Cross Wavelet Research Articles

Attribution of Observed Periodicity in Extreme Weather Events in Eastern North America

AbstractInstrumental weather records (1880–2020s) from eastern North America were analyzed to characterize the regional patterns and drivers of seasonal extreme weather (snow, rain, high and low temperatures). Using agglomerative hierarchical clustering of extreme weather data, the region was divided into three subregions that are influenced by coastal‐marine gradients and latitudinal factors. Subsequent analyses were performed on high‐quality stations from each subregion and results compared between one another. Long‐term locally weighted linear regressions delineated long‐term changes in extreme weather, and a combination of spectral analysis, continuous wavelet transforms, and cross wavelet transforms were used to identify periodic components in the data. Regional extreme weather is generally periodic, composed of interannual to interdecadal‐scale oscillations and driven by several natural climatic oscillations. The most important such oscillation is the 11‐year Schwabe Solar Cycle, which has a strong and continuous effect on regional extreme weather. The Pacific Decadal Oscillation and Quasi Biennial Oscillation also show considerable influence, but intermittently. The El Niño Southern Oscillation, the Arctic Oscillation, and the North Atlantic Oscillation all have a weaker but interrelated influence. While the Atlantic Multidecadal Oscillation showed the weakest overall influence on regional extreme weather, it demonstrated a clear spatial gradient across the region, unlike the aforementioned oscillations. Long‐term changes in regional extreme weather are not generally important, in that a sustained increase or decrease in extreme weather events is not usually characteristic of the weather records. The primary exception to this result is for extreme minimum temperature events, whose frequency has slightly decreased since the 1880s.

Using Nighttime Luminosity as a Proxy for Economic Growth in Africa: Is It a Bright Idea?

In this paper, we question whether night light luminosity data can beused as an alternative measure of GDP in 49 African countries. For thisto be proven true, evidence of significant relationships between night lightdata and GDP time series variables needs to be confirmed through empiricalanalysis. In differing from previous studies, we employ pooled meangroup (PMG) cross sectional cointegration estimators and wavelet coherencetools to examine the cointegration relationships and time-frequencysynchronizations between GDP and DMSP-OLS night light intensity forannual data collected between 1992 and 2012. All in all, we find little evidenceof significant relationships between nighttime data and GDP for individualAfrican countries and therefore caution policymakers in strictlyusing DMSP-OLS data to create synthetic measures of economic growth.Possible avenues for future research are further recommended at the endof the study.

Experimental Investigation on the Bioprotective Role of Trehalose on Glutamine Solutions by Infrared Spectroscopy.

Glutamine plays a significant role in several basic metabolic processes and is an important regulator of heat shock protein response. The present work is focused on the analysis of the thermal response of aqueous solutions of Glutamine and aqueous solutions of Glutamine in the presence of Trehalose by means of infrared absorption technique. The performed study shows how in the case of a multicomponent system, characterized by a huge number of spectral contributions whose assignment are questionable, the Spectral Distance (SD) and the Cross Wavelet Correlation (XWT) approaches are able to furnish explanatory parameters that can characterize the variations in the spectra behaviour, which is an efficient tool for quantitative comparisons. With this purpose, the analysis has been performed by evaluating the SD and the XWT parameters for the whole investigated spectral range, i.e., 4000–400 cm−1, for scans collected as a function of temperature in the range 20 °C ÷ 60 °C both for Glutamine/Water compounds and for Glutamine /Water/Trehalose mixtures. By means of these analyses, it is found that in aqueous solutions of Glutamine, with respect to aqueous solutions of Glutamine in the presence of Trehalose, the SD and XWT temperature trends follow a linear behaviour where the angular coefficient for Glutamine /Water/Trehalose compounds are lower than that of the Glutamine-Water system in both cases. The obtained findings suggest that Trehalose stabilizes Glutamine against heat treatment.

