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Sample records for 10-year-recurrence 1-hour-duration rainfall

  1. Probability and volume of potential postwildfire debris flows in the 2011 Wallow burn area, eastern Arizona

    USGS Publications Warehouse

    Ruddy, Barbara C.

    2011-01-01

    This report presents a preliminary emergency assessment of the debris-flow hazards from drainage basins burned in 2011 by the Wallow wildfire in eastern Arizona. Empirical models derived from statistical evaluation of data collected from recently burned drainage basins throughout the intermountain western United States were used to estimate the probability of debris-flow occurrence and debris-flow volumes for selected drainage basins. Input for the models include measures of burn severity, topographic characteristics, soil properties, and rainfall total and intensity for a (1) 10-year-recurrence, 1-hour-duration rainfall and (2) 25-year-recurrence, 1-hour-duration rainfall. Estimated debris-flow probabilities in the drainage basins of interest ranged from less than 1 percent in response to both the 10-year-recurrence, 1-hour-duration rainfall and the 25-year-recurrence, 1-hour-duration rainfall to a high of 41 percent in response to the 25-year-recurrence, 1-hour-duration rainfall. The low probabilities in all modeled drainage basins are likely due to extensive low-gradient hillslopes, burned at low severities, and large drainage-basin areas (greater than 25 square kilometers). Estimated debris-flow volumes ranged from a low of 24 cubic meters to a high of greater than 100,000 cubic meters, indicating a considerable hazard should debris flows occur

  2. Probability and volume of potential postwildfire debris flows in the 2011 Indian Gulch burn area, near Golden, Colorado

    USGS Publications Warehouse

    Ruddy, Barbara C.

    2011-01-01

    This report presents an assessment of the debris-flow hazards from drainage basins burned in 2011 by the Indian Gulch wildfire near Golden, Colorado. Empirical models derived from statistical evaluation of data collected from recently burned drainage basins throughout the intermountain western United States were used to estimate the probability of debris-flow occurrence and debris-flow volumes for selected drainage basins. Input for the models include measures of burn severity, topographic characteristics, soil properties, and rainfall total and intensity for a (1) 2-year-recurrence, 1-hour-duration rainfall, (2) 10-year-recurrence, 1-hour-duration rainfall, and (3) 25-year-recurrence, 1-hour-duration rainfall. Estimated debris-flow probabilities in the drainage basins of interest ranged from 2 percent in response to the 2-year-recurrence, 1-hour-duration rainfall to a high of 76 percent in response to the 25-year-recurrence, 1-hour-duration rainfall. Estimated debris-flow volumes ranged from a low of 840 cubic meters to a high of 26,000 cubic meters, indicating a considerable hazard should debris flows occur.

  3. Probability and volume of potential postwildfire debris flows in the 2012 High Park Burn Area near Fort Collins, Colorado

    USGS Publications Warehouse

    Verdin, Kristine L.; Dupree, Jean A.; Elliott, John G.

    2012-01-01

    This report presents a preliminary emergency assessment of the debris-flow hazards from drainage basins burned by the 2012 High Park fire near Fort Collins in Larimer County, Colorado. Empirical models derived from statistical evaluation of data collected from recently burned basins throughout the intermountain western United States were used to estimate the probability of debris-flow occurrence and volume of debris flows along the burned area drainage network and to estimate the same for 44 selected drainage basins along State Highway 14 and the perimeter of the burned area. Input data for the models included topographic parameters, soil characteristics, burn severity, and rainfall totals and intensities for a (1) 2-year-recurrence, 1-hour-duration rainfall (25 millimeters); (2) 10-year-recurrence, 1-hour-duration rainfall (43 millimeters); and (3) 25-year-recurrence, 1-hour-duration rainfall (51 millimeters). Estimated debris-flow probabilities along the drainage network and throughout the drainage basins of interest ranged from 1 to 84 percent in response to the 2-year-recurrence, 1-hour-duration rainfall; from 2 to 95 percent in response to the 10-year-recurrence, 1-hour-duration rainfall; and from 3 to 97 in response to the 25-year-recurrence, 1-hour-duration rainfall. Basins and drainage networks with the highest probabilities tended to be those on the eastern edge of the burn area where soils have relatively high clay contents and gradients are steep. Estimated debris-flow volumes range from a low of 1,600 cubic meters to a high of greater than 100,000 cubic meters. Estimated debris-flow volumes increase with basin size and distance along the drainage network, but some smaller drainages were also predicted to produce substantial volumes of material. The predicted probabilities and some of the volumes predicted for the modeled storms indicate a potential for substantial debris-flow impacts on structures, roads, bridges, and culverts located both within and

  4. Influence of rainfall microstructure on rainfall interception

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    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 process is influenced by various meteorological and vegetation parameters. Often neglected meteorological parameter influencing rainfall interception is also rainfall microstructure. Rain is a discrete process consisting of various numbers of individual raindrops with different sizes and velocities. This properties describe rainfall microstructure which is often neglected in hydrological analysis and replaced with rainfall intensity. Throughfall, stemflow and rainfall microstructure have been measured since the beginning of the year 2014 under two tree species (Betula pendula and Pinus nigra) on a study plot in Ljubljana, Slovenia. The preliminary analysis of the influence of rainfall microstructure on rainfall interception has been conducted using three events with different characteristics measured in May 2014. Event A is quite short with low rainfall amount and moderate rainfall intensity, whereas events B and C have similar length but low and high intensities, respectively. Event A was observed on the 1st of May 2014. It was 22 minutes long and delivered 1.2 mm of rainfall. The average rainfall intensity was equal to 3.27 mm/h. The event consisted of 1,350 rain drops with average diameter of 1.517 mm and average velocity of 5.110 m/s. Both Betula pendula and Pinus nigra intercepted similar amount of rainfall, 68 % and 69 %, respectively. Event B was observed in the night from the 7th to 8th of May 2014, it was 16 hours and 18 minutes long, and delivered 4.2 mm of rainfall with average intensity of 0.97 mm/h. There were 39,108 raindrops detected with average diameter of 0.858 mm and average velocity of 3.855 m/s. Betula pendula

  5. Rainfall simulation in education

    NASA Astrophysics Data System (ADS)

    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

  6. Critical rainfall thresholds for debris-flows occurrence and climate changes in the Dolomitic area of Cortina d'Ampezzo (North-Eastern Italian Alps)

    NASA Astrophysics Data System (ADS)

    Floris, M.; D'Alpaos, A.; Tecca, P. R.; Squarzoni, C.; Genevois, R.; Marani, M.

    2009-04-01

    The mountainous area of Cortina d'Ampezzo (Dolomites, Eastern Italian Alps) is prone to debris-flow release in response to summer high intensity-short duration rainfalls. As this area has a great touristic economic value to maintain and is densely populated, it is of the utmost importance to prevent possible property damage and casualties associated to debris flows. According to previous research for predicting debris-flow occurrence, critical rainfall threshold is a crucial triggering factor. Many studies have been carried out to establish such thresholds, based on different approaches. In this note we analyze rainfall data recorded during the period 2000-2005 in the debris-flow monitoring system of Acquabona (Cortina d'Ampezzo) (Tecca et al., 2003), to evaluate the critical rainfall threshold in the study area, expressed in terms of cumulated rainfall and rainfall intensity. Preliminary results show that the triggering threshold seems to be unaffected by long-term antecedent precipitation. All the flows were triggered by rainfalls of less than 1 hour duration, with peak rainfall intensities ranging from 4.8 to 14.7 mm / 10 min. Furthermore it has been observed that the initial debris surges were associated with peak rainfall intensities measured over 10 minutes. Seventy rainfall events, triggering and not-triggering debris flow, have been analyzed in terms of cumulated rainfall, duration, average intensity, maximum hourly intensity, maximum intensity over 10 minutes. Based on the results, using the aforementioned terms, we found that debris-flow triggering rainfalls are clearly discriminated from the not-triggering rainfall when considering the maximum intensity rainfall over 10 minutes. In a peak over threshold framework applied to the rainfall data measured at the Faloria rain gauge station from 1990 to 2006, the probability of occurrence of the determined rainfall threshold for different time intervals has been computed. The exceedance of the precipitation

  7. Tropical Rainfall Measuring Mission

    NASA Technical Reports Server (NTRS)

    1999-01-01

    Tropical rainfall affects the lives and economics of a majority of the Earth's population. Tropical rain systems, such as hurricanes, typhoons, and monsoons, are crucial to sustaining the livelihoods of those living in the tropics. Excess rainfall can cause floods and great property and crop damage, whereas too little rainfall can cause drought and crop failure. The latent heat release during the process of precipitation is a major source of energy that drives the atmospheric circulation. This latent heat can intensify weather systems, affecting weather thousands of kilometers away, thus making tropical rainfall an important indicator of atmospheric circulation and short-term climate change. Tropical forests and the underlying soils are major sources of many of the atmosphere's trace constituents. Together, the forests and the atmosphere act as a water-energy regulating system. Most of the rainfall is returned to the atmosphere through evaporation and transpiration, and the atmospheric trace constituents take part in the recycling process. Hence, the hydrological cycle provides a direct link between tropical rainfall and the global cycles of carbon, nitrogen, and sulfur, all important trace materials for the Earth's system. Because rainfall is such an important component in the interactions between the ocean, atmosphere, land, and the biosphere, accurate measurements of rainfall are crucial to understanding the workings of the Earth-atmosphere system. The large spatial and temporal variability of rainfall systems, however, poses a major challenge to estimating global rainfall. So far, there has been a lack of rain gauge networks, especially over the oceans, which points to satellite measurement as the only means by which global observation of rainfall can be made. The Tropical Rainfall Measuring Mission (TRMM), jointly sponsored by the National Aeronautics and Space Administration (NASA) of the United States and the National Space Development Agency (NASDA) of

  8. Palaeoclimate: Aerosols and rainfall

    NASA Astrophysics Data System (ADS)

    Partin, Jud

    2015-03-01

    Instrumental records have hinted that aerosol emissions may be shifting rainfall over Central America southwards. A 450-year-long precipitation reconstruction indicates that this shift began shortly after the Industrial Revolution.

  9. Rainfall erosivity in Europe.

    PubMed

    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

  10. Tropical Storm Faxai's Rainfall Rates

    NASA Video Gallery

    This animation shows Tropical Storm Faxai's rainfall rates on March 2 from a TRMM TMI/PR rainfall analysis being faded in over infrared cloud data from the TRMM VIRS instrument. Credit: SSAI/NASA, ...

  11. Use of Historical Radar Rainfall Estimates to Develop Design Storms in Los Angeles.

    NASA Astrophysics Data System (ADS)

    Curtis, D. C.; Humphrey, J.; Moffitt, J.

    2007-12-01

    developed for 6X (6 events per year), 4X, 3X, 2X, 1, 2, 5 and 10 year recurrence, and durations from 5 minutes to 7-days. A comparison is made between DARF derived in these analyses with NOAA Atlas 12 DARF, the USACE Sierra Madre Storm and other DARF developed for the interior Southwest. Orographic increases in DDF are related to the Los Angeles County Flood Control District Hydrology Manual 24-hr 50-yr Precipitation maps, elevation from USGS topographic maps and Mean Annual Precipitation maps.

  12. Stochastic modeling of rainfall

    SciTech Connect

    Guttorp, P.

    1996-12-31

    We review several approaches in the literature for stochastic modeling of rainfall, and discuss some of their advantages and disadvantages. While stochastic precipitation models have been around at least since the 1850`s, the last two decades have seen an increased development of models based (more or less) on the physical processes involved in precipitation. There are interesting questions of scale and measurement that pertain to these modeling efforts. Recent modeling efforts aim at including meteorological variables, and may be useful for regional down-scaling of general circulation models.

  13. Rainfall statistics changes in Sicily

    NASA Astrophysics Data System (ADS)

    Arnone, E.; Pumo, D.; Viola, F.; Noto, L. V.; La Loggia, G.

    2013-02-01

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

  14. Rainfall statistics changes in Sicily

    NASA Astrophysics Data System (ADS)

    Arnone, E.; Pumo, D.; Viola, F.; Noto, L. V.; La Loggia, G.

    2013-07-01

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

  15. Prediction of spatially explicit rainfall intensity-duration thresholds for post-fire debris-flow generation in the western United States

    NASA Astrophysics Data System (ADS)

    Staley, Dennis; Negri, Jacquelyn; Kean, Jason

    2016-04-01

    Population expansion into fire-prone steeplands has resulted in an increase in post-fire debris-flow risk in the western United States. Logistic regression methods for determining debris-flow likelihood and the calculation of empirical rainfall intensity-duration thresholds for debris-flow initiation represent two common approaches for characterizing hazard and reducing risk. Logistic regression models are currently being used to rapidly assess debris-flow hazard in response to design storms of known intensities (e.g. a 10-year recurrence interval rainstorm). Empirical rainfall intensity-duration thresholds comprise a major component of the United States Geological Survey (USGS) and the National Weather Service (NWS) debris-flow early warning system at a regional scale in southern California. However, these two modeling approaches remain independent, with each approach having limitations that do not allow for synergistic local-scale (e.g. drainage-basin scale) characterization of debris-flow hazard during intense rainfall. The current logistic regression equations consider rainfall a unique independent variable, which prevents the direct calculation of the relation between rainfall intensity and debris-flow likelihood. Regional (e.g. mountain range or physiographic province scale) rainfall intensity-duration thresholds fail to provide insight into the basin-scale variability of post-fire debris-flow hazard and require an extensive database of historical debris-flow occurrence and rainfall characteristics. Here, we present a new approach that combines traditional logistic regression and intensity-duration threshold methodologies. This method allows for local characterization of both the likelihood that a debris-flow will occur at a given rainfall intensity, the direct calculation of the rainfall rates that will result in a given likelihood, and the ability to calculate spatially explicit rainfall intensity-duration thresholds for debris-flow generation in recently

  16. Mechanisms of Malaysian Rainfall Anomalies.

    NASA Astrophysics Data System (ADS)

    Tangang, Fredolin T.; Juneng, Liew

    2004-09-01

    The behavior of the Malaysian anomalous rainfall is examined in relation to the El Niño Southern Oscillation (ENSO) and local air sea influences. The behavior is consistent with the northward migration of the ENSO-related coherence in the Maritime Continent rainfall. During the June July August (JJA) period, the ENSO-related coherence is low in the Malaysian rainfall but higher in the Indonesian rainfall. During the September October November (SON) period, the behavior of Malaysian anomalous rainfall is similar to that of the Indonesian rainfall since the ENSO-related coherence progresses northward to include the Malaysian region. It is proposed that a mechanism that operates during this period is similar to that in Indonesia, where local anomalous sea surface temperatures (SSTs) act to strengthen the remote influence of anomalous SST associated with ENSO in the eastern central Pacific. However, during the December January February (DJF) period, the behavior is markedly different from that of the Indonesian rainfall. During this period, the ENSO-related coherence has shifted northward across the equator. This shift results in the strengthening of ENSO Malaysia rainfall relationship and the weakening of ENSO Indonesia rainfall relationship. It is proposed that a different mechanism in which the anomalous cyclonic circulation over the South China Sea, northern Borneo, and the Philippine Sea is directly responsible for modulating the anomalous Malaysian rainfall during the DJF period. Finally, it is postulated that the anomalous cyclonic circulation is a response to the SST dipole associated with the strengthening of the northern arm of the boomerang-shaped SST in the northwestern Pacific Ocean.


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

    NASA Astrophysics Data System (ADS)

    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

  18. TRMM Satellite Shows Heavy Rainfall in Cristina

    NASA Video Gallery

    NASA's TRMM satellite rainfall data was overlaid on an enhanced visible/infrared image from NOAA's GOES-East satellite showing cloud and rainfall extent. Green areas indicate rainfall at over 20 mm...

  19. Probability and volume of potential postwildfire debris flows in the 2012 Waldo Canyon Burn Area near Colorado Springs, Colorado

    USGS Publications Warehouse

    Verdin, Kristine L.; Dupree, Jean A.; Elliott, John G.

    2012-01-01

    This report presents a preliminary emergency assessment of the debris-flow hazards from drainage basins burned by the 2012 Waldo Canyon fire near Colorado Springs in El Paso County, Colorado. Empirical models derived from statistical evaluation of data collected from recently burned basins throughout the intermountain western United States were used to estimate the probability of debris-flow occurrence and potential volume of debris flows along the drainage network of the burned area and to estimate the same for 22 selected drainage basins along U.S. Highway 24 and the perimeter of the burned area. Input data for the models included topographic parameters, soil characteristics, burn severity, and rainfall totals and intensities for a (1) 2-year-recurrence, 1-hour-duration rainfall, referred to as a 2-year storm (29 millimeters); (2) 10-year-recurrence, 1-hour-duration rainfall, referred to as a 10-year storm (42 millimeters); and (3) 25-year-recurrence, 1-hour-duration rainfall, referred to as a 25-year storm (48 millimeters). Estimated debris-flow probabilities at the pour points of the the drainage basins of interest ranged from less than 1 to 54 percent in response to the 2-year storm; from less than 1 to 74 percent in response to the 10-year storm; and from less than 1 to 82 percent in response to the 25-year storm. Basins and drainage networks with the highest probabilities tended to be those on the southern and southeastern edge of the burn area where soils have relatively high clay contents and gradients are steep. Nine of the 22 drainage basins of interest have greater than a 40-percent probability of producing a debris flow in response to the 10-year storm. Estimated debris-flow volumes for all rainfalls modeled range from a low of 1,500 cubic meters to a high of greater than 100,000 cubic meters. Estimated debris-flow volumes increase with basin size and distance along the drainage network, but some smaller drainages were also predicted to produce

  20. TRMM Sees Chantal's Rainfall Rates

    NASA Video Gallery

    On July 8, NASA's TRMM satellite saw Tropical Storm Chantal's heaviest rainfall happening at a rate of over 115.5 mm/hr. (~4.5 inches) near Chantal's center where thunderstorms reached heights of o...

  1. Fuzzy conceptual rainfall runoff models

    NASA Astrophysics Data System (ADS)

    Özelkan, Ertunga C.; Duckstein, Lucien

    2001-11-01

    A fuzzy conceptual rainfall-runoff (CRR) framework is proposed herein to deal with those parameter uncertainties of conceptual rainfall-runoff models, that are related to data and/or model structure: with every element of the rainfall-runoff model assumed to be possibly uncertain, taken here as being fuzzy. First, the conceptual rainfall-runoff system is fuzzified and then different operational modes are formulated using fuzzy rules; second, the parameter identification aspect is examined using fuzzy regression techniques. In particular, bi-objective and tri-objective fuzzy regression models are applied in the case of linear conceptual rainfall-runoff models so that the decision maker may be able to trade off prediction vagueness (uncertainty) and the embedding outliers. For the non-linear models, a fuzzy least squares regression framework is applied to derive the model parameters. The methodology is illustrated using: (1) a linear conceptual rainfall-runoff model; (2) an experimental two-parameter model; and (3) a simplified version of the Sacramento soil moisture accounting model of the US National Weather Services river forecast system (SAC-SMA) known as the six-parameter model. It is shown that the fuzzy logic framework enables the decision maker to gain insight about the model sensitivity and the uncertainty stemming from the elements of the CRR model.

  2. Predictability of Zimbabwe summer rainfall

    NASA Astrophysics Data System (ADS)

    Makarau, Amos; Jury, Mark R.

    1997-11-01

    Predictors of Zimbabwe summer rainfall are investigated with a view to improved long-range forecasts. Teleconnectivity is assessed in respect of sea-surface temperatures, the Southern Oscillation index, the Quasi-biennial Oscillation (QBO), outgoing longwave radiation (OLR) and wind. Spectral analyses of historical rainfall gives an indication of cycles in the range 2.3, 18 and 3.8 years, possibly associated with the QBO, the luni-solar tide and the El No-Southern Oscillation (ENSO), respectively. Pair-wise correlations are found between Zimbabwe summer rainfall and SST in the central Indian Ocean (r<-0.5) in austral spring. Below normal OLR values in September over southern Africa corresponds with good rains in the following summer. Rainfall-upper-wind correlations are optimum (r<-0.7) over the equatorial Atlantic in spring. Comparatively weak correlation with the QBO may also reflect biennial adjustment of monsoon and global ENSO teleconnections. Additional predictor variables are utilized and multivariate models are formulated for early and late summer rainfall and maize yield in Zimbabwe. The models use three to five predictors, are trained over a 22-year period and perform well in jack-knife skill tests. Summer rainfall forecasts with one season lead times are viable and could ameliorate hardship caused by drought.

  3. Rainfall variability modelling in Rwanda

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  4. Real-time estimation of rainfall fields using radar rainfall and rain gage data

    NASA Astrophysics Data System (ADS)

    Seo, D.-J.

    1998-07-01

    New attempts at real-time estimation of rainfall fields using rain gage and radar rainfall data are reported. Based on multiplicative decomposition of expectation of rainfall into conditional expectation of rainfall given raining and probability of rainfall, the estimation procedures explicitly account for both within-storm variability of rainfall and variability due to fractional coverage of rainfall. As a result, in addition to the accuracy of radar rainfall data in estimating rainfall given that rainfall is successfully detected, that in discerning rainfall from no rainfall can also be taken into account. To evaluate the estimation procedures, cross validation was performed using hourly radar rainfall data from the Tulsa, Oklahoma, Weather Surveillance Radar-1988 Doppler version (WSR-88D) and hourly rain gage data under the radar umbrella.

  5. Gridded radar rainfall product for comparison with model rainfall

    NASA Astrophysics Data System (ADS)

    Jyothi, K. Amar; Devajyoti, D.; Kumar, D. Preveen; Rajagopal, E. N.; Rao, T. Narayana

    2016-05-01

    A tool for the entire Indian weather radar network using the static composite QI (Quality Index) map is generated. Various customized modules are used for this generation of the radar mosaic. The characterization of quality of DWR (Doppler weather Radar) data in terms of their QI is essential for assimilating the data into NWP (Numerical Weather Prediction) models. The static QI maps give a quick overview about the inherent errors in the DWR data. Quality control algorithms are applied for the generation of composite QI. The near real time access to the DWR data at NCMRWF enables the generation of an accumulated gridded radar rainfall product. This gridded rainfall map is useful for generating products like high resolution rainfall product, QPE (quantitative precipitation estimate) and for other applications. Results of some case studies shall be presented.

  6. Rainfall-Runoff Parameters Uncertainity

    NASA Astrophysics Data System (ADS)

    Heidari, A.; Saghafian, B.; Maknoon, R.

    2003-04-01

    Karkheh river basin, located in southwest of Iran, drains an area of over 40000 km2 and is considered a flood active basin. A flood forecasting system is under development for the basin, which consists of a rainfall-runoff model, a river routing model, a reservior simulation model, and a real time data gathering and processing module. SCS, Clark synthetic unit hydrograph, and Modclark methods are the main subbasin rainfall-runoff transformation options included in the rainfall-runoff model. Infiltration schemes, such as exponentioal and SCS-CN methods, account for infiltration losses. Simulation of snow melt is based on degree day approach. River flood routing is performed by FLDWAV model based on one-dimensional full dynamic equation. Calibration and validation of the rainfall-runoff model on Karkheh subbasins are ongoing while the river routing model awaits cross section surveys.Real time hydrometeological data are collected by a telemetry network. The telemetry network is equipped with automatic sensors and INMARSAT-C comunication system. A geographic information system (GIS) stores and manages the spatial data while a database holds the hydroclimatological historical and updated time series. Rainfall runoff parameters uncertainty is analyzed by Monte Carlo and GLUE approaches.

  7. Extreme Rainfall In A City

    NASA Astrophysics Data System (ADS)

    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

  8. SUB-PIXEL RAINFALL VARIABILITY AND THE IMPLICATIONS FOR UNCERTAINTIES IN RADAR RAINFALL ESTIMATES

    EPA Science Inventory

    Radar estimates of rainfall are subject to significant measurement uncertainty. Typically, uncertainties are measured by the discrepancies between real rainfall estimates based on radar reflectivity and point rainfall records of rain gauges. This study investigates how the disc...

  9. Chapman Conference on Rainfall Fields

    NASA Astrophysics Data System (ADS)

    Gupta, V. K.

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

  10. Commercial application of rainfall simulation

    NASA Astrophysics Data System (ADS)

    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

  11. The Rainfall and Rainfall Kinetic Energy Intensity-Duration of Landslides and Debris flow in Taiwan

    NASA Astrophysics Data System (ADS)

    Chang, Jui-Ming; Chen, Hongey

    2016-04-01

    This research used Joss-Waldvogel Disdrometers (JWD) which set in Shiment catchment, Northern Taiwan and Chishan catchment, Southern Taiwan to record rainfall kinetic energy data, to find the relationship between rainfall kinetic energy and rainfall intensity in these two areas. The distance between the two areas is less than 150 km. These data help the researchers and showed that the equations of relationship were ekN =28.7* (1-0.7027*exp(-0.0395*I)) and ekS=27.4*(1-0.5954*exp(-0.0345*I)). Generally, rainfall kinetic energy in Northern Taiwan is higher than in Southern Taiwan during rainfall period. Also, the occurring time and rainfall records of 143 landslide events from 2006 to 2012 were analyzed. The rainfall-intensity (I-D) relationship could be used to build rainfall threshold which were IN=15.13 D‑0.28 and IS=47.58 D‑0.35. In brief, the rainfall feature in landslide of Northern Taiwan had low rainfall intensity, long rainfall duration and low average accumulative rainfall. By combining rainfall kinetic energy and rainfall threshold, rainfall kinetic energy threshold could be established, which were ¯E N=13.83 D‑0.04 and ¯E S =15.59 D‑0.02. The results showed that not only for rainfall but also for rainfall kinetic energy threshold, the values of thresholds in North were lower than those in South. Due to impaction energy of rainfall to ground surface, rainfall kinetic energy would not forever increase. Therefore, rainfall kinetic energy threshold is also a useful tool for landslide warning. Key words: Rainfall kinetic energy, Rainfall threshold, Rainfall kinetic energy threshold, Landslide

  12. Ocean Origin of Asian Rainfall

    NASA Astrophysics Data System (ADS)

    Liu, W.; Xie, X.; Tang, W.

    2012-12-01

    In examining annual variation of precipitation in the India Subcontinent and the tropical East Asia, we fall back to the basic definition of a monsoon as the seasonal reversal of moisture transport between ocean and land. The improvement of TRMM rainfall and our validated data set of space-based estimate of moisture transport integrated over the depth of atmosphere allow us to relate regional and seasonal variation of rainfall over the land to moisture transport across various coastlines. The slight phase difference of monsoon onsets between the Arabian Sea and the Bay of Bengal could be discerned. The dominant of East Asian rainfall from the Bay of Bengal and South China Sea over those from the Western Pacific is evident. During the past decade, there are several El Nino/Southern Oscillation episodes that dominate the inter-annual anomalies and our analysis reveals how the transport is related to rainfall anomalies. The rain and transport relation at short time scales, including the landfall of tropical cyclones, is being explored.

  13. Hierarchical analysis of rainfall variability across Nigeria

    NASA Astrophysics Data System (ADS)

    Nnaji, Chidozie Charles; Mama, Cordelia Nnennaya; Ukpabi, Okechukwu

    2016-01-01

    Rainfall in Nigeria is subjected to wide variability both in time and space. This variability has assumed a more pronounced dimension as a result of climate change. In this paper, cluster analyses were used to study rainfall variability in Nigeria. Rainfall data in 20 locations spread across the geopolitical and ecological zones of Nigeria were subjected to hierarchical cluster analysis and analysis of time series and coefficient of variation for over periods spanning 30 years. Maps of spatial variations of mean annual rainfall and mean rainfall coefficient of variation were produced using ARCGIS 10.1. Furthermore, a better understanding of temporal variation of rainfall was sought by an investigation into the time series of rainfall coefficients of variation. It was found that the southern parts of the country were given to more severe rainfall variability/fluctuations than the northern parts. The north central parts exhibited more similarity to the southern parts than the other northern locations. The relationship between average annual rainfall and the coefficient of rainfall variation was found to follow a power law with R 2 value approximately 0.7. With respect to variability of annual rainfall, three zones emerged as follows: a linear relationship ( R 2 = 0.90) exists between coefficient of variation and average annual rainfall for the rainforest zone of the southsouth; a power law ( R 2 = 0.86) exists between coefficient of variation and average annual rainfall for all rainforest and derived guinea savannah zones of the southeastern and southwestern states; and a logarithmic relationship ( R 2 = 0.54) exists between coefficient of variation and average annual rainfall for all northern states regardless of ecological zone. Generally, in-year rainfall variability increases from the northwest to the southwest; while between-year (yearly) rainfall variability increases from the north central to the southeast. This study further confirms that rainfall variability

  14. TRMM Satellite Rainfall Data on Iselle

    NASA Video Gallery

    TRMM satellite rainfall data overlaid on an enhanced infrared image from NOAA's GOES-West satellite shows heavy rainfall occurring around the Iselle's eye. The most intense rain was falling at a ra...

  15. NASA Measured Erika's Rainfall Totals From Space

    NASA Video Gallery

    GPM measured rainfall from Tropical Storm Erika August 21 through 29, 2015. The heaviest rainfall in the analysis was estimated to be over 307 mm (12.1 inches) in the area of Dominica. Credit: NASA...

  16. GMI Rainfall Data on Tropical Storm Adjali

    NASA Video Gallery

    This animation shows GMI rainfall data on Tropical Storm Adjali on Nov. 19, 2014 combined with cloud data from the METEOSAT-7 satellite. Rainfall was found to be falling at a rate of over 69 mm/hr ...

  17. NASA's IMERG Measures Flooding Rainfall in Pakistan

    NASA Video Gallery

    NASA used satellite data and added up heavy rainfall that has been occurring in northwestern Pakistan that caused flooding that killed more than 50 people. NASA's IMERG added up rainfall in northwe...

  18. SYNOPTIC RAINFALL DATA ANALYSIS PROGRAM (SYNOP)

    EPA Science Inventory

    An integral part of the assessment of storm loads on water quality is the statistical evaluation of rainfall records. Hourly rainfall records of many years duration are cumbersome and difficult to analyze. The purpose of this rainfall data analysis program is to provide the user ...

  19. Predicting watershed acidification under alternate rainfall conditions

    USGS Publications Warehouse

    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, U.S.A. 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 soil water 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 distribution of rainfall, or evapotranspiration will change net soil water flux and, consequently, will affect the dynamics of the acidification response to continued sulfate loading.

  20. Post-fire debris-flow hazard assessment of the area burned by the 2013 Beaver Creek Fire near Hailey, central Idaho

    USGS Publications Warehouse

    Skinner, Kenneth D.

    2013-01-01

    A preliminary hazard assessment was developed for debris-flow hazards in the 465 square-kilometer (115,000 acres) area burned by the 2013 Beaver Creek fire near Hailey in central Idaho. The burn area covers all or part of six watersheds and selected basins draining to the Big Wood River and is at risk of substantial post-fire erosion, such as that caused by debris flows. Empirical models derived from statistical evaluation of data collected from recently burned basins throughout the Intermountain Region in Western United States were used to estimate the probability of debris-flow occurrence, potential volume of debris flows, and the combined debris-flow hazard ranking along the drainage network within the burn area and to estimate the same for analyzed drainage basins within the burn area. Input data for the empirical models included topographic parameters, soil characteristics, burn severity, and rainfall totals and intensities for a (1) 2-year-recurrence, 1-hour-duration rainfall, referred to as a 2-year storm (13 mm); (2) 10-year-recurrence, 1-hour-duration rainfall, referred to as a 10-year storm (19 mm); and (3) 25-year-recurrence, 1-hour-duration rainfall, referred to as a 25-year storm (22 mm). Estimated debris-flow probabilities for drainage basins upstream of 130 selected basin outlets ranged from less than 1 to 78 percent with the probabilities increasing with each increase in storm magnitude. Probabilities were high in three of the six watersheds. For the 25-year storm, probabilities were greater than 60 percent for 11 basin outlets and ranged from 50 to 60 percent for an additional 12 basin outlets. Probability estimates for stream segments within the drainage network can vary within a basin. For the 25-year storm, probabilities for stream segments within 33 basins were higher than the basin outlet, emphasizing the importance of evaluating the drainage network as well as basin outlets. Estimated debris-flow volumes for the three modeled storms range

  1. Urban rainfall estimation employing commercial microwave links

    NASA Astrophysics Data System (ADS)

    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.

  2. From runoff to rainfall: inverse rainfall-runoff modelling in a high temporal resolution

    NASA Astrophysics Data System (ADS)

    Herrnegger, M.; Nachtnebel, H. P.; Schulz, K.

    2014-12-01

    This paper presents a novel technique to calculate mean areal rainfall in a high temporal resolution of 60 min on the basis of an inverse conceptual rainfall-runoff model and runoff observations. Rainfall exhibits a large spatio-temporal variability, especially in complex alpine terrain. Additionally, the density of the monitoring network in mountainous regions is low and measurements are subjected to major errors, which lead to significant uncertainties in areal rainfall estimates. The most reliable hydrological information available refers to runoff, which in the presented work is used as input for a rainfall-runoff model. Thereby a conceptual, HBV-type model is embedded in an iteration algorithm. For every time step a rainfall value is determined, which results in a simulated runoff value that corresponds to the observation. To verify the existence, uniqueness and stability of the inverse rainfall, numerical experiments with synthetic hydrographs as inputs into the inverse model are carried out successfully. The application of the inverse model with runoff observations as driving input is performed for the Krems catchment (38.4 km2), situated in the northern Austrian Alpine foothills. Compared to station observations in the proximity of the catchment, the inverse rainfall sums and time series have a similar goodness of fit, as the independent INCA rainfall analysis of Austrian Central Institute for Meteorology and Geodynamics (ZAMG). Compared to observations, the inverse rainfall estimates show larger rainfall intensities. Numerical experiments show, that cold state conditions in the inverse model do not influence the inverse rainfall estimates, when considering an adequate spin-up time. The application of the inverse model is a feasible approach to obtain improved estimates of mean areal rainfall. These can be used to enhance interpolated rainfall fields, e.g. for the estimation of rainfall correction factors, the parameterisation of elevation dependency or the

  3. Using rainfall estimates to predict malaria transmission

    NASA Astrophysics Data System (ADS)

    Tretkoff, Ernie

    2011-05-01

    Malaria kills nearly a million people each year, mostly in rural Africa. The disease is spread by mosquitoes, which thrive in wet areas, so malaria transmission is closely linked to rainfall. Rainfall estimates could therefore be used to help predict potential malaria transmission. However, rain gauge networks are sparse in many of the rural areas that are hit hardest by malaria.

  4. Geometric median for missing rainfall data imputation

    NASA Astrophysics Data System (ADS)

    Burhanuddin, Siti Nur Zahrah Amin; Deni, Sayang Mohd; Ramli, Norazan Mohamed

    2015-02-01

    Missing data is a common problem faced by researchers in environmental studies. Environmental data, particularly, rainfall data are highly vulnerable to be missed, which is due to several reasons, such as malfunction instrument, incorrect measurements, and relocation of stations. Rainfall data are also affected by the presence of outliers due to the temporal and spatial variability of rainfall measurements. These problems may harm the quality of rainfall data and subsequently, produce inaccuracy in the results of analysis. Thus, this study is aimed to propose an imputation method that is robust towards the presence of outliers for treating the missing rainfall data. Geometric median was applied to estimate the missing values based on the available rainfall data from neighbouring stations. The method was compared with several conventional methods, such as normal ratio and inverse distance weighting methods, in order to evaluate its performance. Thirteen rainfall stations in Peninsular Malaysia were selected for the application of the imputation methods. The results indicated that the proposed method provided the most accurate estimation values compared to both conventional methods based on the least mean absolute error. The normal ratio was found to be the worst method in estimating the missing rainfall values.

  5. The Spatial Scaling of Global Rainfall Extremes

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  7. NASA's TRMM Satellite Calculates Hurricanes Fay and Gonzalo Rainfall

    NASA Video Gallery

    This rainfall analysis showed that Gonzalo generated several areas over the Atlantic Ocean where rainfall totals topped 12 inches (red). Fay's maximum rainfall appeared between 4 and 8 inches (gree...

  8. Topographic relationships for design rainfalls over Australia

    NASA Astrophysics Data System (ADS)

    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. Improvement of rainfall and flood forecasts by blending ensemble NWP rainfall with radar prediction considering orographic rainfall

    NASA Astrophysics Data System (ADS)

    Yu, Wansik; Nakakita, Eiichi; Kim, Sunmin; Yamaguchi, Kosei

    2015-12-01

    Many basins in Japan are characterized by steep mountainous regions, generating orographic rainfall events. Orographic rainfall may cause localized heavy rainfall to induce flash floods and sediment disasters. However, the accuracy of radar-based rainfall prediction was not enough because of the complex geographical pattern of the mountainous areas. In order to reduce damage due to localized heavy rainfall, characteristics of orographic rainfall must be identified into a short-term rainfall prediction procedure. The accuracy of radar-based rainfall prediction performs best for very short lead time, however the accuracy of radar prediction rapidly decreases with increasing lead times. At longer lead times, higher accuracy QPFs are produced by Numerical Weather Prediction (NWP) models, which solve the dynamics and physics of the atmosphere. This study proposes hybrid blending system of ensemble information from radar-based prediction and numerical weather prediction (NWP) to improve the accuracy of rainfall and flood forecasting. First, an improved radar image extrapolation method, which is comprised of the orographic rainfall identification and the error ensemble scheme, is introduced. Then, ensemble NWP outputs are updated based on mean bias of the error fields considering error structure. Finally, the improved radar-based prediction and updated NWP rainfall considering bias correction are blended dynamically with changing weight functions, which are computed from the expected skill of each radar prediction and updated NWP rainfall. The proposed method is verified temporally and spatially through a target event and is applied to the hybrid flood forecasting for updating with 1 h intervals. The newly proposed method shows sufficient reproducibility in peak discharge value, and could reduce the width of ensemble spread, which is expressed as the uncertainty, in the flood forecasting. Our study is carried out and verified using the largest flood event by typhoon

  10. Rainfall Simulation: methods, research questions and challenges

    NASA Astrophysics Data System (ADS)

    Ries, J. B.; Iserloh, T.

    2012-04-01

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

  11. Schools of the Pacific rainfall climate experiment

    NASA Technical Reports Server (NTRS)

    Postawko, S. E.; Morrissey, M. L.; Taylor, G. J.; Mouginis-Mark, P.

    1993-01-01

    The SPaRCE program is a cooperative rainfall climate field project involving high school and college level students and teachers from various Pacific island and atoll nations. The goals of the SPaRCE program are: (1) to foster interest and increase understanding among Pacific-area students and teachers of climate and climate change; (2) to educate the students and teachers as to the importance of rainfall in the Pacific area to climate studies; (3) to provide the students and teachers an opportunity of making a major contribution to the global climate research effort by collecting and analyzing Pacific rainfall data; and (4) to incorporate collected rainfall observations into a comprehensive Pacific daily rainfall data base to be used for climate research purposes. Schools participating in SPaRCE have received standard raingauges with which to measure rainfall at their sites. Students learned to site and use their raingauges by viewing a video produced at the University of Oklahoma. Four more videos will be produced which will include information on Earth's atmosphere, global climate and climate change, regional climate and implications of climate change, and how to analyze and use the rainfall data they are collecting. The videos are accompanied by workbooks which summarize the main points of each video, and contain concrete learning activities to help the student better understand climate and climate change. Following each video, interactive sessions are held with the students using the PEACESAT (Pan-Pacific Education And Communication Experiments by Satellite) satellite radio communication system.

  12. The Effects of Amazon Deforestation on Rainfall

    NASA Technical Reports Server (NTRS)

    Starr, David OC. (Technical Monitor); Negri, Andrew J.; Adler, Robert F.; Surratt, Jason

    2002-01-01

    This study begins with the hypothesis that heavily deforested regions will experience increased surface heating, leading to local circulations that will ultimately enhance the rainfall, or at least, change the pattern of diurnal evolution of rainfall. This would be an important finding because several modeling studies have concluded that widespread deforestation would lead to decreased rainfall. Towards that end rain estimates from a combined GOES infrared/TRMM microwave technique were analyzed with respect to percent forest cover from Landsat data (courtesy of TRFIC at Michigan State University) and GOES visible channel data over a deforested area in Rondonia (southwest Brazil). Five 1" x 1" areas of varying forest cover were examined during the onset of the wet season in Amazonia (Aug-Sept), when the effects of the surface would not be dominated by large-scale synoptic weather patterns. Preliminary results revealed that: maximum rainfall fell in most deforested area; heavily forested areas received the least rainfall; cumulus cloud development initiated at borders; the amplitude of the diurnal cycle of precipitation was a function of th surface cover. Further work will be presented detailing effects of land surface cover on the GOES infrared-measured surface heating, GOES visible observed cumulus development, thunderstorm initiation based on the location of temperature minima in the infrared data, and estimated rainfall and its diurnal cycle from a combined GOES/TRMM technique. Rainfall estimates derived from non-geosynchronous microwave observations (i.e. Goddard Profiling Algorithm, GPROF) will also be examined.

  13. Rainfall feedback via persistent effects on bioaerosols

    NASA Astrophysics Data System (ADS)

    Bigg, E. K.; Soubeyrand, S.; Morris, C. E.

    2014-10-01

    Consistent temporal differences between ice nucleus concentrations after and before a heavy fall of rain have been found in four areas of Australia. Closely similar differences were found between rainfall quantity or frequency at 106 sites in south-eastern and 61 sites in south-western Australia that had >92 years of daily rainfall records. The differences suggest an impulsive increase in ice nuclei or in rain on the day following heavy rain that decreased exponentially with time and was often still detectable after 20 days. The similarity of ice nucleus concentrations, bacterial populations, bioaerosols and rainfall responses to heavy rain strongly corroborate the involvement of biological ice nuclei in a rainfall feedback process. Cumulative differences of after-before rainfall amount or frequency for each rainfall event were next combined to form a historical record of the feedback process for each site. Comparison of cumulative totals pre-1960 and post-1960 showed differences bearing apparent relations to upwind coal-fired power stations, growth of metropolitan areas and increased areas of cultivation of wheat. These observations suggested that fungal spores or other bioaerosols as well as ice-nucleating bacteria were involved in the feedback. The overall conclusion is that interactions between micro-organisms, bioaerosols and rainfall have impacts over longer time spans and are stronger than have been previously described.

  14. Spatial estimation of debris flows-triggering rainfall and its dependence on rainfall severity

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    Forecasting the occurrence of landslides and debris flows (collectively termed 'debris flows' hereinafter) is fundamental for issuing hazard warnings, and focuses largely on rainfall as a triggering agent. Debris flow forecasting relies very often on the identification of combinations of depth and duration of rainfall - rainfall thresholds - that trigger widespread debris flows. Rainfall estimation errors related to the sparse nature of raingauge data are enhanced in case of convective rainfall events characterized by limited spatial extent. Such errors have been shown to cause underestimation of the rainfall thresholds and, thus, less efficient forecasts of debris flows occurrence. This work examines the spatial organization of debris flows-triggering rainfall around the debris flow initiation points using high-resolution, carefully corrected radar data for a set of short duration (<30 h) storm events occurred in the eastern Italian Alps. The set includes eleven debris-flow triggering rainfall events that occurred in the study area between 2005 and 2014. The selected events are among the most severe in the region during this period and triggered a total of 99 debris flows that caused significant damage to people and infrastructures. We show that the spatial rainfall organisation depends on the severity (measured via the estimated return time-RT) of the debris flow-triggering rainfall. For more frequent events (RT<20 yrs) the rainfall spatial pattern systematically shows that debris flow location coincides with a local minimum, whereas for less frequent events (RT>20 yrs) the triggering rainfall presents a local peak corresponding to the debris flow initiation point. Dependence of these features on rainfall duration is quite limited. The characteristics of the spatial rainfall organisation are exploited to understand the performances and results of three different rainfall interpolation techniques: nearest neighbour (NN), inverse distance weighting (IDW) and

  15. NASA TRMM Satellite 3-D Animation of Cyclone Mahasen Rainfall

    NASA Video Gallery

    This animation shows a simulated 3-D analysis of NASA's Tropical Rainfall Measuring Mission (TRMM) satellite's multisatellite Precipitation Analysis (TMPA). It shows rainfall that occurred with tro...

  16. Rainfall kinetic energy-intensity and rainfall momentum-intensity relationships for Cape Verde

    NASA Astrophysics Data System (ADS)

    Sanchez-Moreno, Juan Francisco; Mannaerts, Chris M.; Jetten, Victor; Löffler-Mang, Martin

    2012-08-01

    Momentum and kinetic energy of rainfall are widely used indices to describe erosivity, the ability of rainfall to detach soil particles and erode the landscape. An optical laser disdrometer was installed in Santiago Island, Cape Verde, between September 2008 and September 2010 to measure rainfall intensity and size distribution of raindrops. A total time series of 5129 observations of radar reflectivity, visibility, rainfall intensity and number of particles were gathered. Rainfall kinetic energy expenditure KEtime (J m-2 h-1), kinetic energy content KEmm (J m-2 mm-1) and momentum flux MtA (kg m s-1 m-2 s-1) were calculated and fitted to different known experimental equations. The best fit between rainfall intensity and kinetic energy expenditure, kinetic energy content and momentum were obtained with power-law equations. These equations were validated in two independent events corresponding to 2008 and 2009, producing high correlation coefficients. The results show that for Cape Verde, KEtime is a more appropriate index to relate with rainfall intensity, and that kinetic energy expenditure and momentum flux are interchangeable parameters for erosivity estimation. New relationships relating kinetic energy and rainfall intensity, and momentum and rainfall intensity were derived, which contribute to the characterization of rainfall originating from tropical depressions at lower latitudes.

  17. Optimization of multiparameter radar estimates of rainfall

    NASA Technical Reports Server (NTRS)

    Chandrasekar, V.; Gorgucci, Eugenio; Scarchilli, Gianfranco

    1993-01-01

    The estimates of rainfall rate derived from a multiparameter radar based on reflectivity factor (R sub ZH), differential reflectivity (R sub DR), and specific differential propagation phase (R sub DP) have widely varying accuracies over the dynamic range of the natural occurrence of rainfall. This paper presents a framework to optimally combine the three estimates, R sub zH, R sub DR, and R sub DP, to derive the best estimate of rainfall using coherent multiparameter radars. The optimization procedure is demonstrated for application to multiparameter radar measurements at C band.

  18. Rainfall mechanisms for the dominant rainfall mode over Zimbabwe relative to ENSO and/or IODZM.

    PubMed

    Manatsa, Desmond; Mukwada, Geoffrey

    2012-01-01

    Zimbabwe's homogeneous precipitation regions are investigated by means of principal component analysis (PCA) with regard to the underlying processes related to ENSO and/or Indian Ocean Dipole zonal mode (IODZM). Station standardized precipitation index rather than direct rainfall values represent the data matrix used in the PCA. The results indicate that the country's rainfall is highly homogeneous and is dominantly described by the first principal mode (PC1). This leading PC can be used to represent the major rainfall patterns affecting the country, both spatially and temporarily. The current practice of subdividing the country into the two seasonal rainfall forecast zones becomes irrelevant. Partial correlation analysis shows that PC1 is linked more to the IODZM than to the traditional ENSO which predominantly demonstrates insignificant association with PC1. The pure IODZM composite is linked to the most intense rainfall suppression mechanisms, while the pure El Niño composite is linked to rainfall enhancing mechanisms. PMID:22645470

  19. TRMM Reveals Daniel's Rainfall - Duration: 6 seconds.

    NASA Video Gallery

    TRMM animation showing a blend between infrared and visible imagery of Tropical Storm Daniel on July 6, 2012. Both images were taken from NASA's Tropical Rainfall Measuring Mission's (TRMM) Visible...

  20. GPM's Rainfall Rate Analysis for Quang

    NASA Video Gallery

    The rainfall accumulation analysis above was computed from data generated by the Integrated Multi-satellite Retrievals for GPM (IMERG) during the period from April 28 to May 3, 2015. Credit: SSAI/N...

  1. GPM IMERG Rainfall Analysis of Etau

    NASA Video Gallery

    This GPM IMERG analysis shows rainfall total estimates for Japan during the seven day period from September 2 to 9. Extraordinary totals of over 750 mm (29.5 inches) were analyzed near the south-ce...

  2. IMERG Analysis of the Rainfall from Colin

    NASA Video Gallery

    This IMERG analysis over June 6 to 8 indicates that Colin's heaviest precipitation occurred over central Florida. Extreme rainfall amounts of over 280 mm (11 inches) were measured during this perio...

  3. GPM Movie of Souledor's Rainfall Structure

    NASA Video Gallery

    On Aug. 5, the GPM satellite data was used to make a 3-D vertical structure of rainfall within Soudelor. Some storms examined with GPM's radar reached heights of over 12.9 km (about 8 miles) and we...

  4. Monsoon Rainfall and Landslides in Nepal

    NASA Astrophysics Data System (ADS)

    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. Contribution of tropical cyclones to global rainfall

    NASA Astrophysics Data System (ADS)

    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

  6. Rainfall runoff model development and applications

    NASA Astrophysics Data System (ADS)

    Brazil, Larry E.

    A special symposium on rainfall runoff modeling was held during the 1986 AGU Fall Meeting in San Francisco, Calif. The purpose of the symposium, which was sponsored by the Surface Runoff Committee of the Hydrology Section, was to provide a forum for discussion between researchers responsible for model development and users of rainfall runoff models. The symposium consisted of morning and afternoon sessions followed by a panel discussion.

  7. Volatility modeling of rainfall time series

    NASA Astrophysics Data System (ADS)

    Yusof, Fadhilah; Kane, Ibrahim Lawal

    2013-07-01

    Networks of rain gauges can provide a better insight into the spatial and temporal variability of rainfall, but they tend to be too widely spaced for accurate estimates. A way to estimate the spatial variability of rainfall between gauge points is to interpolate between them. This paper evaluates the spatial autocorrelation of rainfall data in some locations in Peninsular Malaysia using geostatistical technique. The results give an insight on the spatial variability of rainfall in the area, as such, two rain gauges were selected for an in-depth study of the temporal dependence of the rainfall data-generating process. It could be shown that rainfall data are affected by nonlinear characteristics of the variance often referred to as variance clustering or volatility, where large changes tend to follow large changes and small changes tend to follow small changes. The autocorrelation structure of the residuals and the squared residuals derived from autoregressive integrated moving average (ARIMA) models were inspected, the residuals are uncorrelated but the squared residuals show autocorrelation, and the Ljung-Box test confirmed the results. A test based on the Lagrange multiplier principle was applied to the squared residuals from the ARIMA models. The results of this auxiliary test show a clear evidence to reject the null hypothesis of no autoregressive conditional heteroskedasticity (ARCH) effect. Hence, it indicates that generalized ARCH (GARCH) modeling is necessary. An ARIMA error model is proposed to capture the mean behavior and a GARCH model for modeling heteroskedasticity (variance behavior) of the residuals from the ARIMA model. Therefore, the composite ARIMA-GARCH model captures the dynamics of daily rainfall in the study area. On the other hand, seasonal ARIMA model became a suitable model for the monthly average rainfall series of the same locations treated.

  8. Threshold modeling of extreme spatial rainfall

    NASA Astrophysics Data System (ADS)

    Thibaud, E.; Davison, A.

    2013-12-01

    Complex events such as sustained extreme precipitation have major effects on human populations and environmental sustainability, and there is a growing interest in modeling them realistically. For risk assessment based on spatial quantities such as the total amount of rainfall falling over a region, it is necessary to properly model the dependence among extremes over that region, based on data from perhaps only a few sites within it. We propose an approach to spatial modeling of extreme rainfall, based on max-stable processes fitted using partial duration series and a censored threshold likelihood function. The resulting models are coherent with classical extreme-value theory and allow the consistent treatment of spatial dependence of rainfall using ideas related to those of classical geostatistics. The method can be used to produce simulations needed for hydrological models, and in particular for the generation of spatially heterogeneous extreme rainfall fields over catchments. We illustrate the ideas through data from the Val Ferret watershed in the Swiss Alps, based on daily cumulative rainfall totals recorded at 24 stations for four summers, augmented by a longer series from nearby. References: Davison, A. C., Huser, R., Thibaud, E. (2013). Geostatistics of Dependent and Asymptotically Independent Extremes, Mathematical Geosciences, vol. 45, num. 5, p. 511-529, 2013, doi:10.1007/s11004-013-9469-y Thibaud, E., Mutzner, R., Davison A. C. (2013, to appear). Threshold modeling of extreme spatial rainfall, Water Resources Research, doi:10.1002/wrcr.20329

  9. Reconstruction of rainfall events responsible for landslides using an algorithm

    NASA Astrophysics Data System (ADS)

    Melillo, Massimo; Brunetti, Maria Teresa; Gariano, Stefano Luigi; Guzzetti, Fausto; Peruccacci, Silvia

    2014-05-01

    In Italy, intense or prolonged rainfall is the primary trigger of damaging landslides. The identification of the rainfall conditions responsible for the initiation of landslides is a crucial issue and may contribute to reduce landslide risk. Objective criteria for the identification of rainfall conditions that could initiate slope failures are still lacking or ambiguous. The reconstruction of rainfall events able to trigger past landslides is usually performed manually by expert investigators. Here, we propose an algorithm that reconstructs automatically rainfall events from a series of hourly rainfall data. The automatic reconstruction reproduces the actions performed by an expert investigator that adopts empirical rules to define rainfall conditions that presumably initiated the documented landslides. The algorithm, which is implemented in R (http://www.r-project.org), performs three actions on the data series: (i) removes isolated events with negligible amount of rainfall and random noise generated by the rain gauge; (ii) aggregates rainfall measurements in order to obtain a sequence of distinct rainfall events; (iii) identifies single or multiple rainfall conditions responsible for the slope failures. In particular, the algorithm calculates the duration, D, and the cumulated rainfall, E, for rainfall events, and for rainfall conditions that have resulted in landslides. A set of input parameters allows the automatic reconstruction of rainfall events in different physical settings and climatic conditions. We tested the algorithm using rainfall and landslide information available to us for Sicily, Southern Italy, in the period between January 2002 and December 2012. The algorithm reconstructed 13,537 rainfall events and 343 rainfall conditions as possible triggers of the 163 documented landslides. Most (87.7%) of the rainfall conditions obtained manually were reconstructed accurately. Use of the algorithm shall contribute to an objective and reproducible

  10. Space-Time Characteristics of Rainfall Diurnal Variations

    NASA Technical Reports Server (NTRS)

    Yang, Song; Kummerow, Chris; Olson, Bill; Smith, Eric A.; Einaudi, Franco (Technical Monitor)

    2001-01-01

    The space-time features of rainfall diurnal variation of precipitation are systematically investigated by using the Tropical Rainfall Measuring Mission (TRMM) precipitation products retrieved from TRMM microwave imager (TMI), precipitation radar (PR) and TMI/PR combined algorithms. Results demonstrate that diurnal variability of precipitation is obvious over tropical regions. The dominant feature of rainfall diurnal cycle over, ocean is that there is consistent rainfall peak in early morning, while there is a consistent rainfall peak in mid-late afternoon over land. The seasonal variation on intensity of rainfall diurnal cycle is clearly evidenced. Horizontal distributions of rainfall diurnal variations indicate that there is a clearly early-morning peak with a secondary peak in the middle-late afternoon in ocean rainfall at latitudes dominated by large-scale convergence and deep convection. There is also an analogous early-morning peak in land rainfall along with a stronger afternoon peak forced by surface heating. Amplitude analysis shows that the patterns and its evolution of rainfall diurnal cycle are very close to rainfall distribution pattern and its evolution. These results indicate that rainfall diurnal variations are strongly associated with large-scale convective systems and climate weather systems. Phase studies clearly present the regional and seasonal features of rainfall diurnal activities. Further studies on convective and stratiform rainfall show different characteristics of diurnal cycles. Their spatial and temporal variations of convective and stratiform rainfall indicate that mechanisms for rainfall diurnal variations vary with time and space.

  11. Variable rainfall intensity during soil erosion experiments at the laboratory rainfall simulator

    NASA Astrophysics Data System (ADS)

    Laburda, Tomas; Schwarzova, Pavla; Krasa, Josef

    2016-04-01

    Experimental research of soil erosion at the laboratory rainfall simulator at the CTU in Prague continued with 11th soil set Trebesice III in 2014/2015. Standard simulations with constant rainfall intensity were complemented by additional simulations with variable rainfall intensity with two different patterns. The main objective was to determine the feasibility of these experiments and the effect on erosion characteristics compared to those with constant rainfall intensity. This measurement consist of 60 minute simulations (change in intensity in 20. and 40. minute of simulation) with increasing rainfall intensity with pattern of 20-40-60 mm/hr ("inc") and decreasing intensity with pattern of 60-40-20 mm/hr ("dec") which have been compared with experiments with constant rainfall intensity of 40 mm/hr ("c40"). All experiments thus reaching the same total precipitation during entire simulation. This comparison was done on soil sample with dimensions of 4x0,9x0,15 meters and slope adjusted at 4° and 8°. Final evaluation consists of comparison of development and cumulative values of surface runoff and soil loss. In case of steady soil conditions (in this case, the experiments on the slope 4°) results show there is no significant difference in surface runoff in term of cumulative values and development (in the middle period of simulations with rainfall intensity of 40 mm/hr, i.e. 20-40. minute of every experiment) between "c40", "inc" and "dec". On the other hand, results of soil loss from the same experiments differ according to rainfall intensity pattern in both development and cumulative values. While "inc" experiment has slightly lower (up to 10 %) soil loss than "c40", development of soil loss (in the middle period of simulations with 40 mm/hr) of "dec" experiment is almost two times lower compare to "c40". Experiments with longitudinal soil surface of 8° differ in soil moisture that affects results more than variable rainfall intensity pattern. Experimental

  12. Impact of uncertainty in rainfall estimation on the identification of rainfall thresholds for debris flow occurrence

    NASA Astrophysics Data System (ADS)

    Nikolopoulos, Efthymios I.; Crema, Stefano; Marchi, Lorenzo; Marra, Francesco; Guzzetti, Fausto; Borga, Marco

    2014-09-01

    Estimation of rainfall intensity-duration thresholds, used for the identification of debris flow/landslide triggering rainfall events, has been traditionally based on raingauge observations. The main drawback of using information from gauges is that the measurement stations are usually located far away from the debris flow initiation areas. In complex terrain where debris flows take place, the spatial variability of rainfall can be very high and this translates in large uncertainty of raingauge-based estimates of debris flow triggering rainfall. This work focuses on the assessment of the impact of rainfall estimation uncertainty on identification and use of rainfall thresholds for debris flow occurrence. The Upper Adige River basin, Northern Italy, is the area of study. A detailed database of more than 400 identified debris flow initiation points during the period 2000-2010 and a raingauge network of 100 stations comprise the database used for this work. The methodology examines the intensity-duration thresholds derived from a set of raingauges that are assumed to be located at debris flow initiation points (DFRs) and an equivalent set of raingauges assumed to have the role of the closest (to debris flow) available measurement (MRs). A set of reference rainfall thresholds is used to identify the rainfall events at DFRs that “triggered” debris flows (i.e. exceed the threshold). For these same events, the corresponding rainfall thresholds are derived from MR observations. Comparison between the rainfall thresholds derived from DFRs and MRs revealed that uncertainty in rainfall estimation has a major impact on estimated intensity-duration thresholds. Specifically, the results showed that thresholds estimated from MR observations are consistently underestimated. Evaluation of the estimated thresholds for warning procedures showed that while detection is high, the main issue is the high false alarm ratio, which limits the overall accuracy of the procedure. Overall

  13. Rainfall triggered landslides in unsaturated soils: a numerical sensitivity analysis for rainfall threshold

    NASA Astrophysics Data System (ADS)

    Ahmadiadli, M.; Huvaj, N.; Toker, K.

