Cross-spectral Analysis Research Articles

Unveiling the impact of oil price shocks on global sukuk markets: a focus on quantile coherence and time-frequency connectedness

ABSTRACT This study examines the relationship between oil price shocks and Islamic bonds in 15 global markets. We focus on how they are connected in terms of time and frequency, specifically in quantiles. Through a quantile coherency approach, we discover that oil price shocks affect sukuk indices differently depending on the type of shock. When we increase the frequency of analysis from once a year to once a month, we observe a significant increase in coherence values of oil risk shocks across the majority of sukuk indices of oil exporting nations in both the lower and middle quantiles. Furthermore, based on quantile cross-spectral coherence analysis, we notice that the extreme quantile dependence between oil price shocks and the majority of the oil exporting nations’ sukuk indices remains stable over a short-time horizon. Our research indicates that demand shocks have a significant impact on the correlation between sukuk markets during uncertain periods, such as COVID-19 and the Russian-Ukraine war. Our findings provide a credible understanding of the behaviour of sukuk indices in response to fluctuations in oil prices, which is important for investment portfolio managers and policy decision-makers.

Acute effects of bolus water intake on post-exercise orthostatic hypotension and cardiovascular hemodynamics.

Water intake is known to be effective in preventing orthostatic hypotension (OH). However, it is unknown whether water intake would be effective in acutely preventing exercise-induced OH. Fourteen adults (men/women: 7/7, age: 20 ± 8years) were recruited. Each subject underwent two protocols with and without 500ml water intake using a randomized crossover design (Water vs. Control). Participants underwent 30min of cycle ergometry at the 60-70% predicted VO2 max. OH and hemodynamics were assessed before and after exercise, and immediately (Water 1) and 20min (Water 2) after the water intake. OH was evaluated with a 1-min standing test as the criteria for systolic blood pressure (SBP) < 90mmHg. A cross-spectral analysis for RR and SBP variability was used to evaluate the cardiac autonomic activity and baroreflex sensitivity. In both protocols, the incidence of OH increased after the exercise. The incidence of OH was lower in Water than in Control at Water 1 (OR: 0.093, 95% CI: 0.015-0.591). Heart rate was lower and SBP was higher in Water than in Control at Water 1 and 2 (P < 0.05). High-frequency power of RR variability and transfer function gains in Water were normalized and higher than in Control at Water 1 and 2 (P < 0.05). The ratio of low- to high-frequency power of RR variability in Water was normalized and lower in Water than in Control at Water 1 (P < 0.05). Our findings indicate that water intake may prevent acute exercise-induced OH, accompanied by normalized cardiac autonomic activity and baroreflex sensitivity.

Models of the Impact of Socio-Economic Shocks on Higher Education Development

This article is devoted to the analysis of the impact of socio-economic shocks on the dynamics of higher education development. It is substantiated that, on the one hand, higher education influences the development of society and the economy, on the other hand, the development trends of a country provide both opportunities and limitations for its development. An algorithmic model for studying the impact of social and economic shocks on the development of the higher education system (HES) has been developed. To diagnose the relationship between higher education and the socio-economic development of Ukraine and Slovakia, the following indicators were used: GDP per capita, the Human Development Index, school enrollment, tertiary, and net migration. The presence of nonlinear trends in the change in indicators has been shown and portraits of the socio-economic development of the countries have been constructed. To assess the impact of socio-economic shocks on the HES, the time-series decomposition method and cross-spectral analysis were used. The time-series decomposition allowed us to identify cyclical components of indicators, based on applying cross-spectral analysis, and the most significant local harmonics and the lag of their influence on the occurrence of shocks in the HES were determined. The use of the developed models allows us to predict periods of shock points in the HES depending on shocks in the tendencies of GDP per capita and net migration.

Patients with amnestic mild cognitive impairment have higher cerebrovascular impedance than cognitively normal older adults.

