Projecting Spring Consecutive Rainfall Events in the Three Gorges Reservoir Based on Triple-Nested Dynamical Downscaling

Spring consecutive rainfall events(CREs) are key triggers of geological hazards in the Three Gorges Reservoir area(TGR), China. However, previous projections of CREs based on the direct outputs of global climate models(GCMs) are subject to considerable uncertainties, largely caused by their coarse resolution. This study applies a triple-nested WRF(Weather Research and Forecasting) model dynamical downscaling, driven by a GCM, MIROC6(Model for Interdisciplinary Research on Climate, version 6), to improve the historical simulation and reduce the uncertainties in the future projection of CREs in the TGR. Results indicate that WRF has better performances in reproducing the observed rainfall in terms of the daily probability distribution, monthly evolution and duration of rainfall events, demonstrating the ability of WRF in simulating CREs. Thus, the triple-nested WRF is applied to project the future changes of CREs under the middle-of-the-road and fossil-fueled development scenarios. It is indicated that light and moderate rainfall and the duration of continuous rainfall spells will decrease in the TGR, leading to a decrease in the frequency of CREs. Meanwhile, the duration, rainfall amount, and intensity of CREs is projected to regional increase in the central-west TGR. These results are inconsistent with the raw projection of MIROC6. Observational diagnosis implies that CREs are mainly contributed by the vertical moisture advection. Such a synoptic contribution is captured well by WRF, which is not the case in MIROC6,indicating larger uncertainties in the CREs projected by MIROC6.

Assessing the Performance of a Dynamical Downscaling Simulation Driven by a Bias-Corrected CMIP6 Dataset for Asian Climate

In this study,we aim to assess dynamical downscaling simulations by utilizing a novel bias-corrected global climate model(GCM)data to drive a regional climate model(RCM)over the Asia-western North Pacific region.Three simulations were conducted with a 25-km grid spacing for the period 1980–2014.The first simulation(WRF_ERA5)was driven by the European Centre for Medium-Range Weather Forecasts Reanalysis 5(ERA5)dataset and served as the validation dataset.The original GCM dataset(MPI-ESM1-2-HR model)was used to drive the second simulation(WRF_GCM),while the third simulation(WRF_GCMbc)was driven by the bias-corrected GCM dataset.The bias-corrected GCM data has an ERA5-based mean and interannual variance and long-term trends derived from the ensemble mean of 18 CMIP6 models.Results demonstrate that the WRF_GCMbc significantly reduced the root-mean-square errors(RMSEs)of the climatological mean of downscaled variables,including temperature,precipitation,snow,wind,relative humidity,and planetary boundary layer height by 50%–90%compared to the WRF_GCM.Similarly,the RMSEs of interannual-tointerdecadal variances of downscaled variables were reduced by 30%–60%.Furthermore,the WRF_GCMbc better captured the annual cycle of the monsoon circulation and intraseasonal and day-to-day variabilities.The leading empirical orthogonal function(EOF)shows a monopole precipitation mode in the WRF_GCM.In contrast,the WRF_GCMbc successfully reproduced the observed tri-pole mode of summer precipitation over eastern China.This improvement could be attributed to a better-simulated location of the western North Pacific subtropical high in the WRF_GCMbc after GCM bias correction.

Downscaling Seasonal Precipitation Forecasts over East Africa with Deep Convolutional Neural Networks

This study assesses the suitability of convolutional neural networks(CNNs) for downscaling precipitation over East Africa in the context of seasonal forecasting. To achieve this, we design a set of experiments that compare different CNN configurations and deployed the best-performing architecture to downscale one-month lead seasonal forecasts of June–July–August–September(JJAS) precipitation from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0(NUIST-CFS1.0) for 1982–2020. We also perform hyper-parameter optimization and introduce predictors over a larger area to include information about the main large-scale circulations that drive precipitation over the East Africa region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results show that the CNN-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme precipitation spatial patterns. Besides, CNN-based downscaling yields a much more accurate forecast of extreme and spell indicators and reduces the significant relative biases exhibited by the raw model predictions. Moreover, our results show that CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of East Africa. The results demonstrate the potential usefulness of CNN in downscaling seasonal precipitation predictions over East Africa,particularly in providing improved forecast products which are essential for end users.