    2012-04-01

    Catastrophic precipitation-induced landslides have frequently hit villages, towns and roads in Black Sea Region in northern Turkey, causing extensive damage and many fatalities. Due to global climatic changes, the intensity and frequency of extreme rainfall events are expected to increase. In addition, due to limited available land on level ground, urbanization continue to increase on sloping ground which increases the exposure and elements at risk. Most available methods for predicting rainfall-induced slope instability are based on statistical data of past slope failures and rainfall events. These may often give conservative or unconservative faulty warnings, so a physically-based model that takes into account the mechanism of the problem should be incorporated for more accurate warning system. In this study, main aspects of rainfall triggered landslides, such as infiltration in an unsaturated soil profile, changes in soil suction and shear strength, development of instability in terms of factor of safety and deformations have been studied numerically. The factors/issues that govern this mechanism have been evaluated and a sensitivity analysis is performed using finite element method. We propose a simple 2D numerical approach that is able to predict the evolution of the key factors governing slope stability as a tool to predict the onset of slope failure, with potential benefits for early warning systems. The effect of antecedent rainfall, and different rainfall intensity-duration schemes (short duration intense rainfall, prolonged low intensity rainfall etc.) are considered in evaluating the threshold critical rainfall that may trigger landslides. The approach is calibrated through a well-documented case history, for which the results will be presented in terms of soil suction, deformation and factor of safety versus time and predicted triggering rainfall. The proposed method can be a first-step towards an integrated early warning system for rainfall triggered

  14. Analysis of extreme rainfall events using attributes control charts in temporal rainfall processes

    NASA Astrophysics Data System (ADS)

    Villeta, María; Valencia, Jose Luis; Saá-Requejo, Antonio; María Tarquis, Ana

    2015-04-01

    The impacts of most intense rainfall events on agriculture and insurance industry can be very severe. This research focuses in the analysis of extreme rainfall events throughout the use of attributes control charts, which constitutes a usual tool in Statistical Process Control (SPC) but unusual in climate studios. Here, series of daily precipitations for the years 1931-2009 within a Spanish region are analyzed, based on a new type of attributes control chart that takes into account the autocorrelation between the extreme rainfall events. The aim is to conclude if there exist or not evidence of a change in the extreme rainfall model of the considered series. After adjusting seasonally the precipitation series and considering the data of the first 30 years, a frequency-based criterion allowed fixing specification limits in order to discriminate between extreme observed rainfall days and normal observed rainfall days. The autocorrelation amongst maximum precipitation is taken into account by a New Binomial Markov Extended Process obtained for each rainfall series. These modelling of the extreme rainfall processes provide a way to generate the attributes control charts for the annual fraction of rainfall extreme days. The extreme rainfall processes along the rest of the years under study can then be monitored by such attributes control charts. The results of the application of this methodology show evidence of change in the model of extreme rainfall events in some of the analyzed precipitation series. This suggests that the attributes control charts proposed for the analysis of the most intense precipitation events will be of practical interest to agriculture and insurance sectors in next future.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  16. Blue Nile Rainfall Experiment: Validation Results

    NASA Astrophysics Data System (ADS)

    Gebremichael, M.

    2014-12-01

    The accuracy of three widely-used, near-global, high-resolution satellite rainfall products (CMORPH, TMPA-RT v7, TMPA-RP v7) is assessed over the Blue Nile River Basin, a basin characterized by complex terrain and tropical monsoon. The assessment is made using dense experimental networks of rain gauges deployed at two, 0.25°×0.25°, sites that represent contrasting topographic features: the lowland plain (mean elevation of 719 m.a.s.l.) site and the highland mountain (mean elevation of 2268 m.a.s.l.). The investigation period covers the summer seasons of 2012 through 2014. Compared to the highland mountain site, the lowland plain site exhibits marked extremes of rain intensity, higher rain intensity, lower frequency of rain occurrence, and smaller seasonal rainfall accumulation. All the satellite products considered tend to overestimate the mean rainfall rate at the lowland plain site, but underestimate it at the highland mountain site. The satellite products miss more rainfall at the highland mountain site than at the lowland plain site. The satellite products underestimate the heavy rain rates at both sites. Both sites have uncertainty (root mean square error) values greater than 100% for 3 hour accumulations of less than 5 mm, or daily accumulations of less than 10 mm, and the uncertainty values decrease with increasing rainfall accumulation. Among the satellite products, CMORPH suffers from a large positive bias at the lowland plain site, and TMPA-RP and TMPA-RT miss a large number of rainfall events that contribute nearly half of the total rainfall at the lowland plain.

  17. Multivariate Bayesian Models of Extreme Rainfall

    NASA Astrophysics Data System (ADS)

    Rahill-Marier, B.; Devineni, N.; Lall, U.; Farnham, D.

    2013-12-01

    Accounting for spatial heterogeneity in extreme rainfall has important ramifications in hydrological design and climate models alike. Traditional methods, including areal reduction factors and kriging, are sensitive to catchment shape assumptions and return periods, and do not explicitly model spatial dependence between between data points. More recent spatially dense rainfall simulators depend on newer data sources such as radar and may struggle to reproduce extremes because of physical assumptions in the model and short historical records. Rain gauges offer the longest historical record, key when considering rainfall extremes and changes over time, and particularly relevant in today's environment of designing for climate change. In this paper we propose a probabilistic approach of accounting for spatial dependence using the lengthy but spatially disparate hourly rainfall network in the greater New York City area. We build a hierarchical Bayesian model allowing extremes at one station to co-vary with concurrent rainfall fields occurring at other stations. Subsequently we pool across the extreme rainfall fields of all stations, and demonstrate that the expected catchment-wide events are significantly lower when considering spatial fields instead of maxima-only fields. We additionally demonstrate the importance of using concurrent spatial fields, rather than annual maxima, in producing covariance matrices that describe true storm dynamics. This approach is also unique in that it considers short duration storms - from one hour to twenty-four hours - rather than the daily values typically derived from rainfall gauges. The same methodology can be extended to include the radar fields available in the past decade. The hierarchical multilevel approach lends itself easily to integration of long-record parameters and short-record parameters at a station or regional level. In addition climate covariates can be introduced to support the relationship of spatial covariance with

  18. Monthly Rainfall Erosivity Assessment for Switzerland

    NASA Astrophysics Data System (ADS)

    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

  19. Markov chain decomposition of monthly rainfall into daily rainfall: Evaluation of climate change impact

    DOE PAGESBeta

    Yoo, Chulsang; Lee, Jinwook; Ro, Yonghun

    2016-01-01

    This paper evaluates the effect of climate change on daily rainfall, especially on the mean number of wet days and the mean rainfall intensity. Assuming that the mechanism of daily rainfall occurrences follows the first-order Markov chain model, the possible changes in the transition probabilities are estimated by considering the climate change scenarios. Also, the change of the stationary probabilities of wet and dry day occurrences and finally the change in the number of wet days are derived for the comparison of current (1x CO2) and 2x CO2conditions. As a result of this study, the increase or decrease in themore » mean number of wet days was found to be not enough to explain all of the change in monthly rainfall amounts, so rainfall intensity should also be modified. The application to the Seoul weather station in Korea shows that about 30% of the total change in monthly rainfall amount can be explained by the change in the number of wet days and the remaining 70% by the change in the rainfall intensity. That is, as an effect of climate change, the increase in the rainfall intensity could be more significant than the increase in the wet days and, thus, the risk of flood will be much highly increased.« less

  20. Spatial averaging of oceanic rainfall variability using underwater sound: Ionian Sea rainfall experiment 2004.

    PubMed

    Nystuen, Jeffrey A; Amitai, Eyal; Anagnostou, Emmanuel N; Anagnostou, Marios N

    2008-04-01

    An experiment to evaluate the inherent spatial averaging of the underwater acoustic signal from rainfall was conducted in the winter of 2004 in the Ionian Sea southwest of Greece. A mooring with four passive aquatic listeners (PALs) at 60, 200, 1000, and 2000 m was deployed at 36.85 degrees N, 21.52 degrees E, 17 km west of a dual-polarization X-band coastal radar at Methoni, Greece. The acoustic signal is classified into wind, rain, shipping, and whale categories. It is similar at all depths and rainfall is detected at all depths. A signal that is consistent with the clicking of deep-diving beaked whales is present 2% of the time, although there was no visual confirmation of whale presence. Co-detection of rainfall with the radar verifies that the acoustic detection of rainfall is excellent. Once detection is made, the correlation between acoustic and radar rainfall rates is high. Spatial averaging of the radar rainfall rates in concentric circles over the mooring verifies the larger inherent spatial averaging of the rainfall signal with recording depth. For the PAL at 2000 m, the maximum correlation was at 3-4 km, suggesting a listening area for the acoustic rainfall measurement of roughly 30-50 km(2). PMID:18397003

  1. Markov chain decomposition of monthly rainfall into daily rainfall: Evaluation of climate change impact

    SciTech Connect

    Yoo, Chulsang; Lee, Jinwook; Ro, Yonghun

    2016-01-01

    This paper evaluates the effect of climate change on daily rainfall, especially on the mean number of wet days and the mean rainfall intensity. Assuming that the mechanism of daily rainfall occurrences follows the first-order Markov chain model, the possible changes in the transition probabilities are estimated by considering the climate change scenarios. Also, the change of the stationary probabilities of wet and dry day occurrences and finally the change in the number of wet days are derived for the comparison of current (1x CO2) and 2x CO2conditions. As a result of this study, the increase or decrease in the mean number of wet days was found to be not enough to explain all of the change in monthly rainfall amounts, so rainfall intensity should also be modified. The application to the Seoul weather station in Korea shows that about 30% of the total change in monthly rainfall amount can be explained by the change in the number of wet days and the remaining 70% by the change in the rainfall intensity. That is, as an effect of climate change, the increase in the rainfall intensity could be more significant than the increase in the wet days and, thus, the risk of flood will be much highly increased.

  2. SUBPIXEL-SCALE RAINFALL VARIABILITY AND THE EFFECTS ON SEPARATION OF RADAR AND GAUGE RAINFALL ERRORS

    EPA Science Inventory

    One of the primary sources of the discrepancies between radar-based rainfall estimates and rain gauge measurements is the point-area difference, i.e., the intrinsic difference in the spatial dimensions of the rainfall fields that the respective data sets are meant to represent. ...

  3. Comparison of rainfall sampling schemes using a calibrated stochastic rainfall generator

    SciTech Connect

    Welles, E.

    1994-12-31

    Accurate rainfall measurements are critical to river flow predictions. Areal and gauge rainfall measurements create different descriptions of the same storms. The purpose of this study is to characterize those differences. A stochastic rainfall generator was calibrated using an automatic search algorithm. Statistics describing several rainfall characteristics of interest were used in the error function. The calibrated model was then used to generate storms which were exhaustively sampled, sparsely sampled and sampled areally with 4 x 4 km grids. The sparsely sampled rainfall was also kriged to 4 x 4 km blocks. The differences between the four schemes were characterized by comparing statistics computed from each of the sampling methods. The possibility of predicting areal statistics from gauge statistics was explored. It was found that areally measured storms appeared to move more slowly, appeared larger, appeared less intense and have shallower intensity gradients.

  4. Rainfall variability and seasonality in northern Bangladesh

    NASA Astrophysics Data System (ADS)

    Bari, Sheikh Hefzul; Hussain, Md. Manjurul; Husna, Noor-E.-Ashmaul

    2016-05-01

    This paper aimed at the analysis of rainfall seasonality and variability for the northern part of South-Asian country, Bangladesh. The coefficient of variability was used to determine the variability of rainfall. While rainfall seasonality index (SI ) and mean individual seasonality index ( overline{SI_i} ) were used to identify seasonal contrast. We also applied Mann-Kendall trend test and sequential Mann-Kendall test to determine the trend in seasonality. The lowest variability was found for monsoon among the four seasons whereas winter has the highest variability. Observed variability has a decreasing tendency from the northwest region towards the northeast region. The mean individual seasonality index (0.815378 to 0.977228) indicates that rainfall in Bangladesh is "markedly seasonal with a long dry season." It was found that the length of the dry period is lower at the northeastern part of northern Bangladesh. Trend analysis results show no significant change in the seasonality of rainfall in this region. Regression analysis of overline{SI_i} and SI, and longitude and mean individual seasonality index show a significant linear correlation for this area.

  5. Spatial rainfall data in open source environment

    NASA Astrophysics Data System (ADS)

    Schuurmans, Hanneke; Maarten Verbree, Jan; Leijnse, Hidde; van Heeringen, Klaas-Jan; Uijlenhoet, Remko; Bierkens, Marc; van de Giesen, Nick; Gooijer, Jan; van den Houten, Gert

    2013-04-01

    Since January 2013 The Netherlands have access to innovative high-quality rainfall data that is used for watermanagers. This product is innovative because of the following reasons. (i) The product is developed in a 'golden triangle' construction - corporation between government, business and research. (ii) Second the rainfall products are developed according to the open-source GPL license. The initiative comes from a group of water boards in the Netherlands that joined their forces to fund the development of a new rainfall product. Not only data from Dutch radar stations (as is currently done by the Dutch meteorological organization KNMI) is used but also data from radars in Germany and Belgium. After a radarcomposite is made, it is adjusted according to data from raingauges (ground truth). This results in 9 different rainfall products that give for each moment the best rainfall data. Specific knowledge is necessary to develop these kind of data. Therefore a pool of experts (KNMI, Deltares and 3 universities) participated in the development. The philosophy of the developers (being corporations) is that products like this should be developed in open source. This way knowledge is shared and the whole community is able to make suggestions for improvement. In our opinion this is the only way to make real progress in product development. Furthermore the financial resources of government organizations are optimized. More info (in Dutch): www.nationaleregenradar.nl

  6. From runoff to rainfall: inverse rainfall-runoff modelling in a high temporal resolution

    NASA Astrophysics Data System (ADS)

    Herrnegger, M.; Nachtnebel, H. P.; Schulz, K.

    2015-11-01

    Rainfall exhibits a large spatio-temporal variability, especially in complex alpine terrain. Additionally, the density of the monitoring network in mountainous regions is low and measurements are subjected to major errors, which lead to significant uncertainties in areal rainfall estimates. In contrast, the most reliable hydrological information available refers to runoff, which in the presented work is used as input for an inverted HBV-type rainfall-runoff model that is embedded in a root finding algorithm. For every time step a rainfall value is determined, which results in a simulated runoff value closely matching the observed runoff. The inverse model is applied and tested to the Schliefau and Krems catchments, situated in the northern Austrian Alpine foothills. The correlations between inferred rainfall and station observations in the proximity of the catchments are of similar magnitude compared to the correlations between station observations and independent INCA (Integrated Nowcasting through Comprehensive Analysis) rainfall analyses provided by the Austrian Central Institute for Meteorology and Geodynamics (ZAMG). The cumulative precipitation sums also show similar dynamics. The application of the inverse model is a promising approach to obtain additional information on mean areal rainfall. This additional information is not solely limited to the simulated hourly data but also includes the aggregated daily rainfall rates, which show a significantly higher correlation to the observed values. Potential applications of the inverse model include gaining additional information on catchment rainfall for interpolation purposes, flood forecasting or the estimation of snowmelt contribution. The application is limited to (smaller) catchments, which can be represented with a lumped model setup, and to the estimation of liquid rainfall.

  7. Modelling rainfall erosion resulting from climate change

    NASA Astrophysics Data System (ADS)

    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.

  8. Rainfall and epizootic Rift Valley fever*

    PubMed Central

    Davies, F. G.; Linthicum, K. J.; James, A. D.

    1985-01-01

    Epizootic Rift Valley fever (RVF) has occurred in Kenya four times over the last 30 years. Widespread, frequent, and persistent rainfall has been a feature of these epizootic periods. A composite statistic, based upon measurements of these rainfall characteristics, is positive during periods of epizootic Rift Valley fever. The heavy rainfall raises the level of the water table in certain areas, flooding the grassland depressions (dambos) that are the habitat of the immature forms of certain ground-pool-breeding mosquitos of the genus Aedes. RVF virus is probably transmitted transovarially in these species, very large numbers of which emerge under these damp conditions. This is when clinical signs of the disease are first seen. PMID:3879206

  9. Critical Phenomena of Rainfall in Ecuador

    NASA Astrophysics Data System (ADS)

    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).

  10. Space-time modeling of a rainfall field ; Application to daily rainfall in the Loire basin

    NASA Astrophysics Data System (ADS)

    Lepioufle, Jean-Marie; Leblois, Etienne; Creutin, Jean-Dominique

    2010-05-01

    Water resources management for a watershed necessitates to assess both high flow volumes and the impact of the management practice for different stakeholders (hydropower, irrigation, ecology...). To test different management strategies, hydrologists have developed hydrological distributed models incorporating several computational objects such as digital elevation model, sub-basins, and distances to the basin outlet. A good characterization of rainfall variability in space and time is crucial for the relevance of a hydrological model as a basis for the choice of water management strategy. Climatological references of rainfall hazard must be built from observation over decades. Daily rainfall measurements from raingauge networks are therefore still an invaluable source of information for a precise representation of precipitation hazard despite the recent availability of radar estimates. Based on either raingauge or radar observations, it is possible to mathematically model rainfall field as a space-time intermittent process (superposition of inner variability field and rainfall indicator field, both influenced by advection). Geostatistics enables to investigate the link between an instantaneous process space-time structure and the evolution of spatial structure with time aggregation.. A method is proposed to infer a relevant instantaneous process from observed rainfall statistics. After fitting the parameters of the instantaneous space-time variogram with the simplex method, spatial variograms for different duration respecting time aggregated variograms is calculated. With this basis, an avenue is open to simulate homogeneous rainfall fields which respect major statistical characteristics for hydrologists: expectation and variance of rainfall distribution and spatial variogram for different durations. Benefits and limits of this approach are investigated using daily rainfall data from the Loire basin in France. Two sub-regions are highlighted. A downstream zone

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  12. The Effects of Rainfall Inhomogeneity on Climate Variability of Rainfall Estimated from Passive Microwave Sensors

    NASA Technical Reports Server (NTRS)

    Kummerow, Christian; Poyner, Philip; Berg, Wesley; Thomas-Stahle, Jody

    2007-01-01

    Passive microwave rainfall estimates that exploit the emission signal of raindrops in the atmosphere are sensitive to the inhomogeneity of rainfall within the satellite field of view (FOV). In particular, the concave nature of the brightness temperature (T(sub b)) versus rainfall relations at frequencies capable of detecting the blackbody emission of raindrops cause retrieval algorithms to systematically underestimate precipitation unless the rainfall is homogeneous within a radiometer FOV, or the inhomogeneity is accounted for explicitly. This problem has a long history in the passive microwave community and has been termed the beam-filling error. While not a true error, correcting for it requires a priori knowledge about the actual distribution of the rainfall within the satellite FOV, or at least a statistical representation of this inhomogeneity. This study first examines the magnitude of this beam-filling correction when slant-path radiative transfer calculations are used to account for the oblique incidence of current radiometers. Because of the horizontal averaging that occurs away from the nadir direction, the beam-filling error is found to be only a fraction of what has been reported previously in the literature based upon plane-parallel calculations. For a FOV representative of the 19-GHz radiometer channel (18 km X 28 km) aboard the Tropical Rainfall Measuring Mission (TRMM), the mean beam-filling correction computed in this study for tropical atmospheres is 1.26 instead of 1.52 computed from plane-parallel techniques. The slant-path solution is also less sensitive to finescale rainfall inhomogeneity and is, thus, able to make use of 4-km radar data from the TRMM Precipitation Radar (PR) in order to map regional and seasonal distributions of observed rainfall inhomogeneity in the Tropics. The data are examined to assess the expected errors introduced into climate rainfall records by unresolved changes in rainfall inhomogeneity. Results show that global

  13. Simulation of Rainfall Variability Over West Africa

    NASA Astrophysics Data System (ADS)

    Bader, J.; Latif, M.

    The impact of sea surface temperature (SST) and vegetation on precipitation over West Africa is investigated with the atmospheric general circulation model ECHAM4.x/T42. Ensemble experiments -driven with observed SST- show that At- lantic SST has a significant influence on JJA precipitation over West Africa. Four- teen experiments were performed in which the climatological SST was enhanced or decreased by one Kelvin in certain ocean areas. Changing SST in the eastern tropi- cal Atlantic only caused significant changes along the Guinea Coast, with a positive SSTA increasing rainfall and a negative reducing it. The response was nearly linear. Changing SST in other ocean areas caused significant changes over West Africa, es- pecially 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. Four simulations with a coupled model (the simple dynamic vegetation model (SVege) and the ECHAM4-AGCM were coupled) were also performed, driven with observed SST from 1945 to 1998. The standard ECHAM-AGCM -forced by the same observed SST- was able to reproduce the drying trend from the fifties to the mid-eighties in the Sahel, but failed to mirror the magnitude of the rainfall anomalies. The coupled model was not only able to reproduce this drying trend, but was also able to better reproduce the amplitudes of the rainfall anomalies. The dynamic vegetation acted like an amplifier, increasing the SST induced rainfall anomalies.

  14. Weak linkage between the heaviest rainfall and tallest storms

    PubMed Central

    Hamada, Atsushi; Takayabu, Yukari N.; Liu, Chuntao; Zipser, Edward J.

    2015-01-01

    Conventionally, the heaviest rainfall has been linked to the tallest, most intense convective storms. However, the global picture of the linkage between extreme rainfall and convection remains unclear. Here we analyse an 11-year record of spaceborne precipitation radar observations and establish that a relatively small fraction of extreme convective events produces extreme rainfall rates in any region of the tropics and subtropics. Robust differences between extreme rainfall and convective events are found in the rainfall characteristics and environmental conditions, irrespective of region; most extreme rainfall events are characterized by less intense convection with intense radar echoes not extending to extremely high altitudes. Rainfall characteristics and environmental conditions both indicate the importance of warm-rain processes in producing extreme rainfall rates. Our results demonstrate that, even in regions where severe convective storms are representative extreme weather events, the heaviest rainfall events are mostly associated with less intense convection. PMID:25708295

  15. Weak linkage between the heaviest rainfall and tallest storms.

    PubMed

    Hamada, Atsushi; Takayabu, Yukari N; Liu, Chuntao; Zipser, Edward J

    2015-01-01

    Conventionally, the heaviest rainfall has been linked to the tallest, most intense convective storms. However, the global picture of the linkage between extreme rainfall and convection remains unclear. Here we analyse an 11-year record of spaceborne precipitation radar observations and establish that a relatively small fraction of extreme convective events produces extreme rainfall rates in any region of the tropics and subtropics. Robust differences between extreme rainfall and convective events are found in the rainfall characteristics and environmental conditions, irrespective of region; most extreme rainfall events are characterized by less intense convection with intense radar echoes not extending to extremely high altitudes. Rainfall characteristics and environmental conditions both indicate the importance of warm-rain processes in producing extreme rainfall rates. Our results demonstrate that, even in regions where severe convective storms are representative extreme weather events, the heaviest rainfall events are mostly associated with less intense convection. PMID:25708295

  16. Weak linkage between the heaviest rainfall and tallest storms

    NASA Astrophysics Data System (ADS)

    Hamada, Atsushi; Takayabu, Yukari N.; Liu, Chuntao; Zipser, Edward J.

    2015-02-01

    Conventionally, the heaviest rainfall has been linked to the tallest, most intense convective storms. However, the global picture of the linkage between extreme rainfall and convection remains unclear. Here we analyse an 11-year record of spaceborne precipitation radar observations and establish that a relatively small fraction of extreme convective events produces extreme rainfall rates in any region of the tropics and subtropics. Robust differences between extreme rainfall and convective events are found in the rainfall characteristics and environmental conditions, irrespective of region; most extreme rainfall events are characterized by less intense convection with intense radar echoes not extending to extremely high altitudes. Rainfall characteristics and environmental conditions both indicate the importance of warm-rain processes in producing extreme rainfall rates. Our results demonstrate that, even in regions where severe convective storms are representative extreme weather events, the heaviest rainfall events are mostly associated with less intense convection.

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

    PubMed

    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. PMID:24672332

  18. Analysis of Rainfall Infiltration Law in Unsaturated Soil Slope

    PubMed Central

    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. PMID:24672332

  19. Tropical Rainfall Measurement Mission (TRMM) Operation Summary

    NASA Technical Reports Server (NTRS)

    Nio, Tomomi; Saito, Susumu; Stocker, Erich; Pawloski, James H.; Murayama, Yoshifumi; Ohata, Takeshi

    2015-01-01

    The Tropical Rainfall Measurement Mission (TRMM) is a joint U.S. and Japan mission to observe tropical rainfall, which was launched by H-II No. 6 from Tanegashima in Japan at 6:27 JST on November 28, 1997. After the two-month commissioning of TRMM satellite and instruments, the original nominal mission lifetime was three years. In fact, the operations has continued for approximately 17.5 years. This paper provides a summary of the long term operations of TRMM.

  20. Influences of vegetationand rainfall patterns on scaling in Hortonian rainfall-runoff processes

    NASA Astrophysics Data System (ADS)

    Chen, L.; Sela, S.; Svoray, T.; Assouline, S.

    2015-12-01

    The Hortonian rainfall-runoff process is a critical player for ecosystem in semi-arid regions. It has long been recognized that this process is scale dependent, which may have fundamental impact on water resources distribution and ecosystem sustainability in these regions. Recent studies have disclosed complex feedbacks between rainfall, vegetation patches, microtopography and layered soil characteristics in semi-arid ecosystems. The interactions, however, may also affect the scaling of the process. To quantitatively study the impact of vegetation and rainfall properties on the scaling of the rainfall-runoff process, a modeling approach coupling a two-dimensional surface runoff model and a two-layer conceptual infiltration model was employed. Having been validated in a semi-arid field plot in the Lehavim LTER in Southern Israel, the model was applied to a series of plots of varying scales with statistically identical distributions of land surface properties to examine the vegetation and rainfall impact. The approach provides a basis of comparison for the hydrological responses at various scales. Influences of regular and random vegetation patterns were compared with the Monte Carlo simulation approach. Also examined are the influences of rainfall intensity and rainfall temporal variability. Results show that these impacting factors affect the spatial distribution of infiltration, local as well as global runoff generation at all scales. All these factors affect the scale dependence of Hortonian runoff, while the trends of the scaling laws are expected to maintain.

  1. Rainfall and runoff variability in Ethiopia

    NASA Astrophysics Data System (ADS)

    Billi, Paolo; Fazzini, Massimiliano; Tadesse Alemu, Yonas; Ciampalini, Rossano

    2014-05-01

    Rainfall and river flow variability have been deeply investigated and and the impact of climate change on both is rather well known in Europe (EEA, 2012) or in other industrialized countries. Reports of international organizations (IPCC, 2012) and the scientific literature provide results and outlooks that were found contrasting and spatially incoherent (Manton et al., 2001; Peterson et al., 2002; Griffiths et al., 2003; Herath and Ratnayake, 2004) or weakened by limitation of data quality and quantity. According to IPCC (2012), in East Africa precipitation there are contrasting regional and seasonal variations and trends, though Easterling et al. (2000) and Seleshi and Camberlin (2006) report decreasing trends in heavy precipitation over parts of Ethiopia during the period 1965-2002. Literature on the impact of climate change on river flow is scarce in Africa and IPCC Technical Paper VI (IPCC, 2008) concluded that no evidence, based on instrumental records, has been found for a climate-driven globally widespread change in the magnitude/frequency of floods during the last decades (Rosenzweig et al., 2007), though increases in runoff and increased risk of flood events in East Africa are expected. Some papers have faced issues regarding rainfall and river flow variability in Ethiopia (e.g. Seleshi and Demaree, 1995; Osman and Sauerborn, 2002; Seleshi and Zanke, 2004; Meze-Hausken, 2004; Korecha and Barnston, 2006; Cheung et al., 2008) but their investigations are commonly geographically limited or used a small number of rain and flow gauges with the most recent data bound to the beginning of the last decade. In this study an attempt to depict rainfall and river flow variability, considering the longer as possible time series for the largest as possible number of meteo-stations and flow gauge evenly distributed across Ethiopia, is presented. 25 meteo-stations and 21 flow gauges with as much as possible continuous data records were selected. The length of the time

  2. Influence of rainfall spatial variability on rainfall-runoff modelling: Benefit of a simulation approach?

    NASA Astrophysics Data System (ADS)

    Emmanuel, I.; Andrieu, H.; Leblois, E.; Janey, N.; Payrastre, O.

    2015-12-01

    No consensus has yet been reached regarding the influence of rainfall spatial variability on runoff modelling at catchment outlets. To eliminate modelling and measurement errors, in addition to controlling rainfall variability and both the characteristics and hydrological behaviour of catchments, we propose to proceed by simulation. We have developed a simulation chain that combines a stream network model, a rainfall simulator and a distributed hydrological model (with four production functions and a distributed transfer function). Our objective here is to use this simulation chain as a simplified test bed in order to better understand the impact of the spatial variability of rainfall forcing. We applied the chain to contrasted situations involving catchments ranging from a few tens to several hundreds of square km2, thus corresponding to urban and peri-urban catchments for which surface runoff constitutes the dominant process. The results obtained confirm that the proposed simulation approach is helpful to better understand the influence of rainfall spatial variability on the catchment response. We have shown that significant dispersion exists not only between the various simulation scenarios (defined by a rainfall configuration and a catchment configuration), but also within each simulation scenario. These results show that the organisation of rainfall during the study event over the study catchment plays an important role, leading us to examine rainfall variability indexes capable of summarising the influence of rainfall spatial organisation on the catchment response. Thanks to the simulation chain, we have tested the variability indexes of Zoccatelli et al. (2010) and improved them by proposing two other indexes.

  3. Impact of uncertainty in rainfall estimation on the identification of rainfall thresholds for debris flow occurrence

    NASA Astrophysics Data System (ADS)

    Nikolopoulos, Efthymios I.; Borga, Marco; Crema, Stefano; Marchi, Lorenzo; Marra, Francesco; Guzzetti, Fausto

    2014-05-01

    Estimation of rainfall intensity-duration thresholds, used for the identification of debris flows/landslides triggering rainfall events, has been traditionally based on raingauge observations. The main drawback of using information from gauges is that rainfall estimates are available only over gauge locations, which are usually located far away from the debris flow/landslide initiation areas. Thus, successful implementation of gauge-based rainfall thresholds involves the intrinsic assumption that rainfall over gauge and actual initiation point is highly correlated. However, in complex terrain where this natural hazard takes place, spatial variability of rainfall can be very high even at very small scales due to orographic enhancement of precipitation and the development of highly localized convective systems. This work is focused on the assessment of the impact of rainfall estimation uncertainty on identification and use of rainfall thresholds for debris flow occurrence. The Upper Adige river basin, northern Italy, is the area of study. A detailed database of more than 400 identified debris flows during period 2000-2010 and a raingauge network of 95 stations, is used for this work. The methodology examines the intensity-duration thresholds derived from a set of raingauge locations that is assumed to be collocated with debris flow/landslide points (DFR) and an equivalent set of raingauges assumed to have the role of closest available measurement (MR). Comparison between the rainfall thresholds derived from DFR and MR, revealed that uncertainty in rainfall estimation has a major impact on estimated intensity-duration thresholds. Specifically, results showed that thresholds estimated from MR observations are consistently underestimated. Evaluation of the estimated thresholds for warning procedures showed that while detection is high, the main issue is the high false alarm ratio, which limits the overall accuracy of the procedure. Overall performance on debris flow

  4. Water Conservation Education with a Rainfall Simulator.

    ERIC Educational Resources Information Center

    Kok, Hans; Kessen, Shelly

    1997-01-01

    Describes a program in which a rainfall simulator was used to promote water conservation by showing water infiltration, water runoff, and soil erosion. The demonstrations provided a good background for the discussion of issues such as water conservation, crop rotation, and conservation tillage practices. The program raised awareness of…

  5. Effect of Rainfall Aggregation on Hydrologic Predictions

    NASA Astrophysics Data System (ADS)

    Sharif, H.; Brandes, E.

    2003-12-01

    Remotely sensed soil moisture data are becoming increasingly available, however the variability within the remotely sensed footprint is spatially averaged. The representation of spatial heterogeneity of soil moisture is essential for modeling processes that are nonlinearly related to soil moisture, such as the partitioning of sensible and latent heat fluxes. A number of studies have suggested that the spatial variability of soil moisture varies with wetness. At different locations, scales, and wetting and drying conditions, soil moisture patterns have been linked to topography, soil characteristics such as porosity and wilting point, and rainfall distribution. The objective of the proposed study is to examine the effects of rainfall temporal and spatial aggregation on spatial variability of soil moisture and runoff predictions on a 1000-km2 watershed. High-resolution radar-estimated rainfall from the IHOP2002 experiment will be used. These rain fields are aggregated in space and time. The hydrologic response of a distributed hydrologic model to the aggregated rain fields will be statistically compared with the response of the model to the original rainfall fields to quantify the impact of the spatial and temporal aggregation on hydrologic predictions. The proposed procedure will combine information from these simulations to determine what adjustments need to be made to the predicted fluxes.

  6. Rainfall erosivity in Brazil: A Review

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this paper, we review the erosivity studies conducted in Brazil to verify the quality and representativeness of the results generated and to provide a greater understanding of the rainfall erosivity (R-factor) in Brazil. We searched the ISI Web of Science, Scopus, SciELO, and Google Scholar datab...

  7. URBAN RAINFALL-RUNOFF-QUALITY DATA BASE

    EPA Science Inventory

    Urban rainfall-runoff-quality data gathered by others have been assembled on a storm event basis for one or more catchments in the following eight cities: San Francisco, CA; Broward County, FL; Lincoln, NB; Durham, NC; Windsor, ONT; Lancaster, PA; Seattle, WA; and Racine, WI. Rai...

  8. Comparison of radar data versus rainfall data.

    PubMed

    Espinosa, B; Hromadka, T V; Perez, R

    2015-01-01

    Doppler radar data are increasingly used in rainfall-runoff synthesis studies, perhaps due to radar data availability, among other factors. However, the veracity of the radar data are often a topic of concern. In this paper, three Doppler radar outcomes developed by the United States National Weather Service at three radar sites are examined and compared to actual rain gage data for two separate severe storm events in order to assess accuracy in the published radar estimates of rainfall. Because the subject storms were very intense rainfall events lasting approximately one hour in duration, direct comparisons between the three radar gages themselves can be made, as well as a comparison to rain gage data at a rain gage location subjected to the same storm cells. It is shown that topographic interference with the radar outcomes can be a significant factor leading to differences between radar and rain gage readings, and that care is needed in calibrating radar outcomes using available rain gage data in order to interpolate rainfall estimates between rain gages using the spatial variation observed in the radar readings. The paper establishes and describes•the need for "ground-truthing" of radar data, and•possible errors due to topographic interference. PMID:26649276

  9. Mini rainfall simulation for assessing soil erodibility

    NASA Astrophysics Data System (ADS)

    Peters, Piet; Palese, Dina; Baartman, Jantiene

    2016-04-01

    The mini rainfall simulator is a small portable rainfall simulator to determine erosion and water infiltration characteristics of soils. The advantages of the mini rainfall simulator are that it is suitable for soil conservation surveys and light and easy to handle in the field. Practical experience over the last decade has shown that the used 'standard' shower is a reliable method to assess differences in erodibility due to soil type and/or land use. The mini rainfall simulator was used recently in a study on soil erosion in olive groves (Ferrandina-Italy). The propensity to erosion of a steep rain-fed olive grove (mean slope ~10%) with a sandy loam soil was evaluated by measuring runoff and sediment load under extreme rain events. Two types of soil management were compared: spontaneous grass as a ground cover (GC) and tillage (1 day (T1) and 10 days after tillage (T2)). Results indicate that groundcover reduced surface runoff to approximately one-third and soil-losses to zero compared with T1. The runoff between the two tilled plots was similar, although runoff on T1 plots increased steadily over time whereas runoff on T2 plots remained stable.

  10. Comparison of radar data versus rainfall data

    PubMed Central

    Espinosa, B.; Hromadka, T.V.; Perez, R.

    2015-01-01

    Doppler radar data are increasingly used in rainfall-runoff synthesis studies, perhaps due to radar data availability, among other factors. However, the veracity of the radar data are often a topic of concern. In this paper, three Doppler radar outcomes developed by the United States National Weather Service at three radar sites are examined and compared to actual rain gage data for two separate severe storm events in order to assess accuracy in the published radar estimates of rainfall. Because the subject storms were very intense rainfall events lasting approximately one hour in duration, direct comparisons between the three radar gages themselves can be made, as well as a comparison to rain gage data at a rain gage location subjected to the same storm cells. It is shown that topographic interference with the radar outcomes can be a significant factor leading to differences between radar and rain gage readings, and that care is needed in calibrating radar outcomes using available rain gage data in order to interpolate rainfall estimates between rain gages using the spatial variation observed in the radar readings. The paper establishes and describes•the need for “ground-truthing” of radar data, and•possible errors due to topographic interference. PMID:26649276

  11. Coastal Rainfall Estimation using AMSR-E

    NASA Astrophysics Data System (ADS)

    McCollum, J.; Ferraro, R.

    2003-12-01

    The vast majority of microwave rainfall estimation research has been for either ocean-filled or land-filled fields of view, as the physics for both surface types are quite different. However, neither ocean-based nor land-based methods may be used for coastal pixels that contain a mixture of water and land. Current algorithms for coastal regions perform relatively poorly. We have built upon previous coastal rainfall algorithms developed for the Special Sensor Microwave/Imager (SSM/I) and TRMM Microwave Imager (TMI). Using principal component analysis, we found multi-frequency brightness temperature responses to rainfall over coastal regions, enabling us to do a more accurate rain/no-rain classification. The TMI has similar frequencies and resolutions as AMSR-E, so we could use the co-located TMI and Precipitation Radar (PR) data to determine the principal components related to rainfall. These principal components are effective in distinguishing rain from no-rain AMSR-E pixels, as we show with AMSR-E data. We include global results as well as those from the Eureka, CA, coastal radar AMSR-E validation site.

  12. Real-time radar rainfall estimation

    NASA Astrophysics Data System (ADS)

    Anagnostou, Emmanouil Nikolaos

    1997-08-01

    This research reports on several aspects of real-time monitoring of the spatial and temporal distribution of rainfall from ground-based weather radar. Optimization of the performance of the National Weather Service's Precipitation Processing Subsystem (PPS) is the first objective. This is achieved by developing a calibration procedure which simultaneously estimates the optimal parameter values by providing a global assessment of the system's performance. Evaluation of the system is based on a data set consisting of two months of radar reflectivity measurements, and hourly raingage rainfall accumulations, from the Melbourne, Florida WSR-88D site. Radar-raingage root mean square (RMS) difference reduction up to 20% with respect to the default system parameter values is demonstrated. Investigation of statistical procedures for real-time adjustment of the mean-field systematic radar rainfall error is the second objective. For this purpose, a data- based Monte Carlo simulation experiment is performed. The study uses an extensive data set of hourly radar rainfall products and raingage accumulations from the Tulsa, Oklahoma WSR-88D site. This intercomparison study concluded to a bias procedure which overall appeared to perform better than the other. The main results from this research are: (1) statistical methods with optimal error model parameters perform significantly better than using only bias observations, and (2) bias adjustment is mostly effective in cold season precipitation measurements. Final objective of this research is development of a new real-time radar rainfall estimation algorithm. The new processing steps introduced in this algorithm are beam- height effect correction, vertical integration, rain classification, and continuous range effect correction. Additionally, the algorithm applies advection correction at the gridded rainfall rates to minimize the temporal sampling effect, and its calibration is cast in a recursive formulation with parameters

  13. Mapping Rainfall Trends in Hawai';i

    NASA Astrophysics Data System (ADS)

    Frazier, A. G.; Giambelluca, T. W.

    2013-12-01

    Spatial patterns of rainfall in Hawai';i are among the most diverse in the world; ranges on a single island rival those of continents. As the climate warms, it is essential to understand how rainfall has changed so that we can better understand possible future climate changes. This is especially important in a small island context where resources are limited, and understanding the potential impacts of climate change on freshwater supplies is crucial. Utilizing Hawai';i's extensive network of rain gauges (over 2,000 stations have operated since the mid-1800s), data screening, homogeneity testing, and gap filling were performed to produce a serially complete dataset for as many stations as possible. This dataset was used to develop a set of month-year rainfall maps for Hawai';i from 1920-2007. Maps of rainfall values and anomalies (departures from the most recent 30-year mean) were derived for all major Hawaiian Islands at a 250 m resolution. Using this time series of maps, linear trends for the entire period (1920-2007) and the most recent 30-year period available (1978-2007) and the corresponding significance levels (p-values) were calculated at every pixel across the state, accounting for the effects of autocorrelation, for each month and each 3- and 6-month season. These trends and p-values were then mapped to produce spatially continuous trend maps of Hawai';i. The results show drying trends on all islands, with Hawai';i island experiencing the largest significant long-term declines annually (island mean percent change of -1.39% per decade since 1920) and Maui island experiencing the largest short-term declines annually (-8.10% per decade change since 1978). The seasonal analysis reveals that the largest changes are seen in winter and summer months (clear drying trends on all islands), while spring and fall seasons experience more neutral or positive changes (fewer significant trends). Most of the significant declines in long-term winter rainfall are seen in the

  14. Soil erosion dynamics through multiple rainfall events

    NASA Astrophysics Data System (ADS)

    Jomaa, S.; Barry, D. A.; Brovelli, A.; Heng, B. P.; Parlange, J.

    2012-12-01

    The dynamics of soil erosion during repeated rainfall events was studied, in particular focusing on the effect of initial soil characteristics and surface shielding by rock fragments. A sequence of four 2-h erosive events (named H7- E1, E2, and E3, respectively) separated by 22 h of air drying was performed using a 6-m long laboratory rainfall simulator and erosion flume. A loamy soil was used in all experiments. The surface was hand cultivated before the first event. Rainfall intensities of 28, 74, 74 and 28 mm h-1 were considered. The erosion flume was divided into two identical 1-m wide sections, one of which was covered with rock fragments. Results showed that steady-state behavior is mainly controlled by the rainfall intensity. Soil initial conditions, in particular whether steady state was reached during the previous event, control the sediment yields during the initial transient phase of the erosive event. If quasi-steady behavior was reached for a particular sediment size class, that class's effluent concentration peaked rapidly in the next rainfall event, then declined gradually to its steady-state value. In contrast, if the sediment concentrations were still varying at the end of a rainfall event, the subsequent event produced effluent concentrations that increased gradually to steady state. The surface rock fragments reduced the time needed to achieve the steady state, compared to bare soil conditions. The Hairsine and Rose erosion model was adopted to analyze the measured sediment delivery. A satisfactory comparison was observed for the two experiments in which the soil was only slightly modified by raindrop impact (H7-E3 and H7-E4). On the contrary, the model could not predict accurately the erosion yields of the first two rainfall events (H7-E1 and H7-E2), during which the soil surface was heavily compacted and a surface seal developed. Furthermore, the model could not reproduce in detail the sediment concentrations of the individual size classes

  15. Probabilistic forecasts based on radar rainfall uncertainty

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    The potential advantages resulting from integrating weather radar rainfall estimates in hydro-meteorological forecasting systems is limited by the inherent uncertainty affecting radar rainfall measurements, which is due to various sources of error [1-3]. The improvement of quality control and correction techniques is recognized to play a role for the future improvement of radar-based flow predictions. However, the knowledge of the uncertainty affecting radar rainfall data can also be effectively used to build a hydro-meteorological forecasting system in a probabilistic framework. This work discusses the results of the implementation of a novel probabilistic forecasting system developed to improve ensemble predictions over a small urban area located in the North of England. An ensemble of radar rainfall fields can be determined as the sum of a deterministic component and a perturbation field, the latter being informed by the knowledge of the spatial-temporal characteristics of the radar error assessed with reference to rain-gauges measurements. This approach is similar to the REAL system [4] developed for use in the Southern-Alps. The radar uncertainty estimate can then be propagated with a nowcasting model, used to extrapolate an ensemble of radar rainfall forecasts, which can ultimately drive hydrological ensemble predictions. A radar ensemble generator has been calibrated using radar rainfall data made available from the UK Met Office after applying post-processing and corrections algorithms [5-6]. One hour rainfall accumulations from 235 rain gauges recorded for the year 2007 have provided the reference to determine the radar error. Statistics describing the spatial characteristics of the error (i.e. mean and covariance) have been computed off-line at gauges location, along with the parameters describing the error temporal correlation. A system has then been set up to impose the space-time error properties to stochastic perturbations, generated in real-time at

  16. Postwildfire debris-flow hazard assessment of the area burned by the 2013 West Fork Fire Complex, southwestern Colorado

    USGS Publications Warehouse

    Verdin, Kristine L.; Dupree, Jean A.; Stevens, Michael R.

    2013-01-01

    This report presents a preliminary emergency assessment of the debris-flow hazards from drainage basins burned by the 2013 West Fork Fire Complex near South Fork in southwestern Colorado. Empirical models derived from statistical evaluation of data collected from recently burned basins throughout the intermountain western United States were used to estimate the probability of debris-flow occurrence, potential volume of debris flows, and the combined debris-flow hazard ranking along the drainage network within and just downstream from the burned area, and to estimate the same for 54 drainage basins of interest within the perimeter of the burned area. Input data for the debris-flow models included topographic variables, soil characteristics, burn severity, and rainfall totals and intensities for a (1) 2-year-recurrence, 1-hour-duration rainfall, referred to as a 2-year storm; (2) 10-year-recurrence, 1-hour-duration rainfall, referred to as a 10-year storm; and (3) 25-year-recurrence, 1-hour-duration rainfall, referred to as a 25-year storm. Estimated debris-flow probabilities at the pour points of the 54 drainage basins of interest ranged from less than 1 to 65 percent in response to the 2-year storm; from 1 to 77 percent in response to the 10-year storm; and from 1 to 83 percent in response to the 25-year storm. Twelve of the 54 drainage basins of interest have a 30-percent probability or greater of producing a debris flow in response to the 25-year storm. Estimated debris-flow volumes for all rainfalls modeled range from a low of 2,400 cubic meters to a high of greater than 100,000 cubic meters. Estimated debris-flow volumes increase with basin size and distance along the drainage network, but some smaller drainages also were predicted to produce substantial debris flows. One of the 54 drainage basins of interest had the highest combined hazard ranking, while 9 other basins had the second highest combined hazard ranking. Of these 10 basins with the 2 highest

  17. Changing rainfall and humidity within Southeast Texas.

    PubMed

    Smith, Robert Kennedy

    2015-01-01

    Southeast Texas houses a precipitation transition zone between drier conditions to the North and West and some of the wettest parts of the continental U.S. to the East. The Region has seen an increase in its reported normal annual precipitation totals in recent decades. In order to determine if the additional rainfall has been influenced by warming temperatures or is within the variability of the State's long-term drought cycles, several analyses were performed on historical climate data. The analyses answered several questions: Have global and regional climate change models predicted precipitation increases in Southeast Texas and are future increases expected? Do historical monthly precipitation totals at various sites in the region provide clear trends of wetter conditions that can be discerned from long-term drought cycles? Are rainfall patterns changing with less frequent, heavier rain events? Do the reported increases in annual rainfall actually lead to wetter conditions in the region? Climate models have not predicted larger annual average precipitation totals nor do they forecast increases for Southeast Texas. While recent decades may have seen more rain relative to earlier periods, a combined analysis of observation stations across different parts of the Region shows that long-term trends are dependent on when the data is selected relative to a drought cycle. While some stations show larger amounts of rain falling during fewer days, these trends do not hold across all periods. An examination of hourly data does not show an increase in extreme rainfall events or a decrease in the number of hours during which rain has fallen. Even though rainfall has not decreased, average relative humidity has fallen. This suggests that the area is drying even with steady or increasing amounts of rain. PMID:26322255

  18. Deforestation alters rainfall: a myth or reality

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  19. Neyman-Scott cluster model for daily rainfall processes in lower extremadura (Spain): Rainfall Generating Mechanisms

    NASA Astrophysics Data System (ADS)

    Marroquin, A.; Garcia, J. A.; Garrido, J.; Mateos, V. L.

    1995-09-01

    A Neyman-Scott cluster model was fitted to the daily rainfall data recorded at the observatory of Badajoz (southwestern Spain) for the period 1901 1990. The data were previously homogenized. The goodness of the fit that indicated the daily rainfall process follows some Rainfall Generating Mechanism (RGM). Having decided on the criteria that a block of rainfall must fulfill to be considered as a RGM, a method was proposed to classify the days that belong to RGMs according to the 500 hPa and the surface topography. In this method each day is characterized by a string of 22 alphanumeric characters. From the subsequent analysis, the structure of the synoptic patterns associated with each RGM was deduced.

  20. Observed and NWP simulated rainfall uncertainty cascading into rainfall-runoff and flood inundation impact models

    NASA Astrophysics Data System (ADS)

    Souvignet, M.; Freer, J. E.; de Almeida, G. A.; Coxon, G.; Neal, J. C.; Champion, A.; Cloke, H. L.; Bates, P. D.

    2013-12-01

    Observed and numerical weather prediction (NWP) simulated precipitation products typically show differences in their spatial and temporal distribution. These differences can considerably influence the ability to predict hydrological responses. For flood inundation impact studies, as in forecast situations, an atmospheric-hydrologic-hydraulic model chain is needed to quantify the extent of flood risk. Uncertainties cascaded through the model chain are seldom explored, and more importantly, how potential input uncertainties propagate through this cascade is still poorly understood. Such a project requires a combination of modelling capabilities, the non-linear transformation of rainfall to river flow using rainfall-runoff models, and hydraulic flood wave propagation based on the runoff predictions. Accounting for uncertainty in each component is important for quantifying impacts and understanding flood risk for different return periods. In this paper, we propose to address this issue by i) exploring the effects of errors in rainfall on inundation predictive capacity within an uncertainty framework by testing inundation uncertainty against different comparable meteorological conditions (i.e. using different rainfall products) and ii) testing different techniques to cascade uncertainties (e.g. bootstrapping, PPU envelope) within the GLUE (generalised likelihood uncertainty estimation) framework. Our method cascades rainfall uncertainties into multiple rainfall-runoff model structures as part of the Framework for Understanding Structural Errors (FUSE). The resultant prediction uncertainties in upstream discharge provide uncertain boundary conditions which are cascaded into a simplified shallow water hydraulic model (LISFLOOD-FP). Rainfall data captured by three different measurement techniques - rain gauges, gridded radar data and numerical weather predictions (NWP) models are evaluated. The study is performed in the Severn catchment over summer 2007, where a series of

  1. Rainfall and Flood Frequency Analysis Using High-Resolution Radar Rainfall Fields and Stochastic Storm Transposition

    NASA Astrophysics Data System (ADS)

    Wright, Daniel; Smith, James; Baeck, Mary Lynn

    2013-04-01

    Spatial and temporal variability of rainfall fields, and their interactions with surface, subsurface, and drainage network properties, are important drivers of flood response. 'Design storms,' which are commonly used for flood risk assessment, however, are assumed to be uniform in space and either uniform or highly idealized in time. The impacts of these and other common assumptions on estimates of flood risk are poorly understood. We present an alternative framework for flood risk assessment based on stochastic storm transposition (SST). In this framework, "storm catalogs" are derived from a ten-year high-resolution (15-minute, 1 km2) bias-corrected radar rainfall dataset for the region surrounding Charlotte, North Carolina, USA. SST-based rainfall frequency analyses are developed by resampling from these storm catalogs to synthesize the regional climatology of extreme rainfall. SST-based intensity-frequency-duration (IFD) estimates are driven by the spatial and temporal rainfall variability from weather radar observations, are specifically tailored to the chosen catchment, and do not require simplifying assumptions of storm structure. We are able to use the SST procedure to reproduce IFD estimates from conventional methods for small urban catchments in Charlotte. We further demonstrate that extreme rainfall can vary substantially in time and in space, with important flood risk implications that cannot be assessed using conventional techniques. When coupled with a physics-based distributed hydrologic model, the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model, SST enables us to examine the full impact of spatial and temporal rainfall variability on flood response and flood frequency. The interactions of extreme rainfall with spatially distributed land use, soil properties, and stormwater management infrastructure are assessed for several nested urban catchments in Charlotte. Results suggest that these interactions, which cannot be fully accounted for

  2. TRMM (Tropical Rainfall Measuring Mission): A satellite mission to measure tropical rainfall

    NASA Technical Reports Server (NTRS)

    Simpson, Joanne (Editor)

    1988-01-01

    The Tropical Rainfall Measuring Mission (TRMM) is presented. TRMM is a satellite program being studied jointly by the United States and Japan which would carry out the systematic study of tropical rainfall required for major strides in weather and climate research. The scientific justification for TRMM is discussed. The implementation process for the scientific community, NASA management, and the other decision-makers and advisory personnel who are expected to evaluate the priority of the project is outlined.

  3. NASA Sees Heavy Rainfall, Hot Towers in Tropical Cyclone Nathan

    NASA Video Gallery

    NASA-JAXA's Tropical Rainfall Measuring Mission or TRMM satellite showed that the heaviest rainfall occurring in Tropical Cyclone Nathan on March 18 at 0758 UTC (3:58 a.m. EDT) was falling at a rat...

  4. The Climatology of Extreme Rainfall in the Eastern US (Invited)

    NASA Astrophysics Data System (ADS)

    Smith, J. A.; Baeck, M. L.; Yeung, J. K.; Villarini, G.; Krajewski, W. F.

    2009-12-01

    Recent studies have shown that flood peak distributions in the eastern US can be represented through mixtures of flood generating mechanisms, including landfalling tropical cyclones, extratropical cyclones and organized convective systems. The eastern US is a complex setting for examining rainfall climatology, with land-ocean boundaries, mountainous terrain and the urban megalopolis all playing important roles in controlling rainfall distribution. In this study we examine the dynamics of extreme rainfall in the eastern US through a combination of observational analyses and numerical modeling studies. Observational analyses utilize long records of high-resolution rainfall fields from the Hydro-NEXRAD system. We also utilize observational resources from the Princeton environmental sensor network, including a network of rain gages and disdrometer, to examine rainfall microstructure. Numerical model studies are based on the Weather Research and Forecasting (WRF) model. In addition to rainfall microstructure, analyses focus on spatial heterogeneities of rainfall associated with land surface processes and the diurnal cycle of warm season rainfall.

  5. IMERG Shows Rainfall Totals Over the Philippines from Melor

    NASA Video Gallery

    The highest rainfall totals during this five day period were still found along the typhoon's path in the central Philippines where rainfall totals were now measured by IMERG at over 899 mm (35.4 in...

  6. Unusually Heavy Rainfall and Flooding in Great Britain

    NASA Video Gallery

    Desmond's unusually heavy rainfall resulted in wide spread damaging floods. Data from NASA's Integrated Multi-satellitE Retrievals for GPM (IMERG) were used to estimate rainfall for the period from...

  7. TRMM Sees Rainfall Totals from Tropical Cyclone Guito

    NASA Video Gallery

    This animation of rainfall gathered from February 11-19, 2014 by NASA's TRMM satellite revealed that Tropical Cyclone Guito produced as much as 16.9 inches/430 mm of rainfall in the center of the M...

  8. GPM Shows Large Rainfall Totals from Typhoon Dujuan

    NASA Video Gallery

    GPM showed that Taiwan's heaviest rainfall totals of over 275 mm (10.8 inches) were located along the coast south of where Typhoon Dujuan made landfall. The highest rainfall totals were found over ...

  9. Rainfall Totals from the Tropical Cyclones Passing Over Philippines

    NASA Video Gallery

    Rainfall totals from the TRMM satellite of all tropical cyclones that passed through the Philippines from January through November 11, 2013. Red indicated areas where rainfall totals were greater t...

  10. A new look at rainfall fluctuations and scaling properties of spatial rainfall using orthogonal wavelets

    NASA Technical Reports Server (NTRS)

    Kumar, Praveen; Foufoula-Georgiou, Efi

    1993-01-01

    It has been observed that the finite-dimensional distribution functions of rainfall cannot obey simple scaling laws due to rainfall intermittency (mixed distribution with an atom at zero) and the probability of rainfall being an increasing function of area. Although rainfall fluctuations do not suffer these limitations, it is interesting to note that very few attempts have been made to study them in terms of their self-similarity characteristics. This is due to the lack of unambiguous definition of fluctuations in multidimensions. This paper shows that wavelet transforms offer a convenient and consistent method for the decomposition of inhomogeneous and anisotropic rainfall fields in two dimensions and that the components of this decomposition can be looked at as fluctuations of the rainfall field. It is also shown that under some mild assumptions, the component fields can be treated as homogeneous and thus are amenable to second-order analysis, which can provide useful insight into the nature of the process. The fact that wavelet transforms are a space-scale method also provides a convenient tool to study scaling characteristics of the process. Orthogonal wavelets are used, and these properties are investigated for a squall-line storm to study the presence of self-similarity.

  11. Tropical Rainfall Measuring Mission (TRMM) and the Future of Rainfall Estimation from Space

    NASA Technical Reports Server (NTRS)

    Kakar, Ramesh; Adler, Robert; Smith, Eric; Starr, David OC. (Technical Monitor)

    2001-01-01

    Tropical rainfall is important in the hydrological cycle and to the lives and welfare of humans. Three-fourths of the energy that drives the atmospheric wind circulation comes from the latent heat released by tropical precipitation. Recognizing the importance of rain in the tropics, NASA for the U.S.A. and NASDA for Japan have partnered in the design, construction and flight of a satellite mission to measure tropical rainfall and calculate the associated latent heat release. The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on November 27, 1997, and data from all the instruments first became available approximately 30 days after launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms and applications of these results to areas such as Data Assimilation and model initialization. TRMM has reduced the uncertainty of climatological rainfall in tropics by over a factor of two, therefore establishing a standard for comparison with previous data sets and climatologies. It has documented the diurnal variation of precipitation over the oceans, showing a distinct early morning peak and this satellite mission has shown the utility of precipitation information for the improvement of numerical weather forecasts and climate modeling. This paper discusses some promising applications using TRMM data and introduces a measurement concept being discussed by NASA/NASDA and ESA for the future of rainfall estimation from space.

  12. Improvement of Passive Microwave Rainfall Retrieval Algorithm over Mountainous Terrain

    NASA Astrophysics Data System (ADS)

    Shige, S.; Yamamoto, M.

    2015-12-01

    The microwave radiometer (MWR) algorithms underestimate heavy rainfall associated with shallow orographic rainfall systems owing to weak ice scattering signatures. Underestimation of the Global Satellite Mapping of Precipitation (GSMaP) MWR has been mitigated by an orographic/nonorographic rainfall classification scheme (Shige et al. 2013, 2015; Taniguchi et al. 2013; Yamamoto and Shige 2015). The orographic/nonorographic rainfall classification scheme is developed on the basis of orographically forced upward vertical motion and the convergence of surface moisture flux estimated from ancillary data. Lookup tables derived from orographic precipitation profiles are used to estimate rainfall for an orographic rainfall pixel, whereas those derived from original precipitation profiles are used to estimate rainfall for a nonorographic rainfall pixel. The orographic/nonorographic rainfall classification scheme has been used by the version of GSMaP products, which are available in near real time (about 4 h after observation) via the Internet (http://sharaku.eorc.jaxa.jp/GSMaP/index.htm). The current version of GSMaP MWR algorithm with the orographic/nonorographic rainfall classification scheme improves rainfall estimation over the entire tropical region, but there is still room for improvement. In this talk, further improvement of orographic rainfall retrievals will be shown.

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

    NASA Astrophysics Data System (ADS)

    Ushiyama, Motoyuki

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

  14. Models for estimating daily rainfall erosivity in China

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The multiplication of rainfall energy and maximum 30 minutes intensity (EI30) is the most widely used rainfall erosivity index for empirical soil loss prediction models, however its calculation requires high temporal resolution rainfall data which are often not readily available in China in most loc...

  15. Evaluation of sediment hazards by extreme rainfall in wildfire lands

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Extreme rainfall events in mountainous terrain impacted by wildfire can erode hillslopes and stream channels and produce flooding with large sediment yields. In 2002, typhoon Rusa with a one-day rainfall total of 944.5 mm and a maximum one-hour rainfall intensity of 114.5 mm/hr hit land impacted by ...

  16. SYNOPTIC RAINFALL DATA ANALYSIS PROGRAM (SYNOP). RELEASE NO. 1

    EPA Science Inventory

    An integral part of the assessment of storm loads on water quality is the statistical evaluation of rainfall records. Hourly rainfall records of many years duration are cumbersome and difficult to analyze. The purpose of this rainfall data analysis program is to provide the user ...

  17. Inferences of weekly cycles in summertime rainfall

    NASA Astrophysics Data System (ADS)

    Tuttle, John D.; Carbone, Richard E.

    2011-10-01

    In several continental regions a weekly cycle of air pollution aerosols has been observed. It is usually characterized by concentration minima on weekends (Saturday and Sunday) and maxima on weekdays (Tuesday-Friday). Several studies have associated varying aerosol concentrations with precipitation production and attempted to determine whether or not there is a corresponding weekly cycle of precipitation. Results to date have been mixed. Here we examine a 12 year national composited radar data set for evidence of weekly precipitation cycles during the warm season (June-August). Various statistical quantities are calculated and subjected to "bootstrap" testing in order to assess significance. In many parts of the United States, warm season precipitation is relatively infrequent, with a few extreme events contributing to a large percentage of the total 12 year rainfall. For this reason, the statistics are often difficult to interpret. The general area east of the Mississippi River and north of 37°N contains regions where 25%-50% daily rainfall increases are inferred for weekdays (Tuesday-Friday) relative to weekends. The statistics suggest that western Pennsylvania is the largest and most likely contiguous region to have a weekly cycle. Parts of northern Florida and southeastern coastal areas infer a reverse-phase cycle, with less rainfall during the week than on weekends. Spot checks of surface rain gauge data confirm the phase of these radar-observed anomalies in both Pennsylvania and Florida. While there are indications of a weekly cycle in other locations of the United States, the degree of confidence is considerably lower. There is a strong statistical inference of weekday rainfall maxima over a net 8% of the area examined, which is approximately twice the area of cities. Future examination of lofted aerosol content, related condensation/ice nuclei spectra, and knowledge of the convective dynamical regime are needed in order to assess how anthropogenic aerosols

  18. Satellite Rainfall Uncertainty Estimation by Mathematical Models Using Geophysical Features and Rainfall Rate

    NASA Astrophysics Data System (ADS)

    Gebregiorgis, A. S.; Hossain, F.

