多物理场测井数据联合反演研究进展

联合反演方法在综合地球物理数据分析中应用效果明显,并起着越来越重要的应用,其方法同样也可以应用于多物理场测井数据联合反演.文中阐述了测井联合反演的必要性,综述了测井约束反演和测井数据联合反演的国内外研究现状.根据参与联合反演的数据类型和地层模型的不同,将联合反演进行了分类;研究并举例推导了不同类型测井数据的联合反演方法的原理及具体算法,最后指出了多物理场测井数据联合反演的发展方向.     

俯冲带深海-岩石圈流体交换及其效应

俯冲带是地球上构造活动最复杂、最强烈的区域,也是地球物质循环系统的重要组成部分,对俯冲带的深入研究有助于加深我们对地球系统科学的认识。通过系统地梳理分析国内外相关文献,大洋岩石圈通过在汇聚板块边界的俯冲将大量水带入到地幔中,并对俯冲带地震的发生、地幔的熔融、岩浆的产生、陆壳的形成乃至矿产资源富集都起到了重要的控制作用。弧前隆起区的岩石圈地幔在顺断层渗透的深海水作用下发生强烈水化作用并形成水化地幔,是水富集在岩石圈的主要方式之一。随着俯冲板片深度的增加,在一定的温压条件下,水化地幔(蛇纹岩)发生脱水相变,引发俯冲带中源地震。脱出的水则由于运移的差异,既可以产生板内的水压致裂,也会影响俯冲界面的耦合,进而导致慢滑移地震区的形成。由此可见,俯冲带地区深海-岩石圈流体交换及其在深部的效应是一个包含化学反应-温度-流体流动-应力变形/破坏的多物理场耦合的复杂动力学系统。然而,目前的相关研究工作主要侧重于对其中某个因素、现象或者某个特定条件下具体过程的探索性观测分析研究。因此,我们需要从地球系统科学的角度出发,将流体运移、化学反应与传统的固体地球研究相结合,着眼于多学科交叉的多场耦合动力学综合研究,对俯冲带地区深海-岩石圈流体交换及其效应进行多时空尺度定量化表征和分析。     

不同陆面模式对我国地表温度模拟的适用性评估

基于CLDAS大气驱动数据驱动CLM3.5陆面模式和3种不同参数化方案下的Noah-MP陆面模式模拟得到的地表温度,利用中国气象局2009-2013年2000多个国家级地面观测站地表温度进行质量评估。结果表明:从时间分布看,模拟地表温度与观测的偏差及均方根误差均呈季节性波动;从空间分布看,模拟地表温度与观测的偏差及均方根误差在中国东部地区相对于中国西部地区更小。选择Noah-MP陆面模式3种不同参数化方案模拟结果进行对比,结果表明:Noah-MP模式的非动态植被方案不变时,考虑植被覆盖度的二流近似辐射传输方案的Noah-MP陆面模式模拟的地表温度优于考虑太阳高度角和植被三维结构的二流近似辐射传输方案Noah-MP陆面模式模拟的地表温度;选择动态植被方案的Noah-MP陆面模式模拟的地表温度优于选择非动态植被方案的Noah-MP陆面模式;总体而言,考虑动态植被方案的Noah-MP陆面模式模拟的地表温度优于其他两种参数化方案的Noah-MP陆面模式以及CLM3.5陆面模式模拟的地表温度。     

Heavy Rainfall Ensemble Prediction： Initial Condition Perturbation vs Multi-Physics Perturbation

Mesoscale ensemble is an encouraging technology for improving the accuracy of heavy rainfall predictions. Occurrences of heavy rainfall are closely related to convective instability and topography. In mid-latitudes, perturbed initial fields for medium-range weather forecasts are often configured to focus on the baroclinic instability rather than the convective instability. Thus, alternative approaches to generate initial perturba- tions need to be developed to accommodate the uncertainty of the convective instability. In this paper, an initial condition perturbation approach to mesoscale heavy rainfall ensemble prediction, named as Different Physics Mode Method （DPMM）, is presented in detail. Based on the PSU/NCAR mesoscale model MM5, an ensemble prediction experiment on a typical heavy rainfall event in South China is carried out by using the DPMM, and the structure of the initial condition perturbation is analyzed. Further, the DPMM ensem- ble prediction is compared with a multi-physics ensemble prediction, and the results show that the initial perturbation fields from the DPMM have a reasonable mesoscale circulation structure and could reflect the prediction uncertainty in the sensitive regions of convective instability. An evaluation of the DPMM ini- tial condition perturbation indicates that the DPMM method produces better ensemble members than the multi-physics perturbation method, and can significantly improve the precipitation forecast than the control non-ensemble run.     

THE IMPACT OF DIFFERENT PHYSICAL PROCESSES AND THEIR PARAMETERIZATIONS ON FORECAST OF A HEAVY RAINFALL IN SOUTH CHINA IN ANNUALLY FIRST RAINING SEASON

An ensemble prediction system based on the GRAPES model, using multi-physics, is used to discuss the influence of different physical processes in numerical models on forecast of heavy rainfall in South China in the annually first raining season(AFRS). Pattern, magnitude and area of precipitation, evolution of synoptic situation, as well as apparent heat source and apparent moisture sink between different ensemble members are comparatively analyzed. The choice of parameterization scheme for land-surface processes gives rise to the largest influence on the precipitation prediction. The influences of cumulus-convection and cloud-microphysics processes are mainly focused on heavy rainfall;the use of cumulus-convection parameterization tends to produce large-area and light rainfall. Change in parameterization schemes for land-surface and cumulus-convection processes both will cause prominent change in forecast of both dynamic and thermodynamic variables, while change in cloud-microphysics processes show primary impact on dynamic variables. Comparing simplified Arakawa-Schubert and Kain-Fritsch with Betts-Miller-Janjic schemes, SLAB with NOAH schemes, as well as both WRF single moment 6-class and NCEP 3-class with simplified explicit schemes of phase-mixed cloud and precipitation shows that the former predicts stronger low-level jets and high humidity concentration, more convective rainfall and local heavy rainfall, and have better performance in precipitation forecast. Appropriate parameterization schemes can reasonably describe the physical process related to heavy rainfall in South China in the AFRS, such as low-level convergence, latent heat release, vertical transport of heat and water vapor, thereby depicting the multi-scale interactions of low-level jet and meso-scale convective systems in heavy rainfall suitably, and improving the prediction of heavy rainfall in South China in the AFRS as a result.