Morlet Wavelet Analysis Research Articles

The Spatiotemporal Dynamics of Temperature Variability Across Mts. Qinling: A Comparative Study from 1971 to 2022

Analyzing the spatiotemporal patterns of atmospheric temperature in sensitive areas is critically important for understanding the broader implications of global climate change, which remains a prominent topic in geosciences. It also plays a crucial role in advancing sustainable development. This study utilized daily minimum, maximum, and mean temperature data from twelve meteorological stations across the South and North Mts. Qinling (Qinling Mountains). Employing trend analysis, the Mann–Kendall mutation test, and Morlet wavelet analysis, we explored the predominant temperature trends and characteristics from 1971 to 2022. Our findings revealed consistent inter-annual warming trends in both regions, with more rapid temperature increases in the North compared to the South. Notably, significant shifts occurred in 2003 for both mean and minimum temperatures in the North, while the maximum and minimum temperature values were recorded in the 2010s and 1980s, respectively. Both regions exhibited a primary temperature fluctuation cycle of 28 years. Seasonally, the strongest warming effects appeared in spring, with the weakest in autumn, and moderate effects in winter and summer, indicating that spring contributes most significantly to regional warming. Monthly analysis showed positive temperature trends across all months, with higher rates in the North. The weakening temperature boundary effect of the Mts. Qinling suggested a weakening North–South division, particularly highlighted by the northward shift of the 1 °C isotherm curve for the coldest month, moving away from the previously observed 0 °C isotherm. This northward shift highlights the differential warming rates between the northern and southern regions. Overall, the analysis confirms a robust warming trend, with notable fluctuations in January’s temperatures since 1998, suggesting the Mts. Qinling’s emerging role as a climatic divider in the Chinese Mainland. This introduces new challenges for regional ecosystems, agricultural production, and water resource management, highlighting the pressing need to advance regional sustainable development in the face of climate change.

Spatiotemporal Variation Patterns of Drought in Liaoning Province, China, Based on Copula Theory

Liaoning Province, a crucial agricultural region in Northeast China, has endured frequent drought disasters in recent years, significantly affecting both agricultural production and the ecological environment. Conducting drought research is of paramount importance for formulating scientific drought monitoring and prevention strategies, ensuring agricultural production and ecological safety. This study developed a Comprehensive Joint Drought Index (CJDI) using the empirical Copula function to systematically analyze drought events in Liaoning Province from 1981 to 2020. Through the application of MK trend tests, Morlet wavelet analysis, and run theory, the spatiotemporal variation patterns and recurrence characteristics of drought in Liaoning Province were thoroughly investigated. The results show that, compared to the three classic drought indices, Standardized Precipitation Index (SPI), Evaporative Demand Drought Index (EDDI), and Standardized Precipitation Evapotranspiration Index (SPEI), CJDI has the highest accuracy in monitoring actual drought events. From 1981 to 2020, drought intensity in all regions of Liaoning Province (east, west, south, and north) exhibited an upward trend, with the western region experiencing the most significant increase, as evidenced by an MK test Z-value of −4.53. Drought events in Liaoning Province show clear seasonality, with the most significant periodic fluctuations in spring (main cycles of 5–20 years, longer cycles of 40–57 years), while the frequency and variability of drought events in autumn and winter are lower. Mild droughts frequently occur in Liaoning Province, with joint and co-occurrence recurrence periods ranging from 1.0 to 1.8 years. Moderate droughts have shorter joint recurrence periods in the eastern region (1.2–1.4 years) and longer in the western and southern regions (1.4–2.2 years), with the longest co-occurrence recurrence period in the southern region (3.0–4.0 years). Severe and extreme droughts are less frequent in Liaoning Province. This study provides a scientific foundation for drought monitoring and prevention in Liaoning Province and serves as a valuable reference for developing agricultural production strategies to adapt to climate change.

