Tsunami Modeling and Prediction Using a Data Assimilation Technique with Kalman Filters

Science.gov (United States)

Barnier, G.; Dunham, E. M.

2016-12-01

Earthquake-induced tsunamis cause dramatic damages along densely populated coastlines. It is difficult to predict and anticipate tsunami waves in advance, but if the earthquake occurs far enough from the coast, there may be enough time to evacuate the zones at risk. Therefore, any real-time information on the tsunami wavefield (as it propagates towards the coast) is extremely valuable for early warning systems. After the 2011 Tohoku earthquake, a dense tsunami-monitoring network (S-net) based on cabled ocean-bottom pressure sensors has been deployed along the Pacific coast in Northeastern Japan. Maeda et al. (GRL, 2015) introduced a data assimilation technique to reconstruct the tsunami wavefield in real time by combining numerical solution of the shallow water wave equations with additional terms penalizing the numerical solution for not matching observations. The penalty or gain matrix is determined though optimal interpolation and is independent of time. Here we explore a related data assimilation approach using the Kalman filter method to evolve the gain matrix. While more computationally expensive, the Kalman filter approach potentially provides more accurate reconstructions. We test our method on a 1D tsunami model derived from the Kozdon and Dunham (EPSL, 2014) dynamic rupture simulations of the 2011 Tohoku earthquake. For appropriate choices of model and data covariance matrices, the method reconstructs the tsunami wavefield prior to wave arrival at the coast. We plan to compare the Kalman filter method to the optimal interpolation method developed by Maeda et al. (GRL, 2015) and then to implement the method for 2D.

The use of satellite data assimilation methods in regional NWP for solar irradiance forecasting

Science.gov (United States)

Kurzrock, Frederik; Cros, Sylvain; Chane-Ming, Fabrice; Potthast, Roland; Linguet, Laurent; Sébastien, Nicolas

2016-04-01

As an intermittent energy source, the injection of solar power into electricity grids requires irradiance forecasting in order to ensure grid stability. On time scales of more than six hours ahead, numerical weather prediction (NWP) is recognized as the most appropriate solution. However, the current representation of clouds in NWP models is not sufficiently precise for an accurate forecast of solar irradiance at ground level. Dynamical downscaling does not necessarily increase the quality of irradiance forecasts. Furthermore, incorrectly simulated cloud evolution is often the cause of inaccurate atmospheric analyses. In non-interconnected tropical areas, the large amplitudes of solar irradiance variability provide abundant solar yield but present significant problems for grid safety. Irradiance forecasting is particularly important for solar power stakeholders in these regions where PV electricity penetration is increasing. At the same time, NWP is markedly more challenging in tropic areas than in mid-latitudes due to the special characteristics of tropical homogeneous convective air masses. Numerous data assimilation methods and strategies have evolved and been applied to a large variety of global and regional NWP models in the recent decades. Assimilating data from geostationary meteorological satellites is an appropriate approach. Indeed, models converting radiances measured by satellites into cloud properties already exist. Moreover, data are available at high temporal frequencies, which enable a pertinent cloud cover evolution modelling for solar energy forecasts. In this work, we present a survey of different approaches which aim at improving cloud cover forecasts using the assimilation of geostationary meteorological satellite data into regional NWP models. Various approaches have been applied to a variety of models and satellites and in different regions of the world. Current methods focus on the assimilation of cloud-top information, derived from infrared

Four-Dimensional Data Assimilation Using the Adjoint Method

Science.gov (United States)

Bao, Jian-Wen

The calculus of variations is used to confirm that variational four-dimensional data assimilation (FDDA) using the adjoint method can be implemented when the numerical model equations have a finite number of first-order discontinuous points. These points represent the on/off switches associated with physical processes, for which the Jacobian matrix of the model equation does not exist. Numerical evidence suggests that, in some situations when the adjoint method is used for FDDA, the temperature field retrieved using horizontal wind data is numerically not unique. A physical interpretation of this type of non-uniqueness of the retrieval is proposed in terms of energetics. The adjoint equations of a numerical model can also be used for model-parameter estimation. A general computational procedure is developed to determine the size and distribution of any internal model parameter. The procedure is then applied to a one-dimensional shallow -fluid model in the context of analysis-nudging FDDA: the weighting coefficients used by the Newtonian nudging technique are determined. The sensitivity of these nudging coefficients to the optimal objectives and constraints is investigated. Experiments of FDDA using the adjoint method are conducted using the dry version of the hydrostatic Penn State/NCAR mesoscale model (MM4) and its adjoint. The minimization procedure converges and the initialization experiment is successful. Temperature-retrieval experiments involving an assimilation of the horizontal wind are also carried out using the adjoint of MM4.

Rainfall assimilation in RAMS by means of the Kuo parameterisation inversion: method and preliminary results

Science.gov (United States)

Orlandi, A.; Ortolani, A.; Meneguzzo, F.; Levizzani, V.; Torricella, F.; Turk, F. J.

2004-03-01

In order to improve high-resolution forecasts, a specific method for assimilating rainfall rates into the Regional Atmospheric Modelling System model has been developed. It is based on the inversion of the Kuo convective parameterisation scheme. A nudging technique is applied to 'gently' increase with time the weight of the estimated precipitation in the assimilation process. A rough but manageable technique is explained to estimate the partition of convective precipitation from stratiform one, without requiring any ancillary measurement. The method is general purpose, but it is tuned for geostationary satellite rainfall estimation assimilation. Preliminary results are presented and discussed, both through totally simulated experiments and through experiments assimilating real satellite-based precipitation observations. For every case study, Rainfall data are computed with a rapid update satellite precipitation estimation algorithm based on IR and MW satellite observations. This research was carried out in the framework of the EURAINSAT project (an EC research project co-funded by the Energy, Environment and Sustainable Development Programme within the topic 'Development of generic Earth observation technologies', Contract number EVG1-2000-00030).

A composite state method for ensemble data assimilation with multiple limited-area models

Directory of Open Access Journals (Sweden)

Matthew Kretschmer

2015-04-01

Full Text Available Limited-area models (LAMs allow high-resolution forecasts to be made for geographic regions of interest when resources are limited. Typically, boundary conditions for these models are provided through one-way boundary coupling from a coarser resolution global model. Here, data assimilation is considered in a situation in which a global model supplies boundary conditions to multiple LAMs. The data assimilation method presented combines information from all of the models to construct a single ‘composite state’, on which data assimilation is subsequently performed. The analysis composite state is then used to form the initial conditions of the global model and all of the LAMs for the next forecast cycle. The method is tested by using numerical experiments with simple, chaotic models. The results of the experiments show that there is a clear forecast benefit to allowing LAM states to influence one another during the analysis. In addition, adding LAM information at analysis time has a strong positive impact on global model forecast performance, even at points not covered by the LAMs.

DARLA: Data Assimilation and Remote Sensing for Littoral Applications

Science.gov (United States)

Jessup, A.; Holman, R. A.; Chickadel, C.; Elgar, S.; Farquharson, G.; Haller, M. C.; Kurapov, A. L.; Özkan-Haller, H. T.; Raubenheimer, B.; Thomson, J. M.

2012-12-01

DARLA is 5-year collaborative project that couples state-of-the-art remote sensing and in situ measurements with advanced data assimilation (DA) modeling to (a) evaluate and improve remote sensing retrieval algorithms for environmental parameters, (b) determine the extent to which remote sensing data can be used in place of in situ data in models, and (c) infer bathymetry for littoral environments by combining remotely-sensed parameters and data assimilation models. The project uses microwave, electro-optical, and infrared techniques to characterize the littoral ocean with a focus on wave and current parameters required for DA modeling. In conjunction with the RIVET (River and Inlets) Project, extensive in situ measurements provide ground truth for both the remote sensing retrieval algorithms and the DA modeling. Our goal is to use remote sensing to constrain data assimilation models of wave and circulation dynamics in a tidal inlet and surrounding beaches. We seek to improve environmental parameter estimation via remote sensing fusion, determine the success of using remote sensing data to drive DA models, and produce a dynamically consistent representation of the wave, circulation, and bathymetry fields in complex environments. The objectives are to test the following three hypotheses: 1. Environmental parameter estimation using remote sensing techniques can be significantly improved by fusion of multiple sensor products. 2. Data assimilation models can be adequately constrained (i.e., forced or guided) with environmental parameters derived from remote sensing measurements. 3. Bathymetry on open beaches, river mouths, and at tidal inlets can be inferred from a combination of remotely-sensed parameters and data assimilation models. Our approach is to conduct a series of field experiments combining remote sensing and in situ measurements to investigate signature physics and to gather data for developing and testing DA models. A preliminary experiment conducted at

A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

Science.gov (United States)

Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

2011-01-01

Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

Data Assimilation within the Advanced Circulation (ADCIRC) Modeling Framework for Hurricane Storm Surge Forecasting

KAUST Repository

Butler, T.; Altaf, Muhammad; Dawson, C.; Hoteit, Ibrahim; Luo, X.; Mayo, T.

2012-01-01

levels, and wave heights—during these extreme events. This type of data, if available in real time, could be used in a data assimilation framework to improve hurricane storm surge forecasts. In this paper a data assimilation methodology for storm surge

Nonlinear error dynamics for cycled data assimilation methods

International Nuclear Information System (INIS)

Moodey, Alexander J F; Lawless, Amos S; Potthast, Roland W E; Van Leeuwen, Peter Jan

2013-01-01

We investigate the error dynamics for cycled data assimilation systems, such that the inverse problem of state determination is solved at t k , k = 1, 2, 3, …, with a first guess given by the state propagated via a dynamical system model M k from time t k−1 to time t k . In particular, for nonlinear dynamical systems M k that are Lipschitz continuous with respect to their initial states, we provide deterministic estimates for the development of the error ‖e k ‖ ≔ ‖x (a) k − x (t) k ‖ between the estimated state x (a) and the true state x (t) over time. Clearly, observation error of size δ > 0 leads to an estimation error in every assimilation step. These errors can accumulate, if they are not (a) controlled in the reconstruction and (b) damped by the dynamical system M k under consideration. A data assimilation method is called stable, if the error in the estimate is bounded in time by some constant C. The key task of this work is to provide estimates for the error ‖e k ‖, depending on the size δ of the observation error, the reconstruction operator R α , the observation operator H and the Lipschitz constants K (1) and K (2) on the lower and higher modes of M k controlling the damping behaviour of the dynamics. We show that systems can be stabilized by choosing α sufficiently small, but the bound C will then depend on the data error δ in the form c‖R α ‖δ with some constant c. Since ‖R α ‖ → ∞ for α → 0, the constant might be large. Numerical examples for this behaviour in the nonlinear case are provided using a (low-dimensional) Lorenz ‘63 system. (paper)

Water vapor estimation using digital terrestrial broadcasting waves

Science.gov (United States)

Kawamura, S.; Ohta, H.; Hanado, H.; Yamamoto, M. K.; Shiga, N.; Kido, K.; Yasuda, S.; Goto, T.; Ichikawa, R.; Amagai, J.; Imamura, K.; Fujieda, M.; Iwai, H.; Sugitani, S.; Iguchi, T.

2017-03-01

A method of estimating water vapor (propagation delay due to water vapor) using digital terrestrial broadcasting waves is proposed. Our target is to improve the accuracy of numerical weather forecast for severe weather phenomena such as localized heavy rainstorms in urban areas through data assimilation. In this method, we estimate water vapor near a ground surface from the propagation delay of digital terrestrial broadcasting waves. A real-time delay measurement system with a software-defined radio technique is developed and tested. The data obtained using digital terrestrial broadcasting waves show good agreement with those obtained by ground-based meteorological observation. The main features of this observation are, no need for transmitters (receiving only), applicable wherever digital terrestrial broadcasting is available and its high time resolution. This study shows a possibility to estimate water vapor using digital terrestrial broadcasting waves. In the future, we will investigate the impact of these data toward numerical weather forecast through data assimilation. Developing a system that monitors water vapor near the ground surface with time and space resolutions of 30 s and several kilometers would improve the accuracy of the numerical weather forecast of localized severe weather phenomena.

Data Assimilation in Integrated and Distributed Hydrological Models

DEFF Research Database (Denmark)

Zhang, Donghua

processes and provide simulations in refined temporal and spatial resolutions. Recent developments in measurement and sensor technologies have significantly improved the coverage, quality, frequency and diversity of hydrological observations. Data assimilation provides a great potential in relation...... point of view, different assimilation methodologies and techniques have been developed or customized to better serve hydrological assimilation. From the application point of view, real data and real-world complex catchments are used with the focus of investigating the models’ improvements with data...... a variety of model uncertainty sources and scales. Next the groundwater head assimilation experiment was tested in a much more complex catchment with assimilation of biased real observations. In such cases, the bias-aware assimilation method significantly outperforms the standard assimilation method...

Impact of assimilation window length on diurnal features in a Mars atmospheric analysis

Directory of Open Access Journals (Sweden)

Yongjing Zhao

2015-05-01

Full Text Available Effective simulation of diurnal variability is an important aspect of many geophysical data assimilation systems. For the Martian atmosphere, thermal tides are particularly prominent and contribute much to the Martian atmospheric circulation, dynamics and dust transport. To study the Mars diurnal variability and Mars thermal tides, the Geophysical Fluid Dynamics Laboratory Mars Global Climate Model with the 4D-local ensemble transform Kalman filter (4D-LETKF is used to perform an analysis assimilating spacecraft temperature retrievals. We find that the use of a ‘traditional’ 6-hr assimilation cycle induces spurious forcing of a resonantly enhanced semi-diurnal Kelvin waves represented in both surface pressure and mid-level temperature by forming a wave 4 pattern in the diurnal averaged analysis increment that acts as a ‘topographic’ stationary forcing. Different assimilation window lengths in the 4D-LETKF are introduced to remove the artificially induced resonance. It is found that short assimilation window lengths not only remove the spurious resonance, but also push the migrating semi-diurnal temperature variation at 50 Pa closer to the estimated ‘true’ tides even in the absence of a radiatively active water ice cloud parameterisation. In order to compare the performance of different assimilation window lengths, short-term to mid-range forecasts based on the hour 00 and 12 assimilation are evaluated and compared. Results show that during Northern Hemisphere summer, it is not the assimilation window length, but the radiatively active water ice clouds that influence the model prediction. A ‘diurnal bias correction’ that includes bias correction fields dependent on the local time is shown to effectively reduce the forecast root mean square differences between forecasts and observations, compensate for the absence of water ice cloud parameterisation and enhance Martian atmosphere prediction. The implications of these results for

A balanced Kalman filter ocean data assimilation system with application to the South Australian Sea

Science.gov (United States)

Li, Yi; Toumi, Ralf

2017-08-01

In this paper, an Ensemble Kalman Filter (EnKF) based regional ocean data assimilation system has been developed and applied to the South Australian Sea. This system consists of the data assimilation algorithm provided by the NCAR Data Assimilation Research Testbed (DART) and the Regional Ocean Modelling System (ROMS). We describe the first implementation of the physical balance operator (temperature-salinity, hydrostatic and geostrophic balance) to DART, to reduce the spurious waves which may be introduced during the data assimilation process. The effect of the balance operator is validated in both an idealised shallow water model and the ROMS model real case study. In the shallow water model, the geostrophic balance operator eliminates spurious ageostrophic waves and produces a better sea surface height (SSH) and velocity analysis and forecast. Its impact increases as the sea surface height and wind stress increase. In the real case, satellite-observed sea surface temperature (SST) and SSH are assimilated in the South Australian Sea with 50 ensembles using the Ensemble Adjustment Kalman Filter (EAKF). Assimilating SSH and SST enhances the estimation of SSH and SST in the entire domain, respectively. Assimilation with the balance operator produces a more realistic simulation of surface currents and subsurface temperature profile. The best improvement is obtained when only SSH is assimilated with the balance operator. A case study with a storm suggests that the benefit of the balance operator is of particular importance under high wind stress conditions. Implementing the balance operator could be a general benefit to ocean data assimilation systems.

A statistical data assimilation method for seasonal streamflow forecasting to optimize hydropower reservoir management in data-scarce regions

Science.gov (United States)

Arsenault, R.; Mai, J.; Latraverse, M.; Tolson, B.

2017-12-01

Probabilistic ensemble forecasts generated by the ensemble streamflow prediction (ESP) methodology are subject to biases due to errors in the hydrological model's initial states. In day-to-day operations, hydrologists must compensate for discrepancies between observed and simulated states such as streamflow. However, in data-scarce regions, little to no information is available to guide the streamflow assimilation process. The manual assimilation process can then lead to more uncertainty due to the numerous options available to the forecaster. Furthermore, the model's mass balance may be compromised and could affect future forecasts. In this study we propose a data-driven approach in which specific variables that may be adjusted during assimilation are defined. The underlying principle was to identify key variables that would be the most appropriate to modify during streamflow assimilation depending on the initial conditions such as the time period of the assimilation, the snow water equivalent of the snowpack and meteorological conditions. The variables to adjust were determined by performing an automatic variational data assimilation on individual (or combinations of) model state variables and meteorological forcing. The assimilation aimed to simultaneously optimize: (1) the error between the observed and simulated streamflow at the timepoint where the forecasts starts and (2) the bias between medium to long-term observed and simulated flows, which were simulated by running the model with the observed meteorological data on a hindcast period. The optimal variables were then classified according to the initial conditions at the time period where the forecast is initiated. The proposed method was evaluated by measuring the average electricity generation of a hydropower complex in Québec, Canada driven by this method. A test-bed which simulates the real-world assimilation, forecasting, water release optimization and decision-making of a hydropower cascade was

Studying the properties of Variational Data Assimilation Methods by Applying a Set of Test-Examples

DEFF Research Database (Denmark)

Thomsen, Per Grove; Zlatev, Zahari

2007-01-01

and backward computations are carried out by using the model under consideration and its adjoint equations (both the model and its adjoint are defined by systems of differential equations). The major difficulty is caused by the huge increase of the computational load (normally by a factor more than 100...... assimilation method (numerical algorithms for solving differential equations, splitting procedures and optimization algorithms) have been studied by using these tests. The presentation will include results from testing carried out in the study.......he variational data assimilation methods can successfully be used in different fields of science and engineering. An attempt to utilize available sets of observations in the efforts to improve (i) the models used to study different phenomena (ii) the model results is systematically carried out when...

Data assimilation the ensemble Kalman filter

CERN Document Server

Evensen, Geir

2007-01-01

Data Assimilation comprehensively covers data assimilation and inverse methods, including both traditional state estimation and parameter estimation. This text and reference focuses on various popular data assimilation methods, such as weak and strong constraint variational methods and ensemble filters and smoothers. It is demonstrated how the different methods can be derived from a common theoretical basis, as well as how they differ and/or are related to each other, and which properties characterize them, using several examples. Rather than emphasize a particular discipline such as oceanography or meteorology, it presents the mathematical framework and derivations in a way which is common for any discipline where dynamics is merged with measurements. The mathematics level is modest, although it requires knowledge of basic spatial statistics, Bayesian statistics, and calculus of variations. Readers will also appreciate the introduction to the mathematical methods used and detailed derivations, which should b...

Development and validation of a system of assimilation indices: A mixed method approach to understand change in psychotherapy.

Science.gov (United States)

Neto, David D; Baptista, Telmo M; Dent-Brown, Kim

2015-06-01

Assimilation is an important process in understanding change in psychotherapy. Similar to other psychological processes, assimilation may be traceable in the speech of clients by attending to its signs or indices. In the present research, we aimed to build a system of indices of assimilation. This research follows a mixed method design. The indices were derived through qualitative analysis, using grounded theory. Subsequently, the indices were adjusted quantitatively and applied to 30 single psychotherapy sessions of adult clients with depression and 11 therapists. Forty-two indices were found and grouped into the following five process categories of assimilation: external distress, pain, noticing, decentring and action. The indices showed good inter-rater reliability and internal consistency. Except for noticing, all process categories correlated significantly with each other according to conceptual proximity. The system of indices also showed convergent validity with an existing coding system of assimilation for two process categories. The results suggest that the system of indices is a useful approach for understanding assimilation. The consideration of assimilation in a continuous fashion through sub-processes may help to extend our knowledge of this process and provide a tool for clinical practice. Assimilation is an important process in understanding change in psychotherapy in the sense that it takes into account insight and action-related processes. Clients convey in their speech signs or indices of the assimilation process which can be observed both in the style and content of their utterances. Using these indices, therapists can continuously assess assimilation and use this information in choosing interventions. Limitations: This study follows a cross-sectional design and does not allow consideration of the predictive value of the indices. The outcome of the therapy was not taken into account, which restricts validity considerations to the comparison with

Efficient data assimilation algorithm for bathymetry application

Science.gov (United States)

Ghorbanidehno, H.; Lee, J. H.; Farthing, M.; Hesser, T.; Kitanidis, P. K.; Darve, E. F.

2017-12-01

Information on the evolving state of the nearshore zone bathymetry is crucial to shoreline management, recreational safety, and naval operations. The high cost and complex logistics of using ship-based surveys for bathymetry estimation have encouraged the use of remote sensing techniques. Data assimilation methods combine the remote sensing data and nearshore hydrodynamic models to estimate the unknown bathymetry and the corresponding uncertainties. In particular, several recent efforts have combined Kalman Filter-based techniques such as ensembled-based Kalman filters with indirect video-based observations to address the bathymetry inversion problem. However, these methods often suffer from ensemble collapse and uncertainty underestimation. Here, the Compressed State Kalman Filter (CSKF) method is used to estimate the bathymetry based on observed wave celerity. In order to demonstrate the accuracy and robustness of the CSKF method, we consider twin tests with synthetic observations of wave celerity, while the bathymetry profiles are chosen based on surveys taken by the U.S. Army Corps of Engineer Field Research Facility (FRF) in Duck, NC. The first test case is a bathymetry estimation problem for a spatially smooth and temporally constant bathymetry profile. The second test case is a bathymetry estimation problem for a temporally evolving bathymetry from a smooth to a non-smooth profile. For both problems, we compare the results of CSKF with those obtained by the local ensemble transform Kalman filter (LETKF), which is a popular ensemble-based Kalman filter method.

Assimilative and non-assimilative color spreading in the watercolor configuration

Directory of Open Access Journals (Sweden)

Eiji eKimura

2014-09-01

Full Text Available A colored line flanking a darker contour will appear to spread its color onto an area enclosed by the line (watercolor effect. The watercolor effect has been characterized as an assimilative effect, but non-assimilative color spreading has also been demonstrated in the same spatial configuration; e.g., when a black inner contour (IC is paired with a blue outer contour (OC, yellow color spreading can be observed. To elucidate visual mechanisms underlying these different color spreading effects, this study investigated the effects of luminance ratio between the double contours on the induced color by systematically manipulating the IC and OC luminances (Experiment 1 as well as the background luminance (Experiment 2. The results showed that the luminance conditions suitable for assimilative and non-assimilative color spreading were nearly opposite. When the Weber contrast of the IC to the background luminances (IC contrast was smaller than that of the OC (OC contrast, the induced color became similar to the IC color (assimilative spreading. In contrast, when the OC contrast was smaller than or equal to the IC contrast, the induced color became yellow (non-assimilative spreading. Extending these findings, Experiment 3 showed that bilateral color spreading, e.g., assimilative spreading on one side and non-assimilative spreading on the other side, can also be observed in the watercolor configuration. These results suggest that the assimilative and non-assimilative spreading were mediated by different visual mechanisms. The properties of the assimilative spreading are consistent with the model proposed to account for neon color spreading [Grossberg, S. & Mingolla, E. (1985 Percept. Psychophys., 38, 141-171] and extended for the watercolor effect [Pinna, B., & Grossberg, S. (2005 J. Opt. Soc. Am. A, 22, 2207-2221]. However, the present results suggest that additional mechanisms are needed to account for the non-assimilative color spreading.

Assimilative and non-assimilative color spreading in the watercolor configuration.

Science.gov (United States)

Kimura, Eiji; Kuroki, Mikako

2014-01-01

A colored line flanking a darker contour will appear to spread its color onto an area enclosed by the line (watercolor effect). The watercolor effect has been characterized as an assimilative effect, but non-assimilative color spreading has also been demonstrated in the same spatial configuration; e.g., when a black inner contour (IC) is paired with a blue outer contour (OC), yellow color spreading can be observed. To elucidate visual mechanisms underlying these different color spreading effects, this study investigated the effects of luminance ratio between the double contours on the induced color by systematically manipulating the IC and the OC luminance (Experiment 1) as well as the background luminance (Experiment 2). The results showed that the luminance conditions suitable for assimilative and non-assimilative color spreading were nearly opposite. When the Weber contrast of the IC to the background luminance (IC contrast) was smaller in size than that of the OC (OC contrast), the induced color became similar to the IC color (assimilative spreading). In contrast, when the OC contrast was smaller than or equal to the IC contrast, the induced color became yellow (non-assimilative spreading). Extending these findings, Experiment 3 showed that bilateral color spreading, i.e., assimilative spreading on one side and non-assimilative spreading on the other side, can also be observed in the watercolor configuration. These results suggest that the assimilative and the non-assimilative spreading were mediated by different visual mechanisms. The properties of the assimilative spreading are consistent with the model proposed to account for neon color spreading (Grossberg and Mingolla, 1985) and extended for the watercolor effect (Pinna and Grossberg, 2005). However, the present results suggest that additional mechanisms are needed to account for the non-assimilative color spreading.

The effects of tropical wind data on the prediction of ultralong waves

Science.gov (United States)

Baker, W. E.

1981-01-01

The influence of tropical wind data on the prediction of planetary waves were studied. Two assimilation experiments were performed, one with and one without FGGE tropical winds. The planetary wave error was then analyzed in 72 h forecasts from the initial conditions provided by the two assimilations.

Assimilation of total lightning data using the three-dimensional variational method at convection-allowing resolution

Science.gov (United States)

Zhang, Rong; Zhang, Yijun; Xu, Liangtao; Zheng, Dong; Yao, Wen

2017-08-01

A large number of observational analyses have shown that lightning data can be used to indicate areas of deep convection. It is important to assimilate observed lightning data into numerical models, so that more small-scale information can be incorporated to improve the quality of the initial condition and the subsequent forecasts. In this study, the empirical relationship between flash rate, water vapor mixing ratio, and graupel mixing ratio was used to adjust the model relative humidity, which was then assimilated by using the three-dimensional variational data assimilation system of the Weather Research and Forecasting model in cycling mode at 10-min intervals. To find the appropriate assimilation time-window length that yielded significant improvement in both the initial conditions and subsequent forecasts, four experiments with different assimilation time-window lengths were conducted for a squall line case that occurred on 10 July 2007 in North China. It was found that 60 min was the appropriate assimilation time-window length for this case, and longer assimilation window length was unnecessary since no further improvement was present. Forecasts of 1-h accumulated precipitation during the assimilation period and the subsequent 3-h accumulated precipitation were significantly improved compared with the control experiment without lightning data assimilation. The simulated reflectivity was optimal after 30 min of the forecast, it remained optimal during the following 42 min, and the positive effect from lightning data assimilation began to diminish after 72 min of the forecast. Overall, the improvement from lightning data assimilation can be maintained for about 3 h.

Synthesis, properties, and assimilation methods of aluminium hydride

International Nuclear Information System (INIS)

Mirsaidov, U.M.

2013-01-01

We have discovered a new source of aluminium hydride-conversion of tetrahydrofurane under influence of halogenous alkyls. We have proposed the chlorbenzene method of synthesis of AlH 3 , which excludes adhesion and ensure high quality of the product with respect to its purity, thermal stability, habits of crystals (round shape), and granulometric composition. We determined capability of benzyl chloride to fix AlH 4 -groups by the way of complexes formation. This allows increasing efficient concentration of AlH 3 solutions and their productivity. We have carried out 'direct' crystallization of aluminium hydride in one stage using interaction of binary metal hydride with aluminium chloride in the medium of ether-toluene at 60-100 d ig C a nd using solvent distillation. In the reaction of Li H with AlCl 3 , we achieved output of pure crystal AlH 3 of hexagonal modification, which was close to quantitative. We have discovered the assimilation methods of aluminium hydride in carrying out of solid-phase chemical reactions. (author)

High-frequency Rayleigh-wave method

Science.gov (United States)

Xia, J.; Miller, R.D.; Xu, Y.; Luo, Y.; Chen, C.; Liu, J.; Ivanov, J.; Zeng, C.

2009-01-01

High-frequency (???2 Hz) Rayleigh-wave data acquired with a multichannel recording system have been utilized to determine shear (S)-wave velocities in near-surface geophysics since the early 1980s. This overview article discusses the main research results of high-frequency surface-wave techniques achieved by research groups at the Kansas Geological Survey and China University of Geosciences in the last 15 years. The multichannel analysis of surface wave (MASW) method is a non-invasive acoustic approach to estimate near-surface S-wave velocity. The differences between MASW results and direct borehole measurements are approximately 15% or less and random. Studies show that simultaneous inversion with higher modes and the fundamental mode can increase model resolution and an investigation depth. The other important seismic property, quality factor (Q), can also be estimated with the MASW method by inverting attenuation coefficients of Rayleigh waves. An inverted model (S-wave velocity or Q) obtained using a damped least-squares method can be assessed by an optimal damping vector in a vicinity of the inverted model determined by an objective function, which is the trace of a weighted sum of model-resolution and model-covariance matrices. Current developments include modeling high-frequency Rayleigh-waves in near-surface media, which builds a foundation for shallow seismic or Rayleigh-wave inversion in the time-offset domain; imaging dispersive energy with high resolution in the frequency-velocity domain and possibly with data in an arbitrary acquisition geometry, which opens a door for 3D surface-wave techniques; and successfully separating surface-wave modes, which provides a valuable tool to perform S-wave velocity profiling with high-horizontal resolution. ?? China University of Geosciences (Wuhan) and Springer-Verlag GmbH 2009.

Accelerating assimilation development for new observing systems using EFSO

Science.gov (United States)

Lien, Guo-Yuan; Hotta, Daisuke; Kalnay, Eugenia; Miyoshi, Takemasa; Chen, Tse-Chun

2018-03-01

To successfully assimilate data from a new observing system, it is necessary to develop appropriate data selection strategies, assimilating only the generally useful data. This development work is usually done by trial and error using observing system experiments (OSEs), which are very time and resource consuming. This study proposes a new, efficient methodology to accelerate the development using ensemble forecast sensitivity to observations (EFSO). First, non-cycled assimilation of the new observation data is conducted to compute EFSO diagnostics for each observation within a large sample. Second, the average EFSO conditionally sampled in terms of various factors is computed. Third, potential data selection criteria are designed based on the non-cycled EFSO statistics, and tested in cycled OSEs to verify the actual assimilation impact. The usefulness of this method is demonstrated with the assimilation of satellite precipitation data. It is shown that the EFSO-based method can efficiently suggest data selection criteria that significantly improve the assimilation results.

Recent Updates to SWANFAR (registered trademark), a 5DVAR Data Assimilation System for SWAN

Science.gov (United States)

2016-11-10

inside surf zone. Blue, red, and black lines illustrate heights of small, medium, and large waves as they approach shore (from right to left). If...small, medium, or large offshore waves. Only assimilation from outside the surf zone (such as within the dashed box region) will accu- rately reflect...involv- ing a systematic and consistent examination of much larger global wave datasets and many more model simulations at global , regional, and local

Improvement of basal conditions knowledge in Antarctica using data assimilation methods

Science.gov (United States)

Mosbeux, C.; Gillet-Chaulet, F.; Gagliardini, O.

2017-12-01

The current global warming seems to have direct consequences on ice-sheet mass loss. Unfortunately, as highlighted in the last IPCC report, current ice-sheets models face several difficulties in assessing the future evolution of the dynamics of ice sheets for the next century. Indeed, projections are still plagued with high uncertainties partially due to the poor representation of occurring physical processes, but also due to the poor initialisation of ice flow models. More specifically, simulations are very sensitive to initial parameters such as the basal friction between ice-sheet and bedrock and the bedrock topography which are still badly known because of a lack of direct observations or large uncertainty on measurements. Improving the knowledge of these two parameters in Greenland and Antarctica is therefore a prerequisite for making reliable projections. Data assimilation methods have been developed in order to overcome this problem such as the Bayesian approach of Pralong and Gudmundsson (2009) or the adjoint method tested by Goldberg and Heimbach (2013) and Perego et al. (2014). The present work is based on two different assimilation algorithms to better constrain both basal drag and bedrock elevation parameters. The first algorithm is entirely based on the adjoint method while the second one uses an iterative method coupling inversion of basal friction based on an adjoint method and through an inversion of bedrock topography using a nudging method. Both algorithms have been implemented in the finite element ice sheet and ice flow model Elmer/Ice and have been tested in a twin experiment showing a clear improvement of both parameters knowledge (Mosbeux et al., 2016). Here, the methods are applied to a real 3D case in East Antarctica and with an ensemble method approach. The application of both algorithms reduces the uncertainty on basal conditions, for instance by providing more details to the basal geometry when compared to usual DEM. Moreover, as in the

A data assimilation tool for the Pagasitikos Gulf ecosystem dynamics: Methods and benefits

KAUST Repository

Korres, Gerasimos

2012-06-01

Within the framework of the European INSEA project, an advanced assimilation system has been implemented for the Pagasitikos Gulf ecosystem. The system is based on a multivariate sequential data assimilation scheme that combines satellite ocean sea color (chlorophyll-a) data with the predictions of a three-dimensional coupled physical-biochemical model of the Pagasitikos Gulf ecosystem presented in a companion paper. The hydrodynamics are solved with a very high resolution (1/100°) implementation of the Princeton Ocean Model (POM). This model is nested within a coarser resolution model of the Aegean Sea which is part of the Greek POSEIDON forecasting system. The forecast of the Aegean Sea model, itself nested and initialized from a Mediterranean implementation of POM, is also used to periodically re-initalize the Pagatisikos hydrodynamics model using variational initialization techniques. The ecosystem dynamics of Pagasitikos are tackled with a stand-alone implementation of the European Seas Ecosystem Model (ERSEM). The assimilation scheme is based on the Singular Evolutive Extended Kalman (SEEK) filter, in which the error statistics are parameterized by means of a suitable set of Empirical Orthogonal Functions (EOFs).The assimilation experiments were performed for year 2003 and additionally for a 9-month period over 2006 during which the physical model was forced with the POSEIDON-ETA 6-hour atmospheric fields. The assimilation system is validated by assessing the relevance of the system in fitting the data, the impact of the assimilation on non-observed biochemical processes and the overall quality of the forecasts. Assimilation of either GlobColour in 2003 or SeaWiFS in 2006 chlorophyll-a data enhances the identification of the ecological state of the Pagasitikos Gulf. Results, however, suggest that subsurface ecological observations are needed to improve the controllability of the ecosystem in the deep layers. © 2011 Elsevier B.V.

Assimilation of SAPHIR radiance: impact on hyperspectral radiances in 4D-VAR

Science.gov (United States)

Indira Rani, S.; Doherty, Amy; Atkinson, Nigel; Bell, William; Newman, Stuart; Renshaw, Richard; George, John P.; Rajagopal, E. N.

2016-04-01

Assimilation of a new observation dataset in an NWP system may affect the quality of an existing observation data set against the model background (short forecast), which in-turn influence the use of an existing observation in the NWP system. Effect of the use of one data set on the use of another data set can be quantified as positive, negative or neutral. Impact of the addition of new dataset is defined as positive if the number of assimilated observations of an existing type of observation increases, and bias and standard deviation decreases compared to the control (without the new dataset) experiment. Recently a new dataset, Megha Tropiques SAPHIR radiances, which provides atmospheric humidity information, is added in the Unified Model 4D-VAR assimilation system. In this paper we discuss the impact of SAPHIR on the assimilation of hyper-spectral radiances like AIRS, IASI and CrIS. Though SAPHIR is a Microwave instrument, its impact can be clearly seen in the use of hyper-spectral radiances in the 4D-VAR data assimilation systems in addition to other Microwave and InfraRed observation. SAPHIR assimilation decreased the standard deviation of the spectral channels of wave number from 650 -1600 cm-1 in all the three hyperspectral radiances. Similar impact on the hyperspectral radiances can be seen due to the assimilation of other Microwave radiances like from AMSR2 and SSMIS Imager.

Effective Assimilation of Global Precipitation

Science.gov (United States)

Lien, G.; Kalnay, E.; Miyoshi, T.; Huffman, G. J.

2012-12-01

Assimilating precipitation observations by modifying the moisture and sometimes temperature profiles has been shown successful in forcing the model precipitation to be close to the observed precipitation, but only while the assimilation is taking place. After the forecast start, the model tends to "forget" the assimilation changes and lose their extra skill after few forecast hours. This suggests that this approach is not an efficient way to modify the potential vorticity field, since this is the variable that the model would remember. In this study, the ensemble Kalman filter (EnKF) method is used to effectively change the potential vorticity field by allowing ensemble members with better precipitation to receive higher weights. In addition to using an EnKF, two other changes in the precipitation assimilation process are proposed to solve the problems related to the highly non-Gaussian nature of the precipitation variable: a) transform precipitation into a Gaussian distribution based on its climatological distribution, and b) only assimilate precipitation at the location where some ensemble members have positive precipitation. The idea is first tested by the observing system simulation experiments (OSSEs) using SPEEDY, a simplified but realistic general circulation model. When the global precipitation is assimilated in addition to conventional rawinsonde observations, both the analyses and the medium range forecasts are significantly improved as compared to only having rawinsonde observations. The improvement is much reduced when only modifying the moisture field with the same approach, which shows the importance of the error covariance between precipitation and all other model variables. The effect of precipitation assimilation is larger in the Southern Hemisphere than that in the Northern Hemisphere because the Northern Hemisphere analyses are already accurate as a result of denser rawinsonde stations. Assimilation of precipitation using a more comprehensive

Gabor Wave Packet Method to Solve Plasma Wave Equations

International Nuclear Information System (INIS)

Pletzer, A.; Phillips, C.K.; Smithe, D.N.

2003-01-01

A numerical method for solving plasma wave equations arising in the context of mode conversion between the fast magnetosonic and the slow (e.g ion Bernstein) wave is presented. The numerical algorithm relies on the expansion of the solution in Gaussian wave packets known as Gabor functions, which have good resolution properties in both real and Fourier space. The wave packets are ideally suited to capture both the large and small wavelength features that characterize mode conversion problems. The accuracy of the scheme is compared with a standard finite element approach

Heuristic method for determining outgoing waves in many-body wave functions

International Nuclear Information System (INIS)

Redish, E.F.; Tandy, P.C.; L'Huillier, M.

1975-12-01

A new and simple method is proposed for determining the kinds of outgoing waves present in a given many-body wave function. Whether any particular wave function contains ''hidden'' rearrangement components can be determined. 1 figure

A Robust Non-Gaussian Data Assimilation Method for Highly Non-Linear Models

Directory of Open Access Journals (Sweden)

Elias D. Nino-Ruiz

2018-03-01

Full Text Available In this paper, we propose an efficient EnKF implementation for non-Gaussian data assimilation based on Gaussian Mixture Models and Markov-Chain-Monte-Carlo (MCMC methods. The proposed method works as follows: based on an ensemble of model realizations, prior errors are estimated via a Gaussian Mixture density whose parameters are approximated by means of an Expectation Maximization method. Then, by using an iterative method, observation operators are linearized about current solutions and posterior modes are estimated via a MCMC implementation. The acceptance/rejection criterion is similar to that of the Metropolis-Hastings rule. Experimental tests are performed on the Lorenz 96 model. The results show that the proposed method can decrease prior errors by several order of magnitudes in a root-mean-square-error sense for nearly sparse or dense observational networks.

Applications of Data Assimilation to Analysis of the Ocean on Large Scales

Science.gov (United States)

Miller, Robert N.; Busalacchi, Antonio J.; Hackert, Eric C.

1997-01-01

It is commonplace to begin talks on this topic by noting that oceanographic data are too scarce and sparse to provide complete initial and boundary conditions for large-scale ocean models. Even considering the availability of remotely-sensed data such as radar altimetry from the TOPEX and ERS-1 satellites, a glance at a map of available subsurface data should convince most observers that this is still the case. Data are still too sparse for comprehensive treatment of interannual to interdecadal climate change through the use of models, since the new data sets have not been around for very long. In view of the dearth of data, we must note that the overall picture is changing rapidly. Recently, there have been a number of large scale ocean analysis and prediction efforts, some of which now run on an operational or at least quasi-operational basis, most notably the model based analyses of the tropical oceans. These programs are modeled on numerical weather prediction. Aside from the success of the global tide models, assimilation of data in the tropics, in support of prediction and analysis of seasonal to interannual climate change, is probably the area of large scale ocean modeling and data assimilation in which the most progress has been made. Climate change is a problem which is particularly suited to advanced data assimilation methods. Linear models are useful, and the linear theory can be exploited. For the most part, the data are sufficiently sparse that implementation of advanced methods is worthwhile. As an example of a large scale data assimilation experiment with a recent extensive data set, we present results of a tropical ocean experiment in which the Kalman filter was used to assimilate three years of altimetric data from Geosat into a coarsely resolved linearized long wave shallow water model. Since nonlinear processes dominate the local dynamic signal outside the tropics, subsurface dynamical quantities cannot be reliably inferred from surface height

Data Assimilation in Forest Inventory: First Empirical Results

Directory of Open Access Journals (Sweden)

Mattias Nyström

2015-12-01

Full Text Available Data assimilation techniques were used to estimate forest stand data in 2011 by sequentially combining remote sensing based estimates of forest variables with predictions from growth models. Estimates of stand data, based on canopy height models obtained from image matching of digital aerial images at six different time-points between 2003 and 2011, served as input to the data assimilation. The assimilation routines were built on the extended Kalman filter. The study was conducted in hemi-boreal forest at the Remningstorp test site in southern Sweden (lat. 13°37′ N; long. 58°28′ E. The assimilation results were compared with two other methods used in practice for estimation of forest variables: the first was to use only the most recent estimate obtained from remotely sensed data (2011 and the second was to forecast the first estimate (2003 to the endpoint (2011. All three approaches were validated using nine 40 m radius validation plots, which were carefully measured in the field. The results showed that the data assimilation approach provided better results than the two alternative methods. Data assimilation of remote sensing time series has been used previously for calibrating forest ecosystem models, but, to our knowledge, this is the first study with real data where data assimilation has been used for estimating forest inventory data. The study constitutes a starting point for the development of a framework useful for sequentially utilizing all types of remote sensing data in order to provide precise and up-to-date estimates of forest stand parameters.

Scalable and balanced dynamic hybrid data assimilation

Science.gov (United States)

Kauranne, Tuomo; Amour, Idrissa; Gunia, Martin; Kallio, Kari; Lepistö, Ahti; Koponen, Sampsa

2017-04-01

Scalability of complex weather forecasting suites is dependent on the technical tools available for implementing highly parallel computational kernels, but to an equally large extent also on the dependence patterns between various components of the suite, such as observation processing, data assimilation and the forecast model. Scalability is a particular challenge for 4D variational assimilation methods that necessarily couple the forecast model into the assimilation process and subject this combination to an inherently serial quasi-Newton minimization process. Ensemble based assimilation methods are naturally more parallel, but large models force ensemble sizes to be small and that results in poor assimilation accuracy, somewhat akin to shooting with a shotgun in a million-dimensional space. The Variational Ensemble Kalman Filter (VEnKF) is an ensemble method that can attain the accuracy of 4D variational data assimilation with a small ensemble size. It achieves this by processing a Gaussian approximation of the current error covariance distribution, instead of a set of ensemble members, analogously to the Extended Kalman Filter EKF. Ensemble members are re-sampled every time a new set of observations is processed from a new approximation of that Gaussian distribution which makes VEnKF a dynamic assimilation method. After this a smoothing step is applied that turns VEnKF into a dynamic Variational Ensemble Kalman Smoother VEnKS. In this smoothing step, the same process is iterated with frequent re-sampling of the ensemble but now using past iterations as surrogate observations until the end result is a smooth and balanced model trajectory. In principle, VEnKF could suffer from similar scalability issues as 4D-Var. However, this can be avoided by isolating the forecast model completely from the minimization process by implementing the latter as a wrapper code whose only link to the model is calling for many parallel and totally independent model runs, all of them

Ecocultural range-expansion scenarios for the replacement or assimilation of Neanderthals by modern humans.

Science.gov (United States)

Wakano, Joe Yuichiro; Gilpin, William; Kadowaki, Seiji; Feldman, Marcus W; Aoki, Kenichi

2018-02-01

Recent archaeological records no longer support a simple dichotomous characterization of the cultures/behaviors of Neanderthals and modern humans, but indicate much cultural/behavioral variability over time and space. Thus, in modeling the replacement or assimilation of Neanderthals by modern humans, it is of interest to consider cultural dynamics and their relation to demographic change. The ecocultural framework for the competition between hominid species allows their carrying capacities to depend on some measure of the levels of culture they possess. In the present study both population densities and the densities of skilled individuals in Neanderthals and modern humans are spatially distributed and subject to change by spatial diffusion, ecological competition, and cultural transmission within each species. We analyze the resulting range expansions in terms of the demographic, ecological and cultural parameters that determine how the carrying capacities relate to the local densities of skilled individuals in each species. Of special interest is the case of cognitive and intrinsic-demographic equivalence of the two species. The range expansion dynamics may consist of multiple wave fronts of different speeds, each of which originates from a traveling wave solution. Properties of these traveling wave solutions are mathematically derived. Depending on the parameters, these traveling waves can result in replacement of Neanderthals by modern humans, or assimilation of the former by the latter. In both the replacement and assimilation scenarios, the first wave of intrusive modern humans is characterized by a low population density and a low density of skilled individuals, with implications for archaeological visibility. The first invasion is due to weak interspecific competition. A second wave of invasion may be induced by cultural differences between moderns and Neanderthals. Spatially and temporally extended coexistence of the two species, which would have

Analysis of Different Methods for Wave Generation and Absorption in a CFD-Based Numerical Wave Tank

Directory of Open Access Journals (Sweden)

Adria Moreno Miquel

2018-06-01

Full Text Available In this paper, the performance of different wave generation and absorption methods in computational fluid dynamics (CFD-based numerical wave tanks (NWTs is analyzed. The open-source CFD code REEF3D is used, which solves the Reynolds-averaged Navier–Stokes (RANS equations to simulate two-phase flow problems. The water surface is computed with the level set method (LSM, and turbulence is modeled with the k-ω model. The NWT includes different methods to generate and absorb waves: the relaxation method, the Dirichlet-type method and active wave absorption. A sensitivity analysis has been conducted in order to quantify and compare the differences in terms of absorption quality between these methods. A reflection analysis based on an arbitrary number of wave gauges has been adopted to conduct the study. Tests include reflection analysis of linear, second- and fifth-order Stokes waves, solitary waves, cnoidal waves and irregular waves generated in an NWT. Wave breaking over a sloping bed and wave forces on a vertical cylinder are calculated, and the influence of the reflections on the wave breaking location and the wave forces on the cylinder is investigated. In addition, a comparison with another open-source CFD code, OpenFOAM, has been carried out based on published results. Some differences in the calculated quantities depending on the wave generation and absorption method have been observed. The active wave absorption method is seen to be more efficient for long waves, whereas the relaxation method performs better for shorter waves. The relaxation method-based numerical beach generally results in lower reflected waves in the wave tank for most of the cases simulated in this study. The comparably better performance of the relaxation method comes at the cost of larger computational requirements due to the relaxation zones that have to be included in the domain. The reflections in the NWT in REEF3D are generally lower than the published results for

Data Assimilation for Applied Meteorology

Science.gov (United States)

Haupt, S. E.

2012-12-01

Although atmospheric models provide a best estimate of the future state of the atmosphere, due to sensitivity to initial condition, it is difficult to predict the precise future state. For applied problems, however, users often depend on having accurate knowledge of that future state. To improve prediction of a particular realization of an evolving flow field requires knowledge of the current state of that field and assimilation of local observations into the model. This talk will consider how dynamic assimilation can help address the concerns of users of atmospheric forecasts. First, we will look at the value of assimilation for the renewable energy industry. If the industry decision makers can have confidence in the wind and solar power forecasts, they can build their power allocations around the expected renewable resource, saving money for the ratepayers as well as reducing carbon emissions. We will assess the value to that industry of assimilating local real-time observations into the model forecasts and the value that is provided. The value of the forecasts with assimilation is important on both short (several hour) to medium range (within two days). A second application will be atmospheric transport and dispersion problems. In particular, we will look at assimilation of concentration data into a prediction model. An interesting aspect of this problem is that the dynamics are a one-way coupled system, with the fluid dynamic equations affecting the concentration equation, but not vice versa. So when the observations are of the concentration, one must infer the fluid dynamics. This one-way coupled system presents a challenge: one must first infer the changes in the flow field from observations of the contaminant, then assimilate that to recover both the advecting flow and information on the subgrid processes that provide the mixing. To accomplish such assimilation requires a robust method to match the observed contaminant field to that modeled. One approach is

Experimental methods of shock wave research

CERN Document Server

Seiler, Friedrich

2016-01-01

This comprehensive and carefully edited volume presents a variety of experimental methods used in Shock Waves research. In 14 self contained chapters this 9th volume of the “Shock Wave Science and Technology Reference Library” presents the experimental methods used in Shock Tubes, Shock Tunnels and Expansion Tubes facilities. Also described is their set-up and operation. The uses of an arc heated wind tunnel and a gun tunnel are also contained in this volume. Whenever possible, in addition to the technical description some typical scientific results obtained using such facilities are described. Additionally, this authoritative book includes techniques for measuring physical properties of blast waves and laser generated shock waves. Information about active shock wave laboratories at different locations around the world that are not described in the chapters herein is given in the Appendix, making this book useful for every researcher involved in shock/blast wave phenomena.

A reduced adjoint approach to variational data assimilation

KAUST Repository

Altaf, Muhammad

2013-02-01

The adjoint method has been used very often for variational data assimilation. The computational cost to run the adjoint model often exceeds several original model runs and the method needs significant programming efforts to implement the adjoint model code. The work proposed here is variational data assimilation based on proper orthogonal decomposition (POD) which avoids the implementation of the adjoint of the tangent linear approximation of the original nonlinear model. An ensemble of the forward model simulations is used to determine the approximation of the covariance matrix and only the dominant eigenvectors of this matrix are used to define a model subspace. The adjoint of the tangent linear model is replaced by the reduced adjoint based on this reduced space. Thus the adjoint model is run in reduced space with negligible computational cost. Once the gradient is obtained in reduced space it is projected back in full space and the minimization process is carried in full space. In the paper the reduced adjoint approach to variational data assimilation is introduced. The characteristics and performance of the method are illustrated with a number of data assimilation experiments in a ground water subsurface contaminant model. © 2012 Elsevier B.V.

A reduced adjoint approach to variational data assimilation

KAUST Repository

Altaf, Muhammad; El Gharamti, Mohamad; Heemink, Arnold W.; Hoteit, Ibrahim

2013-01-01

The adjoint method has been used very often for variational data assimilation. The computational cost to run the adjoint model often exceeds several original model runs and the method needs significant programming efforts to implement the adjoint model code. The work proposed here is variational data assimilation based on proper orthogonal decomposition (POD) which avoids the implementation of the adjoint of the tangent linear approximation of the original nonlinear model. An ensemble of the forward model simulations is used to determine the approximation of the covariance matrix and only the dominant eigenvectors of this matrix are used to define a model subspace. The adjoint of the tangent linear model is replaced by the reduced adjoint based on this reduced space. Thus the adjoint model is run in reduced space with negligible computational cost. Once the gradient is obtained in reduced space it is projected back in full space and the minimization process is carried in full space. In the paper the reduced adjoint approach to variational data assimilation is introduced. The characteristics and performance of the method are illustrated with a number of data assimilation experiments in a ground water subsurface contaminant model. © 2012 Elsevier B.V.

A simple lightning assimilation technique for improving ...

Science.gov (United States)

Convective rainfall is often a large source of error in retrospective modeling applications. In particular, positive rainfall biases commonly exist during summer months due to overactive convective parameterizations. In this study, lightning assimilation was applied in the Kain-Fritsch (KF) convective scheme to improve retrospective simulations using the Weather Research and Forecasting (WRF) model. The assimilation method has a straightforward approach: force KF deep convection where lightning is observed and, optionally, suppress deep convection where lightning is absent. WRF simulations were made with and without lightning assimilation over the continental United States for July 2012, July 2013, and January 2013. The simulations were evaluated against NCEP stage-IV precipitation data and MADIS near-surface meteorological observations. In general, the use of lightning assimilation considerably improves the simulation of summertime rainfall. For example, the July 2012 monthly averaged bias of 6 h accumulated rainfall is reduced from 0.54 to 0.07 mm and the spatial correlation is increased from 0.21 to 0.43 when lightning assimilation is used. Statistical measures of near-surface meteorological variables also are improved. Consistent improvements also are seen for the July 2013 case. These results suggest that this lightning assimilation technique has the potential to substantially improve simulation of warm-season rainfall in retrospective WRF applications. The

A problem-solving environment for data assimilation in air quality modelling

NARCIS (Netherlands)

Velzen, N. van; Segers, A.J.

