排序方式： 共有13条查询结果，搜索用时 171 毫秒
1.
2.
应用陆地卫星 TM 资料对南盘江地区进行了烃类微渗漏蚀变信息检测研究。岩石土壤地球化学特征分析表明,该区不同程度地存在着“褪红”、“粘土矿化”、“碳酸盐矿化”等烃类蚀变异常现象。选择 FeO/Fe_2O_3作为褪红的成分因子;(K_2O+Na_2O+Al_2O_3)、(K_2O+Na_2O)/Al_2O_3、(K_2O+Na_2O+Al_2O_3)/S∶O_2和 K_2O/Na_2O 等作为粘土矿化的成分因子;CaO+MgO 和 CaO/MgO 作为碳酸盐矿化的成分因子。利用 TM1/TM3、TM1/TM4识别褪红蚀变信息,TM5/TM7、TM5/TM4用干识别粘土矿化和碳酸盐矿化蚀变信息。建立了地球化学—光谱—遥感图像三位一体的遥感找油气模式,根据油气遥感色调异常对南盘江地区进行了评价和分类。 相似文献
3.
Shaolei TANG Jing-Jia LUO Jiaying HE Jiye WU Yu ZHOU Wushan YING 《大气科学进展》2021,38(12):2023-2039,中插8-中插11
The extreme floods in the Middle/Lower Yangtze River Valley (MLYRV) during June?July 2020 caused more than 170 billion Chinese Yuan direct economic losses. Here, we examine the key features related to this extreme event and explore relative contributions of SST anomalies in different tropical oceans. Our results reveal that the extreme floods over the MLYRV were tightly related to a strong anomalous anticyclone persisting over the western North Pacific, which brought tropical warm moisture northward that converged over the MLYRV. In addition, despite the absence of a strong El Ni?o in 2019/2020 winter, the mean SST anomaly in the tropical Indian Ocean during June?July 2020 reached its highest value over the last 40 years, and 43％ (57％) of it is attributed to the multi-decadal warming trend (interannual variability). Based on the NUIST CFS1.0 model that successfully predicted the wet conditions over the MLYRV in summer 2020 initiated from 1 March 2020 (albeit the magnitude of the predicted precipitation was only about one-seventh of the observed), sensitivity experiment results suggest that the warm SST condition in the Indian Ocean played a dominant role in generating the extreme floods, compared to the contributions of SST anomalies in the Maritime Continent, central and eastern equatorial Pacific, and North Atlantic. Furthermore, both the multi-decadal warming trend and the interannual variability of the Indian Ocean SSTs had positive impacts on the extreme floods. Our results imply that the strong multi-decadal warming trend in the Indian Ocean needs to be taken into consideration for the prediction/projection of summer extreme floods over the MLYRV in the future. 相似文献
4.
近年来,随着人工智能技术在多个领域大数据分析中的应用,许多研究工作者尝试将地学研究与人工智能跨学科结合,取得了很多新的进展,推动了地球科学的发展。其中气候预测与人类生活以及防灾减灾等息息相关,准确的气候预测至关重要。本文简要总结了人工智能技术在气候预测应用方面的研究进展,包括资料同化、模式参数化、求解偏微分方程、构建统计预测模型、改进数值模式产品释用等领域。这些研究证明了利用人工智能提高气候预测技巧的可能性和适用性,可以极大地节省计算成本和时间。然而人工智能应用也存在诸多挑战,例如数据集的构建、模型的适用性和物理可解释性等问题,对这些难点问题的研究和攻克,可以让人工智能在大数据时代中更好地补充传统地球科学方法,产生更多有益的效应,极大地改进气候预测水平。 相似文献
5.
YAN Yi LIN Ge XIA Bin LI Zi''an LI Zhongcheng Key Laboratory of Marginal Sea Geology Guangzhou Institute of Geochemistry South China Sea Institute of Oceanology Guangzhou Institute of Geochemistry Chinese Academy of Sciences Wushan Guangzhou Guangdong Jidong Oil Gas Administration Tangshan Hebei 《《地质学报》英文版》2005,79(2):254-263
1 IntroductionThe Yan-Liao orogenic belt lies in the northern segmentof the North China Block (NCB) (Fig. 1). During Mesozoicto Cenozoic time, it experienced intense tectono-magmaticactivation, accompanied by the formation ofintracontinental basins and widespread magmatism and is avery important area to study continental dynamics andMeso-Cenozoic tectonic evolution in eastern China. Mostof previous work in this area has focused on the formationof basement, structural style and volcano-se… 相似文献
6.
MASUSDA Akimasa 《《地质学报》英文版》2004,78(5):1109-1121
Rare earth element (REE) contents, and Sr and Nd isotopic compositions were measured for three suites of mantle xenoliths from the Kuandian, Hannuoba and Huinan volcanoes in the north of the Sino-Korean Platform. From the correlations of Yb contents with Al/Si and Ca/Si ratios, the peridotites are considered to be the residues of partial melting of the primitive mantle. The chondrite-normalized REE compositions are diverse, varying from strongly LREE-depleted to LREE-enriched, with various types of REE patterns. Metasomatic alteration by small-volume silicate melts, of mantle peridotites previously variably depleted due to fractional melting in the spinel peridotite field, can account for the diversity of REE patterns. The Sr/ Ba versus La/Ba correlation indicates that the metasomatic agent was enriched in Ba over Sr and La, suggestive of its volatile-rich signature and an origin by fluid-triggered melting in an ancient subduction zone. The Sr and Nd isotopic compositions of these xenoliths, even from 相似文献
7.