A Comprehensive Analysis of Environmental Loading Effects on Vertical GPS Time Series in Yunnan, Southwest China

Seasonal variations in the vertical Global Positioning System (GPS) time series are mainly caused by environmental loading, e.g., hydrological loading (HYDL), atmospheric loading (ATML), and nontidal oceanic loading (NTOL), which can be synthesized based on models developed by various institutions. A comprehensive comparison among these models is essential to extract reliable vertical deformation data, especially on a regional scale. In this study, we selected 4 HYDL, 5 ATML, 2 NTOL, and their 40 combined products to investigate their effects on seasonal variations in vertical GPS time series at 27 GPS stations in Yunnan, southwest China. These products were provided by the German Research Center for Geosciences (GFZ), School and Observatory of Earth Sciences (EOST), and International Mass Loading Service (IMLS). Furthermore, we used the Cross Wavelet Transform (XWT) method to analyze the relative phase relationship between the GPS and the environmental loading time series. Our result showed that the largest average Root-Mean-Square (RMS) reduction value was 1.32 mm after removing the deformation associated with 4 HYDL from the vertical GPS time series, whereas the RMS reductions after 5 ATML and 2 NTOL model corrections were negative at most stations in Yunnan. The average RMS reduction value of the optimal combination of environmental loading products was 1.24 mm, which was worse than the HYDL (IMLS_GEOSFPIT)-only correction, indicating that HYDL was the main factor responding for seasonal variations at most stations in Yunnan. The XWT result showed that HYDL also explained the annual variations reasonably. Our finding implies that HYDL (IMLS_GEOSFPIT) contributes the most to the environmental loading in Yunnan, and that the ATML and NTOL models used in this paper cannot be effective to correct seasonal variations.

Multivariable statistical analysis between geomagnetic field, climate, and orbital periodicities over the last 500 KYR, and their relationships during the last interglacial

Relationships between geomagnetic field (GF) variations, paleoclimates, and Milankovitch cycles have increasingly attracted the attention of researchers mainly because of the assumption that GF may have acted as a climate forcing, suggesting that GF variations and orbital forcing may be linked in a complex synergistic way, especially, during interglacials and interstadials. We first performed an exhaustive analysis of the relationship between GF, a paleotemperature proxy, astroclimatic parameters, and the summer solstice mean daily insolation at 65 N over the last 500 kyr. We evaluated the relationship between the variables at the orbital scale, using wavelets, cross wavelets, and multiple cross wavelets. Our novel approach to the subject is the use of a new multiple cross wavelet algorithm, which allowed us to simultaneously analyze several data series and determine the relative phases between the signals. We confirm that the eccentricity modulates the GF behavior, and that the precession could have been related to some short-term GF variations. Both orbital parameters seem to be precursors of GF changes. Also, it is especially interesting to investigate the role of the GF reversion events because they could have acted as an indirect climate forcing, and we focused on the relationship among forcings during Marine Isotope Stage (MIS) 5. During this period, two GF reversions (Blake and post-Blake) could have been associated with relative climate cooling. The consequent lack or weakening of shielding associated with GF events and downward insolation, both influenced by orbital forcing, could finally have promoted a relative global climate cooling during MIS 5. • New multiple cross wavelets of RPI, δ 18 O, insolation, and orbital forcing. • GF is modulated by eccentricity in the trend, by precession in short-term changes. • Orbital forcing seems to be precursor of GF variations over the last 500 kyr. • Cooling is promoted by lows RPI and insolation, both influenced by orbital forcing.

Spatiotemporal Variability in Precipitation Extremes in the Jianghuai Region of China and the Analysis of Its Circulation Features

In the context of global warming, changes in extreme-precipitation events are becoming increasingly complex, and investigating the spatial and temporal variation characteristics of extreme precipitation is extremely important for scientific water-resource planning, preventing new climate risks and maintaining ecosystem balances. Based on the daily precipitation from 1960–2017 at 15 meteorological stations in the Jianghuai region, the extreme-precipitation indices were calculated. The variations in 12 extreme-precipitation indices were detected by using the Mann–Kendall test in the Jianghuai region. The periodicity of indices was examined by wavelet analysis detecting significant time sections. Through the cross wavelet transform and wavelet coherence analyses, the nonlinear connections between extreme precipitation and atmospheric circulation were explored. The results indicate significant increasing trends in the max one-day precipitation amount (Rx1day), extreme wet days (R99p), and simple precipitation intensity index (SDII). The intensity of extreme precipitation increased significantly. The variation in extreme precipitation showed different trends in different regions, with a greater likelihood of increasing extreme-precipitation intensity and frequency in the southern region compared to the central and northern regions. The period of most oscillations of the indices tend toward be on a time scale of 2–4 years and are in the 1990s. The number of heavy precipitation days (R10 mm) and number of very heavy precipitation days (R20 mm) had, mainly, periods of 5.84 years. Additionally, there were significant resonance periods between the extreme-precipitation indices and the atmospheric circulation index; however, there were obvious differences in time domains. The North Atlantic Oscillation (NAO) and East Asian summer monsoon (EASM) had the most significant effect on the duration of extreme precipitation; Atlantic Oscillation (AO) and EASM had the most significant influence on the extreme-precipitation intensity. The results of the study can provide a scientific basis for water-resource management and disaster prevention and control in the Jianghuai region.

