我国南方春季低温冷害气候及其大气环流特征

利用我国南方6省45个站1951－1995年2－4月的月平均气温资料分析该地区春季低温冷害气候特征，发现有7个低温冷害年，1957，1968，1969，1970，1984，1985和1988年，最严重的年份是1968和1988年，严重低温冷害主要发生在3，4月份，严重低温冷害最为频繁的地区是江南南部，南方春季低温冷害年际变化有着明显的阶段性和群发性，80年代我国南方春季低温冷害频繁，50年代次之，60，70年代较少，90年代前期几乎没有，典型的春季低温和高温年份，严洲中高纬度大气环流，西太洋平洋副热带高压以及太平洋热带海洋状况都有显著的差异，特别是，亚洲极涡，纬向环流指数，西太平洋副热带高压比界位置及太平洋暖池的海表面温度等因子均通过了95％（90％）信度水平检验。     

沈阳地区低温冷害浅析

从农业生产角度出发。分析了1951～2000年沈阳地区低温冷害年的概况、气候特征、影响及其与厄尔尼诺的关系，低温冷害的变化情况。     

华南春季低温冷害气候特征研究

利用华南地区４８个台站１９５１－１９９０年２、３月气象资料，比较详细地讨论华南春季低温冷害的气候特征，揭示出如下几点事实：（１）华南的春季低温冷害过程出现频率愈往南去，愈向２月份集中。华南北部，低温过程次数多，持续日数长，温度低，是低温冷害最重的区域，往南依次为中等与轻度低温冷害区域，雷州半岛及海南省基本无低温冷害。（２）低温冷害过程初日与终日的年陆波动非常大，初日极差普遍有１个月左右，终日极差高     

山东省春季低温冷害特征及其成因分析

利用山东省26个站1961～2002年3～5月的月平均气温资料分析了山东春季低温冷害的气候特征,并从中高纬度环流、太阳黑子和赤道东太平洋海温等方面探讨春季低温冷害的成因。发现有1963,1969,1970,1976,1979,1980,1985和1991年共8个低温冷害年。山东春季气温变化具有明显的阶段性,80年代以前,低温冷害频繁,1991年以后再也没有出现过严重低温年份。春季低温和高温年份,亚洲中高纬度大气环流、太阳黑子活动和赤道东太平洋海温都有显著差异。在低温年,亚洲中高纬度盛行经向环流,太阳黑子相对数明显偏多,其前秋至前冬,赤道东太平洋海温为负距平,且海温逐渐升高,春季为正距平。     

沈阳地区低温冷害浅析

从农业生产角度出发 ,分析了 1951～2000年沈阳地区低温冷害年的概况、气候特征、影响及其与厄尔尼诺的关系 ,低温冷害的变化情况     

低温冷害对兴安盟农田作物生态的影响及其防御对策

本文针对农田生态的主体一农作物的低温冷害，确定了其危害气候指标，指出了低温冷害的区域性、持续性、群发阶段性及准周期性等特征，明确了低温冷害的气候关键期。本文分析论述了低温冷害对作物产量的影响和危害，并重点探讨了怎样立足于生态系统，着眼于品种布局方面的对策及加强田间管理；采取一系列有效措施的防与抗相结合的原则。     

用综合权重分析法作春播期低温阴雨长期预报

一、引言我区地处亚热带季风气候区,春播期冷暖空气交替影响,气温变化较大,作好春播期低温阴雨和倒春寒天气预报,对安排全年农业生产,提高农业产量,提高社会和经济效益意义重大。 二、预报因子的选择根据多年来的预报经验,着重抓住天气环流及天气气候的前期变化特征,特别是某些特殊变化值,对提前预报未来将出现某种程度的异常天气变化还是可能的。本文根据以上思路,分别以3月中旬有无低温阴雨天     

山东省春季低温的气候分析及其长期预报

利用济南站１９１９－１９９１年春季气温的历史资料，分析了我省春季低温的气候特征和演变规律及其与大尺度环流背景及我国大范围气候振动之间的联系。得出我省春季低温集中发生在全国气候振动的“冷”期内；它的形成一般是在经向环流发展以及由纬向环流向经向环流的转折阶段。通过对春季高、低温年的５００ｈＰａ环流特征的对比分析，发现两者差异明显。由北半球５００ｈＰａ高度场所建立的预报工具，在近几年预报中取得较好效果。     

