scholarly journals Fractal analysis: Annual rainfall in Chennai

MAUSAM ◽  
2021 ◽  
Vol 61 (1) ◽  
pp. 35-38
Author(s):  
R. SAMUEL SELVARAJ ◽  
S. TAMILSELVI ◽  
R. GAYATHRI
Keyword(s):  
Lyapunov Exponent ◽  
Fractal Analysis ◽  
Fractal Geometry ◽  
Characteristic Exponent ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Fractional Dimension ◽  
Construction Technique ◽  
Lyapunov Characteristic Exponent ◽  
Lyapunov Time

The annual rainfall data of Chennai is analyzed using the Fractal Construction Technique. According to Mandelbrot the dimension of any line including nautical lines may not be Euclidean but Fractional, Mandelbrot, 1982. This fractional dimension leads to a repetitive appearance of any pattern. Climate which is usually periodic by nature can be analyzed through this technique. Efforts are on to search the fractal geometry of climate and to predict its periodicity on different temporal scales. This paper estimates the various parameters like Lyapunov exponent, Maximum Lyapunov characteristic exponent, Lyapunov time, Kaplan-Yorke dimension for the annual rainfall of Chennai.

Optimal Density Determination of Bouguer Anomaly Using Fractal Analysis (Case of study: Charak area,IRAN)

2005 ◽  
Vol 1 (1) ◽  
pp. 21-24
Author(s):  
Hamid Reza Samadi
Keyword(s):  
Surface Roughness ◽  
Fractal Dimension ◽  
Fractal Analysis ◽  
Fractal Geometry ◽  
Host Rock ◽  
Bouguer Anomaly ◽  
Research Area ◽  
Density Difference ◽  
Optimal Density

In exploration geophysics the main and initial aim is to determine density of under-research goals which have certain density difference with the host rock. Therefore, we state a method in this paper to determine the density of bouguer plate, the so-called variogram method based on fractal geometry. This method is based on minimizing surface roughness of bouguer anomaly. The fractal dimension of surface has been used as surface roughness of bouguer anomaly. Using this method, the optimal density of Charak area insouth of Hormozgan province can be determined which is 2/7 g/cfor the under-research area. This determined density has been used to correct and investigate its results about the isostasy of the studied area and results well-coincided with the geology of the area and dug exploratory holes in the text area

COLONY OF THE FUNGUS Aspergillus oryzae AND SELF-AFFINE FRACTAL GEOMETRY OF GROWTH FRONTS

Fractals ◽  
1993 ◽  
Vol 01 (01) ◽  
pp. 11-19 ◽  
Author(s):  
SHU MATSUURA ◽  
SASUKE MIYAZIMA
Keyword(s):  
Aspergillus Oryzae ◽  
Environmental Conditions ◽  
Fractal Geometry ◽  
Nutrient Concentration ◽  
Incubation Temperature ◽  
Characteristic Exponent ◽  
Growth Front ◽  
Favorable Condition ◽  
The Self ◽  
The Mean

A variety of colony shapes of the fungus Aspergillus oryzae under varying environmental conditions such as the nutrient concentration, medium stiffness and incubation temperature are obtained, ranging from a homogeneous Eden-like to a ramified DLA-like pattern. The roughness σ(l, h) of the growth front of the band-shaped colony, where h is the mean front height within l of the horizontal range, satisfies the self-affine fractal relation under favorable environmental conditions. In the most favorable condition of our experiments, its characteristic exponent is found to be a little larger than that of the 2-dimensional Eden model.

Fractal analysis and control of the competition model

2016 ◽  
Vol 09 (03) ◽  
pp. 1650045 ◽  
Author(s):  
Mianmian Zhang ◽  
Yongping Zhang
Keyword(s):  
Feedback Control ◽  
Mathematical Models ◽  
Fractal Analysis ◽  
Fractal Geometry ◽  
Julia Set ◽  
Julia Sets ◽  
Competition Model ◽  
Simulation Results ◽  
Population Competition ◽  
And Control

Lotka–Volterra population competition model plays an important role in mathematical models. In this paper, Julia set of the competition model is introduced by use of the ideas and methods of Julia set in fractal geometry. Then feedback control is taken on the Julia set of the model. And synchronization of two different Julia sets of the model with different parameters is discussed, which makes one Julia set change to be another. The simulation results show the efficacy of these methods.

scholarly journals Performance of TRMM TMPA 3B42 V7 in Replicating Daily Rainfall and Regional Rainfall Regimes in the Amazon Basin (1998–2013)

2018 ◽  
Vol 10 (12) ◽  
pp. 1879 ◽  
Author(s):  
Véronique Michot ◽  
Daniel Vila ◽  
Damien Arvor ◽  
Thomas Corpetti ◽  
Josyane Ronchail ◽  
...  
Keyword(s):  
Amazon Basin ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Spatial Coverage ◽  
Rainfall Regimes ◽  
Trmm 3B42 ◽  
Good Agreement