Spatiotemporal Dynamics of NDVI, Soil Moisture and ENSO in Tropical South America

We evaluated the coupled dynamics of vegetation dynamics (NDVI) and soil moisture (SMOS) at monthly resolution over different regions of tropical South America and the effects of the Eastern Pacific (EP) and the Central Pacific (CP) El Niño–Southern Oscillation (ENSO) events. We used linear Pearson cross-correlation, wavelet and cross wavelet analysis (CWA) and three nonlinear causality methods: ParrCorr, GPDC and PCMCIplus. Results showed that NDVI peaks when SMOS is transitioning from maximum to minimum monthly values, which confirms the role of SMOS in the hydrological dynamics of the Amazonian greening up during the dry season. Linear correlations showed significant positive values when SMOS leads NDVI by 1–3 months. Wavelet analysis evidenced strong 12- and 64-month frequency bands throughout the entire record length, in particular for SMOS, whereas the CWA analyses indicated that both variables exhibit a strong coherency at a wide range of frequency bands from 2 to 32 months. Linear and nonlinear causality measures also showed that ENSO effects are greater on SMOS. Lagged cross-correlations displayed that western (eastern) regions are more associated with the CP (EP), and that the effects of ENSO manifest as a travelling wave over time, from northwest (earlier) to southeast (later) over tropical South America and the Amazon River basin. The ParrCorr and PCMCIplus methods produced the most coherent results, and allowed us to conclude that: (1) the nonlinear temporal persistence (memory) of soil moisture is stronger than that of NDVI; (2) the existence of two-way nonlinear causalities between NDVI and SMOS; (3) diverse causal links between both variables and the ENSO indices: CP (7/12 with ParrCorr; 6/12 with PCMCIplus), and less with EP (5/12 with ParrCorr; 3/12 with PCMCIplus).

Epileptic-seizure onset detection using PARAFAC model with cross-wavelet transformation on multi-channel EEG.

Finding components from multi-channel EEG signal for localizing and detection of onset of seizure, is a new approach in biomedical signal analysis. Tensor-based approaches are utilized to fit the components into multi-dimensional arrays in recent works. We initially decompose EEG signals into Beta band using discrete wavelet transform (DWT). We compare patient templates with normal template for cross-wavelet analysis to obtain Wavelet cross spectrum (WCS) and Wavelet cross coherence coefficients. Next we apply parallel factorization (PARAFAC) modeling, a three-way tensor-based representation in channel, frequency and time-points dimensions on features. Finally, we utilize the ensemble classifier for detecting seizure-free, onset and seizure classes. The clinical dataset for this work comprises of 5 normal subjects and 6 epileptiform patients. The classification performances of WCS features on PARAFAC model for Seizure detection using Ensemble Bagged-Trees classifier obtains 82.21% accuracy, while for Wavelet Coherence features, it provides higher 84.76% accuracy. The results have been compared with well-known Fine Gaussian SVM, Weighted KNN and Ensemble Subspace KNN classifiers. The aim is to analyze data over three dimensions namely, time, frequency and space (channels). This EEG based analysis is significant and effective as an automatic method for detection of seizure before its actual manifestation.

Proper orthogonal decomposition, dynamic mode decomposition, wavelet and cross wavelet analysis of a sloshing flow