地震宽角反射/折射方法发展述评

本文从地震宽角反射/折射方法的仪器装备、观测系统、观测实验、震相识别、数据分析等主要技术环节的出现、改进、发展、完善,回顾了该方法的百年发展历史.按照我们的见解,将其发展过程分为萌芽期、诞生期、成长期和发展期.对于早期的追溯,重点放在方法的孕育和诞生起到关键作用的人物和事件上,并且尽可能详细;对后期的回顾,聚焦在方法的技术内容的萌发、出现、改进、应用和重点文献等方面,如,何时出现了剖面方法、相遇和追逐观测、地震宽角反射/折射剖面数据的完备性等,成果表述不作为重点,而且叙述简略.述及了天然地震学、地震折射勘探、地震反射勘探、电子技术、通讯技术、测量技术、计算机技术、计算数学等相关学科的进步,对地震宽角反射/折射方法发展的促进作用.展望未来,宽角反射/折射方法在我国深部探测与矿产资源勘查领域大有可为.以此文致敬追寻科学真理的地学前辈.

Seasonal Prediction of Indian Summer Monsoon Using WRF: A Dynamical Downscaling Perspective

Seasonal forecasting of the Indian summer monsoon by dynamically downscaling the CFSv2 output using a high resolution WRF model over the hindcast period of 1982-2008 has been performed in this study. The April start ensemble mean of the CFSv2 has been used to provide the initial and lateral boundary conditions for driving the WRF. The WRF model is integrated from 1st May through 1st October for each monsoon season. The analysis suggests that the WRF exhibits potential skill in improving the rainfall skill as well as the seasonal pattern and minimizes the meteorological errors as compared to the parent CFSv2 model. The rainfall pattern is simulated quite closer to the observation (IMD) in the WRF model over CFSv2 especially over the significant rainfall regions of India such as the Western Ghats and the central India. Probability distributions of the rainfall show that the rainfall is improved with the WRF. However, the WRF simulates copious amounts of rainfall over the eastern coast of India. Surface and upper air meteorological parameters show that the WRF model improves the simulation of the lower level and upper-level winds, MSLP, CAPE and PBL height. The specific humidity profiles show substantial improvement along the vertical column of the atmosphere which can be directly related to the net precipitable water. The CFSv2 underestimates the specific humidity along the vertical which is corrected by the WRF model. Over the Bay of Bengal, the WRF model overestimates the CAPE and specific humidity which may be attributed to the copious amount of rainfall along the eastern coast of India. Residual heating profiles also show that the WRF improves the thermodynamics of the atmosphere over 700 hPa and 400 hPa levels which helps in improving the rainfall simulation. Improvement in the land surface fluxes is also witnessed in the WRF model.

装配式建筑梁柱节点疲劳损伤检测方法研究

常规的装配式建筑梁柱节点疲劳损伤检测主要采用梁柱图像分析实现,忽略了节点内部损伤的影响,导致检测结果相对变化量系数与实际系数的差值较大。本文对装配式建筑梁柱节点疲劳损伤检测方法进行了研究,于装配式建筑梁柱周围布置测点对梁柱节点的应变状态进行分析;根据分析结果,结合梁柱内部能量耗散值,计算节点疲劳损伤能量系数;将该系数作为节点应变能密度因子分析节点轴向力,由此得出检测的梁柱节点疲劳损伤值。实验结果表明,所提方法应用后梁柱节点疲劳损伤检测结果表现出的相对变化量系数差值较小,检测结果准确率较高,满足了装配式建筑梁柱安全运维工作的现实需求。

A generative adversarial network-based unified model integrating bias correction and downscaling for global SST

本文提出了一种基于生成对抗网络的全球海表面温度(sea surface temperature,SST)偏差订正及降尺度整合模型.该模型的生成器使用偏差订正模块将数值模式预测结果进行校正,再用可复用的共享降尺度模块将订正后的数据分辨率逐次提高.该模型的判别器可鉴别偏差订正及降尺度结果的质量,以此为标准进行对抗训练。同时,在对抗损失函数中含有物理引导的动力学惩罚项以提高模型的性能.本研究基于分辨率为1°的GFDL SPEAR模式的SST预测结果,选择遥感系统(Remote Sensing System)的观测资料作为真值,面向月尺度ENSO与IOD事件以及天尺度海洋热浪事件开展了验证试验:模型在将分辨率提高到0.0625°×0.0625°的同时将预测误差减少约90.3%,突破了观测数据分辨率的限制,且与观测结果的结构相似性高达96.46%.

