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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

    Directory of Open Access Journals (Sweden)

    G. M. J. HASAN

    2014-10-01

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

  2. Spatial structure of monthly rainfall measurements average over 25 years and trends of the hourly variability of a current rainy day in Rwanda.

    Science.gov (United States)

    Nduwayezu, Emmanuel; Kanevski, Mikhail; Jaboyedoff, Michel

    2013-04-01

    Climate plays a vital role in a wide range of socio-economic activities of most nations particularly of developing countries. Climate (rainfall) plays a central role in agriculture which is the main stay of the Rwandan economy and community livelihood and activities. The majority of the Rwandan population (81,1% in 2010) relies on rain fed agriculture for their livelihoods, and the impacts of variability in climate patterns are already being felt. Climate-related events like heavy rainfall or too little rainfall are becoming more frequent and are impacting on human wellbeing.The torrential rainfall that occurs every year in Rwanda could disturb the circulation for many days, damages houses, infrastructures and causes heavy economic losses and deaths. 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). Globally, 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. What is the hourly variability in this mountainous area? Is there any correlation with the identified zones of the monthly average series (from 1965 to 1990 established by the Rwandan meteorological services)? Where could we have hazards with several consecutive rainy days (using forecasted datas from the Norwegian Meteorological Institute)? Spatio-temporal analysis allows for identifying and explaining large-scale anomalies which are useful for understanding hydrological characteristics and subsequently predicting these hydrological events. The objective of our current research (Rainfall variability) is to proceed to an evaluation of the potential rainfall risk by applying advanced geospatial modelling tools in Rwanda: geostatistical

  3. Monthly Rainfall Erosivity Assessment for Switzerland

    Science.gov (United States)

    Schmidt, Simon; Meusburger, Katrin; Alewell, Christine

    2016-04-01

    Water erosion is crucially controlled by rainfall erosivity, which is quantified out of the kinetic energy of raindrop impact and associated surface runoff. Rainfall erosivity is often expressed as the R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). Just like precipitation, the rainfall erosivity of Switzerland has a characteristic seasonal dynamic throughout the year. This inter-annual variability is to be assessed by a monthly and seasonal modelling approach. We used a network of 86 precipitation gauging stations with a 10-minute temporal resolution to calculate long-term average monthly R-factors. Stepwise regression and Monte Carlo Cross Validation (MCCV) was used to select spatial covariates to explain the spatial pattern of R-factor for each month across Switzerland. The regionalized monthly R-factor is mapped by its individual regression equation and the ordinary kriging interpolation of its residuals (Regression-Kriging). As covariates, a variety of precipitation indicator data has been included like snow height, a combination of hourly gauging measurements and radar observations (CombiPrecip), mean monthly alpine precipitation (EURO4M-APGD) and monthly precipitation sums (Rhires). Topographic parameters were also significant explanatory variables for single months. The comparison of all 12 monthly rainfall erosivity maps showed seasonality with highest rainfall erosivity in summer (June, July, and August) and lowest rainfall erosivity in winter months. Besides the inter-annual temporal regime, a seasonal spatial variability was detectable. Spatial maps of monthly rainfall erosivity are presented for the first time for Switzerland. The assessment of the spatial and temporal dynamic behaviour of the R-factor is valuable for the identification of more susceptible seasons and regions as well as for the application of selective erosion control measures. A combination with monthly vegetation

  4. Effect of monthly areal rainfall uncertainty on streamflow simulation

    Science.gov (United States)

    Ndiritu, J. G.; Mkhize, N.

    2017-08-01

    Areal rainfall is mostly obtained from point rainfall measurements that are sparsely located and several studies have shown that this results in large areal rainfall uncertainties at the daily time step. However, water resources assessment is often carried out a monthly time step and streamflow simulation is usually an essential component of this assessment. This study set out to quantify monthly areal rainfall uncertainties and assess their effect on streamflow simulation. This was achieved by; i) quantifying areal rainfall uncertainties and using these to generate stochastic monthly areal rainfalls, and ii) finding out how the quality of monthly streamflow simulation and streamflow variability change if stochastic areal rainfalls are used instead of historic areal rainfalls. Tests on monthly rainfall uncertainty were carried out using data from two South African catchments while streamflow simulation was confined to one of them. A non-parametric model that had been applied at a daily time step was used for stochastic areal rainfall generation and the Pitman catchment model calibrated using the SCE-UA optimizer was used for streamflow simulation. 100 randomly-initialised calibration-validation runs using 100 stochastic areal rainfalls were compared with 100 runs obtained using the single historic areal rainfall series. By using 4 rain gauges alternately to obtain areal rainfall, the resulting differences in areal rainfall averaged to 20% of the mean monthly areal rainfall and rainfall uncertainty was therefore highly significant. Pitman model simulations obtained coefficient of efficiencies averaging 0.66 and 0.64 in calibration and validation using historic rainfalls while the respective values using stochastic areal rainfalls were 0.59 and 0.57. Average bias was less than 5% in all cases. The streamflow ranges using historic rainfalls averaged to 29% of the mean naturalised flow in calibration and validation and the respective average ranges using stochastic

  5. Regionalization of monthly rainfall erosivity patternsin Switzerland

    Science.gov (United States)

    Schmidt, Simon; Alewell, Christine; Panagos, Panos; Meusburger, Katrin

    2016-10-01

    One major controlling factor of water erosion is rainfall erosivity, which is quantified as the product of total storm energy and a maximum 30 min intensity (I30). Rainfall erosivity is often expressed as R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). As rainfall erosivity is closely correlated with rainfall amount and intensity, the rainfall erosivity of Switzerland can be expected to have a regional characteristic and seasonal dynamic throughout the year. This intra-annual variability was mapped by a monthly modeling approach to assess simultaneously spatial and monthly patterns of rainfall erosivity. So far only national seasonal means and regional annual means exist for Switzerland. We used a network of 87 precipitation gauging stations with a 10 min temporal resolution to calculate long-term monthly mean R-factors. Stepwise generalized linear regression (GLM) and leave-one-out cross-validation (LOOCV) were used to select spatial covariates which explain the spatial and temporal patterns of the R-factor for each month across Switzerland. The monthly R-factor is mapped by summarizing the predicted R-factor of the regression equation and the corresponding residues of the regression, which are interpolated by ordinary kriging (regression-kriging). As spatial covariates, a variety of precipitation indicator data has been included such as snow depths, a combination product of hourly precipitation measurements and radar observations (CombiPrecip), daily Alpine precipitation (EURO4M-APGD), and monthly precipitation sums (RhiresM). Topographic parameters (elevation, slope) were also significant explanatory variables for single months. The comparison of the 12 monthly rainfall erosivity maps showed a distinct seasonality with the highest rainfall erosivity in summer (June, July, and August) influenced by intense rainfall events. Winter months have the lowest rainfall erosivity. A proportion of 62 % of

  6. A method for predicting monthly rainfall patterns

    International Nuclear Information System (INIS)

    Njau, E.C.

    1987-11-01

    A brief survey is made of previous methods that have been used to predict rainfall trends or drought spells in different parts of the earth. The basic methodologies or theoretical strategies used in these methods are compared with contents of a recent theory of Sun-Weather/Climate links (Njau, 1985a; 1985b; 1986; 1987a; 1987b; 1987c) which point towards the possibility of practical climatic predictions. It is shown that not only is the theoretical basis of each of these methodologies or strategies fully incorporated into the above-named theory, but also this theory may be used to develop a technique by which future monthly rainfall patterns can be predicted in further and finer details. We describe the latter technique and then illustrate its workability by means of predictions made on monthly rainfall patterns in some East African meteorological stations. (author). 43 refs, 11 figs, 2 tabs

  7. 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

  8. Mapping monthly rainfall erosivity in Europe

    DEFF Research Database (Denmark)

    Ballabio, C; Meusburger, K; Klik, A

    2017-01-01

    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...... 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...... 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...

  9. 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

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

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    Campos-Aranda Daniel Francisco

    2014-10-01

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

  11. Fitting monthly Peninsula Malaysian rainfall using Tweedie distribution

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    Yunus, R. M.; Hasan, M. M.; Zubairi, Y. Z.

    2017-09-01

    In this study, the Tweedie distribution was used to fit the monthly rainfall data from 24 monitoring stations of Peninsula Malaysia for the period from January, 2008 to April, 2015. The aim of the study is to determine whether the distributions within the Tweedie family fit well the monthly Malaysian rainfall data. Within the Tweedie family, the gamma distribution is generally used for fitting the rainfall totals, however the Poisson-gamma distribution is more useful to describe two important features of rainfall pattern, which are the occurrences (dry months) and the amount (wet months). First, the appropriate distribution of the monthly rainfall was identified within the Tweedie family for each station. Then, the Tweedie Generalised Linear Model (GLM) with no explanatory variable was used to model the monthly rainfall data. Graphical representation was used to assess model appropriateness. The QQ plots of quantile residuals show that the Tweedie models fit the monthly rainfall data better for majority of the stations in the west coast and mid land than those in the east coast of Peninsula. This significant finding suggests that the best fitted distribution depends on the geographical location of the monitoring station. In this paper, a simple model is developed for generating synthetic rainfall data for use in various areas, including agriculture and irrigation. We have showed that the data that were simulated using the Tweedie distribution have fairly similar frequency histogram to that of the actual data. Both the mean number of rainfall events and mean amount of rain for a month were estimated simultaneously for the case that the Poisson gamma distribution fits the data reasonably well. Thus, this work complements previous studies that fit the rainfall amount and the occurrence of rainfall events separately, each to a different distribution.

  12. 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 average...

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

    Science.gov (United States)

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

    2017-10-01

    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 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.

  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 must...

  15. Trends and variation in monthly rainfall and temperature in Suriname

    International Nuclear Information System (INIS)

    Raid, Nurmohamed

    2004-01-01

    As Surinam lies within the equatorial trough zone, climate is mainly influenced by the movement and intensity of the Inter-tropical Convergence Zone and the El Nino Southern Oscillation. Scientist predict that global climate change will directly effect the hydrological cycle such as rainfall and temperature, and extreme events such as a El Nino and La Nina. The aim of this study is to analyze historical changes in monthly rainfall and temperature and to predict future changes, with respect to climate change (doubling of carbon dioxide (CO 2 ) by 2100) and variability. Linear extrapolation and five Global Circulations Models (GCMS) (HadCM2, ECHAM4, GFDL-TR, CSIRO2-EQ, CCSR-NIES) will be used. Results of GCMs have showed that under global climate change by 2100, the monthly rainfall is predicted to change with -82 to 66 mm during January and August, and -36 to 47 mm during September and November. The monthly temperature is predicted to increase with 1.3 to 4.3 C by 2100. El Nino events have showed that along the coastal zone and in the center of Surinam, most months (>50%) during the year are drier than normal (88 to 316 mm), while in the west part of Surinam, most months (>50%) are wetter than normal (110 to 220 mm). La Nina events have showed that over entire Surinam, most of the months are wetter than normal (19 to 122 mm), with respect to the minimum rainfall. It can be concluded that the changes in rainfall due to El Nino and La Nina events may have significant impacts on the design, planning and management of water resources systems in Surinam and should therefore be incorporated in future water resources planning. (Author)

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

    Directory of Open Access Journals (Sweden)

    Panos Panagos

    2016-03-01

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

  17. 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.

  18. Spatial Distribution of Annual and Monthly Rainfall Erosivity in the Jaguarí River Basin

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    Lucas Machado Pontes

    2017-11-01

    Full Text Available ABSTRACT The Jaguarí River Basin forms the main water supply sources for the São Paulo Metropolitan Region and other cities in the state. Since the kinetic energy of rainfall is the driving force of water erosion, the main cause of land and water degradation, we tested the hypothesis of correlation between the erosive potential of rainfall (erosivity and geographical coordinates and altitude for the purpose of predicting the spatial and temporal distribution of the rainfall erosivity index (EI30 in the basin. An equation was used to estimate the (EI30 in accordance with the average monthly and total annual rainfall at rainfall stations with data available for the study area. In the regression kriging technique, the deterministic part was modeled using multiple linear regression between the dependent variable (EI30 and environmental predictor variables: latitude, longitude, and altitude. From the result of equations and the maps generated, a direct correlation between erosivity and altitude could be observed. Erosivity has a markedly seasonal behavior in accordance with the rainy season from October to March. This season concentrates 86 % of the estimated EI30 values, with monthly maximum values of up to 2,342 MJ mm ha-1 h-1 month-1 between December and January, and minimum of 34 MJ mm ha-1 h-1 month-1 in August. The highest values were found in the Mantiqueira Range region (annual average of up to 12,000 MJ mm ha-1 h-1, a region that should be prioritized in soil and water conservation efforts. From this validation, good precision and accuracy of the model was observed for the long period of the annual average, which is the main factor used in soil loss prediction models.

  19. 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

  20. A Stochastic Model of Space-Time Variability of Tropical Rainfall: I. Statistics of Spatial Averages

    Science.gov (United States)

    Kundu, Prasun K.; Bell, Thomas L.; Lau, William K. M. (Technical Monitor)

    2002-01-01

    Global maps of rainfall are of great importance in connection with modeling of the earth s climate. Comparison between the maps of rainfall predicted by computer-generated climate models with observation provides a sensitive test for these models. To make such a comparison, one typically needs the total precipitation amount over a large area, which could be hundreds of kilometers in size over extended periods of time of order days or months. This presents a difficult problem since rain varies greatly from place to place as well as in time. Remote sensing methods using ground radar or satellites detect rain over a large area by essentially taking a series of snapshots at infrequent intervals and indirectly deriving the average rain intensity within a collection of pixels , usually several kilometers in size. They measure area average of rain at a particular instant. Rain gauges, on the other hand, record rain accumulation continuously in time but only over a very small area tens of centimeters across, say, the size of a dinner plate. They measure only a time average at a single location. In making use of either method one needs to fill in the gaps in the observation - either the gaps in the area covered or the gaps in time of observation. This involves using statistical models to obtain information about the rain that is missed from what is actually detected. This paper investigates such a statistical model and validates it with rain data collected over the tropical Western Pacific from ship borne radars during TOGA COARE (Tropical Oceans Global Atmosphere Coupled Ocean-Atmosphere Response Experiment). The model incorporates a number of commonly observed features of rain. While rain varies rapidly with location and time, the variability diminishes when averaged over larger areas or longer periods of time. Moreover, rain is patchy in nature - at any instant on the average only a certain fraction of the observed pixels contain rain. The fraction of area covered by

  1. Desert locust populations, rainfall and climate change: insights from phenomenological models using gridded monthly data

    OpenAIRE

    Tratalos, Jamie A.; Cheke, Robert A.; Healey, Richard G.; Stenseth, Nils Chr.

    2010-01-01

    Using autocorrelation analysis and autoregressive integrated moving average (ARIMA)modelling, we analysed a time series of the monthly number of 1° grid squares infested with desert locust Schistocerca gregaria swarms throughout the geographical range of the species from 1930–1987. Statistically significant first- and higher-order autocorrelations were found in the series. Although endogenous components captured much of the variance, adding rainfall data improved endogenous ARIMA models and r...

  2. Yearly, seasonal and monthly daily average diffuse sky radiation models

    International Nuclear Information System (INIS)

    Kassem, A.S.; Mujahid, A.M.; Turner, D.W.

    1993-01-01

    A daily average diffuse sky radiation regression model based on daily global radiation was developed utilizing two year data taken near Blytheville, Arkansas (Lat. =35.9 0 N, Long. = 89.9 0 W), U.S.A. The model has a determination coefficient of 0.91 and 0.092 standard error of estimate. The data were also analyzed for a seasonal dependence and four seasonal average daily models were developed for the spring, summer, fall and winter seasons. The coefficient of determination is 0.93, 0.81, 0.94 and 0.93, whereas the standard error of estimate is 0.08, 0.102, 0.042 and 0.075 for spring, summer, fall and winter, respectively. A monthly average daily diffuse sky radiation model was also developed. The coefficient of determination is 0.92 and the standard error of estimate is 0.083. A seasonal monthly average model was also developed which has 0.91 coefficient of determination and 0.085 standard error of estimate. The developed monthly daily average and daily models compare well with a selected number of previously developed models. (author). 11 ref., figs., tabs

  3. Ensemble averaging and stacking of ARIMA and GSTAR model for rainfall forecasting

    Science.gov (United States)

    Anggraeni, D.; Kurnia, I. F.; Hadi, A. F.

    2018-04-01

    Unpredictable rainfall changes can affect human activities, such as in agriculture, aviation, shipping which depend on weather forecasts. Therefore, we need forecasting tools with high accuracy in predicting the rainfall in the future. This research focus on local forcasting of the rainfall at Jember in 2005 until 2016, from 77 rainfall stations. The rainfall here was not only related to the occurrence of the previous of its stations, but also related to others, it’s called the spatial effect. The aim of this research is to apply the GSTAR model, to determine whether there are some correlations of spatial effect between one to another stations. The GSTAR model is an expansion of the space-time model that combines the time-related effects, the locations (stations) in a time series effects, and also the location it self. The GSTAR model will also be compared to the ARIMA model that completely ignores the independent variables. The forcested value of the ARIMA and of the GSTAR models then being combined using the ensemble forecasting technique. The averaging and stacking method of ensemble forecasting method here provide us the best model with higher acuracy model that has the smaller RMSE (Root Mean Square Error) value. Finally, with the best model we can offer a better local rainfall forecasting in Jember for the future.

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

    Science.gov (United States)

    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.

  5. Ocean tides in GRACE monthly averaged gravity fields

    DEFF Research Database (Denmark)

    Knudsen, Per

    2003-01-01

    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...... 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 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...

  6. Comparison of mass transport using average and transient rainfall boundary conditions

    International Nuclear Information System (INIS)

    Duguid, J.O.; Reeves, M.

    1976-01-01

    A general two-dimensional model for simulation of saturated-unsaturated transport of radionuclides in ground water has been developed and is currently being tested. The model is being applied to study the transport of radionuclides from a waste-disposal site where field investigations are currently under way to obtain the necessary model parameters. A comparison of the amount of tritium transported is made using both average and transient rainfall boundary conditions. The simulations indicate that there is no substantial difference in the transport for the two conditions tested. However, the values of dispersivity used in the unsaturated zone caused more transport above the water table than has been observed under actual conditions. This deficiency should be corrected and further comparisons should be made before average rainfall boundary conditions are used for long-term transport simulations

  7. Trends and homogeneity of monthly, seasonal, and annual rainfall over arid region of Rajasthan, India

    Science.gov (United States)

    Meena, Hari Mohan; Machiwal, Deepesh; Santra, Priyabrata; Moharana, Pratap Chandra; Singh, D. V.

    2018-05-01

    Knowledge of rainfall variability is important for regional-scale planning and management of water resources in agriculture. This study explores spatio-temporal variations, trends, and homogeneity in monthly, seasonal, and annual rainfall series of 62 stations located in arid region of Rajasthan, India using 55 year (1957-2011) data. Box-whisker plots indicate presence of outliers and extremes in annual rainfall, which made the distribution of annual rainfall right-skewed. Mean and coefficient of variation (CV) of rainfall reveals a high inter-annual variability (CV > 200%) in the western portion where the mean annual rainfall is very low. A general gradient of the mean monthly, seasonal, and annual rainfall is visible from northwest to southeast direction, which is orthogonal to the gradient of CV. The Sen's innovative trend test is found over-sensitive in evaluating statistical significance of the rainfall trends, while the Mann-Kendall test identifies significantly increasing rainfall trends in June and September. Rainfall in July shows prominently decreasing trends although none of them are found statistically significant. Monsoon and annual rainfall show significantly increasing trends at only four stations. The magnitude of trends indicates that the rainfall is increasing at a mean rate of 1.11, 2.85, and 2.89 mm year-1 in August, monsoon season, and annual series. The rainfall is found homogeneous over most of the area except for few stations situated in the eastern and northwest portions where significantly increasing trends are observed. Findings of this study indicate that there are few increasing trends in rainfall of this Indian arid region.

  8. Artificial neural network optimisation for monthly average daily global solar radiation prediction

    International Nuclear Information System (INIS)

    Alsina, Emanuel Federico; Bortolini, Marco; Gamberi, Mauro; Regattieri, Alberto

    2016-01-01

    Highlights: • Prediction of the monthly average daily global solar radiation over Italy. • Multi-location Artificial Neural Network (ANN) model: 45 locations considered. • Optimal ANN configuration with 7 input climatologic/geographical parameters. • Statistical indicators: MAPE, NRMSE, MPBE. - Abstract: The availability of reliable climatologic data is essential for multiple purposes in a wide set of anthropic activities and operative sectors. Frequently direct measures present spatial and temporal lacks so that predictive approaches become of interest. This paper focuses on the prediction of the Monthly Average Daily Global Solar Radiation (MADGSR) over Italy using Artificial Neural Networks (ANNs). Data from 45 locations compose the multi-location ANN training and testing sets. For each location, 13 input parameters are considered, including the geographical coordinates and the monthly values for the most frequently adopted climatologic parameters. A subset of 17 locations is used for ANN training, while the testing step is against data from the remaining 28 locations. Furthermore, the Automatic Relevance Determination method (ARD) is used to point out the most relevant input for the accurate MADGSR prediction. The ANN best configuration includes 7 parameters, only, i.e. Top of Atmosphere (TOA) radiation, day length, number of rainy days and average rainfall, latitude and altitude. The correlation performances, expressed through statistical indicators as the Mean Absolute Percentage Error (MAPE), range between 1.67% and 4.25%, depending on the number and type of the chosen input, representing a good solution compared to the current standards.

  9. Month-to-month variability of Indian summer monsoon rainfall in 2016: role of the Indo-Pacific climatic conditions

    Science.gov (United States)

    Chowdary, Jasti S.; Srinivas, G.; Du, Yan; Gopinath, K.; Gnanaseelan, C.; Parekh, Anant; Singh, Prem

    2018-03-01

    Indian summer monsoon (ISM) rainfall during 2016 exhibited a prominent month-to-month fluctuations over India, with below normal rainfall in June and August and above normal rainfall in July. The factors determining the month-to-month fluctuations in ISM rainfall during 2016 are investigated with main focus on the Indo-Pacific climatic anomalies. Warm sea surface temperature (SST) anomalies associated with super El Niño 2015 disappeared by early summer 2016 over the central and eastern Pacific. On the other hand, negative Indian Ocean dipole (IOD) like SST anomaly pattern over the equatorial Indian Ocean and anomalous anticyclonic circulation over the western North Pacific (WNP) are reported in summer 2016 concurrently with decaying El Niño/developing La Niña phase. Observations revealed that the low rainfall over central north India in June is due to moisture divergence caused by the westward extension of ridge corresponding to WNP anticyclone and subsidence induced by local Hadley cell partly related to negative IOD. Low level convergence of southeasterly wind from Bay of Bengal associated with weak WNP anticyclone and northwesterly wind corresponding to anticyclonic circulation over the northwest India remarkably contributed to positive rainfall in July over most of the Indian subcontinent. While reduced rainfall over the Indian subcontinent in August 2016 is associated with the anomalous moisture transport from ISM region to WNP region, in contrast to July, due to local cyclogenesis corroborated by number of tropical cyclones in the WNP. In addition to this, subsidence related to strong convection supported by cyclonic circulation over the WNP also resulted in low rainfall over the ISM region. Coupled General Circulation model sensitivity experiments confirmed that strong convective activities associated with cyclonic circulation over the WNP is primarily responsible for the observed negative ISM rainfall anomalies in August 2016. It is noted that the Indo

  10. Forecasting of Average Monthly River Flows in Colombia

    Science.gov (United States)

    Mesa, O. J.; Poveda, G.

    2006-05-01

    The last two decades have witnessed a marked increase in our knowledge of the causes of interannual hydroclimatic variability and our ability to make predictions. Colombia, located near the seat of the ENSO phenomenon, has been shown to experience negative (positive) anomalies in precipitation in concert with El Niño (La Niña). In general besides the Pacific Ocean, Colombia has climatic influences from the Atlantic Ocean and the Caribbean Sea through the tropical forest of the Amazon basin and the savannas of the Orinoco River, in top of the orographic and hydro-climatic effects introduced by the Andes. As in various other countries of the region, hydro-electric power contributes a large proportion (75 %) of the total electricity generation in Colombia. Also, most agriculture is rain-fed dependant, and domestic water supply relies mainly on surface waters from creeks and rivers. Besides, various vector borne tropical diseases intensify in response to rain and temperature changes. Therefore, there is a direct connection between climatic fluctuations and national and regional economies. This talk specifically presents different forecasts of average monthly stream flows for the inflow into the largest reservoir used for hydropower generation in Colombia, and illustrates the potential economic savings of such forecasts. Because of planning of the reservoir operation, the most appropriated time scale for this application is the annual to interannual. Fortunately, this corresponds to the scale at which hydroclimate variability understanding has improved significantly. Among the different possibilities we have explored: traditional statistical ARIMA models, multiple linear regression, natural and constructed analogue models, the linear inverse model, neural network models, the non-parametric regression splines (MARS) model, regime dependant Markovian models and one we termed PREBEO, which is based on spectral bands decomposition using wavelets. Most of the methods make

  11. Average monthly and annual climate maps for Bolivia

    KAUST Repository

    Vicente-Serrano, Sergio M.; El Kenawy, Ahmed M.; Azorin-Molina, Cesar; Chura, O.; Trujillo, F.; Aguilar, Enric; Martí n-Herná ndez, Natalia; Ló pez-Moreno, Juan Ignacio; Sanchez-Lorenzo, Arturo; Morá n-Tejeda, Enrique; Revuelto, Jesú s; Ycaza, P.; Friend, F.

    2015-01-01

    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

  12. A modular class of multisite monthly rainfall generators for water resource management and impact studies

    Science.gov (United States)

    Serinaldi, Francesco; Kilsby, Chris G.

    2012-09-01

    SummaryThis study introduces a class of stochastic multisite monthly rainfall generators devised for application in water resources management problems, such as the sensitivity analysis of droughts and extreme rainfall scenarios under external climatic and non-climatic forcing mechanisms. The modelling framework relies on three elements: (1) a classical deseasonalisation scheme based on log-transformed observations, (2) the nonparametric bootstrap resampling approach and (3) parametric Generalized Additive Models for Location, Scale and Shape (GAMLSS). As the bootstrap and GAMLSS modules are alternative techniques for simulating each month, the free choice between them makes the structure of the model modular and flexible, so that it can be easily adapted to different climatic conditions, and can be customized based on the specific water resource problem. The model was set up and calibrated to simulate monthly rainfall from six locations in England and Wales to produce a suitable input for drought analysis. The results of the case study point out that the model can capture several characteristics of the rainfall series. In particular, it enables the simulation of low and high rainfall scenarios more extreme than those observed as well as the reproduction of the distribution of the annual accumulated rainfall, and of the relationship between the rainfall and circulation indices such as North Atlantic Oscillation (NAO) and Sea Surface Temperature (SST), thus making the framework well-suited for sensitivity analysis under alternative climate scenarios and additional forcing variables.

  13. 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

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

    International Nuclear Information System (INIS)

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

    2010-01-01

    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 0 latitude-longitude resolution, and a southeastern Australia regional analysis at 0.1 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 0 and 0.05 0 .

  15. 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.

  16. a multi-period markov model for monthly rainfall in lagos, nigeria

    African Journals Online (AJOL)

    PUBLICATIONS1

    A twelve-period. Markov model has been developed for the monthly rainfall data for Lagos, along the coast of .... autoregressive process to model river flow; Deo et al. (2015) utilized an ...... quences for the analysis of river basins by simulation.

  17. 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.

    2018-01-01

    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.

  18. time series analysis of monthly rainfall in nigeria with emphasis on ...

    African Journals Online (AJOL)

    User

    Monthly rainfall data of twenty-one years (1980 – 2000) were analyzed for the six regions of. Nigeria using the rescaled range (R/S) statistic, the standard fluctuation analysis (FA) and the detrended fluctuation ... 2011 Kwame Nkrumah University of Science and Technology (KNUST) .... starting from the beginning, and s non-.

  19. 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...

  20. Rainfall Erosivity in Europe

    DEFF Research Database (Denmark)

    Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale

    2015-01-01

    Rainfall is one the main drivers of soil erosion. 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 Rfactor in the USLE model and its revised version, RUSLE. At national...... and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based...

  1. 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.

  2. [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.

  3. RSS SSM/I OCEAN PRODUCT GRIDS MONTHLY AVERAGE FROM DMSP F15 NETCDF V7

    Data.gov (United States)

    National Aeronautics and Space Administration — The RSS SSM/I Ocean Product Grids Monthly Average from DMSP F15 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special...

  4. Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using Genetic Programming

    Science.gov (United States)

    Kashid, Satishkumar S.; Maity, Rajib

    2012-08-01

    SummaryPrediction of Indian Summer Monsoon Rainfall (ISMR) is of vital importance for Indian economy, and it has been remained a great challenge for hydro-meteorologists due to inherent complexities in the climatic systems. The Large-scale atmospheric circulation patterns from tropical Pacific Ocean (ENSO) and those from tropical Indian Ocean (EQUINOO) are established to influence the Indian Summer Monsoon Rainfall. The information of these two large scale atmospheric circulation patterns in terms of their indices is used to model the complex relationship between Indian Summer Monsoon Rainfall and the ENSO as well as EQUINOO indices. However, extracting the signal from such large-scale indices for modeling such complex systems is significantly difficult. Rainfall predictions have been done for 'All India' as one unit, as well as for five 'homogeneous monsoon regions of India', defined by Indian Institute of Tropical Meteorology. Recent 'Artificial Intelligence' tool 'Genetic Programming' (GP) has been employed for modeling such problem. The Genetic Programming approach is found to capture the complex relationship between the monthly Indian Summer Monsoon Rainfall and large scale atmospheric circulation pattern indices - ENSO and EQUINOO. Research findings of this study indicate that GP-derived monthly rainfall forecasting models, that use large-scale atmospheric circulation information are successful in prediction of All India Summer Monsoon Rainfall with correlation coefficient as good as 0.866, which may appears attractive for such a complex system. A separate analysis is carried out for All India Summer Monsoon rainfall for India as one unit, and five homogeneous monsoon regions, based on ENSO and EQUINOO indices of months of March, April and May only, performed at end of month of May. In this case, All India Summer Monsoon Rainfall could be predicted with 0.70 as correlation coefficient with somewhat lesser Correlation Coefficient (C.C.) values for different

  5. 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.

  6. ship between IS-month mating mass and average lifetime repro

    African Journals Online (AJOL)

    1976; Elliol, Rae & Wickham, 1979; Napier, et af., 1980). Although being in general agreement with results in the literature, it is evident that the present phenotypic correlations between I8-month mating mass and average lifetime lambing and weaning rate tended to be equal to the highest comparable estimates in the ...

  7. 20 CFR 404.212 - Computing your primary insurance amount from your average indexed monthly earnings.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Computing your primary insurance amount from... ADMINISTRATION FEDERAL OLD-AGE, SURVIVORS AND DISABILITY INSURANCE (1950- ) Computing Primary Insurance Amounts Average-Indexed-Monthly-Earnings Method of Computing Primary Insurance Amounts § 404.212 Computing your...

  8. Stochastic modelling of the monthly average maximum and minimum temperature patterns in India 1981-2015

    Science.gov (United States)

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

    2018-04-01

    The paper investigates the stochastic modelling and forecasting of monthly average maximum and minimum temperature patterns through suitable seasonal auto regressive integrated moving average (SARIMA) model for the period 1981-2015 in India. The variations and distributions of monthly maximum and minimum temperatures are analyzed through Box plots and cumulative distribution functions. The time series plot indicates that the maximum temperature series contain sharp peaks in almost all the years, while it is not true for the minimum temperature series, so both the series are modelled separately. The possible SARIMA model has been chosen based on observing autocorrelation function (ACF), partial autocorrelation function (PACF), and inverse autocorrelation function (IACF) of the logarithmic transformed temperature series. The SARIMA (1, 0, 0) × (0, 1, 1)12 model is selected for monthly average maximum and minimum temperature series based on minimum Bayesian information criteria. The model parameters are obtained using maximum-likelihood method with the help of standard error of residuals. The adequacy of the selected model is determined using correlation diagnostic checking through ACF, PACF, IACF, and p values of Ljung-Box test statistic of residuals and using normal diagnostic checking through the kernel and normal density curves of histogram and Q-Q plot. Finally, the forecasting of monthly maximum and minimum temperature patterns of India for the next 3 years has been noticed with the help of selected model.

  9. Monthly variations of diurnal rainfall in north coast of West Java Indonesia during boreal winter periods

    Science.gov (United States)

    Yulihastin, E.; Trismidianto

    2018-05-01

    Diurnal rainfall during the active monsoon period is usually associated with the highest convective activity that often triggers extreme rainfall. Investigating diurnal rainfall behavior in the north coast of West Java is important to recognize the behavioral trends of data leading to such extreme events in strategic West Java because the city of Jakarta is located in this region. Variability of diurnal rainfall during the period of active monsoon on December-January-February (DJF) composite during the 2000-2016 period was investigated using hourly rainfall data from Tropical Rainfall Measuring Mission (TRMM) 3B41RT dataset. Through the Empirical Mode Decomposition method was appears that the diurnal rain cycle during February has increased significantly in its amplitude and frequency. It is simultaneously shows that the indication of extreme rainfall events is related to diurnal rain divergences during February shown through phase shifts. The diurnal, semidiurnal, and terdiurnal cycles appear on the characteristics of the DJF composite rainfall data during the 2000-2016 period.The significant increases in amplitude occurred during February are the diurnal (IMF 3) and terdiurnal (IMF 1) of rainfall cycles.

  10. Accurate computations of monthly average daily extraterrestrial irradiation and the maximum possible sunshine duration

    International Nuclear Information System (INIS)

    Jain, P.C.

    1985-12-01

    The monthly average daily values of the extraterrestrial irradiation on a horizontal plane and the maximum possible sunshine duration are two important parameters that are frequently needed in various solar energy applications. These are generally calculated by solar scientists and engineers each time they are needed and often by using the approximate short-cut methods. Using the accurate analytical expressions developed by Spencer for the declination and the eccentricity correction factor, computations for these parameters have been made for all the latitude values from 90 deg. N to 90 deg. S at intervals of 1 deg. and are presented in a convenient tabular form. Monthly average daily values of the maximum possible sunshine duration as recorded on a Campbell Stoke's sunshine recorder are also computed and presented. These tables would avoid the need for repetitive and approximate calculations and serve as a useful ready reference for providing accurate values to the solar energy scientists and engineers

  11. Comparing Machine Learning and Decision Making Approaches to Forecast Long Lead Monthly Rainfall: The City of Vancouver, Canada

    Directory of Open Access Journals (Sweden)

    Zahra Zahmatkesh

    2018-01-01

    Full Text Available Estimating maximum possible rainfall is of great value for flood prediction and protection, particularly for regions, such as Canada, where urban and fluvial floods from extreme rainfalls have been known to be a major concern. In this study, a methodology is proposed to forecast real-time rainfall (with one month lead time using different number of spatial inputs with different orders of lags. For this purpose, two types of models are used. The first one is a machine learning data driven-based model, which uses a set of hydrologic variables as inputs, and the second one is an empirical-statistical model that employs the multi-criteria decision analysis method for rainfall forecasting. The data driven model is built based on Artificial Neural Networks (ANNs, while the developed multi-criteria decision analysis model uses Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS approach. A comprehensive set of spatially varying climate variables, including geopotential height, sea surface temperature, sea level pressure, humidity, temperature and pressure with different orders of lags is collected to form input vectors for the forecast models. Then, a feature selection method is employed to identify the most appropriate predictors. Two sets of results from the developed models, i.e., maximum daily rainfall in each month (RMAX and cumulative value of rainfall for each month (RCU, are considered as the target variables for forecast purpose. The results from both modeling approaches are compared using a number of evaluation criteria such as Nash-Sutcliffe Efficiency (NSE. The proposed models are applied for rainfall forecasting for a coastal area in Western Canada: Vancouver, British Columbia. Results indicate although data driven models such as ANNs work well for the simulation purpose, developed TOPSIS model considerably outperforms ANNs for the rainfall forecasting. ANNs show acceptable simulation performance during the

  12. Prediction of monthly average global solar radiation based on statistical distribution of clearness index

    International Nuclear Information System (INIS)

    Ayodele, T.R.; Ogunjuyigbe, A.S.O.

    2015-01-01

    In this paper, probability distribution of clearness index is proposed for the prediction of global solar radiation. First, the clearness index is obtained from the past data of global solar radiation, then, the parameters of the appropriate distribution that best fit the clearness index are determined. The global solar radiation is thereafter predicted from the clearness index using inverse transformation of the cumulative distribution function. To validate the proposed method, eight years global solar radiation data (2000–2007) of Ibadan, Nigeria are used to determine the parameters of appropriate probability distribution for clearness index. The calculated parameters are then used to predict the future monthly average global solar radiation for the following year (2008). The predicted values are compared with the measured values using four statistical tests: the Root Mean Square Error (RMSE), MAE (Mean Absolute Error), MAPE (Mean Absolute Percentage Error) and the coefficient of determination (R"2). The proposed method is also compared to the existing regression models. The results show that logistic distribution provides the best fit for clearness index of Ibadan and the proposed method is effective in predicting the monthly average global solar radiation with overall RMSE of 0.383 MJ/m"2/day, MAE of 0.295 MJ/m"2/day, MAPE of 2% and R"2 of 0.967. - Highlights: • Distribution of clearnes index is proposed for prediction of global solar radiation. • The clearness index is obtained from the past data of global solar radiation. • The parameters of distribution that best fit the clearness index are determined. • Solar radiation is predicted from the clearness index using inverse transformation. • The method is effective in predicting the monthly average global solar radiation.

  13. Assessing Intelligent Models in Forecasting Monthly Rainfall by Means of Teleconnection Patterns (Case Study: Khorasan Razavi Province

    Directory of Open Access Journals (Sweden)

    Farzaneh Nazarieh

    2016-02-01

    Full Text Available Introduction: Rainfall is affected by changes in the global sea level change, especially changes in sea surface temperature SST Sea Surface Temperature and sea level pressure SLP Sea level Pressure. Climate anomalies being related to each other at large distance is called teleconnection. As physical relationships between rainfall and teleconnection patterns are not defined clearly, we used intelligent models for forecasting rainfall. The intelligent models used in this study included Fuzzy Inference Systems, neural network and Neuro-fuzzy. In this study, first the teleconnection indices that could affect rainfall in the study area were identified. Then intelligent models were trained for rainfall forecasting. Finally, the most capable model for forecasting rainfall was presented. The study area for this research is the Khorasan Razavi Province. In order to present a model for rainfall forecasting, rainfall data of seven synoptic stations including Mashhad, Golmakan, Nishapur, Sabzevar, Kashmar, Torbate and Sharks since 1991 to 2010 were used. Materials and Methods: Based on previous studies about Teleconnection Patterns in the study area, effective Teleconnection indexes were identified. After calculating the correlation between the identified teleconnection indices and rainfall in one, two and three months ahead for all stations, fourteen teleconnection indices were chosen as inputs for intelligent models. These indices include, SLP Adriatic , SLP northern Red Sea, SLP Mediterranean Sea, SLP Aral sea, SST Sea surface temperature Labrador sea, SST Oman Sea, SST Caspian Sea, SST Persian Gulf, North Pacific pattern, SST Tropical Pacific in NINO12 and NINO3 regions, North Pacific Oscillation, Trans-Nino Index, Multivariable Enso Index. Inputs of the intelligent models include fourteen teleconnection indices, latitude and altitude of each station and their outputs are the prediction of rainfall for one, two and three months ahead. For calibration of

  14. Table for monthly average daily extraterrestrial irradiation on horizontal surface and the maximum possible sunshine duration

    International Nuclear Information System (INIS)

    Jain, P.C.

    1984-01-01

    The monthly average daily values of the extraterrestrial irradiation on a horizontal surface (H 0 ) and the maximum possible sunshine duration are two important parameters that are frequently needed in various solar energy applications. These are generally calculated by scientists each time they are needed and by using the approximate short-cut methods. Computations for these values have been made once and for all for latitude values of 60 deg. N to 60 deg. S at intervals of 1 deg. and are presented in a convenient tabular form. Values of the maximum possible sunshine duration as recorded on a Campbell Stoke's sunshine recorder are also computed and presented. These tables should avoid the need for repetition and approximate calculations and serve as a useful ready reference for solar energy scientists and engineers. (author)

  15. 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.

  16. 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.

    only SS T. Utilizing the rainfall data of Pa r tha - sarathy et al. 6 and SSTA data (5 ? 5 d e- gree grids) of Kaplan et al. 8 , it is found that the SSTA over the AS du r ing winter (DJF ? 1/0 year) in the region 15 ? 20 ?N; 60 ? 70 ?E... and b ). The corr e lations are almost zero du r ing April and May, which is not shown. SSTA during fall in the CEIO is strongly and positively corr e lated with the seasonal and monthly rai n fall. It is w eak during other months (Figure 1 c...

  17. 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.

  18. GOZCARDS Source Data for Temperature Monthly Zonal Averages on a Geodetic Latitude and Pressure Grid V1.00

    Data.gov (United States)

    National Aeronautics and Space Administration — The GOZCARDS Source Data for Temperature Monthly Zonal Averages on a Geodetic Latitude and Pressure Grid product (GozSmlpT) contains zonal means and related...

  19. 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

    in five dwellings in Greater Copenhagen, Denmark. A passive tracer gas technique (Perfluorocarbon) was used to measure ACR in a seven-month period. Considerable differences were observed between the dwellings with monthly ACRs ranging from 0.21 to 1.75 h-1. Only smaller seasonal variations, generally less...... driving forces for natural ventilation is partially compensated by changed occupant behaviour....

  20. A binary genetic programing model for teleconnection identification between global sea surface temperature and local maximum monthly rainfall events

    Science.gov (United States)

    Danandeh Mehr, Ali; Nourani, Vahid; Hrnjica, Bahrudin; Molajou, Amir

    2017-12-01

    The effectiveness of genetic programming (GP) for solving regression problems in hydrology has been recognized in recent studies. However, its capability to solve classification problems has not been sufficiently explored so far. This study develops and applies a novel classification-forecasting model, namely Binary GP (BGP), for teleconnection studies between sea surface temperature (SST) variations and maximum monthly rainfall (MMR) events. The BGP integrates certain types of data pre-processing and post-processing methods with conventional GP engine to enhance its ability to solve both regression and classification problems simultaneously. The model was trained and tested using SST series of Black Sea, Mediterranean Sea, and Red Sea as potential predictors as well as classified MMR events at two locations in Iran as predictand. Skill of the model was measured in regard to different rainfall thresholds and SST lags and compared to that of the hybrid decision tree-association rule (DTAR) model available in the literature. The results indicated that the proposed model can identify potential teleconnection signals of surrounding seas beneficial to long-term forecasting of the occurrence of the classified MMR events.

