The aim of this technical note is to describe the Cycle 46 reference configuration of the HARMONIE-AROME convection-permitting numerical weather prediction model. HARMONIE-AROME is one of the canonical system configurations that is developed, maintained, and validated in the ACCORD consortium, a collaboration of 26 countries in Europe and northern Africa on short-range mesoscale numerical weather prediction. This technical note describes updates to the physical parametrizations, both upper-air and surface, configuration choices such as lateral boundary conditions, model levels, horizontal resolution, model time step, and databases associated with the model, such as for physiography and aerosols. Much of the physics developments are related to improving the representation of clouds in the model, including developments in the turbulence, shallow convection, and statistical cloud scheme, as well as changes in radiation and cloud microphysics concerning cloud droplet number concentration and longwave cloud liquid optical properties. Near real-time aerosols and the ICE-T microphysics scheme, which improves the representation of supercooled liquid, and a wind farm parametrization have been added as options. Surface-wise, one of the main advances is the implementation of the lake model FLake. An outlook on upcoming developments is also included.

The Marine Institute of Ireland operates a network of weather buoys around Ireland. A wave of 32.3 m height (crest–trough) was recorded by one of these buoys, the M6 buoy, off the coast of Ireland in October 2020. In this paper, the technological evolution of this network is explored, with a particular emphasis on this extremely high wave. Raw data and bulk parameters collected during the event are presented, and the wider met-ocean context is outlined. In addition, wave data across the buoy deployment period from dual wave sensors installed on the buoy are analysed. Differences in calculation methods are discussed, rogue incidence rates are calculated, and the sensors are found to be generally in good agreement for key sea state parameters. Considerations specific to this network of buoys are described, including recent advances in technology that may affect continuity of historic records. Wave data from the buoys are found to be robust; the importance of keeping technological changes in mind and using the full raw dataset for analysis purposes are highlighted.

We present the construction and preliminary tests of the exponential time integration schemes for the Euler equations. The equations are written in terms of potential temperature and Exner function. The time stepping is accomplished with the EPI2 and EPI3 schemes which have been used in the past for very accurate, long time step integration of the shallow water equations on the sphere. The stability of exponential integrators of this class is ensured by approximation of the oscillatory term using an absolutely stable exponential formula. Consequently, the schemes are not subject to the CFL condition imposed by the linear oscillatory part of the system and they also eliminate the phase errors associated with all the known implicit time stepping algorithms. All calculations are performed using the phipm algorithm based on the Krylov space methods. It is shown that the spectral radius of the Jacobian and consequently the Krylov space dimension are very sensitive to the presence of spatial noise. Efficiency and accuracy increase after the Shapiro filter is applied every two time steps. The method is investigated using several standardized and well accepted benchmark tests, including convective bubbles and a cold density current proposed by Straka and collaborators. Numerical experiments show that a stable integration is obtained for the wave Courant number of the order of 60 to 250. We present a detailed discussion of the development of a cold density current capturing the spiraling Prandtl vortex and the subsequent appearance of the Kelvin–Helmholtz billows. Our results from the exponential method compare very well with those obtained from the accurate schemes reported in the recent literature. The algorithm accurately handles both advection as well as acoustic and gravity waves. These results warrant the further development of the scheme for modeling atmospheric processes on a wide range of scales.

Convection-permitting weather forecasting models allow for prediction of rainfall events with increasing levels of detail. However, the high resolutions used can create problems and introduce the so-called "double penalty" problem when attempting to verify the forecast accuracy. Post-processing within an ensemble prediction system can help to overcome these issues. In this paper, two new up-scaling algorithms based on Machine Learning and Statistical approaches are proposed and tested. The aim of these tools is to enhance the skill and value of the forecasts and to provide a better tool for forecasters to predict severe weather.

Abstract. The Northeast Atlantic possesses an energetic and variable wind and wave climate which has a large potential for renewable energy extraction; for example along the western seaboards off Ireland. The role of surface winds in the generation of ocean waves means that global atmospheric circulation patterns and wave climate characteristics are inherently connected. In quantifying how the wave and wind climate of this region may change towards the end of the century due to climate change, it is useful to investigate the influence of large scale atmospheric oscillations using indices such as the North Atlantic Oscillation (NAO), the East Atlantic pattern (EA) and the Scandinavian pattern (SCAND). In this study a statistical analysis of these teleconnections was carried out using an ensemble of EC-Earth global climate simulations run under the RCP4.5 and RCP8.5 forcing scenarios, where EC-Earth is a European-developed atmosphere ocean sea-ice coupled climate model. In addition, EC-Earth model fields were used to drive the WAVEWATCH III wave model over the North Atlantic basin to create the highest resolution wave projection dataset currently available for Ireland. Using this dataset we analysed the correlations between teleconnections and significant wave heights (Hs) with a particular focus on extreme ocean states using a range of statistical methods. The strongest, statistically significant correlations exist between the 95th percentile of significant wave height and the NAO. Correlations between extreme Hs and the EA and SCAND are weaker and not statistically significant over parts of the North Atlantic. When the NAO is in its positive phase (NAO+) and the EA and SCAND are in a negative phase (EA−, SCAND−) the strongest effects are seen on 20-year return levels of extreme ocean waves. Under RCP8.5 there are large areas around Ireland where the 20-year return level of Hs increases by the end of the century, despite an overall decreasing trend in mean wind speeds and hence mean Hs.

