19 resultados para Schwinger variational method

em CentAUR: Central Archive University of Reading - UK


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The triatomic spin-rovibronic variational code RVIB3 has been extended to include the effect of two uncoupled electrons, for both (3)Sigma(-) and (3)Pi (Renner-Teller) electronic states. The spin-orbital-rotational kinetic energy is included in the usual way, via terms (J+L+S). The phenomenological terms AL.S and lambda 2/3(3S(z)(2)) are introduced to reproduce the 3 spin-orbit and spin-spin splittings, respectively. Calculations are performed to evaluate the spin-rovibronic energy levels of CCO (X) over tilde (3) Sigma(-) and CCO (A) over tilde (3) Pi for which the Born-Oppenheimer potentials are derived from high-accuracy ab initio calculations.

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Liquid clouds play a profound role in the global radiation budget but it is difficult to remotely retrieve their vertical profile. Ordinary narrow field-of-view (FOV) lidars receive a strong return from such clouds but the information is limited to the first few optical depths. Wideangle multiple-FOV lidars can isolate radiation scattered multiple times before returning to the instrument, often penetrating much deeper into the cloud than the singly-scattered signal. These returns potentially contain information on the vertical profile of extinction coefficient, but are challenging to interpret due to the lack of a fast radiative transfer model for simulating them. This paper describes a variational algorithm that incorporates a fast forward model based on the time-dependent two-stream approximation, and its adjoint. Application of the algorithm to simulated data from a hypothetical airborne three-FOV lidar with a maximum footprint width of 600m suggests that this approach should be able to retrieve the extinction structure down to an optical depth of around 6, and total opticaldepth up to at least 35, depending on the maximum lidar FOV. The convergence behavior of Gauss-Newton and quasi-Newton optimization schemes are compared. We then present results from an application of the algorithm to observations of stratocumulus by the 8-FOV airborne “THOR” lidar. It is demonstrated how the averaging kernel can be used to diagnose the effective vertical resolution of the retrieved profile, and therefore the depth to which information on the vertical structure can be recovered. This work enables exploitation of returns from spaceborne lidar and radar subject to multiple scattering more rigorously than previously possible.

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The vibrational energy levels of diazocarbene (diazomethylene) in its electronic ground state, (X) over tilde (3) Sigma(-) CNN, have been predicted using the variational method. The potential energy surfaces of (X) over tilde (3) A" CNN were determined by employing ab initio single reference coupled cluster with single and double excitations (CCSD), CCSD with perturbative triple excitations [CCSD(T)], multi-reference complete active space self-consistent-field (CASSCF), and internally contracted multi-reference configuration interaction (ICMRCI) methods. The correlation-consistent polarised valence quadruple zeta (cc-pVQZ) basis set was used. Four sets of vibrational energy levels determined from the four distinct analytical potential functions have been compared with the experimental values from the laser-induced fluorescence measurements of Wurfel et al. obtained in 1992. The CCSD, CCSD(T), and CASSCF potentials have not provided satisfactory agreement with the experimental observations. In this light, the importance of both non-dynamic (static) and dynamic correlation effects in describing the ground state of CNN is emphasised. Our best theoretical fundamental frequencies at the cc-pVQZ ICMRCI level of theory, v(1) = 1230, v(2) = 394, and v(3) = 1420 cm(-1) are in excellent agreement with the experimental values of v(1) = 1235, v(2) = 396, and v(3) = 1419cm(-1) and the mean absolute deviation between the 23 calculated and experimental vibrational energy levels is only 7.4 cm(-1). It is shown that the previously suggested observation of the v(3) frequency at about 2847cm(-1) was in fact the first overtone 2v(3).

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The vibrational-rotational energy levels of aluminum monohydroxide in its electronic ground state, (A) over tilde (1)A' AlOH, have been predicted using the variational method. The potential energy surface of the (X) over tilde (1)A' ground state of AlOH was determined employing the ab initio coupled cluster method with single, double, and perturbative triple excitations [CCSD(T)] and the correlation-consistent polarized valence quadruple zeta (cc-pVQZ) basis set. Low-lying J= 0 and J= 1 vibrational levels are reported. These are analyzed in terms of the quasilinearity of the molecule. Coriolis effects are shown to be significant. We hope that our predictions will be of value in the future when assigning rovibrational transitions in spectroscopic studies. (c) 2006 Elsevier B.V. All rights reserved.

