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Sample records for monthly average rainfall

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

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    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.

  2. 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.

  3. 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...

  4. 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

  5. Average Annual Rainfall over the Globe

    Science.gov (United States)

    Agrawal, D. C.

    2013-01-01

    The atmospheric recycling of water is a very important phenomenon on the globe because it not only refreshes the water but it also redistributes it over land and oceans/rivers/lakes throughout the globe. This is made possible by the solar energy intercepted by the Earth. The half of the globe facing the Sun, on the average, intercepts 1.74 ×…

  6. Average Annual Rainfall over the Globe

    Science.gov (United States)

    Agrawal, D. C.

    2013-01-01

    The atmospheric recycling of water is a very important phenomenon on the globe because it not only refreshes the water but it also redistributes it over land and oceans/rivers/lakes throughout the globe. This is made possible by the solar energy intercepted by the Earth. The half of the globe facing the Sun, on the average, intercepts 1.74 ×…

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

    Science.gov (United States)

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

    2009-02-25

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

  8. 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.

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

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    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.

  10. 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

  11. Monthly snow/ice averages (ISCCP)

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    National Aeronautics and Space Administration — September Arctic sea ice is now declining at a rate of 11.5 percent per decade, relative to the 1979 to 2000 average. Data from NASA show that the land ice sheets in...

  12. 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.

  13. 20 CFR 226.62 - Computing average monthly compensation.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Computing average monthly compensation. 226... Compensation § 226.62 Computing average monthly compensation. The employee's average monthly compensation is computed by first determining the employee's highest 60 months of railroad compensation...

  14. 20 CFR 404.220 - Average-monthly-wage method.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Average-monthly-wage method. 404.220 Section... INSURANCE (1950- ) Computing Primary Insurance Amounts Average-Monthly-Wage Method of Computing Primary Insurance Amounts § 404.220 Average-monthly-wage method. (a) Who is eligible for this method. You...

  15. 20 CFR 404.221 - Computing your average monthly wage.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Computing your average monthly wage. 404.221... DISABILITY INSURANCE (1950- ) Computing Primary Insurance Amounts Average-Monthly-Wage Method of Computing Primary Insurance Amounts § 404.221 Computing your average monthly wage. (a) General. Under the...

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

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    Panos Panagos

    2016-03-01

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

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

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    Ferrara A

    2008-12-01

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

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

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    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.

  19. Average monthly and annual climate maps for Bolivia

    KAUST Repository

    Vicente-Serrano, Sergio M.

    2015-02-24

    This study presents monthly and annual climate maps for relevant hydroclimatic variables in Bolivia. We used the most complete network of precipitation and temperature stations available in Bolivia, which passed a careful quality control and temporal homogenization procedure. Monthly average maps at the spatial resolution of 1 km were modeled by means of a regression-based approach using topographic and geographic variables as predictors. The monthly average maximum and minimum temperatures, precipitation and potential exoatmospheric solar radiation under clear sky conditions are used to estimate the monthly average atmospheric evaporative demand by means of the Hargreaves model. Finally, the average water balance is estimated on a monthly and annual scale for each 1 km cell by means of the difference between precipitation and atmospheric evaporative demand. The digital layers used to create the maps are available in the digital repository of the Spanish National Research Council.

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

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    B. Salahi

    2017-01-01

    precipitation in Ardabil synoptic station indicates that in May, the highest and in August, the lowest monthly total rainfall accounted in this station. Standard deviation of rainfall reached to the lowest level in August and its peak in November. Coefficients of skewness and kurtosis of total rainfall in all seasons, indicates a lack of compliance with normal distribution. From the view of the range of total monthly rainfall, October and August have highest and the lowest tolerance in these parameters, respectively. The results showed that the percentage of the mean absolute error for Arima, Winters and Autoregressive models was 61.82, 148.39 and 81.54 respectively and its R square came to be 88.28, 61.07 and 85.12 respectively. The comparison of the parameters is an indication of the fact that Arima has the highest R square and the lowest mean absolute error of 88.28 and 61.82 respectively than Winters and Autoregressive models. The presence or absence of significant changes in mean precipitation during 1977-1993 and 2010-1994 in Ardabil synoptic station shows that the difference of rainfall is not significant at the 5% error level from statistical point of view. The comparison between the monthly mean rainfall of Ardabil synoptic station in 1994-2010 and 1977-1993 indicates that rainfall has somewhat decreased in the former in recent years. Considering the low average monthly rainfall of Ardabil synoptic station in 1994-2010 compared to 1977-1993 (21.98 versus 26.11 mm, although no statistically significant difference was found in the average rainfall, low rainfall in this station would not be unexpected in the coming years. The comparison of predicted and actual values from 2011 to 2013 in Ardabil synoptic station showed that fitting real data with expected data was relatively acceptable. The observed differences between the actual and predicted values can be related to the influence of rainfalls and many local and dynamical factors of this area. Therefore, it is necessary

  1. Simulation of mosquitoes population dynamic based on rainfall and average daily temperature

    Science.gov (United States)

    Widayani, H.; Seprianus, Nuraini, N.; Arum, J.

    2014-02-01

    This paper proposed rainfall and average daily temperature approximation functions using least square method with trigonometry polynomial. Error value from this method is better than Fast Fourier Transform method. This approximation is used to accommodate climatic factors into deterministic model of mosquitoes population by constructing a carrying capacity function which contains rainfall and average daily temperature functions. We develop a mathematical model for mosquitoes population dynamic which formulated by Yang et al (2010) with dynamic parameter of a daily rainfall as well as temperature on that model. Two fixed points, trivial and non-trivial, are obtained when constant entomological parameters assumed. Basic offspring number, Q0 as mosquitoes reproduction parameter is constructed. Non-trivial fixed point is stable if and only if Q0 > 1. Numerical simulation shown the dynamics of mosquitoes population significantly affected by rainfall and average daily temperature function.

  2. The monthly-averaged and yearly-averaged cosine effect factor of a heliostat field

    Energy Technology Data Exchange (ETDEWEB)

    Al-Rabghi, O.M.; Elsayed, M.M. (King Abdulaziz Univ., Jeddah (Saudi Arabia). Dept. of Thermal Engineering)

    1992-01-01

    Calculations are carried out to determine the dependence of the monthly-averaged and the yearly-averaged daily cosine effect factor on the pertinent parameters. The results are plotted on charts for each month and for the full year. These results cover latitude angles between 0 and 45[sup o]N, for fields with radii up to 50 tower height. In addition, the results are expressed in mathematical correlations to facilitate using them in computer applications. A procedure is outlined to use the present results to preliminary layout the heliostat field, and to predict the rated MW[sub th] reflected by the heliostat field during a period of a month, several months, or a year. (author)

  3. 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.

  4. 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.

  5. Monthly streamflow forecasting with auto-regressive integrated moving average

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    Nasir, Najah; Samsudin, Ruhaidah; Shabri, Ani

    2017-09-01

    Forecasting of streamflow is one of the many ways that can contribute to better decision making for water resource management. The auto-regressive integrated moving average (ARIMA) model was selected in this research for monthly streamflow forecasting with enhancement made by pre-processing the data using singular spectrum analysis (SSA). This study also proposed an extension of the SSA technique to include a step where clustering was performed on the eigenvector pairs before reconstruction of the time series. The monthly streamflow data of Sungai Muda at Jeniang, Sungai Muda at Jambatan Syed Omar and Sungai Ketil at Kuala Pegang was gathered from the Department of Irrigation and Drainage Malaysia. A ratio of 9:1 was used to divide the data into training and testing sets. The ARIMA, SSA-ARIMA and Clustered SSA-ARIMA models were all developed in R software. Results from the proposed model are then compared to a conventional auto-regressive integrated moving average model using the root-mean-square error and mean absolute error values. It was found that the proposed model can outperform the conventional model.

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

    Science.gov (United States)

    Babin, Steven M.

    1995-08-01

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

  7. Ocean tides in GRACE monthly averaged gravity fields

    DEFF Research Database (Denmark)

    Knudsen, Per

    2003-01-01

    aims at. In this analysis the results of Knudsen and Andersen (2002) have been verified using actual post-launch orbit parameter of the GRACE mission. The current ocean tide models are not accurate enough to correct GRACE data at harmonic degrees lower than 47. The accumulated tidal errors may affect......The GRACE mission will map the Earth's gravity fields and its variations with unprecedented accuracy during its 5-year lifetime. Unless ocean tide signals and their load upon the solid earth are removed from the GRACE data, their long period aliases obscure more subtle climate signals which GRACE...... the GRACE data up to harmonic degree 60. A study of the revised alias frequencies confirm that the ocean tide errors will not cancel in the GRACE monthly averaged temporal gravity fields. The S-2 and the K-2 terms have alias frequencies much longer than 30 days, so they remain almost unreduced...

  8. 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.

  9. Association of climate drivers with rainfall in New South Wales, Australia, using Bayesian Model Averaging

    Science.gov (United States)

    Duc, Hiep Nguyen; Rivett, Kelly; MacSween, Katrina; Le-Anh, Linh

    2017-01-01

    Rainfall in New South Wales (NSW), located in the southeast of the Australian continent, is known to be influenced by four major climate drivers: the El Niño/Southern Oscillation (ENSO), the Interdecadal Pacific Oscillation (IPO), the Southern Annular Mode (SAM) and the Indian Ocean Dipole (IOD). Many studies have shown the influences of ENSO, IPO modulation, SAM and IOD on rainfall in Australia and on southeast Australia in particular. However, only limited work has been undertaken using a multiple regression framework to examine the extent of the combined effect of these climate drivers on rainfall. This paper analysed the role of these combined climate drivers and their interaction on the rainfall in NSW using Bayesian Model Averaging (BMA) to account for model uncertainty by considering each of the linear models across the whole model space which is equal to the set of all possible combinations of predictors to find the model posterior probabilities and their expected predictor coefficients. Using BMA for linear regression models, we are able to corroborate and confirm the results from many previous studies. In addition, the method gives the ranking order of importance and the probability of the association of each of the climate drivers and their interaction on the rainfall at a site. The ability to quantify the relative contribution of the climate drivers offers the key to understand the complex interaction of drivers on rainfall, or lack of rainfall in a region, such as the three big droughts in southeastern Australia which have been the subject of discussion and debate recently on their causes.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. 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°.

  18. 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}.

  19. MONTHLY AVERAGE FLOW IN RÂUL NEGRU HYDROGRAPHIC BASIN

    Directory of Open Access Journals (Sweden)

    VIGH MELINDA

    2014-03-01

    Full Text Available Râul Negru hydrographic basin represents a well individualised and relatively homogenous physical-geographical unity from Braşov Depression. The flow is controlled by six hydrometric stations placed on the main collector and on two of the most powerful tributaries. Our analysis period is represented by the last 25 years (1988 - 2012 and it’s acceptable for make pertinent conclusions. The maximum discharge month is April, that it’s placed in the high flow period: March – June. Minimum discharges appear in November - because of the lack of pluvial precipitations; in January because of high solid precipitations and because of water volume retention in ice. Extreme discharge frequencies vary according to their position: in the mountain area – small basin surface; into a depression – high basin surface. Variation coefficients point out very similar variation principles, showing a relative homogeneity of flow processes.

  20. 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.

  1. 20 CFR 404.210 - Average-indexed-monthly-earnings method.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Average-indexed-monthly-earnings method. 404... DISABILITY INSURANCE (1950- ) Computing Primary Insurance Amounts Average-Indexed-Monthly-Earnings Method of Computing Primary Insurance Amounts § 404.210 Average-indexed-monthly-earnings method. (a) Who is...

  2. 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...

  3. 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.

  4. 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.

  5. 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.

  6. Sampling Errors of SSM/I and TRMM Rainfall Averages: Comparison with Error Estimates from Surface Data and a Sample Model

    Science.gov (United States)

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

    2000-01-01

    Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote-sensing error and, in the case of low-orbiting satellites, sampling error due to the limited number of observations of the grid box provided by the satellite. A simple model of rain behavior predicts that Root-mean-square (RMS) random error in grid-box averages should depend in a simple way on the local average rain rate, and the predicted behavior has been seen in simulations using surface rain-gauge and radar data. This relationship was examined using satellite SSM/I data obtained over the western equatorial Pacific during TOGA COARE. RMS error inferred directly from SSM/I rainfall estimates was found to be larger than predicted from surface data, and to depend less on local rain rate than was predicted. Preliminary examination of TRMM microwave estimates shows better agreement with surface data. A simple method of estimating rms error in satellite rainfall estimates is suggested, based on quantities that can be directly computed from the satellite data.

  7. 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.

  8. [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.

  9. 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. 

  10. 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.

  11. Average Wait Time Until Hearing Held Report (By Month), September 2016 (53rd week)

    Data.gov (United States)

    Social Security Administration — A presentation of the average time (in months) from the hearing request date until a hearing is held for claims pending in the Office of Disability Adjudication and...

  12. Assessing diffuse and concentrated recharge in average and dry rainfall year in a semiarid carbonate sloping aquifer a preliminary report

    Energy Technology Data Exchange (ETDEWEB)

    Alcala, F. J.; Were, A.; Serrano-Ortiz, P.; Canton, Y.; Sole, A.; Villagarcia, L.; Contreras, S.; Kowalski, A. S.; Marrero, R.; Puigdefabregas, J.; Domingo, F.

    2009-07-01

    The chloride mass balance (CMB) method was applied in the unsaturated zone to estimate potential recharge (R{sub t}) rainfall in two small catchment of southern mid-to-high slope of Sierra de Gador carbonate aquifer (SE Spain) , in the average hydrological year 2003-04 and the unusually dry 2004-05. Unknown fractions of diffuse (R{sub D}) and concentrated recharge (R{sub c}) into R{sub t} were firstly evaluated to fit average and lower R{sub T} thresholds for modeling further long-term recharge. Daily rainfall and actual evapotranspiration (AET) from the Eddy Covariance (EC) technique provided yearly R{sub T} of 189 mm year{sup -}1 in 2003-04 and 8 mm year{sup -}1 in 2004-05.

  13. Using of rank distributions in the study of perennial changes for monthly average temperatures

    Science.gov (United States)

    Nemirovskiy, V. B.; Stoyanov, A. K.; Tartakovsky, V. A.

    2015-11-01

    The possibility of comparing the climatic data of various years with using rank distributions is considered in this paper. As a climatic data, the annual variation of temperature on the spatial areas of meteorological observations with high variability in average temperatures is considered. The results of clustering of the monthly average temperatures values by means of a recurrent neural network were used as the basis of comparing. For a given space of weather observations the rank distribution of the clusters cardinality identified for each year of observation, is being constructed. The resulting rank distributions allow you to compare the spatial temperature distributions of various years. An experimental comparison for rank distributions of the annual variation of monthly average temperatures has confirmed the presence of scatter for various years, associated with different spatio-temporal distribution of temperature. An experimental comparison of rank distributions revealed a difference in the integral annual variation of monthly average temperatures of various years for the Northern Hemisphere.

  14. Age-specific average head template for typically developing 6-month-old infants.

    Directory of Open Access Journals (Sweden)

    Lisa F Akiyama

    Full Text Available Due to the rapid anatomical changes that occur within the brain structure in early human development and the significant differences between infant brains and the widely used standard adult templates, it becomes increasingly important to utilize appropriate age- and population-specific average templates when analyzing infant neuroimaging data. In this study we created a new and highly detailed age-specific unbiased average head template in a standard MNI152-like infant coordinate system for healthy, typically developing 6-month-old infants by performing linear normalization, diffeomorphic normalization and iterative averaging processing on 60 subjects' structural images. The resulting age-specific average templates in a standard MNI152-like infant coordinate system demonstrate sharper anatomical detail and clarity compared to existing infant average templates and successfully retains the average head size of the 6-month-old infant. An example usage of the average infant templates transforms magnetoencephalography (MEG estimated activity locations from MEG's subject-specific head coordinate space to the standard MNI152-like infant coordinate space. We also created a new atlas that reflects the true 6-month-old infant brain anatomy. Average templates and atlas are publicly available on our website (http://ilabs.washington.edu/6-m-templates-atlas.

  15. 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.

  16. 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.

  17. Seasonal Variation in Monthly Average Air Change Rates Using Passive Tracer Gas Measurements

    DEFF Research Database (Denmark)

    Frederiksen, Marie; Bergsøe, Niels Christian; Kolarik, Barbara

    2011-01-01

    Indoor air quality in dwellings is largely determined by the air change rate (ACR) and the magnitude of indoor air pollution sources. Concurrently, great efforts are made to make buildings energy efficient, which may result in low ACRs. In the present study, the monthly ACR averages were measured...

  18. Monthly average daily global solar radiation in P. D. R. Yemen

    Energy Technology Data Exchange (ETDEWEB)

    Gadhi, S.M.B.; Megdad, R.S.; Albakri, S.A.A. (Aden Univ. (Yemen). Dept. of Mechanical Engineering)

    1991-01-01

    In this paper a study has been made to estimate average global radiation using hours of bright sunshine and measured solar radiation data available for six locations in P.D.R. Yemen. For Aden, data were obtained from Aden Airport. For other locations in P.D.R. Yemen data were obtained from Agricultural Research Center's meteorological sections. Linear regression analysis of the monthly average global radiation and the sunshine duration data of six locations has been performed using the least squares technique. All the above mentioned data have been used in Angstrom's correlation to find the monthly average daily global solar radiation. Results obtained are useful for any solar energy system application in P.D.R. Yemen. (author).

  19. Path-average rainfall estimation from optical extinction measurements using a large-aperture scintillometer

    NARCIS (Netherlands)

    Uijlenhoet, R.; Cohard, J.M.; Gosset, M.

    2011-01-01

    The potential of a near-infrared large-aperture boundary layer scintillometer as path-average rain gauge is investigated. The instrument was installed over a 2.4-km path in Benin as part of the African Monsoon Multidisciplinary Analysis (AMMA) Enhanced Observation Period during 2006 and 2007. Measur

  20. 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.

  1. 20 CFR 404.222 - Use of benefit table in finding your primary insurance amount from your average monthly wage.

    Science.gov (United States)

    2010-04-01

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

  2. Estimation of the diffuse radiation fraction for hourly, daily and monthly-average global radiation

    Science.gov (United States)

    Erbs, D. G.; Klein, S. A.; Duffie, J. A.

    1982-01-01

    Hourly pyrheliometer and pyranometer data from four U.S. locations are used to establish a relationship between the hourly diffuse fraction and the hourly clearness index. This relationship is compared to the relationship established by Orgill and Hollands (1977) and to a set of data from Highett, Australia, and agreement is within a few percent in both cases. The transient simulation program TRNSYS is used to calculate the annual performance of solar energy systems using several correlations. For the systems investigated, the effect of simulating the random distribution of the hourly diffuse fraction is negligible. A seasonally dependent daily diffuse correlation is developed from the data, and this daily relationship is used to derive a correlation for the monthly-average diffuse fraction.

  3. Estimation of monthly average daily global solar irradiation using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Mubiru, J.; Banda, E.J.K.B. [Department of Physics, Makerere University, P.O. Box 7062, Kampala (Uganda)

    2008-02-15

    This study explores the possibility of developing a prediction model using artificial neural networks (ANN), which could be used to estimate monthly average daily global solar irradiation on a horizontal surface for locations in Uganda based on weather station data: sunshine duration, maximum temperature, cloud cover and location parameters: latitude, longitude, altitude. Results have shown good agreement between the estimated and measured values of global solar irradiation. A correlation coefficient of 0.974 was obtained with mean bias error of 0.059 MJ/m{sup 2} and root mean square error of 0.385 MJ/m{sup 2}. The comparison between the ANN and empirical method emphasized the superiority of the proposed ANN prediction model. (author)

  4. Monthly-averaged anthropogenic aerosol direct radiative forcing over the Mediterranean based on AERONET aerosol properties

    Directory of Open Access Journals (Sweden)

    A. Bergamo

    2008-12-01

    Full Text Available The all-sky direct radiative effect by anthropogenic aerosol (DREa is calculated in the solar (0.3–4 μm and infrared (4–200 μm spectral ranges for six Mediterranean sites. The sites are differently affected by pollution and together reflect typical aerosol impacts that are expected over land and coastal sites of the central Mediterranean basin. Central to the simulations are aerosol optical properties from AERONET sun-/sky-photometer statistics for the year 2003. A discussion on the variability of the overall (natural + anthropogenic aerosol properties with site location is provided. Supplementary data include MODIS satellite sensor based solar surface albedos, ISCCP products for high- mid- and low cloud cover and estimates for the anthropogenic aerosol fraction from global aerosol models. Since anthropogenic aerosol particles are considered to be smaller than 1 μm in size, mainly the solar radiation transfer is affected with impacts only during sun-light hours. At all sites the (daily average solar DREa is negative all year round at the top of the atmosphere (ToA. Hence, anthropogenic particles produce over coastal and land sites of the central Mediterranean a significant cooling effect. Monthly DREa values vary from site to site and are seasonally dependent as a consequence of the seasonal dependence of available sun-light and microphysical aerosol properties. At the ToA the monthly average DREa is −(4±1 W m−2 during spring-summer (SS, April–September and −(2±1 W m−2 during autumn-winter (AW, October–March at the polluted sites. In contrast, it varies between −(3±1 W m−2 and −(1±1 W m−2 on SS and AW, respectively at the less polluted site. Due to atmospheric absorption the DREa at the surface is larger than at the ToA. At the surface the monthly average DREa varies between the most and the least polluted

  5. CHAMP climate data based on inversion of monthly average bending angles

    Directory of Open Access Journals (Sweden)

    J. Danzer

    2014-07-01

    Full Text Available GNSS Radio Occultation (RO refractivity climatologies for the stratosphere can be obtained from the Abel inversion of monthly average bending-angle profiles. The averaging of large numbers of profiles suppresses random noise and this, in combination with simple exponential extrapolation above an altitude of 80 km, circumvents the need for a "statistical optimization" step in the processing. Using data from the US-Taiwanese COSMIC mission, which provides ~ 1500–2000 occultations per day, it has been shown that this Average-Profile Inversion (API technique provides a robust method for generating stratospheric refractivity climatologies. Prior to the launch of COSMIC in mid-2006, the data records rely on data from the CHAMP mission. In order to exploit the full range of available RO data, the usage of CHAMP data is also required. CHAMP only provided ~ 200 profiles per day, and the measurements were noisier than COSMIC. As a consequence, the main research question in this study was to see if the average bending angle approach is also applicable to CHAMP data. Different methods for suppression of random noise – statistical and through data quality pre-screening – were tested. The API retrievals were compared with the more conventional approach of averaging individual refractivity profiles, produced with the implementation of statistical optimization used in the EUMETSAT Radio Occultation Meteorology Satellite Application Facility (ROM SAF operational processing. In this study it is demonstrated that the API retrieval technique works well for CHAMP data, enabling the generation of long-term stratospheric RO climate data records from August 2001 and onward. The resulting CHAMP refractivity climatologies are found to be practically identical to the standard retrieval at the DMI below altitudes of 35 km. Between 35 km to 50 km the differences between the two retrieval methods started to increase, showing largest differences at high latitudes and

  6. Comparison of Two Methods for Estimating the Sampling-Related Uncertainty of Satellite Rainfall Averages Based on a Large Radar Data Set

    Science.gov (United States)

    Lau, William K. M. (Technical Monitor); Bell, Thomas L.; Steiner, Matthias; Zhang, Yu; Wood, Eric F.

    2002-01-01

    The uncertainty of rainfall estimated from averages of discrete samples collected by a satellite is assessed using a multi-year radar data set covering a large portion of the United States. The sampling-related uncertainty of rainfall estimates is evaluated for all combinations of 100 km, 200 km, and 500 km space domains, 1 day, 5 day, and 30 day rainfall accumulations, and regular sampling time intervals of 1 h, 3 h, 6 h, 8 h, and 12 h. These extensive analyses are combined to characterize the sampling uncertainty as a function of space and time domain, sampling frequency, and rainfall characteristics by means of a simple scaling law. Moreover, it is shown that both parametric and non-parametric statistical techniques of estimating the sampling uncertainty produce comparable results. Sampling uncertainty estimates, however, do depend on the choice of technique for obtaining them. They can also vary considerably from case to case, reflecting the great variability of natural rainfall, and should therefore be expressed in probabilistic terms. Rainfall calibration errors are shown to affect comparison of results obtained by studies based on data from different climate regions and/or observation platforms.

  7. 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.

  8. Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Average Monthly Precipitation, 2002

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This data set represents the average monthly precipitation in millimeters multiplied by 100 for 2002 compiled for every catchment of NHDPlus for the conterminous...

  9. 20 CFR 404.211 - Computing your average indexed monthly earnings.

    Science.gov (United States)

    2010-04-01

    ..., recompute Ms. M.'s DIB beginning with July 1981 to give her the advantage of the child care dropout. To do... and you exercise, or have the right to exercise, parental control. See § 404.366(c) for a further... period of 3 months, or one-half the time after the child's birth or before the child attained age 3. (iii...

  10. Assessing monthly average solar radiation models: a comparative case study in Turkey.

    Science.gov (United States)

    Sonmete, Mehmet H; Ertekin, Can; Menges, Hakan O; Hacıseferoğullari, Haydar; Evrendilek, Fatih

    2011-04-01

    Solar radiation data are required by solar engineers, architects, agriculturists, and hydrologists for many applications such as solar heating, cooking, drying, and interior illumination of buildings. In order to achieve this, numerous empirical models have been developed all over the world to predict solar radiation. The main objective of this study is to examine and compare 147 solar radiation models available in the literature for the prediction of monthly solar radiation at Ankara (Turkey) based on selected statistical measures such as percentage error, mean percentage error, root mean square error, mean bias error, and correlation coefficient. Our results showed that Ball et al. (Agron J 96:391-397, 2004) model and Chen et al. (Energy Convers Manag 47:2859-2866, 2006) model performed best in the estimation of solar radiation on a horizontal surface for Ankara.

  11. Mean annual water-budget components for the Island of Oahu, Hawaii, for average climate conditions, 1978-2007 rainfall and 2010 land cover

    Science.gov (United States)

    Engott, John A.

    2015-01-01

    The shapefile associated with this metadata file represents the spatial distribution of mean annual water-budget components, in inches, for the Island of Oahu, Hawaii. The water-budget components in the shapefile were computed by a water-budget model for a scenario representative of average climate conditions (1978-2007 rainfall) and 2010 land cover, as described in USGS Scientific Investigations Report (SIR) 2015-5010. The model was developed for estimating groundwater recharge and other water-budget components for each subarea of the model. The model subareas were generated using Esri ArcGIS software by intersecting (merging) multiple spatial data sets that characterize the spatial distribution of rainfall, fog interception, irrigation, reference evapotranspiration, direct runoff, soil type, and land cover. These spatial data sets characterize the spatial distribution of hydrologic and physical conditions that the model uses to compute groundwater recharge and other water-budget components.The model-subarea data set (387,533 polygons) was subsequently intersected with the 0-ft elevation contour of the top of the basalt aquifer to produce the 395,955 polygons in this shapefile. This metadata file describes the process of merging these spatial data sets, The shapefile attribute information associated with each polygon present an estimate of mean annual rainfall, fog interception, irrigation, septic-system leachate, runoff, canopy evaporation, actual evapotranspiration, storm-drain capture, net precipitation, total evapotranspiration, recharge, and seepage from reservoirs and cesspools. This shapefile also includes select geographic and land-cover attributes of the polygons. Brief descriptions of the water-budget components and attributes are included in this metadata file. Refer to USGS SIR 2015-5010 (doi:10.3133/sir20155010) for further details of the methods and sources used to determine these components and attributes.

  12. The impact of orbital sampling, monthly averaging and vertical resolution on climate chemistry model evaluation with satellite observations

    Directory of Open Access Journals (Sweden)

    A. M. Aghedo

    2011-07-01

    Full Text Available Ensemble climate model simulations used for the Intergovernmental Panel on Climate Change (IPCC assessments have become important tools for exploring the response of the Earth System to changes in anthropogenic and natural forcings. The systematic evaluation of these models through global satellite observations is a critical step in assessing the uncertainty of climate change projections. This paper presents the technical steps required for using nadir sun-synchronous infrared satellite observations for multi-model evaluation and the uncertainties associated with each step. This is motivated by need to use satellite observations to evaluate climate models. We quantified the implications of the effect of satellite orbit and spatial coverage, the effect of variations in vertical sensitivity as quantified by the observation operator and the impact of averaging the operators for use with monthly-mean model output. We calculated these biases in ozone, carbon monoxide, atmospheric temperature and water vapour by using the output from two global chemistry climate models (ECHAM5-MOZ and GISS-PUCCINI and the observations from the Tropospheric Emission Spectrometer (TES instrument on board the NASA-Aura satellite from January 2005 to December 2008.