Study on long term troposphere lower stratosphere temperature (TLST) trend in tropical and subtropical northern hemisphere using ground based and COSMIC satellite data

The troposphere, the lowest and closest layer of the atmosphere, is where all meteorological events take place. The tropospheric — lower stratospheric (TLS) temperature trend is determined using linear regression and is essential to comprehending the consequences of climate change in the future. In this article, we explored the long-term temperature variabilities and trends of TLS (1–25 km) temperature and its responses by natural drivers such as El Nino southern oscillation (ENSO), solar flux (SF), quasi-biannual oscillation (QBO), Indian ocean dipole (IOD), and aerosol indexes (AI) using monthly averaged zonal mean COSMIC satellite and ground — based Radiosonde (RS) observations for the period of 2006 – 2020 over tropical station Addis (90 N, 38.80 E) and subtropical station Cairo (30.030 N, 31.230 E). The tropopause is located at the tropical station Addis at 17 km with a temperature of 190–194 K, and for the subtropical station Cairo, it is located at 15 km with a temperature of 201 K, which supports the decrement of tropopause height from the tropics to the subtropics with a slight increase in temperature. The two main oscillations in the TLS region can be seen by using the wavelet analysis technique: the semiannual oscillation (SAO) and the annual oscillation (AO), with the AO being especially strong in the lower troposphere. Furthermore, Morlet wavelet analysis on cold-point tropopause temperature CPTt displays AO and cold point tropopause height CPTh reveals a QBO-like signal. The TLS region has positive peaks at heights of 7, 21, 22, 13, and 4 km for the Addis station, and at 15, 19, 25, 15, and 16 km for the Cairo station in response to natural drivers such as ENSO, SF, QBO, IOD, and aerosol. Lag analyses demonstrate a one-month delay for all natural forcings, except for oceanic indices and SSF, up to three months below the tropopause (below 15 km). There is a noticeable 3 to 4 months lag in every oscillation above the tropopause. A warming trend in the tropospheric region and a cooling trend in the UTLS regions are revealed by MLR trend analysis. In contrast to the subtropical Cairo station, which has the highest warming rate of 0.38 K/decade at 2 km and the maximum cooling rate of −0.2 K/decade at 10 km, the tropical Addis station has the highest cooling rate of −0.38 K/decade at 12 km and the highest warming rate of 0.28 K/decade at 3 km. Our trend findings are consistent with previous research.

Differentiating Periodic Drivers of Air Quality Changes: A Two‐Step Decomposition Approach Integrating Machine Learning and Wavelet Analysis

AbstractAir quality time series exhibit significant periodic patterns, which are linked to a diverse array of emission sources and atmospheric processes. To discern and distinguish these periodic drivers, we have devised a two‐step decomposition approach that integrates a machine learning‐based model for weather normalization with Morlet wavelet analysis. This approach was applied to a 7‐year data set encompassing six regulated air pollutants across eight Chinese cities. Our analysis revealed distinct periodicities in weather‐normalized concentrations of primary air pollutants: a dominant annual cycle with periodicity around 365 days, which accounts for over 50% of the variance on average and is primarily driven by recurrent winter heating activities; daily cycles characterized by regular diurnal patterns attributable to combustion sources such as traffic; and periodicities exceeding 512 days that associated with long‐term regulatory policies targeting SO2. Particularly notable was the significant drop in the strength of the annual cycle in northern cities following the implementation of China's clean heating policies in 2017/2018, affirming the success of these initiatives. Additionally, diurnal dispersion and photochemistry, large‐scale atmospheric circulation, and synoptical weather patterns are likely responsible for the observed daily cycle (accounting for over 40% of the variance), annual periodicities, and intra‐monthly variations in the meteorologically driven concentrations, respectively. The varying power of these periodic drivers across time and locations implies the heterogeneity of emission rates and region‐specific climates. This work highlights the efficacy of this decomposition approach in air quality research, warranting attention for its potential value for enhancing our understanding of air pollution dynamics.

Failure analysis of gear using continuous wavelet transform applied in the context of wind turbines

One of the main reasons for failure in the wind turbine is the wear between the gear teeth during the power conversion and changes in the rotation speed, which is also generally associated with changes in the lubrication regimes. In this sense, vibration and signal analysis are frequently used in predictive maintenance as they usually permit the identification of deviations in the proper functioning of the equipment. Thus, this work aims to apply the continuous wavelet transform (CWT) to correlate gear wear and vibration signals, using visual and straightforward analysis. An experimental setup of a gear system was used to analyze vibration signals from different tooth gear damages. Gears with different levels and modes of damage were used in order to evaluate the sensitivity of vibration signals to them. The features from vibration signals were extracted by Morlet wavelet analysis. Results demonstrate that the proposed method accurately detected the early failure by visualization in frequency–time maps.

