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Sample records for monthly scale rainfall

  1. 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...

  2. 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.

  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. Artificial Neural Network for Monthly Rainfall Rate Prediction

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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

  6. 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

  7. Spatiotemporal Scaling Effect on Rainfall Network Design Using Entropy

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    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.

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

    Directory of Open Access Journals (Sweden)

    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

  9. 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

  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. Hic Sunt Leones: Anomalous Scaling In Rainfall

    Science.gov (United States)

    Ferraris, L.; Gabellani, S.; Provenzale, A.; Rebora, N.

    In recent years the spatio-temporal intermittency of precipitation fields has often been quantified in terms of scaling and/or multifractal behaviour. In this work we anal- yse the spatial scaling properties of precipitation intensity fields measured during the GATE radar experiment, and compare the results with those obtained from surrogate data generated by nonlinearly filtered, linear stochastic processes and from random shuffling of the original data. The results of the study suggest a spurious nature of the spatial multifractal behaviour of the GATE fields and indicate that claims of multifrac- tality and anomalous scaling in rainfall may have to be reconsidered.

  12. 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

  13. 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.

  14. 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...

  15. 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.

  16. Scale-wise evolution of rainfall probability density functions fingerprints the rainfall generation mechanism

    Science.gov (United States)

    Molini, Annalisa; Katul, Gabriel; Porporato, Amilcare

    2010-05-01

    Possible linkages between climatic fluctuations in rainfall at low frequencies and local intensity fluctuations within single storms is now receiving significant attention in climate change research. To progress on a narrower scope of this problem, the cross-scale probabilistic structure of rainfall intensity records collected over time scales ranging from hours to decades at sites dominated by either convective or frontal systems is investigated. Across these sites, intermittency buildup from slow to fast time-scales is analyzed in terms of its heavy tailed and asymmetric signatures in the scale-wise evolution of rainfall probability density functions (pdfs). The analysis demonstrates that rainfall records dominated by convective storms develop heavier-tailed power law pdfs across finer scales when compared with their frontal systems counterpart. A concomitant marked asymmetry buildup also emerges across finer time scales necessitating skewed probability laws for quantifying the scale-wise evolution of rainfall pdfs. A scale-dependent probabilistic description of such fat tails, peakedness and asymmetry appearance is proposed and tested by using a modified q-Gaussian model, able to describe the scale wise evolution of rainfall pdfs in terms of the nonextensivity parameter q, a lacunarity (intermittency) correction γ and a tail asymmetry coefficient c, also functions of q.

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

    Science.gov (United States)

    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.

  18. Accuracy of rainfall measurement for scales of hydrological interest

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    S. J. Wood

    2000-01-01

    Full Text Available The dense network of 49 raingauges over the 135 km2 Brue catchment in Somerset, England is used to examine the accuracy of rainfall estimates obtained from raingauges and from weather radar. Methods for data quality control and classification of precipitation types are first described. A super-dense network comprising eight gauges within a 2 km grid square is employed to obtain a 'true value' of rainfall against which the 2 km radar grid and a single 'typical gauge' estimate can be compared. Accuracy is assessed as a function of rainfall intensity, for different periods of time-integration (15 minutes, 1 hour and 1 day and for two 8-gauge networks in areas of low and high relief. In a similar way, the catchment gauge network is used to provide the 'true catchment rainfall' and the accuracy of a radar estimate (an area-weighted average of radar pixel values and a single 'typical gauge' estimate of catchment rainfall evaluated as a function of rainfall intensity. A single gauge gives a standard error of estimate for rainfall in a 2 km square and over the catchment of 33% and 65% respectively, at rain rates of 4 mm in 15 minutes. Radar data at 2 km resolution give corresponding errors of 50% and 55%. This illustrates the benefit of using radar when estimating catchment scale rainfall. A companion paper (Wood et al., 2000 considers the accuracy of rainfall estimates obtained using raingauge and radar in combination. Keywords: rainfall, accuracy, raingauge, radar

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

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    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.

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

    Science.gov (United States)

    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.

  1. Sensitivity of point scale runoff predictions to rainfall resolution

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    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

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

    Science.gov (United States)

    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

  3. 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.

  4. 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.

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

    Science.gov (United States)

    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°.

  6. 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}.

  7. 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.

  8. 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.

  9. 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.

  10. Short-term rainfall: its scaling properties over Portugal

    Science.gov (United States)

    de Lima, M. Isabel P.

    2010-05-01

    The characterization of rainfall at a variety of space- and time-scales demands usually that data from different origins and resolution are explored. Different tools and methodologies can be used for this purpose. In regions where the spatial variation of rain is marked, the study of the scaling structure of rainfall can lead to a better understanding of the type of events affecting that specific area, which is essential for many engineering applications. The relevant factors affecting rain variability, in time and space, can lead to contrasting statistics which should be carefully taken into account in design procedures and decision making processes. One such region is Mainland Portugal; the territory is located in the transitional region between the sub-tropical anticyclone and the subpolar depression zones and is characterized by strong north-south and east-west rainfall gradients. The spatial distribution and seasonal variability of rain are particularly influenced by the characteristics of the global circulation. One specific feature is the Atlantic origin of many synoptic disturbances in the context of the regional geography (e.g. latitude, orography, oceanic and continental influences). Thus, aiming at investigating the statistical signature of rain events of different origins, resulting from the large number of mechanisms and factors affecting the rainfall climate over Portugal, scale-invariant analyses of the temporal structure of rain from several locations in mainland Portugal were conducted. The study used short-term rainfall time series. Relevant scaling ranges were identified and characterized that help clarifying the small-scale behaviour and statistics of this process.

  11. 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...

  12. 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.

  13. 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

  14. Comparison of different types of medium scale field rainfall simulators

    Science.gov (United States)

    Dostál, Tomáš; Strauss, Peter; Schindewolf, Marcus; Kavka, Petr; Schmidt, Jürgen; Bauer, Miroslav; Neumann, Martin; Kaiser, Andreas; Iserloh, Thomas

    2015-04-01

    Rainfall simulators are used in numerous experiments to study runoff and soil erosion characteristics. However, they usually differ in their construction details, rainfall generation, plot size and other technical parameters. As field experiments using medium to large scale rainfall simulators (plot length 3 - 8 m) are very much time and labor consuming, close cooperation of individual teams and comparability of results is highly desirable to enlarge the database of results. Two experimental campaigns were organized to compare three field rainfall simulators of similar scale (plot size), but with different technical parameters. The results were then compared, to identify parameters that are crucial for soil loss and surface runoff formation and test if results from individual devices can be reliably compared. The rainfall simulators compared were: field rainfall simulator of CTU Prague (the Czech Republic) (Kavka et al., 2012; EGU2015-11025), field simulator of BAW (Austria) (Strauss et al., 2002) and field simulator of TU Bergakademie Freiberg (Germany) (Schindewolf & Schmidt 2012). The device of CTU Prague is usually applied to a plot size of 9,5 x 2 m employing 4 nozzles SS Full Jet 40WSQ mounted on folding arm, working pressure is 0.8 bar, height of nozzles is 2.65 m. The intensity of rainfall is regulated electronically, which leaves the nozzle opened only for certain time. The rainfall simulator of BAW is constructed as a modular system, which is usually applied for a length of 5 m (area 2 x 5 m), using 6 nozzles SS Full Jet 40WSQ. Usual working pressure is 0.25 bar. Elevation of nozzles is 2.6 m. The intensity of rainfall is regulated electronically, which leaves the nozzle opened only for certain time. The device of TU Bergakademie Freiberg is also standard modular system, working usually with a plot size of 3 x 1 m, using 3 oscillating VeeJet 80/100 nozzles with an usual operating pressure of 0.5 bar. Intensity is regulated by the frequency of sweeps above

  15. 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.

  16. 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.

  17. 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.

  18. Nature and Inference of Scaling in Temporal Rainfall

    Science.gov (United States)

    Veneziano, D.; Lepore, C.

    2012-12-01

    We pursue three objectives related to the scaling of temporal rainfall: 1. Develop methods for the analysis of scaling within rainstorms, 2. Explain the difference in scaling results when considering the whole record inclusive of storms and inter-storm periods (continuous analysis) or only the storms (within-storm analysis), and 3. Examine whether scaling follows a beta-lognormal model or a more general beta-log-Levy model. Regarding objective 1, there are well-established techniques for continuous scaling analysis but not for the analysis within storms. For the latter, we develop methods based on the partition coefficients and show how to correct for bias and maximize the estimation accuracy. To pursue objective 2 we use historic records, synthetic time series, and toy rainfall models to show that the continuous results reflect mainly the alternation of dry and wet periods and are insensitive to the fluctuations of rainfall intensity inside the storms. Moreover, we find that the rain support is not fractal. From this we conclude that the results from traditional continuous analysis are spurious. By contrast, there is evidence of within-storm scaling. Inside the storms there is higher intermittency (higher intensity fluctuations) and lower lacunarity (more compact rain support) than in the continuous record. These results have important implications on downscaling and the evaluation of rainfall extremes. Concerning objective 3, we note that popular multifractal models for rainfall are of the log-Levy ("universal") type. A key parameter of those models is the stability index 0 < α ≤ 2, with α = 2 corresponding to lognormal models. To account for the alternation of dry and wet periods (also in within-storm analysis), one should add a "beta component" and thus use beta-log-Levy or beta-lognormal models. By using simulations with α = 2, we show that standard estimators of α are negatively biased and the hypothesis of beta-lognormal multifractality inside the

  19. Along the Rainfall-Runoff Chain: From Scaling of Greatest Point Rainfall to Global Change Attribution

    Science.gov (United States)

    Fraedrich, K.

    2014-12-01

    Processes along the continental rainfall-runoff chain cover a wide range of time and space scales which are presented here combining observations (ranging from minutes to decades) and minimalist concepts. (i) Rainfall, which can be simulated by a censored first-order autoregressive process (vertical moisture fluxes), exhibits 1/f-spectra if presented as binary events (tropics), while extrema world wide increase with duration according to Jennings' scaling law. (ii) Runoff volatility (Yangtze) shows data collapse which, linked to an intra-annual 1/f-spectrum, is represented by a single function not unlike physical systems at criticality and the short and long return times of extremes are Weibull-distributed. Atmospheric and soil moisture variabilities are also discussed. (iii) Soil moisture (in a bucket), whose variability is interpreted by a biased coinflip Ansatz for rainfall events, adds an equation of state to energy and water flux balances comprising Budyko's frame work for quasi-stationary watershed analysis. Eco-hydrologic state space presentations in terms of surface flux ratios of energy excess (loss by sensible heat over supply by net radiation) versus water excess (loss by discharge over gain by precipitation) allow attributions of state change to external (or climate) and internal (or anthropogenic) causes. Including the vegetation-greenness index (NDVI) as an active tracer extends the eco-hydrologic state space analysis to supplement the common geographical presentations. Two examples demonstrate the approach combining ERA and MODIS data sets: (a) global geobotanic classification by combining first and second moments of the dryness ratio (net radiation over precipitation) and (b) regional attributions (Tibetan Plateau) of vegetation changes.

  20. Borneo vortex and meso-scale convective rainfall

    Directory of Open Access Journals (Sweden)

    S. Koseki

    2013-08-01

    Full Text Available We have investigated how the Borneo vortex develops over the equatorial South China Sea under cold surge conditions in December during the Asian winter monsoon. Composite analysis using reanalysis and satellite datasets has revealed that absolute vorticity and water vapour are transported by strong cold surges from upstream of the South China Sea to around the equator. Rainfall is correspondingly enhanced over the equatorial South China Sea. A semi-idealized experiment reproduced the Borneo vortex over the equatorial South China Sea during a "perpetual" cold surge. The Borneo vortex is manifested as a meso-α cyclone with a comma-shaped rainband in the northeast sector of the cyclone. Vorticity budget analysis showed that the growth of the meso-α cyclone was achieved mainly by vortex stretching. The comma-shaped rainband consists of clusters of meso-β scale rainfall patches. The warm and wet cyclonic southeasterly flow meets with the cold and dry northeasterly surge forming a confluence front in the northeastern sector of the cyclone. Intense upward motion and heavy rainfall result both due to the low-level convergence and the favourable thermodynamic profile at the confluence front. At both meso-α and meso-β scales, the convergence is ultimately caused by the deviatoric strain in the confluence wind pattern but is much enhanced by nonlinear self-enhancement dynamics.

  1. Borneo Vortex and Meso-scale Convective Rainfall

    Science.gov (United States)

    Koh, T. Y.; Koseki, S.; Teo, C. K.

    2014-12-01

    We have investigated how the Borneo vortex develops over the equatorial South China Sea under cold surge conditions in December during the Asian winter monsoon. Composite analysis using reanalysis and satellite datasets has revealed that absolute vorticity and water vapour are transported by strong cold surges from upstream of the South China Sea to around the equator. Rainfall is correspondingly enhanced over the equatorial South China Sea. A semi-idealized experiment reproduced the Borneo vortex over the equatorial South China Sea during a perpetual cold surge. The Borneo vortex is manifested as a meso-alpha cyclone with a comma-shaped rainband in the northeast sector of the cyclone. Vorticity budget analysis showed that the growth/maintenance of the meso-alpha cyclone was achieved mainly by the vortex stretching. This vortex stretching is due to the upward motion forced by the latent heat release around the cyclone centre. The comma-shaped rainband consists of clusters of meso-beta scale rainfall cells. The intense rainfall in the comma-head (comma-tail) is generated by the confluence of the warmer and wetter cyclonic easterly flow (cyclonic southeasterly flow) and the cooler and drier northeasterly surge in the northwestern (northeastern) sector of the cyclone. Intense upward motion and heavy rainfall resulted due to the low-level convergence and the favourable thermodynamic profile at the confluence zone. In particular, the convergence in the northwestern sector is responsible for maintenance of the meso-alpha cyclone system. At both meso-alpha and meso-beta scales, the convergence is ultimately caused by the deviatoric strain in the confluence wind pattern but is significantly self-enhanced by the nonlinear dynamics. Reference: Koseki, S., T.-Y. Koh and C.-K. Teo (2014), Atmospheric Chemistry and Physics, 14, 4539-4562, doi:10.5194/acp-14-4539-2014, 2014.

  2. On the relationship of coastal tropical rainfall and the large-scale atmosphere

    CERN Document Server

    Bergemann, Martin; Lane, Todd P

    2015-01-01

    Rainfall in coastal areas of the tropics is often shaped by the presence of circulations directly associated with the topography, such as land-sea and/or mountain-valley breezes. In many regions the coastally-affected rainfall consitutes more than half of the overall rainfall received. Weather and climate models with parametrized convection produce large errors in rainfall in tropical coastal regions, most commonly underestimating rainfall over land and overestimating it over the ocean. 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 the large-scale atmosphere differs from that over the open ocean or over inland areas. We combine 3-hourly satellite estimates of rainfall with estimates of the large-scale atmospheric state from reanalyses. We find that when grouped by rainfall intensity, medium-intensity coastal rainfall in the tropics occurs in more stable conditions and drier ...

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

    Science.gov (United States)

    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.

  4. [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.

  5. 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. 

  6. 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.

  7. 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

  8. 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.

  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. Observed daily large-scale rainfall patterns during BOBMEX-1999

    Indian Academy of Sciences (India)

    A K Mitra; M Das Gupta; R K Paliwal; S V Singh

    2003-06-01

    A daily rainfall dataset and the corresponding rainfall maps have been produced by objective analysis of rainfall data. The satellite estimate of rainfall and the raingauge values are merged to form the final analysis. Associated with epochs of monsoon these rainfall maps are able to show the rainfall activities over India and the Bay of Bengal region during the BOBMEX period. The intra-seasonal variations of rainfall during BOBMEX are also seen using these data. This dataset over the oceanic region compares well with other available popular datasets like GPCP and CMAP. Over land this dataset brings out the features of monsoon in more detail due to the availability of more local raingauge stations.

  11. 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.

  12. 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

  13. Assessment of climate change impacts on rainfall using large scale climate variables and downscaling models – A case study

    Indian Academy of Sciences (India)

    Azadeh Ahmadi; Ali Moridi; Elham Kakaei Lafdani; Ghasem Kianpisheh

    2014-10-01

    Many of the applied techniques in water resources management can be directly or indirectly influenced by hydro-climatology predictions. In recent decades, utilizing the large scale climate variables as predictors of hydrological phenomena and downscaling numerical weather ensemble forecasts has revolutionized the long-lead predictions. In this study, two types of rainfall prediction models are developed to predict the rainfall of the Zayandehrood dam basin located in the central part of Iran. The first seasonal model is based on large scale climate signals data around the world. In order to determine the inputs of the seasonal rainfall prediction model, the correlation coefficient analysis and the new Gamma Test (GT) method are utilized. Comparison of modelling results shows that the Gamma test method improves the Nash–Sutcliffe efficiency coefficient of modelling performance as 8% and 10% for dry and wet seasons, respectively. In this study, Support Vector Machine (SVM) model for predicting rainfall in the region has been used and its results are compared with the benchmark models such as K-nearest neighbours (KNN) and Artificial Neural Network (ANN). The results show better performance of the SVM model at testing stage. In the second model, statistical downscaling model (SDSM) as a popular downscaling tool has been used. In this model, using the outputs from GCM, the rainfall of Zayandehrood dam is projected under two climate change scenarios. Most effective variables have been identified among 26 predictor variables. Comparison of the results of the two models shows that the developed SVM model has lesser errors in monthly rainfall estimation. The results show that the rainfall in the future wet periods are more than historical values and it is lower than historical values in the dry periods. The highest monthly uncertainty of future rainfall occurs in March and the lowest in July.

  14. 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.

  15. 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.

  16. Large Scale Meteorological Pattern of Extreme Rainfall in Indonesia

    Science.gov (United States)

    Kuswanto, Heri; Grotjahn, Richard; Rachmi, Arinda; Suhermi, Novri; Oktania, Erma; Wijaya, Yosep

    2014-05-01

    Extreme Weather Events (EWEs) cause negative impacts socially, economically, and environmentally. Considering these facts, forecasting EWEs is crucial work. Indonesia has been identified as being among the countries most vulnerable to the risk of natural disasters, such as floods, heat waves, and droughts. Current forecasting of extreme events in Indonesia is carried out by interpreting synoptic maps for several fields without taking into account the link between the observed events in the 'target' area with remote conditions. This situation may cause misidentification of the event leading to an inaccurate prediction. Grotjahn and Faure (2008) compute composite maps from extreme events (including heat waves and intense rainfall) to help forecasters identify such events in model output. The composite maps show large scale meteorological patterns (LSMP) that occurred during historical EWEs. Some vital information about the EWEs can be acquired from studying such maps, in addition to providing forecaster guidance. Such maps have robust mid-latitude meteorological patterns (for Sacramento and California Central Valley, USA EWEs). We study the performance of the composite approach for tropical weather condition such as Indonesia. Initially, the composite maps are developed to identify and forecast the extreme weather events in Indramayu district- West Java, the main producer of rice in Indonesia and contributes to about 60% of the national total rice production. Studying extreme weather events happening in Indramayu is important since EWEs there affect national agricultural and fisheries activities. During a recent EWE more than a thousand houses in Indramayu suffered from serious flooding with each home more than one meter underwater. The flood also destroyed a thousand hectares of rice plantings in 5 regencies. Identifying the dates of extreme events is one of the most important steps and has to be carried out carefully. An approach has been applied to identify the

  17. 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.

  18. 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...

  19. Continental-scale impacts of intra-seasonal rainfall variability on simulated ecosystem responses in Africa

    Directory of Open Access Journals (Sweden)

    K. Guan

    2014-05-01

    Full Text Available Climate change is expected to result in an increase of intra-seasonal rainfall variability, which has arisen from concurrent shifts in rainfall frequency, intensity and seasonality. Changes in intra-seasonal rainfall variability are likely to have important ecological impacts for terrestrial ecosystems, and quantifying these impacts across biomes and large climate gradients is required for a better prediction of ecosystem services and their responses to climate change. Here we use a synthetic weather generator and an advanced vegetation dynamic model (SEIB-DGVM to virtually conduct a series of "rainfall manipulation experiments" to study how changes in the intra-seasonal rainfall variability affect continent-scale ecosystem responses across Africa. We generated different rainfall scenarios with fixed total annual rainfall but shifts in: (i frequency vs. intensity, (ii seasonality vs. frequency, (iii intensity vs. seasonality. These scenarios were fed into the SEIB-DGVM to investigate changes in biome distributions and ecosystem productivity. We find a loss of ecosystem productivity with increased rainfall frequency and decreased intensity at very low rainfall regimes (−1 and low frequency (−1; beyond these very dry regimes, most ecosystems benefit from increasing frequency and decreasing intensity, except in the wet tropics (>1800 mm year−1 where radiation limitation prevents further productivity gains. This finding reconciles seemingly contradictory findings in previous field studies on the direction of rainfall frequency/intensity impacts on ecosystem productivity. We also find that changes in rainy season length can yield more dramatic ecosystem responses compared with similar percentage changes in rainfall frequency or intensity, with the largest impacts in semi-arid woodlands. This study demonstrates that not all rainfall regimes are ecologically equivalent, and that intra-seasonal rainfall characteristics play a significant role in

  20. Scaling Properties of Rainfall-Induced Landslides Predicted by a Physically Based Model

    CERN Document Server

    Alvioli, M; Rossi, M

    2013-01-01

    Natural landslides exhibit scaling properties, including the frequency of the size of the landslides, and the rainfall conditions responsible for landslides. Reasons for the scaling behavior of landslides are poorly known, and only a few attempts were made to describe the empirical evidences of the self-similar scaling behavior of landslides with physically based models. We investigate the possibility of using the TRIGRS code, a consolidated, physically motivated, numerical model to describe the stability conditions of natural slopes forced by rainfall, to determine the frequency of the area of the unstable slopes and the rainfall intensity-duration (I-D) conditions that result in landslides in a region.We apply TRIGRS in a portion of the Upper Tiber River Basin, Central Italy. The spatially distributed model predicts the stability conditions of individual grid cells, given the terrain and rainfall conditions. We run TRIGRS using multiple rainfall histories, and we compare the results to empirical evidences o...

  1. Applicability of open rainfall data to event-scale urban rainfall-runoff modelling

    Science.gov (United States)

    Niemi, Tero J.; Warsta, Lassi; Taka, Maija; Hickman, Brandon; Pulkkinen, Seppo; Krebs, Gerald; Moisseev, Dmitri N.; Koivusalo, Harri; Kokkonen, Teemu

    2017-04-01

    Rainfall-runoff simulations in urban environments require meteorological input data with high temporal and spatial resolutions. The availability of precipitation data is constantly increasing due to the shift towards more open data sharing. However, the applicability of such data for urban runoff assessments is often unknown. Here, the feasibility of Finnish Meteorological Institute's open rain gauge and open weather radar data as input sources was studied by conducting Storm Water Management Model simulations at a very small (33.5 ha) urban catchment in Helsinki, Finland. In addition to the open data sources, data were also available from two research gauges, one of them located on-site, and from a research radar. The results confirmed the importance of local precipitation measurements for urban rainfall-runoff simulations, implying the suitability of open gauge data to be largely dictated by the gauge's distance from the catchment. Performance of open radar data with 5 min and 1 km2 resolution was acceptable in terms of runoff reproduction, albeit peak flows were constantly and flow volumes often underestimated. Gauge adjustment and advection interpolation were found to improve the quality of the radar data, and at least gauge adjustment should be performed when open radar data are used. Finally, utilizing dual-polarization capabilities of radars has a potential to improve rainfall estimates for high intensity storms although more research is still needed.

  2. 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.

  3. 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.

  4. Continental-scale impacts of intra-seasonal rainfall variability on simulated ecosystem responses in Africa

    Science.gov (United States)

    Guan, K.; Good, S. P.; Caylor, K. K.; Sato, H.; Wood, E. F.; Li, H.

    2014-12-01

    Climate change is expected to modify intra-seasonal rainfall variability, arising from shifts in rainfall frequency, intensity and seasonality. These intra-seasonal changes are likely to have important ecological impacts on terrestrial ecosystems. Yet, quantifying these impacts across biomes and large climate gradients is largely missing. This gap hinders our ability to better predict ecosystem services and their responses to climate change, especially for arid and semi-arid ecosystems. Here we use a synthetic weather generator and an independently validated vegetation dynamic model (SEIB-Dynamic Global Vegetation Model, DGVM) to virtually conduct a series of "rainfall manipulation experiments" to study how changes in the intra-seasonal rainfall variability affect continent-scale ecosystem responses across Africa. We generate different rainfall scenarios with fixed total annual rainfall but shifts in (i) frequency vs. intensity, (ii) rainy season length vs. frequency, (iii) intensity vs. rainy season length. These scenarios are fed into SEIB-DGVM to investigate changes in biome distributions and ecosystem productivity. We find a loss of ecosystem productivity with increased rainfall frequency and decreased intensity at very low rainfall regimes (year-1) and low frequency (benefit from increased frequency and decreased intensity, except in the wet tropics (>1800 mm year-1) where radiation limitation prevents further productivity gains. This result reconciles seemingly contradictory findings in previous field studies on the impact of rainfall frequency/intensity on ecosystem productivity. We also find that changes in rainy season length can yield more dramatic ecosystem responses compared with similar percentage changes in rainfall frequency or intensity, with the largest impacts in semi-arid woodlands. This study demonstrates that intra-seasonal rainfall characteristics play a significant role in influencing ecosystem function and structure through controls on

  5. The sensitivity of catchment runoff models to rainfall data at different spatial scales

    Directory of Open Access Journals (Sweden)

    V. A. Bell

    2000-01-01

    Full Text Available The sensitivity of catchment runoff models to rainfall is investigated at a variety of spatial scales using data from a dense raingauge network and weather radar. These data form part of the HYREX (HYdrological Radar EXperiment dataset. They encompass records from 49 raingauges over the 135 km2 Brue catchment in south-west England together with 2 and 5 km grid-square radar data. Separate rainfall time-series for the radar and raingauge data are constructed on 2, 5 and 10 km grids, and as catchment average values, at a 15 minute time-step. The sensitivity of the catchment runoff models to these grid scales of input data is evaluated on selected convective and stratiform rainfall events. Each rainfall time-series is used to produce an ensemble of modelled hydrographs in order to investigate this sensitivity. The distributed model is shown to be sensitive to the locations of the raingauges within the catchment and hence to the spatial variability of rainfall over the catchment. Runoff sensitivity is strongest during convective rainfall when a broader spread of modelled hydrographs results, with twice the variability of that arising from stratiform rain. Sensitivity to rainfall data and model resolution is explored and, surprisingly, best performance is obtained using a lower resolution of rainfall data and model. Results from the distributed catchment model, the Simple Grid Model, are compared with those obtained from a lumped model, the PDM. Performance from the distributed model is found to be only marginally better during stratiform rain (R2 of 0.922 compared to 0.911 but significantly better during convective rain (R2 of 0.953 compared to 0.909. The improved performance from the distributed model can, in part, be accredited to the excellence of the dense raingauge network which would not be the norm for operational flood warning systems. In the final part of the paper, the effect of rainfall resolution on the performance of the 2 km distributed

  6. Scaling properties of rainfall time-series in the urban area of Rome

    Science.gov (United States)

    Volpi, E.; Napolitano, F.; Lombardo, F.

    2009-04-01

    The rainfall fields exhibits a high space-time variability which generates a large degree of uncertainty in modelling the process, thus causing lack of accuracy in many key hydrological problems, such as the forecasting of floods and the management of water resources. The large amount of literature produced in the last thirty years about this issue deals with the development of stochastic models able to represent the non-linearity and intermittence of rainfall in order to perform the downscaling process, i.e. transferring to finer scales the information on rainfall observed or forecasted at large scales. Traditionally, these models are based upon point processes in both the time (e.g. Waymire and Gupta, 1981) and the space-time domain (e.g. Rodriguez-Iturbe et al., 1986). Although this approach is cluster-based so as to model the physical structure of rainfall, its application may involve an inconvenient mathematical complexity and a large number of parameters, leading to several problems in parameter estimation. Another approach to this problem is based on the empirical detection of some regularity in hydrological observations, such as the scale-invariance properties of rainfall (e.g. Lovejoy and Schertzer, 1985). Models following this approach are based upon the assumption of a power law dependence of all statistical moments on the scale of aggregation. That means scaling properties can provide simple relationships to link the statistical distribution of the rainfall process at different spatial and temporal scales, in the ranges of which the power-low assumption can be verified (Marani, 2003). This work focuses on the analysis of the scaling properties of rainfall time series from a high density rain gauge network covering the Rome's urban area. The network consists of 24 sites, and the gauge record at each site has 10-minute time resolution and about 16-year length (1992-2007). The aim of the study is the identification of temporal scaling regimes, their ranges

  7. 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.

  8. Large scale features and assessment of spatial scale correspondence between TMPA and IMD rainfall datasets over Indian landmass

    Indian Academy of Sciences (India)

    R Uma; T V Lakshmi Kumar; M S Narayanan; M Rajeevan; Jyoti Bhate; K Niranjan Kumar

    2013-06-01

    Daily rainfall datasets of 10 years (1998–2007) of Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) version 6 and India Meteorological Department (IMD) gridded rain gauge have been compared over the Indian landmass, both in large and small spatial scales. On the larger spatial scale, the pattern correlation between the two datasets on daily scales during individual years of the study period is ranging from 0.4 to 0.7. The correlation improved significantly (∼0.9) when the study was confined to specific wet and dry spells each of about 5–8 days. Wavelet analysis of intraseasonal oscillations (ISO) of the southwest monsoon rainfall show the percentage contribution of the major two modes (30–50 days and 10–20 days), to be ranging respectively between ∼30–40% and 5–10% for the various years. Analysis of inter-annual variability shows the satellite data to be underestimating seasonal rainfall by ∼110 mm during southwest monsoon and overestimating by ∼150 mm during northeast monsoon season. At high spatio-temporal scales, viz., 1° × 1° grid, TMPA data do not correspond to ground truth. We have proposed here a new analysis procedure to assess the minimum spatial scale at which the two datasets are compatible with each other. This has been done by studying the contribution to total seasonal rainfall from different rainfall rate windows (at 1 mm intervals) on different spatial scales (at daily time scale). The compatibility spatial scale is seen to be beyond 5° × 5° average spatial scale over the Indian landmass. This will help to decide the usability of TMPA products, if averaged at appropriate spatial scales, for specific process studies, e.g., cloud scale, meso scale or synoptic scale.

  9. Power-law scaling in daily rainfall patterns and consequences in urban stream discharges

    Science.gov (United States)

    Park, Jeryang; Krueger, Elisabeth H.; Kim, Dongkyun; Rao, Suresh C.

    2016-04-01

    Poissonian rainfall has been frequently used for modelling stream discharge in a catchment at the daily scale. Generally, it is assumed that the daily rainfall depth is described by memoryless exponential distribution which is transformed to stream discharge, resulting in an analytical pdf for discharge [Gamma distribution]. While it is true that catchment hydrological filtering processes (censored by constant rate ET losses, and first-order recession) increases "memory", reflected in 1/f noise in discharge time series. Here, we show that for urban watersheds in South Korea: (1) the observation of daily rainfall depths follow power-law pdfs, and spectral slopes range between 0.2 ~ 0.4; and (2) the stream discharge pdfs have power-law tails. These observation results suggest that multiple hydro-climatic factors (e.g., non-stationarity of rainfall patterns) and hydrologic filtering (increasing impervious area; more complex urban drainage networks) influence the catchment hydrologic responses. We test the role of such factors using a parsimonious model, using different types of daily rainfall patterns (e.g., power-law distributed rainfall depth with Poisson distribution in its frequency) and urban settings to reproduce patterns similar to those observed in empirical records. Our results indicate that fractality in temporally up-scaled rainfall, and the consequences of large extreme events are preserved as high discharge events in urbanizing catchments. Implications of these results to modeling urban hydrologic responses and impacts on receiving waters are discussed.

  10. Rainfall Trends over the Indo-Pak Summer Monsoon and Related Large-Scale Dynamics

    Science.gov (United States)

    Latif, Muhammad; Syed, Faisal; Hannachi, Abdel

    2016-04-01

    The study of regional rainfall trends over South Asia is critically important for food security and infrastructure. This study investigates the presence of trends in seasonal and sub-seasonal (June through September-JJAS) rainfall obtained from multiple observed datasets. The obtained results identified a dipole-type structure in rainfall trends over the region north of the Indo-Pak subcontinent, where significant increasing trends are seen over the core monsoon region of Pakistan and significant decreasing trends are observed over the central-north India and adjacent areas. The study strongly suggests that strengthening of Vertically Integrated Meridional Moisture Transport (VIMMT) over the Arabian Sea is likely reason for the trend of rainfall in the core monsoon region of Pakistan. In contrast, over the central-north India region, the rainfall trends are significantly decreasing due to the weakening of IMT over the Bay of Bengal. The leading EOF clearly shows the strengthening (weakening) patterns of VIMMT over the Arabian Sea (Bay of Bengal) in seasonal and sub-seasonal interannual time-scales. The regression analysis between the principal components and rainfall confirms the dipole pattern over the region. Our results also suggest that the Circumglobal Teleconnection in upper troposphere influence in maintaining the mean rainfall over Pakistan via cross-equatorial flow of moisture into the Arabian Sea. We also investigate seasonal JJAS rainfall trends using historical and climate change (RCP4.5 and RCP8.5) simulations from a set of regional climate models from Coupled Model Intercomparison Project (CMIP5). Trends and asymmetry of seasonal rainfall show great variability across models. Meridional moisture transport and associated large-scale dynamics will also be discussed.

  11. Scaling statistics in a critical, nonlinear physical model of tropical oceanic rainfall

    Directory of Open Access Journals (Sweden)

    K. M. Nordstrom

    2003-01-01

    Full Text Available Over the last two decades, concepts of scale invariance have come to the fore in both modeling and data analysis in hydrological precipitation research. With the advent of the use of the multiplicative random cascade model, these concepts have become increasingly more important. However, unifying this statistical view of the phenomenon with the physics of rainfall has proven to be a rather nontrivial task. In this paper, we present a simple model, developed entirely from qualitative physical arguments, without invoking any statistical assumptions, to represent tropical atmospheric convection over the ocean. The model is analyzed numerically. It shows that the data from the model rainfall look very spiky, as if generated from a random field model. They look qualitatively similar to real rainfall data sets from Global Atmospheric Research Program (GARP Atlantic Tropical Experiment (GATE. A critical point is found in a model parameter corresponding to the Convective Inhibition (CIN, at which rainfall changes abruptly from non-zero to a uniform zero value over the entire domain. Near the critical value of this parameter, the model rainfall field exhibits multifractal scaling determined from a fractional wetted area analysis and a moment scaling analysis. It therefore must exhibit long-range spatial correlations at this point, a situation qualitatively similar to that shown by multiplicative random cascade models and GATE rainfall data sets analyzed previously (Over and Gupta, 1994; Over, 1995. However, the scaling exponents associated with the model data are different from those estimated with real data. This comparison identifies a new theoretical framework for testing diverse physical hypotheses governing rainfall based in empirically observed scaling statistics.

  12. Scaling statistics in a critical, nonlinear physical model of tropical oceanic rainfall

    Science.gov (United States)

    Nordstrom, K. M.; Gupta, V. K.

    Over the last two decades, concepts of scale invariance have come to the fore in both modeling and data analysis in hydrological precipitation research. With the advent of the use of the multiplicative random cascade model, these concepts have become increasingly more important. However, unifying this statistical view of the phenomenon with the physics of rainfall has proven to be a rather nontrivial task. In this paper, we present a simple model, developed entirely from qualitative physical arguments, without invoking any statistical assumptions, to represent tropical atmospheric convection over the ocean. The model is analyzed numerically. It shows that the data from the model rainfall look very spiky, as if generated from a random field model. They look qualitatively similar to real rainfall data sets from Global Atmospheric Research Program (GARP) Atlantic Tropical Experiment (GATE). A critical point is found in a model parameter corresponding to the Convective Inhibition (CIN), at which rainfall changes abruptly from non-zero to a uniform zero value over the entire domain. Near the critical value of this parameter, the model rainfall field exhibits multifractal scaling determined from a fractional wetted area analysis and a moment scaling analysis. It therefore must exhibit long-range spatial correlations at this point, a situation qualitatively similar to that shown by multiplicative random cascade models and GATE rainfall data sets analyzed previously (Over and Gupta, 1994; Over, 1995). However, the scaling exponents associated with the model data are different from those estimated with real data. This comparison identifies a new theoretical framework for testing diverse physical hypotheses governing rainfall based in empirically observed scaling statistics.

  13. Impact Assessment of Uncertainty Propagation of Ensemble NWP Rainfall to Flood Forecasting with Catchment Scale

    Directory of Open Access Journals (Sweden)

    Wansik Yu

    2016-01-01

    Full Text Available The common approach to quantifying the precipitation forecast uncertainty is ensemble simulations where a numerical weather prediction (NWP model is run for a number of cases with slightly different initial conditions. In practice, the spread of ensemble members in terms of flood discharge is used as a measure of forecast uncertainty due to uncertain precipitation forecasts. This study presents the uncertainty propagation of rainfall forecast into hydrological response with catchment scale through distributed rainfall-runoff modeling based on the forecasted ensemble rainfall of NWP model. At first, forecast rainfall error based on the BIAS is compared with flood forecast error to assess the error propagation. Second, the variability of flood forecast uncertainty according to catchment scale is discussed using ensemble spread. Then we also assess the flood forecast uncertainty with catchment scale using an estimation regression equation between ensemble rainfall BIAS and discharge BIAS. Finally, the flood forecast uncertainty with RMSE using specific discharge in catchment scale is discussed. Our study is carried out and verified using the largest flood event by typhoon “Talas” of 2011 over the 33 subcatchments of Shingu river basin (2,360 km2, which is located in the Kii Peninsula, Japan.

  14. 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.

  15. Rainfall Interpolation and Uncertainty Assessment at different Temporal and Spatial Scales

    Science.gov (United States)

    Bárdossy, A.; Pegram, G.

    2012-04-01

    Spatial interpolation of rainfall over different time and spatial scales is necessary in many applications of hydrometeorology including (i) catchment modelling, (ii) blending/conditioning of radar-rainfall images and (iii) correction of remote sensing estimates of rainfall (for example using TRMM) which are known to be biased, to name three. The specific problems encountered in rainfall interpolation include: • the large number of calculations which need to be performed automatically • the quantification of the influence of topography, usually the most influential of exogenous variables • how to use observed zero (dry) values in interpolation, because their proportion increases with shorter time scales • the need to estimate a reasonable uncertainty of the modelled point/pixel distributions • the difficulty of estimating uncertainty of accumulations over a range of spatial scales The approaches used and described in the presentation employ the variables rainfall and altitude. The methods of interpolation, restricted to 10 controls neighbouring the target, include (i) Ordinary Kriging of the rainfall without altitude, (ii) External Drift Kriging with altitude as an exogenous variable, and less conventionally, (iii) truncated Gaussian copulas and v-copulas, both omitting and including the altitude of the control stations as well as that of the target. It is found that truncated Gaussian copulas, with the target's and all control the stations' altitudes included as exogenous variables, produce the lowest Mean Square error in cross-validation and, as a bonus, model with the least bias. In contrast, the uncertainty of interpolation is better described by the v-copulas, but the Gaussian copulas have the computational advantage (by three orders of magnitude) which justifies their use in practice. It turns out that the uncertainty estimates of the OK and EDK interpolants are not competitive at any time scale, from daily to annual.

  16. Rainfall interception at the intrastorm scale: insights from a mature coniferous forest

    Science.gov (United States)

    Iida, S. I.; Levia, D. F., Jr.; Shimizu, A.; Shimizu, T.; Tamai, K.; Nobuhiro, T.; Kabeya, N.; Noguchi, S.; Sawano, S.; Araki, M.

    2016-12-01

    Canopy interception of rainfall is a mature subject. Nonetheless, the canopy interception process is inadequately understood at the intrastorm scale. To help fill our void of knowledge of intrastorm canopy interception, we employed detailed and fine-scale temporal measurements of meteorological and hydrological measurements from a mature coniferous forest in Japan. Throughfall was collected in a total area of 4 m2 and stemflow was measured for 14 trees of Japanese cedar (Cryptomeria japonica D. Don), and hourly intensity of interception loss was calculated as the difference between hourly intensity of gross rainfall and the sum of intensities of throughfall and stemflow. We specifically compared differences in canopy interception between the first and second halves of rainfall. Our results indicated that the interception intensity was larger at the initial stage of rainfall event and that interception intensity does not depend solely on intensity of gross rainfall. The accumulated amounts of interception intensity during the first half were quite larger than those of the second half. We found the decreases in the accumulated interception intensity caused by the higher mean wind speed for only the first half. These findings strongly suggested that water storage on tree surface is the single most important factor affecting the interception loss at this site, outweighing losses by wet canopy evaporation and splash during rain. This study adds insights into intrastorm interception dynamics which are necessary to better model and forecast interception losses at the watershed scale. Publication note: This presentation is based on the following submitted article: Iida, S., Levia, D.F., Shimizu, A., Shimizu, T., Tamai, K., Nobuhiro, T., Kabeya, N., Noguchi, S., Sawano, S. and Araki, M. Intrastorm scale rainfall interception dynamics in a mature coniferous forest stand.