    2012-12-01

    This study addresses the estimation of error variance of three satellite rainfall products: i) Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) product of 3B42RT; ii) Climate Prediction Center (CPC) Morph (CMORPH); and iii) Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Cloud Classification System (PERSIANN-CCS). Nonlinear regression model is used to fit the response variable (satellite rainfall error variance) with explanatory variable (satellite rainfall rate) by grouping them as function of three key geophysical features: topography, climate, and season. The results of the study suggest that the error variance of a rainfall product is strongly correlated with rainfall rate and can be expressed as a power-law function. The geophysical feature based error classification analysis helps in achieving superior functional accuracy for prognostic error variance quantification in the absence of ground truth data. The multiple correlation coefficients between the estimated and observed error variance over an independent validation region (Upper Mississippi River basin) and time period (2007 - 2010) are found to be 0.75, 0.86, and 0.87 for 3B42RT, CMORPH, and PERSIANN-CCS products, respectively. In another validation region (Arkansas-Red River basin), the correlation coefficients are 0.59, 0.89, and 0.92 for the same products, respectively. Results of the assessment of error variance models reveal that the type of error component present in a satellite rainfall product directly impacts on the accuracy of estimated error variance. The model estimates the error variance more accurately when the precipitation error components are mostly hit bias or false precipitation, while for a product with extensive missed precipitation, the accuracy of estimated error variance is significantly compromised. The study clearly demonstrates the feasibility of quantifying the error variance of satellite

  19. Infrared remote sensing for monitoring rainfall

    USGS Publications Warehouse

    Moore, Donald G.; Harlan, J.C.; Heilman, J. L.; Ohlen, Donald O.; Rosenthal, W.D.

    1983-01-01

    Evaluations of thermal infrared satellite data from TIROS-N and the Heat Capacity Mapping Mission (HCMM) showed that rainfall distribution patterns could be reliably detected on images acquired up to at least three days after the event. The temperature relationship decreased eight days after the event when soil variations influenced the signal. A time-series analysis reduced thermal variability normally observed over diverse landscapes and increased the sensitivity of the procedures. The method of repetitive low-resolution thermal observations could be operationally employed over large geographic regions with currently available satellite systems. The results would augment the existing rain gauge stations by increasing the spatial sensitivity and the reliability of detection and mapping individual rainfall events.

  20. Bivariate copula in fitting rainfall data

    NASA Astrophysics Data System (ADS)

    Yee, Kong Ching; Suhaila, Jamaludin; Yusof, Fadhilah; Mean, Foo Hui

    2014-07-01

    The usage of copula to determine the joint distribution between two variables is widely used in various areas. The joint distribution of rainfall characteristic obtained using the copula model is more ideal than the standard bivariate modelling where copula is belief to have overcome some limitation. Six copula models will be applied to obtain the most suitable bivariate distribution between two rain gauge stations. The copula models are Ali-Mikhail-Haq (AMH), Clayton, Frank, Galambos, Gumbel-Hoogaurd (GH) and Plackett. The rainfall data used in the study is selected from rain gauge stations which are located in the southern part of Peninsular Malaysia, during the period from 1980 to 2011. The goodness-of-fit test in this study is based on the Akaike information criterion (AIC).

  1. Autocorrelation of rainfall and streamflow minimums

    USGS Publications Warehouse

    Matalas, N.C.

    1963-01-01

    Hydrologic time series of annual minimum mean monthly rainfall and annual minimum 1-day and 7-day discharge, considered as drought indices, were used to study the distribution of droughts with respect to time. The rainfall data were found to be nearly random. The discharge data, however, were found to be nonrandomly distributed in time and generated by a first-order Markov process. The expected value of the variance for a time series generated by a first-order Markov process was compared with the expected value of the variance for a random time series. This comparison showed that the expected value of the variance for a nonrandom time series converged to the population variance with an increase in sample size at a slower rate than for a random time series.

  2. Network design for heavy rainfall analysis

    NASA Astrophysics Data System (ADS)

    Rietsch, T.; Naveau, P.; Gilardi, N.; Guillou, A.

    2013-12-01

    The analysis of heavy rainfall distributional properties is a complex object of study in hydrology and climatology, and it is essential for impact studies. In this paper, we investigate the question of how to optimize the spatial design of a network of existing weather stations. Our main criterion for such an inquiry is the capability of the network to capture the statistical properties of heavy rainfall described by the Extreme Value Theory. We combine this theory with a machine learning algorithm based on neural networks and a Query By Committee approach. Our resulting algorithm is tested on simulated data and applied to high-quality extreme daily precipitation measurements recorded in France at 331 weather stations during the time period 1980-2010.

  3. Rainfall erosivity and rainfall return period in the experimental watershed of Aracruz, in the Coastal Plain of Espirito Santo, Brazil

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The knowledge of the factors influencing water erosion is relevant to land management practices. Rainfall, expressed by rainfall erosivity, is very important among the factors affecting water erosion. Thus, the objective of this study was to determine rainfall erosivity and return period for the Coa...

  4. Rainfall intensity-duration-frequency formulas.

    USGS Publications Warehouse

    Chen, C.-L.

    1983-01-01

    A new general rainfall intensity-duration-frequency formula is presented, utilizing a method similar to, but more accurate than one previously developed. The previously developed formula was based on the average depth-duration ratio of about 40% and the mean depth-frequency ratio of 1.48. It is shown that this formula is only a particular form of the writer's more general formulation. -from Author

  5. Recent Rainfall and Aerosol Chemistry From Bermuda

    NASA Astrophysics Data System (ADS)

    Landing, W. M.; Shelley, R.; Kadko, D. C.

    2014-12-01

    This project was devoted to testing the use of Be-7 as a tracer for quantifying trace element fluxes from the atmosphere to the oceans. Rainfall and aerosol samples were collected between June 15, 2011 and July 27, 2013 at the Bermuda Institute of Ocean Sciences (BIOS) located near the eastern end of the island of Bermuda. Collectors were situated near ground level, clear of surrounding vegetation, at a meteorological monitoring station in front of the BIOS laboratory, about 10 m above sea level. This is a Bermuda Air Quality Program site used for ambient air quality monitoring. To quantify the atmospheric deposition of Be-7, plastic buckets were deployed for collection of fallout over ~3 week periods. Wet deposition was collected for trace element analysis using a specially modified "GEOTRACES" N-CON automated wet deposition collector. Aerosol samples were collected with a Tisch TE-5170V-BL high volume aerosol sampler, modified to collect 12 replicate samples on acid-washed 47mm diameter Whatman-41 filters, using procedures identical to those used for the US GEOTRACES aerosol program (Morton et al., 2013). Aerosol and rainfall samples were analyzed for total Na, Mg, Al, P, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Rb, Sr, Zr, Cd, Sb, Ba, La, Ce, Nd, Pb, Th, and U using ICPMS. Confirming earlier data from Bermuda, strong seasonality in rainfall and aerosol loading and chemistry was observed, particularly for aerosol and rainfall Fe concentrations when Saharan dust arrives in July/August with SE trajectories.

  6. Paraguay river basin response to seasonal rainfall

    NASA Astrophysics Data System (ADS)

    Krepper, Carlos M.; García, Norberto O.; Jones, Phil D.

    2006-07-01

    The use of river flow as a surrogate to study climatic variability implies the assumption that changes in rainfall are mirrored and likely amplified in streamflow. This is probably not completely true in large basins, particularly those that encompass different climatic regions, like the Paraguay river basin. Not all the signals present in precipitation are reflected in river flow and vice versa. The complex relationship between precipitation and streamflow could filter some signals and introduce new oscillatory modes in the discharge series. In this study the whole basin (1 095 000 km2) was divided into two sub-basins. The upper basin is upstream of the confluence with the River Apa and the lower basin is between the Apa river confluence and the Puerto Bermejo measuring station. The rainfall contribution shows a clear wet season from October to March and a dry season from April to September. A singular spectrum analysis (SSA) shows that there are trends in rainfall contributions over the upper and lower basins. Meanwhile, the lower basin only presents a near-decadal cycle (T 10 years). To determine the flow response to seasonal rainfall contributions, an SSA was applied to seasonal flow discharges at Puerto Bermejo. The seasonal flows, Q(t)O-M and Q(t)A-S, present high significant modes in the low-frequency band, like positive trends. In addition, Q(t)O-M presents a near-decadal mode, but only significant at the 77% level for short window lengths (M ≤ 15 years). Really, the Paraguay river flow is not a good surrogate to study precipitation variation. The low-frequency signals play an important role in the flow behaviour, especially during extreme events from the second half of the last century onwards.

  7. Dust-rainfall feedbacks in the West African Sahel

    NASA Astrophysics Data System (ADS)

    Hui, Wanching Jacquie; Cook, Benjamin I.; Ravi, Sujith; Fuentes, José D.; D'Odorico, Paolo

    2008-05-01

    Dust aerosols can suppress rainfall by increasing the number of cloud condensation nuclei in warm clouds and affecting the surface radiation budget and boundary layer instability. The extent to which atmospheric dust may affect precipitation yields and the hydrologic cycle in semiarid regions remains poorly understood. We investigate the relationship between dust aerosols and rainfall in the West African Sahel where the dust-rainfall feedback has been speculated to contribute to sustained droughts. We find that the amount of dust loadings is negatively correlated with rainfall values, suggesting that dust entrained in the atmosphere can significantly inhibit rainfall in this region.

  8. Rainfall-enhanced blooming in typhoon wakes.

    PubMed

    Lin, Y-C; Oey, L-Y

    2016-01-01

    Strong phytoplankton blooming in tropical-cyclone (TC) wakes over the oligotrophic oceans potentially contributes to long-term changes in global biogeochemical cycles. Yet blooming has traditionally been discussed using anecdotal events and its biophysical mechanics remain poorly understood. Here we identify dominant blooming patterns using 16 years of ocean-color data in the wakes of 141 typhoons in western North Pacific. We observe right-side asymmetric blooming shortly after the storms, attributed previously to sub-mesoscale re-stratification, but thereafter a left-side asymmetry which coincides with the left-side preference in rainfall due to the large-scale wind shear. Biophysical model experiments and observations demonstrate that heavier rainfall freshens the near-surface water, leading to stronger stratification, decreased turbulence and enhanced blooming. Our results suggest that rainfall plays a previously unrecognized, critical role in TC-induced blooming, with potentially important implications for global biogeochemical cycles especially in view of the recent and projected increases in TC-intensity that harbingers stronger mixing and heavier rain under the storm. PMID:27545899

  9. Optimal stomatal behaviour under stochastic rainfall.

    PubMed

    Lu, Yaojie; Duursma, Remko A; Medlyn, Belinda E

    2016-04-01

    Vegetation CO2 uptake is always accompanied by water loss. The balance in this gas exchange is controlled by the stomata, through which CO2 and water vapour diffuse between the leaf and the atmosphere. The optimal stomatal behaviour theory proposes that vegetation should optimise its stomatal behaviour such that, for given water availability, photosynthesis is maximised. In this paper, we optimise stomatal conductance as a function of soil water content for the maximum expected value of photosynthesis rate. This optimisation process is considered under stochastic rainfall. The optimal solution is largely shaped by two constraints: the risks of soil water exhaustion and surface runoff, which results in an inverse S-shaped curve of stomatal conductance along the soil water gradient. We derive the optimal functional relationship between stomatal conductance and soil water content under varying rainfall frequency, mean annual precipitation and atmospheric CO2 concentration. Comparisons with large-scale observational data show that the model is able to broadly capture responses of photosynthesis, transpiration, and water use efficiency along rainfall gradients, although notable discrepancies suggest additional factors are important in shaping these responses. Our work provides a theoretical framework for analysing the vegetation gas exchange under environmental change. PMID:26796317

  10. Cyclical components of local rainfall data

    NASA Astrophysics Data System (ADS)

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

    2000-02-01

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

  11. Rainfall-enhanced blooming in typhoon wakes

    PubMed Central

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

    2016-01-01

    Strong phytoplankton blooming in tropical-cyclone (TC) wakes over the oligotrophic oceans potentially contributes to long-term changes in global biogeochemical cycles. Yet blooming has traditionally been discussed using anecdotal events and its biophysical mechanics remain poorly understood. Here we identify dominant blooming patterns using 16 years of ocean-color data in the wakes of 141 typhoons in western North Pacific. We observe right-side asymmetric blooming shortly after the storms, attributed previously to sub-mesoscale re-stratification, but thereafter a left-side asymmetry which coincides with the left-side preference in rainfall due to the large-scale wind shear. Biophysical model experiments and observations demonstrate that heavier rainfall freshens the near-surface water, leading to stronger stratification, decreased turbulence and enhanced blooming. Our results suggest that rainfall plays a previously unrecognized, critical role in TC-induced blooming, with potentially important implications for global biogeochemical cycles especially in view of the recent and projected increases in TC-intensity that harbingers stronger mixing and heavier rain under the storm. PMID:27545899

  12. The Tropical Rainfall Measuring Mission (TRMM)

    NASA Technical Reports Server (NTRS)

    Simpson, Joanne; Kummerow, Christian D.; Meneghini, Robert; Hou, Arthur; Adler, Robert F.; Huffman, George; Barkstrom, Bruce; Wielicki, Bruce; Goodman, Steven J.; Christian, Hugh; Einaudi, Franco (Technical Monitor)

    1999-01-01

    Recognizing the importance of rain in the tropics and the accompanying latent heat release, NASA for the U.S. and NASDA for Japan have partnered in the design, construction and flight of an Earth Probe satellite to measure tropical rainfall and calculate the associated heating. Primary mission goals are: 1) the understanding of crucial links in climate variability by the hydrological cycle, 2) improvement in the large-scale models of weather and climate, and 3) improvement in understanding cloud ensembles and their impacts on larger scale circulations. The linkage with the tropical oceans and landmasses are also emphasized. The Tropical Rainfall Measuring Mission (TRMM) satellite was launched in November 1997 with fuel enough to obtain a four to five year data set of rainfall over the global tropics from 37 deg N to 37 deg S. This paper reports progress from launch date through the spring of 1999. The data system and its products and their access is described, as are the algorithms used to obtain the data. Some exciting early results from TRMM are described. Some important algorithm improvements are shown. These will be used in the first total data reprocessing, scheduled to be complete in early 2000. The reader is given information on how to access and use the data.

  13. Canopy Structure in Relation to Rainfall Interception

    NASA Astrophysics Data System (ADS)

    Fathizadeh, Omid; Mohsen Hosseini, Seyed; Keim, Richard

    2016-04-01

    Spatial variation of throughfall (TF) is linked to canopy structure. The effects of canopy structure on the spatial redistribution of rainfall in deciduous stands remains poorly documented. Therefore, the objective of this study is to evaluate the influence of canopy structure such as stand density on the partitioning of incident rainfall when passing through the canopy of Brant's oak (Quercus branti) forest stands. The study site is the Zagros forests in the western Iranian state of Ilam, protected forests of Dalab region. Twelve TF plots (50 m × 50 m) with 30 gauges randomly placed within each plot were established. Interception loss was computed as the difference between rain and TF. Canopy cover (%) and leaf area index (LAI, m2 m‑2) were estimated from the analysis of hemispherical photographs obtained during the fully leafed period. Relative interception varied from ˜4% at 0.1 LAI and canopy cover of 10% to ˜25% at 1.5 LAI and canopy cover of 65%. Interception represents a significant component of the seasonal water balance of oak forests, particularly in the case of intensive plantings. Keywords: Canopy Structure, Rainfall redistribution, Zagros forests, Quercus branti

  14. An Improved Polarimetric Radar Rainfall Algorithm With Hydrometeor Classification Optimized For Rainfall Estimation

    NASA Astrophysics Data System (ADS)

    Cifelli, R.; Wang, Y.; Lim, S.; Kennedy, P.; Chandrasekar, V.; Rutledge, S. A.

    2009-05-01

    The efficacy of dual polarimetric radar for quantitative precipitation estimation (QPE) is firmly established. Specifically, rainfall retrievals using combinations of reflectivity (ZH), differential reflectivity (ZDR), and specific differential phase (KDP) have advantages over traditional Z-R methods because more information about the drop size distribution and hydrometeor type are available. In addition, dual-polarization radar measurements are generally less susceptible to error and biases due to the presence of ice in the sampling volume. A number of methods have been developed to estimate rainfall from dual-polarization radar measurements. However, the robustness of these techniques in different precipitation regimes is unknown. Because the National Weather Service (NWS) will soon upgrade the WSR 88-D radar network to dual-polarization capability, it is important to test retrieval algorithms in different meteorological environments in order to better understand the limitations of the different methodologies. An important issue in dual-polarimetric rainfall estimation is determining which method to employ for a given set of polarimetric observables. For example, under what circumstances does differential phase information provide superior rain estimates relative to methods using reflectivity and differential reflectivity? At Colorado State University (CSU), a "blended" algorithm has been developed and used for a number of years to estimate rainfall based on ZH, ZDR, and KDP (Cifelli et al. 2002). The rainfall estimators for each sampling volume are chosen on the basis of fixed thresholds, which maximize the measurement capability of each polarimetric variable and combinations of variables. Tests have shown, however, that the retrieval is sensitive to the calculation of ice fraction in the radar volume via the difference reflectivity (ZDP - Golestani et al. 1989) methodology such that an inappropriate estimator can be selected in situations where radar echo is

  15. Real-Time Flood Estimation by Using Radar Rainfall data and Distributed Rainfall-Runoff Model

    NASA Astrophysics Data System (ADS)

    Yu, P.; Chou, J.; Chiu, Y.; Yang, T.; Kuo, C.

    2011-12-01

    This study aims to establish a flood prediction model in Dajia River by using a grid-based distributed rainfall-runoff model (GDRRM) combined with the predicted QPESUMS radar rainfalls. Flood disasters caused damage to human and property. A proper flood prediction model can provide warning messages against disasters. Since the radar rainfall technology has been developed for years, it has the ability to represent the precipitation in each location. Coupling the real-time radar rainfall with the distributed rainfall-runoff model, it can be used to provide the probable flow in downstream. The study area, Dajia River basin, is located in central Taiwan. The river flow is mainly controlled by two major reservoirs, Shih-Kang Dam in downstream and Te-Chi Reservoir in upstream. Thus, three components are considered for establishing the flood prediction model. The first one is the application of radar rainfalls. The real-time and predicted (1-3hr ahead) radar rainfall data provided by the Central Weather Bureau, Taiwan were set as the input data. It can represent the actual distributed rainfalls of the basin. The second one is the estimation of reservoir inflow by using a GDRRM. The basin was divided into 1234 regular grids (1km by 1km) to exhibit the heterogeneity in the watershed. The parameters of GDRRM were generated by using DEM, Formosat-2 satellite image and soil map to represent the actual geography and physiography of each grid. With the input of real-time and predicted radar rainfall data, the inflow of Te-Chi Reservoir and Shih-Kang Dam can be calculated by using two GDRRMs respectively. The third one is the operation rules of reservoir used for simulating the outflow of the reservoirs during the flow simulation. Then, the downstream (Shih-Kang Dam) GDRRM coupled with the operation rules was used to calculate the outflow of the Te-Chi Reservoir. Thus, the flood can be predicted in advance during typhoon period. The results revealed that the flood prediction

  16. Automatic Extraction of High-Resolution Rainfall Series from Rainfall Strip Charts

    NASA Astrophysics Data System (ADS)

    Saa-Requejo, Antonio; Valencia, Jose Luis; Garrido, Alberto; Tarquis, Ana M.

    2015-04-01

    Soil erosion is a complex phenomenon involving the detachment and transport of soil particles, storage and runoff of rainwater, and infiltration. The relative magnitude and importance of these processes depends on a host of factors, including climate, soil, topography, cropping and land management practices among others. Most models for soil erosion or hydrological processes need an accurate storm characterization. However, this data are not always available and in some cases indirect models are generated to fill this gap. In Spain, the rain intensity data known for time periods less than 24 hours back to 1924 and many studies are limited by it. In many cases this data is stored in rainfall strip charts in the meteorological stations but haven't been transfer in a numerical form. To overcome this deficiency in the raw data a process of information extraction from large amounts of rainfall strip charts is implemented by means of computer software. The method has been developed that largely automates the intensive-labour extraction work based on van Piggelen et al. (2011). The method consists of the following five basic steps: 1) scanning the charts to high-resolution digital images, 2) manually and visually registering relevant meta information from charts and pre-processing, 3) applying automatic curve extraction software in a batch process to determine the coordinates of cumulative rainfall lines on the images (main step), 4) post processing the curves that were not correctly determined in step 3, and 5) aggregating the cumulative rainfall in pixel coordinates to the desired time resolution. A colour detection procedure is introduced that automatically separates the background of the charts and rolls from the grid and subsequently the rainfall curve. The rainfall curve is detected by minimization of a cost function. Some utilities have been added to improve the previous work and automates some auxiliary processes: readjust the bands properly, merge bands when

  17. Simulated changes in daily rainfall intensity due to the enhanced greenhouse effect: Implications for extreme rainfall events

    SciTech Connect

    Gordon, H.B.; Whetton, P.H.; Pittock, A.B.

    1992-10-01

    This study presents rainfall results from equilibrium 1x- and 2xCO{sub 2} experiments with the CSIRO 4-level general circulation model. The 1xCO{sub 2} results are discussed in relation to observed climate. Discussion of the 2xCO{sub 2} results focuses upon changes in convective and non-convective rainfall as simulated in the model, and the consequences these changes have for simulated daily rainfall intensity and the frequency of heavy rainfall events. The significant shortcomings of GCM simulations of precipitation processes are recognized. Generally, the model results show a marked increase in rainfall originating from penetrative convection and, in the mid-latitudes, a decline in large-scale (non-convective) rainfall. It is argued these changes in rainfall type are a consequence of the increased moisture holding capacity of the warmer atmosphere simulated for 2xCO{sub 2} conditions. Related to changes in rainfall type, rainfall intensity (rain per rain day) increases in the model for most global regions. Increases extend even to regions where total rainfall decreases. Indeed, the greater intensity of daily rainfall is a much clearer response of the model to increased greenhouse gases than the changes in total rainfall. We also find a decrease in the number of rainy days in the middle latitudes of both the Northern and Southern Hemispheres. To further elucidate these results daily rainfall frequency distributions are examined globally and four selected regions of interest. In all regions the frequency of high rainfall events increases, and the return period of such events decreases markedly. If realistic, the findings have potentially serious practical implications in terms of an increased frequency and severity of floods in most regions. However, we discuss various important sources of uncertainty in the results presented, and indicate the need for rainfall intensity results to be examined in enhanced greenhouse experiments with other GCMs. 31 refs., 20 figs.

  18. Convective rainfall estimation from digital GOES-1 infrared data

    NASA Technical Reports Server (NTRS)

    Sickler, G. L.; Thompson, A. H.

    1979-01-01

    An investigation was conducted to determine the feasibility of developing and objective technique for estimating convective rainfall from digital GOES-1 infrared data. The study area was a 240 km by 240 km box centered on College Station, Texas (Texas A and M University). The Scofield and Oliver (1977) rainfall estimation scheme was adapted and used with the digital geostationary satellite data. The concept of enhancement curves with respect to rainfall approximation is discussed. Raingage rainfall analyses and satellite-derived rainfall estimation analyses were compared. The correlation for the station data pairs (observed versus estimated rainfall amounts) for the convective portion of the storm was 0.92. It was demonstrated that a fairly accurate objective rainfall technique using digital geostationary infrared satellite data is feasible. The rawinsonde and some synoptic data that were used in this investigation came from NASA's Atmospheric Variability Experiment, AVE 7.

  19. Estimation of the fractional coverage of rainfall in climate models

    NASA Technical Reports Server (NTRS)

    Eltahir, E. A. B.; Bras, R. L.

    1993-01-01

    The fraction of the grid cell area covered by rainfall, mu, is an essential parameter in descriptions of land surface hydrology in climate models. A simple procedure is presented for estimating this fraction, based on extensive observations of storm areas and rainfall volumes. Storm area and rainfall volume are often linearly related; this relation can be used to compute the storm area from the volume of rainfall simulated by a climate model. A formula is developed for computing mu, which describes the dependence of the fractional coverage of rainfall on the season of the year, the geographical region, rainfall volume, and the spatial and temporal resolution of the model. The new formula is applied in computing mu over the Amazon region. Significant temporal variability in the fractional coverage of rainfall is demonstrated. The implications of this variability for the modeling of land surface hydrology in climate models are discussed.

  20. Tropical cyclone rainfall area controlled by relative sea surface temperature

    PubMed Central

    Lin, Yanluan; Zhao, Ming; Zhang, Minghua

    2015-01-01

    Tropical cyclone rainfall rates have been projected to increase in a warmer climate. The area coverage of tropical cyclones influences their impact on human lives, yet little is known about how tropical cyclone rainfall area will change in the future. Here, using satellite data and global atmospheric model simulations, we show that tropical cyclone rainfall area is controlled primarily by its environmental sea surface temperature (SST) relative to the tropical mean SST (that is, the relative SST), while rainfall rate increases with increasing absolute SST. Our result is consistent with previous numerical simulations that indicated tight relationships between tropical cyclone size and mid-tropospheric relative humidity. Global statistics of tropical cyclone rainfall area are not expected to change markedly under a warmer climate provided that SST change is relatively uniform, implying that increases in total rainfall will be confined to similar size domains with higher rainfall rates. PMID:25761457

  1. Radar Rainfall Estimation for Ground Validation Studies of the Tropical Rainfall Measuring Mission.

    NASA Astrophysics Data System (ADS)

    Ciach, Grzegorz J.; Krajewski, Witold F.; Anagnostou, Emmanouil N.; Baeck, Mary L.; Smith, James A.; McCollum, Jeffrey R.; Kruger, Anton

    1997-06-01

    This study presents a multicomponent rainfall estimation algorithm, based on weather radar and rain gauge network, that can be used as a ground-based reference in the satellite Tropical Rainfall Measuring Mission (TRMM). The essential steps are constructing a radar observable, its nonlinear transformation to rainfall, interpolation to rectangular grid, constructing several timescale accumulations, bias adjustment, and merging of the radar rainfall estimates and rain gauge data. Observations from a C-band radar in Darwin, Australia, and a local network of 54 rain gauges were used to calibrate and test the algorithm. A period of 25 days was selected, and the rain gauges were split into two subsamples to apply cross-validation techniques.A Z-R relationship with continuous range dependence and a temporal interpolation scheme that accounts for the advection effects is applied. An innovative methodology was used to estimate the algorithm controlling parameters. The model was globally optimized by using an objective function on the level of the final products. This is equivalent to comparing hundreds of Z-R relationships using a uniform and representative performance criterion. The algorithm performance is fairly insensitive to the parameter variations around the optimum. This suggests that the accuracy limit of the radar rainfall estimation based on power-law Z-R relationships has been reached. No improvement was achieved by using rain regime classification prior to estimation.

  2. Comparison of TAMSAT and CPC rainfall estimates with rainfall for southern Africa

    NASA Astrophysics Data System (ADS)

    Thorne, Virginia; Coakeley, Paul; Grimes, David I. F.; Dugdale, George

    1999-12-01

    Two different TAMSAT methods of Rainfall Estimation were developed respectively for northern and southern Africa, based on Meteosat TIR images; northern Africa since 1987 and southern Africa since 1990. These rainfall estimates are used operationally for agricultural purposes and for predicting famines and floods. The two different methods have both been used to make rainfall estimates for the southern rainy season October 1995 to April 1996, and then compared with estimates produced by the CPC method. The latter are made more simply from TIR, but have the addition of GTS rainfall data and orographic rain. All these estimates were then compared with kriged data from over 800 raingauges in southern Africa. The detailed results were then compared for the whole season across the whole SADC region, and then two detailed cross- sections were studied, with different orography. The results show that operational TAMSAT estimates are better over plateau regions, with 59% estimates within 1 Std of the rainfall, but over the whole region the CPC estimates perform best. Over mountainous regions all methods under-estimate and give only 40% within 1Std. The two TAMSAT methods show little difference across a whole season, but when looked at in detail the northern method gives unsatisfactory calibrations. The CPC method does have significant overall improvements by building in real-time raingauge data, but only where sufficient raingauges are available.

  3. An Empirically Based Error-Model for Radar Rainfall Estimates

    NASA Astrophysics Data System (ADS)

    Ciach, G. J.

    2004-05-01

    Mathematical modeling of the way radar rainfall (RR) approximates the physical truth is a prospective method to quantify the RR uncertainties. In this approach one can represent RR in the form of an "observation equation," that is, as a function of the corresponding true rainfall and a random error process. The error process describes the cumulative effect of all the sources of RR uncertainties. We present the results of our work on the identification and estimation of this relationship. They are based on the Level II reflectivity data from the WSR-88D radar in Tulsa, Oklahoma, and rainfall measurements from 23 surrounding Oklahoma Mesonet raingauges. Accumulation intervals from one hour to one day were analyzed using this sample. The raingauge accumulations were used as an approximation of the true rainfall in this study. The RR error-model that we explored is factorized into a deterministic distortion, which is a function of the true rainfall, and a multiplicative random error factor that is a positively-defined random variable. The distribution of the error factor depends on the true rainfall, however, its expectation in this representation is always equal to one (all the biases are modeled by the deterministic component). With this constraint, the deterministic distortion function can be defined as the conditional mean of RR conditioned on the true rainfall. We use nonparametric regression to estimate the deterministic distortion, and the variance and quantiles of the random error factor, as functions of the true rainfall. The results show that the deterministic distortion is a nonlinear function of the true rainfall that indicates systematic overestimation of week rainfall and underestimation of strong rainfall (conditional bias). The standard deviation of the error factor is a decreasing function of the true rainfall that ranges from about 0.8 for week rainfall to about 0.3 for strong rainfall. For larger time-scales, both the deterministic distortion and the

  4. Comparison of different synthetic 5-min rainfall time series on the results of rainfall runoff simulations in urban drainage modelling

    NASA Astrophysics Data System (ADS)

    Krämer, Stefan; Rohde, Sophia; Schröder, Kai; Belli, Aslan; Maßmann, Stefanie; Schönfeld, Martin; Henkel, Erik; Fuchs, Lothar

    2015-04-01

    The design of urban drainage systems with numerical simulation models requires long, continuous rainfall time series with high temporal resolution. However, suitable observed time series are rare. As a result, usual design concepts often use uncertain or unsuitable rainfall data, which renders them uneconomic or unsustainable. An expedient alternative to observed data is the use of long, synthetic rainfall time series as input for the simulation models. Within the project SYNOPSE, several different methods to generate synthetic rainfall data as input for urban drainage modelling are advanced, tested, and compared. Synthetic rainfall time series of three different precipitation model approaches, - one parametric stochastic model (alternating renewal approach), one non-parametric stochastic model (resampling approach), one downscaling approach from a regional climate model-, are provided for three catchments with different sewer system characteristics in different climate regions in Germany: - Hamburg (northern Germany): maritime climate, mean annual rainfall: 770 mm; combined sewer system length: 1.729 km (City center of Hamburg), storm water sewer system length (Hamburg Harburg): 168 km - Brunswick (Lower Saxony, northern Germany): transitional climate from maritime to continental, mean annual rainfall: 618 mm; sewer system length: 278 km, connected impervious area: 379 ha, height difference: 27 m - Friburg in Brisgau (southern Germany): Central European transitional climate, mean annual rainfall: 908 mm; sewer system length: 794 km, connected impervious area: 1 546 ha, height difference 284 m Hydrodynamic models are set up for each catchment to simulate rainfall runoff processes in the sewer systems. Long term event time series are extracted from the - three different synthetic rainfall time series (comprising up to 600 years continuous rainfall) provided for each catchment and - observed gauge rainfall (reference rainfall) according national hydraulic design

  5. Rainfall simulation experiments with a small portable rainfall simulator: research on runoff generation and soil erosion

    NASA Astrophysics Data System (ADS)

    Iserloh, Thomas; Peter, Klaus Daniel; Fister, Wolfgang; Wirtz, Stefan; Butzen, Verena; Brings, Christine; Marzen, Miriam; Casper, Markus C.; Seeger, Manuel; Ries, Johannes B.

    2015-04-01

    The results of more than 500 rainfall simulations with a small portable rainfall simulator at various locations in West and North Africa and South and Central Europe will be presented. The analysis of this comprehensive database offers results concerning different research objectives: - erodibility of local soils regarding different vegetation cover, stone cover and land uses - runoff generation in gully catchments - process oriented experiments on the influence of sealing and crusting - trail erosion caused by goat- or sheep-trampling - recent erosion on geomorphological forms Runoff coefficients range from 0 to 100 % and eroded material from 0 to 500 g m^-2 during 30 min experiments with a rainfall intensity of 40 mm h^-1.

  6. Simulation of radar rainfall errors and their propagation into rainfall-runoff processes

    NASA Astrophysics Data System (ADS)

    Aghakouchak, A.; Habib, E.

    2008-05-01

    Radar rainfall data compared with rain gauge measurements provide higher spatial and temporal resolution. However, radar data obtained form reflectivity patterns are subject to various errors such as errors in Z-R relationship, vertical profile of reflectivity, spatial and temporal sampling, etc. Characterization of such uncertainties in radar data and their effects on hydrologic simulations (e.g., streamflow estimation) is a challenging issue. This study aims to analyze radar rainfall error characteristics empirically to gain information on prosperities of random error representativeness and its temporal and spatial dependency. To empirically analyze error characteristics, high resolution and accurate rain gauge measurements are required. The Goodwin Creek watershed located in the north part of Mississippi is selected for this study due to availability of a dense rain gauge network. A total of 30 rain gauge measurement stations within Goodwin Creak watershed and the NWS Level II radar reflectivity data obtained from the WSR-88dD Memphis radar station with temporal resolution of 5min and spatial resolution of 1 km2 are used in this study. Radar data and rain gauge measurements comparisons are used to estimate overall bias, and statistical characteristics and spatio-temporal dependency of radar rainfall error fields. This information is then used to simulate realizations of radar error patterns with multiple correlated variables using Monte Calro method and the Cholesky decomposition. The generated error fields are then imposed on radar rainfall fields to obtain statistical realizations of input rainfall fields. Each simulated realization is then fed as input to a distributed physically based hydrological model resulting in an ensemble of predicted runoff hydrographs. The study analyzes the propagation of radar errors on the simulation of different rainfall-runoff processes such as streamflow, soil moisture, infiltration, and over-land flooding.

  7. Quantifying uncertainty in observational rainfall datasets

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    The CO-ordinated Regional Downscaling Experiment (CORDEX) has to date seen the publication of at least ten journal papers that examine the African domain during 2012 and 2013. Five of these papers consider Africa generally (Nikulin et al. 2012, Kim et al. 2013, Hernandes-Dias et al. 2013, Laprise et al. 2013, Panitz et al. 2013) and five have regional foci: Tramblay et al. (2013) on Northern Africa, Mariotti et al. (2014) and Gbobaniyi el al. (2013) on West Africa, Endris et al. (2013) on East Africa and Kalagnoumou et al. (2013) on southern Africa. There also are a further three papers that the authors know about under review. These papers all use an observed rainfall and/or temperature data to evaluate/validate the regional model output and often proceed to assess projected changes in these variables due to climate change in the context of these observations. The most popular reference rainfall data used are the CRU, GPCP, GPCC, TRMM and UDEL datasets. However, as Kalagnoumou et al. (2013) point out there are many other rainfall datasets available for consideration, for example, CMORPH, FEWS, TAMSAT & RIANNAA, TAMORA and the WATCH & WATCH-DEI data. They, with others (Nikulin et al. 2012, Sylla et al. 2012) show that the observed datasets can have a very wide spread at a particular space-time coordinate. As more ground, space and reanalysis-based rainfall products become available, all which use different methods to produce precipitation data, the selection of reference data is becoming an important factor in model evaluation. A number of factors can contribute to a uncertainty in terms of the reliability and validity of the datasets such as radiance conversion algorithims, the quantity and quality of available station data, interpolation techniques and blending methods used to combine satellite and guage based products. However, to date no comprehensive study has been performed to evaluate the uncertainty in these observational datasets. We assess 18 gridded

  8. Impacts of Characteristics of Errors in Radar Rainfall Estimates for Rainfall-Runoff Simulation

    NASA Astrophysics Data System (ADS)

    KO, D.; PARK, T.; Lee, T. S.; Shin, J. Y.; Lee, D.

    2015-12-01

    For flood prediction, weather radar has been commonly employed to measure the amount of precipitation and its spatial distribution. However, estimated rainfall from the radar contains uncertainty caused by its errors such as beam blockage and ground clutter. Even though, previous studies have been focused on removing error of radar data, it is crucial to evaluate runoff volumes which are influenced primarily by the radar errors. Furthermore, resolution of rainfall modeled by previous studies for rainfall uncertainty analysis or distributed hydrological simulation are quite coarse to apply to real application. Therefore, in the current study, we tested the effects of radar rainfall errors on rainfall runoff with a high resolution approach, called spatial error model (SEM). In the current study, the synthetic generation of random and cross-correlated radar errors were employed as SEM. A number of events for the Nam River dam region were tested to investigate the peak discharge from a basin according to error variance. The results indicate that the dependent error brings much higher variations in peak discharge than the independent random error. To further investigate the effect of the magnitude of cross-correlation between radar errors, the different magnitudes of spatial cross-correlations were employed for the rainfall-runoff simulation. The results demonstrate that the stronger correlation leads to higher variation of peak discharge and vice versa. We conclude that the error structure in radar rainfall estimates significantly affects on predicting the runoff peak. Therefore, the efforts must take into consideration on not only removing radar rainfall error itself but also weakening the cross-correlation structure of radar errors in order to forecast flood events more accurately. Acknowledgements This research was supported by a grant from a Strategic Research Project (Development of Flood Warning and Snowfall Estimation Platform Using Hydrological Radars), which

  9. Experiments for comparison of small scale rainfall simulators

    NASA Astrophysics Data System (ADS)

    Iserloh, T.; Ries, J. B.

    2012-04-01

    Small scale portable rainfall simulators are an essential tool in research of recent process dynamics of soil erosion. Such rainfall simulators differ in design, rainfall intensities, rain spectra etc., impeding comparison of the results. Due to different research questions a standardisation of rainfall simulation is not in sight. Nevertheless, the data become progressively important for soil erosion modelling and therefore the basis for decision-makers in application-oriented erosion protection. The project aims at providing a criteria catalogue for estimation of the different simulators as well as the comparability of the results and a uniform calibration procedure for generated rainfall. Within the project "Comparability of simulation results of different rainfall simulators as input data for soil erosion modelling (Deutsche Forschungsgemeinschaft - DFG, Project No. Ri 835/6-1)" many rainfall simulators used by European research groups were compared. The artificially generated rainfall of the rainfall simulators at the Universities Basel, La Rioja, Malaga, Trier, Tübingen, Valencia, Wageningen, Zaragoza and at different Spanish CSIC-institutes (Almeria, Cordoba, Granada, Murcia, Zaragoza) were measured with the same methods (Laser Precipitation Monitor for drop spectra and rain collectors for spatial distribution). The data are very beneficial for improvements of simulators and comparison of simulators and results. Furthermore, they can be used for comparative studies with natural rainfall spectra. A broad range of rainfall data was measured (e.g. intensity: 30 - 149 mmh-1, Christiansen Coefficient for spatial rainfall distribution 61 - 98 %, mean drop diameter 0.375 - 5.0 mm, mean kinetic energy expenditure 25 - 1322 J m-2 h-1, mean kinetic energy per unit area and unit depth of rainfall 4 - 14 J m-2 mm-1). Similarities among the simulators could be found e.g. concerning drop size distributions (maximum drop numbers are reached within the two smallest drop

  10. Investigation of summer monsoon rainfall variability in Pakistan

    NASA Astrophysics Data System (ADS)

    Hussain, Mian Sabir; Lee, Seungho

    2016-08-01

    This study analyzes the inter-annual and intra-seasonal rainfall variability in Pakistan using daily rainfall data during the summer monsoon season (June to September) recorded from 1980 to 2014. The variability in inter-annual monsoon rainfall ranges from 20 % in northeastern regions to 65 % in southwestern regions of Pakistan. The analysis reveals that the transition of the negative and positive anomalies was not uniform in the investigated dataset. In order to acquire broad observations of the intra-seasonal variability, an objective criterion, the pre-active period, active period and post-active periods of the summer monsoon rainfall have demarcated. The analysis also reveals that the rainfall in June has no significant contribution to the increase in intra-seasonal rainfall in Pakistan. The rainfall has, however, been enhanced in the summer monsoon in August. The rainfall of September demonstrates a sharp decrease, resulting in a high variability in the summer monsoon season. A detailed examination of the intra-seasonal rainfall also reveals frequent amplitude from late July to early August. The daily normal rainfall fluctuates significantly with its maximum in the Murree hills and its minimum in the northwestern Baluchistan.

  11. Investigation of summer monsoon rainfall variability in Pakistan

    NASA Astrophysics Data System (ADS)

    Hussain, Mian Sabir; Lee, Seungho

    2016-01-01

    This study analyzes the inter-annual and intra-seasonal rainfall variability in Pakistan using daily rainfall data during the summer monsoon season (June to September) recorded from 1980 to 2014. The variability in inter-annual monsoon rainfall ranges from 20 % in northeastern regions to 65 % in southwestern regions of Pakistan. The analysis reveals that the transition of the negative and positive anomalies was not uniform in the investigated dataset. In order to acquire broad observations of the intra-seasonal variability, an objective criterion, the pre-active period, active period and post-active periods of the summer monsoon rainfall have demarcated. The analysis also reveals that the rainfall in June has no significant contribution to the increase in intra-seasonal rainfall in Pakistan. The rainfall has, however, been enhanced in the summer monsoon in August. The rainfall of September demonstrates a sharp decrease, resulting in a high variability in the summer monsoon season. A detailed examination of the intra-seasonal rainfall also reveals frequent amplitude from late July to early August. The daily normal rainfall fluctuates significantly with its maximum in the Murree hills and its minimum in the northwestern Baluchistan.

  12. Evaluation of rainfall and temperature trends in Brunei Darussalam

    NASA Astrophysics Data System (ADS)

    Hasan, Dk. Siti Nurul Ain binti Pg. Ali; Ratnayake, Uditha; Shams, Shahriar

    2016-02-01

    Climate change is acknowledged as the world's significant environmental predicament. Rainfall and temperature have been widely studied in correlation with climate change. This paper demonstrates the result of the trend analysis of rainfall variables over the period of 1984 to 2013 and temperature variables over the period of 1979 to 2013 in Brunei Darussalam. Mann-Kendall trend test was applied to analyse and detect trends for the variables. This study revealed that the observed rainfall has a statistically significant increasing trend with increasing rainfall duration and decreasing intensity. The annual rainfall has increased significantly at a rate of 26.16 mm per annum. Mann-Kendall test for rainfall data reveals an increasing trend at confidence level of 95% for the annual total rainfall and confidence of level 90% for of annual maximum rainfall. The observed temperature also exhibits a statistically significant increasing trend at a rate of 0.031°C per year. Results of Mann-Kendall test for temperature data indicate a positive trend at a confidence level of 99.9% for the annual average temperature, average day time temperature, minimum day time temperature, average night time temperature and minimum night time temperature and at a confidence level of 95% for maximum night time temperature. The progressive effect of both the observed rainfall and temperature changes will contribute to greater surfaces run off and create flooding problem. Too much rainfall will threaten slope stability while dry periods of increased temperature will cause soil erosion.

  13. Probabilistic rainfall thresholds for landslide occurrence using a Bayesian approach

    NASA Astrophysics Data System (ADS)

    Berti, M.; Martina, M. L. V.; Franceschini, S.; Pignone, S.; Simoni, A.; Pizziolo, M.

    2012-12-01

    Various methods have been proposed in the literature to predict the rainfall conditions that are likely to trigger landslides in a given area. Most of these methods, however, only consider the rainfall events that resulted in landslides and provide deterministic thresholds with a single possible output (landslide or no-landslide) for a given input (rainfall conditions). Such a deterministic view is not always suited to landslides. Slope stability, in fact, is not ruled by rainfall alone and failure conditions are commonly achieved with a combination of numerous relevant factors. When different outputs (landslide or no-landslide) can be obtained for the same input a probabilistic approach is preferable. In this work we propose a new method for evaluating rainfall thresholds based on Bayesian probability. The method is simple, statistically rigorous, and returns a value of landslide probability (from 0 to 1) for each combination of the selected rainfall variables. The proposed approach was applied to the Emilia-Romagna Region of Italy taking advantage of the historical landslide archive, which includes more than 4000 events for which the date of occurrence is known with daily accuracy. The results show that landsliding in the study area is strongly related to rainfall event parameters (duration, intensity, total rainfall) while antecedent rainfall seems to be less important. The distribution of landslide probability in the rainfall duration-intensity shows an abrupt increase at certain duration-intensity values which indicates a radical change of state of the system and suggests the existence of a real physical threshold.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  15. Multidecadal oscillations in rainfall and hydrological extremes

    NASA Astrophysics Data System (ADS)

    Willems, Patrick

    2013-04-01

    Many studies have anticipated a worldwide increase in the frequency and intensity of precipitation extremes and floods since the last decade(s). Natural variability by climate oscillations partly determines the observed evolution of precipitation extremes. Based on a technique for the identification and analysis of changes in extreme quantiles, it is shown that hydrological extremes have oscillatory behaviour at multidecadal time scales. Results are based on nearly independent extremes extracted from long-term historical time series of precipitation intensities and river flows. Study regions include Belgium - The Netherlands (Meuse basin), Ethiopia (Blue Nile basin) and Ecuador (Paute basin). For Belgium - The Netherlands, the past 100 years showed larger and more hydrological extremes around the 1910s, 1950-1960s, and more recently during the 1990-2000s. Interestingly, the oscillations for southwestern Europe are anti-correlated with these of northwestern Europe, thus with oscillation highs in the 1930-1940s and 1970s. The precipitation oscillation peaks are explained by persistence in atmospheric circulation patterns over the North Atlantic during periods of 10 to 15 years. References: Ntegeka V., Willems P. (2008), 'Trends and multidecadal oscillations in rainfall extremes, based on a more than 100 years time series of 10 minutes rainfall intensities at Uccle, Belgium', Water Resources Research, 44, W07402, doi:10.1029/2007WR006471 Mora, D., Willems, P. (2012), 'Decadal oscillations in rainfall and air temperature in the Paute River Basin - Southern Andes of Ecuador', Theoretical and Applied Climatology, 108(1), 267-282, doi:0.1007/s00704-011-0527-4 Taye, M.T., Willems, P. (2011). 'Influence of climate variability on representative QDF predictions of the upper Blue Nile Basin', Journal of Hydrology, 411, 355-365, doi:10.1016/j.jhydrol.2011.10.019 Taye, M.T., Willems, P. (2012). 'Temporal variability of hydro-climatic extremes in the Blue Nile basin', Water

  16. Hic Sunt Leones: Anomalous Scaling In Rainfall

    NASA Astrophysics Data System (ADS)

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

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

  17. Rainfall effects on rare annual plants

    USGS Publications Warehouse

    Levine, J.M.; McEachern, A.K.; Cowan, C.

    2008-01-01

    1. Variation in climate is predicted to increase over much of the planet this century. Forecasting species persistence with climate change thus requires understanding of how populations respond to climate variability, and the mechanisms underlying this response. Variable rainfall is well known to drive fluctuations in annual plant populations, yet the degree to which population response is driven by between-year variation in germination cueing, water limitation or competitive suppression is poorly understood. 2. We used demographic monitoring and population models to examine how three seed banking, rare annual plants of the California Channel Islands respond to natural variation in precipitation and their competitive environments. Island plants are particularly threatened by climate change because their current ranges are unlikely to overlap regions that are climatically favourable in the future. 3. Species showed 9 to 100-fold between-year variation in plant density over the 5-12 years of censusing, including a severe drought and a wet El Nin??o year. During the drought, population sizes were low for all species. However, even in non-drought years, population sizes and per capita growth rates showed considerable temporal variation, variation that was uncorrelated with total rainfall. These population fluctuations were instead correlated with the temperature after the first major storm event of the season, a germination cue for annual plants. 4. Temporal variation in the density of the focal species was uncorrelated with the total vegetative cover in the surrounding community, suggesting that variation in competitive environments does not strongly determine population fluctuations. At the same time, the uncorrelated responses of the focal species and their competitors to environmental variation may favour persistence via the storage effect. 5. Population growth rate analyses suggested differential endangerment of the focal annuals. Elasticity analyses and life

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

    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

  20. Country-wide rainfall maps from cellular communication networks

    NASA Astrophysics Data System (ADS)

    Leijnse, Hidde; Overeem, Aart; Uijlenhoet, Remko

    2013-04-01

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

  1. Impacts of rainfall variability and expected rainfall changes on cost-effective adaptation of water systems to climate change.

    PubMed

    van der Pol, T D; van Ierland, E C; Gabbert, S; Weikard, H-P; Hendrix, E M T

    2015-05-01

    Stormwater drainage and other water systems are vulnerable to changes in rainfall and runoff and need to be adapted to climate change. This paper studies impacts of rainfall variability and changing return periods of rainfall extremes on cost-effective adaptation of water systems to climate change given a predefined system performance target, for example a flood risk standard. Rainfall variability causes system performance estimates to be volatile. These estimates may be used to recurrently evaluate system performance. This paper presents a model for this setting, and develops a solution method to identify cost-effective investments in stormwater drainage adaptations. Runoff and water levels are simulated with rainfall from stationary rainfall distributions, and time series of annual rainfall maxima are simulated for a climate scenario. Cost-effective investment strategies are determined by dynamic programming. The method is applied to study the choice of volume for a storage basin in a Dutch polder. We find that 'white noise', i.e. trend-free variability of rainfall, might cause earlier re-investment than expected under projected changes in rainfall. The risk of early re-investment may be reduced by increasing initial investment. This can be cost-effective if the investment involves fixed costs. Increasing initial investments, therefore, not only increases water system robustness to structural changes in rainfall, but could also offer insurance against additional costs that would occur if system performance is underestimated and re-investment becomes inevitable. PMID:25704748

  2. Vector generalized additive models for extreme rainfall data analysis (study case rainfall data in Indramayu)

    NASA Astrophysics Data System (ADS)

    Utami, Eka Putri Nur; Wigena, Aji Hamim; Djuraidah, Anik

    2016-02-01

    Rainfall pattern are good indicators for potential disasters. Global Circulation Model (GCM) contains global scale information that can be used to predict the rainfall data. Statistical downscaling (SD) utilizes the global scale information to make inferences in the local scale. Essentially, SD can be used to predict local scale variables based on global scale variables. SD requires a method to accommodate non linear effects and extreme values. Extreme value Theory (EVT) can be used to analyze the extreme value. One of methods to identify the extreme events is peak over threshold that follows Generalized Pareto Distribution (GPD). The vector generalized additive model (VGAM) is an extension of the generalized additive model. It is able to accommodate linear or nonlinear effects by involving more than one additive predictors. The advantage of VGAM is to handle multi response models. The key idea of VGAM are iteratively reweighted least square for maximum likelihood estimation, penalized smoothing, fisher scoring and additive models. This works aims to analyze extreme rainfall data in Indramayu using VGAM. The results show that the VGAM with GPD is able to predict extreme rainfall data accurately. The prediction in February is very close to the actual value at quantile 75.

  3. A robust estimator of rainfall rate using differential reflectivity

    NASA Technical Reports Server (NTRS)

    Gorgucci, Eugenio; Scarchilli, Gianfranco; Chandrasekar, V.

    1994-01-01

    Conventional estimator of rainfall rate using reflectivity factor and differential reflectivity Z(sub DR) becomes unstable when the measured values of Z(sub DR) are small due to measurement errors. An alternate estimator of rainfall rate using reflectivity factor and Z(sub DR) is derived, so that this estimator is fairly robust over the full dynamic range of reflectivity factor and Z(sub DR). Simulations are used to study the error structure of this robust estimator in comparison with the conventional estimator of rainfall rate. It is shown that the alternate estimator performs better than the conventional estimator of rainfall rate at all rainfall values. In particular the largest improvement of this estimator is proved to be in light rain. The robust estimator is obtained as a direct regression of rainfall rate against reflectivity factor and Z(sub DR) instead of solving for the drop size distribution.

  4. Estimation of rainfall using remote sensing for Riyadh climate, KSA

    NASA Astrophysics Data System (ADS)

    AlHassoun, Saleh A.

    2013-05-01

    Rainfall data constitute an important parameter for studying water resources-related problems. Remote sensing techniques could provide rapid and comprehensive overview of the rainfall distribution in a given area. Thus, the infrared data from the LandSat satellite in conjunction with the Scofield-oliver method were used to monitor and model rainfall in Riyadh area as a resemble of any area in the Kingdom of Saudi Arabia(KSA). Four convective clouds that covered two rain gage stations were analyzed. Good estimation of rainfall was obtained from satellite images. The results showed that the satellite rainfall estimations were well correlated to rain gage measurements. The satellite climate data appear to be useful for monitoring and modeling rainfall at any area where no rain gage is available.

  5. Satellite and gauge rainfall merging using geographically weighted regression

    NASA Astrophysics Data System (ADS)

    Hu, Q.; Yang, H.; Meng, X.; Wang, Y.; Deng, P.

    2015-05-01

    A residual-based rainfall merging scheme using geographically weighted regression (GWR) has been proposed. This method is capable of simultaneously blending various satellite rainfall data with gauge measurements and could describe the non-stationary influences of geographical and terrain factors on rainfall spatial distribution. Using this new method, an experimental study on merging daily rainfall from the Climate Prediction Center Morphing dataset (CMOROH) and gauge measurements was conducted for the Ganjiang River basin, in Southeast China. We investigated the capability of the merging scheme for daily rainfall estimation under different gauge density. Results showed that under the condition of sparse gauge density the merging rainfall scheme is remarkably superior to the interpolation using just gauge data.

  6. A description and evaluation of FAO satellite rainfall estimation algorithm

    NASA Astrophysics Data System (ADS)

    Dinku, Tufa; Alessandrini, Stefano; Evangelisti, Mauro; Rojas, Oscar

    2015-09-01

    There are ongoing efforts to improve the accuracy of satellite rainfall estimates. One of these efforts comes from the Food and Agriculture Organization (FAO) of the United Nations. The FAO effort involves combining satellite rainfall estimates and meteorological model outputs with station measurements. The algorithm of the FAO satellite rainfall estimates (FAO-RFE) is presented and evaluated by comparing with raingauge data and other satellite rainfall products over eastern and western parts of Africa. The evaluations were done at daily and ten-daily time scales. The FAO-RFE has shown significant improvement over the individual inputs. However, comparison of FAO-RFE with other satellite rainfall products has shown a slight improvement only over areas with good station input. The main weakness of the FAO-RFE is that it overestimates rainfall occurrences, which is attributed to the forecast product used in the algorithm.

  7. Adequacy of satellite derived rainfall data for stream flow modeling

    USGS Publications Warehouse

    Artan, G.; Gadain, Hussein; Smith, Jody L.; Asante, Kwasi; Bandaragoda, C.J.; Verdin, J.P.

    2007-01-01

    Floods are the most common and widespread climate-related hazard on Earth. Flood forecasting can reduce the death toll associated with floods. Satellites offer effective and economical means for calculating areal rainfall estimates in sparsely gauged regions. However, satellite-based rainfall estimates have had limited use in flood forecasting and hydrologic stream flow modeling because the rainfall estimates were considered to be unreliable. In this study we present the calibration and validation results from a spatially distributed hydrologic model driven by daily satellite-based estimates of rainfall for sub-basins of the Nile and Mekong Rivers. The results demonstrate the usefulness of remotely sensed precipitation data for hydrologic modeling when the hydrologic model is calibrated with such data. However, the remotely sensed rainfall estimates cannot be used confidently with hydrologic models that are calibrated with rain gauge measured rainfall, unless the model is recalibrated. ?? Springer Science+Business Media, Inc. 2007.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  9. Satellite rainfall retrieval by logistic regression

    NASA Technical Reports Server (NTRS)

    Chiu, Long S.

    1986-01-01

    The potential use of logistic regression in rainfall estimation from satellite measurements is investigated. Satellite measurements provide covariate information in terms of radiances from different remote sensors.The logistic regression technique can effectively accommodate many covariates and test their significance in the estimation. The outcome from the logistical model is the probability that the rainrate of a satellite pixel is above a certain threshold. By varying the thresholds, a rainrate histogram can be obtained, from which the mean and the variant can be estimated. A logistical model is developed and applied to rainfall data collected during GATE, using as covariates the fractional rain area and a radiance measurement which is deduced from a microwave temperature-rainrate relation. It is demonstrated that the fractional rain area is an important covariate in the model, consistent with the use of the so-called Area Time Integral in estimating total rain volume in other studies. To calibrate the logistical model, simulated rain fields generated by rainfield models with prescribed parameters are needed. A stringent test of the logistical model is its ability to recover the prescribed parameters of simulated rain fields. A rain field simulation model which preserves the fractional rain area and lognormality of rainrates as found in GATE is developed. A stochastic regression model of branching and immigration whose solutions are lognormally distributed in some asymptotic limits has also been developed.

  10. Development of a rainfall model to study rainfall over South Africa using satellite microwave remote sensing

    NASA Astrophysics Data System (ADS)

    Mishra, Anoop Kumar; Rawat, Kishan Singh

    2015-01-01

    In this study, a rainfall model is developed to study rainfall over South Africa (10° to 40°E, 35° to 20°S) using a set of rainfall signatures derived from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) observations at 0.25 deg×0.25 deg spatial grid. Based on measurements at 19-, 21-, and 85-GHz channels of TMI, the scattering index (SI) is derived. Polarization corrected temperature (PCT) is calculated using measurements at the 85-GHz channel. SI, PCT, and their combinations are tested as rain signatures over South Africa. These rain signatures (i.e., PCT and SI and their combinations) are collocated against precipitation radar (PR) onboard TRMM to derive a relationship between rain rate and rain signatures. Rainfall retrieval is attempted using linear as well as nonlinear regressions. The results have been validated using an independent dataset of PR. It is reported that a nonlinear regression outperforms a linear algorithm. Statistical validation with an independent dataset of PR exhibits the correlation coefficients (CCs) of 0.60, 0.64, and 0.66, and root mean square errors (RMSEs) of 5.82, 6.42, and 5.76 mm/h from observations of SI, PCT, and a combination of SI and PCT, respectively, using linear regressions. When nonlinear regression is used, the CC of 0.69, 0.68, and 0.70 and RMSE of 4.75, 4.89, and 4.38 mm/h are observed from the SI, PCT, and the combination of SI and PCT, respectively.

  11. 100 years of Belgian rainfall: are there trends?

    PubMed

    Vaes, G; Willems, P; Berlamont, J

    2002-01-01

    In 1999 the digitisation of old rainfall records of measurements at Uccle (Belgium) was completed, which resulted in a unique rainfall series of 100 years (period 1898-1997). This is an ideal opportunity to search for trends in the rainfall over the last century. Large variations in rainfall probability over the century have been observed. For small aggregation levels there is a small decrease in extreme rainfall events over the century. For large aggregation levels there is a more explicit increase in extreme rainfall. Because the rainfall on seasonal aggregation level is only slightly increased, the increase in extreme rainfall events for aggregation levels between a few days and a few months can only occur due to larger clustering. However, the final conclusion is that no significant trend can be observed. A pure random variation of the rainfall can cause equally large variations. This does not exclude a possible trend in flooding frequency, due to the strong increase in urbanisation over the last century. PMID:11888184

  12. Derivation of critical rainfall thresholds for landslide in Sicily

    NASA Astrophysics Data System (ADS)

    Caracciolo, Domenico; Arnone, Elisa; Noto, Leonardo V.