  1. A 305-year continuous monthly rainfall series for the island of Ireland (1711–2016

    Directory of Open Access Journals (Sweden)

    C. Murphy

    2018-03-01

    Full Text Available A continuous 305-year (1711–2016 monthly rainfall series (IoI_1711 is created for the Island of Ireland. The post 1850 series draws on an existing quality assured rainfall network for Ireland, while pre-1850 values come from instrumental and documentary series compiled, but not published by the UK Met Office. The series is evaluated by comparison with independent long-term observations and reconstructions of precipitation, temperature and circulation indices from across the British–Irish Isles. Strong decadal consistency of IoI_1711 with other long-term observations is evident throughout the annual, boreal spring and autumn series. Annually, the most recent decade (2006–2015 is found to be the wettest in over 300 years. The winter series is probably too dry between the 1740s and 1780s, but strong consistency with other long-term observations strengthens confidence from 1790 onwards. The IoI_1711 series has remarkably wet winters during the 1730s, concurrent with a period of strong westerly airflow, glacial advance throughout Scandinavia and near unprecedented warmth in the Central England Temperature record – all consistent with a strongly positive phase of the North Atlantic Oscillation. Unusually wet summers occurred in the 1750s, consistent with proxy (tree-ring reconstructions of summer precipitation in the region. Our analysis shows that inter-decadal variability of precipitation is much larger than previously thought, while relationships with key modes of climate variability are time-variant. The IoI_1711 series reveals statistically significant multi-centennial trends in winter (increasing and summer (decreasing seasonal precipitation. However, given uncertainties in the early winter record, the former finding should be regarded as tentative. The derived record, one of the longest continuous series in Europe, offers valuable insights for understanding multi-decadal and centennial rainfall variability in Ireland, and provides a

  2. Diffuse radiation models and monthly-average, daily, diffuse data for a wide latitude range

    International Nuclear Information System (INIS)

    Gopinathan, K.K.; Soler, A.

    1995-01-01

    Several years of measured data on global and diffuse radiation and sunshine duration for 40 widely spread locations in the latitude range 36° S to 60° N are used to develop and test models for estimating monthly-mean, daily, diffuse radiation on horizontal surfaces. Applicability of the clearness-index (K) and sunshine fraction (SSO) models for diffuse estimation and the effect of combining several variables into a single multilinear equation are tested. Correlations connecting the diffuse to global fraction (HdH) with K and SSO predict Hd values more accurately than their separate use. Among clearness-index and sunshine-fraction models, SSO models are found to have better accuracy if correlations are developed for wide latitude ranges. By including a term for declinations in the correlation, the accuracy of the estimated data can be marginally improved. The addition of latitude to the equation does not help to improve the accuracy further. (author)

  3. Modeling and forecasting monthly movement of annual average solar insolation based on the least-squares Fourier-model

    International Nuclear Information System (INIS)

    Yang, Zong-Chang

    2014-01-01

    Highlights: • Introduce a finite Fourier-series model for evaluating monthly movement of annual average solar insolation. • Present a forecast method for predicting its movement based on the extended Fourier-series model in the least-squares. • Shown its movement is well described by a low numbers of harmonics with approximately 6-term Fourier series. • Predict its movement most fitting with less than 6-term Fourier series. - Abstract: Solar insolation is one of the most important measurement parameters in many fields. Modeling and forecasting monthly movement of annual average solar insolation is of increasingly importance in areas of engineering, science and economics. In this study, Fourier-analysis employing finite Fourier-series is proposed for evaluating monthly movement of annual average solar insolation and extended in the least-squares for forecasting. The conventional Fourier analysis, which is the most common analysis method in the frequency domain, cannot be directly applied for prediction. Incorporated with the least-square method, the introduced Fourier-series model is extended to predict its movement. The extended Fourier-series forecasting model obtains its optimums Fourier coefficients in the least-square sense based on its previous monthly movements. The proposed method is applied to experiments and yields satisfying results in the different cities (states). It is indicated that monthly movement of annual average solar insolation is well described by a low numbers of harmonics with approximately 6-term Fourier series. The extended Fourier forecasting model predicts the monthly movement of annual average solar insolation most fitting with less than 6-term Fourier series

  4. Sensitivity of monthly streamflow forecasts to the quality of rainfall forcing: When do dynamical climate forecasts outperform the Ensemble Streamflow Prediction (ESP) method?

    Science.gov (United States)

    Tanguy, M.; Prudhomme, C.; Harrigan, S.; Smith, K. A.; Parry, S.

    2017-12-01

    Forecasting hydrological extremes is challenging, especially at lead times over 1 month for catchments with limited hydrological memory and variable climates. One simple way to derive monthly or seasonal hydrological forecasts is to use historical climate data to drive hydrological models using the Ensemble Streamflow Prediction (ESP) method. This gives a range of possible future streamflow given known initial hydrologic conditions alone. The degree of skill of ESP depends highly on the forecast initialisation month and catchment type. Using dynamic rainfall forecasts as driving data instead of historical data could potentially improve streamflow predictions. A lot of effort is being invested within the meteorological community to improve these forecasts. However, while recent progress shows promise (e.g. NAO in winter), the skill of these forecasts at monthly to seasonal timescales is generally still limited, and the extent to which they might lead to improved hydrological forecasts is an area of active research. Additionally, these meteorological forecasts are currently being produced at 1 month or seasonal time-steps in the UK, whereas hydrological models require forcings at daily or sub-daily time-steps. Keeping in mind these limitations of available rainfall forecasts, the objectives of this study are to find out (i) how accurate monthly dynamical rainfall forecasts need to be to outperform ESP, and (ii) how the method used to disaggregate monthly rainfall forecasts into daily rainfall time series affects results. For the first objective, synthetic rainfall time series were created by increasingly degrading observed data (proxy for a `perfect forecast') from 0 % to +/-50 % error. For the second objective, three different methods were used to disaggregate monthly rainfall data into daily time series. These were used to force a simple lumped hydrological model (GR4J) to generate streamflow predictions at a one-month lead time for over 300 catchments

  5. CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_TRMM-PFM_Edition1)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Regional Averages (ES-9) 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 ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=1998-08-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost

  6. 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].

  7. 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].

  8. 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].

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

  10. Rainfall erosivity in Europe.

    Science.gov (United States)

    Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Klik, Andreas; Rousseva, Svetla; Tadić, Melita Perčec; Michaelides, Silas; Hrabalíková, Michaela; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Beguería, Santiago; Alewell, Christine

    2015-04-01

    Rainfall is one the main drivers of soil erosion. 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 USLE model and its revised version, RUSLE. At national and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based on the best available datasets. Data have been collected from 1541 precipitation stations in all European Union (EU) Member States and Switzerland, with temporal resolutions of 5 to 60 min. The R-factor values calculated from precipitation data of different temporal resolutions were normalised to R-factor values with temporal resolutions of 30 min using linear regression functions. Precipitation time series ranged from a minimum of 5 years to a maximum of 40 years. The average time series per precipitation station is around 17.1 years, the most datasets including the first decade of the 21st century. Gaussian Process Regression (GPR) has been used to interpolate the R-factor station values to a European rainfall erosivity map at 1 km resolution. The covariates used for the R-factor interpolation were climatic data (total precipitation, seasonal precipitation, precipitation of driest/wettest months, 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 (>1000 MJ mm ha(-1) h(-1) yr(-1)) in the Mediterranean and alpine regions and the lowest (<500 MJ mm ha(-1) h(-1) yr(-1)) in the Nordic countries. The erosivity density (erosivity normalised to annual precipitation amounts) was also the highest in Mediterranean regions which implies high risk for erosive events and floods

  11. 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.

  12. A comparison of the Angstrom-type correlations and the estimation of monthly average daily global irradiation

    International Nuclear Information System (INIS)

    Jain, S.; Jain, P.C.

    1985-12-01

    Linear regression analysis of the monthly average daily global irradiation and the sunshine duration data of 8 Zambian locations has been performed using the least square technique. Good correlation (r>0.95) is obtained in all the cases showing that the Angstrom equation is valid for Zambian locations. The values of the correlation parameters thus obtained show substantial unsystematic scatter. The analysis was repeated after incorporating the effects of (i) multiple reflections of radiation between the ground and the atmosphere, and (ii) not burning of the sunshine recorder chart, into the Angstrom equation. The surface albedo measurements at Lusaka were used. The scatter in the correlation parameters was investigated by graphical representation, by regression analysis of the data of the individual stations as well as the combined data of the 8 stations. The results show that the incorporation of none of the two effects reduces the scatter significantly. A single linear equation obtained from the regression analysis of the combined data of the 8 stations is found to be appropriate for estimating the global irradiation over Zambian locations with reasonable accuracy from the sunshine duration data. (author)

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

    International Nuclear Information System (INIS)

    Bashahu, M.

    2003-01-01

    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 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 d and N/N d , Ne/8 or K 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)

  14. 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)

  15. 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.

  16. Rainfall Stochastic models

    Science.gov (United States)

    Campo, M. A.; Lopez, J. J.; Rebole, J. P.

    2012-04-01

    This work was carried out in north of Spain. San Sebastian A meteorological station, where there are available precipitation records every ten minutes was selected. Precipitation data covers from October of 1927 to September of 1997. Pulse models describe the temporal process of rainfall as a succession of rainy cells, main storm, whose origins are distributed in time according to a Poisson process and a secondary process that generates a random number of cells of rain within each storm. Among different pulse models, the Bartlett-Lewis was used. On the other hand, alternative renewal processes and Markov chains describe the way in which the process will evolve in the future depending only on the current state. Therefore they are nor dependant on past events. Two basic processes are considered when describing the occurrence of rain: the alternation of wet and dry periods and temporal distribution of rainfall in each rain event, which determines the rainwater collected in each of the intervals that make up the rain. This allows the introduction of alternative renewal processes and Markov chains of three states, where interstorm time is given by either of the two dry states, short or long. Thus, the stochastic model of Markov chains tries to reproduce the basis of pulse models: the succession of storms, each one composed for a series of rain, separated by a short interval of time without theoretical complexity of these. In a first step, we analyzed all variables involved in the sequential process of the rain: rain event duration, event duration of non-rain, average rainfall intensity in rain events, and finally, temporal distribution of rainfall within the rain event. Additionally, for pulse Bartlett-Lewis model calibration, main descriptive statistics were calculated for each month, considering the process of seasonal rainfall in each month. In a second step, both models were calibrated. Finally, synthetic series were simulated with calibration parameters; series

  17. Applications of multiscale change point detections to monthly stream flow and rainfall in Xijiang River in southern China, part I: correlation and variance

    Science.gov (United States)

    Zhu, Yuxiang; Jiang, Jianmin; Huang, Changxing; Chen, Yongqin David; Zhang, Qiang

    2018-04-01

    This article, as part I, introduces three algorithms and applies them to both series of the monthly stream flow and rainfall in Xijiang River, southern China. The three algorithms include (1) normalization of probability distribution, (2) scanning U test for change points in correlation between two time series, and (3) scanning F-test for change points in variances. The normalization algorithm adopts the quantile method to normalize data from a non-normal into the normal probability distribution. The scanning U test and F-test have three common features: grafting the classical statistics onto the wavelet algorithm, adding corrections for independence into each statistic criteria at given confidence respectively, and being almost objective and automatic detection on multiscale time scales. In addition, the coherency analyses between two series are also carried out for changes in variance. The application results show that the changes of the monthly discharge are still controlled by natural precipitation variations in Xijiang's fluvial system. Human activities disturbed the ecological balance perhaps in certain content and in shorter spells but did not violate the natural relationships of correlation and variance changes so far.

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

    African Journals Online (AJOL)

    user1

    extreme frequency); the average intensity of rainfall from extreme events ... frequency and extreme intensity indices, suggesting that extreme events are more frequent and intense during years with high rainfall. The proportion of total rainfall from ...

  19. CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_Aqua-FM4_Edition1)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Geographical Averages (ES-4) 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 ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal

  20. CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_Terra-FM1_Edition2)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Geographical Averages (ES-4) 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 ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal

  1. CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_Aqua-FM4_Edition2)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Geographical Averages (ES-4) 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 ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal

  2. CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_PFM+FM2_Edition1)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Geographical Averages (ES-4) 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 ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal

  3. CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_Aqua-FM3_Edition1)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Geographical Averages (ES-4) 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 ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal

  4. CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_PFM+FM1_Edition1)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Geographical Averages (ES-4) 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 ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal

  5. CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_FM1+FM2_Edition1)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Geographical Averages (ES-4) 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 ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal

  6. CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_FM1+FM4_Edition2)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Geographical Averages (ES-4) 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 ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal

  7. CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_Terra-FM1_Edition1)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Geographical Averages (ES-4) 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 ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal

  8. CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_FM1+FM3_Edition2)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Geographical Averages (ES-4) 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 ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal

  9. CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_Terra-FM2_Edition1-CV)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Geographical Averages (ES-4) 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 ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2006-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal

  10. CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_FM1+FM2_Edition2)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Geographical Averages (ES-4) 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 ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2002-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal

  11. CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_Terra-FM2_Edition1)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Geographical Averages (ES-4) 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 ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal

  12. CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_Aqua-FM4_Edition1-CV)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Geographical Averages (ES-4) 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 ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal

  13. CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_Aqua-FM3_Edition2)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Geographical Averages (ES-4) 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 ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal

  14. Satellite-derived ice data sets no. 2: Arctic monthly average microwave brightness temperatures and sea ice concentrations, 1973-1976

    Science.gov (United States)

    Parkinson, C. L.; Comiso, J. C.; Zwally, H. J.

    1987-01-01

    A summary data set for four years (mid 70's) of Arctic sea ice conditions is available on magnetic tape. The data include monthly and yearly averaged Nimbus 5 electrically scanning microwave radiometer (ESMR) brightness temperatures, an ice concentration parameter derived from the brightness temperatures, monthly climatological surface air temperatures, and monthly climatological sea level pressures. All data matrices are applied to 293 by 293 grids that cover a polar stereographic map enclosing the 50 deg N latitude circle. The grid size varies from about 32 X 32 km at the poles to about 28 X 28 km at 50 deg N. The ice concentration parameter is calculated assuming that the field of view contains only open water and first-year ice with an ice emissivity of 0.92. To account for the presence of multiyear ice, a nomogram is provided relating the ice concentration parameter, the total ice concentration, and the fraction of the ice cover which is multiyear ice.

  15. CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_Aqua-FM3_Edition1)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Regional Averages (ES-9) 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 ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost

  16. CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CERES:CER_ES9_PFM+FM1_Edition2)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Regional Averages (ES-9) 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 ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost

  17. CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_Terra-FM2_Edition1)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Regional Averages (ES-9) 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 ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost

  18. CERES ERBE-like Monthly Regional Averages (ES-9) in HDF ( CER_ES9_Aqua-FM3_Edition1-CV)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Regional Averages (ES-9) 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 ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2006-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost

  19. CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_PFM+FM1_Edition1)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Regional Averages (ES-9) 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 ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost

  20. CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_FM1+FM4_Edition2)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Regional Averages (ES-9) 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 ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost

  1. CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_Aqua-FM4_Edition2)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Regional Averages (ES-9) 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 ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost

  2. CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_PFM+FM2_Edition1)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Regional Averages (ES-9) 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 ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost

  3. CERES ERBE-like Monthly Regional Averages (ES-9) in HDF ( CER_ES9_Terra-FM1_Edition1-CV)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Regional Averages (ES-9) 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 ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2006-09-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost

  4. CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_Aqua-FM4_Edition1)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Regional Averages (ES-9) 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 ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost

  5. CERES ERBE-like Monthly Regional Averages (ES-9) in HDF ( CER_ES9_Aqua-FM4_Edition1-CV)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Regional Averages (ES-9) 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 ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost

  6. CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_Terra-FM1_Edition1)

    Science.gov (United States)

    Wielicki, Bruce A. (Principal Investigator)

    The ERBE-like Monthly Regional Averages (ES-9) 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 ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost

  7. 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.

  8. FROM RAINFALL DATA

    Directory of Open Access Journals (Sweden)

    Sisuru Sendanayake

    2015-01-01

    Full Text Available There are many correlations developed to predict incident solar radiation at a givenlocation developed based on geographical and meteorological parameters. However, allcorrelations depend on accurate measurement and availability of weather data such assunshine duration, cloud cover, relative humidity, maximum and minimumtemperatures etc, which essentially is a costly exercise in terms of equipment andlabour. Sri Lanka being a tropical island of latitudinal change of only 30 along thelength of the country, the meteorological factors govern the amount of incidentradiation. Considering the cloud formation and wind patterns over Sri Lanka as well asthe seasonal rainfall patterns, it can be observed that the mean number of rainy dayscan be used to predict the monthly average daily global radiation which can be used forcalculations in solar related activities conveniently.

  9. Rainfall erosivity map for Ghana

    International Nuclear Information System (INIS)

    Oduro Afriyie, K.

    1995-10-01

    Monthly rainfall data, spanning over a period of more than thirty years, were used to compute rainfall erosivity indices for various stations in Ghana, using the Fournier index, c, defined as p 2 /P, where p is the rainfall amount in the wettest month and P is the annual rainfall amount. Values of the rainfall erosivity indices ranged from 24.5 mm at Sunyani in the mid-portion of Ghana to 180.9 mm at Axim in the south western coastal portion. The indices were used to construct a rainfall erosivity map for the country. The map revealed that Ghana may be broadly divided into five major erosion risk zones. The middle sector of Ghana is generally in the low erosion risk zone; the northern sector is in the moderate to severe erosion risk zone, while the coastal sector is in the severe to extreme severe erosion risk zone. (author). 11 refs, 1 fig., 1 tab

  10. Rainfall Modification by Urban Areas: New Perspectives from TRMM

    Science.gov (United States)

    Shepherd, J. Marshall; Pierce, Harold F.; Negri, Andrew

    2002-01-01

    Data from the Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. 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 changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded 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. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. Future work is extending the investigation to Phoenix, Arizona, an arid U.S. city, and several international cities like Mexico City, Johannesburg, and Brasilia. The study establishes the possibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.

  11. 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.

  12. Trends of rainfall regime in Peninsular Malaysia during northeast and southwest monsoons

    Science.gov (United States)

    Chooi Tan, Kok

    2018-04-01

    The trends of rainfall regime in Peninsular Malaysia is mainly affected by the seasonal monsoon. The aim of this study is to investigate the impact of northeast and southwest monsoons on the monthly rainfall patterns over Badenoch Estate, Kedah. In addition, the synoptic maps of wind vector also being developed to identify the wind pattern over Peninsular Malaysia from 2007 – 2016. On the other hand, the archived daily rainfall data is acquired from Malaysian Meteorological Department. The temporal and trends of the monthly and annual rainfall over the study area have been analysed from 2007 to 2016. Overall, the average annual precipitation over the study area from 2007 to 2016 recorded by rain gauge is 2562.35 mm per year.

  13. 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...

  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. 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

  16. Influence of southern oscillation on autumn rainfall in Iran (1951-2011)

    Science.gov (United States)

    Roghani, Rabbaneh; Soltani, Saeid; Bashari, Hossein

    2016-04-01

    This study aimed to investigate the relationships between southern oscillation and autumn (October-December) rainfall in Iran. It also sought to identify the possible physical mechanisms involved in the mentioned relationships by analyzing observational atmospheric data. Analyses were based on monthly rainfall data from 50 synoptic stations with at least 35 years of records up to the end of 2011. Autumn rainfall time series were grouped by the average Southern Oscillation Index (SOI) and SOI phase methods. Significant differences between rainfall groups in each method were assessed by Kruskal-Wallis and Kolmogorov-Smirnov non-parametric tests. Their relationships were also validated using the linear error in probability space (LEPS) test. The results showed that average SOI and SOI phases during July-September were related with autumn rainfall in some regions located in the west and northwest of Iran, west coasts of the Caspian Sea and southern Alborz Mountains. The El Niño (negative) and La Niña (positive) phases were associated with increased and decreased autumn rainfall, respectively. Our findings also demonstrated the persistence of Southern Pacific Ocean's pressure signals on autumn rainfall in Iran. Geopotential height patterns were totally different in the selected El Niño and La Niña years over Iran. During the El Niño years, a cyclone was formed over the north of Iran and an anticyclone existed over the Mediterranean Sea. During La Niña years, the cyclone shifted towards the Mediterranean Sea and an anticyclone developed over Iran. While these El Niño conditions increased autumn rainfall in Iran, the opposite conditions during the La Niña phase decreased rainfall in the country. In conclusion, development of rainfall prediction models based on the SOI can facilitate agricultural and water resources management in Iran.

  17. 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.

    2018-02-01

    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.

  18. 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.

  19. Predicting watershed acidification under alternate rainfall conditions

    International Nuclear Information System (INIS)

    Huntington, T.G.

    1996-01-01

    The effect of alternate rainfall scenarios on acidification of a forested watershed subjected to chronic acidic deposition was assessed using the model of acidification of groundwater in catchments (MAGIC). The model was calibrated at the Panola Mountain Research Watershed, near Atlanta, Georgia, USA using measured soil properties, wet and dry deposition, and modeled hydrologic routing. Model forecast simulations were evaluated to compare alternate temporal averaging of rainfall inputs and variations in rainfall amount and seasonal distribution. Soil water alkalinity was predicted to decrease to substantially lower concentrations under lower rainfall compared with current or higher rainfall conditions. Soil water alkalinity was also predicted to decrease to lower levels when the majority of rainfall occurred during the growing season compared with other rainfall distributions. Changes in rainfall distribution that result in decreases in net soil water flux will temporarily delay acidification. Ultimately, however, decreased soilwater flux will result in larger increases in soil-adsorbed sulfur and soil-water sulfate concentrations and decreases in alkalinity when compared to higher water flux conditions. Potential climate change resulting in significant changes in rainfall amounts, seasonal distributions of rainfall, or evapotranspiration will change net soil water flux and, consequently, will affect the dynamics of the acidification response to continued sulfate loading. 29 refs., 7 figs., 4 tabs

  20. Effect of rainfall on cropping pattern in mid Himalayan region ...

    African Journals Online (AJOL)

    The analysis of effect of rainfall during the last 20 years is needed to evaluate cropping pattern in the rain-fed region. In this study, trends in annual, seasonal and monthly rainfall of district of Himachal Pradesh in India over the past 20 years were examined. The annual rainfall varies from 863.3 to 1470.0 mm. During the ...

  1. 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.

  2. Spatiotemporal Interpolation of Rainfall by Combining BME Theory and Satellite Rainfall Estimates

    Directory of Open Access Journals (Sweden)

    Tingting Shi

    2015-09-01

    Full Text Available The accurate assessment of spatiotemporal rainfall variability is a crucial and challenging task in many hydrological applications, mainly due to the lack of a sufficient number of rain gauges. The purpose of the present study is to investigate the spatiotemporal variations of annual and monthly rainfall over Fujian province in China by combining the Bayesian maximum entropy (BME method and satellite rainfall estimates. Specifically, based on annual and monthly rainfall data at 20 meteorological stations from 2000 to 2012, (1 the BME method with Tropical Rainfall Measuring Mission (TRMM estimates considered as soft data, (2 ordinary kriging (OK and (3 cokriging (CK were employed to model the spatiotemporal variations of rainfall in Fujian province. Subsequently, the performance of these methods was evaluated using cross-validation statistics. The results demonstrated that BME with TRMM as soft data (BME-TRMM performed better than the other two methods, generating rainfall maps that represented the local rainfall disparities in a more realistic manner. Of the three interpolation (mapping methods, the mean absolute error (MAE and root mean square error (RMSE values of the BME-TRMM method were the smallest. In conclusion, the BME-TRMM method improved spatiotemporal rainfall modeling and mapping by integrating hard data and soft information. Lastly, the study identified new opportunities concerning the application of TRMM rainfall estimates.

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

    Science.gov (United States)

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

    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 rainfall- related extremes such as, maximum daily rainfall, number of rainy days, average rainfall intensity, heavy rainfall days, extreme rainfall days, and precipitation concentration index in the east coast of peninsular Malaysia. Recent 40 years (1971-2010) rainfall records from 54 stations along the east coast of peninsular Malaysia have been analyzed using the non-parametric Mann-Kendall test and the Sen's slope method. The Monte Carlo simulation technique has been used to determine the field significance of the regional trends. The results showed that there was a substantial increase in the annual rainfall as well as the rainfall during the monsoon period. Also, there was an increase in the number of heavy rainfall days during the past four decades.

  4. 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.

  5. Rainfall over Friuli-Venezia Giulia: High amounts and strong geographical gradients

    Science.gov (United States)

    Ceschia, M.; Micheletti, St.; Carniel, R.

    1991-12-01

    The precipitation distribution over Friuli-Venezia Giulia — the easternmost region of Northern Italy extending from the Adriatic Sea to the Alps — has been studied. Monthly rainfall data over the region and the bordering areas of Veneto and Slovenia during the period from 1951 to 1986 have been analyzed by standard statistical methods, including cluster analysis. The overall results emphasize a distribution with rainfall increasing from the sea to the prealpine areas. The highest precipitations were recorded over the Musi-Canin range, with average values exceeding 3 200 mm per year. Noteworthy is the unforeseen subdivision of the region by the clustering procedure by means of the Angot index.

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

    Directory of Open Access Journals (Sweden)

    N. Zambatis

    1995-08-01

    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.

  7. Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

    Science.gov (United States)

    Tesfaye Ayehu, Getachew; Tadesse, Tsegaye; Gessesse, Berhan; Dinku, Tufa

    2018-04-01

    Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor) ground observations) or through integrating with rain gauge measurements. In this study, the potential of a newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall product has been evaluated in comparison to rain gauge data over the Upper Blue Nile basin in Ethiopia for the period of 2000 to 2015. In addition, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT 3) and the African Rainfall Climatology (ARC 2) products have been used as a benchmark and compared with CHIRPS. From the overall analysis at dekadal (10 days) and monthly temporal scale, CHIRPS exhibited better performance in comparison to TAMSAT 3 and ARC 2 products. An evaluation based on categorical/volumetric and continuous statistics indicated that CHIRPS has the greatest skills in detecting rainfall events (POD = 0.99, 1.00) and measure of volumetric rainfall (VHI = 1.00, 1.00), the highest correlation coefficients (r = 0.81, 0.88), better bias values (0.96, 0.96), and the lowest RMSE (28.45 mm dekad-1, 59.03 mm month-1) than TAMSAT 3 and ARC 2 products at dekadal and monthly analysis, respectively. CHIRPS overestimates the frequency of rainfall occurrence (up to 31 % at dekadal scale), although the volume of rainfall recorded during those events was very small. Indeed, TAMSAT 3 has shown a comparable performance with that of the CHIRPS product, mainly with regard to bias. The ARC 2 product was found to have the weakest performance underestimating rain gauge observed rainfall by

  8. CORRELATION BETWEEN RAINFALL PATTERNS AND THE WATER TABLE IN THE GENERAL SEPARATIONS AREA OF THE SAVANNAH RIVER SITE

    International Nuclear Information System (INIS)

    Smith, C.

    2009-01-01

    The objective of the study was to evaluate rainfall and water table elevation data in search of a correlation that could be used to understand and predict water elevation changes. This information will be useful in placing screen zones for future monitoring wells and operations of groundwater treatment units. Fifteen wells in the General Separations Area (GSA) at Savannah River Site were evaluated from 1986 through 2001. The study revealed that the water table does respond to rainfall with minimal delay. (Water level information was available monthly, which restricted the ability to evaluate a shorter delay period.) Water elevations were found to be related to the cumulative sum (Q-Delta Sum) of the difference between the average rainfall for a specific month and the actual rainfall for that month, calculated from an arbitrary starting point. Water table elevations could also be correlated between wells, but using the right well for correlation was very important. The strongest correlation utilized a quadratic equation that takes into account the rainfall in a specific area and the rainfall from an adjacent area that contributes through a horizontal flow. Specific values vary from well to well as a result of geometry and underground variations. R2's for the best models ranged up to 0.96. The data in the report references only GSA wells but other wells (including confined water tables) on the site have been observed to return similar water level fluctuation patterns

  9. Markov chain analysis of the rainfall patterns of five geographical locations in the south eastern coast of Ghana

    Directory of Open Access Journals (Sweden)

    Meshach Tettey

    2017-08-01

    Full Text Available Abstract This study develops an objective rainfall pattern assessment through Markov chain analysis using daily rainfall data from 1980 to 2010, a period of 30 years, for five cities or towns along the south eastern coastal belt of Ghana; Cape Coast, Accra, Akuse, Akatsi and Keta. Transition matrices were computed for each town and each month using the conditional probability of rain or no rain on a particular day given that it rained or did not rain on the previous day. The steady state transition matrices and the steady state probability vectors were also computed for each town and each month. It was found that, the rainy or dry season pattern observed using the monthly steady state rainfall vectors tended to reflect the monthly rainfall time series trajectory. Overall, the probability of rain on any day was low to average: Keta 0.227, Akuse 0.382, Accra 0.467, Cape Coast, 0.50 and Akatsi 0.50. In particular, for Accra, the rainy season was observed to be in the months of May to June and September to October. We also determined that the probability of rainfall generally tended to increase from east to west along the south eastern coast of Ghana.

  10. Continuous Sub-daily Rainfall Simulation for Regional Flood Risk Assessment - Modelling of Spatio-temporal Correlation Structure of Extreme Precipitation in the Austrian Alps

    Science.gov (United States)

    Salinas, J. L.; Nester, T.; Komma, J.; Bloeschl, G.

    2017-12-01

    Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of observed rainfall characteristics, such as regional intensity-duration-frequency curves, and spatial and temporal correlations is necessary to adequately model the magnitude and frequency of the flood peaks, by reproducing antecedent soil moisture conditions before extreme rainfall events, and joint probability of flood waves at confluences. In this work, a modification of the model presented by Bardossy and Platte (1992), where precipitation is first modeled on a station basis as a multivariate autoregressive model (mAr) in a Normal space. The spatial and temporal correlation structures are imposed in the Normal space, allowing for a different temporal autocorrelation parameter for each station, and simultaneously ensuring the positive-definiteness of the correlation matrix of the mAr errors. The Normal rainfall is then transformed to a Gamma-distributed space, with parameters varying monthly according to a sinusoidal function, in order to adapt to the observed rainfall seasonality. One of the main differences with the original model is the simulation time-step, reduced from 24h to 6h. Due to a larger availability of daily rainfall data, as opposite to sub-daily (e.g. hourly), the parameters of the Gamma distributions are calibrated to reproduce simultaneously a series of daily rainfall characteristics (mean daily rainfall, standard deviations of daily rainfall, and 24h intensity-duration-frequency [IDF] curves), as well as other aggregated rainfall measures (mean annual rainfall, and monthly rainfall). The calibration of the spatial and temporal correlation parameters is performed in a way that the catchment-averaged IDF curves aggregated at different temporal scales fit the measured ones. The rainfall model is used to generate 10.000 years of synthetic

  11. Weather model performance on extreme rainfall events simulation's over Western Iberian Peninsula

    Science.gov (United States)

    Pereira, S. C.; Carvalho, A. C.; Ferreira, J.; Nunes, J. P.; Kaiser, J. J.; Rocha, A.

    2012-08-01

    This study evaluates the performance of the WRF-ARW numerical weather model in simulating the spatial and temporal patterns of an extreme rainfall period over a complex orographic region in north-central Portugal. The analysis was performed for the December month of 2009, during the Portugal Mainland rainy season. The heavy rainfall to extreme heavy rainfall periods were due to several low surface pressure's systems associated with frontal surfaces. The total amount of precipitation for December exceeded, in average, the climatological mean for the 1971-2000 time period in +89 mm, varying from 190 mm (south part of the country) to 1175 mm (north part of the country). Three model runs were conducted to assess possible improvements in model performance: (1) the WRF-ARW is forced with the initial fields from a global domain model (RunRef); (2) data assimilation for a specific location (RunObsN) is included; (3) nudging is used to adjust the analysis field (RunGridN). Model performance was evaluated against an observed hourly precipitation dataset of 15 rainfall stations using several statistical parameters. The WRF-ARW model reproduced well the temporal rainfall patterns but tended to overestimate precipitation amounts. The RunGridN simulation provided the best results but model performance of the other two runs was good too, so that the selected extreme rainfall episode was successfully reproduced.

  12. Darfur: rainfall and conflict

    Science.gov (United States)

    Kevane, Michael; Gray, Leslie

    2008-07-01

    Data on rainfall patterns only weakly corroborate the claim that climate change explains the Darfur conflict that began in 2003 and has claimed more than 200 000 lives and displaced more than two million persons. Rainfall in Darfur did not decline significantly in the years prior to the eruption of major conflict in 2003; rainfall exhibited a flat trend in the thirty years preceding the conflict (1972 2002). The rainfall evidence suggests instead a break around 1971. Rainfall is basically stationary over the pre- and post-1971 sub-periods. The break is larger for the more northerly rainfall stations, and is less noticeable for En Nahud. Rainfall in Darfur did indeed decline, but the decline happened over 30 years before the conflict erupted. Preliminary analysis suggests little merit to the proposition that a structural break several decades earlier is a reasonable predictor of the outbreak of large-scale civil conflict in Africa.

  13. Darfur: rainfall and conflict

    International Nuclear Information System (INIS)

    Kevane, Michael; Gray, Leslie

    2008-01-01

    Data on rainfall patterns only weakly corroborate the claim that climate change explains the Darfur conflict that began in 2003 and has claimed more than 200 000 lives and displaced more than two million persons. Rainfall in Darfur did not decline significantly in the years prior to the eruption of major conflict in 2003; rainfall exhibited a flat trend in the thirty years preceding the conflict (1972-2002). The rainfall evidence suggests instead a break around 1971. Rainfall is basically stationary over the pre- and post-1971 sub-periods. The break is larger for the more northerly rainfall stations, and is less noticeable for En Nahud. Rainfall in Darfur did indeed decline, but the decline happened over 30 years before the conflict erupted. Preliminary analysis suggests little merit to the proposition that a structural break several decades earlier is a reasonable predictor of the outbreak of large-scale civil conflict in Africa

  14. Rainfall Product Evaluation for the TRMM Ground Validation Program

    Science.gov (United States)

    Amitai, E.; Wolff, D. B.; Robinson, M.; Silberstein, D. S.; Marks, D. A.; Kulie, M. S.; Fisher, B.; Einaudi, Franco (Technical Monitor)

    2000-01-01

    Evaluation of the Tropical Rainfall Measuring Mission (TRMM) satellite observations is conducted through a comprehensive Ground Validation (GV) Program. Standardized instantaneous and monthly rainfall products are routinely generated using quality-controlled ground based radar data from four primary GV sites. As part of the TRMM GV program, effort is being made to evaluate these GV products and to determine the uncertainties of the rainfall estimates. The evaluation effort is based on comparison to rain gauge data. The variance between the gauge measurement and the true averaged rain amount within the radar pixel is a limiting factor in the evaluation process. While monthly estimates are relatively simple to evaluate, the evaluation of the instantaneous products are much more of a challenge. Scattegrams of point comparisons between radar and rain gauges are extremely noisy for several reasons (e.g. sample volume discrepancies, timing and navigation mismatches, variability of Z(sub e)-R relationships), and therefore useless for evaluating the estimates. Several alternative methods, such as the analysis of the distribution of rain volume by rain rate as derived from gauge intensities and from reflectivities above the gauge network will be presented. Alternative procedures to increase the accuracy of the estimates and to reduce their uncertainties also will be discussed.

  15. Fallout total. beta. radioactivity in every rainfall in Aichi prefecture

    Energy Technology Data Exchange (ETDEWEB)

    Ohnuma, Shoko; Chaya, Kunio; Shimizu, Michihiko; Tomita, Ban-ichi; Hamamura, Norikatsu (Aichi Prefectural Inst. of Public Health, Nagoya (Japan))

    1983-01-01

    Fallout total ..beta.. radioactivity was measured in every rainfall in the period from 1962 to 1981. Maximum value of monthly fallout was 462 mCi/km/sup 2/ at May 1966. Considering changes of monthly fallout, it was assumed that these 20 years were divided to 3 periods and these changes reflected the history of nuclear explosion tests in the world. Maximum value of annual fallout was 1,154 mCi/km/sup 2/ in 1963. Average of annual fallout in 1973 to 1981 was about 1/40 of maximum value. It was confirmed that changes of annual fallout were almost corresponded with changes of annual deposition of /sup 90/Sr and /sup 137/Cs in Tokyo reported by Katsuragi et al. Estimating the staying time of /sup 90/Sr and /sup 137/Cs at Stratosphere by the use of annual fallout of total ..beta.. radioactivity and annual deposition of these radionuclides, /sup 90/Sr was 1.3 years and /sup 137/Cs was 1.5 years. Also, annual correlation between monthly fallout and monthly rainfall was regarded as significant in only 6 years of these 20 years.

  16. Fallout total β radioactivity in every rainfall in Aichi prefecture

    International Nuclear Information System (INIS)

    Ohnuma, Shoko; Chaya, Kunio; Shimizu, Michihiko; Tomita, Ban-ichi; Hamamura, Norikatsu

    1983-01-01

    Fallout total β radioactivity was measured in every rainfall in the period from 1962 to 1981. Maximum value of monthly fallout was 462 mCi/km 2 at May 1966. Considering changes of monthly fallout, it was assumed that these 20 years were divided to 3 periods and these changes reflected the history of nuclear explosion tests in the world. Maximum value of annual fallout was 1,154 mCi/km 2 in 1963. Average of annual fallout in 1973 to 1981 was about 1/40 of maximum value. It was confirmed that changes of annual fallout were almost corresponded with changes of annual deposition of 90 Sr and 137 Cs in Tokyo reported by Katsuragi et al. Estimating the staying time of 90 Sr and 137 Cs at Stratosphere by the use of annual fallout of total β radioactivity and annual deposition of these radionuclides, 90 Sr was 1.3 years and 137 Cs was 1.5 years. Also, annual correlation between monthly fallout and monthly rainfall was regarded as significant in only 6 years of these 20 years. (author)

  17. Detecting Climate Variability in Tropical Rainfall

    Science.gov (United States)

    Berg, W.

    2004-05-01

    A number of satellite and merged satellite/in-situ rainfall products have been developed extending as far back as 1979. While the availability of global rainfall data covering over two decades and encompassing two major El Niño events is a valuable resource for a variety of climate studies, significant differences exist between many of these products. Unfortunately, issues such as availability often determine the use of a product for a given application instead of an understanding of the strengths and weaknesses of the various products. Significant efforts have been made to address the impact of sparse sampling by satellite sensors of variable rainfall processes by merging various satellite and in-situ rainfall products. These combine high spatial and temporal frequency satellite infrared data with higher quality passive microwave observations and rain gauge observations. Combining such an approach with spatial and temporal averaging of the data can reduce the large random errors inherent in satellite rainfall estimates to very small levels. Unfortunately, systematic biases can and do result in artificial climate signals due to the underconstrained nature of the rainfall retrieval problem. Because all satellite retrieval algorithms make assumptions regarding the cloud structure and microphysical properties, systematic changes in these assumed parameters between regions and/or times results in regional and/or temporal biases in the rainfall estimates. These biases tend to be relatively small compared to random errors in the retrieval, however, when random errors are reduced through spatial and temporal averaging for climate applications, they become the dominant source of error. Whether or not such biases impact the results for climate studies is very much dependent on the application. For example, all of the existing satellite rainfall products capture the increased rainfall in the east Pacific associated with El Niño, however, the resulting tropical response to

  18. Sensitivity of point scale surface runoff predictions to rainfall resolution

    Directory of Open Access Journals (Sweden)

    A. J. Hearman

    2007-01-01

    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 at the point scale. The bounded random cascade model, parameterized to three locations in Western Australia, 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 partitioned water into infiltration excess, infiltration, storage, deep drainage, saturation excess and surface runoff, where the fluxes into and out of the soil store were controlled by thresholds. The results of the numerical modelling were scaled by relating soil infiltration properties to soil draining properties, and in turn, relating these to average storm intensities. 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 all three rainfall locations tested. For soils susceptible to both infiltration excess and saturation excess, total runoff sensitivity was scaled by relating drainage coefficients to average storm intensities (g* and parameter ranges where predicted runoff was dominated by infiltration excess or saturation excess depending on the resolution of rainfall data were determined (ln g*<2. Infiltration excess predicted from high resolution rainfall was short and intense, whereas saturation excess produced from low resolution rainfall was more constant and less intense. This has important implications for the accuracy of current hydrological models that use time

  19. Persistence Characteristics of Australian Rainfall Anomalies

    Science.gov (United States)

    Simmonds, Ian; Hope, Pandora

    1997-05-01

    Using 79 years (1913-1991) of Australian monthly precipitation data we examined the nature of the persistence of rainfall anomalies. Analyses were performed for four climate regions covering the country, as well as for the entire Australian continent. We show that rainfall over these regions has high temporal variability and that annual rainfall amounts over all five sectors vary in phase and are, with the exception of the north-west region, significantly correlated with the Southern Oscillation Index (SOI). These relationships were particularly strong during the spring season.It is demonstrated that Australian rainfall exhibits statistically significant persistence on monthly, seasonal, and (to a limited extent) annual time-scales, up to lags of 3 months and one season and 1 year. The persistence showed strong seasonal dependence, with each of the five regions showing memory out to 4 or 5 months from winter and spring. Many aspects of climate in the Australasian region are known to have undergone considerable changes about 1950. We show this to be true for persistence also; its characteristics identified for the entire record were present during the 1951--1980 period, but virtually disappeared in the previous 30-year period.Much of the seasonal distribution of rainfall persistence on monthly time-scales, particularly in the east, is due to the influence of the SOI. However, most of the persistence identified in winter and spring in the north-west is independent of the ENSO phenomenon.Rainfall anomalies following extreme dry and wet months, seasons and years (lowest and highest two deciles) persisted more than would be expected by chance. For monthly extreme events this was more marked in the winter semester for the wet events, except in the south-east region. In general, less persistence was found for the extreme seasons. Although the persistence of dry years was less than would have been expected by chance, the wet years appear to display persistence.