Brain hypoperfusion is associated with cognitive impairment. Higher cerebrovascular impedance modulus (Z) may contribute to brain hypoperfusion. We tested hypotheses that patients with amnestic mild cognitive impairment (aMCI) (i.e., those who have a high risk of developing Alzheimer's disease) have higher Z than age-matched cognitively normal individuals, and that high Z is correlated with brain hypoperfusion. Fifty-eight patients with aMCI (67 ± 7 yr) and 25 cognitively normal subjects (CN, 65 ± 6 yr) underwent simultaneous measurements of carotid artery pressure (CAP, via applanation tonometry) and middle cerebral arterial blood velocity (CBV, via transcranial Doppler). Z was quantified using cross-spectral and transfer function analyses between dynamic changes in CBV and CAP. Patients with aMCI exhibited higher Z than NC (1.18 ± 0.34 vs. 1.01 ± 0.35 mmHg/cm/s, P = 0.044) in the frequency range from 0.78 to 4.29 Hz. The averaged Z in the frequency range (0.78-3.13 Hz) of high coherence (>0.9) was inversely correlated with total cerebral blood flow measured with 2-D Doppler ultrasonography normalized by the brain tissue mass (via structural MRI) across both patients with aMCI and NC (r = -0.311, P = 0.007), and in patients with aMCI alone (r = -0.306, P = 0.007). Our findings suggest that patients with aMCI have higher cerebrovascular impedance than cognitively normal older adults and that increased cerebrovascular impedance is associated with brain hypoperfusion.NEW & NOTEWORTHY This is the first study to compare cerebrovascular impedance between patients with amnestic mild cognitive impairment (aMCI) and age-matched cognitively normal individuals. Patients with aMCI had higher cerebrovascular impedance modulus than age-matched cognitively normal individuals, which was correlated with brain hypoperfusion. These results suggest the presence of cerebrovascular dysfunction in the dynamic regulation of cerebral blood flow in older adults who have high risks of Alzheimer's disease.

Computations of energetic nearshore waves: Are weakly dispersive phase-resolving models telling the same story?

Three phase-resolving weakly dispersive wave models are used for 2DH (2D depth-integrated) computations of large-scale wave-by-wave processes induced by highly energetic sea/swell (SS) forcing near Haleʻiwa on the North Shore of Oʻahu, Hawaiʻi. The computed model results are compared to observations obtained over a nearshore cross-reef transect and from the basin of a small boat harbor. The level of agreement between the model results and observations in complex coastal environments under highly energetic wave forcing, along with the qualitative consistency among the three models, makes these models good candidates for operational applications in nearshore environments exposed to energetic wave forcing conditions.Spectral analyses inside the harbor and over the reef indicate that all three models generally account for infragravity (IG) spatial modal structures that are consistent with observations and the theory of edge and leaky waves. Over the reef, auto- and cross-spectral analyses reveal that the dominant waveforms are qualitatively reproduced by all three models, as indicated through: (i) the growth of IG wave amplitudes from deeper water to the shallow reef sites; (ii) the agreement of power spectral density peaks at the nearshore locations; and (iii) the remarkable similarity of spatial coherence functions among the models and between the models and observations. The computations of swell entering the small boat harbor at Haleʻiwa demonstrate that the models can successfully reproduce the variability in the narrow IG frequency bands that are spatially dependent and often subject to resonant amplifications.

Unsteadiness in vacuum ejector and their sources

This study investigates unsteadiness in the secondary chambers of a vacuum ejector during its transient startup phase. Experiments reveal unsteadiness at various frequencies across different nozzle pressure ratios. These frequencies are categorized as symmetric (in-phase) or asymmetric (counter-phase) through cross-spectral phase analysis. Dynamic mode decomposition, using time-resolved schlieren images, elucidates the corresponding flow structures and acoustic fields. The mode shapes display alternating density gradients along both the longitudinal and lateral axes, which explain the oscillatory behavior of the jet. These oscillations arise from instabilities in the jet's shear layer and acoustic disturbances due to the jet being confined within a duct. Using empirical relations, spectrogram analysis, time-resolved schlieren imaging, and classical wave theory, the sources of unsteadiness in the secondary chamber are identified as jet screech, its harmonics, and modes due to duct acoustics (symmetric and asymmetric). Additionally, the screech feedback loop in the vacuum ejector is found to be distinct from that in open jets, and the effect of screech on duct-mode acoustics is also observed.