Knowledge and studies on precipitation in the Amazon Basin (AB) are determinant for environmental aspects such as hydrology, ecology, as well as for social aspects like agriculture, food security, or health issues. Availability of rainfall data at high spatio-temporal resolution is thus crucial for these purposes. Remote sensing techniques provide extensive spatial coverage compared to ground-based rainfall data but it is imperative to assess the quality of the estimates. Previous studies underline at regional scale in the AB, and for some years, the efficiency of the Tropical Rainfall Measurement Mission (TRMM) 3B42 Version 7 (V7) (hereafter 3B42) daily product data, to provide a good view of the rainfall time variability which is important to understand the impacts of El Nino Southern Oscilation. Then our study aims to enhance the knowledge about the quality of this product on the entire AB and provide a useful understanding about his capacity to reproduce the annual rainfall regimes. For that purpose we compared 3B42 against 205 quality-controlled rain gauge measurements for the period from March 1998 to July 2013, with the aim to know whether 3B42 is reliable for climate studies. Analysis of quantitative (Bias, Relative RMSE) and categorical statistics (POD, FAR) for the whole period show a more accurate spatial distribution of mean daily rainfall estimations in the lowlands than in the Andean regions. In the latter, the location of a rain gauge and its exposure seem to be more relevant to explain mismatches with 3B42 rather than its elevation. In general, a good agreement is observed between rain gauge derived regimes and those from 3B42; however, performance is better in the rainy period. Finally, an original way to validate the estimations is by taking into account the interannual variability of rainfall regimes (i.e., the presence of sub-regimes): four sub-regimes in the northeast AB defined from rain gauges and 3B42 were found to be in good agreement. Furthermore, this work examined whether TRMM 3B42 V7 rainfall estimates for all the grid points in the AB, outgoing longwave radiation (OLR) and water vapor flux patterns are consistent in the northeast of AB.

scholarly journals Climatologia da pluviometria do município de Teresina, Piauí, Brasil

2016 ◽  
Vol 11 (4) ◽  
pp. 135
Author(s):  
Hudson Ellen Alencar Menezes ◽  
Raimundo Mainar de Medeiros ◽  
José Lucas Guilherme Santos
Keyword(s):  
Water Resources ◽  
Rainfall Variability ◽  
Intertropical Convergence Zone ◽  
Atmospheric Dynamics ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Convergence Zone ◽  
Northeast Brazil ◽  
Urban Structures ◽  
Urbanized Areas

<p>As variações nas precipitações refletem claramente a dinâmica atmosférica da região, marcada pela intensa variabilidade, onde se observa a atuação da Zona de Convergência Intertropical (ZCIT) com sua atuação entre os meses de janeiro a março, sendo esse período mais chuvoso. As variabilidades espaço temporal no comportamento das chuvas tem sido analisadas e diagnosticadas por vários autores no Nordeste do Brasil (NEB), portanto objetivou-se diagnosticar a variabilidade dos índices pluviométricos em Teresina no Estado do Piauí no período de 1913 a 2010. A análise do comportamento da precipitação nas cidades de grande e médio porte é de extrema importância para o gerenciamento dos recursos hídricos, uma vez que se trata de áreas densamente urbanizadas. Muitas vezes, sem uma estruturação urbana adequada, estas cidades se encaixam perfeitamente nesse contexto. Foram utilizados dados mensais observados e anuais de precipitação pluviométrica no período de 1913 a 2010, com 97 anos de observações. Os resultados mostraram a recorrência de valores máximos de precipitação anual dentro de um intervalo de 18, 11 e 8 anos. Na análise dos desvios-padrões, os resultados mostraram predominância dos desvios negativos em relação aos desvios positivos.</p><p align="center"><strong><em>Climatology of rainfall in the Teresina city, Piauí state, Brazil</em></strong></p><p>Variations in precipitation clearly reflect the atmospheric dynamics of the region, marked by intense variability, where we observe the performance of the Intertropical Convergence Zone (ITCZ) with his performance in the months of January-March, this being more rain tem period. The timeline of rainfall variability in behavior has been analyzed and diagnosed by several authors in Northeast Brazil (NEB), so let's study this variability between the periods 1913 to 2010 of Teresina city.  The behavior of rainfall in cities large and medium sized is of utmost importance to the managerial of water resources, since it is densely urbanized areas. Often without adequate urban structures these cities fit perfectly in this context. We used observed monthly and annual rainfall data for the period 1913-2010, 97 years of observations. The results showed recurrence of maximum values of annual precipitation an interval of 18, 11 and 8 years. In the analysis of standard deviations, the results showed a predominance of negative deviations from the positive deviations.<strong></strong></p><p align="center"><strong><em><br /></em></strong></p>

scholarly journals Architecture of Artificial Neural Network in Identification of Internal Dynamics and Prediction of Dynamic System Rainfall Data Time Series

