Variation analysis of precipitation during past 286 years in Beijing area,China, using non‐parametric test and wavelet analysis

Non‐parametric methods including Mann–Kendall (M–K) test, continuous wavelet transform (CWT) and discrete wavelet transform analysis are applied in this paper to detect the trend and periodic trait of precipitation data series in Beijing area where the data set spans nearly 300 years from 1724 to 2009. First, the trend of precipitation variables is elaborated by the M–K test (Sequential M–K test). The results show that there is an increasing trend (the value of this trend is 1.98) at the 5%‐significance level and there are not turning points in the whole data series. Then, CWT and wavelet variance are used to check for significant periodic characteristics of data series. In the plots of wavelet transform coefficients and figure of wavelet variance, some periodic events affect the trend of the annual total precipitation series in Beijing area. 85‐year, 35‐year and 21‐year periodic events are found to be the main periodic series of long‐term precipitation data, and they are all statistically significant. Moreover, the results of non‐parametric M–K test are exhibited on seven different combinations of discrete wavelet components. D5 (32‐year periodicity) periodic component is the effective and significant component on data. It is coincident with the result (35‐year periodic event as one part of main periodicity) by using CWT analysis. Moreover, approximation mode shows potential trend of the whole data set because it is the residuals as all periodicities are removed from data series. Thus, the mode A + D5 is responsible for producing a real basic structure of the trend founded on the data. Copyright © 2012 John Wiley & Sons, Ltd.     

Tropical cyclones and floods in Fiji

Abstract

Daily flow records, rainfall data and tropical cyclone maps during 1970–1998 are used to document the impact of tropical cyclones (TCs) on floods in the Rewa River system, Viti Levu, Fiji. Floods are large, brief, isolated events caused by TCs and non-TC tropical rainstorms. More floods are caused by tropical rainstorms than by TCs, but TC floods are larger. The log Pearson Type III distribution consistently provided the best fit to partial duration flood series and the widely-recommended generalized Pareto distribution performed very poorly, underscoring the need to test a variety of distributions for a particular geographic location. Tropical cyclones occur more often in Fiji during negative values of the Southern Oscillation Index (SOI) and all TCs that occurred during El Niño conditions caused floods. Peak flood discharges caused by TCs are inversely correlated with the SOI, reflecting possible links with tropical cyclone frequency and precipitation intensity.     

Complex spatial feedbacks of tephra redistribution,ice melt and surface roughness modulate ablation on tephra covered glaciers

Tephra fallout from the 2011 Grímsvötn eruption onto Svínafellsjökull, Iceland, created an ice‐ash landscape of a type that is rarely studied but is nevertheless common in glacio‐volcanic regions. We used terrestrial laser scanning (TLS) to measure ice surface topography and absorption at high spatial resolution, confirming ablation rates either reduce or increase under thick (insulating) and thin (reduced albedo) ash deposits, respectively. Fourier transform analysis of the TLS data identified that a three‐fold increase in aerodynamic roughness was attributable to an increase in larger (> 0·2 m) surface features. Moreover, TLS measurements revealed the importance of ash redistribution by meltwater in generating differential melting which modifies roughness and ash patchiness, such that the net effect of these spatial ash–ice feedbacks was to reduce ablation rates by up to 59%. The modulating effects of these previously undocumented feedbacks on ablation rates are, therefore, significant and must be correctly parameterized if ash‐covered glacier mass balances are to be predicted correctly. Copyright © 2012 John Wiley & Sons, Ltd.     

Investigation of the fractal dimension of rainfall occurrence in a semi-arid Mediterranean climate

Abstract

The scale invariance of rainfall series in the Tunis area, Tunisia (semi-arid Mediterranean climate) is studied in a mono-fractal framework by applying the box counting method to four series of observations, each about 2.5 years in length, based on a time resolution of 5 min. In addition, a single series of daily rainfall records for the period 1873–2009 was analysed. Three self-similar structures were identified: micro-scale (5 min to 2 d) with fractal dimension 0.44, meso-scale (2 d to one week) and synoptic-scale (one week to eight months) with fractal dimension 0.9. Interpretation of these findings suggests that only the micro-scale and transition to saturation are consistent, while the high fractal dimension relating to the synoptic scale might be affected by the tendency to saturation. A sensitivity analysis of the estimated fractal dimension was performed using daily rainfall data by varying the series length, as well as the intensity threshold for the detection of rain.

Editor Z.W. Kundzewicz; Associate editor S. Grimaldi

Citation Ghanmi, H., Bargaoui, Z., and Mallet, C., 2013. Investigation of the fractal dimension of rainfall occurrence in a semi-arid Mediterranean climate. Hydrological Sciences Journal, 58 (3), 483–497.     

