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Abstract Post Hurricane Abnormal Water Level (PHAWL) poses a persistent inundation threat to coastal communities, yet unresolved knowledge gaps exist regarding its spatiotemporal impacts and causal mechanisms. Using a high-resolution coastal model with a set of observations, we find that the PHAWLs are up to 50 cm higher than the normal water levels for several weeks and cause delayed inundations around residential areas of the U.S. Southeast Coast (USSC). Numerical experiments reveal that while atmospheric forcing modulates the coastal PHAWLs, ocean dynamics primarily driven by the Gulf Stream control the mean component and duration of the shelf-scale PHAWLs. Because of the large spatial impact of the post-hurricane oceanic forcing, the coastal hazards are not limited to a direct hit from a hurricane but can be detected throughout the USSC where the oceanic processes reach.

Abstract While there is evidence for an acceleration in global mean sea level (MSL) since the 1960s, its detection at local levels has been hampered by the considerable influence of natural variability on the rate of MSL change. Here we report a MSL acceleration in tide gauge records along the U.S. Southeast and Gulf coasts that has led to rates (>10 mm yr−1 since 2010) that are unprecedented in at least 120 years. We show that this acceleration is primarily induced by an ocean dynamic signal exceeding the externally forced response from historical climate model simulations. However, when the simulated forced response is removed from observations, the residuals are neither historically unprecedented nor inconsistent with internal variability in simulations. A large fraction of the residuals is consistent with wind driven Rossby waves in the tropical North Atlantic. This indicates that this ongoing acceleration represents the compounding effects of external forcing and internal climate variability.

Abstract Recent studies appear to show that a “hot spot” for accelerated sea level rise (SLR) shifted around 2010 from the Mid‐Atlantic Bight (MAB) to the South Atlantic Bight (SAB) and south Florida. The role of the Gulf Stream (GS) in this shift was thus investigated. The findings show that in the ~15–20 years before, SLR was accelerating in the MAB due to weakening and southward shifting of the GS. After 2010, however, SLR started slowing down in the MAB due to strengthening and northward shifting of the GS. Thermosteric effects seen in altimeter data indicate a warming trend south of 35°N that started around 2010 and contributed to increased SLR south of Cape Hatteras. However, in the MAB, after the GS separated from the coast, the warming of the Subtropical Gyre and cooling of nearshore waters resulted in an opposite SLR response and strengthening of the GS front. Oscillations with periods of 2–5 years dominated the GS flow and coastal sea level variability, but the GS in the MAB is often out of phase with the GS in the SAB due to eddies and recirculation gyres. These oscillations can create temporal changes in SLR rates that are ~10 times larger than the long‐term trend, so recent changes in the local “hot spot” may not be interpreted as a sign of a shift in the long‐term trend, but more likely a temporal shift associated with interannual and decadal variations in the North Atlantic.

A major challenge for managing impacts and implementing effective mitigation measures and adaptation strategies for coastal zones affected by future sea level (SL) rise is our limited capacity to predict SL change at the coast on relevant spatial and temporal scales. Predicting coastal SL requires the ability to monitor and simulate a multitude of physical processes affecting SL, from local effects of wind waves and river runoff to remote influences of the large-scale ocean circulation on the coast. Here we assess our current understanding of the causes of coastal SL variability on monthly to multi-decadal timescales, including geodetic, oceanographic and atmospheric aspects of the problem, and review available observing systems informing on coastal SL. We also review the ability of existing models and data assimilation systems to estimate coastal SL variations and of atmosphere-ocean global coupled models and related regional downscaling efforts to project future SL changes. We discuss (1) observational gaps and uncertainties, and priorities for the development of an optimal and integrated coastal SL observing system, (2) strategies for advancing model capabilities in forecasting short-term processes and projecting long-term changes affecting coastal SL, and (3) possible future developments of sea level services enabling better connection of scientists and user communities and facilitating assessment and decision making for adaptation to future coastal SL change.