This paper aims to extend and update the survey of extreme wave events in Ireland that was previously carried out by O’Brien et al. (2013). The original catalogue highlighted the frequency of such events dating back as far as the turn of the last ice age and as recent as 2012. Ireland's marine territory extends far beyond its coastline and is one of the largest seabed territories in Europe. It is therefore not surprising that extreme waves have continued to occur regularly since 2012, particularly considering the severity of weather during the winters of 2013–2014 and 2015–2016. In addition, a large number of storm surges have been identified since the publication of the original catalogue. This paper updates the O’Brien et al. (2013) catalogue to include events up to the end of 2017. Storm surges are included as a new category and events are categorised into long waves (tsunamis and storm surges) and short waves (storm and rogue waves). New results prior to 2012 are also included and some of the events previously documented are reclassified. Important questions regarding public safety, services and the influence of climate change are also highlighted. An interactive map has been created to allow the reader to navigate through events: https://drive.google.com/open?id=19cZ59pDHfDnXKYIziYAVWV6AfoE&usp=sharing.

The pressure load at a vertical barrier caused by extreme wave run-up is analysed numerically, using the conformal mapping method to solve the two-dimensional free surface Euler equations in a pseudospectral model. Previously this problem has been examined in the case of a flat-bottomed geometry. Here,the model is extended to consider a varying bathymetry. Numerical experiments show that an increasing step-like bottom profile may enhance the extreme run-up of long waves but result in a reduced pressure load.

Abstract. This paper aims to extend and update the survey of extreme wave events in Ireland that was previously carried out by O'Brien et al. (2013). The original catalogue highlighted the frequency of such events dating back as far as the turn of the last ice age through to 2012. Ireland's marine territory extends far beyond its coastline and is one of the largest seabed territories in Europe. It is therefore not surprising that extreme waves have continued to occur regularly since 2012, particularly considering the severity of weather during the winters of 2013–14 and 2015–16. In addition, a large number of storm surges have been identified since the publication of the original catalogue. This paper updates the O'Brien et al. (2013) catalogue to include events up to the end of 2016. Storm surges are included as a new category and events are categorised into long waves (tsunamis and storm surges) and short waves (storm and rogue waves). New results prior to 2012 are also included and some of the events previously documented are reclassified. Important questions regarding public safety, services and the influence of climate change are also highlighted.

Large scale atmospheric oscillations are known to have an influence on waves in the North Atlantic. In quantifying how the wave and wind climate of this region may change towards the end of the century due to climate change, it is useful to investigate the influence of large scale oscillations using indices such as the North Atlantic Oscillation (NAO: fluctuations in the difference between the Icelandic low pressure system and the Azore high pressure system). In this study a statistical analysis of the station-based NAO index was carried out using an ensemble of EC-Earth global climate simulations, where EC-Earth is a European-developed atmosphere ocean sea-ice coupled climate model. The NAO index was compared to observations and to projected changes in the index by the end of the century under the RCP4.5 and RCP8.5 forcing scenarios. In addition, an ensemble of EC-Earth driven WAVEWATCH III wave model projections over the North Atlantic was analysed to determine the correlations between the NAO and significant wave height (H-s) and the NAO and extreme ocean states. For the most part, no statistically significant differences were found between the distributions of observed and modelled station-based NAO or in projected distributions of the NAO.Means and extremes of Hs are projected to decrease on average by the end of this century. The 95th percentile of H-s is strongly positively correlated to the NAO. Projections of H-s extremes are location dependent and in fact, under the influence of positive NAO the 20-year return levels of H-s were found to be amplified in some regions. However, it is important to note that the projected decreases in the 95th percentile of H-s off the west coast of Ireland are not statistically significant in one of the RCP4.5 and one of the RCP8.5 simulations (me41, me83) which indicates that there is still uncertainty in the projections of higher percentiles.

We consider the Laplace transform filtering integration scheme applied to the shallow‐water equations, and demonstrate how it can be formulated as a finite‐difference scheme in the time domain. In addition, we investigate a more accurate treatment of the nonlinear terms. The advantages of the resulting algorithms are demonstrated by means of numerical integrations.

