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Sample records for monthly rainfall amounts

  1. Generating monthly rainfall amount using multivariate skew-t copula

    Science.gov (United States)

    Radi, Noor Fadhilah Ahmad; Zakaria, Roslinazairimah; Zanariah Satari, Siti

    2017-09-01

    This study aims to generate rainfall data in cases where the data is not available or not enough for a certain area of study. In general, the rainfall data is rightly skewed, so the multivariate skew-t copula is used as it able to model rainfall amount and capture the spatial dependence in the data. To illustrate the methodology, three rainfall stations in Kelantan are used. Firstly, the observed data is transformed to uniform unit. The Spearman’s correlation coefficient is calculated between the three stations. It is found that the correlations between the stations are significance at α = 0.05. The next step involved generating the synthetic rainfall data using the multivariate skew-t copula. The data is then transformed to uniform unit and the correlation coefficient is calculated for the generated data. Finally, the correlation coefficient of the observed and the generated data are compared. The Kolmogorov-Smirnov goodness of fit test is used to assess the fit between theoretical and empirical copula and supported by graphical representation. The results show that there is no significant difference between empirical and theoretical copula at 5% significance level. Thus, the multivariate skew-t copula is suitable to generate synthetic rainfall data that can mimic the observed rainfall data. It can also be used to present different rainfall scenarios by changing the value of the parameters in the model.

  2. Mapping monthly rainfall erosivity in Europe

    DEFF Research Database (Denmark)

    Ballabio, C; Meusburger, K; Klik, A

    2017-01-01

    Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale (REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and...

  3. Mapping monthly rainfall erosivity in Europe.

    Science.gov (United States)

    Ballabio, Cristiano; Borrelli, Pasquale; Spinoni, Jonathan; Meusburger, Katrin; Michaelides, Silas; Beguería, Santiago; Klik, Andreas; Petan, Sašo; Janeček, Miloslav; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Tadić, Melita Perčec; Diodato, Nazzareno; Kostalova, Julia; Rousseva, Svetla; Banasik, Kazimierz; Alewell, Christine; Panagos, Panos

    2017-02-01

    Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale (REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part of Britain and Ireland) in May and the highest values are registered during summer months. Starting from September, R-factor has a decreasing trend. The mean rainfall erosivity in summer is almost 4 times higher (315MJmmha(-1)h(-1)) compared to winter (87MJmmha(-1)h(-1)). The Cubist model has been selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency, the sum of all months has to be close to annual erosivity. The performance of the Cubist models proved to be generally high, resulting in R(2) values between 0.40 and 0.64 in cross-validation. The obtained months show an increasing trend of erosivity occurring from winter to summer starting from western to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive events. Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be

  4. Modelling rainfall amounts using mixed-gamma model for Kuantan district

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    Zakaria, Roslinazairimah; Moslim, Nor Hafizah

    2017-05-01

    An efficient design of flood mitigation and construction of crop growth models depend upon good understanding of the rainfall process and characteristics. Gamma distribution is usually used to model nonzero rainfall amounts. In this study, the mixed-gamma model is applied to accommodate both zero and nonzero rainfall amounts. The mixed-gamma model presented is for the independent case. The formulae of mean and variance are derived for the sum of two and three independent mixed-gamma variables, respectively. Firstly, the gamma distribution is used to model the nonzero rainfall amounts and the parameters of the distribution (shape and scale) are estimated using the maximum likelihood estimation method. Then, the mixed-gamma model is defined for both zero and nonzero rainfall amounts simultaneously. The formulae of mean and variance for the sum of two and three independent mixed-gamma variables derived are tested using the monthly rainfall amounts from rainfall stations within Kuantan district in Pahang Malaysia. Based on the Kolmogorov-Smirnov goodness of fit test, the results demonstrate that the descriptive statistics of the observed sum of rainfall amounts is not significantly different at 5% significance level from the generated sum of independent mixed-gamma variables. The methodology and formulae demonstrated can be applied to find the sum of more than three independent mixed-gamma variables.

  5. Artificial Neural Network for Monthly Rainfall Rate Prediction

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    Purnomo, H. D.; Hartomo, K. D.; Prasetyo, S. Y. J.

    2017-03-01

    Rainfall rate forecasting plays an important role in various human activities. Rainfall forecasting is a challenging task due to the uncertainty of natural phenomena. In this paper, two neural network models are proposed for monthly rainfall rate forecasting. The performance of the proposed model is assesses based on monthly rainfall rate in Ampel, Boyolali, from 2001-2013. The experiment results show that the accuracy of the first model is much better than the accuracy of the second model. Its average accuracy is just above 98%, while the accuracy of the second model is approximately 75%. In additional, both models tend to perform better when the fluctuation of rainfall is low.

  6. A review of statistical analyses on monthly and daily rainfall in Catalonia

    Directory of Open Access Journals (Sweden)

    X. Lana

    2009-01-01

    Full Text Available A review on recent studies about monthly and daily rainfall in Catalonia is presented. Monthly rainfall is analysed along the west Mediterranean Coast and in Catalonia, quantifying aspects as the irregularity of monthly amounts and the spatial distribution of the Standard Precipitation Index. Several statistics are applied to daily rainfall series such as their extreme value and intraannual spatial distributions, the variability of the average and standard deviation rain amounts for each month, their amount and time distributions, and time trends affecting four pluviometric indices for different percentiles and class intervals. All these different analyses constitute the continuity of the scientific study of Catalan rainfall, which started about a century ago.

  7. Estimating Monthly Rainfall from Geostationary Satellite Imagery Over Amazonia, Brazil.

    Science.gov (United States)

    Cutrim, Elen Maria Camara

    The infrared regression and the grid-history satellite rainfall estimating techniques were utilized to estimate monthly rainfall in Amazonia during one month of the rainy season (March, 1980) and one month of the dry season (September, 1980). The estimates were based on 3-hourly SMS-II infrared and visible images. Three sets of coefficients for the grid history method (Marajo, Arabian Sea, and GATE) were used to estimate rainfall. The estimated rain was compared with gauge measurements over the region. The infrared regression technique overestimated by a factor of 1.5. The Marajo coefficients yielded the best estimate, especially for eastern Amazonia. In the wet month Marajo coefficients overestimated rain by 10% and in the dry month by 70%. The Arabian Sea coefficients overestimated rain and the GATE coefficients slightly underestimated rain for Amazonia. Two maps of monthly rainfall over Amazonia were constructed for March and September, 1980, combining the ground station and satellite inferred rainfall of the grid history method using the Marajo coefficients. The satellite observations and ground data were mutually compatible and were contourable on these final, composite maps. Monthly rainfall was found to be much more inhomogeneous than previously reported. In March there was a belt of high precipitation trending southwest, with higher values and sharpest gradients in the coastal area. The upper Amazon was also an area of high precipitation, both north and south of the equator. In Roraima rainfall decreased drastically to the north. In September, the area of highest precipitation was the northwestern part of Amazonas State (northern hemisphere). Rainfall elsewhere was very localized and in northeastern Amazonia varied from 0 to 150 mm. Even though the grid history method presented better results for estimating rainfall over Amazonia, the IR model could be utilized more efficiently and economically on an operational basis if the calibration were properly made

  8. Interannual variation in root production in grasslands affected by artificially modified amount of rainfall.

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    Fiala, Karel; Tůma, Ivan; Holub, Petr

    2012-01-01

    The effect of different amounts of rainfall on the below-ground plant biomass was studied in three grassland ecosystems. Responses of the lowland (dry Festuca grassland), highland (wet Cirsium grassland), and mountain (Nardus grassland) grasslands were studied during five years (2006-2010). A field experiment based on rainout shelters and gravity irrigation simulated three climate scenarios: rainfall reduced by 50% (dry), rainfall increased by 50% (wet), and the natural rainfall of the current growing season (ambient). The interannual variation in root increment and total below-ground biomass reflected the experimentally manipulated amount of precipitation and also the amount of current rainfall of individual years. The effect of year on these below-ground parameters was found significant in all studied grasslands. In comparison with dry Festuca grassland, better adapted to drought, submontane wet Cirsium grassland was more sensitive to the different water inputs forming rather lower amount of below-ground plant matter at reduced precipitation.

  9. Interannual Variation in Root Production in Grasslands Affected by Artificially Modified Amount of Rainfall

    Directory of Open Access Journals (Sweden)

    Karel Fiala

    2012-01-01

    Full Text Available The effect of different amounts of rainfall on the below-ground plant biomass was studied in three grassland ecosystems. Responses of the lowland (dry Festuca grassland, highland (wet Cirsium grassland, and mountain (Nardus grassland grasslands were studied during five years (2006–2010. A field experiment based on rainout shelters and gravity irrigation simulated three climate scenarios: rainfall reduced by 50% (dry, rainfall increased by 50% (wet, and the natural rainfall of the current growing season (ambient. The interannual variation in root increment and total below-ground biomass reflected the experimentally manipulated amount of precipitation and also the amount of current rainfall of individual years. The effect of year on these below-ground parameters was found significant in all studied grasslands. In comparison with dry Festuca grassland, better adapted to drought, submontane wet Cirsium grassland was more sensitive to the different water inputs forming rather lower amount of below-ground plant matter at reduced precipitation.

  10. Modeling of the Monthly Rainfall-Runoff Process Through Regressions

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    Campos-Aranda Daniel Francisco

    2014-10-01

    Full Text Available To solve the problems associated with the assessment of water resources of a river, the modeling of the rainfall-runoff process (RRP allows the deduction of runoff missing data and to extend its record, since generally the information available on precipitation is larger. It also enables the estimation of inputs to reservoirs, when their building led to the suppression of the gauging station. The simplest mathematical model that can be set for the RRP is the linear regression or curve on a monthly basis. Such a model is described in detail and is calibrated with the simultaneous record of monthly rainfall and runoff in Ballesmi hydrometric station, which covers 35 years. Since the runoff of this station has an important contribution from the spring discharge, the record is corrected first by removing that contribution. In order to do this a procedure was developed based either on the monthly average regional runoff coefficients or on nearby and similar watershed; in this case the Tancuilín gauging station was used. Both stations belong to the Partial Hydrologic Region No. 26 (Lower Rio Panuco and are located within the state of San Luis Potosi, México. The study performed indicates that the monthly regression model, due to its conceptual approach, faithfully reproduces monthly average runoff volumes and achieves an excellent approximation in relation to the dispersion, proved by calculation of the means and standard deviations.

  11. Spatial interpolation methods for monthly rainfalls and temperatures in Basilicata

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    Ferrara A

    2008-12-01

    Full Text Available Spatial interpolated climatic data on grids are important as input in forest modeling because climate spatial variability has a direct effect on productivity and forest growth. Maps of climatic variables can be obtained by different interpolation methods depending on data quality (number of station, spatial distribution, missed data etc. and topographic and climatic features of study area. In this paper four methods are compared to interpolate monthly rainfall at regional scale: 1 inverse distance weighting (IDW; 2 regularized spline with tension (RST; 3 ordinary kriging (OK; 4 universal kriging (UK. Besides, an approach to generate monthly surfaces of temperatures over regions of complex terrain and with limited number of stations is presented. Daily data were gathered from 1976 to 2006 period and then gaps in the time series were filled in order to obtain monthly mean temperatures and cumulative precipitation. Basic statistics of monthly dataset and analysis of relationship of temperature and precipitation to elevation were performed. A linear relationship was found between temperature and altitude, while no relationship was found between rainfall and elevation. Precipitations were then interpolated without taking into account elevation. Based on root mean squared error for each month the best method was ranked. Results showed that universal kriging (UK is the best method in spatial interpolation of rainfall in study area. Then cross validation was used to compare prediction performance of tree different variogram model (circular, spherical, exponential using UK algorithm in order to produce final maps of monthly precipitations. Before interpolating temperatures were referred to see level using the calculated lapse rate and a digital elevation model (DEM. The result of interpolation with RST was then set to originally elevation with an inverse procedure. To evaluate the quality of interpolated surfaces a comparison between interpolated and

  12. Regularized joint inverse estimation of extreme rainfall amounts in ungauged coastal basins of El Salvador

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    Friedel, M.J.

    2008-01-01

    A regularized joint inverse procedure is presented and used to estimate the magnitude of extreme rainfall events in ungauged coastal river basins of El Salvador: Paz, Jiboa, Grande de San Miguel, and Goascoran. Since streamflow measurements reflect temporal and spatial rainfall information, peak-flow discharge is hypothesized to represent a similarity measure suitable for regionalization. To test this hypothesis, peak-flow discharge values determined from streamflow recurrence information (10-year, 25-year, and 100-year) collected outside the study basins are used to develop regional (country-wide) regression equations. Peak-flow discharge derived from these equations together with preferred spatial parameter relations as soft prior information are used to constrain the simultaneous calibration of 20 tributary basin models. The nonlinear range of uncertainty in estimated parameter values (1 curve number and 3 recurrent rainfall amounts for each model) is determined using an inverse calibration-constrained Monte Carlo approach. Cumulative probability distributions for rainfall amounts indicate differences among basins for a given return period and an increase in magnitude and range among basins with increasing return interval. Comparison of the estimated median rainfall amounts for all return periods were reasonable but larger (3.2-26%) than rainfall estimates computed using the frequency-duration (traditional) approach and individual rain gauge data. The observed 25-year recurrence rainfall amount at La Hachadura in the Paz River basin during Hurricane Mitch (1998) is similar in value to, but outside and slightly less than, the estimated rainfall confidence limits. The similarity in joint inverse and traditionally computed rainfall events, however, suggests that the rainfall observation may likely be due to under-catch and not model bias. ?? Springer Science+Business Media B.V. 2007.

  13. Forecasting and Analysis of Monthly Rainfalls in Ardabil Province by Arima, Autoregrressive, and Winters Models

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    B. Salahi

    2017-01-01

    Full Text Available Introduction: Rainfall has the highest variability at time and place scale. Rainfall fluctuation in different geographical areas reveals the necessity of investigating this climate element and suitable models to forecast the rate of precipitation for regional planning. Ardabil province has always faced rainfall fluctuations and shortage of water supply. Precipitation is one of the most important features of the environment. The amount of precipitation over time and in different places is subject to large fluctuations which may be periodical. Studies show that, due to the certain complexities of rainfall, the models which used to predict future values will also need greater accuracy and less error. Among the forecasting models, Arima has more applications and it has replaced with other models. Materials and Methods: In this research, through order 2 Autoregrressive, Winters, and Arima models, monthly rainfalls of Ardabil synoptic station (representing Ardabil province for a 31-year period (1977-2007 were investigated. To assess the presence or absence of significant changes in mean precipitation of Ardabil synoptic station, rainfall of this station was divided into two periods: 1977-1993 and 1994-2010. T-test was used to statistically examine the difference between the two periods. After adjusting the data, descriptive statistics were applied. In order to model the total monthly precipitation of Ardabil synoptic station, Winters, Autoregressive, and Arima models were used. Among different models, the best options were chosen to predict the time series including the mean absolute deviation (MAD, the mean squared errors (MSE, root mean square errors (RMSE and mean absolute percentage errors (MAPE. In order to select the best model among the available options under investigation, the predicted value of the deviation of the actual value was utilized for the months of 2006-2010. Results and Discussion: Statistical characteristics of the total monthly

  14. Forecasting of Amount of Rainfall in Rainy Season by using Information Obtained from El Nino Data

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    Yamada, Fujihiro; Yamamoto, Nobuyuki; Sugimoto, Shigeyuki; Ichiyanagi, Katsuhiro; Hibino, Yasuyuki; Nakano, Hiroyuki; Mizuno, Katsunori; Yukita, Kazuto; Goto, Yasuyuki

    In electric power system operation and dam management, it is important that we forecast the rainfall depth in the rainy season. This paper studies the technique using neural network in order to forecast the amount of rainfall in rainy season on upper district of dam for hydro power plant. A case study was carried out on Central Japan. We were able to confirm the effectiveness of the information obtained from El Nino and La Nina data.

  15. 18O depletion in monsoon rain relates to large scale organized convection rather than the amount of rainfall.

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    Lekshmy, P R; Midhun, M; Ramesh, R; Jani, R A

    2014-07-11

    Oxygen isotopic variations in rainfall proxies such as tree rings and cave calcites from South and East Asia have been used to reconstruct past monsoon variability, mainly through the amount effect: the observed (18)O depletion of rain with increasing amount, manifested as a negative correlation of the monthly amount of tropical rain with its δ(18)O, both measured at the same station. This relation exhibits a significant spatial variability, and at some sites (especially North-East and peninsular India), the rainfall proxies are not interpretable by this effect. We show here that relatively higher (18)O-depletion in monsoon rain is not related necessarily to its amount, but rather, to large scale organized convection. Presenting δ(18)O analyses of ~654 samples of daily rain collected during summer 2012 across 9 stations in Kerala, southern India, we demonstrate that although the cross correlations between the amounts of rainfall in different stations is insignificant, the δ(18)O values of rain exhibit highly coherent variations (significant at P = 0.05). Significantly more (18)O-depletion in the rain is caused by clouds only during events with a large spatial extent of clouds observable over in the south eastern Arabian Sea.

  16. A 305 year monthly rainfall series for the Island of Ireland (1711-2016)

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    Murphy, Conor; Burt, Tim P.; Broderick, Ciaran; Duffy, Catriona; Macdonald, Neil; Matthews, Tom; McCarthy, Mark P.; Mullan, Donal; Noone, Simon; Ryan, Ciara; Thorne, Peter; Walsh, Seamus; Wilby, Robert L.

    2017-04-01

    This paper derives a continuous 305-year monthly rainfall series for the Island of Ireland (IoI) for the period 1711-2016. Two key data sources are employed: i) a previously unpublished UK Met Office Note which compiled annual rainfall anomalies and corresponding monthly per mille amounts from weather diaries and early observational records for the period 1711-1977; and ii) a long-term, homogenised monthly IoI rainfall series for the period 1850-2016. Using estimates of long-term average precipitation sampled from the quality assured series, the full record is reconstituted and insights drawn regarding notable periods and the range of climate variability and change experienced. Consistency with other long records for the region is examined, including: the England and Wales Precipitation series (EWP; 1766-2016); the early EWP Glasspoole series (1716-1765) and the Central England Temperature series (CET; 1711-2016). Strong correspondence between all records is noted from 1780 onwards. While disparities are evident between the early EWP and Ireland series, the latter shows strong decadal consistency with CET throughout the record. In addition, independent, early observations from Cork and Dublin, along with available documentary sources, corroborate the derived series and add confidence to our reconstruction. The new IoI rainfall record reveals that the wettest decades occurred in the early 18th Century, despite the fact that IoI has experienced a long-term winter wetting trend consistent with climate model projections. These exceptionally wet winters of the 1720s and 1730s were concurrent with almost unprecedented warmth in the CET, glacial advance throughout Scandinavia, and glacial retreat in West Greenland, consistent with a wintertime NAO-type forcing. Our study therefore demonstrates the value of long-term observational records for providing insight to the natural climate variability of the North Atlantic region.

  17. Gross rainfall amount and maximum rainfall intensity in 60-minute influence on interception loss of shrubs: a 10-year observation in the Tengger Desert

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    Zhang, Zhi-Shan; Zhao, Yang; Li, Xin-Rong; Huang, Lei; Tan, Hui-Juan

    2016-05-01

    In water-limited regions, rainfall interception is influenced by rainfall properties and crown characteristics. Rainfall properties, aside from gross rainfall amount and duration (GR and RD), maximum rainfall intensity and rainless gap (RG), within rain events may heavily affect throughfall and interception by plants. From 2004 to 2014 (except for 2007), individual shrubs of Caragana korshinskii and Artemisia ordosica were selected to measure throughfall during 210 rain events. Various rainfall properties were auto-measured and crown characteristics, i.e., height, branch and leaf area index, crown area and volume of two shrubs were also measured. The relative interceptions of C. korshinskii and A. ordosica were 29.1% and 17.1%, respectively. Rainfall properties have more contributions than crown characteristics to throughfall and interception of shrubs. Throughfall and interception of shrubs can be explained by GR, RI60 (maximum rainfall intensities during 60 min), RD and RG in deceasing importance. However, relative throughfall and interception of two shrubs have different responses to rainfall properties and crown characteristics, those of C. korshinskii were closely related to rainfall properties, while those of A. ordosica were more dependent on crown characteristics. We highlight long-term monitoring is very necessary to determine the relationships between throughfall and interception with crown characteristics.

  18. Contribution of Monthly and Regional Rainfall to the Strength of Indian Summer Monsoon

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    Zheng, Y.; Ali, M.; Bourassa, M. A.

    2015-12-01

    Indian Summer Monsoon Rainfall (ISMR: June-September) has both temporal and spatial variability causing floods/droughts in different seasons/locations leading to a strong or weak monsoon. Here, we present the contribution of all-India monthly, seasonal and regional rainfall to the ISMR, with special reference to the strong and weak monsoons. For this purpose, rainfall data provided by the India Meteorological Department (IMD: http://www.imd.gov.in/section/nhac/dynamic/Monsoon_frame.htm) for 1901-2013 have been used. The IMD divided the Indian sub-continent into four homogeneous regions of northwest India (NWI), northeast India (NEI), central India (CI), and south peninsula India (SPIN). Rainfall during July-August contributes the most to the total seasonal rainfall, whether it is a strong or weak monsoon. Although the NEI has the maximum area-weighted rainfall, its contribution is the least toward a strong or weak monsoon. The rainfall in the remaining three regions (NWI, CI, and SPIN) controls whether an ISMR is strong or weak. Compared to the monthly rainfall, the regional rainfall dominates the strong or weak rainfall periods.

  19. Spatiotemporal monthly rainfall forecasts for south-eastern and eastern Australia using climatic indices

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    Montazerolghaem, Maryam; Vervoort, Willem; Minasny, Budiman; McBratney, Alex

    2016-05-01

    Knowledge about future rainfall is important for agriculture management and planning in arid and semi-arid regions. Australia has complex variations in rainfall patterns in time and space, arising from the combination of the geographic structure and the dual effects of Indian and Pacific Ocean. This study aims to develop a forecasting model of spatiotemporal monthly rainfall totals using lagged climate indices and historical rainfall data from 1950-2011 for south-eastern and eastern Australia. Data were obtained from the Australian Bureau of Meteorology (BoM) from 136 high-quality weather stations. To reduce spatial complexity, climate regionalization was used to divide the stations in homogenous sub-regions based on similarity of rainfall patterns and intensity using principal component analysis (PCA) and K-means clustering. Subsequently, a fuzzy ranking algorithm (FRA) was applied to the lagged climatic predictors and monthly rainfall in each sub-region to identify the best predictors. Selected predictors by FRA were found to vary by sub-region. After these two stages of pre-processing, an artificial neural network (ANN) model was developed and optimized separately for each sub-region and the entire area. The results indicate that climate regionalization can improve a monthly spatiotemporal rainfall forecast model. The location and number of sub-regions were important for ranking predictors and modeling. This further suggests that the impact of climate variables on Australian rainfall is more variable in both time and space than indicated thus far.

  20. Spatiotemporal monthly rainfall forecasting for south-eastern and eastern Australia using climatic indices

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    Montazerolghaem, Maryam; Vervoort, Willem; Minasny, Budiman; McBratney, Alex

    2014-05-01

    Knowledge about future rainfall would significantly benefit land, water resources and agriculture management, as this assists with planning and management decisions. Forecasting spatiotemporal monthly rainfall is difficult, especially in Australia where there is a complex interaction between topography and the effect of Indian and Pacific Ocean. This study describes a method for spatiotemporal monthly rainfall forecasting in south-eastern and eastern part of Australia using climatic and non-climatic variables. Rainfall data were obtained from Bureau of Meteorology (BoM) from 136 high quality weather stations from the south-eastern and eastern part of Australia with monthly rainfall records from 1879 to 2012. To reduce spatial complexity of the area and improve model accuracy, spatial classification (regionalization) was considered as first step. Significant predictors for each sub-region among lagged climatic input variables were selected using Fuzzy Ranking Algorithm (FRA). Climate classification: 1) discovered homogenous sub-regions with a similar rainfall patterns and investigated spatiotemporal rainfall variations in the area, 2) allowed selection of significant predictors with a fine resolution for each area, 3) improved the prediction model and increased model accuracy. PCA was used to reduce the dimensions of the dataset and to remove the rainfall time series correlation. K-means clustering was used on the loadings of PCs describing 93% of long-term monthly rainfall variations. The analysis was repeated for different numbers of sub-regions (3 - 8) to identify the best number of clusters to improve the forecast model performance. Subsequently, a Fuzzy Ranking Algorithm (FRA) was applied to the lagged climatic predictors and monthly rainfall in each sub-region to identify the best predictors. After these two stages of pre-processing, a Neural Network model was developed and optimized for each of the sub-regions as well as for the entire area. It is concluded

  1. Comparison of semivariogram models for Kriging monthly rainfall in eastern China

    Institute of Scientific and Technical Information of China (English)

    汤燕冰

    2002-01-01

    An exploratory spatial data analysis method (ESDA) was designed Apr.28,2002 for kriging monthly rainfall. Samples were monthly rainfall observed at 61 weather stations in eastern China over the period 1961-1998. Comparison of five semivariogram models (Spherical, Exponential, Linear, Gaussian and Rational Quadratic) indicated that kriging fulfills the objective of finding better ways to estimate interpolation weights and can provide error information for monthly rainfall interpolation. ESDA yielded the three most common forms of experimental semivariogram for monthly rainfall in the area. All five models were appropriate for monthly rainfall interpolation but under different circumstances. Spherical, Exponential and Linear models perform as smoothing interpolator of the data, whereas Gaussian and Rational Quadratic models serve as an exact interpolator. Spherical, Exponential and Linear models tend to underestimate the values. On the contrary, Gaussian and Rational Quadratic models tend to overestimate the values. Since the suitable model for a specific month usually is not unique and each model does not show any bias toward one or more specific months, an ESDA is recommended for a better interpolation result.

  2. Monthly Rainfall Erosivity: Conversion Factors for Different Time Resolutions and Regional Assessments

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    Panos Panagos

    2016-03-01

    Full Text Available As a follow up and an advancement of the recently published Rainfall Erosivity Database at European Scale (REDES and the respective mean annual R-factor map, the monthly aspect of rainfall erosivity has been added to REDES. Rainfall erosivity is crucial to be considered at a monthly resolution, for the optimization of land management (seasonal variation of vegetation cover and agricultural support practices as well as natural hazard protection (landslides and flood prediction. We expanded REDES by 140 rainfall stations, thus covering areas where monthly R-factor values were missing (Slovakia, Poland or former data density was not satisfactory (Austria, France, and Spain. The different time resolutions (from 5 to 60 min of high temporal data require a conversion of monthly R-factor based on a pool of stations with available data at all time resolutions. Because the conversion factors show smaller monthly variability in winter (January: 1.54 than in summer (August: 2.13, applying conversion factors on a monthly basis is suggested. The estimated monthly conversion factors allow transferring the R-factor to the desired time resolution at a European scale. The June to September period contributes to 53% of the annual rainfall erosivity in Europe, with different spatial and temporal patterns depending on the region. The study also investigated the heterogeneous seasonal patterns in different regions of Europe: on average, the Northern and Central European countries exhibit the largest R-factor values in summer, while the Southern European countries do so from October to January. In almost all countries (excluding Ireland, United Kingdom and North France, the seasonal variability of rainfall erosivity is high. Very few areas (mainly located in Spain and France show the largest from February to April. The average monthly erosivity density is very large in August (1.67 and July (1.63, while very small in January and February (0.37. This study addresses

  3. Network-derived inhomogeneity in monthly rainfall analyses over western Tasmania

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    Fawcett, Robert; Trewin, Blair; Barnes-Keoghan, Ian

    2010-08-01

    Monthly rainfall in the wetter western half of Tasmania was relatively poorly observed in the early to middle parts of the 20th century, and this causes a marked inhomogeneity in the operational gridded monthly rainfall analyses generated by the Australian Bureau of Meteorology up until the end of 2009. These monthly rainfall analyses were generated for the period 1900 to 2009 in two forms; a national analysis at 0.25° latitude-longitude resolution, and a southeastern Australia regional analysis at 0.1° resolution. For any given month, they used all the monthly data from the standard Bureau rainfall gauge network available in the Australian Data Archive for Meteorology. Since this network has changed markedly since Federation (1901), there is obvious scope for network-derived inhomogeneities in the analyses. In this study, we show that the topography-resolving techniques of the new Australian Water Availability Project analyses, adopted as the official operational analyses from the start of 2010, substantially diminish those inhomogeneities, while using largely the same observation network. One result is an improved characterisation of recent rainfall declines across Tasmania. The new analyses are available at two resolutions, 0.25° and 0.05°.

  4. Network-derived inhomogeneity in monthly rainfall analyses over western Tasmania

    Energy Technology Data Exchange (ETDEWEB)

    Fawcett, Robert; Trewin, Blair [National Climate Centre, Australian Bureau of Meteorology, Docklands, Victoria 3008 (Australia); Barnes-Keoghan, Ian, E-mail: r.fawcett@bom.gov.a, E-mail: b.trewin@bom.gov.a, E-mail: i.barnes-keoghan@bom.gov.a [Tasmanian Regional Office, Australian Bureau of Meteorology, Hobart, Tasmania 3000 (Australia)

    2010-08-15

    Monthly rainfall in the wetter western half of Tasmania was relatively poorly observed in the early to middle parts of the 20th century, and this causes a marked inhomogeneity in the operational gridded monthly rainfall analyses generated by the Australian Bureau of Meteorology up until the end of 2009. These monthly rainfall analyses were generated for the period 1900 to 2009 in two forms; a national analysis at 0.25{sup 0} latitude-longitude resolution, and a southeastern Australia regional analysis at 0.1{sup 0} resolution. For any given month, they used all the monthly data from the standard Bureau rainfall gauge network available in the Australian Data Archive for Meteorology. Since this network has changed markedly since Federation (1901), there is obvious scope for network-derived inhomogeneities in the analyses. In this study, we show that the topography-resolving techniques of the new Australian Water Availability Project analyses, adopted as the official operational analyses from the start of 2010, substantially diminish those inhomogeneities, while using largely the same observation network. One result is an improved characterisation of recent rainfall declines across Tasmania. The new analyses are available at two resolutions, 0.25{sup 0} and 0.05{sup 0}.

  5. Comparison of semivariogram models for kriging monthly rainfall in eastern China

    Institute of Scientific and Technical Information of China (English)

    汤燕冰

    2002-01-01

    An exploratory spatial data analysis method(ESDA) was designed Apr.28,2002 for kriging monthly rainfall.Samples were monthly rainfall observed at 61 weather stations in eastern China over the period 1961-1998.Comparison of five semivariogram models(Spherical,Exponential,Linear,Gaussian and Rational Quadratic)indicated that kriging fulfills the objective of finding better ways to estimate interpolation weights and can provide error information for monthly rainfall interpolation.ESDA yielded the three most common forms of experimental semivariogram for monthly rainfall in the erea.All five models were appropriate for monthly rainflaa interpolation but under different circumstances.Spherical,Exponential and Linear models perform as smoothing interpolator of the data,whereas Gaussian and Rational Quadratic models serve as an exact interpolator.Spherical,Exponential and Linear models tend to underestimate the values,On the contrayr,Gaussian and Rational Quadratic models tend to overestimate the values.On the contrary,Gaussian and Rational Quadratic models tend to overestimate the values,Since the suitable model for a specific month usually is not unique and each model does not show any bias toward one or more specific months,an ESDA is recommended for a better interpolation result.

  6. Multivariate analysis applied to monthly rainfall over Rio de Janeiro state, Brazil

    Science.gov (United States)

    Brito, Thábata T.; Oliveira-Júnior, José F.; Lyra, Gustavo B.; Gois, Givanildo; Zeri, Marcelo

    2016-10-01

    Spatial and temporal patterns of rainfall were identified over the state of Rio de Janeiro, southeast Brazil. The proximity to the coast and the complex topography create great diversity of rainfall over space and time. The dataset consisted of time series (1967-2013) of monthly rainfall over 100 meteorological stations. Clustering analysis made it possible to divide the stations into six groups (G1, G2, G3, G4, G5 and G6) with similar rainfall spatio-temporal patterns. A linear regression model was applied to a time series and a reference. The reference series was calculated from the average rainfall within a group, using nearby stations with higher correlation (Pearson). Based on t-test (p < 0.05) all stations had a linear spatiotemporal trend. According to the clustering analysis, the first group (G1) contains stations located over the coastal lowlands and also over the ocean facing area of Serra do Mar (Sea ridge), a 1500 km long mountain range over the coastal Southeastern Brazil. The second group (G2) contains stations over all the state, from Serra da Mantiqueira (Mantiqueira Mountains) and Costa Verde (Green coast), to the south, up to stations in the Northern parts of the state. Group 3 (G3) contains stations in the highlands over the state (Serrana region), while group 4 (G4) has stations over the northern areas and the continent-facing side of Serra do Mar. The last two groups were formed with stations around Paraíba River (G5) and the metropolitan area of the city of Rio de Janeiro (G6). The driest months in all regions were June, July and August, while November, December and January were the rainiest months. Sharp transitions occurred when considering monthly accumulated rainfall: from January to February, and from February to March, likely associated with episodes of "veranicos", i.e., periods of 4-15 days of duration with no rainfall.

  7. Monthly Rainfall Erosivity: Conversion Factors for Different Time Resolutions and Regional Assessments

    DEFF Research Database (Denmark)

    Panagos, Panos; Borrelli, Pasquale; Spinoni, Jonathan

    2016-01-01

    , for the optimization of land management (seasonal variation of vegetation cover and agricultural support practices) as well as natural hazard protection (landslides and flood prediction). We expanded REDES by 140 rainfall stations, thus covering areas where monthly R-factor values were missing (Slovakia, Poland...

  8. Prediction of Monthly Summer Monsoon Rainfall Using Global Climate Models Through Artificial Neural Network Technique

    Science.gov (United States)

    Nair, Archana; Singh, Gurjeet; Mohanty, U. C.

    2017-08-01

    The monthly prediction of summer monsoon rainfall is very challenging because of its complex and chaotic nature. In this study, a non-linear technique known as Artificial Neural Network (ANN) has been employed on the outputs of Global Climate Models (GCMs) to bring out the vagaries inherent in monthly rainfall prediction. The GCMs that are considered in the study are from the International Research Institute (IRI) (2-tier CCM3v6) and the National Centre for Environmental Prediction (Coupled-CFSv2). The ANN technique is applied on different ensemble members of the individual GCMs to obtain monthly scale prediction over India as a whole and over its spatial grid points. In the present study, a double-cross-validation and simple randomization technique was used to avoid the over-fitting during training process of the ANN model. The performance of the ANN-predicted rainfall from GCMs is judged by analysing the absolute error, box plots, percentile and difference in linear error in probability space. Results suggest that there is significant improvement in prediction skill of these GCMs after applying the ANN technique. The performance analysis reveals that the ANN model is able to capture the year to year variations in monsoon months with fairly good accuracy in extreme years as well. ANN model is also able to simulate the correct signs of rainfall anomalies over different spatial points of the Indian domain.

  9. Frequency Analysis of the Monthly Rainfall Data at Sulaimania Region, Iraq

    Directory of Open Access Journals (Sweden)

    Prof. Dr. Rafa H Al-Suhili

    2016-08-01

    Full Text Available Different frequency distributions models were fitted to the monthly rainfall data in Sulaimania region, north Iraq. Three rainfall gauging stations data were used, Sulaimania city, Dokan Dam, and Derbendikhan Dam metrological stations, for the period (1984-2010. The distributions models fitted are of Normal, Log-normal, Wiebull, Exponential and Two parameters Gamma type. The Kolmogorov-Smirnov test was used to evaluate the goodness of fit. The fittings were done for the overall data and for each month separately. The Gamma, Exponential and Weibull distributions were found as the best fits for the three stations respectively for the overall models, while for the monthly models different distribution type was found as the best fit for each month and each station, however the Gamma distributions was found to have the highest percent of best fit. The best fitted distributions were used to forecast three sets of monthly rainfall data for each station and compared to the observed ones for the last 7- years of data. The t-test,F-test and KolmogorovSmirnov test indicate the capability of these models to produce data that has the same frequency distribution of the observed one. Comparison between the performances of the overall and periodic models reveals that there no distinguishable improvement of the monthly model over the overall one.

  10. Medicare Part B income-related monthly adjustment amount. Final rules.

    Science.gov (United States)

    2006-10-27

    We are adding to our regulations a new subpart, Medicare Part B Income-Related Monthly Adjustment Amount, to contain the rules we will follow for Medicare Part B income-related monthly adjustment amount determinations. The monthly adjustment amount represents the amount of decrease in the Medicare Part B premium subsidy, i.e. the amount of the Federal Government's contribution to the Federal Supplementary Medical Insurance (SMI) Trust Fund. This new subpart implements section 811 of the Medicare Prescription Drug, Improvement, and Modernization Act of 2003 (the Medicare Modernization Act or MMA) and contains the rules for determining when, based on income, a monthly adjustment amount will be added to a Medicare Part B beneficiary's standard monthly premium. These final rules describe: What the new subpart is about; what information we will use to determine whether you will pay an income-related monthly adjustment amount and the amount of the adjustment when applicable; when we will consider a major life-changing event that results in a significant reduction in your modified adjusted gross income; and how you can appeal our determination about your income-related monthly adjustment amount.

  11. Daily disaggregation of simulated monthly flows using different rainfall datasets in southern Africa

    Directory of Open Access Journals (Sweden)

    D.A. Hughes

    2015-09-01

    New hydrological insights for the region: There are substantial regional differences in the success of the monthly hydrological model, which inevitably affects the success of the daily disaggregation results. There are also regional differences in the success of using global rainfall data sets (Climatic Research Unit (CRU datasets for monthly, National Oceanic and Atmospheric Administration African Rainfall Climatology, version 2 (ARC2 satellite data for daily. The overall conclusion is that the disaggregation method presents a parsimonious approach to generating daily flow simulations from existing monthly simulations and that these daily flows are likely to be useful for some purposes (e.g. water quality modelling, but less so for others (e.g. peak flow analysis.

  12. Monthly-scale palaeo-rainfall reconstructed using a Belizean stalagmite.

    Science.gov (United States)

    Ridley, H.; Baldini, J. U. L.; Macpherson, C. G.; Prufer, K. M.; Kennett, D. J.; Amserom, Y.

    2012-04-01

    Stable isotope variations and visible growth layers in a fast growing, U-Th dated, aragonitic stalagmite from southern Belize provide an extraordinarily high resolution proxy palaeo-rainfall record for the Central American Atlantic region over the last 1,400 years. The δ18O and δ13C of speleothem carbonate at this location appears to respond primarily to rainfall variability over the cave site. A surprising result is that annual δ13C cycles are present within the stalagmite, conceivably reflecting seasonality in rainfall. With a bi-monthly resolution the record allows the inference of palaeo-tropical cyclone events as well as intra-annual rainfall variations. The record is also sufficiently long as to lend itself to helping decipher long-term behavioural modes of the tropical Atlantic beyond the instrumental record. The annual variability in stalagmite growth rate over the last 1,400 years is feasibly recording ITCZ migration through time. This study therefore has important implications for deconvolving the Atlantic tropical cyclone record, while also increasing our understanding of the links between ENSO, the ITCZ, and Central American climate.

  13. [Seasonality of rotavirus infection in Venezuela: relationship between monthly rotavirus incidence and rainfall rates].

    Science.gov (United States)

    González Chávez, Rosabel

    2015-09-01

    In general, it has been reported that rotavirus infection was detected year round in tropical countries. However, studies in Venezuela and Brazil suggest a seasonal behavior of the infection. On the other hand, some studies link infection with climatic variables such as rainfall. This study analyzes the pattern of behavior of the rotavirus infection in Carabobo-Venezuela (2001-2005), associates the seasonality of the infection with rainfall, and according to the seasonal pattern, estimates the age of greatest risk for infection. The analysis of the rotavirus temporal series and accumulated precipitation was performed with the software SPSS. The infection showed two periods: high incidence (November-April) and low incidence (May-October). Accumulated precipitation presents an opposite behavior. The highest frequency of events (73.8% 573/779) for those born in the period with a low incidence of the virus was recorded at an earlier age (mean age 6.5 +/- 2.0 months) when compared with those born in the station of high incidence (63.5% 568/870, mean age 11.7 +/- 2.2 months). Seasonality of the infection and the inverse relationship between virus incidence and rainfall was demonstrated. In addition, it was found that the period of birth determines the age and risk of infection. This information generated during the preaccine period will be helpful to measure the impact of the vaccine against the rotavirus.

  14. Use of the gamma distribution to represent monthly rainfall in Africa for drought monitoring applications

    Science.gov (United States)

    Husak, Gregory J.; Michaelsen, Joel C.; Funk, Christopher C.

    2007-01-01

    Evaluating a range of scenarios that accurately reflect precipitation variability is critical for water resource applications. Inputs to these applications can be provided using location- and interval-specific probability distributions. These distributions make it possible to estimate the likelihood of rainfall being within a specified range. In this paper, we demonstrate the feasibility of fitting cell-by-cell probability distributions to grids of monthly interpolated, continent-wide data. Future work will then detail applications of these grids to improved satellite-remote sensing of drought and interpretations of probabilistic climate outlook forum forecasts. The gamma distribution is well suited to these applications because it is fairly familiar to African scientists, and capable of representing a variety of distribution shapes. This study tests the goodness-of-fit using the Kolmogorov–Smirnov (KS) test, and compares these results against another distribution commonly used in rainfall events, the Weibull. The gamma distribution is suitable for roughly 98% of the locations over all months. The techniques and results presented in this study provide a foundation for use of the gamma distribution to generate drivers for various rain-related models. These models are used as decision support tools for the management of water and agricultural resources as well as food reserves by providing decision makers with ways to evaluate the likelihood of various rainfall accumulations and assess different scenarios in Africa. 

  15. Dynamics of monthly rainfall-runoff process at the Gota basin: A search for chaos

    Science.gov (United States)

    Sivakumar, B.; Berndtsson, R.; Olsson, J.; Jinno, K.; Kawamura, A.

    Sivakumar et al. (2000a), by employing the correlation dimension method, provided preliminary evidence of the existence of chaos in the monthly rainfall-runoff process at the Gota basin in Sweden. The present study verifies and supports the earlier results and strengthens such evidence. The study analyses the monthly rainfall, runoff and runoff coefficient series using the nonlinear prediction method, and the presence of chaos is investigated through an inverse approach, i.e. identifying chaos from the results of the prediction. The presence of an optimal embedding dimension (the embedding dimension with the best prediction accuracy) for each of the three series indicates the existence of chaos in the rainfall-runoff process, providing additional support to the results obtained using the correlation dimension method. The reasonably good predictions achieved, particularly for the runoff series, suggest that the dynamics of the rainfall-runoff process could be understood from a chaotic perspective. The predictions are also consistent with the correlation dimension results obtained in the earlier study, i.e. higher prediction accuracy for series with a lower dimension and vice-versa, so that the correlation dimension method can indeed be used as a preliminary indicator of chaos. However, the optimal embedding dimensions obtained from the prediction method are considerably less than the minimum dimensions essential to embed the attractor, as obtained by the correlation dimension method. A possible explanation for this could be the presence of noise in the series, since the effects of noise at higher embedding dimensions could be significantly greater than that at lower embedding dimensions.

  16. a Statistically Dependent Approach for the Monthly Rainfall Forecastfrom One Point Observations

    Science.gov (United States)

    Pucheta, J.; Patiño, D.; Kuchen, B.

    In this work an adaptive linear filter model in a autoregressive moving average (ARMA) topology for forecasting time series is presented. The time series are composed by observations of the accumulative rainfall every month during several years. The learning rule used to adjust the filter coefficients is mainly based on the gradient-descendent method. In function of the long and short term stochastic dependence of the time series, we propose an on-line heuristic law to set the training process and to modify the filter topology. The input patterns for the predictor filter are the values of the time series after applying a time-delay operator. Hence, the filter's output will tend to approximate the current value available from the data series. The approach is tested over a time series obtained from measures of the monthly accumulative rainfall from La Perla, Cordoba, Argentina. The performance of the presented approach is shown by forecasting the following 18 months from a hypothetical actual time for four time series of 102 data length.

  17. Detecting trends in 10-day rainfall amounts at five sites in the state ofSão Paulo, Brazil

    Directory of Open Access Journals (Sweden)

    Gabriel Constantino Blain

    2014-09-01

    Full Text Available The temporal distribution of the rainfall events within a crop growing season plays a crucial role on the crop yield. In this way, the main goal of this study was to evaluate the presence of climate trends in the 10-day rainfall totalsobtained from five weather stations in the State of São Paulo, Brazil (1951-2012.The autocorrelation function, the Run test and the Durbin-Watson test indicateda lack of significant serial correlation in theseseries. The wavelet analysis revealed no conclusive evidence of periodicities in the temporal variability of this variable. According to the Mann-Kendall test, most of the 10-day rainfall amounts obtained from the five weather stations shows no significant trends. However, for the locations of States Campinas, Pindorama and Ribeirão Preto, the significant decreasing trends observed during the 2nd and 3rd ten days of October suggests a possible change in the climatic patterns of these locations, which may be linked to a delay in the return of the rainy season.

  18. Transfer function modeling of the monthly accumulated rainfall series over the Iberian Peninsula

    Energy Technology Data Exchange (ETDEWEB)

    Mateos, Vidal L.; Garcia, Jose A.; Serrano, Antonio; De la Cruz Gallego, Maria [Departamento de Fisica, Universidad de Extremadura, Badajoz (Spain)

    2002-10-01

    In order to improve the results given by Autoregressive Moving-Average (ARMA) modeling for the monthly accumulated rainfall series taken at 19 observatories of the Iberian Peninsula, a Discrete Linear Transfer Function Noise (DLTFN) model was applied taking the local pressure series (LP), North Atlantic sea level pressure series (SLP) and North Atlantic sea surface temperature (SST) as input variables, and the rainfall series as the output series. In all cases, the performance of the DLTFN models, measured by the explained variance of the rainfall series, is better than the performance given by the ARMA modeling. The best performance is given by the models that take the local pressure as the input variable, followed by the sea level pressure models and the sea surface temperature models. Geographically speaking, the models fitted to those observatories located in the west of the Iberian Peninsula work better than those on the north and east of the Peninsula. Also, it was found that there is a region located between 0 N and 20 N, which shows the highest cross-correlation between SST and the peninsula rainfalls. This region moves to the west and northwest off the Peninsula when the SLP series are used. [Spanish] Con el objeto de mejorar los resultados porporcionados por los modelos Autorregresivo Media Movil (ARMA) ajustados a las precipitaciones mensuales acumuladas registradas en 19 observatorios de la Peninsula Iberica se han usado modelos de funcion de transferencia (DLTFN) en los que se han empleado como variable independiente la presion local (LP), la presion a nivel del mar (SLP) o la temperatura de agua del mar (SST) en el Atlantico Norte. En todos los casos analizados, los resultados obtenidos con los modelos DLTFN, medidos mediante la varianza explicada por el modelo, han sido mejores que los resultados proporcionados por los modelos ARMA. Los mejores resultados han sido dados por aquellos modelos que usan la presion local como variable de entrada, seguidos

  19. 20 CFR 404.222 - Use of benefit table in finding your primary insurance amount from your average monthly wage.

    Science.gov (United States)

    2010-04-01

    ... insurance amount from your average monthly wage. 404.222 Section 404.222 Employees' Benefits SOCIAL SECURITY... Average-Monthly-Wage Method of Computing Primary Insurance Amounts § 404.222 Use of benefit table in finding your primary insurance amount from your average monthly wage. (a) General. We find your...

  20. Spatiotemporal monthly rainfall reconstruction via artificial neural network – case study: south of Brazil

    Directory of Open Access Journals (Sweden)

    A. O. Cardoso

    2007-04-01

    Full Text Available Climatological records users, frequently, request time series for geographical locations where there is no observed meteorological attributes. Climatological conditions of the areas or points of interest have to be calculated interpolating observations in the time of neighboring stations and climate proxy. The aim of the present work is the application of reliable and robust procedures for monthly reconstruction of precipitation time series. Time series is a special case of symbolic regression and we can use Artificial Neural Network (ANN to explore the spatiotemporal dependence of meteorological attributes. The ANN seems to be an important tool for the propagation of the related weather information to provide practical solution of uncertainties associated with interpolation, capturing the spatiotemporal structure of the data. In practice, one determines the embedding dimension of the time series attractor (delay time that determine how data are processed and uses these numbers to define the network's architecture. Meteorological attributes can be accurately predicted by the ANN model architecture: designing, training, validation and testing; the best generalization of new data is obtained when the mapping represents the systematic aspects of the data, rather capturing the specific details of the particular training set. As illustration one takes monthly total rainfall series recorded in the period 1961–2005 in the Rio Grande do Sul – Brazil. This reliable and robust reconstruction method has good performance and in particular, they were able to capture the intrinsic dynamic of atmospheric activities. The regional rainfall has been related to high-frequency atmospheric phenomena, such as El Niño and La Niña events, and low frequency phenomena, such as the Pacific Decadal Oscillation.

  1. Cluster analysis applied to the spatial and temporal variability of monthly rainfall in Mato Grosso do Sul State, Brazil

    Science.gov (United States)

    Teodoro, Paulo Eduardo; de Oliveira-Júnior, José Francisco; da Cunha, Elias Rodrigues; Correa, Caio Cezar Guedes; Torres, Francisco Eduardo; Bacani, Vitor Matheus; Gois, Givanildo; Ribeiro, Larissa Pereira

    2016-04-01

    The State of Mato Grosso do Sul (MS) located in Brazil Midwest is devoid of climatological studies, mainly in the characterization of rainfall regime and producers' meteorological systems and rain inhibitors. This state has different soil and climatic characteristics distributed among three biomes: Cerrado, Atlantic Forest and Pantanal. This study aimed to apply the cluster analysis using Ward's algorithm and identify those meteorological systems that affect the rainfall regime in the biomes. The rainfall data of 32 stations (sites) of the MS State were obtained from the Agência Nacional de Águas (ANA) database, collected from 1954 to 2013. In each of the 384 monthly rainfall temporal series was calculated the average and applied the Ward's algorithm to identify spatial and temporal variability of rainfall. Bartlett's test revealed only in January homogeneous variance at all sites. Run test showed that there was no increase or decrease in trend of monthly rainfall. Cluster analysis identified five rainfall homogeneous regions in the MS State, followed by three seasons (rainy, transitional and dry). The rainy season occurs during the months of November, December, January, February and March. The transitional season ranges between the months of April and May, September and October. The dry season occurs in June, July and August. The groups G1, G4 and G5 are influenced by South Atlantic Subtropical Anticyclone (SASA), Chaco's Low (CL), Bolivia's High (BH), Low Levels Jet (LLJ) and South Atlantic Convergence Zone (SACZ) and Maden-Julian Oscillation (MJO). Group G2 is influenced by Upper Tropospheric Cyclonic Vortex (UTCV) and Front Systems (FS). The group G3 is affected by UTCV, FS and SACZ. The meteorological systems' interaction that operates in each biome and the altitude causes the rainfall spatial and temporal diversity in MS State.

  2. Amount and Timing of Group-Based Childcare from Birth and Cognitive Development at 51 Months: A UK Study

    Science.gov (United States)

    Barnes, Jacqueline; Melhuish, Edward C.

    2017-01-01

    This study investigated whether the amount and timing of group-based childcare between birth and 51 months were predictive of cognitive development at 51 months, taking into account other non-parental childcare, demographic characteristics, cognitive development at 18 months, sensitive parenting and a stimulating home environment. Children's…

  3. Meta-heuristic ant colony optimization technique to forecast the amount of summer monsoon rainfall: skill comparison with Markov chain model

    Science.gov (United States)

    Chaudhuri, Sutapa; Goswami, Sayantika; Das, Debanjana; Middey, Anirban

    2014-05-01

    Forecasting summer monsoon rainfall with precision becomes crucial for the farmers to plan for harvesting in a country like India where the national economy is mostly based on regional agriculture. The forecast of monsoon rainfall based on artificial neural network is a well-researched problem. In the present study, the meta-heuristic ant colony optimization (ACO) technique is implemented to forecast the amount of summer monsoon rainfall for the next day over Kolkata (22.6°N, 88.4°E), India. The ACO technique belongs to swarm intelligence and simulates the decision-making processes of ant colony similar to other adaptive learning techniques. ACO technique takes inspiration from the foraging behaviour of some ant species. The ants deposit pheromone on the ground in order to mark a favourable path that should be followed by other members of the colony. A range of rainfall amount replicating the pheromone concentration is evaluated during the summer monsoon season. The maximum amount of rainfall during summer monsoon season (June—September) is observed to be within the range of 7.5-35 mm during the period from 1998 to 2007, which is in the range 4 category set by the India Meteorological Department (IMD). The result reveals that the accuracy in forecasting the amount of rainfall for the next day during the summer monsoon season using ACO technique is 95 % where as the forecast accuracy is 83 % with Markov chain model (MCM). The forecast through ACO and MCM are compared with other existing models and validated with IMD observations from 2008 to 2012.

  4. ANALYSIS OF THE STATISTICAL BEHAVIOUR OF DAILY MAXIMUM AND MONTHLY AVERAGE RAINFALL ALONG WITH RAINY DAYS VARIATION IN SYLHET, BANGLADESH

    Directory of Open Access Journals (Sweden)

    G. M. J. HASAN

    2014-10-01

    Full Text Available Climate, one of the major controlling factors for well-being of the inhabitants in the world, has been changing in accordance with the natural forcing and manmade activities. Bangladesh, the most densely populated countries in the world is under threat due to climate change caused by excessive use or abuse of ecology and natural resources. This study checks the rainfall patterns and their associated changes in the north-eastern part of Bangladesh mainly Sylhet city through statistical analysis of daily rainfall data during the period of 1957 - 2006. It has been observed that a good correlation exists between the monthly mean and daily maximum rainfall. A linear regression analysis of the data is found to be significant for all the months. Some key statistical parameters like the mean values of Coefficient of Variability (CV, Relative Variability (RV and Percentage Inter-annual Variability (PIV have been studied and found to be at variance. Monthly, yearly and seasonal variation of rainy days also analysed to check for any significant changes.

  5. Interpolation of monthly precipitation amounts in mountainous catchments with sparse precipitation networks

    Directory of Open Access Journals (Sweden)

    Alexandra P Jacquin

    2013-12-01

    Full Text Available Most studies dealing with the interpolation of precipitation gauge data have focused in areas where the meteorological network is relatively dense, implying that it is still unknown what interpolation methods are more appropriate in the case of mountain catchments with scarce gauge data. This study evaluates the applicability of Kriging with External Drift (KED and the Optimal Interpolation Method (OIM for interpolation of monthly precipitation in these situations. Thiessen Polygons (TP are used as benchmark. The study area corresponds to the upper subcatchment of Aconcagua River, Central Chile. Cross-validation experiments revealed that all these methods show similar performance in the lower zone of the study area, but OIM outperforms TP and KED at high elevations. Optimal Interpolation Method generally produces the smallest bias in the Andean zone of the study area, with mean errors whose absolute values are smaller than 9% of mean monthly precipitation. From April to September, the root mean squared errors of OIM are between 14% and 33% smaller than those of TP and KED in this zone. Although KED achieves a good agreement to mean monthly values at high elevations (mean errors smaller than 19% in absolute value, its performance is comparable to that of TP in terms of root mean squared errors. Long-term water balances did not provide evidence against the applicability of KED and OIM. Nevertheless, the results of the cross-validation experiments indicate that OIM is a better alternative than KED for the interpolation of monthly precipitation in the study area.

  6. Monthly oceanic rainfall based on METH techniques: DMSP SSM/I V6 and SSMIS continuity

    Science.gov (United States)

    Chiu, L. S.; Gao, S.; Shin, D.-B.; Cho, Y.-J.; Adler, R. F.; Huffman, G.; Bolvin, D.; Nelkin, E.

    2012-04-01

    As part of the Global Precipitation Climatology Project (GPCP), our group have been producing oceanic rainfall over 2.5 and 5 degree boxes by applying the Microwave Emission brightness Temperature (Tb) Histogram, or METH technique to the Special Sensor Microwave Imager (SSM/I) data taken on board the Defense Meteorological Satellite Program (DMSP) satellite series. Recently, the rainfall series have been updated using the V6 SSM/I provided by RSS (Chiu and Chokngamwong., 2010). With the demise of the F15 SSM/I sensor, we examine the use of the SSMIS series to continue the DMSP time series. With its long duration, the DMSP satellite sensors constitute a unique data set capable of producing microwave-based products for climate studies. We compared the F13 SSM/I and F17 SSMIS for the period January 2008 - September 2009. The METH technique matches the histogram of Tb (twice 19V minus 22V) to a mixed-distribution of rain rates and estimates the parameters of the rain rate distribution. Mathematical convergence of the matching procedure is reached when a certain Chi-square threshold is reached. The important parameters are the Tb of the non-raining pixels (To) and the freezing level (FL) of the grid box considered. The sample size of the SSMIS is much larger than the SSM/I, hence the convergence criteria is relaxed by changing the Chi-square threshold. Preliminary results show a slight shift of the To (~0.8K). By adjusting To by a constant, the domain average SSMIS rain rates and FL are computed to within 2% and 1% of the SSM/I rain rates, respectively. Further investigation of the SSMIS METH rain rate will involve the comparison of the 19V and 22V and fine tuning the Chi-square parameter.

  7. Medicare determinations and income-related monthly adjustment amounts to Medicare Part B premiums; conforming changes to regulations. Final rule.

    Science.gov (United States)

    2014-03-01

    This final rule adopts, without change, the interim final rule with request for comments we published in the Federal Register on September 18, 2013. The interim final rule modified our rules regarding Medicare Part B income-related monthly adjustment amounts to conform to changes made to the Social Security Act (Act) and Internal Revenue Code by the Affordable Care Act. We also removed provisions that phased in income-related monthly adjustment amounts between 2007 and 2009 and updated a citation to reflect the transfer of authority for hearing appeals under title XVIII of the Act from the Social Security Administration to the Department of Health and Human Services.

  8. Dynamical forecast vs Ensemble Streamflow Prediction (ESP): how sensitive are monthly and seasonal hydrological forecasts to the quality of rainfall drivers?

    Science.gov (United States)

    Tanguy, Maliko; Prudhomme, Christel; Harrigan, Shaun; Smith, Katie

    2017-04-01

    Seasonal forecasting of hydrological extremes is challenging for the hydro-meteorological modelling community, and the performance of hydrological forecasts at lead times over 1 month is still poor especially for catchments with limited hydrological memory. A considerable amount of effort is being invested within the meteorological community to improve dynamic meteorological forecasting which can then be used to drive hydrological models to produce physically-driven hydrological forecasts. However, currently for the UK, these meteorological forecasts are being produced at 1 month or seasonal time-step, whereas hydrological models often require daily or sub-daily time-steps. A simpler way to get seasonal forecasts is to use historical climate data to drive hydrological models using Ensemble Streamflow Prediction (ESP). This gives a range of possible future hydrological status given known initial conditions, but it does not contain any information on the future dynamic of the atmosphere. The error is highly dependent on the type of catchment, but ESP is an improvement compared to simply using climatology of river flows, especially in groundwater dominated catchments. The objective of this study is to find out how accurate the seasonal rainfall forecast has to be (in terms of total rainfall and temporal distribution) for the dynamical seasonal forecast to beat ESP. To this aim, we have looked at the sensitivity of hydrological models to the quality of driving rainfall input, proxy of 'best possible' forecasts. Study catchments representative of the range of UK's hydro-climatic conditions were selected. For these catchments, synthetic rainfall time series derived from observed data were created by increasingly degrading the data. The number of rainy days, their intensity and their sequencing were artificially modified to analyse which of these characteristics is most important to get a better hydrological forecast using a simple lumped hydrological model (GR4J), and

  9. Rainfall erosivity estimation based on rainfall data collected over a range of temporal resolutions

    Directory of Open Access Journals (Sweden)

    S. Yin

    2015-05-01

    Full Text Available Rainfall erosivity is the power of rainfall to cause soil erosion by water. The rainfall erosivity index for a rainfall event, EI30, is calculated from the total kinetic energy and maximum 30 min intensity of individual events. However, these data are often unavailable in many areas of the world. The purpose of this study was to develop models that relate more commonly available rainfall data resolutions, such as daily or monthly totals, to rainfall erosivity. Eleven stations with one-minute temporal resolution rainfall data collected from 1961 through 2000 in the eastern water-erosion areas of China were used to develop and calibrate 21 models. Seven independent stations, also with one-minute data, were utilized to validate those models, together with 20 previously published equations. Results showed that models in this study performed better or similar to models from previous research to estimate rainfall erosivity for these data. Prediction capabilities, as determined using symmetric mean absolute percentage errors and Nash–Sutcliffe model efficiency coefficients, were demonstrated for the 41 models including those for estimating erosivity at event, daily, monthly, yearly, average monthly and average annual time scales. Prediction capabilities were generally better using higher resolution rainfall data as inputs. For example, models with rainfall amount and maximum 60 min rainfall amount as inputs performed better than models with rainfall amount and maximum daily rainfall amount, which performed better than those with only rainfall amount. Recommendations are made for choosing the appropriate estimation equation, which depend on objectives and data availability.

  10. Entropy of stable seasonal rainfall distribution in Kelantan

    Science.gov (United States)

    Azman, Muhammad Az-zuhri; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Radi, Noor Fadhilah Ahmad

    2017-05-01

    Investigating the rainfall variability is vital for any planning and management in many fields related to water resources. Climate change can gives an impact of water availability and may aggravate water scarcity in the future. Two statistics measurements which have been used by many researchers to measure the rainfall variability are variance and coefficient of variation. However, these two measurements are insufficient since rainfall distribution in Malaysia especially in the East Coast of Peninsular Malaysia is not symmetric instead it is positively skewed. In this study, the entropy concept is used as a tool to measure the seasonal rainfall variability in Kelantan and ten rainfall stations were selected. In previous studies, entropy of stable rainfall (ESR) and apportionment entropy (AE) were used to describe the rainfall amount variability during years for Australian rainfall data. In this study, the entropy of stable seasonal rainfall (ESSR) is suggested to model rainfall amount variability during northeast monsoon (NEM) and southwest monsoon (SWM) seasons in Kelantan. The ESSR is defined to measure the long-term average seasonal rainfall amount variability within a given year (1960-2012). On the other hand, the AE measures the rainfall amounts variability across the months. The results of ESSR and AE values show that stations in east coastline are more variable as compared to other stations inland for Kelantan rainfall. The contour maps of ESSR for Kelantan rainfall stations are also presented.

  11. Long-range forecast of monthly rainfall over India during summer monsoon season using SST in the north Indian Ocean

    Digital Repository Service at National Institute of Oceanography (India)

    Sadhuram, Y.

    Long-range forecasting of summer monsoon rainfall was reported through linear models by Delsole and Shukla3. They showed that minimum number of predictors are sufficient for accurate forecasts. Recent studies4,5 reported long-range prediction...

  12. Hydrological behaviour of the Nilgiri sub-watersheds as affected by bluegum plantations, part II. Monthly water balances at different rainfall and runoff probabilities

    Science.gov (United States)

    Sharda, V. N.; Samraj, P.; Chinnamani, S.; Lakshmanan, V.

    1988-11-01

    Frequency analyses of rainfall and runoff at Ootacamund (the Nilgiris) under conditions of natural grassland and savannah "Shola" land have been carried out. Availability of water at different probabilities during different months after conversion of natural grasslands into bluegum (eucalyptus) plantations has also been worked out. Investigations revealed that the maximum rainfall occurs during the month of July (298.2 mm at 50% chance) and the minimum is received during January (1.5 mm at 50% chance). On an average, the expected total flow and base flow under natural conditions of grasslands and "Shola" are 31% and 22% respectively of the expected rainfall of the region. The expected available total flow is maximum (45.8 mm at 50% chance) during the month of August out of which 31.18 mm is contributed by base flow. The minimum expected available water is observed during January-April (the lowest during March). Plantation of bluegum in natural grasslands further reduces water yield by about 23% (at 50% chance) during these months. These reductions in water yield during lean months may affect the water supply into the downstream hydroelectric reservoirs in the region. Hence, caution may have to be exercised while planning large-scale conversion of natural grasslands into bluegum plantations.

  13. Analysis of the Amount of Rainfall Based on the Magnitude of Flood%基于洪水强度的地面雨情信息分析

    Institute of Scientific and Technical Information of China (English)

    刘洋; 李诚志; 孟现勇; 邓兴耀; 刘志辉

    2016-01-01

    two different time scales which corresponding to two different intensity of floods, The results show that using curvature to approach flow process can accurately infer flood level, but there is a modest gap about rainfall amount between model calculation and actual observation.

  14. Regulations regarding income-related monthly adjustment amounts to Medicare beneficiaries' prescription drug coverage premiums. Interim final rule with request for comments.

    Science.gov (United States)

    2010-12-01

    We are adding a new subpart to our regulations, which contains the rules we will apply to determine the income-related monthly adjustment amount for Medicare prescription drug coverage premiums. This new subpart implements changes made to the Social Security Act (Act) by the Affordable Care Act. These rules parallel the rules in subpart B of this part, which describes the rules we apply when we determine the income-related monthly adjustment amount for certain Medicare Part B (medical insurance) beneficiaries. These rules describe the new subpart; what information we will use to determine whether you will pay an income-related monthly adjustment amount and the amount of the adjustment when applicable; when we will consider a major life-changing event that results in a significant reduction in your modified adjusted gross income; and how you can appeal our determination about your income-related monthly adjustment amount. These rules will allow us to implement the provisions of the Affordable Care Act on time that relate to the income-related monthly adjustment amount for Medicare prescription drug coverage premiums, when they go into effect on January 1, 2011.

  15. Variation in stable isotope ratios of monthly rainfall in the Douala and Yaounde cities, Cameroon: local meteoric lines and relationship to regional precipitation cycle

    Science.gov (United States)

    Wirmvem, Mengnjo Jude; Ohba, Takeshi; Kamtchueng, Brice Tchakam; Taylor, Eldred Tunde; Fantong, Wilson Yetoh; Ako, Ako Andrew

    2017-09-01

    Hydrogen (D) and oxygen (18O) stable isotopes in precipitation are useful tools in groundwater recharge and climatological investigations. This study investigated the isotopes in rainfall during the 2013 and 2014 hydrological years in the Douala and Yaounde urban cities. The objectives were to generate local meteoric water lines (LMWLs), define the spatial-temporal variations of the isotopes in rainwater and their relationship to the regional precipitation cycle, and determine the factors controlling the isotopic variation. The LWMLs in Douala and Yaounde were δD = 7.92δ18O + 12.99 and δD = 8.35δ18O + 15.29, respectively. The slopes indicate isotopic equilibrium conditions during rain formation and negligible evaporation effect during rainfall. Precipitation showed similar wide ranges in δ18O values from -5.26 to -0.75 ‰ in Douala and -5.8 to +1.81 ‰ in Yaounde suggesting a common moisture source from the Atlantic Ocean. Enriched weighted mean δ18O (wδ18O) values during the low pre- and post-monsoon showers coincided with low convective activity across the entire region. Enriched isotopic signatures also marked the West African monsoon transition phase during each hydrological year. Abrupt wδ18O depletion after the transition coincided with the monsoon onset in the region. Peak periods of monsoonal rainfall, associated with high convective activities, were characterised by the most depleted wδ18O values. Controls on isotopic variations are the amount effect and moisture recycling. The stable isotope data provide a tool for groundwater recharge studies while the isotopic correlation with regional rainfall cycle demonstrate their use as markers of moisture circulation and detecting climatic changes in precipitation.

  16. Variation in stable isotope ratios of monthly rainfall in the Douala and Yaounde cities, Cameroon: local meteoric lines and relationship to regional precipitation cycle

    Science.gov (United States)

    Wirmvem, Mengnjo Jude; Ohba, Takeshi; Kamtchueng, Brice Tchakam; Taylor, Eldred Tunde; Fantong, Wilson Yetoh; Ako, Ako Andrew

    2016-04-01

    Hydrogen (D) and oxygen (18O) stable isotopes in precipitation are useful tools in groundwater recharge and climatological investigations. This study investigated the isotopes in rainfall during the 2013 and 2014 hydrological years in the Douala and Yaounde urban cities. The objectives were to generate local meteoric water lines (LMWLs), define the spatial-temporal variations of the isotopes in rainwater and their relationship to the regional precipitation cycle, and determine the factors controlling the isotopic variation. The LWMLs in Douala and Yaounde were δD = 7.92δ18O + 12.99 and δD = 8.35δ18O + 15.29, respectively. The slopes indicate isotopic equilibrium conditions during rain formation and negligible evaporation effect during rainfall. Precipitation showed similar wide ranges in δ18O values from -5.26 to -0.75 ‰ in Douala and -5.8 to +1.81 ‰ in Yaounde suggesting a common moisture source from the Atlantic Ocean. Enriched weighted mean δ18O (wδ18O) values during the low pre- and post-monsoon showers coincided with low convective activity across the entire region. Enriched isotopic signatures also marked the West African monsoon transition phase during each hydrological year. Abrupt wδ18O depletion after the transition coincided with the monsoon onset in the region. Peak periods of monsoonal rainfall, associated with high convective activities, were characterised by the most depleted wδ18O values. Controls on isotopic variations are the amount effect and moisture recycling. The stable isotope data provide a tool for groundwater recharge studies while the isotopic correlation with regional rainfall cycle demonstrate their use as markers of moisture circulation and detecting climatic changes in precipitation.