Internal hydrodynamics and its coupling with structural dynamics are non-negligible processes in the design phase of aerospace systems. An improved understanding of the nature of this coupling would allow for greater flexibility in modeling and design of such systems, and could lead eventually to the development of suitable active and/or passive control strategies for enhanced performances. In this manuscript we apply a number of data analysis techniques: proper orthogonal decomposition, dynamic mode decomposition and wavelet transform and their combination to time-resolved images of a liquid sloshing within an enclosure. We use these techniques to identify fluid-dynamic modes in space and time and to verify their coupling with the structural dynamics of vibrating structures.In particular we consider the transient case of a water tank mounted on a free oscillating cantilever. As the acceleration amplitude decays, we observe and quantify the transition from incoherent flow to standing waves. Our results show that the content of the images is very informative and can be used for quantitative analysis. As the main outcome, the hydrodynamic modes are identified using POD and DMD, and related to known features of sloshing flow, such as the frequency of the first symmetric free surface mode. Additionally we perform a comparison of wavelet transforms of POD time coefficients and measured acceleration signals at the tank base. Viewing the latter as the input and the former as the output of the fluid-dynamic system, we are able to correlate the enhanced damping of the cantilever oscillation to the different regimes of the hydrodynamic field.

Streamflow frequency changes across western Europe and interactions with North Atlantic atmospheric circulation patterns

This study identifies significant periodicities in streamflow dynamics across western Europe using a hydrological database encompassing 1874 monthly series from catchments in Ireland, the United Kingdom, France, Spain and Portugal, spanning the years 1962 to 2012. Significant and synchronous periodicities with the main atmospheric mechanisms over the North Atlantic sector are also identified using Cross Wavelet Transform and Wavelet Coherence analysis. Principal Components Analysis (PCA) were applied to the different Wavelet transforms analysis in order to summarize the results. These show the occurrence of a 7-years streamflow cycle in a large proportion of catchments within the study domain since the mid 1980's that was not present in earlier periods. The significance, intensity and persistence of the observed regional cycle follows a spatial gradient around the English Channel. We show how the transitive coupling of key atmospheric mechanisms is an influencing factor causing the general change observed. These results suggest the occurrence of a regional change in the periodicities of streamflow across the western European domain. Our results emphasize the non-stationary interaction between streamflow and atmospheric circulation during recent decades and the prominent role of the North Atlantic Oscillation in the newly stablished streamflow cycles. • We assessed the characteristics of streamflow frequencies across Western Europe by means of different Wavelet Transforms. • We used a database encompassing 1874 monthly streamflow series from 1962 to 2012, covering the European Atlantic façade. • The results unveiled the existence of a clear 7-year cycle in a large proportion of the study domain since the mid 1980's. • We show how the transitive coupling of key atmospheric mechanisms is an influencing factor causing the change observed. • The results emphasize the complexity of the non-stationary interaction between streamflow and atmospheric circulation.

Rock magnetic properties as proxy indicators of characteristic periodicities in Holocene aeolian sediments (Arturo Dune, Tierra del Fuego, Argentina)

The objective of this contribution is to distinguish characteristic wind speed periodicities from a roughly 19 m-thick profile of Arturo Dune (Tierra del Fuego, Argentina), which contains eight interbedded paleosoils. The results include different magnetic properties and ratios measured in 29 aeolian sediment samples. These properties are coercive force (HC), saturation magnetization (MS), low-frequency (470 Hz) magnetic susceptibilities (kLF), anhysteretic remanent magnetization (ARM), among others.The statistical analysis of the variations in the magnetic properties of detrital minerals over time could indirectly indicate prevailing periodicities of the wind rate during the studied interval. The power spectral analysis was done using wavelets and multiple cross wavelets. The analysis by wavelets made it possible to distinguish periodicities in the variations of climatic parameters.A main periodicity of 2824 years was obtained in the different wavelet and multiple cross wavelet analyses of the magnetic parameters. By adding the δ18O series from the deep South Atlantic Ocean to the spectral power analysis, a periodicity of around 3000 years was also obtained.These periodicities could be related to a fundamental solar mode, with a periodicity of 2300 years (Hallstattzeit cycle). Still, they are not conclusive as solid empirical evidence to support sun-climate relationships on a series of millennial suborbital time scales.

Wavelet analysis and energy-based measures for oil-food price relationship as a footprint of financialisation effect

In this paper we exploit the wavelet analysis approach to investigate oil-food price correlation and its determinants in the domains of time and frequency. Wavelet analysis is able to differentiate high frequency from low frequency movements which correspond, respectively, to short and long run dynamics. We show that the significant local correlation between food and oil is only apparent and this is mainly due both to the activity of commodity index investments and, to a lesser extent, to a growing demand from emerging economies. Moreover, the activity of commodity index investments gives evidence of the overall financialisation process. In addition, we employ wavelet entropy to assess the predictability of the time series under consideration at different frequencies. We find that some variables share a similar predictability structure with food and oil. These variables are the ones that move the most along with oil and food. We also introduce a novel measure, the Cross Wavelet Energy Entropy Measure (CWEEM), based on wavelet transformation and information entropy, with the aim of quantifying the intrinsic predictability of food and oil given demand from emerging economies, commodity index investments, financial stress, and global economic activity. The results show that these dynamics are best predicted by global economic activity at all frequencies and by demand from emerging economies and commodity index investments at high frequencies only.