  20. 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

  1. Modified Fournier and rainfall concentration indices, as estimators of soil erosion factors, Sinaloa, Mexico; Indices de Fournier modificado y de concentracion de la precipitacion, como estimadores del factor de riesgo de la erosion, en Sinaloa, Mexico

    Energy Technology Data Exchange (ETDEWEB)

    Velasco, I.; Costes, G.

    2009-07-01

    Some of the parameters which characterize the climatic zones, identified as Hydric Regime Indices are the rainfall concentration index ICP), and the Modified Fournier index (IFM), which allow to evaluate, in terms of the rainfall behavior, the risk of soil erosion. The conventional ICP rank of variation foes from uniforms to irregular (8 to 100%). The calculation of this index must be done for every year and then the average is the value to use. IFM considers the monthly rainfall of the most humid month of the year in relation to the other months. This index characterizes the rainfall aggressiveness, and their conventional values go from very low (0 to 60), until very high (more than 160), and mainly mean the vulnerability and risk to soil loss. (Author) 2 refs.

  2. A Two-year Record of Daily Rainfall Isotopes from Fiji: Implications for Reconstructing Precipitation from Speleothem δ18O

    Science.gov (United States)

    Brett, M.; Mattey, D.; Stephens, M.

    2015-12-01

    Oxygen isotopes in speleothem provide opportunities to construct precisely dated records of palaeoclimate variability, underpinned by an understanding of both the regional climate and local controls on isotopes in rainfall and groundwater. For tropical islands, a potential means to reconstruct past rainfall variability is to exploit the generally high correlation between rainfall amount and δ18O: the 'amount effect'. The GNIP program provides δ18O data at monthly resolution for several tropical Pacific islands but there are few data for precipitation isotopes at daily resolution, for investigating the amount effect over different timescales in a tropical maritime setting. Timescales are important since meteoric water feeding a speleothem has undergone storage and mixing in the aquifer system and understanding how the isotope amount effect is preserved in aquifer recharge has fundamental implications on the interpretation of speleothem δ18O in terms of palaeo-precipitation. The islands of Fiji host speleothem caves. Seasonal precipitation is related to the movement of the South Pacific Convergence Zone, and interannual variations in rainfall are coupled to ENSO behaviour. Individual rainfall events are stratiform or convective, with proximal moisture sources. We have daily resolution isotope data for rainfall collected at the University of the South Pacific in Suva, covering every rain event in 2012 and 2013. δ18O varies between -18‰ and +3‰ with the annual weighted averages at -7.6‰ and -6.8‰ respectively, while total recorded rainfall amount is similar in both years. We shall present analysis of our data compared with GNIP, meteorological data and back trajectory analyses to demonstrate the nature of the relationship between rainfall amount and isotopic signatures over this short timescale. Comparison with GNIP data for 2012-13 will shed light on the origin of the amount effect at monthly and seasonal timescales in convective, maritime, tropical

  3. 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

  4. impacts of rainfall and forest cover change on runoff in small ...

    African Journals Online (AJOL)

    the relationship between rainfall and runoff in the two catchments has changed. Furthermore .... The monthly rainfall data for Namadzi catchment that was used in this .... land cover change with a big jump of forest planted after the 1990s. Fig.

  5. 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.

  6. 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.

  7. Temporal and spatial variations of rainfall erosivity in Southern Taiwan

    Science.gov (United States)

    Lee, Ming-Hsi; Lin, Huan-Hsuan; Chu, Chun-Kuang

    2014-05-01

    Soil erosion models are essential in developing effective soil and water resource conservation strategies. Soil erosion is generally evaluated using the Universal Soil Loss Equation (USLE) with an appropriate regional scale description. Among factors in the USLE model, the rainfall erosivity index (R) provides one of the clearest indications of the effects of climate change. Accurate estimation of rainfall erosivity requires continuous rainfall data; however, such data rarely demonstrate good spatial and temporal coverage. The data set consisted of 9240 storm events for the period 1993 to 2011, monitored by 27 rainfall stations of the Central Weather Bureau (CWB) in southern Taiwan, was used to analyze the temporal-spatial variations of rainfall erosivity. The spatial distribution map was plotted based on rainfall erosivity by the Kriging interpolation method. Results indicated that rainfall erosivity is mainly concentrated in rainy season from June to November typically contributed 90% of the yearly R factor. The temporal variations of monthly rainfall erosivity during June to November and annual rainfall erosivity have increasing trend from 1993 to 2011. There is an increasing trend from southwest to northeast in spatial distribution of rainfall erosivity in southern Taiwan. The results further indicated that there is a higher relationship between elevation and rainfall erosivity. The method developed in this study may also be useful for sediment disasters on Climate Change.

  8. Distributional changes in rainfall and river flow in Sarawak, Malaysia

    Science.gov (United States)

    Sa'adi, Zulfaqar; Shahid, Shamsuddin; Ismail, Tarmizi; Chung, Eun-Sung; Wang, Xiao-Jun

    2017-11-01

    Climate change may not change the rainfall mean, but the variability and extremes. Therefore, it is required to explore the possible distributional changes of rainfall characteristics over time. The objective of present study is to assess the distributional changes in annual and northeast monsoon rainfall (November-January) and river flow in Sarawak where small changes in rainfall or river flow variability/distribution may have severe implications on ecology and agriculture. A quantile regression-based approach was used to assess the changes of scale and location of empirical probability density function over the period 1980-2014 at 31 observational stations. The results indicate that diverse variation patterns exist at all stations for annual rainfall but mainly increasing quantile trend at the lowers, and higher quantiles for the month of January and December. The significant increase in annual rainfall is found mostly in the north and central-coastal region and monsoon month rainfalls in the interior and north of Sarawak. Trends in river flow data show that changes in rainfall distribution have affected higher quantiles of river flow in monsoon months at some of the basins and therefore more flooding. The study reveals that quantile trend can provide more information of rainfall change which may be useful for climate change mitigation and adaptation planning.

  9. Rainfall variability and floods occurrence in the city of Bamenda (Northwest of Cameroon

    Directory of Open Access Journals (Sweden)

    Frederic Saha

    2017-06-01

    Full Text Available This study is based on analysis of rainfall data from 1951-2010 collected at the climatic station of Bamenda. We also use the results of a questionnaire survey applied to 172 households in at-risk neighborhoods. The inventory of some cases of flooding that occurred in the city of Bamenda was done through focus groups. The appreciation of the socio-economic and demographic environment is based on surveys among Cameroonian Households by the National Institute of Statistics (NIS and General Census of Population and Housing. Statistical examination revealed that annual rainfall in the city of Bamenda experienced a break in 1958. This break buckled the wettest decade of the series. After three decades of worsening, rainfall is experiencing rising since early 1990. The average profile of the annual distribution of rainfall shows a concentration of over 53% in 03 months (July, August and September. During these three months, the rivers of the city know their flood flows and populations in the valleys are affected. The analysis of the annual number of rainy days shows a downward trend and an increase of extreme rainfall event frequency (≥50mm in 24h. It is also apparent that more and more years are experiencing erratic distribution of their precipitation. Then, the perception of people is significantly reduced. Subsistence activities are also affected and development is facing new subtleties. In conclusion, the rainfall experienced strong variability in the city of Bamenda. This situation reinforces the risk of flooding by increasing flood water and increasing the vulnerability of populations.

  10. Rainfall: State of the Science

    Science.gov (United States)

    Testik, Firat Y.; Gebremichael, Mekonnen

    Rainfall: State of the Science offers the most up-to-date knowledge on the fundamental and practical aspects of rainfall. Each chapter, self-contained and written by prominent scientists in their respective fields, provides three forms of information: fundamental principles, detailed overview of current knowledge and description of existing methods, and emerging techniques and future research directions. The book discusses • Rainfall microphysics: raindrop morphodynamics, interactions, size distribution, and evolution • Rainfall measurement and estimation: ground-based direct measurement (disdrometer and rain gauge), weather radar rainfall estimation, polarimetric radar rainfall estimation, and satellite rainfall estimation • Statistical analyses: intensity-duration-frequency curves, frequency analysis of extreme events, spatial analyses, simulation and disaggregation, ensemble approach for radar rainfall uncertainty, and uncertainty analysis of satellite rainfall products The book is tailored to be an indispensable reference for researchers, practitioners, and graduate students who study any aspect of rainfall or utilize rainfall information in various science and engineering disciplines.

  11. Radioactive pollution in rainfall

    International Nuclear Information System (INIS)

    Jemtland, R.

    1985-01-01

    Routine measurements of radioactivity in rainfall are carried out at the National Institute for Radiation Hygiene, Norway. The report discusses why the method of ion exchange was selected and gives details on how the measurements are performed

  12. 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

  13. Assessment of climate change impacts on rainfall using large scale

    Indian Academy of Sciences (India)

    In this model, using the outputs from GCM, the rainfall of Zayandehrood dam is projected under two climate change scenarios. Most effective variables have been identified among 26 predictor variables. Comparison of the results of the two models shows that the developed SVM model has lesser errors in monthly rainfall ...

  14. Seasonal rainfall predictability over the Lake Kariba catchment area ...

    African Journals Online (AJOL)

    Retroactive forecasts are produced for lead times of up to 5 months and probabilistic forecast performances evaluated for extreme rainfall thresholds of the 25th and 75th percentile values of the climatological record. The verification of the retroactive forecasts shows that rainfall over the catchment is predictable at extended ...

  15. 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 h...

  16. Characterizing rainfall parameters which influence erosivity in southeastern Nigeria

    International Nuclear Information System (INIS)

    Obi, M.E.; Salako, F.K.

    1993-12-01

    An investigation was carried out to characterize some selected parameters which influence rainfall erosivity in southeastern Nigeria. Rainfall amount, distribution, duration, intensity, storm types, energy loads and frequency of rain events in the region were studied using data from stations located in three major agroecological zones. Raindrop size and detaching capacity were evaluated in one of the stations for two months. The mean annual rainfall erosivity values for southeastern Nigeria point to the fact that rainfall tend to be highly erosive. 25 refs, 6 figs, 8 tabs

  17. Exogenous factors matter when interpreting the results of an impact evaluation: a case study of rainfall and child health programme intervention in Rwanda.

    Science.gov (United States)

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

    2017-12-01

    Public health interventions are often implemented at large scale, and their evaluation seems to be difficult because they are usually multiple and their pathways to effect are complex and subject to modification by contextual factors. We assessed whether controlling for rainfall-related variables altered estimates of the efficacy of a health programme in rural Rwanda and have a quantifiable effect on an intervention evaluation outcomes. We conducted a retrospective quasi-experimental study using previously collected cross-sectional data from the 2005 and 2010 Rwanda Demographic and Health Surveys (DHS), 2010 DHS oversampled data, monthly rainfall data collected from meteorological stations over the same period, and modelled output of long-term rainfall averages, soil moisture, and rain water run-off. Difference-in-difference models were used. Rainfall factors confounded the PIH intervention impact evaluation. When we adjusted our estimates of programme effect by controlling for a variety of rainfall variables, several effectiveness estimates changed by 10% or more. The analyses that did not adjust for rainfall-related variables underestimated the intervention effect on the prevalence of ARI by 14.3%, fever by 52.4% and stunting by 10.2%. Conversely, the unadjusted analysis overestimated the intervention's effect on diarrhoea by 56.5% and wasting by 80%. Rainfall-related patterns have a quantifiable effect on programme evaluation results and highlighted the importance and complexity of controlling for contextual factors in quasi-experimental design evaluations. © 2017 John Wiley & Sons Ltd.

  18. 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

  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. Vertical Motion Changes Related to North-East Brazil Rainfall Variability: a GCM Simulation

    Science.gov (United States)

    Roucou, Pascal; Oribe Rocha de Aragão, José; Harzallah, Ali; Fontaine, Bernard; Janicot, Serge

    1996-08-01

    The atmospheric structure over north-east Brazil during anomalous rainfall years is studied in the 11 levels of the outputs of the Laboratoire de Météorologie Dynamique atmospheric general circulation model (LMD AGCM). Seven 19-year simulations were performed using observed sea-surface temperature (SST) corresponding to the period 1970- 1988. The ensemble mean is calculated for each month of the period, leading to an ensemble-averaged simulation. The simulated March-April rainfall is in good agreement with observations. Correlations of simulated rainfall and three SST indices relative to the equatorial Pacific and northern and southern parts of the Atlantic Ocean exhibit stronger relationships in the simulation than in the observations. This is particularly true with the SST gradient in the Atlantic (Atlantic dipole). Analyses on 200 ;hPa velocity potential, vertical velocity, and vertical integral of the zonal component of mass flux are performed for years of abnormal rainfall and positive/negative SST anomalies in the Pacific and Atlantic oceans in March-April during the rainy season over the Nordeste region. The results at 200 hPa show a convergence anomaly over Nordeste and a divergence anomaly over the Pacific concomitant with dry seasons associated with warm SST anomalies in the Pacific and warm (cold) waters in the North (South) Atlantic. During drought years convection inside the ITCZ indicated by the vertical velocity exhibits a displacement of the convection zone corresponding to a northward migration of the ITCZ. The east-west circulation depicted by the zonal divergent mass flux shows subsiding motion over Nordeste and ascending motion over the Pacific in drought years, accompanied by warm waters in the eastern Pacific and warm/cold waters in northern/southern Atlantic. Rainfall variability of the Nordeste rainfall is linked mainly to vertical motion and SST variability through the migration of the ITCZ and the east-west circulation.

  1. 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 parvovirus occurrence and 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 canine tick paralysis occurrence and 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.

  2. 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.

  3. Concentrations and uncertainties of stratospheric trace species inferred from limb infrared monitor of the stratosphere data. I - Methodology and application to OH and HO2. II - Monthly averaged OH, HO2, H2O2, and HO2NO2

    Science.gov (United States)

    Kaye, J. A.; Jackman, C. H.

    1986-01-01

    Difficulties arise in connection with the verification of multidimensional chemical models of the stratosphere. The present study shows that LIMS data, together with a photochemical equilibrium model, may be used to infer concentrations of a variety of zonally averaged trace Ox, OHx, and NOx species over much of the stratosphere. In the lower stratosphere, where the photochemical equilibrium assumption for HOx species breaks down, inferred concentrations should still be accurate to about a factor of 2 for OH and 2.5 for HO2. The algebraic nature of the considered model makes it possible to see easily to the first order the effect of variation of any model input parameter or its uncertainty on the inferred concontration of the HOx species and their uncertainties.

  4. 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.

  5. Analysis of rainfall distribution in Kelantan river basin, Malaysia

    Science.gov (United States)

    Che Ros, Faizah; Tosaka, Hiroyuki

    2018-03-01

    Using rainfall gauge on its own as input carries great uncertainties regarding runoff estimation, especially when the area is large and the rainfall is measured and recorded at irregular spaced gauging stations. Hence spatial interpolation is the key to obtain continuous and orderly rainfall distribution at unknown points to be the input to the rainfall runoff processes for distributed and semi-distributed numerical modelling. It is crucial to study and predict the behaviour of rainfall and river runoff to reduce flood damages of the affected area along the Kelantan river. Thus, a good knowledge on rainfall distribution is essential in early flood prediction studies. Forty six rainfall stations and their daily time-series were used to interpolate gridded rainfall surfaces using inverse-distance weighting (IDW), inverse-distance and elevation weighting (IDEW) methods and average rainfall distribution. Sensitivity analysis for distance and elevation parameters were conducted to see the variation produced. The accuracy of these interpolated datasets was examined using cross-validation assessment.

  6. A Metastatistical Approach to Satellite Estimates of Extreme Rainfall Events

    Science.gov (United States)

    Zorzetto, E.; Marani, M.

    2017-12-01

    The estimation of the average recurrence interval of intense rainfall events is a central issue for both hydrologic modeling and engineering design. These estimates require the inference of the properties of the right tail of the statistical distribution of precipitation, a task often performed using the Generalized Extreme Value (GEV) distribution, estimated either from a samples of annual maxima (AM) or with a peaks over threshold (POT) approach. However, these approaches require long and homogeneous rainfall records, which often are not available, especially in the case of remote-sensed rainfall datasets. We use here, and tailor it to remotely-sensed rainfall estimates, an alternative approach, based on the metastatistical extreme value distribution (MEVD), which produces estimates of rainfall extreme values based on the probability distribution function (pdf) of all measured `ordinary' rainfall event. This methodology also accounts for the interannual variations observed in the pdf of daily rainfall by integrating over the sample space of its random parameters. We illustrate the application of this framework to the TRMM Multi-satellite Precipitation Analysis rainfall dataset, where MEVD optimally exploits the relatively short datasets of satellite-sensed rainfall, while taking full advantage of its high spatial resolution and quasi-global coverage. Accuracy of TRMM precipitation estimates and scale issues are here investigated for a case study located in the Little Washita watershed, Oklahoma, using a dense network of rain gauges for independent ground validation. The methodology contributes to our understanding of the risk of extreme rainfall events, as it allows i) an optimal use of the TRMM datasets in estimating the tail of the probability distribution of daily rainfall, and ii) a global mapping of daily rainfall extremes and distributional tail properties, bridging the existing gaps in rain gauges networks.

  7. Characteristics of aggregation of daily rainfall in a middle-latitudes region during a climate variability in annual rainfall amount

    Science.gov (United States)

    Lucero, Omar A.; Rozas, Daniel

    Climate variability in annual rainfall occurs because the aggregation of daily rainfall changes. A topic open to debate is whether that change takes place because rainfall becomes more intense, or because it rains more often, or a combination of both. The answer to this question is of interest for water resources planning, hydrometeorological design, and agricultural management. Change in the number of rainy days can cause major disruptions in hydrological and ecological systems, with important economic and social effects. Furthermore, the characteristics of daily rainfall aggregation in ongoing climate variability provide a reference to evaluate the capability of GCM to simulate changes in the hydrologic cycle. In this research, we analyze changes in the aggregation of daily rainfall producing a climate positive trend in annual rainfall in central Argentina, in the southern middle-latitudes. This state-of-the-art agricultural region has a semiarid climate with dry and wet seasons. Weather effects in the region influence world-market prices of several crops. Results indicate that the strong positive trend in seasonal and annual rainfall amount is produced by an increase in number of rainy days. This increase takes place in the 3-month periods January-March (summer) and April-June (autumn). These are also the 3-month periods showing a positive trend in the mean of annual rainfall. The mean of the distribution of annual number of rainy day (ANRD) increased in 50% in a 36-year span (starting at 44 days/year). No statistically significant indications on time changes in the probability distribution of daily rainfall amount were found. Non-periodic fluctuations in the time series of annual rainfall were analyzed using an integral wavelet transform. Fluctuations with a time scale of about 10 and 20 years construct the trend in annual rainfall amount. These types of non-periodic fluctuations have been observed in other regions of the world. This suggests that results of

  8. Runoff Analysis Considering Orographical Features Using Dual Polarization Radar Rainfall

    Science.gov (United States)

    Noh, Hui-seong; Shin, Hyun-seok; Kang, Na-rae; Lee, Choong-Ke; Kim, Hung-soo

    2013-04-01

    Recently, the necessity for rainfall estimation and forecasting using the radar is being highlighted, due to the frequent occurrence of torrential rainfall resulting from abnormal changes of weather. Radar rainfall data represents temporal and spatial distributions properly and replace the existing rain gauge networks. It is also frequently applied in many hydrologic field researches. However, the radar rainfall data has an accuracy limitation since it estimates rainfall, by monitoring clouds and precipitation particles formed around the surface of the earth(1.5-3km above the surface) or the atmosphere. In a condition like Korea where nearly 70% of the land is covered by mountainous areas, there are lots of restrictions to use rainfall radar, because of the occurrence of beam blocking areas by topography. This study is aiming at analyzing runoff and examining the applicability of (R(Z), R(ZDR) and R(KDP)) provided by the Han River Flood Control Office(HRFCO) based on the basin elevation of Nakdong river watershed. For this purpose, the amount of radar rainfall of each rainfall event was estimated according to three sub-basins of Nakdong river watershed with the average basin elevation above 400m which are Namgang dam, Andong dam and Hapcheon dam and also another three sub-basins with the average basin elevation below 150m which are Waegwan, Changryeong and Goryeong. After runoff analysis using a distribution model, Vflo model, the results were reviewed and compared with the observed runoff. This study estimated the rainfall by using the radar-rainfall transform formulas, (R(Z), R(Z,ZDR) and R(Z,ZDR,KDP) for four stormwater events and compared the results with the point rainfall of the rain gauge. As the result, it was overestimated or underestimated, depending on rainfall events. Also, calculation indicates that the values from R(Z,ZDR) and R(Z,ZDR,KDP) relatively showed the most similar results. Moreover the runoff analysis using the estimated radar rainfall is

  9. 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.

  10. 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.

  11. How is rainfall interception in urban area affected by meteorological parameters?

    Science.gov (United States)

    Zabret, Katarina; Rakovec, Jože; Mikoš, Matjaž; Šraj, Mojca

    2017-04-01

    Rainfall interception is part of the hydrological cycle. Precipitation, which hits vegetation, is retained on the leaves and branches, from which it eventually evaporates into the atmosphere (interception) or reaches the ground by dripping from the canopy, falling through the gaps (throughfall) and running down the stems (stemflow). The amount of rainfall reaching the ground depends on various meteorological and vegetation parameters. Rainfall, throughfall and stemflow have been measured in the city of Ljubljana, Slovenia since the beginning of 2014. Manual and automatic measurements are performed regularly under Betula pendula and Pinus nigra trees in urban area. In 2014, there were detected 178 rainfall events with total amount of 1672.1 mm. In average B. pendula intercepted 44% of rainfall and P. nigra intercepted 72% of rainfall. In 2015 we have detected 117 events with 1047.4 mm of rainfall, of which 37% was intercepted by B. pendula and 60% by P. nigra. The effect of various meteorological parameters on the rainfall interception was analysed in the study. The parameters included in the analysis were rainfall rate, rainfall duration, drop size distribution (average drop velocity and diameter), average wind speed, and average temperature. The results demonstrate decreasing rainfall interception with longer rainfall duration and higher rainfall intensity although the impact of the latter one is not statistically significant. In the case of very fast or very slow rainfall drops, the interception is higher than for the mean rain drop velocity values. In the case of P. nigra the impact of the rain drop diameter on interception is similar to the one of rain drop velocity while for B. pendula increasing of drop diameter also increases the interception. As expected, interception is higher for warmer events. This trend is more evident for P. nigra than for B. pendula. Furthermore, the amount of intercepted rainfall also increases with wind although it could be

  12. Analysis of rainfall in the municipality of Castelo do Piauí, Northeast Brazil

    Directory of Open Access Journals (Sweden)

    Francílio de Amorim dos Santos

    2017-10-01

    Full Text Available The objective of this research was to analyze rainfall in the municipality of Cas- telo do Piauí, located in the Northeast of Brazil, based on descriptive statistics and the Rainfall Anomaly Index (RAI. From an historical series of 39 years (1963 to 2001, a historical average of 1006.3 mm was identi ed for this municipality, whereas the years 1985 and 1983 were considered the most and least rainy, re- spectively. The rainy season is concentrated in the months of January to April, with March being the wettest and August being the least rainy. Rainfall variability values were higher than 40% for all months and asymmetric positive distribution. The RAI allowed to establish the following dry and rainy years: 1963, 1964 and 1989 (very rainy; 1974 and 1985 (extremely rainy; 1976, 1981, 1992, 1993, 1998 and 2001 (very dry; 1983 and 1990 (extremely dry. In summary, the present study found a predominance of dry to extremely dry years in the studied area, with 53.8%.

  13. 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

    2017-08-01

    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.

  14. Automated reconstruction of rainfall events responsible for shallow landslides

    Science.gov (United States)

    Vessia, G.; Parise, M.; Brunetti, M. T.; Peruccacci, S.; Rossi, M.; Vennari, C.; Guzzetti, F.

    2014-04-01

    Over the last 40 years, many contributions have been devoted to identifying the empirical rainfall thresholds (e.g. intensity vs. duration ID, cumulated rainfall vs. duration ED, cumulated rainfall vs. intensity EI) for the initiation of shallow landslides, based on local as well as worldwide inventories. Although different methods to trace the threshold curves have been proposed and discussed in literature, a systematic study to develop an automated procedure to select the rainfall event responsible for the landslide occurrence has rarely been addressed. Nonetheless, objective criteria for estimating the rainfall responsible for the landslide occurrence (effective rainfall) play a prominent role on the threshold values. In this paper, two criteria for the identification of the effective rainfall events are presented: (1) the first is based on the analysis of the time series of rainfall mean intensity values over one month preceding the landslide occurrence, and (2) the second on the analysis of the trend in the time function of the cumulated mean intensity series calculated from the rainfall records measured through rain gauges. The two criteria have been implemented in an automated procedure written in R language. A sample of 100 shallow landslides collected in Italy by the CNR-IRPI research group from 2002 to 2012 has been used to calibrate the proposed procedure. The cumulated rainfall E and duration D of rainfall events that triggered the documented landslides are calculated through the new procedure and are fitted with power law in the (D,E) diagram. The results are discussed by comparing the (D,E) pairs calculated by the automated procedure and the ones by the expert method.

  15. Climate Change Impact on Rainfall: How will Threaten Wheat Yield?

    Science.gov (United States)

    Tafoughalti, K.; El Faleh, E. M.; Moujahid, Y.; Ouargaga, F.

    2018-05-01

    Climate change has a significant impact on the environmental condition of the agricultural region. Meknes has an agrarian economy and wheat production is of paramount importance. As most arable area are under rainfed system, Meknes is one of the sensitive regions to rainfall variability and consequently to climate change. Therefore, the use of changes in rainfall is vital for detecting the influence of climate system on agricultural productivity. This article identifies rainfall temporal variability and its impact on wheat yields. We used monthly rainfall records for three decades and wheat yields records of fifteen years. Rainfall variability is assessed utilizing the precipitation concentration index and the variation coefficient. The association between wheat yields and cumulative rainfall amounts of different scales was calculated based on a regression model. The analysis shown moderate seasonal and irregular annual rainfall distribution. Yields fluctuated from 210 to 4500 Kg/ha with 52% of coefficient of variation. The correlation results shows that wheat yields are strongly correlated with rainfall of the period January to March. This investigation concluded that climate change is altering wheat yield and it is crucial to adept the necessary adaptation to challenge the risk.

  16. Apply data mining to analyze the rainfall of landslide

    Directory of Open Access Journals (Sweden)

    Lee Chou-Yuan

    2018-01-01

    Full Text Available Taiwan is listed as extremely dangerous country which suffers from many disasters. The disasters from the landslide result in the loss of agricultural productions, life and property and so on. Many researchers concern about the disasters of landslide, but there are few discussions for the threshold of rainfall for landslide. In this paper, data mining is applied to establish rules and the threshold of rainfall for landslide in Huafan University, Taiwan. These used variables include rainfall, insolation, insolation rate, averaged humidity, averaged temperature, wind speed, and the tilt of inclinometer. The inclinometer is an important instrument for measuring tilt, elevation or depression of an object with respect to gravity. There are 26 inclinometers in Talun mountain area of Huafan University. In this research, the used data were collected from January 2008 to July 2014. In the proposed approach, the regression analysis is used to predict rainfall first. Then, decision tree is used to obtain decision rules and set the threshold of rainfall for landslide. The output of this approach can provide more information for understanding the change of rainfall. The threshold of rainfall could also provide useful information to maintain the security for Huafan University.

  17. Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

    Directory of Open Access Journals (Sweden)

    G. T. Ayehu

    2018-04-01

    Full Text Available Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor ground observations or through integrating with rain gauge measurements. In this study, the potential of a newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS rainfall product has been evaluated in comparison to rain gauge data over the Upper Blue Nile basin in Ethiopia for the period of 2000 to 2015. In addition, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT 3 and the African Rainfall Climatology (ARC 2 products have been used as a benchmark and compared with CHIRPS. From the overall analysis at dekadal (10 days and monthly temporal scale, CHIRPS exhibited better performance in comparison to TAMSAT 3 and ARC 2 products. An evaluation based on categorical/volumetric and continuous statistics indicated that CHIRPS has the greatest skills in detecting rainfall events (POD  =  0.99, 1.00 and measure of volumetric rainfall (VHI  =  1.00, 1.00, the highest correlation coefficients (r =  0.81, 0.88, better bias values (0.96, 0.96, and the lowest RMSE (28.45 mm dekad−1, 59.03 mm month−1 than TAMSAT 3 and ARC 2 products at dekadal and monthly analysis, respectively. CHIRPS overestimates the frequency of rainfall occurrence (up to 31 % at dekadal scale, although the volume of rainfall recorded during those events was very small. Indeed, TAMSAT 3 has shown a comparable performance with that of the CHIRPS product, mainly with regard to bias. The ARC 2 product was found to have the weakest performance

  18. Beryllium-7 in Rainfall, River Sediment and Sewage Sludge - Beryllium-7 in rainwater, river sediment and sewage sludge

    Energy Technology Data Exchange (ETDEWEB)

    Fischer, Helmut W.; Igbinosa, Aimuamwosa; Souti, Maria Evangelia [University of Bremen, Institute of Environmental Physics, Otto-Hahn-Allee 1, D-28359 Bremen (Germany)

    2014-07-01

    Introduction: The cosmogenic radioisotope {sup 7}Be is one of the major contributors to natural airborne radioactivity, with fairly constant concentrations of some mBq/m{sup 3} near the Earth's surface. The isotope is assumed to be bound to aerosols. It is deposited onto the Earth's surface mainly by wet deposition. In environmental surveillance it is detected regularly in air by aerosol sampling, and in topsoil and on plant leaves after rainfall. In previous studies of this laboratory it had also been detected regularly in freshwater sediments and in wastewater treatment primary sludge. River sediment samples from an estuary showed concentrations influenced by dilution with sea water. Thus it appeared interesting to investigate the usefulness of {sup 7}Be as tracer for rainfall contribution in environmental samples. Experimental: In order to investigate possible correlations and interrelations between {sup 7}Be activity in rainfall, sediment and primary sludge, a measurement campaign was planned and conducted covering a time span of 6 months. {sup 7}Be concentrations were determined in weekly samples of rainwater and primary sludge and in monthly samples of river sediment by high resolution gamma spectroscopy. Besides, rainfall amount and intensity were recorded and weekly primary sludge production volume data were obtained from the treatment plant operators. From these numbers, total atmospheric deposition per surface area could be calculated. Results and discussion: The data show a clear correlation between weekly rainfall amount and {sup 7}Be surface deposition. This is more than plausible as wet deposition is known to be the most effective deposition process. Although washout effectivity is assumed to decrease with rainfall intensity, no correlation could be seen in the data, probably due to averaging within the weekly sampling intervals. The time series of {sup 7}Be deposition with rain and its concentration in primary sludge exhibit very similar

  19. Wheat yield vulnerability: relation to rainfall and suggestions for adaptation

    Directory of Open Access Journals (Sweden)

    Khalid Tafoughalti

    2018-04-01

    Full Text Available Wheat production is of paramount importance in the region of Meknes, which is mainly produced under rainfed conditions. It is the dominant cereal, the greater proportion being the soft type. During the past few decades, rainfall flaws have caused a number of cases of droughts. These flaws have seriously affecting wheat production. The main objective of this study is the assessment of rainfall variability at monthly, seasonal and annual scales and to determine their impact on wheat yields. To reduce this impact we suggested some mechanisms of adaptation. We used monthly rainfall records for three decades and wheat yields records of fifteen years. Rainfall variability is assessed utilizing the precipitation concentration index and the variation coefficient. The association between wheat yields and cumulative rainfall amounts of different scales was calculated based on a regression model to evaluate the impact of rainfall on wheat yields. Data analysis shown moderate seasonal and irregular annual rainfall distribution. Yields fluctuated from 210 to 4500 Kg/ha with 52% of coefficient of variation. The correlation results shows that soft wheat and hard wheat are strongly correlated with the period of January to March than with the whole growing-season. While they are adversely correlated with the mid-spring. This investigation concluded that synchronizing appropriate adaptation with the period of January to March was crucial to achieving success yield of wheat.

  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. Determined of Rainfall Erosivity Indices (EI30, Lal, Hudson and Onchev for Namak Lake Basin

    Directory of Open Access Journals (Sweden)

    Z.T. Alipour

    2011-06-01

    Full Text Available In this research the indices EI30, AIm,‎ KE>1‎ as well as P/√t‎ were determined for 16 pluviograph as well as for 3 Namak Lake Basin nearby stations. Regression relationships were established between the dependent variables of EI30, AIm, KE>1‎ as well as P/√t‎ Indices and other easily accessible rainfall indices of: fournier, modified fournier, maximum monthly rainfall, maximum daily rainfall, standard deviation of monthly and annual rainfall as well as pluviometer site elevations. This made the establishment of appropriate relationships between rainfall intensity dependent indices and the dependent variable of rainfall intensity (at stations where intensity was non-existent possible. In the next step, the indices as well as easily accessible rainfall data from pluviograph stations were exploited to find out EI30 ,AIm ,‎ KE>1‎ as well as P/√t‎ indices, while using the previously obtained regression relationships.

  2. Impact of Rainfall, Sales Method, and Time on Land Prices

    OpenAIRE

    Stephens, Steve; Schurle, Bryan

    2013-01-01

    Land prices in Western Kansas are analyzed using regression to estimate the influence of rainfall, sales method, and time of sale. The estimates from regression indicate that land prices decreased about $27 for each range that was farther west which can be converted to about $75 per inch of average rainfall. In addition, the influence of method of sale (private sale or auction) is estimated along with the impact of time of sale. Auction sales prices are approximately $100 higher per acre than...

  3. 461 TIME SERIES ANALYSES OF MEAN MONTHLY RAINFALL ...

    African Journals Online (AJOL)

    Osondu

    insidious hazard of nature that originated from a deficiency of ... as the main input into the hydrological cycle provides water for .... maritime air mass from the Atlantic Ocean and ... The forest vegetation in some parts of ... neighboring Niger Republic, while river Sokoto ..... basin by using the standardised precipitation index ...

  4. 1994 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...

  5. 1993 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 NOAA...

  6. Comparing Satellite Rainfall Estimates with Rain-Gauge Data: Optimal Strategies Suggested by a Spectral Model

    Science.gov (United States)

    Bell, Thomas L.; Kundu, Prasun K.; Lau, William K. M. (Technical Monitor)

    2002-01-01

    Validation of satellite remote-sensing methods for estimating rainfall against rain-gauge data is attractive because of the direct nature of the rain-gauge measurements. Comparisons of satellite estimates to rain-gauge data are difficult, however, because of the extreme variability of rain and the fact that satellites view large areas over a short time while rain gauges monitor small areas continuously. In this paper, a statistical model of rainfall variability developed for studies of sampling error in averages of satellite data is used to examine the impact of spatial and temporal averaging of satellite and gauge data on intercomparison results. The model parameters were derived from radar observations of rain, but the model appears to capture many of the characteristics of rain-gauge data as well. The model predicts that many months of data from areas containing a few gauges are required to validate satellite estimates over the areas, and that the areas should be of the order of several hundred km in diameter. Over gauge arrays of sufficiently high density, the optimal areas and averaging times are reduced. The possibility of using time-weighted averages of gauge data is explored.

  7. Neutron resonance averaging

    International Nuclear Information System (INIS)

    Chrien, R.E.

    1986-10-01

    The principles of resonance averaging as applied to neutron capture reactions are described. Several illustrations of resonance averaging to problems of nuclear structure and the distribution of radiative strength in nuclei are provided. 30 refs., 12 figs

  8. 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

  9. Acidity in rainfall

    International Nuclear Information System (INIS)

    Tisue, G.T.; Kacoyannakis, J.

    1975-01-01

    The reported increasing acidity of rainfall raises many interesting ecological and chemical questions. In spite of extensive studies in Europe and North America there are, for example, great uncertainties in the relative contributions of strong and weak acids to the acid-base properties of rainwater. Unravelling this and similar problems may require even more rigorous sample collection and analytical procedures than previously employed. Careful analysis of titration curves permits inferences to be made regarding chemical composition, the possible response of rainwater to further inputs of acidic components to the atmosphere, and the behavior to be expected when rainwater interacts with the buffers present in biological materials and natural waters. Rainwater samples collected during several precipitation events at Argonne National Laboratory during October and November 1975 have been analyzed for pH, acid and base neutralizing properties, and the ions of ammonium, nitrate, chloride, sulfate, and calcium. The results are tabulated

  10. Distinctive Features of Surface Winds over Indian Ocean Between Strong and Weak Indian Summer Monsoons: Implications With Respect To Regional Rainfall Change in India

    Science.gov (United States)

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

    2017-12-01

    This observational study focuses on characterizing the surface winds in the Arabian Sea (AS), the Bay of Bengal (BoB), and the southern Indian Ocean (SIO) with special reference to the strong and weak Indian summer monsoon rainfall (ISMR) using the latest daily gridded rainfall dataset provided by the Indian Meteorological Department (IMD) and the Cross-Calibrated Multi-Platform (CCMP) gridded wind product version 2.0 produced by Remote Sensing System (RSS) over the overlapped period 1991-2014. The potential links between surface winds and Indian regional rainfall are also examined. Results indicate that the surface wind speeds in AS and BoB during June-August are almost similar during strong ISMRs and weak ISMRs, whereas significant discrepancies are observed during September. By contrast, the surface wind speeds in SIO during June-August are found to be significantly different between strong and weak ISMRs, where they are similar during September. The significant differences in monthly mean surface wind convergence between strong and weak ISMRs are not coherent in space in the three regions. However, the probability density function (PDF) distributions of daily mean area-averaged values are distinctive between strong and weak ISMRs in the three regions. The correlation analysis indicates the area-averaged surface wind speeds in AS and the area-averaged wind convergence in BoB are highly correlated with regional rainfall for both strong and weak ISMRs. The wind convergence in BoB during strong ISMRs is relatively better correlated with regional rainfall than during weak ISMRs. The surface winds in SIO do not greatly affect Indian rainfall in short timescales, however, they will ultimately affect the strength of monsoon circulation by modulating Indian Ocean Dipole (IOD) mode via atmosphere-ocean interactions.

  11. 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.

  12. 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.

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

    Science.gov (United States)

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

    2012-07-01

    To study the number of leptospirosis cases in relations to the seasonal pattern, and its association with climate factors. Time series analysis was used to study the time variations in the number of leptospirosis cases. The Autoregressive Integrated Moving Average (ARIMA) model was used in data curve fitting and predicting the next leptospirosis cases. We found that the amount of rainfall was correlated to leptospirosis cases in both regions of interest, namely the northern and northeastern region of Thailand, while the temperature played a role in the northeastern region only. The use of multivariate ARIMA (ARIMAX) model showed that factoring in rainfall (with an 8 months lag) yields the best model for the northern region while the model, which factors in rainfall (with a 10 months lag) and temperature (with an 8 months lag) was the best for the northeastern region. 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. Copyright © 2012 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

  14. Characteristic and Behavior of Rainfall Induced Landslides in Java Island, Indonesia : an Overview

    Science.gov (United States)

    Christanto, N.; Hadmoko, D. S.; Westen, C. J.; Lavigne, F.; Sartohadi, J.; Setiawan, M. A.

    2009-04-01

    frequency both annual and monthly level during the periods of 1981 - 2007. Simple statistical analysis was done to correlate landslide events, antecedent rainfall during 30 consecutive days and daily rainfall during the landslide day. Analysis the relationship between landslide events and their controlling factors (e.g. slope, geology, geomorphology and landuse) were carried out in GIS environment. The results show that the slope gradient has a good influence to landslides events. The number of landslides increases significantly from slopes inferior to 10° and from 30° to 40°. However, inverse correlation between landslides events occurs on slope steepness more than 40° when the landslide frequency tends to decline with an increasing of slope angle. The result from landuse analysis shows that most of landslides occur on dryland agriculture, followed by paddy fields and artificial. This data indicates that human activities play an important role on landslide occurrence. Dryland agriculture covers not only the lower part of land, but also reached middle and upper slopes; with terraces agriculture that often accelerate landslide triggering. During the period 1981-2007, the annual landslide frequency varies significantly, with an average of 49 events per year. Within a year, the number of landslides increases from June to November and decreases significantly from January to July. Statistically, both January and November are the most susceptible months for landslide generation, with respectively nine and seven events on average. This distribution is closely related to the rainfall monthly variations. Landslides in Java are unevenly distributed. Most landslides are concentrated in West Java Region, followed by Central Java and East Java. The overall landslide density in Java reached 1x10 events/km with the annual average was 3.6 x 10 event/km /year. The amount of annual precipitation is significantly higher in West Java than further East, decreasing with a constant W

  15. Determined of Rainfall Erosivity Indices (EI30, Lal, Hudson and Onchev) for Namak Lake Basin

    OpenAIRE

    Z.T. Alipour; M.H. Mahdian; S. Hakimkhani; M. Saeedi

    2011-01-01

    In this research the indices EI30, AIm,‎ KE>1‎ as well as P/√t‎ were determined for 16 pluviograph as well as for 3 Namak Lake Basin nearby stations. Regression relationships were established between the dependent variables of EI30, AIm, KE>1‎ as well as P/√t‎ Indices and other easily accessible rainfall indices of: fournier, modified fournier, maximum monthly rainfall, maximum daily rainfall, standard deviation of monthly and annual rainfall as well as pluviometer site elevations. This made ...

  16. 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.

  17. Radar rainfall image repair techniques

    Directory of Open Access Journals (Sweden)

    Stephen M. Wesson

    2004-01-01

    Full Text Available There are various quality problems associated with radar rainfall data viewed in images that include ground clutter, beam blocking and anomalous propagation, to name a few. To obtain the best rainfall estimate possible, techniques for removing ground clutter (non-meteorological echoes that influence radar data quality on 2-D radar rainfall image data sets are presented here. These techniques concentrate on repairing the images in both a computationally fast and accurate manner, and are nearest neighbour techniques of two sub-types: Individual Target and Border Tracing. The contaminated data is estimated through Kriging, considered the optimal technique for the spatial interpolation of Gaussian data, where the 'screening effect' that occurs with the Kriging weighting distribution around target points is exploited to ensure computational efficiency. Matrix rank reduction techniques in combination with Singular Value Decomposition (SVD are also suggested for finding an efficient solution to the Kriging Equations which can cope with near singular systems. Rainfall estimation at ground level from radar rainfall volume scan data is of interest and importance in earth bound applications such as hydrology and agriculture. As an extension of the above, Ordinary Kriging is applied to three-dimensional radar rainfall data to estimate rainfall rate at ground level. Keywords: ground clutter, data infilling, Ordinary Kriging, nearest neighbours, Singular Value Decomposition, border tracing, computation time, ground level rainfall estimation

  18. 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.