流感世界大流行的气候特征

流感爆发与气候的剧烈变化有关。本文揭示了拉马德雷冷位相、拉尼娜、太阳黑子极值年、厄尔尼诺、低温冷害、沙尘暴、潮汐南北震荡异常与流行性感冒世界大流行相互对应的关系及其物理机制,对气候及其相关灾害的预测有重大科学意义。规律表明,在拉马德雷冷位相时期,全球强震、低温、飓风伴随拉尼娜、全球性流感伴随厄尔尼诺将越来越强烈。面对日益增大的全球灾害,长期气候预报意义重大。     

黑龙江省玉米低温冷害发生风险趋势及预报模型

利用黑龙江省玉米主产区69个市(县)1961~2003年5~9月逐日气温、玉米发育期与冷害资料,用积温距平作为判别玉米低温冷害发生的主导因子,获得玉米主要发育时期冷害发生指标体系及其风险程度,构建玉米低温冷害风险预报模型;分析了43年来玉米低温冷害发生风险的趋势变化,采用Mann-Kendall方法进行趋势检验。结果表明:1961~1983年为玉米冷害发生的高风险时期,其中1964、1969、1972、1983年是玉米冷害发生的最高风险年。1984年之后为冷害发生的低风险时期,尤其在所研究的后几年各地的UskU0.05,表明此时期积温距平水平上升趋势明显,发生玉米冷害的风险很低;玉米低温冷害风险预报模型能够对冷害发生风险、冷害程度、发生范围进行动态预测预报和灾害评估,预报模型的检验结果具有较好的客观性和适用性。     

NUMERICAL MODELING STUDY OF EFFECTS OF EASTERN PACIFIC WARM POOL ON ENSO

In this study, sensitivity experiments were conducted with the Zebiak-Cane ocean-atmosphere coupled model forced by the wind stress anomaly from the U.S. National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data to study the impacts of eastern Pacific warm pool on the formation and development of ENSO events. The effects of climatological mean sea surface temperature of the warm pool on forecast skill during the ENSO events of 1982–1999 are more considerable that those of climatological mean meridional winds and ocean currents. The forecast skill for the 1997/1998 El Ni?o event is characterized by sensitivity to climatological mean sea surface temperature and anomalies of northerly winds and currents. The forecast skill is found insensitive to climatological mean northerly meridional winds and currents.     

武威地区冬季低温天气的气候分析与预报

通过对１９８０—１９９１年１２—２月武威地区低温天气过程气候特征和天气成因的分析，建立模式预报方程。１９９２—１９９６年试报效果良好，将植入“武威地区冬半年寒潮降温多目标专家系统”，投入业务运行。     

Comparative study of performance of different weather forecast models at specific sites in northwest Himalaya in India

Independent test results of four different weather forecast models [climatological, persistence, analogue, and regional mesoscale weather simulation (MM5) model] have been compared for four past winters (winter 2003–2004 to winter 2006–2007) for qualitative weather (snow day/no snow day) and quantitative categorical snowfall prediction at six different areas in northwest Himalaya (NW-Himalaya) in India. Weather forecast guidance provided by the MM5 model at 10 km resolution was taken for the study. Test results of MM5 and the analogue model were compared for a limited number of days (with irregular gaps) due to lack of availability of MM5 weather forecast guidance for complete winter periods. Forecasts based on the persistence, climatological, and analogue models were compared for day 1 predictions only. Performance of the analogue model for qualitative weather prediction was found to be comparable to that of the MM5 model for day 1 prediction. However, for day 2 and day 3, performance of the MM5 model was found to be marginally better than that of the analogue model. Marginal difference in overall accuracy of the analogue and MM5 models was found for quantitative categorical snowfall prediction for day 3. The quantitative categorical snowfall forecast error of the MM5 model was found to be greater than that for the analogue model for all three days. Comparative study of the performance of the climatological, persistence, and analogue models showed that the analogue model performs better than the persistence and climatological models for day 1 predictions. The results of this study suggest that the analogue model shows some capability for weather prediction and, along with the MM5 model, could be a useful tool for weather forecasters. Comparative study of the performance of the MM5 model at high resolution (about 2–3 km) and the analogue model for complete winter period may provide some interesting and fruitful results.     

