Season-dependent predictability and error growth dynamics of Pacific Decadal Oscillation-related sea surface temperature anomalies     

Wansuo Duan  Yujie Wu 《Climate Dynamics》2015,44(3-4):1053-1072

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2013—2019年度海洋科学技术奖计量统计及其科研合作网络分析          下载免费PDF全文

赵晓龙  李保石  王泉斌 《海洋开发与管理》2020,37(11):19-27

文章基于2013—2019年度海洋科学技术奖，运用计量统计、社会网络分析等研究方法，探究海洋科学技术奖获奖成果计量特征、学科分布、获奖机构及其科研合作关系等，直观揭示海洋科学技术奖所构成的科研合作范式、科研合作网络结构等，以期为海洋科研管理、科技创新和学科建设等提供科学参考。研究表明：整体上，海洋科学技术奖获奖成果呈逐年递增趋势，一等奖与二等奖的获奖等级比值呈下降趋势；学科划分上，获奖成果主要隶属于“海洋科学”学科，又以海洋生物学、海洋装备与设备、海洋化学和物理海洋学为主体；获奖机构方面，海洋科学技术奖已奖励包括中国海洋大学和中国科学院海洋研究所等涉海类高校和科研院所在内的各类海洋科技创新主体285家，分布在山东、浙江、广东、上海、北京、江苏等19个省（市、自治区）；科研合作方面，海洋科学技术奖获奖核心机构所构建的科研合作关系紧密，以自然资源部第二海洋研究所的中心度最高，中国海洋大学的中间中心度最高，其控制该科研合作网络中其他机构之间沟通交流的力度最大。  相似文献   

Spatiotemporal characteristics of Qinghai Lake ice phenology between 2000 and 2016     

Qi  Miaomiao  Yao  Xiaojun  Li  Xiaofeng  Duan  Hongyu  Gao  Yongpeng  Liu  Juan 《地理学报(英文版)》2019,29(1):115-130

Journal of Geographical Sciences - Lake ice phenology is considered a sensitive indicator of regional climate change. We utilized time series information of this kind extracted from a series of...  相似文献   

Generation of continuous surface soil moisture dataset using combined optical and thermal infrared images          下载免费PDF全文

Pei Leng  Xiaoning Song  Si‐Bo Duan  Zhao‐Liang Li 《水文研究》2017,31(6):1398-1407

Surface soil moisture (SSM) is a critical variable for understanding water and energy flux between the atmosphere and the Earth's surface. An easy to apply algorithm for deriving SSM time series that primarily uses temporal parameters derived from simulated and in situ datasets has recently been reported. This algorithm must be assessed for different biophysical and atmospheric conditions by using actual geostationary satellite images. In this study, two currently available coarse‐scale SSM datasets (microwave and reanalysis product) and aggregated in situ SSM measurements were implemented to calibrate the time‐invariable coefficients of the SSM retrieval algorithm for conditions in which conventional observations are rare. These coefficients were subsequently used to obtain SSM time series directly from Meteosat Second Generation (MSG) images over the study area of a well‐organized soil moisture network named REMEDHUS in Spain. The results show a high degree of consistency between the estimated and actual SSM time series values when using the three SSM dataset‐calibrated time‐invariable coefficients to retrieve SSM, with coefficients of determination (R²) varying from 0.304 to 0.534 and root mean square errors ranging from 0.020 m³/m³ to 0.029 m³/m³. Further evaluation with different land use types results in acceptable debiased root mean square errors between 0.021 m³/m³ and 0.048 m³/m³ when comparing the estimated MSG pixel‐scale SSM with in situ measurements. These results indicate that the investigated method is practical for deriving time‐invariable coefficients when using publicly accessed coarse‐scale SSM datasets, which is beneficial for generating continuous SSM dataset at the MSG pixel scale.  相似文献   

Operational climate prediction in the era of big data in China: Reviews and prospects     

王昕  宋连春  王国复  任宏利  吴统文  贾小龙  吴焕萍  吴捷 《Acta Meteorologica Sinica》2016,30(3):444-456

Big data has emerged as the next technological revolution in IT industry after cloud computing and the Internet of Things. With the development of climate observing systems, particularly satellite meteorological observation and high-resolution climate models, and the rapid growth in the volume of climate data, climate prediction is now entering the era of big data. The application of big data will provide new ideas and methods for the continuous development of climate prediction. The rapid integration, cloud storage, cloud computing, and full-sample analysis of massive climate data makes it possible to understand climate states and their evolution more objectively, thus predicting the future climate more accurately. This paper describes the application status of big data in operational climate prediction in China; it analyzes the key big data technologies, discusses the future development of climate prediction operations from the perspective of big data, speculates on the prospects for applying climatic big data in cloud computing and data assimilation, and puts forward the notion of big data-based super-ensemble climate prediction methods and computerbased deep learning climate prediction methods.  相似文献   

A timescale decomposed threshold regression downscaling approach to forecasting South China early summer rainfall     