    2015-04-01

    Rainfall is the primary trigger of shallow landslides that can cause fatalities, damage to properties and economic losses in many areas of the world. For this reason, determining the rainfall amount/intensity responsible for landslide occurrence is important, and may contribute to mitigate the related risk and save lives. Efforts have been made in different countries to investigate triggering conditions in order to define landslide-triggering rainfall thresholds. The rainfall thresholds are generally described by a functional relationship of power in terms of cumulated or intensity event rainfall-duration, whose parameters are estimated empirically from the analysis of historical rainfall events that triggered landslides. The aim of this paper is the derivation of critical rainfall thresholds for landslide occurrence in Sicily, southern Italy, by focusing particularly on the role of the antecedent wet conditions. The creation of the appropriate landslide-rainfall database likely represents one of main efforts in this type of analysis. For this work, historical landslide events occurred in Sicily from 1919 to 2001 were selected from the archive of the Sistema Informativo sulle Catastrofi Idrogeologiche, developed under the project Aree Vulnerabili Italiane. The corresponding triggering precipitations were screened from the raingauges network in Sicily, maintained by the Osservatorio delle Acque - Agenzia Regionale per i Rifiuti e le Acque. In particular, a detailed analysis was carried out to identify and reconstruct the hourly rainfall events that caused the selected landslides. A bootstrapping statistical technique has been used to determine the uncertainties associated with the threshold parameters. The rainfall thresholds at different exceedance probability levels, from 1% to 10%, were defined in terms of cumulated event rainfall, E, and rainfall duration, D. The role of rainfall prior to the damaging events was taken into account by including in the analysis

  13. Rainfall Morphology in Semi-Tropical Convergence Zones

    NASA Technical Reports Server (NTRS)

    Shepherd, J. Marshall; Ferrier, Brad S.; Ray, Peter S.

    2000-01-01

    Central Florida is the ideal test laboratory for studying convergence zone-induced convection. The region regularly experiences sea breeze fronts and rainfall-induced outflow boundaries. The focus of this study is the common yet poorly-studied convergence zone established by the interaction of the sea breeze front and an outflow boundary. Previous studies have investigated mechanisms primarily affecting storm initiation by such convergence zones. Few have focused on rainfall morphology yet these storms contribute a significant amount precipitation to the annual rainfall budget. Low-level convergence and mid-tropospheric moisture have both been shown to correlate with rainfall amounts in Florida. Using 2D and 3D numerical simulations, the roles of low-level convergence and mid-tropospheric moisture in rainfall evolution are examined. The results indicate that time-averaged, vertical moisture flux (VMF) at the sea breeze front/outflow convergence zone is directly and linearly proportional to initial condensation rates. This proportionality establishes a similar relationship between VMF and initial rainfall. Vertical moisture flux, which encompasses depth and magnitude of convergence, is better correlated to initial rainfall production than surface moisture convergence. This extends early observational studies which linked rainfall in Florida to surface moisture convergence. The amount and distribution of mid-tropospheric moisture determines how rainfall associated with secondary cells develop. Rainfall amount and efficiency varied significantly over an observable range of relative humidities in the 850- 500 mb layer even though rainfall evolution was similar during the initial or "first-cell" period. Rainfall variability was attributed to drier mid-tropospheric environments inhibiting secondary cell development through entrainment effects. Observationally, 850-500 mb moisture structure exhibits wider variability than lower level moisture, which is virtually always

  14. A multicomponent self-similar characterization of rainfall fluctuations

    SciTech Connect

    Kumar, P.; Foufoula-Georgiou, E.

    1996-12-31

    Issues of scaling characteristics in spatial rainfall have attracted increasing attention over the last decade. Several models based on simple/multi scaling and multifractal ideas have been put forth and parameter estimation techniques developed for the hypothesized models. Simulations based on these models have realistic resemblance to {open_quotes}generic rainfall fields{close_quotes}. In this research we analyze rainfall data for scaling characteristics without an a priori assumed model. We look at the behavior of rainfall fluctuations obtained at several scales, via orthogonal wavelet transform of the data, to infer the precise nature of scaling exhibited by spatial rainfall. The essential idea behind the analysis is to segregate large scale (long wavelength) features from small scale features and study them independently of each other. The hypothesis is set forward that rainfall might exhibit scaling in small scale fluctuations, if at all, and at large scale this behavior will break down to accommodate the effects of external factors affecting the particular rain producing mechanism. The validity of this hypothesis is examined. In addition we define and estimate parameters that characterize the spatial dependence of the rainfall fluctuations and we use these parameters, estimated for several frames (in time), to relate to and identify the evolutionary nature of rainfall. These parameters and the type of scaling show significant variation from one rainfall field to another.

  15. Estimating rainfall in the tropics using the fractional time raining

    NASA Technical Reports Server (NTRS)

    Morrissey, Mark L.; Krajewski, Witold F.; Mcphaden, Michael J.

    1994-01-01

    The relationship between the fractional time raining and tropical rainfall amount is investigated using raingage data and a point process model of tropical rainfall. Both the strength and the nature of the relationship are dependent upon the resolution of the data used to estimate the fractional time raining. It is found that highly accurate estimates of rainfall amounts over periods of one month or greater can be obtained from the fractional time raining so long as high-time-resolution data are used. It is demonstrated that the relationship between the fractional time raining and monthly atoll rainfall is quasi-homogeneous within the monsoon trough region of the equatorial western Pacific.

  16. Developing seasonal rainfall scenarios for food security early warning

    NASA Astrophysics Data System (ADS)

    Husak, Gregory J.; Funk, Christopher C.; Michaelsen, Joel; Magadzire, Tamuka; Goldsberry, Kirk P.

    2013-10-01

    Rainfed agriculture in Sub-Saharan Africa accounts for 95 % of the local cereal production, impacting hundreds of millions of people. Early identification of poor rainfall conditions is a critical indicator of food security. As such, monitoring accumulated seasonal rainfall gives an important mid-season estimate of final accumulated totals. However, characterizing the remaining uncertainty in a season has largely been ignored by the food security community. This paper presents a new technique describing rainfall conditions over the duration of a crop-growing cycle by combining estimated rainfall-to-date with potential scenarios for the remaining season based on available satellite rainfall estimates, the common tool for rainfall analysis in Africa. The limited historical record provided by satellite rainfall estimates using previous seasons provides only a coarse view of likely seasonal totals. To combat this, scenarios developed by bootstrapping dekadal data to create synthetic seasons allow for a finer understanding of potential seasonal accumulations. Updating this throughout the season shows a narrowing envelope of seasonal totals, converging on the final seasonal result. The resulting scenarios inform the expectations for the final seasonal rainfall accumulation, allowing analysts to quantify and visualize the uncertainty in seasonal totals. Giving decision makers a tool for understanding the likelihood of specific rainfall amounts provides additional time to enact and mobilize efforts to reduce the impact of agricultural drought.

  17. Requirements for future development of small scale rainfall simulators

    NASA Astrophysics Data System (ADS)

    Iserloh, Thomas; Ries, Johannes B.; Seeger, Manuel

    2013-04-01

    Rainfall simulation with small scale simulators is a method used worldwide to assess the generation of overland flow, soil erosion, infiltration and interrelated processes such as soil sealing, crusting, splash and redistribution of solids and solutes. Following the outcomes of the project "Comparability of simulation results of different rainfall simulators as input data for soil erosion modelling (Deutsche Forschungsgemeinschaft - DFG, Project No. Ri 835/6-1)" and the "International Rainfall Simulator Workshop 2011" in Trier, the necessity for further technical improvements of simulators and strategies towards an adaption of designs and methods becomes obvious. Uniform measurements of artificially generated rainfall and comparative measurements on a prepared bare fallow with rainfall simulators used by European research groups showed limitations of the comparability of the results. The following requirements, essential for small portable rainfall simulators, were identified: (I) Low and efficient water consumption for use in areas with water shortage, (II) easy handling and control of test conditions, (III) homogeneous spatial rainfall distribution, (IV) best possible drop spectrum (physically), (V) reproducibility and knowledge of spatial distribution and drop spectrum, (VI) easy and fast training of operators to obtain reproducible experiments and (VII) good mobility and easy installation for use in remote areas and in regions where highly erosive rainfall events are rare or irregular. The presentation discusses possibilities for a common use of identical plot designs, rainfall intensities and nozzles.

  18. River flow mass exponents with fractal channel networks and rainfall

    USGS Publications Warehouse

    Troutman, B.M.; Over, T.M.

    2001-01-01

    An important problem in hydrologic science is understanding how river flow is influenced by rainfall properties and drainage basin characteristics. In this paper we consider one approach, the use of mass exponents, in examining the relation of river flow to rainfall and the channel network, which provides the primary conduit for transport of water to the outlet in a large basin. Mass exponents, which characterize the power-law behavior of moments as a function of scale, are ideally suited for defining scaling behavior of processes that exhibit a high degree of variability or intermittency. The main result in this paper is an expression relating the mass exponent of flow resulting from an instantaneous burst of rainfall to the mass exponents of spatial rainfall and that of the network width function. Spatial rainfall is modeled as a random multiplicative cascade and the channel network as a recursive replacement tree; these fractal models reproduce certain types of self-similar behavior seen in actual rainfall and networks. It is shown that under these modeling assumptions the scaling behavior of flow mirrors that of rainfall if rainfall is highly variable in space, and on the other hand flow mirrors the structure of the network if rainfall is not so highly variable. ?? 2001 Elsevier Science Ltd. All rights reserved.

  19. Landslide occurrences and recurrence intervals of heavy rainfalls in Japan

    NASA Astrophysics Data System (ADS)

    Saito, H.; Uchida, T.; Matsuyama, H.; Korup, O.

    2015-12-01

    Dealing with predicted increases in extreme weather conditions due to climate change requires robust knowledge about controls on rainfall-triggered landslides. This study developed the probable rainfall database from weather radar data, and analyzed the potential correlation between the landslide magnitude-frequency and the recurrence interval of the heavy rainfall across Japan. We analyzed 4,744 rainfall-induced landslides (Saito et al., 2014, Geology), 1 to 72 h rainfalls, and soil water index (SWI). We then estimated recurrence intervals for these rainfall parameters using a Gumbel distribution with jackknife fitting. Results showed that the recurrence intervals of rainfall events which caused landslides (<10^3 m^3) were less than 10 yr across Japan. The recurrence intervals increased with increases in landslide volumes. With regard to the landslides larger than 10^5 m^3, recurrence intervals of the rainfall events were more than 100 yr. These results suggest that recurrence intervals of heavy rainfalls are important for assessing regional landslide hazard in Japan.

  20. Iranian rainfall series analysis by means of nonparametric tests

    NASA Astrophysics Data System (ADS)

    Talaee, P. Hosseinzadeh

    2014-05-01

    The study of the trends and fluctuations in rainfall has received a great deal of attention, since changes in rainfall patterns may lead to floods or droughts. The objective of this study was to analyze the annual, seasonal, and monthly rainfall time series at seven rain gauge stations in the west of Iran for a 40-year period (from October 1969 to September 2009). The homogeneity of the rainfall data sets at the rain gauge stations was checked by using the cumulative deviations test. Three nonparametric tests, namely Kendall, Spearman, and Mann-Kendall, at the 95 % confidence level were used for the trend analysis and the Theil-Sen estimator was applied for determining the magnitudes of the trends. According to the homogeneity analysis, all of the rainfall series except the September series at Vasaj station were found to be homogeneous. The obtained results showed an insignificant trend in the annual and seasonal rainfall series at the majority of the considered stations. Moreover, only three significant trends were observed at the February rainfall of Aghajanbolaghi station, the November series of Vasaj station, and the March rainfall series of Khomigan station. The findings of this study on the temporal trends of rainfall can be implemented to improve the water resources strategies in the study region.

  1. Estimation of the fractional coverage of rainfall in climate models

    SciTech Connect

    Eltahir, E.A.B.; Bras, R.L. )

    1993-04-01

    The fraction of the grid cell area covered by rainfall, [mu], is a very important parameter in the descriptions of land surface hydrology in climate models. A simple procedure is presented for estimating this fraction, on extensive observations of storm areas and rainfall volumes. It is often observed that storm area and rainfall volume are linearly related. This relation is utilized in rainfall measurement to compute rainfall volume from radar observations of the storm area. The authors suggest that the same relation be used to compute the storm area from the volume of rainfall simulated by a climate model. A formula is developed for computing [mu], which describes the dependence of the fractional coverage of rainfall on the season of the year, the geographical region, rainfall volume, spatial resolution of the model, and the temporal resolution of the model. The new formula is applied in computing [mu] over the Amazon region. Significant temporal variability in the fractional coverage of rainfall is demonstrated. The implications of this variability for the modeling of land surface hydrology in climate models are discussed. 16 refs., 3 figs., 1 tab.

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

    NASA Astrophysics Data System (ADS)

    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

  3. Empirical rainfall thresholds for landslide occurrence in Portugal

    NASA Astrophysics Data System (ADS)

    Zêzere, José Luis; Vaz, Teresa; Pereira, Susana; Oliveira, Sérgio C.; Marques, Rui; Garcia, Ricardo A. C.

    2015-04-01

    Rainfall is the most important physical process responsible for the landslide triggering in Portugal. Following the work of Zêzere et al. (2014), we present the state of the art concerning the proposition of empirical rainfall thresholds in Portugal for different types of landslides observed in different zones of the country: the Lisbon region, the Douro Valley and the NW Mountains, and the Povoação Municipality in São Miguel Island (Azores). The empirical thresholds applied in Portugal are based on the identification of 120 landslide events and include (i) the computation of antecedent rainfall threshold defined by linear regression, (ii) the normalization of rainfall by the mean annual precipitation, (iii) the definition of combined rainfall thresholds, which integrates the rainfall event and the antecedent rainfall for different time periods, and (iv) the definition of lower limit and upper limit rainfall thresholds. The intensity-duration (ID) threshold is the empirical rainfall threshold more used worldwide. In mainland Portugal, the highest ID rainfall threshold is registered in the NW Mountains, which is the rainiest zone of the country. The Lisbon Region typically receives less rain per year and the corresponding ID threshold is lower than that obtained in the north part of the country. The Povoação study area evidence a contrasting situation, which is associated to the highest value of the negative exponential of the threshold (-0.66). As a consequence, for short duration (< 10 h) this threshold is only exceeded in the NW Mountains, while for long durations (>1,000 h) it is below the remaining thresholds. The normalization of the ID threshold by the mean annual precipitation (MAP) has showed that, in relative terms: (i) the ID threshold is highest in Lisbon Region for duration less than 50 h; (ii) in the north of the country, the ID threshold is more exigent in the Douro Valley than in the NW Mountains and (iii) the ID threshold in Povoa

  4. Altitude control over rainfall-runoff relationship

    NASA Astrophysics Data System (ADS)

    Bartolini, Elisa; Allamano, Paola; Claps, Pierluigi; Laio, Francesco

    2010-05-01

    Mountainous areas are generally characterized by abundant water resources. In the past, this abundance of water has sometimes been considered as an unlimited resource and led to inappropriate management strategies. In this sense, an important aspect to account for when dealing with water allocation problems is the seasonality of water availability, especially considering the increasing competition between different water uses and the need for a sustainable resource exploitation (e.g. winter tourism, irrigation, hydropower generation). A valuable tool for the control of water management strategies is the runoff regime, intended as the curve of the mean monthly runoff values. Runoff regime prediction in high elevation sites represents a challenging topic due to a number of factors: i) the dynamics of snow accumulation and melting largely affects the timing and the volumes of runoff; ii) the topographic heterogeneity requires detailed spatial characterization of the hydrologic variables; iii) the high spatial variability of precipitation in general is poorly described by meteorological network measurements. In this study a conceptual balance model is proposed aimed at the investigation of the fundamental mechanisms that influence the runoff regime in mountainous regions. The model adopts a temperature threshold to partition precipitation into rainfall and snow and to estimate evapotranspiration volumes. A statistical representation of the temperature regime is also introduced in order to capture the sub-monthly temperature variability (which significantly affects the snow processes). The effects of snow accumulation on the rainfall-runoff mechanism is investigated through a specific snowmelt module describing snowmelt as a non-linear function of temperature. The model is applied to 40 catchments in the North-Western Italian Alps and its performances are assessed by comparing measured and simulated runoff regimes both in terms of total bias and anomalies. The widely

  5. Historical trend of hourly extreme rainfall in Peninsular Malaysia

    NASA Astrophysics Data System (ADS)

    Syafrina, A. H.; Zalina, M. D.; Juneng, L.

    2015-04-01

    Hourly rainfall data between the years 1975 and 2010 across the Peninsular Malaysia were analyzed for trends in hourly extreme rainfall events. The analyses were conducted on rainfall occurrences during the northeast monsoon (November-February) known as NEM, the southwest monsoon (May-August) known as SWM, and the two inter-monsoon seasons, i.e., March-April (MA) and September-October (SO). Several extreme rainfall indices were calculated at the station level. The extreme rainfall events in Peninsular Malaysia showed an increasing trend between the years 1975 and 2010. The trend analysis was conducted using linear regression; no serial correlation was detected from the Durbin-Watson test. Ordinary kriging was used to determine the spatial patterns of trends in seasonal extremes. The total amount of rainfall received during NEM is higher compared to rainfall received during inter-monsoon seasons. However, intense rainfall is observed during the inter-monsoon season with higher hourly total amount of rainfall. The eastern part of peninsular was most affected by stratiform rains, while convective rain contributes more precipitation to areas in the western part of the peninsular. From the distribution of spatial pattern of trend, the extreme frequency index (Freq >20) gives significant contribution to the positive extreme rainfall trend during the monsoon seasons. Meanwhile, both extreme frequency and extreme intensity (24-Hr Max, Freq >95th, Tot >95th, Tot >99th, and Hr Max) indices give significant contribution to the positive extreme rainfall trend during the inter-monsoon seasons. Most of the significant extreme indices showed the positive sign of trends. However, a negative trend of extreme rainfall was found in the northwest coast due to the existence of Titiwangsa Range. The extreme intensity, extreme frequency, and extreme cumulative indices showed increasing trends during the NEM and MA while extreme intensity and extreme frequency had similar trends during

  6. Sources of uncertainty in rainfall maps from cellular communication networks

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  7. Inverse hydrological modelling of spatio-temporal rainfall patterns

    NASA Astrophysics Data System (ADS)

    Grundmann, Jens; Hörning, Sebastian; Bárdossy, András

    2016-04-01

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

  8. Automated reconstruction of rainfall events responsible for shallow landslides

    NASA Astrophysics Data System (ADS)

    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.

  9. Is a chaotic multi-fractal approach for rainfall possible?

    NASA Astrophysics Data System (ADS)

    Sivakumar, Bellie

    2001-04-01

    Applications of the ideas gained from fractal theory to characterize rainfall have been one of the most exciting areas of research in recent times. The studies conducted thus far have nearly unanimously yielded positive evidence regarding the existence of fractal behaviour in rainfall. The studies also revealed the insufficiency of the mono-fractal approaches to characterizing the rainfall process in time and space and, hence, the necessity for multi-fractal approaches. The assumption behind multi-fractal approaches for rainfall is that the variability of the rainfall process could be directly modelled as a stochastic (or random) turbulent cascade process, since such stochastic cascade processes were found to generically yield multi-fractals. However, it has been observed recently that multi-fractal approaches might provide positive evidence of a multi-fractal nature not only in stochastic processes but also in, for example, chaotic processes. The purpose of the present study is to investigate the presence of both chaotic and fractal behaviours in the rainfall process to consider the possibility of using a chaotic multi-fractal approach for rainfall characterization. For this purpose, daily rainfall data observed at the Leaf River basin in Mississippi are studied, and only temporal analysis is carried out. The autocorrelation function, the power spectrum, the empirical probability distribution function, and the statistical moment scaling function are used as indicators to investigate the presence of fractal, whereas the presence of chaos is investigated by employing the correlation dimension method. The results from the fractal identification methods indicate that the rainfall data exhibit multi-fractal behaviour. The correlation dimension method yields a low dimension, suggesting the presence of chaotic behaviour. The existence of both multi-fractal and chaotic behaviours in the rainfall data suggests the possibility of a chaotic multi-fractal approach for

  10. A Physically-based Tropical Cyclone Rainfall Model

    NASA Astrophysics Data System (ADS)

    Lu, P.; Lin, N.; Smith, J. A.; Emanuel, K.; Chavas, D. R.

    2015-12-01

    Rainfall from tropical cyclones (TCs) can cause extreme flooding. Predicting and understanding TC rainfall is thus important but has received relatively less attention, compared to the wind and surge. Here we present a simple, physically-based rainfall model, where the rain rate is obtained from estimated vertical velocity and specific humidity in the lower troposphere. The involved rainfall mechanisms include: 1) vertical motion at the top of the boundary layer owing to frictional effects; 2) vertical motion in the middle troposphere resulted from the time evolution of the gradient wind; 3) vertical motion forced by topographic interaction as well as 4) baroclinic effect. The model has been applied to Texas and shown to generate rainfall statistics comparable to observations (Zhu et al, 2013). Here we further evaluate this model on an event basis; case studies include Hurricane Irene (2011) and Isabel (2003). Without any calibration, hourly rainfall estimated from this model compares well with those from full numerical weather prediction model (WRF) as well as rainfall climatology models (R-CLIPPER and PHRaM). This comparison demonstrates the model's ability to capture main TC rainfall mechanisms, and it can be used as an effective tool to study the relative contribution of each rainfall mechanism. Ongoing work includes possibly improving the rainfall model by coupling it with a more accurate boundary layer model. Given its high computational efficiency, this rainfall model can be applied to large numbers of ensemble or synthetic simulations. This study fits into our long-term goal to quantify the risk of inland flooding associated with landfalling TCs.

  11. Decadal variability in Floods and Extreme Rainfall

    NASA Astrophysics Data System (ADS)

    Lall, Upmanu; Cioffi, Francesco; Devineni, Naresh; Lu, Mengqian

    2014-05-01

    Decadal variability in climate extremes associated with floods is of particular interest for infrastructure development and for insurance programs. From an analysis of US data we note that changes in insurance rates and in the construction of flood control infrastructure emerge soon after a period where there is a high incidence of regional flooding. This leads to the question of whether there is clustering in the incidence of anomalous flooding (or its absence) at decadal scales. The direct examination of this question from streamflow data is often clouded by the modification of flows by the construction of dams and other infrastructure to control floods, especially over a large river basin. Consequently, we explore the answer to this question through the analysis of both extreme rainfall and flood records. Spectral and time domain methods are used to identify the nature of decadal variability and its potential links to large scale climate.

  12. A rainfall simulator based on multifractal generator

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  13. An Online Module on Rainfall Runoff Processes

    NASA Astrophysics Data System (ADS)

    Tarboton, D. G.; Bandaragoda, C.; Kaheil, Y. H.; Zachry, M. R.; Reed, W. B.

    2003-12-01

    This paper will show an online module designed to provide a comprehensive and quantitative understanding of infiltration and runoff generation processes. This module was developed to fulfill National Weather Service training needs and is targeted at professionals with a college degree in science or engineering, and seniors or graduate students in a hydrologic science or engineering program. No prior knowledge on Rainfall Runoff Processes is required. The module first reviews the mechanisms involved in runoff generation and the pathways water takes moving to streams in different settings. The physical factors at the land surface that affect runoff are presented. This leads into a presentation of soil properties fundamental to the partitioning of water inputs at the earth surface and methods and procedures for the calculation of infiltration at a point. The module guides students through the detailed calculations involved. The module then ends with review of the simulation of runoff generation in hydrologic models such as TOPMODEL and the National Weather Service River Forecast System (NWSRFS). The online material takes advantage of streaming video and slide presentations as well as visualizations and computer animations that focus on key concepts. Substantive supporting material is given in the form of a PDF workbook that serves as a text. There is an online quiz at the end of each chapter designed to reinforce knowledge of the material covered in the section. The module compares answers to the solution and provides feedback. There is also an online final exam accessible once each chapter quiz has been attempted. The material in the early parts of the module is qualitative introducing the terminology and conceptual models involved in describing Rainfall Runoff processes. The latter parts of the module require users to perform quantitative calculations using a spreadsheet program such as Excel or an advanced engineering or scientific calculator. The module may be

  14. Measuring rainfall with low-cost cameras

    NASA Astrophysics Data System (ADS)

    Allamano, Paola; Cavagnero, Paolo; Croci, Alberto; Laio, Francesco

    2016-04-01

    In Allamano et al. (2015), we propose to retrieve quantitative measures of rainfall intensity by relying on the acquisition and analysis of images captured from professional cameras (SmartRAIN technique in the following). SmartRAIN is based on the fundamentals of camera optics and exploits the intensity changes due to drop passages in a picture. The main steps of the method include: i) drop detection, ii) blur effect removal, iii) estimation of drop velocities, iv) drop positioning in the control volume, and v) rain rate estimation. The method has been applied to real rain events with errors of the order of ±20%. This work aims to bridge the gap between the need of acquiring images via professional cameras and the possibility of exporting the technique to low-cost webcams. We apply the image processing algorithm to frames registered with low-cost cameras both in the lab (i.e., controlled rain intensity) and field conditions. The resulting images are characterized by lower resolutions and significant distortions with respect to professional camera pictures, and are acquired with fixed aperture and a rolling shutter. All these hardware limitations indeed exert relevant effects on the readability of the resulting images, and may affect the quality of the rainfall estimate. We demonstrate that a proper knowledge of the image acquisition hardware allows one to fully explain the artefacts and distortions due to the hardware. We demonstrate that, by correcting these effects before applying the image processing algorithm, quantitative rain intensity measures are obtainable with a good accuracy also with low-cost modules.

  15. Rainfall simulators - innovations seeking rainfall uniformity and automatic flow rate measurements

    NASA Astrophysics Data System (ADS)

    Bauer, Miroslav; Kavka, Petr; Strouhal, Luděk; Dostál, Tomáš; Krása, Josef

    2016-04-01

    Field rainfall simulators are used worldwide for many experimental purposes, such as runoff generation and soil erosion research. At CTU in Prague a laboratory simulator with swinging nozzles VeeJet has been operated since 2001. Since 2012 an additional terrain simulator is being used with 4 fixed FullJet 40WSQ nozzles with 2,4 m spacing and operating over two simultaneously sprinkled experimental plots sizing 8x2 and 1x1 m. In parallel to other research projects a specific problem was solved: improving rainfall spatial uniformity and overall intensity and surface runoff measurements. These fundamental variables significantly affect investigated processes as well as resulting water balance of the plot, therefore they need to be determined as accurately as possible. Although the original nozzles setting produced (commonly used) Christiansen uniformity index CU over 80 %, detailed measurements proved this index insufficient and showed many unrequired rainfall extremes within the plot. Moreover the number of rainfall intensity scenarios was limited and some of them required problematic multi-pressure operation of the water distribution system. Therefore the simulator was subjected to many substantial changes in 2015. Innovations ranged from pump intensification to control unit upgrade. As essential change was considered increase in number of nozzles to 9 in total and reducing their spacing to 1,2 m. However new uniformity measurements did not bring any significant improvement. Tested scenarios showed equal standard deviations of interpolated intensity rasters and equal or slightly lower CU index. Imperfections of sprinkling nozzles were found to be the limiting factor. Still many other benefits were brought with the new setup. Whole experimental plot 10x2 m is better covered with the rainfall while the water consumption is retained. Nozzles are triggered in triplets, which enables more rainfall intensity scenarios. Water distribution system is more stable due to

  16. NASA Finds Heavy Rainfall in Tropical Depression 8's Center

    NASA Video Gallery

    The core of newborn Tropical Depression 8 contained heavy rainfall. On Aug. 28, 2016 at 11 a.m. EDT GPM saw rainfall rates over 4.9 inches (124.8 mm) per hour in a few storms in the center of Tropi...

  17. Southern Hemisphere rainfall variability over the past 200 years

    NASA Astrophysics Data System (ADS)

    Gergis, Joëlle; Henley, Benjamin J.

    2016-05-01

    This study presents an analysis of three palaeoclimate rainfall reconstructions from the Southern Hemisphere regions of south-eastern Australia (SEA), southern South Africa (SAF) and southern South America (SSA). We provide a first comparison of rainfall variations in these three regions over the past two centuries, with a focus on identifying synchronous wet and dry periods. Despite the uncertainties associated with the spatial and temporal limitations of the rainfall reconstructions, we find evidence of dynamically-forced climate influences. An investigation of the twentieth century relationship between regional rainfall and the large-scale climate circulation features of the Pacific, Indian and Southern Ocean regions revealed that Indo-Pacific variations of the El Niño-Southern Oscillation (ENSO) and the Indian Ocean dipole dominate rainfall variability in SEA and SAF, while the higher latitude Southern Annular Mode (SAM) exerts a greater influence in SSA. An assessment of the stability of the regional rainfall-climate circulation modes over the past two centuries revealed a number of non-stationarities, the most notable of which occurs during the early nineteenth century around 1820. This corresponds to a time when the influence of ENSO on SEA, SAF and SSA rainfall weakens and there is a strengthening of the influence of SAM. We conclude by advocating the use of long-term palaeoclimate data to estimate decadal rainfall variability for future water resource management.

  18. The impact of Amazonian deforestation on Amazon basin rainfall

    NASA Astrophysics Data System (ADS)

    Spracklen, D. V.; Garcia-Carreras, L.

    2015-11-01

    We completed a meta-analysis of regional and global climate model simulations (n = 96) of the impact of Amazonian deforestation on Amazon basin rainfall. Across all simulations, mean (±1σ) change in annual mean Amazon basin rainfall was -12 ± 11%. Variability in simulated rainfall was not explained by differences in model resolution or surface parameters. Across all simulations we find a negative linear relationship between rainfall and deforestation extent, although individual studies often simulate a nonlinear response. Using the linear relationship, we estimate that deforestation in 2010 has reduced annual mean rainfall across the Amazon basin by 1.8 ± 0.3%, less than the interannual variability in observed rainfall. This may explain why a reduction in Amazon rainfall has not consistently been observed. We estimate that business-as-usual deforestation (based on deforestation rates prior to 2004) would lead to an 8.1 ± 1.4% reduction in annual mean Amazon basin rainfall by 2050, greater than natural variability.

  19. Artificial rainfall simulation of pressure wave generated runoff

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Previous gutter experiments, monitoring nearly a year of natural rainfall and subsequent runoff in a study plot situated on a hill slope at the USDA-ARS J, Phil Campbell Sr. Natural Resource Conservation Center in Watkinsville, Georgia, suggest a close relationship between rainfall intensity and sha...

  20. Diagnosing potential discrepancies in satellite rainfall estimates over Ethiopia

    NASA Astrophysics Data System (ADS)

    Young, Matthew; Williams, Charles; Chiu, Christine; Maidment, Ross; Chen, Shu-Hua

    2015-04-01

    Reliable satellite precipitation estimates are vital over many regions of Africa because of the importance of rainfall monitoring for rain-fed agriculture and water resources. In particular, regions with mountainous terrain pose a major challenge for satellite-based rainfall algorithms because retrievals based upon thermal infrared and microwave observations tend to miss orographic precipitation, often associated with warm temperatures and a weak scattering signal. To investigate the skill of satellite rainfall retrievals over mountainous terrain, we evaluate several satellite-based rainfall algorithms against rain gauge measurements over the mountainous Oromia region in Ethiopia. In particular, we assess the skill of rainfall retrieved from algorithms that only use thermal infrared observations and algorithms that combine both thermal infrared and microwave observations. We also investigate the dependency of retrievals on topography by classifying the relationship between the retrieval errors and elevation. Furthermore, we conduct high resolution simulations using the Weather Research and Forecasting model (WRF) during days with significant retrieval errors to determine how the errors relate to the characteristics of precipitation. A qualitative assessment of the vertical atmospheric structure and microphysical content of simulations reveals the potential sources of underestimation and overestimation in the rainfall algorithms. This study will highlight the importance of understanding regional precipitation systems causing uncertainties in satellite rainfall estimates, with a view toward using this knowledge to improve rainfall algorithms.

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

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

    A satellite infrared (IR) technique for estimating rainfall over northern South America is presented. The objectives are to examine the diurnal variability of rainfall and to investigate the relative contributions from the convective and stratiform components. In this study, we apply the Convective-Stratiform Technique (CST) of Adler and Negri (1988). The parameters of the original technique were re-calibrated using coincident rainfall estimates (Olson et W., 2000) derived from the Tropical Rain Measuring Mission (TRMM) Microwave Imager (TMI) and GOES IR (11 micrometer) observations. Local circulations were found to play a major role in modulating the rainfall and its diurnal cycle. These included land/sea circulations (notably along the northeast Brazilian coast and in the Gulf of Panama), mountain/valley circulations (along the Andes Mountains), and circulations associated with the presence of rivers. This last category was examined in detail along the Amazon R. east of Manaus. There we found an early morning rainfall maximum along the river (5 LT at 58W, 3 LT at 56W). Rainfall avoids the river in the afternoon (12 LT and later), notably at 56 W. The width of the river seems to be generating a land/river circulation which enhances early morning rainfall but inhibits afternoon rainfall. Results are compared to ground-based radar data collected during the Large-Scale Biosphere-Atmosphere (LBA) experiment in southwest Brazil, to monthly raingages in northeastern Brazil, and to data from the TRMM Precipitation Radar.

  2. Stochastic rainfall analysis for storm tank performance evaluation

    NASA Astrophysics Data System (ADS)

    Andrés-Doménech, I.; Montanari, A.; Marco, J. B.

    2010-07-01

    Stormwater detention tanks are widely used for mitigating impacts of combined sewer overflows (CSO) from urban catchments into receiving water bodies. The optimal size of detention tanks depends on climate and sewer system behaviours and can be estimated by using derived distribution approaches. They are based on using a stochastic model to fit the statistical pattern of observed rainfall records and a urban hydrology model to transform rainfall in sewer discharge. A key issue is the identification of the optimal structure of the stochastic rainfall model. Point processes are frequently applied, where rainfall events are schematised through the occurrence of rectangular pulses, which are governed by rainfall descriptors. In the presented model these latter descriptors are the interevent time (duration of the dry period between consecutive storms), event rainfall depth and event rainfall duration. This paper focuses on the analytical derivation of the probability distribution of the number and volume of overflows from the storm tank to the receiving water body for different and non-standard shapes of the probability distribution for above mentioned descriptors. The proposed approach is applied to 2 different sites in Spain: Valencia and Santander, located on the Mediterranean and northern Atlantic coastline, respectively. For both cases, it turned out that Pareto and Gamma-2 probability distributions for rainfall depth and duration provided a better fit than the exponential model, widely used in previous studies. A comparison between the two climatic zones, humid and semiarid, respectively, proves the key role played by climatic conditions for storm detention tanks sizing.

  3. Stochastic rainfall analysis for storm tank performance evaluation

    NASA Astrophysics Data System (ADS)

    Andrés-Doménech, I.; Montanari, A.; Marco, J. B.

    2010-03-01

    Stormwater detention tanks are widely used for mitigating impacts of combined sewer overflows (CSO) from urban catchments into receiving water bodies. The optimal size of detention tanks depends on climate and sewer system behaviours and can be estimated by using derived distribution approaches. They are based on using a stochastic model to fit the statistical pattern of observed rainfall records and a urban hydrology model to transform rainfall in sewer discharge. A key issue is the identification of the optimal structure of the stochastic rainfall model. Point processes are frequently applied where rainfall events are schematised through the occurrence of rectangular pulses, which are governed by rainfall descriptors. In the model herein used these latter descriptors are the interevent time (duration of the dry period between consecutive storms), event rainfall depth and event rainfall duration. This paper focuses on the analytical derivation of the probability distribution of the number and volume of overflows from the storm tank to the receiving water body for different and non-standard shapes of the probability distribution for above mentioned descriptors. The proposed approach is applied to 2 different sites in Spain: Valencia and Santander located on the Mediterranean and northern Atlantic coastline, respectively. For both cases, it turned out that Pareto and Gamma-2 probability distributions for rainfall depth and duration provided better fit than the exponential model, widely used in previous studies. A comparison between the two climatic zones, humid and semiarid, respectively, proves the key role played by climatic conditions for storm detention tanks sizing.

  4. Effects of rainfall on scatterometer derived wind speeds

    NASA Technical Reports Server (NTRS)

    Bliven, L. F.; Norcross, G.

    1988-01-01

    Rainfall modification of scatterometer response from the sea surface was simulated in wind-wave tank experiments. Data show that for a given wind speed, radar cross section increases as rainfall rate increases, but this effect decreases as wind speed increases. An empirical model accounts for these observations.

  5. Simulating diverse native C4 perennial grasses with varying rainfall

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  6. Rainfall hotspots over the southern tropical Andes: Spatial distribution, rainfall intensity, and relations with large-scale atmospheric circulation

    NASA Astrophysics Data System (ADS)

    Espinoza, Jhan Carlo; Chavez, Steven; Ronchail, Josyane; Junquas, Clémentine; Takahashi, Ken; Lavado, Waldo

    2015-05-01

    The Andes/Amazon transition is among the rainiest regions of the world and the interactions between large-scale circulation and the topography that determine its complex rainfall distribution remain poorly known. This work provides an in-depth analysis of the spatial distribution, variability, and intensity of rainfall in the southern Andes/Amazon transition, at seasonal and intraseasonal time scales. The analysis is based on comprehensive daily rainfall data sets from meteorological stations in Peru and Bolivia. We compare our results with high-resolution rainfall TRMM-PR 2A25 estimations. Hotspot regions are identified at low elevations in the Andean foothills (400-700 masl) and in windward conditions at Quincemil and Chipiriri, where more than 4000 mm rainfall per year are recorded. Orographic effects and exposure to easterly winds produce a strong annual rainfall gradient between the lowlands and the Andes that can reach 190 mm/km. Although TRMM-PR reproduces the spatial distribution satisfactorily, it underestimates rainfall by 35% in the hotspot regions. In the Peruvian hotspot, exceptional rainfall occurs during the austral dry season (around 1000 mm in June-July-August; JJA), but not in the Bolivian hotspot. The direction of the low-level winds over the Andean foothills partly explains this difference in the seasonal rainfall cycle. At intraseasonal scales in JJA, we found that, during northerly wind regimes, positive rainfall anomalies predominate over the lowland and the eastern flank of the Andes, whereas less rain falls at higher altitudes. On the other hand, during southerly regimes, rainfall anomalies are negative in the hotspot regions. The influence of cross-equatorial winds is particularly clear below 2000 masl.

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

    NASA Astrophysics Data System (ADS)

    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. Congo Basin rainfall climatology: can we believe the climate models?

    PubMed Central

    Washington, Richard; James, Rachel; Pearce, Helen; Pokam, Wilfried M.; Moufouma-Okia, Wilfran

    2013-01-01

    The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models. PMID:23878328

  9. Probabilistic Rainfall Simulation: Structural Analysis for Crop Index Insurance

    NASA Astrophysics Data System (ADS)

    Kaheil, Y. H.; Khalil, A. F.; Osgood, D. E.

    2008-12-01

    A new probabilistic methodology for rainfall simulation/record extension is presented here. The methodology extends the rainfall simulation component of the NOAA Ensemble Streamflow Prediction system which operates using the historical record of precipitation and temperature in combination with the current conditions to produce an ensemble of precipitation time series. In this methodology, a spatial relationship among adjacent stations with longer records is embedded to further enhance the result. Cross-ensemble- member probabilities are updated given spatial proximities. The method could be used to generate rainfall simulations whereby rainfall occurrence and amounts are modeled. The methodology has been applied in Adi Ha in Northern Ethiopia to extend the rainfall record. The extended record will be used to design a weather insurance contract for farmers in the area.

  10. Positive response of Indian summer rainfall to Middle East dust

    NASA Astrophysics Data System (ADS)

    Jin, Qinjian; Wei, Jiangfeng; Yang, Zong-Liang

    2014-06-01

    Using observational and reanalyses data, we investigated the impact of dust aerosols over the Middle East and the Arabian Sea (AS) on the Indian summer monsoon (ISM) rainfall. Satellite and aerosol reanalysis data show extremely heavy aerosol loading, mainly mineral dust, over the Middle East and AS during the ISM season. Multivariate empirical orthogonal function analyses suggest an aerosol-monsoon connection. This connection may be attributed to dust-induced atmospheric heating centered over the Iranian Plateau (IP), which enhances the meridional thermal contrast and strengthens the ISM circulation and rainfall. The enhanced circulation further transports more dust to the AS and IP, heating the atmosphere (positive feedback). The aerosols over the AS and the Arabian Peninsula have a significant correlation with rainfall over central and eastern India about 2 weeks later. This finding highlights the nonlocal radiative effect of dust on the ISM circulation and rainfall and may improve ISM rainfall forecasts.

  11. A clonal selection algorithm model for daily rainfall data prediction.

    PubMed

    Noor Rodi, N S; Malek, M A; Ismail, Amelia Ritahani; Ting, Sie Chun; Tang, Chao-Wei

    2014-01-01

    This study applies the clonal selection algorithm (CSA) in an artificial immune system (AIS) as an alternative method to predicting future rainfall data. The stochastic and the artificial neural network techniques are commonly used in hydrology. However, in this study a novel technique for forecasting rainfall was established. Results from this study have proven that the theory of biological immune systems could be technically applied to time series data. Biological immune systems are nonlinear and chaotic in nature similar to the daily rainfall data. This study discovered that the proposed CSA was able to predict the daily rainfall data with an accuracy of 90% during the model training stage. In the testing stage, the results showed that an accuracy between the actual and the generated data was within the range of 75 to 92%. Thus, the CSA approach shows a new method in rainfall data prediction. PMID:25429452

  12. Probabilistic rainfall thresholds for landslide occurrence using a Bayesian approach

    NASA Astrophysics Data System (ADS)

    Berti, M.; Martina, M.; Franceschini, S.; Pignone, S.; Simoni, A.; Pizziolo, M.

    2012-04-01

    Landslide rainfall thresholds are commonly defined as the critical value of two combined variables (e.g. rainfall duration and rainfall intensity) responsible for the occurrence of landslides in a given area. Various methods have been proposed in the literature to predict the rainfall conditions that are likely to trigger landslides, using for instance physically-based models or statistical analysis of historical catalogues. Most of these methods share an implicit deterministic view: the occurrence of landslides can be predicted by comparing the input value (rainfall conditions) with the threshold, and a single output (landslide or no-landslide) is only possible for a given input. In practical applications, however, a deterministic approach is not always applicable. Failure conditions are often achieved with a unique combination of many relevant factors (hydrologic response, weathering, changes in field stress, anthropic activity) and landslide triggering cannot be predicted by rainfall alone. When different outputs (landslide or no-landslide) can be obtained for the same input (rainfall conditions) a deterministic approach is no longer applicable and a probabilistic model is preferable. In this study we propose a new method to evaluate the rainfall thresholds based on Bayes probability. The method is simple, statistically rigorous, and provides a way to define thresholds in complex cases, when conventional approaches become highly subjective. The Bayes theorem is a direct application of conditional probabilities and it allows to computed the conditional probability to have a landslide (A) when a rainfall event of a given magnitude (B) is expected. The fundamental aspect of the Bayes approach is that the landslide probability P(A|B) depends not only on the observed probability of the triggering rainfall P(B|A), but also on the marginal probability of the expected rainfall event P(B). Therefore, both the rainfall that resulted in landslides and the rainfall that not

  13. Spatial Pattern of Rainfall Trends in Serbia (1961-2009)

    NASA Astrophysics Data System (ADS)

    Lukovic, J.; Bajat, B.; Blagojevic, D.; Kilibarda, M.

    2013-12-01

    This paper examines a spatial pattern of annual, seasonal and monthly rainfall trends in Serbia. The study used data from 63 meteorological stations between 1961 and 2009. The rainfall series was analyzed applying nonparametric method of the Mann Kendall test and Sen's method to determine the significance and magnitude of the trends. Interactive WEB maps were produced to obtain detailed insight in the spatial distribution of rainfall trends in Serbia. Seasonal trends at the confidence level of 95%, however, indicate a slight decrease in winter and spring precipitation and an increase in autumn precipitation. Results for monthly rainfall trends also generally showed non- significant trend, except positive for October (9 stations out of 63) and negative for May (6 stations out of 63). Calculated global autocorrelation statistics (Moran's I) indicate, in general, a random spatial pattern of rainfall trends on annual, seasonal and monthly time scales with exceptions for March, June and November.

  14. Large snowmelt versus rainfall events in the mountains

    NASA Astrophysics Data System (ADS)

    Fassnacht, Steven R.; Records, Rosemary M.

    2015-03-01

    While snow is the dominant precipitation type in mountain regions, estimates of rainfall are used for design, even though snowmelt provides most of the runoff. Daily data were used to estimate the 10 and 100 year, 24 h snowmelt, precipitation, and rainfall events at 90 Snow Telemetry stations across the Southern Rocky Mountains. Three probability distributions were compared, and the Pearson type III distribution yielded the most conservative estimates. Precipitation was on average 33% and 28% more than rainfall for the 10 and 100 year events. Snowfall exceeded rainfall at most of the stations and was on average 53% and 38% more for the 10 and 100 year events. On average, snowmelt was 15% and 8.9% more than precipitation. Where snow accumulation is substantial, it is recommended that snowmelt be considered in conjunction with rainfall and precipitation frequencies to develop flood frequencies.

  15. A statistical analysis of mesoscale rainfall as a random cascade

    NASA Technical Reports Server (NTRS)

    Gupta, Vijay K.; Waymire, Edward C.

    1993-01-01

    The paper considers the random cascade theory for spatial rainfall. Particular attention was given to the following four areas: (1) the relationship of the random cascade theory of rainfall to the simple scaling and the hierarchical cluster-point-process theories, (2) the mathematical foundations for some of the formalisms commonly applied in the develpment of statistical cascade theory, (3) the empirical evidence for a random cascade theory of rainfall, and (4) the way of using data for making estimates of parameters and for making statistical inference within this theoretical framework. An analysis of space-time rainfall data is presented. Cascade simulations are carried out to provide a comparison with methods of analysis that are applied to the rainfall data.

  16. Program control on the Tropical Rainfall Measuring Mission

    NASA Technical Reports Server (NTRS)

    Pennington, Dorothy J.; Majerowicw, Walter

    1994-01-01

    The Tropical Rainfall Measuring Mission (TRMM), an integral part of NASA's Mission to Planet Earth, is the first satellite dedicated to measuring tropical rainfall. TRMM will contribute to an understanding of the mechanisms through which tropical rainfall influences global circulation and climate. Goddard Space Flight Center's (GSFC) Flight Projects Directorate is responsible for establishing a Project Office for the TRMM to manage, coordinate, and integrate the various organizations involved in the development and operation of this complex satellite. The TRMM observatory, the largest ever developed and built inhouse at GSFC, includes state-of-the-art hardware. It will carry five scientific instruments designed to determine the rate of rainfall and the total rainfall occurring between the north and south latitudes of 35 deg. As a secondary science objective, TRMM will also measure the Earth's radiant energy budget and lightning.

  17. Rainfall variability and predictability issues for North America

    NASA Astrophysics Data System (ADS)

    Hunt, B. G.

    2016-04-01

    A multi-millennial simulation with a coupled global climatic model has been used to investigate extreme rainfall events, mainly droughts, over North America. A rainfall index, based on the US Dust Bowl region, was used to generate a time series from which the extreme events could be identified. A very wide range of drought and pluvial multiyear sequences was obtained, all attributable to internal climatic variability. This time series reproduced the basic characteristics of the corresponding observed time series. Composites of years with negative rainfall anomalies over North America from the simulation replicated the observed rainfall composite for the Dust Bowl era, both in spatial character and intensity. Examination of individual years of a simulated composite revealed not only a wide range of rainfall anomaly patterns, dominated by drought conditions, but also ENSO distributions that included El Niño events as well as the expected La Niña events. Composites for pluvial conditions over North America were associated with composited El Niño events, as expected. Correlation of the simulated Dust Bowl rainfall with global surface temperatures identified a principal connection with the ENSO region. No systematic relationship was obtained in the simulation between the Atlantic multidecadal oscillation and Dust Bowl region rainfall, with the simulated oscillation having a much more variable periodicity than that found in the limited observations. However, a marked connection was found for SST anomalies adjacent to the northeast coast of North America, but this appears to be forced by ENSO events. A scatter diagram of NINO3.4 SST anomalies with the Dust Bowl region rainfall anomalies, for observations and the simulation, revealed inconsistencies between the occurrence of an ENSO event and the "expected" rainfall anomaly. This, and other analysis, resulted in the conclusion that annual or longer term rainfall predictions over North America, with any systematic

  18. Primary productivity and its correlation with rainfall on Aldabra Atoll

    NASA Astrophysics Data System (ADS)

    Shekeine, J.; Turnbull, L. A.; Cherubini, P.; de Jong, R.; Baxter, R.; Hansen, D.; Bunbury, N.; Fleischer-Dogley, F.; Schaepman-Strub, G.

    2015-01-01

    Aldabra Atoll, a UNESCO World Heritage Site since 1982, hosts the world's largest population of giant tortoises. In view of recent rainfall declines in the East African region, it is important to assess the implications of local rainfall trends on the atoll's ecosystem and evaluate potential threats to the food resources of the giant tortoises. However, building an accurate picture of the effects of climate change requires detailed context-specific case-studies, an approach often hindered by data deficiencies in remote areas. Here, we present and analyse a new historical rainfall record of Aldabra atoll together with two potential measures of primary productivity: (1) tree-ring measurements of the deciduous tree species Ochna ciliata and, (2) satellite-derived NDVI (normalized difference vegetation index) data for the period 2001-2012. Rainfall declined by about 6 mm yr-1 in the last four decades, in agreement with general regional declines, and this decline could mostly be attributed to changes in wet-season rainfall. We were unable to cross-date samples of O. ciliata with sufficient precision to deduce long-term patterns of productivity. However, satellite data were used to derive Aldabra's land surface phenology (LSP) for the period 2001-2012 which was then linked to rainfall seasonality. This relationship was strongest in the eastern parts of the atoll (with a time-lag of about six weeks between rainfall changes and LSP responses), an area dominated by deciduous grasses that supports high densities of tortoises. While the seasonality in productivity, as reflected in the satellite record, is correlated with rainfall, we did not find any change in mean rainfall or productivity for the shorter period 2001-2012. The sensitivity of Aldabra's vegetation to rainfall highlights the potential impact of increasing water stress in East Africa on the region's endemic ecosystems.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  20. Rainfall estimation using moving cars as rain gauges - laboratory experiments

    NASA Astrophysics Data System (ADS)

    Rabiei, E.; Haberlandt, U.; Sester, M.; Fitzner, D.

    2013-11-01

    The spatial assessment of short time-step precipitation is a challenging task. Low density of observation networks, as well as the bias in radar rainfall estimation motivated the new idea of exploiting cars as moving rain gauges with windshield wipers or optical sensors as measurement devices. In a preliminary study, this idea has been tested with computer experiments (Haberlandt and Sester, 2010). The results have shown that a high number of possibly inaccurate measurement devices (moving cars) provide more reliable areal rainfall estimations than a lower number of precise measurement devices (stationary gauges). Instead of assuming a relationship between wiper frequency (W) and rainfall intensity (R) with an arbitrary error, the main objective of this study is to derive valid W-R relationships between sensor readings and rainfall intensity by laboratory experiments. Sensor readings involve the wiper speed, as well as optical sensors which can be placed on cars and are usually made for automating wiper activities. A rain simulator with the capability of producing a wide range of rainfall intensities is designed and constructed. The wiper speed and two optical sensors are used in the laboratory to measure rainfall intensities, and compare it with tipping bucket readings as reference. Furthermore, the effect of the car speed on the estimation of rainfall using a car speed simulator device is investigated. The results show that the sensor readings, which are observed from manual wiper speed adjustment according to the front visibility, can be considered as a strong indicator for rainfall intensity, while the automatic wiper adjustment show weaker performance. Also the sensor readings from optical sensors showed promising results toward measuring rainfall rate. It is observed that the car speed has a significant effect on the rainfall measurement. This effect is highly dependent on the rain type as well as the windshield angle.

  1. The contribution of tropical cyclones to rainfall in Mexico

    NASA Astrophysics Data System (ADS)

    Agustín Breña-Naranjo, J.; Pedrozo-Acuña, Adrián; Pozos-Estrada, Oscar; Jiménez-López, Salma A.; López-López, Marco R.

    Investigating the contribution of tropical cyclones to the terrestrial water cycle can help quantify the benefits and hazards caused by the rainfall generated from this type of hydro-meteorological event. Rainfall induced by tropical cyclones can enhance both flood risk and groundwater recharge, and it is therefore important to characterise its minimum, mean and maximum contributions to a region or country's water balance. This work evaluates the rainfall contribution of tropical depressions, storms and hurricanes across Mexico from 1998 to 2013 using the satellite-derived precipitation dataset TMPA 3B42. Additionally, the sensitivity of rainfall to other datasets was assessed: the national rain gauge observation network, real-time satellite rainfall and a merged product that combines rain gauges with non-calibrated space-borne rainfall measurements. The lower Baja California peninsula had the highest contribution from cyclonic rainfall in relative terms (∼40% of its total annual rainfall), whereas the contributions in the rest of the country showed a low-to-medium dependence on tropical cyclones, with mean values ranging from 0% to 20%. In quantitative terms, southern regions of Mexico can receive more than 2400 mm of cyclonic rainfall during years with significant TC activity. Moreover, (a) the number of tropical cyclones impacting Mexico has been significantly increasing since 1998, but cyclonic contributions in relative and quantitative terms have not been increasing, and (b) wind speed and rainfall intensity during cyclones are not highly correlated. Future work should evaluate the impacts of such contributions on surface and groundwater hydrological processes and connect the knowledge gaps between the magnitude of tropical cyclones, flood hazards, and economic losses.

  2. Influences of temporal rainfall radar and spatial rainfall-runoff model resolution on flood prediction

    NASA Astrophysics Data System (ADS)

    Weiler, Markus; Steinbrich, Andreas

    2013-04-01

    The rainfall-runoff-model DROGen (Distributed RunOff Generation) was developed to simulate runoff generation processes during floods and flash floods generation with a very high spatial resolution for the whole state of Baden-Württemberg in Southwest Germany. The model connects available spatial geo information with detailed process understanding at the plot and hillslope scale and is not calibrated. The model was successfully validated in 8 meso-scale watersheds with different geology, soils, topography and land-use and the results were very satisfying. We believe that the high spatial resolution of 1*1m² and a temporal resolution of 1 hour especially improved flow dynamics and the runoff concentration behaviour of the different runoff components. Some spatial information used by DROGen is available in very high resolution of 1*1m² (e.g. DEM and degree of sealing of land surface). Other data are much more generalized (e.g. soil information at the scale of 1:200.000) or at a fixed temporal resolution of one hour (e.g. calibrated precipitation radar data of the German weather survey (RADOLAN)). In order to find the adequate temporal and spatial resolution we investigated how the the spatial resolution of the geo data and the temporal resolution of the rainfall radar data effects the model result. Regarding the spatial resolution, we found, that the processes of runoff generation and runoff concentration are sensitive at different spatial scales. A decrease of spatial resolution from 1m to 25m lead to an implausible increase of the generation of saturation overland flow and to an accelerated concentration of subsurface flow, while Hortonian overland flow was almost not affected by the spatial resolution. For the model validation runs we realized that for short convective rain events a one hour resolution of the rainfall data might be not sufficient because of severe underestimation of peak intensities. We developed and tested a new method to estimate the temporal

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  4. Rainfall thresholds for the initiation of landslides in Italy

    NASA Astrophysics Data System (ADS)

    Peruccacci, S.; Brunetti, M. T.; Rossi, M.; Guzzetti, F.

    2009-04-01

    Rainfall is a recognized trigger of landslides, and various investigators have long attempted to determine the amount of precipitation needed to trigger slope failures, and to establish rainfall thresholds for the initiation of landslides. Determining the amount of rainfall needed to trigger a landslide is a problem of both scientific and societal interest, and the literature on the topic is vast. In this work, we describe an attempt to establish rainfall intensity - duration (ID) thresholds for the initiation of landslides in Italy. For the purpose, we have compiled a database of 562 rainfall events that have resulted in landslides. The rainfall and landslide information was obtained by searching the literature, including international journals, proceedings of regional, national and international conferences, and national, regional, and local technical and event reports describing single or multiple rainfall-induced landslides. We plot the rainfall intensity-duration values in logarithmic coordinates, and we establish that with increased rainfall duration the minimum average intensity likely to trigger shallow slope failures decreases linearly, in the range of durations from 10 minutes to 4 days. Based on this observation, we determine minimum ID thresholds for the possible initiation of landslides. The threshold curves are obtained from the empirical rainfall data using two objective statistical techniques, one that exploits Bayesian inference and one that uses a modelling tool in the R statistical environment. The two procedures avoid subjectivity in the determination of the thresholds, a problem that affects several of the published rainfall thresholds for the initiation of landslides. To cope with differences in the intensity and duration of rainfall likely to result in slope failures in different climatic regions, we normalize the rainfall information. Normalization is performed using two climate indexes, the Mean Annual Precipitation (MAP) and the Rainy

  5. A nested multisite daily rainfall stochastic generation model

    NASA Astrophysics Data System (ADS)

    Srikanthan, Ratnasingham; Pegram, Geoffrey G. S.

    2009-06-01

    SummaryThis paper describes a nested multisite daily rainfall generation model which preserves the statistics at daily, monthly and annual levels of aggregation. A multisite two-part daily model is nested in multisite monthly, then annual models. A multivariate set of fourth order Markov chains is used to model the daily occurrence of rainfall; the daily spatial correlation in the occurrence process is handled by using suitably correlated uniformly distributed variates via a Normal Scores Transform (NST) obtained from a set of matched multinormal pseudo-random variates, following Wilks [Wilks, D.S., 1998. Multisite generalisation of a daily stochastic precipitation generation model. Journal of Hydrology 210, 178-191]; we call it a hidden covariance model. A spatially correlated two parameter gamma distribution is used to obtain the rainfall depths; these values are also correlated via a specially matched hidden multinormal process. For nesting, the generated daily rainfall sequences at all the sites are aggregated to monthly rainfall values and these values are modified by a set of lag-1 autoregressive multisite monthly rainfall models. The modified monthly rainfall values are aggregated to annual rainfall and these are then modified by a lag-1 autoregressive multisite annual model. This nesting process ensures that the daily, monthly and annual means and covariances are preserved. The model was applied to a region with 30 rainfall sites, one of the five sets reported by Srikanthan [Srikanthan, R., 2005. Stochastic Generation of Daily Rainfall Data at a Number of Sites. Technical Report 05/7, CRC for Catchment Hydrology. Monash University, 66p]. A comparison of the historical and generated statistics shows that the model preserves all the important characteristics of rainfall at the daily, monthly and annual time scales, including the spatial structure. There are some outstanding features that need to be improved: depths of rainfall on isolated wet days and

  6. A rainfall spatial interpolation algorithm based on inhomogeneous kernels

    NASA Astrophysics Data System (ADS)

    Campo, Lorenzo; Fiori, Elisabetta; Molini, Luca

    2015-04-01

    Rainfall fields constitute the main input of hydrological distributed models, both for long period water balance and for short period flood forecast and monitoring. The importance of an accurate reconstruction of the spatial pattern of rainfall is, thus, well recognized in several fields of application: agricultural planning, water balance at watershed scale, water management, flood monitoring. The latter case is particularly critical, due to the strong effect of the combination of the soil moisture pattern and of the rainfall pattern on the intensity peak of the flood. Despite the importance of the spatial characterization of the rainfall height, this variable still presents several difficulties when an interpolation is required. Rainfall fields present spatial and temporal alternance of large zero-values areas (no-rainfall) and complex pattern of non zero heights (rainfall events). Furthermore, the spatial patterns strongly depend on the type and the origin of rain event (convective, stratiform, orographic) and on the spatial scale. Different kind of rainfall measures and estimates (rainfall gauges, satellite estimates, meteo radar) are available, as well as large amount of literature for the spatial interpolation: from Thiessen polygons to Inverse Distance Weight (IDW) to different variants of kriging, neural network and other deterministic or geostatistic methods. In this work a kernel-based method for interpolation of point measures (raingauges) is proposed, in which spatially inhomogeneous kernel are used. For each gauge a particular kernel is fitted following the particular correlation structures between the rainfall time series of the given gauge and those of its neighbors. In this way the local features of the field are considered following the observed dependence spatial pattern. The kernel are assumed to be Gaussian, whose covariance matrices are fitted basing on the values of the correlation of the time series and the location. A similar approach is

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  8. Effect on the flash-floods distribution of a rainfall stochastic model in a simple rainfall-runoff model

    NASA Astrophysics Data System (ADS)

    Campo, Lorenzo

    2015-04-01

    The rainfall-runoff models, despite their simplicity, are largely used for the short-term forecast in operational flood monitoring, especially in regions in which there is high frequency of flash floods occurrence. The main advantage of such models reside in the short computational time and in the fact that they essentially only require one input, that is the rainfall height time series (or maps series, if the model is distributed). These advantages come from the fact that almost all the slower process of the hydrological cycle (evapotranspiration, base flow, etc.) are neglected. In this study a simple rainfall-runoff lumped model, that include the dynamic of the soil saturation, is used as test-model for a statistical analysis based on a stochastic rainfall model. Given a set of rainfall time series generated basing on hourly rainfall heights observed in different raingauges, these time series were used as input of the model (configured on a small catchment) in order to study the effects of the different input probability distribution of rainfall on the final probability distribution of discharge flows. In particular, the effect of the different rainfall regimes on the extreme flows distribution was investigated for flash-floods. The rainfall stochastic model was based on the fit of the distributions of the rainfall height, of the no-rain interval length, and on the rainy interval length, based on a seasonal analysis. The analysis was performed basing on the rain time series observed in the Italian raingauges network in the period 2006-2012.

