Combined gamma and M-test-based ANN and ARIMA models for groundwater fluctuation forecasting in semiarid regions

The shortage of surface water in arid and semiarid regions has led to the more use of the groundwater resources. In these areas, the groundwater is essential for activities such as water supply and irrigation. One of the most important stages in sustainable yield of groundwater resources is awareness of groundwater level. In this study, we have applied artificial neural networks (ANN) and autoregressive integrated moving average (ARIMA) models for groundwater level forecasting to 4 months ahead in Shiraz basin, southwestern Iran. Time series analysis was conducted according to the Box–Jenkins method. Meanwhile, gamma and M-test were considered for determining the optimal input combination and length of training and testing data in the ANN model. The results indicated that performance of multilayer perceptron neural network (4, 14, 1) and ARIMA (2, 1, 2) is satisfactory in the groundwater level forecasting for one month ahead. The performance comparison shows that the ARIMA model performs appreciably better than the ANN.     

江淮入梅前后大气环流的演变特征和西太平洋副高北跳西伸的可能机制

该文首先采用合成分析的方法研究了江淮入梅前后大尺度大气环流的演变特征和西太平洋副热带高压西伸北跳的可能机制。研究结果表明, 江淮入梅前期的最显著的特征是:副热带高压首先在太平洋中部增强北跳, 而后向西扩展导致太平洋副高西部脊 (120°E) 的增强北跳。进一步分析表明, 在太平洋中部副热带高压的增强北跳和西伸之前, 副热带高压南侧ITCZ中对流和孟加拉湾北部的对流活动明显并且都经历了一次增强活跃过程, 这意味着热带ITCZ和孟加拉湾北部对流的异常活跃可能对副热带高压的增强北跳西伸产生影响。全球大气环流模式模拟结果表明, 赤道中太平洋ITCZ中对流异常活跃不仅可导致副热带高压的增强北移, 而且还可导致副热带高压西伸, 与诊断分析结果相一致。     

Recent Rapid Regional Climate Warming on the Antarctic Peninsula

The Intergovernmental Panel on Climate Change (IPCC) confirmed that mean global warming was 0.6 ± 0.2 °C during the 20th century and cited anthropogenic increases in greenhouse gases as the likely cause of temperature rise in the last 50 years. But this mean value conceals the substantial complexity of observed climate change, which is seasonally- and diurnally-biased, decadally-variable and geographically patchy. In particular, over the last 50 years three high-latitude areas have undergone recent rapid regional (RRR) warming, which was substantially more rapid than the global mean. However, each RRR warming occupies a different climatic regime and may have an entirely different underlying cause. We discuss the significance of RRR warming in one area, the Antarctic Peninsula. Here warming was much more rapid than in the rest of Antarctica where it was not significantly different to the global mean. We highlight climate proxies that appear to show that RRR warming on the Antarctic Peninsula is unprecedented over the last two millennia, and so unlikely to be a natural mode of variability. So while the station records do not indicate a ubiquitous polar amplification of global warming, the RRR warming on the Antarctic Peninsula might be a regional amplification of such warming. This, however, remains unproven since we cannot yet be sure what mechanism leads to such an amplification. We discuss several possible candidate mechanisms: changing oceanographic or changing atmospheric circulation, or a regional air-sea-ice feedback amplifying greenhouse warming. We can show that atmospheric warming and reduction in sea-ice duration coincide in a small area on the west of the Antarctic Peninsula, but here we cannot yet distinguish cause and effect. Thus for the present we cannot determine which process is the probable cause of RRR warming on the Antarctic Peninsula and until the mechanism initiating and sustaining the RRR warming is understood, and is convincingly reproduced in climate models, we lack a sound basis for predicting climate change in this region over the coming century.     

Research on the loss of group residential buildings under fierce winds

The prediction and assessment of the loss of group residential buildings under fierce winds are not only an important but also a very basic work. Many rural buildings, especially situated in southeastern of China, have suffered great damage and losses during such wind events in past 10 years. One new methodology is proposed in this study in order to estimate and evaluate the loss reasonably based on group building types and distribution, wind intensities and directions. This methodology comprehensively considers the mechanisms of interaction between the roof tiles, roof panels, doors and windows, which are more likely damaged seriously during fierce winds, the physical properties of those components, the wind pressure coefficients on the surface of group buildings in different wind directions, etc. Then Monte Carlo simulation is used to estimate the damage of group residential buildings under simulated fluctuating winds with different speeds and measured typhoon records. The simulation results indicate that our proposed quantified assessment method can be utilized for official, developers, architects, designers and homeowners to estimate and mitigate the losses that might be experienced during wind-related disasters either pre- or post-construction.     

