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RAGHAVENDRA, V. K. "Trends and periodicities of rainfall in sub-divisions of Maharashtra State." MAUSAM 25, no. 2 (February 7, 2022): 197–210. http://dx.doi.org/10.54302/mausam.v25i2.5194.
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The Maharashtra State of India is divided into four meteorological sub-divisions, viz., Konkan, Madhya Maharashtra, Marathwada and Vidarbha. Of these, Madhya Maharashtra and Marathwada are prone to droughts. The principal rainy season is the monsoon season of June to September when over 80 per cent of the annual rainfall is received. The coefficient of variation is about 20 per cent for the annual and monsoon rainfall except in Marathwada where it is 25 per cent. The annual and monsoon rainfalls follow the normal distribution for their yearly frequencies. In this region the annual and the monsoon rainfall series are highly correlated. In the loss drought prone sub-division of Konkan, the annual and monsoon rainfalls show a 100 year cycle. In all the sub-divisions the successive years' rainfalls are not dependent. The trend as revealed by fitting of orthogonal polynomials is shown as a quadratic curve for the annual and monsoon rainfalls of Konkan and Madhya, Maharashtra, the sub-divisions on either side of the Western Ghats. The low pass filter and Mann-Kendall test against randomness confirmed the trend in Konkan rainfall. The power spectral analysis of the data indicates the existence of long term trend for monsoon rainfall of Konkan, 60 year cycle for the annual rainfall of Konkan and Madhya Maharashtra, 30.year cycle for the annual and monsoon rainfall or Vidarbha, 20-year cycle for the monsoon rainfall of Marathwada, 15-year cycle for the monsoon rainfall of Madhya Maharashtra, 7.5-year cycle for the annual and monsoon rainfall of Marathwada.
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Stefanidis, Stefanos, and Dimitrios Stathis. "Spatial and Temporal Rainfall Variability over the Mountainous Central Pindus (Greece)." Climate 6, no. 3 (September 6, 2018): 75. http://dx.doi.org/10.3390/cli6030075.
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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.
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Liao, Yifan, Bingzhang Lin, Xiaoyang Chen, and Hui Ding. "A New Look at Storm Separation Technique in Estimation of Probable Maximum Precipitation in Mountainous Areas." Water 12, no. 4 (April 20, 2020): 1177. http://dx.doi.org/10.3390/w12041177.
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Storm separation is a key step when carrying out storm transposition analysis for Probable Maximum Precipitation (PMP) estimation in mountainous areas. The World Meteorological Organization (WMO) has recommended the step-duration-orographic-intensification-factor (SDOIF) method since 2009 as an effective storm separation technique to identify the amounts of precipitation caused by topography from those caused by atmospheric dynamics. The orographic intensification factors (OIFs) are usually developed based on annual maximum rainfall series under such assumption that the mechanism of annual maximum rainfalls is close to that of the PMP-level rainfall. In this paper, an alternative storm separation technique using rainfall quantiles, instead of annual maximum rainfalls, with rare return periods estimated via Regional L-moments Analysis (RLMA) to calculate the OIFs is proposed. Based on Taiwan’s historical 4- and 24-h precipitation data, comparisons of the OIFs obtained from annual maximum rainfalls with that from extreme rainfall quantiles at different return periods, as well as the PMP estimates of Hong Kong from transposing the different corresponding separated nonorographic rainfalls, were conducted. The results show that the OIFs obtained from rainfall quantiles with certain rare probabilities are more stable and reasonable in terms of stability and spatial distribution pattern.
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Ledingham, Jamie, David Archer, Elizabeth Lewis, Hayley Fowler, and Chris Kilsby. "Contrasting seasonality of storm rainfall and flood runoff in the UK and some implications for rainfall-runoff methods of flood estimation." Hydrology Research 50, no. 5 (August 14, 2019): 1309–23. http://dx.doi.org/10.2166/nh.2019.040.
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Abstract Using data from 520 gauging stations in Britain and gridded rainfall datasets, the seasonality of storm rainfall and flood runoff is compared and mapped. Annual maximum (AMAX) daily rainfall occurs predominantly in summer, but AMAX floods occur most frequently in winter. Seasonal occurrences of annual daily rainfall and flood maxima differ by more than 50% in dry lowland catchments. The differences diminish with increasing catchment wetness, increase with rainfalls shorter than daily duration and are shown to depend primarily on catchment wetness, as illustrated by variations in mean annual rainfall. Over the whole dataset, only 34% of AMAX daily flood events are matched to daily rainfall annual maxima (and only 20% for 6-hour rainfall maxima). The discontinuity between rainfall maxima and flooding is explained by the consideration of coincident soil moisture storage. The results have serious implications for rainfall-runoff methods of flood risk estimation in the UK where estimation is based on a depth–duration–frequency model of rainfall highly biased to summer. It is concluded that inadequate treatment of the seasonality of rainfall and soil moisture seriously reduces the reliability of event-based flood estimation in Britain.
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Ologeh, I., and F. Adesina. "Evaluation of climate change as a major determinant of crop yield improvement in Nigeria." IOP Conference Series: Earth and Environmental Science 1077, no. 1 (September 1, 2022): 012002. http://dx.doi.org/10.1088/1755-1315/1077/1/012002.
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Abstract Climate change has adversely affected agricultural productivity leading to decline in food production. The influence of climate change on crops and livestock persists despite irrigation, improved plant and animal hybrids. The continued dependence of agricultural production on climatic factors and the relative dependence of human existence on agricultural products create the need for a comprehensive consideration of the relationship between climate and crop production. This study measured the relationship between annual maize/yam yield as dependent variable and seasonal rainfall as independent variables in four states in Nigeria. It has been proven in the past that yearly rainfall value has no influence on annual crop yield, but seasonal or monthly rainfall does. There is a positive and significant relationship between summed up rainfalls of June/July/August and annual maize yields for the thirty-five years under study. The bi-monthly rainfall values did not influence a major part of total annual maize yield, as it records weak relationship with annual maize yield. On the other hand, bi-monthly rainfall values (May/June and July/August) have positive and significant relationship with annual yam yield. The first quarter- March/April/May rainfall values for each of the states have a positive and significant relationship with annual yam yield. This implies that the rainfall value for this quarter is very essential for annual yam yield for each of the states.
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Junges, Amanda H., Carolina Bremm, and Denise C. Fontana. "Rainfall climatology, variability, and trends in Veranópolis, Rio Grande do Sul, Brazil." Revista Brasileira de Engenharia Agrícola e Ambiental 23, no. 3 (March 2019): 160–66. http://dx.doi.org/10.1590/1807-1929/agriambi.v23n3p160-166.
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ABSTRACT The objective of this study was to characterize the rainfall climatology in Veranópolis, Rio Grande do Sul, Brazil, through analyses of means, variabilities related to El Niño Southern Oscillation (ENSO), and temporal trends, using a 60-year data series (1956-2015). Descriptive statistics of annual, monthly and seasonal rainfall were used to characterize the rainfall climatology. The differences between seasons, and influence of ENSO were evaluated using analysis of variance and the Duncan’s test. Rainfall trends were evaluated by the Mann Kendall test. The local average annual rainfall is 1,683 mm and the average monthly rainfall is 140 mm, varying from 109 (May) to 182 mm (September). The annual rainfall has high interannual (standard deviation of 327 mm), monthly (60-100 mm) and seasonal (124-183 mm) variabilities, which should be considered in non-irrigated agricultural systems using rainfall as the main source of water supply to plants. Although autumn presents lower average rainfall (346 mm) than the other seasons, its average percentages were similar to the total annual rainfall (21-28%), and the rainfalls are well-distributed in the seasons. Differences between ENSO events occurred in the spring; La Niña years showed lower rainfall (385 mm) than El Niño (549 mm) and neutral (481 mm) years. The annual rainfall tended to increase by 6.3 mm per year (p < 0.01), with increases of 2.5 mm in spring and 1.9 mm in winter (p < 0.10) in the period analyzed.
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Dr., A. I. Khan, and T. Gaikwad Vipul. "Rainfall Trend in Drought Prone Region of Ahmednagar District of Maharashtra in India: A Geographical Study." International Journal of Advance and Applied Research 4, no. 1 (January 19, 2023): 46–50. https://doi.org/10.5281/zenodo.7546328.
