Rainfall Variability and Trends in West Africa

Rainfall variability associated with climate change has enormous impacts on ecosystems, agriculture and people in West Africa but few studies have been devoted to it. Monthly rainfall data from 1901 to 2013, provided by the Global Precipitation Climatology Center dataset, were analyzed using segmentation and empirical modal decomposition (EMD) methods to increase our knowledge on past and recent spatio-temporal rainfall trends and their impacts on the West African region. The results obtained showed that the peak of rainfall during the short rainy season is observed in September in Côte d’Ivoire, Ghana and Liberia. The temporal variability of this rainfall is marked by several breakpoints whose durations range from 2 to 70 years. The periods of change in the rainfall regime, characterized by the appearance of breakpoints, vary from one country to another and are of unequal duration. The main breakpoint appears after 1960. Periods of relative or normal increase or decrease in precipitation are observed before and after 1960. The long-term variability of this rainfall is characterized by a decrease in the amount of rainfall over all West African countries. The results of this study can be used as a tool to help raise awareness among populations for sustainable management of water resources in response to climate change and its adverse effects.

A Methodology for Assessing Axial Compressor Stability with Inlet Temperature Ramp Distortion

Based on a small perturbation stability model for periodic flow,the effects of inlet total temperature ramp distortion on the axial compressor are investigated and the compressor stability is quantitatively evaluated.In the beginning,a small perturbation stability model for the periodic flow in compressors is proposed,referring to the governing equations of the Harmonic Balance Method.This stability model is validated on a single-stage low-speed compressor TA36 with uniform inlet flow.Then,the unsteady flow of TA36 with different inlet total temperature ramps and constant back pressure is simulated based on the Harmonic Balance Method.Based on these simulations,the compressor stability is analyzed using the proposed small perturbation model.Further,the Dynamic Mode Decomposition method is employed to accurately extract pressure oscillations.The two parameters of the temperature ramp,ramp rate and Strouhal number,are discussed in this paper.The results indicate the occurrence and extension of hysteresis loops in the rows,and a decrease in compressor stability with increasing ramp rate.Compressor performance is divided into two phases,stable and limit,based on the ramp rate.Furthermore,the model predictions suggest that a decrease in period length and an increase in Strouhal number lead to improved compressor stability.The DMD results imply that for compressors with inlet temperature ramp distortion,the increase of high-order modes and oscillations at the rotor tip is always the signal of decreasing stability.

Forecasting hourly PM_(2.5)concentrations based on decomposition-ensemble-reconstruction framework incorporating deep learning algorithms

Accurate predictions of hourly PM_(2.5)concentrations are crucial for preventing the harmful effects of air pollution.In this study,a new decomposition-ensemble framework incorporating the variational mode decomposition method(VMD),econometric forecasting method(autoregressive integrated moving average model,ARIMA),and deep learning techniques(convolutional neural networks(CNN)and temporal convolutional network(TCN))was developed to model the data characteristics of hourly PM_(2.5)concentrations.Taking the PM_(2.5)concentration of Lanzhou,Gansu Province,China as the sample,the empirical results demonstrated that the developed decomposition-ensemble framework is significantly superior to the benchmarks with the econometric model,machine learning models,basic deep learning models,and traditional decomposition-ensemble models,within one-,two-,or three-step-ahead.This study verified the effectiveness of the new prediction framework to capture the data patterns of PM_(2.5)concentration and can be employed as a meaningful PM_(2.5)concentrations prediction tool.

Extracting the interference components of normal modes in shallow water waveguide using singular value decomposition method

The normal mode interference characteristic in shallow water waveguide is a valu- able topic in the fields of underwater acoustic. A method for extracting the interference components of normal modes from broadband acoustic propagation data recorded by a single hy- drophone without any prior information is present in this paper. First, a Hermitian matrix is formed by the power spectral density. Second, a singular value decomposition （SVD） is performed on the Hermitian matrix to obtain the orthonormal eigenvectors, which are proportional to the interference components of normal modes. The fundamental equations of the new extracting method are derived based on normal mode and waveguide invariant theory. And the validity of the present method is verified by the numerical simulation and experimental results. In addition, the extracted results of normal-mode interference components are intended to be used for passive ranging of broadband sources.

Parameters of Exterior Ballistic Feature Points Extraction in Radar Measurement Data by EMD

The problem of measuring exterior ballistic feature points is always difficult to solve and it is essentiale on exterior ballistic measurement.By analysis of radar reflection characteristics and non-stationary echo signals of exterior ballistic feature points,the echo data of exterior ballistic feature points is measured by using the continuous wave radar.The parameters of feature points are extracted by the empirical mode decomposition method(EMD)of Hilbert-Huang transform(HHT)spectrum analysis technique.The radar echo signal model and EMD extraction model are established to analyze the exterior ballistic mutation point detection and EMD extraction method of aliasing echo signal.Typical feature point parameters of exterior ballistic in rocket flight tests are carried out and the effectiveness of the method is verified.A new method of measuring the parameters of exterior ballistic feature point is therefore presented.

Trends in per capita ecological footprint and biocapacity in China 1949-2013

This paper proposes two concepts: the ecological footprint component index(EFCI) and the biocapacity component index(BCCI), based on the ecological footprint(EF) and Shannon entropy approaches. Per capita EFCI and BCCI in China 1949-2013 are analyzed using empirical mode decomposition(EMD). Nonlinear models of per capita EFCI and BCCI in China 1949-2013 are presented and their cycles and predictions from 2014 to 2023 are analyzed. The results over the last 65 years show:(1) EFCI in China has increased constantly with fluctuations, while BCCI has slowly decreased. Their annual change rates are 2.81% and-1.26%, respectively. The increasing EFCI indicates a gradual improvement in China's sustainable development potential; the decreasing BCCI indicates severe environmental and population challenges.(2) The cycles of per capita EFCI have periods of 5.4 and 16.3 years, while cycles of per capita BCCI have periods of 3.6, 13,and 21.7 years. The predictive models indicate that EFCI will first decrease, reaching 0.02725 in2014, and will subsequently increase to 0.03261 in 2021. BCCI will increase, reaching 0.01365 in2014 and 0.01541 in 2022. EFCI and BCCI will reach 0.03037 and 0.01537, respectively, in 2023.Policymakers should ensure that the EFCI and BCCI increase in 2023.

Optimization design of anti-seismic engineering measures for intake tower based on non-dominated sorting genetic algorithm-Ⅱ

High-rise intake towers in high-intensity seismic areas are prone to structural safety problems under vibration.Therefore,effective and low-cost anti-seismic engineering measures must be designed for protection.An intake tower in northwest China was considered the research object,and its natural vibration characteristics and dynamic response were first analyzed using the mode decomposition response spectrum method based on a three-dimensional finite element model.The non-dominated sorting genetic algorithm-II(NSGA-II)was adopted to optimize the anti-seismic scheme combination by comprehensively considering the dynamic tower response and variable project cost.Finally,the rationality of the original intake tower antiseismic design scheme was evaluated according to the obtained optimal solution set,and recommendations for improvement were proposed.The method adopted in this study may provide significant references for designing anti-seismic measures for high-rise structures such as intake towers located in high-intensity earthquake areas.