  17. Inter-Scale Statistical Analysis of Fine-Resolution Rainfall Datasets over the Japanese Islands

    Science.gov (United States)

    Gómez García Alvéstegui, Martín; Koike, Toshio

    2015-04-01

    The continuous improvement of remotely-sensed precipitation estimates has greatly favored the inter-scale statistical study of rainfall fields and its potential applications. One of the expected results of this type of analysis is intended to provide the guidelines to effectively reproduce at finer scales (downscaling) the characteristic geometrical structure. Intermittency (no-rain areas contained within large rainfall fields), slow-varying gradients of intensity, and sudden sharp rises of intensity (high-intensity regions enclosed, or rapidly followed, by lower-intensity fields) are within the structural properties that define the rainfall fields. The concept of intermittency, indicates a positive probability of having no rain at some point, and for that reason the actual magnitude of rainfall intensity is not compatible with some scaling operations. However, the deviations of local means (local fluctuations) proved to be a process with noteworthy inter-scale statistical properties. Previous research revealed that local fluctuations can be well adjusted to stable distributions, in which the characteristic exponent α defines the thickness of the tails. If so, it can be inferred that this parameter should be related to the type of rainfall (rate of variation of intensity). However, the abovementioned research showed that in order to portray a self-similar relationship between scales the fluctuations needed to be divided by their correspondent local mean (standardization). The distribution of these standardized values was observed to be almost Gaussian (α = 2), and even though remarkable, with this operation becomes more challenging to relate the frequency of extreme values with the type of rainfall. In our study the local fluctuations of rainfall were analyzed by fitting the data to a folded stable distribution which is a distribution of absolute values. This approach not only allowed to reveal a somewhat invariance of the characteristic exponent between scales

  18. Sub-Daily Runoff Simulations with Parameters Inferred at the Daily Time Scale: Impacts of the temporal distribution of rainfall in parameter inference.

    Science.gov (United States)

    Reynolds Puga, Jose Eduardo; Halldin, Sven; Xu, Chong-Yu; Seibert, Jan

    2016-04-01

    procedure was based on the long-term daily distribution of rainfall, another on the long-term daily distribution of rainfall per month, and the last procedure assumed constant rainfall intensities during the day as in Reynolds et al. (2015). Finally, the parameter sets inferred from the 3 disaggregation procedures were compared and used to simulate runoff at the 1-h time scale to identify their impact on performance and their ability to reproduce discharge dynamics. REFERENCE J. E. Reynolds, S. Halldin, C. Y. Xu, J. Seibert, and A. Kauffeldt: Sub-daily runoff simulations with parameters inferred at the daily time scale, Hydrol. Earth Syst. Sci. D., 12(8), 7437-7467.

  19. Development of a censored modelling approach for stochastic estimation of rainfall extremes at fine temporal scales

    Science.gov (United States)

    Cross, David; Onof, Christian; Bernardara, Pietro

    2016-04-01

    With the COP21 drawing to a close in December 2015, storms Desmond, Eva and Frank which swept across the UK and Ireland causing widespread flooding and devastation have acted as a timely reminder of the need for reliable estimation of rainfall extremes in a changing climate. The frequency and intensity of rainfall extremes are predicted to increase in the UK under anthropogenic climate change, and it is notable that the UK's 24 hour rainfall record of 316mm set in Seathwaite, Cumbria in 2009 was broken on the 5 December 2015 with 341mm by storm Desmond at Honister Pass also in Cumbria. Immediate analysis of the latter by the Centre for Ecology and Hydrology (UK) on the 8 December 2015 estimated that this is approximately equivalent to a 1300 year return period event (Centre for Ecology & Hydrology, 2015). Rainfall extremes are typically estimated using extreme value analysis and intensity duration frequency curves. This study investigates the potential for using stochastic rainfall simulation with mechanistic rectangular pulse models for estimation of extreme rainfall. These models have been used since the late 1980s to generate synthetic rainfall time-series at point locations for scenario analysis in hydrological studies and climate impact assessment at the catchment scale. Routinely they are calibrated to the full historical hyetograph and used for continuous simulation. However, their extremal performance is variable with a tendency to underestimate short duration (hourly and sub-hourly) rainfall extremes which are often associated with heavy convective rainfall in temporal climates such as the UK. Focussing on hourly and sub-hourly rainfall, a censored modelling approach is proposed in which rainfall below a low threshold is set to zero prior to model calibration. It is hypothesised that synthetic rainfall time-series are poor at estimating extremes because the majority of the training data are not representative of the climatic conditions which give rise to

  20. Climatology of observed rainfall in Southeast France at the Regional Climate Model scales

    Science.gov (United States)

    Froidurot, Stéphanie; Molinié, Gilles; Diedhiou, Arona

    2016-04-01

    In order to provide convenient data to assess rainfall simulated by Regional Climate Models, a spatial database (hereafter called K-REF) has been designed. This database is used to examine climatological features of rainfall in Southeast France, a study region characterized by two mountain ranges of comparable altitude (the Cévennes and the Alps foothill) on both sides of the Rhône valley. Hourly records from 1993 to 2013 have been interpolated to a 0.1° × 0.1° latitude-longitude regular grid and accumulated over 3-h periods in K-REF. The assessment of K-REF relatively to the SAFRAN daily rainfall reanalysis indicates consistent patterns and magnitudes between the two datasets even though K-REF fields are smoother. A multi-scale analysis of the occurrence and non-zero intensity of rainfall is performed and shows that the maps of the 50th and 95th percentiles of 3- and 24-h rain intensity highlight different patterns. The maxima of the 50th and 95th percentiles are located over plain and mountainous areas respectively. Moreover, the location of these maxima is not the same for the 3- and 24-h intensities. To understand these differences between median and intense rainfall on the one hand and between the 3- and 24-h rainfall on the other hand, we analyze the statistical distributions and the space-time structure of occurrence and intensity of the 3-h rainfall in two classes of days, defined as median and intense. This analysis illustrates the influence of two factors on the triggering and the intensity of rain in the region: the solar cycle and the orography. The orographic forcing appears to be quite different for the two ranges of the domain and is much more pronounced over the Cévennes.

  1. 18O depletion in monsoon rain relates to large scale organized convection rather than the amount of rainfall.

    Science.gov (United States)

    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.

  2. The spatial extent of rainfall events and its relation to precipitation scaling

    Science.gov (United States)

    Lochbihler, Kai; Lenderink, Geert; Siebesma, A. Pier

    2017-08-01

    Observations show that subdaily precipitation extremes increase with dew point temperature at a rate exceeding the Clausius-Clapeyron (CC) relation. The understanding of this so-called super CC scaling is still incomplete, and observations of convective cell properties could provide important information. Here the size and intensity of rain cells are investigated by using a tracking of rainfall events in high-resolution radar data. Higher intensities are accompanied by larger rainfall areas. However, whereas small rain cells mainly follow CC scaling, larger cells display super CC behavior. Even more, for dew point exceeding 15°C, the rain cell size has to increase in order to sustain super CC scaling and a remarked increase in rain cell area is found. Our results imply that the source area of moisture, the cloud size, and the degree of mesoscale organization play key roles in the context of a warming climate.

  3. Intrastorm scale rainfall interception dynamics in a mature coniferous forest stand

    Science.gov (United States)

    Iida, Shin'ichi; Levia, Delphis F.; Shimizu, Akira; Shimizu, Takanori; Tamai, Koji; Nobuhiro, Tatsuhiko; Kabeya, Naoki; Noguchi, Shoji; Sawano, Shinji; Araki, Makoto

    2017-05-01

    Canopy interception of rainfall is an important process in the water balance of forests. The intrastorm dynamics of canopy interception is less well understood than event scale interception. Accordingly, armed with measurements of hourly interception intensity (i) from the field, this study is among the first to examine the differences in canopy interception dynamics between the first and second halves of rainfall events to quantify dynamic storage values for a coniferous forest in Japan. At this site, experimental results demonstrated that: (1) the relationship between interception loss (I) and gross rainfall (GR) at the event scale is better explained by a parabolic curve than a linear relationship, and there is a low correlation between rainfall intensity (gr) and i; (2) the ratio of accumulated i during the first half (IF) to that of gr (GRF) was larger than the second half (IS/GRS), with no significant correlations between potential evaporation during first half (PEF) vs IF or the second half (PES) vs IS; and (3) water storage capacity was similar to the magnitude of maximum I. By emphasizing the comparison between IF and IS, this study concludes that the water storage on tree surface is more important than losses by wet canopy evaporation and splash during rain. This study also adds insights into intrastorm interception dynamics of coniferous forests which are necessary to better model and forecast interception losses.

  4. Mesoscale and Local Scale Evaluations of Quantitative Precipitation Estimates by Weather Radar Products during a Heavy Rainfall Event

    Directory of Open Access Journals (Sweden)

    Basile Pauthier

    2016-01-01

    Full Text Available A 24-hour heavy rainfall event occurred in northeastern France from November 3 to 4, 2014. The accuracy of the quantitative precipitation estimation (QPE by PANTHERE and ANTILOPE radar-based gridded products during this particular event, is examined at both mesoscale and local scale, in comparison with two reference rain-gauge networks. Mesoscale accuracy was assessed for the total rainfall accumulated during the 24-hour event, using the Météo France operational rain-gauge network. Local scale accuracy was assessed for both total event rainfall and hourly rainfall accumulations, using the recently developed HydraVitis high-resolution rain gauge network Evaluation shows that (1 PANTHERE radar-based QPE underestimates rainfall fields at mesoscale and local scale; (2 both PANTHERE and ANTILOPE successfully reproduced the spatial variability of rainfall at local scale; (3 PANTHERE underestimates can be significantly improved at local scale by merging these data with rain gauge data interpolation (i.e., ANTILOPE. This study provides a preliminary evaluation of radar-based QPE at local scale, suggesting that merged products are invaluable for applications at very high resolution. The results obtained underline the importance of using high-density rain-gauge networks to obtain information at high spatial and temporal resolution, for better understanding of local rainfall variation, to calibrate remotely sensed rainfall products.

  5. Comparing rainfall variability, model complexity and hydrological response at the intra-event scale

    Science.gov (United States)

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

    2017-04-01

    The high variability in space and time of rainfall is one of the main aspects that influence hydrological response and generation of pluvial flooding. This phenomenon has a bigger impact in urban areas, where response is usually faster and flow peaks are typically higher, due to the high degree of imperviousness. Previous researchers have investigated sensitivity of urban hydrodynamic models to rainfall space-time resolution as well as interactions with model structure and resolution. They showed that finding a proper match between rainfall resolution and model complexity is important and that sensitivity increases for smaller urban catchment scales. Results also showed high variability in hydrological response sensitivity, the origins of which remain poorly understood. In this work, we investigate the interaction between rainfall input variability and model structure and scale at high resolution, i.e. 1-15 minutes in time and 100m to 3 km in space. Apart from studying summary statistics such as relative peak flow errors and coefficient of determination, we look into characteristics of response hydrographs to find explanations for response variability in relation to catchment properties as well storm event characteristics (e.g. storm scale and movement, single-peak versus multi-peak events). The aim is to identify general relations between storm temporal and spatial scale and catchment scale in explaining variability of hydrological response. Analyses are conducted for the Cranbrook catchment (London, UK), using 3 hydrodynamic models set up in InfoWorks ICM: a low resolution semi-distributed (SD1) model, a high resolution semi-distributed (SD2) model and a fully distributed (FD) model. These models represent the spatial variability of the land in different ways: semi-distributed models divide the surface in subcatchments, each of them modelled in a lumped way (51 subcatchment for the S model and 4409 subcatchments for the SD model), while the fully distributed

  6. Prediction of rainfall-induced shallow landslides at national scale in Italy

    Science.gov (United States)

    Montrasio, Lorella; Valentino, Roberto; Rossi, Lauro; Rudari, Roberto; Terrone, Andrea

    2013-04-01

    In Italy, landslides are very frequent, widespread and dangerous phenomena. In the last decades, climate changes, which provoked weather conditions characterized by localized rainfall events of high intensity and short duration, together with modifications of land use and an increase of urban areas, have led to a progressive increase of the frequency and extent of rainfall-induced landslides. These phenomena caused, in turn, considerable damage to structures, infrastructure and crops, as well as casualties. These natural and anthropogenic factors determine a series of hydrogeological problems for both land resource and for inhabited areas, industrial areas and for the infrastructural network. The need for a continued monitoring activity that ensures the preservation of life and human activities, and for a real-time assessment of landslide risk, in close correlation with rainfall forecasts, is therefore increasing. The paper deals with the application, on national scale in the Italian territory, of the physically-based stability model SLIP (Shallow Landslides Instability Prediction). The SLIP model has been firstly developed at the Department of Civil Engineering at the University of Parma since 1997, in order to describe the triggering mechanism of rainfall-induced landslides. More recently, the SLIP model has been tested as a prototype early warning system for rainfall-induced landslides in Italy, using rainfall data and geospatial datasets. The model, which is based on the limit equilibrium method, is deliberately simplified, in order to evaluate the safety factor of a slope in function of the geotechnical characteristics of the soil, the geometrical features of the slope and the rainfall depth. A back analysis concerning the occurrence of some recent case-histories of rainfall-induced shallow landslides in the Italian territory is carried out and the main results are shown. The main features of the SLIP model are briefly recalled and particular attention is

  7. Small-scale Rainfall Challenges Tested with Semi-distributed and Distributed Hydrological Models

    Science.gov (United States)

    Ichiba, Abdellah; Tchiguirinskaia, Ioulia; Gires, Auguste; Schertzer, Daniel; Bompard, Philippe

    2016-04-01

    Nowadays, there is a growing interest on small-scale rainfall information, provided by weather radars, to be used in urban water management and decision-making. Indeed, it helps to better understand the essential interactions between natural and man-made urban environments, both being complex systems. However the integration of this information in hydrological models remains a big challenge. In fact, urban water managers often rely on lumped or semi-distributed models with much coarser data resolution. The scope of this work is to investigate the sensitivity of two hydrological models to small-scale rainfall, and their potential improvements to integrate wholly the small-scale information. The case study selected to perform this study is a small urban catchment (245 ha), located at Val-de-Marne county (southeast of Paris, France). Investigations were conducted using either CANOE model, a semi-distributed conceptual model that is widely used in France for urban modeling, or a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech (www hmco-dev.enpc.fr/Tools-Training/Tools/Multi-Hydro.php). Initially, in CANOE model the catchment was divided into 9 sub-catchments with size ranging from 1ha to 76ha. A refinement process was conduced in the framework of this investigation in order to improve the model resolution by considering higher number of smaller sub-catchments. The new configuration consists of 44 sub-catchments with size ranging from 1ha-14ha. The Multi-Hydro modeling approach consists on rasterizing the catchment information to a regular spatial grid of a resolution chosen by the user. Each pixel is then affected by specific information, e.g., a unique land type per pixel, for which hydrological and physical properties are set. First of all, both models were validated with respect to real flow measurements using three types of rainfall data: (1) point measurement data coming form the Sucy-en-Brie rain gauge; (2) Meteo

  8. Impact Assessment of Uncertainty Propagation of Ensemble NWP Rainfall to Flood Forecasting with Catchment Scale

    OpenAIRE

    Wansik Yu; Eiichi Nakakita; Sunmin Kim; Kosei Yamaguchi

    2016-01-01

    The common approach to quantifying the precipitation forecast uncertainty is ensemble simulations where a numerical weather prediction (NWP) model is run for a number of cases with slightly different initial conditions. In practice, the spread of ensemble members in terms of flood discharge is used as a measure of forecast uncertainty due to uncertain precipitation forecasts. This study presents the uncertainty propagation of rainfall forecast into hydrological response with catchment scale t...

  9. Effect of Incident Rainfall Redistribution by Maize Canopy on Soil Moisture at the Crop Row Scale

    Directory of Open Access Journals (Sweden)

    Marco Martello

    2015-05-01

    Full Text Available The optimization of irrigation use in agriculture is a key challenge to increase farm profitability and reduce its ecological footprint. To this context, an understanding of more efficient irrigation systems includes the assessment of water redistribution at the microscale. This study aimed to investigate rainfall interception by maize canopy and to model the soil water dynamics at row scale as a result of rain and sprinkler irrigation with HYDRUS 2D/3D. On average, 78% of rainfall below the maize canopy was intercepted by the leaves and transferred along the stem (stemflow, while only 22% reached the ground directly (throughfall. In addition, redistribution of the water with respect to the amount (both rain and irrigation showed that the stemflow/throughfall ratio decreased logarithmically at increasing values of incident rainfall, suggesting the plant capacity to confine the water close to the roots and diminish water stress conditions. This was also underlined by higher soil moisture values observed in the row than in the inter-row at decreasing rainfall events. Modelled data highlighted different behavior in terms of soil water dynamics between simulated irrigation water distributions, although they did not show significant changes in terms of crop water use efficiency. These results were most likely affected by the soil type (silty-loam where the experiment was conducted, as it had unfavorable physical conditions for the rapid vertical water movement that would have increased infiltration and drainage.

  10. Spatial and temporal variations in rainfall over Darwin and its vicinity during different large-scale environments

    Science.gov (United States)

    Rauniyar, Surendra P.; Walsh, Kevin J. E.

    2016-02-01

    This study analyses the regional variations in rainfall over Darwin and its vicinity due to different large-scale circulations during the Australian summer by utilizing the combination of in situ and C-band polarimetric radar rainfall data at hourly resolution. The eight phases of the Madden-Julian oscillation as defined by Wheeler and Hendon (Mon Weather Rev 132(8):1917-1932, 2004) were used as indicators of different large-scale environments. The analysis found that the large-scale forcing starts to build up from phase 4 by the reversal of low- to mid-level easterly winds to moist westerly winds, reaching a maximum in phase 5 and weakening through phases 6-7. During phases 4-6, most of the study domain experiences widespread rainfall, but with distinct spatial and temporal structures. In addition, during these phases, coastal areas near Darwin receive more rainfall in the early morning (0200-0400 LT) due to the spreading or expansion of rainfall from the Beagle Gulf, explaining the occurrence of a secondary diurnal rainfall peak over Darwin. In contrast, local-scale mechanisms (sea breezes) reinvigorate from phase 8, further strengthening through phases 1-3, when low-level easterly winds become established over Darwin producing rainfall predominately over land and island locations during the afternoon. During these phases, below average rainfall is observed over most of the radar domain, except over the Tiwi Islands in phase 2.

  11. Secular spring rainfall variability at local scale over Ethiopia: trend and associated dynamics

    Science.gov (United States)

    Tsidu, Gizaw Mengistu

    2016-07-01

    Spring rainfall secular variability is studied using observations, reanalysis, and model simulations. The joint coherent spatio-temporal secular variability of gridded monthly gauge rainfall over Ethiopia, ERA-Interim atmospheric variables and sea surface temperature (SST) from Hadley Centre Sea Ice and SST (HadISST) data set is extracted using multi-taper method singular value decomposition (MTM-SVD). The contemporaneous associations are further examined using partial Granger causality to determine presence of causal linkage between any of the climate variables. This analysis reveals that only the northwestern Indian Ocean secular SST anomaly has direct causal links with spring rainfall over Ethiopia and mean sea level pressure (MSLP) over Africa inspite of the strong secular covariance of spring rainfall, SST in parts of subtropical Pacific, Atlantic, Indian Ocean and MSLP. High secular rainfall variance and statistically significant linear trend show consistently that there is a massive decline in spring rain over southern Ethiopia. This happened concurrently with significant buildup of MSLP over East Africa, northeastern Africa including parts of the Arabian Peninsula, some parts of central Africa and SST warming over all ocean basins with the exception of the ENSO regions. The east-west pressure gradient in response to the Indian Ocean warming led to secular southeasterly winds over the Arabian Sea, easterly over central Africa and equatorial Atlantic. These flows weakened climatological northeasterly flow over the Arabian Sea and southwesterly flow over equatorial Atlantic and Congo basins which supply moisture into the eastern Africa regions in spring. The secular divergent flow at low level is concurrent with upper level convergence due to the easterly secular anomalous flow. The mechanisms through which the northwestern Indian Ocean secular SST anomaly modulates rainfall are further explored in the context of East Africa using a simplified atmospheric

  12. Formation of low-level meso-scale southwest jet during seasonal rainfall

    Institute of Scientific and Technical Information of China (English)

    赵平; 周秀骥

    2001-01-01

    The meso-scale feature and energy budget of a low-level southwest jet were analyzed using the data collected during the heavy rainfall events that occurred between July 20 ~ 27, 1998 over the basin of the Changjiang.And the dynamic mechanism for the formation and maintenance of the meso-scale low-level jet under the condition of the low-level heterogeneous large-scale south wind was investigated using a shallow water model. The results can explain the mechanism of the formation of the meso-scale jet in this event and the importance of the heterogeneous large-scale horizontal motion in the formation of the meso-scale jet.

  13. How do geomorphic effects of rainfall vary with storm type and spatial scale in a post-fire landscape?

    Science.gov (United States)

    Kampf, Stephanie K.; Brogan, Daniel J.; Schmeer, Sarah; MacDonald, Lee H.; Nelson, Peter A.

    2016-11-01

    In post-fire landscapes, increased runoff and soil erosion can cause rapid geomorphic change. We examined how different types of rainfall events in 2013 affected hillslope-scale erosion and watershed-scale channel change in two 14-16 km2 watersheds within the 2012 High Park Fire burn area in northern Colorado, USA. The first set of rainfall events was a sequence of 12 short, spatially variable summer convective rain storms, and the second was a > 200 mm week-long storm in September. We compared rainfall characteristics, hillslope sediment yields, stream stage, and channel geometry changes from the summer storms to those from the September storm. The summer storms had a wide range of rainfall intensities, and each storm produced erosion primarily in one study watershed. The September storm rainfall had less spatial variability, covered both watersheds, and its total rainfall depth was 1.5 to 2.5 times greater than the total summer rainfall. Because rainfall intensities were highest during some summer storms, average hillslope sediment yields were higher for summer storms (6 Mg ha- 1) than for the September storm (3 Mg ha- 1). Maximum storm rainfall intensities were good predictors of hillslope sediment yield, but sediment yield correlated most strongly with total depths of rainfall exceeding 10-30 mm h- 1 intensity thresholds. The combined summer storms produced relatively small changes in mean channel bed elevation and cross section area, with no clear pattern of incision or aggradation. In contrast, the sustained rain across the entire study area during the September storm led to extensive upstream incision and downstream aggradation. Because of different spatial coverage of storms, summer storms produced more total hillslope erosion, whereas the September storm produced the greatest total channel changes. At both scales, high intensity rainfall above a threshold was responsible for inducing most of the geomorphic change.

  14. An ice core derived 1013-year catchment-scale annual rainfall reconstruction in subtropical eastern Australia

    Science.gov (United States)

    Tozer, Carly R.; Vance, Tessa R.; Roberts, Jason L.; Kiem, Anthony S.; Curran, Mark A. J.; Moy, Andrew D.

    2016-05-01

    Paleoclimate research indicates that the Australian instrumental climate record (˜ 100 years) does not cover the full range of hydroclimatic variability that is possible. To better understand the implications of this on catchment-scale water resources management, a 1013-year (1000-2012 common era (CE)) annual rainfall reconstruction was produced for the Williams River catchment in coastal eastern Australia. No high-resolution paleoclimate proxies are located in the region and so a teleconnection between summer sea salt deposition recorded in ice cores from East Antarctica and rainfall variability in eastern Australia was exploited to reconstruct the catchment-scale rainfall record. The reconstruction shows that significantly longer and more frequent wet and dry periods were experienced in the preinstrumental compared to the instrumental period. This suggests that existing drought and flood risk assessments underestimate the true risks due to the reliance on data and statistics obtained from only the instrumental record. This raises questions about the robustness of existing water security and flood protection measures and has serious implications for water resources management, infrastructure design and catchment planning. The method used in this proof of concept study is transferable and enables similar insights into the true risk of flood/drought to be gained for other paleoclimate proxy poor regions for which suitable remote teleconnected proxies exist. This will lead to improved understanding and ability to deal with the impacts of multi-decadal to centennial hydroclimatic variability.

  15. Debris-flow hazard assessment at regional scale by combining susceptibility mapping and radar rainfall

    Directory of Open Access Journals (Sweden)

    M. Berenguer

    2014-10-01

    Full Text Available This work presents a technique for debris flow (DF hazard assessment able to be used in the framework of DF early warning systems at regional scale. The developed system is applied at subbasin scale and is based on the concepts of fuzzy logic to combine two ingredients: (i DF subbasin susceptibility assessment based on geomorphological variables, and (ii the magnitude of the rainfall situation as depicted from radar rainfall estimates. The output of the developed technique is a three-class hazard level ("low", "moderate" and "high" in each subbasin when a new radar rainfall map is available. The developed technique has been applied in a domain in the Eastern Pyrenees (Spain from May to October 2010. The estimated hazard level stayed "low" during the entire period in 20% of the subbasins, while, in the most susceptible subbasins, the hazard level was at least moderate for up to10 days. Quantitative evaluation of the estimated hazard level was possible in a subbasin where debris flows were monitored during the analysis period. The technique was able to identify the 3 events observed in the catchment (1 debris flow and 2 hyperconcentrated flow events and produced no false alarm.

  16. Orographic signature on multiscale statistics of extreme rainfall: A storm-scale study

    Science.gov (United States)

    Ebtehaj, Mohammad; Foufoula-Georgiou, Efi

    2010-12-01

    Rainfall intensity and spatiotemporal patterns often show a strong dependence on the underlying terrain. The main objective of this work is to study the statistical signature imprinted by orography on the spatial structure of rainfall and its temporal evolution at multiple scales, with the aim of developing a consistent theoretical basis for conditional downscaling of precipitation given the topographic information of the underlying terrain. The results of an extensive analysis of the high-resolution stage II Doppler radar data of the Rapidan storm, June 1995, over the Appalachian Mountains is reported in this study. The orographic signature on the elementary statistical structure of the precipitation fields is studied via a variable-intensity thresholding scheme. This signature is further explored at multiple scales via analysis of the dependence of precipitation fields on the underlying terrain both in Fourier and wavelet domains. The generalized normal distribution is found to be a suitable probability model to explain the variability of the rainfall wavelet coefficients and its dependence on the underlying elevations. These results provide a new perspective for more accurate statistical downscaling of orographic precipitation over complex terrain with emphasis on preservation of extremes.

  17. Satellite radiometric remote sensing of rainfall fields: multi-sensor retrieval techniques at geostationary scale

    Directory of Open Access Journals (Sweden)

    F. S. Marzano

    2005-01-01

    Full Text Available The Microwave Infrared Combined Rainfall Algorithm (MICRA consists in a statistical integration method using the satellite microwave-based rain-rate estimates, assumed to be accurate enough, to calibrate spaceborne infrared measurements on limited sub-regions and time windows. Rainfall retrieval is pursued at the space-time scale of typical geostationary observations, that is at a spatial resolution of few kilometers and a repetition period of few tens of minutes. The actual implementation is explained, although the basic concepts of MICRA are very general and the method is easy to be extended for considering innovative statistical techniques or measurements from additional space-borne platforms. In order to demonstrate the potentiality of MICRA, case studies over central Italy are also discussed. Finally, preliminary results of MICRA validation by ground based remote and in situ measurements are shown and a comparison with a Neural Network (NN based technique is briefly illustrated.

  18. An ice core derived 1013-year catchment scale annual rainfall reconstruction in subtropical eastern Australia

    Science.gov (United States)

    Tozer, C. R.; Vance, T. R.; Roberts, J.; Kiem, A. S.; Curran, M. A. J.; Moy, A. D.

    2015-12-01

    Paleoclimate research indicates that the instrumental climate record (~100 years in Australia) does not cover the full range of hydroclimatic variability possible. To better understand the implications of this for catchment-scale water resources management, an annual rainfall reconstruction is produced for the Williams River catchment in coastal eastern Australia. No high resolution palaeoclimate proxies are located in the region and so a teleconnection between summer sea salt deposition recorded in ice cores from East Antarctica and rainfall variability in eastern Australia was exploited to reconstruct 1013 years of rainfall (AD 1000-2012). The reconstruction shows that significantly longer and more frequent wet and dry periods were experienced in the preinstrumental compared to the instrumental period. This suggests that existing drought and flood risk assessments underestimate the true risks due to the reliance on data and statistics obtained from only the instrumental record. This raises questions about the robustness of existing water security and flood protection measures and has serious implications for water resources management, infrastructure design, and catchment planning. The method used in this proof of concept study is transferable and enables similar insights into the true risk of flood/drought to be gained for other locations that are teleconnected to East Antarctica. This will lead to improved understanding and ability to deal with the impacts of multidecadal to centennial hydroclimatic variability.

  19. Sixth International Conference on Precipitation: Predictability of Rainfall at the Various Scales. Abstracts

    Energy Technology Data Exchange (ETDEWEB)

    None

    1998-06-29

    This volume contains abstracts of the papers presented at the Sixth International Conference on Precipitation: Predictability of Rainfall at the various scales, held at the Mauna Lani Bay and Bungalows, Hawaii, June 29 - July 1, 1998. The main goal of the conference was to bring together meteorologists, hydrologists, mathematicians, physicists, statisticians, and all others who are interested in fundamental principles governing the physical processes of precipitation. The results of the previous conferences have been published in issues of the Journal of Geophysical Research and Journal of Applied Meteorology. A similar format is planned for papers of this conference.

  20. 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...

  1. A large scale rainfall-runoff-inundation analysis of Thailand Flood 2011

    Science.gov (United States)

    Sayama, T.; Tatebe, Y.; Tanaka, S.

    2012-12-01

    A large amount of rainfall during the 2011 monsoonal season caused an unprecedented flood disaster in the Chao Phraya River basin in Thailand. When a large-scale flood occurs, it is very important to take appropriate emergency measures by holistically understanding the characteristics of the flooding based on available information and by predicting its possible development. This paper proposes quick response-type flood simulation that can be conducted during a severe flooding event. The hydrologic simulation model used in this study is designed to simulate river discharges and flood inundation simultaneously for an entire river basin with satellite based rainfall and topographic information. The model is based on two-dimensional diffusive wave equations for rainfall-runoff and inundation calculations. The model takes into account the effects of lateral subsurface flow and vertical infiltration flow since these two types of flow are also important processes. This paper presents prediction results obtained in mid-October 2011, when the flooding in Thailand was approaching to its peak. Our scientific question is how well we can predict the possible development of a large-scale flooding event with limited information and how much we can improve the prediction with more local information. In comparison with a satellite based flood inundation map, the study found that the quick response-type simulation (Case A) was capable of capturing the peak flood inundation extent reasonably. Our interpretation of the prediction was that the flooding might continue even until the end of November, which was positively confirmed to some extent by the actual flooding status in late November. In the meantime, the Case A simulation generally overestimated the peak water level. To address this overestimation, the input data was updated with additional local information (Case B). Consequently, the simulation accuracy improved in the lower basin by up to about 10 % for discharge and up to

  2. Identifying multiple time scale rainfall controls on Mojave Desert ecohydrology using an integrated data and modeling approach for Larrea tridentata

    Science.gov (United States)

    Ng, Gene-Hua Crystal; Bedford, David R.; Miller, David M.

    2015-06-01

    The perennial shrub Larrea tridentata is widely successful in North American warm deserts but is also susceptible to climatic perturbations. Understanding its response to rainfall variability requires consideration of multiple time scales. We examine intra-annual to multiyear relationships using model simulations of soil moisture and vegetation growth over 50 years in the Mojave National Preserve in southeastern California (USA). Ecohydrological model parameters are conditioned on field and remote sensing data using an ensemble Kalman filter. Although no specific periodicities were detected in the rainfall record, simulated leaf-area-index exhibits multiyear dynamics that are driven by multiyear (˜3 years) rains, but with up to a 1 year delay in peak response. Within a multiyear period, Larrea tridentata is more sensitive to winter rains than summer. In the most active part of the root zone (above ˜80 cm), >1 year average soil moisture drives vegetation growth, but monthly average soil moisture is controlled by root uptake. Moisture inputs reach the lower part of the root zone (below ˜80 cm) infrequently, but once there they can persist over a year to help sustain plant growth. Parameter estimates highlight efficient plant physiological properties facilitating persistent growth and high soil hydraulic conductivity allowing deep soil moisture stores. We show that soil moisture as an ecological indicator is complicated by bidirectional interactions with vegetation that depend on time scale and depth. Under changing climate, Larrea tridentata will likely be relatively resilient to shorter-term moisture variability but will exhibit higher sensitivity to shifts in seasonal to multiyear moisture inputs.

  3. 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.

  4. TRMM Science Highlights and Status of Precipitation Estimates on Monthly and Finder Time Scales

    Science.gov (United States)

    Adler, Robert; Einaudi, Franco (Technical Monitor)

    2001-01-01

    The Tropical Rainfall Measuring Mission (TRMM) has completed three years in orbit. A summary of research highlights will be presented focusing on application of TRMM data to topics ranging from climate analysis, through improving forecasts, to microphysical research. Monthly surface rainfall estimates over the ocean based on different instruments on TRMM currently differ by 20%. The difference is not surprising considering the different type of observations available for the first time from TRMM with both the passive and active microwave sensors. Resolving this difference will strengthen the validity and utility of ocean rainfall estimates and is the topic of ongoing research utilizing various facets of the TRMM validation and field experiment programs. The TRMM rainfall estimates are intercompared among themselves and with other estimates, including those of the standard, monthly Global Precipitation Climatology Project (GPCP) analysis. The GPCP analysis agrees roughly in magnitude with the passive microwave-based TRMM estimates which is not surprising considering GPCP over-ocean estimates are based on passive microwave observations. A three year TRMM rainfall climatology is presented based on the TRMM merged product, including anomaly fields related to the changing ENSO situation during the mission. Results of merging TRMM, other passive microwave observations, and geosynchronous infrared rainfall estimates into a global, tropical 3-hour time resolution analysis will also be described.

  5. Effects of wildfire, rainfall and region on desert lizard assemblages: the importance of multi-scale processes.

    Science.gov (United States)

    Pastro, Louise A; Dickman, Christopher R; Letnic, Mike

    2013-10-01

    Vertebrate populations are influenced by environmental processes that operate at a range of spatial and temporal scales. Wildfire is a disturbance that can affect vertebrate populations across large spatial scales, although vertebrate responses are frequently influenced by processes operating at smaller spatial scales such as topography, interspecific interactions and regional history. Here, we investigate the effects of a broad-scale wildfire on lizard assemblages in a desert region. We predicted that a rainfall gradient within the region affected by the wildfire would influence lizard responses to the fire by encouraging post-fire succession to proceed more rapidly in high-rainfall areas, and would be enabled in turn by more rapid vegetation recovery. To test our prediction, we censused lizards, measured rainfall, undertook vegetation surveys and sampled invertebrate abundance across burnt and unburnt habitat ecotones within three regional areas situated along a gradient of long-term annual rainfall. Lizard diversity was not affected by fire or region and lizard abundance was influenced only by region. Lizard assemblage composition was also only influenced by region, but this did not relate to differences in rainfall or habitat as we had predicted. Regional differences in lizard assemblages related instead to food availability. The observed differences also likely reflected regional differences in the strength of biotic interactions with predators and changes in land use. Our study shows that assemblage responses to a disturbance were not uniform within a large desert region and instead were influenced by other environmental processes operating simultaneously at multiple temporal and spatial scales.

  6. A multi-scale approach to quantifying non-rainfall water inputs

    Science.gov (United States)

    Agam, Nurit; Florentin, Anat

    2015-04-01

    Non-rainfall water inputs (NRWIs) are a gain of water to the surface soil layer caused by sources other than rainfall, i.e., by fog deposition, dew formation, or water vapor adsorption. These water inputs usually evaporate the following morning, creating a diurnal cycle of water content in the uppermost soil layer, which involves exchange of latent-heat flux (LE) between the soil and the atmosphere. The significance of the formation and evaporation of NRWIs in drylands is largely acknowledged, yet understanding of the environmental conditions controlling its magnitude are still lacking, and its spatial extent was not studied before. A multi-scale approach to quantifying NWRIs and the corresponding diurnal water cycle in arid regions will be presented. The research has been conducted over a bare loess soil in the Negev desert (30o51'35.30" N, 34o46'40.97" E) during the dry season (May-September 2014). During this dry period, gain in soil water content is only a result of NRWIs. A micro-lysimeter (ML) with a 20 cm diameter and 50 cm depth filled with an undisturbed soil sample was placed on a scale buried in the soil such that the top end of the sample was level with the soil surface and the sample's mass was continuously monitored. The ML served as a point measurement to which larger-scale micrometeorological methods, i.e., eddy covariance (EC) flux tower (field scale, ~2X103 m2) and a surface layer scintillometer (field scale, ~8X103 m2). The ability to obtain spatially distributed NWRIs at the regional scale through mapping changes in land surface emissivity was tested as well. Preliminary results indicate that despite the acknowledged limitations in nighttime measurements, the EC LE followed closely the micro-lysimeter LE; and the sensible heat flux derived by the EC and the scintillometer were in good agreement; demonstrating the feasibility of measuring NRWIs with both methods. This innovative multi-scale approach sheds light on various aspects of the NRWI

  7. Multifractality, imperfect scaling and hydrological properties of rainfall time series simulated by continuous universal multifractal and discrete random cascade models

    Science.gov (United States)

    Serinaldi, F.

    2010-12-01

    Discrete multiplicative random cascade (MRC) models were extensively studied and applied to disaggregate rainfall data, thanks to their formal simplicity and the small number of involved parameters. Focusing on temporal disaggregation, the rationale of these models is based on multiplying the value assumed by a physical attribute (e.g., rainfall intensity) at a given time scale L, by a suitable number b of random weights, to obtain b attribute values corresponding to statistically plausible observations at a smaller L/b time resolution. In the original formulation of the MRC models, the random weights were assumed to be independent and identically distributed. However, for several studies this hypothesis did not appear to be realistic for the observed rainfall series as the distribution of the weights was shown to depend on the space-time scale and rainfall intensity. Since these findings contrast with the scale invariance assumption behind the MRC models and impact on the applicability of these models, it is worth studying their nature. This study explores the possible presence of dependence of the parameters of two discrete MRC models on rainfall intensity and time scale, by analyzing point rainfall series with 5-min time resolution. Taking into account a discrete microcanonical (MC) model based on beta distribution and a discrete canonical beta-logstable (BLS), the analysis points out that the relations between the parameters and rainfall intensity across the time scales are detectable and can be modeled by a set of simple functions accounting for the parameter-rainfall intensity relationship, and another set describing the link between the parameters and the time scale. Therefore, MC and BLS models were modified to explicitly account for these relationships and compared with the continuous in scale universal multifractal (CUM) model, which is used as a physically based benchmark model. Monte Carlo simulations point out that the dependence of MC and BLS

  8. Multifractality, imperfect scaling and hydrological properties of rainfall time series simulated by continuous universal multifractal and discrete random cascade models

    Directory of Open Access Journals (Sweden)

    F. Serinaldi

    2010-12-01

    Full Text Available Discrete multiplicative random cascade (MRC models were extensively studied and applied to disaggregate rainfall data, thanks to their formal simplicity and the small number of involved parameters. Focusing on temporal disaggregation, the rationale of these models is based on multiplying the value assumed by a physical attribute (e.g., rainfall intensity at a given time scale L, by a suitable number b of random weights, to obtain b attribute values corresponding to statistically plausible observations at a smaller L/b time resolution. In the original formulation of the MRC models, the random weights were assumed to be independent and identically distributed. However, for several studies this hypothesis did not appear to be realistic for the observed rainfall series as the distribution of the weights was shown to depend on the space-time scale and rainfall intensity. Since these findings contrast with the scale invariance assumption behind the MRC models and impact on the applicability of these models, it is worth studying their nature. This study explores the possible presence of dependence of the parameters of two discrete MRC models on rainfall intensity and time scale, by analyzing point rainfall series with 5-min time resolution. Taking into account a discrete microcanonical (MC model based on beta distribution and a discrete canonical beta-logstable (BLS, the analysis points out that the relations between the parameters and rainfall intensity across the time scales are detectable and can be modeled by a set of simple functions accounting for the parameter-rainfall intensity relationship, and another set describing the link between the parameters and the time scale. Therefore, MC and BLS models were modified to explicitly account for these relationships and compared with the continuous in scale universal multifractal (CUM model, which is used as a physically based benchmark model. Monte Carlo simulations point out

  9. On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

    Directory of Open Access Journals (Sweden)

    D. Verdon-Kidd

    2008-10-01

    Full Text Available In this paper regional (synoptic and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO, the Southern Annular Mode (SAM and/or Indian Ocean Dipole (IOD are associated with a shift in the relative frequency of wet and dry synoptic types. Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal and long-term (i.e. decadal/multi-decadal scale. In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs may be assessed.

