月)和集中降水期(6～7月)这两个时段作了预报结果检验，并与1998年同期作了比较，还与MM5进行了同一时段降水预报效果比较，结果表明该模式在暴雨落区及强度等方面预报效果良好，但还有待进一步完善。     

不同参数化方案对长江中游汛期降水模式预报试验

利用中尺度模式多个物理过程组合成不同预报方案,对长江中游汛期降水预报进行了对比试验.试验结果表明,使用不同物理过程参数化方案对长江中游汛期降水的预报效果存在差异,这种差异随降水预报量级的提高而愈加明显;而就试验而言,Grell积云对流参数化方案与Blackadar边界层参数化方案的组合预报效果相对较好;就单个降水个例而言,预报效果相对好的参数化方案存在不确定性,集合平均预报相对稳定且优于大多数方案,其对降水评分的改进尤其体现在暴雨以下量级的预报中.     

利用全球环流模式进行我国汛期短期气候预测的试验

利用OSU/NCC全球大气环流模式耦合全球混合层海洋与海冰模式,采用集合预报的方法,对中国汛期降水进行了1982~1995年共14年的跨季度综合性回报检验研究。结果表明,该模式对我国汛期降水具有一定的跨季度预报能力,对部分地区（江淮至华东沿海、东北部分地区等）有较强的预报能力。     

2009 年我国汛期降水形势总结与三个常用模式预报效果检验

利用实况24小时降水、形势场资料及T213、T639、Japan模式降水、形势场的预报资料,对2009年汛期(5-9月,下同)中国降水时空分布进行分析,并对T213、T639、Japan三个常用模式对2009年汛期的天气形势、降水及其影响系统的预报做主客观检验,以期得出2009年汛期降水分布特点及三个模式的降水预报效果对比.结果表明:(1) 2009年汛期华南地区降水量为全国之最,长江中下游和西南东部地区其次,东北和华北地区再次.(2)从TS评分看,Japan模式的小雨～大雨量级评分较高,T639模式暴雨～大暴雨量级评分较高;T213模式对华北地区暴雨、大暴雨量级降水预报评分高于Japan和T639模式.(3)从降水预报偏差看,T213模式对华北预报明显偏强,T639模式对华北预报强度较为适中,两模式对其他区域中等以下强度降水预报偏强,对强降水预报偏弱;T639对中等以下强度降水预报偏强程度明显小于T213,而对强降水除华南和东北区域外,预报偏弱程度明显大于T213;Japan模式预报偏差随降水量级增大而减小,对大雨以上各量级预报均明显偏弱,且偏弱程度明显大于T213、 T639.(4)由代表性形势场预报检验结果可知,除T213对500hPa高度场、850hPa温度场预报效果好于其他两模式外,各模式预报效果相差不大.(5)三个模式对500 hPa副高总体预报偏东、偏北、偏强,但Japan预报效果明显好于T213、T639.(6) T639模式对台风和低涡的预报相对较好,T213较差.     

2013年汛期华中区域业务数值模式降水预报检验

为充分了解华中区域中尺度业务数值预报模式更新为WRF后的预报性能,对该模式2013年汛期24 h和48 h的累积降水预报产品,采用TS评分、预报正确率、漏报率、空报率、偏差及ETS评分等统计量对其进行了较详细的评估。结果表明：从日平均降水率分布来看,24 h预报的降水中心位置和强度与实况更接近,48 h的预报明显偏大、偏强;汛期总体降水检验表明,该模式的降水预报以偏大为主,随着降水量级的增大,TS和ETS评分逐渐减小,且ETS评分逐渐靠近TS;逐月降水检验结果发现,该区域汛期月晴雨预报正确率与雨日率呈正相关;通过梅雨期WRF与GRAPES_Meso的预报对比检验可见,两个模式都表现出了较好的预报性能。值得指出的是,随着降水量级的增大,WRF模式降水预报优势逐渐显现。总的来说,该模式的降水预报产品具有一定的参考价值。     

2005年西南区域集合预报系统试验与检验

在2004年利用MM5模式构造西南区域集合预报系统的基础上,2005年增加了多初值扰动,并在2005年汛期进行了准业务试验。对四川区域152个站的降水检验表明,集合预报对四川区域内小雨到暴雨量级的降水预报有明显的预报技巧,对大暴雨的预报技巧不显著;在四川盆地,预报暴雨发生位置比实际发生区域略偏西、偏北;对于小雨到暴雨量级的降水,集合预报优于T213和大部分集合预报成员。     

Analogue-dynamical prediction of monsoon precipitation in Northeast China based on dynamic and optimal configuration of multiple predictors