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In this paper the present study reveals the tehsil wise annual rainfall trend in Ahmednagar District of Maharashtra State during 1984 to 2018. The rainfall is one of the significant parameters among the climate for the development of society. They determine the scarcity of particular region. The rate of rainfall is varied in different region. The average annual rainfall in the Ahmednagar district varies from about 625.09 mm to 405.3; some area has been traditionally affected by drought. The large area of the district comes under the agriculture due to large population depend on agricultural for employment. This study focusses on the nine (out of total 14) tahsils in Ahmednagar district which is particularly sensitive to drought Karjat, Jamkhed, Shrirampur, Sangamner, Shrigonda, Newasa, Shevgaon, Parner tahsils. The aim of this research to understand trends of rainfall Ahmednagar district. In a study on tahsil wise trend analysis nine tahsils had decreasing trend in annual rainfall. Among two tahsils showing increasing trend, Akole tahsil shows highest rainfall trend. Remaining three tahsil had the same direction of trend in annual rainfall and seasonal scale.
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Whitehead, Peter J., Jeremy Russell-Smith, and Cameron Yates. "Fire patterns in north Australian savannas: extending the reach of incentives for savanna fire emissions abatement." Rangeland Journal 36, no. 4 (2014): 371. http://dx.doi.org/10.1071/rj13129.
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Anthropogenic fires in Australia’s fire-prone savannas produce up to 3% of the nation’s accountable greenhouse gas (GHG) emissions. Incentives to improve fire management have been created by a nationally accredited savanna burning emissions abatement methodology applying to 483 000 km2 of relatively high-rainfall (>1000 mm p.a.) regions. Drawing on 15 years of fire mapping, this paper assesses appropriate biophysical boundaries for a savanna burning methodology extended to cover lower-rainfall regions. We examine a large random sample of points with at least 300 mm of annual rainfall, to show that: (a) relative fire frequencies (percentage of years with fire) decline from 33.3% in higher-rainfall regions (>1000 mm) to straddling ~10% in the range 300–700 mm; (b) there are no marked discontinuities in fire frequency or fire seasonality down the rainfall gradient; (c) at all annual rainfalls, fire frequency is higher when rainfall is more strongly seasonal (very low rainfall in the driest quarter); (d) below 500 mm fire regimes are particularly variable and a large proportion of sampled sites had no fire over the study period; (e) fire is more likely to occur later in the fire season (generating relatively higher emissions) in the 600–700-mm annual rainfall band than in other parts of the rainfall gradient; (f) woodland savannas are most common above and predominantly grassland systems are more common below ~600-mm annual rainfall. We propose that development of a complementary lower-rainfall savanna burning methodology apply to regions between 600 and 1000-mm annual rainfall and ≤15 mm of rainfall in the driest quarter, adding an area more than 1.5 times the existing methodology’s coverage. Given greater variability in biophysical influences on fire regimes and observed levels of fire frequency within this lower-rainfall domain, we suggest that criteria for determining baseline (pre-project) periods require estimates of mean annual emissions equivalent in precision to the project on which the higher-rainfall methodology was based.
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Manike, M. M. A. P., and M. Rajendran. "Analysis of Rainfall Distribution in Kurunegala District, Sri Lanka." Asian Journal of Research in Agriculture and Forestry 10, no. 1 (February 12, 2024): 48–60. http://dx.doi.org/10.9734/ajraf/2024/v10i1268.
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Investigating the dynamics of rainfall has become very crucial in managing water resources efficiently for sustainable development. The present study aimed to analyze the rainfall distribution in Kurunegala district. Historical rainfall data collected from four gauging stations were subjected to both mathematical and statistical analysis. In addition, trends of rainfall, probability of exceedance and meteorological drought conditions were studied. Rainfall distribution in the district shows high variations. Bathalagoda records the highest mean annual rainfall of 1843 mm. The corresponding values for Wariyapola, Mediyawa and Siyambalagamuwa are 1629 mm, 1315 mm and 1222 mm, respectively. Rainfall is concentrated only in certain months in a year. Annual rainfall exceedance at 50% probability is 1825 mm at Bathalagoda. The corresponding figures for Wariyapola, Mediyawa and Siyambalagamuwa are 1662 mm, 1284 mm and 1226 mm, respectively. Mediyawa, Wariyapola, and Siyambalagamuwa show a decreasing trend in annual rainfall while Bathalagoda shows an increasing trend. Southwest monsoonal (SWM) and 2nd inter-monsoonal (IM2) rainfalls show a decreasing trend at all gauging stations. Mediyawa and Bathalagoda show a positive trend in both 1st inter-monsoonal (IM1) and Northeast monsoonal (NEM) rainfalls. A negative trend in Maha seasonal rainfall is observed in all regions except Bathalagoda. A positive trend of Yala seasonal rainfall is observed at Mediyawewa and Bathalogoda. Further, severe drought conditions were experienced in the recent years at Wariyapola, Mediyawa, and Siyambalagamuwa. Compared to other regions, rainfall at Mediyawa and Siyambalagamuwa highly deviates from the long-term mean. In the study area, rainfall distribution shows a cyclic pattern over time. However, the amount of rainfall received in the recent years is lower than the amount received in the immediate past decade at all stations except Bathalagoda. Hence, proper management decisions based on rainfall distribution patterns is vital for the efficient management of water resources while guaranteeing sustainable agricultural production in this district.
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Yoo, Chul-Sang, and Cheol-Soon Park. "Comparison of Annual Maximum Rainfall Series and Annual Maximum Independent Rainfall Event Series." Journal of Korea Water Resources Association 45, no. 5 (May 31, 2012): 431–44. http://dx.doi.org/10.3741/jkwra.2012.45.5.431.
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Miguel, Edward, and Shanker Satyanath. "Re-examining Economic Shocks and Civil Conflict." American Economic Journal: Applied Economics 3, no. 4 (October 1, 2011): 228–32. http://dx.doi.org/10.1257/app.3.4.228.
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Miguel, Satyanath, and Ernest Sergenti (2004), henceforth MSS, show that economic growth is negatively related to civil conflict in Africa, using annual rainfall variation as an IV for growth. Antonio Ciccone (2011) argues that thanks to rainfall's mean-reverting nature, rainfall levels are preferable to annual changes. We make three points. First, MSS's findings hold using rainfall levels as instruments. Second, Ciccone (2011) does not provide theoretical justification for preferring rainfall levels. Third, the first-stage relationship between rainfall and growth is weaker after 2000, suggesting that alternative instruments are needed when studying recent conflicts. We highlight the accumulating microeconomic evidence that adverse economic shocks lead to political violence. (JEL D74, E32, O11, O17, O47)
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SEETHARAM, K. "Rainfall models – a study over Gangtok." MAUSAM 61, no. 2 (November 27, 2021): 225–28. http://dx.doi.org/10.54302/mausam.v61i2.819.
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In this paper, the Pearsonian system of curves were fitted to the monthly rainfalls from January to December, in addition to the seasonal as well as annual rainfalls totalling to 14 data sets of the period 1957-2005 with 49 years of duration for the station Gangtok to determine the probability distribution function of these data sets. The study indicated that the monthly rainfall of July and summer monsoon seasonal rainfall did not fit in to any of the Pearsonian system of curves, but the monthly rainfalls of other months and the annual rainfalls of Gangtok station indicated to fit into Pearsonian type-I distribution which in other words is an uniform distribution. Anderson-Darling test was applied to for null hypothesis. The test indicated the acceptance of null-hypothesis. The statistics of the data sets and their probability distributions are discussed in this paper.
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Mondal, M. Shahjahan, Sara Nowreen, and Mostofa Najmus Sakib. "Scale-Dependent Reliability of Projected Rainfalls over Bangladesh with the PRECIS Model." Climate 8, no. 2 (January 27, 2020): 20. http://dx.doi.org/10.3390/cli8020020.