  17. Rainfall Variability, Drought Characterization, and Efficacy of Rainfall Data Reconstruction: Case of Eastern Kenya

    Directory of Open Access Journals (Sweden)

    M. Oscar Kisaka

    2015-01-01

    Full Text Available This study examined the extent of seasonal rainfall variability, drought occurrence, and the efficacy of interpolation techniques in eastern Kenya. Analyses of rainfall variability utilized rainfall anomaly index, coefficients of variance, and probability analyses. Spline, Kriging, and inverse distance weighting interpolation techniques were assessed using daily rainfall data and digital elevation model using ArcGIS. Validation of these interpolation methods was evaluated by comparing the modelled/generated rainfall values and the observed daily rainfall data using root mean square errors and mean absolute errors statistics. Results showed 90% chance of below cropping threshold rainfall (500 mm exceeding 258.1 mm during short rains in Embu for one year return period. Rainfall variability was found to be high in seasonal amounts (CV = 0.56, 0.47, and 0.59 and in number of rainy days (CV = 0.88, 0.49, and 0.53 in Machang’a, Kiritiri, and Kindaruma, respectively. Monthly rainfall variability was found to be equally high during April and November (CV = 0.48, 0.49, and 0.76 with high probabilities (0.67 of droughts exceeding 15 days in Machang’a and Kindaruma. Dry-spell probabilities within growing months were high, (91%, 93%, 81%, and 60% in Kiambere, Kindaruma, Machang’a, and Embu, respectively. Kriging interpolation method emerged as the most appropriate geostatistical interpolation technique suitable for spatial rainfall maps generation for the study region.

  18. Influence of rainfalls on heat and steam fluxes of fumarolic zones: Six months records along the Ty fault (Soufrière of Guadeloupe, Lesser Antilles)

    Science.gov (United States)

    Gaudin, Damien; Finizola, Anthony; Delcher, Eric; Beauducel, François; Allemand, Pascal; Delacourt, Christophe; Brothelande, Elodie; Peltier, Aline; Di Gangi, Fabio

    2015-09-01

    Fumarolic zones are permeable areas where both steam and heat are expelled to the atmosphere. Surface fluxes and flows, which are representative of the intensity of the hydrothermal circulation in depth, can be monitored by thermometers, thermal infrared cameras, spectrometers, or condensers. However, the superficial activity of fumarolic zones can be modified by the meteorological conditions, in particular the rainfalls, which might result in erroneous estimations. From this perspective, we developed a set of physical equations to quantify the effects of rainfalls on the thermal behavior of fumarolic zones. Results were faced to continuous measurements achieved at the Ty fault fumarolic zone (La Soufrière volcano, Guadeloupe, Lesser Antilles) during six months in 2010, using six vertical series of thermometers measuring the heat transfer in the ground and one condenser measuring the rising steam flux. Results demonstrate that in the absence of rainfalls, heat and steam flux reach an equilibrium that is representative of the geothermal flux in depth. Conversely, after the rainfalls, the cooling of the ground provokes a deepening of the condensation level. The related soil temperature drop can be estimated by computing the heat required to warm the infiltrated water up to boiling temperature while the recovery rate is directly linked to the geothermal flux. Our observations allow defining in which conditions flux are at steady state, but also to build a first-order numerical model allowing estimating both the physical parameters of the ground (thermal conductivity, precipitation efficiency coefficient and surface flux constant) and the long-term thermal behavior of the hydrothermal system. In particular, our results predict that the hydrothermal activity must vanish on the zones where the geothermal flux drops under a certain threshold (60 W/m2 at La Soufrière). The existence of this limit may have strong implications for the precipitation rate of minerals and the

  19. Sampling Errors in Monthly Rainfall Totals for TRMM and SSM/I, Based on Statistics of Retrieved Rain Rates and Simple Models

    Science.gov (United States)

    Bell, Thomas L.; Kundu, Prasun K.; Einaudi, Franco (Technical Monitor)

    2000-01-01

    Estimates from TRMM satellite data of monthly total rainfall over an area are subject to substantial sampling errors due to the limited number of visits to the area by the satellite during the month. Quantitative comparisons of TRMM averages with data collected by other satellites and by ground-based systems require some estimate of the size of this sampling error. A method of estimating this sampling error based on the actual statistics of the TRMM observations and on some modeling work has been developed. "Sampling error" in TRMM monthly averages is defined here relative to the monthly total a hypothetical satellite permanently stationed above the area would have reported. "Sampling error" therefore includes contributions from the random and systematic errors introduced by the satellite remote sensing system. As part of our long-term goal of providing error estimates for each grid point accessible to the TRMM instruments, sampling error estimates for TRMM based on rain retrievals from TRMM microwave (TMI) data are compared for different times of the year and different oceanic areas (to minimize changes in the statistics due to algorithmic differences over land and ocean). Changes in sampling error estimates due to changes in rain statistics due 1) to evolution of the official algorithms used to process the data, and 2) differences from other remote sensing systems such as the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I), are analyzed.

  20. A rainfall simulation model for agricultural development in Bangladesh

    Directory of Open Access Journals (Sweden)

    M. Sayedur Rahman

    2000-01-01

    Full Text Available A rainfall simulation model based on a first-order Markov chain has been developed to simulate the annual variation in rainfall amount that is observed in Bangladesh. The model has been tested in the Barind Tract of Bangladesh. Few significant differences were found between the actual and simulated seasonal, annual and average monthly. The distribution of number of success is asymptotic normal distribution. When actual and simulated daily rainfall data were used to drive a crop simulation model, there was no significant difference of rice yield response. The results suggest that the rainfall simulation model perform adequately for many applications.

  1. Changes in rainfall amount and frequency do not affect the outcome of the interaction between the shrub Retama sphaerocarpa and its neighbouring grasses in two semiarid communities

    Science.gov (United States)

    Soliveres, Santiago; García-Palacios, Pablo; Maestre, Fernando T.; Escudero, Adrián; Valladares, Fernando

    2015-01-01

    We evaluated the net outcome of the interaction between the shrub Retama sphaerocarpa, our target plant, and different herbaceous neighbours in response to changes in the magnitude and frequency of rainfall events during three years. The experiment was conducted in natural and anthropogenic grasslands dominated by a perennial stress-tolerator and ruderal annual species, respectively. In spite of the neutral or positive effects of neighbours on water availability, neighbouring plants reduced the performance of Retama juveniles, suggesting competition for resources other than water. The negative effects of grasses on the photochemical efficiency of Retama juveniles decreased with higher water availabilities or heavier irrigation pulses, depending on the grassland studied; however, these effects did not extent to the survival and growth of Retama juveniles. Our findings show the prevalence of competitive interactions among the studied plants, regardless of the water availability and its temporal pattern. These results suggest that positive interactions may not prevail under harsher conditions when shade-intolerant species are involved. This study could be used to further refine our predictions of how plant-plant interactions will respond to changes in rainfall, either natural or increased by the ongoing climatic change, in ecosystems where grass-shrubs interactions are prevalent. PMID:25914429

  2. Monthly and seasonal variation in the amount of total lipid and fatty acid in the muscle of a silurid cat fish Wallagu attu

    Directory of Open Access Journals (Sweden)

    Pinak Dutta

    2014-09-01

    Full Text Available Monthly and seasonal variation in the amount of total lipid and fatty acid in the muscle tissues of W. attu growing wild in large ponds was studied. The result depicts that both the amounts of total lipid and fatty acid varied monthly and thus seasonally in this fish species (boal belonging to the family of fresh water silurid cat fishes. The percentage of total lipid value reaches its minimum in May and starts increasing from June to October. During breeding season the amount of total fatty acid also shows the same tendency to decrease till May when it reaches its minimum. From June onwards the total fatty acid increases significantly. At the end of the reproductive season, i.e. during the commencement of the nutritional season, the fishes start the process of storing energy in the form of lipids / fatty acids for future use i.e. during reproduction season or during scarcity of food. This is what is reflected in the study that, during the monsoon months in West Bengal the lipid / fatty acid content in the muscle tissues of boal rises to the maximum. This starts decreasing in the winter season as the reproduction period approaches and reaches its minimum in summer.

  3. Assessment for backwater amount in unsaturated zone in landslide in rainfall process%降雨过程中滑体非饱和带的滞水量计算分析

    Institute of Scientific and Technical Information of China (English)

    王智磊; 孙红月; 尚岳全; 赵权利

    2013-01-01

    为研究滑体中的非饱和带滞水在降雨补给潜水过程中的作用,提出降雨过程中非饱和带滞水的计算方法以及以非饱和带滞水为指标的降雨阈值评价方法.通过监测降雨量、坡体潜水位及排水结构的排水流量,建立统计模型来评估降雨产生的非饱和带滞水量.利用排水隧洞影响范围内的坡体模型和均匀渗流理论正坡浸润线分析了潜水位变化所对应的土体中潜水释水量,使潜水位通过量纲变换后与降雨量和排水流量量纲一致,从而进行三者的统计模型分析.利用坡体高度饱和条件下降雨过程的监测数据建立向量自回归模型,用于计算理论降雨量,得到低水位条件下降雨过程中产生的非饱和带滞水量.根据浙江省杭金衢高速公路K103滑坡的案例,采用三次暴雨过程中的降雨、排水隧洞排水流量与潜水位监测值对降雨过程中产生的非饱和带滞水量进行了计算,分析了非饱和带滞水量对降雨补给潜水过程所起的作用,结果表明:可以将当滞水量重量达到60 kN且地下水位达到0.6m时作为指标来确定降雨阈值.%To analyze the effect of backwater in unsaturated zone in the process that rain fed the groundwater in landslide,the computing method for backwater amount in rain process and evaluation method for rainfall threshold with the index of backwater were presented.The backwater amount induced by rainfall was deduced from the statistical model which was based on the monitoring data containing rainfall,groundwater level in landslide and water discharge from drainage structure.To make dimensions consistency of the monitoring data from rainfall,water discharge and groundwater level for statistical analysis,a seepage field model of drainage tunnel was estsablished.In this model,the groundwater level variation was related to water release quantity considering the line of seepage in positive slope in uniform flow theory.In the

  4. Rainfall Erosivity Database on the European Scale (REDES): A product of a high temporal resolution rainfall data collection in Europe

    Science.gov (United States)

    Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Alewell, Christine

    2016-04-01

    The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the (R)USLE model. The R-factor is calculated from a series of single storm events by multiplying the total storm kinetic energy with the measured maximum 30-minutes rainfall intensity. This estimation requests high temporal resolution (e.g. 30 minutes) rainfall data for sufficiently long time periods (i.e. 20 years) which are not readily available at European scale. The European Commission's Joint Research Centre(JRC) in collaboration with national/regional meteorological services and Environmental Institutions made an extensive data collection of high resolution rainfall data in the 28 Member States of the European Union plus Switzerland in order to estimate rainfall erosivity in Europe. This resulted in the Rainfall Erosivity Database on the European Scale (REDES) which included 1,541 rainfall stations in 2014 and has been updated with 134 additional stations in 2015. The interpolation of those point R-factor values with a Gaussian Process Regression (GPR) model has resulted in the first Rainfall Erosivity map of Europe (Science of the Total Environment, 511, 801-815). The intra-annual variability of rainfall erosivity is crucial for modelling soil erosion on a monthly and seasonal basis. The monthly feature of rainfall erosivity has been added in 2015 as an advancement of REDES and the respective mean annual R-factor map. Almost 19,000 monthly R-factor values of REDES contributed to the seasonal and monthly assessments of rainfall erosivity in Europe. According to the first results, more than 50% of the total rainfall erosivity in Europe takes place in the period from June to September. The spatial patterns of rainfall erosivity have significant differences between Northern and Southern Europe as summer is the most erosive period in Central and Northern Europe and autumn in the

  5. Rainfall Analyses of Coonoor Hill Station of Nilgiris District for Landslide Studies

    Science.gov (United States)

    Ramani Sujatha, Evangelin; Suribabu, C. R.

    2017-07-01

    The most common triggering factor of landslides in a hill terrain is rainfall. Assessment of the extreme and antecedent rainfall events and its quantum is imperative to evaluate the temporal occurrence of landslides. It also plays a vital role in the choice of the preventive measures to be adopted. This study focuses on an in-depth rainfall analysis of Coonoor hill station. The analysis includes the study of monthly, seasonal and annual rainfall patterns for a period of 80 years, between 1935 and 2013. Further, one day maximum, 5 day and more antecedent rainfall and its amount is calculated for the years between 2007-2012, 2014 and 2015.The result of the study indicates an increase in the normal rainfall based on the mean of 30 years of data (for the recent decades) and erratic pattern of rainfall during pre-monsoon, post-monsoon south-west monsoon periods. A detailed analysis of daily rainfall for the selected period indicates that extreme highest daily rainfall of more than 300 mm above occurred after consecutive rainfall trigged massive landslides comparing highest rainfall amount around 100 to 180 mm rainfall events.

  6. Medicare determinations and income-related monthly adjustment amounts to Medicare Part B premiums; conforming changes to regulations. Interim final rule with request for comments.

    Science.gov (United States)

    2013-09-18

    We are modifying our regulations regarding Medicare Part B income-related monthly adjustment amounts (IRMAA) in order to conform to changes made to the Social Security Act (Act) by the Affordable Care Act. This rule freezes the modified adjusted gross income threshold and ranges from 2011 through 2019 and removes the requirement that beneficiaries consent to our release of Internal Revenue Service (IRS) information to the U.S. Department of Health and Human Services (HHS) for the purpose of adjudicating any appeal of an IRMAA to the Part B premium subsidy. We are also removing provisions that phased in IRMAA between 2007 and 2009 and updating a citation to reflect the transfer of authority for hearing appeals under Title XVIII of the Act from the Social Security Administration to HHS.

  7. Spatial-Temporal Variation and Prediction of Rainfall in Northeastern Nigeria

    Directory of Open Access Journals (Sweden)

    Umar M. Bibi

    2014-09-01

    Full Text Available In Northeastern Nigeria seasonal rainfall is critical for the availability of water for domestic use through surface and sub-surface recharge and agricultural production, which is mostly rain fed. Variability in rainfall over the last 60 years is the main cause for crop failure and water scarcity in the region, particularly, due to late onset of rainfall, short dry spells and multi-annual droughts. In this study, we analyze 27 years (1980–2006 of gridded daily rainfall data obtained from a merged dataset by the National Centre for Environmental Prediction and Climate Research Unit reanalysis data (NCEP-CRU for spatial-temporal variability of monthly amounts and frequency in rainfall and rainfall trends. Temporal variability was assessed using the percentage coefficient of variation and temporal trends in rainfall were assessed using maps of linear regression slopes for the months of May through October. These six months cover the period of the onset and cessation of the wet season throughout the region. Monthly rainfall amount and frequency were then predicted over a 24-month period using the Auto Regressive Integrated Moving Average (ARIMA Model. The predictions were evaluated using NCEP-CRU data for the same period. Kolmogorov Smirnov test results suggest that despite there are some months during the wet season (May–October when there is no significant agreement (p < 0.05 between the monthly distribution of the values of the model and the corresponding 24-month NCEP-CRU data, the model did better than simply replicating the long term mean of the data used for the prediction. Overall, the model does well in areas and months with lower temporal rainfall variability. Maps of the coefficient of variation and regression slopes are presented to indicate areas of high rainfall variability and water deficit over the period under study. The implications of these results for future policies on Agriculture and Water Management in the region are

  8. An assessment of El Niño and La Niña impacts focused on monthly and seasonal rainfall and extreme dry/precipitation events in mountain regions of Colombia and México

    Science.gov (United States)

    Pinilla Herrera, María Carolina; Andrés Pinzón Correa, Carlos

    2016-03-01

    The influence of El Niño and La Niña on monthly and seasonal rainfall over mountain landscapes in Colombia and México was assessed based on the Oceanic Niño Index (ONI). A statistical analysis was develop to compare the extreme dry/precipitation events between El Niño, La Niña and Neutral episodes. For both areas, it was observed that El Niño and La Niña episodes are associated with important increases or decreases in rainfall. However, Neutral episodes showed the highest occurrence of extreme precipitation/dry events. For a better understanding of the impact of El Niño and La Niña on seasonal precipitation, we did a compound and a GIS analyses to define the high/low probability of above, below or normal seasonal precipitation under El Niño, La Niña and cold/warm Neutral episodes. In San Vicente, Colombia the below-normal seasonal rainfall was identified during El Niño and Neutral episodes in the dry season JJA. In this same municipality we also found above-normal seasonal rainfall during La Niña and Neutral episodes, especially in the dry season DJF. In Tancítaro México the below-normal seasonal rainfall was identified during La Niña winters (DJF) and El Niño summers (JJA), the above-normal seasonal rainfall was found during La Niña summers (JJA) and El Niño winters (DJF).

  9. Reasonability Analysis of Chaotic Identification of Monthly Rainfall Series%月降雨序列的混沌判定的合理性分析

    Institute of Scientific and Technical Information of China (English)

    路剑飞; 陈子燊

    2011-01-01

    针对目前月降雨序列混沌特性研究中存在的问题,以广东省西江流域高要站月降雨序列为例,运用功率谱方法、主成分分析法、饱和关联维数法、C-C方法进行了混沌特性的判定及特征参数的求取,同时分析了数据长度和噪声对混沌研究的影响.研究结果表明,利用功率谱方法进行混沌判定时,单纯的根据连续多峰的噪声背景作为判定混沌存在的依据并不可靠;饱和关联维数法仅从能量角度对混沌序列进行判定,此外,对混沌序列进行滤波会导致此法判定结果的稳健性降低,C-C方法证明了其计算结果的可靠性;为计算出相对稳定的饱和关联维D2,计算数据的长度至少应为450个点;递归图及相应的各种定量判定标准验证了改进的双小波空域降噪方法可有效去除混沌序列中噪声的影响.%A discussion is conducted due to several problems presented in chaotic research of monthly rainfall series.As an example, monthly precipitation data of Gaoyao Station in West River basin in Guangdong Province is utilized for chaotic identification and calculation of characteristic parameters via power spectrum method, PCA, G-P Algorithm and C-C method.Impacts of data length and noise in the dataset are also studied.The results show that it is not reliable to judge a chaotic feature reflected on the power spectrum as successive multi-peaks; although chaotic series and noise can be distinguished directly with PCA method,it can only be held in the way of energy; besides, filtering process on chaotic series will make identification results derived from PCA method unstable; embedded parameters calculated with C-C method prove the validity of results from G-P Algorithm; take dataset used in this paper for example, a relatively stable D2 can be calculated on the premise that at least 450 data points are considered; recurrence plot and corresponding quantitative analysis indices validate effectiveness of

  10. Rainfall generation

    Science.gov (United States)

    Sharma, Ashish; Mehrotra, Raj

    This chapter presents an overview of methods for stochastic generation of rainfall at annual to subdaily time scales, at single- to multiple-point locations, and in a changing climatic regime. Stochastic rainfall generators are used to provide inputs for risk assessment of natural or engineering systems that can undergo failure under sustained (high or low) extremes. As a result, generation of rainfall has evolved to provide options that adequately represent such conditions, leading to sequences that exhibit low-frequency variability of a nature similar to the observed rainfall. The chapter consists of three key sections: the first two outlining approaches for rainfall generation using endogenous predictor variables and the third highlighting approaches for generation using exogenous predictors often simulated to represent future climatic conditions. The first section presents approaches for generation of annual and seasonal rainfall and daily rainfall, both at single-point locations and multiple sites, with an emphasis on alternatives that ensure appropriate representation of low-frequency variability in the generated rainfall sequences. The second section highlights advancements in the subdaily rainfall generation procedures including commonly used approaches for daily to subdaily rainfall generation. The final section (generation using exogenous predictors) presents a range of alternatives for stochastic downscaling of rainfall for climate change impact assessments of natural and engineering systems. We conclude the chapter by outlining some of the key challenges that remain to be addressed, especially in generation under climate change conditions, with an emphasis on the importance of incorporating uncertainty present in both measurements and models, in the rainfall sequences that are generated.

  11. Theoretical framework to estimate spatially averaged rainfalls conditional on river discharges and point rainfall measurements from a single location: an application to Western Greece

    Directory of Open Access Journals (Sweden)

    A. Langousis

    2012-11-01

    Full Text Available We focus on the special case of catchments covered by a single raingauge, and develop a theoretical framework to obtain estimates of spatial rainfall averages conditional on rainfall measurements from a single location, and the flow conditions at the catchment outlet. In doing so we use: (a statistical tools to identify and correct inconsistencies between daily rainfall occurrence and amount and the flow conditions at the outlet of the basin, (b concepts from multifractal theory to relate the fraction of wet intervals in point rainfall measurements and that in spatial rainfall averages, while accounting for the shape and size of the catchment, the size, lifetime and advection velocity of rainfall generating features and the location of the raingauge inside the basin, and (c semi-theoretical arguments to assure consistency between rainfall and runoff volumes at an inter-annual level, implicitly accounting for spatial heterogeneities of rainfall caused by orographic influences. In an application study, using point rainfall records from Glafkos river basin in Western Greece, we find the suggested approach to demonstrate significant skill in resolving rainfall-runoff incompatibilities at a daily level, while reproducing the statistics of spatial rainfall averages at both monthly and annual time scales, independently of the location of the raingauge and the magnitude of the observed deviations between point rainfall measurements and spatial rainfall averages. The developed scheme should serve as an important tool for the effective calibration of rainfall-runoff models in basins covered by a single raingauge and, also, improve hydrologic impact assessment at a river basin level under changing climatic conditions.

  12. Vegetation response to rainfall seasonality and interannual variability in tropical dry forests

    Science.gov (United States)

    Feng, X.; Silva Souza, R. M.; Souza, E.; Antonino, A.; Montenegro, S.; Porporato, A. M.

    2015-12-01

    We analyzed the response of tropical dry forests to seasonal and interannual rainfall variability, focusing on the caatinga biome in semi-arid in Northeast Brazil. We selected four sites across a gradient of rainfall amount and seasonality and analyzed daily rainfall and biweekly Normalized Difference Vegetation Index (NDVI) in the period 2000-2014. The seasonal and interannual rainfall statistics were characterized using recently developed metrics describing duration, location, and intensity of wet season and compared them with those of NDVI time series and modelled soil moisture. A model of NDVI was also developed and forced by different rainfall scenarios (combination amount of rainfall and duration of wet season). The results show that the caatinga tends to have a more stable response characterized by longer and less variable growing seasons (of duration 3.1±0.1 months) compared to the rainfall wet seasons (2.0±0.5 months). Even for more extreme rainfall conditions, the ecosystem shows very little sensitivity to duration of wet season in relation to the amount of rainfall, however the duration of wet season is most evident for wetter sites. This ability of the ecosystem in buffering the interannual variability of rainfall is corroborated by the stability of the centroid location of the growing season compared to the wet season for all sites. The maximal biomass production was observed at intermediate levels of seasonality, suggesting a possible interesting trade-off in the effects of intensity (i.e., amount) and duration of the wet season on vegetation growth.

  13. Extreme Rainfall Impacts in Fractured Permeable Catchments

    Science.gov (United States)

    Ireson, A. M.; Butler, A. P.

    2009-12-01

    Serious groundwater flooding events have occurred on Chalk catchments in both the UK and north west Europe in the last decade, causing substantial amounts of disruption and economic damage. These fractured, permeable catchments are characterized by low surface runoff, high baseflow indices and strongly attenuated streamflow hydrographs. They have a general resilience to drought and pluvial/fluvial flooding. The small pore size of the Chalk matrix (~ 1 µm) exerts a high suction, such that dynamic storage is primarily due to the fractures, and amounts to ~ 1% of the total volume. As a result, under sustained rainfall the water table can rise up to exceptional levels leading to surface water emergence from springs and valleys. Floodwater may slowly drain with the topography, or, in localized depressions, it may simply pond until the groundwater levels decline. In winter 2000/1, a sequence of individually unexceptional rainfall events over several months led to large scale flooding in the Pang catchment, Berkshire, UK. By contrast, an extreme rainfall event on 20th July 2007 in the same catchment caused a very rapid response at the water table, but due to the antecedent conditions did not lead to flooding. The objective of this study is to quantify how the water table in a fractured permeable catchment responds to different types of rainfall, and the implications of this for groundwater flooding. We make use of measurements from the Pang catchment, including: rainfall (tipping bucket gauges); actual evaporation (eddy flux correlation); soil water content (profile probes and neutron probes); near surface matric potential (tensiometers and equitensiometers); deep (>10m) matric potential (deep jacking tensiometers); and water table elevation (piezometers). Conventional treatment of recharge in Chalk aquifers considers a fixed bypass component of rainfall, normally 15%, to account for the role of the fractures. However, interpretation of the field data suggest three modes

  14. The asymmetry of rainfall process

    Institute of Scientific and Technical Information of China (English)

    YU RuCong; YUAN WeiHua; LI Jian

    2013-01-01

    Using hourly station rain gauge data in the warm season (May-October) during 1961-2006,the climatological features of the evolution of the rainfall process are analyzed by compositing rainfall events centered on the maximum hourly rainfall amount of each event.The results reveal that the rainfall process is asymmetric,which means rainfall events usually reach the maximum in a short period and then experience a relatively longer retreat to the end of the event.The effects of rainfall intensity,duration and peak time,as well as topography,are also considered.It is found that the asymmetry is more obvious in rainfall events with strong intensity and over areas with complex terrain,such as the eastern margin of the Tibetan Plateau,the Hengduan Mountains,and the Yungui Plateau.The asymmetry in short-duration rainfall is more obvious than that in long-duration rainfall,but the regional differences are weaker.The rainfall events that reach the maximum during 14:00-02:00 LST exhibit the strongest asymmetry and those during 08:00-14:00 LST show the weakest asymmetry.The rainfall intensity at the peak time stands out,which means that the rainfall intensity increases and decreases quickly both before and after the peak.These results can improve understanding of the rainfall process and provide metrics for the evaluation of climate models.Moreover,the strong asymmetry of the rainfall process should be highly noted when taking measures to defending against geological hazards,such as collapses,landslides and debris flows throughout southwestern China.

  15. FREQUENCY STRUCTURE OF MAJOR RAINFALL EVENTS IN THE NORTH-EASTERN PART OF BANGLADESH

    Directory of Open Access Journals (Sweden)

    RAQUIBUL ALAM

    2012-12-01

    Full Text Available The amount of rainfall received over an area is an important factor in assessing availability of water to meet various demands for agriculture, industry, irrigation, generation of hydroelectricity and other human activities. The distribution of rainfall in time and space is, therefore, an important factor for the economic development of a country. Due to rapid urbanization in various parts of the north-eastern region of Bangladesh, there is a growing need to study the rainfall pattern, and also frequency of the heavy rainfall events. This study was checked monthly average rainfall from daily records of last 50 years for this region. In order to check the major events, time history of monthly rainfall data were transformed into frequency domain using the Fast Fourier Transform (FFT. Estimated peak frequency (11.98 month depicts that major rainfall events of a year are occurring earlier than the previous year. The variability of rainfall in time scale was also checked from filtered signals, which is very useful for long-term water resources planning, agricultural development and disaster management for Bangladesh.

  16. Effect of soil warming and rainfall patterns on soil N cycling in northern Europe

    DEFF Research Database (Denmark)

    Patil, Raveendra Hanumantagoud; Lægdsmand, Mette; Olesen, Jørgen Eivind

    2010-01-01

    With climate change northern Europe is expected to experience extreme increase in air temperatures, particularly during the winter months, influencing soil temperatures in these regions. Climate change is also projected to influence the rainfall amount, and its inter- and intra-annual variability...... temperate climates, which is a major source of N pollution. An open-field lysimeter study was carried out during 2008-2009 in Denmark on loamy sand soil (Typic Hapludult) with three factors: number of rainy days, rainfall amount and soil warming. Number of rainy days included the mean monthly rainy days...

  17. Links between circulation and changes in the characteristics of Iberian rainfall

    Science.gov (United States)

    Goodess, C. M.; Jones, P. D.

    2002-11-01

    Investigation of the links between atmospheric circulation patterns and rainfall is important for the understanding of climatic variability and for the development of empirical circulation-based downscaling methods. Here, spatial and temporal variations in circulation-rainfall relationships over the Iberian Peninsula during the period 1958-97 are explored using an automated circulation classification scheme and daily rainfall totals for 18 stations. Links between the circulation classification scheme and the North Atlantic oscillation (NAO) are also considered, as are the direct links between rainfall and the NAO. Trends in rainfall and circulation-type frequency are explored. A general tendency towards decreasing mean seasonal rainfall over the peninsula, with the exception of the southeastern Mediterranean coast, hides larger changes in wet day amount and rainfall probability. There is a tendency towards more, less-intensive rain days across much of Iberia, with a tendency towards more, more-intensive rain days along the southeastern Mediterranean coast, both of which are reflected in changes in rainfall amount quantiles. A preliminary analysis indicates that these changes may have occurred systematically across all circulation types. Comparison of the trends in rainfall and in circulation-type frequency suggests possible links. These links are supported by linear regression analyses using circulation-type frequencies as predictor variables and rainfall totals for winter months as the predictands. The selected predictor variables reflect the main circulation features influencing winter rainfall across the peninsula, i.e. the strong influence of Atlantic westerly and southwesterly airmasses over much of the peninsula, of northerly and northwesterly surface flow over northern/northwestern Spain and northern Portugal and the stronger effect of Mediterranean rather than Atlantic influences in southeastern Spain. The observed rainfall changes cannot, however, be

  18. Using qflux to constrain modeled Congo Basin rainfall in the CMIP5 ensemble

    Science.gov (United States)

    Creese, A.; Washington, R.

    2016-11-01

    Coupled models are the tools by which we diagnose and project future climate, yet in certain regions they are critically underevaluated. The Congo Basin is one such region which has received limited scientific attention, due to the severe scarcity of observational data. There is a large difference in the climatology of rainfall in global coupled climate models over the basin. This study attempts to address this research gap by evaluating modeled rainfall magnitude and distribution amongst global coupled models in the Coupled Model Intercomparison Project 5 (CMIP5) ensemble. Mean monthly rainfall between models varies by up to a factor of 5 in some months, and models disagree on the location of maximum rainfall. The ensemble mean, which is usually considered a "best estimate" of coupled model output, does not agree with any single model, and as such is unlikely to present a possible rainfall state. Moisture flux (qflux) convergence (which is assumed to be better constrained than parameterized rainfall) is found to have a strong relationship with rainfall; strongest correlations occur at 700 hPa in March-May (r = 0.70) and 850 hPa in June-August, September-November, and December-February (r = 0.66, r = 0.71, and r = 0.81). In the absence of observations, this relationship could be used to constrain the wide spectrum of modeled rainfall and give a better understanding of Congo rainfall climatology. Analysis of moisture transport pathways indicates that modeled rainfall is sensitive to the amount of moisture entering the basin. A targeted observation campaign at key Congo Basin boundaries could therefore help to constrain model rainfall.

  19. Spatial and temporal variability of rainfall erosivity factor for Switzerland

    Directory of Open Access Journals (Sweden)

    A. Steel

    2011-09-01

    Full Text Available Rainfall erosivity, considering rainfall amount and intensity, is an important parameter for soil erosion risk assessment under future land use and climate change. Despite its importance, rainfall erosivity is usually implemented in models with a low spatial and temporal resolution. The purpose of this study is to assess the temporal- and spatial distribution of rainfall erosivity (R-factor in Switzerland. Time series of 22 yr for rainfall (10 min resolution and temperature (1 h resolution data were analysed for 71 automatic gauging stations distributed throughout Switzerland. Multiple regression was used to interpolate the erosivity values of single stations and to generate a map for Switzerland. Latitude, longitude, average annual precipitation, biogeographic units (Jura, Midland, etc., aspect and elevation were used as covariates, of which average annual precipitation, elevation and the biographic unit (Western Alps were significant predictors. The mean value of long-term rainfall erosivity is 1323 MJ mm ha−1 h−1 yr−1 with a range of lowest values of 124 MJ mm ha−1 h−1 yr−1 at an elevated station in Grisons to highest values of 5611 MJ mm ha−1 h−1 yr−1 in Ticino. All stations have highest erosivity values from July to August and lowest values in the winter month. Swiss-wide the month May to October show significantly increasing trends of erosivity (p<0.005. Only in February a significantly decreasing trend of rainfall erosivity is found (p<0.01. The increasing trends of erosivity in May, September and October when vegetation cover is susceptible are likely to enhance soil erosion risk for certain agricultural crops and alpine grasslands in Switzerland.

  20. Rainfall statistics changes in Sicily

    Directory of Open Access Journals (Sweden)

    E. Arnone

    2013-02-01

    Full Text Available Changes in rainfall characteristics are one of the most relevant signs of current climate alterations. Many studies have demonstrated an increase in rainfall intensity and a reduction of frequency in several areas of the world, including Mediterranean areas. Rainfall characteristics may be crucial for vegetation patterns formation and evolution in Mediterranean ecosystems, with important implications, for example, in vegetation water stress or coexistence and competition dynamics. At the same time, characteristics of extreme rainfall events are fundamental for the estimation of flood peaks and quantiles which can be used in many hydrological applications, such as design of the most common hydraulic structures, or planning and management of flood prone areas.

    In the past, Sicily has been screened for several signals of possible climate change. Annual, seasonal and monthly rainfall data in the entire Sicilian region have been analyzed, showing a global reduction of total annual rainfall. Moreover, annual maximum rainfall series for different durations have been rarely analyzed in order to detect the presence of trends. Results indicated that for short durations, historical series generally exhibit increasing trends while for longer durations the trends are mainly negative.

    Starting from these premises, the aim of this study is to investigate and quantify changes in rainfall statistics in Sicily, during the second half of the last century. Time series of about 60 stations over the region have been processed and screened by using the non parametric Mann–Kendall test.

    Particularly, extreme events have been analyzed using annual maximum rainfall series at 1, 3, 6, 12 and 24 h duration while daily rainfall properties have been analyzed in term of frequency and intensity, also characterizing seasonal rainfall features. Results of extreme events analysis confirmed an increasing trend for rainfall of short durations

  1. Rainfall statistics changes in Sicily

    Directory of Open Access Journals (Sweden)

    E. Arnone

    2013-07-01

    Full Text Available Changes in rainfall characteristics are one of the most relevant signs of current climate alterations. Many studies have demonstrated an increase in rainfall intensity and a reduction of frequency in several areas of the world, including Mediterranean areas. Rainfall characteristics may be crucial for vegetation patterns formation and evolution in Mediterranean ecosystems, with important implications, for example, in vegetation water stress or coexistence and competition dynamics. At the same time, characteristics of extreme rainfall events are fundamental for the estimation of flood peaks and quantiles that can be used in many hydrological applications, such as design of the most common hydraulic structures, or planning and management of flood-prone areas. In the past, Sicily has been screened for several signals of possible climate change. Annual, seasonal and monthly rainfall data in the entire Sicilian region have been analyzed, showing a global reduction of total annual rainfall. Moreover, annual maximum rainfall series for different durations have been rarely analyzed in order to detect the presence of trends. Results indicated that for short durations, historical series generally exhibit increasing trends, while for longer durations the trends are mainly negative. Starting from these premises, the aim of this study is to investigate and quantify changes in rainfall statistics in Sicily, during the second half of the last century. Time series of about 60 stations over the region have been processed and screened by using the nonparametric Mann–Kendall test. In particular, extreme events have been analyzed using annual maximum rainfall series at 1, 3, 6, 12 and 24 h duration, while daily rainfall properties have been analyzed in terms of frequency and intensity, also characterizing seasonal rainfall features. Results of extreme events analysis confirmed an increasing trend for rainfall of short durations, especially for 1 h rainfall

  2. Evaluation of forecast skill of monthly rainfall over Northeast China using multi-models%多模式对东北地区月降水预测性能对比评估

    Institute of Scientific and Technical Information of China (English)

    李永生; 段春锋; 王莹

    2016-01-01

    基于中国、美国、欧洲和日本的4种气候模式对1983—2010年东北地区降水的回报试验结果,利用2011—2014年东北地区业务应用的结果和国家气象信息中心提供的东北地区172个气象站的观测资料,采用距平相关系数(ACC)、趋势异常综合评分(Ps)和距平符号一致率(Pc)3种定量方法对比评估了4种模式对东北地区月降水的预测性能。结果表明:EC模式和CFSv 2模式与BCC模式和TCC模式相比,EC模式和CFSv 2模式对东北地区月降水的总体预测效果较好,具有一定的预测技巧。从空间上来看,CFSv 2模式各月Pc的分布存在较明显的差异,模式仍有较大的改进空间。CFSv 2模式对东北地区初夏典型旱涝年具有一定的预测能力,对典型涝年的预测效果优于典型旱年。%The prediction skill of four climate models for monthly rainfall over Northeast China was evaluated using three qualitative evaluation methods,i.e.,anomaly correlation coefficient (ACC),trend anomaly inspection evalu-ation (Ps)and anomaly symbol consistency rate (Pc).Many data were used in this study,including 172 meteoro-logical stations over Northeast China supplied by the National Meteorological Information Center,the hindcast ex-perimental results of rainfall over Northeast China from 1983 to 2010 according to four climate models from Chi-na,America,Japan and Europe,and the operational application results over Northeast China from 201 1 to 2014. The results indicate that the monthly rainfall prediction skills of EC (European Center for Medium-Range Weather Forecasts)and CFSv 2 (Coupled Forecast System Model Version 2)models are better than those of BCC (Bei-jing Climate Center)and TCC (Tokyo Climate Center)models.Looking at the spatial distribution,there is a sig-nificant difference in the distribution of each monthly Pc for CFSv 2 model,indicating that this model has a big space for its improvement.The CFSv 2 model has

  3. Spatial and temporal variability of rainfall erosivity factor for Switzerland

    Directory of Open Access Journals (Sweden)

    K. Meusburger

    2012-01-01

    Full Text Available Rainfall erosivity, considering rainfall amount and intensity, is an important parameter for soil erosion risk assessment under future land use and climate change. Despite its importance, rainfall erosivity is usually implemented in models with a low spatial and temporal resolution. The purpose of this study is to assess the temporal- and spatial distribution of rainfall erosivity in form of the (Revised Universal Soil Loss Equation R-factor for Switzerland. Time series of 22 yr for rainfall (10 min resolution and temperature (1 h resolution data were analysed for 71 automatic gauging stations distributed throughout Switzerland. Regression-kriging was used to interpolate the rainfall erosivity values of single stations and to generate a map for Switzerland. Latitude, longitude, average annual precipitation, biogeographic units (Jura, Midland, etc., aspect and elevation were used as covariates, of which average annual precipitation, elevation and the biographic unit (Western Central Alps were significant (p<0.01 predictors. The mean value of long-term rainfall erosivity is 1330 MJ mm ha−1 h−1 yr−1 with a range of lowest values of 124 MJ mm ha−1 h−1 yr−1 at an elevated station in Grisons to highest values of 5611 MJ mm ha−1 h−1 yr−1 in Ticino. All stations have highest erosivity values from July to August and lowest values in the winter months. Swiss-wide the month May to October show significantly increasing trends of rainfall erosivity for the observed period (p<0.005. Only in February a significantly decreasing trend of rainfall erosivity is found (p<0.01. The increasing trends of rainfall erosivity in May, September and October when vegetation cover is scarce are likely to enhance soil erosion risk for certain agricultural crops and alpine grasslands in Switzerland.

  4. Normalised monthly shortage curves: a contribution for a better understanding of monthly rain deficit in Western Europe

    Science.gov (United States)

    Martínez, M. D.; Lana, X.; Burgueño, A.; Serra, C.

    2012-05-01

    A new approach to the statistics of rainfall shortage at monthly scale in Western Europe is obtained from precipitation records of 115 gauges over the twentieth century. In this paper, a month is considered to have rainfall deficit when its rain amount is below the 50th percentile of the respective calendar month. The monthly shortage, MS, for every month with deficit is then computed as the absolute value of the difference between its monthly amount and the corresponding truncation level. The cumulative distributions of monthly shortage, CMS, and number of shortage months, CNM, constitute a new description of the monthly rainfall deficit. Both CMS and CNM distributions fit well to a Weibull model. Using the analogy to the normalised daily rainfall curves formulation, NRC, the relationship between CMS and CNM, named as normalised shortage curve, NSC, is modelled by the same function applied to NRCs. Similarly to NRCs, the behaviour of the NSCs strongly depends on the coefficient of variation of the monthly shortage, CVMS. Four coordinates characterising every NSC are then introduced: the CMS percentile associated with the median of CNM; the CNM percentile related to the median of CMS; and the percentiles of CMS and CNM for the average monthly shortage. In this way, the degree of asymmetric distribution of the monthly deficit is quantified. With the aim of performing a clustering process based on these four coordinates, a principal component analysis, is previously applied to remove redundancies, being obtained two uncorrelated principal components, PCs, characterising every NSC. An average linkage algorithm is then applied to these two PCs, leading to obtain spatially coherent groups of gauges with very similar NSC patterns. This clustering process permits to discard latitude and vicinity to the Atlantic Ocean or the Mediterranean Sea as main factors conditioning the monthly shortage regime.

  5. Heterogeneity of Dutch rainfall

    NARCIS (Netherlands)

    Witter, J.V.

    1984-01-01

    Rainfall data for the Netherlands have been used in this study to investigate aspects of heterogeneity of rainfall, in particular local differences in rainfall levels, time trends in rainfall, and local differences in rainfall trend. The possible effect of urbanization and industrialization on the

  6. A multi-scale analysis of Namibian rainfall over the recent decade – comparing TMPA satellite estimates and ground observations

    Directory of Open Access Journals (Sweden)

    Xuefei Lu

    2016-12-01

    New hydrological insights for the region: The agreement between ground and satellite rainfall data was generally good at annual/monthly scales but large variations were observed at the daily scale. Results showed a spatial variability of rainfall trends across the rainfall gradient. We observed significant changes in frequency along with insignificant changes in intensity and no changes in total amount for the driest location, but no changes in any of the rainfall parameters were observed for the three wetter locations. The results also showed increased rainfall variability for the driest location. This study provided a useful approach of using TMPA data associated with trend analysis to extend the data record for ecohydrological studies for similar data scarce conditions. The results of this study will also help constrain IPCC predictions in this region.

  7. Enhanced Orographic Tropical Rainfall: An Study of the Colombia's rainfall

    Science.gov (United States)

    Peñaranda, V. M.; Hoyos Ortiz, C. D.; Mesa, O. J.

    2015-12-01

    Convection in tropical regions may be enhanced by orographic barriers. The orographic enhancement is an intensification of rain rates caused by the forced lifting of air over a mountainous structure. Orographic heavy rainfall events, occasionally, comes along by flooding, debris flow and substantial amount of looses, either economics or human lives. Most of the heavy convective rainfall events, occurred in Colombia, have left a lot of victims and material damages by flash flooding. An urgent action is required by either scientific communities or society, helping to find preventive solutions against these kind of events. Various scientific literature reports address the feedback process between the convection and the local orographic structures. The orographic enhancement could arise by several physical mechanism: precipitation transport on leeward side, convection triggered by the forcing of air over topography, the seeder-feeder mechanism, among others. The identification of the physical mechanisms for orographic enhancement of rainfall has not been studied over Colombia. As far as we know, orographic convective tropical rainfall is just the main factor for the altitudinal belt of maximum precipitation, but the lack of detailed hydro-meteorological measurements have precluded a complete understanding of the tropical rainfall in Colombia and its complex terrain. The emergence of the multifractal theory for rainfall has opened a field of research which builds a framework for parsimonious modeling of physical process. Studies about the scaling behavior of orographic rainfall have found some modulating functions between the rainfall intensity probability distribution and the terrain elevation. The overall objective is to advance in the understanding of the orographic influence over the Colombian tropical rainfall based on observations and scaling-analysis techniques. We use rainfall maps, weather radars scans and ground-based rainfall data. The research strategy is

  8. Interrelationship of rainfall, temperature and reference evapotranspiration trends and their net response to the climate change in Central India

    Science.gov (United States)

    Kundu, Sananda; Khare, Deepak; Mondal, Arun

    2016-09-01

    The monthly rainfall data from 1901 to 2011 and maximum and minimum temperature data from 1901 to 2005 are used along with the reference evapotranspiration (ET0) to analyze the climate trend of 45 stations of Madhya Pradesh. ET0 is calculated by the Hargreaves method from 1901 to 2005 and the computed data is then used for trend analysis. The temporal variation and the spatial distribution of trend are studied for seasonal and annual series with the Mann-Kendall (MK) test and Sen's estimator of slope. The percentage of change is used to find the rate of change in 111 years (rainfall) and 105 years (temperatures and ET0). Interrelationships among these variables are analyzed to see the dependency of one variable on the other. The results indicate a decreasing rainfall and increasing temperatures and ET0 trend. A similar pattern is noticeable in all seasons except for monsoon season in temperature and ET0 trend analysis. The highest increase of temperature is noticed during post-monsoon and winter. Rainfall shows a notable decrease in the monsoon season. The entire state of Madhya Pradesh is considered as a single unit, and the calculation of overall net change in the amount of the rainfall, temperatures (maximum and minimum) and ET0 is done to estimate the total loss or gain in monthly, seasonal and annual series. The results show net loss or deficit in the amount of rainfall and the net gain or excess in the temperature and ET0 amount.

  9. Modeling and forecasting rainfall patterns of southwest monsoons in North-East India as a SARIMA process

    Science.gov (United States)

    Narasimha Murthy, K. V.; Saravana, R.; Vijaya Kumar, K.

    2017-02-01

    Weather forecasting is an important issue in the field of meteorology all over the world. The pattern and amount of rainfall are the essential factors that affect agricultural systems. India experiences the precious Southwest monsoon season for four months from June to September. The present paper describes an empirical study for modeling and forecasting the time series of Southwest monsoon rainfall patterns in the North-East India. The Box-Jenkins Seasonal Autoregressive Integrated Moving Average (SARIMA) methodology has been adopted for model identification, diagnostic checking and forecasting for this region. The study has shown that the SARIMA (0, 1, 1) (1, 0, 1)4 model is appropriate for analyzing and forecasting the future rainfall patterns. The Analysis of Means (ANOM) is a useful alternative to the analysis of variance (ANOVA) for comparing the group of treatments to study the variations and critical comparisons of rainfall patterns in different months of the season.

  10. Rainfall erosivity in New Zealand

    Science.gov (United States)

    Klik, Andreas; Haas, Kathrin; Dvorackova, Anna; Fuller, Ian

    2014-05-01

    the mean annual rainfall amounts to 2027 mm and therefore is higher than on the North Island. A high east-to-west gradient can be seen with the lowest rainfall along the east coast and in Inland and the highest values in the Souther Alps. The temporal variation throughout the year is very low. In each season between 24 (winter) and 26% (summer) of precipitation is observed. Like the precipitation P the range of rainfall erosivity R varies greatly and is higher on the South Island than on the North Island. The results show that precipitation between 720 (Napier) and 2730 mm.a-1 (Mt. Ruapehu) delivered R-factors between 477 and 3592 MJ.mm.ha-1.h-1. For 14 stations a good regression between rainfall and R was obtained. On the South Island corresponding mean annual rainfall between of 429 and 4300 mm produces erosivities between 252 and 10850 MJ.mm.ha-1.h-1. Again lowest R-factors occur in Inland South Island around Alexandra which is also the driest region of New Zealand. Highest values are found in the Southern Alps and the West Coast between Arthur's Pass and Fjordland. Based on the erosivity calculations the nine climatic regions can be aggregated into four erosivity regions.

  11. Diagnostic statistics of daily rainfall variability in an evolving climate

    Directory of Open Access Journals (Sweden)

    D. Panagoulia

    2006-01-01

    Full Text Available To investigate the character of daily rainfall variability under present and future climate described via global warming a suite of diagnostic statistics was used. The rainfall was modeled as a stochastic process coupled with atmospheric circulation. In this study we used an automated objective classification of daily patterns based on optimized fuzzy rules. This kind of classification method provided circulation patterns suitable for downscaling of General Circulation Model (GCM-generated precipitation. The precipitation diagnostics included first and second order moments, wet and dry-day renewal process probabilities and spell lengths as well as low-frequency variability via the standard deviation of monthly totals. These descriptors were applied to nine elevation zones and entire area of the Mesochora mountainous catchment in Central Greece for observed, 1×CO2 and 2×CO2 downscaled precipitation. The statistics' comparison revealed significant differences in the most of the daily diagnostics (e.g. mean wet-day amount, 95th percentile of wet-day amount, dry to wet probability, spell statistics (e.g. mean wet/dry spell length, and low-frequency diagnostic (standard deviation of monthly precipitation total between warm (2×CO2 and observed scenario in a progressive rate from lower to upper zone. The differences were very greater for the catchment area. In the light of these results, an increase in rainfall occurrence with diminished rainfall amount and a sequence of less consecutive dry days could describe the behaviour of a possible future climate on the examined catchment.

  12. RAINFALL EROSIVITY IN SOUTHEASTERN NIGERIA *Ezemonye ...

    African Journals Online (AJOL)

    Osondu

    2011-10-13

    Oct 13, 2011 ... annual total amount, and frequency of fall, kinetic energy and ... annual rainfall increases from the northern frontier of the region ... Nigeria Meteorological Agency, Lagos for the ..... Estimation for Australia's Tropics. Aust. J. Soil.

  13. Analysis of rainfall infiltration law in unsaturated soil slope.

    Science.gov (United States)

    Zhang, Gui-rong; Qian, Ya-jun; Wang, Zhang-chun; Zhao, Bo

    2014-01-01

    In the study of unsaturated soil slope stability under rainfall infiltration, it is worth continuing to explore how much rainfall infiltrates into the slope in a rain process, and the amount of rainfall infiltrating into slope is the important factor influencing the stability. Therefore, rainfall infiltration capacity is an important issue of unsaturated seepage analysis for slope. On the basis of previous studies, rainfall infiltration law of unsaturated soil slope is analyzed. Considering the characteristics of slope and rainfall, the key factors affecting rainfall infiltration of slope, including hydraulic properties, water storage capacity (θs - θr), soil types, rainfall intensities, and antecedent and subsequent infiltration rates on unsaturated soil slope, are discussed by using theory analysis and numerical simulation technology. Based on critical factors changing, this paper presents three calculation models of rainfall infiltrability for unsaturated slope, including (1) infiltration model considering rainfall intensity; (2) effective rainfall model considering antecedent rainfall; (3) infiltration model considering comprehensive factors. Based on the technology of system response, the relationship of rainfall and infiltration is described, and the prototype of regression model of rainfall infiltration is given, in order to determine the amount of rain penetration during a rain process.

  14. Synoptic Analysis of Heavy Rainfall and Flood Observed in Izmir on 20 May 2015 Using Radar and Satellite Images

    Science.gov (United States)

    Avsar, Ercument

    2016-07-01

    In this study, a meteorological analysis is conducted on the sudden and heavy rainfall that occurred in Izmir on May 20, 2015. The barotropic model that is observed in upper carts is shown in detail. We can access the data of and analyze the type, severity and amount of many meteorological parameters using the meteorological radars that form a remote sensing system. The one field that uses the radars most intensively is rainfall. Images from the satellite and radar systems are used in the meteorological analysis of the heavy rainfall that occurred in Izmir on 20 May 2015, and the development of the system that led to this rainfall is shown. In this study, data received from Bornova Automatic Meteorological Observation Station (OMGI), which is under the management of Meteorology General Directorate (MGM), Izmir 2. Regional Directorate; satellite images; Radar PPI (Plan Position Indicator) and Radar MAX (Maximum Display) images are evaluated. In addition, synoptic situation, outputs of numerical estimation models, indices calculated from Skew T Log-P diagram are shown. All these results are mapped and analyzed. At the end of these analyses, it is found that this sudden rainfall had developed according to the frontal system motion. A barotropic model occurred on the day of the rainfall over the Aegean Region. As a result of the rainfall that happened in Izmir at 12.00 UTC (Universal Coordinated Time), the May month rainfall record for the last 64 years is achieved with a rainfall amount of 67.7 mm per meter square. Keywords: Izmir, barotropic model, heavy rainfall, radar, synoptic analysis

  15. RAINFALL AGGRESSIVENESS EVALUATION IN REGHIN HILLS USING FOURNIER INDEX

    Directory of Open Access Journals (Sweden)

    J. SZILAGYI

    2016-03-01

    Full Text Available Aggressiveness erosive force of rainfall is the express of kinetic energy and potential energy of rain water runoff on slopes. In the absence of a database for the analysis of parameters that define the torrencial rainfall, the rainfall erosivity factor was calculated by Fournier Index, Modified Fournier Index based on the monthly and annual precipitation.

  16. EVALUATION OF RAINFALL-RUNOFF EROSIVITY FACTOR FOR CAMERON HIGHLAND, PAHANG, MALAYSIA

    Directory of Open Access Journals (Sweden)

    Abdulkadir Taofeeq Sholagberu

    2016-07-01

    Full Text Available Rainfall-runoff is the active agent of soil erosion which often resulted in land degradation and water quality deterioration. Its aggressiveness to induce erosion is usually termed as rainfall erosivity index or factor (R. R-factor is one of the factors to be parameterized in the evaluation of soil loss using the Universal Soil Loss Equation and its reversed versions (USLE/RUSLE. The computation of accurate R-factor for a particular watershed requires high temporal resolution rainfall (pluviograph data with less than 30-minutes intensities for at least 20 yrs, which is available only in a few regions of the world. As a result, various simplified models have been proposed by researchers to evaluate R-factor using readily available daily, monthly or annual precipitation data. This study is thus aimed at estimating R-factor and to establish an approximate relationship between R-factor and rainfall for subsequent usage in the estimation of soil loss in Cameron highlands watershed. The results of the analysis showed that the least and peak (critical R-factors occurred in the months of January and April with 660.82 and 2399.18 MJ mm ha-1 h-1year-1 respectively. Also, it was observed that erosivity power starts to increase from the month of January through April before started falling in the month of July. The monthly and annual peaks (critical periods may be attributed to increased rainfall amount due to climate change which in turn resulted to increased aggressiveness of rains to cause erosion in the study area. The correlation coefficient of 0.985 showed that there was a strong relationship rainfall and R-factor.

  17. Potential of deterministic and geostatistical rainfall interpolation under high rainfall variability and dry spells: case of Kenya's Central Highlands

    Science.gov (United States)

    Kisaka, M. Oscar; Mucheru-Muna, M.; Ngetich, F. K.; Mugwe, J.; Mugendi, D.; Mairura, F.; Shisanya, C.; Makokha, G. L.

    2016-04-01

    digital elevation model in ArcGIS environment. Validation of the selected interpolation methods were based on goodness of fit between gauged (observed) and generated rainfall derived from residual errors statistics, coefficient of determination (R 2), mean absolute errors (MAE) and root mean square error (RMSE) statistics. Analyses showed 90 % chance of below cropping-threshold rainfall (500 mm) exceeding 258.1 mm during short rains in Embu for 1 year return period. Rainfall variability was found to be high in seasonal amounts (e.g. coefficient of variation (CV) = 0.56, 0.47, 0.59) and in number of rainy days (e.g. CV = 0.88, 0.53) in Machang'a and Kiritiri, respectively. Monthly rainfall variability was found to be equally high during April and November (e.g. CV = 0.48, 0.49 and 0.76) with high probabilities (0.67) of droughts exceeding 15 days in Machang'a. Dry spell probabilities within growing months were high, e.g. 81 and 60 % in Machang'a and Embu, respectively. Kriging interpolation method emerged as the most appropriate geostatistical interpolation technique suitable for spatial rainfall maps generation for the study region.

  18. Characteristics of Rainfall-Discharge and Water Quality at Limboto Lake, Gorontalo, Indonesia

    Directory of Open Access Journals (Sweden)

    Luki Subehi

    2016-08-01

    Full Text Available Problems of high turbidity, sedimentation, water pollution and siltation occur at Limboto Lake, Gorontalo, Indonesia. The objective of this study was to analyze the rainfall-discharge relationship and its implications for water quality conditions. Secchi disk (water transparency, chlorophyll-a (chl-a, and total organic matter (TOM were measured in May 2012, September 2012 and March 2013 at three sites of the lake (L-1, L-2 and L-3 to observe the impacts on the surrounding catchment. Based on representative stations for rainfall data from 2004 to 2013, monthly averages of rainfall in March-May (166.7 mm and September (76.4 mm were used to represent the wet and dry period, respectively. Moreover, sediment traps at these three sites were installed in September 2012. Based on the analysis it is suggested that rainfall magnitude and land use change at the Alopohu River catchment influenced the amount of materials flowing into the lake, degrading the water quality. Specifically, the higher average rainfall in May (184.5 mm gave a higher average total sediment load (4.41 g/L/day. In addition, water transparency decreased with increasing chl-a. This indicates that the concentrations of sediment and nutrients, reflected by the high amount of chl-a, influenced the water quality conditions.

  19. Development of a Compound Distribution Markov Chain Model for Stochastic Generation of Rainfall with Long Term Persistence

    Science.gov (United States)

    Kamal Chowdhury, AFM; Lockart, Natalie; Willgoose, Garry; Kuczera, George

    2015-04-01

    One of the overriding issues in the rainfall simulation is the underestimation of observed rainfall variability in longer timescales (e.g. monthly, annual and multi-year), which usually results into under-estimation of reservoir reliability in urban water planning. This study has developed a Compound Distribution Markov Chain (CDMC) model for stochastic generation of daily rainfall. We used two parameters of Markov Chain process (transition probabilities of wet-to-wet and dry-to-dry days) for simulating rainfall occurrence and two parameters of gamma distribution (calculated from mean and standard deviation of wet-day rainfall) for simulating wet-day rainfall amounts. While two models with deterministic parameters underestimated long term variability, our investigation found that the long term variability of rainfall in the model is predominantly governed by the long term variability of gamma parameters, rather than the variability of Markov Chain parameters. Therefore, in the third approach, we developed the CDMC model with deterministic parameters of Markov Chain process, but stochastic parameters of gamma distribution by sampling the mean and standard deviation of wet-day rainfall from their log-normal and bivariate-normal distribution. We have found that the CDMC is able to replicate both short term and long term rainfall variability, when we calibrated the model at two sites in east coast of Australia using three types of daily rainfall data - (1) dynamically downscaled, 10 km resolution gridded data produced by NSW/ACT Regional Climate Modelling project, (2) 5 km resolution gridded data by Australian Water Availability Project and (3) point scale raingauge stations data by Bureau of Meteorology, Australia. We also examined the spatial variability of parameters and their link with local orography at our field site. The suitability of the model in runoff generation and urban reservoir-water simulation will be discussed.

  20. Lixiviação de potássio da palha de espécies de cobertura de solo de acordo com a quantidade de chuva aplicada Potassium leaching from green cover crop residues as affected by rainfall amount

    Directory of Open Access Journals (Sweden)

    C. A. Rosolem

    2003-04-01

    vulgare, black oat (Avena strigosa, triticale (Triticum secale, Indian hemp (Crotalaria juncea and brachiaria (Brachiaria decumbens were grown under greenhouse conditions in pots with soil, in Botucatu, State of São Paulo, Brazil. Forty-five days after emergence, the plants were cut, dried and placed in PVC rings, simulating an amount of 8 t ha-1 of straw. Rainfalls of 4.4, 8.7, 17.4, 34.9, and 69.8 mm were applied. The straws retained up to 3.0 mm of water, irrespective of the plant species, and rains of 5 mm did not cause K leaching. Maximum K leaching per rain unit was observed for rainfalls around 20 mm, and decreased under heavier rainfalls. The amount of K released from the straw right after preparation is species-dependent, but is always below 24.0 kg ha-1 under rains up to 70 mm, and positively related with tissue nutrient contents. Triticale and black oats are more efficient at recycling K.

  1. A Study of Rainfall Variations in the Philippines: 1950-1996

    Directory of Open Access Journals (Sweden)

    Bonifacio Pajuelas

    2000-06-01

    Full Text Available The long-period rainfall variations in the Philippines are studied using unfiltered and filtered Rainfall Anomaly Index (RAI. To have RAI’s that are representative for each group, zones of quasi-homogeneous climate were constructed based on highly correlated stations (r > 0.75, narrow standard deviation, and period of maximum rainfall using the 1950-1996 monthly rainfall total. Variance analyses of the RAI’s suggest that unfiltered samples do not significantly differ from the normal distribution except for the western part (climate type 1 that have significant positive skewness and peakedness. The RAI’s contain a significant amount of non-random elements and a significant negative change in mean is reflected over the central Visayas and Mindanao (climate type 3. Filtered RAI’s that are not significantly different from the normal distribution (at least for c2 test indicated significant trend over areas with high-variable rainfall (i.e., climate types 1, 2, 4 & 5.In general, long-period rainfall may have changed over the period of study. The 10-year filtered RAI’s have the possibility of falling rate over climate types 1, 2 & 5, but increasing rate over climate type 4. These trends are indicated towards the rainfall-sensitive months (i.e., February through May during El Niño or La Niña events. Falling rate is also significant from October through January over climate type 4. Longer periods (30-year filtered RAI’s have significant negative trend for climate types 2 &4, but positive trend for climate type 5. These trends also occurred during February through May.

  2. Forecasting Rainfall Time Series with stochastic output approximated by neural networks Bayesian approach

    Directory of Open Access Journals (Sweden)

    Cristian Rodriguez Rivero

    2014-07-01

    Full Text Available The annual estimate of the availability of the amount of water for the agricultural sector has become a lifetime in places where rainfall is scarce, as is the case of northwestern Argentina. This work proposes to model and simulate monthly rainfall time series from one geographical location of Catamarca, Valle El Viejo Portezuelo. In this sense, the time series prediction is mathematical and computational modelling series provided by monthly cumulative rainfall, which has stochastic output approximated by neural networks Bayesian approach. We propose to use an algorithm based on artificial neural networks (ANNs using the Bayesian inference. The result of the prediction consists of 20% of the provided data consisting of 2000 to 2010. A new analysis for modelling, simulation and computational prediction of cumulative rainfall from one geographical location is well presented. They are used as data information, only the historical time series of daily flows measured in mmH2O. Preliminary results of the annual forecast in mmH2O with a prediction horizon of one year and a half are presented, 18 months, respectively. The methodology employs artificial neural network based tools, statistical analysis and computer to complete the missing information and knowledge of the qualitative and quantitative behavior. They also show some preliminary results with different prediction horizons of the proposed filter and its comparison with the performance Gaussian process filter used in the literature.

  3. Humidity Profiles' Effect On The Relationship Between Ice Scattering And Rainfall In Microwave Rainfall Retrievals

    Science.gov (United States)

    Petkovic, V.; Kummerow, C. D.

    2013-12-01

    Currently, satellite microwave rainfall retrievals base their algorithm on an observed global average of the relationship between high frequency brightness temperature (Tb) depression and rainfall rate. This makes them very sensitive to differences in the ratio of ice to liquid in the cloud, resulting in regional biases of rainfall estimates. To address this problem we investigate how the environmental conditions that precede raining systems influence the ice to rainfall relationship. The vertical profile of humidity was found to be a key variable in predicting this ratio. We found that dry over moist air conditions are favorable for developing intense, well organized systems such as MCSs in West Africa and the Sahel, characterized by strong Tb depressions and amounts of ice aloft significantly above the globally observed average value. As a consequence, microwave retrieval algorithms misinterpret these systems assigning them unrealistically high rainfall rates. The opposite is true in the Amazon region, where observed raining systems exhibit very little ice while producing high rainfall rates. These regional differences correspond well with a map of radar to radiometer biases of rainfall. Deeper understanding of the influence of environmental conditions on this ice to rain ratio provides a foundation for mapping a global ice-scattering to rainfall rate relationship that will improve satellite microwave rainfall retrievals and our understanding of cloud microphysics globally.

  4. Exploring the relationship between malaria, rainfall intermittency, and spatial variation in rainfall seasonality

    Science.gov (United States)

    Merkord, C. L.; Wimberly, M. C.; Henebry, G. M.; Senay, G. B.

    2014-12-01

    Malaria is a major public health problem throughout tropical regions of the world. Successful prevention and treatment of malaria requires an understanding of the environmental factors that affect the life cycle of both the malaria pathogens, protozoan parasites, and its vectors, anopheline mosquitos. Because the egg, larval, and pupal stages of mosquito development occur in aquatic habitats, information about the spatial and temporal distribution of rainfall is critical for modeling malaria risk. Potential sources of hydrological data include satellite-derived rainfall estimates (TRMM and GPM), evapotranspiration derived from a simplified surface energy balance, and estimates of soil moisture and fractional water cover from passive microwave imagery. Previous studies have found links between malaria cases and total monthly or weekly rainfall in areas where both are highly seasonal. However it is far from clear that monthly or weekly summaries are the best metrics to use to explain malaria outbreaks. It is possible that particular temporal or spatial patterns of rainfall result in better mosquito habitat and thus higher malaria risk. We used malaria case data from the Amhara region of Ethiopia and satellite-derived rainfall estimates to explore the relationship between malaria outbreaks and rainfall with the goal of identifying the most useful rainfall metrics for modeling malaria occurrence. First, we explored spatial variation in the seasonal patterns of both rainfall and malaria cases in Amhara. Second, we assessed the relative importance of different metrics of rainfall intermittency, including alternation of wet and dry spells, the strength of intensity fluctuations, and spatial variability in these measures, in determining the length and severity of malaria outbreaks. We also explored the sensitivity of our results to the choice of method for describing rainfall intermittency and the spatial and temporal scale at which metrics were calculated. Results

  5. The stable isotope amount effect: New insights from NEXRAD echo tops, Luquillo Mountains, Puerto Rico

    Science.gov (United States)

    Schol, M.A.; Shanley, J.B.; Zegarra, J.P.; Coplen, T.B.

    2009-01-01

    The stable isotope amount effect has often been invoked to explain patterns of isotopic composition of rainfall in the tropics. This paper describes a new approach, correlating the isotopic composition of precipitation with cloud height and atmospheric temperature using NEXRAD radar echo tops, which are a measure of the maximum altitude of rainfall within the clouds. The seasonal differences in echo top altitudes and their corresponding temperatures are correlated with the isotopic composition of rainfall. These results offer another factor to consider in interpretation of the seasonal variation in isotopic composition of tropical rainfall, which has previously been linked to amount or rainout effects and not to temperature effects. Rain and cloud water isotope collectors in the Luquillo Mountains in northeastern Puerto Rico were sampled monthly for three years and precipitation was analyzed for ??18O and ??2H. Precipitation enriched in , 18O and 2H occurred during the winter dry season (approximately December-May) and was associated with a weather pattern of trade wind showers and frontal systems. During the summer rainy season (approximately June-November), precipitation was depleted in 18O and 2H and originated in low pressure systems and convection associated with waves embedded in the prevailing easterly airflow. Rain substantially depleted in 18O and 2H compared to the aforementioned weather patterns occurred during large low pressure systems. Weather analysis showed that 29% of rain input to the Luquillo Mountains was trade wind orographic rainfall, and 30% of rainfall could be attributed to easterly waves and low pressure systems. Isotopic signatures associated with these major climate patterns can be used to determine their influence on streamflow and groundwater recharge and to monitor possible effects of climate change on regional water resources.

  6. Runoff and leaching of metolachlor from Mississippi River alluvial soil during seasons of average and below-average rainfall.

    Science.gov (United States)

    Southwick, Lloyd M; Appelboom, Timothy W; Fouss, James L

    2009-02-25

    The movement of the herbicide metolachlor [2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)acetamide] via runoff and leaching from 0.21 ha plots planted to corn on Mississippi River alluvial soil (Commerce silt loam) was measured for a 6-year period, 1995-2000. The first three years received normal rainfall (30 year average); the second three years experienced reduced rainfall. The 4-month periods prior to application plus the following 4 months after application were characterized by 1039 +/- 148 mm of rainfall for 1995-1997 and by 674 +/- 108 mm for 1998-2000. During the normal rainfall years 216 +/- 150 mm of runoff occurred during the study seasons (4 months following herbicide application), accompanied by 76.9 +/- 38.9 mm of leachate. For the low-rainfall years these amounts were 16.2 +/- 18.2 mm of runoff (92% less than the normal years) and 45.1 +/- 25.5 mm of leachate (41% less than the normal seasons). Runoff of metolachlor during the normal-rainfall seasons was 4.5-6.1% of application, whereas leaching was 0.10-0.18%. For the below-normal periods, these losses were 0.07-0.37% of application in runoff and 0.22-0.27% in leachate. When averages over the three normal and the three less-than-normal seasons were taken, a 35% reduction in rainfall was characterized by a 97% reduction in runoff loss and a 71% increase in leachate loss of metolachlor on a percent of application basis. The data indicate an increase in preferential flow in the leaching movement of metolachlor from the surface soil layer during the reduced rainfall periods. Even with increased preferential flow through the soil during the below-average rainfall seasons, leachate loss (percent of application) of the herbicide remained below 0.3%. Compared to the average rainfall seasons of 1995-1997, the below-normal seasons of 1998-2000 were characterized by a 79% reduction in total runoff and leachate flow and by a 93% reduction in corresponding metolachlor movement via these routes

  7. Rainfall simulation in education

    Science.gov (United States)

    Peters, Piet; Baartman, Jantiene; Gooren, Harm; Keesstra, Saskia

    2016-04-01

    Rainfall simulation has become an important method for the assessment of soil erosion and soil hydrological processes. For students, rainfall simulation offers an year-round, attractive and active way of experiencing water erosion, while not being dependent on (outdoors) weather conditions. Moreover, using rainfall simulation devices, they can play around with different conditions, including rainfall duration, intensity, soil type, soil cover, soil and water conservation measures, etc. and evaluate their effect on erosion and sediment transport. Rainfall simulators differ in design and scale. At Wageningen University, both BSc and MSc student of the curriculum 'International Land and Water Management' work with different types of rainfall simulation devices in three courses: - A mini rainfall simulator (0.0625m2) is used in the BSc level course 'Introduction to Land Degradation and Remediation'. Groups of students take the mini rainfall simulator with them to a nearby field location and test it for different soil types, varying from clay to more sandy, slope angles and vegetation or litter cover. The groups decide among themselves which factors they want to test and they compare their results and discuss advantage and disadvantage of the mini-rainfall simulator. - A medium sized rainfall simulator (0.238 m2) is used in the MSc level course 'Sustainable Land and Water Management', which is a field practical in Eastern Spain. In this course, a group of students has to develop their own research project and design their field measurement campaign using the transportable rainfall simulator. - Wageningen University has its own large rainfall simulation laboratory, in which a 15 m2 rainfall simulation facility is available for research. In the BSc level course 'Land and Water Engineering' Student groups will build slopes in the rainfall simulator in specially prepared containers. Aim is to experience the behaviour of different soil types or slope angles when (heavy) rain

  8. Rainfall Simulation: methods, research questions and challenges

    Science.gov (United States)

    Ries, J. B.; Iserloh, T.