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The theory of dipole-allowed absorption intensities in triatomic molecules is presented for systems with three close-lying electronic states of doublet multiplicity. Its derivation is within the framework of a recently developed variational method [CARTER, S., HANDY, N. C., PUZZARINI, C., TARRONI, R., and PALMIERI, P., 2000, Molec. Phys., 98,1967]. The method has been applied to the calculation of the infrared absorption spectrum of the C2H radical and its deuterated isotopomer for energies up to 10000 cm(-1) above the ground state, using highly accurate ab initio diabatic potential energy and dipole moment surfaces. The calculated spectra agree very well with those recorded experimentally in a neon matrix [FORNEY, D., JACOX, M. E., and THOMPSON, W. E., 1995, J. molee. Spectrosc., 170, 178] and assignments in the high energy region of the IR spectra are proposed for the first time.

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The three lowest (1(2)A('), 2(2)A('), and 1(2)A(')) potential-energy surfaces of the C2Cl radical, correlating at linear geometries with (2)Sigma(+) and (2)Pi states, have been studied ab initio using a large basis set and multireference configuration-interaction techniques. The electronic ground state is confirmed to be bent with a very low barrier to linearity, due to the strong nonadiabatic electronic interactions taking place in this system. The rovibronic energy levels of the (CCCl)-C-12-C-12-Cl-35 isotopomer and the absolute absorption intensities at a temperature of 5 K have been calculated, to an upper limit of 2000 cm(-1), using diabatic potential-energy and dipole moment surfaces and a recently developed variational method. The resulting vibronic states arise from a strong mixture of all the three electronic components and their assignments are intrinsically ambiguous. (c) 2005 American Institute of Physics.

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The first three electronic states (1(2)A', 2(2)A', 1(2)A '') of the C2Br radical, correlating at linear geometries with (2)Sigma(+) and (2)Pi states, have been studied ab initio, using Multi Reference Configuration Interaction techniques. The electronic ground state is found to have a bent equilibrium geometry, R-CC = 1.2621 angstrom, R-CBr = 1.7967 angstrom, < CCBr 156.1 degrees, with a very low barrier to linearity. Similarly to the valence isoelectronic radicals C2F and C2Cl, this anomalous behaviour is attributed to a strong three-state non-adiabatic electronic interaction. The Sigma, Pi(1/2), Pi(3/2) vibronic energy levels and their absolute infrared absorption intensities at a temperature of 5K have been calculated for the (CCBr)-C-12-C-12-Br-79 isotopomer, to an upper limit of 2000 cm(-1), using ab initio diabatic potential energy and dipole moment surfaces and a recently developed variational method.

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The background error covariance matrix, B, is often used in variational data assimilation for numerical weather prediction as a static and hence poor approximation to the fully dynamic forecast error covariance matrix, Pf. In this paper the concept of an Ensemble Reduced Rank Kalman Filter (EnRRKF) is outlined. In the EnRRKF the forecast error statistics in a subspace defined by an ensemble of states forecast by the dynamic model are found. These statistics are merged in a formal way with the static statistics, which apply in the remainder of the space. The combined statistics may then be used in a variational data assimilation setting. It is hoped that the nonlinear error growth of small-scale weather systems will be accurately captured by the EnRRKF, to produce accurate analyses and ultimately improved forecasts of extreme events.

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Data assimilation is a sophisticated mathematical technique for combining observational data with model predictions to produce state and parameter estimates that most accurately approximate the current and future states of the true system. The technique is commonly used in atmospheric and oceanic modelling, combining empirical observations with model predictions to produce more accurate and well-calibrated forecasts. Here, we consider a novel application within a coastal environment and describe how the method can also be used to deliver improved estimates of uncertain morphodynamic model parameters. This is achieved using a technique known as state augmentation. Earlier applications of state augmentation have typically employed the 4D-Var, Kalman filter or ensemble Kalman filter assimilation schemes. Our new method is based on a computationally inexpensive 3D-Var scheme, where the specification of the error covariance matrices is crucial for success. A simple 1D model of bed-form propagation is used to demonstrate the method. The scheme is capable of recovering near-perfect parameter values and, therefore, improves the capability of our model to predict future bathymetry. Such positive results suggest the potential for application to more complex morphodynamic models.

