A detrended cross-correlation analysis of meteorological and API data in Nanjing, China

Shen, Chenhua; Li, Chao-ling; Si, Ya-li

doi:10.1016/j.physa.2014.10.058

Cited by 43 publications

(14 citation statements)

References 33 publications

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“…These differences suggest that pollen signal responses to climatic influences should be considered at a taxon level rather than an assemblage level. Once longer time series data are available, a more comprehensive analysis of both inter‐ and intraannual relationships between climate parameters and airborne pollen could be carried out on all the main pollen taxa recorded in a location, such as the analysis already carried out for the air pollution index in Nanjing (Shen et al, ). From this 2‐year data set, it appears that such a study will provide valuable insights into the possible causes of variation observed in annual pollen trap data series, and thereby improved understanding of the possible mechanisms underlying longer term fluctuations in pollen concentration and influx seen in the sedimentary record.…”

Section: Analysis and Discussionmentioning

confidence: 99%

Airborne Pollen Concentration in Nanjing, Eastern China, and its Relationship With Meteorological Factors

Fang

Bunting

et al. 2018

JGR Atmospheres

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This paper presents the results of airborne pollen and spore trapping in Nanjing city, eastern China, using a Burkard pollen trap during two consecutive years (2013)(2014). A total of 103 pollen and spore taxa were identified. Two concentration peaks are observed in the annual cycle, a spring peak dominated by arboreal pollen types (Morus, Cupressaceae, Pinus, Pterocarya, and Quercus) and a fall peak dominated by upland herbs (Compositae, Poaceae, Humulus, and Cruciferae). Wetland herbs and ferns dominate summer assemblages and winter assemblages are characterized by sporadic records of Artemisia, Chenopodiaceae, and Pinus. Strong year-to-year differences in measured pollen concentration are seen, probably in response to interyear differences in weather. Compared to long-term means, 2013 was comparatively hot and dry and 2014 had a higher than average number of rain days during the flowering periods. Rising temperatures in early spring are connected with the timing of flowering and therefore pollen release, while rainfall during the flowering period appeared to remove pollen from the air, leading to lower recorded pollen concentration values. Four taxa, Cupressaceae, Quercus, Pinus, and Humulus, were considered in more detail. Each has a different pattern of variation in pollen concentration between the studied years. Cross correlation between pollen concentration and daily temperature, relative humidity, and precipitation at lags from 0 to À30 days also showed different responses for each taxon, suggesting that pollen signal responses to weather conditions have to be considered at a taxon level rather than at the assemblage level.FANG ET AL.

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Section: Analysis and Discussionmentioning

confidence: 99%

Airborne Pollen Concentration in Nanjing, Eastern China, and its Relationship With Meteorological Factors

Fang

Bunting

et al. 2018

JGR Atmospheres

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“…The length of the BFBM is 2 16 . The joint multifractal analysis of the BFBM using the MF-X-PF(p, q) algorithm is presented in figure 3.…”

Section: Joint Multifractal Analysis Of Bivariate Fractional Brownianmentioning

confidence: 99%

Joint multifractal analysis based on the partition function approach: analytical analysis, numerical simulation and empirical application

Xie

Jiang

et al. 2015

New J. Phys.

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Many complex systems generate multifractal time series which are long-range cross-correlated. Numerous methods have been proposed to characterize the multifractal nature of these long-range cross correlations. However, several important issues about these methods are not well understood and most methods consider only one moment order. We study the joint multifractal analysis based on partition function with two moment orders, which was initially invented to investigate fluid fields, and derive analytically several important properties. We apply the method numerically to binomial measures with multifractal cross correlations and bivariate fractional Brownian motions without multifractal cross correlations. For binomial multifractal measures, the explicit expressions of mass function, singularity strength and multifractal spectrum of the cross correlations are derived, which agree excellently with the numerical results. We also apply the method to stock market indexes and unveil intriguing multifractality in the cross correlations of index volatilities.

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“…To investigate multifractal characteristics of non-stationary, non-linear, natural and complex meteorological phenomenon time series (Shen et al, 2015(Shen et al, , 2017Wan et al, 2016;, the MFDFA method was proposed If the time series follow the power law, then we can obtain the scaling function:…”

Section: Description Of Mfdfa Methodsmentioning

confidence: 99%

Multi-fractal Behaviors of long term daily relative humidity and temperature observed over Benin synoptic stations (West Africa)

et al. 2019

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In this study, Multifractal Detrended Fluctuation Analysis (MFDFA) is applied to daily temperature time series in Benin synoptic stations from 1967 to 2012. The purpose is to examine the degree of multifractality and compare multifractal characteristics of temperature in various climatic areas (subequatorial and Sudanian). The analysis reveals that the daily temperature time series shows a multifractal behavior that is sensitive to the station's geographic position and presents a positive long-term correlation. Weather conditions and the geographic position of the synoptic stations affect the shape and the characteristics of temperature spectrum. The multifractality is stronger in subequatorial region than the Sudanian. The major source of multifractality in temperature series is found to be the fat-tailed probability density function. However, long-range correlations also partly contribute to the multifractal features. Except Kandi's synoptic station, the spectrum is left-skewed. The findings indicate the usefulness of the non-linear analysis in climate research due to the complex interactions among the natural processes. It can help understand the mechanisms governing the dynamics of temperature time series in Benin.Comportamientos multifractales de las series temporales de temperatura observadas en las estaciones sinópticas de Benin (Africa Occidental)

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A detrended cross-correlation analysis of meteorological and API data in Nanjing, China

Cited by 43 publications

References 33 publications

Airborne Pollen Concentration in Nanjing, Eastern China, and its Relationship With Meteorological Factors

Airborne Pollen Concentration in Nanjing, Eastern China, and its Relationship With Meteorological Factors

Joint multifractal analysis based on the partition function approach: analytical analysis, numerical simulation and empirical application

Multi-fractal Behaviors of long term daily relative humidity and temperature observed over Benin synoptic stations (West Africa)

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