    2012-04-01

    In erosion research, rainfall simulations are used for the improvement of process knowledge as well as in the field for the assessment of overland flow generation, infiltration, and erosion rates. In all these fields of research, rainfall experiments have become an indispensable part of the research methods. In this context, small portable rainfall simulators with small test-plot sizes of one square-meter or even less, and devices of low weight and water consumption are in demand. Accordingly, devices with manageable technical effort like nozzle-type simulators seem to prevail against larger simulators. The reasons are obvious: lower costs and less time consumption needed for mounting enable a higher repetition rate. Regarding the high number of research questions, of different fields of application, and not least also due to the great technical creativity of our research staff, a large number of different experimental setups is available. Each of the devices produces a different rainfall, leading to different kinetic energy amounts influencing the soil surface and accordingly, producing different erosion results. Hence, important questions contain the definition, the comparability, the measurement and the simulation of natural rainfall and the problem of comparability in general. Another important discussion topic will be the finding of an agreement on an appropriate calibration method for the simulated rainfalls, in order to enable a comparison of the results of different rainfall simulator set-ups. In most of the publications, only the following "nice" sentence can be read: "Our rainfall simulator generates a rainfall spectrum that is similar to natural rainfall!". The most substantial and critical properties of a simulated rainfall are the drop-size distribution, the fall velocities of the drops, and the spatial distribution of the rainfall on the plot-area. In a comparison of the most important methods, the Laser Distrometer turned out to be the most up

  9. Temporal correlation between malaria and rainfall in Sri Lanka

    Directory of Open Access Journals (Sweden)

    Galappaththy Gawrie NL

    2008-05-01

    Full Text Available Abstract Background Rainfall data have potential use for malaria prediction. However, the relationship between rainfall and the number of malaria cases is indirect and complex. Methods The statistical relationships between monthly malaria case count data series and monthly mean rainfall series (extracted from interpolated station data over the period 1972 – 2005 in districts in Sri Lanka was explored in four analyses: cross-correlation; cross-correlation with pre-whitening; inter-annual; and seasonal inter-annual regression. Results For most districts, strong positive correlations were found for malaria time series lagging zero to three months behind rainfall, and negative correlations were found for malaria time series lagging four to nine months behind rainfall. However, analysis with pre-whitening showed that most of these correlations were spurious. Only for a few districts, weak positive (at lags zero and one or weak negative (at lags two to six correlations were found in pre-whitened series. Inter-annual analysis showed strong negative correlations between malaria and rainfall for a group of districts in the centre-west of the country. Seasonal inter-annual analysis showed that the effect of rainfall on malaria varied according to the season and geography. Conclusion Seasonally varying effects of rainfall on malaria case counts may explain weak overall cross-correlations found in pre-whitened series, and should be taken into account in malaria predictive models making use of rainfall as a covariate.

  10. Long-term effects on haemostatic variables of three ad libitum diets differing in type and amount of fat and carbohydrate: a 6-month randomised study in obese individuals

    DEFF Research Database (Denmark)

    Bladbjerg, Else-Marie; Larsen, Thomas M; Due, Anette

    2010-01-01

    ) for 6 months after a weight loss of about 10 %. Protein constituted 10-20 % of energy in all three diets. All foods were provided free of charge from a purpose-built supermarket. Fasting blood samples were collected before and after intervention and analysed for factor VII coagulant activity (FVII...

  11. Statistical Analysis of 30 Years Rainfall Data: A Case Study

    Science.gov (United States)

    Arvind, G.; Ashok Kumar, P.; Girish Karthi, S.; Suribabu, C. R.

    2017-07-01

    Rainfall is a prime input for various engineering design such as hydraulic structures, bridges and culverts, canals, storm water sewer and road drainage system. The detailed statistical analysis of each region is essential to estimate the relevant input value for design and analysis of engineering structures and also for crop planning. A rain gauge station located closely in Trichy district is selected for statistical analysis where agriculture is the prime occupation. The daily rainfall data for a period of 30 years is used to understand normal rainfall, deficit rainfall, Excess rainfall and Seasonal rainfall of the selected circle headquarters. Further various plotting position formulae available is used to evaluate return period of monthly, seasonally and annual rainfall. This analysis will provide useful information for water resources planner, farmers and urban engineers to assess the availability of water and create the storage accordingly. The mean, standard deviation and coefficient of variation of monthly and annual rainfall was calculated to check the rainfall variability. From the calculated results, the rainfall pattern is found to be erratic. The best fit probability distribution was identified based on the minimum deviation between actual and estimated values. The scientific results and the analysis paved the way to determine the proper onset and withdrawal of monsoon results which were used for land preparation and sowing.

  12. Simulating diverse native C4 perennial grasses with varying rainfall

    Science.gov (United States)

    Rainfall is recognized as a major factor affecting the rate of plant growth development. The impact of changes in amount and variability of rainfall on growth and production of different forage grasses needs to be quantified to determine how climate change can impact rangelands. Growth and product...

  13. Prognostic Aspects of Sub-seasonal Rainfall Characteristics using the Outputs of General Circulation Model: An Application of Statistical Downscaling and Temporal Disaggregation

    Science.gov (United States)

    Singh, A.; Mohanty, U. C.; Ghosh, K.

    2015-12-01

    Most regions of India experience varied rainfall duration during the southwest monsoon, changes in which exhibit major impact not only agriculture, but also other sectors like hydrology, agriculture, food and fodder storage etc. In addition, changes in sub-seasonal rainfall characteristics highly impact the rice production. As part of the endeavor seasonal climate outlook, as well as information for weather within climate may be helpful for advance planning and risk management in agriculture. The General Circulation Model (GCM) provide an alternative to gather information for weather within climate but variability is very low in comparison to observation. On the other hand, the spatial resolution of GCM predicted rainfall is not found at the observed station/grid point. To tackle the problem, initially a statistical downscaling over 19 station of Odisha state is undertaken using the atmospheric parameters predicted by a GCM (NCEP-CFSv2). For the purpose, an extended domain is taken for analyzing the significant zone for the atmospheric parameters like zonal wind at 850hPa, Sea Surface Temperature (SST), geopotential height. A statistical model using the pattern projection method is further developed based on empirical orthogonal function. The downscaled rainfall is found better in association with station observation in comparison to raw GCM prediction in view of deterministic and probabilistic skill measure. Further, the sub-seasonal and seasonal forecast from the GCMs can be used at different time steps for risk management. Therefore, downscaled seasonal/monthly rainfall is further converted to sub-seasonal/daily time scale using a non-homogeneous markov model. The simulated weather sequences are further compared with the observed sequence in view of categorical rainfall events. The outcomes suggest that the rainfall amount are overestimated for excess rainfall and henceforth larger excess rainfall events can be realized. The skill for prediction of rainfall

  14. Mapping the world's tropical cyclone rainfall contribution over land using TRMM satellite data: precipitation budget and extreme rainfall

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.

    2012-12-01

    A study was performed to characterize over-land precipitation associated with tropical cyclones (TCs) for basins around the world gathered in the International Best Track Archive for Climate Stewardship (IBTrACS). From 1998 to 2010, rainfall data from TRMM 3B42, showed that TCs accounted for 8-, 11-, 7-, 10-, and 12-% of the annual over-land precipitation for North America, East Asia, Northern Indian Ocean, Australia, and South-West Indian Ocean respectively, and that TC-contribution decreased importantly within the first 150-km from the coast. At the local scale, TCs contributed on average to more than 40% and up to 77% of the annual precipitation budget over very different climatic areas with arid or tropical characteristics. The East Asia domain presented the higher and most constant TC-rain (170±23%-mm/yr) normalized over the area impacted, while the Southwest Indian domain presented the highest variability (130±48%-mm/yr), and the North American domain displayed the lowest average TC-rain (77±27%-mm/yr) despite a higher TC-activity. The maximum monthly TC-contribution (11-15%) was found later in the TC-season and was a conjunction between the peak of TC-activity, TC-rainfall, and the domain annual antagonism between dry and wet regimes if any. Furthermore, TC-days that accounted globally for 2±0.5% of all precipitation events for all basins, represented between 11-30% of rainfall extremes (>101.6mm/day). Locally, TC-rainfall was linked with the majority (>70%) or the quasi-totality (≈100%) of extreme rainfall. Finally, because of their importance in terms of rainfall amount, the contribution of tropical cyclones is provided for a selection of fifty urban areas experiencing cyclonic activity. Cases studies conducted at the regional scale will focus on the link between TC-activity, water resources, and hydrohazards such as floods and droughts.

  15. Multivariate forecast of winter monsoon rainfall in India using SST anomaly as a predictor: Neurocomputing and statistical approaches

    CERN Document Server

    Chattopadhyay, Goutami; Jain, Rajni

    2009-01-01

    In this paper, the complexities in the relationship between rainfall and sea surface temperature (SST) anomalies during the winter monsoon (November-January) over India were evaluated statistically using scatter plot matrices and autocorrelation functions.Linear as well as polynomial trend equations were obtained and it was observed that the coefficient of determination for the linear trend was very low and it remained low even when polynomial trend of degree six was used. An exponential regression equation and an artificial neural network with extensive variable selection were generated to forecast the average winter monsoon rainfall of a given year using the rainfall amounts and the sea surface temperature anomalies in the winter monsoon months of the previous year as predictors. The regression coefficients for the multiple exponential regression equation were generated using Levenberg-Marquardt algorithm. The artificial neural network was generated in the form of a multiplayer perceptron with sigmoid non-l...

  16. The interaction rainfall vs. weight as determinant of total mercury concentration in fish from a tropical estuary.

    Science.gov (United States)

    Barletta, M; Lucena, L R R; Costa, M F; Barbosa-Cintra, S C T; Cysneiros, F J A

    2012-08-01

    Mercury loads in tropical estuaries are largely controlled by the rainfall regime that may cause biodilution due to increased amounts of organic matter (both live and non-living) in the system. Top predators, as Trichiurus lepturus, reflect the changing mercury bioavailability situations in their muscle tissues. In this work two variables [fish weight (g) and monthly total rainfall (mm)] are presented as being important predictors of total mercury concentration (T-Hg) in fish muscle. These important explanatory variables were identified by a Weibull Regression model, which best fit the dataset. A predictive model using readily available variables as rainfall is important, and can be applied for human and ecological health assessments and decisions. The main contribution will be to further protect vulnerable groups as pregnant women and children. Nature conservation directives could also improve by considering monitoring sample designs that include this hypothesis, helping to establish complete and detailed mercury contamination scenarios.

  17. Rainfall measurement using radio links from cellular communication networks

    NARCIS (Netherlands)

    Leijnse, H.; Uijlenhoet, R.; Stricker, J.N.M.

    2007-01-01

    We investigate the potential of radio links such as employed by commercial cellular communication companies to monitor path-averaged rainfall. We present an analysis of data collected using two 38-GHz links during eight rainfall events over a 2-month period (October¿November 2003) during mostly stra

  18. Analysis of a temperature- and rainfall-dependent model for malaria transmission dynamics.

    Science.gov (United States)

    Okuneye, Kamaldeen; Gumel, Abba B

    2017-05-01

    A new non-autonomous model is designed and used to assess the impact of variability in temperature and rainfall on the transmission dynamics of malaria in a population. In addition to adding age-structure in the host population and the dynamics of immature malaria mosquitoes, a notable feature of the new model is that recovered individuals do not revert to wholly-susceptible class (that is, recovered individuals enjoy reduced susceptibility to new malaria infection). In the absence of disease-induced mortality, the disease-free solution of the model is shown to be globally-asymptotically stable when the associated reproduction ratio is less than unity. The model has at least one positive periodic solution when the reproduction ratio exceeds unity (and the disease persists in the community in this case). Detailed uncertainty and sensitivity analysis, using mean monthly temperature and rainfall data from KwaZulu-Natal province of South Africa, shows that the top three parameters of the model that have the most influence on the disease transmission dynamics are the mosquito carrying capacity, transmission probability per contact for susceptible mosquitoes and human recovery rate. Numerical simulations of the model show that, for the KwaZulu-Natal province, malaria burden increases with increasing mean monthly temperature and rainfall in the ranges ([17-25]°C and [32-110] mm), respectively (and decreases with decreasing mean monthly temperature and rainfall values). In particular, transmission is maximized for mean monthly temperature and rainfall in the ranges [21-25]°C and [95-125] mm. This occurs for a six-month period in KwaZulu-Natal (hence, this study suggests that anti-malaria control efforts should be intensified during this period). It is shown, for the fixed mean monthly temperature of KwaZulu-Natal, that malaria burden decreases whenever the amount of rainfall exceeds a certain threshold value. It is further shown (through sensitivity analysis and

  19. Impacts of Two-Type ENSO on Rainfall over Taiwan

    OpenAIRE

    Chen-Chih Lin; Yi-Jiun Liou; Shih-Jen Huang

    2015-01-01

    Impacts of two-type ENSO (El Niño/Southern Oscillation), canonical ENSO and ENSO Modoki, on rainfall over Taiwan are investigated by the monthly mean rainfall data accessed from Taiwan Central Weather Bureau. The periods of the two-type ENSO are distinguished by Niño 3.4 index and ENSO Modoki index (EMI). The rainfall data in variously geographical regions are analyzed with the values of Niño 3.4 and EMI by correlation method. Results show that the seasonal rainfalls over Taiwan are different...

  20. Impacts of Two-Type ENSO on Rainfall over Taiwan

    OpenAIRE

    Chen-Chih Lin; Yi-Jiun Liou; Shih-Jen Huang

    2015-01-01

    Impacts of two-type ENSO (El Niño/Southern Oscillation), canonical ENSO and ENSO Modoki, on rainfall over Taiwan are investigated by the monthly mean rainfall data accessed from Taiwan Central Weather Bureau. The periods of the two-type ENSO are distinguished by Niño 3.4 index and ENSO Modoki index (EMI). The rainfall data in variously geographical regions are analyzed with the values of Niño 3.4 and EMI by correlation method. Results show that the seasonal rainfalls over Taiwan are different...

  1. Daily rainfall statistics of TRMM and CMORPH: A case for trans-boundary Gandak River basin

    Indian Academy of Sciences (India)

    Brijesh Kumar; Kanhu Charan Patra; Venkat Lakshmi

    2016-07-01

    Satellite precipitation products offer an opportunity to evaluate extreme events (flood and drought)for areas where rainfall data are not available or rain gauge stations are sparse. In this study, dailyprecipitation amount and frequency of TRMM 3B42V.7 and CMORPH products have been validatedagainst daily rain gauge precipitation for the monsoon months (June–September or JJAS) from 2005–2010 in the trans-boundary Gandak River basin. The analysis shows that the both TRMM and CMORPHcan detect rain and no-rain events, but they fail to capture the intensity of rainfall.The detection of precipitation amount is strongly dependent on the topography. In the plains areas,TRMM product is capable of capturing high-intensity rain events but in the hilly regions, it underestimatesthe amount of high-intensity rain events. On the other hand, CMORPH entirely fails to capturethe high-intensity rain events but does well with low-intensity rain events in both hilly regions as well asthe plain region. The continuous variable verification method shows better agreement of TRMM rainfallproducts with rain gauge data. TRMM fares better in the prediction of probability of occurrenceof high-intensity rainfall events, but it underestimates intensity at high altitudes. This implies thatTRMM precipitation estimates can be used for flood-related studies only after bias adjustment for thetopography.

  2. Variations of characteristics of consecutive rainfall days over northern Thailand

    Science.gov (United States)

    Klongvessa, P.; Lu, M.; Chotpantarat, S.

    2017-07-01

    The Chao Phraya basin, Thailand, is frequently inundated by flooding during the southwest monsoon period. Most floods coincide with consecutive rainfall days. This study investigated consecutive rainfall days during the southwest monsoon period at 11 stations over northern Thailand, the upstream area of this basin. The Markov chain probability model was used to study the consecutiveness of days with at least 0.1, 10.1, and 35.1 mm of rainfall. The consecutive length of rainfall days from the model showed good agreement with the observed value. A chi-square test of independence was applied to assess the significance of the consecutiveness, and it was found that days with at least 10.1 mm of rainfall tend to be consecutive over the entire area. Moreover, days with at least 35.1 mm of rainfall were found to be consecutive over the joint area where the mountainous region meets the plain area. However, the consecutiveness of days with less than 10.1 mm of rainfall was not obvious. The rainfall amount on days with at least 10.1 mm of rainfall was also calculated and it showed lower values over the mountainous region than over the plain. Hence, this study established the characteristics of consecutive rainfall days over the plain, mountainous region, and joint area.

  3. Development of Rainfall Model using Meteorological Data for Hydrological Use

    Directory of Open Access Journals (Sweden)

    Mohd Adib Mohammad Razi

    2013-11-01

    Full Text Available Abstract At present, research on forecasting unpredictable weather such as heavy rainfall is one of the most important challenges for equipped meteorological center. In addition, the incidence of significant weather events is estimated to rise in the near future due to climate change, and this situation inspires more studies to be done. This study introduces a rainfall model that has been developed using selected rainfall parameters with the aim to recognize rainfall depth in a catchment area. This study proposes a rainfall model that utilizes the amount of rainfall, temperature, humidity and pressure records taken from selected stations in Peninsular Malaysia and they are analyzed using SPSS multiple regression model. Seven meteorological stations are selected for data collection from 1997 until 2007 in Peninsular Malaysia which are Senai, Kuantan, Melaka, Subang, Ipoh, Bayan Lepas, and Chuping. Multiple Regression analysis in Statistical Package for Social Science (SPSS software has been used to analyze a set of eleven years (1997 – 2007 meteorological data. Senai rainfall model gives an accurate result compared to observation rainfall data and this model were validating with data from Kota Tinggi station. The analysis shows that the selected meteorological parameters influence the rainfall development. As a result, the rainfall model developed for Senai proves that it can be used in Kota Tinggi catchment area within the limit boundaries, as the two stations are close from one another. Then, the amounts of rainfall at the Senai and Kota Tinggi stations are compared and the calibration analysis shows that the proposed rainfall model can be used in both areas.

  4. Monitoring Niger River Floods from satellite Rainfall Estimates : overall skill and rainfall uncertainty propagation.

    Science.gov (United States)

    Gosset, Marielle; Casse, Claire; Peugeot, christophe; boone, aaron; pedinotti, vanessa

    2015-04-01

    Global measurement of rainfall offers new opportunity for hydrological monitoring, especially for some of the largest Tropical river where the rain gauge network is sparse and radar is not available. Member of the GPM constellation, the new French-Indian satellite Mission Megha-Tropiques (MT) dedicated to the water and energy budget in the tropical atmosphere contributes to a better monitoring of rainfall in the inter-tropical zone. As part of this mission, research is developed on the use of satellite rainfall products for hydrological research or operational application such as flood monitoring. A key issue for such applications is how to account for rainfall products biases and uncertainties, and how to propagate them into the end user models ? Another important question is how to choose the best space-time resolution for the rainfall forcing, given that both model performances and rain-product uncertainties are resolution dependent. This paper analyses the potential of satellite rainfall products combined with hydrological modeling to monitor the Niger river floods in the city of Niamey, Niger. A dramatic increase of these floods has been observed in the last decades. The study focuses on the 125000 km2 area in the vicinity of Niamey, where local runoff is responsible for the most extreme floods recorded in recent years. Several rainfall products are tested as forcing to the SURFEX-TRIP hydrological simulations. Differences in terms of rainfall amount, number of rainy days, spatial extension of the rainfall events and frequency distribution of the rain rates are found among the products. Their impacts on the simulated outflow is analyzed. The simulations based on the Real time estimates produce an excess in the discharge. For flood prediction, the problem can be overcome by a prior adjustment of the products - as done here with probability matching - or by analysing the simulated discharge in terms of percentile or anomaly. All tested products exhibit some

  5. Performance of CMORPH, TMPA, and PERSIANN rainfall datasets over plain, mountainous, and glacial regions of Pakistan

    Science.gov (United States)

    Hussain, Yawar; Satgé, Frédéric; Hussain, Muhammad Babar; Martinez-Carvajal, Hernan; Bonnet, Marie-Paule; Cárdenas-Soto, Martin; Roig, Henrique Llacer; Akhter, Gulraiz

    2017-01-01

    The present study aims at the assessment of six satellite rainfall estimates (SREs) in Pakistan. For each assessed products, both real-time (RT) and post adjusted (Adj) versions are considered to highlight their potential benefits in the rainfall estimation at annual, monthly, and daily temporal scales. Three geomorphological climatic zones, i.e., plain, mountainous, and glacial are taken under considerations for the determination of relative potentials of these SREs over Pakistan at global and regional scales. All SREs, in general, have well captured the annual north-south rainfall decreasing patterns and rainfall amounts over the typical arid regions of the country. Regarding the zonal approach, the performance of all SREs has remained good over mountainous region comparative to arid regions. This poor performance in accurate rainfall estimation of all the six SREs over arid regions has made their use questionable in these regions. Over glacier region, all SREs have highly overestimated the rainfall. One possible cause of this overestimation may be due to the low surface temperature and radiation absorption over snow and ice cover, resulting in their misidentification with rainy clouds as daily false alarm ratio has increased from mountainous to glacial regions. Among RT products, CMORPH-RT is the most biased product. The Bias was almost removed on CMORPH-Adj thanks to the gauge adjustment. On a general way, all Adj versions outperformed their respective RT versions at all considered temporal scales and have confirmed the positive effects of gauge adjustment. CMORPH-Adj and TMPA-Adj have shown the best agreement with in situ data in terms of Bias, RMSE, and CC over the entire study area.

  6. Rainfall deficit and excess rainfall during vegetation of early potatoes varieties in central-eastern Poland (1971-2005

    Directory of Open Access Journals (Sweden)

    Elżbieta Radzka

    2015-06-01

    Full Text Available The study was based on data collected from nine stations of the Institute of Meteoro­logy and Water Management in central-eastern Poland (1971-2005 concerning monthly precipitation total and mean monthly air temperature during the vegetation period of early potatoes (April-July. Optimal precipitation for early potato was calculated according to the Klatt indexes for medium cohesive and light soils in the successive months of the vegetation period. Rainfall deficit and excess rainfall were determined based on differences between monthly precipitation totals recorded in the years of the study and values considered to be optimal. It was found that the frequency of rainfall deficit during vegetation of early potato in each analysed location both for medium cohesive soil and for light soil exceeded the frequency of its excess. The greatest mean monthly rainfall deficit from the multiannual period in the vegetation season of early potato in all the analysed locations and for both soil types was recorded in June, while excess rainfall was observed in July. Lower values of standard deviation for rainfall deficit were calculated in the case of light soil than medium cohesive soil, while an opposite dependence was recorded for excess rainfall. The risk for early potato plantations on light soil was connected with frequent extreme deficits. They were observed most often in the south-eastern part of the study area, while they were rarest in the belt from Pułtusk towards Szepietowo. Values of the slope of the trend lines were low for all the weather stations and most of them were statistically non-significant. However, all values concerning rainfall deficit were negative, which indicates its slight increase from year to year. A significant trend for changes in rainfall deficit was observed only in Włodawa and Siedlce, while for excess rainfall it was found in Szepietowo and Białowieża.

  7. Key pluvial parameters in assessing rainfall erosivity in the south-west development region, Romania

    Indian Academy of Sciences (India)

    Monica Dumitraşcu; Carmen-Sofia Dragotă; Ines Grigorescu; Costin Dumitraşcu; Alina Vlăduţ

    2017-06-01

    Located in the south-western part of Romania, the south-west development region overlaps the main relief forms: the Carpathians mountains, the Getic Subcarpathians, the Getic piedmont, the Romanian plain and the Danube valley. The study aims at providing an overview on the main pluvial parameters and their role in assessing rainfall erosivity in the study area. The authors assessed the occurrence, frequency and magnitude of some of the most significant pluvial parameters and their impact on the climatic aggressiveness in the study area. Thus, the monthly and annual mean and extreme climatic values for different rainfall related parameters (e.g., maximum amounts of precipitation/24 hr, heavy rainfall), as well as relevant indices and indicators for pluvial aggressiveness (Fournier, Fournier Modified, Angot) were calculated. The rainfall erosivity was assessed in order to provide both the spatial distribution of the triggering extreme weather phenomena and the resulted intensity classes for the analysed indices and indicators. The authors used long-term precipitation records (1961–2010) for the selected relevant meteorological stations distributed throughout all analysed relief units.

  8. The Effect of Rainfall Patterns on the Mechanisms of Shallow Slope Failure

    Directory of Open Access Journals (Sweden)

    Muhammad Suradi

    2014-04-01

    Full Text Available This paper examines how rainfall patterns affect the mechanisms of shallow slope failure. Numerical modelling, utilising the commercial software SVFlux and SVSlope, was carried out for a coupled analysis of rainfall-induced slope seepage and instability, with reference to a shallow landslide took place in Jabiru, Northern Territory (NT Australia in 2007. Rainfall events were varied in terms of pattern in this analysis. The results revealed that slopes are sensitive to rainfall pattern when the rainfall intensity has a high degree of fluctuation at around the same value as that of saturated hydraulic conductivity. Average rainfall intensity at the beginning of a rainfall period plays a primary role in determining the rate of decrease in initial factor of safety (Fi towards minimum factor of safety (Fmin. The effect of rainfall events on the slope instability is attributed to the amount of rainwater infiltration into slope associated with rainfall pattern.

  9. The relationship between the Guinea Highlands and the West African offshore rainfall maximum

    Science.gov (United States)

    Hamilton, H. L.; Young, G. S.; Evans, J. L.; Fuentes, J. D.; Núñez Ocasio, K. M.

    2017-01-01

    Satellite rainfall estimates reveal a consistent rainfall maximum off the West African coast during the monsoon season. An analysis of 16 years of rainfall in the monsoon season is conducted to explore the drivers of such copious amounts of rainfall. Composites of daily rainfall and midlevel meridional winds centered on the days with maximum rainfall show that the day with the heaviest rainfall follows the strongest midlevel northerlies but coincides with peak low-level moisture convergence. Rain type composites show that convective rain dominates the study region. The dominant contribution to the offshore rainfall maximum is convective development driven by the enhancement of upslope winds near the Guinea Highlands. The enhancement in the upslope flow is closely related to African easterly waves propagating off the continent that generate low-level cyclonic vorticity and convergence. Numerical simulations reproduce the observed rainfall maximum and indicate that it weakens if the African topography is reduced.

  10. How important is tropospheric humidity for coastal rainfall in the tropics?

    Science.gov (United States)

    Bergemann, Martin; Jakob, Christian

    2016-06-01

    Climate models show considerable rainfall biases in coastal tropical areas, where approximately 33% of the overall rainfall received is associated with coastal land-sea interaction. Building on an algorithm to objectively identify rainfall that is associated with land-sea interaction we investigate whether the relationship between rainfall in coastal regions and atmospheric humidity differs from that over the open ocean or over inland areas. We combine 3-hourly satellite estimates of rainfall with humidity estimates from reanalyses and investigate if coastal rainfall reveals the well-known relationship between area-averaged precipitation and column-integrated moisture. We find that rainfall that is associated with coastal land-sea effects occurs under much drier midtropospheric conditions than that over the ocean and does not exhibit a pronounced critical value of humidity. In addition, the dependence of the amount of rainfall on midtropospheric moisture is significantly weaker when the rainfall is coastally influenced.

  11. Assessment of satellite rainfall products over the Andean plateau

    Science.gov (United States)

    Satgé, Frédéric; Bonnet, Marie-Paule; Gosset, Marielle; Molina, Jorge; Hernan Yuque Lima, Wilson; Pillco Zolá, Ramiro; Timouk, Franck; Garnier, Jérémie

    2016-01-01

    Nine satellite rainfall estimations (SREs) were evaluated for the first time over the South American Andean plateau watershed by comparison with rain gauge data acquired between 2005 and 2007. The comparisons were carried out at the annual, monthly and daily time steps. All SREs reproduce the salient pattern of the annual rain field, with a marked north-south gradient and a lighter east-west gradient. However, the intensity of the gradient differs among SREs: it is well marked in the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 (TMPA-3B42), Precipitation Estimation from remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Global Satellite Mapping of Precipitation (GSMaP) products, and it is smoothed out in the Climate prediction center MORPHing (CMORPH) products. Another interesting difference among products is the contrast in rainfall amounts between the water surfaces (Lake Titicaca) and the surrounding land. Some products (TMPA-3B42, PERSIANN and GSMaP) show a contradictory rainfall deficit over Lake Titicaca, which may be due to the emissivity contrast between the lake and the surrounding lands and warm rain cloud processes. An analysis differentiating coastal Lake Titicaca from inland pixels confirmed this trend. The raw or Real Time (RT) products have strong biases over the study region. These biases are strongly positive for PERSIANN (above 90%), moderately positive for TMPA-3B42 (28%), strongly negative for CMORPH (- 42%) and moderately negative for GSMaP (- 18%). The biases are associated with a deformation of the rain rate frequency distribution: GSMaP underestimates the proportion of rainfall events for all rain rates; CMORPH overestimates the proportion of rain rates below 2 mm day- 1; and the other products tend to overestimate the proportion of moderate to high rain rates. These biases are greatly reduced by the gauge adjustment in the TMPA-3B42, PERSIANN and CMORPH products, whereas a

  12. Possible relationship between North Korean total rainfall and Arctic Oscillation in May

    Science.gov (United States)

    Choi, Ki-Seon; Kang, Sung-Dae; Kim, Hae-Dong

    2013-05-01

    In this study, a negative correlation between the rainfall over North Korea in May and the Arctic Oscillation (AO) in the same month is analyzed. The reasons for rainfall declines in the positive AO phase are as follows: (a) the strengthening of anomalous anticyclone in the Maritime Province of Siberia, (b) the weakening of the subtropical western North Pacific high, and (c) the stabilization across all the atmospheric layers in North Korea. Anomalous anticyclone strengthened in the Maritime Province of Siberia plays a critical role in placing the North Korean region under the influence of anomalous northeasterlies. In addition, the development of the anomalous northeasterlies results in the supply of a large amount of cold and dry air into North Korea. This consequently stabilizes the atmosphere in North Korea. Moreover, the reinforcement of anomalous cold sea surface temperature in the mid-latitude region of East Asia is found to be another reason for the atmospheric stabilization.

  13. Analysis of daily rainfall of the Sahelian weather-station Linguère (Senegal) - Trends and its impacts on the local population

    Science.gov (United States)

    Strommer, Gabriel; Brandt, Martin; Diongue-Niang, Aida; Samimi, Cyrus

    2013-04-01

    In the 20th century, the West African Sahel has been a hot-spot of climatic changes. After severe drought-events in the 1970s and 1980s which were followed by a significant drop in annual precipitation, rainfall seems to increase again during the past years. Most studies are based on monthly or yearly datasets. However, many processes and events which are important for the local population depending on rainfall are not related to monthly or annual precipitation but are related to intra-annual, often daily scales. During this study, interviews with farmers and herders were conducted in the Senegalese Sahel. The results show, that wet months with unsuitably distributed precipitation can cause more harm than bringing benefits - depending on the phenological stage of the plants. Agricultural crops for example need rainfall breaks. On the other hand, natural herbaceous vegetation tolerates longer wet periods. So, a wet season can still hide dry spells that alter crops and vegetation development. Based on the results of these interviews, this study developed two indexes, one for local farmers and one for herders separately, showing if the year was favorable for them or not. The indexes integrate the length of rainy seasons, intensity and frequency of rainfall events, breaks between events and also the previous year. This way, each year is assigned to one of 5 classes. Using daily rainfall data of the Linguère weather-station (from the Senegal Meteorological Service, ANACIM), trends of the indexes from 1945 to 2002 are detected and compared to results of the interviews. Statistically relating the indexes to yearly and monthly data demonstrates, how much information can be gathered by those datasets. Furthermore, changes in intensity and frequency are related with yearly and monthly sums showing relations between daily data and annual sums. For example, a high correlation (r=0.73) between the amount of rain days (> 1 mm) and the annual rainfall is observed in Linguère.

  14. Assessment of Temperature and Elevation Controls on Spatial Variability of Rainfall in Iran

    OpenAIRE

    Majid Javari

    2017-01-01

    With rainfall changes, hydrological process variability increases. This study predicts the potential effects of temperature and topography characteristics on rainfall spatial variability. Temperature and topography were considered as two effective factors that may influence monthly rainfall. This study uses rainfall and temperature data from 174 synoptic and climatic stations and 39,055 rain, elevation and temperature points extracted by ArcGIS10.3 over the 40 years (1975–2014). In this study...

  15. Long-term variability of the leading seasonal modes of rainfall in south-eastern Australia

    OpenAIRE

    Maryam Montazerolghaem; Willem Vervoort; Budiman Minasny; Alex McBratney

    2016-01-01

    Knowledge of temporal and spatial variability of climate and rainfall can improve agriculture production and can help to manage risks caused by climate variability. Available high-quality monthly rainfall data from the Australian Bureau of Meteorology for 1907–2011 was used to investigate the leading seasonal mode of the long-term rainfall variability over south-eastern and eastern Australia. Spatio-temporal variations of seasonal rainfall and their connection to oceanic-atmospheric predictor...

  16. Spatial Variability of Rainfall

    DEFF Research Database (Denmark)

    Jensen, N.E.; Pedersen, Lisbeth

    2005-01-01

    As a part of a Local Area Weather Radar (LAWR) calibration exercise 15 km south of Århus, Denmark, the variability in accumulated rainfall within a single radar pixel (500 by 500 m) was measured using nine high-resolution rain gauges. The measured values indicate up to a 100% variation between...

  17. The Wageningen Rainfall Simulator

    NARCIS (Netherlands)

    Lassu, Tamas; Seeger, K.M.; Peters, P.D.; Keesstra, S.D.

    2015-01-01

    The set-up and characterisation of an indoor nozzle-type rainfall simulator (RS) at Wageningen University, the Netherlands, are presented. It is equipped with four Lechler nozzles (two nr. 460·788 and two nr. 461·008). The tilting irrigation plot is 6 m long and 2·5 m wide. An electrical pump

  18. RAINFALL ANALYSIS IN KLANG RIVER BASIN USING CONTINUOUS WAVELET TRANSFORM

    Directory of Open Access Journals (Sweden)

    Celso A. G. Santos

    2016-01-01

    Full Text Available The rainfall characteristics within Klang River basin is analyzed by the continuous wavelet transform using monthly rainfall data (1997–2009 from a raingauge and also using daily rainfall data (1998–2013 from the Tropical Rainfall Measuring Mission (TRMM. The wavelet power spectrum showed that some frequency components were presented within the rainfall time series, but the observed time series is short to provide accurate information, thus the daily TRMM rainfall data were used. In such analysis, two main frequency components, i.e., 6 and 12 months, showed to be present during the entire period of 16 years. Such semiannual and annual frequencies were confirmed by the global wavelet power spectra. Finally, the modulation in the 8–16-month and 256– 512-day bands were examined by an average of all scales between 8 and 16 months, and 256 and 512 days, respectively, giving a measure of the average monthly/daily variance versus time, where the periods with low or high variance could be identified.

  19. Historical analysis of interannual rainfall variability and trends in southeastern Brazil based on observational and remotely sensed data

    Science.gov (United States)

    Vásquez P., Isela L.; de Araujo, Lígia Maria Nascimento; Molion, Luiz Carlos Baldicero; de Abdalad, Mariana Araujo; Moreira, Daniel Medeiros; Sanchez, Arturo; Barbosa, Humberto Alves; Rotunno Filho, Otto Corrêa

    2017-04-01

    The Brazilian Southeast is considered a humid region. It is also prone to landslides and floods, a result of significant increases in rainfall during spring and summer caused by the South Atlantic Convergence Zone (SACZ). Recently, however, the region has faced a striking rainfall shortage, raising serious concerns regarding water availability. The present work endeavored to explain the meteorological drought that has led to hydrological imbalance and water scarcity in the region. Hodrick-Prescott smoothing and wavelet transform techniques were applied to long-term hydrologic and sea surface temperature (SST)—based climate indices monthly time series data in an attempt to detect cycles and trends that could help explain rainfall patterns and define a framework for improving the predictability of extreme events in the region. Historical observational hydrologic datasets available include monthly precipitation amounts gauged since 1888 and 1940 and stream flow measured since the 1930s. The spatial representativeness of rain gauges was tested against gridded rainfall satellite estimates from 2000 to 2015. The analyses revealed variability in four time scale domains—infra-annual, interannual, quasi-decadal and inter-decadal or multi-decadal. The strongest oscillations periods revealed were: for precipitation—8 months, 2, 8 and 32 years; for Pacific SST in the Niño-3.4 region—6 months, 2, 8 and 35.6 years, for North Atlantic SST variability—6 months, 2, 8 and 32 years and for Pacific Decadal Oscillation (PDO) index—6.19 months, 2.04, 8.35 and 27.31 years. Other periodicities less prominent but still statistically significant were also highlighted.

  20. Inverse hydrological modelling of spatio-temporal rainfall patterns

    Science.gov (United States)

    Grundmann, Jens; Hörning, Sebastian; Bárdossy, András

    2016-04-01

    Distributed hydrological models are commonly used for simulating the non-linear response of a watershed to rainfall events for addressing different hydrological properties of the landscape. Such models are driven by spatial rainfall patterns for consecutive time steps, which are normally generated from point measurements using spatial interpolation methods. However, such methods fail in reproducing the true spatio-temporal rainfall patterns especially in data scarce regions with poorly gauged catchments or for highly dynamic, small scaled rainstorms which are not well recorded by existing monitoring networks. Consequently, uncertainties are associated with poorly identified spatio-temporal rainfall distribution in distributed rainfall-runoff-modelling since the amount of rainfall received by a catchment as well as the dynamics of the runoff generation of flood waves are underestimated. For addressing these challenges a novel methodology for inverse hydrological modelling is proposed using a Markov-Chain-Monte-Carlo framework. Thereby, potential candidates of spatio-temporal rainfall patterns are generated and selected according their ability to reproduce the observed surface runoff at the catchment outlet for a given transfer function in a best way. The Methodology combines the concept of random mixing of random spatial fields with a grid-based spatial distributed rainfall runoff model. The conditional target rainfall field is obtained as a linear combination of unconditional spatial random fields. The corresponding weights of the linear combination are selected such that the spatial variability of the rainfall amounts as well as the actual observed rainfall values are reproduced. The functionality of the methodology is demonstrated on a synthetic example. Thereby, the known spatio-temporal distribution of rainfall is reproduced for a given number of point observations of rainfall and the integral catchment response at the catchment outlet for a synthetic catchment

  1. The Winter Rainfall of Malaysia

    National Research Council Canada - National Science Library

    Chen, Tsing-Chang; Tsay, Jenq-Dar; Yen, Ming-Cheng; Matsumoto, Jun

    2013-01-01

    .... The major cause of the rainfall maximum of Peninsular Malaysia is cold surge vortices (CSVs) and heavy rainfall/flood (HRF) events propagating from the Philippine area and Borneo. In contrast, the major cause of the rainfall maximum of Borneo is these rain-producing disturbances trapped in Borneo. Disturbances of the former group are formed by the cold sur...

  2. Continuous rainfall generation for a warmer climate using observed temperature sensitivities

    Science.gov (United States)

    Wasko, Conrad; Sharma, Ashish

    2017-01-01

    Continuous rainfall sequences are often used as inputs in hydrologic modeling, particularly where a probabilistic assessment is required. Continuous rainfall sequences provide a means for accounting of all aspects of rainfall that produce flooding, for example, not just the design rainfall event but also the rainfall prior to the extreme rainfall event. With the advent of climate change, higher temperatures have been associated with changes in rainfall, in particular intensifying rainfall extremes with less uniform temporal patterns. Given these demonstrated changes to extreme rainfall with temperature rise, there is a need to modify continuous rainfall generators to account for current and likely future changes in temperature. In this work we propose a novel method for simulating continuous rainfall sequences for a future warmer climate by conditioning parameters on their historical sensitivity with temperature. To demonstrate the proposed technique we use a one-dimensional Neyman-Scott Rectangular Pulses model at two locations across Australia. The statistics used in the parameter estimation are conditioned on their historical sensitivity to average monthly temperature to simulate rainfall for a change in temperature. The results are validated by comparing the simulated rainfall against observations originating from differing temperatures and it is shown that the model captures the relative difference in the mean monthly rainfall and monthly maxima. Encouraged by these results we simulate rainfall for higher temperatures and capture expected changes to annual maxima and design temporal patterns for a warmer climate. While we demonstrate our methodology in the simulation of sub-daily rainfall using a specific model, the approach presented here can be applied to all weather generation schemes for projection in a warmer climate.

  3. Relationships between Rainy Days, Mean Daily Intensity, and Seasonal Rainfall over the Koyna Catchment during 1961–2005

    Science.gov (United States)

    Nandargi, S.; Mulye, S. S.

    2012-01-01

    There are limitations in using monthly rainfall totals in studies of rainfall climatology as well as in hydrological and agricultural investigations. Variations in rainfall may be considered to result from frequency changes in the daily rainfall of the respective regime. In the present study, daily rainfall data of the stations inside the Koyna catchment has been analysed for the period of 1961–2005 to understand the relationship between the rain and rainy days, mean daily intensity (MDI) and seasonal rainfall over the catchment on monthly as well as seasonal scale. Considering the topographical location of the catchment, analysis of seasonal rainfall data of 8 stations suggests that a linear relationship fits better than the logarithmic relationship in the case of seasonal rainfall versus mean daily intensity. So far as seasonal rainfall versus number of rainy days is considered, the logarithmic relationship is found to be better. PMID:22654646

  4. Relationships between Rainy Days, Mean Daily Intensity, and Seasonal Rainfall over the Koyna Catchment during 1961–2005

    Directory of Open Access Journals (Sweden)

    S. Nandargi

    2012-01-01

    Full Text Available There are limitations in using monthly rainfall totals in studies of rainfall climatology as well as in hydrological and agricultural investigations. Variations in rainfall may be considered to result from frequency changes in the daily rainfall of the respective regime. In the present study, daily rainfall data of the stations inside the Koyna catchment has been analysed for the period of 1961–2005 to understand the relationship between the rain and rainy days, mean daily intensity (MDI and seasonal rainfall over the catchment on monthly as well as seasonal scale. Considering the topographical location of the catchment, analysis of seasonal rainfall data of 8 stations suggests that a linear relationship fits better than the logarithmic relationship in the case of seasonal rainfall versus mean daily intensity. So far as seasonal rainfall versus number of rainy days is considered, the logarithmic relationship is found to be better.

  5. Distribuição temporal da precipitação pluvial mensal observada no Posto Meteorológico do Instituto Agronômico, em Campinas, SP Monthly rainfall temporal distribution observed in the Agronomic Institute Weather Station at Campinas, São Paulo State, Brazil

    Directory of Open Access Journals (Sweden)

    Gabriel Constantino Blain

    2007-01-01

    rainfall temporal distribution at Campinas, São Paulo State, from 1890 to 2005. In order to detect possible trends in the precipitation series, the 116 years were divided in four equally spaced periods (P1, P2, P3 e P4 which were compared among themselves then using the gama probability density function for 48 data sets (4 periods of each 12 months. The skewness level of the monthly precipitation series showed that the consistency of climatic water balance that uses monthly precipitations arithmetic means can be questioned in no significant trends were detected on the monthly rainfall time distribution at Campinas.

  6. The influence of seasonal rainfall upon Sahel vegetation

    DEFF Research Database (Denmark)

    Proud, Simon Richard; Rasmussen, Laura Vang

    2011-01-01

    include changes in total yearly rainfall, land-use change and migration. But these factors are not fully explanatory. This study addresses other possible factors for variation in vegetation patterns through the analysis of the Normalized Difference Vegetation Index (NDVI) produced by satellite sensors. We...... focus on precipitation, but instead of looking at the total yearly amount of rainfall, the intra-annual variation is examined. Here we show that plant growth is strongly correlated with the number and frequency of days within the rainy season upon which there is no rainfall. Furthermore, we find...

  7. 461 TIME SERIES ANALYSES OF MEAN MONTHLY RAINFALL ...

    African Journals Online (AJOL)

    Osondu

    tests (trend, cycle, seasonal and decomposition analyses) using additive and multiplicative modeling approach. ... period under review. ... alone (including desertification and soil erosion) ... than one meter co-dominate (Davis 1982 p12).

  8. Association between Australian rainfall and the Southern Annular Mode

    Science.gov (United States)

    Meneghini, Belinda; Simmonds, Ian; Smith, Ian N.

    2007-01-01

    In this study, we explore the relationships between seasonal Australian rainfall and the Southern Annular Mode (SAM). We produce two seasonal indices of the SAM: the Antarctic Oscillation Index (AOI), and an Australian regional version (AOIR) using ERA-40 mean sea-level pressure (MSLP) reanalysis data. The seasonal rainfall data are based on gridded monthly rainfall provided by the Australian Bureau of Meteorology.For the period 1958-2002 a significant inverse relationship is found between the SAM and rainfall in southern Australia, while a significant in-phase relationship is found between the SAM and rainfall in northern Australia. Furthermore, widespread significant inverse relationships in southern Australia are only observed in winter, and only with the AOIR. The AOIR accounts for more of the winter rainfall variability in southwest Western Australia, southern South Australia, western and southern Victoria, and western Tasmania than the Southern Oscillation Index. Overall, our results suggest that changes in the SAM may be partly responsible for the current decline in winter rainfall in southern South Australia, Victoria, and Tasmania, but not the long-term decline in southwest Western Australian winter rainfall.

  9. Impacts of Two-Type ENSO on Rainfall over Taiwan

    Directory of Open Access Journals (Sweden)

    Chen-Chih Lin

    2015-01-01

    Full Text Available Impacts of two-type ENSO (El Niño/Southern Oscillation, canonical ENSO and ENSO Modoki, on rainfall over Taiwan are investigated by the monthly mean rainfall data accessed from Taiwan Central Weather Bureau. The periods of the two-type ENSO are distinguished by Niño 3.4 index and ENSO Modoki index (EMI. The rainfall data in variously geographical regions are analyzed with the values of Niño 3.4 and EMI by correlation method. Results show that the seasonal rainfalls over Taiwan are different depending on the effects of two-type ENSO. In canonical El Niño episode, the rainfall increases in winter and spring while it reduces in summer and autumn. On the contrary, the rainfall increases in summer and autumn but reduces in winter and spring in El Niño Modoki episode. Nevertheless, two types of La Niña cause similar effects on the rainfall over Taiwan. It increases in autumn only. The rainfall variations in different types of ENSO are mainly caused by the monsoon and topography.

  10. Reconstruction of rainfall in Zafra (southwest Spain from 1750 to 1840 from documentary sources

    Directory of Open Access Journals (Sweden)

    M. I. Fernández-Fernández

    2011-11-01

    Full Text Available This work presents the first high-resolution reconstruction of rainfall in southwestern Spain during the period 1750–1840. The weather descriptions used are weekly reports describing the most relevant events that occurred in the Duchy of Feria. An index was defined to characterise the weekly rainfall. Monthly indices were obtained by summing the corresponding weekly indices, obtaining cumulative monthly rainfall indices. The reconstruction method consisted of establishing a linear correlation between the monthly rainfall index and monthly instrumental data (1960–1990. The correlation coefficients were greater than 0.80 for all months. The rainfall reconstruction showed major variability similar to natural variability. The reconstructed rainfall series in Zafra was compared with the rainfall series of Cadiz, Gibraltar and Lisbon for the period 1750–1840, with all four series found to have a similar pattern. The influence of the North Atlantic Oscillation (NAO on the winter rainfall reconstruction was found to behave similarly to that of modern times. Other studies described are of the SLP values over the entire North Atlantic in the months with extreme values of rainfall, and unusual meteorological events (hail, frost, storms and snowfall in the reports of the Duchy of Feria.

  11. Application of seasonal rainfall forecasts and satellite rainfall observations to crop yield forecasting for Africa

    Science.gov (United States)

    Greatrex, H. L.; Grimes, D. I. F.; Wheeler, T. R.

    2009-04-01

    Rain-fed agriculture is of utmost importance in sub-Saharan Africa; the FAO estimates that over 90% of food consumed in the region is grown in rain-fed farming systems. As the climate in sub-Saharan Africa has a high interannual variability, this dependence on rainfall can leave communities extremely vulnerable to food shortages, especially when coupled with a lack of crop management options. The ability to make a regional forecast of crop yield on a timescale of months would be of enormous benefit; it would enable both governmental and non-governmental organisations to be alerted in advance to crop failure and could facilitate national and regional economic planning. Such a system would also enable individual communities to make more informed crop management decisions, increasing their resilience to climate variability and change. It should be noted that the majority of crops in the region are rainfall limited, therefore the ability to create a seasonal crop forecast depends on the ability to forecast rainfall at a monthly or seasonal timescale and to temporally downscale this to a daily time-series of rainfall. The aim of this project is to develop a regional-scale seasonal forecast for sub-Saharan crops, utilising the General Large Area Model for annual crops (GLAM). GLAM would initially be driven using both dynamical and statistical seasonal rainfall forecasts to provide an initial estimate of crop yield. The system would then be continuously updated throughout the season by replacing the seasonal rainfall forecast with daily weather observations. TAMSAT satellite rainfall estimates are used rather than rain-gauge data due to the scarcity of ground based observations. An important feature of the system is the use of the geo-statistical method of sequential simulation to create an ensemble of daily weather inputs from both the statistical seasonal rainfall forecasts and the satellite rainfall estimates. This allows a range of possible yield outputs to be

  12. Modeling seasonal leptospirosis transmission and its association with rainfall and temperature in Thailand using time-series and ARIMAX analyses

    Institute of Scientific and Technical Information of China (English)

    Sudarat Chadsuthi; Charin Modchang; Yongwimon Lenbury; Sopon Iamsirithaworn; Wannapong Triampo

    2012-01-01

    ABSTRACT Objective:To study the number of leptospirosis cases in relations to the seasonal pattern, and its association with climate factors.Methods:Time series analysis was used to study the time variations in the number of leptospirosis cases.TheAutoregressiveIntegratedMovingAverage (ARIMA) model was used in data curve fitting and predicting the next leptospirosis cases. Results:We found that the amount of rainfall was correlated to leptospirosis cases in both regions of interest, namely the northern and northeastern region ofThailand, while the temperature played a role in the northeastern region only.The use of multivariateARIMA(ARIMAX) model showed that factoring in rainfall(with an8 months lag) yields the best model for the northern region while the model, which factors in rainfall(with a10 months lag) and temperature(with an8 months lag) was the best for the northeastern region.Conclusions:The models are able to show the trend in leptospirosis cases and closely fit the recorded data in both regions.The models can also be used to predict the next seasonal peak quite accurately.

  13. A gênese da escassez de chuva em Maringá, Estado do Paraná, Brasil, durante os meses de maio de 2003 e maio de 2005 = The genesis of scanty rainfall in Maringá, Paraná State, Brazil, during the months of May 2003 and May 2005

    Directory of Open Access Journals (Sweden)

    Leonor Marcon da Silveira

    2010-01-01

    Full Text Available O presente estudo teve por objetivo identificar os sistemas atmosféricos geradores da escassez de chuvas durante os meses de maio de 2003 e maio de 2005, em Maringá, Estado do Paraná, Brasil. Para atingir os objetivos propostos, utilizaram-se dados meteorológicos de superfície referentes às variações diárias dos elementos climáticos, com os quais se elaborou uma tabela para cada um dos meses em estudo, eleitos como amostragem de meses de maio secos. Para identificar os sistemas atmosféricos promotores dos diferentes tipos de tempo, tais tabelas foram analisadas concomitantemente à análise de cartas sinóticas meteorológicas de superfície, também diárias, e de imagens de satélite. Constatou-se que a escassez de chuva em Maringá durante os períodos estudados decorreu da atuação de anticiclones frios, que penetraram na retaguarda dos sistemas frontais, e da atuação do Sistema Tropical Atlântico sobre o continente, o qual geralmente bloqueava as frentes frias próximo à latitude de 30°S, de modo que estas se deslocavam para o Atlântico antes de alcançarem a área em estudo. The atmospheric systems accountable for scanty rainfall during May 2003 and May 2005 in Maringá, Paraná State, Brazil, are identified. Surface meteorological data on daily variables of climatic elements have been employed for the creation of a table for each month under analysis. They were chosen as dry May samplings. Tables were analyzed concomitantly with an investigation on daily surface meteorological synoptic charts and on satellite photos, so that the atmosphericsystems causing different types of climate might be identified. Results show that scanty rainfall in Maringá during the periods under analysis was caused by cold anti-cyclone activities which followed after frontal systems and by the activities of Atlantic TropicalSystem on the South American subcontinent. The latter normally blocks out cold fronts near latitude 30°S which, in turn

  14. A radar-based regional extreme rainfall analysis to derive the thresholds for a novel automatic alert system in Switzerland

    Science.gov (United States)

    Panziera, Luca; Gabella, Marco; Zanini, Stefano; Hering, Alessandro; Germann, Urs; Berne, Alexis

    2016-06-01

    This paper presents a regional extreme rainfall analysis based on 10 years of radar data for the 159 regions adopted for official natural hazard warnings in Switzerland. Moreover, a nowcasting tool aimed at issuing heavy precipitation regional alerts is introduced. The two topics are closely related, since the extreme rainfall analysis provides the thresholds used by the nowcasting system for the alerts. Warm and cold seasons' monthly maxima of several statistical quantities describing regional rainfall are fitted to a generalized extreme value distribution in order to derive the precipitation amounts corresponding to sub-annual return periods for durations of 1, 3, 6, 12, 24 and 48 h. It is shown that regional return levels exhibit a large spatial variability in Switzerland, and that their spatial distribution strongly depends on the duration of the aggregation period: for accumulations of 3 h and shorter, the largest return levels are found over the northerly alpine slopes, whereas for longer durations the southern Alps exhibit the largest values. The inner alpine chain shows the lowest values, in agreement with previous rainfall climatologies. The nowcasting system presented here is aimed to issue heavy rainfall alerts for a large variety of end users, who are interested in different precipitation characteristics and regions, such as, for example, small urban areas, remote alpine catchments or administrative districts. The alerts are issued not only if the rainfall measured in the immediate past or forecast in the near future exceeds some predefined thresholds but also as soon as the sum of past and forecast precipitation is larger than threshold values. This precipitation total, in fact, has primary importance in applications for which antecedent rainfall is as important as predicted one, such as urban floods early warning systems. The rainfall fields, the statistical quantity representing regional rainfall and the frequency of alerts issued in case of

  15. Recurring features of extreme rainfall events close to Veneto coast during autumn

    Science.gov (United States)

    Monai, M.; Barbi, A.; Racca, R.

    2010-09-01

    Climate of Veneto (north-east Italy) is characterized by significant differences between specific areas: mountains, plane, coast, etc. Such differences are particulary strong as far as precipitation is concerned. Mean annual rainfall on the coast is approximately 700-1000mm, whereas quantities more than double are measured on Prealps, only 100 km apart. Such differences are mainly related to crucial role of reliefs and with their interaction with southerly warm and humid fluxis coming from the Mediterranean Sea. A more detailed analyses of rainfall distribution highlights some interesting features, associated with a more localized role of the Adriatic Sea. Among others, it is noticeable that coastal area of Veneto is well subject to extreme events even if, as already mentioned, total annual amount of rain is the lowest in the region. Referring to the coast of Veneto, present work deals with: a) Climate study including seasonal and monthly distributions of precipitation; b) Contribution of extreme events to annual total; c) Analyses of recent extreme events happened in September during last four years. In fact for that area of Veneto, September is the most rainy month. Furthermore during September maximum of daily rainfall values were recorded (period of analyses 1993-2009); in particular, during the last four months of September, from 2006 to 2009, every year an extreme event occurred. Final goal was to understand main factors that caused such particular episodes in the same period of the year. Referring to four recent events happened during last four months of September, a detailed analyses was carried out including: - synoptic analyses both at surface than aloft; - study on mesoscale information derived from ground dense network, weather radar, etc. All events evidenced some common features: - deep thought aloft between North Atlantic Ocean and Central Mediterranean, with possible formation of low-level cyclone on Gulf of Genoa; - low-level advection of moist and

  16. Evolution of the rainfall regime in the United Arab Emirates

    Science.gov (United States)

    Ouarda, T. B. M. J.; Charron, C.; Niranjan Kumar, K.; Marpu, P. R.; Ghedira, H.; Molini, A.; Khayal, I.

    2014-06-01

    Arid and semiarid climates occupy more than 1/4 of the land surface of our planet, and are characterized by a strongly intermittent hydrologic regime, posing a major threat to the development of these regions. Despite this fact, a limited number of studies have focused on the climatic dynamics of precipitation in desert environments, assuming the rainfall input - and their temporal trends - as marginal compared with the evaporative component. Rainfall series at four meteorological stations in the United Arab Emirates (UAE) were analyzed for assessment of trends and detection of change points. The considered variables were total annual, seasonal and monthly rainfall; annual, seasonal and monthly maximum rainfall; and the number of rainy days per year, season and month. For the assessment of the significance of trends, the modified Mann-Kendall test and Theil-Sen’s test were applied. Results show that most annual series present decreasing trends, although not statistically significant at the 5% level. The analysis of monthly time series reveals strong decreasing trends mainly occurring in February and March. Many trends for these months are statistically significant at the 10% level and some trends are significant at the 5% level. These two months account for most of the total annual rainfall in the UAE. To investigate the presence of sudden changes in rainfall time-series, the cumulative sum method and a Bayesian multiple change point detection procedure were applied to annual rainfall series. Results indicate that a change point happened around 1999 at all stations. Analyses were performed to evaluate the evolution of characteristics before and after 1999. Student’s t-test and Levene’s test were applied to determine if a change in the mean and/or in the variance occurred at the change point. Results show that a decreasing shift in the mean has occurred in the total annual rainfall and the number of rainy days at all four stations, and that the variance has

  17. Downscaled TRMM Rainfall Time-Series for Catchment Hydrology Applications

    Science.gov (United States)

    Tarnavsky, E.; Mulligan, M.

    2009-04-01

    Hydrology in semi-arid regions is controlled, to a large extent, by the spatial and temporal distribution of rainfall defined in terms of rainfall depth and intensity. Thus, appropriate representation of the space-time variability of rainfall is essential for catchment-scale hydrological models applied in semi-arid regions. While spaceborne platforms equipped with remote sensing instruments provide information on a range of variables for hydrological modelling, including rainfall, the necessary spatial and temporal detail is rarely obtained from a single dataset. This paper presents a new dynamic model of dryland hydrology, DryMOD, which makes best use of free, public-domain remote sensing data for representation of key variables with a particular focus on (a) simulation of spatial rainfall fields and (b) the hydrological response to rainfall, particularly in terms of rainfall-runoff partitioning. In DryMOD, rainfall is simulated using a novel approach combining 1-km spatial detail from a climatology derived from the TRMM 2B31 dataset (mean monthly rainfall) and 3-hourly temporal detail from time-series derived from the 0.25-degree gridded TRMM 3B42 dataset (rainfall intensity). This allows for rainfall simulation at the hourly time step, as well as accumulation of infiltration, recharge, and runoff at the monthly time step. In combination with temperature, topography, and soil data, rainfall-runoff and soil moisture dynamics are simulated over large dryland regions. In order to investigate the hydrological response to rainfall and variable catchment characteristics, the model is applied to two very different catchments in the drylands of North and West Africa. The results of the study demonstrate the use of remote sensing-based estimates of precipitation intensity and volume for the simulation of critical hydrological parameters. The model allows for better spatial planning of water harvesting activities, as well as for optimisation of agricultural activities

  18. Sensitivity of point scale runoff predictions to rainfall resolution

    Directory of Open Access Journals (Sweden)

    A. J. Hearman

    2006-11-01

    Full Text Available This paper investigates the effects of using non-linear, high resolution rainfall, compared to time averaged rainfall on the triggering of hydrologic thresholds and therefore model predictions of infiltration excess and saturation excess runoff. The bounded random cascade model, parameterized to south western Australian rainfall, was used to scale rainfall intensities at various time resolutions ranging from 1.875 min to 2 h. A one dimensional, conceptual rainfall partitioning model was used that instantaneously partitions water into infiltration excess, infiltration, storage, deep drainage, saturation excess and surface runoff, where the fluxes into and out of the soil store are controlled by thresholds. For example, saturation excess is triggered when the soil water content reaches the storage capacity threshold. The results of the numerical modelling were scaled by relating soil infiltration properties to soil draining properties, and inturn, relating these to average storm intensities. By relating maximum soil infiltration capacities to saturated drainage rates (f*, we were able to split soils into two groups; those where all runoff is a result of infiltration excess alone (f*≤0.2 and those susceptible to both infiltration excess and saturation excess runoff (f*>0.2. For all soil types, we related maximum infiltration capacities to average storm intensities (k* and were able to show where model predictions of infiltration excess were most sensitive to rainfall resolution (ln k=0.4 and where using time averaged rainfall data can lead to an under prediction of infiltration excess and an over prediction of the amount of water entering the soil (ln k*>2. For soils susceptible to both infiltration excess and saturation excess, total runoff sensitivity was scaled by relating saturated drainage rates to average storm intensities (g* and parameter ranges where predicted runoff was dominated by

  19. Cyclical components of local rainfall data

    Science.gov (United States)

    Mentz, R. P.; D'Urso, M. A.; Jarma, N. M.; Mentz, G. B.

    2000-02-01

    This paper reports on the use of a comparatively simple statistical methodology to study local short time series rainfall data. The objective is to help in agricultural planning, by diminishing the risks associated with some uncertainties affecting this business activity.The analysis starts by assuming a model of unobservable components, trend, cycle, seasonal and irregular, that is well known in many areas of application. When series are in the realm of business and economics, the statistical methods popularized by the US Census Bureau US National Bureau of Economic Research are used for seasonal and cyclical estimation, respectively. The flexibility of these methods makes them good candidates to be applied in the meteorological context, and this is done in this paper for a selection of monthly rainfall time series.Use of the results to help in analysing and forecasting cyclical components is emphasized. The results are interesting. An agricultural entrepreneur, or a group of them located in a single geographical region, will profit by systematically collecting information (monthly in our work) about rainfall, and adopting the scheme of analysis described in this paper.

  20. Evaluation of short-period rainfall estimates from Kalpana-1 satellite using MET software

    Indian Academy of Sciences (India)

    Soma Sen Roy; Subhendu Brata Saha; Hashmi Fatima; S K Roy Bhowmik; P K Kundu

    2012-10-01

    The INSAT Multispectral Rainfall Algorithm (IMSRA) technique for rainfall estimation, has recently been developed to meet the shortcomings of the Global Precipitation Index (GPI) technique of rainfall estimation from the data of geostationary satellites; especially for accurate short period rainfall estimates. This study evaluates the 3-hourly precipitation estimates by this technique as well as the rainfall estimates by the GPI technique using data of the Kalpana-1 satellite, over the Indian region for the south-west monsoon season of 2010 to understand their relative strengths and weaknesses in estimating short period rainfall. The gridded 3 hourly accumulated TRMM satellite (3B42 V6 product or TMPA product) and surface raingauge data for stations over the Indian region for the same period is used as the standard measure of rainfall estimates. The Method for Object-based Diagnostic Evaluation (MODE) utility of the METv3.0 software, has been used for the evaluation purpose. The results show that the new IMSRA technique is closer to the TMPA rainfall estimate, in terms of areal spread, geometric shape and location of rainfall areas, as compared to the GPI technique. The overlap of matching rainfall areas with respect to TMPA rainfall patches is also higher for the IMSRA estimates as compared to the GPI values. However, both satellite rainfall estimates are observed to be generally higher compared to the TMPA measurements. However, the values for the highest 10% of the rainfall rates in any rainfall patch, is generally higher for rainfall measured by the IMSRA technique, as compared to the estimates by the GPI technique. This may partly be due to the capping maximum limit of 3 mm/hr for rainfall measured by the GPI technique limits the total 3-hour accumulation to 9 mm even during heavy rainfall episodes. This is not so with IMSRA technique, which has no such limiting value. However, this general overestimation of the rainfall amount, measured by both techniques

  1. Mixed forest plantations can efficiently filter rainfall deposits of sulfur and chlorine in Western China

    Science.gov (United States)

    Zhao, Hairong; Yang, Wanqin; Wu, Fuzhong; Tan, Bo

    2017-01-01

    Forest filtering is a well-known and efficient method for diminishing atmospheric pollutant (such as SO42‑ and Cl‑) inputs to soil and water; however, the filtering efficiencies of forests vary depending on the regional vegetation and climate. The rainy area of West China has suffered from heavy rainfall and human activity, which has potentially resulted in large amounts of sulfur and chlorine deposition, but little information is available regarding the filtering effects of typical plantations. Therefore, the migration of SO42‑ and Cl‑ from rainfall to throughfall, stemflow and runoff were investigated in a camphor (Cinnamomum camphora) plantation, a cryptomeria (Cryptomeria fortunei) plantation and a mixed plantation in a 9-month forest hydrology experiment. The results indicated the following: (i) The total SO42‑ and Cl‑ deposition was 43.05 kg ha‑1 and 5.25 kg ha‑1, respectively. (ii) The cover layer had the highest interception rate (60.08%), followed by the soil layer (16.02%) and canopy layer (12.85%). (iii) The mixed plantation resulted in the highest SO42‑ (37.23%) and Cl‑ (51.91%) interception rates at the forest ecosystem scale, and the interception rate increased with increasing rainfall. These results indicate that mixed plantations can effectively filter SO42‑ and Cl‑ in this area and in similar areas.

  2. Linear and Non-Linear Approaches for Statistical Seasonal Rainfall Forecast in the Sirba Watershed Region (SAHEL

    Directory of Open Access Journals (Sweden)

    Abdouramane Gado Djibo

    2015-09-01

    Full Text Available Since the 90s, several studies were conducted to evaluate the predictability of the Sahelian rainy season and propose seasonal rainfall forecasts to help stakeholders to take the adequate decisions to adapt with the predicted situation. Unfortunately, two decades later, the forecasting skills remains low and forecasts have a limited value for decision making while the population is still suffering from rainfall interannual variability: this shows the limit of commonly used predictors and forecast approaches for this region. Thus, this paper developed and tested new predictors and new approaches to predict the upcoming seasonal rainfall amount over the Sirba watershed. Predictors selected through a linear correlation analysis were further processed using combined linear methods to identify those having high predictive power. Seasonal rainfall was forecasted using a set of linear and non-linear models. An average lag time up to eight months was obtained for all models. It is found that the combined linear methods performed better than non-linear, possibly because non-linear models require larger and better datasets for calibration. The R2, Nash and Hit rate score are respectively 0.53, 0.52, and 68% for the combined linear approach; and 0.46, 0.45, 61% for non-linear principal component analysis.

  3. Interannual variability of rainfall characteristics over southwestern Madagascar

    Science.gov (United States)

    Randriamahefasoa, T. S. M.; Reason, C. J. C.

    2017-04-01

    The interannual variability of daily frequency of rainfall [>1 mm/day] and heavy rainfall [>30 mm/day] is studied for the southwestern region of Madagascar, which is relatively arid compared to the rest of the island. Attention is focused on the summer rainy season from December to March at four stations (Morondava, Ranohira, Toliara and Taolagnaro), whose daily rainfall data covering the period 1970-2000 were obtained from the Madagascar Meteorological Service. El Niño Southern Oscillation (ENSO) was found to have a relatively strong correlation with wet day frequency at each station and, particularly, for Toliara in the extreme southwest. In terms of seasonal rainfall totals, most El Niño (La Niña) summers receive below (above) average amounts. An ENSO connection with heavy rainfall events was less clear. However, for heavy rainfall events, the associated atmospheric circulation displays a Southern Annular Mode-like pattern throughout the hemisphere. For ENSO years and the neutral seasons 1979/80, 1981/82 which had large anomalies in wet day frequency, regional atmospheric circulation patterns consisted of strong anomalies in low-level moisture convergence and uplift over and near southwestern Madagascar that made conditions correspondingly more or less favourable for rainfall. Dry (wet) summers in southern Madagascar were also associated with an equatorward (poleward) displacement of the ITCZ in the region.

  4. Elucidating the role of topological pattern discovery and support vector machine in generating predictive models for Indian summer monsoon rainfall

    Science.gov (United States)

    Chattopadhyay, Manojit; Chattopadhyay, Surajit

    2016-10-01

    The present paper reports a study, where growing hierarchical self-organising map (GHSOM) has been applied to achieve a visual cluster analysis to the Indian rainfall dataset consisting of 142 years of Indian rainfall data so that the yearly rainfall can be segregated into small groups to visualise the pattern of clustering behaviour of yearly rainfall due to changes in monthly rainfall for each year. Also, through support vector machine (SVM), it has been observed that generation of clusters impacts positively on the prediction of the Indian summer monsoon rainfall. Results have been presented through statistical and graphical analyses.

  5. Influence of satellite-derived rainfall patterns on plague occurrence in northeast Tanzania.

    Science.gov (United States)

    Debien, Annekatrien; Neerinckx, Simon; Kimaro, Didas; Gulinck, Hubert

    2010-12-13

    In the tropics, rainfall data are seldom accurately recorded, and are often discontinuous in time. In the scope of plague-research in northeast Tanzania, we adapted previous research to reconstruct rainfall patterns at a suitable resolution (1 km), based on time series of NDVI: more accurate satellite imagery was used, in the form of MODIS NDVI, and rainfall data were collected from the TRMM sensors instead of in situ data. First, we established a significant relationship between monthly rainfall and monthly composited MODIS NDVI. The established linear relationship was then used to reconstruct historic precipitation patterns over a mountainous area in northeastern Tanzania. We validated the resulting precipitation estimates with in situ rainfall time series of three meteorological stations located in the study area. Taking the region's topography into account, a correlation coefficient of 0.66 was obtained for two of the three meteorological stations. Our results suggest that the adapted strategy can be applied fruitfully to estimate rainfall variability and seasonality, despite the underestimation of overall rainfall rates. Based on this model, rainfall in previous years (1986) is modelled to obtain a dataset with which we can compare plague occurrence in the area. A positive correlation of 82% is obtained between high rainfall rates and plague incidence with a two month lag between rainfall and plague cases. We conclude that the obtained results are satisfactory in support of the human plague research in which this study is embedded, and that this approach can be applied in other studies with similar goals.

