Current status of ENSO prediction skill in coupled ocean–atmosphere models

The overall skill of ENSO prediction in retrospective forecasts made with ten different coupled GCMs is investigated. The coupled GCM datasets of the APCC/CliPAS and DEMETER projects are used for four seasons in the common 22 years from 1980 to 2001. As a baseline, a dynamic-statistical SST forecast and persistence are compared. Our study focuses on the tropical Pacific SST, especially by analyzing the NINO34 index. In coupled models, the accuracy of the simulated variability is related to the accuracy of the simulated mean state. Almost all models have problems in simulating the mean and mean annual cycle of SST, in spite of the positive influence of realistic initial conditions. As a result, the simulation of the interannual SST variability is also far from perfect in most coupled models. With increasing lead time, this discrepancy gets worse. As one measure of forecast skill, the tier-1 multi-model ensemble (MME) forecasts of NINO3.4 SST have an anomaly correlation coefficient of 0.86 at the month 6. This is higher than that of any individual model as well as both forecasts based on persistence and those made with the dynamic-statistical model. The forecast skill of individual models and the MME depends strongly on season, ENSO phase, and ENSO intensity. A stronger El Niño is better predicted. The growth phases of both the warm and cold events are better predicted than the corresponding decaying phases. ENSO-neutral periods are far worse predicted than warm or cold events. The skill of forecasts that start in February or May drops faster than that of forecasts that start in August or November. This behavior, often termed the spring predictability barrier, is in part because predictions starting from February or May contain more events in the decaying phase of ENSO.     

长江流域夏季降水的贝叶斯多模式集合概率预测

A Bayesian probabilistic prediction scheme of the Yangtze River Valley (YRV) summer rainfall is proposed to combine forecast information from multi-model ensemble dataset provided by ENSEMBLES project.Due to the low forecast skill of rainfall in dynamic models,the time series of regressed YRV summer rainfall are selected as ensemble members in the new scheme,instead of commonly-used YRV summer rainfall simulated by models.Each time series of regressed YRV summer rainfall is derived from a simple linear regression.The predictor in each simple linear regression is the skillfully simulated circulation or surface temperature factor which is highly linear with the observed YRV summer rainfall in the training set.The high correlation between the ensemble mean of these regressed YRV summer rainfall and observation benefit extracting more sample information from the ensemble system.The results show that the cross-validated skill of the new scheme over the period of 1960 to 2002 is much higher than equally-weighted ensemble,multiple linear regression,and Bayesian ensemble with simulated YRV summer rainfall as ensemble members.In addition,the new scheme is also more skillful than reference forecasts (random forecast at a 0.01 significance level for ensemble mean and climatology forecast for probability density function).     

ECC方法在中国夏季气温预测研究中的应用

以中国夏季气温为预测对象,选取东亚地区冬季500 h Pa高度场、海平面气压场、地表温度场和850 h Pa温度场为预测因子,采用1951~2009年去趋势处理后的资料,通过变形的典型相关分析(Barnett-Preisendorfer Canonical Correlation Analysis,BP-CCA)方法分别建立单因子预测模型,再利用集合典型相关分析(Ensemble Canonical Correlation,ECC)方法建立集合预测模型,对中国夏季气温进行基于交叉检验方法的预测试验,然后利用2010~2014年的资料对中国夏季气温进行独立样本检验。通过分析BP-CCA模态可知,一对BP-CCA模态的空间型在一定程度上可以反映预报因子场和对象场的遥相关特征。通过基于交叉检验方法的预测试验表明环流场和热力场均能为气温提供预测信息。ECC预测模型综合了各个预报因子的在不同地区的预报技巧,比单因子BP-CCA预测模型有更高、更稳定的预报技巧。独立样本检验表明ECC模型与单因子BP-CCA预测模型相比,对中国夏季气温有更高、更稳定的实际预测能力,对气温季节预测具有参考价值。     

几年来我国气候年际变异和短期气候预测研究的一些新成果

为了热烈庆祝中国科学院大气物理研究所成立80周年(1928～2008年),作者谨就五年来中国科学院大气物理研究所的科学家们完成的关于我国气候变异和气候预测方面的研究工作若干新成果作一些非常概要性的介绍,个中也包含一点所外科学家的工作。不周和不当之处只有请读者海涵和批评指正了。本文介绍的主要进展有三个方面:关于我国气候年际变异的研究、ENSO预测研究和数值气候预测研究。     

集合预报风场扰动的物理结构及演变特征

初始扰动结构和振幅的合理性直接影响到集合预报的质量和整体性能,合理的初始扰动结构是确保集合预报扰动质量的关键.本文基于欧洲中期天气预报中心数据、我国T639全球集合预报系统以及GRAPES区域集合预报系统的预报场,针对模式初值不确定性,主要研究了风场初始扰动结构及其集合离散度、扰动能量等结构和演变特征,分析了集合预报风...     