GRAPES_GEPS模式对2018年冬季欧亚地区500 hPa高压脊形势的预报效果评估

基于1979～2017年（共39年）NCEP/NCAR第一套再分析数据首先对欧亚大陆500 hPa持续性高值[Persistent open ridges and blocking high (maxima) of 500 hPa geopotential height, PMZ]事件的气候分布特征进行了统计分析,发现欧亚地区冬季PMZ事件主要发生在乌拉尔山地区,该地区的PMZ事件生命史以2～3 d为主,移动距离小于1000 km。通过对2018年冬季发生在鄂霍茨克海地区的阻塞形势检验得出,GRAPES（Global/Regional Assimilation and Prediction Enhanced System）和ECMWF（European Centre for Medium-Range Weather Forecasts）确定性模式在中短期时效对偏强阻塞形势有较好的预报能力,且ECMWF模式预报性能优于GRAPES模式,而对弱阻塞形势预报两家模式均不理想。随后针对 GRAPES全球集合预报系统(GRAPES-GEPS)和ECMWF集合预报对2018年冬季欧亚地区PMZ事件的预报能力开展细致评估,结果表明GRAPES-GEPS控制预报在中期时效预报效果相对短期时效明显偏差,集合预报伴随预报时效临近更多的集合成员可预报出与零场接近的PMZ事件。ECMWF在短期时效预报效果明显由于GRAPES-GEPS,但随着预报时效延长,预报效果显著降低。对于2018年12月25～31日的PMZ事件,GRAPES_GEPS各集合成员在延伸期时效给出预报信息,随预报时效临近,集合成员预报成功率明显增加,但与零场相比PMZ事件维持时间较零场偏短、高压脊强度较零场偏弱。本文给出了中期延伸期时效GRAPES_GEPS对PMZ事件的冬季预报能力,以期未来能为中期延伸期阻塞形势预报提供参考。     

降雪含水比研究进展

降雪深度预报与定量降水预报(QPF)一样是冬季天气预报最重要的业务之一,而降雪含水比是降雪深度预报中所必须的重要参数,国外一般多将其称为snow-to-liquid ratio(SLR)。本文回顾了过去几十年来国内外在SLR的变化特征、影响因素等方面的主要研究进展,并对其预报技术和方法进行了总结和比较。研究表明:SLR具有明显的时间变化,并且存在季节和空间分布差异;大气温度和相对湿度是影响SLR的两个最重要气象因子,气压、垂直运动等气象因素,以及地表风、积雪自重、太阳辐射和积雪融化也会不同程度地影响SLR;随着预报技术的发展,SLR的预报方法可概括为气候学的、统计学的和基于物理基础的三类预报方法,气候学方法过于简单化,统计学方法的应用提高了SLR的预报能力,但仍无法摆脱统计方法自身的缺陷,比较而言,基于数值模式的瞬时预报更符合未来雪深预报业务的精细化发展趋势;目前,国内降雪深度观测资料较少、观测频率较低,有效开展地面降雪和探空加密观测,解决观测资料不足是今后SLR研究中亟待解决的问题;基于数值天气预报业务模式,探索气象因子对SLR的影响机理,建立适合我国冬季天气预报业务需求的降雪预报系统是未来的发展方向。     

新气候平均值在中期预报业务中的应用

中央气象台中期科按照WMO的要求，自2003年1月1日起开始使用的新的气象平均值（1971－2000年30年平均值），平均值改变的结果显示，6－8月期间，南方大部分地区的旬雨量增多较为明显，冬半年（10－4月）多数上的旬平均气温升高，导致气温距平将降低，对冷空气过程强度的划分有一定的影响。     