  10. Persistent decadal-scale rainfall variability in the tropical South Pacific Convergence Zone through the past six centuries

    Directory of Open Access Journals (Sweden)

    C. R. Maupin

    2013-10-01

    Full Text Available Observations and reconstructions of decadal-scale climate variability are necessary to place predictions of future global climate change into temporal context (Goddard et al., 2012. This is especially true for decadal-scale climate variability that originates in the Pacific Ocean (Deser et al., 2004; Dong and Lu, 2013. We focus here on the western tropical Pacific (Solomon Islands; ~ 9.5° S, ~ 160° E, a region directly influenced by: the South Pacific Convergence Zone (SPCZ, the West Pacific Warm Pool (WPWP, the Pacific Walker Circulation (PWC, and the Hadley Circulation. We calibrate δ18O variations in a fast growing stalagmite to local rainfall amount and produce a 600 yr record of rainfall variability from the zonally oriented, tropical portion of the SPCZ. We present evidence for large (~ 1.5 m, persistent and decade(s-long shifts in total annual rainfall amount in the Solomon Islands since 1416 ± 5 CE. The timing of the decadal changes in rainfall inferred from the 20th century portion of the stalagmite δ18O record coincide with previously identified decadal shifts in Pacific ocean-atmosphere behavior (Clement et al., 2011; Deser et al., 2004. The 600 yr Solomons stalagmite δ18O record indicates that decadal oscillations in rainfall are a robust characteristic of SPCZ-related climate variability, which has important implications to water resource management in this region.

  11. Assessing future climatic changes of rainfall extremes at small spatio-temporal scales

    DEFF Research Database (Denmark)

    Gregersen, Ida Bülow; Sørup, Hjalte Jomo Danielsen; Madsen, Henrik;

    2013-01-01

    in relation to urban flooding. The present study focuses on high-resolution regional climate model (RCM) skill in simulating sub-daily rainfall extremes. Temporal and spatial characteristics of output from three different RCM simulations with 25 km resolution are compared to point rainfall extremes estimated......Climate change is expected to influence the occurrence and magnitude of rainfall extremes and hence the flood risks in cities. Major impacts of an increased pluvial flood risk are expected to occur at hourly and sub-hourly resolutions. This makes convective storms the dominant rainfall type...

  12. A Modified Gash Model for Estimating Rainfall Interception Loss of Forest Using Remote Sensing Observations at Regional Scale

    Directory of Open Access Journals (Sweden)

    Yaokui Cui

    2014-04-01

    Full Text Available Rainfall interception loss of forest is an important component of water balance in a forested ecosystem. The Gash analytical model has been widely used to estimate the forest interception loss at field scale. In this study, we proposed a simple model to estimate rainfall interception loss of heterogeneous forest at regional scale with several reasonable assumptions using remote sensing observations. The model is a modified Gash analytical model using easily measured parameters of forest structure from satellite data and extends the original Gash model from point-scale to the regional scale. Preliminary results, using remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS products, field measured rainfall data, and meteorological data of the Automatic Weather Station (AWS over a picea crassifolia forest in the upper reaches of the Heihe River Basin in northwestern China, showed reasonable accuracy in estimating rainfall interception loss at both the Dayekou experimental site (R2 = 0.91, RMSE = 0.34 mm∙d −1 and the Pailugou experimental site (R2 = 0.82, RMSE = 0.6 mm∙d −1, compared with ground measurements based on per unit area of forest. The interception loss map of the study area was shown to be strongly heterogeneous. The modified model has robust physics and is insensitive to the input parameters, according to the sensitivity analysis using numerical simulations. The modified model appears to be stable and easy to be applied for operational estimation of interception loss over large areas.

  13. Linking rainfall-induced landslides with debris flows runout patterns towards catchment scale hazard assessment

    Science.gov (United States)

    Fan, Linfeng; Lehmann, Peter; McArdell, Brian; Or, Dani

    2017-03-01

    Debris flows and landslides induced by heavy rainfall represent an ubiquitous and destructive natural hazard in steep mountainous regions. For debris flows initiated by shallow landslides, the prediction of the resulting pathways and associated hazard is often hindered by uncertainty in determining initiation locations, volumes and mechanical state of the mobilized debris (and by model parameterization). We propose a framework for linking a simplified physically-based debris flow runout model with a novel Landslide Hydro-mechanical Triggering (LHT) model to obtain a coupled landslide-debris flow susceptibility and hazard assessment. We first compared the simplified debris flow model of Perla (1980) with a state-of-the art continuum-based model (RAMMS) and with an empirical model of Rickenmann (1999) at the catchment scale. The results indicate that predicted runout distances by the Perla model are in reasonable agreement with inventory measurements and with the other models. Predictions of localized shallow landslides by LHT model provides information on water content of released mass. To incorporate effects of water content and flow viscosity as provided by LHT on debris flow runout, we adapted the Perla model. The proposed integral link between landslide triggering susceptibility quantified by LHT and subsequent debris flow runout hazard calculation using the adapted Perla model provides a spatially and temporally resolved framework for real-time hazard assessment at the catchment scale or along critical infrastructure (roads, railroad lines).

  14. 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.

  15. Development and testing of a large, transportable rainfall simulator for plot-scale runoff and parameter estimation

    Directory of Open Access Journals (Sweden)

    T. G. Wilson

    2014-04-01

    Full Text Available There is increased interest in the interplay between vegetation conditions and overland flow generation. The literature is unclear on this relationship and there is little quantitative guidance for modeling efforts. Therefore, experimental efforts are needed and these call for a lightweight transportable plot-scale (>10 m2 rainfall simulator that can be deployed quickly and quickly redeployed over various vegetation cover conditions. Accordingly, a variable intensity rainfall simulator and collection system was designed and tested in the laboratory and in the field. The system was tested with three configurations of common pressure washing nozzles producing rainfall intensities of 62, 43, and 32 mm h−1 with uniformity coefficients of 76, 65, and 62, respectively, over a plot of 15.12 m2. Field tests were carried out in on a grassy field with silt-loam soil in Orroli, Sardinia in July and August 2010, and rainfall, soil moisture, and runoff data were collected. The two-term Philip infiltration model was used to find optimal values for the saturated hydraulic conductivity of the soil surface and bulk soil, soil water retention curve slope, and air entry suction head. Optimized hydraulic conductivity values were comparable to both the measured final infiltration rate and literature values for saturated hydraulic conductivity. This inexpensive rainfall simulator can therefore be used to identify field parameters needed for hydrologic modeling.

  16. 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.

  17. 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

  18. 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

  19. 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

  20. BRAVISSIMO: 12-month results from a large scale prospective trial.

    Science.gov (United States)

    Bosiers, M; Deloose, K; Callaert, J; Maene, L; Beelen, R; Keirse, K; Verbist, J; Peeters, P; Schroë, H; Lauwers, G; Lansink, W; Vanslembroeck, K; D'archambeau, O; Hendriks, J; Lauwers, P; Vermassen, F; Randon, C; Van Herzeele, I; De Ryck, F; De Letter, J; Lanckneus, M; Van Betsbrugge, M; Thomas, B; Deleersnijder, R; Vandekerkhof, J; Baeyens, I; Berghmans, T; Buttiens, J; Van Den Brande, P; Debing, E; Rabbia, C; Ruffino, A; Tealdi, D; Nano, G; Stegher, S; Gasparini, D; Piccoli, G; Coppi, G; Silingardi, R; Cataldi, V; Paroni, G; Palazzo, V; Stella, A; Gargiulo, M; Muccini, N; Nessi, F; Ferrero, E; Pratesi, C; Fargion, A; Chiesa, R; Marone, E; Bertoglio, L; Cremonesi, A; Dozza, L; Galzerano, G; De Donato, G; Setacci, C

    2013-04-01

    The BRAVISSIMO study is a prospective, non-randomized, multi-center, multi-national, monitored trial, conducted at 12 hospitals in Belgium and 11 hospitals in Italy. This manuscript reports the findings up to the 12-month follow-up time point for both the TASC A&B cohort and the TASC C&D cohort. The primary endpoint of the study is primary patency at 12 months, defined as a target lesion without a hemodynamically significant stenosis on Duplex ultrasound (>50%, systolic velocity ratio no greater than 2.0) and without target lesion revascularization (TLR) within 12 months. Between July 2009 and September 2010, 190 patients with TASC A or TASC B aortoiliac lesions and 135 patients with TASC C or TASC D aortoiliac lesions were included. The demographic data were comparable for the TASC A/B cohort and the TASC C/D cohort. The number of claudicants was significantly higher in the TASC A/B cohort, The TASC C/D cohort contains more CLI patients. The primary patency rate for the total patient population was 93.1%. The primary patency rates at 12 months for the TASC A, B, C and D lesions were 94.0%, 96.5%, 91.3% and 90.2% respectively. No statistical significant difference was shown when comparing these groups. Our findings confirm that endovascular therapy, and more specifically primary stenting, is the preferred treatment for patients with TASC A, B, C and D aortoiliac lesions. We notice similar endovascular results compared to surgery, however without the invasive character of surgery.

  1. On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

    Directory of Open Access Journals (Sweden)

    D. C. Verdon-Kidd

    2009-04-01

    Full Text Available In this paper regional (synoptic and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO, the Indian Ocean Dipole (IOD and/or the Southern Annular Mode (SAM are associated with a shift in the relative frequency of wet and dry synoptic types on an annual to inter-annual timescale. In addition, the relative frequency of synoptic types is shown to vary on a multi-decadal timescale, associated with changes in the Inter-decadal Pacific Oscillation (IPO. Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal and long-term (i.e. decadal/multi-decadal scale. In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs may be assessed.

  2. 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

  3. Association of Taiwan's October rainfall patterns with large-scale oceanic and atmospheric phenomena

    Science.gov (United States)

    Kuo, Yi-Chun; Lee, Ming-An; Lu, Mong-Ming

    2016-11-01

    The variability of the amount of October rainfall in Taiwan is the highest among all seasons. The October rainfall in Taiwan is attributable to interactions between the northeasterly monsoon and typhoons and their interaction with Taiwan's Central Mountain Range. This study applied long-term gridded rainfall data for defining the major rainfall pattern for October in Taiwan. The empirical orthogonal function Model 1 (80%) of the October rainfall and El Niño Southern Oscillation (ENSO) index exhibited a significant out-of-phase coherence in a 2-4 year period band. This is because an easterly flow on the northern edge of an anomalous low-level cyclonic circulation over the South China Sea during a La Niña developing stage increased the occurrence of an autumn cold front and enhanced the northeasterly monsoon toward northern Taiwan. In addition, a southerly flow on the eastern edge of the anomalous cyclone increased the moisture transport from the tropical Pacific toward Taiwan. The warmer sea surface temperature in the South China Sea, Kuroshio, and the subtropical western Pacific, which may have been induced by an ENSO warm phase peak in the preceding winter, promoted the formation of the anomalous low-level cyclonic circulation.

  4. 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.

  5. Characterization of hydrological responses to rainfall and volumetric coefficients on the event scale in rural catchments of the Iberian Peninsula

    Science.gov (United States)

    Taguas, Encarnación; Nadal-Romero, Estela; Ayuso, José L.; Casalí, Javier; Cid, Patricio; Dafonte, Jorge; Duarte, Antonio C.; Giménez, Rafael; Giráldez, Juan V.; Gómez-Macpherson, Helena; Gómez, José A.; González-Hidalgo, J. Carlos; Lucía, Ana; Mateos, Luciano; Rodríguez-Blanco, M. Luz; Schnabel, Susanne; Serrano-Muela, M. Pilar; Lana-Renault, Noemí; Mercedes Taboada-Castro, M.; Taboada-Castro, M. Teresa

    2016-04-01

    Analysis of storm rainfall-runoff data is essential to improve our understanding of catchment hydrology and to validate models supporting hydrological planning. In a context of climate change, statistical and process-based models are helpful to explore different scenarios which might be represented by simple parameters such as volumetric runoff coefficient. In this work, rainfall-runoff event datasets collected at 17 rural catchments in the Iberian Peninsula were studied. The objectives were: i) to describe hydrological patterns/variability of the relation rainfall-runoff; ii) to explore different methodologies to quantify representative volumetric runoff coefficients. Firstly, the criteria used to define an event were examined in order to standardize the analysis. Linear regression adjustments and statistics of the rainfall-runoff relations were examined to identify possible common patterns. In addition, a principal component analysis was applied to evaluate the variability among catchments based on their physical attributes. Secondly, runoff coefficients at event temporal scale were calculated following different methods. Median, mean, Hawkinś graphic method (Hawkins, 1993), reference values for engineering project of Prevert (TRAGSA, 1994) and the ratio of cumulated runoff and cumulated precipitation of the event that generated runoff (Rcum) were compared. Finally, the relations between the most representative volumetric runoff coefficients with the physical features of the catchments were explored using multiple linear regressions. The mean volumetric runoff coefficient in the studied catchments was 0.18, whereas the median was 0.15, both with variation coefficients greater than 100%. In 6 catchments, rainfall-runoff linear adjustments presented coefficient of determination greater than 0.60 (p hydrological response differences in the catchments. REFERENCES: Hawkins, R. H. (1993). Asymptotic determination of runoff curve numbers from data. J. Irrig. Drain. Eng

  6. A field-scale infiltration model accounting for spatial heterogeneity of rainfall and soil saturated hydraulic conductivity

    Science.gov (United States)

    Morbidelli, Renato; Corradini, Corrado; Govindaraju, Rao S.

    2006-04-01

    This study first explores the role of spatial heterogeneity, in both the saturated hydraulic conductivity Ks and rainfall intensity r, on the integrated hydrological response of a natural slope. On this basis, a mathematical model for estimating the expected areal-average infiltration is then formulated. Both Ks and r are considered as random variables with assessed probability density functions. The model relies upon a semi-analytical component, which describes the directly infiltrated rainfall, and an empirical component, which accounts further for the infiltration of surface water running downslope into pervious soils (the run-on effect). Monte Carlo simulations over a clay loam soil and a sandy loam soil were performed for constructing the ensemble averages of field-scale infiltration used for model validation. The model produced very accurate estimates of the expected field-scale infiltration rate, as well as of the outflow generated by significant rainfall events. Furthermore, the two model components were found to interact appropriately for different weights of the two infiltration mechanisms involved.

  7. Use Of Radar-Rainfall Data for the Southwest Coastal Louisiana Feasibility Study: Regional Scale Hydrologic and Salinity Modeling and Management Scenario Analysis for Chenier Plain

    Science.gov (United States)

    Meselhe, E. A.; Michot, B.; Chen, C.; Habib, E. H.

    2011-12-01

    The Chenier Plain, in Southwest Louisiana, extends from Vermilion Bay to Sabine Lake in southeast Texas. It has great economic, industrial, recreational, and ecological value. Over the years, human activities such as dredging ship channels and access canals, building roads, levees, and hydraulic structures have altered the hydrology of the Chenier Plain. These alterations have affected the fragile equilibrium of the marsh ecology. If no action is taken to restore the Chenier Plain, land loss through conversion of marsh to open water would continue. The Southwest Coastal Louisiana Feasibility Study aims at evaluating proposed protection and restoration measures and ultimately submitting a comprehensive plan to protect and preserve the Chenier Plain at the regional scale. The proposed alternatives include marsh creation, terracing, shoreline protection, and freshwater introduction and salinity control structures. A regional scale hydrodynamic and salinity transport model was developed to screen and assess the proposed restoration measures. A critical component of this modeling effort is local rainfall. The strong spatial variability and limited availability of ground-level precipitation measurements limited our ability to capture local rainfall. Thus, a radar-based rainfall product was used as a viable alternative to the rain gauges. These estimates are based on the National Weather Service from the Multi-Sensor Precipitation Estimator (MPE) algorithm. Since the model was used to perform long-term (yearly) simulations, the 4x4 km2 MPE estimates were represented as daily accumulations. The use of the radar-rainfall product data improved the model performance especially on our ability to capture the spatial and temporal variations of salinity. Overall, the model is improving our understanding of the circulation patterns and salinity regimes of the region. The circulation model used here is the MIKE FLOOD software (Danish Hydraulic Institute, DHI 2008) which dynamically

  8. Hydrological impacts of the small scale rainfall variability in an urban catchment: CALAMAR vs. X-band radar data

    Science.gov (United States)

    Alves de Souza, Bianca; da Silva Rocha Paz, Igor; Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel

    2017-04-01

    Increasing urbanization and population density makes dealing with extreme weather events more difficult notably with regards to flood risks and more generally to storm water management. Such challenge requires the development and practical implementation of new technologies and methods. An example is weather radar which has been increasingly applied to hydrological modelling due to their unique ability to grasp both the spatial and temporal variability of rainfall fields. In this paper 6 radar rainfall products available over the Paris region are compared: CALAMAR and five different X-band radar data products. The first has a resolution of 1 km in space and 5 min in time and is a product provided by RHEA SAS using single polarimetric raw data of a local C-band radar operated by Météo-France and real time adjustment with a network of rain gauges..The latter are obtained from the radar operated by École des Ponts ParisTech currently providing data with a resolution of 250 m in space and 3.4 min in time. Rainfall fields are then inputted in the fully distributed model Multi-Hydro. It is done over a 6.2 km2 urban and peri-urban catchment located in Massy, south of Paris. Simulated outputs are then compared to actual water level measurement in storage basins. Three rainfall events that occurred in May and June 2016 are tested in this study. The comparison of the simulated hydrographs obtained with different inputs illustrates the benefits of a higher resolution for rainfall fields. The impact of the small-scale variability not measured by the CALAMAR data is quantified, as well as the hydrological consequences of the use of various radar algorithms over the same raw radar data. These results highlight the need to use the data available with the higher resolution such as the one operationally provided by X-band radars, as well as to use it better, i.e. notably with models able to take into account the newly observed small scale rainfall variability.

  9. Large-scale circulation patterns and related rainfall in the Amazon Basin: a neuronal networks approach

    Energy Technology Data Exchange (ETDEWEB)

    Espinoza, Jhan Carlo [LOCEAN - IPSL (IRD, CNRS, MNHN, UPMC), Paris Cedex 05 (France); Universidad Agraria La Molina UNALM, Lima (Peru); Lengaigne, Matthieu; Janicot, Serge [LOCEAN - IPSL (IRD, CNRS, MNHN, UPMC), Paris Cedex 05 (France); Ronchail, Josyane [LOCEAN - IPSL (IRD, CNRS, MNHN, UPMC), Paris Cedex 05 (France); Universite Paris 7, Paris (France)

    2012-01-15

    This study describes the main circulation patterns (CP) in the Amazonian Basin over the 1975-2002 period and their relationship with rainfall variability. CPs in the Amazonian Basin have been computed for each season from the ERA-40 daily 850 hPa winds using an approach combining artificial neural network (Self Organizing Maps) and Hierarchical Ascendant Classification. A 6 to 8 cluster solutions (depending on the season considered) is shown to yield an integrated view of the complex regional circulation variability. For austral fall, winter and spring the temporal evolution between the different CPs shows a clear tendency to describe a cycle, with southern wind anomalies and their convergence with the trade winds progressing northward from the La Plata Basin to the Amazon Basin. This sequence is strongly related to eastward moving extra tropical perturbations and their incursion toward low latitude that modulate the geopotential and winds over South America and its adjoining oceans. During Austral summer, CPs are less spatially and temporally organized compared to other seasons, principally due to weaker extra tropical perturbations and more frequent shallow low situations. Each of these CPs is shown to be associated with coherent northward moving regional rainfall patterns (both in in situ data and ERA-40 reanalysis) and convective activity. However, our results reveals that precipitation variability is better reproduced by ERA-40 in the southern part of the Amazonian Basin than in the northern part, where rainfall variability is likely to be more constrained by local and subdaily processes (e.g. squall lines) that could be misrepresented in the reanalysis dataset. This analysis clearly illustrates the existing connections between the southern and northern part of the Amazonian Basin in terms of regional circulation/rainfall patterns. The identification of these CPs provide useful information to understand local rainfall variability and could hence be used to

  10. Towards large-scale monitoring of soil erosion in Africa: Accounting for the dynamics of rainfall erosivity

    Science.gov (United States)

    Vrieling, Anton; Hoedjes, Joost C. B.; van der Velde, Marijn

    2014-04-01

    Soil erosion by water occurs on sloped terrain when erosive rainfall and consequent surface runoff act on soils that are not well-protected by vegetation or other soil protective measures. Both rainfall erosivity and vegetation cover are highly variable through space and time. Joint accounting for the variability of these factors is required to effectively map and monitor soil erosion. However, most studies merely use average annual erosivity values, partly due to data paucity. This study analyses the variability of rainfall erosivity across Africa through the use of 3-hourly TRMM Multi-satellite Precipitation Analysis (TMPA) precipitation data. We obtained average annual erosivity estimates from 15 yr of TMPA data (1998-2012) using intensity-erosivity relationships. Our estimates showed a positive correlation (r = 0.84) with long-term annual erosivity values of 37 stations obtained from literature. Our TMPA-analysis confirmed and mapped the large interannual variability, with maximum annual erosivity often exceeding two to three times the mean value, especially in semi-arid areas. Seasonal variability of erosivity was investigated from TMPA-based average monthly erosivity estimates, which resulted in similar seasonal patterns as those reported in literature. We conclude that (1) spatial and temporal variability of erosivity is important and needs to be accounted for in combination with vegetation cover when monitoring soil erosion; and (2) 3-hourly TMPA data allow for a good first estimate of the variability of erosivity in Africa, which could be improved by upcoming techniques that provide more accurate rainfall information at higher spatial and temporal resolutions.

  11. Multiple regression and Artificial Neural Network for long-term rainfall forecasting using large scale climate modes

    Science.gov (United States)

    Mekanik, F.; Imteaz, M. A.; Gato-Trinidad, S.; Elmahdi, A.

    2013-10-01

    In this study, the application of Artificial Neural Networks (ANN) and Multiple regression analysis (MR) to forecast long-term seasonal spring rainfall in Victoria, Australia was investigated using lagged El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) as potential predictors. The use of dual (combined lagged ENSO-IOD) input sets for calibrating and validating ANN and MR Models is proposed to investigate the simultaneous effect of past values of these two major climate modes on long-term spring rainfall prediction. The MR models that did not violate the limits of statistical significance and multicollinearity were selected for future spring rainfall forecast. The ANN was developed in the form of multilayer perceptron using Levenberg-Marquardt algorithm. Both MR and ANN modelling were assessed statistically using mean square error (MSE), mean absolute error (MAE), Pearson correlation (r) and Willmott index of agreement (d). The developed MR and ANN models were tested on out-of-sample test sets; the MR models showed very poor generalisation ability for east Victoria with correlation coefficients of -0.99 to -0.90 compared to ANN with correlation coefficients of 0.42-0.93; ANN models also showed better generalisation ability for central and west Victoria with correlation coefficients of 0.68-0.85 and 0.58-0.97 respectively. The ability of multiple regression models to forecast out-of-sample sets is compatible with ANN for Daylesford in central Victoria and Kaniva in west Victoria (r = 0.92 and 0.67 respectively). The errors of the testing sets for ANN models are generally lower compared to multiple regression models. The statistical analysis suggest the potential of ANN over MR models for rainfall forecasting using large scale climate modes.

  12. Seasonal rainfall forecasting by adaptive network-based fuzzy inference system (ANFIS) using large scale climate signals

    Science.gov (United States)

    Mekanik, F.; Imteaz, M. A.; Talei, A.

    2016-05-01

    Accurate seasonal rainfall forecasting is an important step in the development of reliable runoff forecast models. The large scale climate modes affecting rainfall in Australia have recently been proven useful in rainfall prediction problems. In this study, adaptive network-based fuzzy inference systems (ANFIS) models are developed for the first time for southeast Australia in order to forecast spring rainfall. The models are applied in east, center and west Victoria as case studies. Large scale climate signals comprising El Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Inter-decadal Pacific Ocean (IPO) are selected as rainfall predictors. Eight models are developed based on single climate modes (ENSO, IOD, and IPO) and combined climate modes (ENSO-IPO and ENSO-IOD). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Pearson correlation coefficient (r) and root mean square error in probability (RMSEP) skill score are used to evaluate the performance of the proposed models. The predictions demonstrate that ANFIS models based on individual IOD index perform superior in terms of RMSE, MAE and r to the models based on individual ENSO indices. It is further discovered that IPO is not an effective predictor for the region and the combined ENSO-IOD and ENSO-IPO predictors did not improve the predictions. In order to evaluate the effectiveness of the proposed models a comparison is conducted between ANFIS models and the conventional Artificial Neural Network (ANN), the Predictive Ocean Atmosphere Model for Australia (POAMA) and climatology forecasts. POAMA is the official dynamic model used by the Australian Bureau of Meteorology. The ANFIS predictions certify a superior performance for most of the region compared to ANN and climatology forecasts. POAMA performs better in regards to RMSE and MAE in east and part of central Victoria, however, compared to ANFIS it shows weaker results in west Victoria in terms of prediction errors and RMSEP skill

  13. Extreme rainfall, vulnerability and risk: a continental-scale assessment for South America

    Science.gov (United States)

    Vorosmarty, Charles J.; de Guenni, Lelys Bravo; Wollheim, Wilfred M.; Pellerin, Brian A.; Bjerklie, David M.; Cardoso, Manoel; D'Almeida, Cassiano; Colon, Lilybeth

    2013-01-01

    Extreme weather continues to preoccupy society as a formidable public safety concern bearing huge economic costs. While attention has focused on global climate change and how it could intensify key elements of the water cycle such as precipitation and river discharge, it is the conjunction of geophysical and socioeconomic forces that shapes human sensitivity and risks to weather extremes. We demonstrate here the use of high-resolution geophysical and population datasets together with documentary reports of rainfall-induced damage across South America over a multi-decadal, retrospective time domain (1960–2000). We define and map extreme precipitation hazard, exposure, affectedpopulations, vulnerability and risk, and use these variables to analyse the impact of floods as a water security issue. Geospatial experiments uncover major sources of risk from natural climate variability and population growth, with change in climate extremes bearing a minor role. While rural populations display greatest relative sensitivity to extreme rainfall, urban settings show the highest rates of increasing risk. In the coming decades, rapid urbanization will make South American cities the focal point of future climate threats but also an opportunity for reducing vulnerability, protecting lives and sustaining economic development through both traditional and ecosystem-based disaster risk management systems.

  14. 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

  15. 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.

  16. Sensitivities of Cumulus-Ensemble Rainfall in a Cloud-Resolving Model with Parameterized Large-Scale Dynamics.

    Science.gov (United States)

    Mapes, Brian E.

    2004-09-01

    The problem of closure in cumulus parameterization requires an understanding of the sensitivities of convective cloud systems to their large-scale setting. As a step toward such an understanding, this study probes some sensitivities of a simulated ensemble of convective clouds in a two-dimensional cloud-resolving model (CRM). The ensemble is initially in statistical equilibrium with a steady imposed background forcing (cooling and moistening). Large-scale stimuli are imposed as horizontally uniform perturbations nudged into the model fields over 10 min, and the rainfall response of the model clouds is monitored.In order to reduce a major source of artificial insensitivity in the CRM, a simple parameterization scheme is devised to account for heating-induced large-scale (i.e., domain averaged) vertical motions that would develop in nature but are forbidden by the periodic boundary conditions. The effects of this large-scale vertical motion are parameterized as advective tendency terms that are applied as a uniform forcing throughout the domain, just like the background forcing. This parameterized advection is assumed to lag rainfall (used as a proxy for heating) by a specified time scale. The time scale determines (via a gravity wave space time conversion factor) the size of the large-scale region represented by the periodic CRM domain, which can be of arbitrary size or dimensionality.The sensitivity of rain rate to deep cooling and moistening, representing an upward displacement by a large-scale wave of first baroclinic mode structure, is positive. Near linearity is found for ±1 K perturbations, and the sensitivity is about equally divided between temperature and moisture effects. For a second baroclinic mode (vertical dipole) displacement, the sign of the perturbation in the lower troposphere dominates the convective response. In this dipole case, the initial sensitivity is very large, but quantitative results are distorted by the oversimplified large-scale

  17. Use of rai and wavelet of analysis of the influence of the temporal multi-scales in the rainfall of the Mundaú River watershed

    Directory of Open Access Journals (Sweden)

    Francisco de Assis Salviano de Sousa

    2009-03-01

    Full Text Available The variations of the rainfall in a region of the Mundaú river watershed, at state of Alagoas, Brazil, had been studied using the rainfall anomaly index (RAI and the Wavelet Analysis. This method involves transformation of a one-dimensional series in a time space and frequency, allowing determining the dominant scales of variability and its secular variations. The results had shown that the precipitation variability in the two regions is defined by located secular multi-scales in certain intervals of time. However, on inter-annual variability to the ENSO cycle and the decadal variability of the scales had influenced in the local pluviometric variability.

  18. 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

  19. West Africa Extreme Rainfall Events and Large-Scale Ocean Surface and Atmospheric Conditions in the Tropical Atlantic

    Directory of Open Access Journals (Sweden)

    S. Ta

    2016-01-01

    Full Text Available Based on daily precipitation from the Global Precipitation Climatology Project (GPCP data during April–October of the 1997–2014 period, the daily extreme rainfall trends and variability over West Africa are characterized using 90th-percentile threshold at each grid point. The contribution of the extreme rainfall amount reaches ~50–90% in the northern region while it is ~30–50% in the south. The yearly cumulated extreme rainfall amount indicates significant and negative trends in the 6°N–12°N; 6°N–12°N; 17°W–10°W and 4°N–7°N; 4°N–7°N; 6°E–10°E 4°N–7°N; 6°E–10°E 4°N–7°N; 6°E–10°E domains, while the number of days exhibits nonsignificant trends over West Africa. The empirical orthogonal functions performed on the standardized anomalies show four variability modes that include all West Africa with a focus on the Sahelian region, the eastern region including the south of Nigeria, the western part including Guinea, Sierra Leone, Liberia, and Guinea-Bissau, and finally a small region at the coast of Ghana and Togo. These four modes are influenced differently by the large-scale ocean surface and atmospheric conditions in the tropical Atlantic. The results are applicable in planning the risks associated with these climate hazards, particularly on water resource management and civil defense.

  20. Large-scale assessment of soil erosion in Africa: satellites help to jointly account for dynamic rainfall and vegetation cover

    Science.gov (United States)

    Vrieling, Anton; Hoedjes, Joost C. B.; van der Velde, Marijn

    2015-04-01

    Efforts to map and monitor soil erosion need to account for the erratic nature of the soil erosion process. Soil erosion by water occurs on sloped terrain when erosive rainfall and consequent surface runoff impact soils that are not well-protected by vegetation or other soil protective measures. Both rainfall erosivity and vegetation cover are highly variable through space and time. Due to data paucity and the relative ease of spatially overlaying geographical data layers into existing models like USLE (Universal Soil Loss Equation), many studies and mapping efforts merely use average annual values for erosivity and vegetation cover as input. We first show that rainfall erosivity can be estimated from satellite precipitation data. We obtained average annual erosivity estimates from 15 yr of 3-hourly TRMM Multi-satellite Precipitation Analysis (TMPA) data (1998-2012) using intensity-erosivity relationships. Our estimates showed a positive correlation (r = 0.84) with long-term annual erosivity values of 37 stations obtained from literature. Using these TMPA erosivity retrievals, we demonstrate the large interannual variability, with maximum annual erosivity often exceeding two to three times the mean value, especially in semi-arid areas. We then calculate erosivity at a 10-daily time-step and combine this with vegetation cover development for selected locations in Africa using NDVI - normalized difference vegetation index - time series from SPOT VEGETATION. Although we do not integrate the data at this point, the joint analysis of both variables stresses the need for joint accounting for erosivity and vegetation cover for large-scale erosion assessment and monitoring.

  1. Towards a real-time susceptibility assessment of rainfall-induced shallow landslides on a regional scale

    Directory of Open Access Journals (Sweden)

    L. Montrasio

    2011-07-01

    Full Text Available In the framework of landslide risk management, it appears relevant to assess, both in space and in time, the triggering of rainfall-induced shallow landslides, in order to prevent damages due to these kind of disasters. In this context, the use of real-time landslide early warning systems has been attracting more and more attention from the scientific community. This paper deals with the application, on a regional scale, of two physically-based stability models: SLIP (Shallow Landslides Instability Prediction and TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope-stability analysis. A back analysis of some recent case-histories of soil slips which occurred in the territory of the central Emilian Apennine, Emilia Romagna Region (Northern Italy is carried out and the main results are shown. The study area is described from geological and climatic viewpoints. The acquisition of geospatial information regarding the topography, the soil properties and the local landslide inventory is also explained.

    The paper outlines the main features of the SLIP model and the basic assumptions of TRIGRS. Particular attention is devoted to the discussion of the input data, which have been stored and managed through a Geographic Information System (GIS platform. Results of the SLIP model on a regional scale, over a one year time interval, are finally presented. The results predicted by the SLIP model are analysed both in terms of safety factor (Fs maps, corresponding to particular rainfall events, and in terms of time-varying percentage of unstable areas over the considered time interval. The paper compares observed landslide localizations with those predicted by the SLIP model. A further quantitative comparison between SLIP and TRIGRS, both applied to the most important event occurred during the analysed period, is presented. The limits of the SLIP model, mainly due to some restrictions of simplifying the physically

  2. On the consideration of scaling properties of extreme rainfall in Madrid (Spain) for developing a generalized intensity-duration-frequency equation and assessing probable maximum precipitation estimates

    Science.gov (United States)

    Casas-Castillo, M. Carmen; Rodríguez-Solà, Raúl; Navarro, Xavier; Russo, Beniamino; Lastra, Antonio; González, Paula; Redaño, Angel

    2016-11-01

    The fractal behavior of extreme rainfall intensities registered between 1940 and 2012 by the Retiro Observatory of Madrid (Spain) has been examined, and a simple scaling regime ranging from 25 min to 3 days of duration has been identified. Thus, an intensity-duration-frequency (IDF) master equation of the location has been constructed in terms of the simple scaling formulation. The scaling behavior of probable maximum precipitation (PMP) for durations between 5 min and 24 h has also been verified. For the statistical estimation of the PMP, an envelope curve of the frequency factor (k m ) based on a total of 10,194 station-years of annual maximum rainfall from 258 stations in Spain has been developed. This curve could be useful to estimate suitable values of PMP at any point of the Iberian Peninsula from basic statistical parameters (mean and standard deviation) of its rainfall series.

  3. Modelling runoff at the plot scale taking into account rainfall partitioning by vegetation: application to stemflow of banana (Musa spp. plant

    Directory of Open Access Journals (Sweden)

    Y.-M. Cabidoche

    2009-06-01

    Full Text Available Rainfall partitioning by vegetation modifies the intensity of rainwater reaching the ground, which affects runoff generation. Incident rainfall is intercepted by the plant canopy and then redistributed into throughfall and stemflow. Rainfall intensities at the soil surface are therefore not spatially uniform, generating local variations of runoff production that are disregarded in runoff models. The aim of this paper was to model runoff at the plot scale, accounting for rainfall partitioning by vegetation in the case of plants concentrating rainwater at the plant foot and promoting stemflow. We developed a lumped modelling approach, including a stemflow function that divided the plot into two compartments: one compartment including stemflow and the relative water pathways and one compartment for the rest of the plot. This stemflow function was coupled with a production function and a transfer function to simulate a flood hydrograph using the MHYDAS model. Calibrated parameters were a "stemflow coefficient", which compartmented the plot; the saturated hydraulic conductivity (Ks, which controls infiltration and runoff; and the two parameters of the diffusive wave equation. We tested our model on a banana plot of 3000 m2 on permeable Andosol (mean Ks=75 mm h−1 under tropical rainfalls, in Guadeloupe (FWI. Runoff simulations without and with the stemflow function were performed and compared to 18 flood events from 10 to 130 mm rainfall depth. Modelling results showed that the stemflow function improved the calibration of hydrographs according to the error criteria on volume and on peakflow and to the Nash and Sutcliffe coefficient. This was particularly the case for low flows observed during residual rainfall, for which the stemflow function allowed runoff to be simulated for rainfall intensities lower than the Ks measured at the soil surface. This approach also allowed us to take into account the experimental data, without needing to calibrate

  4. The influence of forest roads on runoff generation and soil erosion -- an assessment based on small scale rainfall simulation

    Science.gov (United States)

    Zemke, Julian J.

    2016-04-01

    In the course of forestry operations such as pruning and harvesting, a dense network of forest roads and skid trails has to be established. Due to mostly insufficient soil protective measures, the frequent overpassing of previously undisturbed topsoil with heavy forestry equipment on skid trails generates severe soil compaction. On persistent forest roads, the constructional layout and fortification also cause an increase of soil density. As a result of soil compaction, infiltration capacities are significantly reduced. Therefore, the affected areas tend to generate overland flow much quicker than undisturbed soil and differ considerably from the adjacent forest topsoil. As a consequence, decentral water retention on the watershed scale can be affected, if the road network is too dense and/or covers too much of the catchment's surface. Another consequence is the increase of soil erosion rates caused by erosive overland flows and the removal of vegetation cover on roads and skid trails. Again, the road and path surfaces differ significantly from adjacent forest soils where soil erosion rates normally tend to be equal or less than the soil renewal rates. To quantify the influence of forest roads and skid trails on runoff generation and soil erosion rates in a forested catchment area, rainfall simulations were carried out. A small scale rainfall simulator with a plot area of 0,64 m2 was used to simulate rainfall events with an intensity of 45 mm/h, a duration of 3 x 30 minutes and a kinetic energy of 4,6 J/m2*mm. Overland flow and eroded material were collected in a high temporal resolution of 1 minute. The sampled roads and skid trails were differentiated and categorized according to their constructional layout. Beyond that, rutted and unrutted road areas were distinguished. To obtain a benchmark for natural soil characteristics, undisturbed forest soils were also examined. The results show a significant influence of traffic induced soil compaction on the

  5. Developing a methodology for the national-scale assessment of rainfall-induced landslide hazard in a changing climate

    Science.gov (United States)

    Jurchescu, Marta; Micu, Dana; Sima, Mihaela; Bălteanu, Dan; Bojariu, Roxana; Dumitrescu, Alexandru; Dragotă, Carmen; Micu, Mihai; Senzaconi, Francisc

    2017-04-01

    Landslides together with earthquakes and floods represent the main natural hazards in Romania, causing major impacts to human activities. The RO-RISK (Disaster Risk Evaluation at a National Level) project is a flagship project aimed to strengthen risk prevention and management in Romania, by evaluating - among the specific risks in the country - landslide hazard and risk at a national level. Landslide hazard is defined as "the probability of occurrence within a specified period of time and within a given area of a landslide of a given magnitude" (Varnes 1984; Guzzetti et al. 1999). Nevertheless, most landslide ʿhazardʾ maps only consist in susceptibility (i.e. spatial probability) zonations without considering temporal or magnitude information on the hazard. This study proposes a methodology for the assessment of landslide hazard at the national scale on a scenario basis, while also considering changes in hazard patterns and levels under climate change conditions. A national landslide database consisting of more than 3,000 records has been analyzed against a meteorological observation dataset in order to assess the relationship between precipitation and landslides. Various extreme climate indices were computed in order to account for the different rainfall patterns able to prepare/trigger landslides (e.g. extreme levels of seasonal rainfall, 3-days rainfall or number of consecutive rainy days with different return periods). In order to derive national rainfall thresholds, i.e. valid for diverse climatic environments across the country, values in the parameter maps were rendered comparable by means of normalization with the mean annual precipitation and the rainy-day-normal. A hazard assessment builds on a frequency-magnitude relationship. In the current hazard scenario approach, frequency was kept constant for each single map, while the magnitude of the expected geomorphic event was modeled in relation to the distributed magnitude of the triggering factor. Given

  6. A scaling approach for the assessment of biomass changes and rainfall interception using cosmic-ray neutron sensing

    Science.gov (United States)

    Baroni, G.; Oswald, S. E.