Short-term earthquake prediction: Current status of seismo-electromagnetics

Loss of human lives as a result of earthquakes is caused overwhelmingly by the collapse of buildings within less than a few minutes of main shocks. The most urgent countermeasure consists of two key elements. One is strengthening of weak structures and the other is short-term earthquake prediction. Short-term prediction needs precursors. Although some promising precursors are reported, the prevailing views in Japan and elsewhere are overly pessimistic. The pessimism largely roots in the fact that short-term precursors are generally non-seismic and tools developed for seismology are not designed to detect them. Nonetheless, nationally funded large-scale earthquake prediction programs always emphasize the need to reinforce seismometer networks. They do not take into account the views of those in the science community who point to the importance of non-seismic precursors. While there are well-founded causes to be skeptical, the situation needs to be improved. One reason for skepticism is that the observations of precursors have not yet been perfect enough and another is that some important fundamental aspects of non-seismic precursors are still unresolved. We review some of these problems.     

基于单邻点多波段预测的高光谱图像无损压缩算法

提出了一种基于聚类-单邻点、多波段预测-熵编码的高光谱数据无损压缩方法。根据谱向特征,进行高光谱图像矢量聚类。对各个分类,采用单个空间位置邻点、多个波段作为预测数据,训练预测系数,进行三维预测。残差采用Golomb-Rice编码。实验证实了算法的有效性。     

Convergent development of experimental landforms with differing rainfall and substrate properties

Four runs of experimental landform development, with the same uplift rate, different rainfall intensity, and the same material of different permeability adjusted by the degree of compaction, showed complicated effects of rainfall and mound-forming material. In the run with more rainfall on less permeable material, low separated ridges developed in the uplifted area, because abundant overland flow promoted valley erosion and slope processes from early stages. In the run with less rainfall on less permeable material, valley incision proceeded mostly in major valleys where surface water converges. Canyons developed during early stages and later a high massive mountain emerged. The effect of rainfall difference, however, appeared completely opposite on more permeable material accompanied by lower shear strength. In the run with more rainfall on more permeable material, a massive mountain similar to that with less rainfall on less permeable material appeared, and low separated ridges appeared in the run with less rainfall on more permeable material as in the run with more rainfall on less permeable material. In the former case, similar amount of water available for Hortonian overland flow in early stages estimated from rainfall rate and permeability can explain the development of similar landforms. In the latter case, while abundant surface water with more rainfall on less permeable material made fluvial erosion active from early stages, the deficiency in surface water with less rainfall on more permeable material apparently attenuated fluvial erosion but possibly accentuated slope processes and slope failures by seepage water flow through more permeable material of low shear strength. The active erosion from early stages apparently resulted in the development of enduring similar low landforms later in the dynamic equilibrium stage. These experimental results indicate that similar landforms can emerge from different environmental and lithologic controls, and that process does not necessarily follow from form.     

人工主余震作用下桥墩结构损伤预测评估分析

主余震作用下,断层距（R_JB）和余震次数的不同对结构造成的损伤也大不相同,进行主余震序列下桥梁损伤评估时需要考虑断层距、余震次数等影响因素。基于OpenSees平台,以一座连续梁桥为例,根据人工主余震构造时不同的影响因素,选用余震衰减和PGA调幅的人工主余震构造法构造主余震序列进行结构损伤分析,并与实际主余震事件的损伤结果作对比,研究人工构造主余震序列预测结构损伤的可行性。结果表明：基于PGA调幅构造主余震的方法,当考虑余震衰减时,能够较好模拟出结构在实际主余震地震作用下造成的最终损伤,能够较合理的预测结构在实际主余震序列中的损伤指标;对区域主余震作用下的桥梁进行损伤评估时,需要考虑断层距和余震次数影响因素,桥梁距断层距R_JB越近时结构的损伤状态越严重,余震发生次数越多则结构的损伤增量就越大,并且结构在人工主余震作用下R_JB越大的地方,结构损伤增量误差程度越小,预测的损伤状态就越接近实际的损伤状态。     

Predicting Terrestrial Flagstone Reservoirs in the Sha-I Member of the Qibei Depression in the Dagang Oilfield

There are few 3-D seismic profiles and drillings in the middle part of the Qibei depression in the Dagang oilfield, and more than 70% of the 2-D seismic profiles were completed before the 1980s. Meanwhile, changes in the terrestrial formations in this region have been large and complex. These factors have made it difficult to predict reservoirs in this area. The purpose of this paper is to establish a methodology for predicting potential gas and oil reservoirs. Our research combines sequence stratigraphy, well-logs, and seismic analysis to elucidate the prediction of flagstone reservoirs in the S1 (Sha-I) Member in the middle of the Qibei depression. Previous research indicates that these rocks were deposited in an environment that had a semiarid, northern subtropical, and warm, humid climate. The objective strata currently consist mainly of lake fades, deeper lake facies, and shore-shallow lake facies. The study reveals that the lower section of the S1 Member is an important objective region for explora