  19. 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.

  20. A TRMM-Calibrated Infrared Rainfall Algorithm Applied Over Brazil

    Science.gov (United States)

    Negri, A. J.; Xu, L.; Adler, R. F.; Einaudi, Franco (Technical Monitor)

    2000-01-01

    The development of a satellite infrared technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall in Amazonia are presented. The Convective-Stratiform. Technique, calibrated by coincident, physically retrieved rain rates from the Tropical Rain Measuring Mission (TRMM) Microwave Imager (TMI), is applied during January to April 1999 over northern South America. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall is presented. Results compare well (a one-hour lag) with the diurnal cycle derived from Tropical Ocean-Global Atmosphere (TOGA) radar-estimated rainfall in Rondonia. The satellite estimates reveal that the convective rain constitutes, in the mean, 24% of the rain area while accounting for 67% of the rain volume. The effects of geography (rivers, lakes, coasts) and topography on the diurnal cycle of convection are examined. In particular, the Amazon River, downstream of Manaus, is shown to both enhance early morning rainfall and inhibit afternoon convection. Monthly estimates from this technique, dubbed CST/TMI, are verified over a dense rain gage network in the state of Ceara, in northeast Brazil. The CST/TMI showed a high bias equal to +33% of the gage mean, indicating that possibly the TMI estimates alone are also high. The root mean square difference (after removal of the bias) equaled 36.6% of the gage mean. The correlation coefficient was 0.77 based on 72 station-months.

  1. Interannual Rainfall Variability in North-East Brazil: Observation and Model Simulation

    Science.gov (United States)

    Harzallah, A.; Rocha de Aragão, J. O.; Sadourny, R.

    1996-08-01

    The relationship between interannual variability of rainfall in north-east Brazil and tropical sea-surface temperature is studied using observations and model simulations. The simulated precipitation is the average of seven independent realizations performed using the Laboratoire de Météorologie Dynamique atmospheric general model forced by the 1970-1988 observed sea-surface temperature. The model reproduces very well the rainfall anomalies (correlation of 091 between observed and modelled anomalies). The study confirms that precipitation in north-east Brazil is highly correlated to the sea-surface temperature in the tropical Atlantic and Pacific oceans. Using the singular value decomposition method, we find that Nordeste rainfall is modulated by two independent oscillations, both governed by the Atlantic dipole, but one involving only the Pacific, the other one having a period of about 10 years. Correlations between precipitation in north-east Brazil during February-May and the sea-surface temperature 6 months earlier indicate that both modes are essential to estimate the quality of the rainy season.

  2. The Impact of Rainfall on Fecal Coliform Bacteria in Bayou Dorcheat (North Louisiana

    Directory of Open Access Journals (Sweden)

    Paul B. Tchounwou

    2006-03-01

    Full Text Available Fecal coliform bacteria are the most common pollutant in rivers and streams. In Louisiana, it has been reported that 37% of surveyed river miles, 31% of lakes, and 23% of estuarine water had some level of contamination. The objective of this research was to assess the effect of surface runoff amounts and rainfall amount parameters on fecal coliform bacterial densities in Bayou Dorcheat in Louisiana. Bayou Dorcheat has been designated by the Louisiana Department of Environmental Quality as a waterway that has uses such as primary contact recreation, secondary contact recreation, propagation of fish and wildlife, agriculture and as being an outstanding natural resource water. Samples from Bayou Dorcheat were collected monthly and analyzed for the presence of fecal coliforms. Fecal coliforms isolated from these samples were identified to the species level. The analysis of the bacterial levels was performed following standard test protocols as described in Standard Methods for the Examination of Water and Wastewater. Information regarding the rainfall amounts and surface runoff amounts for the selected years was retrieved from the Louisiana Office of State Climatology. It was found that a significant increase in the fecal coliform numbers may be associated with average rainfall amounts. Possible sources of elevated coliform counts could include sewage discharges from municipal treatment plants and septic tanks, storm water overflows, and runoff from pastures and range lands. It can be concluded that nonpoint source pollution that is carried by surface runoff has a significant effect on bacterial levels in water resources.

  3. 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.

  4. Rainfall Patterns Analysis over Ampangan Muda, Kedah from 2007 - 2016

    Science.gov (United States)

    Chooi Tan, Kok

    2018-04-01

    The scientific knowledge about climate change and climate variability over Malaysia pertaining to the extreme water-related disaster such as drought and flood. A deficit or increment in precipitation occurred over the past century becomes a useful tool to understand the climate change in Malaysia. The purpose of this work is to examine the rainfall patterns over Ampangan Muda, Kedah. Daily rainfall data is acquired from Malaysian Meteorological Department to analyse the temporal and trends of the monthly and annual rainfall over the study area from 2007 to 2016. The obtained results show that the temporal and patterns of the rainfall over Ampangan Muda, Kedah is largely affected by the regional phenomena such as monsoon, El Niño Southern Oscillation (ENSO), and the Madden-Julian Oscillation. In addition, backward trajectories analysis is also used to identify the patterns for long-range of synoptic circulation over the region.

  5. The Interdependence between Rainfall and Temperature: Copula Analyses

    DEFF Research Database (Denmark)

    Cong, Ronggang; Brady, Mark

    2012-01-01

    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...

  6. The Variation of Tropical Cyclone Rainfall within the North Atlantic and Pacific as Observed from Satellites

    Science.gov (United States)

    Rodgers, Edward; Pierce, Harold; Adler, Robert

    1999-01-01

    Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations in the North Atlantic and in three equal geographical regions of the North Pacific (i.e., Western, Central, and Eastern North Pacific). These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the 1987-1989, 1991-1998 North Atlantic and Pacific rainfall during June-November when tropical cyclones are most abundant. To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from the Defence Meteorological Satellite Program (DMSP) Special Sensor Microwave/ Radiometer (SSM/I) observations within 444 km radius of the center of those North Atlantic and Pacific tropical cyclones that reached storm stage and greater. These rain rate observations are then multiplied by the number of hours in a given month. Mean monthly rainfall amounts are also constructed for all the other North Atlantic and Pacific raining systems during this eleven year period for the purpose of estimating the geographical distribution and intensity of rainfall contributed by non-tropical cyclone systems. Further, the combination of the non-tropical cyclone and tropical cyclone (i.e., total) rainfall is constructed to delineate the fractional amount that tropical cyclones contributed to the total North Pacific rainfall.

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

    Science.gov (United States)

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

    2015-12-01

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

  8. Rainfall erosivity factor estimation in Republic of Moldova

    Science.gov (United States)

    Castraveš, Tudor; Kuhn, Nikolaus

    2017-04-01

    Rainfall erosivity represents a measure of the erosive force of rainfall. Typically, it is expressed as variable such as the R factor in the Universal Soil Loss Equation (USLE) (Wischmeier and Smith, 1965, 1978) or its derivates. The rainfall erosivity index for a rainfall event (EI30) is calculated from the total kinetic energy and maximum 30 minutes intensity of individual events. However, these data are often unavailable for wide regions and countries. Usually, there are three issues regarding precipitation data: low temporal resolution, low spatial density and limited access to the data. This is especially true for some of postsoviet countries from Eastern Europe, such as Republic of Moldova, where soil erosion is a real and persistent problem (Summer, 2003) and where soils represents the main natural resource of the country. Consequently, researching and managing soil erosion is particularly important. The purpose of this study is to develop a model based on commonly available rainfall data, such as event, daily or monthly amounts, to calculate rainfall erosivity for the territory of Republic of Moldova. Rainfall data collected during 1994-2015 period at 15 meteorological stations in the Republic of Moldova, with 10 minutes temporal resolution, were used to develop and calibrate a model to generate an erosivity map of Moldova. References 1. Summer, W., (2003). Soil erosion in the Republic of Moldova — the importance of institutional arrangements. Erosion Prediction in Ungauged Basins: Integrating Methods and Techniques (Proceedings of symposium HS01 held during IUGG2003 at Sapporo. July 2003). IAHS Publ. no. 279. 2. Wischmeier, W.H., and Smith, D.D. (1965). Predicting rainfall-erosion losses from cropland east of the Rocky Mountains. Agr. Handbook No. 282, U.S. Dept. Agr., Washington, DC 3. Wischmeier, W.H., and Smith, D.D. (1978). Predicting rainfall erosion losses. Agr. handbook No. 537, U.S. Dept. of Agr., Science and Education Administration.

  9. 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.

  10. Contributions of Tropical Cyclones to the North Atlantic Climatological Rainfall as Observed from Satellites

    Science.gov (United States)

    Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.; Einaudi, Franco (Technical Monitor)

    2000-01-01

    The tropical cyclone rainfall climatology study that was performed for the North Pacific was extended to the North Atlantic. Similar to the North Pacific tropical cyclone study, mean monthly rainfall within 444 km of the center of the North Atlantic tropical cyclones (i.e., that reached storm stage and greater) was estimated from passive microwave satellite observations during, an eleven year period. These satellite-observed rainfall estimates were used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the North Atlantic total rainfall during, June-November when tropical cyclones were most abundant. The main results from this study indicate: 1) that tropical cyclones contribute, respectively, 4%, 3%, and 4% to the western, eastern, and entire North Atlantic; 2) similar to that observed in the North Pacific, the maximum in North Atlantic tropical cyclone rainfall is approximately 5 - 10 deg poleward (depending on longitude) of the maximum non-tropical cyclone rainfall; 3) tropical cyclones contribute regionally a maximum of 30% of the total rainfall 'northeast of Puerto Rico, within a region near 15 deg N 55 deg W, and off the west coast of Africa; 4) there is no lag between the months with maximum tropical cyclone rainfall and non-tropical cyclone rainfall in the western North Atlantic, while in the eastern North Atlantic, maximum tropical cyclone rainfall precedes maximum non-tropical cyclone rainfall; 5) like the North Pacific, North Atlantic tropical cyclones Of hurricane intensity generate the greatest amount of rainfall in the higher latitudes; and 6) warm ENSO events inhibit tropical cyclone rainfall.

  11. 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.

  12. Monthly Electrical Energy Overview June 2017

    International Nuclear Information System (INIS)

    2017-07-01

    This publication presents the electricity characteristics and noteworthy developments in France every month: consumption, generation, renewable energies, cross-border trades and transmission system developments, along with feedback on the highlights affecting this data. This issue presents the key figures for June 2017. Average temperatures in June increased by +2.7 deg. compared to June 2016. Demand in June increased by +1.76% compared to June 2016. Demand in June increased by 1.76% compared to June 2016, due in particular to the heat wave that occurred between 19 and 22. Hydraulic generation was again penalized by the lack of rainfall with a fall of 28.6% compared to June 2016. Solar generation was up by 26.7%, driven by the high amount of sunlight in the month. The heat wave had a strong impact on demand in the regions most affected by the high temperatures: Champagne-Ardenne, Pays de la Loire, Midi-Pyrenees. Market prices increased in the south of Europe. France imported more than it exported via Switzerland. Overall, French exchanges remained in favour of exports in the month. 14 new installations went into service in June

  13. 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.

  14. Rainfall measurement from the opportunistic use of an Earth-space link in the Ku band

    Science.gov (United States)

    Barthès, L.; Mallet, C.

    2013-08-01

    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.

  15. Process connectivity reveals ecohydrologic sensitivity to drought and rainfall pulses

    Science.gov (United States)

    Goodwell, A. E.; Kumar, P.

    2017-12-01

    Ecohydrologic fluxes within atmosphere, canopy and soil systems exhibit complex and joint variability. This complexity arises from direct and indirect forcing and feedback interactions that can cause fluctuations to propagate between water, energy, and nutrient fluxes at various time scales. When an ecosystem is perturbed in the form of a single storm event, an accumulating drought, or changes in climate and land cover, this aspect of joint variability may dictate responsiveness and resilience of the entire system. A characterization of the time-dependent and multivariate connectivity between processes, fluxes, and states is necessary to identify and understand these aspects of ecohydrologic systems. We construct Temporal Information Partitioning Networks (TIPNets), based on information theory measures, to identify time-dependencies between variables measured at flux towers along elevation and climate gradients in relation to their responses to moisture-related perturbations. Along a flux tower transect in the Reynolds Creek Critical Zone Observatory (CZO) in Idaho, we detect a significant network response to a large 2015 dry season rainfall event that enhances microbial respiration and latent heat fluxes. At a transect in the Southern Sierra CZO in California, we explore network properties in relation to drought responses from 2011 to 2015. We find that both high and low elevation sites exhibit decreased connectivity between atmospheric and soil variables and latent heat fluxes, but the higher elevation site is less sensitive to this altered connectivity in terms of average monthly heat fluxes. Through a novel approach to gage the responsiveness of ecosystem fluxes to shifts in connectivity, this study aids our understanding of ecohydrologic sensitivity to short-term rainfall events and longer term droughts. This study is relevant to ecosystem resilience under a changing climate, and can lead to a greater understanding of shifting behaviors in many types of

  16. Rainfall prediction with backpropagation method

    Science.gov (United States)

    Wahyuni, E. G.; Fauzan, L. M. F.; Abriyani, F.; Muchlis, N. F.; Ulfa, M.

    2018-03-01

    Rainfall is an important factor in many fields, such as aviation and agriculture. Although it has been assisted by technology but the accuracy can not reach 100% and there is still the possibility of error. Though current rainfall prediction information is needed in various fields, such as agriculture and aviation fields. In the field of agriculture, to obtain abundant and quality yields, farmers are very dependent on weather conditions, especially rainfall. Rainfall is one of the factors that affect the safety of aircraft. To overcome the problems above, then it’s required a system that can accurately predict rainfall. In predicting rainfall, artificial neural network modeling is applied in this research. The method used in modeling this artificial neural network is backpropagation method. Backpropagation methods can result in better performance in repetitive exercises. This means that the weight of the ANN interconnection can approach the weight it should be. Another advantage of this method is the ability in the learning process adaptively and multilayer owned on this method there is a process of weight changes so as to minimize error (fault tolerance). Therefore, this method can guarantee good system resilience and consistently work well. The network is designed using 4 input variables, namely air temperature, air humidity, wind speed, and sunshine duration and 3 output variables ie low rainfall, medium rainfall, and high rainfall. Based on the research that has been done, the network can be used properly, as evidenced by the results of the prediction of the system precipitation is the same as the results of manual calculations.

  17. Contribution of Tropical Cyclones to the North Pacific Climatological Rainfall as Observed from Satellites.

    Science.gov (United States)

    Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.

    2000-10-01

    Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations for an 11-yr period. These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and interannual distribution of the North Pacific Ocean total rainfall during June-November when tropical cyclones are most important.To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from passive microwave satellite observations within 444-km radius of the center of those North Pacific tropical cyclones that reached storm stage and greater. These rain-rate observations are converted to monthly rainfall amounts and then compared with those for nontropical cyclone systems.The main results of this study indicate that 1) tropical cyclones contribute 7% of the rainfall to the entire domain of the North Pacific during the tropical cyclone season and 12%, 3%, and 4% when the study area is limited to, respectively, the western, central, and eastern third of the ocean; 2) the maximum tropical cyclone rainfall is poleward (5°-10° latitude depending on longitude) of the maximum nontropical cyclone rainfall; 3) tropical cyclones contribute a maximum of 30% northeast of the Philippine Islands and 40% off the lower Baja California coast; 4) in the western North Pacific, the tropical cyclone rainfall lags the total rainfall by approximately two months and shows seasonal latitudinal variation following the Intertropical Convergence Zone; and 5) in general, tropical cyclone rainfall is enhanced during the El Niño years by warm SSTs in the eastern North Pacific and by the monsoon trough in the western and central North Pacific.

  18. Lysimeter study to investigate the effect of rainfall patterns on leaching of isoproturon.

    Science.gov (United States)

    Beulke, Sabine; Brown, Colin D; Fryer, Christopher J; Walker, Allan

    2002-01-01

    The influence of five rainfall treatments on water and solute leaching through two contrasting soil types was investigated. Undisturbed lysimeters (diameter 0.25 m, length 0.5 m) from a sandy loam (Wick series) and a moderately structured clay loam (Hodnet series) received autumn applications of the radio-labelled pesticide isoproturon and bromide tracer. Target rainfall plus irrigation from the end of November 1997 to May 1998 ranged from drier to wetter than average (235 to 414 mm); monthly rainfall was varied according to a pre-selected pattern or kept constant (triplicate lysimeters per regime). Leachate was collected at intervals and concentrations of the solutes were determined. Total flow (0.27-0.94 pore volumes) and losses of bromide (3-80% of applied) increased with increasing inputs of water and were larger from the Wick sandy loam than from the Hodnet clay loam soil. Matrix flow appeared to be the main mechanism for transport of isoproturon through the Wick soil whereas there was a greater influence of preferential flow for the Hodnet lysimeters. The total leached load of isoproturon from the Wick lysimeters was 0.02-0.26% of that applied. There was no clear variation in transport processes between the rainfall treatments investigated for this soil and there was an approximately linear relationship (r2 = 0.81) between leached load and total flow. Losses of isoproturon from the Hodnet soil were 0.03-0.39% of applied and there was evidence of enhanced preferential flow in the driest and wettest treatments. Leaching of isoproturon was best described by an exponential relationship between load and total flow (r2 = 0.62). A 45% increase in flow between the two wettest treatments gave a 100% increase in leaching of isoproturon from the Wick soil. For the Hodnet lysimeters, a 35% increase in flow between the same treatments increased herbicide loss by 325%.

  19. 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 belo...... approximations to the Riemannian metric, and that the subsequent corrections are inherient in the least squares estimation. Keywords: averaging rotations, Riemannian metric, matrix, quaternion......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...

  20. NEXRAD Rainfall Data: Eureka, California

    Data.gov (United States)

    National Aeronautics and Space Administration — Next-Generation Radar (NEXRAD) Weather Surveillance Radar 1988 (WSR-88D) measurements were used to support AMSR-E rainfall validation efforts in Eureka, California,...

  1. 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

  2. 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...

  3. 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...

  4. The influence of Atmospheric Rivers over the South Atlantic on rainfall in South Africa

    Science.gov (United States)

    Ramos, A. M.; Trigo, R. M.; Blamey, R. C.; Tome, R.; Reason, C. J. C.

    2017-12-01

    An automated atmospheric river (AR) detection algorithm is used for the South Atlantic Ocean basin, allowing the identification of the major ARs impinging on the west coast of South Africa during the austral winter months (April-September) for the period 1979-2014, using two reanalysis products (NCEP-NCAR and ERA-Interim). The two products show relatively good agreement, with 10-15 persistent ARs (lasting 18h or longer) occurring on average per winter and nearly two thirds of these systems occurring poleward of 35°S. The relationship between persistent AR activity and winter rainfall is demonstrated using South African Weather Service rainfall data. Most stations positioned in areas of high topography contained the highest percentage of rainfall contributed by persistent ARs, whereas stations downwind, to the east of the major topographic barriers, had the lowest contributions. Extreme rainfall days in the region are also ranked by their magnitude and spatial extent. It is found that around 70% of the top 50 daily winter rainfall extremes in South Africa were in some way linked to ARs (both persistent and non-persistent). Results suggest that although persistent ARs are important contributors to heavy rainfall events, they are not necessarily a prerequisite. Overall, the findings of this study support akin assessments in the last decade on ARs in the northern hemisphere bound for the western coasts of USA and Europe. AcknowledgementsThe financial support for attending this workshop was possible through FCT project UID/GEO/50019/2013 - Instituto Dom Luiz. The author wishes also to acknowledge the contribution of project IMDROFLOOD - Improving Drought and Flood Early Warning, Forecasting and Mitigation using real-time hydroclimatic indicators (WaterJPI/0004/2014, Funded by Fundação para a Ciência e a Tecnologia, Portugal (FCT)), with the data provided to achieve this work. A. M. Ramos was also supported by a FCT postdoctoral grant (FCT/DFRH/ SFRH/BPD/84328/2012).

  5. 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.

  6. [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 < 0.01) and also TP mass loss and rainfall, maximum rainfall intensity respectively (p < 0.01).

  7. Averaged RMHD equations

    International Nuclear Information System (INIS)

    Ichiguchi, Katsuji

    1998-01-01

    A new reduced set of resistive MHD equations is derived by averaging the full MHD equations on specified flux coordinates, which is consistent with 3D equilibria. It is confirmed that the total energy is conserved and the linearized equations for ideal modes are self-adjoint. (author)

  8. Determining average yarding distance.

    Science.gov (United States)

    Roger H. Twito; Charles N. Mann

    1979-01-01

    Emphasis on environmental and esthetic quality in timber harvesting has brought about increased use of complex boundaries of cutting units and a consequent need for a rapid and accurate method of determining the average yarding distance and area of these units. These values, needed for evaluation of road and landing locations in planning timber harvests, are easily and...

  9. Average Revisited in Context

    Science.gov (United States)

    Watson, Jane; Chick, Helen

    2012-01-01

    This paper analyses the responses of 247 middle school students to items requiring the concept of average in three different contexts: a city's weather reported in maximum daily temperature, the number of children in a family, and the price of houses. The mixed but overall disappointing performance on the six items in the three contexts indicates…

  10. Averaging operations on matrices

    Indian Academy of Sciences (India)

    2014-07-03

    Jul 3, 2014 ... Role of Positive Definite Matrices. • Diffusion Tensor Imaging: 3 × 3 pd matrices model water flow at each voxel of brain scan. • Elasticity: 6 × 6 pd matrices model stress tensors. • Machine Learning: n × n pd matrices occur as kernel matrices. Tanvi Jain. Averaging operations on matrices ...

  11. Average-energy games

    Directory of Open Access Journals (Sweden)

    Patricia Bouyer

    2015-09-01

    Full Text Available Two-player quantitative zero-sum games provide a natural framework to synthesize controllers with performance guarantees for reactive systems within an uncontrollable environment. Classical settings include mean-payoff games, where the objective is to optimize the long-run average gain per action, and energy games, where the system has to avoid running out of energy. We study average-energy games, where the goal is to optimize the long-run average of the accumulated energy. We show that this objective arises naturally in several applications, and that it yields interesting connections with previous concepts in the literature. We prove that deciding the winner in such games is in NP inter coNP and at least as hard as solving mean-payoff games, and we establish that memoryless strategies suffice to win. We also consider the case where the system has to minimize the average-energy while maintaining the accumulated energy within predefined bounds at all times: this corresponds to operating with a finite-capacity storage for energy. We give results for one-player and two-player games, and establish complexity bounds and memory requirements.

  12. Monsoon rainfall behaviour in recent times on local/regional scale in India

    International Nuclear Information System (INIS)

    Singh, Surender; Rao, V.U.M.; Singh, Diwan

    2002-08-01

    An attempt has been made here to investigate the local/regional monsoon rainfall behaviour in the meteorological sub-division no. 13 comprising the areas of Haryana, Delhi and Chandigarh in India. The monthly monsoon rainfall data of 30 years (1970-99) of different locations in the region were used for the investigation. All locations except Delhi received more rainfall in monsoon season during the decade (1990-99) showing general increasing trend in the rainfall behaviour in recent times. The mean monsoon rainfall at various locations ranged between 324.8 mm at Sirsa and 974.9 mm at Chandigarh. The major amount of monsoon rainfall occurred during the month of July and August in the entire region. Monthly mean rainfall ranged between 37.5 to 144.9 mm (June), 130.6 to 298.2 mm (July), 92.6 to 313.6 mm (August) and 44.0 to 149.4mm (September) at different locations. All the locations in the region exhibited overall increasing trend in monsoon rainfall over the period under study. All locations in the region received their lowest monsoon rainfall in the year 1987 which was a drought year and the season's rainfall ranged between 56.1 mm (Sirsa) and 290.0 mm (Delhi) during this year. Many of the locations observed clusters of fluctuations in their respective monsoon rainfall. The statistical summaries of historical data series (1970-99) gave rainfall information on various time scale. Such information acquires value through its influence on the decision making of the ultimate users. (author)

  13. Impact of Rainfall on Multilane Roundabout Flowrate Contraction

    Science.gov (United States)

    PARKSHIR, Amir; BEN-EDIGBE, Johnnie

    2017-08-01

    In this study, roundabouts at two sites in the Malaysia were investigated under rainy and dry weather conditions. Two automatic traffic counters per roundabout arm as well as two rain gauge stations were used to collect data at each surveyed site. Nearly one million vehicles were investigated at four sites. Vehicle volume, speeds and headways for entry and circulating flows were collected continuously at each roundabout about arm for six weeks between November 2013 and January 2014. Empirical regression technique and gap-acceptance models were modified and used to analyze roundabout capacity. Good fits to the data were obtained; the results also fit models developed in other countries. It was assumed that entry capacity depends on the geometric characteristics of the roundabout, particularly the diameter of the outside circle of the intersection. It was also postulated that geometric characteristics determine the speed of vehicles around the central island and, therefore, have an impact on the gap-acceptance process and consequently the capacity. Only off-peak traffic data per light, moderate or heavy rainfall were analysed. Peak traffic data were not used because of the presence of peak traffic flow. Passenger car equivalent values being an instrument of conversion from traffic volume to flow were modified. Results show that, average entry capacity loss is about 22.6% under light rainfall, about 18.1% under moderate rainfall and about 5.6% under heavy rainfall. Significant entry capacity loss would result from rainfall irrespective of their intensity. It can be postulated that entry capacity loss under heavy rainfall is lowest because the advantage enjoyed by circulating flow would be greatly reduced with increased rainfall intensity. The paper concluded that rainfall has significant impact of flowrate contraction at roundabouts.

  14. 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.

  15. Potentials for Supplemental Irrigation in Some Rainfall Areas of Imo ...

    African Journals Online (AJOL)

    In addition, there were up to five months of the year during which rainwater was much in deficit of evapotranspiration. All these stress the need for irrigation. Analysis of water quality (surface, groundwater, and rainfall runoff) showed their suitability for irrigation. Quantity assessment of supplemental irrigation during the dry ...

  16. Effect of simulated rainfall on gonadal maturation and ripeness in ...

    African Journals Online (AJOL)

    Rainfall and flooding which are major factors in the breeding of catfish in the North Central zone of Nigeria (Semi-arid) were mimicked all-year-round so as to determine if the duration of breeding and hence fingerling production could be extended longer than the usual 5 -6 months period per year. Four different ...

  17. 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

  18. on the performance of Autoregressive Moving Average Polynomial

    African Journals Online (AJOL)

    Timothy Ademakinwa

    estimated using least squares and Newton Raphson iterative methods. To determine the order of the ... r is the degree of polynomial while j is the number of lag of the ..... use a real time series dataset, monthly rainfall and temperature series ...

  19. 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 ...... approximations to the Riemannian metric, and that the subsequent corrections are inherent in the least squares estimation.......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...

  20. 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.

  1. Spatial Interpolation of Rainfall Erosivity Using Artificial Neural Networks for Southern Brazil Conditions

    Directory of Open Access Journals (Sweden)

    Michel Castro Moreira

    Full Text Available ABSTRACT Water erosion is the process of disaggregation and transport of sediments, and rainfall erosivity is a numerical value that expresses the erosive capacity of rain. The scarcity of information on rainfall erosivity makes it difficult or impossible to use to estimate losses occasioned by the erosive process. The objective of this study was to develop Artificial Neural Networks (ANNs for spatial interpolation of the monthly and annual values of rainfall erosivity at any location in the state of Rio Grande do Sul, and a software that enables the use of these networks in a simple and fast manner. This experiment used 103 rainfall stations in Rio Grande do Sul and their surrounding area to generate synthetic rainfall series on the software ClimaBR 2.0. Rainfall erosivity was determined by summing the values of the EI30 and KE >25 indexes, considering two methodologies for obtaining the kinetic energy of rainfall. With these values of rainfall erosivity and latitude, longitude, and altitude of the stations, the ANNs were trained and tested for spatializations of rainfall erosivity. To facilitate the use of the ANNs, a computer program was generated, called netErosividade RS, which makes feasible the use of ANNs to estimate the values of rainfall erosivity for any location in the state of Rio Grande do Sul.

  2. Uganda rainfall variability and prediction

    Science.gov (United States)

    Jury, Mark R.

    2018-05-01

    This study analyzes large-scale controls on Uganda's rainfall. Unlike past work, here, a May-October season is used because of the year-round nature of agricultural production, vegetation sensitivity to rainfall, and disease transmission. The Uganda rainfall record exhibits steady oscillations of ˜3 and 6 years over 1950-2013. Correlation maps at two-season lead time resolve the subtropical ridge over global oceans as an important feature. Multi-variate environmental predictors include Dec-May south Indian Ocean sea surface temperature, east African upper zonal wind, and South Atlantic wind streamfunction, providing a 33% fit to May-Oct rainfall time series. Composite analysis indicates that cool-phase El Niño Southern Oscillation supports increased May-Oct Uganda rainfall via a zonal overturning lower westerly/upper easterly atmospheric circulation. Sea temperature anomalies are positive in the east Atlantic and negative in the west Indian Ocean in respect of wet seasons. The northern Hadley Cell plays a role in limiting the northward march of the equatorial trough from May to October. An analysis of early season floods found that moist inflow from the west Indian Ocean converges over Uganda, generating diurnal thunderstorm clusters that drift southwestward producing high runoff.

  3. 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......) as the model of the storm sewer system. The output of the simulation is the frequency distribution of the peak flow, overflow volume etc. from the overflow or retention storage. The parameters in the transfer model is found either from rainfall/runoff measurements in the catchment or from one or a few...

  4. 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

  5. Average is Over

    Science.gov (United States)

    Eliazar, Iddo

    2018-02-01

    The popular perception of statistical distributions is depicted by the iconic bell curve which comprises of a massive bulk of 'middle-class' values, and two thin tails - one of small left-wing values, and one of large right-wing values. The shape of the bell curve is unimodal, and its peak represents both the mode and the mean. Thomas Friedman, the famous New York Times columnist, recently asserted that we have entered a human era in which "Average is Over" . In this paper we present mathematical models for the phenomenon that Friedman highlighted. While the models are derived via different modeling approaches, they share a common foundation. Inherent tipping points cause the models to phase-shift from a 'normal' bell-shape statistical behavior to an 'anomalous' statistical behavior: the unimodal shape changes to an unbounded monotone shape, the mode vanishes, and the mean diverges. Hence: (i) there is an explosion of small values; (ii) large values become super-large; (iii) 'middle-class' values are wiped out, leaving an infinite rift between the small and the super large values; and (iv) "Average is Over" indeed.

  6. 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.

  7. a stochastic assessment of the effect of global warming on rainfall

    African Journals Online (AJOL)

    PROF EKWUEME

    KEYWORDS: Global Warming; Rainfall; Markov Process; Time Series; Agriculture. INTRODUCTION ... Central Region of Nigeria in the last three decades using .... r. Time. MSD: MAD: MAPE: Length: Moving Average. 68492.0. 229.3. 3806.2. 4.

  8. TRMM Precipitation Radar (PR) Gridded Rainfall Product (TRMM Product 3A25) V6

    Data.gov (United States)

    National Aeronautics and Space Administration — The primary objective of algorithm 3A25 is to compute various rainfall statistics over a month from the level 2 PR products. The statistics are derived at two...

  9. TRMM Precipitation Radar (PR) Gridded Rainfall Product (TRMM Product 3A25) V7

    Data.gov (United States)

    National Aeronautics and Space Administration — The primary objective of algorithm 3A25 is to compute various rainfall statistics over a month from the level 2 PR products. The statistics are derived at two...

  10. Extreme Rainfall In A City

    Science.gov (United States)

    Nkemdirim, Lawrence

    Cities contain many structures and activities that are vulnerable to severe weather. Heavy precipitation cause floods which can damage structures, compromise transportation and water supply systems, and slow down economic and social activities. Rain induced flood patterns in cities must be well understood to enable effective placement of flood control and other regulatory measures. The planning goal is not to eliminate all floods but to reduce their frequency and resulting damage. Possible approaches to such planning include probability based extreme event analysis. Precipitation is normally the most variable hydrologic element over a given area. This variability results from the distribution of clouds and in cloud processes in the atmosphere, the storm path, and the distribution of topographical features on the ground along path. Some studies suggest that point rainfall patterns are also affected by urban industrial effects hence some agreement that cities are wetter than the country surrounding them. However, there are still questions regarding the intra- urban distribution of precipitation. The sealed surfaces, urban structures, and the urban heat anomaly increase convection in cities which may enhance the generation of clouds. Increased dust and gaseous aerosols loads are effective condensation and sublimation nuclei which may also enhance the generation of precipitation. Based on these associations, the greatest amount of convection type rainfall should occur at city center. A study of summer rainfall in Calgary showed that frequencies of trace amounts of rainfall and events under 0.2mm are highest downtown than elsewhere. For amounts greater than than 0.2 mm, downtown sites were not favored. The most compelling evidence for urban-industrial precipitation enhancement came from the Metromex project around St. Loius, Missouri where maximum increases of between 5 to 30 per cent in summer rainfall downwind of the city was linked to urbanization and

  11. Examining spatial-temporal variability and prediction of rainfall in North-eastern Nigeria

    Science.gov (United States)

    Muhammed, B. U.; Kaduk, J.; Balzter, H.

    2012-12-01

    In the last 50 years rainfall in North-eastern Nigeria under the influence of the West African Monsoon (WAM) has been characterised by large annual variations with severe droughts recorded in 1967-1973, and 1983-1987. This variability in rainfall has a large impact on the regions agricultural output, economy and security where the majority of the people depend on subsistence agriculture. In the 1990s there was a sign of recovery with higher annual rainfall totals compared to the 1961-1990 period but annual totals were slightly above the long term mean for the century. In this study we examine how significant this recovery is by analysing medium-term (1980-2006) rainfall of the region using the Climate Research Unit (CRU) and National Centre for Environment Prediction (NCEP) precipitation ½ degree, 6 hourly reanalysis data set. Percentage coefficient of variation increases northwards for annual rainfall (10%-35%) and the number of rainy days (10%-50%). The standardized precipitation index (SPI) of the area shows 7 years during the period as very wet (1996, 1999, 2003 and 2004) with SPI≥1.5 and moderately wet (1993, 1998, and 2006) with values of 1.0≥SPI≤1.49. Annual rainfall indicates a recovery from the 1990s and onwards but significant increases (in the amount of rainfall and number of days recorded with rainfall) is only during the peak of the monsoon season in the months of August and September (pARIMA) model. The model is further evaluated using 24 months rainfall data yielding r=0.79 (regression slope=0.8; pARIMA model and the rainfall data used for this study indicates that the model can be satisfactorily used in forecasting rainfall in the in the sub-humid part of North-eastern Nigeria over a 24 months period.

  12. Effect of temporal averaging of meteorological data on predictions of groundwater recharge

    Directory of Open Access Journals (Sweden)

    Batalha Marcia S.

    2018-06-01

    Full Text Available Accurate estimates of infiltration and groundwater recharge are critical for many hydrologic, agricultural and environmental applications. Anticipated climate change in many regions of the world, especially in tropical areas, is expected to increase the frequency of high-intensity, short-duration precipitation events, which in turn will affect the groundwater recharge rate. Estimates of recharge are often obtained using monthly or even annually averaged meteorological time series data. In this study we employed the HYDRUS-1D software package to assess the sensitivity of groundwater recharge calculations to using meteorological time series of different temporal resolutions (i.e., hourly, daily, weekly, monthly and yearly averaged precipitation and potential evaporation rates. Calculations were applied to three sites in Brazil having different climatological conditions: a tropical savanna (the Cerrado, a humid subtropical area (the temperate southern part of Brazil, and a very wet tropical area (Amazonia. To simplify our current analysis, we did not consider any land use effects by ignoring root water uptake. Temporal averaging of meteorological data was found to lead to significant bias in predictions of groundwater recharge, with much greater estimated recharge rates in case of very uneven temporal rainfall distributions during the year involving distinct wet and dry seasons. For example, at the Cerrado site, using daily averaged data produced recharge rates of up to 9 times greater than using yearly averaged data. In all cases, an increase in the time of averaging of meteorological data led to lower estimates of groundwater recharge, especially at sites having coarse-textured soils. Our results show that temporal averaging limits the ability of simulations to predict deep penetration of moisture in response to precipitation, so that water remains in the upper part of the vadose zone subject to upward flow and evaporation.

  13. Average nuclear surface properties

    International Nuclear Information System (INIS)

    Groote, H. von.

    1979-01-01

    The definition of the nuclear surface energy is discussed for semi-infinite matter. This definition is extended also for the case that there is a neutron gas instead of vacuum on the one side of the plane surface. The calculations were performed with the Thomas-Fermi Model of Syler and Blanchard. The parameters of the interaction of this model were determined by a least squares fit to experimental masses. The quality of this fit is discussed with respect to nuclear masses and density distributions. The average surface properties were calculated for different particle asymmetry of the nucleon-matter ranging from symmetry beyond the neutron-drip line until the system no longer can maintain the surface boundary and becomes homogeneous. The results of the calculations are incorporated in the nuclear Droplet Model which then was fitted to experimental masses. (orig.)

  14. Americans' Average Radiation Exposure

    International Nuclear Information System (INIS)

    2000-01-01

    We live with radiation every day. We receive radiation exposures from cosmic rays, from outer space, from radon gas, and from other naturally radioactive elements in the earth. This is called natural background radiation. It includes the radiation we get from plants, animals, and from our own bodies. We also are exposed to man-made sources of radiation, including medical and dental treatments, television sets and emission from coal-fired power plants. Generally, radiation exposures from man-made sources are only a fraction of those received from natural sources. One exception is high exposures used by doctors to treat cancer patients. Each year in the United States, the average dose to people from natural and man-made radiation sources is about 360 millirem. A millirem is an extremely tiny amount of energy absorbed by tissues in the body

  15. 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.

  16. Commercial application of rainfall simulation

    Science.gov (United States)

    Loch, Rob J.

    2010-05-01

    Landloch Pty Ltd is a commercial consulting firm, providing advice on a range of land management issues to the mining and construction industries in Australia. As part of the company's day-to-day operations, rainfall simulation is used to assess material erodibility and to investigate a range of site attributes. (Landloch does carry out research projects, though such are not its core business.) When treated as an everyday working tool, several aspects of rainfall simulation practice are distinctively modified. Firstly, the equipment used is regularly maintained, and regularly upgraded with a primary focus on ease, safety, and efficiency of use and on reliability of function. As well, trained and experienced technical support is considered essential. Landloch's chief technician has over 10 years experience in running rainfall simulators at locations across Australia and in Africa and the Pacific. Secondly, the specific experimental conditions established for each set of rainfall simulator runs are carefully considered to ensure that they accurately represent the field conditions to which the data will be subsequently applied. Considerations here include: • wetting and drying cycles to ensure material consolidation and/or cementation if appropriate; • careful attention to water quality if dealing with clay soils or with amendments such as gypsum; • strong focus on ensuring that the erosion processes considered are those of greatest importance to the field situation of concern; and • detailed description of both material and plot properties, to increase the potential for data to be applicable to a wider range of projects and investigations. Other important company procedures include: • For each project, the scientist or engineer responsible for analysing and reporting rainfall simulator data is present during the running of all field plots, as it is essential that they be aware of any specific conditions that may have developed when the plots were subjected

  17. 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.

  18. Tea shoot production in relation to rainfall, solar radiation, and temperature in Pagilaran tea estate, Batang

    International Nuclear Information System (INIS)

    Yudono, P.

    2000-01-01

    Tea shoot production pattern in PT Pagilaran tea estate, Batang, is studied in relation to rainfall, solar radiation, and temperature. Pagilaran tea estate is located at 700-1,500 m above the sea level, with temperature of 15-30 deg. C and rainfall ranging from 4,500 mm to 7,000 mm per year. However, the area is also characterized by two up to three dry months for every three years. Monthly data of rainfall, solar radiation, and temperature were collected and were related to tea shoot production using correlation and regression analysis. The results indicated that there was no significant different pattern of tea shoot production form the three estate units (Kayulandak, Pagilaran, and Andongsili). Monthly shoots production increases during October up to December, and then goes down in January up to February. It fluctuated at a lesser degree in the upper units (Kayulandak and Andongsili) which might be attributed to better soil moisture available in the area. They are right below a forests area which understandably serves as rainfall catchment area and maintains soil moisture of the area below in a better condition. Weak to moderate correlation was obtained when monthly tea shoot production was correlated to amount of rainfall (r = -0.3771), days of rainfall (r = -0.3512), maximum temperature (r = -0.3502), minimum temperature (r = -0.2786), and solar radiation (r=0.6607) of the same month. On regressing monthly tea shoot production to those variables, rainfall and duration of solar radiation turned out to be the two significant factors through the following equation y = 759.5616-0.1802 xi-1 + 0.1057 xi-2 + 0.5239 zi-1 (R at the power of 2 = 0.3398), where y = tea shoots production, x=amount of monthly rainfall, z=duration of solar radiation, and i refer to month [in

  19. 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

  20. Daddy Months

    OpenAIRE

    Volker Meier; Helmut Rainer

    2014-01-01

    We consider a bargaining model in which husband and wife decide on the allocation of time and disposable income. Since her bargaining power would go down otherwise more strongly, the wife agrees to having a child only if the husband also leaves the labor market for a while. The daddy months subsidy enables the couple to overcome a hold-up problem and thereby improves efficiency. However, the same ruling harms cooperative couples and may also reduce welfare in an endogenous taxation framework.

  1. 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

  2. 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.

  3. Rainfall estimation with TFR model using Ensemble Kalman filter

    Science.gov (United States)

    Asyiqotur Rohmah, Nabila; Apriliani, Erna

    2018-03-01

    Rainfall fluctuation can affect condition of other environment, correlated with economic activity and public health. The increasing of global average temperature is influenced by the increasing of CO2 in the atmosphere, which caused climate change. Meanwhile, the forests as carbon sinks that help keep the carbon cycle and climate change mitigation. Climate change caused by rainfall intensity deviations can affect the economy of a region, and even countries. It encourages research on rainfall associated with an area of forest. In this study, the mathematics model that used is a model which describes the global temperatures, forest cover, and seasonal rainfall called the TFR (temperature, forest cover, and rainfall) model. The model will be discretized first, and then it will be estimated by the method of Ensemble Kalman Filter (EnKF). The result shows that the more ensembles used in estimation, the better the result is. Also, the accurateness of simulation result is influenced by measurement variable. If a variable is measurement data, the result of simulation is better.