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The regional climate model, Providing REgional Climates for Impact Studies (PRECIS), has been widely used throughout the world to generate climate change projections for impact studies and adaptations. Its recent application in South Asia also includes the projection of rainfall extremes. In spite of its wide application, a stringent validation of the model is yet to be reported. In this study, we assessed the performance of the model in simulating annual, monthly and extreme rainfalls over Bangladesh by using a number of statistical techniques, e.g., pattern (both spatial and temporal) correlation, root mean square difference (RMSD), mean absolute difference (MAD), Student’s t-test for significance, probability density functions, etc. The results indicated that the PRECIS model could capture the overall spatial pattern of mean annual and monthly rainfalls very well. However, the inter-annual variability was poorly simulated by the model. In addition, the model could not capture the rainfall extremes. A spatial aggregation of rainfall data did not improve the reliability of the model as far as variability and extremes are concerned. Therefore, further improvements of the model and/or its driving global climate model are warranted for its practical use in the generation of rainfall scenarios.
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Brychta, Jiří, and Miloslav Janeček. "Determination of erosion rainfall criteria based on natural rainfall measurement and its impact on spatial distribution of rainfall erosivity in the Czech Republic." Soil and Water Research 14, No. 3 (May 27, 2019): 153–62. http://dx.doi.org/10.17221/91/2018-swr.
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Rainfall erosivity is the main factor of the USLE or RUSLE equations. Its accuracy depends on recording precision and its temporal resolution, number of stations and their spatial distribution, length of recorded period, recorded period, erosion rainfall criteria, time step of rainfall intensity and interpolation method. This research focuses on erosion rainfall criteria. A network of 32 ombrographic stations, 1-min temporal resolution rainfall data, 35.6-year period and experimental runoff plots were used. We analysed 8951 rainfalls from ombrographic stations, 100 rainfalls and caused soil losses and runoffs from experimental runoff plots. Main parameter which influenced the number of erosion rainfalls was the precondition AND/OR which determines if conditions of rainfall total (H) have to be fulfilled simultaneously with rainfall intensity (I<sub>15</sub> or I<sub>30</sub>) or not. We proved that if parameters I<sub>15 </sub>&gt; 6.25 mm/15 min AND H &gt; 12.5 mm were fulfilled, then 84.2% of rainfalls caused soil loss &gt; 0.5 t/ha and 73.7% ≥ 1 t/ha. In the case of precondition OR only 44.6% of rainfalls caused soil loss &gt; 0.5 t/ha and 33.9% ≥ 1 t/ha. If the precondition AND was fulfilled, there were on average 75.5 rainfalls, average R factor for each rainfall was 21 MJ/ha·cm/h (without units below in the text, according international unit: 210 MJ/ha·mm/h) and average annual R factor was 45.4. In the case of precondition OR there were on average 279 rainfalls but average R factor for each rainfall was only 9.1 and average annual R factor was 67.4. Therefore if the precondition OR is used, R factor values are overestimated due to a high number of rainfalls with no or very low erosive potential. The resulting overestimated soil losses calculated using USLE/RUSLE subsequently cause an overestimation of financial expenses for erosion-control measures.
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Ahmad, Aimi Athirah, Fadhilah Yusof, Muhamad Radzali Mispan, and Hasliana Kamaruddin. "Rainfall, evapotranspiration and rainfall deficit trend in Alor Setar, Malaysia." Malaysian Journal of Fundamental and Applied Sciences 13, no. 4-1 (December 5, 2017): 400–404. http://dx.doi.org/10.11113/mjfas.v13n4-1.844.
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Rainfall and potential evapotranspiration are important variables in water balance study. Rainfall data were obtained from Malaysian Meteorological Department while estimates of potential evapotranspiration were calculated using Penman-Monteith method. Trend analysis of monthly and annual rainfall, potential evapotranspiration and rainfall deficit are essential to manage irrigation system in agricultural systems. This is because changes in trend of these parameters may affect the water cycle and ecosystem. Annual and monthly values of these variables were analysed from 1980-2009. Results indicated increasing trends of 16.2 mm yr-1 and 3.01 mm yr-1 for both annual rainfall and potential evapotranspiration, respectively. Consequently, these trends resulted in annual rainfall deficit of 1.69 mm per year.
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Gu, Zhijia, Detai Feng, Xingwu Duan, Kuifang Gong, Yawen Li, and Tianyu Yue. "Spatial and Temporal Patterns of Rainfall Erosivity in the Tibetan Plateau." Water 12, no. 1 (January 10, 2020): 200. http://dx.doi.org/10.3390/w12010200.
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The Tibetan Plateau is influenced by global climate change which results in frequent melting of glaciers and snow, and in heavy rainfalls. These conditions may increase the risk of soil erosion, but prediction is not feasible due to scarcity of rainfall data in the high altitudes of the region. In this study, daily precipitation data from 1 January 1981 to 31 December 2015 were selected for 38 meteorological stations in the Tibetan Plateau, and annual and seasonal rainfall erosivity were calculated for each station. Additionally, we used the Mann–Kendall trend test, Sen’s slope, trend coefficient, and climate tendency rate indicators to detect the temporal variation trend of rainfall erosivity. The results showed that the spatial distribution of rainfall erosivity in the Tibetan Plateau exhibited a significant decreasing trend from southeast to northwest. The average annual rainfall erosivity is 714 MJ·mm·ha−1·h−1, and varies from 61 to 1776 MJ·mm·ha−1·h−1. Rainfall erosivity was mainly concentrated in summer and autumn, accounting for 67.5% and 18.5%, respectively. In addition, annual, spring, and summer rainfall erosivity were increasing, with spring rainfall erosivity highly significant. Temporal and spatial patterns of rainfall erosivity indicated that the risk of soil erosion was relatively high in the Hengduan mountains in the eastern Tibetan Plateau, as well as in the Yarlung Zangbo River Valley and its vicinity.
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Paldor, Nathan. "On the Estimation of Trends in Annual Rainfall Using Paired Gauge Observations." Journal of Applied Meteorology and Climatology 47, no. 6 (June 1, 2008): 1814–18. http://dx.doi.org/10.1175/2007jamc1697.1.
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Abstract A method was recently proposed for evaluating the impact of a perturbation, such as air pollution or urbanization, on the precipitation at a location by calculating the ratio between the precipitation at the perturbed location and that at a location believed to be unperturbed. However, this method may be inappropriate because of the high degree of variability of precipitation at each of the stations. To explore the validity of this approach, noisy annual rainfall records are generated numerically in an upwind, unperturbed station and in a downwind, perturbed station, and the time series of ratio between the annual rainfalls in the two stations is analyzed. The noisy rainfall records are 50 yr long, and the imposed trend for the downwind, perturbed station is −2 mm yr−1 while at the upwind station the variations in annual rainfall are purely noisy. Many pairs of noisy rainfall records are numerically generated (each pair constitutes an experiment), and in every experiment the slope of the linear best fit to the rainfall ratio yields an estimate of the trend of rainfall at the perturbed station. In the absence of noise, the trend of the rainfall ratio is explicitly related to the trend of rainfall at the perturbed station, but the natural rainfall variation at the stations completely masks this explicit relationship. The results show that in some experiments the trend line of the rainfall ratio has the opposite sign to the imposed trend and that in only about one-half of the experiments does the ratio’s trend line lie within ±75% of the imposed trend. Trend estimates within ±25% of the imposed trend are obtained in less than one-quarter of the experiments. This result casts doubt on the generality and validity of using trends of rainfall ratio between two stations to estimate trends of precipitation in one of these stations.
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R, RAJA, BALASUBRAMANIAN T N, and KARTHIKEYAN R. "Almanac study on forecasting annual rainfall." Madras Agricultural Journal 90, December (2003): 596–600. http://dx.doi.org/10.29321/maj.10.a00142.
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An analysis was taken up to find out the validity of forecasting annual rainfall by using Tamil almanac information and 90 years (1909-1999) historical rainfall data of Coimbatore. The results revealed that the annual rainfall of a particular Tamil year in a cycle was not the same for the corresponding Tamil year in the fourth- coming cycle and one can expect an opposite event. There was no correlation between occurrence of rainfall at specific dates and total annual rainfall. Between dates of rainfall within a Tamil year had correlation.
