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

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.     

Changes in the boreal summer intraseasonal oscillation projected by the CNRM-CM5 model under the RCP 8.5 scenario

Climate Dynamics - The 30–60-day boreal summer intraseasonal oscillation (BSISO) is the predominant intraseasonal variability in the Asian summer monsoon (ASM) region, representing the...     

1951—2015年乌鲁木齐市升温过程频数及强度气候特征

利用乌鲁木齐市气象站1951年1月1日至2015年12月31日的逐日气温资料,以日最高气温及其升温幅度为指标,整理出乌鲁木齐市近65年升温过程数据库,将升温过程分为Ⅰ级(弱)、Ⅱ级(中等强度)、Ⅲ级(较强)、Ⅳ级(强)以及Ⅴ级(极强)5个等级,分析了乌鲁木齐市各级升温过程发生频数、持续日数、过程不同时段升温幅度、过程最高气温、过程最高气温距平偏高幅度等要素气候特征。结果如下：(1)1951—2015年,乌鲁木齐市出现升温过程5677次,平均每年87.3次,其中Ⅰ级(弱)升温过程占67.8 %。升温过程发生频数的季节分布较均匀,但在春季相对较多。近65年来,年平均升温过程发生频数在7个年代际中差异不大,没有明显的线性变化趋势。(2)1951—2015年,乌鲁木齐市5677次升温过程的平均持续日数为2.14?d,其中持续1 d的过程占43.0 %。随升温过程等级由Ⅰ级到Ⅴ级提高,过程持续日数最高出现频率也从1?d过渡到3?d。升温过程持续日数在春季4、5月份最长。(3)1951—2015年,乌鲁木齐市过程升温幅度平均为5.76℃,在春季最大、秋季最小。Ⅳ级(强)以及Ⅴ级(极强)的过程升温幅度最大的月份分别是5月和3月。65年来,乌鲁木齐市升温过程的最大24h、48h和72h升温幅度平均值分别为3.72℃、6.12℃和8.23℃,最大24 h升温幅度在冬季最大、夏季最小,最大48 h和72 h升温幅度都是在春季最大、秋季最小。(4)1951—2015年,乌鲁木齐市升温过程的最高气温平均值为14.52℃,在夏季7、8月最高,在冬季各月最低,带有显著的季节背景特征。过程最大日气温距平的平均值为2.93℃。Ⅳ级(强)和Ⅴ级(极强)升温过程的日气温距平偏高幅度最大月份分别出现在1月(11.73℃)和12月(19.10℃)。     

