The Dynamical Effects of Divergent Wind on the Intraseasonal variabinty of the East Asian Circulation

宋玉成，黄荣辉ＴｈｅＤｙｎａｍｉｃａｌＥｆｆｅｃｔｓｏｆＤｉｖｅｒｇｅｎｔＷｉｎｄｏｎｔｈｅＩｎｔｒａｓｅａｓｏｎａｌｖａｒｉａｂｉｎｔｙｏｆｔｈｅＥａｓｔＡｓｉａｎＣｉｒｃｕｌａｔｉｏｎ￥ＳｏｎｇＹｕｃｈｅｎｇａｎｄＨｕａｎｇＲｏｎｇｈｕｉ（Ｉｎｓ...     

Some Aspects of the Characteristics of Monsoon Disturbances Using a Combined Barotropic－Baroclinic Model

ＳｏｍｅＡｓｐｅｃｔｓｏｆｔｈｅＣｈａｒａｃｔｅｒｉｓｔｉｃｓｏｆＭｏｎｓｏｏｎＤｉｓｔｕｒｂａｎｃｅｓＵｓｉｎｇａＣｏｍｂｉｎｅｄＢａｒｏｔｒｏｐｉｃ－ＢａｒｏｃｌｉｎｉｃＭｏｄｅｌ￥Ｎ．Ｒ．ＰａｒｉｊａａｎｄＳ．Ｋ．Ｄａｓｈ（ＣｅｎｔｒｅｆｏｒＡ...     

Analysis of Causes and Seasonal Prediction of the Severe Floods in Yangtze／Huaihe Basins during Summer 1991

ＡｎａｌｙｓｉｓｏｆＣａｕｓｅｓａｎｄＳｅａｓｏｎａｌＰｒｅｄｉｃｔｉｏｎｏｆｔｈｅＳｅｖｅｒｅＦｌｏｏｄｓｉｎＹａｎｇｔｚｅ／ＨｕａｉｈｅＢａｓｉｎｓｄｕｒｉｎｇＳｕｍｍｅｒ１９９１ＸｕＱｕｎ（徐群）（ＪｉａｎｇｓｕＭｅｔｅｏｒｏｌｏｇｉｃａｌｉｎ...     

A Diagnostic Study of Explosive Development of Extratropical Cyclone over East Asia and West Pacific Ocean

ＡＤｉａｇｎｏｓｔｉｃＳｔｕｄｙｏｆＥｘｐｌｏｓｉｖｅＤｅｖｅｌｏｐｍｅｎｔｏｆＥｘｔｒａｔｒｏｐｉｃａｌＣｙｃｌｏｎｅｏｖｅｒＥａｓｔＡｓｉａａｎｄＷｅｓｔＰａｃｉｆｉｃＯｃｅａｎ￥ＪｉａＹｉｑｉｎ（贾逸勤）ａｎｄＺｈａｏＳｉｘｉｏｎｇ（赵思雄）（...     

The Vertical Transport of Air Pollutants by Convective Clouds．Part Ⅲ：Transport Features of Different Cloud Systems

ＴｈｅＶｅｒｔｉｃａｌＴｒａｎｓｐｏｒｔｏｆＡｉｒＰｏｌｌｕｔａｎｔｓｂｙＣｏｎｖｅｃｔｉｖｅＣｌｏｕｄｓ．ＰａｒｔⅢ：ＴｒａｎｓｐｏｒｔＦｅａｔｕｒｅｓｏｆＤｉｆｆｅｒｅｎｔＣｌｏｕｄＳｙｓｔｅｍｓＫｏｎｇＦａｎｙｏｕ（孔凡铀）ａｎｄＱｉｎＹｕ（秦...     

Symmetric Development of Meso Perturbation in Zonally Curved Basic Flow

ＳｙｍｍｅｔｒｉｃＤｅｖｅｌｏｐｍｅｎｔｏｆＭｅｓｏＰｅｒｔｕｒｂａｔｉｏｎｉｎＺｏｎａｌｙＣｕｒｖｅｄＢａｓｉｃＦｌｏｗ①ＺｈｏｕＷｅｉｃａｎ（周伟灿），ＣｈｅｎＪｉｕｋａｎｇ（陈久康）ａｎｄＺｈｏｕＳｈｕｎｗｕ（周顺武）ＮａｎｊｉｎｇＩｎｓｔｉｔ...     

Numerical Modelling of the Effects of Ozone on the Summer Atmospheric Circulation

ＮｕｍｅｒｉｃａｌＭｏｄｅｌｌｉｎｇｏｆｔｈｅＥｆｆｅｃｔｓｏｆＯｚｏｎｅｏｎｔｈｅＳｕｍｍｅｒＡｔｍｏｓｐｈｅｒｉｃＣｉｒｃｕｌａｔｉｏｎＷａｎｇＱｉａｎｑｉａｎ（王谦谦）；ＷａｎｇＹｉｎｈｕｉ（汪迎辉）；ＳｏｎｇＹｕ（宋煜）（Ｎａｍｉｎｇｉｎｓｔ...     