A Bayesian hierarchical framework is used to model extreme sea states, incorporating a latent spatial process to more effectively capture the spatial variation of the extremes. The model is applied to a 34-year hindcast of significant wave height off the west coast of Ireland. The generalised Pareto distribution is fitted to declustered peaks over a threshold given by the 99.8th percentile of the data. Return levels of significant wave height are computed and compared against those from a model based on the commonly-used maximum likelihood inference method. The Bayesian spatial model produces smoother maps of return levels. Furthermore, this approach greatly reduces the uncertainty in the estimates, thus providing information on extremes which is more useful for practical applications.

Recent studies have revealed a long history of large waves around Ireland, which can be attributed to persistent strong winds in this area. At the same time, due to the consistently high levels of wave energy, the West Coast of Ireland has attracted a lot of interest as a prospective site for deployment of wave energy converters (WECs) farms. The design of such devices, and in fact of any offshore installation, depends crucially on the knowledge of extreme sea states they will experience during their deployment time. With this in mind, an Extreme Value Analysis incorporating seasonality and accounting for long-term trends was performed, based on a 29 year hindcast for Ireland. The hindcast was performed using the WAVEWATCH III wave model in a 3 nested grid setup, with the largest grid covering the North Atlantic basin and the finest resolution grid (10km) focusing on Ireland. The model was forced with ERA-Interim 10m winds from the European Centre for Medium Range Weather Forecasts. The wave model was validated by comparison to buoy data from the Irish Marine Data Buoy Network. The analysis was performed on the entire fine resolution grid. This affords a characterisation of the spatial variability in extremes both along the coast and with depth gradients. This is of interest in many marine applications, and in particular WEC design and deployment. Indeed, in the nearshore, wave energy levels can be similar to those found in the offshore. This, in conjunction with the diminished risk of extreme sea states, makes nearshore areas attractive for future ocean energy sites.

Global-scale wave climate models, such as WAVEWATCH III, are widely used in oceanography to hindcast the sea state that occurred in a particular geographic area at a particular time. These models are applied in rogue-wave science for characterizing the sea states associated with observations of rogue waves (e.g., the well known "Draupner" [1] or "Andrea" [2] waves). While spectral models are generally successful in providing realistic representations of the sea state and are able to handle a large number of physical factors, they are also based on a very coarse grained representation of the wave field and therefore unsuitable for a detailed resolution of the wave field and refined wave-height statistics.On the other hand, local wave models based on first principle fluid dynamics equations (such as the Higher Order Spectral Method) are able to represent wave fields in detail, but in general they are hard to interface with the full complexity of real-world sea conditions. This paper displays our efforts in coupling these two types of models in order to enhance our under standing of past extreme events and provide scope for rogue wave risk evaluation. In particular, high resolution numerical simulations of a wave field similar to the "Andrea" wave one are performed, allowing for accurate analysis of the event.

In this paper a class of semi-implicit predictor–corrector time integration schemes is proposed. Linear stability analysis is used to identify promising methods and these are applied to the nonlinear system of the shallow water equations on an icosahedral grid. The model used is a testbed for the future development of a more complete atmospheric model. Experiments with standard test cases from the literature show that the investigated time integration schemes produce stable results with relatively long time-steps while maintaining a sufficient level of accuracy. These facts suggest that the analysed methods could be useful for the construction of a more complex model based on the Euler equations.

Exponential integration methods offer a highly accurate approach to the time integration of large systems of differential equations. In recent years, they have attracted increased attention in a number of diverse fields due to advances in their computational efficiency. This has been as a result of the use of Krylov subspace methods for the approximation of the matrix exponentials which typically arise. In this work, we investigate the potential of exponential integration methods for use in atmospheric models. Two schemes are implemented in a shallow water model and tested against reference explicit and semi-implicit methods. In a number of experiments with standard test cases, the exponential methods are found to yield very accurate solutions with time-steps far longer than even the semi-implicit method allows. The relative efficiency of the exponential integrators, which depends mainly on the choice of the specific algorithm used for the calculation of the matrix exponent, is also discussed. The future work aimed at further improvements of the proposed methodology is outlined.

In this article we combine the Laplace transform (LT) scheme with a semi‐Lagrangian advection scheme, and implement it in a shallow‐water model. It is compared to a reference model using the semi‐implicit (SI) scheme, with both Eulerian and Lagrangian advection. We show that the LT scheme is accurate and computationally competitive with these reference schemes. We also show, both analytically and numerically, that the LT scheme is free from the problem of orographic resonance that is found with semi‐implicit schemes. Copyright © 2011 Royal Meteorological Society

A filtering integration scheme is developed, using a modification of the contour used to invert the Laplace transform (LT). It is shown to eliminate components with frequencies higher than a specified cut‐off value. Thus it is valuable for integrations of the equations governing atmospheric flow. The scheme is implemented in a shallow‐water model with an Eulerian treatment of advection. It is compared to a reference model using the semi‐implicit (SI) scheme. The LT scheme is shown to treat dynamically important Kelvin waves more accurately than the SI scheme. Copyright © 2011 Royal Meteorological Society