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Saha, Sudip. "Precipitation concentration index (PCI) a tool to evaluate the distribution of Rainfall, Barishal, Bangladesh." International Journal of Advanced Geosciences 8, no. 2 (September 30, 2020): 193. http://dx.doi.org/10.14419/ijag.v8i2.31074.
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The present research work reveals the mean annual rainfall of Barishal is 2087.34 mm for the investigated period. The maximum annual rainfall was 3390 mm in the year of 1960 and minimum annual rainfall was recorded as 1277 mm in the year of 1964. The annual rainfall is inversely correlated with time. The maximum monthly rainfall is recorded in the month of July. The amount of annual rainfall is strongly significantly positively correlated with the monthly rainfall of May, June, July, August and September. In Barishal, the value of skewness for all rainfall data are positive that indicate the data are skewed to the right. The positive value of kurtosis of the eleven months of the year (except July) means a peaked distribution and a negative value in the month of July reveals the flat distribution with the same mean and standard deviation. The annual PCI value is inversely proportional to the annual rainfall. The analyses of seasonal precipitation concentration index (SPCI) reveals that the rainfall is uniformly distributed in summer monsoon whereas the winter rainfall shows the dominance of strong irregularity in precipitation distribution.
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Gupta, Bashabi, Seema Aggarwal, and Milu Maria Jose. "Long-Term Seasonal and Annual Rainfall Trend Analysis of Giridih District, Jharkhand, India." Asian Journal of Water, Environment and Pollution 21, no. 4 (July 25, 2024): 73–81. http://dx.doi.org/10.3233/ajw240048.
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District Giridih is primarily rain dependent on its 95 per cent net cultivable land under summer-monsoon crops. It is classified as a mono-cropping area as it lacks irrigation facilities, essential for winter crops. In the last few years, the district experienced water stress due to the shortage of monsoon rainfall. We study long term seasonal and annual rainfall trend analyses for the Giridih district of Jharkhand in India using linear regression modelling. The last 100 years of data were taken for the study and were divided into two-time phases of 50 years each to analyse the changing pattern of rainfall trends. We found a decreasing trend in monsoon rainfall from 1 mm y-1 to 3 mm y-1 between the initial (1921-1971) and final (1972-2021) phase of the study period. Similarly, the return period of droughts (rainfall deficit years) has also reduced from 11 years to 5 years. The study has shown that the rainfall pattern has changed, with the winter months showing a decrease and the pre-monsoon months an increase in their relative contributions to the annual rainfalls. The study may help in the formulation of water resource conservation-oriented decision-making to cope-up with the rainfall uncertainties and meet the future water demand.
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Sowjanya, M. Venkata. "Analysis of Normal Annual Rainfall of Kadapa District in Andhra Pradesh." International Journal for Research in Applied Science and Engineering Technology 12, no. 6 (June 30, 2024): 2371–74. http://dx.doi.org/10.22214/ijraset.2024.63498.
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Abstract: Rainfall is an important parameter in the assessment of water resources projects. The normal annual rainfall is the average value of annual rainfall of year over a specified 30 year period. The 30 year normal is recomputed every decade. Normal annual rainfall is important in planning and design of hydraulic structures. The annual rainfall of Kadapa District for the period of 1910 to 2019 is collected from Water Resources Information Systems portal. The change in normal annual rainfall for every decade is calculated by using MS-Excel spread sheet, starting from 1910. Statistical parameters such as mean, standard deviation and coefficient of variation are calculated. The trend of maximum rainfall and minimum rainfall for every 30 years period is analyzed. Index of wetness is also calculated.
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Obi, Lawrence Echefulechukwu. "Application of Hydrological Computations in Predicting Rainfall Trends in Imo State of Nigeria." European Journal of Engineering Research and Science 2, no. 9 (September 23, 2017): 36. http://dx.doi.org/10.24018/ejers.2017.2.9.367.
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This research employed the empirical method in its approach and workings. Empirical data were collected and various hydrological computations and graphs were engaged through the application of the collected data. The mass curve of rainfall, hyetograph, moving average of annual rainfalls and the computations of recurrence intervals were done by applying the Weibul formular. With computations and its analysis, the recurrent intervals of rainfall magnitudes were determined and rainfall pattern within Imo State were predicted.
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Obi, Lawrence Echefulechukwu. "Application of Hydrological Computations in Predicting Rainfall Trends in Imo State of Nigeria." European Journal of Engineering and Technology Research 2, no. 9 (September 23, 2017): 36–41. http://dx.doi.org/10.24018/ejeng.2017.2.9.367.
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This research employed the empirical method in its approach and workings. Empirical data were collected and various hydrological computations and graphs were engaged through the application of the collected data. The mass curve of rainfall, hyetograph, moving average of annual rainfalls and the computations of recurrence intervals were done by applying the Weibul formular. With computations and its analysis, the recurrent intervals of rainfall magnitudes were determined and rainfall pattern within Imo State were predicted.
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Zhang, Peng, He Ping Shu, Jin Zhu Ma, Gang Wang, and Li Ming Tian. "The Relationship of Debris Flow Hazards and Rainfall Erosivity in the Bailong River Basin of Southern Gansu Province, China." Advanced Materials Research 1073-1076 (December 2014): 1614–19. http://dx.doi.org/10.4028/www.scientific.net/amr.1073-1076.1614.
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Rainfall is one of the main factors that drive soil erosion, leading to environmental problems such as increased frequency and severity of debris flows, and ecosystem damage. Rainfall erosivity represents the potential of rainfall to cause soil erosion, and is determined by a combination of rainfall intensity. The spatial and temporal distribution of rainfall erosivity was analyzed to get its relationship with the debris flows in the Bailong River Basin in China's Gansu Province. The mean annual amount of erosive rainfall accounts for 36.0-47.1% of annual precipitation. The annual mean rainfall erosivity amounts to 798.8 MJ mm ha-1 h-1 yr-1 in the Bailong River Basin. A positive correlation between annual precipitation and annual rainfall erosivity was demonstrated at all 18 rainfall stations. However, further research is required to reveal the key factors that explain soil erosion and debris flows.
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Khadke, Parag A., Hanumant S. Sanap, and Subhash V. Karande. "Trend analysis of Annual, Seasonal and South-west Monsoon rainfall on Sahyadri in Maharashtra." RESEARCH REVIEW International Journal of Multidisciplinary 4, no. 3 (March 13, 2019): 508–11. https://doi.org/10.5281/zenodo.2605484.
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The result obtained from a trend analysis of the Annual and Seasonal rainfall of Sahyadri in Maharashtra. In this region, there are great disparities of the rainfall occurrence of 1983 to 2012. In the present study analyzes the trend of Post-Monsoon, Monsoon, Pre-Monsoon and Annual rainfall all over the Sahyadri from 1983 to 2012.The rainfall trend has been worked out for the entire study region on the basis of 90 raingauge stations spread all over the Sahyadri. The Amboli at an elevation of 720 meters gets average rainfall of 6800 mm. other stations of the eastern side of this belt gets average rainfall ranging between 2500 mm to 3200 mm. In the month of June, rainfall is decreasing in the study area since 1983 to 2012. The average decline trend of June month is -0.2mm, similarly the rainfall trend of July is negative (-0.84 mm). The trend of August and September month is positive (1.87 mm & 4.92 mm respectively).Rainfall is decreasing from the southern part to the northern part of Sahyadri. The rainfall pattern of June and July are shifting towards the August and September month in the study region. At the Mahableshwar and Amboli raingauge station rainfall is decreasing in the all seasons.
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Soldini, Luciano, and Giovanna Darvini. "Extreme rainfall statistics in the Marche region, Italy." Hydrology Research 48, no. 3 (April 6, 2017): 686–700. http://dx.doi.org/10.2166/nh.2017.091.