Identification of precipitation zones within São Francisco River basin (Brazil) by global wavelet power spectra

Abstract

The definition of rainfall behaviour at the regional level is of great importance in planning policy for the rational use of water resources for both agricultural and urban uses. It allows the delimitation of areas of homogeneous rainfall features and shows the system dynamics in the area, so providing more comprehensive knowledge about the rainfall. Precipitation zones were identified within the São Francisco River basin, Northeast Brazil, by analysing the rainfall frequencies by means of global wavelet power spectra. Data from 200 raingauges were analysed and the results of the overall power spectra showed a high annual frequency throughout the basin; however, other frequencies are present with minor significance that represent changes in the rainfall regime. Although, the computed global wavelet power spectra presented an annual frequency, they showed peculiar patterns (denoted A and B) that could be used to characterize the region. Thus, three sub-regions with homogeneous rainfall patterns were identified as: Region A (south part of the basin) and Region B (north part of the basin), with frequency patterns A and B, respectively, and a Transition Zone in the central part that shows both frequency patterns.

Citation Santos, C.A.G. and Morais, B.S., 2013. Identification of precipitation zones within São Francisco River basin (Brazil) by global wavelet power spectra. Hydrological Sciences Journal, 58 (4), 789–796.     

Daily streamflow forecasting using a wavelet transform and artificial neural network hybrid models

Abstract

New wavelet and artificial neural network (WA) hybrid models are proposed for daily streamflow forecasting at 1, 3, 5 and 7 days ahead, based on the low-frequency components of the original signal (approximations). The results show that the proposed hybrid models give significantly better results than the classical artificial neural network (ANN) model for all tested situations. For short-term (1-day ahead) forecasts, information on higher-frequency signal components was essential to ensure good model performance. However, for forecasting more days ahead, lower-frequency components are needed as input to the proposed hybrid models. The WA models also proved to be effective for eliminating the lags often seen in daily streamflow forecasts obtained by classical ANN models. 

Editor D. Koutsoyiannis; Associate editor L. See

Citation Santos, C.A.G. and Silva, G.B.L., 2013. Daily streamflow forecasting using a wavelet transform and artificial neural network hybrid models. Hydrological Sciences Journal, 59 (2), 312–324.     

锡林浩特地震台地磁观测干扰分析

对内蒙古自治区锡林浩特地震台2019年10—11月质子矢量磁力仪FHD-2B的数据进行常规分析,发现D分量测值数据出现噪声大、突跳多的异常现象。对该台质子矢量磁力仪受干扰数据进行傅里叶变换和小波分析,确定干扰源范围,排除外界干扰可能。进一步对仪器进行检测,确定干扰原因为参数漂移,在进行参数校正后,观测数据恢复正常。     

广义付里叶变换及其在磁共振成像中的应用

许多共振成像（ＭＲＩ）的应用,要求人体组织磁化强度的空间分布Ｆｏｕｒｉｅｒ变换的幅度和相位的精确分离,及利用正交双通道采集时间和空间高分辨图象序列。在传统的基于Ｆｏｕｒｉｅｒ变换的成象方法中,图象序列从一帧空间编码独立地重建得到,因此给定空间分辨率的情况下,每帧空间编码的数量限制了图象序列的时间分辨力;又常通过牺牲空间分辨率来提高图象序列的空间分辨录。由于传统Ｆｏｕｒｉｅｒ变换的核函数是线性相位,若变换ＭＲＩ技术必须很好地满足主磁场均匀性和梯度场线性的条件,因此传统Ｆｏｕｒｉｅｒ变换成象方法对临床应用中常出现ＭＲ信号相位失真极为敏感。本文提出：利用主磁场中组织的磁化强度不变,能很好消除图象的相位失真。     

叠前共炮点道集的奇性反演研究

讨论了地震波场的Fourier积分算子奇性反演理论与方法,得出常数背景假设条件下二维共炮点道集奇性反演的解析表达式．构造了两个理论地震模型,分别进行二维有限差分正演与奇性反演的数值计算将二维Fourier积分算子奇性反演方法用于野外的二维地震勘探叠前共炮点记录．在勘探范围内,当介质波速变化相对背景波速符合小扰动假设时,理论模型与实际地震数据的计算结果表明这种奇性反演方法的有效性和实用性     

DEEP TECTONIC STRESS CHANGE BASED ON LONG-TERM APPARENT RESISTIVITY TIME SERIES: A CASE STUDY FROM NORTH SECTION OF YISHU FAULT ZONE

Almost all the destructive earthquakes, so called tectonic earthquake, are produced by tectonic movement. The tectonic movement will cause resistivity changes in the earth. It's valuable for strong earthquake forecast to study the relationship between the resistivity change and tectonic movement. According to magnetotelluric sounding method, we establish a robust estimate method to calculate the long-term apparent resistivity from seismic station monitoring data. We first use 1D layered earth models to test the sensitivity of this method. Then we process the continually observed long term electromagnetic data in 4 years (from 2011 to 2014) from Anqiu seismic station which is very close to the north section of Yishu fault zone. The apparent resistivity curves and the apparent resistivity time series for different frequencies are obtained. The time series show the resistivity increase in the selected 4 years, which is in good agreement with the GPS baseline data. This also satisfies the results from rock mechanics experiments on deep rocks (upper mantle) that the resistivity will increase with improved stress in a high temperature and pressure environment. The method is valuable for studying electromagnetic precursor of strong earthquakes and strong earthquake prediction.