近50a江淮地区梅雨期水汽输送特征研究

利用1958—2007年ERA再分析风场及气压场资料和APHRO高分辨率逐日降水资料,对近50 a来梅雨期水汽输送的时空特征及其与江淮地区降水的关系进行了研究,发现各条水汽通道对江淮地区梅雨期降水强度及范围的影响程度均不同。梅雨期影响我国降水的水汽输送有显著的年际变化,并且水汽输送强弱年对应江淮地区降水强度也有明显差异。相关分析及合成差值的结果显示,西太平洋水汽输送贡献更大,且西太平洋水汽输送(东南通道)增强时,江淮地区降水增多。印度洋水汽输送的加强会减弱太平洋的水汽输送从而使得江淮少雨。在全球变暖的背景下,西太平洋的水汽输送对降水的增强作用有所减弱而印度洋输送所导致降水强度减弱的范围则明显扩大。自1980年起,江淮降水出现缓慢增多的趋势与全球变暖所导致的东亚环流异常进而影响水汽输送异常相关。     

深海载人潜水器潜航员岗位要求研究

深海载人潜水器潜航员是国家载人深潜工程的重要战略性人才,针对潜航员这一特殊岗位特点,从思想素质与职业兴趣、专业基础与综合技能、心理素质与身体机能等三个方面开展分析,结合国外潜航员队伍选拔与应用现状以及国内相关领域专家调查结果进行研究,能够明确潜航员岗位的具体要求与人才培养方向,对我国潜航员队伍的科学选拔、科学培养、科学管理具有重要意义。     

干旱研究中的均值生成函数模型

干旱规律研究是水旱灾害对策研究的一个重要内容。较好地模拟历史上干旱发生及其演变规律,对于客观预测未来干旱发生情况和有关部门作出准确相应的决策具有十分重要的意义。本文以分析一维时间序列为基础,介绍了均值生成函数这一概念,提出了应用正交化筛选建立模型的思路,并且经数学推导建立了均值生成函数模型。最后将模型应用于山西省榆林地区、陕西省关中地区的月农业干旱指标序列的模拟与预测。研究结果表明,均值生成函数模     

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

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.     

JSP-1型虹吸校正翻斗雨量计研制与特点

翻斗式雨量计因雨强影响会产生很大的误差,虹吸雨量计不能数字化降雨过程,并需要人工测量虹吸水量进行虹吸订正.本研究成果利用翻斗计量降雨过程,用精确的虹吸计量值智能校正翻斗的误差,综合了翻斗计量和虹吸计量的优点,将分辨率为0.1mm的翻斗雨量计的测量误差从±15%减小到±2%.因此,JSP-1型虹吸校正翻斗雨量计具有很高的精度.     

重庆“6·8”大暴雨过程诊断分析

该文利用NCEP再分析资料和地面观测资料,针对2017年6月8日20时—10日20时重庆地区出现的一次大暴雨过程,对过程发生前的降水实况、环流形势、对流潜势、能量条件、水汽条件、垂直运动以及对应过程发生发展最强时段的卫星及雷达特征进行了分析。此次过程为中高纬呈"两槽一脊"环流背景下,有长波槽分裂小槽东移,配合低层低涡系统及切变线的生成与发展,重庆位于副高584线附近,处在高空急流入口区右侧、低空急流左前侧的强抬升运动区。降水过程分为两个阶段,前一阶段为暖区降水,伴有较强的对流性特征,第二阶段伴随着冷空气的南压,冷暖空气在重庆长江沿线一带交绥,为混合性降水。第一阶段云图上呈现出暴雨云团形态,呈圆形、边界光滑、云团中心白亮区域对应降水大值区。雷达回波表现出较显著的低质心暖云降水特征,降水最强时段径向速度图上存在着明显的气旋式辐合区。第二阶段配合北方冷空气的侵入,云系呈带状分布和发展,伴随着对流云团的不断新生、合并、扩大,云团生命史较长,对应降水时间较长。雷达回波表现为层状云降水回波特征,且在重庆永川及周边区域存在"列车效应",从而造成了相应地区较长时间的持续性强降水。