  9. Global Monsoon Rainfall - What the future holds?

    NASA Astrophysics Data System (ADS)

    Endo, H.; Kitoh, A.; Kumar, K.; Cavalcanti, I. F.; Goswami, P.; Zhou, T.

    2012-12-01

    We provide a latest view of global as well as regional monsoonal rainfall and their changes in the twenty-first century as projected by state-of-the-art climate models participated in the Coupled Model Intercomparison Project phase 5 (CMIP5). The global monsoon area (GMA) defined based on the annual range in precipitation will expand mainly over the central to eastern tropical Pacific, the southern Indian Ocean, and eastern Asia. The global monsoon intensity (GMI) and the global monsoon total precipitation (GMP) are likely to increase, implying that monsoon-related precipitation will remarkably increase in a warmer climate. Heavy precipitation indices are projected to increase much more than the mean precipitation, and their percentage changes depend more on the emission scenario compared to those for mean precipitation. Over the Asian monsoon domain, median increase rate for precipitation is larger than that over other monsoon domains, indicating that the sensitivity of Asian monsoon to global warming is stronger than that of other monsoons. For seasonal progress of monsoon rainfall, CMIP5 models project that the monsoon retreat dates will delay, while the onset dates will either advance or show no change, resulting in lengthening of the monsoon season. It is found that the increase of the global monsoon precipitation can be attributed to the increases of moisture convergence due to increased water vapor in the air column and surface evaporation, offset to a certain extent by the weakening of the monsoon circulation (Figure 1).Figure 1: Time series of anomalies during summer season (%; 20 years running mean) relative to the base period average (1986-2005) over the land global monsoon domain for (a) precipitation (mm day-1), (b) evaporation (mm day-1), (c) water vapor flux convergence in the lower (below 500hPa) troposphere (mm day-1), and (d) wind convergence in the lower troposphere (10-3 kg m-2 s-1), based on 23 CMIP5 model monthly outputs. Historical (grey

  10. Rainfall profile characteristics in erosive and not-erosive events

    NASA Astrophysics Data System (ADS)

    Todisco, Francesca

    2014-05-01

    In a storm the rainfall rate shows fluctuations with showers, low rain periods or rainless periods that follow one another at short or long time intervals. The intra-storm rainfall variations and event profile have been proved to have an important influence and exert a fundamental control in many field and research areas among which in runoff generation and soil erosion (Dunkerley, 2012; Frauenfeld and Truman, 2004; Mermut et al., 1997; Parsons and Stone 2006; Ran et al, 2012; Watung et al. 1996;). In particular the possibility to incorporate into simulated rain events pre-determined intensity variations, have recently driven more investigation on the effect of further intra-storm properties on the hydrograph and on the soil loss dynamic such as the position among the rainfall of the maximum rainfall intensity and of the rainless intervals (Dunkerley, 2008, 2012; El-Jabi and Sarraf, 1991; Parsons and Stone 2006; Ran et al, 2012). The objective of this paper is to derive the statistical expressions for the time distribution of erosive and not-erosive rainfalls and to describe the rainfall factors that influence the time distribution characteristics and that characterize an erosive event compared to a not erosive event. The analysis is based on the database of the experimental site of Masse (Central Italy): event soil loss and runoff volume from bare plot and climatic data, at 5 min time interval for the 5-years period 2008-2012 (Bagarello et al., 2011, Todisco et al., 2012). A total of 228 rainfall events were used in which the rainfall exceed 1 mm, 60 of which erosive. The soil is a Typic Haplustept (Soil Survey Staff, 2006) with a silty-clay-loam texture. The runs theory (Yevjevich, 1967) were applied to the rainfall events hyetograph to select the heavier ones named storms. The sequential periods with rainfall intensity above a threshold are defined as heavy intensity in series and called runs. All the rainfall events characterized by at least one run were

  11. A rainfall-based warning model for shallow landslides

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  12. A TRMM-Calibrated Infrared Technique for Global Rainfall Estimation

    NASA Technical Reports Server (NTRS)

    Negri, Andrew J.; Adler, Robert F.

    2002-01-01

    The development of a satellite infrared (IR) technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall on a global scale is presented. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the global tropics during 2001. The technique is calibrated separately over land and ocean, making ingenious use of the IR data from the TRMM Visible/Infrared Scanner (VIRS) before application to global geosynchronous satellite data. The low sampling rate of TRMM PR imposes limitations on calibrating IR-based techniques; however, our research shows that PR observations can be applied to improve IR-based techniques significantly by selecting adequate calibration areas and calibration length. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall will be presented. The technique is validated using available data sets and compared to other global rainfall products such as Global Precipitation Climatology Project (GPCP) IR product, calibrated with TRMM Microwave Imager (TMI) data. The calibrated CST technique has the advantages of high spatial resolution (4 km), filtering of non-raining cirrus clouds, and the stratification of the rainfall into its convective and stratiform components, the latter being important for the calculation of vertical profiles of latent heating.

  13. A TRMM-Calibrated Infrared Technique for Global Rainfall Estimation

    NASA Technical Reports Server (NTRS)

    Negri, Andrew J.; Adler, Robert F.; Xu, Li-Ming

    2003-01-01

    This paper presents the development of a satellite infrared (IR) technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall on a global scale. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the global tropics during summer 2001. The technique is calibrated separately over land and ocean, making ingenious use of the IR data from the TRMM Visible/Infrared Scanner (VIRS) before application to global geosynchronous satellite data. The low sampling rate of TRMM PR imposes limitations on calibrating IR- based techniques; however, our research shows that PR observations can be applied to improve IR-based techniques significantly by selecting adequate calibration areas and calibration length. The diurnal cycle of rainfall, as well as the division between convective and t i f m rainfall will be presented. The technique is validated using available data sets and compared to other global rainfall products such as Global Precipitation Climatology Project (GPCP) IR product, calibrated with TRMM Microwave Imager (TMI) data. The calibrated CST technique has the advantages of high spatial resolution (4 km), filtering of non-raining cirrus clouds, and the stratification of the rainfall into its convective and stratiform components, the latter being important for the calculation of vertical profiles of latent heating.

  14. Rain-fed fig yield as affected by rainfall distribution

    NASA Astrophysics Data System (ADS)

    Bagheri, Ensieh; Sepaskhah, Ali Reza

    2014-08-01

    Variable annual rainfall and its uneven distribution are the major uncontrolled inputs in rain-fed fig production and possibly the main cause of yield fluctuation in Istahban region of Fars Province, I.R. of Iran. This introduces a considerable risk in rain-fed fig production. The objective of this study was to find relationships between seasonal rainfall distribution and rain-fed fig production in Istahban region to determine the critical rainfall periods for rain-fed fig production and supplementary irrigation water application. Further, economic analysis for rain-fed fig production was considered in this region to control the risk of production. It is concluded that the monthly, seasonal and annual rainfall indices are able to show the effects of rainfall and its distribution on the rain-fed fig yield. Fig yield with frequent occurrence of 80 % is 374 kg ha-1. The internal rates of return for interest rate of 4, 8 and 12 % are 21, 58 and 146 %, respectively, that are economically feasible. It is concluded that the rainfall in spring especially in April and in December has negatively affected fig yield due to its interference with the life cycle of Blastophaga bees for pollination. Further, it is concluded that when the rainfall is limited, supplementary irrigation can be scheduled in March.

  15. Mapping an index of extreme rainfall across the UK

    NASA Astrophysics Data System (ADS)

    Faulkner, D. S.; Prudhomme, C.

    Distance from the sea, proximity of mountains, continentality and elevation are all useful covariates to assist the mapping of extreme rainfalls. Regression models linking these and other variables calculated from a digital terrain model have been built for estimating the median annual maximum rainfall, RMED. This statistic, for rainfall durations between 1 hour and 8 days, is the index variable in the rainfall frequency analysis for the new UK Flood Estimation Handbook. The interpolation of RMED between raingauge sites is most challenging in mountainous regions, which combine the greatest variation in rainfall with the sparsest network of gauges. Sophisticated variables have been developed to account for the influence of topography on extreme rainfall, the geographical orientation of the variables reflecting the prevailing direction of rain-bearing weather systems. The different processes of short and long-duration extreme rainfall are accounted for by separate regression models. The technique of georegression combines estimates from regression models with a map of correction factors interpolated between raingauge locations using the geostatistical method of kriging, to produce final maps of RMED across the UK.

  16. Network theory and spatial rainfall connections: An interpretation

    NASA Astrophysics Data System (ADS)

    Jha, Sanjeev Kumar; Zhao, Honghan; Woldemeskel, Fitsum M.; Sivakumar, Bellie

    2015-08-01

    Adequate knowledge of spatial connections in rainfall is important for reliable modeling of catchment processes and water management. This study applies the ideas of network theory to examine and interpret the spatial connections in rainfall in Australian conditions. As case studies, monthly rainfall data across a network of raingages from two vastly different areas are studied: (1) Western Australia - data over a period of 67 years (1937-2003) from 57 raingages; and (2) Sydney catchment - data over a period of 114 years (1890-2003) from 47 monitoring stations. The spatial rainfall connections in the two networks are examined using clustering coefficient (CC), a popular network connectivity measure. The clustering coefficient measures the local density and quantifies the network's tendency to cluster. Different values of rainfall correlation threshold (CT) are used to measure the strength of connections in rainfall between different stations and, hence, to calculate CC. The clustering coefficient values are interpreted in terms of topographic factors (latitude, longitude, and elevation) and rainfall properties (mean, standard deviation, and coefficient of variation).

  17. Quantifying Uncertainties in Rainfall Maps from Cellular Communication Networks

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    The core idea behind rainfall retrievals from commercial microwave link networks is to measure the decrease in power due to attenuation of the electromagnetic signal by raindrops along the link path. Accurate rainfall measurements are of vital importance in hydrological applications, for instance, flash-flood early-warning systems, agriculture, and climate modeling. Hence, such an alternative technique fulfills the need for measurements with higher resolution in time and space, especially in places where standard rain gauge-networks are scarce or poorly maintained. Rainfall estimation via commercial microwave link networks, at country-wide scales, has recently been demonstrated. Despite their potential applicability in rainfall estimation at higher spatiotemporal resolutions, the uncertainties present in link-based rainfall maps are not yet fully comprehended. Now we attempt to quantify the inherent sources of uncertainty present in interpolated maps computed from commercial microwave link rainfall retrievals. In order to disentangle these sources of uncertainty we identified four main sources of error: 1) microwave link measurements, 2) availability of microwave link measurements, 3) spatial distribution of the network, and 4) interpolation methodology. We computed more than 1000 rainfall fields, for The Netherlands, from real and simulated microwave link data. These rainfall fields were compared to quality-controlled gauge-adjusted radar rainfall maps considered as ground-truth. Thus we were able to quantify the contribution of errors in microwave link measurements to the overall uncertainty. The actual performance of the commercial microwave link network is affected by the intermittent availability of the links, not only in time but also in space. We simulated a fully-operational network in time and space, and thus we quantified the role of the availability of microwave link measurements to the overall uncertainty. This research showed that the largest source of

  18. Cascading rainfall uncertainties into 2D inundation impact models

    NASA Astrophysics Data System (ADS)

    Souvignet, Maxime; de Almeida, Gustavo; Champion, Adrian; Garcia Pintado, Javier; Neal, Jeff; Freer, Jim; Cloke, Hannah; Odoni, Nick; Coxon, Gemma; Bates, Paul; Mason, David

    2013-04-01

    Existing precipitation products show differences in their spatial and temporal distribution and several studies have presented how these differences influence the ability to predict hydrological responses. However, an atmospheric-hydrologic-hydraulic uncertainty cascade is seldom explored and how, importantly, input uncertainties propagate through this cascade is still poorly understood. Such a project requires a combination of modelling capabilities, runoff generation predictions based on those rainfall forecasts, and hydraulic flood wave propagation based on the runoff predictions. Accounting for uncertainty in each component is important in decision making for issuing flood warnings, monitoring or planning. We suggest a better understanding of uncertainties in inundation impact modelling must consider these differences in rainfall products. This will improve our understanding of the input uncertainties on our predictive capability. In this paper, we propose to address this issue by i) exploring the effects of errors in rainfall on inundation predictive capacity within an uncertainty framework, i.e. testing inundation uncertainty against different comparable meteorological conditions (i.e. using different rainfall products). Our method cascades rainfall uncertainties into a lumped hydrologic model (FUSE) within the GLUE uncertainty framework. The resultant prediction uncertainties in discharge provide uncertain boundary conditions, which are cascaded into a simplified shallow water 2D hydraulic model (LISFLOOD-FP). Rainfall data captured by three different measurement techniques - rain gauges, gridded data and numerical weather predictions (NWP) models are used to assess the combined input data and model parameter uncertainty. The study is performed in the Severn catchment over the period between June and July 2007, where a series of rainfall events causing record floods in the study area). Changes in flood area extent are compared and the uncertainty envelope is

  19. The Role of Rainfall Patterns in Seasonal Malaria Transmission

    NASA Astrophysics Data System (ADS)

    Bomblies, A.

    2010-12-01

    Seasonal total precipitation is well known to affect malaria transmission because Anopheles mosquitoes depend on standing water for breeding habitat. However, the within-season temporal pattern of the rainfall influences persistence of standing water and thus rainfall patterns also affect mosquito population dynamics. In this talk, I show that intraseasonal rainfall pattern describes 40% of the variance in simulated mosquito abundance in a Niger Sahel village where malaria is endemic but highly seasonal, demonstrating the necessity for detailed distributed hydrology modeling to explain the variance from this important effect. I apply a field validated, high spatial- and temporal-resolution hydrology model coupled with an entomology model. Using synthetic rainfall time series generated using a stationary first-order Markov Chain model, I hold all variables except hourly rainfall constant, thus isolating the contribution of rainfall pattern to variance in mosquito abundance. I further show the utility of hydrology modeling to assess precipitation effects by analyzing collected water. Time-integrated surface area of pools explains 70% of the variance in mosquito abundance, and time-integrated surface area of pools persisting longer than seven days explains 82% of the variance, showing an improved predictive ability when pool persistence is explicitly modeled at high spatio-temporal resolution. I extend this analysis to investigate the impacts of this effect on malaria vector mosquito populations under climate shift scenarios, holding all climate variables except precipitation constant. In these scenarios, rainfall mean and variance change with climatic change, and the modeling approach evaluates the impact of non-stationarity in rainfall and the associated rainfall patterns on expected mosquito activity.

  20. Assessing the impact of African wetlands on rainfall

    NASA Astrophysics Data System (ADS)

    Taylor, Christopher; Dadson, Simon; Prigent, Catherine

    2015-04-01

    Wetlands are an important component of the landscape in many low-lying tropical regions. Compared to their surroundings, wetlands provide strongly contrasting fluxes of sensible and latent heat into the atmosphere, with the potential to affect convective rainfall locally and regionally. The extents of many tropical wetlands exhibit strong seasonal and interannual variations, in response to rain which may have fallen in previous seasons, many hundreds of kilometres upstream. The timing and extent of wetland flooding is also vulnerable to upstream water management. This suggests that future rainfall patterns around wetlands may change in response to both remote rainfall, and new water infrastructure, for example in hydropower and irrigation projects. Here we use a range of observational datasets to explore the impacts of different wetlands across sub-Saharan Africa on rainfall under current climate conditions. Satellite observations include gridded 3-hourly precipitation (e.g. CMORPH), TRMM precipitation radar, and a dynamic wetland extent dataset based on multiple satellites. These remotely-sensed sources are complemented by river discharge and gauge-based rainfall data. We find that regions containing extensive wetlands typically exhibit suppressed daytime rainfall over the wetland itself, whilst new convective rain events are more likely to develop above nearby drier surfaces. This behaviour, previously documented around the Niger Inland Delta in Mali, is consistent with the development of wetland breezes which provide local convergence zones favourable for convective initiation. In some regions, where long-lived organised convective systems contribute substantially to rainfall totals, local wetland triggers can therefore influence rainfall over a much larger area. Around wetlands which exhibit strong interannual variability driven by remote upstream rainfall, the analysis provides evidence for a surface feedback

  1. A Protocol for Conducting Rainfall Simulation to Study Soil Runoff

    PubMed Central

    Kibet, Leonard C.; Saporito, Louis S.; Allen, Arthur L.; May, Eric B.; Kleinman, Peter J. A.; Hashem, Fawzy M.; Bryant, Ray B.

    2014-01-01

    Rainfall is a driving force for the transport of environmental contaminants from agricultural soils to surficial water bodies via surface runoff. The objective of this study was to characterize the effects of antecedent soil moisture content on the fate and transport of surface applied commercial urea, a common form of nitrogen (N) fertilizer, following a rainfall event that occurs within 24 hr after fertilizer application. Although urea is assumed to be readily hydrolyzed to ammonium and therefore not often available for transport, recent studies suggest that urea can be transported from agricultural soils to coastal waters where it is implicated in harmful algal blooms. A rainfall simulator was used to apply a consistent rate of uniform rainfall across packed soil boxes that had been prewetted to different soil moisture contents. By controlling rainfall and soil physical characteristics, the effects of antecedent soil moisture on urea loss were isolated. Wetter soils exhibited shorter time from rainfall initiation to runoff initiation, greater total volume of runoff, higher urea concentrations in runoff, and greater mass loadings of urea in runoff. These results also demonstrate the importance of controlling for antecedent soil moisture content in studies designed to isolate other variables, such as soil physical or chemical characteristics, slope, soil cover, management, or rainfall characteristics. Because rainfall simulators are designed to deliver raindrops of similar size and velocity as natural rainfall, studies conducted under a standardized protocol can yield valuable data that, in turn, can be used to develop models for predicting the fate and transport of pollutants in runoff. PMID:24748061

  2. How will increases in rainfall intensity affect semiarid ecosystems?

    NASA Astrophysics Data System (ADS)

    Siteur, Koen; Eppinga, Maarten B.; Karssenberg, Derek; Baudena, Mara; Bierkens, Marc F. P.; Rietkerk, Max

    2014-07-01

    Model studies suggest that semiarid ecosystems with patterned vegetation can respond in a nonlinear way to climate change. This means that gradual changes can result in a rapid transition to a desertified state. Previous model studies focused on the response of patterned semiarid ecosystems to changes in mean annual rainfall. The intensity of rain events, however, is projected to change as well in the coming decades. In this paper, we study the effect of changes in rainfall intensity on the functioning of patterned semiarid ecosystems with a spatially explicit model that captures rainwater partitioning and runoff-runon processes with simple event-based process descriptions. Analytical and numerical analyses of the model revealed that rainfall intensity is a key parameter in explaining patterning of vegetation in semiarid ecosystems as low mean rainfall intensities do not allow for vegetation patterning to occur. Surprisingly, we found that, for a constant annual rainfall rate, both an increase and a decrease in mean rainfall intensity can trigger desertification. An increase negatively affects productivity as a greater fraction of the rainwater is lost as runoff. This can result in a shift to a bare desert state only if the mean rainfall intensity exceeds the infiltration capacity of bare soil. On the other hand, a decrease in mean rainfall intensity leads to an increased fraction of rainwater infiltrating in bare soils, remaining unavailable to plants. Our findings suggest that considering rainfall intensity as a variable may help in assessing the proximity to regime shifts in patterned semiarid ecosystems and that monitoring losses of resource through runoff and bare soil infiltration could be used to determine ecosystem resilience.

  3. A protocol for conducting rainfall simulation to study soil runoff.

    PubMed

    Kibet, Leonard C; Saporito, Louis S; Allen, Arthur L; May, Eric B; Kleinman, Peter J A; Hashem, Fawzy M; Bryant, Ray B

    2014-01-01

    Rainfall is a driving force for the transport of environmental contaminants from agricultural soils to surficial water bodies via surface runoff. The objective of this study was to characterize the effects of antecedent soil moisture content on the fate and transport of surface applied commercial urea, a common form of nitrogen (N) fertilizer, following a rainfall event that occurs within 24 hr after fertilizer application. Although urea is assumed to be readily hydrolyzed to ammonium and therefore not often available for transport, recent studies suggest that urea can be transported from agricultural soils to coastal waters where it is implicated in harmful algal blooms. A rainfall simulator was used to apply a consistent rate of uniform rainfall across packed soil boxes that had been prewetted to different soil moisture contents. By controlling rainfall and soil physical characteristics, the effects of antecedent soil moisture on urea loss were isolated. Wetter soils exhibited shorter time from rainfall initiation to runoff initiation, greater total volume of runoff, higher urea concentrations in runoff, and greater mass loadings of urea in runoff. These results also demonstrate the importance of controlling for antecedent soil moisture content in studies designed to isolate other variables, such as soil physical or chemical characteristics, slope, soil cover, management, or rainfall characteristics. Because rainfall simulators are designed to deliver raindrops of similar size and velocity as natural rainfall, studies conducted under a standardized protocol can yield valuable data that, in turn, can be used to develop models for predicting the fate and transport of pollutants in runoff. PMID:24748061

  4. Calibration of rainfall-runoff models: The effect of the temporal distribution of rainfall on uncertainties in model parameter estimation

    NASA Astrophysics Data System (ADS)

    Kaleris, Vassilios; Kourakos, Vassilios; Langousis, Andreas

    2015-04-01

    The temporal distribution of rainfall, which is used as input in rainfall-runoff simulations, determines (along with the model parameters) the form of the simulated hydrographs of the total runoff. Independent of the method used for the calibration of a rainfall-runoff model, the uncertainty in estimating the model parameters depends on the smoothness of the measured hydrographs. For instance, the estimation of those parameters that determine the recession limp of a hydrograph, which is relatively smooth, is less uncertain than the estimation of the parameters determining the peaks of a hydrograph. The smoothness of a runoff hydrograph mainly depends on the temporal distribution of rainfall, which enforces the runoff in the catchment. In this study we investigate the uncertainty in model parameter estimation with respect to the temporal distribution of rainfall. To do so we use smoothed rainfall distributions to study the efficiency of adaptive methods when calibrating rainfall-runoff models. The investigations are performed using the ENNS rainfall-runoff model (Nachtnebel et al., 1993), as follows: (a) The equations used in ENNS are written in dimensionless form to reduce the number of model parameters. (b) Starting with smooth rainfall distributions over the wet period of the year (e.g. uniform, sinusoidal or other distributions) and proceeding with measured distributions smoothed to different degrees, we investigate the sensitivity of the total runoff and its particular components to different model parameters. In this way we assess the effects of the temporal distribution of rainfall on the uncertainty in model parameter estimation. (c) We produce synthetic time series of rainfall smoothed to different degrees and, then, we select a set of model parameters to simulate runoff hydrographs using ENNS. Finally, we apply the uniform random sampling procedure (see e.g. Duan et al., 1992) to identify the parameter set that best approximates the simulated runoff

  5. Rainfall Manipulation Plot Study (RaMPS)

    DOE Data Explorer

    Blair, John [Kansas State University; Fay, Phillip [USDA-ARS; Knapp, Alan [Colorado State University; Collins, Scott [University of New Mexico; Smith, Melinda [Yale University

    Rainfall Manipulation Plots facility (RaMPs) is a unique experimental infrastructure that allows us to manipulate precipitation events and temperature, and assess population community, and ecosystem responses in native grassland. This facility allows us to manipulate the amount and timing of individual precipitation events in replicated field plots at the Konza Prairie Long-Term Ecological Research (LTER) site. Questions we are addressing include: • What is the relative importance of more extreme precipitation patterns (increased climatic variability) vs. increased temperatures (increased climatic mean) with regard to their impact on grassland ecosystem structure and function? Both projected climate change factors are predicted to decrease soil water availability, but the mechanisms by which this resource depletion occurs differ. • Will altered precipitation patterns, increased temperatures and their interaction increase opportunities for invasion by exotic species? • Will long-term (6-10 yr) trajectories of community and ecosystem change in response to more extreme precipitation patterns continue at the same rate as initial responses from years 1-6? Or will non-linear change occur as potential ecological thresholds are crossed? And will increased temperatures accelerate these responses? Data sets are available as ASCII files, in Excel spreadsheets, and in SAS format. (Taken from http://www.konza.ksu.edu/ramps/backgrnd.html

  6. Fluvial signatures of modern and paleo orographic rainfall gradients

    NASA Astrophysics Data System (ADS)

    Schildgen, Taylor; Strecker, Manfred

    2016-04-01

    The morphology of river profiles is intimately linked to both climate and tectonic forcing. While much interest recently has focused on how river profiles can be inverted to derive uplift histories, here we show how in regions of strong orographic rainfall gradients, rivers may primarily record spatial patterns of precipitation. As a case study, we examine the eastern margin of the Andean plateau in NW Argentina, where the outward (eastward) growth of a broken foreland has led to a eastward shift in the main orographic rainfall gradient over the last several million years. Rivers influenced by the modern rainfall gradient are characterized by normalized river steepness values in tributary valleys that closely track spatial variations in rainfall, with higher steepness values in drier areas and lower steepness values in wetter areas. The same river steepness pattern has been predicted in landscape evolution models that apply a spatial gradient in rainfall to a region of uniform erosivity and uplift rate (e.g., Han et al., 2015). Also, chi plots from river networks on individual ranges affected by the modern orographic rainfall reveal patterns consistent with assymmetric precipitation across the range: the largest channels on the windward slopes are characterized by capture, while the longest channels on the leeward slopes are dominated by beheadings. Because basins on the windward side both lengthen and widen, tributary channels in the lengthening basins are characterized by capture, while tributary channels from neighboring basins on the windward side are dominated by beheadings. These patterns from the rivers influenced by the modern orographic rainfall gradient provide a guide for identifying river morphometric signatures of paleo orographic rainfall gradients. Mountain ranges to the west of the modern orographic rainfall have been interpreted to mark the location of orographic rainfall in the past, but these ranges are now in spatially near-uniform semi-arid to

  7. Investigation on rainfall extremes events trough a geoadditive model

    NASA Astrophysics Data System (ADS)

    Bocci, C.; Caporali, E.; Petrucci, A.; Rossi, G.

    2012-04-01

    Rainfall can be considered a very important variable, and rainfall extreme events analysis of great concern for the enormous impacts that they may have on everyday life particularly when related to intense rainfalls and floods, and hydraulic risk management. On the catchment area of Arno River in Tuscany, Central Italy, a geoadditive mixed model of rainfall extremes is developed. Most of the territory of Arno River has suffered in the past of many severe hydro-geological events, with high levels of risk due to the vulnerability of a unique artistic and cultural heritage. The area has a complex topography that greatly influences the precipitation regime. The dataset is composed by the time series of the annual maxima of daily rainfall recorded in about 400 rain gauges, spatially distributed over the catchment area of about 8.800 km2. The record period covers mainly the second half of 20th century. The rainfall observations are assumed to follow generalized extreme value distributions whose locations are spatially dependent and where the dependence is captured using a geoadditive model. In particular, since rainfall has a natural spatial domain and a significant spatial variability, a spatial hierarchical model for extremes is used. The spatial hierarchical models, in fact, take into account data from all locations, borrowing strength from neighbouring locations when they estimate parameters and are of great interest when small set of data is available, as in the case of rainfall extreme values. Together with rain gauges location variables further physiographic variables are investigated as explanation variables. The implemented geoadditive mixed model of spatially referenced time series of rainfall extreme values, is able to capture the spatial dynamics of the rainfall extreme phenomenon. Since the model shows evidence of a spatial trend in the rainfall extreme dynamic, the temporal dynamic and the time influence can be also taken into account. The implemented

  8. Stochastic modeling of hourly rainfall times series in Campania (Italy)

    NASA Astrophysics Data System (ADS)

    Giorgio, M.; Greco, R.

    2009-04-01

    Occurrence of flowslides and floods in small catchments is uneasy to predict, since it is affected by a number of variables, such as mechanical and hydraulic soil properties, slope morphology, vegetation coverage, rainfall spatial and temporal variability. Consequently, landslide risk assessment procedures and early warning systems still rely on simple empirical models based on correlation between recorded rainfall data and observed landslides and/or river discharges. Effectiveness of such systems could be improved by reliable quantitative rainfall prediction, which can allow gaining larger lead-times. Analysis of on-site recorded rainfall height time series represents the most effective approach for a reliable prediction of local temporal evolution of rainfall. Hydrological time series analysis is a widely studied field in hydrology, often carried out by means of autoregressive models, such as AR, ARMA, ARX, ARMAX (e.g. Salas [1992]). Such models gave the best results when applied to the analysis of autocorrelated hydrological time series, like river flow or level time series. Conversely, they are not able to model the behaviour of intermittent time series, like point rainfall height series usually are, especially when recorded with short sampling time intervals. More useful for this issue are the so-called DRIP (Disaggregated Rectangular Intensity Pulse) and NSRP (Neymann-Scott Rectangular Pulse) model [Heneker et al., 2001; Cowpertwait et al., 2002], usually adopted to generate synthetic point rainfall series. In this paper, the DRIP model approach is adopted, in which the sequence of rain storms and dry intervals constituting the structure of rainfall time series is modeled as an alternating renewal process. Final aim of the study is to provide a useful tool to implement an early warning system for hydrogeological risk management. Model calibration has been carried out with hourly rainfall hieght data provided by the rain gauges of Campania Region civil

  9. NOAA AVHRR and its uses for rainfall and evapotranspiration monitoring

    NASA Technical Reports Server (NTRS)

    Kerr, Yann H.; Imbernon, J.; Dedieu, G.; Hautecoeur, O.; Lagouarde, J. P.

    1989-01-01

    NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) Global Vegetation Indices (GVI) were used during the 1986 rainy season (June-September) over Senegal to monitor rainfall. The satellite data were used in conjunction with ground-based measurements so as to derive empirical relationships between rainfall and GVI. The regression obtained was then used to map the total rainfall corresponding to the growing season, yielding good results. Normalized Difference Vegetation Indices (NDVI) derived from High Resolution Picture Transmission (HRPT) data were also compared with actual evapotranspiration (ET) data and proved to be closely correlated with it with a time lapse of 20 days.

  10. Models for estimating daily rainfall erosivity in China

    NASA Astrophysics Data System (ADS)

    Xie, Yun; Yin, Shui-qing; Liu, Bao-yuan; Nearing, Mark A.; Zhao, Ying

    2016-04-01

    The rainfall erosivity factor (R) represents the multiplication of rainfall energy and maximum 30 min intensity by event (EI30) and year. This rainfall erosivity index is widely used for empirical soil loss prediction. Its calculation, however, requires high temporal resolution rainfall data that are not readily available in many parts of the world. The purpose of this study was to parameterize models suitable for estimating erosivity from daily rainfall data, which are more widely available. One-minute resolution rainfall data recorded in sixteen stations over the eastern water erosion impacted regions of China were analyzed. The R-factor ranged from 781.9 to 8258.5 MJ mm ha-1 h-1 y-1. A total of 5942 erosive events from one-minute resolution rainfall data of ten stations were used to parameterize three models, and 4949 erosive events from the other six stations were used for validation. A threshold of daily rainfall between days classified as erosive and non-erosive was suggested to be 9.7 mm based on these data. Two of the models (I and II) used power law functions that required only daily rainfall totals. Model I used different model coefficients in the cool season (Oct.-Apr.) and warm season (May-Sept.), and Model II was fitted with a sinusoidal curve of seasonal variation. Both Model I and Model II estimated the erosivity index for average annual, yearly, and half-month temporal scales reasonably well, with the symmetric mean absolute percentage error MAPEsym ranging from 10.8% to 32.1%. Model II predicted slightly better than Model I. However, the prediction efficiency for the daily erosivity index was limited, with the symmetric mean absolute percentage error being 68.0% (Model I) and 65.7% (Model II) and Nash-Sutcliffe model efficiency being 0.55 (Model I) and 0.57 (Model II). Model III, which used the combination of daily rainfall amount and daily maximum 60-min rainfall, improved predictions significantly, and produced a Nash-Sutcliffe model efficiency

  11. Probabilistic rainfall anomalies over Amazonia associated with ENSO events

    NASA Astrophysics Data System (ADS)

    sansigolo, clovis

    2014-05-01

    ENSO extreme events are associated with climatic extremes over many regions of the globe. Over Amazonia, El Niño and La Niña events are respectively associated with below and above normal rainfall anomalies in the wet season (Sept - May). Correlations and regressions are the methods commonly used for composite analyses. They assume linear interactions between SST anomalies and the expected climatic anomalies, no inter-events differences, symmetries between El Niño and La Niña climatic impacts, and normality of rainfall anomalies, assumptions not found in some regions. A simple and robust alternative method uses contingency tables to assess the influence of an independent variable (El Niño/La Niña) on the probability of a predefined climatic event (e.g. rainfall anomaly tercil). Monthly rainfall data in 30 stations distributed over the region (1950/51 - 2000/01) were used in this work. Seasonal rainfall anomalies were sorted and allocated in tercils corresponding to below, near and above normal categories. Standardized seasonal averages of Niño 3.4 indices were used to assess the phase impact of the 11 strongest El Niño and La Niña events observed in the period. The significance of the number of times that simultaneous and 1 to 3 months lagged rainfall anomalies during ENSO extreme events were in each considered tercil was calculated using 3x2 contingency tables. The significance of the results was assessed using a hypothesis test based on the hypergeometric distribution. Simultaneous and 1 to 3 months lagged below normal rainfall in the northern and central part of the region were significant associated with El Niño in the austral summer (mature phase). In their typical development (SON) phase they were significant associated with below normal rainfall in central Amazonia, simultaneously and 3 months lagged. La Niñas in their development phases (SON) were significantly associated with above normal rainfall in the beginning of the rainy season in eastern

  12. Improving PERSIANN-CCS Rainfall Estimation using Passive Microwave Rainfall Estimation

    NASA Astrophysics Data System (ADS)

    Karbalaee, N.; Hsu, K. L.; Sorooshian, S.

    2014-12-01

    This presentation discusses the recent improvements to the PERSIANN-CCS (Precipitation Estimation from remotely Sensed Information using Artificial Neural Networks-Cloud Classification System). The PERSIANN-CCS is one of the algorithms being integrated in the IMERG (Integrated Multi-Satellite Retrievals for the Global Precipitation Mission GPM) to estimate precipitation at 0.04o lat-long scale at every 30-minute interval. While PERSIANN-CCS has a relatively fine temporal and spatial resolution for generating rainfall estimation over the globe, it sometimes underestimates or overestimates over some regions, depending on certain conditions. In this study, improving the PERSIANN-CCS precipitation estimation using long-term passive microwave (PMW) rainfall estimation is explored. The adjustment is proceeded by matching the probability distribution of PERSIANN-CCS estimates to the PMW rainfall estimation. Four years of concurrent samples from 2008 to 2011 were used in the calibration while one year (2012) of the data was used for the validation of the PMW-adjusted PERSIANN-CCS estimates. Samples over a 5 o x5 o lat-long coverage were collected and an adjustment look up table for each month covering 60oS-60oN was generated. The validation of PERSIANN-CCS estimation before and after PMW adjustment over CONUS using radar data was investigated. The results show that the adjustment has different impact on the PERSIANN-CCS rain estimates depending on the location and time of the year. PERSIANN-CCS adjustments were found to be more significant over high latitude and winter time periods and less significant over the low latitude and summer time period.

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

    NASA Astrophysics Data System (ADS)

    Fraedrich, K.

    2014-12-01

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

  14. New Approaches to Rainfall and Flood Frequency Analysis Using High Resolution Radar Rainfall Fields and Stochastic Storm Transposition

    NASA Astrophysics Data System (ADS)

    Wright, D. B.; Smith, J. A.; Villarini, G.; Baeck, M. L.

    2012-12-01

    Conventional techniques for rainfall and flood frequency analysis in small watersheds involve a variety of assumptions regarding the spatial and temporal structure of extreme rainfall systems as well as how resulting runoff moves through the drainage network. These techniques were developed at a time when observational and computational resources were limited. They continue to be used in practice though their validity has not been fully examined. New observational and computational resources such as high-resolution radar rainfall estimates and distributed hydrologic models allow us to examine these assumptions and to develop alternative methods for estimating flood risk. We have developed a high-resolution (1 square km, 15-minute resolution) radar rainfall dataset for the 2001-2010 period using the Hydro-NEXRAD processing system, which has been bias corrected using a dense network of 71 rain gages in the Charlotte metropolitan area. The accuracy of the bias-corrected radar rainfall estimates compare favorably with rain gage measurements. The radar rainfall dataset is used in a stochastic storm transposition framework to estimate the frequency of extreme rainfall for urban watersheds ranging the point/radar pixel scale up to 240 square km, and can be combined with the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model to estimate flood frequency analysis. The results of these frequency analyses can be compared against the results of conventional methods such as the NOAA Atlas 14 precipitation frequency estimates and peak discharge estimates prepared by FEMA and the North Carolina state government.

  15. Examination on accuracy of the radar rainfall estimated by using Korean dual-pol radar rainfall estimation algorithm

    NASA Astrophysics Data System (ADS)

    Yoon, Jungsoo; Choi, Dayoung; Suk, Mi-Kyung; Nam, Kyung-Yeub; Lee, Sangmi; Ko, Jeong-Seok

    2016-04-01

    Weather Radar Center (WRC) in Korea Meteorological Administration (KMA) have tried to improve the accuracy of the radar rainfall. WRC introduced Radar-AWS Rainrate (RAR) algorithm in 2001 to quantitatively improve the accuracy of the radar rainfall. Whereafter, RAR algorithm have been advanced and still used to estimate the radar rainfall. WRC has developed Korean dual-pol radar rainfall estimation algorithm from 2014 when the project of constructing the dual-pol radar network was initiated. WRC therefore suggested first Korean dual-pol radar rainfall estimation equations (R(Z), R(Z, ZDR), R(ZDR, KDP), and R(KDP)) in 2014 and developed the equations in 2015. Since WRC just suggested each equation, it needs to algorithmize the equations. This study suggested Korean dual-pol radar rainfall estimation algorithm and examined on the accuracy of the radar rainfall estimated by the algorithm. The radar measurements obtained by dual-pol radars (BRI, BSL, and SBS) which were introduced in 2015 were used.

  16. Impact of rainfall spatial distribution on rainfall-runoff modelling efficiency and initial soil moisture conditions estimation

    NASA Astrophysics Data System (ADS)

    Tramblay, Y.; Bouvier, C.; Ayral, P.-A.; Marchandise, A.

    2011-01-01

    A good knowledge of rainfall is essential for hydrological operational purposes such as flood forecasting. The objective of this paper was to analyze, on a relatively large sample of flood events, how rainfall-runoff modeling using an event-based model can be sensitive to the use of spatial rainfall compared to mean areal rainfall over the watershed. This comparison was based not only on the model's efficiency in reproducing the flood events but also through the estimation of the initial conditions by the model, using different rainfall inputs. The initial conditions of soil moisture are indeed a key factor for flood modeling in the Mediterranean region. In order to provide a soil moisture index that could be related to the initial condition of the model, the soil moisture output of the Safran-Isba-Modcou (SIM) model developed by Météo-France was used. This study was done in the Gardon catchment (545 km2) in South France, using uniform or spatial rainfall data derived from rain gauge and radar for 16 flood events. The event-based model considered combines the SCS runoff production model and the Lag and Route routing model. Results show that spatial rainfall increases the efficiency of the model. The advantage of using spatial rainfall is marked for some of the largest flood events. In addition, the relationship between the model's initial condition and the external predictor of soil moisture provided by the SIM model is better when using spatial rainfall, in particular when using spatial radar data with R2 values increasing from 0.61 to 0.72.

  17. What aspects of future rainfall changes matter for crop yields in West Africa?

    NASA Astrophysics Data System (ADS)

    Guan, Kaiyu; Sultan, Benjamin; Biasutti, Michela; Baron, Christian; Lobell, David B.

    2015-10-01

    How rainfall arrives, in terms of its frequency, intensity, the timing and duration of rainy season, may have a large influence on rainfed agriculture. However, a thorough assessment of these effects is largely missing. This study combines a new synthetic rainfall model and two independently validated crop models (APSIM and SARRA-H) to assess sorghum yield response to possible shifts in seasonal rainfall characteristics in West Africa. We find that shifts in total rainfall amount primarily drive the rainfall-related crop yield change, with less relevance to intraseasonal rainfall features. However, dry regions (total annual rainfall below 500 mm/yr) have a high sensitivity to rainfall frequency and intensity, and more intense rainfall events have greater benefits for crop yield than more frequent rainfall. Delayed monsoon onset may negatively impact yields. Our study implies that future changes in seasonal rainfall characteristics should be considered in designing specific crop adaptations in West Africa.

  18. NASA's IMERG Shows Darby's Rainfall Over The Hawaiian Islands

    NASA Video Gallery

    Estimates of rainfall accompanying Tropical Storm Darby were produced using NASA's Integrated Multi-satellitE Retrievals for GPM (IMERG) data. GPM is the Global Precipitation Measurement mission co...

  19. GPM Video of the Rainfall Totals from Joaquin

    NASA Video Gallery

    NASA/JAXA's GPM satellite measured record rainfall that fell over the Carolinas from September 26 to October 5 from a plume of moisture from Hurricane Joaquin when it was located over the Bahamas a...

  20. The Impact of Amazonian Deforestation on Dry-Season Rainfall

    NASA Technical Reports Server (NTRS)

    Negri, Andrew J.; Adler, Robert F.; Xu, Li-Ming; Surratt, Jason; Starr, David OC. (Technical Monitor)

    2002-01-01

    Many modeling studies have concluded that widespread deforestation of Amazonia would lead to decreased rainfall. We analyze geosynchronous infrared satellite data with respect percent cloudiness, and analyze rain estimates from microwave sensors aboard the Tropical Rainfall Measuring Mission satellite. We conclude that in the dry-season, when the effects of the surface are not overwhelmed by synoptic-scale weather disturbances, deep convective cloudiness, as well as rainfall occurrence, all increase over the deforested and non-forested (savanna) regions. This is in response to a local circulation initiated by the differential heating of the region's varying forestation. Analysis of the diurnal cycle of cloudiness reveals a shift toward afternoon hours in the deforested and savanna regions, compared to the forested regions. Analysis of 14 years of data from the Special Sensor Microwave/Imager data revealed that only in August did rainfall amounts increase over the deforested region.

  1. Estimates of daily rainfall over the Amazon basin

    SciTech Connect

    Martin, D.W.; Goodman, B.; Schmit, T.J. ); Cutrim, E.C. )

    1990-09-20

    Five geostationary satellite rain estimation techniques were tested over Amazonia. Individually, the techniques explained 1/4 to 1/3 of the variance of daily gage rainfall. Based in large part on cost, one technique, which involves a nonlinear relation in temperature, was selected to provide a mapping of daily Amazonia rainfall between May 6 and 12, 1987. Accumulated over the 7 days, rainfall by this technique averaged 40 mm. It varied from zero in the southeast to more than 150 mm in the northwest. To the southwest the predominantly convective pattern of the rain image was overlaid by a streakiness, implying some baroclinic influence. In maps combining gage observations with satellite estimates, rainfall varied significantly from day to day. Only over the largest scale did a trend emerge: a tendency for rain to withdraw from south to north.

  2. An Apparent Paradox in Verification of Rainfall Estimates.

    NASA Astrophysics Data System (ADS)

    Ciach, G. J.

    2009-05-01

    A problem that is a source of permanent cognitive confusion in comprehensive evaluations of different rainfall estimates is presented. The problem stems from the existence of two conditional biases (CB) inherent to the uncertainties of the estimates. The two CBs, called "CB type 1" and "CB type 2," are recognized by researchers familiar with the distribution-oriented framework for complete verification of hydrological and meteorological products. Although the mathematical definitions of the two CBs are clear, a reality check reveals that their meaningful interpretation is problematic. It can even result in self-contradictory conclusions suggesting both systematic overestimation and underestimation of strong rainfall by the same rainfall estimation products. A solution to this apparent paradox is discussed. This investigation is based on large data samples of different radar rainfall estimates and the corresponding highly accurate ground reference. Understanding the two CBs, their physical consequences and the fundamental inter-relations between them is essential for informed usage of these uncertainty characteristics.

  3. Trends in Rainfall, Streamflow, and Interannual Variability in Palau

    NASA Astrophysics Data System (ADS)

    Gupta, A.

    2008-05-01

    Anecdotal evidence from Palau suggests that streamflow may be declining with time. This research examines trends in rainfall and streamflow and attempts to identify causes of variability. Rainfall for the period of 1953-2002 exhibited a significant declining trend. Rainfall intensity appears to be increasing and interannual variability also shows an increasing trend. Streamflow also exhibited significant decreasing trends for the period of the early 1970s to early 1990s. Precipitation in Palau is only moderately correlated with the PDO, ENSO, and SO indices. Declining rainfall and streamflow conditions have important policy implications for the developing island nation, which is currently exhibiting rapid population growth. A lack of strong correlation with regional climate indices is also problematic when making flood and drought predictions.

  4. Parameter Estimation for a Model of Space-Time Rainfall

    NASA Astrophysics Data System (ADS)

    Smith, James A.; Karr, Alan F.

    1985-08-01

    In this paper, parameter estimation procedures, based on data from a network of rainfall gages, are developed for a class of space-time rainfall models. The models, which are designed to represent the spatial distribution of daily rainfall, have three components, one that governs the temporal occurrence of storms, a second that distributes rain cells spatially for a given storm, and a third that determines the rainfall pattern within a rain cell. Maximum likelihood and method of moments procedures are developed. We illustrate that limitations on model structure are imposed by restricting data sources to rain gage networks. The estimation procedures are applied to a 240-mi2 (621 km2) catchment in the Potomac River basin.

  5. Rainfall interception by an evergreen beech forest, Nelson, New Zealand

    NASA Astrophysics Data System (ADS)

    Rowe, L. K.

    1983-10-01

    Throughfall under a beech ( Nothofagus) forest canopy at Donald Creek, Nelson, averaged 69% of the rain falling on the canopy, i.e. 1060 mm of 1530 mm in a year of normal rainfall. Using an estimate for stemflow at 2% of gross rainfall, interception loss averaged 29% of the annual rainfall, or 440 mm yr. -1. Seasonal differences in interception loss were significant, ranging from 22% in winter to 35% in summer, and resulted from seasonal variation in evaporation rates from a wet canopy. Seasonal variation in rainfall rate was slight. Four models, storm linear regression, monthly linear regression, sine curve and Gash's analytical model, were tested by comparison of predicted and observed interception. All gave very satisfactory estimates (< 10% error) and tended to slightly underestimate the measured interception loss.

  6. RAINFALL SIMULATOR FOR LABORATORY USE IN ACIDIC PRECIPITATION STUDIES

    EPA Science Inventory

    A rainfall simulator, developed on the principle of droplet formation from needle tips, is described. The simulator is designed for laboratory experimentation to examine the effects of acidic precipitation on terrestrial plants. The system offers sufficient flexibility to simulat...

  7. NASA Adds Up Rainfall from 2 Historic Yemen Tropical Cyclones

    NASA Video Gallery

    Chapala's rainfall were generally 5 to 6 inches or less. Socotra, which was estimated to have received between 12 and 20 inches of rain from Chapala, appears to have received mostly 3 inches (shown...

  8. GOES-West Shows U.S. West's Record Rainfall

    NASA Video Gallery

    A new time-lapse animation of data from NOAA's GOES-West satellite provides a good picture of why the U.S. West Coast continues to experience record rainfall. The new animation shows the movement o...

  9. NASA's TRMM Satellite Sees Heavy Rainfall in Hurricane Odile

    NASA Video Gallery

    NASA's TRMM Satellite measured rainfall in Odile on Sept. 15. Odile contained intense thunderstorms around the eye above 12.5 km (about 7.8 miles) high dropping rain at a rate of over 188.4 mm (abo...

  10. Rainfall Accumulation over the United States for December 2015

    NASA Video Gallery

    This animation shows the accumulation of rainfall over the United States during December 2015, from the IMERG precipitation dataset. The black outline indicates the Mississippi-Missouri River basin...

  11. Tree-ring reconstructed dry season rainfall in Guatemala

    NASA Astrophysics Data System (ADS)

    Anchukaitis, Kevin J.; Taylor, Matthew J.; Leland, Caroline; Pons, Diego; Martin-Fernandez, Javier; Castellanos, Edwin

    2015-09-01

    Drought in Guatemala has negative consequences for agriculture and potable water supplies, particularly in regions of the country with highly seasonal rainfall. General circulation models suggest that a decrease in both winter and summer rainfall over Central America is likely and imminent as a consequence of anthropogenic influences on the climate system. However, precipitation observations over the last several decades are equivocal. Here, we use an Abies guatemalensis tree-ring chronology from the Sierra de los Cuchumatanes to estimate January through March rainfall since the late seventeenth century. Our reconstruction shows that recent winter-spring rainfall from the region is not yet exceptional in the context of the last several centuries, has a significant yet variable decadal component, is associated with large-scale modes of ocean-atmosphere variability, and reveals evidence of past multiyear droughts.

  12. The structure and rainfall features of Tropical Cyclone Rammasun (2002)

    NASA Astrophysics Data System (ADS)

    Ma, Leiming; Duan, Yihong; Zhu, Yongti

    2004-12-01

    Tropical Rainfall Measuring Mission (TRMM) data [TRMM Microwave Imager/Precipitation Radar/Visible and Infrared Scanner (TMI/PR/VIRS)] and a numerical model are used to investigate the structure and rainfall features of Tropical Cyclone (TC) Rammasun (2002). Based on the analysis of TRMM data, which are diagnosed together with NCEP/AVN [Aviation (global model)] analysis data, some typical features of TC structure and rainfall are preliminary discovered. Since the limitations of TRMM data are considered for their time resolution and coverage, the world observed by TRMM at several moments cannot be taken as the representation of the whole period of the TC lifecycle, therefore the picture should be reproduced by a numerical model of high quality. To better understand the structure and rainfall features of TC Rammasun, a numerical simulation is carried out with mesoscale model MM5 in which the validations have been made with the data of TRMM and NCEP/AVN analysis.

  13. Validation of satellite rainfall products over Greece

    NASA Astrophysics Data System (ADS)

    Feidas, H.

    2010-01-01

    Six widely available satellite precipitation products were extensively validated and intercompared on monthly-to-seasonal timescales and various spatial scales, for the period 1998-2006, using a dense station network over Greece. Satellite products were divided into three groups according to their spatial resolution. The first group had high spatial (0.5°) resolution and consists only of Tropical Rainfall Measuring Mission (TRMM) products: the TRMM Microwave Imager (TMI) precipitation product (3A12) and the TRMM multisatellite precipitation analysis products (3B42 and 3B43). The second group comprised products with medium spatial (1°) resolution. These products included the TRMM 3B42 and 3B43 estimates (remapped to 1° resolution) and the Global Precipitation Climatology Project one-degree daily (GPCP-1DD) analysis. The third group consisted of low spatial (2.5°) resolution products and included the 3B43 product (remapped to 2.5° resolution), the GPCP Satellite and Gauge (GPCP-SG) product, and the National Oceanographic and Atmospheric Administration Climate Prediction Center (NOAA-CPC) Merged Analysis (CMAP). Rain gauge data were first gridded and then compared with monthly and seasonal precipitation totals as well as with long-term averages of the six satellite products at different spatial resolutions (2.5°, 1°, and 0.5°). The results demonstrated the excellent performance of the 3B43 product over Greece in all three spatial scales. 3B42 from the first and second group and CMAP from the third exhibited a reasonable skill.

  14. Linear Prediction of Indian Monsoon Rainfall(.

    NASA Astrophysics Data System (ADS)

    Delsole, Timothy; Shukla, J.

    2002-12-01

    This paper proposes a strategy for selecting the best linear prediction model for Indian monsoon rainfall. In this strategy, a cross-validation procedure first screens out all models that perform poorly on independent data, then the error variance of every remaining model is compared to that of every other model to test whether the difference in error variances is statistically significant. This strategy is shown to produce better forecasts on average than selecting either the model that utilizes all predictors, the model that explains the most variance in the independent data, or the model with the most favorable statistic suggested by Mallow. All of the model selection criteria suggest that regression models based on two to three predictors produce better forecasts on average than regression models using a larger number of predictors. For the period up to 1967, the forecast strategy selected the prior climatology as the best predictor. For the period 1967 to the present, the strategy performed better than forecasts based on the prior climatology and all other methodologies investigated. Indexes of Pacific Ocean temperature in the Tropics (called Niño-3) and indexes of pressure fluctuations in the Northern Atlantic (called NAO), at 1-6 lead months, failed to provide prediction models that performed better on average than a prediction based on the antecedent climatology. Forecasts based on the prior 25-yr climatology had especially high skill during the recent period 1989-2000, a fact that appears to be a mere coincidence, but which may be relevant to interpreting the skill of the power regression model currently used by the India Meteorological Department.

  15. Validation of the FEWS NET Satellite Estimated Rainfall Enhancement Process

    NASA Astrophysics Data System (ADS)

    Pedreros, D.; Funk, C.; Michaelsen, J.; Peterson, P.; Verdin, A.; Magadzire, T.; Husak, G. J.; Rowland, J.; Verdin, J. P.; Aguilar, L.; Rodriguez, M.

    2011-12-01

    The Famine Early Warning Systems Network (FEWS NET) relies on satellite rainfall estimates to monitor agricultural food production in many parts of the world. Accurate satellite-derived rainfall estimates are essential for providing reliable information about water resources. In Central and South America 5- and 10-day rainfall accumulations from the Tropical Rainfall Measurement Mission (TRMM) estimates produced by NASA, at 0.25 degree spatial resolution, are used to evaluate available precipitation for rainfed agriculture. The TRMM rainfall estimate combines a variety of satellite measurements from both the TRMM satellite and other low earth orbit platforms. A preliminary comparison of TRMM and independent stations reveals large differences between the two. The relatively coarse spatial resolution of the TRMM estimates is especially a concern with the narrow land mass of some Central American countries and in the topographically dynamic areas of South America. In response to both the low correlation and coarse resolution of the TRMM estimates, FEWS NET sought to enhance satellite estimated rainfall by complementing it with higher spatial resolution climatologic fields. In addition to the TRMM data, the enhancement process includes 1) estimated rainfall from infrared (IR) temperature data from NOAA, at 4-km pixel resolution, and 2) average rainfall fields derived from best-available station means combined with parameter such as elevation, latitude, and distance to the ocean, among others. This process starts by multiplying the TRMM and IR anomalies (percent of normal) with the climatological mean. The output from this first step is the FEWS NET TRMM IR precipitation (FTIP) estimates - pentadal (5-day) rainfall fields at 0.05 degree resolution. A second step, called the Improved Rainfall Estimate (IRE), merges independent station observations with the FTIP estimate using a modified Inverse Distance Weighting technique. This study reports on the validation of the

  16. A map-based South Pacific rainfall climatology

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  17. Cascading rainfall uncertainty into flood inundation impact models

    NASA Astrophysics Data System (ADS)

    Souvignet, Maxime; Freer, Jim E.; de Almeida, Gustavo A. M.; Coxon, Gemma; Neal, Jeffrey C.; Champion, Adrian J.; Cloke, Hannah L.; Bates, Paul D.

    2014-05-01

    Observed and numerical weather prediction (NWP) simulated precipitation products typically show differences in their spatial and temporal distribution. These differences can considerably influence the ability to predict hydrological responses. For flood inundation impact studies, as in forecast situations, an atmospheric-hydrologic-hydraulic model chain is needed to quantify the extent of flood risk. Uncertainties cascaded through the model chain are seldom explored, and more importantly, how potential input uncertainties propagate through this cascade, and how best to approach this, is still poorly understood. This requires a combination of modelling capabilities, the non-linear transformation of rainfall to river flow using rainfall-runoff models, and finally the hydraulic flood wave propagation based on the runoff predictions. Improving the characterisation of uncertainty, and what is important to include, in each component is important for quantifying impacts and understanding flood risk for different return periods. In this paper, we propose to address this issue by i) exploring the effects of errors in rainfall on inundation predictive capacity within an uncertainty framework by testing inundation uncertainty against different comparable meteorological conditions (i.e. using different rainfall products) and ii) testing different techniques to cascade uncertainties (e.g. bootstrapping, PPU envelope) within the GLUE (generalised likelihood uncertainty estimation) framework. Our method cascades rainfall uncertainties into multiple rainfall-runoff model structures using the Framework for Understanding Structural Errors (FUSE). The resultant prediction uncertainties in upstream discharge provide uncertain boundary conditions that are cascaded into a simplified shallow water hydraulic model (LISFLOOD-FP). Rainfall data captured by three different measurement techniques - rain gauges, gridded radar data and numerical weather predictions (NWP) models are evaluated

  18. Meaningful QQ adjustment of TRMM/GPM daily rainfall estimates.

    NASA Astrophysics Data System (ADS)

    Pegram, Geoff; Bardossy, Andras; Sinclair, Scott

    2016-04-01

    In many parts of the world, particularly in Africa, the daily raingauge networks are sparse. It is therefore sensible to use remote sensing estimates of precipitation to fill the gaps, but readily available products like TRMM and it successor GPM are frequently found to be biased. This presentation describes a method of bias adjustment of TRMM using quantile-quantile (QQ) transforms of the probability distributions of TRMM daily rainfall accumulations over its grid of 0.25 degree pixels/blocks. There are 4 main steps in the procedure. The first is to collect the daily gauge readings in those TRMM pixels containing gauges to obtain useful estimates of spatial rainfall for ground referencing. These estimates need to be adjusted from gauge to areal estimates taking the number of gauges in each pixel into account. We found that the distributions of the areal rainfall estimates are influenced by the number of gauges in each block, so we devised a means of transforming point to areal rainfall meaningfully. The second step is to determine the parameters of the probability distributions of the gauge-based block areal rainfall; we found that the Weibull distribution with 2 parameters is a suitable and useful choice. The pairs of Weibull parameters of rainfall on many blocks are correlated. To enable their interpolation, as an intermediate step, they have to be decorrelated using canonical decomposition. These transformed parameter pairs are then separately interpolated to empty blocks over the region of choice. They are then back-transformed at each TRMM pixel to Weibull parameters to provide gauge referenced daily rainfall distributions. The third step is to determine the Weibull distributions of the TRMM daily rainfall estimates in each block, based on their brief 11-year history. The fourth and last step is to QQ transform the individual daily TRMM rainfall estimates via the interpolated gauge-block rainfall distributions. This procedure achieves the desired corrected

  19. Thunderstorm cloud height-rainfall rate relations for use with satellite rainfall estimation techniques

    NASA Technical Reports Server (NTRS)

    Adler, R. F.; Mack, R. A.

    1984-01-01

    Observational studies of thunderstorm cloud height-rainfall rate and cloud height-volume rainfall rate relations are reviewed with significant variations being noted among climatological regimes. Analysis of the Florida (summer) and Oklahoma (spring) relations are made using a one-dimensional cloud model to ascertain the important factors in determining the individual cloud-rain relations and the differences between the two regimes. In general, the observed relations are well simulated by the model-based calculations. The generally lower predicted rain rates in Oklahoma (as compared to Florida) result from lower precipitation efficiencies which are due to a combination of larger entrainment (related to larger vertical wind shear) and drier environment. The generally steeper slope of the Oklahoma rain rate height curves is shown to be due to a stronger variation in maximum vertical velocity with cloud top height, which, in turn, is related to the greater static stability in the range of cloud tops. The impact of the regime-to-regime variations on empirical rain estimation schemes based on satellite-observed cloud height or cloud temperature information is discussed and a rain estimation approach based on model-generated cloud-rain relations is outlined.

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

    NASA Astrophysics Data System (ADS)

    Onyutha, C.; Willems, P.

    2015-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Onyutha, C.; Willems, P.