2010-01-01

A generic toolbox for data assimilation called COSTA (COmmon Set of Tools for the Assimilation of data) makes it possible to simplify the application of data assimilation to models and to try out various methods for a particular model. Concepts of object oriented programming are used to define

Development of A Bayesian Geostatistical Data Assimilation Method and Application to the Hanford 300 Area

Science.gov (United States)

Murakami, Haruko

Probabilistic risk assessment of groundwater contamination requires us to incorporate large and diverse datasets at the site into the stochastic modeling of flow and transport for prediction. In quantifying the uncertainty in our predictions, we must not only combine the best estimates of the parameters based on each dataset, but also integrate the uncertainty associated with each dataset caused by measurement errors and limited number of measurements. This dissertation presents a Bayesian geostatistical data assimilation method that integrates various types of field data for characterizing heterogeneous hydrological properties. It quantifies the parameter uncertainty as a posterior distribution conditioned on all the datasets, which can be directly used in stochastic simulations to compute possible outcomes of flow and transport processes. The goal of this framework is to remove the discontinuity between data analysis and prediction. Such a direct connection between data and prediction also makes it possible to evaluate the worth of each dataset or combined worth of multiple datasets. The synthetic studies described here confirm that the data assimilation method introduced in this dissertation successfully captures the true parameter values and predicted values within the posterior distribution. The shape of the inferred posterior distributions from the method indicates the importance of estimating the entire distribution in fully accounting for parameter uncertainty. The method is then applied to integrate multiple types of datasets at the Hanford 300 Area for characterizing a three-dimensional heterogeneous hydraulic conductivity field. Comparing the results based on the different numbers or combinations of datasets shows that increasing data do not always contribute in a straightforward way to improving the posterior distribution: increasing numbers of the same data type would not necessarily be beneficial above a certain number, and also the combined effect of

Effective assimilation of global precipitation: simulation experiments

Directory of Open Access Journals (Sweden)

Guo-Yuan Lien

2013-07-01

Full Text Available Past attempts to assimilate precipitation by nudging or variational methods have succeeded in forcing the model precipitation to be close to the observed values. However, the model forecasts tend to lose their additional skill after a few forecast hours. In this study, a local ensemble transform Kalman filter (LETKF is used to effectively assimilate precipitation by allowing ensemble members with better precipitation to receive higher weights in the analysis. In addition, two other changes in the precipitation assimilation process are found to alleviate the problems related to the non-Gaussianity of the precipitation variable: (a transform the precipitation variable into a Gaussian distribution based on its climatological distribution (an approach that could also be used in the assimilation of other non-Gaussian observations and (b only assimilate precipitation at the location where at least some ensemble members have precipitation. Unlike many current approaches, both positive and zero rain observations are assimilated effectively. Observing system simulation experiments (OSSEs are conducted using the Simplified Parametrisations, primitivE-Equation DYnamics (SPEEDY model, a simplified but realistic general circulation model. When uniformly and globally distributed observations of precipitation are assimilated in addition to rawinsonde observations, both the analyses and the medium-range forecasts of all model variables, including precipitation, are significantly improved as compared to only assimilating rawinsonde observations. The effect of precipitation assimilation on the analyses is retained on the medium-range forecasts and is larger in the Southern Hemisphere (SH than that in the Northern Hemisphere (NH because the NH analyses are already made more accurate by the denser rawinsonde stations. These improvements are much reduced when only the moisture field is modified by the precipitation observations. Both the Gaussian transformation and

Development of a data assimilation algorithm

DEFF Research Database (Denmark)

Thomsen, Per Grove; Zlatev, Zahari

2008-01-01

It is important to incorporate all available observations when large-scale mathematical models arising in different fields of science and engineering are used to study various physical and chemical processes. Variational data assimilation techniques can be used in the attempts to utilize efficien......It is important to incorporate all available observations when large-scale mathematical models arising in different fields of science and engineering are used to study various physical and chemical processes. Variational data assimilation techniques can be used in the attempts to utilize...... assimilation technique is applied. Therefore, it is important to study the interplay between the three components of the variational data assimilation techniques as well as to apply powerful parallel computers in the computations. Some results obtained in the search for a good combination of numerical methods...... computers, Mathematics and Computers in Simulation, 65 (2004) 557–577, Z. Zlatev, Computer Treatment of Large Air Pollution Models, Kluwer Academic Publishers, Dordrecht, Boston, London, 1995]. The ideas are rather general and can easily be applied in connection with other mathematical models....

Physically consistent data assimilation method based on feedback control for patient-specific blood flow analysis.

Science.gov (United States)

Ii, Satoshi; Adib, Mohd Azrul Hisham Mohd; Watanabe, Yoshiyuki; Wada, Shigeo

2018-01-01

This paper presents a novel data assimilation method for patient-specific blood flow analysis based on feedback control theory called the physically consistent feedback control-based data assimilation (PFC-DA) method. In the PFC-DA method, the signal, which is the residual error term of the velocity when comparing the numerical and reference measurement data, is cast as a source term in a Poisson equation for the scalar potential field that induces flow in a closed system. The pressure values at the inlet and outlet boundaries are recursively calculated by this scalar potential field. Hence, the flow field is physically consistent because it is driven by the calculated inlet and outlet pressures, without any artificial body forces. As compared with existing variational approaches, although this PFC-DA method does not guarantee the optimal solution, only one additional Poisson equation for the scalar potential field is required, providing a remarkable improvement for such a small additional computational cost at every iteration. Through numerical examples for 2D and 3D exact flow fields, with both noise-free and noisy reference data as well as a blood flow analysis on a cerebral aneurysm using actual patient data, the robustness and accuracy of this approach is shown. Moreover, the feasibility of a patient-specific practical blood flow analysis is demonstrated. Copyright © 2017 John Wiley & Sons, Ltd.

Assimilation of Remotely Sensed Leaf Area Index into the Community Land Model with Explicit Carbon and Nitrogen Components using Data Assimilation Research Testbed

Science.gov (United States)

Ling, X.; Fu, C.; Yang, Z. L.; Guo, W.

2017-12-01

Information of the spatial and temporal patterns of leaf area index (LAI) is crucial to understand the exchanges of momentum, carbon, energy, and water between the terrestrial ecosystem and the atmosphere, while both in-situ observation and model simulation usually show distinct deficiency in terms of LAI coverage and value. Land data assimilation, combined with observation and simulation together, is a promising way to provide variable estimation. The Data Assimilation Research Testbed (DART) developed and maintained by the National Centre for Atmospheric Research (NCAR) provides a powerful tool to facilitate the combination of assimilation algorithms, models, and real (as well as synthetic) observations to better understanding of all three. Here we systematically investigated the effects of data assimilation on improving LAI simulation based on NCAR Community Land Model with the prognostic carbon-nitrogen option (CLM4CN) linked with DART using the deterministic Ensemble Adjustment Kalman Filter (EAKF). Random 40-member atmospheric forcing was used to drive the CLM4CN with or without LAI assimilation. The Global Land Surface Satellite LAI data (GLASS LAI) LAI is assimilated into the CLM4CN at a frequency of 8 days, and LAI (and leaf carbon / nitrogen) are adjusted at each time step. The results show that assimilating remotely sensed LAI into the CLM4CN is an effective method for improving model performance. In detail, the CLM4-CN simulated LAI systematically overestimates global LAI, especially in low latitude with the largest bias of 5 m2/m2. While if updating both LAI and leaf carbon and leaf nitrogen simultaneously during assimilation, the analyzed LAI can be corrected, especially in low latitude regions with the bias controlled around ±1 m2/m2. Analyzed LAI could also represent the seasonal variation except for the Southern Temperate (23°S-90°S). The obviously improved regions located in the center of Africa, Amazon, the South of Eurasia, the northeast of

Assimilation of stratospheric ozone in the chemical transport model STRATAQ

Directory of Open Access Journals (Sweden)

B. Grassi

2004-09-01

Full Text Available We describe a sequential assimilation approach useful for assimilating tracer measurements into a three-dimensional chemical transport model (CTM of the stratosphere. The numerical code, developed largely according to Kha00, uses parameterizations and simplifications allowing assimilation of sparse observations and the simultaneous evaluation of analysis errors, with reasonable computational requirements. Assimilation parameters are set by using χ2 and OmF (Observation minus Forecast statistics. The CTM used here is a high resolution three-dimensional model. It includes a detailed chemical package and is driven by UKMO (United Kingdom Meteorological Office analyses. We illustrate the method using assimilation of Upper Atmosphere Research Satellite/Microwave Limb Sounder (UARS/MLS ozone observations for three weeks during the 1996 antarctic spring. The comparison of results from the simulations with TOMS (Total Ozone Mapping Spectrometer measurements shows improved total ozone fields due to assimilation of MLS observations. Moreover, the assimilation gives indications on a possible model weakness in reproducing polar ozone values during springtime.

Assimilation of stratospheric ozone in the chemical transport model STRATAQ

Directory of Open Access Journals (Sweden)

B. Grassi

2004-09-01

Full Text Available We describe a sequential assimilation approach useful for assimilating tracer measurements into a three-dimensional chemical transport model (CTM of the stratosphere. The numerical code, developed largely according to Kha00, uses parameterizations and simplifications allowing assimilation of sparse observations and the simultaneous evaluation of analysis errors, with reasonable computational requirements. Assimilation parameters are set by using χ² and OmF (Observation minus Forecast statistics. The CTM used here is a high resolution three-dimensional model. It includes a detailed chemical package and is driven by UKMO (United Kingdom Meteorological Office analyses. We illustrate the method using assimilation of Upper Atmosphere Research Satellite/Microwave Limb Sounder (UARS/MLS ozone observations for three weeks during the 1996 antarctic spring. The comparison of results from the simulations with TOMS (Total Ozone Mapping Spectrometer measurements shows improved total ozone fields due to assimilation of MLS observations. Moreover, the assimilation gives indications on a possible model weakness in reproducing polar ozone values during springtime.

Reconstruction of Historical Weather by Assimilating Old Weather Diary Data

Science.gov (United States)

Neluwala, P.; Yoshimura, K.; Toride, K.; Hirano, J.; Ichino, M.; Okazaki, A.

2017-12-01

Climate can control not only human life style but also other living beings. It is important to investigate historical climate to understand the current and future climates. Information about daily weather can give a better understanding of past life on earth. Long-term weather influences crop calendar as well as the development of civilizations. Unfortunately, existing reconstructed daily weather data are limited to 1850s due to the availability of instrumental data. The climate data prior to that are derived from proxy materials (e.g., tree-ring width, ice core isotopes, etc.) which are either in annual or decadal scale. However, there are many historical documents which contain information about weather such as personal diaries. In Japan, around 20 diaries in average during the 16th - 19th centuries have been collected and converted into a digitized form. As such, diary data exist in many other countries. This study aims to reconstruct historical daily weather during the 18th and 19th centuries using personal daily diaries which have analogue weather descriptions such as `cloudy' or `sunny'. A recent study has shown the possibility of assimilating coarse weather data using idealized experiments. We further extend this study by assimilating modern weather descriptions similar to diary data in recent periods. The Global Spectral model (GSM) of National Centers for Environmental Prediction (NCEP) is used to reconstruct weather with the Local Ensemble Kalman filter (LETKF). Descriptive data are first converted to model variables such as total cloud cover (TCC), solar radiation and precipitation using empirical relationships. Those variables are then assimilated on a daily basis after adding random errors to consider the uncertainty of actual diary data. The assimilation of downward short wave solar radiation using weather descriptions improves RMSE from 64.3 w/m2 to 33.0 w/m2 and correlation coefficient (R) from 0.5 to 0.8 compared with the case without any

Variational assimilation of streamflow into operational distributed hydrologic models: effect of spatiotemporal adjustment scale

Science.gov (United States)

Lee, H.; Seo, D.-J.; Liu, Y.; Koren, V.; McKee, P.; Corby, R.

2012-01-01

State updating of distributed rainfall-runoff models via streamflow assimilation is subject to overfitting because large dimensionality of the state space of the model may render the assimilation problem seriously under-determined. To examine the issue in the context of operational hydrology, we carry out a set of real-world experiments in which streamflow data is assimilated into gridded Sacramento Soil Moisture Accounting (SAC-SMA) and kinematic-wave routing models of the US National Weather Service (NWS) Research Distributed Hydrologic Model (RDHM) with the variational data assimilation technique. Study basins include four basins in Oklahoma and five basins in Texas. To assess the sensitivity of data assimilation performance to dimensionality reduction in the control vector, we used nine different spatiotemporal adjustment scales, where state variables are adjusted in a lumped, semi-distributed, or distributed fashion and biases in precipitation and potential evaporation (PE) are adjusted hourly, 6-hourly, or kept time-invariant. For each adjustment scale, three different streamflow assimilation scenarios are explored, where streamflow observations at basin interior points, at the basin outlet, or at both interior points and the outlet are assimilated. The streamflow assimilation experiments with nine different basins show that the optimum spatiotemporal adjustment scale varies from one basin to another and may be different for streamflow analysis and prediction in all of the three streamflow assimilation scenarios. The most preferred adjustment scale for seven out of nine basins is found to be the distributed, hourly scale, despite the fact that several independent validation results at this adjustment scale indicated the occurrence of overfitting. Basins with highly correlated interior and outlet flows tend to be less sensitive to the adjustment scale and could benefit more from streamflow assimilation. In comparison to outlet flow assimilation, interior flow

Analysis shear wave velocity structure obtained from surface wave methods in Bornova, Izmir

Energy Technology Data Exchange (ETDEWEB)

Pamuk, Eren, E-mail: eren.pamuk@deu.edu.tr; Akgün, Mustafa, E-mail: mustafa.akgun@deu.edu.tr [Department of Geophysical Engineering, Dokuz Eylul University, Izmir (Turkey); Özdağ, Özkan Cevdet, E-mail: cevdet.ozdag@deu.edu.tr [Dokuz Eylul University Rectorate, Izmir (Turkey)

2016-04-18

Properties of the soil from the bedrock is necessary to describe accurately and reliably for the reduction of earthquake damage. Because seismic waves change their amplitude and frequency content owing to acoustic impedance difference between soil and bedrock. Firstly, shear wave velocity and depth information of layers on bedrock is needed to detect this changing. Shear wave velocity can be obtained using inversion of Rayleigh wave dispersion curves obtained from surface wave methods (MASW- the Multichannel Analysis of Surface Waves, ReMi-Refraction Microtremor, SPAC-Spatial Autocorrelation). While research depth is limeted in active source study, a passive source methods are utilized for deep depth which is not reached using active source methods. ReMi method is used to determine layer thickness and velocity up to 100 m using seismic refraction measurement systems.The research carried out up to desired depth depending on radius using SPAC which is utilized easily in conditions that district using of seismic studies in the city. Vs profiles which are required to calculate deformations in under static and dynamic loads can be obtained with high resolution using combining rayleigh wave dispersion curve obtained from active and passive source methods. In the this study, Surface waves data were collected using the measurements of MASW, ReMi and SPAC at the İzmir Bornova region. Dispersion curves obtained from surface wave methods were combined in wide frequency band and Vs-depth profiles were obtained using inversion. Reliability of the resulting soil profiles were provided by comparison with theoretical transfer function obtained from soil paremeters and observed soil transfer function from Nakamura technique and by examination of fitting between these functions. Vs values are changed between 200-830 m/s and engineering bedrock (Vs>760 m/s) depth is approximately 150 m.

Assimilation of Altimeter Data into a Quasigeostrophic Model of the Gulf Stream System. Part 2; Assimilation Results

Science.gov (United States)

Capotondi, Antonietta; Holland, William R.; Malanotte-Rizzoli, Paola

1995-01-01

The improvement in the climatological behavior of a numerical model as a consequence of the assimilation of surface data is investigated. The model used for this study is a quasigeostrophic (QG) model of the Gulf Stream region. The data that have been assimilated are maps of sea surface height that have been obtained as the superposition of sea surface height variability deduced from the Geosat altimeter measurements and a mean field constructed from historical hydrographic data. The method used for assimilating the data is the nudging technique. Nudging has been implemented in such a way as to achieve a high degree of convergence of the surface model fields toward the observations. Comparisons of the assimilation results with available in situ observations show a significant improvement in the degree of realism of the climatological model behavior, with respect to the model in which no data are assimilated. The remaining discrepancies in the model mean circulation seem to be mainly associated with deficiencies in the mean component of the surface data that are assimilated. On the other hand, the possibility of building into the model more realistic eddy characteristics through the assimilation of the surface eddy field proves very successful in driving components of the mean model circulation that are in relatively good agreement with the available observations. Comparisons with current meter time series during a time period partially overlapping the Geosat mission show that the model is able to 'correctly' extrapolate the instantaneous surface eddy signals to depths of approximately 1500 m. The correlation coefficient between current meter and model time series varies from values close to 0.7 in the top 1500 m to values as low as 0.1-0.2 in the deep ocean.

A case study of aerosol data assimilation with the Community Multi-scale Air Quality Model over the contiguous United States using 3D-Var and optimal interpolation methods

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Y. Tang

2017-12-01

Full Text Available This study applies the Gridpoint Statistical Interpolation (GSI 3D-Var assimilation tool originally developed by the National Centers for Environmental Prediction (NCEP, to improve surface PM2.5 predictions over the contiguous United States (CONUS by assimilating aerosol optical depth (AOD and surface PM2.5 in version 5.1 of the Community Multi-scale Air Quality (CMAQ modeling system. An optimal interpolation (OI method implemented earlier (Tang et al., 2015 for the CMAQ modeling system is also tested for the same period (July 2011 over the same CONUS. Both GSI and OI methods assimilate surface PM2.5 observations at 00:00, 06:00, 12:00 and 18:00 UTC, and MODIS AOD at 18:00 UTC. The assimilations of observations using both GSI and OI generally help reduce the prediction biases and improve correlation between model predictions and observations. In the GSI experiments, assimilation of surface PM2.5 (particle matter with diameter < 2.5 µm leads to stronger increments in surface PM2.5 compared to its MODIS AOD assimilation at the 550 nm wavelength. In contrast, we find a stronger OI impact of the MODIS AOD on surface aerosols at 18:00 UTC compared to the surface PM2.5 OI method. GSI produces smoother result and yields overall better correlation coefficient and root mean squared error (RMSE. It should be noted that the 3D-Var and OI methods used here have several big differences besides the data assimilation schemes. For instance, the OI uses relatively big model uncertainties, which helps yield smaller mean biases, but sometimes causes the RMSE to increase. We also examine and discuss the sensitivity of the assimilation experiments' results to the AOD forward operators.

The essential theory of fast wave current drive with full wave method

International Nuclear Information System (INIS)

Liu Yan; Gong Xueyu; Yang Lei; Yin Chenyan; Yin Lan

2007-01-01

The full wave numerical method is developed for analyzing fast wave current drive in the range of ion cyclotron waves in tokamak plasmas, taking into account finite larmor radius effects and parallel dispersion. the physical model, the dispersion relation on the assumption of Finite Larmor Radius (FLR) effects and the form of full wave be used for computer simulation are developed. All of the work will contribute to further study of fast wave current drive. (authors)

Taylor-series method for four-nucleon wave functions

International Nuclear Information System (INIS)

Sandulescu, A.; Tarnoveanu, I.; Rizea, M.

1977-09-01

Taylor-series method for transforming the infinite or finite well two-nucleon wave functions from individual coordinates to relative and c.m. coordinates, by expanding the single particle shell model wave functions around c.m. of the system, is generalized to four-nucleon wave functions. Also the connections with the Talmi-Moshinsky method for two and four harmonic oscillator wave functions are deduced. For both methods Fortran IV programs for the expansion coefficients have been written and the equivalence of corresponding expressions numerically proved. (author)

A coherent structure approach for parameter estimation in Lagrangian Data Assimilation

Science.gov (United States)

Maclean, John; Santitissadeekorn, Naratip; Jones, Christopher K. R. T.

2017-12-01

We introduce a data assimilation method to estimate model parameters with observations of passive tracers by directly assimilating Lagrangian Coherent Structures. Our approach differs from the usual Lagrangian Data Assimilation approach, where parameters are estimated based on tracer trajectories. We employ the Approximate Bayesian Computation (ABC) framework to avoid computing the likelihood function of the coherent structure, which is usually unavailable. We solve the ABC by a Sequential Monte Carlo (SMC) method, and use Principal Component Analysis (PCA) to identify the coherent patterns from tracer trajectory data. Our new method shows remarkably improved results compared to the bootstrap particle filter when the physical model exhibits chaotic advection.

Surface wave velocity tracking by bisection method

International Nuclear Information System (INIS)

Maeda, T.

2005-01-01

Calculation of surface wave velocity is a classic problem dating back to the well-known Haskell's transfer matrix method, which contributes to solutions of elastic wave propagation, global subsurface structure evaluation by simulating observed earthquake group velocities, and on-site evaluation of subsurface structure by simulating phase velocity dispersion curves and/or H/V spectra obtained by micro-tremor observation. Recently inversion analysis on micro-tremor observation requires efficient method of generating many model candidates and also stable, accurate, and fast computation of dispersion curves and Raleigh wave trajectory. The original Haskell's transfer matrix method has been improved in terms of its divergence tendency mainly by the generalized transmission and reflection matrix method with formulation available for surface wave velocity; however, root finding algorithm has not been fully discussed except for the one by setting threshold to the absolute value of complex characteristic functions. Since surface wave number (reciprocal to the surface wave velocity multiplied by frequency) is a root of complex valued characteristic function, it is intractable to use general root finding algorithm. We will examine characteristic function in phase plane to construct two dimensional bisection algorithm with consideration on a layer to be evaluated and algorithm for tracking roots down along frequency axis. (author)

Study on evaluation methods for Rayleigh wave dispersion characteristic

Science.gov (United States)

Shi, L.; Tao, X.; Kayen, R.; Shi, H.; Yan, S.

2005-01-01

The evaluation of Rayleigh wave dispersion characteristic is the key step for detecting S-wave velocity structure. By comparing the dispersion curves directly with the spectra analysis of surface waves (SASW) method, rather than comparing the S-wave velocity structure, the validity and precision of microtremor-array method (MAM) can be evaluated more objectively. The results from the China - US joint surface wave investigation in 26 sites in Tangshan, China, show that the MAM has the same precision with SASW method in 83% of the 26 sites. The MAM is valid for Rayleigh wave dispersion characteristic testing and has great application potentiality for site S-wave velocity structure detection.

Conservative numerical methods for solitary wave interactions

Energy Technology Data Exchange (ETDEWEB)

Duran, A; Lopez-Marcos, M A [Departamento de Matematica Aplicada y Computacion, Facultad de Ciencias, Universidad de Valladolid, Paseo del Prado de la Magdalena s/n, 47005 Valladolid (Spain)

2003-07-18

The purpose of this paper is to show the advantages that represent the use of numerical methods that preserve invariant quantities in the study of solitary wave interactions for the regularized long wave equation. It is shown that the so-called conservative methods are more appropriate to study the phenomenon and provide a dynamic point of view that allows us to estimate the changes in the parameters of the solitary waves after the collision.

A case study of aerosol data assimilation with the Community Multi-scale Air Quality Model over the contiguous United States using 3D-Var and optimal interpolation methods

Science.gov (United States)

Tang, Youhua; Pagowski, Mariusz; Chai, Tianfeng; Pan, Li; Lee, Pius; Baker, Barry; Kumar, Rajesh; Delle Monache, Luca; Tong, Daniel; Kim, Hyun-Cheol

2017-12-01

This study applies the Gridpoint Statistical Interpolation (GSI) 3D-Var assimilation tool originally developed by the National Centers for Environmental Prediction (NCEP), to improve surface PM2.5 predictions over the contiguous United States (CONUS) by assimilating aerosol optical depth (AOD) and surface PM2.5 in version 5.1 of the Community Multi-scale Air Quality (CMAQ) modeling system. An optimal interpolation (OI) method implemented earlier (Tang et al., 2015) for the CMAQ modeling system is also tested for the same period (July 2011) over the same CONUS. Both GSI and OI methods assimilate surface PM2.5 observations at 00:00, 06:00, 12:00 and 18:00 UTC, and MODIS AOD at 18:00 UTC. The assimilations of observations using both GSI and OI generally help reduce the prediction biases and improve correlation between model predictions and observations. In the GSI experiments, assimilation of surface PM2.5 (particle matter with diameter big differences besides the data assimilation schemes. For instance, the OI uses relatively big model uncertainties, which helps yield smaller mean biases, but sometimes causes the RMSE to increase. We also examine and discuss the sensitivity of the assimilation experiments' results to the AOD forward operators.

Assimilation of wind speed and direction observations: results from real observation experiments

Directory of Open Access Journals (Sweden)

Feng Gao

2015-06-01

Full Text Available The assimilation of wind observations in the form of speed and direction (asm_sd by the Weather Research and Forecasting Model Data Assimilation System (WRFDA was performed using real data and employing a series of cycling assimilation experiments for a 2-week period, as a follow-up for an idealised post hoc assimilation experiment. The satellite-derived Atmospheric Motion Vectors (AMV and surface dataset in Meteorological Assimilation Data Ingest System (MADIS were assimilated. This new method takes into account the observation errors of both wind speed (spd and direction (dir, and WRFDA background quality control (BKG-QC influences the choice of wind observations, due to data conversions between (u,v and (spd, dir. The impacts of BKG-QC, as well as the new method, on the wind analysis were analysed separately. Because the dir observational errors produced by different platforms are not known or tuned well in WRFDA, a practical method, which uses similar assimilation weights in comparative trials, was employed to estimate the spd and dir observation errors. The asm_sd produces positive impacts on analyses and short-range forecasts of spd and dir with smaller root-mean-square errors than the u,v-based system. The bias of spd analysis decreases by 54.8%. These improvements result partly from BKG-QC screening of spd and dir observations in a direct way, but mainly from the independent impact of spd (dir data assimilation on spd (dir analysis, which is the primary distinction from the standard WRFDA method. The potential impacts of asm_sd on precipitation forecasts were evaluated. Results demonstrate that the asm_sd is able to indirectly improve the precipitation forecasts by improving the prediction accuracies of key wind-related factors leading to precipitation (e.g. warm moist advection and frontogenesis.

An investigation on how inner-core structures obtained through radar data assimilation affect track forecasting of typhoon Jangmi (2008) near Taiwan Island

Science.gov (United States)

Wang, Mingjun; Xue, Ming; Zhao, Kun

2016-09-01

The impacts of radar data assimilation (DA) on the westward track deflection of Typhoon Jangmi (2008) near Taiwan Island and the deflection mechanism are investigated. Initial conditions from two data assimilation experiments with significant track forecast differences are analyzed and compared. The environmental, axisymmetric, wave number 1 to 3 asymmetric fields of the typhoon are decomposed by using vortex separation and Fourier decomposition methods. The components are selectively recomposed into new initial conditions that include different vortex-scale components to examine the impact of individual components on the track prediction. The wave number 1 asymmetric structure is found to play a dominant role in the westward deflection of Typhoon Jangmi, and the accurate analysis of this component with radar DA helps to improve the track forecast. The wave number 1 asymmetric circulation is manifested as a pair of cyclonic and anticyclonic gyres with well-defined ventilation flows through the inner-core region, which provides additional steering of the typhoon vortex. The layer-mean environmental steering flow and ventilation flow associated with the wave number 1 gyres are further calculated to quantitatively evaluate the impact of ventilation flow. The ventilation flow is shown to be responsible for most of the westward motion component, suggesting again its role in causing the westward track deflection of Typhoon Jangmi. The results also suggest the importance of analyzing vortex-scale asymmetric structures for accurate tropical cyclone track forecasting, especially when there is a significant track deflection.

Comparison between 3D-Var and 4D-Var data assimilation methods for the simulation of a heavy rainfall case in central Italy

Science.gov (United States)

Mazzarella, Vincenzo; Maiello, Ida; Capozzi, Vincenzo; Budillon, Giorgio; Ferretti, Rossella

2017-08-01

This work aims to provide a comparison between three dimensional and four dimensional variational data assimilation methods (3D-Var and 4D-Var) for a heavy rainfall case in central Italy. To evaluate the impact of the assimilation of reflectivity and radial velocity acquired from Monte Midia Doppler radar into the Weather Research Forecasting (WRF) model, the quantitative precipitation forecast (QPF) is used.The two methods are compared for a heavy rainfall event that occurred in central Italy on 14 September 2012 during the first Special Observation Period (SOP1) of the HyMeX (HYdrological cycle in Mediterranean EXperiment) campaign. This event, characterized by a deep low pressure system over the Tyrrhenian Sea, produced flash floods over the Marche and Abruzzo regions, where rainfall maxima reached more than 150 mm 24 h-1.To identify the best QPF, nine experiments are performed using 3D-Var and 4D-Var data assimilation techniques. All simulations are compared in terms of rainfall forecast and precipitation measured by the gauges through three statistical indicators: probability of detection (POD), critical success index (CSI) and false alarm ratio (FAR). The assimilation of conventional observations with 4D-Var method improves the QPF compared to 3D-Var. In addition, the use of radar measurements in 4D-Var simulations enhances the performances of statistical scores for higher rainfall thresholds.

Comparison between assimilated and non-assimilated experiments of the MACCii global reanalysis near surface ozone

Science.gov (United States)

Tsikerdekis, Athanasios; Katragou, Eleni; Zanis, Prodromos; Melas, Dimitrios; Eskes, Henk; Flemming, Johannes; Huijnen, Vincent; Inness, Antje; Kapsomenakis, Ioannis; Schultz, Martin; Stein, Olaf; Zerefos, Christos

2014-05-01

In this work we evaluate near surface ozone concentrations of the MACCii global reanalysis using measurements from the EMEP and AIRBASE database. The eight-year long reanalysis of atmospheric composition data covering the period 2003-2010 was constructed as part of the FP7-funded Monitoring Atmospheric Composition and Climate project by assimilating satellite data into a global model and data assimilation system (Inness et al., 2013). The study mainly focuses in the differences between the assimilated and the non-assimilated experiments and aims to identify and quantify any improvements achieved by adding data assimilation to the system. Results are analyzed in eight European sub-regions and region-specific Taylor plots illustrate the evaluation and the overall predictive skill of each experiment. The diurnal and annual cycles of near surface ozone are evaluated for both experiments. Furthermore ozone exposure indices for crop growth (AOT40), human health (SOMO35) and the number of days that 8-hour ozone averages exceeded 60ppb and 90ppb have been calculated for each station based on both observed and simulated data. Results indicate mostly improvement of the assimilated experiment with respect to the high near surface ozone concentrations, the diurnal cycle and range and the bias in comparison to the non-assimilated experiment. The limitations of the comparison between assimilated and non-assimilated experiments for near surface ozone are also discussed.

The Major Stratospheric Sudden Warming of January 2013: Analyses and Forecasts in the GEOS-5 Data Assimilation System

Science.gov (United States)

Coy, Lawrence; Pawson, Steven

2014-01-01

We examine the major stratosphere sudden warming (SSW) that occurred on 6 January 2013, using output from the NASA Global Modeling and Assimilation Office (GMAO) GEOS-5 (Goddard Earth Observing System) near-real-time data assimilation system (DAS). Results show that the major SSW of January 2013 falls into the vortex splitting type of SSW, with the initial planetary wave breaking occurring near 10 hPa. The vertical flux of wave activity at the tropopause responsible for the SSW occurred mainly in the Pacific Hemisphere, including the a pulse associated with the preconditioning of the polar vortex by wave 1 identified on 23 December 2012. While most of the vertical wave activity flux was in the Pacific Hemisphere, a rapidly developing tropospheric weather system over the North Atlantic on 28 December is shown to have produced a strong transient upward wave activity flux into the lower stratosphere coinciding with the peak of the SSW event. In addition, the GEOS-5 5-day forecasts accurately predicted the major SSW of January 2013 as well as the upper tropospheric disturbances responsible for the warming. The overall success of the 5-day forecasts provides motivation to produce regular 10-day forecasts with GEOS-5, to better support studies of stratosphere-troposphere interaction.

Assimilation of LAI time-series in crop production models

Science.gov (United States)

Kooistra, Lammert; Rijk, Bert; Nannes, Louis

2014-05-01

Agriculture is worldwide a large consumer of freshwater, nutrients and land. Spatial explicit agricultural management activities (e.g., fertilization, irrigation) could significantly improve efficiency in resource use. In previous studies and operational applications, remote sensing has shown to be a powerful method for spatio-temporal monitoring of actual crop status. As a next step, yield forecasting by assimilating remote sensing based plant variables in crop production models would improve agricultural decision support both at the farm and field level. In this study we investigated the potential of remote sensing based Leaf Area Index (LAI) time-series assimilated in the crop production model LINTUL to improve yield forecasting at field level. The effect of assimilation method and amount of assimilated observations was evaluated. The LINTUL-3 crop production model was calibrated and validated for a potato crop on two experimental fields in the south of the Netherlands. A range of data sources (e.g., in-situ soil moisture and weather sensors, destructive crop measurements) was used for calibration of the model for the experimental field in 2010. LAI from cropscan field radiometer measurements and actual LAI measured with the LAI-2000 instrument were used as input for the LAI time-series. The LAI time-series were assimilated in the LINTUL model and validated for a second experimental field on which potatoes were grown in 2011. Yield in 2011 was simulated with an R2 of 0.82 when compared with field measured yield. Furthermore, we analysed the potential of assimilation of LAI into the LINTUL-3 model through the 'updating' assimilation technique. The deviation between measured and simulated yield decreased from 9371 kg/ha to 8729 kg/ha when assimilating weekly LAI measurements in the LINTUL model over the season of 2011. LINTUL-3 furthermore shows the main growth reducing factors, which are useful for farm decision support. The combination of crop models and sensor

Assimilative model for ionospheric dynamics employing delay, Doppler, and direction of arrival measurements from multiple HF channels

Science.gov (United States)

Fridman, Sergey V.; Nickisch, L. J.; Hausman, Mark; Zunich, George

2016-03-01

We describe the development of new HF data assimilation capabilities for our ionospheric inversion algorithm called GPSII (GPS Ionospheric Inversion). Previously existing capabilities of this algorithm included assimilation of GPS total electron content data as well as assimilation of backscatter ionograms. In the present effort we concentrated on developing assimilation tools for data related to HF propagation channels. Measurements of propagation delay, angle of arrival, and the ionosphere-induced Doppler from any number of known propagation links can now be utilized by GPSII. The resulting ionospheric model is consistent with all assimilated measurements. This means that ray tracing simulations of the assimilated propagation links are guaranteed to be in agreement with measured data within the errors of measurement. The key theoretical element for assimilating HF data is the raypath response operator (RPRO) which describes response of raypath parameters to infinitesimal variations of electron density in the ionosphere. We construct the RPRO out of the fundamental solution of linearized ray tracing equations for a dynamic magnetoactive plasma. We demonstrate performance and internal consistency of the algorithm using propagation delay data from multiple oblique ionograms (courtesy of Defence Science and Technology Organisation, Australia) as well as with time series of near-vertical incidence sky wave data (courtesy of the Intelligence Advanced Research Projects Activity HFGeo Program Government team). In all cases GPSII produces electron density distributions which are smooth in space and in time. We simulate the assimilated propagation links by performing ray tracing through GPSII-produced ionosphere and observe that simulated data are indeed in agreement with assimilated measurements.

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.

AMSR2 all-sky radiance assimilation and its impact on the analysis and forecast of Hurricane Sandy with a limited-area data assimilation system

Directory of Open Access Journals (Sweden)

Chun Yang

2016-06-01

Full Text Available A method to assimilate all-sky radiances from the Advanced Microwave Scanning Radiometer 2 (AMSR2 was developed within the Weather Research and Forecasting (WRF model's data assimilation (WRFDA system. The four essential elements are: (1 extending the community radiative transform model's (CRTM interface to include hydrometeor profiles; (2 using total water Qt as the moisture control variable; (3 using a warm-rain physics scheme for partitioning the Qt increment into individual increments of water vapour, cloud liquid water and rain; and (4 adopting a symmetric observation error model for all-sky radiance assimilation.Compared to a benchmark experiment with no AMSR2 data, the impact of assimilating clear-sky or all-sky AMSR2 radiances on the analysis and forecast of Hurricane Sandy (2012 was assessed through analysis/forecast cycling experiments using WRF and WRFDA's three-dimensional variational (3DVAR data assimilation scheme. With more cloud/precipitation-affected data being assimilated around tropical cyclone (TC core areas in the all-sky AMSR2 assimilation experiment, better analyses were obtained in terms of the TC's central sea level pressure (CSLP, warm-core structure and cloud distribution. Substantial (>20 % error reduction in track and CSLP forecasts was achieved from both clear-sky and all-sky AMSR2 assimilation experiments, and this improvement was consistent from the analysis time to 72-h forecasts. Moreover, the all-sky assimilation experiment consistently yielded better track and CSLP forecasts than the clear-sky did for all forecast lead times, due to a better analysis in the TC core areas. Positive forecast impact from assimilating AMSR2 radiances is also seen when verified against the European Center for Medium-Range Weather Forecasts (ECMWF analysis and the Stage IV precipitation analysis, with an overall larger positive impact from the all-sky assimilation experiment.

Problems of the orthogonalized plane wave method. 1

International Nuclear Information System (INIS)

Farberovich, O.V.; Kurganskii, S.I.; Domashevskaya, E.P.

1979-01-01

The main problems of the orthogonalized plane wave method are discussed including (a) consideration of core states; (b) effect of overlap of wave functions of external core states upon the band structure; (c) calculation of d-type states. The modified orthogonal plane wave method (MOPW method) of Deegan and Twose is applied in a general form to solve the problems of the usual OPW method. For the first time the influence on the spectrum of the main parameters of the MOPW method is studied systematically by calculating the electronic energy spectrum in the transition metals Nb and V. (author)

Disconfirmed hedonic expectations produce perceptual contrast, not assimilation.

Science.gov (United States)

Zellner, Debra A; Strickhouser, Dinah; Tornow, Carina E

2004-01-01

In studies of hedonic ratings, contrast is the usual result when expectations about test stimuli are produced through the presentation of context stimuli, whereas assimilation is the usual result when expectations about test stimuli are produced through labeling, advertising, or the relaying of information to the subject about the test stimuli. Both procedures produce expectations that are subsequently violated, but the outcomes are different. The present studies demonstrate that both assimilation and contrast can occur even when expectations are produced by verbal labels and the degree of violation of the expectation is held constant. One factor determining whether assimilation or contrast occurs appears to be the certainty of the expectation. Expectations that convey certainty are produced by methods that lead to social influence on subjects' ratings, producing assimilation. When social influence is not a factor and subjects give judgments influenced only by the perceived hedonic value of the stimulus, contrast is the result.

Multivariate and multiscale data assimilation in terrestrial systems: a review.

Science.gov (United States)

Montzka, Carsten; Pauwels, Valentijn R N; Franssen, Harrie-Jan Hendricks; Han, Xujun; Vereecken, Harry

2012-11-26

More and more terrestrial observational networks are being established to monitor climatic, hydrological and land-use changes in different regions of the World. In these networks, time series of states and fluxes are recorded in an automated manner, often with a high temporal resolution. These data are important for the understanding of water, energy, and/or matter fluxes, as well as their biological and physical drivers and interactions with and within the terrestrial system. Similarly, the number and accuracy of variables, which can be observed by spaceborne sensors, are increasing. Data assimilation (DA) methods utilize these observations in terrestrial models in order to increase process knowledge as well as to improve forecasts for the system being studied. The widely implemented automation in observing environmental states and fluxes makes an operational computation more and more feasible, and it opens the perspective of short-time forecasts of the state of terrestrial systems. In this paper, we review the state of the art with respect to DA focusing on the joint assimilation of observational data precedents from different spatial scales and different data types. An introduction is given to different DA methods, such as the Ensemble Kalman Filter (EnKF), Particle Filter (PF) and variational methods (3/4D-VAR). In this review, we distinguish between four major DA approaches: (1) univariate single-scale DA (UVSS), which is the approach used in the majority of published DA applications, (2) univariate multiscale DA (UVMS) referring to a methodology which acknowledges that at least some of the assimilated data are measured at a different scale than the computational grid scale, (3) multivariate single-scale DA (MVSS) dealing with the assimilation of at least two different data types, and (4) combined multivariate multiscale DA (MVMS). Finally, we conclude with a discussion on the advantages and disadvantages of the assimilation of multiple data types in a

Multivariate and Multiscale Data Assimilation in Terrestrial Systems: A Review

Directory of Open Access Journals (Sweden)

Harry Vereecken

2012-11-01

Full Text Available More and more terrestrial observational networks are being established to monitor climatic, hydrological and land-use changes in different regions of the World. In these networks, time series of states and fluxes are recorded in an automated manner, often with a high temporal resolution. These data are important for the understanding of water, energy, and/or matter fluxes, as well as their biological and physical drivers and interactions with and within the terrestrial system. Similarly, the number and accuracy of variables, which can be observed by spaceborne sensors, are increasing. Data assimilation (DA methods utilize these observations in terrestrial models in order to increase process knowledge as well as to improve forecasts for the system being studied. The widely implemented automation in observing environmental states and fluxes makes an operational computation more and more feasible, and it opens the perspective of short-time forecasts of the state of terrestrial systems. In this paper, we review the state of the art with respect to DA focusing on the joint assimilation of observational data precedents from different spatial scales and different data types. An introduction is given to different DA methods, such as the Ensemble Kalman Filter (EnKF, Particle Filter (PF and variational methods (3/4D-VAR. In this review, we distinguish between four major DA approaches: (1 univariate single-scale DA (UVSS, which is the approach used in the majority of published DA applications, (2 univariate multiscale DA (UVMS referring to a methodology which acknowledges that at least some of the assimilated data are measured at a different scale than the computational grid scale, (3 multivariate single-scale DA (MVSS dealing with the assimilation of at least two different data types, and (4 combined multivariate multiscale DA (MVMS. Finally, we conclude with a discussion on the advantages and disadvantages of the assimilation of multiple data types in a

Sequential assimilation of multi-mission dynamical topography into a global finite-element ocean model

Directory of Open Access Journals (Sweden)

S. Skachko

2008-12-01

Full Text Available This study focuses on an accurate estimation of ocean circulation via assimilation of satellite measurements of ocean dynamical topography into the global finite-element ocean model (FEOM. The dynamical topography data are derived from a complex analysis of multi-mission altimetry data combined with a referenced earth geoid. The assimilation is split into two parts. First, the mean dynamic topography is adjusted. To this end an adiabatic pressure correction method is used which reduces model divergence from the real evolution. Second, a sequential assimilation technique is applied to improve the representation of thermodynamical processes by assimilating the time varying dynamic topography. A method is used according to which the temperature and salinity are updated following the vertical structure of the first baroclinic mode. It is shown that the method leads to a partially successful assimilation approach reducing the rms difference between the model and data from 16 cm to 2 cm. This improvement of the mean state is accompanied by significant improvement of temporal variability in our analysis. However, it remains suboptimal, showing a tendency in the forecast phase of returning toward a free run without data assimilation. Both the mean difference and standard deviation of the difference between the forecast and observation data are reduced as the result of assimilation.

Studies on the translocation and distribution characteristics of carbon assimilates in blackberry

International Nuclear Information System (INIS)

Wang Shuyu; Liu Hongjia

1990-08-01

The translocation and distribution characteristics of carbon assimilates were studied with the method of 14 CO 2 feeding. The results indicated that there were different translocation and distribution characteristics of carbon assimilates among the upper, middle and lower leaves in a shoot during annual cycle. Taking away leaves, sun-shading and drought could raise the exporting ratio of carbon assimilates in the feeding leaves and could change the distributing model of the tree. Most of the carbon assimilates were translocated to basic born branch after sun-shading and drought

Data Assimilation to Extract Soil Moisture Information from SMAP Observations

Directory of Open Access Journals (Sweden)

Jana Kolassa

2017-11-01

Full Text Available This study compares different methods to extract soil moisture information through the assimilation of Soil Moisture Active Passive (SMAP observations. Neural network (NN and physically-based SMAP soil moisture retrievals were assimilated into the National Aeronautics and Space Administration (NASA Catchment model over the contiguous United States for April 2015 to March 2017. By construction, the NN retrievals are consistent with the global climatology of the Catchment model soil moisture. Assimilating the NN retrievals without further bias correction improved the surface and root zone correlations against in situ measurements from 14 SMAP core validation sites (CVS by 0.12 and 0.16, respectively, over the model-only skill, and reduced the surface and root zone unbiased root-mean-square error (ubRMSE by 0.005 m 3 m − 3 and 0.001 m 3 m − 3 , respectively. The assimilation reduced the average absolute surface bias against the CVS measurements by 0.009 m 3 m − 3 , but increased the root zone bias by 0.014 m 3 m − 3 . Assimilating the NN retrievals after a localized bias correction yielded slightly lower surface correlation and ubRMSE improvements, but generally the skill differences were small. The assimilation of the physically-based SMAP Level-2 passive soil moisture retrievals using a global bias correction yielded similar skill improvements, as did the direct assimilation of locally bias-corrected SMAP brightness temperatures within the SMAP Level-4 soil moisture algorithm. The results show that global bias correction methods may be able to extract more independent information from SMAP observations compared to local bias correction methods, but without accurate quality control and observation error characterization they are also more vulnerable to adverse effects from retrieval errors related to uncertainties in the retrieval inputs and algorithm. Furthermore, the results show that using global bias correction approaches without a

General method for designing wave shape transformers.

Science.gov (United States)

Ma, Hua; Qu, Shaobo; Xu, Zhuo; Wang, Jiafu

2008-12-22

An effective method for designing wave shape transformers (WSTs) is investigated by adopting the coordinate transformation theory. Following this method, the devices employed to transform electromagnetic (EM) wave fronts from one style with arbitrary shape and size to another style, can be designed. To verify this method, three examples in 2D spaces are also presented. Compared with the methods proposed in other literatures, this method offers the general procedure in designing WSTs, and thus is of great importance for the potential and practical applications possessed by such kinds of devices.

Statistical techniques to extract information during SMAP soil moisture assimilation

Science.gov (United States)

Kolassa, J.; Reichle, R. H.; Liu, Q.; Alemohammad, S. H.; Gentine, P.

2017-12-01

Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, the need for bias correction prior to an assimilation of these estimates is reduced, which could result in a more effective use of the independent information provided by the satellite observations. In this study, a statistical neural network (NN) retrieval algorithm is calibrated using SMAP brightness temperature observations and modeled soil moisture estimates (similar to those used to calibrate the SMAP Level 4 DA system). Daily values of surface soil moisture are estimated using the NN and then assimilated into the NASA Catchment model. The skill of the assimilation estimates is assessed based on a comprehensive comparison to in situ measurements from the SMAP core and sparse network sites as well as the International Soil Moisture Network. The NN retrieval assimilation is found to significantly improve the model skill, particularly in areas where the model does not represent processes related to agricultural practices. Additionally, the NN method is compared to assimilation experiments using traditional bias correction techniques. The NN retrieval assimilation is found to more effectively use the independent information provided by SMAP resulting in larger model skill improvements than assimilation experiments using traditional bias correction techniques.

Probabilistic forecasting and Bayesian data assimilation

CERN Document Server

Reich, Sebastian

2015-01-01

In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profusion of low-dimensional, discrete-time numerical examples designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. The McKean approach to sequential filtering in combination with coupling of measures serves as a unifying mathematical framework throughout Part II. Assuming only some basic familiarity with probability, this book is an ideal introduction for graduate students in ap...

Development Of A Data Assimilation Capability For RAPID

Science.gov (United States)

Emery, C. M.; David, C. H.; Turmon, M.; Hobbs, J.; Allen, G. H.; Famiglietti, J. S.

2017-12-01

The global decline of in situ observations associated with the increasing ability to monitor surface water from space motivates the creation of data assimilation algorithms that merge computer models and space-based observations to produce consistent estimates of terrestrial hydrology that fill the spatiotemporal gaps in observations. RAPID is a routing model based on the Muskingum method that is capable of estimating river streamflow over large scales with a relatively short computing time. This model only requires limited inputs: a reach-based river network, and lateral surface and subsurface flow into the rivers. The relatively simple model physics imply that RAPID simulations could be significantly improved by including a data assimilation capability. Here we present the early developments of such data assimilation approach into RAPID. Given the linear and matrix-based structure of the model, we chose to apply a direct Kalman filter, hence allowing for the preservation of high computational speed. We correct the simulated streamflows by assimilating streamflow observations and our early results demonstrate the feasibility of the approach. Additionally, the use of in situ gauges at continental scales motivates the application of our new data assimilation scheme to altimetry measurements from existing (e.g. EnviSat, Jason 2) and upcoming satellite missions (e.g. SWOT), and ultimately apply the scheme globally.

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...

Yeast identification: reassessment of assimilation tests as sole universal identifiers.

Science.gov (United States)

Spencer, J; Rawling, S; Stratford, M; Steels, H; Novodvorska, M; Archer, D B; Chandra, S

2011-11-01

To assess whether assimilation tests in isolation remain a valid method of identification of yeasts, when applied to a wide range of environmental and spoilage isolates. Seventy-one yeast strains were isolated from a soft drinks factory. These were identified using assimilation tests and by D1/D2 rDNA sequencing. When compared to sequencing, assimilation test identifications (MicroLog™) were 18·3% correct, a further 14·1% correct within the genus and 67·6% were incorrectly identified. The majority of the latter could be attributed to the rise in newly reported yeast species. Assimilation tests alone are unreliable as a universal means of yeast identification, because of numerous new species, variability of strains and increasing coincidence of assimilation profiles. Assimilation tests still have a useful role in the identification of common species, such as the majority of clinical isolates. It is probable, based on these results, that many yeast identifications reported in older literature are incorrect. This emphasizes the crucial need for accurate identification in present and future publications. © 2011 The Authors. Letters in Applied Microbiology © 2011 The Society for Applied Microbiology.

Empowering Geoscience with Improved Data Assimilation Using the Data Assimilation Research Testbed "Manhattan" Release.

Science.gov (United States)

Raeder, K.; Hoar, T. J.; Anderson, J. L.; Collins, N.; Hendricks, J.; Kershaw, H.; Ha, S.; Snyder, C.; Skamarock, W. C.; Mizzi, A. P.; Liu, H.; Liu, J.; Pedatella, N. M.; Karspeck, A. R.; Karol, S. I.; Bitz, C. M.; Zhang, Y.

2017-12-01

The capabilities of the Data Assimilation Research Testbed (DART) at NCAR have been significantly expanded with the recent "Manhattan" release. DART is an ensemble Kalman filter based suite of tools, which enables researchers to use data assimilation (DA) without first becoming DA experts. Highlights: significant improvement in efficient ensemble DA for very large models on thousands of processors, direct read and write of model state files in parallel, more control of the DA output for finer-grained analysis, new model interfaces which are useful to a variety of geophysical researchers, new observation forward operators and the ability to use precomputed forward operators from the forecast model. The new model interfaces and example applications include the following: MPAS-A; Model for Prediction Across Scales - Atmosphere is a global, nonhydrostatic, variable-resolution mesh atmospheric model, which facilitates multi-scale analysis and forecasting. The absence of distinct subdomains eliminates problems associated with subdomain boundaries. It demonstrates the ability to consistently produce higher-quality analyses than coarse, uniform meshes do. WRF-Chem; Weather Research and Forecasting + (MOZART) Chemistry model assimilates observations from FRAPPÉ (Front Range Air Pollution and Photochemistry Experiment). WACCM-X; Whole Atmosphere Community Climate Model with thermosphere and ionosphere eXtension assimilates observations of electron density to investigate sudden stratospheric warming. CESM (weakly) coupled assimilation; NCAR's Community Earth System Model is used for assimilation of atmospheric and oceanic observations into their respective components using coupled atmosphere+land+ocean+sea+ice forecasts. CESM2.0; Assimilation in the atmospheric component (CAM, WACCM) of the newly released version is supported. This version contains new and extensively updated components and software environment. CICE; Los Alamos sea ice model (in CESM) is used to assimilate

Variational data assimilation using targetted random walks

KAUST Repository

Cotter, S. L.

2011-02-15

The variational approach to data assimilation is a widely used methodology for both online prediction and for reanalysis. In either of these scenarios, it can be important to assess uncertainties in the assimilated state. Ideally, it is desirable to have complete information concerning the Bayesian posterior distribution for unknown state given data. We show that complete computational probing of this posterior distribution is now within the reach in the offline situation. We introduce a Markov chain-Monte Carlo (MCMC) method which enables us to directly sample from the Bayesian posterior distribution on the unknown functions of interest given observations. Since we are aware that these methods are currently too computationally expensive to consider using in an online filtering scenario, we frame this in the context of offline reanalysis. Using a simple random walk-type MCMC method, we are able to characterize the posterior distribution using only evaluations of the forward model of the problem, and of the model and data mismatch. No adjoint model is required for the method we use; however, more sophisticated MCMC methods are available which exploit derivative information. For simplicity of exposition, we consider the problem of assimilating data, either Eulerian or Lagrangian, into a low Reynolds number flow in a two-dimensional periodic geometry. We will show that in many cases it is possible to recover the initial condition and model error (which we describe as unknown forcing to the model) from data, and that with increasing amounts of informative data, the uncertainty in our estimations reduces. © 2011 John Wiley & Sons, Ltd.

Data assimilation of citizen collected information for real-time flood hazard mapping

Science.gov (United States)

Sayama, T.; Takara, K. T.

2017-12-01

Many studies in data assimilation in hydrology have focused on the integration of satellite remote sensing and in-situ monitoring data into hydrologic or land surface models. For flood predictions also, recent studies have demonstrated to assimilate remotely sensed inundation information with flood inundation models. In actual flood disaster situations, citizen collected information including local reports by residents and rescue teams and more recently tweets via social media also contain valuable information. The main interest of this study is how to effectively use such citizen collected information for real-time flood hazard mapping. Here we propose a new data assimilation technique based on pre-conducted ensemble inundation simulations and update inundation depth distributions sequentially when local data becomes available. The propose method is composed by the following two-steps. The first step is based on weighting average of preliminary ensemble simulations, whose weights are updated by Bayesian approach. The second step is based on an optimal interpolation, where the covariance matrix is calculated from the ensemble simulations. The proposed method was applied to case studies including an actual flood event occurred. It considers two situations with more idealized one by assuming continuous flood inundation depth information is available at multiple locations. The other one, which is more realistic case during such a severe flood disaster, assumes uncertain and non-continuous information is available to be assimilated. The results show that, in the first idealized situation, the large scale inundation during the flooding was estimated reasonably with RMSE effective. Nevertheless, the applications of the proposed data assimilation method demonstrated a high potential of this method for assimilating citizen collected information for real-time flood hazard mapping in the future.

Single-column data assimilation for the Atmospheric Radiation Measurement (ARM) Program

International Nuclear Information System (INIS)

Louis, J.F.

1994-01-01

The main purpose of the ARM program is to provide the necessary data to develop, test and validate the parameterization of clouds and of their interactions with the radiation field, and the computation of radiative transfer in climate models. For various reasons, much of the ARM observations will be imperfect, incomplete, redundant, indirect and unrepresentative. Various techniques of data assimilation have been developed to deal with these problems. The variational data assimilation and adjoint method applied to a single column model is described here. A model is used to simulate the evolution of the atmosphere during an assimilation period. As the model is run, a cost function is computed which is essentially a measure of simulation errors. The method then consists in adjusting some model parameters to minimize the cost function. Optimization of the model parameters needs to be done with a much longer series of data, to cover different meteorological situations. Once parameters are set, nudging terms are used as control variables. The Derber nudging method will require considerable tuning, especially in defining the vertical profiles of the nudging terms. Extensive tests are currently underway of both model optimization and data assimilation

A wave propagation matrix method in semiclassical theory

International Nuclear Information System (INIS)

Lee, S.Y.; Takigawa, N.