Linye Song  Wansuo Duan  Yun Li  Jiangyu Mao 《大气科学进展》2016,33(9):1071-7084

A timescale decomposed threshold regression(TSDTR) downscaling approach to forecasting South China early summer rainfall(SCESR) is described by using long-term observed station rainfall data and NOAA ERSST data. It makes use of two distinct regression downscaling models corresponding to the interannual and interdecadal rainfall variability of SCESR.The two models are developed based on the partial least squares(PLS) regression technique, linking SCESR to SST modes in preceding months on both interannual and interdecadal timescales. Specifically, using the datasets in the calibration period 1915–84, the variability of SCESR and SST are decomposed into interannual and interdecadal components. On the interannual timescale, a threshold PLS regression model is fitted to interannual components of SCESR and March SST patterns by taking account of the modulation of negative and positive phases of the Pacific Decadal Oscillation(PDO). On the interdecadal timescale, a standard PLS regression model is fitted to the relationship between SCESR and preceding November SST patterns. The total rainfall prediction is obtained by the sum of the outputs from both the interannual and interdecadal models. Results show that the TSDTR downscaling approach achieves reasonable skill in predicting the observed rainfall in the validation period 1985–2006, compared to other simpler approaches. This study suggests that the TSDTR approach,considering different interannual SCESR-SST relationships under the modulation of PDO phases, as well as the interdecadal variability of SCESR associated with SST patterns, may provide a new perspective to improve climate predictions.  相似文献   

2014—2016年超强厄尔尼诺事件的气候影响   总被引：7，自引：4，他引：3  

袁媛  高辉  贾小龙  万江华 《气象》2016,42(5):532-539

2014—2016年,赤道中东太平洋发生了一次超强厄尔尼诺事件,此次事件于2015年11月达到峰值,12月开始衰减。其峰值强度超过了1951年以来另外两次超强厄尔尼诺事件（1982/1983年和1997/1998年）的强度,成为了1951年以来最强的事件。截至2016年4月,事件已持续20个月,也成为了1951年以来持续时间最长的厄尔尼诺事件。在这次事件的发展过程中,热带太平洋至东亚副热带地区的大气环流表现出了显著的响应特征：赤道中东太平洋对流活动加强,异常上升运动发展,而赤道西太平洋对流活动受抑制,异常下沉运动控制;菲律宾附近异常反气旋生成并发展加强,西太平洋副热带高压强度偏强、西伸脊点异常偏西,尤其2015年冬季副热带高压强度为1980年以来最强。与此同时,2015年秋、冬季,我国长江以南大部降水偏多,尤其冬季华南地区（广东、广西、海南三省区）平均降水量达历史第一,较常年偏多1.6倍以上。近期,超强厄尔尼诺正处于衰减阶段,但是考虑到热带印度洋暖海温的“接力”作用,厄尔尼诺事件对2016年春、夏季我国气候异常的影响可能仍将持续。  相似文献   

基于部分最小二乘岭估计的粗差定值定位     

金丽宏  吕玉婷  汪耀  许运鹏  张小龙 《测绘工程》2016,25(6):61-64

在利用部分最小二乘原理进行粗差定值定位时,模型的法方程矩阵可能存在病态性,使得到的粗差定值定位结果不可靠。文中针对观测数据包含多个粗差且法方程病态问题,利用岭估计处理病态问题,建立部分最小二乘岭估计的粗差定值定位方法,给出粗差搜索步骤,利用迭代算法实现多个粗差的定值和定位。通过模拟算例分析部分最小二乘法、部分最小二乘岭估计在粗差搜索方面的效果,从另一个角度探讨粗差处理方法,推广现有的误差理论,证明文中方法的有效性。  相似文献   

A Method for Dynamic Risk Assessment and Management of Rockbursts in Drill and Blast Tunnels     

Guo-Feng Liu  Xia-Ting Feng  Guang-Liang Feng  Bing-Rui Chen  Dong-Fang Chen  Shu-Qian Duan 《Rock Mechanics and Rock Engineering》2016,49(8):3257-3279

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胶州湾沉积物重金属形态不同浸取方法的比较与污染讯息指示作用初探   总被引：1，自引：0，他引：1  

梁宪萌  宋金明  段丽琴  袁华茂  李宁  李学刚 《海洋学报》2016,38(10):12-21

海洋沉积物中重金属的活性形态对于指示沉积物污染状况具有重要作用;为探寻简洁且能够有效提取重金属活性形态的浸提方法;实验研究了0.1 mol/L和1 mol/L盐酸的单级提取和欧共体标准局（European Community Bureau of Reference）提出的BCR分级提取法对胶州湾表层沉积物中重金属（Cr、Cu、Ni、Pb、Zn）和Al、Fe、Mn的浸取效果。结果显示;3种提取方法提取的金属含量呈显著正相关关系;两种浓度的稀盐酸对BCR方法中的酸可提取态和可还原态金属均具有较好浸提效果;但对可氧化态金属浸提能力相对较弱。不同提取方法的人为信号指数（ASI）计算结果表明;BCR浸取法提取结果的金属ASI值最大;表明其对沉积物中金属活性形态提取效率较高;1 mol/L HCl提取结果的金属ASI值最低;可能是较高浓度强酸使沉积物较大颗粒内层中“惰性”金属被浸取出来;“增加”了金属活性组分的污染讯息信号;对沉积物中Cu、Pb和Zn而言;0.1 mol/L HCl提取结果的ASI值与BCR方法接近。经过Al归一化后;0.1 mol/L HCl浸提的重金属含量的空间分布与胶州湾的实际污染状况相吻合;表明0.1 mol/L的HCl在一定程度上能够代替复杂的BCR浸取法;此方法可简化重金属活性形态的提取步骤;适合大范围沉积物重金属污染评价。  相似文献