    2015-06-01

    Cosmic-Ray neutron sensing (CRS) is a unique approach to measure soil moisture at field scale filling the gap of current methodologies. However, CRS signal is affected by all the hydrogen pools on the land surface and understanding their relative importance plays an important role for the application of the method e.g., validation of remote sensing products and data assimilation. In this study, a soil moisture scaling approach is proposed to estimate directly the correct CRS soil moisture based on the soil moisture profile measured at least in one position within the field. The approach has the advantage to avoid the need to introduce one correction for each hydrogen contribution and to estimate indirectly all the related time-varying hydrogen pools. Based on the data collected in three crop seasons, the scaling approach shows its ability to identify and to quantify the seasonal biomass water equivalent. Additionally, the analysis conducted at sub-daily time resolution is able to quantify the daily vertical redistribution of the water biomass and the rainfall interception, showing promising applications of the CRS method also for these types of measurements. Overall, the study underlines how not only soil moisture but all the specific hydrological processes in the soil-plant-atmosphere continuum should be considered for a proper evaluation of the CRS signal. For this scope, the scaling approach reveals to be a simple and pragmatic analysis that can be easily extended to other experimental sites.

  7. A Gaussian Random Field Approach for Merging Radar and Ground-Based Rainfall Data on Small Spatial and Temporal Scales

    Science.gov (United States)

    Krebsbach, K.; Friederichs, P.

    2014-12-01

    The generation of reliable precipitation products that explicitly account for spatial and temporal structures of precipitation events requires a combination of data with a variety of error structures and temporal resolutions. In-situ measurements are relatively accurate, but available only at sparse and irregularly distributed locations, whereas remote measurements cover areas but suffer from spatially and temporally inhomogeneous systematic errors. Besides gauge measurements are available on coarser spatial and temporal resolution in contrast to remote sensing measurements which are given on a fine spatial and temporal resolution. In our study we use precipitation rates from the composit of two X-band radars in Bonn and Jülich in Germany. Our aim is to formulate a statistical space-time model that aggregates and disaggregates precipitation rates from radar and gauge observations. We model a Gaussian random field as underlying process, where we face the task of dealing with a large non-Gaussian data set. To start the analysis of the unadjusted radar rainfall rates, we follow the work of D. Allcroft and C. Glasbey (2003) and transform the data to a truncated Gaussian distribution. The advantage of the latent variable approach is that it takes account of the occurence of rainfall and the intensity using a single process. We proceed by estimating the empirical correlation from these transformed values with maximum likelihood methods and fit a parametric correlation function that gives rise to a Gaussian random field. Since the transformation gives censored values to dry locations, we simulate values for this area that lie below some threshold and extend the Gaussian field to the whole domain. In order to merge gauge and radar data for precipitation, we first aggregate the data to a scale on which the comparison is reasonable and then disaggregate again back to smaller desirable scales. The disaggregation step consists of calculating the difference between radar

  8. Probabilistic Risk Assessment in Medium Scale for Rainfall-Induced Earthflows: Catakli Catchment Area (Cayeli, Rize, Turkey

    Directory of Open Access Journals (Sweden)

    H. A. Nefeslioglu

    2011-01-01

    Full Text Available The aim of the present study is to introduce a probabilistic approach to determine the components of the risk evaluation for rainfall-induced earthflows in medium scale. The Catakli catchment area (Cayeli, Rize, Turkey was selected as the application site of this study. The investigations were performed in four different stages: (i evaluation of the conditioning factors, (ii calculation of the probability of spatial occurrence, (iii calculation of the probability of the temporal occurrence, and (iv evaluation of the consequent risk. For the purpose, some basic concepts such as “Risk Cube”, “Risk Plane”, and “Risk Vector” were defined. Additionally, in order to assign the vulnerability to the terrain units being studied in medium scale, a new more robust and more objective equation was proposed. As a result, considering the concrete type of roads in the catchment area, the economic risks were estimated as 3.6×106€—in case the failures occur on the terrain units including element at risk, and 12.3×106€—in case the risks arise from surrounding terrain units. The risk assessments performed in medium scale considering the technique proposed in the present study will supply substantial economic contributions to the mitigation planning studies in the region.

  9. Centennial time scale impacts using stochastically generated rainfall - assessing sediment output from a post-mining catchment

    Science.gov (United States)

    Hancock, G. R.; Verdon-Kidd, D.; Lowry, J.

    2016-12-01

    Rainfall intensity and temporal distribution have a major influence on soil erosion, sediment delivery and landscape evolution. Long-term reliable rainfall data is needed is to understand soil erosion rates and landscape evolution. For many parts of the world rainfall data may not exist locally or may be of insufficient quality (e.g. incomplete or only cover a short time period) and therefore has to be inferred from nearby sites. Further, there is also the question of whether the current climate (and rainfall pattern) is representative of longer term trends, particular into the future under a warming climate scenario. Using reliable rainfall data computer based landscape evolution models can provide insight into both erosion rates and process (i.e. sheetwash, rill, gully erosion). Of particular interest here are mining landscapes. Mining disturbs large areas to access minerals and upon completion of the resource extraction the disturbed area is re-engineered. The landscape once created will remain part of the surrounding landscape system for the foreseeable future. Therefore, understanding the hydrological and erosional behavior of such landscapes is vital so that any issues design can be corrected. It is also vital that these landscapes be evaluated not just for current climate but for how different rainfall patterns may affect erosion and landscape evolution. Here we assess a proposed post-mining landform using existing rainfall data from established weather stations and secondly create stochastically generated rainfall time series based on this rainfall data. The rainfall data is then used in a landscape evolution and sediment transport model. It was found that each rainfall data set produces differences in the position of rills and gullies. Each rainfall scenario also produces a unique pattern of sediment output that suggests non-linear processes. Therefore each rainfall data set produces unique patterns of erosion, deposition and catchment sediment output

  10. A Cornea Substitute Derived from Fish Scale: 6-Month Followup on Rabbit Model

    OpenAIRE

    Fei Yuan; Liyan Wang; Chien-Chen Lin; Cheng-Hung Chou; Lei Li

    2014-01-01

    A fish scale-derived cornea substitute (Biocornea) is proposed as an alternative for human donor corneal tissue. We adopt a regenerative medicine approach to design a primary alternative to the use of fish scale for restoring sight by corneal replacement. Biocornea with corneal multilayer arrangement collagen was implanted to rabbits by pocket implantation. Our study demonstrated the safety and detailed morphologic and physiologic results from the 6 months of followup of rabbit model. In the ...

  11. Multi-scale cyclone activity in the Changjiang River-Huaihe River valleys during spring and its relationship with rainfall anomalies

    Science.gov (United States)

    Qin, Yujing; Lu, Chuhan; Li, Liping

    2017-02-01

    Based on the recognition framework of the outermost closed contours of cyclones, an automated identification algorithm capable of identifying the multi-scale cyclones that occur during spring in the Changjiang River-Huaihe River valleys (CHV) were developed. We studied the characteristics of the multi-scale cyclone activity that affects CHV and its relationship with rainfall during spring since 1979. The results indicated that the automated identification algorithm for cyclones proposed in this paper could intuitively identify multi-scale cyclones that affect CHV. The algorithm allows for effectively describing the shape and coverage area of the closed contours around the periphery of cyclones. We found that, compared to the meso- and sub-synoptic scale cyclone activities, the synoptic-scale cyclone activity showed more intimate correlation with the overall activity intensity of multi-scale CHV cyclones during spring. However, the frequency of occurrence of sub-synoptic scale cyclones was the highest, and their effect on changes in CHV cyclone activity could not be ignored. Based on the area of impact and the depth of the cyclones, the sub-synoptic scale, synoptic scale and comprehensive cyclone intensity indices were further defined, which showed a positive correlation with rainfall in CHV during spring. Additionally, the comprehensive cyclone intensity index was a good indicator of strong rainfall events.

  12. Large-scale Flood Simulation with Rainfall-Runoff-Inundation Model in the Chao Phraya River Basin

    Science.gov (United States)

    Sayama, Takahiro; Tatebe, Yuya; Tanaka, Shigenobu

    2013-04-01

    A large amount of rainfall during the 2011 monsoonal season caused an unprecedented flood disaster in the Chao Phraya River basin in Thailand. When a large-scale flood occurs, it is very important to take appropriate emergency measures by holistically understanding the characteristics of the flooding based on available information and by predicting its possible development. This paper proposes quick response-type flood simulation that can be conducted during a severe flooding event. The hydrologic simulation model used in this study is designed to simulate river discharges and flood inundation simultaneously for an entire river basin with satellite based rainfall and topographic information. The model is based on two-dimensional diffusive wave equations for rainfall-runoff and inundation calculations. The model takes into account the effects of lateral subsurface flow and vertical infiltration flow since these two types of flow are also important processes. This paper presents prediction results obtained in mid-October 2011, when the flooding in Thailand was approaching to its peak. Our scientific question is how well we can predict the possible development of a large-scale flooding event with limited information and how much we can improve the prediction with more local information. In comparison with a satellite based flood inundation map, the study found that the quick response-type simulation (Lv1) was capable of capturing the peak flood inundation extent reasonably as compared to the estimation based on satellite remote sensing. Our interpretation of the prediction was that the flooding might continue even until the end of November, which was also positively confirmed to some extent by the actual flooding status in late November. Nevertheless, the Lv1 simulation generally overestimated the peak water level. To address this overestimation, the input data was updated with additional local information (Lv2). Consequently, the simulation accuracy improved in the

  13. Chance-constrained overland flow modeling for improving conceptual distributed hydrologic simulations based on scaling representation of sub-daily rainfall variability.

    Science.gov (United States)

    Han, Jing-Cheng; Huang, Guohe; Huang, Yuefei; Zhang, Hua; Li, Zhong; Chen, Qiuwen

    2015-08-15

    Lack of hydrologic process representation at the short time-scale would lead to inadequate simulations in distributed hydrological modeling. Especially for complex mountainous watersheds, surface runoff simulations are significantly affected by the overland flow generation, which is closely related to the rainfall characteristics at a sub-time step. In this paper, the sub-daily variability of rainfall intensity was considered using a probability distribution, and a chance-constrained overland flow modeling approach was proposed to capture the generation of overland flow within conceptual distributed hydrologic simulations. The integrated modeling procedures were further demonstrated through a watershed of China Three Gorges Reservoir area, leading to an improved SLURP-TGR hydrologic model based on SLURP. Combined with rainfall thresholds determined to distinguish various magnitudes of daily rainfall totals, three levels of significance were simultaneously employed to examine the hydrologic-response simulation. Results showed that SLURP-TGR could enhance the model performance, and the deviation of runoff simulations was effectively controlled. However, rainfall thresholds were so crucial for reflecting the scaling effect of rainfall intensity that optimal levels of significance and rainfall threshold were 0.05 and 10 mm, respectively. As for the Xiangxi River watershed, the main runoff contribution came from interflow of the fast store. Although slight differences of overland flow simulations between SLURP and SLURP-TGR were derived, SLURP-TGR was found to help improve the simulation of peak flows, and would improve the overall modeling efficiency through adjusting runoff component simulations. Consequently, the developed modeling approach favors efficient representation of hydrological processes and would be expected to have a potential for wide applications.

  14. Functional maintenance and structural flexibility of microbial communities perturbed by simulated intense rainfall in a pilot-scale membrane bioreactor.

    Science.gov (United States)

    Sato, Yuya; Hori, Tomoyuki; Navarro, Ronald R; Habe, Hiroshi; Ogata, Atsushi

    2016-07-01

    Intense rainfall is one of the most serious and common natural events, causing the excessive inflow of rainwater into wastewater treatment plants. However, little is known about the impacts of rainwater dilution on the structure and function of the sludge microorganisms. Here, high-throughput sequencing of 16S ribosomal RNA (rRNA) genes was implemented to describe the microbial community dynamics during the simulated intense rainfall situation (event i) in which approximately 45 % of the sludge biomass was artificially overflowed by massive water supply in a pilot-scale membrane bioreactor. Thereafter, we investigated the functional and structural responses of the perturbed microbial communities to subsequent conditional changes, i.e., an increase in organic loading rate from 225 to 450 mg chemical oxygen demand (COD) l(-1) day(-1) (event ii) and an addition of a microbiota activator (event iii). Due to the event i, the COD removal declined to 78.2 %. This deterioration coincided with the decreased microbial diversity and the proliferation of the oligotrophic Aquabacterium sp. During the succeeding events ii and iii, the sludge biomass increased and the COD removal became higher (86.5-97.4 %). With the apparent recovery of the reactor performance, microbial communities became diversified and the compositions dynamically changed. Notably, various bacterial micropredators were highly enriched under the successive conditions, most likely being involved in the flexible reorganization of microbial communities. These results indicate that the activated sludge harbored functionally redundant microorganisms that were able to thrive and proliferate along with the conditional changes, thereby contributing to the functional maintenance of the membrane bioreactor.

  15. The Impact of Model Resolution and Configuration on Rainfall Characteristics in a Multi-scale Modeling Framework (MMF)

    Science.gov (United States)

    Chern, J. D.; Tao, W. K.

    2016-12-01

    The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has become a promising approach for climate modeling. Despite the overall success of MMFs in simulating the MJO, diurnal variability, and mesoscale convective systems, phenomena difficult for traditional GCMs to simulate well, systematic model deficits in MMFs do exist. One of the major biases for all MMFs is the overestimation of surface rainfall over the West Pacific, South Pacific Convergence Zone (SPCZ), and Indian Ocean. Many hypotheses have been proposed such as the use of cyclic lateral boundary condition in embedded 2D CRMs, the orientation of the 2D CRM and momentum transport, and the nonlinear feedback of wind and surface evaporation, but the tropical positive precipitation biases still persist in all MMFs. In this study, the Goddard MMFs and the stand-alone Goddard Cumulus Ensemble (GCE, a CRM) are used to study the impacts of model resolution and model domain size on the surface precipitation and rainfall characteristics. A series of GCE and MMF simulations have been carried out with different model configuration. The changes of cloud structure, occurrence, and properties such as cloud types, updraft and downdraft, latent heating profile, and cold pool strength in both stand-alone CRMs and the ones embedded inside the MMF are examined in details. We also focus on the multi-scale interaction and feedback in the MMF to understand why the tropica positive precipitation bias and root-mean-square error decrease with decreasing (increasing) GCE grid size (domain).

  16. Chance-constrained overland flow modeling for improving conceptual distributed hydrologic simulations based on scaling representation of sub-daily rainfall variability

    Energy Technology Data Exchange (ETDEWEB)

    Han, Jing-Cheng [State Key Laboratory of Hydroscience & Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084 (China); Huang, Guohe, E-mail: huang@iseis.org [Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Huang, Yuefei [State Key Laboratory of Hydroscience & Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084 (China); Zhang, Hua [College of Science and Engineering, Texas A& M University — Corpus Christi, Corpus Christi, TX 78412-5797 (United States); Li, Zhong [Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Chen, Qiuwen [Center for Eco-Environmental Research, Nanjing Hydraulics Research Institute, Nanjing 210029 (China)

    2015-08-15

    Lack of hydrologic process representation at the short time-scale would lead to inadequate simulations in distributed hydrological modeling. Especially for complex mountainous watersheds, surface runoff simulations are significantly affected by the overland flow generation, which is closely related to the rainfall characteristics at a sub-time step. In this paper, the sub-daily variability of rainfall intensity was considered using a probability distribution, and a chance-constrained overland flow modeling approach was proposed to capture the generation of overland flow within conceptual distributed hydrologic simulations. The integrated modeling procedures were further demonstrated through a watershed of China Three Gorges Reservoir area, leading to an improved SLURP-TGR hydrologic model based on SLURP. Combined with rainfall thresholds determined to distinguish various magnitudes of daily rainfall totals, three levels of significance were simultaneously employed to examine the hydrologic-response simulation. Results showed that SLURP-TGR could enhance the model performance, and the deviation of runoff simulations was effectively controlled. However, rainfall thresholds were so crucial for reflecting the scaling effect of rainfall intensity that optimal levels of significance and rainfall threshold were 0.05 and 10 mm, respectively. As for the Xiangxi River watershed, the main runoff contribution came from interflow of the fast store. Although slight differences of overland flow simulations between SLURP and SLURP-TGR were derived, SLURP-TGR was found to help improve the simulation of peak flows, and would improve the overall modeling efficiency through adjusting runoff component simulations. Consequently, the developed modeling approach favors efficient representation of hydrological processes and would be expected to have a potential for wide applications. - Highlights: • We develop an improved hydrologic model considering the scaling effect of rainfall. • A

  17. 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).

  18. A Cornea Substitute Derived from Fish Scale: 6-Month Followup on Rabbit Model

    Directory of Open Access Journals (Sweden)

    Fei Yuan

    2014-01-01

    Full Text Available A fish scale-derived cornea substitute (Biocornea is proposed as an alternative for human donor corneal tissue. We adopt a regenerative medicine approach to design a primary alternative to the use of fish scale for restoring sight by corneal replacement. Biocornea with corneal multilayer arrangement collagen was implanted to rabbits by pocket implantation. Our study demonstrated the safety and detailed morphologic and physiologic results from the 6 months of followup of rabbit model. In the peripheral Biocornea, the collagen fibrils were arranged in reticular fashion. Slit lamp examination showed that haze and an ulcer were not observed in all groups at 3 months postoperatively while all corneas with Biocornea were clear at both 3 months and 6 months postoperatively. The interface of Biocornea and stromal tissue were filled successfully and without observable immune cells at postoperative day 180. Moreover, the Biocornea was not dissolved and degenerated but remained transparent and showed no apparent fragmentation. Our study demonstrated that the Biocornea derived from fish scale as a good substitute had high biocompatibility and support function after a long-term evaluation. This revealed that the new approach of using Biocornea may yield an ideal artificial cornea substitute for long-term inlay placement.

  19. 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

  20. On the spatial coherence of rainfall over the Saloum delta (Senegal from seasonal to decadal time scales

    Directory of Open Access Journals (Sweden)

    Malick eWADE

    2015-06-01

    Full Text Available A paleoreconstruction of the length and intensity of the rainy season over western Africa has been recently proposed, using analysis of fossil mollusk shells from the Saloum delta region, in western Senegal. In order to evaluate the significance of local long-term reconstructions of precipitations from paleoclimate proxies, and to better characterize the spatial homogeneity of rainfall distribution in northern Africa, we analyze here the spatial representativeness of rainfall in this region, from seasonal to decadal timescales. The spatial coherence of winter episodic rainfall events is relatively low and limited to surrounding countries. On the other hand, the summer rainfall, associated with the West African Monsoon, shows extended spatial coherence. At seasonal timescales, local rainfall over the Saloum is significantly correlated with rainfall in the whole western half of the Sahel. At interannual and longer timescales, the spatial coherence extends as far as the Red Sea, covering the full Sahel region. This spatial coherence is mainly associated to the zonal extension of the Inter Tropical Convergence Zone. Coherently, summer rainfalls appear to be driven by SST anomalies mainly in the Pacific, the Indian Ocean, the Mediterranean basin, and the North Pacific. A more detailed analysis shows that consistency of the spatial rainfall coherence is reduced during the onset season of the West African Monsoon.

  1. Short period forecasting of catchment-scale precipitation. Part II: a water-balance storm model for short-term rainfall and flood forecasting

    Directory of Open Access Journals (Sweden)

    V. A. Bell

    2000-01-01

    Full Text Available A simple two-dimensional rainfall model, based on advection and conservation of mass in a vertical cloud column, is investigated for use in short-term rainfall and flood forecasting at the catchment scale under UK conditions. The model is capable of assimilating weather radar, satellite infra-red and surface weather observations, together with forecasts from a mesoscale numerical weather prediction model, to obtain frequently updated forecasts of rainfall fields. Such data assimilation helps compensate for the simplified model dynamics and, taken together, provides a practical real-time forecasting scheme for catchment scale applications. Various ways are explored for using information from a numerical weather prediction model (16.8 km grid within the higher resolution model (5 km grid. A number of model variants is considered, ranging from simple persistence and advection methods used as a baseline, to different forms of the dynamic rainfall model. Model performance is assessed using data from the Wardon Hill radar in Dorset for two convective events, on 10 June 1993 and 16 July 1995, when thunderstorms occurred over southern Britain. The results show that (i a simple advection-type forecast may be improved upon by using multiscan radar data in place of data from the lowest scan, and (ii advected, steady-state predictions from the dynamic model, using 'inferred updraughts', provides the best performance overall. Updraught velocity is inferred at the forecast origin from the last two radar fields, using the mass-balance equation and associated data and is held constant over the forecast period. This inference model proves superior to the buoyancy parameterisation of updraught employed in the original formulation. A selection of the different rainfall forecasts is used as input to a catchment flow forecasting model, the IH PDM (Probability Distributed Moisture model, to assess their effect on flow forecast accuracy for the 135 km2 Brue catchment

  2. Climatological studies on precipitation features and large-scale atmospheric fields on the heavy rainfall days in the eastern part of Japan from the Baiu to midsummer season

    Science.gov (United States)

    Matsumoto, Kengo; Kato, Kuranoshin; Otani, Kazuo

    2017-04-01

    In East Asia the significant subtropical frontal zone called the Meiyu (in China) / Baiu (in Japan) appears in early summer (just before the midsummer) and the huge rainfall is brought due to the frequent appearance of the "heavy rainfall days" (referred to as HRDs hereafter) mainly in that western part. On the other hand, large-scale fields around the front in eastern Japan is rather different from that in western Japan but the total precipitation in the eastern Japan is still considerable compared to that in the other midlatitude regions. Thus, it is also interesting to examine how the rainfall characteristics and large-scale atmospheric fields on HRDs (with more than 50 mm/day) in the eastern Japan in the mature stage of the Baiu season (16 June 15 July), together with those in midsummer (1 31 August). Based on such scientific background, further analyses were performed in this study mainly with the daily and the hourly precipitation data and the NCEP/NCAR re-analysis date from 1971 to 2010, succeeding to our previous results (e.g., EGU2015). As reported at EGU2014 and 2015, about half of HRDs at Tokyo (eastern Japan) were related to the typhoon even in the Baiu season. Interestingly, half of HRDs were characterized by the large contribution of moderate rain less than 10 mm/h. While, the precipitation on HRDs at Tokyo in midsummer was mainly brought by the intense rainfall with more than 10 mm/h, in association with the typhoons. In the present study, we examined the composite meridional structure of the rainfall area along 140E. In the pattern only associated with a typhoons in the Baiu season (Pattern A), the heavy rainfall area (more than 50 mm/day) with large contribution of the intense rain (stronger than 10 mm/h) showed rather wide meridional extension. The area was characterized by the duration of the intermittent enhancement of the rainfall. In the pattern associated with a typhoon and a front (Pattern B), while the contribution ratio of the rainfall

  3. Global-Scale Associations of Vegetation Phenology with Rainfall and Temperature at a High Spatio-Temporal Resolution

    Directory of Open Access Journals (Sweden)

    Nicholas Clinton

    2014-08-01

    Full Text Available Phenology response to climatic variables is a vital indicator for understanding changes in biosphere processes as related to possible climate change. We investigated global phenology relationships to precipitation and land surface temperature (LST at high spatial and temporal resolution for calendar years 2008–2011. We used cross-correlation between MODIS Enhanced Vegetation Index (EVI, MODIS LST and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN gridded rainfall to map phenology relationships at 1-km spatial resolution and weekly temporal resolution. We show these data to be rich in spatiotemporal information, illustrating distinct phenology patterns as a result of complex overlapping gradients of climate, ecosystem and land use/land cover. The data are consistent with broad-scale, coarse-resolution modeled ecosystem limitations to moisture, temperature and irradiance. We suggest that high-resolution phenology data are useful as both an input and complement to land use/land cover classifiers and for understanding climate change vulnerability in natural and anthropogenic landscapes.

  4. Correcting Errors in Catchment-Scale Satellite Rainfall Accumulation Using Microwave Satellite Soil Moisture Products

    Science.gov (United States)

    Ryu, D.; Crow, W. T.

    2011-12-01

    Streamflow forecasting in the poorly gauged or ungauged catchments is very difficult mainly due to the absence of the input forcing data for forecasting models. This challenge poses a threat to human safety and industry in the areas where proper warning system is not provided. Currently, a number of studies are in progress to calibrate streamflow models without relying on ground observations as an effort to construct a streamflow forecasting systems in the ungauged catchments. Also, recent advances in satellite altimetry and innovative application of the optical has enabled mapping streamflow rate and flood extent in the remote areas. In addition, remotely sensed hydrological variables such as the real-time satellite precipitation data, microwave soil moisture retrievals, and surface thermal infrared observations have the great potential to be used as a direct input or signature information to run the forecasting models. In this work, we evaluate a real-time satellite precipitation product, TRMM 3B42RT, and correct errors of the product using the microwave satellite soil moisture products over 240 catchments in Australia. The error correction is made by analyzing the difference between output soil moisture of a simple model forced by the TRMM product and the satellite retrievals of soil moisture. The real-time satellite precipitation products before and after the error correction are compared with the daily gauge-interpolated precipitation data produced by the Australian Bureau of Meteorology. The error correction improves overall accuracy of the catchment-scale satellite precipitation, especially the root mean squared error (RMSE), correlation, and the false alarm ratio (FAR), however, only a marginal improvement is observed in the probability of detection (POD). It is shown that the efficiency of the error correction is affected by the surface vegetation density and the annual precipitation of the catchments.

  5. 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.

  6. 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.

  7. Modelling runoff at the plot scale taking into account rainfall partitioning by vegetation: application to stemflow of banana (Musa spp. plant

    Directory of Open Access Journals (Sweden)

    Y.-M. Cabidoche

    2009-11-01

    Full Text Available Rainfall partitioning by vegetation modifies the intensity of rainwater reaching the ground, which affects runoff generation. Incident rainfall is intercepted by the plant canopy and then redistributed into throughfall and stemflow. Rainfall intensities at the soil surface are therefore not spatially uniform, generating local variations of runoff production that are disregarded in runoff models. The aim of this paper was to model runoff at the plot scale, accounting for rainfall partitioning by vegetation in the case of plants concentrating rainwater at the plant foot and promoting stemflow. We developed a lumped modelling approach, including a stemflow function that divided the plot into two compartments: one compartment including stemflow and the related water pathways and one compartment for the rest of the plot. This stemflow function was coupled with a production function and a transfer function to simulate a flood hydrograph using the MHYDAS model. Calibrated parameters were a "stemflow coefficient", which compartmented the plot; the saturated hydraulic conductivity (Ks, which controls infiltration and runoff; and the two parameters of the diffusive wave equation. We tested our model on a banana plot of 3000 m2 on permeable Andosol (mean Ks=75 mm h−1 under tropical rainfalls, in Guadeloupe (FWI. Runoff simulations without and with the stemflow function were performed and compared to 18 flood events from 10 to 140 rainfall mm depth. Modelling results showed that the stemflow function improved the calibration of hydrographs according to the error criteria on volume and on peakflow, to the Nash and Sutcliffe coefficient, and to the root mean square error. This was particularly the case for low flows observed during residual rainfall, for which the stemflow function allowed runoff to be simulated for rainfall intensities lower than the Ks measured at the soil surface. This approach also allowed us to take into account the experimental data

  8. Modelling runoff at the plot scale taking into account rainfall partitioning by vegetation: application to stemflow of banana (Musa spp.) plant

    Science.gov (United States)

    Charlier, J.-B.; Moussa, R.; Cattan, P.; Cabidoche, Y.-M.; Voltz, M.

    2009-11-01

    Rainfall partitioning by vegetation modifies the intensity of rainwater reaching the ground, which affects runoff generation. Incident rainfall is intercepted by the plant canopy and then redistributed into throughfall and stemflow. Rainfall intensities at the soil surface are therefore not spatially uniform, generating local variations of runoff production that are disregarded in runoff models. The aim of this paper was to model runoff at the plot scale, accounting for rainfall partitioning by vegetation in the case of plants concentrating rainwater at the plant foot and promoting stemflow. We developed a lumped modelling approach, including a stemflow function that divided the plot into two compartments: one compartment including stemflow and the related water pathways and one compartment for the rest of the plot. This stemflow function was coupled with a production function and a transfer function to simulate a flood hydrograph using the MHYDAS model. Calibrated parameters were a "stemflow coefficient", which compartmented the plot; the saturated hydraulic conductivity (Ks), which controls infiltration and runoff; and the two parameters of the diffusive wave equation. We tested our model on a banana plot of 3000 m2 on permeable Andosol (mean Ks=75 mm h-1) under tropical rainfalls, in Guadeloupe (FWI). Runoff simulations without and with the stemflow function were performed and compared to 18 flood events from 10 to 140 rainfall mm depth. Modelling results showed that the stemflow function improved the calibration of hydrographs according to the error criteria on volume and on peakflow, to the Nash and Sutcliffe coefficient, and to the root mean square error. This was particularly the case for low flows observed during residual rainfall, for which the stemflow function allowed runoff to be simulated for rainfall intensities lower than the Ks measured at the soil surface. This approach also allowed us to take into account the experimental data, without needing to

  9. 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.

  10. 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.

  11. 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

  12. Variational Assimilation of GPS Precipitable Water Vapor and Hourly Rainfall Observations for a Meso-β Scale Heavy Precipitation Event During the 2002 Mei-Yu Season

    Institute of Scientific and Technical Information of China (English)

    ZHANG Meng; NI Yunqi; ZHANG Fuqing

    2007-01-01

    Recent advances in Global Positioning System (GPS) remote sensing technology allow for a direct estimation of the precipitable water vapor (PWV) from delayed signals transmitted by GPS satellites, which can be assimilated into numerical models with four-dimensional variational (4DVAR) data assimilation. A mesoscale model and its 4DVAR system are used to access the impacts of assimilating GPS-PWV and hourly rainfall observations on the short-range prediction of a heavy rainfall event on 20 June 2002. The heavy precipitation was induced by a sequence of meso-β-scale convective systems (MCS) along the mei-yu front in China.The experiments with GPS-PWV assimilation successfully simulated the evolution of the observed MCS cluster and also eliminated the erroneous rainfall systems found in the experiment without 4DVAR assimilation. Experiments with hourly rainfall assimilation performed similarly both on the prediction of MCS initiation and the elimination of erroneous systems, however the MCS dissipated much sooner than it did in observations. It is found that the assimilation-induced moisture perturbation and mesoscale low-level jet are helpful for the MCS generation and development. It is also discovered that spurious gravity waves may post serious limitations for the current 4DVAR algorithm, which would degrade the assimilation efficiency, especially for rainfall data. Sensitivity experiments with different observations, assimilation windows and observation weightings suggest that assimilating GPS-PWV can be quite effective, even with the assimilation window as short as 1 h. On the other hand, assimilating rainfall observations requires extreme cautions on the selection of observation weightings and the control of spurious gravity waves.

  13. Different methods for spatial interpolation of rainfall data for operational hydrology and hydrological modeling at watershed scale: a review

    Directory of Open Access Journals (Sweden)

    Ly, S.

    2013-01-01

    Full Text Available Watershed management and hydrological modeling require data related to the very important matter of precipitation, often measured using raingages or weather stations. Hydrological models often require a preliminary spatial interpolation as part of the modeling process. The success of spatial interpolation varies according to the type of model chosen, its mode of geographical management and the resolution used. The quality of a result is determined by the quality of the continuous spatial rainfall, which ensues from the interpolation method used. The objective of this article is to review the existing methods for interpolation of rainfall data that are usually required in hydrological modeling. We review the basis for the application of certain common methods and geostatistical approaches used in interpolation of rainfall. Previous studies have highlighted the need for new research to investigate ways of improving the quality of rainfall data and ultimately, the quality of hydrological modeling.

  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. 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.

  16. Multi-scale field investigation of water flow pathways and residence times in mountainous catchments during monsoon rainfall

    Science.gov (United States)

    Troch, P. A.; Lyon, S. W.; Desilets, S.

    2007-05-01

    The "sky islands" of Arizona and New Mexico in the southwestern United States form a unique complex of about 27 mountain ranges whose ecosystems support many perennial and ephemeral streams in an arid climate. Among these sky islands are the Santa Catalina Mountains near Tucson, AZ, with a peak elevation of 9157 ft at Mt. Lemmon. Sabino Canyon Creek is the main stream which runs on the south face of the mountain range. It usually flows from July through April with an average daily flow of approximately 0.28 m3/s (10 cfs). However, flash floods are common both during summer as a result of intense monsoon rains and during spring because of rapid snowmelt. During these events, flow increases drastically, reaching peak flows up to 480 m3/s (15,984 cfs, July 2006). Characterizing water flow pathways and residence times in these complex catchments is important for improving flash flood warning systems, estimating mountain front recharge, managing forest and wild fires, and understanding ecosystem functions. In the summer of 2006, we set up an extensive hydrometrical and hydro- chemical monitoring network in Sabino Canyon Creek, comprising 40 tipping bucket rain gauges (two of which were equipped to automatically collect rainwater samples), 5 automatic surface water level stations (three of which were equipped with auto samplers), and 8 manual soil lysimeters. In addition, several rain and stream water grab samples were collected manually during intensive rain events. Water samples are analyzed for major ions and liquid water isotopic concentration (2H and 18O) in rain, soil, ground and surface water. The data allows for a detailed reconstruction of water flow pathways and residence times at 3 different catchment scales (2 km2, 8 km2, and 91 km2) during the recorded flow events, including the highest monsoon rainfall-runoff event ever recorded in these mountains.

  17. A Study of a Heavy Rainfall Event in the Central Part of Korea in a Situation of a Synoptic Scale Ridge over the Korean Peninsula

    Science.gov (United States)

    Kim, Ah-hyun; Lee, Yunkyu

    2016-04-01

    Observational and numerical studies have been carried out to explain the heavy rainfall event over Seoul metropolitan area and Gyeonggi province on June 29 2011. The characteristic features for this heavy rainfall event is convergence produced by the association of low-level mesoscale trough above the Yellow sea in a situation of a synoptic scale ridge over the Korean peninsula. Maximum of 234mm rainfall was recorded in one day, and most of the rainfall occurred in 12 hours. The major cause of this event is the formation of convergence zone. Abrupt wind direction change created by south-westerly low-level jet at the windward side and northerly or south-easterly wind caused by synoptic scale ridge at the lee side of the rainfall region produce horizontal wind shear in the middle of the mesoscale pressure trough. Also, wind speed difference at the exit of the low-level jet is another cause of the convergence. The low-level jet forms around the East China Sea. Land-sea heat capacity difference causes the increase of meridional temperature gradient around the coast line of the East China Sea during the daytime and induces the meridional pressure gradient increase. Therefore, low-level jet strengthens at the area where the meridional pressure gradient is strong. This low-level jet moves along the western flank of Western Pacific Subtropical High (WPSH) and impacts on Korean Peninsula. Formation of the synoptic scale ridge seems to be associated with WPSH and the strong low pressure system at the northeast of Korean Peninsula. The strong cyclone suppresses the northern flank of the WPSH, and relatively high pressure forms at the windward and lee side of the pressure low. Orographic effect plays an important role in intensifying pressure ridge over the Korean Peninsula. Numerical studies have been carried out to understand the effect of the condensation latent heat, land-sea heat capacity difference, and the orography by using WRF model. Topography sensitivity simulation

  18. Assessment of small-scale variability of rainfall and multi-satellite precipitation estimates using measurements from a dense rain gauge network in Southeast India

    Science.gov (United States)

    Sunilkumar, K.; Narayana Rao, T.; Satheeshkumar, S.

    2016-05-01

    This paper describes the establishment of a dense rain gauge network and small-scale variability in rain events (both in space and time) over a complex hilly terrain in Southeast India. Three years of high-resolution gauge measurements are used to validate 3-hourly rainfall and sub-daily variations of four widely used multi-satellite precipitation estimates (MPEs). The network, established as part of the Megha-Tropiques validation program, consists of 36 rain gauges arranged in a near-square grid area of 50 km × 50 km with an intergauge distance of 6-12 km. Morphological features of rainfall in two principal rainy seasons (southwest monsoon, SWM, and northeast monsoon, NEM) show marked differences. The NEM rainfall exhibits significant spatial variability and most of the rainfall is associated with large-scale/long-lived systems (during wet spells), whereas the contribution from small-scale/short-lived systems is considerable during the SWM. Rain events with longer duration and copious rainfall are seen mostly in the western quadrants (a quadrant is 1/4 of the study region) in the SWM and northern quadrants in the NEM, indicating complex spatial variability within the study region. The diurnal cycle also exhibits large spatial and seasonal variability with larger diurnal amplitudes at all the gauge locations (except for 1) during the SWM and smaller and insignificant diurnal amplitudes at many gauge locations during the NEM. On average, the diurnal amplitudes are a factor of 2 larger in the SWM than in the NEM. The 24 h harmonic explains about 70 % of total variance in the SWM and only ˜ 30 % in the NEM. During the SWM, the rainfall peak is observed between 20:00 and 02:00 IST (Indian Standard Time) and is attributed to the propagating systems from the west coast during active monsoon spells. Correlograms with different temporal integrations of rainfall data (1, 3, 12, 24 h) show an increase in the spatial correlation with temporal integration, but the

  19. Linking the Response of Annual Grasslands to Warming and Altered Rainfall Across Scales of Gene Expression, Species, and Ecosystem

    Science.gov (United States)

    Torn, M. S.; Bernard, S. M.; Castanha, C.; Fischer, M. L.; Hopkins, F. M.; Placella, S. A.; St. Clair, S. B.; Salve, R.; Sudderth, E.; Herman, D.; Ackerly, D.; Firestone, M. K.

    2007-12-01

    Climate change can influence terrestrial ecosystems at multiple biological levels: gene expression, species, and ecosystem. We are studying California grassland mesocosms with seven annual species (five grasses, two forbs) that were started in 2005. In the 2006-2007 growing season, they were exposed to three rainfall treatments (297, 552, and 867 mm y-1) and soil and air temperature (ambient and elevated +4oC) in replicated greenhouses. This presentation will combine plant and ecosystem level results with transcript level analyses associated with key enzymes, such as rubisco and glutamine synthetase (GS). Because rainfall is the dominant climate variable for most processes in this Mediterranean ecosystem, the effect of warming was strongly mediated by rainfall. In fact, we saw significant interactions between temperature and rainfall treatments at all three biological levels. For example, at the ecosystem level, warming led to a decrease in aboveground and total NPP under low rainfall, and an increase under high rainfall. For the dominant species, Avena barbata, warming had no effect under high rainfall, but suppressed Avena NPP in low rainfall. At the same time, warmer, wetter conditions accelerated Avena flowering by almost 15 days. This shift in phenology was presaged by observations at the transcript level. Specifically, in the high temperature, high rainfall treatment, the levels of mRNAs for RbcS and GS2 (encoding the small subunit of rubisco and the chloroplastic isoform of GS, respectively) declined while GS1 (encoding the cytosolic isoform of GS) was upregulated several weeks before heading. The transcript level response (along with soil and plant nitrogen data) indicated the leaf had switched from a carbon and nitrogen sink to a source - consistent with more mature plant function and earlier flowering. Soil CO2 respiration also showed strong rain-by-temperature interactions that were due mainly to changes in root response (respiration and/or exudates

  20. 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.

  1. Diagnostic evaluation of distributed physically based model at the REW scale (THREW) using rainfall-runoff event analysis

    Science.gov (United States)

    Tian, F.; Sivapalan, M.; Li, H.; Hu, H.

    2007-12-01

    The importance of diagnostic analysis of hydrological models is increasingly recognized by the scientific community (M. Sivapalan, et al., 2003; H. V. Gupta, et al., 2007). Model diagnosis refers to model structures and parameters being identified not only by statistical comparison of system state variables and outputs but also by process understanding in a specific watershed. Process understanding can be gained by the analysis of observational data and model results at the specific watershed as well as through regionalization. Although remote sensing technology can provide valuable data about the inputs, state variables, and outputs of the hydrological system, observational rainfall-runoff data still constitute the most accurate, reliable, direct, and thus a basic component of hydrology related database. One critical question in model diagnostic analysis is, therefore, what signature characteristic can we extract from rainfall and runoff data. To this date only a few studies have focused on this question, such as Merz et al. (2006) and Lana-Renault et al. (2007), still none of these studies related event analysis with model diagnosis in an explicit, rigorous, and systematic manner. Our work focuses on the identification of the dominant runoff generation mechanisms from event analysis of rainfall-runoff data, including correlation analysis and analysis of timing pattern. The correlation analysis involves the identification of the complex relationship among rainfall depth, intensity, runoff coefficient, and antecedent conditions, and the timing pattern analysis aims to identify the clustering pattern of runoff events in relation to the patterns of rainfall events. Our diagnostic analysis illustrates the changing pattern of runoff generation mechanisms in the DMIP2 test watersheds located in Oklahoma region, which is also well recognized by numerical simulations based on TsingHua Representative Elementary Watershed (THREW) model. The result suggests the usefulness of

  2. Toward an operational tool to simulate green roof hydrological impact at the basin scale: a new version of the distributed rainfall-runoff model Multi-Hydro.

