WRF模式三维变分中背景误差协方差估计

利用WRF模式2008年5-10月逐日预报结果,通过NMC方法进行背景误差协方差(B)估计.给出其结构特征,进行单点数值试验,并利用不同B进行1个月的数值模拟试验,检验模拟降水效果.结果表明:通过单点数值试验验证估算的B结构合理.不同的B,资料同化过程差别较大,应用重新统计的B,同化效率更高,目标函数收敛更稳定.模式模...     

Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004)

We assessed current status of multi-model ensemble (MME) deterministic and probabilistic seasonal prediction based on 25-year (1980–2004) retrospective forecasts performed by 14 climate model systems (7 one-tier and 7 two-tier systems) that participate in the Climate Prediction and its Application to Society (CliPAS) project sponsored by the Asian-Pacific Economic Cooperation Climate Center (APCC). We also evaluated seven DEMETER models’ MME for the period of 1981–2001 for comparison. Based on the assessment, future direction for improvement of seasonal prediction is discussed. We found that two measures of probabilistic forecast skill, the Brier Skill Score (BSS) and Area under the Relative Operating Characteristic curve (AROC), display similar spatial patterns as those represented by temporal correlation coefficient (TCC) score of deterministic MME forecast. A TCC score of 0.6 corresponds approximately to a BSS of 0.1 and an AROC of 0.7 and beyond these critical threshold values, they are almost linearly correlated. The MME method is demonstrated to be a valuable approach for reducing errors and quantifying forecast uncertainty due to model formulation. The MME prediction skill is substantially better than the averaged skill of all individual models. For instance, the TCC score of CliPAS one-tier MME forecast of Niño 3.4 index at a 6-month lead initiated from 1 May is 0.77, which is significantly higher than the corresponding averaged skill of seven individual coupled models (0.63). The MME made by using 14 coupled models from both DEMETER and CliPAS shows an even higher TCC score of 0.87. Effectiveness of MME depends on the averaged skill of individual models and their mutual independency. For probabilistic forecast the CliPAS MME gains considerable skill from increased forecast reliability as the number of model being used increases; the forecast resolution also increases for 2 m temperature but slightly decreases for precipitation. Equatorial Sea Surface Temperature (SST) anomalies are primary sources of atmospheric climate variability worldwide. The MME 1-month lead hindcast can predict, with high fidelity, the spatial–temporal structures of the first two leading empirical orthogonal modes of the equatorial SST anomalies for both boreal summer (JJA) and winter (DJF), which account for about 80–90% of the total variance. The major bias is a westward shift of SST anomaly between the dateline and 120°E, which may potentially degrade global teleconnection associated with it. The TCC score for SST predictions over the equatorial eastern Indian Ocean reaches about 0.68 with a 6-month lead forecast. However, the TCC score for Indian Ocean Dipole (IOD) index drops below 0.40 at a 3-month lead for both the May and November initial conditions due to the prediction barriers across July, and January, respectively. The MME prediction skills are well correlated with the amplitude of Niño 3.4 SST variation. The forecasts for 2 m air temperature are better in El Niño years than in La Niña years. The precipitation and circulation are predicted better in ENSO-decaying JJA than in ENSO-developing JJA. There is virtually no skill in ENSO-neutral years. Continuing improvement of the one-tier climate model’s slow coupled dynamics in reproducing realistic amplitude, spatial patterns, and temporal evolution of ENSO cycle is a key for long-lead seasonal forecast. Forecast of monsoon precipitation remains a major challenge. The seasonal rainfall predictions over land and during local summer have little skill, especially over tropical Africa. The differences in forecast skills over land areas between the CliPAS and DEMETER MMEs indicate potentials for further improvement of prediction over land. There is an urgent need to assess impacts of land surface initialization on the skill of seasonal and monthly forecast using a multi-model framework.     

南支气流对高原低涡移出高原影响的数值试验

本文在对2000年以来移出青藏高原后活动时间长的高原低涡活动过程,进行对流层中层南支气流对高原低涡移出高原的影响的观测事实分析基础上,通过对2001年6月1～5日索县低涡移出高原活动的数值模拟和试验分析,得出了在高原低涡以南的南支气流减弱或者是没有南风或者是没有南风脉动的影响,会使低涡移出高原的速度减慢,移出高原12小时后减弱消失。低涡以南的南支气流起到了向低涡区输送水汽通量、正涡度平流的作用,提供利于低涡活动持续的条件。从而丰富了高原低涡东移的认识,为高原低涡洪涝暴雨的预报提供了科学依据。     

石家庄市采暖期气象服务系统

在采暖期内为了做到既能让人们感到冷暖适宜，又能合理地减少采暖期内的采暖能源浪费，该文对石家庄市采暖期气象条件进行了详细分析，建立了与气象预报相结合的采暖气象服务系统，实际应用效果良好。     

中—β尺度强对流风暴和暴雨数值模拟中的一些问题

本文利用数值模拟方法探讨各环境背景因子对强对流及暴雨系统发生发展所起的作用，分析了暴雨和强对流风暴的形成机制。结果表明：温度场和湿度场的垂直分布，决定着对流是否可以形成；其水平非均匀性只是改变风暴发展强度、生命期以及分裂特性。风场的动力影响对强风暴的移动、分裂及强度特征也十分重要。最后，对第三运动方程做了量纲分析，发现热浮力是对流风暴发展的决定性因素；而热浮力冲量能更细致地反映对流风暴的发展演变特征。     