    The results show that sampling and monthly averaging of the observation operators produce zonal-mean biases of less than ±3 % for ozone and carbon monoxide throughout the entire troposphere in both models. Water vapour sampling zonal-mean biases were also within the insignificant range of ±3 % (that is ±0.14 g kg−1 in both models. Sampling led to a temperature zonal-mean bias of ±0.3 K over the tropical and mid-latitudes in both models, and up to −1.4 K over the boundary layer in the higher latitudes. Using the monthly average of temperature and water vapour operators lead to large biases over the boundary layer in the southern-hemispheric higher latitudes and in the upper

  13. The impact of orbital sampling, monthly averaging and vertical resolution on climate chemistry model evaluation with satellite observations

    Directory of Open Access Journals (Sweden)

    A. M. Aghedo

    2011-03-01

    Full Text Available Ensemble climate model simulations used for the Intergovernmental Panel on Climate Change (IPCC assessments have become important tools for exploring the response of the Earth System to changes in anthropogenic and natural forcings. The systematic evaluation of these models through global satellite observations is a critical step in assessing the uncertainty of climate change projections. This paper presents the technical steps required for using nadir sun-synchronous infrared satellite observations for multi-model evaluation and the uncertainties associated with each step. This is motivated by need to use satellite observations to evaluate climate models. We quantified the implications of the effect of satellite orbit and spatial coverage, the effect of variations in vertical sensitivity as quantified by the observation operator and the impact of averaging the operators for use with monthly-mean model output. We calculated these biases in ozone, carbon monoxide, atmospheric temperature and water vapour by using the output from two global chemistry climate models (ECHAM5-MOZ and GISS-PUCCINI and the observations from the Tropospheric Emission Spectrometer (TES satellite from January 2005 to December 2008.

    The results show that sampling and monthly averaging of the observation operators produce biases of less than ±3% for ozone and carbon monoxide throughout the entire troposphere in both models. Water vapour sampling biases were also within the insignificant range of ±3% (that is ±0.14 g kg−1 in both models. Sampling led to a temperature bias of ±0.3 K over the tropical and mid-latitudes in both models, and up to −1.4 K over the boundary layer in the higher latitudes. Using the monthly average of temperature and water vapour operators lead to large biases over the boundary layer in the southern-hemispheric higher latitudes and in the upper troposphere, respectively. Up to 8% bias was calculated in the upper

  14. 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...

  15. CERES Monthly TOA and SRB Averages (SRBAVG) data in HDF-EOS Grid (CER_SRBAVG_Terra-FM1-MODIS_Edition2D)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Monthly TOA/Surface Averages (SRBAVG) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SRBAVG is also produced for combinations of scanner instruments. The monthly average regional flux is estimated using diurnal models and the 1-degree regional fluxes at the hour of observation from the CERES SFC product. A second set of monthly average fluxes are estimated using concurrent diurnal information from geostationary satellites. These fluxes are given for both clear-sky and total-sky scenes and are spatially averaged from 1-degree regions to 1-degree zonal averages and a global average. For each region, the SRBAVG also contains hourly average fluxes for the month and an overall monthly average. The cloud properties from SFC are column averaged and are included on the SRBAVG. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-02-01; Stop_Date=2004-05-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

  16. CERES Monthly TOA and SRB Averages (SRBAVG) data in HDF-EOS Grid (CER_SRBAVG_Terra-FM1-MODIS_Edition2C)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Monthly TOA/Surface Averages (SRBAVG) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SRBAVG is also produced for combinations of scanner instruments. The monthly average regional flux is estimated using diurnal models and the 1-degree regional fluxes at the hour of observation from the CERES SFC product. A second set of monthly average fluxes are estimated using concurrent diurnal information from geostationary satellites. These fluxes are given for both clear-sky and total-sky scenes and are spatially averaged from 1-degree regions to 1-degree zonal averages and a global average. For each region, the SRBAVG also contains hourly average fluxes for the month and an overall monthly average. The cloud properties from SFC are column averaged and are included on the SRBAVG. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-02-01; Stop_Date=2003-02-28] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

  17. CERES Monthly TOA and SRB Averages (SRBAVG) data in HDF-EOS Grid (CER_SRBAVG_TRMM-PFM-VIRS_Edition2B)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Monthly TOA/Surface Averages (SRBAVG) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SRBAVG is also produced for combinations of scanner instruments. The monthly average regional flux is estimated using diurnal models and the 1-degree regional fluxes at the hour of observation from the CERES SFC product. A second set of monthly average fluxes are estimated using concurrent diurnal information from geostationary satellites. These fluxes are given for both clear-sky and total-sky scenes and are spatially averaged from 1-degree regions to 1-degree zonal averages and a global average. For each region, the SRBAVG also contains hourly average fluxes for the month and an overall monthly average. The cloud properties from SFC are column averaged and are included on the SRBAVG. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-02-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

  18. CERES Monthly TOA and SRB Averages (SRBAVG) data in HDF-EOS Grid (CER_SRBAVG_Terra-FM2-MODIS_Edition2D)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The Monthly TOA/Surface Averages (SRBAVG) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SRBAVG is also produced for combinations of scanner instruments. The monthly average regional flux is estimated using diurnal models and the 1-degree regional fluxes at the hour of observation from the CERES SFC product. A second set of monthly average fluxes are estimated using concurrent diurnal information from geostationary satellites. These fluxes are given for both clear-sky and total-sky scenes and are spatially averaged from 1-degree regions to 1-degree zonal averages and a global average. For each region, the SRBAVG also contains hourly average fluxes for the month and an overall monthly average. The cloud properties from SFC are column averaged and are included on the SRBAVG. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-02-01; Stop_Date=2004-05-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

  19. Two-dimensional monthly average ozone balance from limb infrared monitor of the stratosphere and stratospheric and mesospheric sounder data

    Science.gov (United States)

    Jackman, C. H.; Stolarski, R. S.; Kaye, J. A.

    1986-01-01

    For many years, atmospheric scientists have been concerned with the balance of ozone production and loss terms in the upper stratosphere. Crutzen and Schmailzl (1983) found that the ozone loss was higher than the ozone production in the upper stratosphere. In the present investigation, previous studies are used as a basis in the conduction of a two-dimensional calculation of the production and loss of ozone. The monthly and zonally averaged loss and production rates for ozone are computed using recent Nimbus 7 satellite measurements of stratospheric constituents and accepted reaction and photodissociation rates. It is found that ozone has a loss rate which is about 40-60 percent higher than the production in the photochemical region.

  20. 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.

  1. Estimation of the monthly average daily solar radiation using geographic information system and advanced case-based reasoning.

    Science.gov (United States)

    Koo, Choongwan; Hong, Taehoon; Lee, Minhyun; Park, Hyo Seon

    2013-05-07

    The photovoltaic (PV) system is considered an unlimited source of clean energy, whose amount of electricity generation changes according to the monthly average daily solar radiation (MADSR). It is revealed that the MADSR distribution in South Korea has very diverse patterns due to the country's climatic and geographical characteristics. This study aimed to develop a MADSR estimation model for the location without the measured MADSR data, using an advanced case based reasoning (CBR) model, which is a hybrid methodology combining CBR with artificial neural network, multiregression analysis, and genetic algorithm. The average prediction accuracy of the advanced CBR model was very high at 95.69%, and the standard deviation of the prediction accuracy was 3.67%, showing a significant improvement in prediction accuracy and consistency. A case study was conducted to verify the proposed model. The proposed model could be useful for owner or construction manager in charge of determining whether or not to introduce the PV system and where to install it. Also, it would benefit contractors in a competitive bidding process to accurately estimate the electricity generation of the PV system in advance and to conduct an economic and environmental feasibility study from the life cycle perspective.

  2. Insolation data manual: long-term monthly averages of solar radiation, temperature, degree-days and global anti K/sub T/ for 248 national weather service stations

    Energy Technology Data Exchange (ETDEWEB)

    Knapp, C L; Stoffel, T L; Whitaker, S D

    1980-10-01

    Monthly averaged data is presented which describes the availability of solar radiation at 248 National Weather Service stations. Monthly and annual average daily insolation and temperature values have been computed from a base of 24 to 25 years of data. Average daily maximum, minimum, and monthly temperatures are provided for most locations in both Celsius and Fahrenheit. Heating and cooling degree-days were computed relative to a base of 18.3/sup 0/C (65/sup 0/F). For each station, global anti K/sub T/ (cloudiness index) were calculated on a monthly and annual basis. (MHR)

  3. Statistical comparison of models for estimating the monthly average daily diffuse radiation at a subtropical African site

    Energy Technology Data Exchange (ETDEWEB)

    Bashahu, M. [University of Burundi, Bujumbura (Burundi). Institute of Applied Pedagogy, Department of Physics and Technology

    2003-07-01

    Nine correlations have been developed in this paper to estimate the monthly average diffuse radiation for Dakar, Senegal. A 16-year period data on the global (H) and diffuse (H{sub d}) radiation, together with data on the bright sunshine hours (N), the fraction of the sky's (Ne/8), the water vapour pressure in the air (e) and the ambient temperature (T) have been used for that purpose. A model inter-comparison based on the MBE, RMSE and t statistical tests has shown that estimates in any of the obtained correlations are not significantly different from their measured counterparts, thus all the nine models are recommended for the aforesaid location. Three of them should be particularly selected for their simplicity, universal applicability and high accuracy. Those are simple linear correlations between K{sub d} and N/N{sub d}, Ne/8 or K{sub t}. Even presenting adequate performance, the remaining correlations are either simple but less accurate, or multiple or nonlinear regressions needing one or two input variables. (author)

  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. 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

  6. 4 km AVHRR Pathfinder v5.0 Global Day-Night Sea Surface Temperature Monthly and Yearly Averages, 1985-2009 (NODC Accession 0077816)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains a set of monthly and yearly global day-night sea surface temperature averages, derived from the AVHRR Pathfinder Version 5 sea surface...

  7. 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

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

    Science.gov (United States)

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

    2017-04-01

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

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

    National Research Council Canada - National Science Library

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

    2017-01-01

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

  10. On the Relationship between Solar Wind Speed, Earthward-Directed Coronal Mass Ejections, Geomagnetic Activity, and the Sunspot Cycle Using 12-Month Moving Averages

    Science.gov (United States)

    Wilson, Robert M.; Hathaway, David H.

    2008-01-01

    For 1996 .2006 (cycle 23), 12-month moving averages of the aa geomagnetic index strongly correlate (r = 0.92) with 12-month moving averages of solar wind speed, and 12-month moving averages of the number of coronal mass ejections (CMEs) (halo and partial halo events) strongly correlate (r = 0.87) with 12-month moving averages of sunspot number. In particular, the minimum (15.8, September/October 1997) and maximum (38.0, August 2003) values of the aa geomagnetic index occur simultaneously with the minimum (376 km/s) and maximum (547 km/s) solar wind speeds, both being strongly correlated with the following recurrent component (due to high-speed streams). The large peak of aa geomagnetic activity in cycle 23, the largest on record, spans the interval late 2002 to mid 2004 and is associated with a decreased number of halo and partial halo CMEs, whereas the smaller secondary peak of early 2005 seems to be associated with a slight rebound in the number of halo and partial halo CMEs. Based on the observed aaM during the declining portion of cycle 23, RM for cycle 24 is predicted to be larger than average, being about 168+/-60 (the 90% prediction interval), whereas based on the expected aam for cycle 24 (greater than or equal to 14.6), RM for cycle 24 should measure greater than or equal to 118+/-30, yielding an overlap of about 128+/-20.

  11. A preliminary study of the linear relationship between monthly averaged daily solar radiation and daily thermal amplitude in the north of Buenos Aires provence

    CERN Document Server

    Cionco, R; Rodriguez, R

    2012-01-01

    Using irradiance and temperature measurements obtained at the Facultad Regional San Nicol\\'as of UTN, we performed a preliminary study of the linear relationship between monthly averaged daily solar radiation and daily thermal amplitude. The results show a very satisfactory adjustment (R = 0.848, RMS = 0.066, RMS% = 9.690 %), even taking into account the limited number of months (36). Thus, we have a formula of predictive nature, capable of estimating mean monthly solar radiation for various applications. We expect to have new data sets to expand and improve the statistical significance of these results.

  12. 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.

  13. ACDF Using the Solis Cage with Iliac Bone Graft in Single Level: Clinical and Radiological Outcomes in Average 36 months Follow-up.

    Science.gov (United States)

    Oh, Si-Hyuck; Yoon, Kyeong-Wook; Kim, Young-Jin; Lee, Sang-Koo

    2013-06-01

    To evaluate the utility of anterior cervical discectomy and fusion (ACDF) with polyetheretherketone (PEEK) cage and autograft through long term(average 36 months) follow-up. Thirty selected patients (male:20/female:10) who suffered from cervical radiculopathy, myelopathy or radiculomyelopathy underwent a single level ACDF with PEEK cage and autograft from iliac crest from March 2006 to July 2008 in single institute. We followed patients for an average 36.4±8.1 months (ranged from 23 to 49 months). The Japanese Orthopedic Association (JOA) score for evaluation of myelopathy and visual analogue scale (VAS) for radiating pain was used to estimate postoperative clinical outcome. Plain x-ray on true lateral standing flexion, extension and neutral position view and 3D CT scan were used every 6 months after surgery during follow-up period. The mean VAS and JOA scoring improved significantly after the surgery and radiological fusion rate was accomplished by 100% 36 months after the surgery. We had no complication related with the surgery except one case of osteomyelitis. There was one case of Grade I fusion, four cases of grade II, and 25 cases of grade III by radiologic evaluation. This long term follow-up study for ACDF with PEEK cage shows that this surgical method is comparable with other anterior cervical fusion methods in terms of clinical outcomes and radiologic fusion rate.

  14. 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.

  15. 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.

  16. 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.

  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. 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

  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. 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.

  1. 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.

  2. 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

  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. Influence of Northwest Cloudbands on Southwest Australian Rainfall

    Directory of Open Access Journals (Sweden)

    Nicola Telcik

    2014-01-01

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

  5. Statistical downscaling of general-circulation-model- simulated average monthly air temperature to the beginning of flowering of the dandelion (Taraxacum officinale) in Slovenia

    Science.gov (United States)

    Bergant, Klemen; Kajfež-Bogataj, Lučka; Črepinšek, Zalika

    2002-02-01

    Phenological observations are a valuable source of information for investigating the relationship between climate variation and plant development. Potential climate change in the future will shift the occurrence of phenological phases. Information about future climate conditions is needed in order to estimate this shift. General circulation models (GCM) provide the best information about future climate change. They are able to simulate reliably the most important mean features on a large scale, but they fail on a regional scale because of their low spatial resolution. A common approach to bridging the scale gap is statistical downscaling, which was used to relate the beginning of flowering of Taraxacum officinale in Slovenia with the monthly mean near-surface air temperature for January, February and March in Central Europe. Statistical models were developed and tested with NCAR/NCEP Reanalysis predictor data and EARS predictand data for the period 1960-1999. Prior to developing statistical models, empirical orthogonal function (EOF) analysis was employed on the predictor data. Multiple linear regression was used to relate the beginning of flowering with expansion coefficients of the first three EOF for the Janauary, Febrauary and March air temperatures, and a strong correlation was found between them. Developed statistical models were employed on the results of two GCM (HadCM3 and ECHAM4/OPYC3) to estimate the potential shifts in the beginning of flowering for the periods 1990-2019 and 2020-2049 in comparison with the period 1960-1989. The HadCM3 model predicts, on average, 4 days earlier occurrence and ECHAM4/OPYC3 5 days earlier occurrence of flowering in the period 1990-2019. The analogous results for the period 2020-2049 are a 10- and 11-day earlier occurrence.

  6. Heavy daily-rainfall characteristics over the Gauteng Province

    African Journals Online (AJOL)

    2009-02-09

    Feb 9, 2009 ... Department of Geography, Geoinformatics and Meteorology, Geography Building 2-12, University of .... An example of heavy rainfall 'climatology' in the scientific .... rainfall stations in the calculation of the area-average rainfall.

  7. 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.

  8. 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.

  9. 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.

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

    Science.gov (United States)

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

    2010-01-01

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

  11. 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.

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

    Science.gov (United States)

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

    2012-11-01

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

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

    Science.gov (United States)

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

    2001-01-01

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

  14. 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.

  15. A Regenerative Prediction Algorithm for Indian Rainfall Prediction

    Directory of Open Access Journals (Sweden)

    SEEMA MAHAJAN

    2013-11-01

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

  16. 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.

  17. 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

  18. 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

  19. 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

  20. State Averages

    Data.gov (United States)

    U.S. Department of Health & Human Services — A list of a variety of averages for each state or territory as well as the national average, including each quality measure, staffing, fine amount and number of...

  1. 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

  2. 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.

  3. Monthly Near-Surface Air Temperature Averages

    Data.gov (United States)

    National Aeronautics and Space Administration — Global surface temperatures in 2010 tied 2005 as the warmest on record. The International Satellite Cloud Climatology Project (ISCCP) was established in 1982 as part...

  4. Análisis metodológico de la distribución espacial de la precipitación y la estimación media diaria Methodological analysis of the spatial distribution of rainfall and the average daily stimation

    Directory of Open Access Journals (Sweden)

    Mauro Íñiguez Covarrubias

    2011-02-01

    Full Text Available El objetivo del trabajo consistió en mostrar un análisis metodológico geoestadístico, para generar un patrón espacial de la lluvia, asociado a la precipitación media diaria. Caracterizar y conocer la distribución espacial de la precipitación, también conocida como "campo de tormenta" y asociarla a un modelo de distribución o sustituirla por una precipitación media por métodos convencionales, es un reto importante en estudios de las ciencias del agua. La metodología propuesta requiere de la construcción de un variograma, elaborado por un ajuste de datos experimentales de un campo de tormenta, que sirva como base para generar la distribución espacial de la lluvia con la aplicación del método geoestadístico del "krigeado". Esto permite determinar la precipitación media diaria de una cuenca hidrográfica. Los resultados muestran que es posible obtener una función que relacione la lluvia media con el campo de tormenta, mediante los parámetros α y β del variograma ajustado a un modelo esférico. Para validar la aplicación de la metodología se analizaron varios eventos, aquí se presentan dos eventos de precipitación observada en la cuenca del río Juchipila, y río Calvillo, entre los estados de Aguascalientes y Zacatecas. Los resultados muestran una relación única de la lluvia media diaria con la distribución espacial, representada por el campo de tormenta. Asimismo, se encontró que el valor óptimo de la función es mínimo al compararlo con los resultados obtenidos por cuatro métodos convencionales: promedio aritmético, polígonos de Thiessen, método de isoyetas y método de krigeado lineal.The aim of the study was to show a geostatistical methodological analysis to create a spatial pattern of rain, related to average daily rainfall. Defining and knowing the spatial distribution of rainfall, also known as the "storm field" and related to a distribution model, or replacing it to an average rainfall using conventional

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

    Directory of Open Access Journals (Sweden)

    Sanjay Bhelawe

    2015-04-01

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

  6. 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

  7. 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.

  8. 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...

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

    Directory of Open Access Journals (Sweden)

    Adi Nugroho

    2014-11-01

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

  10. 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

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

    Science.gov (United States)

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

    2017-02-01

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

  12. Rainfall erosivity in subtropical catchments and implications for erosion and particle-bound contaminant transfer: a case-study of the Fukushima region

    Directory of Open Access Journals (Sweden)

    J. P. Laceby

    2015-07-01

    Full Text Available The Fukushima Dai-ichi nuclear power plant (FDNPP accident in March 2011 resulted in a significant fallout of radiocesium over the Fukushima region. After reaching the soil surface, radiocesium is almost irreversibly bound to fine soil particles. Thereafter, rainfall and snow melt run-off events transfer particle-bound radiocesium downstream. Erosion models, such as the Universal Soil Loss Equation (USLE, depict a proportional relationship between rainfall and soil erosion. As radiocesium is tightly bound to fine soil and sediment particles, characterizing the rainfall regime of the fallout-impacted region is fundamental to modelling and predicting radiocesium migration. Accordingly, monthly and annual rainfall data from ~ 60 meteorological stations within a 100 km radius of the FDNPP were analysed. Monthly rainfall erosivity maps were developed for the Fukushima coastal catchments illustrating the spatial heterogeneity of rainfall erosivity in the region. The mean average rainfall in the Fukushima region was 1387 mm yr−1 (σ 230 with the mean rainfall erosivity being 2785 MJ mm ha−1 yr−1 (σ 1359. The results indicate that the majority of rainfall (60 % and rainfall erosivity (86 % occurs between June and October. During the year, rainfall erosivity evolves positively from northwest to southeast in the eastern part of the prefecture, whereas a positive gradient from north to south occurs in July and August, the most erosive months of the year. During the typhoon season, the coastal plain and eastern mountainous areas of the Fukushima prefecture, including a large part of the contamination plume, are most impacted by erosive events. Understanding these rainfall patterns, particularly their spatial and temporal variation, is fundamental to managing soil and particle-bound radiocesium transfers in the Fukushima region. Moreover, understanding the impact of typhoons is important for managing sediment transfers in subtropical regions impacted

  13. Rainfall erosivity in subtropical catchments and implications for erosion and particle-bound contaminant transfer: a case-study of the Fukushima region

    Science.gov (United States)

    Laceby, J. P.; Chartin, C.; Evrard, O.; Onda, Y.; Garcia-Sanchez, L.; Cerdan, O.

    2015-07-01

    The Fukushima Dai-ichi nuclear power plant (FDNPP) accident in March 2011 resulted in a significant fallout of radiocesium over the Fukushima region. After reaching the soil surface, radiocesium is almost irreversibly bound to fine soil particles. Thereafter, rainfall and snow melt run-off events transfer particle-bound radiocesium downstream. Erosion models, such as the Universal Soil Loss Equation (USLE), depict a proportional relationship between rainfall and soil erosion. As radiocesium is tightly bound to fine soil and sediment particles, characterizing the rainfall regime of the fallout-impacted region is fundamental to modelling and predicting radiocesium migration. Accordingly, monthly and annual rainfall data from ~ 60 meteorological stations within a 100 km radius of the FDNPP were analysed. Monthly rainfall erosivity maps were developed for the Fukushima coastal catchments illustrating the spatial heterogeneity of rainfall erosivity in the region. The mean average rainfall in the Fukushima region was 1387 mm yr-1 (σ 230) with the mean rainfall erosivity being 2785 MJ mm ha-1 yr-1 (σ 1359). The results indicate that the majority of rainfall (60 %) and rainfall erosivity (86 %) occurs between June and October. During the year, rainfall erosivity evolves positively from northwest to southeast in the eastern part of the prefecture, whereas a positive gradient from north to south occurs in July and August, the most erosive months of the year. During the typhoon season, the coastal plain and eastern mountainous areas of the Fukushima prefecture, including a large part of the contamination plume, are most impacted by erosive events. Understanding these rainfall patterns, particularly their spatial and temporal variation, is fundamental to managing soil and particle-bound radiocesium transfers in the Fukushima region. Moreover, understanding the impact of typhoons is important for managing sediment transfers in subtropical regions impacted by cyclonic activity.

  14. 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

  15. 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.

  16. Assessing Climate Variability using Extreme Rainfall and ...

    African Journals Online (AJOL)

    user1

    As noted by the Bureau of Meteorology, Canada, to examine whether such ... their local climate, a threshold considered extreme in one part of Australia could be ... (extreme frequency); the average intensity of rainfall from extreme events.

  17. 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.

  18. Mechanisms of improved rainfall simulation over the Maritime Continent due to increased horizontal resolution in an AGCM

    Science.gov (United States)

    Rashid, Harun A.; Hirst, Anthony C.

    2016-10-01

    The General Circulation Models experience a significant challenge in realistically simulating rainfall over the tropical Maritime Continent (hereafter, MC). Here, we investigate the mechanisms of an improvement in monthly rainfall simulation over the MC region in the UK Met Office Unified Model (version Global Atmosphere 6.0), which occurs when the horizontal resolution is increased from N96 (grid spacing 135 km) to N216 ( 60 km). The increased resolution enhances the area-averaged rainfall rate over the MC, thereby reducing the dry rainfall bias seen in the model at the N96 resolution. We find that the enhanced area-averaged rainfall is mostly due to an increase in the medium rainfall rates that occurs over the MC islands in the N216 experiment. The rainfall change is predominantly associated with changes in the atmospheric convective circulation and the related horizontal moisture flux convergence. The vertical profiles of convective circulation show a strong sensitivity to the increased horizontal resolution over the MC islands, but not over the surrounding oceans. It is shown that a significant underestimation of the deep convection (as opposed to the shallow convection) in the N96 experiment is primarily responsible for the stronger dry bias in this experiment. We present evidence that the dry bias, and the associated weaker deep convection, are in part caused by the strongly smoothed orography used in the N96 experiment, which provides a weaker orographic lifting of the moist surface air (in a conditionally unstable atmosphere) than that in the N216 experiment.

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

    Science.gov (United States)

    Shepherd, J. Marshall; Pierce, Harold; Starr, David OC. (Technical Monitor)

    2001-01-01

    This study represents one of the first published attempts to identify rainfall modification by urban areas using satellite-based rainfall measurements. Data from the first space-based rain-radar, the Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar, are employed. Analysis of the data enables identification of rainfall patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas during the warm season. Results reveal an average increase of -28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage chances are relative to an upwind CONTROL area. It was also found that maximum rainfall rates in the downwind impact area can exceed the mean value in the upwind CONTROL area by 48%-116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. These results are consistent with METROMEX studies of St. Louis almost two decades ago and more recent studies near Atlanta. Future work will investi(yate hypothesized factors causing rainfall modification by urban areas. Additional work is also needed to provide more robust validation of space-based rain estimates near major urban areas. Such research has implications for urban planning, water resource management, and understanding human impact on the environment.

  20. 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.

  1. Rainfall and temperatures during the 1991/92 drought in the Kruger National Park

    Directory of Open Access Journals (Sweden)

    N. Zambatis

    1995-09-01

    Full Text Available Rainfall and temperatures during the 1991/92 drought, the severest in the recorded history of the Kruger National Park (KNP, are described. Mean total rainfall for the KNP was 235.6 mm (44.1 of the long- term mean, with a median of 239.9 mm. The num- ber of days on which rain occurred also decreased significantly from a mean annual total of 48.3 to a mean of 24.2 in 1991/92. Daily maximum, minimum and average temperatures for some months increased significantly, as did the number of days within certain maximum temperature range classes.

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

    Directory of Open Access Journals (Sweden)

    Luki Subehi

    2016-08-01

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

  3. 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

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

    Science.gov (United States)

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

    2016-08-01

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

  5. 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.

  6. Investigating changes over time of annual rainfall in Zimbabwe

    Directory of Open Access Journals (Sweden)

    D. Mazvimavi

    2010-12-01

    Full Text Available There is increasing concern in southern Africa about the possible decline of rainfall as a result of global warming. Some studies concluded that average rainfall in Zimbabwe had declined by 10% or 100 mm during the last 100 years. This paper investigates the validity of the assumption that rainfall is declining in Zimbabwe. Time series of annual rainfall, and total rainfall for (a the early part of the rainy season, October-November-December (OND, and (b the mid to end of the rainy season, January-February-March (JFM are analysed for the presence of trends using the Mann-Kendall test, and for the decline or increase during years with either high or low rainfall using quantile regression analysis. The Pettitt test has also been utilized to examine the possible existence of change or break-points in the rainfall time series. The analysis has been done for 40 rainfall stations with records starting during the 1892–1940 period and ending in 2000, and representative of all the rainfall regions.

    The Mann-Kendal test did not identify a significant trend at all the 40 stations, and therefore there is no proof that the average rainfall at each of these stations has changed. Quantile regression analysis revealed a decline in annual rainfall less than the tenth percentile at only one station, and increasing of rainfall greater than the ninetieth percentile at another station. All the other stations had no changes over time in both the low and high rainfall at the annual interval. Climate change effects are therefore not yet statistically significant within time series of total seasonal and annual rainfall in Zimbabwe. The general perception about declining rainfall is likely due to the presence of multidecadal variability characterized by bunching of years with above (e.g. 1951–1958, 1973–1980 and below (e.g. 1959–1972, 1982–1994 average rainfall.

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

    Science.gov (United States)

    Petkovic, V.; Kummerow, C. D.

    2013-12-01

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

  8. Trends in rainfall and rainfall-related extremes in the east coast of peninsular Malaysia

    Indian Academy of Sciences (India)

    Olaniya Olusegun Mayowa; Sahar Hadi Pour; Shamsuddin Shahid; Morteza Mohsenipour; Sobri Bin Harun; Arien Heryansyah; Tarmizi Ismail

    2015-12-01

    The coastlines have been identified as the most vulnerable regions with respect to hydrological hazards as a result of climate change and variability. The east of peninsular Malaysia is not an exception for this, considering the evidence of heavy rainfall resulting in floods as an annual phenomenon and also water scarcity due to long dry spells in the region. This study examines recent trends in rainfall and rainfallrelated extremes such as, maximum daily rainfall, number of rainy days, average rainfall intensity, heavy rainfall days, extreme rainfall days, and precipitation concentration index in the east coast of peninsular Malaysia. Recent 40 years (1971–2010) rainfall records from 54 stations along the east coast of peninsular Malaysia have been analyzed using the non-parametric Mann–Kendall test and the Sen's slope method. The Monte Carlo simulation technique has been used to determine the field significance of the regional trends. The results showed that there was a substantial increase in the annual rainfall as well as the rainfall during the monsoon period. Also, there was an increase in the number of heavy rainfall days during the past four decades.