  4. ANALYSIS OF EFFECTIVE RAINFALL INTENSITY AND WORKING RAINFALL FOR BASIC WARNING CRITERIA DEVELOPMENT ON LAHAR FLOW EVENT

    Directory of Open Access Journals (Sweden)

    Fitriyadi Fitriyadi

    2015-05-01

    The research results showed that the number of reviewed serial rain with total value ≥ 80 mm is 9.28% of the whole serial rain, and 12.5% of them caused lahar flow in Gendol River. Debris flow occurrence probability on total rainfall amount of ≥ 80 mm that may occur on Gendol River amounted to 1.89%. This value represents less possibility of debris flow in Gendol River, this is due to the rain conditions in the Gendol Watershed different from the situation in Japan as well as the limitations of the available data. It is recommended for further research on the limitation of total rainfall in accordance with the conditions in Gendol Watershed by considering other parameters becoming the lahar flow controller factor. Further, it is necessary to perform the analysis using rain catchment method by averaging rainfall values on each of serial rain.

  5. Validation of Satellite Estimates (Tropical Rainfall Measuring Mission, TRMM for Rainfall Variability over the Pacific Slope and Coast of Ecuador

    Directory of Open Access Journals (Sweden)

    Bolívar Erazo

    2018-02-01

    Full Text Available A dense rain-gauge network within continental Ecuador was used to evaluate the quality of various products of rainfall data over the Pacific slope and coast of Ecuador (EPSC. A cokriging interpolation method is applied to the rain-gauge data yielding a gridded product at 5-km resolution covering the period 1965–2015. This product is compared with the Global Precipitation Climatology Centre (GPCC dataset, the Climatic Research Unit–University of East Anglia (CRU dataset, the Tropical Rainfall Measuring Mission (TRMM/TMPA 3B43 Version 7 dataset and the ERA-Interim Reanalysis. The analysis reveals that TRMM data show the most realistic features. The relative bias index (Rbias indicates that TRMM data is closer to the observations, mainly over lowlands (mean Rbias of 7% but have more limitations in reproducing the rainfall variability over the Andes (mean Rbias of −28%. The average RMSE and Rbias of 68.7 and −2.8% of TRMM are comparable with the GPCC (69.8 and 5.7% and CRU (102.3 and −2.3% products. This study also focuses on the rainfall inter-annual variability over the study region which experiences floods that have caused high economic losses during extreme El Niño events. Finally, our analysis evaluates the ability of TRMM data to reproduce rainfall events during El Niño years over the study area and the large basins of Esmeraldas and Guayas rivers. The results show that TRMM estimates report reasonable levels of heavy rainfall detection (for the extreme 1998 El Niño event over the EPSC and specifically towards the center-south of the EPSC (Guayas basin but present underestimations for the moderate El Niño of 2002–2003 event and the weak 2009–2010 event. Generally, the rainfall seasonal features, quantity and long-term climatology patterns are relatively well estimated by TRMM.

  6. Associação genética da prenhez aos 16 meses com o peso à desmama e o ganho de peso em animais da raça Nelore Genetic associations of heifer pregnancy at 16 months with weaning weight and average daily gain from weaning to yearling in Nellore cattle

    Directory of Open Access Journals (Sweden)

    Luciana Shiotsuki

    2009-07-01

    Full Text Available Objetivou-se verificar a possibilidade de utilização da prenhez de novilhas aos 16 meses (Pr16 como critério de seleção e as possíveis associações genéticas entre prenhez em novilhas aos 16 meses e o peso à desmama (PD e o ganho de peso médio da desmama ao sobreano (GP. Foram realizadas análises uni e bicaracterísticas para estimação dos componentes de co-variância, empregando-se um modelo animal linear para peso à desmama e ganho de peso da desmama ao sobreano e não-linear para Pr16. A estimação dos componentes de variância e da predição dos valores genéticos dos animais foi realizada por Inferência Bayesiana. Distribuições "flat" foram utilizadas para todos os componentes de co-variância. As estimativas de herdabilidade direta para Pr16, PD e GP foram 0,50; 0,24 e 0,15, respectivamente, e a estimativa de herdabilidade materna para o PD, de 0,07. As correlações genéticas foram -0,25 e 0,09 entre Pr16, PD e GP, respectivamente, e a correlação genética entre Pr16 e o efeito genético materno do PD, de 0,29. A herdabilidade da prenhez aos 16 meses indica que essa característica pode ser utilizada como critério de seleção. As correlações genéticas estimadas indicam que a seleção por animais mais pesados à desmama, a longo prazo, pode diminuir a ocorrência de prenhez aos 16 meses de idade. Além disso, a seleção para maior habilidade materna favorece a seleção de animais mais precoces. No entanto, a seleção para ganho de peso da desmama ao sobreano não leva a mudanças genéticas na precocidade sexual em fêmeas.The objective of the present study was to determine the possible use of heifer pregnancy at 16 months (HP16 as a selection criterion and its possible genetic associations with weaning weight (WW and average daily gain from weaning to yearling (ADGWY. Covariance components were estimated by uni and bivariate animal models assuming a linear model for weaning weight and average daily gain from

  7. 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.

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

    Directory of Open Access Journals (Sweden)

    Assumpta Mukabutera

    2016-08-01

    Full Text Available Abstract Background 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. Methods 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. Results 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. Conclusion 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.

  9. 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.

  10. Simulation of Tropical Rainfall Variability

    Science.gov (United States)

    Bader, J.; Latif, M.

    2002-12-01

    The impact of sea surface temperature (SST) - especially the role of the tropical Atlantic meridional SST gradient and the El Nino-Southern Oscillation - on precipitation is investigated with the atmospheric general circulation model ECHAM4/T42. Ensemble experiments - driven with observed SST - show that Atlantic SST has a significant influence on precipitation over West Africa and northeast Brazil. SST sensitivity experiments were performed in which the climatological SST was enhanced or decreased by one Kelvin in certain ocean areas. Changing SST in the eastern tropical Atlantic caused only significant changes along the Guinea Coast, with a positive anomaly (SSTA) increasing rainfall and a negative SSTA reducing it. The response was nearly linear. Changing SST in other ocean areas caused significant changes over West Africa, especially in the Sahel area. The response is found to be non linear, with only negative SSTA leading to significant reduction in Sahel rainfall. Also, the impact of the SSTAs from the different ocean regions was not additive with respect to the rainfall. The influence of SST on precipitation over northeast Brazil (Nordeste) was also investigated. Three experiments were performed in which the climatological SST was enhanced/decreased or decreased/enhanced by one Kelvin in the North/South Atlantic and increased by two Kelvin in the Nino3 ocean area. All experiments caused significant changes over Nordeste, with an enhanced/reduced SST gradient in the Atlantic increasing/reducing rainfall. The response was nearly linear. The main effect of the Atlantic SST gradient was a shift of the ITCZ, caused by trade wind changes. The ''El Nino'' event generates a significant reduction in Nordeste rainfall. A significant positive SLP anomaly occurs in northeast Brazil which may be associated with the descending branch of the Walker circulation. Also a significant positive SLP over the Atlantic from 30S to 10N north occurs. This results in a reduced SLP

  11. The effects of wind and rainfall on suspended sediment concentration related to the 2004 Indian Ocean tsunami

    International Nuclear Information System (INIS)

    Zhang Xinfeng; Tang Danling; Li Zizhen; Zhang Fengpan

    2009-01-01

    The effects of rainfall and wind speed on the dynamics of suspended sediment concentration (SSC), during the 2004 Indian Ocean tsunami, were analyzed using spatial statistical models. The results showed a positive effect of wind speed on SSC, and inconsistent effects (positive and negative) of rainfall on SSC. The effects of wind speed and rainfall on SSC weakened immediately around the tsunami, indicating tsunami-caused floods and earthquake-induced shaking may have suddenly disturbed the ocean-atmosphere interaction processes, and thus weakened the effects of wind speed and rainfall on SSC. Wind speed and rainfall increased markedly, and reached their maximum values immediately after the tsunami week. Rainfall at this particular week exceeded twice the average for the same period over the previous 4 years. The tsunami-affected air-sea interactions may have increased both wind speed and rainfall immediately after the tsunami week, which directly lead to the variations in SSC.

  12. Estimation of typhoon rainfall in GaoPing River: A Multivariate Maximum Entropy Method

    Science.gov (United States)

    Pei-Jui, Wu; Hwa-Lung, Yu

    2016-04-01

    The heavy rainfall from typhoons is the main factor of the natural disaster in Taiwan, which causes the significant loss of human lives and properties. Statistically average 3.5 typhoons invade Taiwan every year, and the serious typhoon, Morakot in 2009, impacted Taiwan in recorded history. Because the duration, path and intensity of typhoon, also affect the temporal and spatial rainfall type in specific region , finding the characteristics of the typhoon rainfall type is advantageous when we try to estimate the quantity of rainfall. This study developed a rainfall prediction model and can be divided three parts. First, using the EEOF(extended empirical orthogonal function) to classify the typhoon events, and decompose the standard rainfall type of all stations of each typhoon event into the EOF and PC(principal component). So we can classify the typhoon events which vary similarly in temporally and spatially as the similar typhoon types. Next, according to the classification above, we construct the PDF(probability density function) in different space and time by means of using the multivariate maximum entropy from the first to forth moment statistically. Therefore, we can get the probability of each stations of each time. Final we use the BME(Bayesian Maximum Entropy method) to construct the typhoon rainfall prediction model , and to estimate the rainfall for the case of GaoPing river which located in south of Taiwan.This study could be useful for typhoon rainfall predictions in future and suitable to government for the typhoon disaster prevention .

  13. Modelling monthly runoff generation processes following land use changes: groundwater-surface runoff interactions

    Science.gov (United States)

    Bari, M.; Smettem, K. R. J.

    A conceptual water balance model is presented to represent changes in monthly water balance following land use changes. Monthly rainfall-runoff, groundwater and soil moisture data from four experimental catchments in Western Australia have been analysed. Two of these catchments, "Ernies" (control, fully forested) and "Lemon" (54% cleared) are in a zone of mean annual rainfall of 725 mm, while "Salmon" (control, fully forested) and "Wights" (100% cleared) are in a zone with mean annual rainfall of 1125 mm. At the Salmon forested control catchment, streamflow comprises surface runoff, base flow and interflow components. In the Wights catchment, cleared of native forest for pasture development, all three components increased, groundwater levels rose significantly and stream zone saturated area increased from 1% to 15% of the catchment area. It took seven years after clearing for the rainfall-runoff generation process to stabilise in 1984. At the Ernies forested control catchment, the permanent groundwater system is 20 m below the stream bed and so does not contribute to streamflow. Following partial clearing of forest in the Lemon catchment, groundwater rose steadily and reached the stream bed by 1987. The streamflow increased in two phases: (i) immediately after clearing due to reduced evapotranspiration, and (ii) through an increase in the groundwater-induced stream zone saturated area after 1987. After analysing all the data available, a conceptual monthly model was created, comprising four inter-connecting stores: (i) an upper zone unsaturated store, (ii) a transient stream zone store, (ii) a lower zone unsaturated store and (iv) a saturated groundwater store. Data such as rooting depth, Leaf Area Index, soil porosity, profile thickness, depth to groundwater, stream length and surface slope were incorporated into the model as a priori defined attributes. The catchment average values for different stores were determined through matching observed and predicted

  14. Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

    Science.gov (United States)

    Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

    2018-01-01

    Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are

  15. Continuous rainfall simulation for regional flood risk assessment - application in the Austrian Alps

    Science.gov (United States)

    Salinas, Jose Luis; Nester, Thomas; Komma, Jürgen; Blöschl, Günter

    2017-04-01

    Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of the observed rainfall characteristics, such as regional intensity-duration-frequency curves, is necessary to adequately model the magnitude and frequency of the flood peaks. Furthermore, the replication of the observed rainfall spatial and temporal correlations allows to model important other hydrological features like antecedent soil moisture conditions before extreme rainfall events. In this work, we present an application in the Tirol region (Austrian alps) of a modification of the model presented by Bardossy and Platte (1992), where precipitation is modeled on a station basis as a mutivariate autoregressive model (mAr) in a Normal space, and then transformed to a Gamma-distributed space. For the sake of simplicity, the parameters of the Gamma distributions are assumed to vary monthly according to a sinusoidal function, and are calibrated trying to simultaneously reproduce i) mean annual rainfall, ii) mean daily rainfall amounts, iii) standard deviations of daily rainfall amounts, and iv) 24-hours intensity duration frequency curve. The calibration of the spatial and temporal correlation parameters is performed in a way that the intensity-duration-frequency curves aggregated at different spatial and temporal scales reproduce the measured ones. Bardossy, A., and E. J. Plate (1992), Space-time model for daily rainfall using atmospheric circulation patterns, Water Resour. Res., 28(5), 1247-1259, doi:10.1029/91WR02589.

  16. Heavy rainfall in Mediterranean cyclones. Part I: contribution of deep convection and warm conveyor belt

    Science.gov (United States)

    Flaounas, Emmanouil; Kotroni, Vassiliki; Lagouvardos, Konstantinos; Gray, Suzanne L.; Rysman, Jean-François; Claud, Chantal

    2018-04-01

    In this study, we provide an insight to the role of deep convection (DC) and the warm conveyor belt (WCB) as leading processes to Mediterranean cyclones' heavy rainfall. To this end, we use reanalysis data, lighting and satellite observations to quantify the relative contribution of DC and the WCB to cyclone rainfall, as well as to analyse the spatial and temporal variability of these processes with respect to the cyclone centre and life cycle. Results for the period 2005-2015 show that the relationship between cyclone rainfall and intensity has high variability and demonstrate that even intense cyclones may produce low rainfall amounts. However, when considering rainfall averages for cyclone intensity bins, a linear relationship was found. We focus on the 500 most intense tracked cyclones (responsible for about 40-50% of the total 11-year Mediterranean rainfall) and distinguish between the ones producing high and low rainfall amounts. DC and the WCB are found to be the main cause of rainfall for the former (producing up to 70% of cyclone rainfall), while, for the latter, DC and the WCB play a secondary role (producing up to 50% of rainfall). Further analysis showed that rainfall due to DC tends to occur close to the cyclones' centre and to their eastern sides, while the WCBs tend to produce rainfall towards the northeast. In fact, about 30% of rainfall produced by DC overlaps with rainfall produced by WCBs but this represents only about 8% of rainfall produced by WCBs. This suggests that a considerable percentage of DC is associated with embedded convection in WCBs. Finally, DC was found to be able to produce higher rain rates than WCBs, exceeding 50 mm in 3-h accumulated rainfall compared to a maximum of the order of 40 mm for WCBs. Our results demonstrate in a climatological framework the relationship between cyclone intensity and processes that lead to heavy rainfall, one of the most prominent environmental risks in the Mediterranean. Therefore, we set

  17. 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.

  18. Asian Summer Monsoon Rainfall associated with ENSO and its Predictability

    Science.gov (United States)

    Shin, C. S.; Huang, B.; Zhu, J.; Marx, L.; Kinter, J. L.; Shukla, J.

    2015-12-01

    The leading modes of the Asian summer monsoon (ASM) rainfall variability and their seasonal predictability are investigated using the CFSv2 hindcasts initialized from multiple ocean analyses over the period of 1979-2008 and observation-based analyses. It is shown that the two leading empirical orthogonal function (EOF) modes of the observed ASM rainfall anomalies, which together account for about 34% of total variance, largely correspond to the ASM responses to the ENSO influences during the summers of the developing and decaying years of a Pacific anomalous event, respectively. These two ASM modes are then designated as the contemporary and delayed ENSO responses, respectively. It is demonstrated that the CFSv2 is capable of predicting these two dominant ASM modes up to the lead of 5 months. More importantly, the predictability of the ASM rainfall are much higher with respect to the delayed ENSO mode than the contemporary one, with the predicted principal component time series of the former maintaining high correlation skill and small ensemble spread with all lead months whereas the latter shows significant degradation in both measures with lead-time. A composite analysis for the ASM rainfall anomalies of all warm ENSO events in this period substantiates the finding that the ASM is more predictable following an ENSO event. The enhanced predictability mainly comes from the evolution of the warm SST anomalies over the Indian Ocean in the spring of the ENSO maturing phases and the persistence of the anomalous high sea surface pressure over the western Pacific in the subsequent summer, which the hindcasts are able to capture reasonably well. The results also show that the ensemble initialization with multiple ocean analyses improves the CFSv2's prediction skill of both ENSO and ASM rainfall. In fact, the skills of the ensemble mean hindcasts initialized from the four different ocean analyses are always equivalent to the best ones initialized from any individual ocean

  19. Performance of High Resolution Satellite Rainfall Products over Data Scarce Parts of Eastern Ethiopia

    Directory of Open Access Journals (Sweden)

    Shimelis B. Gebere

    2015-09-01

    Full Text Available Accurate estimation of rainfall in mountainous areas is necessary for various water resource-related applications. Though rain gauges accurately measure rainfall, they are rarely found in mountainous regions and satellite rainfall data can be used as an alternative source over these regions. This study evaluated the performance of three high-resolution satellite rainfall products, the Tropical Rainfall Measuring Mission (TRMM 3B42, the Global Satellite Mapping of Precipitation (GSMaP_MVK+, and the Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Networks (PERSIANN at daily, monthly, and seasonal time scales against rain gauge records over data-scarce parts of Eastern Ethiopia. TRMM 3B42 rain products show relatively better performance at the three time scales, while PERSIANN did much better than GSMaP. At the daily time scale, TRMM correctly detected 88% of the rainfall from the rain gauge. The correlation at the monthly time scale also revealed that the TRMM has captured the observed rainfall better than the other two. For Belg (short rain and Kiremt (long rain seasons, the TRMM did better than the others by far. However, during Bega (dry season, PERSIANN showed a relatively good estimate. At all-time scales, noticing the bias, TRMM tends to overestimate, while PERSIANN and GSMaP tend to underestimate the rainfall. The overall result suggests that monthly and seasonal TRMM rainfall performed better than daily rainfall. It has also been found that both GSMaP and PERSIANN performed better in relatively flat areas than mountainous areas. Before the practical use of TRMM, the RMSE value needs to be improved by considering the topography of the study area or adjusting the bias.

  20. 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)

  1. Migration of 99Tc in unsaturated Chinese loess under artificial rainfall condition: an in situ test

    International Nuclear Information System (INIS)

    Liu, C.L.; Wang, X.Y.; Wang, H.F.; Li, R.J.; Tang, L.T.

    2001-01-01

    The migration of 99 Tc in unsaturated Chinese loess under artificial rainfall condition was investigated in situ. Water suckers were buried at different depths under the bottom of an experimental pit of 2 m x 2 m x 1 m (deep). Quartz containing 3 H and 99 Tc was introduced into the experimental pit to an area of 40 cm x 40 cm and the pit was backfilled to a thickness of 30 cm. An artificial rainfall of 5 mm/h was applied to the experimental pit 4 h a day for 3 months. Moisture water samples were sucked with the help of a vacuum pumping system and the activity of 3 H and 99 Tc in the samples was determined. Breakthrough curves of 3 H and 99 Tc indicated that 99 Tc was slightly retarded. The calculated average apparent distribution coefficient of 99 Tc in the medium was (1.98 ± 0.42) x 10 -2 ml/g. (orig.)

  2. 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

  3. Analysis of climate change impact on rainfall pattern of Sambas district, West Kalimantan

    Science.gov (United States)

    Berliana Sipayung, Sinta; Nurlatifah, Amalia; Siswanto, Bambang; Slamet S, Lilik

    2018-05-01

    Climate change is one of the most important issues being discussed globally. It caused by global warming and indirectly affecting the world climate cycle. This research discussed the effect of climate change on rainfall pattern of Sambas District and predicted the future rainfall pattern due to climate change. CRU and TRMM were used and has been validated using in situ data. This research was used Climate Modelling and Prediction using CCAM (Conformal Cubic Atmospheric Model) which also validated by in situ data (correlation= 0.81). The results show that temperature trends in Sambas regency increased to 0.082°C/yr from 1991-2014 according to CRU data. High temperature trigger changes in rainfall patterns. Rainfall pattern in Sambas District has an equatorial type where the peak occurs when the sun is right on the equator. Rainfall in Sambas reaches the maximum in March and September when the equinox occurs. The CCAM model is used to project rainfall in Sambas District in the future. The model results show that rainfall in Sambas District is projected to increase to 0.018 mm/month until 2055 so the flow rate increase 0.006 m3/month and the water balance increase 0.009 mm/month.

  4. Parents' Reactions to Finding Out That Their Children Have Average or above Average IQ Scores.

    Science.gov (United States)

    Dirks, Jean; And Others

    1983-01-01

    Parents of 41 children who had been given an individually-administered intelligence test were contacted 19 months after testing. Parents of average IQ children were less accurate in their memory of test results. Children with above average IQ experienced extremely low frequencies of sibling rivalry, conceit or pressure. (Author/HLM)

  5. 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

  6. The modification of the typhoon rainfall climatology model in Taiwan

    Directory of Open Access Journals (Sweden)

    C.-S. Lee

    2013-01-01

    Full Text Available This study is focused on the modification of a typhoon rainfall climatological model, by using the dataset up to 2006 and including data collected from rain gauge stations established after the 921 earthquake (1999. Subsequently, the climatology rainfall models for westward- and northward-moving typhoons are established by using the typhoon track classification from the Central Weather Bureau. These models are also evaluated and examined using dependent cases collected between 1989 and 2006 and independent cases collected from 2007 to 2011. For the dependent cases, the average total rainfall at all rain gauge stations forecasted using the climatology rainfall models for westward- (W-TRCM12 and northward-moving (N-TRCM12 typhoons is superior to that obtained using the original climatological model (TRCM06. Model W-TRCM12 significantly improves the precipitation underestimation of model TRCM06. The independent cases show that model W-TRCM12 provides better accumulated rainfall forecasts and distributions than model TRCM06. A climatological model for accompanied northeastern monsoons (A-TRCM12 for special typhoon types has also been established. The current A-TRCM12 model only contains five historical cases and various typhoon combinations can cause precipitation in different regions. Therefore, precipitation is likely to be significantly overestimated and high false alarm ratios are likely to occur in specific regions. For example, model A-TRCM12 significantly overestimates the rainfall forecast for Typhoon Mitag, an independent case from 2007. However, it has a higher probability of detection than model TRCM06. From a disaster prevention perspective, a high probability of detection is much more important than a high false alarm ratio. The modified models can contribute significantly to operational forecast.

  7. Potential Predictability and Prediction Skill for Southern Peru Summertime Rainfall

    Science.gov (United States)

    WU, S.; Notaro, M.; Vavrus, S. J.; Mortensen, E.; Block, P. J.; Montgomery, R. J.; De Pierola, J. N.; Sanchez, C.

    2016-12-01

    The central Andes receive over 50% of annual climatological rainfall during the short period of January-March. This summertime rainfall exhibits strong interannual and decadal variability, including severe drought events that incur devastating societal impacts and cause agricultural communities and mining facilities to compete for limited water resources. An improved seasonal prediction skill of summertime rainfall would aid in water resource planning and allocation across the water-limited southern Peru. While various underlying mechanisms have been proposed by past studies for the drivers of interannual variability in summertime rainfall across southern Peru, such as the El Niño-Southern Oscillation (ENSO), Madden Julian Oscillation (MJO), and extratropical forcings, operational forecasts continue to be largely based on rudimentary ENSO-based indices, such as NINO3.4, justifying further exploration of predictive skill. In order to bridge this gap between the understanding of driving mechanisms and the operational forecast, we performed systematic studies on the predictability and prediction skill of southern Peru summertime rainfall by constructing statistical forecast models using best available weather station and reanalysis datasets. At first, by assuming the first two empirical orthogonal functions (EOFs) of summertime rainfall are predictable, the potential predictability skill was evaluated for southern Peru. Then, we constructed a simple regression model, based on the time series of tropical Pacific sea-surface temperatures (SSTs), and a more advanced Linear Inverse Model (LIM), based on the EOFs of tropical ocean SSTs and large-scale atmosphere variables from reanalysis. Our results show that the LIM model consistently outperforms the more rudimentary regression models on the forecast skill of domain averaged precipitation index and individual station indices. The improvement of forecast correlation skill ranges from 10% to over 200% for different

  8. 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.

  9. 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.

  10. 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.

  11. Statistical analysis of trends in monthly precipitation at the Limbang River Basin, Sarawak (NW Borneo), Malaysia

    Science.gov (United States)

    Krishnan, M. V. Ninu; Prasanna, M. V.; Vijith, H.

    2018-05-01

    Effect of climate change in a region can be characterised by the analysis of rainfall trends. In the present research, monthly rainfall trends at Limbang River Basin (LRB) in Sarawak, Malaysia for a period of 45 years (1970-2015) were characterised through the non-parametric Mann-Kendall and Spearman's Rho tests and relative seasonality index. Statistically processed monthly rainfall of 12 well distributed rain gauging stations in LRB shows almost equal amount of rainfall in all months. Mann-Kendall and Spearman's Rho tests revealed a specific pattern of rainfall trend with a definite boundary marked in the months of January and August with positive trends in all stations. Among the stations, Limbang DID, Long Napir and Ukong showed positive (increasing) trends in all months with a maximum increase of 4.06 mm/year (p = 0.01) in November. All other stations showed varying trends (both increasing and decreasing). Significant (p = 0.05) decreasing trend was noticed in Ulu Medalam and Setuan during September (- 1.67 and - 1.79 mm/year) and October (- 1.59 and - 1.68 mm/year) in Mann-Kendall and Spearman's Rho tests. Spatial pattern of monthly rainfall trends showed two clusters of increasing rainfalls (maximas) in upper and lower part of the river basin separated with a dominant decreasing rainfall corridor. The results indicate a generally increasing trend of rainfall in Sarawak, Borneo.

  12. 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.

  13. Characterization of the Sahelian-Sudan rainfall based on observations and regional climate models

    Science.gov (United States)

    Salih, Abubakr A. M.; Elagib, Nadir Ahmed; Tjernström, Michael; Zhang, Qiong

    2018-04-01

    The African Sahel region is known to be highly vulnerable to climate variability and change. We analyze rainfall in the Sahelian Sudan in terms of distribution of rain-days and amounts, and examine whether regional climate models can capture these rainfall features. Three regional models namely, Regional Model (REMO), Rossby Center Atmospheric Model (RCA) and Regional Climate Model (RegCM4), are evaluated against gridded observations (Climate Research Unit, Tropical Rainfall Measuring Mission, and ERA-interim reanalysis) and rain-gauge data from six arid and semi-arid weather stations across Sahelian Sudan over the period 1989 to 2008. Most of the observed rain-days are characterized by weak (0.1-1.0 mm/day) to moderate (> 1.0-10.0 mm/day) rainfall, with average frequencies of 18.5% and 48.0% of the total annual rain-days, respectively. Although very strong rainfall events (> 30.0 mm/day) occur rarely, they account for a large fraction of the total annual rainfall (28-42% across the stations). The performance of the models varies both spatially and temporally. RegCM4 most closely reproduces the observed annual rainfall cycle, especially for the more arid locations, but all of the three models fail to capture the strong rainfall events and hence underestimate its contribution to the total annual number of rain-days and rainfall amount. However, excessive moderate rainfall compensates this underestimation in the models in an annual average sense. The present study uncovers some of the models' limitations in skillfully reproducing the observed climate over dry regions, will aid model users in recognizing the uncertainties in the model output and will help climate and hydrological modeling communities in improving models.

  14. Atmospheric precursors and assessment of the extreme rainfall responsible for the Madeira flashfloods on 20 February 2010

    Science.gov (United States)

    Fragoso, M.; Trigo, R. M.; Lopes, S.; Lopes, A.; Magro, C.

    2010-09-01

    On February 20, 2010, the Madeira island (Portugal) was hit by torrential rains that triggered catastrophic flash floods, accounting for 43 deaths and 8 missing people. The regional authorities estimated that the total losses exceeded 1 billion of euros resulting from the destructive damages, which were very harmful in Funchal, the capital of the region, where 22 persons died. This paper aims to analyse and discuss two main issues related with the exceptionality of this event. The first part deals with the atmospheric context associated with the rainfall episode, which occurred embedded in a very rainy winter season on this subtropical Atlantic region. Large scale atmospheric controls will be analysed, taking into consideration the low phase conditions of the North Atlantic Oscillation (NAO) that remained overwhelmingly negative between late November 2009 and early April 2010. The role of positive sea surface temperatures anomalies in the subtropical Atlantic region during the prevous weeks will be also investigated. Furthermore, the discussion will be focused on the meteorological precursors of the 20 February rainstorm, using synoptic weather charts and sub-daily reanalysis data and analysing appropriate variables, such as, SLP, geopotential height, instability indices, precipitable water, and others atmospheric parameters. The second section of this work is devoted to the evaluation of the exceptionality of the rainfall records related with this event. In Funchal (Observatory station), the precipitation amount registered during February 2010 was 458 mm, exceeding by seven times (!) the average monthly precipitation, constituting the new absolute record, since 1865, when this meteorological station began its activity. The daily rainfall on 20 February in the same location was 132 mm, which is the highest daily amount since 1920. Return periods of this daily amount will be estimated for the two stations with the longest period available of daily precipitation

  15. Evaluation of empirical relationships between extreme rainfall and daily maximum temperature in Australia

    Science.gov (United States)

    Herath, Sujeewa Malwila; Sarukkalige, Ranjan; Nguyen, Van Thanh Van

    2018-01-01

    Understanding the relationships between extreme daily and sub-daily rainfall events and their governing factors is important in order to analyse the properties of extreme rainfall events in a changing climate. Atmospheric temperature is one of the dominant climate variables which has a strong relationship with extreme rainfall events. In this study, a temperature-rainfall binning technique is used to evaluate the dependency of extreme rainfall on daily maximum temperature. The Clausius-Clapeyron (C-C) relation was found to describe the relationship between daily maximum temperature and a range of rainfall durations from 6 min up to 24 h for seven Australian weather stations, the stations being located in Adelaide, Brisbane, Canberra, Darwin, Melbourne, Perth and Sydney. The analysis shows that the rainfall - temperature scaling varies with location, temperature and rainfall duration. The Darwin Airport station shows a negative scaling relationship, while the other six stations show a positive relationship. To identify the trend in scaling relationship over time the same analysis is conducted using data covering 10 year periods. Results indicate that the dependency of extreme rainfall on temperature also varies with the analysis period. Further, this dependency shows an increasing trend for more extreme short duration rainfall and a decreasing trend for average long duration rainfall events at most stations. Seasonal variations of the scale changing trends were analysed by categorizing the summer and autumn seasons in one group and the winter and spring seasons in another group. Most of 99th percentile of 6 min, 1 h and 24 h rain durations at Perth, Melbourne and Sydney stations show increasing trend for both groups while Adelaide and Darwin show decreasing trend. Furthermore, majority of scaling trend of 50th percentile are decreasing for both groups.

  16. 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

  17. Comparison of four machine learning algorithms for their applicability in satellite-based optical rainfall retrievals

    Science.gov (United States)

    Meyer, Hanna; Kühnlein, Meike; Appelhans, Tim; Nauss, Thomas

    2016-03-01

    Machine learning (ML) algorithms have successfully been demonstrated to be valuable tools in satellite-based rainfall retrievals which show the practicability of using ML algorithms when faced with high dimensional and complex data. Moreover, recent developments in parallel computing with ML present new possibilities for training and prediction speed and therefore make their usage in real-time systems feasible. This study compares four ML algorithms - random forests (RF), neural networks (NNET), averaged neural networks (AVNNET) and support vector machines (SVM) - for rainfall area detection and rainfall rate assignment using MSG SEVIRI data over Germany. Satellite-based proxies for cloud top height, cloud top temperature, cloud phase and cloud water path serve as predictor variables. The results indicate an overestimation of rainfall area delineation regardless of the ML algorithm (averaged bias = 1.8) but a high probability of detection ranging from 81% (SVM) to 85% (NNET). On a 24-hour basis, the performance of the rainfall rate assignment yielded R2 values between 0.39 (SVM) and 0.44 (AVNNET). Though the differences in the algorithms' performance were rather small, NNET and AVNNET were identified as the most suitable algorithms. On average, they demonstrated the best performance in rainfall area delineation as well as in rainfall rate assignment. NNET's computational speed is an additional advantage in work with large datasets such as in remote sensing based rainfall retrievals. However, since no single algorithm performed considerably better than the others we conclude that further research in providing suitable predictors for rainfall is of greater necessity than an optimization through the choice of the ML algorithm.

  18. Rainfall and streamflow from small tree-covered and fern-covered and burned watersheds in Hawaii

    Science.gov (United States)

    H. W. Anderson; P. D. Duffy; Teruo Yamamoto

    1966-01-01

    Streamflow from two 30-acre watersheds near Honolulu was studied by using principal components regression analysis. Models using data on monthly, storm, and peak discharges were tested against several variables expressing amount and intensity of rainfall, and against variables expressing antecedent rainfall. Explained variation ranged from 78 to 94 percent. The...

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

    Science.gov (United States)

    Trend analysis and estimation of monthly and annual precipitation, reference evapotranspiration (ETo) and rainfall deficit are essential for water resources management and cropping system design. Rainfall, ETo, and water deficit patterns and trends in eastern Mississippi USA for a 120-year period (1...

  20. Climate change impacts on rainfall and temperature in sugarcane growing Upper Gangetic Plains of India

    Science.gov (United States)

    Verma, Ram Ratan; Srivastava, Tapendra Kumar; Singh, Pushpa

    2018-01-01

    Assessment of variability in climate extremes is crucial for managing their aftermath on crops. Sugarcane (Saccharum officinarum L.), a major C4 crop, dominates the Upper Gangetic Plain (UGP) in India and is vulnerable to both direct and indirect effects of changes in temperature and rainfall. The present study was taken up to assess the weekly, monthly, seasonal, and annual trends of rainfall and temperature variability during the period 1956-2015 (60 years) for envisaging the probabilities of different levels of rainfall suitable for sugarcane in UGP in the present climate scenario. The analysis revealed that 87% of total annual rainfall was received during southwest monsoon months (June-September) while post-monsoon (October to February) and pre-monsoon months (March-May) accounted for only 9.4 and 3.6%, respectively. There was a decline in both monthly and annual normal rainfall during the period 1986-2015 as compared to 1956-1985, and an annual rainfall deficiency of 205.3 mm was recorded. Maximum monthly normal rainfall deficiencies of 52.8, 84.2, and 54.0 mm were recorded during the months of July, August, and September, respectively, while a minimum rainfall deficiency of 2.2 mm was observed in November. There was a decline by 196.3 mm in seasonal normal rainfall during June-September (kharif). The initial probability of a week going dry was higher (> 70%) from the 1st to the 25th week; however, standard meteorological weeks (SMW) 26 to 37 had more than 50% probability of going wet. The normal annual maximum temperature (Tmax) decreased by 0.4 °C while normal annual minimum temperatures (Tmin) increased by 0.21 °C. Analysis showed that there was an increase in frequency of drought from 1986 onwards in the zone and a monsoon rainfall deficit by about 21.25% during June-September which coincided with tillering and grand growth stage of sugarcane. The imposed drought during the growth and elongation phase is emerging as a major constraint in realizing high

  1. 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.

  2. [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%.

  3. Validation of the TRMM Multi Satellite Rainfall Product 3B42 and estimation of scavenging coefficients for (131)I and (137)Cs using TRMM 3B42 rainfall data.

    Science.gov (United States)

    Shrivastava, R; Dash, S K; Hegde, M N; Pradeepkumar, K S; Sharma, D N

    2014-12-01

    The TRMM rainfall product 3B42 is compared with rain gauge observations for Kaiga, India on monthly and seasonal time scales. This comparison is carried out for the years 2004-2007 spanning four monsoon seasons. A good correlation is obtained between the two data sets however; magnitude wise, the cumulative precipitation of the satellite product on monthly and seasonal time scales is deficient by almost 33-40% as compared to the rain gauge data. The satellite product is also compared with APHRODITE's Monsoon Asia data set on the same time scales. This comparison indicates a much better agreement since both these data sets represent an average precipitation over the same area. The scavenging coefficients for (131)I and (137)Cs are estimated using TRMM 3B42, rain gauge and APHRODITE data. The values obtained using TRMM 3B42 rainfall data compare very well with those obtained using rain gauge and APHRODITE data. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. Polarimetric rainfall retrieval from a C-Band weather radar in a tropical environment (The Philippines)

    Science.gov (United States)

    Crisologo, I.; Vulpiani, G.; Abon, C. C.; David, C. P. C.; Bronstert, A.; Heistermann, Maik

    2014-11-01

    We evaluated the potential of polarimetric rainfall retrieval methods for the Tagaytay C-Band weather radar in the Philippines. For this purpose, we combined a method for fuzzy echo classification, an approach to extract and reconstruct the differential propagation phase, Φ DP , and a polarimetric self-consistency approach to calibrate horizontal and differential reflectivity. The reconstructed Φ DP was used to estimate path-integrated attenuation and to retrieve the specific differential phase, K DP . All related algorithms were transparently implemented in the Open Source radar processing software wradlib. Rainfall was then estimated from different variables: from re-calibrated reflectivity, from re-calibrated reflectivity that has been corrected for path-integrated attenuation, from the specific differential phase, and from a combination of reflectivity and specific differential phase. As an additional benchmark, rainfall was estimated by interpolating the rainfall observed by rain gauges. We evaluated the rainfall products for daily and hourly accumulations. For this purpose, we used observations of 16 rain gauges from a five-month period in the 2012 wet season. It turned out that the retrieval of rainfall from K DP substantially improved the rainfall estimation at both daily and hourly time scales. The measurement of reflectivity apparently was impaired by severe miscalibration while K DP was immune to such effects. Daily accumulations of rainfall retrieved from K DP showed a very low estimation bias and small random errors. Random scatter was, though, strongly present in hourly accumulations.

  5. 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.

  6. Comparing rainfall patterns between regions in Peninsular Malaysia via a functional data analysis technique

    Science.gov (United States)

    Suhaila, Jamaludin; Jemain, Abdul Aziz; Hamdan, Muhammad Fauzee; Wan Zin, Wan Zawiah

    2011-12-01

    SummaryNormally, rainfall data is collected on a daily, monthly or annual basis in the form of discrete observations. The aim of this study is to convert these rainfall values into a smooth curve or function which could be used to represent the continuous rainfall process at each region via a technique known as functional data analysis. Since rainfall data shows a periodic pattern in each region, the Fourier basis is introduced to capture these variations. Eleven basis functions with five harmonics are used to describe the unimodal rainfall pattern for stations in the East while five basis functions which represent two harmonics are needed to describe the rainfall pattern in the West. Based on the fitted smooth curve, the wet and dry periods as well as the maximum and minimum rainfall values could be determined. Different rainfall patterns are observed among the studied regions based on the smooth curve. Using the functional analysis of variance, the test results indicated that there exist significant differences in the functional means between each region. The largest differences in the functional means are found between the East and Northwest regions and these differences may probably be due to the effect of topography and, geographical location and are mostly influenced by the monsoons. Therefore, the same inputs or approaches might not be useful in modeling the hydrological process for different regions.

  7. River catchment rainfall series analysis using additive Holt-Winters method

    Science.gov (United States)

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

    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 rainfall trends 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.

  8. Relationships between High Impact Tropical Rainfall Events and Environmental Conditions

    Science.gov (United States)

    Painter, C.; Varble, A.; Zipser, E. J.

    2017-12-01

    While rainfall increases as moisture and vertical motion increase, relationships between regional environmental conditions and rainfall event characteristics remain more uncertain. Of particular importance are long duration, heavy rain rate, and significant accumulation events that contribute sizable fractions of overall precipitation over short time periods. This study seeks to establish relationships between observed rainfall event properties and environmental conditions. Event duration, rain rate, and rainfall accumulation are derived using the Tropical Rainfall Measuring Mission (TRMM) 3B42 3-hourly, 0.25° resolution rainfall retrieval from 2002-2013 between 10°N and 10°S. Events are accumulated into 2.5° grid boxes and matched to monthly mean total column water vapor (TCWV) and 500-hPa vertical motion (omega) in each 2.5° grid box, retrieved from ERA-interim reanalysis. Only months with greater than 3 mm/day rainfall are included to ensure sufficient sampling. 90th and 99th percentile oceanic events last more than 20% longer and have rain rates more than 20% lower than those over land for a given TCWV-omega condition. Event duration and accumulation are more sensitive to omega than TCWV over oceans, but more sensitive to TCWV than omega over land, suggesting system size, propagation speed, and/or forcing mechanism differences for land and ocean regions. Sensitivities of duration, rain rate, and accumulation to TCWV and omega increase with increasing event extremity. For 3B42 and ERA-Interim relationships, the 90th percentile oceanic event accumulation increases by 0.93 mm for every 1 Pa/min change in rising motion, but this increases to 3.7 mm for every 1 Pa/min for the 99th percentile. Over land, the 90th percentile event accumulation increases by 0.55 mm for every 1 mm increase in TCWV, whereas the 99th percentile increases by 0.90 mm for every 1 mm increase in TCWV. These changes in event accumulation are highly correlated with changes in event

  9. The Influence of ENSO to the Rainfall Variability in North Sumatra Province

    Science.gov (United States)

    Irwandi, H.; Pusparini, N.; Ariantono, J. Y.; Kurniawan, R.; Tari, C. A.; Sudrajat, A.

    2018-04-01

    The El Niño Southern Oscillation (ENSO) is a global phenomenon that affects the variability of rainfall in North Sumatra. The influence of ENSO will be different for each region. This review will analyse the influence of ENSO activity on seasonal and annual rainfall variability. In this research, North Sumatra Province will be divided into 4 (four) regions based on topographical conditions, such as: East Coast (EC), East Slope (ES), Mountains (MT), and West Coast (WC). The method used was statistical and descriptive analysis. Data used in this research were rainfall data from 15 stations / climate observation posts which spread in North Sumatera region and also anomaly data of Nino 3.4 region from period 1981-2016. The results showed that the active El Niño had an effect on the decreasing the rainfall during the period of DJF, JJA and SON in East Coast, East Slope, and Mountains with the decreasing of average percentage of annual rainfall up to 7%. On the contrary, the active La Nina had an effect on the addition of rainfall during the period DJF and JJA in the East Coast and Mountains with the increasing of average percentage of annual rainfall up to 6%.

  10. Some analysis on the diurnal variation of rainfall over the Atlantic Ocean

    Science.gov (United States)

    Gill, T.; Perng, S.; Hughes, A.