Behaviour of Coupled Modes in a Simple Nonlinear Air-Sea Interaction Model

Ｂｅｈａｖｉｏｕｒ　ｏｆ　Ｃｏｕｐｌｅｄ　Ｍｏｄｅｓ　ｉｎ　ａ　Ｓｉｍｐｌｅ　Ｎｏｎｌｉｎｅａｒ　Ａｉｒ－Ｓｅａ　Ｉｎｔｅｒａｃｔｉｏｎ　ＭｏｄｅｌＬｉＣｈｏｎｇｙｉｎａｎｄＬｉａｏＱｉｎｇｈａｉ（ＬＡＳＧ，ＩｎｓｔｉｔｕｔｅｏｆＡｔｍｏｓｐｈｅｒｉ...     

The Vertical Transport of Air Pollutants by Convective Clouds Part Ⅱ：Transport of Soluble Gases and Sensitivity Tests

ＴｈｅＶｅｒｔｉｃａｌＴｒａｎｓｐｏｒｔｏｆＡｉｒＰｏｌｌｕｔａｎｔｓｂｙＣｏｎｖｅｃｔｉｖｅＣｌｏｕｄｓＰａｒｔⅡ：ＴｒａｎｓｐｏｒｔｏｆＳｏｌｕｂｌｅＧａｓｅｓａｎｄＳｅｎｓｉｔｉｖｉｔｙＴｅｓｔｓＫｏｎｇＦａｎｙｏｕ（孔凡铀）（Ｄｅｐａｒｔｍｅ...     

Nonlinear Retrieval of Atmospheric Ozone Profile from Solar Backscatter Ultraviolet Measurements:Theory and Simulation

ＮｏｎｌｉｎｅａｒＲｅｔｒｉｅｖａｌｏｆＡｔｍｏｓｐｈｅｒｉｃＯｚｏｎｅＰｒｏｆｉｌｅｆｒｏｍＳｏｌａｒＢａｃｋｓｃａｔｅｒＵｌｔｒａｖｉｏｌｅｔＭｅａｓｕｒｅｍｅｎｔｓ：ＴｈｅｏｒｙａｎｄＳｉｍｕｌａｔｉｏｎ①ＬｉＪｕｎ（李俊）ａｎｄＬｕＤａｒｅｎ...     

利用一维时间序列重建动力系统的初步研究

通过对月平均气温一维时间序列作相空间拓展,和假定相空间状态变量随时间的演化方程含有线性和非线性二次项,再根据拓展后的资料进行拟合,利用最小二乘法求出各项系数,保留其方差贡献大的项,以重建动力系统.实际计算结果表明,重建的低阶动力系统有可能对月平均气温所表征的短期气候演化过程的非线性特性作出描写.     

利用─维时间序列重建动力系统的进一步研究

对月平均气温一维时间序列作相空间拓展，并根据系统的分维数设定重建的动力系统，且在具有二次非线性项的假定下，利用最小二乘法求解相空间状态演化方程中的各项系数，以重建动力系统。结果表明：随相空间维数的增加，重建的动力系统对气候演化过程可作出更精确、细致的描述。     

月尺度气温可预报性对资料长度的依赖及可信度

利用全国518个站1960—2011年逐日气温观测资料和160个站1983—2012年月尺度气温客观预测数据,基于非线性局部Lyapunov指数和非线性误差增长理论,研究中国区域月尺度气温可预报性期限对资料序列长度的依赖性。结果表明:气温可预报性期限对资料序列的长度有一定程度的依赖性,在西北、东北及华中地区尤为明显。平均而言,45年的资料序列长度才能够得到稳定合理的可预报性期限。为了验证气温可预报期限计算结果的可信度,将月尺度气温的可预报性期限与客观气候预测方法的预报评分技巧进行对比,发现两者结果非常一致。其中,由观测资料得到的1月气温的可预报性期限明显低于7月,1月客观气候预测方法的预报评分技巧也明显低于7月,且1月 (7月) 预报评分的空间分布型与1月 (7月) 气温可预报性期限的空间分布型较为一致。因此,利用非线性局部Lyapunov指数和台站逐日观测资料分析气温的可预报性期限结果是可信的。     

基于改进EMD算法和BP神经网络的SST预测研究

海洋表面温度(Sea Surface Temperature,SST)具有非平稳、非线性的特征,直接将处理平稳数据序列的方法应用到非平稳非线性特征明显的序列上显然是不合适的,预测的误差将会很大。为了提高预测精度,更好地解决非平稳非线性序列预测的问题,本文以东北部太平洋(40°N~50°N、150°W~135°W)区域的月平均海洋表面距平温度为例,首先分别应用集合经验模态分解(EEMD)和互补集合经验模态分解(CEEMD)方法将SST分解为不同尺度的一系列模态分量(IMF),再运用BP(Back Propagation)神经网络模型对每一个模态分量进行分析预测,最后将各IMF预测结果进行重构得到SST的预测值。数值试验的结果表明,CEEMD分解精度比EEMD分解精度高,CEEMD提高了基于BP神经网络的预测精度。系列试验统计分析说明应用这种方法对SST的1年预测是有效的。     