Periodic Behavior of Selected Solar, Geomagnetic and Cosmic Activity Indices during Solar Cycle 24

In this study, we performed periodicity analyses of selected daily solar (flare index, coronal index, number of coronal mass ejections), geomagnetic (planetary equivalent range index, disturbance storm time index, interplanetary magnetic field) and cosmic ray indices for the last Solar Cycle 24 (from December 2008 to December 2019). To study the periodic variation of the above-listed datasets, the following analysis methods were applied; multi-taper method, Morlet wavelet, cross-wavelet transform and wavelet coherence analysis. The outcome of our analyses revealed the following. (i) The 25–33 days solar rotation periodicities exist in all datasets without any exception in the MTM power spectra. (ii) Except for the solar rotation periodicity, all periods show data preference, and they appear around the investigated cycle’s maximum phase. (iii) When comparing the phase relations between periodicities in the used datasets, they exhibit a gradual transition from small to large periods. For short-term periodicities, there are no phase relations but a mixed phase, whereas for high periodicities, there are complete phase/antiphase transitions. (iv) All identified flare index periodicities are common to all other datasets examined in this investigation.

Evaluation of Morlet Wavelet Analysis for Artifact Detection in Low-Frequency Commercial Near-Infrared Spectroscopy Systems.

Regional cerebral oxygen saturation (rSO2), a method of cerebral tissue oxygenation measurement, is recorded using non-invasive near-infrared Spectroscopy (NIRS) devices. A major limitation is that recorded signals often contain artifacts. Manually removing these artifacts is both resource and time consuming. The objective was to evaluate the applicability of using wavelet analysis as an automated method for simple signal loss artifact clearance of rSO2 signals obtained from commercially available devices. A retrospective observational study using existing populations (healthy control (HC), elective spinal surgery patients (SP), and traumatic brain injury patients (TBI)) was conducted. Arterial blood pressure (ABP) and rSO2 data were collected in all patients. Wavelet analysis was determined to be successful in removing simple signal loss artifacts using wavelet coefficients and coherence to detect signal loss artifacts in rSO2 signals. The removal success rates in HC, SP, and TBI populations were 100%, 99.8%, and 99.7%, respectively (though it had limited precision in determining the exact point in time). Thus, wavelet analysis may prove to be useful in a layered approach NIRS signal artifact tool utilizing higher-frequency data; however, future work is needed.

Transformative Trends in Runoff and Sediment Dynamics and Their Influential Drivers in the Wuding River Basin of the Yellow River: A Comprehensive Analysis from 1960 to 2020

The correlation between runoff and sediment challenges ecological preservation and sustainable development in the Yellow River Basin. An understanding of the key factors influencing variations in runoff and sediment transport in crucial river basins is essential for effective soil erosion management within the context of ecological and economic development. The Mann–Kendall test, Pettitt test, and Morlet wavelet analysis were employed in the Wuding River Basin to analyze the trends in runoff and sediment changes from 1960 to 2020. We explored the double cumulative curve method to assess the contribution rates of precipitation and human activities to the variability of runoff and sediment transport. We explored the primary factors driving the changes in runoff and sediment transport through random forest regression analysis. (1) From 1960 to 2020, annual precipitation in the Wuding River Basin increased minimally, while annual runoff and sediment transport decreased strongly with abrupt changes. Abrupt changes in annual runoff and sediment transport occurred in 1971 and 1979, respectively. (2) The relationship between runoff and sediment transport changed in approximately 1972 and 2000. The distribution of monthly runoff became more uniform during Periods II (1973–2001) and III (2002–2020) compared to that during the baseline period (1960–1972, Period I), while sediment transport became increasingly concentrated in the flood season. (3) During Period II, the contribution rates of climate and human activities to runoff and sediment transport were 11.94% and −14.5%, respectively, compared to the baseline period. During Period III, the contribution rates of climate and human activities to runoff and sediment transport were −11.9% and −17.7%, respectively. Human activities substantially reduced runoff and sediment, with greater impacts on sediment reduction. Climate weakly influenced basin sediment transport variations. (4) The normalized difference vegetation index (NDVI) and grassland area extent had the greatest impact on runoff, while the NDVI and forest area extent affected sediment transport.