准噶尔盆地油气源、油气分布与油气系统

准噶尔盆地是中国西部典型的多旋回叠合盆地,发育有石炭系、二叠系、三叠系、侏罗系、白垩系和古近系6套烃源岩,同时存在6大类原油和3大类天然气,广泛分布于盆地不同地区。西北缘原油总体相似,碳同位素组成轻(δ~(13)C-29‰),胡萝卜烷、类异戊二烯烷烃、三环萜烷、伽马蜡烷丰富,甾烷以C_(28)、C_(29)为主,基本没有重排甾烷,为第二类原油,来源于二叠系湖相烃源岩。腹部绝大多数原油与西北缘原油相似,但胡萝卜烷、类异戊二烯烷烃、伽马蜡烷等有差异,来源于不同凹陷的二叠系湖相烃源岩;少量原油碳同位素组成重(δ~(13)C-28‰~-26‰),Pr/Ph大于2.5,三环萜烷以C_(19)、C_(20)为主,藿烷丰富而伽马蜡烷极低,以C_(29)规则甾烷及重排甾烷为主,为第四类原油,来源于侏罗系煤系烃源岩。东部存在5种类型原油,第一类原油碳同位素组成特别重(δ~(13)C-26‰),来源于石炭系烃源岩;第二类原油与腹部地区绝大多数原油十分相似,来源于二叠系湖相烃源岩;第三类原油碳同位索组成轻,重排甾烷、Ts、C_(29)Ts及C_(30)重排藿烷异常丰富,来源于中上三叠统湖相烃源岩;第四类原油源于侏罗系煤系烃源岩;混合类原油为二叠系、三叠系、侏罗系原油的混合,各自贡献平均分别为20%、15%和65%。南缘存在4类典型原油,为第二、第四、第五和第六类原油,其中第二、第四类分别源于二叠系和侏罗系;第五类原油碳同位素组成轻(δ~(13)C-29‰)、Pr/Ph1.0、伽马蜡烷丰富且有两个异构体、Ts、C_(29)Ts、C_(30)重排藿烷、C_(27)~C_(29)异胆甾烷及C_(30)甲基甾烷丰富,来源于白垩系湖相烃源岩;第六类原油主要为中低成熟原油,碳同位素组成δ~(13)C~28‰~-26‰,C_(27)、C_(28)、C_(29)甾烷呈"V"型分布,甲藻甾烷异常丰富,来源于古近系湖相烃源岩。准噶尔盆地天然气有油型气、混合气和煤型气,前两类主要来源于二叠系湖相烃源岩和石炭系海相烃源岩,煤型气主要来源于石炭系和侏罗系煤系烃源岩。不同类型油气分布与不同时代烃源灶具有良好对应关系:石炭系油气主要分布于陆东-五彩湾;二叠系油气主要分布于西北缘、腹部与东部;三叠系原油仅分布于东部;侏罗系原油主要分布于东部与南部;白垩系原油仅分布于南缘中部;古近系原油仅分布于南缘西部。按照盆地构造特征及不同时代烃源灶与油气关系,将准噶尔盆地划分为西部、中部、东部、南部及乌伦古5个油气系统及15个子油气系统。     

Fifteen Years of Ocean Observations with China Argo

For 15 years since the beginning of China Argo project, China has deployed over 350 profiling floats in Pacific and Indian ocean, and constructed China Argo ocean observing network. Moreover, we have setup the Argo data receiving, processing and distributing system, and developed various Argo data products using Argo observations, which has promoted the progress of ocean data sharing in China. The abundant Argo data have become a main data source in oceanic and atmospheric basic researches and operational applications. A batch of important achievements in basic research and operational application have been brought, e.g. in aspects of tropical cyclone (typhoon), ocean circulation, meso-scale eddy, turbulence, heat/salt storage and transport and water mass, as well as in ocean, atmosphere/climate operational forecasting and predicting. With the extension of the international Argo program from “Core Argo” to “Global Argo”, we are faced with great challenges in the long-term maintaining and sustained developing of our Argo ocean observing network. It is suggested that we should take the opportunity to construct China regional Argo ocean observing network as soon as possible in adjacent northwestern Pacific and Indian ocean using Chinese BeiDou profiling floats, which will make us to take responsibility and obligation of a big country for addressing global climate changes and preventing natural disasters.     

Logs Fluid Typing Methods and Adaptive Analysis of Tight Sandstone Reservoir of Yingcheng Formation in Lishu Fault

Tight clastic reservoirs are characterized with low porosity and low permeability, which reduce contributions of reservoir fluids to geophysical logging responses, and it is more difficult to identify fluids of the reservoir. Therefore, it is necessary to study log interpretation and comprehensive evaluation methods for such clastic reservoirs. This study focused on geological characteristics of tight clastic reservoir of Yingcheng formation in Lishu Fault. Based on logs sensitivity to fluids, some fluid typing methods were discussed in detail, which included log curve overlap method, acoustic time overlapping method from density and neutron logs, porosity difference and ratio method, porosity-resistivity crossplot, normal distribution method, and other methods, and some effective fluid evaluation method were established and optimized. These above-mentioned methods were verified, which could achieve layer qualitative identification of tight sandstone in the study area. By contrast, two logs overlapping methods, porosity difference and ratio method, resistivity-porosity crossplot are more suitable for natural gas reservoirs, while porosity difference and ratio method, porosity-resistivity chart, normal distribution method are more suitable for oil and water reservoirs. The case study suggests that these methods be combined to archive more correct log interpretation in the study area, which provides important decision-making reference for oilfield exploration and development.     