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A statistical analysis of the rainfalls is carried out for detecting a possible trend in the observed data. The rainfall dataset refers to the historical series collected in the hydrographic basins of the Marche region. On the one hand, the annual maximum daily, hourly and sub-hourly rainfalls have been analysed, on the other hand Climate Change Indices by Expert Team on Climate Change Detection and Indices (ETCCDI) (R1 mm, Rx1day, R20 mm, R95pTOT, PRCPTOT) have been computed to verify an eventual variation of the frequency of the rainfall regime in the Marche region. The time series, selected in the reference period 1951–2013, have been processed by using the non-parametric Mann–Kendall test. The results confirm that most of the series relating to the annual maximum rainfalls do not exhibit any trend. The absence of trend or the presence of negative trend prevail also in the analysis of the ETCCDI indices. The annual average anomalies of the same indices computed with respect to the climatological reference period 1961–1990 are negative since the mid-1980s, but they appear to show an increasing behaviour in the period 2009–2013.
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Chen, Yi-Ru, Bofu Yu, and Graham Jenkins. "Secular variation in rainfall and intensity–frequency–duration curves in Eastern Australia." Journal of Water and Climate Change 4, no. 3 (April 18, 2013): 244–51. http://dx.doi.org/10.2166/wcc.2013.138.
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Rainfall intensity–frequency–duration curves are used extensively for storm runoff estimation. It is generally assumed that rainfall intensity would increase with global warming irrespective of the underlying changes to rainfall. This study analyzed rainfall and temperature from six sites in Eastern Australia. Two non-overlapping 30-year periods with the greatest difference in the mean annual rainfall were selected at each of the six sites to test for significant changes in the mean annual temperature and rainfall. Changes in the mean rainfall intensity for different frequencies of occurrence and storm durations for each site were also analyzed. Temperature has increased at all sites, and significantly at five out of the six sites. The mean annual rainfall has significantly changed between the two non-overlapping periods at the sites with the exception of Cairns (latitude – 16.87° south). The changes in rainfall intensity for longer durations (≥1 h) positively correlate with changes in the mean annual rainfall. There is evidence to suggest that the 6 min rainfall intensity would increase irrespective of the changes in the mean annual rainfall.
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MAPLES, JOSHUA G., B. WADE BRORSEN, and JON T. BIERMACHER. "THE RAINFALL INDEX ANNUAL FORAGE PILOT PROGRAM AS A RISK MANAGEMENT TOOL FOR COOL-SEASON FORAGE." Journal of Agricultural and Applied Economics 48, no. 1 (February 2016): 29–51. http://dx.doi.org/10.1017/aae.2016.3.
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AbstractThe recently implemented Rainfall Index Annual Forage pilot program aims to provide risk coverage for annual forage producers in select states through the use of area rainfall indices as a proxy for yield. This article utilizes unique data from a long-term study of annual ryegrass production with rainfall recorded at the site to determine whether the use of rainfall indices provides adequate coverage for annual forage growers. The rainfall index is highly correlated with actual rainfall. However, it does not provide much yield loss risk protection for our cool-season forage data.
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Sneha Babu R. and Uma G. "Analyzing the Impact of Rainfall Patterns on Agriculture, Economy and Tourism in India: A Statistical Approach." International Journal of Environment and Climate Change 13, no. 11 (December 11, 2023): 4626–37. http://dx.doi.org/10.9734/ijecc/2023/v13i113642.
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The current study examines rainfall trends in India, encompassing its effect on various economic aspects and forecasting for 2023-2030. The Mann-Kendall test and Sen’s slope estimator are utilized to analyze annual and seasonal rainfall patterns. Results reveal a pronounced winter decline (2001-2022) alongside significant pre- monsoon, monsoon, and post-monsoon increases. Annual rainfall consistently de- creases, contrasting with rising pre-monsoon, monsoon, and post-monsoon trends. Annual rainfall exhibits the steepest decline (-1.0891 mm/year), while the monsoon season displays the highest increase (3.2538 mm/year). Further, the present study explores relationships between rainfall and economic growth, tourism, and agriculture. A statistically insignificant yet positive correlation is found between annual rainfall and per-capita GDP, indicating other economic drivers. Tourism shows a weak, statistically insignificant link with annual rainfall. In contrast, a robust statistically significant correlation emerges between annual rainfall and food- grain production, highlighting its role in agriculture. Finally, the present research forecasts annual rainfall (2023-2030) using the ARIMA (1,0,0) model, predicting a continued decline. This has profound implications for water resources, agriculture, and the economy, necessitating proactive measures such as water conservation, drought-resistant farming, and alternative energy investments.
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SINGH, VIVEKANAND, and ANSHUMAN SINGH. "Variation of temperature and rainfall at Patna." MAUSAM 68, no. 1 (November 30, 2021): 161–68. http://dx.doi.org/10.54302/mausam.v68i1.445.
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In this paper, the variation of temperature and rainfall at Patna are analysed using simple non-parametric tests. The trends in the annual maximum and minimum daily temperatures, annual rainfall, annual maximum daily rainfall, number of rainy days in a year, the annual average rainfall per rainy day and the ratio of maximum to average rainfall per rainy day at Patna have been examined. Tends in total monthly rainfall, Highest daily rainfall in a month and number of rainy days in a month have also been determined for every month in a year. The monthly trends of data using simple Mann-Kendall test indicated statistically significant changes in rainfall pattern for the city.
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Gill, S. I., M. A. Naeth, D. S. Chanasyk, and V. S. Baron. "Runoff and sediment yield from snowmelt and rainfall as influenced by forage type and grazing intensity." Canadian Journal of Soil Science 78, no. 4 (November 1, 1998): 699–706. http://dx.doi.org/10.4141/s97-067.
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Currently, there is interest in Western Canada in extending the grazing season using perennial and annual forages. Of greatest concern is the environmental sustainability of these grazing systems, with emphasis on their ability to withstand erosion. A study to examine the runoff and sediment yields of annual and perennial forages in central Alberta was initiated in 1994. Runoff and sediment yield were quantified under snowmelt and rainfall events for two seasons. Rainfall simulation was used to further examine runoff under growing season conditions. Four forage treatments (two annuals: triticale and a barley/triticale mixture and two perennials: smooth bromegrass and meadow bromegrass) and three grazing intensities (light, medium and heavy) were studied, each replicated four times. Total annual runoff was dominated by snowmelt. Generally runoff volumes, sediment yields, sediment ratios and runoff coefficients were all low. Bare ground increased with increasing grazing intensity and was significantly greater in annuals than perennials for all grazing intensities. Litter biomass decreased with increasing grazing intensity and was generally similar in all species for both years at heavy and medium grazing intensities. Results from the rainfall simulation corroborated those under natural rainfall conditions and generally indicated the sustainability of these grazing systems at this site. Key words: Forages, soil erosion, sustainability, rainfall simulation
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Gemmechis, Wendafiraw. "Climate Change Trend Using Descriptive Time Series Technique in Machine Learning: A Case of Jimma Zone, Southwestern Ethiopia." International Journal of Environmental Monitoring and Analysis 12, no. 3 (July 2, 2024): 48–57. http://dx.doi.org/10.11648/j.ijema.20241203.12.
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Understanding climate variability and monitoring time-series trends of temperature and rainfall is crucial for the sustainable development of our planet. This study utilized historical data from the Global Historical Climatology Network-Monthly (GHCN-M) provided by the National Centers for Environmental Information (NCEI) to analyze the temperature and rainfall data from 2015 to 2022. The analysis was conducted using Python 3.1.1 on Anaconda Jupyter Notebook and the package matplotlib 3.2.1 was used for data visualization. The results revealed a pattern of maximum rainfall between March to May for the years 2020, 2021, and 2022, while for the years 2017, 2018, and 2019, the maximum rainfall was recorded in October, December, and November. Additionally, the annual maximum rainfalls were recorded in the years 2020 and 2022, and the annual maximum temperatures for all study years were recorded in January, February, and March months. On the other hand, the annual minimum temperatures for all study years occurred in June, July, August, and September months. Similarly, annual average temperatures were recorded in January, February, and March months. This study emphasizes the importance of monitoring climate change and its impacts on our planet. By understanding climate variability and time-series trends, we can better prepare for the future and work towards a sustainable world.
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O’Donnell, Alison J., Michael Renton, Kathryn J. Allen, and Pauline F. Grierson. "Tree growth responses to temporal variation in rainfall differ across a continental-scale climatic gradient." PLOS ONE 16, no. 5 (May 4, 2021): e0249959. http://dx.doi.org/10.1371/journal.pone.0249959.