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This paper aims to summarise the current performance of ozone data assimilation (DA) systems, to show where they can be improved, and to quantify their errors. It examines 11 sets of ozone analyses from 7 different DA systems. Two are numerical weather prediction (NWP) systems based on general circulation models (GCMs); the other five use chemistry transport models (CTMs). The systems examined contain either linearised or detailed ozone chemistry, or no chemistry at all. In most analyses, MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) ozone data are assimilated; two assimilate SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Chartography) observations instead. Analyses are compared to independent ozone observations covering the troposphere, stratosphere and lower mesosphere during the period July to November 2003. Biases and standard deviations are largest, and show the largest divergence between systems, in the troposphere, in the upper-troposphere/lower-stratosphere, in the upper-stratosphere and mesosphere, and the Antarctic ozone hole region. However, in any particular area, apart from the troposphere, at least one system can be found that agrees well with independent data. In general, none of the differences can be linked to the assimilation technique (Kalman filter, three or four dimensional variational methods, direct inversion) or the system (CTM or NWP system). Where results diverge, a main explanation is the way ozone is modelled. It is important to correctly model transport at the tropical tropopause, to avoid positive biases and excessive structure in the ozone field. In the southern hemisphere ozone hole, only the analyses which correctly model heterogeneous ozone depletion are able to reproduce the near-complete ozone destruction over the pole. In the upper-stratosphere and mesosphere (above 5 hPa), some ozone photochemistry schemes caused large but easily remedied biases. The diurnal cycle of ozone in the mesosphere is not captured, except by the one system that includes a detailed treatment of mesospheric chemistry. These results indicate that when good observations are available for assimilation, the first priority for improving ozone DA systems is to improve the models. The analyses benefit strongly from the good quality of the MIPAS ozone observations. Using the analyses as a transfer standard, it is seen that MIPAS is similar to 5% higher than HALOE (Halogen Occultation Experiment) in the mid and upper stratosphere and mesosphere (above 30 hPa), and of order 10% higher than ozonesonde and HALOE in the lower stratosphere (100 hPa to 30 hPa). Analyses based on SCIAMACHY total column are almost as good as the MIPAS analyses; analyses based on SCIAMACHY limb profiles are worse in some areas, due to problems in the SCIAMACHY retrievals.

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We have favoured the variational (secular equation) method for the determination of the (ro-) vibrational energy levels of polyatomic molecules. We use predominantly the Watson Hamiltonian in normal coordinates and an associated given potential in the variational code 'Multimode'. The dominant cost is the construction and diagonalization of matrices of ever-increasing size. Here we address this problem, using pertubation theory to select dominant expansion terms within the Davidson-Liu iterative diagonalization method. Our chosen example is the twelve-mode molecule methanol, for which we have an ab initio representation of the potential which includes the internal rotational motion of the OH group relative to CH3. Our new algorithm allows us to obtain converged energy levels for matrices of dimensions in excess of 100 000.

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We consider four-dimensional variational data assimilation (4DVar) and show that it can be interpreted as Tikhonov or L2-regularisation, a widely used method for solving ill-posed inverse problems. It is known from image restoration and geophysical problems that an alternative regularisation, namely L1-norm regularisation, recovers sharp edges better than L2-norm regularisation. We apply this idea to 4DVar for problems where shocks and model error are present and give two examples which show that L1-norm regularisation performs much better than the standard L2-norm regularisation in 4DVar.

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This paper describes the implementation of a 3D variational (3D-Var) data assimilation scheme for a morphodynamic model applied to Morecambe Bay, UK. A simple decoupled hydrodynamic and sediment transport model is combined with a data assimilation scheme to investigate the ability of such methods to improve the accuracy of the predicted bathymetry. The inverse forecast error covariance matrix is modelled using a Laplacian approximation which is calibrated for the length scale parameter required. Calibration is also performed for the Soulsby-van Rijn sediment transport equations. The data used for assimilation purposes comprises waterlines derived from SAR imagery covering the entire period of the model run, and swath bathymetry data collected by a ship-borne survey for one date towards the end of the model run. A LiDAR survey of the entire bay carried out in November 2005 is used for validation purposes. The comparison of the predictive ability of the model alone with the model-forecast-assimilation system demonstrates that using data assimilation significantly improves the forecast skill. An investigation of the assimilation of the swath bathymetry as well as the waterlines demonstrates that the overall improvement is initially large, but decreases over time as the bathymetry evolves away from that observed by the survey. The result of combining the calibration runs into a pseudo-ensemble provides a higher skill score than for a single optimized model run. A brief comparison of the Optimal Interpolation assimilation method with the 3D-Var method shows that the two schemes give similar results.

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We show that the four-dimensional variational data assimilation method (4DVar) can be interpreted as a form of Tikhonov regularization, a very familiar method for solving ill-posed inverse problems. It is known from image restoration problems that L1-norm penalty regularization recovers sharp edges in the image more accurately than Tikhonov, or L2-norm, penalty regularization. We apply this idea from stationary inverse problems to 4DVar, a dynamical inverse problem, and give examples for an L1-norm penalty approach and a mixed total variation (TV) L1–L2-norm penalty approach. For problems with model error where sharp fronts are present and the background and observation error covariances are known, the mixed TV L1–L2-norm penalty performs better than either the L1-norm method or the strong constraint 4DVar (L2-norm)method. A strength of the mixed TV L1–L2-norm regularization is that in the case where a simplified form of the background error covariance matrix is used it produces a much more accurate analysis than 4DVar. The method thus has the potential in numerical weather prediction to overcome operational problems with poorly tuned background error covariance matrices.