The southern Caribbean Sea experiences strong coastal upwelling between December and April due to the seasonal strengthening of the trade winds. A second upwelling was recently detected in the southeastern Caribbean during June–August, when local coastal wind intensities weaken. Using synoptic satellite measurements and in situ data, this mid-year upwelling was characterized in terms of surface and subsurface temperature structures, and its mechanisms were explored. The mid-year upwelling lasts 6–9 weeks with satellite sea surface temperature (SST) ~1–2° C warmer than the primary upwelling. Three possible upwelling mechanisms were analyzed: cross-shore Ekman transport (csET) due to alongshore winds, wind curl (Ekman pumping/suction) due to wind spatial gradients, and dynamic uplift caused by variations in the strength/position of the Caribbean Current. These parameters were derived from satellite wind and altimeter observations. The principal and the mid-year upwelling were driven primarily by csET (78–86%). However, SST had similar or better correlations with the Ekman pumping/suction integrated up to 100 km offshore (WE100) than with csET, possibly due to its influence on the isopycnal depth of the source waters for the coastal upwelling. The mid-year upwelling was not caused by dynamic uplift but it might have been enhanced by the seasonal intensification of the Caribbean Current during that period.

While global mean sea level rise (SLR) and acceleration (SLA) are indicators of climate change and are informative regarding the current state of the climate, assessments of regional and local SLR are essential for policy makers responding to, and preparing for, changes in sea level. In this work, three acceleration detection techniques are used to demonstrate the robust SLA in the China Seas. Interannual to multidecadal sea level variations (periods >2 years), which are mainly related to natural internal climate variability and significantly affect estimation of sea level acceleration, are removed with empirical mode decomposition (EMD) analysis prior to the acceleration determination. Consistent SLAs of 0.085 ± 0.020 mm·yr−2 (1950–2013) and 0.074 ± 0.032 mm·yr−2 (1959–2013) in regional tide gauge records are shown to result from the three applied approaches in the Bohai Sea (BS) and East China Sea (ECS), respectively. The SLAs can be detected in records as short as 20 years if long-term sea level variability is adequately removed. The spatial distribution of SLA derived from a sea level reconstruction shows significant SLA in the BS, Yellow Sea (YS) and Yangtze River Estuary.

A propagation method for time-dependent Schrödinger equations with an explicitly time-dependent Hamiltonian is developed where time ordering is achieved iteratively. The explicit time dependence of the time-dependent Schrödinger equation is rewritten as an inhomogeneous term. At each step of the iteration, the resulting inhomogeneous Schrödinger equation is solved with the Chebychev propagation scheme presented in the work of M. Ndong et al. [J. Chem. Phys. 130, 124108 (2009)]. The iteratively time-ordering Chebychev propagator is shown to be robust, efficient, and accurate and compares very favorably with all other available propagation schemes. [ABSTRACT FROM AUTHOR]

A propagation scheme for time-dependent inhomogeneous Schrödinger equations is presented. Such equations occur in time dependent optimal control theory and in reactive scattering. A formal solution based on a polynomial expansion of the inhomogeneous term is derived. It is subjected to an approximation in terms of Chebychev polynomials. Different variants for the inhomogeneous propagator are demonstrated and applied to two examples from optimal control theory. Convergence behavior and numerical efficiency are analyzed. [ABSTRACT FROM AUTHOR]

A uniformly convergent propagation scheme designed for non-hermitian Hamiltonian operators is presented. The method is based on a Newtonian interpolation polynomial which is created by a recursive application of the Hamiltonian operator on an initial wavefunction. The interpolation points used to construct the Newtonian polynomial are located in the complex eigenvalue space of the Hamiltonian. A new algorithm is developed to construct the interpolation points. Both time dependent and time independent quantities can be obtained using the same polynomial expansion. The method is particularly useful when negative imaginary potentials are used. The photodissociation dynamics of I3- is studied as an example of the utility of the scheme to gain insight on a dynamical encounter. The bond cleavage is followed in time simultaneously with the calculation of the Raman spectra. The study addresses the role of vibrational excitation of the reactant I3- on the nascent I2- spectral modulations and Raman spectra. © 1995 American Institute of Physics. [ABSTRACT FROM AUTHOR]