  9. Bayes统计模型在出山月均径流极小值研究中的应用%A Bayesian Analysis of Monthly Average Runoff Minima in Mountain Areas

    Institute of Scientific and Technical Information of China (English)

    刘友存; 霍雪丽; 郝永红; 崔玉环; 韩添丁; 沈永平; 王建

    2015-01-01

    Global warming has intensified hydrological extreme events and resulted in disasters around the world. For disaster management and adaption of extreme events,it is essential to improve the accuracy of extreme value statistical models. In this study,Bayes’Theorem is introduced to estimate parameters in the Generalized Pareto Distribution( GPD)model which is applied to simulate the distribution of monthly average runoff minima during dry periods in mountain areas of Ürümqi River. Bayes’Theorem treats parameters as random variables and provides machinery way to convert the prior distribution of parameters into a posterior distribution. Statistical inferences based on posterior distribution can provide a more comprehensive representation of the parameters. An improved Markov Chain Monte Carlo( MCMC)method,which can solve high-dimensional integral computation in the Bayes equation,is used to generate parameter simulations from the posterior distribution. Model diagnosis plots are made to guarantee the fitted GPD model is appropriate. Then based on the GPD model with Bayesian parameter esti-mates,monthly average minima corresponding to different return periods can be calculated. The results show that the improved MCMC method is able to make Markov chains converge at a high speed. Compared with the GPD model based on maximum likelihood parameter estimates,the GPD model based on Bayesian parameter estimates obtain more accurate estimations of minimum monthly average runoff. Moreover,the monthly average runoff minima in dry periods corresponding to 10 a,25 a,50 a and 100 a return periods are 0. 60 m3/s,0. 44 m3/s,0. 32 m3/s and 0. 20 m3/s respectively. The lower boundary of 95% confidence interval of 100a return level is -0. 238 m3/s,which implies that Ürümqi River is likely to cease when 100 a return level occurs in dry periods.%数理统计方法在解决全球气候变化引起的洪水、干旱等极端水文事件中获得了越来越广泛的

  10. HOW STRONG IS THE RELATIONSHIP BETWEEN RAINFALL VARIABILITY AND CAATINGA PRODUCTIVITY? A CASE STUDY UNDER A CHANGING CLIMATE.

    Science.gov (United States)

    Salimon, Cleber; Anderson, Liana

    2017-05-22

    Despite the knowledge of the influence of rainfall on vegetation dynamics in semiarid tropical Brazil, few studies address and explore quantitatively the various aspects of this relationship. Moreover, Northeast Brazil is expected to have its rainfall reduced by as much as 60% until the end of the 21st Century, under scenario AII of the IPCC Report 2010. We sampled and analyzed satellite-derived monthly rainfall and a vegetation index data for 40 sites with natural vegetation cover in Paraíba State, Brazil from 2001 to 2012. In addition, the anomalies for both variables were calculated. Rainfall variation explained as much as 50% of plant productivity, using the vegetation index as a proxy, and rainfall anomaly explained 80% of the vegetation productivity anomaly. In an extreme dry year (2012), with 65% less rainfall than average for the period 2001-2012, the vegetation index decreased by 25%. If such decrease persists in a long term trend in rainfall reduction, this could lead to a disruption in this ecosystem functioning and the dominant vegetation could become even more xeric or desert-like, bringing serious environmental, social and economical impacts.

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. Interannual and intra-annual variability of rainfall in Haiti (1905-2005)

    Science.gov (United States)

    Moron, Vincent; Frelat, Romain; Jean-Jeune, Pierre Karly; Gaucherel, Cédric

    2015-08-01

    The interannual variability of annual and monthly rainfall in Haiti is examined from a database of 78 rain gauges in 1905-2005. The spatial coherence of annual rainfall is rather low, which is partly due to Haiti's rugged landscape, complex shoreline, and surrounding warm waters (mean sea surface temperatures >27 °C from May to December). The interannual variation of monthly rainfall is mostly shaped by the intensity of the low-level winds across the Caribbean Sea, leading to a drier- (or wetter-) than-average rainy season associated with easterly (or westerly) anomalies, increasing (or decreasing) winds. The varying speed of low-level easterlies across the Caribbean basin may reflect at least four different processes during the year: (1) an anomalous trough/ridge over the western edge of the Azores high from December to February, peaking in January; (2) a zonal pressure gradient between Eastern Pacific and the tropical Northern Atlantic from May/June to September, with a peak in August (i.e. lower-than-average rainfall in Haiti is associated with positive sea level pressure anomalies over the tropical North Atlantic and negative sea level pressure anomalies over the Eastern Pacific); (3) a local ocean-atmosphere coupling between the speed of the Caribbean Low Level Jet and the meridional sea surface temperature (SST) gradient across the Caribbean basin (i.e. colder-than-average SST in the southern Caribbean sea is associated with increased easterlies and below-average rainfall in Haiti). This coupling is triggered when the warmest Caribbean waters move northward toward the Gulf of Mexico; (4) in October/November, a drier- (or wetter-) than-usual rainy season is related to an almost closed anticyclonic (or cyclonic) anomaly located ENE of Haiti on the SW edge of the Azores high. This suggests a main control of the interannual variations of rainfall by intensity, track and/or recurrence of tropical depressions traveling northeast of Haiti. During this period, the

  16. A multiplier-based method of generating stochastic areal rainfall from point rainfalls

    Science.gov (United States)

    Ndiritu, J. G.

    Catchment modelling for water resources assessment is still mainly based on rain gauge measurements as these are more easily available and cover longer periods than radar and satellite-based measurements. Rain gauges however measure the rain falling on an extremely small proportion of the catchment and the areal rainfall obtained from these point measurements are consequently substantially uncertain. These uncertainties in areal rainfall estimation are generally ignored and the need to assess their impact on catchment modelling and water resources assessment is therefore imperative. A method that stochastically generates daily areal rainfall from point rainfall using multiplicative perturbations as a means of dealing with these uncertainties is developed and tested on the Berg catchment in the Western Cape of South Africa. The differences in areal rainfall obtained by alternately omitting some of the rain gauges are used to obtain a population of plausible multiplicative perturbations. Upper bounds on the applicable perturbations are set to prevent the generation of unrealistically large rainfall and to obtain unbiased stochastic rainfall. The perturbations within the set bounds are then fitted into probability density functions to stochastically generate the perturbations to impose on areal rainfall. By using 100 randomly-initialized calibrations of the AWBM catchment model and Sequent Peak Analysis, the effects of incorporating areal rainfall uncertainties on storage-yield-reliability analysis are assessed. Incorporating rainfall uncertainty is found to reduce the required storage by up to 20%. Rainfall uncertainty also increases flow-duration variability considerably and reduces the median flow-duration values by an average of about 20%.

  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 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

  19. Future rainfall variations reduce abundances of aboveground arthropods in model agroecosystems with different soil types

    Directory of Open Access Journals (Sweden)

    Johann G. Zaller

    2014-10-01

    Full Text Available Climate change scenarios for Central Europe predict less frequent but heavier rainfalls and longer drought periods during the growing season. This is expected to alter arthropods in agroecosystems that are important as biocontrol agents, herbivores or food for predators (e.g. farmland birds. In a lysimeter facility (totally 18 3-m2-plots, we experimentally tested the effects of long-term past vs. prognosticated future rainfall variations (15% increased rainfall per event, 25% more dry days according to regionalized climate change models from the Intergovernmental Panel on Climate Change (IPCC on aboveground arthropods in winter wheat (Triticum aestivum L. cultivated at three different soil types (calcaric phaeozem, calcic chernozem and gleyic phaeozem. Soil types were established 17 years and rainfall treatments one month before arthropod sampling; treatments were fully crossed and replicated three times. Aboveground arthropods were assessed by suction sampling, their mean abundances (± SD differed between April, May and June with 20 ± 3 m-2, 90 ± 35 m-2 and 289 ± 93 individuals m-2, respectively. Averaged across sampling dates, future rainfall reduced the abundance of spiders (Araneae, -47%, cicadas and leafhoppers (Auchenorrhyncha, -39%, beetles (Coleoptera, -52%, ground beetles (Carabidae, -41%, leaf beetles (Chrysomelidae, -64%, spring tails (Collembola, -58%, flies (Diptera, -73% and lacewings (Neuroptera, -73% but increased the abundance of snails (Gastropoda, +69%. Across sampling dates, soil types had no effects on arthropod abundances. Arthropod diversity was neither affected by rainfall nor soil types. Arthropod abundance was positively correlated with weed biomass for almost all taxa; abundance of Hemiptera and of total arthropods was positively correlated with weed density. These detrimental effects of future rainfall varieties on arthropod taxa in wheat fields can potentially alter arthropod-associated agroecosystem services.

  20. 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.

  1. 鄱阳湖干旱多尺度特征及其与月均水位的相关性%Multi-scale characteristics of drought of Poyang Lake and its association to monthly average water level

    Institute of Scientific and Technical Information of China (English)

    张启旺; 张吉; 周涛

    2016-01-01

    以鄱阳湖13个气象站1957~2013年的逐月降水量、平均气温、各站点纬度和同期水位站逐月平均水位为实验数据,分别计算1、3、6、12、24、48个月尺度下标准降水指数( SPI)和标准降水蒸散指数( SPEI)时间序列,并利用Morlet小波分析理论,分析了该序列多时间尺度变化特征。基于Mann-Kendall检验,分析了鄱阳湖气象干旱趋势特征;利用Spearman秩相关系数,研究了不同时间尺度SPI和SPEI序列与月平均水位的相关关系。研究表明,鄱阳湖流域SPI和SPEI序列存在约68个月变化的主周期,两个主要特征时间尺度变化的强分布;气象干旱与湖水位的相关关系随时间尺度的增大而减弱。%The different 1-month, 3-month, 6-month, 12-month, 24-month and 48-month standardized precipitation index ( SPI) and Standardized Precipitation Evapotranspiration Index ( SPEI) time series are calculated based on the monthly precipitation, mean temperature and respective latitudes of 13 meteorological gauging stations from 1957 to 2013 and the simulta-neous monthly mean water level data in Poyang lake;the multi-scale features for these two time series are analyzed based on the wavelet theory with the Morlet function. The trend of meteorological drought of Poyang Lake is tested by the Mann -Kendall method. The correlation between the different scales of SPI and SPEI time series and the mean monthly water level is analyzed by Spearman coefficient. The results show that the SPI and SPEI time series have a cycle of 68-month period and two strong distri-butions with varied temporal scale. The relationship of meteorological drought of Poyang Lake and the water level decreases with the increase of time scale.

  2. 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

  3. Intermittent rainfall in dynamic multimedia fate modeling.

    Science.gov (United States)

    Hertwich, E G

    2001-03-01

    It has been shown that steady-state multimedia models (level III fugacity models) lead to a substantial underestimate of air concentrations for chemicals with a low Henry's law constant (H multimedia models are used to estimate the spatial range or inhalation exposure. A dynamic model of pollutant fate is developed for conditions of intermittent rainfall to calculate the time profile of pollutant concentrations in different environmental compartments. The model utilizes a new, mathematically efficient approach to dynamic multimedia fate modeling that is based on the convolution of solutions to the initial conditions problem. For the first time, this approach is applied to intermittent conditions. The investigation indicates that the time-averaged pollutant concentrations under intermittent rainfall can be approximated by the appropriately weighted average of steady-state concentrations under conditions with and without rainfall.

  4. Identification and characterization of rainfall events responsible for triggering of debris flows and shallow landslides

    Science.gov (United States)

    Iadanza, Carla; Trigila, Alessandro; Napolitano, Francesco

    2016-10-01

    The aim of this study is the development of objective and replicable methodologies for the identification, analysis and characterization of rainfall events responsible for the triggering of shallow landslides and debris flows, in order to define empirical rainfall thresholds. The study area is the province of Trento (6208 km2), located in the north-eastern Alps, and characterized by complex orography, with 70% of the area at an altitude above 1000 m. A rigorous statistical methodology has been defined for the identification of the beginning of the triggering event, based on the critical duration, i.e. the minimum dry period duration separating two stochastically independent rainy periods. The critical duration has been calculated for each rain gauge of the studied area and its variability during the months of the year has been analyzed. An analysis of the rainfall spatial variability in a neighborhood of the landslide detachment zone has been carried out. The adopted methods are: the examination of the Monte Macaion radar maps during some summer convective events, the comparison of rainfall records of rain gauges located in a 10 km buffer around the landslide, and the calculation of the Pearson's correlation coefficient between pairs of neighboring rain gauges. The following rainfall thresholds have been then calibrated with the frequentist approach and compared: average intensity-event duration (I-D), which represents the rainfall event in its entirety, and intensity-duration associated with the event maximum return period (IRP-DRP), which considers the most critical portion of the event. In the absence of information about the landslide time of activation, the end of the triggering event has been identified using two criteria: the rainfall peak intensity and the last registration of the day. The methodology adopted for the objective identification of the beginning of the triggering event has demonstrated good applicability for rainfall induced landslides. During

  5. Hydrologic response in karstic-ridge wetlands to rainfall and evapotranspiration, central Florida, 2001-2003

    Science.gov (United States)

    Knowles, Leel; Phelps, G.G.; Kinnaman, Sandra L.; German, Edward R.

    2005-01-01

    though rainfall was far above average during the study, wetland evaporation volumetrically exceeded rainfall. Ground-water inflow was effective in partially offsetting the negative residual between rainfall and evaporation, thus adding to wetland storage. Ground-water inflow was most common at both wetlands when rainfall continued for days or weeks, or during a week with more than about 2.5 inches of rainfall. Large decreases in wetland storage were associated with large negative fluxes of evaporation and ground-water exchange. The response of wetland water levels to rainfall showed a strong and similar relation at both study sites; however, the greater variability in the relation of wetland water-level change to rainfall at higher rainfall rates indicated that hydrologic processes other than rainfall became more important in the response of the wetland. Changes in wetland water levels seemed to be related more to vertical gradients than to lateral gradients. The largest wetland water-level rises were associated mostly with lower vertical gradients, when vertical head differences were below the 18-month average; however, at the Lyonia large wetland, extremely large lateral gradients toward the wetland during late June 2002 may have contributed to substantial gains in wetland water. During the remainder of the study, wetland water-level rises were associated mostly with decreasing vertical gradients and highly variable lateral gradients. Conversely, wetland water-level decreases were associated mostly with increasing vertical gradients and lateral gradients away from the wetland, particularly during the dry season. The potential for lateral ground-water exchange with the wetlands varied substantially more than that for vertical exchange. Potential for vertical losses of wetland water to ground water was highest during a dry period from December 2001 to June 2002, during the wet season of 2002, and for several months into the following dry season. Lateral he

  6. 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

  7. 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.

  8. Spatial estimation of debris flows-triggering rainfall and its dependence on rainfall return period

    Science.gov (United States)

    Destro, Elisa; Marra, Francesco; Nikolopoulos, Efthymios I.; Zoccatelli, Davide; Creutin, Jean Dominique; Borga, Marco

    2017-02-01

    Forecasting the occurrence of debris flows is fundamental for issuing hazard warnings, and often focuses on rainfall as a triggering agent and on the use of empirical rainfall thresholds based on rain gauge observations. A recognized component of the uncertainty associated with the use of rainfall thresholds is related to the sampling of strongly varying rainfall variability with sparse rain gauge networks. In this work we examine the spatial distribution of rainfall depth in areas up to 10 km from the debris flow initiation points as a function of return period, and we exploit this information to analyze the errors expected in the estimation of debris flow triggering rainfall when rain gauge data are used. In particular, we investigate the impact of rain gauge density and of the use of different interpolation methods. High-resolution, adjusted radar rainfall estimates, representing the best available spatially-distributed rainfall estimates at the debris flows initiation point and in the surrounding area, are sampled by stochastically generated rain gauge networks characterized by varying densities. Debris flow triggering rainfall is estimated by means of three rainfall interpolation methods: nearest neighbor, inverse distance weighting and ordinary kriging. On average, triggering rainfall shows a local peak corresponding to the debris flow initiation point, with a decay of rainfall with distance which increases with the return period of the triggering rainfall. Interpolation of the stochastically generated rain gauge measurements leads to an underestimation of the triggering rainfall that, irrespective of the interpolation methods, increases with the return period and decreases with the rain gauge density. For small return period events and high rain gauge density, the differences among the methods are minor. With increasing the return period and decreasing the rain gauge density, the nearest neighbor method is less biased, because it makes use only of the

  9. 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...

  10. 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...

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

    CERN Document Server

    Chattopadhyay, Goutami; Jain, Rajni

    2009-01-01

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

  12. Interannual rainfall variability over the Cape south coast of South Africa linked to cut-off low associated rainfall

    CSIR Research Space (South Africa)

    Engelbrecht, CJ

    2014-10-01

    Full Text Available The influence of cut-off low (COL) associated rainfall on interannual rainfall variability over the Cape south coast region of South Africa for the period 1979-2011 is investigated. COLs are objectively identified and tracked on daily average 500 hPa...

  13. Accuracy of rainfall measurement for scales of hydrological interest

    Directory of Open Access Journals (Sweden)

    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

  14. THE IMPACT OF CLIMATE CHANGE UPON WINTER RAINFALL

    Directory of Open Access Journals (Sweden)

    Numan Shehadeh

    2013-01-01

    Full Text Available Climatic models that project the impact of climate change upon rainfall in the Eastern Mediterranean region predict that the negative impact will be more pronounced upon winter rainfall rather than Fall or Spring rainfall where instability conditions become more pronounced. Those models, also, predict that, due to the great geographical diversity, projected rainfall trends in the above region will show great spatial variability. Therefore, this study aims to analyze the possible impact of climate change upon winter rainfall (December, January and February in Jordan. Data from six meteorological stations that represent well the spatial variation of rainfall in the country is used. Various statistical techniques are applied in this study including, linear regression, t- test, moving averages and CUSUM charts. Results of the analysis reveal a decreasing rainfall trend in all the sample stations. However, the decreasing trends are significant at the 0.05 level in three stations only (Salt, Amman and Irbid. The negative impact of climate change upon winter rainfall totals in the northern and central parts of Jordan, where most of winter rainfall is associated with Mediterranean depressions, is statistically significant at the 0.05 level. However, such impact is not significant in the southern and eastern parts of the country, where a greater portion of winter rainfall is associated with khamasini depressions and instability conditions. Further research analyzing the impact of climate change upon other climatic elements such as temperature, relative humidity and dust storms is needed.

  15. Sensitivity of point scale runoff predictions to rainfall resolution

    Directory of Open Access Journals (Sweden)

    A. J. Hearman

    2006-11-01

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

  16. 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.

  17. Copula-based IDF curves and empirical rainfall thresholds for flash floods and rainfall-induced landslides

    Science.gov (United States)

    Bezak, Nejc; Šraj, Mojca; Mikoš, Matjaž

    2016-10-01

    Floods, landslides and debris flows are natural events that occur all over the world and are often induced by extreme rainfall conditions. Several extreme events occurred in Slovenia (Europe) in the last 25 years that caused 18 casualties and approximately 500 million Euros of economic loss. The intensity-duration-frequency (IDF) relationship was constructed using the Frank copula function for several rainfall stations using high-resolution rainfall data with an average subsample length of 34 years. The empirical rainfall threshold curves were also evaluated for selected extreme events. Post-event analyses showed that rainfall characteristics triggering flash floods and landslides are different. The sensitivity analysis results indicate that the inter-event time definition (IETD) and subsample definition methodology can have a significant influence on the position of rainfall events in the intensity-duration space, the constructed IDF curves and on the relationship between the empirical rainfall threshold curves and the IDF curves constructed using the copula approach. Furthermore, a combination of several empirical rainfall thresholds with an appropriate high-density rainfall measurement network can be used as part of the early warning system of the initiation of landslides and debris flows. However, different rainfall threshold curves should be used for lowland and mountainous areas in Slovenia.

  18. The relationship between the Southern Oscillation Index, rainfall and the occurrence of canine tick paralysis, feline tick paralysis and canine parvovirus in Australia.

    Science.gov (United States)

    Rika-Heke, Tamara; Kelman, Mark; Ward, Michael P

    2015-07-01

    The aim of this study was to describe the association between climate, weather and the occurrence of canine tick paralysis, feline tick paralysis and canine parvovirus in Australia. The Southern Oscillation Index (SOI) and monthly average rainfall (mm) data were used as indices for climate and weather, respectively. Case data were extracted from a voluntary national companion animal disease surveillance resource. Climate and weather data were obtained from the Australian Government Bureau of Meteorology. During the 4-year study period (January 2010-December 2013), a total of 4742 canine parvovirus cases and 8417 tick paralysis cases were reported. No significant (P ≥ 0.05) correlations were found between the SOI and parvovirus, canine tick paralysis or feline tick paralysis. A significant (P rainfall in the same month (0.28), and significant negative cross-correlations (-0.26 to -0.36) between parvovirus occurrence and rainfall 4-6 months previously. Significant (P rainfall 1-3 months previously, and significant positive cross-correlations (0.29-0.47) between canine tick paralysis occurrence and rainfall 7-10 months previously. Significant positive cross-correlations (0.37-0.68) were found between cases of feline tick paralysis and rainfall 6-10 months previously. These findings may offer a useful tool for the management and prevention of tick paralysis and canine parvovirus, by providing an evidence base supporting the recommendations of veterinarians to clients thus reducing the impact of these diseases. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Modelling rainfall erosion resulting from climate change

    Science.gov (United States)

    Kinnell, Peter

    2016-04-01

    It is well known that soil erosion leads to agricultural productivity decline and contributes to water quality decline. The current widely used models for determining soil erosion for management purposes in agriculture focus on long term (~20 years) average annual soil loss and are not well suited to determining variations that occur over short timespans and as a result of climate change. Soil loss resulting from rainfall erosion is directly dependent on the product of runoff and sediment concentration both of which are likely to be influenced by climate change. This presentation demonstrates the capacity of models like the USLE, USLE-M and WEPP to predict variations in runoff and erosion associated with rainfall events eroding bare fallow plots in the USA with a view to modelling rainfall erosion in areas subject to climate change.

  20. Application of the Season Time Series Model to Forecast the Rainfall in the Area of Well Irrigation Rice in the Sanjiang Plain

    Institute of Scientific and Technical Information of China (English)

    QiangFu; HongFu; ChuanLiang

    2004-01-01

    The area of well irrigation rice became more and more, so the crisis of groundwater appeared. Making the most of rainfall is an availability method in water saving irrigation, increasing water temperature and raising yield. Just based on this, through applying the theory of season random time series, according to the data of average monthly rainfall (1981 - 1999), the authors build up the forecasting model in the area of well irrigation rice in the Sanjiang Plain. Through contrasting with practical value, the model has good effect.So, it can be used in water irrigation management.

  1. 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.

  2. Ensemble climate projections of mean and extreme rainfall over Vietnam

    Science.gov (United States)

    Raghavan, S. V.; Vu, M. T.; Liong, S. Y.

    2017-01-01

    A systematic ensemble high resolution climate modelling study over Vietnam has been performed using the PRECIS model developed by the Hadley Center in UK. A 5 member subset of the 17-member Perturbed Physics Ensembles (PPE) of the Quantifying Uncertainty in Model Predictions (QUMP) project were simulated and analyzed. The PRECIS model simulations were conducted at a horizontal resolution of 25 km for the baseline period 1961-1990 and a future climate period 2061-2090 under scenario A1B. The results of model simulations show that the model was able to reproduce the mean state of climate over Vietnam when compared to observations. The annual cycles and seasonal averages of precipitation over different sub-regions of Vietnam show the ability of the model in also reproducing the observed peak and magnitude of monthly rainfall. The climate extremes of precipitation were also fairly well captured. Projections of future climate show both increases and decreases in the mean climate over different regions of Vietnam. The analyses of future extreme rainfall using the STARDEX precipitation indices show an increase in 90th percentile precipitation (P90p) over the northern provinces (15-25%) and central highland (5-10%) and over southern Vietnam (up to 5%). The total number of wet days (Prcp) indicates a decrease of about 5-10% all over Vietnam. Consequently, an increase in the wet day rainfall intensity (SDII), is likely inferring that the projected rainfall would be much more severe and intense which have the potential to cause flooding in some regions. Risks due to extreme drought also exist in other regions where the number of wet days decreases. In addition, the maximum 5 day consecutive rainfall (R5d) increases by 20-25% over northern Vietnam but decreases in a similar range over the central and southern Vietnam. These results have strong implications for the management water resources, agriculture, bio diversity and economy and serve as some useful findings to be

  3. USING THE FOURNIER INDEXES IN ESTIMATING RAINFALL EROSIVITY. CASE STUDY - THE SECAŞUL MARE BASIN

    Directory of Open Access Journals (Sweden)

    M. COSTEA

    2012-03-01

    Full Text Available Using the Fournier Index in Estimating Rainfall Erosivity. Case Study - The Secaşul Mare Basin. Climatic aggressiveness is one of the most important factors in relief dynamic. Of all climatic parameters, rainfall is directly involved in versant dynamic, in the loss of soil quality and through pluvial denudation and the processes associated with it, through the erosivity of torrential rain. We analyzed rainfall aggressiveness based on monthly and annual average values through the Fournier's index (1970 and Fournier's index modified by Arnoldus (1980. They have the advantage that they can be used not only for evaluating the land susceptibility to erosion and the calculation of erodibility of land and soil losses, but also in assessing land susceptibility to sliding (Aghiruş, 2010. The literature illustrates the successful use of this index which provides a summary assessment of the probability of rainfall with significant erosive effects. The results obtained allow observation of differences in space and time of the distribution of this index.

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

    Directory of Open Access Journals (Sweden)

    Muhammad Suradi

    2014-04-01

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

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

    Science.gov (United States)

    Bergemann, Martin; Jakob, Christian

    2016-06-01

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

  6. Space-time organization of debris flows-triggering rainfall: effects on the identification of the rainfall threshold relationships

    Science.gov (United States)

    Borga, Marco; Nikolopoulos, Efthymios; Creutin, Jean Dominique; Marra, Francesco

    2015-04-01

    Debris flow occurrence is generally forecasted by means of empirical rainfall depth-duration thresholds which are often derived based on rain gauge observations (Guzzetti et al., 2008). Rainfall sampling errors, related to the sparse nature of raingauge data, lead to underestimation of the intensity-duration thresholds (Nikolopoulos et al., 2014, Nikolopoulos et al., 2015). This underestimation may be large when debris flows are triggered by convective rainfall events, characterized by limited spatial extent, turning into less efficient forecasts of debris flow occurrence. This work investigates the spatial and temporal structure of rainfall patterns and its effects on the derived rainfall threshold relationships using high-resolution, carefully corrected radar data for 82 debris flows events occurred in the eastern Italian Alps. We analyze the spatial organization of rainfall depths relative to the rainfall occurred over the debris flows initiation point using the distance from it as the main coordinate observing that, on average, debris flows initiation points are characterized by a maximum in the rainfall depth field. We investigate the relationship between spatial organization and duration of rainfall pointing out that the rainfall underestimation is larger for the shorter durations and increases regularly as the distance between rainfall measurement location and debris flow initiation point increases. We introduce an analytical framework that explains how the combination of the mean rainfall depth spatial pattern and its relationship with rainfall duration causes the bias observed in the raingauge-based thresholds. The consistency of this analytical framework is proved by using a Monte Carlo sampling of radar rainfall fields. References Guzzetti, F., Peruccacci, S., Rossi, M., Stark, C.P., 2008. The rainfall intensity-duration control of shallow landslides and debris flows: an update. Landslides 5, 3-17, 10.1007/s10346-625 007-0112-1 Nikolopoulos, E.I., S

  7. Sea breeze Initiated Rainfall over the east Coast of India during the Indian Southwest Monsoon

    Energy Technology Data Exchange (ETDEWEB)

    Simpson, M; Warrior, H; Raman, S; Aswathanarayana, P A; Mohanty, U C; Suresh, R

    2006-09-05

    Sea breeze initiated convection and precipitation is investigated along the east coast of India during the Indian southwest monsoon season. The sea breeze circulations are observed approximately 70 to 80% of the days during the summer months (June to August) along the Chennai coast. Observations of average sea breeze wind speeds are stronger at a rural location as compared to the wind speeds observed inside the urban region of Chennai. The sea breeze circulation is shown to be the dominant mechanism for initiating rainfall during the Indian southwest monsoon season. Roughly 80% of the total rainfall observed during the southwest monsoon over Chennai is directly related to the convection initiated by sea breeze circulation.

  8. 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...

  9. 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...

  10. Rainfall and runoff regime in the Golema reka watershed on the territory of the hunting ground Valnište

    Directory of Open Access Journals (Sweden)

    Kostadinov Stanimir

    2003-01-01

    Full Text Available Fenced hunting ground "Valnište" covers 410 ha on the slopes of the mountain Čemernik, in the Municipality Crna Trava. The hunting ground is situated in the Golema Reka watershed. Rainfall and runoff regime in the Golema Reka watershed were researched in order to create a hydrological base with the data on rainfall, available water resources and maximal discharges. Average annual rainfall design value for the watershed is 860. 14 mm. The highest monthly rainfall occurs in June and May, and the lowest in September and October. As there are no measured data, runoff regime was determined based on the method of parameter hydrology. The following calculation results are adopted for the maximal discharge: Q1000=19,0 m3·s-1 i Q100=10,90 m3·s-1. The adopted value of mean annual specific discharge (runoff module is MQ=16,0 l·s-1·km-2.The study results of rainfall and runoff regime in the Golema Reka watershed show that hydrological conditions are favorable for the development of hunting and hunting tourism.