2012 ◽  
pp. 34-42
Author(s):  
Sanjeev Karmakar ◽  
Manoj Kumar Kowar ◽  
Pulak Guhathakurta
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Artificial Neural Network ◽  
Dynamic System ◽  
Long Range ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Global Minima ◽  
Internal Dynamics ◽  
Artificial Neural

The objective of this study is to expand and evaluate the back-propagation artificial neural network (BPANN) and to apply in the identification of internal dynamics of very high dynamic system such long-range total rainfall data time series. This objective is considered via comprehensive review of literature (1978-2011). It is found that, detail of discussion concerning the architecture of ANN for the same is rarely visible in the literature; however various applications of ANN are available. The detail architecture of BPANN with its parameters, i.e., learning rate, number of hidden layers, number of neurons in hidden layers, number of input vectors in input layer, initial and optimized weights etc., designed learning algorithm, observations of local and global minima, and results have been discussed. It is observed that obtaining global minima is almost complicated and always a temporal nervousness. However, achievement of global minima for the period of the training has been discussed. It is found that, the application of the BPANN on identification for internal dynamics and prediction for the long-range total annual rainfall has produced good results. The results are explained through the strong association between rainfall predictors i.e., climate parameter (independent parameter) and total annual rainfall (dependent parameter) are presented in this paper as well.

scholarly journals Rainfall Trend and Its Relationship with Normalized Difference Vegetation Index in a Restored Semi-Arid Wetland of South Africa

2020 ◽  
Vol 12 (21) ◽  
pp. 8919
Author(s):  
Florence M. Murungweni ◽  
Onisimo Mutanga ◽  
John O. Odiyo
Keyword(s):  
South Africa ◽  
Quantile Regression ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Rainfall Data ◽  
Ecosystem Change ◽  
Annual Rainfall ◽  
Rainfall Trend ◽  
Vegetation Productivity ◽  
Rainfall Trends

Clearance of terrestrial wetland vegetation and rainfall variations affect biodiversity. The rainfall trend–NDVI (Normalized Difference Vegetation Index) relationship was examined to assess the extent to which rainfall affects vegetation productivity within Nylsvley, Ramsar site in Limpopo Province, South Africa. Daily rainfall data measured from eight rainfall stations between 1950 and 2016 were used to generate seasonal and annual rainfall data. Mann-Kendall and quantile regression were applied to assess trends in rainfall data. NDVI was derived from satellite images from between 1984 and 2003 using Zonal statistics and correlated with rainfall of the same period to assess vegetation dynamics. Mann-Kendall and Sen’s slope estimator showed only one station had a significant increasing rainfall trend annually and seasonally at p < 0.05, whereas all the other stations showed insignificant trends in both rainfall seasons. Quantile regression showed 50% and 62.5% of the stations had increasing annual and seasonal rainfall, respectively. Of the stations, 37.5% were statistically significant at p < 0.05, indicating increasing and decreasing rainfall trends. These rainfall trends show that the rainfall of Nylsvley decreased between 1995 and 2003. The R2 between rainfall and NDVI of Nylsvley is 55% indicating the influence of rainfall variability on vegetation productivity. The results underscore the impact of decadal rainfall patterns on wetland ecosystem change.

A comparison of weather systems in 1870 and 1956 leading to extreme floods in the Murray–Darling Basin

2019 ◽  
Vol 69 (1) ◽  
pp. 84
Author(s):  
Jeff Callaghan
Keyword(s):  
19Th Century ◽  
Heavy Rainfall ◽  
Southern Oscillation ◽  
Linear Trend ◽  
Meteorological Data ◽  
Middle Level ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Murray Darling Basin ◽  
The Impact

