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51.
高云峰  徐友宁  张江华 《地质通报》2018,37(12):2241-2250
为了探索矿业活动对河流水质产生的影响,以秦岭某大型钼矿区下游的东川河流域为研究对象,通过现场采样与室内测试的方法,分析了地表水、沉积物、岩矿样品中重金属Cd的含量特征。采用污染超标倍数法、地累积指数法及Hakanson潜在生态风险评价法分别对东川河流域的河水和底泥样品进行了污染现状评价和生态风险程度评价,最后讨论了Cd的来源。结果表明:东川河主沟16个河水采样点位中,有11个点位的Cd含量明显高于未受矿业活动影响的对照区各点位Cd含量值,Cd含量变异系数达到95.65%,并且从上游到下游各点位Cd含量呈偏态分布,说明东川河流域Cd受矿业活动影响显著。东川河主沟16个河水采样点中有15个Cd含量满足地表水Ⅱ类水标准,比重为93.75%,可以判断东川河整体水质较好。仅5号点位超Ⅱ类水质标准,污染超标倍数为1,为轻度污染。地累积指数分析结果表明,东川河主沟11个底泥样品均存在不同程度的污染:污染最严重的10号点位达到中度-强污染级别;污染最轻的8、9、13号点位为无污染-中度污染;大多数点位为中度污染。东川河主沟11件底泥样品重金属Cd的潜在生态危害指数平均值为120.27,表明东川河主沟底泥总体达到强生态风险程度。酸性矿山废水、原生地质背景、底泥释放、大气干湿降尘等是造成东川河流域Cd重金属污染的主要污染源。  相似文献   
52.
During June and July of 2020, the Yangtze River basin suffered from extreme mei-yu rainfall and catastrophic flooding. This study explores the seasonal predictability and associated dynamical causes for this extreme Yangtze River rainfall event, based on forecasts from the Met Office GloSea5 operational forecast system. The forecasts successfully predicted above-average rainfall over the Yangtze River basin, which arose from the successful reproduction of the anomalous western North Pacific subtropical high (WNPSH). Our results indicate that both the Indian Ocean warm sea surface temperature (SST) and local WNP SST gradient were responsible for the westward extension of the WNPSH, and the forecasts captured these tropical signals well. We explore extratropical drivers but find a large model spread among the forecast members regarding the meridional displacements of the East Asian mid-latitude westerly jet (EAJ). The forecast members with an evident southward displacement of the EAJ favored more extreme Yangtze River rainfall. However, the forecast Yangtze River rainfall anomaly was weaker compared to that was observed and no member showed such strong rainfall. In observations, the EAJ displayed an evident acceleration in summer 2020, which could lead to a significant wind convergence in the lower troposphere around the Yangtze River basin, and favor more mei-yu rainfall. The model forecast failed to satisfactorily reproduce these processes. This difference implies that the observed enhancement of the EAJ intensity gave a large boost to the Yangtze River rainfall, hindering a better forecast of the intensity of the event and disaster mitigation.  相似文献   
53.
In this study, the Weather Research and Forecasting (WRF) model and meteorological observation data were used to research the long-distance moisture transport supply source of the extreme rainfall event that occurred on July 21, 2012 in Beijing. Recording a maximum rainfall amount of 460 mm in 24 h, this rainstorm event had two dominant moisture transport channels. In the early stage of the rainstorm, the first channel comprised southwesterly monsoonal moisture from the Bay of Bengal (BOB) that was directly transported to north China along the eastern edge of Tibetan Plateau (TP) by orographic uplift. During the rainstorm, the southwesterly moisture transport was weakened by the transfer of Typhoon Vicente. Moreover, the southeasterly moisture transport between the typhoon and western Pacific subtropical high (WPSH) became another dominant moisture transport channel. The moisture in the lower troposphere was mainly associated with the southeasterly moisture transport from the South China Sea and the East China Sea, and the moisture in the middle troposphere was mainly transported from the BOB and Indian Ocean. The control experiment well reproduced the distribution and intensity of rainfall and moisture transport. By comparing the control and three sensitivity experiments, we found that the moisture transported from Typhoon Vicente and a tropical cyclone in the BOB both significantly affected this extreme rainfall event. After Typhoon Vicente was removed in a sensitivity experiment, the maximum 24-h accumulated rainfall in north China was reduced by approximately 50% compared with that of the control experiment, while the rainfall after removing the tropical cyclone was reduced by 30%. When both the typhoon and tropical cyclone were removed, the southwesterly moisture transport was enhanced. Moreover, the sensitivity experiment of removing Typhoon Vicente also weakened the tropical cyclone in the BOB. Thus, the moisture pump driven by Typhoon Vicente played an important role in maintaining and strengthening the tropical cyclone in the BOB through its westerly airflow. Typhoon Vicente was not only the moisture transfer source for the southwesterly monsoonal moisture but also affected the tropical cyclone in the BOB, which was a key supply source of long-distance moisture transport for the extreme rainfall event on July 21, 2012 in Beijing.  相似文献   
54.