Based on the National Climate Center (NCC) of China operational seasonal prediction model results for the period 1983–2009 and the US National Weather Service Climate Prediction Center merged analysis of precipitation in the same period, together with the 74 circulation indices of NCC Climate System Diagnostic Division and 40 climate indices of NOAA of US during 1951–2009, an analogue-dynamical technique for objective and quantitative prediction of monsoon precipitation in Northeast China is proposed and implemented. Useful information is extracted from the historical data to estimate the model forecast errors. Dominant predictors and the predictors that exhibit evolving analogues are identified through cross validating the anomaly correlation coefficients (ACC) among single predictors, meanwhile with reference of the results from the dynamic analogue bias correction using four analogue samples. Next, an optimal configuration of multiple predictors is set up and compared with historical optimal multi-predictor configurations and then dynamically adjusted. Finally, the model errors are evaluated and utilized to correct the NCC operational seasonal prediction model results, and the forecast of monsoon precipitation is obtained at last. The independent sample validation shows that this technique has effectively improved the monsoon precipitation prediction skill during 2005–2009. This study demonstrates that the analogue-dynamical approach is feasible in operational prediction of monsoon precipitation.     

上海梅汛期候降水异常的低频信号及延伸期预报

提高汛期降水过程的延伸期预报能力是目前天气预报和气候预测发展的重要方向。本文以上海梅汛期降水为例,利用非传统滤波方法提取多变量季节内分量,分析了梅汛期季节内候降水异常及其相联系的延伸期关键低频信号,进一步综合多变量低频信号建立了梅汛期候降水异常延伸期预报方法,并开展了多年的回报和试报检验。结果表明:①梅汛期候降水异常季节内分量具有显著的40～60d低频振荡周期,与降水异常实况具有显著的正相关和较高的符号一致率;②梅汛期季节内候降水异常与超前10～35d的热带及中高纬低频信号有关,主要包括:热带MJO(Madden Julian Oscillation)自阿拉伯海的向东传播、西太平洋副热带高压季节内活动的西北向传播、PNA(Pacific-North American)遥相关型的季节内位相转换以及东北亚冷空气的持续性异常影响;③综合上述多变量低频信号建立了延伸期候降水异常预报模型,对提前10～35d的延伸期候降水异常的季节内分量具有预报技巧,也能较好地预报实际的候降水异常趋势。     

多时次资料的EOF迭代在云南夏季气候预测中的应用

多时次资料的EOF迭代预测方法能较好地应用历史资料中的信息，并能将经验法则、观测事实和气候规律等引入到实际的短期气候预测过程中，特别是随着我们对影响短期气候变化的物理过程和因子认识的深入，这种预测方法将会得到更加有效地改进和实际应用。本文考虑4个区域月平均海表水温的多时次历史资料，基于EOF迭代方案，建立了云南夏季气候变化的一种多时次EOF迭代预测模型。在对云南分5个区域，每个区域16个气象观测站点的夏季降水和气温趋势的预测中，该模型对云南1995－1999年的夏季6－8月总雨量和平均气温趋势预测检验的最新业务标准评分平均分别达到79．6％和87．0％。该评分成绩表明，这种容纳多时次资料，基于EOF迭代的物理一统计预测方法是一种有效的短期气候预测途径。     

2013年华中区域中尺度业务数值预报的客观检验

应用国家气象中心模式检验方法,对华中区域中尺度业务数值预报模式WRF和中国气象局下发的GRAPES模式2013年1-12月的预报产品（包括降水、2 m温度场、850 hPa温度场、850 hPa风场和500 hPa位势高度场预报）进行统计检验。检验结果表明：所有要素24 h预报均优于48 h;对于晴雨预报,GRAPES模式TS评分高于WRF,但随着降水量级增大,WRF的TS评分基本都高于GRAPES,同时WRF降水预报范围明显偏大;分析2 m温度场的均方根误差及预报准确率发现,WRF的2 m温度场预报优于GRAPES,且暖季预报优于冷季;形势场要素分析表明,WRF对850 hPa温度场和风场预报具有相当大的优势,全年误差变化较稳定,而对500 hPa位势高度场的预报误差存在一定的季节性特征,即夏半年WRF高度场预报优于冬半年,GRAPES模式则相反。总体上,华中区域中尺度业务数值模式产品对天气预报具有一定的参考价值。     