    2014-10-01

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

  2. Processes influencing rainfall deposition of mercury in Florida.

    PubMed

    Guentzel, J L; Landing, W M; Gill, G A; Pollman, C D

    2001-03-01

    The primary goal of the Florida Atmospheric Mercury Study (FAMS) was to quantify the atmospheric deposition of Hg throughout Florida. Monthly integrated precipitation and weekly integrated particulate samples were collected at 10 sites in Florida for periods ranging from 2 to 5 yr. The monthly rainfall across the state and the concentrations of Hg in wet-only and bulk deposition increased by a factor of 2-3 during the summertime "wet season" (May-October). These parallel increases in rainfall amount and Hg concentration resulted in 5-8-fold increases in rainfall Hg deposition during the wet season. The annual volume-weighted Hg concentrations ranged from 14 +/- 2 to 16 +/- 2 ng/L across southern Florida, and the annual rainfall Hg fluxes ranged from 20 +/- 3 to 23 +/- 3 micrograms m-2 yr-1. The weekly integrated particulate Hg concentrations in southern Florida were low (4.9-9.3 pg/m3) and did not exhibit strong seasonal variability. Considering the pronounced seasonal pattern in rainfall Hg deposition, the relatively uniform summertime rainfall Hg concentrations, and the low concentrations of particulate Hg, we conclude that processes other than particulate Hg transport and scavenging govern rainfall Hg deposition in southern Florida. We hypothesize that long-range transport of reactive gaseous Hg (RGM) species coupled with strong convective thunderstorm activity during the summertime represents > 50% of the Hg deposition in southern Florida. Model calculations indicate that local anthropogenic particulate Hg and RGM emissions account for 30-46% of the summertime rainfall Hg deposition across the southern Florida peninsula. PMID:11351528

  3. Variability and teleconnectivity of northeast monsoon rainfall over India

    NASA Astrophysics Data System (ADS)

    Nayagam, Lorna R.; Janardanan, Rajesh; Ram Mohan, H. S.

    2009-12-01

    The spatial and temporal variabilities of rainfall over Peninsular India during the northeast monsoon (NEM) season is studied using a high resolution gridded data, for the period 1951-2003. The dominant modes of the NEM rainfall were identified using Empirical Orthogonal Function (EOF) analysis and the power over the identified scales was extracted using wavelet analysis (scale averaged wavelet power-SAP). Homogenous regions of variability of the SAP of NEM rainfall (smoothed NEM) were studied using EOF. Excluding the subdivisions of Karnataka, the leading mode of EOF explains the spatio-temporal variability of NEM rainfall over Peninsular India. Dominant frequency of smoothed NEM is in the 4 year period and the second dominant mode is in the 8 year period. The energy of the principal components (PCs) is consistent with the above/below-normal rainfall received over the NEM region. Even though PC1 explains the variability over the core region of NEM rainfall, the energy of the WET year 1956 is not captured by PC1. The excess rainfall of this year was contributed by the subdivisions of Karnataka, whose variability is explained by PC2. EOF analysis was also applied on the SAP of SST (smoothed SST) for the months from January to September, over the Indian Ocean (30° S-30° N, 40° E-110° E), the Atlantic Ocean (30° S-30° N, 60° W-10° E) and the Pacific Ocean (30° S-30° N, 120° E-60° W). Correlation between PC1 of smoothed SST for the months of January to September and smoothed NEM averaged over Peninsular India was found and the month that bears high correlation was selected to explain the teleconnections. Thus the smoothed SST for the months of February, March and August over Indian, Atlantic and Pacific Oceans respectively was selected to explain their relations with the smoothed NEM rainfall.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  5. Trends and variability in East African rainfall and temperature observations

    NASA Astrophysics Data System (ADS)

    Seregina, Larisa; Ermert, Volker; Fink, Andreas H.; Pinto, Joaquim G.

    2014-05-01

    The economy of East Africa is highly dependent on agriculture, leading to a strong vulnerability of local society to fluctuations in seasonal rainfall amounts, including extreme events. Hence, the knowledge about the evolution of seasonal rainfall under future climate conditions is crucial. Rainfall regimes over East Africa are influenced by multiple factors, including two monsoon systems, several convergence zones and the Rift Valley lakes. In addition, local conditions, like topography, modulate the large-scale rainfall pattern. East African rainfall variability is also influenced by various teleconnections like the Indian Ocean Zonal Mode and El Niño Southern Oscillation. Regarding future climate projections, regional and global climate models partly disagree on the increase or decrease of East African rainfall. The specific aim of the present study is the acquirement of historic data from weather stations in East Africa (Kenya, Tanzania, Ruanda and Uganda), the use of gridded satellite (rainfall) products (ARC2 and TRMM), and three-dimensional atmospheric reanalysis (e.g., ERA-Interim) to quantify climate variability in the recent past and to understand its causes. Climate variability and trends, including changes in extreme events, are evaluated using ETCCDI climate change and standardized precipitation indices. These climate indices are determined in order to investigate the variability of temperature and rainfall and their trends with the focus on most recent decades. In the follow-up, statistical and dynamical analyses are conducted to quantify the local impact of pertinent large-scale modes of climate variability (Indian Ocean Zonal Mode, El Niño Southern Oscillation, Sea Surface Temperature of the Indian Ocean).

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

    NASA Astrophysics Data System (ADS)

    Biasutti, Michela; Seager, Richard; Kirschbaum, Dalia

    2016-04-01

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

  7. Possible rainfall reduction through reduced surface temperatures due to overgrazing

    NASA Technical Reports Server (NTRS)

    Otterman, J.

    1975-01-01

    Surface temperature reduction in terrain denuded of vegetation (as by overgrazing) is postulated to decrease air convection, reducing cloudiness and rainfall probability during weak meteorological disturbances. By reducing land-sea daytime temperature differences, the surface temperature reduction decreases daytime circulation of thermally driven local winds. The described desertification mechanism, even when limited to arid regions, high albedo soils, and weak meteorological disturbances, can be an effective rainfall reducing process in many areas including most of the Mediterranean lands.

  8. Validation and Intercomparison of Satellite Rainfall Products over Guiana Shield

    NASA Astrophysics Data System (ADS)

    Ringard, J.; Becker, M.; Audois, P.; Seyler, F.; Linguet, L.

    2014-12-01

    Four satellite-based rainfall estimate algorithms TRMM-TMPA 3B42 (Tropical Rainfall Measuring Mission Multi Satellite Precipitation analysis) V7 (Version 7) and RT (Real Time), PERSIANN (Precipitation Estimation from Remote Sensing Information using Artificial Neural Network) and CMORPH (Climate Prediction Center MORPHing technique) are evaluated at daily and monthly time scales, and a spatial resolution of 0.25° longitude/latitude. The reference data come from to rain gauges network over French Guiana and North Brazil. The comparison between the products is obtained with quantitative and qualitative statistical analysis. Results are discussed in terms of the accuracy of the products, the effect of climate variability, and differences between products. The validation and intercomparison of these products is done for the whole as well as different parts of the area. Validation results are reasonably satisfactory for daily and monthly rainfall with a correct match in spatial distribution in rainfall between regions. There is a better correlation for monthly precipitation. On average the bias vary from -0.55 mm to -2.05 mm for daily and from -16.44 mm to -62.04 mm for monthly, the root mean square error vary from 15.15 mm to 16.06 mm for daily and from 159.62 mm to 172.65 mm for monthly. All products underestimate the strong rainfall regimes and overestimate low rainfall regimes. Structures in the occurrence of rainfall are better represented than structures in rainfall amounts. TRMM-V7 and PERSIANN show better performance, CMORPH and TRMM-RT lower, although the differences between products are very low.

  9. The collaborative historical African rainfall model: description and evaluation

    USGS Publications Warehouse

    Funk, Christopher C.; Michaelsen, Joel C.; Verdin, James P.; Artan, Guleid A.; Husak, Gregory; Senay, Gabriel B.; Gadain, Hussein; Magadazire, Tamuka

    2003-01-01

    In Africa the variability of rainfall in space and time is high, and the general availability of historical gauge data is low. This makes many food security and hydrologic preparedness activities difficult. In order to help overcome this limitation, we have created the Collaborative Historical African Rainfall Model (CHARM). CHARM combines three sources of information: climatologically aided interpolated (CAI) rainfall grids (monthly/0.5° ), National Centers for Environmental Prediction reanalysis precipitation fields (daily/1.875° ) and orographic enhancement estimates (daily/0.1° ). The first set of weights scales the daily reanalysis precipitation fields to match the gridded CAI monthly rainfall time series. This produces data with a daily/0.5° resolution. A diagnostic model of orographic precipitation, VDELB—based on the dot-product of the surface wind V and terrain gradient (DEL) and atmospheric buoyancy B—is then used to estimate the precipitation enhancement produced by complex terrain. Although the data are produced on 0.1° grids to facilitate integration with satellite-based rainfall estimates, the ‘true’ resolution of the data will be less than this value, and varies with station density, topography, and precipitation dynamics. The CHARM is best suited, therefore, to applications that integrate rainfall or rainfall-driven model results over large regions. The CHARM time series is compared with three independent datasets: dekadal satellite-based rainfall estimates across the continent, dekadal interpolated gauge data in Mali, and daily interpolated gauge data in western Kenya. These comparisons suggest reasonable accuracies (standard errors of about half a standard deviation) when data are aggregated to regional scales, even at daily time steps. Thus constrained, numerical weather prediction precipitation fields do a reasonable job of representing large-scale diurnal variations.

  10. Verification of Satellite Rainfall Estimates from the Tropical Rainfall Measuring Mission over Ground Validation Sites

    NASA Astrophysics Data System (ADS)

    Fisher, B. L.; Wolff, D. B.; Silberstein, D. S.; Marks, D. M.; Pippitt, J. L.

    2007-12-01

    The Tropical Rainfall Measuring Mission's (TRMM) Ground Validation (GV) Program was originally established with the principal long-term goal of determining the random errors and systematic biases stemming from the application of the TRMM rainfall algorithms. The GV Program has been structured around two validation strategies: 1) determining the quantitative accuracy of the integrated monthly rainfall products at GV regional sites over large areas of about 500 km2 using integrated ground measurements and 2) evaluating the instantaneous satellite and GV rain rate statistics at spatio-temporal scales compatible with the satellite sensor resolution (Simpson et al. 1988, Thiele 1988). The GV Program has continued to evolve since the launch of the TRMM satellite on November 27, 1997. This presentation will discuss current GV methods of validating TRMM operational rain products in conjunction with ongoing research. The challenge facing TRMM GV has been how to best utilize rain information from the GV system to infer the random and systematic error characteristics of the satellite rain estimates. A fundamental problem of validating space-borne rain estimates is that the true mean areal rainfall is an ideal, scale-dependent parameter that cannot be directly measured. Empirical validation uses ground-based rain estimates to determine the error characteristics of the satellite-inferred rain estimates, but ground estimates also incur measurement errors and contribute to the error covariance. Furthermore, sampling errors, associated with the discrete, discontinuous temporal sampling by the rain sensors aboard the TRMM satellite, become statistically entangled in the monthly estimates. Sampling errors complicate the task of linking biases in the rain retrievals to the physics of the satellite algorithms. The TRMM Satellite Validation Office (TSVO) has made key progress towards effective satellite validation. For disentangling the sampling and retrieval errors, TSVO has developed

  11. A space-time downscaling model for rainfall

    NASA Astrophysics Data System (ADS)

    Venugopal, V.; Foufoula-Georgiou, Efi; Sapozhnikov, Victor

    1999-08-01

    Interpretation of the impact of climate change or climate variability on water resources management requires information at scales much smaller than the current resolution of regional climate models. Subgrid-scale variability of precipitation is typically resolved by running nested or variable resolution models or by statistical downscaling, the latter being especially attractive in ensemble predictions due to its computational efficiency. Most existing precipitation downscaling schemes are based on spatial disaggregation of rainfall patterns, independently at different times, and do not properly account for the temporal persistence of rainfall at the subgrid spatial scales. Such a temporal persistence in rainfall directly relates to the spatial variability of accumulated local soil moisture and might be important if the downscaled values were to be used in a coupled atmospheric-hydrologic model. In this paper we propose a rainfall downscaling model which utilizes the presence of dynamic scaling in rainfall [Venugopal et al., 1999] and which in conjunction with a spatial disaggregation scheme preserves both the temporal and spatial correlation structure of rainfall at the subgrid scales.

  12. The Interdependence between Rainfall and Temperature: Copula Analyses

    PubMed Central

    Cong, Rong-Gang; Brady, Mark

    2012-01-01

    Rainfall and temperature are important climatic inputs for agricultural production, especially in the context of climate change. However, accurate analysis and simulation of the joint distribution of rainfall and temperature are difficult due to possible interdependence between them. As one possible approach to this problem, five families of copula models are employed to model the interdependence between rainfall and temperature. Scania is a leading agricultural province in Sweden and is affected by a maritime climate. Historical climatic data for Scania is used to demonstrate the modeling process. Heteroscedasticity and autocorrelation of sample data are also considered to eliminate the possibility of observation error. The results indicate that for Scania there are negative correlations between rainfall and temperature for the months from April to July and September. The student copula is found to be most suitable to model the bivariate distribution of rainfall and temperature based on the Akaike information criterion (AIC) and Bayesian information criterion (BIC). Using the student copula, we simulate temperature and rainfall simultaneously. The resulting models can be integrated with research on agricultural production and planning to study the effects of changing climate on crop yields. PMID:23213286

  13. Climatology of daily rainfall semivariance in The Netherlands

    NASA Astrophysics Data System (ADS)

    van de Beek, C. Z.; Leijnse, H.; Torfs, P. J. J. F.; Uijlenhoet, R.

    2010-03-01

    Rain gauges can offer high quality rainfall measurements at their location. Networks of rain gauges can offer better insight into the space-time variability of rainfall, but they tend to be too widely spaced for accurate estimates between points. While remote sensing systems, such as radars and networks of microwave links, can offer good insight in the spatial variability of rainfall they tend to have more problems in identifying the correct rain amounts at the ground. A way to estimate the variability of rainfall between gauge points is to interpolate between them using fitted variograms. If a dense rain gauge network is lacking it is difficult to estimate accurate variograms. In this paper a 30-year dataset of daily rain accumulations gathered at 29 automatic weather stations operated by KNMI and a one-year dataset of 10 gauges in a network with a radius of 5 km around CESAR (Cabauw Experimental Site for Atmospheric Research) are employed to estimate variograms. Fitted variogram parameters are shown to vary according to season, closely following simple cosine functions allowing for applications in catchment hydrology and rainfall field generation. Semivariances at short ranges during winter and spring tend to be underestimated, but summer and autumn are well predicted. This climatological semivariance can be employed to estimate the accuracy of the rainfall input to a hydrological model even with only few gauges in a given catchment area.

  14. Reclaimed mineland curve number response to temporal distribution of rainfall

    USGS Publications Warehouse

    Warner, R.C.; Agouridis, C.T.; Vingralek, P.T.; Fogle, A.W.

    2010-01-01

    The curve number (CN) method is a common technique to estimate runoff volume, and it is widely used in coal mining operations such as those in the Appalachian region of Kentucky. However, very little CN data are available for watersheds disturbed by surface mining and then reclaimed using traditional techniques. Furthermore, as the CN method does not readily account for variations in infiltration rates due to varying rainfall distributions, the selection of a single CN value to encompass all temporal rainfall distributions could lead engineers to substantially under- or over-size water detention structures used in mining operations or other land uses such as development. Using rainfall and runoff data from a surface coal mine located in the Cumberland Plateau of eastern Kentucky, CNs were computed for conventionally reclaimed lands. The effects of temporal rainfall distributions on CNs was also examined by classifying storms as intense, steady, multi-interval intense, or multi-interval steady. Results indicate that CNs for such reclaimed lands ranged from 62 to 94 with a mean value of 85. Temporal rainfall distributions were also shown to significantly affect CN values with intense storms having significantly higher CNs than multi-interval storms. These results indicate that a period of recovery is present between rainfall bursts of a multi-interval storm that allows depressional storage and infiltration rates to rebound. ?? 2010 American Water Resources Association.

  15. Improvements in nozzle rainfall simulators used in laboratory environment

    NASA Astrophysics Data System (ADS)

    de Lima, João L. M. P.; Isidoro, Jorge M. G. P.; de Lima, M. Isabel P.; Carvalho, Sílvia C. P.

    2015-04-01

    Rainfall simulators are an important tool in studying soil erosion, which is considered a key process contributing to land degradation. The versatility of rainfall simulators enables their use in the laboratory and in the field, providing controlled conditions of rainfall intensity, kinetic energy, drop characteristics and event duration. Pressurized rainfall simulators have spray nozzles that can be characterized by the nozzle discharge, spray angle and pattern, and drop size distribution. However, the drop's properties and hence the entire simulated event depend on the system operating pressure and respective flow rate and also the nozzle design. The objective of this presentation is to report on recent improvements on rainfall simulators used in laboratory environment at the University of Coimbra, namely the use of pressure control devices upstream of nozzles, incorporation of meshes underneath sprays to change the spatial distribution of the kinetic energy and intensity of the simulated rain and fans to induce wind-driven rain. These improvements aimed at changing the simulated rain characteristics (e.g. intensity, kinetic energy and drop size distribution) and improve the quality and reproducibility of the rainfall simulations (e.g. precise start and stop, invariance in time).

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

    NASA Technical Reports Server (NTRS)

    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.

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

    NASA Technical Reports Server (NTRS)

    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.

  18. A Point Process Model of Summer Season Rainfall Occurrences

    NASA Astrophysics Data System (ADS)

    Smith, James A.; Karr, Alan F.

    1983-02-01

    A point process model of summer season rainfall occurrences is developed. The model, which is termed an RCM process, is a member of the family of Cox processes (Poisson processes for which the rate of occurrence of events varies randomly over time). Model development is based on counts and interarrival time statistics estimated from Potomac River basin rainfall data. The counting parameters used are the conditional intensity function, index of dispersion, and counts spectrum; the interarrival time parameters are the coefficient of variation and the autocorrelation function. Explicit results are presented for the counts and interarrival time parameters of RCM processes. Of particular importance in this paper is the interpretation of clustering suggested by the form of the RCM process. For the RCM process the rate of occurrence alternates between two states, one of which is 0, the other positive. During periods when the intensity is 0, no events can occur. The form of the intensity process suggests that clustering of summer season rainfall occurrences in the Potomac River basin results from the alternation of wet and dry periods. Computational results are presented for two extensions of the RCM process model of rainfall occurrences: a marked RCM process model of rainfall occurrences and associated storm depths and a bivariate RCM process model of rainfall occurrences at two sites.

  19. Tropical SST and Sahel rainfall: A non-stationary relationship

    NASA Astrophysics Data System (ADS)

    Losada, T.; Rodriguez-Fonseca, B.; Mohino, E.; Bader, J.; Janicot, S.; Mechoso, C. R.

    2012-06-01

    Sea surface temperature (SST) anomalies in the tropical Atlantic have been associated with precipitation anomalies in West Africa that form a dipole pattern with centers over the Sahel and the Gulf of Guinea. Whilst this was clear before the 1970's, the dipole pattern almost disappeared after that date, as the anti-correlation between rainfall anomalies in the Sahel and Guinea dropped abruptly. Simultaneously, the anti-correlations between Sahel rainfall and tropical Pacific SSTs strengthened. It has been posited that these changes after the 1970's developed as rainfall over West Africa started to co-vary with SSTs in the global tropics. In this co-variability, enhanced summer rainfall over West Africa with a monopole pattern corresponds to warmer SSTs in the tropical Atlantic and Maritime Continent, and colder SSTs in the tropical Pacific and western Indian Oceans. The present paper describes the hitherto unexplored seasonal evolution of this co-variability and the physical mechanisms at work. Sensitivity experiments with two atmospheric general circulation models demonstrate that, after the 1970's, the impacts of SST anomalies in the Indo-Pacific counteract those in the Atlantic in terms of generating rainfall anomalies over the Sahel, and that this superposition of effects is primarily linear. Therefore, at interannual timescales, the change in the patterns of co-variability between West African rainfall and tropical SSTs can explain the non-stationary relationship between the anomalies in these two fields.

  20. Multiscale influences on extreme winter rainfall in the Philippines

    NASA Astrophysics Data System (ADS)

    Pullen, Julie; Gordon, Arnold L.; Flatau, Maria; Doyle, James D.; Villanoy, Cesar; Cabrera, Olivia

    2015-04-01

    During 2007-2008, the Philippines experienced the greatest rainfall in 40 winters. We use a combination of observations (including 48 meteorological stations distributed throughout the islands, Tropical Rainfall Measuring Mission satellite-sensed precipitation, and shipboard measurements) along with a high-resolution two-way coupled ocean/atmosphere model (3 km Coupled Ocean-Atmosphere Mesoscale Prediction System (COAMPS)®) to examine this anomalous season. As expected from climatology, rainfall was greatest on the eastern side of the archipelago, with seasonal totals exceeding 4000 mm in some locations. A moderate to strong La Niña increased the rainfall across the region. But discrete precipitation events delivered the bulk of the rain to the area and coincided with intense Madden-Julian oscillation activity over the archipelago and a late February cold surge. General patterns and magnitudes of rainfall produced by the two-way coupled model agreed with observations from land and from space. During the discrete events, the 3 km COAMPS also produced high amounts of precipitation in the mountainous parts of central Philippines. Direct observations were limited in this region. However, the government reported river flooding and evacuations in Mindoro during February 2008 as a result of significant rainfall. In addition, shipboard measurements from late January 2008 (collected by the Philippines Straits Dynamics Experiment) reveal a fresh lens of water to the west of the island of Mindoro, consistent with high freshwater discharge (river runoff) into the coastal area.

  1. Annual Rainfall Forecasting by Using Mamdani Fuzzy Inference System

    NASA Astrophysics Data System (ADS)

    Fallah-Ghalhary, G.-A.; Habibi Nokhandan, M.; Mousavi Baygi, M.

    2009-04-01

    Long-term rainfall prediction is very important to countries thriving on agro-based economy. In general, climate and rainfall are highly non-linear phenomena in nature giving rise to what is known as "butterfly effect". The parameters that are required to predict the rainfall are enormous even for a short period. Soft computing is an innovative approach to construct computationally intelligent systems that are supposed to possess humanlike expertise within a specific domain, adapt themselves and learn to do better in changing environments, and explain how they make decisions. Unlike conventional artificial intelligence techniques the guiding principle of soft computing is to exploit tolerance for imprecision, uncertainty, robustness, partial truth to achieve tractability, and better rapport with reality. In this paper, 33 years of rainfall data analyzed in khorasan state, the northeastern part of Iran situated at latitude-longitude pairs (31°-38°N, 74°- 80°E). this research attempted to train Fuzzy Inference System (FIS) based prediction models with 33 years of rainfall data. For performance evaluation, the model predicted outputs were compared with the actual rainfall data. Simulation results reveal that soft computing techniques are promising and efficient. The test results using by FIS model showed that the RMSE was obtained 52 millimeter.

  2. Wet and dry spell characteristics of global tropical rainfall

    NASA Astrophysics Data System (ADS)

    Ratan, R.; Venugopal, V.

    2013-06-01

    In this study, we analyze satellite-based daily rainfall observations to compare and contrast the wet and dry spell characteristics of tropical rainfall. Defining a wet (dry) spell as the number of consecutive rainy (nonrainy) days, we find that the distributions of wet spells appear to exhibit universality in the following sense. While both ocean and land regions with high seasonal rainfall accumulation (humid regions; e.g., India, Amazon, Pacific Ocean) show a predominance of 2-4 day wet spells, those regions with low seasonal rainfall accumulation (arid regions; e.g., South Atlantic, South Australia) exhibit a wet spell duration distribution that is essentially exponential in nature, with a peak at 1 day. The behavior that we observed for wet spells is reversed for the dry spell characteristics. In other words, the main contribution to the dry part of the season, in terms of the number of nonrainy days, appears to come from 3-4 day dry spells in the arid regions, as opposed to 1 day dry spells in the humid regions. The total rainfall accumulated in each wet spell has also been analyzed, and we find that the major contribution to seasonal rainfall for arid regions comes from 1-5 day wet spells; however, for humid regions, this contribution comes from wet spells of duration as long as 30 days. We also explore the role of chance as well as the influence of organized convection in determining some of the observed features.

  3. Estimation of rainfall interception in grassland using eddy flux measurements

    NASA Astrophysics Data System (ADS)

    Maruyama, A.; Miyazawa, Y.; Inoue, A.

    2014-12-01

    Rainfall interception plays an important role in the water cycle in natural ecosystems. Interception by the forest canopies have been widely observed or estimated over various ecosystems, such as tropical rainforest, evergreen forest and deciduous forest. However interception by the short canopies, e.g. shrubby plant, grassland and crop, has been rarely observed since it has been difficult to obtain reliable precipitation measurements under the canopy. In this study, we estimated monthly and annual rainfall interception in grassland using evapotranspiration data of eddy flux measurements. Experiments were conducted in grassland (Italian ryegrass) from 2010 to 2012 growing season in Kumamoto, Japan. Evapotranspiration (latent heat flux) were observed throughout the year based on the eddy covariance technique. A three dimensional sonic anemometer and an open path CO2/H2O analyzer were used to calculate 30 min flux. Other meteorological factors, such as air temperature, humidity and solar radiation, were also observed. Rainfall interception was estimated as follows. 1) Using evapotranspiration data during dry period, environmental response of surface conductance (gc) was inversely calculated based on the big-leaf model. 2) Evapotranspiration without interception during precipitation period was estimated using above model and environmental response of gc. 3) Assuming that evaporation of intercepted rainfall is equal to the difference in evapotranspiration between above estimation and actual measurements, rainfall interception was estimated over experimental period. The account of rainfall interception in grassland using this technique will be presented at the meeting.

  4. Introducing hydrological information in rainfall intensity-duration thresholds

    NASA Astrophysics Data System (ADS)

    Greco, Roberto; Bogaard, Thom

    2016-04-01

    Regional landslide hazard assessment is mainly based on empirically derived precipitation-intensity-duration (PID) thresholds. Generally, two features of rainfall events are plotted to discriminate between observed occurrence and absence of occurrence of mass movements. Hereafter, a separation line is drawn in logarithmic space. Although successfully applied in many case studies, such PID thresholds suffer from many false positives as well as limited physical process insight. One of the main limitations is indeed that they do not include any information about the hydrological processes occurring along the slopes, so that the triggering is only related to rainfall characteristics. In order to introduce such an hydrological information in the definition of rainfall thresholds for shallow landslide triggering assessment, in this study the introduction of non-dimensional rainfall characteristics is proposed. In particular, rain storm depth, intensity and duration are divided by a characteristic infiltration depth, a characteristic infiltration rate and a characteristic duration, respectively. These latter variables depend on the hydraulic properties and on the moisture state of the soil cover at the beginning of the precipitation. The proposed variables are applied to the case of a slope covered with shallow pyroclastic deposits in Cervinara (southern Italy), for which experimental data of hourly rainfall and soil suction were available. Rainfall thresholds defined with the proposed non-dimensional variables perform significantly better than those defined with dimensional variables, either in the intensity-duration plane or in the depth-duration plane.

  5. On the Numerical Study of Heavy Rainfall in Taiwan

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Chen, Ching-Sen; Chen, Yi-Leng; Jou, Ben Jong-Dao; Lin, Pay-Liam; Starr, David OC. (Technical Monitor)

    2001-01-01

    Heavy rainfall events are frequently observed over the western side of the CMR (central mountain range), which runs through Taiwan in a north-south orientation, in a southwesterly flow regime and over the northeastern side of the CMR in a northeasterly flow regime. Previous studies have revealed the mechanisms by which the heavy rainfall events are formed. Some of them have examined characteristics of the heavy rainfall via numerical simulations. In this paper, some of the previous numerical studies on heavy rainfall events around Taiwan during the Mei-Yu season (May and June), summer (non-typhoon cases) and autumn will be reviewed. Associated mechanisms proposed from observational studies will be reviewed first, and then characteristics of numerically simulated heavy rainfall events will be presented. The formation mechanisms of heavy rainfall from simulated results and from observational analysis are then compared and discussed. Based on these previous modeling studies, we will also discuss what are the major observations and modeling processes which will be needed for understanding the heavy precipitation in the future.

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  7. Impact of rainfall spatial variability on Flash Flood Forecasting

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  8. Interactive effects of warming and altered rainfall timing on ecosystem processes in tallgrass prairie

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Temperature and rainfall are critical environmental drivers for grasslands. In the U.S. Central Plains mean temperatures are expected to increase and rainfall patterns are predicted to become more variable and extreme, with increased frequency of large rainfall events and extended inter-rainfall dr...

  9. Rainfall Estimation From The Persiann Satellite-based Algorithm

    NASA Astrophysics Data System (ADS)

    Hsu, K.; Sorooshian, S.; Gao, X.; Gupta, H.; Imam, B.

    Satellite-based rainfall estimates are important for many regions of the world where ground-based measurements are not well established and where continuous sensing is required. For years, many algorithms using geostationary satellite infrared imagery were developed. However, because cloud top temperatures are not corresponding well to the surface rainfall at pixel level, rainfall retrievals from algorithms developed us- ing pixel-by-pixel relationships are shown to be less accurate at high spatial-temporal scales. In this study, a rainfall estimation system, named PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks), is introduced. This system uses neural network function classification/approximation procedures to compute an estimate of rainfall rate at each 0.25 ` 0.25 pixel of the infrared brightness temperature image provided by geostationary satellites. More ef- fective features were included in the input system from scanning the infrared pixel array with a 5 ` 5 moving window surrounding an estimation pixel. Five statistics in- cluding the means and standard deviations of various window temperatures were ex- tracted. Further, a classification scheme, name self-organizing feature map, was used to classify those five features into a large number of rain/no-rain groups associated with different cloud characteristics. For each group, a multivariate linear function was provided to relate the values of the input features to the output rain rate at 30-minute time intervals. One additional feature of the PERISANN system is that the system pa- rameters are routinely adjustable from limited observation, such as passive microwave TRMM TMI and DMSP SSM/I rainfall rates and ground-based radar/gauge observa- tions. Therefore, updated rainfall estimates are continually provided. The PERSIANN system is currently in operation, and global six-hour rainfall products (50oS-50oN) are available through Hydrological Data and

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

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

  11. Inter-comparison of radar rainfall rate using Constant Altitude Plan Position Indicator and hybrid surface rainfall maps

    NASA Astrophysics Data System (ADS)

    Kwon, Soohyun; Jung, Sung-Hwa; Lee, GyuWon

    2015-12-01

    Ground clutter and beam blockage caused by complex terrain deteriorates the accuracy of radar quantitative precipitation estimations (QPE). To improve radar QPE, we have developed a technique for radar rainfall estimation, the Kyungpook National University Hybrid Surface Rainfall (KHSR), based on a two-dimensional hybrid surface consisting of the lowest radar bins that are immune to ground clutter, beam blockage, and non-meteorological echoes. The KHSR map is a composite of a ground echo mask, a beam blockage mask, and a rain echo mask, and it was applied to an operational S-band dual-polarimetric radar that scans six PPIs at a low elevation angle every 2.5 min. By using three rainfall estimators, R(ZH), R(ZH, ZDR), and R(ZH, ξDR), this technique was compared with an operational Constant Altitude Plan Position Indicator (CAPPI) QPE of the Korea Meteorological Administration during a summer season from June-August 2012. In comparison with CAPPI, KHSR shows improved rainfall estimates for three algorithms, and it was more effective with dual-polarimetric rainfall algorithms than with single polarimetric rainfall algorithms. Error increased with increasing range from radar, but this increase was more rapid using CAPPI than using KHSR. KHSR using the R(ZH, ZDR) algorithm was the most accurate long range (>100 km from the radar) estimator.

  12. Estimation of trends in rainfall extremes with mixed effects models

    NASA Astrophysics Data System (ADS)

    Kamruzzaman, M.; Beecham, S.; Metcalfe, A. V.

    2016-02-01

    Estimates of seasonal rainfall maxima at durations as short as 6 min are needed for many applications including the design and analysis of urban drainage systems. It is also important to investigate whether or not there is evidence of changes in these extremes, both as an indicator of the sensitivity of rainfall to anthropogenic and natural climate change and as an aid to the calibration of future scenarios. Estimation of trends in extreme values in a region needs to be based on all the available data if precision is to be achieved. However, extremes at different periods of accumulation at neighbouring sites are not independent because there are temporal and spatial correlations, respectively. A linear mixed effects (lme) model allows for this correlation structure, and can be fitted to unequal record lengths at different sites. The modelling technique is demonstrated with an analysis of monthly maximum rainfall, at nine aggregations between 6 min and 24 h, from six sites, with record lengths between 10 and 25 years, from a region in South Australia. In terms of mean value, there is no evidence of a trend or change in the seasonal distribution of the monthly extreme rainfall. However, there is a strong evidence of an increase in variability of monthly extreme rainfall, estimated as a 58% increase in absolute value of deviation from the mean over a 25 year period. Rainfall records are often only available as a daily accumulation. A formula for the ratio of the monthly maxima at durations shorter than 24 h, down to 6 min, to the 24 h monthly maximum, in terms of: duration, month of the year, and a site specific adjustment is estimated. There is a clear seasonal variation in the ratios and there is evidence of a difference between rainfall stations.

  13. Characteristics of daily variation of rainfall over the tropics

    NASA Astrophysics Data System (ADS)

    Inoue, Toshiro

    2015-04-01

    Characteristics of daily variation of rainfall over the tropics were studied using 14 years TRMM 3G68 data. Diurnal variation of rainfall has been studied extensively using in situ, satellite and radar data. Most studies on diurnal variation are focused on one local peak a day. We has noted on two local peaks of rainfall over southern Africa and Amazon during boreal winter from NICAM simulation and satellite observations. Our study suggests solar heating during daytime and radiation cooling during nighttime might cause the two local peaks of rainfall. The amplitude is depending on how strong the solar heating and/or radiation cooling comparing with other atmospheric conditions. Here we studied the two local peaks of rainfall over the tropics (30N-30S) with changing the area size (1.5, 2.5, 5 lat/lon grid) and season. Basic hourly rainfall data was constructed over 0.5 lat/lon grid by averaging 14 years 3G68 data (both PR and TMI). First we select the grid where two local peaks exist. The grid is defined as second peak is larger than 20% of primary peak. Further, when we detect more than two peaks, we discard the grid. Then we applied harmonic analysis for the time series over the grid (where only two local peaks exist) to get the second amplitude. Regardless of area size and sensor (PR/TMI), we can see many grids where the two local peaks a day exist, over both ocean and land. The amplitude is slightly larger over land and larger amount of rainfall area where shifts depending on season. Most grids indicate that earlier peak corresponds to early morning and later peak corresponds to afternoon.

  14. Bias Adjustment of PERSIANN Rainfall for Hydrologic Applications

    NASA Astrophysics Data System (ADS)

    Hsu, K.; Braithwaite, D.; Imam, B.; Gao, X.; Sorooshian, S.

    2008-05-01

    The exchange of water and energy through the land and atmospheric interaction occurs at various space and time scales. Modeling these exchanges, in general, and more specifically, adequate capturing of land surface hydrologic processes such as soil moisture and runoff generation requires reliable modeling and measurement of precipitation at fine time scale. The maturity of Satellite-based rainfall estimates is now sufficient to consider the value of such products in improving land surface models. This study addresses the measurement and bias correction of PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) rainfall to sub-daily scale of 0.25ox0.25o with emphasis on its potential use in land-surface hydrologic applications. The satellite-based PERSIANN system estimates surface rainfall based on infrared temperature and local image texture from geostationary satellites. Model parameters of PERSIANN are frequently adjusted when passive microwave rainfall estimates from low-orbital satellites (EOS, TRMM, NOAA, and DMSP) are available. PERSIANN estimates rainfall at hourly and 0.25ox0.25o lat-long scales. Its products are accumulated to daily and monthly scales for various applications. In this presentation, PERSIANN bias adjustment using monthly estimates from the Global Precipitation Climatology Project (GPCP) product is explored. Hourly PERSIANN rainfall estimates are first aggregated both spatially and temporally to the monthly 2.5ox2.5o scale and subsequently adjusted using GCPC monthly estimates as reference. Values of bias in PERSIANN are used to adjust PERSIANN rainfall at the 0.25ox0.25o hourly scale. The effectiveness of bias adjustment is evaluated using radar and gauge measurements at sub- daily to monthly scales at a spatial resolution of 0.25ox0.25o lat-long. The potential use of adjusted PERSIANN in hydrologic applications will be presented and discussed.

  15. Multiscale Hydrologic Evaluation of Radar Rainfall for Flow Simulations

    NASA Astrophysics Data System (ADS)

    Quintero, Felipe; Krajewski, Witold; Seo, Bong-Chul; Mantilla, Ricardo

    2016-04-01

    We made an evaluation of the performance of a hydrologic model to produce real-time flow forecasts. The model has been developed by the Iowa Flood Center (IFC), and it is implemented operationally to produce streamflow forecast for the communities of the State of Iowa in the United States. The model parameters are calibration-free. It has a parsimonious structure, that reproduces the more significant processes involved in the transformation from rainfall to runoff. The operational model uses a rainfall forcing produced by IFC, derived from the combination of rainfall fields of seven NEXRAD radars. However, this rainfall forcing does not include bias adjustment from rain gauges, due to the non-existence of a raingage network that enable the correction in real-time. In consideration, the model is also run offline using bias-adjusted rainfall products as Stage IV, and more recently MRMS. We used an extensive record of five years of IFC rainfall product and Stage IV, to evaluate the performance of the hydrologic model and the sensitivity of the flow simulations to model input. The model is not calibrated to any particular rainfall product. The distributed structure of the model allows to obtain results at any channel of the drainage network. We obtained simulated hydrographs at about 150 locations with different sub-basin spatial scales, where there are available USGS gages with streamflow observations. We obtained error metrics as Nash Sutcliffe efficiency and root mean square error, by comparing flow simulations to observations. We evaluated also the number of occurrences of hits and false alarms of discharge forecasts exceeding flood stage.

  16. Relationships between Rwandan seasonal rainfall anomalies and ENSO events

    NASA Astrophysics Data System (ADS)

    Muhire, I.; Ahmed, F.; Abutaleb, K.

    2015-10-01

    This study aims primarily at investigating the relationships between Rwandan seasonal rainfall anomalies and El Niño-South Oscillation phenomenon (ENSO) events. The study is useful for early warning of negative effects associated with extreme rainfall anomalies across the country. It covers the period 1935-1992, using long and short rains data from 28 weather stations in Rwanda and ENSO events resourced from Glantz (2001). The mean standardized anomaly indices were calculated to investigate their associations with ENSO events. One-way analysis of variance was applied on the mean standardized anomaly index values per ENSO event to explore the spatial correlation of rainfall anomalies per ENSO event. A geographical information system was used to present spatially the variations in mean standardized anomaly indices per ENSO event. The results showed approximately three climatic periods, namely, dry period (1935-1960), semi-humid period (1961-1976) and wet period (1977-1992). Though positive and negative correlations were detected between extreme short rains anomalies and El Niño events, La Niña events were mostly linked to negative rainfall anomalies while El Niño events were associated with positive rainfall anomalies. The occurrence of El Niño and La Niña in the same year does not show any clear association with rainfall anomalies. However, the phenomenon was more linked with positive long rains anomalies and negative short rains anomalies. The normal years were largely linked with negative long rains anomalies and positive short rains anomalies, which is a pointer to the influence of other factors other than ENSO events. This makes projection of seasonal rainfall anomalies in the country by merely predicting ENSO events difficult.

  17. Downscaling of rainfall in Peru using Generalised Linear Models

    NASA Astrophysics Data System (ADS)

    Bergin, E.; Buytaert, W.; Onof, C.; Wheater, H.

    2012-04-01

    The assessment of water resources in the Peruvian Andes is particularly important because the Peruvian economy relies heavily on agriculture. Much of the agricultural land is situated near to the coast and relies on large quantities of water for irrigation. The simulation of synthetic rainfall series is thus important to evaluate the reliability of water supplies for current and future scenarios of climate change. In addition to water resources concerns, there is also a need to understand extreme heavy rainfall events, as there was significant flooding in Machu Picchu in 2010. The region exhibits a reduction of rainfall in 1983, associated with El Nino Southern Oscillation (SOI). NCEP Reanalysis 1 data was used to provide weather variable data. Correlations were calculated for several weather variables using raingauge data in the Andes. These were used to evaluate teleconnections and provide suggested covariates for the downscaling model. External covariates used in the model include sea level pressure and sea surface temperature over the region of the Humboldt Current. Relative humidity and temperature data over the region are also included. The SOI teleconnection is also used. Covariates are standardised using observations for 1960-1990. The GlimClim downscaling model was used to fit a stochastic daily rainfall model to 13 sites in the Peruvian Andes. Results indicate that the model is able to reproduce rainfall statistics well, despite the large area used. Although the correlation between individual rain gauges is generally quite low, all sites are affected by similar weather patterns. This is an assumption of the GlimClim downscaling model. Climate change scenarios are considered using several GCM outputs for the A1B scenario. GCM data was corrected for bias using 1960-1990 outputs from the 20C3M scenario. Rainfall statistics for current and future scenarios are compared. The region shows an overall decrease in mean rainfall but with an increase in variance.

  18. Month-Year Rainfall Maps of the Hawaiian Islands

    NASA Astrophysics Data System (ADS)

    Frazier, A. G.; Giambelluca, T. W.; Diaz, H. F.

    2010-12-01

    The Hawaiian Islands have one of the most spatially-diverse rainfall patterns on earth. Island topography, persistent trade winds, thermal effects of the islands, and the presence of the trade-wind inversion interact to cause air to be lifted in distinct spatial patterns anchored to the topography. The resulting clouds and rainfall produced by this uplift lead to extreme gradients in monthly and annual rainfall in the islands. Knowledge of the rainfall patterns is critically important for a variety of resource management issues, including ground water and surface water development and protection, controlling and eradicating invasive species, protecting and restoring native ecosystems, and planning for the effects of global warming. In this study, development of month-year rainfall maps from 1920-2007 for the six major Hawaiian islands using geostatistical methods is undertaken. While mean monthly and annual rainfall maps for Hawaii are available, spatially continuous maps of precipitation for individual months do not exist. Simple methods, such as linear interpolation or ordinary kriging, are not appropriate for interpolating month-year rainfall due to the extreme spatial diversity. A method comparison is performed here to choose the best interpolation method for each island. The comparison focuses on different kriging algorithms including kriging with an external drift and simple kriging with varying local means. Parameter sensitivity tests are used for each method, and several covariates are considered to reduce interpolation error. The different combinations of methods, covariates and parameters are evaluated using cross validation statistics. To produce the final maps, the anomaly method is used to relate station data from every individual month with the 1978-2007 mean monthly maps. The anomalies are interpolated using the best method determined from the comparison, and then recombined with the mean maps to produce the final maps for the six major Hawaiian

  19. Satellite remote sensing of global rainfall using passive microwave radiometry

    SciTech Connect

    Ferriday, J.G.

    1994-12-31

    Global rainfall over land and ocean is estimated using measurements of upwelling microwaves by a satellite passive microwave radiometer. Radiative transfer calculations through a cloud model are used to parameterize an inversion technique for retrieving rain rates from brightness temperatures measured by the Special Sensor Microwave Imager (SSM/I). The rainfall retrieval technique is based on the interaction between multi-spectral microwave radiances and millimeter sized liquid and frozen hydrometeors distributed in the satellite`s field of view. The rain rate algorithm is sensitive to both hydrometeor emission and scattering while being relatively insensitive to extraneous atmospheric and surface effects. Separate formulations are used over ocean and land to account for different background microwave characteristics and the algorithm corrects for inhomogeneous distributions of rain rates within the satellite`s field of view. Estimates of instantaneous and climate scale rainfall are validated through comparisons with modeled clouds, surface radars, rain gauges and alternative satellite estimates. The accuracy of the rainfall estimates is determined from a combination of validation comparisons, theoretical sampling error calculations, and modeled sensitivity to variations in atmospheric and surface radiative properties. An error budget is constructed for both instantaneous rain rates and climate scale global estimates. At a one degree resolution, the root mean square errors in instantaneous rain rate estimates are 13% over ocean and 20% over land. The root mean square errors in global rainfall totals over a four month period are found to be 46% over ocean and 63% over land. Global rainfall totals are computed on a monthly scale for a three year period from 1987 to 1990. The time series is analyzed for climate scale rainfall distribution and variability.

  20. Interannual Rainfall Variability in the Tropical Atlantic Region

    NASA Technical Reports Server (NTRS)

    Gu, Guojun

    2005-01-01

    Rainfall variability on seasonal and interannual-to-interdecadal time scales in the tropical Atlantic is quantified using a 25-year (1979-2003) monthly rainfall dataset from the Global Precipitation Climatology Project (GPCP). The ITCZ measured by monthly rainfall between 15-37.5 deg W attains its peak as moving to the northernmost latitude (4-10 deg N) during July-September in which the most total rainfall is observed in the tropical Atlantic basin (17.5 deg S-22.5 deg N, 15 deg-37.5 deg W); the ITCZ becomes weakest during January-February with the least total rainfall as it moves to the south. In contrast, rainfall variability on interannual to interdecadal time scales shows a quite different seasonal preference. The most intense interannual variability occurs during March-May when the ITCZ tends to be near the equator and becomes weaker. Significant, negative correlations between the ITCZ strength and latitude anomalies are observed during boreal spring and early summer. The ITCZ strength and total rainfall amount in the tropical Atlantic basin are significantly modulated by the Pacific El Nino and the Atlantic equatorial mode (or Atlantic Nino) particularly during boreal spring and summer; whereas the impact of the Atlantic interhemispheric mode is considerably weaker. Regarding the anomalous latitudes of the ITCZ, the influence can come from both local, i.e., the Atlantic interhemispheric and equatorial modes, and remote forcings, i. e., El Nino; however, a direct impact of El Nino on the latitudes of the ITCZ can only be found during April-July, not in winter and early spring in which the warmest SST anomalies are usually observed in the equatorial Pacific.

  1. Christiansen Revisited: Rethinking Quantification of Uniformity in Rainfall Simulator Studies

    NASA Astrophysics Data System (ADS)

    Green, Daniel; Pattison, Ian

    2016-04-01

    Rainfall simulators, whether based within a laboratory or field setting are used extensively within a number of fields of research, including plot-scale runoff, infiltration and erosion studies, irrigation and crop management and scaled investigations into urban flooding. Rainfall simulators offer a number of benefits, including the ability to create regulated and repeatable rainfall characteristics (e.g. intensity, duration, drop size distribution and kinetic energy) without relying on unpredictable natural precipitation regimes. Ensuring and quantifying spatially uniform simulated rainfall across the entirety of the plot area is of particular importance to researchers undertaking rainfall simulation. As a result, numerous studies have focused on the quantification and improvement of uniformity values. Several statistical methods for the assessment of rainfall simulator uniformity have been developed. However, the Christiansen Uniformity Coefficient (CUC) suggested by Christiansen (1942) is most frequently used. Despite this, there is no set methodology and researchers can adapt or alter factors such as the quantity, as well as the spacing, distance and location of the measuring beakers used to derive CUC values. Because CUC values are highly sensitive to the resolution of the data, i.e. the number of observations taken, many densely distributed measuring containers subjected to the same experimental conditions may generate a significantly lower CUC value than fewer, more sparsely distributed measuring containers. Thus, the simulated rainfall under a higher resolution sampling method could appear less uniform than when using a coarser resolution sampling method, despite being derived from the same initial rainfall conditions. Expressing entire plot uniformity as a single, simplified percentage value disregards valuable qualitative information about plot uniformity, such as the small-scale spatial distribution of rainfall over the plot surface and whether these

  2. Calibration of three rainfall simulators with automatic measurement methods

    NASA Astrophysics Data System (ADS)

    Roldan, Margarita

    2010-05-01

    CALIBRATION OF THREE RAINFALL SIMULATORS WITH AUTOMATIC MEASUREMENT METHODS M. Roldán (1), I. Martín (2), F. Martín (2), S. de Alba(3), M. Alcázar(3), F.I. Cermeño(3) 1 Grupo de Investigación Ecología y Gestión Forestal Sostenible. ECOGESFOR-Universidad Politécnica de Madrid. E.U.I.T. Forestal. Avda. Ramiro de Maeztu s/n. Ciudad Universitaria. 28040 Madrid. margarita.roldan@upm.es 2 E.U.I.T. Forestal. Avda. Ramiro de Maeztu s/n. Ciudad Universitaria. 28040 Madrid. 3 Facultad de Ciencias Geológicas. Universidad Complutense de Madrid. Ciudad Universitaria s/n. 28040 Madrid The rainfall erosivity is the potential ability of rain to cause erosion. It is function of the physical characteristics of rainfall (Hudson, 1971). Most expressions describing erosivity are related to kinetic energy or momentum and so with drop mass or size and fall velocity. Therefore, research on factors determining erosivity leds to the necessity to study the relation between fall height and fall velocity for different drop sizes, generated in a rainfall simulator (Epema G.F.and Riezebos H.Th, 1983) Rainfall simulators are one of the most used tools for erosion studies and are used to determine fall velocity and drop size. Rainfall simulators allow repeated and multiple measurements The main reason for use of rainfall simulation as a research tool is to reproduce in a controlled way the behaviour expected in the natural environment. But in many occasions when simulated rain is used in order to compare it with natural rain, there is a lack of correspondence between natural and simulated rain and this can introduce some doubt about validity of data because the characteristics of natural rain are not adequately represented in rainfall simulation research (Dunkerley D., 2008). Many times the rainfall simulations have high rain rates and they do not resemble natural rain events and these measures are not comparables. And besides the intensity is related to the kinetic energy which

  3. Singularity-sensitive merging of radar and raingauge rainfall data

    NASA Astrophysics Data System (ADS)

    Wang, Li-Pen; Willems, Patrick; Ochoa-Rodriguez, Susana; Onof, Christian

    2014-05-01

    Traditionally, urban hydrological applications relied mainly upon rain gauge data as input as these provide accurate point rainfall estimates near the ground surface. However, they cannot capture the spatial variability of rainfall, which has a significant impact on the urban hydrological system and thus on the modelling of urban pluvial flooding. Thanks to the development of radar technology, weather radar has been playing an increasingly important role in urban hydrology. Radars can survey large areas and better capture the spatial variability of the rainfall, thus improving the short term predictability of rainfall and flooding. However, the accuracy of radar measurements is in general insufficient, particularly in the case of extreme rainfall magnitudes. This has a tremendous effect on the subsequent hydraulic model outputs. In order to improve the accuracy of radar rainfall estimates while preserving their spatial description of rainfall fields, it is possible to dynamically adjust them based on rain gauge measurements. Studies on this subject have been carried out over the last few years, though most of them focus on the hydrological applications at large scales. A couple of recent research works have examined the applicability of these adjustment techniques to urban-scale hydrological applications and concluded that these techniques can effectively reduce rainfall bias, thus leading to improvements in the reproduction of hydraulic outputs (Wang et al., 2013). However, underestimation of storm peaks can still be seen after adjustment and this is particularly significant in the case of small drainage areas and for extreme rainfall magnitudes. This may be due to the fact that the underlying adjustment techniques, mainly based upon Gaussian approximations, cannot properly cope with the non-normality observed in urban scale applications. With the purpose of improving this aspect, a methodology has been developed which identifies the local extremes or

  4. Droughts, rainfall and rural water supply in northern Nigeria

    NASA Astrophysics Data System (ADS)

    Tarhule, Aondover Augustine

    Knowledge concerning various aspects of drought and water scarcity is required to predict, and to articulate strategies to minimize the effects of future events. This thesis investigated different aspects of droughts and rainfall variability at several time scales and described the dynamics of water supply and use in a rural village in northeastern Nigeria. The parallel existence of measured climatic records and information on famine/folklore events is utilized to calibrate the historical information against the measured data. It is shown that famines or historical droughts occurred when the cumulative deficit of rainfall fell below 1.3 times the standard deviation of the long-term mean rainfall. The study demonstrated that famine chronologies are adequate proxy for drought events, providing a means for the reconstruction of the drought/climatic history of the region. Analysis of recent changes in annual rainfall characteristics show that the series of annual rainfall and number of rain days experienced a discontinuity during the 1960's, caused largely by the decrease in the frequency of moderate to high intensity rain events. The periods prior to and after the change point are homogenous and provide an objective basis for the estimation of changes in rainfall characteristics, drought parameters and for demarcating the region into sub-zones. Rainfall variability was unaffected by the abrupt change. Furthermore, the variability is independently distributed and adequately described by the normal distribution. This allows estimates of the probability of various magnitudes or thresholds of variability. The effects of droughts and rainfall variability are most strongly felt in rural areas. Analysis of the patterns of water supply and use in a typical rural village revealed that the hydrologic system is driven by the local rainfall. Perturbations in the rains propagate through the system with short lag time between the various components. Where fadama aquifers occur

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

    NASA Astrophysics Data System (ADS)

    Callau Poduje, Ana Claudia; Haberlandt, Uwe

    2014-05-01

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

  6. Sensitivity Studies of the Radar-Rainfall Error Models

    NASA Astrophysics Data System (ADS)

    Villarini, G.; Krajewski, W. F.; Ciach, G. J.

    2007-12-01

    It is well acknowledged that there are large uncertainties associated with the operational quantitative precipitation estimates produced by the U.S. national network of WSR-88D radars. These errors are due to the measurement principles, parameter estimation, and not fully understood physical processes. Comprehensive quantitative evaluation of these uncertainties is still at an early stage. The authors proposed an empirically-based model in which the relation between true rainfall (RA) and radar-rainfall (RR) could be described as the product of a deterministic distortion function and a random component. However, how different values of the parameters in the radar-rainfall algorithms used to create these products impact the model results still remains an open question. In this study, the authors investigate the effects of different exponents in the Z-R relation (Marshall- Palmer, NEXRAD, and tropical) and of an anomalous propagation (AP) removal algorithm. Additionally, they generalize the model to describe the radar-rainfall uncertainties in the additive form. This approach is fully empirically based and rain gauge estimates are considered as an approximation of the true rainfall. The proposed results are based on a large sample (six years) of data from the Oklahoma City radar (KTLX) and processed through the Hydro-NEXRAD software system. The radar data are complemented with the corresponding rain gauge observations from the Oklahoma Mesonet, and the Agricultural Research Service Micronet.

  7. Country-wide rainfall maps from cellular communication networks

    PubMed Central

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2013-01-01

    Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal’s attenuation between transmitter and receiver. Here, we show how one such a network can be used to retrieve the space–time dynamics of rainfall for an entire country (The Netherlands, ∼35,500 km2), based on an unprecedented number of links (∼2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrates the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent. PMID:23382210

  8. Evaluation of Rainfall-Runoff Models for Mediterranean Subcatchments

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  9. Country-wide rainfall maps from cellular communication networks.

    PubMed

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2013-02-19

    Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal's attenuation between transmitter and receiver. Here, we show how one such a network can be used to retrieve the space-time dynamics of rainfall for an entire country (The Netherlands, ∼35,500 km(2)), based on an unprecedented number of links (∼2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrates the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent. PMID:23382210

  10. Estimating temporal changes in extreme rainfall in Sicily Region (Italy)

    NASA Astrophysics Data System (ADS)

    Bonaccorso, Brunella; Aronica, Giuseppe

    2016-04-01

    An intensification of extreme rainfall events have characterized several areas of peninsular and insular Italy since the early 2000s, suggesting an upward ongoing trend likely driven by climate change. In the present study temporal changes in 1-, 3-, 6-, 12- and 24-hour annual maxima rainfall series from more than 200 sites in Sicily region (Italy) are examined. A regional study is performed in order to reduce the uncertainty in change detection related to the limited length of the available records of extreme rainfall series. More specifically, annual maxima series are treated according to a regional flood index - type approach to frequency analysis, by assuming stationarity on a decadal time scale. First a cluster analysis using at-site characteristics is used to determine homogeneous rainfall regions. Then, potential changes in regional L-moment ratios are analyzed using a 10-year moving window. Furthermore, the shapes of regional growth curves, derived by splitting the records into separate decades, are compared. In addition, a jackknife procedure is used to assess uncertainty in the fitted growth curves and to identify significant trends in quantile estimates. Results reveal that, despite L-moment ratios show a general decreasing trend and that growth curves corresponding to the last decade (2000-2009) are usually less steep than the ones of the previous periods, rainfall quantile estimates have increased during the 2000s due to a large increase in regional average median, mainly in Western Sicily.

  11. Rainfall results, 1970-1975: Florida area cumulus experiment.

    PubMed

    Woodley, W L; Simpson, J; Biondini, R; Berkeley, J

    1977-02-25

    The latest rainfall results of the Florida Area Cumulus Experiment (FACE) are discussed after a review of the background, design, and early results of this experiment. Analysis without the benefit of data stratification and appropriate covariates of the 48 random experimentation days obtained through 1975 provided no evidence that dynamic seeding appreciably altered the rainfall over the fixed target area (1.3 x 10(4) square kilometers). Partitioning of the experimentation days according to whether the convective echoes moved across the Florida peninsula or developed in situ was more informative. Use of this echo motion covariate with five meaningful predictor models of natural rainfall in a stepwise regression program produced persuasive evidence for an effect of seeding in both echo motion categories. For days with moving echoes, there is evidence for a positive, statistically significant treatment effect on the rainfall from the subject clouds (the floating target) and in the overall target area. The results for days with stationary echoes, although considerably more tentative, suggest that seeding produces more rainfall in the floating target but with no net change of the precipitation in the overall target area. The ramifications of this result and a possible explanation are discussed. Corroborative statistical analyses and discussion are presented, including a discussion of the physical bases and history of the echo motion covariate and the meteorological predictors, analysis that is supportive of the rain-gage-adjusted radar measurements of precipitation in FACE and results of relevant cloud physics measurements in Florida. PMID:17788851

  12. Spatial Scaling of Global Rainfall and Flood Extremes

    NASA Astrophysics Data System (ADS)

    Devineni, Naresh; Lall, Upmanu; Xi, Chen; Ward, Philip

    2014-05-01

    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 and spatial extent of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (up to 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. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances and floods. We present the first ever results on a global analysis of the scaling characteristics of extreme rainfall and flood event duration, volumes and contiguous flooded areas as a result of large scale organization of long duration rainfall events. Results are organized by latitude and with reference to the phases of ENSO, and reveal surprising invariance across latitude. Speculation as to the potential relation to the dynamical factors is presented

  13. The impacts of Middle East dust on Indian summer rainfall

    NASA Astrophysics Data System (ADS)

    Jin, Q.; Yang, Z. L.; Wei, J.

    2014-12-01

    Using the Weather Research and Forecasting model with online chemistry (WRF-Chem), the impact of Middle East dust aerosols on the Indian summer monsoon rainfall was studied. Eight numerical experiments were conducted to take into account uncertainties related to dust-absorbing properties, various assumptions used in calculating aerosol optical depth (AOD), and various radiation schemes. In order to obtain reasonable dust emission, model-simulated AOD and radiation forcing at the top of the atmosphere were compared with multiple satellite- and surface-based observations. Consistent with observations, modeled results show heavy dust loadings in the Arabian Peninsula and Pakistan, which can be transported through long distance to the Arabian Sea and the Indian Peninsula. By heating the atmosphere in the lower troposphere over the Iranian Plateau, these dust aerosols result in strengthened Indian summer monsoon circulations, which in turn transport more water vapor to the Indian Peninsula. The model shows that northern India becomes wetter during the monsoon season in dust cases than non-dust cases. Further observational analyses show an increasing trend in AOD over the Arabian Peninsula, which corresponds to an increasing trend of rainfall in northern India during summer monsoon seasons from 2000 to 2013. These observed trends of AOD and rainfall are consistent with the model-simulated positive relationship between Middle East dust and Indian summer monsoon rainfall. Our results highlight long-term (decadal) impacts of Middle East dust aerosols on the Indian summer rainfall.

  14. Rainfall simulator for laboratory use in acidic precipitation studies

    SciTech Connect

    Chevone, B.I.; Yang, Y.S.; Winner, W.E.; Storks-Cotter, I.; Long, S.J.

    1984-04-01

    A rainfall simulator, developed on the principle of droplet formation from needle tips, is described. The simulator is designed for laboratory experimentation to examine the effects of acidic precipitation on terrestrial plants. Droplet diameter can be varied from 2.5 to 3.4 mm with different gauge needles, and rainfall intensities from 0.50 to 1.25 cm h/sup -1/ can be attained by a variable speed peristaltic pump. Uniform distribution of rainfall was achieved by rotating the target area and by spacing needles, using an empirical cumulative probability distribution function, along eight radial tubular arms. Variation in rainfall distribution across a 1.2 m diameter circular target area was < 5%. Integrity of solution chemistry was maintained upon passage through the simulator with variations in cation concentrations < 10%, anion concentrations < 5% and pH < 0.2. The system offers sufficient flexibility to simulate a range of rainfall characteristics by varying needle diameter, changing pump speed and/or altering the number of radial arms on each unit.

  15. Intensity of Rainfall and Severity of Melioidosis, Australia

    PubMed Central

    Jacups, Susan P.

