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Sample records for mesoscale hydrological ensemble

  1. The Hydrologic Ensemble Prediction Experiment (HEPEX)

    Science.gov (United States)

    Wood, A. W.; Thielen, J.; Pappenberger, F.; Schaake, J. C.; Hartman, R. K.

    2012-12-01

    The Hydrologic Ensemble Prediction Experiment was established in March, 2004, at a workshop hosted by the European Center for Medium Range Weather Forecasting (ECMWF). With support from the US National Weather Service (NWS) and the European Commission (EC), the HEPEX goal was to bring the international hydrological and meteorological communities together to advance the understanding and adoption of hydrological ensemble forecasts for decision support in emergency management and water resources sectors. The strategy to meet this goal includes meetings that connect the user, forecast producer and research communities to exchange ideas, data and methods; the coordination of experiments to address specific challenges; and the formation of testbeds to facilitate shared experimentation. HEPEX has organized about a dozen international workshops, as well as sessions at scientific meetings (including AMS, AGU and EGU) and special issues of scientific journals where workshop results have been published. Today, the HEPEX mission is to demonstrate the added value of hydrological ensemble prediction systems (HEPS) for emergency management and water resources sectors to make decisions that have important consequences for economy, public health, safety, and the environment. HEPEX is now organised around six major themes that represent core elements of a hydrologic ensemble prediction enterprise: input and pre-processing, ensemble techniques, data assimilation, post-processing, verification, and communication and use in decision making. This poster presents an overview of recent and planned HEPEX activities, highlighting case studies that exemplify the focus and objectives of HEPEX.

  2. The Hydrologic Ensemble Prediction Experiment (HEPEX)

    Science.gov (United States)

    Wood, Andy; Wetterhall, Fredrik; Ramos, Maria-Helena

    2015-04-01

    The Hydrologic Ensemble Prediction Experiment was established in March, 2004, at a workshop hosted by the European Center for Medium Range Weather Forecasting (ECMWF), and co-sponsored by the US National Weather Service (NWS) and the European Commission (EC). The HEPEX goal was to bring the international hydrological and meteorological communities together to advance the understanding and adoption of hydrological ensemble forecasts for decision support. HEPEX pursues this goal through research efforts and practical implementations involving six core elements of a hydrologic ensemble prediction enterprise: input and pre-processing, ensemble techniques, data assimilation, post-processing, verification, and communication and use in decision making. HEPEX has grown through meetings that connect the user, forecast producer and research communities to exchange ideas, data and methods; the coordination of experiments to address specific challenges; and the formation of testbeds to facilitate shared experimentation. In the last decade, HEPEX has organized over a dozen international workshops, as well as sessions at scientific meetings (including AMS, AGU and EGU) and special issues of scientific journals where workshop results have been published. Through these interactions and an active online blog (www.hepex.org), HEPEX has built a strong and active community of nearly 400 researchers & practitioners around the world. This poster presents an overview of recent and planned HEPEX activities, highlighting case studies that exemplify the focus and objectives of HEPEX.

  3. Ensemble modelling of nitrogen fluxes: data fusion for a Swedish meso-scale catchment

    Directory of Open Access Journals (Sweden)

    J.-F. Exbrayat

    2010-12-01

    Full Text Available Model predictions of biogeochemical fluxes at the landscape scale are highly uncertain, both with respect to stochastic (parameter and structural uncertainty. In this study 5 different models (LASCAM, LASCAM-S, a self-developed tool, SWAT and HBV-N-D designed to simulate hydrological fluxes as well as mobilisation and transport of one or several nitrogen species were applied to the mesoscale River Fyris catchment in mid-eastern Sweden.

    Hydrological calibration against 5 years of recorded daily discharge at two stations gave highly variable results with Nash-Sutcliffe Efficiency (NSE ranging between 0.48 and 0.83. Using the calibrated hydrological parameter sets, the parameter uncertainty linked to the nitrogen parameters was explored in order to cover the range of possible predictions of exported loads for 3 nitrogen species: nitrate (NO3, ammonium (NH4 and total nitrogen (Tot-N. For each model and each nitrogen species, predictions were ranked in two different ways according to the performance indicated by two different goodness-of-fit measures: the coefficient of determination R2 and the root mean square error RMSE. A total of 2160 deterministic Single Model Ensembles (SME was generated using an increasing number of members (from the 2 best to the 10 best single predictions. Finally the best SME for each model, nitrogen species and discharge station were selected and merged into 330 different Multi-Model Ensembles (MME. The evolution of changes in R2 and RMSE was used as a performance descriptor of the ensemble procedure.

    In each studied case, numerous ensemble merging schemes were identified which outperformed any of their members. Improvement rates were generally higher when worse members were introduced. The highest improvements were achieved for the nitrogen SMEs compiled with multiple linear regression models with R2 selected members, which

  4. Data assimilation in integrated hydrological modeling using ensemble Kalman filtering

    DEFF Research Database (Denmark)

    Rasmussen, Jørn; Madsen, H.; Jensen, Karsten Høgh

    2015-01-01

    Groundwater head and stream discharge is assimilated using the ensemble transform Kalman filter in an integrated hydrological model with the aim of studying the relationship between the filter performance and the ensemble size. In an attempt to reduce the required number of ensemble members...... and estimating parameters requires a much larger ensemble size than just assimilating groundwater head observations. However, the required ensemble size can be greatly reduced with the use of adaptive localization, which by far outperforms distance-based localization. The study is conducted using synthetic data...

  5. Operational hydrological forecasting in Bavaria. Part II: Ensemble forecasting

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    Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

    2009-04-01

    In part I of this study, the operational flood forecasting system in Bavaria and an approach to identify and quantify forecast uncertainty was introduced. The approach is split into the calculation of an empirical 'overall error' from archived forecasts and the calculation of an empirical 'model error' based on hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The 'model error' can especially in upstream catchments where forecast uncertainty is strongly dependent on the current predictability of the atrmosphere be superimposed on the spread of a hydrometeorological ensemble forecast. In Bavaria, two meteorological ensemble prediction systems are currently tested for operational use: the 16-member COSMO-LEPS forecast and a poor man's ensemble composed of DWD GME, DWD Cosmo-EU, NCEP GFS, Aladin-Austria, MeteoSwiss Cosmo-7. The determination of the overall forecast uncertainty is dependent on the catchment characteristics: 1. Upstream catchment with high influence of weather forecast a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. b) Corresponding to the characteristics of the meteorological ensemble forecast, each resulting forecast hydrograph can be regarded as equally likely. c) The 'model error' distribution, with parameters dependent on hydrological case and lead time, is added to each forecast timestep of each ensemble member d) For each forecast timestep, the overall (i.e. over all 'model error' distribution of each ensemble member) error distribution is calculated e) From this distribution, the uncertainty range on a desired level (here: the 10% and 90% percentile) is extracted and drawn as forecast envelope. f) As the mean or median of an ensemble forecast does not necessarily exhibit meteorologically sound temporal evolution, a single hydrological forecast termed 'lead forecast' is chosen and shown in addition to the uncertainty bounds. This can be

  6. Short-term ensemble radar rainfall forecasts for hydrological applications

    Science.gov (United States)

    Codo de Oliveira, M.; Rico-Ramirez, M. A.

    2016-12-01

    Flooding is a very common natural disaster around the world, putting local population and economy at risk. Forecasting floods several hours ahead and issuing warnings are of main importance to permit proper response in emergency situations. However, it is important to know the uncertainties related to the rainfall forecasting in order to produce more reliable forecasts. Nowcasting models (short-term rainfall forecasts) are able to produce high spatial and temporal resolution predictions that are useful in hydrological applications. Nonetheless, they are subject to uncertainties mainly due to the nowcasting model used, errors in radar rainfall estimation, temporal development of the velocity field and to the fact that precipitation processes such as growth and decay are not taken into account. In this study an ensemble generation scheme using rain gauge data as a reference to estimate radars errors is used to produce forecasts with up to 3h lead-time. The ensembles try to assess in a realistic way the residual uncertainties that remain even after correction algorithms are applied in the radar data. The ensembles produced are compered to a stochastic ensemble generator. Furthermore, the rainfall forecast output was used as an input in a hydrodynamic sewer network model and also in hydrological model for catchments of different sizes in north England. A comparative analysis was carried of how was carried out to assess how the radar uncertainties propagate into these models. The first named author is grateful to CAPES - Ciencia sem Fronteiras for funding this PhD research.

  7. Ensemble catchment hydrological modelling for climate change impact analysis

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    Vansteenkiste, Thomas; Ntegeka, Victor; Willems, Patrick

    2014-05-01

    It is vital to investigate how the hydrological model structure affects the climate change impact given that future changes not in the range for which the models were calibrated or validated are likely. Thus an ensemble modelling approach which involves a diversity of models with different structures such as spatial resolutions and process descriptions is crucial. The ensemble modelling approach was applied to a set of models: from the lumped conceptual models NAM, PDM and VHM, an intermediate detailed and distributed model WetSpa, to the highly detailed and fully distributed model MIKE-SHE. Explicit focus was given to the high and low flow extremes. All models were calibrated for sub flows and quick flows derived from rainfall and potential evapotranspiration (ETo) time series. In general, all models were able to produce reliable estimates of the flow regimes under the current climate for extreme peak and low flows. An intercomparison of the low and high flow changes under changed climatic conditions was made using climate scenarios tailored for extremes. Tailoring was important for two reasons. First, since the use of many scenarios was not feasible it was necessary to construct few scenarios that would reasonably represent the range of extreme impacts. Second, scenarios would be more informative as changes in high and low flows would be easily traced to changes of ETo and rainfall; the tailored scenarios are constructed using seasonal changes that are defined using different levels of magnitude (high, mean and low) for rainfall and ETo. After simulation of these climate scenarios in the five hydrological models, close agreement was found among the models. The different models predicted similar range of peak flow changes. For the low flows, however, the differences in the projected impact range by different hydrological models was larger, particularly for the drier scenarios. This suggests that the hydrological model structure is critical in low flow predictions

  8. On the incidence of meteorological and hydrological processors: Effect of resolution, sharpness and reliability of hydrological ensemble forecasts

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    Abaza, Mabrouk; Anctil, François; Fortin, Vincent; Perreault, Luc

    2017-12-01

    Meteorological and hydrological ensemble prediction systems are imperfect. Their outputs could often be improved through the use of a statistical processor, opening up the question of the necessity of using both processors (meteorological and hydrological), only one of them, or none. This experiment compares the predictive distributions from four hydrological ensemble prediction systems (H-EPS) utilising the Ensemble Kalman filter (EnKF) probabilistic sequential data assimilation scheme. They differ in the inclusion or not of the Distribution Based Scaling (DBS) method for post-processing meteorological forecasts and the ensemble Bayesian Model Averaging (ensemble BMA) method for hydrological forecast post-processing. The experiment is implemented on three large watersheds and relies on the combination of two meteorological reforecast products: the 4-member Canadian reforecasts from the Canadian Centre for Meteorological and Environmental Prediction (CCMEP) and the 10-member American reforecasts from the National Oceanic and Atmospheric Administration (NOAA), leading to 14 members at each time step. Results show that all four tested H-EPS lead to resolution and sharpness values that are quite similar, with an advantage to DBS + EnKF. The ensemble BMA is unable to compensate for any bias left in the precipitation ensemble forecasts. On the other hand, it succeeds in calibrating ensemble members that are otherwise under-dispersed. If reliability is preferred over resolution and sharpness, DBS + EnKF + ensemble BMA performs best, making use of both processors in the H-EPS system. Conversely, for enhanced resolution and sharpness, DBS is the preferred method.

  9. A Distributed Hydrological model Forced by DIMP2 Data and the WRF Mesoscale model

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    Wayand, N. E.

    2010-12-01

    Forecasted warming over the next century will drastically reduce seasonal snowpack that provides 40% of the world’s drinking water. With increased climate warming, droughts may occur more frequently, which will increase society’s reliance on this same summer snowpack as a water supply. This study aims to reduce driving data errors that lead to poor simulations of snow ablation and accumulation, and streamflow. Results from the Distributed Hydrological Model Intercomparison Project Phase 2 (DMIP2) project using the Distributed Hydrology Soil and Vegetation Model (DHSVM) highlighted the critical need for accurate driving data that distributed models require. Currently, the meteorological driving data for distributed hydrological models commonly rely on interpolation techniques between a network of observational stations, as well as historical monthly means. This method is limited by two significant issues: snowpack is stored at high elevations, where interpolation techniques perform poorly due to sparse observations, and historic climatological means may be unsuitable in a changing climate. Mesoscale models may provide a physically-based approach to supplement surface observations over high-elevation terrain. Initial results have shown that while temperature lapse rates are well represented by multiple mesoscale models, significant precipitation biases are dependent on the particular model microphysics. We evaluate multiple methods of downscaling surface variables from the Weather and Research Forecasting (WRF) model that are then used to drive DHSVM over the North Fork American River basin in California. A comparison between each downscaled driving data set and paired DHSVM results to observations will determine how much improvement in simulated streamflow and snowpack are gained at the expense of each additional degree of downscaling. Our results from DMIP2 will be used as a benchmark for the best available DHSVM run using all available observational data. The

  10. Characterizing Drought Events from a Hydrological Model Ensemble

    Science.gov (United States)

    Smith, Katie; Parry, Simon; Prudhomme, Christel; Hannaford, Jamie; Tanguy, Maliko; Barker, Lucy; Svensson, Cecilia

    2017-04-01

    Hydrological droughts are a slow onset natural hazard that can affect large areas. Within the United Kingdom there have been eight major drought events over the last 50 years, with several events acting at the continental scale, and covering the entire nation. Many of these events have lasted several years and had significant impacts on agriculture, the environment and the economy. Generally in the UK, due to a northwest-southeast gradient in rainfall and relief, as well as varying underlying geology, droughts tend to be most severe in the southeast, which can threaten water supplies to the capital in London. With the impacts of climate change likely to increase the severity and duration of drought events worldwide, it is crucial that we gain an understanding of the characteristics of some of the longer and more extreme droughts of the 19th and 20th centuries, so we may utilize this information in planning for the future. Hydrological models are essential both for reconstructing such events that predate streamflow records, and for use in drought forecasting. However, whilst the uncertainties involved in modelling hydrological extremes on the flooding end of the flow regime have been studied in depth over the past few decades, the uncertainties in simulating droughts and low flow events have not yet received such rigorous academic attention. The "Cascade of Uncertainty" approach has been applied to explore uncertainty and coherence across simulations of notable drought events from the past 50 years using the airGR family of daily lumped catchment models. Parameter uncertainty has been addressed using a Latin Hypercube sampled experiment of 500,000 parameter sets per model (GR4J, GR5J and GR6J), over more than 200 catchments across the UK. The best performing model parameterisations, determined using a multi-objective function approach, have then been taken forward for use in the assessment of the impact of model parameters and model structure on drought event

  11. Ensemble Analysis of Variational Assimilation of Hydrologic and Hydrometeorological Data into Distributed Hydrologic Model

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    Lee, H.; Seo, D.; Koren, V.

    2008-12-01

    A prototype 4DVAR (four-dimensional variational) data assimilator for gridded Sacramento soil-moisture accounting and kinematic-wave routing models in the Hydrology Laboratory's Research Distributed Hydrologic Model (HL-RDHM) has been developed. The prototype assimilates streamflow and in-situ soil moisture data and adjusts gridded precipitation and climatological potential evaporation data to reduce uncertainty in the model initial conditions for improved monitoring and prediction of streamflow and soil moisture at the outlet and interior locations within the catchment. Due to large degrees of freedom involved, data assimilation (DA) into distributed hydrologic models is complex. To understand and assess sensitivity of the performance of DA to uncertainties in the model initial conditions and in the data, two synthetic experiments have been carried out in an ensemble framework. Results from the synthetic experiments shed much light on the potential and limitations with DA into distributed models. For initial real-world assessment, the prototype DA has also been applied to the headwater basin at Eldon near the Oklahoma-Arkansas border. We present these results and describe the next steps.

  12. An evaluation of the Canadian global meteorological ensemble prediction system for short-term hydrological forecasting

    Directory of Open Access Journals (Sweden)

    F. Anctil

    2009-11-01

    Full Text Available Hydrological forecasting consists in the assessment of future streamflow. Current deterministic forecasts do not give any information concerning the uncertainty, which might be limiting in a decision-making process. Ensemble forecasts are expected to fill this gap.

    In July 2007, the Meteorological Service of Canada has improved its ensemble prediction system, which has been operational since 1998. It uses the GEM model to generate a 20-member ensemble on a 100 km grid, at mid-latitudes. This improved system is used for the first time for hydrological ensemble predictions. Five watersheds in Quebec (Canada are studied: Chaudière, Châteauguay, Du Nord, Kénogami and Du Lièvre. An interesting 17-day rainfall event has been selected in October 2007. Forecasts are produced in a 3 h time step for a 3-day forecast horizon. The deterministic forecast is also available and it is compared with the ensemble ones. In order to correct the bias of the ensemble, an updating procedure has been applied to the output data. Results showed that ensemble forecasts are more skilful than the deterministic ones, as measured by the Continuous Ranked Probability Score (CRPS, especially for 72 h forecasts. However, the hydrological ensemble forecasts are under dispersed: a situation that improves with the increasing length of the prediction horizons. We conjecture that this is due in part to the fact that uncertainty in the initial conditions of the hydrological model is not taken into account.

  13. Multimodel hydrological ensemble forecasts for the Baskatong catchment in Canada using the TIGGE database.

    Science.gov (United States)

    Tito Arandia Martinez, Fabian

    2014-05-01

    Adequate uncertainty assessment is an important issue in hydrological modelling. An important issue for hydropower producers is to obtain ensemble forecasts which truly grasp the uncertainty linked to upcoming streamflows. If properly assessed, this uncertainty can lead to optimal reservoir management and energy production (ex. [1]). The meteorological inputs to the hydrological model accounts for an important part of the total uncertainty in streamflow forecasting. Since the creation of the THORPEX initiative and the TIGGE database, access to meteorological ensemble forecasts from nine agencies throughout the world have been made available. This allows for hydrological ensemble forecasts based on multiple meteorological ensemble forecasts. Consequently, both the uncertainty linked to the architecture of the meteorological model and the uncertainty linked to the initial condition of the atmosphere can be accounted for. The main objective of this work is to show that a weighted combination of meteorological ensemble forecasts based on different atmospheric models can lead to improved hydrological ensemble forecasts, for horizons from one to ten days. This experiment is performed for the Baskatong watershed, a head subcatchment of the Gatineau watershed in the province of Quebec, in Canada. Baskatong watershed is of great importance for hydro-power production, as it comprises the main reservoir for the Gatineau watershed, on which there are six hydropower plants managed by Hydro-Québec. Since the 70's, they have been using pseudo ensemble forecast based on deterministic meteorological forecasts to which variability derived from past forecasting errors is added. We use a combination of meteorological ensemble forecasts from different models (precipitation and temperature) as the main inputs for hydrological model HSAMI ([2]). The meteorological ensembles from eight of the nine agencies available through TIGGE are weighted according to their individual performance and

  14. A polynomial chaos ensemble hydrologic prediction system for efficient parameter inference and robust uncertainty assessment

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    Wang, S.; Huang, G. H.; Baetz, B. W.; Huang, W.

    2015-11-01

    This paper presents a polynomial chaos ensemble hydrologic prediction system (PCEHPS) for an efficient and robust uncertainty assessment of model parameters and predictions, in which possibilistic reasoning is infused into probabilistic parameter inference with simultaneous consideration of randomness and fuzziness. The PCEHPS is developed through a two-stage factorial polynomial chaos expansion (PCE) framework, which consists of an ensemble of PCEs to approximate the behavior of the hydrologic model, significantly speeding up the exhaustive sampling of the parameter space. Multiple hypothesis testing is then conducted to construct an ensemble of reduced-dimensionality PCEs with only the most influential terms, which is meaningful for achieving uncertainty reduction and further acceleration of parameter inference. The PCEHPS is applied to the Xiangxi River watershed in China to demonstrate its validity and applicability. A detailed comparison between the HYMOD hydrologic model, the ensemble of PCEs, and the ensemble of reduced PCEs is performed in terms of accuracy and efficiency. Results reveal temporal and spatial variations in parameter sensitivities due to the dynamic behavior of hydrologic systems, and the effects (magnitude and direction) of parametric interactions depending on different hydrological metrics. The case study demonstrates that the PCEHPS is capable not only of capturing both expert knowledge and probabilistic information in the calibration process, but also of implementing an acceleration of more than 10 times faster than the hydrologic model without compromising the predictive accuracy.

  15. Relative effects of statistical preprocessing and postprocessing on a regional hydrological ensemble prediction system

    Science.gov (United States)

    Sharma, Sanjib; Siddique, Ridwan; Reed, Seann; Ahnert, Peter; Mendoza, Pablo; Mejia, Alfonso

    2018-03-01

    The relative roles of statistical weather preprocessing and streamflow postprocessing in hydrological ensemble forecasting at short- to medium-range forecast lead times (day 1-7) are investigated. For this purpose, a regional hydrologic ensemble prediction system (RHEPS) is developed and implemented. The RHEPS is comprised of the following components: (i) hydrometeorological observations (multisensor precipitation estimates, gridded surface temperature, and gauged streamflow); (ii) weather ensemble forecasts (precipitation and near-surface temperature) from the National Centers for Environmental Prediction 11-member Global Ensemble Forecast System Reforecast version 2 (GEFSRv2); (iii) NOAA's Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM); (iv) heteroscedastic censored logistic regression (HCLR) as the statistical preprocessor; (v) two statistical postprocessors, an autoregressive model with a single exogenous variable (ARX(1,1)) and quantile regression (QR); and (vi) a comprehensive verification strategy. To implement the RHEPS, 1 to 7 days weather forecasts from the GEFSRv2 are used to force HL-RDHM and generate raw ensemble streamflow forecasts. Forecasting experiments are conducted in four nested basins in the US Middle Atlantic region, ranging in size from 381 to 12 362 km2. Results show that the HCLR preprocessed ensemble precipitation forecasts have greater skill than the raw forecasts. These improvements are more noticeable in the warm season at the longer lead times (> 3 days). Both postprocessors, ARX(1,1) and QR, show gains in skill relative to the raw ensemble streamflow forecasts, particularly in the cool season, but QR outperforms ARX(1,1). The scenarios that implement preprocessing and postprocessing separately tend to perform similarly, although the postprocessing-alone scenario is often more effective. The scenario involving both preprocessing and postprocessing consistently outperforms the other scenarios. In some cases

  16. A Further Examination of Potential Observation Network Design with Mesoscale Ensemble Sensitivities in Complex Terrain

    Science.gov (United States)

    2013-03-01

    a successful means of determining forecast error in synoptic storms (Hakim and Torn 2008), storms undergoing extratropical transition (Torn and...677. Torn, R. D., and G. J. Hakim, 2009: Initial condition sensitivity of Western-Pacific extratropical transitions determined using ensemble-based

  17. The Potential Observation Network Design with Mesoscale Ensemble Sensitivities in Complex Terrain

    Science.gov (United States)

    2012-03-01

    in synoptic storms , extratropical transition and developing hurricanes. Because they rely on lagged covariances from a finite-sized ensemble, they...diagnose predictors of forecast error in synoptic storms , extratropical transition and developing hurricanes. Because they rely on lagged covariances...sensitivities can be used successfully to diagnose predictors of forecast error in synoptic storms (Torn and Hakim 2008), extratropical transition (Torn and

  18. Examining dynamic interactions among experimental factors influencing hydrologic data assimilation with the ensemble Kalman filter

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    Wang, S.; Huang, G. H.; Baetz, B. W.; Cai, X. M.; Ancell, B. C.; Fan, Y. R.

    2017-11-01

    The ensemble Kalman filter (EnKF) is recognized as a powerful data assimilation technique that generates an ensemble of model variables through stochastic perturbations of forcing data and observations. However, relatively little guidance exists with regard to the proper specification of the magnitude of the perturbation and the ensemble size, posing a significant challenge in optimally implementing the EnKF. This paper presents a robust data assimilation system (RDAS), in which a multi-factorial design of the EnKF experiments is first proposed for hydrologic ensemble predictions. A multi-way analysis of variance is then used to examine potential interactions among factors affecting the EnKF experiments, achieving optimality of the RDAS with maximized performance of hydrologic predictions. The RDAS is applied to the Xiangxi River watershed which is the most representative watershed in China's Three Gorges Reservoir region to demonstrate its validity and applicability. Results reveal that the pairwise interaction between perturbed precipitation and streamflow observations has the most significant impact on the performance of the EnKF system, and their interactions vary dynamically across different settings of the ensemble size and the evapotranspiration perturbation. In addition, the interactions among experimental factors vary greatly in magnitude and direction depending on different statistical metrics for model evaluation including the Nash-Sutcliffe efficiency and the Box-Cox transformed root-mean-square error. It is thus necessary to test various evaluation metrics in order to enhance the robustness of hydrologic prediction systems.

  19. Design and experimentation of an empirical multistructure framework for accurate, sharp and reliable hydrological ensembles

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    Seiller, G.; Anctil, F.; Roy, R.

    2017-09-01

    This paper outlines the design and experimentation of an Empirical Multistructure Framework (EMF) for lumped conceptual hydrological modeling. This concept is inspired from modular frameworks, empirical model development, and multimodel applications, and encompasses the overproduce and select paradigm. The EMF concept aims to reduce subjectivity in conceptual hydrological modeling practice and includes model selection in the optimisation steps, reducing initial assumptions on the prior perception of the dominant rainfall-runoff transformation processes. EMF generates thousands of new modeling options from, for now, twelve parent models that share their functional components and parameters. Optimisation resorts to ensemble calibration, ranking and selection of individual child time series based on optimal bias and reliability trade-offs, as well as accuracy and sharpness improvement of the ensemble. Results on 37 snow-dominated Canadian catchments and 20 climatically-diversified American catchments reveal the excellent potential of the EMF in generating new individual model alternatives, with high respective performance values, that may be pooled efficiently into ensembles of seven to sixty constitutive members, with low bias and high accuracy, sharpness, and reliability. A group of 1446 new models is highlighted to offer good potential on other catchments or applications, based on their individual and collective interests. An analysis of the preferred functional components reveals the importance of the production and total flow elements. Overall, results from this research confirm the added value of ensemble and flexible approaches for hydrological applications, especially in uncertain contexts, and open up new modeling possibilities.

  20. Mesoscale cavities in hollow-core waveguides for quantum optics with atomic ensembles

    Directory of Open Access Journals (Sweden)

    Haapamaki C.M.

    2016-08-01

    Full Text Available Single-mode hollow-core waveguides loaded with atomic ensembles offer an excellent platform for light–matter interactions and nonlinear optics at low photon levels. We review and discuss possible approaches for incorporating mirrors, cavities, and Bragg gratings into these waveguides without obstructing their hollow cores. With these additional features controlling the light propagation in the hollow-core waveguides, one could potentially achieve optical nonlinearities controllable by single photons in systems with small footprints that can be integrated on a chip. We propose possible applications such as single-photon transistors and superradiant lasers that could be implemented in these enhanced hollow-core waveguides.

  1. Improvement of Hydrological Simulations by Applying Daily Precipitation Interpolation Schemes in Meso-Scale Catchments

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    Mateusz Szcześniak

    2015-02-01

    Full Text Available Ground-based precipitation data are still the dominant input type for hydrological models. Spatial variability in precipitation can be represented by spatially interpolating gauge data using various techniques. In this study, the effect of daily precipitation interpolation methods on discharge simulations using the semi-distributed SWAT (Soil and Water Assessment Tool model over a 30-year period is examined. The study was carried out in 11 meso-scale (119–3935 km2 sub-catchments lying in the Sulejów reservoir catchment in central Poland. Four methods were tested: the default SWAT method (Def based on the Nearest Neighbour technique, Thiessen Polygons (TP, Inverse Distance Weighted (IDW and Ordinary Kriging (OK. =The evaluation of methods was performed using a semi-automated calibration program SUFI-2 (Sequential Uncertainty Fitting Procedure Version 2 with two objective functions: Nash-Sutcliffe Efficiency (NSE and the adjusted R2 coefficient (bR2. The results show that: (1 the most complex OK method outperformed other methods in terms of NSE; and (2 OK, IDW, and TP outperformed Def in terms of bR2. The median difference in daily/monthly NSE between OK and Def/TP/IDW calculated across all catchments ranged between 0.05 and 0.15, while the median difference between TP/IDW/OK and Def ranged between 0.05 and 0.07. The differences between pairs of interpolation methods were, however, spatially variable and a part of this variability was attributed to catchment properties: catchments characterised by low station density and low coefficient of variation of daily flows experienced more pronounced improvement resulting from using interpolation methods. Methods providing higher precipitation estimates often resulted in a better model performance. The implication from this study is that appropriate consideration of spatial precipitation variability (often neglected by model users that can be achieved using relatively simple interpolation methods can

  2. Development of computational infrastructure to support hyper-resolution large-ensemble hydrology simulations from local-to-continental scales

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    National Aeronautics and Space Administration — Development of computational infrastructure to support hyper-resolution large-ensemble hydrology simulations from local-to-continental scales A move is currently...

  3. Transferability of hydrological models and ensemble averaging methods between contrasting climatic periods

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    Broderick, Ciaran; Matthews, Tom; Wilby, Robert L.; Bastola, Satish; Murphy, Conor

    2016-10-01

    Understanding hydrological model predictive capabilities under contrasting climate conditions enables more robust decision making. Using Differential Split Sample Testing (DSST), we analyze the performance of six hydrological models for 37 Irish catchments under climate conditions unlike those used for model training. Additionally, we consider four ensemble averaging techniques when examining interperiod transferability. DSST is conducted using 2/3 year noncontinuous blocks of (i) the wettest/driest years on record based on precipitation totals and (ii) years with a more/less pronounced seasonal precipitation regime. Model transferability between contrasting regimes was found to vary depending on the testing scenario, catchment, and evaluation criteria considered. As expected, the ensemble average outperformed most individual ensemble members. However, averaging techniques differed considerably in the number of times they surpassed the best individual model member. Bayesian Model Averaging (BMA) and the Granger-Ramanathan Averaging (GRA) method were found to outperform the simple arithmetic mean (SAM) and Akaike Information Criteria Averaging (AICA). Here GRA performed better than the best individual model in 51%-86% of cases (according to the Nash-Sutcliffe criterion). When assessing model predictive skill under climate change conditions we recommend (i) setting up DSST to select the best available analogues of expected annual mean and seasonal climate conditions; (ii) applying multiple performance criteria; (iii) testing transferability using a diverse set of catchments; and (iv) using a multimodel ensemble in conjunction with an appropriate averaging technique. Given the computational efficiency and performance of GRA relative to BMA, the former is recommended as the preferred ensemble averaging technique for climate assessment.

  4. Development and verification of a new wind speed forecasting system using an ensemble Kalman filter data assimilation technique in a fully coupled hydrologic and atmospheric model

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    Williams, John L.; Maxwell, Reed M.; Monache, Luca Delle

    2013-12-01

    Wind power is rapidly gaining prominence as a major source of renewable energy. Harnessing this promising energy source is challenging because of the chaotic nature of wind and its inherently intermittent nature. Accurate forecasting tools are critical to support the integration of wind energy into power grids and to maximize its impact on renewable energy portfolios. We have adapted the Data Assimilation Research Testbed (DART), a community software facility which includes the ensemble Kalman filter (EnKF) algorithm, to expand our capability to use observational data to improve forecasts produced with a fully coupled hydrologic and atmospheric modeling system, the ParFlow (PF) hydrologic model and the Weather Research and Forecasting (WRF) mesoscale atmospheric model, coupled via mass and energy fluxes across the land surface, and resulting in the PF.WRF model. Numerous studies have shown that soil moisture distribution and land surface vegetative processes profoundly influence atmospheric boundary layer development and weather processes on local and regional scales. We have used the PF.WRF model to explore the connections between the land surface and the atmosphere in terms of land surface energy flux partitioning and coupled variable fields including hydraulic conductivity, soil moisture, and wind speed and demonstrated that reductions in uncertainty in these coupled fields realized through assimilation of soil moisture observations propagate through the hydrologic and atmospheric system. The sensitivities found in this study will enable further studies to optimize observation strategies to maximize the utility of the PF.WRF-DART forecasting system.

  5. The state of the art of flood forecasting - Hydrological Ensemble Prediction Systems

    Science.gov (United States)

    Thielen-Del Pozo, J.; Pappenberger, F.; Salamon, P.; Bogner, K.; Burek, P.; de Roo, A.

    2010-09-01

    Flood forecasting systems form a key part of ‘preparedness' strategies for disastrous floods and provide hydrological services, civil protection authorities and the public with information of upcoming events. Provided the warning leadtime is sufficiently long, adequate preparatory actions can be taken to efficiently reduce the impacts of the flooding. Because of the specific characteristics of each catchment, varying data availability and end-user demands, the design of the best flood forecasting system may differ from catchment to catchment. However, despite the differences in concept and data needs, there is one underlying issue that spans across all systems. There has been an growing awareness and acceptance that uncertainty is a fundamental issue of flood forecasting and needs to be dealt with at the different spatial and temporal scales as well as the different stages of the flood generating processes. Today, operational flood forecasting centres change increasingly from single deterministic forecasts to probabilistic forecasts with various representations of the different contributions of uncertainty. The move towards these so-called Hydrological Ensemble Prediction Systems (HEPS) in flood forecasting represents the state of the art in forecasting science, following on the success of the use of ensembles for weather forecasting (Buizza et al., 2005) and paralleling the move towards ensemble forecasting in other related disciplines such as climate change predictions. The use of HEPS has been internationally fostered by initiatives such as "The Hydrologic Ensemble Prediction Experiment" (HEPEX), created with the aim to investigate how best to produce, communicate and use hydrologic ensemble forecasts in hydrological short-, medium- und long term prediction of hydrological processes. The advantages of quantifying the different contributions of uncertainty as well as the overall uncertainty to obtain reliable and useful flood forecasts also for extreme events

  6. Estimating predictive hydrological uncertainty by dressing deterministic and ensemble forecasts; a comparison, with application to Meuse and Rhine

    Science.gov (United States)

    Verkade, J. S.; Brown, J. D.; Davids, F.; Reggiani, P.; Weerts, A. H.

    2017-12-01

    Two statistical post-processing approaches for estimation of predictive hydrological uncertainty are compared: (i) 'dressing' of a deterministic forecast by adding a single, combined estimate of both hydrological and meteorological uncertainty and (ii) 'dressing' of an ensemble streamflow forecast by adding an estimate of hydrological uncertainty to each individual streamflow ensemble member. Both approaches aim to produce an estimate of the 'total uncertainty' that captures both the meteorological and hydrological uncertainties. They differ in the degree to which they make use of statistical post-processing techniques. In the 'lumped' approach, both sources of uncertainty are lumped by post-processing deterministic forecasts using their verifying observations. In the 'source-specific' approach, the meteorological uncertainties are estimated by an ensemble of weather forecasts. These ensemble members are routed through a hydrological model and a realization of the probability distribution of hydrological uncertainties (only) is then added to each ensemble member to arrive at an estimate of the total uncertainty. The techniques are applied to one location in the Meuse basin and three locations in the Rhine basin. Resulting forecasts are assessed for their reliability and sharpness, as well as compared in terms of multiple verification scores including the relative mean error, Brier Skill Score, Mean Continuous Ranked Probability Skill Score, Relative Operating Characteristic Score and Relative Economic Value. The dressed deterministic forecasts are generally more reliable than the dressed ensemble forecasts, but the latter are sharper. On balance, however, they show similar quality across a range of verification metrics, with the dressed ensembles coming out slightly better. Some additional analyses are suggested. Notably, these include statistical post-processing of the meteorological forecasts in order to increase their reliability, thus increasing the reliability

  7. Developing an approach to effectively use super ensemble experiments for the projection of hydrological extremes under climate change

    Science.gov (United States)

    Watanabe, S.; Kim, H.; Utsumi, N.

    2017-12-01

    This study aims to develop a new approach which projects hydrology under climate change using super ensemble experiments. The use of multiple ensemble is essential for the estimation of extreme, which is a major issue in the impact assessment of climate change. Hence, the super ensemble experiments are recently conducted by some research programs. While it is necessary to use multiple ensemble, the multiple calculations of hydrological simulation for each output of ensemble simulations needs considerable calculation costs. To effectively use the super ensemble experiments, we adopt a strategy to use runoff projected by climate models directly. The general approach of hydrological projection is to conduct hydrological model simulations which include land-surface and river routing process using atmospheric boundary conditions projected by climate models as inputs. This study, on the other hand, simulates only river routing model using runoff projected by climate models. In general, the climate model output is systematically biased so that a preprocessing which corrects such bias is necessary for impact assessments. Various bias correction methods have been proposed, but, to the best of our knowledge, no method has proposed for variables other than surface meteorology. Here, we newly propose a method for utilizing the projected future runoff directly. The developed method estimates and corrects the bias based on the pseudo-observation which is a result of retrospective offline simulation. We show an application of this approach to the super ensemble experiments conducted under the program of Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI). More than 400 ensemble experiments from multiple climate models are available. The results of the validation using historical simulations by HAPPI indicates that the output of this approach can effectively reproduce retrospective runoff variability. Likewise, the bias of runoff from super ensemble climate

  8. Using stable isotope tracers to assess hydrological flow paths, residence times and landscape influences in a nested mesoscale catchment

    Directory of Open Access Journals (Sweden)

    P. Rodgers

    2005-01-01

    Full Text Available δ18O measurements in precipitation and stream waters were used to investigate hydrological flow paths and residence times at nested spatial scales in the mesoscale (233 km2 River Feugh catchment in the northeast of Scotland over the 2001-2002 hydrological year. Precipitation δ18O exhibited strong seasonal variation, which although significantly damped within the catchment, was reflected in stream water at six sampling sites. This allowed δ18O variations to be used to infer the relative influence of soil-derived storm flows with a seasonally variable isotopic signature, and groundwater of apparently more constant isotopic composition. Periodic regression analysis was then used to examine the sub-catchment difference using an exponential flow model to provide indicative estimates of mean stream water residence times, which varied between approximately 3 and 14 months. This showed that the effects of increasing scale on estimated mean stream water residence time was minimal beyond that of the smallest (ca. 1 km2 headwater catchment scale. Instead, the interaction of catchment soil cover and topography appeared to be the dominant controlling influence. Where sub-catchments had extensive peat coverage, responsive hydrological pathways produced seasonally variable δ18O signatures in runoff with short mean residence times (ca. 3 months. In contrast, areas dominated by steeper slopes, more freely draining soils and larger groundwater storage in shallow valley-bottom aquifers, deeper flow paths allow for more effective mixing and damping of δ18O indicating longer residence times (>12 months. These insights from δ18O measurements extend the hydrological understanding of the Feugh catchment gained from previous geochemical tracer studies, and demonstrate the utility of isotope tracers in investigating the interaction of hydrological processes and catchment characteristics at larger spatial scales.

  9. Building an ensemble of climate scenarios for decision-making in hydrology: benefits, pitfalls and uncertainties

    Science.gov (United States)

    Braun, Marco; Chaumont, Diane

    2013-04-01

    Using climate model output to explore climate change impacts on hydrology requires several considerations, choices and methods in the post treatment of the datasets. In the effort of producing a comprehensive data base of climate change scenarios for over 300 watersheds in the Canadian province of Québec, a selection of state of the art procedures were applied to an ensemble comprising 87 climate simulations. The climate data ensemble is based on global climate simulations from the Coupled Model Intercomparison Project - Phase 3 (CMIP3) and regional climate simulations from the North American Regional Climate Change Assessment Program (NARCCAP) and operational simulations produced at Ouranos. Information on the response of hydrological systems to changing climate conditions can be derived by linking climate simulations with hydrological models. However, the direct use of raw climate model output variables as drivers for hydrological models is limited by issues such as spatial resolution and the calibration of hydro models with observations. Methods for downscaling and bias correcting the data are required to achieve seamless integration of climate simulations with hydro models. The effects on the results of four different approaches to data post processing were explored and compared. We present the lessons learned from building the largest data base yet for multiple stakeholders in the hydro power and water management sector in Québec putting an emphasis on the benefits and pitfalls in choosing simulations, extracting the data, performing bias corrections and documenting the results. A discussion of the sources and significance of uncertainties in the data will also be included. The climatological data base was subsequently used by the state owned hydro power company Hydro-Québec and the Centre d'expertise hydrique du Québec (CEHQ), the provincial water authority, to simulate future stream flows and analyse the impacts on hydrological indicators. While this

  10. Spatially explicit simulation of peatland hydrology and carbon dioxide exchange: Influence of mesoscale topography

    Science.gov (United States)

    Sonnentag, O.; Chen, J. M.; Roulet, N. T.; Ju, W.; Govind, A.

    2008-06-01

    Carbon dynamics in peatlands are controlled, in large part, by their wetness as defined by water table depth and volumetric liquid soil moisture content. A common type of peatland is raised bogs that typically have a multiple-layer canopy of vascular plants over a Sphagnum moss ground cover. Their convex form restricts water supply to precipitation and water is shed toward the margins, usually by lateral subsurface flow. The hydraulic gradient for lateral subsurface flow is governed by the peat surface topography at the mesoscale (˜200 m to 5 km). To investigate the influence of mesoscale topography on wetness, evapotranspiration (ET), and gross primary productivity (GPP) in a bog during the snow-free period, we compare the outputs of a further developed version of the daily Boreal Ecosystem Productivity Simulator (BEPS) with observations made at the Mer Bleue peatland, located near Ottawa, Canada. Explicitly considering mesoscale topography, simulated total ET and GPP correlate well with measured ET (r = 0.91) and derived gross ecosystem productivity (GEP; r = 0.92). Both measured ET and derived GEP are simulated similarly well when mesoscale topography is neglected, but daily simulated values are systematically underestimated by about 10% and 12% on average, respectively, due to greater wetness resulting from the lack of lateral subsurface flow. Owing to the differences in moss surface conductances of water vapor and carbon dioxide with increasing moss water content, the differences in the spatial patterns of simulated total ET and GPP are controlled by the mesotopographic position of the moss ground cover.

  11. Multi-model ensemble hydrological simulation using a BP Neural Network for the upper Yalongjiang River Basin, China

    Science.gov (United States)

    Li, Zhanjie; Yu, Jingshan; Xu, Xinyi; Sun, Wenchao; Pang, Bo; Yue, Jiajia

    2018-06-01

    Hydrological models are important and effective tools for detecting complex hydrological processes. Different models have different strengths when capturing the various aspects of hydrological processes. Relying on a single model usually leads to simulation uncertainties. Ensemble approaches, based on multi-model hydrological simulations, can improve application performance over single models. In this study, the upper Yalongjiang River Basin was selected for a case study. Three commonly used hydrological models (SWAT, VIC, and BTOPMC) were selected and used for independent simulations with the same input and initial values. Then, the BP neural network method was employed to combine the results from the three models. The results show that the accuracy of BP ensemble simulation is better than that of the single models.

  12. Validation of a mesoscale hydrological model in a small-scale forested catchment

    Czech Academy of Sciences Publication Activity Database

    Šípek, Václav; Tesař, Miroslav

    2016-01-01

    Roč. 47, č. 1 (2016), s. 27-41 ISSN 1998-9563 R&D Projects: GA TA ČR TA02021451 Institutional support: RVO:67985874 Keywords : hydrological modelling * small catchment * soil moisture * subsurface lateral flow * SWIM Subject RIV: DA - Hydrology ; Limnology Impact factor: 1.754, year: 2016

  13. Simplifying a hydrological ensemble prediction system with a backward greedy selection of members – Part 1: Optimization criteria

    Directory of Open Access Journals (Sweden)

    D. Brochero

    2011-11-01

    Full Text Available Hydrological Ensemble Prediction Systems (HEPS, obtained by forcing rainfall-runoff models with Meteorological Ensemble Prediction Systems (MEPS, have been recognized as useful approaches to quantify uncertainties of hydrological forecasting systems. This task is complex both in terms of the coupling of information and computational time, which may create an operational barrier. The main objective of the current work is to assess the degree of simplification (reduction of the number of hydrological members that can be achieved with a HEPS configured using 16 lumped hydrological models driven by the 50 weather ensemble forecasts from the European Centre for Medium-range Weather Forecasts (ECMWF. Here, Backward Greedy Selection (BGS is proposed to assess the weight that each model must represent within a subset that offers similar or better performance than a reference set of 800 hydrological members. These hydrological models' weights represent the participation of each hydrological model within a simplified HEPS which would issue real-time forecasts in a relatively short computational time. The methodology uses a variation of the k-fold cross-validation, allowing an optimal use of the information, and employs a multi-criterion framework that represents the combination of resolution, reliability, consistency, and diversity. Results show that the degree of reduction of members can be established in terms of maximum number of members required (complexity of the HEPS or the maximization of the relationship between the different scores (performance.

  14. Improving Robustness of Hydrologic Ensemble Predictions Through Probabilistic Pre- and Post-Processing in Sequential Data Assimilation

    Science.gov (United States)

    Wang, S.; Ancell, B. C.; Huang, G. H.; Baetz, B. W.

    2018-03-01

    Data assimilation using the ensemble Kalman filter (EnKF) has been increasingly recognized as a promising tool for probabilistic hydrologic predictions. However, little effort has been made to conduct the pre- and post-processing of assimilation experiments, posing a significant challenge in achieving the best performance of hydrologic predictions. This paper presents a unified data assimilation framework for improving the robustness of hydrologic ensemble predictions. Statistical pre-processing of assimilation experiments is conducted through the factorial design and analysis to identify the best EnKF settings with maximized performance. After the data assimilation operation, statistical post-processing analysis is also performed through the factorial polynomial chaos expansion to efficiently address uncertainties in hydrologic predictions, as well as to explicitly reveal potential interactions among model parameters and their contributions to the predictive accuracy. In addition, the Gaussian anamorphosis is used to establish a seamless bridge between data assimilation and uncertainty quantification of hydrologic predictions. Both synthetic and real data assimilation experiments are carried out to demonstrate feasibility and applicability of the proposed methodology in the Guadalupe River basin, Texas. Results suggest that statistical pre- and post-processing of data assimilation experiments provide meaningful insights into the dynamic behavior of hydrologic systems and enhance robustness of hydrologic ensemble predictions.

  15. Evaluation of drought propagation in an ensemble mean of large-scale hydrological models

    Directory of Open Access Journals (Sweden)

    A. F. Van Loon

    2012-11-01

    Full Text Available Hydrological drought is increasingly studied using large-scale models. It is, however, not sure whether large-scale models reproduce the development of hydrological drought correctly. The pressing question is how well do large-scale models simulate the propagation from meteorological to hydrological drought? To answer this question, we evaluated the simulation of drought propagation in an ensemble mean of ten large-scale models, both land-surface models and global hydrological models, that participated in the model intercomparison project of WATCH (WaterMIP. For a selection of case study areas, we studied drought characteristics (number of droughts, duration, severity, drought propagation features (pooling, attenuation, lag, lengthening, and hydrological drought typology (classical rainfall deficit drought, rain-to-snow-season drought, wet-to-dry-season drought, cold snow season drought, warm snow season drought, composite drought.

    Drought characteristics simulated by large-scale models clearly reflected drought propagation; i.e. drought events became fewer and longer when moving through the hydrological cycle. However, more differentiation was expected between fast and slowly responding systems, with slowly responding systems having fewer and longer droughts in runoff than fast responding systems. This was not found using large-scale models. Drought propagation features were poorly reproduced by the large-scale models, because runoff reacted immediately to precipitation, in all case study areas. This fast reaction to precipitation, even in cold climates in winter and in semi-arid climates in summer, also greatly influenced the hydrological drought typology as identified by the large-scale models. In general, the large-scale models had the correct representation of drought types, but the percentages of occurrence had some important mismatches, e.g. an overestimation of classical rainfall deficit droughts, and an

  16. Comprehensive Performance Evaluation for Hydrological and Nutrients Simulation Using the Hydrological Simulation Program-Fortran in a Mesoscale Monsoon Watershed, China.

    Science.gov (United States)

    Li, Zhaofu; Luo, Chuan; Jiang, Kaixia; Wan, Rongrong; Li, Hengpeng

    2017-12-19

    The Hydrological Simulation Program-Fortran (HSPF) is a hydrological and water quality computer model that was developed by the United States Environmental Protection Agency. Comprehensive performance evaluations were carried out for hydrological and nutrient simulation using the HSPF model in the Xitiaoxi watershed in China. Streamflow simulation was calibrated from 1 January 2002 to 31 December 2007 and then validated from 1 January 2008 to 31 December 2010 using daily observed data, and nutrient simulation was calibrated and validated using monthly observed data during the period from July 2009 to July 2010. These results of model performance evaluation showed that the streamflows were well simulated over the study period. The determination coefficient ( R ²) was 0.87, 0.77 and 0.63, and the Nash-Sutcliffe coefficient of efficiency (Ens) was 0.82, 0.76 and 0.65 for the streamflow simulation in annual, monthly and daily time-steps, respectively. Although limited to monthly observed data, satisfactory performance was still achieved during the quantitative evaluation for nutrients. The R ² was 0.73, 0.82 and 0.92, and the Ens was 0.67, 0.74 and 0.86 for nitrate, ammonium and orthophosphate simulation, respectively. Some issues may affect the application of HSPF were also discussed, such as input data quality, parameter values, etc. Overall, the HSPF model can be successfully used to describe streamflow and nutrients transport in the mesoscale watershed located in the East Asian monsoon climate area. This study is expected to serve as a comprehensive and systematic documentation of understanding the HSPF model for wide application and avoiding possible misuses.

  17. Ensemble cloud-resolving modelling of a historic back-building mesoscale convective system over Liguria: the San Fruttuoso case of 1915

    Science.gov (United States)

    Parodi, Antonio; Ferraris, Luca; Gallus, William; Maugeri, Maurizio; Molini, Luca; Siccardi, Franco; Boni, Giorgio

    2017-05-01

    Highly localized and persistent back-building mesoscale convective systems represent one of the most dangerous flash-flood-producing storms in the north-western Mediterranean area. Substantial warming of the Mediterranean Sea in recent decades raises concerns over possible increases in frequency or intensity of these types of events as increased atmospheric temperatures generally support increases in water vapour content. However, analyses of the historical record do not provide a univocal answer, but these are likely affected by a lack of detailed observations for older events. In the present study, 20th Century Reanalysis Project initial and boundary condition data in ensemble mode are used to address the feasibility of performing cloud-resolving simulations with 1 km horizontal grid spacing of a historic extreme event that occurred over Liguria: the San Fruttuoso case of 1915. The proposed approach focuses on the ensemble Weather Research and Forecasting (WRF) model runs that show strong convergence over the Ligurian Sea (17 out of 56 members) as these runs are the ones most likely to best simulate the event. It is found that these WRF runs generally do show wind and precipitation fields that are consistent with the occurrence of highly localized and persistent back-building mesoscale convective systems, although precipitation peak amounts are underestimated. Systematic small north-westward position errors with regard to the heaviest rain and strongest convergence areas imply that the reanalysis members may not be adequately representing the amount of cool air over the Po Plain outflowing into the Ligurian Sea through the Apennines gap. Regarding the role of historical data sources, this study shows that in addition to reanalysis products, unconventional data, such as historical meteorological bulletins, newspapers, and even photographs, can be very valuable sources of knowledge in the reconstruction of past extreme events.

  18. A two-update ensemble Kalman filter for land hydrological data assimilation with an uncertain constraint

    Science.gov (United States)

    Khaki, M.; Ait-El-Fquih, B.; Hoteit, I.; Forootan, E.; Awange, J.; Kuhn, M.

    2017-12-01

    Assimilating Gravity Recovery And Climate Experiment (GRACE) data into land hydrological models provides a valuable opportunity to improve the models' forecasts and increases our knowledge of terrestrial water storages (TWS). The assimilation, however, may harm the consistency between hydrological water fluxes, namely precipitation, evaporation, discharge, and water storage changes. To address this issue, we propose a weak constrained ensemble Kalman filter (WCEnKF) that maintains estimated water budgets in balance with other water fluxes. Therefore, in this study, GRACE terrestrial water storages data are assimilated into the World-Wide Water Resources Assessment (W3RA) hydrological model over the Earth's land areas covering 2002-2012. Multi-mission remotely sensed precipitation measurements from the Tropical Rainfall Measuring Mission (TRMM) and evaporation products from the Moderate Resolution Imaging Spectroradiometer (MODIS), as well as ground-based water discharge measurements are applied to close the water balance equation. The proposed WCEnKF contains two update steps; first, it incorporates observations from GRACE to improve model simulations of water storages, and second, uses the additional observations of precipitation, evaporation, and water discharge to establish the water budget closure. These steps are designed to account for error information associated with the included observation sets during the assimilation process. In order to evaluate the assimilation results, in addition to monitoring the water budget closure errors, in situ groundwater measurements over the Mississippi River Basin in the US and the Murray-Darling Basin in Australia are used. Our results indicate approximately 24% improvement in the WCEnKF groundwater estimates over both basins compared to the use of (constraint-free) EnKF. WCEnKF also further reduces imbalance errors by approximately 82.53% (on average) and at the same time increases the correlations between the

  19. A Two-update Ensemble Kalman Filter for Land Hydrological Data Assimilation with an Uncertain Constraint

    KAUST Repository

    Khaki, M.

    2017-10-25

    Assimilating Gravity Recovery And Climate Experiment (GRACE) data into land hydrological models provides a valuable opportunity to improve the models’ forecasts and increases our knowledge of terrestrial water storages (TWS). The assimilation, however, may harm the consistency between hydrological water fluxes, namely precipitation, evaporation, discharge, and water storage changes. To address this issue, we propose a weak constrained ensemble Kalman filter (WCEnKF) that maintains estimated water budgets in balance with other water fluxes. Therefore, in this study, GRACE terrestrial water storages data are assimilated into the World-Wide Water Resources Assessment (W3RA) hydrological model over the Earth’s land areas covering 2002 – 2012. Multi-mission remotely sensed precipitation measurements from the Tropical Rainfall Measuring Mission (TRMM) and evaporation products from the Moderate Resolution Imaging Spectroradiometer (MODIS), as well as ground-based water discharge measurements are applied to close the water balance equation. The proposed WCEnKF contains two update steps; first, it incorporates observations from GRACE to improve model simulations of water storages, and second, uses the additional observations of precipitation, evaporation, and water discharge to establish the water budget closure. These steps are designed to account for error information associated with the included observation sets during the assimilation process. In order to evaluate the assimilation results, in addition to monitoring the water budget closure errors, in-situ groundwater measurements over the Mississippi River Basin in the US and the Murray-Darling Basin in Australia are used. Our results indicate approximately 24% improvement in the WCEnKF groundwater estimates over both basins compared to the use of (constraint-free) EnKF. WCEnKF also further reduces imbalance errors by approximately 82.53% (on average) and at the same time increases the correlations between the

  20. Mesoscale modeling of smoke transport from equatorial Southeast Asian Maritime Continent to the Philippines: First comparison of ensemble analysis with in situ observations

    Science.gov (United States)

    Ge, Cui; Wang, Jun; Reid, Jeffrey S.; Posselt, Derek J.; Xian, Peng; Hyer, Edward

    2017-05-01

    Atmospheric transport of smoke from equatorial Southeast Asian Maritime Continent (Indonesia, Singapore, and Malaysia) to the Philippines was recently verified by the first-ever measurement of aerosol composition in the region of the Sulu Sea from a research vessel named Vasco. However, numerical modeling of such transport can have large uncertainties due to the lack of observations for parameterization schemes and for describing fire emission and meteorology in this region. These uncertainties are analyzed here, for the first time, with an ensemble of 24 Weather Research and Forecasting model with Chemistry (WRF-Chem) simulations. The ensemble reproduces the time series of observed surface nonsea-salt PM2.5 concentrations observed from the Vasco vessel during 17-30 September 2011 and overall agrees with satellite (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and Moderate Resolution Imaging Spectroradiometer (MODIS)) and Aerosol Robotic Network (AERONET) data. The difference of meteorology between National Centers for Environmental Prediction (NCEP's) Final (FNL) and European Center for Medium range Weather Forecasting (ECMWF's) ERA renders the biggest spread in the ensemble (up to 20 μg m-3 or 200% in surface PM2.5), with FNL showing systematically superior results. The second biggest uncertainty is from fire emissions; the 2 day maximum Fire Locating and Modelling of Burning Emissions (FLAMBE) emission is superior than the instantaneous one. While Grell-Devenyi (G3) and Betts-Miller-Janjić cumulus schemes only produce a difference of 3 μg m-3 of surface PM2.5 over the Sulu Sea, the ensemble mean agrees best with Climate Prediction Center (CPC) MORPHing (CMORPH)'s spatial distribution of precipitation. Simulation with FNL-G3, 2 day maximum FLAMBE, and 800 m injection height outperforms other ensemble members. Finally, the global transport model (Navy Aerosol Analysis and Prediction System (NAAPS)) outperforms all WRF

  1. Network-based Modeling of Mesoscale Catchments - The Hydrology Perspective of Glowa-danube

    Science.gov (United States)

    Ludwig, R.; Escher-Vetter, H.; Hennicker, R.; Mauser, W.; Niemeyer, S.; Reichstein, M.; Tenhunen, J.

    Within the GLOWA initiative of the German Ministry for Research and Educa- tion (BMBF), the project GLOWA-Danube is funded to establish a transdisciplinary network-based decision support tool for water related issues in the Upper Danube wa- tershed. It aims to develop and validate integration techniques, integrated models and integrated monitoring procedures and to implement them in the network-based De- cision Support System DANUBIA. An accurate description of processes involved in energy, water and matter fluxes and turnovers requires an intense collaboration and exchange of water related expertise of different scientific disciplines. DANUBIA is conceived as a distributed expert network and is developed on the basis of re-useable, refineable, and documented sub-models. In order to synthesize a common understand- ing between the project partners, a standardized notation of parameters and functions and a platform-independent structure of computational methods and interfaces has been established using the Unified Modeling Language UML. DANUBIA is object- oriented, spatially distributed and raster-based at its core. It applies the concept of "proxels" (Process Pixel) as its basic object, which has different dimensions depend- ing on the viewing scale and connects to its environment through fluxes. The presented study excerpts the hydrological view point of GLOWA-Danube, its approach of model coupling and network based communication (using the Remote Method Invocation RMI), the object-oriented technology to simulate physical processes and interactions at the land surface and the methodology to treat the issue of spatial and temporal scal- ing in large, heterogeneous catchments. The mechanisms applied to communicate data and model parameters across the typical discipline borders will be demonstrated from the perspective of a land-surface object, which comprises the capabilities of interde- pendent expert models for snowmelt, soil water movement, runoff formation, plant

  2. A retrospective streamflow ensemble forecast for an extreme hydrologic event: a case study of Hurricane Irene and on the Hudson River basin

    Science.gov (United States)

    Saleh, Firas; Ramaswamy, Venkatsundar; Georgas, Nickitas; Blumberg, Alan F.; Pullen, Julie

    2016-07-01

    This paper investigates the uncertainties in hourly streamflow ensemble forecasts for an extreme hydrological event using a hydrological model forced with short-range ensemble weather prediction models. A state-of-the art, automated, short-term hydrologic prediction framework was implemented using GIS and a regional scale hydrological model (HEC-HMS). The hydrologic framework was applied to the Hudson River basin ( ˜ 36 000 km2) in the United States using gridded precipitation data from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) and was validated against streamflow observations from the United States Geologic Survey (USGS). Finally, 21 precipitation ensemble members of the latest Global Ensemble Forecast System (GEFS/R) were forced into HEC-HMS to generate a retrospective streamflow ensemble forecast for an extreme hydrological event, Hurricane Irene. The work shows that ensemble stream discharge forecasts provide improved predictions and useful information about associated uncertainties, thus improving the assessment of risks when compared with deterministic forecasts. The uncertainties in weather inputs may result in false warnings and missed river flooding events, reducing the potential to effectively mitigate flood damage. The findings demonstrate how errors in the ensemble median streamflow forecast and time of peak, as well as the ensemble spread (uncertainty) are reduced 48 h pre-event by utilizing the ensemble framework. The methodology and implications of this work benefit efforts of short-term streamflow forecasts at regional scales, notably regarding the peak timing of an extreme hydrologic event when combined with a flood threshold exceedance diagram. Although the modeling framework was implemented on the Hudson River basin, it is flexible and applicable in other parts of the world where atmospheric reanalysis products and streamflow data are available.

  3. REAL - Ensemble radar precipitation estimation for hydrology in a mountainous region

    OpenAIRE

    Germann, Urs; Berenguer Ferrer, Marc; Sempere Torres, Daniel; Zappa, Massimiliano

    2009-01-01

    An elegant solution to characterise the residual errors in radar precipitation estimates is to generate an ensemble of precipitation fields. The paper proposes a radar ensemble generator designed for usage in the Alps using LU decomposition (REAL), and presents first results from a real-time implementation coupling the radar ensemble with a semi-distributed rainfall–runoff model for flash flood modelling in a steep Alpine catchment. Each member of the radar ensemble is a possible realisati...