Groundwater drought characteristics and its influencing factors with corresponding quantitative contribution over the two largest catchments in China

Investigating the characteristics and influencing factors of groundwater drought, and identifying their difference in the regions with different climate conditions can provide an essential reference for the sustainable management of groundwater resources. As a case study in the two largest and typical catchments in China, the temporal evolution, spatial distribution and trend characteristics of groundwater drought are identified by GRACE-based groundwater drought index in the Yangtze River catchments (YZRC) with a humid climate condition, and Yellow River catchments (YRC) with an arid/semi-arid climate condition. Their influencing factors, which include natural net recharge (P-ET), teleconnection factors (ENSO, PDO and AO), and anthropogenic factors (land use and land cover, LULC), are investigated and quantitatively compared based on Pearson correlation analysis, cross wavelet transform and Random Forest. The results indicate that: (1) The groundwater droughts in the YZRC mainly occur during 2002–2009, which are mostly in the middle and lower reaches of the catchments, and they show a decreasing trend in most regions of the catchments. In the YRC, they mainly occur during 2015–2019, which influence almost the whole catchments, and they show an increasing trend in most regions of the catchments. (2) The P-ET has a significant positive impact on the mitigation of groundwater drought in the YZRC, while it fails to reverse the groundwater drought aggravation in the YRC. The teleconnection factors have obvious influences on groundwater drought evolution, among which Arctic Oscillation (AO) and Pacific Decadal Oscillation (PDO) are the important factors affecting groundwater drought in the YZRC and YRC, respectively. For LULC, the decrease of cropland and grassland could alleviate groundwater drought in the YZRC, and the increase of grassland, forest and urban area in the YRC could aggravate groundwater drought in the catchments. (3) When quantitatively comparing the contributions, the LULC and P-ET are the crucial factors affecting groundwater drought in the two catchments, while in the YRC, the impact of teleconnection factors cannot be ignored, although it is relatively weak. Moreover, groundwater exploitation plays an important role on groundwater drought in the YZRC and YRC. Its contribution in the YZRC and YRC is slightly lower than that of P-ET, but obviously higher than that of teleconnection factors.

Precipitation and Temperature Trends and Cycles Derived from Historical 1890–2019 Weather Data for the City of Ottawa, Ontario, Canada

Patterns in historical climate data were analyzed for Ottawa, Ontario, Canada, for the interval 1890–2019. Variables analyzed included records of annual, seasonal, and extreme temperature and precipitation, diurnal temperature range, and various environmental responses. Using LOWESS regressions, it was found that annual and seasonal temperatures in Ottawa have generally increased through this interval, precipitation has shifted to a less snowy, rainier regime, and diurnal temperature variation has decreased. Furthermore, the annual growing season has lengthened by 23 days to ~163 days, and the annual number of frost-free days increased by 13 days to ~215 days. Despite these substantial climatic shifts, some variables (e.g., extreme weather events per year) have remained largely stable through the interval. Time-series analyses (including multitaper spectral analysis and continuous and cross wavelet transforms) have revealed the presence of several strong cyclical patterns in the instrumental record attributable to known natural climate phenomena. The strongest such influence on Ottawa’s climate has been the 11-year solar cycle, while the influence of the El Niño-Southern Oscillation, Arctic Oscillation, North Atlantic Oscillation, and Quasi-Biennial Oscillation were also observed and linked with the trends in annual, seasonal, and extreme weather. The results of this study, particularly the observed linkages between temperature and precipitation variables and cyclic climate drivers, will be of considerable use to policymakers for the planning, development, and maintenance of city infrastructure as Ottawa continues to rapidly grow under a warmer, wetter climate regime.