Multi-Temporal Variabilities of Extreme Precipitation over Central Asia and Associated Planetary-Scale Climate Modes

Arid- and semi-arid Central Asia is particularly sensitive to climate change. The changes in extreme precipitation in Central Asia stemming from climate warming are the subject of intense debate within the scientific community. This study employed a Morlet wavelet analysis to examine the annual occurrence number of extreme precipitation in Central Asia from May to September during the period of 1951–2005. Their modulating planetary-scale climate modes were identified by using linear regression analysis. Two major scales of the temporal variability were derived: 2–3.9 years and 4–6 years. The dominant variability was a 2–3.9-year scale and was associated with the negative phase of the Polar/Eurasia (POL) pattern. The 4–6-year scale provided a secondary contribution and was closely linked to the negative phase of the North Atlantic Oscillation (NAO). These planetary climate modes acted as precursors of extreme precipitation over Central Asia. The negative phase of POL directly contributed to a negative height anomaly over Central Asia, which was intimately related to extreme precipitation. In contrast, the negative NAO phase possibly manifested as a Rossby wave source, which was subsequently exported to Central Asia through a negative–positive–negative Rossby wave train.

A Study of Drought and Flood Cycles in Xinyang, China, Using the Wavelet Transform and M-K Test

Accurately identifying and predicting droughts can provide local managers with a basis for decision-making. The Xinyang region is prone to droughts and floods, which have a large impact on local agriculture and socio-economics. This paper employs precipitation data from the Xinyang region to provide a scientific basis for drought and flood control measures in this region. The data are first treated with standardized precipitation indices (SPIs) on three-month, six-month, and nine-month time scales. Subsequently, a Morlet wavelet analysis is performed for each of the three time scales analyzed for the SPI. The results show multiple time scales of drought and flood disasters in the Xinyang region. The cycles of drought and flood disasters in the Xinyang region show different fluctuations on different SPI scales. The SPI time series reflect a strong fluctuation period of 17a for drought and flood disasters in the Xinyang region. An analysis of the variance of the wavelet coefficients showed that the first main cycle of drought and flood disasters in the Xinyang region is 7a, and the second and third sub-cycles are 4a and 13a, respectively. We conclude that floods are more frequent than droughts in Xinyang and are more likely to occur from 2017 to 2021, with a subsequent shift to droughts. Local managers should put drought prevention measures in place to deal with droughts after 2021.

Spatiotemporal Characteristics of Drought in Northwest China Based on SPEI Analysis

Drought has a direct impact on regional agricultural production, ecological environment, and economic development. The northwest region of China is an important agricultural production area, but it is also one of the most serious areas of water shortage due to drought and little rain. It is of great significance to make full use of agricultural resources to clarify the temporal and spatial distribution characteristics of the drought regime in Northwest China. Based on the Standardized Precipitation Evapotranspiration Index (SPEI), this paper used the methods of Mann–Kendall non-parameter trend, mutation test, and Morlet wavelet analysis to explore the drought characteristics in Northwest China from 1961 to 2017. The results showed that the spatial distribution of SPEI on annual and seasonal scales differed slightly in different regions, but from northwest to southeast, the distribution was generally wetter to drier. The drought intensity (Sij) had a step-like distribution with a range of 1.14–1.98. Based on Sij analysis, the frequency of drought in Northwest China was moderate, followed by extreme drought, severe drought, and light drought. The inter-annual drought station proportion (Pj) ranged from 7.4% to 84.1%. A total of 25, 18, 7, and 5 years of pan-regional drought, regional drought, partial region drought, and local drought occurred, respectively, based on Pj analysis. Moreover, from the whole study period, the regional drought changes tended to cause humidification to different degrees. The results of Morlet wavelet analysis showed that there were multiple time scales of 33–52, 11–19, and 4–7 years of SPEI in the entire time domain, and dry and wet trends occurred. The results of the present research can provide a reference for the efficient utilization of water resources, drought monitoring and early warning, drought prevention, and drought relief in Northwest China.