  4. An ensemble approach to assess hydrological models' contribution to uncertainties in the analysis of climate change impact on water resources

    Science.gov (United States)

    Velázquez, J. A.; Schmid, J.; Ricard, S.; Muerth, M. J.; Gauvin St-Denis, B.; Minville, M.; Chaumont, D.; Caya, D.; Ludwig, R.; Turcotte, R.

    2012-06-01

    Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the QBic3 project (Québec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e. lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in Southern Québec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by a given number of GCMs' members over a reference (1971-2000) and a future (2041-2070) periods. The results show that the choice of the hydrological model does strongly affect the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model. Therefore, the computationally less demanding models (usually simple, lumped and conceptual) give a significant level of trust for high and overall mean flows.

  5. A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset

    Directory of Open Access Journals (Sweden)

    J. Schellekens

    2017-07-01

    Full Text Available The dataset presented here consists of an ensemble of 10 global hydrological and land surface models for the period 1979–2012 using a reanalysis-based meteorological forcing dataset (0.5° resolution. The current dataset serves as a state of the art in current global hydrological modelling and as a benchmark for further improvements in the coming years. A signal-to-noise ratio analysis revealed low inter-model agreement over (i snow-dominated regions and (ii tropical rainforest and monsoon areas. The large uncertainty of precipitation in the tropics is not reflected in the ensemble runoff. Verification of the results against benchmark datasets for evapotranspiration, snow cover, snow water equivalent, soil moisture anomaly and total water storage anomaly using the tools from The International Land Model Benchmarking Project (ILAMB showed overall useful model performance, while the ensemble mean generally outperformed the single model estimates. The results also show that there is currently no single best model for all variables and that model performance is spatially variable. In our unconstrained model runs the ensemble mean of total runoff into the ocean was 46 268 km3 yr−1 (334 kg m−2 yr−1, while the ensemble mean of total evaporation was 537 kg m−2 yr−1. All data are made available openly through a Water Cycle Integrator portal (WCI, wci.earth2observe.eu, and via a direct http and ftp download. The portal follows the protocols of the open geospatial consortium such as OPeNDAP, WCS and WMS. The DOI for the data is https://doi.org/10.1016/10.5281/zenodo.167070.

  6. A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset

    Science.gov (United States)

    Schellekens, Jaap; Dutra, Emanuel; Martínez-de la Torre, Alberto; Balsamo, Gianpaolo; van Dijk, Albert; Sperna Weiland, Frederiek; Minvielle, Marie; Calvet, Jean-Christophe; Decharme, Bertrand; Eisner, Stephanie; Fink, Gabriel; Flörke, Martina; Peßenteiner, Stefanie; van Beek, Rens; Polcher, Jan; Beck, Hylke; Orth, René; Calton, Ben; Burke, Sophia; Dorigo, Wouter; Weedon, Graham P.

    2017-07-01

    The dataset presented here consists of an ensemble of 10 global hydrological and land surface models for the period 1979-2012 using a reanalysis-based meteorological forcing dataset (0.5° resolution). The current dataset serves as a state of the art in current global hydrological modelling and as a benchmark for further improvements in the coming years. A signal-to-noise ratio analysis revealed low inter-model agreement over (i) snow-dominated regions and (ii) tropical rainforest and monsoon areas. The large uncertainty of precipitation in the tropics is not reflected in the ensemble runoff. Verification of the results against benchmark datasets for evapotranspiration, snow cover, snow water equivalent, soil moisture anomaly and total water storage anomaly using the tools from The International Land Model Benchmarking Project (ILAMB) showed overall useful model performance, while the ensemble mean generally outperformed the single model estimates. The results also show that there is currently no single best model for all variables and that model performance is spatially variable. In our unconstrained model runs the ensemble mean of total runoff into the ocean was 46 268 km3 yr-1 (334 kg m-2 yr-1), while the ensemble mean of total evaporation was 537 kg m-2 yr-1. All data are made available openly through a Water Cycle Integrator portal (WCI, wci.earth2observe.eu), and via a direct http and ftp download. The portal follows the protocols of the open geospatial consortium such as OPeNDAP, WCS and WMS. The DOI for the data is https://doi.org/10.1016/10.5281/zenodo.167070.

  7. Evaluation of drought propagation in an ensemble mean of large-scale hydrological models

    NARCIS (Netherlands)

    Loon, van A.F.; Huijgevoort, van M.H.J.; Lanen, van H.A.J.

    2012-01-01

    Hydrological drought is increasingly studied using large-scale models. It is, however, not sure whether large-scale models reproduce the development of hydrological drought correctly. The pressing question is how well do large-scale models simulate the propagation from meteorological to hydrological

  8. Inferring catchment precipitation by doing hydrology backward : A test in 24 small and mesoscale catchments in Luxembourg

    NARCIS (Netherlands)

    Krier, R.; Matgen, P.; Goergen, K.; Pfister, L.; Hoffmann, L.; Kirchner, J.W.; Uhlenbrook, S.; Savenije, H.H.G.

    2012-01-01

    The complexity of hydrological systems and the necessary simplification of models describing these systems remain major challenges in hydrological modeling. Kirchner's (2009) approach of inferring rainfall and evaporation from discharge fluctuations by “doing hydrology backward” is based on the

  9. Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment

    NARCIS (Netherlands)

    Prudhomme, C.; Giuntoli, L.; Robinson, E.L.; Clark, D.B.; Arnell, N.W.; Dankers, R.; Fekete, B.M.; Franssen, W.H.P.

    2014-01-01

    Increasing concentrations of greenhouse gases in the atmosphere are expected to modify the global water cycle with significant consequences for terrestrial hydrology. We assess the impact of climate change on hydrological droughts in a multimodel experiment including seven global impact models

  10. Comprehensive Performance Evaluation for Hydrological and Nutrients Simulation Using the Hydrological Simulation Program–Fortran in a Mesoscale Monsoon Watershed, China

    OpenAIRE

    Zhaofu Li; Chuan Luo; Kaixia Jiang; Rongrong Wan; Hengpeng Li

    2017-01-01

    The Hydrological Simulation Program–Fortran (HSPF) is a hydrological and water quality computer model that was developed by the United States Environmental Protection Agency. Comprehensive performance evaluations were carried out for hydrological and nutrient simulation using the HSPF model in the Xitiaoxi watershed in China. Streamflow simulation was calibrated from 1 January 2002 to 31 December 2007 and then validated from 1 January 2008 to 31 December 2010 using daily observed data, and nu...

  11. Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM). I: Model intercomparison with current land use

    Science.gov (United States)

    Breuer, L.; Huisman, J.A.; Willems, P.; Bormann, H.; Bronstert, A.; Croke, B.F.W.; Frede, H.-G.; Graff, T.; Hubrechts, L.; Jakeman, A.J.; Kite, G.; Lanini, J.; Leavesley, G.; Lettenmaier, D.P.; Lindstrom, G.; Seibert, J.; Sivapalan, M.; Viney, N.R.

    2009-01-01

    This paper introduces the project on 'Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM)' that aims at investigating the envelope of predictions on changes in hydrological fluxes due to land use change. As part of a series of four papers, this paper outlines the motivation and setup of LUCHEM, and presents a model intercomparison for the present-day simulation results. Such an intercomparison provides a valuable basis to investigate the effects of different model structures on model predictions and paves the ground for the analysis of the performance of multi-model ensembles and the reliability of the scenario predictions in companion papers. In this study, we applied a set of 10 lumped, semi-lumped and fully distributed hydrological models that have been previously used in land use change studies to the low mountainous Dill catchment, Germany. Substantial differences in model performance were observed with Nash-Sutcliffe efficiencies ranging from 0.53 to 0.92. Differences in model performance were attributed to (1) model input data, (2) model calibration and (3) the physical basis of the models. The models were applied with two sets of input data: an original and a homogenized data set. This homogenization of precipitation, temperature and leaf area index was performed to reduce the variation between the models. Homogenization improved the comparability of model simulations and resulted in a reduced average bias, although some variation in model data input remained. The effect of the physical differences between models on the long-term water balance was mainly attributed to differences in how models represent evapotranspiration. Semi-lumped and lumped conceptual models slightly outperformed the fully distributed and physically based models. This was attributed to the automatic model calibration typically used for this type of models. Overall, however, we conclude that there was no superior model if several measures of model

  12. Future Flows Climate: an ensemble of 1-km climate change projections for hydrological application in Great Britain

    Directory of Open Access Journals (Sweden)

    C. Prudhomme

    2012-11-01

    Full Text Available The dataset Future Flows Climate was developed as part of the project ''Future Flows and Groundwater Levels'' to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications, and to enable climate change uncertainty and climate variability to be accounted for in the assessment of their possible impacts on the environment.

    Future Flows Climate is derived from the Hadley Centre's ensemble projection HadRM3-PPE that is part of the basis of UKCP09 and includes projections in available precipitation (water available to hydrological processes after snow and ice storages have been accounted for and potential evapotranspiration. It corresponds to an 11-member ensemble of transient projections from January 1950 to December 2098, each a single realisation from a different variant of HadRM3. Data are provided on a 1-km grid over the HadRM3 land areas at a daily (available precipitation and monthly (PE time step as netCDF files.

    Because systematic biases in temperature and precipitation were found between HadRM3-PPE and gridded temperature and precipitation observations for the 1962–1991 period, a monthly bias correction procedure was undertaken, based on a linear correction for temperature and a quantile-mapping correction (using the gamma distribution for precipitation followed by a spatial downscaling. Available precipitation was derived from the bias-corrected precipitation and temperature time series using a simple elevation-dependant snow-melt model. Potential evapotranspiration time series were calculated for each month using the FAO-56 Penman-Monteith equations and bias-corrected temperature, cloud cover, relative humidity and wind speed from HadRM3-PPE along with latitude of the grid and the day of the year.

    Future Flows Climate is freely available for non-commercial use under certain licensing conditions. It is the

  13. An ensemble-based dynamic Bayesian averaging approach for discharge simulations using multiple global precipitation products and hydrological models

    Science.gov (United States)

    Qi, Wei; Liu, Junguo; Yang, Hong; Sweetapple, Chris

    2018-03-01

    Global precipitation products are very important datasets in flow simulations, especially in poorly gauged regions. Uncertainties resulting from precipitation products, hydrological models and their combinations vary with time and data magnitude, and undermine their application to flow simulations. However, previous studies have not quantified these uncertainties individually and explicitly. This study developed an ensemble-based dynamic Bayesian averaging approach (e-Bay) for deterministic discharge simulations using multiple global precipitation products and hydrological models. In this approach, the joint probability of precipitation products and hydrological models being correct is quantified based on uncertainties in maximum and mean estimation, posterior probability is quantified as functions of the magnitude and timing of discharges, and the law of total probability is implemented to calculate expected discharges. Six global fine-resolution precipitation products and two hydrological models of different complexities are included in an illustrative application. e-Bay can effectively quantify uncertainties and therefore generate better deterministic discharges than traditional approaches (weighted average methods with equal and varying weights and maximum likelihood approach). The mean Nash-Sutcliffe Efficiency values of e-Bay are up to 0.97 and 0.85 in training and validation periods respectively, which are at least 0.06 and 0.13 higher than traditional approaches. In addition, with increased training data, assessment criteria values of e-Bay show smaller fluctuations than traditional approaches and its performance becomes outstanding. The proposed e-Bay approach bridges the gap between global precipitation products and their pragmatic applications to discharge simulations, and is beneficial to water resources management in ungauged or poorly gauged regions across the world.

  14. Quantifying the sources of uncertainty in an ensemble of hydrological climate-impact projections

    Science.gov (United States)

    Aryal, Anil; Shrestha, Sangam; Babel, Mukand S.

    2018-01-01

    The objective of this paper is to quantify the various sources of uncertainty in the assessment of climate change impact on hydrology in the Tamakoshi River Basin, located in the north-eastern part of Nepal. Multiple climate and hydrological models were used to simulate future climate conditions and discharge in the basin. The simulated results of future climate and river discharge were analysed for the quantification of sources of uncertainty using two-way and three-way ANOVA. The results showed that temperature and precipitation in the study area are projected to change in near- (2010-2039), mid- (2040-2069) and far-future (2070-2099) periods. Maximum temperature is likely to rise by 1.75 °C under Representative Concentration Pathway (RCP) 4.5 and by 3.52 °C under RCP 8.5. Similarly, the minimum temperature is expected to rise by 2.10 °C under RCP 4.5 and by 3.73 °C under RCP 8.5 by the end of the twenty-first century. Similarly, the precipitation in the study area is expected to change by - 2.15% under RCP 4.5 and - 2.44% under RCP 8.5 scenarios. The future discharge in the study area was projected using two hydrological models, viz. Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center's Hydrologic Modelling System (HEC-HMS). The SWAT model projected discharge is expected to change by small amount, whereas HEC-HMS model projected considerably lower discharge in future compared to the baseline period. The results also show that future climate variables and river hydrology contain uncertainty due to the choice of climate models, RCP scenarios, bias correction methods and hydrological models. During wet days, more uncertainty is observed due to the use of different climate models, whereas during dry days, the use of different hydrological models has a greater effect on uncertainty. Inter-comparison of the impacts of different climate models reveals that the REMO climate model shows higher uncertainty in the prediction of precipitation and

  15. A Two-update Ensemble Kalman Filter for Land Hydrological Data Assimilation with an Uncertain Constraint

    KAUST Repository

    Khaki, M.; Ait-El-Fquih, Boujemaa; Hoteit, Ibrahim; Forootan, E.; Awange, J.; Kuhn, M.

    2017-01-01

    water budgets in balance with other water fluxes. Therefore, in this study, GRACE terrestrial water storages data are assimilated into the World-Wide Water Resources Assessment (W3RA) hydrological model over the Earth’s land areas covering 2002 – 2012

  16. Using an ensemble of climate projections for simulating recent and near-future hydrological change to lake Vaenern in Sweden

    Energy Technology Data Exchange (ETDEWEB)

    Olsson, Jonas; Yang, Wei; Graham, L. Phil; Rosberg, Joergen; Andreasson, Johan (Swedish Meteorological and Hydrological Inst., Norrkoeping (Sweden)), e-mail: jonas.olsson@smhi.se

    2011-01-15

    Lake Vaenern and River Goeta aelv in southern Sweden constitute a large and complex hydrological system that is highly vulnerable to climate change. In this study, an ensemble of 12 regional climate projections is used to simulate the inflow to Lake Vaenern by the HBV hydrological model. By using distribution based scaling of the climate model output, all projections can accurately reproduce the annual cycle of mean monthly inflows for the period 1961-1990 as simulated using HBV with observed temperature and precipitation ('HBVobs'). Significant changes towards higher winter inflow and a reduced spring flood were found when comparing the period 1991-2008 to 1961-1990 in the HBVobs simulations and the ability of the regional projections to reproduce these changes varied. The main uncertainties in the projections for 1991-2008 were found to originate from the global climate model used, including its initialization, and in one case, the emissions scenario, whereas the regional climate model used and its resolution showed a smaller influence. The projections that most accurately reproduce the recent change suggest that the current trends in the winter and spring inflows will continue over the period 2009-2030

  17. Improving wind energy forecasts using an Ensemble Kalman Filter data assimilation technique in a fully coupled hydrologic and atmospheric model

    Science.gov (United States)

    Williams, J. L.; Maxwell, R. M.; Delle Monache, L.

    2012-12-01

    Wind power is rapidly gaining prominence as a major source of renewable energy. Harnessing this promising energy source is challenging because of the chaotic nature of wind and its propensity to change speed and direction over short time scales. Accurate forecasting tools are critical to support the integration of wind energy into power grids and to maximize its impact on renewable energy portfolios. Numerous studies have shown that soil moisture distribution and land surface vegetative processes profoundly influence atmospheric boundary layer development and weather processes on local and regional scales. Using the PF.WRF model, a fully-coupled hydrologic and atmospheric model employing the ParFlow hydrologic model with the Weather Research and Forecasting model coupled via mass and energy fluxes across the land surface, we have explored the connections between the land surface and the atmosphere in terms of land surface energy flux partitioning and coupled variable fields including hydraulic conductivity, soil moisture and wind speed, and demonstrated that reductions in uncertainty in these coupled fields propagate through the hydrologic and atmospheric system. We have adapted the Data Assimilation Research Testbed (DART), an implementation of the robust Ensemble Kalman Filter data assimilation algorithm, to expand our capability to nudge forecasts produced with the PF.WRF model using observational data. Using a semi-idealized simulation domain, we examine the effects of assimilating observations of variables such as wind speed and temperature collected in the atmosphere, and land surface and subsurface observations such as soil moisture on the quality of forecast outputs. The sensitivities we find in this study will enable further studies to optimize observation collection to maximize the utility of the PF.WRF-DART forecasting system.

  18. An operational hydrological ensemble prediction system for the city of Zurich (Switzerland: skill, case studies and scenarios

    Directory of Open Access Journals (Sweden)

    N. Addor

    2011-07-01

    Full Text Available The Sihl River flows through Zurich, Switzerland's most populated city, for which it represents the largest flood threat. To anticipate extreme discharge events and provide decision support in case of flood risk, a hydrometeorological ensemble prediction system (HEPS was launched operationally in 2008. This model chain relies on limited-area atmospheric forecasts provided by the deterministic model COSMO-7 and the probabilistic model COSMO-LEPS. These atmospheric forecasts are used to force a semi-distributed hydrological model (PREVAH, coupled to a hydraulic model (FLORIS. The resulting hydrological forecasts are eventually communicated to the stakeholders involved in the Sihl discharge management. This fully operational setting provides a real framework with which to compare the potential of deterministic and probabilistic discharge forecasts for flood mitigation.

    To study the suitability of HEPS for small-scale basins and to quantify the added-value conveyed by the probability information, a reforecast was made for the period June 2007 to December 2009 for the Sihl catchment (336 km2. Several metrics support the conclusion that the performance gain can be of up to 2 days lead time for the catchment considered. Brier skill scores show that overall COSMO-LEPS-based hydrological forecasts outperforms their COSMO-7-based counterparts for all the lead times and event intensities considered. The small size of the Sihl catchment does not prevent skillful discharge forecasts, but makes them particularly dependent on correct precipitation forecasts, as shown by comparisons with a reference run driven by observed meteorological parameters. Our evaluation stresses that the capacity of the model to provide confident and reliable mid-term probability forecasts for high discharges is limited. The two most intense events of the study period are investigated utilising a novel graphical representation of probability forecasts, and are used

  19. Suitability of Water Harvesting in the Upper Blue Nile Basin, Ethiopia: A First Step towards a Mesoscale Hydrological Modeling Framework

    Directory of Open Access Journals (Sweden)

    Yihun T. Dile

    2016-01-01

    Full Text Available Extreme rainfall variability has been one of the major factors to famine and environmental degradation in Ethiopia. The potential for water harvesting in the Upper Blue Nile Basin was assessed using two GIS-based Multicriteria Evaluation methods: (1 a Boolean approach to locate suitable areas for in situ and ex situ systems and (2 a weighted overlay analysis to classify suitable areas into different water harvesting suitability levels. The sensitivity of the results was analyzed to the influence given to different constraining factors. A large part of the basin was suitable for water harvesting: the Boolean analysis showed that 36% of the basin was suitable for in situ and ex situ systems, while the weighted overlay analysis showed that 6–24% of the basin was highly suitable. Rainfall has the highest influence on suitability for water harvesting. Implementing water harvesting in nonagricultural land use types may further increase the benefit. Assessing water harvesting suitability at the larger catchment scale lays the foundation for modeling of water harvesting at mesoscale, which enables analysis of the potential and implications of upscaling of water harvesting practices for building resilience against climatic shocks. A complete water harvesting suitability study requires socioeconomic analysis and stakeholder consultation.

  20. A two-stage method of quantitative flood risk analysis for reservoir real-time operation using ensemble-based hydrologic forecasts

    Science.gov (United States)

    Liu, P.

    2013-12-01

    Quantitative analysis of the risk for reservoir real-time operation is a hard task owing to the difficulty of accurate description of inflow uncertainties. The ensemble-based hydrologic forecasts directly depict the inflows not only the marginal distributions but also their persistence via scenarios. This motivates us to analyze the reservoir real-time operating risk with ensemble-based hydrologic forecasts as inputs. A method is developed by using the forecast horizon point to divide the future time into two stages, the forecast lead-time and the unpredicted time. The risk within the forecast lead-time is computed based on counting the failure number of forecast scenarios, and the risk in the unpredicted time is estimated using reservoir routing with the design floods and the reservoir water levels of forecast horizon point. As a result, a two-stage risk analysis method is set up to quantify the entire flood risks by defining the ratio of the number of scenarios that excessive the critical value to the total number of scenarios. The China's Three Gorges Reservoir (TGR) is selected as a case study, where the parameter and precipitation uncertainties are implemented to produce ensemble-based hydrologic forecasts. The Bayesian inference, Markov Chain Monte Carlo, is used to account for the parameter uncertainty. Two reservoir operation schemes, the real operated and scenario optimization, are evaluated for the flood risks and hydropower profits analysis. With the 2010 flood, it is found that the improvement of the hydrologic forecast accuracy is unnecessary to decrease the reservoir real-time operation risk, and most risks are from the forecast lead-time. It is therefore valuable to decrease the avarice of ensemble-based hydrologic forecasts with less bias for a reservoir operational purpose.

  1. A CN-Based Ensembled Hydrological Model for Enhanced Watershed Runoff Prediction

    Directory of Open Access Journals (Sweden)

    Muhammad Ajmal

    2016-01-01

    Full Text Available A major structural inconsistency of the traditional curve number (CN model is its dependence on an unstable fixed initial abstraction, which normally results in sudden jumps in runoff estimation. Likewise, the lack of pre-storm soil moisture accounting (PSMA procedure is another inherent limitation of the model. To circumvent those problems, we used a variable initial abstraction after ensembling the traditional CN model and a French four-parameter (GR4J model to better quantify direct runoff from ungauged watersheds. To mimic the natural rainfall-runoff transformation at the watershed scale, our new parameterization designates intrinsic parameters and uses a simple structure. It exhibited more accurate and consistent results than earlier methods in evaluating data from 39 forest-dominated watersheds, both for small and large watersheds. In addition, based on different performance evaluation indicators, the runoff reproduction results show that the proposed model produced more consistent results for dry, normal, and wet watershed conditions than the other models used in this study.

  2. Impact of Uncertainty Characterization of Satellite Rainfall Inputs and Model Parameters on Hydrological Data Assimilation with the Ensemble Kalman Filter for Flood Prediction

    Science.gov (United States)

    Vergara, H. J.; Kirstetter, P.; Hong, Y.; Gourley, J. J.; Wang, X.

    2013-12-01

    The Ensemble Kalman Filter (EnKF) is arguably the assimilation approach that has found the widest application in hydrologic modeling. Its relatively easy implementation and computational efficiency makes it an attractive method for research and operational purposes. However, the scientific literature featuring this approach lacks guidance on how the errors in the forecast need to be characterized so as to get the required corrections from the assimilation process. Moreover, several studies have indicated that the performance of the EnKF is 'sub-optimal' when assimilating certain hydrologic observations. Likewise, some authors have suggested that the underlying assumptions of the Kalman Filter and its dependence on linear dynamics make the EnKF unsuitable for hydrologic modeling. Such assertions are often based on ineffectiveness and poor robustness of EnKF implementations resulting from restrictive specification of error characteristics and the absence of a-priori information of error magnitudes. Therefore, understanding the capabilities and limitations of the EnKF to improve hydrologic forecasts require studying its sensitivity to the manner in which errors in the hydrologic modeling system are represented through ensembles. This study presents a methodology that explores various uncertainty representation configurations to characterize the errors in the hydrologic forecasts in a data assimilation context. The uncertainty in rainfall inputs is represented through a Generalized Additive Model for Location, Scale, and Shape (GAMLSS), which provides information about second-order statistics of quantitative precipitation estimates (QPE) error. The uncertainty in model parameters is described adding perturbations based on parameters covariance information. The method allows for the identification of rainfall and parameter perturbation combinations for which the performance of the EnKF is 'optimal' given a set of objective functions. In this process, information about

  3. A Bayesian consistent dual ensemble Kalman filter for state-parameter estimation in subsurface hydrology

    KAUST Repository

    Ait-El-Fquih, Boujemaa; El Gharamti, Mohamad; Hoteit, Ibrahim

    2016-01-01

    Ensemble Kalman filtering (EnKF) is an efficient approach to addressing uncertainties in subsurface ground-water models. The EnKF sequentially integrates field data into simulation models to obtain a better characterization of the model's state and parameters. These are generally estimated following joint and dual filtering strategies, in which, at each assimilation cycle, a forecast step by the model is followed by an update step with incoming observations. The joint EnKF directly updates the augmented state-parameter vector, whereas the dual EnKF empirically employs two separate filters, first estimating the parameters and then estimating the state based on the updated parameters. To develop a Bayesian consistent dual approach and improve the state-parameter estimates and their consistency, we propose in this paper a one-step-ahead (OSA) smoothing formulation of the state-parameter Bayesian filtering problem from which we derive a new dual-type EnKF, the dual EnKF(OSA). Compared with the standard dual EnKF, it imposes a new update step to the state, which is shown to enhance the performance of the dual approach with almost no increase in the computational cost. Numerical experiments are conducted with a two-dimensional (2-D) synthetic groundwater aquifer model to investigate the performance and robustness of the proposed dual EnKFOSA, and to evaluate its results against those of the joint and dual EnKFs. The proposed scheme is able to successfully recover both the hydraulic head and the aquifer conductivity, providing further reliable estimates of their uncertainties. Furthermore, it is found to be more robust to different assimilation settings, such as the spatial and temporal distribution of the observations, and the level of noise in the data. Based on our experimental setups, it yields up to 25% more accurate state and parameter estimations than the joint and dual approaches.

  4. A Bayesian consistent dual ensemble Kalman filter for state-parameter estimation in subsurface hydrology

    KAUST Repository

    Ait-El-Fquih, Boujemaa

    2016-08-12

    Ensemble Kalman filtering (EnKF) is an efficient approach to addressing uncertainties in subsurface ground-water models. The EnKF sequentially integrates field data into simulation models to obtain a better characterization of the model\\'s state and parameters. These are generally estimated following joint and dual filtering strategies, in which, at each assimilation cycle, a forecast step by the model is followed by an update step with incoming observations. The joint EnKF directly updates the augmented state-parameter vector, whereas the dual EnKF empirically employs two separate filters, first estimating the parameters and then estimating the state based on the updated parameters. To develop a Bayesian consistent dual approach and improve the state-parameter estimates and their consistency, we propose in this paper a one-step-ahead (OSA) smoothing formulation of the state-parameter Bayesian filtering problem from which we derive a new dual-type EnKF, the dual EnKF(OSA). Compared with the standard dual EnKF, it imposes a new update step to the state, which is shown to enhance the performance of the dual approach with almost no increase in the computational cost. Numerical experiments are conducted with a two-dimensional (2-D) synthetic groundwater aquifer model to investigate the performance and robustness of the proposed dual EnKFOSA, and to evaluate its results against those of the joint and dual EnKFs. The proposed scheme is able to successfully recover both the hydraulic head and the aquifer conductivity, providing further reliable estimates of their uncertainties. Furthermore, it is found to be more robust to different assimilation settings, such as the spatial and temporal distribution of the observations, and the level of noise in the data. Based on our experimental setups, it yields up to 25% more accurate state and parameter estimations than the joint and dual approaches.

  5. Ensemble hydrological forecast efficiency evolution over various issue dates and lead-time: case study for the Cheboksary reservoir (Volga River)

    Science.gov (United States)

    Gelfan, Alexander; Moreido, Vsevolod

    2017-04-01

    Ensemble hydrological forecasting allows for describing uncertainty caused by variability of meteorological conditions in the river basin for the forecast lead-time. At the same time, in snowmelt-dependent river basins another significant source of uncertainty relates to variability of initial conditions of the basin (snow water equivalent, soil moisture content, etc.) prior to forecast issue. Accurate long-term hydrological forecast is most crucial for large water management systems, such as the Cheboksary reservoir (the catchment area is 374 000 sq.km) located in the Middle Volga river in Russia. Accurate forecasts of water inflow volume, maximum discharge and other flow characteristics are of great value for this basin, especially before the beginning of the spring freshet season that lasts here from April to June. The semi-distributed hydrological model ECOMAG was used to develop long-term ensemble forecast of daily water inflow into the Cheboksary reservoir. To describe variability of the meteorological conditions and construct ensemble of possible weather scenarios for the lead-time of the forecast, two approaches were applied. The first one utilizes 50 weather scenarios observed in the previous years (similar to the ensemble streamflow prediction (ESP) procedure), the second one uses 1000 synthetic scenarios simulated by a stochastic weather generator. We investigated the evolution of forecast uncertainty reduction, expressed as forecast efficiency, over various consequent forecast issue dates and lead time. We analyzed the Nash-Sutcliffe efficiency of inflow hindcasts for the period 1982 to 2016 starting from 1st of March with 15 days frequency for lead-time of 1 to 6 months. This resulted in the forecast efficiency matrix with issue dates versus lead-time that allows for predictability identification of the basin. The matrix was constructed separately for observed and synthetic weather ensembles.

  6. Should we use seasonnal meteorological ensemble forecasts for hydrological forecasting? A case study for nordic watersheds in Canada.

    Science.gov (United States)

    Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert; Guay, Catherine

    2017-04-01

    Hydro-electricity is a major source of energy for many countries throughout the world, including Canada. Long lead-time streamflow forecasts are all the more valuable as they help decision making and dam management. Different techniques exist for long-term hydrological forecasting. Perhaps the most well-known is 'Extended Streamflow Prediction' (ESP), which considers past meteorological scenarios as possible, often equiprobable, future scenarios. In the ESP framework, those past-observed meteorological scenarios (climatology) are used in turn as the inputs of a chosen hydrological model to produce ensemble forecasts (one member corresponding to each year in the available database). Many hydropower companies, including Hydro-Québec (province of Quebec, Canada) use variants of the above described ESP system operationally for long-term operation planning. The ESP system accounts for the hydrological initial conditions and for the natural variability of the meteorological variables. However, it cannot consider the current initial state of the atmosphere. Climate models can help remedy this drawback. In the context of a changing climate, dynamical forecasts issued from climate models seem to be an interesting avenue to improve upon the ESP method and could help hydropower companies to adapt their management practices to an evolving climate. Long-range forecasts from climate models can also be helpful for water management at locations where records of past meteorological conditions are short or nonexistent. In this study, we compare 7-month hydrological forecasts obtained from climate model outputs to an ESP system. The ESP system mimics the one used operationally at Hydro-Québec. The dynamical climate forecasts are produced by the European Center for Medium range Weather Forecasts (ECMWF) System4. Forecasts quality is assessed using numerical scores such as the Continuous Ranked Probability Score (CRPS) and the Ignorance score and also graphical tools such as the

  7. Role of rock texture and mineralogy on the hydrology and geochemistry of three neutral-drainage mesoscale experimental waste rock piles at the Antamina Mine, Peru

    Science.gov (United States)

    Peterson, H.; Bay, D. S.; Beckie, R. D.; Mayer, K. U.; Klein, B.; Smith, L.

    2009-12-01

    An ongoing study at the Antamina Cu-Zn-Mo mine in Peru investigates the hydrology and geochemistry of heterogeneous waste rock at multiple scales. Three of five instrumented mesoscale experimental waste rock piles (36m X 36m X 10m high) were constructed between 2006 and 2008. The coarsest-grained Pile 1 exhibits rapid, intense response to rain and returns to residual saturation relatively quickly, suggesting a significant influence of preferential flow in addition to high-conductivity matrix flow. Pile 2, the finest-grained of the three piles, exhibits signals from rain events that are significantly delayed and muted in comparison to those from Pile 1. Except for in the finest size fractions, the particle size distribution of Pile 3 closely resembles that of Pile 2, yet Pile 3 responds to rain events more similarly to Pile 1 than Pile 2. The presence of large boulders in Pile 3 could facilitate preferential flow, either through surface flow effects across boulders or by contributing to the formation of unfilled void space acting as macropores at high infiltration rates. The rapid rain event response of Pile 3 could also be attributed to a silt-clay percentage that is similar to Pile 1, which is less than half of the silt-clay percentage observed in Pile 2 (i.e., ~3%, ~8.5%, and ~4% for Piles 1, 2 and 3, respectively). For each of the three piles, the pH of effluent collected from bottom lysimeters and internal pore water sampled with suction lysimeters has remained circumneutral, with notable maximum concentrations of 2.8 mg/L Zn from Pile 1, which is comprised of slightly reactive hornfels and marble waste rock; 13.4 mg/L Zn and 22.7 mg/L Mo from Pile 2, comprised of reactive intrusive waste rock; and 42.5 mg/L Zn from Pile 3, comprised of reactive exoskarn waste rock. Ongoing work includes analysis of two additional mixed-rock experimental piles, studies to investigate the role of microbes on metal release (Dockrey et al., this session), analysis of pore gas

  8. Finding diversity for building one-day ahead Hydrological Ensemble Prediction System based on artificial neural network stacks

    Science.gov (United States)

    Brochero, Darwin; Anctil, Francois; Gagné, Christian; López, Karol

    2013-04-01

    In this study, we addressed the application of Artificial Neural Networks (ANN) in the context of Hydrological Ensemble Prediction Systems (HEPS). Such systems have become popular in the past years as a tool to include the forecast uncertainty in the decision making process. HEPS considers fundamentally the uncertainty cascade model [4] for uncertainty representation. Analogously, the machine learning community has proposed models of multiple classifier systems that take into account the variability in datasets, input space, model structures, and parametric configuration [3]. This approach is based primarily on the well-known "no free lunch theorem" [1]. Consequently, we propose a framework based on two separate but complementary topics: data stratification and input variable selection (IVS). Thus, we promote an ANN prediction stack in which each predictor is trained based on input spaces defined by the IVS application on different stratified sub-samples. All this, added to the inherent variability of classical ANN optimization, leads us to our ultimate goal: diversity in the prediction, defined as the complementarity of the individual predictors. The stratification application on the 12 basins used in this study, which originate from the second and third workshop of the MOPEX project [2], shows that the informativeness of the data is far more important than the quantity used for ANN training. Additionally, the input space variability leads to ANN stacks that outperform an ANN stack model trained with 100% of the available information but with a random selection of dataset used in the early stopping method (scenario R100P). The results show that from a deterministic view, the main advantage focuses on the efficient selection of the training information, which is an equally important concept for the calibration of conceptual hydrological models. On the other hand, the diversity achieved is reflected in a substantial improvement in the scores that define the

  9. A One-Step-Ahead Smoothing-Based Joint Ensemble Kalman Filter for State-Parameter Estimation of Hydrological Models

    KAUST Repository

    El Gharamti, Mohamad; Ait-El-Fquih, Boujemaa; Hoteit, Ibrahim

    2015-01-01

    The ensemble Kalman filter (EnKF) recursively integrates field data into simulation models to obtain a better characterization of the model’s state and parameters. These are generally estimated following a state-parameters joint augmentation

  10. Hydrology

    Science.gov (United States)

    Sharp, John M.

    1977-01-01

    Lists many recent research projects in hydrology, including flow in fractured media, improvements in remote-sensing techniques, effects of urbanization on water resources, and developments in drainage basins. (MLH)

  11. Hydrology

    International Nuclear Information System (INIS)

    Obando G, E.

    1989-01-01

    Isotopical techniques are used in hydrology area for exploration, evaluation and exploration of water investigation. These techniques have been used successfully and are often the best or only means for providing certain hydrogeological parameters

  12. Hydrology

    Science.gov (United States)

    Brutsaert, Wilfried

    2005-08-01

    Water in its different forms has always been a source of wonder, curiosity and practical concern for humans everywhere. Hydrology - An Introduction presents a coherent introduction to the fundamental principles of hydrology, based on the course that Wilfried Brutsaert has taught at Cornell University for the last thirty years. Hydrologic phenomena are dealt with at spatial and temporal scales at which they occur in nature. The physics and mathematics necessary to describe these phenomena are introduced and developed, and readers will require a working knowledge of calculus and basic fluid mechanics. The book will be invaluable as a textbook for entry-level courses in hydrology directed at advanced seniors and graduate students in physical science and engineering. In addition, the book will be more broadly of interest to professional scientists and engineers in hydrology, environmental science, meteorology, agronomy, geology, climatology, oceanology, glaciology and other earth sciences. Emphasis on fundamentals Clarification of the underlying physical processes Applications of fluid mechanics in the natural environment

  13. Simplifying a hydrological ensemble prediction system with a backward greedy selection of members – Part 2: Generalization in time and space

    Directory of Open Access Journals (Sweden)

    D. Brochero

    2011-11-01

    Full Text Available An uncertainty cascade model applied to stream flow forecasting seeks to evaluate the different sources of uncertainty of the complex rainfall-runoff process. The current trend focuses on the combination of Meteorological Ensemble Prediction Systems (MEPS and hydrological model(s. However, the number of members of such a HEPS may rapidly increase to a level that may not be operationally sustainable. This paper evaluates the generalization ability of a simplification scheme of a 800-member HEPS formed by the combination of 16 lumped rainfall-runoff models with the 50 perturbed members from the European Centre for Medium-range Weather Forecasts (ECMWF EPS. Tests are made at two levels. At the local level, the transferability of the 9th day hydrological member selection for the other 8 forecast horizons exhibits an 82% success rate. The other evaluation is made at the regional or cluster level, the transferability from one catchment to another from within a cluster of watersheds also leads to a good performance (85% success rate, especially for forecast time horizons above 3 days and when the basins that formed the cluster presented themselves a good performance on an individual basis. Diversity, defined as hydrological model complementarity addressing different aspects of a forecast, was identified as the critical factor for proper selection applications.

  14. Hydrologi

    DEFF Research Database (Denmark)

    Burcharth, Hans F.

    Hydro1ogi er den videnskab, der omhand1er jordens vand, dets forekomst, cirku1ation og forde1ing, dets kemiske og fysiske egenskaber samt indvirkning på omgivelserne, herunder dets relation ti1 alt liv på jorden. Således lyder en b1andt mange definitioner på begrebet hydrologi, og som man kan se...

  15. State updating of a distributed hydrological model with Ensemble Kalman Filtering: Effects of updating frequency and observation network density on forecast accuracy

    Science.gov (United States)

    Rakovec, O.; Weerts, A.; Hazenberg, P.; Torfs, P.; Uijlenhoet, R.

    2012-12-01

    This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model (Rakovec et al., 2012a). The Ensemble Kalman filter (EnKF) is employed to update the grid-based distributed states of such an hourly spatially distributed version of the HBV-96 model. By using a physically based model for the routing, the time delay and attenuation are modelled more realistically. The discharge and states at a given time step are assumed to be dependent on the previous time step only (Markov property). Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km2), a relatively quickly responding catchment in the Belgian Ardennes. The uncertain precipitation model forcings were obtained using a time-dependent multivariate spatial conditional simulation method (Rakovec et al., 2012b), which is further made conditional on preceding simulations. We assess the impact on the forecasted discharge of (1) various sets of the spatially distributed discharge gauges and (2) the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF procedure is found to mainly change the pdfs of the two routing model storages, even when the uncertainty in the discharge simulations is smaller than the defined observation uncertainty. Rakovec, O., Weerts, A. H., Hazenberg, P., Torfs, P. J. J. F., and Uijlenhoet, R.: State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy, Hydrol. Earth Syst. Sci. Discuss., 9, 3961-3999, doi:10.5194/hessd-9-3961-2012, 2012a. Rakovec, O., Hazenberg, P., Torfs, P. J. J. F., Weerts, A. H., and Uijlenhoet, R.: Generating spatial precipitation ensembles: impact of

  16. Improved regional-scale groundwater representation by the coupling of the mesoscale Hydrologic Model (mHM v5.7) to the groundwater model OpenGeoSys (OGS)

    Science.gov (United States)

    Jing, Miao; Heße, Falk; Kumar, Rohini; Wang, Wenqing; Fischer, Thomas; Walther, Marc; Zink, Matthias; Zech, Alraune; Samaniego, Luis; Kolditz, Olaf; Attinger, Sabine

    2018-06-01

    Most large-scale hydrologic models fall short in reproducing groundwater head dynamics and simulating transport process due to their oversimplified representation of groundwater flow. In this study, we aim to extend the applicability of the mesoscale Hydrologic Model (mHM v5.7) to subsurface hydrology by coupling it with the porous media simulator OpenGeoSys (OGS). The two models are one-way coupled through model interfaces GIS2FEM and RIV2FEM, by which the grid-based fluxes of groundwater recharge and the river-groundwater exchange generated by mHM are converted to fixed-flux boundary conditions of the groundwater model OGS. Specifically, the grid-based vertical reservoirs in mHM are completely preserved for the estimation of land-surface fluxes, while OGS acts as a plug-in to the original mHM modeling framework for groundwater flow and transport modeling. The applicability of the coupled model (mHM-OGS v1.0) is evaluated by a case study in the central European mesoscale river basin - Nägelstedt. Different time steps, i.e., daily in mHM and monthly in OGS, are used to account for fast surface flow and slow groundwater flow. Model calibration is conducted following a two-step procedure using discharge for mHM and long-term mean of groundwater head measurements for OGS. Based on the model summary statistics, namely the Nash-Sutcliffe model efficiency (NSE), the mean absolute error (MAE), and the interquartile range error (QRE), the coupled model is able to satisfactorily represent the dynamics of discharge and groundwater heads at several locations across the study basin. Our exemplary calculations show that the one-way coupled model can take advantage of the spatially explicit modeling capabilities of surface and groundwater hydrologic models and provide an adequate representation of the spatiotemporal behaviors of groundwater storage and heads, thus making it a valuable tool for addressing water resources and management problems.

  17. Identification of changes in hydrological drought characteristics from a multi-GCM driven ensemble constrained by observed discharge

    NARCIS (Netherlands)

    Huijgevoort, van M.H.J.; Lanen, van H.A.J.; Teuling, A.J.; Uijlenhoet, R.

    2014-01-01

    Drought severity and related socio-economic impacts are expected to increase due to climate change. To better adapt to these impacts, more knowledge on changes in future hydrological drought characteristics (e.g. frequency, duration) is needed rather than only knowledge on changes in meteorological

  18. State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy

    Directory of Open Access Journals (Sweden)

    O. Rakovec

    2012-09-01

    Full Text Available This paper presents a study on the optimal setup for discharge assimilation within a spatially distributed hydrological model. The Ensemble Kalman filter (EnKF is employed to update the grid-based distributed states of such an hourly spatially distributed version of the HBV-96 model. By using a physically based model for the routing, the time delay and attenuation are modelled more realistically. The discharge and states at a given time step are assumed to be dependent on the previous time step only (Markov property.

    Synthetic and real world experiments are carried out for the Upper Ourthe (1600 km2, a relatively quickly responding catchment in the Belgian Ardennes. We assess the impact on the forecasted discharge of (1 various sets of the spatially distributed discharge gauges and (2 the filtering frequency. The results show that the hydrological forecast at the catchment outlet is improved by assimilating interior gauges. This augmentation of the observation vector improves the forecast more than increasing the updating frequency. In terms of the model states, the EnKF procedure is found to mainly change the pdfs of the two routing model storages, even when the uncertainty in the discharge simulations is smaller than the defined observation uncertainty.

  19. A One-Step-Ahead Smoothing-Based Joint Ensemble Kalman Filter for State-Parameter Estimation of Hydrological Models

    KAUST Repository

    El Gharamti, Mohamad

    2015-11-26

    The ensemble Kalman filter (EnKF) recursively integrates field data into simulation models to obtain a better characterization of the model’s state and parameters. These are generally estimated following a state-parameters joint augmentation strategy. In this study, we introduce a new smoothing-based joint EnKF scheme, in which we introduce a one-step-ahead smoothing of the state before updating the parameters. Numerical experiments are performed with a two-dimensional synthetic subsurface contaminant transport model. The improved performance of the proposed joint EnKF scheme compared to the standard joint EnKF compensates for the modest increase in the computational cost.

  20. Impact of streamflow data assimilation and length of the verification period on the quality of short-term ensemble hydrologic forecasts

    Science.gov (United States)

    Randrianasolo, A.; Thirel, G.; Ramos, M. H.; Martin, E.

    2014-11-01

    Data assimilation has gained wide recognition in hydrologic forecasting due mainly to its capacity to improve the quality of short-term forecasts. In this study, a comparative analysis is conducted to assess the impact of discharge data assimilation on the quality of streamflow forecasts issued by two different modeling conceptualizations of catchment response. The sensitivity of the performance metrics to the length of the verification period is also investigated. The hydrological modeling approaches are: the coupled physically-based hydro-meteorological model SAFRAN-ISBA-MODCOU, a distributed model with a data assimilation procedure that uses streamflow measurements to assess the initial state of soil water content that optimizes discharge simulations, and the lumped soil moisture-accounting type rainfall-runoff model GRP, which assimilates directly the last observed discharge to update the state of the routing store. The models are driven by the weather ensemble prediction system PEARP of Météo-France, which is based on the global spectral ARPEGE model zoomed over France. It runs 11 perturbed members for a forecast range of 60 h. Forecast and observed data are available for 86 catchments over a 17-month period (March 2005-July 2006) for both models and for 82 catchments over a 52-month period (April 2005-July 2009) for the GRP model. The first dataset is used to investigate the impact of streamflow data assimilation on forecast quality, while the second is used to evaluate the impact of the length of the verification period on the assessment of forecast quality. Forecasts are compared to daily observed discharges and scores are computed for lead times 24 h and 48 h. Results indicate an overall good performance of both hydrological models forced by the PEARP ensemble predictions when the models are run with their data assimilation procedures. In general, when data assimilation is performed, the quality of the forecasts increases: median differences between

  1. Evaluating a Local Ensemble Transform Kalman Filter snow cover data assimilation method to estimate SWE within a high-resolution hydrologic modeling framework across Western US mountainous regions

    Science.gov (United States)

    Oaida, C. M.; Andreadis, K.; Reager, J. T., II; Famiglietti, J. S.; Levoe, S.

    2017-12-01

    Accurately estimating how much snow water equivalent (SWE) is stored in mountainous regions characterized by complex terrain and snowmelt-driven hydrologic cycles is not only greatly desirable, but also a big challenge. Mountain snowpack exhibits high spatial variability across a broad range of spatial and temporal scales due to a multitude of physical and climatic factors, making it difficult to observe or estimate in its entirety. Combing remotely sensed data and high resolution hydrologic modeling through data assimilation (DA) has the potential to provide a spatially and temporally continuous SWE dataset at horizontal scales that capture sub-grid snow spatial variability and are also relevant to stakeholders such as water resource managers. Here, we present the evaluation of a new snow DA approach that uses a Local Ensemble Transform Kalman Filter (LETKF) in tandem with the Variable Infiltration Capacity macro-scale hydrologic model across the Western United States, at a daily temporal resolution, and a horizontal resolution of 1.75 km x 1.75 km. The LETKF is chosen for its relative simplicity, ease of implementation, and computational efficiency and scalability. The modeling/DA system assimilates daily MODIS Snow Covered Area and Grain Size (MODSCAG) fractional snow cover over, and has been developed to efficiently calculate SWE estimates over extended periods of time and covering large regional-scale areas at relatively high spatial resolution, ultimately producing a snow reanalysis-type dataset. Here we focus on the assessment of SWE produced by the DA scheme over several basins in California's Sierra Nevada Mountain range where Airborne Snow Observatory data is available, during the last five water years (2013-2017), which include both one of the driest and one of the wettest years. Comparison against such a spatially distributed SWE observational product provides a greater understanding of the model's ability to estimate SWE and SWE spatial variability

  2. Improving a spatial rainfall product using a data-mining approach and its effect on the hydrological response of a meso-scale catchment.

    Science.gov (United States)

    Oriani, F.; Stisen, S.; Demirel, C.

    2017-12-01

    The spatial representation of rainfall is of primary importance to correctly study the uncertainty of basin recharge and its propagation to the surface and underground circulation. We consider here the daily grid rainfall product provided by the Danish Meteorological Institute as input to the National Water Resources Model of Denmark. Due to a drastic reduction in the rain gauge network (from approximately 500 stations in the period 1996-2006, to 250 in the period 2007-2014), the grid rainfall product, based on the interpolation of these data, is much less reliable. The research is focused on the Skjern catchment (1,050 km2 western Jutland), where we can dispose of the complete rain-gauge database from the Danish Hydrological Observatory and compute the distributed hydrological response at the 1-km scale.To give a better estimation of the gridded rainfall input, we start from ground measurements by simulating the missing data with a stochastic data-mining approach, then we compute again the grid interpolation. To maximize the predictive power of the technique, combinations of station time-series that are the most informative to each other are selected on the basis of their correlation and available historical data. Then, the missing data inside these time-series are simulated together using the direct sampling technique (DS) [1, 2]. DS simulates a datum by sampling the historical record of the same stations where a similar data pattern occurs, preserving their complex statistical relation. The simulated data are reinjected in the whole dataset and used as well as conditioning data to progressively fill up the gaps in other stations.The results show that the proposed methodology, tested on the period 1995-2012, can increase the realism of the grid rainfall product by regenerating the missing ground measurements. The hydrological response is analyzed considering the observations at 5 hydrological stations. The presented methodology can be used in many regions to

  3. Variance-based Sensitivity Analysis of Large-scale Hydrological Model to Prepare an Ensemble-based SWOT-like Data Assimilation Experiments

    Science.gov (United States)

    Emery, C. M.; Biancamaria, S.; Boone, A. A.; Ricci, S. M.; Garambois, P. A.; Decharme, B.; Rochoux, M. C.

    2015-12-01

    Land Surface Models (LSM) coupled with River Routing schemes (RRM), are used in Global Climate Models (GCM) to simulate the continental part of the water cycle. They are key component of GCM as they provide boundary conditions to atmospheric and oceanic models. However, at global scale, errors arise mainly from simplified physics, atmospheric forcing, and input parameters. More particularly, those used in RRM, such as river width, depth and friction coefficients, are difficult to calibrate and are mostly derived from geomorphologic relationships, which may not always be realistic. In situ measurements are then used to calibrate these relationships and validate the model, but global in situ data are very sparse. Additionally, due to the lack of existing global river geomorphology database and accurate forcing, models are run at coarse resolution. This is typically the case of the ISBA-TRIP model used in this study.A complementary alternative to in-situ data are satellite observations. In this regard, the Surface Water and Ocean Topography (SWOT) satellite mission, jointly developed by NASA/CNES/CSA/UKSA and scheduled for launch around 2020, should be very valuable to calibrate RRM parameters. It will provide maps of water surface elevation for rivers wider than 100 meters over continental surfaces in between 78°S and 78°N and also direct observation of river geomorphological parameters such as width ans slope.Yet, before assimilating such kind of data, it is needed to analyze RRM temporal sensitivity to time-constant parameters. This study presents such analysis over large river basins for the TRIP RRM. Model output uncertainty, represented by unconditional variance, is decomposed into ordered contribution from each parameter. Doing a time-dependent analysis allows then to identify to which parameters modeled water level and discharge are the most sensitive along a hydrological year. The results show that local parameters directly impact water levels, while

  4. Modeling mesoscale eddies

    Science.gov (United States)

    Canuto, V. M.; Dubovikov, M. S.

    Mesoscale eddies are not resolved in coarse resolution ocean models and must be modeled. They affect both mean momentum and scalars. At present, no generally accepted model exists for the former; in the latter case, mesoscales are modeled with a bolus velocity u∗ to represent a sink of mean potential energy. However, comparison of u∗(model) vs. u∗ (eddy resolving code, [J. Phys. Ocean. 29 (1999) 2442]) has shown that u∗(model) is incomplete and that additional terms, "unrelated to thickness source or sinks", are required. Thus far, no form of the additional terms has been suggested. To describe mesoscale eddies, we employ the Navier-Stokes and scalar equations and a turbulence model to treat the non-linear interactions. We then show that the problem reduces to an eigenvalue problem for the mesoscale Bernoulli potential. The solution, which we derive in analytic form, is used to construct the momentum and thickness fluxes. In the latter case, the bolus velocity u∗ is found to contain two types of terms: the first type entails the gradient of the mean potential vorticity and represents a positive contribution to the production of mesoscale potential energy; the second type of terms, which is new, entails the velocity of the mean flow and represents a negative contribution to the production of mesoscale potential energy, or equivalently, a backscatter process whereby a fraction of the mesoscale potential energy is returned to the original reservoir of mean potential energy. This type of terms satisfies the physical description of the additional terms given by [J. Phys. Ocean. 29 (1999) 2442]. The mesoscale flux that enters the momentum equations is also contributed by two types of terms of the same physical nature as those entering the thickness flux. The potential vorticity flux is also shown to contain two types of terms: the first is of the gradient-type while the other terms entail the velocity of the mean flow. An expression is derived for the mesoscale

  5. Ensemble Methods

    Science.gov (United States)

    Re, Matteo; Valentini, Giorgio

    2012-03-01

    Ensemble methods are statistical and computational learning procedures reminiscent of the human social learning behavior of seeking several opinions before making any crucial decision. The idea of combining the opinions of different "experts" to obtain an overall “ensemble” decision is rooted in our culture at least from the classical age of ancient Greece, and it has been formalized during the Enlightenment with the Condorcet Jury Theorem[45]), which proved that the judgment of a committee is superior to those of individuals, provided the individuals have reasonable competence. Ensembles are sets of learning machines that combine in some way their decisions, or their learning algorithms, or different views of data, or other specific characteristics to obtain more reliable and more accurate predictions in supervised and unsupervised learning problems [48,116]. A simple example is represented by the majority vote ensemble, by which the decisions of different learning machines are combined, and the class that receives the majority of “votes” (i.e., the class predicted by the majority of the learning machines) is the class predicted by the overall ensemble [158]. In the literature, a plethora of terms other than ensembles has been used, such as fusion, combination, aggregation, and committee, to indicate sets of learning machines that work together to solve a machine learning problem [19,40,56,66,99,108,123], but in this chapter we maintain the term ensemble in its widest meaning, in order to include the whole range of combination methods. Nowadays, ensemble methods represent one of the main current research lines in machine learning [48,116], and the interest of the research community on ensemble methods is witnessed by conferences and workshops specifically devoted to ensembles, first of all the multiple classifier systems (MCS) conference organized by Roli, Kittler, Windeatt, and other researchers of this area [14,62,85,149,173]. Several theories have been

  6. NYYD Ensemble

    Index Scriptorium Estoniae

    2002-01-01

    NYYD Ensemble'i duost Traksmann - Lukk E.-S. Tüüri teosega "Symbiosis", mis on salvestatud ka hiljuti ilmunud NYYD Ensemble'i CDle. 2. märtsil Rakvere Teatri väikeses saalis ja 3. märtsil Rotermanni Soolalaos, kavas Tüür, Kaumann, Berio, Reich, Yun, Hauta-aho, Buckinx

  7. Assessing the hydrological response from an ensemble of CMIP5 climate projections in the transition zone of the Atlantic region (Bay of Biscay)

    Science.gov (United States)

    Meaurio, Maite; Zabaleta, Ane; Boithias, Laurie; Epelde, Ane Miren; Sauvage, Sabine; Sánchez-Pérez, Jose-Miguel; Srinivasan, Raghavan; Antiguedad, Iñaki

    2017-05-01

    The climate changes projected for the 21st century will have consequences on the hydrological response of catchments. These changes, and their consequences, are most uncertain in the transition zones. The study area, in the Bay of Biscay, is located in the transition zone of the European Atlantic region, where hydrological impact of climate change was scarcely studied. In order to address this scarcity, the hydrological impacts of climate change on river discharge were assessed. To do so, a hydrological modelling was carried out considering 16 climate scenarios that include 5 General Circulation Models (GCM) from the 5th report of the Coupled Model Intercomparison Project (CMIP5), 2 statistical downscaling methods and 2 Representative Concentration Pathways. Projections for future discharge (2011-2100) were divided into three 30-year horizons (2030s, 2060s and 2090s) and a comparison was made between these time horizons and the baseline (1961-2000). The results show that the downscaling method used resulted in a higher source of uncertainty than GCM itself. In addition, the uncertainties inherent to the methods used at all the levels do not affect the results equally along the year. In spite of those uncertainties, general trends for the 2090s predict seasonal discharge decreases by around -17% in autumn, -16% in spring, -11% in winter and -7% in summer. These results are in line with those predicted for the Atlantic region (France and the Iberian Peninsula). Trends for extreme flows were also analysed: the most significant show an increase in the duration (days) of low flows. From an environmental point of view, and considering the need to meet the objectives established by the Water Framework Directive (WFD), this will be a major challenge for the future planning on water management.

  8. Mesoscale Connections Summer 2017

    Energy Technology Data Exchange (ETDEWEB)

    Kippen, Karen Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Bourke, Mark Andrew M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-06-21

    Our challenge derives from the fact that in metals or explosives grains, interfaces and defects control engineering performance in ways that are neither amenable to continuum codes (which fail to rigorously describe the heterogeneities derived from microstructure) nor computationally tractable to first principles atomistic calculations. This is a region called the mesoscale, which stands at the frontier of our desire to translate fundamental science insights into confidence in aging system performance over the range of extreme conditions relevant in a nuclear weapon. For dynamic problems, the phenomena of interest can require extremely good temporal resolutions. A shock wave traveling at 1000 m/s (or 1 mm/μs) passes through a grain with a diameter of 1 micron in a nanosecond (10-9 sec). Thus, to observe the mesoscale phenomena—such as dislocations or phase transformations—as the shock passes, temporal resolution better than picoseconds (10-12 sec) may be needed. As we anticipate the science challenges over the next decade, experimental insights on material performance at the micron spatial scale with picosecond temporal resolution—at the mesoscale— are a clear challenge. This is a challenge fit for Los Alamos in partnership with our sister labs and academia. Mesoscale Connections will draw attention to our progress as we tackle the mesoscale challenge. We hope you like it and encourage suggestions of content you are interested in.

  9. Climate change impact on the discharge in meso-scale catchments and consequences for the hydropower-production in Switzerland

    Science.gov (United States)

    Rössler, Ole; Hänggi, Pascal; Köplin, Nina; Meyer, Rapahel; Schädler, Bruno; Weingartner, Rolf

    2013-04-01

    The potential effect of climate change on hydrology is the acceleration of the hydrological cycle that in turn will likely cause changes in the discharge regime. As a result, socio-economic systems (e.g., tourism, hydropower industry) may be drastically affected. In this study, we comprehensively analyzed the effect of climate change on different hydrological components like mean and low-flow levels, and drought stress in mesoscale catchments of Switzerland. In terms of mean flows approx. 200 catchments in Switzerland were simulated for the reference period 1984-2005 using the hydrological model PREVAH and projection for near (2025-2046) and far future (2074-2095) are based on delta-change values of 10 ENSEMBLES regional climate models assuming A1B emission scenario (CH2011 climate scenario data sets). We found seven distinct response types of catchments, each exhibiting a characteristic annual cycle of hydrologic change. A general pattern observed for all catchments, is the clearly decreasing summer runoff. Hence, within a second analysis of future discharge a special focus was set on summer low flow in a selection of 29 catchments in the Swiss Midlands. Low flows are critical as they have great implications on water usage and biodiversity. We re-calibrated the hydrological model PREVAH with a focus on base-flow and gauged discharge and used the aforementioned climate data sets and simulation time periods. We found low flow situations to be very likely to increase in both, magnitude and duration, especially in central and western Switzerland plateau. At third, the drought stress potential was analyzed by simulating the soil moisture level under climate change conditions in a high mountain catchment. We used the distributed hydrological model WaSiM-ETH for this aspect as soil characteristics are much better represented in this model. Soil moisture in forests below 2000 m a.s.l. were found to be affected at most, which might have implication to their function as

  10. Ensembl 2004.

    Science.gov (United States)

    Birney, E; Andrews, D; Bevan, P; Caccamo, M; Cameron, G; Chen, Y; Clarke, L; Coates, G; Cox, T; Cuff, J; Curwen, V; Cutts, T; Down, T; Durbin, R; Eyras, E; Fernandez-Suarez, X M; Gane, P; Gibbins, B; Gilbert, J; Hammond, M; Hotz, H; Iyer, V; Kahari, A; Jekosch, K; Kasprzyk, A; Keefe, D; Keenan, S; Lehvaslaiho, H; McVicker, G; Melsopp, C; Meidl, P; Mongin, E; Pettett, R; Potter, S; Proctor, G; Rae, M; Searle, S; Slater, G; Smedley, D; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Storey, R; Ureta-Vidal, A; Woodwark, C; Clamp, M; Hubbard, T

    2004-01-01

    The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organize biology around the sequences of large genomes. It is a comprehensive and integrated source of annotation of large genome sequences, available via interactive website, web services or flat files. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. The facilities of the system range from sequence analysis to data storage and visualization and installations exist around the world both in companies and at academic sites. With a total of nine genome sequences available from Ensembl and more genomes to follow, recent developments have focused mainly on closer integration between genomes and external data.