实证研究在临床实践指南制订中的思考及方法学建议

临床实践指南制订的方法学理论在真实的制订情境下存在诸多问题,缺乏对于实际情况的考量,致使其对于指南制订的指导性下降。本文深入剖析了指南制订中理论与实践相关的多方面难点,包括指南制订时方法学理论与实践存在偏差、缺乏大样本的指南方法学相关的实证研究、方法学理论在实证运用后对于局限性和未来研究建议的报告内容不足且形式不规范的问题。为提高未来指南制订方法学的指导性,本课题组提出了多项方法学建议,包括倡导开展对方法学理论进行验证的实证研究、促进大样本实证研究和对比研究开展、规范实证研究后对局限性和未来研究建议的报告内容和形式,以期为指南制订方法学研究者及指南制订小组提供参考。

虚拟震源地震探测方法及其应用

SsPmp震相是远震直达S波在地表激发的下行P波在Moho面反射的震相,具有信号能量大、信噪比高、不易受近地表沉积层和地壳小尺度结构扰动的影响等优势.虚拟地震测深方法(VDSS)是近年来发展的利用SsPmp震相与直达Ss波震相的到时差来研究地壳厚度(或Moho面深度)的探测方法.本文介绍了VDSS方法的原理、优势及其在实际应用中的表现.研究表明,VDSS方法在提高探测精度、降低成本、环境影响等方面具有显著优势,且成功应用于克拉通、造山带和沉积盆地、峨眉山大火成岩省等不同地质环境中,在探测地壳结构中展现出巨大潜力和应用价值.但是VDSS方法的准确度高度依赖于地震数据的质量,尤其是远震S波的清晰度和震中距的范围,使得该方法在复杂地质结构区域的应用受到较大限制.未来,VDSS与传统接收函数方法、地震层析成像、重力测量等多类地球物理方法的结合,有望为地壳结构探测提供更全面的约束.

Downscaling法在贵州冬季气温和降水预测中的应用

基于CGCM模式输出500 hPa位势高度场、NCEP/NCAR再分析500 hPa高度资料、贵州冬季降水和气温历史资料,利用降尺度法,对贵州冬季降水和气温预报的技巧和预测效果进行了预测试验和改进。结果表明,该方法从动力与统计相结合的角度,给出季尺度大气环流与局地降水、气温之间的关系,有明确的动力学背景和天气学意义。20年回算及两年回报试验证明了该关系的合理性;对贵州冬季降水的预测率约70%,而对气温的预测率为65%左右。另外,通过对气温反演方程订正后,其预测率达67%左右;在极端异常年,该方法对降水的预测率变幅不大,而对气温的预测效果影响极大。最后利用该方法对2005年贵州冬季降水和气温趋势进行了展望。

气相色谱法测定猪肉脂肪的脂肪酸方法优化

比较在3种程序升温条件下的37种混合脂肪酸甲酯标准品的谱图,确定最适合分析猪肉脂肪的脂肪酸的程序升温条件;比较索氏提取法、酸水解辅助提取法、有机溶剂浸提法、超声波辅助提取法提取猪肉脂肪,确定最佳猪肉脂肪提取方法;比较碱法甲酯化、酸法甲酯化、碱皂化酸酯化法、碱皂化三氟化硼酯化法对猪肉脂肪的脂肪酸进行甲酯化处理,确定最佳甲酯化方法。结果表明:最适合分析猪肉脂肪的脂肪酸的程序升温条件为在初始温度140℃条件下保持5 min,以5℃/min升温至220℃保持15 min;最佳提取方法是超声波辅助提取法;最佳甲酯化方法是碱法甲酯化。

