Changing Spring Phenology Dates in the Three-Rivers Headwater Region of the Tibetan Plateau during 1960–2013     

Shuang YU  Jiangjiang XIA  Zhongwei YAN  Kun YANG 《大气科学进展》2018,35(1):116-126

The variation of the vegetation growing season in the Three-Rivers Headwater Region of the Tibetan Plateau has recently become a controversial topic. One issue is that the estimated local trend in the start of the vegetation growing season(SOS)based on remote sensing data is easily affected by outliers because this data series is short. In this study, we determine that the spring minimum temperature is the most influential factor for SOS. The significant negative linear relationship between the two variables in the region is evaluated using Moderate Resolution Imaging Spectroradiometer–Normalized Difference Vegetation Index data for 2000–13. We then reconstruct the SOS time series based on the temperature data for 1960–2013.The regional mean SOS shows an advancing trend of 1.42 d(10 yr)~(-1) during 1960–2013, with the SOS occurring on the 160th and 151st days in 1960 and 2013, respectively. The advancing trend enhances to 6.04 d(10 yr)~(-1) during the past 14 years. The spatiotemporal variations of the reconstructed SOS data are similar to those deduced from remote sensing data during the past 14 years. The latter exhibit an even larger regional mean trend of SOS [7.98 d(10 yr~(-1) )] during 2000–13. The Arctic Oscillation is found to have significantly influenced the changing SOS, especially for the eastern part of the region,during 2000–13.  相似文献   

北方一次暖区大暴雨降水预报失败案例剖析   总被引：3，自引：1，他引：2  

谌芸  吕伟绮  于超  李晟祺  杨舒楠  朱文剑  徐珺  宫宇 《气象》2018,44(1):15-25

目前全球模式对暖区暴雨的捕捉能力有限,北方地区的暖区暴雨预报更是业务预报中的一个难点。2013年7月1—2日河北、天津等地出现了一次区域性大暴雨过程,降水由锋前暖区降水和锋面降水组成,特别是冀中的特大暴雨[409mm·(24h)~(-1)]暖区降水占60%以上。预报员对此次过程的预报量级显著偏小,特大暴雨、暴雨均出现漏报。各家数值模式预报均不能给预报员提供足够的有用信息,给预报带来很多困难,导致预报的失败。本文利用业务预报中常用的数值预报产品、加密自动站观测资料、常规地面、高空观测资料、新一代天气雷达资料等对此次北方暖区暴雨预报失败案例进行剖析,结果显示:高温高湿的环境中,未能捕捉到可触发对流的次天气及以下尺度的小扰动,如地面辐合线、阵风锋、冷池及中尺度涡旋等及其对强降水的影响,加之对中尺度对流系统的环境场条件,如低空急流、急流核的发展演变等的精细分析不足是导致强降水预报量级偏弱的重要因素;对于发生在深厚暖湿气团中的暖区降水的预报,需考虑高温高湿环境下地面辐合线、冷池及中尺度涡旋的相互作用对对流的触发及组织化发展导致的局地性、对流性强降水的产生;基于地面自动站资料和雷达资料等的短时临近预报可以弥补全球数值预报对中小尺度系统的捕捉能力的不足,提高暖区暴雨的预报准确率。  相似文献   

2017年广州“5·7”暖区特大暴雨的中尺度系统和可预报性   总被引：2，自引：0，他引：2  

伍志方  蔡景就  林良勋  胡胜  张华龙  韦凯华 《气象》2018,44(4):485-499

2017年5月7日广州发生了特大暴雨,各家确定性业务预报模式均漏报了此次过程。本文利用常规观测资料和广州天气雷达资料对此次暖区特大暴雨过程的天气尺度背景、中尺度系统演变和可预报性进行了详细分析,同时通过分析ECMWF集合预报中成功预报出广州周边地区出现局地强降水与预报了弱降水的成员间的差异,探讨影响本次大暴雨发生的关键触发因子。结果表明：2017年“5·7”大暴雨的环境条件和动力强迫较弱,在弱风场环境下,冷高压后部东南风或偏南风回流,经过城市热岛区域,转为偏暖气流,与山坡下滑冷气流在山前一带形成的水平风场辐合,结合山前强水平温度梯度,共同触发了初生对流单体。其后,雷暴出流和边界层暖湿气流形成的辐合线又触发新生单体,并使已减弱的降水单体重新加强产生第二阶段强降水。前两个阶段的局地特大暴雨分别是由稳定少动的块状强回波单体发展到嵌有中涡旋的强单体和较长生命史的弱HP型超级单体造成的,第三阶段的大暴雨是由向南传播合并新生单体并随短波槽东移的带状回波造成;三个阶段成熟回波垂直结构上均呈低质心暖云降水的特点。由ECMWF集合预报成功预报出局地强降水与弱降水成员之间的差异可见,加强的温度梯度及地面风场辐合可能是本次局地强降水的重要触发因子。短期时效内数值模式难以做出暖区尤其是弱风场环境下暴雨以上降水预报,目前的监测和短时临近预警是主要手段。  相似文献   