  11. An educational model for ensemble streamflow simulation and uncertainty analysis

    Directory of Open Access Journals (Sweden)

    A. AghaKouchak

    2013-02-01

    Full Text Available This paper presents the hands-on modeling toolbox, HBV-Ensemble, designed as a complement to theoretical hydrology lectures, to teach hydrological processes and their uncertainties. The HBV-Ensemble can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI and an ensemble simulation scheme that can be used for teaching uncertainty analysis, parameter estimation, ensemble simulation and model sensitivity. HBV-Ensemble was administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of uncertainty in hydrological modeling.

  12. An Integrated Ensemble-Based Operational Framework to Predict Urban Flooding: A Case Study of Hurricane Sandy in the Passaic and Hackensack River Basins

    Science.gov (United States)

    Saleh, F.; Ramaswamy, V.; Georgas, N.; Blumberg, A. F.; Wang, Y.

    2016-12-01

    Advances in computational resources and modeling techniques are opening the path to effectively integrate existing complex models. In the context of flood prediction, recent extreme events have demonstrated the importance of integrating components of the hydrosystem to better represent the interactions amongst different physical processes and phenomena. As such, there is a pressing need to develop holistic and cross-disciplinary modeling frameworks that effectively integrate existing models and better represent the operative dynamics. This work presents a novel Hydrologic-Hydraulic-Hydrodynamic Ensemble (H3E) flood prediction framework that operationally integrates existing predictive models representing coastal (New York Harbor Observing and Prediction System, NYHOPS), hydrologic (US Army Corps of Engineers Hydrologic Modeling System, HEC-HMS) and hydraulic (2-dimensional River Analysis System, HEC-RAS) components. The state-of-the-art framework is forced with 125 ensemble meteorological inputs from numerical weather prediction models including the Global Ensemble Forecast System, the European Centre for Medium-Range Weather Forecasts (ECMWF), the Canadian Meteorological Centre (CMC), the Short Range Ensemble Forecast (SREF) and the North American Mesoscale Forecast System (NAM). The framework produces, within a 96-hour forecast horizon, on-the-fly Google Earth flood maps that provide critical information for decision makers and emergency preparedness managers. The utility of the framework was demonstrated by retrospectively forecasting an extreme flood event, hurricane Sandy in the Passaic and Hackensack watersheds (New Jersey, USA). Hurricane Sandy caused significant damage to a number of critical facilities in this area including the New Jersey Transit's main storage and maintenance facility. The results of this work demonstrate that ensemble based frameworks provide improved flood predictions and useful information about associated uncertainties, thus

  13. Ensembl 2017

    OpenAIRE

    Aken, Bronwen L.; Achuthan, Premanand; Akanni, Wasiu; Amode, M. Ridwan; Bernsdorff, Friederike; Bhai, Jyothish; Billis, Konstantinos; Carvalho-Silva, Denise; Cummins, Carla; Clapham, Peter; Gil, Laurent; Gir?n, Carlos Garc?a; Gordon, Leo; Hourlier, Thibaut; Hunt, Sarah E.

    2016-01-01

    Ensembl (www.ensembl.org) is a database and genome browser for enabling research on vertebrate genomes. We import, analyse, curate and integrate a diverse collection of large-scale reference data to create a more comprehensive view of genome biology than would be possible from any individual dataset. Our extensive data resources include evidence-based gene and regulatory region annotation, genome variation and gene trees. An accompanying suite of tools, infrastructure and programmatic access ...

  14. Ensemble Sampling

    OpenAIRE

    Lu, Xiuyuan; Van Roy, Benjamin

    2017-01-01

    Thompson sampling has emerged as an effective heuristic for a broad range of online decision problems. In its basic form, the algorithm requires computing and sampling from a posterior distribution over models, which is tractable only for simple special cases. This paper develops ensemble sampling, which aims to approximate Thompson sampling while maintaining tractability even in the face of complex models such as neural networks. Ensemble sampling dramatically expands on the range of applica...

  15. Ensemble atmospheric dispersion calculations for decision support systems

    International Nuclear Information System (INIS)

    Borysiewicz, M.; Potempski, S.; Galkowski, A.; Zelazny, R.

    2003-01-01

    This document describes two approaches to long-range atmospheric dispersion of pollutants based on the ensemble concept. In the first part of the report some experiences related to the exercises undertaken under the ENSEMBLE project of the European Union are presented. The second part is devoted to the implementation of mesoscale numerical prediction models RAMS and atmospheric dispersion model HYPACT on Beowulf cluster and theirs usage for ensemble forecasting and long range atmospheric ensemble dispersion calculations based on available meteorological data from NCEO, NOAA (USA). (author)

  16. Mesoscale hybrid calibration artifact

    Science.gov (United States)

    Tran, Hy D.; Claudet, Andre A.; Oliver, Andrew D.

    2010-09-07

    A mesoscale calibration artifact, also called a hybrid artifact, suitable for hybrid dimensional measurement and the method for make the artifact. The hybrid artifact has structural characteristics that make it suitable for dimensional measurement in both vision-based systems and touch-probe-based systems. The hybrid artifact employs the intersection of bulk-micromachined planes to fabricate edges that are sharp to the nanometer level and intersecting planes with crystal-lattice-defined angles.

  17. Mesoscale Climate Evaluation Using Grid Computing

    Science.gov (United States)

    Campos Velho, H. F.; Freitas, S. R.; Souto, R. P.; Charao, A. S.; Ferraz, S.; Roberti, D. R.; Streck, N.; Navaux, P. O.; Maillard, N.; Collischonn, W.; Diniz, G.; Radin, B.

    2012-04-01

    The CLIMARS project is focused to establish an operational environment for seasonal climate prediction for the Rio Grande do Sul state, Brazil. The dynamical downscaling will be performed with the use of several software platforms and hardware infrastructure to carry out the investigation on mesoscale of the global change impact. The grid computing takes advantage of geographically spread out computer systems, connected by the internet, for enhancing the power of computation. The ensemble climate prediction is an appropriated application for processing on grid computing, because the integration of each ensemble member does not have a dependency on information from another ensemble members. The grid processing is employed to compute the 20-year climatology and the long range simulations under ensemble methodology. BRAMS (Brazilian Regional Atmospheric Model) is a mesoscale model developed from a version of the RAMS (from the Colorado State University - CSU, USA). BRAMS model is the tool for carrying out the dynamical downscaling from the IPCC scenarios. Long range BRAMS simulations will provide data for some climate (data) analysis, and supply data for numerical integration of different models: (a) Regime of the extreme events for temperature and precipitation fields: statistical analysis will be applied on the BRAMS data, (b) CCATT-BRAMS (Coupled Chemistry Aerosol Tracer Transport - BRAMS) is an environmental prediction system that will be used to evaluate if the new standards of temperature, rain regime, and wind field have a significant impact on the pollutant dispersion in the analyzed regions, (c) MGB-IPH (Portuguese acronym for the Large Basin Model (MGB), developed by the Hydraulic Research Institute, (IPH) from the Federal University of Rio Grande do Sul (UFRGS), Brazil) will be employed to simulate the alteration of the river flux under new climate patterns. Important meteorological input variables for the MGB-IPH are the precipitation (most relevant

  18. Coupling meteorological and hydrological models for flood forecasting

    Directory of Open Access Journals (Sweden)

    Bartholmes

    2005-01-01

    Full Text Available This paper deals with the problem of analysing the coupling of meteorological meso-scale quantitative precipitation forecasts with distributed rainfall-runoff models to extend the forecasting horizon. Traditionally, semi-distributed rainfall-runoff models have been used for real time flood forecasting. More recently, increased computer capabilities allow the utilisation of distributed hydrological models with mesh sizes from tenths of metres to a few kilometres. On the other hand, meteorological models, providing the quantitative precipitation forecast, tend to produce average values on meshes ranging from slightly less than 10 to 200 kilometres. Therefore, to improve the quality of flood forecasts, the effects of coupling the meteorological and the hydrological models at different scales were analysed. A distributed hydrological model (TOPKAPI was developed and calibrated using a 1x1 km mesh for the case of the river Po closed at Ponte Spessa (catchment area c. 37000 km2. The model was then coupled with several other European meteorological models ranging from the Limited Area Models (provided by DMI and DWD with resolutions from 0.0625° * 0.0625°, to the ECMWF ensemble predictions with a resolution of 1.85° * 1.85°. Interesting results, describing the coupled model behaviour, are available for a meteorological extreme event in Northern Italy (Nov. 1994. The results demonstrate the poor reliability of the quantitative precipitation forecasts produced by meteorological models presently available; this is not resolved using the Ensemble Forecasting technique, when compared with results obtainable with measured rainfall.

  19. Development of multimodel ensemble based district level medium ...

    Indian Academy of Sciences (India)

    tively by computing the anomaly correlation coef- ficient between the predicted rainfall and observed rainfall. High resolution (lat./long.) gridded data ..... particularly in the prediction of intensity and mesoscale rainfall features causing inland flooding. During recent years, Ensemble. Prediction System (EPS) has emerged as ...

  20. Impacts of calibration strategies and ensemble methods on ensemble flood forecasting over Lanjiang basin, Southeast China

    Science.gov (United States)

    Liu, Li; Xu, Yue-Ping

    2017-04-01

    Ensemble flood forecasting driven by numerical weather prediction products is becoming more commonly used in operational flood forecasting applications.In this study, a hydrological ensemble flood forecasting system based on Variable Infiltration Capacity (VIC) model and quantitative precipitation forecasts from TIGGE dataset is constructed for Lanjiang Basin, Southeast China. The impacts of calibration strategies and ensemble methods on the performance of the system are then evaluated.The hydrological model is optimized by parallel programmed ɛ-NSGAII multi-objective algorithm and two respectively parameterized models are determined to simulate daily flows and peak flows coupled with a modular approach.The results indicatethat the ɛ-NSGAII algorithm permits more efficient optimization and rational determination on parameter setting.It is demonstrated that the multimodel ensemble streamflow mean have better skills than the best singlemodel ensemble mean (ECMWF) and the multimodel ensembles weighted on members and skill scores outperform other multimodel ensembles. For typical flood event, it is proved that the flood can be predicted 3-4 days in advance, but the flows in rising limb can be captured with only 1-2 days ahead due to the flash feature. With respect to peak flows selected by Peaks Over Threshold approach, the ensemble means from either singlemodel or multimodels are generally underestimated as the extreme values are smoothed out by ensemble process.

  1. Characterization of Mesoscale Predictability

    Science.gov (United States)

    2017-11-09

    over time scales much shorter than anticipated. Part of the motivation for this effort is to help inform the community of the need to move beyond 1...line colors given in the legend) for the ensemble initialized (a) : 12 UTC 4 February and (b) : 12 UTC 25 December. Only those wavelengths greater...model every 6 hours {line colors given in the legend); black curve shows the saturation spectrum. (b) identical to Fig 1 b, except that the curves for

  2. Ensemble Bayesian forecasting system Part I: Theory and algorithms

    Science.gov (United States)

    Herr, Henry D.; Krzysztofowicz, Roman

    2015-05-01

    The ensemble Bayesian forecasting system (EBFS), whose theory was published in 2001, is developed for the purpose of quantifying the total uncertainty about a discrete-time, continuous-state, non-stationary stochastic process such as a time series of stages, discharges, or volumes at a river gauge. The EBFS is built of three components: an input ensemble forecaster (IEF), which simulates the uncertainty associated with random inputs; a deterministic hydrologic model (of any complexity), which simulates physical processes within a river basin; and a hydrologic uncertainty processor (HUP), which simulates the hydrologic uncertainty (an aggregate of all uncertainties except input). It works as a Monte Carlo simulator: an ensemble of time series of inputs (e.g., precipitation amounts) generated by the IEF is transformed deterministically through a hydrologic model into an ensemble of time series of outputs, which is next transformed stochastically by the HUP into an ensemble of time series of predictands (e.g., river stages). Previous research indicated that in order to attain an acceptable sampling error, the ensemble size must be on the order of hundreds (for probabilistic river stage forecasts and probabilistic flood forecasts) or even thousands (for probabilistic stage transition forecasts). The computing time needed to run the hydrologic model this many times renders the straightforward simulations operationally infeasible. This motivates the development of the ensemble Bayesian forecasting system with randomization (EBFSR), which takes full advantage of the analytic meta-Gaussian HUP and generates multiple ensemble members after each run of the hydrologic model; this auxiliary randomization reduces the required size of the meteorological input ensemble and makes it operationally feasible to generate a Bayesian ensemble forecast of large size. Such a forecast quantifies the total uncertainty, is well calibrated against the prior (climatic) distribution of

  3. A new Method for the Estimation of Initial Condition Uncertainty Structures in Mesoscale Models

    Science.gov (United States)

    Keller, J. D.; Bach, L.; Hense, A.

    2012-12-01

    The estimation of fast growing error modes of a system is a key interest of ensemble data assimilation when assessing uncertainty in initial conditions. Over the last two decades three methods (and variations of these methods) have evolved for global numerical weather prediction models: ensemble Kalman filter, singular vectors and breeding of growing modes (or now ensemble transform). While the former incorporates a priori model error information and observation error estimates to determine ensemble initial conditions, the latter two techniques directly address the error structures associated with Lyapunov vectors. However, in global models these structures are mainly associated with transient global wave patterns. When assessing initial condition uncertainty in mesoscale limited area models, several problems regarding the aforementioned techniques arise: (a) additional sources of uncertainty on the smaller scales contribute to the error and (b) error structures from the global scale may quickly move through the model domain (depending on the size of the domain). To address the latter problem, perturbation structures from global models are often included in the mesoscale predictions as perturbed boundary conditions. However, the initial perturbations (when used) are often generated with a variant of an ensemble Kalman filter which does not necessarily focus on the large scale error patterns. In the framework of the European regional reanalysis project of the Hans-Ertel-Center for Weather Research we use a mesoscale model with an implemented nudging data assimilation scheme which does not support ensemble data assimilation at all. In preparation of an ensemble-based regional reanalysis and for the estimation of three-dimensional atmospheric covariance structures, we implemented a new method for the assessment of fast growing error modes for mesoscale limited area models. The so-called self-breeding is development based on the breeding of growing modes technique

  4. On the forecast skill of a convection-permitting ensemble

    Science.gov (United States)

    Schellander-Gorgas, Theresa; Wang, Yong; Meier, Florian; Weidle, Florian; Wittmann, Christoph; Kann, Alexander

    2017-01-01

    The 2.5 km convection-permitting (CP) ensemble AROME-EPS (Applications of Research to Operations at Mesoscale - Ensemble Prediction System) is evaluated by comparison with the regional 11 km ensemble ALADIN-LAEF (Aire Limitée Adaption dynamique Développement InterNational - Limited Area Ensemble Forecasting) to show whether a benefit is provided by a CP EPS. The evaluation focuses on the abilities of the ensembles to quantitatively predict precipitation during a 3-month convective summer period over areas consisting of mountains and lowlands. The statistical verification uses surface observations and 1 km × 1 km precipitation analyses, and the verification scores involve state-of-the-art statistical measures for deterministic and probabilistic forecasts as well as novel spatial verification methods. The results show that the convection-permitting ensemble with higher-resolution AROME-EPS outperforms its mesoscale counterpart ALADIN-LAEF for precipitation forecasts. The positive impact is larger for the mountainous areas than for the lowlands. In particular, the diurnal precipitation cycle is improved in AROME-EPS, which leads to a significant improvement of scores at the concerned times of day (up to approximately one-third of the scored verification measure). Moreover, there are advantages for higher precipitation thresholds at small spatial scales, which are due to the improved simulation of the spatial structure of precipitation.

  5. Acoustic Characterization of Mesoscale Objects

    Energy Technology Data Exchange (ETDEWEB)

    Chinn, D; Huber, R; Chambers, D; Cole, G; Balogun, O; Spicer, J; Murray, T

    2007-03-13

    This report describes the science and engineering performed to provide state-of-the-art acoustic capabilities for nondestructively characterizing mesoscale (millimeter-sized) objects--allowing micrometer resolution over the objects entire volume. Materials and structures used in mesoscale objects necessitate the use of (1) GHz acoustic frequencies and (2) non-contacting laser generation and detection of acoustic waves. This effort demonstrated that acoustic methods at gigahertz frequencies have the necessary penetration depth and spatial resolution to effectively detect density discontinuities, gaps, and delaminations. A prototype laser-based ultrasonic system was designed and built. The system uses a micro-chip laser for excitation of broadband ultrasonic waves with frequency components reaching 1.0 GHz, and a path-stabilized Michelson interferometer for detection. The proof-of-concept for mesoscale characterization is demonstrated by imaging a micro-fabricated etched pattern in a 70 {micro}m thick silicon wafer.

  6. HIGH-RESOLUTION ATMOSPHERIC ENSEMBLE MODELING AT SRNL

    Energy Technology Data Exchange (ETDEWEB)

    Buckley, R.; Werth, D.; Chiswell, S.; Etherton, B.

    2011-05-10

    The High-Resolution Mid-Atlantic Forecasting Ensemble (HME) is a federated effort to improve operational forecasts related to precipitation, convection and boundary layer evolution, and fire weather utilizing data and computing resources from a diverse group of cooperating institutions in order to create a mesoscale ensemble from independent members. Collaborating organizations involved in the project include universities, National Weather Service offices, and national laboratories, including the Savannah River National Laboratory (SRNL). The ensemble system is produced from an overlapping numerical weather prediction model domain and parameter subsets provided by each contributing member. The coordination, synthesis, and dissemination of the ensemble information are performed by the Renaissance Computing Institute (RENCI) at the University of North Carolina-Chapel Hill. This paper discusses background related to the HME effort, SRNL participation, and example results available from the RENCI website.

  7. Evaluation of medium-range ensemble flood forecasting based on calibration strategies and ensemble methods in Lanjiang Basin, Southeast China

    Science.gov (United States)

    Liu, Li; Gao, Chao; Xuan, Weidong; Xu, Yue-Ping

    2017-11-01

    Ensemble flood forecasts by hydrological models using numerical weather prediction products as forcing data are becoming more commonly used in operational flood forecasting applications. In this study, a hydrological ensemble flood forecasting system comprised of an automatically calibrated Variable Infiltration Capacity model and quantitative precipitation forecasts from TIGGE dataset is constructed for Lanjiang Basin, Southeast China. The impacts of calibration strategies and ensemble methods on the performance of the system are then evaluated. The hydrological model is optimized by the parallel programmed ε-NSGA II multi-objective algorithm. According to the solutions by ε-NSGA II, two differently parameterized models are determined to simulate daily flows and peak flows at each of the three hydrological stations. Then a simple yet effective modular approach is proposed to combine these daily and peak flows at the same station into one composite series. Five ensemble methods and various evaluation metrics are adopted. The results show that ε-NSGA II can provide an objective determination on parameter estimation, and the parallel program permits a more efficient simulation. It is also demonstrated that the forecasts from ECMWF have more favorable skill scores than other Ensemble Prediction Systems. The multimodel ensembles have advantages over all the single model ensembles and the multimodel methods weighted on members and skill scores outperform other methods. Furthermore, the overall performance at three stations can be satisfactory up to ten days, however the hydrological errors can degrade the skill score by approximately 2 days, and the influence persists until a lead time of 10 days with a weakening trend. With respect to peak flows selected by the Peaks Over Threshold approach, the ensemble means from single models or multimodels are generally underestimated, indicating that the ensemble mean can bring overall improvement in forecasting of flows. For

  8. Evaluation of high intensity precipitation from 16 Regional climate models over a meso-scale catchment in the Midlands Regions of England

    Science.gov (United States)

    Wetterhall, F.; He, Y.; Cloke, H.; Pappenberger, F.; Freer, J.; Wilson, M.; McGregor, G.

    2009-04-01

    Local flooding events are often triggered by high-intensity rain-fall events, and it is important that these can be correctly modelled by Regional Climate Models (RCMs) if the results are to be used in climate impact assessment. In this study, daily precipitation from 16 RCMs was compared with observations over a meso-scale catchment in the Midlands Region of England. The RCM data was provided from the European research project ENSEMBLES and the precipitation data from the UK MetOffice. The RCMs were all driven by reanalysis data from the ERA40 dataset over the time period 1961-2000. The ENSEMBLES data is on the spatial scale of 25 x 25 km and it was disaggregated onto a 5 x 5 km grid over the catchment and compared with interpolated observational data with the same resolution. The mean precipitation was generally underestimated by the ENSEMBLES data, and the maximum and persistence of high intensity rainfall was even more underestimated. The inter-annual variability was not fully captured by the RCMs, and there was a systematic underestimation of precipitation during the autumn months. The spatial pattern in the modelled precipitation data was too smooth in comparison with the observed data, especially in the high altitudes in the western part of the catchment where the high precipitation usually occurs. The RCM outputs cannot reproduce the current high intensity precipitation events that are needed to sufficiently model extreme flood events. The results point out the discrepancy between climate model output and the high intensity precipitation input needs for hydrological impact modelling.

  9. World Music Ensemble: Kulintang

    Science.gov (United States)

    Beegle, Amy C.

    2012-01-01

    As instrumental world music ensembles such as steel pan, mariachi, gamelan and West African drums are becoming more the norm than the exception in North American school music programs, there are other world music ensembles just starting to gain popularity in particular parts of the United States. The kulintang ensemble, a drum and gong ensemble…

  10. GLOFRIM v1.0-A globally applicable computational framework for integrated hydrological-hydrodynamic modelling

    NARCIS (Netherlands)

    Hoch, Jannis M.; Neal, Jeffrey C.; Baart, Fedor; Van Beek, Rens; Winsemius, Hessel C.; Bates, Paul D.; Bierkens, Marc F.P.

    2017-01-01

    We here present GLOFRIM, a globally applicable computational framework for integrated hydrological-hydrodynamic modelling. GLOFRIM facilitates spatially explicit coupling of hydrodynamic and hydrologic models and caters for an ensemble of models to be coupled. It currently encompasses the global

  11. Mesoscale climate hydrology: Earth Observation System - definition phase

    NARCIS (Netherlands)

    Menenti, M.; Bastiaanssen, W.G.M.

    1997-01-01

    The use of airborne and space observations to map surface heat fluxes and soil water content at heterogeneous land surfaces was studied. Algorithms to estimate evaporation fluxes with satellite observations were evaluated against measurements. Spatialcorrelation lengths were studied with estimated

  12. Mesoscale climate hydrology: Earth Observation System - definition phase

    NARCIS (Netherlands)

    Menenti, M.; Bastiaanssen, W.G.M.

    1995-01-01

    The use of airborne and space observations to map surface heat fluxes and soil water content at heterogeneous land surfaces was studied. Algorithms to estimate evaporation fluxes with satellite observations were evaluated against measurements. Spatialcorrelation lengths were studied with estimated

  13. Forest hydrology

    Science.gov (United States)

    Ge Sun; Devendra Amatya; Steve McNulty

    2016-01-01

    Forest hydrology studies the distribution, storage, movement, and quality of water and the hydrological processes in forest-dominated ecosystems. Forest hydrological science is regarded as the foundation of modern integrated water¬shed management. This chapter provides an overview of the history of forest hydrology and basic principles of this unique branch of...

  14. Mesoscale Modeling, Forecasting and Remote Sensing Research.

    Science.gov (United States)

    remote sensing , cyclonic scale diagnostic studies and mesoscale numerical modeling and forecasting are summarized. Mechanisms involved in the release of potential instability are discussed and simulated quantitatively, giving particular attention to the convective formulation. The basic mesoscale model is documented including the equations, boundary condition, finite differences and initialization through an idealized frontal zone. Results of tests including a three dimensional test with real data, tests of convective/mesoscale interaction and tests with a detailed

  15. Mesoscale inversion of carbon sources and sinks

    International Nuclear Information System (INIS)

    Lauvaux, T.

    2008-01-01

    Inverse methods at large scales are used to infer the spatial variability of carbon sources and sinks over the continents but their uncertainties remain large. Atmospheric concentrations integrate the surface flux variability but atmospheric transport models at low resolution are not able to simulate properly the local atmospheric dynamics at the measurement sites. However, the inverse estimates are more representative of the large spatial heterogeneity of the ecosystems compared to direct flux measurements. Top-down and bottom-up methods that aim at quantifying the carbon exchanges between the surface and the atmosphere correspond to different scales and are not easily comparable. During this phD, a mesoscale inverse system was developed to correct carbon fluxes at 8 km resolution. The high resolution transport model MesoNH was used to simulate accurately the variability of the atmospheric concentrations, which allowed us to reduce the uncertainty of the retrieved fluxes. All the measurements used here were observed during the intensive regional campaign CERES of May and June 2005, during which several instrumented towers measured CO 2 concentrations and fluxes in the South West of France. Airborne measurements allowed us to observe concentrations at high altitude but also CO 2 surface fluxes over large parts of the domain. First, the capacity of the inverse system to correct the CO 2 fluxes was estimated using pseudo-data experiments. The largest fraction of the concentration variability was attributed to regional surface fluxes over an area of about 300 km around the site locations depending on the meteorological conditions. Second, an ensemble of simulations allowed us to define the spatial and temporal structures of the transport errors. Finally, the inverse fluxes at 8 km resolution were compared to direct flux measurements. The inverse system has been validated in space and time and showed an improvement of the first guess fluxes from a vegetation model

  16. Mesoscale modeling of amorphous metals by shear transformation zone dynamics

    International Nuclear Information System (INIS)

    Homer, Eric R.; Schuh, Christopher A.

    2009-01-01

    A new mesoscale modeling technique for the thermo-mechanical behavior of metallic glasses is proposed. The modeling framework considers the shear transformation zone (STZ) as the fundamental unit of deformation, and coarse-grains an amorphous collection of atoms into an ensemble of STZs on a mesh. By employing finite element analysis and a kinetic Monte Carlo algorithm, the modeling technique is capable of simulating glass processing and deformation on time and length scales greater than those usually attainable by atomistic modeling. A thorough explanation of the framework is presented, along with a specific two-dimensional implementation for a model metallic glass. The model is shown to capture the basic behaviors of metallic glasses, including high-temperature homogeneous flow following the expected constitutive law, and low-temperature strain localization into shear bands. Details of the effects of processing and thermal history on the glass structure and properties are also discussed.

  17. Derivation and precision of mean field electrodynamics with mesoscale fluctuations

    Science.gov (United States)

    Zhou, Hongzhe; Blackman, Eric G.

    2018-06-01

    Mean field electrodynamics (MFE) facilitates practical modelling of secular, large scale properties of astrophysical or laboratory systems with fluctuations. Practitioners commonly assume wide scale separation between mean and fluctuating quantities, to justify equality of ensemble and spatial or temporal averages. Often however, real systems do not exhibit such scale separation. This raises two questions: (I) What are the appropriate generalized equations of MFE in the presence of mesoscale fluctuations? (II) How precise are theoretical predictions from MFE? We address both by first deriving the equations of MFE for different types of averaging, along with mesoscale correction terms that depend on the ratio of averaging scale to variation scale of the mean. We then show that even if these terms are small, predictions of MFE can still have a significant precision error. This error has an intrinsic contribution from the dynamo input parameters and a filtering contribution from differences in the way observations and theory are projected through the measurement kernel. Minimizing the sum of these contributions can produce an optimal scale of averaging that makes the theory maximally precise. The precision error is important to quantify when comparing to observations because it quantifies the resolution of predictive power. We exemplify these principles for galactic dynamos, comment on broader implications, and identify possibilities for further work.

  18. Flood Forecasting Based on TIGGE Precipitation Ensemble Forecast

    Directory of Open Access Journals (Sweden)

    Jinyin Ye

    2016-01-01

    Full Text Available TIGGE (THORPEX International Grand Global Ensemble was a major part of the THORPEX (Observing System Research and Predictability Experiment. It integrates ensemble precipitation products from all the major forecast centers in the world and provides systematic evaluation on the multimodel ensemble prediction system. Development of meteorologic-hydrologic coupled flood forecasting model and early warning model based on the TIGGE precipitation ensemble forecast can provide flood probability forecast, extend the lead time of the flood forecast, and gain more time for decision-makers to make the right decision. In this study, precipitation ensemble forecast products from ECMWF, NCEP, and CMA are used to drive distributed hydrologic model TOPX. We focus on Yi River catchment and aim to build a flood forecast and early warning system. The results show that the meteorologic-hydrologic coupled model can satisfactorily predict the flow-process of four flood events. The predicted occurrence time of peak discharges is close to the observations. However, the magnitude of the peak discharges is significantly different due to various performances of the ensemble prediction systems. The coupled forecasting model can accurately predict occurrence of the peak time and the corresponding risk probability of peak discharge based on the probability distribution of peak time and flood warning, which can provide users a strong theoretical foundation and valuable information as a promising new approach.

  19. Multi-model analysis in hydrological prediction

    Science.gov (United States)

    Lanthier, M.; Arsenault, R.; Brissette, F.

    2017-12-01

    Hydrologic modelling, by nature, is a simplification of the real-world hydrologic system. Therefore ensemble hydrological predictions thus obtained do not present the full range of possible streamflow outcomes, thereby producing ensembles which demonstrate errors in variance such as under-dispersion. Past studies show that lumped models used in prediction mode can return satisfactory results, especially when there is not enough information available on the watershed to run a distributed model. But all lumped models greatly simplify the complex processes of the hydrologic cycle. To generate more spread in the hydrologic ensemble predictions, multi-model ensembles have been considered. In this study, the aim is to propose and analyse a method that gives an ensemble streamflow prediction that properly represents the forecast probabilities and reduced ensemble bias. To achieve this, three simple lumped models are used to generate an ensemble. These will also be combined using multi-model averaging techniques, which generally generate a more accurate hydrogram than the best of the individual models in simulation mode. This new predictive combined hydrogram is added to the ensemble, thus creating a large ensemble which may improve the variability while also improving the ensemble mean bias. The quality of the predictions is then assessed on different periods: 2 weeks, 1 month, 3 months and 6 months using a PIT Histogram of the percentiles of the real observation volumes with respect to the volumes of the ensemble members. Initially, the models were run using historical weather data to generate synthetic flows. This worked for individual models, but not for the multi-model and for the large ensemble. Consequently, by performing data assimilation at each prediction period and thus adjusting the initial states of the models, the PIT Histogram could be constructed using the observed flows while allowing the use of the multi-model predictions. The under-dispersion has been

  20. Wake modelling combining mesoscale and microscale models

    DEFF Research Database (Denmark)

    Badger, Jake; Volker, Patrick; Prospathospoulos, J.

    2013-01-01

    In this paper the basis for introducing thrust information from microscale wake models into mesocale model wake parameterizations will be described. A classification system for the different types of mesoscale wake parameterizations is suggested and outlined. Four different mesoscale wake paramet...

  1. Extracting information from an ensemble of GCMs to reliably assess future global runoff change

    NARCIS (Netherlands)

    Sperna Weiland, F.C.; Beek, L.P.H. van; Weerts, A.H.; Bierkens, M.F.P.

    2011-01-01

    Future runoff projections derived from different global climate models (GCMs) show large differences. Therefore, within this study the, information from multiple GCMs has been combined to better assess hydrological changes. For projections of precipitation and temperature the Reliability ensemble

  2. Hydrology Project

    International Nuclear Information System (INIS)

    Anon.

    Research carried out in the 'Hydrology Project' of the Centro de Energia Nuclear na Agricultura', Piracicaba, Sao Paulo State, Brazil, are described. Such research comprises: Amazon hydrology and Northeast hydrology. Techniques for the measurement of isotope ratios are used. (M.A.) [pt

  3. Multilevel ensemble Kalman filter

    KAUST Repository

    Chernov, Alexey; Hoel, Haakon; Law, Kody; Nobile, Fabio; Tempone, Raul

    2016-01-01

    This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.

  4. Entropy of network ensembles

    Science.gov (United States)

    Bianconi, Ginestra

    2009-03-01

    In this paper we generalize the concept of random networks to describe network ensembles with nontrivial features by a statistical mechanics approach. This framework is able to describe undirected and directed network ensembles as well as weighted network ensembles. These networks might have nontrivial community structure or, in the case of networks embedded in a given space, they might have a link probability with a nontrivial dependence on the distance between the nodes. These ensembles are characterized by their entropy, which evaluates the cardinality of networks in the ensemble. In particular, in this paper we define and evaluate the structural entropy, i.e., the entropy of the ensembles of undirected uncorrelated simple networks with given degree sequence. We stress the apparent paradox that scale-free degree distributions are characterized by having small structural entropy while they are so widely encountered in natural, social, and technological complex systems. We propose a solution to the paradox by proving that scale-free degree distributions are the most likely degree distribution with the corresponding value of the structural entropy. Finally, the general framework we present in this paper is able to describe microcanonical ensembles of networks as well as canonical or hidden-variable network ensembles with significant implications for the formulation of network-constructing algorithms.

  5. Multilevel ensemble Kalman filter

    KAUST Repository

    Chernov, Alexey

    2016-01-06

    This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.

  6. The Ensembl REST API: Ensembl Data for Any Language.

    Science.gov (United States)

    Yates, Andrew; Beal, Kathryn; Keenan, Stephen; McLaren, William; Pignatelli, Miguel; Ritchie, Graham R S; Ruffier, Magali; Taylor, Kieron; Vullo, Alessandro; Flicek, Paul

    2015-01-01

    We present a Web service to access Ensembl data using Representational State Transfer (REST). The Ensembl REST server enables the easy retrieval of a wide range of Ensembl data by most programming languages, using standard formats such as JSON and FASTA while minimizing client work. We also introduce bindings to the popular Ensembl Variant Effect Predictor tool permitting large-scale programmatic variant analysis independent of any specific programming language. The Ensembl REST API can be accessed at http://rest.ensembl.org and source code is freely available under an Apache 2.0 license from http://github.com/Ensembl/ensembl-rest. © The Author 2014. Published by Oxford University Press.

  7. Sequential ensemble-based optimal design for parameter estimation: SEQUENTIAL ENSEMBLE-BASED OPTIMAL DESIGN

    Energy Technology Data Exchange (ETDEWEB)

    Man, Jun [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Zhang, Jiangjiang [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Li, Weixuan [Pacific Northwest National Laboratory, Richland Washington USA; Zeng, Lingzao [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Wu, Laosheng [Department of Environmental Sciences, University of California, Riverside California USA

    2016-10-01

    The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees of freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.

  8. Musical ensembles in Ancient Mesapotamia

    NARCIS (Netherlands)

    Krispijn, T.J.H.; Dumbrill, R.; Finkel, I.

    2010-01-01

    Identification of musical instruments from ancient Mesopotamia by comparing musical ensembles attested in Sumerian and Akkadian texts with depicted ensembles. Lexicographical contributions to the Sumerian and Akkadian lexicon.

  9. Meso-scale wind variability. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Larsen, S.; Larsen, X.; Vincent, C.; Soerensen, P.; Pinson, P.; Trombe, P.-J.; Madsen, H.; Cutululis, N.

    2011-11-15

    The project has aimed to characterize mesoscale meteorological phenomenon for the North Sea and the Inner Danish waters, and additionally aimed on improving the predictability and quality of the power production from offshore windfarms. The meso-scale meteorology has been characterized with respect to the physical processes, climatology, spectral characteristics and correlation properties based on measurements from wind farms, satellite data (SAR) and mesoscale numerical modeling (WRF). The abilities of the WRF model to characterize and predict relevant mesoscale phenomenon has been proven. Additionally application of statistical forecasting, using a Markov switching approach that can be related to the meteorological conditions, to analyze and short term predict the power production from an offshore wind farms have been documented. Two PhD studies have been conducted in connection with the project. The project has been a cooperative project between Risoe DTU, IMM DTU, DONG Energy, Vattenfall and VESTAS. It is registered as Energinet.dk, project no. 2007-1-7141. (Author)

  10. Error Covariance Estimation of Mesoscale Data Assimilation

    National Research Council Canada - National Science Library

    Xu, Qin

    2005-01-01

    The goal of this project is to explore and develop new methods of error covariance estimation that will provide necessary statistical descriptions of prediction and observation errors for mesoscale data assimilation...

  11. Ensemble Data Mining Methods

    Science.gov (United States)

    Oza, Nikunj C.

    2004-01-01

    Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve better prediction accuracy than any of the individual models could on their own. The basic goal when designing an ensemble is the same as when establishing a committee of people: each member of the committee should be as competent as possible, but the members should be complementary to one another. If the members are not complementary, Le., if they always agree, then the committee is unnecessary---any one member is sufficient. If the members are complementary, then when one or a few members make an error, the probability is high that the remaining members can correct this error. Research in ensemble methods has largely revolved around designing ensembles consisting of competent yet complementary models.

  12. Ensemble Data Mining Methods

    Data.gov (United States)

    National Aeronautics and Space Administration — Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve...

  13. Ensembl variation resources

    Directory of Open Access Journals (Sweden)

    Marin-Garcia Pablo

    2010-05-01

    Full Text Available Abstract Background The maturing field of genomics is rapidly increasing the number of sequenced genomes and producing more information from those previously sequenced. Much of this additional information is variation data derived from sampling multiple individuals of a given species with the goal of discovering new variants and characterising the population frequencies of the variants that are already known. These data have immense value for many studies, including those designed to understand evolution and connect genotype to phenotype. Maximising the utility of the data requires that it be stored in an accessible manner that facilitates the integration of variation data with other genome resources such as gene annotation and comparative genomics. Description The Ensembl project provides comprehensive and integrated variation resources for a wide variety of chordate genomes. This paper provides a detailed description of the sources of data and the methods for creating the Ensembl variation databases. It also explores the utility of the information by explaining the range of query options available, from using interactive web displays, to online data mining tools and connecting directly to the data servers programmatically. It gives a good overview of the variation resources and future plans for expanding the variation data within Ensembl. Conclusions Variation data is an important key to understanding the functional and phenotypic differences between individuals. The development of new sequencing and genotyping technologies is greatly increasing the amount of variation data known for almost all genomes. The Ensembl variation resources are integrated into the Ensembl genome browser and provide a comprehensive way to access this data in the context of a widely used genome bioinformatics system. All Ensembl data is freely available at http://www.ensembl.org and from the public MySQL database server at ensembldb.ensembl.org.

  14. Laser guidance of mesoscale particles

    Science.gov (United States)

    Underdown, Frank Hartman, Jr.

    Mesoscale particles are guided and trapped in hollow optical fibers using radiation pressure forces. Laser light from a 0.4W, 780nm diode laser is guided in a low- loss fiber mode and used to generate the guidance forces. Laser scattering and absorption forces propels particles along the fiber and polarization gradient forces attract them to the fiber's axial center. Using two counter propagating laser beams, inside the fiber, particles can be trapped in three dimensions. Measuring the spring constant of the trap gives the gradient force. This dissertation describes Rayleigh and Mie scattering models for calculating guidance forces. Calculated forces as a function of particle size and composition (i.e. dielectric, semiconductor, and metals) will be presented. For example, under typical experimental conditions 100nm Au particles are guided by a 2 × 10-14 N propulsive force in a water filled fiber. In comparison, the measured force, obtained from the particle's velocity and Stokes' law, is 7.98 × 10-14 N.

  15. Wetland Hydrology

    Science.gov (United States)

    This chapter discusses the state of the science in wetland hydrology by touching upon the major hydraulic and hydrologic processes in these complex ecosystems, their measurement/estimation techniques, and modeling methods. It starts with the definition of wetlands, their benefit...

  16. The impact of radiatively active water-ice clouds on Martian mesoscale atmospheric circulations

    Science.gov (United States)

    Spiga, A.; Madeleine, J.-B.; Hinson, D.; Navarro, T.; Forget, F.

    2014-04-01

    Background and Goals Water ice clouds are a key component of the Martian climate [1]. Understanding the properties of the Martian water ice clouds is crucial to constrain the Red Planet's climate and hydrological cycle both in the present and in the past [2]. In recent years, this statement have become all the more true as it was shown that the radiative effects of water ice clouds is far from being as negligible as hitherto believed; water ice clouds plays instead a key role in the large-scale thermal structure and dynamics of the Martian atmosphere [3, 4, 5]. Nevertheless, the radiative effect of water ice clouds at lower scales than the large synoptic scale (the so-called meso-scales) is still left to be explored. Here we use for the first time mesoscale modeling with radiatively active water ice clouds to address this open question.

  17. Skill of Global Raw and Postprocessed Ensemble Predictions of Rainfall over Northern Tropical Africa

    Science.gov (United States)

    Vogel, Peter; Knippertz, Peter; Fink, Andreas H.; Schlueter, Andreas; Gneiting, Tilmann

    2018-04-01

    Accumulated precipitation forecasts are of high socioeconomic importance for agriculturally dominated societies in northern tropical Africa. In this study, we analyze the performance of nine operational global ensemble prediction systems (EPSs) relative to climatology-based forecasts for 1 to 5-day accumulated precipitation based on the monsoon seasons 2007-2014 for three regions within northern tropical Africa. To assess the full potential of raw ensemble forecasts across spatial scales, we apply state-of-the-art statistical postprocessing methods in form of Bayesian Model Averaging (BMA) and Ensemble Model Output Statistics (EMOS), and verify against station and spatially aggregated, satellite-based gridded observations. Raw ensemble forecasts are uncalibrated, unreliable, and underperform relative to climatology, independently of region, accumulation time, monsoon season, and ensemble. Differences between raw ensemble and climatological forecasts are large, and partly stem from poor prediction for low precipitation amounts. BMA and EMOS postprocessed forecasts are calibrated, reliable, and strongly improve on the raw ensembles, but - somewhat disappointingly - typically do not outperform climatology. Most EPSs exhibit slight improvements over the period 2007-2014, but overall have little added value compared to climatology. We suspect that the parametrization of convection is a potential cause for the sobering lack of ensemble forecast skill in a region dominated by mesoscale convective systems.

  18. 'Lazy' quantum ensembles

    International Nuclear Information System (INIS)

    Parfionov, George; Zapatrin, Roman

    2006-01-01

    We compare different strategies aimed to prepare an ensemble with a given density matrix ρ. Preparing the ensemble of eigenstates of ρ with appropriate probabilities can be treated as 'generous' strategy: it provides maximal accessible information about the state. Another extremity is the so-called 'Scrooge' ensemble, which is mostly stingy in sharing the information. We introduce 'lazy' ensembles which require minimal effort to prepare the density matrix by selecting pure states with respect to completely random choice. We consider two parties, Alice and Bob, playing a kind of game. Bob wishes to guess which pure state is prepared by Alice. His null hypothesis, based on the lack of any information about Alice's intention, is that Alice prepares any pure state with equal probability. Then, the average quantum state measured by Bob turns out to be ρ, and he has to make a new hypothesis about Alice's intention solely based on the information that the observed density matrix is ρ. The arising 'lazy' ensemble is shown to be the alternative hypothesis which minimizes type I error

  19. The semantic similarity ensemble

    Directory of Open Access Journals (Sweden)

    Andrea Ballatore

    2013-12-01

    Full Text Available Computational measures of semantic similarity between geographic terms provide valuable support across geographic information retrieval, data mining, and information integration. To date, a wide variety of approaches to geo-semantic similarity have been devised. A judgment of similarity is not intrinsically right or wrong, but obtains a certain degree of cognitive plausibility, depending on how closely it mimics human behavior. Thus selecting the most appropriate measure for a specific task is a significant challenge. To address this issue, we make an analogy between computational similarity measures and soliciting domain expert opinions, which incorporate a subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we define the semantic similarity ensemble (SSE as a composition of different similarity measures, acting as a panel of experts having to reach a decision on the semantic similarity of a set of geographic terms. The approach is evaluated in comparison to human judgments, and results indicate that an SSE performs better than the average of its parts. Although the best member tends to outperform the ensemble, all ensembles outperform the average performance of each ensemble's member. Hence, in contexts where the best measure is unknown, the ensemble provides a more cognitively plausible approach.

  20. Hydrological Bulletin

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Historical report (December 1937-April 1948) containing hydrologic information for the United States, divided into ten regions. While hourly precipitation tables...

  1. Landfilling: Hydrology

    DEFF Research Database (Denmark)

    Kjeldsen, Peter; Beaven, R.

    2011-01-01

    Landfill hydrology deals with the presence and movement of water through a landfill. The main objective in landfill hydrology is usually to predict leachate generation, but the presence and movement of water in a landfill also affect the degradation of the waste, the leaching of pollutants...... and the geotechnical stability of the fill. Understanding landfill hydrology is thus important for many aspects of landfill, in particular siting, design and operation. The objective of this chapter is to give a basic understanding of the hydrology of landfills, and to present ways to estimate leachate quantities...... under specific circumstances. Initially a general water balance equation is defined for a typical landfill, and the different parts of the water balance are discussed. A separate section discusses water flow and the hydrogeology of landfilled wastes and considers the impact of water short...

  2. On the proper use of Ensembles for Predictive Uncertainty assessment

    Science.gov (United States)

    Todini, Ezio; Coccia, Gabriele; Ortiz, Enrique

    2015-04-01

    Probabilistic forecasting has become popular in the last decades. Hydrological probabilistic forecasts have been based either on uncertainty processors (Krzysztofowic, 1999; Todini, 2004; Todini, 2008) or on ensembles, following meteorological traditional approaches and the establishment of the HEPEX program (http://hepex.irstea.fr. Unfortunately, the direct use of ensembles as a measure of the predictive density is an incorrect practice, because the ensemble measures the spread of the forecast instead of, following the definition of predictive uncertainty, the conditional probability of the future outcome conditional on the forecast. Only few correct approaches are reported in the literature, which correctly use the ensemble to estimate an expected conditional predictive density (Reggiani et al., 2009), similarly to what is done when several predictive models are available as in the BMA (Raftery et al., 2005) or MCP(Todini, 2008; Coccia and Todini, 2011) approaches. A major problem, limiting the correct use of ensembles, is in fact the difficulty of defining the time dependence of the ensemble members, due to the lack of a consistent ranking: in other words, when dealing with multiple models, the ith model remains the ith model regardless to the time of forecast, while this does not happen when dealing with ensemble members, since there is no definition for the ith member of an ensemble. Nonetheless, the MCP approach (Todini, 2008; Coccia and Todini, 2011), essentially based on a multiple regression in the Normal space, can be easily extended to use ensembles to represent the local (in time) smaller or larger conditional predictive uncertainty, as a function of the ensemble spread. This is done by modifying the classical linear regression equations, impliying perfectly observed predictors, to alternative regression equations similar to the Kalman filter ones, allowing for uncertain predictors. In this way, each prediction in time accounts for both the predictive

  3. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Haakon

    2016-01-08

    The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.

  4. Neural Network Ensembles

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Salamon, Peter

    1990-01-01

    We propose several means for improving the performance an training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining generalization error can be reduced by invoking ensembles of similar...... networks....

  5. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Haakon; Chernov, Alexey; Law, Kody; Nobile, Fabio; Tempone, Raul

    2016-01-01

    The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.

  6. An Educational Model for Hands-On Hydrology Education

    Science.gov (United States)

    AghaKouchak, A.; Nakhjiri, N.; Habib, E. H.

    2014-12-01

    This presentation provides an overview of a hands-on modeling tool developed for students in civil engineering and earth science disciplines to help them learn the fundamentals of hydrologic processes, model calibration, sensitivity analysis, uncertainty assessment, and practice conceptual thinking in solving engineering problems. The toolbox includes two simplified hydrologic models, namely HBV-EDU and HBV-Ensemble, designed as a complement to theoretical hydrology lectures. The models provide an interdisciplinary application-oriented learning environment that introduces the hydrologic phenomena through the use of a simplified conceptual hydrologic model. The toolbox can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation) are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI) and an ensemble simulation scheme that can be used for teaching more advanced topics including uncertainty analysis, and ensemble simulation. Both models have been administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of hydrology.

  7. Pre- and post-processing of hydro-meteorological ensembles for the Norwegian flood forecasting system in 145 basins.

    Science.gov (United States)

    Jahr Hegdahl, Trine; Steinsland, Ingelin; Merete Tallaksen, Lena; Engeland, Kolbjørn

    2016-04-01

    Probabilistic flood forecasting has an added value for decision making. The Norwegian flood forecasting service is based on a flood forecasting model that run for 145 basins. Covering all of Norway the basins differ in both size and hydrological regime. Currently the flood forecasting is based on deterministic meteorological forecasts, and an auto-regressive procedure is used to achieve probabilistic forecasts. An alternative approach is to use meteorological and hydrological ensemble forecasts to quantify the uncertainty in forecasted streamflow. The hydrological ensembles are based on forcing a hydrological model with meteorological ensemble forecasts of precipitation and temperature. However, the ensembles of precipitation are often biased and the spread is too small, especially for the shortest lead times, i.e. they are not calibrated. These properties will, to some extent, propagate to hydrological ensembles, that most likely will be uncalibrated as well. Pre- and post-processing methods are commonly used to obtain calibrated meteorological and hydrological ensembles respectively. Quantitative studies showing the effect of the combined processing of the meteorological (pre-processing) and the hydrological (post-processing) ensembles are however few. The aim of this study is to evaluate the influence of pre- and post-processing on the skill of streamflow predictions, and we will especially investigate if the forecasting skill depends on lead-time, basin size and hydrological regime. This aim is achieved by applying the 51 medium-range ensemble forecast of precipitation and temperature provided by the European Center of Medium-Range Weather Forecast (ECMWF). These ensembles are used as input to the operational Norwegian flood forecasting model, both raw and pre-processed. Precipitation ensembles are calibrated using a zero-adjusted gamma distribution. Temperature ensembles are calibrated using a Gaussian distribution and altitude corrected by a constant gradient

  8. Evaluation of different downscaling techniques for hydrological climate-change impact studies at the catchment scale

    Energy Technology Data Exchange (ETDEWEB)

    Teutschbein, Claudia [Stockholm University, Department of Physical Geography and Quaternary Geology, Stockholm (Sweden); Wetterhall, Fredrik [King' s College London, Department of Geography, Strand, London (United Kingdom); Swedish Meteorological and Hydrological Institute, Norrkoeping (Sweden); Seibert, Jan [Stockholm University, Department of Physical Geography and Quaternary Geology, Stockholm (Sweden); Uppsala University, Department of Earth Sciences, Uppsala (Sweden); University of Zurich, Department of Geography, Zurich (Switzerland)

    2011-11-15

    Hydrological modeling for climate-change impact assessment implies using meteorological variables simulated by global climate models (GCMs). Due to mismatching scales, coarse-resolution GCM output cannot be used directly for hydrological impact studies but rather needs to be downscaled. In this study, we investigated the variability of seasonal streamflow and flood-peak projections caused by the use of three statistical approaches to downscale precipitation from two GCMs for a meso-scale catchment in southeastern Sweden: (1) an analog method (AM), (2) a multi-objective fuzzy-rule-based classification (MOFRBC) and (3) the Statistical DownScaling Model (SDSM). The obtained higher-resolution precipitation values were then used to simulate daily streamflow for a control period (1961-1990) and for two future emission scenarios (2071-2100) with the precipitation-streamflow model HBV. The choice of downscaled precipitation time series had a major impact on the streamflow simulations, which was directly related to the ability of the downscaling approaches to reproduce observed precipitation. Although SDSM was considered to be most suitable for downscaling precipitation in the studied river basin, we highlighted the importance of an ensemble approach. The climate and streamflow change signals indicated that the current flow regime with a snowmelt-driven spring flood in April will likely change to a flow regime that is rather dominated by large winter streamflows. Spring flood events are expected to decrease considerably and occur earlier, whereas autumn flood peaks are projected to increase slightly. The simulations demonstrated that projections of future streamflow regimes are highly variable and can even partly point towards different directions. (orig.)

  9. Land surface sensitivity of mesoscale convective systems

    Science.gov (United States)

    Tournay, Robert C.

    Mesoscale convective systems (MCSs) are important contributors to the hydrologic cycle in many regions of the world as well as major sources of severe weather. MCSs continue to challenge forecasters and researchers alike, arising from difficulties in understanding system initiation, propagation, and demise. One distinct type of MCS is that formed from individual convective cells initiated primarily by daytime heating over high terrain. This work is aimed at improving our understanding of the land surface sensitivity of this class of MCS in the contiguous United States. First, a climatology of mesoscale convective systems originating in the Rocky Mountains and adjacent high plains from Wyoming southward to New Mexico is developed through a combination of objective and subjective methods. This class of MCS is most important, in terms of total warm season precipitation, in the 500 to 1300m elevations of the Great Plains (GP) to the east in eastern Colorado to central Nebraska and northwest Kansas. Examining MCSs by longevity, short lasting MCSs (15 hrs) reveals that longer lasting systems tend to form further south and have a longer track with a more southerly track. The environment into which the MCS is moving showed differences across commonly used variables in convection forecasting, with some variables showing more favorable conditions throughout (convective inhibition, 0-6 km shear and 250 hPa wind speed) ahead of longer lasting MCSs. Other variables, such as convective available potential energy, showed improving conditions through time for longer lasting MCSs. Some variables showed no difference across longevity of MCS (precipitable water and large-scale vertical motion). From subsets of this MCS climatology, three regions of origin were chosen based on the presence of ridgelines extending eastward from the Rocky Mountains known to be foci for convection initiation and subsequent MCS formation: Southern Wyoming (Cheyenne Ridge), Colorado (Palmer divide) and

  10. Wind-Farm Parametrisations in Mesoscale Models

    DEFF Research Database (Denmark)

    Volker, Patrick; Badger, Jake; Hahmann, Andrea N.

    2013-01-01

    In this paper we compare three wind-farm parametrisations for mesoscale models against measurement data from the Horns Rev I offshore wind-farm. The parametrisations vary from a simple rotor drag method, to more sophisticated models. Additional to (4) we investigated the horizontal resolution dep...

  11. Delayed shear enhancement in mesoscale atmospheric dispersion

    Energy Technology Data Exchange (ETDEWEB)

    Moran, M.D. [Atmospheric Environment Service, Ontario (Canada); Pielke, R.A. [Colorado State Univ., Fort Collins, CO (United States)

    1994-12-31

    Mesoscale atmospheric dispersion (MAD) is more complicated than smaller-scale dispersion because the mean wind field can no longer be considered steady or horizontally homogeneous over mesoscale time and space scales. Wind shear also plays a much more important role on the mesoscale: horizontal dispersion can be enhanced and often dominated by vertical wind shear on these scales through the interaction of horizontal differential advection and vertical mixing. Just over 30 years ago, Pasquill suggested that this interaction need not be simultaneous and that the combination of differential horizontal advection with delayed or subsequent vertical mixing could maintain effective horizontal diffusion in spite of temporal or spatial reductions in boundary-layer turbulence intensity. This two-step mechanism has not received much attention since then, but a recent analysis of observations from and numerical simulations of two mesoscale tracer experiments suggests that delayed shear enhancement can play an important role in MAD. This paper presents an overview of this analysis, with particular emphasis on the influence of resolvable vertical shear on MAD in these two case studies and the contributions made by delayed shear enhancement.

  12. Isotope hydrology

    International Nuclear Information System (INIS)

    Drost, W.

    1978-01-01

    The International Symposium on Isotope Hydrology was jointly organized by the IAEA and UNESCO, in co-operation with the National Committee of the Federal Republic of Germany for the International Hydrological Programme (IHP) and the Gesellschaft fuer Strahlen- und Umweltforschung mbH (GSF). Upon the invitation of the Federal Republic of Germany the Symposium was held from 19-23 June 1978 in Neuherberg on the GSF campus. The Symposium was officially opened by Mr. S. Eklund, Director General of the IAEA. The symposium - the fifth meeting held on isotope hydrology - was attended by over 160 participants from 44 countries and four international organizations and by about 30 observers from the Federal Republic of Germany. Due to the absence of scientists from the USSR five papers were cancelled and therefore only 46 papers of the original programme were presented in ten sessions

  13. Comparison of ensemble post-processing approaches, based on empirical and dynamical error modelisation of rainfall-runoff model forecasts

    Science.gov (United States)

    Chardon, J.; Mathevet, T.; Le Lay, M.; Gailhard, J.

    2012-04-01

    In the context of a national energy company (EDF : Electricité de France), hydro-meteorological forecasts are necessary to ensure safety and security of installations, meet environmental standards and improve water ressources management and decision making. Hydrological ensemble forecasts allow a better representation of meteorological and hydrological forecasts uncertainties and improve human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. An operational hydrological ensemble forecasting chain has been developed at EDF since 2008 and is being used since 2010 on more than 30 watersheds in France. This ensemble forecasting chain is characterized ensemble pre-processing (rainfall and temperature) and post-processing (streamflow), where a large human expertise is solicited. The aim of this paper is to compare 2 hydrological ensemble post-processing methods developed at EDF in order improve ensemble forecasts reliability (similar to Monatanari &Brath, 2004; Schaefli et al., 2007). The aim of the post-processing methods is to dress hydrological ensemble forecasts with hydrological model uncertainties, based on perfect forecasts. The first method (called empirical approach) is based on a statistical modelisation of empirical error of perfect forecasts, by streamflow sub-samples of quantile class and lead-time. The second method (called dynamical approach) is based on streamflow sub-samples of quantile class and streamflow variation, and lead-time. On a set of 20 watersheds used for operational forecasts, results show that both approaches are necessary to ensure a good post-processing of hydrological ensemble, allowing a good improvement of reliability, skill and sharpness of ensemble forecasts. The comparison of the empirical and dynamical approaches shows the limits of the empirical approach which is not able to take into account hydrological

  14. Representing Color Ensembles.

    Science.gov (United States)

    Chetverikov, Andrey; Campana, Gianluca; Kristjánsson, Árni

    2017-10-01

    Colors are rarely uniform, yet little is known about how people represent color distributions. We introduce a new method for studying color ensembles based on intertrial learning in visual search. Participants looked for an oddly colored diamond among diamonds with colors taken from either uniform or Gaussian color distributions. On test trials, the targets had various distances in feature space from the mean of the preceding distractor color distribution. Targets on test trials therefore served as probes into probabilistic representations of distractor colors. Test-trial response times revealed a striking similarity between the physical distribution of colors and their internal representations. The results demonstrate that the visual system represents color ensembles in a more detailed way than previously thought, coding not only mean and variance but, most surprisingly, the actual shape (uniform or Gaussian) of the distribution of colors in the environment.

  15. Tailored Random Graph Ensembles

    International Nuclear Information System (INIS)

    Roberts, E S; Annibale, A; Coolen, A C C

    2013-01-01

    Tailored graph ensembles are a developing bridge between biological networks and statistical mechanics. The aim is to use this concept to generate a suite of rigorous tools that can be used to quantify and compare the topology of cellular signalling networks, such as protein-protein interaction networks and gene regulation networks. We calculate exact and explicit formulae for the leading orders in the system size of the Shannon entropies of random graph ensembles constrained with degree distribution and degree-degree correlation. We also construct an ergodic detailed balance Markov chain with non-trivial acceptance probabilities which converges to a strictly uniform measure and is based on edge swaps that conserve all degrees. The acceptance probabilities can be generalized to define Markov chains that target any alternative desired measure on the space of directed or undirected graphs, in order to generate graphs with more sophisticated topological features.

  16. Mesoscale wind fluctuations over Danish waters

    Energy Technology Data Exchange (ETDEWEB)

    Vincent, C.L.