  6. Study on Measurement of Effects of Rainfall Interception by Forest Crown%森林林冠截留效益计量的研究

    Institute of Scientific and Technical Information of China (English)

    欧阳惠

    2001-01-01

    The rainfall interception by forest crowns in 19 forest stands was studied.The corresponding model of rainfall interception by forest crowns and related parameters,as well as each stem-flow model of stands were also established.The amounts of rainfall intercepted by forest crowns of different stands were compared.The formulas to measure effects of rainfall interception by forest crowns for day, month and year were deduced.Methods of measuring effects of rainfall interception by forest crowns using GIS were introduced.%研究了19种林分林冠截留率,得出了相应林冠截留模型和有关参量以及这些林分的树干茎流模型;比较了各种林分林冠截留能力,据此推算出林分林冠截留效益计量模型和日、月、年林分林冠截留效益计量公式,介绍了如何利用地形图、GIS进行流域林冠截留效益计量,并提出了“3S”技术将会为动态进行森林效益计量和监测发挥作用。

  7. Approximation of Rainfall Erosivity Factors in North Jordan

    Institute of Scientific and Technical Information of China (English)

    N.I.ELTAIF; M.A.GHARAIBEH; F.AL-ZAITAWI; M.N.ALHAMAD

    2010-01-01

    Despite being in arid and semi-arid areas, erosion is largely a result of infrequent but heavy rainfall events; therefore,rainfall erosivity data can be used as an indicator of potential erosion risks. The purpose of this study was to investigate the spatial distribution of annual rainfall erosivity in North Jordan. A simplified procedure was used to correlate erosivity factor R values in both the universal soil loss equation (USLE) and the revised universal soil loss equation (RUSLE) with annual rainfall amount or modified Fournier index (Fmod). Pluviometric data recorded at 18 weather stations covering North Jordan were used to predict R values. The annual values of erosivity ranged between 86-779 MJ mm ha-1 h-1 year-1. The northwest regions of Jordan showed the highest annual erosivity values, while the northeastern regions showed the lowest annual erosivity values.

  8. Influence of Northwest Cloudbands on Southwest Australian Rainfall

    Directory of Open Access Journals (Sweden)

    Nicola Telcik

    2014-01-01

    Full Text Available Northwest cloudbands are tropical-extratropical feature that crosses the Australian continent originating from Australia’s northwest coast and develops in a NW-SE orientation. In paper, atmospheric and oceanic reanalysis data (NCEP and Reynolds reconstructed sea surface temperature data were used to examine northwest cloudband activity across the Australian mainland. An index that reflected the monthly, seasonal, and interannual activity of northwest cloudbands between 1950 and 1999 was then created. Outgoing longwave radiation, total cloud cover, and latent heat flux data were used to determine the number of days when a mature northwest cloudband covered part of the Australian continent between April and October. Regional indices were created for site-specific investigations, especially of cloudband-related rainfall. High and low cloudband activity can affect the distribution of cloudbands and their related rainfall. In low cloudband activity seasons, cloudbands were mostly limited to the south and west Australian coasts. In high cloudband activity seasons, cloudbands penetrated farther inland, which increased the inland rainfall. A case study of the southwest Australian region demonstrated that, in a below average rainfall year, cloudband-related rainfall was limited to the coast. In an above average rainfall year, cloudband-related rainfall occurred further inland.

  9. Estimation of Real-Time Flood Risk on Roads Based on Rainfall Calculated by the Revised Method of Missing Rainfall

    Directory of Open Access Journals (Sweden)

    Eunmi Kim

    2014-09-01

    Full Text Available Recently, flood damage by frequent localized downpours in cities is on the increase on account of abnormal climate phenomena and the growth of impermeable areas due to urbanization. This study suggests a method to estimate real-time flood risk on roads for drivers based on the accumulated rainfall. The amount of rainfall of a road link, which is an intensive type, is calculated by using the revised method of missing rainfall in meteorology, because the rainfall is not measured on roads directly. To process in real time with a computer, we use the inverse distance weighting (IDW method, which is a suitable method in the computing system and is commonly used in relation to precipitation due to its simplicity. With real-time accumulated rainfall, the flooding history, rainfall range causing flooding from previous rainfall information and frequency probability of precipitation are used to determine the flood risk on roads. The result of simulation using the suggested algorithms shows the high concordance rate between actual flooded areas in the past and flooded areas derived from the simulation for the research region in Busan, Korea.

  10. Application of artificial neural networks to rainfall forecasting in Queensland, Australia

    Science.gov (United States)

    Abbot, John; Marohasy, Jennifer

    2012-07-01

    In this study, the application of artificial intelligence to monthly and seasonal rainfall forecasting in Queensland, Australia, was assessed by inputting recognized climate indices, monthly historical rainfall data, and atmospheric temperatures into a prototype stand-alone, dynamic, recurrent, time-delay, artificial neural network. Outputs, as monthly rainfall forecasts 3 months in advance for the period 1993 to 2009, were compared with observed rainfall data using time-series plots, root mean squared error (RMSE), and Pearson correlation coefficients. A comparison of RMSE values with forecasts generated by the Australian Bureau of Meteorology's Predictive Ocean Atmosphere Model for Australia (POAMA)-1.5 general circulation model (GCM) indicated that the prototype achieved a lower RMSE for 16 of the 17 sites compared. The application of artificial neural networks to rainfall forecasting was reviewed. The prototype design is considered preliminary, with potential for significant improvement such as inclusion of output from GCMs and experimentation with other input attributes.

  11. Deterministic Approach for Estimating Critical Rainfall Threshold of Rainfall-induced Landslide in Taiwan

    Science.gov (United States)

    Chung, Ming-Chien; Tan, Chih-Hao; Chen, Mien-Min; Su, Tai-Wei

    2013-04-01

    , the critical rainfall threshold of the slope can be obtained by the coupled analysis of rainfall, infiltration, seepage, and slope stability. Taking the slope located at 50k+650 on Tainan county road No 174 as an example, it located at Zeng-Wun river watershed in the southern Taiwan, is an active landslide due to typhoon events. Coordinates for the case study site are 194925, 2567208 (TWD97). The site was selected as the results of previous reports and geological survey. According to the Central Weather Bureau, the annual precipitation is about 2,450 mm, the highest monthly value is in August with 630 mm, and the lowest value is in November with 13 mm. The results show that the critical rainfall threshold of the study case is around 640 mm. It means that there should be alarmed when the accumulated rainfall over 640 mm. Our preliminary results appear to be useful for rainfall-induced landslide hazard assessments. The findings are also a good reference to establish an early warning system of landslides and develop strategies to prevent so much misfortune from happening in the future.

  12. Monthly errors

    Data.gov (United States)

    U.S. Environmental Protection Agency — The 2006 monthly average statistical metrics for 2m Q (g kg-1) domain-wide for the base and MODIS WRF simulations against MADIS observations. This dataset is...

  13. Analysis of rainfall seasonality from observations and climate models

    CERN Document Server

    Pascale, Salvatore; Feng, Xue; Porporato, Amilcare; Hasson, Shabeh-ul

    2014-01-01

    Precipitation seasonality of observational datasets and CMIP5 historical simulations are analyzed using novel quantitative measures based on information theory. Two new indicators, the relative entropy (RE) and the dimensionless seasonality index (DSI), together with the mean annual rainfall, are evaluated on a global scale for recently updated precipitation gridded datasets and for historical simulations from coupled atmosphere-ocean general circulation models. The RE provides a measure of how peaked the shape of the annual rainfall curve is whereas the DSI quantifies the intensity of the rainfall during the wet season. The global monsoon regions feature the largest values of the DSI. For precipitation regimes featuring one maximum in the monthly rain distribution the RE is related to the duration of the wet season. We show that the RE and the DSI are measures of rainfall seasonality fairly independent of the time resolution of the precipitation data, thereby allowing objective metrics for model intercompari...

  14. Quantitative mapping of rainfall rates over the oceans utilizing Nimbus-5 ESMR data

    Science.gov (United States)

    Rao, M. S. V.; Abbott, W. V.

    1976-01-01

    The electrically scanning microwave radiometer (ESMR) data from the Nimbus 5 satellite was used to deduce estimates of precipitation amount over the oceans. An atlas of the global oceanic rainfall was prepared and the global rainfall maps analyzed and related to available ground truth information as well as to large scale processes in the atmosphere. It was concluded that the ESMR system provides the most reliable and direct approach yet known for the estimation of rainfall over sparsely documented, wide oceanic regions.

  15. Spatial dependence of extreme rainfall

    Science.gov (United States)

    Radi, Noor Fadhilah Ahmad; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Azman, Muhammad Az-zuhri

    2017-05-01

    This study aims to model the spatial extreme daily rainfall process using the max-stable model. The max-stable model is used to capture the dependence structure of spatial properties of extreme rainfall. Three models from max-stable are considered namely Smith, Schlather and Brown-Resnick models. The methods are applied on 12 selected rainfall stations in Kelantan, Malaysia. Most of the extreme rainfall data occur during wet season from October to December of 1971 to 2012. This period is chosen to assure the available data is enough to satisfy the assumption of stationarity. The dependence parameters including the range and smoothness, are estimated using composite likelihood approach. Then, the bootstrap approach is applied to generate synthetic extreme rainfall data for all models using the estimated dependence parameters. The goodness of fit between the observed extreme rainfall and the synthetic data is assessed using the composite likelihood information criterion (CLIC). Results show that Schlather model is the best followed by Brown-Resnick and Smith models based on the smallest CLIC's value. Thus, the max-stable model is suitable to be used to model extreme rainfall in Kelantan. The study on spatial dependence in extreme rainfall modelling is important to reduce the uncertainties of the point estimates for the tail index. If the spatial dependency is estimated individually, the uncertainties will be large. Furthermore, in the case of joint return level is of interest, taking into accounts the spatial dependence properties will improve the estimation process.

  16. Can SAPHIR Instrument Onboard MEGHATROPIQUES Retrieve Hydrometeors and Rainfall Characteristics ?

    Science.gov (United States)

    Goyal, J. M.; Srinivasan, J.; Satheesh, S. K.

    2014-12-01

    MEGHATROPIQUES (MT) is an Indo-French satellite launched in 2011 with the main intention of understanding the water cycle in the tropical region and is a part of GPM constellation. MADRAS was the primary instrument on-board MT to estimate rainfall characteristics, but unfortunately it's scanning mechanism failed obscuring the primary goal of the mission.So an attempt has been made to retrieve rainfall and different hydrometeors using other instrument SAPHIR onboard MT. The most important advantage of using MT is its orbitography which is specifically designed for tropical regions and can reach up to 6 passes per day more than any other satellite currently in orbit. Although SAPHIR is an humidity sounder with six channels centred around 183 GHz channel, it still operates in the microwave region which directly interacts with rainfall, especially wing channels and thus can pick up rainfall signatures. Initial analysis using radiative transfer models also establish this fact .To get more conclusive results using observations, SAPHIR level 1 brightness temperature (BT) data was compared with different rainfall products utilizing the benefits of each product. SAPHIR BT comparison with TRMM 3B42 for one pass clearly showed that channel 5 and 6 have a considerable sensitivity towards rainfall. Following this a huge database of more than 300000 raining pixels of spatially and temporally collocated 3B42 rainfall and corresponding SAPHIR BT for an entire month was created to include all kinds of rainfall events, to attain higher temporal resolution collocated database was also created for SAPHIR BT and rainfall from infrared sensor on geostationary satellite Kalpana 1.These databases were used to understand response of various channels of SAPHIR to different rainfall regimes . TRMM 2A12 rainfall product was also used to identify capabilities of SAPHIR to retrieve cloud and ice water path which also gave significant correlation. Conclusively,we have shown that SAPHIR has

  17. Mathematical model of sediment and solute transport along slope land in different rainfall pattern conditions

    Science.gov (United States)

    Tao, Wanghai; Wu, Junhu; Wang, Quanjiu

    2017-03-01

    Rainfall erosion is a major cause of inducing soil degradation, and rainfall patterns have a significant influence on the process of sediment yield and nutrient loss. The mathematical models developed in this study were used to simulate the sediment and nutrient loss in surface runoff. Four rainfall patterns, each with a different rainfall intensity variation, were applied during the simulated rainfall experiments. These patterns were designated as: uniform-type, increasing-type, increasing- decreasing -type and decreasing-type. The results revealed that changes in the rainfall intensity can have an appreciable impact on the process of runoff generation, but only a slight effect on the total amount of runoff generated. Variations in the rainfall intensity in a rainfall event not only had a significant effect on the process of sediment yield and nutrient loss, but also the total amount of sediment and nutrient produced, and early high rainfall intensity may lead to the most severe erosion and nutrient loss. In this study, the calculated data concur with the measured values. The model can be used to predict the process of surface runoff, sediment transport and nutrient loss associated with different rainfall patterns.

  18. Investigation of Rainfall-Runoff Processes and Soil Moisture Dynamics in Grassland Plots under Simulated Rainfall Conditions

    Directory of Open Access Journals (Sweden)

    Nana Zhao

    2014-09-01

    Full Text Available The characteristics of rainfall-runoff are important aspects of hydrological processes. In this study, rainfall-runoff processes and soil moisture dynamics at different soil depths and slope positions of grassland with two different row spacings (5 cm and 10 cm, respectively, referred to as R5 and R10 were analyzed, by means of a solution of rainfall simulation experiments. Bare land was also considered as a comparison. The results showed that the mechanism of runoff generation was mainly excess infiltration overland flow. The surface runoff amount of R5 plot was greater than that of R10, while the interflow amount of R10 was larger than that of R5 plot, although the differences of the subsurface runoff processes between plots R5 and R10 were little. The effects of rainfall intensity on the surface runoff were significant, but not obvious on the interflow and recession curve, which can be described as a simple exponential equation, with a fitting degree of up to 0.854–0.996. The response of soil moisture to rainfall and evapotranspiration was mainly in the 0–20 cm layer, and the response at the 40 cm layer to rainfall was slower and generally occurred after the rainfall stopped. The upper slope generally responded fastest to rainfall, and the foot of the slope was the slowest. The results presented here could provide insights into understanding the surface and subsurface runoff processes and soil moisture dynamics for grasslands in semi-arid regions.

  19. Spatial and temporal variability of rainfall in the Nile Basin

    Directory of Open Access Journals (Sweden)

    C. Onyutha

    2014-10-01

    Full Text Available Spatio-temporal variability in annual and seasonal rainfall totals were assessed at 37 locations of the Nile Basin in Africa using quantile perturbation method. To get insight into the spatial difference in rainfall statistics, the stations were grouped based on the pattern of the long-term mean of monthly rainfall and that of temporal variability. To find the origin of the driving forces for the temporal variability in rainfall, correlation analyses were carried out using global monthly sea level pressure and surface temperature. Further investigations to support the obtained correlations were made using a total of 10 climate indices. It was possible to obtain 3 groups of stations; those within the equatorial region (A, Sudan and Ethiopia (B, and Egypt (C. For group A, annual rainfall was found to be below (above the reference during the late 1940s to 1950s (1960s to mid 1980s. Conversely for groups B and C, the period 1930s to late 1950s (1960s to 1980s was characterized by anomalies being above (below the reference. For group A, significant linkages were found to Niño 3, Niño 3.4 and the North Atlantic and Indian Ocean drivers. Correlations of annual rainfall of group A with Pacific Ocean-related climate indices were inconclusive. With respect to the main wet seasons, the June to September rainfall of group B has strong connection to the influence from the Indian Ocean. For the March to May (October to February rainfall of group A (C, possible links to the Atlantic and Indian Oceans were found.

  20. Rainfall regimes of the Green Sahara.

    Science.gov (United States)

    Tierney, Jessica E; Pausata, Francesco S R; deMenocal, Peter B

    2017-01-01

    During the "Green Sahara" period (11,000 to 5000 years before the present), the Sahara desert received high amounts of rainfall, supporting diverse vegetation, permanent lakes, and human populations. Our knowledge of rainfall rates and the spatiotemporal extent of wet conditions has suffered from a lack of continuous sedimentary records. We present a quantitative reconstruction of western Saharan precipitation derived from leaf wax isotopes in marine sediments. Our data indicate that the Green Sahara extended to 31°N and likely ended abruptly. We find evidence for a prolonged "pause" in Green Sahara conditions 8000 years ago, coincident with a temporary abandonment of occupational sites by Neolithic humans. The rainfall rates inferred from our data are best explained by strong vegetation and dust feedbacks; without these mechanisms, climate models systematically fail to reproduce the Green Sahara. This study suggests that accurate simulations of future climate change in the Sahara and Sahel will require improvements in our ability to simulate vegetation and dust feedbacks.

  1. Rainfall regimes of the Green Sahara

    Science.gov (United States)

    Tierney, Jessica E.; Pausata, Francesco S. R.; deMenocal, Peter B.

    2017-01-01

    During the “Green Sahara” period (11,000 to 5000 years before the present), the Sahara desert received high amounts of rainfall, supporting diverse vegetation, permanent lakes, and human populations. Our knowledge of rainfall rates and the spatiotemporal extent of wet conditions has suffered from a lack of continuous sedimentary records. We present a quantitative reconstruction of western Saharan precipitation derived from leaf wax isotopes in marine sediments. Our data indicate that the Green Sahara extended to 31°N and likely ended abruptly. We find evidence for a prolonged “pause” in Green Sahara conditions 8000 years ago, coincident with a temporary abandonment of occupational sites by Neolithic humans. The rainfall rates inferred from our data are best explained by strong vegetation and dust feedbacks; without these mechanisms, climate models systematically fail to reproduce the Green Sahara. This study suggests that accurate simulations of future climate change in the Sahara and Sahel will require improvements in our ability to simulate vegetation and dust feedbacks. PMID:28116352

  2. Rainfall erosivity in the Fukushima Prefecture: implications for radiocesium mobilization and migration

    Science.gov (United States)

    Laceby, J. Patrick; Chartin, Caroline; Degan, Francesca; Onda, Yuichi; Evrard, Olivier; Cerdan, Olivier; Ayrault, Sophie

    2015-04-01

    The Fukushima Dai-ichi nuclear power plant (FDNPP) accident in March 2011 led to the fallout of predominantly radiocesium (137Cs and 134Cs) on soils of the Fukushima Prefecture. This radiocesium was primarily fixated to fine soil particles. Subsequently, rainfall and snow melt run-off events result in significant quantities of radiocesium being eroded and transported throughout the coastal catchments and ultimately exported to the Pacific Ocean. Erosion models, such as the Universal Soil Loss Equation (USLE), relate rainfall directly to soil erosion in that an increase in rainfall one month will directly result in a proportional increase in sediment generation. Understanding the rainfall regime of the region is therefore fundamental to modelling and predicting long-term radiocesium export. Here, we analyze rainfall data for ~40 stations within a 100 km radius of the FDNPP. First we present general information on the rainfall regime in the region based on monthly and annual rainfall totals. Second we present general information on rainfall erosivity, the R-factor of the USLE equation and its relationship to the general rainfall data. Third we examine rainfall trends over the last 100 years at several of the rainfall stations to understand temporal trends and whether ~20 years of data is sufficient to calculate the R-factor for USLE models. Fourth we present monthly R-factor maps for the Fukushima coastal catchments impacted by the FDNPP accident. The variability of the rainfall in the region, particularly during the typhoon season, is likely resulting in a similar variability in the transfer and migration of radiocesium throughout the coastal catchments of the Fukushima Prefecture. Characterizing the region's rainfall variability is fundamental to modelling sediment and the concomitant radiocesium migration and transfer throughout these catchments and ultimately to the Pacific Ocean.

  3. On the sensitivity of Tropical Rainfall Measuring Mission (TRMM) Microwave Imager channels to overland rainfall

    Science.gov (United States)

    You, Yalei; Liu, Guosheng; Wang, Yu; Cao, Jie

    2011-06-01

    , and the V37 or V21 channel becomes the top responder to surface rain as the amount of hydrometeors in the atmospheric column reaches very high values. Additionally, it is found that land surface type and 2 m air temperature have significant skills in characterizing rain cloud types, so that the V19-V37 channel is more sensitive to surface rainfall for more vegetated warm surface, while the V85 channel is more sensitive to cold bare land. This finding implies that the above two parameters may be used to prioritize satellite observations at different channels, so that the channel that has the best rainfall sensitivity under a given condition receives the highest weight in retrieval algorithms.

  4. A first-order assessment of climate change effects on rainfall erosivity and soil erosion in New South Wales, Australia

    Science.gov (United States)

    Yu, Bofu; Murphy, Brian; Vaze, Jai; Rawson, Andrew

    2010-05-01

    Rainfall has shown considerable secular variation and statistically significant change on the time scale of decades in New South Wales (NSW), Australia. The climate change predictions seem to suggest an increased rainfall intensity for the region. To assess the likely impact of climate change on rainfall erosivity for 13 sites in NSW, a daily rainfall erosivity model was used to compare rainfall erosivity values using historical rainfall data and adjusted rainfall data representing future climate scenarios. To use the rainfall erosivity model, 6-min rainfall intensity data from the 13 sites were used to calibrate the model. The historical rainfall data were available for the period of 112 years (1895 - 2006) for the 13 sites. Adjusted rainfall data for 112 years were provided based on output from Global Climate Models, namely CSIRO-MK3.0 (CSIRO, Australia), MIROC-M (Centre for Climate Research, Japan); MIUB (Meteorological Institute of the University of Bonn, Germany); MRI (Meteorological Research Institute, Japan). The rainfall erosivity model was run for each of the 13 sites, and mean annual, seasonal rainfall erosivity values were contrasted for the present and future climate scenarios. In addition, rainfall erosivity values were compared for average recurrence intervals of 2, 10, and 100 years so that changes to rainfall erosivity during extreme erosive events can be assessed. The results show rainfall erosivity would increase by about 4.6% on average, and the increase occurs mostly in summer (December-January-February). Output from all 4 models suggests that rainfall erosivity would decrease in winter months. Spatially, the change to rainfall erosivity is quite variable, with greater increase mostly occurring along the coast with a temperate climate. As mean annual soil loss is linearly proportional to rainfall erosion, impact on soil loss of a similar magnitude is therefore implied for the 13 sites in NSW.

  5. Rainfall spatiotemporal variability relation to wetlands hydroperiods

    Science.gov (United States)

    Serrano-Hidalgo, Carmen; Guardiola-Albert, Carolina; Fernandez-Naranjo, Nuria

    2017-04-01

    Doñana natural space (Southwestern Spain) is one of the largest protected wetlands in Europe. The wide marshes present in this natural space have such ecological value that this wetland has been declared a Ramsar reserve in 1982. Apart from the extensive marsh, there are also small lagoons and seasonally flooded areas which are likewise essential to maintain a wide variety of valuable habitats. Hydroperiod, the length of time each point remains flooded along an annual cycle, is a critical ecological parameter that shapes aquatic plants and animals distribution and determines available habitat for many of the living organisms in the marshes. Recently, there have been published two different works estimating the hydroperiod of Doñana lagoons with Landsat Time Series images (Cifuentes et al., 2015; Díaz-Delgado et al., 2016). In both works the flooding cycle hydroperiod in Doñana marshes reveals a flooding regime mainly driven by rainfall, evapotranspiration, topography and local hydrological management actions. The correlation found between rainfall and hydroperiod is studied differently in both works. While in one the rainfall is taken from one raingauge (Cifuentes et al., 2015), the one performed by Díaz-Delgado (2016) uses annual rainfall maps interpolated with the inverse of the distance method. The rainfall spatiotemporal variability in this area can be highly significant; however the amount of this importance has not been quantified at the moment. In the present work the geostatistical tool known as spatiotemporal variogram is used to study the rainfall spatiotemporal variability. The spacetime package implemented in R (Pebesma, 2012) facilities its computation from a high rainfall data base of more than 100 raingauges from 1950 to 2016. With the aid of these variograms the rainfall spatiotemporal variability is quantified. The principal aim of the present work is the study of the relation between the rainfall spatiotemporal variability and the

  6. Tropical stratospheric circulation and monsoon rainfall

    Science.gov (United States)

    Sikder, A. B.; Patwardhan, S. K.; Bhalme, H. N.

    1993-09-01

    Interannual variability of both SW monsoon (June September) and NE monsoon (October December) rainfall over subdivisions of Coastal Andhra Pradesh, Rayalaseema and Tamil Nadu have been examined in relation to monthly zonal wind anomaly for 10 hPa, 30 hPa and 50 hPa at Balboa (9°N, 80°W) for the 29 year period (1958 1986). Correlations of zonal wind anomalies to SW monsoon rainfall ( r=0.57, significant at 1% level) is highest with the longer lead time (August of the previous year) at 10 hPa level suggesting some predictive value for Coastal Andhra Pradesh. The probabilities estimated from the contingency table reveal non-occurrence of flood during easterly wind anomalies and near non-occurrence of drought during westerly anomalies for August of the previous year at 10 hPa which provides information for forecasting of performance of SW monsoon over Coastal Andhra Pradesh. However, NE monsoon has a weak relationship with zonal wind anomalies of 10 hPa, 30 hPa and 50 hPa for Coastal Andhra Pradesh, Rayalaseema and Tamil Nadu. Tracks of the SW monsoon storms and depressions in association with the stratospheric wind were also examined to couple with the fluctuations in SW monsoon rainfall. It is noted that easterly / westerly wind at 10 hPa, in some manner, suppresses / enhances monsoon storms and depressions activity affecting their tracks.

  7. Spatial analysis of rainfall trends in the region of Valencia (east Spain)

    Science.gov (United States)

    de Luís, M.; Raventós, J.; González-Hidalgo, J. C.; Sánchez, J. R.; Cortina, J.

    2000-10-01

    This paper examines the spatial and temporal rainfall characteristics of the region of Valencia, Western Mediterranean Basin (east Spain), during the World Meteorological Organization (WMO) normal period 1961-1990. The study used a dense and homogeneous daily precipitation database comprising 97 rain-gauge stations. Total and monthly rainfall concentrations have been studied in the context of their mean values, interannual variability and spatial diversification. Trends have been analysed using both parametric and non-parametric tests. In order to establish the spatial distribution of rainfall patterns and to detect homogeneous areas with similar rainfall evolution, a statistic based on the Cramér-von Mises test is proposed. The kriging interpolation methods for characterizing the magnitude of observed changes is used.Areas with contrasting rainfall evolution are identified. In more humid areas, a significant decrease in annual rainfall associated with significant increases in interannual rainfall variability is observed. In inland zones, decreases in total annual rainfall and increases in interannual variability are less clear, but there are indications of an increase in monthly rainfall concentration. In these inland zones, where more forest and woodland areas are located and forest fires are frequent, the observed trends could greatly affect desertification through changes in the disturbance regime. In more arid areas, local variability in rainfall evolution is higher and no significant changes can be defined.

  8. Application of Geographic Information Systems (GIS) in Analysing Rainfall Distribution Patterns in Batu Pahat District

    Science.gov (United States)

    Kadir, A. A.; Kaamin, M.; Azizan, N. S.; Sahat, S.; Bukari, S. M.; Mokhtar, M.; Ngadiman, N.; Hamid, N. B.

    2016-07-01

    Rainfall forecasting reports are crucial to provide information and warnings to the population in a particular location. The Malaysian Meteorology Department (MMD) is a department that plays an important role in monitoring the situation and issued the statement of changes in weather and provides services such as weather advisories and gives warnings when the situation requires. Uncertain weather situations normally have created panic situation, especially in big cities because of flash floods due to poor drainage management. Usually, local authorities provided rainfall data in tables, and it is difficult to analyse to acquire the rainfall trend. Therefore, Geographic Information System (GIS) applications are commonly used to generate rainfall patterns in visual formation with a combination of characteristics of rainfall data and then can be used by stakeholders to facilitate the process of analysis and forecasting rainfall. The objective of this study is to determine the pattern of rainfall distribution using GIS applications in Batu Pahat district to assist interested parties to understand and easy to analyse the rainfall data in visual form or mapping form. Rainfall data for a period of 10 years (2004-2013) and monthly data (Dec 2006 - Feb 2007) are provided by the Department of Irrigation and Drainage (DID) for 12 stations in the district of Batu Pahat, and rainfall maps in each year was obtained using the interpolation Inverse Distance Weighted (IDW) method was used in this research. The rainfall map was then analyzed to identify the highest rainfall that was received during the period of study. For the conclusion, this study has proved that rainfall analysis using GIS application is efficient to be used in gaining information of rainfall patterns as the results show that the highest rainfall occurred in 2006 and 2007, and it were the years of major floods occurrence in Batu Pahat district.

  9. Rainfall as proxy for evapotranspiration predictions

    Science.gov (United States)

    Collischonn, Bruno; Collischonn, Walter

    2016-10-01

    In this work, we evaluated the relationship between evapotranspiration and precipitation, based on the data recently made available by the Brazilian Meteorological Institute. ETP tend to be lower in rainy periods and vice-versa. This relationship was assessed both in physical and statistical ways, identifying the contribution of each explaining variable of ETP. We derived regression equations between monthly rainfall and ETP, which can be useful in studies where ETP time series are not available, such as reservoir design, irrigation management and flow forecast.

  10. Rainfall Characterization In An Arid Area

    OpenAIRE

    Bazaraa, A. S.; Ahmed, Shamim

    1991-01-01

    The objective of this work is to characterize the rainfall in Doha which lies in an arid region. The rainfall data included daily rainfall depth since 1962 and the hyetographs of the individual storms since 1976. The rainfall is characterized by high variability and severe thunderstorms which are of limited geographical extent. Four probability distributions were used to fit the maximum rainfall in 24 hours and the annual rainfall depth. The extreme value distribution was found to have the be...

  11. Using long-term daily satellite based rainfall data (1983-2015) to analyze spatio-temporal changes in the sahelian rainfall regime

    Science.gov (United States)

    Zhang, Wenmin; Brandt, Martin; Guichard, Francoise; Tian, Qingjiu; Fensholt, Rasmus

    2017-07-01

    The sahelian rainfall regime is characterized by a strong spatial as well as intra- and inter-annual variability. The satellite based African Rainfall Climatology Version 2 (ARC2) daily gridded rainfall estimates with a 0.1° × 0.1° spatial resolution provides the possibility for in-depth studies of seasonal changes over a 33-year period (1983-2015). Here we analyze rainfall regime variables that require daily observations: onset, cessation, and length of the wet season; seasonal rainfall amount; number of rainy days; intensity and frequency of rainfall events; number, length, and cumulative duration of dry spells. Rain gauge stations and MSWEP (Multi-Source Weighted-Ensemble Precipitation) data were used to evaluate the agreement of rainfall variables in both space and time, and trends were analyzed. Overall, ARC2 rainfall variables reliably show the spatio-temporal dynamics of seasonal rainfall over 33 years when compared to gauge and MSWEP data. However, a higher frequency of low rainfall events (spell characteristics). Most rainfall variables (both ARC2 and gauge data) show negative anomalies (except for onset of rainy season) from 1983 until the end of the 1990s, from which anomalies become mostly positive and inter-annual variability is higher. ARC2 data show a strong increase in seasonal rainfall, wet season length (caused by both earlier onset and a late end), number of rainy days, and high rainfall events (>20 mm day-1) for the western/central Sahel over the period of analysis, whereas the opposite trend characterizes the eastern part of the Sahel.

  12. A map-based South Pacific rainfall climatology

    Science.gov (United States)

    Lorrey, A.; Diamond, H.; Renwick, J.; Salinger, J.; Gergis, J.; Dalu, G.

    2008-12-01

    The lives of more than four million people that reside in the South Pacific are greatly affected by rainfall variability. This region is subjected to large rainfall anomalies on seasonal timescales due to tropical cyclone occurrences, ENSO activity, and the AAO. Regional climate anomalies are also dictated by the IPO on multi- decadal scales that alter the motions of large-scale circulation features like the South Pacific Convergence Zone (SPCZ). Strong climate change impacts are anticipated for this region, so gauging the severity of rainfall variations that can occur are paramount for implementing appropriate climate change adaptation measures. Lack of historical rainfall records and documentation of other climate data hinders our current understanding of South Pacific climate variability. Climate data rescue activities are currently aimed at recovering, archiving, and digitising this information to rectify this issue. This research aims to examine the rainfall database administered by the Island Climate Update (ICU) project, which is contributed to by all Pacific Island national meteorological services (NMS), Meteo-France (New Caledonia and French Polynesia), NIWA (New Zealand), NOAA (USA), the IRI (USA), and the Bureau of Meteorology (Australia). Monthly rainfall totals for all stations in the ICU database were assessed, and allowed construction of master rainfall chronologies for all or portions of the major South Pacific Island nations. Climatic norms were then calculated over common time periods, and monthly-resolved rainfall anomaly maps for the South Pacific covering 1951-2008 were undertaken. Immediate benefits of this exercise have pointed out holes in the rainfall network that can be specifically targeted for data rescue in the near future, which can be achieved by providing financial assistance to Pacific Island NMSs. In addition, there is ample scope to extend the rainfall anomaly map time series into the early 1900s using a spatially degraded data

  13. A rainfall-based warning model for shallow landslides

    Science.gov (United States)

    Zeng, Yi-Chao; Wang, Ji-Shang; Jan, Chyan-Deng; Yin, Hsiao-Yuan; Lo, Wen-Chun

    2016-04-01

    According to the statistical data of past rainfall events, the climate has changed in recent decades. Rainfall patterns have presented a more concentrated, high-intensity and long-duration trend in Taiwan. The most representative event is Typhoon Morakot which induced a total of 67 enormous landslides by the extreme amount of rain during August 7 to 10 in 2009 and resulted in the heaviest casualties in southern Taiwan. In addition, the nature of vulnerability such as steep mountains and rushing rivers, fragile geology and loose surface soil results in more severe sediment-relative disasters, in which shallow landslides are widespread hazards in mountainous regions. This research aims to develop and evaluate a model for predicting shallow landslides triggered by rainfall in mountainous area. Considering the feasibility of large-scale application and practical operation, the statistical techniques is adopted to form the landslide model based on abundant historical rainfall data and landslide events. The 16 landslide inventory maps and 15 variation results by comparing satellite images taken before and after the rainfall event were interpreted and delineated since 2004 to 2011. Logit model is utilized for interpreting the relationship between rainfall characteristics and landslide events delineated from satellite. Based on the analysis results of logistic regression, the rainfall factors that are highly related to shallow landslide occurrence are selected which are 3 hours rainfall intensity I3 (mm/hr) and the effective cumulative precipitation Rt (mm) including accumulated rainfall at time t and antecedent rainfall. A landslide rainfall triggering index (LRTI) proposed for assessing the occurrence potential of shallow landslides is defined as the product of I3 and Rt. A form of probability of shallow landslide triggered threshold is proposed to offer a measure of the likelihood of landslide occurrence. Two major critical lines which represent the lower and upper

  14. Spatio-temporal variability of rainfall regime in the Brahmaputra valley of North East India

    Science.gov (United States)

    Deka, R. L.; Mahanta, C.; Nath, K. K.; Dutta, M. K.

    2016-05-01

    Monthly rainfall data, spanning over 110 years (1901-2010), were utilized for trend analysis at different spatial and temporal scales over the Brahmaputra valley, India. The Mann-Kendall statistic and Sen's slope model were used to identify the trends and estimate the magnitude of change, respectively. Statistical significance of the decadal shifts in rainfall from the overall mean was estimated by using Cramer's test. The analysis revealed decrease in annual as well as monsoon rainfall in the Brahmaputra valley during the last 110 years with large spatial and temporal variations. These decreasing trends of rainfall in the eastern part of the valley were statistically significant. Significant decreasing trend of monsoon rainfall during the recent 30-year period was due to significant decrease of July and September rainfall, and this trend was found to be consistent at different spatial scales. In the last decade (2001-2010) in particular, monsoon rainfall exhibited significant negative deviation from the normal due to three deficient years and absence of excess rainfall years. On the contrary, contribution of pre-monsoon and post-monsoon rainfall to annual total in the Brahmaputra valley increased during the recent 30-year period. Winter rainfall in the valley decreased during the last 30 years due to significant decrease of December rainfall in the eastern and central parts.

  15. Rainfall Predictions From Global Salinity Anomalies

    Science.gov (United States)

    Schmitt, R. W.; Li, L.; Liu, T.

    2016-12-01

    We have discovered that sea surface salinity (SSS) is a better seasonal predictor of terrestrial rainfall than sea surface temperature (SST) or the usual pressure modes of atmospheric variability. In many regions, a 3-6 month lead of SSS over rainfall on land can be seen. While some lead is guaranteed due to the simple conservation of water and salt, the robust seasonal lead for SSS in some places is truly remarkable, often besting traditional SST and pressure predictors by a very significant margin. One mechanism for the lead has been identified in the recycling of water on land through soil moisture in regional ocean to land moisture transfers. However, a global search has yielded surprising long-range SSS-rainfall teleconnections. It is suggested that these teleconnections indicate a marked sensitivity of the atmosphere to where rain falls on the ocean. That is, the latent heat of evaporation is by far the largest energy transfer from ocean to atmosphere and where the atmosphere cashes in this energy in the form of precipitation is well recorded in SSS. SSS also responds to wind driven advection and mixing. Thus, SSS appears to be a robust indicator of atmospheric energetics and moisture transport and the timing and location of rainfall events is suggested to influence the subsequent evolution of the atmospheric circulation. In a sense, if the fall of a rain drop is at least equivalent to the flap of a butterfly's wings, the influence of a billion butterfly rainstorm allows for systematic predictions beyond the chaotic nature of the turbulent atmosphere. SSS is found to be particularly effective in predicting extreme precipitation or droughts, which makes its continued monitoring very important for building societal resilience against natural disasters.

  16. Moisture source for summer monsoon rainfall over India

    Digital Repository Service at National Institute of Oceanography (India)

    Sadhuram, Y.; Rao, D.P.

    Southwest monsoon plays a vital role in India's economy as the major income comes from agriculture. What could be the moisture source for this copious amount of rainfall over the Indian sub-continent?. This has been studied in detail and noticed...

  17. Laboratory-Measured Rainfall Effects on LWIR Soil Reflectance

    Science.gov (United States)

    Howington, S. E.; Ballard, J., Jr.; Wilhelms, S.

    2012-12-01

    The long-wave infrared reflectance of soils will often have distinct spectral characteristics that depend on the soil's physical and spectral properties. Rainfall has the effect of sorting soil particles at the ground surface, thus changing its long-wave infrared reflectance. This study examines how rainfall alters the measured directional-hemispherical thermal infrared (8-14 μm) spectral reflectance by comparing disturbed soil with undisturbed soil and pre-rain with post-rain conditions. The study uses a soil with a specified sand/silt ratio and a calibrated, laboratory rainfall simulator. For an accumulated rainfall of 8 cm, the mean disturbed soil thermal infrared spectral reflectance within 8.1 - 9.2 μm waveband increases from an initial reflectance of 13 percent to a maximum reflectance of 31 percent. Sixty percent of this reflectance change occurred with only 1 cm accumulated rainfall. This study shows that, for this described disturbed sand/silt soil mixture, small accumulated rainfall amounts significantly alter the directional-hemispherical thermal infrared spectral reflectance.

  18. [Rainfall intensity effects on nutrients transport in surface runoff from farmlands in gentle slope hilly area of Taihu Lake Basin].

    Science.gov (United States)

    Li, Rui-ling; Zhang, Yong-chun; Liu, Zhuang; Zeng, Yuan; Li, Wei-xin; Zhang, Hong-ling

    2010-05-01

    To investigate the effect of rainfall on agricultural nonpoint source pollution, watershed scale experiments were conducted to study the characteristics of nutrients in surface runoff under different rainfall intensities from farmlands in gentle slope hilly areas around Taihu Lake. Rainfall intensity significantly affected N and P concentrations in runoff. Rainfall intensity was positively related to TP, PO4(3-) -P and NH4+ -N event mean concentrations(EMC). However, this study have found the EMC of TN and NO3- -N to be positively related to rainfall intensity under light rain and negatively related to rainfall intensity under heavy rain. TN and TP site mean amounts (SMA) in runoff were positively related to rainfall intensity and were 1.91, 311.83, 127.65, 731.69 g/hm2 and 0.04, 7.77, 2.99, 32.02 g/hm2 with rainfall applied under light rain, moderate rain, heavy rain and rainstorm respectively. N in runoff was mainly NO3- -N and NH4+ -N and was primarily in dissolved form from Meilin soils. Dissolved P (DP) was the dominant form of TP under light rain, but particulate P (PP) mass loss increased with the increase of rainfall intensity and to be the dominant form when the rainfall intensity reaches rainstorm. Single relationships were used to describe the dependence of TN and TP mass losses in runoff on rainfall, maximum rainfall intensity, average rainfall intensity and rainfall duration respectively. The results showed a significant positive correlation between TN mass loss and rainfall, maximum rainfall intensity respectively (p rainfall, maximum rainfall intensity respectively (p < 0.01).

  19. How would peak rainfall intensity affect runoff predictions using conceptual water balance models?

    Science.gov (United States)

    Yu, B.

    2015-06-01

    Most hydrological models use continuous daily precipitation and potential evapotranspiration for streamflow estimation. With the projected increase in mean surface temperature, hydrological processes are set to intensify irrespective of the underlying changes to the mean precipitation. The effect of an increase in rainfall intensity on the long-term water balance is, however, not adequately accounted for in the commonly used hydrological models. This study follows from a previous comparative analysis of a non-stationary daily series of stream flow of a forested watershed (River Rimbaud) in the French Alps (area = 1.478 km2) (1966-2006). Non-stationarity in the recorded stream flow occurred as a result of a severe wild fire in 1990. Two daily models (AWBM and SimHyd) were initially calibrated for each of three distinct phases in relation to the well documented land disturbance. At the daily and monthly time scales, both models performed satisfactorily with the Nash-Sutcliffe coefficient of efficiency (NSE) varying from 0.77 to 0.92. When aggregated to the annual time scale, both models underestimated the flow by about 22% with a reduced NSE at about 0.71. Exploratory data analysis was undertaken to relate daily peak hourly rainfall intensity to the discrepancy between the observed and modelled daily runoff amount. Preliminary results show that the effect of peak hourly rainfall intensity on runoff prediction is insignificant, and model performance is unlikely to improve when peak daily precipitation is included. Trend analysis indicated that the large decrease of precipitation when daily precipitation amount exceeded 10-20 mm may have contributed greatly to the decrease in stream flow of this forested watershed.

  20. Heavy rainfall and waterborne disease outbreaks: the Walkerton example.

    Science.gov (United States)

    Auld, Heather; MacIver, D; Klaassen, J

    Recent research indicates that excessive rainfall has been a significant contributor to historical waterborne disease outbreaks. The Meteorological Service of Canada, Environment Canada, provided an analysis and testimony to the Walkerton Inquiry on the excessive rainfall events, including an assessment of the historical significance and expected return periods of the rainfall amounts. While the onset of the majority of the Walkerton, Ontario, Escherichia coli O157:H7 and Campylobacter outbreak occurred several days after a heavy rainfall on May 12, the accumulated 5-d rainfall amounts from 8-12 May were particularly significant. These 5-d accumulations could, on average, only be expected once every 60 yr or more in Walkerton and once every 100 yr or so in the heaviest rainfall area to the south of Walkerton. The significant link between excess rainfall and waterborne disease outbreaks, in conjunction with other multiple risk factors, indicates that meteorological and climatological conditions need to be considered by water managers, public health officials, and private citizens as a significant risk factor for water contamination. A system to identify and project the impacts of such challenging or extreme weather conditions on water supply systems could be developed using a combination of weather/climate monitoring information and weather prediction or quantitative precipitation forecast information. The use of weather monitoring and forecast information or a "wellhead alert system" could alert water system and water supply managers on the potential response of their systems to challenging weather conditions and additional requirements to protect health. Similar approaches have recently been used by beach managers in parts of the United States to predict day-to-day water quality for beach advisories.

  1. Methods to determine the impact of rainfall on fuels and burned area in southern African savannas

    CSIR Research Space (South Africa)

    Archibald, S

    2010-11-01

    Full Text Available of the models by up to 30% compared with indices that only used the previous year’s rainfall. Up to 56% of the variance in burned area between years could be explained by an 18-month accumulated rainfall index. Linear models and probit models performed equally...

  2. Bayesian spatiotemporal interpolation of rainfall in the Central Chilean Andes

    Science.gov (United States)

    Ossa-Moreno, Juan; Keir, Greg; McIntyre, Neil

    2016-04-01

    Water availability in the populous and economically significant Central Chilean region is governed by complex interactions between precipitation, temperature, snow and glacier melt, and streamflow. Streamflow prediction at daily time scales depends strongly on accurate estimations of precipitation in this predominantly dry region, particularly during the winter period. This can be difficult as gauged rainfall records are scarce, especially in the higher elevation regions of the Chilean Andes, and topographic influences on rainfall are not well understood. Remotely sensed precipitation and topographic products can be used to construct spatiotemporal multivariate regression models to estimate rainfall at ungauged locations. However, classical estimation methods such as kriging cannot easily accommodate the complicated statistical features of the data, including many 'no rainfall' observations, as well as non-normality, non-stationarity, and temporal autocorrelation. We use a separable space-time model to predict rainfall using the R-INLA package for computationally efficient Bayesian inference, using the gridded CHIRPS satellite-based rainfall dataset and digital elevation models as covariates. We jointly model both the probability of rainfall occurrence on a given day (using a binomial likelihood) as well as amount (using a gamma likelihood or similar). Correlation in space and time is modelled using a Gaussian Markov Random Field (GMRF) with a Matérn spatial covariance function which can evolve over time according to an autoregressive model if desired. It is possible to evaluate the GMRF at relatively coarse temporal resolution to speed up computations, but still produce daily rainfall predictions. We describe the process of model selection and inference using an information criterion approach, which we use to objectively select from competing models with various combinations of temporal smoothing, likelihoods, and autoregressive model orders.

  3. Vulnerability Assessment of Rainfall-Induced Debris Flow

    Science.gov (United States)

    Lu, G. Y.; Wong, D. W.; Chiu, L. S.

    2006-05-01

    Debris flow is a common hazard triggered by large amount of rainfall over mountainous areas. A debris flow event results from a complex interaction between rainfall and topographical properties of watersheds. Heavy rainfall facilitates this process by increasing pore water pressure, seepage force and reducing effective stress of soils (normal stress carried by soil particles at the points of contact). Since debris flow events are closely related to topography and rainfall, the goal of this research is to assess debris flow vulnerability related to these two factors. Objectives of this research are to: (1) examine new spatial interpolation techniques to estimate high spatial rainfall data relevant to debris flows. (2) develop topographical factors using Geography Information System (GIS) and remote sensing (RS) approaches and (3) combine the estimated rainfall and topographical factors to assess the vulnerability of debris flow. We examined three spatial interpolation techniques: adaptive inversed distance weight (AIDW), simple kriging and spatial disaggregation using wind induced-topographic effect that incorporates gauge measurements, satellite remote sensing data (TRMM). The topographical factors are derived from high resolution digital elevation model (DEM), and adopt fuzzy-based topographical models proposed by Tseng (2004). Estimated rainfall and topographical factors are processed by self-organizing maps (SOM) to provide vulnerability assessment. To demonstrate our technique, rainfall data collected by 39 rain gauges in the central part of Taiwan during the passage of Typhoon Tori-Ji around July 29, 2001 were used. Results indicate that the proposed spatial interpolation methods outperform existing methods (i.e. kriging, inverse distance weight, and co-kriging methods). The vulnerability assessment of 187 debris flows watersheds in the study area will be presented. Keyword: Debris flow, spatial interpolation, adaptive inverse distance weight, TRMM, self

  4. The Interdependence between Rainfall and Temperature: Copula Analyses

    Directory of Open Access Journals (Sweden)

    Rong-Gang Cong

    2012-01-01

    Full Text Available Rainfall and temperature are important climatic inputs for agricultural production, especially in the context of climate change. However, accurate analysis and simulation of the joint distribution of rainfall and temperature are difficult due to possible interdependence between them. As one possible approach to this problem, five families of copula models are employed to model the interdependence between rainfall and temperature. Scania is a leading agricultural province in Sweden and is affected by a maritime climate. Historical climatic data for Scania is used to demonstrate the modeling process. Heteroscedasticity and autocorrelation of sample data are also considered to eliminate the possibility of observation error. The results indicate that for Scania there are negative correlations between rainfall and temperature for the months from April to July and September. The student copula is found to be most suitable to model the bivariate distribution of rainfall and temperature based on the Akaike information criterion (AIC and Bayesian information criterion (BIC. Using the student copula, we simulate temperature and rainfall simultaneously. The resulting models can be integrated with research on agricultural production and planning to study the effects of changing climate on crop yields.

  5. Comparative Analysis of Data Mining Techniques for Malaysian Rainfall Prediction

    Directory of Open Access Journals (Sweden)

    Suhaila Zainudin

    2016-12-01

    Full Text Available Climate change prediction analyses the behaviours of weather for a specific time. Rainfall forecasting is a climate change task where specific features such as humidity and wind will be used to predict rainfall in specific locations. Rainfall prediction can be achieved using classification task under Data Mining. Different techniques lead to different performances depending on rainfall data representation including representation for long term (months patterns and short-term (daily patterns. Selecting an appropriate technique for a specific duration of rainfall is a challenging task. This study analyses multiple classifiers such as Naïve Bayes, Support Vector Machine, Decision Tree, Neural Network and Random Forest for rainfall prediction using Malaysian data. The dataset has been collected from multiple stations in Selangor, Malaysia. Several pre-processing tasks have been applied in order to resolve missing values and eliminating noise. The experimental results show that with small training data (10% from 1581 instances Random Forest correctly classified 1043 instances. This is the strength of an ensemble of trees in Random Forest where a group of classifiers can jointly beat a single classifier.

  6. Postprocessing of simulated precipitation for impact research in West Africa. Part I: model output statistics for monthly data

    Energy Technology Data Exchange (ETDEWEB)

    Paeth, Heiko [University of Wuerzburg, Institute of Geography, Wuerzburg (Germany)

    2011-04-15

    Rainfall represents an important factor in agriculture and food security, particularly, in the low latitudes. Climatological and hydrological studies which attempt to diagnose the hydrological cycle, require high-quality precipitation data. In West Africa, like in many parts of the world, the density of observational data is low and climate models are needed in order to perform homogeneous and complete data sets. However, climate models tend to produce systematic errors, especially, in terms of rainfall and cloud processes, which are usually approximated by physical parameterizations. In this study, a 25-year climatology of monthly precipitation in West Africa is presented, derived from a regional climate model simulation, and evaluated with respect to observational data. It is found that the model systematically underestimates the rainfall amount and variability and does not capture some details of the seasonal cycle in sub-Saharan West Africa. Thus, in its present form the precipitation climatology is not appropriate to draw a realistic picture of the hydrological cycle in West Africa nor to serve as input data for impact research. Therefore, a statistical model is developed in order to adjust the simulated rainfall data to the characteristics of observed precipitation. Assuming that the regional climate model is much more reliable in terms of atmospheric circulation and thermodynamics, model output statistics is used to correct simulated rainfall by means of other simulated parameters of the near-surface climate like temperature, sea level pressure and wind components. Monthly data is adjusted by a cross-validated multiple regression model. The resulting adjusted rainfall climatology reveals a substantial improvement in terms of the model deficiencies mentioned above. In part II of this publication, the characteristics of simulated daily precipitation is adapted to station data by applying a weather generator. Once the postprocessing approach is trained, it can

  7. Record Rainfall and Flooding in Texas and Oklahoma, May 2015; Extent and Historical Perspective

    Science.gov (United States)

    Cepeda, J. C.

    2015-12-01

    Heavy rains began in Texas and Oklahoma in early May 2015 and continued through the end of the month. Both states set all-time records for mean statewide precipitation; Texas - 227mm (8.93 in), Oklahoma - 357mm (14.06 in) -- for the period of record (1895-2015). These new statewide records were set despite the fact that the western portions of both Texas and Oklahoma received only modest rainfall. Parameters used in this study to evaluate the magnitude and historical perspective of the May 2015 rainfall included daily and total storm precipitation, stream flow, changes in the Palmer Drought Severity Index (PDSI), and changes in reservoir water levels. Although the Dallas-Fort Worth area and the cities of Austin, Houston and Oklahoma City sustained the most serious flood events, more than 100 localities in the two states reported some flooding. The region with the largest amounts of precipitation extended from north-central Texas northeastward into eastern Oklahoma. Cumulative May rainfall in this region exceeded 508 mm (20 in). Provisional stream flow data for the river basins most affected -- Red River, Brazos, Colorado, and Trinity rivers -- reveal significant peaks, but the peaks generally are within the ranges of the historical record. With the exception of the Red River the most significant flooding relative to historic flood peaks, occurred on tributaries to the major rivers. Comparison of the PDSI for the months of April and June reveals the dramatic impact of the precipitation during May. By the first week of June both states are classified as moderately moist - with the exception of the extreme northeastern corner of Oklahoma. Changes in Reservoir levels (as a percent of capacity) between April and June was greatest for the Rolling Plains region (+ 15.5%), with lesser, but significant gains in South and Central Texas and the Central Oklahoma region.

  8. Lightning and Rainfall Characteristics in Elevated vs. Surface Based Convection in the Midwest that Produce Heavy Rainfall

    Directory of Open Access Journals (Sweden)

    Joshua S. Kastman

    2017-02-01

    Full Text Available There are differences in the character of surface-based and elevated convection, and one type may pose a greater threat to life or property. The lightning and rainfall characteristics of eight elevated and eight surface-based thunderstorm cases that occurred between 2007 and 2010 over the central Continental United States were tested for statistical differences. Only events that produced heavy rain (>50.8 mm·day−1 were investigated. The nonparametric Mann–Whitney test was used to determine if the characteristics of elevated thunderstorm events were significantly different than the surface based events. Observations taken from these cases include: rainfall–lightning ratios (RLR within the heavy rain area, the extent of the heavy rainfall area, cloud-to-ground (CG lightning flashes, CG flashes·h−1, positive CG flashes, positive CG flashes·h−1, percentage of positive CG flashes within the heavy rainfall area, and maximum and mean rainfall amounts within the heavy rain area. Results show that elevated convection cases produced more rainfall, total CG lightning flashes, and positive CG lightning flashes than surface based thunderstorms. More available moisture and storm morphology explain these differences, suggesting elevated convection is a greater lightning and heavy rainfall threat than surface based convection.

  9. Changing patterns in rainfall extremes in South Australia

    Science.gov (United States)

    Kamruzzaman, Mohammad; Beecham, Simon; Metcalfe, Andrew V.

    2017-02-01

    Daily rainfall records from seven stations in South Australia, with record lengths from 50 to 137 years and a common period of 36 years, are investigated for evidence of changes in the statistical distribution of annual total and annual average of monthly daily maxima. In addition, the monthly time series of monthly totals and monthly daily maxima are analysed for three stations for which records exceed 100 years. The monthly series show seasonality and provide evidence of a reduction in rainfall when the Southern Oscillation Index (SOI) is negative, which is modulated by the Pacific Decadal Oscillation (PDO). However, the monthly series do not provide any evidence of a consistent trend or of any changes in the seasonal pattern. Multivariate analyses, typically used in statistical quality control (SQC), are applied to time series of yearly totals and of averages of the 12 monthly daily maxima, during the common 36-year period. Although there are some outlying points in the charts, there is no evidence of any trend or step changes. However, some supplementary permutation tests do provide weak evidence of an increase of variability of rainfall measures. Furthermore, a factor analysis does provide some evidence of a change in the spatial structure of extremes. The variability of a factor which represents the difference between extremes in the Adelaide Hills and the plains increases in the second 18 years relative to the first 18 years. There is also some evidence that the mean of this factor has increased in absolute magnitude.

  10. What rainfall events trigger landslides on the West Coast US?

    Science.gov (United States)

    Biasutti, Michela; Seager, Richard; Kirschbaum, Dalia

    2016-04-01

    A dataset of landslide occurrences compiled by collating google news reports covers 9 full years of data. We show that, while this compilation cannot provide consistent and widespread monitoring everywhere, it is adequate to capture the distribution of events in the major urban areas of the West Coast US and it can be used to provide a quantitative relationship between landslides and rainfall events. The case of the Seattle metropolitan area is presented as an example. The landslide dataset shows a clear seasonality in landslide occurrence, corresponding to the seasonality of rainfall, modified by the accumulation of soil moisture as winter progresses. Interannual variability of landslide occurrences is also linked to interannual variability of monthly rainfall. In most instances, landslides are clustered on consecutive days or at least within the same pentad and correspond to days of large rainfall accumulation at the regional scale. A joint analysis of the landslide data and of the high-resolution PRISM daily rainfall accumulation shows that on days when landslides occurred, the distribution of rainfall was shifted, with rainfall accumulation higher than 10mm/day being more common. Accumulations above 50mm/day much increase the probability of landslides, including the possibility of a major landslide event (one with multiple landslides in a day). The synoptic meteorological conditions associated with these major events show a mid-tropospheric ridge to the south of the target area steering a surface low and bringing enhanced precipitable water towards the Pacific North West. The interaction of the low-level flow with the local orography results in instances of a strong Puget Sound Convergence Zone, with widespread rainfall accumulation above 30mm/day and localized maxima as high as 100mm/day or more.

  11. Assessing spatio-temporal variability of rainfall using a simple physically based statistical model

    Science.gov (United States)

    Hutchinson, M. F.; Xu, T.; Kesteven, J.

    2010-12-01

    Reliable assessment of spatio-temporal variability of observed rainfall is difficult in the current climate because of the complex spatial variability displayed by daily and shorter time scale rainfall data. As demonstrated in a recent analysis of Canadian daily precipitation data by Hutchinson et al. (2009), direct interpolation of short time scale precipitation data is a poor way to address spatial patterns of rainfall extremes. Addressing the behaviour of projected future precipitation extremes is made even more difficult by the limited temporal and spatial resolution of precipitation as simulated by global climate models. The “uniform drizzle” that tends to be produced by these models makes the assessment of even straightforward statistics, such as daily rainfall occurrence, problematic. Putting aside significant inter-model variability, the more reliable outputs of global models include mean fluxes, such as monthly rainfall amounts, and associated insight into the nature of the modelled precipitation in relation to forcing synoptic systems. The truncated power of normal distribution, as described by Hutchinson (1995), offers a relatively simple way to make progress. Two of the three model parameters are simply calibrated in terms of monthly mean fluxes and the model is able to accurately describe precipitation extremes. These model parameters can also be robustly determined from serially incomplete data. It can be argued that the model has a broad physical process basis by modelling rainfall as an event that occurs as an appropriate threshold is exceeded. This analysis extends the approach of Stidd (1954, 1973) who suggested the cube root as a universal normalising power. We show that the power parameter, once robustly calibrated, displays a broadly spatially varying distribution of around 0.5. This corresponds well with the two dimensional synoptic convergence that is required to produce precipitation. The power parameter appears to be related to the

  12. Applying satellite remote sensing technique in disastrous rainfall systems around Taiwan

    Science.gov (United States)

    Liu, Gin-Rong; Chen, Kwan-Ru; Kuo, Tsung-Hua; Liu, Chian-Yi; Lin, Tang-Huang; Chen, Liang-De

    2016-05-01

    Many people in Asia regions have been suffering from disastrous rainfalls year by year. The rainfall from typhoons or tropical cyclones (TCs) is one of their key water supply sources, but from another perspective such TCs may also bring forth unexpected heavy rainfall, thereby causing flash floods, mudslides or other disasters. So far we cannot stop or change a TC route or intensity via present techniques. Instead, however we could significantly mitigate the possible heavy casualties and economic losses if we can earlier know a TC's formation and can estimate its rainfall amount and distribution more accurate before its landfalling. In light of these problems, this short article presents methods to detect a TC's formation as earlier and to delineate its rainfall potential pattern more accurate in advance. For this first part, the satellite-retrieved air-sea parameters are obtained and used to estimate the thermal and dynamic energy fields and variation over open oceans to delineate the high-possibility typhoon occurring ocean areas and cloud clusters. For the second part, an improved tropical rainfall potential (TRaP) model is proposed with better assumptions then the original TRaP for TC rainfall band rotations, rainfall amount estimation, and topographic effect correction, to obtain more accurate TC rainfall distributions, especially for hilly and mountainous areas, such as Taiwan.

  13. Rainfall variability modelling in Rwanda

    Science.gov (United States)

    Nduwayezu, E.; Kanevski, M.; Jaboyedoff, M.

    2012-04-01

    Support to climate change adaptation is a priority in many International Organisations meetings. But is the international approach for adaptation appropriate with field reality in developing countries? In Rwanda, the main problems will be heavy rain and/or long dry season. Four rainfall seasons have been identified, corresponding to the four thermal Earth ones in the south hemisphere: the normal season (summer), the rainy season (autumn), the dry season (winter) and the normo-rainy season (spring). The spatial rainfall decreasing from West to East, especially in October (spring) and February (summer) suggests an «Atlantic monsoon influence» while the homogeneous spatial rainfall distribution suggests an «Inter-tropical front » mechanism. The torrential rainfall that occurs every year in Rwanda disturbs the circulation for many days, damages the houses and, more seriously, causes heavy losses of people. All districts are affected by bad weather (heavy rain) but the costs of such events are the highest in mountains districts. The objective of the current research is to proceed to an evaluation of the potential rainfall risk by applying advanced geospatial modelling tools in Rwanda: geostatistical predictions and simulations, machine learning algorithm (different types of neural networks) and GIS. The research will include rainfalls variability mapping and probabilistic analyses of extreme events.

  14. Trend analysis and forecast of precipitation, reference evapotranspiration, and rainfall deficit in the Blackland Prairie of eastern Mississippi

    Science.gov (United States)

    Gary Feng; Stacy Cobb; Zaid Abdo; Daniel K. Fisher; Ying Ouyang; Ardeshir Adeli; Johnie N. Jenkins

    2016-01-01

    Trend analysis and estimation of monthly and annual precipitation, reference evapotranspiration ET, and rainfall deficit are essential for water-resources management and cropping-system design. Rainfall, ET, and water-deficit patterns and trends at Macon in eastern Mississippi for a 120-yr period (1894-2014) were analyzed for annual, seasonal, and monthly...

  15. Global detection and analysis of coastline associated rainfall using objective pattern recognition techniques

    CERN Document Server

    Bergemann, Martin; Lane, Todd P

    2015-01-01

    Coastally induced rainfall is a common feature especially in tropical and subtropical regions. However, it has been difficult to quantify the contribution of coastal rainfall features to the overall local rainfall. We develop a novel technique to objectively identify precipitation associated with land-sea interaction and apply it to satellite based rainfall estimates. The Maritime Continent, the Bight of Panama, Madagascar and the Mediterranean are found to be regions where land-sea interactions plays a crucial role in the formation of precipitation. In these regions $\\approx$ 40\\% to 60\\% of the total rainfall can be related to coastline effects. Due to its importance for the climate system, the Maritime Continent is a particular region of interest with high overall amounts of rainfall and large fractions resulting from land-sea interactions throughout the year. To demonstrate the utility of our identification method we investigate the influence of several modes of variability, such as the Madden-Julian-Osci...

  16. Forecasting Rainfall Induced Landslide using High Resolution DEM and Simple Water Budget Model

    Science.gov (United States)

    Luzon, P. K. D.; Lagmay, A. M. F. A.

    2014-12-01

    Philippines is hit by an average of 20 typhoons per year bringing large amount of rainfall. Monsoon carrying rain coming from the southwest of the country also contributes to the annual total rainfall that causes different hazards. Such is shallow landslide mainly triggered by high saturation of soil due to continuous downpour which could take up from hours to days. Recent event like this happened in Zambales province September of 2013 where torrential rain occurred for 24 hours amounting to half a month of rain. Rainfall intensity measured by the nearest weather station averaged to 21 mm/hr from 10 pm of 22 until 10 am the following day. The monsoon rains was intensified by the presence of Typhoon Usagi positioned north and heading northwest of the country. A number of landslides due to this happened in 3 different municipalities; Subic, San Marcelino and Castillejos. The disaster have taken 30 lives from the province. Monitoring these areas for the entire country is but a big challenge in all aspect of disaster preparedness and management. The approach of this paper is utilizing the available forecast of rainfall amount to monitor highly hazardous area during the rainy seasons and forecasting possible landslide that could happen. A simple water budget model following the equation Perct=Pt-R/Ot-∆STt-AETt (where as the terms are Percolation, Runoff, Change in Storage, and Actual Evapotraspiration) was implemented in quantifying all the water budget component. Computations are in Python scripted grid system utilizing the widely used GIS forms for easy transfer of data and faster calculation. Results of successive runs will let percolation and change in water storage as indicators of possible landslide.. This approach needs three primary sets of data; weather data, topographic data, and soil parameters. This research uses 5 m resolution DEM (IfSAR) to define the topography. Soil parameters are from fieldworks conducted. Weather data are from the Philippine

  17. Modelling Ecuador's rainfall distribution according to geographical characteristics.

    Science.gov (United States)

    Tobar, Vladimiro; Wyseure, Guido

    2017-04-01

    It is known that rainfall is affected by terrain characteristics and some studies had focussed on its distribution over complex terrain. Ecuador's temporal and spatial rainfall distribution is affected by its location on the ITCZ, the marine currents in the Pacific, the Amazon rainforest, and the Andes mountain range. Although all these factors are important, we think that the latter one may hold a key for modelling spatial and temporal distribution of rainfall. The study considered 30 years of monthly data from 319 rainfall stations having at least 10 years of data available. The relatively low density of stations and their location in accessible sites near to main roads or rivers, leave large and important areas ungauged, making it not appropriate to rely on traditional interpolation techniques to estimate regional rainfall for water balance. The aim of this research was to come up with a useful model for seasonal rainfall distribution in Ecuador based on geographical characteristics to allow its spatial generalization. The target for modelling was the seasonal rainfall, characterized by nine percentiles for each one of the 12 months of the year that results in 108 response variables, later on reduced to four principal components comprising 94% of the total variability. Predictor variables for the model were: geographic coordinates, elevation, main wind effects from the Amazon and Coast, Valley and Hill indexes, and average and maximum elevation above the selected rainfall station to the east and to the west, for each one of 18 directions (50-135°, by 5°) adding up to 79 predictors. A multiple linear regression model by the Elastic-net algorithm with cross-validation was applied for each one of the PC as response to select the most important ones from the 79 predictor variables. The Elastic-net algorithm deals well with collinearity problems, while allowing variable selection in a blended approach between the Ridge and Lasso regression. The model fitting

  18. Rainfall model investigation and scenario analyses of the effect of government reforestation policy on seasonal rainfalls: A case study from Northern Thailand

    Science.gov (United States)

    Duangdai, Eakkapong; Likasiri, Chulin

    2017-03-01

    In this work, 4 models for predicting rainfall amounts are investigated and compared using Northern Thailand's seasonal rainfall data for 1973-2008. Two models, global temperature, forest area and seasonal rainfall (TFR) and modified TFR based on a system of differential equations, give the relationships between global temperature, Northern Thailand's forest cover and seasonal rainfalls in the region. The other two models studied are time series and Autoregressive Moving Average (ARMA) models. All models are validated using the k-fold cross validation method with the resulting errors being 0.971233, 0.740891, 2.376415 and 2.430891 for time series, ARMA, TFR and modified TFR models, respectively. Under Business as Usual (BaU) scenario, seasonal rainfalls in Northern Thailand are projected through the year 2020 using all 4 models. TFR and modified TFR models are also used to further analyze how global temperature rise and government reforestation policy affect seasonal rainfalls in the region. Rainfall projections obtained via the two models are also compared with those from the International Panel on Climate Change (IPCC) under IS92a scenario. Results obtained through a mathematical model for global temperature, forest area and seasonal rainfall show that the higher the forest cover, the less fluctuation there is between rainy-season and summer rainfalls. Moreover, growth in forest cover also correlates with an increase in summer rainfalls. An investigation into the relationship between main crop productions and rainfalls in dry and rainy seasons indicates that if the rainy-season rainfall is high, that year's main-crop rice production will decrease but the second-crop rice, maize, sugarcane and soybean productions will increase in the following year.

  19. Mallows statistic in the selection of models to predict the monthly and annual average rainfall in Rio Grande do Sul, Brazil. = Estatística de Mallows na seleção de modelos de predição da precipitação média mensal e anual no Rio Grande do Sul.