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Globally, many biomes are being impacted by significant shifts in total annual rainfall as well as increasing variability of rainfall within and among years. Such changes can have potentially large impacts on plant productivity and growth, but remain largely unknown, particularly for much of the Southern Hemisphere. We investigate how growth of the widespread conifer, Callitris columellaris varied with inter-annual variation in the amount, intensity and frequency of rainfall events over the last century and between semi-arid (<500 mm mean annual rainfall) and tropical (>800 mm mean annual rainfall) biomes in Australia. We used linear and polynomial regression models to investigate the strength and shape of the relationships between growth (ring width) and rainfall. At semi-arid sites, growth was strongly and linearly related to rainfall amount, regardless of differences in the seasonality and intensity of rainfall. The linear shape of the relationship indicates that predicted future declines in mean rainfall will have proportional negative impacts on long-term tree growth in semi-arid biomes. In contrast, growth in the tropics showed a weak and asymmetrical (‘concave-down’) response to rainfall amount, where growth was less responsive to changes in rainfall amount at the higher end of the rainfall range (>1250 mm annual rainfall) than at the lower end (<1000 mm annual rainfall). The asymmetric relationship indicates that long-term growth rates of Callitris in the tropics are more sensitive to increased inter-annual variability of rainfall than to changes in the mean amount of rainfall. Our findings are consistent with observations that the responses of vegetation to changes in the mean or variability of rainfall differ between mesic and semi-arid biomes. These results highlight how contrasting growth responses of a widespread species across a hydroclimatic gradient can inform understanding of potential sensitivity of different biomes to climatic variability and change.
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Toni, Abebe Teklu, Andreas Malcherek, and Asfaw Kebede Kassa. "Agroclimatic Zone-Based Analysis of Rainfall Variability and Trends in the Wabi Shebele River Basin, Ethiopia." Water 14, no. 22 (November 16, 2022): 3699. http://dx.doi.org/10.3390/w14223699.
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The amount and annual distribution of rainfall caused a major socioeconomic and environmental problem where rainfed agriculture is predominant. This study assessed the long-term variability and trends of rainfall in the Wabi Shebele River Basin (WSRB), Ethiopia. The basin was discretized into 9 local agroclimatic zones (ACZ) based on annual rainfall and elevation. The coefficient of variation (CV) was used to check the variability of rainfall while modified Mann-Kendall (MK) and Innovative Trend Analysis (ITA) methods were used to detect rainfall trends. For each ACZ, stations with long-term records and less than 10% of missing data were selected for further analysis. The mean annual rainfall in the basin ranges from 227.2 mm to 1047.4 mm. The study revealed most of the ACZs showed a very high variation in Belg/Spring rainfall (CV% > 30) than Kiremt/Summer and annual rainfall. Seasonal and annual rainfall trend analysis revealed that no uniform trend was detected in all ACZs. However, most of ACZs in the arid and semi-arid areas showed a non-significant decreasing trend in annual rainfall. From seasonal analysis, Belg and Kiremt rainfall showed relatively decreasing and increasing trends respectively. In comparison, a similar result was observed using MK and ITA methods.
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Chen, Yi-Ru, Bofu Yu, and Graham Jenkins. "Secular Variation in Rainfall Intensity and Temperature in Eastern Australia." Journal of Hydrometeorology 14, no. 4 (August 1, 2013): 1356–63. http://dx.doi.org/10.1175/jhm-d-12-0110.1.
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Abstract It is generally assumed that rainfall intensity will increase with temperature increase, irrespective of the underlying changes to the average rainfall. This study documents and investigates long-term trends in rainfall intensities, annual rainfall, and mean maximum and minimum temperatures using the Mann–Kendall trend test for nine sites in eastern Australia. Relationships between rainfall intensities at various durations and 1) annual rainfall and 2) the mean maximum and minimum temperatures were investigated. The results showed that the mean minimum temperature has increased significantly at eight out of the nine sites in eastern Australia. Changes in annual rainfall are likely to be associated with changes in rainfall intensity at the long duration of 48 h. Overall, changes in rainfall intensity at short durations (&lt;1 h) positively correlate with changes in the mean maximum temperature, but there is no significant correlation with the mean minimum temperature and annual rainfall. Additionally, changes in rainfall intensity at longer durations (≥1 h) positively correlate with changes in the mean annual rainfall, but not with either mean maximum or minimum temperatures for the nine sites investigated.
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Garai, Sandip, Ranjit Kumar Paul, Debopam Rakshit, Md Yeasin, A. K. Paul, H. S. Roy, Samir Barman, and B. Manjunatha. "An MRA Based MLR Model for Forecasting Indian Annual Rainfall Using Large Scale Climate Indices." International Journal of Environment and Climate Change 13, no. 5 (March 24, 2023): 137–50. http://dx.doi.org/10.9734/ijecc/2023/v13i51755.
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A novel method for rainfall forecasting has been proposed using Multi Resolution Analysis (MRA). This approach decomposes annual rainfall series and long-term climate indices into component sub-series at different temporal scales, allowing for a more detailed analysis of the factors influencing annual rainfall. Multiple Linear Regression (MLR) is then used to predict annual rainfall, with climate indices sub-series as predictive variables, using a step-wise linear regression algorithm. The proposed model has been tested on Indian annual rainfall data and compared with the traditional MLR model. Results show that the MRA-based model outperforms the traditional model in terms of relative absolute error and correlation coefficient metrics. The proposed method offers several advantages over traditional methods as it can identify underlying factors affecting annual rainfall at different temporal scales, providing more accurate and reliable rainfall forecasts for better water resource management and agricultural planning. In conclusion, the MRA-based approach is a promising tool for improving the accuracy of annual rainfall predictions, and its implementation can lead to better water resource management and agricultural planning.
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Bagale, Damdar. "Temporal variability of seasonal and annual rainfall in Nepal." Journal of Nepal Hydrogeological Association 1 (September 1, 2024): 57–66. https://doi.org/10.3126/jnha.v1i1.78222.
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This study analyzed 107 weather stations' 42-year rainfall data (1977-2018), using the normal ratio method to estimate missing rainfall from nearby stations. This study identified the mean winter, monsoon, and annual rainfall as 69.7 mm, 1433.2 mm, and 1791.5 mm respectively. The winter, monsoon, and annual rainfall have large temporal variability. Nepal received high rainfall from Jun to September (monsoon) and the rest of the eight months received low rainfall causing water scarcity in Nepal. This study examined the increase of rainfall with heights up to mid-mountain then the rainfall decreases with height in monsoon season. But in winter generally, the rainfall amount increases with height. However, rainfall totals both seasonal and annual have been decreasing since 2000 both nationally and regional-wise.
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Indarto, Indarto, and Askin Askin. "VARIABILITAS SPASIAL HUJAN DI WILAYAH UPT PSDA DI MALANG." Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) 6, no. 3 (March 28, 2018): 171. http://dx.doi.org/10.23960/jtep-l.v6i3.171-180.
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This study show the spatial variabilit of rainfall (monthly and annual) rainfall in the area of technical implementation unit of water resources management (UPT-PSDA) in Malang. Administrative area of UPT PSDA in Malang include Malang regency, Malang city, Batu, Blitar Regency, Tulungagung Regency, and Trenggalek Regency. Daily rainfall data from 88 pluviometers spread around the areas are used as main input. The research procedures consist of : (1) data pre-analysis; (2) the analyses using ESDA tools (Histogram, voronoi, QQ-Plot); (3) interpolation by using IDW method; (4) producing a thematic map; and (5) interpretation. Analysis using the histogram, voronoi–maps and normal QQ-plots tools illustrates more detail the spatial variability of the monthly and annual rainfall around the regions. Interpolation produces a thematic map of mean monthly-rainfall, between 100 – 400 mm/month. The spatial distribution of annual rainfall was illustrated by a thematic show the average-annual-range from 1000 – 4000 mm/year. Keywords: spatial variability, rainfall, ESDA, IDW, monthly, annual rainfall
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Hari, Durgasrilakshmi, and Ramamohan Reddy Kasa. "Assessment of Spatiotemporal Trends in Rainfall and Rainfall Extremes in the Hyderabad City, India." Grassroots Journal of Natural Resources 7, no. 2 (August 1, 2024): 216–35. http://dx.doi.org/10.33002/nr2581.6853.070211.