基于GRACE/GRACE-FO数据降尺度方法反演库尔勒东区地下水储量变化

GRACE与GRACE-FO重力卫星为全球中大尺度地下水反演监测提供了新的手段,但难以提供小尺度上较高空间分辨率的地下水储量变化(GWSA)信息。本文针对新疆库尔勒东部缺资料区,采用动力降尺度方法提高GRACE/GRACE-FO反演GWSA数据的空间分辨率,分析GWSA的时空分布规律。首先,基于数据融合方法构建了库尔勒东区GWSA数值模型;然后,利用优化后的模型将GWSA反演数据的分辨率从1°降尺度至0.25°和0.05°,将反演的GWSA与水井监测的地下水位(GWL)数据进行对比验证;最后,利用0.05°GWSA数据分析研究区GWSA态势。结果表明:①与降尺度前1°GWSA数据相比,降尺度转换后的高分辨率GWSA数据在空间上更加平滑、展示了更加丰富的细节,且提高了与水井GWL监测数据的相关性,改进了反演精度和可靠性;②小尺度上,降尺度后的GWSA数据能够反映水源地地下水的季节性、年际和长期开采下的亏损等动态特征;③研究区GWSA呈现出时空分布差异性,2005—2020年区内地下水储量变化率为-1~1 mm·a-1,总体上呈南增、北减态势,南、北部山区的变幅大于中部相对平坦区域。

成人压力性损伤减压方法研究进展

压力性损伤(pressure injuries,PI)是全球范围内的健康问题,其发生率介于0%~72.5%之间[1]。Li等[2]的研究发现,全球PI发生率为12.8%,其中院内获得性压力性损伤(hospital-acquired pressure injury,HAPI)发生率为8.4%,II期及以上HAPI发生率为5.1%。PI的发生不仅会增加患者致残率、致死率和医疗负担,同时会严重降低患者及照顾者的生活质量[3]。压力是压力性损伤形成的最主要原因,减压不仅可以有效促进PI伤口的愈合.

2023年LIS期刊论文研究方法应用态势

研究方法的选择和运用影响研究的深度和可靠性,对科学研究发展十分重要。文章在总结LIS领域方法论研究的基础上,将LIS领域常用的研究方法整理、汇总、编码,以LIS领域11种TOP期刊2023年收录的论文为数据源,统计分析LIS期刊论文的研究方法应用态势,探讨LIS学科性质、研究对象、作者学科背景等因素对研究方法的影响。研究发现:LIS领域论文使用的研究方法内容不断演进,跨学科和新兴理论方法以及多元研究方法的应用促进了研究的深入和丰富。

关于高纯石英原料矿石地质学评价方法的探讨

高纯石英资源是一种重要的战略性资源。本文结合高纯石英成矿地质特征及其对后期选矿提纯、材料加工等的影响,系统总结了高纯石英原料中杂质的赋存状态、形成机理以及评价方法等,得出:(1)可以作为高纯石英原料的潜在岩石类型有花岗伟晶岩(包括不含暗色矿物的伟晶状花岗岩)、脉石英以及水晶,岩浆演化晚期的伟晶状花岗岩-伟晶岩早期阶段的NYF型花岗伟晶岩结晶形成的石英纯度更高,后期适当的变形变质作用更有利于高纯石英矿床的形成。高纯石英原料矿石中石英矿物呈现无色透明至半透明,矿物构造裂隙少,伟晶岩型矿石矿物组成通常为石英、钠长石、条纹长石、白云母等,黑云母等暗色矿物含量极少,基本不见锂辉石、独居石等稀有金属矿物和电气石、萤石等含挥发分矿物。(2)影响高纯石英的主要地质因素包括脉石矿物及晶界杂质、包裹体、晶格杂质等。其中包裹体类型、数量和尺寸是包裹体评价的关键指标,天然石英矿物中的气液两相包裹体、矿物包裹体和<10μm包裹体应尽量少;Al和Ti是晶格杂质元素评价标志性元素,通常要求天然石英矿物中Al<50×10-6和Ti<10×10-6。(3)建议按照手标本特征-石英矿物特征-石英中包裹体特征-晶格元素赋存状态及含量的顺序,从宏观到微观,综合借助光学显微镜、扫描电子显微镜(SEM)、阴极荧光光谱分析系统(SEM-CL)、激光剥蚀电感耦合等离子质谱仪(LA-ICP-MS)等开展地质学评价和研究工作。