Experimental Study of the Transient Behavior of a Wind Turbine Wake Following Yaw Actuation

Wind tunnel experiments were performed to investigate the response of a wind turbine model immersed in a replicated atmospheric boundary layer to dynamic changes in the yaw angle. Both the flow field in the wake and the operating properties of the turbine, namely its thrust force, torque, and angular velocity, were monitored during repeated yaw maneuvers for a variety of yaw angles. It was observed that the characteristic time scale of the transient experienced by the turbine scalar quantities was one order of magnitude larger than that of the yaw actuation and depended primarily on the inertia of the rotor and the generator. Furthermore, a Morlet wavelet analysis of the thrust signal showed a strong peak at the rotation frequency of the turbine, with the transient emergence of high activity at a lower frequency during the yaw maneuver. The insights provided by the proper orthogonal decomposition analysis performed on the wake velocity data enabled the development of a simple reduced-order model for the transient in the flow field based on the stationary states before and after the yaw maneuver. This model was then further improved to require only the final state, extending its applicability to any arbitrary wind farm as a dynamical surrogate of the farm behavior.

Synthetic Light Curve Design for Pulsating Binary Stars to Compare the Efficiency in the Detection of Periodicities

B supergiant stars pulsate in regular and quasi-regular oscillations resulting in intricate light variations that might conceal their binary nature. To discuss possible observational bias in a light curve, we performed a simulation design of a binary star affected by sinusoidal functions emulating pulsation phenomena. The Period04 tool and the WaveletComp package of R were used for this purpose. Thirty-two models were analysed based on a combination of two values on each of the k = 6 variables, such as multiple pulsations, the amplitude of the pulsation, the pulsation frequency, the beating phenomenon, the light-time effect, and regular or quasi-regular periods. These synthetic models, unlike others, consider an ARMA (1, 1) statistical noise, irregular sampling, and a gap of about 4 days. Comparing Morlet wavelet with Fourier methods, we observed that the orbital period and its harmonics were well detected in most cases. Although the Fourier method provided more accurate period detection, the wavelet analysis found it more times. Periods seen with the wavelet method have a shift due to the slightly irregular time scale used. The pulsation period hitting rate depends on the wave amplitude and frequency with respect to eclipse depth and orbital period. None of the methods was able to distinguish accurate periods leading to a beating phenomenon when they were longer than the orbital period, resulting, in both cases, in an intermediate value. When the beating period was shorter, the Fourier analysis found it in all cases except for unsolved quasi-regular periods. Overall, the Morlet wavelet analysis performance was lower than the Fourier analysis. Considering the strengths and disadvantages found in these methods, we recommend using at least two diagnosis tools for a detailed time series data analysis to obtain confident results. Moreover, a fine-tuning of trial periods by applying phase diagrams would be helpful for recovering accurate values. The combined analysis could reduce observational bias in searching binaries using photometric techniques.

Spatiotemporal Variation Characteristics of Reference Evapotranspiration and Relative Moisture Index in Heilongjiang Investigated through Remote Sensing Tools

Reference evapotranspiration (ET0) is one of the significant parameters in agricultural irrigation, especially in Heilongjiang, a big agricultural province in China. In this research, the spatiotemporal variation characteristics of evapotranspiration (ET), relative moisture index (MI) and influencing factors of ET0 in Heilongjiang, which was divided into six ecology districts according to landforms, were analyzed with meteorological data observed over 40 years from 1980 and MOD16 products from 2000 to 2017 using Morlet wavelet analysis and partial correlation analysis. The results indicated that (1) the spatial distribution of ET and PET in Heilongjiang in humid, normal and arid years showed a distribution of being higher in the southwest and lower in the northwest, and higher in the south and lower in the north. The PET was higher than ET from 2002 to 2017, and the difference was small, indicating that the overall moisture in Heilongjiang was sufficient in these years. (2) In the last 40 years, the ET0 increased while the annual MI decreased. The annual minimum of MI in the six regions of Heilongjiang was −0.25, showing that all six regions were drought free. (3) The importance of the meteorological factors affecting ET0 was ranked as average relative humidity > average wind speed > sunshine duration. This research provides scientific guidance for the study of using remote sensing to reverse ET.