    1981-01-01

    Data collected from the GARP Atlantic Tropical Experiment (GATE) was examined. The data were collected from 10,000 grid points arranged as a 100 x 100 array; each grid covered a 4 square km area. The amount of rainfall was measured every 15 minutes during the experiment periods using c-band radars. Two types of analyses were performed on the data: analysis of diurnal variation was done on each of grid points based on the rainfall averages at noon and at midnight, and time series analysis on selected grid points based on the hourly averages of rainfall. Since there are no known distribution model which best describes the rainfall amount, nonparametric methods were used to examine the diurnal variation. Kolmogorov-Smirnov test was used to test if the rainfalls at noon and at midnight have the same statistical distribution. Wilcoxon signed-rank test was used to test if the noon rainfall is heavier than, equal to, or lighter than the midnight rainfall. These tests were done on each of the 10,000 grid points at which the data are available.

  11. Climate change and predicting soil loss from rainfall

    Science.gov (United States)

    Kinnell, Peter

    2017-04-01

    Conceptually, rainfall has a certain capacity to cause soil loss from an eroding area while soil surfaces have a certain resistance to being eroded by rainfall. The terms "rainfall erosivity' and "soil erodibility" are frequently used to encapsulate the concept and in the Revised Universal Soil Loss Equation (RUSLE), the most widely used soil loss prediction equation in the world, average annual values of the R "erosivity" factor and the K "erodibility" factor provide a basis for accounting for variation in rainfall erosion associated with geographic variations of climate and soils. In many applications of RUSLE, R and K are considered to be independent but in reality they are not. In RUSLE2, provision has been made to take account of the fact that K values determined using soil physical factors have to be adjusted for variations in climate because runoff is not directly included as a factor in determining R. Also, the USLE event erosivity index EI30 is better related to accounting for event sediment concentration than event soil loss. While the USLE-M, a modification of the USLE which includes runoff as a factor in determining the event erosivity index provides better estimates of event soil loss when event runoff is known, runoff prediction provides a challenge to modelling event soil loss as climate changes

  12. 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.

  13. 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.

  14. 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.

  15. Interpolation of daily rainfall using spatiotemporal models and clustering

    KAUST Repository

    Militino, A. F.; Ugarte, M. D.; Goicoa, T.; Genton, Marc G.

    2014-01-01

    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.

  16. Projected changes of rainfall seasonality and dry spells in a high greenhouse gas emissions scenario

    OpenAIRE

    Pascale, Salvatore; Lucarini, Valerio; Feng, Xue; Porporato, Amilcare; ul Hasson, Shabeh

    2016-01-01

    In this diagnostic study we analyze changes of rainfall seasonality and dry spells by the end of the twenty-first century under the most extreme IPCC5 emission scenario (RCP8.5) as projected by twenty-four coupled climate models contributing to Coupled Model Intercomparison Project 5 (CMIP5). We use estimates of the centroid of the monthly rainfall distribution as an index of the rainfall timing and a threshold-independent, information theory-based quantity such as relative entropy (RE) to qu...

  17. Predictability of the intra-seasonal rainfall characteristics variables over South Africa

    CSIR Research Space (South Africa)

    Phakula, S

    2015-09-01

    Full Text Available for the homogeneous rainfall regions. Keywords: Retro-active validation, Forecast skill, Area-averaged ROC scores, Reliability diagrams. Introduction Southern Africa is a region of significant rainfall variability on a range of temporal and spacial scales... are evaluated using retro-actively generated hindcasts through canonical correlation analysis (CCA). Retro-active forecast validation is a robust method to assess forecast model performance and give unbiased skill levels (Landman et al., 2001). Two...

  18. A Comparative Frequency Analysis of Maximum Daily Rainfall for a SE Asian Region under Current and Future Climate Conditions

    Directory of Open Access Journals (Sweden)

    Velautham Daksiya

    2017-01-01

    Full Text Available The impact of changing climate on the frequency of daily rainfall extremes in Jakarta, Indonesia, is analysed and quantified. The study used three different models to assess the changes in rainfall characteristics. The first method involves the use of the weather generator LARS-WG to quantify changes between historical and future daily rainfall maxima. The second approach consists of statistically downscaling general circulation model (GCM output based on historical empirical relationships between GCM output and station rainfall. Lastly, the study employed recent statistically downscaled global gridded rainfall projections to characterize climate change impact rainfall structure. Both annual and seasonal rainfall extremes are studied. The results show significant changes in annual maximum daily rainfall, with an average increase as high as 20% in the 100-year return period daily rainfall. The uncertainty arising from the use of different GCMs was found to be much larger than the uncertainty from the emission scenarios. Furthermore, the annual and wet seasonal analyses exhibit similar behaviors with increased future rainfall, but the dry season is not consistent across the models. The GCM uncertainty is larger in the dry season compared to annual and wet season.

  19. Influence of rainfall on the dynamics of two prawn populations in the ...

    African Journals Online (AJOL)

    Recruitment takes place 4 to 5 months after spawning. Thus the time span from rainfall to recruitment of the young of a given cohort is 7 to 8 months. For N. hastatus, the catch rate in the ... AJOL African Journals Online. HOW TO USE AJOL.

  20. The development rainfall forecasting using kalman filter

    Science.gov (United States)

    Zulfi, Mohammad; Hasan, Moh.; Dwidja Purnomo, Kosala

    2018-04-01

    Rainfall forecasting is very interesting for agricultural planing. Rainfall information is useful to make decisions about the plan planting certain commodities. In this studies, the rainfall forecasting by ARIMA and Kalman Filter method. Kalman Filter method is used to declare a time series model of which is shown in the form of linear state space to determine the future forecast. This method used a recursive solution to minimize error. The rainfall data in this research clustered by K-means clustering. Implementation of Kalman Filter method is for modelling and forecasting rainfall in each cluster. We used ARIMA (p,d,q) to construct a state space for KalmanFilter model. So, we have four group of the data and one model in each group. In conclusions, Kalman Filter method is better than ARIMA model for rainfall forecasting in each group. It can be showed from error of Kalman Filter method that smaller than error of ARIMA model.

  1. 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.

  2. Deforestation and rainfall recycling in Brazil: Is decreased forest cover connectivity associated with decreased rainfall connectivity?

    Science.gov (United States)

    Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

    2017-12-01

    In the Brazilian rainforest-savanna transition zone, deforestation has the potential to significantly affect rainfall by disrupting rainfall recycling, the process by which regional evapotranspiration contributes to regional rainfall. Understanding rainfall recycling in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching, agriculture, hydropower generation, and drinking water management. Simulations in previous studies suggest complex, scale-dependent interactions between forest cover connectivity and rainfall. For example, the size and distribution of deforested patches has been found to affect rainfall quantity and spatial distribution. Here we take an empirical approach, using the spatial connectivity of rainfall as an indicator of rainfall recycling, to ask: as forest cover connectivity decreased from 1981 - 2015, how did the spatial connectivity of rainfall change in the Brazilian rainforest-savanna transition zone? We use satellite forest cover and rainfall data covering this period of intensive forest cover loss in the region (forest cover from the Hansen Global Forest Change dataset; rainfall from the Climate Hazards Infrared Precipitation with Stations dataset). Rainfall spatial connectivity is quantified using transfer entropy, a metric from information theory, and summarized using network statistics. Networks of connectivity are quantified for paired deforested and non-deforested regions before deforestation (1981-1995) and during/after deforestation (2001-2015). Analyses reveal a decline in spatial connectivity networks of rainfall following deforestation.

  3. [Effects of rainfall intensity on rainfall infiltration and redistribution in soil on Loess slope land].

    Science.gov (United States)

    Li, Yi; Shao, Ming'an

    2006-12-01

    With simulation test, this paper studied the patterns of rainfall infiltration and redistribution in soil on typical Loess slope land, and analyzed the quantitative relations between the infiltration and redistribution and the movement of soil water and mass, with rainfall intensity as the main affecting factor. The results showed that rainfall intensity had significant effects on the rainfall infiltration and water redistribution in soil, and the microcosmic movement of soil water. The larger the rainfall intensity, the deeper the wetting front of rainfall infiltration and redistribution was, and the wetting front of soil water redistribution had a slower increase velocity than that of rainfall infiltration. The power function of the wetting front with time, and also with rainfall intensity, was fitted well. There was also a quantitative relation between the wetting front of rainfall redistribution and the duration of rainfall. The larger the rainfall intensity, the higher the initial and steady infiltration rates were, and the cumulative infiltration increased faster with time. Moreover, the larger the rainfall intensity, the smaller the wetting front difference was at the top and the end of the slope. With the larger rainfall intensity, both the difference of soil water content and its descending trend between soil layers became more obvious during the redistribution process on slope land.

  4. 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

  5. Urban rainfall estimation employing commercial microwave links

    Science.gov (United States)

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

    2015-04-01

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

  6. RAINLINK: Retrieval algorithm for rainfall monitoring employing microwave links from a cellular communication network

    Science.gov (United States)

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

    2017-12-01

    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 for one decade. They are particularly interesting for those countries where few surface rainfall observations are available. Yet to date no operational (real-time) link-based rainfall products are available. To advance the process towards operational application and upscaling of this technique, there is a need for freely available, user-friendly computer code for microwave link data processing and rainfall mapping. Such software is now available as R package "RAINLINK" on GitHub (https://github.com/overeem11/RAINLINK). It contains a working example to compute link-based 15-min rainfall maps for the entire surface area of The Netherlands for 40 hours from real microwave link data. This is a working example using actual data from an extensive network of commercial microwave links, for the first time, which will allow users to test their own algorithms and compare their results with ours. The package consists of modular functions, which facilitates running only part of the algorithm. The main processings steps are: 1) Preprocessing of link data (initial quality and consistency checks); 2) Wet-dry classification using link data; 3) Reference signal determination; 4) Removal of outliers ; 5) Correction of received signal powers; 6) Computation of mean path-averaged rainfall intensities; 7) Interpolation of rainfall intensities ; 8) Rainfall map visualisation. Some applications of RAINLINK will be shown based on microwave link data from a

  7. An Assessment of Satellite-Derived Rainfall Products Relative to Ground Observations over East Africa

    Directory of Open Access Journals (Sweden)

    Margaret Wambui Kimani

    2017-05-01

    Full Text Available Accurate and consistent rainfall observations are vital for climatological studies in support of better agricultural and water management decision-making and planning. In East Africa, accurate rainfall estimation with an adequate spatial distribution is limited due to sparse rain gauge networks. Satellite rainfall products can potentially play a role in increasing the spatial coverage of rainfall estimates; however, their performance needs to be understood across space–time scales and factors relating to their errors. This study assesses the performance of seven satellite products: Tropical Applications of Meteorology using Satellite and ground-based observations (TAMSAT, African Rainfall Climatology And Time series (TARCAT, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS, Tropical Rainfall Measuring Mission (TRMM-3B43, Climate Prediction Centre (CPC Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Climate Data Record (PERSIANN-CDR, CPC Merged Analysis of Precipitation (CMAP, and Global Precipitation Climatology Project (GPCP, using locally developed gridded (0.05° rainfall data for 15 years (1998–2012 over East Africa. The products’ assessments were done at monthly and yearly timescales and were remapped to the gridded rain gauge data spatial scale during the March to May (MAM and October to December (OND rainy seasons. A grid-based statistical comparison between the two datasets was used, but only pixel values located at the rainfall stations were considered for validation. Additionally, the impact of topography on the performance of the products was assessed by analyzing the pixels in areas of highest negative bias. All the products could substantially replicate rainfall patterns, but their differences are mainly based on retrieving high rainfall amounts, especially of localized orographic types. The products exhibited systematic errors, which

  8. 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.

  9. Estimation of potential rainfall recharge in the pothwar area

    International Nuclear Information System (INIS)

    Afzal, M.; Yaseen, M.

    2015-01-01

    Groundwater recharge is complex phenomenon to understand and describe because it cannot be seen with open eyes. We have to depend some theoretical assumptions to understand this complicated hidden natural underground water movement process. There are many factors affecting and controlling the water movement in soil profile. Groundwater use in district chakwal is of a fundamental importance to meet the rapidly expanding drinking and agricultural water requirements. The man factors contributing to groundwater recharge in chakwal are rainfall, evapotranspiration and geology. due to the semi arid climatic conditions of the area, this resource is almost the only key to economic development. There are a number of dug wells in the area where water is getting stored during rainy season. source and processes of recharge in humid areas are different compared with semi-arid areas. Due to the main resource of available water in the area, the potential groundwater recharge estimation could be good exercise to visulize the amount of rainwater entering the ground. For groundwater recharge estimation there are a number of simple and advanced techniques available. In the present study simple methods were used to estimate potential recharge due to available limited resources. Rainfall runoff, gravimetric and water table fluctuation methods were used to quantify rainfall recharge during the monsoon season. The average potential recharge estimated was 60% of the rainfall of 148 mm. Rainfall runoff and gravimetric methods were found to be comparable for short period potential recharge estimation while water table fluctuation method gives actual recharge and require longer period data. Potential recharge values were higher for area having grassland type vegetation and low for area covering shrubs and tick vegetation. (author)

  10. Statistical downscaling of rainfall: a non-stationary and multi-resolution approach

    Science.gov (United States)

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

    2016-05-01

    A novel downscaling technique is proposed in this study whereby the original rainfall and reanalysis variables are first decomposed by wavelet transforms and rainfall is modelled using the semi-parametric additive model formulation of Generalized Additive Model in Location, Scale and Shape (GAMLSS). The flexibility of the GAMLSS model makes it feasible as a framework for non-stationary modelling. Decomposition of a rainfall series into different components is useful to separate the scale-dependent properties of the rainfall as this varies both temporally and spatially. The study was conducted at the Onkaparinga river catchment in South Australia. The model was calibrated over the period 1960 to 1990 and validated over the period 1991 to 2010. The model reproduced the monthly variability and statistics of the observed rainfall well with Nash-Sutcliffe efficiency (NSE) values of 0.66 and 0.65 for the calibration and validation periods, respectively. It also reproduced well the seasonal rainfall over the calibration (NSE = 0.37) and validation (NSE = 0.69) periods for all seasons. The proposed model was better than the tradition modelling approach (application of GAMLSS to the original rainfall series without decomposition) at reproducing the time-frequency properties of the observed rainfall, and yet it still preserved the statistics produced by the traditional modelling approach. When downscaling models were developed with general circulation model (GCM) historical output datasets, the proposed wavelet-based downscaling model outperformed the traditional downscaling model in terms of reproducing monthly rainfall for both the calibration and validation periods.

  11. The difference between alternative averages

    Directory of Open Access Journals (Sweden)

    James Vaupel

    2012-09-01

    Full Text Available BACKGROUND Demographers have long been interested in how compositional change, e.g., change in age structure, affects population averages. OBJECTIVE We want to deepen understanding of how compositional change affects population averages. RESULTS The difference between two averages of a variable, calculated using alternative weighting functions, equals the covariance between the variable and the ratio of the weighting functions, divided by the average of the ratio. We compare weighted and unweighted averages and also provide examples of use of the relationship in analyses of fertility and mortality. COMMENTS Other uses of covariances in formal demography are worth exploring.

  12. 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

  13. 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

  14. Evaluation of CMIP5 twentieth century rainfall simulation over the equatorial East Africa

    Science.gov (United States)

    Ongoma, Victor; Chen, Haishan; Gao, Chujie

    2018-02-01

    This study assesses the performance of 22 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of rainfall over East Africa (EA) against reanalyzed datasets during 1951-2005. The datasets were sourced from Global Precipitation Climatology Centre (GPCC) and Climate Research Unit (CRU). The metrics used to rank CMIP5 Global Circulation Models (GCMs) based on their performance in reproducing the observed rainfall include correlation coefficient, standard deviation, bias, percentage bias, root mean square error, and trend. Performances of individual models vary widely. The overall performance of the models over EA is generally low. The models reproduce the observed bimodal rainfall over EA. However, majority of them overestimate and underestimate the October-December (OND) and March-May (MAM) rainfall, respectively. The monthly (inter-annual) correlation between model and reanalyzed is high (low). More than a third of the models show a positive bias of the annual rainfall. High standard deviation in rainfall is recorded in the Lake Victoria Basin, central Kenya, and eastern Tanzania. A number of models reproduce the spatial standard deviation of rainfall during MAM season as compared to OND. The top eight models that produce rainfall over EA relatively well are as follows: CanESM2, CESM1-CAM5, CMCC-CESM, CNRM-CM5, CSIRO-Mk3-6-0, EC-EARTH, INMCM4, and MICROC5. Although these results form a fairly good basis for selection of GCMs for carrying out climate projections and downscaling over EA, it is evident that there is still need for critical improvement in rainfall-related processes in the models assessed. Therefore, climate users are advised to use the projections of rainfall from CMIP5 models over EA cautiously when making decisions on adaptation to or mitigation of climate change.

  15. 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

  16. Determination of mean rainfall from the Special Sensor Microwave/Imager (SSM/I) using a mixed lognormal distribution

    Science.gov (United States)

    Berg, Wesley; Chase, Robert

    1992-01-01

    Global estimates of monthly, seasonal, and annual oceanic rainfall are computed for a period of one year using data from the Special Sensor Microwave/Imager (SSM/I). Instantaneous rainfall estimates are derived from brightness temperature values obtained from the satellite data using the Hughes D-matrix algorithm. The instantaneous rainfall estimates are stored in 1 deg square bins over the global oceans for each month. A mixed probability distribution combining a lognormal distribution describing the positive rainfall values and a spike at zero describing the observations indicating no rainfall is used to compute mean values. The resulting data for the period of interest are fitted to a lognormal distribution by using a maximum-likelihood. Mean values are computed for the mixed distribution and qualitative comparisons with published historical results as well as quantitative comparisons with corresponding in situ raingage data are performed.

  17. Forecasting the heavy rainfall during Himalayan flooding—June 2013

    Directory of Open Access Journals (Sweden)

    Anumeha Dube

    2014-08-01

    Verification of the synoptic features in forecasts of the two models suggests that NCUM accurately captures the circulation features as compared to T574. Further verification of this event is carried out based on the contiguous rain area (CRA technique. CRA verification is used in computing the total mean square error (MSE which is based on displacement, volume and pattern errors. This verification technique also, confirms the better skill of NCUM over T574 in terms of forecast peak rainfall amounts, volume and average rain rate, lower MSE and root mean square error (RMSE as well as having higher hit rates and lower misses and false alarm rates for different rainfall thresholds from Day 1 to Day 5 forecasts.

  18. Evolution of extreme rainfall in France with a changing climate

    International Nuclear Information System (INIS)

    Soubeyroux, Jean-Michel; Veysseire, Jean-Michel; Gouget, Viviane; Neppel, Luc; Tramblay, Yves; Carreau, Julie

    2015-01-01

    This paper focuses a synthesis of the works led within the framework of the French project ANR/Extraflo on the evolution of the daily (and infra daily) extreme rainfall in France. An important dataset of more than 900 series was used. It was shown that a majority of series presented a not significant upward trend in particular in Mediterranean area, in relation with various recent exceptional extreme events. An interesting way to characterize this evolution consists in identifying climatic co-variables associated to heavy rainfall events (weather patterns, average temperatures, flow of humidity) and in taking into account them with a non stationary POT model. The application of this method with climatic projections under scenario A2 from IPCC could lead to a possible increase on extreme precipitation quantiles on the horizon 2070. (authors)

  19. Forecasting of rainfall using ocean-atmospheric indices with a fuzzy neural technique

    Science.gov (United States)

    Srivastava, Gaurav; Panda, Sudhindra N.; Mondal, Pratap; Liu, Junguo

    2010-12-01

    SummaryForecasting of rainfall is imperative for rainfed agriculture of arid and semi-arid regions of the world where agriculture consumes nearly 80% of the total water demand. Fuzzy-Ranking Algorithm (FRA) is used to identify the significant input variables for rainfall forecast. A case study is carried out to forecast monthly rainfall in India with several ocean-atmospheric predictor variables. Three different scenarios of ocean-atmospheric predictor variables are used as a set of possible input variables for rainfall forecasting model: (1) two climate indices, i.e. Southern Oscillation Index (SOI) and Pacific Decadal Oscillation Index (PDOI); (2) Sea Surface Temperature anomalies (SSTa) in the 5° × 5° grid points in Indian Ocean; and (3) both the climate indices and SSTa. To generate a set of possible input variables for these scenarios, we use climatic indices and the SSTa data with different lags between 1 and 12 months. Nonlinear relationship between identified inputs and rainfall is captured with an Artificial Neural Network (ANN) technique. A new approach based on fuzzy c-mean clustering is proposed for dividing data into representative subsets for training, testing, and validation. The results show that this proposed approach overcomes the difficulty in determining optimal numbers of clusters associated with the data division technique of self-organized map. The ANN model developed with both the climate indices and SSTa shows the best performance for the forecast of the monthly August rainfall in India. Similar approach can be applied to forecast rainfall of any period at selected climatic regions of the world where significant relationship exists between the rainfall and climate indices.

  20. 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.

  1. 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.

  2. Rainfall Interception in Mangrove in the Southeastern Coast of Brazil

    Directory of Open Access Journals (Sweden)

    Emerson Galvani

    2016-06-01

    Full Text Available Mangroves are among the ecosystems biologically more productive and important in the world, providing unique goods and services to societies and coastal systems. These areas, however, are increasingly fragmented, contributing to the loss of their services and benefits. The rains have an important influence in this ecosystem is central to the dissolution of sea salts. This study investigated the total rainfall in the mangroves located in the Coastal System Cananeia-Iguape (SP at different time scales (daily, monthly, sea-sonal and annual and its interception by the mangrove canopy. It found an intercept of 8.8%, ranging from 13% to 4% in the annual scale, showing that the annual variation of rainfall, which reflects both its quantity and its intensity contributes to the percentage of that interception by the canopy. It was also found that as the intensity of precipitation increases, trapping the mangrove canopy reduces.

  3. 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...

  4. Prediction of early summer rainfall over South China by a physical-empirical model

    Science.gov (United States)

    Yim, So-Young; Wang, Bin; Xing, Wen

    2014-10-01

    In early summer (May-June, MJ) the strongest rainfall belt of the northern hemisphere occurs over the East Asian (EA) subtropical front. During this period the South China (SC) rainfall reaches its annual peak and represents the maximum rainfall variability over EA. Hence we establish an SC rainfall index, which is the MJ mean precipitation averaged over 72 stations over SC (south of 28°N and east of 110°E) and represents superbly the leading empirical orthogonal function mode of MJ precipitation variability over EA. In order to predict SC rainfall, we established a physical-empirical model. Analysis of 34-year observations (1979-2012) reveals three physically consequential predictors. A plentiful SC rainfall is preceded in the previous winter by (a) a dipole sea surface temperature (SST) tendency in the Indo-Pacific warm pool, (b) a tripolar SST tendency in North Atlantic Ocean, and (c) a warming tendency in northern Asia. These precursors foreshadow enhanced Philippine Sea subtropical High and Okhotsk High in early summer, which are controlling factors for enhanced subtropical frontal rainfall. The physical empirical model built on these predictors achieves a cross-validated forecast correlation skill of 0.75 for 1979-2012. Surprisingly, this skill is substantially higher than four-dynamical models' ensemble prediction for 1979-2010 period (0.15). The results here suggest that the low prediction skill of current dynamical models is largely due to models' deficiency and the dynamical prediction has large room to improve.

  5. 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.

  6. Determining the precipitable water vapor thresholds under different rainfall strengths in Taiwan

    Science.gov (United States)

    Yeh, Ta-Kang; Shih, Hsuan-Chang; Wang, Chuan-Sheng; Choy, Suelynn; Chen, Chieh-Hung; Hong, Jing-Shan

    2018-02-01

    Precipitable Water Vapor (PWV) plays an important role for weather forecasting. It is helpful in evaluating the changes of the weather system via observing the distribution of water vapor. The ability of calculating PWV from Global Positioning System (GPS) signals is useful to understand the special weather phenomenon. In this study, 95 ground-based GPS and rainfall stations in Taiwan were utilized from 2006 to 2012 to analyze the relationship between PWV and rainfall. The PWV data were classified into four classes (no, light, moderate and heavy rainfall), and the vertical gradients of the PWV were obtained and the variations of the PWV were analyzed. The results indicated that as the GPS elevation increased every 100 m, the PWV values decreased by 9.5 mm, 11.0 mm, 12.2 mm and 12.3 mm during the no, light, moderate and heavy rainfall conditions, respectively. After applying correction using the vertical gradients mentioned above, the average PWV thresholds were 41.8 mm, 52.9 mm, 62.5 mm and 64.4 mm under the no, light, moderate and heavy rainfall conditions, respectively. This study offers another type of empirical threshold to assist the rainfall prediction and can be used to distinguish the rainfall features between different areas in Taiwan.

  7. 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.

  8. 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.

  9. The Spatial Scaling of Global Rainfall Extremes

    Science.gov (United States)

    Devineni, N.; Xi, C.; Lall, U.; Rahill-Marier, B.

    2013-12-01

    Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (upto 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances. We also investigate the connection of persistent rainfall events at different latitudinal bands to large-scale climate phenomena such as ENSO. Finally, we present the scaling phenomena of contiguous flooded areas as a result of large scale organization of long duration rainfall events. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional and portfolio analysis can be developed.

  10. Relationship between rainfall and microbiological contamination of ...

    African Journals Online (AJOL)

    Outbreaks of contamination events in many developing countries occur during periods of peak rainfall. This study presents evidence of direct pulse response of shallow groundwater contamination events to rainfall in Northern Mozambique. The objective of the paper is to establish both a statistical relationship between ...

  11. Statistical Modelling of Extreme Rainfall in Taiwan

    NARCIS (Netherlands)

    L-F. Chu (Lan-Fen); M.J. McAleer (Michael); C-C. Chang (Ching-Chung)

    2012-01-01

    textabstractIn this paper, the annual maximum daily rainfall data from 1961 to 2010 are modelled for 18 stations in Taiwan. We fit the rainfall data with stationary and non-stationary generalized extreme value distributions (GEV), and estimate their future behaviour based on the best fitting model.

  12. Statistical Modelling of Extreme Rainfall in Taiwan

    NARCIS (Netherlands)

    L. Chu (LanFen); M.J. McAleer (Michael); C-H. Chang (Chu-Hsiang)

    2013-01-01

    textabstractIn this paper, the annual maximum daily rainfall data from 1961 to 2010 are modelled for 18 stations in Taiwan. We fit the rainfall data with stationary and non-stationary generalized extreme value distributions (GEV), and estimate their future behaviour based on the best fitting model.

  13. Rainfall and Development of Zika Virus

    African Journals Online (AJOL)

    2017-11-01

    Nov 1, 2017 ... between rainfall and incidence of arbovirus disease such as dengue is well demonstrated (2). For Zika virus an infection, a similar observation can be expected. A recent report from Thailand can also show the expected pattern of the prevalence of Zika virus infection in the areas with high rainfall (3).

  14. Developing empirical relationship between interrill erosion, rainfall ...

    African Journals Online (AJOL)

    In order to develop an empirical relationship for interrill erosion based on rainfall intensity, slope steepness and soil types, an interrill erosion experiment was conducted using laboratory rainfall simulator on three soil types (Vertisols, Cambisols and Leptosols) for the highlands of North Shewa Zone of Oromia Region.

  15. Spatial variability and rainfall characteristics of Kerala

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    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 ...

  16. 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.

  17. 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...

  18. Forecasting Andean rainfall and crop yield from the influence of El Nino on Pleiades visibility

    Science.gov (United States)

    Orlove; Chiang; Cane

    2000-01-06

    Farmers in drought-prone regions of Andean South America have historically made observations of changes in the apparent brightness of stars in the Pleiades around the time of the southern winter solstice in order to forecast interannual variations in summer rainfall and in autumn harvests. They moderate the effect of reduced rainfall by adjusting the planting dates of potatoes, their most important crop. Here we use data on cloud cover and water vapour from satellite imagery, agronomic data from the Andean altiplano and an index of El Nino variability to analyse this forecasting method. We find that poor visibility of the Pleiades in June-caused by an increase in subvisual high cirrus clouds-is indicative of an El Nino year, which is usually linked to reduced rainfall during the growing season several months later. Our results suggest that this centuries-old method of seasonal rainfall forecasting may be based on a simple indicator of El Nino variability.

  19. 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

  20. Using Conditional Analysis to Investigate Spatial and Temporal patterns in Upland Rainfall

    Science.gov (United States)

    Sakamoto Ferranti, Emma Jayne; Whyatt, James Duncan; Timmis, Roger James

    2010-05-01

    The seasonality and characteristics of rainfall in the UK are altering under a changing climate. Summer rainfall is generally decreasing whereas winter rainfall is increasing, particularly in northern and western areas (Maraun et al., 2008) and recent research suggests these rainfall increases are amplified in upland areas (Burt and Ferranti, 2010). Conditional analysis has been used to investigate these rainfall patterns in Cumbria, an upland area in northwest England. Cumbria was selected as an example of a topographically diverse mid-latitude region that has a predominately maritime and westerly-defined climate. Moreover it has a dense network of more than 400 rain gauges that have operated for periods between 1900 and present day. Cumbria has experienced unprecedented flooding in the past decade and understanding the spatial and temporal changes in this and other upland regions is important for water resource and ecosystem management. The conditional analysis method examines the spatial and temporal variations in rainfall under different synoptic conditions and in different geographic sub-regions (Ferranti et al., 2009). A daily synoptic typing scheme, the Lamb Weather Catalogue, was applied to classify rainfall into different weather types, for example: south-westerly, westerly, easterly or cyclonic. Topographic descriptors developed using GIS were used to classify rain gauges into 6 directionally-dependant geographic sub-regions: coastal, windward-lowland, windward-upland, leeward-upland, leeward-lowland, secondary upland. Combining these classification methods enabled seasonal rainfall climatologies to be produced for specific weather types and sub-regions. Winter rainfall climatologies were constructed for all 6 sub-regions for 3 weather types - south-westerly (SW), westerly (W), and cyclonic (C); these weather types contribute more than 50% of total winter rainfall. The frequency of wet-days (>0.3mm), the total winter rainfall and the average wet day

  1. 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.

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

    Science.gov (United States)

    MacLeod, D A; Morse, A P

    2014-12-02

    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.

  3. Integrating real-time subsurface hydrologic monitoring with empirical rainfall thresholds to improve landslide early warning

    Science.gov (United States)

    Mirus, Benjamin B.; Becker, Rachel E.; Baum, Rex L.; Smith, Joel B.

    2018-01-01

    Early warning for rainfall-induced shallow landsliding can help reduce fatalities and economic losses. Although these commonly occurring landslides are typically triggered by subsurface hydrological processes, most early warning criteria rely exclusively on empirical rainfall thresholds and other indirect proxies for subsurface wetness. We explore the utility of explicitly accounting for antecedent wetness by integrating real-time subsurface hydrologic measurements into landslide early warning criteria. Our efforts build on previous progress with rainfall thresholds, monitoring, and numerical modeling along the landslide-prone railway corridor between Everett and Seattle, Washington, USA. We propose a modification to a previously established recent versus antecedent (RA) cumulative rainfall thresholds by replacing the antecedent 15-day rainfall component with an average saturation observed over the same timeframe. We calculate this antecedent saturation with real-time telemetered measurements from five volumetric water content probes installed in the shallow subsurface within a steep vegetated hillslope. Our hybrid rainfall versus saturation (RS) threshold still relies on the same recent 3-day rainfall component as the existing RA thresholds, to facilitate ready integration with quantitative precipitation forecasts. During the 2015–2017 monitoring period, this RS hybrid approach has an increase of true positives and a decrease of false positives and false negatives relative to the previous RA rainfall-only thresholds. We also demonstrate that alternative hybrid threshold formats could be even more accurate, which suggests that further development and testing during future landslide seasons is needed. The positive results confirm that accounting for antecedent wetness conditions with direct subsurface hydrologic measurements can improve thresholds for alert systems and early warning of rainfall-induced shallow landsliding.

  4. Constraining relationships between rainfall and landsliding with satellite derived rainfall measurements and landslide inventories.

    Science.gov (United States)

    Marc, Odin; Malet, Jean-Philippe; Stumpf, Andre; Gosset, Marielle

    2017-04-01

    In mountainous and hilly regions, landslides are an important source of damage and fatalities. Landsliding correlates with extreme rainfall events and may increase with climate change. Still, how precipitation drives landsliding at regional scales is poorly understood quantitatively in part because constraining simultaneously landsliding and rainfall across large areas is challenging. By combining optical images acquired from satellite observation platforms and rainfall measurements from satellite constellations we are building a database of landslide events caused by with single storm events. We present results from storm-induced landslides from Brazil, Taiwan, Micronesia, Central America, Europe and the USA. We present scaling laws between rainfall metrics derived by satellites (total rainfall, mean intensity, antecedent rainfall, ...) and statistical descriptors of landslide events (total area and volume, size distribution, mean runout, ...). Total rainfall seems to be the most important parameter driving non-linearly the increase in total landslide number, and area and volume. The maximum size of bedrock landslides correlates with the total number of landslides, and thus with total rainfall, within the limits of available topographic relief. In contrast, the power-law scaling exponent of the size distribution, controlling the relative abundance of small and large landslides, appears rather independent of the rainfall metrics (intensity, duration and total rainfall). These scaling laws seem to explain both the intra-storm pattern of landsliding, at the scale of satellite rainfall measurements ( 25kmx25km), and the different impacts observed for various storms. Where possible, we evaluate the limits of standard rainfall products (TRMM, GPM, GSMaP) by comparing them to in-situ data. Then we discuss how slope distribution and other geomorphic factors (lithology, soil presence,...) modulate these scaling laws. Such scaling laws at the basin scale and based only on a

  5. Estimation of Rainfall Erosivity via 1-Minute to Hourly Rainfall Data from Taipei, Taiwan

    Science.gov (United States)

    Huang, Ting-Yin; Yang, Ssu-Yao; Jan, Chyan-Deng

    2017-04-01

    Soil erosion is a natural process on hillslopes that threats people's life and properties, having a considerable environmental and economic implications for soil degradation, agricultural activity and water quality. The rainfall erosivity factor (R-factor) in the Universal Soil Loss Equation (USLE), composed of total kinetic energy (E) and the maximum 30-min rainfall intensity (I30), is widely used as an indicator to measure the potential risks of soil loss caused by rainfall at a regional scale. This R factor can represent the detachment and entrainment involved in climate conditions on hillslopes, but lack of 30-min rainfall intensity data usually lead to apply this factor more difficult in many regions. In recent years, fixed-interval, hourly rainfall data is readily available and widely used due to the development of automatic weather stations. Here we assess the estimations of R, E, and I30 based on 1-, 5-, 10-, 15-, 30-, 60-minute rainfall data, and hourly rainfall data obtained from Taipei weather station during 2004 to 2010. Results show that there is a strong correlation among R-factors estimated from different interval rainfall data. Moreover, the shorter time-interval rainfall data (e.g., 1-min) yields larger value of R-factor. The conversion factors of rainfall erosivity (ratio of values estimated from the resolution lower than 30-min rainfall data to those estimated from 60-min and hourly rainfall data, respectively) range from 1.85 to 1.40 (resp. from 1.89 to 1.02) for 60-min (resp. hourly) rainfall data as the time resolution increasing from 30-min to 1-min. This paper provides useful information on estimating R-factor when hourly rainfall data is only available.

  6. How to average logarithmic retrievals?

    Directory of Open Access Journals (Sweden)

    B. Funke

    2012-04-01

    Full Text Available Calculation of mean trace gas contributions from profiles obtained by retrievals of the logarithm of the abundance rather than retrievals of the abundance itself are prone to biases. By means of a system simulator, biases of linear versus logarithmic averaging were evaluated for both maximum likelihood and maximum a priori retrievals, for various signal to noise ratios and atmospheric variabilities. These biases can easily reach ten percent or more. As a rule of thumb we found for maximum likelihood retrievals that linear averaging better represents the true mean value in cases of large local natural variability and high signal to noise ratios, while for small local natural variability logarithmic averaging often is superior. In the case of maximum a posteriori retrievals, the mean is dominated by the a priori information used in the retrievals and the method of averaging is of minor concern. For larger natural variabilities, the appropriateness of the one or the other method of averaging depends on the particular case because the various biasing mechanisms partly compensate in an unpredictable manner. This complication arises mainly because of the fact that in logarithmic retrievals the weight of the prior information depends on abundance of the gas itself. No simple rule was found on which kind of averaging is superior, and instead of suggesting simple recipes we cannot do much more than to create awareness of the traps related with averaging of mixing ratios obtained from logarithmic retrievals.

  7. 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.

    2018-01-01

    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.

  8. 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

  9. prediction of rainfall in the southern highlands of tanzania

    African Journals Online (AJOL)

    User

    distribution at different places in the world. A study to ... climate indices influence rainfall. It has been observed .... Table 4: Summary of Predictors entered MLR and PCR models for MAM and OND rainfalls. .... from the cumulus clouds; rainfall is.

  10. Ostrich recruitment dynamics in relation to rainfall in the Mara ...

    African Journals Online (AJOL)

    Ostrich recruitment dynamics in relation to rainfall in the Mara–Serengeti ... To understand how rainfall influences ostriches, we related changes in ostrich recruitment in the Mara–Serengeti ecosystem to rainfall. ... AJOL African Journals Online.

  11. Lagrangian averaging with geodesic mean.

    Science.gov (United States)

    Oliver, Marcel

    2017-11-01

    This paper revisits the derivation of the Lagrangian averaged Euler (LAE), or Euler- α equations in the light of an intrinsic definition of the averaged flow map as the geodesic mean on the volume-preserving diffeomorphism group. Under the additional assumption that first-order fluctuations are statistically isotropic and transported by the mean flow as a vector field, averaging of the kinetic energy Lagrangian of an ideal fluid yields the LAE Lagrangian. The derivation presented here assumes a Euclidean spatial domain without boundaries.

  12. How important is the spatiotemporal structure of a rainfall field when generating a streamflow hydrograph? An investigation using Reverse Hydrology

    Science.gov (United States)

    Kretzschmar, Ann; Tych, Wlodek; Beven, Keith; Chappell, Nick

    2017-04-01

    Flooding is the most widely occurring natural disaster affecting thousands of lives and businesses worldwide each year, and the size and frequency of flood-events are predicted to increase with climate change. The main input-variable for models used in flood prediction is rainfall. Estimating the rainfall input is often based on a sparse network of raingauges, which may or may not be representative of the salient rainfall characteristics responsible for generating of storm-hydrographs. A method based on Reverse Hydrology (Kretzschmar et al 2014 Environ Modell Softw) has been developed and is being tested using the intensively-instrumented Brue catchment (Southwest England) to explore the spatiotemporal structure of the rainfall-field (using 23 rain gauges over the 135.2 km2 basin). We compare how well the rainfall measured at individual gauges, or averaged over the basin, represent the rainfall inferred from the streamflow signal. How important is it to get the detail of the spatiotemporal rainfall structure right? Rainfall is transformed by catchment processes as it moves to streams, so exact duplication of the structure may not be necessary. 'True' rainfall estimated using 23 gauges / 135.2 km2 is likely to be a good estimate of the overall-catchment-rainfall, however, the integration process 'smears' the rainfall patterns in time, i.e. reduces the number of and lengthens rain-events as they travel across the catchment. This may have little impact on the simulation of stream-hydrographs when events are extensive across the catchment (e.g., frontal rainfall events) but may be significant for high-intensity, localised convective events. The Reverse Hydrology approach uses the streamflow record to infer a rainfall sequence with a lower time-resolution than the original input time-series. The inferred rainfall series is, however, able simulate streamflow as well as the observed, high resolution rainfall (Kretzschmar et al 2015 Hydrol Res). Most gauged catchments in

  13. Application of Statistical Downscaling Techniques to Predict Rainfall and Its Spatial Analysis Over Subansiri River Basin of Assam, India

    Science.gov (United States)

    Barman, S.; Bhattacharjya, R. K.

    2017-12-01

    The River Subansiri is the major north bank tributary of river Brahmaputra. It originates from the range of Himalayas beyond the Great Himalayan range at an altitude of approximately 5340m. Subansiri basin extends from tropical to temperate zones and hence exhibits a great diversity in rainfall characteristics. In the Northern and Central Himalayan tracts, precipitation is scarce on account of high altitudes. On the other hand, Southeast part of the Subansiri basin comprising the sub-Himalayan and the plain tract in Arunachal Pradesh and Assam, lies in the tropics. Due to Northeast as well as Southwest monsoon, precipitation occurs in this region in abundant quantities. Particularly, Southwest monsoon causes very heavy precipitation in the entire Subansiri basin during May to October. In this study, the rainfall over Subansiri basin has been studied at 24 different locations by multiple linear and non-linear regression based statistical downscaling techniques and by Artificial Neural Network based model. APHRODITE's gridded rainfall data of 0.25˚ x 0.25˚ resolutions and climatic parameters of HadCM3 GCM of resolution 2.5˚ x 3.75˚ (latitude by longitude) have been used in this study. It has been found that multiple non-linear regression based statistical downscaling technique outperformed the other techniques. Using this method, the future rainfall pattern over the Subansiri basin has been analyzed up to the year 2099 for four different time periods, viz., 2020-39, 2040-59, 2060-79, and 2080-99 at all the 24 locations. On the basis of historical rainfall, the months have been categorized as wet months, months with moderate rainfall and dry months. The spatial changes in rainfall patterns for all these three types of months have also been analyzed over the basin. Potential decrease of rainfall in the wet months and months with moderate rainfall and increase of rainfall in the dry months are observed for the future rainfall pattern of the Subansiri basin.

  14. Heavy rainfall equations for Santa Catarina, Brazil

    Directory of Open Access Journals (Sweden)

    Álvaro José Back

    2011-12-01

    Full Text Available Knowledge of intensity-duration-frequency (IDF relationships of rainfall events is extremely important to determine the dimensions of surface drainage structures and soil erosion control. The purpose of this study was to obtain IDF equations of 13 rain gauge stations in the state of Santa Catarina in Brazil: Chapecó, Urussanga, Campos Novos, Florianópolis, Lages, Caçador, Itajaí, Itá, Ponte Serrada, Porto União, Videira, Laguna and São Joaquim. The daily rainfall data charts of each station were digitized and then the annual maximum rainfall series were determined for durations ranging from 5 to 1440 min. Based on these, with the Gumbel-Chow distribution, the maximum rainfall was estimated for durations ranging from 5 min to 24 h, considering return periods of 2, 5, 10, 20, 25, 50, and 100 years,. Data agreement with the Gumbel-Chow model was verified by the Kolmogorov-Smirnov test, at 5 % significance level. For each rain gauge station, two IDF equations of rainfall events were adjusted, one for durations from 5 to 120 min and the other from 120 to 1440 min. The results show a high variability in maximum intensity of rainfall events among the studied stations. Highest values of coefficients of variation in the annual maximum series of rainfall were observed for durations of over 600 min at the stations of the coastal region of Santa Catarina.