2017年5月7日广州特大暴雨微物理特征及其触发维持机制分析     

傅佩玲  胡东明  张羽  李怀宇  高美谭  周芯玉 《气象》2018,44(4):500-510

2017年5月7日,广州经历了一次罕见的局地特大暴雨事件,刷新了多个雨量历史纪录,造成了严重的国民财产损失。本文利用双偏振雷达、二维雨滴谱仪、微波辐射计和风廓线雷达等多种新型探测资料,分析这次短时暴雨的演变过程和降水特征,并通过大气环境诊断和双多普勒雷达风场反演方法研究其维持机制。结果表明,此次降水过程发生在弱天气系统强迫条件下,大气层结表现为弱对流抑制、低抬升凝结高度、中等对流有效位能、较厚的暖云层,低层受暖湿气流影响但无明显急流。强降水是由中尺度对流系统直接产生的。午夜至凌晨的初始对流主要由偏南暖湿气流与地形相互作用产生,对流单体不断在后部触发并逐渐形成准静止的对流雨带;黎明至早晨,新生对流单体沿着成熟的强降水风暴出流与低层偏南暖湿气流的交界不断激发,后向传播过程更为显著,形成回波列车效应;此后降水以组织化的对流雨带不断南移。此次暴雨过程中的对流云团为典型的低质心降水云团,降水雨滴谱在高湿环境中表现为暖性降水的特征(小雨滴浓度非常高),但同时存在部分大粒子,从而导致更高的降水效率和局地强降水。不断加强的低层偏南暖湿气流对于对流系统的发展和维持具有重要作用。  相似文献   

Application of Multi-Temporal MODIS NDVI Data to Assess Practiced Maize Calendars in Rwanda     

MUGABOWINDEKWE Maurice  MUYIZERE Aline  LI Fadong  QIAO Yunfeng  RWANYIZIRI Gaspard 《资源与生态学报(英文版)》2018,9(3):273-280

Crop calendar is an important tool providing relevant information on crops cycles in a specific area for effective agricultural management. Crop calendars vary in different areas given dissimilarities in agro-ecosystems’ characteristics. This research used multi-temporal MODIS NDVI stratification to assess differences in practiced maize crop calendars in various areas of Rwanda. Four (4) sample NDVI strata dominated by agriculture were purposively chosen, and 433 local farmers were randomly selected from the strata for interviews. The collected information helped to know about their maize planting as well as harvesting dates in order to generate maize calendars per NDVI strata. The generated crop calendars were later classified using k-means unsupervised classification, and produced 4 groupings of practiced maize calendars irrespective of NDVI strata. ANOVA results revealed significant differences between both the generated maize crop calendars by NDVI strata and the practiced crop calendars irrespective of NDVI strata, at p = 0.05. Moreover, chi-square tests and t-tests revealed not only a significant relationship between maize calendars and number of crop growing seasons, but also a significant relationship between maize calendars and NDVI strata, at p = 0.05. Finally, findings of this research contrasted the present conviction that there exist a single general maize calendar all over the country. Instead, the results were in accordance with the fact that Rwanda agro-ecosystems differ from East to West in terms of, mainly, altitude and rainfall patterns variations.  相似文献   

ECMWF和华东WARMS模式对山东半岛汛期暴雨的预报能力检验          下载免费PDF全文

党英娜 《山东气象》2018,38(4):136-144

利用欧洲中期天气预报中心细网格模式（以下简称ECMWF-Thin）产品和模式水平分辨率为9 km的华东区域气象中心中尺度数值预报模式V1.0（以下简称SMS-WARMS）产品,对山东半岛2016—2017年汛期35个暴雨日（26次过程）的暴雨预报能力进行检验。结果表明：1）对于降水强度,ECMWF-Thin预报偏弱导致暴雨和大暴雨漏报率偏高,大暴雨几乎全部漏报,当其预报有50 mm以上降水时出现暴雨的概率达90%以上,SMS-WARMS则预报降水量偏强、空报率较高,SMS-WARMS降水强度量级预报总体优于ECMWF-Thin,24 h预报能力最佳;2）对于强降水开始时间的预报,两家模式均表现为偏晚为主,且偏晚3 h以内的概率较大,在参考其预报结论的基础上可适当提前3 h;3）对于强降水落区,ECMWF-Thin略优于SMS-WARMS,SMS-WARMS对台风暴雨的落区预报较为精准,而其他类型暴雨的落区ECMWF-Thin预报多偏南或偏向西南1°以内,因此预报员需向偏东或东北1°范围内的区域调整;4）对于强降水范围大小的预报,ECMWF-Thin预报暴雨范围偏小的概率较大,而SMS-WARMS预报范围偏大的概率较大,因此需综合考虑两种数值预报结论进行折中预报。  相似文献   