湘西自治州汛期降水的气候特征

从季度降水预报业务的需要出发，根据湘西自治州８个测站的降水资料，分析了汛期（４－９）降水的气候特征和变化趋势，以期为预报汛期雨量提供参考。     

A PRELIMINARY VALIDATION STUDY OF THE SEASONAL FORECAST OF CCCMA MODEL OVER CHINA

In this study we validate the raw ensemble mean forecasts of the CCCma's GCM2 modelagainst surface temperature and precipitation data obtained from 160 Chinese stations.It is foundthat despite the lagre biases,the model was able to produce seasonal anomalies that haveproperties that are reasonably close to those that are observed.This anomaly is the quantity ofinterest when forecasting seasonal climatic conditions.The root mean squared difference(RMSD)between the forecast and observed anomaly leads us to be modestly optimistic about the prospectsfor using dynamical models to forecast the interannual variability of some meteorological elements.The correlation analysis of the forecast and observation also supports the result given by theRMSD analysis and provides a tool for identify the forecast confidence level in various regions,     

Evaluation of summer temperature and precipitation predictions from NCEP CFSv2 retrospective forecast over China

National Centers for Environmental Prediction recently upgraded its operational seasonal forecast system to the fully coupled climate modeling system referred to as CFSv2. CFSv2 has been used to make seasonal climate forecast retrospectively between 1982 and 2009 before it became operational. In this study, we evaluate the model’s ability to predict the summer temperature and precipitation over China using the 120 9-month reforecast runs initialized between January 1 and May 26 during each year of the reforecast period. These 120 reforecast runs are evaluated as an ensemble forecast using both deterministic and probabilistic metrics. The overall forecast skill for summer temperature is high while that for summer precipitation is much lower. The ensemble mean reforecasts have reduced spatial variability of the climatology. For temperature, the reforecast bias is lead time-dependent, i.e., reforecast JJA temperature become warmer when lead time is shorter. The lead time dependent bias suggests that the initial condition of temperature is somehow biased towards a warmer condition. CFSv2 is able to predict the summer temperature anomaly in China, although there is an obvious upward trend in both the observation and the reforecast. Forecasts of summer precipitation with dynamical models like CFSv2 at the seasonal time scale and a catchment scale still remain challenge, so it is necessary to improve the model physics and parameterizations for better prediction of Asian monsoon rainfall. The probabilistic skills of temperature and precipitation are quite limited. Only the spatially averaged quantities such as averaged summer temperature over the Northeast China of CFSv2 show higher forecast skill, of which is able to discriminate between event and non-event for three categorical forecasts. The potential forecast skill shows that the above and below normal events can be better forecasted than normal events. Although the shorter the forecast lead time is, the higher deterministic prediction skill appears, the probabilistic prediction skill does not increase with decreased lead time. The ensemble size does not play a significant role in affecting the overall probabilistic forecast skill although adding more members improves the probabilistic forecast skill slightly.     

SVD Iteration Model and Its Use in Prediction of Summer Precipitation

A new short-term climatic prediction model based on the singular value decomposition （SVD） iteration was designed with solid mathematics and strict logical reasoning. Taking predictors into prediction model, using iteration computation, and substituting the last results into the next computation, we can acquire better results with improved precision. Precipitation prediction experiments were separately done for 16 stations in North China and 30 stations in the mid-lower catchment of the Yangtze River during 1991-2000. Their average mean square errors are 0.352 and 0.312, and the results are very stable. Mean square errors of 9 yr are less than 0.5 while only that of 1 yr is more than 0.5. The mean sign correlation coefficients between forecast and observed summer precipitation during 1991-2000 are 0.575 in North China and 0.623 in the mid-lower catchment of the Yangtze River. Librations of them in North China during the 10 years are small. Only in 1996 the sign correlation coefficient is below 0.5; the others are all over 0.5. But sign correlation coefficients in the mid-lower catchment of the Yangtze River vary obviously. The lowest is only 0.3 in 1992, and the highest is 0.9 in 1998, As the distribution of the forecast precipitation anomaly field in the summer 1998 of is examined, it is known that the model captured the positive and negative anomalyies of precipitation, and also well forecasted the anomaly distributions. But the errors are obvious in quantities between the forecast and the observed precipitation anomalies. Climate characteristics of large scale meteorological elements, such as summer precipitation have obvious differences in spatial distribution. We can forecast better if we divide a big region into many subregions according to the discrepancy of climatic characteristics in the region, and predict in each subregion. The research shows that the model of SVD iteration is a very effective forecast model and has a strongly applicable value.     

上海区域数值预报模式集合预报系统的建立与试验

以目前运行的上海区域业务数值预报模式为基础,从预报模式的不确定性出发构造8个预报成员,建立了上海区域数值预报模式集合预报系统的初步模型,并对2004年夏季进行了逐日48 h预报试验。结果表明:集合平均对华东地区城市降水、温度、海平面气压等气象要素的总体预报能力与分辨率高3倍的业务模式相当,其中对雨量较大降水、最低温度、海平面气压(0~24 h)的预报效果好于业务模式;集合预报还能提供客观化、定量化的降水概率预报,对降水的发生、尤其是特大降水的发生有着很好的提示作用。