    2010-12-15

    Mesoscale wind fluctuations affect the large scale integration of wind power because they undermine the day-ahead predictability of wind speed and power production, and because they can result in large fluctuations in power generation that must be balanced using reserve power. Large fluctuations in generated power are a particular problem for offshore wind farms because the typically high concentration of turbines within a limited geographical area means that fluctuations can be correlated across large numbers of turbines. Furthermore, organised mesoscale structures that often form over water, such as convective rolls and cellular convection, have length scales of tens of kilometers, and can cause large wind fluctuations on a time scale of around an hour. This thesis is an exploration of the predictability of mesoscale wind fluctuations using observations from the world's first two large offshore wind farms - Horns Rev I in the North Sea, and Nysted in the Baltic Sea. The thesis begins with a climatological analysis of wind fluctuations on time scales of 1-10 hours at the two sites. A novel method for calculating conditional climatologies of spectral information is proposed, based on binning and averaging the time axis of the Hilbert spectrum. Results reveal clear patterns between wind fluctuations and locally observed meteorological conditions. The analysis is expanded by classifying wind fluctuations on time scales of 1-3 hours according to synoptic patterns, satellite pictures and wind classes. Results indicate that cold air outbreaks and open cellular convection are a significant contributor to mesoscale wind variability at Horns Rev. The predictability of mesoscale wind fluctuations is tested by implementing standard statistical models that relate local wind variability to parameters based on a large scale weather analysis. The models show some skill, but only achieve a 15% improvement on a persistence forecast. The possibility of explicitly modelling

  17. Improving the accuracy of flood forecasting with transpositions of ensemble NWP rainfall fields considering orographic effects

    Science.gov (United States)

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

    2016-08-01

    The use of meteorological ensembles to produce sets of hydrological predictions increased the capability to issue flood warnings. However, space scale of the hydrological domain is still much finer than meteorological model, and NWP models have challenges with displacement. The main objective of this study to enhance the transposition method proposed in Yu et al. (2014) and to suggest the post-processing ensemble flood forecasting method for the real-time updating and the accuracy improvement of flood forecasts that considers the separation of the orographic rainfall and the correction of misplaced rain distributions using additional ensemble information through the transposition of rain distributions. In the first step of the proposed method, ensemble forecast rainfalls from a numerical weather prediction (NWP) model are separated into orographic and non-orographic rainfall fields using atmospheric variables and the extraction of topographic effect. Then the non-orographic rainfall fields are examined by the transposition scheme to produce additional ensemble information and new ensemble NWP rainfall fields are calculated by recombining the transposition results of non-orographic rain fields with separated orographic rainfall fields for a generation of place-corrected ensemble information. Then, the additional ensemble information is applied into a hydrologic model for post-flood forecasting with a 6-h interval. The newly proposed method has a clear advantage to improve the accuracy of mean value of ensemble flood forecasting. Our study is carried out and verified using the largest flood event by typhoon 'Talas' of 2011 over the two catchments, which are Futatsuno (356.1 km2) and Nanairo (182.1 km2) dam catchments of Shingu river basin (2360 km2), which is located in the Kii peninsula, Japan.

  18. Mesoscale simulation of concrete spall failure

    Science.gov (United States)

    Knell, S.; Sauer, M.; Millon, O.; Riedel, W.

    2012-05-01

    Although intensively studied, it is still being debated which physical mechanisms are responsible for the increase of dynamic strength and fracture energy of concrete observed at high loading rates, and to what extent structural inertia forces on different scales contribute to the observation. We present a new approach for the three dimensional mesoscale modelling of dynamic damage and cracking in concrete. Concrete is approximated as a composite of spherical elastic aggregates of mm to cm size embedded in an elastic cement stone matrix. Cracking within the matrix and at aggregate interfaces in the μm range are modelled with adaptively inserted—initially rigid—cohesive interface elements. The model is applied to analyse the dynamic tensile failure observed in Hopkinson-Bar spallation experiments with strain rates up to 100/s. The influence of the key mesoscale failure parameters of strength, fracture energy and relative weakening of the ITZ on macromechanic strength, momentum and energy conservation is numerically investigated.

  19. Mesoscale wind fluctuations over Danish waters

    DEFF Research Database (Denmark)

    Vincent, Claire Louise

    in generated power are a particular problem for oshore wind farms because the typically high concentration of turbines within a limited geographical area means that uctuations can be correlated across large numbers of turbines. Furthermore, organised mesoscale structures that often form over water......Mesoscale wind uctuations aect the large scale integration of wind power because they undermine the day-ahead predictability of wind speed and power production, and because they can result in large uctuations in power generation that must be balanced using reserve power. Large uctuations...... that realistic hour-scale wind uctuations and open cellular convection patterns develop in WRF simulations with 2km horizontal grid spacing. The atmospheric conditions during one of the case studies are then used to initialise a simplied version of the model that has no large scale weather forcing, topography...

  20. Imprinting and recalling cortical ensembles.

    Science.gov (United States)

    Carrillo-Reid, Luis; Yang, Weijian; Bando, Yuki; Peterka, Darcy S; Yuste, Rafael

    2016-08-12

    Neuronal ensembles are coactive groups of neurons that may represent building blocks of cortical circuits. These ensembles could be formed by Hebbian plasticity, whereby synapses between coactive neurons are strengthened. Here we report that repetitive activation with two-photon optogenetics of neuronal populations from ensembles in the visual cortex of awake mice builds neuronal ensembles that recur spontaneously after being imprinted and do not disrupt preexisting ones. Moreover, imprinted ensembles can be recalled by single- cell stimulation and remain coactive on consecutive days. Our results demonstrate the persistent reconfiguration of cortical circuits by two-photon optogenetics into neuronal ensembles that can perform pattern completion. Copyright © 2016, American Association for the Advancement of Science.

  1. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Hakon

    2016-06-14

    This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.

  2. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Hakon; Law, Kody J. H.; Tempone, Raul

    2016-01-01

    This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.

  3. Development and Testing of a Coupled Ocean-atmosphere Mesoscale Ensemble Prediction System

    Science.gov (United States)

    2011-06-28

    member 0; see text for a detailed description of the physics parameters) Member abl mixlen Flux w-kf tinc-lcl cld -rad precip Graupel Auto-conv Rain-int...increment has an impact on the convective initiation. 7. The cloud updraft radius used in the K–F parameteri- zation: The radius cld -rad (m) varies

  4. A high space-time resolution dataset linking meteorological forcing and hydro-sedimentary response in a mesoscale Mediterranean catchment (Auzon) of the Ardèche region, France

    NARCIS (Netherlands)

    Nord, Guillaume; Boudevillain, Brice; Berne, Alexis; Branger, Flora; Braud, Isabelle; Dramais, Guillaume; Gérard, Simon; Coz, Le Jérôme; Legoût, Cédric; Molinié, Gilles; Teuling, Ryan

    2017-01-01

    A comprehensive hydrometeorological dataset is presented spanning the period 1 January 2011-31 December 2014 to improve the understanding of the hydrological processes leading to flash floods and the relation between rainfall, runoff, erosion and sediment transport in a mesoscale catchment

  5. Diversity in random subspacing ensembles

    NARCIS (Netherlands)

    Tsymbal, A.; Pechenizkiy, M.; Cunningham, P.; Kambayashi, Y.; Mohania, M.K.; Wöß, W.

    2004-01-01

    Ensembles of learnt models constitute one of the main current directions in machine learning and data mining. It was shown experimentally and theoretically that in order for an ensemble to be effective, it should consist of classifiers having diversity in their predictions. A number of ways are

  6. PSO-Ensemble Demo Application

    DEFF Research Database (Denmark)

    2004-01-01

    Within the framework of the PSO-Ensemble project (FU2101) a demo application has been created. The application use ECMWF ensemble forecasts. Two instances of the application are running; one for Nysted Offshore and one for the total production (except Horns Rev) in the Eltra area. The output...

  7. New concept of statistical ensembles

    International Nuclear Information System (INIS)

    Gorenstein, M.I.

    2009-01-01

    An extension of the standard concept of the statistical ensembles is suggested. Namely, the statistical ensembles with extensive quantities fluctuating according to an externally given distribution is introduced. Applications in the statistical models of multiple hadron production in high energy physics are discussed.

  8. A Diagnostics Tool to detect ensemble forecast system anomaly and guide operational decisions

    Science.gov (United States)

    Park, G. H.; Srivastava, A.; Shrestha, E.; Thiemann, M.; Day, G. N.; Draijer, S.

    2017-12-01

    The hydrologic community is moving toward using ensemble forecasts to take uncertainty into account during the decision-making process. The New York City Department of Environmental Protection (DEP) implements several types of ensemble forecasts in their decision-making process: ensemble products for a statistical model (Hirsch and enhanced Hirsch); the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) forecasts based on the classical Ensemble Streamflow Prediction (ESP) technique; and the new NWS Hydrologic Ensemble Forecasting Service (HEFS) forecasts. To remove structural error and apply the forecasts to additional forecast points, the DEP post processes both the AHPS and the HEFS forecasts. These ensemble forecasts provide mass quantities of complex data, and drawing conclusions from these forecasts is time-consuming and difficult. The complexity of these forecasts also makes it difficult to identify system failures resulting from poor data, missing forecasts, and server breakdowns. To address these issues, we developed a diagnostic tool that summarizes ensemble forecasts and provides additional information such as historical forecast statistics, forecast skill, and model forcing statistics. This additional information highlights the key information that enables operators to evaluate the forecast in real-time, dynamically interact with the data, and review additional statistics, if needed, to make better decisions. We used Bokeh, a Python interactive visualization library, and a multi-database management system to create this interactive tool. This tool compiles and stores data into HTML pages that allows operators to readily analyze the data with built-in user interaction features. This paper will present a brief description of the ensemble forecasts, forecast verification results, and the intended applications for the diagnostic tool.

  9. Ensemble-based flash-flood modelling: Taking into account hydrodynamic parameters and initial soil moisture uncertainties

    Science.gov (United States)

    Edouard, Simon; Vincendon, Béatrice; Ducrocq, Véronique

    2018-05-01

    Intense precipitation events in the Mediterranean often lead to devastating flash floods (FF). FF modelling is affected by several kinds of uncertainties and Hydrological Ensemble Prediction Systems (HEPS) are designed to take those uncertainties into account. The major source of uncertainty comes from rainfall forcing and convective-scale meteorological ensemble prediction systems can manage it for forecasting purpose. But other sources are related to the hydrological modelling part of the HEPS. This study focuses on the uncertainties arising from the hydrological model parameters and initial soil moisture with aim to design an ensemble-based version of an hydrological model dedicated to Mediterranean fast responding rivers simulations, the ISBA-TOP coupled system. The first step consists in identifying the parameters that have the strongest influence on FF simulations by assuming perfect precipitation. A sensitivity study is carried out first using a synthetic framework and then for several real events and several catchments. Perturbation methods varying the most sensitive parameters as well as initial soil moisture allow designing an ensemble-based version of ISBA-TOP. The first results of this system on some real events are presented. The direct perspective of this work will be to drive this ensemble-based version with the members of a convective-scale meteorological ensemble prediction system to design a complete HEPS for FF forecasting.

  10. Ensembl 2002: accommodating comparative genomics.

    Science.gov (United States)

    Clamp, M; Andrews, D; Barker, D; Bevan, P; Cameron, G; Chen, Y; Clark, L; Cox, T; Cuff, J; Curwen, V; Down, T; Durbin, R; Eyras, E; Gilbert, J; Hammond, M; Hubbard, T; Kasprzyk, A; Keefe, D; Lehvaslaiho, H; Iyer, V; Melsopp, C; Mongin, E; Pettett, R; Potter, S; Rust, A; Schmidt, E; Searle, S; Slater, G; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Stupka, E; Ureta-Vidal, A; Vastrik, I; Birney, E

    2003-01-01

    The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of human, mouse and other genome sequences, available as either an interactive web site or as flat files. Ensembl also integrates manually annotated gene structures from external sources where available. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. These range from sequence analysis to data storage and visualisation and installations exist around the world in both companies and at academic sites. With both human and mouse genome sequences available and more vertebrate sequences to follow, many of the recent developments in Ensembl have focusing on developing automatic comparative genome analysis and visualisation.

  11. Intense mesoscale variability in the Sardinia Sea

    Science.gov (United States)

    Russo, Aniello; Borrione, Ines; Falchetti, Silvia; Knoll, Michaela; Fiekas, Heinz-Volker; Heywood, Karen; Oddo, Paolo; Onken, Reiner

    2015-04-01

    From the 6 to 25 June 2014, the REP14-MED sea trial was conducted by CMRE, supported by 20 partners from six different nations. The at-sea activities were carried out onboard the research vessels Alliance (NATO) and Planet (German Ministry of Defense), comprising a marine area of about 110 x 110 km2 to the west of the Sardinian coast. More than 300 CTD casts typically spaced at 10 km were collected; both ships continuously recorded vertical profiles of currents by means of their ADCPs, and a ScanFish® and a CTD chain were towed for almost three days by Alliance and Planet, respectively, following parallel routes. Twelve gliders from different manufacturers (Slocum, SeaGliderTM and SeaExplorer) were continuously sampling the study area following zonal tracks spaced at 10 km. In addition, six moorings, 17 surface drifters and one ARVOR float were deployed. From a first analysis of the observations, several mesoscale features were identified in the survey area, in particular: (i) a warm-core anticyclonic eddy in the southern part of the domain, about 50 km in diameter and with the strongest signal at about 50-m depth (ii) another warm-core anticyclonic eddy of comparable dimensions in the central part of the domain, but extending to greater depth than the former one, and (iii) a small (less than 15 km in diameter) cold-core cyclonic eddy of Winter Intermediate Water in the depth range between 170 m and 370 m. All three eddies showed intensified currents, up to 50 cm s-1. The huge high-resolution observational data set and the variety of observation techniques enabled the mesoscale features and their variability to be tracked for almost three weeks. In order to obtain a deeper understanding of the mesoscale dynamic behaviour and their interactions, assimilation studies with an ocean circulation model are underway.

  12. On Ensemble Nonlinear Kalman Filtering with Symmetric Analysis Ensembles

    KAUST Repository

    Luo, Xiaodong

    2010-09-19

    The ensemble square root filter (EnSRF) [1, 2, 3, 4] is a popular method for data assimilation in high dimensional systems (e.g., geophysics models). Essentially the EnSRF is a Monte Carlo implementation of the conventional Kalman filter (KF) [5, 6]. It is mainly different from the KF at the prediction steps, where it is some ensembles, rather then the means and covariance matrices, of the system state that are propagated forward. In doing this, the EnSRF is computationally more efficient than the KF, since propagating a covariance matrix forward in high dimensional systems is prohibitively expensive. In addition, the EnSRF is also very convenient in implementation. By propagating the ensembles of the system state, the EnSRF can be directly applied to nonlinear systems without any change in comparison to the assimilation procedures in linear systems. However, by adopting the Monte Carlo method, the EnSRF also incurs certain sampling errors. One way to alleviate this problem is to introduce certain symmetry to the ensembles, which can reduce the sampling errors and spurious modes in evaluation of the means and covariances of the ensembles [7]. In this contribution, we present two methods to produce symmetric ensembles. One is based on the unscented transform [8, 9], which leads to the unscented Kalman filter (UKF) [8, 9] and its variant, the ensemble unscented Kalman filter (EnUKF) [7]. The other is based on Stirling’s interpolation formula (SIF), which results in the divided difference filter (DDF) [10]. Here we propose a simplified divided difference filter (sDDF) in the context of ensemble filtering. The similarity and difference between the sDDF and the EnUKF will be discussed. Numerical experiments will also be conducted to investigate the performance of the sDDF and the EnUKF, and compare them to a well‐established EnSRF, the ensemble transform Kalman filter (ETKF) [2].

  13. Assessing uncertainties of water footprints using an ensemble of crop growth models on winter wheat

    Czech Academy of Sciences Publication Activity Database

    Kersebaum, K. C.; Kroes, J.; Gobin, A.; Takáč, J.; Hlavinka, Petr; Trnka, Miroslav; Ventrella, D.; Giglio, L.; Ferrise, R.; Moriondo, M.; Marta, A. D.; Luo, Q.; Eitzinger, Josef; Mirschel, W.; Weigel, H-J.; Manderscheid, R.; Hofmann, M.; Nejedlík, P.; Hösch, J.

    2016-01-01

    Roč. 8, č. 12 (2016), č. článku 571. ISSN 2073-4441 R&D Projects: GA MŠk(CZ) LO1415; GA MŠk(CZ) LD13030 Institutional support: RVO:67179843 Keywords : water footprint * uncertainty * model ensemble * wheat Subject RIV: DA - Hydrology ; Limnology Impact factor: 1.832, year: 2016

  14. Hydrology team

    Science.gov (United States)

    Ragan, R.

    1982-01-01

    General problems faced by hydrologists when using historical records, real time data, statistical analysis, and system simulation in providing quantitative information on the temporal and spatial distribution of water are related to the limitations of these data. Major problem areas requiring multispectral imaging-based research to improve hydrology models involve: evapotranspiration rates and soil moisture dynamics for large areas; the three dimensional characteristics of bodies of water; flooding in wetlands; snow water equivalents; runoff and sediment yield from ungaged watersheds; storm rainfall; fluorescence and polarization of water and its contained substances; discriminating between sediment and chlorophyll in water; role of barrier island dynamics in coastal zone processes; the relationship between remotely measured surface roughness and hydraulic roughness of land surfaces and stream networks; and modeling the runoff process.

  15. A comparison of changes in river runoff from multiple global and catchment-scale hydrological models under global warming scenarios of 1 °C, 2 °C and 3 °C

    NARCIS (Netherlands)

    Gosling, S.N.; Zaherpour, J.J.; Mount, N.J.; Hattermann, F.F.; Dankers, R.; Arheimer, B.; Breuer, L.; Ding, J.; Haddeland, I.; Kumar, R.; Kundu, D.; Liu, J.; van Griensven, A.; Veldkamp, T.I.E.; Vetter, T.; Wang, X.; Zhang, X.

    2017-01-01

    We present one of the first climate change impact assessments on river runoff that utilises an ensemble of global hydrological models (Glob-HMs) and an ensemble of catchment-scale hydrological models (Cat-HMs), across multiple catchments: the upper Amazon, Darling, Ganges, Lena, upper Mississippi,

  16. Mesoscale Eddies in the Solomon Sea

    Science.gov (United States)

    Hristova, H. G.; Kessler, W. S.; McWilliams, J. C.; Molemaker, M. J.

    2011-12-01

    Water mass transformation in the strong equatorward flows through the Solomon Sea influences the properties of the Equatorial Undercurrent and subsequent cold tongue upwelling. High eddy activity in the interior Solomon Sea seen in altimetric sea surface height (SSH) and in several models may provide a mechanism for these transformations. We investigate these effects using a mesoscale (4-km resolution) sigma-coordinate (ROMS) model of the Solomon Sea nested in a basin solution, forced by a repeating seasonal cycle, and evaluated against observational data. The model generates a vigorous upper layer eddy field; some of these are apparently shed as the New Guinea Coastal Undercurrent threads through the complex topography of the region, others are independent of the strong western boundary current. We diagnose the scales and vertical structure of the eddies in different parts of the Solomon Sea to illuminate their generation processes and propagation characteristics, and compare these to observed eddy statistics. Hypotheses tested are that the Solomon Sea mesoscale eddies are generated locally by baroclinic instability, that the eddies are shed as the South Equatorial Current passes around and through the Solomon Island chain, that eddies are generated by the New Guinea Coastal Undercurrent, or that eddies occurring outside of the Solomon Sea propagate into the Solomon Sea. These different mechanisms have different implications for the resulting mixing and property fluxes. They also provide different interpretations for SSH signals observed from satellites (e.g., that will be observed by the upcoming SWOT satellite).

  17. Contact planarization of ensemble nanowires

    Science.gov (United States)

    Chia, A. C. E.; LaPierre, R. R.

    2011-06-01

    The viability of four organic polymers (S1808, SC200, SU8 and Cyclotene) as filling materials to achieve planarization of ensemble nanowire arrays is reported. Analysis of the porosity, surface roughness and thermal stability of each filling material was performed. Sonication was used as an effective method to remove the tops of the nanowires (NWs) to achieve complete planarization. Ensemble nanowire devices were fully fabricated and I-V measurements confirmed that Cyclotene effectively planarizes the NWs while still serving the role as an insulating layer between the top and bottom contacts. These processes and analysis can be easily implemented into future characterization and fabrication of ensemble NWs for optoelectronic device applications.

  18. Assimilation of remote sensing observations into a continuous distributed hydrological model: impacts on the hydrologic cycle

    Science.gov (United States)

    Laiolo, Paola; Gabellani, Simone; Campo, Lorenzo; Cenci, Luca; Silvestro, Francesco; Delogu, Fabio; Boni, Giorgio; Rudari, Roberto

    2015-04-01

    The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce in-situ data. This work investigates the impact of the assimilation of different remote sensing products on the hydrological cycle by using a continuous physically based distributed hydrological model. Three soil moisture products derived by ASCAT (Advanced SCATterometer) are used to update the model state variables. The satellite-derived products are assimilated into the hydrological model using different assimilation techniques: a simple nudging and the Ensemble Kalman Filter. Moreover two assimilation strategies are evaluated to assess the impact of assimilating the satellite products at model spatial resolution or at the satellite scale. The experiments are carried out for three Italian catchments on multi year period. The benefits on the model predictions of discharge, LST, evapotranspiration and soil moisture dynamics are tested and discussed.

  19. On Ensemble Nonlinear Kalman Filtering with Symmetric Analysis Ensembles

    KAUST Repository

    Luo, Xiaodong; Hoteit, Ibrahim; Moroz, Irene M.

    2010-01-01

    However, by adopting the Monte Carlo method, the EnSRF also incurs certain sampling errors. One way to alleviate this problem is to introduce certain symmetry to the ensembles, which can reduce the sampling errors and spurious modes in evaluation of the means and covariances of the ensembles [7]. In this contribution, we present two methods to produce symmetric ensembles. One is based on the unscented transform [8, 9], which leads to the unscented Kalman filter (UKF) [8, 9] and its variant, the ensemble unscented Kalman filter (EnUKF) [7]. The other is based on Stirling’s interpolation formula (SIF), which results in the divided difference filter (DDF) [10]. Here we propose a simplified divided difference filter (sDDF) in the context of ensemble filtering. The similarity and difference between the sDDF and the EnUKF will be discussed. Numerical experiments will also be conducted to investigate the performance of the sDDF and the EnUKF, and compare them to a well‐established EnSRF, the ensemble transform Kalman filter (ETKF) [2].

  20. Ensemble manifold regularization.

    Science.gov (United States)

    Geng, Bo; Tao, Dacheng; Xu, Chao; Yang, Linjun; Hua, Xian-Sheng

    2012-06-01

    We propose an automatic approximation of the intrinsic manifold for general semi-supervised learning (SSL) problems. Unfortunately, it is not trivial to define an optimization function to obtain optimal hyperparameters. Usually, cross validation is applied, but it does not necessarily scale up. Other problems derive from the suboptimality incurred by discrete grid search and the overfitting. Therefore, we develop an ensemble manifold regularization (EMR) framework to approximate the intrinsic manifold by combining several initial guesses. Algorithmically, we designed EMR carefully so it 1) learns both the composite manifold and the semi-supervised learner jointly, 2) is fully automatic for learning the intrinsic manifold hyperparameters implicitly, 3) is conditionally optimal for intrinsic manifold approximation under a mild and reasonable assumption, and 4) is scalable for a large number of candidate manifold hyperparameters, from both time and space perspectives. Furthermore, we prove the convergence property of EMR to the deterministic matrix at rate root-n. Extensive experiments over both synthetic and real data sets demonstrate the effectiveness of the proposed framework.

  1. Applying Multimodel Ensemble from Regional Climate Models for Improving Runoff Projections on Semiarid Regions of Spain

    Science.gov (United States)

    Garcia Galiano, S. G.; Olmos, P.; Giraldo Osorio, J. D.

    2015-12-01

    In the Mediterranean area, significant changes on temperature and precipitation are expected throughout the century. These trends could exacerbate the existing conditions in regions already vulnerable to climatic variability, reducing the water availability. Improving knowledge about plausible impacts of climate change on water cycle processes at basin scale, is an important step for building adaptive capacity to the impacts in this region, where severe water shortages are expected for the next decades. RCMs ensemble in combination with distributed hydrological models with few parameters, constitutes a valid and robust methodology to increase the reliability of climate and hydrological projections. For reaching this objective, a novel methodology for building Regional Climate Models (RCMs) ensembles of meteorological variables (rainfall an temperatures), was applied. RCMs ensembles are justified for increasing the reliability of climate and hydrological projections. The evaluation of RCMs goodness-of-fit to build the ensemble is based on empirical probability density functions (PDF) extracted from both RCMs dataset and a highly resolution gridded observational dataset, for the time period 1961-1990. The applied method is considering the seasonal and annual variability of the rainfall and temperatures. The RCMs ensembles constitute the input to a distributed hydrological model at basin scale, for assessing the runoff projections. The selected hydrological model is presenting few parameters in order to reduce the uncertainties involved. The study basin corresponds to a head basin of Segura River Basin, located in the South East of Spain. The impacts on runoff and its trend from observational dataset and climate projections, were assessed. Considering the control period 1961-1990, plausible significant decreases in runoff for the time period 2021-2050, were identified.

  2. Evaluating uncertainty estimates in hydrologic models: borrowing measures from the forecast verification community

    Directory of Open Access Journals (Sweden)

    K. J. Franz

    2011-11-01

    Full Text Available The hydrologic community is generally moving towards the use of probabilistic estimates of streamflow, primarily through the implementation of Ensemble Streamflow Prediction (ESP systems, ensemble data assimilation methods, or multi-modeling platforms. However, evaluation of probabilistic outputs has not necessarily kept pace with ensemble generation. Much of the modeling community is still performing model evaluation using standard deterministic measures, such as error, correlation, or bias, typically applied to the ensemble mean or median. Probabilistic forecast verification methods have been well developed, particularly in the atmospheric sciences, yet few have been adopted for evaluating uncertainty estimates in hydrologic model simulations. In the current paper, we overview existing probabilistic forecast verification methods and apply the methods to evaluate and compare model ensembles produced from two different parameter uncertainty estimation methods: the Generalized Uncertainty Likelihood Estimator (GLUE, and the Shuffle Complex Evolution Metropolis (SCEM. Model ensembles are generated for the National Weather Service SACramento Soil Moisture Accounting (SAC-SMA model for 12 forecast basins located in the Southeastern United States. We evaluate the model ensembles using relevant metrics in the following categories: distribution, correlation, accuracy, conditional statistics, and categorical statistics. We show that the presented probabilistic metrics are easily adapted to model simulation ensembles and provide a robust analysis of model performance associated with parameter uncertainty. Application of these methods requires no information in addition to what is already available as part of traditional model validation methodology and considers the entire ensemble or uncertainty range in the approach.

  3. The Ensembl genome database project.

    Science.gov (United States)

    Hubbard, T; Barker, D; Birney, E; Cameron, G; Chen, Y; Clark, L; Cox, T; Cuff, J; Curwen, V; Down, T; Durbin, R; Eyras, E; Gilbert, J; Hammond, M; Huminiecki, L; Kasprzyk, A; Lehvaslaiho, H; Lijnzaad, P; Melsopp, C; Mongin, E; Pettett, R; Pocock, M; Potter, S; Rust, A; Schmidt, E; Searle, S; Slater, G; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Stupka, E; Ureta-Vidal, A; Vastrik, I; Clamp, M

    2002-01-01

    The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of the human genome sequence, with confirmed gene predictions that have been integrated with external data sources, and is available as either an interactive web site or as flat files. It is also an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements from sequence analysis to data storage and visualisation. The Ensembl site is one of the leading sources of human genome sequence annotation and provided much of the analysis for publication by the international human genome project of the draft genome. The Ensembl system is being installed around the world in both companies and academic sites on machines ranging from supercomputers to laptops.

  4. DART: New Research Using Ensemble Data Assimilation in Geophysical Models

    Science.gov (United States)

    Hoar, T. J.; Raeder, K.

    2015-12-01

    The Data Assimilation Research Testbed (DART) is a community facilityfor ensemble data assimilation developed and supported by the NationalCenter for Atmospheric Research. DART provides a comprehensive suite of software, documentation, and tutorials that can be used for ensemble data assimilation research, operations, and education. Scientists and software engineers at NCAR are available to support DART users who want to use existing DART products or develop their own applications. Current DART users range from university professors teaching data assimilation, to individual graduate students working with simple models, through national laboratories doing operational prediction with large state-of-the-art models. DART runs efficiently on many computational platforms ranging from laptops through thousands of cores on the newest supercomputers.This poster focuses on several recent research activities using DART with geophysical models.Using CAM/DART to understand whether OCO-2 Total Precipitable Water observations can be useful in numerical weather prediction.Impacts of the synergistic use of Infra-red CO retrievals (MOPITT, IASI) in CAM-CHEM/DART assimilations.Assimilation and Analysis of Observations of Amazonian Biomass Burning Emissions by MOPITT (aerosol optical depth), MODIS (carbon monoxide) and MISR (plume height).Long term evaluation of the chemical response of MOPITT-CO assimilation in CAM-CHEM/DART OSSEs for satellite planning and emission inversion capabilities.Improved forward observation operators for land models that have multiple land use/land cover segments in a single grid cell,Simulating mesoscale convective systems (MCSs) using a variable resolution, unstructured grid in the Model for Prediction Across Scales (MPAS) and DART.The mesoscale WRF+DART system generated an ensemble of year-long, real-time initializations of a convection allowing model over the United States.Constraining WACCM with observations in the tropical band (30S-30N) using DART

  5. Mesoscale model response to random, surface-based perturbations — A sea-breeze experiment

    Science.gov (United States)

    Garratt, J. R.; Pielke, R. A.; Miller, W. F.; Lee, T. J.

    1990-09-01

    The introduction into a mesoscale model of random (in space) variations in roughness length, or random (in space and time) surface perturbations of temperature and friction velocity, produces a measurable, but barely significant, response in the simulated flow dynamics of the lower atmosphere. The perturbations are an attempt to include the effects of sub-grid variability into the ensemble-mean parameterization schemes used in many numerical models. Their magnitude is set in our experiments by appeal to real-world observations of the spatial variations in roughness length and daytime surface temperature over the land on horizontal scales of one to several tens of kilometers. With sea-breeze simulations, comparisons of a number of realizations forced by roughness-length and surface-temperature perturbations with the standard simulation reveal no significant change in ensemble mean statistics, and only small changes in the sea-breeze vertical velocity. Changes in the updraft velocity for individual runs, of up to several cms-1 (compared to a mean of 14 cms-1), are directly the result of prefrontal temperature changes of 0.1 to 0.2K, produced by the random surface forcing. The correlation and magnitude of the changes are entirely consistent with a gravity-current interpretation of the sea breeze.

  6. Transfer Relations Between Landscape Functions - The Hydrological Point of View

    Science.gov (United States)

    Fohrer, N.; Lenhart, T.; Eckhardt, K.; Frede, H.-G.

    EC market policies and regional subsidy programs have an enormous impact on local land use. This has far reaching consequences on various landscape functions. In the joint research project SFB299 at the Giessen University the effect of land use options on economic, ecological and hydrological landscape functions are under investigation. The continuous time step model SWAT-G (Eckhardt et al., 2000; Arnold et al., 1998) is employed to characterize the influence of land use patterns on hydrological processes. The model was calibrated and validated employing a split sample approach. For two mesoscale watersheds (Aar, 60 km2; Dietzhölze, 81 km2) located in the Lahn-Dill- Bergland, Germany, different land use scenarios were analyzed with regard to their hydrological impact. Additionally the effect of land use change was analyzed with an ecological and an agro-economic model. The impact of the stepwise changing land use was expressed as trade off relations between different landscape functions.

  7. Mesoscale Effects on Carbon Export: A Global Perspective

    Science.gov (United States)

    Harrison, Cheryl S.; Long, Matthew C.; Lovenduski, Nicole S.; Moore, Jefferson K.

    2018-04-01

    Carbon export from the surface to the deep ocean is a primary control on global carbon budgets and is mediated by plankton that are sensitive to physical forcing. Earth system models generally do not resolve ocean mesoscale circulation (O(10-100) km), scales that strongly affect transport of nutrients and plankton. The role of mesoscale circulation in modulating export is evaluated by comparing global ocean simulations conducted at 1° and 0.1° horizontal resolution. Mesoscale resolution produces a small reduction in globally integrated export production (export production can be large (±50%), with compensating effects in different ocean basins. With mesoscale resolution, improved representation of coastal jets block off-shelf transport, leading to lower export in regions where shelf-derived nutrients fuel production. Export is further reduced in these regions by resolution of mesoscale turbulence, which restricts the spatial area of production. Maximum mixed layer depths are narrower and deeper across the Subantarctic at higher resolution, driving locally stronger nutrient entrainment and enhanced summer export production. In energetic regions with seasonal blooms, such as the Subantarctic and North Pacific, internally generated mesoscale variability drives substantial interannual variation in local export production. These results suggest that biogeochemical tracer dynamics show different sensitivities to transport biases than temperature and salinity, which should be considered in the formulation and validation of physical parameterizations. Efforts to compare estimates of export production from observations and models should account for large variability in space and time expected for regions strongly affected by mesoscale circulation.

  8. Extreme gust wind estimation using mesoscale modeling

    DEFF Research Database (Denmark)

    Larsén, Xiaoli Guo; Kruger, Andries

    2014-01-01

    , surface turbulence characteristics. In this study, we follow a theory that is different from the local gust concept as described above. In this theory, the gust at the surface is non-local; it is produced by the deflection of air parcels flowing in the boundary layer and brought down to the surface...... from the Danish site Høvsøre help us to understand the limitation of the traditional method. Good agreement was found between the extreme gust atlases for South Africa and the existing map made from a limited number of measurements across the country. Our study supports the non-local gust theory. While...... through turbulent eddies. This process is modeled using the mesoscale Weather Forecasting and Research (WRF) model. The gust at the surface is calculated as the largest winds over a layer where the averaged turbulence kinetic energy is greater than the averaged buoyancy force. The experiments have been...

  9. Mesoscale Modelling of the Response of Aluminas

    International Nuclear Information System (INIS)

    Bourne, N. K.

    2006-01-01

    The response of polycrystalline alumina to shock is not well addressed. There are several operating mechanisms that only hypothesized which results in models which are empirical. A similar state of affairs in reactive flow modelling led to the development of mesoscale representations of the flow to illuminate operating mechanisms. In this spirit, a similar effort is undergone for a polycrystalline alumina. Simulations are conducted to observe operating mechanisms at the micron scale. A method is then developed to extend the simulations to meet response at the continuum level where measurements are made. The approach is validated by comparison with continuum experiments. The method and results are presented, and some of the operating mechanisms are illuminated by the observed response

  10. Probabilistic, meso-scale flood loss modelling

    Science.gov (United States)

    Kreibich, Heidi; Botto, Anna; Schröter, Kai; Merz, Bruno

    2016-04-01

    Flood risk analyses are an important basis for decisions on flood risk management and adaptation. However, such analyses are associated with significant uncertainty, even more if changes in risk due to global change are expected. Although uncertainty analysis and probabilistic approaches have received increased attention during the last years, they are still not standard practice for flood risk assessments and even more for flood loss modelling. State of the art in flood loss modelling is still the use of simple, deterministic approaches like stage-damage functions. Novel probabilistic, multi-variate flood loss models have been developed and validated on the micro-scale using a data-mining approach, namely bagging decision trees (Merz et al. 2013). In this presentation we demonstrate and evaluate the upscaling of the approach to the meso-scale, namely on the basis of land-use units. The model is applied in 19 municipalities which were affected during the 2002 flood by the River Mulde in Saxony, Germany (Botto et al. submitted). The application of bagging decision tree based loss models provide a probability distribution of estimated loss per municipality. Validation is undertaken on the one hand via a comparison with eight deterministic loss models including stage-damage functions as well as multi-variate models. On the other hand the results are compared with official loss data provided by the Saxon Relief Bank (SAB). The results show, that uncertainties of loss estimation remain high. Thus, the significant advantage of this probabilistic flood loss estimation approach is that it inherently provides quantitative information about the uncertainty of the prediction. References: Merz, B.; Kreibich, H.; Lall, U. (2013): Multi-variate flood damage assessment: a tree-based data-mining approach. NHESS, 13(1), 53-64. Botto A, Kreibich H, Merz B, Schröter K (submitted) Probabilistic, multi-variable flood loss modelling on the meso-scale with BT-FLEMO. Risk Analysis.

  11. The canonical ensemble redefined - 1: Formalism

    International Nuclear Information System (INIS)

    Venkataraman, R.

    1984-12-01

    For studying the thermodynamic properties of systems we propose an ensemble that lies in between the familiar canonical and microcanonical ensembles. We point out the transition from the canonical to microcanonical ensemble and prove from a comparative study that all these ensembles do not yield the same results even in the thermodynamic limit. An investigation of the coupling between two or more systems with these ensembles suggests that the state of thermodynamical equilibrium is a special case of statistical equilibrium. (author)

  12. From Quanta to the Continuum: Opportunities for Mesoscale Science

    Energy Technology Data Exchange (ETDEWEB)

    Crabtree, George [Argonne National Lab. (ANL), Argonne, IL (United States); Sarrao, John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Alivisatos, Paul [Univ. of California, Berkeley, CA (United States); Barletta, William [MIT (Massachusetts Inst. of Technology), Cambridge, MA (United States); Bates, Frank [Univ. of Minnesota, Minneapolis, MN (United States); Brown, Gordon [Stanford Univ., CA (United States); French, Roger [Case Western Reserve Univ., Cleveland, OH (United States); Greene, Laura [Univ. of Illinois, Urbana, IL (United States); Hemminger, John [Univ. of California, Irvine, CA (United States); Kastner, Marc [MIT (Massachusetts Inst. of Technology), Cambridge, MA (United States); Kay, Bruce [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lewis, Jennifer [Univ. of Illinois, Urbana, IL (United States); Ratner, Mark [Northwestern Univ., Evanston, IL (United States); Anthony, Rollett [Carnegie Mellon Univ., Pittsburgh, PA (United States); Rubloff, Gary [University of Maryland, College Park, MD (United States); Spence, John [Arizona State Univ., Mesa, AZ (United States); Tobias, Douglas [Univ. of California, Irvine, CA (United States); Tranquada, John [Brookhaven National Lab. (BNL), Upton, NY (United States)

    2012-09-01

    This report explores the opportunity and defines the research agenda for mesoscale science—discovering, understanding, and controlling interactions among disparate systems and phenomena to reach the full potential of materials complexity and functionality. The ability to predict and control mesoscale phenomena and architectures is essential if atomic and molecular knowledge is to blossom into a next generation of technology opportunities, societal benefits, and scientific advances.. The body of this report outlines the need, the opportunities, the challenges, and the benefits of mastering mesoscale science.

  13. Data Pre-Analysis and Ensemble of Various Artificial Neural Networks for Monthly Streamflow Forecasting

    Directory of Open Access Journals (Sweden)

    Jianzhong Zhou

    2018-05-01

    Full Text Available This paper introduces three artificial neural network (ANN architectures for monthly streamflow forecasting: a radial basis function network, an extreme learning machine, and the Elman network. Three ensemble techniques, a simple average ensemble, a weighted average ensemble, and an ANN-based ensemble, were used to combine the outputs of the individual ANN models. The objective was to highlight the performance of the general regression neural network-based ensemble technique (GNE through an improvement of monthly streamflow forecasting accuracy. Before the construction of an ANN model, data preanalysis techniques, such as empirical wavelet transform (EWT, were exploited to eliminate the oscillations of the streamflow series. Additionally, a theory of chaos phase space reconstruction was used to select the most relevant and important input variables for forecasting. The proposed GNE ensemble model has been applied for the mean monthly streamflow observation data from the Wudongde hydrological station in the Jinsha River Basin, China. Comparisons and analysis of this study have demonstrated that the denoised streamflow time series was less disordered and unsystematic than was suggested by the original time series according to chaos theory. Thus, EWT can be adopted as an effective data preanalysis technique for the prediction of monthly streamflow. Concurrently, the GNE performed better when compared with other ensemble techniques.

  14. Quantum ensembles of quantum classifiers.

    Science.gov (United States)

    Schuld, Maria; Petruccione, Francesco

    2018-02-09

    Quantum machine learning witnesses an increasing amount of quantum algorithms for data-driven decision making, a problem with potential applications ranging from automated image recognition to medical diagnosis. Many of those algorithms are implementations of quantum classifiers, or models for the classification of data inputs with a quantum computer. Following the success of collective decision making with ensembles in classical machine learning, this paper introduces the concept of quantum ensembles of quantum classifiers. Creating the ensemble corresponds to a state preparation routine, after which the quantum classifiers are evaluated in parallel and their combined decision is accessed by a single-qubit measurement. This framework naturally allows for exponentially large ensembles in which - similar to Bayesian learning - the individual classifiers do not have to be trained. As an example, we analyse an exponentially large quantum ensemble in which each classifier is weighed according to its performance in classifying the training data, leading to new results for quantum as well as classical machine learning.

  15. North American Mesoscale Forecast System (NAM) [12 km

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The North American Mesoscale Forecast System (NAM) is one of the major regional weather forecast models run by the National Centers for Environmental Prediction...

  16. Assimilation of Doppler weather radar observations in a mesoscale ...

    Indian Academy of Sciences (India)

    Research (PSU–NCAR) mesoscale model (MM5) version 3.5.6. The variational data assimilation ... investigation of the direct assimilation of radar reflectivity data in 3DVAR system. The present ...... Results presented in this paper are based on.

  17. The Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS)

    National Research Council Canada - National Science Library

    Hodur, Richard M; Hong, Xiaodong; Doyle, James D; Pullen, Julie; Cummings, James; Martin, Paul; Rennick, Mary Alice

    2002-01-01

    ... of the Couple Ocean/Atmosphere Mesoscale Prediction System (COAMPS). The goal of this modeling project is to gain predictive skill in simulating the ocean and atmosphere at high resolution on time-scales of hours to several days...

  18. Climate change impact on available water resources obtained using multiple global climate and hydrology models

    Directory of Open Access Journals (Sweden)

    S. Hagemann

    2013-05-01

    Full Text Available Climate change is expected to alter the hydrological cycle resulting in large-scale impacts on water availability. However, future climate change impact assessments are highly uncertain. For the first time, multiple global climate (three and hydrological models (eight were used to systematically assess the hydrological response to climate change and project the future state of global water resources. This multi-model ensemble allows us to investigate how the hydrology models contribute to the uncertainty in projected hydrological changes compared to the climate models. Due to their systematic biases, GCM outputs cannot be used directly in hydrological impact studies, so a statistical bias correction has been applied. The results show a large spread in projected changes in water resources within the climate–hydrology modelling chain for some regions. They clearly demonstrate that climate models are not the only source of uncertainty for hydrological change, and that the spread resulting from the choice of the hydrology model is larger than the spread originating from the climate models over many areas. But there are also areas showing a robust change signal, such as at high latitudes and in some midlatitude regions, where the models agree on the sign of projected hydrological changes, indicative of higher confidence in this ensemble mean signal. In many catchments an increase of available water resources is expected but there are some severe decreases in Central and Southern Europe, the Middle East, the Mississippi River basin, southern Africa, southern China and south-eastern Australia.

  19. Simultaneous calibration of ensemble river flow predictions over an entire range of lead times

    Science.gov (United States)

    Hemri, S.; Fundel, F.; Zappa, M.

    2013-10-01

    Probabilistic estimates of future water levels and river discharge are usually simulated with hydrologic models using ensemble weather forecasts as main inputs. As hydrologic models are imperfect and the meteorological ensembles tend to be biased and underdispersed, the ensemble forecasts for river runoff typically are biased and underdispersed, too. Thus, in order to achieve both reliable and sharp predictions statistical postprocessing is required. In this work Bayesian model averaging (BMA) is applied to statistically postprocess ensemble runoff raw forecasts for a catchment in Switzerland, at lead times ranging from 1 to 240 h. The raw forecasts have been obtained using deterministic and ensemble forcing meteorological models with different forecast lead time ranges. First, BMA is applied based on mixtures of univariate normal distributions, subject to the assumption of independence between distinct lead times. Then, the independence assumption is relaxed in order to estimate multivariate runoff forecasts over the entire range of lead times simultaneously, based on a BMA version that uses multivariate normal distributions. Since river runoff is a highly skewed variable, Box-Cox transformations are applied in order to achieve approximate normality. Both univariate and multivariate BMA approaches are able to generate well calibrated probabilistic forecasts that are considerably sharper than climatological forecasts. Additionally, multivariate BMA provides a promising approach for incorporating temporal dependencies into the postprocessed forecasts. Its major advantage against univariate BMA is an increase in reliability when the forecast system is changing due to model availability.

  20. Ensemble forecasting of species distributions.

    Science.gov (United States)

    Araújo, Miguel B; New, Mark

    2007-01-01

    Concern over implications of climate change for biodiversity has led to the use of bioclimatic models to forecast the range shifts of species under future climate-change scenarios. Recent studies have demonstrated that projections by alternative models can be so variable as to compromise their usefulness for guiding policy decisions. Here, we advocate the use of multiple models within an ensemble forecasting framework and describe alternative approaches to the analysis of bioclimatic ensembles, including bounding box, consensus and probabilistic techniques. We argue that, although improved accuracy can be delivered through the traditional tasks of trying to build better models with improved data, more robust forecasts can also be achieved if ensemble forecasts are produced and analysed appropriately.

  1. Unifying Inference of Meso-Scale Structures in Networks.

    Science.gov (United States)

    Tunç, Birkan; Verma, Ragini

    2015-01-01

    Networks are among the most prevalent formal representations in scientific studies, employed to depict interactions between objects such as molecules, neuronal clusters, or social groups. Studies performed at meso-scale that involve grouping of objects based on their distinctive interaction patterns form one of the main lines of investigation in network science. In a social network, for instance, meso-scale structures can correspond to isolated social groupings or groups of individuals that serve as a communication core. Currently, the research on different meso-scale structures such as community and core-periphery structures has been conducted via independent approaches, which precludes the possibility of an algorithmic design that can handle multiple meso-scale structures and deciding which structure explains the observed data better. In this study, we propose a unified formulation for the algorithmic detection and analysis of different meso-scale structures. This facilitates the investigation of hybrid structures that capture the interplay between multiple meso-scale structures and statistical comparison of competing structures, all of which have been hitherto unavailable. We demonstrate the applicability of the methodology in analyzing the human brain network, by determining the dominant organizational structure (communities) of the brain, as well as its auxiliary characteristics (core-periphery).

  2. Unifying Inference of Meso-Scale Structures in Networks.

    Directory of Open Access Journals (Sweden)

    Birkan Tunç

    Full Text Available Networks are among the most prevalent formal representations in scientific studies, employed to depict interactions between objects such as molecules, neuronal clusters, or social groups. Studies performed at meso-scale that involve grouping of objects based on their distinctive interaction patterns form one of the main lines of investigation in network science. In a social network, for instance, meso-scale structures can correspond to isolated social groupings or groups of individuals that serve as a communication core. Currently, the research on different meso-scale structures such as community and core-periphery structures has been conducted via independent approaches, which precludes the possibility of an algorithmic design that can handle multiple meso-scale structures and deciding which structure explains the observed data better. In this study, we propose a unified formulation for the algorithmic detection and analysis of different meso-scale structures. This facilitates the investigation of hybrid structures that capture the interplay between multiple meso-scale structures and statistical comparison of competing structures, all of which have been hitherto unavailable. We demonstrate the applicability of the methodology in analyzing the human brain network, by determining the dominant organizational structure (communities of the brain, as well as its auxiliary characteristics (core-periphery.

  3. Wind power application research on the fusion of the determination and ensemble prediction

    Science.gov (United States)

    Lan, Shi; Lina, Xu; Yuzhu, Hao

    2017-07-01

    The fused product of wind speed for the wind farm is designed through the use of wind speed products of ensemble prediction from the European Centre for Medium-Range Weather Forecasts (ECMWF) and professional numerical model products on wind power based on Mesoscale Model5 (MM5) and Beijing Rapid Update Cycle (BJ-RUC), which are suitable for short-term wind power forecasting and electric dispatch. The single-valued forecast is formed by calculating the different ensemble statistics of the Bayesian probabilistic forecasting representing the uncertainty of ECMWF ensemble prediction. Using autoregressive integrated moving average (ARIMA) model to improve the time resolution of the single-valued forecast, and based on the Bayesian model averaging (BMA) and the deterministic numerical model prediction, the optimal wind speed forecasting curve and the confidence interval are provided. The result shows that the fusion forecast has made obvious improvement to the accuracy relative to the existing numerical forecasting products. Compared with the 0-24 h existing deterministic forecast in the validation period, the mean absolute error (MAE) is decreased by 24.3 % and the correlation coefficient (R) is increased by 12.5 %. In comparison with the ECMWF ensemble forecast, the MAE is reduced by 11.7 %, and R is increased 14.5 %. Additionally, MAE did not increase with the prolongation of the forecast ahead.

  4. Ensemble method for dengue prediction.

    Science.gov (United States)

    Buczak, Anna L; Baugher, Benjamin; Moniz, Linda J; Bagley, Thomas; Babin, Steven M; Guven, Erhan

    2018-01-01

    In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico) during four dengue seasons: 1) peak height (i.e., maximum weekly number of cases during a transmission season; 2) peak week (i.e., week in which the maximum weekly number of cases occurred); and 3) total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date. Our approach used ensemble models created by combining three disparate types of component models: 1) two-dimensional Method of Analogues models incorporating both dengue and climate data; 2) additive seasonal Holt-Winters models with and without wavelet smoothing; and 3) simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations. Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week. The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru.

  5. Ensemble method for dengue prediction.

    Directory of Open Access Journals (Sweden)

    Anna L Buczak

    Full Text Available In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico during four dengue seasons: 1 peak height (i.e., maximum weekly number of cases during a transmission season; 2 peak week (i.e., week in which the maximum weekly number of cases occurred; and 3 total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date.Our approach used ensemble models created by combining three disparate types of component models: 1 two-dimensional Method of Analogues models incorporating both dengue and climate data; 2 additive seasonal Holt-Winters models with and without wavelet smoothing; and 3 simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations.Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week.The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru.

  6. Advanced Atmospheric Ensemble Modeling Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Buckley, R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Chiswell, S. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Kurzeja, R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Maze, G. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Viner, B. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Werth, D. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2017-09-29

    Ensemble modeling (EM), the creation of multiple atmospheric simulations for a given time period, has become an essential tool for characterizing uncertainties in model predictions. We explore two novel ensemble modeling techniques: (1) perturbation of model parameters (Adaptive Programming, AP), and (2) data assimilation (Ensemble Kalman Filter, EnKF). The current research is an extension to work from last year and examines transport on a small spatial scale (<100 km) in complex terrain, for more rigorous testing of the ensemble technique. Two different release cases were studied, a coastal release (SF6) and an inland release (Freon) which consisted of two release times. Observations of tracer concentration and meteorology are used to judge the ensemble results. In addition, adaptive grid techniques have been developed to reduce required computing resources for transport calculations. Using a 20- member ensemble, the standard approach generated downwind transport that was quantitatively good for both releases; however, the EnKF method produced additional improvement for the coastal release where the spatial and temporal differences due to interior valley heating lead to the inland movement of the plume. The AP technique showed improvements for both release cases, with more improvement shown in the inland release. This research demonstrated that transport accuracy can be improved when models are adapted to a particular location/time or when important local data is assimilated into the simulation and enhances SRNL’s capability in atmospheric transport modeling in support of its current customer base and local site missions, as well as our ability to attract new customers within the intelligence community.

  7. Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

    Directory of Open Access Journals (Sweden)

    M. C. Demirel

    2018-02-01

    Full Text Available Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the

  8. Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

    Science.gov (United States)

    Demirel, Mehmet C.; Mai, Juliane; Mendiguren, Gorka; Koch, Julian; Samaniego, Luis; Stisen, Simon

    2018-02-01

    Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM) is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the shuffled complex

  9. Verification of Ensemble Forecasts for the New York City Operations Support Tool

    Science.gov (United States)

    Day, G.; Schaake, J. C.; Thiemann, M.; Draijer, S.; Wang, L.

    2012-12-01

    The New York City water supply system operated by the Department of Environmental Protection (DEP) serves nine million people. It covers 2,000 square miles of portions of the Catskill, Delaware, and Croton watersheds, and it includes nineteen reservoirs and three controlled lakes. DEP is developing an Operations Support Tool (OST) to support its water supply operations and planning activities. OST includes historical and real-time data, a model of the water supply system complete with operating rules, and lake water quality models developed to evaluate alternatives for managing turbidity in the New York City Catskill reservoirs. OST will enable DEP to manage turbidity in its unfiltered system while satisfying its primary objective of meeting the City's water supply needs, in addition to considering secondary objectives of maintaining ecological flows, supporting fishery and recreation releases, and mitigating downstream flood peaks. The current version of OST relies on statistical forecasts of flows in the system based on recent observed flows. To improve short-term decision making, plans are being made to transition to National Weather Service (NWS) ensemble forecasts based on hydrologic models that account for short-term weather forecast skill, longer-term climate information, as well as the hydrologic state of the watersheds and recent observed flows. To ensure that the ensemble forecasts are unbiased and that the ensemble spread reflects the actual uncertainty of the forecasts, a statistical model has been developed to post-process the NWS ensemble forecasts to account for hydrologic model error as well as any inherent bias and uncertainty in initial model states, meteorological data and forecasts. The post-processor is designed to produce adjusted ensemble forecasts that are consistent with the DEP historical flow sequences that were used to develop the system operating rules. A set of historical hindcasts that is representative of the real-time ensemble

  10. Post-processing of multi-model ensemble river discharge forecasts using censored EMOS

    Science.gov (United States)

    Hemri, Stephan; Lisniak, Dmytro; Klein, Bastian

    2014-05-01

    When forecasting water levels and river discharge, ensemble weather forecasts are used as meteorological input to hydrologic process models. As hydrologic models are imperfect and the input ensembles tend to be biased and underdispersed, the output ensemble forecasts for river runoff typically are biased and underdispersed, too. Thus, statistical post-processing is required in order to achieve calibrated and sharp predictions. Standard post-processing methods such as Ensemble Model Output Statistics (EMOS) that have their origins in meteorological forecasting are now increasingly being used in hydrologic applications. Here we consider two sub-catchments of River Rhine, for which the forecasting system of the Federal Institute of Hydrology (BfG) uses runoff data that are censored below predefined thresholds. To address this methodological challenge, we develop a censored EMOS method that is tailored to such data. The censored EMOS forecast distribution can be understood as a mixture of a point mass at the censoring threshold and a continuous part based on a truncated normal distribution. Parameter estimates of the censored EMOS model are obtained by minimizing the Continuous Ranked Probability Score (CRPS) over the training dataset. Model fitting on Box-Cox transformed data allows us to take account of the positive skewness of river discharge distributions. In order to achieve realistic forecast scenarios over an entire range of lead-times, there is a need for multivariate extensions. To this end, we smooth the marginal parameter estimates over lead-times. In order to obtain realistic scenarios of discharge evolution over time, the marginal distributions have to be linked with each other. To this end, the multivariate dependence structure can either be adopted from the raw ensemble like in Ensemble Copula Coupling (ECC), or be estimated from observations in a training period. The censored EMOS model has been applied to multi-model ensemble forecasts issued on a

  11. Benchmarking ensemble streamflow prediction skill in the UK

    Science.gov (United States)

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

    2018-03-01

    Skilful hydrological forecasts at sub-seasonal to seasonal lead times would be extremely beneficial for decision-making in water resources management, hydropower operations, and agriculture, especially during drought conditions. Ensemble streamflow prediction (ESP) is a well-established method for generating an ensemble of streamflow forecasts in the absence of skilful future meteorological predictions, instead using initial hydrologic conditions (IHCs), such as soil moisture, groundwater, and snow, as the source of skill. We benchmark when and where the ESP method is skilful across a diverse sample of 314 catchments in the UK and explore the relationship between catchment storage and ESP skill. The GR4J hydrological model was forced with historic climate sequences to produce a 51-member ensemble of streamflow hindcasts. We evaluated forecast skill seamlessly from lead times of 1 day to 12 months initialized at the first of each month over a 50-year hindcast period from 1965 to 2015. Results showed ESP was skilful against a climatology benchmark forecast in the majority of catchments across all lead times up to a year ahead, but the degree of skill was strongly conditional on lead time, forecast initialization month, and individual catchment location and storage properties. UK-wide mean ESP skill decayed exponentially as a function of lead time with continuous ranked probability skill scores across the year of 0.75, 0.20, and 0.11 for 1-day, 1-month, and 3-month lead times, respectively. However, skill was not uniform across all initialization months. For lead times up to 1 month, ESP skill was higher than average when initialized in summer and lower in winter months, whereas for longer seasonal and annual lead times skill was higher when initialized in autumn and winter months and lowest in spring. ESP was most skilful in the south and east of the UK, where slower responding catchments with higher soil moisture and groundwater storage are mainly located

  12. Cycloidal meandering of a mesoscale anticyclonic eddy

    Science.gov (United States)

    Kizner, Ziv; Shteinbuch-Fridman, Biana; Makarov, Viacheslav; Rabinovich, Michael

    2017-08-01

    By applying a theoretical approach, we propose a hypothetical scenario that might explain some features of the movement of a long-lived mesoscale anticyclone observed during 1990 in the Bay of Biscay [R. D. Pingree and B. Le Cann, "Three anticyclonic slope water oceanic eddies (SWODDIES) in the southern Bay of Biscay in 1990," Deep-Sea Res., Part A 39, 1147 (1992)]. In the remote-sensing infrared images, at the initial stage of observations, the anticyclone was accompanied by two cyclonic eddies, so the entire structure appeared as a tripole. However, at later stages, only the anticyclone was seen in the images, traveling generally west. Unusual for an individual eddy were the high speed of its motion (relative to the expected planetary beta-drift) and the presence of almost cycloidal meanders in its trajectory. Although surface satellites seem to have quickly disappeared, we hypothesize that subsurface satellites continued to exist, and the coherence of the three vortices persisted for a long time. A significant perturbation of the central symmetry in the mutual arrangement of three eddies constituting a tripole can make reasonably fast cycloidal drift possible. This hypothesis is tested with two-layer contour-dynamics f-plane simulations and with finite-difference beta-plane simulations. In the latter case, the interplay of the planetary beta-effect and that due to the sloping bottom is considered.

  13. Mesoscale simulations of hydrodynamic squirmer interactions.

    Science.gov (United States)

    Götze, Ingo O; Gompper, Gerhard

    2010-10-01

    The swimming behavior of self-propelled microorganisms is studied by particle-based mesoscale simulations. The simulation technique includes both hydrodynamics and thermal fluctuations that are both essential for the dynamics of microswimmers. The swimmers are modeled as squirmers, i.e., spherical objects with a prescribed tangential surface velocity, where the focus of thrust generation can be tuned from pushers to pullers. For passive squirmers (colloids), we show that the velocity autocorrelation function agrees quantitatively with the Boussinesq approximation. Single active squirmers show a persistent random-walk behavior, determined by forward motion, lateral diffusion, and orientational fluctuations, in agreement with theoretical predictions. For pairs of squirmers, which are initially swimming in parallel, we find an attraction for pushers and a repulsion for pullers, as expected. The hydrodynamic force between squirmer pairs is calculated as a function of the center-to-center distances d(cm) and is found to be consistent with a logarithmic distance dependence for d(cm) less than about two sphere diameters; here, the force is considerably stronger than expected from the far-field expansion. The dependence of the force strength on the asymmetry of the polar surface velocity is obtained. During the collision process, thermal fluctuations turn out to be very important and to strongly affect the postcollision velocity directions of both squirmers.

  14. Potentialities of ensemble strategies for flood forecasting over the Milano urban area

    Science.gov (United States)

    Ravazzani, Giovanni; Amengual, Arnau; Ceppi, Alessandro; Homar, Víctor; Romero, Romu; Lombardi, Gabriele; Mancini, Marco

    2016-08-01

    Analysis of ensemble forecasting strategies, which can provide a tangible backing for flood early warning procedures and mitigation measures over the Mediterranean region, is one of the fundamental motivations of the international HyMeX programme. Here, we examine two severe hydrometeorological episodes that affected the Milano urban area and for which the complex flood protection system of the city did not completely succeed. Indeed, flood damage have exponentially increased during the last 60 years, due to industrial and urban developments. Thus, the improvement of the Milano flood control system needs a synergism between structural and non-structural approaches. First, we examine how land-use changes due to urban development have altered the hydrological response to intense rainfalls. Second, we test a flood forecasting system which comprises the Flash-flood Event-based Spatially distributed rainfall-runoff Transformation, including Water Balance (FEST-WB) and the Weather Research and Forecasting (WRF) models. Accurate forecasts of deep moist convection and extreme precipitation are difficult to be predicted due to uncertainties arising from the numeric weather prediction (NWP) physical parameterizations and high sensitivity to misrepresentation of the atmospheric state; however, two hydrological ensemble prediction systems (HEPS) have been designed to explicitly cope with uncertainties in the initial and lateral boundary conditions (IC/LBCs) and physical parameterizations of the NWP model. No substantial differences in skill have been found between both ensemble strategies when considering an enhanced diversity of IC/LBCs for the perturbed initial conditions ensemble. Furthermore, no additional benefits have been found by considering more frequent LBCs in a mixed physics ensemble, as ensemble spread seems to be reduced. These findings could help to design the most appropriate ensemble strategies before these hydrometeorological extremes, given the computational

  15. HYDROLOGY, NESHOBA COUNTY, MISSISSIPPI

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  16. HYDROLOGY, MONTGOMERY COUNTY, MISSISSIPPI

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  17. HYDROLOGY, DOUGLAS COUNTY, MINNESOTA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  18. HYDROLOGY, OSCEOLA COUNTY, FL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  19. HYDROLOGY, STEARNS COUNTY, MN

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  20. HYDROLOGY, CALHOUN COUNTY, MISSISSIPPI

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  1. HYDROLOGY, LEFLORE COUNTY, MISSISSIPPI

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  2. HYDROLOGY, WAYNE COUNTY, MISSISSIPPI

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  3. Hydrology, OCONEE COUNTY, SC

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  4. HYDROLOGY, NEWTON COUNTY, MISSISSIPPI

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  5. HYDROLOGY, TIPPAH COUNTY, MISSISSIPPI

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  6. HYDROLOGY, CALHOUN COUNTY, MICHIGAN

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  7. HYDROLOGY, SUNFLOWER COUNTY, MISSISSIPPI

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  8. HYDROLOGY, HOUSTON COUNTY, ALABAMA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating ALood discharges for a ALood Insurance...