Spectral analysis of geomagnetically induced current and local magnetic field during the 17 March 2013 geomagnetic storm

Geomagnetically induced current (GIC) is known to be closely related to the rate of change of local horizontal magnetic field (dBx/dt); and their spectra can give better insight into the relationship. We study the spectral characteristics of GIC measured in Finland and dBx/dt measured 30 km away during the 17 March 2013 intense geomagnetic storm (SymHMin = −132 nT). Two bursts of large GIC (up to 32A) and dBx/dt occurred at ∼16 UT and 18 UT during the storm main phase. For the first time, the cross wavelet transform (XWT) and wavelet coherence (WTC) techniques are used to investigate the correlation and phase relationship of GIC and dBx/dt in time-frequency domain. Their WTC correlation is strong (over 0.9) over the entire storm period, indicating dBx/dt is the main factor causing GIC. Their XWT spectra show two enclosed periods (8–42 min and 2–42 min) in the high energy region corresponding to the two bursts of activity in GIC and dBx/dt. Morever, we use continuous wavelet transform (CWT) and discrete wavelet transform (DWT) to analyze the spectral characteristics of GIC and dBx/dt. It is found that the CWT and DWT spectra of the two are very similar, especially in the low frequency characteristics, without continuous periodicity. Wavelet coefficients become large when GIC and dBx/dT are large; and the third-order coefficient, which corresponds to low-frequency part, best reflects the disturbance of GIC and dBx/dt.

Bearing fault diagnosis based on XWT-CEEMD noise reduction

In recent years, bearing fault diagnosis has been a research hotspot. In order to improve the reliability of acoustic fault diagnosis, this paper combines Cross Wavelet Transform (XWT) and complementary ensemble empirical mode decomposition (CEEMD) to extract bearing fault features from acoustic signals. Finally, the time-domain features and spectral centroid are input into the SVM for fault classification. The results show that the proposed method can effectively improve the reliability of acoustic fault diagnosis.

Response of Precipitation in Tianshan to Global Climate Change Based on the Berkeley Earth and ERA5 Reanalysis Products

Global climate change has readjusted a global-scale precipitation distribution in magnitude and timing. In mountainous areas, meteorological stations and observation data are very limited, making it difficult to accurately understand the response of precipitation to global climate change. Based on ECMWF Reanalysis v5 precipitation products, Berkeley Earth global temperature, and typical atmospheric circulation indexes, we integrated a gradient descent-nonlinear regression downscaling model, cross wavelet transform, and wavelet correlation method to analyze the precipitation response in Tianshan to global climate change. This study provides a high-resolution (90 m × 90 m) precipitation dataset in Tianshan and confirms that global warming, the North Pacific Pattern (NP), the Western Hemisphere Warm Pool (WHWP), and the Atlantic Multidecadal Oscillation (AMO) are related to the humidification of Tianshan over the past 40 years. The precipitation in Tianshan and global temperature have a resonance period of 8–15 months, and the correlation coefficient is above 0.9. In Tianshan, spring precipitation is determined mainly by AMO, North Tropical Atlantic Sea Level Temperature, Pacific Interdecadal Oscillation (PDO), Tropical North Atlantic Index, WHWP, NP, summer by NP, North Atlantic Oscillation, and PDO, autumn by AMO, and winter by Arctic Oscillation. This research can serve the precipitation forecast of Tianshan and help in the understanding of the regional response to global climate change.

Biomass energy consumption and economic growth: insights from BRICS and developed countries.

This study analyzes the causal associations between economic growth (GDP) and biomass energy consumption (BIO) in the US, UK, and BRICS countries for the period 1990 to 2020 in time-frequency space. The use of wavelets is what distinguishes our approach, i.e., cross wavelet transform, wavelet coherence, and the wavelet-based Granger causality method proposed by Olayeni (2016), which quantifies the causal associations in the time-frequency space. The results uncover that the causal relationships between GDP and BIO are not uniform across time and frequency. In fact, there is a positive relationship between GDP and BIO indicators in the BRICS countries in the medium and long term and in the USA and UK in the short term throughout the research period. In addition, a bidirectional causal effect between GDP and BIO exists in China, Brazil, and India, while there is no long-run causal relationship between GDP and BIO in India and South Africa. The causal impacts of economic growth on biomass energy usage are more pronounced in these countries than in the opposite direction, especially over longer time horizons. The key conclusion is that these countries should boost their biomass energy consumption to promote economic growth and reduce energy reliance.