This research is the extension of a project studying the impact of 19th century severe weather events in Australia and their relation to similar events during the 20th and 21st century. Two floods with the worst known impacts in the Murray–Darling Basin (MDB) are studied. One of these events which occurred during 1956 is relativelywell known and the Bureau of Meteorology archives contain good rainfall data covering the period. Additionally, information on the weather systems causing this rainfall can be obtained. Rainfall, flood and weather system data for this event are presented here and compared with a devastating event during 1870. Although archived Australian rainfall data is negligible during 1870 and there is no record of weather systems affecting Australia during that year, a realistic history of the floods and weather systems in the MDB during 1870 is created. This follows an extensive search through newspaper archives contained in the National Library of Australia’s web site. Examples are presented showing how the meteorological data in 19th century newspapers can be used to create weather charts. Six such events in 1870 are demonstrated and three of these had a phenomenal effect on the Murray–Darling system. The 1870 floods followed drought type conditions and it is remarkable that it was worse in many ways than the 1956 event which followed flood conditions in the MDB during the previous year. The events in 1870 caused much loss of life from drowning in the MDB in particular froman east coast low (ECL) in April 1870 and two Victorian weather systems in September and October 1870. In 1956, there were also record-breaking events especially during March when all-time record monthly rainfall were reported in New South Wales. Overall the greatest impact from flooding across the whole MDB was associated with the 1870 flooding. Analyses of heavy rainfall areas in the MDB showed a linear trend increase from 1900 to 2018. Analysing the same data using an 8-year moving average highlighted three peaks around the five highest annual rainfall years. The largest peak occurred around 1950 and 1956, the second largest around 1973 and 1974 and the third around 2010. Each of these 5 years occurred during negative phases of the Interdecadal Pacific Oscillation (IPO) and positive phases of the Southern Oscillation Index (SOI). Studies have shown that the SOI is a climate driver in the MDB along with a persistent blocking high-pressure systems south of Australia along longitude 140°E with a low to its north. Three major blocking events with record rainfall and flooding in the MDB occurred in 1983, 1984 and 1990. Thiswas during the period 1977–1990 when blocking was conducive to heavy rain in the MDB and was coincidentwith a positive phase of the IPO, thus helping conflictwith the IPO–MDB heavy rainfall relationship. Persistent and unexplained middle level westerly winds kept subtropical Queensland clear of tropical cyclones during the negative phases of the IPO from 1999 to 2009 and during the 1960s, influencing low rainfall in the MDB during those periods.

scholarly journals Spatial and Temporal Rainfall Variability over the Mountainous Central Pindus (Greece)

Climate ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 75 ◽  
Author(s):  
Stefanos Stefanidis ◽  
Dimitrios Stathis
Keyword(s):  
Multiple Regression ◽  
Rainfall Variability ◽  
Multiple Regression Model ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Spatial And Temporal Variability ◽  
Mountain Range ◽  
Rainfall Time Series ◽  
Distribution Maps ◽  
Mountainous Catchment

In this study, the authors evaluated the spatial and temporal variability of rainfall over the central Pindus mountain range. To accomplish this, long-term (1961–2016) monthly rainfall data from nine rain gauges were collected and analyzed. Seasonal and annual rainfall data were subjected to Mann–Kendall tests to assess the possible upward or downward statistically significant trends and to change-point analyses to detect whether a change in the rainfall time series mean had taken place. Additionally, Sen’s slope method was used to estimate the trend magnitude, whereas multiple regression models were developed to determine the relationship between rainfall and geomorphological factors. The results showed decreasing trends in annual, winter, and spring rainfalls and increasing trends in autumn and summer rainfalls, both not statistically significant, for most stations. Rainfall non-stationarity started to occur in the middle of the 1960s for the annual, autumn, spring, and summer rainfalls and in the early 1970s for the winter rainfall in most of the stations. In addition, the average magnitude trend per decade is approximately −1.9%, −3.2%, +0.7%, +0.2%, and +2.4% for annual, winter, autumn, spring, and summer rainfalls, respectively. The multiple regression model can explain 62.2% of the spatial variability in annual rainfall, 58.9% of variability in winter, 75.9% of variability in autumn, 55.1% of variability in spring, and 32.2% of variability in summer. Moreover, rainfall spatial distribution maps were produced using the ordinary kriging method, through GIS software, representing the major rainfall range within the mountainous catchment of the study area.

Application of Fractal Geometry to Fracture Forensics, Research and Production

2006 ◽  
Vol 45 ◽  
pp. 1646-1651 ◽  
Author(s):  
J.J. Mecholsky Jr.
Keyword(s):  
Fractal Analysis ◽  
Fractal Geometry ◽  
Crack Size ◽  
Structural Parameter ◽  
New Materials ◽  
Scale Invariant ◽  
Prepared Material ◽  
Reasonable Approach ◽  
Self Similar ◽  
Production Problems

The fracture surface records past events that occur during the fracture process by leaving characteristic markings. The application of fractal geometry aids in the interpretation and understanding of these events. Quantitative fractographic analysis of brittle fracture surfaces shows that these characteristic markings are self-similar and scale invariant, thus implying that fractal analysis is a reasonable approach to analyzing these surfaces. The fractal dimensional increment, D*, is directly proportional to the fracture energy, γ, during fracture for many brittle materials, i.e., γ = ½ E a0 D* where E is the elastic modulus and a0 is a structural parameter. Also, D* is equal to the crack-size-to-mirror-radius ratio. Using this information can aid in identifying toughening mechanisms in new materials, distinguishing poorly fabricated from well prepared material and identifying stress at fracture for field failures. Examples of the application of fractal analysis in research, fracture forensics and solving production problems are discussed.

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