Near Future (2016-40) Summer Precipitation Changes over China as Projected by a Regional Climate Model (RCM) under the RCP8.5 Emissions Scenario: Comparison between RCM Downscaling and the Driving GCM

Multi-decadal high resolution simulations over the CORDEX East Asia domain were performed with the regional climate model RegCM3 nested within the Flexible Global Ocean-Atmosphere-Land System model, Grid-point Version 2 （FGOALS-g2）. Two sets of simulations were conducted at the resolution of 50 km, one for present day （1980-2005） and another for near-future climate （2015-40） under the Representative Concentration Pathways 8.5 （RCP8.5） scenario. Results show that RegCM3 adds value with respect to FGOALS-g2 in simulating the spatial patterns of summer total and extreme precipitation over China for present day climate. The major deficiency is that RegCM3 underestimates both total and extreme precipi- tation over the Yangtze River valley. The potential changes in total and extreme precipitation over China in summer under the RCP8.5 scenario were analyzed. Both RegCM3 and FGOALS-g2 results show that total and extreme precipitation tend to increase over northeastern China and the Tibetan Plateau, but tend to decrease over southeastern China. In both RegCM3 and FGOALS-g2, the change in extreme precipitation is weaker than that for total precipitation. RegCM3 projects much stronger amplitude of total and extreme precipitation changes and provides more regional-scale features than FGOALS-g2. A large uncertainty is found over the Yangtze River valley, where RegCM3 and FGOALS-g2 project opposite signs in terms of precipitation changes. The projected change of vertically integrated water vapor flux convergence generally follows the changes in total and extreme precipitation in both RegCM3 and FGOALS-g2, while the amplitude of change is stronger in RegCM3. Results suggest that the spatial pattern of projected precipitation changes may be more affected by the changes in water vapor flux convergence, rather than moisture content itself.

Statistical Downscaling for Multi-Model Ensemble Prediction of Summer Monsoon Rainfall in the Asia-Pacific Region Using Geopotential Height Field

The 21-yr ensemble predictions of model precipitation and circulation in the East Asian and western North Pacific （Asia-Pacific） summer monsoon region （0°-50°N, 100° 150°E） were evaluated in nine different AGCM, used in the Asia-Pacific Economic Cooperation Climate Center （APCC） multi-model ensemble seasonal prediction system. The analysis indicates that the precipitation anomaly patterns of model ensemble predictions are substantially different from the observed counterparts in this region, but the summer monsoon circulations are reasonably predicted. For example, all models can well produce the interannual variability of the western North Pacific monsoon index （WNPMI） defined by 850 hPa winds, but they failed to predict the relationship between WNPMI and precipitation anomalies. The interannual variability of the 500 hPa geopotential height （GPH） can be well predicted by the models in contrast to precipitation anomalies. On the basis of such model performances and the relationship between the interannual variations of 500 hPa GPH and precipitation anomalies, we developed a statistical scheme used to downscale the summer monsoon precipitation anomaly on the basis of EOF and singular value decomposition （SVD）. In this scheme, the three leading EOF modes of 500 hPa GPH anomaly fields predicted by the models are firstly corrected by the linear regression between the principal components in each model and observation, respectively. Then, the corrected model GPH is chosen as the predictor to downscale the precipitation anomaly field, which is assembled by the forecasted expansion coefficients of model 500 hPa GPH and the three leading SVD modes of observed precipitation anomaly corresponding to the prediction of model 500 hPa GPH during a 19-year training period. The cross-validated forecasts suggest that this downscaling scheme may have a potential to improve the forecast skill of the precipitation anomaly in the South China Sea, western North Pacific and the East Asia Pacific regions, where the anomaly correlation coefficient （ACC） has been improved by 0.14, corresponding to the reduced RMSE of 10.4% in the conventional multi-model ensemble （MME） forecast.