加权Logistic回归模型在火山岩型铜矿预测中的应用:以宁芜盆地中段为例

文中探讨了加权Logistic回归模型在宁芜盆地中段火山岩型铜矿预测中的应用。首先,结合研究区的成矿地质背景,提取地质体、构造、围岩蚀变三大类证据因子;其次,分析各证据因子与铜矿点之间的空间关系,认为姑山旋回、娘娘山旋回火山机构控制了本区火山岩型铜矿的空间分布,根据计算结果,选取与火山岩型铜矿密切相关的龙王山组、姑山组地层,姑山旋回粗面斑岩、娘娘山旋回二长斑岩、NW向构造1.5 km缓冲区、NE向构造1.3 km缓冲区、EW向构造4.5 km缓冲区、硅化、褐铁矿化、黄铜矿化等作为模型自变量;最后采用加权Logistic回归模型进行成矿概率计算,并结合成矿地质背景,圈定四个成矿远景区,分别为P1、P2、P3、P4,其中P1、P2、P3呈北东向展布,主要受娘娘山和姑山火山机构控制,P4为东西向分布,主要受龙王山火山机构控制,在这些预测区中,均存在已发现的铜矿体,说明预测可信度较高。     

Regional debris flow susceptibility analysis based on principal component analysis and self-organizing map: a case study in Southwest China

A method was developed to analyze the susceptibilities of 541 regional basins affected by debris flows at the Wudongde Dam site in southwest China. Determining susceptibility requires information on source material quantity and occurrence frequency. However, the large number of debris flows can hinder the individual field investigation in a each small basin. Factors that may trigger debris flows can be identified using remotely sensed interpretation information. Susceptibility analysis can then be conducted based on these factors. In this study, SPOT5 satellite imagery, digital elevation models (DEM), a lithology distribution map, and rainfall monitoring data were used to identify 12 debris flow trigger factors: basin relief ratio, slope gradient in the initiation zone, drainage density, downslope curvature of the main channel, vegetation coverage, main channel aspect, topographic wetness index, Melton’s ruggedness number, lithology, annual rainfall, form factor, and cross-slope curvature of the transportation zone. Principal component analysis was used to obtain the eight principal components of these factors that contribute to susceptibility results. Then, a self-organizing map method was adopted to analyze the principal components, which resulted in a debris flow susceptibility classification. Field validation of 26 debris flow basins was used to evaluate the errors of the susceptibility classification, as well as assess the causes of such errors. The study found that principle component analysis and self-organizing map methodologies are good predictors of basin susceptibility to debris flows.     

日本囊对虾Marsupenaeus japonicus)组织蛋白酶D基因克隆及表达分析

组织蛋白酶D是溶酶体天冬氨酸蛋白酶家族的主要成员,广泛参与动物机体细胞内蛋白质的降解过程,对维持细胞稳态和正常代谢具有重要的作用。为研究组织蛋白酶D在甲壳动物非特异性免疫和幼体发育过程中的作用,本研究采用RACE技术首次克隆得到日本囊对虾组织蛋白酶D基因cDNA序列,命名为MjCatD,其中开放阅读框长为1161 bp,编码386个氨基酸残基。序列分析和同源建模显示该基因编码的蛋白含有保守的N-糖基化位点、天冬氨酸蛋白酶签名序列、酶活化位点和非消化性组织蛋白酶D的特征序列,并且呈保守的双叶形结构。同源性比较和系统进化分析发现,MjCatD与斑节对虾、美洲螯龙虾和脊尾白虾相似性较高,并且与它们紧密聚为一支。实时荧光定量PCR结果显示,MjCatD基因在日本囊对虾多个组织中均有表达,其中肝胰腺中表达量最高。在白斑综合征病毒(white spot syndrome virus, WSSV)感染后3～24 h日本囊对虾肝胰腺中MjCatD的表达量逐渐下降,而在48 h急剧上调至最高表达量并且与对照组差异极显著(P<0.01)。此外,MjCatD基因在幼体发育不同阶段中也表现出明显的变化趋势。以上研究表明,MjCatD基因可能参与日本囊对虾先天免疫反应和幼体发育过程。