在川、滇、黔三省晚二叠世峨眉山玄武岩省的中部，产于攀西古裂谷内的龙帚山火山岩建造自下而上有4个喷发旋回：拉斑玄武岩、碱玄响岩、钾粗面玄武岩以及拉斑玄武岩。上下两个玄武岩旋回的岩性与该裂谷带以外大面积展布的高钛玄武岩岩性相同；而其碱玄响岩旋回主要由响碱玄岩—碱玄响岩—响岩岩系组成，夹粗安岩和安粗岩层，此旋回厚达千米，类似于非洲肯尼亚裂谷带的高原溢流响岩岩系。龙帚山晚二叠世火山岩建造的层序和岩石组合不同于古裂谷带外正常的大陆板内暗色岩喷出相的层序和岩浆演化规律，可能是地幔热柱和裂谷背景下岩石圈拉张复合作用的结果。 相似文献
8.
江西雅山黄玉锂云母花岗岩属典型的华南[富氟高磷花岗岩（P2O5＝0．15％－0．55％），表现为富氟（F＝1．07％－2．04％），强过铝性（A／NKC＝1．26－1．60），具有很高的Li,Rb,Cs,Be,Nb,Ta含量和很低的Y、REE含量.磷锂铝石是雅山黄玉锂云母花岗岩中的主要磷酸盐矿物，其产出与否同体的Li,Rb,Cs含量密切相关；磷锂铝石和长石矿物都是雅山黄玉锂云母花岗岩中磷的主要贮体，并且相互之间呈互补关系，当出现磷锂铝石时，磷锂铝石为全岩磷的主要贡献者，当无磷锂铝石晶出时，长石矿物为全岩磷的主要贡献者，体系的强过铝性以及很低的REE，Y，Ca含量使得磷灰石，独居石，磷钇矿都难以达到饱和结晶，磷灰石为少量出现，并且大部分为晚期形成；独居石和磷钇矿都为极少出现，反映出雅山岩体演化过程中具有独居石，磷钇矿等稀土磷酸盐矿物的结晶分离，铍磷酸盐矿物－羟磷铍钙石的出现反映了雅山黄玉锂云母花岗岩存在岩浆期后的含Be,Ca热液流体的作用。 相似文献
9.
Shaolei TANG Jing-Jia LUO Jiaying HE Jiye WU Yu ZHOU Wushan YING 《大气科学进展》2021,38(12):2023-2039,中插8-中插11
The extreme floods in the Middle/Lower Yangtze River Valley (MLYRV) during June?July 2020 caused more than 170 billion Chinese Yuan direct economic losses. Here, we examine the key features related to this extreme event and explore relative contributions of SST anomalies in different tropical oceans. Our results reveal that the extreme floods over the MLYRV were tightly related to a strong anomalous anticyclone persisting over the western North Pacific, which brought tropical warm moisture northward that converged over the MLYRV. In addition, despite the absence of a strong El Ni?o in 2019/2020 winter, the mean SST anomaly in the tropical Indian Ocean during June?July 2020 reached its highest value over the last 40 years, and 43％ (57％) of it is attributed to the multi-decadal warming trend (interannual variability). Based on the NUIST CFS1.0 model that successfully predicted the wet conditions over the MLYRV in summer 2020 initiated from 1 March 2020 (albeit the magnitude of the predicted precipitation was only about one-seventh of the observed), sensitivity experiment results suggest that the warm SST condition in the Indian Ocean played a dominant role in generating the extreme floods, compared to the contributions of SST anomalies in the Maritime Continent, central and eastern equatorial Pacific, and North Atlantic. Furthermore, both the multi-decadal warming trend and the interannual variability of the Indian Ocean SSTs had positive impacts on the extreme floods. Our results imply that the strong multi-decadal warming trend in the Indian Ocean needs to be taken into consideration for the prediction/projection of summer extreme floods over the MLYRV in the future. 相似文献
10.
Accurate prediction of the summer precipitation over the middle and lower reaches of the Yangtze River (MLYR) is of urgent demand for the local economic and societal development. This study assesses the seasonal forecast skill in predicting summer precipitation over the MLYR region based on the global Climate Forecast System of Nanjing University of Information Science and Technology (NUIST-CFS1.0, previously SINTEX-F). The results show that the model can provide moderate skill in predicting the interannual variations of the MLYR rainbands, initialized from 1 March. In addition, the nine-member ensemble mean can realistically reproduce the links between the MLYR precipitation and tropical sea surface temperature (SST) anomalies, but the individual members show great discrepancies, indicating large uncertainty in the forecasts. Furthermore, the NUIST-CFS1.0 can predict five of the seven extreme summer precipitation anomalies over the MLYR during 1982–2020, albeit with underestimated magnitudes. The Weather Forecast and Research (WRF) downscaling hindcast experiments with a finer resolution of 30 km, which are forced by the large-scale information of the NUIST-CFS1.0 predictions with a spectral nudging method, display improved predictions of the extreme summer precipitation anomalies to some extent. However, the performance of the downscaling predictions is highly dependent on the global model forecast skill, suggesting that further improvements on both the global and regional climate models are needed. 相似文献