    2003-01-01

    In a 12-year prospective study of 318 culture-confirmed cases of melioidosis from the Top End of the Northern Territory of Australia, rainfall data for individual patient locations were correlated with patient risk factors, clinical parameters, and outcomes. Median rainfall in the 14 days before admission was highest for those dying with melioidosis (211 mm), in comparison to 110 mm for those surviving (p = 0.0002). Median 14-day rainfall was also significantly higher for those admitted with pneumonia. On univariate analysis, a prior 14-day rainfall of ≥125 mm was significantly correlated with pneumonia (odds ratio [OR] 1.70 [confidence interval [CI] 1.09 to 2.65]), bacteremia (OR 1.93 [CI 1.24 to 3.02]), septic shock (OR 1.94 [CI 1.14 to 3.29]), and death (OR 2.50 [CI 1.36 to 4.57]). On multivariate analysis, rainfall in the 14 days before admission was an independent risk factor for pneumonia (p = 0.023), bacteremic pneumonia (p = 0.001), septic shock (p = 0.005), and death (p < 0.0001). Heavy monsoonal rains and winds may cause a shift towards inhalation of Burkholderia pseudomallei. PMID:14720392

  16. Impacts of rainfall spatial variability on hydrogeological response

    NASA Astrophysics Data System (ADS)

    Sapriza-Azuri, Gonzalo; Jódar, Jorge; Navarro, Vicente; Slooten, Luit Jan; Carrera, Jesús; Gupta, Hoshin V.

    2015-02-01

    There is currently no general consensus on how the spatial variability of rainfall impacts and propagates through complex hydrogeological systems. Most studies to date have focused on the effects of rainfall spatial variability (RSV) on river discharge, while paying little attention to other important aspects of system response. Here, we study the impacts of RSV on several responses of a hydrological model of an overexploited system. To this end, we drive a spatially distributed hydrogeological model for the semiarid Upper Guadiana basin in central Spain with stochastic daily rainfall fields defined at three different spatial resolutions (fine → 2.5 km × 2.5 km, medium → 50 km × 50 km, large → lumped). This enables us to investigate how (i) RSV at different spatial resolutions, and (ii) rainfall uncertainty, are propagated through the hydrogeological model of the system. Our results demonstrate that RSV has a significant impact on the modeled response of the system, by specifically affecting groundwater recharge and runoff generation, and thereby propagating through to various other related hydrological responses (river discharge, river-aquifer exchange, groundwater levels). These results call into question the validity of management decisions made using hydrological models calibrated or forced with spatially lumped rainfall.

  17. Propagation of radar rainfall uncertainty in urban flood simulations

    NASA Astrophysics Data System (ADS)

    Liguori, Sara; Rico-Ramirez, Miguel

    2013-04-01

    This work discusses the results of the implementation of a novel probabilistic system designed to improve ensemble sewer flow predictions for the drainage network of a small urban area in the North of England. The probabilistic system has been developed to model the uncertainty associated to radar rainfall estimates and propagate it through radar-based ensemble sewer flow predictions. The assessment of this system aims at outlining the benefits of addressing the uncertainty associated to radar rainfall estimates in a probabilistic framework, to be potentially implemented in the real-time management of the sewer network in the study area. Radar rainfall estimates are affected by uncertainty due to various factors [1-3] and quality control and correction techniques have been developed in order to improve their accuracy. However, the hydrological use of radar rainfall estimates and forecasts remains challenging. A significant effort has been devoted by the international research community to the assessment of the uncertainty propagation through probabilistic hydro-meteorological forecast systems [4-5], and various approaches have been implemented for the purpose of characterizing the uncertainty in radar rainfall estimates and forecasts [6-11]. A radar-based ensemble stochastic approach, similar to the one implemented for use in the Southern-Alps by the REAL system [6], has been developed for the purpose of this work. An ensemble generator has been calibrated on the basis of the spatial-temporal characteristics of the residual error in radar estimates assessed with reference to rainfall records from around 200 rain gauges available for the year 2007, previously post-processed and corrected by the UK Met Office [12-13]. Each ensemble member is determined by summing a perturbation field to the unperturbed radar rainfall field. The perturbations are generated by imposing the radar error spatial and temporal correlation structure to purely stochastic fields. A

  18. Spatial Variation Scales of Rainfall Characteristics and Bromide Leaching

    NASA Astrophysics Data System (ADS)

    Wendroth, O. O.; Vasquez, V.; Matocha, C.

    2010-12-01

    Amount and intensity of rainfall are known as important characteristics that affect the leaching of surface-applied agri-chemicals. Besides these, the effect of the time interval between a fertilizer, pesticide or tracer application and subsequent rainfall on solute leaching is not well understood. Moreover, little is known about the spatial representativity of the solute concentration based on a relatively small soil sample in field-scale transport studies. To know the spatial representativity of a solute concentration sample at a time is crucial for analyzing solute leaching behavior over time as well as over space. The objectives of this study were to identify the impact of rainfall intensity and amount as well as the application time delay on solute transport in a well-drained Maury silt loam soil. Moreover, an experimental design and protocol had to be developed that exhibited spatial variability structure and representativity of bromide concentration. For this purpose, the variation scale of each of the factors investigated was chosen differently to apply frequency domain statistics. The study was conducted in a Maury silt loam soil at the University of Kentucky, College of Agriculture Experimental Farm Spindletop. Along a 64-m transect, 32 plots each 2-m long and 4-m wide were established. The three different treatments were spatially laid out in sinusoidal patterns at three respective wavelengths. Two different rainfall amounts were applied in blocks of eight consecutive plots, hence a wavelength of 32 m. These two different rainfall amounts were applied at four rates, spatially distributed in two waves each of 16 m length. Individual plots received the irrigation at specific times after the tracer had been applied. Four application delay times were chosen, hence the wavelength for this treatment was 8 m. Bromide concentration was measured for soil samples that were taken with a percussion auger at every 50 cm distance along the 64-m-transect. Auger cores

  19. Some considerations of periodicity and persistence in daily rainfalls

    NASA Astrophysics Data System (ADS)

    Kottegoda, N. T.; Natale, L.; Raiteri, E.

    2004-08-01

    In formulating mathematical models for the evaluation of variability in daily rainfalls, periodicity and persistence are two of the main characteristics to consider. We review periodogram analysis ranging from the Whittaker-Robinson technique to the Schuster periodogram and recent practices such as the modified Daniell window and the autoregressive and entropy spectra. We also reconsider models of the Markovian type of dependence and methods of analysis. The objective is to demonstrate useful practical procedures with the aid of relevant graphical displays. Results from periodograms not based on sinusoids are shown to complement the findings from more conventional methods. Periodicity in rainfall is less effective than in other related phenomena but has wide climatic variations. Preference for the familiar two-state first-order Markov model is reconfirmed with a two-harmonic representation of the seasonal variation in the Markov parameters. Rainfall data from Italy and Sri Lanka are used with observations of temperatures and flow for comparison.

  20. Rainfall Hazards Prevention based on a Local Model Forecasting System

    NASA Astrophysics Data System (ADS)

    Buendia, F.; Ojeda, B.; Buendia Moya, G.; Tarquis, A. M.; Andina, D.

    2009-04-01

    Rainfall is one of the most important events of human life and society. Some rainfall phenomena like floods or hailstone are a threat to the agriculture, business and even life. However in the meteorological observatories there are methods to detect and alarm about this kind of events, nowadays the prediction techniques based on synoptic measurements need to be improved to achieve medium term feasible forecasts. Any deviation in the measurements or in the model description makes the forecast to diverge in time from the real atmosphere evolution. In this paper the advances in a local rainfall forecasting system based on time series estimation with General Regression Neural Networks are presented. The system is introduced, explaining the measurements, methodology and the current state of the development. The aim of the work is to provide a complementary criteria to the current forecast systems, based on the daily atmosphere observation and tracking over a certain place.

  1. Rainfall Measurement with a Ground Based Dual Frequency Radar

    NASA Technical Reports Server (NTRS)

    Takahashi, Nobuhiro; Horie, Hiroaki; Meneghini, Robert

    1997-01-01

    Dual frequency methods are one of the most useful ways to estimate precise rainfall rates. However, there are some difficulties in applying this method to ground based radars because of the existence of a blind zone and possible error in the radar calibration. Because of these problems, supplemental observations such as rain gauges or satellite link estimates of path integrated attenuation (PIA) are needed. This study shows how to estimate rainfall rate with a ground based dual frequency radar with rain gauge and satellite link data. Applications of this method to stratiform rainfall is also shown. This method is compared with single wavelength method. Data were obtained from a dual frequency (10 GHz and 35 GHz) multiparameter radar radiometer built by the Communications Research Laboratory (CRL), Japan, and located at NASA/GSFC during the spring of 1997. Optical rain gauge (ORG) data and broadcasting satellite signal data near the radar t location were also utilized for the calculation.

  2. Integration and application of the Rainfall Runoff Library.

    PubMed

    Kim, S; Vertessy, R A; Perraud, J-M; Sung, Y

    2005-01-01

    The Rainfall Runoff Library (RRL) provides a convenient platform for implementing environment modelling components such as rainfall runoff models, calibration tools, and objective functions. A rainfall-runoff model widely known and used in South Korea, TANK, is added to the RRL, and used along with the models AWBM and SIMHYD to reproduce the historical time series of daily and monthly runoff at the Soyanggang Dam and Youngcheon Dam catchments located in South Korea. The features of the RRL allow for an easy comparison of different models in a standardised and common framework. Three optimisation methods (Genetic algorithm, Rosenbrock method and Shuffled Complex Evolution algorithm) were applied to calibrate the model parameters using three different objective functions. The applicability of each model to these catchments is discussed based on the resulting statistics. PMID:16445198

  3. Suppressed convective rainfall by agricultural expansion in southeastern Burkina Faso

    NASA Astrophysics Data System (ADS)

    Mande, Theophile; Ceperley, Natalie C.; Katul, Gabriel G.; Tyler, Scott W.; Yacouba, Hamma; Parlange, Marc B.

    2015-07-01

    With the "green economy" being promoted as a path to sustainable development and food security within the African continent, the influx of agricultural land is proliferating at a rapid pace often replacing natural savannah forests. Where agriculture is primarily rainfed, the possible adverse impacts of agricultural land influx on rainfall occurrences in water-limited areas such as West Africa warrant attention. Using field observations complemented by model calculations in southeastern Burkina Faso, the main causes of a 10-30% suppressed daytime rainfall recorded over agricultural fields when referenced to natural savannah forests are examined. Measurements and model runs reveal that the crossing of the mixed layer height and lifting condensation levels, a necessary condition for cloud formation and subsequent rainfall occurrence, was 30% more frequent above the natural savannah forest. This increase in crossing statistics was primarily explained by increases in measured sensible heat flux above the savannah forest rather than differences in lifting condensation heights.

  4. Assessment relative soil erodibility index by rainfall simulation experiment

    NASA Astrophysics Data System (ADS)

    Diaz, Jorge; Alonso, Gustavo; Leal, Zuzell; Ruiz, María. Elena; Almoza, Yeleine; Cornelis, Wim; Gabriels, Donald

    2010-05-01

    Soil erosion in agricultural fields is identified as the main source of sediments to the Cuyaguateje River, located in the western part of Cuba. The soil is highly variable across the whole watershed and an accurate estimate of soil erodibility is difficult to asses. A rainfall simulation experiment was carrying out in 16 different soils. Plots of 5 m long by 2 m wide with similar treatments and slope ranging from 5 to 15 % were selected. A constant rainfall intensity of 120 mm/h and 60 J/m2 h of kinetic energy, for 25 minutes was applied. Runoff and sediment concentration were measured every 2 minutes. Different behavior through the rainfall event was observed denoting differences in the mechanism driving the erosion process. The total soil lost during this event is reported as a relative index of soil erodibility. There is practically no correlation between this relative index and others soil erodibility index commonly applied in literature.

  5. Stochastic-Dynamical Modeling of Space Time Rainfall

    NASA Technical Reports Server (NTRS)

    Georgankakos, Konstantine P.

    1997-01-01

    The focus of this research work is the elucidation of the physical origins of the observed extreme-rainfall variability over tropical oceans. The quantitative results of this work may be used to establish links between deterministic models of the mesoscale and synoptic scale with statistical descriptions of the temporal variability of local tropical oceanic rainfall. In addition, they may be used to quantify the influence of measurement error in large-scale forcing and cloud scale observations on the accuracy of local rainfall variability inferences, important for hydrologic studies. A simple statistical-dynamical model, suitable for use in repetitive Monte Carlo experiments, is formulated as a diagnostic tool for this purpose. Stochastic processes with temporal structure and parameters estimated from observed large-scale data represent large-scale forcing.

  6. Abrupt changes in rainfall during the twentieth century

    NASA Astrophysics Data System (ADS)

    Narisma, Gemma T.; Foley, Jonathan A.; Licker, Rachel; Ramankutty, Navin

    2007-03-01

    Complex interactions in the climate system can give rise to strong positive feedback mechanisms that may lead to sudden climatic changes. The prolonged Sahel drought and the Dust Bowl are examples of 20th century abrupt climatic changes that had serious effects on ecosystems and societies. Here we analyze global historical rainfall observations to detect regions that have undergone large, sudden decreases in rainfall. Our results show that in the 20th century about 30 regions in the world have experienced such changes. These events are statistically significant at the 99% level, are persistent for at least ten years, and most have magnitudes of change that are 10% lower than the climatological normal (1901-2000 rainfall average). This analysis illustrates the extent and magnitude of abrupt climate changes across the globe during the 20th century and may be used for studying the dynamics of and the mechanisms behind these abrupt changes.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  8. Representing low-frequency variability in continuous rainfall simulations: A hierarchical random Bartlett Lewis continuous rainfall generation model

    NASA Astrophysics Data System (ADS)

    Wasko, Conrad; Pui, Alexander; Sharma, Ashish; Mehrotra, Rajeshwar; Jeremiah, Erwin

    2015-12-01

    Low-frequency variability, in the form of the El Niño-Southern Oscillation, plays a key role in shaping local weather systems. However, current continuous stochastic rainfall models do not account for this variability in their simulations. Here a modified Random Pulse Bartlett Lewis stochastic generation model is presented for continuous rainfall simulation exhibiting low-frequency variability. Termed the Hierarchical Random Bartlett Lewis Model (HRBLM), the model features a hierarchical structure to represent a range of rainfall characteristics associated with the El Niño-Southern Oscillation with parameters conditioned to vary as functions of relevant climatic states. Long observational records of near-continuous rainfall at various locations in Australia are used to formulate and evaluate the model. The results indicate clear benefits of using the hierarchical climate-dependent structure proposed. In addition to accurately representing the wet spells characteristics and observed low-frequency variability, the model replicates the interannual variability of the antecedent rainfall preceding the extremes, which is known to be of considerable importance in design flood estimation applications.

  9. Quantifying Global Uncertainties in a Simple Microwave Rainfall Algorithm

    NASA Technical Reports Server (NTRS)

    Kummerow, Christian; Berg, Wesley; Thomas-Stahle, Jody; Masunaga, Hirohiko

    2006-01-01

    While a large number of methods exist in the literature for retrieving rainfall from passive microwave brightness temperatures, little has been written about the quantitative assessment of the expected uncertainties in these rainfall products at various time and space scales. The latter is the result of two factors: sparse validation sites over most of the world's oceans, and algorithm sensitivities to rainfall regimes that cause inconsistencies against validation data collected at different locations. To make progress in this area, a simple probabilistic algorithm is developed. The algorithm uses an a priori database constructed from the Tropical Rainfall Measuring Mission (TRMM) radar data coupled with radiative transfer computations. Unlike efforts designed to improve rainfall products, this algorithm takes a step backward in order to focus on uncertainties. In addition to inversion uncertainties, the construction of the algorithm allows errors resulting from incorrect databases, incomplete databases, and time- and space-varying databases to be examined. These are quantified. Results show that the simple algorithm reduces errors introduced by imperfect knowledge of precipitation radar (PR) rain by a factor of 4 relative to an algorithm that is tuned to the PR rainfall. Database completeness does not introduce any additional uncertainty at the global scale, while climatologically distinct space/time domains add approximately 25% uncertainty that cannot be detected by a radiometer alone. Of this value, 20% is attributed to changes in cloud morphology and microphysics, while 5% is a result of changes in the rain/no-rain thresholds. All but 2%-3% of this variability can be accounted for by considering the implicit assumptions in the algorithm. Additional uncertainties introduced by the details of the algorithm formulation are not quantified in this study because of the need for independent measurements that are beyond the scope of this paper. A validation strategy

  10. Trend analysis for rainfall in Delhi and Mumbai, India

    NASA Astrophysics Data System (ADS)

    Rana, Arun; Uvo, Cintia Bertacchi; Bengtsson, Lars; Parth Sarthi, P.

    2012-01-01

    Urbanisation has burdened cities with many problems associated with growth and the physical environment. Some of the urban locations in India are becoming increasingly vulnerable to natural hazards related to precipitation and flooding. Thus it becomes increasingly important to study the characteristics of these events and their physical explanation. This work studies rainfall trends in Delhi and Mumbai, the two biggest Metropolitan cities of Republic of India, during the period from 1951 to 2004. Precipitation data was studied on basis of months, seasons and years, and the total period divided in the two different time periods of 1951-1980 and 1981-2004 for detailed analysis. Long-term trends in rainfall were determined by Man-Kendall rank statistics and linear regression. Further this study seeks for an explanation for precipitation trends during monsoon period by different global climate phenomena. Principal component analysis and Singular value decomposition were used to find relation between southwest monsoon precipitation and global climatic phenomena using climatic indices. Most of the rainfall at both the stations was found out to be taking place in Southwest monsoon season. The analysis revealed great degree of variability in precipitation at both stations. There is insignificant decrease in long term southwest monsoon rainfall over Delhi and slight significant decreasing trends for long term southwest monsoon rainfall in Mumbai. Decrease in average maximum rainfall in a day was also indicated by statistical analysis for both stations. Southwest monsoon precipitation in Delhi was found directly related to Scandinavian Pattern and East Atlantic/West Russia and inversely related to Pacific Decadal Oscillation, whereas precipitation in Mumbai was found inversely related to Indian ocean dipole, El Niño- Southern Oscillation and East Atlantic Pattern.

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

    PubMed

    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

  12. The rainfall regime in Lisbon in the last 150 years

    NASA Astrophysics Data System (ADS)

    Kutiel, H.; Trigo, R. M.

    2014-11-01

    The first decades of the rainfall series of Lisbon have been digitized recently allowing a long-term assessment of the rainfall regime for 150 years of uninterrupted, i.e., the first assessment for the longest continuous precipitation time series in western Iberia. This data has been monitored continuously at the D. Luís observatory having started to be published in 1864 in the Observatory's log books (Annals). We use an approach based on different characteristics of rain spells that has been proved to be satisfactory for the analysis of the different parameters related to the rainfall regime in that part of the world. Thus, a rain spell is defined as a series of consecutive days with a measured daily rainfall equal or higher than 1.0 mm. Each rain spell is preceded and followed by at least one dry day. For each rain spell, its duration, its yield (RSY), and its average intensity (RSI) was calculated. Additionally, the total number of rain spells in each year was also considered. Dryness was analyzed using the dry days since last rain approach. Besides the evaluation over the entire 150-year period available, we have also looked into three equally spaced sub-periods. Lisbon reveals large inter-annual and intra-annual variability and both have increased considerably in the last decades. The large intra-annual variability is demonstrated by both; a very large range of annual rainfall percentage accumulated at any given date and by a very large range of dates on which a certain rainfall percentage was accumulated. Again, both metrics increased in the last decades. Parallel to the increase in the uncertainty, a very significant net increase is noticed in the annual totals since the 1960s compared to the first half of the previous century. The increase is mainly due to more intense events which are reflected by higher RSY and RSI values in the last 50 years.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  14. Spatial and temporal variation of rainfall trends of Sri Lanka

    NASA Astrophysics Data System (ADS)

    Wickramagamage, P.

    2016-08-01

    This study was based on daily rainfall data of 48 stations distributed over the entire island covering a 30-year period from 1981 to 2010. Data analysis was done to identify the spatial pattern of rainfall trends. The methods employed in data analysis are linear regression and interpolation by Universal Kriging and Radial Basis function. The slope of linear regression curves of 48 stations was used in interpolation. The regression coefficients show spatially and seasonally variable positive and negative trends of annual and seasonal rainfall. About half of the mean annual pentad series show negative trends, while the rest shows positive trends. By contrast, the rainfall trends of the Southwest Monsoon (SWM) season are predominantly negative throughout the country. The first phase of the Northeast Monsoon (NEM1) displays downward trends everywhere, with the exception of the Southeastern coastal area. The strongest negative trends were found in the Northeast and in the Central Highlands. The second phase (NEM2) is mostly positive, except in the Northeast. The Inter-Monsoon (IM) periods have predominantly upward trends almost everywhere, but still the trends in some parts of the Highlands and Northeast are negative. The long-term data at Watawala Nuwara Eliya and Sandringham show a consistent decline in the rainfall over the last 100 years, particularly during the SWM. There seems to be a faster decline in the rainfall in the last 3 decades. These trends are consistent with the observations in India. It is generally accepted that there has been changes in the circulation pattern. Weakening of the SWM circulation parameters caused by global warming appears to be the main causes of recent changes. Effect of the Asian Brown Cloud may also play a role in these changes.

  15. Development of microwave rainfall retrieval algorithm for climate applications

    NASA Astrophysics Data System (ADS)

    KIM, J. H.; Shin, D. B.

    2014-12-01

    With the accumulated satellite datasets for decades, it is possible that satellite-based data could contribute to sustained climate applications. Level-3 products from microwave sensors for climate applications can be obtained from several algorithms. For examples, the Microwave Emission brightness Temperature Histogram (METH) algorithm produces level-3 rainfalls directly, whereas the Goddard profiling (GPROF) algorithm first generates instantaneous rainfalls and then temporal and spatial averaging process leads to level-3 products. The rainfall algorithm developed in this study follows a similar approach to averaging instantaneous rainfalls. However, the algorithm is designed to produce instantaneous rainfalls at an optimal resolution showing reduced non-linearity in brightness temperature (TB)-rain rate(R) relations. It is found that the resolution tends to effectively utilize emission channels whose footprints are relatively larger than those of scattering channels. This algorithm is mainly composed of a-priori databases (DBs) and a Bayesian inversion module. The DB contains massive pairs of simulated microwave TBs and rain rates, obtained by WRF (version 3.4) and RTTOV (version 11.1) simulations. To improve the accuracy and efficiency of retrieval process, data mining technique is additionally considered. The entire DB is classified into eight types based on Köppen climate classification criteria using reanalysis data. Among these sub-DBs, only one sub-DB which presents the most similar physical characteristics is selected by considering the thermodynamics of input data. When the Bayesian inversion is applied to the selected DB, instantaneous rain rate with 6 hours interval is retrieved. The retrieved monthly mean rainfalls are statistically compared with CMAP and GPCP, respectively.

  16. Estimating storm areal average rainfall intensity in field experiments

    NASA Astrophysics Data System (ADS)

    Peters-Lidard, Christa D.; Wood, Eric F.

    1994-07-01

    Estimates of areal mean precipitation intensity derived from rain gages are commonly used to assess the performance of rainfall radars and satellite rainfall retrieval algorithms. Areal mean precipitation time series collected during short-duration climate field studies are also used as inputs to water and energy balance models which simulate land-atmosphere interactions during the experiments. In two recent field experiments (1987 First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) and the Multisensor Airborne Campaign for Hydrology 1990 (MAC-HYDRO '90)) designed to investigate the climatic signatures of land-surface forcings and to test airborne sensors, rain gages were placed over the watersheds of interest. These gages provide the sole means for estimating storm precipitation over these areas, and the gage densities present during these experiments indicate that there is a large uncertainty in estimating areal mean precipitation intensity for single storm events. Using a theoretical model of time- and area-averaged space- time rainfall and a model rainfall generator, the error structure of areal mean precipitation intensity is studied for storms statistically similar to those observed in the FIFE and MAC-HYDRO field experiments. Comparisons of the error versus gage density trade-off curves to those calculated using the storm observations show that the rainfall simulator can provide good estimates of the expected measurement error given only the expected intensity, coefficient of variation, and rain cell diameter or correlation length scale, and that these errors can quickly become very large (in excess of 20%) for certain storms measured with a network whose size is below a "critical" gage density. Because the mean storm rainfall error is particularly sensitive to the correlation length, it is important that future field experiments include radar and/or dense rain gage networks capable of accurately characterizing the

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

    NASA Astrophysics Data System (ADS)

    Overeem, Aart; Uijlenhoet, Remko; Leijnse, Hidde

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Bergemann, Martin; Jakob, Christian

    2016-06-01

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

  19. Seasonal Variability of Rainfall Over Indonesia Maritime Continent Based on Trmm pr Observations

    NASA Astrophysics Data System (ADS)

    Yulihastin, Erma; Kodama, Yasu-Masa

    Temporal and spatial distribution of near surface rain and three types of rainfall namely shallow rain, convective rain, and stratiform rain over Indonesia Maritime Continent (90E-150E, 15S-15N) was investigated using Tropical Rainfall Measuring Mission Precipitation Radar in a 10-years dataset (1998-2007). This research also using least square method to confirm distribution of annual and semiannual oscillation of rainfall over Indonesia Maritime Continent (IMC). Climatology rainfall of shallow, stratiform, and convective have agreement to seasonal variability of rainfall over IMC that influenced by monsoon which was rainfall became increased from November to April and reached peak value in January. Conversely, rainfall decreased from May to October and reached lowest value in July. The distribution of shallow rain showed the unique seasonal rainfall for local region namely Sulawesi, Maluku, and closely region. Seasonal of shallow rain in those regions approve to local type of rainfall which was reach peak value in July and August. This rainfall type was opposite to equator rainfall and monsoon rainfall in the most of IMC regions which are dry season occured in the same period. Shallow rain may contributed to local rainfall type over IMC. It might be drived by increasing low level moisture and strongly of subsidence flow in boundary layer which is also influenced by enhancement of Sea Surface Temperature in Malacca Strait at the same period. Keyword: Indonesia Maritime Continent, Tropical Rainfall Measuring Mission, Seasonal Vari-ability

  20. Understanding extreme rainfall events in Australia through historical data

    NASA Astrophysics Data System (ADS)

    Ashcroft, Linden; Karoly, David John

    2016-04-01

    Historical climate data recovery is still an emerging field in the Australian region. The majority of Australia's instrumental climate analyses begin in 1900 for rainfall and 1910 for temperature, particularly those focussed on extreme event analysis. This data sparsity for the past in turn limits our understanding of long-term climate variability, constraining efforts to predict the impact of future climate change. To address this need for improved historical data in Australia, a new network of recovered climate observations has recently been developed, centred on the highly populated southeastern Australian region (Ashcroft et al., 2014a, 2014b). The dataset includes observations from more than 39 published and unpublished sources and extends from British settlement in 1788 to the formation of the Australian Bureau of Meteorology in 1908. Many of these historical sources provide daily temperature and rainfall information, providing an opportunity to improve understanding of the multidecadal variability of Australia's extreme events. In this study we combine the historical data for three major Australian cities - Melbourne, Sydney and Adelaide - with modern observations to examine extreme rainfall variability over the past 174 years (1839-2013). We first explore two case studies, combining instrumental and documentary evidence to support the occurrence of severe storms in Sydney in 1841 and 1844. These events appear to be at least as extreme as Sydney's modern 24-hour rainfall record. Next we use a suite of rainfall indices to assess the long-term variability of rainfall in southeastern Australia. In particular, we focus on the stationarity of the teleconnection between the El Niño-Southern Oscillation (ENSO) phenomenon and extreme rainfall events. Using ENSO reconstructions derived from both palaeoclimatic and documentary sources, we determine the historical relationship between extreme rainfall in southeastern Australia and ENSO, and examine whether or not this

  1. Detecting Trends in Tropical Rainfall Characteristics, 1979-2003

    NASA Technical Reports Server (NTRS)

    Lau, K. M.; Wu, H. T.

    2006-01-01

    From analyses of blended space-based and ground-based global rainfall data, we found increasing trends in the occurrence of extreme heavy and light rain events, coupled to a decreasing trend in moderate rain events in the tropics during 1979-2003. The trends are consistent with a shift in the large-scale circulation associated with a) a relatively uniform increase in warm rain over the tropical oceans, b) enhanced ice-phase rain over the near-equatorial oceans, and c) reduced mixed-phase rain over the tropical ocean and land regions. Due to the large compensation among different rain categories, the total tropical rainfall trend remained undetectable.

  2. The multi-parameter remote measurement of rainfall

    NASA Technical Reports Server (NTRS)

    Atlas, D.; Ulbrich, C. W.; Meneghini, R.

    1982-01-01

    The measurement of rainfall by remote sensors is investigated. One parameter radar rainfall measurement is limited because both reflectivity and rain rate are dependent on at least two parameters of the drop size distribution (DSD), i.e., representative raindrop size and number concentration. A generalized rain parameter diagram is developed which includes a third distribution parameter, the breadth of the DSD, to better specify rain rate and all possible remote variables. Simulations show the improvement in accuracy attainable through the use of combinations of two and three remote measurables. The spectrum of remote measurables is reviewed. These include path integrated techniques of radiometry and of microwave and optical attenuation.

  3. Effects of local circulations on rainfall distributions during TAMEX

    NASA Astrophysics Data System (ADS)

    Yeh, Hsi-Chyi

    1999-11-01

    The orographic effects on the mesoscale flow and rainfall distributions over Taiwan are analyzed based on TAMEX (Taiwan Area Mesoscale Experiment) data and numerical experiments using MM5 (Pennsylvania State University (PSU)/NCAR mesoscale model version 5). The rainfall maxima during TAMEX occurred on the windward slopes of the mountains under the prevailing southwesterly monsoon flow. About fifty percent of the rainfalls there was observed during non-frontal periods as orographic rain showers. In the northwestern coastal region of Taiwan, the total rains were more pronounced than other windward coastal regions. More than eighty percent of the rains occurred during the passage of frontal systems. From a case study during TAMEX IOP 3, moderate rainfalls (~40 mm/6hr) were observed along the northwestern coast of Taiwan associated with the arrival of three successive rainbands, during 1000-1600 LST. This event occurred within the prevailing southwesterly monsoon flow regime ahead of the 850-hPa trough. These rainbands formed within the Taiwan Strait. The intensification of the rainband occurred off the northwestern coast of Taiwan where the deflected southerly flow converged with the prevailing southwesterlies modified by the storm- induced westerlies. From the numerical experiments, when uniform southwesterlies are specified to impinge on the island topography in the absence of synoptic-scale forcing, the MM5 simulates the orographically induced low-level strong winds. However, the offshore convergence zone and the significant rainfall along the northwestern coast are not simulated. For the experiment with synoptic-scale forcing but without the island topography over Taiwan, a large- scale cloud band is simulated within the Taiwan Strait without the localized rainfall maximum along the northwestern coast. The coastal rainfall maximum is simulated, only when the influences of the synoptic-scale forcing and the orographic effects are included. These results indicate

  4. Areal rainfall construction and estimation of extreme quantiles.

    NASA Astrophysics Data System (ADS)

    Penot, David; Paquet, Emmanuel; Lang, Michel

    2014-05-01

    Areal rainfall estimation and extrapolation to extremes is a key issue for catchment flood study. It is a tricky problem which deals with spatial interpolation (to build an estimate at the catchment's scale based on few rain gauges only), and probabilistic extrapolation (for extreme values estimation). In this study, several methods to build an areal rainfall estimation are compared. The first method is the commonly used Thiessen polygons. A second way to build an areal rainfall relies on the SPAZM method [Gottardi, 2012], in which daily rain fields are reconstructed at a 1km2 resolution, with an interpolation scheme integrating the altitude of the pixel and the weather type of the day. These two methods are compared to the stochastic rain field simulator SAMPO [Leblois et Creutin, 2013], which is an adaptation of the turning band method allowing to generate over 50 years of realistic rain fields. Several questions are tackled in this study: In a Thiessen estimation, how many rain gauges should be selected ? Which weighting scheme should be used ? SPAZM is an interpolator designed to produce unbiased mean annual precipitation (MAP) at a catchment's scale. So if a Thiessen areal rainfall is scaled to fit the MAP given by SPAZM, how does it affect its extreme rainfall estimation ? If a virtual rain gauges network is extracted from the rain fields generated by SAMPO, how do behave the Thiessen and SPAZM areal rainfall estimations based on these point values ? At the end, some abatement functions are obtained, showing the influence of the catchment's area and the options chosen to build the areal rainfall estimations. References: F. Gottardi, C. Obled, J. Gailhard, and E. Paquet, Statistical reanalysis of precipitation fields based on ground network data and weather patterns : Application over french mountains. Journal of Hydrology, 432-433:154 - 167, 2012. ISSN 0022-1694. E. Leblois and J-D. Creutin, Space-time simulation of intermittent rainfall with prescribed

  5. TRMM Applications for Rainfall-Induced Landslide Early Warning

    NASA Astrophysics Data System (ADS)

    Dok, A.; Fukuoka, H.; Hong, Y.

    2012-04-01

    Early warning system (EWS) is the most effective method in saving lives and reducing property damages resulted from the catastrophic landslides if properly implemented in populated areas of landslide-prone nations. For predicting the occurrence of landslides, it requires examination of empirical relationship between rainfall characteristics and past landslide occurrence. In developed countries like Japan and the US, precipitation is monitored by rain radars and ground-based rain gauge matrix. However, in developing regions like Southeast Asian countries, very limited number of rain gauges is available, and there is no implemented methodology for issuing effective warming of landslides yet. Correspondingly, satellite precipitation monitoring could be therefore a possible and promising solution for launching landslide quasi-real-time early warning system in those countries. It is due to the fact that TMPA (TRMM Multi-satellite Precipitation Analysis) can provides a globally calibration-based sequential scheme for combining precipitation estimates from multiple satellites, and gauge analyses where feasible, at fine scales (3-hourly with 0.25°x0.25° spatial resolution). It is available both after and in quasi-real time, calibrated by TRMM Combined Instrument and TRMM Microwave Imager precipitation product. However, validation of ground based rain gauge and TRMM satellite data in the vulnerable regions is still not yet operative. Snake-line/Critical-line and Soil Water Index (SWI) are used for issuing warning of landslide occurrence in Japan; whereas, Caine criterion is preferable in Europe and western nations. Herewith, it presents rainfall behavior which took place in Beichuan city (located on the 2008 Chinese Wenchuan earthquake fault), Hofu and Shobara cities in Japan where localized heavy rainfall attacked in 2009 and 2010, respectively, from TRMM 3B42RT correlated with ground based rain gauge data. The 1-day rainfall intensity and 15-day cumulative rainfall

  6. Utilization of regression models for rainfall estimates using radar-derived rainfall data and rain gauge data

    NASA Astrophysics Data System (ADS)

    Sokol, Zbynĕk

    2003-07-01

    The procedure estimating hourly rainfalls by merging radar-derived rainfalls and gauge measurements is developed and tested. It uses simple linear regression, which is complemented by the normalization and correction of distribution. The data from radar Tulsa, Oklahoma, Weather Surveillance Radar-1988 Doppler version and rain gauge data from the radar domain are used. The quality of estimates is evaluated against independent rain gauges by the root-mean-square-error, bias and correlation coefficient in dependence on the density of a gauge network. The results indicate that even a sparse gauge network (about 50 gauges, i.e. 4000 km 2 per one gauge) is sufficient to improve the radar-derived rainfalls. The improvement increases with the number of gauges.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    Drier parts of Kenya's Central Highlands endure persistent crop failure and declining agricultural productivity. These have, in part, attributed to high temperatures, prolonged dry spells and erratic rainfall. Understanding spatial-temporal variability of climatic indices such as rainfall at seasonal level is critical for optimal rain-fed agricultural productivity and natural resource management in the study area. However, the predominant setbacks in analysing hydro-meteorological events are occasioned by either lack, inadequate, or inconsistent meteorological data. Like in most other places, the sole sources of climatic data in the study region are scarce and only limited to single stations, yet with persistent missing/unrecorded data making their utilization a challenge. This study examined seasonal anomalies and variability in rainfall, drought occurrence and the efficacy of interpolation techniques in the drier regions of eastern Kenyan. Rainfall data from five stations (Machang'a, Kiritiri, Kiambere and Kindaruma and Embu) were sourced from both the Kenya Meteorology Department and on-site primary recording. Owing to some experimental work ongoing, automated recording for primary dailies in Machang'a have been ongoing since the year 2000 to date; thus, Machang'a was treated as reference (for period of record) station for selection of other stations in the region. The other stations had data sets of over 15 years with missing data of less than 10 % as required by the world meteorological organization whose quality check is subject to the Centre for Climate Systems Modeling (C2SM) through MeteoSwiss and EMPA bodies. The dailies were also subjected to homogeneity testing to evaluate whether they came from the same population. Rainfall anomaly index, coefficients of variance and probability were utilized in the analyses of rainfall variability. Spline, kriging and inverse distance weighting interpolation techniques were assessed using daily rainfall data and

  8. Runoff-rainfall (sic!) modelling: Comparing two different approaches

    NASA Astrophysics Data System (ADS)

    Herrnegger, Mathew; Schulz, Karsten

    2015-04-01

    Rainfall is an important input variable for many applications. However, the estimation of areal rainfall is afflicted with significant uncertainties, since it exhibits a large spatio-temporal variability, especially in Alpine areas. Additionally the density of the monitoring network is frequently low and measurements are subject to major errors. The most reliable hydrological information that is available refers to runoff. Kirchner (2009) presented a method to infer catchment rainfall from streamflow fluctuations. The approach is however limited to catchments, where discharge is determined by the volume of water in storage and which can be characterized as simple first-order nonlinear dynamical systems. The model has recently been applied to several catchments in France and Luxembourg (Adamovic et. al., 2014; Krier et al., 2012). In Herrnegger et al. (2014) a different technique to calculate mean areal rainfall on the basis of an inverse conceptual rainfall-runoff model and runoff observations was presented. Thereby a conceptual model is embedded in an iteration algorithm, in which for every time step a rainfall value is determined, which results in a simulated runoff value that corresponds to the observation. The two modelling approaches differ substantially, not only concerning the model concepts, but especially in the number of model parameters. The Kirchner (2009) model (when deriving the storage-discharge relationship directly from runoff data) only has a single parameter. In contrast, the Herrnegger et al. (2014) model uses 10 parameters that have to be calibrated initially, but will offer more degrees of freedom and flexibility in describing more complex catchment responses. In this contribution, we present the application and comparison of both models in the Krems catchment (38.4 km²) located at the foothills of the Northern Austrian Alps. Apart from comparing the performance of the runoff simulations, the focus of this paper lies in evaluating the inverse

  9. A rainfall intensity-duration threshold for landslides in a humid- tropical environment, Puerto Rico

    USGS Publications Warehouse

    Larsen, M.C.; Simon, A.

    1993-01-01

    The leading cause of landslides in Puerto Rico is intense and/or prolonged rainfall. A rainfall threshold for rainfall-triggered landsliding is delimited by 256 storms that occurred between 1959 and 1991 in the central mountains of Puerto Rico, where mean annual rainfall is close to or in excess of 2000mm. Forty-one of the 256 storms produced intense and/or prolonged rainfall that resulted in tens to hundreds of landslides. As storm durations approach 100 h, the rainfall conditions necessary to initiate landsliding in Puerto Rico converge with those defined for temperate regions. -from Authors

  10. Trends in rainfall and temperature extremes in Morocco

    NASA Astrophysics Data System (ADS)

    Khomsi, K.; Mahe, G.; Tramblay, Y.; Sinan, M.; Snoussi, M.

    2015-02-01

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

  11. Rainfall interception and partitioning by pinus monophylla and juniperus osteosperma

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study investigated canopy interception of simulated rainfall by singleleaf piñon (Pinus monophylla) and Utah juniper (Juniperus osteosperma) in central Nevada. Research has shown that although piñon and juniper occurred historically throughout the western United States, the infilling of woodlan...

  12. Regional variability of extreme rainfall events in Romania

    NASA Astrophysics Data System (ADS)

    Breza, Traian; Cheval, Sorin; Baciu, Madalina; Dumitrescu, Alexandru; Antonescu, Bogdan; Burcea, Sorin

    2010-05-01

    Extreme rainfall events triggering flash floods occur quite often over the territory of Romania, leaving behind significant damages and casualties. This research is a contribution to the FP6 Project HYDRATE (Hydrometeorological data resources and technologies for effective flash flood forecasting). It aims at investigating the spatial patterns of the extreme rainfall events in Romania, based on the characteristics of their intensity-duration-frequency (IDF). The study uses the peak-over-threshold concept, which basically consists of analyzing all precipitation amounts above certain thresholds selected for different durations. The data come from 60 weather stations. They cover the warm interval (generally, April-October, but less extended for mountain stations), and at least 30 years-datasets have been used. The regional differences were retrieved from the IDF curves and they were also approached by GIS-based mapping the intensities corresponding to sub-daily durations (5 - 180 min.) and to different return periods (10,50, 100 years). The results highlight significant regional variations, that improve the understanding of the impact of the extreme rainfall events and the consequent flash floods on the natural and social environment. At the same time, overlapping the extreme rainfall data and land cover information, we have empahsized the hazard potential of the precipitation events.

  13. Non-stationarity in intermittent rainfall: the 'dry drift'

    NASA Astrophysics Data System (ADS)

    Schleiss, M.; Berne, A.

    2013-12-01

    The non-stationary nature of intermittent rainfall is investigated. It manifests itself in the fact that the average rain rate changes with the distance to the closest dry area. This fundamental link between the average rainfall intensity and the rainfall occurrence process is called the 'dry drift'. The present contribution aims to analyze and model this dry drift using observations from disdrometers and weather radar. The results show that dry drifts are very general features of precipitation that extend between 5-10 kilometers in space and 15-30 minutes in time. More importantly, dry drifts also affect the drop size distribution (DSD). Indeed, both the average drop concentration Nt [m-3] and the average drop size Dm [mm] significantly decrease when approaching a dry region/period. Most of the time, however, the dry drift in Nt is much stronger than the dry drift in Dm. This has some important consequences in remote sensing and means, in particular, that the prefactor and the exponent of the Z-R relationship can change when approaching the border of a rain cell. Because dry drifts are an important source of non-stationarity, it is also important to take them into account when disaggregating large scale rainfall fields for hydrological applications. The authors provide some examples of this problem and discuss possible ways of addressing it.

  14. TRMM-related research: Tropical rainfall and energy analysis experiment

    NASA Technical Reports Server (NTRS)

    Suomi, Verner E.; Ackerman, S.; Hinton, B.; Martin, D.

    1994-01-01

    The overall science objective of the participation in TRMM is the determination of daily rainfall and latent heating in the tropical atmosphere using TRMM and complementary spacecraft observations. The major focus these first three years has been to extend, in space and time, the TRMM satellite observations of rainfall. Observations from TRMM active and passive microwave radiometers will provide the fundamental observations for understanding the hydrological cycle of the tropics. Due to the orbit of the TRMM satellite and the extreme variability of convective rain systems, the TRMM observations provide rainfall estimates representative of a one month period. Monthly mean rainfall rates provide valuable information; however, this time scale limitation neglects the great value of the data towards a better understanding of the physics of tropical convection. Many tropical periodicities will not be characterized by these monthly averages, e.g. diurnal cycles, the 4-6 day easterly waves, and the 30 to 60 day cycle. In the spatial domain, due to its orbit, the TRMM satellite will over-fly many convective systems only once. Indeed, some precipitating systems will not be sampled at all. Observations from geostationary satellites can be used to extend the TRMM observations to smaller time and space scales. Although geostationary satellites cannot probe the interiors of precipitating systems, they do observe their life cycles. To acquire information on cloud water content and rain rate, it is proposed to combine geostationary and other satellite observations with the TRMM satellite measurements.

  15. How constant are pesticide Kd values during a rainfall event?

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Pesticide partitioning between water and sediment (Kd) and surface processes controlling runoff and sediment production determine the magnitude of pesticide losses associated with infiltration, runoff and/or sediment from agricultural fields during a rainfall event. Pesticide Kd values have traditio...

  16. Propagation of radar rainfall uncertainty in urban flood simulations

    NASA Astrophysics Data System (ADS)

    Liguori, Sara; Rico-Ramirez, Miguel

    2013-04-01

    This work discusses the results of the implementation of a novel probabilistic system designed to improve ensemble sewer flow predictions for the drainage network of a small urban area in the North of England. The probabilistic system has been developed to model the uncertainty associated to radar rainfall estimates and propagate it through radar-based ensemble sewer flow predictions. The assessment of this system aims at outlining the benefits of addressing the uncertainty associated to radar rainfall estimates in a probabilistic framework, to be potentially implemented in the real-time management of the sewer network in the study area. Radar rainfall estimates are affected by uncertainty due to various factors [1-3] and quality control and correction techniques have been developed in order to improve their accuracy. However, the hydrological use of radar rainfall estimates and forecasts remains challenging. A significant effort has been devoted by the international research community to the assessment of the uncertainty propagation through probabilistic hydro-meteorological forecast systems [4-5], and various approaches have been implemented for the purpose of characterizing the uncertainty in radar rainfall estimates and forecasts [6-11]. A radar-based ensemble stochastic approach, similar to the one implemented for use in the Southern-Alps by the REAL system [6], has been developed for the purpose of this work. An ensemble generator has been calibrated on the basis of the spatial-temporal characteristics of the residual error in radar estimates assessed with reference to rainfall records from around 200 rain gauges available for the year 2007, previously post-processed and corrected by the UK Met Office [12-13]. Each ensemble member is determined by summing a perturbation field to the unperturbed radar rainfall field. The perturbations are generated by imposing the radar error spatial and temporal correlation structure to purely stochastic fields. A

  17. MINERAL CHARACTERIZATION OF TEMPERATE GRASSES FROM A HIGH RAINFALL ENVIRONMENT

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Straw produced as a co-product of perennial ryegrass (Lolium perenne L.), orchardgrass (Dactylis glomerata L.), tall fescue [Schedonorus phoenix (Scop.) Holub] (formerly Festuca arundinacea Schreb.), and Kentucky bluegrass (Poa pratensis L.) seed production in the high rainfall area of western Orego...

  18. Extreme event statistics of daily rainfall: dynamical systems approach

    NASA Astrophysics Data System (ADS)

    Cigdem Yalcin, G.; Rabassa, Pau; Beck, Christian

    2016-04-01

    We analyse the probability densities of daily rainfall amounts at a variety of locations on Earth. The observed distributions of the amount of rainfall fit well to a q-exponential distribution with exponent q close to q≈ 1.3. We discuss possible reasons for the emergence of this power law. In contrast, the waiting time distribution between rainy days is observed to follow a near-exponential distribution. A careful investigation shows that a q-exponential with q≈ 1.05 yields the best fit of the data. A Poisson process where the rate fluctuates slightly in a superstatistical way is discussed as a possible model for this. We discuss the extreme value statistics for extreme daily rainfall, which can potentially lead to flooding. This is described by Fréchet distributions as the corresponding distributions of the amount of daily rainfall decay with a power law. Looking at extreme event statistics of waiting times between rainy days (leading to droughts for very long dry periods) we obtain from the observed near-exponential decay of waiting times extreme event statistics close to Gumbel distributions. We discuss superstatistical dynamical systems as simple models in this context.

  19. A protocol for conducting rainfall simulation to study soil runoff

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Rainfall is a driving force for the transport of environmental contaminants from agricultural soils to surficial water bodies via surface runoff. The objective of this study was to characterize the effects of antecedent soil moisture content on the fate and transport of surface applied commercial ur...

  20. Behavior analysis by model slope experiment of artificial rainfall

    NASA Astrophysics Data System (ADS)

    Park, Min Cheol

    2016-03-01

    In this study, we performed a model slope experiment with rainfall seepage, and the results were compared and verified with the unsaturated slope stability analysis method. In the model slope experiment, we measured the changes in water content and matric suction due to rainfall seepage, and determined the time at which the slope failure occurred and the shape of the failure. In addition, we compared and verified the changes in the factor of safety and the shape of the failure surface, which was calculated from the unsaturated slope stability analysis with the model experiment. From the results of experiment and analysis, it is concluded that the unsaturated slope stability analysis can be used to accurately analyze and predict rainfall-induced slope failure. It is also concluded that in seepage analysis, setting the initial conditions and boundary conditions is very important. If engineers will use the measured porewater pressure or matric suction, the accuracy of analysis can be enhanced. The real-time monitoring system of porewater pressure or matric suction can be used as a warning of rainfall-induced slope failure.

  1. Earth Sensor Assembly for the Tropical Rainfall Measuring Mission Observatory

    NASA Technical Reports Server (NTRS)

    Prince, Steven S.; Hoover, James M.

    1995-01-01

    EDO Corporation/Barnes Engineering Division (BED) has provided the Tropical Rainfall Measurement Mission (TRMM) Earth Sensor Assembly (ESA), a key element in the TRMM spacecraft's attitude control system. This report documents the history, design, fabrication, assembly, and test of the ESA.

  2. GPM Observatory Looks at Tropical Storm Bill's Rainfall

    NASA Video Gallery

    This visualization of data from NASA/JAXA's GPM satellite shows rainfall over Texas as Tropical Storm Bill further drenched the state with rain on June 17, 2015 at 6:11 UTC (2:11 a.m. EDT). Shades ...

  3. GPM Flyby of Tropical Cyclone Ula's Eye and Rainfall

    NASA Video Gallery

    NASA Sees Tropical Cyclone Ula's Eye and Rainfall On Dec. 29, NASA's GPM saw rain was falling at a rate of over 83.6 mm (3.29 inches) per in a feeder band (of thunderstorms) northeast of the develo...

  4. NASA's GPM Satellite Analyzes Tropical Storm Erika's Rainfall

    NASA Video Gallery

    GPM showed thunderstorm cloud tops reaching to just over 14 km (8.6 miles) high and PM showed rainfall of up to 52.8 mm (2.0 inches) per hour. The GPM data was overlaid on infrared data from the GO...

  5. Mineral accumulation by perennial grasses in a high rainfall environment

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Straw produced as a co-product of perennial ryegrass (Lolium perenne L.), orchardgrass (Dactylis glomerata), tall fescue (Schedonorus phoenix (Scop.) Holub), and Kentucky bluegrass (Poa pratensis L.) seed production in the high rainfall area of western Oregon as well as clippings from urban and recr...

  6. Homology Groups of High-Resolution Temporal Rainfall

    NASA Astrophysics Data System (ADS)

    Fernández, Félix; Vásquez Aguilar, Raciel; Carsteanu, Alin-Andrei

    2016-04-01

    This study applies topological data analysis, by generating homology groups to uncover patterns in the data of high-resolution temporal rainfall intensities from Iowa City (IIHR, U of Iowa). The state-space representation of the data is being investigated for an appropiate embedding dimension, in order to subsequently study topological properties of resulting manifold.

  7. VARIETY, CLASSIFICATION AND ASSOCIATION IN RAINFALL-RUNOFF RESPONSE

    EPA Science Inventory

    A study of over 11,000 event rainfall and associated direct runoff vents from 100 small watersheds was done, in a search for distinct patterns of runoff response and/or association with land type. roupings of similar response type and magnitude were made, and the associations wit...

  8. A spatial-temporal rainfall generator for urban drainage design.

    PubMed

    McRobie, Fiona H; Wang, Li-Pen; Onof, Christian; Kenney, Stephen

    2013-01-01

    The work presented here is a contribution to the Thames Water project of improving the Counters Creek catchment sewerage system in London. An increase in the number of floods affecting basements in the area has indicated the need for improvements to the system. The cost of such improvements could be very high, and as such it is important to determine whether the traditional approach of applying 30-year spatially uniform design storms results in substantial overestimation. The first step in this is to generate simulations of spatially distributed rainfall events, from which 30-year storms can be extracted. Storms are modelled as clusters of Gaussian rainfall cells, extending the earlier Willems method to radar rainfall data. The parameters describing the cells and their motion are sampled from probability distributions derived from parameter estimates gained from 45 historical storm events within the catchment for the period 2000-2011. This spatial-temporal stochastic rainfall generator produces a two-dimensional time series of simulated storm events, from which events of given return period can be identified. PMID:23823561

  9. Rainfall and Deposition of Strontium-90 in Clallam County, Washington.

    PubMed

    Hardy, E; Alexander, L T

    1962-06-01

    A linear relationship between cumulative strontium-90 deposition and rainfall has been observed from measurements made at five sites on the Olympic Peninsula. When an estimated contribution from dry deposition is subtracted from the measured total, the strontium-90 concentration in precipitation is seen to be independent of the amount of precipitation. PMID:17754183

  10. Biologically-Effective Rainfall Pulses in Mediterranean and Monsoonal Regions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In semiarid regions rainfall pulses provide intermittent opportunities for biological activity. These pulses have been shown to affect the activity of microbes and plant differently, altering the net ecosystem exchange of carbon dioxide (NEE) from these ecosystems. We examine NEE and its components ...

  11. Persistence Diagrams of High-Resolution Temporal Rainfall

    NASA Astrophysics Data System (ADS)

    Fernández Méndez, F.; Carsteanu, A. A.

    2015-12-01

    This study applies Topological Data Analysis (TDA), by generating persistence diagrams to uncover patterns in the data of high-resolution temporal rainfall intensities from Iowa City (IIHR, U of Iowa). Persistence diagrams are a way to identify essential cycles in state-space representations of the data.

  12. Exploring social sensing techniques for measuring rainfall and flood response in urban environments

    NASA Astrophysics Data System (ADS)

    Koole, Wouter; Sips, Robert-Jan; ten Veldhuis, Marie-claire

    2016-04-01

    Extreme rainfall is expected to occur more often in the future as a result of climate change. To be able to react to this, urban water managers need to accurately know vulnerable spots in the city, as well as the potential impact to society. Currently, detailed information about rainfall intensities in cities, and effects of intense storm events on urban societies is lacking. In this study, we will present first results of social sensing experiments to measure rainfall and flooding using a smartphone app. Users of the app are asked to submit rainfall reports by selecting an rainfall class from a pre-defined list of (6) classes, to register time and location and to make a photo of the rainfall. Rainfall photos will be used in a future experiment for automated retrieval of rainfall classes using computer vision techniques. With the experiments we aim to validate rainfall observations made by lay people and to evaluate factors that influence the willingness of users to contribute observations. The results show that users consistently distinguish heavy and extreme rainfall from drizzle and mild rainfall, but have difficulty in making more detailed distinctions. The main factor driving willingness to contribute to the social rainfall sensing experiments is the perceived usefulness of rainfall reporting.

  13. Interannual and Decadal Variability of Summer Rainfall over South America

    NASA Technical Reports Server (NTRS)

    Zhou, Jiayu; Lau, K.-M.

    1999-01-01

    Using the CPC (Climate Prediction Center) Merged Analysis of Precipitation product along with the Goddard Earth Observing System reanalysis and the Climate Analysis Center sea surface temperature (SST) data, we conduct a diagnostic study of the interannual and decadal scale variability of summer rainfall over South America. Results show three leading modes of rainfall variation identified with interannual, decadal, and long-term trend variability. Together, these modes explain more than half the total variance. The first mode is highly correlated with El Nino/southern oscillation (ENSO), showing severe drought over Northeast Brazil and copious rainfall over the Ecuador coast and the area of Uruguay-Southern Brazil in El Nino years. This pattern is attributed to the large scale zonal shift of the Walker circulation and local Hadley cell anomaly induced by positive (negative) SST anomaly over the eastern (western) equatorial Pacific. In El Nino years, two convective belts indicated by upper tropospheric velocity potential trough and mid-tropospheric rising motion, which are somewhat symmetric about the equator, extend toward the northeast and the southeast into the tropical North and South Atlantic respectively. Sandwiched between the ascent is a region of descending motion over Northeast Brazil. The southern branch of the anomalous Hadley cell is dynamically linked to the increase of rainfall over Uruguay-Southern Brazil. The regional response of anomalous circulation shows a stronger South American summer monsoon and an enhanced (weakened) subtropical high over the South Atlantic (South Pacific) Ocean. The decadal variation displays a meridional shift of the Intertropical Convergence Zone (ITCZ), which is tie to the anomalous cross-equatorial SST gradient over the Atlantic and the eastern Pacific. In conjunction with this mode is a large scale mass swing between the polar regions and midlatitudes in both hemispheres. Over the South Atlantic and the South Pacific

  14. An experiment of rainfall infiltration under different boundary conditions

    NASA Astrophysics Data System (ADS)

    Hao, Shuang; Tong, Fuguo; Xue, Song

    2016-04-01

    Rainfall infiltration is a two-phase flow of water and gas, which should be simulated through solving the nonlinear governing equations of gas and water flow. In order to avoid the three main problems, such as convergence, numerical stability and computational efficiency in the solution of the nonlinear governing equations, Richard equation was usually used to simulate rainfall infiltration when the effect of gas phase could be ignored. The purpose of this work is to study the effect of boundary condition on rainfall infiltration, and to know in which cases Richard equation is available for the simulation of rainfall infiltration. The sample of soil has a height of 1200 mm. It is tightly enclosed in a toughened glass sleeve. The gas pressure is equal to the atmospheric pressure on the top surface of the model. The gas tight of its bottom can be controlled by a tap to simulate two different gas boundary conditions, permeable boundary and impermeable boundary. When the bottom of the model is not gas tight, the water infiltration rate is entirely bigger than gas tight. There is a big difference over the long time of rainfall that infiltration rate tends to be stable to 0.05cm/min when permeable but it is only 0.002cm/min when impermeable. The dramatic contrast reflects that gas paly a hindered part during rainfall infiltration. In addition, the gas pressure is obviously lower when the model is not gas tight. Although the pore gas pressure rise a little bit when water block gas, it is still same with atmospheric pressure all time. The situation is different when gas tight, the pore gas pressure increases sharply in the early stage and stable to a higher value, such as 10cm gas pressure on 67cm depth. Therefore, people basically negate the correlation between gas pressure and rainfall infiltration rate, but the evidence points out that the effect of gas pressure is in a significant position and Richard equations are not accurate under gas impermeable condition.

  15. WRF Performance Skills in Predicting Rainfall Over the Philippines

    NASA Astrophysics Data System (ADS)

    Perez, G. J. P.; Combinido, J. S.

    2014-12-01

    The Weather Research and Forecasting (WRF) model has been used for predicting rainfall over the Philippines. The period of October 2013 to May 2014 is chosen for the evaluation because of the unprecedented number of new ground instruments (300 to 500 automated rain gauges). It also gives us a good statistical representation of wet and dry seasons in the country. The WRF model configuration makes use of NCEP FNL for the initial boundary condition. Hindcasts are produced at 12-km resolution with 12 hours up to 144 hours lead-time. To assess the predictability of rainfall, we look at the dichotomous case, wherein we evaluate if the model is able to predict correctly the number of rainfall events. The left column in Figure 1 shows the monthly Percent Correct and Critical Success Index (CSI) for different lead-time. Percent Correct represents how well the model performs, 1 being the highest score, with equal bearing on correct positives and correct negatives. On the other hand, CSI is a balanced score that accounts for false alarm and missed events - it has a range of 0 to 1, where 1 means perfect forecast. Results show that during the wet season (October, November and December), PC is approximately 0.7 while in dry season (January, February and March), PC reaches values of around 0.9, which suggests improvement in the performance from wet to dry season. The increase in performance is attributed to the increase in number of correct negatives during the dry season. The CSI score, which excludes the correct negatives, shows that the ability of WRF to predict rainfall events drastically decline in December or during the transition from wet to dry season. This is due to the inability of WRF to pinpoint exact locations of small convective rainfall events. The predictability of actual rainfall values is indicated by the Mean Absolute Errors (MAE) and Root Mean Square Errors (RMSE) in Figure 1. The MAE for 3-hour accumulated rainfall is smallest during the dry season.