  11. 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...

  12. 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

  13. Extreme Rainfall Impacts in Fractured Permeable Catchments

    Science.gov (United States)

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

    2009-12-01

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

  14. Country-wide rainfall maps from cellular communication networks

    Science.gov (United States)

    Leijnse, Hidde; Overeem, Aart; Uijlenhoet, Remko

    2013-04-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information and the number of rain gauges is even severely declining in Europe, South-America, and Africa. This calls for alternative sources of rainfall information. Various studies have shown that microwave links from operational cellular telecommunication networks may be employed for rainfall monitoring. Such networks cover 20% of the land surface of the earth and have a high density, especially in urban areas. The basic principle of rainfall monitoring using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. Here we show how one cellular telecommunication network can be used to retrieve the space-time dynamics of rainfall for an entire country. A dataset from a commercial microwave link network over the Netherlands is analyzed, containing data from an unprecedented number of links (2400) covering the land surface of the Netherlands (35500 km2). This dataset consists of 24 days with substantial rainfall in June - September 2011. A rainfall retrieval algorithm is presented to derive rainfall intensities from the microwave link data, which have a temporal resolution of 15 min. Rainfall maps (1 km spatial resolution) are generated from these rainfall intensities using Kriging. This algorithm is suited for real-time application, and is calibrated on a subset (12 days) of the dataset. The other 12 days in the dataset are used to validate the algorithm. Both

  15. Variation in rainfall interception along a forest succession gradient

    Science.gov (United States)

    Zimmermann, Beate; Zimmermann, Alexander; van Breugel, Michiel

    2013-04-01

    Rainfall interception by forest canopies reduces the water influx to the forest floor. When forests are replaced by pasture, the process of canopy interception temporarily stops until a new forest develops on abandoned pasture land. Modern land-cover change typically involves regrowing forests but the relation between forest succession and canopy interception is hardly understood. This lack of knowledge is unfortunate because rainfall interception plays an important role in regional water cycles and needs to be quantified for modeling purposes. To help close the knowledge gap, we designed a chronosequence study of throughfall along a secondary succession gradient in a tropical forest region of Panama. The investigated gradient comprises 20 natural forest patches regrowing for 1 up to about 130 years. We sampled each patch with a minimum of 20 funnel-type throughfall collectors over a continuous two-month period that had nearly 900 mm of rain. At the same time and locations, we acquired forest structure data based on DBH measurements of all trees > 1 cm DBH, identified all tree species, and took hemispherical photographs to calculate canopy openness. We used Bayesian Model Averaging (BMA) to identify those vegetation parameters that have the strongest influence on interception variation. Interception loss increased with forest age from 0 to nearly 200 mm of the total rainfall input (0 - 20 %), with the steepest rise occurring within the first decade of forest succession. Parsimonious models which contain canopy openness and basal area or stem density of stems smaller than 5 cm DBH are favored about more complex models. Leave-one-out cross validation revealed that our BMA approach can be used to predict interception with an RMSE of 5 %. Based on our results we argue that hydrological modeling exercises should account for variation in interception due to succession stage, which is possible e.g. by using a statistical approach to relate interception estimates to forest

  16. Rainfall and temperature scenarios for Bangladesh for the middle of 21st century using RegCM

    Indian Academy of Sciences (India)

    Md Mizanur Rahman; Md Nazrul Islam; Ahsan Uddin Ahmed; F Georgi

    2012-04-01

    Regional Climate Model of version 3 (RegCM3) was driven with Emissions Scenarios A2 of ECHAM4 at 0.54° × 0.54° horizontal grid resolution in two parameterizations: Grell scheme with Arakawa–Schubert (GAS) and Fritch–Chappell (GFC) assumptions. The simulated rainfall and mean surface air temperature were calibrated and validated against ground-based observed data in Bangladesh during the period 1961–1990. The Climate Research Unit (CRU) data is also used for understanding the model performance. Better performance of RegCM3 obtained through validation process, made it confident in utilizing it in rainfall and temperature projection for Bangladesh in the middle of 21st century. Rainfall and mean surface air temperature projection for Bangladesh is experimentally obtained for 2050 and 2060. This work discloses that simulated rainfall and temperature are not directly useful in application-oriented tasks. However, after calibration and validation, reasonable performance can be obtained in estimating seasonal and annual rainfall, and mean surface air temperature in Bangladesh. The projected change of rainfall for Bangladesh is about +35% for monsoon season (JJAS), −67% for pre-monsoon (MAM), −12% for post-monsoon (ON) and 107% for winter (DJF) for 2050. On an average, rainfall may be less by more than 50% for all seasons for the year 2060. Similarly, change of mean surface air temperature in different months is projected about 0.5°–2.1°C and 0.9°–3.5°C for the year 2050 and 2060, respectively.

  17. 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.

  18. Analysis and prediction of rainfall trends over Bangladesh using Mann-Kendall, Spearman's rho tests and ARIMA model

    Science.gov (United States)

    Rahman, Mohammad Atiqur; Yunsheng, Lou; Sultana, Nahid

    2016-09-01

    In this study, 60-year monthly rainfall data of Bangladesh were analysed to detect trends. Modified Mann-Kendall, Spearman's rho tests and Sen's slope estimators were applied to find the long-term annual, dry season and monthly trends. Sequential Mann-Kendall analysis was applied to detect the potential trend turning points. Spatial variations of the trends were examined using inverse distance weighting (IDW) interpolation. AutoRegressive integrated moving average (ARIMA) model was used for the country mean rainfall and for other two stations data which depicted the highest and the lowest trend in the Mann-Kendall and Spearman's rho tests. Results showed that there is no significant trend in annual rainfall pattern except increasing trends for Cox's Bazar, Khulna, Satkhira and decreasing trend for Srimagal areas. For the dry season, only Bogra area represented significant decreasing trend. Long-term monthly trends demonstrated a mixed pattern; both negative and positive changes were found from February to September. Comilla area showed a significant decreasing trend for consecutive 3 months while Rangpur and Khulna stations confirmed the significant rising trends for three different months in month-wise trends analysis. Rangpur station data gave a maximum increasing trend in April whereas a maximum decreasing trend was found in August for Comilla station. ARIMA models predict +3.26, +8.6 and -2.30 mm rainfall per year for the country, Cox's Bazar and Srimangal areas, respectively. However, all the test results and predictions revealed a good agreement among them in the study.

  19. 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

    regional level. This is done for an intermediate-sized catchment in Italy, i.e. the Flumendosa catchment, using climate model rainfall and atmospheric data from the ENSEMBLES project (http://ensembleseu.metoffice.com). In doing so, we split the historical rainfall record of mean areal precipitation (MAP) in 15-year calibration and 45-year validation periods, and compare the historical rainfall statistics to those obtained from: a) Q-Q corrected climate model rainfall products, and b) synthetic rainfall series generated by the suggested downscaling scheme. To our knowledge, this is the first time that climate model rainfall and statistically downscaled precipitation are compared to catchment-averaged MAP at a daily resolution. The obtained results are promising, since the proposed downscaling scheme is more accurate and robust in reproducing a number of historical rainfall statistics, independent of the climate model used and the length of the calibration period. This is particularly the case for the yearly rainfall maxima, where direct statistical correction of climate model rainfall outputs shows increased sensitivity to the length of the calibration period and the climate model used. The robustness of the suggested downscaling scheme in modeling rainfall extremes at a daily resolution, is a notable feature that can effectively be used to assess hydrologic risk at a regional level under changing climatic conditions. Acknowledgments The research project is implemented within the framework of the Action «Supporting Postdoctoral Researchers» of the Operational Program "Education and Lifelong Learning" (Action's Beneficiary: General Secretariat for Research and Technology), and is co-financed by the European Social Fund (ESF) and the Greek State. CRS4 highly acknowledges the contribution of the Sardinian regional authorities.

  20. 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...

  1. Temporal and spatial characteristics of rainfall events: a Slovenian case study

    Science.gov (United States)

    Dolšak, Domen; Bezak, Nejc; Šraj, Mojca

    2016-04-01

    Temporal rainfall distribution within individual rainfall events can have significant impact on the runoff characteristics such as the time to peak discharge and peak discharge values. Therefore, the information about temporal rainfall distribution within rainfall event is crucial for planning of hydraulic structures, flood protection, reliable hydrological modelling, etc. The main aim of this study was to investigate temporal and spatial characteristics of rainfall events in Slovenia, Europe. Data from 30 rainfall stations in Slovenia were used in order to analyze properties of rainfall events in Slovenia. Rainfall data with 5-minute time step was used and the sample data lengths varied from 10 to 66 years with a mean sample data length of 35 years. Huff curves and binary shape code (BSC) method, which was proposed by Terranova and Iaquinta (2011), were used to analyze temporal and spatial characteristics of rainfall events in Slovenia. All calculations were performed using the free software program R (https://www.r-project.org). The results of the study show that rainfall characteristics in eastern (BSC 1111) and western (BSC 0000) part of Slovenia are not the same. This means that in the western part of Slovenia on average the majority of rainfall occurs in the second part of the rainfall event and in the eastern part of Slovenia on average most of the rainfall occurs in the first part of the rainfall event. Thus, on average higher peak discharge values can be expected in rivers located in the western part of Slovenia due to the higher antecedent conditions. Furthermore, the estimated BSC types did not depend on the rainfall station elevation. Moreover, the calculated BSC types were dependent on the duration of the rainfall event. The BSC 1111 type (most of rainfall occurs in the first part of the rainfall event) was the most frequent for the shorter duration rainfall events (less than 12 hours) and the BSC 0000 type (most of rainfall occurs in the second part

  2. 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.

  3. Differential behaviour of a Lesser Himalayan watershed in extreme rainfall regimes

    Indian Academy of Sciences (India)

    Pankaj Chauhan; Nilendu Singh; Devi Datt Chauniyal; Rajeev S Ahluwalia; Mohit Singhal

    2017-03-01

    Climatic extremes including precipitation are bound to intensify in the global warming environment. The present study intends to understand the response of the Tons sub-watershed in Lesser Himalaya, in 3 years with entirely different hydrological conditions (July 2008–June 2011) in terms of discharge, sedimentflux and denudation rates. Within an uncertainty limit of ±20%, the mean interannual discharge (5.74 ± 1.44 m ³s ⁻¹) (±SE), was found highly variable (CV: 151%; 0.8–38 m ³s ⁻¹). In a normal rainfall year (2008–2009; ~1550 mm), the discharge was 5.12 ± 1.75 m ³s ⁻¹, whereas in a drought year (2009–2010), it reduced by 30% with the reduction in ~23% rainfall (CV: 85%). In an excessive rainfall year (once-in-a-century event) (2010–2011; ~3050 mm), discharge as well as total solid load was ~200% higher. Monsoon months (July–September) accounted for more than 90% of the annual solid load transport. The ratio of dissolved to suspended solid (C/P ratio) was consistently low (<1) during monsoon months and higher (1–7) during the rest of the dry period. C/P ratio was inversely (R ² = 0.49), but significantly (P<0.001) related to the rainfall. The average mechanical erosion rate in the three different rainfall years was 0.24, 0.19 and 1.03 mmyr ⁻¹, whereas the chemical erosion was estimated at 0.12, 0.11 and 0.46 mmyr ⁻¹, respectively. Thus, the average denudation rate of the Tons sub-watershed has been estimated at 0.33 mmyr ⁻¹ (excluding extreme rainfall year: 1.5 mmyr ⁻¹). Our results have implications to understand the hydrological behaviour of the Lesser Himalayan watersheds and will be valuable for the proposed and several upcoming small hydropower plants in the region in the context of regional ecology and naturalresource management.

  4. 降雨变化对东江流域径流的影响模拟分析%The Impact of Variation in Rainfall on Runoff in the Dongjiang River Basin

    Institute of Scientific and Technical Information of China (English)

    刘洁; 陈晓宏; 许振成; 虢清伟; 肖志峰; 王兆礼; 吴根义

    2015-01-01

    rainfall has a greater impact on run-off than the decrease of variation coefficient of rainfall does. The intensity of rainfall change is an important factor affecting the runoff, and heavy rainfall has a great effect on the runoff;(4) Change of runoff due to fluc-tuation of variation coefficient of rainfall gradually decreased, when variation coefficient of rainfall gradually declined;(5) Average annual runoff raised by 33.99%as mean value of rainfall raised by 20%, and raised by 10.84%as variation coefficient of rainfall raised by 20%, which means change of mean value of rainfall has bigger impact on runoff change than variation coefficient of rainfall;(6) Variation of monthly runoff caused by different rainfall scenarios is more obvious in June, July and August than other months.

  5. Averaged Electroencephalic Audiometry in Infants

    Science.gov (United States)

    Lentz, William E.; McCandless, Geary A.

    1971-01-01

    Normal, preterm, and high-risk infants were tested at 1, 3, 6, and 12 months of age using averaged electroencephalic audiometry (AEA) to determine the usefulness of AEA as a measurement technique for assessing auditory acuity in infants, and to delineate some of the procedural and technical problems often encountered. (KW)

  6. 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

  7. 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.

  8. 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.

  9. 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).

  10. 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.

  11. 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.

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

    CERN Document Server

    Bergemann, Martin

    2016-01-01

    Recent research has community have shown that tropical convection and rainfall is sensitive to mid-tropospheric humidity. Therefore it has been suggested to improve the representation of moist convection by making cumulus parameterizations more sensitive to mid-tropospheric moisture. Climate models show considerable rainfall biases in coastal tropical areas, where approx. 33 % of the overall rainfall received is associated with coastal land-sea interaction. Building on an algorithm to objectively identify rainfall that is associated with land-sea interaction we investigate whether the relationship between rainfall in coastal regions and atmospheric humidity differs from that over the open ocean or over inland areas. We combine 3-hourly satellite estimates of rainfall with humidity estimates from reanalyses and investigate if coastal rainfall reveals the well known relationship between area-averaged precipitation and column integrated moisture. We find that rainfall that is associated with coastal land-sea eff...

  13. 2002 Average Monthly Sea Surface Temperature for California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the...

  14. 2003 Average Monthly Sea Surface Temperature for California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the...

  15. 1996 Average Monthly Sea Surface Temperature for California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the...

  16. 2000 Average Monthly Sea Surface Temperature for California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the...

  17. 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.

  18. Evolution of a rainfall induced landslide in Porciles, Asturias (North of Spain)

    Science.gov (United States)

    José Domínguez-Cuesta, María; Quintana, Luis; Alonso, Juan Luis; García Cortés, Silverio

    2017-04-01

    Asturias is a province of the Northern Spain, characterized by an abrupt relief (15° average slope), humid climate (960 mm/yr. rainfall) and a varied substratum mainly composed of sedimentary rocks (mostly limestones, sandstones and lutites). Landslide events, frequently linked to rainfall, are widely extended all around the region, affecting both infrastructures and people, which are largely scattered on it. The 6th of March of 2016 one of these instability events took place near the Porciles village (43°24'N 06°18'W), moving more than 10,000 m3 of land down, totally occupying the N-634 road. The main conditioning factors of this gravity movement were the modified geometry of the slope during the construction of the N-634 road and the lithology (mainly lutites and unconsolidated colluvial deposits). The rainfall is considered as the triggering factor. More than 4 months elapsed between the landslide occurrence and the initiation of the destabilized mass removal, after having stabilized the crown area. A landslide evolution study carried out during that period is presented in this work. The study is based on i) weekly oblique photographs taken from several fixed points, ii) three DTM constructed: one from previous topographic data and two LIDAR models obtained from drone flights and iii) rainfall data collected from the closest gauges to the landslide, including pre-sliding data. Several straight infrastructures affected by the landslide (an auxiliary road, some ditches and fences, among other elements) have been used as references. In this study we analyze, mainly, the relationship between the rainfall data and the evolution of the slide.

  19. 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.

  20. 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

  1. Countrywide rainfall maps from a commercial cellular telecommunication network

    Science.gov (United States)

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

    2012-12-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information. Many countries do not have continuously operating weather radars, and have no or few rain gauges. A new development is rainfall estimation from microwave links of commercial cellular telecommunication networks. Such networks cover large parts of the land surface of the earth and have a high density, especially in urban areas. The estimation of rainfall using commercial microwave links could therefore become a valuable source of information. The data produced by microwave links is essentially a by-product of the communication between mobile telephones. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. A dataset from a commercial microwave link network over the Netherlands is analyzed, containing data from an unprecedented number of links (1500) covering the land surface of the Netherlands (35500 km2). This dataset consists of 24 days with substantial rainfall in June - September 2011. A rainfall retrieval algorithm is presented to derive rainfall intensities from the microwave link data, which have a temporal resolution of 15 min. Rainfall maps (1 km spatial resolution) are generated from these rainfall intensities using Kriging. This algorithm is suited for real-time application, and is calibrated on a subset (12 days) of the dataset. The other 12 days in the dataset are used to validate the algorithm. Both calibration and validation are done using gauge-adjusted radar data

  2. Comparison study of design rainfall mapping using ordinary kriging and kriging with external drift

    CSIR Research Space (South Africa)

    Khuluse, S

    2011-03-01

    Full Text Available by a ratio of the overall average design rainfall (m0) and the average design rainfall for that specific period (mtj); j = 1; 2; : : : ; p. The standardized design value is determined as ~Y (s; t) = Y (s; t) m0 mtj (1) Standardization...

  3. 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

  4. 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

  5. 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

  6. 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.

  7. Global solar irradiation in Italy during 1994 : monthly average daily values for 1614 sites estimated from Meteosat images; Radiazione solare globale al suolo in Italia nel 1994 : valori medi mensili per 1.614 localita` italiane stimate a partire dalle immagini fornite dal satellite Meteosat

    Energy Technology Data Exchange (ETDEWEB)

    Cogliani, E.; Mancini, M.; Petrarca, S.; Spinelli, F. [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dip. Energia

    1995-10-01

    The global solar radiation over Italy is estimated from Meteosat secondary images in the visible band. The stimation method relies on the fact that the cloud cover on a given area of the Earth`s surface statistically determines the amount of solar radiation falling on that area. Estimated values of the monthly average daily global radiation on a horizontal surface for the 1994 have been compared with values computed from data measured by the stations of the two Italian radiation networks: the Meteorological Service of the Italian Air Force and the National Agrometeorological Network (a total of 36 stations have been considered). The mean percentage difference between estimated and computed values over the year is 6 per cent. In the present report, the monthly maps of radiation over Italy and the estimated monthly average daily values for over 1600 sites (having more than 10,000 inhabitants) are given. In the yearly reports to be issued in the years to come, maps and mean values over the period starting with 1994 will be given as well.

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

    Institute of Scientific and Technical Information of China (English)

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

    2012-01-01

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

  9. Variability Modeling of Rainfall, Deforestation, and Incidence of American Tegumentary Leishmaniasis in Orán, Argentina, 1985–2007

    Directory of Open Access Journals (Sweden)

    Juan Carlos Rosales

    2014-01-01

    Full Text Available American tegumentary leishmaniasis (ATL is a disease transmitted to humans by the female sandflies of the genus Lutzomyia. Several factors are involved in the disease transmission cycle. In this work only rainfall and deforestation were considered to assess the variability in the incidence of ATL. In order to reach this goal, monthly recorded data of the incidence of ATL in Orán, Salta, Argentina, were used, in the period 1985–2007. The square root of the relative incidence of ATL and the corresponding variance were formulated as time series, and these data were smoothed by moving averages of 12 and 24 months, respectively. The same procedure was applied to the rainfall data. Typical months, which are April, August, and December, were found and allowed us to describe the dynamical behavior of ATL outbreaks. These results were tested at 95% confidence level. We concluded that the variability of rainfall would not be enough to justify the epidemic outbreaks of ATL in the period 1997–2000, but it consistently explains the situation observed in the years 2002 and 2004. Deforestation activities occurred in this region could explain epidemic peaks observed in both years and also during the entire time of observation except in 2005–2007.

  10. Variability Modeling of Rainfall, Deforestation, and Incidence of American Tegumentary Leishmaniasis in Orán, Argentina, 1985–2007

    Science.gov (United States)

    Rosales, Juan Carlos; Yang, Hyun Mo; Avila Blas, Orlando José

    2014-01-01

    American tegumentary leishmaniasis (ATL) is a disease transmitted to humans by the female sandflies of the genus Lutzomyia. Several factors are involved in the disease transmission cycle. In this work only rainfall and deforestation were considered to assess the variability in the incidence of ATL. In order to reach this goal, monthly recorded data of the incidence of ATL in Orán, Salta, Argentina, were used, in the period 1985–2007. The square root of the relative incidence of ATL and the corresponding variance were formulated as time series, and these data were smoothed by moving averages of 12 and 24 months, respectively. The same procedure was applied to the rainfall data. Typical months, which are April, August, and December, were found and allowed us to describe the dynamical behavior of ATL outbreaks. These results were tested at 95% confidence level. We concluded that the variability of rainfall would not be enough to justify the epidemic outbreaks of ATL in the period 1997–2000, but it consistently explains the situation observed in the years 2002 and 2004. Deforestation activities occurred in this region could explain epidemic peaks observed in both years and also during the entire time of observation except in 2005–2007. PMID:25580116

  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. Prediction of stormwater particle loads from impervious urban surfaces based on a rainfall detachment index.

    Science.gov (United States)

    Brodie, I M

    2007-01-01

    This paper makes use of Non-Coarse Particle (NCP) data collected from three different impervious surfaces in Toowoomba, Australia. NCP is defined as suspended solids less than 500 microm in size. NCP loads (in mg/m(2)) were derived for 24 storms from a galvanized iron roof, a concrete car park and a bitumen road pavement. A scatter plot analysis was used to identify potential correlations between NCP loads and basic rainfall parameters such as rainfall depth and intensity. An exponential-type trend, consistent with many washoff models, was evident between load and average rainfall intensity for all surfaces. However, load data for some storms did not fit this general trend. Various indices, comprising different combinations of basic rainfall parameters, were evaluated as an alternative to rainfall intensity. A composite index, referred to as the Rainfall Detachment Index, was found to be better than average rainfall intensity in explaining a relationship between NCP load and storm rainfall characteristics. The selected rainfall index utilizes 6-minute rainfall intensities and is a variant of the well known Rainfall Erosivity Index (EI30) used for soil erosion estimation.

  13. 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.

  14. 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.

  15. 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.

  16. Sensitivity of Horn of Africa Rainfall to Regional Sea Surface Temperature Forcing

    Directory of Open Access Journals (Sweden)

    Zewdu T. Segele

    2015-05-01

    Full Text Available The Abdus Salam International Center for Theoretical Physics (ICTP version 4.4 Regional Climate Model (RegCM4 is used to investigate the rainfall response to cooler/warmer sea surface temperature anomaly (SSTA forcing in the Indian and Atlantic Oceans. The effect of SSTA forcing in a specific ocean basin is identified by ensemble, averaging 10 individual simulations in which a constant or linearly zonally varying SSTA is prescribed in individual basins while specifying the 1971–2000 monthly varying climatological sea surface temperature (SST across the remaining model domain. The nonlinear rainfall response to SSTA amplitude also is investigated by separately specifying +1K, +2K, and +4K SSTA forcing in the Atlantic and Indian Oceans. The simulation results show that warm SSTs over the entire Indian Ocean produce drier conditions across the larger Blue Nile catchment, whereas warming ≥ +2K generates large positive rainfall anomalies exceeding 10 mm·day−1 over drought prone regions of Northeastern Ethiopia. However, the June–September rainy season tends to be wetter (drier when the SST warming (cooling is limited to either the Northern or Southern Indian Ocean. Wet rainy seasons generally are characterized by deepening of the monsoon trough, east of 40°E, intensification of the Mascarene high, strengthening of the Somali low level jet and the tropical easterly jet, enhanced zonal and meridional vertically integrated moisture fluxes, and steeply vertically decreasing moist static energy. The opposite conditions hold for dry monsoon seasons.

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

    Directory of Open Access Journals (Sweden)

    Abdouramane Gado Djibo

    2015-09-01

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

  18. Interannual variability of rainfall characteristics over southwestern Madagascar

    Science.gov (United States)

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

    2017-04-01

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

  19. 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.

  20. 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.

  1. The effect of aerosol optical depth on rainfall with reference to meteorology over metro cities in India.

    Science.gov (United States)

    Gunaseelan, Indira; Bhaskar, B Vijay; Muthuchelian, K

    2014-01-01

    Rainfall is a key link in the global water cycle and a proxy for changing climate; therefore, proper assessment of the urban environment's impact on rainfall will be increasingly important in ongoing climate diagnostics and prediction. Aerosol optical depth (AOD) measurements on the monsoon seasons of the years 2008 to 2010 were made over four metro regional hotspots in India. The highest average of AOD was in the months of June and July for the four cities during 3 years and lowest was in September. Comparing the four regions, Kolkata was in the peak of aerosol contamination and Chennai was in least. Pearson correlation was made between AOD with climatic parameters. Some changes in the parameters were found during drought year. Temperature, cloud parameters, and humidity play an important role for the drought conditions. The role of aerosols, meteorological parameters, and their impacts towards the precipitation during the monsoon was studied.

  2. 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...

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. Rainfall measurement from the opportunistic use of an Earth–space link in the Ku band

    Directory of Open Access Journals (Sweden)

    L. Barthès

    2013-08-01

    Full Text Available The present study deals with the development of a low-cost microwave device devoted to the measurement of average rain rates observed along Earth–satellite links, the latter being characterized by a tropospheric path length of a few kilometres. The ground-based power measurements, which are made using the Ku-band television transmissions from several different geostationary satellites, are based on the principle that the atmospheric attenuation produced by rain encountered along each transmission path can be used to determine the path-averaged rain rate. This kind of device could be very useful in hilly areas where radar data are not available or in urban areas where such devices could be directly placed in homes by using residential TV antenna. The major difficulty encountered with this technique is that of retrieving rainfall characteristics in the presence of many other causes of received signal fluctuation, produced by atmospheric scintillation, variations in atmospheric composition (water vapour concentration, cloud water content or satellite transmission parameters (variations in emitted power, satellite pointing. In order to conduct a feasibility study with such a device, a measurement campaign was carried out over a period of five months close to Paris. The present paper proposes an algorithm based on an artificial neural network, used to identify dry and rainy periods and to model received signal variability resulting from effects not related to rain. When the altitude of the rain layer is taken into account, the rain attenuation can be inverted to obtain the path-averaged rain rate. The rainfall rates obtained from this process are compared with co-located rain gauges and radar measurements taken throughout the full duration of the campaign, and the most significant rainfall events are analysed.

  8. Rainfall Threshold of Triggering Landslide-an Example of Typhoon Soudelor in 2015

    Science.gov (United States)

    Lin, Yong-Jun; Lin, Ji-Hua; Tan, Yih-Chi

    2016-04-01

    Typhoon Soudelor (2015) stroke southern New Taipei City, Taiwan. It brought huge damages to Xindian District and Wulai District, and those damages including 7 large landslides, blockages to access roads, and strands of hundreds of residents. The main reasons of landslide due to the high intensity rain brought by Typhoon Soudelor. The rain gauges near the sites of landslides showed the maximum hourly rainfall of 70 (mm) and the accumulative rainfall is 500-800 (mm). The largest area of the above-mentioned landslide is 9.7 ha. According to the study conducted in (Cheng et. al, 2014), the average 3hr-rainfall intensity and 24hr-accumulative-rainfall can used for indicators for the rainfall threshold of triggering landslide. Based on the historical landslide events, three rainfall threshold of triggering landslide can be gotten for probability of 30%, 60%, and 90% respectively. Using the rainfall data of Typhoon Soudelor, it is found that the rainfall recording in gauges located very near the line of probability of 90%. The average 3hr-rainfall intensity of 70 (mm/hr) and 24hr-accumulative-rainfall of 700 (mm) are used for probability of 90%. As for probability of 30%, the 3hr-rainfall intensity is 30 (mm/hr) and 24hr-accumulative-rainfall is 300 (mm). As for probability of 60%, the 3hr-rainfall intensity is 50 (mm/hr) and 24hr-accumulative-rainfall is 500 (mm). The curve of trigging landslide adopted in this study is ellipse, and may be modified by verifying more data.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. Analyses of a long-term, high-resolution radar rainfall data set for the Baltimore metropolitan region

    Science.gov (United States)

    Smith, James A.; Baeck, Mary Lynn; Villarini, Gabriele; Welty, Claire; Miller, Andrew J.; Krajewski, Witold F.

    2012-04-01

    We introduce a long-term, high-resolution radar rainfall data set for the Baltimore metropolitan area covering the 10-yr period from 2000-2009. Rainfall fields are developed at 15 min time interval and 1 km horizontal resolution for a 17,000-km2 region centered on the Baltimore metropolitan area. The Hydro-NEXRAD system is used as a platform for generating radar rainfall fields. We utilize the high-resolution, 10-yr data set to characterize striking spatial heterogeneities in rainfall for the Baltimore metropolitan region, both in terms of mean rainfall and rainfall extremes. The role of complex terrain (associated with urbanization, the Chesapeake Bay, and mountainous terrain) in controlling spatial heterogeneities of rainfall climatology for the Baltimore study region is discussed. We also characterize the seasonal and diurnal variation of rainfall over the study region using the 10-yr rainfall data set, with particular focus on the diurnal variation of rainfall during the warm season. High-resolution rainfall fields are especially useful for examining the distribution of rainfall from a drainage basin perspective, as illustrated through analyses of basin-averaged rainfall rate for basins of contrasting drainage area and analyses of the duration of dry periods for small urban watersheds. Analyses and methodologies used to develop the long-term Baltimore rainfall data set are broadly applicable to other regions of the United States and in settings around the world with long-term, high-quality radar data sets.