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Rainfall is a crucial climate variable, shows irregular spatial and temporal variations. Significant spatial variability and persistent changes in land use intensify the complexity of urban weather systems. Therefore, climatological rainfall variables deserve attention from both a scientific and technological perspective. The rapid urban expansion of Hyderabad city, coupled with extreme weather variations, has led to increased environmental vulnerability. The present study aims to assess the spatiotemporal trends of annual rainfall and rainfall extremes in Hyderabad city from 1990 to 2020. This study employed the RClimDex model and daily gridded rainfall data to analyze annual rainfall and rainfall extreme indices, focusing on Consecutive Dry Days (CDD), Consecutive Wet Days (CWD), Total Precipitation (PRCPTOT), Rainfall Events Exceeding 10 mm (R10MM), 20 mm (R20MM), Total Precipitation from Very Wet Days (R95PTOT), Maximum 1-Day Precipitation (RX1DAY), and Maximum 5-Day Precipitation (RX5DAY). The trends in annual rainfall and rainfall extremes were assessed using the Mann-Kendall (MK) test, and spatial distribution variations for the identified trends were evaluated with the Inverse Distance Weighting (IDW) interpolation technique. The results of the study showed that no significant annual rainfall trends from 1990 to 2020, indicating natural variability rather than consistent long-term changes. However, extreme Consecutive Dry Days and Maximum Wet Spell trends show increasing trends. The PRCPTOT pattern remains almost stable, and R10MM rainfall events exhibit an increasing trend at a few locations, suggesting potential shifts in precipitation patterns. Conversely, a decreasing trend for rainfall extremes R20MM, R95PTOT, RX1DAY, and RX5DAY indicate a general reduction in extreme rainfall events and very wet days in GHMC suggesting localized reductions in extreme events and varied impacts of prolonged rainfall reductions at annual scale. The study reveals Hyderabad's high spatial variability in annual rainfall distribution and rainfall extremes, emphasizing the importance of analyzing high resolution gridded rainfall data for effective decision-making and efficient water resource management.
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Gu, Zhijia, Yuemei Li, Shuping Huang, Chong Yao, Keke Ji, Detai Feng, Qiang Yi, and Panying Li. "Assessment of Erosive Rainfall and Its Spatial and Temporal Distribution Characteristics: Case Study of Henan Province, Central China." Water 17, no. 1 (December 29, 2024): 62. https://doi.org/10.3390/w17010062.
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Erosive rainfall is essential for initiating surface runoff and soil erosion to occur. The analysis on its temporal and spatial distribution characteristics is crucial for calculating rainfall erosivity, predicting soil erosion, and implementing soil and water conservation. This study utilized daily rainfall observation data from 90 meteorological stations in Henan from 1981 to 2020, and conducted geostatistical analysis, M-K mutation test analysis, and wavelet analysis on erosive rainfall to reveal the spatiotemporal distribution characteristics over the past 40 years. Building on this foundation, the correlation between erosive rainfall, rainfall, and rainfall erosivity were further explored. The findings indicated that the average annual rainfall in Henan Province varied between 217.66 mm and 812.78 mm, with an average yearly erosive rainfall of 549.24 mm and a standard deviation of 108.32 mm. Erosive rainfall constitutes for 77% of the average annual rainfall on average, and the analysis found that erosive rainfall is highly correlated with rainfall volume. The erosive rainfall increased from northwest to southeast, and had the same spatial distribution characteristics as the total rainfall. The number of days with erosive rainfall was 20.5 days and the annual average sub-erosive rainfall was 26.86 mm. The average annual rainfall erosivity in Henan Province ranged from 1341.81 to 6706.64 MJ·mm·ha−1·h−1, averaging at 3264.63 MJ·mm·ha−1·h−1. Both the erosive rainfall and the rainfall erosivity are influenced by the monsoon, showing a unimodal trend, with majority of the annual total attributed to rainfall erosivity from June to September, amounting to 80%. The results can provide a basis for forecasting of heavy rainfall events, soil conservation and planning, ecological treatment, and restoration.
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Al-Daoudi, Ahmed S., and Y. K. Al-Timimi. "The Spatial Pattern Assessment of Annual Rainfall in Iraq for Periods from 2001 to 2023." IOP Conference Series: Earth and Environmental Science 1371, no. 8 (July 1, 2024): 082031. http://dx.doi.org/10.1088/1755-1315/1371/8/082031.
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Abstract This study aims to investigate the patterns of the annual rainfall in Iraq from 2001 to 2023 using data obtained from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS). The period of study was divided into five periods, each spanning five years (except the first, and the fifth period), to analyze annual rainfall variations. Spatial distribution maps and descriptive statistics were generated to assess rainfall patterns across different regions of Iraq. Results indicate significant variability in rainfall amounts and distributions over the study interval, with the northeastern and southeastern strip regions consistently receiving higher rainfall than western and southwestern areas. During the first period (2001-2004), the highest maximum annual rainfall was in 2002 (912 mm/year), in contrast, the second period (2005-2009) recorded the lowest maximum annual rainfall in 2008 by about (439 mm/year). Analysis of the mean annual accumulative rainfall for each period illustrated that the first period 2001-2004 incorporated the highest maximum value of mean annual accumulative rainfall and standard deviation by about 765 mm/4 years, and 160.5 respectively. In contrast, the fifth period 2020-2023 has the lowest maximum value and standard deviation which reached 512 mm/5 years, and 89.2 correspondingly. Mean annual accumulative rainfall decreased over time, suggesting potential impacts of climate change on precipitation patterns in Iraq. These findings provide valuable insights for understanding and managing water resources, agriculture, and environmental sustainability in the region.
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Gaire, Amrit, Damodar Bagale, Prabin Acharya, and Ram Hari Acharya. "Spatial and Temporal Variability of Rainfall in the Western Region of Nepal." Journal of Hydrology and Meteorology 12, no. 1 (December 16, 2024): 68–80. https://doi.org/10.3126/jhm.v12i1.72656.
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The temporal and spatial variability of seasonal, annual, and decadal rainfall over 44 years in western Nepal was investigated using rainfall data from 36 meteorological stations in various physiographic regions. Missing data were addressed using the normal ratio method, and significant trends in annual rainfall were assessed through the Man-Kendall test. Western Nepal receives about 79.7% of annual rainfall during the monsoon, followed by 10.7% during the pre-monsoon, 3.3% during the post-monsoon, and 6.3% during the winter. The analysis revealed distinct seasonal excess and deficit episodes, with the highest monsoon rainfall recorded in 2000 and the lowest in 1979. During the study period, there is a large temporal variability of seasonal and annual rainfall. The central part of western Nepal receives heavy rainfall in monsoon seasons than other parts. In winter seasons more rainfall is received in the Northwest part and decreases towards the central and eastern parts of western Nepal. The midlands of western Nepal received higher annual rainfall than the other regions. The present study identified that the seasonal rainfall has been decreasing patterns in the Western region of Nepal for the past four decades.
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Zhang, Peng, Gang Wang, Li Ming Tian, and Ya Li Zhang. "Spatiotemporal Distribution of Rainfall Erosivity in the Bailong River Basin, Gansu Province." Advanced Materials Research 936 (June 2014): 2377–82. http://dx.doi.org/10.4028/www.scientific.net/amr.936.2377.
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Rainfall erosivity is one of the key parameters that determine soil erosion, sediment yield, and water quality, thus its importance has grown in modeling of the environmental effects of climate change. The spatial and temporal distribution of rainfall erosivity in the Bailong River Basin in China's Gansu Province were analyzed. We derived a rainfall erosivity map based on data from 18 meteorological stations in and around the basin using the inverse distance weighting interpolation approach. The annual mean rainfall erosivity within the Bailong River Basin was 798.8 MJ mm ha-1h-1yr-1. The mean annual amount of erosive rainfall accounts for 36.0 to 47.1% of annual precipitation, depending on the station. Rainfall erosivity was greatest from June to September, and rainfall during this period accounts for 77.7% to 84.8% of the total annual rainfall erosivity.