  15. Averaging in spherically symmetric cosmology

    International Nuclear Information System (INIS)

    Coley, A. A.; Pelavas, N.

    2007-01-01

    The averaging problem in cosmology is of fundamental importance. When applied to study cosmological evolution, the theory of macroscopic gravity (MG) can be regarded as a long-distance modification of general relativity. In the MG approach to the averaging problem in cosmology, the Einstein field equations on cosmological scales are modified by appropriate gravitational correlation terms. We study the averaging problem within the class of spherically symmetric cosmological models. That is, we shall take the microscopic equations and effect the averaging procedure to determine the precise form of the correlation tensor in this case. In particular, by working in volume-preserving coordinates, we calculate the form of the correlation tensor under some reasonable assumptions on the form for the inhomogeneous gravitational field and matter distribution. We find that the correlation tensor in a Friedmann-Lemaitre-Robertson-Walker (FLRW) background must be of the form of a spatial curvature. Inhomogeneities and spatial averaging, through this spatial curvature correction term, can have a very significant dynamical effect on the dynamics of the Universe and cosmological observations; in particular, we discuss whether spatial averaging might lead to a more conservative explanation of the observed acceleration of the Universe (without the introduction of exotic dark matter fields). We also find that the correlation tensor for a non-FLRW background can be interpreted as the sum of a spatial curvature and an anisotropic fluid. This may lead to interesting effects of averaging on astrophysical scales. We also discuss the results of averaging an inhomogeneous Lemaitre-Tolman-Bondi solution as well as calculations of linear perturbations (that is, the backreaction) in an FLRW background, which support the main conclusions of the analysis

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

    Directory of Open Access Journals (Sweden)

    Abdulkadir Taofeeq Sholagberu

    2016-07-01

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

  17. Averaging models: parameters estimation with the R-Average procedure

    Directory of Open Access Journals (Sweden)

    S. Noventa

    2010-01-01

    Full Text Available The Functional Measurement approach, proposed within the theoretical framework of Information Integration Theory (Anderson, 1981, 1982, can be a useful multi-attribute analysis tool. Compared to the majority of statistical models, the averaging model can account for interaction effects without adding complexity. The R-Average method (Vidotto & Vicentini, 2007 can be used to estimate the parameters of these models. By the use of multiple information criteria in the model selection procedure, R-Average allows for the identification of the best subset of parameters that account for the data. After a review of the general method, we present an implementation of the procedure in the framework of R-project, followed by some experiments using a Monte Carlo method.

  18. Synoptic aspects of the central Chile rainfall variability associated with the southern oscillation

    International Nuclear Information System (INIS)

    Rutllant, J.; Fuenzalida, H.

    1988-07-01

    Central Chile winter rainfall patterns show a positive anomaly during the developing stage of warm events associated to the negative phase of the Southern Oscillation. On the other hand, cold events during the positive phase of the Southern Oscillation, correspond quite closely to dry conditions. However, several dry years seem to precede or follow warm events without being necessarily classified as cold events. A synoptic characterization of major winter storms during the development of the most recent warm events in 1972, 1982 and 1987, is presented. Dry winter months during cold-event years are described in terms of average 500 hPa contour anomaly fields. Significant departures from this general behavior, as storms not associated to warm events and extended dry periods during otherwise wet winters, are also analyzed. It is found that major winter storms occurring during the developing phase of warm events are related to hemispheric types of blocking and anomaly patterns where sonal wavenumber 4 and a particular phase of wavenumber 3 dominate. The blockings, located in the Bellingshausen sea area, split the westerly flow diverting the storm tracks towards central Chile. Cold years, often immediately preceding or following a warm event, bring dry conditions in the study area due to a well developed subtropical anticyclonic belt and predominantly sonal westerly flow. Superimposed on these general conditions, anomaly contour patterns in southern South America reveal opposite signs with respect to those associated to warm events. Heavy winter storms not coinciding with warm events show local types of blocking in the Antartic peninsula area, with meridionally or slightly NE-SW oriented troughs and ridges. Extended dry spells and rainfall episodes during warm-event winters seem to be connected with alternating subtropical anomalies moving east with an intraseasonal time scale, superimposed on the aforementioned anomaly pattern at high latitudes. 21 refs, 17 figs, 1 tab

  19. Rainfall prediction of Cimanuk watershed regions with canonical correlation analysis (CCA)

    Science.gov (United States)

    Rustiana, Shailla; Nurani Ruchjana, Budi; Setiawan Abdullah, Atje; Hermawan, Eddy; Berliana Sipayung, Sinta; Gede Nyoman Mindra Jaya, I.; Krismianto

    2017-10-01

    Rainfall prediction in Indonesia is very influential on various development sectors, such as agriculture, fisheries, water resources, industry, and other sectors. The inaccurate predictions can lead to negative effects. Cimanuk watershed is one of the main pillar of water resources in West Java. This watersheds divided into three parts, which is a headwater of Cimanuk sub-watershed, Middle of Cimanuk sub-watershed and downstream of Cimanuk sub- watershed. The flow of this watershed will flow through the Jatigede reservoir and will supply water to the north-coast area in the next few years. So, the reliable model of rainfall prediction is very needed in this watershed. Rainfall prediction conducted with Canonical Correlation Analysis (CCA) method using Climate Predictability Tool (CPT) software. The prediction is every 3months on 2016 (after January) based on Climate Hazards group Infrared Precipitation with Stations (CHIRPS) data over West Java. Predictors used in CPT were the monthly data index of Nino3.4, Dipole Mode (DMI), and Monsoon Index (AUSMI-ISMI-WNPMI-WYMI) with initial condition January. The initial condition is chosen by the last data update. While, the predictant were monthly rainfall data CHIRPS region of West Java. The results of prediction rainfall showed by skill map from Pearson Correlation. High correlation of skill map are on MAM (Mar-Apr-May), AMJ (Apr-May-Jun), and JJA (Jun-Jul-Aug) which means the model is reliable to forecast rainfall distribution over Cimanuk watersheds region (over West Java) on those seasons. CCA score over those season prediction mostly over 0.7. The accuracy of the model CPT also indicated by the Relative Operating Characteristic (ROC) curve of the results of Pearson correlation 3 representative point of sub-watershed (Sumedang, Majalengka, and Cirebon), were mostly located in the top line of non-skill, and evidenced by the same of rainfall patterns between observation and forecast. So, the model of CPT with CCA method

  20. Modelling monthly runoff generation processes following land use changes: groundwater–surface runoff interactions

    Directory of Open Access Journals (Sweden)

    M. Bari

    2004-01-01

    Full Text Available A conceptual water balance model is presented to represent changes in monthly water balance following land use changes. Monthly rainfall–runoff, groundwater and soil moisture data from four experimental catchments in Western Australia have been analysed. Two of these catchments, 'Ernies' (control, fully forested and 'Lemon' (54% cleared are in a zone of mean annual rainfall of 725 mm, while 'Salmon' (control, fully forested and 'Wights' (100% cleared are in a zone with mean annual rainfall of 1125 mm. At the Salmon forested control catchment, streamflow comprises surface runoff, base flow and interflow components. In the Wights catchment, cleared of native forest for pasture development, all three components increased, groundwater levels rose significantly and stream zone saturated area increased from 1% to 15% of the catchment area. It took seven years after clearing for the rainfall–runoff generation process to stabilise in 1984. At the Ernies forested control catchment, the permanent groundwater system is 20 m below the stream bed and so does not contribute to streamflow. Following partial clearing of forest in the Lemon catchment, groundwater rose steadily and reached the stream bed by 1987. The streamflow increased in two phases: (i immediately after clearing due to reduced evapotranspiration, and (ii through an increase in the groundwater-induced stream zone saturated area after 1987. After analysing all the data available, a conceptual monthly model was created, comprising four inter-connecting stores: (i an upper zone unsaturated store, (ii a transient stream zone store, (ii a lower zone unsaturated store and (iv a saturated groundwater store. Data such as rooting depth, Leaf Area Index, soil porosity, profile thickness, depth to groundwater, stream length and surface slope were incorporated into the model as a priori defined attributes. The catchment average values for different stores were determined through matching observed and

  1. Tropical intraseasonal rainfall variability in the CFSR

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Jiande [I.M. System Group Inc. at NOAA/NCEP/EMC, Camp Springs, MD (United States); Wang, Wanqiu [NOAA/NCEP/CPC, Camp Springs, MD (United States); Fu, Xiouhua [University of Hawaii at Manoa, IPRC, SOEST, Honolulu, HI (United States); Seo, Kyong-Hwan [Pusan National University, Department of Atmospheric Sciences, Busan (Korea, Republic of)

    2012-06-15

    While large-scale circulation fields from atmospheric reanalyses have been widely used to study the tropical intraseasonal variability, rainfall variations from the reanalyses are less focused. Because of the sparseness of in situ observations available in the tropics and strong coupling between convection and large-scale circulation, the accuracy of tropical rainfall from the reanalyses not only measures the quality of reanalysis rainfall but is also to some extent indicative of the accuracy of the circulations fields. This study analyzes tropical intraseasonal rainfall variability in the recently completed NCEP Climate Forecast System Reanalysis (CFSR) and its comparison with the widely used NCEP/NCAR reanalysis (R1) and NCEP/DOE reanalysis (R2). The R1 produces too weak rainfall variability while the R2 generates too strong westward propagation. Compared with the R1 and R2, the CFSR produces greatly improved tropical intraseasonal rainfall variability with the dominance of eastward propagation and more realistic amplitude. An analysis of the relationship between rainfall and large-scale fields using composites based on Madden-Julian Oscillation (MJO) events shows that, in all three NCEP reanalyses, the moisture convergence leading the rainfall maximum is near the surface in the western Pacific but is above 925 hPa in the eastern Indian Ocean. However, the CFSR produces the strongest large-scale convergence and the rainfall from CFSR lags the column integrated precipitable water by 1 or 2 days while R1 and R2 rainfall tends to lead the respective precipitable water. Diabatic heating related to the MJO variability in the CFSR is analyzed and compared with that derived from large-scale fields. It is found that the amplitude of CFSR-produced total heating anomalies is smaller than that of the derived. Rainfall variability from the other two recently produced reanalyses, the ECMWF Re-Analysis Interim (ERAI), and the Modern Era Retrospective-analysis for Research and

  2. Evaluations of average level spacings

    International Nuclear Information System (INIS)

    Liou, H.I.

    1980-01-01

    The average level spacing for highly excited nuclei is a key parameter in cross section formulas based on statistical nuclear models, and also plays an important role in determining many physics quantities. Various methods to evaluate average level spacings are reviewed. Because of the finite experimental resolution, to detect a complete sequence of levels without mixing other parities is extremely difficult, if not totally impossible. Most methods derive the average level spacings by applying a fit, with different degrees of generality, to the truncated Porter-Thomas distribution for reduced neutron widths. A method that tests both distributions of level widths and positions is discussed extensivey with an example of 168 Er data. 19 figures, 2 tables

  3. Evolution of rainfall in the Sahel

    International Nuclear Information System (INIS)

    Diallo, M.A.

    1995-09-01

    In this note, a number of main meteorological stations has been chosen to analyse the rainfall during the last 30 years in the Sahel (1961 to 1990). Reliable climatological data have been used for this study. The concerned area is limited by the 200 mm isohyet in the north and 600 mm isohyet in the south in the Sahel countries (Senegal, Mauritania, Mali, Burkina Faso, Niger and Chad). The evolution of rainfall has pointed out some similar and significant aspects for all stations studied. Established criteria have been used to characterize the annual rainfall and to determine the years with good rainfall and years of drought in the Sahel. (author). 6 refs, 3 figs

  4. Monsoon Rainfall and Landslides in Nepal

    Science.gov (United States)

    Dahal, R. K.; Hasegawa, S.; Bhandary, N. P.; Yatabe, R.

    2009-12-01

    A large number of human settlements on the Nepal Himalayas are situated either on old landslide mass or on landslide-prone areas. As a result, a great number of people are affected by large- and small-scale landslides all over the Himalayas especially during monsoon periods. In Nepal, only in the half monsoon period (June 10 to August 15), 70, 50 and 68 people were killed from landslides in 2007, 2008 and 2009, respectively. In this context, this paper highlights monsoon rainfall and their implications in the Nepal Himalaya. In Nepal, monsoon is major source of rainfall in summer and approximately 80% of the annual total rainfall occurs from June to September. The measured values of mean annual precipitation in Nepal range from a low of approximately 250 mm at area north of the Himalaya to many areas exceeding 6,000 mm. The mean annual rainfall varying between 1500 mm and 2500 mm predominate over most of the country. In Nepal, the daily distribution of precipitation during rainy season is also uneven. Sometime 10% of the total annual precipitation can occur in a single day. Similarly, 50% total annual rainfall also can occur within 10 days of monsoon. This type of uneven distribution plays an important role in triggering many landslides in Nepal. When spatial distribution of landslides was evaluated from record of more than 650 landslides, it is found that more landslides events were concentrated at central Nepal in the area of high mean annual rainfall. When monsoon rainfall and landslide relationship was taken into consideration, it was noticed that a considerable number of landslides were triggered in the Himalaya by continuous rainfall of 3 to 90 days. It has been noticed that continuous rainfall of few days (5 days or 7 days or 10 days) are usually responsible for landsliding in the Nepal Himalaya. Monsoon rains usually fall with interruptions of 2-3 days and are generally characterized by low intensity and long duration. Thus, there is a strong role of

  5. Improving the understanding of rainfall distribution and ...

    African Journals Online (AJOL)

    2016-10-04

    Oct 4, 2016 ... facilities and development of robust methods, especially geosta- tistically-based .... Cathedral Peak historical rainfall dataset, quality control pro- cedures .... used to assess the predictive power of the developed model. The.

  6. 10 Characterisation of Seasonal Rainfall.cdr

    African Journals Online (AJOL)

    Administrator

    El Nino-South Oscillation (ENSO) phenomenon occurs in the Equatorial Eastern Pacific Ocean and has been noted to ... of crops. There is need for more research attention on the onset of rainfall and ... impacts of adverse weather conditions or.

  7. Maximum daily rainfall in South Korea

    Indian Academy of Sciences (India)

    and Dongseok Choi. 2. 1. School of Mathematics, University of Manchester, Manchester M60 1QD, UK. ... This paper provides the first application of extreme value distributions to rainfall data from South Korea. 1. ..... protection. This paper only ...

  8. Ergodic averages via dominating processes

    DEFF Research Database (Denmark)

    Møller, Jesper; Mengersen, Kerrie

    2006-01-01

    We show how the mean of a monotone function (defined on a state space equipped with a partial ordering) can be estimated, using ergodic averages calculated from upper and lower dominating processes of a stationary irreducible Markov chain. In particular, we do not need to simulate the stationary...... Markov chain and we eliminate the problem of whether an appropriate burn-in is determined or not. Moreover, when a central limit theorem applies, we show how confidence intervals for the mean can be estimated by bounding the asymptotic variance of the ergodic average based on the equilibrium chain....

  9. Benchmarking monthly homogenization algorithms

    Science.gov (United States)

    Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratianni, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.

    2011-08-01

    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 precipitation data

  10. Contribution of tropical cyclones to global rainfall

    Science.gov (United States)

    Khouakhi, Abdou; Villarini, Gabriele; Vecchi, Gabriel; Smith, James

    2016-04-01

    Rainfall associated with tropical cyclones (TCs) can have both devastating and beneficial impacts in different parts of the world. In this work, daily precipitation and historical six-hour best track TC datasets are used to quantify the contribution of TCs to global rainfall. We select 18607 rain gauge stations with at least 25 complete (at least 330 measurements per year) years between 1970 and 2014. We consider rainfall associated with TCs if the center of circulation of the storm passed within a given distance from the rain gauge and within a given time window. Spatial and temporal sensitivity analyses are performed with varying time windows (same day, ±1 day) and buffer radii (400 km and 500 km) around each rain gauge. Results highlight regional differences in TC-induced rainfall. The highest TC-induced precipitation totals (400 to 600+ mm/year) are prevalent along eastern Asia, western and northeastern Australia, and in the western Pacific islands. Stations along the southeast of the U.S. coast and surrounding the Gulf of Mexico receive up to 200 mm/year of TC rainfall. The highest annual fractional contributions of TCs to total rainfall (from 35 to 50%) are recorded in stations located in northwestern Australia, southeastern China, the northern Philippines and the southern Mexico peninsula. Seasonally, the highest proportions (40 to 50%) are recorded along eastern Australia and Mauritius in winter, and in eastern Asia and Mexico in summer and autumn. Analyses of the relative contribution of TCs to extreme rainfall using annual maximum (AM) and peaks-over-threshold (POT) approaches indicate notable differences among regions. The highest TC-AM rainfall proportions (45 to 60%) are found in stations located in Japan, eastern China, the Philippines, eastern and western Australia. Substantial contributions (25 to 40% of extreme rainfall) are also recorded in stations located along the U.S. East Coast, the Gulf of Mexico, and the Mexico peninsula. We find similar

  11. Impact of Spatiotemporal Characteristics of Rainfall Inputs on Integrated Catchment Dissolved Oxygen Simulations

    Directory of Open Access Journals (Sweden)

    Antonio M. Moreno-Rodenas

    2017-11-01

    Full Text Available Integrated Catchment Modelling aims to simulate jointly urban drainage systems, wastewater treatment plant and rivers. The effect of rainfall input uncertainties in the modelling of individual urban drainage systems has been discussed in several studies already. However, this influence changes when simultaneously simulating several urban drainage subsystems and their impact on receiving water quality. This study investigates the effect of the characteristics of rainfall inputs on a large-scale integrated catchment simulator for dissolved oxygen predictions in the River Dommel (The Netherlands. Rainfall products were generated with varying time-aggregation (10, 30 and 60 min deriving from different sources of data with increasing spatial information: (1 Homogeneous rainfall from a single rain gauge; (2 block kriging from 13 rain gauges; (3 averaged C-Band radar estimation and (4 kriging with external drift combining radar and rain gauge data with change of spatial support. The influence of the different rainfall inputs was observed at combined sewer overflows (CSO and dissolved oxygen (DO dynamics in the river. Comparison of the simulations with river monitoring data showed a low sensitivity to temporal aggregation of rainfall inputs and a relevant impact of the spatial scale with a link to the storm characteristics to CSO and DO concentration in the receiving water.

  12. Spatial and Temporal Variability of Rainfall in the Gandaki River Basin of Nepal Himalaya

    Directory of Open Access Journals (Sweden)

    Jeeban Panthi

    2015-03-01

    Full Text Available Landslides, floods, and droughts are recurring natural disasters in Nepal related to too much or too little water. The summer monsoon contributes more than 80% of annual rainfall, and rainfall spatial and inter-annual variation is very high. The Gandaki River, one of the three major rivers of Nepal and one of the major tributaries of the Ganges River, covers all agro-ecological zones in the central part of Nepal. Time series tests were applied for different agro-ecological zones of the Gandaki River Basin (GRB for rainfall trends of four seasons (pre-monsoon, monsoon, post-monsoon and winter from 1981 to 2012. The non-parametric Mann-Kendall and Sen’s methods were used to determine the trends. Decadal anomalies relative to the long-term average were analyzed using the APHRODITE precipitation product. Trends in number of rainy days and timing of the monsoon were also analyzed. We found that the post-monsoon, pre-monsoon and winter rainfalls are decreasing significantly in most of the zones but monsoon rainfall is increasing throughout the basin. In the hill region, the annual rainfall is increasing but the rainy days do not show any trend. There is a tendency toward later departure of monsoon from Nepal, indicating an increase in its duration. These seasonally and topographically variable trends may have significant impacts for the agriculture and livestock smallholders that form the majority of the population in the GRB.

  13. ANALISIS CURAH HUJAN DAN DEBIT MODEL SWAT DENGAN METODE MOVING AVERAGE DI DAS CILIWUNG HULU

    Directory of Open Access Journals (Sweden)

    Defri Satiya Zuma

    2017-09-01

    Full Text Available Watershed can be regarded as a hydrological system that has a function in transforming rainwater as an input into outputs such as flow and sediment. The transformation of inputs into outputs has specific forms and properties. The transformation involves many processes, including processes occurred on the surface of the land, river basins, in soil and aquifer. This study aimed to apply the SWAT model  in  Ciliwung Hulu Watershed, asses the effect of average rainfall  on 3 days, 5 days, 7 days and 10 days of the hydrological characteristics in Ciliwung Hulu Watershed. The correlation coefficient (r between rainfall and discharge was positive, it indicated that there was an unidirectional relationship between rainfall and discharge in the upstream, midstream and downstream of the watershed. The upper limit ratio of discharge had a downward trend from upstream to downstream, while the lower limit ratio of  discharge had an upward trend from upstream to downstream. It showed that the discharge peak in Ciliwung  Hulu Watershed from upstream to downstream had a downward trend while the baseflow from upstream to downstream had an upward trend. It showed that the upstream of Ciliwung Hulu Watershed had the highest ratio of discharge peak  and baseflow so it needs the soil and water conservations and technical civil measures. The discussion concluded that the SWAT model could be well applied in Ciliwung Hulu Watershed, the most affecting average rainfall on the hydrological characteristics was the average rainfall of 10 days. On average  rainfall of 10 days, all components had contributed maximally for river discharge.

  14. Global Warming Induced Changes in Rainfall Characteristics in IPCC AR5 Models

    Science.gov (United States)

    Lau, William K. M.; Wu, Jenny, H.-T.; Kim, Kyu-Myong

    2012-01-01

    Changes in rainfall characteristic induced by global warming are examined from outputs of IPCC AR5 models. Different scenarios of climate warming including a high emissions scenario (RCP 8.5), a medium mitigation scenario (RCP 4.5), and 1% per year CO2 increase are compared to 20th century simulations (historical). Results show that even though the spatial distribution of monthly rainfall anomalies vary greatly among models, the ensemble mean from a sizable sample (about 10) of AR5 models show a robust signal attributable to GHG warming featuring a shift in the global rainfall probability distribution function (PDF) with significant increase (>100%) in very heavy rain, reduction (10-20% ) in moderate rain and increase in light to very light rains. Changes in extreme rainfall as a function of seasons and latitudes are also examined, and are similar to the non-seasonal stratified data, but with more specific spatial dependence. These results are consistent from TRMM and GPCP rainfall observations suggesting that extreme rainfall events are occurring more frequently with wet areas getting wetter and dry-area-getting drier in a GHG induced warmer climate.

  15. Development and evaluation of a stochastic daily rainfall model with long-term variability

    Science.gov (United States)

    Kamal Chowdhury, A. F. M.; Lockart, Natalie; Willgoose, Garry; Kuczera, George; Kiem, Anthony S.; Parana Manage, Nadeeka

    2017-12-01

    The primary objective of this study is to develop a stochastic rainfall generation model that can match not only the short resolution (daily) variability but also the longer resolution (monthly to multiyear) variability of observed rainfall. This study has developed a Markov chain (MC) model, which uses a two-state MC process with two parameters (wet-to-wet and dry-to-dry transition probabilities) to simulate rainfall occurrence and a gamma distribution with two parameters (mean and standard deviation of wet day rainfall) to simulate wet day rainfall depths. Starting with the traditional MC-gamma model with deterministic parameters, this study has developed and assessed four other variants of the MC-gamma model with different parameterisations. The key finding is that if the parameters of the gamma distribution are randomly sampled each year from fitted distributions rather than fixed parameters with time, the variability of rainfall depths at both short and longer temporal resolutions can be preserved, while the variability of wet periods (i.e. number of wet days and mean length of wet spell) can be preserved by decadally varied MC parameters. This is a straightforward enhancement to the traditional simplest MC model and is both objective and parsimonious.

  16. Spatial Interpolation of Daily Rainfall Data for Local Climate Impact Assessment over Greater Sydney Region

    Directory of Open Access Journals (Sweden)

    Xihua Yang

    2015-01-01

    Full Text Available This paper presents spatial interpolation techniques to produce finer-scale daily rainfall data from regional climate modeling. Four common interpolation techniques (ANUDEM, Spline, IDW, and Kriging were compared and assessed against station rainfall data and modeled rainfall. The performance was assessed by the mean absolute error (MAE, mean relative error (MRE, root mean squared error (RMSE, and the spatial and temporal distributions. The results indicate that Inverse Distance Weighting (IDW method is slightly better than the other three methods and it is also easy to implement in a geographic information system (GIS. The IDW method was then used to produce forty-year (1990–2009 and 2040–2059 time series rainfall data at daily, monthly, and annual time scales at a ground resolution of 100 m for the Greater Sydney Region (GSR. The downscaled daily rainfall data have been further utilized to predict rainfall erosivity and soil erosion risk and their future changes in GSR to support assessments and planning of climate change impact and adaptation in local scale.

  17. Tropical Atlantic Contributions to Strong Rainfall Variability Along the Northeast Brazilian Coast

    Directory of Open Access Journals (Sweden)

    G. A. Hounsou-gbo

    2015-01-01

    Full Text Available Tropical Atlantic (TA Ocean-atmosphere interactions and their contributions to strong variability of rainfall along the Northeast Brazilian (NEB coast were investigated for the years 1974–2008. The core rainy seasons of March-April and June-July were identified for Fortaleza (northern NEB; NNEB and Recife (eastern NEB; ENEB, respectively. Lagged linear regressions between sea surface temperature (SST and pseudo wind stress (PWS anomalies over the entire TA and strong rainfall anomalies at Fortaleza and Recife show that the rainfall variability of these regions is differentially influenced by the dynamics of the TA. When the Intertropical Convergence Zone is abnormally displaced southward a few months prior to the NNEB rainy season, the associated meridional mode increases humidity and precipitation during the rainy season. Additionally, this study shows predictive effect of SST, meridional PWS, and barrier layer thickness, in the Northwestern equatorial Atlantic, on the NNEB rainfall. The dynamical influence of the TA on the June-July ENEB rainfall variability shows a northwestward-propagating area of strong, positively correlated SST from the southeastern TA to the southwestern Atlantic warm pool (SAWP offshore of Brazil. Our results also show predictive effect of SST, zonal PWS, and mixed layer depth, in the SAWP, on the ENEB rainfall.

  18. Association of Taiwan’s Rainfall Patterns with Large-Scale Oceanic and Atmospheric Phenomena

    Directory of Open Access Journals (Sweden)

    Yi-Chun Kuo

    2016-01-01

    Full Text Available A 50-year (1960–2009 monthly rainfall gridded dataset produced by the Taiwan Climate Change Projection and Information Platform Project was presented in this study. The gridded data (5 × 5 km displayed influence of topography on spatial variability of rainfall, and the results of the empirical orthogonal functions (EOFs analysis revealed the patterns associated with the large-scale sea surface temperature variability over Pacific. The first mode (65% revealed the annual peaks of large rainfall in the southwestern mountainous area, which is associated with southwest monsoons and typhoons during summertime. The second temporal EOF mode (16% revealed the rainfall variance associated with the monsoon and its interaction with the slopes of the mountain range. This pattern is the major contributor to spatial variance of rainfall in Taiwan, as indicated by the first mode (40% of spatial variance EOF analysis. The second temporal EOF mode correlated with the El Niño Southern Oscillation (ENSO. In particular, during the autumn of the La Niña years following the strong El Niño years, the time-varying amplitude was substantially greater than that of normal years. The third temporal EOF mode (7% revealed a north-south out-of-phase rainfall pattern, the slowly evolving variations of which were in phase with the Pacific Decadal Oscillation. Because of Taiwan’s geographic location and the effect of local terrestrial structures, climate variability related to ENSO differed markedly from other regions in East Asia.

  19. Variability of rainfall over small areas

    Science.gov (United States)

    Runnels, R. C.

    1983-01-01

    A preliminary investigation was made to determine estimates of the number of raingauges needed in order to measure the variability of rainfall in time and space over small areas (approximately 40 sq miles). The literature on rainfall variability was examined and the types of empirical relationships used to relate rainfall variations to meteorological and catchment-area characteristics were considered. Relations between the coefficient of variation and areal-mean rainfall and area have been used by several investigators. These parameters seemed reasonable ones to use in any future study of rainfall variations. From a knowledge of an appropriate coefficient of variation (determined by the above-mentioned relations) the number rain gauges needed for the precise determination of areal-mean rainfall may be calculated by statistical estimation theory. The number gauges needed to measure the coefficient of variation over a 40 sq miles area, with varying degrees of error, was found to range from 264 (10% error, mean precipitation = 0.1 in) to about 2 (100% error, mean precipitation = 0.1 in).

  20. High average power supercontinuum sources

    Indian Academy of Sciences (India)

    The physical mechanisms and basic experimental techniques for the creation of high average spectral power supercontinuum sources is briefly reviewed. We focus on the use of high-power ytterbium-doped fibre lasers as pump sources, and the use of highly nonlinear photonic crystal fibres as the nonlinear medium.

  1. A method for combining passive microwave and infrared rainfall observations

    Science.gov (United States)

    Kummerow, Christian; Giglio, Louis

    1995-01-01

    Because passive microwave instruments are confined to polar-orbiting satellites, rainfall estimates must interpolate across long time periods, during which no measurements are available. In this paper the authors discuss a technique that allows one to partially overcome the sampling limitations by using frequent infrared observations from geosynchronous platforms. To accomplish this, the technique compares all coincident microwave and infrared observations. From each coincident pair, the infrared temperature threshold is selected that corresponds to an area equal to the raining area observed in the microwave image. The mean conditional rainfall rate as determined from the microwave image is then assigned to pixels in the infrared image that are colder than the selected threshold. The calibration is also applied to a fixed threshold of 235 K for comparison with established infrared techniques. Once a calibration is determined, it is applied to all infrared images. Monthly accumulations for both methods are then obtained by summing rainfall from all available infrared images. Two examples are used to evaluate the performance of the technique. The first consists of a one-month period (February 1988) over Darwin, Australia, where good validation data are available from radar and rain gauges. For this case it was found that the technique approximately doubled the rain inferred by the microwave method alone and produced exceptional agreement with the validation data. The second example involved comparisons with atoll rain gauges in the western Pacific for June 1989. Results here are overshadowed by the fact that the hourly infrared estimates from established techniques, by themselves, produced very good correlations with the rain gauges. The calibration technique was not able to improve upon these results.

  2. A Numerical Investigation of Vapor Intrusion — the Dynamic Response of Contaminant Vapors to Rainfall Events

    Science.gov (United States)

    Shen, Rui; Pennell, Kelly G.; Suuberg, Eric M.

    2013-01-01

    The U.S. government and various agencies have published guidelines for field investigation of vapor intrusion, most of which suggest soil gas sampling as an integral part of the investigation. Contaminant soil gas data are often relatively more stable than indoor air vapor concentration measurements, but meteorological conditions might influence soil gas values. Although a few field and numerical studies have considered some temporal effects on soil gas vapor transport, a full explanation of the contaminant vapor concentration response to rainfall events is not available. This manuscript seeks to demonstrate the effects on soil vapor transport during and after different rainfall events, by applying a coupled numerical model of fluid flow and vapor transport. Both a single rainfall event and seasonal rainfall events were modeled. For the single rainfall event models, the vapor response process could be divided into three steps: namely, infiltration, water redistribution, and establishment of a water lens atop the groundwater source. In the infiltration step, rainfall intensity was found to determine the speed of the wetting front and wash-out effect on the vapor. The passage of the wetting front led to an increase of the vapor concentration in both the infiltration and water redistribution steps and this effect is noted at soil probes located 1 m below the ground surface. When the mixing of groundwater with infiltrated water was not allowed, a clean water lens accumulated above the groundwater source and led to a capping effect which can reduce diffusion rates of contaminant from the source. Seasonal rainfall with short time intervals involved superposition of the individual rainfall events. This modeling results indicated that for relatively deeper soil that the infiltration wetting front could not flood, the effects were damped out in less than a month after rain; while in the long term (years), possible formation of a water lens played a larger role in

  3. Study of acid mine drainage management with evaluating climate and rainfall in East Pit 3 West Banko coal mine

    Science.gov (United States)

    Rochyani, Neny

    2017-11-01

    Acid mine drainage is a major problem for the mining environment. The main factor that formed acid mine drainage is the volume of rainfall. Therefore, it is important to know clearly the main climate pattern of rainfall and season on the management of acid mine drainage. This study focuses on the effects of rainfall on acid mine water management. Based on daily rainfall data, monthly and seasonal patterns by using Gumbel approach is known the amount of rainfall that occurred in East Pit 3 West Banko area. The data also obtained the highest maximum daily rainfall on 165 mm/day and the lowest at 76.4 mm/day, where it is known that the rainfall conditions during the period 2007 - 2016 is from November to April so the use of lime is also slightly, While the low rainfall is from May to October and the use of lime will be more and more. Based on calculation of lime requirement for each return period, it can be seen the total of lime and financial requirement for treatment of each return period.

  4. Sediment yield during typhoon events in relation to landslides, rainfall, and catchment areas in Taiwan

    Science.gov (United States)

    Chen, Chi-Wen; Oguchi, Takashi; Hayakawa, Yuichi S.; Saito, Hitoshi; Chen, Hongey; Lin, Guan-Wei; Wei, Lun-Wei; Chao, Yi-Chiung

    2018-02-01

    Debris sourced from landslides will result in environmental problems such as increased sediment discharge in rivers. This study analyzed the sediment discharge of 17 main rivers in Taiwan during 14 typhoon events, selected from the catchment area and river length, that caused landslides according to government reports. The measured suspended sediment and water discharge, collected from hydrometric stations of the Water Resources Agency of Taiwan, were used to establish rating-curve relationships, a power-law relation between them. Then sediment discharge during typhoon events was estimated using the rating-curve method and the measured data of daily water discharge. Positive correlations between sediment discharge and rainfall conditions for each river indicate that sediment discharge increases when a greater amount of rainfall or a higher intensity of rainfall falls during a typhoon event. In addition, the amount of sediment discharge during a typhoon event is mainly controlled by the total amount of rainfall, not by peak rainfall. Differences in correlation equations among the rivers suggest that catchments with larger areas produce more sediment. Catchments with relatively low sediment discharge show more distinct increases in sediment discharge in response to increases in rainfall, owing to the little opportunity for deposition in small catchments with high connectivity to rivers and the transportation of the majority of landslide debris to rivers during typhoon events. Also, differences in geomorphic and geologic conditions among catchments around Taiwan lead to a variety of suspended sediment dynamics and the sediment budget. Positive correlation between average sediment discharge and average area of landslides during typhoon events indicates that when larger landslides are caused by heavier rainfall during a typhoon event, more loose materials from the most recent landslide debris are flushed into rivers, resulting in higher sediment discharge. The high

  5. Prediction of Meiyu rainfall in Taiwan by multi-lead physical-empirical models

    Science.gov (United States)

    Yim, So-Young; Wang, Bin; Xing, Wen; Lu, Mong-Ming

    2015-06-01

    Taiwan is located at the dividing point of the tropical and subtropical monsoons over East Asia. Taiwan has double rainy seasons, the Meiyu in May-June and the Typhoon rains in August-September. To predict the amount of Meiyu rainfall is of profound importance to disaster preparedness and water resource management. The seasonal forecast of May-June Meiyu rainfall has been a challenge to current dynamical models and the factors controlling Taiwan Meiyu variability has eluded climate scientists for decades. Here we investigate the physical processes that are possibly important for leading to significant fluctuation of the Taiwan Meiyu rainfall. Based on this understanding, we develop a physical-empirical model to predict Taiwan Meiyu rainfall at a lead time of 0- (end of April), 1-, and 2-month, respectively. Three physically consequential and complementary predictors are used: (1) a contrasting sea surface temperature (SST) tendency in the Indo-Pacific warm pool, (2) the tripolar SST tendency in North Atlantic that is associated with North Atlantic Oscillation, and (3) a surface warming tendency in northeast Asia. These precursors foreshadow an enhanced Philippine Sea anticyclonic anomalies and the anomalous cyclone near the southeastern China in the ensuing summer, which together favor increasing Taiwan Meiyu rainfall. Note that the identified precursors at various lead-times represent essentially the same physical processes, suggesting the robustness of the predictors. The physical empirical model made by these predictors is capable of capturing the Taiwan rainfall variability with a significant cross-validated temporal correlation coefficient skill of 0.75, 0.64, and 0.61 for 1979-2012 at the 0-, 1-, and 2-month lead time, respectively. The physical-empirical model concept used here can be extended to summer monsoon rainfall prediction over the Southeast Asia and other regions.

  6. Selection of meteorological parameters affecting rainfall estimation using neuro-fuzzy computing methodology

    Science.gov (United States)

    Hashim, Roslan; Roy, Chandrabhushan; Motamedi, Shervin; Shamshirband, Shahaboddin; Petković, Dalibor; Gocic, Milan; Lee, Siew Cheng

    2016-05-01

    Rainfall is a complex atmospheric process that varies over time and space. Researchers have used various empirical and numerical methods to enhance estimation of rainfall intensity. We developed a novel prediction model in this study, with the emphasis on accuracy to identify the most significant meteorological parameters having effect on rainfall. For this, we used five input parameters: wet day frequency (dwet), vapor pressure (e̅a), and maximum and minimum air temperatures (Tmax and Tmin) as well as cloud cover (cc). The data were obtained from the Indian Meteorological Department for the Patna city, Bihar, India. Further, a type of soft-computing method, known as the adaptive-neuro-fuzzy inference system (ANFIS), was applied to the available data. In this respect, the observation data from 1901 to 2000 were employed for testing, validating, and estimating monthly rainfall via the simulated model. In addition, the ANFIS process for variable selection was implemented to detect the predominant variables affecting the rainfall prediction. Finally, the performance of the model was compared to other soft-computing approaches, including the artificial neural network (ANN), support vector machine (SVM), extreme learning machine (ELM), and genetic programming (GP). The results revealed that ANN, ELM, ANFIS, SVM, and GP had R2 of 0.9531, 0.9572, 0.9764, 0.9525, and 0.9526, respectively. Therefore, we conclude that the ANFIS is the best method among all to predict monthly rainfall. Moreover, dwet was found to be the most influential parameter for rainfall prediction, and the best predictor of accuracy. This study also identified sets of two and three meteorological parameters that show the best predictions.

  7. Surface temperature of the equatorial Pacific Ocean and the Indian rainfall

    Digital Repository Service at National Institute of Oceanography (India)

    Gopinathan, C.K.

    The time variation of the monthly mean surface temperature of the equatorial Pacific Ocean during 1982-1987 has been studied in relation to summer monsoon rainfall over India The ENSO events of 1982 and 1987 were related to a significant reduction...

  8. Validation and Analysis of Microwave-Derived Rainfall Over the Tropics

    Science.gov (United States)

    1993-01-01

    Intraseasonal Oscillations In addition to the biennial signals identified by Meehl (1987), Lau and col- laborators (Peng 1987; Shen 1987) expound on...temporally integrated, over a 50 x 50 area for a minimum of one month, to create clima - tological rainfall composites. Validation of the ESMR-derived

  9. Effect of temperature and rainfall on the distribution of the South ...

    African Journals Online (AJOL)

    A multiple regression analysis based on quantified spatial abundance (the number of sixteenth degree squares recorded with shelduck in a degree square), mean annual rainfall, mean annual temperature and mean temperature of the coldest (July) and hottest (January) months indicated a significant (P < 0,001) negative ...

  10. Karst Aquifer in Qatar and its bearing on Natural Rainfall Recharge

    Science.gov (United States)

    Baalousha, Husam; Ackerer, Philippe

    2017-04-01

    Qatar is an arid country with little rainfall and high evaporation. Surface water is non-existent so aquifer is the only source of natural water. The annual long-term averages of rainfall and evaporation are 80 mm and more than 2000 mm, respectively. Despite the low rainfall and high evaporation, natural recharge from rainfall occurs at an average of approximately 50 million m3 per year. Rainfall recharge in Qatar takes in land depressions that occur all over the country. These depressions are a result of land collapse due to sinkholes and cavity in the limestone formation. In the northern part of the country, karst features occur as a result of dissolution of limestone, which leads to land depressions. Results of this study shows groundwater recharge occurs in land depression areas, especially in the northern part of the country, where surface runoff accumulates in these land depressions and recharges the aquifer. This paper was made possible by NPRP grant # [NPRP 9-030-1-008] from the Qatar National Research Fund (a member of Qatar Foundation). The findings achieved herein are solely the responsibility of the author[s]."

  11. Rainfall influence on styles of mass movement

    Science.gov (United States)

    Anderson, S. P.; Rengers, F. K.; Foster, M. A.; Winchell, E. W.; Anderson, R. S.

    2017-12-01

    Precipitation characteristics influence whether hillslope materials move in rain-splash driven hops, shallow landslides, or in deep-seated failures. While one might expect a particular style of slope failure to dominate in a region, we report on multiple distinctive mass movements on a single ridge, each associated with different weather events. This suggests that understanding climate regulation of denudation rates and hillslope morphology requires quantifying both triggering hydro-climates, and the corresponding hillslope response to the full spectrum of events. We explore these connections on Dakota Ridge, a hogback at the eastern margin of the Colorado Front Range. The dipslope of Dakota Ridge has generated slumps, debris flows, and an earthflow over the last 4 years; Pleistocene-era deep-seated landslides are also evident. We document mass-movements along a 1 km long segment of Dakota Ridge. Weeklong precipitation and flooding in September 2013 produced slumps, each of which displaced 50-100 m3 of mobile regolith several meters downslope, and some of which triggered shallow, relatively non-erosive debris flows. By contrast, a similar precipitation total over the month of May 2015 mobilized an earthflow. The 10 m wide earthflow displaced mobile regolith downslope as much as 10 m over its 150 m length. These recent landslides are dwarfed by a 400 m wide deep-seated landslide that controls slope morphology from ridge crest to toe. Exposure ages (10Be) suggest a late-Pleistocene age for this feature. Although the September 2013 storm produced record-setting rainfall totals at daily, monthly and annual timescales (e.g., annual exceedance probability of <1/1000 for daily totals), the failures from that event, while numerous, were the smallest of all the landslides in the study area. These observations raise the question: what hydro-climatic conditions produce deep-seated, bedrock involved slope failures? Recent storms suggest that within mobile regolith, individual

  12. Temporal and spatial variability of rainfall distribution and ...

    African Journals Online (AJOL)

    Rainfall and evapotranspiration are the two major climatic factors affecting agricultural production. This study examined the extent and nature of rainfall variability from measured data while estimation of evapotranspiration was made from recorded weather data. Analysis of rainfall variability is made by the rainfall anomaly ...