    Directory of Open Access Journals (Sweden)

    Claudia Fernanda Almeida Teixeira

    2013-08-01

    Full Text Available The Mallows Cp statistic can be used in the selection of the best subsets in hydrological modeling, especially in cases where many variables are used. Besause there are, in many cases, the interest in estimating the monthly and annual average rainfall based on geographic coordinates of latitude and longitude, and altitude. Consequently, the aim of this study was to verify the information gain when applied to statistical Cp Mallows in the selection of the best subsets of multiple linear regression to predict the precipitation of some municipalities in the state of Rio Grande do Sul. Daily precipitation data from 26 meteorological stations, in addition to seven others, used to validation of the proposed linear models, belonging to seven mesoregions of Rio Grande do Sul were collected and analyzed. After the formation of the series, precipitation values were adjusted from linear models, using multiple linear regression in which the dependent variable was the precipitation and independent variables, the geographic coordinates of latitude and longitude, and altitude. The Cp statistic was used in the selection of sets and, subsequently applied statistical indexes mean square error, standard error of prediction bias factor wereused to obtain the accuracy factor for comparison between observed versus predicted precipitation. From the results obtained itcan be concluded that, from the point of view of parsimony, the statistic proposed by Mallows proved adequate in the selectionof models for prediction of monthly and annual rainfall of the stations analyzed. = A estatística Cp de Mallows pode ser utilizada na seleção de melhores subconjuntos na modelagem hidrológica,principalmente nos casos em que são utilizadas muitas variáveis. Com base no fato de que há, em muitos casos, o interesse em estimar a precipitação média mensal e anual baseada nas coordenadas geográficas latitude e longitude, e altitude, objetivouse com este trabalho verificar o

  20. Characteristics of the extreme rainfall event and consequent flash floods in W Slovenia in September 2007

    Directory of Open Access Journals (Sweden)

    S. Rusjan

    2009-06-01

    Full Text Available During a weather front that passed over large parts of Slovenia on 18.9.2007, extreme rainfall events were triggered causing several severe flash floods with six casualties. Out of 210 municipalities in Slovenia, 60 were reporting flood damages, and the total economic flood damage was later estimated at close to 200 million Euro; highest damage was claimed by Železniki municipality in NW Slovenia. The main purpose of the study presented in this paper was to put together available meteorological and hydrological data in order to get better insight into temporal and spatial dynamics and variability of the flash flood event along the Selška Sora River flowing through the town of Železniki. The weather forecast by the Environmental Agency of the Republic of Slovenia (ARSO lead to early warning of floodings but has underestimated rainfall amounts by a factor of 2. Also meteorological radar underestimated ground rainfall as much as by 50%. During that day, in many rainfall gauging stations operated by ARSO in the area under investigation, extreme rainfall amounts were measured, e.g. 303 mm in 24 h or 157 mm in 2 h. Some of the measured rainfall amounts were the highest registered amounts in Slovenia so far. Statistical analysis using Gumble distribution was performed and rainfall return periods were estimated. When assessing rainfall return periods, a question of the sampling error as a consequence of short rainfall records used was raised. Furthermore, measured rainfall data were used to reconstruct hydrographs on selected water stations along the Selška Sora River. The cumulative areal precipitation for the Selška Sora River catchment upstream of Železniki amounted to 219 mm, while the modeled effective precipitation used to simulate the hydrograph peak was only 57 mm. The modeled direct runoff coefficient therefore amounts to 0.26. Surprisingly low value is mainly caused by the applied unit hydrograph method that seeks to meet the peak

  1. Comparison of Two Stochastic Daily Rainfall Models and their Ability to Preserve Multi-year Rainfall Variability

    Science.gov (United States)

    Kamal Chowdhury, AFM; Lockart, Natalie; Willgoose, Garry; Kuczera, George; Kiem, Anthony; Parana Manage, Nadeeka

    2016-04-01

    Stochastic simulation of rainfall is often required in the simulation of streamflow and reservoir levels for water security assessment. As reservoir water levels generally vary on monthly to multi-year timescales, it is important that these rainfall series accurately simulate the multi-year variability. However, the underestimation of multi-year variability is a well-known issue in daily rainfall simulation. Focusing on this issue, we developed a hierarchical Markov Chain (MC) model in a traditional two-part MC-Gamma Distribution modelling structure, but with a new parameterization technique. We used two parameters of first-order MC process (transition probabilities of wet-to-wet and dry-to-dry days) to simulate the wet and dry days, and two parameters of Gamma distribution (mean and standard deviation of wet day rainfall) to simulate wet day rainfall depths. We found that use of deterministic Gamma parameter values results in underestimation of multi-year variability of rainfall depths. Therefore, we calculated the Gamma parameters for each month of each year from the observed data. Then, for each month, we fitted a multi-variate normal distribution to the calculated Gamma parameter values. In the model, we stochastically sampled these two Gamma parameters from the multi-variate normal distribution for each month of each year and used them to generate rainfall depth in wet days using the Gamma distribution. In another study, Mehrotra and Sharma (2007) proposed a semi-parametric Markov model. They also used a first-order MC process for rainfall occurrence simulation. But, the MC parameters were modified by using an additional factor to incorporate the multi-year variability. Generally, the additional factor is analytically derived from the rainfall over a pre-specified past periods (e.g. last 30, 180, or 360 days). They used a non-parametric kernel density process to simulate the wet day rainfall depths. In this study, we have compared the performance of our

  2. Rainfall intensity characteristics at coastal and high altitude stations in Kerala

    Indian Academy of Sciences (India)

    V Sasi Kumar; S Sampath; P V S S K Vinayak; R Harikumar

    2007-10-01

    Rainfall intensities measured at a few stations in Kerala during 2001 –2005 using a disdrometer were found to be in reasonable agreement with the total rainfall measured using a manual rain gauge. The temporal distributions of rainfall intensity at different places and during different months show that rainfall is of low intensity (> 10 mm/hr),65%to 90%of the time.This could be an indication of the relative prevalence of stratiform and cumuliform clouds.Rainfall was of intensity > 5 mm/hr for more than 95%of the time in Kochi in July 2002,which was a month seriously deficient in rainfall,indicating that the deficiency was probably due to the relative absence of cumuliform clouds.Cumulative distribution graphs are also plotted and fitted with the Weibull distribution.The fit parameters do not appear to have any consistent pattern. The higher intensities also contributed signi ficantly to total rainfall most of the time,except in Munnar (a hill station). In this analysis also,the rainfall in Kochi in July 2002 was found to have less presence of high intensities. This supports the hypothesis that the rainfall de ficiency was probably caused by the absence of conditions that favoured the formation of cumuliform clouds.

  3. Toxicity of parking lot runoff after application of simulated rainfall.

    Science.gov (United States)

    Greenstein, D; Tiefenthaler, L; Bay, S

    2004-08-01

    Stormwater runoff is an important source of toxic substances to the marine environment, but the effects of antecedent dry period, rainfall intensity, and duration on the toxicity of runoff are not well understood. In this study, simulated rainfall was applied to parking lots to examine the toxicity of runoff while controlling for antecedent period, intensity, and duration of rainfall. Parking areas were divided into high and low use and maintained and unmaintained treatments. The parking stalls were cleaned by pressure washing at time zero. Simulated rainfall was then applied to subplots of the parking lots so that antecedent periods of 1, 2, and 3 months were achieved, and all of the runoff was collected for analysis. On a separate parking lot, rainfall was applied at a variety of intensities and durations after a 3-month antecedent period. Runoff samples were tested for toxicity using the purple sea urchin fertilization test. Every runoff sample tested was found to be toxic. Mean toxicity for the sea urchin fertilization test ranged from 2.0 to 12.1 acute toxic units. The toxicity increased rapidly during the first month but then decreased approximately to precleaning levels and remained there. No difference in toxicity was found between the different levels of use or maintenance treatments. The intensity and duration of rainfall were inversely related to degree of toxicity. For all intensities tested, toxicity was always greatest in the first sampling time interval. Dissolved zinc was most likely the primary cause of toxicity based on toxicant characterization of selected runoff samples.

  4. Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan.

    Science.gov (United States)

    Tsai, Kuang-Jung; Chiang, Jie-Lun; Lee, Ming-Hsi; Chen, Yie-Ruey

    2017-04-01

    Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan. Kuang-Jung Tsai 1, Jie-Lun Chiang 2,Ming-Hsi Lee 2, Yie-Ruey Chen 1, 1Department of Land Management and Development, Chang Jung Christian Universityt, Tainan, Taiwan. 2Department of Soil and Water Conservation, National Pingtung University of Science and Technology, Pingtung, Taiwan. ABSTRACT The accumulated rainfall amount was recorded more than 2,900mm that were brought by Morakot typhoon in August, 2009 within continuous 3 days. Very serious landslides, and sediment related disasters were induced by this heavy rainfall event. The satellite image analysis project conducted by Soil and Water Conservation Bureau after Morakot event indicated that more than 10,904 sites of landslide with total sliding area of 18,113ha were found by this project. At the same time, all severe sediment related disaster areas are also characterized based on their disaster type, scale, topography, major bedrock formations and geologic structures during the period of extremely heavy rainfall events occurred at the southern Taiwan. Characteristics and mechanism of large scale landslide are collected on the basis of the field investigation technology integrated with GPS/GIS/RS technique. In order to decrease the risk of large scale landslides on slope land, the strategy of slope land conservation, and critical rainfall database should be set up and executed as soon as possible. Meanwhile, study on the establishment of critical rainfall value used for predicting large scale landslides induced by heavy rainfall become an important issue which was seriously concerned by the government and all people live in Taiwan. The mechanism of large scale landslide, rainfall frequency analysis ,sediment budge estimation and river hydraulic analysis under the condition of extremely climate change during the past 10 years would be seriously concerned and recognized as a required issue by this

  5. Critical rainfall conditions for the initiation of torrential flows. Results from the Rebaixader catchment (Central Pyrenees)

    Science.gov (United States)

    Abancó, Clàudia; Hürlimann, Marcel; Moya, José; Berenguer, Marc

    2016-10-01

    Torrential flows like debris flows or debris floods are fast movements formed by a mix of water and different amounts of unsorted solid material. They generally occur in steep torrents and pose high risk in mountainous areas. Rainfall is their most common triggering factor and the analysis of the critical rainfall conditions is a fundamental research task. Due to their wide use in warning systems, rainfall thresholds for the triggering of torrential flows are an important outcome of such analysis and are empirically derived using data from past events. In 2009, a monitoring system was installed in the Rebaixader catchment, Central Pyrenees (Spain). Since then, rainfall data of 25 torrential flows ("TRIG rainfalls") were recorded, with a 5-min sampling frequency. Other 142 rainfalls that did not trigger torrential flows ("NonTRIG rainfalls") were also collected and analyzed. The goal of this work was threefold: (i) characterize rainfall episodes in the Rebaixader catchment and compare rainfall data that triggered torrential flows and others that did not; (ii) define and test Intensity-Duration (ID) thresholds using rainfall data measured inside the catchment by with different techniques; (iii) analyze how the criterion used for defining the rainfall duration and the spatial variability of rainfall influences the value obtained for the thresholds. The statistical analysis of the rainfall characteristics showed that the parameters that discriminate better the TRIG and NonTRIG rainfalls are the rainfall intensities, the mean rainfall and the total rainfall amount. The antecedent rainfall was not significantly different between TRIG and NonTRIG rainfalls, as it can be expected when the source material is very pervious (a sandy glacial soil in the study site). Thresholds were derived from data collected at one rain gauge located inside the catchment. Two different methods were applied to calculate the duration and intensity of rainfall: (i) using total duration, Dtot

  6. Intraseasonal Variability of Summer Monsoon Rainfall and Droughts over Central India

    Science.gov (United States)

    Shrivastava, Sourabh; Kar, Sarat C.; Sharma, Anu Rani

    2017-02-01

    Rainfall over Madhya Pradesh (MP) in central India has large intra-seasonal variability causing droughts and floods in many years. In this study, rainfall variability in daily and monthly scale over central India has been examined using observed data. Consistency among various datasets such as rainfall, surface temperature, soil moisture and evapotranspiration has been examined. These parameters are from various different sources and critical for drought monitoring and prediction. It is found that during weak phases of monsoon, central India receives deficit rainfall with weaker monsoon circulation. This phase is characterized by an anticyclonic circulation at 850 hPa centered on MP. The EOF analysis of daily rainfall suggests that the two leading modes explain about 23-24% of rainfall variability in intraseasonal timescale. These two modes represent drought/flood conditions over MP. Relationship of weak phases of rainfall over central India with real-time multivariate (RMM) indices of Madden Julian Oscillation (MJO) has been examined. It is found that RMM-6, RMM-7, RMM-1 and RMM-2 describe the weak monsoon conditions over central India. However, frequency of drought occurrence over MP is more during RMM-7 phase. Surface temperature increases by about 0.5°-1° during weak phases of rainfall over this region. Soil moisture and evapotranspiration gradually reduce when rainfall reduces over the study region. Soil moisture and evapotranspiration anomalies have positive pattern during good rainfall events over central India and gradually reduce and become negative anomalies during weak phases.

  7. Assessment of Seasonal and Annual Rainfall Trends and Variability in Sharjah City, UAE

    Directory of Open Access Journals (Sweden)

    Tarek Merabtene

    2016-01-01

    Full Text Available Although a few studies on rainfall spatial and temporal variability in the UAE have been carried out, evidence of the impact of climate change on rainfall trends has not been reported. This study aims at assessing the significance of long-term rainfall trends and temporal variability at Sharjah City, UAE. Annual rainfall and seasonal rainfall extending over a period of 81 years (1934–2014 recorded at Sharjah International Airport have been analyzed. To this end, several parametric and nonparametric statistical measures have been applied following systematic data quality assessment. The analyses revealed that the annual rainfall trend decreased from −3 mm to −9.4 mm per decade over the study periods. The decreasing annual rainfall trend is mainly driven by the significant drop in winter rainfall, particularly during the period from 1977 to 2014. The results also indicate that high probability extreme events have shifted toward low frequency (12.7 years with significant variations in monthly rainfall patterns and periodicity. The findings of the present study suggest reevaluating the derivation of design rainfall for infrastructure of Sharjah City and urge developing an integrated framework for its water resources planning and risk under climate change impacts scenarios.

  8. Estimation of Fluorescent Dye Amount in Tracer Dye Test

    Science.gov (United States)

    Pekkan, Emrah; Balkan, Erman; Balkan, Emir

    2015-04-01

    Karstic groundwater is more influenced by human than the groundwater that disperse in pores. On the other hand karstic groundwater resources, in addition to providing agricultural needs, livestock breeding, drinking and domestic water in most of the months of the year, they also supply drinking water to the wild life at high altitudes. Therefore sustainability and hydrogeological investigation of karstic resources is critical. Tracing techniques are widely used in hydrologic and hydrogeologic studies to determine water storage, flow rate, direction and protection area of groundwater resources. Karanfil Mountain (2800 m), located in Adana, Turkey, is one of the karstic recharge areas of the natural springs spread around its periphery. During explorations of the caves of Karanfil mountain, a 600 m deep cave was found by the Turkish and Polish cavers. At the bottom of the cave there is an underground river with a flow rate of approximately 0.5 m3/s during August 2014. The main spring is located 8 km far from the cave's entrance and its mean flow rate changes between 3.4 m3/s and 0.21 m3/s in March and September respectively according to a flowrate observation station of Directorate of Water Works of Turkey. As such frequent storms, snowmelt and normal seasonal variations in rainfall have a significant and rapid effect on the volume of this main spring resource. The objective of our research is to determine and estimate dye amount before its application on the field inspired from the previously literature on the subject. This estimation is intended to provide a preliminary application of a tracer test of a karstic system. In this study dye injection, inlet point will be an underground river located inside the cave and the observation station will be the spring that is approximately 8 km far from the cave entrance. On the other hand there is 600 meter elevation difference between cave entrance and outlet spring. In this test Rodamin-WT will be used as tracer and the

  9. Research on the Fine-Scale Spatial Uniformity of Natural Rainfall and Rainfall from a Rainfall Simulator with a Rotary Platform (RSRP)

    National Research Council Canada - National Science Library

    Bo Liu; Xiaolei Wang; Lihua Shi; Xichuan Liu; Zhaojing Kang; Zhentao Chen

    2017-01-01

    ... and the rainfall uniformity was evaluated using the Christiansen Uniformity Coefficient (CU). Simultaneously, factors influencing the spatial uniformity of natural rainfall, including the average rainfall accumulation (RA...

  10. Rainfall Characteristics and Regionalization in Peninsular Malaysia Based on a High Resolution Gridded Data Set

    Directory of Open Access Journals (Sweden)

    Chee Loong Wong

    2016-11-01

    Full Text Available Daily gridded rainfall data over Peninsular Malaysia are delineated using an objective clustering algorithm, with the objective of classifying rainfall grids into groups of homogeneous regions based on the similarity of the rainfall annual cycles. It has been demonstrated that Peninsular Malaysia can be statistically delineated into eight distinct rainfall regions. This delineation is closely associated with the topographic and geographic characteristics. The variation of rainfall over the Peninsula is generally characterized by bimodal variations with two peaks, i.e., a primary peak occurring during the autumn transitional period and a secondary peak during the spring transitional period. The east coast zones, however, showed a single peak during the northeast monsoon (NEM. The influence of NEM is stronger compared to the southwest monsoon (SWM. Significantly increasing rainfall trends at 95% confidence level are not observed in all regions during the NEM, with exception of northwest zone (R1 and coastal band of west coast interior region (R3. During SWM, most areas have become drier over the last three decades. The study identifies higher variation of mean monthly rainfall over the east coast regions, but spatially, the rainfall is uniformly distributed. For the southwestern coast and west coast regions, a larger range of coefficients of variation is mostly obtained during the NEM, and to a smaller extent during the SWM. The inland region received least rainfall in February, but showed the largest spatial variation. The relationship between rainfall and the El Niño Southern Oscillation (ENSO was examined based on the Multivariate ENSO Index (MEI. Although the concurrent relationships between rainfall in the different regions and ENSO are generally weak with negative correlations, the rainfall shows stronger positive correlation with preceding ENSO signals with a time lag of four to eight months.

  11. Statistical framework to simulate daily rainfall series conditional on upper-air predictor variables

    Science.gov (United States)

    Langousis, Andreas; Kaleris, Vassilios

    2014-05-01

    We propose a statistical framework to generate synthetic rainfall time series at daily resolution, conditional on predictor variables indicative of the atmospheric circulation at the mesoscale. We do so by first introducing a dimensionless measure to assess the relative influence of upper-air variables at different pressure levels on ground-level rainfall statistics, and then simulating rainfall occurrence and amount by proper conditioning on the selected atmospheric predictors. The proposed scheme for conditional rainfall simulation operates at a daily time step (avoiding discrete approaches for identification of weather states), can incorporate any possible number and combination of predictor variables, while it is capable of reproducing rainfall seasonality directly from the variation of upper-air variables, without any type of seasonal analysis or modeling. The suggested downscaling approach is tested using atmospheric data from the ERA-Interim archive and daily rainfall measurements from western Greece. The model is found to accurately reproduce several statistics of actual rainfall time series, at both annual and seasonal levels, including wet day fractions, the alternation of wet and dry intervals, the distributions of dry and wet spell lengths, the distribution of rainfall intensities in wet days, short-range dependencies present in historical rainfall records, the distribution of yearly rainfall maxima, dependencies of rainfall statistics on the observation scale, and long-term climatic features present in historical rainfall records. The suggested approach is expected to serve as a useful tool for stochastic rainfall simulation conditional on climate model outputs at a regional level, where climate change impacts and risks are assessed.

  12. Stochastic generation of daily rainfall events based on rainfall pattern classification and Copula-based rainfall characteristics simulation

    Science.gov (United States)

    Xu, Y. P.; Gao, C.

    2016-12-01

    To deal with the problem of having no or insufficiently long rainfall record, developing a stochastic rainfall model is very essential. This study first proposed a stochastic model of daily rainfall events based on classification and simulation of different rainfall patterns, and copula-based joint simulation of rainfall characteristics. Compared with current stochastic rainfall models, this new model not only keeps the dependence structure of rainfall characteristics by using copula functions, but also takes various rainfall patterns that may cause different hydrological responses to watershed into consideration. In order to determine the appropriate number of representative rainfall patterns in an objective way, we also introduced clustering validation measures to the stochastic model. Afterwards, the developed stochastic rainfall model is applied to 39 gauged meteorological stations in Zhejiang province, East China, and is then extended to ungauged stations for validation by applying the self-organizing map (SOM) method. The final results show that the 39 stations can be classified into seven regions that further fall into three categories based on rainfall generation mechanisms, i.e., plum-rain control region, typhoon-rain control region and typhoon-plum-rain compatible region. Rainfall patterns of each station can be classified into five or six types based on clustering validation measures. This study shows that the stochastic rainfall model is robust and can be applied to both gauged and ungauged stations for generating long rainfall record.

  13. Evaluation of Satellite Rainfall Products over NASA's Iowa Flood Studies (IFloodS) Domain

    Science.gov (United States)

    ElSaadani, Mohamed; Quintero, Felipe; Krajewski, Witold F.; Goska, Radoslaw; Seo, Bongchul

    2014-05-01

    Iowa Flood Studies (IFloodS) is a NASA Global Precipitation Measurement (GPM) Mission to provide better understanding of the strengths and limitations of satellite products in the context of hydrologic applications. IFloodS took place in the central to north eastern part of Iowa in Midwestern United States during the months of April-June, 2013. Quantifying the physical characteristics, space/time variability and assessing satellite rainfall retrieval uncertainties at instantaneous to daily time scales are of the main objectives of IFloodS field experiment beside assessing hydrologic predictive skills as a function of space/time scales and discerning the relative roles of rainfall quantities in flood genesis. The errors of rainfall estimation of three satellite rainfall products (TRMM's TMPA 3B42 V7, CPC's CMORPH and CHRS at UCI's PERSIANN) have been characterized in space and time using NCEP Stage IV radar-rainfall product as a benchmark for comparison. The satellite rainfall products used in this study represent 3 hourly, quarter degree, rainfall accumulation. The benchmark rainfall accumulation has an hourly, four kilometers, resolutions in time and space respectively. We also investigate the adequacy of satellite rainfall products as inputs for hydrological modeling. To this end, these products were used as forcing for the Iowa Flood Center (IFC) hydrological model and produced discharge simulations in a high-resolution drainage network. The IFC hydrological model has been validated using radar rainfall product and thus, the hydrological outputs becomes the reference of comparison for the other rainfall products. We evaluated the hydrological performance of the rainfall products at different spatial scales, ranging from 2 to 14,000 square miles using stream discharge information from USGS gauges network. We discuss the adequacy of the rainfall products for flood forecasting at different spatial scales.

  14. Long-term variability of the leading seasonal modes of rainfall in south-eastern Australia

    Directory of Open Access Journals (Sweden)

    Maryam Montazerolghaem

    2016-09-01

    Full Text Available Knowledge of temporal and spatial variability of climate and rainfall can improve agriculture production and can help to manage risks caused by climate variability. Available high-quality monthly rainfall data from the Australian Bureau of Meteorology for 1907–2011 was used to investigate the leading seasonal mode of the long-term rainfall variability over south-eastern and eastern Australia. Spatio-temporal variations of seasonal rainfall and their connection to oceanic-atmospheric predictors were analysed. The links between the first two Principal Components of rainfall of each season with lagged Southern Oscillation Index (SOI, Indian Ocean Dipole (IOD and Southern Annular Mode (SAM were season-dependent. The relationship between these climatic indices changed within both inter-seasonal and decadal time scales. Spring and winter rainfalls were continuously positively correlated with lagged (SOI. However, summer rainfall variations indicated negative correlations with lagged SOI which increase from 1970. The correlations between lagged SOI and autumn variations were weak and change to a stronger relationship from 1990. Correlations between lagged (IOD which varied across all seasons have recently been increasing. Variations in rainfall across all seasons were highly correlated with Southern Annular Mode (SAM with different signs. Overall, the relationship between predictors and seasonal rainfall has changed after 1970. The results of running correlations between leading modes of seasonal rainfall and lagged SOI, SAM, and IOD indices indicates non-stationary in these links. The relationships of climatic indices and leading modes of seasonal rainfall changed since 1970, with stronger evidence in case of IOD. Recent changes in the relationships between climatic indices and rainfall need to be considered in climate prediction systems. The results of this study suggests that improvement in statistical regional rainfall forecast system with fixed

  15. A new approach to modeling tree rainfall interception

    Science.gov (United States)

    Xiao, Qingfu; McPherson, E. Gregory; Ustin, Susan L.; Grismer, Mark E.

    2000-12-01

    A three-dimensional physically based stochastic model was developed to describe canopy rainfall interception processes at desired spatial and temporal resolutions. Such model development is important to understand these processes because forest canopy interception may exceed 59% of annual precipitation in old growth trees. The model describes the interception process from a single leaf, to a branch segment, and then up to the individual tree level. It takes into account rainfall, meteorology, and canopy architecture factors as explicit variables. Leaf and stem surface roughness, architecture, and geometric shape control both leaf drip and stemflow. Model predictions were evaluated using actual interception data collected for two mature open grown trees, a 9-year-old broadleaf deciduous pear tree (Pyrus calleryana "Bradford" or Callery pear) and an 8-year-old broadleaf evergreen oak tree (Quercus suber or cork oak). When simulating 18 rainfall events for the oak tree and 16 rainfall events for the pear tree, the model over estimated interception loss by 4.5% and 3.0%, respectively, while stemflow was under estimated by 0.8% and 3.3%, and throughfall was under estimated by 3.7% for the oak tree and over estimated by 0.3% for the pear tree. A model sensitivity analysis indicates that canopy surface storage capacity had the greatest influence on interception, and interception losses were sensitive to leaf and stem surface area indices. Among rainfall factors, interception losses relative to gross precipitation were most sensitive to rainfall amount. Rainfall incident angle had a significant effect on total precipitation intercepting the projected surface area. Stemflow was sensitive to stem segment and leaf zenith angle distributions. Enhanced understanding of interception loss dynamics should lead to improved urban forest ecosystem management.

  16. Rainfall, runoff and sediment transport in a Mediterranean mountainous catchment.

    Science.gov (United States)

    Tuset, J; Vericat, D; Batalla, R J

    2016-01-01

    The relation between rainfall, runoff, erosion and sediment transport is highly variable in Mediterranean catchments. Their relation can be modified by land use changes and climate oscillations that, ultimately, will control water and sediment yields. This paper analyses rainfall, runoff and sediment transport relations in a meso-scale Mediterranean mountain catchment, the Ribera Salada (NE Iberian Peninsula). A total of 73 floods recorded between November 2005 and November 2008 at the Inglabaga Sediment Transport Station (114.5 km(2)) have been analysed. Suspended sediment transport and flow discharge were measured continuously. Rainfall data was obtained by means of direct rain gauges and daily rainfall reconstructions from radar information. Results indicate that the annual sediment yield (2.3 t km(-1) y(-1) on average) and the flood-based runoff coefficients (4.1% on average) are low. The Ribera Salada presents a low geomorphological and hydrological activity compared with other Mediterranean mountain catchments. Pearson correlations between rainfall, runoff and sediment transport variables were obtained. The hydrological response of the catchment is controlled by the base flows. The magnitude of suspended sediment concentrations is largely correlated with flood magnitude, while sediment load is correlated with the amount of direct runoff. Multivariate analysis shows that total suspended load can be predicted by integrating rainfall and runoff variables. The total direct runoff is the variable with more weight in the equation. Finally, three main hydro-sedimentary phases within the hydrological year are defined in this catchment: (a) Winter, where the catchment produces only water and very little sediment; (b) Spring, where the majority of water and sediment is produced; and (c) Summer-Autumn, when little runoff is produced but significant amount of sediments is exported out of the catchment. Results show as land use and climate change may have an important

  17. Evaluation of rainfall infiltration characteristics in a volcanic ash soil by time domain reflectometry method

    Directory of Open Access Journals (Sweden)

    S. Hasegawa

    1997-01-01

    Full Text Available Time domain reflectometry (TDR was used to monitor soil water conditions and to evaluate infiltration characteristics associated with rainfall into a volcanic-ash soil (Hydric Hapludand with a low bulk density. Four 1 m TDR probes were installed vertically along a 6 m line in a bare field. Three 30 cm and one 60 cm probes were installed between the 1 m probes. Soil water content was measured every half or every hour throughout the year. TDR enabled prediction of the soil water content precisely even though the empirical equation developed by Topp et al. (1980 underestimated the water content. Field capacity, defined as the amount of water stored to a depth of 1 m on the day following heavy rainfall, was 640 mm. There was approximately 100 mm difference in the amount of water stored between field capacity and the driest period. Infiltration characteristics of rainfall were investigated for 36 rainfall events exceeding 10 mm with a total amount of rain of 969 mm out of an annual rainfall of 1192 mm. In the case of 25 low intensity rainfall events with less than 10 mm h-1 on to dry soils, the increase in the amount of water stored to a depth of 1 m was equal to the cumulative rainfall. For rain intensity in excess of 10 mm h-1, non-uniform infiltration occurred. The increase in the amount of water stored at lower elevation locations was 1.4 to 1.6 times larger than at higher elevation locations even though the difference in ground height among the 1 m probes was 6 cm. In the two instances when rainfall exceeded 100 mm, including the amount of rain in a previous rainfall event, the increase in the amount of water stored to a depth of 1 m was 65 mm lower than the total quantity of rain on the two occasions (220 mm; this indicated that 65 mm of water or 5.5% of the annual rainfall had flowed away either by surface runoff or bypass flow. Hence, approximately 95% of the annual rainfall was absorbed by the soil matrix but it is not possible to simulate

  18. Spatial patterns in the oxygen isotope composition of daily rainfall in the British Isles

    Science.gov (United States)

    Tyler, Jonathan J.; Jones, Matthew; Arrowsmith, Carol; Allott, Tim; Leng, Melanie J.

    2016-09-01

    Understanding the modern day relationship between climate and the oxygen isotopic composition of precipitation (δ18OP) is crucial for obtaining rigorous palaeoclimate reconstructions from a variety of archives. To date, the majority of empirical studies into the meteorological controls over δ18OP rely upon daily, event scale, or monthly time series from individual locations, resulting in uncertainties concerning the representativeness of statistical models and the mechanisms behind those relationships. Here, we take an alternative approach by analysing daily patterns in δ18OP from multiple stations across the British Isles ( n = 10-70 stations). We use these data to examine the spatial and seasonal heterogeneity of regression statistics between δ18OP and common predictors (temperature, precipitation amount and the North Atlantic Oscillation index; NAO). Temperature and NAO are poor predictors of daily δ18OP in the British Isles, exhibiting weak and/or inconsistent effects both spatially and between seasons. By contrast δ18OP and rainfall amount consistently correlate at most locations, and for all months analysed, with spatial and temporal variability in the regression coefficients. The maps also allow comparison with daily synoptic weather types, and suggest characteristic δ18OP patterns, particularly associated with Cylonic Lamb Weather Types. Mapping daily δ18OP across the British Isles therefore provides a more coherent picture of the patterns in δ18OP, which will ultimately lead to a better understanding of the climatic controls. These observations are another step forward towards developing a more detailed, mechanistic framework for interpreting stable isotopes in rainfall as a palaeoclimate and hydrological tracer.

  19. A Regenerative Prediction Algorithm for Indian Rainfall Prediction

    Directory of Open Access Journals (Sweden)

    SEEMA MAHAJAN

    2013-11-01

    Full Text Available Rainfall forecasting is critical for the crop planning and water management strategies. Proposed study presents a novel approach for modelling time series precipitation data. The 51 years of Indian rainfall data is used for the development of the model. We use nonlinear predictive code based on 11th order with 240 coefficients. Coefficients are optimized using gradient descendent algorithm. Algorithm is tested using 40 years of rainfall training data. Prediction error tested outside training period is found less than1% for few months. Prediction period is extended to one year by including progressive predicted values in input samples using regenerative feedback algorithm. This model is applied for different training and testing periods with average error of 2% to 10%.

  20. Evaluation of Rainfall-Runoff Models for Mediterranean Subcatchments

    Science.gov (United States)

    Cilek, A.; Berberoglu, S.; Donmez, C.

    2016-06-01

    The development and the application of rainfall-runoff models have been a corner-stone of hydrological research for many decades. The amount of rainfall and its intensity and variability control the generation of runoff and the erosional processes operating at different scales. These interactions can be greatly variable in Mediterranean catchments with marked hydrological fluctuations. The aim of the study was to evaluate the performance of rainfall-runoff model, for rainfall-runoff simulation in a Mediterranean subcatchment. The Pan-European Soil Erosion Risk Assessment (PESERA), a simplified hydrological process-based approach, was used in this study to combine hydrological surface runoff factors. In total 128 input layers derived from data set includes; climate, topography, land use, crop type, planting date, and soil characteristics, are required to run the model. Initial ground cover was estimated from the Landsat ETM data provided by ESA. This hydrological model was evaluated in terms of their performance in Goksu River Watershed, Turkey. It is located at the Central Eastern Mediterranean Basin of Turkey. The area is approximately 2000 km2. The landscape is dominated by bare ground, agricultural and forests. The average annual rainfall is 636.4mm. This study has a significant importance to evaluate different model performances in a complex Mediterranean basin. The results provided comprehensive insight including advantages and limitations of modelling approaches in the Mediterranean environment.

  1. EVALUATION OF RAINFALL-RUNOFF MODELS FOR MEDITERRANEAN SUBCATCHMENTS

    Directory of Open Access Journals (Sweden)

    A. Cilek

    2016-06-01

    Full Text Available The development and the application of rainfall-runoff models have been a corner-stone of hydrological research for many decades. The amount of rainfall and its intensity and variability control the generation of runoff and the erosional processes operating at different scales. These interactions can be greatly variable in Mediterranean catchments with marked hydrological fluctuations. The aim of the study was to evaluate the performance of rainfall-runoff model, for rainfall-runoff simulation in a Mediterranean subcatchment. The Pan-European Soil Erosion Risk Assessment (PESERA, a simplified hydrological process-based approach, was used in this study to combine hydrological surface runoff factors. In total 128 input layers derived from data set includes; climate, topography, land use, crop type, planting date, and soil characteristics, are required to run the model. Initial ground cover was estimated from the Landsat ETM data provided by ESA. This hydrological model was evaluated in terms of their performance in Goksu River Watershed, Turkey. It is located at the Central Eastern Mediterranean Basin of Turkey. The area is approximately 2000 km2. The landscape is dominated by bare ground, agricultural and forests. The average annual rainfall is 636.4mm. This study has a significant importance to evaluate different model performances in a complex Mediterranean basin. The results provided comprehensive insight including advantages and limitations of modelling approaches in the Mediterranean environment.

  2. The Climatology of Taiwan extreme rainfall events and the attributions

    Science.gov (United States)

    Su, S. H.; Kuo, H. C.; Chen, Y. H.; Chu, J. L.; Lin, L. Y.

    2015-12-01

    Taiwan is located in the East-Asian monsoon region with average 2,500mm annual precipitation. Most significant Meteorological disasters are related to extreme precipitation which is associated with a complex terrain. Therefore, the long-term trends or climate variations in precipitation due to climate change are our major concern. We studied the climatology of extreme rainfall (ER, 95thpercentile) events in Taiwan using hourly precipitation data form 21 surface stations during 1960-2014. ER contributes about 40% of the total rain amount. It was found that approximately 68% of ER is related to typhoon (TY) and 22% associated with the Mei-Yu (MY) frontal system. The total ER amount annual variation is strongly related to TY, with correlation coefficient of 0.89 for rainfall amount and 0.86 for frequency. There is a significant increasing trend of TY-ER in past 55 years, but also has large variations over the annual and decadal time scales. The inter-annual variation of astounding extreme rainfall (AER, 99.9thpercentile) is increased significantly, especially in the past 15 years. It implies that the increasing of AER rainfall amount majorly caused by the increasing of frequency instead of average rain intensity of TY-AER. The MY-ER events are also highly correlated with the frontal system. The correlation is 0.84 for the rainfall amount and 0.83 of the frequency with the frontal days. There are also strong inter-annual variations of MY-ER, but the long-term trends are not as significant as TY-ER. The variation of frontal system number is another parameter may impact the MY-ER. The observational frontal system numbers had positive correlation with the MY-ER. The attribution of Taiwan TY-ER changes was debated in the research community. In general, the public acceptance of Taiwan extreme precipitation events is affected by multi-scale systems. According to observational data, the increasing of TY-ER amount is 37 % (48% )in Taiwan and some resent studies (Wang et al

  3. Quantitative analysis of torrential rainfall associated with typhoon landfall: A case study of typhoon Haitang (2005)

    Institute of Scientific and Technical Information of China (English)

    Caijun Yue

    2009-01-01

    A quantitative analysis of torrential rainfall associated with typhoon Haitang (2005) is carried out using a modified moist ageostrophic Q vector and data from Weather Research and Forecasting (WRF) model simulation.Four major factors determining the ascending motion associated with torrential rainfall have been studied:large-scale and convective condensational heating,topographic lifting and friction.The results show that the convective condensational heating plays a major role in the torrential rainfall process,and the large-scale condensational heating is secondary before the landfall of typhoon Haitang,and vice versa after the landfall.The topographic lifting affects the formation of rainfall,whereas the topographic friction has important impacts on torrential rainfall after the landfall.The rainfall amounts forced by the topographic friction and lifting have similar horizontal distributions,but the magnitudes of the former are 2-3 times larger than those of the latter.The rainfall amounts forced by topography (lifting and friction) and modified moist ageostrophic Q vector have different horizontal distributions,and the magnitudes of the former are 2-5 times larger than those of the latter.Synthetic analysis shows that the typhoon rainfall may be motivated by modified moist ageostrophic Q vector and enhanced further by the topographic effects.

  4. A rainfall design method for spatial flood risk assessment: considering multiple flood sources

    Science.gov (United States)

    Jiang, X.; Tatano, H.

    2015-08-01

    Information about the spatial distribution of flood risk is important for integrated urban flood risk management. Focusing on urban areas, spatial flood risk assessment must reflect all risk information derived from multiple flood sources: rivers, drainage, coastal flooding etc. that may affect the area. However, conventional flood risk assessment deals with each flood source independently, which leads to an underestimation of flood risk in the floodplain. Even in floodplains that have no risk from coastal flooding, flooding from river channels and inundation caused by insufficient drainage capacity should be considered simultaneously. For integrated flood risk management, it is necessary to establish a methodology to estimate flood risk distribution across a floodplain. In this paper, a rainfall design method for spatial flood risk assessment, which considers the joint effects of multiple flood sources, is proposed. The concept of critical rainfall duration determined by the concentration time of flooding is introduced to connect response characteristics of different flood sources with rainfall. A copula method is then adopted to capture the correlation of rainfall amount with different critical rainfall durations. Rainfall events are designed taking advantage of the copula structure of correlation and marginal distribution of rainfall amounts within different critical rainfall durations. A case study in the Otsu River Basin, Osaka prefecture, Japan was conducted to demonstrate this methodology.

  5. A rainfall design method for spatial flood risk assessment: considering multiple flood sources

    Directory of Open Access Journals (Sweden)

    X. Jiang

    2015-08-01

    Full Text Available Information about the spatial distribution of flood risk is important for integrated urban flood risk management. Focusing on urban areas, spatial flood risk assessment must reflect all risk information derived from multiple flood sources: rivers, drainage, coastal flooding etc. that may affect the area. However, conventional flood risk assessment deals with each flood source independently, which leads to an underestimation of flood risk in the floodplain. Even in floodplains that have no risk from coastal flooding, flooding from river channels and inundation caused by insufficient drainage capacity should be considered simultaneously. For integrated flood risk management, it is necessary to establish a methodology to estimate flood risk distribution across a floodplain. In this paper, a rainfall design method for spatial flood risk assessment, which considers the joint effects of multiple flood sources, is proposed. The concept of critical rainfall duration determined by the concentration time of flooding is introduced to connect response characteristics of different flood sources with rainfall. A copula method is then adopted to capture the correlation of rainfall amount with different critical rainfall durations. Rainfall events are designed taking advantage of the copula structure of correlation and marginal distribution of rainfall amounts within different critical rainfall durations. A case study in the Otsu River Basin, Osaka prefecture, Japan was conducted to demonstrate this methodology.

  6. A Multi-Scale Analysis of Namibian Rainfall: Comparing TRMM Satellite Data and Ground Observations

    Science.gov (United States)

    Lu, X.; Wang, L.; Pan, M.; Kaseke, K. F.

    2014-12-01

    Rainfall is critically important in dryland regions, as it is the major source of water for natural vegetation as well as agriculture and livestock production. However, the lack of ground observations has long been a major obstacle to the study of rainfall patterning in drylands. In this study, a continuous 6-year record of ground observations collected at Weltevrede Guest Farm Namibia was used to evaluate the Tropical Rainfall Measuring Mission (TRMM) 0.25-degree (~25 km) 3-hourly satellite rainfall estimates for the period of 2008-2013 for two locations. The agreement between ground and satellite rainfall data was generally good at annual scales but a large variation was observed at the hourly scale. A trend analysis was carried out using bias-corrected annual satellite data (1998-2013) to examine the long-term patterns in rainfall amount, intensity, frequency and seasonal variations. Our results suggest that satellite rainfall estimates offer reasonable performance at annual scale. The preliminary trend analyses showed significant changes in frequency, but not in intensity or total amount in one of the two locations during the rainy season (November - March), but not in the other, emphasizing the spatial variability of the dryland rainfall.

  7. Chapman Conference on Rainfall Fields

    Science.gov (United States)

    Gupta, V. K.

    The Chapman Conference on Rainfall Fields, sponsored by AGU, was the first of its kind; it was devoted to strengthening scientific interaction between the North American and Latin American geophysics communities. It was hosted by Universidad Simon Bolivar and Instituto Internacional de Estudios Avanzados, in Caracas, Venezuela, during March 24-27, 1986. A total of 36 scientists from Latin America, the United States, Canada, and Europe participated. The conference, which was convened by I. Rodriguez-Iturbe (Universidad Simon Bolivar) and V. K. Gupta (University of Mississippi, University), brought together hydrologists, meteorologists, and mathematicians/statisticians in the name of enhancing an interdisciplinary focus on rainfall research.

  8. Rainfall simulation for environmental application

    Energy Technology Data Exchange (ETDEWEB)

    Shriner, D.S.; Abner, C.H.; Mann, L.K.

    1977-08-01

    Rain simulation systems have been designed for field and greenhouse studies which have the capability of reproducing the physical and chemical characteristics of natural rainfall. The systems permit the simulation of variations in rainfall and droplet size similar to that of natural precipitation. The systems are completely automatic and programmable, allowing unattended operation for periods of up to one week, and have been used to expose not only vegetation but also soils and engineering materials, making them versatile tools for studies involving simulated precipitation.

  9. A Case Study of Bivariate Rainfall Frequency Analysis Using Copula in South Korea

    Science.gov (United States)

    Joo, K.; Shin, J.; Kim, W.; Heo, J.

    2011-12-01

    For a given rainfall event, it can be characterized into some properties such as rainfall depth (amount), duration, and intensity. By considering these factors simultaneously, the actual phenomenon of rainfall event can be explained better than univariate model. Using bivariate model, rainfall quantiles can be obtained for a given return period without any limitations of specific rainfall duration. For bivariate(depth and duration) frequency analysis, copula model was used in this study. Recently, copula model has been studied widely for hydrological field. And it is more flexible for marginal distribution than other conventional bivariate models. In this study, five weather stations are applied for frequency analysis from Korea Meteorological Administration (KMA) which are Seoul, Chuncheon, Gangneung, Wonju, and Chungju stations. These sites have 38 ~ 50 years of hourly precipitation data. Inter-event time definition is used for identification of rainfall events. And three copula models (Gumbel-Hougaard, Frank, and Joe) are applied in this study. Maximum pseudo-likelihood estimation method is used to estimate the parameter of copula (θ). The normal, generalized extreme value, Gumbel, 3-parameter gamma, and generalized logistic distributions are examined for marginal distribution. As a result, rainfall quantiles can be obtained for any rainfall durations for a given return period by calculating conditional probability. In addition, rainfall quantiles from copula models are compared to those from univariate model.

  10. Critical rainfall thresholds for triggering shallow landslides in the Serchio River Valley (Tuscany, Italy

    Directory of Open Access Journals (Sweden)

    R. Giannecchini

    2012-03-01

    Full Text Available The Serchio River Valley, in north-western Tuscany, is a well-known tourism area between the Apuan Alps and the Apennines. This area is frequently hit by heavy rainfall, which often triggers shallow landslides, debris flows and debris torrents, sometimes causing damage and death. The assessment of the rainfall thresholds for the initiation of shallow landslides is very important in order to improve forecasting and to arrange efficient alarm systems.

    With the aim of defining the critical rainfall thresholds for the Middle Serchio River Valley, a detailed analysis of the main rainstorm events was carried out. The hourly rainfall recorded by three rain gauges in the 1935–2010 interval was analysed and compared with the occurrence of shallow landslides. The rainfall thresholds were defined in terms of mean intensity I, rainfall duration D, and normalized using the mean annual precipitation. Some attempts were also carried out to analyze the role of rainfall prior to the damaging events. Finally, the rainfall threshold curves obtained for the study area were compared with the local, regional and global curves proposed by various authors. The results of this analysis suggest that in the study area landslide activity initiation requires a higher amount of rainfall and greater intensity than elsewhere.

  11. Rainfall variation and child health: effect of rainfall on diarrhea among under 5 children in Rwanda, 2010.

    Science.gov (United States)

    Mukabutera, Assumpta; Thomson, Dana; Murray, Megan; Basinga, Paulin; Nyirazinyoye, Laetitia; Atwood, Sidney; Savage, Kevin P; Ngirimana, Aimable; Hedt-Gauthier, Bethany L

    2016-08-05

    Diarrhea among children under 5 years of age has long been a major public health concern. Previous studies have suggested an association between rainfall and diarrhea. Here, we examined the association between Rwandan rainfall patterns and childhood diarrhea and the impact of household sanitation variables on this relationship. We derived a series of rain-related variables in Rwanda based on daily rainfall measurements and hydrological models built from daily precipitation measurements collected between 2009 and 2011. Using these data and the 2010 Rwanda Demographic and Health Survey database, we measured the association between total monthly rainfall, monthly rainfall intensity, runoff water and anomalous rainfall and the occurrence of diarrhea in children under 5 years of age. Among the 8601 children under 5 years of age included in the survey, 13.2 % reported having diarrhea within the 2 weeks prior to the survey. We found that higher levels of runoff were protective against diarrhea compared to low levels among children who lived in households with unimproved toilet facilities (OR = 0.54, 95 % CI: [0.34, 0.87] for moderate runoff and OR = 0.50, 95 % CI: [0.29, 0.86] for high runoff) but had no impact among children in household with improved toilets. Our finding that children in households with unimproved toilets were less likely to report diarrhea during periods of high runoff highlights the vulnerabilities of those living without adequate sanitation to the negative health impacts of environmental events.

  12. Research on the Fine-Scale Spatial Uniformity of Natural Rainfall and Rainfall from a Rainfall Simulator with a Rotary Platform (RSRP)

    OpenAIRE

    Bo Liu; Xiaolei Wang; Lihua Shi; Xichuan Liu; Zhaojing Kang; Zhentao Chen

    2017-01-01

    Abstract: The accurate production of a rainfall environment similar to natural rainfall by a rainfall simulator (RS) is a crucial and challenging task in rainfall instrument testing or calibration. Although the spatial uniformity of rainfall accumulation is a key parameter of an RS, the spatial uniformity comparison between simulated rainfall and natural rainfall, and the spatial uniformity improvements for an RS are scant in the literature. In this study, a fine-scale natural rainfall experi...

  13. Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique

    Science.gov (United States)

    Tote, Carolien; Patricio, Domingos; Boogaard, Hendrik; van der Wijngaart, Raymond; Tarnavsky, Elena; Funk, Christopher C.

    2015-01-01

    Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001–2012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

  14. Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

    Directory of Open Access Journals (Sweden)

    Carolien Toté

    2015-02-01

    Full Text Available Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT v2.0, Famine Early Warning System NETwork (FEWS NET Rainfall Estimate (RFE v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS are compared to independent gauge data (2001–2012. This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

  15. Where do forests influence rainfall?

    Science.gov (United States)

    Wang-Erlandsson, Lan; van der Ent, Ruud; Fetzer, Ingo; Keys, Patrick; Savenije, Hubert; Gordon, Line

    2017-04-01

    Forests play a major role in hydrology. Not only by immediate control of soil moisture and streamflow, but also by regulating climate through evaporation (i.e., transpiration, interception, and soil evaporation). The process of evaporation travelling through the atmosphere and returning as precipitation on land is known as moisture recycling. Whether evaporation is recycled depends on wind direction and geography. Moisture recycling and forest change studies have primarily focused on either one region (e.g. the Amazon), or one biome type (e.g. tropical humid forests). We will advance this via a systematic global inter-comparison of forest change impacts on precipitation depending on both biome type and geographic location. The rainfall effects are studied for three contemporary forest changes: afforestation, deforestation, and replacement of mature forest by forest plantations. Furthermore, as there are indications in the literature that moisture recycling in some places intensifies during dry years, we will also compare the rainfall impacts of forest change between wet and dry years. We model forest change effects on evaporation using the global hydrological model STEAM and trace precipitation changes using the atmospheric moisture tracking scheme WAM-2layers. This research elucidates the role of geographical location of forest change driven modifications on rainfall as a function of the type of forest change and climatic conditions. These knowledge gains are important at a time of both rapid forest and climate change. Our conclusions nuance our understanding of how forests regulate climate and pinpoint hotspot regions for forest-rainfall coupling.

  16. Detecting changes in rainfall pattern and seasonality index vis-à-vis increasing water scarcity in Maharashtra

    Indian Academy of Sciences (India)

    Pulak Guhathakurta; Elizabeth Saji

    2013-06-01

    Knowledge of mean rainfall and its variability of smaller spatial scale are important for the planners in various sectors including water and agriculture. In the present work, long rainfall data series (1901–2006) of districts of Maharashtra in monthly and seasonal scales are constructed and then mean rainfall and coefficient of variability are analyzed to get the spatial pattern and variability. Significant long term changes in monthly rainfall in the district scale are identified by trend analysis of rainfall time series. The seasonality index which is the measure of distribution of precipitation throughout the seasonal cycle is used to classify the different rainfall regime. Also long term changes of the seasonality index are identified by the trend analysis. The state Maharashtra which is to the northwest of peninsular India is highly influenced by the southwest monsoon and the state is facing water scarcity almost every year. This study will help to find out possible reason for the increasing water scarcity in Maharashtra.

  17. Quantifying uncertainty in observational rainfall datasets

    Science.gov (United States)

    Lennard, Chris; Dosio, Alessandro; Nikulin, Grigory; Pinto, Izidine; Seid, Hussen

    2015-04-01

    rainfall datasets available over Africa on monthly, daily and sub-daily time scales as appropriate to quantify spatial and temporal differences between the datasets. We find regional wet and dry biases between datasets (using the ensemble mean as a reference) with generally larger biases in reanalysis products. Rainfall intensity is poorly represented in some datasets which demonstrates some datasets should not be used for rainfall intensity analyses. Using 10 CORDEX models we show in east Africa that the spread between observed datasets is often similar to the spread between models. We recommend that specific observational rainfall datasets datasets be used for specific investigations and also that where many datasets are applicable to an investigation, a probabilistic view be adopted for rainfall studies over Africa. Endris, H. S., P. Omondi, S. Jain, C. Lennard, B. Hewitson, L. Chang'a, J. L. Awange, A. Dosio, P. Ketiem, G. Nikulin, H-J. Panitz, M. Büchner, F. Stordal, and L. Tazalika (2013) Assessment of the Performance of CORDEX Regional Climate Models in Simulating East African Rainfall. J. Climate, 26, 8453-8475. DOI: 10.1175/JCLI-D-12-00708.1 Gbobaniyi, E., A. Sarr, M. B. Sylla, I. Diallo, C. Lennard, A. Dosio, A. Dhie ?diou, A. Kamga, N. A. B. Klutse, B. Hewitson, and B. Lamptey (2013) Climatology, annual cycle and interannual variability of precipitation and temperature in CORDEX simulations over West Africa. Int. J. Climatol., DOI: 10.1002/joc.3834 Hernández-Díaz, L., R. Laprise, L. Sushama, A. Martynov, K. Winger, and B. Dugas (2013) Climate simulation over CORDEX Africa domain using the fifth-generation Canadian Regional Climate Model (CRCM5). Clim. Dyn. 40, 1415-1433. DOI: 10.1007/s00382-012-1387-z Kalognomou, E., C. Lennard, M. Shongwe, I. Pinto, A. Favre, M. Kent, B. Hewitson, A. Dosio, G. Nikulin, H. Panitz, and M. Büchner (2013) A diagnostic evaluation of precipitation in CORDEX models over southern Africa. Journal of Climate, 26, 9477-9506. DOI:10

  18. Synthesis of rainfall time series in a high temporal resolution

    Science.gov (United States)

    Callau Poduje, Ana Claudia; Haberlandt, Uwe

    2014-05-01

    In order to optimize the design and operation of urban drainage systems, long and continuous rain series in a high temporal resolution are essential. As the length of the rainfall records is often short, particularly the data available with the temporal and regional resolutions required for urban hydrology, it is necessary to find some numerical representation of the precipitation phenomenon to generate long synthetic rainfall series. An Alternating Renewal Model (ARM) is applied for this purpose, which consists of two structures: external and internal. The former is the sequence of wet and dry spells, described by their durations which are simulated stochastically. The internal structure is characterized by the amount of rain corresponding to each wet spell and its distribution within the spell. A multivariate frequency analysis is applied to analyze the internal structure of the wet spells and to generate synthetic events. The stochastic time series must reproduce the statistical characteristics of observed high resolution precipitation measurements used to generate them. The spatio-temporal interdependencies between stations are addressed by resampling the continuous synthetic series based on the Simulated Annealing (SA) procedure. The state of Lower-Saxony and surrounding areas, located in the north-west of Germany is used to develop the ARM. A total of 26 rainfall stations with high temporal resolution records, i.e. rainfall data every 5 minutes, are used to define the events, find the most suitable probability distributions, calibrate the corresponding parameters, simulate long synthetic series and evaluate the results. The length of the available data ranges from 10 to 20 years. The rainfall series involved in the different steps of calculation are compared using a rainfall-runoff model to simulate the runoff behavior in urban areas. The EPA Storm Water Management Model (SWMM) is applied for this evaluation. The results show a good representation of the

  19. Changes in Convective Rainfall in future climates over Western Europe.

    Science.gov (United States)

    Gadian, A.; Burton, R.; Blyth, A. M.; Mobbs, S.; Warner, J.; Groves, J.; Holland, G. J.; Bruyere, C. L.; Done, J.; Tye, M. R.; Thielen, J.

    2016-12-01

    This project aims to analyse extreme convective weather events over the European domain in a future climate scenario using the Weather Research Forecasting model (WRF). Climate models have insufficient resolution to properly simulate small meso-scale precipitation events which are critical in understanding climate change. Use of a weather model is specifically designed to resolve small (and large) scale processes and in particular to be convection permitting. Changes in extreme weather events in the future climate can be represented as small scale processes and regional meso-scale precipitation events. A channel outer domain (D01), with a resolution of 20km at +/-300 N/S and 8km at 680N, drives a one way nested inner domain resolution which is a factor of 5:1 smaller. For calibration purposes, the outer domain is driven at the Northern / Southern boundaries either by ERA-interim or bias corrected data CCSM for 1989-1995. For the future simulations, the outer domain is driven by CCSM data for 2020-2025 and 2030-2035. An initial analysis for the inner domain convection over Western Europe will be presented. This presentation will provide details of the project. An inter-comparison of the simulations driven for 1990-1995 will provide information on the applicability of using the climate data driven results for the analysis of the future years. Initial plots of changes in precipitation over the future decades will focus on the summer precipitation, providing mean and standard deviation changes. The results indicate that the summer months are dryer, the wet events become shorter, with longer dry periods. The peak precipitation for the events does not increase, but the average rainfall and the amount of heavy rain (>7.6mm / hour) does increase. Future plans for use of the data will be discussed. Use the output data to drive the EFAS (European Flood model) to examine the predicted changes in quantity and frequency of severe and hazardous convective rainfall events and

  20. Forecasting paediatric malaria admissions on the Kenya Coast using rainfall.

    Science.gov (United States)

    Karuri, Stella Wanjugu; Snow, Robert W

    2016-01-01

    Malaria is a vector-borne disease which, despite recent scaled-up efforts to achieve control in Africa, continues to pose a major threat to child survival. The disease is caused by the protozoan parasite Plasmodium and requires mosquitoes and humans for transmission. Rainfall is a major factor in seasonal and secular patterns of malaria transmission along the East African coast. The goal of the study was to develop a model to reliably forecast incidences of paediatric malaria admissions to Kilifi District Hospital (KDH). In this article, we apply several statistical models to look at the temporal association between monthly paediatric malaria hospital admissions, rainfall, and Indian Ocean sea surface temperatures. Trend and seasonally adjusted, marginal and multivariate, time-series models for hospital admissions were applied to a unique data set to examine the role of climate, seasonality, and long-term anomalies in predicting malaria hospital admission rates and whether these might become more or less predictable with increasing vector control. The proportion of paediatric admissions to KDH that have malaria as a cause of admission can be forecast by a model which depends on the proportion of malaria admissions in the previous 2 months. This model is improved by incorporating either the previous month's Indian Ocean Dipole information or the previous 2 months' rainfall. Surveillance data can help build time-series prediction models which can be used to anticipate seasonal variations in clinical burdens of malaria in stable transmission areas and aid the timing of malaria vector control.

  1. Prediction of seasonal summer monsoon rainfall over homogenous regions of India using dynamical prediction system

    Science.gov (United States)

    Ramu, Dandi A.; Rao, Suryachadra A.; Pillai, Prasanth A.; Pradhan, M.; George, G.; Rao, D. Nagarguna; Mahapatra, S.; Pai, D. S.; Rajeevan, M.

    2017-03-01

    Seasonal prediction of Indian summer monsoon rainfall is a challenging task for the modeling community and predicting seasonal mean rainfall at smaller regional scale is much more difficult than predicting all India averaged seasonal mean rainfall. The regional scale prediction of summer monsoon mean rainfall at longer lead time (e.g., predicting 3-4 months in advance) can play a vital role in planning of hydrological and agriculture aspects of the society. Previous attempts for predicting seasonal mean rainfall at regional level (over 5 Homogeneous regions) have resulted with limited success (anomaly correlation coefficient is low, ACC ≈ 0.1-0.4, even at a short lead time of one month). The high resolution Climate Forecast System, version 2 (CFSv2) model, with spectral resolution of T382 (∼38 km), can predict the Indian summer monsoon rainfall (ISMR) at lead time of 3-4 months, with a reasonably good prediction skill (ACC ≈ 0.55). In the present study, we have investigated whether the seasonal mean rainfall over different homogenous regions is predictable using the same model, at 3-4 months lead time? Out of five homogeneous regions of India three regions have shown moderate prediction skill, even at 3 months lead time. Compared to lower resolution model, high resolution model has good skill for all the regions except south peninsular India. High resolution model is able to capture the extreme events and also the teleconnections associated with large scale features at four months lead time and hence shows better skill (ACC ≈ 0.45) in predicting the seasonal mean rainfall over homogeneous regions.

  2. A Web Architecture to Geographically Interrogate CHIRPS Rainfall and eMODIS NDVI for Land Use Change

    Science.gov (United States)

    Burks, Jason E.; Limaye, Ashutosh

    2014-01-01

    Monitoring of rainfall and vegetation over the continent of Africa is important for assessing the status of crop health and agriculture, along with long-term changes in land use change. These issues can be addressed through examination of long-term precipitation (rainfall) data sets and remote sensing of land surface vegetation and land use types. Two products have been used previously to address these goals: the Climate Hazard Group Infrared Precipitation with Stations (CHIRPS) rainfall data, and multi-day composites of Normalized Difference Vegetation Index (NDVI) from the USGS eMODIS product. Combined, these are very large data sets that require unique tools and architecture to facilitate a variety of data analysis methods or data exploration by the end user community. To address these needs, a web-enabled system has been developed to allow end-users to interrogate CHIRPS rainfall and eMODIS NDVI data over the continent of Africa. The architecture allows end-users to use custom defined geometries, or the use of predefined political boundaries in their interrogation of the data. The massive amount of data interrogated by the system allows the end-users with only a web browser to extract vital information in order to investigate land use change and its causes. The system can be used to generate daily, monthly and yearly averages over a geographical area and range of dates of interest to the user. It also provides analysis of trends in precipitation or vegetation change for times of interest. The data provided back to the end-user is displayed in graphical form and can be exported for use in other, external tools. The development of this tool has significantly decreased the investment and requirements for end-users to use these two important datasets, while also allowing the flexibility to the end-user to limit the search to the area of interest.

  3. Modifying rainfall patterns in a Mediterranean shrubland: system design, plant responses, and experimental burning

    Science.gov (United States)

    Parra, Antonio; Ramírez, David A.; Resco, Víctor; Velasco, Ángel; Moreno, José M.

    2012-11-01

    Global warming is projected to increase the frequency and intensity of droughts in the Mediterranean region, as well as the occurrence of large fires. Understanding the interactions between drought, fire and plant responses is therefore important. In this study, we present an experiment in which rainfall patterns were modified to simulate various levels of drought in a Mediterranean shrubland of central Spain dominated by Cistus ladanifer, Erica arborea and Phillyrea angustifolia. A system composed of automatic rainout shelters with an irrigation facility was used. It was designed to be applied in vegetation 2 m tall, treat relatively large areas (36 m2), and be quickly dismantled to perform experimental burning and reassembled back again. Twenty plots were subjected to four rainfall treatments from early spring: natural rainfall, long-term average rainfall (2 months drought), moderate drought (25% reduction from long-term rainfall, 5 months drought) and severe drought (45% reduction, 7 months drought). The plots were burned in late summer, without interfering with rainfall manipulations. Results indicated that rainfall manipulations caused differences in soil moisture among treatments, leading to reduced water availability and growth of C. ladanifer and E. arborea in the drought treatments. However, P. angustifolia was not affected by the manipulations. Rainout shelters had a negligible impact on plot microenvironment. Experimental burns were of high fire intensity, without differences among treatments. Our system provides a tool to study the combined effects of drought and fire on vegetation, which is important to assess the threats posed by climate change in Mediterranean environments.

  4. El-Niño southern oscillation and rainfall erosivity in the headwater region of the Grande River Basin, Southeast Brazil

    Directory of Open Access Journals (Sweden)

    C. R. Mello

    2011-12-01

    Full Text Available Relationships between regional climate and oceanic and atmospheric anomalies are important tools in order to promote the development of models for predicting rainfall erosivity, especially in regions with substantial intra-annual variability in the rainfall regime. In this context, this work aimed to analyze the rainfall erosivity in headwaters of Grande River Basin, Southern Minas Gerais State, Brazil. This study considered the two most representative environments, the Mantiqueira Range (MR and Plateau of Southern Minas Gerais (PSM. These areas are affected by the El Nino Southern Oscillation (ENSO indicators Sea Surface Temperature (SST for Niño 3.4 Region and Multivariate ENSO Index (MEI. Rainfall erosivity was calculated for individual rainfall events from January 2006 to December 2010. The analyses were conducted using the monthly data of ENSO indicators and the following rainfall variables: rainfall erosivity (EI30, rainfall depth (P, erosive rainfall depth (E, number of rainfall events (NRE, number of erosive rainfall events (NEE, frequency of occurrence of an early rainfall pattern (EP, occurrence of late rainfall pattern (LP and occurrence of intermediate rainfall patter (IP. Pearson's coefficient of correlation was used to evaluate the relationships between the rainfall variables and SST and MEI. The coefficients of correlation were significant for SST in the PSM sub-region. Correlations between the rainfall variables and negative oscillations of SST were also significant, especially in the MR sub-region, however, the Person's coefficients were lesser than those obtained for the SST positive oscillations. The correlations between the rainfall variables and MEI were also significant but lesser than the SST correlations. These results demonstrate that SST positive oscillations play a more important role in rainfall erosivity, meaning they were more influenced by El-Niño episodes. Also, these results have shown

  5. Trends in rainfall erosivity in NE Spain at annual, seasonal and daily scales, 1955–2006

    Directory of Open Access Journals (Sweden)

    S. Beguería

    2012-10-01

    Full Text Available Rainfall erosivity refers to the ability of precipitation to erode soil, and depends on characteristics such as its total volume, duration, and intensity and amount of energy released by raindrops. Despite the relevance of rainfall erosivity for soil degradation prevention, very few studies have addressed its spatial and temporal variability. In this study the time variation of rainfall erosivity in the Ebro Valley (NE Spain is assessed for the period 1955–2006. The results show a general decrease in annual and seasonal rainfall erosivity, which is explained by a decrease of very intense rainfall events whilst the frequency of moderate and low events increased. This trend is related to prevailing positive conditions of the main atmospheric teleconnection indices affecting the West Mediterranean, i.e. the North Atlantic Oscillation (NAO, the Mediterranean Oscillation (MO and the Western Mediterranean Oscillation (WeMO.

  6. Road accidents and rainfall in a large Australian city.

    Science.gov (United States)

    Keay, Kevin; Simmonds, Ian

    2006-05-01

    We investigate the impact of rainfall on daily road accidents in the metropolitan area of Melbourne, Australia, over 1987-2002. Our analysis from several viewpoints of the accident count, which has been normalised for variation in traffic volume, indicated that the effect of rainfall is multifaceted. Owing to a large non-linear trend a subdivision into three epochs (1987-1991, 1992-1996 and 1997-2002) was made. Nominal daytime and nighttime as well as 3h raw counts were available for the first two epochs only. Generally, the effect of rainfall across the epochs shows a tendency for larger values in autumn with smaller values in spring. For the daily, daytime and nighttime cases there is an approximate 40% decrease in both the volume-normalised dry and wet means from the first to second epoch. Since the second epoch is wetter than the first, and both dry and wet cases are affected in a similar way, then it appears that a non-weather influence is at work. It is suggested that law enforcement measures may be largely responsible. We obtained a conservative estimate of relative risk of an accident in wet conditions based on a matched-pair analysis of 3h dry and wet periods over the first two epochs (1987-1996). As with other studies we find that the risk is greater than unity in almost all cases suggesting that the presence of rainfall consistently represents a driving hazard. Rainfall occurring after a dry spell has an enhanced effect on the volume-normalised accident count as the spell duration increases. The effect of dry spells is more clearly described when broken down by rain class. Generally, there is an increase in the impact of a dry spell when it first rains as the spell duration and rainfall amount increase.

  7. Stochastic modelling of daily rainfall sequences

    NARCIS (Netherlands)

    Buishand, T.A.

    1977-01-01

    Rainfall series of different climatic regions were analysed with the aim of generating daily rainfall sequences. A survey of the data is given in I, 1. When analysing daily rainfall sequences one must be aware of the following points:
    a. Seasonality. Because of seasonal variation

  8. Sampling errors for satellite-derived tropical rainfall - Monte Carlo study using a space-time stochastic model

    Science.gov (United States)

    Bell, Thomas L.; Abdullah, A.; Martin, Russell L.; North, Gerald R.

    1990-01-01

    Estimates of monthly average rainfall based on satellite observations from a low earth orbit will differ from the true monthly average because the satellite observes a given area only intermittently. This sampling error inherent in satellite monitoring of rainfall would occur even if the satellite instruments could measure rainfall perfectly. The size of this error is estimated for a satellite system being studied at NASA, the Tropical Rainfall Measuring Mission (TRMM). First, the statistical description of rainfall on scales from 1 to 1000 km is examined in detail, based on rainfall data from the Global Atmospheric Research Project Atlantic Tropical Experiment (GATE). A TRMM-like satellite is flown over a two-dimensional time-evolving simulation of rainfall using a stochastic model with statistics tuned to agree with GATE statistics. The distribution of sampling errors found from many months of simulated observations is found to be nearly normal, even though the distribution of area-averaged rainfall is far from normal. For a range of orbits likely to be employed in TRMM, sampling error is found to be less than 10 percent of the mean for rainfall averaged over a 500 x 500 sq km area.

  9. Spatiotemporal Scaling Effect on Rainfall Network Design Using Entropy

    Directory of Open Access Journals (Sweden)

    Chiang Wei

    2014-08-01

    Full Text Available Because of high variation in mountainous areas, rainfall data at different spatiotemporal scales may yield potential uncertainty for network design. However, few studies focus on the scaling effect on both the spatial and the temporal scale. By calculating the maximum joint entropy of hourly typhoon events, monthly, six dry and wet months and annual rainfall between 1992 and 2012 for 1-, 3-, and 5-km grids, the relocated candidate rain gauges in the National Taiwan University Experimental Forest of Central Taiwan are prioritized. The results show: (1 the network exhibits different locations for first prioritized candidate rain gauges for different spatiotemporal scales; (2 the effect of spatial scales is insignificant compared to temporal scales; and (3 a smaller number and a lower percentage of required stations (PRS reach stable joint entropy for a long duration at finer spatial scale. Prioritized candidate rain gauges provide key reference points for adjusting the network to capture more accurate information and minimize redundancy.

  10. Multiple linear regression models of urban runoff pollutant load and event mean concentration considering rainfall variables.

    Science.gov (United States)

    Maniquiz, Marla C; Lee, Soyoung; Kim, Lee-Hyung

    2010-01-01

    Rainfall is an important factor in estimating the event mean concentration (EMC) which is used to quantify the washed-off pollutant concentrations from non-point sources (NPSs). Pollutant loads could also be calculated using rainfall, catchment area and runoff coefficient. In this study, runoff quantity and quality data gathered from a 28-month monitoring conducted on the road and parking lot sites in Korea were evaluated using multiple linear regression (MLR) to develop equations for estimating pollutant loads and EMCs as a function of rainfall variables. The results revealed that total event rainfall and average rainfall intensity are possible predictors of pollutant loads. Overall, the models are indicators of the high uncertainties of NPSs; perhaps estimation of EMCs and loads could be accurately obtained by means of water quality sampling or a long-term monitoring is needed to gather more data that can be used for the development of estimation models.

  11. Identification and Diagnosis of Rainfall Types over Southern West Africa Using Satellite and Rain Gauge Data

    Science.gov (United States)

    Maranan, Marlon; Fink, Andreas H.; Amekudzi, Leonard K.; Atiah, Winifred A.

    2017-04-01

    Rainfall over Southern West Africa (SWA) is mainly controlled by the West African Monsoon circulation. Not much is known, however, about the (thermo-)dynamic environmental conditions and storm dynamics of various regional rainfall systems that contribute to the total annual rainfall. This study exploits both satellite and rain gauge measurements to quantify the contribution and to examine the importance of different rainfall types in SWA. For the period of the Tropical Rainfall Measuring Mission (TRMM) 1998-2014, the rainfall types are identified by analyzing the 3-D reflectivity structure using scans of the TRMM Precipitation Radar (TRMM-PR). Since TRMM-PR scans only provide instantaneous snapshots, the rainfall events are then traced back and forward in time with observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) over the overlapping period of 2004-2014 to obtain information about their life cycle. The composition of the ensemble of the different rainfall types exhibits a substantial regional variability across SWA. Strong convection (Radar echo > 40 dBZ) generally makes a dominant contribution to the number of rainfall events and to the total rainfall amount. However, the influence of deeper (40 dBZ echo at altitudes > 10 km) and wider (Area of 40 dBZ echo > 1000 km2) systems on the total rainfall amount increases going farther northward into the continent. Additionally, the number of tracks of those systems features relative minima along the Ivorian and Ghanaian-Togolese coast, the latter reflecting the climatologically dry Dahomey Gap. In contrast, local warm rain from isolated shallow convection develops more often along the immediate coast line. Yet, their contribution to total rainfall remains negligible and is almost non-existent further north. Compared with high-resolution rain gauge data around Kumasi, Ghana, for the year 2016, it can be assumed that warm rain events show an even higher occurrence frequency. Likewise, their

  12. Determination of rainfall and condensational heating in the South Pacific convergence zone during FGGE SOP-1

    Science.gov (United States)

    Robertson, F. R.