1977-05-01

A wave propagation matrix method is used to derive the semiclassical formulae of the multiturning point problem. A phase shift matrix and a barrier transformation matrix are introduced to describe the processes of a particle travelling through a potential well and crossing a potential barrier respectively. The wave propagation matrix is given by the products of phase shift matrices and barrier transformation matrices. The method to study scattering by surface transparent potentials and the Bloch wave in solids is then applied

Distorted wave method in reactions with composite particles

International Nuclear Information System (INIS)

Zelenskaya, N.S.; Teplov, I.B.

1980-01-01

The work deals with the distorbed wave method with a finite radius of interaction (DWBAFR) as applied to quantitative analysis of direct nuclear reactions with composite particles (including heavy ions) considering the reaction mechanisms other than the cluster stripping mechanism, in particular the exchange processes. The accurate equations of the distorbed-wave method in the three-body problem and the general formula dor calculating differential cross-sections of arbitrary binary reactions by DWBAFR are presented. Accurate and approximate methods allowing for finite interaction radius are discussed. Two main versions of exact account of recoil effects: separation of variables in wave functions of relative motion of particles and in interaction potentials and separation of variables in distorted waves are analysed. Given is a characteristic of the known calculated programs approximately and exactly taking account of recoil effects for direct and exchange processes [ru

Assimilation of SMOS Retrievals in the Land Information System

Science.gov (United States)

Blankenship, Clay B.; Case, Jonathan L.; Zavodsky, Bradley T.; Crosson, William L.

2016-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in the upper 5 cm with a 30-50 km resolution and a mission accuracy requirement of 0.04 cm(sub 3 cm(sub -3). These observations can be used to improve land surface model soil moisture states through data assimilation. In this paper, SMOS soil moisture retrievals are assimilated into the Noah land surface model via an Ensemble Kalman Filter within the NASA Land Information System. Bias correction is implemented using Cumulative Distribution Function (CDF) matching, with points aggregated by either land cover or soil type to reduce sampling error in generating the CDFs. An experiment was run for the warm season of 2011 to test SMOS data assimilation and to compare assimilation methods. Verification of soil moisture analyses in the 0-10 cm upper layer and root zone (0-1 m) was conducted using in situ measurements from several observing networks in the central and southeastern United States. This experiment showed that SMOS data assimilation significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10 cm layer. Time series at specific stations demonstrate the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared to using a simple uniform correction curve.

Triple collocation-based estimation of spatially correlated observation error covariance in remote sensing soil moisture data assimilation

Science.gov (United States)

Wu, Kai; Shu, Hong; Nie, Lei; Jiao, Zhenhang

2018-01-01

Spatially correlated errors are typically ignored in data assimilation, thus degenerating the observation error covariance R to a diagonal matrix. We argue that a nondiagonal R carries more observation information making assimilation results more accurate. A method, denoted TC_Cov, was proposed for soil moisture data assimilation to estimate spatially correlated observation error covariance based on triple collocation (TC). Assimilation experiments were carried out to test the performance of TC_Cov. AMSR-E soil moisture was assimilated with a diagonal R matrix computed using the TC and assimilated using a nondiagonal R matrix, as estimated by proposed TC_Cov. The ensemble Kalman filter was considered as the assimilation method. Our assimilation results were validated against climate change initiative data and ground-based soil moisture measurements using the Pearson correlation coefficient and unbiased root mean square difference metrics. These experiments confirmed that deterioration of diagonal R assimilation results occurred when model simulation is more accurate than observation data. Furthermore, nondiagonal R achieved higher correlation coefficient and lower ubRMSD values over diagonal R in experiments and demonstrated the effectiveness of TC_Cov to estimate richly structuralized R in data assimilation. In sum, compared with diagonal R, nondiagonal R may relieve the detrimental effects of assimilation when simulated model results outperform observation data.

Data assimilation and PWR primary measurement

International Nuclear Information System (INIS)

Mercier, Thibaud

2015-01-01

A Pressurized Water Reactor (PWR) Reactor Coolant System (RCS) is a highly complex physical process: heterogeneous power, flow and temperature distributions are difficult to be accurately measured, since instrumentations are limited in number, thus leading to the relevant safety and protection margins. EDF R and D is seeking to assess the potential benefits of applying Data Assimilation to a PWR's RCS (Reactor Coolant System) measurements, in order to improve the estimators for parameters of a reactor's operating setpoint, i.e. improving accuracy and reducing uncertainties and biases of measured RCS parameters. In this thesis, we define a 0D semi-empirical model for RCS, satisfying the description level usually chosen by plant operators, and construct a Monte-Carlo Method (inspired from Ensemble Methods) in order to use this model with Data Assimilation tools. We apply this method on simulated data in order to assess the reduction of uncertainties on key parameters: results are beyond expectations, however strong hypothesis are required, implying a careful preprocessing of input data. (author)

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

Science.gov (United States)

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.

Assimilation of satellite altimeter data into an open ocean model

Science.gov (United States)

Vogeler, Armin; SchröTer, Jens

1995-08-01

Geosat sea surface height data are assimilated into an eddy-resolving quasi-geostrophic open ocean model using the adjoint technique. The method adjusts the initial conditions for all layers and is successful on the timescale of a few weeks. Time-varying values for the open boundaries are prescribed by a much larger quasi-geostrophic model of the Antarctic Circumpolar Current (ACC). Both models have the same resolution of approximately 20×20 km (1/3°×1/6°), have three layers, and include realistic bottom topography and coastlines. The open model box is embedded in the African sector of the ACC. For continuous assimilation of satellite data into the larger model the nudging technique is applied. These results are used for the adjoint optimization procedure as boundary conditions and as a first guess for the initial condition. For the open model box the difference between model and satellite sea surface height that remains after the nudging experiment amounts to a 19-cm root-mean-square error (rmse). By assimilation into the regional model this value can be reduced to a 6-cm rmse for an assimilation period of 20 days. Several experiments which attempt to improve the convergence of the iterative optimization method are reported. Scaling and regularization by smoothing have to be applied carefully. Especially during the first 10 iterations, the convergence can be improved considerably by low-pass filtering of the cost function gradient. The result of a perturbation experiment shows that for longer assimilation periods the influence of the boundary values becomes dominant and they should be determined inversely by data assimilation into the open ocean model.

Application of Observed Precipitation in NCEP Global and Regional Data Assimilation Systems, Including Reanalysis and Land Data Assimilation

Science.gov (United States)

Mitchell, K. E.

2006-12-01

precipitation analyses by other institutions. Other global precipitation analyses produced by other methodologies are also used by EMC in certain applications, such as CPC's well-known satellite-IR based technique known as "GPI", and satellite-microwave based estimates from NESDIS or NASA. Finally, the presentation will cover the three assimilation methods used by EMC to assimilate precipitation data, including 1) 3D-VAR variational assimilation in NCEP's Global Data Assimilation System (GDAS), 2) direct insertion of precipitation-inferred vertical latent heating profiles in NCEP's N. American Data Assimilation System (NDAS) and its N. American Regional Reanalysis (NARR) counterpart, and 3) direct use of observed precipitation to drive the Noah land model component of NCEP's Global and N. American Land Data Assimilation Systems (GLDAS and NLDAS). In the applications of precipitation analyses in data assimilation at NCEP, the analyses are temporally disaggregated to hourly or less using time-weights calculated from A) either radar-based estimates or an analysis of hourly gauge-observations for the CONUS-domain daily precipitation analyses, or B) global model forecasts of 6-hourly precipitation (followed by linear interpolation to hourly or less) for the global CMAP precipitation analysis.

Determination of optimum "multi-channel surface wave method" field parameters.

Science.gov (United States)

2012-12-01

Multi-channel surface wave methods (especially the multi-channel analyses of surface wave method; MASW) are routinely used to : determine the shear-wave velocity of the subsurface to depths of 100 feet for site classification purposes. Users are awar...

Mediterranea Forecasting System: a focus on wave-current coupling

Science.gov (United States)

Clementi, Emanuela; Delrosso, Damiano; Pistoia, Jenny; Drudi, Massimiliano; Fratianni, Claudia; Grandi, Alessandro; Pinardi, Nadia; Oddo, Paolo; Tonani, Marina

2016-04-01

The Mediterranean Forecasting System (MFS) is a numerical ocean prediction system that produces analyses, reanalyses and short term forecasts for the entire Mediterranean Sea and its Atlantic Ocean adjacent areas. MFS became operational in the late 90's and has been developed and continuously improved in the framework of a series of EU and National funded programs and is now part of the Copernicus Marine Service. The MFS is composed by the hydrodynamic model NEMO (Nucleus for European Modelling of the Ocean) 2-way coupled with the third generation wave model WW3 (WaveWatchIII) implemented in the Mediterranean Sea with 1/16 horizontal resolution and forced by ECMWF atmospheric fields. The model solutions are corrected by the data assimilation system (3D variational scheme adapted to the oceanic assimilation problem) with a daily assimilation cycle, using a background error correlation matrix varying seasonally and in different sub-regions of the Mediterranean Sea. The focus of this work is to present the latest modelling system upgrades and the related achieved improvements. In order to evaluate the performance of the coupled system a set of experiments has been built by coupling the wave and circulation models that hourly exchange the following fields: the sea surface currents and air-sea temperature difference are transferred from NEMO model to WW3 model modifying respectively the mean momentum transfer of waves and the wind speed stability parameter; while the neutral drag coefficient computed by WW3 model is passed to NEMO that computes the turbulent component. In order to validate the modelling system, numerical results have been compared with in-situ and remote sensing data. This work suggests that a coupled model might be capable of a better description of wave-current interactions, in particular feedback from the ocean to the waves might assess an improvement on the prediction capability of wave characteristics, while suggests to proceed toward a fully

Land Surface Data Assimilation

Science.gov (United States)

Houser, P. R.

2012-12-01

Information about land surface water, energy and carbon conditions is of critical importance to real-world applications such as agricultural production, water resource management, flood prediction, water supply, weather and climate forecasting, and environmental preservation. While ground-based observational networks are improving, the only practical way to observe these land surface states on continental to global scales is via satellites. Remote sensing can make spatially comprehensive measurements of various components of the terrestrial system, but it cannot provide information on the entire system (e.g. evaporation), and the observations represent only an instant in time. Land surface process models may be used to predict temporal and spatial terrestrial dynamics, but these predictions are often poor, due to model initialization, parameter and forcing, and physics errors. Therefore, an attractive prospect is to combine the strengths of land surface models and observations (and minimize the weaknesses) to provide a superior terrestrial state estimate. This is the goal of land surface data assimilation. Data Assimilation combines observations into a dynamical model, using the model's equations to provide time continuity and coupling between the estimated fields. Land surface data assimilation aims to utilize both our land surface process knowledge, as embodied in a land surface model, and information that can be gained from observations. Both model predictions and observations are imperfect and we wish to use both synergistically to obtain a more accurate result. Moreover, both contain different kinds of information, that when used together, provide an accuracy level that cannot be obtained individually. Model biases can be mitigated using a complementary calibration and parameterization process. Limited point measurements are often used to calibrate the model(s) and validate the assimilation results. This presentation will provide a brief background on land

Data Assimilation by delay-coordinate nudging

Science.gov (United States)

Pazo, Diego; Lopez, Juan Manuel; Carrassi, Alberto

2016-04-01

A new nudging method for data assimilation, delay-coordinate nudging, is presented. Delay-coordinate nudging makes explicit use of present and past observations in the formulation of the forcing driving the model evolution at each time-step. Numerical experiments with a low order chaotic system show that the new method systematically outperforms standard nudging in different model and observational scenarios, also when using an un-optimized formulation of the delay-nudging coefficients. A connection between the optimal delay and the dominant Lyapunov exponent of the dynamics is found based on heuristic arguments and is confirmed by the numerical results, providing a guideline for the practical implementation of the algorithm. Delay-coordinate nudging preserves the easiness of implementation, the intuitive functioning and the reduced computational cost of the standard nudging, making it a potential alternative especially in the field of seasonal-to-decadal predictions with large Earth system models that limit the use of more sophisticated data assimilation procedures.

Impact of Assimilation on Heavy Rainfall Simulations Using WRF Model: Sensitivity of Assimilation Results to Background Error Statistics

Science.gov (United States)

Rakesh, V.; Kantharao, B.

2017-03-01

Data assimilation is considered as one of the effective tools for improving forecast skill of mesoscale models. However, for optimum utilization and effective assimilation of observations, many factors need to be taken into account while designing data assimilation methodology. One of the critical components that determines the amount and propagation observation information into the analysis, is model background error statistics (BES). The objective of this study is to quantify how BES in data assimilation impacts on simulation of heavy rainfall events over a southern state in India, Karnataka. Simulations of 40 heavy rainfall events were carried out using Weather Research and Forecasting Model with and without data assimilation. The assimilation experiments were conducted using global and regional BES while the experiment with no assimilation was used as the baseline for assessing the impact of data assimilation. The simulated rainfall is verified against high-resolution rain-gage observations over Karnataka. Statistical evaluation using several accuracy and skill measures shows that data assimilation has improved the heavy rainfall simulation. Our results showed that the experiment using regional BES outperformed the one which used global BES. Critical thermo-dynamic variables conducive for heavy rainfall like convective available potential energy simulated using regional BES is more realistic compared to global BES. It is pointed out that these results have important practical implications in design of forecast platforms while decision-making during extreme weather events

Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models

Science.gov (United States)

Mazzoleni, Maurizio; Alfonso, Leonardo; Chacon-Hurtado, Juan; Solomatine, Dimitri

2015-09-01

Catastrophic floods cause significant socio-economical losses. Non-structural measures, such as real-time flood forecasting, can potentially reduce flood risk. To this end, data assimilation methods have been used to improve flood forecasts by integrating static ground observations, and in some cases also remote sensing observations, within water models. Current hydrologic and hydraulic research works consider assimilation of observations coming from traditional, static sensors. At the same time, low-cost, mobile sensors and mobile communication devices are becoming also increasingly available. The main goal and innovation of this study is to demonstrate the usefulness of assimilating uncertain streamflow observations that are dynamic in space and intermittent in time in the context of two different semi-distributed hydrological model structures. The developed method is applied to the Brue basin, where the dynamic observations are imitated by the synthetic observations of discharge. The results of this study show how model structures and sensors locations affect in different ways the assimilation of streamflow observations. In addition, it proves how assimilation of such uncertain observations from dynamic sensors can provide model improvements similar to those of streamflow observations coming from a non-optimal network of static physical sensors. This can be a potential application of recent efforts to build citizen observatories of water, which can make the citizens an active part in information capturing, evaluation and communication, helping simultaneously to improvement of model-based flood forecasting.

Joint Center for Satellite Data Assimilation Overview and Research Activities

Science.gov (United States)

Auligne, T.

2017-12-01

In 2001 NOAA/NESDIS, NOAA/NWS, NOAA/OAR, and NASA, subsequently joined by the US Navy and Air Force, came together to form the Joint Center for Satellite Data Assimilation (JCSDA) for the common purpose of accelerating the use of satellite data in environmental numerical prediction modeling by developing, using, and anticipating advances in numerical modeling, satellite-based remote sensing, and data assimilation methods. The primary focus was to bring these advances together to improve operational numerical model-based forecasting, under the premise that these partners have common technical and logistical challenges assimilating satellite observations into their modeling enterprises that could be better addressed through cooperative action and/or common solutions. Over the last 15 years, the JCSDA has made and continues to make major contributions to operational assimilation of satellite data. The JCSDA is a multi-agency U.S. government-owned-and-operated organization that was conceived as a venue for the several agencies NOAA, NASA, USAF and USN to collaborate on advancing the development and operational use of satellite observations into numerical model-based environmental analysis and forecasting. The primary mission of the JCSDA is to "accelerate and improve the quantitative use of research and operational satellite data in weather, ocean, climate and environmental analysis and prediction systems." This mission is fulfilled through directed research targeting the following key science objectives: Improved radiative transfer modeling; new instrument assimilation; assimilation of humidity, clouds, and precipitation observations; assimilation of land surface observations; assimilation of ocean surface observations; atmospheric composition; and chemistry and aerosols. The goal of this presentation is to briefly introduce the JCSDA's mission and vision, and to describe recent research activities across various JCSDA partners.

[Simulation of water and carbon fluxes in harvard forest area based on data assimilation method].

Science.gov (United States)

Zhang, Ting-Long; Sun, Rui; Zhang, Rong-Hua; Zhang, Lei

2013-10-01

Model simulation and in situ observation are the two most important means in studying the water and carbon cycles of terrestrial ecosystems, but have their own advantages and shortcomings. To combine these two means would help to reflect the dynamic changes of ecosystem water and carbon fluxes more accurately. Data assimilation provides an effective way to integrate the model simulation and in situ observation. Based on the observation data from the Harvard Forest Environmental Monitoring Site (EMS), and by using ensemble Kalman Filter algorithm, this paper assimilated the field measured LAI and remote sensing LAI into the Biome-BGC model to simulate the water and carbon fluxes in Harvard forest area. As compared with the original model simulated without data assimilation, the improved Biome-BGC model with the assimilation of the field measured LAI in 1998, 1999, and 2006 increased the coefficient of determination R2 between model simulation and flux observation for the net ecosystem exchange (NEE) and evapotranspiration by 8.4% and 10.6%, decreased the sum of absolute error (SAE) and root mean square error (RMSE) of NEE by 17.7% and 21.2%, and decreased the SAE and RMSE of the evapotranspiration by 26. 8% and 28.3%, respectively. After assimilated the MODIS LAI products of 2000-2004 into the improved Biome-BGC model, the R2 between simulated and observed results of NEE and evapotranspiration was increased by 7.8% and 4.7%, the SAE and RMSE of NEE were decreased by 21.9% and 26.3%, and the SAE and RMSE of evapotranspiration were decreased by 24.5% and 25.5%, respectively. It was suggested that the simulation accuracy of ecosystem water and carbon fluxes could be effectively improved if the field measured LAI or remote sensing LAI was integrated into the model.

Four-dimensional variational data assimilation for inverse modelling of atmospheric methane emissions: method and comparison with synthesis inversion

Directory of Open Access Journals (Sweden)

J. F. Meirink

2008-11-01

Full Text Available A four-dimensional variational (4D-Var data assimilation system for inverse modelling of atmospheric methane emissions is presented. The system is based on the TM5 atmospheric transport model. It can be used for assimilating large volumes of measurements, in particular satellite observations and quasi-continuous in-situ observations, and at the same time it enables the optimization of a large number of model parameters, specifically grid-scale emission rates. Furthermore, the variational method allows to estimate uncertainties in posterior emissions. Here, the system is applied to optimize monthly methane emissions over a 1-year time window on the basis of surface observations from the NOAA-ESRL network. The results are rigorously compared with an analogous inversion by Bergamaschi et al. (2007, which was based on the traditional synthesis approach. The posterior emissions as well as their uncertainties obtained in both inversions show a high degree of consistency. At the same time we illustrate the advantage of 4D-Var in reducing aggregation errors by optimizing emissions at the grid scale of the transport model. The full potential of the assimilation system is exploited in Meirink et al. (2008, who use satellite observations of column-averaged methane mixing ratios to optimize emissions at high spatial resolution, taking advantage of the zooming capability of the TM5 model.

A case study of GWE satellite data impact on GLA assimilation analyses of two ocean cyclones

Science.gov (United States)

Gallimore, R. G.; Johnson, D. R.

1986-01-01

The effects of the Global Weather Experiment (GWE) data obtained on January 18-20, 1979 on Goddard Laboratory for Atmospheres assimilation analyses of simultaneous cyclones in the western Pacific and Atlantic oceans are examined. The ability of satellite data within assimilation models to determine the baroclinic structures of developing extratropical cyclones is evaluated. The impact of the satellite data on the amplitude and phase of the temperature structure within the storm domain, potential energy, and baroclinic growth rate is studied. The GWE data are compared with Data Systems Test results. It is noted that it is necessary to characterize satellite effects on the baroclinic structure of cyclone waves which degrade numerical weather predictions of cyclogenesis.

Assimilation of qualitative hydrological information in water-related risk framework

Science.gov (United States)

Mazzoleni, Maurizio; Alfonso, Leonardo; Solomatine, Dimitri

2013-04-01

In recent years water-related risks are increasing worldwide. In particular, floods have been one of the most damaging natural disasters in Europe, in terms of economic losses. Non-structural measures such as flood risk mapping are generally used to reduce the impact of flood in important area. The increasing data availability makes it possible to develop new models which can be used to assimilate different kinds of information and reduce the uncertainty of the state of a basin. The aim of this work is to propose a methodology to assimilate uncertain, qualitative information within hydrological models in order to improve the evaluation of catchment responses. Qualitative information is defined here as the one that can be interpreted as and assimilated into a hydrological model as a fuzzy value, for instance those coming from text messages or citizen's pictures. The methodology is applied in the Brue catchment, located in the South West of England, having a drainage area of 135 km2, average annual rainfall of 867 mm and average discharge of 1.92 m3/s at Lovington considering the period among 1961 and 1990. In order to estimate the response of the catchment to a flood event with given intensity, a conceptual distributed hydrological model was implemented. First, the basin was divided in different sub-basins, then, the hydrograph at the outlet section was estimated using a Nash cascade model and the propagation of the flood wave was carried out considering the lag time in the other each sub-basins. The assimilation of the qualitative information was carried out using different techniques. The results of this work show how the spatial location and uncertainty of the qualitative information can affect the flow hydrograph in the outlet section and the consequent flood extent in the downstream area. This study is part of the FP7 European Project WeSenseIt.

Towards a Comprehensive Dynamic-chemistry Assimilation for Eos-Chem: Plans and Status in NASA's Data Assimilation Office

Science.gov (United States)

Pawson, Steven; Lin, Shian-Jiann; Rood, Richard B.; Stajner, Ivanka; Nebuda, Sharon; Nielsen, J. Eric; Douglass, Anne R.

2000-01-01

In order to support the EOS-Chem project, a comprehensive assimilation package for the coupled chemical-dynamical system is being developed by the Data Assimilation Office at NASA GSFC. This involves development of a coupled chemistry/meteorology model and of data assimilation techniques for trace species and meteorology. The model is being developed using the flux-form semi-Lagrangian dynamical core of Lin and Rood, the physical parameterizations from the NCAR Community Climate Model, and atmospheric chemistry modules from the Atmospheric Chemistry and Dynamics branch at NASA GSFC. To date the following results have been obtained: (i) multi-annual simulations with the dynamics-radiation model show the credibility of the package for atmospheric simulations; (ii) initial simulations including a limited number of middle atmospheric trace gases reveal the realistic nature of transport mechanisms, although there is still a need for some improvements. Samples of these results will be shown. A meteorological assimilation system is currently being constructed using the model; this will form the basis for the proposed meteorological/chemical assimilation package. The latter part of the presentation will focus on areas targeted for development in the near and far terms, with the objective of Providing a comprehensive assimilation package for the EOS-Chem science experiment. The first stage will target ozone assimilation. The plans also encompass a reanalysis (ReSTS) for the 1991-1995 period, which includes the Mt. Pinatubo eruption and the time when a large number of UARS observations were available. One of the most challenging aspects of future developments will be to couple theoretical advances in tracer assimilation with the practical considerations of a real environment and eventually a near-real-time assimilation system.

Satellite Data Assimilation within KIAPS-LETKF system

Science.gov (United States)

Jo, Y.; Lee, S., Sr.; Cho, K.

2016-12-01

Korea Institute of Atmospheric Prediction Systems (KIAPS) has been developing an ensemble data assimilation system using four-dimensional local ensemble transform kalman filter (LETKF; Hunt et al., 2007) within KIAPS Integrated Model (KIM), referred to as "KIAPS-LETKF". KIAPS-LETKF system was successfully evaluated with various Observing System Simulation Experiments (OSSEs) with NCAR Community Atmospheric Model - Spectral Element (Kang et al., 2013), which has fully unstructured quadrilateral meshes based on the cubed-sphere grid as the same grid system of KIM. Recently, assimilation of real observations has been conducted within the KIAPS-LETKF system with four-dimensional covariance functions over the 6-hr assimilation window. Then, conventional (e.g., sonde, aircraft, and surface) and satellite (e.g., AMSU-A, IASI, GPS-RO, and AMV) observations have been provided by the KIAPS Package for Observation Processing (KPOP). Wind speed prediction was found most beneficial due to ingestion of AMV and for the temperature prediction the improvement in assimilation is mostly due to ingestion of AMSU-A and IASI. However, some degradation in the simulation of the GPS-RO is presented in the upper stratosphere, even though GPS-RO leads positive impacts on the analysis and forecasts. We plan to test the bias correction method and several vertical localization strategies for radiance observations to improve analysis and forecast impacts.

Methodological Developments in Geophysical Assimilation Modeling

Science.gov (United States)

Christakos, George

2005-06-01

This work presents recent methodological developments in geophysical assimilation research. We revisit the meaning of the term "solution" of a mathematical model representing a geophysical system, and we examine its operational formulations. We argue that an assimilation solution based on epistemic cognition (which assumes that the model describes incomplete knowledge about nature and focuses on conceptual mechanisms of scientific thinking) could lead to more realistic representations of the geophysical situation than a conventional ontologic assimilation solution (which assumes that the model describes nature as is and focuses on form manipulations). Conceptually, the two approaches are fundamentally different. Unlike the reasoning structure of conventional assimilation modeling that is based mainly on ad hoc technical schemes, the epistemic cognition approach is based on teleologic criteria and stochastic adaptation principles. In this way some key ideas are introduced that could open new areas of geophysical assimilation to detailed understanding in an integrated manner. A knowledge synthesis framework can provide the rational means for assimilating a variety of knowledge bases (general and site specific) that are relevant to the geophysical system of interest. Epistemic cognition-based assimilation techniques can produce a realistic representation of the geophysical system, provide a rigorous assessment of the uncertainty sources, and generate informative predictions across space-time. The mathematics of epistemic assimilation involves a powerful and versatile spatiotemporal random field theory that imposes no restriction on the shape of the probability distributions or the form of the predictors (non-Gaussian distributions, multiple-point statistics, and nonlinear models are automatically incorporated) and accounts rigorously for the uncertainty features of the geophysical system. In the epistemic cognition context the assimilation concept may be used to

Coupled assimilation for an intermediated coupled ENSO prediction model

Science.gov (United States)

Zheng, Fei; Zhu, Jiang

2010-10-01

The value of coupled assimilation is discussed using an intermediate coupled model in which the wind stress is the only atmospheric state which is slavery to model sea surface temperature (SST). In the coupled assimilation analysis, based on the coupled wind-ocean state covariance calculated from the coupled state ensemble, the ocean state is adjusted by assimilating wind data using the ensemble Kalman filter. As revealed by a series of assimilation experiments using simulated observations, the coupled assimilation of wind observations yields better results than the assimilation of SST observations. Specifically, the coupled assimilation of wind observations can help to improve the accuracy of the surface and subsurface currents because the correlation between the wind and ocean currents is stronger than that between SST and ocean currents in the equatorial Pacific. Thus, the coupled assimilation of wind data can decrease the initial condition errors in the surface/subsurface currents that can significantly contribute to SST forecast errors. The value of the coupled assimilation of wind observations is further demonstrated by comparing the prediction skills of three 12-year (1997-2008) hindcast experiments initialized by the ocean-only assimilation scheme that assimilates SST observations, the coupled assimilation scheme that assimilates wind observations, and a nudging scheme that nudges the observed wind stress data, respectively. The prediction skills of two assimilation schemes are significantly better than those of the nudging scheme. The prediction skills of assimilating wind observations are better than assimilating SST observations. Assimilating wind observations for the 2007/2008 La Niña event triggers better predictions, while assimilating SST observations fails to provide an early warning for that event.

Motion estimation by data assimilation in reduced dynamic models

International Nuclear Information System (INIS)

Drifi, Karim

2013-01-01

Motion estimation is a major challenge in the field of image sequence analysis. This thesis is a study of the dynamics of geophysical flows visualized by satellite imagery. Satellite image sequences are currently underused for the task of motion estimation. A good understanding of geophysical flows allows a better analysis and forecast of phenomena in domains such as oceanography and meteorology. Data assimilation provides an excellent framework for achieving a compromise between heterogeneous data, especially numerical models and observations. Hence, in this thesis we set out to apply variational data assimilation methods to estimate motion on image sequences. As one of the major drawbacks of applying these assimilation techniques is the considerable computation time and memory required, we therefore define and use a model reduction method in order to significantly decrease the necessary computation time and the memory. We then explore the possibilities that reduced models provide for motion estimation, particularly the possibility of strictly imposing some known constraints on the computed solutions. In particular, we show how to estimate a divergence free motion with boundary conditions on a complex spatial domain [fr

Data assimilation in hydrological modelling

DEFF Research Database (Denmark)

Drecourt, Jean-Philippe

Data assimilation is an invaluable tool in hydrological modelling as it allows to efficiently combine scarce data with a numerical model to obtain improved model predictions. In addition, data assimilation also provides an uncertainty analysis of the predictions made by the hydrological model....... In this thesis, the Kalman filter is used for data assimilation with a focus on groundwater modelling. However the developed techniques are general and can be applied also in other modelling domains. Modelling involves conceptualization of the processes of Nature. Data assimilation provides a way to deal...... with model non-linearities and biased errors. A literature review analyzes the most popular techniques and their application in hydrological modelling. Since bias is an important problem in groundwater modelling, two bias aware Kalman filters have been implemented and compared using an artificial test case...

Uncertainty of Flood Forecasting Based on Radar Rainfall Data Assimilation

Directory of Open Access Journals (Sweden)

Xinchi Chen

2016-01-01

Full Text Available Precipitation is the core data input to hydrological forecasting. The uncertainty in precipitation forecast data can lead to poor performance of predictive hydrological models. Radar-based precipitation measurement offers advantages over ground-based measurement in the quantitative estimation of temporal and spatial aspects of precipitation, but errors inherent in this method will still act to reduce the performance. Using data from White Lotus River of Hubei Province, China, five methods were used to assimilate radar rainfall data transformed from the classified Z-R relationship, and the postassimilation data were compared with precipitation measured by rain gauges. The five sets of assimilated rainfall data were then used as input to the Xinanjiang model. The effect of precipitation data input error on runoff simulation was analyzed quantitatively by disturbing the input data using the Breeding of Growing Modes method. The results of practical application demonstrated that the statistical weight integration and variational assimilation methods were superior. The corresponding performance in flood hydrograph prediction was also better using the statistical weight integration and variational methods compared to the others. It was found that the errors of radar rainfall data disturbed by the Breeding of Growing Modes had a tendency to accumulate through the hydrological model.

Satellite Sounder Data Assimilation for Improving Alaska Region Weather Forecast

Science.gov (United States)

Zhu, Jiang; Stevens, E.; Zavodsky, B. T.; Zhang, X.; Heinrichs, T.; Broderson, D.

2014-01-01

Data assimilation has been demonstrated very useful in improving both global and regional numerical weather prediction. Alaska has very coarser surface observation sites. On the other hand, it gets much more satellite overpass than lower 48 states. How to utilize satellite data to improve numerical prediction is one of hot topics among weather forecast community in Alaska. The Geographic Information Network of Alaska (GINA) at University of Alaska is conducting study on satellite data assimilation for WRF model. AIRS/CRIS sounder profile data are used to assimilate the initial condition for the customized regional WRF model (GINA-WRF model). Normalized standard deviation, RMSE, and correlation statistic analysis methods are applied to analyze one case of 48 hours forecasts and one month of 24-hour forecasts in order to evaluate the improvement of regional numerical model from Data assimilation. The final goal of the research is to provide improved real-time short-time forecast for Alaska regions.

On the retrieval of significant wave heights from spaceborne Synthetic Aperture Radar using the Max-Planck Institut algorithm.

Science.gov (United States)

Violante-Carvalho, Nelson

2005-12-01

Synthetic Aperture Radar (SAR) onboard satellites is the only source of directional wave spectra with continuous and global coverage. Millions of SAR Wave Mode (SWM) imagettes have been acquired since the launch in the early 1990's of the first European Remote Sensing Satellite ERS-1 and its successors ERS-2 and ENVISAT, which has opened up many possibilities specially for wave data assimilation purposes. The main aim of data assimilation is to improve the forecasting introducing available observations into the modeling procedures in order to minimize the differences between model estimates and measurements. However there are limitations in the retrieval of the directional spectrum from SAR images due to nonlinearities in the mapping mechanism. The Max-Planck Institut (MPI) scheme, the first proposed and most widely used algorithm to retrieve directional wave spectra from SAR images, is employed to compare significant wave heights retrieved from ERS-1 SAR against buoy measurements and against the WAM wave model. It is shown that for periods shorter than 12 seconds the WAM model performs better than the MPI, despite the fact that the model is used as first guess to the MPI method, that is the retrieval is deteriorating the first guess. For periods longer than 12 seconds, the part of the spectrum that is directly measured by SAR, the performance of the MPI scheme is at least as good as the WAM model.

Projector augmented wave method: ab initio molecular dynamics ...

Indian Academy of Sciences (India)

Unknown

kinetic energy is small and the wave function is smooth. However, the wave ... and various strategies have been developed. ... methods let us briefly review the history of augmented ..... alleviated by adding an intelligent zero: If an operator B.

Data Assimilation in Marine Models

DEFF Research Database (Denmark)

Frydendall, Jan

maximum likelihood framework. These issues are discussed in paper B. The third part of the thesis falls a bit out of the above context is work published in papers C, F. In the first paper, a simple data assimilation scheme was investigated to examine the potential benefits of incorporating a data......This thesis consists of six research papers published or submitted for publication in the period 2006-2009 together with a summary report. The main topics of this thesis are nonlinear data assimilation techniques and estimation in dynamical models. The focus has been on the nonlinear filtering...... techniques for large scale geophysical numerical models and making them feasible to work with in the data assimilation framework. The filtering techniques investigated are all Monte Carlo simulation based. Some very nice features that can be exploited in the Monte Carlo based data assimilation framework from...

IMITATING MODEL OF ASSIMILATION AND FORGETTING OF THE LOGICALLY CONNECTED INFORMATION

Directory of Open Access Journals (Sweden)

Robert Valerievich Mayer

2017-09-01

Full Text Available The educational material we present as a set of a number of information blocks consisting of learning material elements (LMEs; therefore its assimilation and forgetting occurs differently, than in the Ebbinghaus’s experiments. The purpose of the article is constructing of a computer model of assimilation and forgetting of the logically connected information allowing: 1 to prove the fast rise of understanding while training; 2 to receive the forgetting curve for the comprehended information. The modeling methods help to receive the graphs of the knowledge level dependence on time. It is shown, that the processes of assimilation and forgetting occurs according to the logistic law.

Music playlist generation by assimilating GMMs into SOMs

NARCIS (Netherlands)

Balkema, Wietse; van der Heijden, Ferdinand

A method for music playlist generation, using assimilated Gaussian mixture models (GMMs) in self organizing maps (SOMs) is presented. Traditionally, the neurons in a SOM are represented by vectors, but in this paper we propose to use GMMs instead. To this end, we introduce a method to adapt a GMM

Assimilation of Gridded GRACE Terrestrial Water Storage Estimates in the North American Land Data Assimilation System

Science.gov (United States)

Kumar, Sujay V.; Zaitchik, Benjamin F.; Peters-Lidard, Christa D.; Rodell, Matthew; Reichle, Rolf; Li, Bailing; Jasinski, Michael; Mocko, David; Getirana, Augusto; De Lannoy, Gabrielle;

An Efficient Local Correlation Matrix Decomposition Approach for the Localization Implementation of Ensemble-Based Assimilation Methods

Science.gov (United States)

Zhang, Hongqin; Tian, Xiangjun

2018-04-01

Ensemble-based data assimilation methods often use the so-called localization scheme to improve the representation of the ensemble background error covariance (Be). Extensive research has been undertaken to reduce the computational cost of these methods by using the localized ensemble samples to localize Be by means of a direct decomposition of the local correlation matrix C. However, the computational costs of the direct decomposition of the local correlation matrix C are still extremely high due to its high dimension. In this paper, we propose an efficient local correlation matrix decomposition approach based on the concept of alternating directions. This approach is intended to avoid direct decomposition of the correlation matrix. Instead, we first decompose the correlation matrix into 1-D correlation matrices in the three coordinate directions, then construct their empirical orthogonal function decomposition at low resolution. This procedure is followed by the 1-D spline interpolation process to transform the above decompositions to the high-resolution grid. Finally, an efficient correlation matrix decomposition is achieved by computing the very similar Kronecker product. We conducted a series of comparison experiments to illustrate the validity and accuracy of the proposed local correlation matrix decomposition approach. The effectiveness of the proposed correlation matrix decomposition approach and its efficient localization implementation of the nonlinear least-squares four-dimensional variational assimilation are further demonstrated by several groups of numerical experiments based on the Advanced Research Weather Research and Forecasting model.

ASSIMILATION OF COARSE-SCALEDATAUSINGTHE ENSEMBLE KALMAN FILTER

KAUST Repository

Efendiev, Yalchin

2011-01-01

Reservoir data is usually scale dependent and exhibits multiscale features. In this paper we use the ensemble Kalman filter (EnKF) to integrate data at different spatial scales for estimating reservoir fine-scale characteristics. Relationships between the various scales is modeled via upscaling techniques. We propose two versions of the EnKF to assimilate the multiscale data, (i) where all the data are assimilated together and (ii) the data are assimilated sequentially in batches. Ensemble members obtained after assimilating one set of data are used as a prior to assimilate the next set of data. Both of these versions are easily implementable with any other upscaling which links the fine to the coarse scales. The numerical results with different methods are presented in a twin experiment setup using a two-dimensional, two-phase (oil and water) flow model. Results are shown with coarse-scale permeability and coarse-scale saturation data. They indicate that additional data provides better fine-scale estimates and fractional flow predictions. We observed that the two versions of the EnKF differed in their estimates when coarse-scale permeability is provided, whereas their results are similar when coarse-scale saturation is used. This behavior is thought to be due to the nonlinearity of the upscaling operator in the case of the former data. We also tested our procedures with various precisions of the coarse-scale data to account for the inexact relationship between the fine and coarse scale data. As expected, the results show that higher precision in the coarse-scale data yielded improved estimates. With better coarse-scale modeling and inversion techniques as more data at multiple coarse scales is made available, the proposed modification to the EnKF could be relevant in future studies.

The extended (G/G)-expansion method and travelling wave ...

Indian Academy of Sciences (India)

In this paper, we construct the travelling wave solutions to the perturbed nonlinear Schrödinger's equation (NLSE) with Kerr law non-linearity by the extended (′/)-expansion method. Based on this method, we obtain abundant exact travelling wave solutions of NLSE with Kerr law nonlinearity with arbitrary parameters.

The Seasonal Cycle of Water Vapour on Mars from Assimilation of Thermal Emission Spectrometer Data

Science.gov (United States)

Steele, Liam J.; Lewis, Stephen R.; Patel, Manish R.; Montmessin, Franck; Forget, Francois; Smith, Michael D.

2014-01-01

We present for the first time an assimilation of Thermal Emission Spectrometer (TES) water vapour column data into a Mars global climate model (MGCM). We discuss the seasonal cycle of water vapour, the processes responsible for the observed water vapour distribution, and the cross-hemispheric water transport. The assimilation scheme is shown to be robust in producing consistent reanalyses, and the global water vapour column error is reduced to around 2-4 pr micron depending on season. Wave activity is shown to play an important role in the water vapour distribution, with topographically steered flows around the Hellas and Argyre basins acting to increase transport in these regions in all seasons. At high northern latitudes, zonal wavenumber 1 and 2 stationary waves during northern summer are responsible for spreading the sublimed water vapour away from the pole. Transport by the zonal wavenumber 2 waves occurs primarily to the west of Tharsis and Arabia Terra and, combined with the effects of western boundary currents, this leads to peak water vapour column abundances here as observed by numerous spacecraft. A net transport of water to the northern hemisphere over the course of one Mars year is calculated, primarily because of the large northwards flux of water vapour which occurs during the local dust storm around L(sub S) = 240-260deg. Finally, outlying frost deposits that surround the north polar cap are shown to be important in creating the peak water vapour column abundances observed during northern summer.

UNIFICATION AND APPLICATIONS OF MODERN OCEANIC/ATMOSPHERIC DATA ASSIMILATION ALGORITHMS

Institute of Scientific and Technical Information of China (English)

QIAO Fang-li; ZHANG Shao-qing; YUAN Ye-li

2004-01-01

The key mathematics and applications of various modern atmospheric/oceanic data assimilation methods including Optimal Interpolation(OI),4-dimensional variational approach(4D-Var)and filters were systematically reviewed and classified.Based on the data assimilation philosophy,I.e.,using model dynamics to extract the observational information,the common character of the problem,such as the probabilistic nature of the evolution of the atmospheric/oceanic system,noisy and irregularly spaced observations,and the advantages and disadvantages of these data assimilation algorithms,were discussed.In the filtering framework,all modern data assimilation algorithms were unified: OI/3D-Var is a stationary filter,4D-Var is a linear(Kalman)filter and an ensemble of Kalman filters is able to construct a nonlinear filter.The nonlinear filter such as the Ensemble Kalman Filter(ENKF),Ensemble Adjustment Kalman Filter(EAKF)and Ensemble Transformation Kalman Filter(ETKF)can,to some extent,account for the non-Gaussian information of the prior distribution from the model.The flow-dependent covariance estimated by an ensemble filter may be introduced to OI and 4D-Var to improve these traditional algorithms.In practice,the performance of algorithms may depend on the specific numerical model and the choice of algorithm may depend on the specific problem.However,the unification of algorithms allows us to establish a unified test system to evaluate these algorithms,which provides more insights into data assimilation philosophies and helps improve data assimilation techniques.

IASI Radiance Data Assimilation in Local Ensemble Transform Kalman Filter

Science.gov (United States)

Cho, K.; Hyoung-Wook, C.; Jo, Y.

2016-12-01

Korea institute of Atmospheric Prediction Systems (KIAPS) is developing NWP model with data assimilation systems. Local Ensemble Transform Kalman Filter (LETKF) system, one of the data assimilation systems, has been developed for KIAPS Integrated Model (KIM) based on cubed-sphere grid and has successfully assimilated real data. LETKF data assimilation system has been extended to 4D- LETKF which considers time-evolving error covariance within assimilation window and IASI radiance data assimilation using KPOP (KIAPS package for observation processing) with RTTOV (Radiative Transfer for TOVS). The LETKF system is implementing semi operational prediction including conventional (sonde, aircraft) observation and AMSU-A (Advanced Microwave Sounding Unit-A) radiance data from April. Recently, the semi operational prediction system updated radiance observations including GPS-RO, AMV, IASI (Infrared Atmospheric Sounding Interferometer) data at July. A set of simulation of KIM with ne30np4 and 50 vertical levels (of top 0.3hPa) were carried out for short range forecast (10days) within semi operation prediction LETKF system with ensemble forecast 50 members. In order to only IASI impact, our experiments used only conventional and IAIS radiance data to same semi operational prediction set. We carried out sensitivity test for IAIS thinning method (3D and 4D). IASI observation number was increased by temporal (4D) thinning and the improvement of IASI radiance data impact on the forecast skill of model will expect.

Assimilation of microwave brightness temperatures for soil moisture estimation using particle filter

International Nuclear Information System (INIS)

Bi, H Y; Ma, J W; Qin, S X; Zeng, J Y

2014-01-01

Soil moisture plays a significant role in global water cycles. Both model simulations and remote sensing observations have their limitations when estimating soil moisture on a large spatial scale. Data assimilation (DA) is a promising tool which can combine model dynamics and remote sensing observations to obtain more precise ground soil moisture distribution. Among various DA methods, the particle filter (PF) can be applied to non-linear and non-Gaussian systems, thus holding great potential for DA. In this study, a data assimilation scheme based on the residual resampling particle filter (RR-PF) was developed to assimilate microwave brightness temperatures into the macro-scale semi-distributed Variance Infiltration Capacity (VIC) Model to estimate surface soil moisture. A radiative transfer model (RTM) was used to link brightness temperatures with surface soil moisture. Finally, the data assimilation scheme was validated by experimental data obtained at Arizona during the Soil Moisture Experiment 2004 (SMEX04). The results show that the estimation accuracy of soil moisture can be improved significantly by RR-PF through assimilating microwave brightness temperatures into VIC model. Both the overall trends and specific values of the assimilation results are more consistent with ground observations compared with model simulation results

expansion method and travelling wave solutions for the perturbed ...

Indian Academy of Sciences (India)

Abstract. In this paper, we construct the travelling wave solutions to the perturbed nonlinear. Schrödinger's equation (NLSE) with Kerr law non-linearity by the extended (G /G)-expansion method. Based on this method, we obtain abundant exact travelling wave solutions of NLSE with. Kerr law nonlinearity with arbitrary ...

Comparison of matrix methods for elastic wave scattering problems

International Nuclear Information System (INIS)

Tsao, S.J.; Varadan, V.K.; Varadan, V.V.

1983-01-01

This article briefly describes the T-matrix method and the MOOT (method of optimal truncation) of elastic wave scattering as they apply to A-D, SH- wave problems as well as 3-D elastic wave problems. Two methods are compared for scattering by elliptical cylinders as well as oblate spheroids of various eccentricity as a function of frequency. Convergence, and symmetry of the scattering cross section are also compared for ellipses and spheroidal cavities of different aspect ratios. Both the T-matrix approach and the MOOT were programmed on an AMDHL 470 computer using double precision arithmetic. Although the T-matrix method and MOOT are not always in agreement, it is in no way implied that any of the published results using MOOT are in error

Simulation of breaking waves using the high-order spectral method with laboratory experiments: wave-breaking energy dissipation

Science.gov (United States)

Seiffert, Betsy R.; Ducrozet, Guillaume

2018-01-01

We examine the implementation of a wave-breaking mechanism into a nonlinear potential flow solver. The success of the mechanism will be studied by implementing it into the numerical model HOS-NWT, which is a computationally efficient, open source code that solves for the free surface in a numerical wave tank using the high-order spectral (HOS) method. Once the breaking mechanism is validated, it can be implemented into other nonlinear potential flow models. To solve for wave-breaking, first a wave-breaking onset parameter is identified, and then a method for computing wave-breaking associated energy loss is determined. Wave-breaking onset is calculated using a breaking criteria introduced by Barthelemy et al. (J Fluid Mech https://arxiv.org/pdf/1508.06002.pdf, submitted) and validated with the experiments of Saket et al. (J Fluid Mech 811:642-658, 2017). Wave-breaking energy dissipation is calculated by adding a viscous diffusion term computed using an eddy viscosity parameter introduced by Tian et al. (Phys Fluids 20(6): 066,604, 2008, Phys Fluids 24(3), 2012), which is estimated based on the pre-breaking wave geometry. A set of two-dimensional experiments is conducted to validate the implemented wave breaking mechanism at a large scale. Breaking waves are generated by using traditional methods of evolution of focused waves and modulational instability, as well as irregular breaking waves with a range of primary frequencies, providing a wide range of breaking conditions to validate the solver. Furthermore, adjustments are made to the method of application and coefficient of the viscous diffusion term with negligible difference, supporting the robustness of the eddy viscosity parameter. The model is able to accurately predict surface elevation and corresponding frequency/amplitude spectrum, as well as energy dissipation when compared with the experimental measurements. This suggests the model is capable of calculating wave-breaking onset and energy dissipation

Extreme Wave Analysis by Integrating Model and Wave Buoy Data

Directory of Open Access Journals (Sweden)

Fabio Dentale

2018-03-01

Full Text Available Estimating the extreme values of significant wave height (HS, generally described by the HS return period TR function HS(TR and by its confidence intervals, is a necessity in many branches of coastal science and engineering. The availability of indirect wave data generated by global and regional wind and wave model chains have brought radical changes to the estimation procedures of such probability distribution—weather and wave modeling systems are routinely run all over the world, and HS time series for each grid point are produced and published after assimilation (analysis of the ground truth. However, while the sources of such indirect data are numerous, and generally of good quality, many aspects of their procedures are hidden to the users, who cannot evaluate the reliability and the limits of the HS(TR deriving from such data. In order to provide a simple engineering tool to evaluate the probability of extreme sea-states as well as the quality of such estimates, we propose here a procedure based on integrating HS time series generated by model chains with those recorded by wave buoys in the same area.

Skill Assessment in Ocean Biological Data Assimilation

Science.gov (United States)

Gregg, Watson W.; Friedrichs, Marjorie A. M.; Robinson, Allan R.; Rose, Kenneth A.; Schlitzer, Reiner; Thompson, Keith R.; Doney, Scott C.

2008-01-01

There is growing recognition that rigorous skill assessment is required to understand the ability of ocean biological models to represent ocean processes and distributions. Statistical analysis of model results with observations represents the most quantitative form of skill assessment, and this principle serves as well for data assimilation models. However, skill assessment for data assimilation requires special consideration. This is because there are three sets of information in the free-run model, data, and the assimilation model, which uses Data assimilation information from both the flee-run model and the data. Intercom parison of results among the three sets of information is important and useful for assessment, but is not conclusive since the three information sets are intertwined. An independent data set is necessary for an objective determination. Other useful measures of ocean biological data assimilation assessment include responses of unassimilated variables to the data assimilation, performance outside the prescribed region/time of interest, forecasting, and trend analysis. Examples of each approach from the literature are provided. A comprehensive list of ocean biological data assimilation and their applications of skill assessment, in both ecosystem/biogeochemical and fisheries efforts, is summarized.

Data assimilation techniques in modeling ocean processes

Digital Repository Service at National Institute of Oceanography (India)

Mahadevan, R.; Fernandes, A.A.; Naqvi, S.W.A.

are usually called data analysis or assimilation. These homogeneous fields are prerequisites for various practical applications and theoretical studies. The fields produced by an analysi the one hand, they must be close to the observations.... The practical usefulness of variational methods for meteorological problems are pointed out very early by Sasaki (1955, 1958), but in spite of that these methods have not been fully utilized. Probably, the complex mathematical technicality of these methods...

Treating Sample Covariances for Use in Strongly Coupled Atmosphere-Ocean Data Assimilation

Science.gov (United States)

Smith, Polly J.; Lawless, Amos S.; Nichols, Nancy K.

2018-01-01

Strongly coupled data assimilation requires cross-domain forecast error covariances; information from ensembles can be used, but limited sampling means that ensemble derived error covariances are routinely rank deficient and/or ill-conditioned and marred by noise. Thus, they require modification before they can be incorporated into a standard assimilation framework. Here we compare methods for improving the rank and conditioning of multivariate sample error covariance matrices for coupled atmosphere-ocean data assimilation. The first method, reconditioning, alters the matrix eigenvalues directly; this preserves the correlation structures but does not remove sampling noise. We show that it is better to recondition the correlation matrix rather than the covariance matrix as this prevents small but dynamically important modes from being lost. The second method, model state-space localization via the Schur product, effectively removes sample noise but can dampen small cross-correlation signals. A combination that exploits the merits of each is found to offer an effective alternative.

Real-space grid implementation of the projector augmented wave method

DEFF Research Database (Denmark)

Mortensen, Jens Jørgen; Hansen, Lars Bruno; Jacobsen, Karsten Wedel

2005-01-01

A grid-based real-space implementation of the projector augmented wave sPAWd method of Blöchl fPhys. Rev. B 50, 17953 s1994dg for density functional theory sDFTd calculations is presented. The use of uniform three-dimensional s3Dd real-space grids for representing wave functions, densities...... valence wave functions that can be represented on relatively coarse grids. We demonstrate the accuracy of the method by calculating the atomization energies of 20 small molecules, and the bulk modulus and lattice constants of bulk aluminum. We show that the approach in terms of computational efficiency...... is comparable to standard plane-wave methods, but the memory requirements are higher....

Ensemble-Based Data Assimilation in Reservoir Characterization: A Review

Directory of Open Access Journals (Sweden)

Seungpil Jung

2018-02-01

Full Text Available This paper presents a review of ensemble-based data assimilation for strongly nonlinear problems on the characterization of heterogeneous reservoirs with different production histories. It concentrates on ensemble Kalman filter (EnKF and ensemble smoother (ES as representative frameworks, discusses their pros and cons, and investigates recent progress to overcome their drawbacks. The typical weaknesses of ensemble-based methods are non-Gaussian parameters, improper prior ensembles and finite population size. Three categorized approaches, to mitigate these limitations, are reviewed with recent accomplishments; improvement of Kalman gains, add-on of transformation functions, and independent evaluation of observed data. The data assimilation in heterogeneous reservoirs, applying the improved ensemble methods, is discussed on predicting unknown dynamic data in reservoir characterization.

Assimilating concentration observations for transport and dispersion modeling in a meandering wind field

Science.gov (United States)

Haupt, Sue Ellen; Beyer-Lout, Anke; Long, Kerrie J.; Young, George S.

Assimilating concentration data into an atmospheric transport and dispersion model can provide information to improve downwind concentration forecasts. The forecast model is typically a one-way coupled set of equations: the meteorological equations impact the concentration, but the concentration does not generally affect the meteorological field. Thus, indirect methods of using concentration data to influence the meteorological variables are required. The problem studied here involves a simple wind field forcing Gaussian dispersion. Two methods of assimilating concentration data to infer the wind direction are demonstrated. The first method is Lagrangian in nature and treats the puff as an entity using feature extraction coupled with nudging. The second method is an Eulerian field approach akin to traditional variational approaches, but minimizes the error by using a genetic algorithm (GA) to directly optimize the match between observations and predictions. Both methods show success at inferring the wind field. The GA-variational method, however, is more accurate but requires more computational time. Dynamic assimilation of a continuous release modeled by a Gaussian plume is also demonstrated using the genetic algorithm approach.

Reflection and diffraction of atomic de Broglie waves by evanescent laser waves. Bare-state method

International Nuclear Information System (INIS)

Feng, Xiaoping; Witte, N.S.; Hollenberg, C.L.; Opat, G.