Monthly Mean Temperature Prediction Based on a Multi－level Mapping Model of Neural Network BP Type

In terms of 34-year monthly mean temperature series in 1946-1979, the multi-level mapping model of neural network BP type was applied to calculate the system’s fractual dimension D0 = 2.8, leading to a three-level model of this type with i × j = 3 × 2, k = 1, and the 1980 monthly mean temperture prediction on a long-term basis were pre-pared by steadily modifying the weighting coefficient, making for the correlation coefficient of 97% with the measurements. Furthermore, the weighting parameter was modified for each month of 1980 by means of observations, therefore constructing monthly mean temperature forecasts from January to December of the year, reaching the correlation of 99.9% with the measurements. Likewise, the resulting 1981 monthly predictions on a long-range basis with 1946-1980 corresponding records yielded the correlation of 98% and the month-to month forecasts of 99.4%.     

Experiments of Reconstructing Discrete Atmospheric Dynamic Models from Data (I)

In this paper, we give some experimental results of our study in reconstructing discrete atmospheric dynamic models from data. After a great deal of numerical experiments, we found that the logistic map, xn +1= 1-uxn2 could be used in monthly mean temperature prediction when it was approaching the chaotic region, and its predictive results were in reverse states to the practical data. This means that the nonlinear developing behavior of the monthly mean temperature system is bifurcating back into the critical chaotic states from the chaotic ones.     

河北保定气象站长序列气温资料缺测记录插补和非均一性订正

基于多源的气温月值资料,在数据整合和初步质量控制基础上,同时采用标准化序列法和多元线性回归法对河北保定气象站1913-2014 年月平均气温、最高气温和最低气温资料进行了插补。通过交叉检验法分析发现,标准化序列法插补得到的气温序列效果较好,并且气候统计特征与同区域周边站的研究结果更具一致性。利用惩罚最大F 检验（PMF）对插补后序列的均一性进行了检验,结果表明：通过插补得到的保定站百年气温月值序列的均一性相对较好,仅月平均最低气温序列存在2 个显著间断点,分别由同类型仪器的更换和台站迁移导致,研究中采用分位数匹配（QM）对其进行了订正,建立了保定站百年气温月值序列。通过与邻近单站及我国中东部区域均一化百年气温序列的综合对比显示,本文建立的保定站百年气温月值序列与邻近单站的相关性基本达到0.8 以上;从增暖趋势来看,保定站与中东部区域平均序列分别达0.121 ℃/10a、0.204 ℃/10a,基本在同一量级内：这一定程度上说明建立的保定站百年气温序列相对合理。     

Climate change detection and annual extreme temperature analysis of the Irtysh Basin

As the largest tributary of the Ob River, the Irtysh River is an international river partially joining the territories of China, Kazakhstan, and Russia. Four meteorological stations in the Irtysh Basin were selected and the long-term observed daily temperature data were collected. The extreme temperature change was analyzed considering climate change. Detected by the heuristic segmentation by histogram comparison approach, climate was changed during the first half of the 1970s in terms of the increased mean value and decreased standard deviation of the daily temperature series. The noticeable change of the monthly mean temperature was the warmer winter. After climate change, the annual maximum temperature was little changed and its series was not segmented. However, the annual minimum temperature was significantly changed in terms of the increased mean value by more than 2°C, so its series was segmented to the pre- and post-change point subseries. The generalized extreme value distribution was fitted to the annual extreme temperature and the parameters were estimated by the maximum likelihood method. The return levels for 10/50/100-year return periods estimated by the profile likelihood method were obtained for the annual extreme temperature. The probability of occurrence of the cold extremes was decreased after 1970s.     

气温的天气和气候记忆性特征分析:以济南和青岛为例

气温的天气和气候记忆性特征分析对于提高气候预测水平具有积极意义。利用济南和青岛1961—2020 年逐日、月和年平均气温资料,运用自相关性函数和标准化频率分布分析了上述时间序列的气温记忆性特征和概率分布特征,并利用结构函数法建立了月、年平均气温距平与日平均气温距平之间的分数阶导数关系。结果表明:(1)济南和青岛的月、年平均气温距平呈现不同程度的记忆性特征,其中年平均气温距平相比于月平均气温距平具有更好的记忆性。(2)济南和青岛的月、年平均气温距平与日平均气温距平之间存在分数阶导数关系,济南和青岛相应的月、年尺度阶数分别为0. 529、0. 665 和0. 553、0. 791,两地的月尺度阶数相近,但青岛略大,青岛的年尺度阶数大于济南,即青岛月和年平均气温距平的记忆性大于济南。(3)济南和青岛的月和年平均气温距平相比于日平均气温距平有不同程度的长尾特征,长尾特征反映了极值温度发生的概率。