  9. Weber County Hydrology Report

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  10. HYDROLOGY, LEAKE COUNTY, MISSISSIPPI

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  11. HYDROLOGY, CHISAGO COUNTY, MN

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  12. HYDROLOGY, CLAIBORNE COUNTY, MS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  13. HYDROLOGY, LAFAYETTE COUNTY, MS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  14. HYDROLOGY, Yazoo COUNTY, MS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  15. HYDROLOGY, Lawrence County, ARKANSAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a Flood Insurance...

  16. HYDROLOGY, Allegheny County, PA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a Flood Insurance...

  17. HYDROLOGY, SIMPSON COUNTY, MS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  18. HYDROLOGY, GILCHRIST COUNTY, FL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  19. HYDROLOGY, GLADES COUNTY, FLORIDA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a Flood Insurance...

  20. HYDROLOGY, LEE COUNTY, TEXAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a Flood Insurance...

  1. HYDROLOGY, GREENE County, ARKANSAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a Flood Insurance...

  2. Ensemble forecasting of potential habitat for three invasive fishes

    Science.gov (United States)

    Poulos, Helen M.; Chernoff, Barry; Fuller, Pam L.; Butman, David

    2012-01-01

    Aquatic invasive species pose major ecological and economic threats to aquatic ecosystems worldwide via displacement, predation, or hybridization with native species and the alteration of aquatic habitats and hydrologic cycles. Modeling the habitat suitability of alien aquatic species through spatially explicit mapping is an increasingly important risk assessment tool. Habitat modeling also facilitates identification of key environmental variables influencing invasive species distributions. We compared four modeling methods to predict the potential continental United States distributions of northern snakehead Channa argus (Cantor, 1842), round goby Neogobius melanostomus (Pallas, 1814), and silver carp Hypophthalmichthys molitrix (Valenciennes, 1844) using maximum entropy (Maxent), the genetic algorithm for rule set production (GARP), DOMAIN, and support vector machines (SVM). We used inventory records from the USGS Nonindigenous Aquatic Species Database and a geographic information system of 20 climatic and environmental variables to generate individual and ensemble distribution maps for each species. The ensemble maps from our study performed as well as or better than all of the individual models except Maxent. The ensemble and Maxent models produced significantly higher accuracy individual maps than GARP, one-class SVMs, or DOMAIN. The key environmental predictor variables in the individual models were consistent with the tolerances of each species. Results from this study provide insights into which locations and environmental conditions may promote the future spread of invasive fish in the US.

  3. The progress of hydrology

    Energy Technology Data Exchange (ETDEWEB)

    Chow, V T [University of Illinois, Urbana, IL (United States)

    1967-05-15

    This paper discusses mainly the challenge of hydrology, recent activities, events, and major problems in hydrology, and advances in hydrological techniques. New scientific knowledge and techniques developed in many modern scientific disciplines, and the recognition of the importance of hydrology in water-resources development enable and encourage the hydrologist to advance scientific hydrology. Many programmes to promote hydrology and to expand its attendant activities have been developed in recent years. Therefore, the activities in the United States of America, such as the Universities Council on Water Resources and the President's Water for Peace Programme, and the programmes in the International Hydrological Decade are mentioned. The most important advance in theoretical hydrology is the development of a new concept of dynamic sequential systems for the hydrological cycle, thus creating new fields of systems, parametric, and stochastic hydrology. Modern scientific instrumentation provide the hydrologist with better tools for solving his problems. The most important of these, such as electronic computers, remote sensing, and nuclear techniques are discussed. Today various major problems, both theoretical and practical, face the hydrologist. Theoretical problems concern the basic understanding of hydrological systems and the mathematical simulation and physical interpretation of hydrological phenomena. Major practical problems are numerous and diversified, but they are mostly related to the multiple-purpose development of water resources. Four central problematical subjects are discussed; namely, the effects of man on his environment, the dynamics of aqueous flow systems, hydrological transport mechanism, and groundwater hydrology. Also, the use of nuclear techniques in solving various hydrological problems is discussed. It is believed that the application of nuclear techniques would prove extremely valuable in helping solve problems, but their ultimate use in

  4. The progress of hydrology

    International Nuclear Information System (INIS)

    Chow, V.T.

    1967-01-01

    This paper discusses mainly the challenge of hydrology, recent activities, events, and major problems in hydrology, and advances in hydrological techniques. New scientific knowledge and techniques developed in many modern scientific disciplines, and the recognition of the importance of hydrology in water-resources development enable and encourage the hydrologist to advance scientific hydrology. Many programmes to promote hydrology and to expand its attendant activities have been developed in recent years. Therefore, the activities in the United States of America, such as the Universities Council on Water Resources and the President's Water for Peace Programme, and the programmes in the International Hydrological Decade are mentioned. The most important advance in theoretical hydrology is the development of a new concept of dynamic sequential systems for the hydrological cycle, thus creating new fields of systems, parametric, and stochastic hydrology. Modern scientific instrumentation provide the hydrologist with better tools for solving his problems. The most important of these, such as electronic computers, remote sensing, and nuclear techniques are discussed. Today various major problems, both theoretical and practical, face the hydrologist. Theoretical problems concern the basic understanding of hydrological systems and the mathematical simulation and physical interpretation of hydrological phenomena. Major practical problems are numerous and diversified, but they are mostly related to the multiple-purpose development of water resources. Four central problematical subjects are discussed; namely, the effects of man on his environment, the dynamics of aqueous flow systems, hydrological transport mechanism, and groundwater hydrology. Also, the use of nuclear techniques in solving various hydrological problems is discussed. It is believed that the application of nuclear techniques would prove extremely valuable in helping solve problems, but their ultimate use in

  5. Ensemble hydro-meteorological forecasting for early warning of floods and scheduling of hydropower production

    Science.gov (United States)

    Solvang Johansen, Stian; Steinsland, Ingelin; Engeland, Kolbjørn

    2016-04-01

    Running hydrological models with precipitation and temperature ensemble forcing to generate ensembles of streamflow is a commonly used method in operational hydrology. Evaluations of streamflow ensembles have however revealed that the ensembles are biased with respect to both mean and spread. Thus postprocessing of the ensembles is needed in order to improve the forecast skill. The aims of this study is (i) to to evaluate how postprocessing of streamflow ensembles works for Norwegian catchments within different hydrological regimes and to (ii) demonstrate how post processed streamflow ensembles are used operationally by a hydropower producer. These aims were achieved by postprocessing forecasted daily discharge for 10 lead-times for 20 catchments in Norway by using EPS forcing from ECMWF applied the semi-distributed HBV-model dividing each catchment into 10 elevation zones. Statkraft Energi uses forecasts from these catchments for scheduling hydropower production. The catchments represent different hydrological regimes. Some catchments have stable winter condition with winter low flow and a major flood event during spring or early summer caused by snow melting. Others has a more mixed snow-rain regime, often with a secondary flood season during autumn, and in the coastal areas, the stream flow is dominated by rain, and the main flood season is autumn and winter. For post processing, a Bayesian model averaging model (BMA) close to (Kleiber et al 2011) is used. The model creates a predictive PDF that is a weighted average of PDFs centered on the individual bias corrected forecasts. The weights are here equal since all ensemble members come from the same model, and thus have the same probability. For modeling streamflow, the gamma distribution is chosen as a predictive PDF. The bias correction parameters and the PDF parameters are estimated using a 30-day sliding window training period. Preliminary results show that the improvement varies between catchments depending

  6. Teaching Strategies for Specialized Ensembles.

    Science.gov (United States)

    Teaching Music, 1999

    1999-01-01

    Provides a strategy, from the book "Strategies for Teaching Specialized Ensembles," that addresses Standard 9A of the National Standards for Music Education. Explains that students will identify and describe the musical and historical characteristics of the classical era in music they perform and in audio examples. (CMK)

  7. Multimodel ensembles of wheat growth

    DEFF Research Database (Denmark)

    Martre, Pierre; Wallach, Daniel; Asseng, Senthold

    2015-01-01

    , but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24...

  8. Spectral Diagonal Ensemble Kalman Filters

    Czech Academy of Sciences Publication Activity Database

    Kasanický, Ivan; Mandel, Jan; Vejmelka, Martin

    2015-01-01

    Roč. 22, č. 4 (2015), s. 485-497 ISSN 1023-5809 R&D Projects: GA ČR GA13-34856S Grant - others:NSF(US) DMS-1216481 Institutional support: RVO:67985807 Keywords : data assimilation * ensemble Kalman filter * spectral representation Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.321, year: 2015

  9. Genetic Algorithm Optimized Neural Networks Ensemble as ...

    African Journals Online (AJOL)

    Marquardt algorithm by varying conditions such as inputs, hidden neurons, initialization, training sets and random Gaussian noise injection to ... Several such ensembles formed the population which was evolved to generate the fittest ensemble.

  10. Global Ensemble Forecast System (GEFS) [1 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...

  11. Localization of atomic ensembles via superfluorescence

    International Nuclear Information System (INIS)

    Macovei, Mihai; Evers, Joerg; Keitel, Christoph H.; Zubairy, M. Suhail

    2007-01-01

    The subwavelength localization of an ensemble of atoms concentrated to a small volume in space is investigated. The localization relies on the interaction of the ensemble with a standing wave laser field. The light scattered in the interaction of the standing wave field and the atom ensemble depends on the position of the ensemble relative to the standing wave nodes. This relation can be described by a fluorescence intensity profile, which depends on the standing wave field parameters and the ensemble properties and which is modified due to collective effects in the ensemble of nearby particles. We demonstrate that the intensity profile can be tailored to suit different localization setups. Finally, we apply these results to two localization schemes. First, we show how to localize an ensemble fixed at a certain position in the standing wave field. Second, we discuss localization of an ensemble passing through the standing wave field

  12. Multiscale investigation of catchment functioning using environmental tracers: Insights from the mesoscale Attert basin in Luxembourg

    Science.gov (United States)

    Wrede, S.; Pfister, L.; Krein, A.; Bogaard, T. A.; Savenije, H. H. G.; Uhlenbrook, S.

    2009-04-01

    Experimental hydrology focuses traditionally on field investigations at smaller spatial and temporal scales and research is driven by small-scale, detailed and complex investigations of densely instrumented research sites. However, to improve operational water management and protection of water resources at the river basin scale, it is necessary to study the hydrological processes across a range of scales. Empirical studies investigating catchment structure and functioning across multiple scales are still rare and urgently needed. Besides geomorphologic and climatic catchment descriptors, environmental tracers have been recognized as a fundamental tool in experimental hydrology to assess the scaling gap, as they provide an independent and integrative perspective of catchment functioning and scaling. A three year tracer study is being carried out in the Attert river basin in Luxembourg to identify how major controls of runoff generation change across scales and to investigate the spatial and temporal functioning of larger basins. The mesoscale (300 km²) Attert catchment is located in the Midwestern part of Luxembourg and lies at the transition zone of contrasting bedrock lithology that is a major control for runoff generation: The Northern part is characterized by Devonian schist of the Ardennes massif, while sedimentary deposits of sandstone and marls dominate in the Southern part of the basin. Major hydrochemical tracers including stable water isotopes were grab sampled fortnightly and, where possible, also event-based at 13 nested stream locations ranging in size from 0.5 to 300 km² throughout the basin. Results using Deuterium and a range of hydrochemical tracers confirm the major role of bedrock lithology for runoff response of different geological parts of the basins: Hydrological response of schistose basins is characterized by seasonal variation and a delayed shallow groundwater component originating from a saprolitic zone, sandstone basins exhibit a

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

    Science.gov (United States)

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

    2013-04-01

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

  14. Diatoms as a fingerprint of sub-catchment contributions to meso-scale catchment runoff

    Science.gov (United States)

    Klaus, Julian; Wetzel, Carlos E.; Martinez-Carreras, Nuria; Ector, Luc; Pfister, Laurent

    2014-05-01

    In recent years, calls were made for new eco-hydrological approaches to improve understanding of hydrological processes. Recently diatoms, one of the most common and diverse algal groups that can be easily transported by flowing water due to their small size (~10-200 µm), were used to detect the onset and cessation of surface runoff to small headwater streams and constrain isotopic and hydro-chemical hydrograph separation methods. While the method showed its potential in the hillslope-riparian zone-stream continuum of headwater catchments, the behavior of diatoms and their use for hydrological process research in meso-scale catchments remains uncertain. Diatoms can be a valuable support for isotope and hydro-chemical tracer methods when these become ambiguous with increasing scale. Distribution and abundance of diatom species is controlled by various environmental factors (pH, soil type, moisture conditions, exposition to sunlight, etc.). We therefore hypothesize that species abundance and composition can be used as a proxy for source areas. This presentation evaluates the potential for diatoms to trace source-areas in the nested meso-scale Attert River basin (250 km2, Luxembourg, Europe). We sampled diatom populations in streamwater during one flood event in Fall 2011 in 6 sub-catchments and the basin outlet - 17 to 28 samples/catchment for the different sampling locations. Diatoms were classified and counted in every individual sample. In total more than 400 diatom species were detected. Ordination analysis revealed a clear distinction between communities sampled in different sub-catchments. The species composition at the catchment outlet reflects a mixing of the diatom composition originating from different sub-catchments. This data suggests that diatoms indeed can reflect the geographic origin of stream water at the catchment outlet. The centroids of the ordination analysis might be linked to the physiographic characteristics (geology and land use) of the

  15. Squeezing of Collective Excitations in Spin Ensembles

    DEFF Research Database (Denmark)

    Kraglund Andersen, Christian; Mølmer, Klaus

    2012-01-01

    We analyse the possibility to create two-mode spin squeezed states of two separate spin ensembles by inverting the spins in one ensemble and allowing spin exchange between the ensembles via a near resonant cavity field. We investigate the dynamics of the system using a combination of numerical an...

  16. Assessment of robustness and significance of climate change signals for an ensemble of distribution-based scaled climate projections

    DEFF Research Database (Denmark)

    Seaby, Lauren Paige; Refsgaard, J.C.; Sonnenborg, T.O.

    2013-01-01

    An ensemble of 11 regional climate model (RCM) projections are analysed for Denmark from a hydrological modelling inputs perspective. Two bias correction approaches are applied: a relatively simple monthly delta change (DC) method and a more complex daily distribution-based scaling (DBS) method...

  17. A multi-model ensemble of downscaled spatial climate change scenarios for the Dommel catchment, Western Europe

    NARCIS (Netherlands)

    Vliet, M.T.H. van; Blenkinsop, S.; Burton, A.; Harpham, C.; Broers, H.P.; Fowler, H.J.

    2012-01-01

    Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations

  18. Vertical Transport by Coastal Mesoscale Convective Systems

    Science.gov (United States)

    Lombardo, K.; Kading, T.

    2016-12-01

    This work is part of an ongoing investigation of coastal mesoscale convective systems (MCSs), including changes in vertical transport of boundary layer air by storms moving from inland to offshore. The density of a storm's cold pool versus that of the offshore marine atmospheric boundary layer (MABL), in part, determines the ability of the storm to successfully cross the coast, the mechanism driving storm propagation, and the ability of the storm to lift air from the boundary layer aloft. The ability of an MCS to overturn boundary layer air can be especially important over the eastern US seaboard, where warm season coastal MCSs are relatively common and where large coastal population centers generate concentrated regions of pollution. Recent work numerically simulating idealized MCSs in a coastal environment has provided some insight into the physical mechanisms governing MCS coastal crossing success and the impact on vertical transport of boundary layer air. Storms are simulated using a cloud resolving model initialized with atmospheric conditions representative of a Mid-Atlantic environment. Simulations are run in 2-D at 250 m horizontal resolution with a vertical resolution stretched from 100 m in the boundary layer to 250 m aloft. The left half of the 800 km domain is configured to represent land, while the right half is assigned as water. Sensitivity experiments are conducted to quantify the influence of varying MABL structure on MCS coastal crossing success and air transport, with MABL values representative of those observed over the western Mid-Atlantic during warm season. Preliminary results indicate that when the density of the cold pool is much greater than the MABL, the storm successfully crosses the coastline, with lifting of surface parcels, which ascend through the troposphere. When the density of the cold pool is similar to that of the MABL, parcels within the MABL remain at low levels, though parcels above the MABL ascend through the troposphere.

  19. Ensemble streamflow assimilation with the National Water Model.

    Science.gov (United States)

    Rafieeinasab, A.; McCreight, J. L.; Noh, S.; Seo, D. J.; Gochis, D.

    2017-12-01

    Through case studies of flooding across the US, we compare the performance of the National Water Model (NWM) data assimilation (DA) scheme to that of a newly implemented ensemble Kalman filter approach. The NOAA National Water Model (NWM) is an operational implementation of the community WRF-Hydro modeling system. As of August 2016, the NWM forecasts of distributed hydrologic states and fluxes (including soil moisture, snowpack, ET, and ponded water) over the contiguous United States have been publicly disseminated by the National Center for Environmental Prediction (NCEP) . It also provides streamflow forecasts at more than 2.7 million river reaches up to 30 days in advance. The NWM employs a nudging scheme to assimilate more than 6,000 USGS streamflow observations and provide initial conditions for its forecasts. A problem with nudging is how the forecasts relax quickly to open-loop bias in the forecast. This has been partially addressed by an experimental bias correction approach which was found to have issues with phase errors during flooding events. In this work, we present an ensemble streamflow data assimilation approach combining new channel-only capabilities of the NWM and HydroDART (a coupling of the offline WRF-Hydro model and NCAR's Data Assimilation Research Testbed; DART). Our approach focuses on the single model state of discharge and incorporates error distributions on channel-influxes (overland and groundwater) in the assimilation via an ensemble Kalman filter (EnKF). In order to avoid filter degeneracy associated with a limited number of ensemble at large scale, DART's covariance inflation (Anderson, 2009) and localization capabilities are implemented and evaluated. The current NWM data assimilation scheme is compared to preliminary results from the EnKF application for several flooding case studies across the US.

  20. Development and analysis of prognostic equations for mesoscale kinetic energy and mesoscale (subgrid scale) fluxes for large-scale atmospheric models

    Science.gov (United States)

    Avissar, Roni; Chen, Fei

    1993-01-01

    Generated by landscape discontinuities (e.g., sea breezes) mesoscale circulation processes are not represented in large-scale atmospheric models (e.g., general circulation models), which have an inappropiate grid-scale resolution. With the assumption that atmospheric variables can be separated into large scale, mesoscale, and turbulent scale, a set of prognostic equations applicable in large-scale atmospheric models for momentum, temperature, moisture, and any other gaseous or aerosol material, which includes both mesoscale and turbulent fluxes is developed. Prognostic equations are also developed for these mesoscale fluxes, which indicate a closure problem and, therefore, require a parameterization. For this purpose, the mean mesoscale kinetic energy (MKE) per unit of mass is used, defined as E-tilde = 0.5 (the mean value of u'(sub i exp 2), where u'(sub i) represents the three Cartesian components of a mesoscale circulation (the angle bracket symbol is the grid-scale, horizontal averaging operator in the large-scale model, and a tilde indicates a corresponding large-scale mean value). A prognostic equation is developed for E-tilde, and an analysis of the different terms of this equation indicates that the mesoscale vertical heat flux, the mesoscale pressure correlation, and the interaction between turbulence and mesoscale perturbations are the major terms that affect the time tendency of E-tilde. A-state-of-the-art mesoscale atmospheric model is used to investigate the relationship between MKE, landscape discontinuities (as characterized by the spatial distribution of heat fluxes at the earth's surface), and mesoscale sensible and latent heat fluxes in the atmosphere. MKE is compared with turbulence kinetic energy to illustrate the importance of mesoscale processes as compared to turbulent processes. This analysis emphasizes the potential use of MKE to bridge between landscape discontinuities and mesoscale fluxes and, therefore, to parameterize mesoscale fluxes

  1. Do we need full mesoscale models to simulate the urban heat island? A study over the city of Barcelona.

    Science.gov (United States)

    García-Díez, Markel; Ballester, Joan; De Ridder, Koen; Hooyberghs, Hans; Lauwaet, Dirk; Rodó, Xavier

    2016-04-01

    As most of the population lives in urban environments, the simulation of the urban climate has become an important part of the global climate change impact assessment. However, due to the high resolution required, these simulations demand a large amount of computational resources. Here we present a comparison between a simplified fast urban climate model (UrbClim) and a widely used full mesoscale model, the Weather Research and Forecasting (WRF) model, over the city of Barcelona. In order to check the advantages and disadvantages of each approach, both simulations were compared with station data and with land surface temperature observations retrieved by satellites, focusing on the urban heat island. The effect of changing the UrbClim boundary conditions was studied too, by using low resolution global reanalysis data (70 km) and a higher resolution forecast model (15 km). Finally, a strict comparison of the computational resources consumed by both models was carried out. Results show that, generally, the performance of the simple model is comparable to or better than the mesoscale model. The exception are the winds and the day-to-day correlation in the reanalysis driven run, but these problems disappear when taking the boundary conditions from a higher resolution global model. UrbClim was found to run 133 times faster than WRF, using 4x times higher resolution and, thus, it is an efficient solution for running long climate change simulations over large city ensembles.

  2. Eigenfunction statistics of Wishart Brownian ensembles

    International Nuclear Information System (INIS)

    Shukla, Pragya

    2017-01-01

    We theoretically analyze the eigenfunction fluctuation measures for a Hermitian ensemble which appears as an intermediate state of the perturbation of a stationary ensemble by another stationary ensemble of Wishart (Laguerre) type. Similar to the perturbation by a Gaussian stationary ensemble, the measures undergo a diffusive dynamics in terms of the perturbation parameter but the energy-dependence of the fluctuations is different in the two cases. This may have important consequences for the eigenfunction dynamics as well as phase transition studies in many areas of complexity where Brownian ensembles appear. (paper)

  3. Ensemble Streamflow Forecast Improvements in NYC's Operations Support Tool

    Science.gov (United States)

    Wang, L.; Weiss, W. J.; Porter, J.; Schaake, J. C.; Day, G. N.; Sheer, D. P.

    2013-12-01

    Like most other water supply utilities, New York City's Department of Environmental Protection (DEP) has operational challenges associated with drought and wet weather events. During drought conditions, DEP must maintain water supply reliability to 9 million customers as well as meet environmental release requirements downstream of its reservoirs. During and after wet weather events, DEP must maintain turbidity compliance in its unfiltered Catskill and Delaware reservoir systems and minimize spills to mitigate downstream flooding. Proactive reservoir management - such as release restrictions to prepare for a drought or preventative drawdown in advance of a large storm - can alleviate negative impacts associated with extreme events. It is important for water managers to understand the risks associated with proactive operations so unintended consequences such as endangering water supply reliability with excessive drawdown prior to a storm event are minimized. Probabilistic hydrologic forecasts are a critical tool in quantifying these risks and allow water managers to make more informed operational decisions. DEP has recently completed development of an Operations Support Tool (OST) that integrates ensemble streamflow forecasts, real-time observations, and a reservoir system operations model into a user-friendly graphical interface that allows its water managers to take robust and defensible proactive measures in the face of challenging system conditions. Since initial development of OST was first presented at the 2011 AGU Fall Meeting, significant improvements have been made to the forecast system. First, the monthly AR1 forecasts ('Hirsch method') were upgraded with a generalized linear model (GLM) utilizing historical daily correlations ('Extended Hirsch method' or 'eHirsch'). The development of eHirsch forecasts improved predictive skill over the Hirsch method in the first week to a month from the forecast date and produced more realistic hydrographs on the tail

  4. Modelling climate impact on floods under future emission scenarios using an ensemble of climate model projections

    Science.gov (United States)

    Wetterhall, F.; Cloke, H. L.; He, Y.; Freer, J.; Pappenberger, F.

    2012-04-01

    Evidence provided by modelled assessments of climate change impact on flooding is fundamental to water resource and flood risk decision making. Impact models usually rely on climate projections from Global and Regional Climate Models, and there is no doubt that these provide a useful assessment of future climate change. However, cascading ensembles of climate projections into impact models is not straightforward because of problems of coarse resolution in Global and Regional Climate Models (GCM/RCM) and the deficiencies in modelling high-intensity precipitation events. Thus decisions must be made on how to appropriately pre-process the meteorological variables from GCM/RCMs, such as selection of downscaling methods and application of Model Output Statistics (MOS). In this paper a grand ensemble of projections from several GCM/RCM are used to drive a hydrological model and analyse the resulting future flood projections for the Upper Severn, UK. The impact and implications of applying MOS techniques to precipitation as well as hydrological model parameter uncertainty is taken into account. The resultant grand ensemble of future river discharge projections from the RCM/GCM-hydrological model chain is evaluated against a response surface technique combined with a perturbed physics experiment creating a probabilisic ensemble climate model outputs. The ensemble distribution of results show that future risk of flooding in the Upper Severn increases compared to present conditions, however, the study highlights that the uncertainties are large and that strong assumptions were made in using Model Output Statistics to produce the estimates of future discharge. The importance of analysing on a seasonal basis rather than just annual is highlighted. The inability of the RCMs (and GCMs) to produce realistic precipitation patterns, even in present conditions, is a major caveat of local climate impact studies on flooding, and this should be a focus for future development.

  5. Nonequilibrium statistical mechanics ensemble method

    CERN Document Server

    Eu, Byung Chan

    1998-01-01

    In this monograph, nonequilibrium statistical mechanics is developed by means of ensemble methods on the basis of the Boltzmann equation, the generic Boltzmann equations for classical and quantum dilute gases, and a generalised Boltzmann equation for dense simple fluids The theories are developed in forms parallel with the equilibrium Gibbs ensemble theory in a way fully consistent with the laws of thermodynamics The generalised hydrodynamics equations are the integral part of the theory and describe the evolution of macroscopic processes in accordance with the laws of thermodynamics of systems far removed from equilibrium Audience This book will be of interest to researchers in the fields of statistical mechanics, condensed matter physics, gas dynamics, fluid dynamics, rheology, irreversible thermodynamics and nonequilibrium phenomena

  6. Statistical Analysis of Protein Ensembles

    Science.gov (United States)

    Máté, Gabriell; Heermann, Dieter

    2014-04-01

    As 3D protein-configuration data is piling up, there is an ever-increasing need for well-defined, mathematically rigorous analysis approaches, especially that the vast majority of the currently available methods rely heavily on heuristics. We propose an analysis framework which stems from topology, the field of mathematics which studies properties preserved under continuous deformations. First, we calculate a barcode representation of the molecules employing computational topology algorithms. Bars in this barcode represent different topological features. Molecules are compared through their barcodes by statistically determining the difference in the set of their topological features. As a proof-of-principle application, we analyze a dataset compiled of ensembles of different proteins, obtained from the Ensemble Protein Database. We demonstrate that our approach correctly detects the different protein groupings.

  7. Ensemble methods for handwritten digit recognition

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Liisberg, Christian; Salamon, P.

    1992-01-01

    Neural network ensembles are applied to handwritten digit recognition. The individual networks of the ensemble are combinations of sparse look-up tables (LUTs) with random receptive fields. It is shown that the consensus of a group of networks outperforms the best individual of the ensemble....... It is further shown that it is possible to estimate the ensemble performance as well as the learning curve on a medium-size database. In addition the authors present preliminary analysis of experiments on a large database and show that state-of-the-art performance can be obtained using the ensemble approach...... by optimizing the receptive fields. It is concluded that it is possible to improve performance significantly by introducing moderate-size ensembles; in particular, a 20-25% improvement has been found. The ensemble random LUTs, when trained on a medium-size database, reach a performance (without rejects) of 94...

  8. Mesoscale modeling of solute precipitation and radiation damage

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yongfeng [Idaho National Lab. (INL), Idaho Falls, ID (United States); Schwen, Daniel [Idaho National Lab. (INL), Idaho Falls, ID (United States); Ke, Huibin [Idaho National Lab. (INL), Idaho Falls, ID (United States); Univ. of Wisconsin, Madison, WI (United States); Bai, Xianming [Idaho National Lab. (INL), Idaho Falls, ID (United States); Hales, Jason [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-09-01

    This report summarizes the low length scale effort during FY 2014 in developing mesoscale capabilities for microstructure evolution in reactor pressure vessels. During operation, reactor pressure vessels are subject to hardening and embrittlement caused by irradiation-induced defect accumulation and irradiation-enhanced solute precipitation. Both defect production and solute precipitation start from the atomic scale, and manifest their eventual effects as degradation in engineering-scale properties. To predict the property degradation, multiscale modeling and simulation are needed to deal with the microstructure evolution, and to link the microstructure feature to material properties. In this report, the development of mesoscale capabilities for defect accumulation and solute precipitation are summarized. Atomic-scale efforts that supply information for the mesoscale capabilities are also included.

  9. Low-level wind response to mesoscale pressure systems

    Science.gov (United States)

    Garratt, J. R.; Physick, W. L.

    1983-09-01

    Observations are presented which show a strong correlation between low-level wind behaviour (e.g., rotation near the surface) and the passage of mesoscale pressure systems. The latter are associated with frontal transition zones, are dominated by a pressure-jump line and a mesoscale high pressure area, and produce locally large horizontal pressure gradients. The wind observations are simulated by specifying a time sequence of perturbation pressure gradient and subsequently solving the vertically-integrated momentum equations with appropriate initial conditions. Very good agreement is found between observed and calculated winds; in particular, (i) a 360 ° rotation in wind on passage of the mesoscale high; (ii) wind-shift lines produced dynamically by the pressure-jump line; (iii) rapid linear increase in wind speed on passage of the pressure jump.

  10. Benchmarking Commercial Conformer Ensemble Generators.

    Science.gov (United States)

    Friedrich, Nils-Ole; de Bruyn Kops, Christina; Flachsenberg, Florian; Sommer, Kai; Rarey, Matthias; Kirchmair, Johannes

    2017-11-27

    We assess and compare the performance of eight commercial conformer ensemble generators (ConfGen, ConfGenX, cxcalc, iCon, MOE LowModeMD, MOE Stochastic, MOE Conformation Import, and OMEGA) and one leading free algorithm, the distance geometry algorithm implemented in RDKit. The comparative study is based on a new version of the Platinum Diverse Dataset, a high-quality benchmarking dataset of 2859 protein-bound ligand conformations extracted from the PDB. Differences in the performance of commercial algorithms are much smaller than those observed for free algorithms in our previous study (J. Chem. Inf. 2017, 57, 529-539). For commercial algorithms, the median minimum root-mean-square deviations measured between protein-bound ligand conformations and ensembles of a maximum of 250 conformers are between 0.46 and 0.61 Å. Commercial conformer ensemble generators are characterized by their high robustness, with at least 99% of all input molecules successfully processed and few or even no substantial geometrical errors detectable in their output conformations. The RDKit distance geometry algorithm (with minimization enabled) appears to be a good free alternative since its performance is comparable to that of the midranked commercial algorithms. Based on a statistical analysis, we elaborate on which algorithms to use and how to parametrize them for best performance in different application scenarios.

  11. A high space-time resolution dataset linking meteorological forcing and hydro-sedimentary response in a mesoscale Mediterranean catchment (Auzon) of the Ardèche region, France

    OpenAIRE

    Nord, Guillaume; Boudevillain, Brice; Berne, Alexis; Branger, Flora; Braud, Isabelle; Dramais, Guillaume; Gérard, Simon; Coz, Le, Jérôme; Legoût, Cédric; Molinié, Gilles; Teuling, Ryan

    2017-01-01

    A comprehensive hydrometeorological dataset is presented spanning the period 1 January 2011-31 December 2014 to improve the understanding of the hydrological processes leading to flash floods and the relation between rainfall, runoff, erosion and sediment transport in a mesoscale catchment (Auzon, 116km2) of the Mediterranean region. Badlands are present in the Auzon catchment and well connected to high-gradient channels of bedrock rivers which promotes the transfer of suspended solids downst...

  12. Spatial patterns of stream temperatures and electric conductivity in a mesoscale catchment

    Science.gov (United States)

    Lieder, Ernestine; Weiler, Markus; Blume, Theresa

    2017-04-01

    Stream temperature and electric conductivity (EC) are both relatively easily measured and can provide valuable information on runoff generation processes and catchment storage.This study investigates the spatial variability of stream temperature and EC in a mesoscale basin. We focus on the mesoscale (sub-catchments and reach scale), and long term (seasonal / annual) stream temperature and EC patterns. Our study basin is the Attert catchment in Luxembourg (288km2), which contains multiple sub-catchments of different geology, topography and land use patterns. We installed 90 stream temperature and EC sensors at sites across the basin in summer 2015. The collected data is complemented by land use and discharge data and an extensive climate data set. Thermal sensitivity was calculated as the slope of daily air temperature-water-temperature regression line and describes the sensitivity of stream temperature to long term environmental change. Amplitude sensitivity was calculated as slope of the daily air and water temperature amplitude regression and describes the short term warming capacity of the stream. We found that groups with similar long term thermal and EC patterns are strongly related to different geological units. The sandstone reaches show the coldest temperatures and lowest annual thermal sensitivity to air temperature. The slate reaches are characterized by comparably low EC and high daily temperature amplitudes and amplitude sensitivity. Furthermore, mean annual temperatures and thermal sensitivities increase exponentially with drainage area, which can be attributed to the accumulation of heat throughout the system. On the reach scale, daily stream temperature fluctuations or sensitivities were strongly influenced by land cover distribution, stream shading and runoff volume. Daily thermal sensitivities were low for headwater streams; peaked for intermediate reaches in the middle of the catchment and then decreased again further downstream with increasing

  13. The impact of anticyclonic mesoscale structures on microbial food webs in the Mediterranean Sea

    Science.gov (United States)

    Christaki, U.; van Wambeke, F.; Lefevre, D.; Lagaria, A.; Prieur, L.; Pujo-Pay, M.; Grattepanche, J.-D.; Colombet, J.; Psarra, S.; Dolan, J. R.; Sime-Ngando, T.; Conan, P.; Weinbauer, M. G.; Moutin, T.

    2011-01-01

    The abundance and activity of the major members of the heterotrophic microbial community - from viruses to ciliates - were studied along a longitudinal transect across the Mediterranean Sea in the summer of 2008. The Mediterranean Sea is characterized by a west to the east gradient of deepening of DCM (deep chlorophyll maximum) and increasing oligotrophy reflected in gradients of heterotrophic microbial biomass and production. However, within this longitudinal trend, hydrological mesoscale features exist and likely influence microbial dynamics. We show here the importance of mesoscale structures by a description of the structure and function of the microbial food web through an investigation of 3 geographically distant eddies within a longitudinal transect. Three selected sites each located in the center of an anticyclonic eddy were intensively investigated: in the Algero-Provencal Basin (St. A), the Ionian Basin (St. B), and the Levantine Basin (St. C). The 3 geographically distant eddies showed the lowest values of the different heterotrophic compartments of the microbial food web, and except for viruses in site C, all stocks were higher in the neighboring stations outside the eddies. During our study the 3 eddies showed equilibrium between GCP (Gross Community Production) and DCR (Dark Community Respiration); moreover, the west-east (W-E) gradient was evident in terms of heterotrophic biomass but not in terms of production. Means of integrated PPp values were higher at site B (~190 mg C m-2 d-1) and about 15% lower at sites A and C (~160 mg C m-2 d-1). Net community production fluxes were similar at all three stations exhibiting equilibrium between gross community production and dark community respiration.

  14. Ensemble seasonal forecast of extreme water inflow into a large reservoir

    Directory of Open Access Journals (Sweden)

    A. N. Gelfan

    2015-06-01

    Full Text Available An approach to seasonal ensemble forecast of unregulated water inflow into a large reservoir was developed. The approach is founded on a physically-based semi-distributed hydrological model ECOMAG driven by Monte-Carlo generated ensembles of weather scenarios for a specified lead-time of the forecast (3 months ahead in this study. Case study was carried out for the Cheboksary reservoir (catchment area is 374 000 km2 located on the middle Volga River. Initial watershed conditions on the forecast date (1 March for spring freshet and 1 June for summer low-water period were simulated by the hydrological model forced by daily meteorological observations several months prior to the forecast date. A spatially distributed stochastic weather generator was used to produce time-series of daily weather scenarios for the forecast lead-time. Ensemble of daily water inflow into the reservoir was obtained by driving the ECOMAG model with the generated weather time-series. The proposed ensemble forecast technique was verified on the basis of the hindcast simulations for 29 spring and summer seasons beginning from 1982 (the year of the reservoir filling to capacity to 2010. The verification criteria were used in order to evaluate an ability of the proposed technique to forecast freshet/low-water events of the pre-assigned severity categories.

  15. On Improving 4-km Mesoscale Model Simulations

    Science.gov (United States)

    Deng, Aijun; Stauffer, David R.

    2006-03-01

    A previous study showed that use of analysis-nudging four-dimensional data assimilation (FDDA) and improved physics in the fifth-generation Pennsylvania State University National Center for Atmospheric Research Mesoscale Model (MM5) produced the best overall performance on a 12-km-domain simulation, based on the 18 19 September 1983 Cross-Appalachian Tracer Experiment (CAPTEX) case. However, reducing the simulated grid length to 4 km had detrimental effects. The primary cause was likely the explicit representation of convection accompanying a cold-frontal system. Because no convective parameterization scheme (CPS) was used, the convective updrafts were forced on coarser-than-realistic scales, and the rainfall and the atmospheric response to the convection were too strong. The evaporative cooling and downdrafts were too vigorous, causing widespread disruption of the low-level winds and spurious advection of the simulated tracer. In this study, a series of experiments was designed to address this general problem involving 4-km model precipitation and gridpoint storms and associated model sensitivities to the use of FDDA, planetary boundary layer (PBL) turbulence physics, grid-explicit microphysics, a CPS, and enhanced horizontal diffusion. Some of the conclusions include the following: 1) Enhanced parameterized vertical mixing in the turbulent kinetic energy (TKE) turbulence scheme has shown marked improvements in the simulated fields. 2) Use of a CPS on the 4-km grid improved the precipitation and low-level wind results. 3) Use of the Hong and Pan Medium-Range Forecast PBL scheme showed larger model errors within the PBL and a clear tendency to predict much deeper PBL heights than the TKE scheme. 4) Combining observation-nudging FDDA with a CPS produced the best overall simulations. 5) Finer horizontal resolution does not always produce better simulations, especially in convectively unstable environments, and a new CPS suitable for 4-km resolution is needed. 6

  16. Multiscale Modeling of Mesoscale and Interfacial Phenomena

    Science.gov (United States)

    Petsev, Nikolai Dimitrov

    With rapidly emerging technologies that feature interfaces modified at the nanoscale, traditional macroscopic models are pushed to their limits to explain phenomena where molecular processes can play a key role. Often, such problems appear to defy explanation when treated with coarse-grained continuum models alone, yet remain prohibitively expensive from a molecular simulation perspective. A prominent example is surface nanobubbles: nanoscopic gaseous domains typically found on hydrophobic surfaces that have puzzled researchers for over two decades due to their unusually long lifetimes. We show how an entirely macroscopic, non-equilibrium model explains many of their anomalous properties, including their stability and abnormally small gas-side contact angles. From this purely transport perspective, we investigate how factors such as temperature and saturation affect nanobubbles, providing numerous experimentally testable predictions. However, recent work also emphasizes the relevance of molecular-scale phenomena that cannot be described in terms of bulk phases or pristine interfaces. This is true for nanobubbles as well, whose nanoscale heights may require molecular detail to capture the relevant physics, in particular near the bubble three-phase contact line. Therefore, there is a clear need for general ways to link molecular granularity and behavior with large-scale continuum models in the treatment of many interfacial problems. In light of this, we have developed a general set of simulation strategies that couple mesoscale particle-based continuum models to molecular regions simulated through conventional molecular dynamics (MD). In addition, we derived a transport model for binary mixtures that opens the possibility for a wide range of applications in biological and drug delivery problems, and is readily reconciled with our hybrid MD-continuum techniques. Approaches that couple multiple length scales for fluid mixtures are largely absent in the literature, and

  17. New Mesoscale Fluvial Landscapes - Seismic Geomorphology and Exploration

    Science.gov (United States)

    Wilkinson, M. J.

    2013-01-01

    Megafans (100-600 km radius) are very large alluvial fans that cover significant areas on most continents, the surprising finding of recent global surveys. The number of such fans and patterns of sedimentation on them provides new mesoscale architectures that can now be applied on continental fluvial depositional systems, and therefore on. Megafan-scale reconstructions underground as yet have not been attempted. Seismic surveys offer new possibilities in identifying the following prospective situations at potentially unsuspected locations: (i) sand concentrations points, (ii) sand-mud continuums at the mesoscale, (iii) paleo-valley forms in these generally unvalleyed landscapes, (iv) stratigraphic traps, and (v) structural traps.

  18. Uncertainty Assessment: Reservoir Inflow Forecasting with Ensemble Precipitation Forecasts and HEC-HMS

    Directory of Open Access Journals (Sweden)

    Sheng-Chi Yang

    2014-01-01

    Full Text Available During an extreme event, having accurate inflow forecasting with enough lead time helps reservoir operators decrease the impact of floods downstream. Furthermore, being able to efficiently operate reservoirs could help maximize flood protection while saving water for drier times of the year. This study combines ensemble quantitative precipitation forecasts and a hydrological model to provide a 3-day reservoir inflow in the Shihmen Reservoir, Taiwan. A total of six historical typhoons were used for model calibration, validation, and application. An understanding of cascaded uncertainties from the numerical weather model through the hydrological model is necessary for a better use for forecasting. This study thus conducted an assessment of forecast uncertainty on magnitude and timing of peak and cumulative inflows. It found that using the ensemble-mean had less uncertainty than randomly selecting individual member. The inflow forecasts with shorter length of cumulative time had a higher uncertainty. The results showed that using the ensemble precipitation forecasts with the hydrological model would have the advantage of extra lead time and serve as a valuable reference for operating reservoirs.

  19. Global operational hydrological forecasts through eWaterCycle

    Science.gov (United States)

    van de Giesen, Nick; Bierkens, Marc; Donchyts, Gennadii; Drost, Niels; Hut, Rolf; Sutanudjaja, Edwin

    2015-04-01

    Central goal of the eWaterCycle project (www.ewatercycle.org) is the development of an operational hyper-resolution hydrological global model. This model is able to produce 14 day ensemble forecasts based on a hydrological model and operational weather data (presently NOAA's Global Ensemble Forecast System). Special attention is paid to prediction of situations in which water related issues are relevant, such as floods, droughts, navigation, hydropower generation, and irrigation stress. Near-real time satellite data will be assimilated in the hydrological simulations, which is a feature that will be presented for the first time at EGU 2015. First, we address challenges that are mainly computer science oriented but have direct practical hydrological implications. An important feature in this is the use of existing standards and open-source software to the maximum extent possible. For example, we use the Community Surface Dynamics Modeling System (CSDMS) approach to coupling models (Basic Model Interface (BMI)). The hydrological model underlying the project is PCR-GLOBWB, built by Utrecht University. This is the motor behind the predictions and state estimations. Parts of PCR-GLOBWB have been re-engineered to facilitate running it in a High Performance Computing (HPC) environment, run parallel on multiple nodes, as well as to use BMI. Hydrological models are not very CPU intensive compared to, say, atmospheric models. They are, however, memory hungry due to the localized processes and associated effective parameters. To accommodate this memory need, especially in an ensemble setting, a variation on the traditional Ensemble Kalman Filter was developed that needs much less on-chip memory. Due to the operational nature, the coupling of the hydrological model with hydraulic models is very important. The idea is not to run detailed hydraulic routing schemes over the complete globe but to have on-demand simulation prepared off-line with respect to topography and

  20. Constraining the ensemble Kalman filter for improved streamflow forecasting

    Science.gov (United States)

    Maxwell, Deborah H.; Jackson, Bethanna M.; McGregor, James

    2018-05-01

    Data assimilation techniques such as the Ensemble Kalman Filter (EnKF) are often applied to hydrological models with minimal state volume/capacity constraints enforced during ensemble generation. Flux constraints are rarely, if ever, applied. Consequently, model states can be adjusted beyond physically reasonable limits, compromising the integrity of model output. In this paper, we investigate the effect of constraining the EnKF on forecast performance. A "free run" in which no assimilation is applied is compared to a completely unconstrained EnKF implementation, a 'typical' hydrological implementation (in which mass constraints are enforced to ensure non-negativity and capacity thresholds of model states are not exceeded), and then to a more tightly constrained implementation where flux as well as mass constraints are imposed to force the rate of water movement to/from ensemble states to be within physically consistent boundaries. A three year period (2008-2010) was selected from the available data record (1976-2010). This was specifically chosen as it had no significant data gaps and represented well the range of flows observed in the longer dataset. Over this period, the standard implementation of the EnKF (no constraints) contained eight hydrological events where (multiple) physically inconsistent state adjustments were made. All were selected for analysis. Mass constraints alone did little to improve forecast performance; in fact, several were significantly degraded compared to the free run. In contrast, the combined use of mass and flux constraints significantly improved forecast performance in six events relative to all other implementations, while the remaining two events showed no significant difference in performance. Placing flux as well as mass constraints on the data assimilation framework encourages physically consistent state estimation and results in more accurate and reliable forward predictions of streamflow for robust decision-making. We also

  1. Distributed HUC-based modeling with SUMMA for ensemble streamflow forecasting over large regional domains.

    Science.gov (United States)

    Saharia, M.; Wood, A.; Clark, M. P.; Bennett, A.; Nijssen, B.; Clark, E.; Newman, A. J.

    2017-12-01

    Most operational streamflow forecasting systems rely on a forecaster-in-the-loop approach in which some parts of the forecast workflow require an experienced human forecaster. But this approach faces challenges surrounding process reproducibility, hindcasting capability, and extension to large domains. The operational hydrologic community is increasingly moving towards `over-the-loop' (completely automated) large-domain simulations yet recent developments indicate a widespread lack of community knowledge about the strengths and weaknesses of such systems for forecasting. A realistic representation of land surface hydrologic processes is a critical element for improving forecasts, but often comes at the substantial cost of forecast system agility and efficiency. While popular grid-based models support the distributed representation of land surface processes, intermediate-scale Hydrologic Unit Code (HUC)-based modeling could provide a more efficient and process-aligned spatial discretization, reducing the need for tradeoffs between model complexity and critical forecasting requirements such as ensemble methods and comprehensive model calibration. The National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the USACE to implement, assess, and demonstrate real-time, over-the-loop distributed streamflow forecasting for several large western US river basins and regions. In this presentation, we present early results from short to medium range hydrologic and streamflow forecasts for the Pacific Northwest (PNW). We employ a real-time 1/16th degree daily ensemble model forcings as well as downscaled Global Ensemble Forecasting System (GEFS) meteorological forecasts. These datasets drive an intermediate-scale configuration of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) model, which represents the PNW using over 11,700 HUCs. The system produces not only streamflow forecasts (using the Mizu

  2. NCAR's Experimental Real-time Convection-allowing Ensemble Prediction System

    Science.gov (United States)

    Schwartz, C. S.; Romine, G. S.; Sobash, R.; Fossell, K.

    2016-12-01

    Since April 2015, the National Center for Atmospheric Research's (NCAR's) Mesoscale and Microscale Meteorology (MMM) Laboratory, in collaboration with NCAR's Computational Information Systems Laboratory (CISL), has been producing daily, real-time, 10-member, 48-hr ensemble forecasts with 3-km horizontal grid spacing over the conterminous United States (http://ensemble.ucar.edu). These computationally-intensive, next-generation forecasts are produced on the Yellowstone supercomputer, have been embraced by both amateur and professional weather forecasters, are widely used by NCAR and university researchers, and receive considerable attention on social media. Initial conditions are supplied by NCAR's Data Assimilation Research Testbed (DART) software and the forecast model is NCAR's Weather Research and Forecasting (WRF) model; both WRF and DART are community tools. This presentation will focus on cutting-edge research results leveraging the ensemble dataset, including winter weather predictability, severe weather forecasting, and power outage modeling. Additionally, the unique design of the real-time analysis and forecast system and computational challenges and solutions will be described.

  3. Data assimilation for groundwater flow modelling using Unbiased Ensemble Square Root Filter: Case study in Guantao, North China Plain

    Science.gov (United States)

    Li, N.; Kinzelbach, W.; Li, H.; Li, W.; Chen, F.; Wang, L.

    2017-12-01

    Data assimilation techniques are widely used in hydrology to improve the reliability of hydrological models and to reduce model predictive uncertainties. This provides critical information for decision makers in water resources management. This study aims to evaluate a data assimilation system for the Guantao groundwater flow model coupled with a one-dimensional soil column simulation (Hydrus 1D) using an Unbiased Ensemble Square Root Filter (UnEnSRF) originating from the Ensemble Kalman Filter (EnKF) to update parameters and states, separately or simultaneously. To simplify the coupling between unsaturated and saturated zone, a linear relationship obtained from analyzing inputs to and outputs from Hydrus 1D is applied in the data assimilation process. Unlike EnKF, the UnEnSRF updates parameter ensemble mean and ensemble perturbations separately. In order to keep the ensemble filter working well during the data assimilation, two factors are introduced in the study. One is called damping factor to dampen the update amplitude of the posterior ensemble mean to avoid nonrealistic values. The other is called inflation factor to relax the posterior ensemble perturbations close to prior to avoid filter inbreeding problems. The sensitivities of the two factors are studied and their favorable values for the Guantao model are determined. The appropriate observation error and ensemble size were also determined to facilitate the further analysis. This study demonstrated that the data assimilation of both model parameters and states gives a smaller model prediction error but with larger uncertainty while the data assimilation of only model states provides a smaller predictive uncertainty but with a larger model prediction error. Data assimilation in a groundwater flow model will improve model prediction and at the same time make the model converge to the true parameters, which provides a successful base for applications in real time modelling or real time controlling strategies

  4. Skills of different mesoscale models over Indian region during ...

    Indian Academy of Sciences (India)

    tion and prediction of high impact severe weather systems. Such models ... mesoscale models can be run at cloud resolving resolutions (∼1km) ... J. Earth Syst. Sci. 117, No. ..... similar to climate drift, indicating that those error components are ...

  5. Mesoscale meteorological model based on radioactive explosion cloud simulation

    International Nuclear Information System (INIS)

    Zheng Yi; Zhang Yan; Ying Chuntong

    2008-01-01

    In order to simulate nuclear explosion and dirty bomb radioactive cloud movement and concentration distribution, mesoscale meteorological model RAMS was used. Particles-size, size-active distribution and gravitational fallout in the cloud were considered. The results show that the model can simulate the 'mushroom' clouds of explosion. Three-dimension fluid field and radioactive concentration field were received. (authors)

  6. Role of land state in a high resolution mesoscale model

    Indian Academy of Sciences (India)

    ... Proceedings – Mathematical Sciences · Resonance – Journal of Science ... Land surface characteristics; high resolution mesoscale model; Uttarakhand ... to predict realistic location, timing, amount,intensity and distribution of rainfall ... region embedded within two low pressure centers over Arabian Seaand Bay of Bengal.

  7. Modeling Air-Quality in Complex Terrain Using Mesoscale and ...

    African Journals Online (AJOL)

    Air-quality in a complex terrain (Colorado-River-Valley/Grand-Canyon Area, Southwest U.S.) is modeled using a higher-order closure mesoscale model and a higher-order closure dispersion model. Non-reactive tracers have been released in the Colorado-River valley, during winter and summer 1992, to study the ...

  8. Mesoscale characterization of local property distributions in heterogeneous electrodes

    Science.gov (United States)

    Hsu, Tim; Epting, William K.; Mahbub, Rubayyat; Nuhfer, Noel T.; Bhattacharya, Sudip; Lei, Yinkai; Miller, Herbert M.; Ohodnicki, Paul R.; Gerdes, Kirk R.; Abernathy, Harry W.; Hackett, Gregory A.; Rollett, Anthony D.; De Graef, Marc; Litster, Shawn; Salvador, Paul A.

    2018-05-01

    The performance of electrochemical devices depends on the three-dimensional (3D) distributions of microstructural features in their electrodes. Several mature methods exist to characterize 3D microstructures over the microscale (tens of microns), which are useful in understanding homogeneous electrodes. However, methods that capture mesoscale (hundreds of microns) volumes at appropriate resolution (tens of nm) are lacking, though they are needed to understand more common, less ideal electrodes. Using serial sectioning with a Xe plasma focused ion beam combined with scanning electron microscopy (Xe PFIB-SEM), two commercial solid oxide fuel cell (SOFC) electrodes are reconstructed over volumes of 126 × 73 × 12.5 and 124 × 110 × 8 μm3 with a resolution on the order of ≈ 503 nm3. The mesoscale distributions of microscale structural features are quantified and both microscale and mesoscale inhomogeneities are found. We analyze the origin of inhomogeneity over different length scales by comparing experimental and synthetic microstructures, generated with different particle size distributions, with such synthetic microstructures capturing well the high-frequency heterogeneity. Effective medium theory models indicate that significant mesoscale variations in local electrochemical activity are expected throughout such electrodes. These methods offer improved understanding of the performance of complex electrodes in energy conversion devices.

  9. Onset of meso-scale turbulence in active nematics

    NARCIS (Netherlands)

    Doostmohammadi, A.; Shendruk, T.N.; Thijssen, K.; Yeomans, J.M.

    2017-01-01

    Meso-scale turbulence is an innate phenomenon, distinct from inertial turbulence, that spontaneously occurs at low Reynolds number in fluidized biological systems. This spatiotemporal disordered flow radically changes nutrient and molecular transport in living fluids and can strongly affect the

  10. Calculation of extreme wind atlases using mesoscale modeling. Final report

    DEFF Research Database (Denmark)

    Larsén, Xiaoli Guo; Badger, Jake

    This is the final report of the project PSO-10240 "Calculation of extreme wind atlases using mesoscale modeling". The overall objective is to improve the estimation of extreme winds by developing and applying new methodologies to confront the many weaknesses in the current methodologies as explai...

  11. Measuring social interaction in music ensembles.

    Science.gov (United States)

    Volpe, Gualtiero; D'Ausilio, Alessandro; Badino, Leonardo; Camurri, Antonio; Fadiga, Luciano

    2016-05-05

    Music ensembles are an ideal test-bed for quantitative analysis of social interaction. Music is an inherently social activity, and music ensembles offer a broad variety of scenarios which are particularly suitable for investigation. Small ensembles, such as string quartets, are deemed a significant example of self-managed teams, where all musicians contribute equally to a task. In bigger ensembles, such as orchestras, the relationship between a leader (the conductor) and a group of followers (the musicians) clearly emerges. This paper presents an overview of recent research on social interaction in music ensembles with a particular focus on (i) studies from cognitive neuroscience; and (ii) studies adopting a computational approach for carrying out automatic quantitative analysis of ensemble music performances. © 2016 The Author(s).

  12. Statistical ensembles in quantum mechanics

    International Nuclear Information System (INIS)

    Blokhintsev, D.

    1976-01-01

    The interpretation of quantum mechanics presented in this paper is based on the concept of quantum ensembles. This concept differs essentially from the canonical one by that the interference of the observer into the state of a microscopic system is of no greater importance than in any other field of physics. Owing to this fact, the laws established by quantum mechanics are not of less objective character than the laws governing classical statistical mechanics. The paradoxical nature of some statements of quantum mechanics which result from the interpretation of the wave functions as the observer's notebook greatly stimulated the development of the idea presented. (Auth.)

  13. Wind Power Prediction using Ensembles

    DEFF Research Database (Denmark)

    Giebel, Gregor; Badger, Jake; Landberg, Lars

    2005-01-01

    offshore wind farm and the whole Jutland/Funen area. The utilities used these forecasts for maintenance planning, fuel consumption estimates and over-the-weekend trading on the Leipzig power exchange. Othernotable scientific results include the better accuracy of forecasts made up from a simple...... superposition of two NWP provider (in our case, DMI and DWD), an investigation of the merits of a parameterisation of the turbulent kinetic energy within thedelivered wind speed forecasts, and the finding that a “naïve” downscaling of each of the coarse ECMWF ensemble members with higher resolution HIRLAM did...

  14. Climate Change Impacts on the Upper Indus Hydrology: Sources, Shifts and Extremes

    NARCIS (Netherlands)

    Lutz, A.; Immerzeel, W.W.; Kraaijenbrink, P.D.A.; Shresta, A.B.; Bierkens, M.F.P.

    2016-01-01

    The Indus basin heavily depends on its upstream mountainous part for the downstream supply of water while downstream demands are high. Since downstream demands will likely continue to increase, accurate hydrological projections for the future supply are important. We use an ensemble of statistically

  15. EnsembleGASVR: A novel ensemble method for classifying missense single nucleotide polymorphisms

    KAUST Repository

    Rapakoulia, Trisevgeni; Theofilatos, Konstantinos A.; Kleftogiannis, Dimitrios A.; Likothanasis, Spiridon D.; Tsakalidis, Athanasios K.; Mavroudi, Seferina P.

    2014-01-01

    do not support their predictions with confidence scores. Results: To overcome these limitations, a novel ensemble computational methodology is proposed. EnsembleGASVR facilitates a twostep algorithm, which in its first step applies a novel

  16. Fundamentals of watershed hydrology

    Science.gov (United States)

    Pamela J. Edwards; Karl W.J. Williard; Jon E. Schoonover

    2015-01-01

    This is a primer about hydrology, the science of water. Watersheds are the basic land unit for water resource management and their delineation, importance, and variation are explained and illustrated. The hydrologic cycle and its components (precipitation, evaporation, transpiration, soil water, groundwater, and streamflow) which collectively provide a foundation for...

  17. Hands-On Hydrology

    Science.gov (United States)

    Mathews, Catherine E.; Monroe, Louise Nelson

    2004-01-01

    A professional school and university collaboration enables elementary students and their teachers to explore hydrology concepts and realize the beneficial functions of wetlands. Hands-on experiences involve young students in determining water quality at field sites after laying the groundwork with activities related to the hydrologic cycle,…

  18. Hydrologic Services Course.

    Science.gov (United States)

    National Oceanic and Atmospheric Administration (DOC), Rockville, MD. National Weather Service.

    A course to develop an understanding of the scope of water resource activities, of the need for forecasting, of the National Weather Service's role in hydrology, and of the proper procedures to follow in fulfilling this role is presented. The course is one of self-help, guided by correspondence. Nine lessons are included: (1) Hydrology in the…

  19. Arid Zone Hydrology

    Science.gov (United States)

    Arid zone hydrology encompasses a wide range of topics and hydro-meteorological and ecological characteristics. Although arid and semi-arid watersheds perform the same functions as those in humid environments, their hydrology and sediment transport characteristics cannot be readily predicted by inf...

  20. Multi-Model Ensemble Wake Vortex Prediction

    Science.gov (United States)

    Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

    2015-01-01

    Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

  1. Urban runoff forecasting with ensemble weather predictions

    DEFF Research Database (Denmark)

    Pedersen, Jonas Wied; Courdent, Vianney Augustin Thomas; Vezzaro, Luca

    This research shows how ensemble weather forecasts can be used to generate urban runoff forecasts up to 53 hours into the future. The results highlight systematic differences between ensemble members that needs to be accounted for when these forecasts are used in practice.......This research shows how ensemble weather forecasts can be used to generate urban runoff forecasts up to 53 hours into the future. The results highlight systematic differences between ensemble members that needs to be accounted for when these forecasts are used in practice....

  2. Using High-Resolution Data to Test Parameter Sensitivity of the Distributed Hydrological Model HydroGeoSphere

    Directory of Open Access Journals (Sweden)

    Thomas Cornelissen

    2016-05-01

    Full Text Available Parameterization of physically based and distributed hydrological models for mesoscale catchments remains challenging because the commonly available data base is insufficient for calibration. In this paper, we parameterize a mesoscale catchment for the distributed model HydroGeoSphere by transferring evapotranspiration parameters calibrated at a highly-equipped headwater catchment in addition to literature data. Based on this parameterization, the sensitivity of the mesoscale catchment to spatial variability in land use, potential evapotranspiration and precipitation and of the headwater catchment to mesoscale soil and land use data was conducted. Simulations of the mesoscale catchment with transferred parameters reproduced daily discharge dynamics and monthly evapotranspiration of grassland, deciduous and coniferous vegetation in a satisfactory manner. Precipitation was the most sensitive input data with respect to total runoff and peak flow rates, while simulated evapotranspiration components and patterns were most sensitive to spatially distributed land use parameterization. At the headwater catchment, coarse soil data resulted in a change in runoff generating processes based on the interplay between higher wetness prior to a rainfall event, enhanced groundwater level rise and accordingly, lower transpiration rates. Our results indicate that the direct transfer of parameters is a promising method to benefit highly equipped simulations of the headwater catchments.