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Liang, Rui, Qiao Zhu, Huan Lian Ren, and Hua Jin. "Analysis on Characteristics of the Rainfall-Runoff in Beizhangdian Watershed." Applied Mechanics and Materials 90-93 (September 2011): 2578–82. http://dx.doi.org/10.4028/www.scientific.net/amm.90-93.2578.
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Beizhangdian watershed is a typical semi-dry and semi-humid region, where human activities have little effect on the hydrological cycle. Based on a 30-year hydrological observation data, the precipitation, runoff, and rainfall-runoff relationship were researched by the hydrology statistics analysis methods. The results indicated that the inter-annual change of rainfall-runoff of the watershed is remarkable, the annual distribution of rainfall-runoff is extremely uneven, and rainfall-runoff mainly occurred in flood season (June ~ September). There is a good uniformity between the variation tendency of annual rainfall and annual runoff in time and amount, the correlation coefficient of rainfall and runoff is 0.74, the value of the F-test is 4.23.
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Mushayt, Amal. "Comparative Analysis of the General Attitude of Rainfall Changes in the Regions of Hail and Assir, Kingdom of Saudi Arabia." Journal of Umm Al-Qura University for Social Sciences 15, no. 3 (September 15, 2023): 1–20. http://dx.doi.org/10.54940/ss27928411.
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This comparative study analyzes the general rainfall in Ha'il and Assir based on the maximum daily and annual rainfall over 42 years (1976-2017). The data were collected at seven stations in Ha'il and ten stations in Assir to detect climate change phenomena there. The Shapiro-Wilk Test examined the rainfall data distribution. The Levene and ANOVA Tests examined variances of homogeneity. To analyze the general rainfall trend and its statistical significance, the study adopts the Semi-Averages Ratio, Binomial, and the Student's T-Tests. In Ha'il, the Semi-averages method results, and the Binomial Test showed a maximum annual and daily rainfall decrease. The Student's T-Test confirmed this trend for the daily and annual rainfall in Simira, Al Ha'it, Ha'il, and Al Ghazalah stations, and for the maximum daily rainfall in the stations of Simira, Al Ha'it, Uqlat Bin Jibrin, and Al Ghazala. The results revealed increasing annual rainfall in Sabah Billahmar, Al Tajir, Bani Thawr, and As Sudah. Similar trends were detected for the maximum daily rainfall in Khaybar Al Janoub, Bani Thawr, and An Namas. A rainfall decrease was detected in all other stations in Assir. The results of the Binomial and the Student's T-Tests varied. The rest of the annual rainfall trends have no statistical significance and are just phenomenal. This study concluded that the decreasing and increasing trends of annual and maximum daily rains do not definitively indicate there is climate change in Assir and Ha'il. Despite some decreasing rainfall trends of statistical significance, this did not deny some increasing rainfall trends.
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Hunt, B. G. "Climatological Extremes of Simulated Annual Mean Rainfall." Journal of Climate 19, no. 20 (October 15, 2006): 5289–304. http://dx.doi.org/10.1175/jcli3921.1.
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Abstract The Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mark 2 global coupled climatic model has been used to generate a 10 000-yr simulation of “present” climate. The resultant dataset has been used to investigate a number of aspects of extremes associated with annual mean rainfall. Multimillennial time series of normalized rainfall amounts for selected points are used to highlight secular variability, spatial variations, and the differences between pluvial and drought conditions. Global distributions are also presented for selected rainfall characteristics, including the frequency of occurrence of specified rainfall anomalies with annual durations, the frequency of occurrence of 5-yr sequences of specified rainfall anomalies, and the maximum and minimum normalized rainfall amounts attained in the simulation. Such features cannot be obtained from observations because of their limited duration. A case study is also made of a megadrought over the southwestern United States, together with an analysis of the associated causal mechanisms. Given the exclusion of all external forcing from the model, it is concluded that the extreme annual mean rainfall extremes presented in the paper are attributable to stochastic events.
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Bagale, Damodar, Lochan Prasad Devkota, Tirtha Raj Adhikari, and Deepak Aryal. "Spatio-Temporal Variability of Rainfall Over Kathmandu Valley of Nepal." Journal of Hydrology and Meteorology 11, no. 1 (November 2, 2023): 10–19. http://dx.doi.org/10.3126/jhm.v11i1.59661.
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The present study used and analyzed rainfall data from 18 meteorological stations from 1971 to 2013 to examine the spatial and temporal variability of seasonal and annual rainfall based on rain gauge measurements. The monthly to annual rainfall analysis was carried out for each site of Kathmandu Valley. Rainfall amounts in Kathmandu Valley vary considerably in space and time. The minimum mean monthly rainfall is observed in November which is 6.5 mm and maximums of 447.8 mm in July. Monsoon is the main contributor of the rainfall which is 80% followed by pre-monsoon with 13.6%, post-monsoon with 3.6% and winter with 2.8%. Spatial interpolation was used to explore spatial variability of seasonal and annual rainfall over Kathmandu Valley. There is large spatial variability of monsoon rainfall; generally, the upper parts of the Kathmandu Valley received the heavy monsoon rainfall than the lower parts of the Valley floor. The rainfall of Kathmandu has marked decreasing in recent a couple of decades. Annual rainfall has decreased by 0.96 mm/year observed in Kathmandu Valley.
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Pawar, Uttam, Pramodkumar Hire, Miyuru B. Gunathilake, and Upaka Rathnayake. "Spatiotemporal Rainfall Variability and Trends over the Mahi Basin, India." Climate 11, no. 8 (July 31, 2023): 163. http://dx.doi.org/10.3390/cli11080163.
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Climate change can have an influence on rainfall that significantly affects the magnitude frequency of floods and droughts. Therefore, the analysis of the spatiotemporal distribution, variability, and trends of rainfall over the Mahi Basin in India is an important objective of the present work. Accordingly, a serial autocorrelation, coefficient of variation, Mann–Kendall (MK) and Sen’s slope test, innovative trend analysis (ITA), and Pettitt’s test were used in the rainfall analysis. The outcomes were derived from the monthly precipitation data (1901–2012) of 14 meteorology stations in the Mahi Basin. The serial autocorrelation results showed that there is no autocorrelation in the data series. The rainfall statistics denoted that the Mahi Basin receives 94.8% of its rainfall (821 mm) in the monsoon period (June–September). The normalized accumulated departure from the mean reveals that the annual and monsoon rainfall of the Mahi Basin were below average from 1901 to 1930 and above average from 1930 to 1990, followed by a period of fluctuating conditions. Annual and monsoon rainfall variations increase in the lower catchment of the basin. The annual and monsoon rainfall trend analysis specified a significant declining tendency for four stations and an increasing tendency for 3 stations, respectively. A significant declining trend in winter rainfall was observed for 9 stations under review. Likewise, out of 14 stations, 9 stations denote a significant decrease in pre-monsoon rainfall. Nevertheless, there is no significant increasing or decreasing tendency in annual, monsoon, and post-monsoon rainfall in the Mahi Basin. The Mann–Kendall test and innovative trend analysis indicate identical tendencies of annual and seasonal rainfall on the basin scale. The annual and monsoon rainfall of the basin showed a positive shift in rainfall after 1926. The rainfall analysis confirms that despite spatiotemporal variations in rainfall, there are no significant positive or negative trends of annual and monsoon rainfall on the basin scale. It suggests that the Mahi Basin received average rainfall (867 mm) annually and in the monsoon season (821 mm) from 1901 to 2012, except for a few years of high and low rainfall. Therefore, this study is important for flood and drought management, agriculture, and water management in the Mahi Basin.
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SELVARAJ, R. SAMUEL, S. TAMILSELVI, and R. GAYATHRI. "Fractal analysis: Annual rainfall in Chennai." MAUSAM 61, no. 1 (November 27, 2021): 35–38. http://dx.doi.org/10.54302/mausam.v61i1.774.
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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.
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Levine, Jonathan M., A. Kathryn McEachern, and Clark Cowan. "Rainfall effects on rare annual plants." Journal of Ecology 96, no. 4 (July 2008): 795–806. http://dx.doi.org/10.1111/j.1365-2745.2008.01375.x.
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