scholarly journals STWAVE: Steady-State Spectral Wave Model. Report 1: User's Manual for STWAVE Version 2.0

Author(s):  
Jane M. Smith ◽  
Donald T. Resio ◽  
Alan K. Zundel
2019 ◽  
Vol 55 (2) ◽  
pp. 1279-1295 ◽  
Author(s):  
D. C. Roberts ◽  
P. Moreno‐Casas ◽  
F. A. Bombardelli ◽  
S. J. Hook ◽  
B. R. Hargreaves ◽  
...  

2011 ◽  
Author(s):  
Thomas C. Massey ◽  
Mary E. Anderson ◽  
Jane M. Smith ◽  
Julieta Gomez ◽  
Rusty Jones

2021 ◽  
Author(s):  
Ali Abdolali ◽  
Andre van der Westhuysen ◽  
Zaizhong Ma ◽  
Avichal Mehra ◽  
Aron Roland ◽  
...  

AbstractVarious uncertainties exist in a hindcast due to the inabilities of numerical models to resolve all the complicated atmosphere-sea interactions, and the lack of certain ground truth observations. Here, a comprehensive analysis of an atmospheric model performance in hindcast mode (Hurricane Weather and Research Forecasting model—HWRF) and its 40 ensembles during severe events is conducted, evaluating the model accuracy and uncertainty for hurricane track parameters, and wind speed collected along satellite altimeter tracks and at stationary source point observations. Subsequently, the downstream spectral wave model WAVEWATCH III is forced by two sets of wind field data, each includes 40 members. The first ones are randomly extracted from original HWRF simulations and the second ones are based on spread of best track parameters. The atmospheric model spread and wave model error along satellite altimeters tracks and at stationary source point observations are estimated. The study on Hurricane Irma reveals that wind and wave observations during this extreme event are within ensemble spreads. While both Models have wide spreads over areas with landmass, maximum uncertainty in the atmospheric model is at hurricane eye in contrast to the wave model.


2010 ◽  
Vol 40 (1) ◽  
pp. 155-169 ◽  
Author(s):  
Heidi Pettersson ◽  
Kimmo K. Kahma ◽  
Laura Tuomi

Abstract In slanting fetch conditions the direction of actively growing waves is strongly controlled by the fetch geometry. The effect was found to be pronounced in the long and narrow Gulf of Finland in the Baltic Sea, where it significantly modifies the directional wave climate. Three models with different assumptions on the directional coupling between the wave components were used to analyze the physics responsible for the directional behavior of the waves in the gulf. The directionally decoupled model produced the direction at the spectral peak correctly when the slanting fetch geometry was narrow but gave a weaker steering than observed when the fetch geometry was broader. The method of Donelan estimated well the direction at the spectral peak in well-defined slanting fetch conditions, but overestimated the longer fetch components during wave growth from a more complex shoreline. Neither the decoupled nor the Donelan model reproduced the observed shifting of direction with the frequency. The performance of the third-generation spectral wave model (WAM) in estimating the wave directions was strongly dependent on the grid resolution of the model. The dominant wave directions were estimated satisfactorily when the grid-step size was dropped to 5 km in the gulf, which is 70 km in its narrowest part. A mechanism based on the weakly nonlinear interactions is proposed to explain the strong steering effect in slanting fetch conditions.


Energy ◽  
2021 ◽  
pp. 121404
Author(s):  
Bárður Joensen ◽  
Bárður A. Niclasen ◽  
Harry B. Bingham

Author(s):  
Jane McKee Smith ◽  
Spicer Bak ◽  
Tyler Hesser ◽  
Mary A. Bryant ◽  
Chris Massey

An automated Coastal Model Test Bed has been built for the US Army Corps of Engineers Field Research Facility to evaluate coastal numerical models. In October of 2015, the test bed was expanded during a multi-investigator experiment, called BathyDuck, to evaluate two bathymetry sources: traditional survey data and bathymetry generated through the cBathy inversion algorithm using Argus video measurements. Comparisons were made between simulations using the spectral wave model STWAVE with half-hourly cBathy bathymetry and the more temporally sparse surveyed bathymetry. The simulation results using cBathy bathymetry were relatively close to those using the surveyed bathymetry. The largest differences were at the shallowest gauges within 250 m of the coast, where wave model normalized root-mean-square was approximately twice are large using the cBathy bathymetry. The nearshore errors using the cBathy input were greatest during events with wave height greater than 2 m. For this limited application, the Argus cBathy algorithm proved to be a suitable bathymetry input for nearshore wave modeling. cBathy bathymetry was easily incorporated into the modeling test bed and had the advantage of being updated on approximately the same temporal scale as the other model input conditions. cBathy has great potential for modeling applications where traditional surveys are sparse (seasonal or yearly).


1990 ◽  
Vol 14 ◽  
pp. 331-332
Author(s):  
Keith A. Brugger

Rabots glaciär and Storglaciären are small valley glaciers located in the Kebnekaise massif of northern Sweden. Rabots glaciär flows west from the summit of Kebnekaise (2114 m) and Storglaciären flows east; thus regional climate affecting the glaciers is the same. The glaciers are of comparable size and geometry, although differences exist in the variation of ice thickness and the subglacial bedrock topography within the respective basins. The thickness of Rabots glaciär appears to be relatively uniform over much of its length and its bed smooth. The bed over which Storglaciären flows is characterized by a “riegel and basin” topography and ice thicknesses vary accordingly. Advance and retreat of the glaciers during the last 100 years has been documented by historical records and photographs, measurements of ice retreats, and detailed glacial and geological studies. Both advanced to their maximum 20th century extents around 1916. In their subsequent retreat, Rabots glaciär has lagged behind Storglaciären by 10 years. Mass-balance studies for the years 1981–87 suggest that while the “local” climate for each glacier is slightly different (in terms of the magnitude of acumulation and ablation), variations in local climate are synchronous. Non-synchronous response of the glaciers is therefore attributed to differences in glacier dynamics, which are quite apparent when velocity profiles are compared. Ice velocities on Rabots glaciär vary little from an average of −7.5 m/yr, resulting in a longitudinal strain rate, r, of about 6 × 10−3yr −1. In contrast, values for r on Storglaciären are as high as 2.5 × 10−2 yr−1 owing to greater ice velocities and variation in ice velocity. Since the response time of a glacier is proportional to 1/r, the lower strain rates found on Rabots glaciär probably account for its more sluggish retreat. A simple, non-diffusive, kinematic wave model is used to analyze the response of the glaciers to a step-like perturbation in mass balance. This model predicts that the response time of Storglaciären is on the order of 30 years and that a new steady-state profile would be attained in about 50 years. The predicted response time of Rabots glaciär is about 75 years, its new steady-state profile being reached after more than 100 years. More accurate analyses of each glacier's response to climatic change use a time-dependent numerical model which includes the effects of diffusion. The climatic forcing in these modelling efforts is represented by the changes in mass balance resulting from changes in the equilibrium line altitude (ELA). ELAs can be correlated to regional meteorological variables which in turn are used to create a “synthetic” record of ELA variations where necessary. Therefore climatic oscillations since the turn of the century can be simulated by the appropriate changes in ELA. Using synchronous variations of ELAs and their 1916 profiles as datum states, the modeled behavior of Rabots glaciär and Storglaciären shows that: (a) the rates of ice retreat for each glacier are in reasonable agreement with those observed; and (b) Rabots glaciär took slightly longer than Storglaciären to react to the slight warming that occurred shortly after their 1916 advance.


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