    Science.gov (United States)

    Versini, Pierre-Antoine; Gires, Auguste; Tchinguirinskaia, Ioulia; Schertzer, Daniel

    2016-10-01

    Currently widespread in new urban projects, green roofs have shown a positive impact on urban runoff at the building scale: decrease and slow-down of the peak discharge, and decrease of runoff volume. The present work aims to study their possible impact at the catchment scale, more compatible with stormwater management issues. For this purpose, a specific module dedicated to simulating the hydrological behaviour of a green roof has been developed in the distributed rainfall-runoff model (Multi-Hydro). It has been applied on a French urban catchment where most of the building roofs are flat and assumed to accept the implementation of a green roof. Catchment responses to several rainfall events covering a wide range of meteorological situations have been simulated. The simulation results show green roofs can significantly reduce runoff volume and the magnitude of peak discharge (up to 80%) depending on the rainfall event and initial saturation of the substrate. Additional tests have been made to assess the susceptibility of this response regarding both spatial distributions of green roofs and precipitation. It appears that the total area of greened roofs is more important than their locations. On the other hand, peak discharge reduction seems to be clearly dependent on spatial distribution of precipitation.

  3. 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.

  4. Experimental real-time multi-model ensemble (MME) prediction of rainfall during Monsoon 2008: Large-scale medium-range aspects

    Indian Academy of Sciences (India)

    A K Mitra; G R Iyengar; V R Durai; J Sanjay; T N Krishnamurti; A Mishra; D R Sikka

    2011-02-01

    Realistic simulation/prediction of the Asian summer monsoon rainfall on various space–time scales is a challenging scientific task. Compared to mid-latitudes, a proportional skill improvement in the prediction of monsoon rainfall in the medium range has not happened in recent years. Global models and data assimilation techniques are being improved for monsoon/tropics. However, multi-model ensemble (MME) forecasting is gaining popularity, as it has the potential to provide more information for practical forecasting in terms of making a consensus forecast and handling model uncertainties. As major centers are exchanging model output in near real-time, MME is a viable inexpensive way of enhancing the forecasting skill and information content. During monsoon 2008, on an experimental basis, an MME forecasting of large-scale monsoon precipitation in the medium range was carried out in real-time at National Centre for Medium Range Weather Forecasting (NCMRWF), India. Simple ensemble mean (EMN) giving equal weight to member models, bias-corrected ensemble mean (BCEMn) and MME forecast, where different weights are given to member models, are the products of the algorithm tested here. In general, the aforementioned products from the multi-model ensemble forecast system have a higher skill than individual model forecasts. The skill score for the Indian domain and other sub-regions indicates that the BCEMn produces the best result, compared to EMN and MME. Giving weights to different models to obtain an MME product helps to improve individual member models only marginally. It is noted that for higher rainfall values, the skill of the global model rainfall forecast decreases rapidly beyond day-3, and hence for day-4 and day-5, the MME products could not bring much improvement over member models. However, up to day-3, the MME products were always better than individual member models.

  5. Effective Saturated Hydraulic Conductivity for Representing Field-Scale Infiltration and Surface Soil Moisture in Heterogeneous Unsaturated Soils Subjected to Rainfall Events

    Directory of Open Access Journals (Sweden)

    Richa Ojha

    2017-02-01

    Full Text Available Spatial heterogeneity in soil properties has been a challenge for providing field-scale estimates of infiltration rates and surface soil moisture content over natural fields. In this study, we develop analytical expressions for effective saturated hydraulic conductivity for use with the Green-Ampt model to describe field-scale infiltration rates and evolution of surface soil moisture over unsaturated fields subjected to a rainfall event. The heterogeneity in soil properties is described by a log-normal distribution for surface saturated hydraulic conductivity. Comparisons between field-scale numerical and analytical simulation results for water movement in heterogeneous unsaturated soils show that the proposed expressions reproduce the evolution of surface soil moisture and infiltration rate with time. The analytical expressions hold promise for describing mean field infiltration rates and surface soil moisture evolution at field-scale over sandy loam and loamy sand soils.

  6. Influence of SWR on the hydrological response on two contrasting Mediterranean hillslopes at plot scale using rainfall simulations.

    Science.gov (United States)

    Gabarron Galeote, M. A.; Martinez Murillo, J. F.; Ruiz Sinoga, J. D.

    2012-04-01

    Soil water repellency (SWR) has proved to be a common phenomenon in Mediterranean environments, where it is favored by a four-month-long dry season and a high organic matter input in the soil from vegetation. Among the main effects of SWR are reducing infiltration and enhancing overland flow. The objectives of this study are: i) to characterize the SWR in two contrasting hillslopes and over different microenvironments; ii) to determine the effect of SWR in infiltration, run-off generation and soil loss processes. The experimental area is located in southern Spain (36°50'N, 4°50'W), 22 km northwestern of the city of Málaga, and includes two hillslopes having different exposures. In general, the area is characterized by a dry Mediterranean climate (mean annual precipitation: 576.1 mm year-1; mean annual temperature: 15.7°C), the dominance of water erosion processes on steep hillslopes (> 12.5°) with a substratum of metamorphic rocks (phyllites). Vegetation cover consists on an open wood of cork oak with typical degraded Mediterranean scrub, where the dominant genus is Cistus spp. Soil depths range from 20 to 50 cm. Three soil microenvironments were selected on each hillslope: Soil covered by Cistus spp. and litter, soil covered by Cistus spp. removing the litter and bare soil. On each microenvironment SWR was measured by mean of WDPT method and 5 rainfall simulations was performed. Experiments were carried out in September, after a prolonged drought period, when SWR is supposed to be most strongly expressed. The water repellency for all micro-environments was an order of magnitude greater on the north-facing hillslope (p<0.000), where the greatest value was found for plots of Cistus spp. with litter (843.2 s ± 675.4 s, followed by plots of Cistus spp. without litter (492.0 s ± 56 s) and bare soil plots (97.4 s ± 86.7 s). On the south-facing hillslope the Cistus spp. plots with and without litter had mean water repellency values of 77.3 s ± 49.3 s (strong

  7. 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...

  8. Hydrological processes obtained on the plot scale under four simulated rainfall tests during the cycle of different crop systems

    Directory of Open Access Journals (Sweden)

    Ildegardis Bertol

    2014-04-01

    Full Text Available The cropping system influences the interception of water by plants, water storage in depressions on the soil surface, water infiltration into the soil and runoff. The aim of this study was to quantify some hydrological processes under no tillage cropping systems at the edge of a slope, in 2009 and 2010, in a Humic Dystrudept soil, with the following treatments: corn, soybeans, and common beans alone; and intercropped corn and common bean. Treatments consisted of four simulated rainfall tests at different times, with a planned intensity of 64 mm h-1 and 90 min duration. The first test was applied 18 days after sowing, and the others at 39, 75 and 120 days after the first test. Different times of the simulated rainfall and stages of the crop cycle affected soil water content prior to the rain, and the time runoff began and its peak flow and, thus, the surface hydrological processes. The depth of the runoff and the depth of the water intercepted by the crop + soil infiltration + soil surface storage were affected by the crop systems and the rainfall applied at different times. The corn crop was the most effective treatment for controlling runoff, with a water loss ratio of 0.38, equivalent to 75 % of the water loss ratio exhibited by common bean (0.51, the least effective treatment in relation to the others. Total water loss by runoff decreased linearly with an increase in the time that runoff began, regardless of the treatment; however, soil water content on the gravimetric basis increased linearly from the beginning to the end of the rainfall.

  9. 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

  10. The ScaLIng Macroweather Model (SLIMM) and monthly and inter annual regional forecasting.

    Science.gov (United States)

    Lovejoy, S.; Del Rio Amador, L.; Sloman, L.

    2015-12-01

    By exploiting the sensitive dependence on initial conditions, GCM's can generate a statistical ensemble of future states in which the high frequency "weather" is treated as a driving noise. Following Hasselman, 1976, this has lead to stochastic models that directly generate the noise, and model the low frequencies using systems of integer ordered linear ordinary differential equations, the most well known are the linear inverse models (LIM). These have been presented as a benchmark for decadal surface temperature forecast. Using the LIM, hindcast skills comparable to and sometimes even better than the skill of (coupled) Global Circulation Models (GCM's) from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Nevertheless, the short range exponential temporal decorrelations implicit in the LIM models are unrealistic (the true decorrelations are closer to long range power laws), and - as a consequence - the useful limit to the forecast horizon is roughly one year: it enormously underestimates the memory of the system. In presentation, we make a scaling analogue of the LIM: ScaLIng Macroweather Model (SLIMM) that exploits the power law (scaling) behavior in time of the temperature field and consequently, make use of the long history dependence of the data to improve the skill. The results predicted analytically by the model have been tested by performing actual hindcasts in different 5º x 5º regions on the planet using the Twentieth Century Reanalysis as a reference datasets. As a first step, we removed the anthropogenic component of each time series based on its sensitivity to equivalent CO2 concentration for the last 130 years, the residues are our estimates of the natural variability that SLIMM predicts. This residues were treated as fractional Gaussian noise processes with scaling exponent H between -0.5 and 0. The value of H for each grid-point can be obtained directly from the data. We report maps of theoretical skill predicted by the model and we

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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

  16. 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

  17. 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

  18. Spatial interpolation of daily rainfall at catchment scale: a case study of the Ourthe and Ambleve catchments, Belgium

    Directory of Open Access Journals (Sweden)

    S. Ly

    2010-09-01

    Full Text Available Spatial interpolation of precipitation data is of great importance for hydrological modelling. Geostatistical methods (krigings are widely used in spatial interpolation from point measurement to continuous surfaces. However, the majority of existing geostatistical algorithms are available only for single-moment data. The first step in kriging computation is the semi-variogram modelling which usually uses only one variogram model for all-moment data. The objective of this paper was to develop different algorithms of spatial interpolation for daily rainfall on 1 km2 regular grids in the catchment area and to compare the results of geostatistical and deterministic approaches. In this study, we used daily rainfall data from 70 raingages in the hilly landscape of the Ourthe and Ambleve catchments in Belgium (2908 km2. This area lies between 35 and 693 m in elevation and consists of river networks, which are tributaries of the Meuse River. For geostatistical algorithms, Cressie's Approximate Weighted Least Squares method was used to fit seven semi-variogram models (logarithmic, power, exponential, Gaussian, rational quadratic, spherical and penta-spherical to daily sample semi-variogram on a daily basis. Seven selected raingages were used to compare the interpolation performance of these algorithms applied to many degenerated-raingage cases. Spatial interpolation with the geostatistical and Inverse Distance Weighting (IDW algorithms outperformed considerably interpolation with the Thiessen polygon that is commonly used in various hydrological models. Kriging with an External Drift (KED and Ordinary Cokriging (OCK presented the highest Root Mean Square Error (RMSE between the geostatistical and IDW methods. Ordinary Kriging (ORK and IDW were considered to be the best methods, as they provided smallest RMSE value for nearly all cases.

  19. 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.

  20. On the Fine-Scale Topography Regulating Changes in Atmospheric Hydrological Cycle and Extreme Rainfall over West Africa in a Regional Climate Model Projections

    Directory of Open Access Journals (Sweden)

    M. B. Sylla

    2012-01-01

    Full Text Available The ICTP-RegCM3 is used to downscale at 40 km projections from ECHAM5 over West Africa during the mid and late 21st Century. The results show that while ECHAM5 projects wetter climate along the Gulf of Guinea and drier conditions along the Sahel, RegCM3 produces contrasting changes for low-elevation (negative and high-elevation (positive terrains more marked during the second period. These wetter conditions in the uplands result from an intensification of the atmospheric hydrological cycle arising as a consequence of more frequent and denser rainy days and leading to larger intensity and more extreme events. Examination of the large-scale dynamics reveal that these conditions are mostly driven by increased low-level moisture convergence which produces elevated vertical motion above Cameroun’s mountainous areas favoring more atmospheric instability, moisture, and rainfall. This regulation of climate change signal by high-elevation terrains is feasible only in RegCM3 as the driving ECHAM5 is smoothing along all the Gulf of Guinea. This consolidates the need to use regional climate model to investigate the regional and local response of the hydrological cycle, the daily rainfall and extreme events to the increasing anthropogenic GHG warming for suitable impact studies specifically over region with complex topography such as West Africa.

  1. Prototyping an Early-warning System for Rainfall-triggered Landslides on a Regional Scale Using a Physically-based Model and Remote Sensing Datasets

    Science.gov (United States)

    Liao, Z.; Hong, Y.; Kirschbaum, D. B.; Fukuoka, H.; Sassa, K.; Karnawati, D.; Fathani, F.

    2010-12-01

    Recent advancements in the availability of remotely sensed datasets provide an opportunity to advance the predictability of rainfall-triggered landslides at larger spatial scales. An early-warning system based on a physical landslide model and remote sensing information is used to simulate the dynamical response of the soil water content to the spatiotemporal variability of rainfall in complex terrain. The system utilizes geomorphologic datasets including a 30-meter ASTER DEM, a 1-km downscaled FAO soil map, and satellite-based Tropical Rainfall Measuring Mission (TRMM) precipitation. The applied physical model SLIDE (SLope-Infiltration-Distributed Equilibrium) defines a direct relationship between a factor of safety and the rainfall depth on an infinite slope. This prototype model is applied to a case study in Honduras during Hurricane Mitch in 1998 and a secondary case of typhoon-induced shallow landslides over Java Island, Indonesia. In Honduras, two study areas were selected which cover approximately 1,200 square kilometers and where a high density of shallow landslides occurred. The results were quantitatively evaluated using landslide inventory data compiled by the United States Geological Survey (USGS) following Hurricane Mitch, and show a good agreement between the modeling results and observations. The success rate for accurately estimating slope failure locations reached as high as 78% and 75%, while the error indices were 35% and 49%, respectively for each of the two selected study areas. Advantages and limitations of this application are discussed with respect to future assessment and challenges of performing a slope-stability estimation using coarse data at 1200 square kilometers. In Indonesia, the system has been applied over the whole Java Island. The prototyped early-warning system has been enhanced by integration of a susceptibility mapping and a precipitation forecasting model (i.e. Weather Research Forecast). The performance has been evaluated

  2. 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.

  3. 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

  4. 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.

  5. Intercomparison of PERSIANN-CDR and TRMM-3B42V7 precipitation estimates at monthly and daily time scales

    Science.gov (United States)

    Katiraie-Boroujerdy, Pari-Sima; Akbari Asanjan, Ata; Hsu, Kuo-lin; Sorooshian, Soroosh

    2017-09-01

    In the first part of this paper, monthly precipitation data from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) and Tropical Rainfall Measuring Mission 3B42 algorithm Version 7 (TRMM-3B42V7) are evaluated over Iran using the Generalized Three-Cornered Hat (GTCH) method which is self-sufficient of reference data as input. Climate Data Unit (CRU) is added to the GTCH evaluations as an independent gauge-based dataset thus, the minimum requirement of three datasets for the model is satisfied. To ensure consistency of all datasets, the two satellite products were aggregated to 0.5° spatial resolution, which is the minimum resolution of CRU. The results show that the PERSIANN-CDR has higher Signal to Noise Ratio (SNR) than TRMM-3B42V7 for the monthly rainfall estimation, especially in the northern half of the country. All datasets showed low SNR in the mountainous area of southwestern Iran, as well as the arid parts in the southeast region of the country. Additionally, in order to evaluate the efficacy of PERSIANN-CDR and TRMM-3B42V7 in capturing extreme daily-precipitation amounts, an in-situ rain-gauge dataset collected by the Islamic Republic of the Iran Meteorological Organization (IRIMO) was employed. Given the sparsity of the rain gauges, only 0.25° pixels containing three or more gauges were used for this evaluation. There were 228 such pixels where daily and extreme rainfall from PERSIANN-CDR and TRMM-3B42V7 could be compared. However, TRMM-3B42V7 overestimates most of the intensity indices (correlation coefficients; R between 0.7648-0.8311, Root Mean Square Error; RMSE between 3.29mm/day-21.2mm/5day); PERSIANN-CDR underestimates these extremes (R between 0.6349-0.7791 and RMSE between 3.59mm/day-30.56mm/5day). Both satellite products show higher correlation coefficients and lower RMSEs for the annual mean of consecutive dry spells than wet spells. The results show that TRMM-3B42V7

  6. 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.

  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. 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.

  9. Changes in rainfall thresholds for debris flow initiation and run-out on a local and regional scale in the Wenchuan earthquake area, SW China.

    Science.gov (United States)

    van Asch, Theo; Luna, Byron Quan; Tang, Chenxiao; van Westen, Cees; Alkema, Dinand; Fan, Xuanmei

    2013-04-01

    For the development of early warning systems for the initiation and run-out distances of debris flows, to avoid or mitigate intolerable risks, it is necessary to assess rainfall thresholds. However one must be aware that these thresholds can change. These changes can be ascribed to environmental and climate change as well as socio-economical changes. In the Wenchuan area in the Sichuan Province, SW China, changes in thresholds are related to a depletion of source materials for these debris flows. The intensive Earthquake of 2008 in the Wenchuan area generated many co-seismic landslides, which delivered a lot of loose source material. It caused a dramatic increase in debris flow occurrences in the subsequent years. A preliminary model was designed, with entrainment processes driven by run-off water as the main triggering mechanism, to describe the relationship between rain input and debris flow run-out with the intention to assess rainfall thresholds for the start of debris flows and critical run out distances. The model was calibrated on the depositional volumes of debris flow events which occurred in individual catchments in August 2011. The calibrated model was used to construct rainfall intensity -duration threshold curves. These curves describe the thresholds for a critical run-out distance, determined by the outlet of the catchment, which was considered as the limit beyond which elements at risk situated in the main river plain are threatened. The research is focused on the change in these thresholds curves after a range of consecutive debris flow triggering rain events. It appeared that for individual catchments the rate of change of these thresholds can vary dramatically which is related to the location of available loose erodible material in the catchment. The model is also applied on a regional scale in the Jingxiu area. A method was proposed to made a general estimate of the time duration to arrive at a debris flow frequency level before the earthquake

  10. The Use of Rainfall Forecasts as a Decision Guide for Small-Scale Farming in Limpopo Province, South Africa

    Science.gov (United States)

    Moeletsi, M. E.; Mellaart, E. A. R.; Mpandeli, N. S.; Hamandawana, H.

    2013-01-01

    Purpose: New innovative ways of communicating agrometeorological information are needed to help farmers, especially subsistence/small-scale farmers, to cope with the high climate variability experienced in most parts of southern Africa. Design/methodology/approach: The article introduces an early warning system for farmers. It utilizes short…

  11. 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

  12. Arctic energy budget in relation to sea ice variability on monthly-to-annual time scales

    NARCIS (Netherlands)

    Krikken, F.; Hazeleger, W.

    2015-01-01

    The large decrease in Arctic sea ice in recent years has triggered a strong interest in Arctic sea ice predictions on seasonal-to-decadal time scales. Hence, it is important to understand physical processes that provide enhanced predictability beyond persistence of sea ice anomalies. This study

  13. Arctic energy budget in relation to sea ice variability on monthly-to-annual time scales

    NARCIS (Netherlands)

    Krikken, F.; Hazeleger, W.

    2015-01-01

    The large decrease in Arctic sea ice in recent years has triggered a strong interest in Arctic sea ice predictions on seasonal-to-decadal time scales. Hence, it is important to understand physical processes that provide enhanced predictability beyond persistence of sea ice anomalies. This study anal

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

    Science.gov (United States)

    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.

  15. 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.

  16. 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.

  17. From seconds to months: an overview of multi-scale dynamics of mobile telephone calls

    Science.gov (United States)

    Saramäki, Jari; Moro, Esteban

    2015-06-01

    Big Data on electronic records of social interactions allow approaching human behaviour and sociality from a quantitative point of view with unforeseen statistical power. Mobile telephone Call Detail Records (CDRs), automatically collected by telecom operators for billing purposes, have proven especially fruitful for understanding one-to-one communication patterns as well as the dynamics of social networks that are reflected in such patterns. We present an overview of empirical results on the multi-scale dynamics of social dynamics and networks inferred from mobile telephone calls. We begin with the shortest timescales and fastest dynamics, such as burstiness of call sequences between individuals, and "zoom out" towards longer temporal and larger structural scales, from temporal motifs formed by correlated calls between multiple individuals to long-term dynamics of social groups. We conclude this overview with a future outlook.

  18. From seconds to months: multi-scale dynamics of mobile telephone calls

    CERN Document Server

    Saramaki, Jari

    2015-01-01

    Big Data on electronic records of social interactions allow approaching human behaviour and sociality from a quantitative point of view with unforeseen statistical power. Mobile telephone Call Detail Records (CDRs), automatically collected by telecom operators for billing purposes, have proven especially fruitful for understanding one-to-one communication patterns as well as the dynamics of social networks that are reflected in such patterns. We present an overview of empirical results on the multi-scale dynamics of social dynamics and networks inferred from mobile telephone calls. We begin with the shortest timescales and fastest dynamics, such as burstiness of call sequences between individuals, and "zoom out" towards longer temporal and larger structural scales, from temporal motifs formed by correlated calls between multiple individuals to long-term dynamics of social groups. We conclude this overview with a future outlook.

  19. 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

  20. 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

    hierarchical MC model with the semi-parametric model in preserving rainfall variability in daily, monthly, and multi-year scales. To calibrate the parameters of both models and assess their ability to preserve observed statistics, we have used ground based data from 15 raingauge stations around Australia, which consist a wide range of climate zones including coastal, monsoonal, and arid climate characteristics. In preliminary results, both models show comparative performances in preserving the multi-year variability of rainfall depth and occurrence. However, the semi-parametric model shows a tendency of overestimating the mean rainfall depth, while our model shows a tendency of overestimating the number of wet days. We will discuss further the relative merits of the both models for hydrology simulation in the presentation.

  1. US stock market efficiency over weekly, monthly, quarterly and yearly time scales

    Science.gov (United States)

    Rodriguez, E.; Aguilar-Cornejo, M.; Femat, R.; Alvarez-Ramirez, J.

    2014-11-01

    In financial markets, the weak form of the efficient market hypothesis implies that price returns are serially uncorrelated sequences. In other words, prices should follow a random walk behavior. Recent developments in evolutionary economic theory (Lo, 2004) have tailored the concept of adaptive market hypothesis (AMH) by proposing that market efficiency is not an all-or-none concept, but rather market efficiency is a characteristic that varies continuously over time and across markets. Within the AMH framework, this work considers the Dow Jones Index Average (DJIA) for studying the deviations from the random walk behavior over time. It is found that the market efficiency also varies over different time scales, from weeks to years. The well-known detrended fluctuation analysis was used for the characterization of the serial correlations of the return sequences. The results from the empirical showed that interday and intraday returns are more serially correlated than overnight returns. Also, some insights in the presence of business cycles (e.g., Juglar and Kuznets) are provided in terms of time variations of the scaling exponent.

  2. Effects of doubled carbon dioxide on rainfall responses to large-scale forcing: A two-dimensional cloud-resolving modeling study

    Science.gov (United States)

    Li, Xiaofan; Shen, Xinyong; Liu, Jia

    2014-05-01

    Rainfall responses to doubled atmospheric carbon dioxide concentration were investigated through the analysis of two pairs of two-dimensional cloud-resolving model sensitivity experiments. One pair of experiments simulated pre-summer heavy rainfall over southern China around the summer solstice, whereas the other pair of experiments simulated tropical rainfall around the winter solstice. The analysis of the time and model domain mean heat budget revealed that the enhanced local atmospheric warming was associated with doubled carbon dioxide through the weakened infrared radiative cooling during the summer solstice. The weakened mean pre-summer rainfall corresponded to the weakened mean infrared radiative cooling. Doubled carbon dioxide increased the mean tropical atmospheric warming via the enhanced mean latent heat in correspondence with the strengthened mean infrared radiative cooling during the winter solstice. The enhanced mean tropical rainfall was associated with the increased mean latent heat.

  3. Empirical behavior of a world stock index from intra-day to monthly time scales

    Science.gov (United States)

    Breymann, W.; Lüthi, D. R.; Platen, E.

    2009-10-01

    Most of the papers that study the distributional and fractal properties of financial instruments focus on stock prices or foreign exchange rates. This typically leads to mixed results concerning the distributions of log-returns and some multi-fractal properties of exchange rates, stock prices, and regional indices. This paper uses a well diversified world stock index as the central object of analysis. Such index approximates the growth optimal portfolio, which is demonstrated under the benchmark approach, it is the ideal reference unit for studying basic securities. When denominating this world index in units of a given currency, one measures the movements of the currency against the entire market. This provides a least disturbed observation of the currency dynamics. In this manner, one can expect to disentangle, e.g., the superposition of the two currencies involved in an exchange rate. This benchmark approach to the empirical analysis of financial data allows us to establish remarkable stylized facts. Most important is the observation that the repeatedly documented multi-fractal appearance of financial time series is very weak and much less pronounced than the deviation of the mono-scaling properties from Brownian-motion type scaling. The generalized Hurst exponent H(2) assumes typical values between 0.55 and 0.6. Accordingly, autocorrelations of log-returns decay according to a power law, and the quadratic variation vanishes when going to vanishing observation time step size. Furthermore, one can identify the Student t distribution as the log-return distribution of a well-diversified world stock index for long time horizons when a long enough data series is used for estimation. The study of dependence properties, finally, reveals that jumps at daily horizon originate primarily in the stock market while at 5min horizon they originate in the foreign exchange market. The principal message of the empirical analysis is that there is evidence that a diffusion model

  4. ERP-Variations on Time Scales Between Hours and Months Derived From GNSS Observations

    Science.gov (United States)

    Weber, R.; Englich, S.; Mendes Cerveira, P.

    2007-05-01

    Current observations gained by the space geodetic techniques, especially VLBI, GPS and SLR, allow for the determination of Earth Rotation Parameters (ERPs - polar motion, UT1/LOD) with unprecedented accuracy and temporal resolution. This presentation focuses on contributions to the ERP recovery provided by satellite navigation systems (primarily GPS). The IGS (International GNSS Service), for example, currently provides daily polar motion with an accuracy of less than 0.1mas and LOD estimates with an accuracy of a few microseconds. To study more rapid variations in polar motion and LOD we established in a first step a high resolution (hourly resolution) ERP-time series from GPS observation data of the IGS network covering the year 2005. The calculations were carried out by means of the Bernese GPS Software V5.0 considering observations from a subset of 113 fairly stable stations out of the IGS05 reference frame sites. From these ERP time series the amplitudes of the major diurnal and semidiurnal variations caused by ocean tides are estimated. After correcting the series for ocean tides the remaining geodetic observed excitation is compared with variations of atmospheric excitation (AAM). To study the sensitivity of the estimates with respect to the applied mapping function we applied both the widely used NMF (Niell Mapping Function) and the VMF1 (Vienna Mapping Function 1). In addition, based on computations covering two months in 2005, the potential improvement due to the use of additional GLONASS data will be discussed.

  5. Evaluating the effectiveness of management practices on hydrology and water quality at watershed scale with a rainfall-runoff model.

    Science.gov (United States)

    Liu, Yaoze; Bralts, Vincent F; Engel, Bernard A

    2015-04-01

    The adverse influence of urban development on hydrology and water quality can be reduced by applying best management practices (BMPs) and low impact development (LID) practices. This study applied green roof, rain barrel/cistern, bioretention system, porous pavement, permeable patio, grass strip, grassed swale, wetland channel, retention pond, detention basin, and wetland basin, on Crooked Creek watershed. The model was calibrated and validated for annual runoff volume. A framework for simulating BMPs and LID practices at watershed scales was created, and the impacts of BMPs and LID practices on water quantity and water quality were evaluated with the Long-Term Hydrologic Impact Assessment-Low Impact Development 2.1 (L-THIA-LID 2.1) model for 16 scenarios. The various levels and combinations of BMPs/LID practices reduced runoff volume by 0 to 26.47%, Total Nitrogen (TN) by 0.30 to 34.20%, Total Phosphorus (TP) by 0.27 to 47.41%, Total Suspended Solids (TSS) by 0.33 to 53.59%, Lead (Pb) by 0.30 to 60.98%, Biochemical Oxygen Demand (BOD) by 0 to 26.70%, and Chemical Oxygen Demand (COD) by 0 to 27.52%. The implementation of grass strips in 25% of the watershed where this practice could be applied was the most cost-efficient scenario, with cost per unit reduction of $1m3/yr for runoff, while cost for reductions of two pollutants of concern was $445 kg/yr for Total Nitrogen (TN) and $4871 kg/yr for Total Phosphorous (TP). The scenario with very high levels of BMP and LID practice adoption (scenario 15) reduced runoff volume and pollutant loads from 26.47% to 60.98%, and provided the greatest reduction in runoff volume and pollutant loads among all scenarios. However, this scenario was not as cost-efficient as most other scenarios. The L-THIA-LID 2.1 model is a valid tool that can be applied to various locations to help identify cost effective BMP/LID practice plans at watershed scales.

  6. 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.

  7. Effects of practice on the Wechsler Adult Intelligence Scale-IV across 3- and 6-month intervals.

    Science.gov (United States)

    Estevis, Eduardo; Basso, Michael R; Combs, Dennis

    2012-01-01

    A total of 54 participants (age M = 20.9; education M = 14.9; initial Full Scale IQ M = 111.6) were administered the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) at baseline and again either 3 or 6 months later. Scores on the Full Scale IQ, Verbal Comprehension, Working Memory, Perceptual Reasoning, Processing Speed, and General Ability Indices improved approximately 7, 5, 4, 5, 9, and 6 points, respectively, and increases were similar regardless of whether the re-examination occurred over 3- or 6-month intervals. Reliable change indices (RCI) were computed using the simple difference and bivariate regression methods, providing estimated base rates of change across time. The regression method provided more accurate estimates of reliable change than did the simple difference between baseline and follow-up scores. These findings suggest that prior exposure to the WAIS-IV results in significant score increments. These gains reflect practice effects instead of genuine intellectual changes, which may lead to errors in clinical judgment.

  8. Arctic energy budget in relation to sea-ice variability on monthly to annual time scales

    Science.gov (United States)

    Krikken, Folmer; Hazeleger, Wilco

    2015-04-01

    The strong decrease in Arctic sea-ice in recent years has triggered a strong interest in Arctic sea-ice predictions on seasonal to decadal time scales. Hence, it is key to understand physical processes that provide enhanced predictability beyond persistence of sea ice anomalies. The authors report on an analysis of natural variability of Arctic sea-ice from an energy budget perspective, using 15 CMIP5 climate models, and comparing these results to atmospheric and oceanic reanalyses data. We quantify the persistence of sea ice anomalies and the cross-correlation with the surface and top energy budget components. The Arctic energy balance components primarily indicate the important role of the seasonal sea-ice albedo feedback, in which sea-ice anomalies in the melt season reemerge in the growth season. This is a robust anomaly reemergence mechanism among all 15 climate models. The role of ocean lies mainly in storing heat content anomalies in spring, and releasing them in autumn. Ocean heat flux variations only play a minor role. The role of clouds is further investigated. We demonstrate that there is no direct atmospheric response of clouds to spring sea-ice anomalies, but a delayed response is evident in autumn. Hence, there is no cloud-ice feedback in late spring and summer, but there is a cloud-ice feedback in autumn, which strengthens the ice-albedo feedback. Anomalies in insolation are positively correlated with sea-ice variability. This is primarily a result of reduced multiple-reflection of insolation due to an albedo decrease. This effect counteracts the sea-ice albedo effect up to 50%. ERA-Interim and ORAS4 confirm the main findings from the climate models.

  9. 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.

  10. 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.

  11. Application of the rainfall infiltration breakthrough (RIB) model for ...

    African Journals Online (AJOL)

    Application of the rainfall infiltration breakthrough (RIB) model for groundwater ... Correlation analysis between rainfall and observed WLF data at daily scale and ... data are more realistic than those for daily data, when using long time series.

  12. 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).

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Present and future connection of Asian-Pacific Oscillation to large-scale atmospheric circulations and East Asian rainfall: results of CMIP5

    Science.gov (United States)

    Zhou, Botao; Xu, Ying; Shi, Ying

    2017-03-01

    The summer Asian-Pacific oscillation (APO), one of the major modes of climate variability over the Asian-Pacific sector, has a pronounced effect on variations of large-scale atmospheric circulations and climate. This study evaluated the capability of 30 state-of-the-art climate models among the Coupled Model Intercomparison Project Phase 5 (CMIP5) in simulating its association with the atmospheric circulations over the Asian-Pacific region and the precipitation over East Asia. Furthermore, their future connections under the RCP8.5 scenario were examined. The evaluation results show that 5 out of 30 climate models can well capture the observed APO-related features in a comprehensive way, including the strengthened South Asian high (SAH), deepened North Pacific trough (NPT) and northward East Asian jet (EAJ) in the upper troposphere; an intensification of the Asian low and the North Pacific subtropical high (NPSH) as well as a northward shift of the western Pacific subtropical high (WPSH) in the lower troposphere; and a decrease in East Asian summer rainfall (EASR) under the positive APO phase. Based on the five CMIP5 models' simulations, the dynamic linkages of the APO to the SAH, NPT, AL, and NPSH are projected to maintain during the second half of the twenty-first century. However, its connection with the EASR tends to reduce significantly. Such a reduction might result from the weakening of the linkage of the APO to the meridional displacement of the EAJ and WPSH as a response to the warming scenario.

  18. Utility of daily vs. monthly large-scale climate data: an intercomparison of two statistical downscaling methods

    Directory of Open Access Journals (Sweden)

    E. P. Maurer

    2008-03-01

    Full Text Available Downscaling of climate model data is essential to local and regional impact analysis. We compare two methods of statistical downscaling to produce continuous, gridded time series of precipitation and surface air temperature at a 1/8-degree (approximately 140 km2 per grid cell resolution over the western U.S. We use NCEP/NCAR Reanalysis data from 1950–1999 as a surrogate General Circulation Model (GCM. The two methods included are constructed analogues (CA and a bias correction and spatial downscaling (BCSD, both of which have been shown to be skillful in different settings, and BCSD has been used extensively in hydrologic impact analysis. Both methods use the coarse scale Reanalysis fields of precipitation and temperature as predictors of the corresponding fine scale fields. CA downscales daily large-scale data directly and BCSD downscales monthly data, with a random resampling technique to generate daily values. The methods produce generally comparable skill in producing downscaled, gridded fields of precipitation and temperatures at a monthly and seasonal level. For daily precipitation, both methods exhibit limited skill in reproducing both observed wet and dry extremes and the difference between the methods is not significant, reflecting the general low skill in daily precipitation variability in the reanalysis data. For low temperature extremes, the CA method produces greater downscaling skill than BCSD for fall and winter seasons. For high temperature extremes, CA demonstrates higher skill than BCSD in summer. We find that the choice of most appropriate downscaling technique depends on the variables, seasons, and regions of interest, on the availability of daily data, and whether the day to day correspondence of weather from the GCM needs to be reproduced for some applications. The ability to produce skillful downscaled daily data depends primarily on the ability of the climate model to show daily skill.

  19. 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.

  20. 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

  1. Predicting monthly precipitation along coastal Ecuador: ENSO and transfer function models

    Science.gov (United States)

    de Guenni, Lelys B.; García, Mariangel; Muñoz, Ángel G.; Santos, José L.; Cedeño, Alexandra; Perugachi, Carlos; Castillo, José

    2017-08-01

    It is well known that El Niño-Southern Oscillation (ENSO) modifies precipitation patterns in several parts of the world. One of the most impacted areas is the western coast of South America, where Ecuador is located. El Niño events that occurred in 1982-1983, 1987-1988, 1991-1992, and 1997-1998 produced important positive rainfall anomalies in the coastal zone of Ecuador, bringing considerable damage to livelihoods, agriculture, and infrastructure. Operational climate forecasts in the region provide only seasonal scale (e.g., 3-month averages) information, but during ENSO events it is key for decision-makers to use reliable sub-seasonal scale forecasts, which at the present time are still non-existent in most parts of the world. This study analyzes the potential predictability of coastal Ecuador rainfall at monthly scale. Instead of the discrete approach that considers training models using only particular seasons, continuous (i.e., all available months are used) transfer function models are built using standard ENSO indices to explore rainfall forecast skill along the Ecuadorian coast and Galápagos Islands. The modeling approach considers a large-scale contribution, represented by the role of a sea-surface temperature index, and a local-scale contribution represented here via the use of previous precipitation observed in the same station. The study found that the Niño3 index is the best ENSO predictor of monthly coastal rainfall, with a lagged response varying from 0 months (simultaneous) for Galápagos up to 3 months for the continental locations considered. Model validation indicates that the skill is similar to the one obtained using principal component regression models for the same kind of experiments. It is suggested that the proposed approach could provide skillful rainfall forecasts at monthly scale for up to a few months in advance.

  2. Effect of erosion on productivity in subtropical red soil hilly region: a multi-scale spatio-temporal study by simulated rainfall.

    Science.gov (United States)

    Li, Zhongwu; Huang, Jinquan; Zeng, Guangming; Nie, Xiaodong; Ma, Wenming; Yu, Wei; Guo, Wang; Zhang, Jiachao

    2013-01-01

    The effects of water erosion (including long-term historical erosion and single erosion event) on soil properties and productivity in different farming systems were investigated. A typical sloping cropland with homogeneous soil properties was designed in 2009 and then protected from other external disturbances except natural water erosion. In 2012, this cropland was divided in three equally sized blocks. Three treatments were performed on these blocks with different simulated rainfall intensities and farming methods: (1) high rainfall intensity (1.5-1.7 mm min(-1)), no-tillage operation; (2) low rainfall intensity (0.5-0.7 mm min(-1)), no-tillage operation; and (3) low rainfall intensity, tillage operation. All of the blocks were divided in five equally sized subplots along the slope to characterize the three-year effects of historical erosion quantitatively. Redundancy analysis showed that the effects of long-term historical erosion significantly caused most of the variations in soil productivity in no-tillage and low rainfall erosion intensity systems. The intensities of the simulated rainfall did not exhibit significant effects on soil productivity in no-tillage systems. By contrast, different farming operations induced a statistical difference in soil productivity at the same single erosion intensity. Soil organic carbon (SOC) was the major limiting variable that influenced soil productivity. Most explanations of long-term historical erosion for the variation in soil productivity arose from its sharing with SOC. SOC, total nitrogen, and total phosphorus were found as the regressors of soil productivity because of tillage operation. In general, this study provided strong evidence that single erosion event could also impose significant constraints on soil productivity by integrating with tillage operation, although single erosion is not the dominant effect relative to the long-term historical erosion. Our study demonstrated that an effective management of organic

  3. Effect of Erosion on Productivity in Subtropical Red Soil Hilly Region: A Multi-Scale Spatio-Temporal Study by Simulated Rainfall

    Science.gov (United States)

    Li, Zhongwu; Huang, Jinquan; Zeng, Guangming; Nie, Xiaodong; Ma, Wenming; Yu, Wei; Guo, Wang; Zhang, Jiachao

    2013-01-01

    The effects of water erosion (including long-term historical erosion and single erosion event) on soil properties and productivity in different farming systems were investigated. A typical sloping cropland with homogeneous soil properties was designed in 2009 and then protected from other external disturbances except natural water erosion. In 2012, this cropland was divided in three equally sized blocks. Three treatments were performed on these blocks with different simulated rainfall intensities and farming methods: (1) high rainfall intensity (1.5 - 1.7 mm min−1), no-tillage operation; (2) low rainfall intensity (0.5 - 0.7 mm min−1), no-tillage operation; and (3) low rainfall intensity, tillage operation. All of the blocks were divided in five equally sized subplots along the slope to characterize the three-year effects of historical erosion quantitatively. Redundancy analysis showed that the effects of long-term historical erosion significantly caused most of the variations in soil productivity in no-tillage and low rainfall erosion intensity systems. The intensities of the simulated rainfall did not exhibit significant effects on soil productivity in no-tillage systems. By contrast, different farming operations induced a statistical difference in soil productivity at the same single erosion intensity. Soil organic carbon (SOC) was the major limiting variable that influenced soil productivity. Most explanations of long-term historical erosion for the variation in soil productivity arose from its sharing with SOC. SOC, total nitrogen, and total phosphorus were found as the regressors of soil productivity because of tillage operation. In general, this study provided strong evidence that single erosion event could also impose significant constraints on soil productivity by integrating with tillage operation, although single erosion is not the dominant effect relative to the long-term historical erosion. Our study demonstrated that an effective management of

  4. 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.

  5. Performance of a pilot scale microbial electrolysis cell fed on domestic wastewater at ambient temperatures for a 12 month period.