    1984-01-01

    The role of cloud related diabatic processes in maintaining the structure of the South Pacific Convergence Zone is discussed. The method chosen to evaluate the condensational heating is a diagnostic cumulus mass flux technique which uses GOES digital IR data to characterize the cloud population. This method requires as input an estimate of time/area mean rainfall rate over the area in question. Since direct observation of rainfall in the South Pacific is not feasible, a technique using GOES IR data is being developed to estimate rainfall amounts for a 2.5 degree grid at 12h intervals.

  13. Evaluation of satellite rainfall products through hydrologic simulation in a fully distributed hydrologic model

    Science.gov (United States)

    Bitew, Menberu M.; Gebremichael, Mekonnen

    2011-06-01

    The goal of this study is to evaluate the accuracy of four global high-resolution satellite rainfall products (CMORPH, TMPA 3B42RT, TMPA 3B42, and PERSIANN) through the hydrologic simulation of a 1656 km2 mountainous watershed in the fully distributed MIKE SHE hydrologic model. This study shows that there are significant biases in the satellite rainfall estimates and large variations in rainfall amounts, leading to large variations in hydrologic simulations. The rainfall algorithms that use primarily microwave data (CMORPH and TMPA 3B42RT) show consistent and better performance in streamflow simulation (bias in the order of -53% to -3%, Nash-Sutcliffe efficiency (NSE) from 0.34 to 0.65); the rainfall algorithm that uses primarily infrared data (PERSIANN) shows lower performance (bias from -82% to -3%, Nash-Sutcliffe efficiency from -0.39 to 0.43); and the rainfall algorithm that merges the satellite data with rain gage data (TMPA 3B42) shows inconsistencies and the lowest performance (bias from -86% to 0.43%, Nash-Sutcliffe efficiency from -0.50 to 0.27). A dilemma between calibrating the hydrologic model with rain gage data and calibrating it with the corresponding satellite rainfall data is presented. Calibrating the model with corresponding satellite rainfall data increases the performance of satellite streamflow simulation compared to the model calibrated with rain gage data, but decreases the performance of satellite evapotranspiration simulation.

  14. A climatological analysis of the southwest monsoon rainfall in the Philippines

    Science.gov (United States)

    Cruz, F. T.; Narisma, G. T.; Villafuerte, M. Q.; Cheng Chua, K. U.; Olaguera, L. M.

    2013-03-01

    The historical behavior of the southwest monsoon (SWM) rainfall in the Philippines is described using observed rainfall during the months of June to September from 1961 to 2010. Data are obtained from meteorological stations situated in the western half of the country where the impact of SWM is well pronounced. Time series analysis indicates significant decreasing trends from 0.026% to 0.075% per decade in the total SWM rainfall in six of the nine stations (Ambulong, Baguio, Coron, Dagupan, Iba and Vigan) in the past 50 years. A rainfall anomaly index is derived to characterize the inter-annual variability and the influence of the El Niño Southern Oscillation on the SWM rainfall. Results show no above normal rainfall events associated with La Niña years and few occurrences of below normal rainfall associated with El Niño events. Years where the SWM rainfall significantly deviates from its climate mean are also identified. Furthermore, an examination of the rainfall extremes indicate an increasing trend in the number of days without rain, which can be detected with statistical confidence in Ambulong (2.9% per decade), Baguio (5.9% per decade) and Dagupan (4.0% per decade), as well as a decreasing trend in the heavy rainfall days. These findings suggest a climatic change towards a prolonged dry period and an overall decreasing trend in rainfall during the SWM season over western Philippines in the recent decades, which can have serious implications on the country's agricultural sector.

  15. Analysis of NDVI-rainfall relationships reveals vegetation structure and ANPP dynamics in a Chihuahuan grassland-shrubland ecotone

    Science.gov (United States)

    Moreno de las Heras, Mariano; Diaz-Sierra, Ruben; Turnbull, Laura; Wainwright, John

    2015-04-01

    Shrub encroachment is perceived as a symptom of land degradation in the American Southwest, where large areas of grasslands dominated by black and blue grama have transitioned over the last 150 years to shrublands dominated by woody species (mainly creosotebush and mesquite), accompanied by accelerated water and wind erosion. In this study, simulations of plant biomass dynamics indicate that herbaceous and shrub vegetation in drylands have different responses to antecedent precipitation due to functional differences in plant growth and water-use patterns, and therefore shrub encroachment may be reflected in the analysis of landscape-scale vegetation-rainfall relationships. We analyze the structure and dynamics of vegetation at an 18-km2 grassland-shrubland ecotone in the northern edge of the Chihuahuan Desert (Sevilleta National Wildlife Refuge, New Mexico, USA) by investigating the relationship between 2000-13 records of remotely sensed MODIS NDVI and precipitation. Spatial analysis of NDVI-rainfall relationships at the studied ecotone indicates that herbaceous vegetation shows quick growth pulses associated with short-term (previous 2 months) precipitation, while shrubs show a slow response to medium-term (previous 5 months) precipitation. We use these relationships to (a) classify landscape types as a function of the spatial distribution of dominant vegetation, and (b) decompose the NDVI signal into partial primary production components for herbaceous vegetation and shrubs across the study site. We further apply remote-sensed annual net primary production (ANPP) estimations and landscape-type classification to explore the influence of inter-annual variations in seasonal precipitation on the production of herbaceous and shrub vegetation. Our results suggest that changes in the amount and temporal pattern of precipitation comprising reductions in monsoonal summer rainfall and/or increases in winter precipitation may enhance the shrub-encroachment process in the

  16. A Preliminary Study on Rainfall Interception Loss and Water Yield Analysis on Arabica Coffee Plants in Central Aceh Regency, Indonesia

    Directory of Open Access Journals (Sweden)

    Reza Benara

    2012-12-01

    Full Text Available Rainfall interception loss from plants or trees can reduce a net rainfall as source of water yield. The amount of rainfall interception loss depends on kinds of plants and hydro-meteorological characteristics. Therefore, it is important to study rainfall interception loss such as from Arabica Coffee plantation which is as main agricultural commodity for Central Aceh Regency. In this study, rainfall interception loss from Arabica Coffee plants was studied in Kebet Village of Central Aceh Regency, Indonesia from January 20 to March 9, 2011. Arabica coffee plants used in this study was 15 years old, height of 1.5 m and canopy of 4.567 m2. Rainfall interception loss was determined based on water balance approach of daily rainfall, throughfall, and stemflow data. Empirical regression equation between rainfall interception loss and rainfall were adopted as a model to estimate rainfall interception loss from Arabica Coffee plantation, which the coefficient of correlation, r is 0.98. In water yield analysis, this formula was applied and founded that Arabica Coffee plants intercept 76% of annual rainfall or it leaved over annual net rainfall 24% of annual rainfall. Using this net rainfall, water yield produced from Paya Bener River which is the catchment area covered by Arabica Coffee plantation was analyzed in a planning of water supply project for water needs domestic of 3 sub-districts in Central Aceh Regency. Based on increasing population until year of 2025, the results showed that the water yield will be not enough from year of 2015. However, if the catchment area is covered by forest, the water yield is still enough until year of 2025

  17. Trends in rainfall and temperature extremes in Morocco

    Directory of Open Access Journals (Sweden)

    K. Khomsi

    2015-02-01

    Full Text Available In Morocco, socioeconomic fields are vulnerable to weather extreme events. This work aims to analyze the frequency and the trends of temperature and rainfall extreme events in two contrasted Moroccan regions (the Tensift in the semi-arid South, and the Bouregreg in the sub-humid North, during the second half of the 20th century. This study considers long time series of daily extreme temperatures and rainfall, recorded in the stations of Marrakech and Safi for the Tensift region, and Kasba-Tadla and Rabat-Sale for the Bouregreg region, data from four other stations (Tanger, Fes, Agadir and Ouarzazate from outside the regions were added. Extremes are defined by using as thresholds the 1st, 5th, 90th, 95th, and 99th percentiles. Results show upward trends in maximum and minimum temperatures of both regions and no generalized trends in rainfall amounts. Changes in cold events are larger than those for warm events, and the number of very cold events decrease significantly in the whole studied area. The southern region is the most affected with the changes of the temperature regime. Most of the trends found in rainfall heavy events are positive with weak magnitudes even though no statistically significant generalized trends could be identified during both seasons.

  18. Are global mangrove carbon stocks driven by rainfall?

    Science.gov (United States)

    Sanders, Christian J.; Maher, Damien T.; Tait, Douglas R.; Williams, Darren; Holloway, Ceylena; Sippo, James Z.; Santos, Isaac R.

    2016-10-01

    Mangrove forests produce significant amounts of organic carbon and maintain large carbon stocks in tidally inundated, anoxic soils. This work analyzes new and published data from 17 regions spanning a latitudinal gradient from 22°N to 38°S to assess some of the global drivers (temperature, tidal range, latitude, and rainfall) of mangrove carbon stocks. Mangrove forests from the tropics have larger carbon stocks (895 ± 90 t C ha-1) than the subtropics and temperate regions (547 ± 66 t C ha-1). A multiple regression model showed that 86% of the observed variability is associated with annual rainfall, which is the best predictor of mangrove ecosystem carbon stocks. Therefore, a predicted increase in rainfall along the tropical Indo-Pacific may increase mangrove forest carbon stocks. However, there are other potentially important factors that may regulate organic matter diagenesis, such as nutrient availability and pore water salinity. Our predictive model shows that if mangrove deforestation is halted, global mangrove forest carbon stocks could increase by almost 10% by 2115 as a result of increased rainfall in the tropics.

  19. Rainfall-induced landslides in Europe: hotspots and thresholds (Invited)

    Science.gov (United States)

    Cepeda, J.; Jaedicke, C.; Nadim, F.; Kalsnes, B.

    2010-12-01

    This contribution presents preliminary results of the European project SafeLand. SafeLand is a large-scale integrating collaborative research project on landslide risks in Europe, funded by the Seventh Framework Programme for research and technological development (FP7) of the European Commission. SafeLand was launched in May 2009 and will run for three years. The project team, which comprises 27 institutions from 12 European countries, is coordinated by the International Centre for Geohazards (ICG) in Norway. SafeLand aims to develop and implement an integrated and comprehensive approach to help and guide decision-making in connection with mitigation of landslide risks. Quantifying the effects of global change (changes in demography and climate change) on evolution of landslide risk in Europe is one of the main goals of SafeLand. The methodologies are tested in selected hazard and risk "hotspots” in Europe, in turn improving knowledge, methodologies and integration strategies for the management of landslide risk. The present contribution is focused on two components of SafeLand: (1) the identification of landslide hazard and risk hotspots and (2) the estimation and assessment of rainfall thresholds for triggering of landslides. Hotspots of landslide hazard and risk were identified by an objective GIS-based analysis. The results show clearly where landslide pose the largest hazard in Europe and the objective approach allows a ranking of the countries by exposed area and population. In absolute numbers, Italy is the country with the highest amount of area and population exposed. Relative to absolute number of inhabitants and area, small alpine countries such as Lichtenstein and Montenegro score highest where as much as 40% of the population could be exposed. It is obvious that the type and quality of the input data are decisive for the quality of the results. Especially the estimation of extreme precipitation events needs improvement. These preliminary results are

  20. Spatial variability and rainfall characteristics of Kerala

    Indian Academy of Sciences (India)

    Anu Simon; K Mohankumar

    2004-06-01

    Geographical regions of covariability in precipitation over the Kerala state are exposed using factor analysis. The results suggest that Kerala can be divided into three unique rainfall regions, each region having a similar covariance structure of annual rainfall. Stations north of 10°N (north Kerala) fall into one group and they receive more rainfall than stations south of 10°N (south Kerala). Group I stations receive more than 65% of the annual rainfall during the south-west monsoon period, whereas stations falling in Group II receive 25-30% of annual rainfall during the pre-monsoon and the north-east monsoon periods. The meteorology of Kerala is profoundly influenced by its orographical features, however it is difficult to make out a direct relationship between elevation and rainfall. Local features of the state as reflected in the rainfall distribution are also clearly brought out by the study.

  1. Variability of rainfall over Lake Kariba catchment area in the Zambezi river basin, Zimbabwe

    Science.gov (United States)

    Muchuru, Shepherd; Botai, Joel O.; Botai, Christina M.; Landman, Willem A.; Adeola, Abiodun M.

    2016-04-01

    In this study, average monthly and annual rainfall totals recorded for the period 1970 to 2010 from a network of 13 stations across the Lake Kariba catchment area of the Zambezi river basin were analyzed in order to characterize the spatial-temporal variability of rainfall across the catchment area. In the analysis, the data were subjected to intervention and homogeneity analysis using the Cumulative Summation (CUSUM) technique and step change analysis using rank-sum test. Furthermore, rainfall variability was characterized by trend analysis using the non-parametric Mann-Kendall statistic. Additionally, the rainfall series were decomposed and the spectral characteristics derived using Cross Wavelet Transform (CWT) and Wavelet Coherence (WC) analysis. The advantage of using the wavelet-based parameters is that they vary in time and can therefore be used to quantitatively detect time-scale-dependent correlations and phase shifts between rainfall time series at various localized time-frequency scales. The annual and seasonal rainfall series were homogeneous and demonstrated no apparent significant shifts. According to the inhomogeneity classification, the rainfall series recorded across the Lake Kariba catchment area belonged to category A (useful) and B (doubtful), i.e., there were zero to one and two absolute tests rejecting the null hypothesis (at 5 % significance level), respectively. Lastly, the long-term variability of the rainfall series across the Lake Kariba catchment area exhibited non-significant positive and negative trends with coherent oscillatory modes that are constantly locked in phase in the Morlet wavelet space.

  2. The Effectiveness of Canopy Trees to Reduce Rainfall Acidity in the Industrial Area at Medan

    Directory of Open Access Journals (Sweden)

    Tyas Mutiara Basuki

    2004-01-01

    Full Text Available The term of acid rain is referred to the mean rainfall with a pH less than 5,65. The element of Sox and Nox are the major sources of aid rain. These two elements are oxidized into SO4 and NO3 respectively in the air. Sulfate and Nitrate are water soluble and the primary sources of hydrogen ions in acid precipitation. Rain passing through a tree canopy may lose or gain mineral elements trough some combination of natural process of absorption and leaching. By this process, the canopy may reduce rainfall acidity and negatif effects of the acid rain which will enter into the soil. Due to characteristic differences among tree canopies, a study to evaluate effectiveness of the trees in reducing rainfall acidity was done. In this study, rainfall and troughfall were collected every single rain and the pH measure by portable pH-meter. Based on data collection during 3 months in Medan Industrial Estate, it found that the mean pH of rainfall was 5,15. The highest pH of throughfall was found from Gnetum gnemon, that was 5,70; following by Mimusops elengi, Filicium decipiens, Acacia mangium, and the lowest was Nephelium lappacum. G. Gnemon was able to reduce 11% of rainfall acidity, but N. Lappacum caused 13% increasing rainfall acidity. In this study, the main source of rainfall acidity was hidrogen from sulfate acid (54%, following by chloride acid (30%, and nitrate acid (16%.

  3. Coupled Modes of Rainfall over China and the Pacific Sea Surface Temperature in Boreal Summertime

    Institute of Scientific and Technical Information of China (English)

    LI Chun; MA Hao

    2011-01-01

    In this study,monthly NCEP/NCAR reanalysis data and NOAA ERSST as well as observed precipitation data from 160 stations in China were used to investigate coupled modes affecting the rainfall over China and sea surface temperature (SST) in the Pacific during boreal summertime based on singular value decomposition (SVD) method.The SVD analysis revealed three remarkable coupled modes:rainfall over North China associated with an ENSO-like SST pattern (ENSO NC),rainfall over the Yangtze River valley associated with SST anomalies in the western tropical Pacific (WTP-YRV),and rainfall over the Ycllow River loop valley associated with tropical Pacific meridional mode-like SST pattern (TPMM-YRLV).These coupled SVD modes appear robust and closely correlated with the single field,Furthermore,the covariabilities among of the three coupled modes have different characteristics at the decadal time scale.In addition,the possible atmospheric teleconnections of the coupled rainfall and SST modes were discussed.For the ENSO-NC mode,anomalous low-pressure and high-pressure over the Asian continent induces moisture divergence over North China and reduces summer rainfall there.For the WTP-YRV mode,East Asia-Pacific teleconnection induces moisture convergence over the Yangtze River valley and enhances the summer rainfall there.The TPMM SST and the summer rainfall anomalies over the YRVL are linked by a circumglobal,wave-train-like,atmospheric teleconnection.

  4. Simulation skill of APCC set of global climate models for Asian summer monsoon rainfall variability

    Science.gov (United States)

    Singh, U. K.; Singh, G. P.; Singh, Vikas

    2015-04-01

    The performance of 11 Asia-Pacific Economic Cooperation Climate Center (APCC) global climate models (coupled and uncoupled both) in simulating the seasonal summer (June-August) monsoon rainfall variability over Asia (especially over India and East Asia) has been evaluated in detail using hind-cast data (3 months advance) generated from APCC which provides the regional climate information product services based on multi-model ensemble dynamical seasonal prediction systems. The skill of each global climate model over Asia was tested separately in detail for the period of 21 years (1983-2003), and simulated Asian summer monsoon rainfall (ASMR) has been verified using various statistical measures for Indian and East Asian land masses separately. The analysis found a large variation in spatial ASMR simulated with uncoupled model compared to coupled models (like Predictive Ocean Atmosphere Model for Australia, National Centers for Environmental Prediction and Japan Meteorological Agency). The simulated ASMR in coupled model was closer to Climate Prediction Centre Merged Analysis of Precipitation (CMAP) compared to uncoupled models although the amount of ASMR was underestimated in both models. Analysis also found a high spread in simulated ASMR among the ensemble members (suggesting that the model's performance is highly dependent on its initial conditions). The correlation analysis between sea surface temperature (SST) and ASMR shows that that the coupled models are strongly associated with ASMR compared to the uncoupled models (suggesting that air-sea interaction is well cared in coupled models). The analysis of rainfall using various statistical measures suggests that the multi-model ensemble (MME) performed better compared to individual model and also separate study indicate that Indian and East Asian land masses are more useful compared to Asia monsoon rainfall as a whole. The results of various statistical measures like skill of multi-model ensemble, large spread

  5. Multilayer perceptron neural network for downscaling rainfall in arid region: A case study of Baluchistan, Pakistan

    Indian Academy of Sciences (India)

    Kamal Ahmed; Shamsuddin Shahid; Sobri Bin Haroon; Wang Xiao-Jun

    2015-08-01

    Downscaling rainfall in an arid region is much challenging compared to wet region due to erratic and infrequent behaviour of rainfall in the arid region. The complexity is further aggregated due to scarcity of data in such regions. A multilayer perceptron (MLP) neural network has been proposed in the present study for the downscaling of rainfall in the data scarce arid region of Baluchistan province of Pakistan, which is considered as one of the most vulnerable areas of Pakistan to climate change. The National Center for Environmental Prediction (NCEP) reanalysis datasets from 20 grid points surrounding the study area were used to select the predictors using principal component analysis. Monthly rainfall data for the time periods 1961–1990 and 1991–2001 were used for the calibration and validation of the MLP model, respectively. The performance of the model was assessed using various statistics including mean, variance, quartiles, root mean square error (RMSE), mean bias error (MBE), coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE). Comparisons of mean monthly time series of observed and downscaled rainfall showed good agreement during both calibration and validation periods, while the downscaling model was found to underpredict rainfall variance in both periods. Other statistical parameters also revealed good agreement between observed and downscaled rainfall during both calibration and validation periods in most of the stations.

  6. Towards estimates of future rainfall erosivity in Europe based on REDES and WorldClim datasets.

    Science.gov (United States)

    Panagos, Panos; Ballabio, Cristiano; Meusburger, Katrin; Spinoni, Jonathan; Alewell, Christine; Borrelli, Pasquale

    2017-05-01

    The policy requests to develop trends in soil erosion changes can be responded developing modelling scenarios of the two most dynamic factors in soil erosion, i.e. rainfall erosivity and land cover change. The recently developed Rainfall Erosivity Database at European Scale (REDES) and a statistical approach used to spatially interpolate rainfall erosivity data have the potential to become useful knowledge to predict future rainfall erosivity based on climate scenarios. The use of a thorough statistical modelling approach (Gaussian Process Regression), with the selection of the most appropriate covariates (monthly precipitation, temperature datasets and bioclimatic layers), allowed to predict the rainfall erosivity based on climate change scenarios. The mean rainfall erosivity for the European Union and Switzerland is projected to be 857 MJ mm ha(-1) h(-1) yr(-1) till 2050 showing a relative increase of 18% compared to baseline data (2010). The changes are heterogeneous in the European continent depending on the future projections of most erosive months (hot period: April-September). The output results report a pan-European projection of future rainfall erosivity taking into account the uncertainties of the climatic models.

  7. Rainfall interception by the vegetation in a Mediterranean type climate

    Science.gov (United States)

    Moreno-Pérez, M. F.; Roldán-Cañas, J.; Cienfuegos, I.

    2012-04-01

    The study of rainfall interception by the canopy of the vegetation is of great importance in the basin water balance, because a large part returns to the atmosphere as evaporation. The presence or absence of vegetation not only affects the amount of rainfall that reaches the ground level also affects the moisture content in soil and surface runoff. In arid or semiarid regions there are few studies related to the Mediterranean vegetation and its relationship to hydrological processes. Furthermore, most studies have characterized the interception by rainfall simulators in the laboratory. The aim of this study was to evaluate in situ the amount and distribution of rainfall through the process of interception by the canopy of trees and shrubs present in the hydrologic watershed of "The Cabril" (Córdoba, southern Spain). The predominant vegetation is scrub, composed mostly of rockrose (Cistus ladanifer), and arboreal formations of tree pines (Pinus pinea). The record of precipitation was performed using a rain gauge tipping bowl Eijkelkamp mark during periods of rain occurred in 2010 and 2011. The amount of precipitation intercepted by the canopy has been determined indirectly from the difference between incident precipitation and rain that passes through the canopy of vegetation, which is divided into the flow of throughfall and cortical flow. To measure the throughfall the soil surface was waterproofed. Throughfall volume that is generated after each rain event is collected in four tanks of 200 liters capacity interconnected. For measurement of cortical flow a spiral hose previously cut lengthwise was placed around the trunk in the case of tree pines. In rockrose, a container was installed around it at its base. Monitoring soil moisture was determined by moisture probes 6 Delta-T SM200 randomly distributed, which records the water content of the topsoil. Compared with rockrose, there is a higher percentage of interception in pine and lowest percentage of cortical

  8. Interpolation of daily rainfall using spatiotemporal models and clustering

    KAUST Repository

    Militino, A. F.

    2014-06-11

    Accumulated daily rainfall in non-observed locations on a particular day is frequently required as input to decision-making tools in precision agriculture or for hydrological or meteorological studies. Various solutions and estimation procedures have been proposed in the literature depending on the auxiliary information and the availability of data, but most such solutions are oriented to interpolating spatial data without incorporating temporal dependence. When data are available in space and time, spatiotemporal models usually provide better solutions. Here, we analyse the performance of three spatiotemporal models fitted to the whole sampled set and to clusters within the sampled set. The data consists of daily observations collected from 87 manual rainfall gauges from 1990 to 2010 in Navarre, Spain. The accuracy and precision of the interpolated data are compared with real data from 33 automated rainfall gauges in the same region, but placed in different locations than the manual rainfall gauges. Root mean squared error by months and by year are also provided. To illustrate these models, we also map interpolated daily precipitations and standard errors on a 1km2 grid in the whole region. © 2014 Royal Meteorological Society.

  9. Canopy interception during rainfall, storm break time and after cessation of rainfall: experimental study using artificial Christmas trees

    Science.gov (United States)

    Murakami, Shigeki

    2017-04-01

    Evaporation of canopy interception can be divided into three phases: evaporation during rainfall IR, storm break time when it stops raining temporarily ISbt, and after cessation of rainfall IAft. In this study, IR, ISbt, and IAft were measured using model forests, i.e. plastic Christmas tree stands. The method and preliminary results are described in Murakami and Toba (2013). Christmas trees with original height of 65 cm (small tree) and 150 cm (large tree) were placed on three trays. Small trees were set on Tray #1. The same trees with height of 110 cm (extended using plastic rod) were placed on Tray #2, and large trees with height of 240 cm (raised using iron pipe) were set on Tray #3. The dimension of Tray #1 and #2 were a 180-cm square, and Tray #3 was a 360-cm square. Measurement was conducted under natural rainfall. Gross rainfall and net rainfall of each tray (discharge from each tray), in addition to single tree weight on Tray #1 and #3 were measured. Initial tree density of each tray was 41 trees per tray. Thinning was conducted in the middle of the experiment period and it was reduced to 25 trees per tray on Tray #2 and #3, but Tray #1 was unthinned. Total rainfall for pre-thinning period was 204.2 mm with 16 rain events and canopy interception CI was 10.8% (22.0 mm), 13.9% (28.3 mm) and 16.3% (33.4 mm) of rainfall for Tray #1, #2 and #3, respectively. Amount of rainfall for after thinning period was 291.5 mm with 24 rain events and canopy interception was 12.7% (40.0 mm), 21.7% (63.3 mm) and 13.6% (39.7 mm) of rainfall for Tray #1, #2 and #3, respectively. It is noteworthy that canopy interception increased on Tray #2 after thinning. IR, ISbt, and IAft were calculated for each tray using gross rainfall, net rainfall and the weight of single tree. Before thinning the value of IR/CI was 67.3% to74.9% and IAft occupied the remaining part of CI with ISbt/CI being nearly equal to zero. After thinning, IR/CI ranged from 65.3% to 93.8%. Both before and after

  10. Dry/Wet Conditions Monitoring Based on TRMM Rainfall Data and Its Reliability Validation over Poyang Lake Basin, China

    Directory of Open Access Journals (Sweden)

    Xianghu Li

    2013-11-01

    Full Text Available Local dry/wet conditions are of great concern in regional water resource and floods/droughts disaster risk management. Satellite-based precipitation products have greatly improved their accuracy and applicability and are expected to offer an alternative to ground rain gauges data. This paper investigated the capability of Tropical Rainfall Measuring Mission (TRMM rainfall data for monitoring the temporal and spatial variation of dry/wet conditions in Poyang Lake basin during 1998–2010, and validated its reliability with rain gauges data from 14 national meteorological stations in the basin. The results show that: (1 the daily TRMM rainfall data does not describe the occurrence and contribution rates of precipitation accurately, but monthly TRMM data have a good linear relationship with rain gauges rainfall data; (2 both the Z index and Standardized Precipitation Index (SPI based on monthly TRMM rainfall data oscillate around zero and show a consistent interannual variability as compared with rain gauges data; (3 the spatial pattern of moisture status, either in dry months or wet months, based on both the Z index and SPI using TRMM data, agree with the observed rainfall. In conclusion, the monthly TRMM rainfall data can be used for monitoring the variation and spatial distribution of dry/wet conditions in Poyang Lake basin.

  11. Gully Growth Patterns and Soil Loss under Rainfall at Urban Underground Drainage Construction Site, Uyo

    Directory of Open Access Journals (Sweden)

    O.E. Essien

    2012-08-01

    Full Text Available This study investigated, evaluated and modeled patterns of growth of gully morphometric dimension and soil loss volume under prevailing rainfall on the slopes of land graded for the construction of underground drainage at Uyo but delayed in completion. Land grading at underground (tunnel drainage construction site rendered the exposed surface very impervious but young ephemeral gullies developed due to delays in completion. Data on gully morphometric dimension, soil loss and depth of rainfall were analyzed using SPSS ver. 17 statistical package. Mean gully growth in length, width and depth were different at 2.54±0.86, 0.923±0.29 and 0.41±0.11 m, respectively, yielding 3.87±0.08 m2 as mean volume of soil loss at full stage. Cubic polynomial was best-fit model for growth in length (R2 = 79% and width (R2 = 69% using weekly rainfall for an annual season. All gully sites had constant depth change, better predicted by quadratic (R2 = 13% than linear (R2 = 9% functions. Mean volume of soil loss per unit rainfall amount varied with low, medium and high rainfall amount and was highest at slope bottom (33 cm3/cm and least at the crest (6.99 cm3/cm with R2 = 38-34%. Land grading to impervious sublayer produced constant depth change in all gullies at the sites. The models for morphometric incremental growth and soil loss volume under the rainfall effect was significantly improved (p<0.05 by bifurcating the lumped annual curve into two growth periods in a year: the periods for increasing rainfall (from week 10-30 and for receding rainfall (from week 31-43 in a year and applying quadratic regressing functions on each (R2 = 91-99%. Rainfall was the principal gully factor and construction delays should be avoided.

  12. Modelling and Simulation of Seasonal Rainfall Using the Principle of Maximum Entropy

    Directory of Open Access Journals (Sweden)

    Jonathan Borwein

    2014-02-01

    Full Text Available We use the principle of maximum entropy to propose a parsimonious model for the generation of simulated rainfall during the wettest three-month season at a typical location on the east coast of Australia. The model uses a checkerboard copula of maximum entropy to model the joint probability distribution for total seasonal rainfall and a set of two-parameter gamma distributions to model each of the marginal monthly rainfall totals. The model allows us to match the grade correlation coefficients for the checkerboard copula to the observed Spearman rank correlation coefficients for the monthly rainfalls and, hence, provides a model that correctly describes the mean and variance for each of the monthly totals and also for the overall seasonal total. Thus, we avoid the need for a posteriori adjustment of simulated monthly totals in order to correctly simulate the observed seasonal statistics. Detailed results are presented for the modelling and simulation of seasonal rainfall in the town of Kempsey on the mid-north coast of New South Wales. Empirical evidence from extensive simulations is used to validate this application of the model. A similar analysis for Sydney is also described.

  13. Warning Model for Shallow Landslides Induced by Extreme Rainfall

    Directory of Open Access Journals (Sweden)

    Lien-Kwei Chien

    2015-08-01

    Full Text Available In this study, the geophysical properties of the landslide-prone catchment of the Gaoping River in Taiwan were investigated using zones based on landslide history in conjunction with landslide analysis using a deterministic approach based on the TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope-Stability model. Typhoon Morakot in 2009 was selected as a simulation scenario to calibrate the combination of geophysical parameters in each zone before analyzing changes in the factor of safety (FS. Considering the amount of response time required for typhoons, suitable FS thresholds for landslide warnings are proposed for each town in the catchment area. Typhoon Fanapi of 2010 was used as a test scenario to verify the applicability of the FS as well as the efficacy of the cumulative rainfall thresholds derived in this study. Finally, the amount of response time provided by the FS thresholds in cases of yellow and red alerts was determined. All five of the landslide events reported by the Soil and Water Conservation Bureau were listed among the unstable sites identified in the proposed model, thereby demonstrating its effectiveness and accuracy in determining unstable areas and areas that require evacuation. These cumulative rainfall thresholds provide a valuable reference to guide disaster prevention authorities in the issuance of yellow and red alerts with the ability to reduce losses and save lives.

  14. Time and Space Variability of Rainfall in Central-East Argentina.

    Science.gov (United States)

    Krepper, Carlos M.; Scian, Beatriz V.; Pierini, Jorge O.

    1989-01-01

    Climatic variability of monthly rainfall data over a period of 30 yr is analyzed. Twenty-three precipitation locations of the central pampa region of Argentina were used. They are spread over the transition zone between wet and dry pampa. The variance contribution for three frequency bands were emphasized using spectral analysis. They include interannual, annual and intraannual variability. Temporal variability for high frequency (that of periods up to 5 months) accounts for 60% of the total variance. Space variability for monthly, three-month, seasonal, and annual periods are analyzed by empirical orthogonal functions. An axis of maximum mean monthly rainfall variability is found oriented from Sierra de la Ventana towards the NE. Spectral contributions for the monthly temporal coefficients of the first two eigenvalues show main peaks with 12-, 6- and 7-month periods.

  15. Seasonal variation and climate change impact in Rainfall Erosivity across Europe

    Science.gov (United States)

    Panagos, Panos; Borrelli, Pasquale; Meusburger, Katrin; Alewell, Christine; Ballabio, Cristiano

    2017-04-01

    Rainfall erosivity quantifies the climatic effect on water erosion and is of high importance for soil scientists, land use planners, agronomists, hydrologists and environmental scientists in general. The rainfall erosivity combines the influence of rainfall duration, magnitude, frequency and intensity. Rainfall erosivity is calculated from a series of single storm events by multiplying the total storm kinetic energy with the measured maximum 30-minute rainfall intensity. This estimation requests high temporal resolution (e.g. 30 minutes) rainfall data for sufficiently long time periods (i.e. 20 years). The European Commission's Joint Research Centr(JRC) in collaboration with national/regional meteorological services and Environmental Institutions made an extensive data collection of high resolution rainfall data in the 28 Member States of the European Union plus Switzerland to estimate rainfall erosivity in Europe. This resulted in the Rainfall Erosivity Database on the European Scale (REDES) which included 1,675 stations. The interpolation of those point erosivity values with a Gaussian Process Regression (GPR) model has resulted in the first Rainfall Erosivity map of Europe (Science of the Total Environment, 511: 801-815). In 2016, REDES extended with a monthly component, which allowed developing monthly and seasonal erosivity maps and assessing rainfall erosivity both spatially and temporally for European Union and Switzerland. The monthly erosivity maps have been used to develop composite indicators that map both intra-annual variability and concentration of erosive events (Science of the Total Environment, 579: 1298-1315). Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be applied in different seasons of the year. Finally, the identification of the most erosive month allows recommending certain agricultural management practices (crop

  16. Influence of Changing Rainfall Patterns on the Yield of Rambutan (Nephelium lappaceum L. and Selection of Genotypes in Known Drought-tolerant Fruit Species for Climate Change Adaptation

    Directory of Open Access Journals (Sweden)

    Pablito M. Magdalita

    2015-06-01

    Full Text Available In fruit crop production, rainfall, water stress, temperature, and wind are key variables for success, and the present changes in rainfall patterns could affect the flowering and yield of the rambutan (Nephelium lappaceum L. Other fruit species like macopa (Syzygium samarangense, siniguelas (Spondias purpurea, and native santol or cotton fruit (Sandoricum koetjape remain productive despite extreme climatic changes. This study assessed the influence of rainfall on rambutan yield and evaluated and selected tree genotypes of known drought-tolerant fruit species. Rambutan yield in a selected farm in Calauan, Laguna, Philippines, dropped remarkably from 152.2 kg/tree in 2008 to 8.6 kg/tree in 2009. This reduction could be attributed to the high rainfall in April 2009 at 334.4 mm, and possibly other environmental factors like temperature, relative humidity, solar radiation, and strong wind. Furthermore, wet months in 2009 also inhibited the flowering of rambutan. However, a low yield obtained in 2010 at 45.5 kg/tree could be partly attributed to the very low rainfall in May 2010 at only 9.1 mm. On the other hand, in relation to changing climate, selection of tree genotypes for use as varieties in known drought- and flood-tolerant fruit species based on important fruit qualities like sweetness, juiciness, and high edible portion was done. Among 103 macopa genotypes, Mc-13, 43, and 91 were selected and the best (i.e. , Mc-13 had sweet (7.15 °Brix and crispy fruits weighing 49.44 g, creamy white (RHCC 155 A, and had high edible portion (EP, 93.22%. Among 114 siniguelas genotypes, Sg-41, 42 and 105 were selected and the best selection (i.e., Sg-41, had sweet (12.50 °Brix and juicy fruit weighing 20.42 g, ruby red (RHCC 59 A, and had high EP (83.27%. Among 101 native santol genotypes, Sn-47, 59, and 74 were selected and the best selection (i.e. , Sn-59 had relatively sweet (5.56 °Brix and juicy fruits weighing 51.96 g, maize yellow (RHCC 21 B, and had

  17. Responses of soil water percolation to dynamic interactions among rainfall, antecedent moisture and season in a forest site

    Science.gov (United States)

    Lai, Xiaoming; Liao, Kaihua; Feng, Huihui; Zhu, Qing

    2016-09-01

    Knowledge of soil water percolation below the rooting zone and its responses to the dynamic interactions of different factors are important for the control of non-point source pollution. Based on 3600 scenarios in Hydrus-1D simulation, this study revealed the integrated effects of rainfall characteristics (rainfall amount, maximum rainfall intensity or MRI, time distribution characteristics of rainfall or TDC), antecedent moisture and the season on deep percolation (DP) at a forest site in Taihu Lake Basin, China. Results showed that Hydrus-1D model can well simulate the soil water dynamics at this site. Antecedent moisture had the greatest relative contribution to DP (85.7%), followed by rainfall amount (10.9%) and MRI (3.4%). As the antecedent moisture increased, the relative contribution of the season on DP increased from 0.0% to 16.4%. In comparison, that of MRI decreased from 58.7% to 38.5% and that of rainfall amount followed a bell shape pattern (greatest when the antecedent moisture was 0.26 m3 m-3). The relative contribution of antecedent moisture to DP in summer was the greatest (87.8%), while that of the rainfall was the least. The TDC influenced DP by affecting the responses of DP to other factors. When the rainfall amount was ⩾80 mm and the antecedent moisture content was ⩾0.34 m3 m-3, effect of TDC on DP could be observed. The DP of TDC_B (rainfall intensity linearly increased with time) was the lowest, while that of TDC_E (rainfall intensity kept constant with time) was the greatest. Findings of this study have practical significance for investigating the water and pollutant transport in vadose zone.

  18. Statistical downscaling of CMIP5 outputs for projecting future changes in rainfall in the Onkaparinga catchment

    Energy Technology Data Exchange (ETDEWEB)

    Rashid, Md. Mamunur, E-mail: mdmamunur.rashid@mymail.unisa.edu.au [Centre for Water Management and Reuse, School of Natural and Built Environments, University of South Australia, Mawson Lakes, SA 5095 (Australia); Beecham, Simon, E-mail: simon.beecham@unisa.edu.au [Centre for Water Management and Reuse, School of Natural and Built Environments, University of South Australia, Mawson Lakes, SA 5095 (Australia); Chowdhury, Rezaul K., E-mail: rezaulkabir@uaeu.ac.ae [Centre for Water Management and Reuse, School of Natural and Built Environments, University of South Australia, Mawson Lakes, SA 5095 (Australia); Department of Civil and Environmental Engineering, United Arab Emirates University, Al Ain, PO Box 15551 (United Arab Emirates)

    2015-10-15

    A generalized linear model was fitted to stochastically downscaled multi-site daily rainfall projections from CMIP5 General Circulation Models (GCMs) for the Onkaparinga catchment in South Australia to assess future changes to hydrologically relevant metrics. For this purpose three GCMs, two multi-model ensembles (one by averaging the predictors of GCMs and the other by regressing the predictors of GCMs against reanalysis datasets) and two scenarios (RCP4.5 and RCP8.5) were considered. The downscaling model was able to reasonably reproduce the observed historical rainfall statistics when the model was driven by NCEP reanalysis datasets. Significant bias was observed in the rainfall when downscaled from historical outputs of GCMs. Bias was corrected using the Frequency Adapted Quantile Mapping technique. Future changes in rainfall were computed from the bias corrected downscaled rainfall forced by GCM outputs for the period 2041–2060 and these were then compared to the base period 1961–2000. The results show that annual and seasonal rainfalls are likely to significantly decrease for all models and scenarios in the future. The number of dry days and maximum consecutive dry days will increase whereas the number of wet days and maximum consecutive wet days will decrease. Future changes of daily rainfall occurrence sequences combined with a reduction in rainfall amounts will lead to a drier catchment, thereby reducing the runoff potential. Because this is a catchment that is a significant source of Adelaide's water supply, irrigation water and water for maintaining environmental flows, an effective climate change adaptation strategy is needed in order to face future potential water shortages. - Highlights: • A generalized linear model was used for multi-site daily rainfall downscaling. • Rainfall was downscaled from CMIP5 GCM outputs. • Two multi-model ensemble approaches were used. • Bias was corrected using the Frequency Adapted Quantile Mapping

  19. Comparison between intensity- duration thresholds and cumulative rainfall thresholds for the forecasting of landslide

    Science.gov (United States)

    Lagomarsino, Daniela; Rosi, Ascanio; Rossi, Guglielmo; Segoni, Samuele; Catani, Filippo

    2014-05-01

    This work makes a quantitative comparison between the results of landslide forecasting obtained using two different rainfall threshold models, one using intensity-duration thresholds and the other based on cumulative rainfall thresholds in an area of northern Tuscany of 116 km2. The first methodology identifies rainfall intensity-duration thresholds by means a software called MaCumBA (Massive CUMulative Brisk Analyzer) that analyzes rain-gauge records, extracts the intensities (I) and durations (D) of the rainstorms associated with the initiation of landslides, plots these values on a diagram, and identifies thresholds that define the lower bounds of the I-D values. A back analysis using data from past events can be used to identify the threshold conditions associated with the least amount of false alarms. The second method (SIGMA) is based on the hypothesis that anomalous or extreme values of rainfall are responsible for landslide triggering: the statistical distribution of the rainfall series is analyzed, and multiples of the standard deviation (σ) are used as thresholds to discriminate between ordinary and extraordinary rainfall events. The name of the model, SIGMA, reflects the central role of the standard deviations in the proposed methodology. The definition of intensity-duration rainfall thresholds requires the combined use of rainfall measurements and an inventory of dated landslides, whereas SIGMA model can be implemented using only rainfall data. These two methodologies were applied in an area of 116 km2 where a database of 1200 landslides was available for the period 2000-2012. The results obtained are compared and discussed. Although several examples of visual comparisons between different intensity-duration rainfall thresholds are reported in the international literature, a quantitative comparison between thresholds obtained in the same area using different techniques and approaches is a relatively undebated research topic.

  20. Improvements of Satellite-Derived Cyclonic Rainfall over the North Atlantic.

    Science.gov (United States)

    Klepp, Christian-Philipp; Bakan, Stephan; Graßl, Hartmut

    2003-02-01

    Case studies of rainfall, derived from Special Sensor Microwave Imager (SSM/I) satellite data during the passage of individual cyclones over the North Atlantic, are presented to enhance the knowledge of rainfall processes associated with frontal systems. A multisatellite method is applied for complete coverage of the North Atlantic twice a day. Different SSM/I precipitation algorithms have been tested for individual cyclones and compared to the Global Precipitation Climatology Project (GPCP) datasets. An independent rainfall pattern and intensity validation method is presented using voluntary observing ship (VOS) datasets and Advanced Very High Resolution Radiometer (AVHRR) images.Intense cyclones occur frequently in the wintertime period, with cold fronts propagating far south over the North Atlantic. Following upstream, large cloud clusters are frequently embedded in the cellular structured cold air of the backside regions, which produce heavy convective rainfall events, especially in the region off Newfoundland around 50°N. These storms can be easily identified on AVHRR images. It transpired that only the SSM/I rainfall algorithm of Bauer and Schlüssel is sensitive enough to detect the rainfall patterns and intensities observed by VOS for those cyclone types over the North Atlantic. In contrast, the GPCP products do not recognize this backside rainfall, whereas the frontal rainfall conditions are well represented in all tested datasets. This is suggested from the results of an intensive intercomparison study with ship reports from the time period of the Fronts and Atlantic Storm Track Experiment (FASTEX) field campaign. For this purpose, a new technique has been developed to transfer ship report codes into rain-rate estimates. From the analysis of a complete life cycle of a cyclone, it follows that these mesoscale backside rainfall events contribute up to 25% to the total amount of rainfall in North Atlantic cyclones.

  1. TENACITY AND PERSISTENCE OF COPPER FUNGICIDES IN CITRUS SEEDLINGS UNDER SIMULATED RAINFALL

    Directory of Open Access Journals (Sweden)

    ANTONIO EDUARDO FONSECA

    2016-01-01

    Full Text Available The amount of fungicide that adheres to the leaf during spraying and the amount that remain on the leaf after weathering are the main factors that defines the amount of active residue on the leaf surface to effectively control plant pathogens. Thus, the objective of this work was to evaluate the tenacity and persistence of copper in citrus seedling leaves under simulated rainfall in Jaboticabal, State of São Paulo, Brazil. The evaluated variables were copper content, solution retention, surface tension and drop spectrum. A significant and inversely proportional linear relationship to drops <100 μm was found. The percentage of copper retained in leaves of citrus seedlings with copper fungicides of suspension concentrate (SC formulations after simulated rainfall was greater than 80%. Copper fungicides of SC formulations presented the lowest surface tension, allowing greater tenacity and persistence of copper on seedlings of citrus leaves after simulated rainfall and increased contact between the drops and leaf surface.

  2. Rainfall erosivity in catchments contaminated with fallout from the Fukushima Daiichi nuclear power plant accident

    Science.gov (United States)

    Laceby, J. Patrick; Chartin, Caroline; Evrard, Olivier; Onda, Yuichi; Garcia-Sanchez, Laurent; Cerdan, Olivier

    2016-06-01

    The Fukushima Daiichi nuclear power plant (FDNPP) accident in March 2011 resulted in the fallout of significant quantities of radiocesium over the Fukushima region. After reaching the soil surface, radiocesium is quickly bound to fine soil particles. Thereafter, rainfall and snowmelt run-off events transfer particle-bound radiocesium downstream. Characterizing the precipitation regime of the fallout-impacted region is thus important for understanding post-deposition radiocesium dynamics. Accordingly, 10 min (1995-2015) and daily precipitation data (1977-2015) from 42 meteorological stations within a 100 km radius of the FDNPP were analyzed. Monthly rainfall erosivity maps were developed to depict the spatial heterogeneity of rainfall erosivity for catchments entirely contained within this radius. The mean average precipitation in the region surrounding the FDNPP is 1420 mm yr-1 (SD 235) with a mean rainfall erosivity of 3696 MJ mm ha-1 h-1 yr-1 (SD 1327). Tropical cyclones contribute 22 % of the precipitation (422 mm yr-1) and 40 % of the rainfall erosivity (1462 MJ mm ha-1 h-1 yr-1 (SD 637)). The majority of precipitation (60 %) and rainfall erosivity (82 %) occurs between June and October. At a regional scale, rainfall erosivity increases from the north to the south during July and August, the most erosive months. For the remainder of the year, this gradient occurs mostly from northwest to southeast. Relief features strongly influence the spatial distribution of rainfall erosivity at a smaller scale, with the coastal plains and coastal mountain range having greater rainfall erosivity than the inland Abukuma River valley. Understanding these patterns, particularly their spatial and temporal (both inter- and intraannual) variation, is important for contextualizing soil and particle-bound radiocesium transfers in the Fukushima region. Moreover, understanding the impact of tropical cyclones will be important for managing sediment and sediment-bound contaminant

  3. Rainfall thresholds and flood warning: an operative case study

    Directory of Open Access Journals (Sweden)

    V. Montesarchio

    2009-02-01

    Full Text Available An operative methodology for rainfall thresholds definition is illustrated, in order to provide at critical river section optimal flood warnings. Threshold overcoming could produce a critical situation in river sites exposed to alluvial risk and trigger the prevention and emergency system alert. The procedure for the definition of critical rainfall threshold values is based both on the quantitative precipitation observed and the hydrological response of the basin. Thresholds values specify the precipitation amount for a given duration that generates a critical discharge in a given cross section and are estimated by hydrological modelling for several scenarios (e.g.: modifying the soil moisture conditions. Some preliminary results, in terms of reliability analysis (presence of false alarms and missed alarms, evaluated using indicators like hit rate and false alarm rate for the case study of Mignone River are presented.

  4. On the significance of mechanisms of disastrous rainfall triggered landslides

    Science.gov (United States)

    Alcántara-Ayala, Irasema; Garnica-Peña, Ricardo Javier; Borja-Baeza, Roberto Carlos

    2010-05-01

    Rainfall triggered landslides have caused major disasters worldwide. As such, human and economic losses have had a considerable impact in different regions of the planet, but they have been particularly severe in developing countries. During the fall of 1998, due to the intense rainfall caused by hurricane Mitch, a complex mass movement -rock fall-avalanche- took place in the South flank of Casita Volcano, in Nicaragua; the towns of El Porvenir and Rolando Rodríguez were completely swept away and around 1600 people died. A year later, in the Sierra Norte de Puebla, Mexico, dozens of landslides triggered by an extreme rainfall event caused approximately 200 victims. A month after, in December, 1999, Northern Venezuela suffered the loss of more than 10,000 people as a result of flash floods and debris flows. In 2006, the village of Guinsaugon in St. Bernard, Southern Leyte, Philippines, was buried by a mudslide that killed about 1,000 inhabitants, among which there were 246 students and 7 teachers of an elementary school. In this paper, a review of both, landslides mechanisms -hazards-, and conditions of the exposed populations -vulnerability- was undertaken in order to analyse the factors that control the occurrence of disasters and their associated magnitude and impact. Preliminary results indicated that while magnitude is derived by landslides mechanisms, impact of disasters associated to rainfall induced landslides is determined by the vulnerability of the population groups. It is suggested that in order to prevent disasters, findings from vulnerability analysis need to be always considered for risk assessment and management. Key words: Landslides mechanisms, rainfall triggered, vulnerability, disasters.

  5. Urban rainfall estimation employing commercial microwave links

    Science.gov (United States)

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko; ten Veldhuis, Marie-claire

    2015-04-01

    Urban areas often lack rainfall information. To increase the number of rainfall observations in cities, microwave links from operational cellular telecommunication networks may be employed. Although this new potential source of rainfall information has been shown to be promising, its quality needs to be demonstrated more extensively. In the Rain Sense kickstart project of the Amsterdam Institute for Advanced Metropolitan Solutions (AMS), sensors and citizens are preparing Amsterdam for future weather. Part of this project is rainfall estimation using new measurement techniques. Innovative sensing techniques will be utilized such as rainfall estimation from microwave links, umbrellas for weather sensing, low-cost sensors at lamp posts and in drainage pipes for water level observation. These will be combined with information provided by citizens in an active way through smartphone apps and in a passive way through social media posts (Twitter, Flickr etc.). Sensor information will be integrated, visualized and made accessible to citizens to help raise citizen awareness of urban water management challenges and promote resilience by providing information on how citizens can contribute in addressing these. Moreover, citizens and businesses can benefit from reliable weather information in planning their social and commercial activities. In the end city-wide high-resolution rainfall maps will be derived, blending rainfall information from microwave links and weather radars. This information will be used for urban water management. This presentation focuses on rainfall estimation from commercial microwave links. Received signal levels from tens of microwave links within the Amsterdam region (roughly 1 million inhabitants) in the Netherlands are utilized to estimate rainfall with high spatial and temporal resolution. Rainfall maps will be presented and compared to a gauge-adjusted radar rainfall data set. Rainfall time series from gauge(s), radars and links will be compared.

  6. Size-class structure and growth traits of Anastatica hierochuntica L. populations as rainfall indicators in aridlands

    Directory of Open Access Journals (Sweden)

    Ahmad K. Hegazy

    2010-10-01

    Full Text Available Field data verified by green house experiment were used to evaluate the response of Anastatica hierochuntica L. to the amount of rainfall. Field study of the populations was carried out in the runnel and depression microhabitats of gravel and sand sites. Four water treatments, equivalent to 100, 200, 500 and 1000 mm rainfall, were used to simulate different levels of water availability. Under 500 and 1000 mm rainfall, the size-class structure of A. hierochuntica populations consists of a high proportion of large size-class individuals, while a higher proportion of small size-class individuals was obtained under 100 and 200 mm rainfall. The dry skeletons of A. hierochuntica can be used as a “rain gauge” to predict the amount of rain or water received. The dominance of small size-classes (from 500 mm rainfall produce large size-classes (>64 cm3. Small size-class individuals produced under low amounts of rainfall allocated up to 60% of their phytomass to the reproductive organs. Allocation to reproductive organs decreased with the increase in the amount of rainfall, while allocation to the stem increased in large size-class individuals produced under the highest amount of rainfall (1000 mm reaching 54%. Increased allocation to stem in large-sized individuals favours the hygrochastic seed dispersal role in the plant. The root/shoot ratio decreased with the increase of the individual size-class, i.e. under high rainfall treatments. Higher values of relative growth rate, net assimilation rate and leaf area index were obtained under high water treatments. Conversely, less expanded leaves, i.e. lower specific leaf area, were manifested in the lowest water treatments.

  7. An assessment of spatial and temporal rainfall variability and its implications to Molapo farming in the Okavango Delta, Botswana

    Science.gov (United States)

    Dikgola, Kobamelo; Mazvimavi, Dominic

    2013-04-01

    This paper assesses the variability of rainfall on the entire Okavango Delta. Due to the effects of climate change as a result of global warming there is a concern of possibility of decline of rainfall over Southren Africa. Rainfall is a very important component driving the hydrological cycle and therefore the understanding of rainfall spatial and temporal variation is crucial for agricultural production and general water resources management. Time series of individual months, continuous month- to month, total rainfall for the early part ofthe rainy season, October-November-December (OND), the mid to end of the rainy season, January-February-March JFM) andannual rainfall, for 16 stations spread on the entire Okavango Delta are analysed and assessed for correlations and any significant trends to proof any changes in rainfall. A homogeneity test was conducted using four different methods; the Standard Normal Homogeneity, the Buishand Range, the Pettit and the Von Neuman ratio to examine the possible existence of change or break-pointsin the rainfall time series.Spatial rainfall variability was investigated using the spatial correlation function.The Mann-Kendall trend test was used to investigate existence of trends. The results showed a fluctuation from one months to another in existence of trend; e,g October a more negative trend for all stations, then a more positive trend for November and so on and so forth. For a seasonal series half of the stations were showing a negative trend while the other half was positive. The annual series also followed the same order as seasonal. The trends were statistically non-significant.A linear regression and quantile regression were used for further investigation of trends. The spatial rainfall correlation amongst stations and the indication of trends has implications on distribution and yields of molapo farming in the Okavango Delta.

  8. Application of vector autoregressive model for rainfall and groundwater level analysis

    Science.gov (United States)

    Keng, Chai Yoke; Shan, Fam Pei; Shimizu, Kunio; Imoto, Tomoaki; Lateh, Habibah; Peng, Koay Swee

    2017-08-01

    Groundwater is a crucial water supply for industrial, agricultural and residential use, hence it is important to understand groundwater system. Groundwater is a dynamic natural resource and can be recharged. The amount of recharge depends on the rate and duration of rainfall, as rainfall comprises an important component of the water cycle and is the prime source of groundwater recharge. This study applies Vector Autoregressive (VAR) model in the analysis of rainfall and groundwater level. The study area that is focused in the study is along the East-West Highway, Gerik-Jeli, Malaysia. The VAR model with optimum lag length 8, VAR(8) is selected to model the rainfall and groundwater level in the study area. Result of Granger causality test shows significant influence of rainfall to groundwater level. Impulse Response Function reveals that changes in rainfall significantly affect changes in groundwater level after some time lags. Moreover, Variance Decomposition reported that rainfall contributed to the forecast of the groundwater level. The VAR(8) model is validated by comparing the actual value with the in-sample forecasted value and the result is satisfied with all forecasted groundwater level values lies inside the confidence interval which indicate that the model is reliable. Furthermore, the closeness of both actual and forecasted groundwater level time series plots implies the high degree of accurateness of the estimated model.

  9. Influence of competition and rainfall manipulation on the growth responses of savanna trees and grasses.

    Science.gov (United States)

    February, Edmund C; Higgins, Steven I; Bond, William J; Swemmer, Louise

    2013-05-01

    In this study, we explored how rainfall manipulation influenced competitive interactions between grasses and juvenile trees (small nonreproductive trees capable of resprouting) in savanna. To do this, we manipulated rainfall amount in the field using an incomplete factorial experiment that determined the effects of rainfall reduction, no manipulation, rainfall addition, and competition between grasses and trees on grass and tree growth. As response variables, we focused on several measures of tree growth and Disc Pasture Meter settling height as an estimate of grass aboveground biomass. We conducted the study over four years, at two sites in the Kruger National Park, South Africa. Our results show that rainfall manipulation did not have substantial effects on any of the measures of tree growth we considered. However, trees at plots where grasses had been removed grew on average 15 cm more in height and 1.3-1.7 times more in basal area per year than those in plots with grasses. Grass biomass was not influenced by the presence of trees but was significantly and positively influenced by rainfall addition. These findings were not fundamentally influenced by soil type or by prevailing precipitation, suggesting applicability of our results to a wide range of savannas. Our results suggest that, in savannas, increasing rainfall serves to increase the competitive pressure exerted by grasses on trees. The implication is that recruitment into the adult tree stage from the juvenile stage is most likely in drought years when there is little competition from grass for resources and grass fuel loads are low.

  10. Urban-Induced Mechanisms for an Extreme Rainfall Event in Beijing China: A Satellite Perspective

    Directory of Open Access Journals (Sweden)

    Menglin S. Jin

    2015-03-01

    Full Text Available Using 1 km satellite remote sensing observations, this paper examines the clouds, aerosols, water vapor and surface skin temperature over Beijing to understand the possible urban system contributions to the extreme rainfall event on 21 July 2012 (i.e., 721 event. Remote sensing measurements, with the advantage of high spatial resolution and coverage, reveal three key urban-related mechanisms: (a the urban heat island effect (UHI resulted in strong surface convection and high level cloud cover over Beijing; (b urban aerosol amount peaked before the rainfall, which “seeded” the clouds and invigorated precipitation; and (c urban tall buildings provided additional lift for the air mass and provided heat at the underlying boundary to keep the rainfall system alive for a long duration precipitation (>10 hours. With the existing rainfall system moving from the northwest and abundant water vapor was transported from the southeast into Beijing, the urban canyon-lifting, aerosol, and UHI effects all enhanced this extreme rainfall event. This work proves that urban system is responsible, at least partly, for urban rainfall extremes and thus should be considered for urban extreme rainfall prediction in the future.

  11. Patterns of Dekadal Rainfall Variation Over a Selected Region in Lake Victoria Basin, Uganda

    Directory of Open Access Journals (Sweden)

    Isaac Mugume

    2016-11-01

    Full Text Available Understanding variations in rainfall in tropical regions is important due to its impacts on water resources, health and agriculture. This study assessed the dekadal rainfall patterns and rain days to determine intra-seasonal rainfall variability during the March–May season using the Mann–Kendall ( M K trend test and simple linear regression ( S L R over the period 2000–2015. Results showed an increasing trend of both dekadal rainfall amount and rain days (third and seventh dekads. The light rain days ( S L R = 0.181; M K = 0.350 and wet days ( S L R = 0.092; M K = 0.118 also depict an increasing trend. The rate of increase of light rain days and wet days during the third dekad (light rain days: S L R = 0.020; M K = 0.279 and wet days: S L R = 0.146; M K = 0.376 was slightly greater than during the seventh dekad (light rain days: S L R = 0.014; M K = 0.018 and wet days: S L R = 0.061; M K = 0.315 dekad. Seventy-four percent accounted for 2–4 consecutive dry days, but no significant trend was detected. The extreme rainfall was increasing over the third ( M K = 0.363 and seventh ( M K = 0.429 dekads. The rainfall amount and rain days were highly correlated (r: 0.43–0.72.

  12. Sensitivity of Average Annual Runoff to Spatial Variability and Temporal Correlation of Rainfall.

    Science.gov (United States)

    Babin, Steven M.

    1995-08-01

    This paper examines the sensitivity of annual area mean runoff calculations to the effects of spatial variability and temporal correlation of rainfall. The model used is based upon the hypothesis that the annual water balance is determined only by rainfall, potential evapotranspiration, and soil water storage. A simple bucket hydrology model with a seasonally varying potential evapotranspiration is used with rainfall data measured at several sites on the Delmarva Peninsula. Annual area mean runoffs are calculated for three cases: 1) actual spatial variability among the rain gauge sites and temporal correlation between consecutive 1-min rainfall amounts are maintained (the actual case); 2) actual spatial variability among the sites is maintained but temporal correlation between the consecutive 1-min rainfall amounts is minimized (the site-shuffled case); and 3) both spatial variability and temporal correlation are ignored (the area-averaged case). The actual case represents the baseline for comparison with the other two cases. The annual a' mean runoffs show little sensitivity to spatial variability and temporal correlation for this model. Therefore, if finite soil permeability effects are ignored in favor of simple water storage capacity, then spatial variability and temporal correlation of rainfall appear to have little impact on the annual area mean runoff for the data considered in this study.

  13. 20 CFR 404.333 - Wife's and husband's benefit amounts.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Wife's and husband's benefit amounts. 404.333... Disability Benefits for Spouses and Divorced Spouses § 404.333 Wife's and husband's benefit amounts. Your wife's or husband's monthly benefit is equal to one-half the insured person's primary insurance...

  14. Application of Artificial Neural Networks to Rainfall Forecasting in Queensland, Australia

    Institute of Scientific and Technical Information of China (English)

    John ABBOT; Jennifer MAROHASY

    2012-01-01

    In this study,the application of artificial intelligence to monthly and seasonal rainfall forecasting in Queensland,Australia,was assessed by inputting recognized climate indices,monthly historical rainfall data,and atmospheric temperatures into a prototype stand-alone,dynamic,recurrent,time-delay,artificial neural network.Outputs,as monthly rainfall forecasts 3 months in advance for the period 1993 to 2009,were compared with observed rainfall data using time-series plots,root mean squared error (RMSE),and Pearson correlation coefficients.A comparison of RMSE values with forecasts generated by the Australian Bureau of Meteorology's Predictive Ocean Atmosphere Model for Australia (POAMA)-1.5 general circulation model (GCM) indicated that the prototype achieved a lower RMSE for 16 of the 17 sites compared.The application of artificial neural networks to rainfall forecasting was reviewed.The prototype design is considered preliminary,with potential for significant improvement such as inclusion of output from GCMs and experimentation with other input attributes.

  15. Variability of rainfall in Suriname and the relation with ENSO-SST and TA-SST

    Directory of Open Access Journals (Sweden)

    R. J. Nurmohamed

    2006-01-01

    Full Text Available Spatial correlations in the annual rainfall anomalies are analyzed using principle component analyses (PCA. Cross correlation analysis and composites are used to measure the influence of sea surface temperatures anomalies (SSTAs in the tropical Atlantic and tropical Pacific Ocean with the seasonal rainfall in Suriname. The spatial and time variability in rainfall is mainly determined by the meridional movement of the Inter-tropical Convergence Zone (ITCZ. Rainfall anomalies tend to occur fairly uniformly over the whole country. In December-January (short wet season, there is a lagged correlation with the SSTAs in the Pacific region (clag3Nino1+2=-0.63. The strongest correlation between the March-May rainfall (beginning long wet season and the Pacific SSTAs is found with a correlation coefficient of ckNino1+2=0.59 at lag 1 month. The June-August rainfall (end part of long wet season shows the highest correlation with SSTAs in the TSA region and is about c=-0.52 for lag 0. In the September-November long dry season there is also a lagged correlation with the TSA SSTAs of about clag3=0.66. The different correlations and predictors can be used for seasonal rainfall predictions.

  16. Intraseasonal responses of the East Asia summer rainfall to anthropogenic aerosol climate forcing

    Science.gov (United States)

    Chen, Guoxing; Yang, Jing; Bao, Qing; Wang, Wei-Chyung

    2017-04-01

    The WRF Model is used to investigate intraseasonal responses of the summer rainfall to aerosol direct and cloud-adjustment effects over East Asia, where the anthropogenic aerosol loading has been increasing in the past few decades. The responses are evaluated by comparing two cases for each year during 2002-2008: a control case imposing the observed aerosol optical depth of the corresponding year and a sensitivity case having anthropogenic components of the control case reduced by 75%. Analyses of multiple-year simulations reveal that aerosol-induced changes of rainfall and circulation exhibit strong intraseasonal variability, and that the spatial pattern of changes in the monthly rainfall is related to the intensification and westward extension of the western North-Pacific subtropical high (WNPSH) by increased aerosols. This perturbation of the WNPSH induces surface air divergence over the southeast China and convergence over regions to the north and west of the WNPSH, causing, respectively, decreased and increased rainfall. As the WNPSH migration path varies year by year, however, the variability of rainfall changes over subregions of the eastern China (e.g., North China) is large within the decade. Meanwhile, the pattern of summer-gross rainfall changes also shows large interannual variation, but the general pattern of wetter in the west and dryer in the east persists. Results also suggest that the aerosol increase tends to reduce the number of Tibet Plateau vortices, which indirectly influence summer rainfall over the eastern China.

  17. Analysis of Rainfall Probabilities for Strategic Crop Planning in Raipur District of Chhattisgarh State

    Directory of Open Access Journals (Sweden)

    Sanjay Bhelawe

    2015-04-01

    Full Text Available Rainfall data of recent forty three years (1971-2013 of Labhandi station, Indira Gandhi Krishi Vishwavidhyalaya Raipur, Chhattisgarh was analysed with the method of incomplete gamma probability. The data revealed that the average rainfall of labhandi station is 1202 mm spread over 61 rainy days. Out of this 1055, 68, 53 and 27 mm received from south west monsoon (June-September, north east (October-December, summer (March-May and winter season (January -February respectively. Probability for receiving more than 100 mm of rainfall can be expected only at 25% probability level and that too in four weeks which is leading to the interpretation that rainfed rice production is a challenging task in this region. it has been found that at 75 per cent assured probability level rainfall of more than 200 mms can be expected only in July and August months and this rainfall is hardly sufficient for meeting the water requirement in upland situations. However at 50 per cent probability which is equivalent to average condition, cultivation of rice is possible under well water management conditions. On seasonal basis rainfall at assured probability level of 75% is not sufficient as the quantity is 795 mm rainfall in south-western monsoon season.

  18. River catchment rainfall series analysis using additive Holt–Winters method

    Indian Academy of Sciences (India)

    Yan Jun Puah; Yuk Feng Huang; Kuan Chin Chua; Teang Shui Lee

    2016-03-01

    Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfalltrends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt–Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10%missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010–2012. Most of the forecasts are acceptable.

  19. STUDY OF RAINFALL PERIODS IN THE CRASNA BASIN UNTIL THE CONFLUENCE WITH ZALAU

    Directory of Open Access Journals (Sweden)

    OANA MOIGRĂDEAN

    2013-04-01

    Full Text Available Study of Rainfall Periods in the Crasna Basin Until the Confluence with Zalau. The rainfall periods in the Crasna Basin were determined using the weighted anomaly standardized precipitation (WASP. We processed and analyzed data from the period between 1990-2000 from one meteorological station and eight rainfall stations. WASP values were calculated for intervals of one year and of six months (semesters. The frequency analysis was done on three domains of the precipitation periods (rainy, normal and dry. The rainfall risk characterization was studied on three groups: risk by excess, risk by deficiency and free of risk. By analyzing the resulting rainfall periods the wet domains have the predominant share followed by the normal and dry domains. The frequency analysis of the group with risk and without risk indicate a net predominance of situations without rainfall risk. In the spatial distribution of exceeding rainfall periods appear some contrasts, determined by the positions of stations and posts regarding the prevailing western air masses advections.

  20. EFFECTS OF ENSO ON THE RELATIONSHIP BETWEEN IOD AND SUMMER RAINFALL IN CHINA

    Institute of Scientific and Technical Information of China (English)

    LIU Xuan-fei; YUAN Hui-zhen; GUAN Zhao-yong

    2009-01-01

    Based on the data of 1950 - 1999 monthly global SST from Hadley Center. NCAR/NCEP reanalysis data and rainfall over 160 weather stations in China,investigation is conducted into the difference of summer rainfall in China (hereafter referred to as the "CS rainfall") between the years with the Indian Ocean Dipole (IOD) occurring independently and those with IOD occurring along with ENSO so as to study the effects of El Ni(n)o - Southern Oscillation (ENSO) on the relationship between IOD and the CS rainfall. It is shown that CS rainfall will be more than normal in South China (centered in Hunan province) in the years of positive IOI) occurring independently; the CS rainfall will be less (more) than normal in North China (Southeast China) in the years of positive IOI) occurring together with ENSO. The effect of ENSO is offsetting (enhancing) the relationship between IOD and summer rainfall in Southwest China,the region joining the Yangtze River basin with the ttuaihe River basin (hereafter referred to as the "Yangtze-Huaihe basin") and North China (Southeast China). The circulation field is also examined for preliminary causes of such an influence.

  1. Application of ATOVS Microwave Radiance Assimilation to Rainfall Prediction in Summer 2004

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Experiments are performed in this paper to understand the influence of satellite radiance data on the initial field of a numerical prediction system and rainfall prediction. First, Advanced Microwave Sounder Unit A (AMSU-A) and Unit B (AMSU-B) radiance data are directly used by three-dimensional variational data assimilation to improve the background field of the numerical model. Then, the detailed effect of the radiance data on the background field is analyzed. Secondly, the background field, which is formed by application of Advanced Television and Infrared Observation Satellite Operational Vertical Sounder (ATOVS) microwave radiance assimilation, is employed to simulate some heavy rainfall cases.The experiment results show that the assimilation of AMSU-A (B) microwave radiance data has a certain impact on the geopotential height, temperature, relative humidity and flow fields. And the impacts on the background field are mostly similar in the different months in summer. The heavy rainfall experiments reveal that the application of AMSU-A (B) microwave radiance data can improve the rainfall prediction significantly. In particular, the AMSU-A radiance data can significantly enhance the prediction of rainfall above 10 mm within 48 h, and the AMSU-B radiance data can improve the prediction of rainfall above 50 mm within 24 h. The present study confirms that the direct assimilation of satellite radiance data is an effective way to improve the prediction of heavy rainfall in the summer in China.

  2. Identification of homogeneous rainfall regimes in parts of Western Ghats region of Karnataka

    Indian Academy of Sciences (India)

    B Venkatesh; Mathew K Jose

    2007-08-01

    In view of the ongoing environmental and ecological changes in the Western Ghats, it is important to understand the environmental parameters pertaining to the sustenance of the region. Rainfall is one such parameter governing the hydrological processes crucial to agriculture planning, afforestation and eco-system management. Therefore, it is essential to understand rainfall distribution and its variation in relevance to such activities. The present study is an attempt to gain in-depth understanding in this direction. The study area comprises of one coastal district and its adjoining areas in Karnataka State. Mean annual rainfall data of 93 rain gauge stations distributed over the study area for a period of 10–50 years are used for the study. In order to assess the variation of rainfall across the ghats, several bands were constructed parallel to the latitudes to facilitate the analysis. The statistical analyses conducted included cluster analysis and analysis of variance. The study revealed that there exist three distinct zones of rainfall regimes in the study area, namely, Coastal zone, Transition zone and Malanad zone. It is observed that, the maximum rainfall occurs on the windward side ahead of the geographical peak. Further, mean monthly rainfall distribution over the zones has been depicted to enable agricultural planning in the study area.