Variability of solar periodicities in southern African baobab δ 13 C data during the Wolf, Spörer, Maunder and Dalton minima

Variability of several solar periodicities in southern African Baobab δ13C data during the Wolf (1280–1350 AD), Spörer (1415–1550 AD), Maunder (1645–1715 AD) and Dalton (1790–1830 AD) solar minima have been investigated using Morlet wavelet and Lomb-Scargle spectral analysis methods. Annual stable carbon isotope (δ13C) data obtained from the Pafuri Baobab trees from north-eastern Southern Africa for the period 1200 AD – 1900 AD were used in this investigation. Results obtained showed for the first time that considerable variation in the power of the 11-year Schwabe and the 22-year Hale cycles exist in the δ13C proxy summer rainfall data for Southern Africa during the respective solar sunspot minima intervals. The findings in this investigation provides clear evidence of the influence of solar activity on the climate of the Southern Hemisphere. In contrast, most previous solar-climate interaction results were based on Northern Hemisphere data sets.

Spatial-Temporal Characteristics of Spring Maize Drought in Songnen Plain, Northeast China

With the intensification of global warming, food production will face serious drought risk. In view of the insufficient applicability of the existing crop drought index, a standardized crop water deficit index (SCWDI) was constructed based on the construction idea of the standardized precipitation evapotranspiration index (SPEI) and the crop water deficit index (CWDI) in this study. On this basis, the spatial and temporal characteristics of spring maize drought in Songnen Plain were explored by the slope trend analysis and Morlet wavelet analysis methods. The results show the following: (1) Compared with the existing drought index, the SCWDI shows obvious advantages in drought monitoring of spring maize. (2) In the whole growth stage of spring maize, the change trend of SCWDI was small in the temporal series (−0.012/10a). Spatially, the drought trend of spring maize was mainly decreasing (−0.14~0/10a). The drought frequency of spring maize in each growth stage was mainly light drought in most regions. (3) The three main drought cycles of spring maize in Songnen Plain were 29 years, 10 years, and 4 years. In the next few years, the drought of spring maize in Songnen Plain was controlled by the first main cycle, and the drought years may increase, which should be prevented. The research was expected to provide technical support for crop drought monitoring and agricultural disaster prevention.

The profile and fluttering characteristics of a codend with different mesh sizes and catch by fast Fourier transform and Morlet wavelet methods

The codend is the end and an essential part of the trawl, which plays a vital role in the selectivity and the storage of fish catches. Thus, to improve the trawl selectivity and control the probability of the fish escaping, it is essential to understand its hydrodynamic performance, fluttering motions, and spatial form of the codend structure. This study investigates the effects of the mesh size and simulated catch on hydrodynamic characteristics, net cross-section, and fluttering motions of the codend in the flume tank. Thus, three codends models were designed using polyethylene material with three different mesh sizes (60 mm, 80 mm, and 100 mm). Fourier analysis was performed via the Morlet wavelet analysis and the fast Fourier transform (FFT) method to observe the content of the wavelet coefficient variance and amplitude of the codend fluttering motions and time evolution of the drag forces. The results showed that at the empty stage, the decrease in mesh size led to an increase in drag force by 6.6%− 25.1%, an increase of the codend length by 2.6%− 4.3%, and a decrease in cross-sectional area by 14.9%− 51.7% of the codend. In addition, the time evolution was oscillatory quasi-periodic and related to the low-frequency activity. The codend drag oscillation frequency was mainly 0.30–0.45 Hz and decreased with the mesh size, and the amplitude and wavelet coefficient of the drag force increased with decreasing mesh size. For the codend with simulated catch, the shape of each codend was closed at the front of the mesh and bulging atthe rear contour, with the middle part of each codend being the most closed, and the cross-sectional area was about 15.1% of the empty codend (X = 104 cm). The codend position oscillates frequency was 0.30–0.45 Hz in X and Z directions. The drag oscillation frequency was mainly 0.30–0.45 Hz and synchronized with the position motion. The dominant frequencies of these codend motions and the associated drag showed low-frequency activities, with a small wavelet spectrum shifting from small-scale to large-scale motions. In addition, the codend with a greater mesh size showed a more stable behavior with a lower frequency and oscillatory motions than the codend with a small mesh size led to a decrease in drag on this codend. In addition, we recommend that the FFT can be used to obtain the amplitude and frequency directly for codend steady oscillation.