  3. Development of Gridded Ensemble Precipitation and Temperature Datasets for the Contiguous United States Plus Hawai'i and Alaska

    Science.gov (United States)

    Newman, A. J.; Clark, M. P.; Nijssen, B.; Wood, A.; Gutmann, E. D.; Mizukami, N.; Longman, R. J.; Giambelluca, T. W.; Cherry, J.; Nowak, K.; Arnold, J.; Prein, A. F.

    2016-12-01

    Gridded precipitation and temperature products are inherently uncertain due to myriad factors. These include interpolation from a sparse observation network, measurement representativeness, and measurement errors. Despite this inherent uncertainty, uncertainty is typically not included, or is a specific addition to each dataset without much general applicability across different datasets. A lack of quantitative uncertainty estimates for hydrometeorological forcing fields limits their utility to support land surface and hydrologic modeling techniques such as data assimilation, probabilistic forecasting and verification. To address this gap, we have developed a first of its kind gridded, observation-based ensemble of precipitation and temperature at a daily increment for the period 1980-2012 over the United States (including Alaska and Hawaii). A longer, higher resolution version (1970-present, 1/16th degree) has also been implemented to support real-time hydrologic- monitoring and prediction in several regional US domains. We will present the development and evaluation of the dataset, along with initial applications of the dataset for ensemble data assimilation and probabilistic evaluation of high resolution regional climate model simulations. We will also present results on the new high resolution products for Alaska and Hawaii (2 km and 250 m respectively), to complete the first ensemble observation based product suite for the entire 50 states. Finally, we will present plans to improve the ensemble dataset, focusing on efforts to improve the methods used for station interpolation and ensemble generation, as well as methods to fuse station data with numerical weather prediction model output.

  4. Hydrological and meteorological aspects of floods in the Alps: an overview

    Directory of Open Access Journals (Sweden)

    Baldassare Bacchi

    2003-01-01

    Full Text Available This introductory paper presents and summarises recent research on meteorological and hydrological aspects of floods in the Alps. The research activities were part of the international research project RAPHAEL (Runoff and Atmospheric Processes for flood HAzard forEcasting and controL together with experiments within the Special Observing Period-SOP conducted in autumn 1999 for the Mesoscale Alpine Programme —MAP. The investigations were based on both field experiments and numerical simulations, using meteorological and hydrological models, of ten major floods that occurred in the past decade in the European Alps. The two basins investigated were the Ticino (6599 km2 at the Lago Maggiore outlet on the southern side of the Alps and the Ammer catchment (709 km2 in the Bavarian Alps. These catchments and their sub-catchments cover an appropriate range of spatial scales with which to investigate and test in an operational context the potential of both mesoscale meteorological and distributed hydrological models for flood forecasting. From the data analyses and model simulations described in this Special Issue, the major sources of uncertainties for flood forecasts in mid-size mountain basins are outlined and the accuracy flood forecasts is assessed. Keywords: floods, mountain hydrology, meteorological models, Alps

  5. Joys of Community Ensemble Playing: The Case of the Happy Roll Elastic Ensemble in Taiwan

    Science.gov (United States)

    Hsieh, Yuan-Mei; Kao, Kai-Chi

    2012-01-01

    The Happy Roll Elastic Ensemble (HREE) is a community music ensemble supported by Tainan Culture Centre in Taiwan. With enjoyment and friendship as its primary goals, it aims to facilitate the joys of ensemble playing and the spirit of social networking. This article highlights the key aspects of HREE's development in its first two years…

  6. Study of the air-sea interactions at the mesoscale: the SEMAPHORE experiment

    Directory of Open Access Journals (Sweden)

    L. Eymard

    1996-09-01

    Full Text Available The SEMAPHORE (Structure des Echanges Mer-Atmosphère, Propriétés des Hétérogénéités Océaniques: Recherche Expérimentale experiment has been conducted from June to November 1993 in the Northeast Atlantic between the Azores and Madeira. It was centered on the study of the mesoscale ocean circulation and air-sea interactions. The experimental investigation was achieved at the mesoscale using moorings, floats, and ship hydrological survey, and at a smaller scale by one dedicated ship, two instrumented aircraft, and surface drifting buoys, for one and a half month in October-November (IOP: intense observing period. Observations from meteorological operational satellites as well as spaceborne microwave sensors were used in complement. The main studies undertaken concern the mesoscale ocean, the upper ocean, the atmospheric boundary layer, and the sea surface, and first results are presented for the various topics. From data analysis and model simulations, the main characteristics of the ocean circulation were deduced, showing the close relationship between the Azores front meander and the occurrence of Mediterranean water lenses (meddies, and the shift between the Azores current frontal signature at the surface and within the thermocline. Using drifting buoys and ship data in the upper ocean, the gap between the scales of the atmospheric forcing and the oceanic variability was made evident. A 2 °C decrease and a 40-m deepening of the mixed layer were measured within the IOP, associated with a heating loss of about 100 W m-2. This evolution was shown to be strongly connected to the occurrence of storms at the beginning and the end of October. Above the surface, turbulent measurements from ship and aircraft were analyzed across the surface thermal front, showing a 30% difference in heat fluxes between both sides during a 4-day period, and the respective contributions of the wind and the surface temperature were evaluated. The classical

  7. Study of the air-sea interactions at the mesoscale: the SEMAPHORE experiment

    Science.gov (United States)

    Eymard, L.; Planton, S.; Durand, P.; Le Visage, C.; Le Traon, P. Y.; Prieur, L.; Weill, A.; Hauser, D.; Rolland, J.; Pelon, J.; Baudin, F.; Bénech, B.; Brenguier, J. L.; Caniaux, G.; de Mey, P.; Dombrowski, E.; Druilhet, A.; Dupuis, H.; Ferret, B.; Flamant, C.; Flamant, P.; Hernandez, F.; Jourdan, D.; Katsaros, K.; Lambert, D.; Lefèvre, J. M.; Le Borgne, P.; Le Squere, B.; Marsoin, A.; Roquet, H.; Tournadre, J.; Trouillet, V.; Tychensky, A.; Zakardjian, B.

    1996-09-01

    The SEMAPHORE (Structure des Echanges Mer-Atmosphère, Propriétés des Hétérogénéités Océaniques: Recherche Expérimentale) experiment has been conducted from June to November 1993 in the Northeast Atlantic between the Azores and Madeira. It was centered on the study of the mesoscale ocean circulation and air-sea interactions. The experimental investigation was achieved at the mesoscale using moorings, floats, and ship hydrological survey, and at a smaller scale by one dedicated ship, two instrumented aircraft, and surface drifting buoys, for one and a half month in October-November (IOP: intense observing period). Observations from meteorological operational satellites as well as spaceborne microwave sensors were used in complement. The main studies undertaken concern the mesoscale ocean, the upper ocean, the atmospheric boundary layer, and the sea surface, and first results are presented for the various topics. From data analysis and model simulations, the main characteristics of the ocean circulation were deduced, showing the close relationship between the Azores front meander and the occurrence of Mediterranean water lenses (meddies), and the shift between the Azores current frontal signature at the surface and within the thermocline. Using drifting buoys and ship data in the upper ocean, the gap between the scales of the atmospheric forcing and the oceanic variability was made evident. A 2 °C decrease and a 40-m deepening of the mixed layer were measured within the IOP, associated with a heating loss of about 100 W m-2. This evolution was shown to be strongly connected to the occurrence of storms at the beginning and the end of October. Above the surface, turbulent measurements from ship and aircraft were analyzed across the surface thermal front, showing a 30% difference in heat fluxes between both sides during a 4-day period, and the respective contributions of the wind and the surface temperature were evaluated. The classical momentum flux bulk

  8. Study of the air-sea interactions at the mesoscale: the SEMAPHORE experiment

    Directory of Open Access Journals (Sweden)

    L. Eymard

    Full Text Available The SEMAPHORE (Structure des Echanges Mer-Atmosphère, Propriétés des Hétérogénéités Océaniques: Recherche Expérimentale experiment has been conducted from June to November 1993 in the Northeast Atlantic between the Azores and Madeira. It was centered on the study of the mesoscale ocean circulation and air-sea interactions. The experimental investigation was achieved at the mesoscale using moorings, floats, and ship hydrological survey, and at a smaller scale by one dedicated ship, two instrumented aircraft, and surface drifting buoys, for one and a half month in October-November (IOP: intense observing period. Observations from meteorological operational satellites as well as spaceborne microwave sensors were used in complement. The main studies undertaken concern the mesoscale ocean, the upper ocean, the atmospheric boundary layer, and the sea surface, and first results are presented for the various topics. From data analysis and model simulations, the main characteristics of the ocean circulation were deduced, showing the close relationship between the Azores front meander and the occurrence of Mediterranean water lenses (meddies, and the shift between the Azores current frontal signature at the surface and within the thermocline. Using drifting buoys and ship data in the upper ocean, the gap between the scales of the atmospheric forcing and the oceanic variability was made evident. A 2 °C decrease and a 40-m deepening of the mixed layer were measured within the IOP, associated with a heating loss of about 100 W m-2. This evolution was shown to be strongly connected to the occurrence of storms at the beginning and the end of October. Above the surface, turbulent measurements from ship and aircraft were analyzed across the surface thermal front, showing a 30% difference in heat fluxes between both sides during a 4-day period, and the respective contributions of the wind and the surface temperature were evaluated. The

  9. Towards an Australian ensemble streamflow forecasting system for flood prediction and water management

    Science.gov (United States)

    Bennett, J.; David, R. E.; Wang, Q.; Li, M.; Shrestha, D. L.

    2016-12-01

    Flood forecasting in Australia has historically relied on deterministic forecasting models run only when floods are imminent, with considerable forecaster input and interpretation. These now co-existed with a continually available 7-day streamflow forecasting service (also deterministic) aimed at operational water management applications such as environmental flow releases. The 7-day service is not optimised for flood prediction. We describe progress on developing a system for ensemble streamflow forecasting that is suitable for both flood prediction and water management applications. Precipitation uncertainty is handled through post-processing of Numerical Weather Prediction (NWP) output with a Bayesian rainfall post-processor (RPP). The RPP corrects biases, downscales NWP output, and produces reliable ensemble spread. Ensemble precipitation forecasts are used to force a semi-distributed conceptual rainfall-runoff model. Uncertainty in precipitation forecasts is insufficient to reliably describe streamflow forecast uncertainty, particularly at shorter lead-times. We characterise hydrological prediction uncertainty separately with a 4-stage error model. The error model relies on data transformation to ensure residuals are homoscedastic and symmetrically distributed. To ensure streamflow forecasts are accurate and reliable, the residuals are modelled using a mixture-Gaussian distribution with distinct parameters for the rising and falling limbs of the forecast hydrograph. In a case study of the Murray River in south-eastern Australia, we show ensemble predictions of floods generally have lower errors than deterministic forecasting methods. We also discuss some of the challenges in operationalising short-term ensemble streamflow forecasts in Australia, including meeting the needs for accurate predictions across all flow ranges and comparing forecasts generated by event and continuous hydrological models.

  10. The HIRLAM fast radiation scheme for mesoscale numerical weather prediction models

    Science.gov (United States)

    Rontu, Laura; Gleeson, Emily; Räisänen, Petri; Pagh Nielsen, Kristian; Savijärvi, Hannu; Hansen Sass, Bent

    2017-07-01

    This paper provides an overview of the HLRADIA shortwave (SW) and longwave (LW) broadband radiation schemes used in the HIRLAM numerical weather prediction (NWP) model and available in the HARMONIE-AROME mesoscale NWP model. The advantage of broadband, over spectral, schemes is that they can be called more frequently within the model, without compromising on computational efficiency. In mesoscale models fast interactions between clouds and radiation and the surface and radiation can be of greater importance than accounting for the spectral details of clear-sky radiation; thus calling the routines more frequently can be of greater benefit than the deterioration due to loss of spectral details. Fast but physically based radiation parametrizations are expected to be valuable for high-resolution ensemble forecasting, because as well as the speed of their execution, they may provide realistic physical perturbations. Results from single-column diagnostic experiments based on CIRC benchmark cases and an evaluation of 10 years of radiation output from the FMI operational archive of HIRLAM forecasts indicate that HLRADIA performs sufficiently well with respect to the clear-sky downwelling SW and longwave LW fluxes at the surface. In general, HLRADIA tends to overestimate surface fluxes, with the exception of LW fluxes under cold and dry conditions. The most obvious overestimation of the surface SW flux was seen in the cloudy cases in the 10-year comparison; this bias may be related to using a cloud inhomogeneity correction, which was too large. According to the CIRC comparisons, the outgoing LW and SW fluxes at the top of atmosphere are mostly overestimated by HLRADIA and the net LW flux is underestimated above clouds. The absorption of SW radiation by the atmosphere seems to be underestimated and LW absorption seems to be overestimated. Despite these issues, the overall results are satisfying and work on the improvement of HLRADIA for the use in HARMONIE-AROME NWP system

  11. Popular Music and the Instrumental Ensemble.

    Science.gov (United States)

    Boespflug, George

    1999-01-01

    Discusses popular music, the role of the musical performer as a creator, and the styles of jazz and popular music. Describes the pop ensemble at the college level, focusing on improvisation, rehearsals, recording, and performance. Argues that pop ensembles be used in junior and senior high school. (CMK)

  12. Layered Ensemble Architecture for Time Series Forecasting.

    Science.gov (United States)

    Rahman, Md Mustafizur; Islam, Md Monirul; Murase, Kazuyuki; Yao, Xin

    2016-01-01

    Time series forecasting (TSF) has been widely used in many application areas such as science, engineering, and finance. The phenomena generating time series are usually unknown and information available for forecasting is only limited to the past values of the series. It is, therefore, necessary to use an appropriate number of past values, termed lag, for forecasting. This paper proposes a layered ensemble architecture (LEA) for TSF problems. Our LEA consists of two layers, each of which uses an ensemble of multilayer perceptron (MLP) networks. While the first ensemble layer tries to find an appropriate lag, the second ensemble layer employs the obtained lag for forecasting. Unlike most previous work on TSF, the proposed architecture considers both accuracy and diversity of the individual networks in constructing an ensemble. LEA trains different networks in the ensemble by using different training sets with an aim of maintaining diversity among the networks. However, it uses the appropriate lag and combines the best trained networks to construct the ensemble. This indicates LEAs emphasis on accuracy of the networks. The proposed architecture has been tested extensively on time series data of neural network (NN)3 and NN5 competitions. It has also been tested on several standard benchmark time series data. In terms of forecasting accuracy, our experimental results have revealed clearly that LEA is better than other ensemble and nonensemble methods.

  13. Ensemble methods for seasonal limited area forecasts

    DEFF Research Database (Denmark)

    Arritt, Raymond W.; Anderson, Christopher J.; Takle, Eugene S.

    2004-01-01

    The ensemble prediction methods used for seasonal limited area forecasts were examined by comparing methods for generating ensemble simulations of seasonal precipitation. The summer 1993 model over the north-central US was used as a test case. The four methods examined included the lagged-average...

  14. Toward Improving Short-Range Fog Prediction in Data-Denied Areas Using the Air Force Weather Agency Mesoscale Ensemble

    Science.gov (United States)

    2012-09-01

    hre - del’k:it( K) vitual t~ hre del’k:I:(K) all sl:e-s, a ll rnerrbers (exc l 1 S...2 01 vitual t~ hre del’k:l(K) vitual t~ hre del’k:l(K) all sit~s. atl~(e-xcl1 S& 17) all sit~s. atl~(e-xcl 1 S& 17) vitual t~ hre del’k:l(K) vitual...t~ hre del’k:l(K) all sit~s. a tl~(e-xcl1 S& 17) all sit~s. atl~(e-xcl 1 S& 17) vitual t~ hre del’k:l(K) vitual t~ hre del’k:l(K) 166

  15. Nuclear techniques in hydrology

    International Nuclear Information System (INIS)

    Moser, H.

    1976-01-01

    The nuclear techniques used in hydrology are usually tracer techniques based on the use of nuclides either intentionally introduced into, or naturally present in the water. The low concentrations of these nuclides, which must be detected in groundwater and surface water, require special measurement techniques for the concentrations of radioactive or of stable nuclides. The nuclear techniques can be used most fruitfully in conjunction with conventional methods for the solution of problems in the areas of hydrology, hydrogeology and glacier hydrology. Nuclear techniques are used in practice in the areas of prospecting for water, environment protection and engineering hydrogeology. (orig.) [de

  16. Topological quantization of ensemble averages

    International Nuclear Information System (INIS)

    Prodan, Emil

    2009-01-01

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

  17. Characterizing Ensembles of Superconducting Qubits

    Science.gov (United States)

    Sears, Adam; Birenbaum, Jeff; Hover, David; Rosenberg, Danna; Weber, Steven; Yoder, Jonilyn L.; Kerman, Jamie; Gustavsson, Simon; Kamal, Archana; Yan, Fei; Oliver, William

    We investigate ensembles of up to 48 superconducting qubits embedded within a superconducting cavity. Such arrays of qubits have been proposed for the experimental study of Ising Hamiltonians, and efficient methods to characterize and calibrate these types of systems are still under development. Here we leverage high qubit coherence (> 70 μs) to characterize individual devices as well as qubit-qubit interactions, utilizing the common resonator mode for a joint readout. This research was funded by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA) under Air Force Contract No. FA8721-05-C-0002. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of ODNI, IARPA, or the US Government.

  18. Long-range hydrometeorological ensemble predictions of drought parameters

    Science.gov (United States)

    Fundel, F.; Jörg-Hess, S.; Zappa, M.

    2012-06-01

    Low streamflow as consequence of a drought event affects numerous aspects of life. Economic sectors that may be impacted by drought are, e.g. power production, agriculture, tourism and water quality management. Numerical models have increasingly been used to forecast low-flow and have become the focus of recent research. Here, we consider daily ensemble runoff forecasts for the river Thur, which has its source in the Swiss Alps. We focus on the low-flow indices duration, severity and magnitude, with a forecast lead-time of one month, to assess their potential usefulness for predictions. The ECMWF VarEPS 5 member reforecast, which covers 18 yr, is used as forcing for the hydrological model PREVAH. A thorough verification shows that, compared to peak flow, probabilistic low-flow forecasts are skillful for longer lead-times, low-flow index forecasts could also be beneficially included in a decision-making process. The results suggest monthly runoff forecasts are useful for accessing the risk of hydrological droughts.

  19. Micro- and meso-scale effects of forested terrain

    DEFF Research Database (Denmark)

    Dellwik, Ebba; Mann, Jakob; Sogachev, Andrey

    2011-01-01

    scales are the height of the planetary boundary layer and the Monin-Obukhov length, which both are related to the energy balance of the surface. Examples of important micro- and meso-scale effects of forested terrain are shown using data and model results from recent and ongoing experiments. For micro......The height and rotor diameter of modern wind turbines are so extensive, that the wind conditions they encounter often are well above the surface layer, where traditionally it is assumed that wind direction and turbulent fluxes are constant with respect to height, if the surface is homogenous....... Deviations from the requirement of homogeneity are often the focus of micro-scale studies in forested areas. Yet, to explain the wind climate in the relevant height range for turbines, it is necessary to also account for the length scales that are important parameters for the meso-scale flow. These length...

  20. Spectral structure of mesoscale winds over the water

    DEFF Research Database (Denmark)

    Larsén, Xiaoli Guo; Vincent, Claire Louise; Larsen, Søren Ejling

    2013-01-01

    to describe the spectral slope transition as well as the limit for application of the Taylor hypothesis. The stability parameter calculated from point measurements, the bulk Richardson number, is found insufficient to represent the various atmospheric structures that have their own spectral behaviours under...... spectra show universal characteristics, in agreement with the findings in literature, including the energy amplitude and the −5/3 spectral slope in the mesoscale range transitioning to a slope of −3 for synoptic and planetary scales. The integral time-scale of the local weather is found to be useful...... different stability conditions, such as open cells and gravity waves. For stationary conditions, the mesoscale turbulence is found to bear some characteristics of two-dimensional isotropy, including (1) very minor vertical variation of spectra; (2) similar spectral behaviour for the along- and across...

  1. Assessment of MARMOT. A Mesoscale Fuel Performance Code

    Energy Technology Data Exchange (ETDEWEB)

    Tonks, M. R. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Schwen, D. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zhang, Y. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Chakraborty, P. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Bai, X. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Fromm, B. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Yu, J. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Teague, M. C. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Andersson, D. A. [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-04-01

    MARMOT is the mesoscale fuel performance code under development as part of the US DOE Nuclear Energy Advanced Modeling and Simulation Program. In this report, we provide a high level summary of MARMOT, its capabilities, and its current state of validation. The purpose of MARMOT is to predict the coevolution of microstructure and material properties of nuclear fuel and cladding. It accomplished this using the phase field method coupled to solid mechanics and heat conduction. MARMOT is based on the Multiphysics Object-Oriented Simulation Environment (MOOSE), and much of its basic capability in the areas of the phase field method, mechanics, and heat conduction come directly from MOOSE modules. However, additional capability specific to fuel and cladding is available in MARMOT. While some validation of MARMOT has been completed in the areas of fission gas behavior and grain growth, much more validation needs to be conducted. However, new mesoscale data needs to be obtained in order to complete this validation.

  2. Mesoscale modeling: solving complex flows in biology and biotechnology.

    Science.gov (United States)

    Mills, Zachary Grant; Mao, Wenbin; Alexeev, Alexander

    2013-07-01

    Fluids are involved in practically all physiological activities of living organisms. However, biological and biorelated flows are hard to analyze due to the inherent combination of interdependent effects and processes that occur on a multitude of spatial and temporal scales. Recent advances in mesoscale simulations enable researchers to tackle problems that are central for the understanding of such flows. Furthermore, computational modeling effectively facilitates the development of novel therapeutic approaches. Among other methods, dissipative particle dynamics and the lattice Boltzmann method have become increasingly popular during recent years due to their ability to solve a large variety of problems. In this review, we discuss recent applications of these mesoscale methods to several fluid-related problems in medicine, bioengineering, and biotechnology. Copyright © 2013 Elsevier Ltd. All rights reserved.

  3. Allegheny County Hydrology Areas

    Data.gov (United States)

    Allegheny County / City of Pittsburgh / Western PA Regional Data Center — The Hydrology Feature Dataset contains photogrammetrically compiled water drainage features and structures including rivers, streams, drainage canals, locks, dams,...

  4. PNW Hydrologic Landscape Class

    Data.gov (United States)

    U.S. Environmental Protection Agency — Work has been done to expand the hydrologic landscapes (HLs) concept and to develop an approach for using it to address streamflow vulnerability from climate change....

  5. Hydrologic Engineering Center

    Data.gov (United States)

    Federal Laboratory Consortium — The Hydrologic Engineering Center (HEC), an organization within the Institute for Water Resources, is the designated Center of Expertise for the U.S. Army Corps of...

  6. Allegheny County Hydrology Lines

    Data.gov (United States)

    Allegheny County / City of Pittsburgh / Western PA Regional Data Center — The Hydrology Feature Dataset contains photogrammetrically compiled water drainage features and structures including rivers, streams, drainage canals, locks, dams,...

  7. Hydrologic Areas of Concern

    Data.gov (United States)

    University of New Hampshire — A Hydrologic Area of Concern (HAC) is a land area surrounding a water source, which is intended to include the portion of the watershed in which land uses are likely...

  8. Parameterization of phase change of water in a mesoscale model

    Energy Technology Data Exchange (ETDEWEB)

    Levkov, L; Eppel, D; Grassl, H

    1987-01-01

    A parameterization scheme of phase change of water is suggested to be used in the 3-D numerical nonhydrostatic model GESIMA. The microphysical formulation follows the so-called bulk technique. With this procedure the net production rates in the balance equations for water and potential temperature are given both for liquid and ice-phase. Convectively stable as well as convectively unstable mesoscale systems are considered. With 2 figs..

  9. Maps of mesoscale wind variability over the North Sea region

    DEFF Research Database (Denmark)

    Vincent, Claire Louise; Hahmann, Andrea N.; Badger, Jake

    Mesoscale wind fluctuations affect the operation of wind farms, particularly as the number of geographically concentrated wind farms in the North Sea increases (Akhmatov et al. 2007). The frequency and intensity of wind fluctuations could be considered as a new siting criterion, together with exi...... for a 1 year period. The model was run with a horizontal grid spacing of 2 km. The variability maps are created by integrating the average 24 hour spectra at every grid point over different time-scales....

  10. Mesoscale modeling of metal-loaded high explosives

    Energy Technology Data Exchange (ETDEWEB)

    Bdzil, John Bohdan [Los Alamos National Laboratory; Lieberthal, Brandon [UNIV OF ILLINOIS; Srewart, Donald S [UNIV OF ILLINOIS

    2010-01-01

    We describe a 3D approach to modeling multi-phase blast explosive, which is primarily condensed explosive by volume with inert embedded particles. These embedded particles are uniform in size and placed on the array of a regular lattice. The asymptotic theory of detonation shock dynamics governs the detonation shock propagation in the explosive. Mesoscale hydrodynamic simulations are used to show how the particles are compressed, deformed, and accelerated by the high-speed detonation products flow.

  11. Mesoscale Frontogenesis: An Analysis of Two Cold Front Case Studies

    Science.gov (United States)

    1993-01-01

    marked the boundary of warm air or the "warm sector". Further development of this cyclone model by Bjerknes and Solberg (1922) and Bergeron (1928) provided...represent 25 mn s -1 Relative humidity of greater than 80% indicated by the shaded region in gray. Frontal zones marked with solid black lines. 24 two... Zuckerberg , J.T. Schaefer, and G.E. Rasch, 1986: Forecast problems: The meteorological and operational factors, In: Mesoscale Meteorology and Forecasting

  12. Explicit simulation of a midlatitude Mesoscale Convective System

    Energy Technology Data Exchange (ETDEWEB)

    Alexander, G.D.; Cotton, W.R. [Colorado State Univ., Fort Collins, CO (United States)

    1996-04-01

    We have explicitly simulated the mesoscale convective system (MCS) observed on 23-24 June 1985 during PRE-STORM, the Preliminary Regional Experiment for the Stormscale Operational and Research and Meterology Program. Stensrud and Maddox (1988), Johnson and Bartels (1992), and Bernstein and Johnson (1994) are among the researchers who have investigated various aspects of this MCS event. We have performed this MCS simulation (and a similar one of a tropical MCS; Alexander and Cotton 1994) in the spirit of the Global Energy and Water Cycle Experiment Cloud Systems Study (GCSS), in which cloud-resolving models are used to assist in the formulation and testing of cloud parameterization schemes for larger-scale models. In this paper, we describe (1) the nature of our 23-24 June MCS dimulation and (2) our efforts to date in using our explicit MCS simulations to assist in the development of a GCM parameterization for mesoscale flow branches. The paper is organized as follows. First, we discuss the synoptic situation surrounding the 23-24 June PRE-STORM MCS followed by a discussion of the model setup and results of our simulation. We then discuss the use of our MCS simulation. We then discuss the use of our MCS simulations in developing a GCM parameterization for mesoscale flow branches and summarize our results.

  13. Mesoscale cyclogenesis over the western north Pacific Ocean during TPARC

    Directory of Open Access Journals (Sweden)

    Christopher A. Davis

    2013-01-01

    Full Text Available Three cases of mesoscale marine cyclogenesis over the subtropics of the Western Pacific Ocean are investigated. Each case occurred during the THORPEX Pacific Asia Regional Campaign and Tropical Cyclone Structure (TCS-08 field phases in 2008. Each cyclone developed from remnants of disturbances that earlier showed potential for tropical cyclogenesis within the tropics. Two of the cyclones produced gale-force surface winds, and one, designated as a tropical cyclone, resulted in a significant coastal storm over eastern Japan. Development was initiated by a burst of organized mesoscale convection that consolidated and intensified the surface cyclonic circulation over a period of 12–24 h. Upper-tropospheric potential vorticity anomalies modulated the vertical wind shear that, in turn, influenced the periods of cyclone intensification and weakening. Weak baroclinicity associated with vertical shear was also deemed important in organizing mesoscale ascent and the convection outbreaks. The remnant tropical disturbances contributed exceptional water vapour content to higher latitudes that led to strong diabatic heating, and the tropical remnants contributed vorticity that was the seed of the development in the subtropics. Predictability of these events more than three days in advance appears to be minimal.

  14. Examining Chaotic Convection with Super-Parameterization Ensembles

    Science.gov (United States)

    Jones, Todd R.

    This study investigates a variety of features present in a new configuration of the Community Atmosphere Model (CAM) variant, SP-CAM 2.0. The new configuration (multiple-parameterization-CAM, MP-CAM) changes the manner in which the super-parameterization (SP) concept represents physical tendency feedbacks to the large-scale by using the mean of 10 independent two-dimensional cloud-permitting model (CPM) curtains in each global model column instead of the conventional single CPM curtain. The climates of the SP and MP configurations are examined to investigate any significant differences caused by the application of convective physical tendencies that are more deterministic in nature, paying particular attention to extreme precipitation events and large-scale weather systems, such as the Madden-Julian Oscillation (MJO). A number of small but significant changes in the mean state climate are uncovered, and it is found that the new formulation degrades MJO performance. Despite these deficiencies, the ensemble of possible realizations of convective states in the MP configuration allows for analysis of uncertainty in the small-scale solution, lending to examination of those weather regimes and physical mechanisms associated with strong, chaotic convection. Methods of quantifying precipitation predictability are explored, and use of the most reliable of these leads to the conclusion that poor precipitation predictability is most directly related to the proximity of the global climate model column state to atmospheric critical points. Secondarily, the predictability is tied to the availability of potential convective energy, the presence of mesoscale convective organization on the CPM grid, and the directive power of the large-scale.

  15. MSEBAG: a dynamic classifier ensemble generation based on `minimum-sufficient ensemble' and bagging

    Science.gov (United States)

    Chen, Lei; Kamel, Mohamed S.

    2016-01-01

    In this paper, we propose a dynamic classifier system, MSEBAG, which is characterised by searching for the 'minimum-sufficient ensemble' and bagging at the ensemble level. It adopts an 'over-generation and selection' strategy and aims to achieve a good bias-variance trade-off. In the training phase, MSEBAG first searches for the 'minimum-sufficient ensemble', which maximises the in-sample fitness with the minimal number of base classifiers. Then, starting from the 'minimum-sufficient ensemble', a backward stepwise algorithm is employed to generate a collection of ensembles. The objective is to create a collection of ensembles with a descending fitness on the data, as well as a descending complexity in the structure. MSEBAG dynamically selects the ensembles from the collection for the decision aggregation. The extended adaptive aggregation (EAA) approach, a bagging-style algorithm performed at the ensemble level, is employed for this task. EAA searches for the competent ensembles using a score function, which takes into consideration both the in-sample fitness and the confidence of the statistical inference, and averages the decisions of the selected ensembles to label the test pattern. The experimental results show that the proposed MSEBAG outperforms the benchmarks on average.

  16. Contribution of mesoscale eddies to Black Sea ventilation

    Science.gov (United States)

    Capet, Arthur; Mason, Evan; Pascual, Ananda; Grégoire, Marilaure

    2017-04-01

    The shoaling of the Black Sea oxycline is one of the most urgent environmental issues in the Black Sea. The permanent oxycline derives directly from the Black Sea permanent stratification and has shoaled alarmingly in the last decades, due to a shifting balance between oxygen consumption and ventilation processes (Capet et al. 2016). The understanding of this balance is thus of the utmost importance and requires to quantify 1) the export of nutrients and organic materials from the shelf regions to the open sea and 2) the ventilation processes. These two processes being influenced by mesoscale features, it is critical to understand the role of the semi-permanent mesoscale structures in horizontal (center/periphery) and vertical (diapycnal and isopycnal) exchanges. A useful insight can be obtained by merging observations from satellite altimeter and in situ profilers (ARGO). In such composite analyses, eddies are first automatically identified and tracked from altimeter data (Mason et al. 2014, py-eddy-tracker). Vertical ARGO profiles are then expressed in terms of their position relative to eddy centers and radii. Derived statistics indicate how consistently mesoscale eddies alter the vertical structure, and provide a deeper understanding of the associated horizontal and vertical fluxes. However, this data-based approach is limited in the Black Sea due to the lower quality of gridded altimetric products in the vicinity of the coast, where semi-permanent mesoscale structures prevail. To complement the difficult analysis of this sparse dataset, a compositing methodology. is also applied to model outputs from the 5km GHER-BHAMBI Black Sea implementation (CMEMS BS-MFC). Characteristic biogeochemical anomalies associated with eddies in the model are analyzed per se, and compared to the observation-based analysis. Capet, A., Stanev, E. V., Beckers, J.-M., Murray, J. W., and Grégoire, M.: Decline of the Black Sea oxygen inventory, Biogeosciences, 13, 1287-1297, doi:10

  17. Spatially explicit simulation of peatland hydrology and carbon dioxide exchange

    International Nuclear Information System (INIS)

    Sonnentag, O.

    2008-01-01

    A recent version of the Boreal Ecosystem Productivity Simulator (BEPS) was extended and modified to include northern peatlands. This thesis evaluated the BEPS-TerrainLab using observations made at the Mer Bleue bog located near Ottawa, Ontario, and the Sandhill fen located near Prince Albert, Saskatchewan. The code was revised to represent the multi-layer canopy and processes related to energy, water vapour and carbon dioxide fluxes through remotely-sensed leaf area index (LAI) maps. A quick and reliable method was also developed to determine shrub LAI with the LAI-2000 plant canopy analyzer. A large number of LAI data was collected at the Mer Bleue bog for the development of a new remote sensing-based methodology using multiple end member spectral unmixing to allow for separate tree and shrub LAI mapping in ombrotrophic peatlands. The methodology was also adapted for use in minerotrophic peatlands and their surrounding landscapes. These LAI maps within the BEPS-TerrainLab represented the tree and shrub layers of the Mer Bleue bog and the tree and shrub/sedge layers of the Sandhill fen. The study examined the influence of mesoscale topography (Mer Bleue bog) and macro- and mesoscale topography (Sandhill fen) on wetness, evapotranspiration, and gross primary productivity during the snow-free period of 2004. The results suggested that a peatland type-specific differentiation of macro- and mesoscale topographic effects on hydrology should be included in future peatland ecosystem modelling efforts in order to allow for a more realistic simulation of the soil water balance in peatlands and to reduce uncertainties in carbon dioxide and methane annual fluxes from wetlands

  18. Spatially explicit simulation of peatland hydrology and carbon dioxide exchange

    Energy Technology Data Exchange (ETDEWEB)

    Sonnentag, O.

    2008-08-01

    A recent version of the Boreal Ecosystem Productivity Simulator (BEPS) was extended and modified to include northern peatlands. This thesis evaluated the BEPS-TerrainLab using observations made at the Mer Bleue bog located near Ottawa, Ontario, and the Sandhill fen located near Prince Albert, Saskatchewan. The code was revised to represent the multi-layer canopy and processes related to energy, water vapour and carbon dioxide fluxes through remotely-sensed leaf area index (LAI) maps. A quick and reliable method was also developed to determine shrub LAI with the LAI-2000 plant canopy analyzer. A large number of LAI data was collected at the Mer Bleue bog for the development of a new remote sensing-based methodology using multiple end member spectral unmixing to allow for separate tree and shrub LAI mapping in ombrotrophic peatlands. The methodology was also adapted for use in minerotrophic peatlands and their surrounding landscapes. These LAI maps within the BEPS-TerrainLab represented the tree and shrub layers of the Mer Bleue bog and the tree and shrub/sedge layers of the Sandhill fen. The study examined the influence of mesoscale topography (Mer Bleue bog) and macro- and mesoscale topography (Sandhill fen) on wetness, evapotranspiration, and gross primary productivity during the snow-free period of 2004. The results suggested that a peatland type-specific differentiation of macro- and mesoscale topographic effects on hydrology should be included in future peatland ecosystem modelling efforts in order to allow for a more realistic simulation of the soil water balance in peatlands and to reduce uncertainties in carbon dioxide and methane annual fluxes from wetlands.

  19. Hydro-economic assessment of hydrological forecasting systems

    Science.gov (United States)

    Boucher, M.-A.; Tremblay, D.; Delorme, L.; Perreault, L.; Anctil, F.

    2012-01-01

    SummaryAn increasing number of publications show that ensemble hydrological forecasts exhibit good performance when compared to observed streamflow. Many studies also conclude that ensemble forecasts lead to a better performance than deterministic ones. This investigation takes one step further by not only comparing ensemble and deterministic forecasts to observed values, but by employing the forecasts in a stochastic decision-making assistance tool for hydroelectricity production, during a flood event on the Gatineau River in Canada. This allows the comparison between different types of forecasts according to their value in terms of energy, spillage and storage in a reservoir. The motivation for this is to adopt the point of view of an end-user, here a hydroelectricity production society. We show that ensemble forecasts exhibit excellent performances when compared to observations and are also satisfying when involved in operation management for electricity production. Further improvement in terms of productivity can be reached through the use of a simple post-processing method.

  20. Analyzing the uncertainty of ensemble-based gridded observations in land surface simulations and drought assessment

    Science.gov (United States)

    Ahmadalipour, Ali; Moradkhani, Hamid

    2017-12-01

    Hydrologic modeling is one of the primary tools utilized for drought monitoring and drought early warning systems. Several sources of uncertainty in hydrologic modeling have been addressed in the literature. However, few studies have assessed the uncertainty of gridded observation datasets from a drought monitoring perspective. This study provides a hydrologic modeling oriented analysis of the gridded observation data uncertainties over the Pacific Northwest (PNW) and its implications on drought assessment. We utilized a recently developed 100-member ensemble-based observed forcing data to simulate hydrologic fluxes at 1/8° spatial resolution using Variable Infiltration Capacity (VIC) model, and compared the results with a deterministic observation. Meteorological and hydrological droughts are studied at multiple timescales over the basin, and seasonal long-term trends and variations of drought extent is investigated for each case. Results reveal large uncertainty of observed datasets at monthly timescale, with systematic differences for temperature records, mainly due to different lapse rates. The uncertainty eventuates in large disparities of drought characteristics. In general, an increasing trend is found for winter drought extent across the PNW. Furthermore, a ∼3% decrease per decade is detected for snow water equivalent (SWE) over the PNW, with the region being more susceptible to SWE variations of the northern Rockies than the western Cascades. The agricultural areas of southern Idaho demonstrate decreasing trend of natural soil moisture as a result of precipitation decline, which implies higher appeal for anthropogenic water storage and irrigation systems.

  1. Mesoscale variability in the Bransfield Strait region (Antarctica during Austral summer

    Directory of Open Access Journals (Sweden)

    M. A. García

    1994-08-01

    Full Text Available The Bransfield Strait is one the best-known areas of Antarctica's oceanic surroundings. In spite of this, the study of the mesoscale variability of its local circulation has been addressed only recently. This paper focuses on the mesoscale structure of local physical oceanographic conditions in the Bransfield Strait during the Austral summer as derived from the BIOANTAR 93 cruise and auxiliary remote sensing data. Moreover, data recovered from moored current meters allow identification of transient mesoscale phenomena.

  2. Creating ensembles of decision trees through sampling

    Science.gov (United States)

    Kamath, Chandrika; Cantu-Paz, Erick

    2005-08-30

    A system for decision tree ensembles that includes a module to read the data, a module to sort the data, a module to evaluate a potential split of the data according to some criterion using a random sample of the data, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method is based on statistical sampling techniques and includes the steps of reading the data; sorting the data; evaluating a potential split according to some criterion using a random sample of the data, splitting the data, and combining multiple decision trees in ensembles.

  3. Derivation of Mayer Series from Canonical Ensemble

    International Nuclear Information System (INIS)

    Wang Xian-Zhi

    2016-01-01

    Mayer derived the Mayer series from both the canonical ensemble and the grand canonical ensemble by use of the cluster expansion method. In 2002, we conjectured a recursion formula of the canonical partition function of a fluid (X.Z. Wang, Phys. Rev. E 66 (2002) 056102). In this paper we give a proof for this formula by developing an appropriate expansion of the integrand of the canonical partition function. We further derive the Mayer series solely from the canonical ensemble by use of this recursion formula. (paper)

  4. Derivation of Mayer Series from Canonical Ensemble

    Science.gov (United States)

    Wang, Xian-Zhi

    2016-02-01

    Mayer derived the Mayer series from both the canonical ensemble and the grand canonical ensemble by use of the cluster expansion method. In 2002, we conjectured a recursion formula of the canonical partition function of a fluid (X.Z. Wang, Phys. Rev. E 66 (2002) 056102). In this paper we give a proof for this formula by developing an appropriate expansion of the integrand of the canonical partition function. We further derive the Mayer series solely from the canonical ensemble by use of this recursion formula.

  5. eWaterCycle: A global operational hydrological forecasting model

    Science.gov (United States)

    van de Giesen, Nick; Bierkens, Marc; Donchyts, Gennadii; Drost, Niels; Hut, Rolf; Sutanudjaja, Edwin

    2015-04-01

    Development of an operational hyper-resolution hydrological global model is a central goal of the eWaterCycle project (www.ewatercycle.org). This operational model includes ensemble forecasts (14 days) to predict water related stress around the globe. Assimilation of near-real time satellite data is part of the intended product that will be launched at EGU 2015. The challenges come from several directions. First, there are challenges that are mainly computer science oriented but have direct practical hydrological implications. For example, we aim to make use as much as possible of existing standards and open-source software. For example, different parts of our system are coupled through the Basic Model Interface (BMI) developed in the framework of the Community Surface Dynamics Modeling System (CSDMS). The PCR-GLOBWB model, built by Utrecht University, is the basic hydrological model that is the engine of the eWaterCycle project. Re-engineering of parts of the software was needed for it to run efficiently in a High Performance Computing (HPC) environment, and to be able to interface using BMI, and run on multiple compute nodes in parallel. The final aim is to have a spatial resolution of 1km x 1km, which is currently 10 x 10km. This high resolution is computationally not too demanding but very memory intensive. The memory bottleneck becomes especially apparent for data assimilation, for which we use OpenDA. OpenDa allows for different data assimilation techniques without the need to build these from scratch. We have developed a BMI adaptor for OpenDA, allowing OpenDA to use any BMI compatible model. To circumvent memory shortages which would result from standard applications of the Ensemble Kalman Filter, we have developed a variant that does not need to keep all ensemble members in working memory. At EGU, we will present this variant and how it fits well in HPC environments. An important step in the eWaterCycle project was the coupling between the hydrological and

  6. A meteo-hydrological prediction system based on a multi-model approach for precipitation forecasting

    Directory of Open Access Journals (Sweden)

    S. Davolio

    2008-02-01

    Full Text Available The precipitation forecasted by a numerical weather prediction model, even at high resolution, suffers from errors which can be considerable at the scales of interest for hydrological purposes. In the present study, a fraction of the uncertainty related to meteorological prediction is taken into account by implementing a multi-model forecasting approach, aimed at providing multiple precipitation scenarios driving the same hydrological model. Therefore, the estimation of that uncertainty associated with the quantitative precipitation forecast (QPF, conveyed by the multi-model ensemble, can be exploited by the hydrological model, propagating the error into the hydrological forecast.

    The proposed meteo-hydrological forecasting system is implemented and tested in a real-time configuration for several episodes of intense precipitation affecting the Reno river basin, a medium-sized basin located in northern Italy (Apennines. These episodes are associated with flood events of different intensity and are representative of different meteorological configurations responsible for severe weather affecting northern Apennines.

    The simulation results show that the coupled system is promising in the prediction of discharge peaks (both in terms of amount and timing for warning purposes. The ensemble hydrological forecasts provide a range of possible flood scenarios that proved to be useful for the support of civil protection authorities in their decision.

  7. Evaluation of bias-correction methods for ensemble streamflow volume forecasts

    Directory of Open Access Journals (Sweden)

    T. Hashino

    2007-01-01

    Full Text Available Ensemble prediction systems are used operationally to make probabilistic streamflow forecasts for seasonal time scales. However, hydrological models used for ensemble streamflow prediction often have simulation biases that degrade forecast quality and limit the operational usefulness of the forecasts. This study evaluates three bias-correction methods for ensemble streamflow volume forecasts. All three adjust the ensemble traces using a transformation derived with simulated and observed flows from a historical simulation. The quality of probabilistic forecasts issued when using the three bias-correction methods is evaluated using a distributions-oriented verification approach. Comparisons are made of retrospective forecasts of monthly flow volumes for a north-central United States basin (Des Moines River, Iowa, issued sequentially for each month over a 48-year record. The results show that all three bias-correction methods significantly improve forecast quality by eliminating unconditional biases and enhancing the potential skill. Still, subtle differences in the attributes of the bias-corrected forecasts have important implications for their use in operational decision-making. Diagnostic verification distinguishes these attributes in a context meaningful for decision-making, providing criteria to choose among bias-correction methods with comparable skill.

  8. An adaptive Gaussian process-based iterative ensemble smoother for data assimilation

    Science.gov (United States)

    Ju, Lei; Zhang, Jiangjiang; Meng, Long; Wu, Laosheng; Zeng, Lingzao

    2018-05-01

    Accurate characterization of subsurface hydraulic conductivity is vital for modeling of subsurface flow and transport. The iterative ensemble smoother (IES) has been proposed to estimate the heterogeneous parameter field. As a Monte Carlo-based method, IES requires a relatively large ensemble size to guarantee its performance. To improve the computational efficiency, we propose an adaptive Gaussian process (GP)-based iterative ensemble smoother (GPIES) in this study. At each iteration, the GP surrogate is adaptively refined by adding a few new base points chosen from the updated parameter realizations. Then the sensitivity information between model parameters and measurements is calculated from a large number of realizations generated by the GP surrogate with virtually no computational cost. Since the original model evaluations are only required for base points, whose number is much smaller than the ensemble size, the computational cost is significantly reduced. The applicability of GPIES in estimating heterogeneous conductivity is evaluated by the saturated and unsaturated flow problems, respectively. Without sacrificing estimation accuracy, GPIES achieves about an order of magnitude of speed-up compared with the standard IES. Although subsurface flow problems are considered in this study, the proposed method can be equally applied to other hydrological models.

  9. Mesoscale Model Data Preparation and Execution: A New Method Utilizing the Internet

    National Research Council Canada - National Science Library

    Kirby, Stephen

    2002-01-01

    In order to streamline and simplify the methodologies required to obtain and process the requisite meteorological data for mesoscale meteorological models such as the Battlescale Forecast Model (BFM...

  10. North Pacific Mesoscale Coupled Air-Ocean Simulations Compared with Observations

    Energy Technology Data Exchange (ETDEWEB)

    Cerovecki, Ivana [Univ. of California, San Diego, CA (United States). Scripps Inst. of Oceanography; McClean, Julie [Univ. of California, San Diego, CA (United States). Scripps Inst. of Oceanography; Koracin, Darko [Desert Research Inst. (DRI), Reno, NV (United States). Division of Atmospheric Sciences

    2014-11-14

    The overall objective of this study was to improve the representation of regional ocean circulation in the North Pacific by using high resolution atmospheric forcing that accurately represents mesoscale processes in ocean-atmosphere regional (North Pacific) model configuration. The goal was to assess the importance of accurate representation of mesoscale processes in the atmosphere and the ocean on large scale circulation. This is an important question, as mesoscale processes in the atmosphere which are resolved by the high resolution mesoscale atmospheric models such as Weather Research and Forecasting (WRF), are absent in commonly used atmospheric forcing such as CORE forcing, employed in e.g. the Community Climate System Model (CCSM).

  11. Experimental Study on Meso-Scale Milling Process Using Nanofluid Minimum Quantity Lubrication

    International Nuclear Information System (INIS)

    Lee, P. H.; Nam, T. S.; Li, Cheng Jun; Lee, S. W.

    2010-01-01

    This paper present the characteristics of micro- and meso-scale milling processes in which compressed cold air, minimum quantity lubrication (MQL) and MoS 2 nanofluid MQL are used. For process characterization, the micro and meso-scale milling experiments are conducted using desktop meso-scale machine tool system and the surface roughness is measured. The experimental results show that the use of compressed chilly air and nanofluid MQL in the micro- and meso-scale milling processes is effective in improving the surface finish

  12. Assessing uncertainties in flood forecasts for decision making: prototype of an operational flood management system integrating ensemble predictions

    Directory of Open Access Journals (Sweden)

    J. Dietrich

    2009-08-01

    Full Text Available Ensemble forecasts aim at framing the uncertainties of the potential future development of the hydro-meteorological situation. A probabilistic evaluation can be used to communicate forecast uncertainty to decision makers. Here an operational system for ensemble based flood forecasting is presented, which combines forecasts from the European COSMO-LEPS, SRNWP-PEPS and COSMO-DE prediction systems. A multi-model lagged average super-ensemble is generated by recombining members from different runs of these meteorological forecast systems. A subset of the super-ensemble is selected based on a priori model weights, which are obtained from ensemble calibration. Flood forecasts are simulated by the conceptual rainfall-runoff-model ArcEGMO. Parameter uncertainty of the model is represented by a parameter ensemble, which is a priori generated from a comprehensive uncertainty analysis during model calibration. The use of a computationally efficient hydrological model within a flood management system allows us to compute the hydro-meteorological model chain for all members of the sub-ensemble. The model chain is not re-computed before new ensemble forecasts are available, but the probabilistic assessment of the output is updated when new information from deterministic short range forecasts or from assimilation of measured data becomes available. For hydraulic modelling, with the desired result of a probabilistic inundation map with high spatial resolution, a replacement model can help to overcome computational limitations. A prototype of the developed framework has been applied for a case study in the Mulde river basin. However these techniques, in particular the probabilistic assessment and the derivation of decision rules are still in their infancy. Further research is necessary and promising.

  13. A new strategy for snow-cover mapping using remote sensing data and ensemble based systems techniques

    Science.gov (United States)

    Roberge, S.; Chokmani, K.; De Sève, D.

    2012-04-01

    The snow cover plays an important role in the hydrological cycle of Quebec (Eastern Canada). Consequently, evaluating its spatial extent interests the authorities responsible for the management of water resources, especially hydropower companies. The main objective of this study is the development of a snow-cover mapping strategy using remote sensing data and ensemble based systems techniques. Planned to be tested in a near real-time operational mode, this snow-cover mapping strategy has the advantage to provide the probability of a pixel to be snow covered and its uncertainty. Ensemble systems are made of two key components. First, a method is needed to build an ensemble of classifiers that is diverse as much as possible. Second, an approach is required to combine the outputs of individual classifiers that make up the ensemble in such a way that correct decisions are amplified, and incorrect ones are cancelled out. In this study, we demonstrate the potential of ensemble systems to snow-cover mapping using remote sensing data. The chosen classifier is a sequential thresholds algorithm using NOAA-AVHRR data adapted to conditions over Eastern Canada. Its special feature is the use of a combination of six sequential thresholds varying according to the day in the winter season. Two versions of the snow-cover mapping algorithm have been developed: one is specific for autumn (from October 1st to December 31st) and the other for spring (from March 16th to May 31st). In order to build the ensemble based system, different versions of the algorithm are created by varying randomly its parameters. One hundred of the versions are included in the ensemble. The probability of a pixel to be snow, no-snow or cloud covered corresponds to the amount of votes the pixel has been classified as such by all classifiers. The overall performance of ensemble based mapping is compared to the overall performance of the chosen classifier, and also with ground observations at meteorological

  14. Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios

    Science.gov (United States)

    Gelfan, Alexander; Moreydo, Vsevolod; Motovilov, Yury; Solomatine, Dimitri P.

    2018-04-01

    A long-term forecasting ensemble methodology, applied to water inflows into the Cheboksary Reservoir (Russia), is presented. The methodology is based on a version of the semi-distributed hydrological model ECOMAG (ECOlogical Model for Applied Geophysics) that allows for the calculation of an ensemble of inflow hydrographs using two different sets of weather ensembles for the lead time period: observed weather data, constructed on the basis of the Ensemble Streamflow Prediction methodology (ESP-based forecast), and synthetic weather data, simulated by a multi-site weather generator (WG-based forecast). We have studied the following: (1) whether there is any advantage of the developed ensemble forecasts in comparison with the currently issued operational forecasts of water inflow into the Cheboksary Reservoir, and (2) whether there is any noticeable improvement in probabilistic forecasts when using the WG-simulated ensemble compared to the ESP-based ensemble. We have found that for a 35-year period beginning from the reservoir filling in 1982, both continuous and binary model-based ensemble forecasts (issued in the deterministic form) outperform the operational forecasts of the April-June inflow volume actually used and, additionally, provide acceptable forecasts of additional water regime characteristics besides the inflow volume. We have also demonstrated that the model performance measures (in the verification period) obtained from the WG-based probabilistic forecasts, which are based on a large number of possible weather scenarios, appeared to be more statistically reliable than the corresponding measures calculated from the ESP-based forecasts based on the observed weather scenarios.

  15. Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios

    Directory of Open Access Journals (Sweden)

    A. Gelfan

    2018-04-01

    Full Text Available A long-term forecasting ensemble methodology, applied to water inflows into the Cheboksary Reservoir (Russia, is presented. The methodology is based on a version of the semi-distributed hydrological model ECOMAG (ECOlogical Model for Applied Geophysics that allows for the calculation of an ensemble of inflow hydrographs using two different sets of weather ensembles for the lead time period: observed weather data, constructed on the basis of the Ensemble Streamflow Prediction methodology (ESP-based forecast, and synthetic weather data, simulated by a multi-site weather generator (WG-based forecast. We have studied the following: (1 whether there is any advantage of the developed ensemble forecasts in comparison with the currently issued operational forecasts of water inflow into the Cheboksary Reservoir, and (2 whether there is any noticeable improvement in probabilistic forecasts when using the WG-simulated ensemble compared to the ESP-based ensemble. We have found that for a 35-year period beginning from the reservoir filling in 1982, both continuous and binary model-based ensemble forecasts (issued in the deterministic form outperform the operational forecasts of the April–June inflow volume actually used and, additionally, provide acceptable forecasts of additional water regime characteristics besides the inflow volume. We have also demonstrated that the model performance measures (in the verification period obtained from the WG-based probabilistic forecasts, which are based on a large number of possible weather scenarios, appeared to be more statistically reliable than the corresponding measures calculated from the ESP-based forecasts based on the observed weather scenarios.

  16. Isotope methods in hydrology

    International Nuclear Information System (INIS)

    Moser, H.; Rauert, W.

    1980-01-01

    Of the investigation methods used in hydrology, tracer methods hold a special place as they are the only ones which give direct insight into the movement and distribution processes taking place in surface and ground waters. Besides the labelling of water with salts and dyes, as in the past, in recent years the use of isotopes in hydrology, in water research and use, in ground-water protection and in hydraulic engineering has increased. This by no means replaces proven methods of hydrological investigation but tends rather to complement and expand them through inter-disciplinary cooperation. The book offers a general introduction to the application of various isotope methods to specific hydrogeological and hydrological problems. The idea is to place the hydrogeologist and the hydrologist in the position to recognize which isotope method will help him solve his particular problem or indeed, make a solution possible at all. He should also be able to recognize what the prerequisites are and what work and expenditure the use of such methods involves. May the book contribute to promoting cooperation between hydrogeologists, hydrologists, hydraulic engineers and isotope specialists, and thus supplement proven methods of investigation in hydrological research and water utilization and protection wherever the use of isotope methods proves to be of advantage. (orig./HP) [de

  17. Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations

    Science.gov (United States)

    Qi, W.; Zhang, C.; Fu, G.; Sweetapple, C.; Zhou, H.

    2016-02-01

    The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products, using different precipitation computation recipes, is evaluated using statistical and hydrological methods in northeastern China. In addition, a framework quantifying uncertainty contributions of precipitation products, hydrological models, and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products are Tropical Rainfall Measuring Mission (TRMM) products (TRMM3B42 and TRMM3B42RT), Global Land Data Assimilation System (GLDAS)/Noah, Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and a Global Satellite Mapping of Precipitation (GSMAP-MVK+) product. Two hydrological models of different complexities, i.e. a water and energy budget-based distributed hydrological model and a physically based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and GSMAP-MVK+ shows huge advantage and is better than TRMM3B42 in relative bias (RB), Nash-Sutcliffe coefficient of efficiency (NSE), root mean square error (RMSE), correlation coefficient (CC), false alarm ratio, and critical success index. These findings could be very useful for validation, refinement, and future development of satellite-based products (e.g. NASA Global Precipitation Measurement). Although large uncertainty exists in heavy precipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models can have the similar magnitude of contribution to discharge uncertainty as the hydrological models. A

  18. MATLAB algorithm to implement soil water data assimilation with the Ensemble Kalman Filter using HYDRUS.

    Science.gov (United States)

    Valdes-Abellan, Javier; Pachepsky, Yakov; Martinez, Gonzalo

    2018-01-01

    Data assimilation is becoming a promising technique in hydrologic modelling to update not only model states but also to infer model parameters, specifically to infer soil hydraulic properties in Richard-equation-based soil water models. The Ensemble Kalman Filter method is one of the most widely employed method among the different data assimilation alternatives. In this study the complete Matlab© code used to study soil data assimilation efficiency under different soil and climatic conditions is shown. The code shows the method how data assimilation through EnKF was implemented. Richards equation was solved by the used of Hydrus-1D software which was run from Matlab. •MATLAB routines are released to be used/modified without restrictions for other researchers•Data assimilation Ensemble Kalman Filter method code.•Soil water Richard equation flow solved by Hydrus-1D.

  19. Ensemble Weight Enumerators for Protograph LDPC Codes

    Science.gov (United States)

    Divsalar, Dariush

    2006-01-01

    Recently LDPC codes with projected graph, or protograph structures have been proposed. In this paper, finite length ensemble weight enumerators for LDPC codes with protograph structures are obtained. Asymptotic results are derived as the block size goes to infinity. In particular we are interested in obtaining ensemble average weight enumerators for protograph LDPC codes which have minimum distance that grows linearly with block size. As with irregular ensembles, linear minimum distance property is sensitive to the proportion of degree-2 variable nodes. In this paper the derived results on ensemble weight enumerators show that linear minimum distance condition on degree distribution of unstructured irregular LDPC codes is a sufficient but not a necessary condition for protograph LDPC codes.

  20. Ensemble Kalman filtering with residual nudging

    KAUST Repository

    Luo, X.; Hoteit, Ibrahim

    2012-01-01

    Covariance inflation and localisation are two important techniques that are used to improve the performance of the ensemble Kalman filter (EnKF) by (in effect) adjusting the sample covariances of the estimates in the state space. In this work

  1. Ensemble Machine Learning Methods and Applications

    CERN Document Server

    Ma, Yunqian

    2012-01-01

    It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face detection and are now being applied in areas as diverse as object trackingand bioinformatics.   Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including various contributions from researchers in leading industrial research labs. At once a solid theoretical study and a practical guide, the volume is a windfall for r...

  2. AUC-Maximizing Ensembles through Metalearning.

    Science.gov (United States)

    LeDell, Erin; van der Laan, Mark J; Petersen, Maya

    2016-05-01

    Area Under the ROC Curve (AUC) is often used to measure the performance of an estimator in binary classification problems. An AUC-maximizing classifier can have significant advantages in cases where ranking correctness is valued or if the outcome is rare. In a Super Learner ensemble, maximization of the AUC can be achieved by the use of an AUC-maximining metalearning algorithm. We discuss an implementation of an AUC-maximization technique that is formulated as a nonlinear optimization problem. We also evaluate the effectiveness of a large number of different nonlinear optimization algorithms to maximize the cross-validated AUC of the ensemble fit. The results provide evidence that AUC-maximizing metalearners can, and often do, out-perform non-AUC-maximizing metalearning methods, with respect to ensemble AUC. The results also demonstrate that as the level of imbalance in the training data increases, the Super Learner ensemble outperforms the top base algorithm by a larger degree.

  3. Multivariate localization methods for ensemble Kalman filtering

    KAUST Repository

    Roh, S.; Jun, M.; Szunyogh, I.; Genton, Marc G.