  14. 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.

  15. 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...

  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. 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.

  18. 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.

  19. 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.

  20. Aggregation and Averaging.

    Science.gov (United States)

    Siegel, Irving H.

    The arithmetic processes of aggregation and averaging are basic to quantitative investigations of employment, unemployment, and related concepts. In explaining these concepts, this report stresses need for accuracy and consistency in measurements, and describes tools for analyzing alternative measures. (BH)

  1. MN Temperature Average (1961-1990) - Line

    Data.gov (United States)

    Minnesota Department of Natural Resources — This data set depicts 30-year averages (1961-1990) of monthly and annual temperatures for Minnesota. Isolines and regions were created using kriging and...

  2. MN Temperature Average (1961-1990) - Polygon

    Data.gov (United States)

    Minnesota Department of Natural Resources — This data set depicts 30-year averages (1961-1990) of monthly and annual temperatures for Minnesota. Isolines and regions were created using kriging and...

  3. On Averaging Rotations

    DEFF Research Database (Denmark)

    Gramkow, Claus

    1999-01-01

    In this article two common approaches to averaging rotations are compared to a more advanced approach based on a Riemannian metric. Very offten the barycenter of the quaternions or matrices that represent the rotations are used as an estimate of the mean. These methods neglect that rotations belong...... approximations to the Riemannian metric, and that the subsequent corrections are inherient in the least squares estimation. Keywords: averaging rotations, Riemannian metric, matrix, quaternion...

  4. Changes in extreme rainfall over South-East Asia and their link to the monsoon system in 21th century from CMIP5 simulations

    Science.gov (United States)

    Freychet, N.; Chou, C.; Hsu, H.; Wu, C.

    2013-12-01

    The South-East Asia is well known for its recurrent heavy rainfall, either due to typhoons or monsoon systems. In a global warming scenario, extreme rainfall are expected to increase, both in intensity and frequency, because of the increase in air moisture. This increase often comes along with an augmentation of dry days frequency, indicating that the atmospheric water is released less frequently but more intensively. This can be explained by a rise of mid-level troposphere temperature, which increase the required CAPE for convection. Several studies already pointed out this aspect with the CMIP3 results. Here we investigate the change in extreme rainfall (i.e. the 99th percentile of precipitation) over South-East Asia, using the CMIP5 daily results. We compare the mean long term trend (i.e. the mean of 30 years at the end of the 21th century forecast), with the average of 30 years from historical runs. We do not only perform global statistical analysis, but we mainly look at the spatial pattern of changes, along with the modification of the monsoon system in this region. We also investigate the seasonal and monthly signal of changes. This study focus on rainfall over lands only, because of their possible social and economic impacts. The results show first a wild range between models regarding their sensitivity to the global warming. In the mean, they all show an increase in extreme rainfall. But the range of the change in intensity goes from 0 to 50 percent (increase), which point out great uncertainties. In all the models, the extreme rainfall increase much faster than the average precipitation. This increase is weaker during winter (about 10%) and stronger during summer (30%), characterizing an intensification in the monsoon system. This also means that the inter-seasonal signal should increase by the end of the century. The monsoon is not affected uniformly. We observe intra-seasonal variation, with enhance or decrease in winds velocities, and also differences

  5. Interception of rainfall and surface runoff in the Brazilian Cerrado

    Science.gov (United States)

    Tarso Oliveira, Paulo; Wendland, Edson; Nearing, Mark; Perea Martins, João

    2014-05-01

    The Brazilian Cerrado plays a fundamental role in water resources dynamics because it distributes fresh water to the largest basins in Brazil and South America. In recent decades, the native Cerrado vegetation has increasingly been replaced by agricultural crops and pasture. These land cover and land use changes have altered the hydrological processes. Meanwhile, little is known about the components of the water balance in the Brazilian Cerrado, mainly because the experimental field studies in this region are scarce or nonexistent. The objective of this study was to evaluate two hydrological processes under native Cerrado vegetation, the canopy interception (CI) and the surface runoff (R). The Cerrado physiognomy was classified as "cerrado sensu stricto denso" with an absolute density of 15,278 trees ha-1, and a basal area of 11.44 m2 ha-1. We measured the gross rainfall (P) from an automated tipping bucket rain gauge (model TB4) located in a tower with 11 m of height on the Cerrado. Throughfall (TF) was obtained from 15 automated tipping bucket rain gauges (model Davis) spread below the Cerrado vegetation and randomly relocated every month during the wet season. Stemflow (SF) was measured on 12 trees using a plastic hose wrapped around the trees trunks, sealed with neutral silicone sealant, and a bucket to store the water. The canopy interception was computed by the difference between P and the sum of TF and SF. Surface runoff under undisturbed Cerrado was collected in three plots of 100 m2(5 x 20 m) in size and slope steepness of approximately 0.09 m m-1. The experimental study was conducted between January 2012 and November 2013. We found TF of 81.0% of P and SF of 1.6% of P, i.e. the canopy interception was calculated at 17.4% of P. There was a statistically significant correlation (p 0.8. Our results suggest that the rainfall intensity, the characteristics of the trees trunks (crooked and twisted) and stand structure are the main factors that have influenced

  6. 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...

  7. 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.

  8. 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.

  9. Characteristics of rainfall events in regional climate model simulations for the Czech Republic

    Science.gov (United States)

    Svoboda, Vojtěch; Hanel, Martin; Máca, Petr; Kyselý, Jan

    2017-02-01

    Characteristics of rainfall events in an ensemble of 23 regional climate model (RCM) simulations are evaluated against observed data in the Czech Republic for the period 1981-2000. Individual rainfall events are identified using the concept of minimum inter-event time (MIT) and only heavy events (15 % of events with the largest event depths) during the warm season (May-September) are considered. Inasmuch as an RCM grid box represents a spatial average, the effects of areal averaging of rainfall data on characteristics of events are investigated using the observed data. Rainfall events from the RCM simulations are then compared to those from the at-site and area-average observations. Simulated number of heavy events and seasonal total precipitation due to heavy events are on average represented relatively well despite the higher spatial variation compared to observations. RCM-simulated event depths are comparable to the area-average observations, while event durations are overestimated and other characteristics related to rainfall intensity are significantly underestimated. The differences between RCM-simulated and at-site observed rainfall event characteristics are in general dominated by the biases of the climate models rather than the areal-averaging effect. Most of the rainfall event characteristics in the majority of the RCM simulations show a similar altitude-dependence pattern as in the observed data. The number of heavy events and seasonal total precipitation due to heavy events increase with altitude, and this dependence is captured better by the RCM simulations with higher spatial resolution.

  10. Should seasonal rainfall forecasts be used for flood preparedness?

    Directory of Open Access Journals (Sweden)

    E. Coughlan de Perez

    2017-09-01

    Full Text Available In light of strong encouragement for disaster managers to use climate services for flood preparation, we question whether seasonal rainfall forecasts should indeed be used as indicators of the likelihood of flooding. Here, we investigate the primary indicators of flooding at the seasonal timescale across sub-Saharan Africa. Given the sparsity of hydrological observations, we input bias-corrected reanalysis rainfall into the Global Flood Awareness System to identify seasonal indicators of floodiness. Results demonstrate that in some regions of western, central, and eastern Africa with typically wet climates, even a perfect tercile forecast of seasonal total rainfall would provide little to no indication of the seasonal likelihood of flooding. The number of extreme events within a season shows the highest correlations with floodiness consistently across regions. Otherwise, results vary across climate regimes: floodiness in arid regions in southern and eastern Africa shows the strongest correlations with seasonal average soil moisture and seasonal total rainfall. Floodiness in wetter climates of western and central Africa and Madagascar shows the strongest relationship with measures of the intensity of seasonal rainfall. Measures of rainfall patterns, such as the length of dry spells, are least related to seasonal floodiness across the continent. Ultimately, identifying the drivers of seasonal flooding can be used to improve forecast information for flood preparedness and to avoid misleading decision-makers.

  11. Demography of Verreaux's sifaka in a stochastic rainfall environment.

    Science.gov (United States)

    Lawler, Richard R; Caswell, Hal; Richard, Alison F; Ratsirarson, Joelisoa; Dewar, Robert E; Schwartz, Marion

    2009-09-01

    In this study, we use deterministic and stochastic models to analyze the demography of Verreaux's sifaka (Propithecus verreauxi verreauxi) in a fluctuating rainfall environment. The model is based on 16 years of data from Beza Mahafaly Special Reserve, southwest Madagascar. The parameters in the stage-classified life cycle were estimated using mark-recapture methods. Statistical models were evaluated using information-theoretic techniques and multi-model inference. The highest ranking model is time-invariant, but the averaged model includes rainfall-dependence of survival and breeding. We used a time-series model of rainfall to construct a stochastic demographic model. The time-invariant model and the stochastic model give a population growth rate of about 0.98. Bootstrap confidence intervals on the growth rates, both deterministic and stochastic, include 1. Growth rates are most elastic to changes in adult survival. Many demographic statistics show a nonlinear response to annual rainfall but are depressed when annual rainfall is low, or the variance in annual rainfall is high. Perturbation analyses from both the time-invariant and stochastic models indicate that recruitment and survival of older females are key determinants of population growth rate.

  12. Should seasonal rainfall forecasts be used for flood preparedness?

    Science.gov (United States)

    Coughlan de Perez, Erin; Stephens, Elisabeth; Bischiniotis, Konstantinos; van Aalst, Maarten; van den Hurk, Bart; Mason, Simon; Nissan, Hannah; Pappenberger, Florian

    2017-09-01

    In light of strong encouragement for disaster managers to use climate services for flood preparation, we question whether seasonal rainfall forecasts should indeed be used as indicators of the likelihood of flooding. Here, we investigate the primary indicators of flooding at the seasonal timescale across sub-Saharan Africa. Given the sparsity of hydrological observations, we input bias-corrected reanalysis rainfall into the Global Flood Awareness System to identify seasonal indicators of floodiness. Results demonstrate that in some regions of western, central, and eastern Africa with typically wet climates, even a perfect tercile forecast of seasonal total rainfall would provide little to no indication of the seasonal likelihood of flooding. The number of extreme events within a season shows the highest correlations with floodiness consistently across regions. Otherwise, results vary across climate regimes: floodiness in arid regions in southern and eastern Africa shows the strongest correlations with seasonal average soil moisture and seasonal total rainfall. Floodiness in wetter climates of western and central Africa and Madagascar shows the strongest relationship with measures of the intensity of seasonal rainfall. Measures of rainfall patterns, such as the length of dry spells, are least related to seasonal floodiness across the continent. Ultimately, identifying the drivers of seasonal flooding can be used to improve forecast information for flood preparedness and to avoid misleading decision-makers.

  13. [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).

  14. Rainfall Reduction Increases Soil Methane Uptake in Broadleaf Evergreen Eucalypt Forest - a Negative Feedback to Climate Change

    Science.gov (United States)

    Fest, B. J.; Hinko-Najera, N.; Livesley, S. J.; Arndt, S. K.

    2013-12-01

    Well-drained aerated soils are important sinks for atmospheric methane (CH4), a process driven by CH4 oxidation through methanotrophic bacteria. Soils in temperate forest ecosystems represent the greatest terrestrial CH4 sink and soil moisture is one of the key regulators of soil CH4 flux in these systems. Most climate change models predict a decrease in average rainfall, an increase in extreme rainfall events and an increase in temperatures for mid-latitude and sub-arid regions. However, most studies of soil CH4 flux under altered rainfall scenarios have been conducted in mid-latitude forest and grassland systems of the northern hemisphere or in tropical forest systems and have often investigated extended drought rather than an reduction in long-term average rainfall. We measured soil CH4 flux for 18 months (October 2010 - April 2012) after installing a passive rainfall reduction system to intercept approximately 40% of canopy throughfall (as compared to control plots) in a temperate broadleaf evergreen eucalypt forest in south-eastern Australia. Throughfall reduction caused an average reduction of 15.1 × 6.4 (SE) % in soil volumetric water content, a reduction of 19.8 × 6.9 (SE) % in soil water filled pore space (WFPS) and a 20.1 × 6.8 (SE) % increase in soil air filled porosity (AFP). In response to these changes, soil CH4 uptake increased by 54.7 × 19.8 (SE) %. Relative changes in CH4 uptake related better to relative changes in AFP than to relative changes in WFPS, indicating a close relationship between AFP and soil gas diffusivity. Our data indicated that soil moisture was the dominant regulating factor of seasonality in soil CH4 uptake explaining up to 80% of the seasonal variability and accounting for the observed throughfall reduction treatment effect. This was confirmed by additional soil diffusivity measurements and passive soil warming treatments. We investigated non-linear functions to describe the relationship between soil moisture and soil CH4

  15. 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.

  16. Real Rainfall Time Series for Storm Sewer Design

    DEFF Research Database (Denmark)

    Larsen, Torben

    1981-01-01

    This paper describes a simulation method for the design of retention storages, overflows etc. in storm sewer systems. The method is based on computer simulation with real real rainfall time series as input and with a simple transfer model of the ARMA-type (Autoregressive moving average) applied...

  17. Real Rainfall Time Series for Storm Sewer Design

    DEFF Research Database (Denmark)

    Larsen, Torben

    The paper describes a simulation method for the design of retention storages, overflows etc. in storm sewer systems. The method is based on computer simulation with real rainfall time series as input ans with the aply of a simple transfer model of the ARMA-type (autoregressiv moving average model...

  18. Rainfall Erosivity in Europe

    DEFF Research Database (Denmark)

    Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale

    2015-01-01

    , average temperature), elevation and latitude/longitude. The mean R-factor for the EU plus Switzerland is 722 MJ mm ha−1 h−1 yr−1, with the highest values (N1000 MJ mm ha−1 h−1 yr−1) in the Mediterranean and alpine regions and the lowest (b500 MJ mm ha−1 h−1 yr−1) in the Nordic countries....

  19. 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.

  20. Partitioning the impacts of spatial and climatological rainfall variability in urban drainage modeling

    Science.gov (United States)

    Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

    2017-03-01

    The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall input is uniformly distributed, i.e., derived from a single or very few rain gauges. When models are fed with a single uniformly distributed rainfall realization, the response of the urban drainage system to the rainfall variability remains unexplored. The goal of this study was to understand how climate variability and spatial rainfall variability, jointly or individually considered, affect the response of a calibrated hydrodynamic urban drainage model. A stochastic spatially distributed rainfall generator (STREAP - Space-Time Realizations of Areal Precipitation) was used to simulate many realizations of rainfall for a 30-year period, accounting for both climate variability and spatial rainfall variability. The generated rainfall ensemble was used as input into a calibrated hydrodynamic model (EPA SWMM - the US EPA's Storm Water Management Model) to simulate surface runoff and channel flow in a small urban catchment in the city of Lucerne, Switzerland. The variability of peak flows in response to rainfall of different return periods was evaluated at three different locations in the urban drainage network and partitioned among its sources. The main contribution to the total flow variability was found to originate from the natural climate variability (on average over 74 %). In addition, the relative contribution of the spatial rainfall variability to the total flow variability was found to increase with longer return periods. This suggests that while the use of spatially distributed rainfall data can supply valuable information for sewer network design (typically based on rainfall with return periods from 5 to 15 years), there is a more pronounced relevance when conducting flood risk assessments for larger return periods. The results show the importance of using multiple distributed rainfall realizations in urban hydrology studies to capture the

  1. Space–Time Characterization of Rainfall Field in Tuscany

    Directory of Open Access Journals (Sweden)

    Alessandro Mazza

    2017-01-01

    Full Text Available Precipitation during the period 2001–2016 over the northern and central part of Tuscany was studied in order to characterize the rainfall regime. The dataset consisted of hourly cumulative rainfall series recorded by a network of 801 rain gauges. The territory was divided into 30 × 30 km2 square areas where the annual and seasonal Average Cumulative Rainfall (ACR and its uncertainty were estimated using the Non-Parametric Ordinary Block Kriging (NPOBK technique. The choice of area size was a compromise that allows a satisfactory spatial resolution and an acceptable uncertainty of ACR estimates. The daily ACR was estimated using a less computationally expensive technique, averaging the cumulative rainfall measurements in the area. The trend analysis of annual and seasonal ACR time series was performed by means of the Mann–Kendall test. Four climatic zones were identified: the north-western was the rainiest, followed by the north-eastern, northcentral and south-central. An overall increase in precipitation was identified, more intense in the north-west, and determined mostly by the increase in winter precipitation. On the entire territory, the number of rainy days, mean precipitation intensity and sum of daily ACR in four intensity groups were evaluated at annual and seasonal scale. The main result was a magnitude of the ACR trend evaluated as 35 mm/year, due mainly to an increase in light and extreme precipitations. This result is in contrast with the decreasing rainfall detected in the past decades.

  2. 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...

  3. Your Average Nigga

    Science.gov (United States)

    Young, Vershawn Ashanti

    2004-01-01

    "Your Average Nigga" contends that just as exaggerating the differences between black and white language leaves some black speakers, especially those from the ghetto, at an impasse, so exaggerating and reifying the differences between the races leaves blacks in the impossible position of either having to try to be white or forever struggling to…

  4. On Averaging Rotations

    DEFF Research Database (Denmark)

    Gramkow, Claus

    2001-01-01

    In this paper two common approaches to averaging rotations are compared to a more advanced approach based on a Riemannian metric. Very often the barycenter of the quaternions or matrices that represent the rotations are used as an estimate of the mean. These methods neglect that rotations belong...

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

    Science.gov (United States)

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

    2016-04-01

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

  6. Space-time organization of debris flows-triggering rainfall and its effect on the identification of the rainfall threshold relationship

    Science.gov (United States)

    Marra, F.; Nikolopoulos, E. I.; Creutin, J. D.; Borga, M.

    2016-10-01

    Debris flow occurrence is generally forecasted by means of empirical rainfall depth-duration thresholds based on raingauge observations. Rainfall estimation errors related to the sparse nature of raingauge data are enhanced in case of convective rainfall events characterized by limited spatial extent. Such errors have been shown to cause underestimation of the rainfall thresholds and, thus, less efficient forecasts of debris flows occurrence. This work examines the spatial organization of debris flows-triggering rainfall around the debris flow initiation points using high-resolution, carefully corrected radar data for a set of short duration (debris flow initiation point, with rain depth at 5 km (10 km) distance being on average around 70% (40%) of rain depth observed at the debris flow initiation points. The peak is consistently enhanced for events characterized by short durations and causes a systematic underestimation of the rainfall depth-duration thresholds when rainfall is measured away from the debris flow initiation points. We develop an analytical framework that exploits the general characteristics of the spatial rainfall organization to predict the systematic underestimation of the depth-duration thresholds when rainfall is sampled away from the initiation points. Predictions obtained based on this analytical framework are assessed using a Monte Carlo sampling technique.

  7. 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.

  8. 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.

  9. Modeling rainfall-runoff processes using smoothed particle hydrodynamics with mass-varied particles

    Science.gov (United States)

    Chang, Tsang-Jung; Chang, Yu-Sheng; Chang, Kao-Hua

    2016-12-01

    In this study, a novel treatment of adopting mass-varied particles in smoothed particle hydrodynamics (SPH) is proposed to solve the shallow water equations (SWEs) and model the rainfall-runoff process. Since SWEs have depth-averaged or cross-section-averaged features, there is no sufficient dimension to add rainfall particles. Thus, SPH-SWE methods have focused on modeling discharge flows in open channels or floodplains without rainfall. With the proposed treatment, the application of SPH-SWEs can be extended to rainfall-runoff processes in watersheds. First, the numerical procedures associated with using mass-varied particles in SPH-SWEs are introduced and derived. Then, numerical validations are conducted for three benchmark problems, including uniform rainfall over a 1D flat sloping channel, nonuniform rain falling over a 1D three-slope channel with different rainfall durations, and uniform rainfall over a 2D plot with complex topography. The simulated results indicate that the proposed treatment can avoid the necessity of a source term function of mass variation, and no additional particles are needed for the increase of mass. Rainfall-runoff processes can be well captured in the presence of hydraulic jumps, dry/wet bed flows, and supercritical/subcritical/transcritical flows. The proposed treatment using mass-varied particles was proven robust and reliable for modeling rainfall-runoff processes. It can provide a new alternative for investigating practical hydrological problems.

  10. 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.

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

    Science.gov (United States)

    Duangdai, Eakkapong; Likasiri, Chulin

    2017-03-01

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

  12. Predictability of rainfall and teleconnections patterns influencing on Southwest Europe from sea surfaces temperatures

    Science.gov (United States)

    Lorenzo, M. N.; Iglesias, I.; Taboada, J. J.; Gómez-Gesteira, M.; Ramos, A. M.

    2009-04-01

    This work assesses the possibility of doing a forecast of rainfall and the main teleconnections patterns that influences climate in Southwest Europe by using sea surface temperature anomalies (SSTA). The area under study is located in the NW Iberian Peninsula. This region has a great oceanic influence on its climate and has an important dependency of the water resources. In this way if the different SST patterns are known, the different rainfall situations can be predicted. On the other hand, the teleconnection patterns, which have strong weight on rainfall, are influenced by the SSTA of different areas. In the light of this, the aim of this study is to explore the relationship between global SSTAs, rainfall and the main teleconnection patterns influencing on Europe. The SST data with a 2.0 degree resolution was provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA. A monthly averaged data from 1 January 1951 through December 2006 was considered. The monthly precipitation data from 1951-2006 were obtained from the database CLIMA of the University of Santiago de Compostela with data from the Meteorological State Agency (AEMET) and the Regional Government of Galicia. The teleconnection indices were taken of the Climate Prediction Center of the NOAA between 1950 and 2006. A monthly and seasonal study was analysed considering up to three months of delay in the first case and up to four seasons of delay in the second case. The Pearson product-moment correlation coefficient r was considered to quantify linear associations between SSTA and precipitation and/or SSTA and teleconnection indices. A test for field-significance was applied considering the properties of finiteness and interdependence of the spatial grid to avoid spurious correlations. Analysing the results obtained with the global SSTA and the teleconnection indices, a great number of ocean regions with high correlations can be found. The spatial patterns show very high correlations with Indian Ocean waters

  13. 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.

  14. 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.

  15. Influence of cosmic-ray variability on the monsoon rainfall and temperature

    CERN Document Server

    Badruddin,

    2014-01-01

    We study the role of galactic cosmic ray (GCR) variability in influencing the rainfall variability in Indian Summer Monsoon Rainfall (ISMR) season. We find that on an average during 'drought' (low ISMR) periods in India, GCR flux is decreasing, and during 'flood' (high ISMR) periods, GCR flux is increasing. The results of our analysis suggest for a possibility that the decreasing GCR flux during the summer monsoon season in India may suppress the rainfall. On the other hand, increasing GCR flux may enhance the rainfall. We suspect that in addition to real environmental conditions, significant levitation/dispersion of low clouds and hence reduced possibility of collision/coalescence to form raindrops suppresses the rainfall during decreasing GCR flux in monsoon season. On the other hand, enhanced collision/coalescence efficiency during increasing GCR flux due to electrical effects may contribute to enhancing the rainfall. Based on the observations, we put forward the idea that, under suitable environmental con...

  16. Covariant approximation averaging

    CERN Document Server

    Shintani, Eigo; Blum, Thomas; Izubuchi, Taku; Jung, Chulwoo; Lehner, Christoph

    2014-01-01

    We present a new class of statistical error reduction techniques for Monte-Carlo simulations. Using covariant symmetries, we show that correlation functions can be constructed from inexpensive approximations without introducing any systematic bias in the final result. We introduce a new class of covariant approximation averaging techniques, known as all-mode averaging (AMA), in which the approximation takes account of contributions of all eigenmodes through the inverse of the Dirac operator computed from the conjugate gradient method with a relaxed stopping condition. In this paper we compare the performance and computational cost of our new method with traditional methods using correlation functions and masses of the pion, nucleon, and vector meson in $N_f=2+1$ lattice QCD using domain-wall fermions. This comparison indicates that AMA significantly reduces statistical errors in Monte-Carlo calculations over conventional methods for the same cost.

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

    Directory of Open Access Journals (Sweden)

    Chee Loong Wong

    2016-11-01

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

  18. rainfall runoff model for cala noff model for calabar metropolis u ...

    African Journals Online (AJOL)

    eobe

    4 DEPARTMENT OF CIVIL ENGINEERING, R. E-mail addresses ... have the highest average rainfall. However, due ...... [10] Nigerian Meteorological Agency, 2010. [11] Darayatne ... and Environment Research, Queensland, Australia,. 6-8 July ...

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

    Science.gov (United States)

    Xu, Y. P.; Gao, C.

    2016-12-01

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

  20. 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

  1. 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.

  2. 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

  3. Is rainfall erosivity influenced by climate change?. A case study in a Mediterranean Climate area of North East Spain

    Science.gov (United States)

    Ramos, Maria C.

    2014-05-01

    One of the main characteristics of the Mediterranean climate is the high intensity rainfall events usually recorded in autumn and spring. Those events usually concentrate a high percentage of annual rainfall. Different studies carried out in the Mediterranean countries suggest that notable changes in seasonal precipitation regimes have occurred during the second half of the 20th century. In addition, precipitation extremes seem to increase in association with global warming, which may favour erosion processes. Under this hypothesis one question arise: is the rainfall erosivity increasing influenced by climate change? In this work rainfall erosivity and its variability in the last two decades was analysed in an area located NE Spain, where erosion processes of high magnitude are recorded. The main land use in that area is grape vines, which due to the scarce soil cover is usually associated with the highest erosion rates. The study area was located in the Penedès depression (North East Spain). Hourly data from four observatories Els Hostalets de Pierola (UTM X: 400664, Y: 4598608m, elv: 326m ), La Granada ( X:393758; Y:4580393), Sant Martí Sarroca (X: 385556; Y:4581486, elv: 257m) and Font_Rubi (X: 385118, Y:4587935. elev: 415 m ) belonging to the period 1997-2013 were used in the analysis together with a tipping bucket rainfall series recorded at one minute intervals (10 years within the period 1996-2012). Rainfall erosivity was quantified by the index rainfall kinetic energy multiplied by the maximum intensity in 30minute periods (E*Imax30). The Imax30 was estimated from the relationship between hourly and 30 minute data obtained for the tipping bucket series using the Marquard algoritme. In order to analsye changes in rainfall erosivity, the annual and monthly number of erosive events were analysed for each observatory and in each year, the events were classified into intervals according to their erosivity. The intervals used were: 0-100; 100-200; 200-300; 300

  4. Rainfall Variability across the Agneby Watershed at the Agboville Outlet in Côte d’Ivoire, West Africa

    Directory of Open Access Journals (Sweden)

    Akissi Bienve Pélagie Kouakou

    2016-12-01

    Full Text Available This study analyzes, at local and regional scales, the rainfall variability across the Agneby watershed at the Agboville outlet over the period 1950–2013. Daily rainfall data from 14 rain gauges are used. The methods used are based, firstly, on the rainfall index which aims to characterize the inter-annual and decadal variability of rainfall and, secondly, on the moving average to determine the dynamics of the mean seasonal cycle of the precipitations. Furthermore, the Pettitt test and the Hubert segmentation are applied to detect change-point in the rainfall series. At the basin scale, analysis of rainfall signals composites has shown that the rainfall deficit was more pronounced after the leap of monsoon. Dry years were characterized by an early monsoon demise which is remarkable after 1968. Moreover, the years after 1969 presented a shift of the peaks in precipitation for about 12 days. These peaks were reached early. The rainfall signal showed that the rainfall deficit for the period after 1968, relatively to the period before, was 10% in June against 36% in October for the average rainfall in the Agneby basin. At the local scale, the deficit of the peaks depends on the location. These rainfall deficits were 23% against 36.3% in June for the Agboville and Bongouanou rain gauges, respectively.

  5. Negative Average Preference Utilitarianism

    Directory of Open Access Journals (Sweden)

    Roger Chao

    2012-03-01

    Full Text Available For many philosophers working in the area of Population Ethics, it seems that either they have to confront the Repugnant Conclusion (where they are forced to the conclusion of creating massive amounts of lives barely worth living, or they have to confront the Non-Identity Problem (where no one is seemingly harmed as their existence is dependent on the “harmful” event that took place. To them it seems there is no escape, they either have to face one problem or the other. However, there is a way around this, allowing us to escape the Repugnant Conclusion, by using what I will call Negative Average Preference Utilitarianism (NAPU – which though similar to anti-frustrationism, has some important differences in practice. Current “positive” forms of utilitarianism have struggled to deal with the Repugnant Conclusion, as their theory actually entails this conclusion; however, it seems that a form of Negative Average Preference Utilitarianism (NAPU easily escapes this dilemma (it never even arises within it.

