scholarly journals Short-Range Water Temperature Profiling in a Lake with Coastal Acoustic Tomography

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4498
Author(s):  
Haocai Huang ◽  
Yong Guo ◽  
Guangming Li ◽  
Kaneko Arata ◽  
Xinyi Xie ◽  
...  
Keyword(s):  
Water Temperature ◽  
Short Range ◽  
Moving Average ◽  
Time Windows ◽  
Innovative Technology ◽  
Acoustic Tomography ◽  
Transmission Experiment ◽  
Regularized Inversion ◽  
Vertical Slice ◽  
Tomography Method

Coastal acoustic tomography (CAT), as an innovative technology, can perform water temperature measurements both in horizontal and vertical slices. Investigations on vertical slice observations are significantly fewer in number than horizontal observations due to difficulties in multi-path arrival peak identification. In this study, a two-station sound transmission experiment is carried out in Thousand-Island Lake, Hangzhou, China, to acquire acoustic data for water temperature profiling. Time windows, determined by range-independent ray simulation, are used to identify multi-path arrival peaks and obtain corresponding sound wave travel times. Special attention is paid to travel time correction, whose errors are caused by position drifting by more than 2 m of moored stations. The sound speed and temperature profiling are divided into four layers and are calculated by regularized inversion. Results show a good consistency with conductivity–temperature–depth (CTD) measurements. The root mean square error (RMSE) of water temperature is 0.3494, 0.6838, 1.0236 and 1.0985 °C for layer 1, 2, 3 and 4, respectively. The fluctuations of measurement are further smoothed by the moving average, which decreases the RMSE of water temperature to 0.2858, 0.4742, 0.7719 and 0.9945 °C, respectively. This study illustrates the feasibility and high accuracy of the coastal acoustic tomography method in short-range water temperature measurement. Furthermore, 3D water temperature field profiling can be performed with combined analyzing in horizontal and vertical slices.

Continuously sensing of water temperature in a lake using acoustic tomography method

2021 ◽  
Vol 13 (3) ◽  
pp. 219-225
Author(s):  
Haocai Huang ◽  
Xinyi Xie ◽  
Shijie Xu ◽  
Yong Guo ◽  
Shuo Liu ◽  
...  
Keyword(s):  
Water Temperature ◽  
Acoustic Tomography ◽  
Tomography Method

scholarly journals Layer-Averaged Water Temperature Sensing in a Lake by Acoustic Tomography with a Focus on the Inversion Stratification Mechanism

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7448
Author(s):  
Shijie Xu ◽  
Zhao Xue ◽  
Xinyi Xie ◽  
Haocai Huang ◽  
Guangming Li
Keyword(s):  
Water Temperature ◽  
Fluid Dynamic ◽  
Field Measurements ◽  
Temperature Sensing ◽  
Acoustic Tomography ◽  
Inversion Method ◽  
Average Water Temperature ◽  
Travel Information ◽  
Average Water ◽  
Tomography Method

Continuous sensing of water parameters is of great importance to fluid dynamic progress study in oceans, coastal areas and inland waters. The acoustic tomography technique can perform water temperature field measurements horizontally and vertically using sound wave travel information. The layer-averaged water temperature can also be measured with the acoustic tomography method. However, investigations focusing on the stratified mechanism, which consists of stratification form and its influence on inversion error, are seldom performed. In this study, an acoustic tomography experiment was carried out in a reservoir along two vertical slices to observe the layer-averaged water temperature. Specifically, multi-path sound travel information is identified through ray tracing using high-precision topography data obtained via a ship-mounted ADCP during the experiment. Vertical slices between sound stations are divided into different layers to study layer division inversion methods in different preset types. The inversion method is used to calculate the average water temperature and inversion temperature error of every layer. Different layer methods are studied with a comparison of results. The layer division principle studied in this paper can be used for layer-averaged water temperature sensing with multi-path sound transmission information.

scholarly journals Continuous Sensing of Water Temperature in a Reservoir with Grid Inversion Method Based on Acoustic Tomography System