1994-01-01

Two methods are presented for the investigation of the reflection and diffraction of atoms by gratings formed either by standing or travelling evanescent laser waves. Both methods use the bare-state rather than dressed-state picture. One method is based on the Born series, whereas the other is based on the Laplace transformation of the coupled differential equations. The two methods yield the same theoretical expressions for the reflected and diffracted atomic waves in the whole space including the interaction and the asymptotic regions. 1 ref., 1 fig

Symmetrized partial-wave method for density-functional cluster calculations

International Nuclear Information System (INIS)

Averill, F.W.; Painter, G.S.

1994-01-01

The computational advantage and accuracy of the Harris method is linked to the simplicity and adequacy of the reference-density model. In an earlier paper, we investigated one way the Harris functional could be extended to systems outside the limits of weakly interacting atoms by making the charge density of the interacting atoms self-consistent within the constraints of overlapping spherical atomic densities. In the present study, a method is presented for augmenting the interacting atom charge densities with symmetrized partial-wave expansions on each atomic site. The added variational freedom of the partial waves leads to a scheme capable of giving exact results within a given exchange-correlation approximation while maintaining many of the desirable convergence and stability properties of the original Harris method. Incorporation of the symmetry of the cluster in the partial-wave construction further reduces the level of computational effort. This partial-wave cluster method is illustrated by its application to the dimer C 2 , the hypothetical atomic cluster Fe 6 Al 8 , and the benzene molecule

Efficient Data Assimilation Algorithms for Bathymetry Applications

Science.gov (United States)

Ghorbanidehno, H.; Kokkinaki, A.; Lee, J. H.; Farthing, M.; Hesser, T.; Kitanidis, P. K.; Darve, E. F.

2016-12-01

Information on the evolving state of the nearshore zone bathymetry is crucial to shoreline management, recreational safety, and naval operations. The high cost and complex logistics of using ship-based surveys for bathymetry estimation have encouraged the use of remote sensing monitoring. Data assimilation methods combine monitoring data and models of nearshore dynamics to estimate the unknown bathymetry and the corresponding uncertainties. Existing applications have been limited to the basic Kalman Filter (KF) and the Ensemble Kalman Filter (EnKF). The former can only be applied to low-dimensional problems due to its computational cost; the latter often suffers from ensemble collapse and uncertainty underestimation. This work explores the use of different variants of the Kalman Filter for bathymetry applications. In particular, we compare the performance of the EnKF to the Unscented Kalman Filter and the Hierarchical Kalman Filter, both of which are KF variants for non-linear problems. The objective is to identify which method can better handle the nonlinearities of nearshore physics, while also having a reasonable computational cost. We present two applications; first, the bathymetry of a synthetic one-dimensional cross section normal to the shore is estimated from wave speed measurements. Second, real remote measurements with unknown error statistics are used and compared to in situ bathymetric survey data collected at the USACE Field Research Facility in Duck, NC. We evaluate the information content of different data sets and explore the impact of measurement error and nonlinearities.

Analysis of efficient preconditioned defect correction methods for nonlinear water waves

DEFF Research Database (Denmark)

Engsig-Karup, Allan Peter

2014-01-01

Robust computational procedures for the solution of non-hydrostatic, free surface, irrotational and inviscid free-surface water waves in three space dimensions can be based on iterative preconditioned defect correction (PDC) methods. Such methods can be made efficient and scalable to enable...... prediction of free-surface wave transformation and accurate wave kinematics in both deep and shallow waters in large marine areas or for predicting the outcome of experiments in large numerical wave tanks. We revisit the classical governing equations are fully nonlinear and dispersive potential flow...... equations. We present new detailed fundamental analysis using finite-amplitude wave solutions for iterative solvers. We demonstrate that the PDC method in combination with a high-order discretization method enables efficient and scalable solution of the linear system of equations arising in potential flow...

Simulation of breaking waves using the high-order spectral method with laboratory experiments: Wave-breaking onset

Science.gov (United States)

Seiffert, Betsy R.; Ducrozet, Guillaume; Bonnefoy, Félicien

2017-11-01

This study investigates a wave-breaking onset criteria to be implemented in the non-linear potential flow solver HOS-NWT. The model is a computationally efficient, open source code, which solves for the free surface in a numerical wave tank using the High-Order Spectral (HOS) method. The goal of this study is to determine the best method to identify the onset of random single and multiple breaking waves over a large domain at the exact time they occur. To identify breaking waves, a breaking onset criteria based on the ratio of local energy flux velocity to the local crest velocity, introduced by Barthelemy et al. (2017) is selected. The breaking parameter is uniquely applied in the numerical model in that calculations of the breaking onset criteria ratio are not made only at the location of the wave crest, but at every point in the domain and at every time step. This allows the model to calculate the onset of a breaking wave the moment it happens, and without knowing anything about the wave a priori. The application of the breaking criteria at every point in the domain and at every time step requires the phase velocity to be calculated instantaneously everywhere in the domain and at every time step. This is achieved by calculating the instantaneous phase velocity using the Hilbert transform and dispersion relation. A comparison between more traditional crest-tracking techniques shows the calculation of phase velocity using Hilbert transform at the location of the breaking wave crest provides a good approximation of crest velocity. The ability of the selected wave breaking criteria to predict single and multiple breaking events in two dimensions is validated by a series of large-scale experiments. Breaking waves are generated by energy focusing and modulational instability methods, with a wide range of primary frequencies. Steep irregular waves which lead to breaking waves, and irregular waves with an energy focusing wave superimposed are also generated. This set of

Damage detection in composite materials using Lamb wave methods

Science.gov (United States)

Kessler, Seth S.; Spearing, S. Mark; Soutis, Constantinos

2002-04-01

Cost-effective and reliable damage detection is critical for the utilization of composite materials. This paper presents part of an experimental and analytical survey of candidate methods for in situ damage detection of composite materials. Experimental results are presented for the application of Lamb wave techniques to quasi-isotropic graphite/epoxy test specimens containing representative damage modes, including delamination, transverse ply cracks and through-holes. Linear wave scans were performed on narrow laminated specimens and sandwich beams with various cores by monitoring the transmitted waves with piezoceramic sensors. Optimal actuator and sensor configurations were devised through experimentation, and various types of driving signal were explored. These experiments provided a procedure capable of easily and accurately determining the time of flight of a Lamb wave pulse between an actuator and sensor. Lamb wave techniques provide more information about damage presence and severity than previously tested methods (frequency response techniques), and provide the possibility of determining damage location due to their local response nature. These methods may prove suitable for structural health monitoring applications since they travel long distances and can be applied with conformable piezoelectric actuators and sensors that require little power.

ERP ASSIMILATION: AN END-USER APPROACH

Directory of Open Access Journals (Sweden)

Hurbean Luminita

2013-07-01

The paper discusses the ERP adoption based on the IT assimilation theory. The ERP lifecycle is associated with the IT assimilation steps. We propose a distribution of these steps along the lifecycle. Derived from the findings in the reviewed literature we will focus the cultural factors, in particular those related to the end-users (determined as a major impact factor in our previous study: Negovan et al., 2011. Our empirical study is centred on the end-users perspective and it tries to determine if and how their behaviour affects the achievement of the ERP assimilation steps. The paper reasons that organizations that understand the IT assimilation steps correlated to the ERP implementation critical factors are more likely to implement and use ERP successfully.

Mathematical foundations of hybrid data assimilation from a synchronization perspective

Science.gov (United States)

Penny, Stephen G.

2017-12-01

The state-of-the-art data assimilation methods used today in operational weather prediction centers around the world can be classified as generalized one-way coupled impulsive synchronization. This classification permits the investigation of hybrid data assimilation methods, which combine dynamic error estimates of the system state with long time-averaged (climatological) error estimates, from a synchronization perspective. Illustrative results show how dynamically informed formulations of the coupling matrix (via an Ensemble Kalman Filter, EnKF) can lead to synchronization when observing networks are sparse and how hybrid methods can lead to synchronization when those dynamic formulations are inadequate (due to small ensemble sizes). A large-scale application with a global ocean general circulation model is also presented. Results indicate that the hybrid methods also have useful applications in generalized synchronization, in particular, for correcting systematic model errors.

Data-Driven Model Uncertainty Estimation in Hydrologic Data Assimilation

Science.gov (United States)

Pathiraja, S.; Moradkhani, H.; Marshall, L.; Sharma, A.; Geenens, G.

2018-02-01

The increasing availability of earth observations necessitates mathematical methods to optimally combine such data with hydrologic models. Several algorithms exist for such purposes, under the umbrella of data assimilation (DA). However, DA methods are often applied in a suboptimal fashion for complex real-world problems, due largely to several practical implementation issues. One such issue is error characterization, which is known to be critical for a successful assimilation. Mischaracterized errors lead to suboptimal forecasts, and in the worst case, to degraded estimates even compared to the no assimilation case. Model uncertainty characterization has received little attention relative to other aspects of DA science. Traditional methods rely on subjective, ad hoc tuning factors or parametric distribution assumptions that may not always be applicable. We propose a novel data-driven approach (named SDMU) to model uncertainty characterization for DA studies where (1) the system states are partially observed and (2) minimal prior knowledge of the model error processes is available, except that the errors display state dependence. It includes an approach for estimating the uncertainty in hidden model states, with the end goal of improving predictions of observed variables. The SDMU is therefore suited to DA studies where the observed variables are of primary interest. Its efficacy is demonstrated through a synthetic case study with low-dimensional chaotic dynamics and a real hydrologic experiment for one-day-ahead streamflow forecasting. In both experiments, the proposed method leads to substantial improvements in the hidden states and observed system outputs over a standard method involving perturbation with Gaussian noise.

Parabolic approximation method for fast magnetosonic wave propagation in tokamaks

International Nuclear Information System (INIS)

Phillips, C.K.; Perkins, F.W.; Hwang, D.Q.

1985-07-01

Fast magnetosonic wave propagation in a cylindrical tokamak model is studied using a parabolic approximation method in which poloidal variations of the wave field are considered weak in comparison to the radial variations. Diffraction effects, which are ignored by ray tracing mthods, are included self-consistently using the parabolic method since continuous representations for the wave electromagnetic fields are computed directly. Numerical results are presented which illustrate the cylindrical convergence of the launched waves into a diffraction-limited focal spot on the cyclotron absorption layer near the magnetic axis for a wide range of plasma confinement parameters

Numerical method for wave forces acting on partially perforated caisson

Science.gov (United States)

Jiang, Feng; Tang, Xiao-cheng; Jin, Zhao; Zhang, Li; Chen, Hong-zhou

2015-04-01

The perforated caisson is widely applied to practical engineering because of its great advantages in effectively wave energy consumption and cost reduction. The attentions of many scientists were paid to the fluid-structure interaction between wave and perforated caisson studies, but until now, most concerns have been put on theoretical analysis and experimental model set up. In this paper, interaction between the wave and the partial perforated caisson in a 2D numerical wave flume is investigated by means of the renewed SPH algorithm, and the mathematical equations are in the form of SPH numerical approximation based on Navier-Stokes equations. The validity of the SPH mathematical method is examined and the simulated results are compared with the results of theoretical models, meanwhile the complex hydrodynamic characteristics when the water particles flow in or out of a wave absorbing chamber are analyzed and the wave pressure distribution of the perforated caisson is also addressed here. The relationship between the ratio of total horizontal force acting on caisson under regular waves and its influence factors is examined. The data show that the numerical calculation of the ratio of total horizontal force meets the empirical regression equation very well. The simulations of SPH about the wave nonlinearity and breaking are briefly depicted in the paper, suggesting that the advantages and great potentiality of the SPH method is significant compared with traditional methods.

S-wave velocity measurements along levees in New Orleans using passive surface wave methods

Science.gov (United States)

Hayashi, K.; Lorenzo, J. M.; Craig, M. S.; Gostic, A.

2017-12-01

In order to develop non-invasive methods for levee inspection, geophysical investigations were carried out at four sites along levees in the New Orleans area: 17th Street Canal, London Avenue Canal, Marrero Levee, and Industrial Canal. Three of the four sites sustained damage from Hurricane Katrina in 2005 and have since been rebuilt. The geophysical methods used include active and passive surface wave methods, and capacitively coupled resistivity. This paper summarizes the acquisition and analysis of the 1D and 2D passive surface wave data. Twelve wireless seismic data acquisition units with 2 Hz vertical component geophones were used to record data. Each unit includes a GPS receiver so that all units can be synchronized over any distance without cables. The 1D passive method used L shaped arrays of three different sizes with geophone spacing ranging from 5 to 340 m. Ten minutes to one hour of ambient noise was recorded with each array, and total data acquisition took approximately two hours at each site. The 2D method used a linear array with a geophone spacing of 5m. Four geophones were moved forward every 10 minutes along 400 1000 m length lines. Data acquisition took several hours for each line. Recorded ambient noise was processed using the spatial autocorrelation method and clear dispersion curves were obtained at all sites (Figure 1a). Minimum frequencies ranged from 0.4 to 0.7 Hz and maximum frequencies ranged from 10 to 30 Hz depending on the site. Non-linear inversion was performed and 1D and 2D S-wave velocity models were obtained. The 1D method penetrated to depths ranging from 200 to 500 m depending on the site (Figure 1b). The 2D method penetrated to a depth of 40 60 m and provided 400 1000 m cross sections along the levees (Figure 2). The interpretation focused on identifying zones beneath the levees or canal walls having low S-wave velocities corresponding to saturated, unconsolidated sands, or low-rigidity clays. Resultant S-wave velocity profiles

Producing accurate wave propagation time histories using the global matrix method

International Nuclear Information System (INIS)

Obenchain, Matthew B; Cesnik, Carlos E S

2013-01-01

This paper presents a reliable method for producing accurate displacement time histories for wave propagation in laminated plates using the global matrix method. The existence of inward and outward propagating waves in the general solution is highlighted while examining the axisymmetric case of a circular actuator on an aluminum plate. Problems with previous attempts to isolate the outward wave for anisotropic laminates are shown. The updated method develops a correction signal that can be added to the original time history solution to cancel the inward wave and leave only the outward propagating wave. The paper demonstrates the effectiveness of the new method for circular and square actuators bonded to the surface of isotropic laminates, and these results are compared with exact solutions. Results for circular actuators on cross-ply laminates are also presented and compared with experimental results, showing the ability of the new method to successfully capture the displacement time histories for composite laminates. (paper)

Assessing the value of variational assimilation of streamflow data into distributed hydrologic models for improved streamflow monitoring and prediction at ungauged and gauged locations in the catchment

Science.gov (United States)

Lee, Hak Su; Seo, Dong-Jun; Liu, Yuqiong; McKee, Paul; Corby, Robert

2010-05-01

State updating of distributed hydrologic models via assimilation of streamflow data is subject to "overfitting" because large dimensionality of the state space of the model may render the assimilation problem seriously underdetermined. To examine the issue in the context of operational hydrology, we carried out a set of real-world experiments in which we assimilate streamflow data at interior and/or outlet locations into gridded SAC and kinematic-wave routing models of the U.S. National Weather Service (NWS) Research Distributed Hydrologic Model (RDHM). We used for the experiments nine basins in the southern plains of the U.S. The experiments consist of selectively assimilating streamflow at different gauge locations, outlet and/or interior, and carrying out both dependent and independent validation. To assess the sensitivity of the quality of assimilation-aided streamflow simulation to the reduced dimensionality of the state space, we carried out data assimilation at spatially semi-distributed or lumped scale and by adjusting biases in precipitation and potential evaporation at a 6-hourly or larger scale. In this talk, we present the results and findings.

Improving operational flood forecasting through data assimilation

Science.gov (United States)

Rakovec, Oldrich; Weerts, Albrecht; Uijlenhoet, Remko; Hazenberg, Pieter; Torfs, Paul

2010-05-01

Accurate flood forecasts have been a challenging topic in hydrology for decades. Uncertainty in hydrological forecasts is due to errors in initial state (e.g. forcing errors in historical mode), errors in model structure and parameters and last but not least the errors in model forcings (weather forecasts) during the forecast mode. More accurate flood forecasts can be obtained through data assimilation by merging observations with model simulations. This enables to identify the sources of uncertainties in the flood forecasting system. Our aim is to assess the different sources of error that affect the initial state and to investigate how they propagate through hydrological models with different levels of spatial variation, starting from lumped models. The knowledge thus obtained can then be used in a data assimilation scheme to improve the flood forecasts. This study presents the first results of this framework and focuses on quantifying precipitation errors and its effect on discharge simulations within the Ourthe catchment (1600 km2), which is situated in the Belgian Ardennes and is one of the larger subbasins of the Meuse River. Inside the catchment, hourly rain gauge information from 10 different locations is available over a period of 15 years. Based on these time series, the bootstrap method has been applied to generate precipitation ensembles. These were then used to simulate the catchment's discharges at the outlet. The corresponding streamflow ensembles were further assimilated with observed river discharges to update the model states of lumped hydrological models (R-PDM, HBV) through Residual Resampling. This particle filtering technique is a sequential data assimilation method and takes no prior assumption of the probability density function for the model states, which in contrast to the Ensemble Kalman filter does not have to be Gaussian. Our further research will be aimed at quantifying and reducing the sources of uncertainty that affect the initial

The Method of Lines Solution of the Regularized Long-Wave Equation Using Runge-Kutta Time Discretization Method

Directory of Open Access Journals (Sweden)

H. O. Bakodah

2013-01-01

Full Text Available A method of lines approach to the numerical solution of nonlinear wave equations typified by the regularized long wave (RLW is presented. The method developed uses a finite differences discretization to the space. Solution of the resulting system was obtained by applying fourth Runge-Kutta time discretization method. Using Von Neumann stability analysis, it is shown that the proposed method is marginally stable. To test the accuracy of the method some numerical experiments on test problems are presented. Test problems including solitary wave motion, two-solitary wave interaction, and the temporal evaluation of a Maxwellian initial pulse are studied. The accuracy of the present method is tested with and error norms and the conservation properties of mass, energy, and momentum under the RLW equation.

Development of KIAPS Observation Processing Package for Data Assimilation System

Science.gov (United States)

Kang, Jeon-Ho; Chun, Hyoung-Wook; Lee, Sihye; Han, Hyun-Jun; Ha, Su-Jin

2015-04-01

The Korea Institute of Atmospheric Prediction Systems (KIAPS) was founded in 2011 by the Korea Meteorological Administration (KMA) to develop Korea's own global Numerical Weather Prediction (NWP) system as nine year (2011-2019) project. Data assimilation team at KIAPS has been developing the observation processing system (KIAPS Package for Observation Processing: KPOP) to provide optimal observations to the data assimilation system for the KIAPS Global Model (KIAPS Integrated Model - Spectral Element method based on HOMME: KIM-SH). Currently, the KPOP is capable of processing the satellite radiance data (AMSU-A, IASI), GPS Radio Occultation (GPS-RO), AIRCRAFT (AMDAR, AIREP, and etc…), and synoptic observation (SONDE and SURFACE). KPOP adopted Radiative Transfer for TOVS version 10 (RTTOV_v10) to get brightness temperature (TB) for each channel at top of the atmosphere (TOA), and Radio Occultation Processing Package (ROPP) 1-dimensional forward module to get bending angle (BA) at each tangent point. The observation data are obtained from the KMA which has been composited with BUFR format to be converted with ODB that are used for operational data assimilation and monitoring at the KMA. The Unified Model (UM), Community Atmosphere - Spectral Element (CAM-SE) and KIM-SH model outputs are used for the bias correction (BC) and quality control (QC) of the observations, respectively. KPOP provides radiance and RO data for Local Ensemble Transform Kalman Filter (LETKF) and also provides SONDE, SURFACE and AIRCRAFT data for Three-Dimensional Variational Assimilation (3DVAR). We are expecting all of the observation type which processed in KPOP could be combined with both of the data assimilation method as soon as possible. The preliminary results from each observation type will be introduced with the current development status of the KPOP.

Conditions for successful data assimilation

Science.gov (United States)

Morzfeld, M.; Chorin, A. J.

2013-12-01

Many applications in science and engineering require that the predictions of uncertain models be updated by information from a stream of noisy data. The model and the data jointly define a conditional probability density function (pdf), which contains all the information one has about the process of interest and various numerical methods can be used to study and approximate this pdf, e.g. the Kalman filter, variational methods or particle filters. Given a model and data, each of these algorithms will produce a result. We are interested in the conditions under which this result is reasonable, i.e. consistent with the real-life situation one is modeling. In particular, we show, using idealized models, that numerical data assimilation is feasible in principle only if a suitably defined effective dimension of the problem is not excessive. This effective dimension depends on the noise in the model and the data, and in physically reasonable problems it can be moderate even when the number of variables is huge. In particular, we find that the effective dimension being moderate induces a balance condition between the noises in the model and the data; this balance condition is often satisfied in realistic applications or else the noise levels are excessive and drown the underlying signal. We also study the effects of the effective dimension on particle filters in two instances, one in which the importance function is based on the model alone, and one in which it is based on both the model and the data. We have three main conclusions: (1) the stability (i.e., non-collapse of weights) in particle filtering depends on the effective dimension of the problem. Particle filters can work well if the effective dimension is moderate even if the true dimension is large (which we expect to happen often in practice). (2) A suitable choice of importance function is essential, or else particle filtering fails even when data assimilation is feasible in principle with a sequential algorithm

Adjustment of trendy, gaming and less assimilated tweens in the United States.

Science.gov (United States)

Comulada, W Scott; Rotheram-Borus, Mary Jane; Carey, George; Poris, Michelle; Lord, Lynwood R; Mayfield Arnold, Elizabeth

2011-09-01

Youth transitioning from childhood to adolescence (tweens) are exposed to increasing amounts of media and advertisement. Tweens have also emerged as a major marketing segment for corporate America with increasing buying power.We examine how tweens relate to popular culture messages and the association of different orientations to popular culture on adjustment. A secondary data analysis was conducted on a marketing survey of 3527 tweens, aged 10-14 years, obtained from 49 schools using stratified sampling methods. A sample of children nationwide described their preferences on popular culture and measures of psychosocial adjustment. Using cluster analysis, we identified three main clusters or adaptation styles of tweens: (1) those who enjoyed gaming, (2) trendy youth and (3) youth less assimilated into popular culture. There were differences in clusters based on adjustment indices. Gaming and trendy tweens reported higher self-perceptions of being smart, caring and confident compared to less assimilated tweens. However, gaming and trendy tweens worried more about fitting in than less assimilated tweens. Gaming and trendy tweens also endorsed future goals and traditional values more strongly than less assimilated tweens. Trendy tweens reported the strongest positive feelings about substance use. Results suggest that for each method of adaptation (gamer, trendy and less assimilated), there are unique differences in adjustment that can impact the child's future. Parents and service providers must recognize the complexity of these decisions and be sensitive to the unique needs of youth as they move from childhood to adolescence.

Ocean Data Assimilation in the Gulf of Mexico Using 3D VAR Approach - Preliminary Results

Science.gov (United States)

Paturi, S.; Garraffo, Z. D.; Cummings, J. A.; Rivin, I.; Mehra, A.; Kim, H. C.

2016-12-01

Approaches to ocean data assimilation vary widely, both in terms of the sophistication of the method and the observations assimilated.A three-dimensional variational (3DVAR) data assimilation system, part of the Navy Coupled Ocean Data Assimilation (NCODA) system developed at Navy Research Laboratory (NRL), is used for assimilating Sea Surface Temperature (SST) and Sea Surface Height (SSH) in the Gulf of Mexico (GoM). The NCODA 3DVAR produces simultaneous analyses of temperature, salinity, and vector velocity and uses all possible sources of ocean data observations.The Hybrid Coordinate Ocean Model (HYCOM) is used for the simulations, at 1/25o grid resolution for July 2011 period. After successful implementation of NCODA 3DVAR in the GoM, the system will be extended to the global ocean with the intent of making it operational.

Wave propagation retrieval method for chiral metamaterials

DEFF Research Database (Denmark)

Andryieuski, Andrei; Malureanu, Radu; Lavrinenko, Andrei

2010-01-01

In this paper we present the wave propagation method for the retrieving of effective properties of media with circularly polarized eigenwaves, in particularly for chiral metamaterials. The method is applied for thick slabs and provides bulk effective parameters. Its strong sides are the absence...

A new method for data assimilation: the back and forth nudging algorithm

OpenAIRE

Auroux , Didier; Blum , Jacques; Nodet , Maëlle

2013-01-01

International audience; In this paper, we propose an improvement to the Back and Forth Nudging algorithm for handling diffusion in the context of geophysical data assimilation. We detail the Diffusive Back and Forth Nudging algorithm, in which the sign of the diffusion term is changed in the backward integrations. We study the convergence of this algorithm, in particular for linear transport equations.

Spectral analysis of surface waves method to assess shear wave velocity within centrifuge models

Science.gov (United States)

Murillo, Carol Andrea; Thorel, Luc; Caicedo, Bernardo

2009-06-01

The method of the spectral analysis of surface waves (SASW) is tested out on reduced scale centrifuge models, with a specific device, called the mini Falling Weight, developed for this purpose. Tests are performed on layered materials made of a mixture of sand and clay. The shear wave velocity VS determined within the models using the SASW is compared with the laboratory measurements carried out using the bender element test. The results show that the SASW technique applied to centrifuge testing is a relevant method to characterize VS near the surface.

A virtual reality catchment for data assimilation experiments

Science.gov (United States)

Schalge, Bernd; Rihani, Jehan; Haese, Barbara; Baroni, Gabriele; Erdal, Daniel; Neuweiler, Insa; Hendricks-Franssen, Harrie-Jan; Geppert, Gernot; Ament, Felix; Kollet, Stefan; Cirpka, Olaf; Saavedra, Pablo; Han, Xujun; Attinger, Sabine; Kunstmann, Harald; Vereecken, Harry; Simmer, Clemens

2016-04-01

Current data assimilation (DA) systems often lack the possibility to assimilate measurements across compartments to accurately estimate states and fluxes in subsurface-land surface-atmosphere systems (SLAS). In order to develop a new DA framework that is able to realize this cross-compartmental assimilation a comprehensive testing environment is needed. Therefore a virtual reality (VR) catchment is constructed with the Terrestrial System Modeling Platform (TerrSysMP). This catchment mimics the Neckar catchment in Germany. TerrSysMP employs the atmospheric model COSMO, the land surface model CLM and the hydrological model ParFlow coupled with the external coupler OASIS. We will show statistical tests to prove the plausibility of the VR. The VR is running in a fully-coupled mode (subsurface - land surface - atmosphere) which includes the interactions of subsurface dynamics with the atmosphere, such as the effects of soil moisture, which can influence near-surface temperatures, convection patterns or the surface heat fluxes. A reference high resolution run serves as the "truth" from which virtual observations are extracted with observation operators like virtual rain gauges, synoptic stations and satellite observations (amongst others). This effectively solves the otherwise often encountered data scarcity issues with respect to DA. Furthermore an ensemble of model runs at a reduced resolution is performed. This ensemble serves also for open loop runs to be compared with data assimilation experiments. The model runs with this ensemble served to identify sets of parameters that are especially sensitive to changes and have the largest impact on the system. These parameters were the focus of subsequent ensemble simulations and DA experiments. We will show to what extend the VR states can be re-constructed using data assimilation methods with only a limited number of virtual observations available.

On the use of liquid scintillation counting of 51Cr and 14C in the twin tracer method of measuring assimilation efficiency

International Nuclear Information System (INIS)

Cammen, L.M.

1977-01-01

Calow and Fletcher (1972) calculated assimilation efficiency from the ratio of an assimilated radiotracer ( 14 C) to a non-assimilated tracer ( 51 Cr) in food and feces. Wightman (1975) improved the efficiency of their technique by using liquid scintillation to count both isotopes simultaneously, but stated incorrectly that it was not necessary to convert count per minute (CPM) to disintegration per minute (DPM). Unless the CPM data are corrected for quenching and converted to DPM prior to calculation of assimilation efficiency, a significant error may be introduced. (orig.) [de

Algebraic method for constructing singular steady solitary waves: a case study

Science.gov (United States)

Clamond, Didier; Dutykh, Denys; Galligo, André

2016-07-01

This article describes the use of algebraic methods in a phase plane analysis of ordinary differential equations. The method is illustrated by the study of capillary-gravity steady surface waves propagating in shallow water. We consider the (fully nonlinear, weakly dispersive) Serre-Green-Naghdi equation with surface tension, because it provides a tractable model that, at the same time, is not too simple, so interest in the method can be emphasized. In particular, we analyse a special class of solutions, the solitary waves, which play an important role in many fields of physics. In capillary-gravity regime, there are two kinds of localized infinitely smooth travelling wave solutions-solitary waves of elevation and of depression. However, if we allow the solitary waves to have an angular point, then the `zoology' of solutions becomes much richer, and the main goal of this study is to provide a complete classification of such singular localized solutions using the methods of the effective algebraic geometry.

On the comparsion of the Spherical Wave Expansion-to-Plane Wave Expansion and the Sources Reconstruction Method for Antenna Diagnostics

DEFF Research Database (Denmark)

Alvarez, Yuri; Cappellin, Cecilia; Las-Heras, Fernando

2008-01-01

A comparison between two recently developed methods for antenna diagnostics is presented. On one hand, the Spherical Wave Expansion-to-Plane Wave Expansion (SWE-PWE), based on the relationship between spherical and planar wave modes. On the other hand, the Sources Reconstruction Method (SRM), based...

A robust absorbing layer method for anisotropic seismic wave modeling

Energy Technology Data Exchange (ETDEWEB)

Métivier, L., E-mail: ludovic.metivier@ujf-grenoble.fr [LJK, CNRS, Université de Grenoble, BP 53, 38041 Grenoble Cedex 09 (France); ISTerre, Université de Grenoble I, BP 53, 38041 Grenoble Cedex 09 (France); Brossier, R. [ISTerre, Université de Grenoble I, BP 53, 38041 Grenoble Cedex 09 (France); Labbé, S. [LJK, CNRS, Université de Grenoble, BP 53, 38041 Grenoble Cedex 09 (France); Operto, S. [Géoazur, Université de Nice Sophia-Antipolis, CNRS, IRD, OCA, Villefranche-sur-Mer (France); Virieux, J. [ISTerre, Université de Grenoble I, BP 53, 38041 Grenoble Cedex 09 (France)

2014-12-15

When applied to wave propagation modeling in anisotropic media, Perfectly Matched Layers (PML) exhibit instabilities. Incoming waves are amplified instead of being absorbed. Overcoming this difficulty is crucial as in many seismic imaging applications, accounting accurately for the subsurface anisotropy is mandatory. In this study, we present the SMART layer method as an alternative to PML approach. This method is based on the decomposition of the wavefield into components propagating inward and outward the domain of interest. Only outgoing components are damped. We show that for elastic and acoustic wave propagation in Transverse Isotropic media, the SMART layer is unconditionally dissipative: no amplification of the wavefield is possible. The SMART layers are not perfectly matched, therefore less accurate than conventional PML. However, a reasonable increase of the layer size yields an accuracy similar to PML. Finally, we illustrate that the selective damping strategy on which is based the SMART method can prevent the generation of spurious S-waves by embedding the source in a small zone where only S-waves are damped.

A robust absorbing layer method for anisotropic seismic wave modeling

International Nuclear Information System (INIS)

Métivier, L.; Brossier, R.; Labbé, S.; Operto, S.; Virieux, J.

2014-01-01

When applied to wave propagation modeling in anisotropic media, Perfectly Matched Layers (PML) exhibit instabilities. Incoming waves are amplified instead of being absorbed. Overcoming this difficulty is crucial as in many seismic imaging applications, accounting accurately for the subsurface anisotropy is mandatory. In this study, we present the SMART layer method as an alternative to PML approach. This method is based on the decomposition of the wavefield into components propagating inward and outward the domain of interest. Only outgoing components are damped. We show that for elastic and acoustic wave propagation in Transverse Isotropic media, the SMART layer is unconditionally dissipative: no amplification of the wavefield is possible. The SMART layers are not perfectly matched, therefore less accurate than conventional PML. However, a reasonable increase of the layer size yields an accuracy similar to PML. Finally, we illustrate that the selective damping strategy on which is based the SMART method can prevent the generation of spurious S-waves by embedding the source in a small zone where only S-waves are damped

The role of ocean-atmosphere interaction in Typhoon Sinlaku (2008) using a regional coupled data assimilation system

Science.gov (United States)

Wada, Akiyoshi; Kunii, Masaru

2017-05-01

For improving analyses of tropical cyclone (TC) and sea surface temperature (SST) and thereby TC simulations, a regional mesoscale strongly coupled atmosphere-ocean data assimilation system was developed with the local ensemble transform Kalman filter (LETKF) implemented with the Japan Meteorological Agency's nonhydrostatic model (NHM) coupled with a multilayer ocean model and the third-generation ocean wave model. The NHM-LETKF coupled data assimilation system was applied to Typhoon Sinlaku (2008) along with the original NHM-LETKF system to investigate the sensitivity of Sinlaku to SST assimilation with the Level 2 Pre-processed (L2P) standard product of satellite SST. SST calculated in the coupled-assimilation experiment with the coupled data assimilation system and the satellite SST (CPL) showed a better correlation with Optimally Interpolated SST than SST used in the control experiment with the original NHM-LETKF (CNTL) and SST calculated in the succession experiment with the coupled system without satellite SST (SUCC). The time series in the CPL experiment well captured the variation in the SST observed at the Kuroshio Extension Observation buoy site. In addition, TC-induced sea surface cooling was analyzed more realistically in the CPL experiment than that in the CNTL and SUCC experiments. However, the central pressure analyzed in each three experiments was overestimated compared with the Regional Specialized Meteorological Center Tokyo best-track central pressure, mainly due to the coarse horizontal resolution of 15 km. The 96 h TC simulations indicated that the CPL experiment provided more favorable initial and boundary conditions than the CNTL experiment to simulate TC tracks more accurately.

Assimilation of radar-based nowcast into HIRLAM NWP model

DEFF Research Database (Denmark)

Jensen, David Getreuer; Petersen, Claus; Rasmussen, Michael R.

2015-01-01

The present study introduces a nowcast scheme that assimilates radar extrapolation data (RED) into a nowcasting version of the high resolution limited area model (HIRLAM) numerical weather prediction (NWP) model covering the area of Denmark. The RED are based on the Co-TREC (tracking radar echoes...... by correlation) methodology and are generated from cleaned radar mosaics from the Danish weather radar network. The assimilation technique is a newly developed method that increases model precipitation by increasing low-level convergence and decreasing convergence aloft in order to increase the vertical velocity....... The level of improved predictability relies on the RED quality, which again relies on the type of event....

A novel method for predicting the power outputs of wave energy converters

Science.gov (United States)

Wang, Yingguang

2018-03-01

This paper focuses on realistically predicting the power outputs of wave energy converters operating in shallow water nonlinear waves. A heaving two-body point absorber is utilized as a specific calculation example, and the generated power of the point absorber has been predicted by using a novel method (a nonlinear simulation method) that incorporates a second order random wave model into a nonlinear dynamic filter. It is demonstrated that the second order random wave model in this article can be utilized to generate irregular waves with realistic crest-trough asymmetries, and consequently, more accurate generated power can be predicted by subsequently solving the nonlinear dynamic filter equation with the nonlinearly simulated second order waves as inputs. The research findings demonstrate that the novel nonlinear simulation method in this article can be utilized as a robust tool for ocean engineers in their design, analysis and optimization of wave energy converters.

Ozone data assimilation with GEOS-Chem: a comparison between 3-D-Var, 4-D-Var, and suboptimal Kalman filter approaches

Science.gov (United States)

Singh, K.; Sandu, A.; Bowman, K. W.; Parrington, M.; Jones, D. B. A.; Lee, M.

2011-08-01

Chemistry transport models determine the evolving chemical state of the atmosphere by solving the fundamental equations that govern physical and chemical transformations subject to initial conditions of the atmospheric state and surface boundary conditions, e.g., surface emissions. The development of data assimilation techniques synthesize model predictions with measurements in a rigorous mathematical framework that provides observational constraints on these conditions. Two families of data assimilation methods are currently widely used: variational and Kalman filter (KF). The variational approach is based on control theory and formulates data assimilation as a minimization problem of a cost functional that measures the model-observations mismatch. The Kalman filter approach is rooted in statistical estimation theory and provides the analysis covariance together with the best state estimate. Suboptimal Kalman filters employ different approximations of the covariances in order to make the computations feasible with large models. Each family of methods has both merits and drawbacks. This paper compares several data assimilation methods used for global chemical data assimilation. Specifically, we evaluate data assimilation approaches for improving estimates of the summertime global tropospheric ozone distribution in August 2006 based on ozone observations from the NASA Tropospheric Emission Spectrometer and the GEOS-Chem chemistry transport model. The resulting analyses are compared against independent ozonesonde measurements to assess the effectiveness of each assimilation method. All assimilation methods provide notable improvements over the free model simulations, which differ from the ozonesonde measurements by about 20 % (below 200 hPa). Four dimensional variational data assimilation with window lengths between five days and two weeks is the most accurate method, with mean differences between analysis profiles and ozonesonde measurements of 1-5 %. Two sequential

Forecasting ocean wave energy: A Comparison of the ECMWF wave model with time series methods

DEFF Research Database (Denmark)

Reikard, Gordon; Pinson, Pierre; Bidlot, Jean

2011-01-01

Recently, the technology has been developed to make wave farms commercially viable. Since electricity is perishable, utilities will be interested in forecasting ocean wave energy. The horizons involved in short-term management of power grids range from as little as a few hours to as long as several...... days. In selecting a method, the forecaster has a choice between physics-based models and statistical techniques. A further idea is to combine both types of models. This paper analyzes the forecasting properties of a well-known physics-based model, the European Center for Medium-Range Weather Forecasts...... (ECMWF) Wave Model, and two statistical techniques, time-varying parameter regressions and neural networks. Thirteen data sets at locations in the Atlantic and Pacific Oceans and the Gulf of Mexico are tested. The quantities to be predicted are the significant wave height, the wave period, and the wave...

Transportation assimilation revisited: New evidence from repeated cross-sectional survey data

Science.gov (United States)

2018-01-01

Background Based on single cross-sectional data, prior research finds evidence of “transportation assimilation” among U.S. immigrants: the length of stay in the U.S. is negatively correlated with public transit use. This paper revisits this question by using repeated cross-sectional data, and examines the trend of transportation assimilation over time. Methods and results Using 1980, 1990, 2000 1% census and 2010 (1%) American Community Survey, I examine the relationship between the length of stay in the U.S. and public transit ridership among immigrants. I first run regressions separately in four data sets: I regress public transit ridership on the length of stay, controlling for other individual and geographic variables. I then compare the magnitudes of the relationship in four regressions. To study how the rate of transportation assimilation changes over time, I pool the data set and regress public transit ridership on the length of stay and its interactions with year dummies to compare the coefficients across surveys. Results confirm the conclusion of transportation assimilation: as the length of stay in the U.S. increases, an immigrant’s public transit use decreases. However, the repeated cross-section analysis suggests the assimilation rate has been decreasing in the past few decades. Conclusions This paper finds evidence of transportation assimilation: immigrants become less likely to ride public transit as the length of stay in the U.S. increases. The assimilation rate, however, has been decreasing over time. This paper finds that the rate of public transit ridership among new immigrants upon arrival, the geographic distribution of immigrants, and the changing demographics of the U.S. immigrants play roles in affecting the trend of transportation assimilation. PMID:29668676

Development of the Nonstationary Incremental Analysis Update Algorithm for Sequential Data Assimilation System

Directory of Open Access Journals (Sweden)

Yoo-Geun Ham

2016-01-01

Full Text Available This study introduces a modified version of the incremental analysis updates (IAU, called the nonstationary IAU (NIAU method, to improve the assimilation accuracy of the IAU while keeping the continuity of the analysis. Similar to the IAU, the NIAU is designed to add analysis increments at every model time step to improve the continuity in the intermittent data assimilation. However, unlike the IAU, the NIAU procedure uses time-evolved forcing using the forward operator as corrections to the model. The solution of the NIAU is superior to that of the forward IAU, of which analysis is performed at the beginning of the time window for adding the IAU forcing, in terms of the accuracy of the analysis field. It is because, in the linear systems, the NIAU solution equals that in an intermittent data assimilation method at the end of the assimilation interval. To have the filtering property in the NIAU, a forward operator to propagate the increment is reconstructed with only dominant singular vectors. An illustration of those advantages of the NIAU is given using the simple 40-variable Lorenz model.

Land Surface Model Biases and their Impacts on the Assimilation of Snow-related Observations

Science.gov (United States)

Arsenault, K. R.; Kumar, S.; Hunter, S. M.; Aman, R.; Houser, P. R.; Toll, D.; Engman, T.; Nigro, J.

2007-12-01

Some recent snow modeling studies have employed a wide range of assimilation methods to incorporate snow cover or other snow-related observations into different hydrological or land surface models. These methods often include taking both model and observation biases into account throughout the model integration. This study focuses more on diagnosing the model biases and presenting their subsequent impacts on assimilating snow observations and modeled snowmelt processes. In this study, the land surface model, the Community Land Model (CLM), is used within the Land Information System (LIS) modeling framework to show how such biases impact the assimilation of MODIS snow cover observations. Alternative in-situ and satellite-based observations are used to help guide the CLM LSM in better predicting snowpack conditions and more realistic timing of snowmelt for a western US mountainous region. Also, MODIS snow cover observation biases will be discussed, and validation results will be provided. The issues faced with inserting or assimilating MODIS snow cover at moderate spatial resolutions (like 1km or less) will be addressed, and the impacts on CLM will be presented.

Mathematical Methods in Wave Propagation: Part 2--Non-Linear Wave Front Analysis

Science.gov (United States)

Jeffrey, Alan

1971-01-01

The paper presents applications and methods of analysis for non-linear hyperbolic partial differential equations. The paper is concluded by an account of wave front analysis as applied to the piston problem of gas dynamics. (JG)

Volcanic Ash Data Assimilation System for Atmospheric Transport Model

Science.gov (United States)

Ishii, K.; Shimbori, T.; Sato, E.; Tokumoto, T.; Hayashi, Y.; Hashimoto, A.

2017-12-01

The Japan Meteorological Agency (JMA) has two operations for volcanic ash forecasts, which are Volcanic Ash Fall Forecast (VAFF) and Volcanic Ash Advisory (VAA). In these operations, the forecasts are calculated by atmospheric transport models including the advection process, the turbulent diffusion process, the gravitational fall process and the deposition process (wet/dry). The initial distribution of volcanic ash in the models is the most important but uncertain factor. In operations, the model of Suzuki (1983) with many empirical assumptions is adopted to the initial distribution. This adversely affects the reconstruction of actual eruption plumes.We are developing a volcanic ash data assimilation system using weather radars and meteorological satellite observation, in order to improve the initial distribution of the atmospheric transport models. Our data assimilation system is based on the three-dimensional variational data assimilation method (3D-Var). Analysis variables are ash concentration and size distribution parameters which are mutually independent. The radar observation is expected to provide three-dimensional parameters such as ash concentration and parameters of ash particle size distribution. On the other hand, the satellite observation is anticipated to provide two-dimensional parameters of ash clouds such as mass loading, top height and particle effective radius. In this study, we estimate the thickness of ash clouds using vertical wind shear of JMA numerical weather prediction, and apply for the volcanic ash data assimilation system.

Spatial dependence of color assimilation by the watercolor effect.

Science.gov (United States)

Devinck, Frédéric; Delahunt, Peter B; Hardy, Joseph L; Spillmann, Lothar; Werner, John S

2006-01-01

Color assimilation with bichromatic contours was quantified for spatial extents ranging from von Bezold-type color assimilation to the watercolor effect. The magnitude and direction of assimilative hue change was measured as a function of the width of a rectangular stimulus. Assimilation was quantified by hue cancellation. Large hue shifts were required to null the color of stimuli < or = 9.3 min of arc in width, with an exponential decrease for stimuli increasing up to 7.4 deg. When stimuli were viewed through an achromatizing lens, the magnitude of the assimilation effect was reduced for narrow stimuli, but not for wide ones. These results demonstrate that chromatic aberration may account, in part, for color assimilation over small, but not large, surface areas.

Numerical simulation of electromagnetic wave propagation using time domain meshless method

International Nuclear Information System (INIS)

Ikuno, Soichiro; Fujita, Yoshihisa; Itoh, Taku; Nakata, Susumu; Nakamura, Hiroaki; Kamitani, Atsushi

2012-01-01

The electromagnetic wave propagation in various shaped wave guide is simulated by using meshless time domain method (MTDM). Generally, Finite Differential Time Domain (FDTD) method is applied for electromagnetic wave propagation simulation. However, the numerical domain should be divided into rectangle meshes if FDTD method is applied for the simulation. On the other hand, the node disposition of MTDM can easily describe the structure of arbitrary shaped wave guide. This is the large advantage of the meshless time domain method. The results of computations show that the damping rate is stably calculated in case with R < 0.03, where R denotes a support radius of the weight function for the shape function. And the results indicate that the support radius R of the weight functions should be selected small, and monomials must be used for calculating the shape functions. (author)

Coupled atmosphere and land-surface assimilation of surface observations with a single column model and ensemble data assimilation

Science.gov (United States)

Rostkier-Edelstein, Dorita; Hacker, Joshua P.; Snyder, Chris

2014-05-01

Numerical weather prediction and data assimilation models are composed of coupled atmosphere and land-surface (LS) components. If possible, the assimilation procedure should be coupled so that observed information in one module is used to correct fields in the coupled module. There have been some attempts in this direction using optimal interpolation, nudging and 2/3DVAR data assimilation techniques. Aside from satellite remote sensed observations, reference height in-situ observations of temperature and moisture have been used in these studies. Among other problems, difficulties in coupled atmosphere and LS assimilation arise as a result of the different time scales characteristic of each component and the unsteady correlation between these components under varying flow conditions. Ensemble data-assimilation techniques rely on flow dependent observations-model covariances. Provided that correlations and covariances between land and atmosphere can be adequately simulated and sampled, ensemble data assimilation should enable appropriate assimilation of observations simultaneously into the atmospheric and LS states. Our aim is to explore assimilation of reference height in-situ temperature and moisture observations into the coupled atmosphere-LS modules(simultaneously) in NCAR's WRF-ARW model using the NCAR's DART ensemble data-assimilation system. Observing system simulation experiments (OSSEs) are performed using the single column model (SCM) version of WRF. Numerical experiments during a warm season are centered on an atmospheric and soil column in the South Great Plains. Synthetic observations are derived from "truth" WRF-SCM runs for a given date,initialized and forced using North American Regional Reanalyses (NARR). WRF-SCM atmospheric and LS ensembles are created by mixing the atmospheric and soil NARR profile centered on a given date with that from another day (randomly chosen from the same season) with weights drawn from a logit-normal distribution. Three

Data assimilation using a GPU accelerated path integral Monte Carlo approach

Science.gov (United States)

Quinn, John C.; Abarbanel, Henry D. I.

2011-09-01

The answers to data assimilation questions can be expressed as path integrals over all possible state and parameter histories. We show how these path integrals can be evaluated numerically using a Markov Chain Monte Carlo method designed to run in parallel on a graphics processing unit (GPU). We demonstrate the application of the method to an example with a transmembrane voltage time series of a simulated neuron as an input, and using a Hodgkin-Huxley neuron model. By taking advantage of GPU computing, we gain a parallel speedup factor of up to about 300, compared to an equivalent serial computation on a CPU, with performance increasing as the length of the observation time used for data assimilation increases.

Data assimilation of CALIPSO aerosol observations

Directory of Open Access Journals (Sweden)

T. T. Sekiyama

2010-01-01

Full Text Available We have developed an advanced data assimilation system for a global aerosol model with a four-dimensional ensemble Kalman filter in which the Level 1B data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO were successfully assimilated for the first time, to the best of the authors' knowledge. A one-month data assimilation cycle experiment for dust, sulfate, and sea-salt aerosols was performed in May 2007. The results were validated via two independent observations: 1 the ground-based lidar network in East Asia, managed by the National Institute for Environmental Studies of Japan, and 2 weather reports of aeolian dust events in Japan. Detailed four-dimensional structures of aerosol outflows from source regions over oceans and continents for various particle types and sizes were well reproduced. The intensity of dust emission at each grid point was also corrected by this data assimilation system. These results are valuable for the comprehensive analysis of aerosol behavior as well as aerosol forecasting.

Turbulent viscosity optimized by data assimilation

Directory of Open Access Journals (Sweden)

Y. Leredde

Full Text Available As an alternative approach to classical turbulence modelling using a first or second order closure, the data assimilation method of optimal control is applied to estimate a time and space-dependent turbulent viscosity in a three-dimensional oceanic circulation model. The optimal control method, described for a 3-D primitive equation model, involves the minimization of a cost function that quantifies the discrepancies between the simulations and the observations. An iterative algorithm is obtained via the adjoint model resolution. In a first experiment, a k + L model is used to simulate the one-dimensional development of inertial oscillations resulting from a wind stress at the sea surface and with the presence of a halocline. These results are used as synthetic observations to be assimilated. The turbulent viscosity is then recovered without the k + L closure, even with sparse and noisy observations. The problems of controllability and of the dimensions of the control are then discussed. A second experiment consists of a two-dimensional schematic simulation. A 2-D turbulent viscosity field is estimated from data on the initial and final states of a coastal upwelling event.

Key words. Oceanography: general (numerical modelling · Oceanography: physical (turbulence · diffusion · and mixing processes

Testbed model and data assimilation for ARM

International Nuclear Information System (INIS)

Louis, J.F.

1992-01-01

The objectives of this contract are to further develop and test the ALFA (AER Local Forecast and Assimilation) model originally designed at AER for local weather prediction and apply it to three distinct but related purposes in connection with the Atmospheric Radiation Measurement (ARM) program: (a) to provide a testbed that simulates a global climate model in order to facilitate the development and testing of new cloud parametrizations and radiation models; (b) to assimilate the ARM data continuously at the scale of a climate model, using the adjoint method, thus providing the initial conditions and verification data for testing parameumtions; (c) to study the sensitivity of a radiation scheme to cloud parameters, again using the adjoint method, thus demonstrating the usefulness of the testbed model. The data assimilation will use a variational technique that minimizes the difference between the model results and the observation during the analysis period. The adjoint model is used to compute the gradient of a measure of the model errors with respect to nudging terms that are added to the equations to force the model output closer to the data. The radiation scheme that will be included in the basic ALFA model makes use of a gen two-stream approximation, and is designed for vertically inhonogeneous, multiple-scattering atmospheres. The sensitivity of this model to the definition of cloud parameters will be studied. The adjoint technique will also be used to compute the sensitivities. This project is designed to provide the Science Team members with the appropriate tools and modeling environment for proper testing and tuning of new radiation models and cloud parametrization schemes

A low-order coupled chemistry meteorology model for testing online and offline data assimilation schemes

Science.gov (United States)

Haussaire, J.-M.; Bocquet, M.

2015-08-01

Bocquet and Sakov (2013) have introduced a low-order model based on the coupling of the chaotic Lorenz-95 model which simulates winds along a mid-latitude circle, with the transport of a tracer species advected by this zonal wind field. This model, named L95-T, can serve as a playground for testing data assimilation schemes with an online model. Here, the tracer part of the model is extended to a reduced photochemistry module. This coupled chemistry meteorology model (CCMM), the L95-GRS model, mimics continental and transcontinental transport and the photochemistry of ozone, volatile organic compounds and nitrogen oxides. Its numerical implementation is described. The model is shown to reproduce the major physical and chemical processes being considered. L95-T and L95-GRS are specifically designed and useful for testing advanced data assimilation schemes, such as the iterative ensemble Kalman smoother (IEnKS) which combines the best of ensemble and variational methods. These models provide useful insights prior to the implementation of data assimilation methods on larger models. We illustrate their use with data assimilation schemes on preliminary, yet instructive numerical experiments. In particular, online and offline data assimilation strategies can be conveniently tested and discussed with this low-order CCMM. The impact of observed chemical species concentrations on the wind field can be quantitatively estimated. The impacts of the wind chaotic dynamics and of the chemical species non-chaotic but highly nonlinear dynamics on the data assimilation strategies are illustrated.

Information-Based Analysis of Data Assimilation (Invited)

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Nearing, G. S.; Gupta, H. V.; Crow, W. T.; Gong, W.

2013-12-01

Data assimilation is defined as the Bayesian conditioning of uncertain model simulations on observations for the purpose of reducing uncertainty about model states. Practical data assimilation methods make the application of Bayes' law tractable either by employing assumptions about the prior, posterior and likelihood distributions (e.g., the Kalman family of filters) or by using resampling methods (e.g., bootstrap filter). We propose to quantify the efficiency of these approximations in an OSSE setting using information theory and, in an OSSE or real-world validation setting, to measure the amount - and more importantly, the quality - of information extracted from observations during data assimilation. To analyze DA assumptions, uncertainty is quantified as the Shannon-type entropy of a discretized probability distribution. The maximum amount of information that can be extracted from observations about model states is the mutual information between states and observations, which is equal to the reduction in entropy in our estimate of the state due to Bayesian filtering. The difference between this potential and the actual reduction in entropy due to Kalman (or other type of) filtering measures the inefficiency of the filter assumptions. Residual uncertainty in DA posterior state estimates can be attributed to three sources: (i) non-injectivity of the observation operator, (ii) noise in the observations, and (iii) filter approximations. The contribution of each of these sources is measurable in an OSSE setting. The amount of information extracted from observations by data assimilation (or system identification, including parameter estimation) can also be measured by Shannon's theory. Since practical filters are approximations of Bayes' law, it is important to know whether the information that is extracted form observations by a filter is reliable. We define information as either good or bad, and propose to measure these two types of information using partial

Wave field restoration using three-dimensional Fourier filtering method.

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Kawasaki, T; Takai, Y; Ikuta, T; Shimizu, R

2001-11-01

A wave field restoration method in transmission electron microscopy (TEM) was mathematically derived based on a three-dimensional (3D) image formation theory. Wave field restoration using this method together with spherical aberration correction was experimentally confirmed in through-focus images of amorphous tungsten thin film, and the resolution of the reconstructed phase image was successfully improved from the Scherzer resolution limit to the information limit. In an application of this method to a crystalline sample, the surface structure of Au(110) was observed in a profile-imaging mode. The processed phase image showed quantitatively the atomic relaxation of the topmost layer.