Use of groundwater level measurements to support hydrogeological studies in the Maputo aquifer, Mozambique

AbstractHigh-frequency dataloggers for groundwater level monitoring were used in combination with other tools to analyze tidal effects on groundwater levels (GWLs) in the Maputo aquifer, Mozambique. Power spectral analysis was used to ascertain the dominant periodic components in the tide and GWLs, and cross-spectral analysis was used to determine the lag time between them. Wavelet analysis was applied to investigate changes in periodic components over the measured period in the time-frequency domain. The estimated amplitudes and lag times were then used to estimate aquifer diffusivity and the water-table fluctuation (WTF) method was used to compute groundwater recharge. The results identified a 12.42 h dominant periodic component both in the tide and GWLs in the coastal area. However, GWLs lag behind the tide by 2–4 h, depending on the distance of the observation wells to the coastline. The wavelet analysis results showed no changes in the dominant periodic components over time. The estimated specific storage values for four piezometers were estimated to be 3.19 × 10–5, 5.04 × 10–5 and 1.02 × 10–4 1/m, respectively. Annual groundwater recharge for the young sand dune aquifer was estimated for one piezometer with a specific yield of 0.15–0.25 was within the range of 123–205, 185–309, 504–840 and 244–407 mm, for four hydrological years from 2018 to 2021. Estimated specific storage values and recharge rates are essential inputs to support the construction of transient groundwater models for the Maputo aquifer.

Sparse Tensor Decomposition of Multi-Sensory Data for Fault Localization in Rotating Machinery Health Monitoring

Multi-sensor monitoring is prevalent in modern structural health monitoring (SHM) practice. As the number of sensors and sampling requirements increase, a monitoring sensor network can generate substantial data which are high-volume and high-dimensional, especially for large structure and machinery. In condition-based monitoring (CBM) of rotating machines, e.g., gas turbine, rotor fault diagnosis serves a significant role in the system reliability, safety, and efficiency, which helps reduce potential damage to the on-rotor structures and avoid catastrophic failures. For multi-channel vibration measurement, classical rotor diagnosis approaches typically involve data fusion techniques based on cross spectral analysis for identifying spectral correlation, e.g., cross power spectral density, and/or matrix analysis tool for dimensionality reduction, e.g., principal component analysis. The operation on vectors or matrices may limit their effectiveness for higher-order array or tensor data. To circumvent this limitation, the third order vibrational spectral tensor is generated by representing the multi-channel acceleration spectra as the three-way array. Through nonnegative Tucker decomposition (NTD), the spectral tensor is decomposed into multiple principal factors: the spectral factor, segmental factor, channel-wise factor, and the dense tensor core. The correlations across the characteristic spectral contents and the sensor channels are revealed by the factorization, which enables the diagnosis of rotor fault and facilitates fault localization by identifying the dominant channels of the characteristic spectral factor. The method is validated on an experimental rotor testbed where the faulty channel with crack, rub, or misalignment fault, is effectively localized via 4-channel vibration measurements, which presents a promising approach for multi-sensor fusion and fault diagnosis in rotating machinery health monitoring.

Tail connectedness of DeFi and CeFi with accessible banking pillars: Unveiling novel insights through wavelet and quantile cross-spectral coherence analyses

This study evaluates the interplay between decentralized finance (DeFi) and centralized finance (CeFi) within the realm of inclusive banking by examining their foundational components, namely, alternative finance industry, distributed ledger platforms, and future payment technologies. The alternative finance industry leverages innovative technologies, such as direct lending, crowdfunding, automated wealth management, on-demand insurance, and digital currencies. This feature aligns well with the DeFi principles, and it is also beneficial to CeFi. Distributed ledger platforms offer transparency and security for both DeFi and CeFi, whereas future payment technologies provide user-friendly solutions. This study applies novel wavelet and quantile cross-spectral coherence analyses to obtain nuanced relationship insights. This methodology categorizes crypto finance into the DeFi and broader cryptocurrency ecosystems to facilitate robust comparison with traditional banking. It further delineates democratized banking into alternative financing mechanisms, distributed ledger technologies, and future payment capabilities. Wavelet coherence analysis reveals time–frequency associations, whereas quantile cross-spectral coherence unveils extreme connections under different market conditions. The findings suggest the existence of dynamic relationships between inclusive banking components and various financial infrastructures. These relationships vary across return distributions and time scales. In regular markets, positive associations are seen in yearly and monthly frequency cycles with alternative finance and centralized services exhibiting the strongest linkage. During periods of extremely high returns, CeFi and centralized-decentralized (hybrid) infrastructures exhibit limited interconnectivity with democratized banking. Moreover, DeFi's association with distributed ledger technology is negligible. In bear markets, the strongest positive associations are observed between inclusive access and conventional, hybrid, and decentralized financial systems. These insights provide new perspectives on the dynamics between financial systems during extreme conditions. This study emphasizes the need for adaptive regulation, international cooperation, and a balance between innovation and stability to protect and empower users. Collaboration between academia and policymakers is essential to navigate this evolving landscape and advance democratized banking.

