Comparison of Multi-GNSS Time and Frequency Transfer Performance Using Overlap-Frequency Observations

The modernized GPS, Galileo, and BeiDou global navigation satellite system (BDS3) offers new potential for time transfer using overlap-frequency (L1/E1/B1, L5/E5a/B2a) observations. To assess the performance of time and frequency transfer with overlap-frequency observations for GPS, Galileo, and BDS3, the mathematical models of single- and dual-frequency using the carrier-phase (CP) technique are discussed and presented. For the single-frequency CP model, the three-day average RMS values of the L5/E5a/B2a clock difference series were 0.218 ns for Galileo and 0.263 ns for BDS3, of which the improvements were 36.2% for Galileo and 43.9% for BDS3 when compared with the L1/E1/B1 solution at BRUX–PTBB. For the hydrogen–cesium time link BRUX–KIRU, the RMS values of the L5/E5a/B2a solution were 0.490 ns for Galileo and 0.608 ns for BDS3, improving Galileo by 6.4% and BDS3 by 12.5% when compared with the L1/E1/B1 solution. For the dual-frequency CP model, the average stability values of the L5/E5a/B2a solution at the BRUX–PTBB time link were 3.54∙× 10−12 for GPS, 2.20 × 10−12 for Galileo, and 2.69 × 10−12 for BDS3, of which the improvements were 21.0%, 45.1%, and 52.3%, respectively, when compared with the L1/E1/B1 solution. For the BRUX–KIRU time link, the improvements were 4.2%, 30.5%, and 36.1%, respectively.

A novel dissolved oxygen prediction model based on enhanced semi-naive Bayes for ocean ranches in northeast China

A challenge of achieving intelligent marine ranching is the prediction of dissolved oxygen (DO). DO directly reflects marine ranching environmental conditions. Through accurate DO predictions, timely human intervention can be made in marine pasture water environments to avoid problems such as reduced yields or marine crop death due to low oxygen concentrations in the water. We use an enhanced semi-naive Bayes model for prediction based on an analysis of DO data from marine pastures in northeastern China from the past three years. Based on the semi-naive Bayes model, this paper takes the possible values of a DO difference series as categories, counts the possible values of the first-order difference series and the difference series of the interval before each possible value, and selects the most probable difference series value at the next moment. The prediction accuracy is optimized by adjusting the attribute length and frequency threshold of the difference sequence. The enhanced semi-naive Bayes model is compared with LSTM, RBF, SVR and other models, and the error function and Willmott’s index of agreement are used to evaluate the prediction accuracy. The experimental results show that the proposed model has high prediction accuracy for DO attributes in marine pastures.

Urbanization Effect on Estimate of Global Trends in Mean and Extreme Air Temperature

Identifying and separating the signal of urbanization effect in current temperature data series are essential for accurately detecting, attributing and projecting mean and extreme temperature change on varied spatial scales. This paper proposes a new method based on machine learning to classify the observational stations into rural stations and urban stations. Based the classification of rural and urban stations, the global and regional land annual mean and extreme temperature indices series over 1951-2018 for all stations and rural stations were calculated, and the urbanization effects and the urbanization contribution of global land annual mean and extreme temperature indices series are quantitatively evaluated using the difference series between the all stations and the rural stations. The results showed that the global land annual mean time series for mean temperature and most extreme temperature indices experienced statistically significant urbanization effects. The urbanization effects in the ETI series generally occurred after the mid-1980s, and there were significant differences of the magnitudes of urbanization effects among different regions. The urbanization effect on the trends of annual temperature indices series in East Asia is generally the strongest, which is consistent with the rapidly urbanization process in the region over the past decades, but it is generally small in Europe during the recent decades.

A new approach to homogenize global sub-daily radiosonde temperature data from 1958 to 2018

This study develops an innovative approach to homogenize discontinuities in both mean and variance in global sub-daily radiosonde temperature data from 1958-2018. First, temperature natural variations and changes are estimated using reanalyses and removed from the radiosonde data to construct monthly and daily difference series. A Penalized Maximal F test and an improved Kolmogorov-Smirnov test are then applied to the monthly and daily difference series to detect spurious shifts in the mean and variance, respectively. About 60% (40%) of the changepoints appear in the mean (variance), and ∼56% of them are confirmed by available metadata. The changepoints display a country-dependent pattern likely due to changes in national radiosonde networks. Mean segment length is 7.2 (14.6) years for the mean (variance)-based detection. A mean (quantile)-matching method using up to 5-years of data from two adjacent mean (variance)-based segments is used to adjust the earlier segments relative to the latest segment. The homogenized series is obtained by adding the two homogenized difference series back to the subtracted reference series. The homogenized data exhibit more spatially coherent trends and temporally consistent variations than the raw data, and lack the spurious tropospheric cooling over North China and Mongolia seen in several reanalyses and raw datasets. The homogenized data clearly show a warming maximum around 300hPa over 30oS-30oN, consistent with model simulations, in contrast to the raw data. The results suggest that spurious changes are numerous and significant in the radiosonde records and our method can greatly improve their homogeneity.