  3. Relationship of Rainfall Distribution and Water Level on Major Flood 2014 in Pahang River Basin, Malaysia

    Directory of Open Access Journals (Sweden)

    Nur Hishaam Sulaiman

    2017-01-01

    Full Text Available Climate change gives impact on extreme hydrological events especially in extreme rainfall. This article discusses about the relationship of rainfall distribution and water level on major flood 2014 in Pahang River Basin, Malaysia in helping decision makers to flood management system. Based on DID Malaysia rainfall station, 56 stations have being use as point in this research and it is including Pahang, Terengganu, Kelantan and Perak. Data set for this study were analysed with GIS analysis using interpolation method to develop Isohyet map and XLstat statistical software for PCA and SPC analyses. The results that were obtained from the Isohyet Map for three months was mid-November, rainfall started to increase about in range of 800mm-1200mm and the intensity keep increased to 2200mm at mid-December 2014. The high rainfall intensity sense at highland that is upstream of Pahang River. The PCA and SPC analysis also indicates the high relationship between rainfall and water level of few places at Pahang River. The Sg. Yap station and Kg. Serambi station obtained the high relationship of rainfall and water level with factor loading value at 0.9330 and 0.9051 for each station. Hydrological pattern and trend are extremely affected by climate such as north east monsoon season that occurred in South China Sea and affected Pahang during November to March. The findings of this study are important to local authorities by providing basic data as guidelines to the integrated river management at Pahang River Basin.

  4. Extreme Rainfall Events and Associated Natural Hazards in Alaknanda Valley, Indian Himalayan Region

    Institute of Scientific and Technical Information of China (English)

    JOSHI Varun; KUMAR Kireet

    2006-01-01

    Entire Himalayan region is vulnerable to rain-induced (torrential rainfall) hazards in the form of flash flood, cloudburst or glacial lake outburst flood. Flash floods and cloudburst are generally caused by high intensity rainfall followed by debris flow or landslide often resulting into blockade of river channels. The examples of some major disasters caused by torrential rainfall events in last fifty years are the flash floods of 1968 in Teesta valley, in 1993 and 20o0 in Sntlej valley, in 1978 in Bhagirathi and in 197o in Alaknanda river valleys. The formation of landslide dams and subsequent breaching is also associated with such rainfall events. These dams may persist for years or may burst within a short span of its formation. Due to sudden surge of water level in the river valleys, havoc and panic are created in the down stream. In Alaknanda valley, frequencies of such extreme rainfall events are found to be increasing in last two decades. However, the monthly trend of extreme rainfall events has partly indicated this increase. In most of the years extreme rainfall events and cloudburst disaster were reported in August during the later part of the monsoon season.

  5. An Analysis of Thermally-Related Surface Rainfall Budgets Associated with Convective and Stratiform Rainfall

    Institute of Scientific and Technical Information of China (English)

    ZHOU Yushu; Xiaofan LI

    2011-01-01

    Both water vapor and heat processes play key roles in producing surface rainfall.While the water vapor effects of sea surface temperature and cloud radiative and microphysical processes on surface rainfall have been investigated in previous studies,the thermal effects on rainfall are analyzed in this study using a series of two-dimensional equilibrium cloud-resolving model experiments forced by zonally-uniform,constant,large-scale zonal wind and zero large-scale vertical velocity.The analysis of thermally-related surface rainfall budget reveals that the model domain mean surface rain rate is primarily associated with the mean infrared cooling rate.Convective rainfall and transport of hydrometeor concentration from convective regions to raining stratiform regions corresponds to the heat divergence over convective regions,whereas stratiform rainfall corresponds to the transport of hydrometeor concentration from convective regions and heat divergence over raining stratiform regions.The heat divergence over convective regions is mainly balanced by the heat convergence over rainfall-free regions,which is,in turn,offset by the radiative cooling over rainfall-free regions.The sensitivity experiments of rainfall to the effects of sea surface temperature and cloud radiative and microphysical processes show that the sea surface temperature and cloud processes affect convective rainfall through the changes in infrared cooling rate over rainfall-free regions and transport rate of heat from convective regions to rainfall-free regions.

  6. The all-year rainfall region of South Africa: Satellite rainfall-estimate perspective

    CSIR Research Space (South Africa)

    Engelbrecht, CJ

    2012-09-01

    Full Text Available Climate predictability and variability studies over South Africa typically focus on the summer rainfall region and to a lesser extent on the winter rainfall region. The all-year rainfall region of South Africa, a narrow strip located along the Cape...

  7. The impacts of the Indian summer rainfall on North China summer rainfall

    Science.gov (United States)

    Wu, Renguang; Jiao, Yang

    2017-05-01

    Previous studies have indicated a connection between interannual variations of the Indian and North China summer rainfall. An atmospheric circulation wave pattern over the mid-latitude Asia plays an important role in the connection. The present study compares the influence of the above-normal and below-normal Indian summer rainfall on the North China summer rainfall variations. Composite analysis shows that the mid-latitude Asian atmospheric circulation and the North China rainfall anomalies during summer tend to be anti-symmetric in above-normal and below-normal Indian rainfall years. Analysis indicates that the Indian-North China summer rainfall relation tends to be stronger when larger Indian rainfall anomaly occurs during a higher mean rainfall period. The observed long-term change in the Indian-North China summer rainfall relationship cannot be explained by the impact of the El Niño-Southern Oscillation (ENSO). The present study evaluates the Indian-North China summer rainfall relationship in climate models. Analysis shows that the Indian-North China summer rainfall relationship differs largely among different climate models and among different simulations of a specific model. The relationship also displays obvious temporal variations in both individual and ensemble mean model simulations. This suggests an important role of the atmospheric internal variability in the change of the Indian-North China summer rainfall relationship.

  8. Rainfall and runoff water quality of the Pang and Lambourn, tributaries of the River Thames, south-eastern England

    Directory of Open Access Journals (Sweden)

    C. Neal

    2004-01-01

    Full Text Available The water quality of rainfall and runoff is described for two catchments of two tributaries of the River Thames, the Pang and Lambourn. Rainfall chemistry is variable and concentrations of most determinands decrease with increasing volume of catch probably due to 'wash out' processes. Two rainfall sites have been monitored, one for each catchment. The rainfall site on the Lambourn shows higher chemical concentrations than the one for the Pang which probably reflects higher amounts of local inputs from agricultural activity. Rainfall quality data at a long-term rainfall site on the Pang (UK National Air Quality Archive shows chemistries similar to that for the Lambourn site, but with some clear differences. Rainfall chemistries show considerable variation on an event-to-event basis. Average water quality concentrations and flow-weighted concentrations as well as fluxes vary across the sites, typically by about 30%. Stream chemistry is much less variable due to the main source of water coming from aquifer sources of high storage. The relationship between rainfall and runoff chemistry at the catchment outlet is described in terms of the relative proportions of atmospheric and within-catchment sources. Remarkably, in view of the quantity of agricultural and sewage inputs to the streams, the catchments appear to be retaining both P and N. Keywords: water quality, nitrate, ammonium, phosphorus, ammonia, nitrogen dioxide, pH, alkalinity, nutrients, trace metals, rainfall, river, Pang, Lambourn, LOCAR

  9. Variability in rainfall threshold for debris flow after the Chi-Chi earthquake in central Taiwan, China

    Institute of Scientific and Technical Information of China (English)

    C. L. SHIEH; Y. S. CHEN; Y. J. TSAI; J. H. WU

    2009-01-01

    The purpose of this study is to analyze variability in rainfall threshold for debris flow (critical rainfall for debris flow triggering) after the ML 7.3 Chi-Chi earthquake in central Taiwan in 1999.Two study sites with different geological conditions were surveyed in the earthquake area. Streambed surveys were conducted to continuously monitor debris flows between 1999 and 2006. During the 7-year study period, every debris flow event was identified, and the streambed characterized. Results show that the rainfall threshold for debris flow was remarkably lower just after the Chi-ChiEarthquake, but gradually recovered. To date, this rainfall threshold is still lower than the original level prior to the earthquake. This variability in rainfall threshold is closely related to the amount of sediment material in the initiation area of debris flow, which increased rapidly due to landslides resulting from the earthquake. With the increase in sediment material, the rainfall threshold was lowered severely during the first year following the Chi-Chi earthquake. However, heavy rainfalls mobilized the sediment material, causing debris flows and transporting sediment downstream. With the decrease in sediment material, the rainfall threshold recovered gradually over time. Furthermore,debris flows occurred only in the subbasins that had sufficient sediment material to cause significant movement. Hence, these results confirm that the sediment material in the initiation area of debris flow is a crucial component of the rainfall threshold for debris flow.

  10. Trend analysis of rainfall and temperature and its relationship over India

    Science.gov (United States)

    Subash, N.; Sikka, A. K.

    2014-08-01

    This study investigated the trends in rainfall and temperature and the possibility of any rational relationship between the trends over the homogeneous regions over India. Annual maximum temperature shows an increasing trend in all the homogeneous temperature regions and corresponding annual rainfall also follow the same pattern in all the regions, except North East. As far as monthly analysis is concerned, no definite pattern has been observed between trends in maximum and minimum temperature and rainfall, except during October. Increasing trends of maximum and minimum temperature during October accelerate the water vapor demand and most of the lakes, rivers, ponds and other water bodies with no limitation of water availability during this time fulfills the water vapor demand and shows an increasing trend of rainfall activity. This study shows there exists no direct relationship between increasing rainfall and increasing maximum temperature when monthly or seasonal pattern is concerned over meteorological subdivisions of India, however we can make a conclusion that the relation between the trends of rainfall and temperature have large scale spatial and temporal dependence.

  11. Influence of high resolution rainfall data on the hydrological response of urban flat catchments

    Science.gov (United States)

    Cristiano, Elena; ten Veldhuis, Marie-claire; van de Giesen, Nick

    2016-04-01

    hydrological response of some subcatchments of the district of Kralingen was studied. Rainfall data were combined with level and discharge measurements at the pumping station that connects the sewer system with the waste water treatment plane. Using this data it was possible to study the water balance and to have a better idea of the amount of water that leave the system during a specific rainfall events. Results show that the hydrological response of flat and looped catchments is sensitive to spatial and temporal rainfall variability and it can be strongly influenced by rainfall event characteristics, such as intensity, velocity and intermittency of the storm.

  12. Numerical rainfall simulation with different spatial and temporal evenness by using a WRF multiphysics ensemble

    Science.gov (United States)

    Tian, Jiyang; Liu, Jia; Yan, Denghua; Li, Chuanzhe; Yu, Fuliang

    2017-04-01

    The Weather Research and Forecasting (WRF) model is used in this study to simulate six storm events in two semi-humid catchments of northern China. The six storm events are classified into four types based on the rainfall evenness in the spatial and temporal dimensions. Two microphysics, two planetary boundary layers (PBL) and three cumulus parameterizations are combined to develop an ensemble containing 16 members for rainfall generation. The WRF model performs the best for type 1 events with relatively even distributions of rainfall in both space and time. The average relative error (ARE) for the cumulative rainfall amount is 15.82 %. For the spatial rainfall simulation, the lowest root mean square error (RMSE) is found with event II (0.4007), which has the most even spatial distribution, and for the temporal simulation the lowest RMSE is found with event I (1.0218), which has the most even temporal distribution. The most difficult to reproduce are found to be the very convective storms with uneven spatiotemporal distributions (type 4 event), and the average relative error for the cumulative rainfall amounts is up to 66.37 %. The RMSE results of event III, with the most uneven spatial and temporal distribution, are 0.9688 for the spatial simulation and 2.5327 for the temporal simulation, which are much higher than the other storms. The general performance of the current WRF physical parameterizations is discussed. The Betts-Miller-Janjic (BMJ) scheme is found to be unsuitable for rainfall simulation in the study sites. For type 1, 2 and 4 storms, member 4 performs the best. For type 3 storms, members 5 and 7 are the better choice. More guidance is provided for choosing among the physical parameterizations for accurate rainfall simulations of different storm types in the study area.

  13. Generation of future high-resolution rainfall time series with a disaggregation model

    Science.gov (United States)

    Müller, Hannes; Haberlandt, Uwe

    2017-04-01

    High-resolution rainfall data are needed in many fields of hydrology and water resources management. For analyzes of future rainfall condition climate scenarios exist with hourly values of rainfall. However, the direct usage of these data is associated with uncertainties which can be indicated by comparisons of observations and C20 control runs. An alternative is the derivation of changes of rainfall behavior over the time from climate simulations. Conclusions about future rainfall conditions can be drawn by adding these changes to observed time series. A multiplicative cascade model is used in this investigation for the disaggregation of daily rainfall amounts to hourly values. Model parameters can be estimated by REMO rainfall time series (UBA-, BfG- and ENS-realization), based on ECHAM5. Parameter estimation is carried out for C20 period as well as near term and long term future (2021-2050 and 2071-2100). Change factors for both future periods are derived by parameter comparisons and added to the parameters estimated from observed time series. This enables the generation of hourly rainfall time series from observed daily values with respect to future changes. The investigation is carried out for rain gauges in Lower Saxony. Generated Time series are analyzed regarding statistical characteristics, e.g. extreme values, event-based (wet spell duration and amounts, dry spell duration, …) and continuum characteristics (average intensity, fraction of dry intervals,…). The generation of the time series is validated by comparing the changes in the statistical characteristics from the REMO data and from the disaggregated data.

  14. Modelling rainfall interception in unlogged and logged forest areas of Central Kalimantan, Indonesia

    Directory of Open Access Journals (Sweden)

    C. Asdak

    1998-01-01

    Full Text Available Rainfall interception losses were monitored for twelve months and related to vegetation and rainfall characteristics at the Wanariset Sangai on the upper reaches of the Mentaya river, Central Kalimantan. The rainfall interception losses were quantified for one hectare each of unlogged and logged humid tropical rainforests. The results show that interception loss is higher in the unlogged forest (11% of total gross rainfall than in the logged forest (6%. Interception loss was also simulated by the modified Rutter model and Gash's original and revised models. Both the Rutter and revised Gash models predicted total interception loss over a long period adequately, and resulted in estimates of the interception loss that deviated by 6 to 14% of the measured values, for both the unlogged and logged plots.

  15. Exploring changes in rainfall intensity and seasonal variability in the Southeastern U.S.: Stakeholder engagement, observations, and adaptation

    Directory of Open Access Journals (Sweden)

    Daniel R. Dourte

    2015-01-01

    Full Text Available The distribution of rainfall has major impacts in agriculture, affecting the soil, hydrology, and plant health in agricultural systems. The goal of this study was to test for recent changes in rainfall intensity and seasonal rainfall variability in the Southeastern U.S. by exploring the data collaboratively with agricultural stakeholders. Daily rainfall records from the Global Historical Climatology Network were used to analyze changes in rain intensity and seasonal rainfall variability. During the last 30 years (1985–2014, there has been a significant change (53% increase in the number of extreme rainfall days (>152.4 mm/day and there have been significant decreases in the number of moderate intensity (12.7–25.4 mm/day and heavy (25.4–76.2 mm/day rainfall days in the Southeastern U.S., when compared to the previous 30-year period (1955–1984. There have also been significant decreases in the return period of months in which greater than half of the monthly total rain occurred in a single day; this is an original, stakeholder-developed rainfall intensity metric. The variability in spring and summer rainfall increased during the last 30 years, but winter and fall showed less variability in seasonal totals in the last 30 years. In agricultural systems, rainfall is one of the leading factors affecting yield variability; so it can be expected that more variable rainfall and more intense rain events could bring new challenges to agricultural production. However, these changes can also present opportunities for producers who are taking measures to adjust management strategies to make their systems more resilient to increased rain intensity and variability.

  16. Construction of rainfall change scenarios over the Chilka Lagoon in India

    Science.gov (United States)

    Das, Lalu; Meher, Jitendra Kumar; Dutta, Monami

    2016-12-01

    The present study attempted to quantify long-term seasonal and annual rainfall change for the period 1901-2004 over the Chilka Lagoon in India, the second largest lagoon in the world using multiple gridded data sources. The future rainfall projection is also constructed using the four Representative Concentration Pathways (RCPs) of the Global Circulation Models (GCMs) of the Coupled Model Intercomparison Project phase 5 (CMIP5). Skill of GCMs to simulate the observed rainfall over the lagoon was investigated through estimation of long-term trends and comparison of mean seasonal cycles using Taylor diagram. Finally based on the combined results obtained through trend analysis as well as seasonal cycles, 12 better performing GCMs were selected. Ensemble mean of better performing GCMs reveal that the rainfall in annual, monsoon and winter seasons have increased in the last century similar to three observational gridded data sources. The projected seasonal cycle of rainfall from different RCPs shows a dipole like characteristics where the drier (winter) and moist (monsoon) seasons show a surplus of rainfall (11-25%) while the premonsoon and the postmonsoon seasons show a deficient rainfall (3-52%) at the end of 21st century. It is interesting to note that the Chilka Lake will expected to receive an increasing amount of annual rainfall by 3-7% in 2020s, 7-11% in 2050s and 10-21% in 2080s. Ensemble mean of future downscaled scenarios revealed that the annual rainfall will increase slightly higher rate as compared to without downscaling indicating high uncertainty in future projection.

  17. Quantifying Rainfall Interception Loss of a Subtropical Broadleaved Forest in Central Taiwan

    Directory of Open Access Journals (Sweden)

    Yi-Ying Chen

    2016-01-01

    Full Text Available The factors controlling seasonal rainfall interception loss are investigated by using a double-mass curve analysis, based on direct measurements of high-temporal resolution gross rainfall, throughfall and stemflow from 43 rainfall events that occurred in central Taiwan from April 2008 to April 2009. The canopy water storage capacity for the wet season was estimated to be 1.86 mm, about twice that for the dry season (0.91 mm, likely due to the large reduction in the leaf area index (LAI from 4.63 to 2.23 (m2·m−2. Changes in seasonal canopy structure and micro-meteorological conditions resulted in temporal variations in the amount of interception components, and rainfall partitioning into stemflow and throughfall. Wet canopy evaporation after rainfall contributed 41.8% of the wet season interception loss, but only 17.1% of the dry season interception loss. Wet canopy evaporation during rainfall accounted for 82.9% of the dry season interception loss, but only 58.2% of the wet season interception loss. Throughfall accounted for over 79.7% of the dry season precipitation and 76.1% of the wet season precipitation, possibly due to the change in gap fraction from 64.2% in the dry season to 50.0% in the wet season. The reduced canopy cover in the dry season also produced less stemflow than that of the wet season. The rainfall stemflow ratio ( P s f / P g was reduced from 12.6% to 8.9%. Despite relatively large changes in canopy structure, seasonal variation of the ratio of rainfall partitioned to interception was quite small. Rainfall interception loss accounted for nearly 12% of gross precipitation for both dry and wet seasons.

  18. Future rainfall variability in Indonesia under different ENSO and IOD composites based on decadal predictions of CMIP5 datasets

    Science.gov (United States)

    Bilhaqqi Qalbi, Harisa; Faqih, Akhmad; Hidayat, Rahmat

    2017-01-01

    El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) are amongst important climate drivers that play a significant role in driving rainfall variability in Indonesia, especially on inter-annual timescales. The phenomena are suggested to have an association with interdecadal climate variability through the modulation of their oscillations. This study aims to analyse the characteristics of future rainfall variability in Indonesia during different condition of ENSO and IOD events based on decadal predictions of near-term climate change CMIP5 GCM data outputs up to year 2035. Monthly data of global rainfall data with 5x5 km grid resolutions of CHIRPS dataset is used in this study to represent historical rainfall variability as well to serve as a reference for future rainfall predictions. The current and future rainfall and sea surface temperature data have been bias corrected before performing the analysis. Given the comparison between rainfall composites during El-Nino and positive IOD events, the study showed that the future rainfall conditions in Indonesia will become drier than the historical condition resulted from the same composite approach. In general, this study showed the Indonesian rainfall variability in the future is expected to respond differently to a different combination of ENSO and IOD conditions.

  19. Vector Autoregression (Var Model for Rainfall Forecast and Isohyet Mapping in Semarang – Central Java – Indonesia

    Directory of Open Access Journals (Sweden)

    Adi Nugroho

    2014-11-01

    Full Text Available Agricultural and plantation activities in Indonesia, especially in Semarang, Central Java, Indonesia rely on water supply from the rainfall. The rainfall in the future is basically influenced by rainfall patterns, humidity and temperature in the past. In this case, Vector Autoregression (VAR multivariate model is applied to forecast the rainfall in the future, in which all along Indonesian Agency for Meteorology, Climatology and Geophysics (BMKG generally uses ARIMA model (Autoregressive Integrated Moving Average to carry out the same thing. The study applied the data, comprising the data of rainfall, humidity and temperature taken on a monthly basis during 2001-2013 periods from 5 measurement stations. Plotting of rainfall forecast result with VAR method is portrayed in the form of isohyet contour map to see the correlation between rainfall and coordinates of the area of the rainfall. The forecast result shows that VAR method is quite accurate to use for rainfall forecast in the study area as well as better than ARIMA method to forecast the same thing as having smaller Mean Absolute Error (MAE and Mean Absolute Percentage Error(MAPE.

  20. On Rainfall Modification by Major Urban Areas. Part 1; Observations from Space-borne Rain Radar Aboard TRMM

    Science.gov (United States)

    Shepherd, J. Marshell; Starr, David OC. (Technical Monitor)

    2001-01-01

    A novel approach is introduced to correlating urbanization and rainfall modification. This study represents one of the first published attempts (possibly the first) to identify and quantify rainfall modification by urban areas using satellite-based rainfall measurements. Previous investigations successfully used rain gauge networks and around-based radar to investigate this phenomenon but still encountered difficulties due to limited, specialized measurements and separation of topographic and other influences. Three years of mean monthly rainfall rates derived from the first space-based rainfall radar, Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar, are employed. Analysis of data at half-degree latitude resolution enables identification of rainfall patterns around major metropolitan areas of Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas during the warm season. Preliminary results reveal an average increase of 5.6% in monthly rainfall rates (relative to a mean upwind CONTROL area) over the metropolis but an average increase of approx. 28%, in monthly rainfall rates within 30-60 kilometers downwind of the metropolis. Some portions of the downwind area exhibit increases as high as 51%. It was also found that maximum rainfall rates found in the downwind impact area exceeded the mean value in the upwind CONTROL area by 48%-116% and were generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. These results are quite consistent studies of St. Louis (e.g' METROMEX) and Chicago almost two decades ago and more recent studies in the Atlanta and Mexico City areas.

  1. Weather radar rainfall data in urban hydrology

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Einfalt, Thomas; Willems, Patrick

    2017-01-01

    Application of weather radar data in urban hydrological applications has evolved significantly during the past decade as an alternative to traditional rainfall observations with rain gauges. Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology...... necessitate an updated review of the state of the art in such radar rainfall data and applications. Three key areas with significant advances over the past decade have been identified: (1) temporal and spatial resolution of rainfall data required for different types of hydrological applications, (2) rainfall...... estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Based on these three fields of research, the paper provides recommendations based on an updated overview of shortcomings, gains, and novel developments in relation to urban hydrological...

  2. Modelling persistence in annual Australia point rainfall

    Directory of Open Access Journals (Sweden)

    J. P. Whiting

    2003-01-01

    Full Text Available Annual rainfall time series for Sydney from 1859 to 1999 is analysed. Clear evidence of nonstationarity is presented, but substantial evidence for persistence or hidden states is more elusive. A test of the hypothesis that a hidden state Markov model reduces to a mixture distribution is presented. There is strong evidence of a correlation between the annual rainfall and climate indices. Strong evidence of persistence of one of these indices, the Pacific Decadal Oscillation (PDO, is presented together with a demonstration that this is better modelled by fractional differencing than by a hidden state Markov model. It is shown that conditioning the logarithm of rainfall on PDO, the Southern Oscillation index (SOI, and their interaction provides realistic simulation of rainfall that matches observed statistics. Similar simulation models are presented for Brisbane, Melbourne and Perth. Keywords: Hydrological persistence,hidden state Markov models, fractional differencing, PDO, SOI, Australian rainfall

  3. A large sample investigation of temporal scale-invariance in rainfall over the tropical urban island of Singapore

    Science.gov (United States)

    Mandapaka, Pradeep V.; Qin, Xiaosheng

    2015-11-01

    Scaling behavior of rainfall time series is characterized using monofractal, spectral, and multifractal frameworks. The study analyzed temporal scale-invariance of rainfall in the tropical island of Singapore using a large dataset comprising 31 years of hourly and 3 years of 1-min rainfall measurements. First, the rainfall time series is transformed into an occurrence-non-occurrence binary series, and its scaling behavior is analyzed using box-counting analysis. The results indicated that the rainfall support displays fractal structure, but within a limited range of scales. The rainfall support has a fractal dimension ( D f ) of 0.56 for scales ranging from 1 min to 1.5 h and a D f of 0.37 from 1.5 h to 1.5 days. The results further showed that the fractal dimension decreases with the increase in the threshold used to define binary series. Spectral analysis carried out on the rainfall time series and the corresponding binary series showed three distinct scaling regimes of 4 min-2 h, 2-24 h, and 24 h-1 month. In all the scaling regimes, the spectral exponents for the rainfall series were smaller than those for the binary series. The study then investigated the presence of multiscaling behavior in rainfall time series using moment scaling analysis. The results confirmed that the rainfall fluctuations display a multiscaling structure, which was modeled in the framework of universal multifractals. The results from this study would not only improve our understanding of the temporal rainfall structure in Singapore and the surrounding Maritime Continent but also help us build and parameterize parsimonious models and statistical downscaling techniques for rainfall in this region.

  4. Enhanced propagation of rainfall kinetic energy in the UK

    Science.gov (United States)

    Diodato, Nazzareno; Bellocchi, Gianni

    2017-08-01

    A gridded 0.25° reconstruction of rainfall kinetic energy (RKE) over the UK, on the basis of pluviometric observations and reanalysis back to 1765, shows that autumn RKE doubled in 1991-2013 (˜2 MJ m-2) compared to 1948-1990 (˜1 MJ m-2). A shift eastward is underway, which includes southern and northern portions of the country. Analyzing the long-running England and Wales precipitation series, we conclude that it is likely that increased precipitation amounts associated with more frequent convective storms created conditions for higher energy events.

  5. Variability of East African rainfall based on multi-year RegCM3 simulations

    Science.gov (United States)

    Anyah, R.; Semazzi, F.

    2009-04-01

    The International Center for Theoretical Physics(ICTP) regional climate model version 3(ICTP-RegCM3) multi-year simulations of East Africa rainfall during the October-December, short rains season are evaluated. Two parallel runs; based on NCEP reanalysis and NASA FvGCM lateral boundary conditions are performed. The simulated monthly and seasonal rainfall climatology as well as the inter-annual variability are found to be fairly consistent with observations. The model climatology over specific homogeneous climate sub-regions, except central Kenya highlands, also reasonably agree with the observed. The latitude-time evolution(intra-seasonal variability) of the simulated seasonal rainfall exhibits two distinct modes of behavior. The first is a quasi-stationary mode associated with high rainfall throughout the season within the equatorial belt between; 1oS and 2oN. The second mode is associated with the ITCZ-driven southward migration of regions of rainfall maxima as the season progresses, which is also consistent with the observed. Furthermore, observed rainfall variability over distinct homogeneous climate sub-regions is also fairly reproduced by the model, except over central Kenya Highlands and northeastern parts of Kenya. The spatial correlation between simulated seasonal rainfall and some of the global teleconnections(DMI and Nino3.4 indices) show that the regional model conserves some of the observed regional ‘hot spots' where rainfall-ENSO/DMI association are strong. At the same, unlike observations, the model reveals that along the East Africa Rift Valley and over western parts of Lake Victoria Basin, the association is weak, perhaps an indication that non-linear interactions between local forcing (captured by the model) and large scale systems either suppresses or obscures the dominant influence of the teleconnections on rainfall over certain parts.

  6. On the dust load and rainfall relationship in South Asia: an analysis from CMIP5

    Science.gov (United States)

    Singh, Charu; Ganguly, Dilip; Dash, S. K.

    2017-03-01

    This study is aimed at examining the consistency of the relationship between load of dust and rainfall simulated by different climate models and its implication for the Indian summer monsoon system. Monthly mean outputs of 12 climate models, obtained from the archive of the Coupled Model Intercomparison Project phase 5 (CMIP5) for the period 1951-2004, are analyzed to investigate the relationship between dust and rainfall. Comparative analysis of the model simulated precipitation with the India Meteorological Department (IMD) gridded rainfall, CRU TS3.21 and GPCP version 2.2 data sets show significant differences between the spatial patterns of JJAS rainfall as well as annual cycle of rainfall simulated by various models and observations. Similarly, significant inter-model differences are also noted in the simulation of load of dust, nevertheless it is further noted that most of the CMIP5 models are able to capture the major dust sources across the study region. Although the scatter plot analysis and the lead-lag pattern correlation between the dust load and the rainfall show strong relationship between the dust load over distant sources and the rainfall in the South Asian region in individual models, the temporal scale of this association indicates large differences amongst the models. Our results caution that it would be pre-mature to draw any robust conclusions on the time scale of the relationship between dust and the rainfall in the South Asian region based on either CMIP5 results or limited number of previous studies. Hence, we would like to emphasize upon the fact that any conclusions drawn on the relationship between the dust load and the South Asian rainfall using model simulation is highly dependent on the degree of complexity incorporated in those models such as the representation of aerosol life cycle, their interaction with clouds, precipitation and other components of the climate system.

  7. Simulation of extreme rainfall and projection of future changes using the GLIMCLIM model

    Science.gov (United States)

    Rashid, Md. Mamunur; Beecham, Simon; Chowdhury, Rezaul Kabir

    2016-08-01

    In this study, the performance of the Generalized LInear Modelling of daily CLImate sequence (GLIMCLIM) statistical downscaling model was assessed to simulate extreme rainfall indices and annual maximum daily rainfall (AMDR) when downscaled daily rainfall from National Centers for Environmental Prediction (NCEP) reanalysis and Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCM) (four GCMs and two scenarios) output datasets and then their changes were estimated for the future period 2041-2060. The model was able to reproduce the monthly variations in the extreme rainfall indices reasonably well when forced by the NCEP reanalysis datasets. Frequency Adapted Quantile Mapping (FAQM) was used to remove bias in the simulated daily rainfall when forced by CMIP5 GCMs, which reduced the discrepancy between observed and simulated extreme rainfall indices. Although the observed AMDR were within the 2.5th and 97.5th percentiles of the simulated AMDR, the model consistently under-predicted the inter-annual variability of AMDR. A non-stationary model was developed using the generalized linear model for local, shape and scale to estimate the AMDR with an annual exceedance probability of 0.01. The study shows that in general, AMDR is likely to decrease in the future. The Onkaparinga catchment will also experience drier conditions due to an increase in consecutive dry days coinciding with decreases in heavy (>long term 90th percentile) rainfall days, empirical 90th quantile of rainfall and maximum 5-day consecutive total rainfall for the future period (2041-2060) compared to the base period (1961-2000).

  8. Analysis of rainfall inputs and runoff under an A-frame oscillating rainfall simulator in a sugarcane field, Mackay region of Queensland: Matching measurement techniques to meet project water balance objectives

    Science.gov (United States)

    Fentie, Banti; Yu, Bofu; Ciesiolka, Cyril

    2010-05-01

    A total of 11 rainfall simulations were conducted on four different plots (ranging in area from 22.10 to 26.20 m2) in a sugarcane field (with slopes varying from 1-9% and a groundcover variability of bare - 100% cover) in the Mackay region of Northern Queensland. The objectives of these rainfall simulation experiments were many, but this paper discusses the measurement methodology and data quality of rainfall generated and subsequent runoff. Rainfall amount during the simulations was measured using two different sizes of rain gauges placed at different locations on the plot (left, centre, and right sides of the experimental plot). In addition to the 203mm ordinary rain gauges, three pluviometers (300mm) were placed along the centre of the plot to measure rainfall as a function of time during the simulation. The rainfall data from these three pluviometers was collected using dataloggers and processed using a computer program called Datalog, which converted the number of tips/minute into mm/h. Due to spatial variation of rainfall intensity applied to the surface as a function of height from the nozzles of the rainfall simulators, correction factors were determined using a computer program called ERFS developed for this purpose. The rainfall from each gauge and pluviometer was subsequently corrected for distance from the nozzles of the simulator and height of the gauge by multiplying it by the corresponding correction factor. The spatial distribution of rainfall amount during each simulation was determined by spatially interpolating measured amounts in order to ascertain the best estimate of applied rainfall and its energy. Runoff data during each simulation was collected using tipping buckets connected to data loggers. Runoff amounts were also manually collected at specified intervals as a back up, and for validation of those collected using tipping buckets in determining runoff rates for each simulation. Soil cores were taken for determining soil moisture balances

  9. Rainfall and temperature changes and variability in the Upper East Region of Ghana

    Science.gov (United States)

    Issahaku, Abdul-Rahaman; Campion, Benjamin Betey; Edziyie, Regina

    2016-08-01

    The aim of the research was to assess the current trend and variation in rainfall and temperature in the Upper East Region, Ghana, using time series moving average analysis and decomposition methods. Meteorological data obtained from the Ghana Meteorological Agency in Accra, Ghana, from 1954 to 2014 were used in the models. The additive decomposition model was used to analyze the rainfall because the seasonal variation was relatively constant over time, while the multiplicative model was used for both the daytime and nighttime temperatures because their seasonal variations increase over time. The monthly maximum and the minimum values for the entire period were as follows: rainfall 455.50 and 0.00 mm, nighttime temperature 29.10°C and 13.25°C and daytime temperature 41.10°C and 26.10°C, respectively. Also, while rainfall was decreasing, nighttime and daytime temperatures were increasing in decadal times. Since both the daytime and nighttime temperatures were increasing and rainfall was decreasing, climate extreme events such as droughts could result and affect agriculture in the region, which is predominantly rain fed. Also, rivers, dams, and dugouts are likely to dry up in the region. It was also observed that there was much variation in rainfall making prediction difficult. Day temperatures were generally high with the months of March and April have been the highest. The months of December recorded the lowest night temperature. Inhabitants are therefore advised to sleep in well-ventilated rooms during the warmest months and wear protective clothing during the cold months to avoid contracting climate-related diseases.

  10. Forecasting paediatric malaria admissions on the Kenya Coast using rainfall

    Directory of Open Access Journals (Sweden)

    Stella Wanjugu Karuri

    2016-02-01

    Full Text Available Background: Malaria is a vector-borne disease which, despite recent scaled-up efforts to achieve control in Africa, continues to pose a major threat to child survival. The disease is caused by the protozoan parasite Plasmodium and requires mosquitoes and humans for transmission. Rainfall is a major factor in seasonal and secular patterns of malaria transmission along the East African coast. Objective: The goal of the study was to develop a model to reliably forecast incidences of paediatric malaria admissions to Kilifi District Hospital (KDH. Design: In this article, we apply several statistical models to look at the temporal association between monthly paediatric malaria hospital admissions, rainfall, and Indian Ocean sea surface temperatures. Trend and seasonally adjusted, marginal and multivariate, time-series models for hospital admissions were applied to a unique data set to examine the role of climate, seasonality, and long-term anomalies in predicting malaria hospital admission rates and whether these might become more or less predictable with increasing vector control. Results: The proportion of paediatric admissions to KDH that have malaria as a cause of admission can be forecast by a model which depends on the proportion of malaria admissions in the previous 2 months. This model is improved by incorporating either the previous month's Indian Ocean Dipole information or the previous 2 months’ rainfall. Conclusions: Surveillance data can help build time-series prediction models which can be used to anticipate seasonal variations in clinical burdens of malaria in stable transmission areas and aid the timing of malaria vector control.

  11. Heavy daily-rainfall characteristics over the Gauteng Province

    African Journals Online (AJOL)

    2009-02-09

    Feb 9, 2009 ... Department of Geography, Geoinformatics and Meteorology, Geography Building 2-12, University of .... An example of heavy rainfall 'climatology' in the scientific .... rainfall stations in the calculation of the area-average rainfall.

  12. Topographic relationships for design rainfalls over Australia

    Science.gov (United States)

    Johnson, F.; Hutchinson, M. F.; The, C.; Beesley, C.; Green, J.

    2016-02-01

    Design rainfall statistics are the primary inputs used to assess flood risk across river catchments. These statistics normally take the form of Intensity-Duration-Frequency (IDF) curves that are derived from extreme value probability distributions fitted to observed daily, and sub-daily, rainfall data. The design rainfall relationships are often required for catchments where there are limited rainfall records, particularly catchments in remote areas with high topographic relief and hence some form of interpolation is required to provide estimates in these areas. This paper assesses the topographic dependence of rainfall extremes by using elevation-dependent thin plate smoothing splines to interpolate the mean annual maximum rainfall, for periods from one to seven days, across Australia. The analyses confirm the important impact of topography in explaining the spatial patterns of these extreme rainfall statistics. Continent-wide residual and cross validation statistics are used to demonstrate the 100-fold impact of elevation in relation to horizontal coordinates in explaining the spatial patterns, consistent with previous rainfall scaling studies and observational evidence. The impact of the complexity of the fitted spline surfaces, as defined by the number of knots, and the impact of applying variance stabilising transformations to the data, were also assessed. It was found that a relatively large number of 3570 knots, suitably chosen from 8619 gauge locations, was required to minimise the summary error statistics. Square root and log data transformations were found to deliver marginally superior continent-wide cross validation statistics, in comparison to applying no data transformation, but detailed assessments of residuals in complex high rainfall regions with high topographic relief showed that no data transformation gave superior performance in these regions. These results are consistent with the understanding that in areas with modest topographic relief, as

  13. A study on the decreasing trend in tropical easterly jet stream (TEJ) and its impact on Indian summer monsoon rainfall

    Science.gov (United States)

    Sreekala, P. P.; Bhaskara Rao, S. V.; Arunachalam, M. S.; Harikiran, C.

    2014-10-01

    Using the NCEP/NCAR reanalysis wind and temperature data (1948-2011) and India Meteorological Department (IMD) rainfall data, a long-term trend in the tropical easterly jet stream and its effect on Indian summer monsoon rainfall has been explained in the present study. A decreasing trend in zonal wind speed at 100 mb (maximum decrease), 150 mb, and 200 mb (minimum) is observed. The upper-level (100, 150, and 200 mb) zonal wind speed has been correlated with the surface air temperature anomaly index (ATAI) in the month of May, which is taken as the difference in temperature anomaly over land (22.5°N-27.5°N, 80°E-90°E) and Ocean (5°S-0°S, 75°E-85°E). Significant high correlation is observed between May ATAI and tropical easterly jet stream (TEJ) which suggests that the decreasing land-sea temperature contrast could be one major reason behind the decreasing trend in TEJ. The analysis of spatial distribution of rainfall over India shows a decreasing trend in rainfall over Jammu and Kashmir, Arunachal Pradesh, central Indian region, and western coast of India. Increasing trend in rainfall is observed over south peninsular and northeastern part of India. From the spatial correlation analysis of zonal wind with gridded rainfall, it is observed that the correlation of rainfall is found to be high with the TEJ speed over the regions where the decreasing trend in rainfall is observed. Similarly, from the analysis of spatial correlation between rainfall and May ATAI, positive spatial correlation is observed between May ATAI and summer monsoon rainfall over the regions such as south peninsular India where the rainfall trend is positive, and negative correlation is observed over the places such as Jammu and Kashmir where negative rainfall trend is observed. The decreased land-sea temperature contrast in the pre-monsoon month could be one major reason behind the decreased trend in TEJ as well as the observed spatial variation in the summer monsoon rainfall trend. Thus

  14. Regionalized rainfall-runoff model to estimate low flow indices

    Science.gov (United States)

    Garcia, Florine; Folton, Nathalie; Oudin, Ludovic

    2016-04-01

    Estimating low flow indices is of paramount importance to manage water resources and risk assessments. These indices are derived from river discharges which are measured at gauged stations. However, the lack of observations at ungauged sites bring the necessity of developing methods to estimate these low flow indices from observed discharges in neighboring catchments and from catchment characteristics. Different estimation methods exist. Regression or geostatistical methods performed on the low flow indices are the most common types of methods. Another less common method consists in regionalizing rainfall-runoff model parameters, from catchment characteristics or by spatial proximity, to estimate low flow indices from simulated hydrographs. Irstea developed GR2M-LoiEau, a conceptual monthly rainfall-runoff model, combined with a regionalized model of snow storage and melt. GR2M-LoiEau relies on only two parameters, which are regionalized and mapped throughout France. This model allows to cartography monthly reference low flow indices. The inputs data come from SAFRAN, the distributed mesoscale atmospheric analysis system, which provides daily solid and liquid precipitation and temperature data from everywhere in the French territory. To exploit fully these data and to estimate daily low flow indices, a new version of GR-LoiEau has been developed at a daily time step. The aim of this work is to develop and regionalize a GR-LoiEau model that can provide any daily, monthly or annual estimations of low flow indices, yet keeping only a few parameters, which is a major advantage to regionalize them. This work includes two parts. On the one hand, a daily conceptual rainfall-runoff model is developed with only three parameters in order to simulate daily and monthly low flow indices, mean annual runoff and seasonality. On the other hand, different regionalization methods, based on spatial proximity and similarity, are tested to estimate the model parameters and to simulate

  15. Some characteristics of very heavy rainfall over Orissa during summer monsoon season

    Indian Academy of Sciences (India)

    M Mohapatra; U C Mohanty

    2005-02-01

    Orissa is one of the most flood prone states of India. The floods in Orissa mostly occur during monsoon season due to very heavy rainfall caused by synoptic scale monsoon disturbances. Hence a study is undertaken to find out the characteristic features of very heavy rainfall (24 hours rainfall ≥ 125mm) over Orissa during summer monsoon season (June-September) by analysing 20 years (1980-1999) daily rainfall data of different stations in Orissa. The principal objective of this study is to find out the role of synoptic scale monsoon disturbances in spatial and temporal variability of very heavy rainfall over Orissa. Most of the very heavy rainfall events occur in July and August. The region, extending from central part of coastal Orissa in the southeast towards Sambalpur district in the northwest, experiences higher frequency and higher intensity of very heavy rainfall with less interannual variability. It is due to the fact that most of the causative synoptic disturbances like low pressure systems (LPS) develop over northwest (NW) Bay of Bengal with minimum interannual variation and the monsoon trough extends in west-northwesterly direction from the centre of the system. The very heavy rainfall occurs more frequently with less interannual variability on the western side of Eastern Ghat during all the months and the season except September. It occurs more frequently with less interannual variability on the eastern side of Eastern Ghat during September. The NW Bay followed by Gangetic West Bengal/Orissa is the most favourable region of LPS to cause very heavy rainfall over different parts of Orissa except eastern side of Eastern Ghat. The NW Bay and west central (WC) Bay are equally favourable regions of LPS to cause very heavy rainfall over eastern side of Eastern Ghat. The frequency of very heavy rain-fall does not show any significant trend in recent years over Orissa except some places in north-east Orissa which exhibit significant rising trend in all the

  16. Heavy rainfall equations for Santa Catarina, Brazil

    Directory of Open Access Journals (Sweden)

    Álvaro José Back

    2011-12-01

    Full Text Available Knowledge of intensity-duration-frequency (IDF relationships of rainfall events is extremely important to determine the dimensions of surface drainage structures and soil erosion control. The purpose of this study was to obtain IDF equations of 13 rain gauge stations in the state of Santa Catarina in Brazil: Chapecó, Urussanga, Campos Novos, Florianópolis, Lages, Caçador, Itajaí, Itá, Ponte Serrada, Porto União, Videira, Laguna and São Joaquim. The daily rainfall data charts of each station were digitized and then the annual maximum rainfall series were determined for durations ranging from 5 to 1440 min. Based on these, with the Gumbel-Chow distribution, the maximum rainfall was estimated for durations ranging from 5 min to 24 h, considering return periods of 2, 5, 10, 20, 25, 50, and 100 years,. Data agreement with the Gumbel-Chow model was verified by the Kolmogorov-Smirnov test, at 5 % significance level. For each rain gauge station, two IDF equations of rainfall events were adjusted, one for durations from 5 to 120 min and the other from 120 to 1440 min. The results show a high variability in maximum intensity of rainfall events among the studied stations. Highest values of coefficients of variation in the annual maximum series of rainfall were observed for durations of over 600 min at the stations of the coastal region of Santa Catarina.

  17. Monthly Meteorological Reports

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly forms that do not fit into any regular submission. Tabulation sheets and generic monthly forms designed to capture miscellaneous monthly observations.

  18. WRF model performance under flash-flood associated rainfall

    Science.gov (United States)

    Mejia-Estrada, Iskra; Bates, Paul; Ángel Rico-Ramírez, Miguel

    2017-04-01

    Understanding the natural processes that precede the occurrence of flash floods is crucial to improve the future flood projections in a changing climate. Using numerical weather prediction tools allows to determine one of the triggering conditions for these particularly dangerous events, difficult to forecast due to their short lead-time. However, simulating the spatial and temporal evolution of the rainfall that leads to a rapid rise in river levels requires determining the best model configuration without compromising the computational efficiency. The current research involves the results of the first part of a cascade modeling approach, where the Weather Research and Forecasting (WRF) model is used to simulate the heavy rainfall in the east of the UK in June 2012 when stationary thunderstorms caused 2-hour accumulated values to match those expected in the whole month of June over the city of Newcastle. The optimum model set-up was obtained after extensive testing regarding physics parameterizations, spin-up times, datasets used as initial conditions and model resolution and nesting, hence determining its sensitivity to reproduce localised events of short duration. The outputs were qualitatively and quantitatively assessed using information from the national weather radar network as well as interpolated rainfall values from gauges, respectively. Statistical and skill score values show that the model is able to produce reliable accumulated precipitation values while explicitly solving the atmospheric equations in high resolution domains as long as several hydrometeors are considered with a spin-up time that allows the model to assimilate the initial conditions without going too far back in time from the event of interest. The results from the WRF model will serve as input to run a semi-distributed hydrological model to determine the rainfall-runoff relationship within an uncertainty assessment framework that will allow evaluating the implications of assumptions at

  19. Changes in CO2 dynamics related to rainfall and water level variations in a subtropical lake

    DEFF Research Database (Denmark)

    Tonetta, Denise; Staehr, Peter Anton; Petrucio, Mauricio Mello

    2017-01-01

    We investigated the implications of low rainfall and reduced water level for changes in nutrients and chlorophyll-a in a subtropical lake, and how these changes affected levels and atmospheric fluxes of CO2. Based on nine consecutive years of monthly monitoring of pH, alkalinity, oxygen, and temp......We investigated the implications of low rainfall and reduced water level for changes in nutrients and chlorophyll-a in a subtropical lake, and how these changes affected levels and atmospheric fluxes of CO2. Based on nine consecutive years of monthly monitoring of pH, alkalinity, oxygen......, and temperature, we calculated the pCO(2) and CO2 flux and related these to environmental drivers. Variations in annual rainfall, with extreme low levels along 2012-2014 caused the water level to decrease up to 1 m. Low water levels were associated with higher concentrations of chlorophyll-a and organic carbon...

  20. Assessment of probabilistic areal reduction factors of precipitations for the entire French territory with gridded rainfall data.

    Science.gov (United States)

    Fouchier, Catherine; Maire, Alexis; Arnaud, Patrick; Cantet, Philippe; Odry, Jean

    2016-04-01

    The starting point of our study was the availability of maps of rainfall quantiles available for the entire French mainland territory at the spatial resolution of 1 km². These maps display the rainfall amounts estimated for different rainfall durations (from 15 minutes to 72 hours) and different return periods (from 2 years up to 1 000 years). They are provided by a regionalized stochastic hourly point rainfall generator, the SHYREG method which was previously developed by Irstea (Arnaud et al., 2007; Cantet and Arnaud, 2014). Being calibrated independently on numerous raingauges data (with an average density across the country of 1 raingauge per 200 km²), this method suffers from a limitation common to point-process rainfall generators: it can only reproduce point rainfall patterns and has no capacity to generate rainfall fields. It can't hence provide areal rainfall quantiles, the estimation of the latter being however needed for the construction of design rainfall or for the diagnostic of observed events. One means of bridging this gap between our local rainfall quantiles and areal rainfall quantiles is given by the concept of probabilistic areal reduction factors of rainfall (ARF) as defined by Omolayo (1993). This concept enables to estimate areal rainfall of a particular frequency within a certain amount of time from point rainfalls of the same frequency and duration. Assessing such ARF for the whole French territory is of particular interest since it should allow us to compute areal rainfall quantiles, and eventually watershed rainfall quantiles, by using the already available grids of statistical point rainfall of the SHYREG method. Our purpose was then to assess these ARF thanks to long time-series of spatial rainfall data. We have used two sets of rainfall fields: i) hourly rainfall fields from a 10-year reference database of Quantitative Precipitation Estimation (QPE) over France (Tabary et al., 2012), ii) daily rainfall fields resulting from a 53-year

  1. Spatial Coherence of Tropical Rainfall

    Science.gov (United States)

    Ratan, Ram; Venugopal, V.; Sukhatme, Jai; Murtugudde, Raghu

    2014-05-01

    We characterise the spatial coherence of tropical rain and its wet spells from observations (TRMM) and assess if models (CMIP5) are able to reproduce the observed features. Based on 15 years (1998-2012) of TRMM 3B42 (V7) 1-degree, daily rainfall, we estimate the spatial decorrelation scale (e-folding distance) of rain at each location in the tropics. A ratio of zonal to meridional spatial scales clearly illustrates that while rain patterns tend to be anisotropic (ratio of 4) over tropical ocean regions (particularly over Pacific ITCZ); over land regions, rain tends to be mostly isotropic. This contrast between ocean and land appears to be reasonably well captured by CMIP5 models, although the anisotropy (ratio) over ocean is much higher than in observations. A very curious behaviour in observations is the presence of a coherent band of spatial decorrelation lengths straddling the equator, in the East Pacific, reminiscent of a double ITCZ that some models tend to simulate. A similar analysis of wet spells of different durations suggests that the decorrelation scale is largely independent of the duration of wet spell.

  2. Meso-scale distribution of summer monsoon rainfall near the Western Ghats (India)

    Science.gov (United States)

    Patwardhan, S. K.; Asnani, G. C.

    2000-04-01

    The spatial distribution of southwest monsoon rainfall is studied over Maharashtra State (India), which includes part of the well-known Western Ghats mountain range, near its western boundary, running almost from north to south, perpendicular to the summer monsoon current in the lower troposphere. Meso-scale analysis of daily rainfall is performed for Maharashtra State, including the Western Ghats, for the two mid-monsoon months of July and August, during the 10-year period of 1971-1980. Strong and weak monsoon days were identified for the 5-year period of 1976-1980. The meso-scale pattern of average daily rainfall is obtained separately for strong and for weak monsoon conditions.All these average patterns show the following features: (i) the rainfall increases rapidly from the Arabian Sea coast close to the line of maximum height of the Western Ghats; (ii) there are two rainfall maxima corresponding to the two mountain peaks parallel to the coast line; (iii) between the two mountain peaks, there is a valley which is narrow at the western end (upwind end), broadening towards the east (on the downwind side). Ground contour height of the valley rises eastwards and ends as a part of the Deccan Plateau east of the Ghats. Here the valley opens out like a funnel with higher mountains flanking its two sides. In the valley, the rainfall increases from the coast up to the line of maximum height of the Ghats, and then decreases eastwards towards the plateau. The rainfall isopleths also take a funnel-shaped configuration. An interesting feature is that near the wider section of the valley funnel, there is a rainfall minimum and then the rainfall increases further eastwards on the downwind side. This feature of rainfall minimum is somewhat similar to the rainfall minimum reported by Asnani and Kinuthia (personal communication); Asnani (Asnani GC. 1993. Tropical Meteorology, Vol. I. Prof. G.C. Asnani: Pune, India; 603) attributed the rainfall minimum to the Bernoulli effect. A

  3. Trends in rainfall and rainfall-related extremes in the east coast of peninsular Malaysia

    Indian Academy of Sciences (India)

    Olaniya Olusegun Mayowa; Sahar Hadi Pour; Shamsuddin Shahid; Morteza Mohsenipour; Sobri Bin Harun; Arien Heryansyah; Tarmizi Ismail

    2015-12-01

    The coastlines have been identified as the most vulnerable regions with respect to hydrological hazards as a result of climate change and variability. The east of peninsular Malaysia is not an exception for this, considering the evidence of heavy rainfall resulting in floods as an annual phenomenon and also water scarcity due to long dry spells in the region. This study examines recent trends in rainfall and rainfallrelated extremes such as, maximum daily rainfall, number of rainy days, average rainfall intensity, heavy rainfall days, extreme rainfall days, and precipitation concentration index in the east coast of peninsular Malaysia. Recent 40 years (1971–2010) rainfall records from 54 stations along the east coast of peninsular Malaysia have been analyzed using the non-parametric Mann–Kendall test and the Sen's slope method. The Monte Carlo simulation technique has been used to determine the field significance of the regional trends. The results showed that there was a substantial increase in the annual rainfall as well as the rainfall during the monsoon period. Also, there was an increase in the number of heavy rainfall days during the past four decades.

  4. A point rainfall model and rainfall intensity-duration-frequency analysis

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Chul-Sang; Jung, Kwang-Sik [Korea University, Jochiwon(Korea); Kim, Nam-Won [Korea Institute of Construction Technology, Koyang(Korea)

    2001-12-31

    This study proposes a theoretical methodology for deriving a rainfall intensity-duration-frequency(I-D-F) curve using a simple rectangular pulses Poisson process model. As the I-D-F curve derived by considering the model structure is dependent on the rainfall model parameters estimated using the observed first and second order statistics, it becomes less sensitive to the unusual rainfall events than that derived using the annual maxima rainfall series. This study has been applied to the rainfall data at Seoul and Incheon stations to check its applicability by comparing the two I-D-F curves from the model and the data. The results obtained are as followed. (1) As the duration becomes longer, the overlap probability increases significantly. However, its contribution to the rainfall intensity decreases a little. (2) When considering the overlap of each rainfall event, especially for large duration and return period, we could see obvious increases of rainfall intensity. This result is normal as the rainfall intensity is calculated by considering both the overlap probability and return period. Also, the overlap effect for Seoul station is found much higher than that for Incheon station, which is mainly due to the different overlap probabilities calculated using different rainfall model parameter sets. (3) As the rectangular pulses Poisson processes model used in this study cannot consider the clustering characteristics of rainfall, the derived I-D-F curves show less rainfall intensities than those from the annual maxima series. However, overall pattern of both I-D-F curves are found very similar, and the difference is believed to be overcome by use of a rainfall model with the clustering consideration. (author). 14 refs., 6 tabs., 2 figs.

  5. Physical simulation of urban rainfall infiltration

    Institute of Scientific and Technical Information of China (English)

    LI Jie; ZENG Bing; WANG Yan-xia; SHEN Lei

    2008-01-01

    To meet the demand of urban rainwater integrated management, we designed and complemented a physical simulation experimental system of urban rainfall infiltration regulation parameters. We discuss the feasibility of quantitative regulations of urban underlying surface rainfall infiltration conditions and a practical application of a simulated experimental system. In a comprehensive analysis of the composition of an effective rainwater harvesting system and selection of water storage material, we simulated the major parameters of an experimental area rainfall, soil moisture and water storage capacity by providing an effective regulation of the experimental area runoff coefficient, obtained from basic data.

  6. Detecting Rainfall Onset Using Sky Images

    CERN Document Server

    Dev, Soumyabrata; Lee, Yee Hui; Winkler, Stefan

    2016-01-01

    Ground-based sky cameras (popularly known as Whole Sky Imagers) are increasingly used now-a-days for continuous monitoring of the atmosphere. These imagers have higher temporal and spatial resolutions compared to conventional satellite images. In this paper, we use ground-based sky cameras to detect the onset of rainfall. These images contain additional information about cloud coverage and movement and are therefore useful for accurate rainfall nowcast. We validate our results using rain gauge measurement recordings and achieve an accuracy of 89% for correct detection of rainfall onset.

  7. Rainfall intensity switches ecohydrological runoff/runon redistribution patterns in dryland vegetation patches.

    Science.gov (United States)

    Magliano, Patricio N; Breshears, David D; Fernández, Roberto J; Jobbágy, Esteban G

    2015-12-01

    Effectively managing net primary productivity in drylands for grazing and other uses depends on understanding how limited rainfall input is redistributed by runoff and runon among vegetation patches, particularly for patches that contrast between lesser and greater amounts of vegetation cover. Due in part to data limitations, ecohydrologists generally have focused on rainfall event size to characterize water redistribution processes. Here we use soil moisture data from a semiarid woodland to highlight how, when event size is controlled and runoff and interception are negligible at the stand scale, rainfall intensity drives the relationship between water redistribution and canopy and soil patch attributes. Horizontal water redistribution variability increased with rainfall intensity and differed between patches with contrasting vegetation cover. Sparsely vegetated patches gained relatively more water during lower intensity events, whereas densely vegetated ones gained relatively more water during higher intensity events. Consequently, range managers need to account for the distribution of rainfall event intensity, as well as event size, to assess the consequences of climate variability and change on net primary productivity. More generally, our results suggest that rainfall intensity needs to be considered in addition to event size to understand vegetation patch dynamics in drylands.

  8. A space-time stochastic model of rainfall for satellite remote-sensing studies

    Science.gov (United States)

    Bell, Thomas L.

    1987-01-01

    A model of the spatial and temporal distribution of rainfall is described that produces random spatial rainfall patterns with these characteristics: (1) the model is defined on a grid with each grid point representing the average rain rate over the surrounding grid box, (2) rain occurs at any one grid point, on average, a specified percentage of the time and has a lognormal probability distribution, (3) spatial correlation of the rainfall can be arbitrarily prescribed, and (4) time stepping is carried out so that large-scale features persist longer than small-scale features. Rain is generated in the model from the portion of a correlated Gaussian random field that exceeds a threshold. The portion of the field above the threshold is rescaled to have a lognormal probability distribution. Sample output of the model designed to mimic radar observations of rainfall during the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE), is shown. The model is intended for use in evaluating sampling strategies for satellite remote-sensing of rainfall and for development of algorithms for converting radiant intensity received by an instrument from its field of view into rainfall amount.

  9. A Bivariate Mixed Distribution with a Heavy-tailed Component and its Application to Single-site Daily Rainfall Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Li, Chao ..; Singh, Vijay P.; Mishra, Ashok K.

    2013-02-06

    This paper presents an improved brivariate mixed distribution, which is capable of modeling the dependence of daily rainfall from two distinct sources (e.g., rainfall from two stations, two consecutive days, or two instruments such as satellite and rain gauge). The distribution couples an existing framework for building a bivariate mixed distribution, the theory of copulae and a hybrid marginal distribution. Contributions of the improved distribution are twofold. One is the appropriate selection of the bivariate dependence structure from a wider admissible choice (10 candidate copula families). The other is the introduction of a marginal distribution capable of better representing low to moderate values as well as extremes of daily rainfall. Among several applications of the improved distribution, particularly presented here is its utility for single-site daily rainfall simulation. Rather than simulating rainfall occurrences and amounts separately, the developed generator unifies the two processes by generalizing daily rainfall as a Markov process with autocorrelation described by the improved bivariate mixed distribution. The generator is first tested on a sample station in Texas. Results reveal that the simulated and observed sequences are in good agreement with respect to essential characteristics. Then, extensive simulation experiments are carried out to compare the developed generator with three other alternative models: the conventional two-state Markov chain generator, the transition probability matrix model and the semi-parametric Markov chain model with kernel density estimation for rainfall amounts. Analyses establish that overall the developed generator is capable of reproducing characteristics of historical extreme rainfall events and is apt at extrapolating rare values beyond the upper range of available observed data. Moreover, it automatically captures the persistence of rainfall amounts on consecutive wet days in a relatively natural and easy way

  10. Research on the Fine-Scale Spatial Uniformity of Natural Rainfall and Rainfall from a Rainfall Simulator with a Rotary Platform (RSRP

    Directory of Open Access Journals (Sweden)

    Bo Liu

    2017-06-01

    Full Text Available Abstract: The accurate production of a rainfall environment similar to natural rainfall by a rainfall simulator (RS is a crucial and challenging task in rainfall instrument testing or calibration. Although the spatial uniformity of rainfall accumulation is a key parameter of an RS, the spatial uniformity comparison between simulated rainfall and natural rainfall, and the spatial uniformity improvements for an RS are scant in the literature. In this study, a fine-scale natural rainfall experiment was studied using the same testing methods of an RS and the rainfall uniformity was evaluated using the Christiansen Uniformity Coefficient (CU. Simultaneously, factors influencing the spatial uniformity of natural rainfall, including the average rainfall accumulation (RA, the deviation of RA, and the area of the test zone, were analyzed. The results successfully reproduced some of the behaviors observed in natural rainfall experiments, showing that CU is dependent on these parameters. Based on these studies, we developed a rainfall simulator with a rotary platform (RSRP and found that although spatial uniformity of the RSRP was greatly improved using an appropriate rotary speed, it was not consistent with the spatial uniformity of natural rainfall. Furthermore, we tested four tipping-bucket rain gauges using this imperfect RSRP, and found that the RSRP might acquire the instrumental errors associated with RA for a tested rainfall instrument.

  11. A verification of monthly weather forecasts in the seventies

    NARCIS (Netherlands)

    Oerlemans, J.; Nap, J.L.; Dool, H.M. van den

    1981-01-01

    Monthly forecasts of temperature, rainfall and sunshine have been verified during the period 1970–79. The predictions were based on seven different schemes. Of the seven methods, five refer to De Bilt (The Netherlands), one to southeast England and one to the Federal Republic of Germany. The results

  12. Spatial variability in the isotopic composition of rainfall in a small headwater catchment and its effect on hydrograph separation

    Science.gov (United States)

    Fischer, Benjamin M. C.; van Meerveld, H. J. (Ilja); Seibert, Jan

    2017-04-01

    Isotope hydrograph separation (IHS) is a valuable tool to study runoff generation processes. To perform an IHS, samples of baseflow (pre-event water) and streamflow are taken at the catchment outlet. For rainfall (event water) either a bulk sample is collected or it is sampled sequentially during the event. For small headwater catchment studies, event water samples are usually taken at only one sampling location in or near the catchment because the spatial variability in the isotopic composition of rainfall is assumed to be small. However, few studies have tested this assumption. In this study, we investigated the spatiotemporal variability in the isotopic composition of rainfall and its effects on IHS results using detailed measurements from a small pre-alpine headwater catchment in Switzerland. Rainfall was sampled sequentially at eight locations across the 4.3 km2 Zwäckentobel catchment and stream water was collected in three subcatchments (0.15, 0.23, and 0.70 km2) during ten events. The spatial variability in rainfall amount, average and maximum rainfall intensity and the isotopic composition of rainfall was different for each event. There was no significant relation between the isotopic composition of rainfall and total rainfall amount, rainfall intensity or elevation. For eight of the ten studied events the temporal variability in the isotopic composition of rainfall was larger than the spatial variability in the rainfall isotopic composition. The isotope hydrograph separation results, using only one rain sampler, varied considerably depending on which rain sampler was used to represent the isotopic composition of event water. The calculated minimum pre-event water contributions differed up to 60%. The differences were particularly large for events with a large spatial variability in the isotopic composition of rainfall and a small difference between the event and pre-event water isotopic composition. Our results demonstrate that even in small catchments

  13. Spatial estimation of debris flows-triggering rainfall and its dependence on rainfall severity

    Science.gov (United States)

    Destro, Elisa; Marra, Francesco; Nikolopoulos, Efthymios; Zoccatelli, Davide; Creutin, Jean-Dominique; Borga, Marco

    2016-04-01

    Forecasting the occurrence of landslides and debris flows (collectively termed 'debris flows' hereinafter) is fundamental for issuing hazard warnings, and focuses largely on rainfall as a triggering agent. Debris flow forecasting relies very often on the identification of combinations of depth and duration of rainfall - rainfall thresholds - that trigger widespread debris flows. Rainfall estimation errors related to the sparse nature of raingauge data are enhanced in case of convective rainfall events characterized by limited spatial extent. Such errors have been shown to cause underestimation of the rainfall thresholds and, thus, less efficient forecasts of debris flows occurrence. This work examines the spatial organization of debris flows-triggering rainfall around the debris flow initiation points using high-resolution, carefully corrected radar data for a set of short duration (debris-flow triggering rainfall events that occurred in the study area between 2005 and 2014. The selected events are among the most severe in the region during this period and triggered a total of 99 debris flows that caused significant damage to people and infrastructures. We show that the spatial rainfall organisation depends on the severity (measured via the estimated return time-RT) of the debris flow-triggering rainfall. For more frequent events (RTdebris flow location coincides with a local minimum, whereas for less frequent events (RT>20 yrs) the triggering rainfall presents a local peak corresponding to the debris flow initiation point. Dependence of these features on rainfall duration is quite limited. The characteristics of the spatial rainfall organisation are exploited to understand the performances and results of three different rainfall interpolation techniques: nearest neighbour (NN), inverse distance weighting (IDW) and ordinary kriging (OK). We show that the features of the spatial organization of the debris flow triggering rainfall explain the biases in the

  14. Spatial and temporal characteristics of rainfall across Ganjiang River Basin in China

    Science.gov (United States)

    Xiao, Yang; Zhang, Xiang; Wan, Hui; Wang, Yeqiao; Liu, Cheng; Xia, Jun

    2016-04-01

    The hydrological variations of Ganjiang River Basin have significant influence on the ecological environment of Poyang Lake, which is one of the largest freshwater lake and wetland in the world. This study analyzed the spatial and temporal characteristics of rainfall across Ganjiang River Basin. The analyses include annual total rainfall amount (ATRA), annual total rainy day (ATRD) and annual mean daily rainfall intensity (AMDRI). To detect changes in the hydrological trends, data from 19 rainfall stations from 1953 to 2013 were used in the analyses. First, quality control and homogeneity detection was carried out to examine the annual rainfall series. Second, the spatial correlation analysis was used to identify the spatial relationship among the measurements from different stations. Finally, the statistics of coefficient of variation (CV) and average were used to analyze the interannual variation trend. The modified Mann-Kendall (MMK) trend test method was used to detect the temporal characteristics of rainfall. The results include: (1) Some outliers were detected and corrected. (2) The correlation of ATRA and ATRD series of all the stations had lower spatial variability while the AMDRI series of all the stations had higher spatial variability. On the other hand, the ATRA, ATRD and AMDRI series of single stations show similar spatial variability and the influencing radius of the rainfall events was less than 50 km. (3) the rainfall at the northern and southern parts of the basin had smaller CV. Further, by applying the MMK test method to the ATRA, ATRD, and AMDRI series, the ATRA series has an increasing trend which is opposite to that of the ATRD series. The increasing trend in the ATRA series also led to the increasing trend in the AMDRI series. These stations are mainly in central and northern parts of the basin which are more likely to experience droughts and floods. Thus, for the central and northern parts of the basin, they should receive particular

  15. Rainfall estimation from microwave links in São Paulo, Brazil.

    Science.gov (United States)

    Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2017-04-01

    Rainfall estimation from microwave link networks has been successfully demonstrated in countries such as the Netherlands, Israel and Germany. The path-averaged rainfall intensity can be computed from the signal attenuation between cell phone towers. Although this technique is still in development, it offers great opportunities to retrieve rainfall rates at high spatiotemporal resolutions very close to the ground surface. High spatiotemporal resolutions and closer-to-ground measurements are highly appreciated, especially in urban catchments where high-impact events such as flash-floods develop in short time scales. We evaluate here this rainfall measurement technique for a tropical climate, something that has hardly been done previously. This is highly relevant since many countries with few surface rainfall observations are located in the tropics. The test-bed is the Brazilian city of São Paulo. The performance of 16 microwave links was evaluated, from a network of 200 links, for the last 3 months of 2014. The open software package RAINLINK was employed to obtain link rainfall estimates. The evaluation was done through a dense automatic gauge network. Results are promising and encouraging, especially for short links for which a high correlation (> 0.9) and a low bias (< 5%) were obtained.

  16. DETERMINATION OF SPACE-TIME PATTERNS AND RAINFALL HOMOGENEOUS AREAS AT MINAS GERAIS STATE

    Directory of Open Access Journals (Sweden)

    Leandro Rodrigues Souza

    2011-07-01

    Full Text Available The present study aimed to determine the spatial and temporal rainfall in Minas Gerais State relating to their respective rainfall weather systems and to identify homogeneous regions. The method of Factorial Analysis in Principal Components and Hierarchical Grouping were used to determine the seasonal and spatial patterns and homogeneous groups of rainfall. It was observed that the three first principal components describe 80.4% of the total variance of rainfall observed, in that the first factor explains 34.3% of the variance and showed high correlations with the rains from December to April in the southern State, which is influenced, mainly by the performance of frontal systems. The second factor explains 26.6% of data variance and showed significant correlations with rainfall from May to September in the northwest and southwest, and is possibly related to cold fronts and the South Atlantic Convergence Zone. Finally, the relative contributions to the third factor, with 19.5% of data variance accounted for the months of October and November, and are associated with mesoscale and microscale systems. Four homogeneous regions in relation to seasonal and interannual variability of rainfall were found. It concludes that statistical methods tested showed satisfactory results for this type of analyze, corroborates previous studies.