Combining orbital tuning and direct dating approaches to age-depth model development for Chew Bahir, Ethiopia

The directly dated RRMarch2021 age model (Roberts et al., 2021) for the ∼293 m long composite core from Chew Bahir, southern Ethiopia, has provided a valuable chronology for long-term climate changes in northeastern Africa. However, the age model has limitations on shorter time scales (less than 1–2 precession cycles), especially in the time range <20 kyr BP (kiloyears before present or thousand years before 1950) and between ∼155 and 428 kyr BP. To address those constraints we developed a partially orbitally tuned age model. A comparison with the ODP Site 967 record of the wetness index from the eastern Mediterranean, 3300 km away but connected to the Ethiopian plateau via the River Nile, suggests that the partially orbitally tuned age model offers some advantages compared to the exclusively directly dated age model, with the limitation of the reduced significance of (cross) spectral analysis results of tuned age models in cause-effect studies. The availability of this more detailed age model is a prerequisite for further detailed spatiotemporal correlations of climate variability and its potential impact on the exchange of different populations of Homo sapiens in the region.

Investigating the Response of Vegetation to Flash Droughts by Using Cross-Spectral Analysis and an Evapotranspiration-Based Drought Index

Flash droughts tend to cause severe damage to agriculture due to their characteristics of sudden onset and rapid intensification. Early detection of the response of vegetation to flash droughts is of utmost importance in mitigating the effects of flash droughts, as it can provide a scientific basis for establishing an early warning system. The commonly used method of determining the response time of vegetation to flash drought, based on the response time index or the correlation between the precipitation anomaly and vegetation growth anomaly, leads to the late detection of irreversible drought effects on vegetation, which may not be sufficient for use in analyzing the response of vegetation to flash drought for early earning. The evapotranspiration-based (ET-based) drought indices are an effective indicator for identifying and monitoring flash drought. This study proposes a novel approach that applies cross-spectral analysis to an ET-based drought index, i.e., Evaporative Stress Anomaly Index (ESAI), as the forcing and a vegetation-based drought index, i.e., Normalized Vegetation Anomaly Index (NVAI), as the response, both from medium-resolution remote sensing data, to estimate the time lag of the response of vegetation vitality status to flash drought. An experiment on the novel method was carried out in North China during March–September for the period of 2001–2020 using remote sensing products at 1 km spatial resolution. The results show that the average time lag of the response of vegetation to water availability during flash droughts estimated by the cross-spectral analysis over North China in 2001–2020 was 5.9 days, which is shorter than the results measured by the widely used response time index (26.5 days). The main difference between the phase lag from the cross-spectral analysis method and the response time from the response time index method lies in the fundamental processes behind the definitions of the vegetation response in the two methods, i.e., a subtle and dynamic fluctuation signature in the response signal (vegetation-based drought index) that correlates with the fluctuation in the forcing signal (ET-based drought index) versus an irreversible impact indicated by a negative NDVI anomaly. The time lag of the response of vegetation to flash droughts varied with vegetation types and irrigation conditions. The average time lag for rainfed cropland, irrigated cropland, grassland, and forest in North China was 5.4, 5.8, 6.1, and 6.9 days, respectively. Forests have a longer response time to flash droughts than grasses and crops due to their deeper root systems, and irrigation can mitigate the impacts of flash droughts. Our method, based on cross-spectral analysis and the ET-based drought index, is innovative and can provide an earlier warning of impending drought impacts, rather than waiting for the irreversible impacts to occur. The information detected at an earlier stage of flash droughts can help decision makers in developing more effective and timely strategies to mitigate the impact of flash droughts on ecosystems.

Examining the quantile cross-coherence between fossil energy and clean energy: Is the dependence structure changing with the COVID-19 outbreak?