Annual and semi-annual variations of electron density in the topside ionosphere observed by CSES

In this paper, based on the observations from Langmuir probe (LAP) onboard the China Seismo-Electromagnetic Satellite (CSES), the annual/semi-annual variations of electron density (Ne) measured at 02:00 and 14:00 local time (LT) in the topside ionosphere have been analyzed. Results indicated that the Ne exhibits an amplification-linear-saturation with the increase of P10.7 in the daytime, while roughly linear in the nighttime. The annual/semi-annual variations of CSES Ne at around 500 km are found by morphological analysis and Morlet wavelet analysis, with dominant period of 187 days and 374 days. The annual components of longitude-averaged Ne dominate at most magnetic latitudes (Mlats) with maxima around the June solstices in the northern hemisphere and the December solstice in the southern hemisphere (except for the northern hemisphere in the nighttime), while the semi-annual variation dominates at the magnetic equator and low magnetic latitudes with two maxima at equinoxes. The Ne dominant period is characterized by a transition from semi-annual variation at the equator and low magnetic latitudes regions to annual variation at the middle magnetic latitudes region. The annual/semi-annual variations of Ne observed by CSES satellite show a consistent performance with previous studies, and have complemented the ionospheric characteristics at 500 km altitude, especially in the nighttime.

ИЗМЕНЕНИЯ ИСПАРЕНИЯ ПО ДАННЫМ ИНСТРУМЕНТАЛЬНЫХ НАБЛЮДЕНИЙ И ЕГО РЕАКЦИЯ НА ИЗМЕНЕНИЕ КЛИМАТА В ПРОВИНЦИИ ХЭЙЛУНЦЗЯН

In this study, instrument-measured evaporation and conventional meteorological observations from 80 stations in Heilongjiang Province from 1961 to 2020 were collected. Using these data, methods such as linear trend estimation, cumulative anomaly, multiple linear regression, and Morlet wavelet analysis were employed to analyze the changes of instrument-measured evaporation annually and seasonally in Heilongjiang Province. Additionally, we analyzed its response to climate change. The results showed that from 1961 to 2020, annual pan evaporation in Heilongjiang Province showed a significant downward trend, decreasing at 10.5 mm per decade. Evaporation decreased significantly in spring, while the magnitude of this decrease in summer and autumn was relatively small, and evaporation increased significantly in winter. In the periodic change, annual and seasonal evaporation have significant periods on short time scales. Among them, PE y and PE Su mainly have a short period of 3-4 years, PE Sp has short periods of about 3 years and 6 years, PE A mainly has short periods of 2 years and 3 years, and PE W mainly has short periods of about 4 years. The geographical correlation of evaporation was significant, with evaporation decreasing as latitude, longitude and altitude increased. Additionally, we found that changes in annual and seasonal pan evaporation were positively correlated to changes in average temperature, hours of sunshine, and wind speed, and negatively correlated to changes relative humidity. Our analysis indicates that a significant decrease in wind speed and hours of sunshine is the dominant factor leading to the decrease in evaporation throughout the year as well as in spring, summer, and autumn, while higher temperatures and lower relative humidity may lead to a significant increase in evaporation in winter.

The role of solar energy usage in environmental sustainability: Fresh evidence through time-frequency analyses

The most important challenge for both developed and developing countries is to ensure sustainability while struggling with environmental degradation. CO2 emissions as a proxy for environmental degradation can be considered an obstacle to sustainability. There exist several significant works in the literature on the effects of solar energy use on environmental degradation/sustainability. In this study, the effects of the use of solar energy within different time and frequency dimensions on CO2 emissions were examined with the methodology of the continuous wavelet transform. The paper investigated the association between solar energy consumption and total energy-related CO2 emissions in the USA through Morlet wavelet analysis, which is one of the most advanced time-frequency analysis methods for the period 1990:1–2022:6. In the wavelet coherency computations, geothermal energy consumption, hydroelectric energy consumption, industrial production, and manufacturing industry production variables were also included as control variables. Empirical findings demonstrate that solar energy consumption can have reducing effects on CO2 emissions at lower frequencies (longer-term cycles) and sub-time periods (2014:1–2022:1) in the USA. The findings can guide the energy and environmental policies of developed and developing countries that aim to struggle with global warming and/or climate change through the increase in solar energy usage.