基于三种机器学习方法的降水相态高分辨率格点预报模型的构建及对比分析

冬季降水相态及其转变时间的精细化客观预报对提高气象预报和服务质量具有重要的现实意义。利用京津冀地区国家级自动气象站观测资料及网格化快速更新精细集成产品,统计分析了京津冀地区复杂地形下各类降水相态温度和湿球温度平均气候概率的分布差异及不同降水相态时网格化快速更新精细集成产品中可能影响降水相态判断的特征信息。然后将地面观测天气现象资料、复杂地形下降水相态气候特征及高分辨率模式输出产品作为特征向量,分别基于梯度提升（XGBoost）、支持向量机（SVM）、深度神经网络（DNN）3种机器学习方法建立了降水相态的高分辨率客观分类模型,并对同样条件下3种机器学习方法对雨、雨夹雪和雪3种京津冀主要降水相态的预报效果进行了对比检验,进一步提升了雨夹雪复杂降水相态的客观分类预报技巧。      

西北区东部寒潮天气短期预报

分析了西北区东部寒潮短期预报的气候概况和环流特征，对不同类型寒潮个例进行归纳总结，组合成预报规则，建立了短期寒潮预报模式，输入计算机得出有无寒潮天气预报     

Influence of Eurasian snow on Indian summer monsoon in NCEP CFSv2 freerun

The latest version of the state-of-the-art global land–atmosphere–ocean coupled climate forecast system of NCEP has shown considerable improvement in various aspects of the Indian summer monsoon. However, climatological mean dry bias over the Indian sub-continent is further increased as compared to the previous version. Here we have attempted to link this dry bias with climatological mean bias in the Eurasian winter/spring snow, which is one of the important predictors of the Indian summer monsoon rainfall (ISMR). Simulation of interannual variability of the Eurasian snow and its teleconnection with the ISMR are quite reasonable in the model. Using composite analysis it is shown that a positive snow anomaly, which is comparable to the systematic bias in the model, results into significant decrease in the summer monsoon rainfall over the central India and part of the Equatorial Indian Ocean. Decrease in the summer monsoon rainfall is also found to be linked with weaker northward propagation of intraseasonal oscillation (ISO). A barotropic stationary wave triggered by positive snow anomaly over west Eurasia weakens the upper level monsoon circulation, which in turn reduces the zonal wind shear and hence, weakens the northward propagation of summer monsoon ISOs. A sensitivity experiment by reducing snow fall over Eurasian region causes decrease in winter and spring snow depth, which in turn leads to decrease in Indian summer monsoon rainfall. Results from the sensitivity experiment corroborate with those of composite analysis based on long free run. This study suggests that further improvements in the snow parametrization schemes as well as Arctic sea ice are needed to reduce the Eurasian snow bias during winter/spring, which may reduce the dry bias over Indian sub-continent and hence predictability aspect of the model.     

Yearly evolution of Euro-Atlantic weather regimes and of their sub-seasonal predictability

It is often assumed that weather regimes adequately characterize atmospheric circulation variability. However, regime classifications spanning many months and with a low number of regimes may not satisfy this assumption. The first aim of this study is to test such hypothesis for the Euro-Atlantic region. The second one is to extend the assessment of sub-seasonal forecast skill in predicting the frequencies of occurrence of the regimes beyond the winter season. Two regime classifications of four regimes each were obtained from sea level pressure anomalies clustered from October to March and from April to September respectively. Their spatial patterns were compared with those representing the annual cycle. Results highlight that the two regime classifications are able to reproduce most part of the patterns of the annual cycle, except during the transition weeks between the two periods, when patterns of the annual cycle resembling Atlantic Low regime are not also observed in any of the two classifications. Forecast skill of Atlantic Low was found to be similar to that of NAO+, the regime replacing Atlantic Low in the two classifications. Thus, although clustering yearly circulation data in two periods of 6 months each introduces a few deviations from the annual cycle of the regime patterns, it does not negatively affect sub-seasonal forecast skill. Beyond the winter season and the first ten forecast days, sub-seasonal forecasts of ECMWF are still able to achieve weekly frequency correlations of r = 0.5 for some regimes and start dates, including summer ones. ECMWF forecasts beat climatological forecasts in case of long-lasting regime events, and when measured by the fair continuous ranked probability skill score, but not when measured by the Brier skill score. Thus, more efforts have to be done yet in order to achieve minimum skill necessary to develop forecast products based on weather regimes outside winter season.