  6. Numerical analysis of rainfall effects in external overburden dump

    Institute of Scientific and Technical Information of China (English)

    Radhakanta Koner⇑; Debashish Chakravarty

    2016-01-01

    The effect of slope angle for external overburden dump in response to average and heavy rainfall has been analyzed using a two dimensional finite difference method of transient water flow through unsaturated–saturated soil. The external dump stability is evaluated for five geomaterial types on the basis of globally accepted safety factor analysis technique, based on shear strength reduction approach using finite differ-ence method. The results obtained from the finite difference method of analysis indicate that the external dump with more than 30? slope angle is greatly influenced by the rainfall under the studied conditions for geomaterial 3, 4 and 5, whereas dumps with geomaterial 1 and 2 remain safe. The analysis shows that major slope failure is out of preview for the studied rainfall conditions.

  7. Radar rainfall estimation for the identification of debris-flow precipitation thresholds

    Science.gov (United States)

    Marra, Francesco; Nikolopoulos, Efthymios I.; Creutin, Jean-Dominique; Borga, Marco

    2014-05-01

    Identification of rainfall thresholds for the prediction of debris-flow occurrence is a common approach for warning procedures. Traditionally the debris-flow triggering rainfall is derived from the closest available raingauge. However, the spatial and temporal variability of intense rainfall on mountainous areas, where debris flows take place, may lead to large uncertainty in point-based estimates. Nikolopoulos et al. (2014) have shown that this uncertainty translates into a systematic underestimation of the rainfall thresholds, leading to a step degradation of the performances of the rainfall threshold for identification of debris flows occurrence under operational conditions. A potential solution to this limitation lies on use of rainfall estimates from weather radar. Thanks to their high spatial and temporal resolutions, these estimates offer the advantage of providing rainfall information over the actual debris flow location. The aim of this study is to analyze the value of radar precipitation estimations for the identification of debris flow precipitation thresholds. Seven rainfall events that triggered debris flows in the Adige river basin (Eastern Italian Alps) are analyzed using data from a dense raingauge network and a C-Band weather radar. Radar data are elaborated by using a set of correction algorithms specifically developed for weather radar rainfall application in mountainous areas. Rainfall thresholds for the triggering of debris flows are identified in the form of average intensity-duration power law curves using a frequentist approach by using both radar rainfall estimates and raingauge data. Sampling uncertainty associated to the derivation of the thresholds is assessed by using a bootstrap technique (Peruccacci et al. 2012). Results show that radar-based rainfall thresholds are largely exceeding those obtained by using raingauge data. Moreover, the differences between the two thresholds may be related to the spatial characteristics (i.e., spatial

  8. Rainfall partitioning by desert shrubs in arid regions

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    We measured the rainfall partitioning among throughfall, stemflow, and interception by desert shrubs in an arid region of China, and analyzed the influence of rainfall and canopy characteristics on this partitioning and its ecohydrological effects. The percent-ages of total rainfall accounted for by throughfall, stemflow, and interception ranged from 78.85±2.78 percent to 86.29±5.07 per-cent, from 5.50±3.73 percent to 8.47±4.19 percent, and from 7.54±2.36 percent to 15.95±4.70 percent, respectively, for the four shrubs in our study (Haloxylon ammodendron, Elaeagnus angustifolia, Tamarix ramosissima, and Nitraria sphaerocarpa). Rain-fall was significantly linearly correlated with throughfall, stemflow, and interception (P < 0.0001). The throughfall, stemflow, and interception percentages were logarithmically related to total rainfall (P < 0.01), but were quadratically related to the maximum 1-hour rainfall intensity (P < 0.01). The throughfall and stemflow percentages increased significantly with increasing values of the rainfall characteristics, whereas the interception percentage generally decreased (except for average wind speed, air temperature, and canopy evaporation). Regression analysis suggested that the stemflow percentage increased significantly with increasing crown length, number of branches, and branch angle (R2 = 0.92, P < 0.001). The interception percentage increased significantly with increasing LAI (leaf area index) and crown length, but decreased with increasing branch angle (R2 = 0.96, P < 0.001). The mean funnelling percentages for the four shrubs ranged from 30.27±4.86 percent to 164.37±6.41 percent of the bulk precipitation. Much of the precipitation was funnelled toward the basal area of the stem, confirming that shrub stemflow conserved in deep soil layers may be an available moisture source to support plant survival and growth under arid conditions.

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

    Science.gov (United States)

    Auld, Heather; MacIver, D; Klaassen, J

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

  10. Impact of rainfall spatial variability on Flash Flood Forecasting

    Science.gov (United States)

    Douinot, Audrey; Roux, Hélène; Garambois, Pierre-André; Larnier, Kevin

    2014-05-01

    According to the United States National Hazard Statistics database, flooding and flash flooding have caused the largest number of deaths of any weather-related phenomenon over the last 30 years (Flash Flood Guidance Improvement Team, 2003). Like the storms that cause them, flash floods are very variable and non-linear phenomena in time and space, with the result that understanding and anticipating flash flood genesis is far from straightforward. In the U.S., the Flash Flood Guidance (FFG) estimates the average number of inches of rainfall for given durations required to produce flash flooding in the indicated county. In Europe, flash flood often occurred on small catchments (approximately 100 km2) and it has been shown that the spatial variability of rainfall has a great impact on the catchment response (Le Lay and Saulnier, 2007). Therefore, in this study, based on the Flash flood Guidance method, rainfall spatial variability information is introduced in the threshold estimation. As for FFG, the threshold is the number of millimeters of rainfall required to produce a discharge higher than the discharge corresponding to the first level (yellow) warning of the French flood warning service (SCHAPI: Service Central d'Hydrométéorologie et d'Appui à la Prévision des Inondations). The indexes δ1 and δ2 of Zoccatelli et al. (2010), based on the spatial moments of catchment rainfall, are used to characterize the rainfall spatial distribution. Rainfall spatial variability impacts on warning threshold and on hydrological processes are then studied. The spatially distributed hydrological model MARINE (Roux et al., 2011), dedicated to flash flood prediction is forced with synthetic rainfall patterns of different spatial distributions. This allows the determination of a warning threshold diagram: knowing the spatial distribution of the rainfall forecast and therefore the 2 indexes δ1 and δ2, the threshold value is read on the diagram. A warning threshold diagram is

  11. Chapman Conference on Rainfall Fields

    Science.gov (United States)

    Gupta, V. K.

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

  12. Rainfall simulation for environmental application

    Energy Technology Data Exchange (ETDEWEB)

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

    1977-08-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  14. Evaluation of Rainfall-Runoff Models for Mediterranean Subcatchments

    Science.gov (United States)

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

    2016-06-01

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

  15. EVALUATION OF RAINFALL-RUNOFF MODELS FOR MEDITERRANEAN SUBCATCHMENTS

    Directory of Open Access Journals (Sweden)

    A. Cilek

    2016-06-01

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

  16. Model for forecasting of monthly average insulation at ground level taking into account the radiation absorption losses crossing atmosphere in the thermal solar applications; Modelo de previsao da insolacao media mensal ao nivel do solo levando em conta a perda por absorcao na atmosfera em aplicacoes solares termicas

    Energy Technology Data Exchange (ETDEWEB)

    Camargo, J.C.; Apolinario, F.R.; Silva, E.P. da [Universidade Estadual de Campinas, SP (Brazil). Lab. de Hidrogenio]. E-mails: joaoc@fem.unicamp.br; rezende@ifi.unicamp.br; lh2ennio@ifi.unicamp.br

    2000-07-01

    The use of the solar energy, for thermal or photovoltaic ends, depends basically on the amount of radiation that reaches the ground in the place where desires to carry through this use, defining the necessary area of the collectors, or panels, that in turn are the main components of the final cost of the system and, therefore, of the viability or not on its use. The incident radiation in the terrestrial surface is minor that one reaches the top of the atmosphere due to the absorption and dispersion factors. The objective of this work is to present a model of forecast the monthly average radiation for ends of use in systems of flat solar collectors for heating water, in the city of Campinas - Sao Paulo, Brazil. This work has been developed by the Hydrogen Laboratory of the Institute of Physics of the UNICAMP, being also used for other applications with solar energy. Based in the radiation data, taken from a local station, a theoretical study was developed to calculate a parameter of loss of radiation when this cross the atmosphere. This Kt loss factor, has basic importance for the knowledge of the effective available energy for use. With this data it is possible to determine, on the basis of the incident radiation in the top of the atmosphere, the value of the radiation on a surface. (author)

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

    Science.gov (United States)

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

    2016-08-05

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

  18. 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...

  19. Boreal summer quasi-monthly oscillation in the global tropics

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Bin; Kikuchi, Kazuyoshi [University of Hawaii, Department of Meteorology and the International Pacific Research Center (IPRC), Honolulu, HI (United States); Webster, Peter [Georgia Tech University, School of Earth and Atmospheric Science and Civil and Environmental Engineering, Atlanta, GA (United States); Yasunari, Tetsuzo [Nagoya University, Hydrospheric and Atmospheric Research Center, Nagoya (Japan); Qi, Yanjun [Chinese Academy of Science, Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Beijing (China)

    2006-12-15

    The boreal summer intraseasonal oscillation (ISO) in the global tropics is documented here using a 7-year suite (1998-2004) of satellite measurements. A composite scenario was made of 28 selected events with reference to the oscillation in the eastern equatorial Indian Ocean (EIO), where the oscillation is most regular and its intensity is indicative of the strength of the subsequent northward propagation. The average oscillation period is about 32 days, and this quasi-monthly oscillation (QMO) is primarily confined to the tropical Indian and Pacific Oceans. Topics that were investigated are the partition of convective versus stratiform clouds, the vertical structure of precipitation rates, and the evolution of cloud types during the initial organization and the development of intraseasonal convective anomalies in the central Indian Ocean. During the initiation of the convective anomalies, the stratiform and convective rains have comparable rates; the prevailing cloud type experiences a trimodal evolution from shallow to deep convection, and finally to anvil and extended stratiform clouds. A major northwest/southeast-slanted rainband forms as the equatorial rainfall anomalies reach Sumatra, and the rainband subsequently propagates northeastward into the west Pacific Ocean. The enhanced precipitation in the west Pacific then rapidly traverses the Pacific along the Intertropical Convergence Zone, meanwhile migrating northward to the Philippine Sea. A seesaw teleconnection in rainfall anomalies is found between the southern Bay of Bengal (5-15 N, 80-100 E) and the eastern Pacific (5-15 N, 85-105 W). Local sea-surface temperature (SST)-rainfall anomalies display a negative simultaneous correlation in the off-equatorial regions but a zero correlation (quadrature phase relationship) near the equator. We propose that atmosphere-ocean interaction and the vertical monsoon easterly shear are important contributors to the northeastward propagation component of the

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

    Science.gov (United States)

    Creese, A.; Washington, R.

    2016-11-01

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

  1. Developing a warning system in Ambon city, Indonesia: Rainfall threshold for sediment related disasters

    Science.gov (United States)

    Hasnawir, H.; Kubota, T.; Sanchez Castillo, L. R. M.

    2014-12-01

    Ambon city of Indonesia is extremely vulnerable to climatic hazards and the frequency of sediment related disasters appears to increase. During 2012 to 2013, more than one hundred of sediment related disasters including landslides occurred especially in the settlement area. The damage was particularly severe in the city and at several sites along the transportation network. The sediment related disasters resulted of hundreds houses destroyed, including 43 deaths, numerous injured people and hundreds people evacuated. Rainfall threshold method is an approach for develop a warning system for sediment related disasters occurence. Two types of rainfall thresholds can be established (Aleotti, 2004): (1) empirical thresholds, based on historic analysis of relationship rainfall/landslide (sediment related disaster) occurrence, and (2) physical thresholds, based on numeric models that take into account the relationship between rainfall, pore pressure and slope stability by coupling hydrologic and stability models. Empirical thresholds were used in this study. Empirical threshold has been considered as collecting rainfall data for sediment related disaster events from 2007 to 2013. The results show that the sediment related disasters occurred in short periods (2 hours) with a high average intensity and longer periods (48 hours) with a lower average intensity. We determined new rainfall thresholds for possible sediment related disaster occurrence with the regression value of I = 83.88D-0.80 (I is rainfall intensity, mm/hr and D is duration, hr). It is expected that the new rainfall thresholds could be used for the development of a warning system in Ambon city.

  2. Trends and spatial distribution of annual and seasonal rainfall in Ethiopia

    Science.gov (United States)

    Cheung, W.H.; Senay, G.B.; Singh, A.

    2008-01-01

    As a country whose economy is heavily dependent on low-productivity rainfed agriculture, rainfall trends are often cited as one of the more important factors in explaining various socio-economic problems such as food insecurity. Therefore, in order to help policymakers and developers make more informed decisions, this study investigated the temporal dynamics of rainfall and its spatial distribution within Ethiopia. Changes in rainfall were examined using data from 134 stations in 13 watersheds between 1960 and 2002. The variability and trends in seasonal and annual rainfall were analysed at the watershed scale with data (1) from all available years, and (2) excluding years that lacked observations from at least 25% of the gauges. Similar anlyses were also performed at the gauge, regional, and national levels. By regressing annual watershed rainfall on time, results from the one-sample t-test show no significant changes in rainfall for any of the watersheds examined. However, in our regressions of seasonal rainfall averages against time, we found a significant decline in June to September rainfall (i.e. Kiremt) for the Baro-Akobo, Omo-Ghibe, Rift Valley, and Southern Blue Nile watersheds located in the southwestern and central parts of Ethiopia. While the gauge level analysis showed that certain gauge stations experienced recent changes in rainfall, these trends are not necessarily reflected at the watershed or regional levels. Copyright ?? 2008 Royal Meteorological Society.

  3. Where do forests influence rainfall?

    Science.gov (United States)

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

    2017-04-01

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

  4. 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.

  5. 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

  6. Rainfall is a risk factor for sporadic cases of Legionella pneumophila pneumonia.

    Science.gov (United States)

    Garcia-Vidal, Carolina; Labori, Maria; Viasus, Diego; Simonetti, Antonella; Garcia-Somoza, Dolors; Dorca, Jordi; Gudiol, Francesc; Carratalà, Jordi

    2013-01-01

    It is not known whether rainfall increases the risk of sporadic cases of Legionella pneumonia. We sought to test this hypothesis in a prospective observational cohort study of non-immunosuppressed adults hospitalized for community-acquired pneumonia (1995-2011). Cases with Legionella pneumonia were compared with those with non-Legionella pneumonia. Using daily rainfall data obtained from the regional meteorological service we examined patterns of rainfall over the days prior to admission in each study group. Of 4168 patients, 231 (5.5%) had Legionella pneumonia. The diagnosis was based on one or more of the following: sputum (41 cases), antigenuria (206) and serology (98). Daily rainfall average was 0.556 liters/m(2) in the Legionella pneumonia group vs. 0.328 liters/m(2) for non-Legionella pneumonia cases (p = 0.04). A ROC curve was plotted to compare the incidence of Legionella pneumonia and the weighted median rainfall. The cut-off point was 0.42 (AUC 0.54). Patients who were admitted to hospital with a prior weighted median rainfall higher than 0.42 were more likely to have Legionella pneumonia (OR 1.35; 95% CI 1.02-1.78; p = .03). Spearman Rho correlations revealed a relationship between Legionella pneumonia and rainfall average during each two-week reporting period (0.14; p = 0.003). No relationship was found between rainfall average and non-Legionella pneumonia cases (-0.06; p = 0.24). As a conclusion, rainfall is a significant risk factor for sporadic Legionella pneumonia. Physicians should carefully consider Legionella pneumonia when selecting diagnostic tests and antimicrobial therapy for patients presenting with CAP after periods of rainfall.

  7. Rainfall is a risk factor for sporadic cases of Legionella pneumophila pneumonia.

    Directory of Open Access Journals (Sweden)

    Carolina Garcia-Vidal

    Full Text Available It is not known whether rainfall increases the risk of sporadic cases of Legionella pneumonia. We sought to test this hypothesis in a prospective observational cohort study of non-immunosuppressed adults hospitalized for community-acquired pneumonia (1995-2011. Cases with Legionella pneumonia were compared with those with non-Legionella pneumonia. Using daily rainfall data obtained from the regional meteorological service we examined patterns of rainfall over the days prior to admission in each study group. Of 4168 patients, 231 (5.5% had Legionella pneumonia. The diagnosis was based on one or more of the following: sputum (41 cases, antigenuria (206 and serology (98. Daily rainfall average was 0.556 liters/m(2 in the Legionella pneumonia group vs. 0.328 liters/m(2 for non-Legionella pneumonia cases (p = 0.04. A ROC curve was plotted to compare the incidence of Legionella pneumonia and the weighted median rainfall. The cut-off point was 0.42 (AUC 0.54. Patients who were admitted to hospital with a prior weighted median rainfall higher than 0.42 were more likely to have Legionella pneumonia (OR 1.35; 95% CI 1.02-1.78; p = .03. Spearman Rho correlations revealed a relationship between Legionella pneumonia and rainfall average during each two-week reporting period (0.14; p = 0.003. No relationship was found between rainfall average and non-Legionella pneumonia cases (-0.06; p = 0.24. As a conclusion, rainfall is a significant risk factor for sporadic Legionella pneumonia. Physicians should carefully consider Legionella pneumonia when selecting diagnostic tests and antimicrobial therapy for patients presenting with CAP after periods of rainfall.

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

    Science.gov (United States)

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

    2014-12-01

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

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

    Science.gov (United States)

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

    2002-11-01

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

  10. PEMANFAATAN DATA SATELIT TROPICAL RAINFALL MEASURING MISSION (TRMM UNTUK PEMETAAN ZONA AGROKLIMAT OLDEMAN DI KALIMANTAN SELATAN

    Directory of Open Access Journals (Sweden)

    Riza Arian Noor

    2016-12-01

    Full Text Available The irregularity of observation sites distribution and network density, lack data availability and discontinuity are the obstacles to analyzing and producing the information of agroclimate zone in South Kalimantan. TRMM satellite needs to be researched to overcome the limitations of surface observation data. This study intended to validate TRMM 3B43 satellite data with surface rainfall, to produce Oldeman agroclimate zone based on TRMM satellite data and to analyze the agroclimate zone for agricultural resources management. Data validation is done using the statistical method by analyzing the correlation value (r and RMSE (Root Mean Square Error. The agroclimate zone is classified based on Oldeman climate classification type. The calculation results are mapped spatially using Arc GIS 10.2 software. The validation result of the TRMM satellite and surface rainfall data shows a high correlation value for the monthly average. The value of correlation coefficient is 0,97 and 25 mm for RMSE value. Oldeman agroclimate zone based on TRMM satellite data in south Kalimantan is divided into five climate zones, such as B1, B2, C1, C2, and D1.

  11. The Effect of Rainfall Measurement Technique and Its Spatiotemporal Resolution on Discharge Predictions in the Netherlands

    Science.gov (United States)

    Uijlenhoet, R.; Brauer, C.; Overeem, A.; Sassi, M.; Rios Gaona, M. F.

    2014-12-01

    Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of these spatiotemporal resolutions on discharge simulations in lowland catchments by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in a freely draining lowland catchment and a polder with controlled water levels. We used rain gauge networks with automatic (hourly resolution but low spatial density) and manual gauges (high spatial density but daily resolution). Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. We also investigated the effect of spatiotemporal resolution with a high-resolution X-band radar data set for catchments with different sizes. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. When catchments are divided into sub-catchments, rainfall spatial variability can become more important, especially during convective rainfall events, leading to spatially varying catchment wetness and spatially varying contribution of quick flow routes. Improving rainfall measurements and their spatiotemporal resolution can improve the performance of rainfall

  12. Three Years of Country-Wide Rainfall Maps from Cellular Communication Networks

    Science.gov (United States)

    Uijlenhoet, R.; Overeem, A.; Leijnse, H.; Rios Gaona, M. F.

    2014-12-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information and the number of rain gauges is even severely declining in Europe, South-America, and Africa. This calls for alternative sources of rainfall information. Various studies have shown that microwave links from operational cellular communication networks may be used for rainfall monitoring. Such networks cover 20% of the land surface of the earth and have a high density, especially in urban areas. The basic principle of rainfall estimation using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated, which can be converted to average rainfall intensities over the length of a link. This is particularly interesting for those countries where few surface rainfall observations are available. A data set from a commercial microwave link network over the Netherlands is analyzed. The data set runs from January 2011 - January 2014 and consists of roughly 2000 links covering the land surface of the Netherlands (35,500 square kilometers). From this 3-year data set country-wide rainfall maps are retrieved, which are compared to a gauge-adjusted radar data set. The ability of cellular communication networks to estimate rainfall is studied for different temporal and spatial scales, as well as for several air temperature classes. Case studies are presented to investigate the performance of the algorithm during snow and sleet and to show the influence of dew formation on the antennas on the received signal levels. To summarize, the results further confirm the potential of these networks for rainfall monitoring.

  13. Long term country-wide rainfall monitoring employing cellular communication networks

    Science.gov (United States)

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2013-04-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information and the number of rain gauges is even severely declining in Europe, South-America, and Africa. This calls for alternative sources of rainfall information. Various studies have shown that microwave links from operational cellular telecommunication networks may be employed for rainfall monitoring. Such networks cover 20% of the land surface of the earth and have a high density, especially in urban areas. The basic principle of rainfall monitoring using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. This is particularly interesting for those countries where few surface rainfall observations are available. Here we present preliminary results of long term country-wide rainfall monitoring employing cellular communication networks. A dataset from a commercial microwave link network over the Netherlands is analyzed, containing data from an unprecedented number of links (~ 2000) covering the land surface of the Netherlands (35500 square kilometres). This dataset spans from January 2011 through October 2012. Daily rainfall maps (1 km spatial resolution) are derived from the microwave link data and compared to maps from a gauge-adjusted radar dataset. The performance of the rainfall retrieval algorithm will be investigated, particularly a possible seasonal dependence.

  14. Three Years of Country-Wide Rainfall Maps from Cellular Communication Networks

    Science.gov (United States)

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

    2015-04-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information and the number of rain gauges is even severely declining in Europe, South-America, and Africa. This calls for alternative sources of rainfall information. Various studies have shown that microwave links from operational cellular communication networks may be used for rainfall monitoring. Such networks cover 20% of the land surface of the earth and have a high density, especially in urban areas. The basic principle of rainfall estimation using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated, which can be converted to average rainfall intensities over the length of a link. This is particularly interesting for those countries where few surface rainfall observations are available. A data set from a commercial microwave link network over the Netherlands is analyzed. The data set runs from January 2011 - January 2014 and consists of roughly 2,000 links covering the land surface of the Netherlands (35,500 square kilometers). From this 3-year data set country-wide rainfall maps are retrieved, which are compared to a gauge-adjusted radar data set. The ability of cellular communication networks to estimate rainfall is studied for different temporal and spatial scales (including the catchment scale). To summarize, the results further confirm the potential of these networks for rainfall monitoring for hydrological applications.

  15. 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.

  16. 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

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

    Directory of Open Access Journals (Sweden)

    C. R. Mello

    2011-12-01

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

  18. 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

  19. Stochastic modelling of daily rainfall sequences

    NARCIS (Netherlands)

    Buishand, T.A.

    1977-01-01

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

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

    Science.gov (United States)

    Burks, Jason E.; Limaye, Ashutosh

    2014-01-01

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

  1. Spatiotemporal Scaling Effect on Rainfall Network Design Using Entropy

    Directory of Open Access Journals (Sweden)

    Chiang Wei

    2014-08-01

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

  2. Seasonal prediction of summer monsoon rainfall over cluster regions of India

    Indian Academy of Sciences (India)

    S B Kakade; Ashwini Kulkarni

    2017-04-01

    Shared nearest neighbour (SNN) cluster algorithm has been applied to seasonal (June–September) rainfall departures over 30 sub-divisions of India to identify the contiguous homogeneous cluster regions over India. Five cluster regions are identified. Rainfall departure series for these cluster regions are prepared by area weighted average rainfall departures over respective sub-divisions in each cluster. The interannual and decadal variability in rainfall departures over five cluster regions is discussed. In order to consider the combined effect of North Atlantic Oscillation (NAO) and Southern Oscillation (SO), an index called effective strength index (ESI) has been defined. It has been observed that the circulation is drastically different in positive and negative phases of ESI-tendency from January to April. Hence, for each phaseof ESI-tendency (positive and negative), separate prediction models have been developed for predicting summer monsoon rainfall over identified clusters. The performance of these models have been tested and found to be encouraging.

  3. Relationships between rainfall and Combined Sewer Overflow (CSO) occurrences

    Science.gov (United States)

    Mailhot, A.; Talbot, G.; Lavallée, B.

    2015-04-01

    Combined Sewer Overflow (CSO) has been recognized as a major environmental issue in many countries. In Canada, the proposed reinforcement of the CSO frequency regulations will result in new constraints on municipal development. Municipalities will have to demonstrate that new developments do not increase CSO frequency above a reference level based on historical CSO records. Governmental agencies will also have to define a framework to assess the impact of new developments on CSO frequency and the efficiency of the various proposed measures to maintain CSO frequency at its historic level. In such a context, it is important to correctly assess the average number of days with CSO and to define relationships between CSO frequency and rainfall characteristics. This paper investigates such relationships using available CSO and rainfall datasets for Quebec. CSO records for 4285 overflow structures (OS) were analyzed. A simple model based on rainfall thresholds was developed to forecast the occurrence of CSO on a given day based on daily rainfall values. The estimated probability of days with CSO have been used to estimate the rainfall threshold value at each OS by imposing that the probability of exceeding this rainfall value for a given day be equal to the estimated probability of days with CSO. The forecast skill of this model was assessed for 3437 OS using contingency tables. The statistical significance of the forecast skill could be assessed for 64.2% of these OS. The threshold model has demonstrated significant forecast skill for 91.3% of these OS confirming that for most OS a simple threshold model can be used to assess the occurrence of CSO.

  4. Measurement and interpolation uncertainties in rainfall maps from cellular communication networks

    Science.gov (United States)

    Rios Gaona, M. F.; Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-08-01

    Accurate measurements of rainfall are important in many hydrological and meteorological applications, for instance, flash-flood early-warning systems, hydraulic structures design, irrigation, weather forecasting, and climate modelling. Whenever possible, link networks measure and store the received power of the electromagnetic signal at regular intervals. The decrease in power can be converted to rainfall intensity, and is largely due to the attenuation by raindrops along the link paths. Such an alternative technique fulfils the continuous effort to obtain 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 errors involved in link rainfall retrievals, such as wet antenna attenuation, sampling interval of measurements, wet/dry period classification, dry weather baseline attenuation, quantization of the received power, drop size distribution (DSD), and multi-path propagation; and (2) those associated with mapping, i.e. the combined effect of the interpolation methodology and the spatial density 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. Simulated link rainfall depths refer to path-averaged rainfall depths obtained from radar data. The ~ 3500 real and simulated rainfall maps were

  5. Assessment of Rainfall-induced Landslide Potential and Spatial Distribution

    Science.gov (United States)

    Chen, Yie-Ruey; Tsai, Kuang-Jung; Chen, Jing-Wen; Chiang, Jie-Lun; Hsieh, Shun-Chieh; Chue, Yung-Sheng

    2016-04-01

    , and elevation are the secondary important factors. Under the different rainfall, the greater the average of EAR, the more the landslide occurrence and area increments. The determination coefficients of trend lines on the charts of the average of EAR versus number and area of landslide increment are 0.83 and 0.92, respectively. The relations between landslide potential level, degree of land disturbance, and the ratio of number and area of landslide increment corresponding six heavy rainfall events are positive and the determination coefficients of trend lines are 0.82 and 0.72, respectively. The relation between the average of EAR and the area of landslide increment corresponding five heavy rainfall events (excluding Morakot) is positive and the determination coefficient of trend line is 0.98. Furthermore, the relation between the area increment of secondary landslide, average of EAR or the slope disturbance is positive. Under the same slope disturbance, the greater the EAR, the more the area increment of secondary landslide. Contrarily, under the same EAR, the greater the slope disturbance, the more the area increment of secondary landslide. The results of the analysis of this study can be a reference for the government for subsequent countermeasures for slope sediment disaster sensitive area to reduce the number of casualties and significantly reduce the social cost of post-disaster.

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

    Science.gov (United States)

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

    2016-04-01

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

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

    Science.gov (United States)

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

    2015-12-01

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

  8. Electric power monthly

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-08-01

    The Energy Information Administration (EIA) prepares the Electric Power Monthly (EPM) for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. This publication provides monthly statistics for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source, consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead.

  9. Electric power monthly

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Sandra R.; Johnson, Melvin; McClevey, Kenneth; Calopedis, Stephen; Bolden, Deborah

    1992-05-01

    The Electric Power Monthly is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the national, Census division, and State levels for net generation, fuel consumption, fuel stocks, quantity and quality of fuel, cost of fuel, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fuel are also displayed for the North American Electric Reliability Council (NERC) regions. Additionally, statistics by company and plant are published in the EPM on capability of new plants, new generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fuel.