2021 ◽  
Vol 13 (13) ◽  
pp. 2633
Author(s):  
Haocai Huang ◽  
Shijie Xu ◽  
Xinyi Xie ◽  
Yong Guo ◽  
Luwen Meng ◽  
...  
Keyword(s):  
Water Temperature ◽  
Grid Method ◽  
Small Scale ◽  
Acoustic Tomography ◽  
Inversion Method ◽  
Sound Waves ◽  
Water Parameters ◽  
Tomography System ◽  
Vertical Slice ◽  
Over Time

The continuous sensing of water parameters is of great importance to the study of dynamic processes in the ocean, coastal areas, and inland waters. Conventional fixed-point and ship-based observing systems cannot provide sufficient sampling of rapidly varying processes, especially for small-scale phenomena. Acoustic tomography can achieve the sensing of water parameter variations over time by continuously using sound wave propagation information. A multi-station acoustic tomography experiment was carried out in a reservoir with three sound stations for water temperature observation. Specifically, multi-path propagation sound waves were identified with ray tracing using high-precision topography data obtained with ship-mounted ADCP. A new grid inverse method is proposed in this paper for water temperature profiling along a vertical slice. The progression of water temperature variation in three vertical slices between acoustic stations was mapped by solving an inverse problem. The reliability and adaptability of the grid method developed in this research are verified by comparison with layer-averaged water temperature results. The grid method can be further developed for the 3D mapping of water parameters over time, especially in small-scale water areas, where sufficient multi-path propagation sound waves can be obtained.

Harmonic Analysis of Non-Sinusoidal Harmonic Signals in Electric Power System

2014 ◽  
Vol 1070-1072 ◽  
pp. 779-784
Author(s):  
Dan Luo ◽  
Yi Xiao ◽  
Jie Na Zhou
Keyword(s):  
Power System ◽  
Harmonic Analysis ◽  
Short Range ◽  
Time Windows ◽  
Electric Power System ◽  
Normal Operation ◽  
Calculation Error ◽  
Interpolation Algorithm ◽  
Harmonic Signals ◽  
And Control

Harmonic Analysis and control is very important for the power system because harmonics have serious harm to its normal operation. Harmonic Analysis uses fast Fourier transform (FFT) to solve this problem though it causes the spectrum leakage which Increases the calculation error. To solve this problem, the interpolation algorithm combine with tapered time windows are used. The tapered time windows solve the long-range leakage and the interpolation algorithm solves the problem of short-range leakage.

Spatial and Temporal Variability of Water Temperature during early Stage of Kelp Culture in Sanggou Bay, China

2014 ◽  
Vol 955-959 ◽  
pp. 1151-1154
Author(s):  
Xu Dong Qiao ◽  
Da Ji Huang ◽  
Ding Yong Zeng ◽  
Zeng Jie Jiang ◽  
Jian Guang Fang
Keyword(s):  
Water Temperature ◽  
Water Depth ◽  
Temporal Variability ◽  
Early Stage ◽  
Moving Average ◽  
Spatial And Temporal Variability ◽  
Synoptic Scale ◽  
Temperature Variations ◽  
Sanggou Bay ◽  
Filter Water

The spatial-temporal variability of water temperature in autumn during the early stage of kelp culture in Sanggou Bay was studied based on moored measurements. The vertical profiles of temperature demonstrated that the water columns were well mixed. By using moving average filter, water temperature variations were decomposed to the trend (>12d), synoptic-scale (5~12d) component, and tidal-scale (<25h) component. Temperature variations were dominated by the trend which dropped gradually during the observation. The temperature decline rates, which were affected by water depth, varied from 0.16 °C/d to 0.24 °C/d. Synoptic and tidal cycles contributed to the temporal oscillations of temperature. The synoptic-scale components were also modulated by water depth. The ranges of tidal-scale component were higher at the bay mouth than those in the inner bay. Water temperature during the early stage of kelp culture was basically within the optimum ranges for kelp and bivalves.