    Science.gov (United States)

    Heidrich, Elizabeth S; Edwards, Stephen R; Dolfing, Jan; Cotterill, Sarah E; Curtis, Thomas P

    2014-12-01

    A 100-L microbial electrolysis cell (MEC) was operated for a 12-month period fed on raw domestic wastewater at temperatures ranging from 1°C to 22°C, producing an average of 0.6 L/day of hydrogen. Gas production was continuous though decreased with time. An average 48.7% of the electrical energy input was recovered, with a Coulombic efficiency of 41.2%. COD removal was inconsistent and below the standards required. Limitations to the cell design, in particular the poor pumping system and large overpotential account for many of the problems. However these are surmountable hurdles that can be addressed in future cycles of pilot scale research. This research has established that the biological process of an MEC will to work at low temperatures with real wastewater for prolonged periods. Testing and demonstrating the robustness and durability of bioelectrochemical systems far beyond that in any previous study, the prospects for developing MEC at full scale are enhanced. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

  6. 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

  7. 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.

  8. 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).

  9. Heavy Rainfall Episodes in the Eastern Northeast Brazil Linked to Large-Scale Ocean-Atmosphere Conditions in the Tropical Atlantic

    Directory of Open Access Journals (Sweden)

    Yves K. Kouadio

    2012-01-01

    Full Text Available Relationships between simultaneous occurrences of distinctive atmospheric easterly wave (EW signatures that cross the south-equatorial Atlantic, intense mesoscale convective systems (lifespan > 2 hour that propagate westward over the western south-equatorial Atlantic, and subsequent strong rainfall episodes (anomaly > 10 mm·day−1 that occur in eastern Northeast Brazil (ENEB are investigated. Using a simple diagnostic analysis, twelve cases with EW lifespan ranging between 3 and 8 days and a mean velocity of 8 m·s−1 were selected and documented during each rainy season of 2004, 2005, and 2006. These cases, which represent 50% of the total number of strong rainfall episodes and 60% of the rainfall amount over the ENEB, were concomitant with an acceleration of the trade winds over the south-equatorial Atlantic, an excess of moisture transported westward from Africa to America, and a strengthening of the convective activity in the oceanic region close to Brazil. Most of these episodes occurred during positive sea surface temperature anomaly patterns over the entire south-equatorial Atlantic and low-frequency warm conditions within the oceanic mixing layer. A real-time monitoring and the simulation of this ocean-atmosphere relationship could help in forecasting such dramatic rainfall events.

  10. Changes in rainfall thresholds for debris flow initiation and run-out on a local and regional scale in the Wenchuan earthquake area, SW China

    NARCIS (Netherlands)

    van Asch, Th.W.J.; Quan Luna, B.; Tang, C.; van Westen, A.; Alkema, D.; Fan, X.

    2013-01-01

    For the development of early warning systems for the initiation and run-out distances of debris flows, to avoid or mitigate intolerable risks, it is necessary to assess rainfall thresholds. However one must be aware that these thresholds can change. These changes can be ascribed to environmental and

  11. Models are likely to underestimate increase in heavy rainfall in the extratropical regions with high rainfall intensity

    Science.gov (United States)

    Borodina, Aleksandra; Fischer, Erich M.; Knutti, Reto

    2017-07-01

    Model projections of regional changes in heavy rainfall are uncertain. On timescales of few decades, internal variability plays an important role and therefore poses a challenge to detect robust model response in heavy rainfall to rising temperatures. We use spatial aggregation to reduce the major role of internal variability and evaluate the heavy rainfall response to warming temperatures with observations. We show that in the regions with high rainfall intensity and for which gridded observations exist, most of the models underestimate the historical scaling of heavy rainfall and the land fraction with significant positive heavy rainfall scalings during the historical period. The historical behavior is correlated with the projected heavy rainfall intensification across models allowing to apply an observational constraint, i.e., to calibrate multimodel ensembles with observations in order to narrow the range of projections. The constraint suggests a substantially stronger intensification of future heavy rainfall than the multimodel mean.

  12. Exploiting the atmosphere's memory for monthly, seasonal and interannual temperature forecasting using Scaling LInear Macroweather Model (SLIMM)

    Science.gov (United States)

    Del Rio Amador, Lenin; Lovejoy, Shaun

    2016-04-01

    . The corresponding space-time model (the ScaLIng Macroweather Model (SLIMM) is thus only multifractal in space where the spatial intermittency is associated with different climate zones. SLIMM exploits the power law (scaling) behavior in time of the temperature field and uses the long historical memory of the temperature series to improve the skill. The only model parameter is the fluctuation scaling exponent, H (usually in the range -0.5 - 0), which is directly related to the skill and can be obtained from the data. The results predicted analytically by the model have been tested by performing actual hindcasts in different 5° x 5° regions covering the planet using ERA-Interim, 20CRv2 and NCEP/NCAR reanalysis as reference datasets. We report maps of theoretical skill predicted by the model and we compare it with actual skill based on hindcasts for monthly, seasonal and annual resolutions. We also present maps of calibrated probability hindcasts with their respective validations. Comparisons between our results using SLIMM, some other stochastic autoregressive model, and hindcasts from the Canadian Seasonal to Interannual Prediction System (CanSIPS) and the National Centers for Environmental Prediction (NCEP)'s model CFSv2, are also shown. For seasonal temperature forecasts, SLIMM outperforms the GCM based forecasts in over 90% of the earth's surface. SLIMM forecasts can be accessed online through the site: http://www.to_be_announced.mcgill.ca.

  13. Monthly to seasonal trends of streamflow in Romania and their connection with large-scale atmospheric circulation

    Science.gov (United States)

    Chelcea, Silvia; Ionita, Monica; Scholz, Patrick

    2016-04-01

    Water resources management has become a challenging issue in the southern Europe, an area under a recurrent water stress. It is widely known that hydrologic variables, such as streamflow, are significantly influenced by various large-scale atmospheric circulation patterns. The identification of relationships between the climate conditions given by these patterns and the seasonal streamflow may provide a valuable tool for long-range streamflow forecasting, adding helpful information for developing efficient water-management policies. As such, the aim of this study is to detect the trends in observed hydrological data and to look for the physical mechanisms responsible for the seasonal modes of inter-annual variability of mean streamflow over Romania in connection with teleconnections indices and atmospheric circulation patterns. The trend detection is performed for the monthly, seasonal and annual mean streamflow and the Standardized Streamflow Index (SSI) for an accumulation period of 1 month at 46 stations located over the whole Romanian territory, over the period 1935 - 2010. The results of the trend analysis show increasing trends (95% confidence level) in winter, spring, autumn and at annual time scale over the north-western part of the country and decreasing trends (95% confidence level) in spring over the southern part of the country. To identify the physical mechanisms responsible for the relationships between the annual and seasonal time series of the mean streamflow and large-scale atmospheric circulation patterns, the potential impact of large-scale climate patterns of the Arctic Oscillation (AO), North Atlantic Oscillation (NAO), El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation in modulating streamflow variability at country level is assessed. The correlation map analysis between the annual and seasonal streamflow time series and the Northern Hemisphere teleconnection patterns emphasize that AO

  14. Maize yield and rainfall on different spatial and temporal scales in Southern Brazil Rendimento de milho e chuva em diferentes escalas espaço-temporais no Sul do Brasil

    Directory of Open Access Journals (Sweden)

    Homero Bergamaschi

    2007-05-01

    Full Text Available This study aimed to establish relationships between maize yield and rainfall on different temporal and spatial scales, in order to provide a basis for crop monitoring and modelling. A 16-year series of maize yield and daily rainfall from 11 municipalities and micro-regions of Rio Grande do Sul State was used. Correlation and regression analyses were used to determine associations between crop yield and rainfall for the entire crop cycle, from tasseling to 30 days after, and from 5 days before tasseling to 40 days after. Close relationships between maize yield and rainfall were found, particularly during the reproductive period (45-day period comprising the flowering and grain filling. Relationships were closer on a regional scale than at smaller scales. Implications of the crop-rainfall relationships for crop modelling are discussed.Este trabalho teve como objetivo estabelecer relações entre rendimentos de milho e totais de chuva em diferentes escalas temporais e espaciais, com a finalidade de fornecer bases para modelagem e monitoramento de safras. Utilizou-se uma série de 16 anos de rendimento de milho e dados diários de chuva de 11 municípios e microrregiões do Estado do Rio Grande do Sul. Análises de correlação e regressão foram utilizadas para determinar associações entre rendimento e total de chuva no ciclo do milho, do pendoamento até 30 dias depois, e de 5 dias antes a 40 dias após o pendoamento. Altas relações foram encontradas entre rendimento de milho e chuvas do período reprodutivo, em particular dos 45 dias que englobam florescimento e enchimento de grãos. Essas relações foram mais elevadas em escala regional do que em nível de município. São discutidas implicações das relações clima-chuva para modelagem de cultivos.

  15. Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments, Belgium

    Directory of Open Access Journals (Sweden)

    S. Ly

    2011-07-01

    Full Text Available Spatial interpolation of precipitation data is of great importance for hydrological modelling. Geostatistical methods (kriging are widely applied in spatial interpolation from point measurement to continuous surfaces. The first step in kriging computation is the semi-variogram modelling which usually used only one variogram model for all-moment data. The objective of this paper was to develop different algorithms of spatial interpolation for daily rainfall on 1 km2 regular grids in the catchment area and to compare the results of geostatistical and deterministic approaches. This study leaned on 30-yr daily rainfall data of 70 raingages in the hilly landscape of the Ourthe and Ambleve catchments in Belgium (2908 km2. This area lies between 35 and 693 m in elevation and consists of river networks, which are tributaries of the Meuse River. For geostatistical algorithms, seven semi-variogram models (logarithmic, power, exponential, Gaussian, rational quadratic, spherical and penta-spherical were fitted to daily sample semi-variogram on a daily basis. These seven variogram models were also adopted to avoid negative interpolated rainfall. The elevation, extracted from a digital elevation model, was incorporated into multivariate geostatistics. Seven validation raingages and cross validation were used to compare the interpolation performance of these algorithms applied to different densities of raingages. We found that between the seven variogram models used, the Gaussian model was the most frequently best fit. Using seven variogram models can avoid negative daily rainfall in ordinary kriging. The negative estimates of kriging were observed for convective more than stratiform rain. The performance of the different methods varied slightly according to the density of raingages, particularly between 8 and 70 raingages but it was much different for interpolation using 4 raingages. Spatial interpolation with the geostatistical and

  16. 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.

  17. Two and a half years of country-wide rainfall maps using radio links from commercial cellular telecommunication networks

    Science.gov (United States)

    Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2016-10-01

    Although rainfall estimation employing microwave links from cellular telecommunication networks is recognized as a new promising measurement technique, its potential for long-term large-scale operational rainfall monitoring remains to be demonstrated. This study contributes to this endeavor by deriving a continuous series of rainfall maps from a large 2.5 year microwave link data set of, on average, 3383 links (2044 link paths) covering Netherlands (˜3.5 × 104 km2), a midlatitude country (˜5°E, ˜52°N) with a temperate climate. Maps are extensively verified against an independent gauge-adjusted radar rainfall data set for different temporal (15 min, 1 h, 1 day, 1 month) and spatial (0.9, 74 km2) scales. The usefulness of different steps in the rainfall retrieval algorithm, i.e., a wet-dry classification method and a filter to remove outliers, is systematically assessed. A novel dew filter is developed to correct for dew-induced wet antenna attenuation, which, although a relative underestimation of 6% to 9% is found, generally yields good results. The microwave link rainfall estimation technique performs well for the summer months (June, July, August), even outperforming interpolation of automatic rain gauge data (with a density of ˜1 gauge per 1000 km2), but large deviations are found for the winter months (December, January, February). These deviations are generally expected to be related to frozen or melting precipitation. Hence, our results show the potential of commercial microwave links for long-term large-scale operational rainfall monitoring.

  18. Rainfall and Elevation Influence the Local-Scale Distribution of Tree Community in the Southern Region of Western Ghats Biodiversity Hotspot (India

    Directory of Open Access Journals (Sweden)

    Shijo Joseph

    2012-01-01

    Full Text Available The present study characterises the tree communities with respect to topographic and climatic variables and identifies the most important environmental correlate of species richness in the southern region of Western Ghats Biodiversity Hotspot, India. Digitally derived environmental variables in combination with tree species richness information were analysed using Canonical Correspondence Analysis (CCA to characterise the communities. Multiple regression technique based on stepwise backward elimination was used to identify the most important environment correlate of species richness. Canonical correspondence analysis results in six major tree communities along the first and second axes. Rainfall is the dominant environmental gradient influencing vegetation patterns on the first CCA axis while elevation showed the highest correlation with the second CCA axis. Backward elimination regression technique yielded rainfall as the most important environmental correlate of species richness. Results were in agreement with the observations in the Neotropics that rainier areas maintain high species diversity.

  19. Changes in rainfall thresholds for debris flow initiation and run-out on a local and regional scale in the Wenchuan earthquake area, SW China

    OpenAIRE

    Asch, Th. W. J. van; B. Quan Luna; Tang, C.; Westen, A. Van; Alkema, D.; Fan, X.

    2013-01-01

    For the development of early warning systems for the initiation and run-out distances of debris flows, to avoid or mitigate intolerable risks, it is necessary to assess rainfall thresholds. However one must be aware that these thresholds can change. These changes can be ascribed to environmental and climate change as well as socio-economical changes. In the Wenchuan area in the Sichuan Province, SW China, changes in thresholds are related to a depletion of source materials for these debris fl...

  20. 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.

  1. 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

  2. Linking ENSO and heavy rainfall events over Coastal British Columbia through a weather pattern classification

    Directory of Open Access Journals (Sweden)

    P. Brigode

    2012-10-01

    Full Text Available Classifications of atmospheric weather patterns (WPs are widely used for the description of the climate of a given region and are employed for many applications, such as weather forecasting, downscaling of global circulation model outputs and reconstruction of past climates. WP classifications were recently used to improve the statistical characterisation of heavy rainfall. In this context, bottom-up approaches, combining spatial distribution of heavy rainfall observations and geopotential height fields have been used to define WP classifications relevant for heavy rainfall statistical analysis. The definition of WPs at the synoptic scale creates an interesting variable which could be used as a link between the global scale of climate signals and the local scale of precipitation station measurements. We introduce here a new WP classification centred on the British Columbia Coastal region (Canada and based on a bottom-up approach. Five contrasted WPs composed this classification, four rainy WPs and one non-rainy WP, the anticyclonic pattern. The four rainy WPs are mainly observed in the winter months (October to March, which is the period of heavy precipitation events in Coastal BC and is thus consistent with the local climatology. The combination of this WP classification with the seasonal description of rainfall is shown to be useful for splitting observed precipitation series into more homogeneous sub-samples and thus identifying, for each station, the synoptic situations that generate the highest hazard in terms of heavy rainfall events. El Niño Southern Oscillations significantly influence the frequency of occurrence of two Coastal BC WPs. Within each WP, ENSO seem to influence only the frequency of rainy events and not the magnitudes of heavy rainfall events. Consequently, MEWP heavy rainfall estimations do not show significant evolution of heavy rainfall behaviour between Niño and Niña winters. However, the WP approach captures the

  3. Linking ENSO and heavy rainfall events over coastal British Columbia through a weather pattern classification

    Directory of Open Access Journals (Sweden)

    P. Brigode

    2013-04-01

    Full Text Available Classifications of atmospheric weather patterns (WPs are widely used for the description of the climate of a given region and are employed for many applications, such as weather forecasting, downscaling of global circulation model outputs and reconstruction of past climates. WP classifications were recently used to improve the statistical characterisation of heavy rainfall. In this context, bottom-up approaches, combining spatial distribution of heavy rainfall observations and geopotential height fields have been used to define WP classifications relevant for heavy rainfall statistical analysis. The definition of WPs at the synoptic scale creates an interesting variable which could be used as a link between the global scale of climate signals and the local scale of precipitation station measurements. We introduce here a new WP classification centred on the British Columbia (BC coastal region (Canada and based on a bottom-up approach. Five contrasted WPs composed this classification, four rainy WPs and one non-rainy WP, the anticyclonic pattern. The four rainy WPs are mainly observed in the winter months (October to March, which is the period of heavy precipitation events in coastal BC and is thus consistent with the local climatology. The combination of this WP classification with the seasonal description of rainfall is shown to be useful for splitting observed precipitation series into more homogeneous sub-samples (i.e. sub-samples constituted by days having similar atmospheric circulation patterns and thus identifying, for each station, the synoptic situations that generate the highest hazard in terms of heavy rainfall events. El Niño-Southern Oscillations (ENSO significantly influence the frequency of occurrence of two coastal BC WPs. Within each WP, ENSO seem to influence only the frequency of rainy events and not the magnitudes of heavy rainfall events. Consequently, heavy rainfall estimations do not show significant evolution of heavy

  4. Linking ENSO and heavy rainfall events over coastal British Columbia through a weather pattern classification

    Science.gov (United States)

    Brigode, P.; Mićović, Z.; Bernardara, P.; Paquet, E.; Garavaglia, F.; Gailhard, J.; Ribstein, P.

    2013-04-01

    Classifications of atmospheric weather patterns (WPs) are widely used for the description of the climate of a given region and are employed for many applications, such as weather forecasting, downscaling of global circulation model outputs and reconstruction of past climates. WP classifications were recently used to improve the statistical characterisation of heavy rainfall. In this context, bottom-up approaches, combining spatial distribution of heavy rainfall observations and geopotential height fields have been used to define WP classifications relevant for heavy rainfall statistical analysis. The definition of WPs at the synoptic scale creates an interesting variable which could be used as a link between the global scale of climate signals and the local scale of precipitation station measurements. We introduce here a new WP classification centred on the British Columbia (BC) coastal region (Canada) and based on a bottom-up approach. Five contrasted WPs composed this classification, four rainy WPs and one non-rainy WP, the anticyclonic pattern. The four rainy WPs are mainly observed in the winter months (October to March), which is the period of heavy precipitation events in coastal BC and is thus consistent with the local climatology. The combination of this WP classification with the seasonal description of rainfall is shown to be useful for splitting observed precipitation series into more homogeneous sub-samples (i.e. sub-samples constituted by days having similar atmospheric circulation patterns) and thus identifying, for each station, the synoptic situations that generate the highest hazard in terms of heavy rainfall events. El Niño-Southern Oscillations (ENSO) significantly influence the frequency of occurrence of two coastal BC WPs. Within each WP, ENSO seem to influence only the frequency of rainy events and not the magnitudes of heavy rainfall events. Consequently, heavy rainfall estimations do not show significant evolution of heavy rainfall

  5. Comparative rainfall data analysis from two vertically pointing radars, an optical disdrometer, and a rain gauge

    Directory of Open Access Journals (Sweden)

    E. I. Nikolopoulos

    2008-12-01

    Full Text Available The authors present results of a comparative analysis of rainfall data from several ground-based instruments. The instruments include two vertically pointing Doppler radars, S-band and X-band, an optical disdrometer, and a tipping-bucket rain gauge. All instruments were collocated at the Iowa City Municipal Airport in Iowa City, Iowa, for a period of several months. The authors used the rainfall data derived from the four instruments to first study the temporal variability and scaling characteristics of rainfall and subsequently assess the instrumental effects on these derived properties. The results revealed obvious correspondence between the ground and remote sensors, which indicates the significance of the instrumental effect on the derived properties.

  6. 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

  7. 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

  8. 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.

  9. Universal Inverse Power Law Distribution of Rainfall in the Indian Region

    CERN Document Server

    Selvam, A M

    2013-01-01

    Space-time fluctuations of meteorological parameters exhibit selfsimilar fractal fluctuations. A general systems theory developed by the author predicts universal inverse power law form incorporating the golden mean for the fractal fluctuations. The monthly total rainfall for the Indian region for the period 1871 to 2011 (141 years) was analysed. The model predicted distribution is in close agreement with observed fractal fluctuations of all size scales. The results of the study are presented.

  10. 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.

  11. A STUDY OF RELATIONSHIP BETWEEN "GUERILLA HEAVY RAINFALL" AND DISASTER

    Science.gov (United States)

    Ushiyama, Motoyuki

    "Guerilla heavy rainfall" is a newly-coined word by mass media of Japan. The four major newspaper publishing companies began to use this word frequently from the beginning of August, 2008. The definition of "Guerilla heavy rainfall" is not clear. It was found from the result of newspaper article analysis from 2008 to 2009 that short-time very heavy rainfall events are called "Guerilla heavy rainfall". In this study, the rainfall event of 80mm or more of rainfalls of 1 hour and 149mm or less of rainfalls was defined as "Guerilla heavy rainfall". 104 events of "Guerilla heavy rainfall" were extracted from AMeDAS precipitation data from 1979 to 2008. There were two victims of these heavy rainfall events in total. They killed at basement or underpass. Although inundation above the floor level occurred in 38% of event, the damage of 100 or more buildings was 9%. We may say that "Guerilla heavy rainfall" does not cause large-scale damage. However, it is necessary to keep in mind that damage caused by "Guerilla heavy rainfall" is generated well in high-risk area of flood, such as basement, underpass, low land and river park.

  12. 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.

  13. All India summer monsoon rainfall prediction using an artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Sahai, A.K.; Soman, M.K.; Satyan, V. [Indian Inst. of Tropical Meteorol., Pune (India). Climate and Global Modelling Div.

    2000-04-01

    The prediction of Indian summer monsoon rainfall (ISMR) on a seasonal time scales has been attempted by various research groups using different techniques including artificial neural networks. The prediction of ISMR on monthly and seasonal time scales is not only scientifically challenging but is also important for planning and devising agricultural strategies. This article describes the artificial neural network (ANN) technique with error- back-propagation algorithm to provide prediction (hindcast) of ISMR on monthly and seasonal time scales. The ANN technique is applied to the five time series of June, July, August, September monthly means and seasonal mean (June+July+August+September) rainfall from 1871 to 1994 based on Parthasarathy data set. The previous five years values from all the five time-series were used to train the ANN to predict for the next year. The details of the models used are discussed. Various statistics are calculated to examine the performance of the models and it is found that the models could be used as a forecasting tool on seasonal and monthly time scales. It is observed by various researchers that with the passage of time the relationships between various predictors and Indian monsoon are changing, leading to changes in monsoon predictability. This issue is discussed and it is found that the monsoon system inherently has a decadal scale variation in predictability. (orig.)

  14. 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

  15. 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.

  16. 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.

  17. Hydroclimate variability and its statistical links to the large-scale climate indices for the Upper Chao Phraya River Basin, Thailand

    Science.gov (United States)

    Singhrattna, N.; Babel, M. S.; Perret, S. R.

    2009-10-01

    The local hydroclimates get impacts from the large-scale atmospheric variables via atmospheric circulation. The developing of their relationships could enhance the understanding of hydroclimate variability. This study focuses on the Upper Chao Phraya River Basin in Thailand in which rainfall is influenced by the Indian Ocean and tropical Pacific Ocean atmospheric circulation. The Southwest monsoon from the Indian Ocean to Thailand is strengthened by the temperature gradient between land and ocean. Thus, the anomalous sea surface temperature (SST) is systematically correlated with the monthly rainfall and identified as the best predictor based on the significant relationships revealed by cross-correlation analysis. It is found that rainfall, especially during the monsoon season in the different zones of study basin, corresponds to the different SST indices. This suggests that the region over the ocean which develops the temperature gradient plays a role in strengthening the monsoon. The enhanced gradient with the SST over the South China Sea is related to rainfall in High Rainfall Zone (HRZ); however, the anomalous SST over the Indian Ocean and the equatorial Pacific Ocean are associated with rainfall in Normal and Low Rainfall Zone (NRZ and LRZ) in the study area. Moreover, the identified predictors are related to the rainfall with lead periods of 1-4 months for the pre-monsoon rainfall and 6-12 months for the monsoon and dry season rainfall. The study results are very useful in developing rainfall forecasting models and consequently in the management of water resources and extreme events.

  18. Rainfall forecast in northeast of thailand using modified k-nearest neighbor

    Directory of Open Access Journals (Sweden)

    Uruya Weesakul

    2014-06-01

    Full Text Available Since damage from natural disasters have increased due to anomalous global climate, scientists and engineers are interested in studying incorporation of the occurence of natural disasters. Thailand faces with flood in the wet season and drought in the dry season every year. The Northeast of Thailand is a region where found damages from disasters especially. This study developed a statistical model for forecasting rainfall in the Chi River Basin using large-scale atmospheric variables (LAV as the independent variables to the modified k-nearest neighbor model. The significant LAV were identified over both Indian and Pacific Oceans. The model performance was evaluated using box plot of 3-month rainfall to present how well the model can capture the historical data and likelihood skill score (LLH. From both model evaluation, approximately 62% of historical rainfall data was captured forecasting model. LLH of rainfall ensembles in the Chi River Basin are quite good and better LLH can be found post 2000, especially June-August and July-September rainfall.

  19. 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.

  20. 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

  1. Synergistic effects of seasonal rainfall, parasites and demography on fluctuations in springbok body condition

    Science.gov (United States)

    Turner, Wendy C.; Versfeld, Wilferd D.; Kilian, J. Werner; Getz, Wayne M.

    2011-01-01

    Summary 1. Seasonality of rainfall can exert a strong influence on animal condition and on host-parasite interactions. The body condition of ruminants fluctuates seasonally in response to changes in energy requirements, foraging patterns and resource availability, and seasonal variation in parasite infections may further alter ruminant body condition. 2. This study disentangles effects of rainfall and gastrointestinal parasite infections on springbok (Antidorcas marsupialis) body condition and determines how these factors vary among demographic groups. 3. Using data from four years and three study areas, we investigated i) the influence of rainfall variation, demographic factors and parasite interactions on parasite prevalence or infection intensity, ii) whether parasitism or rainfall is a more important predictor of springbok body condition and iii) how parasitism and condition vary among study areas along a rainfall gradient. 4. We found that increased parasite intensity is associated with reduced body condition only for adult females. For all other demographic groups, body condition was significantly related to prior rainfall and not to parasitism. Rainfall lagged by two months had a positive effect on body condition. 5. Adult females showed evidence of a “periparturient rise” in parasite intensity, and had higher parasite intensity and lower body condition than adult males after parturition and during early lactation. After juveniles were weaned, adult females had lower parasite intensity than adult males. Sex differences in parasitism and condition may be due to differences between adult females and males in the seasonal timing of reproductive effort and its effects on host immunity, as well as documented sex differences in vulnerability to predation. 6. Our results highlight that parasites and the environment can synergistically affect host populations, but that these interactions might be masked by their interwoven relationships, their differential

  2. 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...

  3. 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...

  4. 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.

  5. Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

    Science.gov (United States)

    Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

    2010-01-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with

  6. A Modeling Study of Surface Rainfall Processes Associated with a Torrential Rainfall Event over Hubei, China, during July 2007

    Institute of Scientific and Technical Information of China (English)

    ZHOU Yushu; CUI Chunguang

    2011-01-01

    The surface rainfall processes associated with the torrential rainfall event over Hubei,China,during July 2007 were investigated using a two-dimensional cloud-resolving model.The model integrated the large-scale vertical velocity and zonal wind data from National Centers for Environmental Prediction (NCEP)/Global Data Assimilation System (GDAS) for 5 days.The time and model domain mean surface rain rate was used to identify the onset,mature,and decay periods of rainfall.During the onset period,the descending motion data imposed in the lower troposphere led to a large contribution of stratiform rainfall to the model domain mean surface rainfall.The local atmospheric drying and transport of rain from convective regions mainly contributes to the stratiform rainfall.During the mature periods,the ascending motion data integrated into the model was so strong that water vapor convergence was the dominant process for both convective and stratiform rainfall.Both convective and stratiform rainfalls made important contributions to the model domain mean surface rainfall. During the decay period,descending motion data input into the model prevailed,making stratiform rainfall dominant.Stratiform rainfall was mainly caused by the water vapor convergence over raining stratiform regions.

  7. 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

  8. 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

    skills in detecting the relatively heavy rainfall that preceded the flood and in predicting that the 95th percentile of the discharge (i.e. the flood alert level in Niamey) will be exceeded. One outcome of the work is to show how different types of satellite information can be relevant and their scales complementing each-other for tropical hydrology. The red flood of the Niger river in Niamey is a good example of these scale complementarity. Satellite altimetry is needed to monitor the low frequency variation of the Niger outflow associated with early season rainfall far ahead of Niamey ; while high resolution satellite rainfall products are needed to model the fast response to the rainfall occurring during the heart of the monsoon season near Niamey.

  9. Spatial validation of large scale land surface models against monthly land surface temperature patterns using innovative performance metrics.

    Science.gov (United States)

    Koch, Julian; Siemann, Amanda; Stisen, Simon; Sheffield, Justin

    2016-04-01

    Land surface models (LSMs) are a key tool to enhance process understanding and to provide predictions of the terrestrial hydrosphere and its atmospheric coupling. Distributed LSMs predict hydrological states and fluxes, such as land surface temperature (LST) or actual evapotranspiration (aET), at each grid cell. LST observations are widely available through satellite remote sensing platforms that enable comprehensive spatial validations of LSMs. In spite of the availability of LST data, most validation studies rely on simple cell to cell comparisons and thus do not regard true spatial pattern information. This study features two innovative spatial performance metrics, namely EOF- and connectivity-analysis, to validate predicted LST patterns by three LSMs (Mosaic, Noah, VIC) over the contiguous USA. The LST validation dataset is derived from global High-Resolution-Infrared-Radiometric-Sounder (HIRS) retrievals for a 30 year period. The metrics are bias insensitive, which is an important feature in order to truly validate spatial patterns. The EOF analysis evaluates the spatial variability and pattern seasonality, and attests better performance to VIC in the warm months and to Mosaic and Noah in the cold months. Further, more than 75% of the LST variability can be captured by a single pattern that is strongly driven by air temperature. The connectivity analysis assesses the homogeneity and smoothness of patterns. The LSMs are most reliable at predicting cold LST patterns in the warm months and vice versa. Lastly, the coupling between aET and LST is investigated at flux tower sites and compared against LSMs to explain the identified LST shortcomings.

  10. 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.

  11. Rainfall Downscaling Conditional on Upper-air Atmospheric Predictors: Improved Assessment of Rainfall Statistics in a Changing Climate

    Science.gov (United States)

    Langousis, Andreas; Mamalakis, Antonis; Deidda, Roberto; Marrocu, Marino

    2015-04-01

    To improve the level skill of Global Climate Models (GCMs) and Regional Climate Models (RCMs) in reproducing the statistics of rainfall at a basin level and at hydrologically relevant temporal scales (e.g. daily), two types of statistical approaches have been suggested. One is the statistical correction of climate model rainfall outputs using historical series of precipitation. The other is the use of stochastic models of rainfall to conditionally simulate precipitation series, based on large-scale atmospheric predictors produced by climate models (e.g. geopotential height, relative vorticity, divergence, mean sea level pressure). The latter approach, usually referred to as statistical rainfall downscaling, aims at reproducing the statistical character of rainfall, while accounting for the effects of large-scale atmospheric circulation (and, therefore, climate forcing) on rainfall statistics. While promising, statistical rainfall downscaling has not attracted much attention in recent years, since the suggested approaches involved complex (i.e. subjective or computationally intense) identification procedures of the local weather, in addition to demonstrating limited success in reproducing several statistical features of rainfall, such as seasonal variations, the distributions of dry and wet spell lengths, the distribution of the mean rainfall intensity inside wet periods, and the distribution of rainfall extremes. In an effort to remedy those shortcomings, Langousis and Kaleris (2014) developed a statistical framework for simulation of daily rainfall intensities conditional on upper air variables, which accurately reproduces the statistical character of rainfall at multiple time-scales. Here, we study the relative performance of: a) quantile-quantile (Q-Q) correction of climate model rainfall products, and b) the statistical downscaling scheme of Langousis and Kaleris (2014), in reproducing the statistical structure of rainfall, as well as rainfall extremes, at a

  12. An Objective Approach for Prediction of Daily Summer Monsoon Rainfall over Orissa (India) due to Interaction of Mesoscale and Large-scale Synoptic Systems

    Science.gov (United States)

    Mohapatra, M.; Mohanty, U. C.

    2007-09-01

    Orissa State, a meteorological subdivision of India, lies on the east coast of India close to north Bay of Bengal and to the south of the normal position of the monsoon trough. The monsoon disturbances such as depressions and cyclonic storms mostly develop to the north of 15° N over the Bay of Bengal and move along the monsoon trough. As Orissa lies in the southwest sector of such disturbances, it experiences very heavy rainfall due to the interaction of these systems with mesoscale convection sometimes leading to flood. The orography due to the Eastern Ghat and other hill peaks in Orissa and environs play a significant role in this interaction. The objective of this study is to develop an objective statistical model to predict the occurrence and quantity of precipitation during the next 24 hours over specific locations of Orissa, due to monsoon disturbances over north Bay and adjoining west central Bay of Bengal based on observations to up 0300 UTC of the day. A probability of precipitation (PoP) model has been developed by applying forward stepwise regression with available surface and upper air meteorological parameters observed in and around Orissa in association with monsoon disturbances during the summer monsoon season (June-September). The PoP forecast has been converted into the deterministic occurrence/non-occurrence of precipitation forecast using the critical value of PoP. The parameters selected through stepwise regression have been considered to develop quantitative precipitation forecast (QPF) model using multiple discriminant analysis (MDA) for categorical prediction of precipitation in different ranges such as 0.1 10, 11 25, 26 50, 51 100 and >100 mm if the occurrence of precipitation is predicted by PoP model. All the above models have been developed based on data of summer monsoon seasons of 1980 1994, and data during 1995 1998 have been used for testing the skill of the models. Considering six representative stations for six homogeneous regions

  13. Family caregivers’ assessment of symptoms in persons with dementia using the GBS-scale: differences in rating after psychosocial intervention – an 18-month follow-up study

    Directory of Open Access Journals (Sweden)

    Beth Dahlrup

    2010-12-01

    Full Text Available Beth Dahlrup, Eva Nordell, Signe Andrén, Sölve ElmståhlDepartment of Health Sciences, Division of Geriatric Medicine, Lund University, SwedenAbstract: The purpose of this study was to examine if psychosocial intervention for family caregivers made any differences in describing symptoms of dementia in the persons they cared for. The study population comprised family caregivers of persons aged 70 years and older receiving social services and diagnosed with dementia disorders. A group of 129 family caregivers underwent psychosocial intervention including education, information, and provision of a support group, while 133 family caregivers did not and these formed the control group. Family caregivers were followed-up every 6 months for a total of 18 months. They rated intellectual, emotional, and activity of daily living (ADL functions in persons with dementia using the Gottfries-Bråne-Steen scale (GBS-scale. Family caregivers who underwent psychosocial intervention rated the intellectual and emotional symptoms of dementia significantly higher 6 months later compared to controls and the effect was sustained during the 18-month follow-up irrespective of relationship and education. Most notably, decrease in function of recent memory, ability to increase tempo, long-windedness, distractibility, and blunting were better identified. Our findings suggest that the family caregivers who underwent psychosocial intervention achieved better understanding of different symptoms and the behaviors of dementia. These findings may explain earlier findings of positive effects after psychosocial intervention on family caregivers’ sense of burden, satisfaction, and ability to delay nursing home placement.Keywords: intervention, dementia, family caregivers, education, GBS-scale

  14. Introducing uncertainty of radar-rainfall estimates to the verification of mesoscale model precipitation forecasts

    Directory of Open Access Journals (Sweden)

    M. P. Mittermaier

    2008-05-01

    Full Text Available A simple measure of the uncertainty associated with using radar-derived rainfall estimates as "truth" has been introduced to the Numerical Weather Prediction (NWP verification process to assess the effect on forecast skill and errors. Deterministic precipitation forecasts from the mesoscale version of the UK Met Office Unified Model for a two-day high-impact event and for a month were verified at the daily and six-hourly time scale using a spatially-based intensity-scale method and various traditional skill scores such as the Equitable Threat Score (ETS and log-odds ratio. Radar-rainfall accumulations from the UK Nimrod radar-composite were used.

    The results show that the inclusion of uncertainty has some effect, shifting the forecast errors and skill. The study also allowed for the comparison of results from the intensity-scale method and traditional skill scores. It showed that the two methods complement each other, one detailing the scale and rainfall accumulation thresholds where the errors occur, the other showing how skillful the forecast is. It was also found that for the six-hourly forecasts the error distributions remain similar with forecast lead time but skill decreases. This highlights the difference between forecast error and forecast skill, and that they are not necessarily the same.

  15. Introducing uncertainty of radar-rainfall estimates to the verification of mesoscale model precipitation forecasts

    Science.gov (United States)

    Mittermaier, M. P.

    2008-05-01

    A simple measure of the uncertainty associated with using radar-derived rainfall estimates as "truth" has been introduced to the Numerical Weather Prediction (NWP) verification process to assess the effect on forecast skill and errors. Deterministic precipitation forecasts from the mesoscale version of the UK Met Office Unified Model for a two-day high-impact event and for a month were verified at the daily and six-hourly time scale using a spatially-based intensity-scale method and various traditional skill scores such as the Equitable Threat Score (ETS) and log-odds ratio. Radar-rainfall accumulations from the UK Nimrod radar-composite were used. The results show that the inclusion of uncertainty has some effect, shifting the forecast errors and skill. The study also allowed for the comparison of results from the intensity-scale method and traditional skill scores. It showed that the two methods complement each other, one detailing the scale and rainfall accumulation thresholds where the errors occur, the other showing how skillful the forecast is. It was also found that for the six-hourly forecasts the error distributions remain similar with forecast lead time but skill decreases. This highlights the difference between forecast error and forecast skill, and that they are not necessarily the same.

  16. Constraining continuous rainfall simulations for derived design flood estimation

    Science.gov (United States)

    Woldemeskel, F. M.; Sharma, A.; Mehrotra, R.; Westra, S.

    2016-11-01

    Stochastic rainfall generation is important for a range of hydrologic and water resources applications. Stochastic rainfall can be generated using a number of models; however, preserving relevant attributes of the observed rainfall-including rainfall occurrence, variability and the magnitude of extremes-continues to be difficult. This paper develops an approach to constrain stochastically generated rainfall with an aim of preserving the intensity-durationfrequency (IFD) relationships of the observed data. Two main steps are involved. First, the generated annual maximum rainfall is corrected recursively by matching the generated intensity-frequency relationships to the target (observed) relationships. Second, the remaining (non-annual maximum) rainfall is rescaled such that the mass balance of the generated rain before and after scaling is maintained. The recursive correction is performed at selected storm durations to minimise the dependence between annual maximum values of higher and lower durations for the same year. This ensures that the resulting sequences remain true to the observed rainfall as well as represent the design extremes that may have been developed separately and are needed for compliance reasons. The method is tested on simulated 6 min rainfall series across five Australian stations with different climatic characteristics. The results suggest that the annual maximum and the IFD relationships are well reproduced after constraining the simulated rainfall. While our presentation focusses on the representation of design rainfall attributes (IFDs), the proposed approach can also be easily extended to constrain other attributes of the generated rainfall, providing an effective platform for post-processing of stochastic rainfall generators.

  17. Sources of Uncertainty in Rainfall Maps from Cellular Communication Networks

    Science.gov (United States)

    Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2015-04-01

    Accurate measurements of rainfall are important in many hydrological applications, for instance, flash-flood early-warning systems, hydraulic structures design, agriculture, weather forecasting, and climate modelling. Rainfall intensities can be retrieved from (commercial) microwave link networks. Whenever possible, link networks measure and store the decrease in power of the electromagnetic signal at regular intervals. The decrease in power is largely due to the attenuation by raindrops along the link paths. Such an alternative technique fulfills the continuous strive for measurements of rainfall in time and space at higher resolutions, especially in places where traditional rain gauge networks are scarce or poorly maintained. Rainfall maps from microwave link networks have recently been introduced at country-wide scales. Despite their potential in rainfall estimation at high spatiotemporal resolutions, the uncertainties present in rainfall maps from link networks are not yet fully comprehended. The aim of this work is to identify and quantify the sources of uncertainty present in interpolated rainfall maps from link rainfall depths. In order to disentangle these sources of uncertainty, we classified them into two categories: (1) those associated with the individual microwave link measurements, i.e., the physics involved in the measurements such as wet antenna attenuation, sampling interval of measurements, wet/dry period classification, drop size distribution (DSD), and multi-path propagation; (2) those associated with mapping, i.e., the combined effect of the interpolation methodology, the spatial density of the network, and the availability of link measurements. We computed ~ 3500 rainfall maps from real and simulated link rainfall depths for 12 days for the land surface of The Netherlands. These rainfall maps were compared against quality-controlled gauge-adjusted radar rainfall fields (assumed to be the ground truth). Thus, we were able to not only identify

  18. 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...

  19. 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...