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

    Science.gov (United States)

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

    2013-03-01

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

  11. Spatial variability and rainfall characteristics of Kerala

    Indian Academy of Sciences (India)

    Anu Simon; K Mohankumar

    2004-06-01

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

  12. Modeling and Prediction of Monthly Total Ozone Concentrations by Use of an Artificial Neural Network Based on Principal Component Analysis

    Science.gov (United States)

    Chattopadhyay, Surajit; Chattopadhyay, Goutami

    2012-10-01

    In the work discussed in this paper we considered total ozone time series over Kolkata (22°34'10.92″N, 88°22'10.92″E), an urban area in eastern India. Using cloud cover, average temperature, and rainfall as the predictors, we developed an artificial neural network, in the form of a multilayer perceptron with sigmoid non-linearity, for prediction of monthly total ozone concentrations from values of the predictors in previous months. We also estimated total ozone from values of the predictors in the same month. Before development of the neural network model we removed multicollinearity by means of principal component analysis. On the basis of the variables extracted by principal component analysis, we developed three artificial neural network models. By rigorous statistical assessment it was found that cloud cover and rainfall can act as good predictors for monthly total ozone when they are considered as the set of input variables for the neural network model constructed in the form of a multilayer perceptron. In general, the artificial neural network has good potential for predicting and estimating monthly total ozone on the basis of the meteorological predictors. It was further observed that during pre-monsoon and winter seasons, the proposed models perform better than during and after the monsoon.

  13. 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.

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

    Directory of Open Access Journals (Sweden)

    Tyas Mutiara Basuki

    2004-01-01

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

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

    Indian Academy of Sciences (India)

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

    2015-08-01

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

  17. 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.

  18. [Monitoring and analysis on evolution process of rainfall runoff water quality in urban area].

    Science.gov (United States)

    Dong, Wen; Li, Huai-En; Li, Jia-Ke

    2013-02-01

    In order to find the water quality evolution law and pollution characteristics of the rainfall runoff from undisturbed to the neighborhood exit, 6 times evolution process of rainfall runoff water quality were monitored and analyzed from July to October in 2011, and contrasted the clarification efficiency of the grassland to the roof runoff rudimentarily at the same time. The research showed: 1. the results of the comparison from "undisturbed, rainfall-roof, rainfall runoff-road, rainfall-runoff the neighborhood exit runoff " showed that the water quality of the undisturbed rain was better than that from the roof and the neighborhood exist, but the road rainfall runoff water quality was the worst; 2. the average concentrations of the parameters such as COD, ammonia nitrogen and total nitrogen all exceeded the Fifth Class of the Surface Water Quality Standard except for the soluble total phosphorus from undisturbed rainfall to the neighborhood exit; 3. the runoff water quality of the short early fine days was better than that of long early fine days, and the last runoff water quality was better than that of the initial runoff in the same rainfall process; 4. the concentration reduction of the grassland was notable, and the reduction rate of the grassland which is 1.0 meter wide of the roof runoff pollutants such as COD and nitrogen reached 30%.

  19. NUMERICAL SIMULATION OF ATOMIZATION RAINFALL AND THE GENERATED FLOW ON A SLOPE

    Institute of Scientific and Technical Information of China (English)

    LIU Shi-he; TAI Wei; FAN Min; LUO Qiu-shi

    2012-01-01

    This article studies the atomization rainfall and the generated flow on a slope by numerical simulations.The atomization rainfall is simulated by a unified model for splash droplets and a suspended mist,and the distribution of the diameter of splash rain drops is analyzed.The slope runoff generated by the atomization rainfall is simulated by a depth-averaged 2-D model,and the localization of the rainfall intensity in space is specially considered.The simulation results show that:(1) the median rain size of the atomization rainfall increases in the longitudinal direction at first,then monotonously decreases,and the maximum value is taken at the longitudinal position not in consistent with the position where the maximum rain intensity is taken.In the lateral direction the median rain size monotonously decreases,(2) since the atomization rainfall is distributed in a strongly localized area,it takes a longer time for its runoff yield to reach a steady state than that in the natural rainfall,the variation ranges of the water depth and the velocity in the longitudinal and lateral directions are larger than those in the natural rainfall.

  20. The evaluation of rainfall influence on combined sewer overflows characteristics: the Berlin case study.

    Science.gov (United States)

    Sandoval, S; Torres, A; Pawlowsky-Reusing, E; Riechel, M; Caradot, N

    2013-01-01

    The present study aims to explore the relationship between rainfall variables and water quality/quantity characteristics of combined sewer overflows (CSOs), by the use of multivariate statistical methods and online measurements at a principal CSO outlet in Berlin (Germany). Canonical correlation results showed that the maximum and average rainfall intensities are the most influential variables to describe CSO water quantity and pollutant loads whereas the duration of the rainfall event and the rain depth seem to be the most influential variables to describe CSO pollutant concentrations. The analysis of partial least squares (PLS) regression models confirms the findings of the canonical correlation and highlights three main influences of rainfall on CSO characteristics: (i) CSO water quantity characteristics are mainly influenced by the maximal rainfall intensities, (ii) CSO pollutant concentrations were found to be mostly associated with duration of the rainfall and (iii) pollutant loads seemed to be principally influenced by dry weather duration before the rainfall event. The prediction quality of PLS models is rather low (R² < 0.6) but results can be useful to explore qualitatively the influence of rainfall on CSO characteristics.

  1. Sampling error study for rainfall estimate by satellite using a stochastic model

    Science.gov (United States)

    Shin, Kyung-Sup; North, Gerald R.

    1988-01-01

    In a parameter study of satellite orbits, sampling errors of area-time averaged rain rate due to temporal sampling by satellites were estimated. The sampling characteristics were studied by accounting for the varying visiting intervals and varying fractions of averaging area on each visit as a function of the latitude of the grid box for a range of satellite orbital parameters. The sampling errors were estimated by a simple model based on the first-order Markov process of the time series of area averaged rain rates. For a satellite of nominal Tropical Rainfall Measuring Mission (Thiele, 1987) carrying an ideal scanning microwave radiometer for precipitation measurements, it is found that sampling error would be about 8 to 12 pct of estimated monthly mean rates over a grid box of 5 X 5 degrees. It is suggested that an observation system based on a low inclination satellite combined with a sunsynchronous satellite simultaneously might be the best candidate for making precipitation measurements from space.

  2. Rainfall measurement from opportunistic use of earth-space link in Ku Band

    Directory of Open Access Journals (Sweden)

    L. Barthès

    2013-02-01

    Full Text Available The present study deals with the development of a low cost microwave device devoted to measure average rain rate observed along earth – satellite links. The principle is to use rain atmospheric attenuation along Earth – space links in Ku-band to deduce the path averaged rain rate. These links are characterized by a path length of a few km through the troposphere. Ground based power measurements are carried out by receiving TV channels from different geostationary satellites in Ku-band.

    The major difficulty in this study is to retrieve rain characteristics among many fluctuations of the received signal which are due to atmospheric scintillations, changes in the composition of the atmosphere (water vapour concentration, cloud water content or satellite features (variation of the emitted power, satellite motions. In order to perform a feasibility study of such a device, a measurement campaign has been performed for five months near Paris. This paper proposes an algorithm based on an artificial neural network to identify drought and rainy periods and to suppress the variability of the received signal due to no-rain effects. Taking into account the height of the rain layer, rain attenuation is then inverted to obtain path averaged rain rate. Obtained rainfall rates are compared with co-located rain gauges and radar measurements on the whole experiment period, then the most significant rainy events are analyzed.

  3. A rainfall simulator based on multifractal generator

    Science.gov (United States)

    Akrour, Nawal; mallet, Cecile; barthes, Laurent; chazottes, Aymeric

    2015-04-01

    The Precipitations are due to complex meteorological phenomenon's and unlike other geophysical constituents such as water vapour concentration they present a relaxation behaviour leading to an alternation of dry and wet periods. Thus, precipitations can be described as intermittent process. The spatial and temporal variability of this phenomenon is significant and covers large scales. This high variability can cause extreme events which are difficult to observe properly because of their suddenness and their localized character. For all these reasons, the precipitations are therefore difficult to model. This study aims to adapt a one-dimensional time series model previously developed by the authors [Akrour et al., 2013, 2014] to a two-dimensional rainfall generator. The original time series model can be divided into 3 major steps : rain support generation, intra event rain rates generation using multifractal and finally calibration process. We use the same kind of methodology in the present study. Based on dataset obtained from meteorological radar of Météo France with a spatial resolution of 1 km x 1 km we present the used approach : Firstly, the extraction of rain support (rain/no rain area) allowing the retrieval of the rain support structure function (variogram) and fractal properties. This leads us to use either the rain support modelisation proposed by ScleissXXX [ref] or directly real rain support extracted from radar rain maps. Then, the generation (over rain areas) of rain rates is made thanks to a 2D multifractal Fractionnally Integrated Flux (FIF) model [ref]. This second stage is followed by a calibration/forcing step (forcing average rain rate per events) added in order to provide rain rate coherent with observed rain-rate distribution. The forcing process is based on a relation identified from the average rain rate of observed events and their surfaces. The presentation will first explain the different steps presented above, then some results

  4. Interpolation of daily rainfall using spatiotemporal models and clustering

    KAUST Repository

    Militino, A. F.

    2014-06-11

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

  5. Effects of Rainfall on Water Quality of Aquaculture along the Coastal Areas of Jiangsu Province and Countermeasures

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    [Objective] The study aimed to decrease the effects of rainfall on water quality of aquaculture along the coastal areas of Jiangsu Province and improve the yield and quality of aquatic products.[Method] We firstly designed the methods to calculate average pH of different rainfalls,total precipitation,as well as the changes of pH and salinity in the studied pond and coastal culture zone,then analyzed the dynamic variation of precipitation,pH and salinity caused by rainfall to discuss the effects of rainfall ...

  6. Generalized linear model for estimation of missing daily rainfall data

    Science.gov (United States)

    Rahman, Nurul Aishah; Deni, Sayang Mohd; Ramli, Norazan Mohamed

    2017-04-01

    The analysis of rainfall data with no missingness is vital in various applications including climatological, hydrological and meteorological study. The issue of missing data is a serious concern since it could introduce bias and lead to misleading conclusions. In this study, five imputation methods including simple arithmetic average, normal ratio method, inverse distance weighting method, correlation coefficient weighting method and geographical coordinate were used to estimate the missing data. However, these imputation methods ignored the seasonality in rainfall dataset which could give more reliable estimation. Thus this study is aimed to estimate the missingness in daily rainfall data by using generalized linear model with gamma and Fourier series as the link function and smoothing technique, respectively. Forty years daily rainfall data for the period from 1975 until 2014 which consists of seven stations at Kelantan region were selected for the analysis. The findings indicated that the imputation methods could provide more accurate estimation values based on the least mean absolute error, root mean squared error and coefficient of variation root mean squared error when seasonality in the dataset are considered.

  7. Effects of Spatial Heterogeneity in Rainfall and Vegetation Type on Soil Moisture and Evapotranspiration

    CERN Document Server

    Puma, Michael J; Rodriguez-Iturbe, Ignacio; Nordbotten, Jan M; Guswa, Andrew J; Kavetski, Dmitri

    2016-01-01

    Nonlinear plant-scale interactions controlling the soil-water balance are generally not valid at larger spatial scales due to spatial heterogeneity in rainfall and vegetation type. The relationships between spatially averaged variables are hysteretic even when unique relationships are imposed at the plant scale. The characteristics of these hysteretic relationships depend on the size of the averaging area and the spatial properties of the soil, vegetation, and rainfall. We upscale the plant-scale relationships to the scale of a regional land-surface model based on simulation data obtained through explicit representation of spatial heterogeneity in rainfall and vegetation type. The proposed upscaled function improves predictions of spatially averaged soil moisture and evapotranspiration relative to the effective-parameter approach for a water-limited Texas shrubland. The degree of improvement is a function of the scales of heterogeneity and the size of the averaging area. We also find that single-valued functi...

  8. A TRMM Rainfall Estimation Method Applicable to Land Areas

    Science.gov (United States)

    Prabhakara, C.; Iacovazzi, R.; Weinman, J.; Dalu, G.

    1999-01-01

    . Based on this observation, in this study we have developed a method to estimate the mesoscale-average rain rate over land utilizing microwave radiometer data. Because of the high degree of geographic and seasonal variability in the nature and intensity of rain, this method requires some tuning with 15-minute rain gauge data on land. After tuning the method, it can be applied to an independent set of rain events that are close in time and space. We find that the mesoscale rain rates retrieved over the period of a month on land with this method shows a correlation of about 0.85 with respect to the surface rain-gauge observations. This mesoscale-average rain rate estimation method can be useful to extend the spatial and temporal coverage of the rainfall data provided by the Precipitation Radar on board the Tropical Rainfall Measuring Mission (TRMM) satellite.

  9. Towards operational rainfall monitoring with microwave links from cellular telecommunication networks

    Science.gov (United States)

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2017-04-01

    The basic principle of rainfall estimation using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated, which can be converted to average rainfall intensities over the length of a link. Microwave links from cellular communication networks have been proposed as a promising new rainfall measurement technique since one decade. They are particularly interesting for those countries where few surface rainfall observations are available. Yet too date no operational (real-time) link-based rainfall products are available. To advance the process towards operational application and upscaling of this technique, long time series should be analyzed for different networks and climates. Here the potential for long-term large-scale operational rainfall monitoring is demonstrated by utilizing a 2.5-year data set from a cellular communication network. The data set consists of roughly 2,000 links covering the land surface of the Netherlands (35,500 square kilometers). The quality of link rainfall maps is thoroughly quantified by an extensive validation against independent gauge-adjusted radar rainfall maps for, among others, different seasons and extremes. One of the goals is to quantify whether the cellular telecommunication network can yield rainfall maps of comparable quality as those based on automatic rain gauge data (with a density of 1 gauge per 1000 square kilometers). Developing countries will usually have rain gauge networks with a lower density (and little or no weather radars). This helps to assess the possibly added value of link-based rainfall estimates with respect to those from existing rain gauge networks. Moreover, this shows the possibly added value of link rainfall estimates for adjustment of radar rainfall images. The results further confirm

  10. First flush characteristics of rainfall runoff from a paddy field in the Taihu Lake watershed, China.

    Science.gov (United States)

    Li, Songmin; Wang, Xiaoling; Qiao, Bin; Li, Jiansheng; Tu, Jiamin

    2017-02-06

    follow a similar trend as runoff changes, NO3(-)-N concentration is lower in the early part of runoff and higher in the later, and TP mainly occurs in the particle state in storm runoff and mainly in the dissolved state when the rainfall intensity is smaller. Nitrogen and phosphorus losses from paddy fields are closely related to the average rainfall intensity and the max rainfall intensity, and the runoff loss of nitrogen and phosphorus is more severe when the rainfall intensity is large. Based on an analysis of multiple methodologies, TN and NH4(+)-N show a certain degree of a first flush effect, whereas the first flush effect of TP is not obvious. The first flush effect of SS is obvious in larger intensity rainfall and shows a slight secondary flush effect in smaller rainfall events.

  11. Prediction of rainfall intensity measurement errors using commercial microwave communication links

    Directory of Open Access Journals (Sweden)

    A. Zinevich

    2010-10-01

    Full Text Available Commercial microwave radio links forming cellular communication networks are known to be a valuable instrument for measuring near-surface rainfall. However, operational communication links are more uncertain relatively to the dedicated installations since their geometry and frequencies are optimized for high communication performance rather than observing rainfall. Quantification of the uncertainties for measurements that are non-optimal in the first place is essential to assure usability of the data.

    In this work we address modeling of instrumental impairments, i.e. signal variability due to antenna wetting, baseline attenuation uncertainty and digital quantization, as well as environmental ones, i.e. variability of drop size distribution along a link affecting accuracy of path-averaged rainfall measurement and spatial variability of rainfall in the link's neighborhood affecting the accuracy of rainfall estimation out of the link path. Expressions for root mean squared error (RMSE for estimates of path-averaged and point rainfall have been derived. To verify the RMSE expressions quantitatively, path-averaged measurements from 21 operational communication links in 12 different locations have been compared to records of five nearby rain gauges over three rainstorm events.

    The experiments show that the prediction accuracy is above 90% for temporal accumulation less than 30 min and lowers for longer accumulation intervals. Spatial variability in the vicinity of the link, baseline attenuation uncertainty and, possibly, suboptimality of wet antenna attenuation model are the major sources of link-gauge discrepancies. In addition, the dependence of the optimal coefficients of a conventional wet antenna attenuation model on spatial rainfall variability and, accordingly, link length has been shown.

    The expressions for RMSE of the path-averaged rainfall estimates can be useful for integration of measurements from multiple

  12. The rainfall erosivity factor in the Czech Republic and its uncertainty

    Science.gov (United States)

    Hanel, Martin; Máca, Petr; Bašta, Petr; Vlnas, Radek; Pech, Pavel

    2016-10-01

    In the present paper, the rainfall erosivity factor (R factor) for the area of the Czech Republic is assessed. Based on 10 min data for 96 stations and corresponding R factor estimates, a number of spatial interpolation methods are applied and cross-validated. These methods include inverse distance weighting, standard, ordinary, and regression kriging with parameters estimated by the method of moments and restricted maximum likelihood, and a generalized least-squares (GLS) model. For the regression-based methods, various statistics of monthly precipitation as well as geographical indices are considered as covariates. In addition to the uncertainty originating from spatial interpolation, the uncertainty due to estimation of the rainfall kinetic energy (needed for calculation of the R factor) as well as the effect of record length and spatial coverage are also addressed. Finally, the contribution of each source of uncertainty is quantified. The average R factor for the area of the Czech Republic is 640 MJ ha-1 mm h-1, with values for the individual stations ranging between 320 and 1520 MJ ha-1 mm h-1. Among various spatial interpolation methods, the GLS model relating the R factor to the altitude, longitude, mean precipitation, and mean fraction of precipitation above the 95th percentile of monthly precipitation performed best. Application of the GLS model also reduced the uncertainty due to the record length, which is substantial when the R factor is estimated for individual sites. Our results revealed that reasonable estimates of the R factor can be obtained even from relatively short records (15-20 years), provided sufficient spatial coverage and covariates are available.

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

    Directory of Open Access Journals (Sweden)

    Xianghu Li

    2013-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Jonathan Borwein

    2014-02-01

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

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

    Science.gov (United States)

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

    1989-01-01

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

  16. 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

  17. Incidence of Dengue Hemorrhagic Fever Related to Annual Rainfall, Population Density, Larval Free Index and Prevention Program in Bandung 2008 to 2011

    Directory of Open Access Journals (Sweden)

    Anggia Karina

    2015-06-01

    Full Text Available Background: Dengue Hemorrhagic Fever (DHF remains one of health problems in all provinces in Indonesia including West Java. Bandung as the capital of West Java province has dengue prevalence that is above the average prevalence of all provinces. This study aimed to describe the pattern of dengue incidence rate, annual rainfall, population density, and larval free index as well as the implementation of prevention program in sub-districts with the highest incidence rate in Bandung between 2008 and 2011. Methods: A descriptive retrospective study was conducted in September 2012 using secondary data during the period of January 2008 to December 2011. The incidence rate was calculated based on DHF patients who live in Bandung. Data were analyzed using computer and Arc View 3.3. Pattern of incidence rate was characterized with red, yellow, and green region respectively. Results: The highest incidence rate of DHF occurred in 2009. Incidence increased in January to February and declined in the end of the year. Subdistricts with highest incidence had no highest annual rainfall and the population density below the average of population density in Bandung. The highest implementation of fogging program was not only performed in high incidence subdistricts but also in area with larval free index less than 95%. Larval free index in subdistricts with highest incidence were not all below 95%. Conclusions: Incidence of DHF increases after months of highly rainfall. The pattern of incidence rate in all subdistrict is dynamic and suspected do not related to annual rainfall, population density, high larva free index, and frequency of fogging.

  18. Ensemble flood simulation for a small dam catchment in Japan using 10 and 2 km resolution nonhydrostatic model rainfalls

    Science.gov (United States)

    Kobayashi, Kenichiro; Otsuka, Shigenori; Apip; Saito, Kazuo

    2016-08-01

    This paper presents a study on short-term ensemble flood forecasting specifically for small dam catchments in Japan. Numerical ensemble simulations of rainfall from the Japan Meteorological Agency nonhydrostatic model (JMA-NHM) are used as the input data to a rainfall-runoff model for predicting river discharge into a dam. The ensemble weather simulations use a conventional 10 km and a high-resolution 2 km spatial resolutions. A distributed rainfall-runoff model is constructed for the Kasahori dam catchment (approx. 70 km2) and applied with the ensemble rainfalls. The results show that the hourly maximum and cumulative catchment-average rainfalls of the 2 km resolution JMA-NHM ensemble simulation are more appropriate than the 10 km resolution rainfalls. All the simulated inflows based on the 2 and 10 km rainfalls become larger than the flood discharge of 140 m3 s-1, a threshold value for flood control. The inflows with the 10 km resolution ensemble rainfall are all considerably smaller than the observations, while at least one simulated discharge out of 11 ensemble members with the 2 km resolution rainfalls reproduces the first peak of the inflow at the Kasahori dam with similar amplitude to observations, although there are spatiotemporal lags between simulation and observation. To take positional lags into account of the ensemble discharge simulation, the rainfall distribution in each ensemble member is shifted so that the catchment-averaged cumulative rainfall of the Kasahori dam maximizes. The runoff simulation with the position-shifted rainfalls shows much better results than the original ensemble discharge simulations.

  19. Updating Rainfall Erosivity Map of the Mediterranean Region in Turkey by RUSLE-R and GIS

    Science.gov (United States)

    Topcu, P.; Deviren Saygin, S.; Erpul, G.; Bayramin, I.

    2009-04-01

    To understand and analyze rainfall variability is a need for evaluating the erosive potential of rainfall in terms of space and time. In this study of revising rainfall erosivity index by RUSLE-R equation and recent data set, we focus in particular on the semi-arid areas of the Mediterranean Region, Turkey, where soil erosion is one of the major threats to soil and water resources and where soil erosion is as acute as or more severe than those in other Mediterranean countries. The primary data set included electronically stored daily rainfall records of the Turkish State Meteorological Service for the years from 1993 to 2004 at the 38 climate stations located in the Mediterranean Region. After analyzing the time-depth records of each independent erosive rainfall, RUSLE-R was calculated as the product of average rainfall energy and a 30-min maximum intensity of rainfall. Point RUSLE-R values as long-term averages obtained for each climate station were interpolated using tri-variate functions of longitude, latitude, and elevation to have a map. Summarily, by integrating Digital Elevation Model (DEM) of the region and Geographic Information Systems (GIS), the rainfall erosivity map of the Mediterranean Region in Turkey was updated. Doubtlessly, this study would provide data not only for climate studies but also opportunities for integration of climate data with properties of soil, topography and land use to understand complicated hydrologic processes at watershed and regional scales and would be effectively employed to take soil and water conservation measures. Key words: rainfall erosivity index, RUSLE prediction technology, soil erosion, GIS. Acknowledgement Authors gratefully acknowledge "The Scientific and Technological Research Council of Turkey", TUBITAK, for support within project of CAYDAG-107Y155.

  20. Physical Theories with Average Symmetry

    OpenAIRE

    Alamino, Roberto C.

    2013-01-01

    This Letter probes the existence of physical laws invariant only in average when subjected to some transformation. The concept of a symmetry transformation is broadened to include corruption by random noise and average symmetry is introduced by considering functions which are invariant only in average under these transformations. It is then shown that actions with average symmetry obey a modified version of Noether's Theorem with dissipative currents. The relation of this with possible violat...

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

    Science.gov (United States)

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

    2010-05-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-10-15

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

  3. A space-time hybrid hourly rainfall model for derived flood frequency analysis

    Directory of Open Access Journals (Sweden)

    U. Haberlandt

    2008-12-01

    Full Text Available For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series.

    First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in

  4. Average Convexity in Communication Situations

    NARCIS (Netherlands)

    Slikker, M.

    1998-01-01

    In this paper we study inheritance properties of average convexity in communication situations. We show that the underlying graph ensures that the graphrestricted game originating from an average convex game is average convex if and only if every subgraph associated with a component of the underlyin

  5. The onset and cessation of seasonal rainfall over Africa

    Science.gov (United States)

    Dunning, Caroline M.; Black, Emily C. L.; Allan, Richard P.

    2016-10-01

    Variation in the seasonal cycle of African rainfall is of key importance for agriculture. Here an objective method of determining the timing of onset and cessation is, for the first time, extended to the whole of Africa. The method is applied to five observational data sets and the ERA-Interim reanalysis. Compatibility with known physical drivers of African rainfall, consistency with indigenous methods, and generally strong agreement between satellite-based rainfall data sets confirm that the method is capturing the correct seasonal progression of African rainfall. The biannual rainfall regime is correctly identified over the coastal region of Ghana and the Ivory Coast. However, the ERA-Interim reanalysis exhibits timing biases over areas with two rainy seasons, and both ERA-Interim and the ARCv2 observational data set exhibit some inconsistent deviations over West Africa. The method can be used to analyze both seasonal-interannual variability and long-term change. Over East Africa, we find that failure of the rains and subsequent humanitarian disaster is associated with shorter as well as weaker rainy seasons, e.g., on average the long rains were 11 days shorter in 2011. Cessation of the short rains over this region is 7 days later in El Niño and 5 days earlier in La Niña years with only a small change in onset date. The methodology described in this paper is applicable to multiple data sets and to large regions, including those that experience multiple rainy seasons. As such, it provides a means for investigating variability and change in the seasonal cycle over the whole of Africa.

  6. Satellite-derived estimates of forest leaf area index in southwest Western Australia are not tightly coupled to interannual variations in rainfall: implications for groundwater decline in a drying climate.

    Science.gov (United States)

    Smettem, Keith R J; Waring, Richard H; Callow, John N; Wilson, Melissa; Mu, Qiaozhen

    2013-08-01

    There is increasing concern that widespread forest decline could occur in regions of the world where droughts are predicted to increase in frequency and severity as a result of climate change. The average annual leaf area index (LAI) is an indicator of canopy cover and the difference between the annual maximum and minimum LAI is an indicator of annual leaf turnover. In this study, we analyzed satellite-derived estimates of monthly LAI across forested coastal catchments of southwest Western Australia over a 12 year period (2000-2011) that included the driest year on record for the last 60 years. We observed that over the 12 year study period, the spatial pattern of average annual satellite-derived LAI values was linearly related to mean annual rainfall. However, interannual changes to LAI in response to changes in annual rainfall were far less than expected from the long-term LAI-rainfall trend. This buffered response was investigated using a physiological growth model and attributed to availability of deep soil moisture and/or groundwater storage. The maintenance of high LAIs may be linked to a long-term decline in areal average underground water storage and diminished summer flows, with an emerging trend toward more ephemeral flow regimes.

  7. Urban rainfall estimation employing commercial microwave links

    Science.gov (United States)

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

    2015-04-01

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

  8. 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

  9. On the sensitivity of urban hydrodynamic modelling to rainfall spatial and temporal resolution

    Directory of Open Access Journals (Sweden)

    G. Bruni

    2014-06-01

    Full Text Available Cities are increasingly vulnerable to floods generated by intense rainfall, because of their high degree of imperviousness, implementation of infrastructures, and changes in precipitation patterns due to climate change. Accurate information of convective storm characteristics at high spatial and temporal resolution is a crucial input for urban hydrological models to be able to simulate fast runoff processes and enhance flood prediction. In this paper, a detailed study of the sensitivity of urban hydrological response to high resolution radar rainfall was conducted. Rainfall rates derived from X-band dual polarimetric weather radar for four rainstorms were used as input into a detailed hydrodynamic sewer model for an urban catchment in Rotterdam, the Netherlands. Dimensionless parameters were derived to compare results between different storm conditions and to describe the effect of rainfall spatial resolution in relation to storm and hydrodynamic model properties: rainfall sampling number (rainfall resolution vs. storm size, catchment sampling number (rainfall resolution vs. catchment size, runoff and sewer sampling number (rainfall resolution vs. runoff and sewer model resolution respectively. Results show catchment smearing effect for rainfall resolution approaching half the catchment size, i.e. for catchments sampling numbers greater than 0.5 averaged rainfall volumes decrease about 20%. Moreover, deviations in maximum water depths, form 10 to 30% depending on the storm, occur for rainfall resolution close to storm size, describing storm smearing effect due to rainfall coarsening. Model results also show the sensitivity of modelled runoff peaks and maximum water depths to the resolution of the runoff areas and sewer density respectively. Sensitivity to temporal resolution of rainfall input seems low compared to spatial resolution, for the storms analysed in this study. Findings are in agreement with previous studies on natural catchments

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

    Science.gov (United States)

    Dikgola, Kobamelo; Mazvimavi, Dominic

    2013-04-01

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

  11. Sampling Based Average Classifier Fusion

    Directory of Open Access Journals (Sweden)

    Jian Hou

    2014-01-01

    fusion algorithms have been proposed in literature, average fusion is almost always selected as the baseline for comparison. Little is done on exploring the potential of average fusion and proposing a better baseline. In this paper we empirically investigate the behavior of soft labels and classifiers in average fusion. As a result, we find that; by proper sampling of soft labels and classifiers, the average fusion performance can be evidently improved. This result presents sampling based average fusion as a better baseline; that is, a newly proposed classifier fusion algorithm should at least perform better than this baseline in order to demonstrate its effectiveness.