  17. Tropical Atlantic Contributions to Strong Rainfall Variability Along the Northeast Brazilian Coast

    Directory of Open Access Journals (Sweden)

    G. A. Hounsou-gbo

    2015-01-01

    Full Text Available Tropical Atlantic (TA Ocean-atmosphere interactions and their contributions to strong variability of rainfall along the Northeast Brazilian (NEB coast were investigated for the years 1974–2008. The core rainy seasons of March-April and June-July were identified for Fortaleza (northern NEB; NNEB and Recife (eastern NEB; ENEB, respectively. Lagged linear regressions between sea surface temperature (SST and pseudo wind stress (PWS anomalies over the entire TA and strong rainfall anomalies at Fortaleza and Recife show that the rainfall variability of these regions is differentially influenced by the dynamics of the TA. When the Intertropical Convergence Zone is abnormally displaced southward a few months prior to the NNEB rainy season, the associated meridional mode increases humidity and precipitation during the rainy season. Additionally, this study shows predictive effect of SST, meridional PWS, and barrier layer thickness, in the Northwestern equatorial Atlantic, on the NNEB rainfall. The dynamical influence of the TA on the June-July ENEB rainfall variability shows a northwestward-propagating area of strong, positively correlated SST from the southeastern TA to the southwestern Atlantic warm pool (SAWP offshore of Brazil. Our results also show predictive effect of SST, zonal PWS, and mixed layer depth, in the SAWP, on the ENEB rainfall.

  18. Global Warming Induced Changes in Rainfall Characteristics in IPCC AR5 Models

    Science.gov (United States)

    Lau, William K. M.; Wu, Jenny, H.-T.; Kim, Kyu-Myong

    2012-01-01

    Changes in rainfall characteristic induced by global warming are examined from outputs of IPCC AR5 models. Different scenarios of climate warming including a high emissions scenario (RCP 8.5), a medium mitigation scenario (RCP 4.5), and 1% per year CO2 increase are compared to 20th century simulations (historical). Results show that even though the spatial distribution of monthly rainfall anomalies vary greatly among models, the ensemble mean from a sizable sample (about 10) of AR5 models show a robust signal attributable to GHG warming featuring a shift in the global rainfall probability distribution function (PDF) with significant increase (>100%) in very heavy rain, reduction (10-20% ) in moderate rain and increase in light to very light rains. Changes in extreme rainfall as a function of seasons and latitudes are also examined, and are similar to the non-seasonal stratified data, but with more specific spatial dependence. These results are consistent from TRMM and GPCP rainfall observations suggesting that extreme rainfall events are occurring more frequently with wet areas getting wetter and dry-area-getting drier in a GHG induced warmer climate.

  19. Discovering historical rainfall erosivity with a parsimonious approach: A case study in Western Germany

    Science.gov (United States)

    Diodato, Nazzareno; Borrelli, Pasquale; Fiener, Peter; Bellocchi, Gianni; Romano, Nunzio

    2017-01-01

    An in-depth analysis of the interannual variability of storms is required to detect changes in soil erosive power of rainfall, which can also result in severe on-site and off-site damages. Evaluating long-term rainfall erosivity is a challenging task, mainly because of the paucity of high-resolution historical precipitation observations that are generally reported at coarser temporal resolutions (e.g., monthly to annual totals). In this paper we suggest overcoming this limitation through an analysis of long-term processes governing rainfall erosivity with an application to datasets available the central Ruhr region (Western Germany) for the period 1701-2011. Based on a parsimonious interpretation of seasonal rainfall-related processes (from spring to autumn), a model was derived using 5-min erosivity data from 10 stations covering the period 1937-2002, and then used to reconstruct a long series of annual rainfall erosivity values. Change-points in the evolution of rainfall erosivity are revealed over the 1760s and the 1920s that mark three sub-periods characterized by increasing mean values. The results indicate that the erosive hazard tends to increase as a consequence of an increased frequency of extreme precipitation events occurred during the last decades, characterized by short-rain events regrouped into prolonged wet spells.

  20. Spatial Interpolation of Daily Rainfall Data for Local Climate Impact Assessment over Greater Sydney Region

    Directory of Open Access Journals (Sweden)

    Xihua Yang

    2015-01-01

    Full Text Available This paper presents spatial interpolation techniques to produce finer-scale daily rainfall data from regional climate modeling. Four common interpolation techniques (ANUDEM, Spline, IDW, and Kriging were compared and assessed against station rainfall data and modeled rainfall. The performance was assessed by the mean absolute error (MAE, mean relative error (MRE, root mean squared error (RMSE, and the spatial and temporal distributions. The results indicate that Inverse Distance Weighting (IDW method is slightly better than the other three methods and it is also easy to implement in a geographic information system (GIS. The IDW method was then used to produce forty-year (1990–2009 and 2040–2059 time series rainfall data at daily, monthly, and annual time scales at a ground resolution of 100 m for the Greater Sydney Region (GSR. The downscaled daily rainfall data have been further utilized to predict rainfall erosivity and soil erosion risk and their future changes in GSR to support assessments and planning of climate change impact and adaptation in local scale.

  1. Temporal analysis (1940-2010) of rainfall aggressiveness in the Iberian Peninsula basins

    Science.gov (United States)

    García-Barrón, L.; Camarillo, J. M.; Morales, J.; Sousa, A.

    2015-06-01

    Rainfall aggressiveness causes environmental impacts and it is related to several natural hazards. Therefore, this parameter has been chosen as an environmental indicator. The present study is based on the monthly estimated rainfall using the Precipitation Runoff Integrated Model (SIMPA) for each Spanish hydrographic basin from 1940 to 2010. The main aim is to analyse temporal irregularity of rainfall aggressiveness in large geographic areas and to extract spatio-temporal patterns. For each year the rainfall aggressiveness was calculated using the Modified Fournier Index (IFM) and Oliver's Index of Precipitation Concentration (IPC). The temporal variability of the annual series of these indices was analysed for each zone delimited. The results obtained made it possible to characterize the rainfall aggressiveness in the Iberian Peninsula and to determine its evolution over the past decades. They also reveal that the general pattern of the rainfall aggressiveness is determined by the dual effect of latitude (north-south) and longitude (east-west) as a result of the different maritime influences of the Atlantic and the Mediterranean watersheds. Finally a new variable is proposed, the Annual Aggressiveness Risk RA, which summarizes the information provided by IFM and IPC.

  2. Association of Taiwan’s Rainfall Patterns with Large-Scale Oceanic and Atmospheric Phenomena

    Directory of Open Access Journals (Sweden)

    Yi-Chun Kuo

    2016-01-01

    Full Text Available A 50-year (1960–2009 monthly rainfall gridded dataset produced by the Taiwan Climate Change Projection and Information Platform Project was presented in this study. The gridded data (5 × 5 km displayed influence of topography on spatial variability of rainfall, and the results of the empirical orthogonal functions (EOFs analysis revealed the patterns associated with the large-scale sea surface temperature variability over Pacific. The first mode (65% revealed the annual peaks of large rainfall in the southwestern mountainous area, which is associated with southwest monsoons and typhoons during summertime. The second temporal EOF mode (16% revealed the rainfall variance associated with the monsoon and its interaction with the slopes of the mountain range. This pattern is the major contributor to spatial variance of rainfall in Taiwan, as indicated by the first mode (40% of spatial variance EOF analysis. The second temporal EOF mode correlated with the El Niño Southern Oscillation (ENSO. In particular, during the autumn of the La Niña years following the strong El Niño years, the time-varying amplitude was substantially greater than that of normal years. The third temporal EOF mode (7% revealed a north-south out-of-phase rainfall pattern, the slowly evolving variations of which were in phase with the Pacific Decadal Oscillation. Because of Taiwan’s geographic location and the effect of local terrestrial structures, climate variability related to ENSO differed markedly from other regions in East Asia.

  3. Rainfall erosivity in subtropical catchments and implications for erosion and particle-bound contaminant transfer: a case-study of the Fukushima region

    Directory of Open Access Journals (Sweden)

    J. P. Laceby

    2015-07-01

    Full Text Available The Fukushima Dai-ichi nuclear power plant (FDNPP accident in March 2011 resulted in a significant fallout of radiocesium over the Fukushima region. After reaching the soil surface, radiocesium is almost irreversibly bound to fine soil particles. Thereafter, rainfall and snow melt run-off events transfer particle-bound radiocesium downstream. Erosion models, such as the Universal Soil Loss Equation (USLE, depict a proportional relationship between rainfall and soil erosion. As radiocesium is tightly bound to fine soil and sediment particles, characterizing the rainfall regime of the fallout-impacted region is fundamental to modelling and predicting radiocesium migration. Accordingly, monthly and annual rainfall data from ~ 60 meteorological stations within a 100 km radius of the FDNPP were analysed. Monthly rainfall erosivity maps were developed for the Fukushima coastal catchments illustrating the spatial heterogeneity of rainfall erosivity in the region. The mean average rainfall in the Fukushima region was 1387 mm yr−1 (σ 230 with the mean rainfall erosivity being 2785 MJ mm ha−1 yr−1 (σ 1359. The results indicate that the majority of rainfall (60 % and rainfall erosivity (86 % occurs between June and October. During the year, rainfall erosivity evolves positively from northwest to southeast in the eastern part of the prefecture, whereas a positive gradient from north to south occurs in July and August, the most erosive months of the year. During the typhoon season, the coastal plain and eastern mountainous areas of the Fukushima prefecture, including a large part of the contamination plume, are most impacted by erosive events. Understanding these rainfall patterns, particularly their spatial and temporal variation, is fundamental to managing soil and particle-bound radiocesium transfers in the Fukushima region. Moreover, understanding the impact of typhoons is important for managing sediment transfers in subtropical regions impacted

  4. Rainfall erosivity in subtropical catchments and implications for erosion and particle-bound contaminant transfer: a case-study of the Fukushima region

    Science.gov (United States)

    Laceby, J. P.; Chartin, C.; Evrard, O.; Onda, Y.; Garcia-Sanchez, L.; Cerdan, O.

    2015-07-01

    The Fukushima Dai-ichi nuclear power plant (FDNPP) accident in March 2011 resulted in a significant fallout of radiocesium over the Fukushima region. After reaching the soil surface, radiocesium is almost irreversibly bound to fine soil particles. Thereafter, rainfall and snow melt run-off events transfer particle-bound radiocesium downstream. Erosion models, such as the Universal Soil Loss Equation (USLE), depict a proportional relationship between rainfall and soil erosion. As radiocesium is tightly bound to fine soil and sediment particles, characterizing the rainfall regime of the fallout-impacted region is fundamental to modelling and predicting radiocesium migration. Accordingly, monthly and annual rainfall data from ~ 60 meteorological stations within a 100 km radius of the FDNPP were analysed. Monthly rainfall erosivity maps were developed for the Fukushima coastal catchments illustrating the spatial heterogeneity of rainfall erosivity in the region. The mean average rainfall in the Fukushima region was 1387 mm yr-1 (σ 230) with the mean rainfall erosivity being 2785 MJ mm ha-1 yr-1 (σ 1359). The results indicate that the majority of rainfall (60 %) and rainfall erosivity (86 %) occurs between June and October. During the year, rainfall erosivity evolves positively from northwest to southeast in the eastern part of the prefecture, whereas a positive gradient from north to south occurs in July and August, the most erosive months of the year. During the typhoon season, the coastal plain and eastern mountainous areas of the Fukushima prefecture, including a large part of the contamination plume, are most impacted by erosive events. Understanding these rainfall patterns, particularly their spatial and temporal variation, is fundamental to managing soil and particle-bound radiocesium transfers in the Fukushima region. Moreover, understanding the impact of typhoons is important for managing sediment transfers in subtropical regions impacted by cyclonic activity.

  5. Maritime Continent rainfall variability during the TRMM era: The role of monsoon, topography and El Niño Modoki

    Science.gov (United States)

    As-syakur, Abd. Rahman; Osawa, Takahiro; Miura, Fusanori; Nuarsa, I. Wayan; Ekayanti, Ni Wayan; Dharma, I. Gusti Bagus Sila; Adnyana, I. Wayan Sandi; Arthana, I. Wayan; Tanaka, Tasuku

    2016-09-01

    Rainfall is among the most important climatic elements of the Maritime Continent. The Maritime Continent rainfall climate is uniquely located in the world's most active convective area. Satellite data measured by the Tropical Rainfall Measuring Mission (TRMM) 3B43 based high-resolution rainfall products represent monthly Maritime Continent rainfall characteristics over 16 years. Several statistical scores were employed to analyse annual means, linear trends, seasonal means, and anomalous Maritime Continent rainfall characteristic percentages. The effects of land and topography on rainfall quantities were also studied and compared with the Global Precipitation Climatology Project (GPCP) gridded precipitation estimates which has low-resolution. Comparison also applied on linear correlation and partial correlation techniques to determine the relationship between rainfall and the El Niño Modoki and El Niño-Southern Oscillation (ENSO; hereafter conventional El Niño). The results show that north-south Maritime Continent precipitation is associated with and generated by the northwest and southeast monsoon patterns. In addition, the large-scale circulations are linked with heavy rainfall over this land-ocean region due to large-scale island-topography-induced convective organization. The rainfall responses to El Niño Modoki and conventional El Niño clearly indicated the times at which the conventional El Niño had a higher impact than El Niño Modoki, especially during northern winter and spring, and vice versa during northern fall, and similarly affect during northern summer. Furthermore, the dynamic movements of rainfall anomaly that are caused by El Niño Modoki and the conventional El Niño events spanned from the southwest during June-July-August (JJA) to throughout the northeast ending in March-April-May (MAM).

  6. Rainfall mechanisms for the dominant rainfall mode over Zimbabwe relative to ENSO and/or IODZM.

    Science.gov (United States)

    Manatsa, Desmond; Mukwada, Geoffrey

    2012-01-01

    Zimbabwe's homogeneous precipitation regions are investigated by means of principal component analysis (PCA) with regard to the underlying processes related to ENSO and/or Indian Ocean Dipole zonal mode (IODZM). Station standardized precipitation index rather than direct rainfall values represent the data matrix used in the PCA. The results indicate that the country's rainfall is highly homogeneous and is dominantly described by the first principal mode (PC1). This leading PC can be used to represent the major rainfall patterns affecting the country, both spatially and temporarily. The current practice of subdividing the country into the two seasonal rainfall forecast zones becomes irrelevant. Partial correlation analysis shows that PC1 is linked more to the IODZM than to the traditional ENSO which predominantly demonstrates insignificant association with PC1. The pure IODZM composite is linked to the most intense rainfall suppression mechanisms, while the pure El Niño composite is linked to rainfall enhancing mechanisms.

  7. Maximum daily rainfall in South Korea

    Indian Academy of Sciences (India)

    Saralees Nadarajah; Dongseok Choi

    2007-08-01

    Annual maxima of daily rainfall for the years 1961–2001 are modeled for five locations in South Korea (chosen to give a good geographical representation of the country). The generalized extreme value distribution is fitted to data from each location to describe the extremes of rainfall and to predict its future behavior. We find evidence to suggest that the Gumbel distribution provides the most reasonable model for four of the five locations considered. We explore the possibility of trends in the data but find no evidence suggesting trends. We derive estimates of 10, 50, 100, 1000, 5000, 10,000, 50,000 and 100,000 year return levels for daily rainfall and describe how they vary with the locations. This paper provides the first application of extreme value distributions to rainfall data from South Korea.

  8. Assessing Climate Variability using Extreme Rainfall and ...

    African Journals Online (AJOL)

    user1

    As noted by the Bureau of Meteorology, Canada, to examine whether such ... their local climate, a threshold considered extreme in one part of Australia could be ... (extreme frequency); the average intensity of rainfall from extreme events.

  9. Rainfall Fields: Estimation, Analysis, and Prediction

    Science.gov (United States)

    The problem of predicting rainfall and its characteristics has always been one of overriding concern for both hydrologists and meteorologists. Yet, for decades the two disciplines have pursued its solution using radically different techniques and communicating relatively little about recent advances in understanding rainfall processes, new technology, and improvements in predictive skill.Meteorologists tend to publish in journals that deal almost exclusively with atmospheric processes, while hydrologists prefer media which focus on the Earth's surface and below. Meteorologists tend to concentrate on developing and improving numerical hydrodynamical models of the atmospheric processes that generate rainfall. Their approach is essentially to solve an initial value problem where the observed three-dimensional state of the atmosphere is input to the model and the rainfall is one of the output parameters.

  10. Validation and Analysis of Microwave-Derived Rainfall Over the Tropics

    Science.gov (United States)

    1993-01-01

    Intraseasonal Oscillations In addition to the biennial signals identified by Meehl (1987), Lau and col- laborators (Peng 1987; Shen 1987) expound on...temporally integrated, over a 50 x 50 area for a minimum of one month, to create clima - tological rainfall composites. Validation of the ESMR-derived

  11. Surface temperature of the equatorial Pacific Ocean and the Indian rainfall

    Digital Repository Service at National Institute of Oceanography (India)

    Gopinathan, C.K.

    The time variation of the monthly mean surface temperature of the equatorial Pacific Ocean during 1982-1987 has been studied in relation to summer monsoon rainfall over India The ENSO events of 1982 and 1987 were related to a significant reduction...

  12. A method for combining passive microwave and infrared rainfall observations

    Science.gov (United States)

    Kummerow, Christian; Giglio, Louis

    1995-01-01

    Because passive microwave instruments are confined to polar-orbiting satellites, rainfall estimates must interpolate across long time periods, during which no measurements are available. In this paper the authors discuss a technique that allows one to partially overcome the sampling limitations by using frequent infrared observations from geosynchronous platforms. To accomplish this, the technique compares all coincident microwave and infrared observations. From each coincident pair, the infrared temperature threshold is selected that corresponds to an area equal to the raining area observed in the microwave image. The mean conditional rainfall rate as determined from the microwave image is then assigned to pixels in the infrared image that are colder than the selected threshold. The calibration is also applied to a fixed threshold of 235 K for comparison with established infrared techniques. Once a calibration is determined, it is applied to all infrared images. Monthly accumulations for both methods are then obtained by summing rainfall from all available infrared images. Two examples are used to evaluate the performance of the technique. The first consists of a one-month period (February 1988) over Darwin, Australia, where good validation data are available from radar and rain gauges. For this case it was found that the technique approximately doubled the rain inferred by the microwave method alone and produced exceptional agreement with the validation data. The second example involved comparisons with atoll rain gauges in the western Pacific for June 1989. Results here are overshadowed by the fact that the hourly infrared estimates from established techniques, by themselves, produced very good correlations with the rain gauges. The calibration technique was not able to improve upon these results.

  13. Rainfall variability in suriname and its relationship with the tropical Pacific ENSO SST anomalies and the Atlantic SST anomalies

    Science.gov (United States)

    Nurmohamed, Riad; Naipal, Sieuwnath; Becker, Cor

    2007-02-01

    Spatial correlations in the annual rainfall anomalies are analyzed using principal component analysis (PCA). Cross correlation analysis and composites are used to measure the influence of sea-surface temperature anomalies (SSTAs) in the tropical Atlantic (TA) and the tropical Pacific Ocean on the seasonal rainfall in Suriname. It is shown that the spatial and time variability in rainfall is mainly determined by the meridional movement of the inter-tropical convergence zone (ITCZ). The rainfall anomalies are fairly uniform over the whole country. The strongest correlation in the December-January rainfall (short wet season) at station Cultuurtuin is found to occur with the SSTAs in the Pacific region and is about ckNino1 + 2 = 0.59 at lag 1 month. In the March-May rainfall (beginning of the long wet season), there is a lagged correlation with the SSTAs in the Pacific region (clag3Nino1 + 2 = 0.59). The June-August rainfall (end of the long wet season) shows the highest correlation with SSTAs in the TSA region and is about c = -0.52 for lag 0. In the September-November long dry season there is also a lagged correlation with the TSA SSTAs of about clag3 = 0.66. These different correlations and predictors can be used for seasonal rainfall predictions.

  14. Improving radar rainfall estimation by merging point rainfall measurements within a model combination framework

    Science.gov (United States)

    Hasan, Mohammad Mahadi; Sharma, Ashish; Mariethoz, Gregoire; Johnson, Fiona; Seed, Alan

    2016-11-01

    While the value of correcting raw radar rainfall estimates using simultaneous ground rainfall observations is well known, approaches that use the complete record of both gauge and radar measurements to provide improved rainfall estimates are much less common. We present here two new approaches for estimating radar rainfall that are designed to address known limitations in radar rainfall products by using a relatively long history of radar reflectivity and ground rainfall observations. The first of these two approaches is a radar rainfall estimation algorithm that is nonparametric by construction. Compared to the traditional gauge adjusted parametric relationship between reflectivity (Z) and ground rainfall (R), the suggested new approach is based on a nonparametric radar rainfall estimation method (NPR) derived using the conditional probability distribution of reflectivity and gauge rainfall. The NPR method is applied to the densely gauged Sydney Terrey Hills radar network, where it reduces the RMSE in rainfall estimates by 10%, with improvements observed at 90% of the gauges. The second of the two approaches is a method to merge radar and spatially interpolated gauge measurements. The two sources of information are combined using a dynamic combinatorial algorithm with weights that vary in both space and time. The weight for any specific period is calculated based on the error covariance matrix that is formulated from the radar and spatially interpolated rainfall errors of similar reflectivity periods in a cross-validation setting. The combination method reduces the RMSE by about 20% compared to the traditional Z-R relationship method, and improves estimates compared to spatially interpolated point measurements in sparsely gauged areas.

  15. A Numerical Investigation of Vapor Intrusion — the Dynamic Response of Contaminant Vapors to Rainfall Events

    Science.gov (United States)

    Shen, Rui; Pennell, Kelly G.; Suuberg, Eric M.

    2013-01-01

    The U.S. government and various agencies have published guidelines for field investigation of vapor intrusion, most of which suggest soil gas sampling as an integral part of the investigation. Contaminant soil gas data are often relatively more stable than indoor air vapor concentration measurements, but meteorological conditions might influence soil gas values. Although a few field and numerical studies have considered some temporal effects on soil gas vapor transport, a full explanation of the contaminant vapor concentration response to rainfall events is not available. This manuscript seeks to demonstrate the effects on soil vapor transport during and after different rainfall events, by applying a coupled numerical model of fluid flow and vapor transport. Both a single rainfall event and seasonal rainfall events were modeled. For the single rainfall event models, the vapor response process could be divided into three steps: namely, infiltration, water redistribution, and establishment of a water lens atop the groundwater source. In the infiltration step, rainfall intensity was found to determine the speed of the wetting front and wash-out effect on the vapor. The passage of the wetting front led to an increase of the vapor concentration in both the infiltration and water redistribution steps and this effect is noted at soil probes located 1 m below the ground surface. When the mixing of groundwater with infiltrated water was not allowed, a clean water lens accumulated above the groundwater source and led to a capping effect which can reduce diffusion rates of contaminant from the source. Seasonal rainfall with short time intervals involved superposition of the individual rainfall events. This modeling results indicated that for relatively deeper soil that the infiltration wetting front could not flood, the effects were damped out in less than a month after rain; while in the long term (years), possible formation of a water lens played a larger role in

  16. A numerical investigation of vapor intrusion--the dynamic response of contaminant vapors to rainfall events.

    Science.gov (United States)

    Shen, Rui; Pennell, Kelly G; Suuberg, Eric M

    2012-10-15

    The U.S. government and various agencies have published guidelines for field investigation of vapor intrusion, most of which suggest soil gas sampling as an integral part of the investigation. Contaminant soil gas data are often relatively more stable than indoor air vapor concentration measurements, but meteorological conditions might influence soil gas values. Although a few field and numerical studies have considered some temporal effects on soil gas vapor transport, a full explanation of the contaminant vapor concentration response to rainfall events is not available. This manuscript seeks to demonstrate the effects on soil vapor transport during and after different rainfall events, by applying a coupled numerical model of fluid flow and vapor transport. Both a single rainfall event and seasonal rainfall events were modeled. For the single rainfall event models, the vapor response process could be divided into three steps: namely, infiltration, water redistribution, and establishment of a water lens atop the groundwater source. In the infiltration step, rainfall intensity was found to determine the speed of the wetting front and wash-out effect on the vapor. The passage of the wetting front led to an increase of the vapor concentration in both the infiltration and water redistribution steps and this effect is noted at soil probes located 1m below the ground surface. When the mixing of groundwater with infiltrated water was not allowed, a clean water lens accumulated above the groundwater source and led to a capping effect which can reduce diffusion rates of contaminant from the source. Seasonal rainfall with short time intervals involved superposition of the individual rainfall events. This modeling results indicated that for relatively deeper soil that the infiltration wetting front could not flood, the effects were damped out in less than a month after rain; while in the long term (years), possible formation of a water lens played a larger role in determining

  17. Selection of meteorological parameters affecting rainfall estimation using neuro-fuzzy computing methodology

    Science.gov (United States)

    Hashim, Roslan; Roy, Chandrabhushan; Motamedi, Shervin; Shamshirband, Shahaboddin; Petković, Dalibor; Gocic, Milan; Lee, Siew Cheng

    2016-05-01

    Rainfall is a complex atmospheric process that varies over time and space. Researchers have used various empirical and numerical methods to enhance estimation of rainfall intensity. We developed a novel prediction model in this study, with the emphasis on accuracy to identify the most significant meteorological parameters having effect on rainfall. For this, we used five input parameters: wet day frequency (dwet), vapor pressure (e̅a), and maximum and minimum air temperatures (Tmax and Tmin) as well as cloud cover (cc). The data were obtained from the Indian Meteorological Department for the Patna city, Bihar, India. Further, a type of soft-computing method, known as the adaptive-neuro-fuzzy inference system (ANFIS), was applied to the available data. In this respect, the observation data from 1901 to 2000 were employed for testing, validating, and estimating monthly rainfall via the simulated model. In addition, the ANFIS process for variable selection was implemented to detect the predominant variables affecting the rainfall prediction. Finally, the performance of the model was compared to other soft-computing approaches, including the artificial neural network (ANN), support vector machine (SVM), extreme learning machine (ELM), and genetic programming (GP). The results revealed that ANN, ELM, ANFIS, SVM, and GP had R2 of 0.9531, 0.9572, 0.9764, 0.9525, and 0.9526, respectively. Therefore, we conclude that the ANFIS is the best method among all to predict monthly rainfall. Moreover, dwet was found to be the most influential parameter for rainfall prediction, and the best predictor of accuracy. This study also identified sets of two and three meteorological parameters that show the best predictions.

  18. An East Asian Subtropical Summer Monsoon Index and Its Relationship to Summer Rainfall in China

    Institute of Scientific and Technical Information of China (English)

    ZHAO Ping; ZHOU Zijiang

    2009-01-01

    Using the monthly mean NCEP/NCAR reanalysis data and the monthly rainfall observations at 160 rain gauge stations of China during 1961-1999, and based on major characteristics of the atmospheric circulation over East Asia and the western Pacific, a simple index for the East Asian subtropical summer monsoon (EASSM) is defined. The relationship between this index and summer rainfall in China and associated circulation features are examined. A comparison is made between this index and other monsoon indices. The results indicate that the index defined herein is reflective of variations of both the thermal low pressure centered in Siberia and the subtropical ridge over the western Pacific. It epitomizes the intensity of the EASSM and the variability of summer rainfall along the Yangtze River. Analysis shows that the Siberian low has a greater effect on the rainfall than the subtropical ridge, suggesting that the summer rainfall variability over the eastern parts of China is to a large extent affected by anomalies of the atmospheric circulation and cold air development in the midlatitudes. Taking into account of the effects of both the Siberian low and the subtropical ridge can better capture the summer rainfall anomalies of China. The index exhibits interannual and decadai variabilities, with high-index values occurring mainly in the 1960s and 1970s and low-index values in the 1980s and 1990s. When the EASSM index is low, the Siberian low and the subtropical ridge are weaker, and northerly wind anomalies appear at low levels over the midlatitudes and subtropics of East Asia, whereas southwesterly wind anomalies dominate in the upper troposphere over the tropics and subtropics of Asia and the western Pacific. The northerly wind anomalies bring about frequent cold air disturbances from the midlatitudes of East Asia, strengthening the convergence and ascending motions along the Meiyu front, and result in an increase of summer rainfall over the Yangtze River.

  19. 20 CFR 404.220 - Average-monthly-wage method.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Average-monthly-wage method. 404.220 Section... INSURANCE (1950- ) Computing Primary Insurance Amounts Average-Monthly-Wage Method of Computing Primary Insurance Amounts § 404.220 Average-monthly-wage method. (a) Who is eligible for this method. You...

  20. 20 CFR 404.221 - Computing your average monthly wage.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Computing your average monthly wage. 404.221... DISABILITY INSURANCE (1950- ) Computing Primary Insurance Amounts Average-Monthly-Wage Method of Computing Primary Insurance Amounts § 404.221 Computing your average monthly wage. (a) General. Under the...

  1. Drought Index Analizes With Rainfall Patern Indicators Use SPI Method (Case Study Bangga Watershed

    Directory of Open Access Journals (Sweden)

    Beti Mayasari

    2017-05-01

    Full Text Available Irregular weather and climate changes caused by El – Nino effect drought in some areas, including in Indonesia. The location of this study lies in the Bangga watershed. The purpose of this study was to determine rainfall patterns, drought level, the worst drought that occurred and the prediction for the future. One method for analysis of drought is using SPI (Standardized Precipitation Index. This method aims to calculate the value of a drought index that would indicate the level of the existing drought in a region. Data used are monthly rainfall from two station for 23 years (year 1993-2015. After analyzing the drought, the projection made with software Makesens 1.0. The study results showed that the worst drought in Bangga watershed occurred in April 2015 with drought index -3516 for one monthly SPI, -2815 for three monthly SPI, -3254 for six monthly SPI, -2171 for nine monthly SPI, and - 2922 for twelve 12 monthly SPI. Once projected until 2050, generally Bangga watershed experiencing dry conditions with the worst drought in July with a value of -3.83 for one monthly SPI, -3.65 for three monthly SPI, -3.44 for six monthly SPI, -2.6 for nine monthly SPI and -2.32 for twelve monthly SPI.

  2. Weather radar rainfall data in urban hydrology

    Science.gov (United States)

    Thorndahl, Søren; Einfalt, Thomas; Willems, Patrick; Ellerbæk Nielsen, Jesper; ten Veldhuis, Marie-Claire; Arnbjerg-Nielsen, Karsten; Rasmussen, Michael R.; Molnar, Peter

    2017-03-01

    Application of weather radar data in urban hydrological applications has evolved significantly during the past decade as an alternative to traditional rainfall observations with rain gauges. Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology necessitate an updated review of the state of the art in such radar rainfall data and applications. Three key areas with significant advances over the past decade have been identified: (1) temporal and spatial resolution of rainfall data required for different types of hydrological applications, (2) rainfall estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Based on these three fields of research, the paper provides recommendations based on an updated overview of shortcomings, gains, and novel developments in relation to urban hydrological applications. The paper also reviews how the focus in urban hydrology research has shifted over the last decade to fields such as climate change impacts, resilience of urban areas to hydrological extremes, and online prediction/warning systems. It is discussed how radar rainfall data can add value to the aforementioned emerging fields in current and future applications, but also to the analysis of integrated water systems.

  3. On the uncertainties associated with using gridded rainfall data as a proxy for observed

    Science.gov (United States)

    Tozer, C. R.; Kiem, A. S.; Verdon-Kidd, D. C.

    2012-05-01

    Gridded rainfall datasets are used in many hydrological and climatological studies, in Australia and elsewhere, including for hydroclimatic forecasting, climate attribution studies and climate model performance assessments. The attraction of the spatial coverage provided by gridded data is clear, particularly in Australia where the spatial and temporal resolution of the rainfall gauge network is sparse. However, the question that must be asked is whether it is suitable to use gridded data as a proxy for observed point data, given that gridded data is inherently "smoothed" and may not necessarily capture the temporal and spatial variability of Australian rainfall which leads to hydroclimatic extremes (i.e. droughts, floods). This study investigates this question through a statistical analysis of three monthly gridded Australian rainfall datasets - the Bureau of Meteorology (BOM) dataset, the Australian Water Availability Project (AWAP) and the SILO dataset. The results of the monthly, seasonal and annual comparisons show that not only are the three gridded datasets different relative to each other, there are also marked differences between the gridded rainfall data and the rainfall observed at gauges within the corresponding grids - particularly for extremely wet or extremely dry conditions. Also important is that the differences observed appear to be non-systematic. To demonstrate the hydrological implications of using gridded data as a proxy for gauged data, a rainfall-runoff model is applied to one catchment in South Australia initially using gauged data as the source of rainfall input and then gridded rainfall data. The results indicate a markedly different runoff response associated with each of the different sources of rainfall data. It should be noted that this study does not seek to identify which gridded dataset is the "best" for Australia, as each gridded data source has its pros and cons, as does gauged data. Rather, the intention is to quantify

  4. On the uncertainties associated with using gridded rainfall data as a proxy for observed

    Directory of Open Access Journals (Sweden)

    C. R. Tozer

    2012-05-01

    Full Text Available Gridded rainfall datasets are used in many hydrological and climatological studies, in Australia and elsewhere, including for hydroclimatic forecasting, climate attribution studies and climate model performance assessments. The attraction of the spatial coverage provided by gridded data is clear, particularly in Australia where the spatial and temporal resolution of the rainfall gauge network is sparse. However, the question that must be asked is whether it is suitable to use gridded data as a proxy for observed point data, given that gridded data is inherently "smoothed" and may not necessarily capture the temporal and spatial variability of Australian rainfall which leads to hydroclimatic extremes (i.e. droughts, floods. This study investigates this question through a statistical analysis of three monthly gridded Australian rainfall datasets – the Bureau of Meteorology (BOM dataset, the Australian Water Availability Project (AWAP and the SILO dataset. The results of the monthly, seasonal and annual comparisons show that not only are the three gridded datasets different relative to each other, there are also marked differences between the gridded rainfall data and the rainfall observed at gauges within the corresponding grids – particularly for extremely wet or extremely dry conditions. Also important is that the differences observed appear to be non-systematic. To demonstrate the hydrological implications of using gridded data as a proxy for gauged data, a rainfall-runoff model is applied to one catchment in South Australia initially using gauged data as the source of rainfall input and then gridded rainfall data. The results indicate a markedly different runoff response associated with each of the different sources of rainfall data. It should be noted that this study does not seek to identify which gridded dataset is the "best" for Australia, as each gridded data source has its pros and cons, as does gauged data. Rather, the intention is

  5. The Amazon forest-rainfall feedback: the roles of transpiration and interception

    Science.gov (United States)

    Dekker, Stefan; Staal, Arie; Tuinenburg, Obbe

    2017-04-01

    In the Amazon, deep-rooted trees increase local transpiration and high tree cover increase local interception evaporation. These increased local evapotranspiration fluxes to the atmosphere have both positive effects on forests down-wind, as they stimulate rainfall. Although important for the functioning of the Amazon, we have an inadequate assessment on the strength and the timing of these forest-rainfall feedbacks. In this study we (i) estimate local forest transpiration and local interception evaporation, (ii) simulate the trajectories of these moisture flows through the atmosphere and (iii) quantify their contributions to the forest-rainfall feedback for the whole Amazon basin. To determine the atmospheric moisture flows in tropical South America we use a Lagrangian moisture tracking algorithm on 0.25° (c. 25 km) resolution with eight atmospheric layers on a monthly basis for the period 2003-2015. With our approach we account for multiple re-evaporation cycles of this moisture. We also calculate for each month the potential effects of forest loss on evapotranspiration. Combined, these calculations allow us to simulate the effects of land-cover changes on rainfall in downwind areas and estimate the effect on the forest. We found large regional and temporal differences in the importance how forest contribute to rainfall. The transpiration-rainfall feedback is highly important during the dry season. Between September-November, when large parts of the Amazon are at the end of the dry season, more than 50% of the rainfall is caused by the forests upstream. This means that droughts in the Amazon are alleviated by the forest. Furthermore, we found that much moisture cycles several times during its trajectory over the Amazon. After one evapotranspiration-rainfall cycle, more than 40% of the moisture is re-evaporated again. The interception-evaporation feedback is less important during droughts. Finally from our analysis, we show that the forest-rainfall feedback is

  6. The stable hydrogen isotopic composition of sedimentary plant waxes as quantitative proxy for rainfall in the West African Sahel

    Science.gov (United States)

    Niedermeyer, Eva M.; Forrest, Matthew; Beckmann, Britta; Sessions, Alex L.; Mulch, Andreas; Schefuß, Enno

    2016-07-01

    Various studies have demonstrated that the stable hydrogen isotopic composition (δD) of terrestrial leaf waxes tracks that of precipitation (δDprecip) both spatially across climate gradients and over a range of different timescales. Yet, reconstructed estimates of δDprecip and corresponding rainfall typically remain largely qualitative, due mainly to uncertainties in plant ecosystem net fractionation, relative humidity, and the stability of the amount effect through time. Here we present δD values of the C31n-alkane (δDwax) from a marine sediment core offshore the Northwest (NW) African Sahel covering the past 100 years and overlapping with the instrumental record of rainfall. We use this record to investigate whether accurate, quantitative estimates of past rainfall can be derived from our δDwax time series. We infer the composition of vegetation (C3/C4) within the continental catchment area by analysis of the stable carbon isotopic composition of the same compounds (δ13Cwax), calculated a net ecosystem fractionation factor, and corrected the δDwax time series accordingly to derive δDprecip. Using the present-day relationship between δDprecip and the amount of precipitation in the tropics, we derive quantitative estimates of past precipitation amounts. Our data show that (a) vegetation composition can be inferred from δ13Cwax, (b) the calculated net ecosystem fractionation represents a reasonable estimate, and (c) estimated total amounts of rainfall based on δDwax correspond to instrumental records of rainfall. Our study has important implications for future studies aiming to reconstruct rainfall based on δDwax; the combined data presented here demonstrate that it is feasible to infer absolute rainfall amounts from sedimentary δDwax in tandem with δ13Cwax in specific depositional settings.

  7. Satellite-based estimation of rainfall erosivity for Africa

    NARCIS (Netherlands)

    Vrieling, A.; Sterk, G.; Jong, S.M. de

    2010-01-01

    Rainfall erosivity is a measure for the erosive force of rainfall. Rainfall kinetic energy determines the erosivity and is in turn greatly dependent on rainfall intensity. Attempts for its large-scale mapping are rare. Most are based on interpolation of erosivity values derived from rain gauge data.

  8. Ensemble climate projections of mean and extreme rainfall over Vietnam

    Science.gov (United States)

    Raghavan, S. V.; Vu, M. T.; Liong, S. Y.

    2017-01-01

    A systematic ensemble high resolution climate modelling study over Vietnam has been performed using the PRECIS model developed by the Hadley Center in UK. A 5 member subset of the 17-member Perturbed Physics Ensembles (PPE) of the Quantifying Uncertainty in Model Predictions (QUMP) project were simulated and analyzed. The PRECIS model simulations were conducted at a horizontal resolution of 25 km for the baseline period 1961-1990 and a future climate period 2061-2090 under scenario A1B. The results of model simulations show that the model was able to reproduce the mean state of climate over Vietnam when compared to observations. The annual cycles and seasonal averages of precipitation over different sub-regions of Vietnam show the ability of the model in also reproducing the observed peak and magnitude of monthly rainfall. The climate extremes of precipitation were also fairly well captured. Projections of future climate show both increases and decreases in the mean climate over different regions of Vietnam. The analyses of future extreme rainfall using the STARDEX precipitation indices show an increase in 90th percentile precipitation (P90p) over the northern provinces (15-25%) and central highland (5-10%) and over southern Vietnam (up to 5%). The total number of wet days (Prcp) indicates a decrease of about 5-10% all over Vietnam. Consequently, an increase in the wet day rainfall intensity (SDII), is likely inferring that the projected rainfall would be much more severe and intense which have the potential to cause flooding in some regions. Risks due to extreme drought also exist in other regions where the number of wet days decreases. In addition, the maximum 5 day consecutive rainfall (R5d) increases by 20-25% over northern Vietnam but decreases in a similar range over the central and southern Vietnam. These results have strong implications for the management water resources, agriculture, bio diversity and economy and serve as some useful findings to be

  9. How Sensitive is Large-scale Flood Inundation to Rainfall Variability?: Water Balance Analysis Based on Basin-wide Rainfall-Runoff-Inundation Simulation

    Science.gov (United States)

    Sayama, T.; Tatebe, Y.; Tanaka, S.

    2013-12-01

    The 2011 large-scale flood over the Chao Phraya River (CPR) basin resulted in the worst economic flood damage to Thailand. The flooding was induced mainly by unprecedented rainfall from five typhoons and tropical depressions between May and October. The total rainfall in the six months during the monsoon season was approximately 1,400 mm, while the average monsoon-season rainfall in this region is about 1,000 mm, and previous large-scale floods were caused by a total rainfall of approximately 1,200 mm. The interpretation of the additional 200 mm of rainfall compared to past events can greatly affect the understanding of the 2011 flood disaster. Up until now, the magnitude of the flood hazard itself has received little attention due to the seemingly insignificant rainfall variability. Instead, the increase of societal vulnerability, such as accumulation of assets in flood-prone areas, has been more highlighted. Nevertheless, without understanding the impact of the rainfall variability on flood runoff and inundation, essential characteristics of the flood disaster may be misinterpreted. In this study, we focused on the hydrologic characteristics of the flood based on 52 year-long inundation simulation. We applied a 2D Rainfall-Runoff-Inundation (RRI) model to the entire CPR basin. After the model validation with river discharges and water levels, remote sensing inundation extents, and peak inundation water depths for 2011, we conducted water balance analysis from the simulation results to investigate the relationship among rainfall, runoff and inundation volumes. The simulation, by taking two major dams into account, found that 131 mm (9%) of the total rainfall (1,400 mm) may have flooded at the peak. The estimated sensitivity of flood inundation to rainfall (dF/dP) was 0.25. This suggests that the additional 200 mm of rainfall may have resulted in a 50 mm, or 8.2 billion m3, increase in flood inundation volume. It accounts for more than 60 % of the total storage

  10. Projected changes of rainfall seasonality and dry spells in a high greenhouse gas emissions scenario

    Science.gov (United States)

    Pascale, Salvatore; Lucarini, Valerio; Feng, Xue; Porporato, Amilcare; ul Hasson, Shabeh

    2016-02-01

    In this diagnostic study we analyze changes of rainfall seasonality and dry spells by the end of the twenty-first century under the most extreme IPCC5 emission scenario (RCP8.5) as projected by twenty-four coupled climate models contributing to Coupled Model Intercomparison Project 5 (CMIP5). We use estimates of the centroid of the monthly rainfall distribution as an index of the rainfall timing and a threshold-independent, information theory-based quantity such as relative entropy (RE) to quantify the concentration of annual rainfall and the number of dry months and to build a monsoon dimensionless seasonality index (DSI). The RE is projected to increase, with high inter-model agreement over Mediterranean-type regions—southern Europe, northern Africa and southern Australia—and areas of South and Central America, implying an increase in the number of dry days up to 1 month by the end of the twenty-first century. Positive RE changes are also projected over the monsoon regions of southern Africa and North America, South America. These trends are consistent with a shortening of the wet season associated with a more prolonged pre-monsoonal dry period. The extent of the global monsoon region, characterized by large DSI, is projected to remain substantially unaltered. Centroid analysis shows that most of CMIP5 projections suggest that the monsoonal annual rainfall distribution is expected to change from early to late in the course of the hydrological year by the end of the twenty-first century and particularly after year 2050. This trend is particularly evident over northern Africa, southern Africa and western Mexico, where more than 90 % of the models project a delay of the rainfall centroid from a few days up to 2 weeks. Over the remaining monsoonal regions, there is little inter-model agreement in terms of centroid changes.

  11. Remote sensing of rainfall for debris-flow hazard assessment

    Science.gov (United States)

    Wieczorek, G.F.; Coe, J.A.; Godt, J.W.; ,

    2003-01-01

    Recent advances in remote sensing of rainfall provide more detailed temporal and spatial data on rainfall distribution. Four case studies of abundant debris flows over relatively small areas triggered during intense rainstorms are examined noting the potential for using remotely sensed rainfall data for landslide hazard analysis. Three examples with rainfall estimates from National Weather Service Doppler radar and one example with rainfall estimates from infrared imagery from a National Oceanic and Atmospheric Administration satellite are compared with ground-based measurements of rainfall and with landslide distribution. The advantages and limitations of using remote sensing of rainfall for landslide hazard analysis are discussed. ?? 2003 Millpress,.

  12. Evaluation of TRMM 3B42 V7 Rainfall Product over the Oum Er Rbia Watershed in Morocco

    Directory of Open Access Journals (Sweden)

    Hamza Ouatiki

    2017-01-01

    Full Text Available In arid and semi-arid areas, rainfall is often characterized by a strong spatial and temporal variability. These environmental factors, combined with the sparsity of the measurement networks in developing countries, constitute real constraints for water resources management. In recent years, several spatial rainfall measurement sources have become available, such as TRMM data (Tropical Rainfall Measurement Mission. In this study, the TRMM 3B42 Version 7 product was evaluated using rain gauges measurements from 19 stations in the Oum-Er-Bia (OER basin located in the center of Morocco. The relevance of the TRMM product was tested by direct comparison with observations at different time scales (daily, monthly, and annual between 1998 and 2010. Results show that the satellite product provides poor estimations of rainfall at the daily time scale giving an average Pearson correlation coefficient (r of 0.2 and average Root Mean Square Error (RMSE of 10 mm. However, the accuracy of TRMM rainfall is improved when temporally averaged to monthly time scale (r of 0.8 and RMSE of 28 mm or annual time scale (r of 0.71 and RMSE of 157 mm. Moreover, improved correlation with observed data was obtained for data spatially averaged at the watershed scale. Therefore, at the monthly and annual time scales, TRMM data can be a useful source of rainfall data for water resources monitoring and management in ungauged basins in semi-arid regions.

  13. Temporal Variation of Rainfall Intensity, Rainfall Partitioning and its Correlation with Meteorological Elements of Eastern India

    Science.gov (United States)

    Tripathi, P.; Chaturvedi, A.

    2007-07-01

    Rainfall plays a vital role in Indian agriculture hence economy of the country, but very crucial and risky due to its erratic/ unpredictable behavior and uneven distribution. Since monsoonal vagaries in eastern India are very frequent hence involve a great risk in Argil. Production and quality of atmosphere at desired level. Though prediction of onset of monsoon with total quantum of rainfall is available through different agencies but still not accurate and not in consonance of observed behavior. Therefore, surface weather data of meteorological elements needs to be critically examined for prediction of onset of monsoon, rainfall rate and its variability with space and time and strategy to cope the uncertainty of risk (drought and flood etc) needs to be evolved. In the present study an analysis of rainfall of Eastern India (Eastern U.P., Bihar and Jharkhand) has been made for rainfall partitioning, rate of rainfall and its variation with space and time. A location specific six parameter model were developed with multiple correlation technique to predict the medium and long range rainfall forecast and found 65% accurate for long range and 79% accurate to medium range. This will not only help to predict the accurate rainfall but also provides a clue for assessment of quality of rainfall under different aerosol levels of atmosphere which ultimately led to link designers with radio wave propagation. In addition, correlation of physical variables of atmosphere like vapor pressure deficit, dew point and relative humidity were also made with quantum of rainfall, rate of rainfall and its quantitative characteristics in the study area as to understand the mechanism behavior of atmosphere for space research.

  14. A multiplier-based method of generating stochastic areal rainfall from point rainfalls

    Science.gov (United States)

    Ndiritu, J. G.

    Catchment modelling for water resources assessment is still mainly based on rain gauge measurements as these are more easily available and cover longer periods than radar and satellite-based measurements. Rain gauges however measure the rain falling on an extremely small proportion of the catchment and the areal rainfall obtained from these point measurements are consequently substantially uncertain. These uncertainties in areal rainfall estimation are generally ignored and the need to assess their impact on catchment modelling and water resources assessment is therefore imperative. A method that stochastically generates daily areal rainfall from point rainfall using multiplicative perturbations as a means of dealing with these uncertainties is developed and tested on the Berg catchment in the Western Cape of South Africa. The differences in areal rainfall obtained by alternately omitting some of the rain gauges are used to obtain a population of plausible multiplicative perturbations. Upper bounds on the applicable perturbations are set to prevent the generation of unrealistically large rainfall and to obtain unbiased stochastic rainfall. The perturbations within the set bounds are then fitted into probability density functions to stochastically generate the perturbations to impose on areal rainfall. By using 100 randomly-initialized calibrations of the AWBM catchment model and Sequent Peak Analysis, the effects of incorporating areal rainfall uncertainties on storage-yield-reliability analysis are assessed. Incorporating rainfall uncertainty is found to reduce the required storage by up to 20%. Rainfall uncertainty also increases flow-duration variability considerably and reduces the median flow-duration values by an average of about 20%.

  15. Changes in rainfall seasonality in the tropics

    Science.gov (United States)

    Feng, X.; Porporato, A. M.; Rodriguez-Iturbe, I.

    2012-12-01

    Climate change has altered not only the overall magnitude of rainfall but also their seasonal distribution and interannual variability across the world. Such changes in the rainfall regimes will be most keenly felt in arid and semiarid regions, where the availability and timing of water are key factors controlling biogeochemical cycles, primary productivity, and phenology, in addition to regulating regional agricultural production and economic output. Nevertheless, due to the inherent complexity of the signals, a comprehensive framework to understand seasonal rainfall profiles across multiple timescales and geographical regions is still lacking. Here, we formulate a global measure of seasonality and investigate changes in the seasonal rainfall regime across the tropics in the past century. The seasonality index, which captures the effects of both the magnitude and concentration of the rainy season, is highest in the northeast region of Brazil, western and central Africa, northern Australia, and parts of the Caribbean and Southeast Asia (the seasonally dry tropics). Further decomposing rainfall seasonality into its magnitude, duration, and timing components using spectral techniques and information theory, we find marked increase in the interannual variability of seasonality over most of the dry tropics, implying increasing uncertainty in the intensity, duration, and arrival of seasonal rainfall over the past century. We also show that such increase in variability has occurred in conjunction with shifts in the seasonal timing and changes in its overall magnitude. Thus, it is importance to place the analysis of rainfall regimes in these regions into a seasonal context that is most relevant to local ecological and social processes. These changes, if sustained into the next century, will portend significant shifts in the timing of plant activities and ecosystem composition and distribution, with consequences for water and carbon cycling and water resource management in

  16. Rainfall and temperatures during the 1991/92 drought in the Kruger National Park

    Directory of Open Access Journals (Sweden)

    N. Zambatis

    1995-09-01

    Full Text Available Rainfall and temperatures during the 1991/92 drought, the severest in the recorded history of the Kruger National Park (KNP, are described. Mean total rainfall for the KNP was 235.6 mm (44.1 of the long- term mean, with a median of 239.9 mm. The num- ber of days on which rain occurred also decreased significantly from a mean annual total of 48.3 to a mean of 24.2 in 1991/92. Daily maximum, minimum and average temperatures for some months increased significantly, as did the number of days within certain maximum temperature range classes.

  17. Patching rainfall data using regression methods. 3. Grouping, patching and outlier detection

    Science.gov (United States)

    Pegram, Geoffrey

    1997-11-01

    Rainfall data are used, amongst other things, for augmenting or repairing streamflow records in a water resources analysis environment. Gaps in rainfall records cause problems in the construction of water-balance models using monthly time-steps, when it becomes necessary to estimate missing values. Modest extensions are sometimes also desirable. It is also important to identify outliers as possible erroneous data and to group data which are hydrologically similar in order to accomplish good patching. Algorithms are described which accomplish these tasks using the covariance biplot, multiple linear regression, singular value decomposition and the pseudo-Expectation-Maximization algorithm.

  18. Monthly Weather Review

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Supplements to the Monthly Weather Review publication. The Weather Bureau published the Monthly weather review Supplement irregularly from 1914 to 1949. The...

  19. Proposing Chinese Pharmacists Month

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    @@ Dear Pharmacists: Today I would like to share with you about the American Pharmacists Month which is celebrated in October every year.This month-long observance is promoted by American Pharmacist Association.

  20. Modeling the Distribution of Rainfall Intensity using Hourly Data

    OpenAIRE

    Salisu Dan'azumi; Supiah Shamsudin; Azmi Aris

    2010-01-01

    Problem statement: Design of storm water best management practices to control runoff and water pollution can be achieved if a prior knowledge of the distribution of rainfall characteristics is known. Rainfall intensity, particularly in tropical climate, plays a major role in the design of runoff conveyance and erosion control systems. This study is aimed to explore the statistical distribution of rainfall intensity for Peninsular Malaysia using hourly rainfall data. Approach: Hourly rainfall ...

  1. A regional landslide warning system based on spatially variable rainfall thresholds

    Science.gov (United States)

    Segoni, Samuele; Rossi, Guglielmo; Rosi, Ascanio; Catani, Filippo

    2010-05-01

    Rainfall is widely recognized as one of the major causes for landsliding. When studying the conditions of triggering of mass movements at regional scale, a process-based approach is seldom possible because of the complexity in the spatial organization of the involved independent variables (e.g. soil properties). Therefore, empirical methods based on the definition of triggering thresholds are usually employed for the definition of warning systems or for landslide hazard assessments. Such thresholds are defined by observing the characteristics of past rainfall events that have resulted in landslides and selecting the lower bound envelope curve in intensity-duration plots depicting such events. These curves, generally represented by power-law type functions linking, e.g., intensity and duration of the critical rainfall, define the lowest level above which landslides should be expected. In the present work, concerning the territory of Tuscany (ab. 23,000 km2), a similar approach is adopted and described which presents some improvements with respect to traditional methods. First of all, the strong variability of environmental, meteorological and geological factors within the study area, together with evidences from available data on triggering conditions, imply that a single general threshold would be affected by a too large degree of overestimation of hazard and suggest the adoption of locally defined thresholds. The studied area was then partitioned in 25 Alert Zones and each of them has been analyzed separately to provide distinct rainfall thresholds. Secondly, to handle the amount of available data (the analysis regards the period 2000-2007 and involves 408 rainfall events, which were registered by a network of 332 rain-gauges and that caused 2132 landslides), a software has been developed for automatically analyzing rainfall patterns and defining such thresholds. In particular, the automated analysis performs the following tasks: i) Defining, for every rain

  2. Assessing vegetation structure and ANPP dynamics in a grassland-shrubland Chihuahuan ecotone using NDVI-rainfall relationships

    Science.gov (United States)

    Moreno-de las Heras, M.; Diaz-Sierra, R.; Turnbull, L.; Wainwright, J.

    2015-01-01

    Climate change and the widespread alteration of natural habitats are major drivers of vegetation change in drylands. A classic case of vegetation change is the shrub-encroachment process that has been taking place over the last 150 years in the Chihuahuan Desert, where large areas of grasslands dominated by perennial grass species (black grama, Bouteloua eriopoda, and blue grama, B. gracilis) have transitioned to shrublands dominated by woody species (creosotebush, Larrea tridentata, and mesquite, Prosopis glandulosa), accompanied by accelerated water and wind erosion. Multiple mechanisms drive the shrub-encroachment process, including exogenous triggering factors such as precipitation variations and land-use change, and endogenous amplifying mechanisms brought about by soil erosion-vegetation feedbacks. In this study, simulations of plant biomass dynamics with a simple modelling framework indicate that herbaceous (grasses and forbs) and shrub vegetation in drylands have different responses to antecedent precipitation due to functional differences in plant growth and water-use patterns, and therefore shrub encroachment may be reflected in the analysis of landscape-scale vegetation-rainfall relationships. We analyze the structure and dynamics of vegetation at an 18 km2 grassland-shrubland ecotone in the northern edge of the Chihuahuan Desert (McKenzie Flats, Sevilleta National Wildlife Refuge, NM, USA) by investigating the relationship between decade-scale (2000-2013) records of medium-resolution remote sensing of vegetation greenness (MODIS NDVI) and precipitation. Spatial evaluation of NDVI-rainfall relationship at the studied ecotone indicates that herbaceous vegetation shows quick growth pulses associated with short-term (previous 2 months) precipitation, while shrubs show a slow response to medium-term (previous 5 months) precipitation. We use these relationships to (a) classify landscape types as a function of the spatial distribution of dominant vegetation

  3. Development of Rainfall-Discharge Model for Future NPP candidate Site

    Energy Technology Data Exchange (ETDEWEB)

    An, Ji-hong; Yee, Eric [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

    2015-10-15

    By this study, most suitable model for future nuclear power plant site in Yeongdeok to be used to predict peak amount of riverine flooding was developed by examining historical rainfall and discharge data from the nearest gage station which is Jodong water level gage station in Taehwa basin. Sitting a nuclear power plant (NPP) requires safety analyses that include the effects of extreme events such as flooding or earthquake. In light of South Korean government's 15-year power supply plan that calls for the construction of new nuclear power station in Yeongdeok, it becomes more important to site new station in a safe area from flooding. Because flooding or flooding related accidents mostly happen due to extremely intense rainfall, it is necessary to find out the relationship between rainfall and run-off by setting up feasible model to figure out the peak flow of the river around nuclear related facilities.

  4. Spatial estimation of debris flows-triggering rainfall and its dependence on rainfall return period

    Science.gov (United States)

    Destro, Elisa; Marra, Francesco; Nikolopoulos, Efthymios I.; Zoccatelli, Davide; Creutin, Jean Dominique; Borga, Marco

    2017-02-01

    Forecasting the occurrence of debris flows is fundamental for issuing hazard warnings, and often focuses on rainfall as a triggering agent and on the use of empirical rainfall thresholds based on rain gauge observations. A recognized component of the uncertainty associated with the use of rainfall thresholds is related to the sampling of strongly varying rainfall variability with sparse rain gauge networks. In this work we examine the spatial distribution of rainfall depth in areas up to 10 km from the debris flow initiation points as a function of return period, and we exploit this information to analyze the errors expected in the estimation of debris flow triggering rainfall when rain gauge data are used. In particular, we investigate the impact of rain gauge density and of the use of different interpolation methods. High-resolution, adjusted radar rainfall estimates, representing the best available spatially-distributed rainfall estimates at the debris flows initiation point and in the surrounding area, are sampled by stochastically generated rain gauge networks characterized by varying densities. Debris flow triggering rainfall is estimated by means of three rainfall interpolation methods: nearest neighbor, inverse distance weighting and ordinary kriging. On average, triggering rainfall shows a local peak corresponding to the debris flow initiation point, with a decay of rainfall with distance which increases with the return period of the triggering rainfall. Interpolation of the stochastically generated rain gauge measurements leads to an underestimation of the triggering rainfall that, irrespective of the interpolation methods, increases with the return period and decreases with the rain gauge density. For small return period events and high rain gauge density, the differences among the methods are minor. With increasing the return period and decreasing the rain gauge density, the nearest neighbor method is less biased, because it makes use only of the

  5. Downscaling site rainfall from daily to 11.25-minute resolution: event, diurnal, seasonal and decadal controls on downscaling parameters

    Science.gov (United States)

    McIntyre, Neil; Shi, Shirley; Onof, Christian

    2016-04-01

    Downscaling site rainfall from daily to sub-daily resolution is often approached using the multiplicative discrete random cascade (MDRC) class of models, with mixed success. Questions in any application - for MDRCs or indeed other classes of downscaling model - is to what extent and in what way are model parameters functions of rainfall event type and/or large scale climate controls for example those linked to the El Nino Southern Oscillation (ENSO). These questions underlie the applicability of downscaling models for analysing rainfall and hydrological extremes, in particular for synthesising long-term historical or future sub-daily extremes conditional on historic or projected daily data. Coastal Queensland, Australia, is subject to combinations of multiple weather systems, including tropical cyclones, blocking systems, convective storms, frontal systems and ENSO influences. Using 100 years of fine resolution data from two gauges in central Brisbane, microcanonical MDRC models are fitted to data from 1 day to 11.25 minutes in seven cascade levels, each level dividing the time interval and its rainfall volume into two sub-intervals. Each cascade level involves estimating: the probabilities that all the rainfall observed in a time interval is concentrated in only the first of the two sub-intervals and that all the rainfall observed in a time interval is concentrated in only the second of the two sub-intervals; and also two beta distribution parameters that define the probability of a given division of the rainfall into both sub-intervals. These parameters are found to vary systematically with time of day, rainfall volume, event temporal structure, month of year, and ENSO anomaly. Reasonable downscaling performance is achieved (in terms of replicating extreme values of 11.25 minute rainfall given the observed daily data) by including the parameter dependence on the rainfall volume and event structure, although particular applications may justify development of more

  6. Space-time variability of Indonesian rainfall at inter-annual and multi-decadal time scales

    Science.gov (United States)

    Yanto; Rajagopalan, Balaji; Zagona, Edith

    2016-11-01

    We investigated the space-time variability of wet (Nov-Apr) and dry (May-Oct) season rainfall over Indonesia, using monthly gridded rainfall data from the University of East Anglia Climatic Research Unit covering the period 1901-2012. Three complimentary techniques were employed—(1) principal component analysis to identify the dominant modes of variability, (2) wavelet spectral analysis to identify the spectral characteristics of the leading modes and their coherence with large scale climate variables and (3) Bayesian Dynamical Linear Model (BDLM) to quantify the temporal variability of the association between rainfall modes and climate variables. In the dry season when the Inter Tropical Convergence Zone (ITCZ) is to the north of the equator the leading two principal components (PCs) explain close to 50 % of the rainfall. In the wet season the ITCZ moves to the south and the leading PCs explain close to 30 % of the variance. El Niño Southern Oscillation (ENSO) is the driver of the leading modes of rainfall variability during both seasons. We find asymmetry in the teleconnections of ENSO to high and low rainfall years in the dry season. Furthermore, ENSO and the leading PCs of rainfall have spectral coherence in the inter-annual band (2-8 years) over the entire period of record and in the multi-decadal (8-16 years) band in post-1980 years. In addition, during the 1950-1980 period the second mode of variability in both seasons has a strong relationship with Pacific Decadal Oscillation. The association between ENSO and the leading mode of Indonesian rainfall has strengthened in recent decades, more so during dry season. These inter-annual and multi-decadal variability of Indonesian rainfall modulated by Pacific climate drivers has implications for rainfall and hydrologic predictability important for water resources management.

  7. Rainfall variability and seasonality in northern Bangladesh

    Science.gov (United States)

    Bari, Sheikh Hefzul; Hussain, Md. Manjurul; Husna, Noor-E.-Ashmaul

    2016-05-01

    This paper aimed at the analysis of rainfall seasonality and variability for the northern part of South-Asian country, Bangladesh. The coefficient of variability was used to determine the variability of rainfall. While rainfall seasonality index (SI ) and mean individual seasonality index ( overline{SI_i} ) were used to identify seasonal contrast. We also applied Mann-Kendall trend test and sequential Mann-Kendall test to determine the trend in seasonality. The lowest variability was found for monsoon among the four seasons whereas winter has the highest variability. Observed variability has a decreasing tendency from the northwest region towards the northeast region. The mean individual seasonality index (0.815378 to 0.977228) indicates that rainfall in Bangladesh is "markedly seasonal with a long dry season." It was found that the length of the dry period is lower at the northeastern part of northern Bangladesh. Trend analysis results show no significant change in the seasonality of rainfall in this region. Regression analysis of overline{SI_i} and SI, and longitude and mean individual seasonality index show a significant linear correlation for this area.

  8. Does GPM-based multi-satellite precipitation enhance rainfall estimates over Pakistan and Bolivia arid regions?

    Science.gov (United States)

    Hussain, Y.; Satgé, F.; Bonnet, M. P.; Pillco, R.; Molina, J.; Timouk, F.; Roig, H.; Martinez-Carvajal, H., Sr.; Gulraiz, A.

    2016-12-01

    Arid regions are sensitive to rainfall variations which are expressed in the form of flooding and droughts. Unfortunately, those regions are poorly monitored and high quality rainfall estimates are still needed. The Global Precipitation Measurement (GPM) mission released two new satellite rainfall products named Integrated Multisatellite Retrievals GPM (IMERG) and Global Satellite Mapping of Precipitation version 6 (GSMaP-v6) bringing the possibility of accurate rainfall monitoring over these countries. This study assessed both products at monthly scale over Pakistan considering dry and wet season over the 4 main climatic zones from 2014 to 2016. With similar climatic conditions, the Altiplano region of Bolivia is considered to quantify the influence of big lakes (Titicaca and Poopó) in rainfall estimates. For comparison, the widely used TRMM-Multisatellite Precipitation Analysis 3B43 (TMPA-3B43) version 7 is also involved in the analysis to observe the potential enhancement in rainfall estimate brought by GPM products. Rainfall estimates derived from 110 rain-gauges are used as reference to compare IMERG, GSMaP-v6 and TMPA-3B43 at the 0.1° and 0.25° spatial resolution. Over both regions, IMERG and GSMaP-v6 capture the spatial pattern of precipitation as well as TMPA-3B43. All products tend to over estimates rainfall over very arid regions. This feature is even more marked during dry season. However, during this season, both reference and estimated rainfall remain very low and do not impact seasonal water budget computation. On a general way, IMERG slightly outperforms TMPA-3B43 and GSMaP-v6 which provides the less accurate rainfall estimate. The TMPA-3B43 rainfall underestimation previously found over Lake Titicaca is still observed in IMERG estimates. However, GSMaP-v6 considerably decreases the underestimation providing the most accurate rainfall estimate over the lake. MOD11C3 Land Surface Temperature (LST) and ASTER Global Emissivity Dataset reveal strong

  9. Spatial moments of catchment rainfall: rainfall spatial organisation, basin morphology, and flood response

    Directory of Open Access Journals (Sweden)

    D. Zoccatelli

    2011-12-01

    Full Text Available This paper describes a set of spatial rainfall statistics (termed "spatial moments of catchment rainfall" quantifying the dependence existing between spatial rainfall organisation, basin morphology and runoff response. These statistics describe the spatial rainfall organisation in terms of concentration and dispersion statistics as a function of the distance measured along the flow routing coordinate. The introduction of these statistics permits derivation of a simple relationship for the quantification of catchment-scale storm velocity. The concept of the catchment-scale storm velocity takes into account the role of relative catchment orientation and morphology with respect to storm motion and kinematics. The paper illustrates the derivation of the statistics from an analytical framework recently proposed in literature and explains the conceptual meaning of the statistics by applying them to five extreme flash floods occurred in various European regions in the period 2002–2007. High resolution radar rainfall fields and a distributed hydrologic model are employed to examine how effective are these statistics in describing the degree of spatial rainfall organisation which is important for runoff modelling. This is obtained by quantifying the effects of neglecting the spatial rainfall variability on flood modelling, with a focus on runoff timing. The size of the study catchments ranges between 36 to 982 km2. The analysis reported here shows that the spatial moments of catchment rainfall can be effectively employed to isolate and describe the features of rainfall spatial organization which have significant impact on runoff simulation. These statistics provide useful information on what space-time scales rainfall has to be monitored, given certain catchment and flood characteristics, and what are the effects of space-time aggregation on flood response modeling.

  10. Scale dependence of Hortonian rainfall-runoff processes in a semiarid environment

    Science.gov (United States)

    Chen, L.; Sela, S.; Svoray, T.; Assouline, S.

    2016-07-01

    Scale dependence of Hortonian rainfall-runoff processes has received much attention in the literature but has not been fully resolved. To further explore this issue, a recently developed model was applied to simulate rainfall-infiltration-runoff processes at multiple spatial scales. The model consists of the coupling between a two-dimensional runoff routing module and a two-layer infiltration module, thus accounting for spatial variability in soil properties, soil surface sealing, topography, and partial vegetation cover. A 76 m2 semiarid experimental plot with sparse cover of vegetation patches and a sealed soil surface in inter-patch bare areas was used as a representative elementary area (REA). A series of four larger artificial plots of different areas was created based on this REA to examine the scale dependence of rainfall-runoff relationships in the case of stationary heterogeneity. Results show that runoff depth (or runoff coefficient) decreases with increasing scale. This trend is more prominent at scales less than 10 times the REA length. Power law relationships can quantitatively describe the scaling law. The major mechanism of the scale effect is run-on infiltration. However, rainfall intensity and soil properties can both affect the scaling trend through their interaction with run-on. Higher intensity and less temporal variability of rainfall can both reduce the scale effect. Temporally intermittent rainfall may produce spatially oscillating infiltration rates at large scales. Vegetation patterns are another factor that may affect the scaling. Random-vegetation patterns, compared with regular patterns with similar statistical properties, change the spatial distributions, but do not significantly change either the total amount and statistical properties of infiltration and runoff or the scale dependence of the rainfall-runoff process.

  11. Seasonal not annual rainfall determines grassland biomass response to carbon dioxide

    Science.gov (United States)

    Hovenden, Mark J.; Newton, Paul C. D.; Wills, Karen E.

    2014-07-01

    The rising atmospheric concentration of carbon dioxide (CO2) should stimulate ecosystem productivity, but to what extent is highly uncertain, particularly when combined with changing temperature and precipitation. Ecosystem response to CO2 is complicated by biogeochemical feedbacks but must be understood if carbon storage and associated dampening of climate warming are to be predicted. Feedbacks through the hydrological cycle are particularly important and the physiology is well known; elevated CO2 reduces stomatal conductance and increases plant water use efficiency (the amount of water required to produce a unit of plant dry matter). The CO2 response should consequently be strongest when water is limiting; although this has been shown in some experiments, it is absent from many. Here we show that large annual variation in the stimulation of above-ground biomass by elevated CO2 in a mixed C3/C4 temperate grassland can be predicted accurately using seasonal rainfall totals; summer rainfall had a positive effect but autumn and spring rainfall had negative effects on the CO2 response. Thus, the elevated CO2 effect mainly depended upon the balance between summer and autumn/spring rainfall. This is partly because high rainfall during cool, moist seasons leads to nitrogen limitation, reducing or even preventing biomass stimulation by elevated CO2. Importantly, the prediction held whether plots were warmed by 2 °C or left unwarmed, and was similar for C3 plants and total biomass, allowing us to make a powerful generalization about ecosystem responses to elevated CO2. This new insight is particularly valuable because climate projections predict large changes in the timing of rainfall, even where annual totals remain static. Our findings will help resolve apparent differences in the outcomes of CO2 experiments and improve the formulation and interpretation of models that are insensitive to differences in the seasonal effects of rainfall on the CO2 response.

  12. Downscaling summer rainfall in the UK from North Atlantic ocean temperatures

    Directory of Open Access Journals (Sweden)

    R. L. Wilby

    2001-01-01

    Full Text Available Annual series of three stochastic rainfal