Stokes profiles inversion techniques

Inversion techniques of the radiative transfer equation for polarized light are presented as one of the best current procedures to infer the vector magnetic field, as well as other quantities governing the physical state of the atmospheric layers that photons are coming from. Several characteristics of the various available inversion procedures are pointed out. They are mostly based on the diagnostic contents of the spectral lines as well as on the main hypotheses assumed in these procedures. In particular, the role of gradients in the atmospheric quantities is emphasized as of paramount importance in any diagnostic analysis and, hence, in any interpretation of inversion results.     

水库诱发地震最大震级的预测

水库蓄水诱发地震虽然是水利工程建设伴生的少见现象,但有时会诱发6级以上地震,加之震中距小,震源浅,成为水利工程抗震设防的重要因素。已有震例还证明,水库规模越大,诱震的可能性越大,诱震的最大震级Mmax(以下简写M)也越高。我们曾提出用水库的“综合影响参数E”来表征水库的“规模”,并给出了M～E回归关系式。本文在补充了部分震例资料,并把M和E以及最大库深Hmax(以下简写H)都视为随机量,经模式识别的分类判别后把所用震例分为两组(第一组为M≥4.5的21个震例:第二组为全部37个震例),把变量E取为确定量或取为随机量和把变量E、lnH取为两个随机量与M进行了回归。回归结果:第一组的双随机量(M、E)模型的回归标准差为口σ_M=0.610,变异系数V=0.118,三随机量(M,E,H)σ_M=0.576。V=0.111;第二组的双随机量的σ_M=1.028,V=0.234,三随机量时σ_M=1.032,V=0.235。说明第一组三随机量模型对可能发生M≥4.5级的新建水库的最大诱震震级的预测是可用的。     

连云港区台风增水预报方法探讨

本文采用增水峰、谷时与高、低潮时的对应关系预报未来24小时之内的增水峰、谷时。采用增水峰增、减趋势外延和回归计算相结合的方法预报其峰值。然后,利用模拟的增水曲线,对港区内的台风增水及潮位进行预报,效果很好。     

Ecohydrological modelling in a deciduous boreal forest: Model evaluation for application in non-stationary climates

Soil moisture is an important driver of growth in boreal Alaska, but estimating soil hydraulic parameters can be challenging in this data-sparse region. Parameter estimation is further complicated in regions with rapidly warming climate, where there is a need to minimize model error dependence on interannual climate variations. To better identify soil hydraulic parameters and quantify energy and water balance and soil moisture dynamics, we applied the physically based, one-dimensional ecohydrological Simultaneous Heat and Water (SHAW) model, loosely coupled with the Geophysical Institute of Permafrost Laboratory (GIPL) model, to an upland deciduous forest stand in interior Alaska over a 13-year period. Using a Generalized Likelihood Uncertainty Estimation parameterisation, SHAW reproduced interannual and vertical spatial variability of soil moisture during a five-year validation period quite well, with root mean squared error (RMSE) of volumetric water content at 0.5 m as low as 0.020 cm³/cm³. Many parameter sets reproduced reasonable soil moisture dynamics, suggesting considerable equifinality. Model performance generally declined in the eight-year validation period, indicating some overfitting and demonstrating the importance of interannual variability in model evaluation. We compared the performance of parameter sets selected based on traditional performance measures such as the RMSE that minimize error in soil moisture simulation, with one that is designed to minimize the dependence of model error on interannual climate variability using a new diagnostic approach we call CSMP, which stands for Climate Sensitivity of Model Performance. Use of the CSMP approach moderately decreases traditional model performance but may be more suitable for climate change applications, for which it is important that model error is independent from climate variability. These findings illustrate (1) that the SHAW model, coupled with GIPL, can adequately simulate soil moisture dynamics in this boreal deciduous region, (2) the importance of interannual variability in model parameterisation, and (3) a novel objective function for parameter selection to improve applicability in non-stationary climates.     

回归分析和BP神经网络在地表沉降监测中的应用

采用回归分析法中的曲线拟合法和BP神经网络模型的数值处理方法,对比两种方法在预测地表沉降中的有效性和准确性,对提高信息预测的精度和准确度有着积极的作用。     

Regression modeling method of space weather prediction

A regression modeling method of space weather prediction is proposed. It allows forecasting Dst index up to 6 hours ahead with about 90% correlation. It can also be used for constructing phenomenological models of interaction between the solar wind and the magnetosphere. With its help two new geoeffective parameters were found: latitudinal and longitudinal flow angles of the solar wind. It was shown that Dst index remembers its previous values for 2000 hours.     

P-σ全球模式的月尺度动力延伸预报试验

用P－σ混合坐标系原始方程模式（Nju-PσM)，以观测的瞬时气象要素场作为模式初始场，作了24个月动力延伸预报试验，利用距平符号一致率（P）、距平相关系数（AC）和均方根误差（RMS）对预报结果进行了评估和分析。试验表明Nju-PσM对月平均环流有一定的预报能力，气候漂移证正和预报结果的线性、势力的线型两种合成方法都对预报效果有明显的改进，把动力延伸预报与年际和月际持续性预报进行对比后，表明动力预报结果的各项评估分均为最高。预报场和实况场的空间滤波和经验正交函数（EOF）分析表明，模式对大尺度天气系统的预报能力较强，而对较小尺度天气系统的预报能力则差一例。     

祁连山强震构造带分段及其地震危险性评估

祁连山强震构造带由祁连山北缘断裂和海原断裂组成。断裂带主要表现为压扭性左旋滑动，最大滑动速率达９ｍｍ／ａ。沿带有一系列的古地震事件，且有多次历史地震发生。海原８．６级地震就发生在该带上。根据该带的断裂活动习性，按照一定的原则和依据划分成３个一级断层段和１７个二级断层段。建立了古地震、历史大震图像识别和地震重现间隔二元分析的数学模型。在此基础之上对该带作了地震危险性别定，划分出３个Ａ类危险段和４个Ｂ类危险段     

Comparative analysis of scalar upper tail indicators

ABSTRACT

Different upper tail indicators exist to characterize heavy tail phenomena, but no comparative study has been carried out so far. We evaluate the shape parameter (GEV), obesity index, Gini index and upper tail ratio (UTR) against a novel benchmark of tail heaviness – the surprise factor. Sensitivity analyses to sample size and changes in scale-to-location ratio are carried out in bootstrap experiments. The UTR replicates the surprise factor best but is most uncertain and only comparable between records of similar length. For samples with symmetric Lorenz curves, shape parameter, obesity and Gini indices provide consistent indications. For asymmetric Lorenz curves, however, the first two tend to overestimate, whereas Gini index tends to underestimate tail heaviness. We suggest the use of a combination of shape parameter, obesity and Gini index to characterize tail heaviness. These indicators should be supported with calculation of the Lorenz asymmetry coefficients and interpreted with caution.