Subsurface influence on SST in the tropical Indian Ocean: structure and interannual variability

Interannual variations of subsurface influence on SST in the Indian Ocean show strong seasonality. The subsurface influence on SST confines to the southern Indian Ocean (SIO) in boreal winter and spring; it is observed on both sides of the equator in boreal summer and fall. Interannual long Rossby waves are at the heart of this influence, and contribute significantly to the coupled climate variability in the tropical Indian Ocean (TIO). Principal forcing mechanism for the generation of these interannual waves in the Indian Ocean and the relative influence of two dominant interannual signals in the tropics, namely El Niño and Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD), are also discussed. Two distinct regions dominated by either of the above climate signals are identified. IOD dominates the forcing of the off-equatorial Rossby waves, north of 10°S, and the forcing comes mainly from the anomalous Ekman pumping associated with the IOD. However, after the demise of IOD activity by December, Rossby waves are dominantly forced by ENSO, particularly south of 10°S.It is found that the subsurface feedback in the northern flank of the southern Indian Ocean ridge region (north of 10°S) significantly influences the central east African rainfall in boreal fall. The Indian Ocean coupled process further holds considerable capability of predicting the east African rainfall by one season ahead. Decadal modulation of the subsurface influence is also noticed during the study period. The subsurface influence north of 10°S coherently varies with the IOD, while it varies coherently with the ENSO south of this latitude.     

近百年西北太平洋热带气旋年频数的变化特征

利用经趋势订正的１８８４－１９８８年西北太平洋热带气旋年频数资料，分析了热带气旋年频数的多年变化及其与海面温度、南方涛动指数、太阳黑子数和环流型日数等的统计关系。初步结果表明，热带气旋年频数的变化具有明显的２１年、３１年、１５年和６年左右的周期和持续期平均为１２年左右的阶段变化；近百年来有三次较明显的转折，分别出现在１９３１、１９５９年１９７７年。热带气旋年频数在厄尔尼诺年有冬春季偏少、夏秋季偏多     

WRF中土壤图及参数表的更新对华北夏季预报的影响研究

土壤质地及其物理性质的参数化对陆面过程模拟具有明显的影响。研究了土壤质地和土壤水文参数表的更新对WRF（Weather Research and Forecasting）模拟性能的影响。使用北京师范大学土壤属性数据集和修正后的土壤水文参数表替换WRF默认数据,对2017年6—8月华北地区开展数值模拟试验和评估验证。结果表明,模拟结果对土壤类型数据集和水文参数表的更新较为敏感,对地面要素预报有正效果。WRF默认土壤数据集中,中国东部以粘壤土为主,而在北京师范大学土壤数据集里则以壤土为主;修正后的土壤水文参数在Noah陆面过程中增强了裸土潜热蒸发能力。数值模拟试验表明,土壤输入数据和土壤水文参数的更新能够增强陆面向大气的潜热同时减弱感热输送,致使大气底层温度降低而湿度增大。利用华北区域748个地面气象观测站的2 m温度和2 m湿度对2017年夏季的模拟结果进行验证,结果显示更新试验对地面要素的预报偏差有较好的修正作用,能够将2 m温、湿度的预报技巧分别提高3.4%和2.9%。      

天山乌鲁木齐河源１号冰川消融对气候变化的响应

目前气候变暖导致的冰川退缩,引起了全世界的广泛关注。 以新疆天山乌鲁木齐河源1号冰川为例,根据1958年以来的观测资料,研究了冰川消融对气候变化的响应。结果表明,近50 a来冰川在表面粒雪特征、成冰带、冰川温度、面积、厚度及末端位置等方面发生了显著变化,而这些变化均与气温的升高有着密切的联系;20世纪80年代以来的快速升温,使冰川的退缩出现了加速趋势,冰川融水径流量也呈加速增大趋势。     

季节指数及其在季节性监测资料分析和预报中的应用

基于灰色模型的诸多优点，作者选用GM(1，1)模型分析和预报形变监测序列。然而直接应用GM(1，1)灰色模型分析和预报具有季节性的监测序列时往往精度不高。因此，作者提出运用基于季节指数的“去季节波动”法与GM(1，1)混合建模，对监测资料进行分析与预报。基于均方差和平均绝对误差两个精度准则，作者对此方法与周期函数拟合模型进行了比较。结果表明，此方法提高了具有季节性波动监测序列的预报精度，且建模方法简便、快捷。     

天绘一号卫星三线阵影像RPC模型定位精度验证与分析

天绘一号卫星以RPC参数作为主要的影像辅助数据提供给用户,对传感器的技术参数进行隐藏.文中简要介绍RPC模型的立体定位方法,并针对定位结果中存在的明显的系统误差,采用像方补偿方案进行补偿,最后利用两景天绘一号卫星三线阵影像RPC模型对测区进行实验验证和分析.结果表明,采用少量地面控制点进行系统误差补偿后,定位精度提升效果明显,验证了模型的正确性和有效性.     