  20. Seasonal UK hydrological forecasts using rainfall forecasts - what level of skill?

    Science.gov (United States)

    Bell, Victoria; Davies, Helen; Kay, Alison; Scaife, Adam

    2017-04-01

    Skilful winter seasonal predictions for the North Atlantic circulation and Northern Europe, including the UK have now been demonstrated and the potential for seasonal hydrological forecasting in the UK is now being explored. The Hydrological Outlook UK (HOUK: www.hydoutuk.net) is the first operational hydrological forecast system for the UK that delivers monthly outlooks of the water situation for both river flow and groundwater levels. The output from the HOUK are publicly available and used each month by government agencies, practitioners and academics alongside other sources of information such as flood warnings and meteorological forecasts. The HOUK brings together information on current and forecast weather conditions, and river flows, and uses several modelling approaches to explore possible future hydrological conditions. One of the techniques combines ensembles of monthly-resolution seasonal rainfall forecasts provided by the Met Office GloSea5 forecast system with hydrological modelling tools to provide estimates of river flows up to a few months ahead. The approach combines a high resolution, spatially distributed hydrological initial condition (HIC) provided by a hydrological model (Grid-to-Grid) driven by weather observations up to the forecast time origin. Considerable efforts have been made to accommodate the temporal and spatial resolution of the GloSea5 rainfall forecasts (monthly time-step and national-scale) in a spatially distributed forecasting system, leading to the development of a monthly resolution water balance model (WBM) to forecast regional mean river flows for the next 1 and 3 months ahead. The work presented here provides the first assessment of the skill in the HOUK national-scale flow forecasts using an ensemble of rainfall forecasts (hindcasts) from the GloSea5 model (1996 to 2009). The skill in the combined modelling system has been assessed for different seasons and regions of Britain, and compared to what might be achieved using

  1. Observed and Forecasted Intraseasonal Activity of Southwest Monsoon Rainfall over India During 2010, 2011 and 2012

    Science.gov (United States)

    Pattanaik, D. R.; Rathore, L. S.; Kumar, Arun

    2013-12-01

    The monsoon seasons of 2010 and 2011, with almost identical seasonal total rainfall over India from June to September, are associated with slightly different patterns of intraseasonal rainfall fluctuations. Similarly, the year 2012, with relatively less rainfall compared to 2010 and 2011, also witnessed different intraseasonal rainfall fluctuations, leading to drought-like situations over some parts of the country. The present article discusses the forecasting aspect of monsoon activity over India during these 3 years on an extended range time scale (up to 3 weeks) by using the multimodel ensemble (MME), based on operational coupled model outputs from the ECMWF monthly forecasting system and the NCEP's Climate Forecast System (CFS). The average correlation coefficient (CC) of weekly observed all-India rainfall (AIR) and the corresponding MME forecast AIR is found to be significant, above the 98 % level up to 2 weeks (up to 18 days) with a slight positive CC for the week 3 (days 19-25) forecast. However, like the variation of observed intraseasonal rainfall fluctuations during 2010, 2011 and 2012 monsoon seasons, the MME forecast skills of weekly AIR are also found to be different from one another, with the 2012 monsoon season indicating significant CC (above 99 % level) up to week 2 (12-18 days), and also a comparatively higher CC (0.45) during the week 3 forecast (days 19-25). The average CC between observed and forecasted weekly AIR rainfall over four homogeneous regions of India is found to be the lowest over the southern peninsula of India (SPI), and northeast India (NEI) is found to be significant only for the week 1 (days 5-11) forecast. However, the CC is found to be significant over northwest India (NWI) and central India (CEI), at least above the 90 % level up to 18 days, with NWI having slightly better skill compared to the CEI. For the individual monsoon seasons of 2010, 2011 and 2012, there is some variation in CC and other skill scores over the four

  2. Extreme Rainfall Events Over Southern Africa: Assessment of a Climate Model to Reproduce Daily Extremes

    Science.gov (United States)

    Williams, C.; Kniveton, D.; Layberry, R.

    2007-12-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable extreme events, due to a number of factors including extensive poverty, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of a state-of-the-art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of SST anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the UK Meteorological Office Hadley Centre's climate model's domain size are firstly presented. Then simulations of current climate from the model, operating in both regional and global mode, are compared to the MIRA dataset at daily timescales. Thirdly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. Finally, the results from the idealised SST experiments are briefly presented, suggesting associations between rainfall extremes and both local and remote SST anomalies.

  3. 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...

  4. 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

  5. Flood risk reduction and flow buffering as ecosystem services - Part 2: Land use and rainfall intensity effects in Southeast Asia

    Science.gov (United States)

    van Noordwijk, Meine; Tanika, Lisa; Lusiana, Betha

    2017-05-01

    Watersheds buffer the temporal pattern of river flow relative to the temporal pattern of rainfall. This ecosystem service is inherent to geology and climate, but buffering also responds to human use and misuse of the landscape. Buffering can be part of management feedback loops if salient, credible and legitimate indicators are used. The flow persistence parameter Fp in a parsimonious recursive model of river flow (Part 1, van Noordwijk et al., 2017) couples the transmission of extreme rainfall events (1 - Fp), to the annual base-flow fraction of a watershed (Fp). Here we compare Fp estimates from four meso-scale watersheds in Indonesia (Cidanau, Way Besai and Bialo) and Thailand (Mae Chaem), with varying climate, geology and land cover history, at a decadal timescale. The likely response in each of these four to variation in rainfall properties (including the maximum hourly rainfall intensity) and land cover (comparing scenarios with either more or less forest and tree cover than the current situation) was explored through a basic daily water-balance model, GenRiver. This model was calibrated for each site on existing data, before being used for alternative land cover and rainfall parameter settings. In both data and model runs, the wet-season (3-monthly) Fp values were consistently lower than dry-season values for all four sites. Across the four catchments Fp values decreased with increasing annual rainfall, but specific aspects of watersheds, such as the riparian swamp (peat soils) in Cidanau reduced effects of land use change in the upper watershed. Increasing the mean rainfall intensity (at constant monthly totals for rainfall) around the values considered typical for each landscape was predicted to cause a decrease in Fp values by between 0.047 (Bialo) and 0.261 (Mae Chaem). Sensitivity of Fp to changes in land use change plus changes in rainfall intensity depends on other characteristics of the watersheds, and generalisations made on the basis of one or two

  6. The relationship between balance measured with a modified bathroom scale and falls and disability in older adults: a 6-month follow-up study.

    Science.gov (United States)

    Vermeulen, Joan; Neyens, Jacques C L; Spreeuwenberg, Marieke D; van Rossum, Erik; Boessen, April B C G; Sipers, Walther; de Witte, Luc P

    2015-05-27

    There are indications that older adults who suffer from poor balance have an increased risk for adverse health outcomes, such as falls and disability. Monitoring the development of balance over time enables early detection of balance decline, which can identify older adults who could benefit from interventions aimed at prevention of these adverse outcomes. An innovative and easy-to-use device that can be used by older adults for home-based monitoring of balance is a modified bathroom scale. The objective of this paper is to study the relationship between balance scores obtained with a modified bathroom scale and falls and disability in a sample of older adults. For this 6-month follow-up study, participants were recruited via physiotherapists working in a nursing home, geriatricians, exercise classes, and at an event about health for older adults. Inclusion criteria were being aged 65 years or older, being able to stand on a bathroom scale independently, and able to provide informed consent. A total of 41 nursing home patients and 139 community-dwelling older adults stepped onto the modified bathroom scale three consecutive times at baseline to measure their balance. Their mean balance scores on a scale from 0 to 16 were calculated-higher scores indicated better balance. Questionnaires were used to study falls and disability at baseline and after 6 months of follow-up. The cross-sectional relationship between balance and falls and disability at baseline was studied using t tests and Spearman rank correlations. Univariate and multivariate logistic regression analyses were conducted to study the relationship between balance measured at baseline and falls and disability development after 6 months of follow-up. A total of 128 participants with complete datasets--25.8% (33/128) male-and a mean age of 75.33 years (SD 6.26) were included in the analyses of this study. Balance scores of participants who reported at baseline that they had fallen at least once in the past 6

  7. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    Science.gov (United States)

    Overeem, Aart; Uijlenhoet, Remko; Leijnse, Hidde

    2016-04-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. We present a rainfall retrieval algorithm, which is employed to obtain rainfall maps from microwave links in a cellular communication network. We compare these rainfall maps to gauge-adjusted radar rainfall maps. The microwave link data set, as well as the developed code, a package in the open source scripting language "R", are freely available at GitHub (https://github.com/overeem11/RAINLINK). The purpose of this presentation is to promote rainfall mapping utilizing microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.

  8. National Spatiotemporal Exposure Surface for NO2: Monthly Scaling of a Satellite-Derived Land-Use Regression, 2000-2010.

    Science.gov (United States)

    Bechle, Matthew J; Millet, Dylan B; Marshall, Julian D

    2015-10-20

    Land-use regression (LUR) is widely used for estimating within-urban variability in air pollution. While LUR has recently been extended to national and continental scales, these models are typically for long-term averages. Here we present NO2 surfaces for the continental United States with excellent spatial resolution (∼100 m) and monthly average concentrations for one decade. We investigate multiple potential data sources (e.g., satellite column and surface estimates, high- and standard-resolution satellite data, and a mechanistic model [WRF-Chem]), approaches to model building (e.g., one model for the whole country versus having separate models for urban and rural areas, monthly LURs versus temporal scaling of a spatial LUR), and spatial interpolation methods for temporal scaling factors (e.g., kriging versus inverse distance weighted). Our core approach uses NO2 measurements from U.S. EPA monitors (2000-2010) to build a spatial LUR and to calculate spatially varying temporal scaling factors. The model captures 82% of the spatial and 76% of the temporal variability (population-weighted average) of monthly mean NO2 concentrations from U.S. EPA monitors with low average bias (21%) and error (2.4 ppb). Model performance in absolute terms is similar near versus far from monitors, and in urban, suburban, and rural locations (mean absolute error 2-3 ppb); since low-density locations generally experience lower concentrations, model performance in relative terms is better near monitors than far from monitors (mean bias 3% versus 40%) and is better for urban and suburban locations (1-6%) than for rural locations (78%, reflecting the relatively clean conditions in many rural areas). During 2000-2010, population-weighted mean NO2 exposure decreased 42% (1.0 ppb [∼5.2%] per year), from 23.2 ppb (year 2000) to 13.5 ppb (year 2010). We apply our approach to all U.S. Census blocks in the contiguous United States to provide 132 months of publicly available, high

  9. Will seasonally dry tropical forests be sensitive or resistant to future changes in rainfall regimes?

    Science.gov (United States)

    Allen, Kara; Dupuy, Juan Manuel; Gei, Maria G.; Hulshof, Catherine; Medvigy, David; Pizano, Camila; Salgado-Negret, Beatriz; Smith, Christina M.; Trierweiler, Annette; Van Bloem, Skip J.; Waring, Bonnie G.; Xu, Xiangtao; Powers, Jennifer S.

    2017-02-01

    Seasonally dry tropical forests (SDTF) are located in regions with alternating wet and dry seasons, with dry seasons that last several months or more. By the end of the 21st century, climate models predict substantial changes in rainfall regimes across these regions, but little is known about how individuals, species, and communities in SDTF will cope with the hotter, drier conditions predicted by climate models. In this review, we explore different rainfall scenarios that may result in ecological drought in SDTF through the lens of two alternative hypotheses: 1) these forests will be sensitive to drought because they are already limited by water and close to climatic thresholds, or 2) they will be resistant/resilient to intra- and inter-annual changes in rainfall because they are adapted to predictable, seasonal drought. In our review of literature that spans microbial to ecosystem processes, a majority of the available studies suggests that increasing frequency and intensity of droughts in SDTF will likely alter species distributions and ecosystem processes. Though we conclude that SDTF will be sensitive to altered rainfall regimes, many gaps in the literature remain. Future research should focus on geographically comparative studies and well-replicated drought experiments that can provide empirical evidence to improve simulation models used to forecast SDTF responses to future climate change at coarser spatial and temporal scales.

  10. 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...

  11. 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.

  12. Statistical Testing of Dynamically Downscaled Rainfall Data for the East Coast of Australia

    Science.gov (United States)

    Parana Manage, Nadeeka; Lockart, Natalie; Willgoose, Garry; Kuczera, George

    2015-04-01

    This study performs a validation of statistical properties of downscaled climate data, concentrating on the rainfall which is required for hydrology predictions used in reservoir simulations. The data sets used in this study have been produced by the NARCliM (NSW/ACT Regional Climate Modelling) project which provides a dynamically downscaled climate dataset for South-East Australia at 10km resolution. NARCliM has used three configurations of the Weather Research Forecasting Regional Climate Model and four different GCMs (MIROC-medres 3.2, ECHAM5, CCCMA 3.1 and CSIRO mk3.0) from CMIP3 to perform twelve ensembles of simulations for current and future climates. Additionally to the GCM-driven simulations, three control run simulations driven by the NCEP/NCAR reanalysis for the entire period of 1950-2009 has also been performed by the project. The validation has been performed in the Upper Hunter region of Australia which is a semi-arid to arid region 200 kilometres North-West of Sydney. The analysis used the time series of downscaled rainfall data and ground based measurements for selected Bureau of Meteorology rainfall stations within the study area. The initial testing of the gridded rainfall was focused on the autoregressive characteristics of time series because the reservoir performance depends on long-term average runoffs. A correlation analysis was performed for fortnightly, monthly and annual averaged time resolutions showing a good statistical match between reanalysis and ground truth. The spatial variation of the statistics of gridded rainfall series were calculated and plotted at the catchment scale. The spatial correlation analysis shows a poor agreement between NARCliM data and ground truth at each time resolution. However, the spatial variability plots show a strong link between the statistics and orography at the catchment scale.

  13. Rainfall Distributions in Sri Lanka in Time and Space: An Analysis Based on Daily Rainfall Data

    Directory of Open Access Journals (Sweden)

    T. P. Burt

    2014-09-01

    Full Text Available Daily rainfall totals are analyzed for the main agro-climatic zones of Sri Lanka for the period 1976–2006. The emphasis is on daily rainfall rather than on longer-period totals, in particular the number of daily falls exceeding given threshold totals. For one station (Mapalana, where a complete daily series is available from 1950, a longer-term perspective on changes over half a century is provided. The focus here is particularly on rainfall in March and April, given the sensitivity of agricultural decisions to early southwest monsoon rainfall at the beginning of the Yala cultivation season but other seasons are also considered, in particular the northeast monsoon. Rainfall across Sri Lanka over three decades is investigated in relation to the main atmospheric drivers known to affect climate in the region: sea surface temperatures in the Pacific and Indian Oceans, of which the former are shown to be more important. The strong influence of El Niño and La Niña phases on various aspects of the daily rainfall distribution in Sri Lanka is confirmed: positive correlations with Pacific sea-surface temperatures during the north east monsoon and negative correlations at other times. It is emphasized in the discussion that Sri Lanka must be placed in its regional context and it is important to draw on regional-scale research across the Indian subcontinent and the Bay of Bengal.

  14. Prospects for Improved Forecasts of Weather and Short-Term Climate Variability on Subseasonal (2-Week to 2-Month) Times Scales

    Science.gov (United States)

    Schubert, Siegfried; Dole, Randall; vandenDool, Huug; Suarez, Max; Waliser, Duane

    2002-01-01

    This workshop, held in April 2002, brought together various Earth Sciences experts to focus on the subseasonal prediction problem. While substantial advances have occurred over the last few decades in both weather and seasonal prediction, progress in improving predictions on these intermediate time scales (time scales ranging from about two weeks to two months) has been slow. The goals of the workshop were to get an assessment of the "state of the art" in predictive skill on these time scales, to determine the potential sources of "untapped" predictive skill, and to make recommendations for a course of action that will accelerate progress in this area. One of the key conclusions of the workshop was that there is compelling evidence for predictability at forecast lead times substantially longer than two weeks. Tropical diabatic heating and soil wetness were singled out as particularly important processes affecting predictability on these time scales. Predictability was also linked to various low-frequency atmospheric "phenomena" such as the annular modes in high latitudes (including their connections to the stratosphere), the Pacific/North American (PNA) pattern, and the Madden Julian Oscillation (MJO). The latter, in particular, was highlighted as a key source of untapped predictability in the tropics and subtropics, including the Asian and Australian monsoon regions.

  15. A space-time multifractal analysis on radar rainfall sequences from central Poland

    Science.gov (United States)

    Licznar, Paweł; Deidda, Roberto

    2014-05-01

    Rainfall downscaling belongs to most important tasks of modern hydrology. Especially from the perspective of urban hydrology there is real need for development of practical tools for possible rainfall scenarios generation. Rainfall scenarios of fine temporal scale reaching single minutes are indispensable as inputs for hydrological models. Assumption of probabilistic philosophy of drainage systems design and functioning leads to widespread application of hydrodynamic models in engineering practice. However models like these covering large areas could not be supplied with only uncorrelated point-rainfall time series. They should be rather supplied with space time rainfall scenarios displaying statistical properties of local natural rainfall fields. Implementation of a Space-Time Rainfall (STRAIN) model for hydrometeorological applications in Polish conditions, such as rainfall downscaling from the large scales of meteorological models to the scale of interest for rainfall-runoff processes is the long-distance aim of our research. As an introduction part of our study we verify the veracity of the following STRAIN model assumptions: rainfall fields are isotropic and statistically homogeneous in space; self-similarity holds (so that, after having rescaled the time by the advection velocity, rainfall is a fully homogeneous and isotropic process in the space-time domain); statistical properties of rainfall are characterized by an "a priori" known multifractal behavior. We conduct a space-time multifractal analysis on radar rainfall sequences selected from the Polish national radar system POLRAD. Radar rainfall sequences covering the area of 256 km x 256 km of original 2 km x 2 km spatial resolution and 15 minutes temporal resolution are used as study material. Attention is mainly focused on most severe summer convective rainfalls. It is shown that space-time rainfall can be considered with a good approximation to be a self-similar multifractal process. Multifractal

  16. Dynamic Hydrological Modeling in Drylands with TRMM Based Rainfall

    Directory of Open Access Journals (Sweden)

    Elena Tarnavsky

    2013-12-01

    Full Text Available This paper introduces and evaluates DryMOD, a dynamic water balance model of the key hydrological process in drylands that is based on free, public-domain datasets. The rainfall model of DryMOD makes optimal use of spatially disaggregated Tropical Rainfall Measuring Mission (TRMM datasets to simulate hourly rainfall intensities at a spatial resolution of 1-km. Regional-scale applications of the model in seasonal catchments in Tunisia and Senegal characterize runoff and soil moisture distribution and dynamics in response to varying rainfall data inputs and soil properties. The results highlight the need for hourly-based rainfall simulation and for correcting TRMM 3B42 rainfall intensities for the fractional cover of rainfall (FCR. Without FCR correction and disaggregation to 1 km, TRMM 3B42 based rainfall intensities are too low to generate surface runoff and to induce substantial changes to soil moisture storage. The outcomes from the sensitivity analysis show that topsoil porosity is the most important soil property for simulation of runoff and soil moisture. Thus, we demonstrate the benefit of hydrological investigations at a scale, for which reliable information on soil profile characteristics exists and which is sufficiently fine to account for the heterogeneities of these. Where such information is available, application of DryMOD can assist in the spatial and temporal planning of water harvesting according to runoff-generating areas and the runoff ratio, as well as in the optimization of agricultural activities based on realistic representation of soil moisture conditions.

  17. 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.

  18. 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.

  19. A statistical downscaling model for summer rainfall over Pakistan

    Science.gov (United States)

    Kazmi, Dildar Hussain; Li, Jianping; Ruan, Chengqing; Zhao, Sen; Li, Yanjie

    2016-10-01

    A statistical approach is utilized to construct an interannual model for summer (July-August) rainfall over the western parts of South Asian Monsoon. Observed monthly rainfall data for selected stations of Pakistan for the last 55 years (1960-2014) is taken as predictand. Recommended climate indices along with the oceanic and atmospheric data on global scales, for the period April-June are employed as predictors. First 40 years data has been taken as training period and the rest as validation period. Cross-validation stepwise regression approach adopted to select the robust predictors. Upper tropospheric zonal wind at 200 hPa over the northeastern Atlantic is finally selected as the best predictor for interannual model. Besides, the next possible candidate `geopotential height at upper troposphere' is taken as the indirect predictor for being a source of energy transportation from core region (northeast Atlantic/western Europe) to the study area. The model performed well for both the training as well as validation period with correlation coefficient of 0.71 and tolerable root mean square errors. Cross-validation of the model has been processed by incorporating JRA-55 data for potential predictors in addition to NCEP and fragmentation of study period to five non-overlapping test samples. Subsequently, to verify the outcome of the model on physical grounds, observational analyses as well as the model simulations are incorporated. It is revealed that originating from the jet exit region through large vorticity gradients, zonally dominating waves may transport energy and momentum to the downstream areas of west-central Asia, that ultimately affect interannual variability of the specific rainfall. It has been detected that both the circumglobal teleconnection and Rossby wave propagation play vital roles in modulating the proposed mechanism.

  20. General Rainfall Patterns in Indonesia and the Potential Impacts of Local Seas on Rainfall Intensity

    Directory of Open Access Journals (Sweden)

    Han Soo Lee

    2015-04-01

    Full Text Available The relationships between observed rainfall, El Niño/Southern Oscillation (ENSO and sea surface temperature (SST variations in the Pacific and Indian Oceans were analyzed using a 1° latitude–longitude grid over Indonesia. The Global Summary of the Day rainfall records provide 26 years of rainfall data (January 1985 to August 2010 for 23 stations throughout the Indonesian islands. The ENSO and SST variations were calculated using the Multivariate ENSO Index (MEI, the Pacific Decadal Oscillation (PDO, NINO1 + 2, NINO3, NINO3.4, NINO4, the Dipole Mode Index (DMI for the Indian Ocean Dipole (IOD, and Indian Ocean Basin-wide (IOBW index. The results show that the rainfall in the southern Sumatra and southern Java Islands, which face the Indian Ocean, was positively correlated with the negative IOD, whereas the rainfall in northwestern Sumatra was positively correlated with the positive IOD. In eastern Indonesia, the rainfall was positively correlated with La Niña. The PDO index was also strongly correlated with the rainfall in this region. In central Indonesia, seasonal variations due to monsoons are predominant, and the rainfall exhibited strong negative and positive correlations with the MEI and NINO.WEST, respectively, indicating that high rainfall occurred during strong La Niña episodes. The highly negative and positive correlations with the MEI and NINO.WEST, respectively, in central Indonesia led us to analyze the impacts of Indonesian seas on the rainfall in the region. Using four synoptic-scale scenarios, we investigated the relative residence time of Indonesian seawater along the pathways associated with the Pacific-Indian hydraulic head difference. The results show that when both the western Pacific and eastern Indian Oceans are warm (positive NINO.WEST and negative DMI, the rainfall intensity over central Indonesia is strongest. This increase is explained by the relationship between the residence time of Indonesian seawater and the

  1. 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).

  2. 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.

  3. 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.

  4. Trends in total rainfall, heavy rain events, and number of dry days in San Juan, Puerto Rico, 1955-2009

    Directory of Open Access Journals (Sweden)

    Pablo A. Méndez-Lázaro

    2014-06-01

    Full Text Available Climate variability is a threat to water resources on a global scale and in tropical regions in particular. Rainfall events and patterns are associated worldwide with natural disasters like mudslides and landslides, meteorological phenomena like hurricanes, risks/hazards including severe storms and flooding, and health effects like vector-borne and waterborne diseases. Therefore, in the context of global change, research on rainfall patterns and their variations presents a challenge to the scientific community. The main objective of this research was to analyze recent trends in precipitation in the San Juan metropolitan area in Puerto Rico and their relationship with regional and global climate variations. The statistical trend analysis of precipitation was performed with the nonparametric Mann-Kendall test. All stations showed positive trends of increasing annual rainfall between 1955 and 2009. The winter months of January and February had an increase in monthly rainfall, although winter is normally a dry season on the island. Regarding dry days, we found an annual decreasing trend, also specifically in winter. In terms of numbers of severe rainfall events described as more than 78 mm in 24 hours, 63 episodes have occurred in the San Juan area in the last decade, specifically in the 2000-2009 time frame, with an average of 6 severe events per year. The majority of the episodes occurred in summer, more frequently in August and September. These results can be seen as a clear example of the complexity of spatial and temporal of rainfall distribution over a tropical city.

  5. 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.

  6. 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.

  7. 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.

  8. Predictability and prediction of summer rainfall in the arid and semi-arid regions of China

    Science.gov (United States)

    Xing, Wen; Wang, Bin

    2016-09-01

    Northwest China (NWC) is an arid and semi-arid region where climate variability and environmental changes are sensitive to precipitation. The present study explores sources and limits of predictability of summer precipitation over NWC using the predictable mode analysis (PMA) of percentage of rainfall anomaly data. Two major modes of NWC summer rainfall variability are identified which are tied to Eurasian continental scale precipitation variations. The first mode features wet northern China corresponding to dry central Siberia and wet Mongolia, which is mainly driven by tropical Pacific sea surface temperature anomalies (SSTA). The second mode features wet western China reflecting wet Central Asia and dry Ural-western Siberia, which strongly links to Indian Ocean SSTA. Anomalous land warming over Eurasia also provides important precursors for the two modes. The cross-validated hindcast results demonstrate these modes can be predicted with significant correlation skills, suggesting that they may be considered as predictable modes. The domain averaged temporal correlation coefficient (TCC) skill during 1979 to 2015 using 0-month (1-month) lead models is 0.39 (0.35), which is considerably higher than dynamical models' multi-model ensemble mean skill (-0.02). Maximum potential attainable prediction skills are also estimated and discussed. The result illustrates advantage of PMA in predicting rainfall over dry land areas and large room for dynamical model improvement. However, secular changes of predictors need to be detected continuously in order to make practical useful prediction.

  9. The Efficacy of Arabic Version of the Developmental Assessment of Young Children Second Edition (DAYC-2) Scale in Detecting Developmental Delay among Jordanian Children Aged Birth to 71 Months

    Science.gov (United States)

    Saleh, Rawan M. Abu; Smadi, Jamil M.

    2017-01-01

    This study aimed to assess the efficacy of the developmental assessment of young children second edition (DAYC-2) Scale in detecting Developmental Delay among Jordanian children aged birth to 71 months. Firstly, the scale was translated and reviewed for language and cultural appropriateness. Secondly, the Arabic Jordanian version of the scale was…

  10. 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.

  11. Observed and projected urban extreme rainfall events in India

    Science.gov (United States)

    Ali, Haider; Mishra, Vimal; Pai, D. S.

    2014-11-01

    We examine changes in extreme rainfall indices over 57 major urban areas in India under the observed (1901-2010) and projected future climate (2010-2060). Between 1901 and 2010, only four out of the total 57 urban areas showed a significant (p-value urban areas experienced significant increases in the extreme rainfall indices for the different periods. Moreover, rainfall maxima for 1-10 day durations and at 100 year return period did not change significantly over the majority of urban areas in the post-1955 period. Results do not indicate any significant change (p > 0.05) in the pooled mean and distribution of the extreme rainfall indices for the pre- and post-1983 periods revealing an insignificant role of urbanization on rainfall extremes in the major urban areas in India. We find that at the majority of urban areas changes in the extreme rainfall indices are driven by large scale climate variability. Regional Climate Models (RCMs) that participated in the CORDEX-South Asia program showed a significant bias in the monsoon maximum rainfall and rainfall maxima at 100 year return period for the majority of urban areas. For instance, most of the models fail to simulate rainfall maxima within ±10% bias, which can be considered appropriate for a storm water design at many urban areas. Rainfall maxima at 1-3 day durations and 100 year return period is projected to increase significantly under the projected future climate at the majority of urban areas in India. The number of urban areas with significant increases in rainfall maxima under the projected future climate is far larger than the number of areas that experienced significant changes in the historic climate (1901-2010), which warrants a careful attention for urban storm water infrastructure planning and management.

  12. Characterization of nested watershed hydrologic response from high-resolution rainfall and runoff data in the Baltimore Ecosystem Study LTER

    Science.gov (United States)

    Miller, A. J.; Lindner, G. A.; Smith, J. A.; Baeck, M. L.; Welty, C.; Miller, J.; Meierdiercks, K. L.

    2011-12-01

    This presentation reports initial results from analysis of data collected at a set of six stream gages representing three nested watershed scales (1-2 km2, 5-6 km2, 14 km2) in Dead Run, a highly impervious suburban watershed in Baltimore County, MD, USA. Streamflow data collected at 5-minute temporal resolution during the period 2007-2011 are compared with 1-km2 gridded and watershed-average precipitation data with 15-minute temporal resolution provided by the HydroNEXRAD project for the Baltimore metropolitan area. The period of overlapping precipitation and runoff data currently available for all six nested watersheds includes calendar years 2008 and 2009. Analyses include mass balance for monthly time periods as well as individual storm events; comparison of hydrologic response among nested watersheds of similar scale and across scales; and characterization of spatial and temporal patterns in storm-period rainfall, drainage network structure, watershed morphometry, and urban infrastructure as potential influences on patterns of hydrologic response. We attempted to isolate the effects of watershed characteristics by selecting a subset of storm events with a rainfall "pulse" defined by minimum accumulation of ~10 mm and >80% of storm-total rainfall arriving within a one-hour period at all six nested subwatersheds. Hydrographs were compared to assess characteristic shape, runoff ratio, and timing. We also examined several longer, more complex storm events with multiple rainfall pulses in order to observe the response at multiple watershed scales. Despite the constraints imposed on storm structure we find that even slight variations in the spatial and temporal distribution of rainfall may be associated with major differences in watershed response (volume and timing) at the 1-2 km2 and 5-6 km2 scales. Some of these variations would be difficult to explain without availability of high-resolution rainfall data. In multiple events we observe that the 5-6 km2 watersheds

  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. The bi-decadal rainfall cycle, Southern Annular Mode and tropical cyclones over the Limpopo River Basin, southern Africa

    CSIR Research Space (South Africa)

    Malherbe, J

    2014-06-01

    Full Text Available The association between bi-decadal rainfall variability over southern Africa and the rainfall contributed by tropical cyclonic systems from the Southwest Indian Ocean (SWIO) provides a potential means towards understanding decadal-scale variability...

  15. An Evaluation of the Italian Version of the Yale Food Addiction Scale in Obese Adult Inpatients Engaged in a 1-Month-Weight-Loss Treatment.

    Science.gov (United States)

    Ceccarini, Martina; Manzoni, Gian Mauro; Castelnuovo, Gianluca; Molinari, Enrico

    2015-11-01

    Addiction is a compulsive need for and use of a specific substance leading to a habit, tolerance, and psychophysiological symptoms. Excessive food consumption is similar to that of substance addiction. Some individuals who have trouble losing weight display addictive eating symptoms. To investigate food addiction in a sample of obese adults referred to hospital for a 1-month-weight-loss treatment. The Italian version of the Yale Food Addiction Scale (YFAS-16) was used as a screening tool in 88 obese inpatients. The construct validity of the YFAS-16 was assessed by testing its correlations with measures of binge eating (Binge Eating Scale), impulsiveness (Barratt Impulsiveness Scale), and emotional dysregulation (Difficulties in Emotion Regulation Scale). 34.1% of our sample was diagnosed with YFAS food addiction. Such diagnosis was also supported by strong associations between FA and psychological and behavioral features, typically descriptive of classic addiction. Patients who endorsed the YFAS-16 criteria for food addiction (FA) had significantly higher binge eating levels, greater emotional dysregulation, and nonacceptance of negative feelings; they lacked goal-oriented behavior, had little impulse control, had difficulty in emotion recognition, and attentional impulsivity; and they were unable to concentrate and lacked inhibitory control behavior, unlike participants who did not meet the FA criteria. Further research is needed to support the reliability of the YFAS-16. This measure has the potential to be applied in epidemiological research, estimating the prevalence of FA within the Italian population and to assess new treatments' efficacy for obese patients with food addiction symptoms seeking weight-loss treatments.

  16. East coast lows, atmospheric blocking and rainfall: A Tasmanian perspective

    Energy Technology Data Exchange (ETDEWEB)

    Pook, Michael; Risbey, James; McIntosh, Peter, E-mail: Mike.Pook@csiro.a [Centre for Australian Weather and Climate Research (A partnership between CSIRO and Bureau of Meteorology), Castray Esplanade, Hobart, Tasmania 7000 (Australia)

    2010-08-15

    Although the term 'east coast low' is normally associated with intense cyclones near the east coast of mainland Australia, cutoff lows of similar type also affect Tasmania. This paper demonstrates that the cutoff low is a major source of rainfall for the agricultural districts and water catchments of eastern Tasmania. In particular, an analysis of synoptic systems and daily rainfall reveals that cutoff lows are responsible for almost 50% of April to October rainfall in parts of the northeast and a slightly lower proportion in the southeast. The other large contribution to rainfall is from frontal systems but the relative effects of the various synoptic types vary widely across the state as a result of the complex topography. Cutoff lows commonly form the cyclonic portion of a blocking dipole which can have opposing influences on Tasmanian rainfall. The high latitude anticyclone suppresses rainfall in western and southwestern Tasmania, while the cutting off of a relatively small cyclonic component equatorwards of the high frequently results in enhanced rainfall over eastern Tasmania. Results from two climate models indicate that the accurate simulation of blocking and cutoff lows remains difficult to achieve and this has implications for projections of Tasmanian rainfall on seasonal and longer time scales.

  17. 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

  18. 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

  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. Analysis of extreme rainfall in the Ebre Observatory (Spain)

    Science.gov (United States)

    Pérez-Zanón, Núria; Casas-Castillo, M. Carmen; Rodríguez-Solà, Raúl; Peña, Juan Carlos; Rius, Anna; Solé, J. Germán; Redaño, Ángel

    2016-05-01

    The relationship between maximum rainfall rates for time intervals between 5 min and 24 h has been studied from almost a century (1905-2003) of rainfall data registered in the Ebre Observatory (Tarragona, Spain). Intensity-duration-frequency (IDF) curves and their master equation for every return period in the location have been obtained, as well as the probable maximum precipitation (PMP) for all the considered durations. In particular, the value of the 1-day PMP has resulted to be 415 mm, very similar to previous estimations of this variable for the same location. Extreme rainfall events recorded in this period have been analyzed and classified according to their temporal scale. Besides the three main classes of cases corresponding to the main meteorological scales, local, mesoscale, and synoptic, a fourth group constituted by complex events with high-intensity rates for a large range of durations has been identified also, indicating the contribution of different scale meteorological processes acting together in the origin of the rainfall. A weighted intensity index taking into account the maximum rainfall rate in representative durations of every meteorological scale has been calculated for every extreme rainfall event in order to reflect their complexity.

  1. Oceanographic Monthly Summary

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic Monthly Summary contains sea surface temperature (SST) analyses on both regional and ocean basin scales for the Atlantic, Pacific, and Indian Oceans....

  2. Applying econometric techniques to hydrological problems in a large basin: Quantifying the rainfall-discharge relationship in the Burdekin, Queensland, Australia

    Science.gov (United States)

    Jarvis, Diane; Stoeckl, Natalie; Chaiechi, Taha

    2013-07-01

    This study seeks to explore the relationship between rainfall and river discharge within a large river basin flowing into the waters surrounding the Great Barrier Reef (GBR), and to investigate the best method of measuring the relationship. This aim is addressed by focusing on three specific research questions: (A) Has there been any evidence that global climate change has impacted on either rainfall or river discharge resulting in any change to the relationship between these variables over time? (B) What is the best measure of rainfall to be used to quantify the rainfall-discharge relationship, including the optimal number of rain stations to be included in the sample? (C) What is the optimal temporal scale for measuring the relationship (ranging from fine scale monthly data, medium scale quarterly data, and coarse scale annual data)? Modern econometric time series techniques are utilised, and compared with results using an alternate technique developed by researchers from the bio-physical sciences; the widely used Thiessen Polygon method. Firstly, stationarity testing, using econometric unit root tests, did not find evidence to suggest that the data are non-stationary. Evidently, climate change has not had a measurable impact on rainfall or river discharge in the region during the period covered by this study. Secondly, the analysis shows that the when dealing with fairly simple models with a fairly small number of explanatory variables, those which best represent the river-discharge relationship are those using the coarser scales (both geographic and temporal). In other words, stronger and more robust results are derived from models using fewer rain stations, and annual data (rather than quarterly or monthly data). This approach provides a viable alternative that may be very useful in data-poor environments when it is not possible to use other more data-hungry modelling approaches. The econometric models provided a better explanation of the relationship than the

  3. 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.

  4. Feeling the Pulse of the Stratosphere: An Emerging Opportunity for Predicting Continental-Scale Cold Air Outbreaks One Month in Advance

    Science.gov (United States)

    Cai, Ming

    2016-04-01

    Extreme weather events such as cold air outbreaks (CAOs) pose great threats to human life and socioeconomic well-being of the modern society. In the past, our capability to predict their occurrences is constrained by the 2-week predictability limit for weather. We demonstrate here for the first time that a rapid increase of air mass transported into the polar stratosphere, referred to as "the pulse of the stratosphere (PULSE)", can often be predicted with a useful skill 4-6 weeks in advance by operational forecast models. We further show that the probability of the occurrence of continental-scale CAOs in mid-latitudes increases substantially above the normal condition within a short time period from one week before to 1-2 weeks after the peak day of a PULSE event. In particular, we reveal that the three massive CAOs over North America in January and February of 2014 were preceded by three episodes of extreme mass transport into the polar stratosphere with peak intensities reaching a trillion tons per day, twice of that on an average winter day. Therefore, our capability to predict the PULSEs with operational forecast models, in conjunction with its linkage to continental-scale CAOs, opens up a new opportunity for 30-day forecasts of continental-scale CAOs, such as those occurring over North America in the 2013-14 winter. A real time forecast experiment inaugurated in the winter of 2014-15 has given support to the idea that it is feasible to forecast CAOs one month in advance.

  5. Feeling the pulse of the stratosphere: An emerging opportunity for predicting continental-scale cold air outbreaks one month in advance

    Science.gov (United States)

    Cai, M.; Yu, Y.

    2016-12-01

    Extreme weather events such as cold air outbreaks (CAOs) pose great threats to human life and socioeconomic well-being of the modern society. In the past, our capability to predict their occurrences is constrained by the 2-week predictability limit for weather. We demonstrate here for the first time that a rapid increase of air mass transported into the polar stratosphere, referred to as "the pulse of the stratosphere (PULSE)", can often be predicted with a useful skill 4-6 weeks in advance by operational forecast models. We further show that the probability of the occurrence of continental-scale CAOs in mid-latitudes increases substantially above the normal condition within a short time period from one week before to 1-2 weeks after the peak day of a PULSE event. In particular, we reveal that the three massive CAOs over North America in January and February of 2014 were preceded by three episodes of extreme mass transport into the polar stratosphere with peak intensities reaching a trillion tons per day, twice of that on an average winter day. Therefore, our capability to predict the PULSEs with operational forecast models, in conjunction with its linkage to continental-scale CAOs, opens up a new opportunity for 30-day forecasts of continental-scale CAOs, such as those occurring over North America in the 2013-14 winter. A real time forecast experiment inaugurated in the winter of 2014-15 has given support to the idea that it is feasible to forecast CAOs one month in advance.

  6. 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.

  7. Comparative Study of Monsoon Rainfall Variability over India and the Odisha State

    Directory of Open Access Journals (Sweden)

    K C Gouda

    2017-10-01

    Full Text Available Indian summer monsoon (ISM plays an important role in the weather and climate system over India. The rainfall during monsoon season controls many sectors from agriculture, food, energy, and water, to the management of disasters. Being a coastal province on the eastern side of India, Odisha is one of the most important states affected by the monsoon rainfall and associated hydro-meteorological systems. The variability of monsoon rainfall is highly unpredictable at multiple scales both in space and time. In this study, the monsoon variability over the state of Odisha is studied using the daily gridded rainfall data from India Meteorological Department (IMD. A comparative analysis of the behaviour of monsoon rainfall at a larger scale (India, regional scale (Odisha, and sub-regional scale (zones of Odisha is carried out in terms of the seasonal cycle of monsoon rainfall and its interannual variability. It is seen that there is no synchronization in the seasonal monsoon category (normal/excess/deficit when analysed over large (India and regional (Odisha scales. The impact of El Niño, La Niña, and the Indian Ocean Dipole (IOD on the monsoon rainfall at both scales (large scale and regional scale is analysed and compared. The results show that the impact is much more for rainfall over India, but it has no such relation with the rainfall over Odisha. It is also observed that there is a positive (negative relation of the IOD with the seasonal monsoon rainfall variability over Odisha (India. The correlation between the IAV of monsoon rainfall between the large scale and regional scale was found to be 0.46 with a phase synchronization of 63%. IAV on a sub-regional scale is also presented.

  8. 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

  9. Probabilistic forecasts based on radar rainfall uncertainty

    Science.gov (United States)

    Liguori, S.; Rico-Ramirez, M. A.