This study explores the potential for directly assimilating polarimetric radar data (including reflectivity Z and differential reflectivity ZDR) using an ensemble Kalman filter (EnKF) based on the Weather Research and Forecasting (WRF) model to improve analysis and forecast of Tropical Storm Ewiniar (2018). Ewiniar weakened but brought about heavy rainfall over Guangdong, China after its final landfall. Two experiments are performed, one assimilating only Z and the other assimilating both Z and ZDR. Assimilation of ZDR together with Z effectively modifies hydrometeor fields, and improves the intensity, shape and position of rainbands. Forecast of 24-hour extraordinary rainfall ≥250 mm is significantly improved. Improvement can also be seen in the wind fields because of cross-variable covariance. The current study shows the possibility of applying polarimetric radar data to improve forecasting of tropical cyclones, which deserves more researches in the future.  相似文献   
55.
In the present study, the performances of the NWP models on two heavy rainfalls on 20 July and 22 August 2021 over Henan Province were investigated. The impacts of the water vapor transport to the extreme rainfall were further discussed. The results showed that the regional model system in the Guangzhou Meteorological Service generally showed high scores on the extreme rainfall over Henan. The maximum 24h accumulative rainfall by the 24h forecasts by the CMA-GD reached 556 mm over Henan Province. The 24-h and 48-h Threat Score (TS) of heavy rainfall reached 0.56 and 0.64. The comparisons of the Fraction Skill Score (FSS) verifications of the heavy rainfall by CMA-GD and CMA-TRAMS at the radium of 40km reached 0.96 and 0.87. The water vapor transport to the extreme rainfall showed that the vertically integrated water vapor transport (IVT) of the whole layer before the occurrence of the heavy rainfall exhibited a double-eyes distribution in case 7 · 20. The north eye over Henan reached the same magnitude of IVT as the typhoon eye (Cempaka) over south China. The IVT over the lower troposphere (<500 hPa) showed an overwhelming magnitude than the upper level, especially in the planetary boundary layer (<700 hPa). More practical technical needs to be developed to improve its performances on the forecasting of extreme rainfall, as well as more experiments need to be conducted to examine the effects of the specific terrain and physical schemes on the extreme rainfall.  相似文献   
56.
选取了甘肃平凉地区2015-2019年6-8月发生的27次短时强降水事件。利用自动站逐小时降水资料和高空探测资料,按照短时强降水阈值分类统计法和常规天气分析方法对甘肃平凉地区夏季短时强降水时空分布、影响天气系统及大气环境背景进行了统计分析。结果表明:6月短时强降水频次少,强降水高发区为六盘山山区;7月频次明显增多,活跃地区为静宁、崇信、泾川一带;8月频次及强度达到峰值,密集区为平凉北部的崆峒山区、崇信南部河谷地带。6月短时强降水日变化呈现单峰型特征,以午后居多,1 h降水量在20-30 mm段发生频次最高,占6月频次的80%以上;7月和8月日变化呈多峰型结构,夜间短时强降水频次增多,1 h降水量大于30 mm的频次显著增加,约占7月和8月总频次的40%。分析总结了平凉地区短时强降水天气类型,即高空低槽类、副热带高压类、西北气流类。另外,对表征动力、水汽、不稳定条件的环境参数统计分析,结果显示K指数、CAPET850-T500Q850θse-850等物理量平均特征值对平凉地区强降水预报有较好的指示意义。  相似文献   
57.