  12. Gauge-adjusted rainfall estimates from commercial microwave links

    Science.gov (United States)

    Fencl, Martin; Dohnal, Michal; Rieckermann, Jörg; Bareš, Vojtěch

    2017-01-01

    monitoring system. Unfortunately, adjusting CML observations to RGs with longer aggregation intervals of up to 24 h has drawbacks. Although it substantially reduces bias, it unfavourably smoothes out rainfall peaks of high intensities, which is undesirable for stormwater management. A similar, but less severe, effect occurs due to spatial averaging when CMLs are adjusted to remote RGs. Nevertheless, even here, adjusted CMLs perform better than RGs alone. Furthermore, we provide first evidence that the joint use of multiple CMLs together with RGs also reduces bias in their QPEs. In summary, we believe that our adjustment method has great potential to improve the space-time resolution of current urban rainfall monitoring networks. Nevertheless, future work should aim to better understand the reason for the observed systematic error in QPEs from CMLs.

  13. Evaluation of the impacts of the Madden-Julian Oscillation on rainfall and hurricanes in Central and South America and the Atlantic Ocean using ICI-RAFT

    Science.gov (United States)

    Giovannettone, J. P.

    2013-12-01

    Based on the method of Regional Frequency Analysis (RFA) and L-moments (Hosking & Wallis, 1997), a tool was developed to estimate the frequency/intensity of a rainfall event of a particular duration using ground-based rainfall observations. Some of the code used to develop this tool was taken from the FORTRAN code provided by Hosking & Wallis and rewritten in Visual Basic 2010. This tool was developed at the International Center for Integrated Water Resources Management (ICIWaRM) and is referred to as the ICIWaRM Regional Analysis of Frequency Tool (ICI-RAFT) (Giovannettone & Wright, 2012). In order to study the effectiveness of ICI-RAFT, three case studies were selected for the analysis. The studies take place in selected regions within Argentina, Nicaragua, and Venezuela. Rainfall data were provided at locations throughout each country; total rainfall for specific periods were computed and analyzed with respect to several global climate indices using lag times ranging from 1 to 6 months. Each analysis attempts to identify a global climate index capable of predicting above or below average rainfall several months in advance, qualitatively and using an equation that is developed. The index that had the greatest impact was the MJO (Madden-Julian Oscillation), which is the focus of the current study. The MJO is considered the largest element of intra-seasonal (30 - 90 days) variability in the tropical atmosphere and, unlike other indices, is characterized by the eastward propagation of large areas of convective anomalies near the equator, propagating from the Indian Ocean east into the Pacific Ocean. The anomalies are monitored globally using ten different indices located on lines of longitude near the equator, with seven in the eastern hemisphere and three in the western hemisphere. It has been found in previous studies that the MJO is linked to summer rainfall in Southeast China (Zhang et al., 2009) and southern Africa (Pohl et al., 2007) and to rainfall patterns

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

    Institute of Scientific and Technical Information of China (English)

    John ABBOT; Jennifer MAROHASY

    2012-01-01

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

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

    Science.gov (United States)

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

    2015-12-01

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

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

    Directory of Open Access Journals (Sweden)

    D. Panagoulia

    2006-01-01

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

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

    Directory of Open Access Journals (Sweden)

    R. J. Nurmohamed

    2006-01-01

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

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

    Science.gov (United States)

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

    2017-04-01

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

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

    Indian Academy of Sciences (India)

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

    2016-03-01

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

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

    Directory of Open Access Journals (Sweden)

    OANA MOIGRĂDEAN

    2013-04-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2009-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

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

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

    Indian Academy of Sciences (India)

    B Venkatesh; Mathew K Jose

    2007-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Nur Hishaam Sulaiman

    2017-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    JOSHI Varun; KUMAR Kireet

    2006-01-01

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

  6. Exploratory analysis of rainfall events in Coimbra, Portugal: variability of raindrop characteristics

    Science.gov (United States)

    Carvalho, S. C. P.; de Lima, M. I. P.; de Lima, J. L. M. P.

    2012-04-01

    Laser disdrometers can monitor efficiently rainfall characteristics at small temporal scales, providing data on rain intensity, raindrop diameter and fall speed, and raindrop counts over time. This type of data allows for the increased understanding of the rainfall structure at small time scales. Of particular interest for many hydrological applications is the characterization of the properties of extreme events, including the intra-event variability, which are affected by different factors (e.g. geographical location, rainfall generating mechanisms). These properties depend on the microphysical, dynamical and kinetic processes that interact to produce rain. In this study we explore rainfall data obtained during two years with a laser disdrometer installed in the city of Coimbra, in the centre region of mainland Portugal. The equipment was developed by Thies Clima. The data temporal resolution is one-minute. Descriptive statistics of time series of raindrop diameter (D), fall speed, kinetic energy, and rain rate were studied at the event scale; for different variables, the average, maximum, minimum, median, variance, standard deviation, quartile, coefficient of variation, skewness and kurtosis were determined. The empirical raindrop size distribution, N(D), was also calculated. Additionally, the parameterization of rainfall was attempted by investigating the applicability of different theoretical statistical distributions to fit the empirical data (e.g. exponential, gamma and lognormal distributions). As expected, preliminary results show that rainfall properties and structure vary with rainfall type and weather conditions over the year. Although only two years were investigated, already some insight into different rain events' structure was obtained.

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

    Science.gov (United States)

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

    2013-05-01

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

  8. Rainfall Intra-Seasonal Variability and Vegetation Growth in the Ferlo Basin (Senegal

    Directory of Open Access Journals (Sweden)

    Soukèye Cissé

    2016-01-01

    Full Text Available During the monsoon season, the spatiotemporal variability of rainfall impacts the growth of vegetation in the Sahel. This study evaluates this effect for the Ferlo basin in central northern Senegal. Relationships between rainfall, soil moisture (SM, and vegetation are assessed using remote sensing data (TRMM3B42 and RFE 2.0 for rainfall, ESA-CCI.SM for soil moisture and MODIS Leaf Area Index (LAI. The principal objective was to analyze the response of vegetation growth to water availability during the rainy season using statistical criteria at the scale of homogeneous vegetation-soil zones. The study covers the period from June to September for the years 2000 to 2010. The surface SM is well correlated with both rainfall products. On ferruginous soils, better correlation of intra-seasonal variations and stronger sensitivity of the vegetation to rainfall are found compared to lithosols soils. LAI responds, on average, two to three weeks after a rainfall anomaly. Moreover, dry spells (negative anomalies of seven days’ length (three days for SM anomaly significantly affect vegetation growth (maximum LAI within the season. A strong and significant link is also found between total precipitation and the number of dry spells. These datasets proved to be sufficiently reliable to assess the impacts of rainfall variability on vegetation dynamics.

  9. Homogeneous clusters over India using probability density function of daily rainfall

    Science.gov (United States)

    Kulkarni, Ashwini

    2017-07-01

    The Indian landmass has been divided into homogeneous clusters by applying the cluster analysis to the probability density function of a century-long time series of daily summer monsoon (June through September) rainfall at 357 grids over India, each of approximately 100 km × 100 km. The analysis gives five clusters over Indian landmass; only cluster 5 happened to be the contiguous region and all other clusters are dispersed away which confirms the erratic behavior of daily rainfall over India. The area averaged seasonal rainfall over cluster 5 has a very strong relationship with Indian summer monsoon rainfall; also, the rainfall variability over this region is modulated by the most important mode of climate system, i.e., El Nino Southern Oscillation (ENSO). This cluster could be considered as the representative of the entire Indian landmass to examine monsoon variability. The two-sample Kolmogorov-Smirnov test supports that the cumulative distribution functions of daily rainfall over cluster 5 and India as a whole do not differ significantly. The clustering algorithm is also applied to two time epochs 1901-1975 and 1976-2010 to examine the possible changes in clusters in a recent warming period. The clusters are drastically different in two time periods. They are more dispersed in recent period implying the more erroneous distribution of daily rainfall in recent period.

  10. 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.

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

    CSIR Research Space (South Africa)

    Engelbrecht, CJ

    2012-09-01

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

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

    Science.gov (United States)

    Wu, Renguang; Jiao, Yang

    2017-05-01

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

  13. Benchmarking monthly homogenization algorithms

    Directory of Open Access Journals (Sweden)

    V. K. C. Venema

    2011-08-01

    Full Text Available The COST (European Cooperation in Science and Technology Action ES0601: Advances in homogenization methods of climate series: an integrated approach (HOME has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies and because they represent two important types of statistics (additive and multiplicative. The algorithms were validated against a realistic benchmark dataset. The benchmark contains real inhomogeneous data as well as simulated data with inserted inhomogeneities. Random break-type inhomogeneities were added to the simulated datasets modeled as a Poisson process with normally distributed breakpoint sizes. To approximate real world conditions, breaks were introduced that occur simultaneously in multiple station series within a simulated network of station data. The simulated time series also contained outliers, missing data periods and local station trends. Further, a stochastic nonlinear global (network-wide trend was added.

    Participants provided 25 separate homogenized contributions as part of the blind study as well as 22 additional solutions submitted after the details of the imposed inhomogeneities were revealed. These homogenized datasets were assessed by a number of performance metrics including (i the centered root mean square error relative to the true homogeneous value at various averaging scales, (ii the error in linear trend estimates and (iii traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Contingency scores by themselves are not very informative. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve

  14. 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.

  15. A space-time stochastic model of rainfall for satellite remote-sensing studies

    Science.gov (United States)

    Bell, Thomas L.

    1987-01-01

    A model of the spatial and temporal distribution of rainfall is described that produces random spatial rainfall patterns with these characteristics: (1) the model is defined on a grid with each grid point representing the average rain rate over the surrounding grid box, (2) rain occurs at any one grid point, on average, a specified percentage of the time and has a lognormal probability distribution, (3) spatial correlation of the rainfall can be arbitrarily prescribed, and (4) time stepping is carried out so that large-scale features persist longer than small-scale features. Rain is generated in the model from the portion of a correlated Gaussian random field that exceeds a threshold. The portion of the field above the threshold is rescaled to have a lognormal probability distribution. Sample output of the model designed to mimic radar observations of rainfall during the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE), is shown. The model is intended for use in evaluating sampling strategies for satellite remote-sensing of rainfall and for development of algorithms for converting radiant intensity received by an instrument from its field of view into rainfall amount.

  16. Rainfall estimation using an optical and a microwave link in the Ardèche catchment.

    Science.gov (United States)

    Pietersen, Henk; Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2013-04-01

    The Mediterranean basin is considered to be one of the "hotspots" for climate change. One of the main factors in these changes is the availability and distribution of water, both in time and space. To gain more understanding about the hydrological cycle in the Mediterranean basin and to quantify the related processes, the HYdrological cycle in the Mediterranean EXperiment (HyMeX) was set up. This experiment focuses on inter-annual to decadal variability in the coupled Mediterranean system, running during the second decade of the 21st century. During this long experiment, special intensive observation periods are planned, of which the first passed during the autumn of 2012. Within the HyMeX framework, one working group pays special attention to (flash) floods and heavy rainfall. To investigate this, several (small) catchments were heavily instrumented during the first special observation period. We show the first results on rainfall estimation employing an optical link, a microwave link, and a disdrometer in the Ardèche catchment in the south of France for the first special observation period of HyMeX. Optical and microwave links can be employed to estimate path-averaged rain intensities along a transect of several kilometers, similar in length to the cross-section of a small catchment. The transmitted signal is attenuated by rain along the link path causing a decrease in received power at the end of the link. The attenuation of this signal has a power-law relation to the average rainfall intensity along the link. As a reference, the disdrometer is placed at one end of the link. Link-based rainfall intensities are compared to those based on disdrometer data. However, due to the nature of the observational technique (point measurement vs. average along a link) errors in representation may occur. The estimation of rainfall intensity from attenuation can be hampered by a number of factors. Principal among these are: moisture on the antennae that is perceived to be

  17. Physical Theories with Average Symmetry

    CERN Document Server

    Alamino, Roberto C

    2013-01-01

    This Letter probes the existence of physical laws invariant only in average when subjected to some transformation. The concept of a symmetry transformation is broadened to include corruption by random noise and average symmetry is introduced by considering functions which are invariant only in average under these transformations. It is then shown that actions with average symmetry obey a modified version of Noether's Theorem with dissipative currents. The relation of this with possible violations of physical symmetries, as for instance Lorentz invariance in some quantum gravity theories, is briefly commented.

  18. Changes in Average Annual Precipitation in Argentina’s Pampa Region and Their Possible Causes

    Directory of Open Access Journals (Sweden)

    Silvia Pérez

    2015-01-01

    Full Text Available Changes in annual rainfall in five sub-regions of the Argentine Pampa Region (Rolling, Central, Mesopotamian, Flooding and Southern were examined for the period 1941 to 2010 using data from representative locations in each sub-region. Dubious series were adjusted by means of a homogeneity test and changes in mean value were evaluated using a hydrometeorological time series segmentation method. In addition, an association was sought between shifts in mean annual rainfall and changes in large-scale atmospheric pressure systems, as measured by the Atlantic Multidecadal Oscillation (AMO, the Pacific Decadal Oscillation (PDO and the Southern Oscillation Index (SOI. The results indicate that the Western Pampas (Central and Southern are more vulnerable to abrupt changes in average annual rainfall than the Eastern Pampas (Mesopotamian, Rolling and Flooding. Their vulnerability is further increased by their having the lowest average rainfall. The AMO showed significant negative correlations with all sub-regions, while the PDO and SOI showed significant positive and negative correlations respectively with the Central, Flooding and Southern Pampa. The fact that the PDO and AMO are going through the phases of their cycles that tend to reduce rainfall in much of the Pampas helps explain the lower rainfall recorded in the Western Pampas sub-regions in recent years. This has had a significant impact on agriculture and the environment.

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

    Directory of Open Access Journals (Sweden)

    C. Asdak

    1998-01-01

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

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

    DEFF Research Database (Denmark)

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

    2010-01-01

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

  1. Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk

    Science.gov (United States)

    MacLeod, D. A.; Morse, A. P.

    2014-12-01

    Around $1.6 billion per year is spent financing anti-malaria initiatives, and though malaria morbidity is falling, the impact of annual epidemics remains significant. Whilst malaria risk may increase with climate change, projections are highly uncertain and to sidestep this intractable uncertainty, adaptation efforts should improve societal ability to anticipate and mitigate individual events. Anticipation of climate-related events is made possible by seasonal climate forecasting, from which warnings of anomalous seasonal average temperature and rainfall, months in advance are possible. Seasonal climate hindcasts have been used to drive climate-based models for malaria, showing significant skill for observed malaria incidence. However, the relationship between seasonal average climate and malaria risk remains unquantified. Here we explore this relationship, using a dynamic weather-driven malaria model. We also quantify key uncertainty in the malaria model, by introducing variability in one of the first order uncertainties in model formulation. Results are visualized as location-specific impact surfaces: easily integrated with ensemble seasonal climate forecasts, and intuitively communicating quantified uncertainty. Methods are demonstrated for two epidemic regions, and are not limited to malaria modeling; the visualization method could be applied to any climate impact.

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

    Directory of Open Access Journals (Sweden)

    Daniel R. Dourte

    2015-01-01

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

  3. A Sudden Change In Rainfall Characteristics In Amman, Jordan During The Mid 1950s

    Directory of Open Access Journals (Sweden)

    Mohammad M. Samdi

    2006-01-01

    Full Text Available This study examines recent changes, trends and fluctuations in the total rainfall and number of rainy days at Amman Airport Meteorological (AAM station in Jordan during the period 1922-2003. The occurrence of abrupt changes and trends were examined and identified using the Pettitt test, a combination of cumulative sum charts (CUSUM and bootstrapping and the sequential version of Mann-Kendall rank tests. A sudden change and shift in the average of the total rainfall and annual number of rain days occurred in 1957. Annual total rainfall series from Madaba and Mafraq stations are also analyzed and showed similar change and shift points as that which appeared in AAM station. The analysis prevail a decline in the total rainfall and number of rain days in the second half of the past centaury.

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

    Science.gov (United States)

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

    2017-01-01

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

  5. Overland flow connectivity in olive orchard plots with cover crops and conventional tillage, and under different rainfall scenarios

    Science.gov (United States)

    López-Vicente, Manuel; García-Ruiz, Roberto; Guzmán, Gema; Vicente-Vicente, José Luis; Gómez, José Alfonso

    2016-04-01

    The study of overland flow connectivity (QC) allows understanding the redistribution dynamics of runoff and soil components as an emergent property of the spatio-temporal interactions of hydrological and geomorphic processes. However, very few studies have dealt with runoff connectivity in olive orchards. In this study we simulated QC in four olive orchard plots, located on the Santa Marta farm (37° 20' 33.6" N, 6° 13' 44" W), in Seville province (Andalusia) in SW Spain. The olive plantation was established in 1985 with trees planted at 8 m x 6 m. Each bounded plot is 8 m wide (between 2 tree lines) and 60 m long (total area of 480 m2), laid out with the longest dimension parallel to the maximum slope and to the tree lines. The slope is uniform, with an average steepness of 11%. Two plots (P2 and P4) were devoted to conventional tillage (CT) consisting of regular chisel plow passes depending on weed growth. Another set of two plots had two types of cover crops (CC) in the inter tree rows (the area outside the vertical olive canopy projection): uniform CC of Lolium multiflorum (P3) and a mixture of L. rigidum and L. multiflorum together with other species (P5). The tree rows were treated with herbicide to keep bare soil. We selected the Index of runoff and sediment Connectivity (IC) of Borselli et al. (2008) to simulate three rainfall scenarios: i) low rainfall intensity (Sc-LowInt) and using the MD flow accumulation algorithm; ii) moderate rainfall intensity (Sc-ModInt) and using MD8; and iii) high rainfall intensity (Sc-HighInt) and using D8. After analysing the values of rainfall intensity during two hydrological years (Oct'09-Sep'10 and Oct'10-Sep'11) we associated the three scenarios with the followings months: Sc-LowInt during the period Jan-Mar, that summarizes 42% of all annual rainfall events; Sc-ModInt during Oct-Nov and Apr-May (32% of all events); and Sc-HighInt during the period Jun-Sep and in December (26% of all events). Instead of using the C

  6. Two years of country-wide rainfall maps employing cellular communication networks

    Science.gov (United States)

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

    2014-05-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information and the number of rain gauges is even severely declining in Europe, South-America, and Africa. This calls for alternative sources of rainfall information. Various studies have shown that microwave links from operational cellular telecommunication networks may be employed for rainfall monitoring. Such networks cover 20% of the land surface of the earth and have a high density, especially in urban areas. The basic principle of rainfall monitoring using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. This is particularly interesting for those countries where few surface rainfall observations are available. Here we present almost two years of country-wide rainfall maps employing cellular communication networks. A data set from a commercial microwave link network over the Netherlands is analyzed, containing data from an unprecedented number of links (~ 2000) covering the land surface of the Netherlands (35500 square kilometers). This data set almost completely covers the years 2011 and 2012. Fifteen-minute and daily rainfall maps (1 km spatial resolution) are derived from the microwave link data and compared to maps from a gauge-adjusted radar data set. The performance of the rainfall retrieval algorithm will be studied, particularly differences in time and space. Time series of air temperature and snow from automatic weather stations, operated by the

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

    Directory of Open Access Journals (Sweden)

    C. Neal

    2004-01-01

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

  8. Weather radar rainfall data in urban hydrology

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Einfalt, Thomas; Willems, Patrick

    2017-01-01

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

  9. Modelling persistence in annual Australia point rainfall

    Directory of Open Access Journals (Sweden)

    J. P. Whiting

    2003-01-01

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

  10. 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.

  11. Quantized average consensus with delay

    NARCIS (Netherlands)

    Jafarian, Matin; De Persis, Claudio

    2012-01-01

    Average consensus problem is a special case of cooperative control in which the agents of the network asymptotically converge to the average state (i.e., position) of the network by transferring information via a communication topology. One of the issues of the large scale networks is the cost of co

  12. 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.

  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. 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).

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

    Science.gov (United States)

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

    2017-04-01

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

  16. Beyond Rainfall Multipliers: Describing Input Uncertainty as an Autocorrelated Stochastic Process Improves Inference in Hydrology

    Science.gov (United States)

    Del Giudice, D.; Albert, C.; Reichert, P.; Rieckermann, J.

    2015-12-01

    Rainfall is the main driver of hydrological systems. Unfortunately, it is highly variable in space and time and therefore difficult to observe accurately. This poses a serious challenge to correctly estimate the catchment-averaged precipitation, a key factor for hydrological models. As biased precipitation leads to biased parameter estimation and thus to biased runoff predictions, it is very important to have a realistic description of precipitation uncertainty. Rainfall multipliers (RM), which correct each observed storm with a random factor, provide a first step into this direction. Nevertheless, they often fail when the estimated input has a different temporal pattern from the true one or when a storm is not detected by the raingauge. In this study we propose a more realistic input error model, which is able to overcome these challenges and increase our certainty by better estimating model input and parameters. We formulate the average precipitation over the watershed as a stochastic input process (SIP). We suggest a transformed Gauss-Markov process, which is estimated in a Bayesian framework by using input (rainfall) and output (runoff) data. We tested the methodology in a 28.6 ha urban catchment represented by an accurate conceptual model. Specifically, we perform calibration and predictions with SIP and RM using accurate data from nearby raingauges (R1) and inaccurate data from a distant gauge (R2). Results show that using SIP, the estimated model parameters are "protected" from the corrupting impact of inaccurate rainfall. Additionally, SIP can correct input biases during calibration (Figure) and reliably quantify rainfall and runoff uncertainties during both calibration (Figure) and validation. In our real-word application with non-trivial rainfall errors, this was not the case with RM. We therefore recommend SIP in all cases where the input is the predominant source of uncertainty. Furthermore, the high-resolution rainfall intensities obtained with this

  17. Regime shifts in annual maximum rainfall across Australia - implications for intensity-frequency-duration (IFD) relationships

    Science.gov (United States)

    Verdon-Kidd, D. C.; Kiem, A. S.

    2015-12-01

    Rainfall intensity-frequency-duration (IFD) relationships are commonly required for the design and planning of water supply and management systems around the world. Currently, IFD information is based on the "stationary climate assumption" that weather at any point in time will vary randomly and that the underlying climate statistics (including both averages and extremes) will remain constant irrespective of the period of record. However, the validity of this assumption has been questioned over the last 15 years, particularly in Australia, following an improved understanding of the significant impact of climate variability and change occurring on interannual to multidecadal timescales. This paper provides evidence of regime shifts in annual maximum rainfall time series (between 1913-2010) using 96 daily rainfall stations and 66 sub-daily rainfall stations across Australia. Furthermore, the effect of these regime shifts on the resulting IFD estimates are explored for three long-term (1913-2010) sub-daily rainfall records (Brisbane, Sydney, and Melbourne) utilizing insights into multidecadal climate variability. It is demonstrated that IFD relationships may under- or over-estimate the design rainfall depending on the length and time period spanned by the rainfall data used to develop the IFD information. It is recommended that regime shifts in annual maximum rainfall be explicitly considered and appropriately treated in the ongoing revisions of the Engineers Australia guide to estimating and utilizing IFD information, Australian Rainfall and Runoff (ARR), and that clear guidance needs to be provided on how to deal with the issue of regime shifts in extreme events (irrespective of whether this is due to natural or anthropogenic climate change). The findings of our study also have important implications for other regions of the world that exhibit considerable hydroclimatic variability and where IFD information is based on relatively short data sets.

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

    Directory of Open Access Journals (Sweden)

    Abdulkadir Taofeeq Sholagberu

    2016-07-01

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

  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. 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

  1. A study on the decreasing trend in tropical easterly jet stream (TEJ) and its impact on Indian summer monsoon rainfall

    Science.gov (United States)

    Sreekala, P. P.; Bhaskara Rao, S. V.; Arunachalam, M. S.; Harikiran, C.

    2014-10-01

    Using the NCEP/NCAR reanalysis wind and temperature data (1948-2011) and India Meteorological Department (IMD) rainfall data, a long-term trend in the tropical easterly jet stream and its effect on Indian summer monsoon rainfall has been explained in the present study. A decreasing trend in zonal wind speed at 100 mb (maximum decrease), 150 mb, and 200 mb (minimum) is observed. The upper-level (100, 150, and 200 mb) zonal wind speed has been correlated with the surface air temperature anomaly index (ATAI) in the month of May, which is taken as the difference in temperature anomaly over land (22.5°N-27.5°N, 80°E-90°E) and Ocean (5°S-0°S, 75°E-85°E). Significant high correlation is observed between May ATAI and tropical easterly jet stream (TEJ) which suggests that the decreasing land-sea temperature contrast could be one major reason behind the decreasing trend in TEJ. The analysis of spatial distribution of rainfall over India shows a decreasing trend in rainfall over Jammu and Kashmir, Arunachal Pradesh, central Indian region, and western coast of India. Increasing trend in rainfall is observed over south peninsular and northeastern part of India. From the spatial correlation analysis of zonal wind with gridded rainfall, it is observed that the correlation of rainfall is found to be high with the TEJ speed over the regions where the decreasing trend in rainfall is observed. Similarly, from the analysis of spatial correlation between rainfall and May ATAI, positive spatial correlation is observed between May ATAI and summer monsoon rainfall over the regions such as south peninsular India where the rainfall trend is positive, and negative correlation is observed over the places such as Jammu and Kashmir where negative rainfall trend is observed. The decreased land-sea temperature contrast in the pre-monsoon month could be one major reason behind the decreased trend in TEJ as well as the observed spatial variation in the summer monsoon rainfall trend. Thus

  2. Gaussian moving averages and semimartingales

    DEFF Research Database (Denmark)

    Basse-O'Connor, Andreas

    2008-01-01

    In the present paper we study moving averages (also known as stochastic convolutions) driven by a Wiener process and with a deterministic kernel. Necessary and sufficient conditions on the kernel are provided for the moving average to be a semimartingale in its natural filtration. Our results...... are constructive - meaning that they provide a simple method to obtain kernels for which the moving average is a semimartingale or a Wiener process. Several examples are considered. In the last part of the paper we study general Gaussian processes with stationary increments. We provide necessary and sufficient...

  3. Regionalized rainfall-runoff model to estimate low flow indices

    Science.gov (United States)

    Garcia, Florine; Folton, Nathalie; Oudin, Ludovic

    2016-04-01

    Estimating low flow indices is of paramount importance to manage water resources and risk assessments. These indices are derived from river discharges which are measured at gauged stations. However, the lack of observations at ungauged sites bring the necessity of developing methods to estimate these low flow indices from observed discharges in neighboring catchments and from catchment characteristics. Different estimation methods exist. Regression or geostatistical methods performed on the low flow indices are the most common types of methods. Another less common method consists in regionalizing rainfall-runoff model parameters, from catchment characteristics or by spatial proximity, to estimate low flow indices from simulated hydrographs. Irstea developed GR2M-LoiEau, a conceptual monthly rainfall-runoff model, combined with a regionalized model of snow storage and melt. GR2M-LoiEau relies on only two parameters, which are regionalized and mapped throughout France. This model allows to cartography monthly reference low flow indices. The inputs data come from SAFRAN, the distributed mesoscale atmospheric analysis system, which provides daily solid and liquid precipitation and temperature data from everywhere in the French territory. To exploit fully these data and to estimate daily low flow indices, a new version of GR-LoiEau has been developed at a daily time step. The aim of this work is to develop and regionalize a GR-LoiEau model that can provide any daily, monthly or annual estimations of low flow indices, yet keeping only a few parameters, which is a major advantage to regionalize them. This work includes two parts. On the one hand, a daily conceptual rainfall-runoff model is developed with only three parameters in order to simulate daily and monthly low flow indices, mean annual runoff and seasonality. On the other hand, different regionalization methods, based on spatial proximity and similarity, are tested to estimate the model parameters and to simulate

  4. A Unified Theory of Rainfall Extremes, Rainfall Excesses, and IDF Curves

    Science.gov (United States)

    Veneziano, D.; Yoon, S.

    2012-04-01

    Extreme rainfall events are a key component of hydrologic risk management and design. Yet, a consistent mathematical theory of such extremes remains elusive. This study aims at laying new statistical foundations for such a theory. The quantities of interest are the distribution of the annual maximum, the distribution of the excess above a high threshold z, and the intensity-duration-frequency (IDF) curves. Traditionally, the modeling of annual maxima and excesses is based on extreme value (EV) and extreme excess (EE) theories. These theories establish that the maximum of n iid variables is attracted as n →∞ to a generalized extreme value (GEV) distribution with a certain index k and the distribution of the excess is attracted as z →∞ to a generalized Pareto distribution with the same index. The empirical value of k tends to decrease as the averaging duration d increases. To a first approximation, the IDF intensities scale with d and the return period T . Explanations for this approximate scaling behavior and theoretical predictions of the scaling exponents have emerged over the past few years. This theoretical work has been largely independent of that on the annual maxima and the excesses. Deviations from exact scaling include a tendency of the IDF curves to converge as d and T increase. To bring conceptual clarity and explain the above observations, we analyze the extremes of stationary multifractal measures, which provide good representations of rainfall within storms. These extremes follow from large deviation theory rather than EV/EE theory. A unified framework emerges that (a) encompasses annual maxima, excesses and IDF values without relying on EV or EE asymptotics, (b) predicts the index k and the IDF scaling exponents, (c) explains the dependence of k on d and the deviations from exact scaling of the IDF curves, and (d) explains why the empirical estimates of k tend to be positive (in the Frechet range) while, based on frequently assumed marginal

  5. 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