PREDICTION OF FLOOD SEASON PRECIPITATION IN SOUTHWEST CHINA BASED ON IMPROVED PSO-PLS     

王志毅  胡邦辉  杨修群  王学忠  王举  黄泓 《热带气象学报(英文版)》2018,24(2):163-175

In order to achieve the best predictive effect of the Partial Least Squares (PLS) regression model, Particle Swarm Optimization (PSO) algorithm is applied to automatically filter the optimal subset of a set of candidate factors of PLS regression model in this study. An improved version of the Particle Swarm Optimization-Partial Least Squares (PSO-PLS) regression model is applied to the station data of precipitation in Southwest China during flood season. Using the PSO-PLS regression method, the prediction of flood season precipitation in Southwest China has been studied. By introducing the precipitation period series of the mean generating function (MGF) extension as an alternative factor, the MGF improved PSO-PLS regression model was also build up to improve the prediction results. Randomly selected 10%, 20%, 30% of the modeling samples were used as a test trial; random cross validation was conducted on the MGF improved PSO-PLS regression model. The results show that the accuracy of PSO-PLS regression model and the MGF improved PSO-PLS regression model are better than that of the traditional PLS regression model. The training results of the three prediction models with regard to the regional and single station precipitation are considerable, whereas the forecast results indicate that the PSO-PLS regression method and the MGF improved PSO-PLS regression method are much better than the traditional PLS regression method. The MGF improved PSO-PLS regression model has the best forecast performance on precipitation anomaly during the flood season in the southwest of China among three models. The average precipitation (PS score) of 36 stations is 74.7. With the increase of the number of modeling samples, the PS score remained stable. This shows that the PSO algorithm is objective and stable. The MGF improved PSO-PLS regression prediction model is also showed to have good prediction stability and ability.  相似文献   

湖南一次暖区暴雨的Barnes滤波客观分析          下载免费PDF全文

蔡海朝  刘红武  邓梅  王萍 《中低纬山地气象》2018,42(3):51-57

利用ECMWF高分辨率0.25×0.25格点资料、逐小时加密雨量观测资料,基于Barnes滤波原理,设计了3套从格点资料中提取中α尺度气象信息的方案,对2017年4月8日湖南的一次暖区暴雨过程进行Barnes滤波对比客观分析。结果表明:此次强降水过程发生在高空槽南侧的西南暖湿气流中,中尺度扰动是造成此次暖区暴雨的重要原因;通过选取不同参数的Barnes带通滤波方案,能够有效分离出中α尺度天气系统,进而剖析其一致性和差异特征,对中尺度雨团落区预报有很好的指示作用,同时,也可以作为判断滤波过程中产生虚假系统的参考依据,在实际业务应用中意义重大。  相似文献   

贵州玉屏四季气候季节的划分及特征分析          下载免费PDF全文

吴丽华  杨明  李小兰  罗俊祎  何为 《中低纬山地气象》2018,42(5):75-80

利用玉屏国家地面气象观测站1961—2016年逐日平均气温资料,采用《气候季节划分》(QX/T15—2012)方法,对玉屏县四季起始日期及长度进行分析。结果表明:(1)玉屏县常年四季起始日期:入春3月5日,入夏5月23日,入秋9月22日,入冬11月28日;四季长度:春季79 d,夏季122 d,秋季67 d,冬季97 d。(2)56 a来玉屏县春季起始日期呈提前趋势,长度呈增加趋势,两者均在20世纪90年代前后出现了转折,但未发生气候突变;夏季起始日期及长度趋势变化不明显;秋季起始日期呈推后趋势,长度变化不明显;冬季起始日期变化不明显,长度呈减少趋势;春季长度增加、冬季长度减少主要为春季起始日期提前所致。(3)玉屏县四季起始日期的年际变幅大,起始日期比常年偏早(晚)连续2候以上的异常年份,春季为23%,夏季为27%,秋季为32%,冬季为25%。(4)玉屏县春季开始后出现低于季节指标≥1候的概率达41%,表明玉屏县春季出现倒春寒天气的概率很大。(5)比较气象行标法与稳定通过法的四季起始日期及长度,气象行标法对玉屏县的四季划分更能满足于农业生产的需要。  相似文献   

陕西汛雨开始日期异常的气候特征及其影响系统     

王娜  赵俊虎  李明  赵晓萌  雷田旺  姜锋 《地理科学》2021,41(1):167-176

利用陕西省1961—2018年逐日降水资料、NCEP/NCAR再分析资料及NOAA海温资料,基于合成分析、相关分析等方法,研究了陕西汛雨开始早晚的气候特征及其影响系统。结果表明:陕西入汛日具有显著的年际和年代际变化特征,20世纪60年代主要以偏晚为主,70、80年代以偏早为主,90年代偏晚,进入21世纪以后以偏早为主,雨季主要集中在7月上旬至中旬中期。入汛偏早年,东亚副热带西风急流于6月下旬北跳,强度偏强,北跳偏早,欧亚中高纬为两槽一脊,副高偏强、偏西、偏北;低层,孟加拉湾至中国南海为巨大的气旋式距平环流,西北太平洋为显著的反气旋距平环流。入汛偏晚年,环流系统与偏早年相反。入汛早晚与冬春季海表温度相关,当冬季印度洋、春季热带北大西洋海温偏高,有利于入汛。  相似文献