Multi-parametric variational data assimilation for hydrological forecasting

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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.

Diffusion Filters for Variational Data Assimilation of Sea Surface Temperature in an Intermediate Climate Model

Directory of Open Access Journals (Sweden)

Xuefeng Zhang

2015-01-01

Full Text Available Sequential, adaptive, and gradient diffusion filters are implemented into spatial multiscale three-dimensional variational data assimilation (3DVAR as alternative schemes to model background error covariance matrix for the commonly used correction scale method, recursive filter method, and sequential 3DVAR. The gradient diffusion filter (GDF is verified by a two-dimensional sea surface temperature (SST assimilation experiment. Compared to the existing DF, the new GDF scheme shows a superior performance in the assimilation experiment due to its success in extracting the spatial multiscale information. The GDF can retrieve successfully the longwave information over the whole analysis domain and the shortwave information over data-dense regions. After that, a perfect twin data assimilation experiment framework is designed to study the effect of the GDF on the state estimation based on an intermediate coupled model. In this framework, the assimilation model is subject to “biased” initial fields from the “truth” model. While the GDF reduces the model bias in general, it can enhance the accuracy of the state estimation in the region that the observations are removed, especially in the South Ocean. In addition, the higher forecast skill can be obtained through the better initial state fields produced by the GDF.

Synthesis of Numerical Methods for Modeling Wave Energy Converter-Point Absorbers: Preprint

Energy Technology Data Exchange (ETDEWEB)

Li, Y.; Yu, Y. H.

2012-05-01

During the past few decades, wave energy has received significant attention among all ocean energy formats. Industry has proposed hundreds of prototypes such as an oscillating water column, a point absorber, an overtopping system, and a bottom-hinged system. In particular, many researchers have focused on modeling the floating-point absorber as the technology to extract wave energy. Several modeling methods have been used such as the analytical method, the boundary-integral equation method, the Navier-Stokes equations method, and the empirical method. However, no standardized method has been decided. To assist the development of wave energy conversion technologies, this report reviews the methods for modeling the floating-point absorber.

Assessment of the radiological inventory of EDF's graphite waste through an assimilation method

International Nuclear Information System (INIS)

Poncet, B.

2014-01-01

The definitive disposal of graphite from the decommissioned UNGG reactors (Chinon A3, Saint-Laurent A1, Saint-Laurent A2 and Bugey 1) has required a radiological inventory of the irradiated graphite. This study focuses on Cl 36 that is produced by neutron absorption on Cl 35 that was present initially in graphite as an impurity (about 80 mg/t of Cl initially in Bugey 1 graphite)). It appears that the changes of Cl 36 concentration along the height of a stack of graphite do neither fit the changes in the neutron flux nor the changes in the graphite temperature. This fact is explained by the high level of purity of the graphite and the nugget effect. Challenged by the absence of spatial correlation of the Cl 36 concentration, an EDF's team has developed an assimilation method based on comparisons between calculations and measurements in order to get a conservative inventory. (A.C.)

First assimilations of COSMIC radio occultation data into the Electron Density Assimilative Model (EDAM

Directory of Open Access Journals (Sweden)

M. J. Angling

2008-02-01

Full Text Available Ground based measurements of slant total electron content (TEC can be assimilated into ionospheric models to produce 3-D representations of ionospheric electron density. The Electron Density Assimilative Model (EDAM has been developed for this purpose. Previous tests using EDAM and ground based data have demonstrated that the information on the vertical structure of the ionosphere is limited in this type of data. The launch of the COSMIC satellite constellation provides the opportunity to use radio occultation data which has more vertical information. EDAM assimilations have been run for three time periods representing quiet, moderate and disturbed geomagnetic conditions. For each run, three data sets have been ingested – only ground based data, only COSMIC data and both ground based and COSMIC data. The results from this preliminary study show that both ground and space based data are capable of improving the representation of the vertical structure of the ionosphere. However, the analysis is limited by the incomplete deployment of the COSMIC constellation and the use of auto-scaled ionosonde data. The first of these can be addressed by repeating this type of study once full deployment has been achieved. The latter requires the manual scaling of ionosonde data; ideally an agreed data set would be scaled and made available to the community to facilitate comparative testing of assimilative models.

Chromatic assimilation unaffected by perceived depth of inducing light.

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Shevell, Steven K; Cao, Dingcai

2004-01-01

Chromatic assimilation is a shift toward the color of nearby light. Several studies conclude that a neural process contributes to assimilation but the neural locus remains in question. Some studies posit a peripheral process, such as retinal receptive-field organization, while others claim the neural mechanism follows depth perception, figure/ground segregation, or perceptual grouping. The experiments here tested whether assimilation depends on a neural process that follows stereoscopic depth perception. By introducing binocular disparity, the test field judged in color was made to appear in a different depth plane than the light that induced assimilation. The chromaticity and spatial frequency of the inducing light, and the chromaticity of the test light, were varied. Chromatic assimilation was found with all inducing-light sizes and chromaticities, but the magnitude of assimilation did not depend on the perceived relative depth planes of the test and inducing fields. We found no evidence to support the view that chromatic assimilation depends on a neural process that follows binocular combination of the two eyes' signals.

Application Of Multi-grid Method On China Seas' Temperature Forecast

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Li, W.; Xie, Y.; He, Z.; Liu, K.; Han, G.; Ma, J.; Li, D.

2006-12-01

Correlation scales have been used in traditional scheme of 3-dimensional variational (3D-Var) data assimilation to estimate the background error covariance for the numerical forecast and reanalysis of atmosphere and ocean for decades. However there are still some drawbacks of this scheme. First, the correlation scales are difficult to be determined accurately. Second, the positive definition of the first-guess error covariance matrix cannot be guaranteed unless the correlation scales are sufficiently small. Xie et al. (2005) indicated that a traditional 3D-Var only corrects some certain wavelength errors and its accuracy depends on the accuracy of the first-guess covariance. And in general, short wavelength error can not be well corrected until long one is corrected and then inaccurate first-guess covariance may mistakenly take long wave error as short wave ones and result in erroneous analysis. For the purpose of quickly minimizing the errors of long and short waves successively, a new 3D-Var data assimilation scheme, called multi-grid data assimilation scheme, is proposed in this paper. By assimilating the shipboard SST and temperature profiles data into a numerical model of China Seas, we applied this scheme in two-month data assimilation and forecast experiment which ended in a favorable result. Comparing with the traditional scheme of 3D-Var, the new scheme has higher forecast accuracy and a lower forecast Root-Mean-Square (RMS) error. Furthermore, this scheme was applied to assimilate the SST of shipboard, AVHRR Pathfinder Version 5.0 SST and temperature profiles at the same time, and a ten-month forecast experiment on sea temperature of China Seas was carried out, in which a successful forecast result was obtained. Particularly, the new scheme is demonstrated a great numerical efficiency in these analyses.

Microstrip natural wave spectrum mathematical model using partial inversion method

International Nuclear Information System (INIS)

Pogarsky, S.A.; Litvinenko, L.N.; Prosvirnin, S.L.

1995-01-01

It is generally agreed that both microstrip lines itself and different discontinuities based on microstrips are the most difficult problem for accurate electrodynamic analysis. Over the last years much has been published about principles and accurate (or full wave) methods of microstrip lines investigations. The growing interest for this problem may be explained by the microstrip application in the millimeter-wave range for purpose of realizing interconnects and a variety of passive components. At these higher operating rating frequencies accurate component modeling becomes more critical. A creation, examination and experimental verification of the accurate method for planar electrodynamical structures natural wave spectrum investigations are the objects of this manuscript. The moment method with partial inversion operator method using may be considered as a basical way for solving this problem. This method is outlook for accurate analysis of different planar discontinuities in microstrip: such as step discontinuities, microstrip turns, Y- and X-junctions and etc., substrate space steps dielectric constants and other anisotropy types

Chemical Source Inversion using Assimilated Constituent Observations in an Idealized Two-dimensional System

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Tangborn, Andrew; Cooper, Robert; Pawson, Steven; Sun, Zhibin

2009-01-01

We present a source inversion technique for chemical constituents that uses assimilated constituent observations rather than directly using the observations. The method is tested with a simple model problem, which is a two-dimensional Fourier-Galerkin transport model combined with a Kalman filter for data assimilation. Inversion is carried out using a Green's function method and observations are simulated from a true state with added Gaussian noise. The forecast state uses the same spectral spectral model, but differs by an unbiased Gaussian model error, and emissions models with constant errors. The numerical experiments employ both simulated in situ and satellite observation networks. Source inversion was carried out by either direct use of synthetically generated observations with added noise, or by first assimilating the observations and using the analyses to extract observations. We have conducted 20 identical twin experiments for each set of source and observation configurations, and find that in the limiting cases of a very few localized observations, or an extremely large observation network there is little advantage to carrying out assimilation first. However, in intermediate observation densities, there decreases in source inversion error standard deviation using the Kalman filter algorithm followed by Green's function inversion by 50% to 95%.

Assimilation of GMS-5 satellite winds using nudging method with MM5

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Gao, Shanhong; Wu, Zengmao; Yang, Bo

2006-09-01

With the aid of Meteorological Information Composite and Processing System (MICAPS), satellite wind vectors derived from the Geostationary Meteorological Statellite-5 (GMS-5) and retrieved by National Satellite Meteorology Center of China (NSMC) can be obtained. Based on the nudging method built in the fifth-generation Mesoscale Model (MM5) of Pennsylvania State University and National Center for Atmospheric Research, a data preprocessor is developed to convert these satellite wind vectors to those with specified format required in MM5. To examine the data preprocessor and evaluate the impact of satellite winds from GMS-5 on MM5 simulations, a series of numerical experimental forecasts consisting of four typhoon cases in 2002 are designed and implemented. The results show that the preprocessor can process satellite winds smoothly and MM5 model runs successfully with a little extra computational load during ingesting these winds, and that assimilation of satellite winds by MM5 nudging method can obviously improve typhoon track forecast but contributes a little to typhoon intensity forecast. The impact of the satellite winds depends heavily upon whether the typhoon bogussing scheme in MM5 was turned on or not. The data preprocessor developed in this paper not only can treat GMS-5 satellite winds but also has capability with little modification to process derived winds from other geostationary satellites.

Wave resistance calculation method combining Green functions based on Rankine and Kelvin source

Directory of Open Access Journals (Sweden)

LI Jingyu

2017-12-01

Full Text Available [Ojectives] At present, the Boundary Element Method(BEM of wave-making resistance mostly uses a model in which the velocity distribution near the hull is solved first, and the pressure integral is then calculated using the Bernoulli equation. However,the process of this model of wave-making resistance is complex and has low accuracy.[Methods] To address this problem, the present paper deduces a compound method for the quick calculation of ship wave resistance using the Rankine source Green function to solve the hull surface's source density, and combining the Lagally theorem concerning source point force calculation based on the Kelvin source Green function so as to solve the wave resistance. A case for the Wigley model is given.[Results] The results show that in contrast to the thin ship method of the linear wave resistance theorem, this method has higher precision, and in contrast to the method which completely uses the Kelvin source Green function, this method has better computational efficiency.[Conclusions] In general, the algorithm in this paper provides a compromise between precision and efficiency in wave-making resistance calculation.

Regional Ocean Data Assimilation

KAUST Repository

Edwards, Christopher A.

2015-01-03

This article reviews the past 15 years of developments in regional ocean data assimilation. A variety of scientific, management, and safety-related objectives motivate marine scientists to characterize many ocean environments, including coastal regions. As in weather prediction, the accurate representation of physical, chemical, and/or biological properties in the ocean is challenging. Models and observations alone provide imperfect representations of the ocean state, but together they can offer improved estimates. Variational and sequential methods are among the most widely used in regional ocean systems, and there have been exciting recent advances in ensemble and four-dimensional variational approaches. These techniques are increasingly being tested and adapted for biogeochemical applications.

Development of airborne remote sensing data assimilation system

International Nuclear Information System (INIS)

Gudu, B R; Bi, H Y; Wang, H Y; Qin, S X; Ma, J W

2014-01-01

In this paper, an airborne remote sensing data assimilation system for China Airborne Remote Sensing System is introduced. This data assimilation system is composed of a land surface model, data assimilation algorithms, observation data and fundamental parameters forcing the land surface model. In this data assimilation system, Variable Infiltration Capacity hydrologic model is selected as the land surface model, which also serves as the main framework of the system. Three-dimensional variation algorithm, four-dimensional variation algorithms, ensemble Kalman filter and Particle filter algorithms are integrated in this system. Observation data includes ground observations and remotely sensed data. The fundamental forcing parameters include soil parameters, vegetation parameters and the meteorological data

An OSSE Study for Deep Argo Array using the GFDL Ensemble Coupled Data Assimilation System

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Chang, You-Soon; Zhang, Shaoqing; Rosati, Anthony; Vecchi, Gabriel A.; Yang, Xiaosong

2018-03-01

An observing system simulation experiment (OSSE) using an ensemble coupled data assimilation system was designed to investigate the impact of deep ocean Argo profile assimilation in a biased numerical climate system. Based on the modern Argo observational array and an artificial extension to full depth, "observations" drawn from one coupled general circulation model (CM2.0) were assimilated into another model (CM2.1). Our results showed that coupled data assimilation with simultaneous atmospheric and oceanic constraints plays a significant role in preventing deep ocean drift. However, the extension of the Argo array to full depth did not significantly improve the quality of the oceanic climate estimation within the bias magnitude in the twin experiment. Even in the "identical" twin experiment for the deep Argo array from the same model (CM2.1) with the assimilation model, no significant changes were shown in the deep ocean, such as in the Atlantic meridional overturning circulation and the Antarctic bottom water cell. The small ensemble spread and corresponding weak constraints by the deep Argo profiles with medium spatial and temporal resolution may explain why the deep Argo profiles did not improve the deep ocean features in the assimilation system. Additional studies using different assimilation methods with improved spatial and temporal resolution of the deep Argo array are necessary in order to more thoroughly understand the impact of the deep Argo array on the assimilation system.

Temporal Reference, Attentional Modulation, and Crossmodal Assimilation

Directory of Open Access Journals (Sweden)

Yingqi Wan

2018-06-01

Full Text Available Crossmodal assimilation effect refers to the prominent phenomenon by which ensemble mean extracted from a sequence of task-irrelevant distractor events, such as auditory intervals, assimilates/biases the perception (such as visual interval of the subsequent task-relevant target events in another sensory modality. In current experiments, using visual Ternus display, we examined the roles of temporal reference, materialized as the time information accumulated before the onset of target event, as well as the attentional modulation in crossmodal temporal interaction. Specifically, we examined how the global time interval, the mean auditory inter-intervals and the last interval in the auditory sequence assimilate and bias the subsequent percept of visual Ternus motion (element motion vs. group motion. We demonstrated that both the ensemble (geometric mean and the last interval in the auditory sequence contribute to bias the percept of visual motion. Longer mean (or last interval elicited more reports of group motion, whereas the shorter mean (or last auditory intervals gave rise to more dominant percept of element motion. Importantly, observers have shown dynamic adaptation to the temporal reference of crossmodal assimilation: when the target visual Ternus stimuli were separated by a long gap interval after the preceding sound sequence, the assimilation effect by ensemble mean was reduced. Our findings suggested that crossmodal assimilation relies on a suitable temporal reference on adaptation level, and revealed a general temporal perceptual grouping principle underlying complex audio-visual interactions in everyday dynamic situations.

Data Assimilation: Making Sense of Earth Observation

Directory of Open Access Journals (Sweden)

William Albert Lahoz

2014-05-01

Full Text Available Climate change, air quality and environmental degradation are important societal challenges for the 21st Century. These challenges require an intelligent response from society, which in turn requires access to information about the Earth System. This information comes from observations and prior knowledge, the latter typically embodied in a model describing relationships between variables of the Earth System. Data assimilation provides an objective methodology to combine observational and model information to provide an estimate of the most likely state and its uncertainty for the whole Earth System. This approach adds value to the observations – by filling in the spatio-temporal gaps in observations; and to the model – by constraining it with the observations. In this review paper we motivate data assimilation as a methodology to fill in the gaps in observational information; illustrate the data assimilation approach with examples that span a broad range of features of the Earth System (atmosphere, including chemistry; ocean; land surface; and discuss the outlook for data assimilation, including the novel application of data assimilation ideas to observational information obtained using Citizen Science. Ultimately, a strong motivation of data assimilation is the many benefits it provides to users. These include: providing the initial state for weather and air quality forecasts; providing analyses and reanalyses for studying the Earth System; evaluating observations, instruments and models; assessing the relative value of elements of the Global Observing System (GOS; and assessing the added value of future additions to the GOS.

Lidar data assimilation for improved analyses of volcanic aerosol events

Science.gov (United States)

Lange, Anne Caroline; Elbern, Hendrik

2014-05-01

data in a variational data assimilation algorithm. The implemented method is tested by the assimilation of CALIPSO attenuated backscatter data that were taken during the eruption of the Eyjafjallajökull volcano in April 2010. It turned out that the implemented module is fully capable to integrate unexpected aerosol events in an automatic way into reasonable analyses. The estimations of the aerosol mass concentrations showed promising properties for the application of observations that are taken by lidar systems with both, higher and lower sophistication than CALIOP.

The Impact of the Assimilation of Aquarius Sea Surface Salinity Data in the GEOS Ocean Data Assimilation System

Science.gov (United States)

Vernieres, Guillaume Rene Jean; Kovach, Robin M.; Keppenne, Christian L.; Akella, Santharam; Brucker, Ludovic; Dinnat, Emmanuel Phillippe

2014-01-01

Ocean salinity and temperature differences drive thermohaline circulations. These properties also play a key role in the ocean-atmosphere coupling. With the availability of L-band space-borne observations, it becomes possible to provide global scale sea surface salinity (SSS) distribution. This study analyzes globally the along-track (Level 2) Aquarius SSS retrievals obtained using both passive and active L-band observations. Aquarius alongtrack retrieved SSS are assimilated into the ocean data assimilation component of Version 5 of the Goddard Earth Observing System (GEOS-5) assimilation and forecast model. We present a methodology to correct the large biases and errors apparent in Version 2.0 of the Aquarius SSS retrieval algorithm and map the observed Aquarius SSS retrieval into the ocean models bulk salinity in the topmost layer. The impact of the assimilation of the corrected SSS on the salinity analysis is evaluated by comparisons with insitu salinity observations from Argo. The results show a significant reduction of the global biases and RMS of observations-minus-forecast differences at in-situ locations. The most striking results are found in the tropics and southern latitudes. Our results highlight the complementary role and problems that arise during the assimilation of salinity information from in-situ (Argo) and space-borne surface (SSS) observations

The Impact of Ocean Data Assimilation on Seasonal-to-Interannual Forecasts: A Case Study of the 2006 El Nino Event

Science.gov (United States)

Yang, Shu-Chih; Rienecker, Michele; Keppenne, Christian

2010-01-01

This study investigates the impact of four different ocean analyses on coupled forecasts of the 2006 El Nino event. Forecasts initialized in June 2006 using ocean analyses from an assimilation that uses flow-dependent background error covariances are compared with those using static error covariances that are not flow dependent. The flow-dependent error covariances reflect the error structures related to the background ENSO instability and are generated by the coupled breeding method. The ocean analyses used in this study result from the assimilation of temperature and salinity, with the salinity data available from Argo floats. Of the analyses, the one using information from the coupled bred vectors (BV) replicates the observed equatorial long wave propagation best and exhibits more warming features leading to the 2006 El Nino event. The forecasts initialized from the BV-based analysis agree best with the observations in terms of the growth of the warm anomaly through two warming phases. This better performance is related to the impact of the salinity analysis on the state evolution in the equatorial thermocline. The early warming is traced back to salinity differences in the upper ocean of the equatorial central Pacific, while the second warming, corresponding to the mature phase, is associated with the effect of the salinity assimilation on the depth of the thermocline in the western equatorial Pacific. The series of forecast experiments conducted here show that the structure of the salinity in the initial conditions is important to the forecasts of the extension of the warm pool and the evolution of the 2006 El Ni o event.

Variational data assimilation schemes for transport and transformation models of atmospheric chemistry

Science.gov (United States)

Penenko, Alexey; Penenko, Vladimir; Tsvetova, Elena; Antokhin, Pavel

2016-04-01

work has been partially supported by RFBR grant 14-01-00125 and RAS Presidium II.4P. References: [1] Penenko V.V., Tsvetova E.A., Penenko A.V. Development of variational approach for direct and inverse problems of atmospheric hydrodynamics and chemistry // IZVESTIYA ATMOSPHERIC AND OCEANIC PHYSICS, 2015, v 51 , p. 311 - 319 [2] A.V. Penenko and V.V. Penenko. Direct data assimilation method for convection-diffusion models based on splitting scheme. Computational technologies, 19(4):69-83, 2014. [3] A. Penenko; V. Penenko; R. Nuterman; A. Baklanov and A. Mahura Direct variational data assimilation algorithm for atmospheric chemistry data with transport and transformation model, Proc. SPIE 9680, 21st International Symposium Atmospheric and Ocean Optics: Atmospheric Physics, 968076 (November 19, 2015); doi:10.1117/12.2206008;http://dx.doi.org/10.1117/12.2206008

Skin Temperature Analysis and Bias Correction in a Coupled Land-Atmosphere Data Assimilation System

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Bosilovich, Michael G.; Radakovich, Jon D.; daSilva, Arlindo; Todling, Ricardo; Verter, Frances

2006-01-01

In an initial investigation, remotely sensed surface temperature is assimilated into a coupled atmosphere/land global data assimilation system, with explicit accounting for biases in the model state. In this scheme, an incremental bias correction term is introduced in the model's surface energy budget. In its simplest form, the algorithm estimates and corrects a constant time mean bias for each gridpoint; additional benefits are attained with a refined version of the algorithm which allows for a correction of the mean diurnal cycle. The method is validated against the assimilated observations, as well as independent near-surface air temperature observations. In many regions, not accounting for the diurnal cycle of bias caused degradation of the diurnal amplitude of background model air temperature. Energy fluxes collected through the Coordinated Enhanced Observing Period (CEOP) are used to more closely inspect the surface energy budget. In general, sensible heat flux is improved with the surface temperature assimilation, and two stations show a reduction of bias by as much as 30 Wm(sup -2) Rondonia station in Amazonia, the Bowen ratio changes direction in an improvement related to the temperature assimilation. However, at many stations the monthly latent heat flux bias is slightly increased. These results show the impact of univariate assimilation of surface temperature observations on the surface energy budget, and suggest the need for multivariate land data assimilation. The results also show the need for independent validation data, especially flux stations in varied climate regimes.

Dynamic calibration of agent-based models using data assimilation.

Science.gov (United States)

Ward, Jonathan A; Evans, Andrew J; Malleson, Nicolas S

2016-04-01

A widespread approach to investigating the dynamical behaviour of complex social systems is via agent-based models (ABMs). In this paper, we describe how such models can be dynamically calibrated using the ensemble Kalman filter (EnKF), a standard method of data assimilation. Our goal is twofold. First, we want to present the EnKF in a simple setting for the benefit of ABM practitioners who are unfamiliar with it. Second, we want to illustrate to data assimilation experts the value of using such methods in the context of ABMs of complex social systems and the new challenges these types of model present. We work towards these goals within the context of a simple question of practical value: how many people are there in Leeds (or any other major city) right now? We build a hierarchy of exemplar models that we use to demonstrate how to apply the EnKF and calibrate these using open data of footfall counts in Leeds.

Quasi-static ensemble variational data assimilation: a theoretical and numerical study with the iterative ensemble Kalman smoother

Science.gov (United States)

Fillion, Anthony; Bocquet, Marc; Gratton, Serge

2018-04-01

The analysis in nonlinear variational data assimilation is the solution of a non-quadratic minimization. Thus, the analysis efficiency relies on its ability to locate a global minimum of the cost function. If this minimization uses a Gauss-Newton (GN) method, it is critical for the starting point to be in the attraction basin of a global minimum. Otherwise the method may converge to a local extremum, which degrades the analysis. With chaotic models, the number of local extrema often increases with the temporal extent of the data assimilation window, making the former condition harder to satisfy. This is unfortunate because the assimilation performance also increases with this temporal extent. However, a quasi-static (QS) minimization may overcome these local extrema. It accomplishes this by gradually injecting the observations in the cost function. This method was introduced by Pires et al. (1996) in a 4D-Var context. We generalize this approach to four-dimensional strong-constraint nonlinear ensemble variational (EnVar) methods, which are based on both a nonlinear variational analysis and the propagation of dynamical error statistics via an ensemble. This forces one to consider the cost function minimizations in the broader context of cycled data assimilation algorithms. We adapt this QS approach to the iterative ensemble Kalman smoother (IEnKS), an exemplar of nonlinear deterministic four-dimensional EnVar methods. Using low-order models, we quantify the positive impact of the QS approach on the IEnKS, especially for long data assimilation windows. We also examine the computational cost of QS implementations and suggest cheaper algorithms.

Flow-dependent assimilation of sea surface temperature in isopycnal coordinates with the Norwegian Climate Prediction Model

Directory of Open Access Journals (Sweden)

François Counillon

2016-12-01

Full Text Available We document a pilot stochastic re-analysis computed by assimilating sea surface temperature (SST anomalies into the ocean component of the coupled Norwegian Climate Prediction Model (NorCPM for the period 1950–2010 (doi: 10.11582/2016.00002. NorCPM is based on the Norwegian Earth System Model and uses the ensemble Kalman filter for data assimilation (DA. Here, we assimilate SST from the stochastic HadISST2 historical reconstruction. The accuracy, reliability and drift are investigated using both assimilated and independent observations. NorCPM is slightly overdispersive against assimilated observations but shows stable performance through the analysis period. It demonstrates skills against independent measurements: sea surface height, heat and salt content, in particular in the Equatorial and North Pacific, the North Atlantic Subpolar Gyre (SPG region and the Nordic Seas. Furthermore, NorCPM provides a reliable monitoring of the SPG index and represents the vertical temperature variability there, in good agreement with observations. The monitoring of the Atlantic meridional overturning circulation is also encouraging. The benefit of using a flow-dependent assimilation method and constructing the covariance in isopycnal coordinates are investigated in the SPG region. Isopycnal coordinates discretisation is found to better capture the vertical structure than standard depth-coordinate discretisation, because it leads to a deeper influence of the assimilated surface observations. The vertical covariance shows a pronounced seasonal and decadal variability that highlights the benefit of flow-dependent DA method. This study demonstrates the potential of NorCPM to compute an ocean re-analysis for the 19th and 20th centuries when SST observations are available.

The finite product method in the theory of linear wave propagation

DEFF Research Database (Denmark)

Sorokin, Sergey; Chapman, John

2012-01-01

of the method are presented for several non-trivial examples, that of symmetric/anti-symmetric elastic waves in a layer and in a thin plate. In each case, the method gives a sequence of polynomial approximations to the dispersion relation of remarkable accuracy over a broad range of frequencies and wave numbers...

Application of data assimilation to improve the forecasting capability of an atmospheric dispersion model for a radioactive plume

International Nuclear Information System (INIS)

Jeong, H.J.; Han, M.H.; Hwang, W.T.; Kim, E.H.

2008-01-01

Modeling an atmospheric dispersion of a radioactive plume plays an influential role in assessing the environmental impacts caused by nuclear accidents. The performance of data assimilation techniques combined with Gaussian model outputs and measurements to improve forecasting abilities are investigated in this study. Tracer dispersion experiments are performed to produce field data by assuming a radiological emergency. Adaptive neuro-fuzzy inference system (ANFIS) and linear regression filter are considered to assimilate the Gaussian model outputs with measurements. ANFIS is trained so that the model outputs are likely to be more accurate for the experimental data. Linear regression filter is designed to assimilate measurements similar to the ANFIS. It is confirmed that ANFIS could be an appropriate method for an improvement of the forecasting capability of an atmospheric dispersion model in the case of a radiological emergency, judging from the higher correlation coefficients between the measured and the assimilated ones rather than a linear regression filter. This kind of data assimilation method could support a decision-making system when deciding on the best available countermeasures for public health from among emergency preparedness alternatives

Advanced Data Assimilation for Geosciences : Lecture Notes of the Les Houches School of Physics

CERN Document Server

Bocquet, Marc; Cosme, Emmanuel; Cugliandolo, Leticia F

2014-01-01

This book gathers notes from lectures and seminars given during a three-week school on theoretical and applied data assimilation held in Les Houches in 2012. Data assimilation aims at determining as accurately as possible the state of a dynamical system by combining heterogeneous sources of information in an optimal way. Generally speaking, the mathematical methods of data assimilation describe algorithms for forming optimal combinations of observations of a system, a numerical model that describes its evolution, and appropriate prior information. Data assimilation has a long history of application to high-dimensional geophysical systems dating back to the 1960s, with application to the estimation of initial conditions for weather forecasts. It has become a major component of numerical forecasting systems in geophysics, and an intensive field of research, with numerous additional applications in oceanography and atmospheric chemistry, with extensions to other geophysical sciences. The physical complexity and ...

Finite element and discontinuous Galerkin methods for transient wave equations

CERN Document Server

Cohen, Gary

2017-01-01

This monograph presents numerical methods for solving transient wave equations (i.e. in time domain). More precisely, it provides an overview of continuous and discontinuous finite element methods for these equations, including their implementation in physical models, an extensive description of 2D and 3D elements with different shapes, such as prisms or pyramids, an analysis of the accuracy of the methods and the study of the Maxwell’s system and the important problem of its spurious free approximations. After recalling the classical models, i.e. acoustics, linear elastodynamics and electromagnetism and their variational formulations, the authors present a wide variety of finite elements of different shapes useful for the numerical resolution of wave equations. Then, they focus on the construction of efficient continuous and discontinuous Galerkin methods and study their accuracy by plane wave techniques and a priori error estimates. A chapter is devoted to the Maxwell’s system and the important problem ...

Assimilation of Ocean-Color Plankton Functional Types to Improve Marine Ecosystem Simulations

Science.gov (United States)

Ciavatta, S.; Brewin, R. J. W.; Skákala, J.; Polimene, L.; de Mora, L.; Artioli, Y.; Allen, J. I.

2018-02-01

We assimilated phytoplankton functional types (PFTs) derived from ocean color into a marine ecosystem model, to improve the simulation of biogeochemical indicators and emerging properties in a shelf sea. Error-characterized chlorophyll concentrations of four PFTs (diatoms, dinoflagellates, nanoplankton, and picoplankton), as well as total chlorophyll for comparison, were assimilated into a physical-biogeochemical model of the North East Atlantic, applying a localized Ensemble Kalman filter. The reanalysis simulations spanned the years 1998-2003. The skill of the reference and reanalysis simulations in estimating ocean color and in situ biogeochemical data were compared by using robust statistics. The reanalysis outperformed both the reference and the assimilation of total chlorophyll in estimating the ocean-color PFTs (except nanoplankton), as well as the not-assimilated total chlorophyll, leading the model to simulate better the plankton community structure. Crucially, the reanalysis improved the estimates of not-assimilated in situ data of PFTs, as well as of phosphate and pCO2, impacting the simulation of the air-sea carbon flux. However, the reanalysis increased further the model overestimation of nitrate, in spite of increases in plankton nitrate uptake. The method proposed here is easily adaptable for use with other ecosystem models that simulate PFTs, for, e.g., reanalysis of carbon fluxes in the global ocean and for operational forecasts of biogeochemical indicators in shelf-sea ecosystems.

A variational ensemble scheme for noisy image data assimilation

Science.gov (United States)

Yang, Yin; Robinson, Cordelia; Heitz, Dominique; Mémin, Etienne

2014-05-01

Data assimilation techniques aim at recovering a system state variables trajectory denoted as X, along time from partially observed noisy measurements of the system denoted as Y. These procedures, which couple dynamics and noisy measurements of the system, fulfill indeed a twofold objective. On one hand, they provide a denoising - or reconstruction - procedure of the data through a given model framework and on the other hand, they provide estimation procedures for unknown parameters of the dynamics. A standard variational data assimilation problem can be formulated as the minimization of the following objective function with respect to the initial discrepancy, η, from the background initial guess: δ« J(η(x)) = 1∥Xb (x) - X (t ,x)∥2 + 1 tf∥H(X (t,x ))- Y (t,x)∥2dt. 2 0 0 B 2 t0 R (1) where the observation operator H links the state variable and the measurements. The cost function can be interpreted as the log likelihood function associated to the a posteriori distribution of the state given the past history of measurements and the background. In this work, we aim at studying ensemble based optimal control strategies for data assimilation. Such formulation nicely combines the ingredients of ensemble Kalman filters and variational data assimilation (4DVar). It is also formulated as the minimization of the objective function (1), but similarly to ensemble filter, it introduces in its objective function an empirical ensemble-based background-error covariance defined as: B ≡ )(Xb - )T>. (2) Thus, it works in an off-line smoothing mode rather than on the fly like sequential filters. Such resulting ensemble variational data assimilation technique corresponds to a relatively new family of methods [1,2,3]. It presents two main advantages: first, it does not require anymore to construct the adjoint of the dynamics tangent linear operator, which is a considerable advantage with respect to the method's implementation, and second, it enables the handling of a flow

Comparative Study of Three Data Assimilation Methods for Ice Sheet Model Initialisation

Science.gov (United States)

Mosbeux, Cyrille; Gillet-Chaulet, Fabien; Gagliardini, Olivier

2015-04-01

The current global warming has direct consequences on ice-sheet mass loss contributing to sea level rise. This loss is generally driven by an acceleration of some coastal outlet glaciers and reproducing these mechanisms is one of the major issues in ice-sheet and ice flow modelling. The construction of an initial state, as close as possible to current observations, is required as a prerequisite before producing any reliable projection of the evolution of ice-sheets. For this step, inverse methods are often used to infer badly known or unknown parameters. For instance, the adjoint inverse method has been implemented and applied with success by different authors in different ice flow models in order to infer the basal drag [ Schafer et al., 2012; Gillet-chauletet al., 2012; Morlighem et al., 2010]. Others data fields, such as ice surface and bedrock topography, are easily measurable with more or less uncertainty but only locally along tracks and interpolated on finer model grid. All these approximations lead to errors on the data elevation model and give rise to an ill-posed problem inducing non-physical anomalies in flux divergence [Seroussi et al, 2011]. A solution to dissipate these divergences of flux is to conduct a surface relaxation step at the expense of the accuracy of the modelled surface [Gillet-Chaulet et al., 2012]. Other solutions, based on the inversion of ice thickness and basal drag were proposed [Perego et al., 2014; Pralong & Gudmundsson, 2011]. In this study, we create a twin experiment to compare three different assimilation algorithms based on inverse methods and nudging to constrain the bedrock friction and the bedrock elevation: (i) cyclic inversion of friction parameter and bedrock topography using adjoint method, (ii) cycles coupling inversion of friction parameter using adjoint method and nudging of bedrock topography, (iii) one step inversion of both parameters with adjoint method. The three methods show a clear improvement in parameters

Data assimilation strategies for volcano geodesy

Science.gov (United States)

Zhan, Yan; Gregg, Patricia M.

2017-09-01

Ground deformation observed using near-real time geodetic methods, such as InSAR and GPS, can provide critical information about the evolution of a magma chamber prior to volcanic eruption. Rapid advancement in numerical modeling capabilities has resulted in a number of finite element models targeted at better understanding the connection between surface uplift associated with magma chamber pressurization and the potential for volcanic eruption. Robust model-data fusion techniques are necessary to take full advantage of the numerical models and the volcano monitoring observations currently available. In this study, we develop a 3D data assimilation framework using the Ensemble Kalman Filter (EnKF) approach in order to combine geodetic observations of surface deformation with geodynamic models to investigate volcanic unrest. The EnKF sequential assimilation method utilizes disparate data sets as they become available to update geodynamic models of magma reservoir evolution. While the EnKF has been widely applied in hydrologic and climate modeling, the adaptation for volcano monitoring is in its initial stages. As such, our investigation focuses on conducting a series of sensitivity tests to optimize the EnKF for volcano applications and on developing specific strategies for assimilation of geodetic data. Our numerical experiments illustrate that the EnKF is able to adapt well to the spatial limitations posed by GPS data and the temporal limitations of InSAR, and that specific strategies can be adopted to enhance EnKF performance to improve model forecasts. Specifically, our numerical experiments indicate that: (1) incorporating additional iterations of the EnKF analysis step is more efficient than increasing the number of ensemble members; (2) the accuracy of the EnKF results are not affected by initial parameter assumptions; (3) GPS observations near the center of uplift improve the quality of model forecasts; (4) occasionally shifting continuous GPS stations to

Spectral analysis of surface waves method to assess shear wave velocity within centrifuge models

OpenAIRE

MURILLO, Carol Andrea; THOREL, Luc; CAICEDO, Bernardo

2009-01-01

The method of the spectral analysis of surface waves (SASW) is tested out on reduced scale centrifuge models, with a specific device, called the mini Falling Weight, developed for this purpose. Tests are performed on layered materials made of a mixture of sand and clay. The shear wave velocity VS determined within the models using the SASW is compared with the laboratory measurements carried out using the bender element test. The results show that the SASW technique applied to centrifuge test...

A tuning method for nonuniform traveling-wave accelerating structures

International Nuclear Information System (INIS)

Gong Cunkui; Zheng Shuxin; Shao Jiahang; Jia Xiaoyu; Chen Huaibi

2013-01-01

The tuning method of uniform traveling-wave structures based on non-resonant perturbation field distribution measurement has been widely used in tuning both constant-impedance and constant-gradient structures. In this paper, the method of tuning nonuniform structures is proposed on the basis of the above theory. The internal reflection coefficient of each cell is obtained from analyzing the normalized voltage distribution. A numerical simulation of tuning process according to the coupled cavity chain theory has been done and the result shows each cell is in right phase advance after tuning. The method will be used in the tuning of a disk-loaded traveling-wave structure being developed at the Accelerator Laboratory, Tsinghua University. (authors)

Development of Extended Ray-tracing method including diffraction, polarization and wave decay effects

Science.gov (United States)

Yanagihara, Kota; Kubo, Shin; Dodin, Ilya; Nakamura, Hiroaki; Tsujimura, Toru

2017-10-01

Geometrical Optics Ray-tracing is a reasonable numerical analytic approach for describing the Electron Cyclotron resonance Wave (ECW) in slowly varying spatially inhomogeneous plasma. It is well known that the result with this conventional method is adequate in most cases. However, in the case of Helical fusion plasma which has complicated magnetic structure, strong magnetic shear with a large scale length of density can cause a mode coupling of waves outside the last closed flux surface, and complicated absorption structure requires a strong focused wave for ECH. Since conventional Ray Equations to describe ECW do not have any terms to describe the diffraction, polarization and wave decay effects, we can not describe accurately a mode coupling of waves, strong focus waves, behavior of waves in inhomogeneous absorption region and so on. For fundamental solution of these problems, we consider the extension of the Ray-tracing method. Specific process is planned as follows. First, calculate the reference ray by conventional method, and define the local ray-base coordinate system along the reference ray. Then, calculate the evolution of the distributions of amplitude and phase on ray-base coordinate step by step. The progress of our extended method will be presented.

Multiscale Data Assimilation for Large-Eddy Simulations

Science.gov (United States)

Li, Z.; Cheng, X.; Gustafson, W. I., Jr.; Xiao, H.; Vogelmann, A. M.; Endo, S.; Toto, T.

2017-12-01

Large-eddy simulation (LES) is a powerful tool for understanding atmospheric turbulence, boundary layer physics and cloud development, and there is a great need for developing data assimilation methodologies that can constrain LES models. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility has been developing the capability to routinely generate ensembles of LES. The LES ARM Symbiotic Simulation and Observation (LASSO) project (https://www.arm.gov/capabilities/modeling/lasso) is generating simulations for shallow convection days at the ARM Southern Great Plains site in Oklahoma. One of major objectives of LASSO is to develop the capability to observationally constrain LES using a hierarchy of ARM observations. We have implemented a multiscale data assimilation (MSDA) scheme, which allows data assimilation to be implemented separately for distinct spatial scales, so that the localized observations can be effectively assimilated to constrain the mesoscale fields in the LES area of about 15 km in width. The MSDA analysis is used to produce forcing data that drive LES. With such LES workflow we have examined 13 days with shallow convection selected from the period May-August 2016. We will describe the implementation of MSDA, present LES results, and address challenges and opportunities for applying data assimilation to LES studies.

Analysis of a plane stress wave by the moving least squares method

Directory of Open Access Journals (Sweden)

Wojciech Dornowski

2014-08-01

Full Text Available A meshless method based on the moving least squares approximation is applied to stress wave propagation analysis. Two kinds of node meshes, the randomly generated mesh and the regular mesh are used. The nearest neighbours’ problem is developed from a triangulation that satisfies minimum edges length conditions. It is found that this method of neighbours’ choice significantly improves the solution accuracy. The reflection of stress waves from the free edge is modelled using fictitious nodes (outside the plate. The comparison with the finite difference results also demonstrated the accuracy of the proposed approach.[b]Keywords[/b]: civil engineering, meshless method, moving least squares method, elastic waves

Systems and methods for wave energy conversion

Science.gov (United States)

MacDonald, Daniel G.; Cantara, Justin; Nathan, Craig; Lopes, Amy M.; Green, Brandon E.

2017-02-28

Systems for wave energy conversion that have components that can survive the harsh marine environment and that can be attached to fixed structures, such as a pier, and having the ability to naturally adjust for tidal height and methods for their use are presented.

A fast method for linear waves based on geometrical optics

NARCIS (Netherlands)

Stolk, C.C.

2009-01-01

We develop a fast method for solving the one-dimensional wave equation based on geometrical optics. From geometrical optics (e.g., Fourier integral operator theory or WKB approximation) it is known that high-frequency waves split into forward and backward propagating parts, each propagating with the

Using data assimilation to study extratropical Northern Hemisphere climate over the last millennium

Directory of Open Access Journals (Sweden)

M. Widmann

2010-09-01

Full Text Available Climate proxy data provide noisy, and spatially incomplete information on some aspects of past climate states, whereas palaeosimulations with climate models provide global, multi-variable states, which may however differ from the true states due to unpredictable internal variability not related to climate forcings, as well as due to model deficiencies. Using data assimilation for combining the empirical information from proxy data with the physical understanding of the climate system represented by the equations in a climate model is in principle a promising way to obtain better estimates for the climate of the past.

Data assimilation has been used for a long time in weather forecasting and atmospheric analyses to control the states in atmospheric General Circulation Models such that they are in agreement with observation from surface, upper air, and satellite measurements. Here we discuss the similarities and the differences between the data assimilation problem in palaeoclimatology and in weather forecasting, and present and conceptually compare three data assimilation methods that have been developed in recent years for applications in palaeoclimatology. All three methods (selection of ensemble members, Forcing Singular Vectors, and Pattern Nudging are illustrated by examples that are related to climate variability over the extratropical Northern Hemisphere during the last millennium. In particular it is shown that all three methods suggest that the cold period over Scandinavia during 1790–1820 is linked to anomalous northerly or easterly atmospheric flow, which in turn is related to a pressure anomaly that resembles a negative state of the Northern Annular Mode.

Traveling Wave Resonance and Simplified Analysis Method for Long-Span Symmetrical Cable-Stayed Bridges under Seismic Traveling Wave Excitation

Directory of Open Access Journals (Sweden)

Zhong-ye Tian

2014-01-01

Full Text Available The seismic responses of a long-span cable-stayed bridge under uniform excitation and traveling wave excitation in the longitudinal direction are, respectively, computed. The numerical results show that the bridge’s peak seismic responses vary significantly as the apparent wave velocity decreases. Therefore, the traveling wave effect must be considered in the seismic design of long-span bridges. The bridge’s peak seismic responses do not vary monotonously with the apparent wave velocity due to the traveling wave resonance. A new traveling wave excitation method that can simplify the multisupport excitation process into a two-support excitation process is developed.

Assimilate unloading from maize (Zea mays L.) pedicel tissues. II. Effects of chemical agents on sugar, amino acid, and 14C-assimilate unloading

International Nuclear Information System (INIS)

Porter, G.A.; Knievel, D.P.; Shannon, J.C.

1987-01-01

Sugar, amino acid, and 14 C-assimilate release from attached maize (Zea mays L.) pedicels was studied following treatment with several chemical inhibitors. In the absence of these agents, sugar release was nearly linear over a 7-hour period. At least 13 amino acids were released with glutamine comprising over 30% of the total. Release was not affected by potassium concentration, 10-minute pretreatments with p-chloromercuribenzene sulfonic acid (PCMBS) or dithiothreitol, and low concentrations of CaCl 2 . Three hours or more exposure to PCMBS, dinitrophenol, N-ethylmaleimide, or 2,4,6-trinitrobenzene sulfonic acid strongly inhibited 14 C-assimilate, sugar, and amino acid release from the pedicel. These treatments also reduced 14 C-assimilate movement into the kernel bases. It is, therefore, likely that reduced unloading, caused by these relatively long-term exposures to chemical inhibitors, was related to reduced translocation of assimilates into treated kernels. Whether this effect is due to disruption of kernel metabolism and sieve element function or reduced assimilate unloading and subsequent accumulation of unlabeled assimilates within the pedicel tissues cannot be determined at this time

A comparison of high-order polynomial and wave-based methods for Helmholtz problems

Science.gov (United States)

Lieu, Alice; Gabard, Gwénaël; Bériot, Hadrien

2016-09-01

The application of computational modelling to wave propagation problems is hindered by the dispersion error introduced by the discretisation. Two common strategies to address this issue are to use high-order polynomial shape functions (e.g. hp-FEM), or to use physics-based, or Trefftz, methods where the shape functions are local solutions of the problem (typically plane waves). Both strategies have been actively developed over the past decades and both have demonstrated their benefits compared to conventional finite-element methods, but they have yet to be compared. In this paper a high-order polynomial method (p-FEM with Lobatto polynomials) and the wave-based discontinuous Galerkin method are compared for two-dimensional Helmholtz problems. A number of different benchmark problems are used to perform a detailed and systematic assessment of the relative merits of these two methods in terms of interpolation properties, performance and conditioning. It is generally assumed that a wave-based method naturally provides better accuracy compared to polynomial methods since the plane waves or Bessel functions used in these methods are exact solutions of the Helmholtz equation. Results indicate that this expectation does not necessarily translate into a clear benefit, and that the differences in performance, accuracy and conditioning are more nuanced than generally assumed. The high-order polynomial method can in fact deliver comparable, and in some cases superior, performance compared to the wave-based DGM. In addition to benchmarking the intrinsic computational performance of these methods, a number of practical issues associated with realistic applications are also discussed.

Assimilation of enterprise technology upgrades: a factor-based study

Science.gov (United States)

Claybaugh, Craig C.; Ramamurthy, Keshavamurthy; Haseman, William D.

2017-02-01

The purpose of this study is to gain a better understanding of the differences in the propensity of firms to initiate and commit to the assimilation of an enterprise technology upgrade. A research model is proposed that examines the influences that four technological and four organisational factors have on predicting assimilation of a technology upgrade. Results show that firms with a greater propensity to assimilate the new enterprise resource planning (ERP) version have a higher assessment of relative advantage, IS technical competence, and the strategic role of IS relative to those firms with a lower propensity to assimilate a new ERP version.

Damage evaluation by a guided wave-hidden Markov model based method

Science.gov (United States)

Mei, Hanfei; Yuan, Shenfang; Qiu, Lei; Zhang, Jinjin

2016-02-01

Guided wave based structural health monitoring has shown great potential in aerospace applications. However, one of the key challenges of practical engineering applications is the accurate interpretation of the guided wave signals under time-varying environmental and operational conditions. This paper presents a guided wave-hidden Markov model based method to improve the damage evaluation reliability of real aircraft structures under time-varying conditions. In the proposed approach, an HMM based unweighted moving average trend estimation method, which can capture the trend of damage propagation from the posterior probability obtained by HMM modeling is used to achieve a probabilistic evaluation of the structural damage. To validate the developed method, experiments are performed on a hole-edge crack specimen under fatigue loading condition and a real aircraft wing spar under changing structural boundary conditions. Experimental results show the advantage of the proposed method.

A Low-order Coupled Chemistry Meteorology Model for Testing Online and Offline Advanced Data Assimilation Schemes

Science.gov (United States)

Bocquet, M.; Haussaire, J. M.

2015-12-01

Bocquet and Sakov have recently introduced a low-order model based on the coupling of thechaotic Lorenz-95 model which simulates winds along a mid-latitude circle, with thetransport of a tracer species advected by this wind field. It has been used to testadvanced data assimilation methods with an online model that couples meteorology andtracer transport. In the present study, the tracer subsystem of the model is replacedwith a reduced photochemistry module meant to emulate reactive air pollution. Thiscoupled chemistry meteorology model, the L95-GRS model, mimics continental andtranscontinental transport and photochemistry of ozone, volatile organic compounds andnitrogen dioxides.The L95-GRS is specially useful in testing advanced data assimilation schemes, such as theiterative ensemble Kalman smoother (IEnKS) that combines the best of ensemble andvariational methods. The model provides useful insights prior to any implementation ofthe data assimilation method on larger models. For instance, online and offline dataassimilation strategies based on the ensemble Kalman filter or the IEnKS can easily beevaluated with it. It allows to document the impact of species concentration observationson the wind estimation. The model also illustrates a long standing issue in atmosphericchemistry forecasting: the impact of the wind chaotic dynamics and of the chemical speciesnon-chaotic but highly nonlinear dynamics on the selected data assimilation approach.

The extended hyperbolic function method and exact solutions of the long-short wave resonance equations

International Nuclear Information System (INIS)

Shang Yadong

2008-01-01

The extended hyperbolic functions method for nonlinear wave equations is presented. Based on this method, we obtain a multiple exact explicit solutions for the nonlinear evolution equations which describe the resonance interaction between the long wave and the short wave. The solutions obtained in this paper include (a) the solitary wave solutions of bell-type for S and L, (b) the solitary wave solutions of kink-type for S and bell-type for L, (c) the solitary wave solutions of a compound of the bell-type and the kink-type for S and L, (d) the singular travelling wave solutions, (e) periodic travelling wave solutions of triangle function types, and solitary wave solutions of rational function types. The variety of structure to the exact solutions of the long-short wave equation is illustrated. The methods presented here can also be used to obtain exact solutions of nonlinear wave equations in n dimensions

An algorithm for variational data assimilation of contact concentration measurements for atmospheric chemistry models

Science.gov (United States)

Penenko, Alexey; Penenko, Vladimir

2014-05-01

Contact concentration measurement data assimilation problem is considered for convection-diffusion-reaction models originating from the atmospheric chemistry study. High dimensionality of models imposes strict requirements on the computational efficiency of the algorithms. Data assimilation is carried out within the variation approach on a single time step of the approximated model. A control function is introduced into the source term of the model to provide flexibility for data assimilation. This function is evaluated as the minimum of the target functional that connects its norm to a misfit between measured and model-simulated data. In the case mathematical model acts as a natural Tikhonov regularizer for the ill-posed measurement data inversion problem. This provides flow-dependent and physically-plausible structure of the resulting analysis and reduces a need to calculate model error covariance matrices that are sought within conventional approach to data assimilation. The advantage comes at the cost of the adjoint problem solution. This issue is solved within the frameworks of splitting-based realization of the basic convection-diffusion-reaction model. The model is split with respect to physical processes and spatial variables. A contact measurement data is assimilated on each one-dimensional convection-diffusion splitting stage. In this case a computationally-efficient direct scheme for both direct and adjoint problem solution can be constructed based on the matrix sweep method. Data assimilation (or regularization) parameter that regulates ratio between model and data in the resulting analysis is obtained with Morozov discrepancy principle. For the proper performance the algorithm takes measurement noise estimation. In the case of Gaussian errors the probability that the used Chi-squared-based estimate is the upper one acts as the assimilation parameter. A solution obtained can be used as the initial guess for data assimilation algorithms that assimilate

Assimilation of remote sensing observations into a sediment transport model of China's largest freshwater lake: spatial and temporal effects.

Science.gov (United States)

Zhang, Peng; Chen, Xiaoling; Lu, Jianzhong; Zhang, Wei

2015-12-01

Numerical models are important tools that are used in studies of sediment dynamics in inland and coastal waters, and these models can now benefit from the use of integrated remote sensing observations. This study explores a scheme for assimilating remotely sensed suspended sediment (from charge-coupled device (CCD) images obtained from the Huanjing (HJ) satellite) into a two-dimensional sediment transport model of Poyang Lake, the largest freshwater lake in China. Optimal interpolation is used as the assimilation method, and model predictions are obtained by combining four remote sensing images. The parameters for optimal interpolation are determined through a series of assimilation experiments evaluating the sediment predictions based on field measurements. The model with assimilation of remotely sensed sediment reduces the root-mean-square error of the predicted sediment concentrations by 39.4% relative to the model without assimilation, demonstrating the effectiveness of the assimilation scheme. The spatial effect of assimilation is explored by comparing model predictions with remotely sensed sediment, revealing that the model with assimilation generates reasonable spatial distribution patterns of suspended sediment. The temporal effect of assimilation on the model's predictive capabilities varies spatially, with an average temporal effect of approximately 10.8 days. The current velocities which dominate the rate and direction of sediment transport most likely result in spatial differences in the temporal effect of assimilation on model predictions.