scholarly journals Streamflow drought: implication of drought definitions and its application for drought forecasting

2020 ◽  
Author(s):  
Samuel J. Sutanto ◽  
Henny A. J. Van Lanen
Keyword(s):  
Moving Average ◽  
Time Windows ◽  
Early Warning Systems ◽  
Streamflow Forecasting ◽  
Drought Forecasting ◽  
Comprehensive Overview ◽  
Variable Threshold ◽  
Daily Streamflow ◽  
Streamflow Data ◽  
Drought Early Warning

Abstract. Streamflow drought forecasting is a key element of contemporary Drought Early Warning Systems (DEWS). The term streamflow drought forecasting, rather than streamflow forecasting, however, has created confusion within the scientific hydro-meteorological community, as well as in operational weather and water management services. The way, how streamflow drought is defined, is the main reason for this misperception. The purpose of this study, therefore, is to provide a comprehensive overview of the differences within streamflow droughts using different identification approaches for European rivers, including an analysis of both historical drought and implications of forecasting of these extreme events. Streamflow data were obtained from a LISFLOOD hydrological model forced with gridded meteorological observed (known as LISFLOOD-Simulation Forced with Observed, SFO). The same model fed with seasonal meteorological forecasts of the European Centre for Medium-range Weather Forecasts system 5 (ECMWF SEAS 5) was used to obtain the forecasted streamflow. Streamflow droughts were analyzed using the Variable Threshold (VT), Fixed Threshold (FT), and the Standardized Streamflow Index (SSI). Our results clearly show that streamflow droughts derived from different approaches deviate from each other both in occurrence and timing, associated with different climate regions across Europe. The occurrence of FT drought is higher than droughts based upon VT and SSI, which highlights the importance of seasonality. FT drought happens earlier in the year than droughts obtained from VT and SSI. The use of aggregating daily streamflow data into monthly time windows for forecasting drought, such as the application of 30-day Moving Average (30DMA), is recommended to identify the VT and FT droughts. This approach will eliminate the undesired minor drought events, which are identified when using non-aggregated daily flow data. There is no unique hydrological drought definition that fits all purposes, hence developers of DEWS and end-users should clearly agree among themselves upon a sharp definition on which type of streamflow drought is required to be forecasted for a specific application.

scholarly journals Long-Term Residential Exposure to Particulate Matter and Its Components, Nitrogen Dioxide and Ozone—A Northern Sweden Cohort Study on Mortality

2021 ◽  
Vol 18 (16) ◽  
pp. 8476
Author(s):  
Johan N. Sommar ◽  
Ulla Hvidtfeldt ◽  
Camilla Geels ◽  
Lise M. Frohn ◽  
Jørgen Brandt ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Nitrogen Dioxide ◽  
Moving Average ◽  
Time Windows ◽  
Lung Cancer Mortality ◽  
Natural Mortality ◽  
Carbonaceous Particles ◽  
Low Exposure ◽  
Cvd Mortality

This study aims to estimate the mortality risk associated with air pollution in a Swedish cohort with relatively low exposure. Air pollution models were used to estimate annual mean concentrations of particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5), primary emitted carbonaceous particles (BC/pOC), sea salt, chemically formed particles grouped as secondary inorganic and organic aerosols (SIA and SOA) as well as ozone (O3) and nitrogen dioxide (NO2). The exposure, as a moving average was calculated based on home address for the time windows 1 year (lag 1), 1–5 years (lag 1–5) and 1–10 years (lag 1–10) preceding the death. During the study period, 1151 cases of natural mortality, 253 cases of cardiovascular disease (CVD) mortality and 113 cases of respiratory and lung cancer mortality were observed during 369,394 person-years of follow-up. Increased natural mortality was observed in association with NO2 (3% [95% CI −8–14%] per IQR) and PM2.5 (2% [95% CI −5–9%] for an IQR increase) and its components, except for SOA where a decreased risk was observed. Higher risk increases were observed for CVD mortality (e.g., 18% [95% CI 1–39%] per IQR for NO2). These findings at low exposure levels are relevant for future decisions concerning air quality policies.