乾安地区盐碱地显热通量的测量

文中给出了用大孔径闪烁仪在 2 0 0 0年生长季观测到的盐碱地区显热通量的主要结果 ,并初步计算了当地的水热平衡状况。结果表明 :乾安盐碱地区显热通量占净辐射量的百分比在干旱、非生长季达到 6 5 % ,在多雨、植被生长季仅为 11% ;显热通量因降水而明显降低 ,幅度与降水强度有关 ,反映了当地的气候和土壤特征。文中还把LAS的测量结果与传统的梯度法作了比较 ,结果基本一致。     

Evaluation of global climate model on performances of precipitation simulation and prediction in the Huaihe River basin

Using climate models with high performance to predict the future climate changes can increase the reliability of results. In this paper, six kinds of global climate models that selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) under Representative Concentration Path (RCP) 4.5 scenarios were compared to the measured data during baseline period (1960–2000) and evaluate the simulation performance on precipitation. Since the results of single climate models are often biased and highly uncertain, we examine the back propagation (BP) neural network and arithmetic mean method in assembling the precipitation of multi models. The delta method was used to calibrate the result of single model and multimodel ensembles by arithmetic mean method (MME-AM) during the validation period (2001–2010) and the predicting period (2011–2100). We then use the single models and multimodel ensembles to predict the future precipitation process and spatial distribution. The result shows that BNU-ESM model has the highest simulation effect among all the single models. The multimodel assembled by BP neural network (MME-BP) has a good simulation performance on the annual average precipitation process and the deterministic coefficient during the validation period is 0.814. The simulation capability on spatial distribution of precipitation is: calibrated MME-AM > MME-BP > calibrated BNU-ESM. The future precipitation predicted by all models tends to increase as the time period increases. The order of average increase amplitude of each season is: winter > spring > summer > autumn. These findings can provide useful information for decision makers to make climate-related disaster mitigation plans.     

Biological marker compounds as indicators of the depositions! history of the Maoming oil shale

The Eocene Maoming oil shale from Guangdong Province occurs as a laterally uniform stratigraphic section, typically 20–25 m thick, from which the aliphatic hydrocarbon constituents of six representative samples were investigated using GC and C-GC-MS. The sediments evaluated included the basal lignite, a vitrinite lens from the overlying claystone, and four intervals from the massive oil shale bed. As expected, the lignite and vitrinite differ markedly from the oil shales. The lignite is dominated by bacterial hopanoids and components of higher plant origin, including C₂₉ steroids and triterpenoids such as oleanenes. Visually, the oil shale samples show corroded and degraded phytoclasts, spores, wispy particles of fluorescent organic material attributable to dinoflagellates and, especially in the uppermost sample, colonial algal bodies. The distributions of biological markers in the oil shales show many features in common, notably a dominance of dinoflagellate-derived 4-methylsteroids, and a significant proportion of higher-plant derived n-alkanes with marked odd-over-even carbon number predominance. Overall, they exhibit several features that resemble characteristics of the Messel shale. The hydrocarbons of the lowest shale horizon suggest that there may have been a gradual transition between deposition of the original peat and the subsequent oil shales. The aliphatic hydrocarbons of the uppermost shale are dominated by a number of C₃₁ and C₃₃ botryococcane homologues and other unusual branched alkanes possibly derived from green algae. All of the samples are immature. Overall, molecular and microscopic examination of the stratigraphic succession of the Maoming oil shale suggests a shallow, lacustrine environment within which peats were deposited. This lake subsequently deepened to support abundant algal populations, especially dinoflagellates, culminating in a dominance of botryococcoid algae.     

造山带中增生楔识别与地质意义

增生楔主要由海沟复理石、远洋—半远洋沉积和洋岛/海山等大洋板块地层岩石及蛇绿岩共同构成,是汇聚板块边缘古俯冲带构造—沉积作用的综合产物,以发育叠瓦状逆冲断层、双冲断层和紧闭—倒转褶皱,以及片理、碎裂构造、小型褶皱、膝折等不同尺度的构造为特征。增生楔组成包括连续单元和混杂岩两部分,严格受滑脱面位置控制。增生楔是增生型造山带最基本大地构造相,它与弧前盆地、岛弧/大陆边缘弧的时空配置关系可直接指示大洋板块俯冲极性、揭示洋盆演化与造山作用方式。准确识别增生楔,详细解剖其结构特征与组成特征,综合判别并恢复大洋板块地层,可为古板块边界与古大洋盆地消亡位置确定、造山带结构精细划分及造山作用过程重建提供基本依据。大比例尺地质填图是研究增生楔结构和组成、以及大洋板块地层重建的有效手段。以南祁连拉脊山石灰窑增生楔为例,地质填图结果表明它是由中寒武世—早奥陶世洋壳物质构成,自北而南依次可分为海沟—大洋盆地—海山OPS和六道沟SSZ型蛇绿岩,被南倾逆冲断层分割成多个岩片。海沟—大洋盆地OPS岩片基本保留完整地层序列,海山OPS岩片包括连续单元和混杂岩两部分。顶帽山增生楔主要由海山OPS构成,内部结构层序相对完好,是南祁连构造带中保留最为完整、规模最大的海山OPS岩石组合序列。上述不同类型OPS片段和六道沟SSZ型蛇绿岩组成的增生楔与其南侧岛弧带同时代。增生楔—岩浆弧的时空配置暗示寒武纪—早奥陶世时期原特提斯洋自北向南俯冲极性。这些认识为南祁连早古生代火山—岩浆—沉积构造演化以及是否存在古洋盆与古洋盆演化重建提供基本佐证。     

Study on Monitoring Technology of Surrounding Rock in Deep Layered Roadway Based on Constant Resistance and Large Deformation Bolt

Geotechnical and Geological Engineering - The stability monitoring of surrounding rock in layered roadway is an important method to ensure the safety of deep mining coal mine. In view of the actual...