Statistical Downscaling Based on Dynamically Downscaled Predictors: Application to Monthly Precipitation in Sweden

A prerequisite of a successful statistical downscaling is that large-scale predictors simulated by the General Circulation Model (GCM) must be realistic. It is assumed here that features smaller than the GCM resolution are important in determining the realism of the large-scale predictors. It is tested whether a three-step method can improve conventional one-step statistical downscaling. The method uses predictors that are upscaled from a dynamical downscaling instead of predictors taken directly from a GCM simulation. The method is applied to downscaling of monthly precipitation in Sweden. The statistical model used is a multiple regression model that uses indices of large-scale atmospheric circulation and 850-hPa specific humidity as predictors. Data from two GCMs (HadCM2 and ECHAM4) and two RCM experiments of the Rossby Centre model (RCA1) driven by the GCMs are used. It is found that upscaled RCA1 predictors capture the seasonal cycle better than those from the GCMs, and hence increase the reliability of the downscaled precipitation. However, there are only slight improvements in the simulation of the seasonal cycle of downscaled precipitation. Due to the cost of the method and the limited improvements in the downscaling results, the three-step method is not justified to replace the one-step method for downscaling of Swedish precipitation.

如何在旅游管理研究中使用严谨规范的扎根理论和案例研究方法

扎根理论和案例研究方法在当前旅游管理、工商管理研究中应用普遍,但学界对于这两种方法的本质特征、评价标准和关键操作步骤仍然存在诸多争议和不清晰之处。因此,本文围绕如何用好扎根理论和案例研究方法这一话题展开讨论,得出主要结论为:(1)高质量的质性与案例研究方法具有5个主要特征,即研究设计具有高可信度及高可靠性、样本与案例选择与研究问题及研究范式相匹配、数据分析过程严谨及规范、理论构建能找到“最优区分”平衡点、文章写作注重研究方法的独特性。(2)学界需要深入反思扎根理论的内涵体系并规避4种典型误区,要重视处理理论抽样、编码技巧、信效度检验等核心问题。(3)扎根理论数据分析的规范性特别是编码过程在文章中的说明与展示越来越受到重视,但值得注意的是对数据进行“持续比较”与合理解释才是扎根理论数据分析的核心,不能为了编码而编码。(4)案例研究的数据分析与理论构建可以概括为“数据—概念—概念间关系—理论”逻辑链条,首先是从数据到概念,即通过将案例数据进行压缩和抽象,使之与相关概念联系到一起,其次是概念间关系及理论解释,即将这些概念以一定的逻辑联系起来,描述案例现象的模式,解释其背后的机制。(5)案例研究适用于揭示理论机制和构建新理论,选择相匹配的数据处理方法能有效提升案例研究的质量,根据理论类型不同可将案例研究分为过程理论型和因素理论型,且分别适配不同的研究设计和数据处理方法。

Dynamic Downscaling of Summer Precipitation Prediction over China in 1998 Using WRF and CCSM4

To study the prediction of the anomalous precipitation and general circulation for the summer（June–July–August） of1998, the Community Climate System Model Version 4.0（CCSM4.0） integrations were used to drive version 3.2 of the Weather Research and Forecasting（WRF3.2） regional climate model to produce hindcasts at 60 km resolution. The results showed that the WRF model produced improved summer precipitation simulations. The systematic errors in the east of the Tibetan Plateau were removed, while in North China and Northeast China the systematic errors still existed. The improvements in summer precipitation interannual increment prediction also had regional characteristics. There was a marked improvement over the south of the Yangtze River basin and South China, but no obvious improvement over North China and Northeast China. Further analysis showed that the improvement was present not only for the seasonal mean precipitation, but also on a sub-seasonal timescale. The two occurrences of the Mei-yu rainfall agreed better with the observations in the WRF model,but were not resolved in CCSM. These improvements resulted from both the higher resolution and better topography of the WRF model.