陈涛  董林  罗玲  杨舒楠 《气象》2021,47(12):1433-1443
2019年9号台风利奇马在浙江造成极端降水,其中8月9日白天浙江东部受台风外围螺旋雨带长时间影响,9日夜间在台风内核对流影响下降水有显著增强;降水中心与浙江临海地区的天台山、括苍山和雁荡山等地形特征密切相关。GPM(Global Precipitation Measure)卫星遥感反演表明近岸台风螺旋雨带以层积混合型降水为主,台风眼墙区域以热带暖云对流型降水为主;眼墙区雨滴有效直径更大、雨滴数密度更高,有利于形成高降水强度。台风登陆前移动速度较慢,浙江沿海地区维持低层锋生和辐合,有利于外围螺旋雨带降水维持和增强;登陆前后受环境垂直切变等因素影响,台风中心左前侧眼墙区域对流活跃,在登陆点附近强降水区偏向于台风中心左侧。分钟级降水观测表明台风登陆期间浙江近海山区降水强度2~3倍于平原地区,其中地形性降水增幅效应与台风对流非对称结构差异对降水影响程度基本相当,有利于在台风中心左前侧的括苍山—雁荡山山区形成强降水中心。  相似文献   
58.
基于2012—2019年兰州地区146个区域自动气象站小时降水数据,从不同时间尺度分析兰州地区近8 a降水精细化特征。结论如下:(1)2012—2019年,兰州地区年均降水量总体呈"北少南多、外多内少"的空间分布特征;年降水量具有明显的年际变化,2018年降水异常偏多46%,而2015、2017年降水异常偏少,尤其2015年偏少30%。(2)兰州地区降水主要集中在7—8月,受环流形势影响,7—8月南部降水明显多于北部,其余月份南北降水差异不明显。(3)兰州地区降水量和降水范围分别表现为"朝少夕多"、"夜大日小"的日变化特征;受海拔高度影响,城区降水量总体比山区小,且因热岛效应,城区降水主要集中在午后至傍晚前后,多为对流性降水,而山区降水日分布较为均匀,整体日波动较小。(4)安宁区短时强降水发生频次最高,但短时强降水频发的站点出现在皋兰县六合站和永登县徐家磨村站,永登县是兰州地区短时强降水预报需重点关注的地区。  相似文献   
59.
基于2012—2019年兰州地区146个区域自动气象站小时降水数据,从不同时间尺度分析兰州地区近8 a降水精细化特征。结论如下:(1)2012—2019年,兰州地区年均降水量总体呈"北少南多、外多内少"的空间分布特征;年降水量具有明显的年际变化,2018年降水异常偏多46%,而2015、2017年降水异常偏少,尤其2015年偏少30%。(2)兰州地区降水主要集中在7—8月,受环流形势影响,7—8月南部降水明显多于北部,其余月份南北降水差异不明显。(3)兰州地区降水量和降水范围分别表现为"朝少夕多"、"夜大日小"的日变化特征;受海拔高度影响,城区降水量总体比山区小,且因热岛效应,城区降水主要集中在午后至傍晚前后,多为对流性降水,而山区降水日分布较为均匀,整体日波动较小。(4)安宁区短时强降水发生频次最高,但短时强降水频发的站点出现在皋兰县六合站和永登县徐家磨村站,永登县是兰州地区短时强降水预报需重点关注的地区。  相似文献   
60.
In recent work, three physical factors of the Dynamical-Statistical-Analog Ensemble Forecast Model for Landfalling Typhoon Precipitation (DSAEF_LTP model) have been introduced, namely, tropical cyclone (TC) track, TC landfall season, and TC intensity. In the present study, we set out to test the forecasting performance of the improved model with new similarity regions and ensemble forecast schemes added. Four experiments associated with the prediction of accumulated precipitation were conducted based on 47 landfalling TCs that occurred over South China during 2004-2018. The first experiment was designed as the DSAEF_LTP model with TC track, TC landfall season, and intensity (DSAEF_LTP-1). The other three experiments were based on the first experiment, but with new ensemble forecast schemes added (DSAEF_LTP-2), new similarity regions added (DSAEF_LTP-3), and both added (DSAEF_LTP- 4), respectively. Results showed that, after new similarity regions added into the model (DSAEF_LTP-3), the forecasting performance of the DSAEF_LTP model for heavy rainfall (accumulated precipitation ≥250 mm and ≥100 mm) improved, and the sum of the threat score (TS250 + TS100) increased by 4.44%. Although the forecasting performance of DSAEF_LTP-2 was the same as that of DSAEF_LTP-1, the forecasting performance was significantly improved and better than that of DSAEF_LTP-3 when the new ensemble schemes and similarity regions were added simultaneously (DSAEF_LTP-4), with the TS increasing by 25.36%. Moreover, the forecasting performance of the four experiments was compared with four operational numerical weather prediction models, and the comparison indicated that the DSAEF_LTP model showed advantages in predicting heavy rainfall. Finally, some issues associated with the experimental results and future improvements of the DSAEF_LTP model were discussed.  相似文献   
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