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Meteorological tsunamis (meteotsunamis) are defined as anomalous long-period (2 to 120 min) sea-level oscillations resulting from atmospheric forcing. In the current version of the Global Historical Tsunami Database covering almost 4000 years and including about 2500 tsunamis and tsunami-like events, meteotsunamis constitute a very small fraction of all events (4.1%). In the twenty-first century, when digital instruments for sea-level recording became widely available, identified meteotsunamis still only constitute 5.8% of all catalogued tsunami events. At the same time, there are many regions (Great Lakes, northeastern Gulf of Mexico, US East coast, southern Britain, Balearic Islands, Adriatic Sea, Yellow Sea, south-west coast of Japan, south-east coast of Brazil), where meteotsunamis dominate over all the other types of tsunamigenic events. Cataloguing of meteotsunami events, as reported in mass media, and described in scientific publications, faces the problems of their correct parameterization within the adopted format of the tsunami database. This format was developed in the late 1980s primarily for parameterization of seismogenic tsunamis, which at that time constituted more than 90% of the database's content. As a result, most of the meteotsunamis included in the database lack some basic parameters, such as time of origin, location of source as well as run-up heights. The present paper addresses these issues and discusses the ways for their possible resolution. Several well-known cases of recent meteotsunamis are considered from the standpoint of their parameterization and hazard assessment. [ABSTRACT FROM AUTHOR]

A mechanistic model was developed to predict midsummer bottom-water dissolved oxygen (BWDO) concentration and hypoxic area on the Louisiana shelf of the northern Gulf of Mexico, USA (1985-2011). Because of its parsimonious formulation, the model possesses many of the benefits of simpler, more empirical models, in that it is computationally efficient and can rigorously account for uncertainty through Bayesian inference. At the same time, the model incorporates important biophysical processes such that its parameterization can be informed by field-measured biological and physical rates. The model is used to explore how freshwater flow, nutrient load, benthic oxygen demand, and wind velocity affect hypoxia on the western and eastern sections of the shelf, delineated by the Atchafalaya River outfall. The model explains over 70% of the variability in BWDO on both shelf sections, and outperforms linear regression models developed from the same input variables. Model results suggest that physical factors (i.e., wind and flow) control a larger portion of the year-to-year variability in hypoxia than previously thought, especially on the western shelf, though seasonal nutrient loads remain an important driver of hypoxia, as well. Unlike several previous Gulf hypoxia modeling studies, results do not indicate a temporal shift in the system's propensity for hypoxia formation (i.e., no regime change). Results do indicate that benthic oxygen demand is a substantial BWDO sink, and a better understanding of the long-term dynamics of this sink is required to better predict how the size of the hypoxic zone will respond to proposed reductions in nutrient loading. [ABSTRACT FROM AUTHOR]

Complex simulation models are a valuable tool to inform nutrient management decisions aimed at reducing hypoxia in the northern Gulf of Mexico, yet simulated hypoxia response to reduced nutrients varies greatly between models. We compared two biogeochemical models driven by the same hydrodynamics, the Coastal Generalized Ecosystem Model (CGEM) and Gulf of Mexico Dissolved Oxygen Model (GoMDOM), to investigate how they differ in simulating hypoxia and their response to reduced nutrients. Different phytoplankton nutrient kinetics produced 2–3 times more hypoxic area and volume on the western shelf in CGEM compared to GoMDOM. Reductions in hypoxic area were greatest in the western shelf, comprising 72% (∼4,200 km2) of the total shelfwide hypoxia response. The range of hypoxia responses from multiple models suggests a 60% load reduction may result in a 33% reduction in hypoxic area, leaving an annual hypoxic area of ∼9,000 km2 based on the latest 5-yr average (13,928 km2). • Complex model formulations significantly altered outcomes of hypoxia simulations. • Hypoxic area and volume varied spatially across the shelf between two models. • Hypoxia responded differently to reduced nutrient load scenarios between models. • Models must be evaluated in context with multiple models to inform decision making. [ABSTRACT FROM AUTHOR]

To simulate winds and water levels, numerical weather prediction (NWP) and storm surge models generally use the traditional bulk relation for wind stress, which is characterized by a wind drag coefficient. A still commonly used drag coefficient in those models, some of them were developed in the past, is based on a relation, according to which the magnitude of the coefficient is either constant or increases monotonically with increasing surface wind speed (Bender, 2007; Kim et al., 2008; Kohno and Higaki, 2006). The NWP and surge models are often tuned independently from each other in order to obtain good results. Observations have indicated that the magnitude of the drag coefficient levels off at a wind speed of about 30 m s-1, and then decreases with further increase of the wind speed. Above a wind speed of approximately 30 m s-1, the stress above the air-sea interface starts to saturate. To represent the reducing and levelling off of the drag coefficient, the original Charnock drag formulation has been extended with a correction term. In line with the above, the Delft3D storm surge model is tested using both Charnock's and improved Makin's wind drag parameterization to evaluate the improvements on the storm surge model results, with and without inclusion of the wave effects. The effect of waves on storm surge is included by simultaneously simulating waves with the SWAN model on identical model grids in a coupled mode. However, the results presented here will focus on the storm surge results that include the wave effects. The runs were carried out in the Gulf of Mexico for Katrina and Ivan hurricane events. The storm surge model was initially forced with H*wind data (Powell et al., 2010) to test the effect of the Makin's wind drag parameterization on the storm surge model separately. The computed wind, water levels and waves are subsequently compared with observation data. Based on the good results obtained, we conclude that, for a good reproduction of the storm surges under hurricane conditions, Makin's new drag parameterization is favourable above the traditional Charnock relation. Furthermore, we are encouraged by these results to continue the studies and establish the effect of improved Makin's wind drag parameterization in the wave model. The results from this study will be used to evaluate the relevance of extending the present towards implementation of a similar wind drag parameterization in the SWAN wave model, in line with our aim to apply a consistent wind drag formulation throughout the entire storm surge modelling approach. [ABSTRACT FROM AUTHOR]