  16. Rainfall variability effects on aggregate crop model predictions

    NASA Astrophysics Data System (ADS)

    Dzotsi, Kofikuma Adzewoda

    Crop production operates in a highly heterogeneous environment. Space-time variability in weather and spatial heterogeneity in soil and management generate variability in crop yield. While it is practically unfeasible to thoroughly sample the variability of the crop environment, quantification of the associated uncertainties in crop performance can provide vital information for decision-making. The present study used rainfall data collected in southwestern Georgia at scales ranging from 1 km to 60 km to assess the effect of weather variability (in particular rainfall) on crop predictions aggregated over soil and management variations. The simple SALUS (System Approach to Land Use Sustainability) crop model was integrated in DSSAT (Decision Support System for Agrotechnology Transfer) then parameterized and tested for maize, peanut and cotton for use in obtaining the crop predictions. Analysis of the rainfall data indicated that variability in storm characteristics depends upon the season. Winter rainfall was more correlated at a mean distance of 54 km between locations than summer rainfall was at a mean distance of 3 km. The pairwise correlation between locations decreased with distance faster in the summer than in the winter. This rainfall variability translated into crop yield variability in the study area (about 3100 km²). It was found that weather variability explained 60% and 49% of maize yield variability respectively in 2010 and 2011 when heterogeneity in weather, soil, cultivar and planting dates were accounted for simultaneously. Uncertainties in crop predictions due to rainfall spatial uncertainty decreased as the number of sites where weather data were collected increased. Expressed in terms of maize yield coefficient of variation, this uncertainty decreased exponentially from 27% to approximately 4% at a sampling density of 20 weather locations. Based on 30 years of generated weather data, it was concluded that the general form of the relationship

  17. Regional Frequency Analysis of extreme rainfall events, Tuscany (Italy)

    NASA Astrophysics Data System (ADS)

    Caporali, E.; Chiarello, V.; Rossi, G.

    2014-12-01

    The assessment of extreme hydrological events at sites characterized by short time series or where no data record exists has been mainly obtained by regional models. Regional frequency analysis based on the index variable procedure is implemented here to describe the annual maximum of rainfall depth of short durations in Tuscany region. The probability distribution TCEV - Two Component Extreme Value is used in the frame of the procedure for the parameters estimation based on a three levels hierarchical approach. The methodology deal with the delineation of homogeneous regions, the identification of a robust regional frequency distribution and the assessment of the scale factor, i.e. the index rainfall. The data set includes the annual maximum of daily rainfall of 351 gauge stations with at least 30 years of records, in the period 1916 - 2012, and the extreme rainfalls of short duration, 1 hour and 3, 6, 12, 24 hours. Different subdivisions hypotheses have been verified. A four regions subdivision, coincident with four subregions, which takes into account the orography, the geomorphological and climatic peculiarities of the Tuscany region, has been adopted. Particularly, for testing the regional homogeneity, the cumulate frequency distributions of the observed skewness and variation coefficients of the recorded times series, are compared with the theoretical frequency distribution obtained through a Monte Carlo technique. The related L-skewness and L-variation coefficients are also examined. The application of the Student t -test and the Wilcoxon test for the mean, as well as the χ2 was also performed. Further tests of subdivision hypotheses have been made through the application of discordancy D and heterogeneity H tests and the analysis of the observed and the theoretical TCEV model growth curves. For each region the daily rainfall growth curve has been estimated. The growth curves for the hourly duration have been estimated when the daily rainfall growth curve

  18. How El-Nino affects Ethiopian summer rainfall

    NASA Astrophysics Data System (ADS)

    Gleixner, Stephanie; Keenlyside, Noel; Viste, Ellen

    2016-04-01

    Ethiopian economy and society are strongly dependent on agriculture and therefore rainfall. Reliable forecasts for the rainy seasons are important to allow for agricultural planning and drought preparations. The operational seasonal forecasts for Ethiopia are based on analogue methods relying mainly on sea surface temperature (SST) indices. A better understanding of the physical links between Ethiopian rainfall and SST may help to improve forecasts. The highest rainfall rates are observed in the Kiremt season (defined as JJAS), which is the rainy season in Central and Northwestern Ethiopia. Kiremt rainfall shows clear negative correlation with Central Pacific SST, linking dry Ethiopian summers with ENSO-like warm SST anomalies. We use the atmosphere general circulation model Echam5.3 to investigate the physical link between Pacific SST anomalies and Kiremt rainfall. We compare a historical simulation with a T106 horizontal resolution (~ 1.125°), forced with reconstructed SST data, to gauge-based rainfall observations for the time period of 1961 to 2009. Composite analysis for model and observations show warm SST anomalies in the Central Pacific and a corresponding large-scale circulation anomaly with subsidence over Ethiopia in dry Kiremt seasons. Horizontal wind fields show a slow-down of the whole Indian monsoon system with a weaker Tropical Easterly Jet (TEJ) and a weaker East African Low-Level Jet (EALLJ) in these summers. We conducted a sensitivity experiment with El Nino like SST anomalies in the Central Pacific with the same Echam version. Its results show that warm Pacific SST anomalies cause dry summer conditions over Ethiopia. While the large-scale subsidence over East Africa is present in the experiment, there is no significant weakening of the Indian monsoon system. We rather find an anomalous circulation cell over Northern Africa with westerlies at 100-200 hPa and easterlies below 500 hPa. The anomalous easterly flow in the lower and middle

  19. Monitoring Southern African Rainfall Season Utilizing Growing Regions

    NASA Astrophysics Data System (ADS)

    Husak, G. J.; Magadzire, T.

    2005-12-01

    Variability in timing and amount of rainfall during the growing season in southern Africa can have a dramatic impact on livelihoods in the region. This research integrates satellite model rainfall amounts with expectations for the remainder of the season to provide an envelope of likely outcomes for different growing regions. Satellite information combined with station observations combine to make the African Rainfall Climatology (ARC), which is used to estimate the start of season (SOS) and monitor the season-to-date rainfall accumulations at a pixel level. The Collaborative Historical African Rainfall Model (CHARM) - a 36-year climatology based on available station fields, global climate models and an orographic component - is used to estimate various scenarios for the remainder of the season. The season length is defined by location specific length of growing period provided by the Southern African Development Community (SADC). Once the SOS is observed according to the ARC, seasonal accumulations for each pixel begin and are evaluated at a dekadal interval. These accumulations can be compared to historical accumulations after an equal number of dekads to evaluate the progression of the season as a percentage of historical season-to-date totals for each pixel. Rainfall accumulations for the remainder of the growing period can be tallied for each year of the CHARM dataset, and Gamma probability distribution parameters can be fit to these values. Using these distribution parameters, it is possible to evaluate scenarios for the remainder of the season and combine them with the accumulations from the ARC to arrive at total rainfall accumulated during a growing period. Analysis of these totals can be compared with long-term mean accumulations for the growing period to estimate how crops will fare relative to past performance. Evaluation of various wet and dry scenarios for the remainder of the season, defined here as the 80th percentile and 20th percentile, provide an

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

    NASA Astrophysics Data System (ADS)

    Dolšak, Domen; Bezak, Nejc; Šraj, Mojca

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    Recently, due to the global climate change, most of the time the rainfall in Taiwan is of short duration but with high intensity. Due to Taiwan's steep terrain, rainfall-induced landslides often occur and lead to human causalities and properties loss. Taiwan's government has invested huge reconstruction funds to the affected areas. However, after rehabilitation they still face the risk of secondary sediment disasters. Therefore, this study assesses rainfall-induced (secondary) landslide potential and spatial distribution in watershed of Southern Taiwan under extreme climate change. The study areas in this research are Baolai and Jianshan villages in the watershed of the Laonongxi River Basin in the Southern Taiwan. This study focused on the 3 years after Typhoon Morakot (2009 to 2011). During this period, the study area experienced six heavy rainfall events including five typhoons and one heavy rainfall. The genetic adaptive neural network, texture analysis and GIS were implemented in the analysis techniques for the interpretation of satellite images and to obtain surface information and hazard log data and to analyze land use change. A multivariate hazards evaluation method was applied to quantitatively analyze the weights of various natural environmental and slope development hazard factors. Furthermore, this study established a slope landslide potential assessment model and depicted a slope landslide potential diagram by using the GIS platform. The interaction between (secondary) landslide mechanism, scale, and location was analyzed using association analysis of landslide historical data and regional environmental characteristics. The results of image classification before and after six heavy rainfall events show that the values of coefficient of agreement are at medium-high level. By multivariate hazards evaluation method, geology and the effective accumulative rainfall (EAR) are the most important factors. Slope, distance from fault, aspect, land disturbance

  2. Tropical Lake Levels and Their Relationship to Rainfall

    NASA Astrophysics Data System (ADS)

    Ricko, M.; Carton, J.; Birkett, C. M.

    2009-12-01

    The availability of satellite altimeters and improvements in satellite estimates of river and lake levels are offering an exciting monitoring alternative to currently limited prediction systems using current climate models. Aware of existing limitations in data retrievals, we have developed a simple linear model for estimating lake level as a function of freshwater flux into the catchment basin for 12 tropical lakes and reservoirs: 8 in Africa, 3 in Central and South America, and 1 in Southeast Asia. In our model three parameters, effective catchment basin, time delay, and drainage timescale are determined from linear regression based on the simultaneous availability of remotely sensed lake level and rainfall. We present results of estimates of net surface freshwater flux and lake levels during a 16-year period (1992-2007). Comparison between two different altimeter satellite-based lake level datasets shows very good agreement for most lakes. For net freshwater flux (i.e., rainfall minus evaporation), we use three different rainfall products: the European Centre for Medium Range Weather Forecasts (ECMWF) ERA-Interim reanalysis, the Global Precipitation Climatology Project (GPCP) rainfall, and the Tropical Rainfall Measurement Mission (TRMM) 3B42 precipitation index rainfall. ERA-Interim evaporation is combined with each of the three rainfall products to form three estimates of net surface freshwater flux. Results from models are denominated as Model-I, Model-G, Model-T, respectively. A comparison of rainfall products shows differences, and as a result the best model for a given lake varies. The median correlation between the observed LEGOS and Model-G lake levels is significantly higher than for Model-I, with the median RMS difference between observation and model slightly lower for Model-G than for Model-I. For many tropical lakes the best results are obtained using one of the observation-based products, GPCP or TRMM. All three model results show that all lakes

  3. Detection of High Quality Rainfall Data to Improve Flood Resilience

    NASA Astrophysics Data System (ADS)

    Hoang, T. C.; Tchiguirinskaia, I.; Schertzer, D. J.; Lovejoy, S.

    2012-12-01

    European flood management systems require reliable rainfall statistics, e.g. the Intensity-duration-Frequency curves for shorter and shorter durations and for a larger and larger range of return periods. Preliminary studies showed that the number of floods depends on the quality of available data, e.g. the time resolution quality. These facts suggest that a particular attention should be paid to the rainfall data quality in order to adequately investigate flood risk aiming to achieve flood resilience. The potential consequences of changes in measuring and recording techniques have been somewhat discussed in the literature with respect to a possible introduction of artificial inhomogeneities in time series. In this direction, we developed a first version of a SERQUAL procedure to automatically detect the effective time resolution of highly mixed data. We show that most of the rainfall time series have a lower recording frequency than that is assumed. This question is particularly important for operational hydrology, because an error on the effective recording high frequency introduces biases in the corresponding statistics. It is therefore essential to quantify the quality of the rainfall time series before their use. Due to the fact that the multiple scales and possible scaling behaviour of hydrological data are particularly important for many applications, including flood resilience research, this paper first investigates the sensitivity of the scaling estimates and methods to the deficit of short duration rainfall data, and consequently propose a few simple criteria for a reliable evaluation of the data quality. The SERQUAL procedure enable us to extract high quality sub-series from longer time series that will be much more reliable to calibrate and/or validate short duration quantiles and hydrological models.

  4. Analysis of rainfall seasonality from observations and climate models

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

    Two new indicators of rainfall seasonality based on information entropy, the relative entropy (RE) and the dimensionless seasonality index (DSI), together with the mean annual rainfall, are evaluated on a global scale for recently updated precipitation gridded datasets and for historical simulations from coupled atmosphere-ocean general circulation models. The RE provides a measure of the number of wet months and, for precipitation regimes featuring a distinct wet and dry season, it is directly related to the duration of the wet season. The DSI combines the rainfall intensity with its degree of seasonality and it is an indicator of the extent of the global monsoon region. We show that the RE and the DSI are fairly independent of the time resolution of the precipitation data, thereby allowing objective metrics for model intercomparison and ranking. Regions with different precipitation regimes are classified and characterized in terms of RE and DSI. Comparison of different land observational datasets reveals substantial difference in their local representation of seasonality. It is shown that two-dimensional maps of RE provide an easy way to compare rainfall seasonality from various datasets and to determine areas of interest. Models participating to the Coupled Model Intercomparison Project platform, Phase 5, consistently overestimate the RE over tropical Latin America and underestimate it in West Africa, western Mexico and East Asia. It is demonstrated that positive RE biases in a general circulation model are associated with excessively peaked monthly precipitation fractions, too large during the wet months and too small in the months preceding and following the wet season; negative biases are instead due, in most cases, to an excess of rainfall during the premonsoonal months.

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  6. Asian summer monsoon rainfall predictability: a predictable mode analysis

    NASA Astrophysics Data System (ADS)

    Wang, Bin; Lee, June-Yi; Xiang, Baoqiang

    2015-01-01

    To what extent the Asian summer monsoon (ASM) rainfall is predictable has been an important but long-standing issue in climate science. Here we introduce a predictable mode analysis (PMA) method to estimate predictability of the ASM rainfall. The PMA is an integral approach combining empirical analysis, physical interpretation and retrospective prediction. The empirical analysis detects most important modes of variability; the interpretation establishes the physical basis of prediction of the modes; and the retrospective predictions with dynamical models and physics-based empirical (P-E) model are used to identify the "predictable" modes. Potential predictability can then be estimated by the fractional variance accounted for by the "predictable" modes. For the ASM rainfall during June-July-August, we identify four major modes of variability in the domain (20°S-40°N, 40°E-160°E) during 1979-2010: (1) El Niño-La Nina developing mode in central Pacific, (2) Indo-western Pacific monsoon-ocean coupled mode sustained by a positive thermodynamic feedback with the aid of background mean circulation, (3) Indian Ocean dipole mode, and (4) a warming trend mode. We show that these modes can be predicted reasonably well by a set of P-E prediction models as well as coupled models' multi-model ensemble. The P-E and dynamical models have comparable skills and complementary strengths in predicting ASM rainfall. Thus, the four modes may be regarded as "predictable" modes, and about half of the ASM rainfall variability may be predictable. This work not only provides a useful approach for assessing seasonal predictability but also provides P-E prediction tools and a spatial-pattern-bias correction method to improve dynamical predictions. The proposed PMA method can be applied to a broad range of climate predictability and prediction problems.

  7. Have Tropical Cyclones Been Feeding More Extreme Rainfall?

    NASA Technical Reports Server (NTRS)

    Lau, K.-M.; Zhou, Y. P.; Wu, H.-T.

    2008-01-01

    We have conducted a study of the relationship between tropical cyclone (TC) and extreme rain events using GPCP and TRMM rainfall data, and storm track data for July through November (JASON) in the North Atlantic (NAT) and the western North Pacific (WNP). Extreme rain events are defined in terms of percentile rainrate, and TC-rain by rainfall associated with a named TC. Results show that climatologically, 8% of rain events and 17% of the total rain amount in NAT are accounted by TCs, compared to 9% of rain events and 21% of rain amount in WNP. The fractional contribution of accumulated TC-rain to total rain, Omega, increases nearly linearly as a function of rainrate. Extending the analyses using GPCP pentad data for 1979-2005, and for the post-SSM/I period (1988-2005), we find that while there is no significant trend in the total JASON rainfall over NAT or WNP, there is a positive significant trend in heavy rain over both basins for the 1979-2005 period, but not for the post-SSM/I period. Trend analyses of Omega for both periods indicate that TCs have been feeding increasingly more to rainfall extremes in NAT, where the expansion of the warm pool area can explain slight more than 50% of the change in observed trend in total TC rainfall. In WNP, trend signals for Omega are mixed, and the long-term relationship between TC rain and warm pool areas are strongly influenced by interannual and interdecadal variability.

  8. A fully probabilistic approach to extreme rainfall modeling

    NASA Astrophysics Data System (ADS)

    Coles, Stuart; Pericchi, Luis Raúl; Sisson, Scott

    2003-03-01

    It is an embarrassingly frequent experience that statistical practice fails to foresee historical disasters. It is all too easy to blame global trends or some sort of external intervention, but in this article we argue that statistical methods that do not take comprehensive account of the uncertainties involved in both model and predictions, are bound to produce an over-optimistic appraisal of future extremes that is often contradicted by observed hydrological events. Based on the annual and daily rainfall data on the central coast of Venezuela, different modeling strategies and inference approaches show that the 1999 rainfall which caused the worst environmentally related tragedy in Venezuelan history was extreme, but not implausible given the historical evidence. We follow in turn a classical likelihood and Bayesian approach, arguing that the latter is the most natural approach for taking into account all uncertainties. In each case we emphasize the importance of making inference on predicted levels of the process rather than model parameters. Our most detailed model comprises of seasons with unknown starting points and durations for the extremes of daily rainfall whose behavior is described using a standard threshold model. Based on a Bayesian analysis of this model, so that both prediction uncertainty and process heterogeneity are properly modeled, we find that the 1999 event has a sizeable probability which implies that such an occurrence within a reasonably short time horizon could have been anticipated. Finally, since accumulation of extreme rainfall over several days is an additional difficulty—and indeed, the catastrophe of 1999 was exaggerated by heavy rainfall on successive days—we examine the effect of timescale on our broad conclusions, finding results to be broadly similar across different choices.

  9. Response of African humid tropical forests to recent rainfall anomalies

    PubMed Central

    Asefi-Najafabady, Salvi; Saatchi, Sassan

    2013-01-01

    During the last decade, strong negative rainfall anomalies resulting from increased sea surface temperature in the tropical Atlantic have caused extensive droughts in rainforests of western Amazonia, exerting persistent effects on the forest canopy. In contrast, there have been no significant impacts on rainforests of West and Central Africa during the same period, despite large-scale droughts and rainfall anomalies during the same period. Using a combination of rainfall observations from meteorological stations from the Climate Research Unit (CRU; 1950–2009) and satellite observations of the Tropical Rainfall Measuring Mission (TRMM; 1998–2010), we show that West and Central Africa experienced strong negative water deficit (WD) anomalies over the last decade, particularly in 2005, 2006 and 2007. These anomalies were a continuation of an increasing drying trend in the region that started in the 1970s. We monitored the response of forests to extreme rainfall anomalies of the past decade by analysing the microwave scatterometer data from QuickSCAT (1999–2009) sensitive to variations in canopy water content and structure. Unlike in Amazonia, we found no significant impacts of extreme WD events on forests of Central Africa, suggesting potential adaptability of these forests to short-term severe droughts. Only forests near the savanna boundary in West Africa and in fragmented landscapes of the northern Congo Basin responded to extreme droughts with widespread canopy disturbance that lasted only during the period of WD. Time-series analyses of CRU and TRMM data show most regions in Central and West Africa experience seasonal or decadal extreme WDs (less than −600 mm). We hypothesize that the long-term historical extreme WDs with gradual drying trends in the 1970s have increased the adaptability of humid tropical forests in Africa to droughts. PMID:23878335

  10. Variation of soil surface roughness under simulated rainfall

    NASA Astrophysics Data System (ADS)

    Tarquis, A. M.; Saa-Requejo, A.; Valencia, J. L.; Moratiel, R.; Paz-Gonzalez, A.

    2012-04-01

    Soil surface micro-topography or roughness (SSR) defines the physical boundary between overland flow and soil. Due to its unique position, soil roughness potentially affects surface processes such as infiltration, flow routing, erosion and sedimentation. Thus the decay of SSR under different rainfall intensities is of most interest in soil erosion. While some authors have chosen exponent function of cumulative rainfall to describe the decay of SSR, others have used the kinetic energy of rainfall. SSR at the field level is an easy visually perceptible notion, but difficult to describe numerically. In this study we didn't use pin-meter or laser techniques to quantify SSR. Percentage of micro-topographic shadows, under fixed sunlight conditions, has been applied based on former works that proved it is an easy and reliable method to estimate SSR. Two experimental plots, of 1m x 1m, were subjected to successive simulated rainfall events with an intensity of 67 mm/h and a height of 2 m. Both plots were a harrowed plot with an oriented roughness and 6% slope. Images were obtained each 15 minutes of rainfall with an incident angle of light of 45° approximately. The image was acquired by an OLYMPUS X-925, having a size of 2976x3968 pixels and corresponding to an area of 75 cm x 100 cm. For denoising process, the image was cropped to 590x800 pixels and for image binarization Indicator Kriging (IK) method was used. Comparisons of both plots respect to SSR evolution, runoff accumulation and shadows morphology are showed. Acknowledgements Funding provided by Spanish Ministerio de Ciencia e Innovación (MICINN) through project no. AGL2010-21501/AGR is greatly appreciated.

  11. Research On Rainfall and The Prediction of Debris Flow

    NASA Astrophysics Data System (ADS)

    Yu, B.

    Accurate prediction of debris flow so that economic losses and human ca- sualties can be reduced or prevented is currently the most focused and difficult point of studying debris flows. Most predictive methods have relied on rainfall as the basic parameter to make predictions, with the result that there is only the prediction of the actual occurrence without that of its arrival time and scale. This article takes Jiangjia Gully in Dongchuan of Yunnan Province as an example, and considers, on the basis of the already possessed essential condition U solid material, the abundant conditions for ° the formation of debris flow. Based on the mechanism of the occurrence of debris flow and the volume of rainfall in the basin, this paper also gives a systematic analysis on the arrival time and scale of debris flow, and suggests that the hydrological condition for forming debris flow is the unit discharge of the flood 8805; 0.35m2/s.m. It uses the ten-minute rainfall intensity to calculate both the runoffs of the rainfall and the unit discharge from the runoff, thus predicting the occurrence of debris flow. The velocity and the arrival time of a debris flow can be figured out by using the unit discharge of the runoffs. The total amount of debris flow can be calculated out and the scale of a debris flow can be predicted by using the ten-minute intensity of rainfall and the total volume of the runoffs, together with the volume concentration of sediment in a debris flow and the basin block up coefficient.

  12. Southeast Atlantic warm events and southern african rainfall

    NASA Astrophysics Data System (ADS)

    Rouault, M.

    2003-04-01

    From January to May 2001, several countries of Southern Africa experienced above normal rainfall and floods. 23 000 people were displaced in Southern Angola after a flood in April. In March, an inundation killed several people and displaced 5,000 others in eastern Zambia's. The situation in Zambia was aggravated when authorities had to open the spillway gates at the Kariba Dam, the main source of electricity for Zambia and Zimbabwe. Water discharged from the Kariba dam ran into neighbouring Mozambique, aggravating floods in that country. At the same time warm sea surface anomalies were measured off the Angolan and Namibian coast. Warm events in the Southeast Tropical Atlantic off Angola and Namibia called "Benguela Nino" are known to affect the fisheries of the region but they also affect the rainfall. In 1995, the warmest recorded Benguela Nino happened with anomalies off up to 8°C extending 300 km offshore with a southward extension to 27°S. During the 1984, 1986, 1995 and 2001 warm events, above average rainfall occurred near the sea surface temperature anomalies and extended inland from the coast to an extent that appeared to depend on the intensity of the regional moisture convergence and atmospheric circulation anomalies. Rainfall over western Angola / Namibia is greatest for those events for which the local circulation anomalies act to strengthen the climatological westwards flux of Indian Ocean sourced moisture across low latitude southern Africa and which flow anticyclonically over the warmest SST off the northern coast. The significance of the warm events occurring during the February to April period is that this is the time when SST reaches its maximum in the annual cycle (up to 28oC off northern Angola) and this favours more intense local evaporation and convection and a greater impact on late austral summer rainfall.

  13. Identification of anomalous motion of thunderstorms using daily rainfall fields

    NASA Astrophysics Data System (ADS)

    del Moral, Anna; Llasat, Maria Carmen; Rigo, Tomeu

    2016-04-01

    Adverse weather phenomena in Catalonia (NE of the Iberian Peninsula) is commonly associated to heavy rains, large hail, strong winds, and/or tornados, all of them caused by thunderstorms. In most of the cases with adverse weather, thunderstorms vary sharply their trajectories in a concrete moment, changing completely the motion directions that have previously followed. Furthermore, it is possible that a breaking into several cells may be produced, or, in the opposite, it can be observed a joining of different thunderstorms into a bigger system. In order to identify the main features of the developing process of thunderstorms and the anomalous motions that these may follow in some cases, this contribution presents a classification of the events using daily rainfall fields, with the purpose of distinguishing quickly anomalous motion of thunderstorms. The methodology implemented allows classifying the daily rainfall fields in three categories by applying some thresholds related with the daily precipitation accumulated values and their extension: days with "no rain", days with "potentially convective" rain and days with "non-potentially convective" rain. Finally, for those "potentially convective" daily rainfall charts, it also allows a geometrical identification and classification of all the convective structures into "ellipse" and "non-ellipse", obtaining then the structures with "normal" or "anomalous" motion pattern, respectively. The work is focused on the period 2008-2015, and presents some characteristics of the rainfall behaviour in terms of the seasonal distribution of convective rainfall or the geographic variability. It shows that convective structures are mainly found during late spring and summer, even though they can be recorded in any time of the year. Consequently, the maximum number of convective structures with anomalous motion is recorded between July and November. Furthermore, the contribution shows the role of the orography of Catalonia in the

  14. Modeling rainfall-runoff relationship using multivariate GARCH model

    NASA Astrophysics Data System (ADS)

    Modarres, R.; Ouarda, T. B. M. J.

    2013-08-01

    The traditional hydrologic time series approaches are used for modeling, simulating and forecasting conditional mean of hydrologic variables but neglect their time varying variance or the second order moment. This paper introduces the multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) modeling approach to show how the variance-covariance relationship between hydrologic variables varies in time. These approaches are also useful to estimate the dynamic conditional correlation between hydrologic variables. To illustrate the novelty and usefulness of MGARCH models in hydrology, two major types of MGARCH models, the bivariate diagonal VECH and constant conditional correlation (CCC) models are applied to show the variance-covariance structure and cdynamic correlation in a rainfall-runoff process. The bivariate diagonal VECH-GARCH(1,1) and CCC-GARCH(1,1) models indicated both short-run and long-run persistency in the conditional variance-covariance matrix of the rainfall-runoff process. The conditional variance of rainfall appears to have a stronger persistency, especially long-run persistency, than the conditional variance of streamflow which shows a short-lived drastic increasing pattern and a stronger short-run persistency. The conditional covariance and conditional correlation coefficients have different features for each bivariate rainfall-runoff process with different degrees of stationarity and dynamic nonlinearity. The spatial and temporal pattern of variance-covariance features may reflect the signature of different physical and hydrological variables such as drainage area, topography, soil moisture and ground water fluctuations on the strength, stationarity and nonlinearity of the conditional variance-covariance for a rainfall-runoff process.

  15. Classification of rainfall variability by using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Michaelides, Silas Chr.; Pattichis, Constantinos S.; Kleovoulou, Georgia

    2001-09-01

    In this paper, the usefulness of artificial neural networks (ANNs) as a suitable tool for the study of the medium and long-term climatic variability is examined. A method for classifying the inherent variability of climatic data, as represented by the rainfall regime, is investigated. The rainfall recorded at a climatological station in Cyprus over a long time period has been used in this paper as the input for various ANN and cluster analysis models. The analysed rainfall data cover the time span 1917-1995. Using these values, two different procedures were followed for structuring the input vectors for training the ANN models: (a) each 1-year subset consisting of the 12 monthly elements, and (b) each 2-year subset consisting of the 24 monthly elements. Several ANN models with a varying number of output nodes have been trained, using an unsupervised learning paradigm, namely, the Kohonen's self-organizing feature maps algorithm. For both the 1- and 2-year subsets, 16 classes were empirically considered as the optimum for computing the prototype classes of weather variability for this meteorological parameter. The classification established by using the ANN methodology is subsequently compared with the classification generated by using cluster analysis, based on the agglomerative hierarchical clustering algorithm. To validate the classification results, the rainfall distributions for the more recent years 1996, 1997 and 1998 were utilized. The respective 1- and 2-year distributions for these years were assigned to particular classes for both the ANN and cluster analysis procedures. Compared with cluster analysis, the ANN models were more capable of detecting even minor characteristics in the rainfall waveshapes investigated, and they also performed a more realistic categorization of the available data. It is suggested that the proposed ANN methodology can be applied to more climatological parameters, and with longer cycles.

  16. Have Tropical Cyclones been Feeding More Extreme Rainfall?

    NASA Technical Reports Server (NTRS)

    Lau, K.-M.; Zhou, Y. P.; Wu, H.-T.

    2008-01-01

    We have conducted a study of the relationship between tropical cyclone (TC) and extreme rain events using GPCP and TRMM rainfall data ; and storm track data for July through November (JASON) in the North Atlantic (NAT) and the western North Pacific (WNP). Extreme rain events are defined in terms of percentile rainrate, and TC-gain by rainfall associated with a named TC. Results show that climatologically, 8% of rain events and 17% of the total rain amount in NAT are accounted by TCs, compared to 9% of rain events, and 21% of rain amount in WN.P. The fractional contribution of accumulated TC-rain to total rain, Omega, increases nearly linearly as a function of rainrate. Extending the analyses using GPCP pentad data for 1979-2005, and for the post-SSM/I period (1988-2005), we find that while there is no significant trend in the total JASON rainfall over NAT or WNP there is a positive significant trend in heavy rain over both basins for the 1979-2005 period, but not for the post-SSM/I period. Trend analyses of Omega for bout periods indicate that TCs have been feeding increasingly more to rainfall extremes in NAT, where the expansion of the warm pool area can explain slightly more than 50% of the change in observed trend in total TC rainfall. In. WNP, trend signals for Omega are mixed, and the loner term relationship between TC rain and warm pool area is strongly influenced by interannual and interdecadal variability.

  17. Quantitative rainfall metrics for comparing volumetric rainfall retrievals to fine scale models

    NASA Astrophysics Data System (ADS)

    Collis, Scott; Tao, Wei-Kuo; Giangrande, Scott; Fridlind, Ann; Theisen, Adam; Jensen, Michael

    2013-04-01

    Precipitation processes play a significant role in the energy balance of convective systems for example, through latent heating and evaporative cooling. Heavy precipitation "cores" can also be a proxy for vigorous convection and vertical motions. However, comparisons between rainfall rate retrievals from volumetric remote sensors with forecast rain fields from high-resolution numerical weather prediction simulations are complicated by differences in the location and timing of storm morphological features. This presentation will outline a series of metrics for diagnosing the spatial variability and statistical properties of precipitation maps produced both from models and retrievals. We include existing metrics such as Contoured by Frequency Altitude Diagrams (Yuter and Houze 1995) and Statistical Coverage Products (May and Lane 2009) and propose new metrics based on morphology, cell and feature based statistics. Work presented focuses on observations from the ARM Southern Great Plains radar network consisting of three agile X-Band radar systems with a very dense coverage pattern and a C Band system providing site wide coverage. By combining multiple sensors resolutions of 250m2 can be achieved, allowing improved characterization of fine-scale features. Analyses compare data collected during the Midlattitude Continental Convective Clouds Experiment (MC3E) with simulations of observed systems using the NASA Unified Weather Research and Forecasting model. May, P. T., and T. P. Lane, 2009: A method for using weather radar data to test cloud resolving models. Meteorological Applications, 16, 425-425, doi:10.1002/met.150, 10.1002/met.150. Yuter, S. E., and R. A. Houze, 1995: Three-Dimensional Kinematic and Microphysical Evolution of Florida Cumulonimbus. Part II: Frequency Distributions of Vertical Velocity, Reflectivity, and Differential Reflectivity. Mon. Wea. Rev., 123, 1941-1963, doi:10.1175/1520-0493(1995)123<1941:TDKAME>2.0.CO;2.

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

    PubMed Central

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

    2016-01-01

    In water-limited regions, rainfall interception is influenced by rainfall properties and crown characteristics. Rainfall properties, aside from gross rainfall amount and duration (GR and RD), maximum rainfall intensity and rainless gap (RG), within rain events may heavily affect throughfall and interception by plants. From 2004 to 2014 (except for 2007), individual shrubs of Caragana korshinskii and Artemisia ordosica were selected to measure throughfall during 210 rain events. Various rainfall properties were auto-measured and crown characteristics, i.e., height, branch and leaf area index, crown area and volume of two shrubs were also measured. The relative interceptions of C. korshinskii and A. ordosica were 29.1% and 17.1%, respectively. Rainfall properties have more contributions than crown characteristics to throughfall and interception of shrubs. Throughfall and interception of shrubs can be explained by GR, RI60 (maximum rainfall intensities during 60 min), RD and RG in deceasing importance. However, relative throughfall and interception of two shrubs have different responses to rainfall properties and crown characteristics, those of C. korshinskii were closely related to rainfall properties, while those of A. ordosica were more dependent on crown characteristics. We highlight long-term monitoring is very necessary to determine the relationships between throughfall and interception with crown characteristics. PMID:27184918

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

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

    PubMed

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

    2016-01-01

    In water-limited regions, rainfall interception is influenced by rainfall properties and crown characteristics. Rainfall properties, aside from gross rainfall amount and duration (GR and RD), maximum rainfall intensity and rainless gap (RG), within rain events may heavily affect throughfall and interception by plants. From 2004 to 2014 (except for 2007), individual shrubs of Caragana korshinskii and Artemisia ordosica were selected to measure throughfall during 210 rain events. Various rainfall properties were auto-measured and crown characteristics, i.e., height, branch and leaf area index, crown area and volume of two shrubs were also measured. The relative interceptions of C. korshinskii and A. ordosica were 29.1% and 17.1%, respectively. Rainfall properties have more contributions than crown characteristics to throughfall and interception of shrubs. Throughfall and interception of shrubs can be explained by GR, RI60 (maximum rainfall intensities during 60 min), RD and RG in deceasing importance. However, relative throughfall and interception of two shrubs have different responses to rainfall properties and crown characteristics, those of C. korshinskii were closely related to rainfall properties, while those of A. ordosica were more dependent on crown characteristics. We highlight long-term monitoring is very necessary to determine the relationships between throughfall and interception with crown characteristics. PMID:27184918

  1. Correcting rainfall using satellite-based surfae soil moisture retrievals: The soil moisture analysis rainfall tool(SMART)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Recent work in Crow et al. (2009) developed an algorithm for enhancing satellite-based land rainfall products via the assimilation of remotely-sensed surface soil moisture retrievals into a water balance model. As a follow-up, this paper describes the benefits of modifying their approach to incorpor...

  2. A simplified diagnostic model of orographic rainfall for enhancing satellite-based rainfall estimates in data-poor regions

    USGS Publications Warehouse

    Funk, Christopher C.; Michaelsen, Joel C.

    2004-01-01

    An extension of Sinclair's diagnostic model of orographic precipitation (“VDEL”) is developed for use in data-poor regions to enhance rainfall estimates. This extension (VDELB) combines a 2D linearized internal gravity wave calculation with the dot product of the terrain gradient and surface wind to approximate terrain-induced vertical velocity profiles. Slope, wind speed, and stability determine the velocity profile, with either sinusoidal or vertically decaying (evanescent) solutions possible. These velocity profiles replace the parameterized functions in the original VDEL, creating VDELB, a diagnostic accounting for buoyancy effects. A further extension (VDELB*) uses an on/off constraint derived from reanalysis precipitation fields. A validation study over 365 days in the Pacific Northwest suggests that VDELB* can best capture seasonal and geographic variations. A new statistical data-fusion technique is presented and is used to combine VDELB*, reanalysis, and satellite rainfall estimates in southern Africa. The technique, matched filter regression (MFR), sets the variance of the predictors equal to their squared correlation with observed gauge data and predicts rainfall based on the first principal component of the combined data. In the test presented here, mean absolute errors from the MFR technique were 35% lower than the satellite estimates alone. VDELB assumes a linear solution to the wave equations and a Boussinesq atmosphere, and it may give unrealistic responses under extreme conditions. Nonetheless, the results presented here suggest that diagnostic models, driven by reanalysis data, can be used to improve satellite rainfall estimates in data-sparse regions.

  3. A satellite rainfall retrieval technique over northern Algeria based on the probability of rainfall intensities classification from MSG-SEVIRI

    NASA Astrophysics Data System (ADS)

    Lazri, Mourad; Ameur, Soltane

    2016-09-01

    In this paper, an algorithm based on the probability of rainfall intensities classification for rainfall estimation from Meteosat Second Generation/Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) has been developed. The classification scheme uses various spectral parameters of SEVIRI that provide information about cloud top temperature and optical and microphysical cloud properties. The presented method is developed and trained for the north of Algeria. The calibration of the method is carried out using as a reference rain classification fields derived from radar for rainy season from November 2006 to March 2007. Rainfall rates are assigned to rain areas previously identified and classified according to the precipitation formation processes. The comparisons between satellite-derived precipitation estimates and validation data show that the developed scheme performs reasonably well. Indeed, the correlation coefficient presents a significant level (r:0.87). The values of POD, POFD and FAR are 80%, 13% and 25%, respectively. Also, for a rainfall estimation of about 614 mm, the RMSD, Bias, MAD and PD indicate 102.06(mm), 2.18(mm), 68.07(mm) and 12.58, respectively.

  4. Rainfall erosivity-intensity relationships for normal rainfall events and a tropical cyclone on the US southeast coast

    NASA Astrophysics Data System (ADS)

    Nanko, Kazuki; Moskalski, Susanne M.; Torres, Raymond

    2016-03-01

    The work done on the intertidal landscape by low tide rainfall events has been shown to augment the cycling of dissolved and particulate nutrients, but low tide rainfall events are not a well-documented component of coastal ecosystem models. Here we develop the relationships between rainfall intensity (I), and median volume raindrop diameter, and three rainfall erosivity indices (kinetic energy, momentum, and momentum multiplied by the drop diameter) using an optical disdrometer deployed in the intertidal zone during summer and fall of 2010 and 2011. These data include the local effects of Hurricane Irene in 2011. Raindrop data measured for 27 days of late summer were analyzed. The best fit between median volume raindrop diameter and I was a combination of the power-law and logarithm equations, and the best fits of three erosivity indices and I were obtained with power-law equations. Kinetic energy was slightly higher than the world average. Observed raindrop velocity was typically lower and more widely distributed than the theoretical raindrop terminal velocity. Hence, erosivity indices based on observed velocity were lower than those based on terminal velocity. The hurricane provided larger raindrops and more widely distributed raindrop velocity than normal events. Overall, results indicate that it is not suitable to assume that background erosivity-I relationships apply to cyclonic events. We derived new erosivity-I relationships to help characterize soil erosion processes in salt marsh areas for normal events. These results will help predict material and nutrient fluxes between intertidal and subtidal landscapes.

  5. Characterization of high spatiotemporal rainfall events in the upper washita river basin

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Transport phenomena at the watershed scale are driven by spatially distributed hydrological processes in which variable rainfall duration and intensity plays a fundamental role. Characterization of these rainfall phenomena using high spatiotemporal resolution is essential when using models to assess...

  6. Sahel decadal rainfall variability and the role of model horizontal resolution

    NASA Astrophysics Data System (ADS)

    Vellinga, Michael; Roberts, Malcolm; Vidale, Pier Luigi; Mizielinski, Matthew S.; Demory, Marie-Estelle; Schiemann, Reinhard; Strachan, Jane; Bain, Caroline

    2016-01-01

    Substantial low-frequency rainfall fluctuations occurred in the Sahel throughout the twentieth century, causing devastating drought. Modeling these low-frequency rainfall fluctuations has remained problematic for climate models for many years. Here we show using a combination of state-of-the-art rainfall observations and high-resolution global climate models that changes in organized heavy rainfall events carry most of the rainfall variability in the Sahel at multiannual to decadal time scales. Ability to produce intense, organized convection allows climate models to correctly simulate the magnitude of late-twentieth century rainfall change, underlining the importance of model resolution. Increasing model resolution allows a better coupling between large-scale circulation changes and regional rainfall processes over the Sahel. These results provide a strong basis for developing more reliable and skilful long-term predictions of rainfall (seasons to years) which could benefit many sectors in the region by allowing early adaptation to impending extremes.

  7. NASA's IMERG Adds Up a Week of Soaking Rainfall in Texas

    NASA Video Gallery

    An estimate of rainfall totals from May 27, 2016 to June 2, 2016 was made using data from NASA's Integrated Multi-satellitE Retrievals for GPM (IMERG). During this period rainfall totals in parts o...

  8. An Investigation of Trends and Variability of Rainfall in Shillong City.

    NASA Astrophysics Data System (ADS)

    Tanti, Kamal Kumar; Moni Saikia, Nayan; Swer, Markynti

    2016-07-01

    This study aims to investigate and analyse the trends and variability of rainfall in Shillong and its nearby areas, located in Meghalaya hills of North-east India; which is geographically a neighbouring area to the wettest places of the Earth, i.e., Cherrapunji and Mawsynram. The analysis of variability and trends to annual, seasonal, monthly and daily rainfall was carried out, using the data collected from the IMD station at Shillong; thereby attempting to highlight whether rainfall in Shillong area has been increasing or decreasing over the years. Rainfall variability coefficient is utilized to compare the current rainfall trend of the area with its past rainfall trends. The present study also aims to analyse the frequency of occurrence of extreme rainfall events over the region. These studies will help us to establish a correlation between the current rainfall trend and climate change scenario of the study area.

  9. Analysis of seasonal and annual rainfall trends in the northern region of Bangladesh

    NASA Astrophysics Data System (ADS)

    Bari, Sheikh Hefzul; Rahman, M. Tauhid Ur; Hoque, Muhammad Azizul; Hussain, Md. Manjurul

    2016-07-01

    The aim of the present study was to investigate 50 years (1964-2013) of seasonal and annual rainfall trends and their fluctuation over time in northern Bangladesh. After testing the autocorrelation, non-parametric Mann-Kendall test along with Sen Slope estimator was used to examine rainfall trends and their magnitudes. The sequential Mann-Kendall test was used to identify any fluctuations in the trends over time and to detect the possible points of change in the rainfall series. We found that pre-monsoon and post-monsoon rainfall is increasing in most of the rainfall stations. The only decrement in pre-monsoon rainfall was found for Ishurdi (1.28 mm/year). However, the sequential Mann-Kendall test detected decreasing pre-monsoon rainfall trend after early the 1990s. Monsoon rainfall showed a decreasing trend in the majority of the area studied. The maximum decrement in monsoon rainfall was found for Sylhet station (8.10 mm/year) and minimum in Mymensingh (1.53 mm/year). An upward monsoon rainfall trend was found for Rangpur (2.02 mm/year). Annual rainfall followed the monsoon rainfall trend. However, all of the positive and negative trends were found statistically non-significant at 95% confidence limit with the only exception for monsoon and annual rainfall at Rajshahi station. Rajshahi station was the only region where the monsoon and annual rainfall has a significant negative trend at 95% confidence limit. The sequential Mann-Kendall test detected several non-significant points of change for seasonal and annual rainfall at most of the stations. Periodic fluctuations were also detected. We observed that there were decreasing seasonal rainfall trend after early the 1990s for the majority of the stations.

  10. Real-time estimation of rainfall fields using rain gage data under fractional coverage conditions

    NASA Astrophysics Data System (ADS)

    Seo, D.-J.

    1998-07-01

    Two new attempts at optimal estimation of rainfall fields using hourly rain gage data under fractional coverage conditions are reported; (1) double optimal estimation using analogues of indicator and simple kriging to estimate probability of rainfall and rainfall amount given raining, respectively, and (2) single optimal estimation using an analogue of simple kriging to directly estimate rainfall ???. They are evaluated via cross validation using ??? from the operational network under the Tulsa, Oklahoma, WSR-88D (Weather Surveillance Radar-1988 Doppler version) umbrella.

  11. Estimating rainfall and water balance over the Okavango River Basin for hydrological applications

    NASA Astrophysics Data System (ADS)

    Wilk, Julie; Kniveton, Dominic; Andersson, Lotta; Layberry, Russell; Todd, Martin C.; Hughes, Denis; Ringrose, Susan; Vanderpost, Cornelis

    2006-11-01

    SummaryA historical database for use in rainfall-runoff modeling of the Okavango River Basin in Southwest Africa is presented. The work has relevance for similar data-sparse regions. The parameters of main concern are rainfall and catchment water balance, which are key variables for subsequent studies of the hydrological impacts of development and climate change. Rainfall estimates are based on a combination of in situ gauges and satellite sources. Rain gauge measurements are most extensive from 1955 to 1972, after which they are drastically reduced due to the Angolan civil war. The sensitivity of the rainfall fields to spatial interpolation techniques and the density of gauges were evaluated. Satellite based rainfall estimates for the basin are developed for the period from 1991 onwards, based on the Tropical Rainfall Measuring Mission (TRMM) and Special Sensor Microwave Imager (SSM/I) datasets. The consistency between the gauges and satellite estimates was considered. A methodology was developed to allow calibration of the rainfall-runoff hydrological model against rain gauge data from 1960 to 1972, with the prerequisite that the model should be driven by satellite derived rainfall products from 1990 onwards. With the rain gauge data, addition of a single rainfall station (Longa) in regions where stations earlier were lacking was more important than the chosen interpolation method. Comparison of satellite and gauge rainfall outside the basin indicated that the satellite overestimates rainfall by 20%. A non-linear correction was derived by fitting the rainfall frequency characteristics to those of the historical rainfall data. This satellite rainfall dataset was found satisfactory when using the Pitman rainfall-runoff model (Hughes, D., Andersson, L., Wilk, J., Savenije, H.H.G., this issue. Regional calibration of the Pitman model for the Okavango River. Journal of Hydrology). Intensive monitoring in the region is recommended to increase accuracy of the

  12. Simulation of yearly rainfall time series at microscale resolution with actual properties: Intermittency, scale invariance, and rainfall distribution

    NASA Astrophysics Data System (ADS)

    Akrour, Nawal; Chazottes, Aymeric; Verrier, Sébastien; Mallet, Cécile; Barthes, Laurent

    2015-09-01

    Rainfall is a physical phenomenon resulting from the combination of numerous physical processes involving a wide range of scales, from microphysical processes to the general circulation of the atmosphere. Moreover, unlike other geophysical variables such as water vapor concentration, rainfall is characterized by a relaxation behavior that leads to an alternation of wet and dry periods. It follows that rainfall is a complex process which is highly variable both in time and space. Precipitation is thus characterized by the following features: rain/no-rain intermittency, multiple scaling regimes, and extreme events. All these properties are difficult to model simultaneously, especially when a large time and/or space scale domain is required. The aim of this paper is to develop a simulator capable of generating high-resolution rain-rate time series (15 s), the main statistical properties of which are close to an observed rain-rate time series. We also attempt to develop a model having consistent properties even when the fine-resolution-simulated time series are aggregated to a coarser resolution. In order to break the simulation problem down into subcomponents, the authors have focused their attention on several key properties of rainfall. The simulator is based on a sequential approach in which, first, the simulation of rain/no-rain durations permits the retrieval of fractal properties of the rain support. Then, the generation of rain rates through the use of a multifractal, Fractionally Integrated Flux (FIF), model enables the restitution of the rainfall's multifractal properties. This second step includes a denormalization process that was added in order to generate realistic rain-rate distributions.

  13. An observational analysis of warm-sector rainfall characteristics associated with the 21 July 2012 Beijing extreme rainfall event

    NASA Astrophysics Data System (ADS)

    Zhong, Lingzhi; Mu, Rong; Zhang, Dalin; Zhao, Ping; Zhang, Zhiqiang; Wang, Nan

    2015-04-01

    An observational analysis of the multiscale processes leading to the extreme rainfall event in Beijing on 21 July 2012 is performed using rain gauge records, Doppler radar, and satellite products, radiosondes, and atmospheric analysis. This rainstorm process included two heavy rainfall stages in the early afternoon [1300-1400 Beijing Standard time (BST) (0500-0600 UTC)] and the evening (1600-1900 BST), respectively. The first stage exhibited warm-sector rainfall characteristics as it occurred under low-level warm and moist southeasterly flows ahead of a synoptic-scale vortex and a cold front. When the southeasterly flows turned northeastward along a southwest-northeast oriented mountain range in western Beijing, mesoscale convergence centers formed on the windward side of the mountain range in the early afternoon, initiating moist convection. Radar echo showed a northeastward propagation as these flows extended northward. Despite the shallowness of moist convection in the warm sector, atmospheric liquid water content showed the rapid accumulation, and a large amount of supercooled water and/or ice particles was possibly accumulated above the melting level. These appeared to contribute to the occurrence of the largest rainfall rate. During the second stage, as the synoptic-scale vortex moved across Beijing, with southeastward intrusion of its northwesterly flows, the vortex-associated lifting caused the generation of strong updrafts aloft and formed deep convection. This facilitated the further accumulation of supercooled water and/or ice particles above the melting level. Radar echo propagated southeastward. Liquid water showed a decrease in the lower troposphere, and there were strong downdrafts due to evaporation of liquid water particles, which resulted in the relatively weak hourly rainfall rates.

  14. High-resolution stochastic generation of extreme rainfall intensity for urban drainage modelling applications

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    Urban drainage response is highly dependent on the spatial and temporal structure of rainfall. Therefore, measuring and simulating rainfall at a high spatial and temporal resolution is a fundamental step to fully assess urban drainage system reliability and related uncertainties. This is even more relevant when considering extreme rainfall events. However, the current space-time rainfall models have limitations in capturing extreme rainfall intensity statistics for short durations. Here, we use the STREAP (Space-Time Realizations of Areal Precipitation) model, which is a novel stochastic rainfall generator for simulating high-resolution rainfall fields that preserve the spatio-temporal structure of rainfall and its statistical characteristics. The model enables a generation of rain fields at 102 m and minute scales in a fast and computer-efficient way matching the requirements for hydrological analysis of urban drainage systems. The STREAP model was applied successfully in the past to generate high-resolution extreme rainfall intensities over a small domain. A sub-catchment in the city of Luzern (Switzerland) was chosen as a case study to: (i) evaluate the ability of STREAP to disaggregate extreme rainfall intensities for urban drainage applications; (ii) assessing the role of stochastic climate variability of rainfall in flow response and (iii) evaluate the degree of non-linearity between extreme rainfall intensity and system response (i.e. flow) for a small urban catchment. The channel flow at the catchment outlet is simulated by means of a calibrated hydrodynamic sewer model.

  15. Crop Canopy and Residue Rainfall Interception Effects on Water and Crop Growth

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop canopies and residues have been shown to intercept a significant amount of rainfall. However, rainfall or irrigation interception by crops and residues has often been overlooked in hydrologic modelling. Crop canopy interception is controlled by canopy density and rainfall intensity and durati...

  16. Hydrological appraisal of operational weather radar rainfall estimates in the context of different modelling structures

    NASA Astrophysics Data System (ADS)

    Zhu, D.; Xuan, Y.; Cluckie, I.

    2014-01-01

    Radar rainfall estimates have become increasingly available for hydrological modellers over recent years, especially for flood forecasting and warning over poorly gauged catchments. However, the impact of using radar rainfall as compared with conventional raingauge inputs, with respect to various hydrological model structures, remains unclear and yet to be addressed. In the study presented by this paper, we analysed the flow simulations of the upper Medway catchment of southeast England using the UK NIMROD radar rainfall estimates, using three hydrological models based upon three very different structures (e.g. a physically based distributed MIKE SHE model, a lumped conceptual model PDM and an event-based unit hydrograph model PRTF). We focused on the sensitivity of simulations in relation to the storm types and various rainfall intensities. The uncertainty in radar rainfall estimates, scale effects and extreme rainfall were examined in order to quantify the performance of the radar. We found that radar rainfall estimates were lower than raingauge measurements in high rainfall rates; the resolutions of radar rainfall data had insignificant impact at this catchment scale in the case of evenly distributed rainfall events but was obvious otherwise for high-intensity, localised rainfall events with great spatial heterogeneity. As to hydrological model performance, the distributed model had consistent reliable and good performance on peak simulation with all the rainfall types tested in this study.

  17. Hydrological appraisal of operational weather radar rainfall estimates in the context of different modelling structures

    NASA Astrophysics Data System (ADS)

    Zhu, D.; Xuan, Y.; Cluckie, I.

    2013-08-01

    Radar rainfall estimates have become increasingly available for hydrological modellers over recent years, especially for flood forecasting and warning over poorly gauged catchments. However, the impact of using radar rainfall as compared with conventional raingauge inputs, with respect to various hydrological model structures, remains unclear and yet to be addressed. In the study presented by this paper, we analysed the flow simulations of the Upper Medway catchment of Southeast England using the UK NIMROD radar rainfall estimates using three hydrological models based upon three very different structures, e.g. a physically based distributed MIKE SHE model, a lumped conceptual model PDM and an event-based unit hydrograph model PRTF. We focused on the sensitivity of simulations in relation to the storm types and various rainfall intensities. The uncertainty in radar-rainfall estimates, scale effects and extreme rainfall were examined in order to quantify the performance of the radar. We found that radar rainfall estimates were lower than raingauge measurements in high rainfall rates; the resolutions of radar rainfall data had insignificant impact at this catchment scale in the case of evenly distributed rainfall events but was obvious otherwise for high-intensity, localised rainfall events with great spatial heterogeneity. As to hydrological model performance, the distributed model had consistent reliable and good performance on peak simulation with all the rainfall types tested in this study.

  18. Runoff responses to long-term rainfall variability in a shrub-dominated catchment

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this study we investigate how rainfall has changed between two nine year periods (1977e1985 and 2003e2011), and evaluate the effects of changes in rainfall on runoff from a shrub-dominated catchment in the southwestern USA. Analysis of rainfall characteristics shows that between these two periods...

  19. Statistical downscaling with generalized Pareto distribution (Study case: Extreme rainfall estimation)

    NASA Astrophysics Data System (ADS)

    Kinanti, Shynde Limar; Wigena, Aji Hamim; Djuraidah, Anik

    2016-02-01

    Indonesia has tropical climate with small variation of temperature but quite large variation of rainfall. So the rainfall which is an essential climate element related to climate change has to be observed. Climate change may increase the incidence of extreme rainfall that affects flooding in farmland. In order to anticipate the occurrence of extreme rainfall, the information of rainfall forecast is required. Statistical Downscaling (SD) is a technique to model the relationship between global scale data and local scale data. Global Circulation Model (GCM) output is global scale data and rainfall is local scale data. GCM has characteristic non-linear, high dimension, and multicolinierity. These problem can be overcome by principal component analysis (PCA). One of the primary methods for estimating extreme rainfall is generalize Pareto distribution (GPD) regression based on a threshold. The objective of this study is SD modeling based on GPD to predict extreme rainfall. The result show that GPD models can predict extreme rainfall well. Monthly rainfall prediction in January and December show a higher value than the actual data, but predictions follow actual data pettern well, especially during extreme rainfall. February has the highest rainfall that occurred in 2008 with a value of 439 mm/month. This value can be estimated either by prediction on quantile 0.95.

  20. Experimental research of soil erosion using laboratory rainfall simulator

    NASA Astrophysics Data System (ADS)

    Laburda, Tomáš; Schwarzová, Pavla; Krása, Josef

    2015-04-01

    Soil erosion has been an important part of research at the Department of Irrigation, Drainage and Landscape Engineering, Czech Technical University in Prague since the 50s of the 20th century. Bigger emphasis was put later on practical methods resulting in acquisition of laboratory rainfall simulator in 1999. This article compares data from simulations done at the laboratory rainfall simulator which is used for experimental measurement of rainfall-runoff processes on soil samples (typical soil type groups) from agriculture land in the Czech Republic. Total 10 soil sets have been tested within 255 simulations (247 rainfall-runoff hours in total) from 2002 to 2014. These soil sets cover wide range of soil types from silty clay loam to sandy loam soils or from impervious to pervious soils. Setting values of rainfall intensity (40 to 60 mm/hr), inclination (longitudinal slope from 4° to 8°) and initial condition of surface runoff (crusted or loosened) present primary parameters of every experiment. On the basis of different combinations of setting, 2 representative evaluation states of the minimum (min LC) and maximum (max LC) load conditions were established. The most important data obtained at the Simulator are soil moisture content, progression of surface runoff, soil loss and infiltration. Results clearly show dependence of initial moisture content on physical properties, when impervious soils with high fraction of clay reach over 30 % wt., pervious soils with high fraction of sand achieve initial average moisture content only about 20 % wt. Results of steady-state values of surface runoff and soil loss for minimum and maximum load conditions and its ratio show that highest increase of values due to higher load conditions reach silt loamy soil (Horomerice), silt clay loamy soil (Klapy) and loamy soil (Vsetaty), while the lowest increase reach silt loamy soil (Trebsin I) and sandy loamy soil (Trebesice I). General trend in all cases is obviously to increase both

  1. Rainfall and the length of the growing season in Nigeria

    NASA Astrophysics Data System (ADS)

    Odekunle, T. O.

    2004-03-01

    This study examines the length of the growing season in Nigeria using the daily rainfall data of Ikeja, Ondo, Ilorin, Kaduna and Kano. The data were collected from the archives of the Nigerian Meteorological Services, Oshodi, Lagos. The length of the growing season was determined using the cumulative percentage mean rainfall and daily rainfall probability methods.Although rainfall in Ikeja, Ondo, Ilorin, Kaduna, and Kano appears to commence around the end of the second dekad of March, middle of the third dekad of March, mid April, end of the first dekad of May, and early June respectively, its distribution characteristics at the respective stations remain inadequate for crop germination, establishment, and development till the end of the second dekad of May, early third dekad of May, mid third dekad of May, end of May, and end of the first dekad of July respectively. Also, rainfall at the various stations appears to retreat starting from the early third dekad of October, early third dekad of October, end of the first dekad of October, end of September, and early second dekad of September respectively, but its distribution characteristics only remain adequate for crop development at the respective stations till around the end of the second dekad of October, end of the second dekad of October, middle of the first dekad of October, early October, and middle of the first dekad of September respectively. Thus, the active lengths of the growing season are approximately 5 months, 5 months, 4 months, 4 months, and 2 months respectively. Plants that are short-dry-spell tolerant may thrive early in the rainy season, i.e. from the end of the second dekad of March to the end of the second dekad of May (in Ikeja), middle of the third dekad of March to the early third dekad of May (in Ondo), mid April to the middle of the third dekad of May (in Ilorin), end of the first dekad of May to end of May (in Kaduna), and early June to the end of the first dekad in July (in Kano), but

  2. Analysis of spatial variability of extreme rainfall at radar subpixel scale using IDF curves

    NASA Astrophysics Data System (ADS)

    Peleg, Nadav; Marra, Francesco; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

    2016-04-01

    Extreme rainfall is quantified in engineering practice using Intensity-Duration-Frequency curves (IDFs) that are traditionally derived from rain-gauges and, more recently, also from weather radars. These instruments measure rainfall at different spatial scales: rain-gauge samples rainfall at the point scale while weather radar averages precipitation over a relatively large area, generally around 1 km2. As such, a radar derived IDF curve is representative of the mean areal rainfall over a given radar pixel and neglects the within-pixel rainfall variability. In this study, we quantify subpixel variability of extreme rainfall by using a novel space-time rainfall generator (STREAP model) that downscales in space the rainfall within a given radar pixel. The study was conducted using a long radar data record (23 years) and a very dense rain-gauge network in the Eastern Mediterranean area. Radar-IDF curves, together with an ensemble of point-based IDF curves representing the radar subpixel extreme rainfall variability, were developed fitting GEV distributions to annual rainfall maxima. It was found that the mean areal extreme rainfall derived from the radar underestimate most of the extreme values computed for point locations within the radar pixel. The subpixel variability of extreme rainfall was found to increase with longer return periods and shorter durations. For the longer return periods, a considerable enhancement of extreme rainfall variability was found when stochastic (natural) climate variability was taken into account. Bounding the range of the subpixel extreme rainfall derived from radar-IDF can be of major importance for applications that require very local estimates of rainfall extremes.

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  4. Organization of vertical shear of wind and daily variability of monsoon rainfall

    NASA Astrophysics Data System (ADS)

    Gouda, K. C.; Goswami, P.

    2016-02-01

    Very little is known about the mechanisms that govern the day to day variability of the Indian summer monsoon (ISM) rainfall; in the current dominant view, the daily rainfall is essentially a result of chaotic dynamics. Most studies in the past have thus considered monsoon in terms of its seasonal (June-September) or monthly rainfall. We show here that the daily rainfall in June is associated with vertical shear of horizontal winds at specific scales. While vertical shear had been used in the past to investigate interannual variability of seasonal rainfall, rarely any effort has been made to examine daily rainfall. Our work shows that, at least during June, the daily rainfall variability of ISM rainfall is associated with a large scale dynamical coherence in the sense that the vertical shear averaged over large spatial extents are significantly correlated with area-averaged daily rainfall. An important finding from our work is the existence of a clearly delineated monsoon shear domain (MSD) with strong coherence between area-averaged shear and area-averaged daily rainfall in June; this association of daily rainfall is not significant with shear over only MSD. Another important feature is that the association between daily rainfall and vertical shear is present only during the month of June. Thus while ISM (June-September) is a single seasonal system, it is important to consider the dynamics and variation of June independently of the seasonal ISM rainfall. The association between large-scale organization of circulation and daily rainfall is suggested as a basis for attempting prediction of daily rainfall by ensuring accurate simulation of wind shear.