The advent of COVID-19 has markedly affected financial and energy markets. Clean energy positions itself as a feasible substitute for fossil fuels, and the crisis has altered the interdependence of these two counterpart markets. This study uses quantile cross-spectral analysis to investigate the dependence structure features of the fossil and clean energy markets, pre- and post-COVID-19 outbreak, under various market conditions and across different investment horizons. Empirical results suggest an anomalous intensification or inversion in the interaction between fossil and clean energy under extreme market conditions post-COVID-19 outbreak, manifesting either an extraordinarily high or low dependency. Additionally, the asset dependence structure exhibits increased heterogeneity across investment horizons after the COVID-19 outbreak, with short-term structures demonstrating higher volatility, while medium- and long-term structures show similarity. Finally, by generating a dynamic energy portfolio, this paper measures the investment allocation weights of each asset before and after the emergence of COVID-19. Findings indicate an increased need for investment in natural gas, crude oil, and clean energy post-COVID-19 outbreak, suggesting a reduction in coal investment. The analyses aim to assist energy investors in enhancing their economic decision-making processes and refining their portfolio management strategies.

Impact of climate risk shocks on global food and agricultural markets: A multiscale and tail connectedness analysis

We examine the time-frequency nexus between climate change, agricultural and food markets over normal and extreme market conditions by employing advanced methods such as quantile cross-spectral analysis and wavelet quantile correlation. To identify how climate change affects food and agricultural market price returns, we examine daily data from January 1, 2019, to May 9, 2022, using two climate change proxies: European CO2 emissions and MSCI World Climate Paris Aligned Net indices, four global food market indices, and four agricultural commodities. Our results reveal significant insights into the impact of CO2 emissions and environmental policy on these markets, emphasizing the nuanced nature of these effects across different market conditions and time frames. The results suggest that, in the long run, environmental policies contribute positively to agricultural and food markets, while the impact of CO2 emissions manifests as predominantly negative. This research provides valuable contributions to understanding the intricate dynamics between climate change, environmental policies, and the financial aspects of food and agricultural markets.

Correction of high-frequency (&amp;gt; 0.3 mHz) air pressure effects in gravity time-series

SUMMARY Correcting atmospheric effects in measurements of vertical acceleration is challenging, particularly at frequencies above 0.3 mHz. Corrections based on 4-D atmosphere models should be the most effective, but are limited in temporal and spatial resolutions. So these models are commonly combined with a constant admittance between air pressure and gravity, though the correction can be further improved by allowing a frequency-dependent admittance. This paper studies the effectiveness of such procedures given that air pressure admittance varies with time because of variability in the underlying local atmospheric process, and finds that admittances estimated by cross-spectral analysis gives better results than a constant admittance does. The best results are achieved by combining a 4-D model with admittances estimated from time-series that cover the event of interest.

Seismic Velocity Variations Observed Prior to the La Palma Volcano Eruption on 19 September 2021, in Cumbre Vieja, Canary Islands (Spain)

Abstract In the recent years, coda-wave interferometry from seismic noise correlation functions has been increasingly used for volcanic eruption forecasting through velocity changes observed in the crust. Because La Palma Island in the Canary Archipelago is very well instrumented, we studied the possible velocity variations related to the last Cumbre Vieja eruption on 19 September 2021, aiming to obtain clear variations in the seismic velocity. For this purpose, we used the moving-window cross-spectral analysis technique for seismic noise within the 0.1–1.0 Hz frequency interval for determining two- and single-station cross-component correlations. During the 2018–2022 observation period, we first detected a seasonal seismic velocity variation possibly caused by annual rainfall and the induced pore pressure change. On 12 September 2021, a dramatic decrease in the velocity of −0.15% was detected, leading to the volcanic eruption at Cumbre Vieja seven days later. The results are compatible with those of models proposed for rapid magma migration from a shallow reservoir at 11 km to the surface.

Cross-Spectral Analysis of SAR Altimetry Waveform Tails

Cross-Spectral Analysis of SAR Altimetry Waveform Tails

Calculating the connection between precipitation and shallow groundwater

From a water management point of view, it is particularly important to be able to examine the temporality of the precipitation that replenishes the shallow or even deeper groundwater layers. In our study, we use a method that allows us to analyze the evolution of both the precipitation and groundwater levels together. With cross-correlation and cross-spectral analyses, we can quantify the relationship between the two hydrological parameters for a given sample area, and the periods found in the relationship can also be detected. During our calculations, we were able to determine such delay times for a sample area in Debrecen using monthly and daily data series, so an 8-10 month and a shorter 3-4 day linear relationship between precipitation and groundwater was detected. Based on our results, several periodic components can also be found in this relation.