改进的能量守恒方法及其在CHAMP重力场恢复中的应用

An efficient method for gravity field determination from CHAMP orbits and accelerometer data is referred to as the energy balance approach. A new CHAMP gravity field recovery strategy based on the improved energy balance approach IS developed in this paper. The method simultaneously solves the spherical harmonic coefficients, daily Integration constant, scale and bias parameters. Two 60 degree and order gravitational potential models, XISM-CHAMPO1S from the classical energy balance approach, and XISM-CHAMPO2S from the improved energy balance, are determined using about one year＇s worth of CHAMP kinematic orbits from TUM and accelerometer data from GFZ. Comparisons among XISM-CHAMPO1S, XISM-CHAMPO2S, EIGEN-CGO3C, EIGEN-CHAMPO3S, EIGEN2, ENIGNIS and EGM96 are made. The results show that the XISM-CHAMPO2S model is more accurate than EGM96, EIGENIS, EIGEN2 and XISM-CHAMPO1S at the same degree and order, and has almost the same accuracy as EIGEN-CHAMPO3S.     

基于临近相似性考虑的犯罪热点密度图预测准确性比较——以DP半岛街头抢劫犯罪为例

在无时空考虑的密度估计算法基础上,分别加入了案件点之间的时间临近相似性、空间临近相似性和时空临近相似性的考虑,利用DP半岛2006~2007年的街头抢劫犯罪数据为基础计算无时空临近相似性、时间临近相似性、空间临近相似性和时空临近相似性4种不同算法所得到的犯罪热点图,并以之预测2008年的街头抢劫。通过Natural breaks（Jenks）分级方法和等比例面积选取两种方式来划定热点区域进行预测并进行PAI指数得分比较,结果表明时空临近相似性的密度估计算方法在犯罪预测的优势比较显著。     

The relationship between significant wave height and Indian Ocean Dipole in the equatorial North Indian Ocean

Based on reanalysis data, we find that the Indian Ocean Dipole (IOD) plays an important role in the variability of wave climate in the equatorial Northern Indian Ocean (NIO). Significant wave height (SWH) in the equatorial NIO, especially over the waters southeast to Sri Lanka, exhibits strong interannual variations. SWH anomalies in the waters southeast to Sri Lanka correlate well with dipole mode index (DMI) during both summer and autumn. Negative SWH anomalies occur over the oceanic area southeast to Sri Lanka during positive IOD events and vary with different types of IOD. During positive prolonged (unseasonable) IOD, the SWH anomalies are the strongest in autumn (summer); while during positive normal IOD, the SWH anomalies are weak in both summer and autumn. Strong easterly wind anomalies over the southeast oceanic area of Sri Lanka during positive IOD events weaken the original equatorial westerly wind stress, which leads to the decrease in wind-sea waves. The longer wave period during positive IOD events further confirms less wind-sea waves. The SWH anomaly pattern during negative IOD events is nearly opposite to that during positive IOD events.     

Bottom pressure change associated with the 2004–2005 large meander of the Kuroshio south of Japan

A large meander of the Kuroshio was generated in the region off the southern coast of Japan in August 2004 and continued until approximately July 2005. The formation and decay of the large-meander (LM) path was observed by bottom pressure (BP) sensors installed on inverted echo sounders (PIESs) and a seismic observing system off Shikoku. The variation in BP was examined focusing on the development, persistence, and decay of the LM path. The BP was found to be depressed associated with a Kuroshio path disturbance, called a small meander, and this BP depression led the sea surface height (SSH) depression by up to approximately two months. The temporal phase shift between the sea surface and deep disturbances was significantly greater than those of other small meanders that did not develop into large meanders. After the formation of the LM path, the BP beneath the Kuroshio increased with a lag of approximately two months behind the SSH elevation along with the upward displacement of the main thermocline. The increase in BP is associated with that of the positive southward BP gradient anomaly, i.e., the eastward deep Kuroshio current anomaly, which suggests an enhancement of the topographic steering and stability of the LM path. This is consistent with the fact that no small meanders occurred in the early LM period from late July 2004 to late January 2005.     

Enhancing the Forecasting of Monthly Streamflow in the Main Key Stations of the River Nile Basin

Predicting the streamflow of rivers can have a significant economic impact, as this can help in agricultural water management and in providing protection from water shortages and possible flood damage. In this study, two statistical models have been used; Deseasonalized Autoregressive moving average model (DARMA) and Artificial Neural Network (ANN) to predict monthly streamflow which important for reservoir operation policy using different time scale, monthly and 1/3 monthly (ten-days) flow data for River Nile basin at five key stations. The streamflow series is deseasonalized at different time scale and then an appropriate nonseasonal stochastic DARMA (p, q) models are built by using the plots of Partial Auto Correlation Function (PACF) to determine the order (p) of DARMA model. Then the deseasonalized data for key stations are used as input to ANN models with lags equals to the order (p) of DARMA model. The performance of ANN and DARMA models are compared using statistical methods. The results show that the developed model (using 1/3 monthly (ten-days) and ANN) has the best performance to predict monthly streamflow at all key stations. The results also show that the relative error in the developed model result did not exceed 9% while in the traditional models reach to 68% in the flood months in the testing period. The result also indicates that ANN has considerable potential for river flow forecasting.     

河北昌黎地震台地电阻率异常分析

河北昌黎台地电阻率EW测道2017年6-8月出现快速下降变化,经检测,观测系统工作正常。通过环境调研和辅助资料对比分析,发现该变化与降雨和粉丝厂干扰有一定关系。采用褶积滤波法去掉降雨干扰,EW测道地电阻率仍为下降趋势,说明该下降变化不能完全用降雨来解释,不排除是地震前异常变化的可能。