Exergy analysis of large temperature difference series air conditioners in subway stations

In view of the large difference in the heat and humidity ratio of each air-conditioning zone in the subway, the unified cooling and dehumidification method is adopted, which changes the traditional connection mode of air-conditioning terminal in parallel. A cooling system of air-conditioning terminal surface cooler in series, i.e. large temperature difference series cooling system, is applied to the subway station. The large temperature difference series cooling system is divided into three subsystems: cooling water system, chilled water system and end refrigeration system. The second law of thermodynamics, namely the law of exergy equilibrium and thermoeconomics, is used to analyze the feasibility and economy of the large temperature difference series system and its subsystems. After comparing energy consumption and economy with the conventional air conditioning system, it was found that the exergy efficiency of the chilled water system using the large temperature difference series cooling system was reduced. However, the exergy efficiency of the end refrigeration system in the subway equipment area has been significantly improved, saving electricity costs, and the investment can be recovered in 3.7 years, and the exergy cost has dropped significantly. The use of a large temperature difference series cooling system in a subway station can achieve the effect of energy saving and cost reduction.

Mengungkap Pemahaman Konsep Listrik Dinamis di Sekolah Berbasis Kemaritiman

This study aims to describe the understanding of students' concepts on dynamic electric metrics in maritime-based schools in the city of Tegal. The study was conducted through a four-stage diagnostic test. The concept of dynamic electricity includes: Electric current strength, potential difference, series-parallel circuit, electric power, and Kirchoff's 1 law. The study was conducted at Tegal Nahdlatul Ulama High School as a sample of maritime-based schools in Tegal in the 2018/2019 school year. The sample used in the study was 29 students of class XII IPA Nahdlatul Ulama High School in Tegal city. The stages of research include (1) Reviewing references and journals related to understanding concept research; (2) Reviewing the syllabus to obtain misconceptions in the material of dynamic electric chapter physics; (3) Designing a question instrument in the form of a four tier test that can diagnose student misconceptions; (5) Validation by experts, namely with lecturers; (6) Test instruments to determine validity, reliability, degree of difficulty and differentiation of questions; (7) Test of student misconceptions carried out to students of class XII IPA at Nahdlatul Ulama High School. The results of data analysis obtained a description of students' understanding which could be categorized as understanding concepts, misconceptions, not understanding concepts and errors.

Solar activity cycle of ∼200 yr from mediaeval Korean records and reconstructions of cosmogenic radionuclides

ABSTRACT We have investigated Korean records of naked-eye observations of sunspots and we have found evidence that implies a periodicity of about 200 yr. Adding Chinese records, we show that these historical naked-eye observations of sunspots have a similar periodicity. Recently, some authors have shown that there are no intrinsic periodicities except for the 11-yr cycle. We adopt a new approach called a samplogram to test the sampling stability of cycles in terms of power spectra and difference series. We show that the Suess/de Vries cycle of about 207 yr is a deterministic cycle of stochastic solar activity. Also, we show that occurrences of grand minima are not necessarily expected with the Suess/de Vries cycle and it is possible for double or multiple grand maxima to appear without a grand minimum within them.

Asymmetric multiscale multifractal analysis of wind speed signals

We develop a new method called asymmetric multiscale multifractal analysis (A-MMA) to explore the multifractality and asymmetric autocorrelations of the signals with a variable scale range. Three numerical experiments are provided to demonstrate the effectiveness of our approach. Then, the proposed method is applied to investigate multifractality and asymmetric autocorrelations of difference sequences between wind speed fluctuations with uptrends or downtrends. The results show that these sequences appear to be far more complex and contain abundant fractal dynamics information. Through analyzing the Hurst surfaces of nine difference sequences, we found that all series exhibit multifractal properties and multiscale structures. Meanwhile, the asymmetric autocorrelations are observed in all variable scale ranges and the asymmetry results are of good consistency within a certain spatial range. The sources of multifractality and asymmetry in nine difference series are further discussed using the corresponding shuffled series and surrogate series. We conclude that the multifractality of these series is due to both long-range autocorrelation and broad probability density function, but the major source of multifractality is long-range autocorrelation, and the source of asymmetry is affected by the spatial distance.

Study on an Algorithm for SAR Raw Data Compression

t is difficult to directly compress the raw data of synthetic aperture radar for its low relativity. In this paper, a new algorithm is put forward. Firstly range focusing is imposed to SAR raw data, which makes it have comparative high relativity, secondly a linear prediction is performed along the azimuth, lastly block adaptive quantization is used to the prediction difference series. The experiments manifest that with same bit rate, SQNR and SDNR of the algorithm proposed in this paper surpass that of BAQ algorithm. The calculation in this paper is far less than that of compression method after range focusing advised in corresponding reference. The algorithm proposed in this paper has a certain practical value.