Full wave simulation of waves in ECRIS plasmas based on the finite element method

Energy Technology Data Exchange (ETDEWEB)

Torrisi, G. [INFN - Laboratori Nazionali del Sud, via S. Sofia 62, 95123, Catania, Italy and Università Mediterranea di Reggio Calabria, Dipartimento di Ingegneria dell' Informazione, delle Infrastrutture e dell' Energia Sostenibile (DIIES), Via Graziella, I (Italy); Mascali, D.; Neri, L.; Castro, G.; Patti, G.; Celona, L.; Gammino, S.; Ciavola, G. [INFN - Laboratori Nazionali del Sud, via S. Sofia 62, 95123, Catania (Italy); Di Donato, L. [Università degli Studi di Catania, Dipartimento di Ingegneria Elettrica Elettronica ed Informatica (DIEEI), Viale Andrea Doria 6, 95125 Catania (Italy); Sorbello, G. [INFN - Laboratori Nazionali del Sud, via S. Sofia 62, 95123, Catania, Italy and Università degli Studi di Catania, Dipartimento di Ingegneria Elettrica Elettronica ed Informatica (DIEEI), Viale Andrea Doria 6, 95125 Catania (Italy); Isernia, T. [Università Mediterranea di Reggio Calabria, Dipartimento di Ingegneria dell' Informazione, delle Infrastrutture e dell' Energia Sostenibile (DIIES), Via Graziella, I-89100 Reggio Calabria (Italy)

2014-02-12

This paper describes the modeling and the full wave numerical simulation of electromagnetic waves propagation and absorption in an anisotropic magnetized plasma filling the resonant cavity of an electron cyclotron resonance ion source (ECRIS). The model assumes inhomogeneous, dispersive and tensorial constitutive relations. Maxwell's equations are solved by the finite element method (FEM), using the COMSOL Multiphysics{sup ®} suite. All the relevant details have been considered in the model, including the non uniform external magnetostatic field used for plasma confinement, the local electron density profile resulting in the full-3D non uniform magnetized plasma complex dielectric tensor. The more accurate plasma simulations clearly show the importance of cavity effect on wave propagation and the effects of a resonant surface. These studies are the pillars for an improved ECRIS plasma modeling, that is mandatory to optimize the ion source output (beam intensity distribution and charge state, especially). Any new project concerning the advanced ECRIS design will take benefit by an adequate modeling of self-consistent wave absorption simulations.

Estimating model parameters for an impact-produced shock-wave simulation: Optimal use of partial data with the extended Kalman filter

International Nuclear Information System (INIS)

Kao, Jim; Flicker, Dawn; Ide, Kayo; Ghil, Michael

2006-01-01

This paper builds upon our recent data assimilation work with the extended Kalman filter (EKF) method [J. Kao, D. Flicker, R. Henninger, S. Frey, M. Ghil, K. Ide, Data assimilation with an extended Kalman filter for an impact-produced shock-wave study, J. Comp. Phys. 196 (2004) 705-723.]. The purpose is to test the capability of EKF in optimizing a model's physical parameters. The problem is to simulate the evolution of a shock produced through a high-speed flyer plate. In the earlier work, we have showed that the EKF allows one to estimate the evolving state of the shock wave from a single pressure measurement, assuming that all model parameters are known. In the present paper, we show that imperfectly known model parameters can also be estimated accordingly, along with the evolving model state, from the same single measurement. The model parameter optimization using the EKF can be achieved through a simple modification of the original EKF formalism by including the model parameters into an augmented state variable vector. While the regular state variables are governed by both deterministic and stochastic forcing mechanisms, the parameters are only subject to the latter. The optimally estimated model parameters are thus obtained through a unified assimilation operation. We show that improving the accuracy of the model parameters also improves the state estimate. The time variation of the optimized model parameters results from blending the data and the corresponding values generated from the model and lies within a small range, of less than 2%, from the parameter values of the original model. The solution computed with the optimized parameters performs considerably better and has a smaller total variance than its counterpart using the original time-constant parameters. These results indicate that the model parameters play a dominant role in the performance of the shock-wave hydrodynamic code at hand

Ensemble Kalman Filter data assimilation and storm surge experiments of tropical cyclone Nargis

Directory of Open Access Journals (Sweden)

Le Duc

2015-07-01

Full Text Available Data assimilation experiments on Myanmar tropical cyclone (TC, Nargis, using the Local Ensemble Transform Kalman Filter (LETKF method and the Japan Meteorological Agency (JMA non-hydrostatic model (NHM were performed to examine the impact of LETKF on analysis performance in real cases. Although the LETKF control experiment using NHM as its driving model (NHM–LETKF produced a weak vortex, the subsequent 3-day forecast predicted Nargis’ track and intensity better than downscaling from JMA's global analysis. Some strategies to further improve the final analysis were considered. They were sea surface temperature (SST perturbations and assimilation of TC advisories. To address SST uncertainty, SST analyses issued by operational forecast centres were used in the assimilation window. The use of a fixed source of SST analysis for each ensemble member was more effective in practice. SST perturbations were found to have slightly positive impact on the track forecasts. Assimilation of TC advisories could have a positive impact with a reasonable choice of its free parameters. However, the TC track forecasts exhibited northward displacements, when the observation error of intensities was underestimated in assimilation of TC advisories. The use of assimilation of TC advisories was considered in the final NHM–LETKF by choosing an appropriate set of free parameters. The extended forecast based on the final analysis provided meteorological forcings for a storm surge simulation using the Princeton Ocean Model. Probabilistic forecasts of the water levels at Irrawaddy and Yangon significantly improved the results in the previous studies.

Benefits and Pitfalls of GRACE Terrestrial Water Storage Data Assimilation

Science.gov (United States)

Girotto, Manuela

2018-01-01

Satellite observations of terrestrial water storage (TWS) from the Gravity Recovery and Climate Experiment (GRACE) mission have a coarse resolution in time (monthly) and space (roughly 150,000 sq km at midlatitudes) and vertically integrate all water storage components over land, including soil moisture and groundwater. Nonetheless, data assimilation can be used to horizontally downscale and vertically partition GRACE-TWS observations. This presentation illustrates some of the benefits and drawbacks of assimilating TWS observations from GRACE into a land surface model over the continental United States and India. The assimilation scheme yields improved skill metrics for groundwater compared to the no-assimilation simulations. A smaller impact is seen for surface and root-zone soil moisture. Further, GRACE observes TWS depletion associated with anthropogenic groundwater extraction. Results from the assimilation emphasize the importance of representing anthropogenic processes in land surface modeling and data assimilation systems.

Application of the Most Likely Extreme Response Method for Wave Energy Converters: Preprint

Energy Technology Data Exchange (ETDEWEB)

Quon, Eliot; Platt, Andrew; Yu, Yi-Hsiang; Lawson, Michael

2016-07-01

Extreme loads are often a key cost driver for wave energy converters (WECs). As an alternative to exhaustive Monte Carlo or long-term simulations, the most likely extreme response (MLER) method allows mid- and high-fidelity simulations to be used more efficiently in evaluating WEC response to events at the edges of the design envelope, and is therefore applicable to system design analysis. The study discussed in this paper applies the MLER method to investigate the maximum heave, pitch, and surge force of a point absorber WEC. Most likely extreme waves were obtained from a set of wave statistics data based on spectral analysis and the response amplitude operators (RAOs) of the floating body; the RAOs were computed from a simple radiation-and-diffraction-theory-based numerical model. A weakly nonlinear numerical method and a computational fluid dynamics (CFD) method were then applied to compute the short-term response to the MLER wave. Effects of nonlinear wave and floating body interaction on the WEC under the anticipated 100-year waves were examined by comparing the results from the linearly superimposed RAOs, the weakly nonlinear model, and CFD simulations. Overall, the MLER method was successfully applied. In particular, when coupled to a high-fidelity CFD analysis, the nonlinear fluid dynamics can be readily captured.

Assimilation of ice and water observations from SAR imagery to improve estimates of sea ice concentration

Directory of Open Access Journals (Sweden)

K. Andrea Scott

2015-09-01

Full Text Available In this paper, the assimilation of binary observations calculated from synthetic aperture radar (SAR images of sea ice is investigated. Ice and water observations are obtained from a set of SAR images by thresholding ice and water probabilities calculated using a supervised maximum likelihood estimator (MLE. These ice and water observations are then assimilated in combination with ice concentration from passive microwave imagery for the purpose of estimating sea ice concentration. Due to the fact that the observations are binary, consisting of zeros and ones, while the state vector is a continuous variable (ice concentration, the forward model used to map the state vector to the observation space requires special consideration. Both linear and non-linear forward models were investigated. In both cases, the assimilation of SAR data was able to produce ice concentration analyses in closer agreement with image analysis charts than when assimilating passive microwave data only. When both passive microwave and SAR data are assimilated, the bias between the ice concentration analyses and the ice concentration from ice charts is 19.78%, as compared to 26.72% when only passive microwave data are assimilated. The method presented here for the assimilation of SAR data could be applied to other binary observations, such as ice/water information from visual/infrared sensors.

Chiral metamaterials characterisation using the wave propagation retrieval method

DEFF Research Database (Denmark)

Andryieuski, Andrei; Lavrinenko, Andrei; Malureanu, Radu

2010-01-01

In this presentation we extend the wave propagation method for the retrieval of the effective properties to the case of chiral metamaterials with circularly polarised eigenwaves. The method is unambiguous, simple and provides bulk effective parameters. Advantages and constraints are discussed...

The development of efficient numerical time-domain modeling methods for geophysical wave propagation

Science.gov (United States)

Zhu, Lieyuan

This Ph.D. dissertation focuses on the numerical simulation of geophysical wave propagation in the time domain including elastic waves in solid media, the acoustic waves in fluid media, and the electromagnetic waves in dielectric media. This thesis shows that a linear system model can describe accurately the physical processes of those geophysical waves' propagation and can be used as a sound basis for modeling geophysical wave propagation phenomena. The generalized stability condition for numerical modeling of wave propagation is therefore discussed in the context of linear system theory. The efficiency of a series of different numerical algorithms in the time-domain for modeling geophysical wave propagation are discussed and compared. These algorithms include the finite-difference time-domain method, pseudospectral time domain method, alternating directional implicit (ADI) finite-difference time domain method. The advantages and disadvantages of these numerical methods are discussed and the specific stability condition for each modeling scheme is carefully derived in the context of the linear system theory. Based on the review and discussion of these existing approaches, the split step, ADI pseudospectral time domain (SS-ADI-PSTD) method is developed and tested for several cases. Moreover, the state-of-the-art stretched-coordinate perfect matched layer (SCPML) has also been implemented in SS-ADI-PSTD algorithm as the absorbing boundary condition for truncating the computational domain and absorbing the artificial reflection from the domain boundaries. After algorithmic development, a few case studies serve as the real-world examples to verify the capacities of the numerical algorithms and understand the capabilities and limitations of geophysical methods for detection of subsurface contamination. The first case is a study using ground penetrating radar (GPR) amplitude variation with offset (AVO) for subsurface non-aqueous-liquid (NAPL) contamination. The

On the role of perception in shaping phonological assimilation rules.

Science.gov (United States)

Hura, S L; Lindblom, B; Diehl, R L

1992-01-01

Assimilation of nasals to the place of articulation of following consonants is a common and natural process among the world's languages. Recent phonological theory attributes this naturalness to the postulated geometry of articulatory features and the notion of spreading (McCarthy, 1988). Others view assimilation as a result of perception (Ohala, 1990), or as perceptually tolerated articulatory simplification (Kohler, 1990). Kohler notes that certain consonant classes (such as nasals and stops) are more likely than other classes (such as fricatives) to undergo place assimilation to a following consonant. To explain this pattern, he proposes that assimilation tends not to occur when the members of a consonant class are relatively distinctive perceptually, such that their articulatory reduction would be particularly salient. This explanation, of course, presupposes that the stops and nasals which undergo place assimilation are less distinctive than fricatives, which tend not to assimilate. We report experimental results that confirm Kohler's perceptual assumption: In the context of a following word initial stop, fricatives were less confusable than nasals or unreleased stops. We conclude, in agreement with Ohala and Kohler, that perceptual factors are likely to shape phonological assimilation rules.

Limitations of ozone data assimilation with adjustment of NOx emissions: mixed effects on NO2 forecasts over Beijing and surrounding areas

Directory of Open Access Journals (Sweden)

X. Tang

2016-05-01

Full Text Available This study investigates a cross-variable ozone data assimilation (DA method based on an ensemble Kalman filter (EnKF that has been used in the companion study to improve ozone forecasts over Beijing and surrounding areas. The main purpose is to delve into the impacts of the cross-variable adjustment of nitrogen oxide (NOx emissions on the nitrogen dioxide (NO2 forecasts over this region during the 2008 Beijing Olympic Games. A mixed effect on the NO2 forecasts was observed through application of the cross-variable assimilation approach in the real-data assimilation (RDA experiments. The method improved the NO2 forecasts over almost half of the urban sites with reductions of the root mean square errors (RMSEs by 15–36 % in contrast to big increases of the RMSEs over other urban stations by 56–239 %. Over the urban stations with negative DA impacts, improvement of the NO2 forecasts (with 7 % reduction of the RMSEs was noticed at night and in the morning versus significant deterioration during daytime (with 190 % increase of the RMSEs, suggesting that the negative data assimilation impacts mainly occurred during daytime. Ideal-data assimilation (IDA experiments with a box model and the same cross-variable assimilation method confirmed the mixed effects found in the RDA experiments. In the same way, NOx emission estimation was improved at night and in the morning even under large biases in the prior emission, while it deteriorated during daytime (except for the case of minor errors in the prior emission. The mixed effects observed in the cross-variable data assimilation, i.e., positive data assimilation impacts on NO2 forecasts over some urban sites, negative data assimilation impacts over the other urban sites, and weak data assimilation impacts over suburban sites, highlighted the limitations of the EnKF under strong nonlinear relationships between chemical variables. Under strong nonlinearity between daytime ozone concentrations and

An Unconditionally Stable Method for Solving the Acoustic Wave Equation

Directory of Open Access Journals (Sweden)

Zhi-Kai Fu

2015-01-01

Full Text Available An unconditionally stable method for solving the time-domain acoustic wave equation using Associated Hermit orthogonal functions is proposed. The second-order time derivatives in acoustic wave equation are expanded by these orthogonal basis functions. By applying Galerkin temporal testing procedure, the time variable can be eliminated from the calculations. The restriction of Courant-Friedrichs-Levy (CFL condition in selecting time step for analyzing thin layer can be avoided. Numerical results show the accuracy and the efficiency of the proposed method.

A Novel Grey Wave Method for Predicting Total Chinese Trade Volume

Directory of Open Access Journals (Sweden)

Kedong Yin

2017-12-01

Full Text Available The total trade volume of a country is an important way of appraising its international trade situation. A prediction based on trade volume will help enterprises arrange production efficiently and promote the sustainability of the international trade. Because the total Chinese trade volume fluctuates over time, this paper proposes a Grey wave forecasting model with a Hodrick–Prescott filter (HP filter to forecast it. This novel model first parses time series into long-term trend and short-term cycle. Second, the model uses a general GM (1,1 to predict the trend term and the Grey wave forecasting model to predict the cycle term. Empirical analysis shows that the improved Grey wave prediction method provides a much more accurate forecast than the basic Grey wave prediction method, achieving better prediction results than autoregressive moving average model (ARMA.

Assimilation of GNSS radio occultation observations in GRAPES

Science.gov (United States)

Liu, Y.; Xue, J.

2014-07-01

This paper reviews the development of the global navigation satellite system (GNSS) radio occultation (RO) observations assimilation in the Global/Regional Assimilation and PrEdiction System (GRAPES) of China Meteorological Administration, including the choice of data to assimilate, the data quality control, the observation operator, the tuning of observation error, and the results of the observation impact experiments. The results indicate that RO data have a significantly positive effect on analysis and forecast at all ranges in GRAPES not only in the Southern Hemisphere where conventional observations are lacking but also in the Northern Hemisphere where data are rich. It is noted that a relatively simple assimilation and forecast system in which only the conventional and RO observation are assimilated still has analysis and forecast skill even after nine months integration, and the analysis difference between both hemispheres is gradually reduced with height when compared with NCEP (National Centers for Enviromental Prediction) analysis. Finally, as a result of the new onboard payload of the Chinese FengYun-3 (FY-3) satellites, the research status of the RO of FY-3 satellites is also presented.

Data Assimilation in Air Contaminant Dispersion Using a Particle Filter and Expectation-Maximization Algorithm

Directory of Open Access Journals (Sweden)

Rongxiao Wang

2017-09-01

Full Text Available The accurate prediction of air contaminant dispersion is essential to air quality monitoring and the emergency management of contaminant gas leakage incidents in chemical industry parks. Conventional atmospheric dispersion models can seldom give accurate predictions due to inaccurate input parameters. In order to improve the prediction accuracy of dispersion models, two data assimilation methods (i.e., the typical particle filter & the combination of a particle filter and expectation-maximization algorithm are proposed to assimilate the virtual Unmanned Aerial Vehicle (UAV observations with measurement error into the atmospheric dispersion model. Two emission cases with different dimensions of state parameters are considered. To test the performances of the proposed methods, two numerical experiments corresponding to the two emission cases are designed and implemented. The results show that the particle filter can effectively estimate the model parameters and improve the accuracy of model predictions when the dimension of state parameters is relatively low. In contrast, when the dimension of state parameters becomes higher, the method of particle filter combining the expectation-maximization algorithm performs better in terms of the parameter estimation accuracy. Therefore, the proposed data assimilation methods are able to effectively support air quality monitoring and emergency management in chemical industry parks.

SMOS brightness temperature assimilation into the Community Land Model

Directory of Open Access Journals (Sweden)

D. Rains

2017-11-01

Full Text Available SMOS (Soil Moisture and Ocean Salinity mission brightness temperatures at a single incident angle are assimilated into the Community Land Model (CLM across Australia to improve soil moisture simulations. Therefore, the data assimilation system DasPy is coupled to the local ensemble transform Kalman filter (LETKF as well as to the Community Microwave Emission Model (CMEM. Brightness temperature climatologies are precomputed to enable the assimilation of brightness temperature anomalies, making use of 6 years of SMOS data (2010–2015. Mean correlation R with in situ measurements increases moderately from 0.61 to 0.68 (11 % for upper soil layers if the root zone is included in the updates. A reduced improvement of 5 % is achieved if the assimilation is restricted to the upper soil layers. Root-zone simulations improve by 7 % when updating both the top layers and root zone, and by 4 % when only updating the top layers. Mean increments and increment standard deviations are compared for the experiments. The long-term assimilation impact is analysed by looking at a set of quantiles computed for soil moisture at each grid cell. Within hydrological monitoring systems, extreme dry or wet conditions are often defined via their relative occurrence, adding great importance to assimilation-induced quantile changes. Although still being limited now, longer L-band radiometer time series will become available and make model output improved by assimilating such data that are more usable for extreme event statistics.

You are not always what we think you eat. Selective assimilation across multiple whole-stream isotopic tracer studies

International Nuclear Information System (INIS)

Dodds, W. K.; Collins, S. M.; Hamilton, S. K.; Johnson, S.; Webster, J. R.; Simon, K. S.; Whiles, M. R.; Rantala, H. M.; McDowell, W. H.; Peterson, S. D.; Riis, T.; Crenshaw, C. L.; Thomas, S. A.; Kristensen, P. B.; Cheever, B. M.; Flecker, A. S.; Griffiths, N. A.; Crowl, T.; Rosi-Marshall, E. J.; El-Sabaawi, R.; Marti, E.

2014-01-01

Analyses of 21 15 N stable isotope tracer experiments, designed to examine food web dynamics in streams around the world, indicated that the isotopic composition of food resources assimilated by primary consumers (mostly invertebrates) poorly reflected the presumed food sources. Modeling indicated that consumers assimilated only 33-50% of the N available in sampled food sources such as decomposing leaves, epilithon, and fine particulate detritus over feeding periods of weeks or more. Thus, common methods of sampling food sources consumed by animals in streams do not sufficiently reflect the pool of N they assimilate. Lastly, Isotope tracer studies, combined with modeling and food separation techniques, can improve estimation of N pools in food sources that are assimilated by consumers

Refinements to the method of epicentral location based on surface waves from ambient seismic noise: introducing Love waves

Science.gov (United States)

Levshin, Anatoli L.; Barmin, Mikhail P.; Moschetti, Morgan P.; Mendoza, Carlos; Ritzwoller, Michael H.

2012-01-01

The purpose of this study is to develop and test a modification to a previous method of regional seismic event location based on Empirical Green’s Functions (EGFs) produced from ambient seismic noise. Elastic EGFs between pairs of seismic stations are determined by cross-correlating long ambient noise time-series recorded at the two stations. The EGFs principally contain Rayleigh- and Love-wave energy on the vertical and transverse components, respectively, and we utilize these signals between about 5 and 12 s period. The previous method, based exclusively on Rayleigh waves, may yield biased epicentral locations for certain event types with hypocentral depths between 2 and 5 km. Here we present theoretical arguments that show how Love waves can be introduced to reduce or potentially eliminate the bias. We also present applications of Rayleigh- and Love-wave EGFs to locate 10 reference events in the western United States. The separate Rayleigh and Love epicentral locations and the joint locations using a combination of the two waves agree to within 1 km distance, on average, but confidence ellipses are smallest when both types of waves are used.

Coupling of WRF meteorological model to WAM spectral wave model through sea surface roughness at the Balearic Sea: impact on wind and wave forecasts

Science.gov (United States)

Tolosana-Delgado, R.; Soret, A.; Jorba, O.; Baldasano, J. M.; Sánchez-Arcilla, A.

2012-04-01

scope of the 7th EU FP Project FIELD_AC, assesses the impact of coupling WAM and WRF on wind and wave forecasts on the Balearic Sea, and compares it with other possible improvements, like using available high-resolution circulation information from MyOcean GMES core services, or assimilating altimeter data on the Western Mediterranean. This is done in an ordered fashion following statistical design rules, which allows to extract main effects of each of the factors considered (coupling, better circulation information, data assimilation following Lionello et al., 1992) as well as two-factor interactions. Moreover, the statistical significance of these improvements can be tested in the future, though this requires maximum likelihood ratio tests with correlated data. Charnock, H. (1955) Wind stress on a water surface. Quart.J. Row. Met. Soc. 81: 639-640 Donelan, M. (1982) The dependence of aerodynamic drag coefficient on wave parameters. Proc. 1st Int. Conf. on Meteorology and Air-Sea Interactions of teh Coastal Zone. The Hague (Netherlands). AMS. 381-387 Janssen, P.A.E.M., Doyle, J., Bidlot, J., Hansen, B., Isaksen, L. and Viterbo, P. (1990) The impact of oean waves on the atmosphere. Seminars of the ECMWF. Lionello, P., Günther, H., and Janssen P.A.E.M. (1992) Assimilation of altimeter data in a global third-generation wave model. Journal of Geophysical Research 97 (C9): 453-474. Warner, J., Armstrong, B., He, R. and Zambon, J.B. (2010) Development of a Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modeling System. Ocean Modelling 35: 230-244.

Ensemble Kalman Filtering with a Divided State-Space Strategy for Coupled Data Assimilation Problems

KAUST Repository

Luo, Xiaodong

2014-12-01

This study considers the data assimilation problem in coupled systems, which consists of two components (subsystems) interacting with each other through certain coupling terms. A straightforward way to tackle the assimilation problem in such systems is to concatenate the states of the subsystems into one augmented state vector, so that a standard ensemble Kalman filter (EnKF) can be directly applied. This work presents a divided state-space estimation strategy, in which data assimilation is carried out with respect to each individual subsystem, involving quantities from the subsystem itself and correlated quantities from other coupled subsystems. On top of the divided state-space estimation strategy, the authors also consider the possibility of running the subsystems separately. Combining these two ideas, a few variants of the EnKF are derived. The introduction of these variants is mainly inspired by the current status and challenges in coupled data assimilation problems and thus might be of interest from a practical point of view. Numerical experiments with a multiscale Lorenz 96 model are conducted to evaluate the performance of these variants against that of the conventional EnKF. In addition, specific for coupled data assimilation problems, two prototypes of extensions of the presented methods are also developed in order to achieve a trade-offbetween efficiency and accuracy.

Ensemble Kalman Filtering with a Divided State-Space Strategy for Coupled Data Assimilation Problems

KAUST Repository

Luo, Xiaodong; Hoteit, Ibrahim

2014-01-01

This study considers the data assimilation problem in coupled systems, which consists of two components (subsystems) interacting with each other through certain coupling terms. A straightforward way to tackle the assimilation problem in such systems is to concatenate the states of the subsystems into one augmented state vector, so that a standard ensemble Kalman filter (EnKF) can be directly applied. This work presents a divided state-space estimation strategy, in which data assimilation is carried out with respect to each individual subsystem, involving quantities from the subsystem itself and correlated quantities from other coupled subsystems. On top of the divided state-space estimation strategy, the authors also consider the possibility of running the subsystems separately. Combining these two ideas, a few variants of the EnKF are derived. The introduction of these variants is mainly inspired by the current status and challenges in coupled data assimilation problems and thus might be of interest from a practical point of view. Numerical experiments with a multiscale Lorenz 96 model are conducted to evaluate the performance of these variants against that of the conventional EnKF. In addition, specific for coupled data assimilation problems, two prototypes of extensions of the presented methods are also developed in order to achieve a trade-offbetween efficiency and accuracy.

Bayesian Modeling of the Assimilative Capacity Component of Stream Nutrient Export

Science.gov (United States)

Implementing stream restoration techniques and best management practices to reduce nonpoint source nutrients implies enhancement of the assimilative capacity for the stream system. In this paper, a Bayesian method for evaluating this component of a TMDL load capacity is developed...

Description and verification of a U.S. Naval Research Lab's loosely coupled data assimilation system for the Navy's Earth System Model

Science.gov (United States)

Barton, N. P.; Metzger, E. J.; Smedstad, O. M.; Ruston, B. C.; Wallcraft, A. J.; Whitcomb, T.; Ridout, J. A.; Zamudio, L.; Posey, P.; Reynolds, C. A.; Richman, J. G.; Phelps, M.

2017-12-01

The Naval Research Laboratory is developing an Earth System Model (NESM) to provide global environmental information to meet Navy and Department of Defense (DoD) operations and planning needs from the upper atmosphere to under the sea. This system consists of a global atmosphere, ocean, ice, wave, and land prediction models and the individual models include: atmosphere - NAVy Global Environmental Model (NAVGEM); ocean - HYbrid Coordinate Ocean Model (HYCOM); sea ice - Community Ice CodE (CICE); WAVEWATCH III™; and land - NAVGEM Land Surface Model (LSM). Data assimilation is currently loosely coupled between the atmosphere component using a 6-hour update cycle in the Naval Research Laboratory (NRL) Atmospheric Variational Data Assimilation System - Accelerated Representer (NAVDAS-AR) and the ocean/ice components using a 24-hour update cycle in the Navy Coupled Ocean Data Assimilation (NCODA) with 3 hours of incremental updating. This presentation will describe the US Navy's coupled forecast model, the loosely coupled data assimilation, and compare results against stand-alone atmosphere and ocean/ice models. In particular, we will focus on the unique aspects of this modeling system, which includes an eddy resolving ocean model and challenges associated with different update-windows and solvers for the data assimilation in the atmosphere and ocean. Results will focus on typical operational diagnostics for atmosphere, ocean, and ice analyses including 500 hPa atmospheric height anomalies, low-level winds, temperature/salinity ocean depth profiles, ocean acoustical proxies, sea ice edge, and sea ice drift. Overall, the global coupled system is performing with comparable skill to the stand-alone systems.

Adjoint-Free Variational Data Assimilation into a Regional Wave Model

Science.gov (United States)

2015-07-01

Wave Model 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER...developed by Oceanweather, Inc. using the methodology of Cardone et al. (1995, 1996). The winds were taken for the period 11–20 September 2011 and...International Arctic Research Center, NSF Grants 1107925 and 1203740. It was also supported by theOffice of Naval Research (Program Element 0602435N, pro

Improving Snow Modeling by Assimilating Observational Data Collected by Citizen Scientists

Science.gov (United States)

Crumley, R. L.; Hill, D. F.; Arendt, A. A.; Wikstrom Jones, K.; Wolken, G. J.; Setiawan, L.

2017-12-01

Modeling seasonal snow pack in alpine environments includes a multiplicity of challenges caused by a lack of spatially extensive and temporally continuous observational datasets. This is partially due to the difficulty of collecting measurements in harsh, remote environments where extreme gradients in topography exist, accompanied by large model domains and inclement weather. Engaging snow enthusiasts, snow professionals, and community members to participate in the process of data collection may address some of these challenges. In this study, we use SnowModel to estimate seasonal snow water equivalence (SWE) in the Thompson Pass region of Alaska while incorporating snow depth measurements collected by citizen scientists. We develop a modeling approach to assimilate hundreds of snow depth measurements from participants in the Community Snow Observations (CSO) project (www.communitysnowobs.org). The CSO project includes a mobile application where participants record and submit geo-located snow depth measurements while working and recreating in the study area. These snow depth measurements are randomly located within the model grid at irregular time intervals over the span of four months in the 2017 water year. This snow depth observation dataset is converted into a SWE dataset by employing an empirically-based, bulk density and SWE estimation method. We then assimilate this data using SnowAssim, a sub-model within SnowModel, to constrain the SWE output by the observed data. Multiple model runs are designed to represent an array of output scenarios during the assimilation process. An effort to present model output uncertainties is included, as well as quantification of the pre- and post-assimilation divergence in modeled SWE. Early results reveal pre-assimilation SWE estimations are consistently greater than the post-assimilation estimations, and the magnitude of divergence increases throughout the snow pack evolution period. This research has implications beyond the

Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments

Science.gov (United States)

van Peet, Jacob C. A.; van der A, Ronald J.; Kelder, Hennie M.; Levelt, Pieternel F.

2018-02-01

A three-dimensional global ozone distribution has been derived from assimilation of ozone profiles that were observed by satellites. By simultaneous assimilation of ozone profiles retrieved from the nadir looking satellite instruments Global Ozone Monitoring Experiment 2 (GOME-2) and Ozone Monitoring Instrument (OMI), which measure the atmosphere at different times of the day, the quality of the derived atmospheric ozone field has been improved. The assimilation is using an extended Kalman filter in which chemical transport model TM5 has been used for the forecast. The combined assimilation of both GOME-2 and OMI improves upon the assimilation results of a single sensor. The new assimilation system has been demonstrated by processing 4 years of data from 2008 to 2011. Validation of the assimilation output by comparison with sondes shows that biases vary between -5 and +10 % between the surface and 100 hPa. The biases for the combined assimilation vary between -3 and +3 % in the region between 100 and 10 hPa where GOME-2 and OMI are most sensitive. This is a strong improvement compared to direct retrievals of ozone profiles from satellite observations.

Multiple travelling wave solutions of nonlinear evolution equations using a unified algebraic method

International Nuclear Information System (INIS)

Fan Engui

2002-01-01

A new direct and unified algebraic method for constructing multiple travelling wave solutions of general nonlinear evolution equations is presented and implemented in a computer algebraic system. Compared with most of the existing tanh methods, the Jacobi elliptic function method or other sophisticated methods, the proposed method not only gives new and more general solutions, but also provides a guideline to classify the various types of the travelling wave solutions according to the values of some parameters. The solutions obtained in this paper include (a) kink-shaped and bell-shaped soliton solutions, (b) rational solutions, (c) triangular periodic solutions and (d) Jacobi and Weierstrass doubly periodic wave solutions. Among them, the Jacobi elliptic periodic wave solutions exactly degenerate to the soliton solutions at a certain limit condition. The efficiency of the method can be demonstrated on a large variety of nonlinear evolution equations such as those considered in this paper, KdV-MKdV, Ito's fifth MKdV, Hirota, Nizhnik-Novikov-Veselov, Broer-Kaup, generalized coupled Hirota-Satsuma, coupled Schroedinger-KdV, (2+1)-dimensional dispersive long wave, (2+1)-dimensional Davey-Stewartson equations. In addition, as an illustrative sample, the properties of the soliton solutions and Jacobi doubly periodic solutions for the Hirota equation are shown by some figures. The links among our proposed method, the tanh method, extended tanh method and the Jacobi elliptic function method are clarified generally. (author)

Determination of the atomic C/N assimilation ratio values of a pure culture of dunaliella and samples from rivers in Terengganu using the sup 14 C tracer method

International Nuclear Information System (INIS)

Lokman bin Shamsudin

1990-01-01

The C/N assimilation ratio has been defined by Chan and Raine as the ratio of carbon assimilated by a given algal population to that of the total inorganic nitrogen assimilated. The apparent carbon to nitrogen assimilation ratio for Dunaliella (pure algal culture) as well as subsurface water taken from some rivers in Terengganu was mainly attributed to the assimilation of the type of inorganic nitrogen, namely ammonium or nitrate found in the medium. The high C/N value for the various water samples was mainly attributed to the assimilation of ammonium nitrogen available in large amount in the tropical aquatic environment. The ammonium-nitrogen contents exceeds that of nitrate contents at the two stations

Overdetermined shooting methods for computing standing water waves with spectral accuracy

International Nuclear Information System (INIS)

Wilkening, Jon; Yu Jia

2012-01-01

A high-performance shooting algorithm is developed to compute time-periodic solutions of the free-surface Euler equations with spectral accuracy in double and quadruple precision. The method is used to study resonance and its effect on standing water waves. We identify new nucleation mechanisms in which isolated large-amplitude solutions, and closed loops of such solutions, suddenly exist for depths below a critical threshold. We also study degenerate and secondary bifurcations related to Wilton's ripples in the traveling case, and explore the breakdown of self-similarity at the crests of extreme standing waves. In shallow water, we find that standing waves take the form of counter-propagating solitary waves that repeatedly collide quasi-elastically. In deep water with surface tension, we find that standing waves resemble counter-propagating depression waves. We also discuss the existence and non-uniqueness of solutions, and smooth versus erratic dependence of Fourier modes on wave amplitude and fluid depth. In the numerical method, robustness is achieved by posing the problem as an overdetermined nonlinear system and using either adjoint-based minimization techniques or a quadratically convergent trust-region method to minimize the objective function. Efficiency is achieved in the trust-region approach by parallelizing the Jacobian computation, so the setup cost of computing the Dirichlet-to-Neumann operator in the variational equation is not repeated for each column. Updates of the Jacobian are also delayed until the previous Jacobian ceases to be useful. Accuracy is maintained using spectral collocation with optional mesh refinement in space, a high-order Runge–Kutta or spectral deferred correction method in time and quadruple precision for improved navigation of delicate regions of parameter space as well as validation of double-precision results. Implementation issues for transferring much of the computation to a graphic processing units are briefly

TSOS and TSOS-FK hybrid methods for modelling the propagation of seismic waves

Science.gov (United States)

Ma, Jian; Yang, Dinghui; Tong, Ping; Ma, Xiao

2018-05-01

We develop a new time-space optimized symplectic (TSOS) method for numerically solving elastic wave equations in heterogeneous isotropic media. We use the phase-preserving symplectic partitioned Runge-Kutta method to evaluate the time derivatives and optimized explicit finite-difference (FD) schemes to discretize the space derivatives. We introduce the averaged medium scheme into the TSOS method to further increase its capability of dealing with heterogeneous media and match the boundary-modified scheme for implementing free-surface boundary conditions and the auxiliary differential equation complex frequency-shifted perfectly matched layer (ADE CFS-PML) non-reflecting boundaries with the TSOS method. A comparison of the TSOS method with analytical solutions and standard FD schemes indicates that the waveform generated by the TSOS method is more similar to the analytic solution and has a smaller error than other FD methods, which illustrates the efficiency and accuracy of the TSOS method. Subsequently, we focus on the calculation of synthetic seismograms for teleseismic P- or S-waves entering and propagating in the local heterogeneous region of interest. To improve the computational efficiency, we successfully combine the TSOS method with the frequency-wavenumber (FK) method and apply the ADE CFS-PML to absorb the scattered waves caused by the regional heterogeneity. The TSOS-FK hybrid method is benchmarked against semi-analytical solutions provided by the FK method for a 1-D layered model. Several numerical experiments, including a vertical cross-section of the Chinese capital area crustal model, illustrate that the TSOS-FK hybrid method works well for modelling waves propagating in complex heterogeneous media and remains stable for long-time computation. These numerical examples also show that the TSOS-FK method can tackle the converted and scattered waves of the teleseismic plane waves caused by local heterogeneity. Thus, the TSOS and TSOS-FK methods proposed in

A Full-wave Model for Wave Propagation and Dissipation in the Inner Magnetosphere Using the Finite Element Method

International Nuclear Information System (INIS)

Valeo, Ernest; Johnson, Jay R.; Kim, Eun-Hwa; Phillips, Cynthia

2012-01-01

A wide variety of plasma waves play an important role in the energization and loss of particles in the inner magnetosphere. Our ability to understand and model wave-particle interactions in this region requires improved knowledge of the spatial distribution and properties of these waves as well as improved understanding of how the waves depend on changes in solar wind forcing and/or geomagnetic activity. To this end, we have developed a two-dimensional, finite element code that solves the full wave equations in global magnetospheric geometry. The code describes three-dimensional wave structure including mode conversion when ULF, EMIC, and whistler waves are launched in a two-dimensional axisymmetric background plasma with general magnetic field topology. We illustrate the capabilities of the code by examining the role of plasmaspheric plumes on magnetosonic wave propagation; mode conversion at the ion-ion and Alfven resonances resulting from external, solar wind compressions; and wave structure and mode conversion of electromagnetic ion cyclotron waves launched in the equatorial magnetosphere, which propagate along the magnetic field lines toward the ionosphere. We also discuss advantages of the finite element method for resolving resonant structures, and how the model may be adapted to include nonlocal kinetic effects.

Introduction to the physics properties of the waves trough the sound and acoustic didactics

OpenAIRE

Bernad Martínez, Jordi

2017-01-01

The project makes a journey through sound and acoustics to introduce abstract concepts related with the properties of waves, its processing and acquisition, digitization and compression. Develop a portfolio of basic theory adapted to students, which provides support for practices in order to consolidate and assimilate concepts related to the world of waves and communication. The project aims to link the content with situations or activities related to daily experiences of young students. Curr...

Regional Ocean Data Assimilation

KAUST Repository

Edwards, Christopher A.; Moore, Andrew M.; Hoteit, Ibrahim; Cornuelle, Bruce D.

2015-01-01

This article reviews the past 15 years of developments in regional ocean data assimilation. A variety of scientific, management, and safety-related objectives motivate marine scientists to characterize many ocean environments, including coastal

The Effects of Chlorophyll Assimilation on Carbon Fluxes in a Global Biogeochemical Model. [Technical Report Series on Global Modeling and Data Assimilation

Science.gov (United States)

Koster, Randal D. (Editor); Rousseaux, Cecile Severine; Gregg, Watson W.

2014-01-01

In this paper, we investigated whether the assimilation of remotely-sensed chlorophyll data can improve the estimates of air-sea carbon dioxide fluxes (FCO2). Using a global, established biogeochemical model (NASA Ocean Biogeochemical Model, NOBM) for the period 2003-2010, we found that the global FCO2 values produced in the free-run and after assimilation were within -0.6 mol C m(sup -2) y(sup -1) of the observations. The effect of satellite chlorophyll assimilation was assessed in 12 major oceanographic regions. The region with the highest bias was the North Atlantic. Here the model underestimated the fluxes by 1.4 mol C m(sup -2) y(sup -1) whereas all the other regions were within 1 mol C m(sup -2) y(sup -1) of the data. The FCO2 values were not strongly impacted by the assimilation, and the uncertainty in FCO2 was not decreased, despite the decrease in the uncertainty in chlorophyll concentration. Chlorophyll concentrations were within approximately 25% of the database in 7 out of the 12 regions, and the assimilation improved the chlorophyll concentration in the regions with the highest bias by 10-20%. These results suggest that the assimilation of chlorophyll data does not considerably improve FCO2 estimates and that other components of the carbon cycle play a role that could further improve our FCO2 estimates.

An assimilation test of Doppler radar reflectivity and radial velocity from different height layers in improving the WRF rainfall forecasts

Science.gov (United States)

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

2017-12-01

Hydrological forecasts require high-resolution and accurate rainfall information, which is one of the most difficult variables to be captured by the mesoscale Numerical Weather Prediction (NWP) systems. Radar data assimilation is an effective method for improving rainfall forecasts by correcting the initial and lateral boundary conditions of the NWP system. The aim of this study is to explore an efficient way of utilizing the Doppler radar observations for data assimilation, which is implemented by exploring the effect of assimilating radar data from different height layers on the improvement of the NWP rainfall accuracy. The Weather Research and Forecasting (WRF) model is used for numerical rainfall forecast in the Zijingguan catchment located in the ;Jing-Jin-Ji; (Beijing-Tianjin-Hebei) Region of Northern China, and the three-dimensional variational data assimilation (3-DVar) technique is adopted to assimilate the radar data. Radar reflectivity and radial velocity are assimilated separately and jointly. Each type of radar data is divided into seven data sets according to the height layers: (1) 2000 m, and (7) all layers. The results show that radar reflectivity assimilation leads to better results than radial velocity assimilation. The accuracy of the forecasted rainfall deteriorates with the rise of the height of the assimilated radar reflectivity. The same results can be found when assimilating radar reflectivity and radial velocity at the same time. The conclusions of this study provide a reference for efficient assimilation of the radar data in improving the NWP rainfall products.

Two modified symplectic partitioned Runge-Kutta methods for solving the elastic wave equation

Science.gov (United States)

Su, Bo; Tuo, Xianguo; Xu, Ling

2017-08-01

Based on a modified strategy, two modified symplectic partitioned Runge-Kutta (PRK) methods are proposed for the temporal discretization of the elastic wave equation. The two symplectic schemes are similar in form but are different in nature. After the spatial discretization of the elastic wave equation, the ordinary Hamiltonian formulation for the elastic wave equation is presented. The PRK scheme is then applied for time integration. An additional term associated with spatial discretization is inserted into the different stages of the PRK scheme. Theoretical analyses are conducted to evaluate the numerical dispersion and stability of the two novel PRK methods. A finite difference method is used to approximate the spatial derivatives since the two schemes are independent of the spatial discretization technique used. The numerical solutions computed by the two new schemes are compared with those computed by a conventional symplectic PRK. The numerical results, which verify the new method, are superior to those generated by traditional conventional methods in seismic wave modeling.

Nitrogen assimilation in soybean nodules, 1

International Nuclear Information System (INIS)

Ohyama, Takuji; Kumazawa, Kikuo

1980-01-01

In order to elucidate the pathways to assimilate the ammonia produced by N 2 -fixation in soybean nodules, 15 N-labeled compounds were administered to intact nodules or nodule slices pretreated with various inhibitors of nitrogen assimilation. After exposure to 15 N 2 , 15 N-incorporation into various nitrogenous compounds was investigated in attached nodules injected with methionine sulfoximine (MSX) or azaserine (AS). MSX treatment increased the 15 N content of ammonia more than 6 times, however, depressed 15 N content of most of amides and amino acids. AS treatment enhanced 15 N content of amido-N of glutamine as well as ammonia, but decreased amino-N of glutamine and most of amino acids. Experiments with nodule slices pretreated with MSX or AS solution and then fed with 15 N-labeled ammonia or amido- 15 N of glutamine showed the same trends. Aminooxyacetate inhibited nitrogen flow from glutamic acid to other amino acids. These results strongly indicate that the ammonia produced by N 2 -fixation is assimilated by GS/GOGAT system to glutamic acid and then transaminated to various amino acids in situ. 15 N-incorporation patterns in nodule slices fed with 15 N-labeled ammonia, hydroxylamine, nitrite were similar, but nitrate seemed to be reduced in a definite compartment and assimilated similarly as in intact nodules fed with 15 N 2 (author)

Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites

Directory of Open Access Journals (Sweden)

K. Aalstad

2018-01-01

Full Text Available With its high albedo, low thermal conductivity and large water storing capacity, snow strongly modulates the surface energy and water balance, which makes it a critical factor in mid- to high-latitude and mountain environments. However, estimating the snow water equivalent (SWE is challenging in remote-sensing applications already at medium spatial resolutions of 1 km. We present an ensemble-based data assimilation framework that estimates the peak subgrid SWE distribution (SSD at the 1 km scale by assimilating fractional snow-covered area (fSCA satellite retrievals in a simple snow model forced by downscaled reanalysis data. The basic idea is to relate the timing of the snow cover depletion (accessible from satellite products to the peak SSD. Peak subgrid SWE is assumed to be lognormally distributed, which can be translated to a modeled time series of fSCA through the snow model. Assimilation of satellite-derived fSCA facilitates the estimation of the peak SSD, while taking into account uncertainties in both the model and the assimilated data sets. As an extension to previous studies, our method makes use of the novel (to snow data assimilation ensemble smoother with multiple data assimilation (ES-MDA scheme combined with analytical Gaussian anamorphosis to assimilate time series of Moderate Resolution Imaging Spectroradiometer (MODIS and Sentinel-2 fSCA retrievals. The scheme is applied to Arctic sites near Ny-Ålesund (79° N, Svalbard, Norway where field measurements of fSCA and SWE distributions are available. The method is able to successfully recover accurate estimates of peak SSD on most of the occasions considered. Through the ES-MDA assimilation, the root-mean-square error (RMSE for the fSCA, peak mean SWE and peak subgrid coefficient of variation is improved by around 75, 60 and 20 %, respectively, when compared to the prior, yielding RMSEs of 0.01, 0.09 m water equivalent (w.e. and 0.13, respectively. The ES-MDA either

Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites

Science.gov (United States)

Aalstad, Kristoffer; Westermann, Sebastian; Vikhamar Schuler, Thomas; Boike, Julia; Bertino, Laurent

2018-01-01

With its high albedo, low thermal conductivity and large water storing capacity, snow strongly modulates the surface energy and water balance, which makes it a critical factor in mid- to high-latitude and mountain environments. However, estimating the snow water equivalent (SWE) is challenging in remote-sensing applications already at medium spatial resolutions of 1 km. We present an ensemble-based data assimilation framework that estimates the peak subgrid SWE distribution (SSD) at the 1 km scale by assimilating fractional snow-covered area (fSCA) satellite retrievals in a simple snow model forced by downscaled reanalysis data. The basic idea is to relate the timing of the snow cover depletion (accessible from satellite products) to the peak SSD. Peak subgrid SWE is assumed to be lognormally distributed, which can be translated to a modeled time series of fSCA through the snow model. Assimilation of satellite-derived fSCA facilitates the estimation of the peak SSD, while taking into account uncertainties in both the model and the assimilated data sets. As an extension to previous studies, our method makes use of the novel (to snow data assimilation) ensemble smoother with multiple data assimilation (ES-MDA) scheme combined with analytical Gaussian anamorphosis to assimilate time series of Moderate Resolution Imaging Spectroradiometer (MODIS) and Sentinel-2 fSCA retrievals. The scheme is applied to Arctic sites near Ny-Ålesund (79° N, Svalbard, Norway) where field measurements of fSCA and SWE distributions are available. The method is able to successfully recover accurate estimates of peak SSD on most of the occasions considered. Through the ES-MDA assimilation, the root-mean-square error (RMSE) for the fSCA, peak mean SWE and peak subgrid coefficient of variation is improved by around 75, 60 and 20 %, respectively, when compared to the prior, yielding RMSEs of 0.01, 0.09 m water equivalent (w.e.) and 0.13, respectively. The ES-MDA either outperforms or at least

A method of acoustic wave registration and determination their generation region

International Nuclear Information System (INIS)

Kozin, I.D.; Marchenko, M.V.

1998-01-01

Here is presented a method of acoustic wave registration with using of a synchronous LF broadcasting system. This method of detection and determination of underground nuclear explosion location is based on a registration of ionospheric disturbances induced by acoustic waves at the region of LF sign al reflection. The measuring complex created in the institute of the Ionosphere /1/ allows to register amplitude-frequency characteristics of composite signal from synchronous broadcasting net

Experiments of Long-range Inspection Method in Straight Pipes using Ultrasonic Guided Waves

International Nuclear Information System (INIS)

Eom, H. S.; Lim, S. H.; Kim, J. H.; Joo, Y.S.

2006-02-01

This report describes experimental results of a long-range inspection method of pipes using ultrasonic guided waves. In chapter 2, theory of guided wave was reviewed. In chapter 3, equipment and procedures which were used in the experiments were described. Detailed specifications of the specimens described in chapter 4. In chapter 5, we analyzed characteristics of guided wave signals according to shapes and sizes of defects and presents results of various signal processing methods

Application of Wave Distribution Function Method to the ERG/PWE Data

Science.gov (United States)

Ota, M.; Kasahara, Y.; Matsuda, S.; Kojima, H.; Matsuoka, A.; Hikishima, M.; Kasaba, Y.; Ozaki, M.; Yagitani, S.; Tsuchiya, F.; Kumamoto, A.

2017-12-01

The ERG (Arase) satellite was launched on 20 December 2016 to study acceleration and loss mechanisms of relativistic electrons in the Earth's magnetosphere. The Plasma Wave Experiment (PWE), which is one of the science instruments on board the ERG satellite, measures electric field and magnetic field. The PWE consists of three sub-systems; EFD (Electric Field Detector), OFA/WFC (Onboard Frequency Analyzer and Waveform Capture), and HFA (High Frequency Analyzer).The OFA/WFC measures electromagnetic field spectra and raw waveforms in the frequency range from few Hz to 20 kHz. The OFA produces three kind of data; OFA-SPEC (power spectrum), OFA-MATRIX (spectral matrix), and OFA-COMPLEX (complex spectrum). The OFA-MATRIX measures ensemble averaged complex cross-spectra of two electric field components, and of three magnetic field components. The OFA-COMPLEX measures instantaneous complex spectra of electric and magnetic fields. These data are produced every 8 seconds in the nominal mode, and it can be used for polarization analysis and wave propagation direction finding.In general, spectral matrix composed by cross-spectra of observed signals is used for direction finding, and many algorithms have been proposed. For example, Means method and SVD method can be applied on the assumption that the spectral matrix is consists of a single plane wave, while wave distribution function (WDF) method is applicable even to the data in which multiple numbers of plane waves are simultaneously included. In this presentation, we introduce the results when the WDF method is applied to the ERG/PWE data.

The (′/-Expansion Method for Abundant Traveling Wave Solutions of Caudrey-Dodd-Gibbon Equation

Directory of Open Access Journals (Sweden)

Hasibun Naher

2011-01-01

Full Text Available We construct the traveling wave solutions of the fifth-order Caudrey-Dodd-Gibbon (CDG equation by the (/-expansion method. Abundant traveling wave solutions with arbitrary parameters are successfully obtained by this method and the wave solutions are expressed in terms of the hyperbolic, the trigonometric, and the rational functions. It is shown that the (/-expansion method is a powerful and concise mathematical tool for solving nonlinear partial differential equations.

Variational data assimilation for the optimized ozone initial state and the short-time forecasting

Directory of Open Access Journals (Sweden)

S.-Y. Park

2016-03-01

Full Text Available In this study, we apply the four-dimensional variational (4D-Var data assimilation to optimize initial ozone state and to improve the predictability of air quality. The numerical modeling systems used for simulations of atmospheric condition and chemical formation are the Weather Research and Forecasting (WRF model and the Community Multiscale Air Quality (CMAQ model. The study area covers the capital region of South Korea, where the surface measurement sites are relatively evenly distributed. The 4D-Var code previously developed for the CMAQ model is modified to consider background error in matrix form, and various numerical tests are conducted. The results are evaluated with an idealized covariance function for the appropriateness of the modified codes. The background error is then constructed using the NMC method with long-term modeling results, and the characteristics of the spatial correlation scale related to local circulation are analyzed. The background error is applied in the 4D-Var research, and a surface observational assimilation is conducted to optimize the initial concentration of ozone. The statistical results for the 12 h assimilation periods and the 120 observatory sites show a 49.4 % decrease in the root mean squared error (RMSE, and a 59.9 % increase in the index of agreement (IOA. The temporal variation of spatial distribution of the analysis increments indicates that the optimized initial state of ozone concentration is transported to inland areas by the clockwise-rotating local circulation during the assimilation windows. To investigate the predictability of ozone concentration after the assimilation window, a short-time forecasting is carried out. The ratios of the RMSE (root mean squared error with assimilation versus that without assimilation are 8 and 13 % for the +24 and +12 h, respectively. Such a significant improvement in the forecast accuracy is obtained solely by using the optimized initial state. The potential

Assimilation of satellite color observations in a coupled ocean GCM-ecosystem model

Science.gov (United States)

Sarmiento, Jorge L.

1992-01-01

Monthly average coastal zone color scanner (CZCS) estimates of chlorophyll concentration were assimilated into an ocean global circulation model(GCM) containing a simple model of the pelagic ecosystem. The assimilation was performed in the simplest possible manner, to allow the assessment of whether there were major problems with the ecosystem model or with the assimilation procedure. The current ecosystem model performed well in some regions, but failed in others to assimilate chlorophyll estimates without disrupting important ecosystem properties. This experiment gave insight into those properties of the ecosystem model that must be changed to allow data assimilation to be generally successful, while raising other important issues about the assimilation procedure.

Unscented Kalman filter assimilation of time-lapse self-potential data for monitoring solute transport

Science.gov (United States)

Cui, Yi-an; Liu, Lanbo; Zhu, Xiaoxiong

2017-08-01

Monitoring the extent and evolution of contaminant plumes in local and regional groundwater systems from existing landfills is critical in contamination control and remediation. The self-potential survey is an efficient and economical nondestructive geophysical technique that can be used to investigate underground contaminant plumes. Based on the unscented transform, we have built a Kalman filtering cycle to conduct time-lapse data assimilation for monitoring the transport of solute based on the solute transport experiment using a bench-scale physical model. The data assimilation was formed by modeling the evolution based on the random walk model and observation correcting based on the self-potential forward. Thus, monitoring self-potential data can be inverted by the data assimilation technique. As a result, we can reconstruct the dynamic process of the contaminant plume instead of using traditional frame-to-frame static inversion, which may cause inversion artifacts. The data assimilation inversion algorithm was evaluated through noise-added synthetic time-lapse self-potential data. The result of the numerical experiment shows validity, accuracy and tolerance to the noise of the dynamic inversion. To validate the proposed algorithm, we conducted a scaled-down sandbox self-potential observation experiment to generate time-lapse data that closely mimics the real-world contaminant monitoring setup. The results of physical experiments support the idea that the data assimilation method is a potentially useful approach for characterizing the transport of contamination plumes using the unscented Kalman filter (UKF) data assimilation technique applied to field time-lapse self-potential data.

Time delayed Ensemble Nudging Method

Science.gov (United States)

An, Zhe; Abarbanel, Henry

Optimal nudging method based on time delayed embedding theory has shows potentials on analyzing and data assimilation in previous literatures. To extend the application and promote the practical implementation, new nudging assimilation method based on the time delayed embedding space is presented and the connection with other standard assimilation methods are studied. Results shows the incorporating information from the time series of data can reduce the sufficient observation needed to preserve the quality of numerical prediction, making it a potential alternative in the field of data assimilation of large geophysical models.