    2012-04-01

    gauges location, and then interpolated back onto the radar domain, in order to obtain probabilistic radar rainfall fields in real time. The deterministic nowcasting model integrated in the STEPS system [7-8] has been used for the purpose of propagating the uncertainty and assessing the benefit of implementing the radar ensemble generator for probabilistic rainfall forecasts and ultimately sewer flow predictions. For this purpose, events representative of different types of precipitation (i.e. stratiform/convective) and significant at the urban catchment scale (i.e. in terms of sewer overflow within the urban drainage system) have been selected. As high spatial/temporal resolution is required to the forecasts for their use in urban areas [9-11], the probabilistic nowcasts have been set up to be produced at 1 km resolution and 5 min intervals. The forecasting chain is completed by a hydrodynamic model of the urban drainage network. The aim of this work is to discuss the implementation of this probabilistic system, which takes into account the radar error to characterize the forecast uncertainty, with consequent potential benefits in the management of urban systems. It will also allow a comparison with previous findings related to the analysis of different approaches to uncertainty estimation and quantification in terms of rainfall [12] and flows at the urban scale [13]. Acknowledgements The authors would like to acknowledge the BADC, the UK Met Office and Dr. Alan Seed from the Australian Bureau of Meteorology for providing the radar data and the nowcasting model. The authors acknowledge the support from the Engineering and Physical Sciences Research Council (EPSRC) via grant EP/I012222/1.

  10. 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.

  11. Comparison of Gridded and Measured Rainfall Data for Basin-scale Hydrological Studies Comparación de Datos de Precipitación Grillados y Medidos para Estudios Hidrológicos a Escala de Cuenca

    Directory of Open Access Journals (Sweden)

    Enrique Muñoz

    2011-09-01

    Full Text Available Global gridded climatological (GGC datasets, including precipitation and temperature, are becoming more and more precise, accessible, and common, but the utility of these datasets and their limits for hydrological research are still not well determined. In this paper, we compare the performance of two hydrological models that are identical in structure but built with two different inputs: rainfall from rain gauge stations and from a GGC dataset. The objective is to evaluate the utility of gridded datasets in water resource availability studies mainly for hydroelectric and agricultural purposes. The Andean basin of the Laja River, located in south-central Chile, was chosen for this study. It was based on an 18-yr simulation, and it was concluded that i with gridded climatological datasets in a monthly water balance model, it is possible to reproduce the behavior of an Andean basin with good goodness-of-fit, but with worse results than when using inputs from rain gauges; ii the amount of rainfall in gridded datasets in the Andean area of the Laja basin is underestimated and damped, an effect which is transferred to the simulated flows; and iii regarding the main activities in the Laja basin, global gridded datasets are useful for hydrological studies with agricultural purposes prior to a treatment that considers the orographic effect. On the other hand, these datasets are useless for hydroelectric purposes due to the large underestimation of peak flows obtained during the rainy season.Datos grillados a escala mundial como precipitación y temperatura están siendo cada vez más precisos, accesibles y comunes, pero la utilidad de estos datos y sus limitaciones para estudios hidrológicos, todavía no están bien definidas. En este trabajo se compara el comportamiento de dos modelos hidrológicos, idénticos en estructura, pero construidos con dos entradas diferentes: la precipitación proveniente de estaciones pluviométricas y la precipitaci

  12. Influence of Northwest Cloudbands on Southwest Australian Rainfall

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    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.

  13. Evaluating rainfall kinetic energy - intensity relationships with observed disdrometric data

    Science.gov (United States)

    Angulo-Martinez, Marta; Begueria, Santiago; Latorre, Borja

    2016-04-01

    Rainfall kinetic energy is required for determining erosivity, the ability of rainfall to detach soil particles and initiate erosion. Its determination relay on the use of disdrometers, i.e. devices capable of measuring the drop size distribution and velocity of falling raindrops. In the absence of such devices, rainfall kinetic energy is usually estimated with empirical expressions relating rainfall energy and intensity. We evaluated the performance of 14 rainfall energy equations in estimating one-minute rainfall energy and event total energy, in comparison with observed data from 821 rainfall episodes (more than 100 thousand one-minute observations) by means of an optical disdrometer. In addition, two sources of bias when using such relationships were evaluated: i) the influence of using theoretical terminal raindrop fall velocities instead of measured values; and ii) the influence of time aggregation (rainfall intensity data every 5-, 10-, 15-, 30-, and 60-minutes). Empirical relationships did a relatively good job when complete events were considered (R2 > 0.82), but offered poorer results for within-event (one-minute resolution) variation. Also, systematic biases where large for many equations. When raindrop size distribution was known, estimating the terminal fall velocities by empirical laws produced good results even at fine time resolution. The influence of time aggregation was very high in the estimated kinetic energy, although linear scaling may allow empirical correction. This results stress the importance of considering all these effects when rainfall energy needs to be estimated from more standard precipitation records. , and recommends the use of disdrometer data to locally determine rainfall kinetic energy.

  14. Daily rainfall variability at a local scale (1,000 ha, in Piracicaba, SP, Brazil, and its implications on soil water recharge Variabilidade diária da chuva em uma escala local (1000 ha em Piracicaba, SP, e suas implicações na recarga da água do solo

    Directory of Open Access Journals (Sweden)

    K. Reichardt

    1995-04-01

    Full Text Available Daily rainfall variability at a local scale (1,000 ha was studied at Piracicaba, SP, Brazil, for the period of one year (1993-1994, in order to better understand the process of soil water recharge. Coefficients of variation of daily data for ten observation points varied from 2.2 to 169.3% and the variability was independent of rain type, i.e. whether convective, frontal or of other origin. Data were not related to separation distances between observation points and it is concluded that one observation point does not represent areas as far as 1,000 to 2,500 m apart, for daily, monthly or even quarterly averages. Yearly totals for the ten observation points presented a coefficient of variation as low as 3.06%, indicating that all points can replace each other in annual terms.A variabilidade diária da chuva em uma escala local (1000 ha foi estudada em Piracicaba, SP, Brasil, pelo período de um ano (1993-1994. Os coeficientes de variação de dados diários para dez pontos de observação variaram de 2,2 a 169,3 % e a variabilidade independeu do tipo de chuva, isto é, se convectiva, frontal ou de outra origem. Os dados não apresentaram correlação com a distância entre os pontos de observação e concluiu-se que uni ponto de observação não representa áreas distantes dele de 1000 a 2500 m, para médias diárias, mensais ou mesmo trimestrais. Os totais anuais dos dez pontos apresentaram um coeficiente de variação de apenas 3,06 %, indicando que cada ponto pode representar qualquer outro em termos anuais.

  15. Deforestation alters rainfall: a myth or reality

    Science.gov (United States)

    Hanif, M. F.; Mustafa, M. R.; Hashim, A. M.; Yusof, K. W.

    2016-06-01

    To cope with the issue of food safety and human shelter, natural landscape has gone through a number of alterations. In the coming future, the expansion of urban land and agricultural farms will likely disrupt the natural environment. Researchers have claimed that land use change may become the most serious issue of the current century. Thus, it is necessary to understand the consequences of land use change on the climatic variables, e.g., rainfall. This study investigated the impact of deforestation on local rainfall. An integrated methodology was adopted to achieve the objectives. Above ground biomass was considered as the indicator of forest areas. Time series data of a Moderate Resolution Imaging Spectroradiometer (MODIS) sensor were obtained for the year of 2000, 2005, and 2010. Rainfall data were collected from the Department of Irrigation and Drainage, Malaysia. The MODIS time series data were classified and four major classes were developed based on the Normalised Difference Vegetation Index (NDVI) ranges. The results of the classification showed that water, and urban and agricultural lands have increased in their area by 2, 3, and 6%, respectively. On the other hand, the area of forest has decreased 10% collectively from 2000 to 2010. The results of NDVI and rainfall data were analysed by using a linear regression analysis. The results showed a significant relationship at a 90% confidence interval between rainfall and deforestation (t = 1.92, p = 0.06). The results of this study may provide information about the consequences of land use on the climate on the local scale.

  16. 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.

  17. 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.

  18. 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...

  19. Rainfall variability and extremes over southern Africa: Assessment of a climate model to reproduce daily extremes

    Science.gov (United States)

    Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

    2009-04-01

    It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will

  20. 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.

  1. Relationships between atmospheric circulation indices and rainfall in Northern Algeria and comparison of observed and RCM-generated rainfall

    Science.gov (United States)

    Taibi, S.; Meddi, M.; Mahé, G.; Assani, A.

    2017-01-01

    This work aims, as a first step, to analyze rainfall variability in Northern Algeria, in particular extreme events, during the period from 1940 to 2010. Analysis of annual rainfall shows that stations in the northwest record a significant decrease in rainfall since the 1970s. Frequencies of rainy days for each percentile (5th, 10th, 25th, 50th, 75th, 90th, 95th, and 99th) and each rainfall interval class (1-5, 5-10, 10-20, 20-50, and ≥50 mm) do not show a significant change in the evolution of daily rainfall. The Tenes station is the only one to show a significant decrease in the frequency of rainy days up to the 75th percentile and for the 10-20-mm interval class. There is no significant change in the temporal evolution of extreme events in the 90th, 95th, and 99th percentiles. The relationships between rainfall variability and general atmospheric circulation indices for interannual and extreme event variability are moderately influenced by the El Niño-Southern Oscillation and Mediterranean Oscillation. Significant correlations are observed between the Southern Oscillation Index and annual rainfall in the northwestern part of the study area, which is likely linked with the decrease in rainfall in this region. Seasonal rainfall in Northern Algeria is affected by the Mediterranean Oscillation and North Atlantic Oscillation in the west. The ENSEMBLES regional climate models (RCMs) are assessed using the bias method to test their ability to reproduce rainfall variability at different time scales. The Centre National de Recherches Météorologiques (CNRM), Czech Hydrometeorological Institute (CHMI), Eidgenössische Technische Hochschule Zürich (ETHZ), and Forschungszentrum Geesthacht (GKSS) models yield the least biased results.

  2. 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

  3. Hydro-meteorological evaluation of downscaled global ensemble rainfall forecasts

    Science.gov (United States)

    Gaborit, Étienne; Anctil, François; Fortin, Vincent; Pelletier, Geneviève

    2013-04-01

    Ensemble rainfall forecasts are of high interest for decision making, as they provide an explicit and dynamic assessment of the uncertainty in the forecast (Ruiz et al. 2009). However, for hydrological forecasting, their low resolution currently limits their use to large watersheds (Maraun et al. 2010). In order to bridge this gap, various implementations of the statistic-stochastic multi-fractal downscaling technique presented by Perica and Foufoula-Georgiou (1996) were compared, bringing Environment Canada's global ensemble rainfall forecasts from a 100 by 70-km resolution down to 6 by 4-km, while increasing each pixel's rainfall variance and preserving its original mean. For comparison purposes, simpler methods were also implemented such as the bi-linear interpolation, which disaggregates global forecasts without modifying their variance. The downscaled meteorological products were evaluated using different scores and diagrams, from both a meteorological and a hydrological view points. The meteorological evaluation was conducted comparing the forecasted rainfall depths against nine days of observed values taken from Québec City rain gauge database. These 9 days present strong precipitation events occurring during the summer of 2009. For the hydrologic evaluation, the hydrological models SWMM5 and (a modified version of) GR4J were implemented on a small 6 km2 urban catchment located in the Québec City region. Ensemble hydrologic forecasts with a time step of 3 hours were then performed over a 3-months period of the summer of 2010 using the original and downscaled ensemble rainfall forecasts. The most important conclusions of this work are that the overall quality of the forecasts was preserved during the disaggregation procedure and that the disaggregated products using this variance-enhancing method were of similar quality than bi-linear interpolation products. However, variance and dispersion of the different members were, of course, much improved for the

  4. 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.

  5. 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.

  6. Borneo vortex and mesoscale convective rainfall

    Science.gov (United States)

    Koseki, S.; Koh, T.-Y.; Teo, C.-K.

    2014-05-01

    We have investigated how the Borneo vortex develops over the equatorial South China Sea under cold surge conditions in December during the Asian winter monsoon. Composite analysis using reanalysis and satellite data sets has revealed that absolute vorticity and water vapour are transported by strong cold surges from upstream of the South China Sea to around the Equator. Rainfall is correspondingly enhanced over the equatorial South China Sea. A semi-idealized experiment reproduced the Borneo vortex over the equatorial South China Sea during a "perpetual" cold surge. The Borneo vortex is manifested as a meso-α cyclone with a comma-shaped rainband in the northeast sector of the cyclone. Vorticity budget analysis showed that the growth/maintenance of the meso-α cyclone was achieved mainly by the vortex stretching. This vortex stretching is due to the upward motion forced by the latent heat release around the cyclone centre. The comma-shaped rainband consists of clusters of meso-β-scale rainfall cells. The intense rainfall in the comma head (comma tail) is generated by the confluence of the warmer and wetter cyclonic easterly flow (cyclonic southeasterly flow) and the cooler and drier northeasterly surge in the northwestern (northeastern) sector of the cyclone. Intense upward motion and heavy rainfall resulted due to the low-level convergence and the favourable thermodynamic profile at the confluence zone. In particular, the convergence in the northwestern sector is responsible for maintenance of the meso-α cyclone system. At both meso-α and meso-β scales, the convergence is ultimately caused by the deviatoric strain in the confluence wind pattern but is significantly self-enhanced by the nonlinear dynamics.

  7. Adherence styles of schizophrenia patients identified by a latent class analysis of the Medication Adherence Rating Scale (MARS): a six-month follow-up study.

    Science.gov (United States)

    Jaeger, Susanne; Pfiffner, Carmen; Weiser, Prisca; Kilian, Reinhold; Becker, Thomas; Längle, Gerhard; Eschweiler, Gerhard Wilhelm; Croissant, Daniela; Schepp, Wiltrud; Steinert, Tilman

    2012-12-30

    The purpose of this study was to examine patients' response profiles to the Medication Adherence Rating Scale (MARS) and to evaluate the potential of response styles as predictors of the future course of psychotic disorders in terms of rehospitalisation and maintenance of medication. A total of 371 psychiatric in-patients with schizophrenia or schizoaffective disorder who were taking part in a naturalistic long-term study completed a German version of the MARS. A Latent Class Analysis (LCA) was performed. Five latent classes of response styles could be identified: "moderately adherent", "critical discontinuers", "good compliers", "careless and forgetful", and "compliant sceptics". Class membership was found to be related to the severity of symptoms, level of functioning, insight into illness, insight into necessity of treatment, treatment satisfaction and medication side effects. At a six-month follow-up appointment, significant differences between the classes persisted. Participants showing a "good compliers" response pattern had a significantly better prognosis in terms of rehospitalisation rate and maintenance of the original medication than "critical discontinuers". Evaluation of the MARS by studying response profiles provides informative results that reach beyond the results obtained by an evaluation by scores. Patients can be classified into adherence groups that are of predictive value for long-term patient outcome.

  8. 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.

  9. 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.

  10. 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.

  11. Spatial distribution of the daily rainfall concentration index in Argentina: comparison with other countries

    Science.gov (United States)

    Llano, María Paula

    2017-08-01

    The precipitation is a meteorological variable studied in Argentina mainly in annual, seasonal and monthly scales. Its variability is a significant climate element and also a critical socioeconomic factor. This study aims to contribute to the knowledge of daily rainfall in Argentina. Daily records of precipitation for 66 stations provided by the Servicio Meteorológico Nacional are used (period 1991-2014). The spatial distribution of the annual precipitation presents an east-west gradient in the north of the country. In monthly scale, there are different precipitation distributions such as a double maximum in the centre-east zone or a single maximum in the northwest in summer time and in the southern Andes range during the winter. To carry out the study, the concentration index (CI) of daily precipitation with a resolution of 1 mm is used. Precipitation in Argentina, given its vast territory, presents a great variability with a wide range of rainfall regimes; CI values are found between 0.54 and 0.68. These values are categorized as high (greater than 0.61) and low (less than 0.58). The north of the country and the Atlantic coast show the highest CI values. The lower values are present in the Andes range and in the south of the country. The results are compared with other studies in the world.

  12. 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.

  13. 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.

  14. 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...

  15. Rainfall Infiltration Characteristics of High-class Dump Downstream of a Large-scale Tailing Pond%大型尾矿库下游高等级排土场的降雨入渗特性

    Institute of Scientific and Technical Information of China (English)

    朱君星; 李跃; 李从德

    2015-01-01

    尾矿库和排土场都是高势能的泥石流重大危险源,二者的降雨入渗特性均较复杂。而当高等级排土场位于大型尾矿库的下游时,其复杂性更不言而喻。通过对太和铁矿的工程实例分析,计算得到尾矿库在千年一遇洪水条件下的浸润线分布,将其导入到排土场中作为初始条件,计算得到初始浸润线;再据此分析整个研究区域的降雨条件下入渗特性。研究结果表明,尾矿库内的浸润线分布对下游排土场的影响很大,入渗作用改变了排土场边坡内的地下水渗流场,而地下水的升高则是一个缓慢的过程。%Both of tailing pond and waster dump is high -potential fatal danger fountainhead for debris flow , and the infiltration characteristic are all complex of them .Especially , when a high-class dump is downstream of a large-scale tailing pond , the degree of complexity is more self -evident .Based on the engineering instance a-nalysis of Taihe Iron Mining , phreatic line under the case of the millennium of the tailing pond was obtained , which is introduced into the waster dump model as an initial condition to calculate the initial phreatic line .On the basis, the infiltration characteristic in the entire area under rainfall was analyzed .The study results showed that the phreatic line distribution in the tailing pond has great influence on the waster dump at downstream , the groundwater seepage field in the dump was changed by the infiltration , and the rise of groundwater is a slow .

  16. 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.

  17. On merging rainfall data from diverse sources using a Bayesian approach

    Science.gov (United States)

    Bhattacharya, Biswa; Tarekegn, Tegegne

    2014-05-01

    Numerous studies have presented comparison of satellite rainfall products, such as from Tropical Rainfall Measuring Mission (TRMM), with rain gauge data and have concluded, in general, that the two sources of data are comparable at suitable space and time scales. The comparison is not a straightforward one as they employ different measurement techniques and are dependent on very different space-time scales of measurements. The number of available gauges in a catchment also influences the comparability and thus adds to the complexity. The TRMM rainfall data also has been directly used in hydrological modelling. As the space-time scale reduces so does the accuracy of these models. It seems that combining the two sources of rainfall data, or more sources of rainfall data, can enormously benefit hydrological studies. Various rainfall data, due to the differences in their space-time structure, contains information about the spatio-temporal distribution of rainfall, which is not available to a single source of data. In order to harness this benefit we have developed a method of merging these two (or more) rainfall products under the framework of Bayesian Data Fusion (BDF) principle. By applying this principle the rainfall data from the various sources can be combined to a single time series of rainfall data. The usefulness of the approach has been explored in a case study on Lake Tana Basin of Upper Blue Nile Basin in Ethiopia. A 'leave one rain gauge out' cross validation technique was employed for evaluating the accuracy of the rainfall time series with rainfall interpolated from rain gauge data using Inverse Distance Weighting (referred to as IDW), TRMM and the fused data (BDF). The result showed that BDF prediction was better compared to the TRMM and IDW. Further evaluation of the three rainfall estimates was done by evaluating the capability in predicting observed stream flow using a lumped conceptual rainfall-runoff model using NAM. Visual inspection of the

  18. Hydroclimate variability and its statistical links to the large-scale climate indices for the Upper Chao Phraya River Basin, Thailand

    Directory of Open Access Journals (Sweden)

    N. Singhrattna

    2009-10-01

    Full Text Available The local hydroclimates get impacts from the large-scale atmospheric variables via atmospheric circulation. The developing of their relationships could enhance the understanding of hydroclimate variability. This study focuses on the Upper Chao Phraya River Basin in Thailand in which rainfall is influenced by the Indian Ocean and tropical Pacific Ocean atmospheric circulation. The Southwest monsoon from the Indian Ocean to Thailand is strengthened by the temperature gradient between land and ocean. Thus, the anomalous sea surface temperature (SST is systematically correlated with the monthly rainfall and identified as the best predictor based on the significant relationships revealed by cross-correlation analysis. It is found that rainfall, especially during the monsoon season in the different zones of study basin, corresponds to the different SST indices. This suggests that the region over the ocean which develops the temperature gradient plays a role in strengthening the monsoon. The enhanced gradient with the SST over the South China Sea is related to rainfall in High Rainfall Zone (HRZ; however, the anomalous SST over the Indian Ocean and the equatorial Pacific Ocean are associated with rainfall in Normal and Low Rainfall Zone (NRZ and LRZ in the study area. Moreover, the identified predictors are related to the rainfall with lead periods of 1–4 months for the pre-monsoon rainfall and 6–12 months for the monsoon and dry season rainfall. The study results are very useful in developing rainfall forecasting models and consequently in the management of water resources and extreme events.

  19. Rainfall erosivity in New Zealand

    Science.gov (United States)

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

    2014-05-01

    Rainfall and its kinetic energy expressed by the rainfall erosivity is the main driver of soil erosion processes by water. The Rainfall-Runoff Erosivity Factor (R) of the Revised Universal Soil Loss Equation is one oft he most widely used parameters describing rainfall erosivity. This factor includes the cumulative effects of the many moderate-sized storms as well as the effects oft he occasional severe ones: R quantifies the effect of raindrop impact and reflects the amopunt and rate of runoff associated with the rain. New Zealand is geologically young and not comparable with any other country in the world. Inordinately high rainfall and strong prevailing winds are New Zealand's dominant climatic features. Annual rainfall up to 15000 mm, steep slopes, small catchments and earthquakes are the perfect basis for a high rate of natural and accelerated erosion. Due to the multifacted landscape of New Zealand its location as island between the Pacific and the Tasmanian Sea there is a high gradient in precipitation between North and South Island as well as between West and East Coast. The objective of this study was to determine the R-factor for the different climatic regions in New Zealand, in order to create a rainfall erosivity map. We used rainfall data (breakpoint data in 10-min intervals) from 34 gauging stations for the calcuation of the rainfall erosivity. 15 stations were located on the North Island and 19 stations on the South Island. From these stations, a total of 397 station years with 12710 rainstorms were analyzed. The kinetic energy for each rainfall event was calculated based on the equation by Brown and Foster (1987), using the breakpoint precipitation data for each storm. On average, a mean annual precipitation of 1357 mm was obtained from the 15 observed stations on the North Island. Rainfall distribution throughout the year is relatively even with 22-24% of annual rainfall occurring in spring , fall and winter and 31% in summer. On the South Island

  20. Rainfall-enhanced blooming in typhoon wakes

    Science.gov (United States)

    Lin, Y.-C.; Oey, L.-Y.

    2016-08-01

    Strong phytoplankton blooming in tropical-cyclone (TC) wakes over the oligotrophic oceans potentially contributes to long-term changes in global biogeochemical cycles. Yet blooming has traditionally been discussed using anecdotal events and its biophysical mechanics remain poorly understood. Here we identify dominant blooming patterns using 16 years of ocean-color data in the wakes of 141 typhoons in western North Pacific. We observe right-side asymmetric blooming shortly after the storms, attributed previously to sub-mesoscale re-stratification, but thereafter a left-side asymmetry which coincides with the left-side preference in rainfall due to the large-scale wind shear. Biophysical model experiments and observations demonstrate that heavier rainfall freshens the near-surface water, leading to stronger stratification, decreased turbulence and enhanced blooming. Our results suggest that rainfall plays a previously unrecognized, critical role in TC-induced blooming, with potentially important implications for global biogeochemical cycles especially in view of the recent and projected increases in TC-intensity that harbingers stronger mixing and heavier rain under the storm.

  1. Rainfall simulators in hydrological and geomorphological sciences: benefits, applications and future research directions

    Science.gov (United States)

    Iserloh, Thomas; Cerdà, Artemi; Fister, Wolfgang; Seitz, Steffen; Keesstra, Saskia; Green, Daniel; Gabriels, Donald

    2017-04-01

    Rainfall simulators are used extensively within the hydrological and geomorphological sciences and provide a useful investigative tool to understand many processes, such as: (i) plot-scale runoff, infiltration and erosion; (ii) irrigation and crop management, and; (iii) investigations into flooding within a laboratory setting. Although natural rainfall is desirable as it represents actual conditions in a given geographic location, data acquisition relying on natural rainfall is often hindered by its unpredictable nature. Furthermore, rainfall characteristics such as the intensity, duration, drop size distribution and kinetic energy cannot be spatially or temporally regulated or repeated between experimentation. Rainfall simulators provide a suitable method to overcome the issues associated with depending on potentially erratic and unpredictable natural rainfall as they allow: (i) multiple measurements to be taken quickly without waiting for suitable natural rainfall conditions; (ii) the simulation of spatially and/or temporally controlled rainfall patterns over a given plot area, and; (iii) the creation of a closed environment, allowing simplified measurement of input and output conditions. There is no standardisation of rainfall simulation and as such, rainfall simulators differ in their design, rainfall characteristics and research application. Although this impedes drawing meaningful comparisons between studies, this allows researchers to create a bespoke and tailored rainfall simulator for the specific research application. This paper summarises the rainfall simulators used in European research institutions (Universities of Trier, Valencia, Basel, Tuebingen, Wageningen, Loughborough and Ghent) to investigate a number of hydrological and geomorphological issues and includes details on the design specifications (such as the extent and characteristics of simulated rainfall), as well as a discussion of the purpose and application of the rainfall simulator.

  2. 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...

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. Interannual and Interdecadal Variations in Atmospheric Circulation Factors and Rainfall in China and Their Relationship

    Institute of Scientific and Technical Information of China (English)

    YAN Huasheng; WAN Yunxia; CHENG Jiangang

    2005-01-01

    Wavelet analysis is used to study the interannual and interdecadal variations of rainfall in China and atmospheric circulation factors, including the key atmospheric oscillations, W, C, E patterns and subtropical high. Regression analysis and correlation analysis are both used to study the relationship of atmospheric circulation factors and China rainfall on different time scale and spatial scale. The results are as follows:(1) The variations of atmospheric circulation and rainfall in China are characterized by interannual and interdecadal scales. The variations of atmospheric circulation and rainfall are composed of interannual and interdecadal variations. It is necessary to separate those two time scales when climate changes and forecast are studied. (2) The variations of China rainfall are due to the interaction of multi-factors rather than single factors. The marked factors which influence the interannual and interdecadal variations are various.Subtropical high is one of the marked factors which influence interannual variations of rainfall, while AO,NAO, and NPO are one of the marked factors which influence interdecadal variations of rainfall. (3) The longer the time scale is, and the larger the spatial scale is, and the more remarkable the relationships between atmospheric circulation and rainfall are.

  9. Analysis of spatial and temporal extreme monsoonal rainfall over South Asia using complex networks

    Energy Technology Data Exchange (ETDEWEB)

    Malik, Nishant [Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, Potsdam (Germany); University of Potsdam, Institute of Physics, Potsdam-Golm (Germany); Bookhagen, Bodo [University of California Santa Barbara, Department of Geography, Santa Barbara, CA (United States); Marwan, Norbert [Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, Potsdam (Germany); Kurths, Juergen [Potsdam Institute for Climate Impact Research, P.O. Box 60 12 03, Potsdam (Germany); Humboldt University, Department of Physics, Berlin (Germany)

    2012-08-15

    We present a detailed analysis of summer monsoon rainfall over the Indian peninsular using nonlinear spatial correlations. This analysis is carried out employing the tools of complex networks and a measure of nonlinear correlation for point processes such as rainfall, called event synchronization. This study provides valuable insights into the spatial organization, scales, and structure of the 90th and 94th percentile rainfall events during the Indian summer monsoon (June-September). We furthermore analyse the influence of different critical synoptic atmospheric systems and the impact of the steep Himalayan topography on rainfall patterns. The presented method not only helps us in visualising the structure of the extreme-event rainfall fields, but also identifies the water vapor pathways and decadal-scale moisture sinks over the region. Furthermore a simple scheme based on complex networks is presented to decipher the spatial intricacies and temporal evolution of monsoonal rainfall patterns over the last 6 decades. (orig.)

  10. Canonical correlation analysis of hydrological response and soil erosion under moving rainfall

    Institute of Scientific and Technical Information of China (English)

    Qi-hua RAN; Zhi-nan SHI; Yue-ping XU

    2013-01-01

    The impacts of rainfall direction on the degree of hydrological response to rainfall properties were investigated using comparative rainfall-runoff experiments on a small-scale slope (4 m×l m),as well as canonical correlation analysis (CCA).The results of the CCA,based on the observed data showed that,under conditions of both upstream and downstream rainfall movements,the hydrological process can be divided into instantaneous and cumulative responses,for which the driving forces are rainfall intensity and total rainfall,and coupling with splash erosion and wash erosion,respectively.The response of peak runoff (Pr) to intensity-dominated rainfall action appeared to be the most significant,and also runoff (R) to rainfall-dominated action,both for upstream-and downstream-moving conditions.Furthermore,the responses of sediment erosion in downstream-moving condition were more significant than those in upstream-moving condition.This study indicated that a CCA between rainfall and hydrological characteristics is effective for further exploring the rainfall-runoff-erosion mechanism under conditions of moving rainfall,especially for the downstream movement condition.

  11. Resolving orographic rainfall on the Indian west coast

    Digital Repository Service at National Institute of Oceanography (India)

    Suprit, K.; Shankar, D.

    consequence of the small scale of these west-coast rivers. This need for estimating the freshwater discharge into the seas around India led Shankar et al. (2004) to assemble a framework for estimating river discharge. The framework was based on Terrestrial... at various spatial and temporal scales. Some of these data sets are based on rain-gauge measurements and some on satellite estimates; some of them use model- derived reanalysis data. We tested three available rainfall data sets to see if these rainfall data...

  12. 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

  13. 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.

  14. 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.

  15. 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...

  16. 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.

  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. 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.

  19. More rain, less soil: long-term changes in rainfall intensity with climate change

    OpenAIRE

    Burt, Tim; Boardman, John; Foster, Ian D L; Howden, Nicholas

    2016-01-01

    This commentary discusses the role of long-term climate change in driving increases in soil erosion. Assuming that land use and management remain effectively constant, we discuss changes in the ability of rainfall to cause erosion (erosivity), using long daily rainfall data sets from south east England. An upward trend in mean rainfall per rain day is detected at the century-plus time scale. Implications for soil erosion and sediment delivery are discussed and evidence from other regions revi...

  20. 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

  1. Cold Air Activities in July 2004 and Its Impact on Intense Rainfalls over Southwest China

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The severe rainfall events in the mid-summer of July 2004 and the roles of cold air in the formation of heavy precipitation are investigated by using daily observational precipitation data of China and NCEP/NCAR reanalysis. The results show that the severe rainfalls in Southwest China are closely related to the cold air activities from the mid-high latitudes, and the events take place under the cooperative effects of mid-high latitude circulation and low latitude synoptic regimes. It is the merging of a cold vortex over mid-latitudes with the northward landing typhoon and eastward Southwest China Vortex, as well as the abrupt transformation from a transversal trough into an upright one that causes three large alterations of mid-high atmospheric circulation respectively in the early and middle ten days of this month. Then, the amplitude of long waves soon magnifies, leading to the unusual intrusion of cold air to low-latitude areas in the mid-summer. Meanwhile, the warm and humid southwest summer monsoon is quite active. The strong interactions of cold air and summer monsoon over Southwest China result in the large-scale convective rainfalls on the southern side of cold air.With regard to the activities of cold air, it can influence rainfalls in three prominent ways. Firstly, the incursion of upper-level cold air is often accompanied by partial southerly upper-level jet. The ascending branch of the corresponding secondary circulation, which is on the left front side of the jet center, provides the favorite dynamic upward motion for the rainfalls. Secondly, the southward movement of cold air contributes to the establishment of atmospheric baroclinic structure, which would lead to baroclinic disturbances. The atmospheric disturbances associated with the intrusion of cold air can destroy the potential instability stratification, release the convective available potential energy (CAPE) and finally cause convective activities. In addition, the advection processes of dry

  2. Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi)

    Science.gov (United States)

    Kneis, D.; Chatterjee, C.; Singh, R.

    2014-07-01

    The paper examines the quality of satellite-based precipitation estimates for the lower Mahanadi River basin (eastern India). The considered data sets known as 3B42 and 3B42-RT (version 7/7A) are routinely produced by the tropical rainfall measuring mission (TRMM) from passive microwave and infrared recordings. While the 3B42-RT data are disseminated in real time, the gauge-adjusted 3B42 data set is published with a delay of some months. The quality of the two products was assessed in a two-step procedure. First, the correspondence between the remotely sensed precipitation rates and rain gauge data was evaluated at the sub-basin scale. Second, the quality of the rainfall estimates was assessed by analysing their performance in the context of rainfall-runoff simulation. At sub-basin level (4000 to 16 000 km2) the satellite-based areal precipitation estimates were found to be moderately correlated with the gauge-based counterparts (R2 of 0.64-0.74 for 3B42 and 0.59-0.72 for 3B42-RT). Significant discrepancies between TRMM data and ground observations were identified at high-intensity levels. The rainfall depth derived from rain gauge data is often not reflected by the TRMM estimates (hit rate 80 mm day-1). At the same time, the remotely sensed rainfall rates frequently exceed the gauge-based equivalents (false alarm ratios of 0.2-0.6). In addition, the real-time product 3B42-RT was found to suffer from a spatially consistent negative bias. Since the regionalisation of rain gauge data is potentially associated with a number of errors, the above results are subject to uncertainty. Hence, a validation against independent information, such as stream flow, was essential. In this case study, the outcome of rainfall-runoff simulation experiments was consistent with the above-mentioned findings. The best fit between observed and simulated stream flow was obtained if rain gauge data were used as model input (Nash-Sutcliffe index of 0.76-0.88 at gauges not affected by

  3. A multi-sensor approach to landslide monitoring of rainfall-induced failures in Scotland.

    Science.gov (United States)

    Gilles, Charlie; Hoey, Trevor; Williams, Richard

    2017-04-01

    Landslides are of significant interest in upland areas of the United Kingdom due to their: complex mechanics, potential to channelize into hazardous debris flows and their costly potential impacts on infrastructure. The British Geological Survey National Landslide Database contains an average of 367 landslides per year (from 1970). Slope failures in the UK are typically triggered by extended periods of intense rainfall, and can occur at any time of year. In any given rainfall event that triggers landslides, most potentially vulnerable slopes remain stable. Accurate warning systems would be facilitated by identifying landslide precursors prior to failure events. This project tests whether such precursors can be identified in the valley of Glen Ogle, Scotland (87 km north-west of Edinburgh), where in summer 2004 two debris flows blocked the main road (A85), trapping fifty-seven people. Two adjacent sites have been selected on a west facing slope in Glen Ogle, one of which (the control) has been stable since at least 2004 and the other failed in 2004 and remains unstable. Understanding the immediate causes and antecedent conditions responsible for landslides requires a multi-scale approach. This project uses multiple sensors to assess failure mechanisms of landslides in Glen Ogle: (1) 3-monthly, high (1.8 arcsec) resolution terrestrial laser scanning of topography to detect changes and identify patterns of movement prior to major failure, using the Riegl VZ-1000 (NERC Geophysical Equipment Fund); (2) rainfall and soil moisture data to monitor pore pressure of landslide failure prior to and after hydrologically triggered events; (3) monitoring ground motion using grain-scale sensors which are becoming lower cost, more efficient in terms of power, and can be wirelessly networked these will be used to detect small scale movement of the landslide. Comparative data from the control and test sites will be presented, from which patterns of surface deformation between failure

  4. [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).

  5. 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.

  6. 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.

  7. East Australian rainfall events: Interannual variations, trends, and relationships with the Southern Oscillation

    Energy Technology Data Exchange (ETDEWEB)

    Nicholls, N.; Kariko, A. (Bureau of Meteorology Research Centre, Melbourne (Australia))

    1993-06-01

    The number, average length, and average intensity of rain events at five stations located in eastern Australia have been calculated for each year from 1910 to 1988, using daily rainfall totals. A rain event has been defined as a period of consecutive days on which rainfall has been recorded on each day. Inter-relationships between the rain-event variables (at each station and between stations), along with their relationships with annual rainfall and the El Nino-Southern Oscillation, have been investigated. Trends in the time series of the rain-event variables have also been examined. Annual rainfall variations are found to be primarily caused by variations in intensity. Fluctuations in the three rain-event variables are essentially independent of each other. This is due, in some cases, to inter-relationships at interdecadal time scales offsetting relationships of the opposite sense at shorter time scales. The large-scale geographical nature of east Australian rainfall fluctuations mainly reflects interstation correlations in the number of events. The El Nino-Southern Oscillation affects rainfall mainly by influencing the number and intensity of rain events. Twentieth century increases in east Australian rainfall have been due, primarily, to increased numbers of events. Intensity of rain events has generally declined, offsetting some of the increase in rainfall expected from more frequent events. Information about historical trends in australian rain events might provide a basis for determining if rainfall change were due to an enhanced greenhouse effect. 31 refs., 13 figs.

  8. 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.

  9. The DOPAS full-scale demonstation of plugs and seals project and related GRS national RD and D programs. A retrospective view on 24-month of investigation

    Energy Technology Data Exchange (ETDEWEB)

    Czaikowski, Oliver; Meyer, Thorsten; Miehe, Ruediger [GRS mbH, Braunschweig (Germany). Final Repository Safety Div.

    2015-07-01

    The DOPAS Full-Scale Demonstration of Plugs and Seals project consisting of 14 beneficiaries from 8 European countries brings forward important demonstration activities in plugging and sealing. These activities are also a part of each participants national long-term RD and D programm and are therefore jointly funded by Euratom's Seventh Framework Programme and national funding organizations. The Demonstration experiments which will be partially or wholly implemented during the DOPAS project are a full-scale seal (FSS) implemented in Saint-Dizier in France, an experimental pressure sealing plug (EPSP) underground in the Josef Gallery in Czech Republic, a deposition tunnel dome plug (DOMPLU) in the AespoeHard Rock Laboratory in Sweden, a deposition tunnel wedge plug (POPLU) in the underground rock characterization facility ONKALO (future spent fuel repository) in Finland, and components of a shaft sealing system (ELSA) in Germany (Dopas 2012). ELSA is a program of laboratory and in-situ experiments that will be used to further develop the reference shaft seal for the German disposal concept for a repository in rock salt and to develop reference shaft seals for a repository in clay host rocks (Kudla et al. 2013). On behalf of BMWi, the national funding organization for R and D work related to radioactive waste management, facing the ELSA project phase 3, GRS is investigating sealing and backfilling materials planned to be utilized in salt and clay formations. The program aims at providing experimental data needed for the theoretical analysis of the long-term sealing capacity of these sealing materials. According to current R and D work on the salt option, the shaft and drift seal components considered in Germany comprise seal components consisting of MgO and cement based salt concrete (Mueller-Hoeppe et al. 2012). In order to demonstrate hydro-mechanical material stability under representative load scenarios, the sealing capacity of the seal system and the impact

  10. 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.

  11. Migrating deformation in the Central Andes from enhanced orographic rainfall

    Science.gov (United States)

    Norton, Kevin; Schlunegger, Fritz

    2011-12-01

    Active shortening in the Central Andes shifted from the western to the eastern margin between 10-7Ma. Here we propose that this shift was primarily controlled by changes in erosion patterns. The uplift of the Andes blocked easterly winds, resulting in enhanced orographic rainfall on the eastern margin and reduced rainfall on the western margin. Lower erosion rates, associated with the arid conditions, caused the western margin to steepen inhibiting internal deformation and the migration of deformation to the eastern margin where it is active today. River channel profiles on the western margin are indicative of long-term transience from an older tectonic event whereas those on the eastern margin reflect ongoing coupled climatic-tectonic feedback. Both critical wedge theory and local-scale fault friction calculations support this interpretation. This work emphasizes the role that orographic rainfall and erosion can have on the orogen-scale development of mountain belts.

  12. Recent Trends in the Regime of Extreme Rainfall in the West African Sahel

    Science.gov (United States)

    Lebel, T.; Panthou, G.; Vischel, T.; Quantin, G.

    2015-12-01

    West Africa is known for having experienced an extreme drought starting at the end of the 1960s that is recognized to be the greatest climatic signal at regional scale since the beginning of meteorological measurements. Despite a moderate recovery of the annual precipitations since the 1990s in the Central and Eastern Sahel, rainfall over the last two decades remains lower by 15% than during the period 1950-1970. Paradoxically these persisting dry conditions have been accompanied by a dramatic increase of flood fatalities especially over the recent 10 years. Using a homogeneous dataset of 41 daily rainfall series covering the period 1950-2010, an integrated regional approach based on the statistical extreme value theory was then used to reduce the local sampling effects and to provide robust estimates of intense rainfall distributions to be analyzed in conjunction with the annual rainfall series. This led to identify some key rainfall regime cha