  13. Satellite-based estimation of rainfall erosivity for Africa

    NARCIS (Netherlands)

    Vrieling, A.; Sterk, G.; Jong, S.M. de

    2010-01-01

    Rainfall erosivity is a measure for the erosive force of rainfall. Rainfall kinetic energy determines the erosivity and is in turn greatly dependent on rainfall intensity. Attempts for its large-scale mapping are rare. Most are based on interpolation of erosivity values derived from rain gauge

  14. On the uncertainties associated with using gridded rainfall data as a proxy for observed

    Directory of Open Access Journals (Sweden)

    C. R. Tozer

    2012-05-01

    Full Text Available Gridded rainfall datasets are used in many hydrological and climatological studies, in Australia and elsewhere, including for hydroclimatic forecasting, climate attribution studies and climate model performance assessments. The attraction of the spatial coverage provided by gridded data is clear, particularly in Australia where the spatial and temporal resolution of the rainfall gauge network is sparse. However, the question that must be asked is whether it is suitable to use gridded data as a proxy for observed point data, given that gridded data is inherently "smoothed" and may not necessarily capture the temporal and spatial variability of Australian rainfall which leads to hydroclimatic extremes (i.e. droughts, floods. This study investigates this question through a statistical analysis of three monthly gridded Australian rainfall datasets – the Bureau of Meteorology (BOM dataset, the Australian Water Availability Project (AWAP and the SILO dataset. The results of the monthly, seasonal and annual comparisons show that not only are the three gridded datasets different relative to each other, there are also marked differences between the gridded rainfall data and the rainfall observed at gauges within the corresponding grids – particularly for extremely wet or extremely dry conditions. Also important is that the differences observed appear to be non-systematic. To demonstrate the hydrological implications of using gridded data as a proxy for gauged data, a rainfall-runoff model is applied to one catchment in South Australia initially using gauged data as the source of rainfall input and then gridded rainfall data. The results indicate a markedly different runoff response associated with each of the different sources of rainfall data. It should be noted that this study does not seek to identify which gridded dataset is the "best" for Australia, as each gridded data source has its pros and cons, as does gauged data. Rather, the intention is

  15. When good = better than average

    Directory of Open Access Journals (Sweden)

    Don A. Moore

    2007-10-01

    Full Text Available People report themselves to be above average on simple tasks and below average on difficult tasks. This paper proposes an explanation for this effect that is simpler than prior explanations. The new explanation is that people conflate relative with absolute evaluation, especially on subjective measures. The paper then presents a series of four studies that test this conflation explanation. These tests distinguish conflation from other explanations, such as differential weighting and selecting the wrong referent. The results suggest that conflation occurs at the response stage during which people attempt to disambiguate subjective response scales in order to choose an answer. This is because conflation has little effect on objective measures, which would be equally affected if the conflation occurred at encoding.

  16. Estimation of monthly-mean daily global solar radiation based on MODIS and TRMM products

    International Nuclear Information System (INIS)

    Qin, Jun; Chen, Zhuoqi; Yang, Kun; Liang, Shunlin; Tang, Wenjun

    2011-01-01

    Global solar radiation (GSR) is required in a large number of fields. Many parameterization schemes are developed to estimate it using routinely measured meteorological variables, since GSR is directly measured at a limited number of stations. Even so, meteorological stations are sparse, especially, in remote areas. Satellite signals (radiance at the top of atmosphere in most cases) can be used to estimate continuous GSR in space. However, many existing remote sensing products have a relatively coarse spatial resolution and these inversion algorithms are too complicated to be mastered by experts in other research fields. In this study, the artificial neural network (ANN) is utilized to build the mathematical relationship between measured monthly-mean daily GSR and several high-level remote sensing products available for the public, including Moderate Resolution Imaging Spectroradiometer (MODIS) monthly averaged land surface temperature (LST), the number of days in which the LST retrieval is performed in 1 month, MODIS enhanced vegetation index, Tropical Rainfall Measuring Mission satellite (TRMM) monthly precipitation. After training, GSR estimates from this ANN are verified against ground measurements at 12 radiation stations. Then, comparisons are performed among three GSR estimates, including the one presented in this study, a surface data-based estimate, and a remote sensing product by Japan Aerospace Exploration Agency (JAXA). Validation results indicate that the ANN-based method presented in this study can estimate monthly-mean daily GSR at a spatial resolution of about 5 km with high accuracy.

  17. Trends analysis of rainfall and rainfall extremes in Sarawak, Malaysia using modified Mann-Kendall test

    Science.gov (United States)

    Sa'adi, Zulfaqar; Shahid, Shamsuddin; Ismail, Tarmizi; Chung, Eun-Sung; Wang, Xiao-Jun

    2017-11-01

    This study assesses the spatial pattern of changes in rainfall extremes of Sarawak in recent years (1980-2014). The Mann-Kendall (MK) test along with modified Mann-Kendall (m-MK) test, which can discriminate multi-scale variability of unidirectional trend, was used to analyze the changes at 31 stations. Taking account of the scaling effect through eliminating the effect of autocorrelation, m-MK was employed to discriminate multi-scale variability of the unidirectional trends of the annual rainfall in Sarawak. It can confirm the significance of the MK test. The annual rainfall trend from MK test showed significant changes at 95% confidence level at five stations. The seasonal trends from MK test indicate an increasing rate of rainfall during the Northeast monsoon and a decreasing trend during the Southwest monsoon in some region of Sarawak. However, the m-MK test detected an increasing trend in annual rainfall only at one station and no significant trend in seasonal rainfall at any stations. The significant increasing trends of the 1-h maximum rainfall from the MK test are detected mainly at the stations located in the urban area giving concern to the occurrence of the flash flood. On the other hand, the m-MK test detected no significant trend in 1- and 3-h maximum rainfalls at any location. On the contrary, it detected significant trends in 6- and 72-h maximum rainfalls at a station located in the Lower Rajang basin area which is an extensive low-lying agricultural area and prone to stagnant flood. These results indicate that the trends in rainfall and rainfall extremes reported in Malaysia and surrounding region should be verified with m-MK test as most of the trends may result from scaling effect.

  18. Assessment of satellite rainfall products over the Andean plateau

    Science.gov (United States)

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

    2016-01-01

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

  19. Variations of extreme rainfall in space and time

    DEFF Research Database (Denmark)

    Gregersen, Ida Bülow; Madsen, H.; Rosbjerg, Dan

    2012-01-01

    variation, whereas annual variations are related to changes in the average Danish summer precipitation, the average Danish summer temperature and the East Atlantic pattern. The spatio-temporal Poisson regression model was found to be a helpful tool when comparing the internal importance of these variables......In the ongoing climate change discussion, methods for identification of variability governed by climate change are important tools. The magnitude of variables that can describe this variability should be compared with magnitudes of variables describing variability in a stationary setting....... This study focuses on variations of extreme rainfall events, observed at 70 different locations in Denmark over a period of 31 years. The aim is to identify and compare variables, both spatially and temporally, which can explain different parts of the variability in this data set. Assuming that the number...

  20. Autoregressive Moving Average Graph Filtering

    OpenAIRE

    Isufi, Elvin; Loukas, Andreas; Simonetto, Andrea; Leus, Geert

    2016-01-01

    One of the cornerstones of the field of signal processing on graphs are graph filters, direct analogues of classical filters, but intended for signals defined on graphs. This work brings forth new insights on the distributed graph filtering problem. We design a family of autoregressive moving average (ARMA) recursions, which (i) are able to approximate any desired graph frequency response, and (ii) give exact solutions for tasks such as graph signal denoising and interpolation. The design phi...

  1. Assessment of probabilistic areal reduction factors of precipitations for the entire French territory with gridded rainfall data.

    Science.gov (United States)

    Fouchier, Catherine; Maire, Alexis; Arnaud, Patrick; Cantet, Philippe; Odry, Jean

    2016-04-01

    The starting point of our study was the availability of maps of rainfall quantiles available for the entire French mainland territory at the spatial resolution of 1 km². These maps display the rainfall amounts estimated for different rainfall durations (from 15 minutes to 72 hours) and different return periods (from 2 years up to 1 000 years). They are provided by a regionalized stochastic hourly point rainfall generator, the SHYREG method which was previously developed by Irstea (Arnaud et al., 2007; Cantet and Arnaud, 2014). Being calibrated independently on numerous raingauges data (with an average density across the country of 1 raingauge per 200 km²), this method suffers from a limitation common to point-process rainfall generators: it can only reproduce point rainfall patterns and has no capacity to generate rainfall fields. It can't hence provide areal rainfall quantiles, the estimation of the latter being however needed for the construction of design rainfall or for the diagnostic of observed events. One means of bridging this gap between our local rainfall quantiles and areal rainfall quantiles is given by the concept of probabilistic areal reduction factors of rainfall (ARF) as defined by Omolayo (1993). This concept enables to estimate areal rainfall of a particular frequency within a certain amount of time from point rainfalls of the same frequency and duration. Assessing such ARF for the whole French territory is of particular interest since it should allow us to compute areal rainfall quantiles, and eventually watershed rainfall quantiles, by using the already available grids of statistical point rainfall of the SHYREG method. Our purpose was then to assess these ARF thanks to long time-series of spatial rainfall data. We have used two sets of rainfall fields: i) hourly rainfall fields from a 10-year reference database of Quantitative Precipitation Estimation (QPE) over France (Tabary et al., 2012), ii) daily rainfall fields resulting from a 53-year

  2. Averaging Robertson-Walker cosmologies

    International Nuclear Information System (INIS)

    Brown, Iain A.; Robbers, Georg; Behrend, Juliane

    2009-01-01

    The cosmological backreaction arises when one directly averages the Einstein equations to recover an effective Robertson-Walker cosmology, rather than assuming a background a priori. While usually discussed in the context of dark energy, strictly speaking any cosmological model should be recovered from such a procedure. We apply the scalar spatial averaging formalism for the first time to linear Robertson-Walker universes containing matter, radiation and dark energy. The formalism employed is general and incorporates systems of multiple fluids with ease, allowing us to consider quantitatively the universe from deep radiation domination up to the present day in a natural, unified manner. Employing modified Boltzmann codes we evaluate numerically the discrepancies between the assumed and the averaged behaviour arising from the quadratic terms, finding the largest deviations for an Einstein-de Sitter universe, increasing rapidly with Hubble rate to a 0.01% effect for h = 0.701. For the ΛCDM concordance model, the backreaction is of the order of Ω eff 0 ≈ 4 × 10 −6 , with those for dark energy models being within a factor of two or three. The impacts at recombination are of the order of 10 −8 and those in deep radiation domination asymptote to a constant value. While the effective equations of state of the backreactions in Einstein-de Sitter, concordance and quintessence models are generally dust-like, a backreaction with an equation of state w eff < −1/3 can be found for strongly phantom models

  3. Analyses of the temporal and spatial structures of heavy rainfall from a catalog of high-resolution radar rainfall fields

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Smith, James A.; Baeck, Mary Lynn

    2014-01-01

    that relate to size, structure and evolution of heavy rainfall. Extreme rainfall is also linked with severe weather (tornados, large hail and damaging wind). The diurnal cycle of rainfall for heavy rain days is characterized by an early peak in the largest rainfall rates, an afternoon-evening peak in rain...

  4. Analysis of Rainfall Infiltration Law in Unsaturated Soil Slope

    OpenAIRE

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

    2014-01-01

    In the study of unsaturated soil slope stability under rainfall infiltration, it is worth continuing to explore how much rainfall infiltrates into the slope in a rain process, and the amount of rainfall infiltrating into slope is the important factor influencing the stability. Therefore, rainfall infiltration capacity is an important issue of unsaturated seepage analysis for slope. On the basis of previous studies, rainfall infiltration law of unsaturated soil slope is analyzed. Considering t...

  5. Determining rainfall thresholds that trigger landslides in Colombia

    International Nuclear Information System (INIS)

    Mayorga Marquez, Ruth

    2003-01-01

    Considering that rainfall is the natural event that more often triggers landslides, it is important to study the relationship between this phenomenon and the occurrence of earth mass movements, by determining rainfall thresholds that trigger landslides in different zones of Colombia. The research presents a methodology that allows proposing rainfall thresholds that trigger landslides in Colombia, by means of a relationship between the accumulated rain in the soil (antecedent rainfall) and the rain that falls the day of the landslide occurrence (event rainfall)

  6. Identifying multiple timescale rainfall controls on Mojave Desert ecohydrology using an integrated data and modeling approach for Larrea tridentata

    Science.gov (United States)

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

    2015-01-01

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

  7. Relationship between oxygen isotopes in rainfall, cave percolation waters and speleothem calcite at Waitomo, New Zealand

    International Nuclear Information System (INIS)

    Williams, P.W.; Fowler, A.

    2002-01-01

    The relationship between the δ 18 O values of rainfall, vadose percolation water, and speleothem calcite was investigated in a cave at Waitomo. Water samples were obtained approximately monthly for two years from a storage rain gauge on the surface and from stored seepage from three stalactites underground. Rain water δ 18 O SMOW values varied considerably throughout the observation period, with a precipitation-weighted mean of -5.3 permille. Seasonal variability was evident, with winter values being more negative than summer values. Cave seepage waters had a mean of about -5 permille and showed very little variability and no discernible annual variation. This is explained by thorough mixing in the soil and subcutaneous zone stores. Given the average cave temperature (12.8 degrees C) and the δ 18 O SMOW value determined for seepage water, the δ 18 O PDB value of calcite that is actively depositing in isotopic equilibrium on speleothems at Waitomo should fall in the range of -4.1 to -4.6 permille. Observed delta-values of modern speleothem calcites overlap the positive end of this range of theoretical values, indicating that some growing speleothems are not in isotopic equilibrium with seepage waters, but are experiencing either evaporation or kinetic fractionation. (author). 32 refs., 8 figs

  8. Measurement of average radon gas concentration at workplaces

    International Nuclear Information System (INIS)

    Kavasi, N.; Somlai, J.; Kovacs, T.; Gorjanacz, Z.; Nemeth, Cs.; Szabo, T.; Varhegyi, A.; Hakl, J.

    2003-01-01

    In this paper results of measurement of average radon gas concentration at workplaces (the schools and kindergartens and the ventilated workplaces) are presented. t can be stated that the one month long measurements means very high variation (as it is obvious in the cases of the hospital cave and the uranium tailing pond). Consequently, in workplaces where the expectable changes of radon concentration considerable with the seasons should be measure for 12 months long. If it is not possible, the chosen six months period should contain summer and winter months as well. The average radon concentration during working hours can be differ considerable from the average of the whole time in the cases of frequent opening the doors and windows or using artificial ventilation. (authors)

  9. Detection of rainfall-induced landslides on regional seismic networks

    Science.gov (United States)

    Manconi, Andrea; Coviello, Velio; Gariano, Stefano Luigi; Picozzi, Matteo

    2017-04-01

    Seismic techniques are increasingly adopted to detect signals induced by mass movements and to quantitatively evaluate geo-hydrological hazards at different spatial and temporal scales. By analyzing landslide-induced seismicity, it is possible obtaining significant information on the source of the mass wasting, as well as on its dynamics. However, currently only few studies have performed a systematic back analysis on comprehensive catalogues of events to evaluate the performance of proposed algorithms. In this work, we analyze a catalogue of 1058 landslides induced by rainfall in Italy. Among these phenomena, there are 234 rock falls, 55 debris flows, 54 mud flows, and 715 unspecified shallow landslides. This is a subset of a larger catalogue collected by the Italian research institute for geo-hydrological protection (CNR IRPI) during the period 2000-2014 (Brunetti et al., 2015). For each record, the following information are available: the type of landslide; the geographical location of the landslide (coordinates, site, municipality, province, and 3 classes of geographic accuracy); the temporal information on the landslide occurrence (day, month, year, time, date, and 3 classes of temporal accuracy); the rainfall conditions (rainfall duration and cumulated event rainfall) that have resulted in the landslide. We consider here only rainfall-induced landslides for which exact date and time were known from chronicle information. The analysis of coeval seismic data acquired by regional seismic networks show clear signals in at least 3 stations for 64 events (6% of the total dataset). Among them, 20 are associated to local earthquakes and 2 to teleseisms; 10 are anomalous signals characterized by irregular and impulsive waveforms in both time and frequency domains; 33 signals are likely associated to the landslide occurrence, as they have a cigar-shaped waveform characterized by emerging onsets, duration of several tens of seconds, and low frequencies (1-10 Hz). For

  10. Estimation of underground river water availability based on rainfall in the Maros karst region, South Sulawesi

    Science.gov (United States)

    Arsyad, Muhammad; Ihsan, Nasrul; Tiwow, Vistarani Arini

    2016-02-01

    Maros karst region, covering an area of 43.750 hectares, has water resources that determine the life around it. Water resources in Maros karst are in the rock layers or river underground in the cave. The data used in this study are primary and secondary data. Primary data includes characteristics of the medium. Secondary data is rainfall data from BMKG, water discharge data from the PSDA, South Sulawesi province in 1990-2010, and the other characteristics data Maros karst, namely cave, flora and fauna of the Bantimurung Bulusaraung National Park. Data analysis was conducted using laboratory test for medium characteristics Maros karst, rainfall and water discharge were analyzed using Minitab Program 1.5 to determine their profile. The average rainfall above 200 mm per year occurs in the range of 1999 to 2005. The availability of the water discharge at over 50 m3/s was happened in 1993 and 1995. Prediction was done by modeling Autoregressive Integrated Moving Average (ARIMA), with the rainfall data shows that the average precipitation for four years (2011-2014) will sharply fluctuate. The prediction of water discharge in Maros karst region was done for the period from January to August in 2011, including the type of 0. In 2012, the addition of the water discharge started up in early 2014.

  11. Critical Phenomena of Rainfall in Ecuador

    Science.gov (United States)

    Serrano, Sh.; Vasquez, N.; Jacome, P.; Basile, L.

    2014-02-01

    Self-organized criticality (SOC) is characterized by a power law behavior over complex systems like earthquakes and avalanches. We study rainfall using data of one day, 3 hours and 10 min temporal resolution from INAMHI (Instituto Nacional de Meteorologia e Hidrologia) station at Izobamba, DMQ (Metropolitan District of Quito), satellite data over Ecuador from Tropical Rainfall Measure Mission (TRMM,) and REMMAQ (Red Metropolitana de Monitoreo Atmosferico de Quito) meteorological stations over, respectively. Our results show a power law behavior of the number of rain events versus mm of rainfall measured for the high resolution case (10 min), and as the resolution decreases this behavior gets lost. This statistical property is the fingerprint of a self-organized critical process (Peter and Christensen, 2002) and may serve as a benchmark for models of precipitation based in phase transitions between water vapor and precipitation (Peter and Neeling, 2006).

  12. Weather radar rainfall data in urban hydrology

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Einfalt, Thomas; Willems, Patrick

    2017-01-01

    estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Based on these three fields of research, the paper provides recommendations based on an updated overview of shortcomings, gains, and novel developments in relation to urban hydrological...... applications. The paper also reviews how the focus in urban hydrology research has shifted over the last decade to fields such as climate change impacts, resilience of urban areas to hydrological extremes, and online prediction/warning systems. It is discussed how radar rainfall data can add value......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...

  13. Rainfall Climatology over Asir Region, Saudi Arabia

    Science.gov (United States)

    Sharif, H.; Furl, C.; Al-Zahrani, M.

    2012-04-01

    Arid and semi-arid lands occupy about one-third of the land surface of the earth and support about one-fifth of the world population. The Asir area in Saudi Arabia is an example of these areas faced with the problem of maintaining sustainable water resources. This problem is exacerbated by the high levels of population growth, land use changes, increasing water demand, and climate variability. In this study, the characteristics of decade-scale variations in precipitation are examined in more detail for Asir region. The spatio-temporal distributions of rainfall over the region are analyzed. The objectives are to identify the sensitivity, magnitude, and range of changes in annual and seasonal evapotranspiration resulting from observed decade-scale precipitation variations. An additional objective is to characterize orographic controls on the space-time variability of rainfall. The rainfall data is obtained from more than 30 rain gauges spread over the region.

  14. Electric power monthly, April 1993

    Energy Technology Data Exchange (ETDEWEB)

    1993-05-07

    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 US, Census division, and State levels 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.

  15. Electric power monthly, May 1993

    Energy Technology Data Exchange (ETDEWEB)

    1993-05-25

    The Electric Power Monthly (EPM) 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 US, Census division, and State levels 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.

  16. Does GPM-based multi-satellite precipitation enhance rainfall estimates over Pakistan and Bolivia arid regions?

    Science.gov (United States)

    Hussain, Y.; Satgé, F.; Bonnet, M. P.; Pillco, R.; Molina, J.; Timouk, F.; Roig, H.; Martinez-Carvajal, H., Sr.; Gulraiz, A.

    2016-12-01

    Arid regions are sensitive to rainfall variations which are expressed in the form of flooding and droughts. Unfortunately, those regions are poorly monitored and high quality rainfall estimates are still needed. The Global Precipitation Measurement (GPM) mission released two new satellite rainfall products named Integrated Multisatellite Retrievals GPM (IMERG) and Global Satellite Mapping of Precipitation version 6 (GSMaP-v6) bringing the possibility of accurate rainfall monitoring over these countries. This study assessed both products at monthly scale over Pakistan considering dry and wet season over the 4 main climatic zones from 2014 to 2016. With similar climatic conditions, the Altiplano region of Bolivia is considered to quantify the influence of big lakes (Titicaca and Poopó) in rainfall estimates. For comparison, the widely used TRMM-Multisatellite Precipitation Analysis 3B43 (TMPA-3B43) version 7 is also involved in the analysis to observe the potential enhancement in rainfall estimate brought by GPM products. Rainfall estimates derived from 110 rain-gauges are used as reference to compare IMERG, GSMaP-v6 and TMPA-3B43 at the 0.1° and 0.25° spatial resolution. Over both regions, IMERG and GSMaP-v6 capture the spatial pattern of precipitation as well as TMPA-3B43. All products tend to over estimates rainfall over very arid regions. This feature is even more marked during dry season. However, during this season, both reference and estimated rainfall remain very low and do not impact seasonal water budget computation. On a general way, IMERG slightly outperforms TMPA-3B43 and GSMaP-v6 which provides the less accurate rainfall estimate. The TMPA-3B43 rainfall underestimation previously found over Lake Titicaca is still observed in IMERG estimates. However, GSMaP-v6 considerably decreases the underestimation providing the most accurate rainfall estimate over the lake. MOD11C3 Land Surface Temperature (LST) and ASTER Global Emissivity Dataset reveal strong

  17. Validation and correction of rainfall data from the WegenerNet high density network in southeast Austria

    Science.gov (United States)

    O, Sungmin; Foelsche, U.; Kirchengast, G.; Fuchsberger, J.

    2018-01-01

    Eight years of daily rainfall data from WegenerNet were analyzed by comparison with data from Austrian national weather stations. WegenerNet includes 153 ground level weather stations in an area of about 15 km × 20 km in the Feldbach region in southeast Austria. Rainfall has been measured by tipping bucket gauges at 150 stations of the network since the beginning of 2007. Since rain gauge measurements are considered close to true rainfall, there are increasing needs for WegenerNet data for the validation of rainfall data products such as remote sensing based estimates or model outputs. Serving these needs, this paper aims at providing a clearer interpretation on WegenerNet rainfall data for users in hydro-meteorological communities. Five clusters - a cluster consists of one national weather station and its four closest WegenerNet stations - allowed us close comparison of datasets between the stations. Linear regression analysis and error estimation with statistical indices were conducted to quantitatively evaluate the WegenerNet daily rainfall data. It was found that rainfall data between the stations show good linear relationships with an average correlation coefficient (r) of 0.97 , while WegenerNet sensors tend to underestimate rainfall according to the regression slope (0.87). For the five clusters investigated, the bias and relative bias were - 0.97 mm d-1 and - 11.5 % on average (except data from new sensors). The average of bias and relative bias, however, could be reduced by about 80 % through a simple linear regression-slope correction, with the assumption that the underestimation in WegenerNet data was caused by systematic errors. The results from the study have been employed to improve WegenerNet data for user applications so that a new version of the data (v5) is now available at the WegenerNet data portal (www.wegenernet.org).

  18. Topological quantization of ensemble averages

    International Nuclear Information System (INIS)

    Prodan, Emil

    2009-01-01

    We define the current of a quantum observable and, under well-defined conditions, we connect its ensemble average to the index of a Fredholm operator. The present work builds on a formalism developed by Kellendonk and Schulz-Baldes (2004 J. Funct. Anal. 209 388) to study the quantization of edge currents for continuous magnetic Schroedinger operators. The generalization given here may be a useful tool to scientists looking for novel manifestations of the topological quantization. As a new application, we show that the differential conductance of atomic wires is given by the index of a certain operator. We also comment on how the formalism can be used to probe the existence of edge states

  19. Flexible time domain averaging technique

    Science.gov (United States)

    Zhao, Ming; Lin, Jing; Lei, Yaguo; Wang, Xiufeng

    2013-09-01

    Time domain averaging(TDA) is essentially a comb filter, it cannot extract the specified harmonics which may be caused by some faults, such as gear eccentric. Meanwhile, TDA always suffers from period cutting error(PCE) to different extent. Several improved TDA methods have been proposed, however they cannot completely eliminate the waveform reconstruction error caused by PCE. In order to overcome the shortcomings of conventional methods, a flexible time domain averaging(FTDA) technique is established, which adapts to the analyzed signal through adjusting each harmonic of the comb filter. In this technique, the explicit form of FTDA is first constructed by frequency domain sampling. Subsequently, chirp Z-transform(CZT) is employed in the algorithm of FTDA, which can improve the calculating efficiency significantly. Since the signal is reconstructed in the continuous time domain, there is no PCE in the FTDA. To validate the effectiveness of FTDA in the signal de-noising, interpolation and harmonic reconstruction, a simulated multi-components periodic signal that corrupted by noise is processed by FTDA. The simulation results show that the FTDA is capable of recovering the periodic components from the background noise effectively. Moreover, it can improve the signal-to-noise ratio by 7.9 dB compared with conventional ones. Experiments are also carried out on gearbox test rigs with chipped tooth and eccentricity gear, respectively. It is shown that the FTDA can identify the direction and severity of the eccentricity gear, and further enhances the amplitudes of impulses by 35%. The proposed technique not only solves the problem of PCE, but also provides a useful tool for the fault symptom extraction of rotating machinery.

  20. Censored rainfall modelling for estimation of fine-scale extremes

    Science.gov (United States)

    Cross, David; Onof, Christian; Winter, Hugo; Bernardara, Pietro

    2018-01-01

    Reliable estimation of rainfall extremes is essential for drainage system design, flood mitigation, and risk quantification. However, traditional techniques lack physical realism and extrapolation can be highly uncertain. In this study, we improve the physical basis for short-duration extreme rainfall estimation by simulating the heavy portion of the rainfall record mechanistically using the Bartlett-Lewis rectangular pulse (BLRP) model. Mechanistic rainfall models have had a tendency to underestimate rainfall extremes at fine temporal scales. Despite this, the simple process representation of rectangular pulse models is appealing in the context of extreme rainfall estimation because it emulates the known phenomenology of rainfall generation. A censored approach to Bartlett-Lewis model calibration is proposed and performed for single-site rainfall from two gauges in the UK and Germany. Extreme rainfall estimation is performed for each gauge at the 5, 15, and 60 min resolutions, and considerations for censor selection discussed.

  1. Rainfall recharge estimation on a nation-wide scale using satellite information in New Zealand

    Science.gov (United States)

    Westerhoff, Rogier; White, Paul; Moore, Catherine

    2015-04-01

    Models of rainfall recharge to groundwater are challenged by the need to combine uncertain estimates of rainfall, evapotranspiration, terrain slope, and unsaturated zone parameters (e.g., soil drainage and hydraulic conductivity of the subsurface). Therefore, rainfall recharge is easiest to estimate on a local scale in well-drained plains, where it is known that rainfall directly recharges groundwater. In New Zealand, this simplified approach works in the policy framework of regional councils, who manage water allocation at the aquifer and sub-catchment scales. However, a consistent overview of rainfall recharge is difficult to obtain at catchment and national scale: in addition to data uncertainties, data formats are inconsistent between catchments; the density of ground observations, where these exist, differs across regions; each region typically uses different local models for estimating recharge components; and different methods and ground observations are used for calibration and validation of these models. The research described in this paper therefore presents a nation-wide approach to estimate rainfall recharge in New Zealand. The method used is a soil water balance approach, with input data from national rainfall and soil and geology databases. Satellite data (i.e., evapotranspiration, soil moisture, and terrain) aid in the improved calculation of rainfall recharge, especially in data-sparse areas. A first version of the model has been implemented on a 1 km x 1 km and monthly scale between 2000 and 2013. A further version will include a quantification of recharge estimate uncertainty: with both "top down" input error propagation methods and catchment-wide "bottom up" assessments of integrated uncertainty being adopted. Using one nation-wide methodology opens up new possibilities: it can, for example, help in more consistent estimation of water budgets, groundwater fluxes, or other hydrological parameters. Since recharge is estimated for the entire land

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

    Science.gov (United States)

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

    2014-01-01

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

  3. Satellite observations of rainfall effect on sea surface salinity in the waters adjacent to Taiwan

    Science.gov (United States)

    Ho, Chung-Ru; Hsu, Po-Chun; Lin, Chen-Chih; Huang, Shih-Jen

    2017-10-01

    Changes of oceanic salinity are highly related to the variations of evaporation and precipitation. To understand the influence of rainfall on the sea surface salinity (SSS) in the waters adjacent to Taiwan, satellite remote sensing data from the year of 2012 to 2014 are employed in this study. The daily rain rate data obtained from Special Sensor Microwave Imager (SSM/I), Tropical Rainfall Measuring Mission's Microwave Imager (TRMM/TMI), Advanced Microwave Scanning Radiometer (AMSR), and WindSat Polarimetric Radiometer. The SSS data was derived from the measurements of radiometer instruments onboard the Aquarius satellite. The results show the average values of SSS in east of Taiwan, east of Luzon and South China Sea are 33.83 psu, 34.05 psu, and 32.84 psu, respectively, in the condition of daily rain rate higher than 1 mm/hr. In contrast to the rainfall condition, the average values of SSS are 34.07 psu, 34.26 psu, and 33.09 psu in the three areas, respectively at no rain condition (rain rate less than 1 mm/hr). During the cases of heavy rainfall caused by spiral rain bands of typhoon, the SSS is diluted with an average value of -0.78 psu when the average rain rate is higher than 4 mm/hr. However, the SSS was increased after temporarily decreased during the typhoon cases. A possible reason to explain this phenomenon is that the heavy rainfall caused by the spiral rain bands of typhoon may dilute the sea surface water, but the strong winds can uplift the higher salinity of subsurface water to the sea surface.

  4. A Stochastic Fractional Dynamics Model of Rainfall Statistics

    Science.gov (United States)

    Kundu, Prasun; Travis, James

    2013-04-01

    Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is designed to faithfully reflect the scale dependence and is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. The main restriction is the assumption that the statistics of the precipitation field is spatially homogeneous and isotropic and stationary in time. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of the radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment. Some data sets containing periods of non-stationary behavior that involves occasional anomalously correlated rain events, present a challenge for the model.

  5. Spatio-temporal modelling of rainfall in the Murray-Darling Basin

    Science.gov (United States)

    Nowak, Gen; Welsh, A. H.; O'Neill, T. J.; Feng, Lingbing

    2018-02-01

    The Murray-Darling Basin (MDB) is a large geographical region in southeastern Australia that contains many rivers and creeks, including Australia's three longest rivers, the Murray, the Murrumbidgee and the Darling. Understanding rainfall patterns in the MDB is very important due to the significant impact major events such as droughts and floods have on agricultural and resource productivity. We propose a model for modelling a set of monthly rainfall data obtained from stations in the MDB and for producing predictions in both the spatial and temporal dimensions. The model is a hierarchical spatio-temporal model fitted to geographical data that utilises both deterministic and data-derived components. Specifically, rainfall data at a given location are modelled as a linear combination of these deterministic and data-derived components. A key advantage of the model is that it is fitted in a step-by-step fashion, enabling appropriate empirical choices to be made at each step.

  6. Erosivity factor in the Universal Soil Loss Equation estimated from Finnish rainfall data

    Directory of Open Access Journals (Sweden)

    Maximilian Posch

    1993-07-01

    Full Text Available Continuous rainfall data recorded for many years at 8 stations in Finland were used to estimate rainfall erosivity, a quantity needed for soil loss predictions with the Universal Soil Loss Equation (USLE. The obtained erosivity values were then used to determine the 2 parameters of a power-law function describing the relationship between daily precipitation and erosivity. This function is of importance in erosion modeling at locations where no breakpoint rainfall data are available. The parameters of the power-law were estimated both by linear regression of the log-transformed data and by non-linear least-square fitting of the original data. Results indicate a considerable seasonal (monthly variation of the erosivity, whereas the spatial variation over Finland is rather small.

  7. Empirical rainfall thresholds for the triggering of landslides in Asturias (NW Spain)

    Science.gov (United States)

    Valenzuela, Pablo; Luís Zêzere, José; José Domínguez-Cuesta, María; Mora García, Manuel Antonio

    2017-04-01

    Rainfall-triggered landslides are common and widespread phenomena in Asturias, a mountainous region in the NW of Spain where the climate is characterized by average annual precipitation and temperature values of 960 mm and 13.3°C respectively. Different types of landslides (slides, flows and rockfalls) frequently occur during intense rainfall events, causing every year great economic losses and sometimes human injuries or fatalities. For this reason, its temporal forecast is of great interest. The main goal of the present research is the calculation of empirical rainfall thresholds for the triggering of landslides in the Asturian region, following the methodology described by Zêzere et al., 2015. For this purpose, data from 559 individual landslides collected from press archives during a period of eight hydrological years (October 2008-September 2016) and gathered within the BAPA landslide database (http://geol.uniovi.es/BAPA) were used. Precipitation data series of 37 years came from 6 weather stations representative of the main geographical and climatic conditions within the study area. Applied methodology includes: (i) the definition of landslide events, (ii) the reconstruction of the cumulative antecedent rainfall for each event from 1 to 90 consecutive days, (iii) the estimation of the return period for each cumulated rainfall-duration condition using Gumbel probability distribution, (iv) the definition of the critical cumulated rainfall-duration conditions taking into account the highest return period, (v) the calculation of the thresholds considering both the conditions for the occurrence and non-occurrence of landslides. References: Zêzere, J.L., Vaz, T., Pereira, S., Oliveira, S.C., Marqués, R., García, R.A.C. 2015. Rainfall thresholds for landslide activity in Portugal: a state of the art. Environmental Earth Sciences, 73, 2917-2936. doi: 10.1007/s12665-014-3672-0

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

    Science.gov (United States)

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

    2011-01-01

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

  9. Relationships between southeastern Australian rainfall and sea surface temperatures examined using a climate model

    Science.gov (United States)

    Watterson, I. G.

    2010-05-01

    Rainfall in southeastern Australia has declined in recent years, particularly during austral autumn over the state of Victoria. A recent study suggests that sea surface temperature (SST) variations in both the Indonesian Throughflow (ITF) region and in a meridional dipole in the central Indian Ocean have influenced Victorian late autumn rainfall since 1950. However, it remains unclear to what extent SSTs in these and other regions force such a teleconnection. Analysis of a 1080 year simulation by the climate model CSIRO Mk3.5 shows that the model Victorian rainfall is correlated rather realistically with SSTs but that part of the above relationships is due to the model ENSO. Furthermore, the remote patterns of pressure, rainfall, and land temperature greatly diminish when the data are lagged by 1 month, suggesting that the true forcing by the persisting SSTs is weak. In a series of simulations of the atmospheric Mk3.5 with idealized SST anomalies, raised SSTs to the east of Indonesia lower the simulated Australian rainfall, while those to the west raise it. A positive ITF anomaly lowers pressure over Australia, but with little effect on Victorian rainfall. The meridional dipole and SSTs to the west and southeast of Australia have little direct effect on southeastern Australia in the model. The results suggest that tropical SSTs predominate as an influence on Victorian rainfall. However, the SST indices appear to explain only a fraction of the observed trend, which in the case of decadal means remains within the range of unforced variability simulated by Mk3.5.

  10. Regionalization of the Modified Bartlett-Lewis Rectangular Pulse Stochastic Rainfall Model

    Directory of Open Access Journals (Sweden)

    Dongkyun Kim

    2013-01-01

    Full Text Available Parameters of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP stochastic rainfall simulation model were regionalized across the contiguous United States. Three thousand four hundred forty-four National Climate Data Center (NCDC rain gauges were used to obtain spatial and seasonal patterns of the model parameters. The MBLRP model was calibrated to minimize the discrepancy between the precipitation depth statistics between the observed and MBLRP-generated precipitation time series. These statistics included the mean, variance, probability of zero rainfall and autocorrelation at 1-, 3-, 12- and 24-hour accumulation intervals. The Ordinary Kriging interpolation technique was used to generate maps of the six MBLRP model parameters for each of the 12 months of the year. All parameters had clear to discernible regional tendencies; except for one related to rain cell duration distribution. Parameter seasonality was not obvious and it was more apparent in some locations than in others, depending on the seasonality of the rainfall statistics. Cross-validation was used to assess the validity of the parameter maps. The results indicate that the suggested maps reproduce well the observed rainfall statistics for different accumulation intervals, except for the lag-1 autocorrelation coefficient. The boundaries of the expected residual, with 95% confidence, between the observed rainfall statistics and the simulated rainfall statistics based on the map parameters were approximately ±0.064 mm hr-1, ±1.63 mm2 hr-2, ±0.16, and ±0.030 for the mean, variance, lag-1 autocorrelation and probability of zero rainfall at hourly accumulation levels, respectively. The estimated parameter values were also used to estimate the storm and rain cell characteristics.

  11. Spatiotemporal trends in extreme rainfall and temperature indices over Upper Tapi Basin, India

    Science.gov (United States)

    Sharma, Priyank J.; Loliyana, V. D.; S. R., Resmi; Timbadiya, P. V.; Patel, P. L.

    2017-12-01

    The flood risk across the globe is intensified due to global warming and subsequent increase in extreme temperature and precipitation. The long-term trends in extreme rainfall (1944-2013) and temperature (1969-2012) indices have been investigated at annual, seasonal, and monthly time scales using nonparametric Mann-Kendall (MK), modified Mann-Kendall (MMK), and Sen's slope estimator tests. The extreme rainfall and temperature indices, recommended by the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI), have been analyzed at finer spatial scales for trend detection. The results of trend analyses indicate decreasing trend in annual total rainfall, significant decreasing trend in rainy days, and increasing trend in rainfall intensity over the basin. The seasonal rainfall has been found to decrease for all the seasons except postmonsoon, which could affect the rain-fed agriculture in the basin. The 1- and 5-day annual maximum rainfalls exhibit mixed trends, wherein part of the basin experiences increasing trend, while other parts experience a decreasing trend. The increase in dry spells and concurrent decrease in wet spells are also observed over the basin. The extreme temperature indices revealed increasing trends in hottest and coldest days, while decreasing trends in coldest night are found over most parts of the basin. Further, the diurnal temperature range is also found to increase due to warming tendency in maximum temperature (T max) at a faster rate compared to the minimum temperature (T min). The increase in frequency and magnitude of extreme rainfall in the basin has been attributed to the increasing trend in maximum and minimum temperatures, reducing forest cover, rapid pace of urbanization, increase in human population, and thereby increase in the aerosol content in the atmosphere. The findings of the present study would significantly help in sustainable water resource planning, better decision-making for policy framework, and setting up

  12. Influence of declining mean annual rainfall on the behavior and yield of sediment and particulate organic carbon from tropical watersheds

    Science.gov (United States)

    Strauch, Ayron M.; MacKenzie, Richard A.; Giardina, Christian P.; Bruland, Gregory L.

    2018-04-01

    The capacity to forecast climate and land-use driven changes to runoff, soil erosion and sediment transport in the tropics is hindered by a lack of long-term data sets and model study systems. To address these issues we utilized three watersheds characterized by similar shape, geology, soils, vegetation cover, and land use arranged across a 900 mm gradient in mean annual rainfall (MAR). Using this space-for-time design, we quantified suspended sediment (SS) and particulate organic carbon (POC) export over 18 months to examine how large-scale climate trends (MAR) affect sediment supply and delivery patterns (hysteresis) in tropical watersheds. Average daily SS yield ranged from 0.128 to 0.618 t km- 2 while average daily POC ranged from 0.002 to 0.018 t km- 2. For the largest storm events, we found that sediment delivery exhibited similar clockwise hysteresis patterns among the watersheds, with no significant differences in the similarity function between watershed pairs, indicating that: (1) in-stream and near-stream sediment sources drive sediment flux; and (2) the shape and timing of hysteresis is not affected by MAR. With declining MAR, the ratio of runoff to baseflow and inter-storm length between pulse events both increased. Despite increases in daily rainfall and the number of days with large rainfall events increasing with MAR, there was a decline in daily SS yield possibly due to the exhaustion of sediment supply by frequent runoff events in high MAR watersheds. By contrast, mean daily POC yield increased with increasing MAR, possibly as a result of increased soil organic matter decomposition, greater biomass, or increased carbon availability in higher MAR watersheds. We compared results to modeled values using the Load Estimator (LOADEST) FORTRAN model, confirming the negative relationship between MAR and sediment yield. However, because of its dependency on mean daily flow, LOADEST tended to under predict sediment yield, a result of its poor ability to

  13. Rainfall runoff and erosion in Napa Valley vineyards: effects of slope, cover and surface roughness

    Science.gov (United States)

    Battany, M. C.; Grismer, M. E.

    2000-05-01

    The effects of slope, cover and surface roughness on rainfall runoff, infiltration and erosion were determined at two sites on a hillside vineyard in Napa County, California, using a portable rainfall simulator. Rainfall simulation experiments were carried out at two sites, with five replications of three slope treatments (5%, 10% and 15%) in a randomized block design at each site (0%bsol;64 m2 plots). Prior to initiation of the rainfall simulations, detailed assessments, not considered in previous vineyard studies, of soil slope, cover and surface roughness were conducted. Significant correlations (at the 95% confidence level) between the physical characteristics of slope, cover and surface roughness, with total infiltration, runoff, sediment discharge and average sediment concentration were obtained. The extent of soil cracking, a physical characteristic not directly measured, also affected analysis of the rainfall-runoff-erosion process. Average cumulative runoff and cumulative sediment discharge from site A was 87% and 242