    2015-01-01

    the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function

  4. Polarized ensembles of random pure states

    International Nuclear Information System (INIS)

    Cunden, Fabio Deelan; Facchi, Paolo; Florio, Giuseppe

    2013-01-01

    A new family of polarized ensembles of random pure states is presented. These ensembles are obtained by linear superposition of two random pure states with suitable distributions, and are quite manageable. We will use the obtained results for two purposes: on the one hand we will be able to derive an efficient strategy for sampling states from isopurity manifolds. On the other, we will characterize the deviation of a pure quantum state from separability under the influence of noise. (paper)

  5. Polarized ensembles of random pure states

    Science.gov (United States)

    Deelan Cunden, Fabio; Facchi, Paolo; Florio, Giuseppe

    2013-08-01

    A new family of polarized ensembles of random pure states is presented. These ensembles are obtained by linear superposition of two random pure states with suitable distributions, and are quite manageable. We will use the obtained results for two purposes: on the one hand we will be able to derive an efficient strategy for sampling states from isopurity manifolds. On the other, we will characterize the deviation of a pure quantum state from separability under the influence of noise.

  6. Quark ensembles with infinite correlation length

    OpenAIRE

    Molodtsov, S. V.; Zinovjev, G. M.

    2014-01-01

    By studying quark ensembles with infinite correlation length we formulate the quantum field theory model that, as we show, is exactly integrable and develops an instability of its standard vacuum ensemble (the Dirac sea). We argue such an instability is rooted in high ground state degeneracy (for 'realistic' space-time dimensions) featuring a fairly specific form of energy distribution, and with the cutoff parameter going to infinity this inherent energy distribution becomes infinitely narrow...

  7. Orbital magnetism in ensembles of ballistic billiards

    International Nuclear Information System (INIS)

    Ullmo, D.; Richter, K.; Jalabert, R.A.

    1993-01-01

    The magnetic response of ensembles of small two-dimensional structures at finite temperatures is calculated. Using semiclassical methods and numerical calculation it is demonstrated that only short classical trajectories are relevant. The magnetic susceptibility is enhanced in regular systems, where these trajectories appear in families. For ensembles of squares large paramagnetic susceptibility is obtained, in good agreement with recent measurements in the ballistic regime. (authors). 20 refs., 2 figs

  8. Multivariate localization methods for ensemble Kalman filtering

    OpenAIRE

    S. Roh; M. Jun; I. Szunyogh; M. G. Genton

    2015-01-01

    In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of ...

  9. Towards a GME ensemble forecasting system: Ensemble initialization using the breeding technique

    Directory of Open Access Journals (Sweden)

    Jan D. Keller

    2008-12-01

    Full Text Available The quantitative forecast of precipitation requires a probabilistic background particularly with regard to forecast lead times of more than 3 days. As only ensemble simulations can provide useful information of the underlying probability density function, we built a new ensemble forecasting system (GME-EFS based on the GME model of the German Meteorological Service (DWD. For the generation of appropriate initial ensemble perturbations we chose the breeding technique developed by Toth and Kalnay (1993, 1997, which develops perturbations by estimating the regions of largest model error induced uncertainty. This method is applied and tested in the framework of quasi-operational forecasts for a three month period in 2007. The performance of the resulting ensemble forecasts are compared to the operational ensemble prediction systems ECMWF EPS and NCEP GFS by means of ensemble spread of free atmosphere parameters (geopotential and temperature and ensemble skill of precipitation forecasting. This comparison indicates that the GME ensemble forecasting system (GME-EFS provides reasonable forecasts with spread skill score comparable to that of the NCEP GFS. An analysis with the continuous ranked probability score exhibits a lack of resolution for the GME forecasts compared to the operational ensembles. However, with significant enhancements during the 3 month test period, the first results of our work with the GME-EFS indicate possibilities for further development as well as the potential for later operational usage.

  10. Hillslope hydrology and stability

    Science.gov (United States)

    Lu, Ning; Godt, Jonathan

    2012-01-01

    Landslides are caused by a failure of the mechanical balance within hillslopes. This balance is governed by two coupled physical processes: hydrological or subsurface flow and stress. The stabilizing strength of hillslope materials depends on effective stress, which is diminished by rainfall. This book presents a cutting-edge quantitative approach to understanding hydro-mechanical processes across variably saturated hillslope environments and to the study and prediction of rainfall-induced landslides. Topics covered include historic synthesis of hillslope geomorphology and hydrology, total and effective stress distributions, critical reviews of shear strength of hillslope materials and different bases for stability analysis. Exercises and homework problems are provided for students to engage with the theory in practice. This is an invaluable resource for graduate students and researchers in hydrology, geomorphology, engineering geology, geotechnical engineering and geomechanics and for professionals in the fields of civil and environmental engineering and natural hazard analysis.

  11. Conductor gestures influence evaluations of ensemble performance.

    Science.gov (United States)

    Morrison, Steven J; Price, Harry E; Smedley, Eric M; Meals, Cory D

    2014-01-01

    Previous research has found that listener evaluations of ensemble performances vary depending on the expressivity of the conductor's gestures, even when performances are otherwise identical. It was the purpose of the present study to test whether this effect of visual information was evident in the evaluation of specific aspects of ensemble performance: articulation and dynamics. We constructed a set of 32 music performances that combined auditory and visual information and were designed to feature a high degree of contrast along one of two target characteristics: articulation and dynamics. We paired each of four music excerpts recorded by a chamber ensemble in both a high- and low-contrast condition with video of four conductors demonstrating high- and low-contrast gesture specifically appropriate to either articulation or dynamics. Using one of two equivalent test forms, college music majors and non-majors (N = 285) viewed sixteen 30 s performances and evaluated the quality of the ensemble's articulation, dynamics, technique, and tempo along with overall expressivity. Results showed significantly higher evaluations for performances featuring high rather than low conducting expressivity regardless of the ensemble's performance quality. Evaluations for both articulation and dynamics were strongly and positively correlated with evaluations of overall ensemble expressivity.

  12. Verification of ECMWF System 4 for seasonal hydrological forecasting in a northern climate

    Science.gov (United States)

    Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert

    2017-11-01

    Hydropower production requires optimal dam and reservoir management to prevent flooding damage and avoid operation losses. In a northern climate, where spring freshet constitutes the main inflow volume, seasonal forecasts can help to establish a yearly strategy. Long-term hydrological forecasts often rely on past observations of streamflow or meteorological data. Another alternative is to use ensemble meteorological forecasts produced by climate models. In this paper, those produced by the ECMWF (European Centre for Medium-Range Forecast) System 4 are examined and bias is characterized. Bias correction, through the linear scaling method, improves the performance of the raw ensemble meteorological forecasts in terms of continuous ranked probability score (CRPS). Then, three seasonal ensemble hydrological forecasting systems are compared: (1) the climatology of simulated streamflow, (2) the ensemble hydrological forecasts based on climatology (ESP) and (3) the hydrological forecasts based on bias-corrected ensemble meteorological forecasts from System 4 (corr-DSP). Simulated streamflow computed using observed meteorological data is used as benchmark. Accounting for initial conditions is valuable even for long-term forecasts. ESP and corr-DSP both outperform the climatology of simulated streamflow for lead times from 1 to 5 months depending on the season and watershed. Integrating information about future meteorological conditions also improves monthly volume forecasts. For the 1-month lead time, a gain exists for almost all watersheds during winter, summer and fall. However, volume forecasts performance for spring varies from one watershed to another. For most of them, the performance is close to the performance of ESP. For longer lead times, the CRPS skill score is mostly in favour of ESP, even if for many watersheds, ESP and corr-DSP have comparable skill. Corr-DSP appears quite reliable but, in some cases, under-dispersion or bias is observed. A more complex bias

  13. River Flow Prediction Using the Nearest Neighbor Probabilistic Ensemble Method

    Directory of Open Access Journals (Sweden)

    H. Sanikhani

    2016-02-01

    Full Text Available Introduction: In the recent years, researchers interested on probabilistic forecasting of hydrologic variables such river flow.A probabilistic approach aims at quantifying the prediction reliability through a probability distribution function or a prediction interval for the unknown future value. The evaluation of the uncertainty associated to the forecast is seen as a fundamental information, not only to correctly assess the prediction, but also to compare forecasts from different methods and to evaluate actions and decisions conditionally on the expected values. Several probabilistic approaches have been proposed in the literature, including (1 methods that use resampling techniques to assess parameter and model uncertainty, such as the Metropolis algorithm or the Generalized Likelihood Uncertainty Estimation (GLUE methodology for an application to runoff prediction, (2 methods based on processing the forecast errors of past data to produce the probability distributions of future values and (3 methods that evaluate how the uncertainty propagates from the rainfall forecast to the river discharge prediction, as the Bayesian forecasting system. Materials and Methods: In this study, two different probabilistic methods are used for river flow prediction.Then the uncertainty related to the forecast is quantified. One approach is based on linear predictors and in the other, nearest neighbor was used. The nonlinear probabilistic ensemble can be used for nonlinear time series analysis using locally linear predictors, while NNPE utilize a method adapted for one step ahead nearest neighbor methods. In this regard, daily river discharge (twelve years of Dizaj and Mashin Stations on Baranduz-Chay basin in west Azerbijan and Zard-River basin in Khouzestan provinces were used, respectively. The first six years of data was applied for fitting the model. The next three years was used to calibration and the remained three yeas utilized for testing the models

  14. Rotationally invariant family of Levy-like random matrix ensembles

    International Nuclear Information System (INIS)

    Choi, Jinmyung; Muttalib, K A

    2009-01-01

    We introduce a family of rotationally invariant random matrix ensembles characterized by a parameter λ. While λ = 1 corresponds to well-known critical ensembles, we show that λ ≠ 1 describes 'Levy-like' ensembles, characterized by power-law eigenvalue densities. For λ > 1 the density is bounded, as in Gaussian ensembles, but λ < 1 describes ensembles characterized by densities with long tails. In particular, the model allows us to evaluate, in terms of a novel family of orthogonal polynomials, the eigenvalue correlations for Levy-like ensembles. These correlations differ qualitatively from those in either the Gaussian or the critical ensembles. (fast track communication)

  15. Evaluation of the NMC regional ensemble prediction system during the Beijing 2008 Olympic Games

    Science.gov (United States)

    Li, Xiaoli; Tian, Hua; Deng, Guo

    2011-10-01

    Based on the B08RDP (Beijing 2008 Olympic Games Mesoscale Ensemble Prediction Research and Development Project) that was launched by the World Weather Research Programme (WWRP) in 2004, a regional ensemble prediction system (REPS) at a 15-km horizontal resolution was developed at the National Meteorological Center (NMC) of the China Meteorological Administration (CMA). Supplementing to the forecasters' subjective affirmation on the promising performance of the REPS during the 2008 Beijing Olympic Games (BOG), this paper focuses on the objective verification of the REPS for precipitation forecasts during the BOG period. By use of a set of advanced probabilistic verification scores, the value of the REPS compared to the quasi-operational global ensemble prediction system (GEPS) is assessed for a 36-day period (21 July-24 August 2008). The evaluation here involves different aspects of the REPS and GEPS, including their general forecast skills, specific attributes (reliability and resolution), and related economic values. The results indicate that the REPS generally performs significantly better for the short-range precipitation forecasts than the GEPS, and for light to heavy rainfall events, the REPS provides more skillful forecasts for accumulated 6- and 24-h precipitation. By further identifying the performance of the REPS through the attribute-focused measures, it is found that the advantages of the REPS over the GEPS come from better reliability (smaller biases and better dispersion) and increased resolution. Also, evaluation of a decision-making score reveals that a much larger group of users benefits from using the REPS forecasts than using the single model (the control run) forecasts, especially for the heavy rainfall events.

  16. Towards a generalization procedure for WRF mesoscale wind climatologies

    DEFF Research Database (Denmark)

    Hahmann, Andrea N.; Casso, P.; Campmany, E.

    We present a method for generalizing wind climatologies generated from mesoscale model output (e.g. the Weather, Research and Forecasting (WRF) model.) The generalization procedure is based on Wind Atlas framework of WAsP and KAMM/WAsP, and been extensively in wind resources assessment in DTU Wind...... generalized wind climatologies estimated by the microscale model WAsP and the methodology presented here. For the Danish wind measurements the mean absolute error in the ‘raw’ wind speeds is 9.2%, while the mean absolute error in the generalized wind speeds is 4.1%. The generalization procedure has been...

  17. A Reanalysis System for the Generation of Mesoscale Climatographies

    DEFF Research Database (Denmark)

    Hahmann, Andrea N.; Rostkier-Edelstein, Dorita; Warner, Thomas T.

    2010-01-01

    ), wherein Newtonian relaxation terms in the prognostic equations continually nudge the model solution toward surface and upper-air observations. When applied to a mesoscale climatography, the system is called Climate-FDDA (CFDDA). Here, the CFDDA system is used for downscaling eastern Mediterranean...... the frequency distributions of atmospheric states in addition to time means. The verification of the monthly rainfall climatography shows that CFDDA captures most of the observed spatial and interannual variability, although the model tends to underestimate rainfall amounts over the sea. The frequency...

  18. LBM estimation of thermal conductivity in meso-scale modelling

    International Nuclear Information System (INIS)

    Grucelski, A

    2016-01-01

    Recently, there is a growing engineering interest in more rigorous prediction of effective transport coefficients for multicomponent, geometrically complex materials. We present main assumptions and constituents of the meso-scale model for the simulation of the coal or biomass devolatilisation with the Lattice Boltzmann method. For the results, the estimated values of the thermal conductivity coefficient of coal (solids), pyrolytic gases and air matrix are presented for a non-steady state with account for chemical reactions in fluid flow and heat transfer. (paper)

  19. Adaptation of Mesoscale Weather Models to Local Forecasting

    Science.gov (United States)

    Manobianco, John T.; Taylor, Gregory E.; Case, Jonathan L.; Dianic, Allan V.; Wheeler, Mark W.; Zack, John W.; Nutter, Paul A.

    2003-01-01

    Methodologies have been developed for (1) configuring mesoscale numerical weather-prediction models for execution on high-performance computer workstations to make short-range weather forecasts for the vicinity of the Kennedy Space Center (KSC) and the Cape Canaveral Air Force Station (CCAFS) and (2) evaluating the performances of the models as configured. These methodologies have been implemented as part of a continuing effort to improve weather forecasting in support of operations of the U.S. space program. The models, methodologies, and results of the evaluations also have potential value for commercial users who could benefit from tailoring their operations and/or marketing strategies based on accurate predictions of local weather. More specifically, the purpose of developing the methodologies for configuring the models to run on computers at KSC and CCAFS is to provide accurate forecasts of winds, temperature, and such specific thunderstorm-related phenomena as lightning and precipitation. The purpose of developing the evaluation methodologies is to maximize the utility of the models by providing users with assessments of the capabilities and limitations of the models. The models used in this effort thus far include the Mesoscale Atmospheric Simulation System (MASS), the Regional Atmospheric Modeling System (RAMS), and the National Centers for Environmental Prediction Eta Model ( Eta for short). The configuration of the MASS and RAMS is designed to run the models at very high spatial resolution and incorporate local data to resolve fine-scale weather features. Model preprocessors were modified to incorporate surface, ship, buoy, and rawinsonde data as well as data from local wind towers, wind profilers, and conventional or Doppler radars. The overall evaluation of the MASS, Eta, and RAMS was designed to assess the utility of these mesoscale models for satisfying the weather-forecasting needs of the U.S. space program. The evaluation methodology includes

  20. An experimental seasonal hydrological forecasting system over the Yellow River basin - Part 1: Understanding the role of initial hydrological conditions

    Science.gov (United States)

    Yuan, Xing; Ma, Feng; Wang, Linying; Zheng, Ziyan; Ma, Zhuguo; Ye, Aizhong; Peng, Shaoming

    2016-06-01

    The hydrological cycle over the Yellow River has been altered by the climate change and human interventions greatly during past decades, with a decadal drying trend mixed with a large variation of seasonal hydrological extremes. To provide support for the adaptation to a changing environment, an experimental seasonal hydrological forecasting system is established over the Yellow River basin. The system draws from a legacy of a global hydrological forecasting system that is able to make use of real-time seasonal climate predictions from North American Multimodel Ensemble (NMME) climate models through a statistical downscaling approach but with a higher resolution and a spatially disaggregated calibration procedure that is based on a newly compiled hydrological observation dataset with 5 decades of naturalized streamflow at 12 mainstream gauges and a newly released meteorological observation dataset including 324 meteorological stations over the Yellow River basin. While the evaluation of the NMME-based seasonal hydrological forecasting will be presented in a companion paper to explore the added values from climate forecast models, this paper investigates the role of initial hydrological conditions (ICs) by carrying out 6-month Ensemble Streamflow Prediction (ESP) and reverse ESP-type simulations for each calendar month during 1982-2010 with the hydrological models in the forecasting system, i.e., a large-scale land surface hydrological model and a global routing model that is regionalized over the Yellow River. In terms of streamflow predictability, the ICs outweigh the meteorological forcings up to 2-5 months during the cold and dry seasons, but the latter prevails over the former in the predictability after the first month during the warm and wet seasons. For the streamflow forecasts initialized at the end of the rainy season, the influence of ICs for lower reaches of the Yellow River can be 5 months longer than that for the upper reaches, while such a difference

  1. Operational aspects of asynchronous filtering for hydrological forecasting

    Science.gov (United States)

    Rakovec, O.; Weerts, A. H.; Sumihar, J.; Uijlenhoet, R.

    2015-03-01

    This study investigates the suitability of the Asynchronous Ensemble Kalman Filter (AEnKF) and a partitioned updating scheme for hydrological forecasting. The AEnKF requires forward integration of the model for the analysis and enables assimilation of current and past observations simultaneously at a single analysis step. The results of discharge assimilation into a grid-based hydrological model for the Upper Ourthe catchment in the Belgian Ardennes show that including past predictions and observations in the data assimilation method improves the model forecasts. Additionally, we show that elimination of the strongly non-linear relation between the soil moisture storage and assimilated discharge observations from the model update becomes beneficial for improved operational forecasting, which is evaluated using several validation measures.

  2. Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

    Directory of Open Access Journals (Sweden)

    A. Endalamaw

    2017-09-01

    Full Text Available Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which better represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW in Interior Alaska: one nearly permafrost-free (LowP sub-basin and one permafrost-dominated (HighP sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC mesoscale hydrological model to simulate runoff, evapotranspiration (ET, and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub

  3. HYDROLOGY, JEFFERSON COUNTY, WI, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  4. HYDROLOGY, DODGE COUNTY, WI, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  5. HYDROLOGY, WASHINGTON COUNTY, WI, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  6. HYDROLOGY, DUNN COUNTY, WI, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  7. HYDROLOGY, yakima County, WA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  8. HYDROLOGY, GEORGETOWN COUNTY, SC, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  9. HYDROLOGY, LAUREL COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  10. HYDROLOGY, LAMAR COUNTY, GEORGIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  11. HYDROLOGY, IONIA COUNTY, MI, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  12. HYDROLOGY, Bourbon COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  13. HYDROLOGY, MADISON COUNTY, FL, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  14. HYDROLOGY, MONITEAU COUNTY, MISSOURI USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  15. HYDROLOGY, IRON COUNTY, UTAH, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  16. HYDROLOGY, WHITLEY COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  17. HYDROLOGY, TUSCOLA COUNTY, MI, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  18. HYDROLOGIC ANALYSIS, HONOLULU COUNTY, HI

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  19. HYDROLOGY, Richland County, ND, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  20. HYDROLOGY, Grant County, SD, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  1. HYDROLOGY, LEVY COUNTY, FL, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  2. HYDROLOGY, WASHINGTON COUNTY, FL, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  3. HYDROLOGY, HAMILTON COUNTY, FL, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  4. HYDROLOGY, LIBERTY COUNTY, FL, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  5. HYDROLOGY, RICE COUNTY, MN, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  6. HYDROLOGY, MADISON COUNTY, ALABAMA USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  7. HYDROLOGY, BALLARD COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  8. HYDROLOGY, STORY COUNTY, IOWA USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  9. HYDROLOGIC ANALYSIS, MONO COUNTY, CA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  10. HYDROLOGIC ANALYSIS, EDGEFIELD COUNTY, SC

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  11. HYDROLOGY, SIMPSON COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Hydrology data include spatial datasets and data tables necessary for documenting the hydrologic procedures for estimating flood discharges for a flood insurance...

  12. Ensemble Streamflow Prediction in Korea: Past and Future 5 Years

    Science.gov (United States)

    Jeong, D.; Kim, Y.; Lee, J.

    2005-05-01

    The Ensemble Streamflow Prediction (ESP) approach was first introduced in 2000 by the Hydrology Research Group (HRG) at Seoul National University as an alternative probabilistic forecasting technique for improving the 'Water Supply Outlook' That is issued every month by the Ministry of Construction and Transportation in Korea. That study motivated the Korea Water Resources Corporation (KOWACO) to establish their seasonal probabilistic forecasting system for the 5 major river basins using the ESP approach. In cooperation with the HRG, the KOWACO developed monthly optimal multi-reservoir operating systems for the Geum river basin in 2004, which coupled the ESP forecasts with an optimization model using sampling stochastic dynamic programming. The user interfaces for both ESP and SSDP have also been designed for the developed computer systems to become more practical. More projects for developing ESP systems to the other 3 major river basins (i.e. the Nakdong, Han and Seomjin river basins) was also completed by the HRG and KOWACO at the end of December 2004. Therefore, the ESP system has become the most important mid- and long-term streamflow forecast technique in Korea. In addition to the practical aspects, resent research experience on ESP has raised some concerns into ways of improving the accuracy of ESP in Korea. Jeong and Kim (2002) performed an error analysis on its resulting probabilistic forecasts and found that the modeling error is dominant in the dry season, while the meteorological error is dominant in the flood season. To address the first issue, Kim et al. (2004) tested various combinations and/or combining techniques and showed that the ESP probabilistic accuracy could be improved considerably during the dry season when the hydrologic models were combined and/or corrected. In addition, an attempt was also made to improve the ESP accuracy for the flood season using climate forecast information. This ongoing project handles three types of climate

  13. Hydrology and soil erosion

    Science.gov (United States)

    Leonard J. Lane; Mary R. Kidwell

    2003-01-01

    We review research on surface water hydrology and soil erosion at the Santa Rita Experimental Range (SRER). Almost all of the research was associated with eight small experimental watersheds established from 1974 to 1975 and operated until the present. Analysis of climatic features of the SRER supports extending research findings from the SRER to broad areas of the...

  14. Hydrology and flow forecasting

    NARCIS (Netherlands)

    Vrijling, J.K.; Kwadijk, J.; Van Duivendijk, J.; Van Gelder, P.; Pang, H.; Rao, S.Q.; Wang, G.Q.; Huang, X.Q.

    2002-01-01

    We have studied and applied the statistic model (i.e. MMC) and hydrological models to Upper Yellow River. This report introduces the results and some conclusions from the model. The three models, MMC, MWBM and NAM, have be applied in the research area. The forecasted discharge by the three models

  15. Environmental isotope hydrology

    International Nuclear Information System (INIS)

    1973-01-01

    Environmental isotope hydrology is a relatively new field of investigation based on isotopic variations observed in natural waters. These isotopic characteristics have been established over a broad space and time scale. They cannot be controlled by man, but can be observed and interpreted to gain valuable regional information on the origin, turnover and transit time of water in the system which often cannot be obtained by other techniques. The cost of such investigations is usually relatively small in comparison with the cost of classical hydrological studies. The main environmental isotopes of hydrological interest are the stable isotopes deuterium (hydrogen-2), carbon-13, oxygen-18, and the radioactive isotopes tritium (hydrogen-3) and carbon-14. Isotopes of hydrogen and oxygen are ideal geochemical tracers of water because their concentrations are usually not subject to change by interaction with the aquifer material. On the other hand, carbon compounds in groundwater may interact with the aquifer material, complicating the interpretation of carbon-14 data. A few other environmental isotopes such as 32 Si and 238 U/ 234 U have been proposed recently for hydrological purposes but their use has been quite limited until now and they will not be discussed here. (author)

  16. Watershed hydrology. Chapter 7.

    Science.gov (United States)

    Elons S. Verry; Kenneth N. Brooks; Dale S. Nichols; Dawn R. Ferris; Stephen D. Sebestyen

    2011-01-01

    Watershed hydrology is determined by the local climate, land use, and pathways of water flow. At the Marcell Experimental Forest (MEF), streamflow is dominated by spring runoff events driven by snowmelt and spring rains common to the strongly continental climate of northern Minnesota. Snowmelt and rainfall in early spring saturate both mineral and organic soils and...

  17. Recipes for correcting the impact of effective mesoscale resolution on the estimation of extreme winds

    DEFF Research Database (Denmark)

    Larsén, Xiaoli Guo; Ott, Søren; Badger, Jake

    2012-01-01

    Extreme winds derived from simulations using mesoscale models are underestimated due to the effective spatial and temporal resolutions. This is reflected in the spectral domain as an energy deficit in the mesoscale range. The energy deficit implies smaller spectral moments and thus underestimatio...

  18. netherland hydrological modeling instrument

    Science.gov (United States)

    Hoogewoud, J. C.; de Lange, W. J.; Veldhuizen, A.; Prinsen, G.

    2012-04-01

    Netherlands Hydrological Modeling Instrument A decision support system for water basin management. J.C. Hoogewoud , W.J. de Lange ,A. Veldhuizen , G. Prinsen , The Netherlands Hydrological modeling Instrument (NHI) is the center point of a framework of models, to coherently model the hydrological system and the multitude of functions it supports. Dutch hydrological institutes Deltares, Alterra, Netherlands Environmental Assessment Agency, RWS Waterdienst, STOWA and Vewin are cooperating in enhancing the NHI for adequate decision support. The instrument is used by three different ministries involved in national water policy matters, for instance the WFD, drought management, manure policy and climate change issues. The basis of the modeling instrument is a state-of-the-art on-line coupling of the groundwater system (MODFLOW), the unsaturated zone (metaSWAP) and the surface water system (MOZART-DM). It brings together hydro(geo)logical processes from the column to the basin scale, ranging from 250x250m plots to the river Rhine and includes salt water flow. The NHI is validated with an eight year run (1998-2006) with dry and wet periods. For this run different parts of the hydrology have been compared with measurements. For instance, water demands in dry periods (e.g. for irrigation), discharges at outlets, groundwater levels and evaporation. A validation alone is not enough to get support from stakeholders. Involvement from stakeholders in the modeling process is needed. There fore to gain sufficient support and trust in the instrument on different (policy) levels a couple of actions have been taken: 1. a transparent evaluation of modeling-results has been set up 2. an extensive program is running to cooperate with regional waterboards and suppliers of drinking water in improving the NHI 3. sharing (hydrological) data via newly setup Modeling Database for local and national models 4. Enhancing the NHI with "local" information. The NHI is and has been used for many

  19. Comparison of three different methods of perturbing the potential vorticity field in mesoscale forecasts of Mediterranean heavy precipitation events: PV-gradient, PV-adjoint and PV-satellite

    Science.gov (United States)

    Vich, M.; Romero, R.; Richard, E.; Arbogast, P.; Maynard, K.

    2010-09-01

    Heavy precipitation events occur regularly in the western Mediterranean region. These events often have a high impact on the society due to economic and personal losses. The improvement of the mesoscale numerical forecasts of these events can be used to prevent or minimize their impact on the society. In previous studies, two ensemble prediction systems (EPSs) based on perturbing the model initial and boundary conditions were developed and tested for a collection of high-impact MEDEX cyclonic episodes. These EPSs perturb the initial and boundary potential vorticity (PV) field through a PV inversion algorithm. This technique ensures modifications of all the meteorological fields without compromising the mass-wind balance. One EPS introduces the perturbations along the zones of the three-dimensional PV structure presenting the local most intense values and gradients of the field (a semi-objective choice, PV-gradient), while the other perturbs the PV field over the MM5 adjoint model calculated sensitivity zones (an objective method, PV-adjoint). The PV perturbations are set from a PV error climatology (PVEC) that characterizes typical PV errors in the ECMWF forecasts, both in intensity and displacement. This intensity and displacement perturbation of the PV field is chosen randomly, while its location is given by the perturbation zones defined in each ensemble generation method. Encouraged by the good results obtained by these two EPSs that perturb the PV field, a new approach based on a manual perturbation of the PV field has been tested and compared with the previous results. This technique uses the satellite water vapor (WV) observations to guide the correction of initial PV structures. The correction of the PV field intents to improve the match between the PV distribution and the WV image, taking advantage of the relation between dark and bright features of WV images and PV anomalies, under some assumptions. Afterwards, the PV inversion algorithm is applied to run

  20. Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing

    KAUST Repository

    Toye, Habib

    2017-05-26

    We present our efforts to build an ensemble data assimilation and forecasting system for the Red Sea. The system consists of the high-resolution Massachusetts Institute of Technology general circulation model (MITgcm) to simulate ocean circulation and of the Data Research Testbed (DART) for ensemble data assimilation. DART has been configured to integrate all members of an ensemble adjustment Kalman filter (EAKF) in parallel, based on which we adapted the ensemble operations in DART to use an invariant ensemble, i.e., an ensemble Optimal Interpolation (EnOI) algorithm. This approach requires only single forward model integration in the forecast step and therefore saves substantial computational cost. To deal with the strong seasonal variability of the Red Sea, the EnOI ensemble is then seasonally selected from a climatology of long-term model outputs. Observations of remote sensing sea surface height (SSH) and sea surface temperature (SST) are assimilated every 3 days. Real-time atmospheric fields from the National Center for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) are used as forcing in different assimilation experiments. We investigate the behaviors of the EAKF and (seasonal-) EnOI and compare their performances for assimilating and forecasting the circulation of the Red Sea. We further assess the sensitivity of the assimilation system to various filtering parameters (ensemble size, inflation) and atmospheric forcing.

  1. Curricula and Syllabi in Hydrology.

    Science.gov (United States)

    United Nations Educational, Scientific, and Cultural Organization, Paris (France).

    This collection of papers is intended to provide a means for the exchange of information on hydrological techniques and for the coordination of research and data collection. The objectives and trends in hydrological education are presented. The International Hydrological Decade (IHD) Working Group on Education recommends a series of topics that…

  2. Forecasting skills of the ensemble hydro-meteorological system for the Po river floods

    Science.gov (United States)

    Ricciardi, Giuseppe; Montani, Andrea; Paccagnella, Tiziana; Pecora, Silvano; Tonelli, Fabrizio

    2013-04-01

    The Po basin is the largest and most economically important river-basin in Italy. Extreme hydrological events, including floods, flash floods and droughts, are expected to become more severe in the next future due to climate change, and related ground effects are linked both with environmental and social resilience. A Warning Operational Center (WOC) for hydrological event management was created in Emilia Romagna region. In the last years, the WOC faced challenges in legislation, organization, technology and economics, achieving improvements in forecasting skill and information dissemination. Since 2005, an operational forecasting and modelling system for flood modelling and forecasting has been implemented, aimed at supporting and coordinating flood control and emergency management on the whole Po basin. This system, referred to as FEWSPo, has also taken care of environmental aspects of flood forecast. The FEWSPo system has reached a very high level of complexity, due to the combination of three different hydrological-hydraulic chains (HEC-HMS/RAS - MIKE11 NAM/HD, Topkapi/Sobek), with several meteorological inputs (forecasted - COSMOI2, COSMOI7, COSMO-LEPS among others - and observed). In this hydrological and meteorological ensemble the management of the relative predictive uncertainties, which have to be established and communicated to decision makers, is a debated scientific and social challenge. Real time activities face professional, modelling and technological aspects but are also strongly interrelated with organization and human aspects. The authors will report a case study using the operational flood forecast hydro-meteorological ensemble, provided by the MIKE11 chain fed by COSMO_LEPS EQPF. The basic aim of the proposed approach is to analyse limits and opportunities of the long term forecast (with a lead time ranging from 3 to 5 days), for the implementation of low cost actions, also looking for a well informed decision making and the improvement of

  3. Combining super-ensembles and statistical emulation to improve a regional climate and vegetation model

    Science.gov (United States)

    Hawkins, L. R.; Rupp, D. E.; Li, S.; Sarah, S.; McNeall, D. J.; Mote, P.; Betts, R. A.; Wallom, D.

    2017-12-01

    Changing regional patterns of surface temperature, precipitation, and humidity may cause ecosystem-scale changes in vegetation, altering the distribution of trees, shrubs, and grasses. A changing vegetation distribution, in turn, alters the albedo, latent heat flux, and carbon exchanged with the atmosphere with resulting feedbacks onto the regional climate. However, a wide range of earth-system processes that affect the carbon, energy, and hydrologic cycles occur at sub grid scales in climate models and must be parameterized. The appropriate parameter values in such parameterizations are often poorly constrained, leading to uncertainty in predictions of how the ecosystem will respond to changes in forcing. To better understand the sensitivity of regional climate to parameter selection and to improve regional climate and vegetation simulations, we used a large perturbed physics ensemble and a suite of statistical emulators. We dynamically downscaled a super-ensemble (multiple parameter sets and multiple initial conditions) of global climate simulations using a 25-km resolution regional climate model HadRM3p with the land-surface scheme MOSES2 and dynamic vegetation module TRIFFID. We simultaneously perturbed land surface parameters relating to the exchange of carbon, water, and energy between the land surface and atmosphere in a large super-ensemble of regional climate simulations over the western US. Statistical emulation was used as a computationally cost-effective tool to explore uncertainties in interactions. Regions of parameter space that did not satisfy observational constraints were eliminated and an ensemble of parameter sets that reduce regional biases and span a range of plausible interactions among earth system processes were selected. This study demonstrated that by combining super-ensemble simulations with statistical emulation, simulations of regional climate could be improved while simultaneously accounting for a range of plausible land

  4. Combining multi-objective optimization and bayesian model averaging to calibrate forecast ensembles of soil hydraulic models

    Energy Technology Data Exchange (ETDEWEB)

    Vrugt, Jasper A [Los Alamos National Laboratory; Wohling, Thomas [NON LANL

    2008-01-01

    Most studies in vadose zone hydrology use a single conceptual model for predictive inference and analysis. Focusing on the outcome of a single model is prone to statistical bias and underestimation of uncertainty. In this study, we combine multi-objective optimization and Bayesian Model Averaging (BMA) to generate forecast ensembles of soil hydraulic models. To illustrate our method, we use observed tensiometric pressure head data at three different depths in a layered vadose zone of volcanic origin in New Zealand. A set of seven different soil hydraulic models is calibrated using a multi-objective formulation with three different objective functions that each measure the mismatch between observed and predicted soil water pressure head at one specific depth. The Pareto solution space corresponding to these three objectives is estimated with AMALGAM, and used to generate four different model ensembles. These ensembles are post-processed with BMA and used for predictive analysis and uncertainty estimation. Our most important conclusions for the vadose zone under consideration are: (1) the mean BMA forecast exhibits similar predictive capabilities as the best individual performing soil hydraulic model, (2) the size of the BMA uncertainty ranges increase with increasing depth and dryness in the soil profile, (3) the best performing ensemble corresponds to the compromise (or balanced) solution of the three-objective Pareto surface, and (4) the combined multi-objective optimization and BMA framework proposed in this paper is very useful to generate forecast ensembles of soil hydraulic models.

  5. Mesoscale eddies are oases for higher trophic marine life

    KAUST Repository

    Godø , Olav R.; Samuelsen, Annette; Macaulay, Gavin J.; Patel, Ruben; Hjø llo, Solfrid Sæ tre; Horne, John; Kaartvedt, Stein; Johannessen, Johnny A.

    2012-01-01

    Mesoscale eddies stimulate biological production in the ocean, but knowledge of energy transfers to higher trophic levels within eddies remains fragmented and not quantified. Increasing the knowledge base is constrained by the inability of traditional sampling methods to adequately sample biological processes at the spatio-temporal scales at which they occur. By combining satellite and acoustic observations over spatial scales of 10 s of km horizontally and 100 s of m vertically, supported by hydrographical and biological sampling we show that anticyclonic eddies shape distribution and density of marine life from the surface to bathyal depths. Fish feed along density structures of eddies, demonstrating that eddies catalyze energy transfer across trophic levels. Eddies create attractive pelagic habitats, analogous to oases in the desert, for higher trophic level aquatic organisms through enhanced 3-D motion that accumulates and redistributes biomass, contributing to overall bioproduction in the ocean. Integrating multidisciplinary observation methodologies promoted a new understanding of biophysical interaction in mesoscale eddies. Our findings emphasize the impact of eddies on the patchiness of biomass in the sea and demonstrate that they provide rich feeding habitat for higher trophic marine life. 2012 God et al.

  6. Rotational and divergent kinetic energy in the mesoscale model ALADIN

    Directory of Open Access Journals (Sweden)

    V. Blažica

    2013-03-01

    Full Text Available Kinetic energy spectra from the mesoscale numerical weather prediction (NWP model ALADIN with horizontal resolution 4.4 km are split into divergent and rotational components which are then compared at horizontal scales below 300 km and various vertical levels. It is shown that about 50% of kinetic energy in the free troposphere in ALADIN is divergent energy. The percentage increases towards 70% near the surface and in the upper troposphere towards 100 hPa. The maximal percentage of divergent energy is found at stratospheric levels around 100 hPa and at scales below 100 km which are not represented by the global models. At all levels, the divergent energy spectra are characterised by shallower slopes than the rotational energy spectra, and the difference increases as horizontal scales become larger. A very similar vertical distribution of divergent energy is obtained by using the standard ALADIN approach for the computation of spectra based on the extension zone and by applying detrending approach commonly used in mesoscale NWP community.

  7. Optogenetic stimulation of a meso-scale human cortical model

    Science.gov (United States)

    Selvaraj, Prashanth; Szeri, Andrew; Sleigh, Jamie; Kirsch, Heidi

    2015-03-01

    Neurological phenomena like sleep and seizures depend not only on the activity of individual neurons, but on the dynamics of neuron populations as well. Meso-scale models of cortical activity provide a means to study neural dynamics at the level of neuron populations. Additionally, they offer a safe and economical way to test the effects and efficacy of stimulation techniques on the dynamics of the cortex. Here, we use a physiologically relevant meso-scale model of the cortex to study the hypersynchronous activity of neuron populations during epileptic seizures. The model consists of a set of stochastic, highly non-linear partial differential equations. Next, we use optogenetic stimulation to control seizures in a hyperexcited cortex, and to induce seizures in a normally functioning cortex. The high spatial and temporal resolution this method offers makes a strong case for the use of optogenetics in treating meso scale cortical disorders such as epileptic seizures. We use bifurcation analysis to investigate the effect of optogenetic stimulation in the meso scale model, and its efficacy in suppressing the non-linear dynamics of seizures.

  8. On the Nature of the Mesoscale Variability in Denmark Strait

    Science.gov (United States)

    Pickart, Robert; von Appen, Wilken; Mastropole, Dana; Valdimarsson, Hedinn; Vage, Kjetil; Jonsson, Steingriumur; Jochumsen, Kerstin; Girton, James

    2017-04-01

    The dense overflow through Denmark Strait is the largest contributor to the lower limb of the Atlantic Meridional Overturning Circulation. As such, it is important to understand the sources of water feeding the overflow and how the water negotiates the sill as it passes into the Irminger Sea. Here we use a large collection of shipboard hydrographic transects occupied across the strait, together with 6-years of mooring data from the sill, to investigate the water masses and mesoscale variability of the overflow water. Two dominant types of mesoscale features were identified, referred to as a "bolus" and a "pulse". The former is a large lens of weakly stratified water corresponding to a slight increase in along-strait velocity. The latter is a thin layer with greater stratification and strongly enhanced along-strait flow. The boluses, which are often noted in the historical literature, are associated with cyclonic circulation, while pulses, which have not been previously identified, are associated with anti-cyclonic circulation. Both features result in increased transport of overflow water. It is argued that these fluctuations at the sill trigger energetic variability downstream in the Deep Western Boundary Current.

  9. Mesoscale eddies are oases for higher trophic marine life.

    Directory of Open Access Journals (Sweden)

    Olav R Godø

    Full Text Available Mesoscale eddies stimulate biological production in the ocean, but knowledge of energy transfers to higher trophic levels within eddies remains fragmented and not quantified. Increasing the knowledge base is constrained by the inability of traditional sampling methods to adequately sample biological processes at the spatio-temporal scales at which they occur. By combining satellite and acoustic observations over spatial scales of 10 s of km horizontally and 100 s of m vertically, supported by hydrographical and biological sampling we show that anticyclonic eddies shape distribution and density of marine life from the surface to bathyal depths. Fish feed along density structures of eddies, demonstrating that eddies catalyze energy transfer across trophic levels. Eddies create attractive pelagic habitats, analogous to oases in the desert, for higher trophic level aquatic organisms through enhanced 3-D motion that accumulates and redistributes biomass, contributing to overall bioproduction in the ocean. Integrating multidisciplinary observation methodologies promoted a new understanding of biophysical interaction in mesoscale eddies. Our findings emphasize the impact of eddies on the patchiness of biomass in the sea and demonstrate that they provide rich feeding habitat for higher trophic marine life.

  10. Use of ground-based wind profiles in mesoscale forecasting

    Science.gov (United States)

    Schlatter, Thomas W.

    1985-01-01

    A brief review is presented of recent uses of ground-based wind profile data in mesoscale forecasting. Some of the applications are in real time, and some are after the fact. Not all of the work mentioned here has been published yet, but references are given wherever possible. As Gage and Balsley (1978) point out, sensitive Doppler radars have been used to examine tropospheric wind profiles since the 1970's. It was not until the early 1980's, however, that the potential contribution of these instruments to operational forecasting and numerical weather prediction became apparent. Profiler winds and radiosonde winds compare favorably, usually within a few m/s in speed and 10 degrees in direction (see Hogg et al., 1983), but the obvious advantage of the profiler is its frequent (hourly or more often) sampling of the same volume. The rawinsonde balloon is launched only twice a day and drifts with the wind. In this paper, I will: (1) mention two operational uses of data from a wind profiling system developed jointly by the Wave Propagation and Aeronomy Laboratories of NOAA; (2) describe a number of displays of these same data on a workstation for mesoscale forecasting developed by the Program for Regional Observing and Forecasting Services (PROFS); and (3) explain some interesting diagnostic calculations performed by meteorologists of the Wave Propagation Laboratory.

  11. Mesoscale eddies are oases for higher trophic marine life

    KAUST Repository

    Godø, Olav R.

    2012-01-17

    Mesoscale eddies stimulate biological production in the ocean, but knowledge of energy transfers to higher trophic levels within eddies remains fragmented and not quantified. Increasing the knowledge base is constrained by the inability of traditional sampling methods to adequately sample biological processes at the spatio-temporal scales at which they occur. By combining satellite and acoustic observations over spatial scales of 10 s of km horizontally and 100 s of m vertically, supported by hydrographical and biological sampling we show that anticyclonic eddies shape distribution and density of marine life from the surface to bathyal depths. Fish feed along density structures of eddies, demonstrating that eddies catalyze energy transfer across trophic levels. Eddies create attractive pelagic habitats, analogous to oases in the desert, for higher trophic level aquatic organisms through enhanced 3-D motion that accumulates and redistributes biomass, contributing to overall bioproduction in the ocean. Integrating multidisciplinary observation methodologies promoted a new understanding of biophysical interaction in mesoscale eddies. Our findings emphasize the impact of eddies on the patchiness of biomass in the sea and demonstrate that they provide rich feeding habitat for higher trophic marine life. 2012 God et al.

  12. Mesoscale eddies in the Subantarctic Front-Southwest Atlantic

    Directory of Open Access Journals (Sweden)

    Pablo D. Glorioso

    2005-12-01

    Full Text Available Satellite and ship observations in the southern southwest Atlantic (SSWA reveal an intense eddy field and highlight the potential for using continuous real-time satellite altimetry to detect and monitor mesoscale phenomena with a view to understanding the regional circulation. The examples presented suggest that mesoscale eddies are a dominant feature of the circulation and play a fundamental role in the transport of properties along and across the Antarctic Circumpolar Current (ACC. The main ocean current in the SSWA, the Falkland-Malvinas Current (FMC, exhibits numerous embedded eddies south of 50°S which may contribute to the patchiness, transport and mixing of passive scalars by this strong, turbulent current. Large eddies associated with meanders are observed in the ACC fronts, some of them remaining stationary for long periods. Two particular cases are examined using a satellite altimeter in combination with in situ observations, suggesting that cross-frontal eddy transport and strong meandering occur where the ACC flow intensifies along the sub-Antarctic Front (SAF and the Southern ACC Front (SACCF.

  13. Lightning characteristics of derecho producing mesoscale convective systems

    Science.gov (United States)

    Bentley, Mace L.; Franks, John R.; Suranovic, Katelyn R.; Barbachem, Brent; Cannon, Declan; Cooper, Stonie R.

    2016-06-01

    Derechos, or widespread, convectively induced wind storms, are a common warm season phenomenon in the Central and Eastern United States. These damaging and severe weather events are known to sweep quickly across large spatial regions of more than 400 km and produce wind speeds exceeding 121 km h-1. Although extensive research concerning derechos and their parent mesoscale convective systems already exists, there have been few investigations of the spatial and temporal distribution of associated cloud-to-ground lightning with these events. This study analyzes twenty warm season (May through August) derecho events between 2003 and 2013 in an effort to discern their lightning characteristics. Data used in the study included cloud-to-ground flash data derived from the National Lightning Detection Network, WSR-88D imagery from the University Corporation for Atmospheric Research, and damaging wind report data obtained from the Storm Prediction Center. A spatial and temporal analysis was conducted by incorporating these data into a geographic information system to determine the distribution and lightning characteristics of the environments of derecho producing mesoscale convective systems. Primary foci of this research include: (1) finding the approximate size of the lightning activity region for individual and combined event(s); (2) determining the intensity of each event by examining the density and polarity of lightning flashes; (3) locating areas of highest lightning flash density; and (4) to provide a lightning spatial analysis that outlines the temporal and spatial distribution of flash activity for particularly strong derecho producing thunderstorm episodes.

  14. Generating spatial precipitation ensembles: impact of temporal correlation structure

    Science.gov (United States)

    Rakovec, O.; Hazenberg, P.; Torfs, P. J. J. F.; Weerts, A. H.; Uijlenhoet, R.

    2012-09-01

    Sound spatially distributed rainfall fields including a proper spatial and temporal error structure are of key interest for hydrologists to force hydrological models and to identify uncertainties in the simulated and forecasted catchment response. The current paper presents a temporally coherent error identification method based on time-dependent multivariate spatial conditional simulations, which are conditioned on preceding simulations. A sensitivity analysis and real-world experiment are carried out within the hilly region of the Belgian Ardennes. Precipitation fields are simulated for pixels of 10 km × 10 km resolution. Uncertainty analyses in the simulated fields focus on (1) the number of previous simulation hours on which the new simulation is conditioned, (2) the advection speed of the rainfall event, (3) the size of the catchment considered, and (4) the rain gauge density within the catchment. The results for a sensitivity analysis show for typical advection speeds >20 km h-1, no uncertainty is added in terms of across ensemble spread when conditioned on more than one or two previous hourly simulations. However, for the real-world experiment, additional uncertainty can still be added when conditioning on a larger number of previous simulations. This is because for actual precipitation fields, the dynamics exhibit a larger spatial and temporal variability. Moreover, by thinning the observation network with 50%, the added uncertainty increases only slightly and the cross-validation shows that the simulations at the unobserved locations are unbiased. Finally, the first-order autocorrelation coefficients show clear temporal coherence in the time series of the areal precipitation using the time-dependent multivariate conditional simulations, which was not the case using the time-independent univariate conditional simulations. The presented work can be easily implemented within a hydrological calibration and data assimilation framework and can be used as an

  15. Generating spatial precipitation ensembles: impact of temporal correlation structure

    Directory of Open Access Journals (Sweden)

    O. Rakovec

    2012-09-01

    Full Text Available Sound spatially distributed rainfall fields including a proper spatial and temporal error structure are of key interest for hydrologists to force hydrological models and to identify uncertainties in the simulated and forecasted catchment response. The current paper presents a temporally coherent error identification method based on time-dependent multivariate spatial conditional simulations, which are conditioned on preceding simulations. A sensitivity analysis and real-world experiment are carried out within the hilly region of the Belgian Ardennes. Precipitation fields are simulated for pixels of 10 km × 10 km resolution. Uncertainty analyses in the simulated fields focus on (1 the number of previous simulation hours on which the new simulation is conditioned, (2 the advection speed of the rainfall event, (3 the size of the catchment considered, and (4 the rain gauge density within the catchment. The results for a sensitivity analysis show for typical advection speeds >20 km h−1, no uncertainty is added in terms of across ensemble spread when conditioned on more than one or two previous hourly simulations. However, for the real-world experiment, additional uncertainty can still be added when conditioning on a larger number of previous simulations. This is because for actual precipitation fields, the dynamics exhibit a larger spatial and temporal variability. Moreover, by thinning the observation network with 50%, the added uncertainty increases only slightly and the cross-validation shows that the simulations at the unobserved locations are unbiased. Finally, the first-order autocorrelation coefficients show clear temporal coherence in the time series of the areal precipitation using the time-dependent multivariate conditional simulations, which was not the case using the time-independent univariate conditional simulations. The presented work can be easily implemented within a hydrological calibration and data assimilation

  16. A framework for improving a seasonal hydrological forecasting system using sensitivity analysis

    Science.gov (United States)

    Arnal, Louise; Pappenberger, Florian; Smith, Paul; Cloke, Hannah

    2017-04-01

    Seasonal streamflow forecasts are of great value for the socio-economic sector, for applications such as navigation, flood and drought mitigation and reservoir management for hydropower generation and water allocation to agriculture and drinking water. However, as we speak, the performance of dynamical seasonal hydrological forecasting systems (systems based on running seasonal meteorological forecasts through a hydrological model to produce seasonal hydrological forecasts) is still limited in space and time. In this context, the ESP (Ensemble Streamflow Prediction) remains an attractive forecasting method for seasonal streamflow forecasting as it relies on forcing a hydrological model (starting from the latest observed or simulated initial hydrological conditions) with historical meteorological observations. This makes it cheaper to run than a standard dynamical seasonal hydrological forecasting system, for which the seasonal meteorological forecasts will first have to be produced, while still producing skilful forecasts. There is thus the need to focus resources and time towards improvements in dynamical seasonal hydrological forecasting systems which will eventually lead to significant improvements in the skill of the streamflow forecasts generated. Sensitivity analyses are a powerful tool that can be used to disentangle the relative contributions of the two main sources of errors in seasonal streamflow forecasts, namely the initial hydrological conditions (IHC; e.g., soil moisture, snow cover, initial streamflow, among others) and the meteorological forcing (MF; i.e., seasonal meteorological forecasts of precipitation and temperature, input to the hydrological model). Sensitivity analyses are however most useful if they inform and change current operational practices. To this end, we propose a method to improve the design of a seasonal hydrological forecasting system. This method is based on sensitivity analyses, informing the forecasters as to which element of

  17. Quantifying Direct and Indirect Impact of Future Climate on Sub-Arctic Hydrology

    Science.gov (United States)

    Endalamaw, A. M.; Bolton, W. R.; Young-Robertson, J. M.; Morton, D.; Hinzman, L. D.

    2016-12-01

    Projected future climate will have a significant impact on the hydrology of interior Alaskan sub-arctic watersheds, directly though the changes in precipitation and temperature patterns, and indirectly through the cryospheric and ecological impacts. Although the latter is the dominant factor controlling the hydrological processes in the interior Alaska sub-arctic, it is often overlooked in many climate change impact studies. In this study, we aim to quantify and compare the direct and indirect impact of the projected future climate on the hydrology of the interior Alaskan sub-arctic watersheds. The Variable Infiltration Capacity (VIC) meso-scale hydrological model will be implemented to simulate the hydrological processes, including runoff, evapotranspiration, and soil moisture dynamics in the Chena River Basin (area = 5400km2), located in the interior Alaska sub-arctic region. Permafrost and vegetation distribution will be derived from the Geophysical Institute Permafrost Lab (GIPL) model and the Lund-Potsdam-Jena Dynamic Global Model (LPJ) model, respectively. All models will be calibrated and validated using historical data. The Scenario Network for Alaskan and Arctic Planning (SNAP) 5-model average projected climate data products will be used as forcing data for each of these models. The direct impact of climate change on hydrology is estimated using surface parameterization derived from the present day permafrost and vegetation distribution, and future climate forcing from SNAP projected climate data products. Along with the projected future climate, outputs of GIPL and LPJ will be incorporated into the VIC model to estimate the indirect and overall impact of future climate on the hydrology processes in the interior Alaskan sub-arctic watersheds. Finally, we will present the potential hydrological and ecological changes by the end of the 21st century.

  18. Hydrology and Conservation Ecology

    Science.gov (United States)

    Narayanan, M.

    2006-12-01

    Responses to change in the behavior of ecological systems are largely governed by interactions at different levels. Research is essential and is to be necessarily designed to gain insights into various interactions at the community level. Sustainable resource management is only possible if conservation of biodiversity can be accomplished by properly using the knowledge discovered. It is well known that the United States Department of Agriculture provides technical information, resources, and data necessary to assist the researchers in addressing their conservation needs. Conservation aims to protect, preserve and conserve the earth's natural resources. These include, but not limited to the conservation of soil, water, minerals, air, plants and all living beings. The United States Department of Agriculture also encourages farmers and ranchers to voluntarily address threats to soil and water. Protection of wetlands and wildlife habitat has been on the radar screen of conservation experts for a very long time. The main objective has always been to help farmers and landowners conform and comply with federal and state environmental laws. During the implementation phase, farmers should be encouraged to make beneficial, cost-effective changes to methods of irrigation systems. In some cases, the hydrologic regime of the project area can be thought of as principally an issue of river flow regimes for floodplain forests. In this presentation, the author tries to focus on the impact of hydrology and conservation ecology on global warming. He also discusses the impact of hydrology and conservation ecology global air concerns such as greenhouse gas concentrations in the atmosphere. References: Chow, V. T, D. R. Maidment, and L. W. Mays. 1988. Applied Hydrology. McGraw-Hill, Inc. U.S. Soil Conservation Service. Technical Release 55: Urban Hydrology for Small Watersheds. USDA (U.S. Department of Agriculture). June 1986. Lehner, B. and P. Döll (2004). Development and validation

  19. Relating climate change signals and physiographic catchment properties to clustered hydrological response types

    Directory of Open Access Journals (Sweden)

    N. Köplin

    2012-07-01

    Full Text Available We propose an approach to reduce a comprehensive set of 186 mesoscale catchments in Switzerland to fewer response types to climate change and to name sensitive regions as well as catchment characteristics that govern hydrological change. We classified the hydrological responses of our study catchments through an agglomerative-hierarchical cluster analysis, and we related the dominant explanatory variables, i.e. the determining catchment properties and climate change signals, to the catchments' hydrological responses by means of redundancy analysis. All clusters except for one exhibit clearly decreasing summer runoff and increasing winter runoff. This seasonal shift was observed for the near future period (2025–2046 but is particularly obvious in the far future period (2074–2095. Within a certain elevation range (between 1000 and 2500 m a.s.l., the hydrological change is basically a function of elevation, because the latter governs the dominant hydro-climatological processes associated with temperature, e.g. the ratio of liquid to solid precipitation and snow melt processes. For catchments below the stated range, hydrological change is mainly a function of precipitation change, which is not as pronounced as the temperature signal is. Future impact studies in Switzerland can be conducted on a reduced sample of catchments representing the sensitive regions or covering a range of altitudes.

  20. Understanding The Individual Impacts Of Human Interventions And Climate Change On Hydrologic Variables In India

    Science.gov (United States)

    Sharma, T.; Chhabra, S., Jr.; Karmakar, S.; Ghosh, S.

    2015-12-01

    We have quantified the historical climate change and Land Use Land Cover (LULC) change impacts on the hydrologic variables of Indian subcontinent by using Variable Infiltration Capacity (VIC) mesoscale model at 0.5° spatial resolution and daily temporal resolution. The results indicate that the climate change in India has predominating effects on the basic water balance components such as water yield, evapotranspiration and soil moisture. This analysis is with the assumption of naturalised hydrologic cycle, i.e., the impacts of human interventions like construction of controlled (primarily dams, diversions and reservoirs) and water withdrawals structures are not taken into account. The assumption is unrealistic since there are numerous anthropogenic disturbances which result in large changes on vegetation composition and distribution patterns. These activities can directly or indirectly influence the dynamics of water cycle; subsequently affecting the hydrologic processes like plant transpiration, infiltration, evaporation, runoff and sublimation. Here, we have quantified the human interventions by using the reservoir and irrigation module of VIC model which incorporates the irrigation schemes, reservoir characteristics and water withdrawals. The impact of human interventions on hydrologic variables in many grids are found more predominant than climate change and might be detrimental to water resources at regional level. This spatial pattern of impacts will facilitate water manager and planners to design and station hydrologic structures for a sustainable water resources management.

  1. [Socio-hydrology: A review].

    Science.gov (United States)

    Ding, Jing-yi; Zhao, Wen-wu; Fang, Xue-ning

    2015-04-01

    Socio-hydrology is an interdiscipline of hydrology, nature, society and humanity. It mainly explores the two-way feedbacks of coupled human-water system and its dynamic mechanism of co-evolution, and makes efforts to solve the issues that human faces today such as sustainable utilization of water resources. Starting from the background, formation process, and fundamental concept of socio-hydrology, this paper summarized the features of socio-hydrology. The main research content of socio-hydrology was reduced to three aspects: The tradeoff in coupled human-water system, interests in water resources management and virtual water research in coupled human-water system. And its differences as well as relations with traditional hydrology, eco-hydrology and hydro-sociology were dwelled on. Finally, with hope to promote the development of socio-hydrology researches in China, the paper made prospects for the development of the subject from following aspects: Completing academic content and deepening quantitative research, focusing on scale studies of socio-hydrology, fusing socio-hydrology and eco-hydrology.

  2. Understanding ensemble protein folding at atomic detail

    International Nuclear Information System (INIS)

    Wallin, Stefan; Shakhnovich, Eugene I

    2008-01-01

    Although far from routine, simulating the folding of specific short protein chains on the computer, at a detailed atomic level, is starting to become a reality. This remarkable progress, which has been made over the last decade or so, allows a fundamental aspect of the protein folding process to be addressed, namely its statistical nature. In order to make quantitative comparisons with experimental kinetic data a complete ensemble view of folding must be achieved, with key observables averaged over the large number of microscopically different folding trajectories available to a protein chain. Here we review recent advances in atomic-level protein folding simulations and the new insight provided by them into the protein folding process. An important element in understanding ensemble folding kinetics are methods for analyzing many separate folding trajectories, and we discuss techniques developed to condense the large amount of information contained in an ensemble of trajectories into a manageable picture of the folding process. (topical review)

  3. Lattice gauge theory in the microcanonical ensemble

    International Nuclear Information System (INIS)

    Callaway, D.J.E.; Rahman, A.

    1983-01-01

    The microcanonical-ensemble formulation of lattice gauge theory proposed recently is examined in detail. Expectation values in this new ensemble are determined by solving a large set of coupled ordinary differential equations, after the fashion of a molecular dynamics simulation. Following a brief review of the microcanonical ensemble, calculations are performed for the gauge groups U(1), SU(2), and SU(3). The results are compared and contrasted with standard methods of computation. Several advantages of the new formalism are noted. For example, no random numbers are required to update the system. Also, this update is performed in a simultaneous fashion. Thus the microcanonical method presumably adapts well to parallel processing techniques, especially when the p action is highly nonlocal (such as when fermions are included)

  4. Ensemble Network Architecture for Deep Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Xi-liang Chen

    2018-01-01

    Full Text Available The popular deep Q learning algorithm is known to be instability because of the Q-value’s shake and overestimation action values under certain conditions. These issues tend to adversely affect their performance. In this paper, we develop the ensemble network architecture for deep reinforcement learning which is based on value function approximation. The temporal ensemble stabilizes the training process by reducing the variance of target approximation error and the ensemble of target values reduces the overestimate and makes better performance by estimating more accurate Q-value. Our results show that this architecture leads to statistically significant better value evaluation and more stable and better performance on several classical control tasks at OpenAI Gym environment.

  5. Embedded random matrix ensembles in quantum physics

    CERN Document Server

    Kota, V K B

    2014-01-01

    Although used with increasing frequency in many branches of physics, random matrix ensembles are not always sufficiently specific to account for important features of the physical system at hand. One refinement which retains the basic stochastic approach but allows for such features consists in the use of embedded ensembles.  The present text is an exhaustive introduction to and survey of this important field. Starting with an easy-to-read introduction to general random matrix theory, the text then develops the necessary concepts from the beginning, accompanying the reader to the frontiers of present-day research. With some notable exceptions, to date these ensembles have primarily been applied in nuclear spectroscopy. A characteristic example is the use of a random two-body interaction in the framework of the nuclear shell model. Yet, topics in atomic physics, mesoscopic physics, quantum information science and statistical mechanics of isolated finite quantum systems can also be addressed using these ensemb...