Data assimilation in the decision support system RODOS

DEFF Research Database (Denmark)

Rojas-Palma, C.; Madsen, H.; Gering, F.

2003-01-01

. The process of combining model predictions and observations, usually referred to as data assimilation, is described in this article within the framework of the real time on-line decision support system (RODOS) for off-site nuclear emergency management in Europe. Data assimilation capabilities, based on Kalman...

Perfectly Matched Layer for the Wave Equation Finite Difference Time Domain Method

Science.gov (United States)

Miyazaki, Yutaka; Tsuchiya, Takao

2012-07-01

The perfectly matched layer (PML) is introduced into the wave equation finite difference time domain (WE-FDTD) method. The WE-FDTD method is a finite difference method in which the wave equation is directly discretized on the basis of the central differences. The required memory of the WE-FDTD method is less than that of the standard FDTD method because no particle velocity is stored in the memory. In this study, the WE-FDTD method is first combined with the standard FDTD method. Then, Berenger's PML is combined with the WE-FDTD method. Some numerical demonstrations are given for the two- and three-dimensional sound fields.

Runge-Kutta Integration of the Equal Width Wave Equation Using the Method of Lines

Directory of Open Access Journals (Sweden)

M. A. Banaja

2015-01-01

Full Text Available The equal width (EW equation governs nonlinear wave phenomena like waves in shallow water. Numerical solution of the (EW equation is obtained by using the method of lines (MOL based on Runge-Kutta integration. Using von Neumann stability analysis, the scheme is found to be unconditionally stable. Solitary wave motion and interaction of two solitary waves are studied using the proposed method. The three invariants of the motion are evaluated to determine the conservation properties of the generated scheme. Accuracy of the proposed method is discussed by computing the L2 and L∞ error norms. The results are found in good agreement with exact solution.

Measuring longitudinal wave speed in solids: two methods and a half

International Nuclear Information System (INIS)

Fazio, C; Guastella, I; Sperandeo-Mineo, R M; Tarantino, G

2006-01-01

Three methods to analyse longitudinal wave propagation in metallic rods are discussed. Two of these methods also prove to be useful for measuring the sound propagation speed. The experimental results, as well as some interpretative models built in the context of a workshop on mechanical waves at the Graduate School for Pre-Service Physics Teacher Education, Palermo University, are described. Some considerations about observed modifications in trainee teachers' attitudes to utilizing physics experiments to build pedagogical activities are discussed

Assessment of the ocean circulation in the Azores region as predicted by a numerical model assimilating altimeter data from Topex/Poseidon and ERS-1 satellites

Directory of Open Access Journals (Sweden)

T. Mailly

1997-10-01

Full Text Available Two years of altimetric data from Topex/Poseidon (October 1992–September 1994 and ERS-1 (October 1992–December 1993 were assimilated into a numerical model of the North Atlantic. The results of these simulations are analysed in the Azores region to assess the performance of our model in this particular region. Maps of instantaneous dynamic topography and transports show that the model performs well in reproducing the velocities and transports of the Azores Front. Drifter data from the Semaphore experiment are also used to study the correlation between the drifter velocities and the corresponding model velocities. Some interesting oceanographic results are also obtained by examining the seasonal and interannual variability of the circulation and the influence of bathymetry on the variability of the Azores Front. Thus, on the basis of our two year experiment, it is possible to confirm the circulation patterns proposed by previous studies regarding the seasonal variations in the origin of the Azores Current. Moreover, it is shown that the Azores Current is quite narrow in the first year of assimilation (1992–1993, but becomes much wider in the second year (1993–1994. The role of the bathymetry appears important in this area since the mesoscale activity is shown to be strongly related to the presence of topographic slopes. Finally, spectral analyses of sea-level changes over time and space are used to identify two types of wave already noticed in other studies: a wave with (300 km–1 wave number and (120 days–1 frequency, which is characteristic of mesoscale undulation, and a wave with (600 km–1 wave number and (250 days–1 frequency which probably corresponds to a Rossby wave generated in the east of the basin.

Assessment of the ocean circulation in the Azores region as predicted by a numerical model assimilating altimeter data from Topex/Poseidon and ERS-1 satellites

Directory of Open Access Journals (Sweden)

T. Mailly

Full Text Available Two years of altimetric data from Topex/Poseidon (October 1992–September 1994 and ERS-1 (October 1992–December 1993 were assimilated into a numerical model of the North Atlantic. The results of these simulations are analysed in the Azores region to assess the performance of our model in this particular region. Maps of instantaneous dynamic topography and transports show that the model performs well in reproducing the velocities and transports of the Azores Front. Drifter data from the Semaphore experiment are also used to study the correlation between the drifter velocities and the corresponding model velocities. Some interesting oceanographic results are also obtained by examining the seasonal and interannual variability of the circulation and the influence of bathymetry on the variability of the Azores Front. Thus, on the basis of our two year experiment, it is possible to confirm the circulation patterns proposed by previous studies regarding the seasonal variations in the origin of the Azores Current. Moreover, it is shown that the Azores Current is quite narrow in the first year of assimilation (1992–1993, but becomes much wider in the second year (1993–1994. The role of the bathymetry appears important in this area since the mesoscale activity is shown to be strongly related to the presence of topographic slopes. Finally, spectral analyses of sea-level changes over time and space are used to identify two types of wave already noticed in other studies: a wave with (300 km^–1 wave number and (120 days^–1 frequency, which is characteristic of mesoscale undulation, and a wave with (600 km^–1 wave number and (250 days^–1 frequency which probably corresponds to a Rossby wave generated in the east of the basin.

Assessment of the ocean circulation in the Azores region as predicted by a numerical model assimilating altimeter data from Topex/Poseidon and ERS-1 satellites

Science.gov (United States)

Mailly, T.; Blayo, E.; Verron, J.

1997-10-01

Two years of altimetric data from Topex/Poseidon (October 1992-September 1994) and ERS-1 (October 1992-December 1993) were assimilated into a numerical model of the North Atlantic. The results of these simulations are analysed in the Azores region to assess the performance of our model in this particular region. Maps of instantaneous dynamic topography and transports show that the model performs well in reproducing the velocities and transports of the Azores Front. Drifter data from the Semaphore experiment are also used to study the correlation between the drifter velocities and the corresponding model velocities. Some interesting oceanographic results are also obtained by examining the seasonal and interannual variability of the circulation and the influence of bathymetry on the variability of the Azores Front. Thus, on the basis of our two year experiment, it is possible to confirm the circulation patterns proposed by previous studies regarding the seasonal variations in the origin of the Azores Current. Moreover, it is shown that the Azores Current is quite narrow in the first year of assimilation (1992-1993), but becomes much wider in the second year (1993-1994). The role of the bathymetry appears important in this area since the mesoscale activity is shown to be strongly related to the presence of topographic slopes. Finally, spectral analyses of sea-level changes over time and space are used to identify two types of wave already noticed in other studies: a wave with (300 km)-1 wave number and (120 days)-1 frequency, which is characteristic of mesoscale undulation, and a wave with (600 km)-1 wave number and (250 days)-1 frequency which probably corresponds to a Rossby wave generated in the east of the basin.

The importance of peers: assimilation patterns among second-generation Turkish immigrants in Western Europe

NARCIS (Netherlands)

Ali, S.; Fokkema, C.M.

2011-01-01

The two dominant approaches to immigrant assimilation, segmented assimilation and "new" assimilation theories, have been successful at reporting and analyzing between-group differences in assimilation patterns. However, studies of assimilation generally do not address differences at the individual

Health Assimilation among Hispanic Immigrants in the United States: The Impact of Ignoring Arrival-cohort Effects.

Science.gov (United States)

Hamilton, Tod G; Palermo, Tia; Green, Tiffany L

2015-12-01

A large literature has documented that Hispanic immigrants have a health advantage over their U.S.-born counterparts upon arrival in the United States. Few studies, however, have disentangled the effects of immigrants' arrival cohort from their tenure of U.S. residence, an omission that could produce imprecise estimates of the degree of health decline experienced by Hispanic immigrants as their U.S. tenure increases. Using data from the 1996-to-2014 waves of the March Current Population Survey, we show that the health (i.e., self-rated health) of Hispanic immigrants varies by both arrival cohort and U.S. tenure for immigrants hailing from most of the primary sending countries/regions of Hispanic immigrants. We also find evidence that acculturation plays an important role in determining the health trajectories of Hispanic immigrants. With respect to self-rated health, however, our findings demonstrate that omitting arrival-cohort measures from health assimilation models may result in overestimates of the degree of downward health assimilation experienced by Hispanic immigrants. © American Sociological Association 2015.

Piecewise parabolic method for simulating one-dimensional shear shock wave propagation in tissue-mimicking phantoms

Science.gov (United States)

Tripathi, B. B.; Espíndola, D.; Pinton, G. F.

2017-11-01

The recent discovery of shear shock wave generation and propagation in the porcine brain suggests that this new shock phenomenology may be responsible for a broad range of traumatic injuries. Blast-induced head movement can indirectly lead to shear wave generation in the brain, which could be a primary mechanism for injury. Shear shock waves amplify the local acceleration deep in the brain by up to a factor of 8.5, which may tear and damage neurons. Currently, there are numerical methods that can model compressional shock waves, such as comparatively well-studied blast waves, but there are no numerical full-wave solvers that can simulate nonlinear shear shock waves in soft solids. Unlike simplified representations, e.g., retarded time, full-wave representations describe fundamental physical behavior such as reflection and heterogeneities. Here we present a piecewise parabolic method-based solver for one-dimensional linearly polarized nonlinear shear wave in a homogeneous medium and with empirical frequency-dependent attenuation. This method has the advantage of being higher order and more directly extendable to multiple dimensions and heterogeneous media. The proposed numerical scheme is validated analytically and experimentally and compared to other shock capturing methods. A Riemann step-shock problem is used to characterize the numerical dissipation. This dissipation is then tuned to be negligible with respect to the physical attenuation by choosing an appropriate grid spacing. The numerical results are compared to ultrasound-based experiments that measure planar polarized shear shock wave propagation in a tissue-mimicking gelatin phantom. Good agreement is found between numerical results and experiment across a 40 mm propagation distance. We anticipate that the proposed method will be a starting point for the development of a two- and three-dimensional full-wave code for the propagation of nonlinear shear waves in heterogeneous media.

Ultrasound viscoelasticity assessment using an adaptive torsional shear wave propagation method

Energy Technology Data Exchange (ETDEWEB)

Ouared, Abderrahmane [Laboratory of Biorheology and Medical Ultrasonics, University of Montréal Hospital Research Center (CRCHUM), Montréal, Québec H2X 0A9, Canada and Institute of Biomedical Engineering, University of Montréal, Montréal, Québec H3T 1J4 (Canada); Kazemirad, Siavash; Montagnon, Emmanuel [Laboratory of Biorheology and Medical Ultrasonics, University of Montréal Hospital Research Center (CRCHUM), Montréal, Québec H2X 0A9 (Canada); Cloutier, Guy, E-mail: guy.cloutier@umontreal.ca [Laboratory of Biorheology and Medical Ultrasonics, University of Montréal Hospital Research Center (CRCHUM), Montréal, Québec H2X 0A9 (Canada); Department of Radiology, Radio-Oncology and Nuclear Medicine, University of Montréal, Montréal, Québec H3T 1J4 (Canada); Institute of Biomedical Engineering, University of Montréal, Montréal, Québec H3T 1J4 (Canada)

2016-04-15

Purpose: Different approaches have been used in dynamic elastography to assess mechanical properties of biological tissues. Most techniques are based on a simple inversion based on the measurement of the shear wave speed to assess elasticity, whereas some recent strategies use more elaborated analytical or finite element method (FEM) models. In this study, a new method is proposed for the quantification of both shear storage and loss moduli of confined lesions, in the context of breast imaging, using adaptive torsional shear waves (ATSWs) generated remotely with radiation pressure. Methods: A FEM model was developed to solve the inverse wave propagation problem and obtain viscoelastic properties of interrogated media. The inverse problem was formulated and solved in the frequency domain and its robustness to noise and geometric constraints was evaluated. The proposed model was validated in vitro with two independent rheology methods on several homogeneous and heterogeneous breast tissue-mimicking phantoms over a broad range of frequencies (up to 400 Hz). Results: Viscoelastic properties matched benchmark rheology methods with discrepancies of 8%–38% for the shear modulus G′ and 9%–67% for the loss modulus G″. The robustness study indicated good estimations of storage and loss moduli (maximum mean errors of 19% on G′ and 32% on G″) for signal-to-noise ratios between 19.5 and 8.5 dB. Larger errors were noticed in the case of biases in lesion dimension and position. Conclusions: The ATSW method revealed that it is possible to estimate the viscoelasticity of biological tissues with torsional shear waves when small biases in lesion geometry exist.

Assimilation of NUCAPS Retrieved Profiles in GSI for Unique Forecasting Applications

Science.gov (United States)

Berndt, Emily Beth; Zavodsky, Bradley; Srikishen, Jayanthi; Blankenship, Clay

2015-01-01

Hyperspectral IR profiles can be assimilated in GSI as a separate observation other than radiosondes with only changes to tables in the fix directory. Assimilation of profiles does produce changes to analysis fields and evidenced by: Innovations larger than +/-2.0 K are present and represent where individual profiles impact the final temperature analysis.The updated temperature analysis is colder behind the cold front and warmer in the warm sector. The updated moisture analysis is modified more in the low levels and tends to be drier than the original model background Analysis of model output shows: Differences relative to 13-km RAP analyses are smaller when profiles are assimilated with NUCAPS errors. CAPE is under-forecasted when assimilating NUCAPS profiles, which could be problematic for severe weather forecasting Refining the assimilation technique to incorporate an error covariance matrix and creating a separate GSI module to assimilate satellite profiles may improve results.

DATA ASSIMILATION APPROACH FOR FORECAST OF SOLAR ACTIVITY CYCLES

Energy Technology Data Exchange (ETDEWEB)

Kitiashvili, Irina N., E-mail: irina.n.kitiashvili@nasa.gov [NASA Ames Research Center, Moffett Field, Mountain View, CA 94035 (United States)

2016-11-01

Numerous attempts to predict future solar cycles are mostly based on empirical relations derived from observations of previous cycles, and they yield a wide range of predicted strengths and durations of the cycles. Results obtained with current dynamo models also deviate strongly from each other, thus raising questions about criteria to quantify the reliability of such predictions. The primary difficulties in modeling future solar activity are shortcomings of both the dynamo models and observations that do not allow us to determine the current and past states of the global solar magnetic structure and its dynamics. Data assimilation is a relatively new approach to develop physics-based predictions and estimate their uncertainties in situations where the physical properties of a system are not well-known. This paper presents an application of the ensemble Kalman filter method for modeling and prediction of solar cycles through use of a low-order nonlinear dynamo model that includes the essential physics and can describe general properties of the sunspot cycles. Despite the simplicity of this model, the data assimilation approach provides reasonable estimates for the strengths of future solar cycles. In particular, the prediction of Cycle 24 calculated and published in 2008 is so far holding up quite well. In this paper, I will present my first attempt to predict Cycle 25 using the data assimilation approach, and discuss the uncertainties of that prediction.

Study of Lamb Waves for Non-Destructive Testing Behind Screens

Science.gov (United States)

Kauffmann, P.; Ploix, M.-A.; Chaix, J.-F.; Gueudré, C.; Corneloup, G.; Baqué, F. AF(; )

2018-01-01

The inspection and control of sodium-cooled fast reactors (SFR) is a major issue for the nuclear industry. Ultrasonic solutions are under study because of the opacity of liquid sodium. In this paper, the use of leaky Lamb waves is considered for non-destructive testing (NDT) on parallel and immersed structures assimilated as plates. The first phase of our approach involved studying the propagation properties of leaky Lamb waves. Equations that model the propagation of Lamb waves in an immersed plate were solved numerically. The phase velocity can be experimentally measured using a two dimensional Fourier transform. The group velocity can be experimentally measured using a short-time Fourier transform technique. Attenuation of leaky Lamb waves is mostly due to the re-emission of energy into the surrounding fluid, and it can be measured by these two techniques.

A parallel orbital-updating based plane-wave basis method for electronic structure calculations

International Nuclear Information System (INIS)

Pan, Yan; Dai, Xiaoying; Gironcoli, Stefano de; Gong, Xin-Gao; Rignanese, Gian-Marco; Zhou, Aihui

2017-01-01

Highlights: • Propose three parallel orbital-updating based plane-wave basis methods for electronic structure calculations. • These new methods can avoid the generating of large scale eigenvalue problems and then reduce the computational cost. • These new methods allow for two-level parallelization which is particularly interesting for large scale parallelization. • Numerical experiments show that these new methods are reliable and efficient for large scale calculations on modern supercomputers. - Abstract: Motivated by the recently proposed parallel orbital-updating approach in real space method , we propose a parallel orbital-updating based plane-wave basis method for electronic structure calculations, for solving the corresponding eigenvalue problems. In addition, we propose two new modified parallel orbital-updating methods. Compared to the traditional plane-wave methods, our methods allow for two-level parallelization, which is particularly interesting for large scale parallelization. Numerical experiments show that these new methods are more reliable and efficient for large scale calculations on modern supercomputers.

Impact of real-time measurements for data assimilation in reservoir simulation

Energy Technology Data Exchange (ETDEWEB)

Schulze-Riegert, R; Krosche, M [Scandpower Petroleum Technology GmbH, Hamburg (Germany); Pajonk, O [TU Braunschweig (Germany). Inst. fuer Wissenschaftliches Rechnen; Myrland, T [Morges Teknisk-Naturvitenskapelige Univ. (NTNU), Trondheim (Germany)

2008-10-23

This paper gives an overview on the conceptual background of data assimilation techniques. The framework of sequential data assimilation as described for the ensemble Kalman filter implementation allows a continuous integration of new measurement data. The initial diversity of ensemble members will be critical for the assimilation process and the ability to successfully assimilate measurement data. At the same time the initial ensemble will impact the propagation of uncertainties with crucial consequences for production forecasts. Data assimilation techniques have complimentary features compared to other optimization techniques built on selection or regression schemes. Specifically, EnKF is applicable to real field cases and defines an important perspective for facilitating continuous reservoir simulation model updates in a reservoir life cycle. (orig.)

A study on reducing update frequency of the forecast samples in the ensemble-based 4DVar data assimilation method

Energy Technology Data Exchange (ETDEWEB)

Shao, Aimei; Xu, Daosheng [Lanzhou Univ. (China). Key Lab. of Arid Climatic Changing and Reducing Disaster of Gansu Province; Chinese Academy of Meteorological Sciences, Beijing (China). State Key Lab. of Severe Weather; Qiu, Xiaobin [Lanzhou Univ. (China). Key Lab. of Arid Climatic Changing and Reducing Disaster of Gansu Province; Tianjin Institute of Meteorological Science (China); Qiu, Chongjian [Lanzhou Univ. (China). Key Lab. of Arid Climatic Changing and Reducing Disaster of Gansu Province

2013-02-15

In the ensemble-based four dimensional variational assimilation method (SVD-En4DVar), a singular value decomposition (SVD) technique is used to select the leading eigenvectors and the analysis variables are expressed as the orthogonal bases expansion of the eigenvectors. The experiments with a two-dimensional shallow-water equation model and simulated observations show that the truncation error and rejection of observed signals due to the reduced-dimensional reconstruction of the analysis variable are the major factors that damage the analysis when the ensemble size is not large enough. However, a larger-sized ensemble is daunting computational burden. Experiments with a shallow-water equation model also show that the forecast error covariances remain relatively constant over time. For that reason, we propose an approach that increases the members of the forecast ensemble while reducing the update frequency of the forecast error covariance in order to increase analysis accuracy and to reduce the computational cost. A series of experiments were conducted with the shallow-water equation model to test the efficiency of this approach. The experimental results indicate that this approach is promising. Further experiments with the WRF model show that this approach is also suitable for the real atmospheric data assimilation problem, but the update frequency of the forecast error covariances should not be too low. (orig.)

A simplified method of evaluating the stress wave environment of internal equipment

Science.gov (United States)

Colton, J. D.; Desmond, T. P.

1979-01-01

A simplified method called the transfer function technique (TFT) was devised for evaluating the stress wave environment in a structure containing internal equipment. The TFT consists of following the initial in-plane stress wave that propagates through a structure subjected to a dynamic load and characterizing how the wave is altered as it is transmitted through intersections of structural members. As a basis for evaluating the TFT, impact experiments and detailed stress wave analyses were performed for structures with two or three, or more members. Transfer functions that relate the wave transmitted through an intersection to the incident wave were deduced from the predicted wave response. By sequentially applying these transfer functions to a structure with several intersections, it was found that the environment produced by the initial stress wave propagating through the structure can be approximated well. The TFT can be used as a design tool or as an analytical tool to determine whether a more detailed wave analysis is warranted.

Mesospheric Precursors to the Major Stratospheric Sudden Warming of 2009: Validation and Dynamical Attribution using a Ground-to-Edge-of-Space Data Assimilation System

Science.gov (United States)

2011-01-01

et al., 2008). Since wind observations are sparse and standard data assimilation systems ( DASs ) do not extend through the mesosphere, we have far...et al., 2008). Figure 1f plots a time-height cross section of wave- 2 F z at 60◦N, scaled by exp(z/2H), where z is pres- sure altitude and H =7 km. As

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

Biomass burning source characterization requirements in air quality models with and without data assimilation: challenges and opportunities

Science.gov (United States)

Hyer, E. J.; Zhang, J. L.; Reid, J. S.; Curtis, C. A.; Westphal, D. L.

2007-12-01

Quantitative models of the transport and evolution of atmospheric pollution have graduated from the laboratory to become a part of the operational activity of forecast centers. Scientists studying the composition and variability of the atmosphere put great efforts into developing methods for accurately specifying sources of pollution, including natural and anthropogenic biomass burning. These methods must be adapted for use in operational contexts, which impose additional strictures on input data and methods. First, only input data sources available in near real-time are suitable for use in operational applications. Second, operational applications must make use of redundant data sources whenever possible. This is a shift in philosophy: in a research context, the most accurate and complete data set will be used, whereas in an operational context, the system must be designed with maximum redundancy. The goal in an operational context is to produce, to the extent possible, consistent and timely output, given sometimes inconsistent inputs. The Naval Aerosol Analysis and Prediction System (NAAPS), a global operational aerosol analysis and forecast system, recently began incorporating assimilation of satellite-derived aerosol optical depth. Assimilation of satellite AOD retrievals has dramatically improved aerosol analyses and forecasts from this system. The use of aerosol data assimilation also changes the strategy for improving the smoke source function. The absolute magnitude of emissions events can be refined through feedback from the data assimilation system, both in real- time operations and in post-processing analysis of data assimilation results. In terms of the aerosol source functions, the largest gains in model performance are now to be gained by reducing data latency and minimizing missed detections. In this presentation, recent model development work on the Fire Locating and Monitoring of Burning Emissions (FLAMBE) system that provides smoke aerosol

Continuous dynamic assimilation of the inner region data in hydrodynamics modelling: optimization approach

Directory of Open Access Journals (Sweden)

F. I. Pisnitchenko

2008-11-01

Full Text Available In meteorological and oceanological studies the classical approach for finding the numerical solution of the regional model consists in formulating and solving a Cauchy-Dirichlet problem. The boundary conditions are obtained by linear interpolation of coarse-grid data provided by a global model. Errors in boundary conditions due to interpolation may cause large deviations from the correct regional solution. The methods developed to reduce these errors deal with continuous dynamic assimilation of known global data available inside the regional domain. One of the approaches of this assimilation procedure performs a nudging of large-scale components of regional model solution to large-scale global data components by introducing relaxation forcing terms into the regional model equations. As a result, the obtained solution is not a valid numerical solution to the original regional model. Another approach is the use a four-dimensional variational data assimilation procedure which is free from the above-mentioned shortcoming. In this work we formulate the joint problem of finding the regional model solution and data assimilation as a PDE-constrained optimization problem. Three simple model examples (ODE Burgers equation, Rossby-Oboukhov equation, Korteweg-de Vries equation are considered in this paper. Numerical experiments indicate that the optimization approach can significantly improve the precision of the regional solution.

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.

Potential of an ensemble Kalman smoother for stratospheric chemical-dynamical data assimilation

Directory of Open Access Journals (Sweden)

Thomas Milewski

2013-02-01

Full Text Available A new stratospheric ensemble Kalman smoother (EnKS system is introduced, and the potential of assimilating posterior stratospheric observations to better constrain the whole model state at analysis time is investigated. A set of idealised perfect-model Observation System Simulation Experiments (OSSE assimilating synthetic limb-sounding temperature or ozone retrievals are performed with a chemistry–climate model. The impact during the analysis step is characterised in terms of the root mean square error reduction between the forecast state and the analysis state. The performances of (1 a fixed-lag EnKS assimilating observations spread over 48 hours and (2 an ensemble Kalman Filter (EnKF assimilating a denser network of observations are compared with a reference EnKF. The ozone assimilation with EnKS shows a significant additional reduction of analysis error of the order of 10% for dynamical and chemical variables in the extratropical upper troposphere lower stratosphere (UTLS and Polar Vortex regions when compared to the reference EnKF. This reduction has similar magnitude to the one achieved by the denser-network EnKF assimilation. Similarly, the temperature assimilation with EnKS significantly decreases the error in the UTLS for the wind variables like the denser-network EnKF assimilation. However, the temperature assimilation with EnKS has little or no significant impact on the temperature and ozone analyses, whereas the denser-network EnKF shows improvement with respect to the reference EnKF. The different analysis impacts from the assimilation of current and posterior ozone observations indicate the capacity of time-lagged background-error covariances to represent temporal interactions up to 48 hours between variables during the ensemble data assimilation analysis step, and the possibility to use posterior observations whenever additional current observations are unavailable. The possible application of the EnKS for reanalyses is

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.

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.

The Goddard Snow Radiance Assimilation Project: An Integrated Snow Radiance and Snow Physics Modeling Framework for Snow/cold Land Surface Modeling

Science.gov (United States)

Kim, E.; Tedesco, M.; Reichle, R.; Choudhury, B.; Peters-Lidard C.; Foster, J.; Hall, D.; Riggs, G.

2006-01-01

Microwave-based retrievals of snow parameters from satellite observations have a long heritage and have so far been generated primarily by regression-based empirical "inversion" methods based on snapshots in time. Direct assimilation of microwave radiance into physical land surface models can be used to avoid errors associated with such retrieval/inversion methods, instead utilizing more straightforward forward models and temporal information. This approach has been used for years for atmospheric parameters by the operational weather forecasting community with great success. Recent developments in forward radiative transfer modeling, physical land surface modeling, and land data assimilation are converging to allow the assembly of an integrated framework for snow/cold lands modeling and radiance assimilation. The objective of the Goddard snow radiance assimilation project is to develop such a framework and explore its capabilities. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. In fact, multiple models are available for each element enabling optimization to match the needs of a particular study. Together these form a modular and flexible framework for self-consistent, physically-based remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster. Capabilities for assimilation of snow retrieval products are already under development for LIS. We will describe plans to add radiance-based assimilation capabilities. Plans for validation activities using field measurements will also be discussed.

A high-order multiscale finite-element method for time-domain acoustic-wave modeling

Science.gov (United States)

Gao, Kai; Fu, Shubin; Chung, Eric T.

2018-05-01

Accurate and efficient wave equation modeling is vital for many applications in such as acoustics, electromagnetics, and seismology. However, solving the wave equation in large-scale and highly heterogeneous models is usually computationally expensive because the computational cost is directly proportional to the number of grids in the model. We develop a novel high-order multiscale finite-element method to reduce the computational cost of time-domain acoustic-wave equation numerical modeling by solving the wave equation on a coarse mesh based on the multiscale finite-element theory. In contrast to existing multiscale finite-element methods that use only first-order multiscale basis functions, our new method constructs high-order multiscale basis functions from local elliptic problems which are closely related to the Gauss-Lobatto-Legendre quadrature points in a coarse element. Essentially, these basis functions are not only determined by the order of Legendre polynomials, but also by local medium properties, and therefore can effectively convey the fine-scale information to the coarse-scale solution with high-order accuracy. Numerical tests show that our method can significantly reduce the computation time while maintain high accuracy for wave equation modeling in highly heterogeneous media by solving the corresponding discrete system only on the coarse mesh with the new high-order multiscale basis functions.

An Analytical Method of Auxiliary Sources Solution for Plane Wave Scattering by Impedance Cylinders

DEFF Research Database (Denmark)

Larsen, Niels Vesterdal; Breinbjerg, Olav

2004-01-01

Analytical Method of Auxiliary Sources solutions for plane wave scattering by circular impedance cylinders are derived by transformation of the exact eigenfunction series solutions employing the Hankel function wave transformation. The analytical Method of Auxiliary Sources solution thus obtained...

Modelling viscoacoustic wave propagation with the lattice Boltzmann method.

Science.gov (United States)

Xia, Muming; Wang, Shucheng; Zhou, Hui; Shan, Xiaowen; Chen, Hanming; Li, Qingqing; Zhang, Qingchen

2017-08-31

In this paper, the lattice Boltzmann method (LBM) is employed to simulate wave propagation in viscous media. LBM is a kind of microscopic method for modelling waves through tracking the evolution states of a large number of discrete particles. By choosing different relaxation times in LBM experiments and using spectrum ratio method, we can reveal the relationship between the quality factor Q and the parameter τ in LBM. A two-dimensional (2D) homogeneous model and a two-layered model are tested in the numerical experiments, and the LBM results are compared against the reference solution of the viscoacoustic equations based on the Kelvin-Voigt model calculated by finite difference method (FDM). The wavefields and amplitude spectra obtained by LBM coincide with those by FDM, which demonstrates the capability of the LBM with one relaxation time. The new scheme is relatively simple and efficient to implement compared with the traditional lattice methods. In addition, through a mass of experiments, we find that the relaxation time of LBM has a quantitative relationship with Q. Such a novel scheme offers an alternative forward modelling kernel for seismic inversion and a new model to describe the underground media.

A global carbon assimilation system based on a dual optimization method

Science.gov (United States)

Zheng, H.; Li, Y.; Chen, J. M.; Wang, T.; Huang, Q.; Huang, W. X.; Wang, L. H.; Li, S. M.; Yuan, W. P.; Zheng, X.; Zhang, S. P.; Chen, Z. Q.; Jiang, F.

2015-02-01

Ecological models are effective tools for simulating the distribution of global carbon sources and sinks. However, these models often suffer from substantial biases due to inaccurate simulations of complex ecological processes. We introduce a set of scaling factors (parameters) to an ecological model on the basis of plant functional type (PFT) and latitudes. A global carbon assimilation system (GCAS-DOM) is developed by employing a dual optimization method (DOM) to invert the time-dependent ecological model parameter state and the net carbon flux state simultaneously. We use GCAS-DOM to estimate the global distribution of the CO2 flux on 1° × 1° grid cells for the period from 2001 to 2007. Results show that land and ocean absorb -3.63 ± 0.50 and -1.82 ± 0.16 Pg C yr-1, respectively. North America, Europe and China contribute -0.98 ± 0.15, -0.42 ± 0.08 and -0.20 ± 0.29 Pg C yr-1, respectively. The uncertainties in the flux after optimization by GCAS-DOM have been remarkably reduced by more than 60%. Through parameter optimization, GCAS-DOM can provide improved estimates of the carbon flux for each PFT. Coniferous forest (-0.97 ± 0.27 Pg C yr-1) is the largest contributor to the global carbon sink. Fluxes of once-dominant deciduous forest generated by the Boreal Ecosystems Productivity Simulator (BEPS) are reduced to -0.78 ± 0.23 Pg C yr-1, the third largest carbon sink.

An Optimal Control Method for Maximizing the Efficiency of Direct Drive Ocean Wave Energy Extraction System

Science.gov (United States)

Chen, Zhongxian; Yu, Haitao; Wen, Cheng

2014-01-01

The goal of direct drive ocean wave energy extraction system is to convert ocean wave energy into electricity. The problem explored in this paper is the design and optimal control for the direct drive ocean wave energy extraction system. An optimal control method based on internal model proportion integration differentiation (IM-PID) is proposed in this paper though most of ocean wave energy extraction systems are optimized by the structure, weight, and material. With this control method, the heavy speed of outer heavy buoy of the energy extraction system is in resonance with incident wave, and the system efficiency is largely improved. Validity of the proposed optimal control method is verified in both regular and irregular ocean waves, and it is shown that IM-PID control method is optimal in that it maximizes the energy conversion efficiency. In addition, the anti-interference ability of IM-PID control method has been assessed, and the results show that the IM-PID control method has good robustness, high precision, and strong anti-interference ability. PMID:25152913

An optimal control method for maximizing the efficiency of direct drive ocean wave energy extraction system.

Science.gov (United States)

Chen, Zhongxian; Yu, Haitao; Wen, Cheng

2014-01-01

The goal of direct drive ocean wave energy extraction system is to convert ocean wave energy into electricity. The problem explored in this paper is the design and optimal control for the direct drive ocean wave energy extraction system. An optimal control method based on internal model proportion integration differentiation (IM-PID) is proposed in this paper though most of ocean wave energy extraction systems are optimized by the structure, weight, and material. With this control method, the heavy speed of outer heavy buoy of the energy extraction system is in resonance with incident wave, and the system efficiency is largely improved. Validity of the proposed optimal control method is verified in both regular and irregular ocean waves, and it is shown that IM-PID control method is optimal in that it maximizes the energy conversion efficiency. In addition, the anti-interference ability of IM-PID control method has been assessed, and the results show that the IM-PID control method has good robustness, high precision, and strong anti-interference ability.

Integral Equation Methods for Electromagnetic and Elastic Waves

CERN Document Server

Chew, Weng; Hu, Bin

2008-01-01

Integral Equation Methods for Electromagnetic and Elastic Waves is an outgrowth of several years of work. There have been no recent books on integral equation methods. There are books written on integral equations, but either they have been around for a while, or they were written by mathematicians. Much of the knowledge in integral equation methods still resides in journal papers. With this book, important relevant knowledge for integral equations are consolidated in one place and researchers need only read the pertinent chapters in this book to gain important knowledge needed for integral eq

Comparison of Transmission Line Methods for Surface Acoustic Wave Modeling

Science.gov (United States)

Wilson, William; Atkinson, Gary

2009-01-01

Surface Acoustic Wave (SAW) technology is low cost, rugged, lightweight, extremely low power and can be used to develop passive wireless sensors. For these reasons, NASA is investigating the use of SAW technology for Integrated Vehicle Health Monitoring (IVHM) of aerospace structures. To facilitate rapid prototyping of passive SAW sensors for aerospace applications, SAW models have been developed. This paper reports on the comparison of three methods of modeling SAWs. The three models are the Impulse Response Method (a first order model), and two second order matrix methods; the conventional matrix approach, and a modified matrix approach that is extended to include internal finger reflections. The second order models are based upon matrices that were originally developed for analyzing microwave circuits using transmission line theory. Results from the models are presented with measured data from devices. Keywords: Surface Acoustic Wave, SAW, transmission line models, Impulse Response Method.

Displacement data assimilation

Energy Technology Data Exchange (ETDEWEB)

Rosenthal, W. Steven [Pacific Northwest Laboratory, Richland, WA 99354 (United States); Venkataramani, Shankar [Department of Mathematics and Program in Applied Mathematics, University of Arizona, Tucson, AZ 85721 (United States); Mariano, Arthur J. [Rosenstiel School of Marine & Atmospheric Science, University of Miami, Miami, FL 33149 (United States); Restrepo, Juan M., E-mail: restrepo@math.oregonstate.edu [Department of Mathematics, Oregon State University, Corvallis, OR 97331 (United States)

2017-02-01

We show that modifying a Bayesian data assimilation scheme by incorporating kinematically-consistent displacement corrections produces a scheme that is demonstrably better at estimating partially observed state vectors in a setting where feature information is important. While the displacement transformation is generic, here we implement it within an ensemble Kalman Filter framework and demonstrate its effectiveness in tracking stochastically perturbed vortices.

Incorporating Parallel Computing into the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

Science.gov (United States)

Larson, Jay W.

1998-01-01

Atmospheric data assimilation is a method of combining actual observations with model forecasts to produce a more accurate description of the earth system than the observations or forecast alone can provide. The output of data assimilation, sometimes called the analysis, are regular, gridded datasets of observed and unobserved variables. Analysis plays a key role in numerical weather prediction and is becoming increasingly important for climate research. These applications, and the need for timely validation of scientific enhancements to the data assimilation system pose computational demands that are best met by distributed parallel software. The mission of the NASA Data Assimilation Office (DAO) is to provide datasets for climate research and to support NASA satellite and aircraft missions. The system used to create these datasets is the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The core components of the the GEOS DAS are: the GEOS General Circulation Model (GCM), the Physical-space Statistical Analysis System (PSAS), the Observer, the on-line Quality Control (QC) system, the Coupler (which feeds analysis increments back to the GCM), and an I/O package for processing the large amounts of data the system produces (which will be described in another presentation in this session). The discussion will center on the following issues: the computational complexity for the whole GEOS DAS, assessment of the performance of the individual elements of GEOS DAS, and parallelization strategy for some of the components of the system.

Air Quality Modeling Using the NASA GEOS-5 Multispecies Data Assimilation System

Science.gov (United States)

Keller, Christoph A.; Pawson, Steven; Wargan, Krzysztof; Weir, Brad

2018-01-01

The NASA Goddard Earth Observing System (GEOS) data assimilation system (DAS) has been expanded to include chemically reactive tropospheric trace gases including ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). This system combines model analyses from the GEOS-5 model with detailed atmospheric chemistry and observations from MLS (O3), OMI (O3 and NO2), and MOPITT (CO). We show results from a variety of assimilation test experiments, highlighting the improvements in the representation of model species concentrations by up to 50% compared to an assimilation-free control experiment. Taking into account the rapid chemical cycling of NO2 when applying the assimilation increments greatly improves assimilation skills for NO2 and provides large benefits for model concentrations near the surface. Analysis of the geospatial distribution of the assimilation increments suggest that the free-running model overestimates biomass burning emissions but underestimates lightning NOx emissions by 5-20%. We discuss the capability of the chemical data assimilation system to improve atmospheric composition forecasts through improved initial value and boundary condition inputs, particularly during air pollution events. We find that the current assimilation system meaningfully improves short-term forecasts (1-3 day). For longer-term forecasts more emphasis on updating the emissions instead of initial concentration fields is needed.

An Initial Assessment of the Impact of CYGNSS Ocean Surface Wind Assimilation on Navy Global and Mesoscale Numerical Weather Prediction

Science.gov (United States)

Baker, N. L.; Tsu, J.; Swadley, S. D.

2017-12-01

We assess the impact of assimilation of CYclone Global Navigation Satellite System (CYGNSS) ocean surface winds observations into the NAVGEM[i] global and COAMPS®[ii] mesoscale numerical weather prediction (NWP) systems. Both NAVGEM and COAMPS® used the NRL 4DVar assimilation system NAVDAS-AR[iii]. Long term monitoring of the NAVGEM Forecast Sensitivity Observation Impact (FSOI) indicates that the forecast error reduction for ocean surface wind vectors (ASCAT and WindSat) are significantly larger than for SSMIS wind speed observations. These differences are larger than can be explained by simply two pieces of information (for wind vectors) versus one (wind speed). To help understand these results, we conducted a series of Observing System Experiments (OSEs) to compare the assimilation of ASCAT wind vectors with the equivalent (computed) ASCAT wind speed observations. We found that wind vector assimilation was typically 3 times more effective at reducing the NAVGEM forecast error, with a higher percentage of beneficial observations. These results suggested that 4DVar, in the absence of an additional nonlinear outer loop, has limited ability to modify the analysis wind direction. We examined several strategies for assimilating CYGNSS ocean surface wind speed observations. In the first approach, we assimilated CYGNSS as wind speed observations, following the same methodology used for SSMIS winds. The next two approaches converted CYGNSS wind speed to wind vectors, using NAVGEM sea level pressure fields (following Holton, 1979), and using NAVGEM 10-m wind fields with the AER Variational Analysis Method. Finally, we compared these methods to CYGNSS wind speed assimilation using multiple outer loops with NAVGEM Hybrid 4DVar. Results support the earlier studies suggesting that NAVDAS-AR wind speed assimilation is sub-optimal. We present detailed results from multi-month NAVGEM assimilation runs along with case studies using COAMPS®. Comparisons include the fit of

A ''quadratized'' augmented plane wave method

International Nuclear Information System (INIS)

Smrcka, L.

1982-02-01

The exact radial solution inside the muffin-tin sphere is replaced by its Taylor expansion with respect to the energy, truncated after the quadratic term. Making use of it the energy independent augmented plane waves are formed which lead to the secular equations linear in energy. The method resembles the currently used linearized APW method but yields higher accuracy. The analysis of solution inside one muffin-tin sphere shows that the eigenvalue error is proportional to (E-E 0 ) 6 as compared with (E-E 0 ) 4 for LAPW. The error of eigenfunctions is (E-E 0 ) 3 ((E-E 0 ) 2 for LAPW). These conclusions are confirmed by direct numerical calculation of band structure of Cu and Al. (author)

Assimilate unloading from maize (Zea mays L.) pedicel tissues

International Nuclear Information System (INIS)

Porter, G.A.; Knievel, D.P.; Shannon, J.C.

1987-01-01

Sugar and 14 C-assimilate release from the pedicel tissue of attached maize (Zea mays L.) kernels was studied following treatment with solute concentrations of up to 800 millimolal. Exposure and collection times ranged from 3 to 6 hours. Sugar and 14 C-assimilate unloading and collection in agar traps was reduced by 25 and 43%, respectively, following exposure to 800 millimolal mannitol. Inhibition of unloading was not specific to mannitol, since similar concentrations of glucose, fructose, or equimolar glucose plus fructose resulted in comparable inhibition. Ethylene glycol, a rapidly permeating solute which should not greatly influence cell turgor, did not inhibit 14 C-assimilate unloading. Based on these results, they suggest that inhibition of unloading by high concentrations of sugar or mannitol was due to reduced pedicel cell turgor. Changes in pedicel cell turgor may play a role in the regulation of assimilate transfer within the maize kernel

Investigation of dispersion-relation-preserving scheme and spectral analysis methods for acoustic waves

Science.gov (United States)

Vanel, Florence O.; Baysal, Oktay

1995-01-01

Important characteristics of the aeroacoustic wave propagation are mostly encoded in their dispersion relations. Hence, a computational aeroacoustic (CAA) algorithm, which reasonably preserves these relations, was investigated. It was derived using an optimization procedure to ensure, that the numerical derivatives preserved the wave number and angular frequency of the differential terms in the linearized, 2-D Euler equations. Then, simulations were performed to validate the scheme and a compatible set of discretized boundary conditions. The computational results were found to agree favorably with the exact solutions. The boundary conditions were transparent to the outgoing waves, except when the disturbance source was close to a boundary. The time-domain data generated by such CAA solutions were often intractable until their spectra was analyzed. Therefore, the relative merits of three different methods were included in the study. For simple, periodic waves, the periodogram method produced better estimates of the steep-sloped spectra than the Blackman-Tukey method. Also, for this problem, the Hanning window was more effective when used with the weighted-overlapped-segment-averaging and Blackman-Tukey methods gave better results than the periodogram method. Finally, it was demonstrated that the representation of time domain-data was significantly dependent on the particular spectral analysis method employed.

NUMERICAL METHODS FOR SOLVING THE MULTI-TERM TIME-FRACTIONAL WAVE-DIFFUSION EQUATION

OpenAIRE

Liu, F.; Meerschaert, M.M.; McGough, R.J.; Zhuang, P.; Liu, Q.

2013-01-01

In this paper, the multi-term time-fractional wave-diffusion equations are considered. The multi-term time fractional derivatives are defined in the Caputo sense, whose orders belong to the intervals [0,1], [1,2), [0,2), [0,3), [2,3) and [2,4), respectively. Some computationally effective numerical methods are proposed for simulating the multi-term time-fractional wave-diffusion equations. The numerical results demonstrate the effectiveness of theoretical analysis. These methods and technique...

Delineating Facies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics with Level Set Transformation.

Energy Technology Data Exchange (ETDEWEB)

Hammond, Glenn Edward; Song, Xuehang; Ye, Ming; Dai, Zhenxue; Zachara, John; Chen, Xingyuan

2017-03-01

A new approach is developed to delineate the spatial distribution of discrete facies (geological units that have unique distributions of hydraulic, physical, and/or chemical properties) conditioned not only on direct data (measurements directly related to facies properties, e.g., grain size distribution obtained from borehole samples) but also on indirect data (observations indirectly related to facies distribution, e.g., hydraulic head and tracer concentration). Our method integrates for the first time ensemble data assimilation with traditional transition probability-based geostatistics. The concept of level set is introduced to build shape parameterization that allows transformation between discrete facies indicators and continuous random variables. The spatial structure of different facies is simulated by indicator models using conditioning points selected adaptively during the iterative process of data assimilation. To evaluate the new method, a two-dimensional semi-synthetic example is designed to estimate the spatial distribution and permeability of two distinct facies from transient head data induced by pumping tests. The example demonstrates that our new method adequately captures the spatial pattern of facies distribution by imposing spatial continuity through conditioning points. The new method also reproduces the overall response in hydraulic head field with better accuracy compared to data assimilation with no constraints on spatial continuity on facies.

Development of an Evapotranspiration Data Assimilation Technique for Streamflow Estimates: A Case Study in a Semi-Arid Region

Directory of Open Access Journals (Sweden)

Ying Zhang

2017-09-01

Full Text Available Streamflow estimates are substantially important as fresh water shortages increase in arid and semi-arid regions where evapotranspiration (ET is a significant contribution to the water balance. In this regard, evapotranspiration data can be assimilated into a distributed hydrological model (SWAT, Soil and Water Assessment Tool for improving streamflow estimates. The SWAT model has been widely used for streamflow estimations, but the applications combining SWAT and ET products were rare. Thus, this study aims to develop a SWAT-based evapotranspiration data assimilation system. In particular, SWAT is gridded at Hydrologic Response Unit (HRU level to incorporate gridded ET products acquired from the remote sensing-based ETMonitor model. In the modeling case, Gridded SWAT (GSWAT shows a good agreement of streamflow modeling with the original SWAT. Such a scant margin between them is due to the modeling domain mismatch caused by different HRU delineations. In the ET assimilation case, we carry out a synthetic data experiment to illustrate the state augmentation Direct Insertion (DI method and a real data experiment for the upper Heihe River Basin. The results demonstrate the benefits of the ET assimilation for improving hydrologic processes representations. In the future, more remotely sensed data can be assimilated into the data assimilation system to provide more reliable hydrological predictions.

Elastic wave scattering methods: assessments and suggestions

International Nuclear Information System (INIS)

Gubernatis, J.E.

1985-01-01

The author was asked by the meeting organizers to review and assess the developments over the past ten or so years in elastic wave scattering methods and to suggest areas of future research opportunities. He highlights the developments, focusing on what he feels were distinct steps forward in our theoretical understanding of how elastic waves interact with flaws. For references and illustrative figures, he decided to use as his principal source the proceedings of the various annual Reviews of Progress in Quantitative Nondestructive Evaluation (NDE). These meetings have been the main forum not only for presenting results of theoretical research but also for demonstrating the relevance of the theoretical research for the design and interpretation of experiment. In his opinion a quantitative NDE is possible only if this relevance exists, and his major objective is to discuss and illustrate the degree to which relevance has developed

Numerical simulation methods for wave propagation through optical waveguides

International Nuclear Information System (INIS)

Sharma, A.

1993-01-01

The simulation of the field propagation through waveguides requires numerical solutions of the Helmholtz equation. For this purpose a method based on the principle of orthogonal collocation was recently developed. The method is also applicable to nonlinear pulse propagation through optical fibers. Some of the salient features of this method and its application to both linear and nonlinear wave propagation through optical waveguides are discussed in this report. 51 refs, 8 figs, 2 tabs

A study on assimilating potential vorticity data

Science.gov (United States)

Li, Yong; Ménard, Richard; Riishøjgaard, Lars Peter; Cohn, Stephen E.; Rood, Richard B.

1998-08-01

The correlation that exists between the potential vorticity (PV) field and the distribution of chemical tracers such as ozone suggests the possibility of using tracer observations as proxy PV data in atmospheric data assimilation systems. Especially in the stratosphere, there are plentiful tracer observations but a general lack of reliable wind observations, and the correlation is most pronounced. The issue investigated in this study is how model dynamics would respond to the assimilation of PV data. First, numerical experiments of identical-twin type were conducted with a simple univariate nuding algorithm and a global shallow water model based on PV and divergence (PV-D model). All model fields are successfully reconstructed through the insertion of complete PV data alone if an appropriate value for the nudging coefficient is used. A simple linear analysis suggests that slow modes are recovered rapidly, at a rate nearly independent of spatial scale. In a more realistic experiment, appropriately scaled total ozone data from the NIMBUS-7 TOMS instrument were assimilated as proxy PV data into the PV-D model over a 10-day period. The resulting model PV field matches the observed total ozone field relatively well on large spatial scales, and the PV, geopotential and divergence fields are dynamically consistent. These results indicate the potential usefulness that tracer observations, as proxy PV data, may offer in a data assimilation system.

Improving 7-Day Forecast Skill by Assimilation of Retrieved AIRS Temperature Profiles

Science.gov (United States)

Susskind, Joel; Rosenberg, Bob

2016-01-01

We conducted a new set of Data Assimilation Experiments covering the period January 1 to February 29, 2016 using the GEOS-5 DAS. Our experiments assimilate all data used operationally by GMAO (Control) with some modifications. Significant improvement in Global and Southern Hemisphere Extra-tropical 7-day forecast skill was obtained when: We assimilated AIRS Quality Controlled temperature profiles in place of observed AIRS radiances, and also did not assimilate CrISATMS radiances, nor did we assimilate radiosonde temperature profiles or aircraft temperatures. This new methodology did not improve or degrade 7-day Northern Hemispheric Extra-tropical forecast skill. We are conducting experiments aimed at further improving of Northern Hemisphere Extra-tropical forecast skill.

Cholesterol Assimilation by Lactobacillus Probiotic Bacteria: An In Vitro Investigation

Directory of Open Access Journals (Sweden)

Catherine Tomaro-Duchesneau

2014-01-01

Full Text Available Excess cholesterol is associated with cardiovascular diseases (CVD, an important cause of mortality worldwide. Current CVD therapeutic measures, lifestyle and dietary interventions, and pharmaceutical agents for regulating cholesterol levels are inadequate. Probiotic bacteria have demonstrated potential to lower cholesterol levels by different mechanisms, including bile salt hydrolase activity, production of compounds that inhibit enzymes such as 3-hydroxy-3-methylglutaryl coenzyme A, and cholesterol assimilation. This work investigates 11 Lactobacillus strains for cholesterol assimilation. Probiotic strains for investigation were selected from the literature: Lactobacillus reuteri NCIMB 11951, L. reuteri NCIMB 701359, L. reuteri NCIMB 702655, L. reuteri NCIMB 701089, L. reuteri NCIMB 702656, Lactobacillus fermentum NCIMB 5221, L. fermentum NCIMB 8829, L. fermentum NCIMB 2797, Lactobacillus rhamnosus ATCC 53103 GG, Lactobacillus acidophilus ATCC 314, and Lactobacillus plantarum ATCC 14917. Cholesterol assimilation was investigated in culture media and under simulated intestinal conditions. The best cholesterol assimilator was L. plantarum ATCC 14917 (15.18 ± 0.55 mg/1010 cfu in MRS broth. L. reuteri NCIMB 701089 assimilated over 67% (2254.70 ± 63.33 mg/1010 cfu of cholesterol, the most of all the strains, under intestinal conditions. This work demonstrates that probiotic bacteria can assimilate cholesterol under intestinal conditions, with L. reuteri NCIMB 701089 showing great potential as a CVD therapeutic.

Assimilation of Baba and Nyonya in Malaysia

OpenAIRE

Razaleigh Muhamat Kawangit

2015-01-01

This research set outs to explore the exact level of the social aspect of assimilation between Baba and Nyonya and their Malay counterparts in Malaysia. It was sure that assimilation in social aspect is a dilemma which Baba and Nyonya face when they interact with Malays as a dominant ethnic group. It suggests that when the process of interaction, their behavior changes in line with the identity of the Malays. This is because the majority influenced the minority in the Malaysian context. Whils...

The effect of network resolution on data assimilation in a mesoscale model

International Nuclear Information System (INIS)

Dudhia, J.

1994-01-01

One goal of the Atmospheric Radiation Measurement (ARM) Program is to characterize meteorological fields over wide areas (200-km square) in order to better parameterize sub-grid-scale variability in general circulation models used for climate studies. Such a detailed knowledge over these areas is impossible with current observational methods alone, but the synthesis of a dataset by combining observations with a mesoscale numerical model is feasible. Current data assimilation techniques allow observed data to be incorporated while a model is running, thus constraining the model to fit the data as well as the data to be dynamically consistent with the model atmosphere. This interaction may therefore be regarded as a dynamical analysis technique. The technique used for data assimilation here will be the nudging method (Stauffer and Seaman 1990, Kuo and Guo 1989). Specifically, observational nudging where data at observational sites are gradually forced in the model without the need for a gridded analysis. This method is particularly appropriate for asynoptic data covering meso-β-scales, such as will be available at the Cloud and Radiation Testbed (CART) sites. The method makes it possible to incorporate the wide variety of data coming from these sites

Love waves in functionally graded piezoelectric materials by stiffness matrix method.