scholarly journals On the Use of Running Trends as Summary Statistics for Univariate Time Series and Time Series Association

2015 ◽  
Vol 28 (19) ◽  
pp. 7489-7502 ◽  
Author(s):  
Mario Trottini ◽  
Maria Isabel ◽  
Vigo Aguiar ◽  
Santiago Belda Palazón
Keyword(s):  
Time Series ◽  
Applied Research ◽  
Moving Average ◽  
Time Windows ◽  
Diagnostic Tools ◽  
Summary Statistics ◽  
Original Series ◽  
Univariate Time Series ◽  
Consecutive Time ◽  
Weighted Moving Average

Abstract Given a time series, running trends analysis (RTA) involves evaluating least squares trends over overlapping time windows of L consecutive time points, with overlap by all but one observation. This produces a new series called the “running trends series,” which is used as summary statistics of the original series for further analysis. In recent years, RTA has been widely used in climate applied research as summary statistics for time series and time series association. There is no doubt that RTA might be a useful descriptive tool, but, despite its general use in applied research, precisely what it reveals about the underlying time series is unclear and, as a result, its interpretation is unclear too. This paper contributes to such interpretation in two ways: 1) an explicit formula is obtained for the set of time series with a given series of running trends, making it possible to show that running trends, alone, perform very poorly as summary statistics for univariate time series and time series association; and 2) an equivalence is established between RTA and the estimation of a (possibly nonlinear) trend component of the underlying time series using a weighted moving average filter. Such equivalence provides a solid ground for RTA implementation and interpretation/validation. In this respect, the authors propose as diagnostic tools for RTA 1) the plot of the original series, with RTA trend estimation superposed, 2) the average R2 value and the percentage of statistically significant running trends across windows, and 3) the plot of the running trends series with the corresponding confidence intervals.

The robustness of seismic attenuation measurements using fixed- and variable-window time-frequency transforms

Geophysics ◽  
2009 ◽  
Vol 74 (2) ◽  
pp. WA123-WA135 ◽  
Author(s):  
Carl Reine ◽  
Mirko van der Baan ◽  
Roger Clark
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Time Window ◽  
Time Windows ◽  
Seismic Attenuation ◽  
Continuous Wavelet ◽  
Transmission Experiment ◽  
Time Frequency ◽  
S Transform ◽  
Variable Window

Frequency-based methods for measuring seismic attenuation are used commonly in exploration geophysics. To measure the spectrum of a nonstationary seismic signal, different methods are available, including transforms with time windows that are either fixed or systematically varying with the frequency being analyzed. We compare four time-frequency transforms and show that the choice of a fixed- or variable-window transform affects the robustness and accuracy of the resulting attenuation measurements. For fixed-window transforms, we use the short-time Fourier transform and Gabor transform. The S-transform and continuous wavelet transform are analyzed as the variable-length transforms. First we conduct a synthetic transmission experiment, and compare the frequency-dependent scattering attenuation to the theoretically predicted values. From this procedure, we find that variable-window transforms reduce the uncertainty and biasof the resulting attenuation estimate, specifically at the upper and lower ends of the signal bandwidth. Our second experiment measures attenuation from a zero-offset reflection synthetic using a linear regression of spectral ratios. Estimates for constant-[Formula: see text] attenuation obtained with the variable-window transforms depend less on the choice of regression bandwidth, resulting in a more precise attenuation estimate. These results are repeated in our analysis of surface seismic data, whereby we also find that the attenuation measurements made by variable-window transforms have a stronger match to their expected trend with offset. We conclude that time-frequency transforms with a systematically varying time window, such as the S-transform and continuous wavelet transform, allow for more robust estimates of seismic attenuation. Peaks and notches in the measured spectrum are reduced because the analyzed primary signal is better isolated from the coda, and because of high-frequency spectral smoothing implicit in the use of short-analysis windows.

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