基于HJ-1遥感数据的矿区水体污染监测与分析——以龙岩紫金山金铜矿为例

矿产资源的持续开采与加工利用使得矿区周边水资源受到的污染日趋严重,急需采用先进技术对水污染进行监测分析,遥感技术是水环境监测最为有效的技术之一。利用国产环境一号小卫星多光谱遥感影像数据,针对福建省龙岩市紫金山矿区不同时相的数据进行水质遥感监测。利用近红外单波段阈值分割法提取悬浮物浓度信息,基于矿区酸碱性水体光谱曲线特性采用342波段假彩色合成影像,采用SVM分类方法进行分类,判别矿区水体酸碱性以及分析水体受污染程度变化和污染源。结果表明,研究区汀江水体2008年呈现碱性,2010年呈现弱碱性,水质在研究时段内得到一定的改善,但在选矿厂与矿区附近的水体中仍含有大量重金属沉积物。     

典型湖泊天然有机质与四环素的相互作用

采用荧光滴定法研究四环素(tetracycline,TC)与太湖溶解性有机质(dissolved organic matter,DOM)和玄武湖DOM的相互作用.三维荧光光谱结合平行因子分析显示,2个湖泊的DOM含有3个荧光组分:类富里酸组分C1、类色氨酸组分C2和类络氨酸组分C3.其中C2的荧光强度远高于C1和C3,是DOM的主要荧光组成.3个荧光组分与TC发生了不同程度的静态猝灭,特别当TC浓度为45.5μmol/L时,类蛋白组分的荧光强度完全被猝灭(100%),并且猝灭作用改变了DOM分子的微环境极性.同步荧光光谱联合二维相关图谱进一步表明类色氨酸组分优先和TC发生猝灭作用,其次为类络氨酸组分和类富里酸组分.Ryan-Weber方程适于拟合DOM与TC的猝灭过程,2个湖泊的DOM中3个荧光组分的络合常数lg K值范围为5.05~5.85,大小顺序为C2C3C1.因此,类蛋白组分为主的DOM对TC的络合作用大于类腐殖组分为主的DOM,影响抗生素在湖泊水体中的生物有效性和生态毒性.     

合肥塘西河异味物质及异味影响因子研究

以合肥市塘西河为研究对象,2014-2015年逐月对其水体水质和异味物质进行监测,同时结合塘西河浮游植物群落结构调查,综合分析塘西河异味物质变化规律及其影响因素.研究发现,塘西河异味暴发集中发生在夏季,夏季二甲基异莰醇浓度可达4909 ng/L,土腥素浓度可达197 ng/L.浮游植物群落结构调查表明,秋、冬季塘西河优势种类为蓝藻,春、夏季为硅藻、绿藻或隐藻.主成分分析得到5种主成分分别解释了光照、有机质、微生物活动、氮、磷等对水质的影响.相关性分析结果表明,氮是塘西河异味的限制因素,水体中氮浓度较高是异味产生的重要原因.     

The sensitivity of ground surface temperature prediction to soil thermal properties Using the Simple Biosphere Model (SiB2)

Using the Simple Biosphere Model (SiB2), soil thermal properties (STP) were examined in a Tibetan prairie during the monsoon period to investigate ground surface temperature prediction. We improved the SiB2 model by incorporating a revised force-restore method (FRM) to take the vertical heterogeneity of soil thermal diffusivity (k) into account. The results indicate that (1) the revised FRM alleviates daytime overestimation and nighttime underestimation in modeled ground surface temperature (T_g), and (2) its role in little rainfall events is significant because the vertical gradient of k increases with increasing surface evaporation. Since the original formula of thermal conductivity (λ) in the SiB2 greatly underestimates soil thermal conductivity, we compared five algorithms of λ involving soil moisture to investigate the cause of overestimation during the day and underestimation at night on the basis of the revised FRM. The results show that (1) the five algorithms significantly improve T_g prediction, especially in daytime, and (2) taking one of these five algorithms as an example, the simulated T_g values in the daytime are closer to the field measurements than those in the nighttime. The differences between modeled T_g and field measurements are mostly within the margin of error of ±2 K during 3 August to 4 September 1998.