Science.gov (United States)

Ben Salah, Issam; Wali, Yassine; Ben Ghozlen, Mohamed Hédi

2011-04-01

A numerical matrix method relative to the propagation of ultrasonic guided waves in functionally graded piezoelectric heterostructure is given in order to make a comparative study with the respective performances of analytical methods proposed in literature. The preliminary obtained results show a good agreement, however numerical approach has the advantage of conceptual simplicity and flexibility brought about by the stiffness matrix method. The propagation behaviour of Love waves in a functionally graded piezoelectric material (FGPM) is investigated in this article. It involves a thin FGPM layer bonded perfectly to an elastic substrate. The inhomogeneous FGPM heterostructure has been stratified along the depth direction, hence each state can be considered as homogeneous and the ordinary differential equation method is applied. The obtained solutions are used to study the effect of an exponential gradient applied to physical properties. Such numerical approach allows applying different gradient variation for mechanical and electrical properties. For this case, the obtained results reveal opposite effects. The dispersive curves and phase velocities of the Love wave propagation in the layered piezoelectric film are obtained for electrical open and short cases on the free surface, respectively. The effect of gradient coefficients on coupled electromechanical factor, on the stress fields, the electrical potential and the mechanical displacement are discussed, respectively. Illustration is achieved on the well known heterostructure PZT-5H/SiO(2), the obtained results are especially useful in the design of high-performance acoustic surface devices and accurately prediction of the Love wave propagation behaviour. Copyright © 2010 Elsevier B.V. All rights reserved.

Photonic band structures solved by a plane-wave-based transfer-matrix method.

Science.gov (United States)

Li, Zhi-Yuan; Lin, Lan-Lan

2003-04-01

Transfer-matrix methods adopting a plane-wave basis have been routinely used to calculate the scattering of electromagnetic waves by general multilayer gratings and photonic crystal slabs. In this paper we show that this technique, when combined with Bloch's theorem, can be extended to solve the photonic band structure for 2D and 3D photonic crystal structures. Three different eigensolution schemes to solve the traditional band diagrams along high-symmetry lines in the first Brillouin zone of the crystal are discussed. Optimal rules for the Fourier expansion over the dielectric function and electromagnetic fields with discontinuities occurring at the boundary of different material domains have been employed to accelerate the convergence of numerical computation. Application of this method to an important class of 3D layer-by-layer photonic crystals reveals the superior convergency of this different approach over the conventional plane-wave expansion method.

Photonic band structures solved by a plane-wave-based transfer-matrix method

International Nuclear Information System (INIS)

Li Zhiyuan; Lin Lanlan

2003-01-01

Transfer-matrix methods adopting a plane-wave basis have been routinely used to calculate the scattering of electromagnetic waves by general multilayer gratings and photonic crystal slabs. In this paper we show that this technique, when combined with Bloch's theorem, can be extended to solve the photonic band structure for 2D and 3D photonic crystal structures. Three different eigensolution schemes to solve the traditional band diagrams along high-symmetry lines in the first Brillouin zone of the crystal are discussed. Optimal rules for the Fourier expansion over the dielectric function and electromagnetic fields with discontinuities occurring at the boundary of different material domains have been employed to accelerate the convergence of numerical computation. Application of this method to an important class of 3D layer-by-layer photonic crystals reveals the superior convergency of this different approach over the conventional plane-wave expansion method

Naming game with biased assimilation over adaptive networks

Science.gov (United States)

Fu, Guiyuan; Zhang, Weidong

2018-01-01

The dynamics of two-word naming game incorporating the influence of biased assimilation over adaptive network is investigated in this paper. Firstly an extended naming game with biased assimilation (NGBA) is proposed. The hearer in NGBA accepts the received information in a biased manner, where he may refuse to accept the conveyed word from the speaker with a predefined probability, if the conveyed word is different from his current memory. Secondly, the adaptive network is formulated by rewiring the links. Theoretical analysis is developed to show that the population in NGBA will eventually reach global consensus on either A or B. Numerical simulation results show that the larger strength of biased assimilation on both words, the slower convergence speed, while larger strength of biased assimilation on only one word can slightly accelerate the convergence; larger population size can make the rate of convergence slower to a large extent when it increases from a relatively small size, while such effect becomes minor when the population size is large; the behavior of adaptively reconnecting the existing links can greatly accelerate the rate of convergence especially on the sparse connected network.

Improving Forecast Skill by Assimilation of AIRS Temperature Soundings

Science.gov (United States)

Susskind, Joel; Reale, Oreste

2010-01-01

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU-A are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The AIRS Version 5 retrieval algorithm, is now being used operationally at the Goddard DISC in the routine generation of geophysical parameters derived from AIRS/AMSU data. A major innovation in Version 5 is the ability to generate case-by-case level-by-level error estimates delta T(p) for retrieved quantities and the use of these error estimates for Quality Control. We conducted a number of data assimilation experiments using the NASA GEOS-5 Data Assimilation System as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The model was run at a horizontal resolution of 0.5 deg. latitude X 0.67 deg longitude with 72 vertical levels. These experiments were run during four different seasons, each using a different year. The AIRS temperature profiles were presented to the GEOS-5 analysis as rawinsonde profiles, and the profile error estimates delta (p) were used as the uncertainty for each measurement in the data assimilation process. We compared forecasts analyses generated from the analyses done by assimilation of AIRS temperature profiles with three different sets of thresholds; Standard, Medium, and Tight. Assimilation of Quality Controlled AIRS temperature profiles significantly improve 5-7 day forecast skill compared to that obtained without the benefit of AIRS data in all of the cases studied. In addition, assimilation of Quality Controlled AIRS temperature soundings performs better than assimilation of AIRS observed radiances. Based on the experiments shown, Tight Quality Control of AIRS temperature profile performs best

Comparison of gridded multi-mission and along-track mono-mission satellite altimetry wave heights with in situ near-shore buoy data.

Digital Repository Service at National Institute of Oceanography (India)

Shanas, P.R.; SanilKumar, V.; Hithin, N.K.

and studied the validity of these observations against ship-reported and buoy data. Many studies have been undertaken on how best to use the data available from satellite observation systems in wave models (Mastenbroek, 1994; Young and Glowacki, 1996... Sea wave model. Journal of Geophysical Research 10, 5829–5849. Young, I.R., 1994. Global ocean wave statistics obtained from satellite observations. Applied Ocean Research 16, 235-248. Young, I.R., Glowacki, T.J., 1996. Assimilation of altimeter...

A study of regional-scale aerosol assimilation using a Stretch-NICAM

Science.gov (United States)

Misawa, S.; Dai, T.; Schutgens, N.; Nakajima, T.

2013-12-01

Although aerosol is considered to be harmful to human health and it became a social issue, aerosol models and emission inventories include large uncertainties. In recent studies, data assimilation is applied to aerosol simulation to get more accurate aerosol field and emission inventory. Most of these studies, however, are carried out only on global scale, and there are only a few researches about regional scale aerosol assimilation. In this study, we have created and verified an aerosol assimilation system on regional scale, in hopes to reduce an error associated with the aerosol emission inventory. Our aerosol assimilation system has been developed using an atmospheric climate model, NICAM (Non-hydrostaric ICosahedral Atmospheric Model; Satoh et al., 2008) with a stretch grid system and coupled with an aerosol transport model, SPRINTARS (Takemura et al., 2000). Also, this assimilation system is based on local ensemble transform Kalman filter (LETKF). To validate this system, we used a simulated observational data by adding some artificial errors to the surface aerosol fields constructed by Stretch-NICAM-SPRINTARS. We also included a small perturbation in original emission inventory. This assimilation with modified observational data and emission inventory was performed in Kanto-plane region around Tokyo, Japan, and the result indicates the system reducing a relative error of aerosol concentration by 20%. Furthermore, we examined a sensitivity of the aerosol assimilation system by varying the number of total ensemble (5, 10 and 15 ensembles) and local patch (domain) size (radius of 50km, 100km and 200km), both of which are the tuning parameters in LETKF. The result of the assimilation with different ensemble number 5, 10 and 15 shows that the larger the number of ensemble is, the smaller the relative error become. This is consistent with ensemble Kalman filter theory and imply that this assimilation system works properly. Also we found that assimilation system

Wave Equation Inversion of Skeletonized SurfaceWaves

KAUST Repository

Zhang, Zhendong

2015-08-19

We present a surface-wave inversion method that inverts for the S-wave velocity from the Rayleigh dispersion curve for the fundamental-mode. We call this wave equation inversion of skeletonized surface waves because the dispersion curve for the fundamental-mode Rayleigh wave is inverted using finite-difference solutions to the wave equation. The best match between the predicted and observed dispersion curves provides the optimal S-wave velocity model. Results with synthetic and field data illustrate the benefits and limitations of this method.

Validation of Standing Wave Liner Impedance Measurement Method, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Hersh Acoustical Engineering, Inc. proposes to establish the feasibility and practicality of using the Standing Wave Method (SWM) to measure the impedance of...

Spatial Dynamics Methods for Solitary Waves on a Ferrofluid Jet

Science.gov (United States)

Groves, M. D.; Nilsson, D. V.

2018-04-01

This paper presents existence theories for several families of axisymmetric solitary waves on the surface of an otherwise cylindrical ferrofluid jet surrounding a stationary metal rod. The ferrofluid, which is governed by a general (nonlinear) magnetisation law, is subject to an azimuthal magnetic field generated by an electric current flowing along the rod. The ferrohydrodynamic problem for axisymmetric travelling waves is formulated as an infinite-dimensional Hamiltonian system in which the axial direction is the time-like variable. A centre-manifold reduction technique is employed to reduce the system to a locally equivalent Hamiltonian system with a finite number of degrees of freedom, and homoclinic solutions to the reduced system, which correspond to solitary waves, are detected by dynamical-systems methods.

Impact of data assimilation on ocean current forecasts in the Angola Basin

Science.gov (United States)

Phillipson, Luke; Toumi, Ralf

2017-06-01

The ocean current predictability in the data limited Angola Basin was investigated using the Regional Ocean Modelling System (ROMS) with four-dimensional variational data assimilation. Six experiments were undertaken comprising a baseline case of the assimilation of salinity/temperature profiles and satellite sea surface temperature, with the subsequent addition of altimetry, OSCAR (satellite-derived sea surface currents), drifters, altimetry and drifters combined, and OSCAR and drifters combined. The addition of drifters significantly improves Lagrangian predictability in comparison to the baseline case as well as the addition of either altimetry or OSCAR. OSCAR assimilation only improves Lagrangian predictability as much as altimetry assimilation. On average the assimilation of either altimetry or OSCAR with drifter velocities does not significantly improve Lagrangian predictability compared to the drifter assimilation alone, even degrading predictability in some cases. When the forecast current speed is large, it is more likely that the combination improves trajectory forecasts. Conversely, when the currents are weaker, it is more likely that the combination degrades the trajectory forecast.

The Failure to Construct Proof Based on Assimilation and Accommodation Framework from Piaget

Science.gov (United States)

Netti, Syukma; Nusantara, Toto; Subanji; Abadyo; Anwar, Lathiful

2016-01-01

The purpose of this article is to describe the process of a proof construction. It is more specific on the failure of the process. Piaget's frameworks, assimilation and accommodation, were used to analyze it. Method of this research was qualitative method. Data were collected by asking five students working on problems of proof using think aloud…

Hyperspherical time-dependent method with semiclassical outgoing waves for double photoionization of helium

International Nuclear Information System (INIS)

Kazansky, A.K.; Selles, P.; Malegat, L.

2003-01-01

The hyperspherical time-dependent method with semiclassical outgoing waves for study of double photoionization of helium is presented. It is closely related to the hyperspherical R-matrix method with semiclassical outgoing waves [Phys. Rev. A 65, 032711 (2002)]: both split configuration space into two regions to solve the stationary inhomogeneous Schroedinger equation associated with the one-photon ionization problem, and both apply the same treatment to the outer region. However, the two methods differ radically in their treatments of the problem in the inner region: the most recent one applies a time-dependent approach for calculating the stationary wave function, while the previous one uses a R-matrix treatment. The excellent agreement observed between the triple differential cross sections obtained from these two basically different methods provides very strong support for both of them. Importantly, the very different numerical structures of both methods might make the most recent one a better candidate for investigating the near-threshold region

A new approach for assimilation of 2D radar precipitation in a high-resolution NWP model

DEFF Research Database (Denmark)

Korsholm, Ulrik Smith; Petersen, Claus; Sass, Bent Hansen

2015-01-01

of precipitation, the strength of the nudging is proportional to the offset between observed and modelled precipitation, leading to increased moisture convergence. If the model over-predicts precipitation, the low level moisture source is reduced, and in-cloud moisture is nudged towards environmental values......A new approach for assimilation of 2D precipitation in numerical weather prediction models is presented and tested in a case with convective, heavy precipitation. In the scheme a nudging term is added to the horizontal velocity divergence tendency equation. In case of underproduction....... The method was implemented in the Danish Meteorological Institute numerical weather prediction (DMI NWP) nowcasting system, running with hourly cycles, performing a surface analysis and 3D variational analysis for upper air assimilation at each cycle restart, followed by nudging assimilation of precipitation...

Analysis of global multiscale finite element methods for wave equations with continuum spatial scales

KAUST Repository

Jiang, Lijian; Efendiev, Yalchin; Ginting, Victor

2010-01-01

In this paper, we discuss a numerical multiscale approach for solving wave equations with heterogeneous coefficients. Our interest comes from geophysics applications and we assume that there is no scale separation with respect to spatial variables. To obtain the solution of these multiscale problems on a coarse grid, we compute global fields such that the solution smoothly depends on these fields. We present a Galerkin multiscale finite element method using the global information and provide a convergence analysis when applied to solve the wave equations. We investigate the relation between the smoothness of the global fields and convergence rates of the global Galerkin multiscale finite element method for the wave equations. Numerical examples demonstrate that the use of global information renders better accuracy for wave equations with heterogeneous coefficients than the local multiscale finite element method. © 2010 IMACS.

Analysis of global multiscale finite element methods for wave equations with continuum spatial scales

KAUST Repository

Jiang, Lijian

2010-08-01

In this paper, we discuss a numerical multiscale approach for solving wave equations with heterogeneous coefficients. Our interest comes from geophysics applications and we assume that there is no scale separation with respect to spatial variables. To obtain the solution of these multiscale problems on a coarse grid, we compute global fields such that the solution smoothly depends on these fields. We present a Galerkin multiscale finite element method using the global information and provide a convergence analysis when applied to solve the wave equations. We investigate the relation between the smoothness of the global fields and convergence rates of the global Galerkin multiscale finite element method for the wave equations. Numerical examples demonstrate that the use of global information renders better accuracy for wave equations with heterogeneous coefficients than the local multiscale finite element method. © 2010 IMACS.

Temperature Data Assimilation with Salinity Corrections: Validation for the NSIPP Ocean Data Assimilation System in the Tropical Pacific Ocean, 1993-1998

Science.gov (United States)

Troccoli, Alberto; Rienecker, Michele M.; Keppenne, Christian L.; Johnson, Gregory C.

2003-01-01

The NASA Seasonal-to-Interannual Prediction Project (NSIPP) has developed an Ocean data assimilation system to initialize the quasi-isopycnal ocean model used in our experimental coupled-model forecast system. Initial tests of the system have focused on the assimilation of temperature profiles in an optimal interpolation framework. It is now recognized that correction of temperature only often introduces spurious water masses. The resulting density distribution can be statically unstable and also have a detrimental impact on the velocity distribution. Several simple schemes have been developed to try to correct these deficiencies. Here the salinity field is corrected by using a scheme which assumes that the temperature-salinity relationship of the model background is preserved during the assimilation. The scheme was first introduced for a zlevel model by Troccoli and Haines (1999). A large set of subsurface observations of salinity and temperature is used to cross-validate two data assimilation experiments run for the 6-year period 1993-1998. In these two experiments only subsurface temperature observations are used, but in one case the salinity field is also updated whenever temperature observations are available.

Global SWOT Data Assimilation of River Hydrodynamic Model; the Twin Simulation Test of CaMa-Flood

Science.gov (United States)

Ikeshima, D.; Yamazaki, D.; Kanae, S.

2016-12-01

CaMa-Flood is a global scale model for simulating hydrodynamics in large scale rivers. It can simulate river hydrodynamics such as river discharge, flooded area, water depth and so on by inputting water runoff derived from land surface model. Recently many improvements at parameters or terrestrial data are under process to enhance the reproducibility of true natural phenomena. However, there are still some errors between nature and simulated result due to uncertainties in each model. SWOT (Surface water and Ocean Topography) is a satellite, which is going to be launched in 2021, can measure open water surface elevation. SWOT observed data can be used to calibrate hydrodynamics model at river flow forecasting and is expected to improve model's accuracy. Combining observation data into model to calibrate is called data assimilation. In this research, we developed data-assimilated river flow simulation system in global scale, using CaMa-Flood as river hydrodynamics model and simulated SWOT as observation data. Generally at data assimilation, calibrating "model value" with "observation value" makes "assimilated value". However, the observed data of SWOT satellite will not be available until its launch in 2021. Instead, we simulated the SWOT observed data using CaMa-Flood. Putting "pure input" into CaMa-Flood produce "true water storage". Extracting actual daily swath of SWOT from "true water storage" made simulated observation. For "model value", we made "disturbed water storage" by putting "noise disturbed input" to CaMa-Flood. Since both "model value" and "observation value" are made by same model, we named this twin simulation. At twin simulation, simulated observation of "true water storage" is combined with "disturbed water storage" to make "assimilated value". As the data assimilation method, we used ensemble Kalman filter. If "assimilated value" is closer to "true water storage" than "disturbed water storage", the data assimilation can be marked effective. Also

Two-dimensional simulation of broad-band ferrite electromagnetic wave absorbers by using the FDTD method

Energy Technology Data Exchange (ETDEWEB)

Yoon, Hyun Jin; Kim, Dong Il [Korea Maritime University, Busan (Korea, Republic of)

2004-10-15

The purpose of this simulation study is to design and fabricate an electromagnetic (EM) wave absorber in order to develop a wide-band absorber. We have proposed and modeled a bird-eye-type and cutting-cone-type EM wave absorber by using the equivalent material constants method (EMCM), and we simulated them by using a finite-difference time-domain (FDTD) method. A two or a three-dimensional simulation would be desirable to analyze the EM wave absorber characteristics and to develop new structures. The two-dimensional FDTD simulation requires less computer resources than a three-dimensional simulation to consider the structural effects of the EM wave absorbers. The numerical simulation by using the FDTD method shows propagating EM waves in various types of periodic structure EM wave absorbers. Simultaneously, a Fourier analysis is used to characterize the input pulse and the reflected EM waves for ferrite absorbers with various structures. The results have a wide-band reflection-reducing characteristic. The validity of the proposed model was confirmed by comparing the two-dimensional simulation with the experimental results. The simulations were carried out in the frequency band from 30 MHz to 10 GHz.

Two-dimensional simulation of broad-band ferrite electromagnetic wave absorbers by using the FDTD method

International Nuclear Information System (INIS)

Yoon, Hyun Jin; Kim, Dong Il

2004-01-01

The purpose of this simulation study is to design and fabricate an electromagnetic (EM) wave absorber in order to develop a wide-band absorber. We have proposed and modeled a bird-eye-type and cutting-cone-type EM wave absorber by using the equivalent material constants method (EMCM), and we simulated them by using a finite-difference time-domain (FDTD) method. A two or a three-dimensional simulation would be desirable to analyze the EM wave absorber characteristics and to develop new structures. The two-dimensional FDTD simulation requires less computer resources than a three-dimensional simulation to consider the structural effects of the EM wave absorbers. The numerical simulation by using the FDTD method shows propagating EM waves in various types of periodic structure EM wave absorbers. Simultaneously, a Fourier analysis is used to characterize the input pulse and the reflected EM waves for ferrite absorbers with various structures. The results have a wide-band reflection-reducing characteristic. The validity of the proposed model was confirmed by comparing the two-dimensional simulation with the experimental results. The simulations were carried out in the frequency band from 30 MHz to 10 GHz.

Vibration isolation design for periodically stiffened shells by the wave finite element method

Science.gov (United States)

Hong, Jie; He, Xueqing; Zhang, Dayi; Zhang, Bing; Ma, Yanhong

2018-04-01

Periodically stiffened shell structures are widely used due to their excellent specific strength, in particular for aeronautical and astronautical components. This paper presents an improved Wave Finite Element Method (FEM) that can be employed to predict the band-gap characteristics of stiffened shell structures efficiently. An aero-engine casing, which is a typical periodically stiffened shell structure, was employed to verify the validation and efficiency of the Wave FEM. Good agreement has been found between the Wave FEM and the classical FEM for different boundary conditions. One effective wave selection method based on the Wave FEM has thus been put forward to filter the radial modes of a shell structure. Furthermore, an optimisation strategy by the combination of the Wave FEM and genetic algorithm was presented for periodically stiffened shell structures. The optimal out-of-plane band gap and the mass of the whole structure can be achieved by the optimisation strategy under an aerodynamic load. Results also indicate that geometric parameters of stiffeners can be properly selected that the out-of-plane vibration attenuates significantly in the frequency band of interest. This study can provide valuable references for designing the band gaps of vibration isolation.

Three-Dimensional Passive-Source Reverse-Time Migration of Converted Waves: The Method

Science.gov (United States)

Li, Jiahang; Shen, Yang; Zhang, Wei

2018-02-01

At seismic discontinuities in the crust and mantle, part of the compressional wave energy converts to shear wave, and vice versa. These converted waves have been widely used in receiver function (RF) studies to image discontinuity structures in the Earth. While generally successful, the conventional RF method has its limitations and is suited mostly to flat or gently dipping structures. Among the efforts to overcome the limitations of the conventional RF method is the development of the wave-theory-based, passive-source reverse-time migration (PS-RTM) for imaging complex seismic discontinuities and scatters. To date, PS-RTM has been implemented only in 2D in the Cartesian coordinate for local problems and thus has limited applicability. In this paper, we introduce a 3D PS-RTM approach in the spherical coordinate, which is better suited for regional and global problems. New computational procedures are developed to reduce artifacts and enhance migrated images, including back-propagating the main arrival and the coda containing the converted waves separately, using a modified Helmholtz decomposition operator to separate the P and S modes in the back-propagated wavefields, and applying an imaging condition that maintains a consistent polarity for a given velocity contrast. Our new approach allows us to use migration velocity models with realistic velocity discontinuities, improving accuracy of the migrated images. We present several synthetic experiments to demonstrate the method, using regional and teleseismic sources. The results show that both regional and teleseismic sources can illuminate complex structures and this method is well suited for imaging dipping interfaces and sharp lateral changes in discontinuity structures.

Sensitivity analysis of a data assimilation technique for hindcasting and forecasting hydrodynamics of a complex coastal water body

Science.gov (United States)

Ren, Lei; Hartnett, Michael

2017-02-01

Accurate forecasting of coastal surface currents is of great economic importance due to marine activities such as marine renewable energy and fish farms in coastal regions in recent twenty years. Advanced oceanographic observation systems such as satellites and radars can provide many parameters of interest, such as surface currents and waves, with fine spatial resolution in near real time. To enhance modelling capability, data assimilation (DA) techniques which combine the available measurements with the hydrodynamic models have been used since the 1990s in oceanography. Assimilating measurements into hydrodynamic models makes the original model background states follow the observation trajectory, then uses it to provide more accurate forecasting information. Galway Bay is an open, wind dominated water body on which two coastal radars are deployed. An efficient and easy to implement sequential DA algorithm named Optimal Interpolation (OI) was used to blend radar surface current data into a three-dimensional Environmental Fluid Dynamics Code (EFDC) model. Two empirical parameters, horizontal correlation length and DA cycle length (CL), are inherent within OI. No guidance has previously been published regarding selection of appropriate values of these parameters or how sensitive OI DA is to variations in their values. Detailed sensitivity analysis has been performed on both of these parameters and results presented. Appropriate value of DA CL was examined and determined on producing the minimum Root-Mean-Square-Error (RMSE) between radar data and model background states. Analysis was performed to evaluate assimilation index (AI) of using an OI DA algorithm in the model. AI of the half-day forecasting mean vectors' directions was over 50% in the best assimilation model. The ability of using OI to improve model forecasts was also assessed and is reported upon.

Hindcasting and Forecasting of Surface Flow Fields through Assimilating High Frequency Remotely Sensing Radar Data

Directory of Open Access Journals (Sweden)

Lei Ren

2017-09-01

Full Text Available In order to improve the forecasting ability of numerical models, a sequential data assimilation scheme, nudging, was applied to blend remotely sensing high-frequency (HF radar surface currents with results from a three-dimensional numerical, EFDC (Environmental Fluid Dynamics Code model. For the first time, this research presents the most appropriate nudging parameters, which were determined from sensitivity experiments. To examine the influence of data assimilation cycle lengths on forecasts and to extend forecasting improvements, the duration of data assimilation cycles was studied through assimilating linearly interpolated temporal radar data. Data assimilation nudging parameters have not been previously analyzed. Assimilation of HF radar measurements at each model computational timestep outperformed those assimilation models using longer data assimilation cycle lengths; root-mean-square error (RMSE values of both surface velocity components during a 12 h model forecasting period indicated that surface flow fields were significantly improved when implementing nudging assimilation at each model computational timestep. The Data Assimilation Skill Score (DASS technique was used to quantitatively evaluate forecast improvements. The averaged values of DASS over the data assimilation domain were 26% and 33% for east–west and north–south velocity components, respectively, over the half-day forecasting period. Correlation of Averaged Kinetic Energy (AKE was improved by more than 10% in the best data assimilation model. Time series of velocity components and surface flow fields were presented to illustrate the improvement resulting from data assimilation application over time.

Aerosol data assimilation in the chemical transport model MOCAGE during the TRAQA/ChArMEx campaign: aerosol optical depth

Science.gov (United States)

Sič, Bojan; El Amraoui, Laaziz; Piacentini, Andrea; Marécal, Virginie; Emili, Emanuele; Cariolle, Daniel; Prather, Michael; Attié, Jean-Luc

2016-11-01

In this study, we describe the development of the aerosol optical depth (AOD) assimilation module in the chemistry transport model (CTM) MOCAGE (Modèle de Chimie Atmosphérique à Grande Echelle). Our goal is to assimilate the spatially averaged 2-D column AOD data from the National Aeronautics and Space Administration (NASA) Moderate-resolution Imaging Spectroradiometer (MODIS) instrument, and to estimate improvements in a 3-D CTM assimilation run compared to a direct model run. Our assimilation system uses 3-D-FGAT (first guess at appropriate time) as an assimilation method and the total 3-D aerosol concentration as a control variable. In order to have an extensive validation dataset, we carried out our experiment in the northern summer of 2012 when the pre-ChArMEx (CHemistry and AeRosol MEditerranean EXperiment) field campaign TRAQA (TRAnsport à longue distance et Qualité de l'Air dans le bassin méditerranéen) took place in the western Mediterranean basin. The assimilated model run is evaluated independently against a range of aerosol properties (2-D and 3-D) measured by in situ instruments (the TRAQA size-resolved balloon and aircraft measurements), the satellite Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instrument and ground-based instruments from the Aerosol Robotic Network (AERONET) network. The evaluation demonstrates that the AOD assimilation greatly improves aerosol representation in the model. For example, the comparison of the direct and the assimilated model run with AERONET data shows that the assimilation increased the correlation (from 0.74 to 0.88), and reduced the bias (from 0.050 to 0.006) and the root mean square error in the AOD (from 0.12 to 0.07). When compared to the 3-D concentration data obtained by the in situ aircraft and balloon measurements, the assimilation consistently improves the model output. The best results as expected occur when the shape of the vertical profile is correctly simulated by the direct model. We

Improving quantitative precipitation nowcasting with a local ensemble transform Kalman filter radar data assimilation system: observing system simulation experiments

Directory of Open Access Journals (Sweden)

Chih-Chien Tsai

2014-03-01

Full Text Available This study develops a Doppler radar data assimilation system, which couples the local ensemble transform Kalman filter with the Weather Research and Forecasting model. The benefits of this system to quantitative precipitation nowcasting (QPN are evaluated with observing system simulation experiments on Typhoon Morakot (2009, which brought record-breaking rainfall and extensive damage to central and southern Taiwan. The results indicate that the assimilation of radial velocity and reflectivity observations improves the three-dimensional winds and rain-mixing ratio most significantly because of the direct relations in the observation operator. The patterns of spiral rainbands become more consistent between different ensemble members after radar data assimilation. The rainfall intensity and distribution during the 6-hour deterministic nowcast are also improved, especially for the first 3 hours. The nowcasts with and without radar data assimilation have similar evolution trends driven by synoptic-scale conditions. Furthermore, we carry out a series of sensitivity experiments to develop proper assimilation strategies, in which a mixed localisation method is proposed for the first time and found to give further QPN improvement in this typhoon case.

Assimilating the Future for Better Forecasts and Earlier Warnings

Science.gov (United States)

Du, H.; Wheatcroft, E.; Smith, L. A.

2016-12-01

Multi-model ensembles have become popular tools to account for some of the uncertainty due to model inadequacy in weather and climate simulation-based predictions. The current multi-model forecasts focus on combining single model ensemble forecasts by means of statistical post-processing. Assuming each model is developed independently or with different primary target variables, each is likely to contain different dynamical strengths and weaknesses. Using statistical post-processing, such information is only carried by the simulations under a single model ensemble: no advantage is taken to influence simulations under the other models. A novel methodology, named Multi-model Cross Pollination in Time, is proposed for multi-model ensemble scheme with the aim of integrating the dynamical information regarding the future from each individual model operationally. The proposed approach generates model states in time via applying data assimilation scheme(s) to yield truly "multi-model trajectories". It is demonstrated to outperform traditional statistical post-processing in the 40-dimensional Lorenz96 flow. Data assimilation approaches are originally designed to improve state estimation from the past to the current time. The aim of this talk is to introduce a framework that uses data assimilation to improve model forecasts at future time (not to argue for any one particular data assimilation scheme). Illustration of applying data assimilation "in the future" to provide early warning of future high-impact events is also presented.

An Improved Split-Step Wavelet Transform Method for Anomalous Radio Wave Propagation Modelling

Directory of Open Access Journals (Sweden)

A. Iqbal

2014-12-01

Full Text Available Anomalous tropospheric propagation caused by ducting phenomenon is a major problem in wireless communication. Thus, it is important to study the behavior of radio wave propagation in tropospheric ducts. The Parabolic Wave Equation (PWE method is considered most reliable to model anomalous radio wave propagation. In this work, an improved Split Step Wavelet transform Method (SSWM is presented to solve PWE for the modeling of tropospheric propagation over finite and infinite conductive surfaces. A large number of numerical experiments are carried out to validate the performance of the proposed algorithm. Developed algorithm is compared with previously published techniques; Wavelet Galerkin Method (WGM and Split-Step Fourier transform Method (SSFM. A very good agreement is found between SSWM and published techniques. It is also observed that the proposed algorithm is about 18 times faster than WGM and provide more details of propagation effects as compared to SSFM.

Global Data Assimilation System (GDAS)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Global Data Assimilation System (GDAS) is the system used by the Global Forecast System (GFS) model to place observations into a gridded model space for the...

Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation

Science.gov (United States)

Li, Shan; Zhang, Shaoqing; Liu, Zhengyu; Lu, Lv; Zhu, Jiang; Zhang, Xuefeng; Wu, Xinrong; Zhao, Ming; Vecchi, Gabriel A.; Zhang, Rong-Hua; Lin, Xiaopei

2018-04-01

Parametric uncertainty in convection parameterization is one major source of model errors that cause model climate drift. Convection parameter tuning has been widely studied in atmospheric models to help mitigate the problem. However, in a fully coupled general circulation model (CGCM), convection parameters which impact the ocean as well as the climate simulation may have different optimal values. This study explores the possibility of estimating convection parameters with an ensemble coupled data assimilation method in a CGCM. Impacts of the convection parameter estimation on climate analysis and forecast are analyzed. In a twin experiment framework, five convection parameters in the GFDL coupled model CM2.1 are estimated individually and simultaneously under both perfect and imperfect model regimes. Results show that the ensemble data assimilation method can help reduce the bias in convection parameters. With estimated convection parameters, the analyses and forecasts for both the atmosphere and the ocean are generally improved. It is also found that information in low latitudes is relatively more important for estimating convection parameters. This study further suggests that when important parameters in appropriate physical parameterizations are identified, incorporating their estimation into traditional ensemble data assimilation procedure could improve the final analysis and climate prediction.

A New Alternative in Urban Geophysics: Multi-Channel Analysis of Surface Waves (MASW) Method

International Nuclear Information System (INIS)

Ozcep, F.

2007-01-01

Geophysical studies are increasingly being applied to geotechnical investigations as they can identify soil properties and soil boundaries. Other advantage is that many of these methods are non-invasive and environment friendly. Soil stiffness is one of the critical material parameters considered during an early stage of most foundation construction. It is related directly to the stability of structural load, especially as it relates to possible earthquake hazard. Soil lacking sufficient stiffness for a given load can experience a significant reduction in strength under earthquake shaking resulting in liquefaction, a condition responsible for tremendous amounts of damage from earthquakes around the world The multichannel analysis of surface waves (MASW) method originated from the traditional seismic exploration approach that employs multiple (twelve or more) receivers placed along a linear survey line. Main advantage is its capability of recognizing different types of seismic waves based on wave propagation characteristics such as velocity and attenuation. The MASW method utilizes this capability to discriminate the fundamental-mode Rayleigh wave against all other types of surface and body waves generated not only from the active seismic source but also from the ambient site conditions. Dispersive characteristics of seismic waves are imaged from an objective 2-D wave field transformation. The present paper indicates results from MASW survey at different urban site in Turkey. MASW techniques will prove to be important tools for obtaining shear wave velocity and evaluating liquefaction potential, soil bearing capacity and soil amplification, etc. for future geophysical and geotechnical engineering community

Differentiation between Trichophyton mentagrophytes and T. rubrum by sorbitol assimilation.

OpenAIRE

Rezusta, A; Rubio, M C; Alejandre, M C

1991-01-01

Trichophyton rubrum was easily differentiated from T. mentagrophytes by its ability to assimilate sorbitol with an API 20C AUX strip. One hundred percent of 36 T. rubrum strains and none of 147 T. mentagrophytes strains assimilated sorbitol.

Assimilating GRACE terrestrial water storage data into a conceptual hydrology model for the River Rhine

Science.gov (United States)

Widiastuti, E.; Steele-Dunne, S. C.; Gunter, B.; Weerts, A.; van de Giesen, N.

2009-12-01

Terrestrial water storage (TWS) is a key component of the terrestrial and global hydrological cycles, and plays a major role in the Earth’s climate. The Gravity Recovery and Climate Experiment (GRACE) twin satellite mission provided the first space-based dataset of TWS variations, albeit with coarse resolution and limited accuracy. Here, we examine the value of assimilating GRACE observations into a well-calibrated conceptual hydrology model of the Rhine river basin. In this study, the ensemble Kalman filter (EnKF) and smoother (EnKS) were applied to assimilate the GRACE TWS variation data into the HBV-96 rainfall run-off model, from February 2003 to December 2006. Two GRACE datasets were used, the DMT-1 models produced at TU Delft, and the CSR-RL04 models produced by UT-Austin . Each center uses its own data processing and filtering methods, yielding two different estimates of TWS variations and therefore two sets of assimilated TWS estimates. To validate the results, the model estimated discharge after the data assimilation was compared with measured discharge at several stations. As expected, the updated TWS was generally somewhere between the modeled and observed TWS in both experiments and the variance was also lower than both the prior error covariance and the assumed GRACE observation error. However, the impact on the discharge was found to depend heavily on the assimilation strategy used, in particular on how the TWS increments were applied to the individual storage terms of the hydrology model.

A stabilised nodal spectral element method for fully nonlinear water waves

DEFF Research Database (Denmark)

Engsig-Karup, Allan Peter; Eskilsson, C.; Bigoni, Daniele

2016-01-01

can cause severe aliasing problems and consequently numerical instability for marginally resolved or very steep waves. We show how the scheme can be stabilised through a combination of over-integration of the Galerkin projections and a mild spectral filtering on a per element basis. This effectively......We present an arbitrary-order spectral element method for general-purpose simulation of non-overturning water waves, described by fully nonlinear potential theory. The method can be viewed as a high-order extension of the classical finite element method proposed by Cai et al. (1998) [5], although...... the numerical implementation differs greatly. Features of the proposed spectral element method include: nodal Lagrange basis functions, a general quadrature-free approach and gradient recovery using global L2 projections. The quartic nonlinear terms present in the Zakharov form of the free surface conditions...

Topology optimization for three-dimensional electromagnetic waves using an edge element-based finite-element method.

Science.gov (United States)

Deng, Yongbo; Korvink, Jan G

2016-05-01

This paper develops a topology optimization procedure for three-dimensional electromagnetic waves with an edge element-based finite-element method. In contrast to the two-dimensional case, three-dimensional electromagnetic waves must include an additional divergence-free condition for the field variables. The edge element-based finite-element method is used to both discretize the wave equations and enforce the divergence-free condition. For wave propagation described in terms of the magnetic field in the widely used class of non-magnetic materials, the divergence-free condition is imposed on the magnetic field. This naturally leads to a nodal topology optimization method. When wave propagation is described using the electric field, the divergence-free condition must be imposed on the electric displacement. In this case, the material in the design domain is assumed to be piecewise homogeneous to impose the divergence-free condition on the electric field. This results in an element-wise topology optimization algorithm. The topology optimization problems are regularized using a Helmholtz filter and a threshold projection method and are analysed using a continuous adjoint method. In order to ensure the applicability of the filter in the element-wise topology optimization version, a regularization method is presented to project the nodal into an element-wise physical density variable.

Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media

Energy Technology Data Exchange (ETDEWEB)

Gao, Kai, E-mail: kaigao87@gmail.com [Department of Geology and Geophysics, Texas A& M University, College Station, TX 77843 (United States); Fu, Shubin, E-mail: shubinfu89@gmail.com [Department of Mathematics, Texas A& M University, College Station, TX 77843 (United States); Gibson, Richard L., E-mail: gibson@tamu.edu [Department of Geology and Geophysics, Texas A& M University, College Station, TX 77843 (United States); Chung, Eric T., E-mail: tschung@math.cuhk.edu.hk [Department of Mathematics, The Chinese University of Hong Kong, Shatin, NT (Hong Kong); Efendiev, Yalchin, E-mail: efendiev@math.tamu.edu [Department of Mathematics, Texas A& M University, College Station, TX 77843 (United States); Numerical Porous Media SRI Center (NumPor), King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)

2015-08-15

It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale medium property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.

Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media

International Nuclear Information System (INIS)

Gao, Kai; Fu, Shubin; Gibson, Richard L.; Chung, Eric T.; Efendiev, Yalchin

2015-01-01

It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both the boundaries and interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale medium property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system

Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media

KAUST Repository

Gao, Kai

2015-04-14

It is important to develop fast yet accurate numerical methods for seismic wave propagation to characterize complex geological structures and oil and gas reservoirs. However, the computational cost of conventional numerical modeling methods, such as finite-difference method and finite-element method, becomes prohibitively expensive when applied to very large models. We propose a Generalized Multiscale Generalized Multiscale Finite-Element Method (GMsFEM) for elastic wave propagation in heterogeneous, anisotropic media, where we construct basis functions from multiple local problems for both boundaries and the interior of a coarse node support or coarse element. The application of multiscale basis functions can capture the fine scale medium property variations, and allows us to greatly reduce the degrees of freedom that are required to implement the modeling compared with conventional finite-element method for wave equation, while restricting the error to low values. We formulate the continuous Galerkin and discontinuous Galerkin formulation of the multiscale method, both of which have pros and cons. Applications of the multiscale method to three heterogeneous models show that our multiscale method can effectively model the elastic wave propagation in anisotropic media with a significant reduction in the degrees of freedom in the modeling system.

Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction

Science.gov (United States)

Li, Zhijin; Chao, Yi; Li, P. Peggy

2012-01-01

A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.

Estimation and calibration of observation impact signals using the Lanczos method in NOAA/NCEP data assimilation system

Directory of Open Access Journals (Sweden)

M. Wei

2012-09-01

Full Text Available Despite the tremendous progress that has been made in data assimilation (DA methodology, observing systems that reduce observation errors, and model improvements that reduce background errors, the analyses produced by the best available DA systems are still different from the truth. Analysis error and error covariance are important since they describe the accuracy of the analyses, and are directly related to the future forecast errors, i.e., the forecast quality. In addition, analysis error covariance is critically important in building an efficient ensemble forecast system (EFS.

Estimating analysis error covariance in an ensemble-based Kalman filter DA is straightforward, but it is challenging in variational DA systems, which have been in operation at most NWP (Numerical Weather Prediction centers. In this study, we use the Lanczos method in the NCEP (the National Centers for Environmental Prediction Gridpoint Statistical Interpolation (GSI DA system to look into other important aspects and properties of this method that were not exploited before. We apply this method to estimate the observation impact signals (OIS, which are directly related to the analysis error variances. It is found that the smallest eigenvalue of the transformed Hessian matrix converges to one as the number of minimization iterations increases. When more observations are assimilated, the convergence becomes slower and more eigenvectors are needed to retrieve the observation impacts. It is also found that the OIS over data-rich regions can be represented by the eigenvectors with dominant eigenvalues.

Since only a limited number of eigenvectors can be computed due to computational expense, the OIS is severely underestimated, and the analysis error variance is consequently overestimated. It is found that the mean OIS values for temperature and wind components at typical model levels are increased by about 1.5 times when the number of eigenvectors is doubled

Implementation and testing of a simple data assimilation algorithm in the regional air pollution forecast model, DEOM

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J. Frydendall

2009-08-01

Full Text Available A simple data assimilation algorithm based on statistical interpolation has been developed and coupled to a long-range chemistry transport model, the Danish Eulerian Operational Model (DEOM, applied for air pollution forecasting at the National Environmental Research Institute (NERI, Denmark. In this paper, the algorithm and the results from experiments designed to find the optimal setup of the algorithm are described. The algorithm has been developed and optimized via eight different experiments where the results from different model setups have been tested against measurements from the EMEP (European Monitoring and Evaluation Programme network covering a half-year period, April–September 1999. The best performing setup of the data assimilation algorithm for surface ozone concentrations has been found, including the combination of determining the covariances using the Hollingsworth method, varying the correlation length according to the number of adjacent observation stations and applying the assimilation routine at three successive hours during the morning. Improvements in the correlation coefficient in the range of 0.1 to 0.21 between the results from the reference and the optimal configuration of the data assimilation algorithm, were found. The data assimilation algorithm will in the future be used in the operational THOR integrated air pollution forecast system, which includes the DEOM.

The Multi-Wave Method for Exact Solutions of Nonlinear Partial Differential Equations

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Yusuf Pandir

2018-02-01

Full Text Available In this research, we use the multi-wave method to obtain new exact solutions for generalized forms of 5th order KdV equation and fth order KdV (fKdV equation with power law nonlinearity. Computations are performed with the help of the mathematics software Mathematica. Then, periodic wave solutions, bright soliton solutions and rational function solutions with free parameters are obtained by this approach. It is shown that this method is very useful and effective.

Ultrasonic Guided Wave Method For Crack Detection In Buried Plastic Pipe

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Wan Hamat Wan Sofian

2016-01-01

Full Text Available Plastic pipe are widely used in many fields for the fluid or gaseous product conveyance but basic components of a plastic material made it very sensitive to damage, which requires techniques for detecting damage reliable and efficient. Ultrasonic guided wave is a sensitive method based on propagation of low-frequency excitation in solid structures for damage detection. Ultrasonic guided wave method are performed to investigate the effect of crack to the frequency signal using Fast Fourier Transform (FFT analysis. This paper researched to determine performance of ultrasonic guided wave method in order to detect crack in buried pipeline. It was found that for an uncrack pipe, FFT analysis shows one peak which is the operating frequency by the piezoelectric actuator itself while the FFT analysis for single cracked pipe shows two peak which is the operating frequency by the piezoelectric actuator itself and the resultant frequency from the crack. For multi cracked pipe, the frequency signal shows more than two peak depend the number of crack. The results presented here may facilitate improvements in the accuracy and precision of pipeline crack detection.

Site Classification using Multichannel Channel Analysis of Surface Wave (MASW) method on Soft and Hard Ground

Science.gov (United States)

Ashraf, M. A. M.; Kumar, N. S.; Yusoh, R.; Hazreek, Z. A. M.; Aziman, M.

2018-04-01

Site classification utilizing average shear wave velocity (Vs(30) up to 30 meters depth is a typical parameter. Numerous geophysical methods have been proposed for estimation of shear wave velocity by utilizing assortment of testing configuration, processing method, and inversion algorithm. Multichannel Analysis of Surface Wave (MASW) method is been rehearsed by numerous specialist and professional to geotechnical engineering for local site characterization and classification. This study aims to determine the site classification on soft and hard ground using MASW method. The subsurface classification was made utilizing National Earthquake Hazards Reduction Program (NERHP) and international Building Code (IBC) classification. Two sites are chosen to acquire the shear wave velocity which is in the state of Pulau Pinang for soft soil and Perlis for hard rock. Results recommend that MASW technique can be utilized to spatially calculate the distribution of shear wave velocity (Vs(30)) in soil and rock to characterize areas.

Dispersive photonic crystals from the plane wave method

Energy Technology Data Exchange (ETDEWEB)

Guevara-Cabrera, E.; Palomino-Ovando, M.A. [Facultad de Ciencias Físico Matemáticas, Benemérita Universidad Autónoma de Puebla, Apdo. Post. 165, Puebla, Pue. 72000, México (Mexico); Flores-Desirena, B., E-mail: bflores@fcfm.buap.mx [Facultad de Ciencias Físico Matemáticas, Benemérita Universidad Autónoma de Puebla, Apdo. Post. 165, Puebla, Pue. 72000, México (Mexico); Gaspar-Armenta, J.A. [Departamento de Investigación en Física de la Universidad de Sonora Apdo, Post 5-088, Hermosillo Sonora 83190, México (Mexico)

2016-03-01

Nowadays photonic crystals are widely used in many different applications. One of the most used methods to compute their band structure is the plane wave method (PWM). However, it can only be applied directly to non-dispersive media and be extended to systems with a few model dielectric functions. We explore an extension of the PWM to photonic crystals containing dispersive materials, that solves an eigenvalue equation for the Bloch wave vectors. First we compare our calculation with analytical results for one dimensional photonic crystals containing Si using experimental values of its optical parameters, and obtainig very well agreement, even for the spectrum region with strong absorption. Then, using the same method, we computed the band structure for a two dimensional photonic crystal without absorption, formed by an square array of MgO cylinders in air. The optical parameters for MgO were modeled with the Lorentz dielectric function. Finally, we studied an array of MgO cylinders in a metal, using Drude model without absorption, for the metal dielectric function. For this last case, we study the gap–midgap ratio as a function of the filling fraction for both the square and triangular lattice. The gap–midgap ratio is larger for the triangular lattice, with a maximum value of 10% for a filling fraction of 0.6. Our results show that the method can be applied to dispersive materials, and then to a wide range of applications where photonic crystals can be used.

Assimilation scheme of the Mediterranean Forecasting System: operational implementation

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E. Demirov

Full Text Available This paper describes the operational implementation of the data assimilation scheme for the Mediterranean Forecasting System Pilot Project (MFSPP. The assimilation scheme, System for Ocean Forecast and Analysis (SOFA, is a reduced order Optimal Interpolation (OI scheme. The order reduction is achieved by projection of the state vector into vertical Empirical Orthogonal Functions (EOF. The data assimilated are Sea Level Anomaly (SLA and temperature profiles from Expandable Bathy Termographs (XBT. The data collection, quality control, assimilation and forecast procedures are all done in Near Real Time (NRT. The OI is used intermittently with an assimilation cycle of one week so that an analysis is produced once a week. The forecast is then done for ten days following the analysis day. The root mean square (RMS between the model forecast and the analysis (the forecast RMS is below 0.7°C in the surface layers and below 0.2°C in the layers deeper than 200 m for all the ten forecast days. The RMS between forecast and initial condition (persistence RMS is higher than forecast RMS after the first day. This means that the model improves forecast with respect to persistence. The calculation of the misfit between the forecast and the satellite data suggests that the model solution represents well the main space and time variability of the SLA except for a relatively short period of three – four weeks during the summer when the data show a fast transition between the cyclonic winter and anti-cyclonic summer regimes. This occurs in the surface layers that are not corrected by our assimilation scheme hypothesis. On the basis of the forecast skill scores analysis, conclusions are drawn about future improvements.

Key words. Oceanography; general (marginal and semi-enclosed seas; numerical modeling; ocean prediction

Assimilation scheme of the Mediterranean Forecasting System: operational implementation

Directory of Open Access Journals (Sweden)

E. Demirov

2003-01-01

Full Text Available This paper describes the operational implementation of the data assimilation scheme for the Mediterranean Forecasting System Pilot Project (MFSPP. The assimilation scheme, System for Ocean Forecast and Analysis (SOFA, is a reduced order Optimal Interpolation (OI scheme. The order reduction is achieved by projection of the state vector into vertical Empirical Orthogonal Functions (EOF. The data assimilated are Sea Level Anomaly (SLA and temperature profiles from Expandable Bathy Termographs (XBT. The data collection, quality control, assimilation and forecast procedures are all done in Near Real Time (NRT. The OI is used intermittently with an assimilation cycle of one week so that an analysis is produced once a week. The forecast is then done for ten days following the analysis day. The root mean square (RMS between the model forecast and the analysis (the forecast RMS is below 0.7°C in the surface layers and below 0.2°C in the layers deeper than 200 m for all the ten forecast days. The RMS between forecast and initial condition (persistence RMS is higher than forecast RMS after the first day. This means that the model improves forecast with respect to persistence. The calculation of the misfit between the forecast and the satellite data suggests that the model solution represents well the main space and time variability of the SLA except for a relatively short period of three – four weeks during the summer when the data show a fast transition between the cyclonic winter and anti-cyclonic summer regimes. This occurs in the surface layers that are not corrected by our assimilation scheme hypothesis. On the basis of the forecast skill scores analysis, conclusions are drawn about future improvements. Key words. Oceanography; general (marginal and semi-enclosed seas; numerical modeling; ocean prediction

Study of Wave-Particle Interactions for Whistler Mode Waves at Oblique Angles by Utilizing the Gyroaveraging Method

Science.gov (United States)

Hsieh, Yi-Kai; Omura, Yoshiharu

2017-10-01

We investigate the properties of whistler mode wave-particle interactions at oblique wave normal angles to the background magnetic field. We find that electromagnetic energy of waves at frequencies below half the electron cyclotron frequency can flow nearly parallel to the ambient magnetic field. We thereby confirm that the gyroaveraging method, which averages the cyclotron motion to the gyrocenter and reduces the simulation from two-dimensional to one-dimensional, is valid for oblique wave-particle interaction. Multiple resonances appear for oblique propagation but not for parallel propagation. We calculate the possible range of resonances with the first-order resonance condition as a function of electron kinetic energy and equatorial pitch angle. To reveal the physical process and the efficiency of electron acceleration by multiple resonances, we assume a simple uniform wave model with constant amplitude and frequency in space and time. We perform test particle simulations with electrons starting at specific equatorial pitch angles and kinetic energies. The simulation results show that multiple resonances contribute to acceleration and pitch angle scattering of energetic electrons. Especially, we find that electrons with energies of a few hundred keV can be accelerated efficiently to a few MeV through the n = 0 Landau resonance.

Data Assimilation by Conditioning of Driving Noise on Future Observations

KAUST Repository

Lee, Wonjung

2014-08-01

Conventional recursive filtering approaches, designed for quantifying the state of an evolving stochastic dynamical system with intermittent observations, use a sequence of i) an uncertainty propagation step followed by ii) a step where the associated data is assimilated using Bayes\\' rule. Alternatively, the order of the steps can be switched to i) one step ahead data assimilation followed by ii) uncertainty propagation. In this paper, we apply this smoothing-based sequential filter to systems driven by random noise, however with the conditioning on future observation not only to the system variable but to the driving noise. Our research reveals that, for the nonlinear filtering problem, the conditioned driving noise is biased by a nonzero mean and in turn pushes forward the filtering solution in time closer to the true state when it drives the system. As a result our proposed method can yield a more accurate approximate solution for the state estimation problem. © 1991-2012 IEEE.

Assimilate partitioning during reproductive growth

International Nuclear Information System (INIS)

Finazzo, S.F.; Davenport, T.L.

1987-01-01

Leaves having various phyllotactic relationships to fruitlets were labeled for 1 hour with 10/sub r/Ci of 14 CO 2 . Fruitlets were also labeled. Fruitlets did fix 14 CO 2 . Translocation of radioactivity from the peel into the fruit occurred slowly and to a limited extent. No evidence of translocation out of the fruitlets was observed. Assimilate partitioning in avocado was strongly influenced by phyllotaxy. If a fruit and the labeled leaf had the same phyllotaxy then greater than 95% of the radiolabel was present in this fruit. When the fruit did not have the same phyllotaxy as the labeled leaf, the radiolabel distribution was skewed with 70% of the label going to a single adjacent position. Avocado fruitlets exhibit uniform labeling throughout a particular tissue. In avocado, assimilates preferentially move from leaves to fruits with the same phyllotaxy

Snow multivariable data assimilation for hydrological predictions in mountain areas

Science.gov (United States)

Piazzi, Gaia; Campo, Lorenzo; Gabellani, Simone; Rudari, Roberto; Castelli, Fabio; Cremonese, Edoardo; Morra di Cella, Umberto; Stevenin, Hervé; Ratto, Sara Maria

2016-04-01

The seasonal presence of snow on alpine catchments strongly impacts both surface energy balance and water resource. Thus, the knowledge of the snowpack dynamics is of critical importance for several applications, such as water resource management, floods prediction and hydroelectric power production. Several independent data sources provide information about snowpack state: ground-based measurements, satellite data and physical models. Although all these data types are reliable, each of them is affected by specific flaws and errors (respectively dependency on local conditions, sensor biases and limitations, initialization and poor quality forcing data). Moreover, there are physical factors that make an exhaustive reconstruction of snow dynamics complicated: snow intermittence in space and time, stratification and slow phenomena like metamorphism processes, uncertainty in snowfall evaluation, wind transportation, etc. Data Assimilation (DA) techniques provide an objective methodology to combine observational and modeled information to obtain the most likely estimate of snowpack state. Indeed, by combining all the available sources of information, the implementation of DA schemes can quantify and reduce the uncertainties of the estimations. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model, strengthened by a robust multivariable data assimilation algorithm. The model is physically based on mass and energy balances and can be used to reproduce the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity, relative air humidity, precipitation and incident solar radiation) to provide a complete estimate of snowpack state. The implementation of an Ensemble Kalman Filter (EnKF) scheme enables to assimilate simultaneously ground