  6. Ensemble Kalman methods for inverse problems

    International Nuclear Information System (INIS)

    Iglesias, Marco A; Law, Kody J H; Stuart, Andrew M

    2013-01-01

    The ensemble Kalman filter (EnKF) was introduced by Evensen in 1994 (Evensen 1994 J. Geophys. Res. 99 10143–62) as a novel method for data assimilation: state estimation for noisily observed time-dependent problems. Since that time it has had enormous impact in many application domains because of its robustness and ease of implementation, and numerical evidence of its accuracy. In this paper we propose the application of an iterative ensemble Kalman method for the solution of a wide class of inverse problems. In this context we show that the estimate of the unknown function that we obtain with the ensemble Kalman method lies in a subspace A spanned by the initial ensemble. Hence the resulting error may be bounded above by the error found from the best approximation in this subspace. We provide numerical experiments which compare the error incurred by the ensemble Kalman method for inverse problems with the error of the best approximation in A, and with variants on traditional least-squares approaches, restricted to the subspace A. In so doing we demonstrate that the ensemble Kalman method for inverse problems provides a derivative-free optimization method with comparable accuracy to that achieved by traditional least-squares approaches. Furthermore, we also demonstrate that the accuracy is of the same order of magnitude as that achieved by the best approximation. Three examples are used to demonstrate these assertions: inversion of a compact linear operator; inversion of piezometric head to determine hydraulic conductivity in a Darcy model of groundwater flow; and inversion of Eulerian velocity measurements at positive times to determine the initial condition in an incompressible fluid. (paper)

  7. Hydrological land surface modelling

    DEFF Research Database (Denmark)

    Ridler, Marc-Etienne Francois

    Recent advances in integrated hydrological and soil-vegetation-atmosphere transfer (SVAT) modelling have led to improved water resource management practices, greater crop production, and better flood forecasting systems. However, uncertainty is inherent in all numerical models ultimately leading...... temperature are explored in a multi-objective calibration experiment to optimize the parameters in a SVAT model in the Sahel. The two satellite derived variables were effective at constraining most land-surface and soil parameters. A data assimilation framework is developed and implemented with an integrated...... and disaster management. The objective of this study is to develop and investigate methods to reduce hydrological model uncertainty by using supplementary data sources. The data is used either for model calibration or for model updating using data assimilation. Satellite estimates of soil moisture and surface...

  8. AGU hydrology publication outlets

    Science.gov (United States)

    Freeze, R. Allan

    In recent months I have been approached on several occasions by members of the hydrology community who asked me which of the various AGU journals and publishing outlets would be most suitable for a particular paper or article that they have prepared.Water Resources Research (WRR) is the primary AGU outlet for research papers in hydrology. It is an interdisciplinary journal that integrates research in the social and natural sciences of water. The editors of WRR invite original contributions in the physical, chemical and biological sciences and also in the social and policy sciences, including economics, systems analysis, sociology, and law. The editor for the physical sciences side of the journal is Donald R. Nielson, LAWR Veihmeyer Hall, University of California Davis, Davis, CA 95616. The editor for the policy sciences side of the journal is Ronald G. Cummings, Department of Economics, University of New Mexico, Albuquerque, NM 87131

  9. Deforestation Hydrological Effects

    International Nuclear Information System (INIS)

    Poveda J, G.; Mesa S, O.J.

    1995-01-01

    Deforestation causes strong disturbances in ecosystems and in hydrological cycle, increasing or reducing wealths. Particularly in this work, effects of feed back between interface processes land - atmosphere are discussed and is demonstrated that losses of water by evaporation-transpiration are thoroughly indispensable to maintain the balance of hydrological regime. It's concluded that as a rule the effect of deforestation is to reduce wealth middle and to increase extreme wealth with consequent stronger and more frequent droughts or flood effects. Other deforestation effects as increase in superficial temperature, increase in atmospherical pressure, decrease in soil moisture, decrease in evaporation-transpiration, decrease of soil ruggedness, decrease of thickness of atmospherical cap limit, decrease of clouds, decrease of rain in both medium and long term and the consequent decrease of rivers wealth middle are explained. Of other side, the basins with greater deforestation affectation in Colombia are indicated. Finally, it's demonstrated the need of implementing reforestation programs

  10. Virtual hydrology observatory: an immersive visualization of hydrology modeling

    Science.gov (United States)

    Su, Simon; Cruz-Neira, Carolina; Habib, Emad; Gerndt, Andreas

    2009-02-01

    The Virtual Hydrology Observatory will provide students with the ability to observe the integrated hydrology simulation with an instructional interface by using a desktop based or immersive virtual reality setup. It is the goal of the virtual hydrology observatory application to facilitate the introduction of field experience and observational skills into hydrology courses through innovative virtual techniques that mimic activities during actual field visits. The simulation part of the application is developed from the integrated atmospheric forecast model: Weather Research and Forecasting (WRF), and the hydrology model: Gridded Surface/Subsurface Hydrologic Analysis (GSSHA). Both the output from WRF and GSSHA models are then used to generate the final visualization components of the Virtual Hydrology Observatory. The various visualization data processing techniques provided by VTK are 2D Delaunay triangulation and data optimization. Once all the visualization components are generated, they are integrated into the simulation data using VRFlowVis and VR Juggler software toolkit. VR Juggler is used primarily to provide the Virtual Hydrology Observatory application with fully immersive and real time 3D interaction experience; while VRFlowVis provides the integration framework for the hydrologic simulation data, graphical objects and user interaction. A six-sided CAVETM like system is used to run the Virtual Hydrology Observatory to provide the students with a fully immersive experience.

  11. Cluster ensembles, quantization and the dilogarithm

    DEFF Research Database (Denmark)

    Fock, Vladimir; Goncharov, Alexander B.

    2009-01-01

    A cluster ensemble is a pair of positive spaces (i.e. varieties equipped with positive atlases), coming with an action of a symmetry group . The space is closely related to the spectrum of a cluster algebra [ 12 ]. The two spaces are related by a morphism . The space is equipped with a closed -form......, possibly degenerate, and the space has a Poisson structure. The map is compatible with these structures. The dilogarithm together with its motivic and quantum avatars plays a central role in the cluster ensemble structure. We define a non-commutative -deformation of the -space. When is a root of unity...

  12. Ensemble computing for the petroleum industry

    International Nuclear Information System (INIS)

    Annaratone, M.; Dossa, D.

    1995-01-01

    Computer downsizing is one of the most often used buzzwords in today's competitive business, and the petroleum industry is at the forefront of this revolution. Ensemble computing provides the key for computer downsizing with its first incarnation, i.e., workstation farms. This paper concerns the importance of increasing the productivity cycle and not just the execution time of a job. The authors introduce the concept of ensemble computing and workstation farms. The they discuss how different computing paradigms can be addressed by workstation farms

  13. Thermal-hydrological models

    Energy Technology Data Exchange (ETDEWEB)

    Buscheck, T., LLNL

    1998-04-29

    This chapter describes the physical processes and natural and engineered system conditions that affect thermal-hydrological (T-H) behavior in the unsaturated zone (UZ) at Yucca Mountain and how these effects are represented in mathematical and numerical models that are used to predict T-H conditions in the near field, altered zone, and engineered barrier system (EBS), and on waste package (WP) surfaces.

  14. Nuclear techniques in hydrology

    International Nuclear Information System (INIS)

    Bahadur, J.; Saxena, R.K.

    1974-01-01

    Several types of sealed radioactive sources, stable isotopes and water soluble radioactive tracers, used by different investigators, have been listed for studying the dynamic behaviour of water in nature. In general, all the facets of hydrological cycle, are amenable to these isotopic techniques. It is recommended that environmental isotopes data collection should be started for studying the water balance and also the interrelationships between surface and subsurface water in various rivers catchments with changing physical, geological and climatic parameters. (author)

  15. Dynamically adaptive data-driven simulation of extreme hydrological flows

    Science.gov (United States)

    Kumar Jain, Pushkar; Mandli, Kyle; Hoteit, Ibrahim; Knio, Omar; Dawson, Clint

    2018-02-01

    Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Data-driven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The technology is tested using actual data from the Chile tsunami event of February 27, 2010. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.

  16. Dynamically adaptive data-driven simulation of extreme hydrological flows

    KAUST Repository

    Kumar Jain, Pushkar

    2017-12-27

    Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Data-driven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The technology is tested using actual data from the Chile tsunami event of February 27, 2010. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.

  17. Deep drivers of mesoscale circulation in the central Rockall Trough

    Science.gov (United States)

    Sherwin, T. J.; Alyenik, D.; Dumont, E.; Inall, M.

    2014-11-01

    Mesoscale variability in the central Rockall Trough between about 56 and 58° N has been investigated using a combination of ship-borne, underwater glider and gridded satellite altimeter measurements. Altimeter observations show that mesoscale features such as eddies and large scale circulation cells are ubiquitous phenomena. They have horizontal length scales of order 100 km with vertical scales of over 1000 m and are associated with mean current speeds (over the upper 1000 m) of 15 ± 7 cm s-1. Monthly area averaged surface Eddy Kinetic Energy (EKE) has substantial inter-annual variability, which at times can dominate a mean seasonal signal that varies from a maximum in May (74 cm2 s-2) to a minimum in October (52 cm2 s-2) and has increased gradually since 1992 at about 1.1 cm2 s-2 per year. A five month glider mission in the Trough showed that much of this energy comes from features that are located over 1000 m below the surface in the deep cold waters of the Trough (possibly from eddies associated the North Atlantic Current). The surface currents from altimeters had similar magnitude to the drift currents averaged over 1000 m from the glider in the stratified autumn, but were half the deep water speed during late winter. Although the mesoscale features move in an apparent random manner they may also be quasi-trapped by submarine topography such as seamounts. Occasionally anti-cyclonic and cyclonic cells combine to cause a coherent westward deflection of the European slope current that warms the Rockall side of the Trough. Such deflections contribute to the inter-annual variability in the observed temperature and salinity that are monitored in the upper 800 m of the Trough. By combining glider and altimeter measurements it is shown that altimeter measurements fail to observe a 15 cm s-1 northward flowing slope current on the eastern side and a small persistent southward current on the western side. There is much to be gained from the synergy between satellite

  18. Embedding complex hydrology in the regional climate system – Dynamic coupling across different modelling domains

    DEFF Research Database (Denmark)

    Butts, Michael; Drews, Martin; Larsen, Morten Andreas Dahl

    2014-01-01

    the atmosphere and the groundwater via the land surface and can represent the lateral movement of water in both the surface and subsurface and their interactions, not normally accounted for in climate models. Meso-scale processes are important for climate in general and rainfall in particular. Hydrological......To improve our understanding of the impacts of feedback between the atmosphere and the terrestrial water cycle including groundwater and to improve the integration of water resource management modelling for climate adaption we have developed a dynamically coupled climate–hydrological modelling...... impacts are assessed at the catchment scale, the most important scale for water management. Feedback between groundwater, the land surface and the atmosphere occurs across a range of scales. Recognising this, the coupling was developed to allow dynamic exchange of water and energy at the catchment scale...

  19. A four-stage hybrid model for hydrological time series forecasting.

    Science.gov (United States)

    Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

    2014-01-01

    Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of 'denoising, decomposition and ensemble'. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models.

  20. Evaluation of ensemble precipitation forecasts generated through post-processing in a Canadian catchment

    Directory of Open Access Journals (Sweden)

    S. K. Jha

    2018-03-01

    Full Text Available Flooding in Canada is often caused by heavy rainfall during the snowmelt period. Hydrologic forecast centers rely on precipitation forecasts obtained from numerical weather prediction (NWP models to enforce hydrological models for streamflow forecasting. The uncertainties in raw quantitative precipitation forecasts (QPFs are enhanced by physiography and orography effects over a diverse landscape, particularly in the western catchments of Canada. A Bayesian post-processing approach called rainfall post-processing (RPP, developed in Australia (Robertson et al., 2013; Shrestha et al., 2015, has been applied to assess its forecast performance in a Canadian catchment. Raw QPFs obtained from two sources, Global Ensemble Forecasting System (GEFS Reforecast 2 project, from the National Centers for Environmental Prediction, and Global Deterministic Forecast System (GDPS, from Environment and Climate Change Canada, are used in this study. The study period from January 2013 to December 2015 covered a major flood event in Calgary, Alberta, Canada. Post-processed results show that the RPP is able to remove the bias and reduce the errors of both GEFS and GDPS forecasts. Ensembles generated from the RPP reliably quantify the forecast uncertainty.

  1. Evaluation of ensemble precipitation forecasts generated through post-processing in a Canadian catchment

    Science.gov (United States)

    Jha, Sanjeev K.; Shrestha, Durga L.; Stadnyk, Tricia A.; Coulibaly, Paulin

    2018-03-01

    Flooding in Canada is often caused by heavy rainfall during the snowmelt period. Hydrologic forecast centers rely on precipitation forecasts obtained from numerical weather prediction (NWP) models to enforce hydrological models for streamflow forecasting. The uncertainties in raw quantitative precipitation forecasts (QPFs) are enhanced by physiography and orography effects over a diverse landscape, particularly in the western catchments of Canada. A Bayesian post-processing approach called rainfall post-processing (RPP), developed in Australia (Robertson et al., 2013; Shrestha et al., 2015), has been applied to assess its forecast performance in a Canadian catchment. Raw QPFs obtained from two sources, Global Ensemble Forecasting System (GEFS) Reforecast 2 project, from the National Centers for Environmental Prediction, and Global Deterministic Forecast System (GDPS), from Environment and Climate Change Canada, are used in this study. The study period from January 2013 to December 2015 covered a major flood event in Calgary, Alberta, Canada. Post-processed results show that the RPP is able to remove the bias and reduce the errors of both GEFS and GDPS forecasts. Ensembles generated from the RPP reliably quantify the forecast uncertainty.

  2. Mesoscale Benchmark Demonstration Problem 1: Mesoscale Simulations of Intra-granular Fission Gas Bubbles in UO2 under Post-irradiation Thermal Annealing

    Energy Technology Data Exchange (ETDEWEB)

    Li, Yulan; Hu, Shenyang Y.; Montgomery, Robert; Gao, Fei; Sun, Xin; Tonks, Michael; Biner, Bullent; Millet, Paul; Tikare, Veena; Radhakrishnan, Balasubramaniam; Andersson , David

    2012-04-11

    A study was conducted to evaluate the capabilities of different numerical methods used to represent microstructure behavior at the mesoscale for irradiated material using an idealized benchmark problem. The purpose of the mesoscale benchmark problem was to provide a common basis to assess several mesoscale methods with the objective of identifying the strengths and areas of improvement in the predictive modeling of microstructure evolution. In this work, mesoscale models (phase-field, Potts, and kinetic Monte Carlo) developed by PNNL, INL, SNL, and ORNL were used to calculate the evolution kinetics of intra-granular fission gas bubbles in UO2 fuel under post-irradiation thermal annealing conditions. The benchmark problem was constructed to include important microstructural evolution mechanisms on the kinetics of intra-granular fission gas bubble behavior such as the atomic diffusion of Xe atoms, U vacancies, and O vacancies, the effect of vacancy capture and emission from defects, and the elastic interaction of non-equilibrium gas bubbles. An idealized set of assumptions was imposed on the benchmark problem to simplify the mechanisms considered. The capability and numerical efficiency of different models are compared against selected experimental and simulation results. These comparisons find that the phase-field methods, by the nature of the free energy formulation, are able to represent a larger subset of the mechanisms influencing the intra-granular bubble growth and coarsening mechanisms in the idealized benchmark problem as compared to the Potts and kinetic Monte Carlo methods. It is recognized that the mesoscale benchmark problem as formulated does not specifically highlight the strengths of the discrete particle modeling used in the Potts and kinetic Monte Carlo methods. Future efforts are recommended to construct increasingly more complex mesoscale benchmark problems to further verify and validate the predictive capabilities of the mesoscale modeling

  3. A class of energy-based ensembles in Tsallis statistics

    International Nuclear Information System (INIS)

    Chandrashekar, R; Naina Mohammed, S S

    2011-01-01

    A comprehensive investigation is carried out on the class of energy-based ensembles. The eight ensembles are divided into two main classes. In the isothermal class of ensembles the individual members are at the same temperature. A unified framework is evolved to describe the four isothermal ensembles using the currently accepted third constraint formalism. The isothermal–isobaric, grand canonical and generalized ensembles are illustrated through a study of the classical nonrelativistic and extreme relativistic ideal gas models. An exact calculation is possible only in the case of the isothermal–isobaric ensemble. The study of the ideal gas models in the grand canonical and the generalized ensembles has been carried out using a perturbative procedure with the nonextensivity parameter (1 − q) as the expansion parameter. Though all the thermodynamic quantities have been computed up to a particular order in (1 − q) the procedure can be extended up to any arbitrary order in the expansion parameter. In the adiabatic class of ensembles the individual members of the ensemble have the same value of the heat function and a unified formulation to described all four ensembles is given. The nonrelativistic and the extreme relativistic ideal gases are studied in the isoenthalpic–isobaric ensemble, the adiabatic ensemble with number fluctuations and the adiabatic ensemble with number and particle fluctuations

  4. Parameterization of Mixed Layer and Deep-Ocean Mesoscales Including Nonlinearity

    Science.gov (United States)

    Canuto, V. M.; Cheng, Y.; Dubovikov, M. S.; Howard, A. M.; Leboissetier, A.

    2018-01-01

    In 2011, Chelton et al. carried out a comprehensive census of mesoscales using altimetry data and reached the following conclusions: "essentially all of the observed mesoscale features are nonlinear" and "mesoscales do not move with the mean velocity but with their own drift velocity," which is "the most germane of all the nonlinear metrics."� Accounting for these results in a mesoscale parameterization presents conceptual and practical challenges since linear analysis is no longer usable and one needs a model of nonlinearity. A mesoscale parameterization is presented that has the following features: 1) it is based on the solutions of the nonlinear mesoscale dynamical equations, 2) it describes arbitrary tracers, 3) it includes adiabatic (A) and diabatic (D) regimes, 4) the eddy-induced velocity is the sum of a Gent and McWilliams (GM) term plus a new term representing the difference between drift and mean velocities, 5) the new term lowers the transfer of mean potential energy to mesoscales, 6) the isopycnal slopes are not as flat as in the GM case, 7) deep-ocean stratification is enhanced compared to previous parameterizations where being more weakly stratified allowed a large heat uptake that is not observed, 8) the strength of the Deacon cell is reduced. The numerical results are from a stand-alone ocean code with Coordinated Ocean-Ice Reference Experiment I (CORE-I) normal-year forcing.

  5. Hydrological AnthropoScenes

    Science.gov (United States)

    Cudennec, Christophe

    2016-04-01

    The Anthropocene concept encapsulates the planetary-scale changes resulting from accelerating socio-ecological transformations, beyond the stratigraphic definition actually in debate. The emergence of multi-scale and proteiform complexity requires inter-discipline and system approaches. Yet, to reduce the cognitive challenge of tackling this complexity, the global Anthropocene syndrome must now be studied from various topical points of view, and grounded at regional and local levels. A system approach should allow to identify AnthropoScenes, i.e. settings where a socio-ecological transformation subsystem is clearly coherent within boundaries and displays explicit relationships with neighbouring/remote scenes and within a nesting architecture. Hydrology is a key topical point of view to be explored, as it is important in many aspects of the Anthropocene, either with water itself being a resource, hazard or transport force; or through the network, connectivity, interface, teleconnection, emergence and scaling issues it determines. We will schematically exemplify these aspects with three contrasted hydrological AnthropoScenes in Tunisia, France and Iceland; and reframe therein concepts of the hydrological change debate. Bai X., van der Leeuw S., O'Brien K., Berkhout F., Biermann F., Brondizio E., Cudennec C., Dearing J., Duraiappah A., Glaser M., Revkin A., Steffen W., Syvitski J., 2016. Plausible and desirable futures in the Anthropocene: A new research agenda. Global Environmental Change, in press, http://dx.doi.org/10.1016/j.gloenvcha.2015.09.017 Brondizio E., O'Brien K., Bai X., Biermann F., Steffen W., Berkhout F., Cudennec C., Lemos M.C., Wolfe A., Palma-Oliveira J., Chen A. C-T. Re-conceptualizing the Anthropocene: A call for collaboration. Global Environmental Change, in review. Montanari A., Young G., Savenije H., Hughes D., Wagener T., Ren L., Koutsoyiannis D., Cudennec C., Grimaldi S., Blöschl G., Sivapalan M., Beven K., Gupta H., Arheimer B., Huang Y

  6. Green's Kernels and meso-scale approximations in perforated domains

    CERN Document Server

    Maz'ya, Vladimir; Nieves, Michael

    2013-01-01

    There are a wide range of applications in physics and structural mechanics involving domains with singular perturbations of the boundary. Examples include perforated domains and bodies with defects of different types. The accurate direct numerical treatment of such problems remains a challenge. Asymptotic approximations offer an alternative, efficient solution. Green’s function is considered here as the main object of study rather than a tool for generating solutions of specific boundary value problems. The uniformity of the asymptotic approximations is the principal point of attention. We also show substantial links between Green’s functions and solutions of boundary value problems for meso-scale structures. Such systems involve a large number of small inclusions, so that a small parameter, the relative size of an inclusion, may compete with a large parameter, represented as an overall number of inclusions. The main focus of the present text is on two topics: (a) asymptotics of Green’s kernels in domai...

  7. Development of a parameterization scheme of mesoscale convective systems

    International Nuclear Information System (INIS)

    Cotton, W.R.

    1994-01-01

    The goal of this research is to develop a parameterization scheme of mesoscale convective systems (MCS) including diabatic heating, moisture and momentum transports, cloud formation, and precipitation. The approach is to: Perform explicit cloud-resolving simulation of MCSs; Perform statistical analyses of simulated MCSs to assist in fabricating a parameterization, calibrating coefficients, etc.; Test the parameterization scheme against independent field data measurements and in numerical weather prediction (NWP) models emulating general circulation model (GCM) grid resolution. Thus far we have formulated, calibrated, implemented and tested a deep convective engine against explicit Florida sea breeze convection and in coarse-grid regional simulations of mid-latitude and tropical MCSs. Several explicit simulations of MCSs have been completed, and several other are in progress. Analysis code is being written and run on the explicitly simulated data

  8. Design of a mesoscale continuous flow route towards lithiated methoxyallene.

    Science.gov (United States)

    Seghers, Sofie; Heugebaert, Thomas S A; Moens, Matthias; Sonck, Jolien; Thybaut, Joris; Stevens, Chris Victor

    2018-05-11

    The unique nucleophilic properties of lithiated methoxyallene allow for C-C bond formation with a wide variety of electrophiles, thus introducing an allenic group for further functionalization. This approach has yielded a tremendously broad range of (hetero)cyclic scaffolds, including API precursors. To date, however, its valorization at scale is hampered by the batch synthesis protocol which suffers from serious safety issues. Hence, the attractive heat and mass transfer properties of flow technology were exploited to establish a mesoscale continuous flow route towards lithiated methoxyallene. An excellent conversion of 94% was obtained, corresponding to a methoxyallene throughput of 8.2 g/h. The process is characterized by short reaction times, mild reaction conditions and a stoichiometric use of reagents. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. Advanced mesoscale forecasts of icing events for Gaspe wind farms

    International Nuclear Information System (INIS)

    Gayraud, A.; Benoit, R.; Camion, A.

    2009-01-01

    Atmospheric icing includes every event which causes ice accumulations of various shapes on different structures. In terms of its effects on wind farms, atmospheric icing can decrease the aerodynamic performance, cause structure overloading, and add vibrations leading to failure and breaking. This presentation discussed advanced mesoscale forecasts of icing events for Gaspe wind farms. The context of the study was discussed with particular reference to atmospheric icing; effects on wind farms; and forecast objectives. The presentation also described the models and results of the study. These included MC2, a compressible community model, as well as a Milbrandt and Yau condensation scheme. It was shown that the study has provided good estimates of the duration of events as well as reliable precipitation categories. tabs., figs.

  10. A three-dimensional viscous topography mesoscale model

    Energy Technology Data Exchange (ETDEWEB)

    Eichhorn, J; Flender, M; Kandlbinder, T; Panhans, W G; Trautmann, T; Zdunkowski, W G [Mainz Univ. (Germany). Inst. fuer Physik der Atmosphaere; Cui, K; Ries, R; Siebert, J; Wedi, N

    1997-11-01

    This study describes the theoretical foundation and applications of a newly designed mesoscale model named CLIMM (climate model Mainz). In contrast to terrain following coordinates, a cartesian grid is used to keep the finite difference equations as simple as possible. The method of viscous topography is applied to the flow part of the model. Since the topography intersects the cartesian grid cells, the new concept of boundary weight factors is introduced for the solution of Poisson`s equation. A three-dimensional radiosity model was implemented to handle radiative transfer at the ground. The model is applied to study thermally induced circulations and gravity waves at an idealized mountain. Furthermore, CLIMM was used to simulate typical wind and temperature distributions for the city of Mainz and its rural surroundings. It was found that the model in all cases produced realistic results. (orig.) 38 refs.

  11. Mesoscale simulations of shockwave energy dissipation via chemical reactions.

    Science.gov (United States)

    Antillon, Edwin; Strachan, Alejandro

    2015-02-28

    We use a particle-based mesoscale model that incorporates chemical reactions at a coarse-grained level to study the response of materials that undergo volume-reducing chemical reactions under shockwave-loading conditions. We find that such chemical reactions can attenuate the shockwave and characterize how the parameters of the chemical model affect this behavior. The simulations show that the magnitude of the volume collapse and velocity at which the chemistry propagates are critical to weaken the shock, whereas the energetics in the reactions play only a minor role. Shock loading results in transient states where the material is away from local equilibrium and, interestingly, chemical reactions can nucleate under such non-equilibrium states. Thus, the timescales for equilibration between the various degrees of freedom in the material affect the shock-induced chemistry and its ability to attenuate the propagating shock.

  12. Dynamics of premixed hydrogen/air flames in mesoscale channels

    Energy Technology Data Exchange (ETDEWEB)

    Pizza, Gianmarco [Paul Scherrer Institute, Combustion Research, CH-5232, Villigen PSI (Switzerland); Aerothermochemistry and Combustion Systems Laboratory, Swiss Federal Institute of Technology, CH-8092, Zurich (Switzerland); Frouzakis, Christos E.; Boulouchos, Konstantinos [Aerothermochemistry and Combustion Systems Laboratory, Swiss Federal Institute of Technology, CH-8092, Zurich (Switzerland); Mantzaras, John [Paul Scherrer Institute, Combustion Research, CH-5232, Villigen PSI (Switzerland); Tomboulides, Ananias G. [Department of Engineering and Management of Energy Resources, University of Western Macedonia, 50100 Kozani (Greece)

    2008-10-15

    Direct numerical simulation with detailed chemistry and transport is used to study the stabilization and dynamics of lean ({phi}=0.5) premixed hydrogen/air atmospheric pressure flames in mesoscale planar channels. Channel heights of h=2, 4, and 7 mm, and inflow velocities in the range 0.3{<=}U{sub IN}{<=}1100cm/ s are investigated. Six different burning modes are identified: mild combustion, ignition/extinction, closed steady symmetric flames, open steady symmetric flames, oscillating and, finally, asymmetric flames. Chaotic behavior of cellular flame structures is observed for certain values of U{sub IN}. Stability maps delineating the regions of the different flame types are finally constructed. (author)

  13. Assimilation of Aircraft Observations in High-Resolution Mesoscale Modeling

    Directory of Open Access Journals (Sweden)

    Brian P. Reen

    2018-01-01

    Full Text Available Aircraft-based observations are a promising source of above-surface observations for assimilation into mesoscale model simulations. The Tropospheric Airborne Meteorological Data Reporting (TAMDAR observations have potential advantages over some other aircraft observations including the presence of water vapor observations. The impact of assimilating TAMDAR observations via observation nudging in 1 km horizontal grid spacing Weather Research and Forecasting model simulations is evaluated using five cases centered over California. Overall, the impact of assimilating the observations is mixed, with the layer with the greatest benefit being above the surface in the lowest 1000 m above ground level and the variable showing the most consistent benefit being temperature. Varying the nudging configuration demonstrates the sensitivity of the results to details of the assimilation, but does not clearly demonstrate the superiority of a specific configuration.

  14. Multi-parametric variational data assimilation for hydrological forecasting

    Science.gov (United States)

    Alvarado-Montero, R.; Schwanenberg, D.; Krahe, P.; Helmke, P.; Klein, B.

    2017-12-01

    Ensemble forecasting is increasingly applied in flow forecasting systems to provide users with a better understanding of forecast uncertainty and consequently to take better-informed decisions. A common practice in probabilistic streamflow forecasting is to force deterministic hydrological model with an ensemble of numerical weather predictions. This approach aims at the representation of meteorological uncertainty but neglects uncertainty of the hydrological model as well as its initial conditions. Complementary approaches use probabilistic data assimilation techniques to receive a variety of initial states or represent model uncertainty by model pools instead of single deterministic models. This paper introduces a novel approach that extends a variational data assimilation based on Moving Horizon Estimation to enable the assimilation of observations into multi-parametric model pools. It results in a probabilistic estimate of initial model states that takes into account the parametric model uncertainty in the data assimilation. The assimilation technique is applied to the uppermost area of River Main in Germany. We use different parametric pools, each of them with five parameter sets, to assimilate streamflow data, as well as remotely sensed data from the H-SAF project. We assess the impact of the assimilation in the lead time performance of perfect forecasts (i.e. observed data as forcing variables) as well as deterministic and probabilistic forecasts from ECMWF. The multi-parametric assimilation shows an improvement of up to 23% for CRPS performance and approximately 20% in Brier Skill Scores with respect to the deterministic approach. It also improves the skill of the forecast in terms of rank histogram and produces a narrower ensemble spread.

  15. Dynamics of Clouds and Mesoscale Circulations over the Maritime Continent

    Science.gov (United States)

    Jin, Y.; Wang, S.; Xian, P.; Reid, J. S.; Nachamkin, J.

    2010-12-01

    In recent decades Southeast Asia (SEA) has seen rapid economic growth as well as increased biomass burning, resulting in high air pollution levels and reduced air qual-ity. At the same time clouds often prevent accurate air-quality monitoring and analysis using satellite observations. The Seven SouthEast Asian Studies (7SEAS) field campaign currently underway over SEA provides an unprecedented opportunity to study the com-plex interplay between aerosol and clouds. 7SEAS is a comprehensive interdisciplinary atmospheric sciences program through international partnership of NASA, NRL, ONR and seven local institutions including those from Indonesia, Malaysia, the Philippines, Singapore, Taiwan, Thailand, and Vietnam. While the original goal of 7SEAS is to iso-late the impacts of aerosol particles on weather and the environment, it is recognized that better understanding of SEA meteorological conditions, especially those associated with cloud formation and evolution, is critical to the success of the campaign. In this study we attempt to gain more insight into the dynamic and physical processes associated with low level clouds and atmospheric circulation at the regional scale over SEA, using the Navy’s Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS® ), a regional forecast model in operation at FNMOC since 1998. This effort comprises two main components. First, multiple-years of COAMPS operational forecasts over SEA are analyzed for basic climatology of atmospheric fea-tures. Second, mesoscale circulation and cloud properties are simulated at relatively higher resolution (15-km) for selected periods in the Gulf of Tonkin and adjacent coastal areas. Simulation results are compared to MODIS cloud observations and local sound-ings obtained during 7SEAS for model verifications. Atmospheric boundary layer proc-esses are examined in relation to spatial and temporal variations of cloud fields. The cur-rent work serves as an important step toward improving our

  16. Modification of inertial oscillations by the mesoscale eddy field

    Science.gov (United States)

    Elipot, Shane; Lumpkin, Rick; Prieto, GermáN.

    2010-09-01

    The modification of near-surface near-inertial oscillations (NIOs) by the geostrophic vorticity is studied globally from an observational standpoint. Surface drifter are used to estimate NIO characteristics. Despite its spatial resolution limits, altimetry is used to estimate the geostrophic vorticity. Three characteristics of NIOs are considered: the relative frequency shift with respect to the local inertial frequency; the near-inertial variance; and the inverse excess bandwidth, which is interpreted as a decay time scale. The geostrophic mesoscale flow shifts the frequency of NIOs by approximately half its vorticity. Equatorward of 30°N and S, this effect is added to a global pattern of blue shift of NIOs. While the global pattern of near-inertial variance is interpretable in terms of wind forcing, it is also observed that the geostrophic vorticity organizes the near-inertial variance; it is maximum for near zero values of the Laplacian of the vorticity and decreases for nonzero values, albeit not as much for positive as for negative values. Because the Laplacian of vorticity and vorticity are anticorrelated in the altimeter data set, overall, more near-inertial variance is found in anticyclonic vorticity regions than in cyclonic regions. While this is compatible with anticyclones trapping NIOs, the organization of near-inertial variance by the Laplacian of vorticity is also in very good agreement with previous theoretical and numerical predictions. The inverse bandwidth is a decreasing function of the gradient of vorticity, which acts like the gradient of planetary vorticity to increase the decay of NIOs from the ocean surface. Because the altimetry data set captures the largest vorticity gradients in energetic mesoscale regions, it is also observed that NIOs decay faster in large geostrophic eddy kinetic energy regions.

  17. Optical 3D printing: bridging the gaps in the mesoscale

    Science.gov (United States)

    Jonušauskas, Linas; Juodkazis, Saulius; Malinauskas, Mangirdas

    2018-05-01

    Over the last decade, optical 3D printing has proved itself to be a flexible and capable approach in fabricating an increasing variety of functional structures. One of the main reasons why this technology has become so prominent is the fact that it allows the creation of objects in the mesoscale, where structure dimensions range from nanometers to centimeters. At this scale, the size and spatial configuration of produced single features start to influence the characteristics of the whole object, enabling an array of new, exotic and otherwise unachievable properties and structures (i.e. metamaterials). Here, we present the advantages of this technology in creating mesoscale structures in comparison to subtractive manufacturing techniques and to other branches of 3D printing. Differences between stereolithography, sintering, laser-induced forward transfer and femtosecond laser 3D multi-photon polymerization are highlighted. Attention is given to the discussion of applicable light sources, as well as to an ongoing analysis of the light–matter interaction mechanisms, as they determine the processable materials, required technological steps and the fidelity of feature sizes in fabricated patterns and workpieces. Optical 3D printing-enabled functional structures in micromechanics, medicine, microfluidics, micro-optics and photonics are discussed, with an emphasis on how this particular technology benefits advances in those fields. 4D printing, achieved by varying both the architecture and spatial material composition of the 3D structure, feature-size reduction via stimulated emission depletion-inspired nanolithography or thermal post-treatment, as well as plasmonic nanoparticle-polymer nanocomposites, are presented among examples of the newest trends in the development of this technology. Finally, an outlook is given, examining further scientific frontiers in the field as well as possibilities and challenges in transferring laboratory-level know-how to industrial

  18. Meso-scale modeling of irradiated concrete in test reactor

    International Nuclear Information System (INIS)

    Giorla, A.; Vaitová, M.; Le Pape, Y.; Štemberk, P.

    2015-01-01

    Highlights: • A meso-scale finite element model for irradiated concrete is developed. • Neutron radiation-induced volumetric expansion is a predominant degradation mode. • Confrontation with expansion and damage obtained from experiments is successful. • Effects of paste shrinkage, creep and ductility are discussed. - Abstract: A numerical model accounting for the effects of neutron irradiation on concrete at the mesoscale is detailed in this paper. Irradiation experiments in test reactor (Elleuch et al., 1972), i.e., in accelerated conditions, are simulated. Concrete is considered as a two-phase material made of elastic inclusions (aggregate) subjected to thermal and irradiation-induced swelling and embedded in a cementitious matrix subjected to shrinkage and thermal expansion. The role of the hardened cement paste in the post-peak regime (brittle-ductile transition with decreasing loading rate), and creep effects are investigated. Radiation-induced volumetric expansion (RIVE) of the aggregate cause the development and propagation of damage around the aggregate which further develops in bridging cracks across the hardened cement paste between the individual aggregate particles. The development of damage is aggravated when shrinkage occurs simultaneously with RIVE during the irradiation experiment. The post-irradiation expansion derived from the simulation is well correlated with the experimental data and, the obtained damage levels are fully consistent with previous estimations based on a micromechanical interpretation of the experimental post-irradiation elastic properties (Le Pape et al., 2015). The proposed modeling opens new perspectives for the interpretation of test reactor experiments in regards to the actual operation of light water reactors.

  19. Meso-scale modeling of irradiated concrete in test reactor

    Energy Technology Data Exchange (ETDEWEB)

    Giorla, A. [Oak Ridge National Laboratory, One Bethel Valley Road, Oak Ridge, TN 37831 (United States); Vaitová, M. [Czech Technical University, Thakurova 7, 166 29 Praha 6 (Czech Republic); Le Pape, Y., E-mail: lepapeym@ornl.gov [Oak Ridge National Laboratory, One Bethel Valley Road, Oak Ridge, TN 37831 (United States); Štemberk, P. [Czech Technical University, Thakurova 7, 166 29 Praha 6 (Czech Republic)

    2015-12-15

    Highlights: • A meso-scale finite element model for irradiated concrete is developed. • Neutron radiation-induced volumetric expansion is a predominant degradation mode. • Confrontation with expansion and damage obtained from experiments is successful. • Effects of paste shrinkage, creep and ductility are discussed. - Abstract: A numerical model accounting for the effects of neutron irradiation on concrete at the mesoscale is detailed in this paper. Irradiation experiments in test reactor (Elleuch et al., 1972), i.e., in accelerated conditions, are simulated. Concrete is considered as a two-phase material made of elastic inclusions (aggregate) subjected to thermal and irradiation-induced swelling and embedded in a cementitious matrix subjected to shrinkage and thermal expansion. The role of the hardened cement paste in the post-peak regime (brittle-ductile transition with decreasing loading rate), and creep effects are investigated. Radiation-induced volumetric expansion (RIVE) of the aggregate cause the development and propagation of damage around the aggregate which further develops in bridging cracks across the hardened cement paste between the individual aggregate particles. The development of damage is aggravated when shrinkage occurs simultaneously with RIVE during the irradiation experiment. The post-irradiation expansion derived from the simulation is well correlated with the experimental data and, the obtained damage levels are fully consistent with previous estimations based on a micromechanical interpretation of the experimental post-irradiation elastic properties (Le Pape et al., 2015). The proposed modeling opens new perspectives for the interpretation of test reactor experiments in regards to the actual operation of light water reactors.

  20. Air Pollutant Distribution and Mesoscale Circulation Systems During Escompte

    Science.gov (United States)

    Kottmeier, Ch.; Kalthoff, N.; Corsmeier, U.; Robin, D.; Thürauf, J.; Hofherr, T.; Hasel, M.

    The distribution of pollutants observed with an Dornier 128 instrumented aircraft and from AIRMARAIX ground stations during one day of the Escompte experiment (June 25, 2001) is analysed in relation to the mesoscale wind systems and vertical mixing from aircraft and radiosonde data. The ESCOMPTE-experiment (http://medias.obs- mip.fr/escompte) was carried out in June and July 2001 in the urban area of Marseille and its rural surroundings to investigate periods with photosmog conditions. The over- all aim is to produce an appropriate high quality 3-D data set which includes emission, meteorological, and chemical data. The data is used for the validation of mesoscale models and for chemical and meteorological process studies. The evolution of pho- tosmog episodes with high ozone concentrations depends on both chemical transfor- mation processes and meteorological conditions. As Marseille is situated between the Mediterranean Sea in the south and mountainous sites in the north, under weak large- scale flow the meteorological conditions are dominated by thermally driven circula- tion systems which strongly influence the horizontal transport of air pollutants. Ad- ditionally, vertically exchange processes like mountain venting and slope winds may contribute in the temporal evolution of the trace gas concentration of the city plume in the atmospheric boundary layer and are particularly studied by the Dornier flight measurements. Therefore the experiment was designed to measure both, the chemi- cal species and meteorological parameters with high resolution in space and time by surface stations, aircraft and vertical profiling systems like radiosondes, sodars and lidars. Results are shown (a) on the evolution of the wind field and the ozone concen- trations during June 25, when an ozone maximum develops about 60 km in the lee site of Marseille and (b) the vertical transport of air pollutants between the boundary layer and the free troposphere.

  1. An application of ensemble/multi model approach for wind power production forecast.

    Science.gov (United States)

    Alessandrini, S.; Decimi, G.; Hagedorn, R.; Sperati, S.

    2010-09-01

    The wind power forecast of the 3 days ahead period are becoming always more useful and important in reducing the problem of grid integration and energy price trading due to the increasing wind power penetration. Therefore it's clear that the accuracy of this forecast is one of the most important requirements for a successful application. The wind power forecast is based on a mesoscale meteorological models that provides the 3 days ahead wind data. A Model Output Statistic correction is then performed to reduce systematic error caused, for instance, by a wrong representation of surface roughness or topography in the meteorological models. The corrected wind data are then used as input in the wind farm power curve to obtain the power forecast. These computations require historical time series of wind measured data (by an anemometer located in the wind farm or on the nacelle) and power data in order to be able to perform the statistical analysis on the past. For this purpose a Neural Network (NN) is trained on the past data and then applied in the forecast task. Considering that the anemometer measurements are not always available in a wind farm a different approach has also been adopted. A training of the NN to link directly the forecasted meteorological data and the power data has also been performed. The normalized RMSE forecast error seems to be lower in most cases by following the second approach. We have examined two wind farms, one located in Denmark on flat terrain and one located in a mountain area in the south of Italy (Sicily). In both cases we compare the performances of a prediction based on meteorological data coming from a single model with those obtained by using two or more models (RAMS, ECMWF deterministic, LAMI, HIRLAM). It is shown that the multi models approach reduces the day-ahead normalized RMSE forecast error of at least 1% compared to the singles models approach. Moreover the use of a deterministic global model, (e.g. ECMWF deterministic

  2. A method for ensemble wildland fire simulation

    Science.gov (United States)

    Mark A. Finney; Isaac C. Grenfell; Charles W. McHugh; Robert C. Seli; Diane Trethewey; Richard D. Stratton; Stuart Brittain

    2011-01-01

    An ensemble simulation system that accounts for uncertainty in long-range weather conditions and two-dimensional wildland fire spread is described. Fuel moisture is expressed based on the energy release component, a US fire danger rating index, and its variation throughout the fire season is modeled using time series analysis of historical weather data. This analysis...

  3. The Phantasmagoria of Competition in School Ensembles

    Science.gov (United States)

    Abramo, Joseph Michael

    2017-01-01

    Participation in competition festivals--where students and ensembles compete against each other for high scores and accolades--is a widespread practice in North American formal music education. In this article, I use Marx's theories of labor, value, and phantasmagoria to suggest a capitalist logic that structures these competitions. Marx's…

  4. Ensembl Genomes 2016: more genomes, more complexity.

    Science.gov (United States)

    Kersey, Paul Julian; Allen, James E; Armean, Irina; Boddu, Sanjay; Bolt, Bruce J; Carvalho-Silva, Denise; Christensen, Mikkel; Davis, Paul; Falin, Lee J; Grabmueller, Christoph; Humphrey, Jay; Kerhornou, Arnaud; Khobova, Julia; Aranganathan, Naveen K; Langridge, Nicholas; Lowy, Ernesto; McDowall, Mark D; Maheswari, Uma; Nuhn, Michael; Ong, Chuang Kee; Overduin, Bert; Paulini, Michael; Pedro, Helder; Perry, Emily; Spudich, Giulietta; Tapanari, Electra; Walts, Brandon; Williams, Gareth; Tello-Ruiz, Marcela; Stein, Joshua; Wei, Sharon; Ware, Doreen; Bolser, Daniel M; Howe, Kevin L; Kulesha, Eugene; Lawson, Daniel; Maslen, Gareth; Staines, Daniel M

    2016-01-04

    Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of programmatic and interactive interfaces to a rich range of data including reference sequence, gene models, transcriptional data, genetic variation and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments. These include the development of new analyses and views to represent polyploid genomes (of which bread wheat is the primary exemplar); and the continued up-scaling of the resource, which now includes over 23 000 bacterial genomes, 400 fungal genomes and 100 protist genomes, in addition to 55 genomes from invertebrate metazoa and 39 genomes from plants. This dramatic increase in the number of included genomes is one part of a broader effort to automate the integration of archival data (genome sequence, but also associated RNA sequence data and variant calls) within the context of reference genomes and make it available through the Ensembl user interfaces. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  5. NYYD Ensemble ja Riho Sibul / Anneli Remme

    Index Scriptorium Estoniae

    Remme, Anneli, 1968-

    2001-01-01

    Gavin Bryarsi teos "Jesus' Blood Never Failed Me Yet" NYYD Ensemble'i ja Riho Sibula esituses 27. detsembril Pauluse kirikus Tartus ja 28. detsembril Rootsi- Mihkli kirikus Tallinnas. Kaastegevad Tartu Ülikooli Kammerkoor (Tartus) ja kammerkoor Voces Musicales (Tallinnas). Kunstiline juht Olari Elts

  6. Conductor gestures influence evaluations of ensemble performance

    Directory of Open Access Journals (Sweden)

    Steven eMorrison

    2014-07-01

    Full Text Available Previous research has found that listener evaluations of ensemble performances vary depending on the expressivity of the conductor’s gestures, even when performances are otherwise identical. It was the purpose of the present study to test whether this effect of visual information was evident in the evaluation of specific aspects of ensemble performance, articulation and dynamics. We constructed a set of 32 music performances that combined auditory and visual information and were designed to feature a high degree of contrast along one of two target characteristics: articulation and dynamics. We paired each of four music excerpts recorded by a chamber ensemble in both a high- and low-contrast condition with video of four conductors demonstrating high- and low-contrast gesture specifically appropriate to either articulation or dynamics. Using one of two equivalent test forms, college music majors and nonmajors (N = 285 viewed sixteen 30-second performances and evaluated the quality of the ensemble’s articulation, dynamics, technique and tempo along with overall expressivity. Results showed significantly higher evaluations for performances featuring high rather than low conducting expressivity regardless of the ensemble’s performance quality. Evaluations for both articulation and dynamics were strongly and positively correlated with evaluations of overall ensemble expressivity.

  7. Genetic Algorithm Optimized Neural Networks Ensemble as ...

    African Journals Online (AJOL)

    NJD

    Improvements in neural network calibration models by a novel approach using neural network ensemble (NNE) for the simultaneous ... process by training a number of neural networks. .... Matlab® version 6.1 was employed for building principal component ... provide a fair simulation of calibration data set with some degree.

  8. A Theoretical Analysis of Why Hybrid Ensembles Work

    Directory of Open Access Journals (Sweden)

    Kuo-Wei Hsu

    2017-01-01

    Full Text Available Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithms to create a hybrid ensemble. Why does such an ensemble work? The question remains. Following the concept of diversity, which is one of the fundamental elements of the success of ensembles, we conduct a theoretical analysis of why hybrid ensembles work, connecting using different algorithms to accuracy gain. We also conduct experiments on classification performance of hybrid ensembles of classifiers created by decision tree and naïve Bayes classification algorithms, each of which is a top data mining algorithm and often used to create non-hybrid ensembles. Therefore, through this paper, we provide a complement to the theoretical foundation of creating and using hybrid ensembles.

  9. Ensemble-based Kalman Filters in Strongly Nonlinear Dynamics

    Institute of Scientific and Technical Information of China (English)

    Zhaoxia PU; Joshua HACKER

    2009-01-01

    This study examines the effectiveness of ensemble Kalman filters in data assimilation with the strongly nonlinear dynamics of the Lorenz-63 model, and in particular their use in predicting the regime transition that occurs when the model jumps from one basin of attraction to the other. Four configurations of the ensemble-based Kalman filtering data assimilation techniques, including the ensemble Kalman filter, ensemble adjustment Kalman filter, ensemble square root filter and ensemble transform Kalman filter, are evaluated with their ability in predicting the regime transition (also called phase transition) and also are compared in terms of their sensitivity to both observational and sampling errors. The sensitivity of each ensemble-based filter to the size of the ensemble is also examined.

  10. Ensemble of classifiers based network intrusion detection system performance bound

    CSIR Research Space (South Africa)

    Mkuzangwe, Nenekazi NP

    2017-11-01

    Full Text Available This paper provides a performance bound of a network intrusion detection system (NIDS) that uses an ensemble of classifiers. Currently researchers rely on implementing the ensemble of classifiers based NIDS before they can determine the performance...

  11. Global Ensemble Forecast System (GEFS) [2.5 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...

  12. Major Risks, Uncertain Outcomes: Making Ensemble Forecasts Work for Multiple Audiences

    Science.gov (United States)

    Semmens, K. A.; Montz, B.; Carr, R. H.; Maxfield, K.; Ahnert, P.; Shedd, R.; Elliott, J.

    2017-12-01

    When extreme river levels are possible in a community, effective communication of weather and hydrologic forecasts is critical to protect life and property. Residents, emergency personnel, and water resource managers need to make timely decisions about how and when to prepare. Uncertainty in forecasting is a critical component of this decision-making, but often poses a confounding factor for public and professional understanding of forecast products. In 2016 and 2017, building on previous research about the use of uncertainty forecast products, and with funding from NOAA's CSTAR program, East Carolina University and Nurture Nature Center (a non-profit organization with a focus on flooding issues, based in Easton, PA) conducted a research project to understand how various audiences use and interpret ensemble forecasts showing a range of hydrologic forecast possibilities. These audiences include community residents, emergency managers and water resource managers. The research team held focus groups in Jefferson County, WV and Frederick County, MD, to test a new suite of products from the National Weather Service's Hydrologic Ensemble Forecast System (HEFS). HEFS is an ensemble system that provides short and long-range forecasts, ranging from 6 hours to 1 year, showing uncertainty in hydrologic forecasts. The goal of the study was to assess the utility of the HEFS products, identify the barriers to proper understanding of the products, and suggest modifications to product design that could improve the understandability and accessibility for residential, emergency managers, and water resource managers. The research team worked with the Sterling, VA Weather Forecast Office and the Middle Atlantic River Forecast center to develop a weather scenario as the basis of the focus group discussions, which also included pre and post session surveys. This presentation shares the findings from those focus group discussions and surveys, including recommendations for revisions to

  13. HEPS4Power - Extended-range Hydrometeorological Ensemble Predictions for Improved Hydropower Operations and Revenues

    Science.gov (United States)

    Bogner, Konrad; Monhart, Samuel; Liniger, Mark; Spririg, Christoph; Jordan, Fred; Zappa, Massimiliano

    2015-04-01

    In recent years large progresses have been achieved in the operational prediction of floods and hydrological drought with up to ten days lead time. Both the public and the private sectors are currently using probabilistic runoff forecast in order to monitoring water resources and take actions when critical conditions are to be expected. The use of extended-range predictions with lead times exceeding 10 days is not yet established. The hydropower sector in particular might have large benefits from using hydro meteorological forecasts for the next 15 to 60 days in order to optimize the operations and the revenues from their watersheds, dams, captions, turbines and pumps. The new Swiss Competence Centers in Energy Research (SCCER) targets at boosting research related to energy issues in Switzerland. The objective of HEPS4POWER is to demonstrate that operational extended-range hydro meteorological forecasts have the potential to become very valuable tools for fine tuning the production of energy from hydropower systems. The project team covers a specific system-oriented value chain starting from the collection and forecast of meteorological data (MeteoSwiss), leading to the operational application of state-of-the-art hydrological models (WSL) and terminating with the experience in data presentation and power production forecasts for end-users (e-dric.ch). The first task of the HEPS4POWER will be the downscaling and post-processing of ensemble extended-range meteorological forecasts (EPS). The goal is to provide well-tailored forecasts of probabilistic nature that should be reliable in statistical and localized at catchment or even station level. The hydrology related task will consist in feeding the post-processed meteorological forecasts into a HEPS using a multi-model approach by implementing models with different complexity. Also in the case of the hydrological ensemble predictions, post-processing techniques need to be tested in order to improve the quality of the

  14. Using ensemble forecasting for wind power

    Energy Technology Data Exchange (ETDEWEB)

    Giebel, G.; Landberg, L.; Badger, J. [Risoe National Lab., Roskilde (Denmark); Sattler, K.

    2003-07-01

    Short-term prediction of wind power has a long tradition in Denmark. It is an essential tool for the operators to keep the grid from becoming unstable in a region like Jutland, where more than 27% of the electricity consumption comes from wind power. This means that the minimum load is already lower than the maximum production from wind energy alone. Danish utilities have therefore used short-term prediction of wind energy since the mid-90ies. However, the accuracy is still far from being sufficient in the eyes of the utilities (used to have load forecasts accurate to within 5% on a one-week horizon). The Ensemble project tries to alleviate the dependency of the forecast quality on one model by using multiple models, and also will investigate the possibilities of using the model spread of multiple models or of dedicated ensemble runs for a prediction of the uncertainty of the forecast. Usually, short-term forecasting works (especially for the horizon beyond 6 hours) by gathering input from a Numerical Weather Prediction (NWP) model. This input data is used together with online data in statistical models (this is the case eg in Zephyr/WPPT) to yield the output of the wind farms or of a whole region for the next 48 hours (only limited by the NWP model horizon). For the accuracy of the final production forecast, the accuracy of the NWP prediction is paramount. While many efforts are underway to increase the accuracy of the NWP forecasts themselves (which ultimately are limited by the amount of computing power available, the lack of a tight observational network on the Atlantic and limited physics modelling), another approach is to use ensembles of different models or different model runs. This can be either an ensemble of different models output for the same area, using different data assimilation schemes and different model physics, or a dedicated ensemble run by a large institution, where the same model is run with slight variations in initial conditions and

  15. Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing

    KAUST Repository

    Toye, Habib; Zhan, Peng; Gopalakrishnan, Ganesh; Kartadikaria, Aditya R.; Huang, Huang; Knio, Omar; Hoteit, Ibrahim

    2017-01-01

    We present our efforts to build an ensemble data assimilation and forecasting system for the Red Sea. The system consists of the high-resolution Massachusetts Institute of Technology general circulation model (MITgcm) to simulate ocean circulation

  16. Robust Ensemble Filtering and Its Relation to Covariance Inflation in the Ensemble Kalman Filter

    KAUST Repository

    Luo, Xiaodong; Hoteit, Ibrahim

    2011-01-01

    A robust ensemble filtering scheme based on the H∞ filtering theory is proposed. The optimal H∞ filter is derived by minimizing the supremum (or maximum) of a predefined cost function, a criterion different from the minimum variance used

  17. Climate Change Impacts on the Upper Indus Hydrology: Sources, Shifts and Extremes.

    Directory of Open Access Journals (Sweden)

    A F Lutz

    Full Text Available The Indus basin heavily depends on its upstream mountainous part for the downstream supply of water while downstream demands are high. Since downstream demands will likely continue to increase, accurate hydrological projections for the future supply are important. We use an ensemble of statistically downscaled CMIP5 General Circulation Model outputs for RCP4.5 and RCP8.5 to force a cryospheric-hydrological model and generate transient hydrological projections for the entire 21st century for the upper Indus basin. Three methodological advances are introduced: (i A new precipitation dataset that corrects for the underestimation of high-altitude precipitation is used. (ii The model is calibrated using data on river runoff, snow cover and geodetic glacier mass balance. (iii An advanced statistical downscaling technique is used that accounts for changes in precipitation extremes. The analysis of the results focuses on changes in sources of runoff, seasonality and hydrological extremes. We conclude that the future of the upper Indus basin's water availability is highly uncertain in the long run, mainly due to the large spread in the future precipitation projections. Despite large uncertainties in the future climate and long-term water availability, basin-wide patterns and trends of seasonal shifts in water availability are consistent across climate change scenarios. Most prominent is the attenuation of the annual hydrograph and shift from summer peak flow towards the other seasons for most ensemble members. In addition there are distinct spatial patterns in the response that relate to monsoon influence and the importance of meltwater. Analysis of future hydrological extremes reveals that increases in intensity and frequency of extreme discharges are very likely for most of the upper Indus basin and most ensemble members.

  18. Climate Change Impacts on the Upper Indus Hydrology: Sources, Shifts and Extremes

    Science.gov (United States)

    Immerzeel, W. W.; Kraaijenbrink, P. D. A.; Shrestha, A. B.; Bierkens, M. F. P.

    2016-01-01

    The Indus basin heavily depends on its upstream mountainous part for the downstream supply of water while downstream demands are high. Since downstream demands will likely continue to increase, accurate hydrological projections for the future supply are important. We use an ensemble of statistically downscaled CMIP5 General Circulation Model outputs for RCP4.5 and RCP8.5 to force a cryospheric-hydrological model and generate transient hydrological projections for the entire 21st century for the upper Indus basin. Three methodological advances are introduced: (i) A new precipitation dataset that corrects for the underestimation of high-altitude precipitation is used. (ii) The model is calibrated using data on river runoff, snow cover and geodetic glacier mass balance. (iii) An advanced statistical downscaling technique is used that accounts for changes in precipitation extremes. The analysis of the results focuses on changes in sources of runoff, seasonality and hydrological extremes. We conclude that the future of the upper Indus basin’s water availability is highly uncertain in the long run, mainly due to the large spread in the future precipitation projections. Despite large uncertainties in the future climate and long-term water availability, basin-wide patterns and trends of seasonal shifts in water availability are consistent across climate change scenarios. Most prominent is the attenuation of the annual hydrograph and shift from summer peak flow towards the other seasons for most ensemble members. In addition there are distinct spatial patterns in the response that relate to monsoon influence and the importance of meltwater. Analysis of future hydrological extremes reveals that increases in intensity and frequency of extreme discharges are very likely for most of the upper Indus basin and most ensemble members. PMID:27828994

  19. Climate Change Impacts on the Upper Indus Hydrology: Sources, Shifts and Extremes.

    Science.gov (United States)

    Lutz, A F; Immerzeel, W W; Kraaijenbrink, P D A; Shrestha, A B; Bierkens, M F P

    2016-01-01

    The Indus basin heavily depends on its upstream mountainous part for the downstream supply of water while downstream demands are high. Since downstream demands will likely continue to increase, accurate hydrological projections for the future supply are important. We use an ensemble of statistically downscaled CMIP5 General Circulation Model outputs for RCP4.5 and RCP8.5 to force a cryospheric-hydrological model and generate transient hydrological projections for the entire 21st century for the upper Indus basin. Three methodological advances are introduced: (i) A new precipitation dataset that corrects for the underestimation of high-altitude precipitation is used. (ii) The model is calibrated using data on river runoff, snow cover and geodetic glacier mass balance. (iii) An advanced statistical downscaling technique is used that accounts for changes in precipitation extremes. The analysis of the results focuses on changes in sources of runoff, seasonality and hydrological extremes. We conclude that the future of the upper Indus basin's water availability is highly uncertain in the long run, mainly due to the large spread in the future precipitation projections. Despite large uncertainties in the future climate and long-term water availability, basin-wide patterns and trends of seasonal shifts in water availability are consistent across climate change scenarios. Most prominent is the attenuation of the annual hydrograph and shift from summer peak flow towards the other seasons for most ensemble members. In addition there are distinct spatial patterns in the response that relate to monsoon influence and the importance of meltwater. Analysis of future hydrological extremes reveals that increases in intensity and frequency of extreme discharges are very likely for most of the upper Indus basin and most ensemble members.

  20. Regionalization of meso-scale physically based nitrogen modeling outputs to the macro-scale by the use of regression trees

    Science.gov (United States)

    Künne, A.; Fink, M.; Kipka, H.; Krause, P.; Flügel, W.-A.

    2012-06-01

    In this paper, a method is presented to estimate excess nitrogen on large scales considering single field processes. The approach was implemented by using the physically based model J2000-S to simulate the nitrogen balance as well as the hydrological dynamics within meso-scale test catchments. The model input data, the parameterization, the results and a detailed system understanding were used to generate the regression tree models with GUIDE (Loh, 2002). For each landscape type in the federal state of Thuringia a regression tree was calibrated and validated using the model data and results of excess nitrogen from the test catchments. Hydrological parameters such as precipitation and evapotranspiration were also used to predict excess nitrogen by the regression tree model. Hence they had to be calculated and regionalized as well for the state of Thuringia. Here the model J2000g was used to simulate the water balance on the macro scale. With the regression trees the excess nitrogen was regionalized for each landscape type of Thuringia. The approach allows calculating the potential nitrogen input into the streams of the drainage area. The results show that the applied methodology was able to transfer the detailed model results of the meso-scale catchments to the entire state of Thuringia by low computing time without losing the detailed knowledge from the nitrogen transport modeling. This was validated with modeling results from Fink (2004) in a catchment lying in the regionalization area. The regionalized and modeled excess nitrogen correspond with 94%. The study was conducted within the framework of a project in collaboration with the Thuringian Environmental Ministry, whose overall aim was to assess the effect of agro-environmental measures regarding load reduction in the water bodies of Thuringia to fulfill the requirements of the European Water Framework Directive (Bäse et al., 2007; Fink, 2006; Fink et al., 2007).