Evaluating the relationships between wildfires and drought using machine learning

In recent years, many destructive wildfires have plagued California. Extreme fire conditions, such as drought, have been taking place simultaneously with many of these wildfires. In this study, the relationship was quantified between the self-calibrated Palmer Drought Severity Index (sc-PDSI) and wildfire burn area (BA) in California during the time of 1984–2018, and results indicate that the drought is a significant driver of wildfire BA in California. The methods of wavelet transform coherence, cross wavelet transform, and continuous wavelet transform were used in conjunction with machine learning algorithms to analyse and establish the relationship between sc-PDSI and wildfire BA. This study concludes that there was a statistically significant relationship between wildfire BA and sc-PDSI in 6–8-, 5–6-, and 2–3-year bands during the study period, during which sc-PDSI was one of the main drivers for wildfire BA. In addition, machine learning was utilised in conjunction with the Quantile Regression Model (QRM) in order to quantify the relationship between sc-PDSI and wildfire BA in California. The findings provide a promising direction to improved prediction of wildfire BA which is significant in the aid of damage control of wildfires in California, potentially leading to less burned area, less economic damage, and fewer casualties.

Spatiotemporal variations and influencing factors of river dissolved oxygen in Dongguan section of Dongjiang River, Pearl River Basin

溶解氧是水生生态系统健康程度的重要度量指标，研究溶解氧时空变化及其影响因素对揭示河流溶解氧动态过程和理解水体生物地球化学循环具有重要意义. 当前，许多河流均存在溶解氧偏低问题，严重影响河流水质. 基于此，收集了珠江流域东江(东莞段)上游桥头、中游樟村和下游沙田泗盛3个水质监测站的实测资料，采用折线图和箱型图分析溶解氧在月、季节和年际时间尺度下的变化规律及其空间差异; 采用最大信息系数、交叉小波转换和多元线性回归3种方法解析溶解氧时空变化的影响因素. 结果表明：空间分布上，溶解氧浓度从上游到下游逐渐降低，低值区分布在入海口处的沙田泗盛站，多年平均溶解氧浓度仅为3.11 mg/L. 时间变化上，2011—2019年溶解氧主要在11.64个月的周期下循环变化. 溶解氧展现出明显的季节性. 3个站点丰水期溶解氧浓度比枯水期分别降低1.68、2.03和1.77 mg/L. 驱动因素上，溶解氧的时空变化受到多个因素的综合作用. 桥头站和樟村站水质较好，水温是这两个站点溶解氧时空变化的主要影响因素. 其主要在8~16个月的周期上调控溶解氧变化，在两个站点分别可以解释溶解氧整体变化的70%和57%. 沙田泗盛站受多条支流汇入的影响，水体中硝化和氧化作用耗氧增强，加之悬浮物遮光效应，使得该处的溶解氧浓度降低.;Dissolved oxygen (DO) is a vital metric indicating aquatic ecosystem health. Exploring the spatiotemporal variations and influencing factors of DO is of great significance to reveal the river DO dynamics and to understand the river biogeochemical cycle. Presently many rivers have a problem of low DO, which seriously affects the river water quality. This study collected data of three water quality monitoring stations in the upper reaches of Qiaotou, the middle reaches of Zhangcun and the lower reaches of Shatiansisheng in Dongguan section of Dongjiang River, Pearl River Basin. The DO variations on monthly, seasonal and inter-annual timescales and corresponding spatial heterogeneity were analyzed using broken line and box diagrams. Influencing factors of DO variations were explored by three approaches including maximum information coefficient, cross wavelet transform and multiple linear regression. The results showed that DO concentration gradually decreased from upstream to downstream. The low DO values (3.11 mg/L) appeared in the Shatiansisheng station near the estuary. Temporally, DO changed in a cycle of 11.64 months from 2011 to 2019, exhibiting obvious seasonality. In wet seasons DO concentrations at three stations were 1.68, 2.03 and 1.77 mg/L lower than those in dry seasons, respectively. The water qualities of Qiaotou and Zhangcun stations were better. Water temperature was the main factor affecting the spatiotemporal variations of DO in these two stations. Water temperature regulated DO changes in a cycle of 8-16 months and accounted for 70% and 57% of the total DO changes at these two stations, respectively. Impacted by multiple tributaries inflows, nitrification and oxidation processes, oxygen demands were strengthened in Shatiansisheng station, coupled with the shading effect of suspended solids, resulting in a low DO concentration.