Eigenvalues and eigenvectors are an essential theme in numerical linear algebra. Their study is mainly motivated by their high importance in a wide range of applications. Knowledge of eigenvalues is essential in quantum molecular science. Solutions of the Schrödinger equation for the electrons composing the molecule are the basis of electronic structure theory. Electronic eigenvalues compose the potential energy surfaces for nuclear motion. The eigenvectors allow calculation of diople transition matrix elements, the core of spectroscopy. The vibrational dynamics molecule also requires knowledge of the eigenvalues of the vibrational Hamiltonian. Typically in these problems, the dimension of Hilbert space is huge. Practically, only a small subset of eigenvalues is required. In this paper, we present a highly efficient algorithm, named EvArnoldi, for solving the large-scale eigenvalues problem. The algorithm, in its basic formulation, is mathematically equivalent to ARPACK (Sorensen, D. C. Implicitly Restarted Arnoldi/Lanczos Methods for Large Scale Eigenvalue Calculations; Springer, 1997; Lehoucq, R. B.; Sorensen, D. C. SIAM Journal on Matrix Analysis and Applications 1996, 17, 789; Calvetti, -D.; Reichel, L.; Sorensen, D. C. Electronic Transactions on Numerical Analysis 1994, 2, 21) (or Eigs of Matlab) but significantly simpler. [ABSTRACT FROM AUTHOR]

A new scheme for the calculation of spatial derivatives has been developed. The technique is based on recursive derivative operators that are generated by an L∞ fit in the spectral domain. The use of recursive operators enables us to extend acoustic and elastic wave simulations to shorter wavelengths. The method is applied to the numerical solution of the 2D acoustic wave equation and to the solution of the equations of 2D dynamic elasticity in an isotropic medium. An example of reverse-time migration of a synthetic data set shows that the numerical dispersion can be significantly reduced with respect to schemes that are based on finite differences. The method is tested for the solutions of the equations of dynamic elasticity by comparing numerical and analytic solutions to Lamb's problem. [ABSTRACT FROM AUTHOR]

The innermost computational kernel of many large-scale scientific applications is often a large set of linear equations of the form Ax = b which typically consumes a significant portion of the overall computational time required by the simulation. The traditional approach for solving this problem is to use direct methods. This approach is often preferred in industry because direct solvers are robust and effective for moderate size problems. However, direct methods can consume a huge amount of memory, and CPU time, in large-scale cases. In these cases, iterative techniques are the only viable alternative. Unfortunately, iterative methods lack the robustness of direct methods. The situation is especially difficult when the matrix is nonsymmetric. A lot of research has been devoted to trying to develop a robust iterative algorithm for nonsymmetric systems. The present paper describes a new robust and efficient algorithm aimed at solving iteratively nonsymmetric linear systems. It is based on looking for an approximation to the "optimal" polynomial Pm(z) which satisfies ∥Pm(z)∥∞ = minQϵIIm ∥Q(z)∥∞, z ϵ D, where IIm is the set of all polynomials of degree m which satisfies Qm(0) = 1 and D is a domain in the complex plane which includes all the eigenvalues of A. The resulting algorithm is an efficient one, especially in the case where we have a set of linear systems which share the same matrix A. We present several applications, including the exterior Helmholtz problem, which leads to a large indefinite, nonsymmetric, and complex system. [ABSTRACT FROM AUTHOR]

Long-term hydrographic temperature and salinity transect data in the East China Sea from June 1955 to November 2001 are analyzed in order to examine the geostrophic velocity and the structure of the Kuroshio current. The structure of the Kuroshio Current is divided into three basic forms, a single-core structure, a double-core structure and a multi-core structure; the appearance percentage of the three forms are 53.1%, 31.4%, and 15.4%, respectively. The analysis suggests that multi-core structures have significant seasonal and interannual variabilities that are not fully understood but may relate to variations in transport and associated flow instabilities. The Kuroshio's spatial character is also analyzed in detail by applying a simplified model of motion instability into this multi-core structure of the East China Sea Kuroshio. The theoretical results are found to be consistent with the observations, suggesting that the instability of the Kuroshio in the East China Sea may bring forth the formation of the observed multi-core structure. [ABSTRACT FROM AUTHOR]

We introduce a Locally Optimal Projection operator (LOP) for surface approximation from point-set data. The operator is parameterization free, in the sense that it does not rely on estimating a local normal, fitting a local plane, or using any other local parametric representation. Therefore, it can deal with noisy data which clutters the orientation of the points. The method performs well in cases of ambiguous orientation, e.g., if two folds of a surface lie near each other, and other cases of complex geometry in which methods based upon local plane fitting may fail. Although defined by a global minimization problem, the method is effectively local, and it provides a second order approximation to smooth surfaces. Hence allowing good surface approximation without using any explicit or implicit approximation space. Furthermore, we show that LOP is highly robust to noise and outliers and demonstrate its effectiveness by applying it to raw scanned data of complex shapes. [ABSTRACT FROM AUTHOR]

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