Reconstruction of ENSO variability using the standardized growth index of a Tridacna shell from Yongshu Reef, South China Sea

El Niño-Southern Oscillation (ENSO) is the strongest signal of global interannual climate anomaly and reconstructing past ENSO variations using high-resolution paleoclimate archives can improve our understanding of ENSO variability, as well as improve our ability to predict future climate changes. Here, a daily resolution standardized growth index (SGI) was established using a giant clam (Tridacna spp.) shell specimen MD2 (life span: 1994–2013 CE), collected from the Yongshu Reef, southern South China Sea (SCS). The cross-spectral and correlation analysis indicated that the SGI variation of MD2 was strongly influenced by ENSO variability on an interannual timescale. Tridacna spp. is in symbiosis with zooxanthellae, and its growth index is usually modulated by the photosynthetic efficiency of zooxanthellae. During the El Niño (La Niña) period, the convective anomalies stimulated in western Pacific would increase (decrease) the effective solar radiation on Yongshu Reef, and in turn influence the photosynthesis rate of zooxanthellae and enzyme activity for the calcification site and thus the SGI of giant clam MD2. The SGI can explain 54.7 % of ENSO variance, demonstrating the potential for Tridacna SGI in ENSO reconstruction. Compared with conventional ENSO reconstruction using high-resolution geochemical proxies, the method of giant clam SGI is rapid and economical.

Cross-spectral analysis of cerebral autoregulation after mild traumatic brain injury.

Severe traumatic brain injury (TBI) disrupts cerebral autoregulation (CAR), which may increase the risk of secondary neuronal damage in victims with large fluctuations in blood pressure (BP). CAR is also impaired in mild TBI. Given that mild TBI accounts for up to 70% of cases, this issue needs to be addressed. Physiological and non-invasive methods are now required to study CAR without the sharp fluctuations in blood pressure that underlie CAR tests. The cross-spectral analysis of fluctuations between cerebral blood flow and blood pressure discussed in the article is truly non-invasive and physiological. Forty-eight victims with mild traumatic brain injury were studied. CAR was assessed using two methods. The cuff test was used as a control method to assess autoregulation (RoR). Non-invasive cross-spectral analysis with phase shift (PS) detection was performed. The RoR values were normal, but there were cases within the group with varying severity of symptoms of the acute period of mild TBI. For example, the RoR was significantly higher (p < 0.001) in 32 patients with regression of symptoms than in 16 with persistence of symptoms. Their RoR and PS indicated a violation of the CAR, which required correction of the treatment. It was found that in 1/3 of the patients with mild TBI, a different state of CAR required individual tactics. RoR and PS correlated well.

Flow structure and impinging interactions of two confined turbulent converging jets in crossflow

In this work, time-resolved particle image velocimetry (TR-PIV) measurements are carried out to study the flow structure and impinging interactions of two confined turbulent converging jets in crossflow, with the upstream and downstream jets inclined at 20° and 170° with respect to the oncoming crossflow direction. Experiments are conducted for fixed dimensionless nozzle separation distance of s=L/D=3, fixed dimensionless nozzle-to-target surface distance of H/D=6.73, fixed duct Reynolds number of Re=3500 and two jets' Reynolds numbers of Rej=3000 and 6000 that correspond to jets'-to-crossflow velocity ratios of rj=3.45 and 6.91, respectively. Flow visualization images showing ensemble-averaged and instantaneous flow distributions and turbulent characteristics including Reynolds stresses and turbulence intensities for equal and non-equal discharge velocities of the jets are presented on several orthogonal planes of the test section. The swirling strength criterion has been employed to identify coherent structures, and cross spectral analysis of the fluctuating velocity signals detecting subharmonic and harmonic sideband frequencies identify the merging and breakup interactions of the evolving coherent structures. The snapshot proper orthogonal decomposition technique (POD) has been applied to extract the dominant vortical structures and to quantify their relative and cumulative energy contributions to the total kinetic energy fluctuation. The spatial structure of the main four POD modes and the temporal projections of these POD coefficients have been explored to understand the spatio-temporal characteristics of the dominant turbulent fluctuations and their spectral characteristics. Our results show the effect of the velocity ratios on the jets' trajectories, penetration, spreading characteristics, crossflow entrainment through the inner and outer shear layers, transverse velocity decay, size of the converging region and location of the combining point. In addition, the dimensionless shedding frequencies of the oscillating combined jet, the developing wall jets and wake vortices have been obtained. Furthermore, it has been shown that for all values of the jets' velocity ratios employed in this study, a recirculation region does not develop in the converging region.